Regression Trees Identify Relevant Interactions: Can This Improve the Predictive Performance of Risk Adjustment?

PubMed

Buchner, Florian; Wasem, Jürgen; Schillo, Sonja

2017-01-01

Risk equalization formulas have been refined since their introduction about two decades ago. Because of the complexity and the abundance of possible interactions between the variables used, hardly any interactions are considered. A regression tree is used to systematically search for interactions, a methodologically new approach in risk equalization. Analyses are based on a data set of nearly 2.9 million individuals from a major German social health insurer. A two-step approach is applied: In the first step a regression tree is built on the basis of the learning data set. Terminal nodes characterized by more than one morbidity-group-split represent interaction effects of different morbidity groups. In the second step the 'traditional' weighted least squares regression equation is expanded by adding interaction terms for all interactions detected by the tree, and regression coefficients are recalculated. The resulting risk adjustment formula shows an improvement in the adjusted R 2 from 25.43% to 25.81% on the evaluation data set. Predictive ratios are calculated for subgroups affected by the interactions. The R 2 improvement detected is only marginal. According to the sample level performance measures used, not involving a considerable number of morbidity interactions forms no relevant loss in accuracy. Copyright © 2015 John Wiley & Sons, Ltd. Copyright © 2015 John Wiley & Sons, Ltd.

Reduced Lung Cancer Mortality With Lower Atmospheric Pressure.

PubMed

Merrill, Ray M; Frutos, Aaron

2018-01-01

Research has shown that higher altitude is associated with lower risk of lung cancer and improved survival among patients. The current study assessed the influence of county-level atmospheric pressure (a measure reflecting both altitude and temperature) on age-adjusted lung cancer mortality rates in the contiguous United States, with 2 forms of spatial regression. Ordinary least squares regression and geographically weighted regression models were used to evaluate the impact of climate and other selected variables on lung cancer mortality, based on 2974 counties. Atmospheric pressure was significantly positively associated with lung cancer mortality, after controlling for sunlight, precipitation, PM2.5 (µg/m 3 ), current smoker, and other selected variables. Positive county-level β coefficient estimates ( P < .05) for atmospheric pressure were observed throughout the United States, higher in the eastern half of the country. The spatial regression models showed that atmospheric pressure is positively associated with age-adjusted lung cancer mortality rates, after controlling for other selected variables.

Cross-sectional associations of cortical β-amyloid with erythrocyte membrane long-chain polyunsaturated fatty acids in older adults with subjective memory complaints.

PubMed

Hooper, Claudie; De Souto Barreto, Philipe; Payoux, Pierre; Salabert, Anne Sophie; Guyonnet, Sophie; Andrieu, Sandrine; Vellas, Bruno

2017-08-01

Omega-3 (n-3) and 6 (n-6) polyunsaturated fatty acids (PUFAs) have been associated with reduced cognitive decline in observational studies. Hence, we examined the cross-sectional associations between cortical β-amyloid (Aβ) and erythrocyte membrane PUFAs in 61 non-demented elderly individuals reporting subjective memory complaints from the Multidomain Alzheimer Preventive Trial placebo arm. Cortical-to-cerebellar standard uptake value ratios were obtained using [ 18 F] florbetapir positron emission tomography. Fatty acids were measured in erythrocyte membranes by gas chromatography. Associations were explored using adjusted multiple linear regression models and were considered significant at p ≤ 0.005 after correction for multiple testing (10 comparisons). We found no significant associations between cortical Aβ and erythrocyte membrane PUFAs. The associations closest to significance after adjustment were those between Aβ and erythrocyte membrane arachidonic acid (without apolipoprotein E status adjustment: B-coefficient, 0.03; CI, 0.01, 0.05; p = 0.02. Including Apolipoprotein E adjustment: B-coefficient, 0.03; CI, 0.00, 0.06; p = 0.04) and Aβ and erythrocyte membrane linoleic acid (without apolipoprotein E status adjustment: B-coefficient, -0.02; CI, -0.04, 0.00; p = 0.02. Including Apolipoprotein E adjustment: B-coefficient, -0.02; CI, -0.04, 0.00; p = 0.09). Furthermore, the association between Aβ and erythrocyte membrane arachidonic acid seemed to be specific to Apolipoprotein E ε4 non-carriers (B-coefficient 0.03, CI: 0.00, 0.06, p = 0.03, n = 36). In contrast, no association was found between Aβ and erythrocyte membrane linoleic acid in Apolipoprotein E ε4 stratified analysis. Investigating the relationships between Aβ and PUFAs longitudinally would provide further evidence as to whether fatty acids, particularly arachidonic acid and linoleic acid, might modulate cognition through Aβ-dependent mechanisms. © 2017 International Society for Neurochemistry.

Stepwise multiple regression method of greenhouse gas emission modeling in the energy sector in Poland.

PubMed

Kolasa-Wiecek, Alicja

2015-04-01

The energy sector in Poland is the source of 81% of greenhouse gas (GHG) emissions. Poland, among other European Union countries, occupies a leading position with regard to coal consumption. Polish energy sector actively participates in efforts to reduce GHG emissions to the atmosphere, through a gradual decrease of the share of coal in the fuel mix and development of renewable energy sources. All evidence which completes the knowledge about issues related to GHG emissions is a valuable source of information. The article presents the results of modeling of GHG emissions which are generated by the energy sector in Poland. For a better understanding of the quantitative relationship between total consumption of primary energy and greenhouse gas emission, multiple stepwise regression model was applied. The modeling results of CO2 emissions demonstrate a high relationship (0.97) with the hard coal consumption variable. Adjustment coefficient of the model to actual data is high and equal to 95%. The backward step regression model, in the case of CH4 emission, indicated the presence of hard coal (0.66), peat and fuel wood (0.34), solid waste fuels, as well as other sources (-0.64) as the most important variables. The adjusted coefficient is suitable and equals R2=0.90. For N2O emission modeling the obtained coefficient of determination is low and equal to 43%. A significant variable influencing the amount of N2O emission is the peat and wood fuel consumption. Copyright © 2015. Published by Elsevier B.V.

Remote-sensing data processing with the multivariate regression analysis method for iron mineral resource potential mapping: a case study in the Sarvian area, central Iran

NASA Astrophysics Data System (ADS)

Mansouri, Edris; Feizi, Faranak; Jafari Rad, Alireza; Arian, Mehran

2018-03-01

This paper uses multivariate regression to create a mathematical model for iron skarn exploration in the Sarvian area, central Iran, using multivariate regression for mineral prospectivity mapping (MPM). The main target of this paper is to apply multivariate regression analysis (as an MPM method) to map iron outcrops in the northeastern part of the study area in order to discover new iron deposits in other parts of the study area. Two types of multivariate regression models using two linear equations were employed to discover new mineral deposits. This method is one of the reliable methods for processing satellite images. ASTER satellite images (14 bands) were used as unique independent variables (UIVs), and iron outcrops were mapped as dependent variables for MPM. According to the results of the probability value (p value), coefficient of determination value (R2) and adjusted determination coefficient (Radj2), the second regression model (which consistent of multiple UIVs) fitted better than other models. The accuracy of the model was confirmed by iron outcrops map and geological observation. Based on field observation, iron mineralization occurs at the contact of limestone and intrusive rocks (skarn type).

Relationships of the phase velocity with the microarchitectural parameters in bovine trabecular bone in vitro: Application of a stratified model

NASA Astrophysics Data System (ADS)

Lee, Kang Il

2012-08-01

The present study aims to provide insight into the relationships of the phase velocity with the microarchitectural parameters in bovine trabecular bone in vitro. The frequency-dependent phase velocity was measured in 22 bovine femoral trabecular bone samples by using a pair of transducers with a diameter of 25.4 mm and a center frequency of 0.5 MHz. The phase velocity exhibited positive correlation coefficients of 0.48 and 0.32 with the ratio of bone volume to total volume and the trabecular thickness, respectively, but a negative correlation coefficient of -0.62 with the trabecular separation. The best univariate predictor of the phase velocity was the trabecular separation, yielding an adjusted squared correlation coefficient of 0.36. The multivariate regression models yielded adjusted squared correlation coefficients of 0.21-0.36. The theoretical phase velocity predicted by using a stratified model for wave propagation in periodically stratified media consisting of alternating parallel solid-fluid layers showed reasonable agreements with the experimental measurements.

The relationship between body mass index and uric acid: a study on Japanese adult twins.

PubMed

Tanaka, Kentaro; Ogata, Soshiro; Tanaka, Haruka; Omura, Kayoko; Honda, Chika; Hayakawa, Kazuo

2015-09-01

The present study aimed to investigate the association between body mass index (BMI) and uric acid (UA) using the twin study methodology to adjust for genetic factors. The association between BMI and UA was investigated in a cross-sectional study using data from both monozygotic and dizygotic twins registered at the Osaka University Center for Twin Research and the Osaka University Graduate School of Medicine. From January 2011 to March 2014, 422 individuals participated in the health examination. We measured height, weight, age, BMI, lifestyle habits (Breslow's Health Practice Index), serum UA, and serum creatinine. To investigate the association between UA and BMI with adjustment for the clustering of a twin within a pair, individual-level analyses were performed using generalized linear mixed models (GLMMs). To investigate an association with adjustment for genetic and family environmental factors, twin-pair difference values analyses were performed. In all analysis, BMI was associated with UA in men and women. Using the GLMMs, standardized regression coefficients were 0.194 (95 % confidence interval: 0.016-0.373) in men and 0.186 (95 % confidence interval: 0.071-0.302) in women. Considering twin-pair difference value analyses, standardized regression coefficients were 0.333 (95 % confidence interval: 0.072-0.594) in men and 0.314 (95 % confidence interval: 0.151-0.477) in women. The present study shows that BMI was significantly associated with UA, after adjusting for both genetic and familial environment factors in both men and women.

Developing a stroke severity index based on administrative data was feasible using data mining techniques.

PubMed

Sung, Sheng-Feng; Hsieh, Cheng-Yang; Kao Yang, Yea-Huei; Lin, Huey-Juan; Chen, Chih-Hung; Chen, Yu-Wei; Hu, Ya-Han

2015-11-01

Case-mix adjustment is difficult for stroke outcome studies using administrative data. However, relevant prescription, laboratory, procedure, and service claims might be surrogates for stroke severity. This study proposes a method for developing a stroke severity index (SSI) by using administrative data. We identified 3,577 patients with acute ischemic stroke from a hospital-based registry and analyzed claims data with plenty of features. Stroke severity was measured using the National Institutes of Health Stroke Scale (NIHSS). We used two data mining methods and conventional multiple linear regression (MLR) to develop prediction models, comparing the model performance according to the Pearson correlation coefficient between the SSI and the NIHSS. We validated these models in four independent cohorts by using hospital-based registry data linked to a nationwide administrative database. We identified seven predictive features and developed three models. The k-nearest neighbor model (correlation coefficient, 0.743; 95% confidence interval: 0.737, 0.749) performed slightly better than the MLR model (0.742; 0.736, 0.747), followed by the regression tree model (0.737; 0.731, 0.742). In the validation cohorts, the correlation coefficients were between 0.677 and 0.725 for all three models. The claims-based SSI enables adjusting for disease severity in stroke studies using administrative data. Copyright © 2015 Elsevier Inc. All rights reserved.

Objectively measured sedentary time and academic achievement in schoolchildren.

PubMed

Lopes, Luís; Santos, Rute; Mota, Jorge; Pereira, Beatriz; Lopes, Vítor

2017-03-01

This study aimed to evaluate the relationship between objectively measured total sedentary time and academic achievement (AA) in Portuguese children. The sample comprised of 213 children (51.6% girls) aged 9.46 ± 0.43 years, from the north of Portugal. Sedentary time was measured with accelerometry, and AA was assessed using the Portuguese Language and Mathematics National Exams results. Multilevel linear regression models were fitted to assess regression coefficients predicting AA. The results showed that objectively measured total sedentary time was not associated with AA, after adjusting for potential confounders.

Wheat flour dough Alveograph characteristics predicted by Mixolab regression models.

PubMed

Codină, Georgiana Gabriela; Mironeasa, Silvia; Mironeasa, Costel; Popa, Ciprian N; Tamba-Berehoiu, Radiana

2012-02-01

In Romania, the Alveograph is the most used device to evaluate the rheological properties of wheat flour dough, but lately the Mixolab device has begun to play an important role in the breadmaking industry. These two instruments are based on different principles but there are some correlations that can be found between the parameters determined by the Mixolab and the rheological properties of wheat dough measured with the Alveograph. Statistical analysis on 80 wheat flour samples using the backward stepwise multiple regression method showed that Mixolab values using the ‘Chopin S’ protocol (40 samples) and ‘Chopin + ’ protocol (40 samples) can be used to elaborate predictive models for estimating the value of the rheological properties of wheat dough: baking strength (W), dough tenacity (P) and extensibility (L). The correlation analysis confirmed significant findings (P < 0.05 and P < 0.01) between the parameters of wheat dough studied by the Mixolab and its rheological properties measured with the Alveograph. A number of six predictive linear equations were obtained. Linear regression models gave multiple regression coefficients with R²(adjusted) > 0.70 for P, R²(adjusted) > 0.70 for W and R²(adjusted) > 0.38 for L, at a 95% confidence interval. Copyright © 2011 Society of Chemical Industry.

Association between subjective memory complaints and depressive symptoms after adjustment for genetic and family environmental factors in a Japanese twin study.

PubMed

Tanaka, Haruka; Ogata, Soshiro; Omura, Kayoko; Honda, Chika; Kamide, Kei; Hayakawa, Kazuo

2016-03-01

The aim of this study was to investigate the association between subjective memory complaints (SMCs) and depressive symptoms, with and without adjustment for genetic and family environmental factors. We conducted a cross-sectional study using twins and measured SMCs and depressive symptoms as outcomes and explanatory variables, respectively. First, we performed regression analyses using generalized estimating equations to investigate the associations between SMCs and depressive symptoms without adjustment for genetic and family environmental factors (individual-level analyses). We then performed regression analyses for within-pair differences using monozygotic (MZ) and dizygotic (DZ) twin pairs and MZ twin pairs to investigate these associations with adjustment for genetic and family environmental factors by subtracting the values of one twin from those of co-twin variables (within-pair level analyses). Therefore, differences between the associations at individual- and within-pair level analyses suggested confounding by genetic factors. We included 556 twins aged ≥ 20 years. In the individual-level analyses, SMCs were significantly associated with depressive symptoms in both males and females [standardized coefficients: males, 0.23 (95% CI 0.08-0.38); females, 0.35 (95% CI 0.23-0.46)]. In the within-pair level analyses using MZ and same-sex DZ twin pairs, SMCs were significantly associated with depressive symptoms. In the within-pair level analyses using the MZ twin pairs, SMCs were significantly associated with depressive symptoms [standardized coefficients: males, 0.32 (95% CI 0.08-0.56); females, 0.24 (95% CI 0.13-0.42)]. This study suggested that SMCs were significantly associated with depressive symptoms after adjustment for genetic and family environmental factors.

MANCOVA for one way classification with homogeneity of regression coefficient vectors

NASA Astrophysics Data System (ADS)

Mokesh Rayalu, G.; Ravisankar, J.; Mythili, G. Y.

2017-11-01

The MANOVA and MANCOVA are the extensions of the univariate ANOVA and ANCOVA techniques to multidimensional or vector valued observations. The assumption of a Gaussian distribution has been replaced with the Multivariate Gaussian distribution for the vectors data and residual term variables in the statistical models of these techniques. The objective of MANCOVA is to determine if there are statistically reliable mean differences that can be demonstrated between groups later modifying the newly created variable. When randomization assignment of samples or subjects to groups is not possible, multivariate analysis of covariance (MANCOVA) provides statistical matching of groups by adjusting dependent variables as if all subjects scored the same on the covariates. In this research article, an extension has been made to the MANCOVA technique with more number of covariates and homogeneity of regression coefficient vectors is also tested.

Background stratified Poisson regression analysis of cohort data.

PubMed

Richardson, David B; Langholz, Bryan

2012-03-01

Background stratified Poisson regression is an approach that has been used in the analysis of data derived from a variety of epidemiologically important studies of radiation-exposed populations, including uranium miners, nuclear industry workers, and atomic bomb survivors. We describe a novel approach to fit Poisson regression models that adjust for a set of covariates through background stratification while directly estimating the radiation-disease association of primary interest. The approach makes use of an expression for the Poisson likelihood that treats the coefficients for stratum-specific indicator variables as 'nuisance' variables and avoids the need to explicitly estimate the coefficients for these stratum-specific parameters. Log-linear models, as well as other general relative rate models, are accommodated. This approach is illustrated using data from the Life Span Study of Japanese atomic bomb survivors and data from a study of underground uranium miners. The point estimate and confidence interval obtained from this 'conditional' regression approach are identical to the values obtained using unconditional Poisson regression with model terms for each background stratum. Moreover, it is shown that the proposed approach allows estimation of background stratified Poisson regression models of non-standard form, such as models that parameterize latency effects, as well as regression models in which the number of strata is large, thereby overcoming the limitations of previously available statistical software for fitting background stratified Poisson regression models.

Change in active travel and changes in recreational and total physical activity in adults: longitudinal findings from the iConnect study

PubMed Central

2013-01-01

Background To better understand the health benefits of promoting active travel, it is important to understand the relationship between a change in active travel and changes in recreational and total physical activity. Methods These analyses, carried out in April 2012, use longitudinal data from 1628 adult respondents (mean age 54 years; 47% male) in the UK-based iConnect study. Travel and recreational physical activity were measured using detailed seven-day recall instruments. Adjusted linear regression models were fitted with change in active travel defined as ‘decreased’ (<−15 min/week), ‘maintained’ (±15 min/week) or ‘increased’ (>15 min/week) as the primary exposure variable and changes in (a) recreational and (b) total physical activity (min/week) as the primary outcome variables. Results Active travel increased in 32% (n=529), was maintained in 33% (n=534) and decreased in 35% (n=565) of respondents. Recreational physical activity decreased in all groups but this decrease was not greater in those whose active travel increased. Conversely, changes in active travel were associated with commensurate changes in total physical activity. Compared with those whose active travel remained unchanged, total physical activity decreased by 176.9 min/week in those whose active travel had decreased (adjusted regression coefficient −154.9, 95% CI −195.3 to −114.5) and was 112.2 min/week greater among those whose active travel had increased (adjusted regression coefficient 135.1, 95% CI 94.3 to 175.9). Conclusion An increase in active travel was associated with a commensurate increase in total physical activity and not a decrease in recreational physical activity. PMID:23445724

What Financial Incentives Will Be Created by Medicare Bundled Payments for Total Hip Arthroplasty?

PubMed

Clement, R Carter; Kheir, Michael M; Soo, Adrianne E; Derman, Peter B; Levin, L Scott; Fleisher, Lee A

2016-09-01

Bundled payments are gaining popularity in arthroplasty as a tactic for encouraging providers and hospitals to work together to reduce costs. However, this payment model could potentially motivate providers to avoid unprofitable patients, limiting their access to care. Rigorous risk adjustment can prevent this adverse effect, but most current bundling models use limited, if any, risk-adjustment techniques. This study aims to identify and quantify the financial incentives that are likely to develop with total hip arthroplasty (THA) bundled payments that are not accompanied by comprehensive risk stratification. Financial data were collected for all Medicare-eligible patients (age 65+) undergoing primary unilateral THA at an academic center over a 2-year period (n = 553). Bundles were considered to include operative hospitalizations and unplanned readmissions. Multivariate regression was performed to assess the impact of clinical and demographic factors on the variable cost of THA episodes, including unplanned readmissions. (Variable costs reflect the financial incentives that will emerge under bundled payments). Increased costs were associated with advanced age (P < .001), elevated body mass index (BMI; P = .005), surgery performed for hip fracture (P < .001), higher American Society of Anaesthesiologists (ASA) Physical Classification System grades (P < .001), and MCCs (Medicare modifier for major complications; P < .001). Regression coefficients were $155/y, $107/BMI point, $2775 for fracture cases, $2137/ASA grade, and $4892 for major complications. No association was found between costs and gender or race. If generalizable, our results suggest that Centers for Medicare and Medicaid Services bundled payments encompassing acute inpatient care should be adjusted upward by the aforementioned amounts (regression coefficients above) for advanced age, increasing BMI, cases performed for fractures, elevated ASA grade, and major complications (as defined by Medicare MCC modifiers). Furthermore, these figures likely underestimate costs in many bundling models which incorporate larger proportions of postdischarge care. Failure to adjust for factors affecting costs may create barriers to care for specific patient populations. Copyright © 2016 Elsevier Inc. All rights reserved.

Facial convective heat exchange coefficients in cold and windy environments estimated from human experiments

NASA Astrophysics Data System (ADS)

Ben Shabat, Yael; Shitzer, Avraham

2012-07-01

Facial heat exchange convection coefficients were estimated from experimental data in cold and windy ambient conditions applicable to wind chill calculations. Measured facial temperature datasets, that were made available to this study, originated from 3 separate studies involving 18 male and 6 female subjects. Most of these data were for a -10°C ambient environment and wind speeds in the range of 0.2 to 6 m s-1. Additional single experiments were for -5°C, 0°C and 10°C environments and wind speeds in the same range. Convection coefficients were estimated for all these conditions by means of a numerical facial heat exchange model, applying properties of biological tissues and a typical facial diameter of 0.18 m. Estimation was performed by adjusting the guessed convection coefficients in the computed facial temperatures, while comparing them to measured data, to obtain a satisfactory fit ( r 2 > 0.98, in most cases). In one of the studies, heat flux meters were additionally used. Convection coefficients derived from these meters closely approached the estimated values for only the male subjects. They differed significantly, by about 50%, when compared to the estimated female subjects' data. Regression analysis was performed for just the -10°C ambient temperature, and the range of experimental wind speeds, due to the limited availability of data for other ambient temperatures. The regressed equation was assumed in the form of the equation underlying the "new" wind chill chart. Regressed convection coefficients, which closely duplicated the measured data, were consistently higher than those calculated by this equation, except for one single case. The estimated and currently used convection coefficients are shown to diverge exponentially from each other, as wind speed increases. This finding casts considerable doubts on the validity of the convection coefficients that are used in the computation of the "new" wind chill chart and their applicability to humans in cold and windy environments.

Facial convective heat exchange coefficients in cold and windy environments estimated from human experiments.

PubMed

Ben Shabat, Yael; Shitzer, Avraham

2012-07-01

Facial heat exchange convection coefficients were estimated from experimental data in cold and windy ambient conditions applicable to wind chill calculations. Measured facial temperature datasets, that were made available to this study, originated from 3 separate studies involving 18 male and 6 female subjects. Most of these data were for a -10°C ambient environment and wind speeds in the range of 0.2 to 6 m s(-1). Additional single experiments were for -5°C, 0°C and 10°C environments and wind speeds in the same range. Convection coefficients were estimated for all these conditions by means of a numerical facial heat exchange model, applying properties of biological tissues and a typical facial diameter of 0.18 m. Estimation was performed by adjusting the guessed convection coefficients in the computed facial temperatures, while comparing them to measured data, to obtain a satisfactory fit (r(2) > 0.98, in most cases). In one of the studies, heat flux meters were additionally used. Convection coefficients derived from these meters closely approached the estimated values for only the male subjects. They differed significantly, by about 50%, when compared to the estimated female subjects' data. Regression analysis was performed for just the -10°C ambient temperature, and the range of experimental wind speeds, due to the limited availability of data for other ambient temperatures. The regressed equation was assumed in the form of the equation underlying the "new" wind chill chart. Regressed convection coefficients, which closely duplicated the measured data, were consistently higher than those calculated by this equation, except for one single case. The estimated and currently used convection coefficients are shown to diverge exponentially from each other, as wind speed increases. This finding casts considerable doubts on the validity of the convection coefficients that are used in the computation of the "new" wind chill chart and their applicability to humans in cold and windy environments.

Estimation of flood discharges at selected annual exceedance probabilities for unregulated, rural streams in Vermont, with a section on Vermont regional skew regression

USGS Publications Warehouse

Olson, Scott A.; with a section by Veilleux, Andrea G.

2014-01-01

This report provides estimates of flood discharges at selected annual exceedance probabilities (AEPs) for streamgages in and adjacent to Vermont and equations for estimating flood discharges at AEPs of 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent (recurrence intervals of 2-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-years, respectively) for ungaged, unregulated, rural streams in Vermont. The equations were developed using generalized least-squares regression. Flood-frequency and drainage-basin characteristics from 145 streamgages were used in developing the equations. The drainage-basin characteristics used as explanatory variables in the regression equations include drainage area, percentage of wetland area, and the basin-wide mean of the average annual precipitation. The average standard errors of prediction for estimating the flood discharges at the 50-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent AEP with these equations are 34.9, 36.0, 38.7, 42.4, 44.9, 47.3, 50.7, and 55.1 percent, respectively. Flood discharges at selected AEPs for streamgages were computed by using the Expected Moments Algorithm. To improve estimates of the flood discharges for given exceedance probabilities at streamgages in Vermont, a new generalized skew coefficient was developed. The new generalized skew for the region is a constant, 0.44. The mean square error of the generalized skew coefficient is 0.078. This report describes a technique for using results from the regression equations to adjust an AEP discharge computed from a streamgage record. This report also describes a technique for using a drainage-area adjustment to estimate flood discharge at a selected AEP for an ungaged site upstream or downstream from a streamgage. The final regression equations and the flood-discharge frequency data used in this study will be available in StreamStats. StreamStats is a World Wide Web application providing automated regression-equation solutions for user-selected sites on streams.

Quantum Chemically Estimated Abraham Solute Parameters Using Multiple Solvent-Water Partition Coefficients and Molecular Polarizability.

PubMed

Liang, Yuzhen; Xiong, Ruichang; Sandler, Stanley I; Di Toro, Dominic M

2017-09-05

Polyparameter Linear Free Energy Relationships (pp-LFERs), also called Linear Solvation Energy Relationships (LSERs), are used to predict many environmentally significant properties of chemicals. A method is presented for computing the necessary chemical parameters, the Abraham parameters (AP), used by many pp-LFERs. It employs quantum chemical calculations and uses only the chemical's molecular structure. The method computes the Abraham E parameter using density functional theory computed molecular polarizability and the Clausius-Mossotti equation relating the index refraction to the molecular polarizability, estimates the Abraham V as the COSMO calculated molecular volume, and computes the remaining AP S, A, and B jointly with a multiple linear regression using sixty-five solvent-water partition coefficients computed using the quantum mechanical COSMO-SAC solvation model. These solute parameters, referred to as Quantum Chemically estimated Abraham Parameters (QCAP), are further adjusted by fitting to experimentally based APs using QCAP parameters as the independent variables so that they are compatible with existing Abraham pp-LFERs. QCAP and adjusted QCAP for 1827 neutral chemicals are included. For 24 solvent-water systems including octanol-water, predicted log solvent-water partition coefficients using adjusted QCAP have the smallest root-mean-square errors (RMSEs, 0.314-0.602) compared to predictions made using APs estimated using the molecular fragment based method ABSOLV (0.45-0.716). For munition and munition-like compounds, adjusted QCAP has much lower RMSE (0.860) than does ABSOLV (4.45) which essentially fails for these compounds.

Health care burden of Clostridium difficile infection in hospitalized children with inflammatory bowel disease.

PubMed

Pant, Chaitanya; Anderson, Michael P; Deshpande, Abhishek; Altaf, Muhammad A; Grunow, John E; Atreja, Ashish; Sferra, Thomas J

2013-04-01

Children with inflammatory bowel disease (IBD), similar to adults, are at increased risk of acquiring a Clostridium difficile infection (CDI). Our objective was to characterize the health care burden associated with CDI in hospitalized pediatric patients with IBD. We extracted and analyzed cases with a discharge diagnosis of IBD or CDI from the U.S. Healthcare Cost and Utilization Project Kids' Inpatient Database. In our primary analysis, we evaluated pediatric cases with a principal diagnosis of IBD or CDI. For the year 2009, we identified 12,610 weighted cases with IBD of which 3.5% had CDI. In children with IBD, CDI was independently associated with lengthier hospital stays (8.0 versus 6.0 days; adjusted regression coefficient, 2.1 days; 95% confidence interval [CI], 1.4-2.8), higher charges ($45,126 versus $34,703; adjusted regression coefficient, $11,506; 95% CI, 6192-16,820), and greater need for parenteral nutrition (15.9% versus 12.1%; adjusted odds ratio, 1.5; 95% CI, 1.1-2.0) and blood transfusion (17.7% versus 9.8%; adjusted odds ratio, 1.8; 95% CI, 1.4-2.4). There were no deaths. We made similar observations in a subanalysis of cases with principal or secondary diagnoses of IBD or CDI. The incidence of CDI in patients with IBD increased between 2000 and 2009 from 21.7 to 28.0 cases per 1000 IBD cases per year (P < 0.001). There was a significant increase in CDI complicating ulcerative colitis (28.1 versus 42.2, P < 0.001) but not for Crohn's disease (18.3 versus 20.3). CDI represents a significant health care burden in hospitalized children with IBD.

Household food insecurity is associated with less physical activity among children and adults in the U.S. population.

PubMed

To, Quyen G; Frongillo, Edward A; Gallegos, Danielle; Moore, Justin B

2014-11-01

Household food insecurity and physical activity are each important public-health concerns in the United States, but the relation between them has not been investigated thoroughly. This study aimed to examine the association between food insecurity and physical activity in the U.S. population. Physical activity measured by accelerometry (PAM) and physical activity measured by questionnaire (PAQ) data from the NHANES 2003-2006 were used. Individuals aged <6 y or >65 y, pregnant women, individuals with physical limitations, and individuals with family income >350% of the poverty line were excluded. Food insecurity was measured by the USDA Household Food Security Survey Module. Adjusted ORs were calculated from logistic regression to identify the association between food insecurity and adherence to the physical-activity guidelines. Adjusted coefficients were obtained from linear regression to identify the association between food insecurity with sedentary/physical-activity minutes. In children, food insecurity was not associated with adherence to physical-activity guidelines measured via PAM or PAQ and with sedentary minutes (P > 0.05). Food-insecure children did less moderate to vigorous physical activity than food-secure children (adjusted coefficient = -5.24, P = 0.02). In adults, food insecurity was significantly associated with adherence to physical-activity guidelines (adjusted OR = 0.72, P = 0.03 for PAM; and OR = 0.84, P < 0.01 for PAQ) but was not associated with sedentary minutes (P > 0.05). Food-insecure children did less moderate to vigorous physical activity, and food-insecure adults were less likely to adhere to the physical-activity guidelines than those without food insecurity. © 2014 American Society for Nutrition.

Comparisons of monthly mean cosmic ray counting rates observes from worldwide network of neutron monitors

NASA Technical Reports Server (NTRS)

Ryu, J. Y.; Wada, M.

1985-01-01

In order to examine the stability of neutron monitor observation, each of the monthly average counting rates of a neutron monitors is correlated to those of Kiel neutron monitor. The regression coefficients thus obtained are compared with the coupling coefficients of isotropic intensity radiation. The results of the comparisons for five year periods during 1963 to 1982, and for whole period are given. The variation spectrum with a single power law with an exponent of -0.75 up to 50 GV is not so unsatisfactory one. More than one half of the stations show correlations with the coefficient greater than 0.9. Some stations have shifted the level of mean counting rates by changing the instrumental characteristics which can be adjusted.

Modified Regression Correlation Coefficient for Poisson Regression Model

NASA Astrophysics Data System (ADS)

Kaengthong, Nattacha; Domthong, Uthumporn

2017-09-01

This study gives attention to indicators in predictive power of the Generalized Linear Model (GLM) which are widely used; however, often having some restrictions. We are interested in regression correlation coefficient for a Poisson regression model. This is a measure of predictive power, and defined by the relationship between the dependent variable (Y) and the expected value of the dependent variable given the independent variables [E(Y|X)] for the Poisson regression model. The dependent variable is distributed as Poisson. The purpose of this research was modifying regression correlation coefficient for Poisson regression model. We also compare the proposed modified regression correlation coefficient with the traditional regression correlation coefficient in the case of two or more independent variables, and having multicollinearity in independent variables. The result shows that the proposed regression correlation coefficient is better than the traditional regression correlation coefficient based on Bias and the Root Mean Square Error (RMSE).

Intermittent nocturnal hypoxia and metabolic risk in obese adolescents with obstructive sleep apnea.

PubMed

Narang, Indra; McCrindle, Brian W; Manlhiot, Cedric; Lu, Zihang; Al-Saleh, Suhail; Birken, Catherine S; Hamilton, Jill

2018-01-22

There is conflicting data regarding the independent associations of obstructive sleep apnea (OSA) with metabolic risk in obese youth. Previous studies have not consistently addressed central adiposity, specifically elevated waist to height ratio (WHtR), which is associated with metabolic risk independent of body mass index. The objective of this study was to determine the independent effects of the obstructive apnea-hypopnea index (OAHI) and associated indices of nocturnal hypoxia on metabolic function in obese youth after adjusting for WHtR. Subjects had standardized anthropometric measurements. Fasting blood included insulin, glucose, glycated hemoglobin, alanine transferase, and aspartate transaminase. Insulin resistance was quantified with the homeostatic model assessment. Overnight polysomnography determined the OAHI and nocturnal oxygenation indices. Of the 75 recruited subjects, 23% were diagnosed with OSA. Adjusting for age, gender, and WHtR in multivariable linear regression models, a higher oxygen desaturation index was associated with a higher fasting insulin (coefficient [standard error] = 48.076 [11.255], p < 0.001), higher glycated hemoglobin (coefficient [standard error] = 0.097 [0.041], p = 0.02), higher insulin resistance (coefficient [standard error] = 1.516 [0.364], p < 0.001), elevated alanine transferase (coefficient [standard error] = 11.631 [2.770], p < 0.001), and aspartate transaminase (coefficient [standard error] = 4.880 [1.444], p = 0.001). However, there were no significant associations between OAHI, glucose metabolism, and liver enzymes. Intermittent nocturnal hypoxia rather than the OAHI was associated with metabolic risk in obese youth after adjusting for WHtR. Measures of abdominal adiposity such as WHtR should be considered in future studies that evaluate the impact of OSA on metabolic health.

The Covariance Adjustment Approaches for Combining Incomparable Cox Regressions Caused by Unbalanced Covariates Adjustment: A Multivariate Meta-Analysis Study.

PubMed

Dehesh, Tania; Zare, Najaf; Ayatollahi, Seyyed Mohammad Taghi

2015-01-01

Univariate meta-analysis (UM) procedure, as a technique that provides a single overall result, has become increasingly popular. Neglecting the existence of other concomitant covariates in the models leads to loss of treatment efficiency. Our aim was proposing four new approximation approaches for the covariance matrix of the coefficients, which is not readily available for the multivariate generalized least square (MGLS) method as a multivariate meta-analysis approach. We evaluated the efficiency of four new approaches including zero correlation (ZC), common correlation (CC), estimated correlation (EC), and multivariate multilevel correlation (MMC) on the estimation bias, mean square error (MSE), and 95% probability coverage of the confidence interval (CI) in the synthesis of Cox proportional hazard models coefficients in a simulation study. Comparing the results of the simulation study on the MSE, bias, and CI of the estimated coefficients indicated that MMC approach was the most accurate procedure compared to EC, CC, and ZC procedures. The precision ranking of the four approaches according to all above settings was MMC ≥ EC ≥ CC ≥ ZC. This study highlights advantages of MGLS meta-analysis on UM approach. The results suggested the use of MMC procedure to overcome the lack of information for having a complete covariance matrix of the coefficients.

Investigating bias in squared regression structure coefficients

PubMed Central

Nimon, Kim F.; Zientek, Linda R.; Thompson, Bruce

2015-01-01

The importance of structure coefficients and analogs of regression weights for analysis within the general linear model (GLM) has been well-documented. The purpose of this study was to investigate bias in squared structure coefficients in the context of multiple regression and to determine if a formula that had been shown to correct for bias in squared Pearson correlation coefficients and coefficients of determination could be used to correct for bias in squared regression structure coefficients. Using data from a Monte Carlo simulation, this study found that squared regression structure coefficients corrected with Pratt's formula produced less biased estimates and might be more accurate and stable estimates of population squared regression structure coefficients than estimates with no such corrections. While our findings are in line with prior literature that identified multicollinearity as a predictor of bias in squared regression structure coefficients but not coefficients of determination, the findings from this study are unique in that the level of predictive power, number of predictors, and sample size were also observed to contribute bias in squared regression structure coefficients. PMID:26217273

The association between short interpregnancy interval and preterm birth in Louisiana: a comparison of methods.

PubMed

Howard, Elizabeth J; Harville, Emily; Kissinger, Patricia; Xiong, Xu

2013-07-01

There is growing interest in the application of propensity scores (PS) in epidemiologic studies, especially within the field of reproductive epidemiology. This retrospective cohort study assesses the impact of a short interpregnancy interval (IPI) on preterm birth and compares the results of the conventional logistic regression analysis with analyses utilizing a PS. The study included 96,378 singleton infants from Louisiana birth certificate data (1995-2007). Five regression models designed for methods comparison are presented. Ten percent (10.17 %) of all births were preterm; 26.83 % of births were from a short IPI. The PS-adjusted model produced a more conservative estimate of the exposure variable compared to the conventional logistic regression method (β-coefficient: 0.21 vs. 0.43), as well as a smaller standard error (0.024 vs. 0.028), odds ratio and 95 % confidence intervals [1.15 (1.09, 1.20) vs. 1.23 (1.17, 1.30)]. The inclusion of more covariate and interaction terms in the PS did not change the estimates of the exposure variable. This analysis indicates that PS-adjusted regression may be appropriate for validation of conventional methods in a large dataset with a fairly common outcome. PS's may be beneficial in producing more precise estimates, especially for models with many confounders and effect modifiers and where conventional adjustment with logistic regression is unsatisfactory. Short intervals between pregnancies are associated with preterm birth in this population, according to either technique. Birth spacing is an issue that women have some control over. Educational interventions, including birth control, should be applied during prenatal visits and following delivery.

Evaluation of AUC(0-4) predictive methods for cyclosporine in kidney transplant patients.

PubMed

Aoyama, Takahiko; Matsumoto, Yoshiaki; Shimizu, Makiko; Fukuoka, Masamichi; Kimura, Toshimi; Kokubun, Hideya; Yoshida, Kazunari; Yago, Kazuo

2005-05-01

Cyclosporine (CyA) is the most commonly used immunosuppressive agent in patients who undergo kidney transplantation. Dosage adjustment of CyA is usually based on trough levels. Recently, trough levels have been replacing the area under the concentration-time curve during the first 4 h after CyA administration (AUC(0-4)). The aim of this study was to compare the predictive values obtained using three different methods of AUC(0-4) monitoring. AUC(0-4) was calculated from 0 to 4 h in early and stable renal transplant patients using the trapezoidal rule. The predicted AUC(0-4) was calculated using three different methods: the multiple regression equation reported by Uchida et al.; Bayesian estimation for modified population pharmacokinetic parameters reported by Yoshida et al.; and modified population pharmacokinetic parameters reported by Cremers et al. The predicted AUC(0-4) was assessed on the basis of predictive bias, precision, and correlation coefficient. The predicted AUC(0-4) values obtained using three methods through measurement of three blood samples showed small differences in predictive bias, precision, and correlation coefficient. In the prediction of AUC(0-4) measurement of one blood sample from stable renal transplant patients, the performance of the regression equation reported by Uchida depended on sampling time. On the other hand, the performance of Bayesian estimation with modified pharmacokinetic parameters reported by Yoshida through measurement of one blood sample, which is not dependent on sampling time, showed a small difference in the correlation coefficient. The prediction of AUC(0-4) using a regression equation required accurate sampling time. In this study, the prediction of AUC(0-4) using Bayesian estimation did not require accurate sampling time in the AUC(0-4) monitoring of CyA. Thus Bayesian estimation is assumed to be clinically useful in the dosage adjustment of CyA.

Relationship between Body Composition and Pulmonary Function in Early Adult Life: A Cross-Sectional Analysis Nested in Two Birth Cohort Studies.

PubMed

Oliveira, Paula Duarte de; Wehrmeister, Fernando C; Pérez-Padilla, Rogelio; Gonçalves, Helen; Assunção, Maria Cecília F; Horta, Bernardo Lessa; Gigante, Denise P; Barros, Fernando C; Menezes, Ana Maria Baptista

Overweight/obesity has been reported to worsen pulmonary function (PF). This study aimed to examine the association between PF and several body composition (BC) measures in two population-based cohorts. We performed a cross-sectional analysis of individuals aged 18 and 30 years from two Pelotas Birth Cohorts in southern Brazil. PF was assessed by spirometry. Body measures that were collected included body mass index, waist circumference, skinfold thickness, percentages of total and segmented (trunk, arms and legs) fat mass (FM) and total fat-free mass (FFM). FM and FFM were measured by air-displacement plethysmography (BODPOD) and by dual-energy x-ray absorptiometry (DXA). Associations were verified through linear regressions stratified by sex, and adjusted for weight, height, skin color, and socioeconomic, behavioral, and perinatal variables. A total of 7347 individuals were included in the analyses (3438 and 3909 at 30 and 18 years, respectively). Most BC measures showed a significant positive association between PF and FFM, and a negative association with FM. For each additional percentage point of FM, measured by BOD POD, the forced vital capacity regression coefficient adjusted by height, weight and skin color, at 18 years, was -33 mL (95% CI -38, -29) and -26 mL (95% CI -30, -22), and -30 mL (95% CI -35, -25) and -19 mL (95% CI -23, -14) at 30 years, in men and women, respectively. All the BOD POD regression coefficients for FFM were the same as for the FM coefficients, but in a positive trend (p<0.001 for all associations). All measures that distinguish FM from FFM (skinfold thickness-FM estimation-BOD POD, total and segmental DXA measures-FM and FFM proportions) showed negative trends in the association of FM with PF for both ages and sexes. On the other hand, FFM showed a positive association with PF.

A method for the selection of a functional form for a thermodynamic equation of state using weighted linear least squares stepwise regression

NASA Technical Reports Server (NTRS)

Jacobsen, R. T.; Stewart, R. B.; Crain, R. W., Jr.; Rose, G. L.; Myers, A. F.

1976-01-01

A method was developed for establishing a rational choice of the terms to be included in an equation of state with a large number of adjustable coefficients. The methods presented were developed for use in the determination of an equation of state for oxygen and nitrogen. However, a general application of the methods is possible in studies involving the determination of an optimum polynomial equation for fitting a large number of data points. The data considered in the least squares problem are experimental thermodynamic pressure-density-temperature data. Attention is given to a description of stepwise multiple regression and the use of stepwise regression in the determination of an equation of state for oxygen and nitrogen.

Using a Grocery List Is Associated With a Healthier Diet and Lower BMI Among Very High-Risk Adults.

PubMed

Dubowitz, Tamara; Cohen, Deborah A; Huang, Christina Y; Beckman, Robin A; Collins, Rebecca L

2015-01-01

Examine whether use of a grocery list is associated with healthier diet and weight among food desert residents. Cross-sectional analysis of in-person interview data from randomly selected household food shoppers in 2 low-income, primarily African American urban neighborhoods in Pittsburgh, PA with limited access to healthy foods. Multivariate ordinary least-square regressions conducted among 1,372 participants and controlling for sociodemographic factors and other potential confounding variables indicated that although most of the sample (78%) was overweight or obese, consistently using a list was associated with lower body mass index (based on measured height and weight) (adjusted multivariant coefficient = 0.095) and higher dietary quality (based on the Healthy Eating Index-2005) (adjusted multivariant coefficient = 0.103) (P < .05). Shopping with a list may be a useful tool for low-income individuals to improve diet or decrease body mass index. Copyright © 2015 Society for Nutrition Education and Behavior. Published by Elsevier Inc. All rights reserved.

Standards for Standardized Logistic Regression Coefficients

ERIC Educational Resources Information Center

Menard, Scott

2011-01-01

Standardized coefficients in logistic regression analysis have the same utility as standardized coefficients in linear regression analysis. Although there has been no consensus on the best way to construct standardized logistic regression coefficients, there is now sufficient evidence to suggest a single best approach to the construction of a…

The problem of natural funnel asymmetries: a simulation analysis of meta-analysis in macroeconomics.

PubMed

Callot, Laurent; Paldam, Martin

2011-06-01

Effect sizes in macroeconomic are estimated by regressions on data published by statistical agencies. Funnel plots are a representation of the distribution of the resulting regression coefficients. They are normally much wider than predicted by the t-ratio of the coefficients and often asymmetric. The standard method of meta-analysts in economics assumes that the asymmetries are because of publication bias causing censoring and adjusts the average accordingly. The paper shows that some funnel asymmetries may be 'natural' so that they occur without censoring. We investigate such asymmetries by simulating funnels by pairs of data generating processes (DGPs) and estimating models (EMs), in which the EM has the problem that it disregards a property of the DGP. The problems are data dependency, structural breaks, non-normal residuals, non-linearity, and omitted variables. We show that some of these problems generate funnel asymmetries. When they do, the standard method often fails. Copyright © 2011 John Wiley & Sons, Ltd. Copyright © 2011 John Wiley & Sons, Ltd.

Local spatial variations analysis of smear-positive tuberculosis in Xinjiang using Geographically Weighted Regression model.

PubMed

Wei, Wang; Yuan-Yuan, Jin; Ci, Yan; Ahan, Alayi; Ming-Qin, Cao

2016-10-06

The spatial interplay between socioeconomic factors and tuberculosis (TB) cases contributes to the understanding of regional tuberculosis burdens. Historically, local Poisson Geographically Weighted Regression (GWR) has allowed for the identification of the geographic disparities of TB cases and their relevant socioeconomic determinants, thereby forecasting local regression coefficients for the relations between the incidence of TB and its socioeconomic determinants. Therefore, the aims of this study were to: (1) identify the socioeconomic determinants of geographic disparities of smear positive TB in Xinjiang, China (2) confirm if the incidence of smear positive TB and its associated socioeconomic determinants demonstrate spatial variability (3) compare the performance of two main models: one is Ordinary Least Square Regression (OLS), and the other local GWR model. Reported smear-positive TB cases in Xinjiang were extracted from the TB surveillance system database during 2004-2010. The average number of smear-positive TB cases notified in Xinjiang was collected from 98 districts/counties. The population density (POPden), proportion of minorities (PROmin), number of infectious disease network reporting agencies (NUMagen), proportion of agricultural population (PROagr), and per capita annual gross domestic product (per capita GDP) were gathered from the Xinjiang Statistical Yearbook covering a period from 2004 to 2010. The OLS model and GWR model were then utilized to investigate socioeconomic determinants of smear-positive TB cases. Geoda 1.6.7, and GWR 4.0 software were used for data analysis. Our findings indicate that the relations between the average number of smear-positive TB cases notified in Xinjiang and their socioeconomic determinants (POPden, PROmin, NUMagen, PROagr, and per capita GDP) were significantly spatially non-stationary. This means that in some areas more smear-positive TB cases could be related to higher socioeconomic determinant regression coefficients, but in some areas more smear-positive TB cases were found to do with lower socioeconomic determinant regression coefficients. We also found out that the GWR model could be better exploited to geographically differentiate the relationships between the average number of smear-positive TB cases and their socioeconomic determinants, which could interpret the dataset better (adjusted R 2  = 0.912, AICc = 1107.22) than the OLS model (adjusted R 2  = 0.768, AICc = 1196.74). POPden, PROmin, NUMagen, PROagr, and per capita GDP are socioeconomic determinants of smear-positive TB cases. Comprehending the spatial heterogeneity of POPden, PROmin, NUMagen, PROagr, per capita GDP, and smear-positive TB cases could provide valuable information for TB precaution and control strategies.

Income inequality, disinvestment in health care and use of dental services.

PubMed

Bhandari, Bishal; Newton, Jonathan T; Bernabé, Eduardo

2015-01-01

To explore the interrelationships between income inequality, disinvestment in health care, and use of dental services at country level. This study pooled national estimates for use of dental services among adults aged 18 years or older from the 70 countries that participated in the World Health Survey from 2002 to 2004, together with aggregate data on national income (GDP per capita), income inequality (Gini coefficient), and disinvestment in health care (total health expenditure and dentist-to-population ratio) from various international sources. Use of dental services was defined as having had dental problems in the last 12 months and having received any treatment to address those needs. Associations between variables were explored using Pearson correlation coefficients and linear regression. Data from 63 countries representing the six WHO regions were analyzed. Use of dental services was negatively correlated with Gini coefficient (Pearson correlation coefficient -0.48, P < 0.001) and positively correlated with GDP per capita (0.40, P < 0.05), total health expenditure (0.45, P < 0.001), and dentist-to-population ratio (0.67, P < 0.001). The association between Gini coefficient and use of dental services was attenuated but remained significant after adjustments for GDP per capita, total health expenditure, and dentist-to-population ratio (regression coefficient -0.36; 95% CI -0.57, -0.15). This study shows an inverse relationship between income inequality and use of dental services. Of the two indicators of disinvestment in health care assessed, only dentist-to-population ratio was associated with income inequality and use of dental services. © 2014 American Association of Public Health Dentistry.

Association between intake of dairy products and short-term memory with and without adjustment for genetic and family environmental factors: A twin study.

PubMed

Ogata, Soshiro; Tanaka, Haruka; Omura, Kayoko; Honda, Chika; Hayakawa, Kazuo

2016-04-01

Previous studies have indicated associations between intake of dairy products and better cognitive function and reduced risk of dementia. However, these studies did not adjust for genetic and family environmental factors that may influence food intake, cognitive function, and metabolism of dairy product nutrients. In the present study, we investigated the association between intake of dairy products and short-term memory with and without adjustment for almost all genetic and family environmental factors using a genetically informative sample of twin pairs. A cross-sectional study was conducted among twin pairs aged between 20 and 74. Short-term memory was assessed as primary outcome variable, intake of dairy products was analyzed as the predictive variable, and sex, age, education level, marital status, current smoking status, body mass index, dietary alcohol intake, and medical history of hypertension or diabetes were included as possible covariates. Generalized estimating equations (GEE) were performed by treating twins as individuals and regression analyses were used to identify within-pair differences of a twin pair to adjust for genetic and family environmental factors. Data are reported as standardized coefficients and 95% confidence intervals (CI). Analyses were performed on data from 78 men and 278 women. Among men, high intake of dairy products was significantly associated with better short-term memory after adjustment for the possible covariates (standardized coefficients = 0.22; 95% CI, 0.06-0.38) and almost all genetic and family environmental factors (standardized coefficients = 0.38; 95% CI, 0.07-0.69). Among women, no significant associations were found between intake of dairy products and short-term memory. Subsequent sensitivity analyses were adjusted for small samples and showed similar results. Intake of dairy product may prevent cognitive declines regardless of genetic and family environmental factors in men. Copyright © 2015 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Army Physical Therapy Productivity According to the Performance Based Adjustment Model

DTIC Science & Technology

2008-05-02

variation in processes often fell along a bell shaped curve or normal distribution. Shewart later developed a control chart to track and analyze variation in...References Abdi, H. (2003). Partial regression coefficients. In M. Lewis-Beck, A . Bryman & T. Futing (Eds.), Encyclopedia of Social Sciences Research...other provision of law. no person shall be subject to any penalty for failing to comply with a collection of information if it does not display a

The Role of Inflation and Price Escalation Adjustments in Properly Estimating Program Costs: F-35 Case Study

DTIC Science & Technology

2016-03-01

regression models that yield hedonic price indexes is closely related to standard techniques for developing cost estimating relationships ( CERs ...October 2014). iii analysis) and derives a price index from the coefficients on variables reflecting the year of purchase. In CER development, the...index. The relevant cost metric in both cases is unit recurring flyaway (URF) costs. For the current project, we develop a “Baseline” CER model, taking

The distribution of income is worse than you think: Including pollution impacts into measures of income inequality.

PubMed

Muller, Nicholas Z; Matthews, Peter Hans; Wiltshire-Gordon, Virginia

2018-01-01

This paper calculates the distribution of an adjusted measure of income that deducts damages due to exposure to air pollution from reported market income in the United States from 2011 to 2014. The Gini coefficient for this measure of adjusted income is 0.682 in 2011, as compared to 0.482 for market income. By 2014, we estimate that the Gini for adjusted income fell to 0.646, while the market income Gini did not appreciably change. The inclusion of air pollution damage acts like a regressive tax: with air pollution, the bottom 20% of households lose roughly 10% of the share of income, while the top 20% of households gain 10%. We find that, unlike the case for market income, New England is not the most unequal division with respect to adjusted income. Further, the difference between adjusted income for white and Hispanics is smaller than expected. However, the gap in augmented income between whites and African-Americans is widening.

Soil-adjusted sorption isotherms for arsenic(V) and vanadium(V)

NASA Astrophysics Data System (ADS)

Rückamp, Daniel; Utermann, Jens; Florian Stange, Claus

2017-04-01

The sorption characteristic of a soil is usually determined by fitting a sorption isotherm model to laboratory data. However, such sorption isotherms are only valid for the studied soil and cannot be transferred to other soils. For this reason, a soil-adjusted sorption isotherm can be calculated by using the data of several soils. Such soil-adjusted sorption isotherms exist for cationic heavy metals, but are lacking for heavy metal oxyanions. Hence, the aim of this study is to establish soil-adjusted sorption isotherms for the oxyanions arsenate (arsenic(V)) and vanadate (vanadium(V)). For the laboratory experiment, 119 soils (samples from top- and subsoils) typical for Germany were chosen. The batch experiments were conducted with six concentrations of arsenic(V) and vanadium(V), respectively. By using the laboratory data, sorption isotherms for each soil were derived. Then, the soil-adjusted sorption isotherms were calculated by non-linear regression of the sorption isotherms with additional soil parameters. The results indicated a correlation between the sorption strength and oxalate-extractable iron, organic carbon, clay, and electrical conductivity for both, arsenic and vanadium. However, organic carbon had a negative regression coefficient. As total organic carbon was correlated with dissolved organic carbon; we attribute this observation to an effect of higher amounts of dissolved organic substances. We conclude that these soil-adjusted sorption isotherms can be used to assess the potential of soils to adsorb arsenic(V) and vanadium(V) without performing time-consuming sorption experiments.

On causal interpretation of race in regressions adjusting for confounding and mediating variables

PubMed Central

VanderWeele, Tyler J.; Robinson, Whitney R.

2014-01-01

We consider several possible interpretations of the “effect of race” when regressions are run with race as an exposure variable, controlling also for various confounding and mediating variables. When adjustment is made for socioeconomic status early in a person’s life, we discuss under what contexts the regression coefficients for race can be interpreted as corresponding to the extent to which a racial inequality would remain if various socioeconomic distributions early in life across racial groups could be equalized. When adjustment is also made for adult socioeconomic status, we note how the overall racial inequality can be decomposed into the portion that would be eliminated by equalizing adult socioeconomic status across racial groups and the portion of the inequality that would remain even if adult socioeconomic status across racial groups were equalized. We also discuss a stronger interpretation of the “effect of race” (stronger in terms of assumptions) involving the joint effects of race-associated physical phenotype (e.g. skin color), parental physical phenotype, genetic background and cultural context when such variables are thought to be hypothetically manipulable and if adequate control for confounding were possible. We discuss some of the challenges with such an interpretation. Further discussion is given as to how the use of selected populations in examining racial disparities can additionally complicate the interpretation of the effects. PMID:24887159

On using summary statistics from an external calibration sample to correct for covariate measurement error.

PubMed

Guo, Ying; Little, Roderick J; McConnell, Daniel S

2012-01-01

Covariate measurement error is common in epidemiologic studies. Current methods for correcting measurement error with information from external calibration samples are insufficient to provide valid adjusted inferences. We consider the problem of estimating the regression of an outcome Y on covariates X and Z, where Y and Z are observed, X is unobserved, but a variable W that measures X with error is observed. Information about measurement error is provided in an external calibration sample where data on X and W (but not Y and Z) are recorded. We describe a method that uses summary statistics from the calibration sample to create multiple imputations of the missing values of X in the regression sample, so that the regression coefficients of Y on X and Z and associated standard errors can be estimated using simple multiple imputation combining rules, yielding valid statistical inferences under the assumption of a multivariate normal distribution. The proposed method is shown by simulation to provide better inferences than existing methods, namely the naive method, classical calibration, and regression calibration, particularly for correction for bias and achieving nominal confidence levels. We also illustrate our method with an example using linear regression to examine the relation between serum reproductive hormone concentrations and bone mineral density loss in midlife women in the Michigan Bone Health and Metabolism Study. Existing methods fail to adjust appropriately for bias due to measurement error in the regression setting, particularly when measurement error is substantial. The proposed method corrects this deficiency.

Locoregional Control of Non-Small Cell Lung Cancer in Relation to Automated Early Assessment of Tumor Regression on Cone Beam Computed Tomography

DOE Office of Scientific and Technical Information (OSTI.GOV)

Brink, Carsten, E-mail: carsten.brink@rsyd.dk; Laboratory of Radiation Physics, Odense University Hospital; Bernchou, Uffe

2014-07-15

Purpose: Large interindividual variations in volume regression of non-small cell lung cancer (NSCLC) are observable on standard cone beam computed tomography (CBCT) during fractionated radiation therapy. Here, a method for automated assessment of tumor volume regression is presented and its potential use in response adapted personalized radiation therapy is evaluated empirically. Methods and Materials: Automated deformable registration with calculation of the Jacobian determinant was applied to serial CBCT scans in a series of 99 patients with NSCLC. Tumor volume at the end of treatment was estimated on the basis of the first one third and two thirds of the scans.more » The concordance between estimated and actual relative volume at the end of radiation therapy was quantified by Pearson's correlation coefficient. On the basis of the estimated relative volume, the patients were stratified into 2 groups having volume regressions below or above the population median value. Kaplan-Meier plots of locoregional disease-free rate and overall survival in the 2 groups were used to evaluate the predictive value of tumor regression during treatment. Cox proportional hazards model was used to adjust for other clinical characteristics. Results: Automatic measurement of the tumor regression from standard CBCT images was feasible. Pearson's correlation coefficient between manual and automatic measurement was 0.86 in a sample of 9 patients. Most patients experienced tumor volume regression, and this could be quantified early into the treatment course. Interestingly, patients with pronounced volume regression had worse locoregional tumor control and overall survival. This was significant on patient with non-adenocarcinoma histology. Conclusions: Evaluation of routinely acquired CBCT images during radiation therapy provides biological information on the specific tumor. This could potentially form the basis for personalized response adaptive therapy.« less

Psychomotor development index in children younger than 6 years from Argentine provinces.

PubMed

Lejarraga, Horacio; Kelmansky, Diana M; Masautis, Alicia; Nunes, Fernando

2018-04-01

To obtain a psychomotor development index (PDI) for each Argentine province. Using a national, probabilistic, and stratified sample of 13 323 male and female children younger than 6 years selected for the National Survey on Nutrition and Health (Encuesta Nacional de Nutrición y Salud, ENNyS 2004), we estimated the PDI per province based on compliance with 10 developmental milestones. The median age at attainment (median age) of each milestone was estimated adjusting a logistic regression. The PDI was estimated as 100* (1 + b), where "b" is the regression coefficient of y= a + b x, where "y" is the median age as per the national reference (x) minus the median age at attainment of a milestone. The theoretical value expected for the PDI was 100. The PDI per province ranged between 72.1 and 106.4. Most provinces showed a negative regression coefficient, which indicated a progressive increase of the delay in the age at attainment of milestones. The correlation coefficient between the PDI per province and infant mortality in 2005was extremely high: -0.85, suggesting that both indicators share similar biological and social determinants. The PDI was negative because the higher the mortality, the lower the PDI. We have now a positive health indicator available in Argentina: the psychomotor development index, which is a low-cost, easy to collect, and reliable tool that may be used in national health statistics. Sociedad Argentina de Pediatría.

Differential impact of anxiety symptoms and anxiety disorders on treatment outcome for psychotic depression in the STOP-PD study

PubMed Central

Davies, Simon J.C.; Mulsant, Benoit H.; Flint, Alastair J.; Rothschild, Anthony J.; Whyte, Ellen M.; Meyers, Barnett S.

2014-01-01

Background There are conflicting results on the impact of anxiety on depression outcomes. The impact of anxiety has not been studied in major depression with psychotic features (“psychotic depression”). Aims We assessed the impact of specific anxiety symptoms and disorders on the outcomes of psychotic depression. Methods We analyzed data from the Study of Pharmacotherapy for Psychotic Depression that randomized 259 younger and older participants to either olanzapine plus placebo or olanzapine plus sertraline. We assessed the impact of specific anxiety symptoms from the Brief Psychiatric Rating Scale (“tension”, “anxiety” and “somatic concerns” and a composite anxiety score) and diagnoses (panic disorder and GAD) on psychotic depression outcomes using linear or logistic regression. Age, gender, education and benzodiazepine use (at baseline and end) were included as covariates. Results Anxiety symptoms at baseline and anxiety disorder diagnoses differentially impacted outcomes. On adjusted linear regression there was an association between improvement in depressive symptoms and both baseline “tension” (coefficient = 0.784; 95% CI: 0.169–1.400; p = 0.013) and the composite anxiety score (regression coefficient = 0.348; 95% CI: 0.064–0.632; p = 0.017). There was an interaction between “tension” and treatment group, with better responses in those randomized to combination treatment if they had high baseline anxiety scores (coefficient = 1.309; 95% CI: 0.105–2.514; p = 0.033). In contrast, panic disorder was associated with worse clinical outcomes (coefficient = −3.858; 95% CI: –7.281 to −0.434; p = 0.027) regardless of treatment. Conclusions Our results suggest that analysis of the impact of anxiety on depression outcome needs to differentiate psychic and somatic symptoms. PMID:24656524

Meta-regression analysis to evaluate relationships between maternal blood levels of placentation biomarkers and low delivery weight.

PubMed

Goto, Eita

2018-05-03

Caution is required for women at increased risk of low neonatal delivery weight. To evaluate relationships between maternal placentation biomarkers and the odds of low delivery weight. Databases including PubMed/MEDLINE were searched up to May 2017 using keywords involving biomarker names and "low birthweight." English language studies providing true- and false-positive, and true- and false-negative results of low delivery weight classified by maternal blood levels of placentation biomarkers (in units of multiple of the mean [MoM]) were included. Coefficients representing changes in log odds ratio for low delivery weight per 1 MoM increase in maternal blood placentation biomarkers, and those adjusted for race, sampling period, and/or study quality were calculated. Adjusted coefficients representing changes in log odds ratio for low delivery weight per 1 MoM increase in maternal blood levels of α-fetoprotein (AFP) and β-human chorionic gonadotropin (β-hCG) were significantly greater than 0 (both P<0.001), whereas that for pregnancy-associated plasma protein A (PAPP-A) was significantly less than 0 (P=0.028). Adjusted models explained the higher proportion of between-study variance better than non-adjusted models. Elevated AFP and β-hCG, and reduced PAPP-A in maternal blood were positively associated with odds of low delivery weight. © 2018 International Federation of Gynecology and Obstetrics.

Water Intake by Outdoor Temperature Among Children Aged 1-10 Years: Implications for Community Water Fluoridation in the U.S.

PubMed

Beltrán-Aguilar, Eugenio D; Barker, Laurie; Sohn, Woosung; Wei, Liang

2015-01-01

The U.S. water fluoridation recommendations, which have been in place since 1962, were based in part on findings from the 1950s that children's water intake increased with outdoor temperature. We examined whether or not water intake is associated with outdoor temperature. Using linked data from the National Health and Nutrition Examination Survey (NHANES) 1999-2004 and the National Oceanic and Atmospheric Administration, we examined reported 24-hour total and plain water intake in milliliters per kilogram of body weight per day of children aged 1-10 years by maximum outdoor temperature on the day of reported water intake, unadjusted and adjusted for age, sex, race/ethnicity, and poverty status. We applied linear regression methods that were used in previously reported analyses of data from NHANES 1988-1994 and from the 1950s. We found that total water intake was not associated with temperature. Plain water intake was weakly associated with temperature in unadjusted (coefficient 5 0.2, p=0.015) and adjusted (coefficient 5 0.2, p=0.013) linear regression models. However, these models explained little of the individual variation in plain water intake (unadjusted: R(2)=0.005; adjusted: R(2)=0.023). Optimal fluoride concentration in drinking water to prevent caries need not be based on outdoor temperature, given the lack of association between total water intake and outdoor temperature, the weak association between plain water intake and outdoor temperature, and the minimal amount of individual variance in plain water intake explained by outdoor temperature. These findings support the change in the U.S. Public Health Service recommendation for fluoride concentration in drinking water for the prevention of dental caries from temperature-related concentrations to a single concentration that is not related to outdoor temperature.

Association Between Facility Type During Pediatric Inpatient Rehabilitation and Functional Outcomes

PubMed Central

Fuentes, Molly M.; Apkon, Susan; Jimenez, Nathalia; Rivara, Frederick P.

2017-01-01

Objective To compare functional outcomes between children receiving inpatient rehabilitation at children’s hospitals and those at other facilities. Design Retrospective cohort study. Setting Inpatient rehabilitation facilities. Participants Children (N=28,793) aged 6 months to 18 years who received initial inpatient rehabilitation. Interventions Not applicable. Main Outcome Measures Total, cognitive, and motor developmental functional quotients (DFQs; which is the WeeFIM score divided by age-adjusted norms and multiplied by 100) at discharge from inpatient rehabilitation and WeeFIM efficiency (the change in WeeFIM score from admission to discharge divided by the length of the rehabilitation stay), adjusting for age, sex, race, insurance, region, admission function, impairment type, discharge year, and length of stay. Results A total of 12,732 children received rehabilitation at 25 children’s hospitals and 16,061 at 36 other facilities (general hospitals or freestanding rehabilitation hospitals). Adjusting for clustering by facility, patients at children’s hospitals had a lower cognitive DFQ at admission (difference between children’s hospitals and other facility types, −3.8; 95% confidence interval [CI], −7.7 to −0.1), a shorter length of stay (median, 16d vs 22d; P<.001), and a higher WeeFIM efficiency (difference, 0.63; 95% CI, 0.25–1.00) than did children at other facility types. Rehabilitation in a children’s hospital was independently associated with a higher discharge cognitive DFQ (regression coefficient, 2.3; 95% CI, 0.3–4.2) and more efficient rehabilitation admissions (regression coefficient, 0.3; 95% CI, 0.1–0.6). Conclusions Children who receive inpatient rehabilitation at children’s hospitals have more efficient inpatient rehabilitation admissions, a shorter median length of stay, and a slight improvement in cognitive function than do children at other facility types. PMID:27026580

Infection biomarkers in primary care patients with acute respiratory tract infections-comparison of Procalcitonin and C-reactive protein.

PubMed

Meili, Marc; Kutz, Alexander; Briel, Matthias; Christ-Crain, Mirjam; Bucher, Heiner C; Mueller, Beat; Schuetz, Philipp

2016-03-24

There is a lack of studies comparing the utility of C-reactive protein (CRP) with Procalcitonin (PCT) for the management of patients with acute respiratory tract infections (ARI) in primary care. Our aim was to study the correlation between these markers and to compare their predictive accuracy in regard to clinical outcome prediction. This is a secondary analysis using clinical and biomarker data of 458 primary care patients with pneumonic and non-pneumonic ARI. We used correlation statistics (spearman's rank test) and multivariable regression models to assess association of markers with adverse outcome, namely days with restricted activities and persistence of discomfort from infection at day 14. At baseline, CRP and PCT did not correlate well in the overall population (r(2) = 0.16) and particularly in the subgroup of patients with non-pneumonic ARI (r(2) = 0.08). Low correlation of biomarkers were also found when comparing cut-off ranges, day seven levels or changes from baseline to day seven. High baseline levels of CRP (>100 mg/dL, regression coefficient 1.6, 95 % CI 0.5 to 2.6, sociodemographic-adjusted model) as well as PCT (>0.5ug/L regression coefficient 2.0, 95 % CI 0.0 to 4.0, sociodemographic-adjusted model) were significantly associated with larger number of days with restricted activities. There were no associations of either biomarker with persistence of discomfort at day 14. CRP and PCT levels do not well correlate, but both have moderate prognostic accuracy in primary care patients with ARI to predict clinical outcomes. The low correlation between the two biomarkers calls for interventional research comparing these markers head to head in regard to their ability to guide antibiotic decisions. Current Controlled Trials, ISRCTN73182671.

Differential item functioning analysis with ordinal logistic regression techniques. DIFdetect and difwithpar.

PubMed

Crane, Paul K; Gibbons, Laura E; Jolley, Lance; van Belle, Gerald

2006-11-01

We present an ordinal logistic regression model for identification of items with differential item functioning (DIF) and apply this model to a Mini-Mental State Examination (MMSE) dataset. We employ item response theory ability estimation in our models. Three nested ordinal logistic regression models are applied to each item. Model testing begins with examination of the statistical significance of the interaction term between ability and the group indicator, consistent with nonuniform DIF. Then we turn our attention to the coefficient of the ability term in models with and without the group term. If including the group term has a marked effect on that coefficient, we declare that it has uniform DIF. We examined DIF related to language of test administration in addition to self-reported race, Hispanic ethnicity, age, years of education, and sex. We used PARSCALE for IRT analyses and STATA for ordinal logistic regression approaches. We used an iterative technique for adjusting IRT ability estimates on the basis of DIF findings. Five items were found to have DIF related to language. These same items also had DIF related to other covariates. The ordinal logistic regression approach to DIF detection, when combined with IRT ability estimates, provides a reasonable alternative for DIF detection. There appear to be several items with significant DIF related to language of test administration in the MMSE. More attention needs to be paid to the specific criteria used to determine whether an item has DIF, not just the technique used to identify DIF.

Procedures for adjusting regional regression models of urban-runoff quality using local data

USGS Publications Warehouse

Hoos, A.B.; Sisolak, J.K.

1993-01-01

Statistical operations termed model-adjustment procedures (MAP?s) can be used to incorporate local data into existing regression models to improve the prediction of urban-runoff quality. Each MAP is a form of regression analysis in which the local data base is used as a calibration data set. Regression coefficients are determined from the local data base, and the resulting `adjusted? regression models can then be used to predict storm-runoff quality at unmonitored sites. The response variable in the regression analyses is the observed load or mean concentration of a constituent in storm runoff for a single storm. The set of explanatory variables used in the regression analyses is different for each MAP, but always includes the predicted value of load or mean concentration from a regional regression model. The four MAP?s examined in this study were: single-factor regression against the regional model prediction, P, (termed MAP-lF-P), regression against P,, (termed MAP-R-P), regression against P, and additional local variables (termed MAP-R-P+nV), and a weighted combination of P, and a local-regression prediction (termed MAP-W). The procedures were tested by means of split-sample analysis, using data from three cities included in the Nationwide Urban Runoff Program: Denver, Colorado; Bellevue, Washington; and Knoxville, Tennessee. The MAP that provided the greatest predictive accuracy for the verification data set differed among the three test data bases and among model types (MAP-W for Denver and Knoxville, MAP-lF-P and MAP-R-P for Bellevue load models, and MAP-R-P+nV for Bellevue concentration models) and, in many cases, was not clearly indicated by the values of standard error of estimate for the calibration data set. A scheme to guide MAP selection, based on exploratory data analysis of the calibration data set, is presented and tested. The MAP?s were tested for sensitivity to the size of a calibration data set. As expected, predictive accuracy of all MAP?s for the verification data set decreased as the calibration data-set size decreased, but predictive accuracy was not as sensitive for the MAP?s as it was for the local regression models.

Ridge: a computer program for calculating ridge regression estimates

Treesearch

Donald E. Hilt; Donald W. Seegrist

1977-01-01

Least-squares coefficients for multiple-regression models may be unstable when the independent variables are highly correlated. Ridge regression is a biased estimation procedure that produces stable estimates of the coefficients. Ridge regression is discussed, and a computer program for calculating the ridge coefficients is presented.

A regularization corrected score method for nonlinear regression models with covariate error.

PubMed

Zucker, David M; Gorfine, Malka; Li, Yi; Tadesse, Mahlet G; Spiegelman, Donna

2013-03-01

Many regression analyses involve explanatory variables that are measured with error, and failing to account for this error is well known to lead to biased point and interval estimates of the regression coefficients. We present here a new general method for adjusting for covariate error. Our method consists of an approximate version of the Stefanski-Nakamura corrected score approach, using the method of regularization to obtain an approximate solution of the relevant integral equation. We develop the theory in the setting of classical likelihood models; this setting covers, for example, linear regression, nonlinear regression, logistic regression, and Poisson regression. The method is extremely general in terms of the types of measurement error models covered, and is a functional method in the sense of not involving assumptions on the distribution of the true covariate. We discuss the theoretical properties of the method and present simulation results in the logistic regression setting (univariate and multivariate). For illustration, we apply the method to data from the Harvard Nurses' Health Study concerning the relationship between physical activity and breast cancer mortality in the period following a diagnosis of breast cancer. Copyright © 2013, The International Biometric Society.

Comparison of a Full Food-Frequency Questionnaire with the Three-Day Unweighted Food Records in Young Polish Adult Women: Implications for Dietary Assessment

PubMed Central

Kowalkowska, Joanna; Slowinska, Malgorzata A.; Slowinski, Dariusz; Dlugosz, Anna; Niedzwiedzka, Ewa; Wadolowska, Lidia

2013-01-01

The food frequency questionnaire (FFQ) and the food record (FR) are among the most common methods used in dietary research. It is important to know that is it possible to use both methods simultaneously in dietary assessment and prepare a single, comprehensive interpretation. The aim of this study was to compare the energy and nutritional value of diets, determined by the FFQ and by the three-day food records of young women. The study involved 84 female students aged 21–26 years (mean of 22.2 ± 0.8 years). Completing the FFQ was preceded by obtaining unweighted food records covering three consecutive days. Energy and nutritional value of diets was assessed for both methods (FFQ-crude, FR-crude). Data obtained for FFQ-crude were adjusted with beta-coefficient equaling 0.5915 (FFQ-adjusted) and regression analysis (FFQ-regressive). The FFQ-adjusted was calculated as FR-crude/FFQ-crude ratio of mean daily energy intake. FFQ-regressive was calculated for energy and each nutrient separately using regression equation, including FFQ-crude and FR-crude as covariates. For FR-crude and FFQ-crude the energy value of diets was standardized to 2000 kcal (FR-standardized, FFQ-standardized). Methods of statistical comparison included a dependent samples t-test, a chi-square test, and the Bland-Altman method. The mean energy intake in FFQ-crude was significantly higher than FR-crude (2740.5 kcal vs. 1621.0 kcal, respectively). For FR-standardized and FFQ-standardized, significance differences were found in the mean intake of 18 out of 31 nutrients, for FR-crude and FFQ-adjusted in 13 out of 31 nutrients and FR-crude and FFQ-regressive in 11 out of 31 nutrients. The Bland-Altman method showed an overestimation of energy and nutrient intake by FFQ-crude in comparison to FR-crude, e.g., total protein was overestimated by 34.7 g/day (95% Confidence Interval, CI: −29.6, 99.0 g/day) and fat by 48.6 g/day (95% CI: −36.4, 133.6 g/day). After regressive transformation of FFQ, the absolute difference between FFQ-regressive and FR-crude equaled 0.0 g/day and 95% CI were much better (e.g., for total protein 95% CI: −32.7, 32.7 g/day, for fat 95% CI: −49.6, 49.6 g/day). In conclusion, differences in nutritional value of diets resulted from overestimating energy intake by the FFQ in comparison to the three-day unweighted food records. Adjustment of energy and nutrient intake applied for the FFQ using various methods, particularly regression equations, significantly improved the agreement between results obtained by both methods and dietary assessment. To obtain the most accurate results in future studies using this FFQ, energy and nutrient intake should be adjusted by the regression equations presented in this paper. PMID:23877089

On the Importance of Age-Adjustment Methods in Ecological Studies of Social Determinants of Mortality

PubMed Central

Milyo, Jeffrey; Mellor, Jennifer M

2003-01-01

Objective To illustrate the potential sensitivity of ecological associations between mortality and certain socioeconomic factors to different methods of age-adjustment. Data Sources Secondary analysis employing state-level data from several publicly available sources. Crude and age-adjusted mortality rates for 1990 are obtained from the U.S. Centers for Disease Control. The Gini coefficient for family income and percent of persons below the federal poverty line are from the U.S. Bureau of Labor Statistics. Putnam's (2000) Social Capital Index was downloaded from ; the Social Mistrust Index was calculated from responses to the General Social Survey, following the method described in Kawachi et al. (1997). All other covariates are obtained from the U.S. Census Bureau. Study Design We use least squares regression to estimate the effect of several state-level socioeconomic factors on mortality rates. We examine whether these statistical associations are sensitive to the use of alternative methods of accounting for the different age composition of state populations. Following several previous studies, we present results for the case when only mortality rates are age-adjusted. We contrast these results with those obtained from regressions of crude mortality on age variables. Principal Findings Different age-adjustment methods can cause a change in the sign or statistical significance of the association between mortality and various socioeconomic factors. When age variables are included as regressors, we find no significant association between mortality and either income inequality, minority racial concentration, or social capital. Conclusions Ecological associations between certain socioeconomic factors and mortality may be extremely sensitive to different age-adjustment methods. PMID:14727797

The relationship of plasma Trans fatty acids with dietary inflammatory index among US adults.

PubMed

Mazidi, Mohsen; Gao, Hong-Kai; Shivappa, Nitin; Wirth, Michael D; Hebert, James R; Kengne, Andre Pascal

2017-08-04

It has been suggested that trans fatty acids (TFAs) play an important role in cardiovascular diseases. We investigated the association between plasma TFAs and the dietary inflammatory index (DII) ™ in US adults. National Health and Nutrition Examination Survey (NHANES) participants with data on plasma TFAs measured from 1999 to 2010 were included. Energy-adjusted-DII ™ (E-DII ™) expressed per 1000 kcal was calculated from 24-h dietary recalls. All statistical analyses accounted for the survey design and sample weights. Of the 5446 eligible participants, 46.8% (n = 2550) were men. The mean age of the population was 47.1 years overall, 47.8 years for men and 46.5 years for women (p = 0.09). After adjustment for C-reactive protein, body-mass-index, smoking, race, age, education, and marital status in linear regressions, trans 9-hexadecenoic acid [β coefficient 0.068 (95% CI: 0.032 to 0.188)], trans 11-octadecenoic acid [β coefficient 0.143 (95% CI: 0.155 to 0.310)], trans 9-octadecenoic acid [β coefficient 0.122 (95% CI: 0.120 to 0.277)], trans 9, and trans 12-octadienoic acid [β coefficient 0.103 (95% CI: 0.090 to 0.247)] were positively associated with the DII (all p < 0.001). The association of plasma TFAs with a marker of dietary inflammation suggests an underlying mechanism in the initiation and progression of cardiovascular diseases.

Analysis of Palm Oil Production, Export, and Government Consumption to Gross Domestic Product of Five Districts in West Kalimantan by Panel Regression

NASA Astrophysics Data System (ADS)

Sulistianingsih, E.; Kiftiah, M.; Rosadi, D.; Wahyuni, H.

2017-04-01

Gross Domestic Product (GDP) is an indicator of economic growth in a region. GDP is a panel data, which consists of cross-section and time series data. Meanwhile, panel regression is a tool which can be utilised to analyse panel data. There are three models in panel regression, namely Common Effect Model (CEM), Fixed Effect Model (FEM) and Random Effect Model (REM). The models will be chosen based on results of Chow Test, Hausman Test and Lagrange Multiplier Test. This research analyses palm oil about production, export, and government consumption to five district GDP are in West Kalimantan, namely Sanggau, Sintang, Sambas, Ketapang and Bengkayang by panel regression. Based on the results of analyses, it concluded that REM, which adjusted-determination-coefficient is 0,823, is the best model in this case. Also, according to the result, only Export and Government Consumption that influence GDP of the districts.

Differences in trunk control between early and late pregnancy during gait.

PubMed

Sawa, Ryuichi; Doi, Takehiko; Asai, Tsuyoshi; Watanabe, Kaori; Taniguchi, Takeshi; Ono, Rei

2015-10-01

The aim of this study was to compare gait characteristics, including the functional ability of the trunk, between women before and during the third trimester of pregnancy. Gait measurements were performed on 27 pregnant women, who were divided into two groups using the threshold of 28 gestational weeks. The subjects were instructed to walk at their preferred speed. In addition to stride-time coefficient of variation, root mean square (RMS) and autocorrelation coefficient, coefficient of attenuation (CoA) of acceleration was computed as an index to assess the functional ability of the trunk. Differences of gait characteristics between the groups were determined by the Mann-Whitney U test. Gait characteristics that showed a significant difference between the groups were further analyzed with adjustment by age, height, weight and gait velocity by using multiple regression analysis. Women during the third trimester of pregnancy showed significantly smaller RMS in the anteroposterior direction at the lower trunk than those before the third trimester of pregnancy, even after adjusting for age, height, weight and gait velocity [β=0.47; 95% confidence interval (CI) 0.07-0.25]. CoA in the anteroposterior direction was also significantly lower in women during the third trimester of pregnancy than in those before the third trimester of pregnancy after adjustment by age, height, weight and gait velocity (β=0.44; 95% CI 0.39-18.52). The present cross-sectional study suggests the possibility that the functional ability of the trunk during gait declines in late pregnancy. Copyright © 2015 Elsevier B.V. All rights reserved.

[Developing Perceived Competence Scale (PCS) for Adolescents].

PubMed

Özer, Arif; Gençtanirim Kurt, Dilek; Kizildağ, Seval; Demırtaş Zorbaz, Selen; Arici Şahın, Fatma; Acar, Tülin; Ergene, Tuncay

2016-01-01

In this study, Perceived Competence Scale was developed to measure high school students' perceived competence. Scale development process was verified on three different samples. Participants of the research are some high school students in 2011-2012 academic terms from Ankara. Participants' numbers are incorporated in exploratory factor analysis, confirmatory factor analysis and test-retest reliability respectively, as follows: 372, 668 and 75. Internal consistency coefficients (Cronbach's and stratified α) are calculated separately for each group. For data analysis Factor 8.02 and LISREL 8.70 package programs were used. According to results of the analyses, internal consistency coefficients (α) are .90 - .93 for academic competence, .82 - .86 for social competence in the samples that exploratory and confirmatory factor analysis performed. For the whole scale internal consistency coefficient (stratified α) is calculated as .91. As a result of test-retest reliability, adjusted correlation coefficients (r) are .94 for social competence and .90 for academic competence. In addition, to fit indexes and regression weights obtained from factor analysis, findings related convergent and discriminant validity, indicating that competence can be addressed in two dimensions which are academic (16 items) and social (14 items).

Impact of case-mix on comparisons of patient-reported experience in NHS acute hospital trusts in England.

PubMed

Raleigh, Veena; Sizmur, Steve; Tian, Yang; Thompson, James

2015-04-01

To examine the impact of patient-mix on National Health Service (NHS) acute hospital trust scores in two national NHS patient surveys. Secondary analysis of 2012 patient survey data for 57,915 adult inpatients at 142 NHS acute hospital trusts and 45,263 adult emergency department attendees at 146 NHS acute hospital trusts in England. Changes in trust scores for selected questions, ranks, inter-trust variance and score-based performance bands were examined using three methods: no adjustment for case-mix; the current standardization method with weighting for age, sex and, for inpatients only, admission method; and a regression model adjusting in addition for ethnicity, presence of a long-term condition, proxy response (inpatients only) and previous emergency attendances (emergency department survey only). For both surveys, all the variables examined were associated with patients' responses and affected inter-trust variance in scores, although the direction and strength of impact differed between variables. Inter-trust variance was generally greatest for the unadjusted scores and lowest for scores derived from the full regression model. Although trust scores derived from the three methods were highly correlated (Kendall's tau coefficients 0.70-0.94), up to 14% of trusts had discordant ranks of when the standardization and regression methods were compared. Depending on the survey and question, up to 14 trusts changed performance bands when the regression model with its fuller case-mix adjustment was used rather than the current standardization method. More comprehensive case-mix adjustment of patient survey data than the current limited adjustment reduces performance variation between NHS acute hospital trusts and alters the comparative performance bands of some trusts. Given the use of these data for high-impact purposes such as performance assessment, regulation, commissioning, quality improvement and patient choice, a review of the long-standing method for analysing patient survey data would be timely, and could improve rigour and comparability across the NHS. Performance comparisons need to be perceived as fair and scientifically robust to maintain confidence in publicly reported data, and to support their use by both the public and the NHS. © The Author(s) 2014 Reprints and permissions: sagepub.co.uk/journalsPermissions.nav.

[Analysis of risk factors for dry eye syndrome in visual display terminal workers].

PubMed

Zhu, Yong; Yu, Wen-lan; Xu, Ming; Han, Lei; Cao, Wen-dong; Zhang, Hong-bing; Zhang, Heng-dong

2013-08-01

To analyze the risk factors for dry eye syndrome in visual display terminal (VDT) workers and to provide a scientific basis for protecting the eye health of VDT workers. Questionnaire survey, Schirmer I test, tear break-up time test, and workshop microenvironment evaluation were performed in 185 VDT workers. Multivariate logistic regression analysis was performed to determine the risk factors for dry eye syndrome in VDT workers after adjustment for confounding factors. In the logistic regression model, the regression coefficients of daily mean time of exposure to screen, daily mean time of watching TV, parallel screen-eye angle, upward screen-eye angle, eye-screen distance of less than 20 cm, irregular breaks during screen-exposed work, age, and female gender on the results of Schirmer I test were 0.153, 0.548, 0.400, 0.796, 0.234, 0.516, 0.559, and -0.685, respectively; the regression coefficients of daily mean time of exposure to screen, parallel screen-eye angle, upward screen-eye angle, age, working years, and female gender on tear break-up time were 0.021, 0.625, 2.652, 0.749, 0.403, and 1.481, respectively. Daily mean time of exposure to screen, daily mean time of watching TV, parallel screen-eye angle, upward screen-eye angle, eye-screen distance of less than 20 cm, irregular breaks during screen-exposed work, age, and working years are risk factors for dry eye syndrome in VDT workers.

Serum lipid level and lifestyles are associated with carotid femoral pulse wave velocity among adults: 4.4-year prospectively longitudinal follow-up of a clinical trial.

PubMed

Zhao, XiaoXiao; Wang, Hongyu; Bo, LiuJin; Zhao, Hongwei; Li, Lihong; Zhou, Yingyan

2018-01-01

Lifestyle modifications are recommended as the initial treatment for high blood pressure. The influence of dyslipidemia might be via moderate arterial stiffness, which results in hypertension and cardiovascular disease. We used data from a subgroup of the lifestyle, level of serum lipids/carotid femoral-pulse wave velocity (CF-PWV) Susceptibility BEST Study, a population-based study of community-dwelling adults aged 45-75 years. The serum lipid level and CF-PWV were measured at baseline, and lifestyle such as smoking status, sleeping habits, and the level of oil or salt intake was determined with the use of a validated questionnaire during follow-up. Arterial stiffness was determined as CF-PWV using an electrocardiogram after a mean follow-up of 4.4 years. Regression coefficients (95% CIs), adjusted for demographics, risk factors, cholesterol, and triglycerides (TGs), were calculated by linear regression. Logistic regression analysis was used to identify the association between the variables with CF-PWV independently. In the results, glucose and total cholesterol (TC) were associated with higher CF-PWV (p = 0.000) and lower-destiny lipoprotein was associated with lower CF-PWV (p = 0.001) after adjustments for age, sex, mean arterial pressure, and heart rate. There were significant associations observed for current salt intake in relation to CF-PWV (p-trend = 0.038) without adjustment. This association was retained after adjustments for covariates and had statistical significance (p-trend = 0.048) in model 3, which adjusted age, sex, baseline CF-PWV, mean arterial pressure, heart rate waist circumference, education, smoking status, physical activity, diabetes mellitus (DM), heart disease, high-density lipoprotein (HDL) cholesterol, low-density lipoprotein (LDL) cholesterol, TGs, antihypertensive medicine, nitrate medicine, and antiplatelet medicine. Linear regression showed statistically significant associations between LDL and CF-PWV in the fully adjusted models (model 1 p = 0.010, model 2 p = 0.020, model 3 p = 0.017). Logistic regression analysis showed that CF-PWV was independently associated with age (p = 0.000), TC (p = 0.000), TGs (p = 0.000), and homo-cysteine (p = 0.000), and their odds ratios were 0.781, 3.424, 0.075, and 1.046, respectively. Our results showed a positive association between LDL and arterial stiffness, and suggested that less smoking status, sleeping disorder, and salt intake were associated with less arterial stiffness.

Alternatives for using multivariate regression to adjust prospective payment rates

PubMed Central

Sheingold, Steven H.

1990-01-01

Multivariate regression analysis has been used in structuring three of the adjustments to Medicare's prospective payment rates. Because the indirect-teaching adjustment, the disproportionate-share adjustment, and the adjustment for large cities are responsible for distributing approximately $3 billion in payments each year, the specification of regression models for these adjustments is of critical importance. In this article, the application of regression for adjusting Medicare's prospective rates is discussed, and the implications that differing specifications could have for these adjustments are demonstrated. PMID:10113271

Risk Adjustment for Medicare Total Knee Arthroplasty Bundled Payments.

PubMed

Clement, R Carter; Derman, Peter B; Kheir, Michael M; Soo, Adrianne E; Flynn, David N; Levin, L Scott; Fleisher, Lee

2016-09-01

The use of bundled payments is growing because of their potential to align providers and hospitals on the goal of cost reduction. However, such gain sharing could incentivize providers to "cherry-pick" more profitable patients. Risk adjustment can prevent this unintended consequence, yet most bundling programs include minimal adjustment techniques. This study was conducted to determine how bundled payments for total knee arthroplasty (TKA) should be adjusted for risk. The authors collected financial data for all Medicare patients (age≥65 years) undergoing primary unilateral TKA at an academic center over a period of 2 years (n=941). Multivariate regression was performed to assess the effect of patient factors on the costs of acute inpatient care, including unplanned 30-day readmissions. This analysis mirrors a bundling model used in the Medicare Bundled Payments for Care Improvement initiative. Increased age, American Society of Anesthesiologists (ASA) class, and the presence of a Medicare Major Complications/Comorbid Conditions (MCC) modifier (typically representing major complications) were associated with increased costs (regression coefficients, $57 per year; $729 per ASA class beyond I; and $3122 for patients meeting MCC criteria; P=.003, P=.001, and P<.001, respectively). Differences in costs were not associated with body mass index, sex, or race. If the results are generalizable, Medicare bundled payments for TKA encompassing acute inpatient care should be adjusted upward by the stated amounts for older patients, those with elevated ASA class, and patients meeting MCC criteria. This is likely an underestimate for many bundling models, including the Comprehensive Care for Joint Replacement program, incorporating varying degrees of postacute care. Failure to adjust for factors that affect costs may create adverse incentives, creating barriers to care for certain patient populations. [Orthopedics. 2016; 39(5):e911-e916.]. Copyright 2016, SLACK Incorporated.

A Note on the Relationship between the Number of Indicators and Their Reliability in Detecting Regression Coefficients in Latent Regression Analysis

ERIC Educational Resources Information Center

Dolan, Conor V.; Wicherts, Jelte M.; Molenaar, Peter C. M.

2004-01-01

We consider the question of how variation in the number and reliability of indicators affects the power to reject the hypothesis that the regression coefficients are zero in latent linear regression analysis. We show that power remains constant as long as the coefficient of determination remains unchanged. Any increase in the number of indicators…

Application of third molar development and eruption models in estimating dental age in Malay sub-adults.

PubMed

Mohd Yusof, Mohd Yusmiaidil Putera; Cauwels, Rita; Deschepper, Ellen; Martens, Luc

2015-08-01

The third molar development (TMD) has been widely utilized as one of the radiographic method for dental age estimation. By using the same radiograph of the same individual, third molar eruption (TME) information can be incorporated to the TMD regression model. This study aims to evaluate the performance of dental age estimation in individual method models and the combined model (TMD and TME) based on the classic regressions of multiple linear and principal component analysis. A sample of 705 digital panoramic radiographs of Malay sub-adults aged between 14.1 and 23.8 years was collected. The techniques described by Gleiser and Hunt (modified by Kohler) and Olze were employed to stage the TMD and TME, respectively. The data was divided to develop three respective models based on the two regressions of multiple linear and principal component analysis. The trained models were then validated on the test sample and the accuracy of age prediction was compared between each model. The coefficient of determination (R²) and root mean square error (RMSE) were calculated. In both genders, adjusted R² yielded an increment in the linear regressions of combined model as compared to the individual models. The overall decrease in RMSE was detected in combined model as compared to TMD (0.03-0.06) and TME (0.2-0.8). In principal component regression, low value of adjusted R(2) and high RMSE except in male were exhibited in combined model. Dental age estimation is better predicted using combined model in multiple linear regression models. Copyright © 2015 Elsevier Ltd and Faculty of Forensic and Legal Medicine. All rights reserved.

Co-morbidity, body mass index and quality of life in COPD using the Clinical COPD Questionnaire.

PubMed

Sundh, Josefin; Ställberg, Björn; Lisspers, Karin; Montgomery, Scott M; Janson, Christer

2011-06-01

Quality of life is an important patient-oriented measure in COPD. The Clinical COPD Questionnaire (CCQ) is a validated instrument for estimating quality of life. The impact of different factors on the CCQ-score remains an understudied area. The aim of this study was to investigate the association of co-morbidity and body mass index with quality of life measured by CCQ. A patient questionnaire including the CCQ and a review of records were used. A total of 1548 COPD patients in central Sweden were randomly selected. Complete data were collected for 919 patients, 639 from primary health care and 280 from hospital clinics. Multiple linear regression with adjustment for sex, age, level of education, smoking habits and level of care was performed. Subanalyses included additional adjustment for lung function in the subgroup (n = 475) where spirometry data were available. Higher mean CCQ score indicating lower quality of life was statistically significant and independently associated with heart disease (adjusted regression coefficient (95%CI) 0.26; 0.06 to 0.47), depression (0.50; 0.23 to 0.76) and underweight (0.58; 0.29 to 0.87). Depression and underweight were associated with higher scores in all CCQ subdomains. Further adjustment for lung function in the subgroup with this measure resulted in statistically significant and independent associations with CCQ for heart disease, depression, obesity and underweight. The CCQ identified that heart disease, depression and underweight are independently associated with lower health-related quality of life in COPD.

Sensitivity Analysis of the Integrated Medical Model for ISS Programs

NASA Technical Reports Server (NTRS)

Goodenow, D. A.; Myers, J. G.; Arellano, J.; Boley, L.; Garcia, Y.; Saile, L.; Walton, M.; Kerstman, E.; Reyes, D.; Young, M.

2016-01-01

Sensitivity analysis estimates the relative contribution of the uncertainty in input values to the uncertainty of model outputs. Partial Rank Correlation Coefficient (PRCC) and Standardized Rank Regression Coefficient (SRRC) are methods of conducting sensitivity analysis on nonlinear simulation models like the Integrated Medical Model (IMM). The PRCC method estimates the sensitivity using partial correlation of the ranks of the generated input values to each generated output value. The partial part is so named because adjustments are made for the linear effects of all the other input values in the calculation of correlation between a particular input and each output. In SRRC, standardized regression-based coefficients measure the sensitivity of each input, adjusted for all the other inputs, on each output. Because the relative ranking of each of the inputs and outputs is used, as opposed to the values themselves, both methods accommodate the nonlinear relationship of the underlying model. As part of the IMM v4.0 validation study, simulations are available that predict 33 person-missions on ISS and 111 person-missions on STS. These simulated data predictions feed the sensitivity analysis procedures. The inputs to the sensitivity procedures include the number occurrences of each of the one hundred IMM medical conditions generated over the simulations and the associated IMM outputs: total quality time lost (QTL), number of evacuations (EVAC), and number of loss of crew lives (LOCL). The IMM team will report the results of using PRCC and SRRC on IMM v4.0 predictions of the ISS and STS missions created as part of the external validation study. Tornado plots will assist in the visualization of the condition-related input sensitivities to each of the main outcomes. The outcomes of this sensitivity analysis will drive review focus by identifying conditions where changes in uncertainty could drive changes in overall model output uncertainty. These efforts are an integral part of the overall verification, validation, and credibility review of IMM v4.0.

Association of Cortical β-Amyloid with Erythrocyte Membrane Monounsaturated and Saturated Fatty Acids in Older Adults at Risk of Dementia.

PubMed

Hooper, C; De Souto Barreto, P; Payoux, P; Salabert, A S; Guyonnet, S; Andrieu, S; Sourdet, S; Delrieu, J; Vellas, B

2017-01-01

We examined the relationships between erythrocyte membrane monounsaturated fatty acids (MUFAs) and saturated fatty acids (SFAs) and cortical β-amyloid (Aβ) load in older adults reporting subjective memory complaints. This is a cross-sectional study using data from the Multidomain Alzheimer Preventive Trial (MAPT); a randomised controlled trial. French community dwellers aged 70 or over reporting subjective memory complaints, but free from a diagnosis of clinical dementia. Participants of this study were 61 individuals from the placebo arm of the MAPT trial with data on erythrocyte membrane fatty acid levels and cortical Aβ load. Cortical-to-cerebellar standard uptake value ratios were assessed using [18F] florbetapir positron emission tomography (PET). Fatty acids were measured in erythrocyte cell membranes using gas chromatography. Associations between erythrocyte membrane MUFAs and SFAs and cortical Aβ load were explored using adjusted multiple linear regression models and were considered significant at p ≤ 0.005 (10 comparisons) after correction for multiple testing. We found no significant associations between fatty acids and cortical Aβ load using multiple linear regression adjusted for age, sex, education, cognition, PET-scan to clinical assessment interval, PET-scan to blood collection interval and apolipoprotein E (ApoE) status. The association closest to significance was that between erythrocyte membrane stearic acid and Aβ (B-coefficient 0.03, 95 % CI: 0.00,0.05, p = 0.05). This association, although statistically non-significant, appeared to be stronger amongst ApoE ε4 carriers (B-coefficient 0.04, 95 % CI: -0.01,0.09, p = 0.08) compared to ApoE ε4 non-carriers (B-coefficient 0.02, 95 % CI: -0.01,0.05, p = 0.18) in age and sex stratified analysis. Future research in the form of large longitudinal observational study is needed to validate our findings, particularly regarding the potential association of stearic acid with cortical Aβ.

Estimation of diffusion coefficients from voltammetric signals by support vector and gaussian process regression

PubMed Central

2014-01-01

Background Support vector regression (SVR) and Gaussian process regression (GPR) were used for the analysis of electroanalytical experimental data to estimate diffusion coefficients. Results For simulated cyclic voltammograms based on the EC, Eqr, and EqrC mechanisms these regression algorithms in combination with nonlinear kernel/covariance functions yielded diffusion coefficients with higher accuracy as compared to the standard approach of calculating diffusion coefficients relying on the Nicholson-Shain equation. The level of accuracy achieved by SVR and GPR is virtually independent of the rate constants governing the respective reaction steps. Further, the reduction of high-dimensional voltammetric signals by manual selection of typical voltammetric peak features decreased the performance of both regression algorithms compared to a reduction by downsampling or principal component analysis. After training on simulated data sets, diffusion coefficients were estimated by the regression algorithms for experimental data comprising voltammetric signals for three organometallic complexes. Conclusions Estimated diffusion coefficients closely matched the values determined by the parameter fitting method, but reduced the required computational time considerably for one of the reaction mechanisms. The automated processing of voltammograms according to the regression algorithms yields better results than the conventional analysis of peak-related data. PMID:24987463

Clinical associations of Human T-Lymphotropic Virus type 1 infection in an indigenous Australian population.

PubMed

Einsiedel, Lloyd; Spelman, Tim; Goeman, Emma; Cassar, Olivier; Arundell, Mick; Gessain, Antoine

2014-01-01

In resource-poor areas, infectious diseases may be important causes of morbidity among individuals infected with the Human T-Lymphotropic Virus type 1 (HTLV-1). We report the clinical associations of HTLV-1 infection among socially disadvantaged Indigenous adults in central Australia. HTLV-1 serological results for Indigenous adults admitted 1(st) January 2000 to 31(st) December 2010 were obtained from the Alice Springs Hospital pathology database. Infections, comorbid conditions and HTLV-1 related diseases were identified using ICD-10 AM discharge morbidity codes. Relevant pathology and imaging results were reviewed. Disease associations, admission rates and risk factors for death were compared according to HTLV-1 serostatus. HTLV-1 western blots were positive for 531 (33.3%) of 1595 Indigenous adults tested. Clinical associations of HTLV-1 infection included bronchiectasis (adjusted Risk Ratio, 1.35; 95% CI, 1.14-1.60), blood stream infections (BSI) with enteric organisms (aRR, 1.36; 95% CI, 1.05-1.77) and admission with strongyloidiasis (aRR 1.38; 95% CI, 1.16-1.64). After adjusting for covariates, HTLV-1 infection remained associated with increased numbers of BSI episodes (adjusted negative binomial regression, coefficient, 0.21; 95% CI, 0.02-0.41) and increased admission numbers with strongyloidiasis (coefficient, 0.563; 95% CI, 0.17-0.95) and respiratory conditions including asthma (coefficient, 0.99; 95% CI, 0.27-1.7), lower respiratory tract infections (coefficient, 0.19; 95% CI, 0.04-0.34) and bronchiectasis (coefficient, 0.60; 95% CI, 0.02-1.18). Two patients were admitted with adult T-cell Leukemia/Lymphoma, four with probable HTLV-1 associated myelopathy and another with infective dermatitis. Independent predictors of mortality included BSI with enteric organisms (aRR 1.78; 95% CI, 1.15-2.74) and bronchiectasis (aRR 2.07; 95% CI, 1.45-2.98). HTLV-1 infection contributes to morbidity among socially disadvantaged Indigenous adults in central Australia. This is largely due to an increased risk of other infections and respiratory disease. The spectrum of HTLV-1 related diseases may vary according to the social circumstances of the affected population.

Prediction of random-regression coefficient for daily milk yield after 305 days in milk by using the regression-coefficient estimates from the first 305 days.

PubMed

Yamazaki, Takeshi; Takeda, Hisato; Hagiya, Koichi; Yamaguchi, Satoshi; Sasaki, Osamu

2018-03-13

Because lactation periods in dairy cows lengthen with increasing total milk production, it is important to predict individual productivities after 305 days in milk (DIM) to determine the optimal lactation period. We therefore examined whether the random regression (RR) coefficient from 306 to 450 DIM (M2) can be predicted from those during the first 305 DIM (M1) by using a random regression model. We analyzed test-day milk records from 85690 Holstein cows in their first lactations and 131727 cows in their later (second to fifth) lactations. Data in M1 and M2 were analyzed separately by using different single-trait RR animal models. We then performed a multiple regression analysis of the RR coefficients of M2 on those of M1 during the first and later lactations. The first-order Legendre polynomials were practical covariates of random regression for the milk yields of M2. All RR coefficients for the additive genetic (AG) effect and the intercept for the permanent environmental (PE) effect of M2 had moderate to strong correlations with the intercept for the AG effect of M1. The coefficients of determination for multiple regression of the combined intercepts for the AG and PE effects of M2 on the coefficients for the AG effect of M1 were moderate to high. The daily milk yields of M2 predicted by using the RR coefficients for the AG effect of M1 were highly correlated with those obtained by using the coefficients of M2. Milk production after 305 DIM can be predicted by using the RR coefficient estimates of the AG effect during the first 305 DIM.

Interpreting Regression Results: beta Weights and Structure Coefficients are Both Important.

ERIC Educational Resources Information Center

Thompson, Bruce

Various realizations have led to less frequent use of the "OVA" methods (analysis of variance--ANOVA--among others) and to more frequent use of general linear model approaches such as regression. However, too few researchers understand all the various coefficients produced in regression. This paper explains these coefficients and their…

Biases and Standard Errors of Standardized Regression Coefficients

ERIC Educational Resources Information Center

Yuan, Ke-Hai; Chan, Wai

2011-01-01

The paper obtains consistent standard errors (SE) and biases of order O(1/n) for the sample standardized regression coefficients with both random and given predictors. Analytical results indicate that the formulas for SEs given in popular text books are consistent only when the population value of the regression coefficient is zero. The sample…

Breast feeding and resilience against psychosocial stress.

PubMed

Montgomery, S M; Ehlin, A; Sacker, A

2006-12-01

Some early life exposures may result in a well controlled stress response, which can reduce stress related anxiety. Breast feeding may be a marker of some relevant exposures. To assess whether breast feeding is associated with modification of the relation between parental divorce and anxiety. Observational study using longitudinal birth cohort data. Linear regression was used to assess whether breast feeding modifies the association of parental divorce/separation with anxiety using stratification and interaction testing. Data were obtained from the 1970 British Cohort Study, which is following the lives of those born in one week in 1970 and living in Great Britain. This study uses information collected at birth and at ages 5 and 10 years for 8958 subjects. Class teachers answered a question on anxiety among 10 year olds using an analogue scale (range 0-50) that was log transformed to minimise skewness. Among 5672 non-breast fed subjects, parental divorce/separation was associated with a statistically significantly raised risk of anxiety, with a regression coefficient (95% CI) of 9.4 (6.1 to 12.8). Among the breast fed group this association was much lower: 2.2 (-2.6 to 7.0). Interaction testing confirmed statistically significant effect modification by breast feeding, independent of simultaneous adjustment for multiple potential confounding factors, producing an interaction coefficient of -7.0 (-12.8 to -1.2), indicating a 7% reduction in anxiety after adjustment. Breast feeding is associated with resilience against the psychosocial stress linked with parental divorce/separation. This could be because breast feeding is a marker of exposures related to maternal characteristics and parent-child interaction.

Remote sensing and GIS-based landslide hazard analysis and cross-validation using multivariate logistic regression model on three test areas in Malaysia

NASA Astrophysics Data System (ADS)

Pradhan, Biswajeet

2010-05-01

This paper presents the results of the cross-validation of a multivariate logistic regression model using remote sensing data and GIS for landslide hazard analysis on the Penang, Cameron, and Selangor areas in Malaysia. Landslide locations in the study areas were identified by interpreting aerial photographs and satellite images, supported by field surveys. SPOT 5 and Landsat TM satellite imagery were used to map landcover and vegetation index, respectively. Maps of topography, soil type, lineaments and land cover were constructed from the spatial datasets. Ten factors which influence landslide occurrence, i.e., slope, aspect, curvature, distance from drainage, lithology, distance from lineaments, soil type, landcover, rainfall precipitation, and normalized difference vegetation index (ndvi), were extracted from the spatial database and the logistic regression coefficient of each factor was computed. Then the landslide hazard was analysed using the multivariate logistic regression coefficients derived not only from the data for the respective area but also using the logistic regression coefficients calculated from each of the other two areas (nine hazard maps in all) as a cross-validation of the model. For verification of the model, the results of the analyses were then compared with the field-verified landslide locations. Among the three cases of the application of logistic regression coefficient in the same study area, the case of Selangor based on the Selangor logistic regression coefficients showed the highest accuracy (94%), where as Penang based on the Penang coefficients showed the lowest accuracy (86%). Similarly, among the six cases from the cross application of logistic regression coefficient in other two areas, the case of Selangor based on logistic coefficient of Cameron showed highest (90%) prediction accuracy where as the case of Penang based on the Selangor logistic regression coefficients showed the lowest accuracy (79%). Qualitatively, the cross application model yields reasonable results which can be used for preliminary landslide hazard mapping.

Relationship between MRI-measured bone marrow adipose tissue and hip and spine bone mineral density in African-American and Caucasian participants: the CARDIA study.

PubMed

Shen, Wei; Scherzer, Rebecca; Gantz, Madeleine; Chen, Jun; Punyanitya, Mark; Lewis, Cora E; Grunfeld, Carl

2012-04-01

An increasing number of studies suggest that bone marrow adipose tissue (BMAT) might play a role in the pathogenesis of osteoporosis. Our previous study of Caucasian women demonstrated that there is an inverse relationship between BMAT and whole-body bone mineral density (BMD). It is unknown whether visceral adipose tissue (VAT), sc adipose tissue (SAT), and skeletal muscle had an effect on the relationship between BMAT and BMD. In the present study we investigated the relationship between pelvic, hip, and lumbar spine BMAT with hip and lumbar spine BMD in the population-based Coronary Artery Risk Development in Young Adults (CARDIA) sample with adjustment for whole-body magnetic resonance imaging (MRI)-measured VAT, SAT, and skeletal muscle. T1-weighted MRI was acquired for 210 healthy African-American and Caucasian men and women (age 38-52 yr). Hip and lumbar spine BMD were measured by dual-energy x-ray absorptiometry. Pelvic, hip, and lumbar spine BMAT had negative correlations with hip and lumbar spine BMD (r = -0.399 to -0.550, P < 0.001). The inverse associations between BMAT and BMD remained strong after adjusting for demographics, weight, skeletal muscle, SAT, VAT, total adipose tissue (TAT), menopausal status, lifestyle factors, and inflammatory markers (standardized regression coefficients = -0. 296 to -0.549, P < 0.001). Among body composition measures, skeletal muscle was the strongest correlate of BMD after adjusting for BMAT (standardized regression coefficients = 0.268-0.614, P < 0.05), with little additional contribution from weight, SAT, VAT, or total adipose tissue. In this middle-aged population, a negative relationship existed between MRI-measured BMAT and hip and lumbar spine BMD independent of demographics and body composition. These observations support the growing evidence linking BMAT with low bone density.

Relationship between MRI-Measured Bone Marrow Adipose Tissue and Hip and Spine Bone Mineral Density in African-American and Caucasian Participants: The CARDIA Study

PubMed Central

Scherzer, Rebecca; Gantz, Madeleine; Chen, Jun; Punyanitya, Mark; Lewis, Cora E.; Grunfeld, Carl

2012-01-01

Context: An increasing number of studies suggest that bone marrow adipose tissue (BMAT) might play a role in the pathogenesis of osteoporosis. Our previous study of Caucasian women demonstrated that there is an inverse relationship between BMAT and whole-body bone mineral density (BMD). It is unknown whether visceral adipose tissue (VAT), sc adipose tissue (SAT), and skeletal muscle had an effect on the relationship between BMAT and BMD. Objective: In the present study we investigated the relationship between pelvic, hip, and lumbar spine BMAT with hip and lumbar spine BMD in the population-based Coronary Artery Risk Development in Young Adults (CARDIA) sample with adjustment for whole-body magnetic resonance imaging (MRI)-measured VAT, SAT, and skeletal muscle. Design: T1-weighted MRI was acquired for 210 healthy African-American and Caucasian men and women (age 38–52 yr). Hip and lumbar spine BMD were measured by dual-energy x-ray absorptiometry. Results: Pelvic, hip, and lumbar spine BMAT had negative correlations with hip and lumbar spine BMD (r = −0.399 to −0.550, P < 0.001). The inverse associations between BMAT and BMD remained strong after adjusting for demographics, weight, skeletal muscle, SAT, VAT, total adipose tissue (TAT), menopausal status, lifestyle factors, and inflammatory markers (standardized regression coefficients = −0. 296 to −0.549, P < 0.001). Among body composition measures, skeletal muscle was the strongest correlate of BMD after adjusting for BMAT (standardized regression coefficients = 0.268–0.614, P < 0.05), with little additional contribution from weight, SAT, VAT, or total adipose tissue. Conclusion: In this middle-aged population, a negative relationship existed between MRI-measured BMAT and hip and lumbar spine BMD independent of demographics and body composition. These observations support the growing evidence linking BMAT with low bone density. PMID:22319043

Patient satisfaction with ambulatory care in Germany: effects of patient- and medical practice-related factors.

PubMed

Auras, Silke; Ostermann, Thomas; de Cruppé, Werner; Bitzer, Eva-Maria; Diel, Franziska; Geraedts, Max

2016-12-01

The study aimed to illustrate the effect of the patients' sex, age, self-rated health and medical practice specialization on patient satisfaction. Secondary analysis of patient survey data using multilevel analysis (generalized linear mixed model, medical practice as random effect) using a sequential modelling strategy. We examined the effects of the patients' sex, age, self-rated health and medical practice specialization on four patient satisfaction dimensions: medical practice organization, information, interaction, professional competence. The study was performed in 92 German medical practices providing ambulatory care in general medicine, internal medicine or gynaecology. In total, 9888 adult patients participated in a patient survey using the validated 'questionnaire on satisfaction with ambulatory care-quality from the patient perspective [ZAP]'. We calculated four models for each satisfaction dimension, revealing regression coefficients with 95% confidence intervals (CIs) for all independent variables, and using Wald Chi-Square statistic for each modelling step (model validity) and LR-Tests to compare the models of each step with the previous model. The patients' sex and age had a weak effect (maximum regression coefficient 1.09, CI 0.39; 1.80), and the patients' self-rated health had the strongest positive effect (maximum regression coefficient 7.66, CI 6.69; 8.63) on satisfaction ratings. The effect of medical practice specialization was heterogeneous. All factors studied, specifically the patients' self-rated health, affected patient satisfaction. Adjustment should always be considered because it improves the comparability of patient satisfaction in medical practices with atypically varying patient populations and increases the acceptance of comparisons. © The Author 2016. Published by Oxford University Press in association with the International Society for Quality in Health Care. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Development of an anaerobic threshold (HRLT, HRVT) estimation equation using the heart rate threshold (HRT) during the treadmill incremental exercise test

PubMed Central

Ham, Joo-ho; Park, Hun-Young; Kim, Youn-ho; Bae, Sang-kon; Ko, Byung-hoon

2017-01-01

[Purpose] The purpose of this study was to develop a regression model to estimate the heart rate at the lactate threshold (HRLT) and the heart rate at the ventilatory threshold (HRVT) using the heart rate threshold (HRT), and to test the validity of the regression model. [Methods] We performed a graded exercise test with a treadmill in 220 normal individuals (men: 112, women: 108) aged 20–59 years. HRT, HRLT, and HRVT were measured in all subjects. A regression model was developed to estimate HRLT and HRVT using HRT with 70% of the data (men: 79, women: 76) through randomization (7:3), with the Bernoulli trial. The validity of the regression model developed with the remaining 30% of the data (men: 33, women: 32) was also examined. [Results] Based on the regression coefficient, we found that the independent variable HRT was a significant variable in all regression models. The adjusted R2 of the developed regression models averaged about 70%, and the standard error of estimation of the validity test results was 11 bpm, which is similar to that of the developed model. [Conclusion] These results suggest that HRT is a useful parameter for predicting HRLT and HRVT. PMID:29036765

Development of an anaerobic threshold (HRLT, HRVT) estimation equation using the heart rate threshold (HRT) during the treadmill incremental exercise test.

PubMed

Ham, Joo-Ho; Park, Hun-Young; Kim, Youn-Ho; Bae, Sang-Kon; Ko, Byung-Hoon; Nam, Sang-Seok

2017-09-30

The purpose of this study was to develop a regression model to estimate the heart rate at the lactate threshold (HRLT) and the heart rate at the ventilatory threshold (HRVT) using the heart rate threshold (HRT), and to test the validity of the regression model. We performed a graded exercise test with a treadmill in 220 normal individuals (men: 112, women: 108) aged 20-59 years. HRT, HRLT, and HRVT were measured in all subjects. A regression model was developed to estimate HRLT and HRVT using HRT with 70% of the data (men: 79, women: 76) through randomization (7:3), with the Bernoulli trial. The validity of the regression model developed with the remaining 30% of the data (men: 33, women: 32) was also examined. Based on the regression coefficient, we found that the independent variable HRT was a significant variable in all regression models. The adjusted R2 of the developed regression models averaged about 70%, and the standard error of estimation of the validity test results was 11 bpm, which is similar to that of the developed model. These results suggest that HRT is a useful parameter for predicting HRLT and HRVT. ©2017 The Korean Society for Exercise Nutrition

Society of Thoracic Surgeons Risk Score Predicts Hospital Charges and Resource Utilization After Aortic Valve Replacement

PubMed Central

Arnaoutakis, George J.; George, Timothy J.; Alejo, Diane E.; Merlo, Christian A.; Baumgartner, William A.; Cameron, Duke E.; Shah, Ashish S.

2011-01-01

Context The impact of Society of Thoracic Surgeons (STS) predicted mortality risk score on resource utilization after aortic valve replacement (AVR) has not been previously studied. Objective We hypothesize that increasing STS risk scores in patients having AVR are associated with greater hospital charges. Design, Setting, and Patients Clinical and financial data for patients undergoing AVR at a tertiary care, university hospital over a ten-year period (1/2000–12/2009) were retrospectively reviewed. The current STS formula (v2.61) for in-hospital mortality was used for all patients. After stratification into risk quartiles (Q), index admission hospital charges were compared across risk strata with Rank-Sum tests. Linear regression and Spearman’s coefficient assessed correlation and goodness of fit. Multivariable analysis assessed relative contributions of individual variables on overall charges. Main Outcome Measures Inflation-adjusted index hospitalization total charges Results 553 patients had AVR during the study period. Average predicted mortality was 2.9% (±3.4) and actual mortality was 3.4% for AVR. Median charges were greater in the upper Q of AVR patients [Q1–3,$39,949 (IQR32,708–51,323) vs Q4,$62,301 (IQR45,952–97,103), p=<0.01]. On univariate linear regression, there was a positive correlation between STS risk score and log-transformed charges (coefficient: 0.06, 95%CI 0.05–0.07, p<0.01). Spearman’s correlation R-value was 0.51. This positive correlation persisted in risk-adjusted multivariable linear regression. Each 1% increase in STS risk score was associated with an added $3,000 in hospital charges. Conclusions This study showed increasing STS risk score predicts greater charges after AVR. As competing therapies such as percutaneous valve replacement emerge to treat high risk patients, these results serve as a benchmark to compare resource utilization. PMID:21497834

Projection of incidence rates to a larger population using ecologic variables.

PubMed

Frey, C M; Feuer, E J; Timmel, M J

1994-09-15

There is wide acceptance of direct standardization of vital rates to adjust for differing age distributions according to the representation within age categories of some referent population. One can use a similar process to standardize, and subsequently project vital rates with respect to continuous, or ratio scale ecologic variables. We obtained from the National Cancer Institute's Surveillance, Epidemiology and End Results (SEER) programme, a 10 per cent subset of the total U.S. population, country-level breast cancer incidence during 1987-1989 for white women aged 50 and over. We applied regression coefficients that relate ecologic factors to SEER incidence to the full national complement of county-level information to produce an age and ecologic factor adjusted rate that may be more representative of the U.S. than the simple age-adjusted SEER incidence. We conducted a validation study using breast cancer mortality data available for the entire U.S. and which supports the appropriateness of this method for projecting rates.

Breastfeeding in Children of Women Taking Antiepileptic Drugs

PubMed Central

Meador, Kimford J.; Baker, Gus A.; Browning, Nancy; Cohen, Morris J.; Bromley, Rebecca L.; Clayton-Smith, Jill; Kalayjian, Laura A.; Kanner, Andres; Liporace, Joyce D.; Pennell, Page B.; Privitera, Michael; Loring, David W.

2014-01-01

IMPORTANCE Breastfeeding is known to have beneficial effects, but concern exists that breastfeeding during maternal antiepileptic drug (AED) therapy may be harmful. We previously noted no adverse effects of breastfeeding associated with AED use on IQ at age 3 years, but IQ at age 6 years is more predictive of school performance and adult abilities. OBJECTIVES To examine the effects of AED exposure via breastfeeding on cognitive functions at age 6 years. DESIGN, SETTING, AND PARTICIPANTS Prospective observational multicenter study of long-term neurodevelopmental effects of AED use. Pregnant women with epilepsy receiving monotherapy (ie, carbamazepine, lamotrigine, phenytoin, or valproate) were enrolled from October 14, 1999, through April 14, 2004, in the United States and the United Kingdom. At age 6 years, 181 children were assessed for whom we had both breastfeeding and IQ data. All mothers in this analysis continued taking the drug after delivery. MAIN OUTCOMES AND MEASURES Differential Ability Scales IQ was the primary outcome. Secondary measures included measures of verbal, nonverbal, memory, and executive functions. For our primary analysis, we used a linear regression model with IQ at age 6 years as the dependent variable, comparing children who breastfed with those who did not. Similar secondary analyses were performed for the other cognitive measures. RESULTS In total, 42.9% of children were breastfed a mean of 7.2 months. Breastfeeding rates and duration did not differ across drug groups. The IQ at age 6 years was related to drug group (P italic> .001 [adjusted IQ worse by 7–13 IQ points for valproate compared to other drugs]), drug dosage (regression coefficient, −0.1; 95% CI, −0.2 to 0.0; P = .01 [higher dosage worse]), maternal IQ (regression coefficient, 0.2; 95% CI, 0.0 to 0.4; P = .01 [higher child IQ with higher maternal IQ]), periconception folate use (adjusted IQ 6 [95% CI, 2–10] points higher for folate, P = .005), and breastfeeding (adjusted IQ 4 [95% CI, 0–8] points higher for breastfeeding, P = .045). For the other cognitive domains, only verbal abilities differed between the breastfed and nonbreastfed groups (adjusted verbal index 4 [95% CI, 0–7] points higher for breastfed children, P = .03). CONCLUSIONS AND RELEVANCE No adverse effects of AED exposure via breast milk were observed at age 6 years, consistent with another recent study at age 3 years. In our study, breastfed children exhibited higher IQ and enhanced verbal abilities. Additional studies are needed to fully delineate the effects of all AEDs. TRIAL REGISTRATION clinicaltrials.gov Identifier: NCT00021866 PMID:24934501

Breastfeeding in children of women taking antiepileptic drugs: cognitive outcomes at age 6 years.

PubMed

Meador, Kimford J; Baker, Gus A; Browning, Nancy; Cohen, Morris J; Bromley, Rebecca L; Clayton-Smith, Jill; Kalayjian, Laura A; Kanner, Andres; Liporace, Joyce D; Pennell, Page B; Privitera, Michael; Loring, David W

2014-08-01

Breastfeeding is known to have beneficial effects, but concern exists that breastfeeding during maternal antiepileptic drug (AED) therapy may be harmful. We previously noted no adverse effects of breastfeeding associated with AED use on IQ at age 3 years, but IQ at age 6 years is more predictive of school performance and adult abilities. To examine the effects of AED exposure via breastfeeding on cognitive functions at age 6 years. Prospective observational multicenter study of long-term neurodevelopmental effects of AED use. Pregnant women with epilepsy receiving monotherapy (ie, carbamazepine, lamotrigine, phenytoin, or valproate) were enrolled from October 14, 1999, through April 14, 2004, in the United States and the United Kingdom. At age 6 years, 181 children were assessed for whom we had both breastfeeding and IQ data. All mothers in this analysis continued taking the drug after delivery. Differential Ability Scales IQ was the primary outcome. Secondary measures included measures of verbal, nonverbal, memory, and executive functions. For our primary analysis, we used a linear regression model with IQ at age 6 years as the dependent variable, comparing children who breastfed with those who did not. Similar secondary analyses were performed for the other cognitive measures. In total, 42.9% of children were breastfed a mean of 7.2 months. Breastfeeding rates and duration did not differ across drug groups. The IQ at age 6 years was related to drug group (P < .001 [adjusted IQ worse by 7-13 IQ points for valproate compared to other drugs]), drug dosage (regression coefficient, -0.1; 95% CI, -0.2 to 0.0; P = .01 [higher dosage worse]), maternal IQ (regression coefficient, 0.2; 95% CI, 0.0 to 0.4; P = .01 [higher child IQ with higher maternal IQ]), periconception folate use (adjusted IQ 6 [95% CI, 2-10] points higher for folate, P = .005), and breastfeeding (adjusted IQ 4 [95% CI, 0-8] points higher for breastfeeding, P = .045). For the other cognitive domains, only verbal abilities differed between the breastfed and nonbreastfed groups (adjusted verbal index 4 [95% CI, 0-7] points higher for breastfed children, P = .03). No adverse effects of AED exposure via breast milk were observed at age 6 years, consistent with another recent study at age 3 years. In our study, breastfed children exhibited higher IQ and enhanced verbal abilities. Additional studies are needed to fully delineate the effects of all AEDs. clinicaltrials.gov Identifier: NCT00021866.

On the Occurrence of Standardized Regression Coefficients Greater than One.

ERIC Educational Resources Information Center

Deegan, John, Jr.

1978-01-01

It is demonstrated here that standardized regression coefficients greater than one can legitimately occur. Furthermore, the relationship between the occurrence of such coefficients and the extent of multicollinearity present among the set of predictor variables in an equation is examined. Comments on the interpretation of these coefficients are…

Estimating regression coefficients from clustered samples: Sampling errors and optimum sample allocation

NASA Technical Reports Server (NTRS)

Kalton, G.

1983-01-01

A number of surveys were conducted to study the relationship between the level of aircraft or traffic noise exposure experienced by people living in a particular area and their annoyance with it. These surveys generally employ a clustered sample design which affects the precision of the survey estimates. Regression analysis of annoyance on noise measures and other variables is often an important component of the survey analysis. Formulae are presented for estimating the standard errors of regression coefficients and ratio of regression coefficients that are applicable with a two- or three-stage clustered sample design. Using a simple cost function, they also determine the optimum allocation of the sample across the stages of the sample design for the estimation of a regression coefficient.

The Outlier Detection for Ordinal Data Using Scalling Technique of Regression Coefficients

NASA Astrophysics Data System (ADS)

Adnan, Arisman; Sugiarto, Sigit

2017-06-01

The aims of this study is to detect the outliers by using coefficients of Ordinal Logistic Regression (OLR) for the case of k category responses where the score from 1 (the best) to 8 (the worst). We detect them by using the sum of moduli of the ordinal regression coefficients calculated by jackknife technique. This technique is improved by scalling the regression coefficients to their means. R language has been used on a set of ordinal data from reference distribution. Furthermore, we compare this approach by using studentised residual plots of jackknife technique for ANOVA (Analysis of Variance) and OLR. This study shows that the jackknifing technique along with the proper scaling may lead us to reveal outliers in ordinal regression reasonably well.

Using average cost methods to estimate encounter-level costs for medical-surgical stays in the VA.

PubMed

Wagner, Todd H; Chen, Shuo; Barnett, Paul G

2003-09-01

The U.S. Department of Veterans Affairs (VA) maintains discharge abstracts, but these do not include cost information. This article describes the methods the authors used to estimate the costs of VA medical-surgical hospitalizations in fiscal years 1998 to 2000. They estimated a cost regression with 1996 Medicare data restricted to veterans receiving VA care in an earlier year. The regression accounted for approximately 74 percent of the variance in cost-adjusted charges, and it proved to be robust to outliers and the year of input data. The beta coefficients from the cost regression were used to impute costs of VA medical-surgical hospital discharges. The estimated aggregate costs were reconciled with VA budget allocations. In addition to the direct medical costs, their cost estimates include indirect costs and physician services; both of these were allocated in proportion to direct costs. They discuss the method's limitations and application in other health care systems.

Parsimonious estimation of the Wechsler Memory Scale, Fourth Edition demographically adjusted index scores: immediate and delayed memory.

PubMed

Miller, Justin B; Axelrod, Bradley N; Schutte, Christian

2012-01-01

The recent release of the Wechsler Memory Scale Fourth Edition contains many improvements from a theoretical and administration perspective, including demographic corrections using the Advanced Clinical Solutions. Although the administration time has been reduced from previous versions, a shortened version may be desirable in certain situations given practical time limitations in clinical practice. The current study evaluated two- and three-subtest estimations of demographically corrected Immediate and Delayed Memory index scores using both simple arithmetic prorating and regression models. All estimated values were significantly associated with observed index scores. Use of Lin's Concordance Correlation Coefficient as a measure of agreement showed a high degree of precision and virtually zero bias in the models, although the regression models showed a stronger association than prorated models. Regression-based models proved to be more accurate than prorated estimates with less dispersion around observed values, particularly when using three subtest regression models. Overall, the present research shows strong support for estimating demographically corrected index scores on the WMS-IV in clinical practice with an adequate performance using arithmetically prorated models and a stronger performance using regression models to predict index scores.

Methamphetamine abuse during pregnancy and its health impact on neonates born at Siriraj Hospital, Bangkok, Thailand.

PubMed

Chomchai, Chulathida; Na Manorom, Natawadee; Watanarungsan, Pornchai; Yossuck, Panitan; Chomchai, Summon

2004-03-01

To ascertain the impact of intrauterine methamphetamine exposure on the overall health of newborn infants at Siriraj Hospital, Bangkok, Thailand, birth records of somatic growth parameters and neonatal withdrawal symptoms of 47 infants born to methamphetamine-abusing women during January 2001 to December 2001 were compared to 49 newborns whose mothers did not use methamphetamines during pregnancy. The data on somatic growth was analyzed using linear regression and multiple linear regression. The association between methamphetamine use and withdrawal symptoms was analyzed using the chi-square. Home visitation and maternal interview records were reviewed in order to assess for child-rearing attitude, and psychosocial parameters. Infants of methamphetamine-abusing mothers were found to have a significantly smaller gestational age-adjusted head circumference (regression coefficient = -1.458, p < 0.001) and birth weight (regression coefficient = -217.9, p < or = 0.001) measurements. Methamphetamine exposure was also associated with symptoms of agitation (5/47), vomiting (11/47) and tachypnea (12/47) when compared to the non-exposed group (p < 0r =0.001). Maternal interviews were conducted in 23 cases and showed that: 96% of the cases had inadequate prenatal care (<5 visits), 48% had at least one parent involved in prostitution, 39% of the mothers were unwilling to take their children home, and government or non-government support were provided in only 30% of the cases. In-utero methamphetamine exposure has been shown to adversely effect somatic growth of newborns and cause a variety of withdrawal-like symptoms. These infants are also psychosocially disadvantaged and are at greater risk for abuse and neglect.

A quantitative property-property relationship for the internal diffusion coefficients of organic compounds in solid materials.

PubMed

Huang, L; Fantke, P; Ernstoff, A; Jolliet, O

2017-11-01

Indoor releases of organic chemicals encapsulated in solid materials are major contributors to human exposures and are directly related to the internal diffusion coefficient in solid materials. Existing correlations to estimate the diffusion coefficient are only valid for a limited number of chemical-material combinations. This paper develops and evaluates a quantitative property-property relationship (QPPR) to predict diffusion coefficients for a wide range of organic chemicals and materials. We first compiled a training dataset of 1103 measured diffusion coefficients for 158 chemicals in 32 consolidated material types. Following a detailed analysis of the temperature influence, we developed a multiple linear regression model to predict diffusion coefficients as a function of chemical molecular weight (MW), temperature, and material type (adjusted R 2 of .93). The internal validations showed the model to be robust, stable and not a result of chance correlation. The external validation against two separate prediction datasets demonstrated the model has good predicting ability within its applicability domain (Rext2>.8), namely MW between 30 and 1178 g/mol and temperature between 4 and 180°C. By covering a much wider range of organic chemicals and materials, this QPPR facilitates high-throughput estimates of human exposures for chemicals encapsulated in solid materials. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Choline in anxiety and depression: the Hordaland Health Study.

PubMed

Bjelland, Ingvar; Tell, Grethe S; Vollset, Stein E; Konstantinova, Svetlana; Ueland, Per M

2009-10-01

Despite its importance in the central nervous system as a precursor for acetylcholine and membrane phosphatidylcholine, the role of choline in mental illness has been little studied. We examined the cross-sectional association between plasma choline concentrations and scores of anxiety and depression symptoms in a general population sample. We studied a subsample (n = 5918) of the Hordaland Health Study, including both sexes and 2 age groups of 46-49 and 70-74 y who had valid information on plasma choline concentrations and symptoms of anxiety and depression measured by the Hospital Anxiety and Depression Scale--the latter 2 as continuous measures and dichotomized at a score > or =8 for both subscales. The lowest choline quintile was significantly associated with high anxiety levels (odds ratio: 1.33; 95% CI: 1.06, 1.69) in the fully adjusted (age group, sex, time since last meal, educational level, and smoking habits) logistic regression model. Also, the trend test in the anxiety model was significant (P = 0.007). In the equivalent fully adjusted linear regression model, a significant inverse association was found between choline quintiles and anxiety levels (standardized regression coefficient = -0.027, P = 0.045). We found no significant associations in the corresponding analyses of the relation between plasma choline and depression symptoms. In this large population-based study, choline concentrations were negatively associated with anxiety symptoms but not with depression symptoms.

Bayesian Estimation of Multivariate Latent Regression Models: Gauss versus Laplace

ERIC Educational Resources Information Center

Culpepper, Steven Andrew; Park, Trevor

2017-01-01

A latent multivariate regression model is developed that employs a generalized asymmetric Laplace (GAL) prior distribution for regression coefficients. The model is designed for high-dimensional applications where an approximate sparsity condition is satisfied, such that many regression coefficients are near zero after accounting for all the model…

Viability estimation of pepper seeds using time-resolved photothermal signal characterization

NASA Astrophysics Data System (ADS)

Kim, Ghiseok; Kim, Geon-Hee; Lohumi, Santosh; Kang, Jum-Soon; Cho, Byoung-Kwan

2014-11-01

We used infrared thermal signal measurement system and photothermal signal and image reconstruction techniques for viability estimation of pepper seeds. Photothermal signals from healthy and aged seeds were measured for seven periods (24, 48, 72, 96, 120, 144, and 168 h) using an infrared camera and analyzed by a regression method. The photothermal signals were regressed using a two-term exponential decay curve with two amplitudes and two time variables (lifetime) as regression coefficients. The regression coefficients of the fitted curve showed significant differences for each seed groups, depending on the aging times. In addition, the viability of a single seed was estimated by imaging of its regression coefficient, which was reconstructed from the measured photothermal signals. The time-resolved photothermal characteristics, along with the regression coefficient images, can be used to discriminate the aged or dead pepper seeds from the healthy seeds.

Some comparisons of complexity in dictionary-based and linear computational models.

PubMed

Gnecco, Giorgio; Kůrková, Věra; Sanguineti, Marcello

2011-03-01

Neural networks provide a more flexible approximation of functions than traditional linear regression. In the latter, one can only adjust the coefficients in linear combinations of fixed sets of functions, such as orthogonal polynomials or Hermite functions, while for neural networks, one may also adjust the parameters of the functions which are being combined. However, some useful properties of linear approximators (such as uniqueness, homogeneity, and continuity of best approximation operators) are not satisfied by neural networks. Moreover, optimization of parameters in neural networks becomes more difficult than in linear regression. Experimental results suggest that these drawbacks of neural networks are offset by substantially lower model complexity, allowing accuracy of approximation even in high-dimensional cases. We give some theoretical results comparing requirements on model complexity for two types of approximators, the traditional linear ones and so called variable-basis types, which include neural networks, radial, and kernel models. We compare upper bounds on worst-case errors in variable-basis approximation with lower bounds on such errors for any linear approximator. Using methods from nonlinear approximation and integral representations tailored to computational units, we describe some cases where neural networks outperform any linear approximator. Copyright © 2010 Elsevier Ltd. All rights reserved.

The association between season of pregnancy and birth-sex among Chinese.

PubMed

Xu, Tan; Lin, Dongdong; Liang, Hui; Chen, Mei; Tong, Weijun; Mu, Yongping; Feng, Cindy Xin; Gao, Yongqing; Zheng, Yumei; Sun, Wenjie

2014-08-11

although numerous studies have reported the association between birth season and sex ratio, few studies have been conducted in subtropical regions in a non-Western setting. The present study assessed the effects of pregnancy season on birth sex ratio in China. We conducted a national population-based retrospective study from 2006-2008 with 3175 children-parents pairs enrolled in the Northeast regions of China. Demographics and data relating to pregnancy and birth were collected and analyzed. A multiple logistical regression model was fitted to estimate the regression coefficient and 95% confidence interval (CI) of refractive error for mother pregnancy season, adjusting for potential confounders. After adjusting for parental age (cut-off point was 30 years), region, nationality, mother education level, and mother miscarriage history, there is a significant statistical different mother pregnancy season on birth-sex. Compared with mothers who were pregnant in spring, those pregnant in summer or winter had a high probability of delivering girls (p < 0.05). The birth-sex ratio varied with months. Our results suggested that mothers pregnant in summer and winter were more likely to deliver girls, compared with those pregnant in spring. Pregnancy season may play an important role in the birth-sex.

The association between higher nurse staffing standards in the fee schedules and the geographic distribution of hospital nurses: A cross-sectional study using nationwide administrative data.

PubMed

Morioka, Noriko; Tomio, Jun; Seto, Toshikazu; Kobayashi, Yasuki

2017-01-01

In Japan, the revision of the fee schedules in 2006 introduced a new category of general care ward for more advanced care, with a higher staffing standard, a patient-to-nurse ratio of 7:1. Previous studies have suggested that these changes worsened inequalities in the geographic distribution of nurses, but there have been few quantitative studies evaluating this effect. This study aimed to investigate the association between the distribution of 7:1 beds and the geographic distribution of hospital nursing staffs. We conducted a secondary data analysis of hospital reimbursement reports in 2012 in Japan. The study units were secondary medical areas (SMAs) in Japan, which are roughly comparable to hospital service areas in the United States. The outcome variable was the nurse density per 100,000 population in each SMA. The 7:1 bed density per 100,000 population was the main independent variable. To investigate the association between the nurse density and 7:1 bed density, adjusting for other variables, we applied a multiple linear regression model, with nurse density as an outcome variable, and the bed densities by functional category of inpatient ward as independent variables, adding other variables related to socio-economic status and nurse workforce. To investigate whether 7:1 bed density made the largest contribution to the nurse density, compared to other bed densities, we estimated the standardized regression coefficients. There were 344 SMAs in the study period, of which 343 were used because of data availability. There were approximately 553,600 full time equivalent nurses working in inpatient wards in hospitals. The mean (standard deviation) of the full time equivalent nurse density was 426.4 (147.5) and for 7:1 bed density, the figures were 271.9 (185.9). The 7:1 bed density ranged from 0.0 to 1,295.5. After adjusting for the possible confounders, there were more hospital nurses in the areas with higher densities of 7:1 beds (standardized regression coefficient 0.62, 95% confidence interval 0.56-0.68). We found that the 7:1 nurse staffing standard made the largest contribution to the geographic distribution of hospital nurses, adjusted for socio-economic status and nurse workforce-related factors.

Progression of Mortality due to Diseases of the Circulatory System and Human Development Index in Rio de Janeiro Municipalities

PubMed Central

Soares, Gabriel Porto; Klein, Carlos Henrique; Silva, Nelson Albuquerque de Souza e; de Oliveira, Glaucia Maria Moraes

2016-01-01

Background Diseases of the circulatory system (DCS) are the major cause of death in Brazil and worldwide. Objective To correlate the compensated and adjusted mortality rates due to DCS in the Rio de Janeiro State municipalities between 1979 and 2010 with the Human Development Index (HDI) from 1970 onwards. Methods Population and death data were obtained in DATASUS/MS database. Mortality rates due to ischemic heart diseases (IHD), cerebrovascular diseases (CBVD) and DCS adjusted by using the direct method and compensated for ill-defined causes. The HDI data were obtained at the Brazilian Institute of Applied Research in Economics. The mortality rates and HDI values were correlated by estimating Pearson linear coefficients. The correlation coefficients between the mortality rates of census years 1991, 2000 and 2010 and HDI data of census years 1970, 1980 and 1991 were calculated with discrepancy of two demographic censuses. The linear regression coefficients were estimated with disease as the dependent variable and HDI as the independent variable. Results In recent decades, there was a reduction in mortality due to DCS in all Rio de Janeiro State municipalities, mainly because of the decline in mortality due to CBVD, which was preceded by an elevation in HDI. There was a strong correlation between the socioeconomic indicator and mortality rates. Conclusion The HDI progression showed a strong correlation with the decline in mortality due to DCS, signaling to the relevance of improvements in life conditions. PMID:27849263

Progression of Mortality due to Diseases of the Circulatory System and Human Development Index in Rio de Janeiro Municipalities.

PubMed

Soares, Gabriel Porto; Klein, Carlos Henrique; Silva, Nelson Albuquerque de Souza E; Oliveira, Glaucia Maria Moraes de

2016-10-01

Diseases of the circulatory system (DCS) are the major cause of death in Brazil and worldwide. To correlate the compensated and adjusted mortality rates due to DCS in the Rio de Janeiro State municipalities between 1979 and 2010 with the Human Development Index (HDI) from 1970 onwards. Population and death data were obtained in DATASUS/MS database. Mortality rates due to ischemic heart diseases (IHD), cerebrovascular diseases (CBVD) and DCS adjusted by using the direct method and compensated for ill-defined causes. The HDI data were obtained at the Brazilian Institute of Applied Research in Economics. The mortality rates and HDI values were correlated by estimating Pearson linear coefficients. The correlation coefficients between the mortality rates of census years 1991, 2000 and 2010 and HDI data of census years 1970, 1980 and 1991 were calculated with discrepancy of two demographic censuses. The linear regression coefficients were estimated with disease as the dependent variable and HDI as the independent variable. In recent decades, there was a reduction in mortality due to DCS in all Rio de Janeiro State municipalities, mainly because of the decline in mortality due to CBVD, which was preceded by an elevation in HDI. There was a strong correlation between the socioeconomic indicator and mortality rates. The HDI progression showed a strong correlation with the decline in mortality due to DCS, signaling to the relevance of improvements in life conditions.

Optimization of selective breeding through analysis of morphological traits in Chinese sea bass (Lateolabrax maculatus).

PubMed

Wang, W; Ma, C Y; Chen, W; Ma, H Y; Zhang, H; Meng, Y Y; Ni, Y; Ma, L B

2016-08-19

Determining correlations between certain traits of economic importance constitutes an essential component of selective activities. In this study, our aim was to provide effective indicators for breeding programs of Lateolabrax maculatus, an important aquaculture species in China. We analyzed correlations between 20 morphometric traits and body weight, using correlation and path analyses. The results indicated that the correlations among all 21 traits were highly significant, with the highest correlation coefficient identified between total length and body weight. The path analysis indicated that total length (X 1 ), body width (X 5 ), distance from first dorsal fin origin to anal fin origin (X 10 ), snout length (X 16 ), eye diameter (X 17 ), eye cross (X 18 ), and slanting distance from snout tip to first dorsal fin origin (X 19 ) significantly affected body weight (Y) directly. The following multiple-regression equation was obtained using stepwise multiple-regression analysis: Y = -472.108 + 1.065X 1 + 7.728X 5 + 1.973X 10 - 7.024X 16 - 4.400X 17 - 3.338X 18 + 2.138X 19 , with an adjusted multiple-correlation coefficient of 0.947. Body width had the largest determinant coefficient, as well as the highest positive direct correlation with body weight. At the same time, high indirect effects with six other morphometric traits on L. maculatus body weight, through body width, were identified. Hence, body width could be a key factor that efficiently indicates significant effects on body weight in L. maculatus.

Premature Cardiac Aging in South Asian Compared to Afro-Caribbean Subjects in a Community-Based Screening Study.

PubMed

Shantsila, Eduard; Shantsila, Alena; Gill, Paramjit S; Lip, Gregory Y H

2016-11-10

People of South Asian (SAs) and African Caribbean (AC) origin have increased cardiovascular morbidity, but underlying mechanisms are poorly understood. Aging is the key predictor of deterioration in diastolic function, which can be assessed by echocardiography using E/e' ratio as a surrogate of left ventricular (LV) filling pressure. The study aimed to assess a possibility of premature cardiac aging in SA and AC subjects. We studied 4540 subjects: 2880 SA and 1660 AC subjects. All participants underwent detailed echocardiography, including LV ejection fraction, average septal-lateral E/e', and LV mass index (LVMI). When compared to ACs, SAs were younger, with lower mean LVMI, systolic blood pressure (BP), diastolic BP, and body mass index (BMI), as well as a lower prevalence of hypertension and smoking (P≤0.001 for all). In a multivariate linear regression model including age, sex, ethnicity, BP, heart rate, BMI, waist circumference, LVMI, history of smoking, hypertension, coronary artery disease, diabetes mellitus, medications, SA origin was independently associated with higher E/e' (regression coefficient±standard error, -0.66±0.10; P<0.001, adjusted R 2 for the model 0.21; P<0.001). Furthermore, SAs had significantly accelerated age-dependent increase in E/e' compared to ACs. On multivariable Cox regression analysis without adjustment for E/e', SA ethnicity was independently predictive of mortality (P=0.04). After additional adjustment for E/e', the ethnicity lost its significance value, whereas E/e' was independently predictive of higher risk of death (P=0.008). Premature cardiac aging is evident in SAs and may contribute to high cardiovascular morbidity in this ethnic group, compared to ACs. © 2016 The Authors. Published on behalf of the American Heart Association, Inc., by Wiley Blackwell.

Penalized spline estimation for functional coefficient regression models.

PubMed

Cao, Yanrong; Lin, Haiqun; Wu, Tracy Z; Yu, Yan

2010-04-01

The functional coefficient regression models assume that the regression coefficients vary with some "threshold" variable, providing appreciable flexibility in capturing the underlying dynamics in data and avoiding the so-called "curse of dimensionality" in multivariate nonparametric estimation. We first investigate the estimation, inference, and forecasting for the functional coefficient regression models with dependent observations via penalized splines. The P-spline approach, as a direct ridge regression shrinkage type global smoothing method, is computationally efficient and stable. With established fixed-knot asymptotics, inference is readily available. Exact inference can be obtained for fixed smoothing parameter λ, which is most appealing for finite samples. Our penalized spline approach gives an explicit model expression, which also enables multi-step-ahead forecasting via simulations. Furthermore, we examine different methods of choosing the important smoothing parameter λ: modified multi-fold cross-validation (MCV), generalized cross-validation (GCV), and an extension of empirical bias bandwidth selection (EBBS) to P-splines. In addition, we implement smoothing parameter selection using mixed model framework through restricted maximum likelihood (REML) for P-spline functional coefficient regression models with independent observations. The P-spline approach also easily allows different smoothness for different functional coefficients, which is enabled by assigning different penalty λ accordingly. We demonstrate the proposed approach by both simulation examples and a real data application.

Relation between histological prostatitis and lower urinary tract symptoms and erectile function.

PubMed

Mizuno, Taiki; Hiramatsu, Ippei; Aoki, Yusuke; Shimoyama, Hirofumi; Nozaki, Taiji; Shirai, Masato; Lu, Yan; Horie, Shigeo; Tsujimura, Akira

2017-09-01

Chronic prostatitis (CP) significantly worsens a patient's quality of life (QOL), but its etiology is heterogeneous. Although the inflammatory process must be associated with CP symptoms, not all patients with benign prostatic hyperplasia and histological prostatitis complain of CP symptoms. The relation between the severity of histological inflammation and lower urinary tract symptoms (LUTS) and erectile function is not fully understood. This study comprised 26 men with suspected prostate cancer but with no malignant lesion by pathological examination of prostate biopsy specimens. LUTS were assessed by several questionnaires including the International Prostate Symptom Score (IPSS), QOL index, Overactive Bladder Symptom Score (OABSS), and the National Institutes of Health-Chronic Prostatitis Symptom Index (NIH-CPSI), and erectile function was assessed by the Sexual Health Inventory for Men. Prostate volume (PV) measured by transabdominal ultrasound, maximum flow rate by uroflowmetry, and serum concentration of prostate-specific antigen were also evaluated. All data collections were performed before prostate biopsy. Histological prostatitis was assessed by immunohistochemical staining with anti-CD45 antibody as the Quick score. The relation between the Quick score and several factors was assessed by Pearson correlation coefficient and a multivariate linear regression model after adjustment for PV. The Pearson correlation coefficient showed a correlation between the Quick score and several factors including PV, IPSS, QOL index, OABSS, and NIH-CPSI. A multivariate linear regression model after adjustment for PV showed only the NIH-CPSI to be associated with the Quick score. The relation between the Quick score and each domain score of the NIH-CPSI showed only the subscore of urinary symptoms to be an associated factor. We found a correlation only between histological prostatitis and LUTS, but not erectile dysfunction. Especially, the subscore of urinary symptoms (residual feeling and urinary frequency) was associated with histological prostatitis.

Chronic obstructive pulmonary disease in Welsh slate miners.

PubMed

Reynolds, C J; MacNeill, S J; Williams, J; Hodges, N G; Campbell, M J; Newman Taylor, A J; Cullinan, P

2017-01-01

Exposure to respirable crystalline silica (RCS) causes emphysema, airflow limitation and chronic obstructive pulmonary disease (COPD). Slate miners are exposed to slate dust containing RCS but their COPD risk has not previously been studied. To study the cumulative effect of mining on lung function and risk of COPD in a cohort of Welsh slate miners and whether these were independent of smoking and pneumoconiosis. The study was based on a secondary analysis of Medical Research Council (MRC) survey data. COPD was defined as forced expiratory volume in 1 s/forced vital capacity (FEV 1 /FVC) ratio <0.7. We created multivariable models to assess the association between mining and lung function after adjusting for age and smoking status. We used linear regression models for FEV 1 and FVC and logistic regression for COPD. In the original MRC study, 1255 men participated (726 slate miners, 529 unexposed non-miners). COPD was significantly more common in miners (n = 213, 33%) than non-miners (n = 120, 26%), P < 0.05. There was no statistically significant difference in risk of COPD between miners and non-miners when analysis was limited to non-smokers or those without radiographic evidence of pneumoconiosis. After adjustment for smoking, slate mining was associated with a reduction in %predicted FEV 1 [β coefficient = -3.97, 95% confidence interval (CI) -6.65, -1.29] and FVC (β coefficient = -2.32, 95% CI -4.31, -0.33) and increased risk of COPD (odds ratio: 1.38, 95% CI 1.06, 1.81). Slate mining may reduce lung function and increase the incidence of COPD independently of smoking and pneumoconiosis. © The Author 2016. Published by Oxford University Press on behalf of the Society of Occupational Medicine. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Medication adherence and visit-to-visit variability of systolic blood pressure in African Americans with chronic kidney disease in the AASK trial.

PubMed

Hong, K; Muntner, P; Kronish, I; Shilane, D; Chang, T I

2016-01-01

Lower adherence to antihypertensive medications may increase visit-to-visit variability of blood pressure (VVV of BP), a risk factor for cardiovascular events and death. We used data from the African American Study of Kidney Disease and Hypertension (AASK) trial to examine whether lower medication adherence is associated with higher systolic VVV of BP in African Americans with hypertensive chronic kidney disease (CKD). Determinants of VVV of BP were also explored. AASK participants (n=988) were categorized by self-report or pill count as having perfect (100%), moderately high (75-99%), moderately low (50-74%) or low (<50%) proportion of study visits with high medication adherence over a 1-year follow-up period. We used multinomial logistic regression to examine determinants of medication adherence, and multivariable-adjusted linear regression to examine the association between medication adherence and systolic VVV of BP, defined as the coefficient of variation or the average real variability (ARV). Participants with lower self-reported adherence were generally younger and had a higher prevalence of comorbid conditions. Compared with perfect adherence, moderately high, moderately low and low adherence was associated with 0.65% (±0.31%), 0.99% (±0.31%) and 1.29% (±0.32%) higher systolic VVV of BP (defined as the coefficient of variation) in fully adjusted models. Results were qualitatively similar when using ARV or when using pill counts as the measure of adherence. Lower medication adherence is associated with higher systolic VVV of BP in African Americans with hypertensive CKD; efforts to improve medication adherence in this population may reduce systolic VVV of BP.

Breast feeding and resilience against psychosocial stress

PubMed Central

Montgomery, S M; Ehlin, A; Sacker, A

2006-01-01

Background Some early life exposures may result in a well controlled stress response, which can reduce stress related anxiety. Breast feeding may be a marker of some relevant exposures. Aims To assess whether breast feeding is associated with modification of the relation between parental divorce and anxiety. Methods Observational study using longitudinal birth cohort data. Linear regression was used to assess whether breast feeding modifies the association of parental divorce/separation with anxiety using stratification and interaction testing. Data were obtained from the 1970 British Cohort Study, which is following the lives of those born in one week in 1970 and living in Great Britain. This study uses information collected at birth and at ages 5 and 10 years for 8958 subjects. Class teachers answered a question on anxiety among 10 year olds using an analogue scale (range 0–50) that was log transformed to minimise skewness. Results Among 5672 non‐breast fed subjects, parental divorce/separation was associated with a statistically significantly raised risk of anxiety, with a regression coefficient (95% CI) of 9.4 (6.1 to 12.8). Among the breast fed group this association was much lower: 2.2 (−2.6 to 7.0). Interaction testing confirmed statistically significant effect modification by breast feeding, independent of simultaneous adjustment for multiple potential confounding factors, producing an interaction coefficient of −7.0 (−12.8 to −1.2), indicating a 7% reduction in anxiety after adjustment. Conclusions Breast feeding is associated with resilience against the psychosocial stress linked with parental divorce/separation. This could be because breast feeding is a marker of exposures related to maternal characteristics and parent–child interaction. PMID:16887859

Can Salivary Acetylcholinesterase be a Diagnostic Biomarker for Alzheimer?

PubMed

Bakhtiari, Sedigheh; Moghadam, Nahid Beladi; Ehsani, Marjan; Mortazavi, Hamed; Sabour, Siamak; Bakhshi, Mahin

2017-01-01

The loss of brain cholinergic activity is a key phenomenon in the biochemistry of Alzheimer's Disease (AD). Due to the specific biosynthesis of Acetylcholinesterase (AChE) of cholinergic neurons, the enzyme has been proposed as a potential biochemical marker of cholinergic activity. AChE is expressed not only in the Central Nervous System (CNS), Peripheral Nervous System (PNS) and muscles, but also on the surface of blood cells and saliva. This study aimed to measure salivary AChE activity in AD and to determine the feasibility of creating a simple laboratory test for diagnosing such patients. In this cross-sectional study, the recorded data were obtained from 15 Alzheimer's patients on memantine therapy and 15 healthy subjects. Unstimulated whole saliva samples were collected from the participants and salivary levels of AChE activity were determined by using the Ellman colorimetric method. The Mann Whitney U test was used to compare the average (median) of AChE activity between AD and controls. In order to adjust for possible confounding factors, partial correlation coefficient and multivariate linear regressions were used. Although the average of AChE activity in the saliva of people with AD was lower compared to the control group, we found no statistically significant differences using Mann Whitney U test (138 in control group vs. 175 in Alzheimer's patients, p value=0.25). Additionally, no significant differences were observed in the activity of this enzyme in both sexes or with increased age or duration of the disease. After adjusting for age and gender, there was no association between AChE activity and AD (regression coefficient β=0.08; p value= 0.67). Saliva AChE activity was not significantly associated with AD. This study might help in introduce a new diagnostic aid for AD or monitor patients with AD.

Hidden Connections between Regression Models of Strain-Gage Balance Calibration Data

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert

2013-01-01

Hidden connections between regression models of wind tunnel strain-gage balance calibration data are investigated. These connections become visible whenever balance calibration data is supplied in its design format and both the Iterative and Non-Iterative Method are used to process the data. First, it is shown how the regression coefficients of the fitted balance loads of a force balance can be approximated by using the corresponding regression coefficients of the fitted strain-gage outputs. Then, data from the manual calibration of the Ames MK40 six-component force balance is chosen to illustrate how estimates of the regression coefficients of the fitted balance loads can be obtained from the regression coefficients of the fitted strain-gage outputs. The study illustrates that load predictions obtained by applying the Iterative or the Non-Iterative Method originate from two related regression solutions of the balance calibration data as long as balance loads are given in the design format of the balance, gage outputs behave highly linear, strict statistical quality metrics are used to assess regression models of the data, and regression model term combinations of the fitted loads and gage outputs can be obtained by a simple variable exchange.

Temperature-viscosity models reassessed.

PubMed

Peleg, Micha

2017-05-04

The temperature effect on viscosity of liquid and semi-liquid foods has been traditionally described by the Arrhenius equation, a few other mathematical models, and more recently by the WLF and VTF (or VFT) equations. The essence of the Arrhenius equation is that the viscosity is proportional to the absolute temperature's reciprocal and governed by a single parameter, namely, the energy of activation. However, if the absolute temperature in K in the Arrhenius equation is replaced by T + b where both T and the adjustable b are in °C, the result is a two-parameter model, which has superior fit to experimental viscosity-temperature data. This modified version of the Arrhenius equation is also mathematically equal to the WLF and VTF equations, which are known to be equal to each other. Thus, despite their dissimilar appearances all three equations are essentially the same model, and when used to fit experimental temperature-viscosity data render exactly the same very high regression coefficient. It is shown that three new hybrid two-parameter mathematical models, whose formulation bears little resemblance to any of the conventional models, can also have excellent fit with r 2 ∼ 1. This is demonstrated by comparing the various models' regression coefficients to published viscosity-temperature relationships of 40% sucrose solution, soybean oil, and 70°Bx pear juice concentrate at different temperature ranges. Also compared are reconstructed temperature-viscosity curves using parameters calculated directly from 2 or 3 data points and fitted curves obtained by nonlinear regression using a larger number of experimental viscosity measurements.

Association between income inequality and dental status in Japanese older adults: Analysis of data from JAGES2013.

PubMed

Tashiro, Atsushi; Aida, Jun; Shobugawa, Yugo; Fujiyama, Yuki; Yamamoto, Tatsuo; Saito, Reiko; Kondo, Katsunori

2017-01-01

Objectives　Personal income affects dental status in older people. However, the impact of income inequality on dental status at the community level (junior high school district) is unclear. The purpose of this study was to examine the association between dental status and community level income inequity after adjust for individual socio-economic status in Japanese older adults, and to verify the relative income hypothesis, also known as the Wilkinson hypothesis.Methods　We used data from the Japan Gerontological Evaluation Study (JAGES) conducted in Niigata city. JAGES is a postal survey of functionally independent adults aged 65 years or older. We enrolled 4,983 respondents (response rate 62.3%) and used data on 3,980 of them after excluding incomplete data. We evaluated health condition and socio-economic status using questionnaires. The Gini coefficient, as an indicator of income inequality, was calculated by junior high school district (57 districts) based on the data from the questionnaire. Additionally, the Pearson's coefficient of correlation was calculated to evaluate the association between the mean number of remaining teeth and the community level Gini coefficient. Then we evaluated the mean number of remaining teeth among the groups stratified by the Gini coefficient conditions. Next, we conducted a multilevel analysis using an ordinal logistic regression model. The number of remaining teeth was set as the dependent variable, while sex, age, household size, education, smoking status, diabetes treatment, current living conditions, and equivalent income were used as independent variables at the individual level. The Gini coefficient and average equivalent income in the junior high school district were used as independent variables at the community level.Results　The Pearson's correlation coefficient for the relationship between the Gini coefficient and the mean number of remaining teeth in the junior high school district was -0.44 (P<0.01). Wider income disparity area (Gini coefficient≧0.35) revealed a significantly small number of remaining teeth (P<0.001). The multilevel analysis showed that a higher Gini coefficient and a lower average equivalent income at the community level were significantly associated with a lower number of remaining teeth, and with educational attainment, smoking status, current living conditions, and equivalent income at the individual level, after adjusting for sex and age. On the other hand, educational attainment at the individual level, and average equivalent income at the community level were not significant factors after adjusting for all individual level variables.Conclusion　This study showed that, in addition to individual socio-economic status, income inequality at the community level was significantly associated with number of remaining teeth in Japanese older adults. Although the precise mechanism of this association is still unclear, our result supports the relative income hypothesis.

Estimation of Flood Discharges at Selected Recurrence Intervals for Streams in New Hampshire

USGS Publications Warehouse

Olson, Scott A.

2009-01-01

This report provides estimates of flood discharges at selected recurrence intervals for streamgages in and adjacent to New Hampshire and equations for estimating flood discharges at recurrence intervals of 2-, 5-, 10-, 25-, 50-, 100-, and 500-years for ungaged, unregulated, rural streams in New Hampshire. The equations were developed using generalized least-squares regression. Flood-frequency and drainage-basin characteristics from 117 streamgages were used in developing the equations. The drainage-basin characteristics used as explanatory variables in the regression equations include drainage area, mean April precipitation, percentage of wetland area, and main channel slope. The average standard error of prediction for estimating the 2-, 5-, 10-, 25-, 50-, 100-, and 500-year recurrence interval flood discharges with these equations are 30.0, 30.8, 32.0, 34.2, 36.0, 38.1, and 43.4 percent, respectively. Flood discharges at selected recurrence intervals for selected streamgages were computed following the guidelines in Bulletin 17B of the U.S. Interagency Advisory Committee on Water Data. To determine the flood-discharge exceedence probabilities at streamgages in New Hampshire, a new generalized skew coefficient map covering the State was developed. The standard error of the data on new map is 0.298. To improve estimates of flood discharges at selected recurrence intervals for 20 streamgages with short-term records (10 to 15 years), record extension using the two-station comparison technique was applied. The two-station comparison method uses data from a streamgage with long-term record to adjust the frequency characteristics at a streamgage with a short-term record. A technique for adjusting a flood-discharge frequency curve computed from a streamgage record with results from the regression equations is described in this report. Also, a technique is described for estimating flood discharge at a selected recurrence interval for an ungaged site upstream or downstream from a streamgage using a drainage-area adjustment. The final regression equations and the flood-discharge frequency data used in this study will be available in StreamStats. StreamStats is a World Wide Web application providing automated regression-equation solutions for user-selected sites on streams.

The association of endothelial function and tone by digital arterial tonometry with MRI left ventricular mass in African Americans: the Jackson Heart Study.

PubMed

Tripathi, Avnish; Benjamin, Emelia J; Musani, Solomon K; Hamburg, Naomi M; Tsao, Connie W; Saraswat, Arti; Vasan, Ramachandran S; Mitchell, Gary F; Fox, Ervin R

2017-05-01

Peripheral vascular endothelial dysfunction assessed by digital peripheral arterial tonometry (PAT) has been associated with risk for adverse cardiovascular events. We examined the relations of peripheral microvascular dysfunction and left ventricular mass in a community-based cohort of African Americans. We examined participants of the Jackson Heart Study who had PAT and cardiac magnetic resonance imaging evaluations between 2007 and 2013. Consistent with pertinent literature, left ventricular mass index (LVMI) was adjusted for body size by indexing to height 2.7 . Pearson's correlation and general linear regression analyses were used to relate reactive hyperemia index, baseline pulse amplitude (BPA), and augmentation index (markers of microvascular vasodilator function, baseline vascular pulsatility, and relative wave reflection, respectively) to LVMI after adjusting for traditional cardiovascular risk factors. A total of 440 participants (mean age 59 ± 10 years, 60% women) were included. Age- and sex-adjusted Pearson's correlation analysis suggested that natural log transformed LVMI was negatively correlated with reactive hyperemia index (coefficient: -0.114; P = .02) and positively correlated with BPA (coefficient: 0.272; P < .001). In multivariable analyses, higher log e LVMI was associated with higher BPA (β: 0.210; P = .03) after accounting for age, sex, body mass index, diabetes, hypertension, ratio of total cholesterol and high-density lipoprotein cholesterol, smoking, and history of cardiovascular disease. In a community-based sample of African Americans, higher baseline pulsatility measured by PAT was associated with higher LVMI by cardiac magnetic resonance imaging after adjusting for traditional risk factors. Copyright © 2017 American Society of Hypertension. Published by Elsevier Inc. All rights reserved.

Wrong Signs in Regression Coefficients

NASA Technical Reports Server (NTRS)

McGee, Holly

1999-01-01

When using parametric cost estimation, it is important to note the possibility of the regression coefficients having the wrong sign. A wrong sign is defined as a sign on the regression coefficient opposite to the researcher's intuition and experience. Some possible causes for the wrong sign discussed in this paper are a small range of x's, leverage points, missing variables, multicollinearity, and computational error. Additionally, techniques for determining the cause of the wrong sign are given.

Comparison of Nimbus-7 SMMR and GOES-1 VISSR Atmospheric Liquid Water Content.

NASA Astrophysics Data System (ADS)

Lojou, Jean-Yves; Frouin, Robert; Bernard, René

1991-02-01

Vertically integrated atmospheric liquid water content derived from Nimbus-7 Scanning Multichannel Microwave Radiometer (SMMR) brightness temperatures and from GOES-1 Visible and Infrared Spin-Scan Radiometer (VISSR) radiances in the visible are compared over the Indian Ocean during MONEX (monsoon experiment). In the retrieval procedure, Wilheit and Chang' algorithm and Stephens' parameterization schemes are applied to the SMMR and VISSR data, respectively. The results indicate that in the 0-100 mg cm2 range of liquid water content considered, the correlation coefficient between the two types of estimates is 0.83 (0.81- 0.85 at the 99 percent confidence level). The Wilheit and Chang algorithm, however, yields values lower than those obtained with Stephens's schemes by 24.5 mg cm2 on the average, and occasionally the SMMR-based values are negative. Alternative algorithms are proposed for use with SMMR data, which eliminate the bias, augment the correlation coefficient, and reduce the rms difference. These algorithms include using the Witheit and Chang formula with modified coefficients (multilinear regression), the Wilheit and Chang formula with the same coefficients but different equivalent atmospheric temperatures for each channel (temperature bias adjustment), and a second-order polynomial in brightness temperatures at 18, 21, and 37 GHz (polynomial development). When applied to a dataset excluded from the regressionn dataset, the multilinear regression algorithm provides the best results, namely a 0.91 correlation coefficient, a 5.2 mg cm2 (residual) difference, and a 2.9 mg cm2 bias. Simply shifting the liquid water content predicted by the Wilheit and Chang algorithm does not yield as good comparison statistics, indicating that the occasional negative values are not due only to a bias. The more accurate SMMR-derived liquid water content allows one to better evaluate cloud transmittance in the solar spectrum, at least in the area and during the period analyzed. Combining this cloud transmittance with a clear sky model would provide ocean surface insulation estimates from SMMR data alone.

Covariate Imbalance and Adjustment for Logistic Regression Analysis of Clinical Trial Data

PubMed Central

Ciolino, Jody D.; Martin, Reneé H.; Zhao, Wenle; Jauch, Edward C.; Hill, Michael D.; Palesch, Yuko Y.

2014-01-01

In logistic regression analysis for binary clinical trial data, adjusted treatment effect estimates are often not equivalent to unadjusted estimates in the presence of influential covariates. This paper uses simulation to quantify the benefit of covariate adjustment in logistic regression. However, International Conference on Harmonization guidelines suggest that covariate adjustment be pre-specified. Unplanned adjusted analyses should be considered secondary. Results suggest that that if adjustment is not possible or unplanned in a logistic setting, balance in continuous covariates can alleviate some (but never all) of the shortcomings of unadjusted analyses. The case of log binomial regression is also explored. PMID:24138438

Noninvasive spectral imaging of skin chromophores based on multiple regression analysis aided by Monte Carlo simulation

NASA Astrophysics Data System (ADS)

Nishidate, Izumi; Wiswadarma, Aditya; Hase, Yota; Tanaka, Noriyuki; Maeda, Takaaki; Niizeki, Kyuichi; Aizu, Yoshihisa

2011-08-01

In order to visualize melanin and blood concentrations and oxygen saturation in human skin tissue, a simple imaging technique based on multispectral diffuse reflectance images acquired at six wavelengths (500, 520, 540, 560, 580 and 600nm) was developed. The technique utilizes multiple regression analysis aided by Monte Carlo simulation for diffuse reflectance spectra. Using the absorbance spectrum as a response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as predictor variables, multiple regression analysis provides regression coefficients. Concentrations of melanin and total blood are then determined from the regression coefficients using conversion vectors that are deduced numerically in advance, while oxygen saturation is obtained directly from the regression coefficients. Experiments with a tissue-like agar gel phantom validated the method. In vivo experiments with human skin of the human hand during upper limb occlusion and of the inner forearm exposed to UV irradiation demonstrated the ability of the method to evaluate physiological reactions of human skin tissue.

Risk-adjusted antibiotic consumption in 34 public acute hospitals in Ireland, 2006 to 2014

PubMed Central

Oza, Ajay; Donohue, Fionnuala; Johnson, Howard; Cunney, Robert

2016-01-01

As antibiotic consumption rates between hospitals can vary depending on the characteristics of the patients treated, risk-adjustment that compensates for the patient-based variation is required to assess the impact of any stewardship measures. The aim of this study was to investigate the usefulness of patient-based administrative data variables for adjusting aggregate hospital antibiotic consumption rates. Data on total inpatient antibiotics and six broad subclasses were sourced from 34 acute hospitals from 2006 to 2014. Aggregate annual patient administration data were divided into explanatory variables, including major diagnostic categories, for each hospital. Multivariable regression models were used to identify factors affecting antibiotic consumption. Coefficient of variation of the root mean squared errors (CV-RMSE) for the total antibiotic usage model was very good (11%), however, the value for two of the models was poor (> 30%). The overall inpatient antibiotic consumption increased from 82.5 defined daily doses (DDD)/100 bed-days used in 2006 to 89.2 DDD/100 bed-days used in 2014; the increase was not significant after risk-adjustment. During the same period, consumption of carbapenems increased significantly, while usage of fluoroquinolones decreased. In conclusion, patient-based administrative data variables are useful for adjusting hospital antibiotic consumption rates, although additional variables should also be employed. PMID:27541730

Estimation of peak discharge quantiles for selected annual exceedance probabilities in northeastern Illinois

USGS Publications Warehouse

Over, Thomas M.; Saito, Riki J.; Veilleux, Andrea G.; Sharpe, Jennifer B.; Soong, David T.; Ishii, Audrey L.

2016-06-28

This report provides two sets of equations for estimating peak discharge quantiles at annual exceedance probabilities (AEPs) of 0.50, 0.20, 0.10, 0.04, 0.02, 0.01, 0.005, and 0.002 (recurrence intervals of 2, 5, 10, 25, 50, 100, 200, and 500 years, respectively) for watersheds in Illinois based on annual maximum peak discharge data from 117 watersheds in and near northeastern Illinois. One set of equations was developed through a temporal analysis with a two-step least squares-quantile regression technique that measures the average effect of changes in the urbanization of the watersheds used in the study. The resulting equations can be used to adjust rural peak discharge quantiles for the effect of urbanization, and in this study the equations also were used to adjust the annual maximum peak discharges from the study watersheds to 2010 urbanization conditions.The other set of equations was developed by a spatial analysis. This analysis used generalized least-squares regression to fit the peak discharge quantiles computed from the urbanization-adjusted annual maximum peak discharges from the study watersheds to drainage-basin characteristics. The peak discharge quantiles were computed by using the Expected Moments Algorithm following the removal of potentially influential low floods defined by a multiple Grubbs-Beck test. To improve the quantile estimates, regional skew coefficients were obtained from a newly developed regional skew model in which the skew increases with the urbanized land use fraction. The drainage-basin characteristics used as explanatory variables in the spatial analysis include drainage area, the fraction of developed land, the fraction of land with poorly drained soils or likely water, and the basin slope estimated as the ratio of the basin relief to basin perimeter.This report also provides the following: (1) examples to illustrate the use of the spatial and urbanization-adjustment equations for estimating peak discharge quantiles at ungaged sites and to improve flood-quantile estimates at and near a gaged site; (2) the urbanization-adjusted annual maximum peak discharges and peak discharge quantile estimates at streamgages from 181 watersheds including the 117 study watersheds and 64 additional watersheds in the study region that were originally considered for use in the study but later deemed to be redundant.The urbanization-adjustment equations, spatial regression equations, and peak discharge quantile estimates developed in this study will be made available in the web application StreamStats, which provides automated regression-equation solutions for user-selected stream locations. Figures and tables comparing the observed and urbanization-adjusted annual maximum peak discharge records by streamgage are provided at https://doi.org/10.3133/sir20165050 for download.

Clinical Associations of Human T-Lymphotropic Virus Type 1 Infection in an Indigenous Australian Population

PubMed Central

Einsiedel, Lloyd; Spelman, Tim; Goeman, Emma; Cassar, Olivier; Arundell, Mick; Gessain, Antoine

2014-01-01

Introduction In resource-poor areas, infectious diseases may be important causes of morbidity among individuals infected with the Human T-Lymphotropic Virus type 1 (HTLV-1). We report the clinical associations of HTLV-1 infection among socially disadvantaged Indigenous adults in central Australia. Methodology and Principal Findings HTLV-1 serological results for Indigenous adults admitted 1st January 2000 to 31st December 2010 were obtained from the Alice Springs Hospital pathology database. Infections, comorbid conditions and HTLV-1 related diseases were identified using ICD-10 AM discharge morbidity codes. Relevant pathology and imaging results were reviewed. Disease associations, admission rates and risk factors for death were compared according to HTLV-1 serostatus. HTLV-1 western blots were positive for 531 (33.3%) of 1595 Indigenous adults tested. Clinical associations of HTLV-1 infection included bronchiectasis (adjusted Risk Ratio, 1.35; 95% CI, 1.14–1.60), blood stream infections (BSI) with enteric organisms (aRR, 1.36; 95% CI, 1.05–1.77) and admission with strongyloidiasis (aRR 1.38; 95% CI, 1.16–1.64). After adjusting for covariates, HTLV-1 infection remained associated with increased numbers of BSI episodes (adjusted negative binomial regression, coefficient, 0.21; 95% CI, 0.02–0.41) and increased admission numbers with strongyloidiasis (coefficient, 0.563; 95% CI, 0.17–0.95) and respiratory conditions including asthma (coefficient, 0.99; 95% CI, 0.27–1.7), lower respiratory tract infections (coefficient, 0.19; 95% CI, 0.04–0.34) and bronchiectasis (coefficient, 0.60; 95% CI, 0.02–1.18). Two patients were admitted with adult T-cell Leukemia/Lymphoma, four with probable HTLV-1 associated myelopathy and another with infective dermatitis. Independent predictors of mortality included BSI with enteric organisms (aRR 1.78; 95% CI, 1.15–2.74) and bronchiectasis (aRR 2.07; 95% CI, 1.45–2.98). Conclusion HTLV-1 infection contributes to morbidity among socially disadvantaged Indigenous adults in central Australia. This is largely due to an increased risk of other infections and respiratory disease. The spectrum of HTLV-1 related diseases may vary according to the social circumstances of the affected population. PMID:24454973

Determination of organic compounds in water using ultraviolet LED

NASA Astrophysics Data System (ADS)

Kim, Chihoon; Ji, Taeksoo; Eom, Joo Beom

2018-04-01

This paper describes a method of detecting organic compounds in water using an ultraviolet LED (280 nm) spectroscopy system and a photodetector. The LED spectroscopy system showed a high correlation between the concentration of the prepared potassium hydrogen phthalate and that calculated by multiple linear regression, indicating an adjusted coefficient of determination ranging from 0.953-0.993. In addition, a comparison between the performance of the spectroscopy system and the total organic carbon analyzer indicated that the difference in concentration was small. Based on the close correlation between the spectroscopy and photodetector absorbance values, organic measurement with a photodetector could be configured for monitoring.

Boosting structured additive quantile regression for longitudinal childhood obesity data.

PubMed

Fenske, Nora; Fahrmeir, Ludwig; Hothorn, Torsten; Rzehak, Peter; Höhle, Michael

2013-07-25

Childhood obesity and the investigation of its risk factors has become an important public health issue. Our work is based on and motivated by a German longitudinal study including 2,226 children with up to ten measurements on their body mass index (BMI) and risk factors from birth to the age of 10 years. We introduce boosting of structured additive quantile regression as a novel distribution-free approach for longitudinal quantile regression. The quantile-specific predictors of our model include conventional linear population effects, smooth nonlinear functional effects, varying-coefficient terms, and individual-specific effects, such as intercepts and slopes. Estimation is based on boosting, a computer intensive inference method for highly complex models. We propose a component-wise functional gradient descent boosting algorithm that allows for penalized estimation of the large variety of different effects, particularly leading to individual-specific effects shrunken toward zero. This concept allows us to flexibly estimate the nonlinear age curves of upper quantiles of the BMI distribution, both on population and on individual-specific level, adjusted for further risk factors and to detect age-varying effects of categorical risk factors. Our model approach can be regarded as the quantile regression analog of Gaussian additive mixed models (or structured additive mean regression models), and we compare both model classes with respect to our obesity data.

Crossbred steer temperament as yearlings and whole genome association of steer temperament as yearlings and calf temperament post-weaning.

PubMed

Riley, D G; Gill, C A; Boldt, C R; Funkhouser, R R; Herring, A D; Riggs, P K; Sawyer, J E; Lunt, D K; Sanders, J O

2016-04-01

cattle often have the reputation for a poor or dangerous temperament. Identification of genomic regions that associate with temperament of such cattle may be useful for genetic improvement strategies. The objectives of this study were to evaluate subjective temperament scores (1 to 9; higher scores indicated more unfavorable temperament) for aggressiveness, nervousness, flightiness, gregariousness, and overall temperament of one-half steers in feedlot conditions at 1 yr of age and compare those scores of those steers when evaluated approximately 1 mo postweaning, and conduct whole genome association analyses using SNP markers and the temperament traits of those steers at 1 yr of age and for temperament traits of all calves at weaning. Contemporary groups ( < 0.001) were steers born in the same year and season, and fed in the same feedlot pen. Aggressiveness of steers at 1 yr of age was not associated with aggressiveness at weaning (linear regression coefficient did not differ from 0; = 0.96), but regressions of all other yearling scores of steers on the scores at weaning were positive (coefficients ranged from 0.26 ± 0.04 to 0.32 ± 0.04; < 0.001). Estimates of Pearson correlation coefficients (using unadjusted values and residual values) of the different traits measured at 1 yr of age were large ( > 0.63; < 0.008) except for aggressiveness with nervousness, flightiness, or gregariousness, which did not differ from 0 ( > 0.1). Five SNP on BTA 1, 24, and 29 had suggestive associations (0.17 < [adjusted for FDR] < 0.24) with aggressiveness, nervousness, or flightiness at evaluation postweaning and 13 SNP on 11 chromosomes had suggestive associations (0.07 < [adjusted for FDR] < 0.24) with aggressiveness, nervousness, flightiness, or overall temperament score of steers at 1 yr of age. Genes close to these loci with roles in neural systems of various organisms included synaptotagmin 4 (BTA 24), FAT atypical cadhedrin 3 (BTA 29), tubulin tyrosine ligase-like 1 (BTA 5), spermatogenesis associated 17 (BTA 16), stanniocalcin 2 (BTA 20), and GABA receptor γ 3 (BTA 21).

Adjustment of regional regression equations for urban storm-runoff quality using at-site data

USGS Publications Warehouse

Barks, C.S.

1996-01-01

Regional regression equations have been developed to estimate urban storm-runoff loads and mean concentrations using a national data base. Four statistical methods using at-site data to adjust the regional equation predictions were developed to provide better local estimates. The four adjustment procedures are a single-factor adjustment, a regression of the observed data against the predicted values, a regression of the observed values against the predicted values and additional local independent variables, and a weighted combination of a local regression with the regional prediction. Data collected at five representative storm-runoff sites during 22 storms in Little Rock, Arkansas, were used to verify, and, when appropriate, adjust the regional regression equation predictions. Comparison of observed values of stormrunoff loads and mean concentrations to the predicted values from the regional regression equations for nine constituents (chemical oxygen demand, suspended solids, total nitrogen as N, total ammonia plus organic nitrogen as N, total phosphorus as P, dissolved phosphorus as P, total recoverable copper, total recoverable lead, and total recoverable zinc) showed large prediction errors ranging from 63 percent to more than several thousand percent. Prediction errors for 6 of the 18 regional regression equations were less than 100 percent and could be considered reasonable for water-quality prediction equations. The regression adjustment procedure was used to adjust five of the regional equation predictions to improve the predictive accuracy. For seven of the regional equations the observed and the predicted values are not significantly correlated. Thus neither the unadjusted regional equations nor any of the adjustments were appropriate. The mean of the observed values was used as a simple estimator when the regional equation predictions and adjusted predictions were not appropriate.

Impact of baseline systolic blood pressure on visit-to-visit blood pressure variability: the Kailuan study.

PubMed

Wang, Anxin; Li, Zhifang; Yang, Yuling; Chen, Guojuan; Wang, Chunxue; Wu, Yuntao; Ruan, Chunyu; Liu, Yan; Wang, Yilong; Wu, Shouling

2016-01-01

To investigate the relationship between baseline systolic blood pressure (SBP) and visit-to-visit blood pressure variability in a general population. This is a prospective longitudinal cohort study on cardiovascular risk factors and cardiovascular or cerebrovascular events. Study participants attended a face-to-face interview every 2 years. Blood pressure variability was defined using the standard deviation and coefficient of variation of all SBP values at baseline and follow-up visits. The coefficient of variation is the ratio of the standard deviation to the mean SBP. We used multivariate linear regression models to test the relationships between SBP and standard deviation, and between SBP and coefficient of variation. Approximately 43,360 participants (mean age: 48.2±11.5 years) were selected. In multivariate analysis, after adjustment for potential confounders, baseline SBPs <120 mmHg were inversely related to standard deviation (P<0.001) and coefficient of variation (P<0.001). In contrast, baseline SBPs ≥140 mmHg were significantly positively associated with standard deviation (P<0.001) and coefficient of variation (P<0.001). Baseline SBPs of 120-140 mmHg were associated with the lowest standard deviation and coefficient of variation. The associations between baseline SBP and standard deviation, and between SBP and coefficient of variation during follow-ups showed a U curve. Both lower and higher baseline SBPs were associated with increased blood pressure variability. To control blood pressure variability, a good target SBP range for a general population might be 120-139 mmHg.

Partial F-tests with multiply imputed data in the linear regression framework via coefficient of determination.

PubMed

Chaurasia, Ashok; Harel, Ofer

2015-02-10

Tests for regression coefficients such as global, local, and partial F-tests are common in applied research. In the framework of multiple imputation, there are several papers addressing tests for regression coefficients. However, for simultaneous hypothesis testing, the existing methods are computationally intensive because they involve calculation with vectors and (inversion of) matrices. In this paper, we propose a simple method based on the scalar entity, coefficient of determination, to perform (global, local, and partial) F-tests with multiply imputed data. The proposed method is evaluated using simulated data and applied to suicide prevention data. Copyright © 2014 John Wiley & Sons, Ltd.

Lower verbal intelligence is associated with diabetic complications and slower walking speed in people with Type 2 diabetes: the Maastricht Study.

PubMed

Spauwen, P J J; Martens, R J H; Stehouwer, C D A; Verhey, F R J; Schram, M T; Sep, S J S; van der Kallen, C J H; Dagnelie, P C; Henry, R M A; Schaper, N C; van Boxtel, M P J

2016-12-01

To determine the association of verbal intelligence, a core constituent of health literacy, with diabetic complications and walking speed in people with Type 2 diabetes. This study was performed in 228 people with Type 2 diabetes participating in the Maastricht Study, a population-based cohort study. We examined the cross-sectional associations of score on the vocabulary test of the Groningen Intelligence Test with: 1) determinants of diabetic complications (HbA 1c , blood pressure and lipid level); 2) diabetic complications: chronic kidney disease, neuropathic pain, self-reported history of cardiovascular disease and carotid intima-media thickness; and 3) walking speed. Analyses were performed using linear regression and adjusted in separate models for potential confounders and mediators. Significant age- and sex-adjusted associations were additionally adjusted for educational level in a separate model. After full adjustment, lower verbal intelligence was associated with the presence of neuropathic pain [odds ratio (OR) 1.18, 95% CI 1.02;1.36], cardiovascular disease (OR 1.14, 95% CI 1.01;1.30), and slower walking speed (regression coefficient -0.011 m/s, 95% CI -0.021; -0.002 m/s). These associations were largely explained by education. Verbal intelligence was not associated with blood pressure, glycaemic control, lipid control, chronic kidney disease or carotid intima-media thickness. Lower verbal intelligence was associated with the presence of some diabetic complications and with a slower walking speed, a measure of physical functioning. Educational level largely explained these associations. This implies that clinicians should be aware of the educational level of people with diabetes and should provide information at a level of complexity tailored to the patient. © 2016 Diabetes UK.

Application of the environmental Gini coefficient in allocating water governance responsibilities: a case study in Taihu Lake Basin, China.

PubMed

Zhou, Shenbei; Du, Amin; Bai, Minghao

2015-01-01

The equitable allocation of water governance responsibilities is very important yet difficult to achieve, particularly for a basin which involves many stakeholders and policymakers. In this study, the environmental Gini coefficient model was applied to evaluate the inequality of water governance responsibility allocation, and an environmental Gini coefficient optimisation model was built to achieve an optimal adjustment. To illustrate the application of the environmental Gini coefficient, the heavily polluted transboundary Taihu Lake Basin in China, was chosen as a case study. The results show that the original environmental Gini coefficient of the chemical oxygen demand (COD) was greater than 0.2, indicating that the allocation of water governance responsibilities in Taihu Lake Basin was unequal. Of seven decision-making units, three were found to be inequality factors and were adjusted to reduce the water pollutant emissions and to increase the water governance inputs. After the adjustment, the environmental Gini coefficient of the COD was less than 0.2 and the reduction rate was 27.63%. The adjustment process provides clear guidance for policymakers to develop appropriate policies and improve the equality of water governance responsibility allocation.

Practical Guidance for Conducting Mediation Analysis With Multiple Mediators Using Inverse Odds Ratio Weighting

PubMed Central

Nguyen, Quynh C.; Osypuk, Theresa L.; Schmidt, Nicole M.; Glymour, M. Maria; Tchetgen Tchetgen, Eric J.

2015-01-01

Despite the recent flourishing of mediation analysis techniques, many modern approaches are difficult to implement or applicable to only a restricted range of regression models. This report provides practical guidance for implementing a new technique utilizing inverse odds ratio weighting (IORW) to estimate natural direct and indirect effects for mediation analyses. IORW takes advantage of the odds ratio's invariance property and condenses information on the odds ratio for the relationship between the exposure (treatment) and multiple mediators, conditional on covariates, by regressing exposure on mediators and covariates. The inverse of the covariate-adjusted exposure-mediator odds ratio association is used to weight the primary analytical regression of the outcome on treatment. The treatment coefficient in such a weighted regression estimates the natural direct effect of treatment on the outcome, and indirect effects are identified by subtracting direct effects from total effects. Weighting renders treatment and mediators independent, thereby deactivating indirect pathways of the mediators. This new mediation technique accommodates multiple discrete or continuous mediators. IORW is easily implemented and is appropriate for any standard regression model, including quantile regression and survival analysis. An empirical example is given using data from the Moving to Opportunity (1994–2002) experiment, testing whether neighborhood context mediated the effects of a housing voucher program on obesity. Relevant Stata code (StataCorp LP, College Station, Texas) is provided. PMID:25693776

Threshold regression to accommodate a censored covariate.

PubMed

Qian, Jing; Chiou, Sy Han; Maye, Jacqueline E; Atem, Folefac; Johnson, Keith A; Betensky, Rebecca A

2018-06-22

In several common study designs, regression modeling is complicated by the presence of censored covariates. Examples of such covariates include maternal age of onset of dementia that may be right censored in an Alzheimer's amyloid imaging study of healthy subjects, metabolite measurements that are subject to limit of detection censoring in a case-control study of cardiovascular disease, and progressive biomarkers whose baseline values are of interest, but are measured post-baseline in longitudinal neuropsychological studies of Alzheimer's disease. We propose threshold regression approaches for linear regression models with a covariate that is subject to random censoring. Threshold regression methods allow for immediate testing of the significance of the effect of a censored covariate. In addition, they provide for unbiased estimation of the regression coefficient of the censored covariate. We derive the asymptotic properties of the resulting estimators under mild regularity conditions. Simulations demonstrate that the proposed estimators have good finite-sample performance, and often offer improved efficiency over existing methods. We also derive a principled method for selection of the threshold. We illustrate the approach in application to an Alzheimer's disease study that investigated brain amyloid levels in older individuals, as measured through positron emission tomography scans, as a function of maternal age of dementia onset, with adjustment for other covariates. We have developed an R package, censCov, for implementation of our method, available at CRAN. © 2018, The International Biometric Society.

Examining geological controls on baseflow index (BFI) using regression analysis: An illustration from the Thames Basin, UK

NASA Astrophysics Data System (ADS)

Bloomfield, J. P.; Allen, D. J.; Griffiths, K. J.

2009-06-01

SummaryLinear regression methods can be used to quantify geological controls on baseflow index (BFI). This is illustrated using an example from the Thames Basin, UK. Two approaches have been adopted. The areal extents of geological classes based on lithostratigraphic and hydrogeological classification schemes have been correlated with BFI for 44 'natural' catchments from the Thames Basin. When regression models are built using lithostratigraphic classes that include a constant term then the model is shown to have some physical meaning and the relative influence of the different geological classes on BFI can be quantified. For example, the regression constants for two such models, 0.64 and 0.69, are consistent with the mean observed BFI (0.65) for the Thames Basin, and the signs and relative magnitudes of the regression coefficients for each of the lithostratigraphic classes are consistent with the hydrogeology of the Basin. In addition, regression coefficients for the lithostratigraphic classes scale linearly with estimates of log 10 hydraulic conductivity for each lithological class. When a regression is built using a hydrogeological classification scheme with no constant term, the model does not have any physical meaning, but it has a relatively high adjusted R2 value and because of the continuous coverage of the hydrogeological classification scheme, the model can be used for predictive purposes. A model calibrated on the 44 'natural' catchments and using four hydrogeological classes (low-permeability surficial deposits, consolidated aquitards, fractured aquifers and intergranular aquifers) is shown to perform as well as a model based on a hydrology of soil types (BFIHOST) scheme in predicting BFI in the Thames Basin. Validation of this model using 110 other 'variably impacted' catchments in the Basin shows that there is a correlation between modelled and observed BFI. Where the observed BFI is significantly higher than modelled BFI the deviations can be explained by an exogenous factor, catchment urban area. It is inferred that this is may be due influences from sewage discharge, mains leakage, and leakage from septic tanks.

Relationship between parent–infant attachment and parental satisfaction with supportive nursing care

PubMed Central

Ghadery-Sefat, Akram; Abdeyazdan, Zahra; Badiee, Zohreh; Zargham-Boroujeni, Ali

2016-01-01

Background: Parent–infant attachment is an important factor in accepting parenting role, accelerating infant survival, and adjusting to the environment outside the uterus. Since family supportive interventions can strengthen the parent–infant caring relationship, this study sought to investigate the relationship between mother–infant attachment and satisfaction of the mothers with the supportive nursing care received in the neonatal intensive care unit (NICU). Materials and Methods: In this descriptive–correlational study, 210 mothers with premature infants who were hospitalized in the NICUs affiliated to Isfahan Medical University hospitals took part. The data were collected via Maternal Postnatal Attachment Scale and researcher's self-tailored questionnaire based on Nurse Parent Support Tool. Pearson correlation coefficient and multiple linear regressions were used to analyze the collected data. Results: The results showed that the overall score of mother–infant attachment and the overall score of maternal satisfaction correlated with a correlation coefficient of r = 0.195. Also, the overall score of mother–infant attachment and mothers’ satisfaction scores in the emotional, communicative-informative, and self-confidence domains correlated with correlation coefficients of r = 0.182, r = 0.0.189, and r = 0.0.304, respectively. The results of multiple regression analysis revealed that about 15% of changes in the dependent variable (mother–infant attachment) could be explained by different dimensions of mothers’ satisfaction. Conclusions: The results of the study showed that mother–infant attachment improved by increasing mothers’ satisfaction of supportive nursing care. Therefore, it seems necessary to increase maternal satisfaction through given nursing care support, in order to promote mother–infant attachment. PMID:26985225

Relationship between parent-infant attachment and parental satisfaction with supportive nursing care.

PubMed

Ghadery-Sefat, Akram; Abdeyazdan, Zahra; Badiee, Zohreh; Zargham-Boroujeni, Ali

2016-01-01

Parent-infant attachment is an important factor in accepting parenting role, accelerating infant survival, and adjusting to the environment outside the uterus. Since family supportive interventions can strengthen the parent-infant caring relationship, this study sought to investigate the relationship between mother-infant attachment and satisfaction of the mothers with the supportive nursing care received in the neonatal intensive care unit (NICU). In this descriptive-correlational study, 210 mothers with premature infants who were hospitalized in the NICUs affiliated to Isfahan Medical University hospitals took part. The data were collected via Maternal Postnatal Attachment Scale and researcher's self-tailored questionnaire based on Nurse Parent Support Tool. Pearson correlation coefficient and multiple linear regressions were used to analyze the collected data. The results showed that the overall score of mother-infant attachment and the overall score of maternal satisfaction correlated with a correlation coefficient of r = 0.195. Also, the overall score of mother-infant attachment and mothers' satisfaction scores in the emotional, communicative-informative, and self-confidence domains correlated with correlation coefficients of r = 0.182, r = 0.0.189, and r = 0.0.304, respectively. The results of multiple regression analysis revealed that about 15% of changes in the dependent variable (mother-infant attachment) could be explained by different dimensions of mothers' satisfaction. The results of the study showed that mother-infant attachment improved by increasing mothers' satisfaction of supportive nursing care. Therefore, it seems necessary to increase maternal satisfaction through given nursing care support, in order to promote mother-infant attachment.

Identification of confounders in the assessment of the relationship between lead exposure and child development.

PubMed

Tong, I S; Lu, Y

2001-01-01

To explore the best approach to identify and adjust for confounders in epidemiologic practice. In the Port Pirie cohort study, the selection of covariates was based on both a priori and an empirical consideration. In an assessment of the relationship between exposure to environmental lead and child development, change-in-estimate (CE) and significance testing (ST) criteria were compared in identifying potential confounders. The Pearson correlation coefficients were used to evaluate the potential for collinearity between pairs of major quantitative covariates. In multivariate analyses, the effects of confounding factors were assessed with multiple linear regression models. The nature and number of covariates selected varied with different confounder selection criteria and different cutoffs. Four covariates (i.e., quality of home environment, socioeconomic status (SES), maternal intelligence, and parental smoking behaviour) met the conventional CE criterion (> or =10%), whereas 14 variables met the ST criterion (p < or = 0.25). However, the magnitude of the relationship between blood lead concentration and children's IQ differed slightly after adjustment for confounding, using either the CE (partial regression coefficient: -4.4; 95% confidence interval (CI): -0.5 to -8.3) or ST criterion (-4.3; 95% CI: -0.2 to -8.4). Identification and selection of confounding factors need to be viewed cautiously in epidemiologic studies. Either the CE (e.g., > or = 10%) or ST (e.g., p < or = 0.25) criterion may be implemented in identification of a potential confounder if a study sample is sufficiently large, and both the methods are subject to arbitrariness of selecting a cut-off point. In this study, the CE criterion (i.e., > or = 10%) appears to be more stringent than the ST method (i.e., p < or = 0.25) in the identification of confounders. However, the ST rule cannot be used to determine the trueness of confounding because it cannot reflect the causal relationship between the confounder and outcome. This study shows the complexities one can expect to encounter in the identification of and adjustment for confounders.

Carotid arterial remodeling: a maladaptive phenomenon in type 2 diabetes but not in impaired glucose metabolism: the Hoorn study.

PubMed

Henry, Ronald M A; Kostense, Piet J; Dekker, Jacqueline M; Nijpels, Giel; Heine, Robert J; Kamp, Otto; Bouter, Lex M; Stehouwer, Coen D A

2004-03-01

Deteriorating glucose tolerance is associated with an increased cardiovascular disease (CVD) risk. The underlying mechanisms remain unclear. Arterial remodeling is the change in structural properties through time in response to atherogenic and/or hemodynamic alterations and aims to maintain circumferential wall stress constant (sigma(C)). Arterial remodeling has not been studied in relation to glucose tolerance. The study population consisted of 278 people with normal glucose metabolism, 168 with impaired glucose metabolism, and 301 with type 2 diabetes (DM-2); their mean age was 67.8 years. We assessed carotid intima-media thickness (IMT), interadventitial diameter (IAD), lumen diameter (LD), and sigma(C). After adjustment for age, sex, height, body mass index, and prior CVD, DM-2 was associated with increased IAD, IMT, and sigma(C) but not LD (regression coefficients: 0.24 mm; 95% confidence interval [CI], 0.07 to 0.41; 0.050 mm; 95% CI, 0.024 to 0.077; 5.00 kPa; 95% CI, 0.92 to 9.08; and 0.13 mm; 95% CI, -0.03 to 0.29, respectively). After additional adjustment for pulse pressure, the association between DM-2 and IAD disappeared, whereas the association with IMT remained. After adjustment, impaired glucose metabolism was not significantly associated with LD (0.12 mm; 95% CI, -0.06 to 0.33), sigma(C) (0.25 kPa; 95% CI, -4.49 to 4.98), IAD (0.08 mm; 95% CI, -0.11 to 0.27), or IMT (0.029 mm; 95% CI, -0.002 to 0.060). However, the IMT regression coefficient was half that of DM-2. DM-2 is associated with preserved LD at increased IMT, which, however, does not normalize the increased sigma(C). In contrast, impaired glucose metabolism is not associated with changes in LD or IAD, whereas IMT is moderately increased but sigma(C) remains constant. Carotid remodeling in DM-2 thus appears maladaptive, which may explain the increased CVD risk, especially stroke, in DM-2.

[Culture and quality of life assessment in Chinese populations].

PubMed

Xia, Ping; Li, Ning-Xiu; Liu, Chao-Jie; Lü, Yu-Bo; Zhang, Qiang; Ou, Ai-Hua

2010-07-01

To investigate the impact of cultural factors on quality of life (QOL) and to identify appropriate ways of dividing sub-populations for population norm-based quality of life assessment. The WHOQOL-BREF was used as a QOL instrument. Another questionnaire was developed to assess cultural values. A cross-sectional survey was undertaken in 1090 Guangzhou residents, which included 635 respondents from communities and 455 patients who visited outpatient departments of hospitals. Cronbach's a coefficients and item-domain correlation coefficients were calculated to test the reliability and validity of the WHOQOL-BREF, respectively. Student t test, ANOVA and stepwise multiple linear regression analysis were performed to identify the variables that might have an impact on the QOL. Two regression models with and without including cultural variables were constructed, and the extent of impact exerted by the cultural factors was assessed through a comparison of the change of adjusted R square values. A total of 1052 (96%) valid questionnaire were returned. The Cronbach's alpha coefficients of the WHOQOL-BREF ranged from 0.67 to 0.78. Age, education, occupation and family income were correlated with all of the domains of the WHOQOL-BREF. Chronic condition was correlated with physical, psychological, and social relationship domains of the WHOQOL-BREF. Gender was correlated with physical and psychological domains of the WHOQOL-BREF. The multiple regression analysis showed that social and demographic factors contributed to 6.3%, 13.6%, 10.4% and 8.7% of the predicted variances for the physical, psychological, social relationship, and environment domains, respectively. Social support, horizontal collectivism, vertical individualism, escape acceptance, fear of death, health value, supernatural belief had a significant impact on QOL. However, social support was the only one factor that had an impact on all of the four QOL domains. It is necessary to divide sub-cultural populations for population norm-based QOL assessment. Further research is needed to develop a practical approach to the sub-cultural population division.

Associations between active commuting and physical and mental wellbeing.

PubMed

Humphreys, David K; Goodman, Anna; Ogilvie, David

2013-08-01

To examine whether a relationship exists between active commuting and physical and mental wellbeing. In 2009, cross-sectional postal questionnaire data were collected from a sample of working adults (aged 16 and over) in the Commuting and Health in Cambridge study. Travel behaviour and physical activity were ascertained using the Recent Physical Activity Questionnaire (RPAQ) and a seven-day travel-to-work recall instrument from which weekly time spent in active commuting (walking and cycling) was derived. Physical and mental wellbeing were assessed using the Medical Outcomes Study Short Form survey (SF-8). Associations were tested using multivariable linear regression. An association was observed between physical wellbeing (PCS-8) score and time spent in active commuting after adjustment for other physical activity (adjusted regression coefficients 0.48, 0.79 and 1.21 for 30-149 min/week, 150-224 min/week and ≥ 225 min/week respectively versus < 30 min/week, p=0.01 for trend; n=989). No such relationship was found for mental wellbeing (MCS-8) (p=0.52). Greater time spent actively commuting is associated with higher levels of physical wellbeing. Longitudinal studies should examine the contribution of changing levels of active commuting and other forms of physical activity to overall health and wellbeing. Copyright © 2013 Elsevier Inc. All rights reserved.

Association of serum uric acid with high-sensitivity C-reactive protein in postmenopausal women.

PubMed

Raeisi, A; Ostovar, A; Vahdat, K; Rezaei, P; Darabi, H; Moshtaghi, D; Nabipour, I

2017-02-01

To explore the independent correlation between serum uric acid and low-grade inflammation (measured by high-sensitivity C-reactive protein, hs-CRP) in postmenopausal women. A total of 378 healthy Iranian postmenopausal women were randomly selected in a population-based study. Circulating hs-CRP levels were measured by highly specific enzyme-linked immunosorbent assay method and an enzymatic calorimetric method was used to measure serum levels of uric acid. Pearson correlation coefficient, multiple linear regression and logistic regression models were used to analyze the association between uric acid and hs-CRP levels. A statistically significant correlation was seen between serum levels of uric acid and log-transformed circulating hs-CRP (r = 0.25, p < 0.001). After adjustment for age and cardiovascular risk factors (according to NCEP ATP III criteria), circulating hs-CRP levels were significantly associated with serum uric acid levels (β = 0.20, p < 0.001). After adjustment for age and cardiovascular risk factors, hs-CRP levels ≥3 mg/l were significantly associated with higher uric acid levels (odds ratio =1.52, 95% confidence interval 1.18-1.96). Higher serum uric acid levels were positively and independently associated with circulating hs-CRP in healthy postmenopausal women.

Discrimination of orange beverage emulsions with different formulations using multivariate analysis.

PubMed

Mirhosseini, Hamed; Tan, Chin Ping

2010-06-01

The constituents in a food emulsion interact with each other, either physically or chemically, determining the overall physico-chemical and organoleptic properties of the final product. Thus, the main objective of present study was to investigate the effect of emulsion components on beverage emulsion properties. In most cases, the second-order polynomial regression models with no significant (P > 0.05) lack of fit and high adjusted coefficient of determination (adjusted R(2), 0.851-0.996) were significantly fitted to explain the beverage emulsion properties as function of main emulsion components. The main effect of gum arabic was found to be significant (P < 0.05) in all response regression models. Orange beverage emulsion containing 222.0 g kg(-1) gum arabic, 2.4 g kg(-1) xanthan gum and 152.7 g kg(-1) orange oil was predicted to provide the desirable emulsion properties. The present study suggests that the concentration of gum arabic should be considered as a primary critical factor for the formulation of orange beverage emulsion. This study also indicated that the interaction effect between xanthan gum and orange oil showed the most significant (P < 0.05) effect among all interaction effects influencing all the physicochemical properties except for density. Copyright (c) 2010 Society of Chemical Industry.

Do effects of common case-mix adjusters on patient experiences vary across patient groups?

PubMed

de Boer, Dolf; van der Hoek, Lucas; Rademakers, Jany; Delnoij, Diana; van den Berg, Michael

2017-11-22

Many survey studies in health care adjust for demographic characteristics such as age, gender, educational attainment and general health when performing statistical analyses. Whether the effects of these demographic characteristics are consistent between patient groups remains to be determined. This is important as the rationale for adjustment is often that demographic sub-groups differ in their so-called 'response tendency'. This rationale may be less convincing if the effects of response tendencies vary across patient groups. The present paper examines whether the impact of these characteristics on patients' global rating of care varies across patient groups. Secondary analyses using multi-level regression models were performed on a dataset including 32 different patient groups and 145,578 observations. For each demographic variable, the 95% expected range of case-mix coefficients across patient groups is presented. In addition, we report whether the variance of coefficients for demographic variables across patient groups is significant. Overall, men, elderly, lower educated people and people in good health tend to give higher global ratings. However, these effects varied significantly across patient groups and included the possibility of no effect or an opposite effect in some patient groups. The response tendency attributed to demographic characteristics - such as older respondents being milder, or higher educated respondents being more critical - is not general or universal. As such, the mechanism linking demographic characteristics to survey results on patient experiences with quality of care is more complicated than a general response tendency. It is possible that the response tendency interacts with patient group, but it is also possible that other mechanisms are at play.

Comparing Regression Coefficients between Nested Linear Models for Clustered Data with Generalized Estimating Equations

ERIC Educational Resources Information Center

Yan, Jun; Aseltine, Robert H., Jr.; Harel, Ofer

2013-01-01

Comparing regression coefficients between models when one model is nested within another is of great practical interest when two explanations of a given phenomenon are specified as linear models. The statistical problem is whether the coefficients associated with a given set of covariates change significantly when other covariates are added into…

On approaches to analyze the sensitivity of simulated hydrologic fluxes to model parameters in the community land model

DOE PAGES

Bao, Jie; Hou, Zhangshuan; Huang, Maoyi; ...

2015-12-04

Here, effective sensitivity analysis approaches are needed to identify important parameters or factors and their uncertainties in complex Earth system models composed of multi-phase multi-component phenomena and multiple biogeophysical-biogeochemical processes. In this study, the impacts of 10 hydrologic parameters in the Community Land Model on simulations of runoff and latent heat flux are evaluated using data from a watershed. Different metrics, including residual statistics, the Nash-Sutcliffe coefficient, and log mean square error, are used as alternative measures of the deviations between the simulated and field observed values. Four sensitivity analysis (SA) approaches, including analysis of variance based on the generalizedmore » linear model, generalized cross validation based on the multivariate adaptive regression splines model, standardized regression coefficients based on a linear regression model, and analysis of variance based on support vector machine, are investigated. Results suggest that these approaches show consistent measurement of the impacts of major hydrologic parameters on response variables, but with differences in the relative contributions, particularly for the secondary parameters. The convergence behaviors of the SA with respect to the number of sampling points are also examined with different combinations of input parameter sets and output response variables and their alternative metrics. This study helps identify the optimal SA approach, provides guidance for the calibration of the Community Land Model parameters to improve the model simulations of land surface fluxes, and approximates the magnitudes to be adjusted in the parameter values during parametric model optimization.« less

Correlation of Vitamin D status and orthodontic-induced external apical root resorption.

PubMed

Tehranchi, Azita; Sadighnia, Azin; Younessian, Farnaz; Abdi, Amir H; Shirvani, Armin

2017-01-01

Adequate Vitamin D is essential for dental and skeletal health in children and adult. The purpose of this study was to assess the correlation of serum Vitamin D level with external-induced apical root resorption (EARR) following fixed orthodontic treatment. In this cross-sectional study, the prevalence of Vitamin D deficiency (defined by25-hydroxyvitamin-D) was determined in 34 patients (23.5% male; age range 12-23 years; mean age 16.63 ± 2.84) treated with fixed orthodontic treatment. Root resorption of four maxillary incisors was measured using before and after periapical radiographs (136 measured teeth) by means of a design-to-purpose software to optimize data collection. Teeth with a maximum percentage of root resorption (%EARR) were indicated as representative root resorption for each patient. A multiple linear regression model and Pearson correlation coefficient were used to assess the association of Vitamin D status and observed EARR. P < 0.05 was considered statistically significant. The Pearson coefficient between these two variables was determined about 0.15 ( P = 0.38). Regression analysis revealed that Vitamin D status of the patients demonstrated no significant statistical correlation with EARR, after adjustment of confounding variables using linear regression model ( P > 0.05). This study suggests that Vitamin D level is not among the clinical variables that are potential contributors for EARR. The prevalence of Vitamin D deficiency does not differ in patients with higher EARR. These data suggest the possibility that Vitamin D insufficiency may not contribute to the development of more apical root resorption although this remains to be confirmed by further longitudinal cohort studies.

Tools to Support Interpreting Multiple Regression in the Face of Multicollinearity

PubMed Central

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K.

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses. PMID:22457655

Tools to support interpreting multiple regression in the face of multicollinearity.

PubMed

Kraha, Amanda; Turner, Heather; Nimon, Kim; Zientek, Linda Reichwein; Henson, Robin K

2012-01-01

While multicollinearity may increase the difficulty of interpreting multiple regression (MR) results, it should not cause undue problems for the knowledgeable researcher. In the current paper, we argue that rather than using one technique to investigate regression results, researchers should consider multiple indices to understand the contributions that predictors make not only to a regression model, but to each other as well. Some of the techniques to interpret MR effects include, but are not limited to, correlation coefficients, beta weights, structure coefficients, all possible subsets regression, commonality coefficients, dominance weights, and relative importance weights. This article will review a set of techniques to interpret MR effects, identify the elements of the data on which the methods focus, and identify statistical software to support such analyses.

Meta-analytical synthesis of regression coefficients under different categorization scheme of continuous covariates.

PubMed

Yoneoka, Daisuke; Henmi, Masayuki

2017-11-30

Recently, the number of clinical prediction models sharing the same regression task has increased in the medical literature. However, evidence synthesis methodologies that use the results of these regression models have not been sufficiently studied, particularly in meta-analysis settings where only regression coefficients are available. One of the difficulties lies in the differences between the categorization schemes of continuous covariates across different studies. In general, categorization methods using cutoff values are study specific across available models, even if they focus on the same covariates of interest. Differences in the categorization of covariates could lead to serious bias in the estimated regression coefficients and thus in subsequent syntheses. To tackle this issue, we developed synthesis methods for linear regression models with different categorization schemes of covariates. A 2-step approach to aggregate the regression coefficient estimates is proposed. The first step is to estimate the joint distribution of covariates by introducing a latent sampling distribution, which uses one set of individual participant data to estimate the marginal distribution of covariates with categorization. The second step is to use a nonlinear mixed-effects model with correction terms for the bias due to categorization to estimate the overall regression coefficients. Especially in terms of precision, numerical simulations show that our approach outperforms conventional methods, which only use studies with common covariates or ignore the differences between categorization schemes. The method developed in this study is also applied to a series of WHO epidemiologic studies on white blood cell counts. Copyright © 2017 John Wiley & Sons, Ltd.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Weaver, Virginia M., E-mail: vweaver@jhsph.edu; Johns Hopkins University School of Medicine, Baltimore, MD; Welch Center for Prevention, Epidemiology, and Clinical Research, Johns Hopkins Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD

Positive associations between urine toxicant levels and measures of glomerular filtration rate (GFR) have been reported recently in a range of populations. The explanation for these associations, in a direction opposite that of traditional nephrotoxicity, is uncertain. Variation in associations by urine concentration adjustment approach has also been observed. Associations of urine cadmium, thallium and uranium in models of serum creatinine- and cystatin-C-based estimated GFR (eGFR) were examined using multiple linear regression in a cross-sectional study of adolescents residing near a lead smelter complex. Urine concentration adjustment approaches compared included urine creatinine, urine osmolality and no adjustment. Median age, bloodmore » lead and urine cadmium, thallium and uranium were 13.9 years, 4.0 μg/dL, 0.22, 0.27 and 0.04 g/g creatinine, respectively, in 512 adolescents. Urine cadmium and thallium were positively associated with serum creatinine-based eGFR only when urine creatinine was used to adjust for urine concentration (β coefficient=3.1 mL/min/1.73 m{sup 2}; 95% confidence interval=1.4, 4.8 per each doubling of urine cadmium). Weaker positive associations, also only with urine creatinine adjustment, were observed between these metals and serum cystatin-C-based eGFR and between urine uranium and serum creatinine-based eGFR. Additional research using non-creatinine-based methods of adjustment for urine concentration is necessary. - Highlights: • Positive associations between urine metals and creatinine-based eGFR are unexpected. • Optimal approach to urine concentration adjustment for urine biomarkers uncertain. • We compared urine concentration adjustment methods. • Positive associations observed only with urine creatinine adjustment. • Additional research using non-creatinine-based methods of adjustment needed.« less

[Development of an automatic pneumatic tourniquet system that determines pressures in synchrony with systolic blood pressure].

PubMed

Liu, Hongyun; Li, Kaiyuan; Zhang, Zhengbo; Guo, Junyan; Wang, Weidong

2012-11-01

The correlation coefficients between arterial occlusion pressure and systolic blood pressure, diastolic blood pressure, limb circumference, body mass etc were obtained through healthy volunteer experiments, in which tourniquet were applied on upper/lower extremities. The prediction equations were derived from the data of experiments by multiple regression analysis. Based on the microprocessor C8051F340, a new pneumatic tourniquet system that can determine tourniquet pressure in synchrony with systolic blood pressure was developed and verified the function and stability of designed system. Results showed that the pneumatic tourniquet which automatically adjusts occlusion pressure in accordance with systolic blood pressure could stop the flow of blood to get a bloodless field.

Using the Coefficient of Determination "R"[superscript 2] to Test the Significance of Multiple Linear Regression

ERIC Educational Resources Information Center

Quinino, Roberto C.; Reis, Edna A.; Bessegato, Lupercio F.

2013-01-01

This article proposes the use of the coefficient of determination as a statistic for hypothesis testing in multiple linear regression based on distributions acquired by beta sampling. (Contains 3 figures.)

SPSS macros to compare any two fitted values from a regression model.

PubMed

Weaver, Bruce; Dubois, Sacha

2012-12-01

In regression models with first-order terms only, the coefficient for a given variable is typically interpreted as the change in the fitted value of Y for a one-unit increase in that variable, with all other variables held constant. Therefore, each regression coefficient represents the difference between two fitted values of Y. But the coefficients represent only a fraction of the possible fitted value comparisons that might be of interest to researchers. For many fitted value comparisons that are not captured by any of the regression coefficients, common statistical software packages do not provide the standard errors needed to compute confidence intervals or carry out statistical tests-particularly in more complex models that include interactions, polynomial terms, or regression splines. We describe two SPSS macros that implement a matrix algebra method for comparing any two fitted values from a regression model. The !OLScomp and !MLEcomp macros are for use with models fitted via ordinary least squares and maximum likelihood estimation, respectively. The output from the macros includes the standard error of the difference between the two fitted values, a 95% confidence interval for the difference, and a corresponding statistical test with its p-value.

Implementations of geographically weighted lasso in spatial data with multicollinearity (Case study: Poverty modeling of Java Island)

NASA Astrophysics Data System (ADS)

Setiyorini, Anis; Suprijadi, Jadi; Handoko, Budhi

2017-03-01

Geographically Weighted Regression (GWR) is a regression model that takes into account the spatial heterogeneity effect. In the application of the GWR, inference on regression coefficients is often of interest, as is estimation and prediction of the response variable. Empirical research and studies have demonstrated that local correlation between explanatory variables can lead to estimated regression coefficients in GWR that are strongly correlated, a condition named multicollinearity. It later results on a large standard error on estimated regression coefficients, and, hence, problematic for inference on relationships between variables. Geographically Weighted Lasso (GWL) is a method which capable to deal with spatial heterogeneity and local multicollinearity in spatial data sets. GWL is a further development of GWR method, which adds a LASSO (Least Absolute Shrinkage and Selection Operator) constraint in parameter estimation. In this study, GWL will be applied by using fixed exponential kernel weights matrix to establish a poverty modeling of Java Island, Indonesia. The results of applying the GWL to poverty datasets show that this method stabilizes regression coefficients in the presence of multicollinearity and produces lower prediction and estimation error of the response variable than GWR does.

An improved multiple linear regression and data analysis computer program package

NASA Technical Reports Server (NTRS)

Sidik, S. M.

1972-01-01

NEWRAP, an improved version of a previous multiple linear regression program called RAPIER, CREDUC, and CRSPLT, allows for a complete regression analysis including cross plots of the independent and dependent variables, correlation coefficients, regression coefficients, analysis of variance tables, t-statistics and their probability levels, rejection of independent variables, plots of residuals against the independent and dependent variables, and a canonical reduction of quadratic response functions useful in optimum seeking experimentation. A major improvement over RAPIER is that all regression calculations are done in double precision arithmetic.

Regression equations to estimate seasonal flow duration, n-day high-flow frequency, and n-day low-flow frequency at sites in North Dakota using data through water year 2009

USGS Publications Warehouse

Williams-Sether, Tara; Gross, Tara A.

2016-02-09

Seasonal mean daily flow data from 119 U.S. Geological Survey streamflow-gaging stations in North Dakota; the surrounding states of Montana, Minnesota, and South Dakota; and the Canadian provinces of Manitoba and Saskatchewan with 10 or more years of unregulated flow record were used to develop regression equations for flow duration, n-day high flow and n-day low flow using ordinary least-squares and Tobit regression techniques. Regression equations were developed for seasonal flow durations at the 10th, 25th, 50th, 75th, and 90th percent exceedances; the 1-, 7-, and 30-day seasonal mean high flows for the 10-, 25-, and 50-year recurrence intervals; and the 1-, 7-, and 30-day seasonal mean low flows for the 2-, 5-, and 10-year recurrence intervals. Basin and climatic characteristics determined to be significant explanatory variables in one or more regression equations included drainage area, percentage of basin drainage area that drains to isolated lakes and ponds, ruggedness number, stream length, basin compactness ratio, minimum basin elevation, precipitation, slope ratio, stream slope, and soil permeability. The adjusted coefficient of determination for the n-day high-flow regression equations ranged from 55.87 to 94.53 percent. The Chi2 values for the duration regression equations ranged from 13.49 to 117.94, whereas the Chi2 values for the n-day low-flow regression equations ranged from 4.20 to 49.68.

The effect of protein intake and resistance training on muscle mass in acutely ill old medical patients - A randomized controlled trial.

PubMed

Buhl, Sussi F; Andersen, Aino L; Andersen, Jens R; Andersen, Ove; Jensen, Jens-Erik B; Rasmussen, Anne Mette L; Pedersen, Mette M; Damkjær, Lars; Gilkes, Hanne; Petersen, Janne

2016-02-01

Stress metabolism is associated with accelerated loss of muscle that has large consequences for the old medical patient. The aim of this study was to investigate if an intervention combining protein and resistance training was more effective in counteracting loss of muscle than standard care. Secondary outcomes were changes in muscle strength, functional ability and body weight. 29 acutely admitted old (>65 years) patients were randomly assigned to the intervention (n = 14) or to standard care (n = 15). The Intervention Group received 1.7 g protein/kg/day during admission and a daily protein supplement (18.8 g protein) and resistance training 3 times per week the 12 weeks following discharge. Muscle mass was assessed by Dual-energy X-ray Absorptiometry. Muscle strength was assessed by Hand Grip Strength and Chair Stand Test. Functional ability was assessed by the de Morton Mobility Index, the Functional Recovery Score and the New Mobility Score. Changes in outcomes from time of admission to three-months after discharge were analysed by linear regression analysis. The intention-to-treat analysis showed no significant effect of the intervention on lean mass (unadjusted: β-coefficient = -1.28 P = 0.32, adjusted for gender: β-coefficient = -0.02 P = 0.99, adjusted for baseline lean mass: β-coefficient = -0.31 P = 0.80). The de Morton Mobility Index significantly increased in the Control Group (β-coefficient = -11.43 CI: 0.72-22.13, P = 0.04). No other differences were found. No significant effect on muscle mass was observed in this group of acutely ill old medical patients. High compliance was achieved with the dietary intervention, but resistance training was challenging. Clinical trials identifier NCT02077491. Copyright © 2015 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Glutathione Peroxidase Enzyme Activity in Aging

PubMed Central

Espinoza, Sara E.; Guo, Hongfei; Fedarko, Neal; DeZern, Amy; Fried, Linda P.; Xue, Qian-Li; Leng, Sean; Beamer, Brock; Walston, Jeremy D.

2010-01-01

Background It is hypothesized that free radical damage contributes to aging. Age-related decline in activity of the antioxidant enzyme glutathione peroxidase (GPx) may contribute to increased free radicals. We hypothesized that GPx activity decreases with age in a population of older women with disability. Methods Whole blood GPx activity was measured in baseline stored samples from participants in the Women's Health and Aging Study I, a cohort of disabled community-dwelling older women. Linear regression was used to determine cross-sectional associations between GPx activity and age, adjusting for hemoglobin, coronary disease, diabetes, selenium, and body mass index. Results Six hundred one participants had complete demographic, disease, and laboratory information. An inverse association was observed between GPx and age (regression coefficient = −2.9, p < .001), indicating that for each 1-year increase in age, GPx activity decreased by 2.9 μmol/min/L. This finding remained significant after adjustment for hemoglobin, coronary disease, diabetes, and selenium, but not after adjustment for body mass index and weight loss. Conclusion This is the first study to examine the association between age and GPx activity in an older adult cohort with disability and chronic disease. These findings suggest that, after age 65, GPx activity declines with age in older women with disability. This decline does not appear to be related to diseases that have been previously reported to alter GPx activity. Longitudinal examination of GPx activity and other antioxidant enzymes in diverse populations of older adults will provide additional insight into age- and disease-related changes in these systems. PMID:18511755

Maternal pre-pregnancy BMI and intelligence quotient (IQ) in 5-year-old children: a cohort based study.

PubMed

Bliddal, Mette; Olsen, Jørn; Støvring, Henrik; Eriksen, Hanne-Lise F; Kesmodel, Ulrik S; Sørensen, Thorkild I A; Nøhr, Ellen A

2014-01-01

An association between maternal pre-pregnancy BMI and childhood intelligence quotient (IQ) has repeatedly been found but it is unknown if this association is causal or due to confounding caused by genetic or social factors. We used a cohort of 1,783 mothers and their 5-year-old children sampled from the Danish National Birth Cohort. The children participated between 2003 and 2008 in a neuropsychological assessment of cognitive ability including IQ tests taken by both the mother and the child. Linear regression analyses were used to estimate the associations between parental BMI and child IQ adjusted for a comprehensive set of potential confounders. Child IQ was assessed with the Wechsler Primary and Preschool Scales of Intelligence--Revised (WPPSI-R). The crude association between maternal BMI and child IQ showed that BMI was adversely associated with child IQ with a reduction in IQ of -0.40 point for each one unit increase in BMI. This association was attenuated after adjustment for social factors and maternal IQ to a value of -0.27 (-0.50 to -0.03). After mutual adjustment for the father's BMI and all other factors except maternal IQ, the association between paternal BMI and child IQ yielded a regression coefficient of -0.26 (-0.59 to 0.07), which was comparable to that seen for maternal BMI (-0.20 (-0.44 to 0.04)). Although maternal pre-pregnancy BMI was inversely associated with the IQ of her child, the similar association with paternal BMI suggests that it is not a specific pregnancy related adiposity effect.

Neighborhood education inequality and drinking behavior.

PubMed

Lê, Félice; Ahern, Jennifer; Galea, Sandro

2010-11-01

The neighborhood distribution of education (education inequality) may influence substance use among neighborhood residents. Using data from the New York Social Environment Study (conducted in 2005; n=4000), we examined the associations of neighborhood education inequality (measured using Gini coefficients of education) with alcohol use prevalence and levels of alcohol consumption among alcohol users. Analyses were adjusted for neighborhood education level, income level and income inequality, as well as for individual demographic and socioeconomic characteristics and history of drinking prior to residence in the current neighborhood. Neighborhood social norms about drinking were examined as a possible mediator. In adjusted generalized estimating equation regression models, one-standard-deviation-higher education inequality was associated with 1.18 times higher odds of alcohol use (logistic regression odds ratio=1.18, 95% confidence interval 1.08-1.30) but 0.79 times lower average daily alcohol consumption among alcohol users (Poisson regression relative rate=0.79, 95% confidence interval 0.68-0.92). The results tended to differ in magnitude depending on respondents' individual educational levels. There was no evidence that these associations were mediated by social drinking norms, although norms did vary with education inequality. Our results provide further evidence of a relation between education inequality and drinking behavior while illustrating the importance of considering different drinking outcomes and heterogeneity between neighborhood subgroups. Future research could fruitfully consider other potential mechanisms, such as alcohol availability or the role of stress; research that considers multiple mechanisms and their combined effects may be most informative. Copyright © 2010 Elsevier Ireland Ltd. All rights reserved.

Placental three-dimensional power Doppler indices in mid-pregnancy and late pregnancy complicated by gestational diabetes mellitus.

PubMed

Surányi, A; Kozinszky, Z; Molnár, A; Nyári, T; Bitó, T; Pál, A

2013-10-01

The aim of our study was to evaluate placental three-dimensional power Doppler indices in diabetic pregnancies in the second and third trimesters and to compare them with those of the normal controls. Placental vascularization of pregnant women was determined by three-dimensional power Doppler ultrasound technique. The calculated indices included vascularization index (VI), flow index (FI), and vascularization flow index (VFI). Uncomplicated pregnancies (n = 113) were compared with pregnancies complicated by gestational diabetes mellitus (n = 56) and diabetes mellitus (n = 43). The three-dimensional power Doppler indices were not significantly different between the two diabetic subgroups. All the indices in diabetic patients were significantly reduced compared with those in non-diabetic individuals (p < 0.001). Placental three-dimensional power Doppler indices are slightly diminished throughout diabetic pregnancy [regression coefficients: -0.23 (FI), -0.06 (VI), and -0.04 (VFI)] and normal pregnancy [regression coefficients: -0.13 (FI), -0.20 (VI), and -0.11 (VFI)]. The uteroplacental circulation (umbilical and uterine artery) was not correlated significantly to the three-dimensional power Doppler indices. If all placental indices are low during late pregnancy, then the odds of the diabetes are significantly high (adjusted odds ratio: 1.10). A decreased placental vascularization could be an adjunct sonographic marker in the diagnosis of diabetic pregnancy in mid-gestation and late gestation. © 2013 John Wiley & Sons, Ltd.

100-point scale evaluating job satisfaction and the results of the 12-item General Health Questionnaire in occupational workers.

PubMed

Kawada, Tomoyuki; Yamada, Natsuki

2012-01-01

Job satisfaction is an important factor in the occupational lives of workers. In this study, the relationship between one-dimensional scale of job satisfaction and psychological wellbeing was evaluated. A total of 1,742 workers (1,191 men and 551 women) participated. 100-point scale evaluating job satisfaction (0 [extremely dissatisfied] to 100 [extremely satisfied]) and the General Health Questionnaire, 12-item version (GHQ-12) evaluating psychological wellbeing were used. A multiple regression analysis was then used, controlling for gender and age. The change in the GHQ-12 and job satisfaction scores after a two-year interval was also evaluated. The mean age for the subjects was 42.2 years for the men and 36.2 years for the women. The GHQ-12 and job satisfaction scores were significantly correlated in each generation. The partial correlation coefficients between the changes in the two variables, controlling for age, were -0.395 for men and -0.435 for women (p< 0.001). A multiple regression analysis revealed that the 100-point job satisfaction score was associated with the GHQ-12 results (p< 0.001). The adjusted multiple correlation coefficient was 0.275. The 100-point scale, which is a simple and easy tool for evaluating job satisfaction, was significantly associated with psychological wellbeing as judged using the GHQ-12.

Reliability and validity of the photogrammetry for scoliosis evaluation: a cross-sectional prospective study.

PubMed

Saad, Karen Ruggeri; Colombo, Alexandra S; João, Silvia M Amado

2009-01-01

The purpose of this study was to investigate the reliability and validity of photogrammetry in measuring the lateral spinal inclination angles. Forty subjects (32 female and 8 males) with a mean age of 23.4 +/- 11.2 years had their scoliosis evaluated by radiographs of their trunk, determined by the Cobb angle method, and by photogrammetry. The statistical methods used included Cronbach alpha, Pearson/Spearman correlation coefficients, and regression analyses. The Cronbach alpha values showed that the photogrammetric measures showed high internal consistency, which indicated that the sample was bias free. The radiograph method showed to be more precise with intrarater reliabilities of 0.936, 0.975, and 0.945 for the thoracic, lumbar, and thoracolumbar curves, respectively, and interrater reliabilities of 0.942 and 0.879 for the angular measures of the thoracic and thoracolumbar segments, respectively. The regression analyses revealed a high determination coefficient although limited to the adjusted linear model between the radiographic and photographic measures. It was found that with more severe scoliosis, the lateral curve measures obtained with the photogrammetry were for the thoracic and lumbar regions (R = 0.619 and 0.551). The photogrammetric measures were found to be reproducible in this study and could be used as supplementary information to decrease the number of radiographs necessary for the monitoring of scoliosis.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach.

PubMed

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate - adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research.

Association of Protein Translation and Extracellular Matrix Gene Sets with Breast Cancer Metastasis: Findings Uncovered on Analysis of Multiple Publicly Available Datasets Using Individual Patient Data Approach

PubMed Central

Chowdhury, Nilotpal; Sapru, Shantanu

2015-01-01

Introduction Microarray analysis has revolutionized the role of genomic prognostication in breast cancer. However, most studies are single series studies, and suffer from methodological problems. We sought to use a meta-analytic approach in combining multiple publicly available datasets, while correcting for batch effects, to reach a more robust oncogenomic analysis. Aim The aim of the present study was to find gene sets associated with distant metastasis free survival (DMFS) in systemically untreated, node-negative breast cancer patients, from publicly available genomic microarray datasets. Methods Four microarray series (having 742 patients) were selected after a systematic search and combined. Cox regression for each gene was done for the combined dataset (univariate, as well as multivariate – adjusted for expression of Cell cycle related genes) and for the 4 major molecular subtypes. The centre and microarray batch effects were adjusted by including them as random effects variables. The Cox regression coefficients for each analysis were then ranked and subjected to a Gene Set Enrichment Analysis (GSEA). Results Gene sets representing protein translation were independently negatively associated with metastasis in the Luminal A and Luminal B subtypes, but positively associated with metastasis in Basal tumors. Proteinaceous extracellular matrix (ECM) gene set expression was positively associated with metastasis, after adjustment for expression of cell cycle related genes on the combined dataset. Finally, the positive association of the proliferation-related genes with metastases was confirmed. Conclusion To the best of our knowledge, the results depicting mixed prognostic significance of protein translation in breast cancer subtypes are being reported for the first time. We attribute this to our study combining multiple series and performing a more robust meta-analytic Cox regression modeling on the combined dataset, thus discovering 'hidden' associations. This methodology seems to yield new and interesting results and may be used as a tool to guide new research. PMID:26080057

Risk-adjusted capitation funding models for chronic disease in Australia: alternatives to casemix funding.

PubMed

Antioch, K M; Walsh, M K

2002-01-01

Under Australian casemix funding arrangements that use Diagnosis-Related Groups (DRGs) the average price is policy based, not benchmarked. Cost weights are too low for State-wide chronic disease services. Risk-adjusted Capitation Funding Models (RACFM) are feasible alternatives. A RACFM was developed for public patients with cystic fibrosis treated by an Australian Health Maintenance Organization (AHMO). Adverse selection is of limited concern since patients pay solidarity contributions via Medicare levy with no premium contributions to the AHMO. Sponsors paying premium subsidies are the State of Victoria and the Federal Government. Cost per patient is the dependent variable in the multiple regression. Data on DRG 173 (cystic fibrosis) patients were assessed for heteroskedasticity, multicollinearity, structural stability and functional form. Stepwise linear regression excluded non-significant variables. Significant variables were 'emergency' (1276.9), 'outlier' (6377.1), 'complexity' (3043.5), 'procedures' (317.4) and the constant (4492.7) (R(2)=0.21, SE=3598.3, F=14.39, Prob<0.0001. Regression coefficients represent the additional per patient costs summed to the base payment (constant). The model explained 21% of the variance in cost per patient. The payment rate is adjusted by a best practice annual admission rate per patient. The model is a blended RACFM for in-patient, out-patient, Hospital In The Home, Fee-For-Service Federal payments for drugs and medical services; lump sum lung transplant payments and risk sharing through cost (loss) outlier payments. State and Federally funded home and palliative services are 'carved out'. The model, which has national application via Coordinated Care Trials and by Australian States for RACFMs may be instructive for Germany, which plans to use Australian DRGs for casemix funding. The capitation alternative for chronic disease can improve equity, allocative efficiency and distributional justice. The use of Diagnostic Cost Groups (DCGs) is a promising alternative classification system for capitation arrangements.

Seasonal variations in tuberculosis diagnosis among HIV-positive individuals in Southern Africa: analysis of cohort studies at antiretroviral treatment programmes

PubMed Central

Ballif, Marie; Zürcher, Kathrin; Reid, Stewart E; Boulle, Andrew; Fox, Matthew P; Prozesky, Hans W; Chimbetete, Cleophas; Egger, Matthias; Fenner, Lukas

2018-01-01

Objectives Seasonal variations in tuberculosis diagnoses have been attributed to seasonal climatic changes and indoor crowding during colder winter months. We investigated trends in pulmonary tuberculosis (PTB) diagnosis at antiretroviral therapy (ART) programmes in Southern Africa. Setting Five ART programmes participating in the International Epidemiology Database to Evaluate AIDS in South Africa, Zambia and Zimbabwe. Participants We analysed data of 331 634 HIV-positive adults (>15 years), who initiated ART between January 2004 and December 2014. Primary outcome measure We calculated aggregated averages in monthly counts of PTB diagnoses and ART initiations. To account for time trends, we compared deviations of monthly event counts to yearly averages, and calculated correlation coefficients. We used multivariable regressions to assess associations between deviations of monthly ART initiation and PTB diagnosis counts from yearly averages, adjusted for monthly air temperatures and geographical latitude. As controls, we used Kaposi sarcoma and extrapulmonary tuberculosis (EPTB) diagnoses. Results All programmes showed monthly variations in PTB diagnoses that paralleled fluctuations in ART initiations, with recurrent patterns across 2004–2014. The strongest drops in PTB diagnoses occurred in December, followed by April–May in Zimbabwe and South Africa. This corresponded to holiday seasons, when clinical activities are reduced. We observed little monthly variation in ART initiations and PTB diagnoses in Zambia. Correlation coefficients supported parallel trends in ART initiations and PTB diagnoses (correlation coefficient: 0.28, 95% CI 0.21 to 0.35, P<0.001). Monthly temperatures and latitude did not substantially change regression coefficients between ART initiations and PTB diagnoses. Trends in Kaposi sarcoma and EPTB diagnoses similarly followed changes in ART initiations throughout the year. Conclusions Monthly variations in PTB diagnosis at ART programmes in Southern Africa likely occurred regardless of seasonal variations in temperatures or latitude and reflected fluctuations in clinical activities and changes in health-seeking behaviour throughout the year, rather than climatic factors. PMID:29330173

The alarming problems of confounding equivalence using logistic regression models in the perspective of causal diagrams.

PubMed

Yu, Yuanyuan; Li, Hongkai; Sun, Xiaoru; Su, Ping; Wang, Tingting; Liu, Yi; Yuan, Zhongshang; Liu, Yanxun; Xue, Fuzhong

2017-12-28

Confounders can produce spurious associations between exposure and outcome in observational studies. For majority of epidemiologists, adjusting for confounders using logistic regression model is their habitual method, though it has some problems in accuracy and precision. It is, therefore, important to highlight the problems of logistic regression and search the alternative method. Four causal diagram models were defined to summarize confounding equivalence. Both theoretical proofs and simulation studies were performed to verify whether conditioning on different confounding equivalence sets had the same bias-reducing potential and then to select the optimum adjusting strategy, in which logistic regression model and inverse probability weighting based marginal structural model (IPW-based-MSM) were compared. The "do-calculus" was used to calculate the true causal effect of exposure on outcome, then the bias and standard error were used to evaluate the performances of different strategies. Adjusting for different sets of confounding equivalence, as judged by identical Markov boundaries, produced different bias-reducing potential in the logistic regression model. For the sets satisfied G-admissibility, adjusting for the set including all the confounders reduced the equivalent bias to the one containing the parent nodes of the outcome, while the bias after adjusting for the parent nodes of exposure was not equivalent to them. In addition, all causal effect estimations through logistic regression were biased, although the estimation after adjusting for the parent nodes of exposure was nearest to the true causal effect. However, conditioning on different confounding equivalence sets had the same bias-reducing potential under IPW-based-MSM. Compared with logistic regression, the IPW-based-MSM could obtain unbiased causal effect estimation when the adjusted confounders satisfied G-admissibility and the optimal strategy was to adjust for the parent nodes of outcome, which obtained the highest precision. All adjustment strategies through logistic regression were biased for causal effect estimation, while IPW-based-MSM could always obtain unbiased estimation when the adjusted set satisfied G-admissibility. Thus, IPW-based-MSM was recommended to adjust for confounders set.

A hybrid PSO-SVM-based method for predicting the friction coefficient between aircraft tire and coating

NASA Astrophysics Data System (ADS)

Zhan, Liwei; Li, Chengwei

2017-02-01

A hybrid PSO-SVM-based model is proposed to predict the friction coefficient between aircraft tire and coating. The presented hybrid model combines a support vector machine (SVM) with particle swarm optimization (PSO) technique. SVM has been adopted to solve regression problems successfully. Its regression accuracy is greatly related to optimizing parameters such as the regularization constant C , the parameter gamma γ corresponding to RBF kernel and the epsilon parameter \\varepsilon in the SVM training procedure. However, the friction coefficient which is predicted based on SVM has yet to be explored between aircraft tire and coating. The experiment reveals that drop height and tire rotational speed are the factors affecting friction coefficient. Bearing in mind, the friction coefficient can been predicted using the hybrid PSO-SVM-based model by the measured friction coefficient between aircraft tire and coating. To compare regression accuracy, a grid search (GS) method and a genetic algorithm (GA) are used to optimize the relevant parameters (C , γ and \\varepsilon ), respectively. The regression accuracy could be reflected by the coefficient of determination ({{R}2} ). The result shows that the hybrid PSO-RBF-SVM-based model has better accuracy compared with the GS-RBF-SVM- and GA-RBF-SVM-based models. The agreement of this model (PSO-RBF-SVM) with experiment data confirms its good performance.

Pricing of surgeries for colon cancer: patient severity and market factors.

PubMed

Dor, Avi; Koroukian, Siran; Xu, Fang; Stulberg, Jonah; Delaney, Conor; Cooper, Gregory

2012-12-01

This study examined effects of health maintenance organization (HMO) penetration, hospital competition, and patient severity on the uptake of laparoscopic colectomy and its price relative to open surgery for colon cancer. The MarketScan Database (data from 2002-2007) was used to identify admissions for privately insured colorectal cancer patients undergoing laparoscopic or open partial colectomy (n = 1035 and n = 6389, respectively). Patient and health plan characteristics were retrieved from these data; HMO market penetration rates and an index of hospital market concentration, the Herfindahl-Hirschman index (HHI), were derived from national databases. Logistic and logarithmic regressions were used to examine the odds of having laparoscopic colectomy, effect of covariates on colectomy prices, and the differential price of laparoscopy. Adoption of laparoscopy was highly sensitive to market forces, with a 10% increase in HMO penetration leading to a 10.9% increase in the likelihood of undergoing laparoscopic colectomy (adjusted odds ratio = 1.109; 95% confidence interval [CI] = 1.062, 1.158) and a 10% increase in HHI resulting in 6.6% lower likelihood (adjusted odds ratio = 0.936; 95% CI = 0.880, 0.996). Price models indicated that the price of laparoscopy was 7.6% lower than that of open surgery (transformed coefficient = 0.927; 95% CI = 0.895, 0.960). A 10% increase in HMO penetration was associated with 1.6% lower price (transformed coefficient = 0.985; 95% CI = 0.977, 0.992), whereas a 10% increase in HHI was associated with 1.6% higher price (transformed coefficient = 1.016; 95% CI = 1.006, 1.027; P < .001 for all comparisons). Laparoscopy was significantly associated with lower hospital prices. Moreover, laparoscopic surgery may result in cost savings, while market pressures contribute to its adoption. Copyright © 2012 American Cancer Society.

Influence of context in social participation of people with disabilities in Brazil.

PubMed

Silva, Fabiana C M; Sampaio, Rosana F; Ferreira, Fabiane R; Camargos, Vitor P; Neves, Jorge A

2013-10-01

To identify environmental and personal factors associated with social participation in adults with various diseases/health conditions residing in the urban areas of the Belo Horizonte Metropolitan Region, Minas Gerais, Brazil. Individual characteristics, social participation, and perception of environmental barriers of 226 patients treated at a public rehabilitation referral service were evaluated. Regression analyses with hierarchical entry of data were performed to verify the association of personal and environmental factors with social participation. More years of schooling, being engaged in the labor market, and consuming alcohol are conditions that increase the social participation of patients. Natural environment, transportation, access to health services, and social capital are perceived as the most important barriers to participation. Based on the linear regression analysis, the adjusted coefficient (R²(adj)) of the full model was 0.42 (P = 0.000). The results of this study may contribute to the planning and implementation of interventions and public policies at the individual and contextual level that are considered appropriate for reducing barriers and facilitate full participation.

Optimization by response surface methodology of lutein recovery from paprika leaves using accelerated solvent extraction.

PubMed

Kang, Jae-Hyun; Kim, Suna; Moon, BoKyung

2016-08-15

In this study, we used response surface methodology (RSM) to optimize the extraction conditions for recovering lutein from paprika leaves using accelerated solvent extraction (ASE). The lutein content was quantitatively analyzed using a UPLC equipped with a BEH C18 column. A central composite design (CCD) was employed for experimental design to obtain the optimized combination of extraction temperature (°C), static time (min), and solvent (EtOH, %). The experimental data obtained from a twenty sample set were fitted to a second-order polynomial equation using multiple regression analysis. The adjusted coefficient of determination (R(2)) for the lutein extraction model was 0.9518, and the probability value (p=0.0000) demonstrated a high significance for the regression model. The optimum extraction conditions for lutein were temperature: 93.26°C, static time: 5 min, and solvent: 79.63% EtOH. Under these conditions, the predicted extraction yield of lutein was 232.60 μg/g. Copyright © 2016 Elsevier Ltd. All rights reserved.

[Correlation coefficient-based classification method of hydrological dependence variability: With auto-regression model as example].

PubMed

Zhao, Yu Xi; Xie, Ping; Sang, Yan Fang; Wu, Zi Yi

2018-04-01

Hydrological process evaluation is temporal dependent. Hydrological time series including dependence components do not meet the data consistency assumption for hydrological computation. Both of those factors cause great difficulty for water researches. Given the existence of hydrological dependence variability, we proposed a correlationcoefficient-based method for significance evaluation of hydrological dependence based on auto-regression model. By calculating the correlation coefficient between the original series and its dependence component and selecting reasonable thresholds of correlation coefficient, this method divided significance degree of dependence into no variability, weak variability, mid variability, strong variability, and drastic variability. By deducing the relationship between correlation coefficient and auto-correlation coefficient in each order of series, we found that the correlation coefficient was mainly determined by the magnitude of auto-correlation coefficient from the 1 order to p order, which clarified the theoretical basis of this method. With the first-order and second-order auto-regression models as examples, the reasonability of the deduced formula was verified through Monte-Carlo experiments to classify the relationship between correlation coefficient and auto-correlation coefficient. This method was used to analyze three observed hydrological time series. The results indicated the coexistence of stochastic and dependence characteristics in hydrological process.

Diffusion capacity and CT measures of emphysema and airway wall thickness - relation to arterial oxygen tension in COPD patients.

PubMed

Saure, Eirunn Waatevik; Bakke, Per Sigvald; Lind Eagan, Tomas Mikal; Aanerud, Marianne; Jensen, Robert Leroy; Grydeland, Thomas Blix; Johannessen, Ane; Nilsen, Roy Miodini; Thorsen, Einar; Hardie, Jon Andrew

2016-01-01

Decreased diffusing capacity of the lung for carbon monoxide (DLCO) is associated with emphysema. DLCO is also related to decreased arterial oxygen tension (PaO2), but there are limited data on associations between PaO2 and computed tomography (CT) derived measures of emphysema and airway wall thickness. To examine whether CT measures of emphysema and airway wall thickness are associated with level of arterial oxygen tension beyond that provided by measurements of diffusion capacity and spirometry. The study sample consisted of 271 smoking or ex-smoking COPD patients from the Bergen COPD Cohort Study examined in 2007-2008. Emphysema was assessed as percent of low-attenuation areas<-950 Hounsfield units (%LAA), and airway wall thickness as standardised measure at an internal perimeter of 10 mm (AWT-Pi10). Multiple linear regression models were fitted with PaO2 as the outcome variable, and %LAA, AWT-Pi10, DLCO and carbon monoxide transfer coefficient (KCO) as main explanatory variables. The models were adjusted for sex, age, smoking status, and haemoglobin concentration, as well as forced expiratory volume in one second (FEV1). Sixty two per cent of the subjects were men, mean (SD) age was 64 (7) years, mean (SD) FEV1 in percent predicted was 50 (15)%, and mean PaO2 (SD) was 9.3 (1.1) kPa. The adjusted regression coefficient (CI) for PaO2 was -0.32 (-0.04-(-0.019)) per 10% increase in %LAA (p<0.01). When diffusion capacity and FEV1 were added to the model, respectively, the association lost its statistical significance. No relationship between airway wall thickness and PaO2 was found. CT assessment of airway wall thickness is not associated with arterial oxygen tension in COPD patients. Emphysema score measured by chest CT, is related to decreased PaO2, but cannot replace measurements of diffusion capacity in the clinical evaluation of hypoxaemia.

Trends in inequalities in utilization of reproductive health services from 2000 to 2011 in Vietnam.

PubMed

Duc, Nguyen Huu Chau; Nakamura, Keiko; Kizuki, Masashi; Seino, Kaoruko; Rahman, Mosiur

2015-01-01

This study aimed to examine changes in utilization of reproductive health services by wealth status from 2000 to 2011 in Vietnam. Data from the Vietnam Multiple Indicator Cluster Surveys in 2000, 2006, and 2011 were used. The subjects were 550, 1023, and 1363 women, respectively, aged between 15 and 49 years who had given birth in the previous one or two years. The wealth index, a composite measure of a household's ownership of selected assets, materials used for housing construction, and types of water access and sanitation facilities, was used as a measure of wealth status. Main utilization indicators were utilization of antenatal care services, receipt of a tetanus vaccine, receipt of blood pressure measurement, blood examination and urine examination during antenatal care, receipt of HIV testing, skilled birth attendance at delivery, health-facility-based delivery, and cesarean section delivery. Inequalities by wealth index were measured by prevalence ratios, concentration indices, and multivariable adjusted regression coefficients. Significant increase in overall utilization was observed in all indicators (all p < 0.001). The concentration indices were 0.19 in 2000 and 0.06 in 2011 for antenatal care, 0.10 in 2000 and 0.06 in 2011 for tetanus vaccination, 0.23 in 2000 and 0.08 in 2011 for skilled birth attendance, 0.29 in 2006 and 0.12 in 2011 for blood examination, and 0.18 in 2006 and 0.09 in 2011 for health-facility-based delivery. The multivariable adjusted regression coefficients of reproductive health service utilization by wealth category were 0.06 in 2000 and 0.04 in 2011 for antenatal care, 0.07 in 2000 and 0.05 in 2011 for skilled birth attendance, and 0.07 in 2006 and 0.05 in 2011 for health-facility-based delivery. More women utilized reproductive health services in 2011 than in 2000. Inequality by wealth status in utilization of antenatal care, skilled birth attendance, and health-facility-based delivery had been reduced.

Factors signifying gender differences in clinical presentation of sarcoidosis among Estonian population.

PubMed

Lill, Hille; Kliiman, Kai; Altraja, Alan

2016-05-01

Sarcoidosis is endemically prevalent in Northern Europe, but gender differences among the sarcoidosis population have not yet been compositely addressed. To reveal independent factors that formulate gender differences in the presentation of sarcoidosis. All Caucasian patients with confirmed sarcoidosis were recruited from the outpatient department of the Lung Clinic of the Tartu University Hospital, Estonia, between February 2009 and April 2011. Data on demographics, complaints, symptoms, clinical presentation, extrapulmonary manifestations, radiographic stage, lung function parameters and sarcoidosis-related laboratory indices were all drawn from patients' clinical records at presentation. Factors characteristic of female gender were estimated using multivariate logistic regression analysis. Of 230 cases included, there were significantly more females (56.5%, P = 0.005). After adjustment for age, females appeared distinguishable from males by older age [adjusted odds ratio (OR) 1.04, 95% confidence interval (CI) 1.02-1.07], less frequent smoking (OR 0.25, 95% CI 0.13-0.49), higher probability of extrapulmonary complaints (OR 2.06, 95% CI 1.16-3.65) and musculoskeletal sarcoidosis (OR 3.22, 95% CI 1.65-6.29), and after adjustment for both age and smoking status lower forced expiratory volume in 1 s and lung carbon monoxide diffusing coefficient % predicted (OR 0.89, 95% CI 0.82-0.97 and OR 0.98, 95% CI 0.96-0.995, respectively), but by higher forced vital capacity % predicted (OR 1.12, 95% CI 1.03-1.22). Women with sarcoidosis are independently characterized by greater airflow obstruction, lower lung diffusing coefficient, older age, less smoking, and more frequent extrapulmonary complaints and musculoskeletal involvement. This may urge special attention when addressing female patients in both differential diagnostic and management settings. © 2014 John Wiley & Sons Ltd.

Social capital, tolerance of diversity and adherence to Mediterranean diet: the Rhea Mother-Child Cohort in Crete, Greece.

PubMed

Kritsotakis, George; Chatzi, Leda; Vassilaki, Maria; Georgiou, Vaggelis; Kogevinas, Manolis; Philalithis, Anastassios E; Koutis, Antonis

2015-05-01

To estimate the associations of individual maternal social capital and social capital dimensions (Participation in the Community, Feelings of Safety, Value of Life and Social Agency, Tolerance of Diversity) with adherence to the Mediterranean diet during pregnancy. This is a cross-sectional analysis of data from a prospective mother-child cohort (Rhea Study). Participants completed a social capital questionnaire and an FFQ in mid-pregnancy. Mediterranean diet adherence was evaluated through an a priori score ranging from 0 to 8 (minimal-maximal adherence). Maternal social capital scores were categorized into three groups: the upper 10 % was the high social capital group, the middle 80 % was the medium and the lowest 10 % was the low social capital group. Multivariable log-binomial and linear regression models adjusted for confounders were performed. Heraklion, Crete, Greece. A total of 377 women with singleton pregnancies. High maternal Total Social Capital was associated with an increase of almost 1 point in Mediterranean diet score (highest v. lowest group: β coefficient=0·95, 95 % CI 0·23, 1·68), after adjustment for confounders. Similar dose-response effects were noted for the scale Tolerance of Diversity (highest v. lowest group: adjusted β coefficient=1·08, 95 % CI 0·39, 1·77). Individual social capital and tolerance of diversity are associated with adherence to the Mediterranean diet in pregnancy. Women with higher social capital may exhibit a higher sense of obligation to themselves and to others that may lead to proactive nutrition-related activities. Less tolerant women may not provide the opportunity to new healthier, but unfamiliar, nutritional recommendations to become part of their regular diet.

Sex Hormones and Sleep in Men and Women From the General Population: A Cross-Sectional Observational Study.

PubMed

Kische, Hanna; Ewert, Ralf; Fietze, Ingo; Gross, Stefan; Wallaschofski, Henri; Völzke, Henry; Dörr, Marcus; Nauck, Matthias; Obst, Anne; Stubbe, Beate; Penzel, Thomas; Haring, Robin

2016-11-01

Associations between sex hormones and sleep habits originate mainly from small and selected patient-based samples. We examined data from a population-based sample with various sleep characteristics and the major part of sex hormones measured by mass spectrometry. We used data from 204 men and 213 women of the cross-sectional Study of Health in Pomerania-TREND. Associations of total T (TT) and free T, androstenedione (ASD), estrone, estradiol (E2), dehydroepiandrosterone-sulphate, SHBG, and E2 to TT ratio with sleep measures (including total sleep time, sleep efficiency, wake after sleep onset, apnea-hypopnea index [AHI], Insomnia Severity Index, Epworth Sleepiness Scale, and Pittsburgh Sleep Quality Index) were assessed by sex-specific multivariable regression models. In men, age-adjusted associations of TT (odds ratio 0.62; 95% confidence interval (CI) 0.46-0.83), free T, and SHBG with AHI were rendered nonsignificant after multivariable adjustment. In multivariable analyses, ASD was associated with Epworth Sleepiness Scale (β-coefficient per SD increase in ASD: -0.71; 95% CI: -1.18 to -0.25). In women, multivariable analyses showed positive associations of dehydroepiandrosterone-sulphate with wake after sleep onset (β-coefficient: .16; 95% CI 0.03-0.28) and of E2 and E2 to TT ratio with Epworth Sleepiness Scale. Additionally, free T and SHBG were associated with AHI in multivariable models among premenopausal women. The present cross-sectional, population-based study observed sex-specific associations of androgens, E2, and SHBG with sleep apnea and daytime sleepiness. However, multivariable-adjusted analyses confirmed the impact of body composition and health-related lifestyle on the association between sex hormones and sleep.

Detection of Cutting Tool Wear using Statistical Analysis and Regression Model

NASA Astrophysics Data System (ADS)

Ghani, Jaharah A.; Rizal, Muhammad; Nuawi, Mohd Zaki; Haron, Che Hassan Che; Ramli, Rizauddin

2010-10-01

This study presents a new method for detecting the cutting tool wear based on the measured cutting force signals. A statistical-based method called Integrated Kurtosis-based Algorithm for Z-Filter technique, called I-kaz was used for developing a regression model and 3D graphic presentation of I-kaz 3D coefficient during machining process. The machining tests were carried out using a CNC turning machine Colchester Master Tornado T4 in dry cutting condition. A Kistler 9255B dynamometer was used to measure the cutting force signals, which were transmitted, analyzed, and displayed in the DasyLab software. Various force signals from machining operation were analyzed, and each has its own I-kaz 3D coefficient. This coefficient was examined and its relationship with flank wear lands (VB) was determined. A regression model was developed due to this relationship, and results of the regression model shows that the I-kaz 3D coefficient value decreases as tool wear increases. The result then is used for real time tool wear monitoring.

Profile local linear estimation of generalized semiparametric regression model for longitudinal data.

PubMed

Sun, Yanqing; Sun, Liuquan; Zhou, Jie

2013-07-01

This paper studies the generalized semiparametric regression model for longitudinal data where the covariate effects are constant for some and time-varying for others. Different link functions can be used to allow more flexible modelling of longitudinal data. The nonparametric components of the model are estimated using a local linear estimating equation and the parametric components are estimated through a profile estimating function. The method automatically adjusts for heterogeneity of sampling times, allowing the sampling strategy to depend on the past sampling history as well as possibly time-dependent covariates without specifically model such dependence. A [Formula: see text]-fold cross-validation bandwidth selection is proposed as a working tool for locating an appropriate bandwidth. A criteria for selecting the link function is proposed to provide better fit of the data. Large sample properties of the proposed estimators are investigated. Large sample pointwise and simultaneous confidence intervals for the regression coefficients are constructed. Formal hypothesis testing procedures are proposed to check for the covariate effects and whether the effects are time-varying. A simulation study is conducted to examine the finite sample performances of the proposed estimation and hypothesis testing procedures. The methods are illustrated with a data example.

SCI model structure determination program (OSR) user's guide. [optimal subset regression

NASA Technical Reports Server (NTRS)

1979-01-01

The computer program, OSR (Optimal Subset Regression) which estimates models for rotorcraft body and rotor force and moment coefficients is described. The technique used is based on the subset regression algorithm. Given time histories of aerodynamic coefficients, aerodynamic variables, and control inputs, the program computes correlation between various time histories. The model structure determination is based on these correlations. Inputs and outputs of the program are given.

Ecotoxicology of phenylphosphonothioates.

PubMed Central

Francis, B M; Hansen, L G; Fukuto, T R; Lu, P Y; Metcalf, R L

1980-01-01

The phenylphosphonothioate insecticides EPN and leptophos, and several analogs, were evaluated with respect to their delayed neurotoxic effects in hens and their environmental behavior in a terrestrial-aquatic model ecosystem. Acute toxicity to insects was highly correlated with sigma sigma of the substituted phenyl group (regression coefficient r = -0.91) while acute toxicity to mammals was slightly less well correlated (regression coefficient r = -0.71), and neurotoxicity was poorly correlated with sigma sigma (regression coefficient r = -0.35). Both EPN and leptophos were markedly more persistent and bioaccumulative in the model ecosystem than parathion. Desbromoleptophos, a contaminant and metabolite of leptophos, was seen to be a highly stable and persistent terminal residue of leptophos. PMID:6159210

Associations between active commuting and physical and mental wellbeing☆

PubMed Central

Humphreys, David K.; Goodman, Anna; Ogilvie, David

2013-01-01

Objective To examine whether a relationship exists between active commuting and physical and mental wellbeing. Method In 2009, cross-sectional postal questionnaire data were collected from a sample of working adults (aged 16 and over) in the Commuting and Health in Cambridge study. Travel behaviour and physical activity were ascertained using the Recent Physical Activity Questionnaire (RPAQ) and a seven-day travel-to-work recall instrument from which weekly time spent in active commuting (walking and cycling) was derived. Physical and mental wellbeing were assessed using the Medical Outcomes Study Short Form survey (SF-8). Associations were tested using multivariable linear regression. Results An association was observed between physical wellbeing (PCS-8) score and time spent in active commuting after adjustment for other physical activity (adjusted regression coefficients 0.48, 0.79 and 1.21 for 30–149 min/week, 150–224 min/week and ≥ 225 min/week respectively versus < 30 min/week, p = 0.01 for trend; n = 989). No such relationship was found for mental wellbeing (MCS-8) (p = 0.52). Conclusion Greater time spent actively commuting is associated with higher levels of physical wellbeing. Longitudinal studies should examine the contribution of changing levels of active commuting and other forms of physical activity to overall health and wellbeing. PMID:23618913

Validation of a food frequency questionnaire measurement of dietary acrylamide intake using hemoglobin adducts of acrylamide and glycidamide

PubMed Central

Wilson, Kathryn M.; Vesper, Hubert W.; Tocco, Paula; Sampson, Laura; Rosén, Johan; Hellenäs, Karl-Erik; Törnqvist, Margareta; Willett, Walter C.

2011-01-01

Objective Acrylamide, a probable human carcinogen, is formed during high-heat cooking of many common foods. The validity of food frequency questionnaire (FFQ) measures of acrylamide intake has not been established. We assessed the validity of acrylamide intake calculated from an FFQ using a biomarker of acrylamide exposure. Methods We calculated acrylamide intake from an FFQ in the Nurses' Health Study II. We measured hemoglobin adducts of acrylamide and its metabolite, glycidamide, in a random sample of 296 women. Correlation and regression analyses were used to assess the relationship between acrylamide intake and adducts. Results The correlation between acrylamide intake and the sum of acrylamide and glycidamide adducts was 0.31 (95% CI: 0.20 – 0.41), adjusted for laboratory batch, energy intake, and age. Further adjustment for BMI, alcohol intake, and correction for random within-person measurement error in adducts gave a correlation of 0.34 (CI: 0.23 – 0.45). The intraclass correlation coefficient for the sum of adducts was 0.77 in blood samples collected 1 to 3 years apart in a subset of 45 women. Intake of several foods significantly predicted adducts in multiple regression. Conclusions Acrylamide intake and hemoglobin adducts of acrylamide and glycidamide were moderately correlated. Within-person consistency in adducts was high over time. PMID:18855107

Energy intake and dietary patterns in childhood and throughout adulthood and mammographic density: results from a British prospective cohort.

PubMed

Mishra, Gita D; dos Santos Silva, Isabel; McNaughton, Sarah A; Stephen, Alison; Kuh, Diana

2011-02-01

To examine the role of energy intake and dietary patterns in childhood and throughout adulthood on subsequent mammographic density. Prospective data were available from a cohort of 1161 British women followed up since their birth in 1946. Dietary intakes at age 4 years were determined by 24-hour recalls and during adulthood, average food consumed at ages 36 and 43 years by 5-day food records. Dietary patterns were determined by factor analysis. Associations between energy intake, dietary patterns, and percent breast density were investigated using regression analysis. During adulthood, energy intake was positively associated with percent breast density (adjusted regression coefficient [per SD) (95% CI): 0.12 (0.01, 0.23)]. The effect of the high fat and sugar dietary pattern remained similar when adjusted for total energy intake [0.06 (-0.01, 0.13)]. There was no evidence of an associations for the patterns low fat, high fiber pattern 0.03 (-0.04, 0.11); the alcohol and fish -0.02 (-0.13, 0.17); meat, potatoes, and vegetables -0.03 (-0.10, 0.04). No association was found for dietary pattern at age 4 and percent breast density. This study supports the hypothesis that overall energy intake during middle life is a determinant of subsequent mammographic breast density measured 15 years later.

Correlation of Vitamin D status and orthodontic-induced external apical root resorption

PubMed Central

Tehranchi, Azita; Sadighnia, Azin; Younessian, Farnaz; Abdi, Amir H.; Shirvani, Armin

2017-01-01

Background: Adequate Vitamin D is essential for dental and skeletal health in children and adult. The purpose of this study was to assess the correlation of serum Vitamin D level with external-induced apical root resorption (EARR) following fixed orthodontic treatment. Materials and Methods: In this cross-sectional study, the prevalence of Vitamin D deficiency (defined by25-hydroxyvitamin-D) was determined in 34 patients (23.5% male; age range 12–23 years; mean age 16.63 ± 2.84) treated with fixed orthodontic treatment. Root resorption of four maxillary incisors was measured using before and after periapical radiographs (136 measured teeth) by means of a design-to-purpose software to optimize data collection. Teeth with a maximum percentage of root resorption (%EARR) were indicated as representative root resorption for each patient. A multiple linear regression model and Pearson correlation coefficient were used to assess the association of Vitamin D status and observed EARR. P < 0.05 was considered statistically significant. Results: The Pearson coefficient between these two variables was determined about 0.15 (P = 0.38). Regression analysis revealed that Vitamin D status of the patients demonstrated no significant statistical correlation with EARR, after adjustment of confounding variables using linear regression model (P > 0.05). Conclusion: This study suggests that Vitamin D level is not among the clinical variables that are potential contributors for EARR. The prevalence of Vitamin D deficiency does not differ in patients with higher EARR. These data suggest the possibility that Vitamin D insufficiency may not contribute to the development of more apical root resorption although this remains to be confirmed by further longitudinal cohort studies. PMID:29238379

Adherence to preferable behavior for lipid control by high-risk dyslipidemic Japanese patients under pravastatin treatment: the APPROACH-J study.

PubMed

Kitagawa, Yasuhisa; Teramoto, Tamio; Daida, Hiroyuki

2012-01-01

We evaluated the impact of adherence to preferable behavior on serum lipid control assessed by a self-reported questionnaire in high-risk patients taking pravastatin for primary prevention of coronary artery disease. High-risk patients taking pravastatin were followed for 2 years. Questionnaire surveys comprising 21 questions, including 18 questions concerning awareness of health, and current status of diet, exercise, and drug therapy, were conducted at baseline and after 1 year. Potential domains were established by factor analysis from the results of questionnaires, and adherence scores were calculated in each domain. The relationship between adherence scores and lipid values during the 1-year treatment period was analyzed by each domain using multiple regression analysis. A total of 5,792 patients taking pravastatin were included in the analysis. Multiple regression analysis showed a significant correlation in terms of "Intake of high fat/cholesterol/sugar foods" (regression coefficient -0.58, p=0.0105) and "Adherence to instructions for drug therapy" (regression coefficient -6.61, p<0.0001). Low-density lipoprotein cholesterol (LDL-C) values were significantly lower in patients who had an increase in the adherence score in the "Awareness of health" domain compared with those with a decreased score. There was a significant correlation between high-density lipoprotein (HDL-C) values and "Awareness of health" (regression coefficient 0.26; p= 0.0037), "Preferable dietary behaviors" (regression coefficient 0.75; p<0.0001), and "Exercise" (regression coefficient 0.73; p= 0.0002). Similar relations were seen with triglycerides. In patients who have a high awareness of their health, a positive attitude toward lipid-lowering treatment including diet, exercise, and high adherence to drug therapy, is related with favorable overall lipid control even in patients under treatment with pravastatin.

[Habitat suitability index of larval Japanese Halfbeak (Hyporhamphus sajori) in Bohai Sea based on geographically weighted regression.

PubMed

Zhao, Yang; Zhang, Xue Qing; Bian, Xiao Dong

2018-01-01

To investigate the early supplementary processes of fishre sources in the Bohai Sea, the geographically weighted regression (GWR) was introduced to the habitat suitability index (HSI) model. The Bohai Sea larval Japanese Halfbeak HSI GWR model was established with four environmental variables, including sea surface temperature (SST), sea surface salinity (SSS), water depth (DEP), and chlorophyll a concentration (Chl a). Results of the simulation showed that the four variables had different performances in August 2015. SST and Chl a were global variables, and had little impacts on HSI, with the regression coefficients of -0.027 and 0.006, respectively. SSS and DEP were local variables, and had larger impacts on HSI, while the average values of absolute values of their regression coefficients were 0.075 and 0.129, respectively. In the central Bohai Sea, SSS showed a negative correlation with HSI, and the most negative correlation coefficient was -0.3. In contrast, SSS was correlated positively but weakly with HSI in the three bays of Bohai Sea, and the largest correlation coefficient was 0.1. In particular, DEP and HSI were negatively correlated in the entire Bohai Sea, while they were more negatively correlated in the three bays of Bohai than in the central Bohai Sea, and the most negative correlation coefficient was -0.16 in the three bays. The Poisson regression coefficient of the HSI GWR model was 0.705, consistent with field measurements. Therefore, it could provide a new method for the research on fish habitats in the future.

History of Gestational Diabetes Mellitus in Relation to Cardiovascular Disease and Cardiovascular Risk Factors in US Women.

PubMed

Shostrom, Derrick C V; Sun, Yangbo; Oleson, Jacob J; Snetselaar, Linda G; Bao, Wei

2017-01-01

Findings from previous studies examining the association between gestational diabetes mellitus (GDM) and subsequent risk of cardiovascular disease (CVD) have been inconsistent and inconclusive. We aimed to examine the associations of a previous history of GDM with risk of CVD and status of cardiovascular risk factors in a nationwide population-based study in the United States. This study included 8,127 parous women aged 20 years or older in the 2007-2014 cycles of the National Health and Nutrition Examination Survey in the United States. The exposure was self-reported diagnostic history of GDM and the outcomes were self-reported diagnostic history of CVD and measurements of cardiovascular risk factors, including blood pressure and blood lipids. Regression models with sample weights were used to examine the associations of GDM with CVD and cardiovascular risk factors. Among women with a history of both GDM and CVD, CVD was diagnosed on average 22.9 years after the diagnosis of GDM. After adjustment for demographic, socioeconomic, and lifestyle factors, a history of GDM was associated with 63% higher odds of CVD [odds ratio (OR) 1.63, 95% confidence interval (CI) 1.02, 2.62, p -value = 0.04]. Further adjustment for body mass index (BMI) modestly attenuated the association (OR 1.52, 95% CI 0.95, 2.44, p -value = 0.08). A history of GDM was significantly associated with lower serum level of HDL-cholesterol (adjusted β-coefficient -3.33, 95% CI -5.17, -1.50, p -value ≤ 0.001), but not associated with total cholesterol, LDL-cholesterol, triglycerides, or systolic or diastolic blood pressure. Similarly, the association between a history of GDM and HDL cholesterol was attenuated after additional adjustment for BMI (adjusted β-coefficient -1.68, 95% CI -3.38, 0.03, p -value = 0.54). Women with a previous history of GDM have significantly higher risk for developing CVD and lower serum level of HDL cholesterol, compared to women without a history of GDM. The associations may be explained, at least partly, by BMI.

On the use and misuse of scalar scores of confounders in design and analysis of observational studies.

PubMed

Pfeiffer, R M; Riedl, R

2015-08-15

We assess the asymptotic bias of estimates of exposure effects conditional on covariates when summary scores of confounders, instead of the confounders themselves, are used to analyze observational data. First, we study regression models for cohort data that are adjusted for summary scores. Second, we derive the asymptotic bias for case-control studies when cases and controls are matched on a summary score, and then analyzed either using conditional logistic regression or by unconditional logistic regression adjusted for the summary score. Two scores, the propensity score (PS) and the disease risk score (DRS) are studied in detail. For cohort analysis, when regression models are adjusted for the PS, the estimated conditional treatment effect is unbiased only for linear models, or at the null for non-linear models. Adjustment of cohort data for DRS yields unbiased estimates only for linear regression; all other estimates of exposure effects are biased. Matching cases and controls on DRS and analyzing them using conditional logistic regression yields unbiased estimates of exposure effect, whereas adjusting for the DRS in unconditional logistic regression yields biased estimates, even under the null hypothesis of no association. Matching cases and controls on the PS yield unbiased estimates only under the null for both conditional and unconditional logistic regression, adjusted for the PS. We study the bias for various confounding scenarios and compare our asymptotic results with those from simulations with limited sample sizes. To create realistic correlations among multiple confounders, we also based simulations on a real dataset. Copyright © 2015 John Wiley & Sons, Ltd.

Academic research productivity of post-graduate students at Makerere University College of Health Sciences, Uganda, from 1996 to 2010: a retrospective review.

PubMed

Obuku, E A; Lavis, J N; Kinengyere, A; Mafigiri, D K; Sengooba, F; Karamagi, C; Sewankambo, N K

2017-04-04

Research is a core business of universities globally, and is crucial in the scientific process as a precursor for knowledge uptake and use. We aimed to assess the academic productivity of post-graduate students in a university located in a low-income country. This is an observational retrospective documentary analysis using hand searching archives, Google Scholar and PubMed electronic databases. The setting is Makerere University College of Health Sciences, Uganda. Records of post-graduate students (Masters) enrolled from 1996 to 2010, and followed to 2016 for outcomes were analysed. The outcome measures were publications (primary), citations, electronic dissertations found online or conference abstracts (secondary). Descriptive and multivariable logistic regression analyses were performed using Stata 14.1. We found dissertations of 1172 Masters students over the 20-year period of study. While half (590, 50%) had completed clinical graduate disciplines (surgery, internal medicine, paediatrics, obstetrics and gynaecology), Master of Public Health was the single most popular course, with 393 students (31%). Manuscripts from 209 dissertations (18%; 95% CI, 16-20%) were published and approximately the same proportion was cited (196, 17%; 95% CI, 15-19%). Very few (4%) policy-related documents (technical reports and guidelines) cited these dissertations. Variables that remained statistically significant in the multivariable model were students' age at enrolment into the Masters programme (adjusted coefficient -0.12; 95% CI, -0.18 to -0.06; P < 0.001) and type of research design (adjusted coefficient 0.22; 0.03 to 0.40; P = 0.024). Cohort studies were more likely to be published compared to cross-sectional designs (adjusted coefficient 0.78; 95% CI, 0.2 to 1.36; P = 0.008). The productivity and use of post-graduate students' research conducted at the College of Health Sciences Makerere University is considerably low in terms of peer-reviewed publications and citations in policy-related documents. The need for effective strategies to reverse this 'waste' is urgent if the College, decision-makers, funders and the Ugandan public are to enjoy the 'return on investment' from post-graduate students research.

Bone lead (Pb) content at the tibia is associated with thinner distal tibia cortices and lower volumetric bone density in postmenopausal women

PubMed Central

Wong, Andy K.O.; Beattie, Karen A.; Bhargava, Aakash; Cheung, Marco; Webber, Colin E.; Chettle, David R.; Papaioannou, Alexandra; Adachi, Jonathan D.

2016-01-01

Conflicting evidence suggests that bone lead or blood lead may reduce areal bone mineral density (BMD). Little is known about how lead at either compartment affects bone structure. This study examined postmenopausal women (N = 38, mean age 76 ± 8, body mass index (BMI): 26.74 ± 4.26 kg/m2) within the Hamilton cohort of the Canadian Multicentre Osteoporosis Study (CaMos), measuring bone lead at 66% of the non-dominant leg and at the calcaneus using 109Cadmium X-ray fluorescence. Volumetric BMD and structural parameters were obtained from peripheral quantitative computed tomography images (200 μm in-plane resolution, 2.3 ± 0.5 mm slice thickness) of the same 66% site and of the distal 4% site of the tibia length. Blood lead was measured using atomic absorption spectrometry and blood-to-bone lead partition coefficients (PBB, log ratio) were computed. Multivariable linear regression examined each of bone lead at the 66% tibia, calcaneus, blood lead and PBB as related to each of volumetric BMD and structural parameters, adjusting for age and BMI, diabetes or antiresorptive therapy. Regression coefficients were reported along with 95% confidence intervals. Higher amounts of bone lead at the tibia were associated with thinner distal tibia cortices (−0.972 (−1.882, −0.061) per 100 μg Pb/g of bone mineral) and integral volumetric BMD (−3.05 (−6.05, −0.05) per μg Pb/g of bone mineral). A higher PBB was associated with larger trabecular separation (0.115 (0.053, 0.178)), lower trabecular volumetric BMD (−26.83 (−50.37, −3.29)) and trabecular number (−0.08 (−0.14, −0.02)), per 100 μg Pb/g of bone mineral after adjusting for age and BMI, and remained significant while accounting for diabetes or use of antiresorptives. Total lead exposure activities related to bone lead at the calcaneus (8.29 (0.11, 16.48)) and remained significant after age and antiresorptives-adjustment. Lead accumulated in bone can have a mild insult on bone structure; but greater partitioning of lead in blood versus bone revealed more dramatic effects on both microstructure and volumetric BMD. PMID:25986335

Association between age associated cognitive decline and health related quality of life among Iranian older individuals.

PubMed

Kazazi, Leila; Foroughan, Mahshid; Nejati, Vahid; Shati, Mohsen

2018-04-01

Age associated cognitive decline or normal cognitive aging is related with lower levels of functioning in real life, and may interfere with maintaining independence and health related quality of life (HRQL). In this study, health related quality of life and cognitive function in community-dwelling older adults were evaluated with the aim of exploring the association between them by adjusting for potential confounders. This cross-sectional study, was implemented on 425 community-dwelling older adults aged 60 and over, between August 2016 and October 2016 in health centers of the municipality of Tehran, Iran, using Mini Mental State Examination (MMSE) to assess cognitive function and Short Form-36 scales (SF-36) to assess HRQL. The relation between HRQL and cognitive function was evaluated by Pearson's correlation coefficient, and the impact of cognitive function on HRQL adjusted for potential confounders was estimated by linear regression model. All analyses were done using SPSS, version 22.0. A positive significant correlation between cognitive function and quality of life (r=0.434; p<0.001) and its dimensions was observed. Two variables of educational level (B=2.704; 95% CI: 2.09 to 3.30; p<0.001) and depression (B=2.554; 95% CI: 2.00 to 3.10; p<0.001) were assumed as potential confounder by changing effect measure after entering the model. After adjusting for potential confounders in regression model, the association between MMSE scores and quality of life persisted (B=2.417; 95% CI: 1.86 to 2.96; p<0.001). The results indicate that cognitive function was associated with HRQL in older adults with age associated cognitive function. Two variables of educational level and depression can affect the relation between cognitive decline and HRQL.

Inconsistent Correlation Between Carotid Artery Intima-Media Thickness and Peripheral Arterial Tonometry

PubMed Central

Lemos, Sara P.; Passos, Valéria Maria A.; Brant, Luisa C.C.; Bensenor, Isabela J.M.; Ribeiro, Antônio Luiz P.; Barreto, Sandhi Maria

2015-01-01

Abstract To estimate the association between 2 markers for atherosclerosis, measurements of carotid artery intima-media thickness (IMT) and of peripheral arterial tonometry (PAT), and to evaluate the role of traditional cardiovascular risk factors in this association. We applied the 2 diagnostic tests to 588 participants from the ELSA-Brazil longitudinal study cohort. The PAT measurements, obtained with the EndoPAT2000, were the reactive hyperemia index (RHI), the Framingham RHI (F-RHI), and the mean basal pulse amplitude (BPA). We used the mean of the mean scores of carotid IMT of the distal layers of the left and right common carotids obtained by ultrasonography after 3 cardiac cycles. We used linear regression and the Spearman correlation coefficient to test the relationship between the 2 markers, and multiple linear regressions to exam the relationship between the RHI/F-RHI scores and the mean BPA and IMT scores after adjusting for cardiovascular risk factors. In the multivariate analysis, RHI (but not F-RHI) was positively correlated with the mean of the means of the IMT values after adjusting for sex and risk factors connected with both measures (β = 0.05, P = 0.02). Mean BPA did not remain significantly associated with IMT after adjusting for common risk factors. We found that the higher the IMT (or the worse the IMT), the higher the RHI (or the better the endothelial function). F-RHI was not associated with IMT. These 2 results are against the direction that one would expect and may imply that digital endothelial function (RHI and F-RHI) and IMT correspond to distinct and independent stages of the complex atherosclerosis process and represent different pathways in the disease's progression. Therefore, IMT and PAT measures may be considered complementary and not interchangeable. PMID:26287431

Waist Circumference Adjusted for Body Mass Index and Intra-Abdominal Fat Mass

PubMed Central

Berentzen, Tina Landsvig; Ängquist, Lars; Kotronen, Anna; Borra, Ronald; Yki-Järvinen, Hannele; Iozzo, Patricia; Parkkola, Riitta; Nuutila, Pirjo; Ross, Robert; Allison, David B.; Heymsfield, Steven B.; Overvad, Kim; Sørensen, Thorkild I. A.; Jakobsen, Marianne Uhre

2012-01-01

Background The association between waist circumference (WC) and mortality is particularly strong and direct when adjusted for body mass index (BMI). One conceivable explanation for this association is that WC adjusted for BMI is a better predictor of the presumably most harmful intra-abdominal fat mass (IAFM) than WC alone. We studied the prediction of abdominal subcutaneous fat mass (ASFM) and IAFM by WC alone and by addition of BMI as an explanatory factor. Methodology/Principal Findings WC, BMI and magnetic resonance imaging data from 742 men and women who participated in clinical studies in Canada and Finland were pooled. Total adjusted squared multiple correlation coefficients (R2) of ASFM and IAFM were calculated from multiple linear regression models with WC and BMI as explanatory variables. Mean BMI and WC of the participants in the pooled sample were 30 kg/m2 and 102 cm, respectively. WC explained 29% of the variance in ASFM and 51% of the variance in IAFM. Addition of BMI to WC added 28% to the variance explained in ASFM, but only 1% to the variance explained in IAFM. Results in subgroups stratified by study center, sex, age, obesity level and type 2 diabetes status were not systematically different. Conclusion/Significance The prediction of IAFM by WC is not improved by addition of BMI. PMID:22384179

Faith-Based Hospitals and Variation in Psychiatric Inpatient Length of Stay in California, 2002-2011.

PubMed

Banta, Jim E; McKinney, Ogbochi

2016-06-01

We examined current treatment patterns at faith-based hospitals. Psychiatric discharges from all community-based hospitals in California were obtained for 2002-2011 and a Behavioral Model of Health Services Utilization approach used to study hospital religious affiliation and length of stay (LOS). During 10 years there were 1,976,893 psychiatric inpatient discharges, of which 14.3% were from faith-based nonprofit hospitals (eighteen Catholic, seven Seventh-day Adventist, and one Jewish hospital). Modest differences in patient characteristics and shorter LOS (7.5 vs. 8.3 days) were observed between faith-based and other hospitals. Multivariable negative binomial regression found shorter LOS at faith-based nonprofit hospitals (coefficient = -0.1169, p < 0.001, Wald χ (2) = 55) and greater LOS at all nonprofits (coefficient = 1.5909, p < 0.001, Wald χ (2) = 2755) as compared to local government-controlled hospitals. Faith-based hospitals provide a substantial and consistent amount of psychiatric care in California and may have slightly lower LOS after adjusting for patient and other hospital characteristics.

Confidence Intervals for Squared Semipartial Correlation Coefficients: The Effect of Nonnormality

ERIC Educational Resources Information Center

Algina, James; Keselman, H. J.; Penfield, Randall D.

2010-01-01

The increase in the squared multiple correlation coefficient ([delta]R[superscript 2]) associated with a variable in a regression equation is a commonly used measure of importance in regression analysis. Algina, Keselman, and Penfield found that intervals based on asymptotic principles were typically very inaccurate, even though the sample size…

Impacts of land use and population density on seasonal surface water quality using a modified geographically weighted regression.

PubMed

Chen, Qiang; Mei, Kun; Dahlgren, Randy A; Wang, Ting; Gong, Jian; Zhang, Minghua

2016-12-01

As an important regulator of pollutants in overland flow and interflow, land use has become an essential research component for determining the relationships between surface water quality and pollution sources. This study investigated the use of ordinary least squares (OLS) and geographically weighted regression (GWR) models to identify the impact of land use and population density on surface water quality in the Wen-Rui Tang River watershed of eastern China. A manual variable excluding-selecting method was explored to resolve multicollinearity issues. Standard regression coefficient analysis coupled with cluster analysis was introduced to determine which variable had the greatest influence on water quality. Results showed that: (1) Impact of land use on water quality varied with spatial and seasonal scales. Both positive and negative effects for certain land-use indicators were found in different subcatchments. (2) Urban land was the dominant factor influencing N, P and chemical oxygen demand (COD) in highly urbanized regions, but the relationship was weak as the pollutants were mainly from point sources. Agricultural land was the primary factor influencing N and P in suburban and rural areas; the relationship was strong as the pollutants were mainly from agricultural surface runoff. Subcatchments located in suburban areas were identified with urban land as the primary influencing factor during the wet season while agricultural land was identified as a more prevalent influencing factor during the dry season. (3) Adjusted R 2 values in OLS models using the manual variable excluding-selecting method averaged 14.3% higher than using stepwise multiple linear regressions. However, the corresponding GWR models had adjusted R 2 ~59.2% higher than the optimal OLS models, confirming that GWR models demonstrated better prediction accuracy. Based on our findings, water resource protection policies should consider site-specific land-use conditions within each watershed to optimize mitigation strategies for contrasting land-use characteristics and seasonal variations. Copyright © 2016 Elsevier B.V. All rights reserved.

Estimation of octanol/water partition coefficients using LSER parameters

USGS Publications Warehouse

Luehrs, Dean C.; Hickey, James P.; Godbole, Kalpana A.; Rogers, Tony N.

1998-01-01

The logarithms of octanol/water partition coefficients, logKow, were regressed against the linear solvation energy relationship (LSER) parameters for a training set of 981 diverse organic chemicals. The standard deviation for logKow was 0.49. The regression equation was then used to estimate logKow for a test of 146 chemicals which included pesticides and other diverse polyfunctional compounds. Thus the octanol/water partition coefficient may be estimated by LSER parameters without elaborate software but only moderate accuracy should be expected.

Variations in hospitals costs for surgical procedures: inefficient care or sick patients?

PubMed

Gani, Faiz; Hundt, John; Daniel, Michael; Efron, Jonathan E; Makary, Martin A; Pawlik, Timothy M

2017-01-01

Reducing unwanted variations has been identified as an avenue for cost containment. We sought to characterize variations in hospital costs after major surgery and quantitate the variability attributable to the patient, procedure, and provider. A total of 22,559 patients undergoing major surgical procedure at a tertiary-care center between 2009 and 2013 were identified. Hierarchical linear regression analysis was performed to calculate risk-adjusted fixed, variable and total costs. The median cost of surgery was $23,845 (interquartile ranges, 13,353 to 43,083). Factors associated with increased costs included insurance status (Medicare vs private; coefficient: 14,934; 95% CI = 12,445.7 to 17,422.5, P < .001), preoperative comorbidity (Charlson Comorbidity Index = 1; coefficient: 10,793; 95% CI = 8,412.7 to 13,174.2; Charlson Comorbidity Index ≥2; coefficient: 24,468; 95% CI = 22,552.7 to 26,383.6; both P < .001) and the development of a postoperative complication (coefficient: 58,624.1; 95% CI = 56,683.6 to 60,564.7; P < .001). Eighty-six percent of total variability was explained by patient-related factors, whereas 8% of the total variation was attributed to surgeon practices and 6% due to factors at the level of surgical specialty. Although inpatient costs varied markedly between procedures and providers, the majority of variation in costs was due to patient-level factors and should be targeted by future cost containment strategies. Copyright © 2016 Elsevier Inc. All rights reserved.

Thermal requirements of Dermanyssus gallinae (De Geer, 1778) (Acari: Dermanyssidae).

PubMed

Tucci, Edna Clara; do Prado, Angelo P; de Araújo, Raquel Pires

2008-01-01

The thermal requirements for development of Dermanyssus gallinae were studied under laboratory conditions at 15, 20, 25, 30 and 35 degrees C, a 12h photoperiod and 60-85% RH. The thermal requirements for D. gallinae were as follows. Preoviposition: base temperature 3.4 degrees C, thermal constant (k) 562.85 degree-hours, determination coefficient (R(2)) 0.59, regression equation: Y= -0.006035 + 0.001777x. Egg: base temperature 10.60 degrees C, thermal constant (k) 689.65 degree-hours, determination coefficient (R(2)) 0.94, regression equation: Y= -0.015367 + 0.001450x. Larva: base temperature 9.82 degrees C, thermal constant (k) 464.91 degree-hours, determination coefficient (R(2)) 0.87, regression equation: Y= -0.021123 + 0.002151x. Protonymph: base temperature 10.17 degrees C, thermal constant (k) 504.49 degree-hours, determination coefficient (R(2)) 0.90, regression equation: Y= -0.020152 + 0.001982x. Deutonymph: base temperature 11.80 degrees C, thermal constant (k) 501.11 degree-hours, determination coefficient (R(2)) 0.99, regression equation: Y= -0.023555 + 0.001996x. The results obtained showed that 15 to 42 generations of Dermanyssus gallinae may occur during the year in the State of São Paulo, as estimated based on isotherm charts. Dermanyssus gallinae may develop continually in the State of São Paulo, with a population decrease in the winter. There were differences between the developmental stages of D. gallinae in relation to thermal requirements.

Practical guidance for conducting mediation analysis with multiple mediators using inverse odds ratio weighting.

PubMed

Nguyen, Quynh C; Osypuk, Theresa L; Schmidt, Nicole M; Glymour, M Maria; Tchetgen Tchetgen, Eric J

2015-03-01

Despite the recent flourishing of mediation analysis techniques, many modern approaches are difficult to implement or applicable to only a restricted range of regression models. This report provides practical guidance for implementing a new technique utilizing inverse odds ratio weighting (IORW) to estimate natural direct and indirect effects for mediation analyses. IORW takes advantage of the odds ratio's invariance property and condenses information on the odds ratio for the relationship between the exposure (treatment) and multiple mediators, conditional on covariates, by regressing exposure on mediators and covariates. The inverse of the covariate-adjusted exposure-mediator odds ratio association is used to weight the primary analytical regression of the outcome on treatment. The treatment coefficient in such a weighted regression estimates the natural direct effect of treatment on the outcome, and indirect effects are identified by subtracting direct effects from total effects. Weighting renders treatment and mediators independent, thereby deactivating indirect pathways of the mediators. This new mediation technique accommodates multiple discrete or continuous mediators. IORW is easily implemented and is appropriate for any standard regression model, including quantile regression and survival analysis. An empirical example is given using data from the Moving to Opportunity (1994-2002) experiment, testing whether neighborhood context mediated the effects of a housing voucher program on obesity. Relevant Stata code (StataCorp LP, College Station, Texas) is provided. © The Author 2015. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

An iteratively reweighted least-squares approach to adaptive robust adjustment of parameters in linear regression models with autoregressive and t-distributed deviations

NASA Astrophysics Data System (ADS)

Kargoll, Boris; Omidalizarandi, Mohammad; Loth, Ina; Paffenholz, Jens-André; Alkhatib, Hamza

2018-03-01

In this paper, we investigate a linear regression time series model of possibly outlier-afflicted observations and autocorrelated random deviations. This colored noise is represented by a covariance-stationary autoregressive (AR) process, in which the independent error components follow a scaled (Student's) t-distribution. This error model allows for the stochastic modeling of multiple outliers and for an adaptive robust maximum likelihood (ML) estimation of the unknown regression and AR coefficients, the scale parameter, and the degree of freedom of the t-distribution. This approach is meant to be an extension of known estimators, which tend to focus only on the regression model, or on the AR error model, or on normally distributed errors. For the purpose of ML estimation, we derive an expectation conditional maximization either algorithm, which leads to an easy-to-implement version of iteratively reweighted least squares. The estimation performance of the algorithm is evaluated via Monte Carlo simulations for a Fourier as well as a spline model in connection with AR colored noise models of different orders and with three different sampling distributions generating the white noise components. We apply the algorithm to a vibration dataset recorded by a high-accuracy, single-axis accelerometer, focusing on the evaluation of the estimated AR colored noise model.

Association between Personality Traits and Sleep Quality in Young Korean Women

PubMed Central

Kim, Han-Na; Cho, Juhee; Chang, Yoosoo; Ryu, Seungho

2015-01-01

Personality is a trait that affects behavior and lifestyle, and sleep quality is an important component of a healthy life. We analyzed the association between personality traits and sleep quality in a cross-section of 1,406 young women (from 18 to 40 years of age) who were not reporting clinically meaningful depression symptoms. Surveys were carried out from December 2011 to February 2012, using the Revised NEO Personality Inventory and the Pittsburgh Sleep Quality Index (PSQI). All analyses were adjusted for demographic and behavioral variables. We considered beta weights, structure coefficients, unique effects, and common effects when evaluating the importance of sleep quality predictors in multiple linear regression models. Neuroticism was the most important contributor to PSQI global scores in the multiple regression models. By contrast, despite being strongly correlated with sleep quality, conscientiousness had a near-zero beta weight in linear regression models, because most variance was shared with other personality traits. However, conscientiousness was the most noteworthy predictor of poor sleep quality status (PSQI≥6) in logistic regression models and individuals high in conscientiousness were least likely to have poor sleep quality, which is consistent with an OR of 0.813, with conscientiousness being protective against poor sleep quality. Personality may be a factor in poor sleep quality and should be considered in sleep interventions targeting young women. PMID:26030141

Determinants of The Grade A Embryos in Infertile Women; Zero-Inflated Regression Model.

PubMed

Almasi-Hashiani, Amir; Ghaheri, Azadeh; Omani Samani, Reza

2017-10-01

In assisted reproductive technology, it is important to choose high quality embryos for embryo transfer. The aim of the present study was to determine the grade A embryo count and factors related to it in infertile women. This historical cohort study included 996 infertile women. The main outcome was the number of grade A embryos. Zero-Inflated Poisson (ZIP) regression and Zero-Inflated Negative Binomial (ZINB) regression were used to model the count data as it contained excessive zeros. Stata software, version 13 (Stata Corp, College Station, TX, USA) was used for all statistical analyses. After adjusting for potential confounders, results from the ZINB model show that for each unit increase in the number 2 pronuclear (2PN) zygotes, we get an increase of 1.45 times as incidence rate ratio (95% confidence interval (CI): 1.23-1.69, P=0.001) in the expected grade A embryo count number, and for each increase in the cleavage day we get a decrease 0.35 times (95% CI: 0.20-0.61, P=0.001) in expected grade A embryo count. There is a significant association between both the number of 2PN zygotes and cleavage day with the number of grade A embryos in both ZINB and ZIP regression models. The estimated coefficients are more plausible than values found in earlier studies using less relevant models. Copyright© by Royan Institute. All rights reserved.

Aldosterone and glomerular filtration--observations in the general population.

PubMed

Hannemann, Anke; Rettig, Rainer; Dittmann, Kathleen; Völzke, Henry; Endlich, Karlhans; Nauck, Matthias; Wallaschofski, Henri

2014-03-10

Increasing evidence suggests that aldosterone promotes renal damage. Since data on the association between aldosterone and renal function in the general population are sparse, we chose to address this issue. We investigated the associations between the plasma aldosterone concentration (PAC) or the aldosterone-to-renin ratio (ARR) and the estimated glomerular filtration rate (eGFR) in a sample of adult men and women from Northeast Germany. A study population of 1921 adult men and women who participated in the first follow-up of the Study of Health in Pomerania was selected. None of the subjects used drugs that alter PAC or ARR. The eGFR was calculated according to the four-variable Modification of Diet in Renal Disease formula. Chronic kidney disease (CKD) was defined as an eGFR < 60 ml/min/1.73 m2. Linear regression models, adjusted for sex, age, waist circumference, diabetes mellitus, smoking status, systolic and diastolic blood pressures, serum triglyceride concentrations and time of blood sampling revealed inverse associations of PAC or ARR with eGFR (ß-coefficient for log-transformed PAC -3.12, p < 0.001; ß-coefficient for log-transformed ARR -3.36, p < 0.001). Logistic regression models revealed increased odds for CKD with increasing PAC (odds ratio for a one standard deviation increase in PAC: 1.35, 95% confidence interval: 1.06-1.71). There was no statistically significant association between ARR and CKD. Our study demonstrates that PAC and ARR are inversely associated with the glomerular filtration rate in the general population.

Biostatistics Series Module 6: Correlation and Linear Regression.

PubMed

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient ( r ). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r 2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation ( y = a + bx ), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous.

Biostatistics Series Module 6: Correlation and Linear Regression

PubMed Central

Hazra, Avijit; Gogtay, Nithya

2016-01-01

Correlation and linear regression are the most commonly used techniques for quantifying the association between two numeric variables. Correlation quantifies the strength of the linear relationship between paired variables, expressing this as a correlation coefficient. If both variables x and y are normally distributed, we calculate Pearson's correlation coefficient (r). If normality assumption is not met for one or both variables in a correlation analysis, a rank correlation coefficient, such as Spearman's rho (ρ) may be calculated. A hypothesis test of correlation tests whether the linear relationship between the two variables holds in the underlying population, in which case it returns a P < 0.05. A 95% confidence interval of the correlation coefficient can also be calculated for an idea of the correlation in the population. The value r2 denotes the proportion of the variability of the dependent variable y that can be attributed to its linear relation with the independent variable x and is called the coefficient of determination. Linear regression is a technique that attempts to link two correlated variables x and y in the form of a mathematical equation (y = a + bx), such that given the value of one variable the other may be predicted. In general, the method of least squares is applied to obtain the equation of the regression line. Correlation and linear regression analysis are based on certain assumptions pertaining to the data sets. If these assumptions are not met, misleading conclusions may be drawn. The first assumption is that of linear relationship between the two variables. A scatter plot is essential before embarking on any correlation-regression analysis to show that this is indeed the case. Outliers or clustering within data sets can distort the correlation coefficient value. Finally, it is vital to remember that though strong correlation can be a pointer toward causation, the two are not synonymous. PMID:27904175

Temperature correction in conductivity measurements

USGS Publications Warehouse

Smith, Stanford H.

1962-01-01

Electrical conductivity has been widely used in freshwater research but usual methods employed by limnologists for converting measurements to conductance at a given temperature have not given uniformly accurate results. The temperature coefficient used to adjust conductivity of natural waters to a given temperature varies depending on the kinds and concentrations of electrolytes, the temperature at the time of measurement, and the temperature to which measurements are being adjusted. The temperature coefficient was found to differ for various lake and stream waters, and showed seasonal changes. High precision can be obtained only by determining temperature coefficients for each water studied. Mean temperature coefficients are given for various temperature ranges that may be used where less precision is required.

Factor Scores, Structure Coefficients, and Communality Coefficients

ERIC Educational Resources Information Center

Goodwyn, Fara

2012-01-01

This paper presents heuristic explanations of factor scores, structure coefficients, and communality coefficients. Common misconceptions regarding these topics are clarified. In addition, (a) the regression (b) Bartlett, (c) Anderson-Rubin, and (d) Thompson methods for calculating factor scores are reviewed. Syntax necessary to execute all four…

Inbreeding among Caribbean Hispanics from the Dominican Republic and its effects on risk of Alzheimer disease.

PubMed

Vardarajan, Badri N; Schaid, Daniel J; Reitz, Christiane; Lantigua, Rafael; Medrano, Martin; Jiménez-Velázquez, Ivonne Z; Lee, Joseph H; Ghani, Mahdi; Rogaeva, Ekaterina; St George-Hyslop, Peter; Mayeux, Richard P

2015-08-01

Inbreeding can be associated with a modification of disease risk due to excess homozygosity of recessive alleles affecting a wide range of phenotypes. We estimated the inbreeding coefficient in Caribbean Hispanics and examined its effects on risk of late-onset Alzheimer disease. The inbreeding coefficient was calculated in 3,392 subjects (1,451 late-onset Alzheimer disease patients and 1,941 age-matched healthy controls) of Caribbean Hispanic ancestry using 177,997 nearly independent single-nucleotide polymorphisms from genome-wide array. The inbreeding coefficient was estimated using the excess homozygosity method with and without adjusting for admixture. The average inbreeding coefficient in Caribbean Hispanics without accounting for admixture was F = 0.018 (±0.048), suggesting a mating equivalent to that of second cousins or second cousins once removed. Adjusting for admixture from three parent populations, the average inbreeding coefficient was found to be 0.0034 (±0.019) or close to third-cousin mating. Inbreeding coefficient was a significant predictor of Alzheimer disease when age, sex, and APOE genotype were used as adjusting covariates (P = 0.03). The average inbreeding coefficient of this population is significantly higher than that of the general Caucasian populations in North America. The high rate of inbreeding resulting in increased frequency of recessive variants is advantageous for the identification of rare variants associated with late-onset Alzheimer disease.Genet Med 17 8, 639-643.

Ensemble of trees approaches to risk adjustment for evaluating a hospital's performance.

PubMed

Liu, Yang; Traskin, Mikhail; Lorch, Scott A; George, Edward I; Small, Dylan

2015-03-01

A commonly used method for evaluating a hospital's performance on an outcome is to compare the hospital's observed outcome rate to the hospital's expected outcome rate given its patient (case) mix and service. The process of calculating the hospital's expected outcome rate given its patient mix and service is called risk adjustment (Iezzoni 1997). Risk adjustment is critical for accurately evaluating and comparing hospitals' performances since we would not want to unfairly penalize a hospital just because it treats sicker patients. The key to risk adjustment is accurately estimating the probability of an Outcome given patient characteristics. For cases with binary outcomes, the method that is commonly used in risk adjustment is logistic regression. In this paper, we consider ensemble of trees methods as alternatives for risk adjustment, including random forests and Bayesian additive regression trees (BART). Both random forests and BART are modern machine learning methods that have been shown recently to have excellent performance for prediction of outcomes in many settings. We apply these methods to carry out risk adjustment for the performance of neonatal intensive care units (NICU). We show that these ensemble of trees methods outperform logistic regression in predicting mortality among babies treated in NICU, and provide a superior method of risk adjustment compared to logistic regression.

Multiple linear regression analysis

NASA Technical Reports Server (NTRS)

Edwards, T. R.

1980-01-01

Program rapidly selects best-suited set of coefficients. User supplies only vectors of independent and dependent data and specifies confidence level required. Program uses stepwise statistical procedure for relating minimal set of variables to set of observations; final regression contains only most statistically significant coefficients. Program is written in FORTRAN IV for batch execution and has been implemented on NOVA 1200.

Life-space mobility and social support in elderly adults with orthopaedic disorders.

PubMed

Suzuki, Tomoko; Kitaike, Tadashi; Ikezaki, Sumie

2014-03-01

The purpose of this cross-sectional survey was to explore relationships between life-space mobility and the related factors in elderly Japanese people who attend orthopaedic clinics. The study measures included surveys of life-space mobility (Life-space Assessment (LSA) score), social support (social network diversity and social ties), physical ability (instrumental self-maintenance, intellectual activity, social role), orthopaedic factors (diseases and symptoms) and demographic information. The questionnaire was distributed to 156 subjects; 152 persons responded, yielding 140 valid responses. Mean age of the sample was 76.0 ± 6.4 (range, 65-96 years), with 57.9% women (n = 81). In a multiple regression analysis, the six factors were significantly associated with LSA. Standardized partial regression coefficients (β) were gender (0.342), instrumental self-maintenance (0.297), social network diversity (0.217), age (-0.170), difficulty of motion (-0.156) and intellectual activity (0.150), with an adjusted R(2) = 0.488. These results suggest that outpatient health-care providers need to intervene in not only addressing orthopaedic factors but also promoting social support among elderly Japanese. © 2014 Wiley Publishing Asia Pty Ltd.

Intra-individual reaction time variability and all-cause mortality over 17 years: a community-based cohort study.

PubMed

Batterham, Philip J; Bunce, David; Mackinnon, Andrew J; Christensen, Helen

2014-01-01

very few studies have examined the association between intra-individual reaction time variability and subsequent mortality. Furthermore, the ability of simple measures of variability to predict mortality has not been compared with more complex measures. a prospective cohort study of 896 community-based Australian adults aged 70+ were interviewed up to four times from 1990 to 2002, with vital status assessed until June 2007. From this cohort, 770-790 participants were included in Cox proportional hazards regression models of survival. Vital status and time in study were used to conduct survival analyses. The mean reaction time and three measures of intra-individual reaction time variability were calculated separately across 20 trials of simple and choice reaction time tasks. Models were adjusted for a range of demographic, physical health and mental health measures. greater intra-individual simple reaction time variability, as assessed by the raw standard deviation (raw SD), coefficient of variation (CV) or the intra-individual standard deviation (ISD), was strongly associated with an increased hazard of all-cause mortality in adjusted Cox regression models. The mean reaction time had no significant association with mortality. intra-individual variability in simple reaction time appears to have a robust association with mortality over 17 years. Health professionals such as neuropsychologists may benefit in their detection of neuropathology by supplementing neuropsychiatric testing with the straightforward process of testing simple reaction time and calculating raw SD or CV.

Mortality prediction of head Abbreviated Injury Score and Glasgow Coma Scale: analysis of 7,764 head injuries.

PubMed

Demetriades, Demetrios; Kuncir, Eric; Murray, James; Velmahos, George C; Rhee, Peter; Chan, Linda

2004-08-01

We assessed the prognostic value and limitations of Glasgow Coma Scale (GCS) and head Abbreviated Injury Score (AIS) and correlated head AIS with GCS. We studied 7,764 patients with head injuries. Bivariate analysis was performed to examine the relationship of GCS, head AIS, age, gender, and mechanism of injury with mortality. Stepwise logistic regression analysis was used to identify the independent risk factors associated with mortality. The overall mortality in the group of head injury patients with no other major extracranial injuries and no hypotension on admission was 9.3%. Logistic regression analysis identified head AIS, GCS, age, and mechanism of injury as significant independent risk factors of death. The prognostic value of GCS and head AIS was significantly affected by the mechanism of injury and the age of the patient. Patients with similar GCS or head AIS but different mechanisms of injury or ages had significantly different outcomes. The adjusted odds ratio of death in penetrating trauma was 5.2 (3.9, 7.0), p < 0.0001, and in the age group > or = 55 years the adjusted odds ratio was 3.4 (2.6, 4.6), p < 0.0001. There was no correlation between head AIS and GCS (correlation coefficient -0.31). Mechanism of injury and age have a major effect in the predictive value of GCS and head AIS. There is no good correlation between GCS and head AIS.

Abdominal Subcutaneous Fat: A Favorable or Nonfunctional Fat Depot for Glucose Metabolism in Chinese Adults?

PubMed

Hou, Xuhong; Chen, Peizhu; Hu, Gang; Wei, Li; Jiao, Lei; Wang, Hongmei; Liang, Yebei; Bao, Yuqian; Jia, Weiping

2018-06-01

The objective of this study was to assess the associations of abdominal visceral and subcutaneous adipose tissue with blood glucose and beta-cell function. In this study, 11,223 participants without known diabetes were selected for this cross-sectional analysis. Visceral and subcutaneous fat area (VFA and SFA) were measured by magnetic resonance imaging. An oral glucose tolerance test was conducted, and beta-cell function was evaluated. Men had significantly larger VFA but smaller SFA than women. After controlling for age, linear regression showed that SFA was adversely associated with 0-minute, 30-minute, and 2-hour plasma glucose (PG) and early-, first- and second-phase disposition indices (DIs). After further adjustment for BMI and VFA, some associations of SFA with PG indices and DIs disappeared, while the other associations became significantly weaker in men (2-hour PG: 0.05 and DI 2nd : -0.05) or were reversed in women (0-minute, 30-minute, and 2-hour PG: from -0.07 to -0.04; DI 1st : 0.04, P < 0.05). After adjustment for age, BMI, and SFA, VFA was significantly and adversely associated with PG indices and DIs, with the largest standardized regression coefficients with 2-hour PG. The associations of SFA with blood glucose and beta-cell function were clinically insignificant in Chinese adults. VFA had the strongest association with 2-hour PG. © 2018 The Obesity Society.

Testing for gene-environment interaction under exposure misspecification.

PubMed

Sun, Ryan; Carroll, Raymond J; Christiani, David C; Lin, Xihong

2017-11-09

Complex interplay between genetic and environmental factors characterizes the etiology of many diseases. Modeling gene-environment (GxE) interactions is often challenged by the unknown functional form of the environment term in the true data-generating mechanism. We study the impact of misspecification of the environmental exposure effect on inference for the GxE interaction term in linear and logistic regression models. We first examine the asymptotic bias of the GxE interaction regression coefficient, allowing for confounders as well as arbitrary misspecification of the exposure and confounder effects. For linear regression, we show that under gene-environment independence and some confounder-dependent conditions, when the environment effect is misspecified, the regression coefficient of the GxE interaction can be unbiased. However, inference on the GxE interaction is still often incorrect. In logistic regression, we show that the regression coefficient is generally biased if the genetic factor is associated with the outcome directly or indirectly. Further, we show that the standard robust sandwich variance estimator for the GxE interaction does not perform well in practical GxE studies, and we provide an alternative testing procedure that has better finite sample properties. © 2017, The International Biometric Society.

The role of muscle mass and body fat on disability among older adults: A cross-national analysis.

PubMed

Tyrovolas, Stefanos; Koyanagi, Ai; Olaya, Beatriz; Ayuso-Mateos, Jose Luis; Miret, Marta; Chatterji, Somnath; Tobiasz-Adamczyk, Beata; Koskinen, Seppo; Leonardi, Matilde; Haro, Josep Maria

2015-09-01

The aim of this study was to evaluate the association of sarcopenia and sarcopenic obesity with disability among older adults (≥65years old) in nine high-, middle- and low-income countries from Asia, Africa, Europe, and Latin America. Data were available for 53,289 people aged ≥18years who participated in the Collaborative Research on Ageing in Europe (COURAGE) survey conducted in Finland, Poland, and Spain, and the WHO Study on global AGEing and adult health (SAGE) survey conducted in China, Ghana, India, Mexico, Russia, and South Africa, between 2007 and 2012. Skeletal muscle mass, skeletal muscle mass index, and percent body fat were calculated with specific population formulas. Sarcopenia and sarcopenic obesity were defined by specific cut-offs used in previous studies. Disability was assessed with the WHODAS 2.0 score (range 0-100) with higher scores corresponding to higher levels of disability. Multivariable linear regression analysis was conducted with disability as the outcome. The analytical sample consisted of 18,363 people (males; n=8116, females; n=10247) aged ≥65years with mean (SD) age 72.9 (11.1) years. In the fully-adjusted overall analysis, sarcopenic obesity was associated with greater levels of disability [b-coefficient 3.01 (95% CI 1.14-4.88)]. In terms of country-wise analyses, sarcopenia was associated with higher WHODAS 2.0 scores in China [b-coefficient 4.56 (95% CI: 3.25-5.87)], Poland [b-coefficient 6.66 (95% CI: 2.17-11.14)], Russia [b-coefficient 5.60 (95% CI: 2.03-9.16)], and South Africa [b-coefficient 7.75 (95% CI: 1.56-13.94)]. Prevention of muscle mass decline may contribute to reducing the global burden of disability. Copyright © 2015 Elsevier Inc. All rights reserved.

Exposure measurement error in PM2.5 health effects studies: A pooled analysis of eight personal exposure validation studies

PubMed Central

2014-01-01

Background Exposure measurement error is a concern in long-term PM2.5 health studies using ambient concentrations as exposures. We assessed error magnitude by estimating calibration coefficients as the association between personal PM2.5 exposures from validation studies and typically available surrogate exposures. Methods Daily personal and ambient PM2.5, and when available sulfate, measurements were compiled from nine cities, over 2 to 12 days. True exposure was defined as personal exposure to PM2.5 of ambient origin. Since PM2.5 of ambient origin could only be determined for five cities, personal exposure to total PM2.5 was also considered. Surrogate exposures were estimated as ambient PM2.5 at the nearest monitor or predicted outside subjects’ homes. We estimated calibration coefficients by regressing true on surrogate exposures in random effects models. Results When monthly-averaged personal PM2.5 of ambient origin was used as the true exposure, calibration coefficients equaled 0.31 (95% CI:0.14, 0.47) for nearest monitor and 0.54 (95% CI:0.42, 0.65) for outdoor home predictions. Between-city heterogeneity was not found for outdoor home PM2.5 for either true exposure. Heterogeneity was significant for nearest monitor PM2.5, for both true exposures, but not after adjusting for city-average motor vehicle number for total personal PM2.5. Conclusions Calibration coefficients were <1, consistent with previously reported chronic health risks using nearest monitor exposures being under-estimated when ambient concentrations are the exposure of interest. Calibration coefficients were closer to 1 for outdoor home predictions, likely reflecting less spatial error. Further research is needed to determine how our findings can be incorporated in future health studies. PMID:24410940

On Using the Average Intercorrelation Among Predictor Variables and Eigenvector Orientation to Choose a Regression Solution.

ERIC Educational Resources Information Center

Mugrage, Beverly; And Others

Three ridge regression solutions are compared with ordinary least squares regression and with principal components regression using all components. Ridge regression, particularly the Lawless-Wang solution, out-performed ordinary least squares regression and the principal components solution on the criteria of stability of coefficient and closeness…

Building a new predictor for multiple linear regression technique-based corrective maintenance turnaround time.

PubMed

Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa

2008-01-01

This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.

Evaluation of the magnitude and frequency of floods in urban watersheds in Phoenix and Tucson, Arizona

USGS Publications Warehouse

Kennedy, Jeffrey R.; Paretti, Nicholas V.

2014-01-01

Flooding in urban areas routinely causes severe damage to property and often results in loss of life. To investigate the effect of urbanization on the magnitude and frequency of flood peaks, a flood frequency analysis was carried out using data from urbanized streamgaging stations in Phoenix and Tucson, Arizona. Flood peaks at each station were predicted using the log-Pearson Type III distribution, fitted using the expected moments algorithm and the multiple Grubbs-Beck low outlier test. The station estimates were then compared to flood peaks estimated by rural-regression equations for Arizona, and to flood peaks adjusted for urbanization using a previously developed procedure for adjusting U.S. Geological Survey rural regression peak discharges in an urban setting. Only smaller, more common flood peaks at the 50-, 20-, 10-, and 4-percent annual exceedance probabilities (AEPs) demonstrate any increase in magnitude as a result of urbanization; the 1-, 0.5-, and 0.2-percent AEP flood estimates are predicted without bias by the rural-regression equations. Percent imperviousness was determined not to account for the difference in estimated flood peaks between stations, either when adjusting the rural-regression equations or when deriving urban-regression equations to predict flood peaks directly from basin characteristics. Comparison with urban adjustment equations indicates that flood peaks are systematically overestimated if the rural-regression-estimated flood peaks are adjusted upward to account for urbanization. At nearly every streamgaging station in the analysis, adjusted rural-regression estimates were greater than the estimates derived using station data. One likely reason for the lack of increase in flood peaks with urbanization is the presence of significant stormwater retention and detention structures within the watershed used in the study.

[Individual and contextual determinants of the prevalence of untreated caries in Brazil].

PubMed

Frias, Antônio Carlos; Antunes, José Leopoldo Ferreira; Junqueira, Simone Rennó; Narvai, Paulo Capel

2007-10-01

To describe the prevalence of untreated caries among adolescents in Brazil and to analyze the association between caries and individual and contextual factors in the municipalities where these adolescents live. A Ministry of Health database (projeto SB-Brasil) provided health records on 16 833 adolescents from 15-19 years of age. The study variable used was the presence of at least one permanent tooth having been lost to caries. The individual variables considered were: sex, ethnic group, living in an urban versus a rural area, and being a student or not. Contextual variables related to the municipality were: municipal human development index (MHDI), proportion of households connected to the water system, and water fluoridation for 5 years or more. Multilevel logistic regression analysis was carried out to adjust the outcome to the individual and contextual variables. Individual determinants related to a higher probability of untreated caries were: the ethnic group described as "black or brown," (adjusted odds ratio, OR(adjust) = 1.79; 1.68 to 1.92); and living in a rural area (OR(adjust) = 1.31; 1.19 to 1.45). Being a student was identified as a protective factor (OR(adjust) = 0.67; 0.62 to 0.73). Secondary variables identified as contextual determinants of caries were MHDI (adjusted coefficient beta = -0.213), water fluoridation (beta = -0.201), and households connected to the water system (beta = -0.197). The results show inequalities in the distribution of health services in the various Brazilian regions, and suggest that inequalities may also be present in the effectiveness of the services provided. Policies to increase access to fluoride-treated water and school enrollment may contribute to preventing caries in adolescents.

The microcomputer scientific software series 2: general linear model--regression.

Treesearch

Harold M. Rauscher

1983-01-01

The general linear model regression (GLMR) program provides the microcomputer user with a sophisticated regression analysis capability. The output provides a regression ANOVA table, estimators of the regression model coefficients, their confidence intervals, confidence intervals around the predicted Y-values, residuals for plotting, a check for multicollinearity, a...

Difficulties with Regression Analysis of Age-Adjusted Rates.

DTIC Science & Technology

1982-09-01

variables used in those analyses, such as death rates in various states, have been age adjusted, whereas the predictor variables have not been age adjusted...The use of crude state death rates as the outcome variable with crude covariates and age as predictors can avoid the problem, at least under some...should be regressed on age-adjusted exposure Z+B+ Although age-specific death rates , Yas+’ may be available, it is often difficult to obtain age

Simulation-based coefficients for adjusting climate impact on energy consumption of commercial buildings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wang, Na; Makhmalbaf, Atefe; Srivastava, Viraj

This paper presents a new technique for and the results of normalizing building energy consumption to enable a fair comparison among various types of buildings located near different weather stations across the U.S. The method was developed for the U.S. Building Energy Asset Score, a whole-building energy efficiency rating system focusing on building envelope, mechanical systems, and lighting systems. The Asset Score is calculated based on simulated energy use under standard operating conditions. Existing weather normalization methods such as those based on heating and cooling degrees days are not robust enough to adjust all climatic factors such as humidity andmore » solar radiation. In this work, over 1000 sets of climate coefficients were developed to separately adjust building heating, cooling, and fan energy use at each weather station in the United States. This paper also presents a robust, standardized weather station mapping based on climate similarity rather than choosing the closest weather station. This proposed simulated-based climate adjustment was validated through testing on several hundreds of thousands of modeled buildings. Results indicated the developed climate coefficients can isolate and adjust for the impacts of local climate for asset rating.« less

Innovating patient care delivery: DSRIP's interrupted time series analysis paradigm.

PubMed

Shenoy, Amrita G; Begley, Charles E; Revere, Lee; Linder, Stephen H; Daiger, Stephen P

2017-12-08

Adoption of Medicaid Section 1115 waiver is one of the many ways of innovating healthcare delivery system. The Delivery System Reform Incentive Payment (DSRIP) pool, one of the two funding pools of the waiver has four categories viz. infrastructure development, program innovation and redesign, quality improvement reporting and lastly, bringing about population health improvement. A metric of the fourth category, preventable hospitalization (PH) rate was analyzed in the context of eight conditions for two time periods, pre-reporting years (2010-2012) and post-reporting years (2013-2015) for two hospital cohorts, DSRIP participating and non-participating hospitals. The study explains how DSRIP impacted Preventable Hospitalization (PH) rates of eight conditions for both hospital cohorts within two time periods. Eight PH rates were regressed as the dependent variable with time, intervention and post-DSRIP Intervention as independent variables. PH rates of eight conditions were then consolidated into one rate for regressing with the above independent variables to evaluate overall impact of DSRIP. An interrupted time series regression was performed after accounting for auto-correlation, stationarity and seasonality in the dataset. In the individual regression model, PH rates showed statistically significant coefficients for seven out of eight conditions in DSRIP participating hospitals. In the combined regression model, the coefficient of the PH rate showed a statistically significant decrease with negative p-values for regression coefficients in DSRIP participating hospitals compared to positive/increased p-values for regression coefficients in DSRIP non-participating hospitals. Several macro- and micro-level factors may have likely contributed DSRIP hospitals outperforming DSRIP non-participating hospitals. Healthcare organization/provider collaboration, support from healthcare professionals, DSRIP's design, state reimbursement and coordination in care delivery methods may have led to likely success of DSRIP. IV, a retrospective cohort study based on longitudinal data. Copyright © 2017 Elsevier Inc. All rights reserved.

New insights into scaling of fat-free mass to height across children and adults.

PubMed

Wang, Zimian; Zhang, Junyi; Ying, Zhiliang; Heymsfield, Steven B

2012-01-01

Forbes expressed fat-free mass (FFM, in kg) as the cube of height (H, in m): FFM = 10.3 × H(3). Our objective is to examine the potential influence of gender and population ancestry on the association between FFM and height. This is a cross-sectional analysis involving an existing dataset of 279 healthy subjects (155 males and 124 females) with age 5-59 years and body mass index (BMI) 14-28 kg/m(2). FFM was measured by a four-component model as the criterion. Nonlinear regression models were fitted: FFM = 10.8 × H(2.95) for the males and FFM = 10.1 × H(2.90) for the females. The 95% confidence intervals for the exponential coefficients were (2.83, 3.07) for the males and (2.72, 3.08) for the females, both containing hypothesized value 3.0. Population ancestry adjustment was considered in the H-FFM model. The coefficient of the H-FFM model for male Asians is smaller than that for male Caucasians (P = 0.006), while there is no statistically significant difference among African-Americans, Caucasians and Hispanics: 10.6 for the males (10.1 for Asians, 10.8 for African-Americans, 10.7 for Caucasians and 10.4 for Hispanics) and 9.6 for the females (9.3 for Asians, 9.8 for African-Americans, 9.6 for Caucasians and 9.5 for Hispanics). Age adjustment was unnecessary for the coefficient of the H-FFM model. Height is the most important factor contributing to the magnitude of FFM across most of the lifespan, though both gender and ancestry effects are significant in the H-FFM model. The proposed H-FFM model can be further used to develop a mechanistic model to explain why population ancestry, gender and age influence the associations between BMI and %Fat. Copyright © 2012 Wiley Periodicals, Inc.

Adiposity among 132 479 UK Biobank participants; contribution of sugar intake vs other macronutrients.

PubMed

Anderson, J J; Celis-Morales, C A; Mackay, D F; Iliodromiti, S; Lyall, D M; Sattar, N; Gill, Jmr; Pell, J P

2017-04-01

Policy makers are being encouraged to specifically target sugar intake in order to combat obesity. We examined the extent to which sugar, relative to other macronutrients, was associated with adiposity. We used baseline data from UK Biobank to examine the associations between energy intake (total and individual macronutrients) and adiposity [body mass index (BMI), percentage body fat and waist circumference]. Linear regression models were conducted univariately and adjusted for age, sex, ethnicity and physical activity. Among 132 479 participants, 66.3% of men and 51.8% of women were overweight/obese. There was a weak correlation (r = 0.24) between energy from sugar and fat; 13% of those in the highest quintile for sugar were in the lowest for fat, and vice versa. Compared with normal BMI, obese participants had 11.5% higher total energy intake and 14.6%, 13.8%, 9.5% and 4.7% higher intake from fat, protein, starch and sugar, respectively. Hence, the proportion of energy derived from fat was higher (34.3% vs 33.4%, P < 0.001) but from sugar was lower (22.0% vs 23.4%, P < 0.001). BMI was more strongly associated with total energy [coefficient 2.47, 95% confidence interval (CI) 2.36-2.55] and energy from fat (coefficient 1.96, 95% CI 1.91-2.06) than sugar (coefficient 0.48, 95% CI 0.41-0.55). The latter became negative after adjustment for total energy. Fat is the largest contributor to overall energy. The proportion of energy from fat in the diet, but not sugar, is higher among overweight/obese individuals. Focusing public health messages on sugar may mislead on the need to reduce fat and overall energy consumption. © The Author 2016; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association

Case-mix fails to explain variation in mastectomy rates: management of screen-detected breast cancer in a UK region 1997–2003

PubMed Central

Caldon, L J M; Walters, S J; Reed, J A; Murphy, A; Worley, A; Reed, M W R

2004-01-01

Wide variation in the surgical management of breast cancer exists at hospital, regional, national and international level. To demonstrate whether variation in surgical practice observed at aggregate level between breast units persists following adjustment for case-mix, individual patient-level data from the Trent Breast Screening Programme Quality Assurance database (1997–2003) was analysed. Expected case-mix adjusted mastectomy rates were derived by logistic regression using the variables tumour size, site and grade, patient age and year of presentation, employing the region's overall case-mix adjusted practice as the reference population. The region's 11 breast screening units detected 5109 (3989 invasive) surgically managed primary breast cancers over the 6-year period. A total of 1828 mastectomies (Mx) were performed (Mx rate 35.8%, 95% confidence interval: 34.5–37.1%). Significant variation in mastectomy rates were observed between units (range 25–45%, P<0.0001), and persists following case-mix adjustment (P<0.0001). Two-fold variation in observed to expected unit mastectomy rate coefficient is demonstrated overall (range 0.66–1.36), increasing to almost four-fold variation in cancers less than 15 mm diameter (range 0.55–1.95). Significant variation in surgery for screen-detected primary breast cancer is not explained by case-mix. Further research is required to investigate potential patient and professional causative factors. PMID:15611797

Short-term blood pressure variability over 24 h and target organ damage in middle-aged men and women.

PubMed

Madden, J M; O'Flynn, A M; Dolan, E; Fitzgerald, A P; Kearney, P M

2015-12-01

Blood pressure variability (BPV) has been associated with cardiovascular events; however, the prognostic significance of short-term BPV remains uncertain. As uncertainty also remains as to which measure of variability most accurately describes short-term BPV, this study explores different indices and investigates their relationship with subclinical target organ damage (TOD). We used data from the Mitchelstown Study, a cross-sectional study of Irish adults aged 47-73 years (n=2047). A subsample (1207) underwent 24-h ambulatory BP monitoring (ABPM). As measures of short-term BPV, we estimated the s.d., weighted s.d. (wSD), coefficient of variation (CV) and average real variability (ARV). TOD was documented by microalbuminuria and electrocardiogram (ECG) left ventricular hypertrophy (LVH). There was no association found between any measure of BPV and LVH in both unadjusted and fully adjusted logistic regression models. Similar analysis found that ARV (24 h, day and night), s.d. (day and night) and wSD were all univariately associated with microalbuminuria and remained associated after adjustment for age, gender, smoking, body mass index (BMI), diabetes and antihypertensive treatment. However, when the models were further adjusted for the mean BP the association did not persist for all indices. Our findings illustrate choosing the appropriate summary measure, which accurately captures that short-term BPV is difficult. Despite discrepancies in values between the different measures, there was no association between any indexes of variability with TOD measures after adjustment for the mean BP.

Household water treatment in developing countries: comparing different intervention types using meta-regression.

PubMed

Hunter, Paul R

2009-12-01

Household water treatment (HWT) is being widely promoted as an appropriate intervention for reducing the burden of waterborne disease in poor communities in developing countries. A recent study has raised concerns about the effectiveness of HWT, in part because of concerns over the lack of blinding and in part because of considerable heterogeneity in the reported effectiveness of randomized controlled trials. This study set out to attempt to investigate the causes of this heterogeneity and so identify factors associated with good health gains. Studies identified in an earlier systematic review and meta-analysis were supplemented with more recently published randomized controlled trials. A total of 28 separate studies of randomized controlled trials of HWT with 39 intervention arms were included in the analysis. Heterogeneity was studied using the "metareg" command in Stata. Initial analyses with single candidate predictors were undertaken and all variables significant at the P < 0.2 level were included in a final regression model. Further analyses were done to estimate the effect of the interventions over time by MonteCarlo modeling using @Risk and the parameter estimates from the final regression model. The overall effect size of all unblinded studies was relative risk = 0.56 (95% confidence intervals 0.51-0.63), but after adjusting for bias due to lack of blinding the effect size was much lower (RR = 0.85, 95% CI = 0.76-0.97). Four main variables were significant predictors of effectiveness of intervention in a multipredictor meta regression model: Log duration of study follow-up (regression coefficient of log effect size = 0.186, standard error (SE) = 0.072), whether or not the study was blinded (coefficient 0.251, SE 0.066) and being conducted in an emergency setting (coefficient -0.351, SE 0.076) were all significant predictors of effect size in the final model. Compared to the ceramic filter all other interventions were much less effective (Biosand 0.247, 0.073; chlorine and safe waste storage 0.295, 0.061; combined coagulant-chlorine 0.2349, 0.067; SODIS 0.302, 0.068). A Monte Carlo model predicted that over 12 months ceramic filters were likely to be still effective at reducing disease, whereas SODIS, chlorination, and coagulation-chlorination had little if any benefit. Indeed these three interventions are predicted to have the same or less effect than what may be expected due purely to reporting bias in unblinded studies With the currently available evidence ceramic filters are the most effective form of HWT in the longterm, disinfection-only interventions including SODIS appear to have poor if any longterm public health benefit.

Regression modeling plan for 29 biochemical indicators of diet and nutrition measured in NHANES 2003-2006.

PubMed

Sternberg, Maya R; Schleicher, Rosemary L; Pfeiffer, Christine M

2013-06-01

The collection of articles in this supplement issue provides insight into the association of various covariates with concentrations of biochemical indicators of diet and nutrition (biomarkers), beyond age, race, and sex, using linear regression. We studied 10 specific sociodemographic and lifestyle covariates in combination with 29 biomarkers from NHANES 2003-2006 for persons aged ≥ 20 y. The covariates were organized into 2 sets or "chunks": sociodemographic (age, sex, race-ethnicity, education, and income) and lifestyle (dietary supplement use, smoking, alcohol consumption, BMI, and physical activity) and fit in hierarchical fashion by using each category or set of related variables to determine how covariates, jointly, are related to biomarker concentrations. In contrast to many regression modeling applications, all variables were retained in a full regression model regardless of significance to preserve the interpretation of the statistical properties of β coefficients, P values, and CIs and to keep the interpretation consistent across a set of biomarkers. The variables were preselected before data analysis, and the data analysis plan was designed at the outset to minimize the reporting of false-positive findings by limiting the amount of preliminary hypothesis testing. Although we generally found that demographic differences seen in biomarkers were over- or underestimated when ignoring other key covariates, the demographic differences generally remained significant after adjusting for sociodemographic and lifestyle variables. These articles are intended to provide a foundation to researchers to help them generate hypotheses for future studies or data analyses and/or develop predictive regression models using the wealth of NHANES data.

The use of regression analysis in determining reference intervals for low hematocrit and thrombocyte count in multiple electrode aggregometry and platelet function analyzer 100 testing of platelet function.

PubMed

Kuiper, Gerhardus J A J M; Houben, Rik; Wetzels, Rick J H; Verhezen, Paul W M; Oerle, Rene van; Ten Cate, Hugo; Henskens, Yvonne M C; Lancé, Marcus D

2017-11-01

Low platelet counts and hematocrit levels hinder whole blood point-of-care testing of platelet function. Thus far, no reference ranges for MEA (multiple electrode aggregometry) and PFA-100 (platelet function analyzer 100) devices exist for low ranges. Through dilution methods of volunteer whole blood, platelet function at low ranges of platelet count and hematocrit levels was assessed on MEA for four agonists and for PFA-100 in two cartridges. Using (multiple) regression analysis, 95% reference intervals were computed for these low ranges. Low platelet counts affected MEA in a positive correlation (all agonists showed r 2 ≥ 0.75) and PFA-100 in an inverse correlation (closure times were prolonged with lower platelet counts). Lowered hematocrit did not affect MEA testing, except for arachidonic acid activation (ASPI), which showed a weak positive correlation (r 2 = 0.14). Closure time on PFA-100 testing was inversely correlated with hematocrit for both cartridges. Regression analysis revealed different 95% reference intervals in comparison with originally established intervals for both MEA and PFA-100 in low platelet or hematocrit conditions. Multiple regression analysis of ASPI and both tests on the PFA-100 for combined low platelet and hematocrit conditions revealed that only PFA-100 testing should be adjusted for both thrombocytopenia and anemia. 95% reference intervals were calculated using multiple regression analysis. However, coefficients of determination of PFA-100 were poor, and some variance remained unexplained. Thus, in this pilot study using (multiple) regression analysis, we could establish reference intervals of platelet function in anemia and thrombocytopenia conditions on PFA-100 and in thrombocytopenia conditions on MEA.

Comparison between light scattering and gravimetric samplers for PM10 mass concentration in poultry and pig houses

NASA Astrophysics Data System (ADS)

Cambra-López, María; Winkel, Albert; Mosquera, Julio; Ogink, Nico W. M.; Aarnink, André J. A.

2015-06-01

The objective of this study was to compare co-located real-time light scattering devices and equivalent gravimetric samplers in poultry and pig houses for PM10 mass concentration, and to develop animal-specific calibration factors for light scattering samplers. These results will contribute to evaluate the comparability of different sampling instruments for PM10 concentrations. Paired DustTrak light scattering device (DustTrak aerosol monitor, TSI, U.S.) and PM10 gravimetric cyclone sampler were used for measuring PM10 mass concentrations during 24 h periods (from noon to noon) inside animal houses. Sampling was conducted in 32 animal houses in the Netherlands, including broilers, broiler breeders, layers in floor and in aviary system, turkeys, piglets, growing-finishing pigs in traditional and low emission housing with dry and liquid feed, and sows in individual and group housing. A total of 119 pairs of 24 h measurements (55 for poultry and 64 for pigs) were recorded and analyzed using linear regression analysis. Deviations between samplers were calculated and discussed. In poultry, cyclone sampler and DustTrak data fitted well to a linear regression, with a regression coefficient equal to 0.41, an intercept of 0.16 mg m-3 and a correlation coefficient of 0.91 (excluding turkeys). Results in turkeys showed a regression coefficient equal to 1.1 (P = 0.49), an intercept of 0.06 mg m-3 (P < 0.0001) and a correlation coefficient of 0.98. In pigs, we found a regression coefficient equal to 0.61, an intercept of 0.05 mg m-3 and a correlation coefficient of 0.84. Measured PM10 concentrations using DustTraks were clearly underestimated (approx. by a factor 2) in both poultry and pig housing systems compared with cyclone pre-separators. Absolute, relative, and random deviations increased with concentration. DustTrak light scattering devices should be self-calibrated to investigate PM10 mass concentrations accurately in animal houses. We recommend linear regression equations as animal-specific calibration factors for DustTraks instead of manufacturer calibration factors, especially in heavily dusty environments such as animal houses.

Poor methodological quality and reporting standards of systematic reviews in burn care management.

PubMed

Wasiak, Jason; Tyack, Zephanie; Ware, Robert; Goodwin, Nicholas; Faggion, Clovis M

2017-10-01

The methodological and reporting quality of burn-specific systematic reviews has not been established. The aim of this study was to evaluate the methodological quality of systematic reviews in burn care management. Computerised searches were performed in Ovid MEDLINE, Ovid EMBASE and The Cochrane Library through to February 2016 for systematic reviews relevant to burn care using medical subject and free-text terms such as 'burn', 'systematic review' or 'meta-analysis'. Additional studies were identified by hand-searching five discipline-specific journals. Two authors independently screened papers, extracted and evaluated methodological quality using the 11-item A Measurement Tool to Assess Systematic Reviews (AMSTAR) tool and reporting quality using the 27-item Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. Characteristics of systematic reviews associated with methodological and reporting quality were identified. Descriptive statistics and linear regression identified features associated with improved methodological quality. A total of 60 systematic reviews met the inclusion criteria. Six of the 11 AMSTAR items reporting on 'a priori' design, duplicate study selection, grey literature, included/excluded studies, publication bias and conflict of interest were reported in less than 50% of the systematic reviews. Of the 27 items listed for PRISMA, 13 items reporting on introduction, methods, results and the discussion were addressed in less than 50% of systematic reviews. Multivariable analyses showed that systematic reviews associated with higher methodological or reporting quality incorporated a meta-analysis (AMSTAR regression coefficient 2.1; 95% CI: 1.1, 3.1; PRISMA regression coefficient 6·3; 95% CI: 3·8, 8·7) were published in the Cochrane library (AMSTAR regression coefficient 2·9; 95% CI: 1·6, 4·2; PRISMA regression coefficient 6·1; 95% CI: 3·1, 9·2) and included a randomised control trial (AMSTAR regression coefficient 1·4; 95%CI: 0·4, 2·4; PRISMA regression coefficient 3·4; 95% CI: 0·9, 5·8). The methodological and reporting quality of systematic reviews in burn care requires further improvement with stricter adherence by authors to the PRISMA checklist and AMSTAR tool. © 2016 Medicalhelplines.com Inc and John Wiley & Sons Ltd.

Body image, body dissatisfaction and weight status in South Asian children: a cross-sectional study.

PubMed

Pallan, Miranda J; Hiam, Lucinda C; Duda, Joan L; Adab, Peymane

2011-01-09

Childhood obesity is a continuing problem in the UK and South Asian children represent a group that are particularly vulnerable to its health consequences. The relationship between body dissatisfaction and obesity is well documented in older children and adults, but is less clear in young children, particularly South Asians. A better understanding of this relationship in young South Asian children will inform the design and delivery of obesity intervention programmes. The aim of this study is to describe body image size perception and dissatisfaction, and their relationship to weight status in primary school aged UK South Asian children. Objective measures of height and weight were undertaken on 574 predominantly South Asian children aged 5-7 (296 boys and 278 girls). BMI z-scores, and weight status (underweight, healthy weight, overweight or obese) were calculated based on the UK 1990 BMI reference charts. Figure rating scales were used to assess perceived body image size (asking children to identify their perceived body size) and dissatisfaction (difference between perceived current and ideal body size). The relationship between these and weight status were examined using multivariate analyses. Perceived body image size was positively associated with weight status (partial regression coefficient for overweight/obese vs. non-overweight/obese was 0.63 (95% CI 0.26-0.99) and for BMI z-score was 0.21 (95% CI 0.10-0.31), adjusted for sex, age and ethnicity). Body dissatisfaction was also associated with weight status, with overweight and obese children more likely to select thinner ideal body size than healthy weight children (adjusted partial regression coefficient for overweight/obese vs. non-overweight/obese was 1.47 (95% CI 0.99-1.96) and for BMI z-score was 0.54 (95% CI 0.40-0.67)). Awareness of body image size and increasing body dissatisfaction with higher weight status is established at a young age in this population. This needs to be considered when designing interventions to reduce obesity in young children, in terms of both benefits and harms.

Trends in inequalities in utilization of reproductive health services from 2000 to 2011 in Vietnam

PubMed Central

Duc, Nguyen Huu Chau; Nakamura, Keiko; Kizuki, Masashi; Seino, Kaoruko; Rahman, Mosiur

2015-01-01

Objective: This study aimed to examine changes in utilization of reproductive health services by wealth status from 2000 to 2011 in Vietnam. Methods: Data from the Vietnam Multiple Indicator Cluster Surveys in 2000, 2006, and 2011 were used. The subjects were 550, 1023, and 1363 women, respectively, aged between 15 and 49 years who had given birth in the previous one or two years. The wealth index, a composite measure of a household’s ownership of selected assets, materials used for housing construction, and types of water access and sanitation facilities, was used as a measure of wealth status. Main utilization indicators were utilization of antenatal care services, receipt of a tetanus vaccine, receipt of blood pressure measurement, blood examination and urine examination during antenatal care, receipt of HIV testing, skilled birth attendance at delivery, health-facility-based delivery, and cesarean section delivery. Inequalities by wealth index were measured by prevalence ratios, concentration indices, and multivariable adjusted regression coefficients. Results: Significant increase in overall utilization was observed in all indicators (all p < 0.001). The concentration indices were 0.19 in 2000 and 0.06 in 2011 for antenatal care, 0.10 in 2000 and 0.06 in 2011 for tetanus vaccination, 0.23 in 2000 and 0.08 in 2011 for skilled birth attendance, 0.29 in 2006 and 0.12 in 2011 for blood examination, and 0.18 in 2006 and 0.09 in 2011 for health-facility-based delivery. The multivariable adjusted regression coefficients of reproductive health service utilization by wealth category were 0.06 in 2000 and 0.04 in 2011 for antenatal care, 0.07 in 2000 and 0.05 in 2011 for skilled birth attendance, and 0.07 in 2006 and 0.05 in 2011 for health-facility-based delivery. Conclusions: More women utilized reproductive health services in 2011 than in 2000. Inequality by wealth status in utilization of antenatal care, skilled birth attendance, and health-facility-based delivery had been reduced. PMID:26705431

Body image, body dissatisfaction and weight status in south asian children: a cross-sectional study

PubMed Central

2011-01-01

Background Childhood obesity is a continuing problem in the UK and South Asian children represent a group that are particularly vulnerable to its health consequences. The relationship between body dissatisfaction and obesity is well documented in older children and adults, but is less clear in young children, particularly South Asians. A better understanding of this relationship in young South Asian children will inform the design and delivery of obesity intervention programmes. The aim of this study is to describe body image size perception and dissatisfaction, and their relationship to weight status in primary school aged UK South Asian children. Methods Objective measures of height and weight were undertaken on 574 predominantly South Asian children aged 5-7 (296 boys and 278 girls). BMI z-scores, and weight status (underweight, healthy weight, overweight or obese) were calculated based on the UK 1990 BMI reference charts. Figure rating scales were used to assess perceived body image size (asking children to identify their perceived body size) and dissatisfaction (difference between perceived current and ideal body size). The relationship between these and weight status were examined using multivariate analyses. Results Perceived body image size was positively associated with weight status (partial regression coefficient for overweight/obese vs. non-overweight/obese was 0.63 (95% CI 0.26-0.99) and for BMI z-score was 0.21 (95% CI 0.10-0.31), adjusted for sex, age and ethnicity). Body dissatisfaction was also associated with weight status, with overweight and obese children more likely to select thinner ideal body size than healthy weight children (adjusted partial regression coefficient for overweight/obese vs. non-overweight/obese was 1.47 (95% CI 0.99-1.96) and for BMI z-score was 0.54 (95% CI 0.40-0.67)). Conclusions Awareness of body image size and increasing body dissatisfaction with higher weight status is established at a young age in this population. This needs to be considered when designing interventions to reduce obesity in young children, in terms of both benefits and harms. PMID:21214956

Parent-Child Resemblance in Weight Status and Its Correlates in the United States

PubMed Central

Liang, Lan; Wang, Youfa

2013-01-01

Background Few studies have examined parent-child resemblance in body weight status using nationally representative data for the US. Design We analyzed Body Mass Index (BMI), weight status, and related correlates for 4,846 boys, 4,725 girls, and their parents based on US nationally representative data from the 2006 and 2007 Medical Expenditure Panel Survey (MEPS). Pearson partial correlation coefficients, percent agreement, weighted kappa coefficients, and binary and multinomial logistic regression were used to examine parent-child resemblance, adjusted for complex sampling design. Results Pearson partial correlation coefficients between parent and child’s BMI measures were 0.15 for father-son pairs, 0.17 for father-daughter pairs, 0.20 for mother-son pairs, and 0.23 for mother-daughter pairs. The weighted kappa coefficients between BMI quintiles of parent and child ranged from −0.02 to 0.25. Odds ratio analyses found children were 2.1 (95% confidence interval (CI): 1.6, 2.8) times more likely to be obese if only their father was obese, 1.9 (95% CI: 1.5, 2.4) times more likely if only their mother was obese, and 3.2 (95% CI: 2.5, 4.2) times more likely if both parents were obese. Conclusions Parent-child resemblance in BMI appears weak and may vary across parent-child dyad types in the US population. However, parental obesity status is associated with children’s obesity status. Use of different measures of parent-child resemblance in body weight status can lead to different conclusions. PMID:23762352

The association between hospital outcomes and diagnostic imaging: early findings.

PubMed

Lee, David W; Foster, David A

2009-11-01

Resource use variation across the United States prompts the important question of whether "more is better" when it comes to health care services. The aim of this study was to examine correlations between the use of 4 common imaging modalities (CT, MR, ultrasound, and radiography) and in-hospital mortality and costs. Using clinical and utilization data for 1.1 million inpatient admissions at 102 US hospitals during 2007, two hospital-specific, risk-adjusted imaging utilization measures for each modality were constructed that controlled for patients' demographic and clinical characteristics and for hospital characteristics were constructed for each modality. First, logistic regression was used to estimate the odds that each type of imaging service would be provided during an admission. Second, the mean number of services per admission was estimated using output from a two-part ordinary least squares model. Hospital-specific, risk-adjusted inpatient mortality and total hospital costs were also computed, and correlations between the imaging utilization measures and the mortality and cost outcome measures were then assessed using Pearson's correlation coefficients (P < .05). The correlation analyses were weighted by hospital admission volume. Hospitals in which patients were more likely to receive imaging services during admissions had lower mortality, even after controlling for potential confounders. Correlation coefficients were -0.2 for all modalities (P = .02-.05). Weaker correlations existed between mean services per admission and mortality, while costs trended insignificantly higher with greater utilization. This study lays the foundation for further exploration of the relationship between resource use and the clinical and economic outcomes associated with imaging utilization.

Adjusted adaptive Lasso for covariate model-building in nonlinear mixed-effect pharmacokinetic models.

PubMed

Haem, Elham; Harling, Kajsa; Ayatollahi, Seyyed Mohammad Taghi; Zare, Najaf; Karlsson, Mats O

2017-02-01

One important aim in population pharmacokinetics (PK) and pharmacodynamics is identification and quantification of the relationships between the parameters and covariates. Lasso has been suggested as a technique for simultaneous estimation and covariate selection. In linear regression, it has been shown that Lasso possesses no oracle properties, which means it asymptotically performs as though the true underlying model was given in advance. Adaptive Lasso (ALasso) with appropriate initial weights is claimed to possess oracle properties; however, it can lead to poor predictive performance when there is multicollinearity between covariates. This simulation study implemented a new version of ALasso, called adjusted ALasso (AALasso), to take into account the ratio of the standard error of the maximum likelihood (ML) estimator to the ML coefficient as the initial weight in ALasso to deal with multicollinearity in non-linear mixed-effect models. The performance of AALasso was compared with that of ALasso and Lasso. PK data was simulated in four set-ups from a one-compartment bolus input model. Covariates were created by sampling from a multivariate standard normal distribution with no, low (0.2), moderate (0.5) or high (0.7) correlation. The true covariates influenced only clearance at different magnitudes. AALasso, ALasso and Lasso were compared in terms of mean absolute prediction error and error of the estimated covariate coefficient. The results show that AALasso performed better in small data sets, even in those in which a high correlation existed between covariates. This makes AALasso a promising method for covariate selection in nonlinear mixed-effect models.

Solid harmonic wavelet scattering for predictions of molecule properties

NASA Astrophysics Data System (ADS)

Eickenberg, Michael; Exarchakis, Georgios; Hirn, Matthew; Mallat, Stéphane; Thiry, Louis

2018-06-01

We present a machine learning algorithm for the prediction of molecule properties inspired by ideas from density functional theory (DFT). Using Gaussian-type orbital functions, we create surrogate electronic densities of the molecule from which we compute invariant "solid harmonic scattering coefficients" that account for different types of interactions at different scales. Multilinear regressions of various physical properties of molecules are computed from these invariant coefficients. Numerical experiments show that these regressions have near state-of-the-art performance, even with relatively few training examples. Predictions over small sets of scattering coefficients can reach a DFT precision while being interpretable.

Traveltime and reaeration characteristics for a reach of the Rio Grande, Albuquerque, New Mexico, October 1991

USGS Publications Warehouse

Waltemeyer, S.D.

1994-01-01

Traveltime characteristics were determined using stream-velocity data and tracer-dye data for a reach of the Rio Grande. Traveltimes determined by the stream-velocity method were virtually the same as those determined by the tracer-dye and tracer-gas technique. The mean velocity of the stream was 1.12 miles per hour at a flow of about 300 cubic feet per second. Reaeration characteristics were determined using a propane tracer gas and a tracer-dye (rhodamine WT). Reaeration coefficients were adjusted for water temperature and the effects of wind movement on the water surface. The peak method-adjusted reaeration-coefficient mean value for the reach was 7.0 per day and ranged from 4.6 to 8.3 per day. The area method-adjusted reaeration- coefficient mean value for the reach was 7.7 per day and ranged from 5.5 to 10.4 per day.

Advantages of geographically weighted regression for modeling benthic substrate in two Greater Yellowstone Ecosystem streams

USGS Publications Warehouse

Sheehan, Kenneth R.; Strager, Michael P.; Welsh, Stuart A.

2013-01-01

Stream habitat assessments are commonplace in fish management, and often involve nonspatial analysis methods for quantifying or predicting habitat, such as ordinary least squares regression (OLS). Spatial relationships, however, often exist among stream habitat variables. For example, water depth, water velocity, and benthic substrate sizes within streams are often spatially correlated and may exhibit spatial nonstationarity or inconsistency in geographic space. Thus, analysis methods should address spatial relationships within habitat datasets. In this study, OLS and a recently developed method, geographically weighted regression (GWR), were used to model benthic substrate from water depth and water velocity data at two stream sites within the Greater Yellowstone Ecosystem. For data collection, each site was represented by a grid of 0.1 m2 cells, where actual values of water depth, water velocity, and benthic substrate class were measured for each cell. Accuracies of regressed substrate class data by OLS and GWR methods were calculated by comparing maps, parameter estimates, and determination coefficient r 2. For analysis of data from both sites, Akaike’s Information Criterion corrected for sample size indicated the best approximating model for the data resulted from GWR and not from OLS. Adjusted r 2 values also supported GWR as a better approach than OLS for prediction of substrate. This study supports GWR (a spatial analysis approach) over nonspatial OLS methods for prediction of habitat for stream habitat assessments.

Aldosterone and glomerular filtration – observations in the general population

PubMed Central

2014-01-01

Background Increasing evidence suggests that aldosterone promotes renal damage. Since data on the association between aldosterone and renal function in the general population are sparse, we chose to address this issue. We investigated the associations between the plasma aldosterone concentration (PAC) or the aldosterone-to-renin ratio (ARR) and the estimated glomerular filtration rate (eGFR) in a sample of adult men and women from Northeast Germany. Methods A study population of 1921 adult men and women who participated in the first follow-up of the Study of Health in Pomerania was selected. None of the subjects used drugs that alter PAC or ARR. The eGFR was calculated according to the four-variable Modification of Diet in Renal Disease formula. Chronic kidney disease (CKD) was defined as an eGFR <60 ml/min/1.73 m2. Results Linear regression models, adjusted for sex, age, waist circumference, diabetes mellitus, smoking status, systolic and diastolic blood pressures, serum triglyceride concentrations and time of blood sampling revealed inverse associations of PAC or ARR with eGFR (ß-coefficient for log-transformed PAC −3.12, p < 0.001; ß-coefficient for log-transformed ARR −3.36, p < 0.001). Logistic regression models revealed increased odds for CKD with increasing PAC (odds ratio for a one standard deviation increase in PAC: 1.35, 95% confidence interval: 1.06-1.71). There was no statistically significant association between ARR and CKD. Conclusion Our study demonstrates that PAC and ARR are inversely associated with the glomerular filtration rate in the general population. PMID:24612948

Is the Professional Satisfaction of General Internists Associated with Patient Satisfaction?

PubMed Central

Haas, Jennifer S; Cook, E Francis; Puopolo, Ann Louise; Burstin, Helen R; Cleary, Paul D; Brennan, Troyen A

2000-01-01

BACKGROUND The growth of managed care has raised a number of concerns about patient and physician satisfaction. An association between physicians' professional satisfaction and the satisfaction of their patients could suggest new types of organizational interventions to improve the satisfaction of both. OBJECTIVE To examine the relation between the satisfaction of general internists and their patients. DESIGN Cross-sectional surveys of patients and physicians. SETTING Eleven academically affiliated general internal medicine practices in the greater-Boston area. PARTICIPANTS A random sample of English-speaking and Spanish-speaking patients (n = 2,620) with at least one visit to their physician (n = 166) during the preceding year. MEASUREMENTS Patients' overall satisfaction with their health care, and their satisfaction with their most recent physician visit. MAIN RESULTS After adjustment, the patients of physicians who rated themselves to be very or extremely satisfied with their work had higher scores for overall satisfaction with their health care (regression coefficient 2.10; 95% confidence interval 0.73–3.48), and for satisfaction with their most recent physician visit (regression coefficient 1.23; 95% confidence interval 0.26–2.21). In addition, younger patients, those with better overall health status, and those cared for by a physician who worked part-time were significantly more likely to report better satisfaction with both measures. Minority patients and those with managed care insurance also reported lower overall satisfaction. CONCLUSIONS The patients of physicians who have higher professional satisfaction may themselves be more satisfied with their care. Further research will need to consider factors that may mediate the relation between patient and physician satisfaction. PMID:10672116

The relationship of exposure to air pollutants in pregnancy with surrogate markers of endothelial dysfunction in umbilical cord.

PubMed

Poursafa, Parinaz; Baradaran-Mahdavi, Sadegh; Moradi, Bita; Haghjooy Javanmard, Shaghayegh; Tajadini, Mohammadhasan; Mehrabian, Ferdous; Kelishadi, Roya

2016-04-01

This study aims to investigate the association of exposure to ambient air pollution during pregnancy with cord blood concentrations of surrogate markers of endothelial dysfunction. This population-based cohort was conducted from March 2014 to March 2015 among 250 mother-neonate pairs in urban areas of Isfahan, the second large and air-polluted city in Iran. We analyzed the association between the ambient carbon monoxide (CO), ozone (O3), nitrogen dioxide (NO2), sulfur dioxide (SO2), particular matter 10 (PM10), and air quality index (AQI) with cord blood levels of endothelin-1, vascular adhesion molecule (VCAM), and intercellular adhesion molecule (ICAM). Multiple regression analysis was conducted after adjustment for potential confounding factors and covariates. The regression coefficient (beta), standard error of the estimate (SE), and 95% confidence intervals for each regression coefficient (95% CI) are reported. Data of 233 mother-neonate pairs were complete, and included in the analysis. Multiple regression analyses showed that AQI, CO and O3 had significant correlation with cord blood ICAM-1 [Beta (SE), 95%CI: 2.93 (0.72), 1.33,5.54; 2.28(1.44), 1.56,5.12; and 2.02(0.01), 1.03,2.04, respectively] as well as with VCAM-1 [2.78(0.91), 1.69,4.57; 2.47(1.47), 1.43,5.37; and 2.01(0.01),1.07,2.04, respectively]. AQI, PM10, and SO2 were significantly associated with Endothelin-1 concentrations [Beta (SE), 95%CI: 10.16(5.08),7.61,14.28; 9.70(3.46), 2.88,16.52; and 1.07(0.02), 1.03,2.11, respectively]. The significant associations of air pollutants with markers of endothelial dysfunction during fetal period may provide another evidence on the adverse health effects of air pollutants on early stages of atherosclerosis from fetal period. Our findings underscore the importance of considering environmental factors in primordial prevention of chronic diseases. Copyright © 2015 Elsevier Inc. All rights reserved.

Urinary trace element concentrations in environmental settings: is there a value for systematic creatinine adjustment or do we introduce a bias?

PubMed

Hoet, Perrine; Deumer, Gladys; Bernard, Alfred; Lison, Dominique; Haufroid, Vincent

2016-01-01

Systematic creatinine adjustment of urinary concentrations of biomarkers has been a challenge over the past years because the assumption of a constant creatinine excretion rate appears erroneous and the issue of overadjustment has recently emerged. This study aimed at determining whether systematic creatinine adjustment is to be recommended for urinary concentrations of trace elements (TEs) in environmental settings. Paired 24-h collection and random spot urine samples (spotU) were obtained from 39 volunteers not occupationally exposed to TEs. Four models to express TEs concentration in spotU were tested to predict the 24-h excretion rate of these TEs (TEμg/24h) considered as the gold standard reference: absolute concentration (TEμg/l); ratio to creatinine (TEμg/gcr); TEμg/gcr adjusted to creatinine (TEμg/gcr-adj); and concentration adjusted to specific gravity (TEμg/l-SG). As, Ba, Cd, Co, Cr, Cu, Hg, Li, Mo, Ni, Pb, Sn, Sb, Se, Te, V and Zn were analyzed by inductively coupled argon plasma mass spectrometry. There was no single pattern of relationship between urinary TEs concentrations in spotU and TEμg/24h. TEμg/l predicted TEμg/24h with an explained variance ranging from 0 to 60%. Creatinine adjustment improved the explained variance by an additional 5 to ~60% for many TEs, but with a risk of overadjustment for the most of them. This issue could be addressed by adjusting TE concentrations on the basis of the regression coefficient of the relationship between TEμg/gcr and creatinine concentration. SG adjustment was as suitable as creatinine adjustment to predict TEμg/24h with no SG-overadjustment (except V). Regarding Cd, Cr, Cu, Ni and Te, none of the models were found to reflect TEμg/24h. In the context of environmental exposure, systematic creatinine adjustment is not recommended for urinary concentrations of TEs. SG adjustment appears to be a more reliable alternative. For some TEs, however, neither methods appear suitable.

Reduction of shading-derived artifacts in skin chromophore imaging without measurements or assumptions about the shape of the subject

NASA Astrophysics Data System (ADS)

Yoshida, Kenichiro; Nishidate, Izumi; Ojima, Nobutoshi; Iwata, Kayoko

2014-01-01

To quantitatively evaluate skin chromophores over a wide region of curved skin surface, we propose an approach that suppresses the effect of the shading-derived error in the reflectance on the estimation of chromophore concentrations, without sacrificing the accuracy of that estimation. In our method, we use multiple regression analysis, assuming the absorbance spectrum as the response variable and the extinction coefficients of melanin, oxygenated hemoglobin, and deoxygenated hemoglobin as the predictor variables. The concentrations of melanin and total hemoglobin are determined from the multiple regression coefficients using compensation formulae (CF) based on the diffuse reflectance spectra derived from a Monte Carlo simulation. To suppress the shading-derived error, we investigated three different combinations of multiple regression coefficients for the CF. In vivo measurements with the forearm skin demonstrated that the proposed approach can reduce the estimation errors that are due to shading-derived errors in the reflectance. With the best combination of multiple regression coefficients, we estimated that the ratio of the error to the chromophore concentrations is about 10%. The proposed method does not require any measurements or assumptions about the shape of the subjects; this is an advantage over other studies related to the reduction of shading-derived errors.

Correlation and simple linear regression.

PubMed

Zou, Kelly H; Tuncali, Kemal; Silverman, Stuart G

2003-06-01

In this tutorial article, the concepts of correlation and regression are reviewed and demonstrated. The authors review and compare two correlation coefficients, the Pearson correlation coefficient and the Spearman rho, for measuring linear and nonlinear relationships between two continuous variables. In the case of measuring the linear relationship between a predictor and an outcome variable, simple linear regression analysis is conducted. These statistical concepts are illustrated by using a data set from published literature to assess a computed tomography-guided interventional technique. These statistical methods are important for exploring the relationships between variables and can be applied to many radiologic studies.

Assessing oral health-related quality of life in general dental practice in Scotland: validation of the OHIP-14.

PubMed

Fernandes, Marcelo José; Ruta, Danny Adolph; Ogden, Graham Richard; Pitts, Nigel Berry; Ogston, Simon Alexander

2006-02-01

To validate the Oral Health Impact Profile (OHIP)-14 in a sample of patients attending general dental practice. Patients with pathology-free impacted wisdom teeth were recruited from six general dental practices in Tayside, Scotland, and followed for a year to assess the development of problems related to impaction. The OHIP-14 was completed at baseline and at 1-year follow-up, and analysed using three different scoring methods: a summary score, a weighted and standardized score and the total number of problems reported. Instrument reliability was measured by assessing internal consistency and test-retest reliability. Construct validity was assessed using a number of variables. Linear regression was then used to model the relationship between OHIP-14 and all significantly correlated variables. Responsiveness was measured using the standardized response mean (SRM). Adjusted R(2)s and SRMs were calculated for each of the three scoring methods. Estimates for the differences between adjusted R(2)s and the differences between SRMs were obtained with 95% confidence intervals. A total of 278 and 169 patients completed the questionnaire at baseline and follow-up, respectively. Reliability - Cronbach's alpha coefficients ranged from 0.30 to 0.75. Alpha coefficients for all 14 items were 0.88 and 0.87 for baseline and follow-up, respectively. Test-retest coefficients ranged from 0.72 to 0.78. Validity - OHIP-14 scores were significantly correlated with number of teeth, education, main activity, the use of mouthwash, frequency of seeing a dentist, the reason for the last dental appointment, smoking, alcohol intake, pain and symptoms. Adjusted R(2)s ranged from 0.123 to 0.202 and there were no statistically significant differences between those for the three different scoring methods. Responsiveness - The SRMs ranged from 0.37 to 0.56 and there was a statistically significant difference between the summary scores method and the total number of problems method for symptomatic patients. The OHIP-14 is a valid and reliable measure of oral health-related quality of life in general dental practice and is responsive to third molar clinical change. The summary score method demonstrated performance as good as, or better than, the other methods studied.

Linear solvation energy relationship for the adsorption of synthetic organic compounds on single-walled carbon nanotubes in water.

PubMed

Ding, H; Chen, C; Zhang, X

2016-01-01

The linear solvation energy relationship (LSER) was applied to predict the adsorption coefficient (K) of synthetic organic compounds (SOCs) on single-walled carbon nanotubes (SWCNTs). A total of 40 log K values were used to develop and validate the LSER model. The adsorption data for 34 SOCs were collected from 13 published articles and the other six were obtained in our experiment. The optimal model composed of four descriptors was developed by a stepwise multiple linear regression (MLR) method. The adjusted r(2) (r(2)adj) and root mean square error (RMSE) were 0.84 and 0.49, respectively, indicating good fitness. The leave-one-out cross-validation Q(2) ([Formula: see text]) was 0.79, suggesting the robustness of the model was satisfactory. The external Q(2) ([Formula: see text]) and RMSE (RMSEext) were 0.72 and 0.50, respectively, showing the model's strong predictive ability. Hydrogen bond donating interaction (bB) and cavity formation and dispersion interactions (vV) stood out as the two most influential factors controlling the adsorption of SOCs onto SWCNTs. The equilibrium concentration would affect the fitness and predictive ability of the model, while the coefficients varied slightly.

Gender empowerment and female-to-male smoking prevalence ratios

PubMed Central

Fong, Geoffrey T

2011-01-01

Abstract Objective To determine whether in countries with high gender empowerment the female-to-male smoking prevalence ratio is also higher. Methods Bivariate and multiple regression analyses were performed to explore the relation between the United Nations Development Programme’s gender empowerment measure (GEM) and the female-to-male smoking prevalence ratio (calculated from the 2008 WHO global tobacco control report). Because a country’s progression through the various stages of the tobacco epidemic and its gender smoking ratio (GSR) are thought to be influenced by its level of development, we explored this correlation as well, with economic development defined in terms of gross national income (GNI) per capita and income inequality (Gini coefficient). Findings The GSR was significantly and positively correlated with the GEM (r = 0.680; P < 0.001). In addition, the GEM was the strongest predictor of the GSR (β, adjusted: 0.47; P < 0.0001) after controlling for GNI per capita and for Gini coefficient. Conclusion Whether progress towards gender empowerment can take place without a corresponding increase in smoking among women remains to be seen. Strong tobacco control measures are needed in countries where women are being increasingly empowered. PMID:21379415

Casemix classification payment for sub-acute and non-acute inpatient care, Thailand.

PubMed

Khiaocharoen, Orathai; Pannarunothai, Supasit; Zungsontiporn, Chairoj; Riewpaiboon, Wachara

2010-07-01

There is a need to develop other casemix classifications, apart from DRG for sub-acute and non-acute inpatient care payment mechanism in Thailand. To develop a casemix classification for sub-acute and non-acute inpatient service. The study began with developing a classification system, analyzing cost, assigning payment weights, and ended with testing the validity of this new casemix system. Coefficient of variation, reduction in variance, linear regression, and split-half cross-validation were employed. The casemix for sub-acute and non-acute inpatient services contained 98 groups. Two percent of them had a coefficient of variation of the cost of higher than 1.5. The reduction in variance of cost after the classification was 32%. Two classification variables (physical function and the rehabilitation impairment categories) were key determinants of the cost (adjusted R2 = 0.749, p = .001). Validity results of split-half cross-validation of sub-acute and non-acute inpatient service were high. The present study indicated that the casemix for sub-acute and non-acute inpatient services closely predicted the hospital resource use and should be further developed for payment of the inpatients sub-acute and non-acute phase.

Landsat-8/OLI images has the potential to estimate the CDOM absorption coefficient in tropical inland water

NASA Astrophysics Data System (ADS)

Alcantara, E.; Bernardo, N.

2016-12-01

Colored dissolved organic matter (CDOM) is the most abundant dissolved organic matter (DOM) in many natural waters and can affect the water quality, such as the light penetration and the thermal properties of water system. So the objective of this letter was to estimate the colored dissolved organic matter (CDOM) absorption coefficient at 440 nm, aCDOM(440), in Barra Bonita Reservoir (São Paulo State, Brazil) using OLI/Landsat-8 images. For this two field campaigns were conducted in May and October 2014. During the field campaigns remote sensing reflectance (Rrs) were measured using a TriOS hyperspectral radiometer. Water samples were collected and analyzed to obtain the aCDOM(440). To predict the aCDOM(440) from Rrs at two key wavelengths (650 and 480 nm) were regressed against laboratory derived aCDOM(440) values. The validation using in situ data of aCDOM(440) algorithm indicated a goodness of fit, R2 = 0.70, with a root-mean-square error (RMSE) of 10.65%. The developed algorithm was applied to the OLI/Lansat-8 images. Distribution maps were created with OLI/Landsat-8 images based on the adjusted algorithm.

Application of a parameter-estimation technique to modeling the regional aquifer underlying the eastern Snake River plain, Idaho

USGS Publications Warehouse

Garabedian, Stephen P.

1986-01-01

A nonlinear, least-squares regression technique for the estimation of ground-water flow model parameters was applied to the regional aquifer underlying the eastern Snake River Plain, Idaho. The technique uses a computer program to simulate two-dimensional, steady-state ground-water flow. Hydrologic data for the 1980 water year were used to calculate recharge rates, boundary fluxes, and spring discharges. Ground-water use was estimated from irrigated land maps and crop consumptive-use figures. These estimates of ground-water withdrawal, recharge rates, and boundary flux, along with leakance, were used as known values in the model calibration of transmissivity. Leakance values were adjusted between regression solutions by comparing model-calculated to measured spring discharges. In other simulations, recharge and leakance also were calibrated as prior-information regression parameters, which limits the variation of these parameters using a normalized standard error of estimate. Results from a best-fit model indicate a wide areal range in transmissivity from about 0.05 to 44 feet squared per second and in leakance from about 2.2x10 -9 to 6.0 x 10 -8 feet per second per foot. Along with parameter values, model statistics also were calculated, including the coefficient of correlation between calculated and observed head (0.996), the standard error of the estimates for head (40 feet), and the parameter coefficients of variation (about 10-40 percent). Additional boundary flux was added in some areas during calibration to achieve proper fit to ground-water flow directions. Model fit improved significantly when areas that violated model assumptions were removed. It also improved slightly when y-direction (northwest-southeast) transmissivity values were larger than x-direction (northeast-southwest) transmissivity values. The model was most sensitive to changes in recharge, and in some areas, to changes in transmissivity, particularly near the spring discharge area from Milner Dam to King Hill.

Energy Setting and Visual Outcomes in SMILE: A Retrospective Cohort Study.

PubMed

Li, Liuyang; Schallhorn, Julie M; Ma, Jiaonan; Cui, Tong; Wang, Yan

2018-01-01

To assess the independent effect of energy setting on postoperative uncorrected distance visual acuity (UDVA) in small incision lenticule extraction (SMILE) and further investigate an optimal energy setting for the 4.5-μm spot-track-distance, which is in wide clinical use. A total of 1,130 eyes were included in a retrospective cohort study from Tianjin Eye Hospital, Tianjin Medical University from April 2015 to July 2016. Energy settings and baseline characteristics were recorded and 3-month UDVA was tested by a nurse blinded to the energy settings used. Multiple regression analysis and generalized estimating equations were used to take into account the correlation between the measurements from two eyes. The 3-month UDVA (mean ± standard deviation) of 125 to 160 nJ (by 5-nJ increments) was 1.39 ± 0.19, 1.40 ± 0.32, 1.33 ± 0.27, 1.36 ± 0.27, 1.34 ± 0.25, 1.29 ± 0.19, 1.36 ± 0.27, and 1.19 ± 0.22, respectively. Energy was significantly associated with postoperative logMAR UDVA in different models and the regression coefficient (β) was robust (β = 0.01, 95% confidence interval = 0.00 to 0.01). The regression coefficient β (0.01, 95% confidence interval = 0.00 to 0.02, P = .0029) of energy (125 to 150 nJ, by 5-nJ increments) on 4.5-μm spot-track-distance was still associated with the logMAR UDVA when adjusted for sex, age, myopia, astigmatism, mean keratometry, central corneal thickness, preoperative logMAR CDVA, and side spot-track-distance. The lower end of the energy studied was associated with a better postoperative UDVA in this population. The spot-track-distance of 4.5 μm with 125 nJ energy was the optimal combination within this range. [J Refract Surg. 2018;34(1):11-16.]. Copyright 2018, SLACK Incorporated.

The associations of body mass index with physical and mental aspects of health-related quality of life in Chinese patients with type 2 diabetes mellitus: results from a cross-sectional survey.

PubMed

Wong, Carlos K H; Lo, Yvonne Y C; Wong, Winnie H T; Fung, Colman S C

2013-08-21

This study aimed to determine the associations of various clinical factors with generic health-related quality of life (HRQOL) scores among Hong Kong Chinese patients with type 2 diabetes mellitus (T2DM) in the outpatient primary care setting using the short-form 12 (SF-12). A cross-sectional survey of 488 Chinese adults with T2DM recruited from a primary care outpatient clinic was conducted from May to August 2008. Data on the standard Chinese (HK) SF-12 Health Survey and patients' socio-demographics were collected from face-to-face interviews. Glycaemic control, body mass index (BMI), chronic co-morbidities, diabetic complications and treatment modalities were determined for each patient through medical records. Associations of socio-demographic and clinical factors with physical component summary (PCS-12) and mental component summary scores (MCS-12) were evaluated using multiple linear regression. The socio-demographic correlates of PCS-12 and MCS-12 were age, gender and BMI. After adjustment for socio-demographic variables, the BMI was negatively associated with PCS-12 but positively associated with MCS-12. The presence of diabetic complications was associated with lower PCS-12 (regression coefficient:-3.0 points, p < 0.05) while being on insulin treatment was associated with lower MCS-12 (regression coefficient:-5.8 points, p < 0.05). In contrast, glycaemic control, duration of T2DM and treatment with oral hypoglycaemic drugs were not significantly associated with PCS-12 or MCS-12. Among T2DM subjects in the primary care setting, impairments in the physical aspect of HRQOL were evident in subjects who were obese or had diabetic complications whereas defects in the mental aspect of HRQOL were observed in patients with lower BMI or receiving insulin injections.

The Relation between Polyphenols and Body Composition in US Hispanics/Latinos: Results from the Hispanic Community Health Study/Study of Latinos (HCHS/SOL) Study of Latinos Nutrition and Physical Activity Assessment Study (SOLNAS)

PubMed Central

Makarem, Nour; Mossavar-Rahmani, Yasmin; Hua, Simin; Wong, William W; Van Horn, Linda; Daviglus, Martha L; Franke, Adrian A; Gellman, Marc D; Kaplan, Robert C; Beasley, Jeannette M

2017-01-01

Abstract Background: Polyphenols offer high antioxidant potential that may protect against chronic diseases. Epidemiologic evidence documenting their influence on body composition and obesity risk is limited, particularly among Hispanics/Latinos who are disproportionately prone to obesity. Objectives: The aims of this study were to evaluate cross-sectional associations of urinary polyphenols with body mass index (BMI) and body fat percentage (%BF) in a diverse Hispanic/Latino population and to assess the reliability of polyphenol measurements. Methods: Participants were 442 adults from the Study of Latinos/Nutrition and Physical Activity Assessment Study (SOLNAS) aged 18–74 y. Doubly labeled water was used as an objective recovery biomarker of energy. Polyphenol excretion from 24-h urine samples was assessed. Measures were repeated in a subsample (n = 90) to provide a reliability measure. Anthropometric measures were obtained by trained personnel, and %BF was measured by 18O dilution. Linear regression models were used to evaluate multivariable associations between body composition and polyphenols. Spearman correlation coefficients between BMI and %BF with polyphenols and intraclass correlation coefficients (ICCs) between polyphenol measures were computed. Results: A weak correlation was observed for resveratrol and %BF (r = −0.11, P = 0.02). In multivariable-adjusted regression models, weak inverse associations were observed for resveratrol and urolithin A with %BF [β ± SE: −0.010 ± 0.004 (P = 0.007) and −0.004 ± 0.002 (P = 0.03), respectively]. For every 50% increase in these urinary polyphenols, there was a 1% and 0.4% decrease in %BF. Urolithin A was inversely associated with BMI (β ± SE: −0.004 ± 0.002; P = 0.02) and with 5% lower odds of obesity in models not adjusted for total energy expenditure (TEE; OR: 0.95; 95% CI: 0.91, 0.99; P = 0.02). For every 50% increase in urolithin A, there was a 0.4-unit decrease in BMI. Associations were attenuated after adjustment for TEE. Reliability study findings were indicative of weak to moderate correlations (ICCs: 0.11–0.65), representing a degree of within-person variation in polyphenol biomarkers. Conclusions: Although associations were weak, resveratrol and urolithin A were inversely associated with obesity. Repeated polyphenol urine measures could clarify their long-term impact on body adiposity.

Contributions of maternal and paternal adiposity and smoking to adult offspring adiposity and cardiovascular risk: the Midspan Family Study

PubMed Central

Han, T S; Hart, C L; Haig, C; Logue, J; Upton, M N; Watt, G C M; Lean, M E J

2015-01-01

Objective Obesity has some genetic basis but requires interaction with environmental factors for phenotypic expression. We examined contributions of gender-specific parental adiposity and smoking to adiposity and related cardiovascular risk in adult offspring. Design Cross-sectional general population survey. Setting Scotland. Participants 1456 of the 1477 first generation families in the Midspan Family Study: 2912 parents (aged 45–64 years surveyed between 1972 and 1976) who had 1025 sons and 1283 daughters, aged 30–59 years surveyed in 1996. Main measures Offspring body mass index (BMI), waist circumference (WC), cardiometabolic risk (lipids, blood pressure and glucose) and cardiovascular disease as outcome measures, and parental BMI and smoking as determinants. All analyses adjusted for age, socioeconomic status and family clustering and offspring birth weight. Results Regression coefficients for BMI associations between father–son (0.30) and mother–daughter (0.33) were greater than father–daughter (0.23) or mother–son (0.22). Regression coefficient for the non-genetic, shared-environment or assortative-mating relationship between BMIs of fathers and mothers was 0.19. Heritability estimates for BMI were greatest among women with mothers who had BMI either <25 or ≥30 kg/m2. Compared with offspring without obese parents, offspring with two obese parents had adjusted OR of 10.25 (95% CI 6.56 to 13.93) for having WC ≥102 cm for men, ≥88 cm women, 2.46 (95% CI 1.33 to 4.57) for metabolic syndrome and 3.03 (95% CI 1.55 to 5.91) for angina and/or myocardial infarct (p<0.001). Neither parental adiposity nor smoking history determined adjusted offspring individual cardiometabolic risk factors, diabetes or stroke. Maternal, but not paternal, smoking had significant effects on WC in sons (OR=1.50; 95% CI 1.13 to 2.01) and daughters (OR=1.42; 95% CI 1.10 to 1.84) and metabolic syndrome OR=1.68; 95% CI 1.17 to 2.40) in sons. Conclusions There are modest genetic/epigenetic influences on the environmental factors behind adverse adiposity. Maternal smoking appears a specific hazard on obesity and metabolic syndrome. A possible epigenetic mechanism linking maternal smoking to obesity and metabolic syndrome in offspring is proposed. Individuals with family histories of obesity should be targeted from an early age to prevent obesity and complications. PMID:26525718

Contributions of maternal and paternal adiposity and smoking to adult offspring adiposity and cardiovascular risk: the Midspan Family Study.

PubMed

Han, T S; Hart, C L; Haig, C; Logue, J; Upton, M N; Watt, G C M; Lean, M E J

2015-11-02

Obesity has some genetic basis but requires interaction with environmental factors for phenotypic expression. We examined contributions of gender-specific parental adiposity and smoking to adiposity and related cardiovascular risk in adult offspring. Cross-sectional general population survey. Scotland. 1456 of the 1477 first generation families in the Midspan Family Study: 2912 parents (aged 45-64 years surveyed between 1972 and 1976) who had 1025 sons and 1283 daughters, aged 30-59 years surveyed in 1996. Offspring body mass index (BMI), waist circumference (WC), cardiometabolic risk (lipids, blood pressure and glucose) and cardiovascular disease as outcome measures, and parental BMI and smoking as determinants. All analyses adjusted for age, socioeconomic status and family clustering and offspring birth weight. Regression coefficients for BMI associations between father-son (0.30) and mother-daughter (0.33) were greater than father-daughter (0.23) or mother-son (0.22). Regression coefficient for the non-genetic, shared-environment or assortative-mating relationship between BMIs of fathers and mothers was 0.19. Heritability estimates for BMI were greatest among women with mothers who had BMI either <25 or ≥30 kg/m(2). Compared with offspring without obese parents, offspring with two obese parents had adjusted OR of 10.25 (95% CI 6.56 to 13.93) for having WC ≥102 cm for men, ≥88 cm women, 2.46 (95% CI 1.33 to 4.57) for metabolic syndrome and 3.03 (95% CI 1.55 to 5.91) for angina and/or myocardial infarct (p<0.001). Neither parental adiposity nor smoking history determined adjusted offspring individual cardiometabolic risk factors, diabetes or stroke. Maternal, but not paternal, smoking had significant effects on WC in sons (OR=1.50; 95% CI 1.13 to 2.01) and daughters (OR=1.42; 95% CI 1.10 to 1.84) and metabolic syndrome OR=1.68; 95% CI 1.17 to 2.40) in sons. There are modest genetic/epigenetic influences on the environmental factors behind adverse adiposity. Maternal smoking appears a specific hazard on obesity and metabolic syndrome. A possible epigenetic mechanism linking maternal smoking to obesity and metabolic syndrome in offspring is proposed. Individuals with family histories of obesity should be targeted from an early age to prevent obesity and complications. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Improved Conjugate Gradient Bundle Adjustment of Dunhuang Wall Painting Images

NASA Astrophysics Data System (ADS)

Hu, K.; Huang, X.; You, H.

2017-09-01

Bundle adjustment with additional parameters is identified as a critical step for precise orthoimage generation and 3D reconstruction of Dunhuang wall paintings. Due to the introduction of self-calibration parameters and quasi-planar constraints, the structure of coefficient matrix of the reduced normal equation is banded-bordered, making the solving process of bundle adjustment complex. In this paper, Conjugate Gradient Bundle Adjustment (CGBA) method is deduced by calculus of variations. A preconditioning method based on improved incomplete Cholesky factorization is adopt to reduce the condition number of coefficient matrix, as well as to accelerate the iteration rate of CGBA. Both theoretical analysis and experimental results comparison with conventional method indicate that, the proposed method can effectively conquer the ill-conditioned problem of normal equation and improve the calculation efficiency of bundle adjustment with additional parameters considerably, while maintaining the actual accuracy.

Exact Analysis of Squared Cross-Validity Coefficient in Predictive Regression Models

ERIC Educational Resources Information Center

Shieh, Gwowen

2009-01-01

In regression analysis, the notion of population validity is of theoretical interest for describing the usefulness of the underlying regression model, whereas the presumably more important concept of population cross-validity represents the predictive effectiveness for the regression equation in future research. It appears that the inference…

Comparing spatially varying coefficient models: a case study examining violent crime rates and their relationships to alcohol outlets and illegal drug arrests

NASA Astrophysics Data System (ADS)

Wheeler, David C.; Waller, Lance A.

2009-03-01

In this paper, we compare and contrast a Bayesian spatially varying coefficient process (SVCP) model with a geographically weighted regression (GWR) model for the estimation of the potentially spatially varying regression effects of alcohol outlets and illegal drug activity on violent crime in Houston, Texas. In addition, we focus on the inherent coefficient shrinkage properties of the Bayesian SVCP model as a way to address increased coefficient variance that follows from collinearity in GWR models. We outline the advantages of the Bayesian model in terms of reducing inflated coefficient variance, enhanced model flexibility, and more formal measuring of model uncertainty for prediction. We find spatially varying effects for alcohol outlets and drug violations, but the amount of variation depends on the type of model used. For the Bayesian model, this variation is controllable through the amount of prior influence placed on the variance of the coefficients. For example, the spatial pattern of coefficients is similar for the GWR and Bayesian models when a relatively large prior variance is used in the Bayesian model.

Multiscale modeling for ferroelectric materials: identification of the phase-field model’s free energy for PZT from atomistic simulations

NASA Astrophysics Data System (ADS)

Völker, Benjamin; Landis, Chad M.; Kamlah, Marc

2012-03-01

Within a knowledge-based multiscale simulation approach for ferroelectric materials, the atomic level can be linked to the mesoscale by transferring results from first-principles calculations into a phase-field model. A recently presented routine (Völker et al 2011 Contin. Mech. Thermodyn. 23 435-51) for adjusting the Helmholtz free energy coefficients to intrinsic and extrinsic ferroelectric material properties obtained by DFT calculations and atomistic simulations was subject to certain limitations: caused by too small available degrees of freedom, an independent adjustment of the spontaneous strains and piezoelectric coefficients was not possible, and the elastic properties could only be considered in cubic instead of tetragonal symmetry. In this work we overcome such restrictions by expanding the formulation of the free energy function, i.e. by motivating and introducing new higher-order terms that have not appeared in the literature before. Subsequently we present an improved version of the adjustment procedure for the free energy coefficients that is solely based on input parameters from first-principles calculations performed by Marton and Elsässer, as documented in Völker et al (2011 Contin. Mech. Thermodyn. 23 435-51). Full sets of adjusted free energy coefficients for PbTiO3 and tetragonal Pb(Zr,Ti)O3 are presented, and the benefits of the newly introduced higher-order free energy terms are discussed.

Associations between active travel and adiposity in rural India and Bangladesh: a cross-sectional study.

PubMed

McKay, Ailsa J; Laverty, Anthony A; Shridhar, Krithiga; Alam, Dewan; Dias, Amit; Williams, Joseph; Millett, Christopher; Ebrahim, Shah; Dhillon, Preet K

2015-10-24

Data on use and health benefits of active travel in rural low- and middle- income country settings are sparse. We aimed to examine correlates of active travel, and its association with adiposity, in rural India and Bangladesh. Cross sectional study of 2,122 adults (≥18 years) sampled in 2011-13 from two rural sites in India (Goa and Chennai) and one in Bangladesh (Matlab). Logistic regression was used to examine whether ≥150 min/week of active travel was associated with socio-demographic indices, smoking, oil/butter consumption, and additional physical activity. Adjusting for these same factors, associations between active travel and BMI, waist circumference and waist-to-hip ratio were examined using linear and logistic regression. Forty-six percent of the sample achieved recommended levels of physical activity (≥150 min/week) through active travel alone (range: 33.1 % in Matlab to 54.8 % in Goa). This was more frequent among smokers (adjusted odds ratio 1.36, 95 % confidence interval 1.07-1.72; p = 0.011) and those that spent ≥150 min/week in work-based physical activity (OR 1.71, 1.35-2.16; p < 0.001), but less frequent among females than males (OR 0.25, 0.20-0.31; p < 0.001). In fully adjusted analyses, ≥150 min/week of active travel was associated with lower BMI (adjusted coefficient -0.39 kg/m(2), -0.77 to -0.02; p = 0.037) and a lower likelihood of high waist circumference (OR 0.77, 0.63-0.96; p = 0.018) and high waist-to-hip ratio (OR 0.72, 0.58-0.89; p = 0.002). Use of active travel for ≥150 min/week was associated with being male, smoking, and higher levels of work-based physical activity. It was associated with lower BMI, and lower risk of a high waist circumference or high waist-to-hip ratio. Promotion of active travel is an important component of strategies to address the growing prevalence of overweight in rural low- and middle- income country settings.

The roles of prostate-specific antigen (PSA) density, prostate volume, and their zone-adjusted derivatives in predicting prostate cancer in patients with PSA less than 20.0 ng/mL.

PubMed

Shen, P; Zhao, J; Sun, G; Chen, N; Zhang, X; Gui, H; Yang, Y; Liu, J; Shu, K; Wang, Z; Zeng, H

2017-05-01

The aim of this study was to develop nomograms for predicting prostate cancer and its zonal location using prostate-specific antigen density, prostate volume, and their zone-adjusted derivatives. A total of 928 consecutive patients with prostate-specific antigen (PSA) less than 20.0 ng/mL, who underwent transrectal ultrasound-guided transperineal 12-core prostate biopsy at West China Hospital between 2011 and 2014, were retrospectively enrolled. The patients were randomly split into training cohort (70%, n = 650) and validation cohort (30%, n = 278). Predicting models and the associated nomograms were built using the training cohort, while the validations of the models were conducted using the validation cohort. Univariate and multivariate logistic regression was performed. Then, new nomograms were generated based on multivariate regression coefficients. The discrimination power and calibration of these nomograms were validated using the area under the ROC curve (AUC) and the calibration curve. The potential clinical effects of these models were also tested using decision curve analysis. In total, 285 (30.7%) patients were diagnosed with prostate cancer. Among them, 131 (14.1%) and 269 (29.0%) had transition zone prostate cancer and peripheral zone prostate cancer. Each of zone-adjusted derivatives-based nomogram had an AUC more than 0.75. All nomograms had higher calibration and much better net benefit than the scenarios in predicting patients with or without different zones prostate cancer. Prostate-specific antigen density, prostate volume, and their zone-adjusted derivatives have important roles in detecting prostate cancer and its zonal location for patients with PSA 2.5-20.0 ng/mL. To the best of our knowledge, this is the first nomogram using these parameters to predict outcomes of 12-core prostate biopsy. These instruments can help clinicians to increase the accuracy of prostate cancer screening and to avoid unnecessary prostate biopsy. © 2017 American Society of Andrology and European Academy of Andrology.

Use of age-adjusted rates of suicide in time series studies in Israel.

PubMed

Bridges, F Stephen; Tankersley, William B

2009-01-01

Durkheim's modified theory of suicide was examined to explore how consistent it was in predicting Israeli rates of suicide from 1965 to 1997 when using age-adjusted rates rather than crude ones. In this time-series study, Israeli male and female rates of suicide increased and decreased, respectively, between 1965 and 1997. Conforming to Durkheim's modified theory, the Israeli male rate of suicide was lower in years when rates of marriage and birth are higher, while rates of suicide are higher in years when rates of divorce are higher, the opposite to that of Israeli women. The corrected regression coefficients suggest that the Israeli female rate of suicide remained lower in years when rate of divorce is higher, again the opposite suggested by Durkheim's modified theory. These results may indicate that divorce affects the mental health of Israeli women as suggested by their lower rate of suicide. Perhaps the "multiple roles held by Israeli females creates suicidogenic stress" and divorce provides some sense of stress relief, mentally speaking. The results were not as consistent with predictions suggested by Durkheim's modified theory of suicide as were rates from the United States for the same period nor were they consistent with rates based on "crude" suicide data. Thus, using age-adjusted rates of suicide had an influence on the prediction of the Israeli rate of suicide during this period.

Dietary linolenic acid and fasting glucose and insulin: the National Heart, Lung, and Blood Institute Family Heart Study.

PubMed

Djoussé, Luc; Hunt, Steven C; Tang, Weihong; Eckfeldt, John H; Province, Michael A; Ellison, R Curtis

2006-02-01

To assess whether dietary linolenic acid is associated with fasting insulin and glucose. In a cross-sectional design, we studied 3993 non-diabetic participants of the National Heart, Lung, and Blood Institute Family Heart Study 25 to 93 years of age. Linolenic acid was assessed through a food frequency questionnaire, and laboratory data were obtained after at least a 12-hour fast. We used generalized linear models to calculate adjusted means of insulin and glucose across quartiles of dietary linolenic acid. From the lowest to the highest sex-specific quartile of dietary linolenic acid, means +/- standard error for logarithmic transformed fasting insulin were 4.06 +/- 0.02 (reference), 4.09 +/- 0.02, 4.13 +/- 0.02, and 4.17 +/- 0.02 pM, respectively (trend, p < 0.0001), after adjustment for age, sex, energy intake, waist-to-hip ratio, smoking, and high-density lipoprotein-cholesterol. When dietary linolenic acid was used as a continuous variable, the multivariable adjusted regression coefficient was 0.42 +/- 0.08. There was no association between dietary linolenic acid and fasting glucose (trend p = 0.82). Our data suggest that higher consumption of dietary linolenic acid is associated with higher plasma insulin, but not glucose levels, in non-diabetic subjects. Additional studies are needed to assess whether higher intake of linolenic acid results in an increased insulin secretion and improved glucose use in vivo.

Harmonic regression of Landsat time series for modeling attributes from national forest inventory data

NASA Astrophysics Data System (ADS)

Wilson, Barry T.; Knight, Joseph F.; McRoberts, Ronald E.

2018-03-01

Imagery from the Landsat Program has been used frequently as a source of auxiliary data for modeling land cover, as well as a variety of attributes associated with tree cover. With ready access to all scenes in the archive since 2008 due to the USGS Landsat Data Policy, new approaches to deriving such auxiliary data from dense Landsat time series are required. Several methods have previously been developed for use with finer temporal resolution imagery (e.g. AVHRR and MODIS), including image compositing and harmonic regression using Fourier series. The manuscript presents a study, using Minnesota, USA during the years 2009-2013 as the study area and timeframe. The study examined the relative predictive power of land cover models, in particular those related to tree cover, using predictor variables based solely on composite imagery versus those using estimated harmonic regression coefficients. The study used two common non-parametric modeling approaches (i.e. k-nearest neighbors and random forests) for fitting classification and regression models of multiple attributes measured on USFS Forest Inventory and Analysis plots using all available Landsat imagery for the study area and timeframe. The estimated Fourier coefficients developed by harmonic regression of tasseled cap transformation time series data were shown to be correlated with land cover, including tree cover. Regression models using estimated Fourier coefficients as predictor variables showed a two- to threefold increase in explained variance for a small set of continuous response variables, relative to comparable models using monthly image composites. Similarly, the overall accuracies of classification models using the estimated Fourier coefficients were approximately 10-20 percentage points higher than the models using the image composites, with corresponding individual class accuracies between six and 45 percentage points higher.

SPSS and SAS programs for comparing Pearson correlations and OLS regression coefficients.

PubMed

Weaver, Bruce; Wuensch, Karl L

2013-09-01

Several procedures that use summary data to test hypotheses about Pearson correlations and ordinary least squares regression coefficients have been described in various books and articles. To our knowledge, however, no single resource describes all of the most common tests. Furthermore, many of these tests have not yet been implemented in popular statistical software packages such as SPSS and SAS. In this article, we describe all of the most common tests and provide SPSS and SAS programs to perform them. When they are applicable, our code also computes 100 × (1 - α)% confidence intervals corresponding to the tests. For testing hypotheses about independent regression coefficients, we demonstrate one method that uses summary data and another that uses raw data (i.e., Potthoff analysis). When the raw data are available, the latter method is preferred, because use of summary data entails some loss of precision due to rounding.

Quantitative Structure-Activity Relationship of Insecticidal Activity of Benzyl Ether Diamidine Derivatives

NASA Astrophysics Data System (ADS)

Zhai, Mengting; Chen, Yan; Li, Jing; Zhou, Jun

2017-12-01

The molecular electrongativity distance vector (MEDV-13) was used to describe the molecular structure of benzyl ether diamidine derivatives in this paper, Based on MEDV-13, The three-parameter (M 3, M 15, M 47) QSAR model of insecticidal activity (pIC 50) for 60 benzyl ether diamidine derivatives was constructed by leaps-and-bounds regression (LBR) . The traditional correlation coefficient (R) and the cross-validation correlation coefficient (R CV ) were 0.975 and 0.971, respectively. The robustness of the regression model was validated by Jackknife method, the correlation coefficient R were between 0.971 and 0.983. Meanwhile, the independent variables in the model were tested to be no autocorrelation. The regression results indicate that the model has good robust and predictive capabilities. The research would provide theoretical guidance for the development of new generation of anti African trypanosomiasis drugs with efficiency and low toxicity.

Consistent model identification of varying coefficient quantile regression with BIC tuning parameter selection

PubMed Central

Zheng, Qi; Peng, Limin

2016-01-01

Quantile regression provides a flexible platform for evaluating covariate effects on different segments of the conditional distribution of response. As the effects of covariates may change with quantile level, contemporaneously examining a spectrum of quantiles is expected to have a better capacity to identify variables with either partial or full effects on the response distribution, as compared to focusing on a single quantile. Under this motivation, we study a general adaptively weighted LASSO penalization strategy in the quantile regression setting, where a continuum of quantile index is considered and coefficients are allowed to vary with quantile index. We establish the oracle properties of the resulting estimator of coefficient function. Furthermore, we formally investigate a BIC-type uniform tuning parameter selector and show that it can ensure consistent model selection. Our numerical studies confirm the theoretical findings and illustrate an application of the new variable selection procedure. PMID:28008212

Does the Aging Process Significantly Modify the Mean Heart Rate?

PubMed Central

Santos, Marcos Antonio Almeida; Sousa, Antonio Carlos Sobral; Reis, Francisco Prado; Santos, Thayná Ramos; Lima, Sonia Oliveira; Barreto-Filho, José Augusto

2013-01-01

Background The Mean Heart Rate (MHR) tends to decrease with age. When adjusted for gender and diseases, the magnitude of this effect is unclear. Objective To analyze the MHR in a stratified sample of active and functionally independent individuals. Methods A total of 1,172 patients aged ≥ 40 years underwent Holter monitoring and were stratified by age group: 1 = 40-49, 2 = 50-59, 3 = 60-69, 4 = 70-79, 5 = ≥ 80 years. The MHR was evaluated according to age and gender, adjusted for Hypertension (SAH), dyslipidemia and non-insulin dependent diabetes mellitus (NIDDM). Several models of ANOVA, correlation and linear regression were employed. A two-tailed p value <0.05 was considered significant (95% CI). Results The MHR tended to decrease with the age range: 1 = 77.20 ± 7.10; 2 = 76.66 ± 7.07; 3 = 74.02 ± 7.46; 4 = 72.93 ± 7.35; 5 = 73.41 ± 7.98 (p < 0.001). Women showed a correlation with higher MHR (p <0.001). In the ANOVA and regression models, age and gender were predictors (p < 0.001). However, R2 and ETA2 < 0.10, as well as discrete standardized beta coefficients indicated reduced effect. Dyslipidemia, hypertension and DM did not influence the findings. Conclusion The MHR decreased with age. Women had higher values of MHR, regardless of the age group. Correlations between MHR and age or gender, albeit significant, showed the effect magnitude had little statistical relevance. The prevalence of SAH, dyslipidemia and diabetes mellitus did not influence the results. PMID:24029962

Protein Biomarkers for Insulin Resistance and Type 2 Diabetes Risk in Two Large Community Cohorts

PubMed Central

Nowak, Christoph; Sundström, Johan; Gustafsson, Stefan; Giedraitis, Vilmantas; Lind, Lars; Ingelsson, Erik; Fall, Tove

2016-01-01

Insulin resistance (IR) is a precursor of type 2 diabetes (T2D), and improved risk prediction and understanding of the pathogenesis are needed. We used a novel high-throughput 92-protein assay to identify circulating biomarkers for HOMA of IR in two cohorts of community residents without diabetes (n = 1,367) (mean age 73 ± 3.6 years). Adjusted linear regression identified cathepsin D and confirmed six proteins (leptin, renin, interleukin-1 receptor antagonist [IL-1ra], hepatocyte growth factor, fatty acid–binding protein 4, and tissue plasminogen activator [t-PA]) as IR biomarkers. Mendelian randomization analysis indicated a positive causal effect of IR on t-PA concentrations. Two biomarkers, IL-1ra (hazard ratio [HR] 1.28, 95% CI 1.03–1.59) and t-PA (HR 1.30, 1.02–1.65) were associated with incident T2D, and t-PA predicted 5-year transition to hyperglycemia (odds ratio 1.30, 95% CI 1.02–1.65). Additional adjustment for fasting glucose rendered both coefficients insignificant and revealed an association between renin and T2D (HR 0.79, 0.62–0.99). LASSO regression suggested a risk model including IL-1ra, t-PA, and the Framingham Offspring Study T2D score, but prediction improvement was nonsignificant (difference in C-index 0.02, 95% CI −0.08 to 0.12) over the T2D score only. In conclusion, proteomic blood profiling indicated cathepsin D as a new IR biomarker and suggested a causal effect of IR on t-PA. PMID:26420861

Relationship between periodontal status and intellectual function among community-dwelling elderly persons.

PubMed

Moriya, Shingo; Tei, Kanchu; Toyoshita, Yoshifumi; Koshino, Hisashi; Inoue, Nobuo; Miura, Hiroko

2012-06-01

The aim of this study was to indicate the relationship between periodontal status and intellectual function in the elderly. Periodontal status has been shown to be related to demographic, socioeconomic, and psychological status. Intellectual function is a significant indicator of health status. Nevertheless, the relationship between periodontal status and intellectual function has not been elucidated in detail among the elderly. A total of 152 community-dwelling elderly persons, aged 70-74 years, were enrolled in the study. Periodontal status was evaluated using the WHO Community Periodontal Index of Treatment Needs (CPITN). Intellectual function was assessed by four neuropsychological tests: Raven's Coloured Progressive Matrices (RCPM) test, the Verbal Paired Associates 1 (VerPA) task and the Visual Paired Associates 1 (VirPA) task, extracted from the Wechsler Memory Scale Revised Edition, and the Block Design subtest, extracted from the Wechsler Adult Intelligence Scales, Third Edition. Correlations between CPITN and each test were examined using Spearman rank correlation coefficients. The ordinal regression model was constructed with CPITN as the dependent variable and neuropsychological test as the principal independent variable to adjust for demographic factors, general health, lifestyle and oral health behaviour. Significant correlations were found between the RCPM test, the VerPA task, the Visual Paired Associates 1 and CPITN. In the ordinal regression model, CPITN was significantly related to measures of RCPM after adjusting for demographic factors, general health status, lifestyle and oral health behaviour. Intellectual function is considered a significant indicator of periodontal status among community-dwelling elderly persons. © 2011 The Gerodontology Society and John Wiley & Sons A/S.

International comparisons of preterm birth: higher rates of late preterm birth are associated with lower rates of stillbirth and neonatal death.

PubMed

Lisonkova, S; Sabr, Y; Butler, B; Joseph, K S

2012-12-01

To examine international rates of preterm birth and potential associations with stillbirths and neonatal deaths at late preterm and term gestation. Ecological study. Canada, USA and 26 countries in Europe. All deliveries in 2004. Information on preterm birth (<37, 32-36, 28-31 and 24-27 weeks of gestation) and perinatal deaths was obtained for 28 countries. Data sources included files and publications from Statistics Canada, the EURO-PERISTAT project and the National Center for Health Statistics. Pearson correlation coefficients and random-intercept Poisson regression were used to examine the association between preterm birth rates and gestational age-specific stillbirth and neonatal death rates. Rate ratios with 95% confidence intervals were estimated after adjustment for maternal age, parity and multiple births. Stillbirths and neonatal deaths ≥ 32 and ≥ 37 weeks of gestation. International rates of preterm birth (<37 weeks) ranged between 5.3 and 11.4 per 100 live births. Preterm birth rates at 32-36 weeks were inversely associated with stillbirths at ≥ 32 weeks (adjusted rate ratio 0.94, 95% CI 0.92-0.96) and ≥ 37 weeks (adjusted rate ratio 0.88, 95% CI 0.85-0.91) of gestation and inversely associated with neonatal deaths at ≥ 32 weeks (adjusted rate ratio 0.88, 95% CI 0.85-0.91) and ≥ 37 weeks (adjusted rate ratio 0.82, 95% CI 0.78-0.86) of gestation. Countries with high rates of preterm birth at 32-36 weeks of gestation have lower stillbirth and neonatal death rates at and beyond 32 weeks of gestation. Contemporary rates of preterm birth are indicators of both perinatal health and obstetric care services. © 2012 The Authors BJOG An International Journal of Obstetrics and Gynaecology © 2012 RCOG.

Unemployment and disability pension--an 18-year follow-up study of a 40-year-old population in a Norwegian county.

PubMed

Støver, Morten; Pape, Kristine; Johnsen, Roar; Fleten, Nils; Sund, Erik R; Claussen, Bjørgulf; Bjørngaard, Johan H

2012-02-28

This study explored the association of unemployment and an increased risk of receiving disability pension, and the possibility that this risk is attributed to municipality-specific characteristics. A cohort of 7,985 40-42 year olds was followed for 18 years in national registers, identifying new episodes of unemployment and cases of disability pension. The association between an unemployment period and disability pension in the subsequent year was estimated using discrete time multilevel logistic regressions and clustering individuals by municipality. The association between unemployment and disability pension was adjusted for age in the follow up-period, sex, baseline health status, health behaviour and education level. A conditional intra-class correlation coefficient (ICC) was estimated as a measure of inter-municipality variance. In the follow-up period, 2784 (35%) of the participants were granted disability pension. The crude odds ratio for receiving disability pension after unemployment (adjusted for age in follow-up period and sex only) was 1.42 (95% CI 1.1-1.8). Adjusting for baseline health indicators reduced the odds ratio of unemployment to 1.33 (CI 1.1-1.7). A fully adjusted model, including education level, further reduced the odds ratio of unemployment to 1.25 (CI 1.00-1.6). The ICC of the municipality level was approximately 2%. Becoming unemployed increased the risk of receiving subsequent disability pension. However, adjusting for baseline health status, health behaviour and education attenuated this impact considerably. The multilevel analysis indicated that a minor, yet statistically significant, proportion of the risk of disability pension can be attributed to the municipality of residence.

Unemployment and disability pension-an 18-year follow-up study of a 40-year-old population in a Norwegian county

PubMed Central

2012-01-01

Background This study explored the association of unemployment and an increased risk of receiving disability pension, and the possibility that this risk is attributed to municipality-specific characteristics. Methods A cohort of 7,985 40-42 year olds was followed for 18 years in national registers, identifying new episodes of unemployment and cases of disability pension. The association between an unemployment period and disability pension in the subsequent year was estimated using discrete time multilevel logistic regressions and clustering individuals by municipality. The association between unemployment and disability pension was adjusted for age in the follow up-period, sex, baseline health status, health behaviour and education level. A conditional intra-class correlation coefficient (ICC) was estimated as a measure of inter-municipality variance. Results In the follow-up period, 2784 (35%) of the participants were granted disability pension. The crude odds ratio for receiving disability pension after unemployment (adjusted for age in follow-up period and sex only) was 1.42 (95% CI 1.1-1.8). Adjusting for baseline health indicators reduced the odds ratio of unemployment to 1.33 (CI 1.1-1.7). A fully adjusted model, including education level, further reduced the odds ratio of unemployment to 1.25 (CI 1.00-1.6). The ICC of the municipality level was approximately 2%. Conclusions Becoming unemployed increased the risk of receiving subsequent disability pension. However, adjusting for baseline health status, health behaviour and education attenuated this impact considerably. The multilevel analysis indicated that a minor, yet statistically significant, proportion of the risk of disability pension can be attributed to the municipality of residence. PMID:22369630

Early exclusive breastfeeding is associated with longer telomeres in Latino preschool children.

PubMed

Wojcicki, Janet M; Heyman, Melvin B; Elwan, Deena; Lin, Jue; Blackburn, Elizabeth; Epel, Elissa

2016-08-01

Telomere length (TL) is a marker of cellular aging, with the majority of lifetime attrition occurring during the first 4 y. Little is known about risk factors for telomere shortening in childhood. We evaluated the relation between early life feeding variables and preschool TL. We assessed the relation between dietary, feeding, and weight-associated risk factors measured from birth and TL from blood samples taken at 4 y of age (n = 108) and 5 y of age (n = 92) in a cohort of urban, Latino children (n = 121 individual children). Feeding variables were evaluated in children with repeat measurements (n = 77). Mean TL (in bp) was associated with exclusive breastfeeding at 4-6 wk of age (adjusted coefficient: 353.85; 95% CI: 72.81, 634.89; P = 0.01), maternal TL (adjusted coefficient: 0.32; 95% CI: 0.11, 0.54; P < 0.01), and older paternal age (adjusted coefficient: 33.27; 95% CI: 4.10, 62.44; P = 0.03). The introduction of other foods or drinks in addition to breast-milk or replacement-milk substitutes before 4-6 wk of age was associated with mean TL at 4 and 5 y of age (adjusted coefficient: -457.01; 95% CI: -720.50, -193.51; P < 0.01). Infant obesity at 6 mo of age and soda consumption at 4 y of age mediated the relation in part between exclusive breastfeeding at 4-6 wk of age and mean TL at 4 and 5 y of age. High soda consumption at 3 y of age was associated with an accelerated attrition from 4 to 5 y of age (adjusted coefficient: -515.14; 95% CI: -986.06, -41.22; P = 0.03). Exclusive breastfeeding at 4-6 wk of age may have long-term effects on child health as evidenced by longer TL at 4 and 5 y of age. © 2016 American Society for Nutrition.

Testing a single regression coefficient in high dimensional linear models

PubMed Central

Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2017-01-01

In linear regression models with high dimensional data, the classical z-test (or t-test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z-test to assess the significance of each covariate. Based on the p-value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively. PMID:28663668

Testing a single regression coefficient in high dimensional linear models.

PubMed

Lan, Wei; Zhong, Ping-Shou; Li, Runze; Wang, Hansheng; Tsai, Chih-Ling

2016-11-01

In linear regression models with high dimensional data, the classical z -test (or t -test) for testing the significance of each single regression coefficient is no longer applicable. This is mainly because the number of covariates exceeds the sample size. In this paper, we propose a simple and novel alternative by introducing the Correlated Predictors Screening (CPS) method to control for predictors that are highly correlated with the target covariate. Accordingly, the classical ordinary least squares approach can be employed to estimate the regression coefficient associated with the target covariate. In addition, we demonstrate that the resulting estimator is consistent and asymptotically normal even if the random errors are heteroscedastic. This enables us to apply the z -test to assess the significance of each covariate. Based on the p -value obtained from testing the significance of each covariate, we further conduct multiple hypothesis testing by controlling the false discovery rate at the nominal level. Then, we show that the multiple hypothesis testing achieves consistent model selection. Simulation studies and empirical examples are presented to illustrate the finite sample performance and the usefulness of the proposed method, respectively.

Synthesis of linear regression coefficients by recovering the within-study covariance matrix from summary statistics.

PubMed

Yoneoka, Daisuke; Henmi, Masayuki

2017-06-01

Recently, the number of regression models has dramatically increased in several academic fields. However, within the context of meta-analysis, synthesis methods for such models have not been developed in a commensurate trend. One of the difficulties hindering the development is the disparity in sets of covariates among literature models. If the sets of covariates differ across models, interpretation of coefficients will differ, thereby making it difficult to synthesize them. Moreover, previous synthesis methods for regression models, such as multivariate meta-analysis, often have problems because covariance matrix of coefficients (i.e. within-study correlations) or individual patient data are not necessarily available. This study, therefore, proposes a brief explanation regarding a method to synthesize linear regression models under different covariate sets by using a generalized least squares method involving bias correction terms. Especially, we also propose an approach to recover (at most) threecorrelations of covariates, which is required for the calculation of the bias term without individual patient data. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Population heterogeneity in the salience of multiple risk factors for adolescent delinquency.

PubMed

Lanza, Stephanie T; Cooper, Brittany R; Bray, Bethany C

2014-03-01

To present mixture regression analysis as an alternative to more standard regression analysis for predicting adolescent delinquency. We demonstrate how mixture regression analysis allows for the identification of population subgroups defined by the salience of multiple risk factors. We identified population subgroups (i.e., latent classes) of individuals based on their coefficients in a regression model predicting adolescent delinquency from eight previously established risk indices drawn from the community, school, family, peer, and individual levels. The study included N = 37,763 10th-grade adolescents who participated in the Communities That Care Youth Survey. Standard, zero-inflated, and mixture Poisson and negative binomial regression models were considered. Standard and mixture negative binomial regression models were selected as optimal. The five-class regression model was interpreted based on the class-specific regression coefficients, indicating that risk factors had varying salience across classes of adolescents. Standard regression showed that all risk factors were significantly associated with delinquency. Mixture regression provided more nuanced information, suggesting a unique set of risk factors that were salient for different subgroups of adolescents. Implications for the design of subgroup-specific interventions are discussed. Copyright © 2014 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Retro-regression--another important multivariate regression improvement.

PubMed

Randić, M

2001-01-01

We review the serious problem associated with instabilities of the coefficients of regression equations, referred to as the MRA (multivariate regression analysis) "nightmare of the first kind". This is manifested when in a stepwise regression a descriptor is included or excluded from a regression. The consequence is an unpredictable change of the coefficients of the descriptors that remain in the regression equation. We follow with consideration of an even more serious problem, referred to as the MRA "nightmare of the second kind", arising when optimal descriptors are selected from a large pool of descriptors. This process typically causes at different steps of the stepwise regression a replacement of several previously used descriptors by new ones. We describe a procedure that resolves these difficulties. The approach is illustrated on boiling points of nonanes which are considered (1) by using an ordered connectivity basis; (2) by using an ordering resulting from application of greedy algorithm; and (3) by using an ordering derived from an exhaustive search for optimal descriptors. A novel variant of multiple regression analysis, called retro-regression (RR), is outlined showing how it resolves the ambiguities associated with both "nightmares" of the first and the second kind of MRA.

[From clinical judgment to linear regression model.

PubMed

Palacios-Cruz, Lino; Pérez, Marcela; Rivas-Ruiz, Rodolfo; Talavera, Juan O

2013-01-01

When we think about mathematical models, such as linear regression model, we think that these terms are only used by those engaged in research, a notion that is far from the truth. Legendre described the first mathematical model in 1805, and Galton introduced the formal term in 1886. Linear regression is one of the most commonly used regression models in clinical practice. It is useful to predict or show the relationship between two or more variables as long as the dependent variable is quantitative and has normal distribution. Stated in another way, the regression is used to predict a measure based on the knowledge of at least one other variable. Linear regression has as it's first objective to determine the slope or inclination of the regression line: Y = a + bx, where "a" is the intercept or regression constant and it is equivalent to "Y" value when "X" equals 0 and "b" (also called slope) indicates the increase or decrease that occurs when the variable "x" increases or decreases in one unit. In the regression line, "b" is called regression coefficient. The coefficient of determination (R 2 ) indicates the importance of independent variables in the outcome.

Interpretation of commonly used statistical regression models.

PubMed

Kasza, Jessica; Wolfe, Rory

2014-01-01

A review of some regression models commonly used in respiratory health applications is provided in this article. Simple linear regression, multiple linear regression, logistic regression and ordinal logistic regression are considered. The focus of this article is on the interpretation of the regression coefficients of each model, which are illustrated through the application of these models to a respiratory health research study. © 2013 The Authors. Respirology © 2013 Asian Pacific Society of Respirology.

The association between financial literacy and Problematic Internet Shopping in a multinational sample.

PubMed

Lam, Lawrence T; Lam, Mary K

2017-12-01

To examine the association between financial literacy and Problematic Internet Shopping in adults. This cross-sectional online survey recruited participants, aged between 18 and 60 years, through an online research facility. The sample consisted of multinational participants from mainly three continents including Europe, North America, and Asia. Problematic Internet Shopping was assessed using the Bergen Shopping Addiction Scale (BSAS). Financial Literacy was measured by the Financial Literacy subscale of the Financial Wellbeing Questionnaire. Multiple linear regression analyses were conducted to elucidate the relationship between the study and outcome variables with adjustment for other potential risk factors. Of the total of 997 respondents with an average age of 30.9 (s.d. = 8.8), 135 (13.8%) could be classified as having a high risk of being Problematic Internet Shoppers. Results from the multiple regression analyses suggested a significant and negative relationship between financial literacy and Problematic Internet Shopping with a regression coefficient of - 0.13, after controlling for the effects of potential risk factors such as age, region of birth, employment, income, shopping frequency, self-regulation and anxiety (t = - 6.42, p < 0.001). The clinical management of PIS should include a financial counselling as a component of the treatment regime. Enhancement of financial literacy in the general population, particularly among young people, will likely have a positive effect on the occurrence of PIS.

Racial and Gender Discrimination, Early Life Factors, and Chronic Physical Health Conditions in Midlife

PubMed Central

McDonald, Jasmine A.; Terry, Mary Beth; Tehranifar, Parisa

2013-01-01

Purpose Most studies of perceived discrimination have been cross-sectional and focused primarily on mental rather than physical health conditions. We examined the associations of perceived racial and gender discrimination reported in adulthood with early life factors and self-reported physician-diagnosis of chronic physical health conditions. Methods We used data from a racially diverse birth cohort of U.S. women (N=168, average age=41 years) with prospectively collected early life data (e.g., parental socioeconomic factors) and adult reported data on perceived discrimination, physical health conditions, and relevant risk factors. We performed modified robust Poisson regression due to the high prevalence of the outcomes. Results Fifty-percent of participants reported racial and 39% reported gender discrimination. Early life factors did not have strong associations with perceived discrimination. In adjusted regression models, participants reporting at least three experiences of gender or racial discrimination had a 38% increased risk of having at least one physical health conditions (RR=1.38, 95% CI: 1.01-1.87). Using standardized regression coefficients, the magnitude of the association of having physical health conditions was larger for perceived discrimination than for being overweight or obese. Conclusion Our results suggest a substantial chronic disease burden associated with perceived discrimination, which may exceed the impact of established risk factors for poor physical health. PMID:24345610

A Snack Dietary Pattern Increases the Risk of Hypercholesterolemia in Northern Chinese Adults: A Prospective Cohort Study

PubMed Central

Na, Lixin; Han, Tianshu; Zhang, Wei; Wu, Xiaoyan; Na, Guanqiong; Du, Shanshan; Li, Ying; Sun, Changhao

2015-01-01

The evidence about the effect of dietary patterns on blood cholesterol from cohort studies was very scarce. The study was to identify the association of dietary patterns with lipid profile, especially cholesterol, in a cohort in north China. Using a 1-year food frequency questionnaire, we assessed the dietary intake of 4515 adults from the Harbin People’s Health Study in 2008, aged 20-74 years. Principle component analysis was used to identify dietary patterns. The follow-up was completed in 2012. Fasting blood samples were collected for the determination of blood lipid concentrations. Logistic regression models were used to evaluate the association of dietary patterns with the incidence of hypercholesterolemia, hypertriglyceridemia, and low-HDL cholesterolemia. Five dietary patterns were identified (“staple food”, “vegetable, fruit and milk”, “potato, soybean and egg”, “snack”, and “meat”). The relative risk (RR) between the extreme tertiles of the snack dietary pattern scores was 1.72 (95% CI = 1.14, 2.59, P = 0.004) for hypercholesterolemia, 1.39 (1.13, 1.75, P = 0.036) for hypertriglyceridemia, after adjustment for age, sex, education, body mass index, smoking, alcohol consumption, energy intake, exercise and baseline lipid concentrations. There was a significant positive association between the snack dietary pattern scores and fasting serum total cholesterol (SRC (standardized regression coefficient) = 0.262, P = 0.025), LDL-c (SRC = 0.324, P = 0.002) and triglycerides (SRC = 0.253, P = 0.035), after adjustment for the multiple variables above. Moreover, the adjusted RR of hypertriglyceridemia between the extreme tertiles was 0.73 (0.56, 0.94, P = 0.025) for the vegetable, fruit and milk dietary pattern, and 1.86 (1.33, 2.41, P = 0.005) for the meat dietary pattern. The snack dietary pattern was a newly emerged dietary pattern in northern Chinese adults. It appears conceivable that the risk of hypercholesterolemia can be reduced by changing the snack dietary pattern. PMID:26244510

Association of urinary bisphenol A concentration with medical disorders and laboratory abnormalities in adults.

PubMed

Lang, Iain A; Galloway, Tamara S; Scarlett, Alan; Henley, William E; Depledge, Michael; Wallace, Robert B; Melzer, David

2008-09-17

Bisphenol A (BPA) is widely used in epoxy resins lining food and beverage containers. Evidence of effects in animals has generated concern over low-level chronic exposures in humans. To examine associations between urinary BPA concentrations and adult health status. Cross-sectional analysis of BPA concentrations and health status in the general adult population of the United States, using data from the National Health and Nutrition Examination Survey 2003-2004. Participants were 1455 adults aged 18 through 74 years with measured urinary BPA and urine creatinine concentrations. Regression models were adjusted for age, sex, race/ethnicity, education, income, smoking, body mass index, waist circumference, and urinary creatinine concentration. The sample provided 80% power to detect unadjusted odds ratios (ORs) of 1.4 for diagnoses of 5% prevalence per 1-SD change in BPA concentration, or standardized regression coefficients of 0.075 for liver enzyme concentrations, at a significance level of P < .05. Chronic disease diagnoses plus blood markers of liver function, glucose homeostasis, inflammation, and lipid changes. Higher urinary BPA concentrations were associated with cardiovascular diagnoses in age-, sex-, and fully adjusted models (OR per 1-SD increase in BPA concentration, 1.39; 95% confidence interval [CI], 1.18-1.63; P = .001 with full adjustment). Higher BPA concentrations were also associated with diabetes (OR per 1-SD increase in BPA concentration, 1.39; 95% confidence interval [CI], 1.21-1.60; P < .001) but not with other studied common diseases. In addition, higher BPA concentrations were associated with clinically abnormal concentrations of the liver enzymes gamma-glutamyltransferase (OR per 1-SD increase in BPA concentration, 1.29; 95% CI, 1.14-1.46; P < .001) and alkaline phosphatase (OR per 1-SD increase in BPA concentration, 1.48; 95% CI, 1.18-1.85; P = .002). Higher BPA exposure, reflected in higher urinary concentrations of BPA, may be associated with avoidable morbidity in the community-dwelling adult population.

Inconsistent Correlation Between Carotid Artery Intima-Media Thickness and Peripheral Arterial Tonometry: Brazilian Longitudinal Study of Adult Health (ELSA-Brasil).

PubMed

Lemos, Sara P; Passos, Valéria Maria A; Brant, Luisa C C; Bensenor, Isabela J M; Ribeiro, Antônio Luiz P; Barreto, Sandhi Maria

2015-08-01

To estimate the association between 2 markers for atherosclerosis, measurements of carotid artery intima-media thickness (IMT) and of peripheral arterial tonometry (PAT), and to evaluate the role of traditional cardiovascular risk factors in this association.We applied the 2 diagnostic tests to 588 participants from the ELSA-Brazil longitudinal study cohort. The PAT measurements, obtained with the EndoPAT2000, were the reactive hyperemia index (RHI), the Framingham RHI (F-RHI), and the mean basal pulse amplitude (BPA). We used the mean of the mean scores of carotid IMT of the distal layers of the left and right common carotids obtained by ultrasonography after 3 cardiac cycles. We used linear regression and the Spearman correlation coefficient to test the relationship between the 2 markers, and multiple linear regressions to exam the relationship between the RHI/F-RHI scores and the mean BPA and IMT scores after adjusting for cardiovascular risk factors.In the multivariate analysis, RHI (but not F-RHI) was positively correlated with the mean of the means of the IMT values after adjusting for sex and risk factors connected with both measures (β = 0.05, P = 0.02). Mean BPA did not remain significantly associated with IMT after adjusting for common risk factors.We found that the higher the IMT (or the worse the IMT), the higher the RHI (or the better the endothelial function). F-RHI was not associated with IMT. These 2 results are against the direction that one would expect and may imply that digital endothelial function (RHI and F-RHI) and IMT correspond to distinct and independent stages of the complex atherosclerosis process and represent different pathways in the disease's progression. Therefore, IMT and PAT measures may be considered complementary and not interchangeable.

A Snack Dietary Pattern Increases the Risk of Hypercholesterolemia in Northern Chinese Adults: A Prospective Cohort Study.

PubMed

Na, Lixin; Han, Tianshu; Zhang, Wei; Wu, Xiaoyan; Na, Guanqiong; Du, Shanshan; Li, Ying; Sun, Changhao

2015-01-01

The evidence about the effect of dietary patterns on blood cholesterol from cohort studies was very scarce. The study was to identify the association of dietary patterns with lipid profile, especially cholesterol, in a cohort in north China. Using a 1-year food frequency questionnaire, we assessed the dietary intake of 4515 adults from the Harbin People's Health Study in 2008, aged 20-74 years. Principle component analysis was used to identify dietary patterns. The follow-up was completed in 2012. Fasting blood samples were collected for the determination of blood lipid concentrations. Logistic regression models were used to evaluate the association of dietary patterns with the incidence of hypercholesterolemia, hypertriglyceridemia, and low-HDL cholesterolemia. Five dietary patterns were identified ("staple food", "vegetable, fruit and milk", "potato, soybean and egg", "snack", and "meat"). The relative risk (RR) between the extreme tertiles of the snack dietary pattern scores was 1.72 (95% CI = 1.14, 2.59, P = 0.004) for hypercholesterolemia, 1.39 (1.13, 1.75, P = 0.036) for hypertriglyceridemia, after adjustment for age, sex, education, body mass index, smoking, alcohol consumption, energy intake, exercise and baseline lipid concentrations. There was a significant positive association between the snack dietary pattern scores and fasting serum total cholesterol (SRC (standardized regression coefficient) = 0.262, P = 0.025), LDL-c (SRC = 0.324, P = 0.002) and triglycerides (SRC = 0.253, P = 0.035), after adjustment for the multiple variables above. Moreover, the adjusted RR of hypertriglyceridemia between the extreme tertiles was 0.73 (0.56, 0.94, P = 0.025) for the vegetable, fruit and milk dietary pattern, and 1.86 (1.33, 2.41, P = 0.005) for the meat dietary pattern. The snack dietary pattern was a newly emerged dietary pattern in northern Chinese adults. It appears conceivable that the risk of hypercholesterolemia can be reduced by changing the snack dietary pattern.

Predicting Salt Permeability Coefficients in Highly Swollen, Highly Charged Ion Exchange Membranes.

PubMed

Kamcev, Jovan; Paul, Donald R; Manning, Gerald S; Freeman, Benny D

2017-02-01

This study presents a framework for predicting salt permeability coefficients in ion exchange membranes in contact with an aqueous salt solution. The model, based on the solution-diffusion mechanism, was tested using experimental salt permeability data for a series of commercial ion exchange membranes. Equilibrium salt partition coefficients were calculated using a thermodynamic framework (i.e., Donnan theory), incorporating Manning's counterion condensation theory to calculate ion activity coefficients in the membrane phase and the Pitzer model to calculate ion activity coefficients in the solution phase. The model predicted NaCl partition coefficients in a cation exchange membrane and two anion exchange membranes, as well as MgCl 2 partition coefficients in a cation exchange membrane, remarkably well at higher external salt concentrations (>0.1 M) and reasonably well at lower external salt concentrations (<0.1 M) with no adjustable parameters. Membrane ion diffusion coefficients were calculated using a combination of the Mackie and Meares model, which assumes ion diffusion in water-swollen polymers is affected by a tortuosity factor, and a model developed by Manning to account for electrostatic effects. Agreement between experimental and predicted salt diffusion coefficients was good with no adjustable parameters. Calculated salt partition and diffusion coefficients were combined within the framework of the solution-diffusion model to predict salt permeability coefficients. Agreement between model and experimental data was remarkably good. Additionally, a simplified version of the model was used to elucidate connections between membrane structure (e.g., fixed charge group concentration) and salt transport properties.

A SEMIPARAMETRIC BAYESIAN MODEL FOR CIRCULAR-LINEAR REGRESSION

EPA Science Inventory

We present a Bayesian approach to regress a circular variable on a linear predictor. The regression coefficients are assumed to have a nonparametric distribution with a Dirichlet process prior. The semiparametric Bayesian approach gives added flexibility to the model and is usefu...

Telomere attrition, kidney function, and prevalent chronic kidney disease in the United States.

PubMed

Mazidi, Moshen; Rezaie, Peyman; Covic, Adriac; Malyszko, Jolanta; Rysz, Jacek; Kengne, Andre Pascal; Banach, Maciej

2017-10-06

Telomere length is an emerging novel biomarker of biologic age, cardiovascular risk and chronic medical conditions. Few studies have focused on the association between telomere length (TL) and kidney function. We investigated the association between TL and kidney function/prevalent chronic kidney disease (CKD) in US adults. The National Health and Nutrition Examination Survey (NHANES) participants with measured data on kidney function and TL from 1999 to 2002 were included. Estimated glomerular filtration rate (eGFR) was based on CKD Epidemiology Collaboration (CKD-EPI) equation. Urinary albumin excretion was assessed using urinary albumin-creatinine ratio (ACR). We used multivariable adjusted linear and logistic regression models, accounting for the survey design and sample weights. Of the 10568 eligible participants, 48.0% ( n =5020) were men. Their mean age was 44.1 years. eGFR significantly decreased and ACR significantly increased across increasing quarters of TL (all p <0.001). The association between TL and kidney function remained robust even after adjusting for potential confounding factors, but the association between TL and ACR was only borderline significant (β-coefficient= -0.012, p =0.056). The association of kidney function with a marker of cellular senescence suggests an underlying mechanism influencing the progression of nephropathy.

Mechanical dyssynchrony is additive to ECG criteria and independently associated with reverse remodelling and clinical response to cardiac resynchronisation therapy in patients with advanced heart failure

PubMed Central

Bank, Alan J; Gage, Ryan M; Marek, Josef J; Onishi, Toshinari; Burns, Kevin V; Schwartzman, David; Saba, Samir; Gorcsan, John

2015-01-01

Background QRS duration and morphology are known established predictors of cardiac resynchronisation therapy (CRT) response, whereas mechanical dyssynchrony is not. Our aim was to determine if mechanical dyssynchrony provides independent prognostic information on CRT response. Methods We studied 369 consecutive patients with heart failure (HF) with low ejection fraction (EF) and widened QRS receiving CRT. Radial dyssynchrony (septal-posterior radial peak strain delay ≥130 ms by speckle tracking) assessment was possible in 318 patients (86%). Associations with left ventricular end-systolic volume (LVESV) changes were examined using linear regression, and clinical outcomes analysed using Cox regression adjusted for multiple established outcome correlates. Results Patients with radial dyssynchrony before CRT (64%) had greater improvements in EF (8.8±9.4 vs 6.1±9.7 units, p=0.04) and LVESV (−30±41 vs −10±30 mL, p<0.01). Radial dyssynchrony was independently associated with reduction in LVESV (regression coefficient −10.5 mL, 95% CI −20.5 to −0.5, p=0.040) as was left bundle-branch block (−17.7 mL, −27.6 to −7.7, p=0.001). Patients with radial dyssynchrony had a 46% lower incidence of death, transplant or implantation of a left ventricular assist device (adjusted HR 0.54, 95% CI 0.31 to 0.92, p=0.02) and a 39% lower incidence of death or HF hospitalisation (0.61, 0.40 to 0.93, p=0.02) over 2 years. Conclusions Radial dyssynchrony was associated with significant improvements in LVESV and clinical outcomes following CRT and is independent of QRS duration or morphology, and additive to current ECG selection criteria to predict response to CRT. PMID:25973213

Volume and functional outcome of intracerebral hemorrhage according to oral anticoagulant type

PubMed Central

Wilson, Duncan; Charidimou, Andreas; Shakeshaft, Clare; Ambler, Gareth; White, Mark; Cohen, Hannah; Yousry, Tarek; Al-Shahi Salman, Rustam; Lip, Gregory Y.H.; Brown, Martin M.; Jäger, Hans Rolf

2016-01-01

Objective: To compare intracerebral hemorrhage (ICH) volume and clinical outcome of non–vitamin K oral anticoagulants (NOAC)–associated ICH to warfarin-associated ICH. Methods: In this multicenter cross-sectional observational study of patients with anticoagulant-associated ICH, consecutive patients with NOAC-ICH were compared to those with warfarin-ICH selected from a population of 344 patients with anticoagulant-associated ICH. ICH volume was measured by an observer blinded to clinical details. Outcome measures were ICH volume and clinical outcome adjusted for confounding factors. Results: We compared 11 patients with NOAC-ICH to 52 patients with warfarin-ICH. The median ICH volume was 2.4 mL (interquartile range [IQR] 0.3–5.4 mL) for NOAC-ICH vs 8.9 mL (IQR 4.0–21.3 mL) for warfarin-ICH (p = 0.0028). In univariate linear regression, use of warfarin (difference in cube root volume 1.61; 95% confidence interval [CI] 0.69 to 2.53) and lobar ICH location (compared with nonlobar ICH; difference in cube root volume 1.52; 95% CI 2.20 to 0.85) were associated with larger ICH volumes. In multivariable linear regression adjusting for confounding factors (sex, hypertension, previous ischemic stroke, white matter disease burden, and premorbid modified Rankin Scale score [mRS]), warfarin use remained independently associated with larger ICH (cube root) volumes (coefficient 0.64; 95% CI 0.24 to 1.25; p = 0.042). Ordered logistic regression showed an increased odds of a worse clinical outcome (as measured by discharge mRS) in warfarin-ICH compared with NOAC-ICH: odds ratio 4.46 (95% CI 1.10 to 18.14; p = 0.037). Conclusions: In this small prospective observational study, patients with NOAC-associated ICH had smaller ICH volumes and better clinical outcomes compared with warfarin-associated ICH. PMID:26718576

Volume and functional outcome of intracerebral hemorrhage according to oral anticoagulant type.

PubMed

Wilson, Duncan; Charidimou, Andreas; Shakeshaft, Clare; Ambler, Gareth; White, Mark; Cohen, Hannah; Yousry, Tarek; Al-Shahi Salman, Rustam; Lip, Gregory Y H; Brown, Martin M; Jäger, Hans Rolf; Werring, David J

2016-01-26

To compare intracerebral hemorrhage (ICH) volume and clinical outcome of non-vitamin K oral anticoagulants (NOAC)-associated ICH to warfarin-associated ICH. In this multicenter cross-sectional observational study of patients with anticoagulant-associated ICH, consecutive patients with NOAC-ICH were compared to those with warfarin-ICH selected from a population of 344 patients with anticoagulant-associated ICH. ICH volume was measured by an observer blinded to clinical details. Outcome measures were ICH volume and clinical outcome adjusted for confounding factors. We compared 11 patients with NOAC-ICH to 52 patients with warfarin-ICH. The median ICH volume was 2.4 mL (interquartile range [IQR] 0.3-5.4 mL) for NOAC-ICH vs 8.9 mL (IQR 4.0-21.3 mL) for warfarin-ICH (p = 0.0028). In univariate linear regression, use of warfarin (difference in cube root volume 1.61; 95% confidence interval [CI] 0.69 to 2.53) and lobar ICH location (compared with nonlobar ICH; difference in cube root volume 1.52; 95% CI 2.20 to 0.85) were associated with larger ICH volumes. In multivariable linear regression adjusting for confounding factors (sex, hypertension, previous ischemic stroke, white matter disease burden, and premorbid modified Rankin Scale score [mRS]), warfarin use remained independently associated with larger ICH (cube root) volumes (coefficient 0.64; 95% CI 0.24 to 1.25; p = 0.042). Ordered logistic regression showed an increased odds of a worse clinical outcome (as measured by discharge mRS) in warfarin-ICH compared with NOAC-ICH: odds ratio 4.46 (95% CI 1.10 to 18.14; p = 0.037). In this small prospective observational study, patients with NOAC-associated ICH had smaller ICH volumes and better clinical outcomes compared with warfarin-associated ICH. © 2015 American Academy of Neurology.

Empirical likelihood inference in randomized clinical trials.

PubMed

Zhang, Biao

2017-01-01

In individually randomized controlled trials, in addition to the primary outcome, information is often available on a number of covariates prior to randomization. This information is frequently utilized to undertake adjustment for baseline characteristics in order to increase precision of the estimation of average treatment effects; such adjustment is usually performed via covariate adjustment in outcome regression models. Although the use of covariate adjustment is widely seen as desirable for making treatment effect estimates more precise and the corresponding hypothesis tests more powerful, there are considerable concerns that objective inference in randomized clinical trials can potentially be compromised. In this paper, we study an empirical likelihood approach to covariate adjustment and propose two unbiased estimating functions that automatically decouple evaluation of average treatment effects from regression modeling of covariate-outcome relationships. The resulting empirical likelihood estimator of the average treatment effect is as efficient as the existing efficient adjusted estimators 1 when separate treatment-specific working regression models are correctly specified, yet are at least as efficient as the existing efficient adjusted estimators 1 for any given treatment-specific working regression models whether or not they coincide with the true treatment-specific covariate-outcome relationships. We present a simulation study to compare the finite sample performance of various methods along with some results on analysis of a data set from an HIV clinical trial. The simulation results indicate that the proposed empirical likelihood approach is more efficient and powerful than its competitors when the working covariate-outcome relationships by treatment status are misspecified.

Heavy metal bioaccumulation by Miscanthus sacchariflorus and its potential for removing metals from the Dongting Lake wetlands, China.

PubMed

Yao, Xin; Niu, Yandong; Li, Youzhi; Zou, Dongsheng; Ding, Xiaohui; Bian, Hualin

2018-05-09

Bioaccumulation of five heavy metals (Cd, Cu, Mn, Pb, and Zn) in six plant organs (panicle, leaf, stem, root, rhizome, and bud) of the emergent and perennial plant species, Miscanthus sacchariflorus, were investigated to estimate the plant's potential for accumulating heavy metals in the wetlands of Dongting Lake. We found the highest Cd concentrations in the panicles and leaves; while the highest Cu and Mn were observed in the roots, the highest Pb in the panicles, and the highest Zn in the panicles and buds. In contrast, the lowest Cd concentrations were detected in the stem, roots, and buds; the lowest Cu concentrations in the leaves and stems; the lowest Mn concentrations in the panicles, rhizomes, and buds; the lowest Pb concentrations in the stems; and the lowest Zn concentrations in the leaves, stems, and rhizomes. Mean Cu concentration in the plant showed a positive regression coefficient with plot elevation, soil organic matter content, and soil Cu concentration, whereas it showed a negative regression coefficient with soil moisture and electrolyte leakage. Mean Mn concentration showed positive and negative regression coefficients with soil organic matter and soil moisture, respectively. Mean Pb concentration exhibited positive regression coefficient with plot elevation and soil total P concentration, and Zn concentration showed a positive regression coefficient with soil available P and total P concentrations. However, there was no significant regression coefficient between mean Cd concentration in the plant and the investigated environmental parameters. Stems and roots were the main organs involved in heavy metal accumulation from the environment. The mean quantities of heavy metals accumulated in the plant tissues were 2.2 mg Cd, 86.7 mg Cu, 290.3 mg Mn, 15.9 mg Pb, and 307 mg Zn per square meter. In the Dongting Lake wetlands, 0.7 × 10 3  kg Cd, 22.9 × 10 3  kg Cu, 77.5 × 10 3  kg Mn, 3.1 × 10 3  kg Pb, and 95.9 × 10 3  kg Zn per year were accumulated by aboveground organs and removed from the lake through harvesting for paper manufacture.

Spectral regression and correlation coefficients of some benzaldimines and salicylaldimines in different solvents

NASA Astrophysics Data System (ADS)

Hammud, Hassan H.; Ghannoum, Amer; Masoud, Mamdouh S.

2006-02-01

Sixteen Schiff bases obtained from the condensation of benzaldehyde or salicylaldehyde with various amines (aniline, 4-carboxyaniline, phenylhydrazine, 2,4-dinitrophenylhydrazine, ethylenediamine, hydrazine, o-phenylenediamine and 2,6-pyridinediamine) are studied with UV-vis spectroscopy to observe the effect of solvents, substituents and other structural factors on the spectra. The bands involving different electronic transitions are interpreted. Computerized analysis and multiple regression techniques were applied to calculate the regression and correlation coefficients based on the equation that relates peak position λmax to the solvent parameters that depend on the H-bonding ability, refractive index and dielectric constant of solvents.

Heritability of Respiratory Infection with Pseudomonas aeruginosa in Cystic Fibrosis

PubMed Central

Green, Deanna M.; Collaco, J. Michael; McDougal, Kathryn E.; Naughton, Kathleen M.; Blackman, Scott M.; Cutting, Garry R.

2013-01-01

Objective To quantify the relative contribution of factors other than cystic fibrosis transmembrane conductance regulator genotype and environment on the acquisition of Pseudomonas aeruginosa (Pa) by patients with cystic fibrosis. Study design Lung infection with Pa and mucoid Pa was assessed using a co-twin study design of 44 monozygous (MZ) and 17 dizygous (DZ) twin pairs. Two definitions were used to establish infection: first positive culture and persistent positive culture. Genetic contribution to infection (ie, heritability) was estimated based on concordance analysis, logistic regression, and age at onset of infection through comparison of intraclass correlation coefficients. Results Concordance for persistent Pa infection was higher in MZ (0.83; 25 of 30 pairs) than DZ twins (0.45; 5 of 11 pairs), generating a heritability of 0.76. Logistic regression adjusted for age corroborated genetic control of persistent Pa infection. The correlation for age at persistent Pa infection was higher in MZ twins (0.589; 95% CI, 0.222-0.704) than in DZ twins (0.162; 95% CI, −0.352 to 0.607), generating a heritability of 0.85. Conclusion Genetic modifiers play a significant role in the establishment and timing of persistent Pa infection in individuals with cystic fibrosis. PMID:22364820

Neutropenia is independently associated with sub-therapeutic serum concentration of vancomycin.

PubMed

Choi, Min Hyuk; Choe, Yeon Hwa; Lee, Sang-Guk; Jeong, Seok Hoon; Kim, Jeong-Ho

2017-02-01

We aimed to identify the impact of the presence of neutropenia on serum vancomycin concentration (SVC). A retrospective study was conducted from January 2005 to December 2015. The study population was comprised of adult patients who were performed serum concentration of vancomycin. Patients with renal failure or using non-conventional dosages of vancomycin were excluded. A total of 1307 adult patients were included in this study, of whom 163 (12.4%) were neutropenic. Patients with neutropenia presented significantly lower SVCs than non-neutropenic patients (P<0.0001). Multiple linear regressions showed significant association between neutropenia and trough SVC (beta coefficients, -2.351; P=0.004). Multiple logistic regression analysis also revealed a significant association between sub-therapeutic vancomycin concentrations (trough SVC values<10mg/l) and neutropenia (odds ratio, 1.75, P=0.029) CONCLUSIONS: The presence of neutropenia is significantly associated with low SVC, even after adjusting for other variables. Therefore, neutropenic patients had a higher risk of sub-therapeutic SVC compared with non-neutropenic patients. We recommended that vancomycin therapy should be monitored with TDM-guided optimization of dosage and intervals, especially in neutropenic patients. Copyright © 2016 Elsevier B.V. All rights reserved.

Modelling of the batch biosorption system: study on exchange of protons with cell wall-bound mineral ions.

PubMed

Mishra, Vishal

2015-01-01

The interchange of the protons with the cell wall-bound calcium and magnesium ions at the interface of solution/bacterial cell surface in the biosorption system at various concentrations of protons has been studied in the present work. A mathematical model for establishing the correlation between concentration of protons and active sites was developed and optimized. The sporadic limited residence time reactor was used to titrate the calcium and magnesium ions at the individual data point. The accuracy of the proposed mathematical model was estimated using error functions such as nonlinear regression, adjusted nonlinear regression coefficient, the chi-square test, P-test and F-test. The values of the chi-square test (0.042-0.017), P-test (<0.001-0.04), sum of square errors (0.061-0.016), root mean square error (0.01-0.04) and F-test (2.22-19.92) reported in the present research indicated the suitability of the model over a wide range of proton concentrations. The zeta potential of the bacterium surface at various concentrations of protons was observed to validate the denaturation of active sites.

The Use of Alternative Regression Methods in Social Sciences and the Comparison of Least Squares and M Estimation Methods in Terms of the Determination of Coefficient

ERIC Educational Resources Information Center

Coskuntuncel, Orkun

2013-01-01

The purpose of this study is two-fold; the first aim being to show the effect of outliers on the widely used least squares regression estimator in social sciences. The second aim is to compare the classical method of least squares with the robust M-estimator using the "determination of coefficient" (R[superscript 2]). For this purpose,…

Methods for peak-flow frequency analysis and reporting for streamgages in or near Montana based on data through water year 2015

USGS Publications Warehouse

Sando, Steven K.; McCarthy, Peter M.

2018-05-10

This report documents the methods for peak-flow frequency (hereinafter “frequency”) analysis and reporting for streamgages in and near Montana following implementation of the Bulletin 17C guidelines. The methods are used to provide estimates of peak-flow quantiles for 50-, 42.9-, 20-, 10-, 4-, 2-, 1-, 0.5-, and 0.2-percent annual exceedance probabilities for selected streamgages operated by the U.S. Geological Survey Wyoming-Montana Water Science Center (WY–MT WSC). These annual exceedance probabilities correspond to 2-, 2.33-, 5-, 10-, 25-, 50-, 100-, 200-, and 500-year recurrence intervals, respectively.Standard procedures specific to the WY–MT WSC for implementing the Bulletin 17C guidelines include (1) the use of the Expected Moments Algorithm analysis for fitting the log-Pearson Type III distribution, incorporating historical information where applicable; (2) the use of weighted skew coefficients (based on weighting at-site station skew coefficients with generalized skew coefficients from the Bulletin 17B national skew map); and (3) the use of the Multiple Grubbs-Beck Test for identifying potentially influential low flows. For some streamgages, the peak-flow records are not well represented by the standard procedures and require user-specified adjustments informed by hydrologic judgement. The specific characteristics of peak-flow records addressed by the informed-user adjustments include (1) regulated peak-flow records, (2) atypical upper-tail peak-flow records, and (3) atypical lower-tail peak-flow records. In all cases, the informed-user adjustments use the Expected Moments Algorithm fit of the log-Pearson Type III distribution using the at-site station skew coefficient, a manual potentially influential low flow threshold, or both.Appropriate methods can be applied to at-site frequency estimates to provide improved representation of long-term hydroclimatic conditions. The methods for improving at-site frequency estimates by weighting with regional regression equations and by Maintenance of Variance Extension Type III record extension are described.Frequency analyses were conducted for 99 example streamgages to indicate various aspects of the frequency-analysis methods described in this report. The frequency analyses and results for the example streamgages are presented in a separate data release associated with this report consisting of tables and graphical plots that are structured to include information concerning the interpretive decisions involved in the frequency analyses. Further, the separate data release includes the input files to the PeakFQ program, version 7.1, including the peak-flow data file and the analysis specification file that were used in the peak-flow frequency analyses. Peak-flow frequencies are also reported in separate data releases for selected streamgages in the Beaverhead River and Clark Fork Basins and also for selected streamgages in the Ruby, Jefferson, and Madison River Basins.

Multicollinearity and Regression Analysis

NASA Astrophysics Data System (ADS)

Daoud, Jamal I.

2017-12-01

In regression analysis it is obvious to have a correlation between the response and predictor(s), but having correlation among predictors is something undesired. The number of predictors included in the regression model depends on many factors among which, historical data, experience, etc. At the end selection of most important predictors is something objective due to the researcher. Multicollinearity is a phenomena when two or more predictors are correlated, if this happens, the standard error of the coefficients will increase [8]. Increased standard errors means that the coefficients for some or all independent variables may be found to be significantly different from In other words, by overinflating the standard errors, multicollinearity makes some variables statistically insignificant when they should be significant. In this paper we focus on the multicollinearity, reasons and consequences on the reliability of the regression model.

QSAR modeling of flotation collectors using principal components extracted from topological indices.

PubMed

Natarajan, R; Nirdosh, Inderjit; Basak, Subhash C; Mills, Denise R

2002-01-01

Several topological indices were calculated for substituted-cupferrons that were tested as collectors for the froth flotation of uranium. The principal component analysis (PCA) was used for data reduction. Seven principal components (PC) were found to account for 98.6% of the variance among the computed indices. The principal components thus extracted were used in stepwise regression analyses to construct regression models for the prediction of separation efficiencies (Es) of the collectors. A two-parameter model with a correlation coefficient of 0.889 and a three-parameter model with a correlation coefficient of 0.913 were formed. PCs were found to be better than partition coefficient to form regression equations, and inclusion of an electronic parameter such as Hammett sigma or quantum mechanically derived electronic charges on the chelating atoms did not improve the correlation coefficient significantly. The method was extended to model the separation efficiencies of mercaptobenzothiazoles (MBT) and aminothiophenols (ATP) used in the flotation of lead and zinc ores, respectively. Five principal components were found to explain 99% of the data variability in each series. A three-parameter equation with correlation coefficient of 0.985 and a two-parameter equation with correlation coefficient of 0.926 were obtained for MBT and ATP, respectively. The amenability of separation efficiencies of chelating collectors to QSAR modeling using PCs based on topological indices might lead to the selection of collectors for synthesis and testing from a virtual database.

Correcting Coefficient Alpha for Correlated Errors: Is [alpha][K]a Lower Bound to Reliability?

ERIC Educational Resources Information Center

Rae, Gordon

2006-01-01

When errors of measurement are positively correlated, coefficient alpha may overestimate the "true" reliability of a composite. To reduce this inflation bias, Komaroff (1997) has proposed an adjusted alpha coefficient, ak. This article shows that ak is only guaranteed to be a lower bound to reliability if the latter does not include correlated…

Liver steatosis is associated with insulin resistance in skeletal muscle rather than in the liver in Japanese patients with non-alcoholic fatty liver disease.

PubMed

Kato, Ken-Ichiro; Takeshita, Yumie; Misu, Hirofumi; Zen, Yoh; Kaneko, Shuichi; Takamura, Toshinari

2015-03-01

To examine the association between liver histological features and organ-specific insulin resistance indices calculated from 75-g oral glucose tolerance test data in patients with non-alcoholic fatty liver disease. Liver biopsy specimens were obtained from 72 patients with non-alcoholic fatty liver disease, and were scored for steatosis, grade and stage. Hepatic and skeletal muscle insulin resistance indices (hepatic insulin resistance index and Matsuda index, respectively) were calculated from 75-g oral glucose tolerance test data, and metabolic clearance rate was measured using the euglycemic hyperinsulinemic clamp method. The degree of hepatic steatosis, and grade and stage of non-alcoholic steatohepatitis were significantly correlated with Matsuda index (steatosis r = -0.45, P < 0.001; grade r = -0.54, P < 0.001; stage r = -0.37, P < 0.01), but not with hepatic insulin resistance index. Multiple regression analyses adjusted for age, sex, body mass index and each histological score showed that the degree of hepatic steatosis (coefficient = -0.22, P < 0.05) and grade (coefficient = -0.40, P < 0.01) were associated with Matsuda index, whereas the association between stage and Matsuda index (coefficient = -0.07, P = 0.593) was no longer significant. A similar trend was observed for the association between steatosis and metabolic clearance rate (coefficient = -0.62, P = 0.059). Liver steatosis is associated with insulin resistance in skeletal muscle rather than in the liver in patients with non-alcoholic fatty liver disease, suggesting a central role of fatty liver in the development of peripheral insulin resistance and the existence of a network between the liver and skeletal muscle.

Parametric regression model for survival data: Weibull regression model as an example

PubMed Central

2016-01-01

Weibull regression model is one of the most popular forms of parametric regression model that it provides estimate of baseline hazard function, as well as coefficients for covariates. Because of technical difficulties, Weibull regression model is seldom used in medical literature as compared to the semi-parametric proportional hazard model. To make clinical investigators familiar with Weibull regression model, this article introduces some basic knowledge on Weibull regression model and then illustrates how to fit the model with R software. The SurvRegCensCov package is useful in converting estimated coefficients to clinical relevant statistics such as hazard ratio (HR) and event time ratio (ETR). Model adequacy can be assessed by inspecting Kaplan-Meier curves stratified by categorical variable. The eha package provides an alternative method to model Weibull regression model. The check.dist() function helps to assess goodness-of-fit of the model. Variable selection is based on the importance of a covariate, which can be tested using anova() function. Alternatively, backward elimination starting from a full model is an efficient way for model development. Visualization of Weibull regression model after model development is interesting that it provides another way to report your findings. PMID:28149846

Standardized Regression Coefficients as Indices of Effect Sizes in Meta-Analysis

ERIC Educational Resources Information Center

Kim, Rae Seon

2011-01-01

When conducting a meta-analysis, it is common to find many collected studies that report regression analyses, because multiple regression analysis is widely used in many fields. Meta-analysis uses effect sizes drawn from individual studies as a means of synthesizing a collection of results. However, indices of effect size from regression analyses…

The Associations of Serum Lipids with Vitamin D Status.

PubMed

Wang, Ying; Si, Shaoyan; Liu, Junli; Wang, Zongye; Jia, Haiying; Feng, Kai; Sun, Lili; Song, Shu Jun

2016-01-01

Vitamin D deficiency has been associated with some disorders including cardiovascular diseases. Dyslipidemia is a major risk factor for cardiovascular diseases. However, data about the relationships between vitamin D and lipids are inconsistent. The relationship of vitamin D and Atherogenic Index of Plasma (AIP), as an excellent predictor of level of small and dense LDL, has not been reported. The objective of this study was to investigate the effects of vitamin D status on serum lipids in Chinese adults. The study was carried out using 1475 participants from the Center for Physical Examination, 306 Hospital of PLA in Beijing, China. Fasting blood samples were collected and serum concentrations of 25(OH)D, total cholesterol (TC), triglyceride (TG), high density lipoprotein cholesterol (HDL-C) and low density lipoprotein cholesterol (LDL-C) were measured. AIP was calculated based on the formula: log [TG/HDL-C]. Multiple linear regression analysis was used to estimate the associations between serum 25(OH)D and lipids. The association between the occurrences of dyslipidemias and vitamin D levels was assessed by multiple logistic regression analysis. Confounding factors, age and BMI, were used for the adjustment. The median of serum 25(OH)D concentration was 47 (27-92.25) nmol/L in all subjects. The overall percentage of 25(OH)D ≦ 50 nmol/L was 58.5% (males 54.4%, females 63.7%). The serum 25(OH)D levels were inversely associated with TG (β coefficient = -0.24, p < 0.001) and LDL-C (β coefficient = -0.34, p < 0.001) and positively associated with TC (β coefficient = 0.35, p < 0.002) in men. The associations between serum 25(OH)D and LDL-C (β coefficient = -0.25, p = 0.01) and TC (β coefficient = 0.39, p = 0.001) also existed in women. The serum 25(OH)D concentrations were negatively associated with AIP in men (r = -0.111, p < 0.01) but not in women. In addition, vitamin D deficient men had higher AIP values than vitamin D sufficient men. Furthermore, the occurrences of dyslipidemias (reduced HDL-C, elevated TG and elevated AIP) correlated with lower 25(OH)D levels in men, whereas the higher TC and LDL-C associated with higher 25(OH)D levels in women. It seems that the serum 25(OH)D levels are closely associated with the serum lipids and AIP. Vitamin D deficiency may be associated with the increased risk of dyslipidemias, especially in men. The association between vitamin D status and serum lipids may differ by genders.

The solar wind effect on cosmic rays and solar activity

NASA Technical Reports Server (NTRS)

Fujimoto, K.; Kojima, H.; Murakami, K.

1985-01-01

The relation of cosmic ray intensity to solar wind velocity is investigated, using neutron monitor data from Kiel and Deep River. The analysis shows that the regression coefficient of the average intensity for a time interval to the corresponding average velocity is negative and that the absolute effect increases monotonously with the interval of averaging, tau, that is, from -0.5% per 100km/s for tau = 1 day to -1.1% per 100km/s for tau = 27 days. For tau 27 days the coefficient becomes almost constant independently of the value of tau. The analysis also shows that this tau-dependence of the regression coefficiently is varying with the solar activity.

Adherence to the Mediterranean diet and quality of life in the SUN Project.

PubMed

Henríquez Sánchez, P; Ruano, C; de Irala, J; Ruiz-Canela, M; Martínez-González, M A; Sánchez-Villegas, A

2012-03-01

Mediterranean diet has been related with reduced morbidity and better well-being. The aim of this study was to assess whether the adherence to the Mediterranean diet were associated with mental and physical health related to quality of life. This analysis included 11 015 participants with 4 years of follow-up in the SUN Project (a multipurpose cohort study based on university graduates from Spain). A validated 136-item food frequency questionnaire was used to assess the adherence to the Mediterranean diet at baseline, according to a nine-point score, presented in four categories (low, low-moderate, moderate-high and high). Health-related quality of life (HRQL) was measured after 4 years of follow-up with the Spanish version of the SF-36 Health Survey. Generalized Linear Models were fitted to assess adjusted mean scores, the regression coefficients (β) and their 95% confidence intervals (95% CIs) for the SF-36 domains according to categories of adherence to Mediterranean diet. Multivariate-adjusted models revealed a significant direct association between adherence to Mediterranean diet and all the physical and most mental health domains (vitality, social functioning and role emotional). Vitality (β=0.50, 95% CI=0.32-0.68) and general health (β=0.45, 95% CI=0.26-0.62) showed the highest coefficients. Mean values for physical functioning, role physical, bodily pain, general health and vitality domains were significantly better with increasing adherence to the Mediterranean diet. Those having improved their initial high diet scores have better scores in physical functioning, general health and vitality. Adherence to the Mediterranean diet seems to be a factor importantly associated with a better HRQL.

Relationship between markers of body fat and calcaneal bone stiffness differs between preschool and primary school children: results from the IDEFICS baseline survey.

PubMed

Sioen, Isabelle; Mouratidou, Theodora; Herrmann, Diana; De Henauw, Stefaan; Kaufman, Jean-Marc; Molnár, Dénes; Moreno, Luis A; Marild, Staffan; Barba, Gianvincenzo; Siani, Alfonso; Gianfagna, Francesco; Tornaritis, Michael; Veidebaum, Toomas; Ahrens, Wolfgang

2012-10-01

The aim of this study was to investigate the relationship between markers of body fat and bone status assessed as calcaneal bone stiffness in a large sample of European healthy pre- and primary school children. Participants were 7,447 children from the IDEFICS study (spread over eight different European countries), age 6.1 ± 1.8 years (range 2.1-9.9), 50.5 % boys. Anthropometric measurements (weight, height, bioelectrical impedance, waist and hip circumference, and tricipital and subscapular skinfold thickness) as well as quantitative ultrasonographic measurements to determine calcaneal stiffness index (SI) were performed. Partial correlation analysis, linear regression analysis, and ANCOVA were stratified by sex and age group: preschool boys (n = 1,699) and girls (n = 1,599) and primary school boys (n = 2,062) and girls (n = 2,087). In the overall study population, the average calcaneal SI was equal to 80.2 ± 14.0, ranging 42.4-153. The results showed that preschool children with higher body fat had lower calcaneal SI (significant correlation coefficients between -0.05 and -0.20), while primary school children with higher body fat had higher calcaneal SI (significant correlation coefficients between 0.05 and 0.13). After adjusting for fat-free mass, both preschool and primary school children showed an inverse relationship between body fat and calcaneal stiffness. To conclude, body fat is negatively associated with calcaneal bone stiffness in children after adjustment for fat-free mass. Fat-free mass may confound the association in primary school children but not in preschool children. Muscle mass may therefore be an important determinant of bone stiffness.

Bisphenol A Exposure Is Associated with in Vivo Estrogenic Gene Expression in Adults

PubMed Central

Melzer, David; Harries, Lorna; Cipelli, Riccardo; Henley, William; Money, Cathryn; McCormack, Paul; Young, Anita; Guralnik, Jack; Ferrucci, Luigi; Bandinelli, Stefania; Corsi, Anna Maria

2011-01-01

Background: Bisphenol A (BPA) is a synthetic estrogen commonly used in polycarbonate plastic and resin-lined food and beverage containers. Exposure of animal and cell models to doses of BPA below the recommended tolerable daily intake (TDI) of 50 μg/kg/day have been shown to alter specific estrogen-responsive gene expression, but this has not previously been shown in humans. Objective: We investigated associations between BPA exposure and in vivo estrogenic gene expression in humans. Methods: We studied 96 adult men from the InCHIANTI population study and examined in vivo expression of six estrogen receptor, estrogen-related receptor, and androgen receptor genes in peripheral blood leukocytes. Results: The geometric mean urinary BPA concentration was 3.65 ng/mL [95% confidence interval (CI): 3.13, 4.28], giving an estimated mean excretion of 5.84 μg/day (95% CI: 5.00, 6.85), significantly below the current TDI. In age-adjusted models, there were positive associations between higher BPA concentrations and higher ESR2 [estrogen receptor 2 (ER beta)] expression (unstandardized linear regression coefficient = 0.1804; 95% CI: 0.0388, 0.3221; p = 0.013) and ESRRA (estrogen related receptor alpha) expression (coefficient = 0.1718; 95% CI: 0.0213, 0.3223; p = 0.026): These associations were little changed after adjusting for potential confounders, including obesity, serum lipid concentrations, and white cell subtype percentages. Upper-tertile BPA excretors (urinary BPA > 4.6 ng/mL) had 65% higher mean ESR2 expression than did lower-tertile BPA excretors (0–2.4 ng/mL). Conclusions: Because activation of nuclear-receptor–mediated pathways by BPA is consistently found in laboratory studies, such activation in humans provides evidence that BPA is likely to function as a xenoestrogen in this sample of adults. PMID:21831745

Diabetes mellitus, hypertension and frailty: A population-based, cross-sectional study of Mexican older adults.

PubMed

Castrejón-Pérez, Roberto Carlos; Gutiérrez-Robledo, Luis Miguel; Cesari, Matteo; Pérez-Zepeda, Mario Ulises

2017-06-01

Chronic diseases are frequent in older adults, particularly hypertension and diabetes. The relationship between frailty and these two conditions is still unclear. The aim of the present analyses was to explore the association between frailty with diabetes and hypertension in Mexican older adults. Analyses of the Mexican Health and Nutrition Survey, a cross-sectional survey, are presented. Data on diabetes and hypertension were acquired along with associated conditions (time since diagnosis, pharmacological treatment, among others). A 36-item frailty index was constructed and rescaled to z-values (individual scores minus population mean divided by one standard deviation). Multiple linear regression models were carried out, adjusted for age and sex. From 7164 older adults, 54.8% were women, and their mean age was 70.6 years with a mean frailty index score of 0.175. The prevalence of diabetes was of 22.2%, and 37.3% for hypertension. An independent association between diabetes, hypertension or both conditions (coefficients 0.28, 0.4 and 0.63, respectively, P < 0.001) with frailty was found. Having any diabetic complication was significantly associated with frailty with a coefficient of 0.55 (95% CI 0.45-0.65, P < 0.001) in the adjusted model. The number of years since diagnosis was also associated with frailty for both conditions. Diabetes and hypertension are associated with frailty. In addition, an incremental association was found when both conditions were present or with worse associated features (any complication, more time since diagnosis). Frailty should be of particular concern in populations with a high prevalence of these conditions. Geriatr Gerontol Int 2017; 17: 925-930. © 2016 Japan Geriatrics Society.

[Influence of habitual chocolate consumption over the Mini-Mental State Examination in Spanish older adults].

PubMed

Orozco Arbelaez, Edilbeto; Banegas, José Ramón; Rodríguez Artalejo, Fernando; López García, Esther

2017-07-28

There are associations described between dementia, mild cognitive impairment (MCI) and foods with a high content of polyphenols. To assess the infl uence of habitual chocolate consumption over the MMSE in Spanish older adults. Cross-sectional study, using data of the follow-up of the Seniors-Study on Nutrition and Cardiovascular Risk in Spain (ENRICA) cohort. Habitual chocolate consumption in the last year was assessed with a computerized dietary history; differences between dark chocolate and milk chocolate were recorded. Chocolate intake was classified into the following categories: no consumption, < 10 g/day, and ≥ 10 g/day. Validated MMSE scores for Spain were obtained during an interview and different cutoff points were used to define ≤ 25, ≤ 24 and ≤ 23. Linear and logistic regression models were used to calculate adjusted beta coefficients and odds ratios (OR). Compared to non-consumers, participants with a habitual chocolate consumption of ≥ 10 g/d had a better MMSE score (adjusted beta coefficient and 95% confidence interval: 0.26 (0.02-0.50; p trend = 0.05); for dark chocolate, the results were also statistically significant (0.48 [0.18-0.78]; p trend < 0.001). Total chocolate consumption was not associated with higher likelihood of having MCI. However, dark chocolate consumption was associated with less likelihood of MCI (OR and 95%CI for MMSE ≤ 25: 0.39 [0.20-0.77]; for MMSE ≤ 24: 0.26 [0.10-0.67]; and for MMSE ≤ 23: 0.25 [0.07-0.82]). Our results suggest that habitual dark chocolate consumption might improve cognitive function among the older population.

[Comparison of three stand-level biomass estimation methods].

PubMed

Dong, Li Hu; Li, Feng Ri

2016-12-01

At present, the forest biomass methods of regional scale attract most of attention of the researchers, and developing the stand-level biomass model is popular. Based on the forestry inventory data of larch plantation (Larix olgensis) in Jilin Province, we used non-linear seemly unrelated regression (NSUR) to estimate the parameters in two additive system of stand-level biomass equations, i.e., stand-level biomass equations including the stand variables and stand biomass equations including the biomass expansion factor (i.e., Model system 1 and Model system 2), listed the constant biomass expansion factor for larch plantation and compared the prediction accuracy of three stand-level biomass estimation methods. The results indicated that for two additive system of biomass equations, the adjusted coefficient of determination (R a 2 ) of the total and stem equations was more than 0.95, the root mean squared error (RMSE), the mean prediction error (MPE) and the mean absolute error (MAE) were smaller. The branch and foliage biomass equations were worse than total and stem biomass equations, and the adjusted coefficient of determination (R a 2 ) was less than 0.95. The prediction accuracy of a constant biomass expansion factor was relatively lower than the prediction accuracy of Model system 1 and Model system 2. Overall, although stand-level biomass equation including the biomass expansion factor belonged to the volume-derived biomass estimation method, and was different from the stand biomass equations including stand variables in essence, but the obtained prediction accuracy of the two methods was similar. The constant biomass expansion factor had the lower prediction accuracy, and was inappropriate. In addition, in order to make the model parameter estimation more effective, the established stand-level biomass equations should consider the additivity in a system of all tree component biomass and total biomass equations.

Variation in inpatient tonsillectomy costs within and between US hospitals attributable to postoperative complications.

PubMed

Sun, Gordon H; Auger, Katherine A; Aliu, Oluseyi; Patrick, Stephen W; DeMonner, Sonya; Davis, Matthew M

2013-12-01

Tonsillectomy is the second most common inpatient procedure in US children. However, the factors that influence tonsillectomy-related costs are unknown. The objective of the study was to describe variation in US inpatient tonsillectomy costs and examine whether postoperative complications contribute to these disparities in costs. This is a retrospective cohort study of the 2009 Nationwide Inpatient Sample. Hierarchical, mixed-effects linear regression modeling was used to analyze the association between postoperative complications and cost, controlling for clinically relevant characteristics such as age, number of chronic comorbidity indicators, and hospital mean complication rates. We also estimated the variance in cost attributable to the treating hospital using the intraclass correlation coefficient. The study cohort comprised 12,512 adult and pediatric patients undergoing tonsillectomy or adenotonsillectomy in the inpatient setting. Cost, posttonsillectomy hemorrhage, and mechanical ventilator use at the individual encounter and at hospital level were evaluated. The aggregate cost of tonsillectomies in the cohort was $94.2 million. The median cost per encounter across all hospitals was $4393 (interquartile range, $3279-$6981), whereas the mean cost was $7525 (95% confidence interval, $6453-$8597). Mechanical ventilation was associated with an adjusted increase of $30,081 per encounter (95% confidence interval, $18,199-$41,964). The intraclass correlation coefficient declined from 0.117 to 0.070 after adjusting for mean hospital mechanical ventilation rate, which accounted for 40.2% of the interhospital variation in cost. Use of mechanical ventilation significantly increases the cost of inpatient tonsillectomy care. Further research should examine risk factors contributing to higher rates of mechanical ventilation after tonsillectomy, which in turn can guide systemic quality improvement interventions to reduce costs.

Solitary and combined negative influences of diabetes, obesity and hypertension on health-related quality of life of elderly individuals: A population-based cross-sectional study.

PubMed

Hajian-Tilaki, K; Heidari, B; Hajian-Tilaki, A

2016-01-01

The health-related quality of life (HRQoL) is a matter of concern in elderly people with chronic diseases. The objective of this study was to investigate the impact of obesity, hypertension and diabetes on HRQoL among elderly. A population based cross sectional study was conducted with 750 representative sample of elderly people aged 60-90 years in Babol, the northern Iran. The demographic data and the measurement of blood pressure and other anthropometric measures were collected. The validated short form (SF-36) questionnaire was used to assess the HRQoL. A multiple linear regression model was applied to assess the impact of obesity, abdominal obesity, hypertension and diabetes on QoL. The mean age (SD) of participants was 68.0±7.6 and 67.7±7.9 years for men and women respectively. Diabetes exerted the most negative effect on QoL score (adjusted coefficient=-9.2, 95% CI: -11.7, -6.5 points) followed by abdominal obesity and hypertension. Whereas a combination of three conditions was associated with a greater significant reduction in QoL scores in both sexes(adjusted coefficient=-14.5, 95% CI: -19.0, -9.9 points). However, the negative influence of obesity and hypertension on QoL was significant only in women. Most components of the QoL is affected by diabetes, obesity and hypertension particularly in women. Diabetes alone or in combination with other conditions has a negative influence in both sexes with greater effect in women. These findings justify further professional support to compensate the negative influences chronic conditions on health-related QoL especially for older obese diabetic women. Copyright © 2016 Diabetes India. Published by Elsevier Ltd. All rights reserved.

Treating liver fat and serum triglyceride levels in NAFLD, effects of PNPLA3 and TM6SF2 genotypes: Results from the WELCOME trial.

PubMed

Scorletti, Eleonora; West, Annette L; Bhatia, Lokpal; Hoile, Samuel P; McCormick, Keith G; Burdge, Graham C; Lillycrop, Karen A; Clough, Geraldine F; Calder, Philip C; Byrne, Christopher D

2015-12-01

Genetic variation in both patatin-like phospholipase domain-containing protein-3 (PNPLA3) (I148M) and the transmembrane 6 superfamily member 2 protein (TM6SF2) (E167K) influences severity of liver disease, and serum triglyceride concentrations in non-alcoholic fatty liver disease (NAFLD), but whether either genotype influences the responses to treatments is uncertain. One hundred three patients with NAFLD were randomised to omega-3 fatty acids (DHA+EPA) or placebo for 15-18months in a double blind placebo controlled trial. Erythrocyte enrichment with DHA and EPA was measured by gas chromatography. PNPLA3 and TM6SF2 genotypes were measured by PCR technologies. Multivariable linear regression and analysis of covariance were undertaken to test the effect of genotypes on omega-3 fatty acid enrichment, end of study liver fat percentage and serum triglyceride concentrations. All models were adjusted for baseline measurements of each respective outcome. Fifty-five men and 40 women (Genotypes PNPLA3 I148M, 148I/I=41, 148I/M=43, 148M/M=11; TM6SF2 E167K 167E/E=78, 167E/K+167K/K=17 participants) (mean ± SD age, 51 ± 11 years) completed the trial. Adjusting for baseline measurement, measured covariates and confounders, PNPLA3 148M/M variant was independently associated with percentage of DHA enrichment (B coefficient -1.02 (95% CI -1.97, -0.07), p=0.036) but not percentage of EPA enrichment (B coefficient -0.31 (95% CI -1.38, 0.75), p=0.56). This genotype was also independently associated with end of study liver fat percentage (B coefficient 9.5 (95% CI 2.53, 16.39), p=0.008), but not end of study triglyceride concentration (B coefficient -0.11 (95% CI -0.64, 0.42), p=0.68). PNPLA3 148M/M variant influences the changes in liver fat and DHA tissue enrichment during the trial but not the change in serum triglyceride concentration. Copyright © 2015 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Relative validity of an FFQ to estimate daily food and nutrient intakes for Chilean adults.

PubMed

Dehghan, Mahshid; Martinez, Solange; Zhang, Xiaohe; Seron, Pamela; Lanas, Fernando; Islam, Shofiqul; Merchant, Anwar T

2013-10-01

FFQ are commonly used to rank individuals by their food and nutrient intakes in large epidemiological studies. The purpose of the present study was to develop and validate an FFQ to rank individuals participating in an ongoing Prospective Urban and Rural Epidemiological (PURE) study in Chile. An FFQ and four 24 h dietary recalls were completed over 1 year. Pearson correlation coefficients, energy-adjusted and de-attenuated correlations and weighted kappa were computed between the dietary recalls and the FFQ. The level of agreement between the two dietary assessment methods was evaluated by Bland-Altman analysis. Temuco, Chile. Overall, 166 women and men enrolled in the present study. One hundred men and women participated in FFQ development and sixty-six individuals participated in FFQ validation. The FFQ consisted of 109 food items. For nutrients, the crude correlation coefficients between the dietary recalls and FFQ varied from 0.14 (protein) to 0.44 (fat). Energy adjustment and de-attenuation improved correlation coefficients and almost all correlation coefficients exceeded 0.40. Similar correlation coefficients were observed for food groups; the highest de-attenuated energy adjusted correlation coefficient was found for margarine and butter (0.75) and the lowest for potatoes (0.12). The FFQ showed moderate to high agreement for most nutrients and food groups, and can be used to rank individuals based on energy, nutrient and food intakes. The validation study was conducted in a unique setting and indicated that the tool is valid for use by adults in Chile.

High-dose chemotherapy for patients with high-risk breast cancer: a clinical and economic assessment using a quality-adjusted survival analysis.

PubMed

Marino, Patricia; Roché, Henri; Moatti, Jean-Paul

2008-04-01

The benefit of high-dose chemotherapy (HDC) has not been clearly demonstrated. It may offer disease-free survival improvement at the expense of major toxicity and increasing cost. We evaluated the trade-offs between toxicity, relapse, and costs using a quality-adjusted time without symptoms or toxicity (Q-TWiST) analysis. The analysis was conducted in the context of a randomized trial (PEGASE 01) evaluating the benefit of HDC for 314 patients with high-risk breast cancer. A Q-TWiST analysis was first performed to compare HDC with standard chemotherapy. We then used the results of this Q-TWiST analysis to inform a cost per quality-adjusted life-year (QALY) comparison between treatments. Q-TWiST durations were in favor of HDC, whatever the weighting coefficients used for the analysis. This benefit was significant when the weighting coefficient related to the time spent after relapse was low (<0.38). For quite high values of this coefficient (>0.78), HDC offered no benefit. For intermediate values, the results depended on the weighting coefficient attributed to the toxicity period. The incremental cost per QALY ranged from 12,691euro/QALY to 26,439euro/QALY, according to the coefficients used to weight toxicity and relapse. The benefits of HDC outweigh the burdens of treatment for a wide range of utility coefficients. Economic impact is not a barrier to HDC diffusion in this situation. Nevertheless, no significant benefit was demonstrated for a certain range of utility values.

7 CFR 275.23 - Determination of State agency program performance.

Code of Federal Regulations, 2011 CFR

2011-01-01

... NUTRITION SERVICE, DEPARTMENT OF AGRICULTURE FOOD STAMP AND FOOD DISTRIBUTION PROGRAM PERFORMANCE REPORTING... section, the adjusted regressed payment error rate shall be calculated to yield the State agency's payment error rate. The adjusted regressed payment error rate is given by r 1″ + r 2″. (ii) If FNS determines...

Interpretation of the Coefficients in the Fit y = at + bx + c

ERIC Educational Resources Information Center

Farnsworth, David L.

2006-01-01

The goals of this note are to derive formulas for the coefficients a and b in the least-squares regression plane y = at + bx + c for observations (t[subscript]i,x[subscript]i,y[subscript]i), i = 1, 2, ..., n, and to present meanings for the coefficients a and b. In this note, formulas for the coefficients a and b in the least-squares fit are…

Adjusting STEMS growth model for Wisconsin forests.

Treesearch

Margaret R. Holdaway

1985-01-01

Describes a simple procedure for adjusting growth in the STEMS regional tree growth model to compensate for subregional differences. Coefficients are reported to adjust Lake States STEMS to the forests of Northern and Central Wisconsin--an area of essentially uniform climate and similar broad physiographic features. Errors are presented for various combinations of...

Transfrontal and Transsphenoidal Approaches to Pediatric Craniopharyngioma: A National Perspective.

PubMed

Lin, Yimo; Hansen, Daniel; Sayama, Christina M; Pan, I-Wen; Lam, Sandi

2017-01-01

This study compared transsphenoidal (TS) and transfrontal (TF) approaches to craniopharyngioma utilizing a national database. The Kids' Inpatient Database (2003, 2006, and 2009) was surveyed for patients with a diagnosis of craniopharyngioma who underwent a subset of surgical interventions to compare TS and TF surgery. Demographics, hospital variables, and complications/comorbidities were analyzed with multivariate regression. 314 admissions (TS = 104, TF = 210) were identified. The mean age was 14.8 (TS) versus 9.8 (TF) years (p < 0.001). The mean number of diagnoses was 4.6 (TS) versus 6.2 (TF) (p < 0.001). Diabetes insipidus was associated with 38% (TS) and 69% (TF). Cerebrospinal fluid (CSF) leak affected 19% TS and 4% TF resections. Other complications and comorbidities included postoperative stroke (2% TS vs. 5% TF), panhypopituitarism (5 vs. 8%), death (0 vs. 1%), cranial nerve deficits (1 vs. 6%), thrombotic events (7 vs. 17%), and seizures (0 vs. 12%). 98% of patients were discharged home after a mean 6-day length of stay (LOS) after TS, whereas 90% of TF patients had a LOS of 12 days. TS cases were more likely to be privately insured (68%) and from higher income brackets (61%) than TF ones (56 and 2%, respectively) (p < 0.05). In multivariate regression models adjusting for age, sex, race, number of diagnoses, surgical approach, hospital volume, and insurance type, the TS approach was associated with an increased incidence of CSF leak (OR 10, p < 0.001). More documented diagnoses (OR 16-60, p < 0.01) and TF approach (OR 2.6, p < 0.01) were associated with an increased incidence of other complications and comorbidities. Age younger than 10 (β-coefficient 2.3, p = 0.01), more diagnoses (β-coefficient 1.2, p < 0.001), and TF approach (β- coefficient 3.0, p < 0.01) were associated with increased LOS. A higher number of diagnoses were associated with nonhome discharge destinations (β-coefficient 1.29, p < 0.001). TS surgery was associated with an increased incidence of CSF leak but shorter LOS; TF surgery was associated with an increased incidence of other complications. Patients undergoing TS surgery were more likely to have private insurance and a higher family income bracket. © 2017 S. Karger AG, Basel.

Determinants of serum cadmium levels in a Northern Italy community: A cross-sectional study

DOE Office of Scientific and Technical Information (OSTI.GOV)

Filippini, Tommaso

Introduction: Cadmium (Cd) is a heavy metal and a serious environmental hazard to humans. Some uncertainties still exist about major sources of Cd exposure in non-occupationally exposed subjects in addition to cigarette smoking, such as diet and outdoor air pollution. We sought to determine the influence of these sources on a biomarker of exposure, serum Cd concentration. Methods: We recruited 51 randomly selected residents from an Italian urban community, from whom we obtained detailed information about dietary habits and smoking habits, and a blood sample for serum Cd determination. We also assessed outdoor air Cd exposure, by modeling outdoor airmore » levels of particulate matter ≤10 µm (PM{sub 10}) from motorized traffic at geocoded subjects’ residence. Results: In crude analysis, regression beta coefficients for dietary Cd, smoking and PM10 on serum Cd levels were 0.03 (95% CI -0.83 to 0.88), 6.96 (95% CI -0.02 to 13.95) and 0.62 (95% CI -0.19 to 1.43), respectively. In the adjusted analysis, regression beta coefficients were -0.34 (95% CI -1-40 to 0.71), 5.81 (95% CI -1.43 to 13.04) and 0.47 (95% CI -0.35 to 1.29), respectively. Conclusion: Cigarette smoking was the most important factor influencing serum Cd in our non-occupationally exposed population, as expected, while dietary Cd was not associated with this biomarker. Outdoor air pollution, as assessed through exposure to particulate matter generated by motorized traffic, was an additional source of Cd exposure. - Highlights: • Smoking markedly increases serum Cd levels in non-occupationally exposed individuals. • Overall dietary Cd intake shows little association with serum Cd levels. • Air pollution from motorized traffic increases serum Cd levels.« less

Reliable Change Indices and Standardized Regression-Based Change Score Norms for Evaluating Neuropsychological Change in Children with Epilepsy

PubMed Central

Busch, Robyn M.; Lineweaver, Tara T.; Ferguson, Lisa; Haut, Jennifer S.

2015-01-01

Reliable change index scores (RCIs) and standardized regression-based change score norms (SRBs) permit evaluation of meaningful changes in test scores following treatment interventions, like epilepsy surgery, while accounting for test-retest reliability, practice effects, score fluctuations due to error, and relevant clinical and demographic factors. Although these methods are frequently used to assess cognitive change after epilepsy surgery in adults, they have not been widely applied to examine cognitive change in children with epilepsy. The goal of the current study was to develop RCIs and SRBs for use in children with epilepsy. Sixty-three children with epilepsy (age range 6–16; M=10.19, SD=2.58) underwent comprehensive neuropsychological evaluations at two time points an average of 12 months apart. Practice adjusted RCIs and SRBs were calculated for all cognitive measures in the battery. Practice effects were quite variable across the neuropsychological measures, with the greatest differences observed among older children, particularly on the Children’s Memory Scale and Wisconsin Card Sorting Test. There was also notable variability in test-retest reliabilities across measures in the battery, with coefficients ranging from 0.14 to 0.92. RCIs and SRBs for use in assessing meaningful cognitive change in children following epilepsy surgery are provided for measures with reliability coefficients above 0.50. This is the first study to provide RCIs and SRBs for a comprehensive neuropsychological battery based on a large sample of children with epilepsy. Tables to aid in evaluating cognitive changes in children who have undergone epilepsy surgery are provided for clinical use. An excel sheet to perform all relevant calculations is also available to interested clinicians or researchers. PMID:26043163

Relationship between self-esteem and living conditions among stroke survivors at home.

PubMed

Shida, Junko; Sugawara, Kyoko; Goto, Junko; Sekito, Yoshiko

2014-10-01

To clarify the relationship between self-esteem of stroke survivors at home and their living conditions. Study participants were stroke survivors who lived at home and commuted to one of two medical facilities in the Tohoku region of Japan. Stroke survivors were recruited for the present study when they came to the hospital for a routine visit. The researcher or research assistant explained the study objective and methods to the stroke survivor, and the questionnaire survey was conducted. Survey contents included the Japanese version of the Rosenberg Self-Esteem Scale (RSE) and questions designed to assess living conditions. A total of 65 participants with complete RSE data were included in the analysis. The mean (standard deviation) age of participants was 70.9 years (± 11.1), with a mean RSE score of 32.12 (± 8.32). Only a minor decrease in participant self-esteem was observed, even after having experienced a stroke. Factors associated with self-esteem, including "independent bathing" (standardized partial regression coefficient, β = 0.405, P < 0.001), "being needed by family members" (β = 0.389, P < 0.001), "independent grooming" (β = 0.292, P = 0.009), and "sleep satisfaction" (β = 0.237, P = 0.017), were analyzed by stepwise multiple regression analysis. The multiple correlation coefficient adjusted for the degrees of freedom was 0.738 (P < 0.001). Our analysis revealed that the maintenance of activities of daily living, and the presence of a suitable environment that enhances physical function recovery and promotes activity and participation, are necessary to improve self-esteem in stroke survivors living at home. © 2013 The Authors. Japan Journal of Nursing Science © 2013 Japan Academy of Nursing Science.

Secondhand smoke exposure (SHS) and health-related quality of life (HRQoL) in Chinese never smokers in Hong Kong

PubMed Central

Chen, Jing; Wang, Man-Ping; Wang, Xin; Viswanath, Kasisomayajula; Lam, Tai-Hing; Chan, Sophia S

2015-01-01

Objective The evidence on the effect of secondhand smoke (SHS) on Health Related Quality of Life (HRQoL) is limited. We examined the relation between SHS and HRQoL among Chinese in Hong Kong. Methods Adult never smokers from a probability sample of three cross-sectional waves (2010, 2012, 2013) of The Hong Kong Family and Health Information Trends Survey who completed the Cantonese-version of Short-Form 12 Health Survey Questionnaire (SF12v2) were included in the data analysis conducted in 2014. Models were used to examine associations of SHS with SF12 domains and summary scores of Physical (PCS12) and Mental Component (MCS12) with subgroups analysis by SHS locations. Results After adjustments, SHS was associated with lower scores on all SF12 domains except physical functioning. PCS12 (regress coefficient=−0.76, 95% CI −1.34 to −0.17) and MCS12 (regress coefficient=−1.35, 95% CI −2.06 to −0.64) were lower in those with SHS exposure than those non-exposed. Those exposed to SHS in outdoor public places had lower scores on most SF12 domains and PSC12 and MCS12. SHS exposure in one's home and workplace was associated with lower scores on role physical, body pain and role emotional while SHS exposure in friends’ homes was additionally associated with lower social functioning and mental health scores. Lower MCS12 was associated with SHS exposure at all locations except one's home. Conclusions Our study showed that SHS exposure, particularly in outdoor public places, was associated with decreased HRQoL. It can provide new evidence for stronger smoke-free policies on public places and promoting smoke-free homes. PMID:26338682

Wavelet-based functional linear mixed models: an application to measurement error-corrected distributed lag models.

PubMed

Malloy, Elizabeth J; Morris, Jeffrey S; Adar, Sara D; Suh, Helen; Gold, Diane R; Coull, Brent A

2010-07-01

Frequently, exposure data are measured over time on a grid of discrete values that collectively define a functional observation. In many applications, researchers are interested in using these measurements as covariates to predict a scalar response in a regression setting, with interest focusing on the most biologically relevant time window of exposure. One example is in panel studies of the health effects of particulate matter (PM), where particle levels are measured over time. In such studies, there are many more values of the functional data than observations in the data set so that regularization of the corresponding functional regression coefficient is necessary for estimation. Additional issues in this setting are the possibility of exposure measurement error and the need to incorporate additional potential confounders, such as meteorological or co-pollutant measures, that themselves may have effects that vary over time. To accommodate all these features, we develop wavelet-based linear mixed distributed lag models that incorporate repeated measures of functional data as covariates into a linear mixed model. A Bayesian approach to model fitting uses wavelet shrinkage to regularize functional coefficients. We show that, as long as the exposure error induces fine-scale variability in the functional exposure profile and the distributed lag function representing the exposure effect varies smoothly in time, the model corrects for the exposure measurement error without further adjustment. Both these conditions are likely to hold in the environmental applications we consider. We examine properties of the method using simulations and apply the method to data from a study examining the association between PM, measured as hourly averages for 1-7 days, and markers of acute systemic inflammation. We use the method to fully control for the effects of confounding by other time-varying predictors, such as temperature and co-pollutants.

Maternal Education Gradients in Infant Health in Four South American Countries.

PubMed

Wehby, George L; López-Camelo, Jorge S

2017-11-01

Objective We investigate gradients (i.e. differences) in infant health outcomes by maternal education in Argentina, Brazil, Chile, and Venezuela and explore channels related to father's education, household labor outcomes, and maternal health, fertility, and use of prenatal services and technology. Methods We employ secondary interview and birth record data similarly collected across a network of birth hospitals from the early 1980s through 2011 within the Latin American Collaborative Study of Congenital Anomalies (ECLAMC). Focusing on children without birth defects, we estimate gradients in several infant health outcomes including birth weight, gestational age, and hospital discharge status by maternal education using ordinary least squares regression models adjusting for several demographic factors. To explore channels, we add as covariates father's education, parental occupational activity, maternal health and fertility history, and use of prenatal services and technology and evaluate changes in the coefficient of maternal education. We use the same models for each country sample. Results We find important differences in gradients across countries. We find evidence for educational gradients in preterm birth in three countries but weaker evidence for gradients in fetal growth. The extent to which observed household and maternal factors explain these gradients based on changes in the regression coefficient of maternal education when controlling for these factors as covariates also varies between countries. In contrast, we generally find evidence across all countries that higher maternal education is associated with increased use of prenatal care services and technology. Conclusions Our findings suggest that differences in infant health by maternal education and their underlying mechanisms vary and are not necessarily generalizable across countries. However, the positive association between maternal education and use of prenatal services and technology is more consistent across examined countries.

Development and Validation of a Practical Instrument for Injury Prevention: The Occupational Safety and Health Monitoring and Assessment Tool (OSH-MAT).

PubMed

Sun, Yi; Arning, Martin; Bochmann, Frank; Börger, Jutta; Heitmann, Thomas

2018-06-01

The Occupational Safety and Health Monitoring and Assessment Tool (OSH-MAT) is a practical instrument that is currently used in the German woodworking and metalworking industries to monitor safety conditions at workplaces. The 12-item scoring system has three subscales rating technical, organizational, and personnel-related conditions in a company. Each item has a rating value ranging from 1 to 9, with higher values indicating higher standard of safety conditions. The reliability of this instrument was evaluated in a cross-sectional survey among 128 companies and its validity among 30,514 companies. The inter-rater reliability of the instrument was examined independently and simultaneously by two well-trained safety engineers. Agreement between the double ratings was quantified by the intraclass correlation coefficient and absolute agreement of the rating values. The content validity of the OSH-MAT was evaluated by quantifying the association between OSH-MAT values and 5-year average injury rates by Poisson regression analysis adjusted for the size of the companies and industrial sectors. The construct validity of OSH-MAT was examined by principle component factor analysis. Our analysis indicated good to very good inter-rater reliability (intraclass correlation coefficient = 0.64-0.74) of OSH-MAT values with an absolute agreement of between 72% and 81%. Factor analysis identified three component subscales that met exactly the structure theory of this instrument. The Poisson regression analysis demonstrated a statistically significant exposure-response relationship between OSH-MAT values and the 5-year average injury rates. These analyses indicate that OSH-MAT is a valid and reliable instrument that can be used effectively to monitor safety conditions at workplaces.

Application of seasonal auto-regressive integrated moving average model in forecasting the incidence of hand-foot-mouth disease in Wuhan, China.

PubMed

Peng, Ying; Yu, Bin; Wang, Peng; Kong, De-Guang; Chen, Bang-Hua; Yang, Xiao-Bing

2017-12-01

Outbreaks of hand-foot-mouth disease (HFMD) have occurred many times and caused serious health burden in China since 2008. Application of modern information technology to prediction and early response can be helpful for efficient HFMD prevention and control. A seasonal auto-regressive integrated moving average (ARIMA) model for time series analysis was designed in this study. Eighty-four-month (from January 2009 to December 2015) retrospective data obtained from the Chinese Information System for Disease Prevention and Control were subjected to ARIMA modeling. The coefficient of determination (R 2 ), normalized Bayesian Information Criterion (BIC) and Q-test P value were used to evaluate the goodness-of-fit of constructed models. Subsequently, the best-fitted ARIMA model was applied to predict the expected incidence of HFMD from January 2016 to December 2016. The best-fitted seasonal ARIMA model was identified as (1,0,1)(0,1,1) 12 , with the largest coefficient of determination (R 2 =0.743) and lowest normalized BIC (BIC=3.645) value. The residuals of the model also showed non-significant autocorrelations (P Box-Ljung (Q) =0.299). The predictions by the optimum ARIMA model adequately captured the pattern in the data and exhibited two peaks of activity over the forecast interval, including a major peak during April to June, and again a light peak for September to November. The ARIMA model proposed in this study can forecast HFMD incidence trend effectively, which could provide useful support for future HFMD prevention and control in the study area. Besides, further observations should be added continually into the modeling data set, and parameters of the models should be adjusted accordingly.

The Reliability of Individualized Load-Velocity Profiles.

PubMed

Banyard, Harry G; Nosaka, K; Vernon, Alex D; Haff, G Gregory

2017-11-15

This study examined the reliability of peak velocity (PV), mean propulsive velocity (MPV), and mean velocity (MV) in the development of load-velocity profiles (LVP) in the full depth free-weight back squat performed with maximal concentric effort. Eighteen resistance-trained men performed a baseline one-repetition maximum (1RM) back squat trial and three subsequent 1RM trials used for reliability analyses, with 48-hours interval between trials. 1RM trials comprised lifts from six relative loads including 20, 40, 60, 80, 90, and 100% 1RM. Individualized LVPs for PV, MPV, or MV were derived from loads that were highly reliable based on the following criteria: intra-class correlation coefficient (ICC) >0.70, coefficient of variation (CV) ≤10%, and Cohen's d effect size (ES) <0.60. PV was highly reliable at all six loads. Importantly, MPV and MV were highly reliable at 20, 40, 60, 80 and 90% but not 100% 1RM (MPV: ICC=0.66, CV=18.0%, ES=0.10, standard error of the estimate [SEM]=0.04m·s -1 ; MV: ICC=0.55, CV=19.4%, ES=0.08, SEM=0.04m·s -1 ). When considering the reliable ranges, almost perfect correlations were observed for LVPs derived from PV 20-100% (r=0.91-0.93), MPV 20-90% (r=0.92-0.94) and MV 20-90% (r=0.94-0.95). Furthermore, the LVPs were not significantly different (p>0.05) between trials, movement velocities, or between linear regression versus second order polynomial fits. PV 20-100% , MPV 20-90% , and MV 20-90% are reliable and can be utilized to develop LVPs using linear regression. Conceptually, LVPs can be used to monitor changes in movement velocity and employed as a method for adjusting sessional training loads according to daily readiness.

Reliable change indices and standardized regression-based change score norms for evaluating neuropsychological change in children with epilepsy.

PubMed

Busch, Robyn M; Lineweaver, Tara T; Ferguson, Lisa; Haut, Jennifer S

2015-06-01

Reliable change indices (RCIs) and standardized regression-based (SRB) change score norms permit evaluation of meaningful changes in test scores following treatment interventions, like epilepsy surgery, while accounting for test-retest reliability, practice effects, score fluctuations due to error, and relevant clinical and demographic factors. Although these methods are frequently used to assess cognitive change after epilepsy surgery in adults, they have not been widely applied to examine cognitive change in children with epilepsy. The goal of the current study was to develop RCIs and SRB change score norms for use in children with epilepsy. Sixty-three children with epilepsy (age range: 6-16; M=10.19, SD=2.58) underwent comprehensive neuropsychological evaluations at two time points an average of 12 months apart. Practice effect-adjusted RCIs and SRB change score norms were calculated for all cognitive measures in the battery. Practice effects were quite variable across the neuropsychological measures, with the greatest differences observed among older children, particularly on the Children's Memory Scale and Wisconsin Card Sorting Test. There was also notable variability in test-retest reliabilities across measures in the battery, with coefficients ranging from 0.14 to 0.92. Reliable change indices and SRB change score norms for use in assessing meaningful cognitive change in children following epilepsy surgery are provided for measures with reliability coefficients above 0.50. This is the first study to provide RCIs and SRB change score norms for a comprehensive neuropsychological battery based on a large sample of children with epilepsy. Tables to aid in evaluating cognitive changes in children who have undergone epilepsy surgery are provided for clinical use. An Excel sheet to perform all relevant calculations is also available to interested clinicians or researchers. Copyright © 2015 Elsevier Inc. All rights reserved.

Effect on Patient-Reported Outcomes of Debridement or Microfracture of Concomitant Full-Thickness Cartilage Lesions in Anterior Cruciate Ligament-Reconstructed Knees: A Nationwide Cohort Study From Norway and Sweden of 357 Patients With 2-Year Follow-up.

PubMed

Røtterud, Jan Harald; Sivertsen, Einar Andreas; Forssblad, Magnus; Engebretsen, Lars; Årøen, Asbjørn

2016-02-01

The treatment of concomitant cartilage lesions in anterior cruciate ligament (ACL)-injured knees is debatable. To evaluate the effect of debridement or microfracture (MF) compared with no treatment of concomitant full-thickness (International Cartilage Repair Society [ICRS] grades 3-4) cartilage lesions on patient-reported outcomes after ACL reconstruction. Cohort study; Level of evidence, 2. Six hundred forty-four patients who underwent primary unilateral ACL reconstruction and had a concomitant full-thickness cartilage lesion treated simultaneously by debridement (n = 129) or MF (n = 164), or underwent no treatment (n = 351) of the cartilage lesion, registered in the Norwegian and Swedish National Knee Ligament Registries from 2005 to 2008 were included. The Knee Injury and Osteoarthritis Outcome Score (KOOS) was used to measure patient-reported outcomes. At a mean follow-up of 2.1 ± 0.2 years after surgery, 357 (55%) patients completed the KOOS. Linear regression analyses were used to evaluate the effect of debridement or MF on the KOOS. No significant effects of debridement were detected in the unadjusted or adjusted regression analyses on any of the KOOS subscales at 2-year follow-up. The MF treatment of the cartilage lesions had significant negative effects at 2-year follow-up on the KOOS Sport and Recreation (Sport/Rec) (regression coefficient [β] = -8.9; 95% confidence interval [CI], -15.1 to -1.5) and Knee-Related Quality of Life (QoL) (β = -8.1; 95% CI, -14.1 to -2.1) subscales in the unadjusted analyses. When adjusting for confounders, MF had significant negative effects on the same KOOS subscales of Sport/Rec (β = -8.6; 95% CI, -16.4 to -0.7) and QoL (β = -7.2; 95% CI, -13.6 to -0.8). For the remaining KOOS subscales of Pain, Symptoms, and Activities of Daily Living, there were no significant unadjusted or adjusted effects of MF. MF of concomitant full-thickness cartilage lesions showed adverse effects on patient-reported outcomes at 2-year follow-up after ACL reconstruction. Debridement of concomitant full-thickness cartilage lesions showed neither positive nor negative effects on patient-reported outcomes at 2-year follow-up after ACL reconstruction. © 2015 The Author(s).

Work-family conflicts and self-reported work ability: cross-sectional findings in women with chronic musculoskeletal disorders.

PubMed

Bethge, Matthias; Borngräber, Yvonne

2015-03-18

Under conditions of gender-specific division of paid employment and unpaid childcare and housework, rising employment of women increases the likelihood that they will be faced with work-family conflicts. As recent research indicates, such conflicts might also contribute to musculoskeletal disorders. However, research in patient samples is needed to clarify how important these conflicts are for relevant health-related measures of functioning (e.g., work ability). We therefore examined, in a sample of women with chronic musculoskeletal disorders, the indirect and direct associations between the indicators of work-family conflicts and self-reported work ability as well as whether the direct effects remained significant after adjustment for covariates. A cross-sectional questionnaire-based study was conducted. Participants were recruited from five rehabilitation centers. Work-family conflicts were assessed by four scales referring to time- and strain-based work interference with family (WIF) and family interference with work (FIW). Self-reported work ability was measured by the Work Ability Index. A confirmatory factor analysis was performed to approve the anticipated four-factor structure of the work-family conflict measure. Direct and indirect associations between work-family conflict indicators and self-reported work ability were examined by path model analysis. Multivariate regression models were performed to calculate adjusted estimators of the direct effects of strain-based WIF and FIW on work ability. The study included 351 employed women. The confirmatory factor analysis provided support for the anticipated four-factor structure of the work-family conflict measure. The path model analysis identified direct effects of both strain-based scales on self-reported work ability. The time-based scales were indirectly associated with work ability via the strain-based scales. Adjusted regression analyses showed that a five-point increase in strain-based WIF or FIW was associated with a four- and two-point decrease in self-reported work ability, respectively. The standardized regression coefficients were β = 0.35 and β = 0.12. Our findings indicate that work-family conflicts are associated with poor work ability in female patients with chronic musculoskeletal disorders. However, longitudinal research is needed to establish a causal relationship. Better compatibility of work and family life might be an environmental facilitator of better rehabilitation outcomes in female patients with musculoskeletal disorders.

Three methods to construct predictive models using logistic regression and likelihood ratios to facilitate adjustment for pretest probability give similar results.

PubMed

Chan, Siew Foong; Deeks, Jonathan J; Macaskill, Petra; Irwig, Les

2008-01-01

To compare three predictive models based on logistic regression to estimate adjusted likelihood ratios allowing for interdependency between diagnostic variables (tests). This study was a review of the theoretical basis, assumptions, and limitations of published models; and a statistical extension of methods and application to a case study of the diagnosis of obstructive airways disease based on history and clinical examination. Albert's method includes an offset term to estimate an adjusted likelihood ratio for combinations of tests. Spiegelhalter and Knill-Jones method uses the unadjusted likelihood ratio for each test as a predictor and computes shrinkage factors to allow for interdependence. Knottnerus' method differs from the other methods because it requires sequencing of tests, which limits its application to situations where there are few tests and substantial data. Although parameter estimates differed between the models, predicted "posttest" probabilities were generally similar. Construction of predictive models using logistic regression is preferred to the independence Bayes' approach when it is important to adjust for dependency of tests errors. Methods to estimate adjusted likelihood ratios from predictive models should be considered in preference to a standard logistic regression model to facilitate ease of interpretation and application. Albert's method provides the most straightforward approach.

[The relationship between depressive symptoms and family functioning in institutionalized elderly].

PubMed

de Oliveira, Simone Camargo; dos Santos, Ariene Angelini; Pavarini, Sofia Cristina Iost

2014-02-01

The present study aimed to investigate the relationship between family functioning and depressive symptoms among institutionalized elderly. This is a descriptive, cross-sectional study of quantitative character. A total of 107 institutionalized elderly were assessed using a sociodemographic questionnaire, the Geriatric Depression Scale (to track depressive symptoms) and the Family APGAR (to assess family functioning). The correlation coefficient of Pearson's, the chi-square test and the crude and adjusted logistic regression were used in the data analysis with a significance level of 5 %. The institutionalized elderly with depressive symptoms were predominantly women and in the age group of 80 years and older. Regarding family functioning, most elderly had high family dysfunctioning (57 %). Family dysfunctioning was higher among the elderly with depressive symptoms. There was a significant correlation between family functioning and depressive symptoms. The conclusion is that institutionalized elderly with dysfunctional families are more likely to have depressive symptoms.

An investigation of the key parameters for predicting PV soiling losses

DOE PAGES

Micheli, Leonardo; Muller, Matthew

2017-01-25

One hundred and two environmental and meteorological parameters have been investigated and compared with the performance of 20 soiling stations installed in the USA, in order to determine their ability to predict the soiling losses occurring on PV systems. The results of this investigation showed that the annual average of the daily mean particulate matter values recorded by monitoring stations deployed near the PV systems are the best soiling predictors, with coefficients of determination ( R 2) as high as 0.82. The precipitation pattern was also found to be relevant: among the different meteorological parameters, the average length of drymore » periods had the best correlation with the soiling ratio. Lastly, a preliminary investigation of two-variable regressions was attempted and resulted in an adjusted R 2 of 0.90 when a combination of PM 2.5 and a binary classification for the average length of the dry period was introduced.« less

Investigating the Performance of Alternate Regression Weights by Studying All Possible Criteria in Regression Models with a Fixed Set of Predictors

ERIC Educational Resources Information Center

Waller, Niels; Jones, Jeff

2011-01-01

We describe methods for assessing all possible criteria (i.e., dependent variables) and subsets of criteria for regression models with a fixed set of predictors, x (where x is an n x 1 vector of independent variables). Our methods build upon the geometry of regression coefficients (hereafter called regression weights) in n-dimensional space. For a…

Neither fixed nor random: weighted least squares meta-regression.

PubMed

Stanley, T D; Doucouliagos, Hristos

2017-03-01

Our study revisits and challenges two core conventional meta-regression estimators: the prevalent use of 'mixed-effects' or random-effects meta-regression analysis and the correction of standard errors that defines fixed-effects meta-regression analysis (FE-MRA). We show how and explain why an unrestricted weighted least squares MRA (WLS-MRA) estimator is superior to conventional random-effects (or mixed-effects) meta-regression when there is publication (or small-sample) bias that is as good as FE-MRA in all cases and better than fixed effects in most practical applications. Simulations and statistical theory show that WLS-MRA provides satisfactory estimates of meta-regression coefficients that are practically equivalent to mixed effects or random effects when there is no publication bias. When there is publication selection bias, WLS-MRA always has smaller bias than mixed effects or random effects. In practical applications, an unrestricted WLS meta-regression is likely to give practically equivalent or superior estimates to fixed-effects, random-effects, and mixed-effects meta-regression approaches. However, random-effects meta-regression remains viable and perhaps somewhat preferable if selection for statistical significance (publication bias) can be ruled out and when random, additive normal heterogeneity is known to directly affect the 'true' regression coefficient. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Physical activity and sedentary lifestyle among children from private and public schools in Northern Brazil.

PubMed

Oliveira, Thiara Castro de; Silva, Antônio Augusto Moura da; Santos, Cristiane de Jesus Nunes dos; Silva, Josenilde Sousa e; Conceição, Sueli Ismael Oliveira da

2010-12-01

To analyze factors associated with physical activity and the mean time spent in some sedentary activities among school-aged children. A cross-sectional study was carried out in a random sample of 592 schoolchildren aged nine to 16 years in 2005, in São Luís, Northern Brazil. Data were collected by means of a 24-Hour Physical Activity Recall Questionnaire, concerning demographic and socioeconomic variables, physical activities practiced and time spent in certain sedentary activities. Physical activities were classified according to their metabolic equivalents (MET), and a physical activity index was estimated for each child. Sedentary lifestyle was estimated based on time spent watching television, playing videogames and on the computer/internet. Chi square test was used to compare proportions. Linear regression analysis was used to establish associations. Estimates were adjusted for the effect of the sampling design. The mean of the physical activity index was 605.73 MET-min/day (SD = 509.45). School children that were male (coefficient=134.57; 95%CI 50.77; 218.37), from public schools (coefficient.= 94.08; 95%CI 12.54; 175.62 and in the 5th to 7th grade (coefficient.=95.01; 95%CI 8.10;181.92 presented higher indices than females, children from private schools and in the 8th to the 9th grade (p<0.05). On average, students spent 2.66 hours/day in sedentary activities. Time spent in sedentary activities was significantly lower for children aged nine to 11 years (coefficient.= -0.49 hr/day; 95%CI -0.88; -0.10) and in lower socioeconomic classes (coefficient.=-0.87; 95%CI -1.45;-0.30). Domestic chores (59.43%) and walking to school (58.43%) were the most common physical activities. Being female, in private schools and in the 8th to 9th grade were factors associated with lower levels of physical activity. Younger schoolchildren and those from low economic classes spent less time engaged in sedentary activities.

Interpreting Bivariate Regression Coefficients: Going beyond the Average

ERIC Educational Resources Information Center

Halcoussis, Dennis; Phillips, G. Michael

2010-01-01

Statistics, econometrics, investment analysis, and data analysis classes often review the calculation of several types of averages, including the arithmetic mean, geometric mean, harmonic mean, and various weighted averages. This note shows how each of these can be computed using a basic regression framework. By recognizing when a regression model…

Beyond Multiple Regression: Using Commonality Analysis to Better Understand R[superscript 2] Results

ERIC Educational Resources Information Center

Warne, Russell T.

2011-01-01

Multiple regression is one of the most common statistical methods used in quantitative educational research. Despite the versatility and easy interpretability of multiple regression, it has some shortcomings in the detection of suppressor variables and for somewhat arbitrarily assigning values to the structure coefficients of correlated…

Precision Efficacy Analysis for Regression.

ERIC Educational Resources Information Center

Brooks, Gordon P.

When multiple linear regression is used to develop a prediction model, sample size must be large enough to ensure stable coefficients. If the derivation sample size is inadequate, the model may not predict well for future subjects. The precision efficacy analysis for regression (PEAR) method uses a cross- validity approach to select sample sizes…

40 CFR 53.34 - Test procedure for methods for PM10 and Class I methods for PM2.5.

Code of Federal Regulations, 2011 CFR

2011-07-01

... linear regression parameters (slope, intercept, and correlation coefficient) describing the relationship... correlation coefficient. (2) To pass the test for comparability, the slope, intercept, and correlation...

Seismic site coefficients and acceleration design response spectra based on conditions in South Carolina : final report.

DOT National Transportation Integrated Search

2014-11-15

The simplified procedure in design codes for determining earthquake response spectra involves : estimating site coefficients to adjust available rock accelerations to site accelerations. Several : investigators have noted concerns with the site coeff...

Association of surgical care improvement project infection-related process measure compliance with risk-adjusted outcomes: implications for quality measurement.

PubMed

Ingraham, Angela M; Cohen, Mark E; Bilimoria, Karl Y; Dimick, Justin B; Richards, Karen E; Raval, Mehul V; Fleisher, Lee A; Hall, Bruce L; Ko, Clifford Y

2010-12-01

Facility-level process measure adherence is being publicly reported. However, the association between measure adherence and surgical outcomes is not well-established. Our objective was to determine the degree to which Surgical Care Improvement Project (SCIP) process measures are associated with American College of Surgeons National Surgical Quality Improvement Program (ACS NSQIP) risk-adjusted outcomes. This cross-sectional study included hospitals participating in the ACS NSQIP and SCIP (n = 200). ACS NSQIP outcomes (30-day overall morbidity, serious morbidity, surgical site infections [SSI], and mortality) and adherence to SCIP SSI-related process measures (from the Hospital Compare database) were collected from January 1, 2008, through December 31, 2008. Hospital-level correlation coefficients between compliance with 4 process measures (ie, antibiotic administration within 1 hour before incision [SCIP-1]; appropriate antibiotic prophylaxis [SCIP-2]; antibiotic discontinuation within 24 hours after surgery [SCIP-3]; and appropriate hair removal [SCIP 6]) and 4 risk-adjusted outcomes were calculated. Regression analyses estimated the contribution of process measure adherence to risk-adjusted outcomes. Of 211 ACS NSQIP hospitals, 95% had data reported by Hospital Compare. Depending on the measure, hospital-level compliance ranged from 60% to 100%. Of the 16 correlations, 15 demonstrated nonsignificant associations with risk-adjusted outcomes. The exception was the relationship between SCIP-2 and SSI (p = 0.004). SCIP-1 demonstrated an intriguing but nonsignificant relationship with SSI (p = 0.08) and overall morbidity (p = 0.08). Although adherence to SCIP-2 was a significant predictor of risk-adjusted SSI (p < 0.0001) and overall morbidity (p < 0.0001), inclusion of compliance for SCIP-1 and SCIP-2 caused only slight improvement in model quality. Better adherence to infection-related process measures over the observed range was not significantly associated with better outcomes with one exception. Different measures of quality might be needed for surgical infection. Copyright © 2010 American College of Surgeons. Published by Elsevier Inc. All rights reserved.

Local polynomial estimation of heteroscedasticity in a multivariate linear regression model and its applications in economics.

PubMed

Su, Liyun; Zhao, Yanyong; Yan, Tianshun; Li, Fenglan

2012-01-01

Multivariate local polynomial fitting is applied to the multivariate linear heteroscedastic regression model. Firstly, the local polynomial fitting is applied to estimate heteroscedastic function, then the coefficients of regression model are obtained by using generalized least squares method. One noteworthy feature of our approach is that we avoid the testing for heteroscedasticity by improving the traditional two-stage method. Due to non-parametric technique of local polynomial estimation, it is unnecessary to know the form of heteroscedastic function. Therefore, we can improve the estimation precision, when the heteroscedastic function is unknown. Furthermore, we verify that the regression coefficients is asymptotic normal based on numerical simulations and normal Q-Q plots of residuals. Finally, the simulation results and the local polynomial estimation of real data indicate that our approach is surely effective in finite-sample situations.

Data Mining Methods Applied to Flight Operations Quality Assurance Data: A Comparison to Standard Statistical Methods

NASA Technical Reports Server (NTRS)

Stolzer, Alan J.; Halford, Carl

2007-01-01

In a previous study, multiple regression techniques were applied to Flight Operations Quality Assurance-derived data to develop parsimonious model(s) for fuel consumption on the Boeing 757 airplane. The present study examined several data mining algorithms, including neural networks, on the fuel consumption problem and compared them to the multiple regression results obtained earlier. Using regression methods, parsimonious models were obtained that explained approximately 85% of the variation in fuel flow. In general data mining methods were more effective in predicting fuel consumption. Classification and Regression Tree methods reported correlation coefficients of .91 to .92, and General Linear Models and Multilayer Perceptron neural networks reported correlation coefficients of about .99. These data mining models show great promise for use in further examining large FOQA databases for operational and safety improvements.

Predicting Air Permeability of Handloom Fabrics: A Comparative Analysis of Regression and Artificial Neural Network Models

NASA Astrophysics Data System (ADS)

Mitra, Ashis; Majumdar, Prabal Kumar; Bannerjee, Debamalya

2013-03-01

This paper presents a comparative analysis of two modeling methodologies for the prediction of air permeability of plain woven handloom cotton fabrics. Four basic fabric constructional parameters namely ends per inch, picks per inch, warp count and weft count have been used as inputs for artificial neural network (ANN) and regression models. Out of the four regression models tried, interaction model showed very good prediction performance with a meager mean absolute error of 2.017 %. However, ANN models demonstrated superiority over the regression models both in terms of correlation coefficient and mean absolute error. The ANN model with 10 nodes in the single hidden layer showed very good correlation coefficient of 0.982 and 0.929 and mean absolute error of only 0.923 and 2.043 % for training and testing data respectively.

Improvement of Storm Forecasts Using Gridded Bayesian Linear Regression for Northeast United States

NASA Astrophysics Data System (ADS)

Yang, J.; Astitha, M.; Schwartz, C. S.

2017-12-01

Bayesian linear regression (BLR) is a post-processing technique in which regression coefficients are derived and used to correct raw forecasts based on pairs of observation-model values. This study presents the development and application of a gridded Bayesian linear regression (GBLR) as a new post-processing technique to improve numerical weather prediction (NWP) of rain and wind storm forecasts over northeast United States. Ten controlled variables produced from ten ensemble members of the National Center for Atmospheric Research (NCAR) real-time prediction system are used for a GBLR model. In the GBLR framework, leave-one-storm-out cross-validation is utilized to study the performances of the post-processing technique in a database composed of 92 storms. To estimate the regression coefficients of the GBLR, optimization procedures that minimize the systematic and random error of predicted atmospheric variables (wind speed, precipitation, etc.) are implemented for the modeled-observed pairs of training storms. The regression coefficients calculated for meteorological stations of the National Weather Service are interpolated back to the model domain. An analysis of forecast improvements based on error reductions during the storms will demonstrate the value of GBLR approach. This presentation will also illustrate how the variances are optimized for the training partition in GBLR and discuss the verification strategy for grid points where no observations are available. The new post-processing technique is successful in improving wind speed and precipitation storm forecasts using past event-based data and has the potential to be implemented in real-time.

Correlation and prediction of dynamic human isolated joint strength from lean body mass

NASA Technical Reports Server (NTRS)

Pandya, Abhilash K.; Hasson, Scott M.; Aldridge, Ann M.; Maida, James C.; Woolford, Barbara J.

1992-01-01

A relationship between a person's lean body mass and the amount of maximum torque that can be produced with each isolated joint of the upper extremity was investigated. The maximum dynamic isolated joint torque (upper extremity) on 14 subjects was collected using a dynamometer multi-joint testing unit. These data were reduced to a table of coefficients of second degree polynomials, computed using a least squares regression method. All the coefficients were then organized into look-up tables, a compact and convenient storage/retrieval mechanism for the data set. Data from each joint, direction and velocity, were normalized with respect to that joint's average and merged into files (one for each curve for a particular joint). Regression was performed on each one of these files to derive a table of normalized population curve coefficients for each joint axis, direction, and velocity. In addition, a regression table which included all upper extremity joints was built which related average torque to lean body mass for an individual. These two tables are the basis of the regression model which allows the prediction of dynamic isolated joint torques from an individual's lean body mass.

Relationship of extinction coefficient, air pollution, and meteorological parameters in an urban area during 2007 to 2009.

PubMed

Sabetghadam, Samaneh; Ahmadi-Givi, Farhang

2014-01-01

Light extinction, which is the extent of attenuation of light signal for every distance traveled by light in the absence of special weather conditions (e.g., fog and rain), can be expressed as the sum of scattering and absorption effects of aerosols. In this paper, diurnal and seasonal variations of the extinction coefficient are investigated for the urban areas of Tehran from 2007 to 2009. Cases of visibility impairment that were concurrent with reports of fog, mist, precipitation, or relative humidity above 90% are filtered. The mean value and standard deviation of daily extinction are 0.49 and 0.39 km(-1), respectively. The average is much higher than that in many other large cities in the world, indicating the rather poor air quality over Tehran. The extinction coefficient shows obvious diurnal variations in each season, with a peak in the morning that is more pronounced in the wintertime. Also, there is a very slight increasing trend in the annual variations of atmospheric extinction coefficient, which suggests that air quality has regressed since 2007. The horizontal extinction coefficient decreased from January to July in each year and then increased between July and December, with the maximum value in the winter. Diurnal variation of extinction is often associated with small values for low relative humidity (RH), but increases significantly at higher RH. Annual correlation analysis shows that there is a positive correlation between the extinction coefficient and RH, CO, PM10, SO2, and NO2 concentration, while negative correlation exists between the extinction and T, WS, and O3, implying their unfavorable impact on extinction variation. The extinction budget was derived from multiple regression equations using the regression coefficients. On average, 44% of the extinction is from suspended particles, 3% is from air molecules, about 5% is from NO2 absorption, 0.35% is from RH, and approximately 48% is unaccounted for, which may represent errors in the data as well as contribution of other atmospheric constituents omitted from the analysis. Stronger regression equation is achieved in the summer, meaning that the extinction is more predictable in this season using pollutant concentrations.

[Quantitative structure-gas chromatographic retention relationship of polycyclic aromatic sulfur heterocycles using molecular electronegativity-distance vector].

PubMed

Li, Zhenghua; Cheng, Fansheng; Xia, Zhining

2011-01-01

The chemical structures of 114 polycyclic aromatic sulfur heterocycles (PASHs) have been studied by molecular electronegativity-distance vector (MEDV). The linear relationships between gas chromatographic retention index and the MEDV have been established by a multiple linear regression (MLR) model. The results of variable selection by stepwise multiple regression (SMR) and the powerful predictive abilities of the optimization model appraised by leave-one-out cross-validation showed that the optimization model with the correlation coefficient (R) of 0.994 7 and the cross-validated correlation coefficient (Rcv) of 0.994 0 possessed the best statistical quality. Furthermore, when the 114 PASHs compounds were divided into calibration and test sets in the ratio of 2:1, the statistical analysis showed our models possesses almost equal statistical quality, the very similar regression coefficients and the good robustness. The quantitative structure-retention relationship (QSRR) model established may provide a convenient and powerful method for predicting the gas chromatographic retention of PASHs.

A Machine Learning Framework for Plan Payment Risk Adjustment.

PubMed

Rose, Sherri

2016-12-01

To introduce cross-validation and a nonparametric machine learning framework for plan payment risk adjustment and then assess whether they have the potential to improve risk adjustment. 2011-2012 Truven MarketScan database. We compare the performance of multiple statistical approaches within a broad machine learning framework for estimation of risk adjustment formulas. Total annual expenditure was predicted using age, sex, geography, inpatient diagnoses, and hierarchical condition category variables. The methods included regression, penalized regression, decision trees, neural networks, and an ensemble super learner, all in concert with screening algorithms that reduce the set of variables considered. The performance of these methods was compared based on cross-validated R 2 . Our results indicate that a simplified risk adjustment formula selected via this nonparametric framework maintains much of the efficiency of a traditional larger formula. The ensemble approach also outperformed classical regression and all other algorithms studied. The implementation of cross-validated machine learning techniques provides novel insight into risk adjustment estimation, possibly allowing for a simplified formula, thereby reducing incentives for increased coding intensity as well as the ability of insurers to "game" the system with aggressive diagnostic upcoding. © Health Research and Educational Trust.

Validity of a self-administered food frequency questionnaire in the 5-year follow-up survey of the JPHC Study Cohort I to assess sodium and potassium intake: comparison with dietary records and 24-hour urinary excretion level.

PubMed

Sasaki, Satoshi; Ishihara, Junko; Tsugane, Shoichiro

2003-01-01

We compared the intake levels of sodium and potassium assessed with a self-administered semi-quantitative food frequency questionnaire (FFQ) used in a 5-year follow-up survey of the JPHC study and 28-day dietary record (DR), and the corresponding two 24-hour urinary excretion levels (32 men and 57 women) in 3-areas, i.e., Ninohe, Yokote, and Saku Public Health Center areas. The Spearman rank correlation coefficients between dietary sodium assessed with FFQ and the urinary excretion for crude values were 0.24 and -0.10 in men and women, respectively. After adjusting for energy and creatinine, the sodium correlation coefficients were 0.35 and 0.25 in men and women, respectively. The correlation coefficients for crude potassium values were 0.18 and -0.13 in men and women, respectively. After adjusting for energy and creatinine, the potassium correlation coefficients were 0.48 and 0.18 in men and women, respectively in conclusion, a weak correlation was observed both for sodium and potassium after energy and creatinine adjustment in men, whereas no meaningful correlation was observed in women.

Material variability and repetitive member allowable property adjustments in forest products engineering

Treesearch

Steve Verrill; David Kretschmann

2008-01-01

It has been argued that repetitive member allowable property adjustments should be larger for high-variability material than for low-variability material. We report analytic calculations and simulations that suggest that the order of such adjustments should be reversed. That is, given the manner in which allowable properties are currently calculated, as the coefficient...

Parapapillary beta zone in primary school children in Beijing: associations with outdoor activity.

PubMed

Guo, Yin; Liu, Li Juan; Xu, Liang; Lv, Yan Yun; Tang, Ping; Feng, Yi; Zhou, Jin Qiong; Meng, Meng; Jonas, Jost B

2014-02-14

To investigate prevalence and size of parapapillary alpha zone and beta zone and associations with myopia-related factors in primary school children in Beijing. The school-based study included 382 grade-1 children and 299 grade-4 children. The children underwent a comprehensive eye examination and the parents, an interview. The examination was repeated after 1 year. Beta zone (prevalence: 44.5% ± 2.1%; mean area: 0.17 ± 0.29 mm(2)) was significantly associated with more time spent indoors with studying (P = 0.004; standardized correlation coefficient β: 0.14; regression coefficient B: 0.05; 95% confidence interval [CI]: 0.02, 0.09) after adjusting for longer axial length (P < 0.001; β: 0.22; B: 0.07; 95% CI: 0.04, 0.10), more myopic refractive error (P < 0.001; β: -0.29; B: -0.07; 95% CI: -0.09, -0.04), region of habitation (P = 0.03; β: 0.11; B: 0.07; 95% CI: 0.01, 0.14), and vertical disc diameter (P = 0.03; β: 0.10; B: 0.16; 95% CI: 0.02, 0.30). As a corollary, indoors studying time was associated with larger area of beta zone (P = 0.01; β: 0.11; B: 0.30; 95% CI: 0.07, 0.54) after adjusting for higher axial length/corneal curvature radius ratio (AL/CC; P = 0.006; β: 0.12; B: 0.94; 95% CI: 0.27, 1.62) and urban region of habitation (P < 0.001; β: -0.44; B: -0.75; 95% CI: -0.89, -0.61). An increase in AL/CC ratio at 1-year follow-up was associated with more indoors studying time (P = 0.04; β: 0.10; B: 0.01; 95% CI: 0.00, 0.01) and larger beta zone area (P < 0.001; β: 0.19; B: 0.04; 95% CI: 0.02, 0.05) after adjusting for axial length (P < 0.001; β: -0.21; B: -0.01; 95% CI: -0.02, -0.01). Larger parapapillary beta zone area was associated with more indoors studying time after adjustment for axial length, refractive error, and region of habitation, and reversely, more indoors studying time was associated with larger beta zone in multivariate analysis. The results could indicate that parapapillary beta zone is associated with external factors-dependent development of myopia.

Determining Sample Size for Accurate Estimation of the Squared Multiple Correlation Coefficient.

ERIC Educational Resources Information Center

Algina, James; Olejnik, Stephen

2000-01-01

Discusses determining sample size for estimation of the squared multiple correlation coefficient and presents regression equations that permit determination of the sample size for estimating this parameter for up to 20 predictor variables. (SLD)

Levels of Motivation and Readiness for Treatment Aligned With Criminal Justice Referral and Coercion Among Substance Users in England.

PubMed

Jones, Andrew; Hayhurst, Karen Petra; Millar, Tim

2017-11-01

Motivation and readiness for substance misuse treatment predict treatment retention and successful treatment outcomes but may be lower among substance users coerced into treatment. We tested for differences associated with legal involvement and with client perceptions of coercion among individuals entering drug misuse treatment in England. Data collection involved 342 treatment agencies. Measures of motivation and readiness for treatment were taken from the Circumstances, Motivation, and Readiness (CMR) scale. Referral source was ordered to represent level of legal involvement and conditions. Perceived coercion was defined by a CMR item. Linear regression models, adjusting for client complexity, tested for differences in motivation and readiness by these measures. Levels of motivation and readiness did not differ according to level of legal conditions (coefficient = -0.38, 95% CI [-1.65, 0.88]). Motivation was inversely associated with perceived coercion (coefficient = -0.28, 95% CI [-0.05, -0.50], p = .014). At the point of treatment entry, criminal justice referral and aligned conditions have no impact on levels of motivation to achieve positive treatment outcomes. Concerns around lower levels of motivation are better focused on those who perceive themselves as coerced rather than on those whose referral carries a level of legal condition.

Quantitative assessment of human body shape using Fourier analysis

NASA Astrophysics Data System (ADS)

Friess, Martin; Rohlf, F. J.; Hsiao, Hongwei

2004-04-01

Fall protection harnesses are commonly used to reduce the number and severity of injuries. Increasing the efficiency of harness design requires the size and shape variation of the user population to be assessed as detailed and as accurately as possible. In light of the unsatisfactory performance of traditional anthropometry with respect to such assessments, we propose the use of 3D laser surface scans of whole bodies and the statistical analysis of elliptic Fourier coefficients. Ninety-eight male and female adults were scanned. Key features of each torso were extracted as a 3D curve along front, back and the thighs. A 3D extension of Elliptic Fourier analysis4 was used to quantify their shape through multivariate statistics. Shape change as a function of size (allometry) was predicted by regressing the coefficients onto stature, weight and hip circumference. Upper and lower limits of torso shape variation were determined and can be used to redefine the design of the harness that will fit most individual body shapes. Observed allometric changes are used for adjustments to the harness shape in each size. Finally, the estimated outline data were used as templates for a free-form deformation of the complete torso surface using NURBS models (non-uniform rational B-splines).

Regional regression of flood characteristics employing historical information

USGS Publications Warehouse

Tasker, Gary D.; Stedinger, J.R.

1987-01-01

Streamflow gauging networks provide hydrologic information for use in estimating the parameters of regional regression models. The regional regression models can be used to estimate flood statistics, such as the 100 yr peak, at ungauged sites as functions of drainage basin characteristics. A recent innovation in regional regression is the use of a generalized least squares (GLS) estimator that accounts for unequal station record lengths and sample cross correlation among the flows. However, this technique does not account for historical flood information. A method is proposed here to adjust this generalized least squares estimator to account for possible information about historical floods available at some stations in a region. The historical information is assumed to be in the form of observations of all peaks above a threshold during a long period outside the systematic record period. A Monte Carlo simulation experiment was performed to compare the GLS estimator adjusted for historical floods with the unadjusted GLS estimator and the ordinary least squares estimator. Results indicate that using the GLS estimator adjusted for historical information significantly improves the regression model. ?? 1987.

A quantile regression approach can reveal the effect of fruit and vegetable consumption on plasma homocysteine levels.

PubMed

Verly, Eliseu; Steluti, Josiane; Fisberg, Regina Mara; Marchioni, Dirce Maria Lobo

2014-01-01

A reduction in homocysteine concentration due to the use of supplemental folic acid is well recognized, although evidence of the same effect for natural folate sources, such as fruits and vegetables (FV), is lacking. The traditional statistical analysis approaches do not provide further information. As an alternative, quantile regression allows for the exploration of the effects of covariates through percentiles of the conditional distribution of the dependent variable. To investigate how the associations of FV intake with plasma total homocysteine (tHcy) differ through percentiles in the distribution using quantile regression. A cross-sectional population-based survey was conducted among 499 residents of Sao Paulo City, Brazil. The participants provided food intake and fasting blood samples. Fruit and vegetable intake was predicted by adjusting for day-to-day variation using a proper measurement error model. We performed a quantile regression to verify the association between tHcy and the predicted FV intake. The predicted values of tHcy for each percentile model were calculated considering an increase of 200 g in the FV intake for each percentile. The results showed that tHcy was inversely associated with FV intake when assessed by linear regression whereas, the association was different when using quantile regression. The relationship with FV consumption was inverse and significant for almost all percentiles of tHcy. The coefficients increased as the percentile of tHcy increased. A simulated increase of 200 g in the FV intake could decrease the tHcy levels in the overall percentiles, but the higher percentiles of tHcy benefited more. This study confirms that the effect of FV intake on lowering the tHcy levels is dependent on the level of tHcy using an innovative statistical approach. From a public health point of view, encouraging people to increase FV intake would benefit people with high levels of tHcy.

Appendectomy in patients with human immunodeficiency virus: Not as bad as we once thought.

PubMed

Smith, Michael C; Chung, Paul J; Constable, Yohannes C; Boylan, Matthew R; Alfonso, Antonio E; Sugiyama, Gainosuke

2017-04-01

The number of patients living with human immunodeficiency virus and acquired immunodeficiency syndrome is growing due to advances in antiretroviral therapy. Existing literature on appendectomy within this patient population has been limited by small sample sizes. Therefore, we used a large, multiyear, nationwide database to study this topic comprehensively. Using the Nationwide Inpatient Sample, we identified 338,805 patients between 2005 and 2012 who underwent laparoscopic or open appendectomy for acute appendicitis. Interval appendectomies were excluded. We used multivariable adjusted regression models to test differences between patients with human immunodeficiency virus without acquired immunodeficiency syndrome and a reference group, as well as human immunodeficiency virus with acquired immunodeficiency syndrome and a reference group, with regard to duration of stay, hospital charges, in-hospital complications, and in-hospital mortality. Models were adjusted for patient age, sex, race, insurance, socioeconomic status, Elixhauser comorbidity score, and appendix perforation. There were 1,291 (0.38%) patients with human immunodeficiency virus, among which 497 (0.15%) patients had acquired immunodeficiency syndrome. In regression analysis, human immunodeficiency virus alone was not associated with adverse outcomes, while acquired immunodeficiency syndrome alone was associated with longer duration of stay (incidence rate ratio 1.40 [1.37-1.57 95% confidence interval], P < .0001), increased total charges (exponentiated coefficient 1.16 [1.10-1.23 95% confidence interval], P < .0001), and increased risk of postoperative infection (odds ratio 2.12 [1.44-3.13 95% confidence interval], P = .0002). Patients with acquired immunodeficiency syndrome who undergo appendectomy for acute appendicitis are subject to longer and more expensive hospital admissions and have greater rates of postoperative infections while patients with human immunodeficiency virus alone are not at risk for adverse outcomes. Copyright © 2016 Elsevier Inc. All rights reserved.

Dual energy X-ray absorptiometry spine scans to determine abdominal fat in post-menopausal women

PubMed Central

Bea, J. W.; Blew, R. M.; Going, S. B.; Hsu, C-H; Lee, M. C.; Lee, V. R.; Caan, B.J.; Kwan, M.L.; Lohman, T. G.

2016-01-01

Body composition may be a better predictor of chronic disease risk than body mass index (BMI) in older populations. Objectives We sought to validate spine fat fraction (%) from dual energy X-ray absorptiometry (DXA) spine scans as a proxy for total abdominal fat. Methods Total body DXA scan abdominal fat regions of interest (ROI) that have been previously validated by magnetic resonance imaging were assessed among healthy, postmenopausal women who also had antero-posterior spine scans (n=103). ROIs were 1) lumbar vertebrae L2-L4 and 2) L2-Iliac Crest (L2-IC), manually selected by two independent raters, and 3) trunk, auto-selected by DXA software. Intra-class correlation coefficients evaluated intra and inter-rater reliability on a random subset (N=25). Linear regression models, validated by bootstrapping, assessed the relationship between spine fat fraction (%) and total abdominal fat (%) ROIs. Results Mean age, BMI and total body fat were: 66.1 ± 4.8y, 25.8 ± 3.8kg/m2 and 40.0 ± 6.6%, respectively. There were no significant differences within or between raters. Linear regression models adjusted for several participant and scan characteristics were equivalent to using only BMI and spine fat fraction. The model predicted L2-L4 (Adj. R2: 0.83) and L2-IC (Adj.R2:0.84) abdominal fat (%) well; the adjusted R2 for trunk fat (%) was 0.78. Model validation demonstrated minimal over-fitting (Adj. R2: 0.82, 0.83, and 0.77 for L2-L4, L2-IC, and trunk fat respectively). Conclusions The strong correlation between spine fat fraction and DXA abdominal fat measures make it suitable for further development in post-menopausal chronic disease risk prediction models. PMID:27416964

The association of subjective orthodontic treatment need with oral health-related quality of life.

PubMed

Kragt, Lea; Jaddoe, Vincent; Wolvius, Eppo; Ongkosuwito, Edwin

2017-08-01

The existing body of evidence reports an inconsistent association between subjective and objective orthodontic treatment need. The concept of oral health-related quality of life (OHRQoL) might help to explain the differences in subjective and objective orthodontic treatment need. Our aim was to investigate the association of subjective orthodontic treatment with OHRQoL in children. This cross-sectional study was embedded in the Generation R Study, a population-based prospective cohort study. OHRQoL and subjective orthodontic treatment need were assessed by parental questionnaires. Questionnaire items were individually compared among children with no, borderline and definite subjective orthodontic need. The association between subjective orthodontic treatment need and OHRQoL was investigated in multivariate regression analysis with weighted least squares. Differences by sex and levels of objective orthodontic treatment need were evaluated. In total, 3774 children were included in the analysis. Children with borderline subjective orthodontic treatment need and those with definite subjective orthodontic treatment need had significantly poorer OHRQoL based on the fully adjusted model (adjusted regression coefficient (aβ)=-0.49, 95% CI: -0.75, -0.30; (aβ)=-1.58, 95% CI: -1.81, -1.58, respectively). The association between subjective orthodontic treatment need and OHRQoL was stronger in girls than in boys and stronger in children with objective orthodontic treatment need than in those with none. Oral health-related quality of life is poorer in children with subjective orthodontic treatment need. This has not been investigated before in such a large-population-based study and clearly offers an explanation for the lack of concurrence between objective and subjective orthodontic treatment need. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Epidemiology of inflammatory bowel disease: Is there a shift towards onset at a younger age?

PubMed

Braegger, Christian P; Ballabeni, Pierluigi; Rogler, Daniela; Vavricka, Stephan R; Friedt, Michael; Pittet, Valérie

2011-08-01

Increasing numbers of paediatric and adolescent patients with Crohn disease (CD) and ulcerative colitis (UC) are reported. To determine whether this observation is a consequence of a shift towards onset at a younger age, we analysed retrospective data from patients enrolled in the Swiss IBD Cohort Study (SIBDCS). The SIBDCS is a disease-based cohort in Switzerland, which collects retrospective and prospective data on a large sample of patients with inflammatory bowel disease (IBD). Patients, diagnosed from 1980, were stratified according to diagnosis of CD and UC. Age at disease onset (age at first symptoms and age at diagnosis) was analysed in relation to calendar year of disease onset. Data were extracted from physician and patient questionnaires. Linear regressions of age at disease onset by calendar year of disease onset adjusted by sex, country of birth, and education were performed. Adjusted regression coefficients for CD and UC were significantly positive, that is, age at disease onset has increased with time. Male sex was associated with an increase in age at disease onset, and birth in Switzerland with a decrease. These associations were statistically significant. The results from the SIBDCS do not support the hypothesis that disease onset of both CD and UC occur today at a younger age. On the contrary, our results show that there is a significant trend for age at disease onset occurring at an older age today as compared with recent decades. We conclude that the observation of increasing numbers of paediatric and adolescent patients with IBD is not caused by a trend towards disease onset at a younger age, but that this may rather be a consequence of the overall increasing incidence of these conditions.

Effects of low-level prenatal lead exposure on child IQ at 4 and 8 years in a UK birth cohort study.

PubMed

Taylor, Caroline M; Kordas, Katarzyna; Golding, Jean; Emond, Alan M

2017-09-01

The association between childhood exposure to lead (Pb) and deficits in cognitive function is well established. The association with prenatal exposure, however, is not well understood, even though the potential adverse effects are equally important. To evaluate the association between low prenatal exposure to lead and IQ in children, to determine whether there were sex differences in the associations, and to evaluate the moderation effect of prenatal Pb exposure on child IQ. Whole blood samples from pregnant women enrolled in ALSPAC (n=4285) and from offspring at age 30 months (n=235) were analysed for Pb. Associations between prenatal blood lead concentrations (B-Pb) and child IQ at age 4 and 8 years (WPPSI and WISC-III, respectively) were examined in adjusted regression models. There was no association of prenatal lead exposure with child IQ at 4 or 8 years old in adjusted regression models, and no moderation of the association between child B-Pb and IQ. However, there was a positive association for IQ at age 8 years in girls with a predicted increase in IQ (points) per 1μg/dl of: verbal 0.71, performance 0.57, total 0.73. In boys, the coefficients tended to be negative (-0.15, -0.42 and -0.29 points, respectively). Prenatal lead exposure was not associated with adverse effects on child IQ at age 4 or 8 years in this study. There was, however, some evidence to suggest that boys are more susceptible than girls to prenatal exposure to lead. Further investigation in other cohorts is required. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

Relationships between serum leptin levels and bone mineral parameters in school-aged children: a 3-year follow-up study.

PubMed

Kouda, Katsuyasu; Ohara, Kumiko; Fujita, Yuki; Nakamura, Harunobu; Tachiki, Takahiro; Iki, Masayuki

2018-02-02

Leptin regulates bone cell differentiation and functions via direct and indirect actions in experimental settings. Epidemiologically, however, the impact of leptin on the regulation of bone metabolism remains unclear. While some studies have reported a positive relationship between leptin and bone mineral parameters, other studies found an inverse or no association. We analyzed data from a population-based follow-up survey of community-dwelling children in Hamamatsu, Japan, to investigate relationships between leptin levels and bone mineral parameters. Multiple regression analysis was performed. Multicollinearity was quantified using the variance infiltration factor (VIF). Among 408 children who participated in the baseline survey (at age 11.2 years), 254 (121 boys and 133 girls) completed the follow-up survey (at age 14.2 years). Leptin levels were strongly related to fat mass (r = 0.87 in boys, r = 0.80 in girls). Leptin levels at baseline were significantly (P < 0.05) positively related to total body less head (TBLH) areal bone mineral density (aBMD) at follow-up in girls (standardized partial regression coefficient: β = 0.302, VIF = 2.246), after adjusting for body fat percentage (%). On the other hand, leptin levels were inversely related to TBLH aBMD in boys (β = - 0.395, VIF = 4.116), after adjusting for body fat mass (kg). Positive relationships between leptin levels and bone mineral parameters were observed with VIF values < 4.0, whereas inverse relationships were observed with VIF values ≥ 4.0. These findings suggest that positive relationships between leptin levels and bone mineral parameters are weak, or not always observed, due to statistical problems (i.e., multicollinearity) and other factors derived from adipose tissue.

Biomechanical CT Metrics Are Associated With Patient Outcomes in COPD

PubMed Central

Bodduluri, Sandeep; Bhatt, Surya P; Hoffman, Eric A.; Newell, John D.; Martinez, Carlos H.; Dransfield, Mark T.; Han, Meilan K.; Reinhardt, Joseph M.

2017-01-01

Background Traditional metrics of lung disease such as those derived from spirometry and static single-volume CT images are used to explain respiratory morbidity in patients with chronic obstructive pulmonary disease (COPD), but are insufficient. We hypothesized that the mean Jacobian determinant, a measure of local lung expansion and contraction with respiration, would contribute independently to clinically relevant functional outcomes. Methods We applied image registration techniques to paired inspiratory-expiratory CT scans and derived the Jacobian determinant of the deformation field between the two lung volumes to map local volume change with respiration. We analyzed 490 participants with COPD with multivariable regression models to assess strengths of association between traditional CT metrics of disease and the Jacobian determinant with respiratory morbidity including dyspnea (mMRC), St Georges Respiratory Questionnaire (SGRQ) score, six-minute walk distance (6MWD), and the BODE index, as well as all-cause mortality. Results The Jacobian determinant was significantly associated with SGRQ (adjusted regression co-efficient β = −11.75,95%CI −21.6 to −1.7;p=0.020), and with 6MWD (β=321.15, 95%CI 134.1 to 508.1;p<0.001), independent of age, sex, race, body-mass-index, FEV1, smoking pack-years, CT emphysema, CT gas trapping, airway wall thickness, and CT scanner protocol. The mean Jacobian determinant was also independently associated with the BODE index (β= −0.41, 95%CI −0.80 to −0.02; p = 0.039), and mortality on follow-up (adjusted hazards ratio = 4.26, 95%CI = 0.93 to 19.23; p = 0.064). Conclusion Biomechanical metrics representing local lung expansion and contraction improve prediction of respiratory morbidity and mortality and offer additional prognostic information beyond traditional measures of lung function and static single-volume CT metrics. PMID:28044005

The self-perception of dyspnoea threshold during the 6-min walk test: a good alternative to estimate the ventilatory threshold in chronic obstructive pulmonary disease.

PubMed

Couillard, Annabelle; Tremey, Emilie; Prefaut, Christian; Varray, Alain; Heraud, Nelly

2016-12-01

To determine and/or adjust exercise training intensity for patients when the cardiopulmonary exercise test is not accessible, the determination of dyspnoea threshold (defined as the onset of self-perceived breathing discomfort) during the 6-min walk test (6MWT) could be a good alternative. The aim of this study was to evaluate the feasibility and reproducibility of self-perceived dyspnoea threshold and to determine whether a useful equation to estimate ventilatory threshold from self-perceived dyspnoea threshold could be derived. A total of 82 patients were included and performed two 6MWTs, during which they raised a hand to signal self-perceived dyspnoea threshold. The reproducibility in terms of heart rate (HR) was analysed. On a subsample of patients (n=27), a stepwise regression analysis was carried out to obtain a predictive equation of HR at ventilatory threshold measured during a cardiopulmonary exercise test estimated from HR at self-perceived dyspnoea threshold, age and forced expiratory volume in 1 s. Overall, 80% of patients could identify self-perceived dyspnoea threshold during the 6MWT. Self-perceived dyspnoea threshold was reproducibly expressed in HR (coefficient of variation=2.8%). A stepwise regression analysis enabled estimation of HR at ventilatory threshold from HR at self-perceived dyspnoea threshold, age and forced expiratory volume in 1 s (adjusted r=0.79, r=0.63, and relative standard deviation=9.8 bpm). This study shows that a majority of patients with chronic obstructive pulmonary disease can identify a self-perceived dyspnoea threshold during the 6MWT. This HR at the dyspnoea threshold is highly reproducible and enable estimation of the HR at the ventilatory threshold.

Dual purpose recovered coagulant from drinking water treatment residuals for adjustment of initial pH and coagulation aid in electrocoagulation process.

PubMed

Jung, Kyung-Won; Ahn, Kyu-Hong

2016-01-01

The present study is focused on the application of recovered coagulant (RC) by acidification from drinking water treatment residuals for both adjusting the initial pH and aiding coagulant in electrocoagulation. To do this, real cotton textile wastewater was used as a target pollutant, and decolorization and chemical oxygen demand (COD) removal efficiency were monitored. A preliminary test indicated that a stainless steel electrode combined with RC significantly accelerated decolorization and COD removal efficiencies, by about 52% and 56%, respectively, even at an operating time of 5 min. A single electrocoagulation system meanwhile requires at least 40 min to attain the similar removal performances. Subsequently, the interactive effect of three independent variables (applied voltage, initial pH, and reaction time) on the response variables (decolorization and COD removal) was evaluated, and these parameters were statistically optimized using the response surface methodology. Analysis of variance showed a high coefficient of determination values (decolorization, R(2) = 0.9925 and COD removal, R(2) = 0.9973) and satisfactory prediction second-order polynomial quadratic regression models. Average decolorization and COD removal of 89.52% and 94.14%, respectively, were achieved, corresponding to 97.8% and 98.1% of the predicted values under statistically optimized conditions. The results suggest that the RC effectively played a dual role of both adjusting the initial pH and aiding coagulant in the electrocoagulation process.

Combined dietary and exercise intervention for control of serum cholesterol in the workplace

NASA Technical Reports Server (NTRS)

Angotti, C. M.; Chan, W. T.; Sample, C. J.; Levine, M. S.

2000-01-01

PURPOSE: To elucidate a potential combined dietary and exercise intervention affect on cardiovascular risk reduction of the National Aeronautics and Space Administration Headquarters employees. DESIGN: A nonexperimental, longitudinal, clinical-chart review study (1987 to 1996) of an identified intervention group and a reference (not a control) group. SETTING: The study group worked in an office environment and participated in the annual medical examinations. SUBJECTS: An intervention group of 858 people with initially elevated serum cholesterol, and a reference group of 963 people randomly sampled from 10% of the study group. MEASURES: Serum cholesterol data were obtained for both groups, respectively, from pre- and postintervention and annual examinations. The reference group was adjusted by statistical exclusion of potential intervention participants. Regression equations (cholesterol vs. study years) for the unadjusted/adjusted reference groups were tested for statistical significance. INTERVENTION: An 8-week individualized, combined dietary and exercise program was instituted with annual follow-ups and was repeated where warranted. RESULTS: Only the unadjusted (but not the adjusted) reference group with initial mean total serum cholesterol levels above 200 mg/dL shows a significant 9-year decline trend and significant beta coefficient tests. An intervention effect is suggested. Mean high density lipoprotein cholesterol rose slightly in the intervention group but was maintained in the reference group. CONCLUSION: With potential design limitations, the NASA intervention program focusing on a high risk group may be associated to some degree, if not fully, with an overall cardiovascular risk profile improvement.

Neighbourhood socioeconomic inequality and gender differences in body mass index: The role of unhealthy behaviours.

PubMed

Feng, Xiaoqi; Wilson, Andrew

2017-08-01

Reported differences in the severity of the social gradient in body mass index (BMI) by gender may be attributable to differences in behaviour. Self-reported height, weight, socioeconomic and behavioural data were obtained for a sample of 10,281 Australians aged ≥15years in 2009. Multilevel regressions were fitted with BMI as the outcome variable. Two-way interactions between gender and neighbourhood disadvantage were fitted, adjusted for confounders. Models were then adjusted for four behavioural factors ("chips, snacks and confectionary", "smoking, little fruit or veg", "time poor and less physically active" and "alcohol consumption"). Additional models were fitted on a subset with accurate perceptions of weight status (determined by World Health Organization criteria) to control for potential social desirability bias. Although higher BMI was observed for men in most disadvantaged compared with most affluent neighbourhoods (coefficient 0.87, 95% CI 0.35 to 1.40), this pattern was stronger among women (1.80, 95% CI 1.17 to 2.42). Adjusting for differences in behaviours attenuated, but did not fully explain the differences in social gradients observed for men (0.73, 95% CI 0.21 to 1.26) and women (1.73, 1.10 to 2.36). Differences in behaviour did not explain contrasting socioeconomic gradients in adult BMI by gender. Further research on differences in BMI, health and behaviour over time aligned with how heavy a person may perceive themselves to be is warranted. Copyright © 2017. Published by Elsevier Inc.

Evaluation of the influence of the definition of an isolated hip fracture as an exclusion criterion for trauma system benchmarking: a multicenter cohort study.

PubMed

Tiao, J; Moore, L; Porgo, T V; Belcaid, A

2016-06-01

To assess whether the definition of an IHF used as an exclusion criterion influences the results of trauma center benchmarking. We conducted a multicenter retrospective cohort study with data from an integrated Canadian trauma system. The study population included all patients admitted between 1999 and 2010 to any of the 57 adult trauma centers. Seven definitions of IHF based on diagnostic codes, age, mechanism of injury, and secondary injuries, identified in a systematic review, were used. Trauma centers were benchmarked using risk-adjusted mortality estimates generated using the Trauma Risk Adjustment Model. The agreement between benchmarking results generated under different IHF definitions was evaluated with correlation coefficients on adjusted mortality estimates. Correlation coefficients >0.95 were considered to convey acceptable agreement. The study population consisted of 172,872 patients before exclusion of IHF and between 128,094 and 139,588 patients after exclusion. Correlation coefficients between risk-adjusted mortality estimates generated in populations including and excluding IHF varied between 0.86 and 0.90. Correlation coefficients of estimates generated under different definitions of IHF varied between 0.97 and 0.99, even when analyses were restricted to patients aged ≥65 years. Although the exclusion of patients with IHF has an influence on the results of trauma center benchmarking based on mortality, the definition of IHF in terms of diagnostic codes, age, mechanism of injury and secondary injury has no significant impact on benchmarking results. Results suggest that there is no need to obtain formal consensus on the definition of IHF for benchmarking activities.

Comparison of regression coefficient and GIS-based methodologies for regional estimates of forest soil carbon stocks.

PubMed

Campbell, J Elliott; Moen, Jeremie C; Ney, Richard A; Schnoor, Jerald L

2008-03-01

Estimates of forest soil organic carbon (SOC) have applications in carbon science, soil quality studies, carbon sequestration technologies, and carbon trading. Forest SOC has been modeled using a regression coefficient methodology that applies mean SOC densities (mass/area) to broad forest regions. A higher resolution model is based on an approach that employs a geographic information system (GIS) with soil databases and satellite-derived landcover images. Despite this advancement, the regression approach remains the basis of current state and federal level greenhouse gas inventories. Both approaches are analyzed in detail for Wisconsin forest soils from 1983 to 2001, applying rigorous error-fixing algorithms to soil databases. Resulting SOC stock estimates are 20% larger when determined using the GIS method rather than the regression approach. Average annual rates of increase in SOC stocks are 3.6 and 1.0 million metric tons of carbon per year for the GIS and regression approaches respectively.

Radon-222 concentrations in ground water and soil gas on Indian reservations in Wisconsin

USGS Publications Warehouse

DeWild, John F.; Krohelski, James T.

1995-01-01

For sites with wells finished in the sand and gravel aquifer, the coefficient of determination (R2) of the regression of concentration of radon-222 in ground water as a function of well depth is 0.003 and the significance level is 0.32, which indicates that there is not a statistically significant relation between radon-222 concentrations in ground water and well depth. The coefficient of determination of the regression of radon-222 in ground water and soil gas is 0.19 and the root mean square error of the regression line is 271 picocuries per liter. Even though the significance level (0.036) indicates a statistical relation, the root mean square error of the regression is so large that the regression equation would not give reliable predictions. Because of an inadequate number of samples, similar statistical analyses could not be performed for sites with wells finished in the crystalline and sedimentary bedrock aquifers.

Clinical Utility of Random Anti–Tumor Necrosis Factor Drug–Level Testing and Measurement of Antidrug Antibodies on the Long‐Term Treatment Response in Rheumatoid Arthritis

PubMed Central

Jani, Meghna; Chinoy, Hector; Warren, Richard B.; Griffiths, Christopher E. M.; Plant, Darren; Fu, Bo; Morgan, Ann W.; Wilson, Anthony G.; Isaacs, John D.; Hyrich, KimmeL.; Prouse, P. J.; Moitra, R. K.; Shawe, D. J.; Nisar, M.; Fairburn, K.; Nixon, J.; Barnes, T.; Hui, M.; Coady, D.; Wright, D.; Morley, C.; Raftery, G.; Bracewell, C.; Bridges, M.; Armstrong, D.; Chuck, A. J.; Hailwood, S.; Kumar, N.; Ashok, D.; Reece, R.; O'Reilly, S. C.; Ding, T.; Badcock, L. J.; Deighton, C. M.; Raj, N.; Regan, M. R.; Summers, G. D.; Williams, R. A.; Lambert, J. R.; Stevens, R.; Wilkinson, C.; Kelly, C. A.; Hamilton, J.; Heycock, C. R.; Saravanan, V.; Cope, A.; Garrood, T.; Ng, N.; Kirkham, B.; Green, M.; Gough, A.; Lawson, C.; Das, D.; Borbas, E.; Wazir, T.; Emery, P.; Bingham, S.; Bird, H. A.; Conaghan, P.G.; Pease, C. T.; Wakefield, R. J.; Buch, M.; Bruce, I.; Gorodkin, R.; Ho, P.; Parker, B.; Smith, W.; Jenkins, E.; Mukhtyar, C.; Gaffney, K.; Macgregor, A. J.; Marshall, T.; Merry, P.; DeSilva, C.; Birrell, F. N.; Crook, P. R.; Szebenyi, B.; Bates, D.; James, D.; Gillott, T.; Alvi, A.; Grey, C.; Browning, J.; McHale, J. F.; Gaywood, I.C.; Jones, A. C.; Lanyon, P.; Pande, I.; Doherty, M.; Gupta, A.; Courtney, P. A.; Srikanth, A.; Abhishek, A.; Das, L.; Pattrick, M.; Snowden, H. N.; Bowden, A. P.; Smith, E. E.; Klimiuk, P.; Speden, D. J.; Naz, S.; Ledingham, J. M.; Hull, R. G.; McCrae, F.; Cooper, A.; Young‐Min, S. A.; Wong, E.; Shaban, R.; Woolf, A. D.; Davis, M.; Hutchinson, D.; Endean, A.; Mewar, D.; Tunn, E. J.; Nelson, K.; Kennedy, T. D.; Dubois, C.; Pauling, J.; Korendowych, E.; Jenkinson, T.; Sengupta, R.; Bhalla, A.; McHugh, N.; O'Neil, T.; Herrick, A. L.; Jones, A. K.; Cooper, R. G.; Dixon, W. G.; Harrison, B.; Buckley, C. D.; Carruthers, D. C.; Elamanchi, R.; Gordon, P. C.; Grindulis, K. A.; Khattak, F.; Raza, K.; Situnayake, K.; Akil, M.; Till, S.; Dunkley, L.; Tattersall, R.; Kilding, R.; Tait, T.; Maxwell, J.; Till, S.; Kuet, K.-P.; Plant, M. J.; Clarke, F.; Fordham, J. N.; Tuck, S.; Pathare, S. K.; Paul, A.; Marguerie, C. P.; Rigby, S. P.; Dunn, N.; Abbas, I.; Filer, C.; Abernethy, V. E.; Clewes, A. R.; Dawson, J. K.; Kitas, G.; Erb, N.; Klocke, R.; Whallett, A. J.; Douglas, K.; Pace, A.; Sandhu, R.; John, H.; Shand, L.; Lane, S.; Foster, H.; Griffiths, B.; Griffiths, I.; Kay, L.; Ng, W.-F.; Platt, P. N.; Walker, D. J.; Peterson, P.; Lorenzi, A.; Friswell, M.; Thompson, B.; Lee, M.; Pratt, A.; Hopkinson, N. D.; Dunne, C. A.; Quilty, B.; Marks, J.; Mukherjee, S.; Mulherin, D.; Chalam, S. V.; Price, T.; Sheeran, T.; Venkatachalam, S.; Baskar, S.; Al- Allaf, W.; McKenna, F.; Shah, P.; Filer, A.; Bowman, S. J.; Jobanputra, P.; Rankin, E. C.; Allen, M.; Chaudhuri, K.; Dubey, S.; Price‐Forbes, A.; Ravindran, J.; Samanta, A.; Sheldon, P.; Hassan, W.; Francis, J.; Kinder, A.; Neame, R.; Moorthy, A.; Bukhari, M.; Ottewell, L.; Palkonyai, E.; Hider, S.; Hassell, A.; Menon, A.; Dowson, C.; Kamath, S.; Packham, J.; Dutta, S.; Price, S.; Roddy, E.; Paskins, Z.; O'Reilly, D. T.; Rajagopal, V.; Bhagat, S.; Chattopadhyay, C. B.; Green, M.; Quinn, D.; Isdale, A.; Brown, A.; Saleem, B.; Foo, B.; Al Saffar, Z.; Koduri, G.

2015-01-01

Objective To investigate whether antidrug antibodies and/or drug non‐trough levels predict the long‐term treatment response in a large cohort of patients with rheumatoid arthritis (RA) treated with adalimumab or etanercept and to identify factors influencing antidrug antibody and drug levels to optimize future treatment decisions. Methods A total of 331 patients from an observational prospective cohort were selected (160 patients treated with adalimumab and 171 treated with etanercept). Antidrug antibody levels were measured by radioimmunoassay, and drug levels were measured by enzyme‐linked immunosorbent assay in 835 serial serum samples obtained 3, 6, and 12 months after initiation of therapy. The association between antidrug antibodies and drug non‐trough levels and the treatment response (change in the Disease Activity Score in 28 joints) was evaluated. Results Among patients who completed 12 months of followup, antidrug antibodies were detected in 24.8% of those receiving adalimumab (31 of 125) and in none of those receiving etanercept. At 3 months, antidrug antibody formation and low adalimumab levels were significant predictors of no response according to the European League Against Rheumatism (EULAR) criteria at 12 months (area under the receiver operating characteristic curve 0.71 [95% confidence interval (95% CI) 0.57, 0.85]). Antidrug antibody–positive patients received lower median dosages of methotrexate compared with antidrug antibody–negative patients (15 mg/week versus 20 mg/week; P = 0.01) and had a longer disease duration (14.0 versus 7.7 years; P = 0.03). The adalimumab level was the best predictor of change in the DAS28 at 12 months, after adjustment for confounders (regression coefficient 0.060 [95% CI 0.015, 0.10], P = 0.009). Etanercept levels were associated with the EULAR response at 12 months (regression coefficient 0.088 [95% CI 0.019, 0.16], P = 0.012); however, this difference was not significant after adjustment. A body mass index of ≥30 kg/m2 and poor adherence were associated with lower drug levels. Conclusion Pharmacologic testing in anti–tumor necrosis factor–treated patients is clinically useful even in the absence of trough levels. At 3 months, antidrug antibodies and low adalimumab levels are significant predictors of no response according to the EULAR criteria at 12 months. PMID:26109489

Modeling Group Differences in OLS and Orthogonal Regression: Implications for Differential Validity Studies

ERIC Educational Resources Information Center

Kane, Michael T.; Mroch, Andrew A.

2010-01-01

In evaluating the relationship between two measures across different groups (i.e., in evaluating "differential validity") it is necessary to examine differences in correlation coefficients and in regression lines. Ordinary least squares (OLS) regression is the standard method for fitting lines to data, but its criterion for optimal fit…

Incremental Net Effects in Multiple Regression

ERIC Educational Resources Information Center

Lipovetsky, Stan; Conklin, Michael

2005-01-01

A regular problem in regression analysis is estimating the comparative importance of the predictors in the model. This work considers the 'net effects', or shares of the predictors in the coefficient of the multiple determination, which is a widely used characteristic of the quality of a regression model. Estimation of the net effects can be a…

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

USGS Publications Warehouse

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-01-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

Panel regressions to estimate low-flow response to rainfall variability in ungaged basins

NASA Astrophysics Data System (ADS)

Bassiouni, Maoya; Vogel, Richard M.; Archfield, Stacey A.

2016-12-01

Multicollinearity and omitted-variable bias are major limitations to developing multiple linear regression models to estimate streamflow characteristics in ungaged areas and varying rainfall conditions. Panel regression is used to overcome limitations of traditional regression methods, and obtain reliable model coefficients, in particular to understand the elasticity of streamflow to rainfall. Using annual rainfall and selected basin characteristics at 86 gaged streams in the Hawaiian Islands, regional regression models for three stream classes were developed to estimate the annual low-flow duration discharges. Three panel-regression structures (random effects, fixed effects, and pooled) were compared to traditional regression methods, in which space is substituted for time. Results indicated that panel regression generally was able to reproduce the temporal behavior of streamflow and reduce the standard errors of model coefficients compared to traditional regression, even for models in which the unobserved heterogeneity between streams is significant and the variance inflation factor for rainfall is much greater than 10. This is because both spatial and temporal variability were better characterized in panel regression. In a case study, regional rainfall elasticities estimated from panel regressions were applied to ungaged basins on Maui, using available rainfall projections to estimate plausible changes in surface-water availability and usable stream habitat for native species. The presented panel-regression framework is shown to offer benefits over existing traditional hydrologic regression methods for developing robust regional relations to investigate streamflow response in a changing climate.

Essays in energy economics: The electricity industry

NASA Astrophysics Data System (ADS)

Martinez-Chombo, Eduardo

Electricity demand analysis using cointegration and error-correction models with time varying parameters: The Mexican case. In this essay we show how some flexibility can be allowed in modeling the parameters of the electricity demand function by employing the time varying coefficient (TVC) cointegrating model developed by Park and Hahn (1999). With the income elasticity of electricity demand modeled as a TVC, we perform tests to examine the adequacy of the proposed model against the cointegrating regression with fixed coefficients, as well as against the spuriousness of the regression with TVC. The results reject the specification of the model with fixed coefficients and favor the proposed model. We also show how some flexibility is gained in the specification of the error correction model based on the proposed TVC cointegrating model, by including more lags of the error correction term as predetermined variables. Finally, we present the results of some out-of-sample forecast comparison among competing models. Electricity demand and supply in Mexico. In this essay we present a simplified model of the Mexican electricity transmission network. We use the model to approximate the marginal cost of supplying electricity to consumers in different locations and at different times of the year. We examine how costs and system operations will be affected by proposed investments in generation and transmission capacity given a forecast of growth in regional electricity demands. Decomposing electricity prices with jumps. In this essay we propose a model that decomposes electricity prices into two independent stochastic processes: one that represents the "normal" pattern of electricity prices and the other that captures temporary shocks, or "jumps", with non-lasting effects in the market. Each contains specific mean reverting parameters to estimate. In order to identify such components we specify a state-space model with regime switching. Using Kim's (1994) filtering algorithm we estimate the parameters of the model, the transition probabilities and the unobservable components for the mean adjusted series of New South Wales' electricity prices. Finally, bootstrap simulations were performed to estimate the expected contribution of each of the components in the overall electricity prices.

Multi-band transit observations of the TrES-2b exoplanet

NASA Astrophysics Data System (ADS)

Mislis, D.; Schröter, S.; Schmitt, J. H. M. M.; Cordes, O.; Reif, K.

2010-02-01

We present a new data set of transit observations of the TrES-2b exoplanet taken in spring 2009, using the 1.2 m Oskar-Lühning telescope (OLT) of Hamburg Observatory and the 2.2 m telescope at Calar Alto Observatory using BUSCA (Bonn University Simultaneous CAmera). Both the new OLT data, taken with the same instrumental setup as our data taken in 2008, as well as the simultaneously recorded multicolor BUSCA data confirm the low inclination values reported previously, and in fact suggest that the TrES-2b exoplanet has already passed the first inclination threshold (imin,1 = 83.417°) and is not eclipsing the full stellar surface any longer. Using the multi-band BUSCA data we demonstrate that the multicolor light curves can be consistently fitted with a given set of limb darkening coefficients without the need to adjust these coefficients, and further, we can demonstrate that wavelength dependent stellar radius changes must be small as expected from theory. Our new observations provide further evidence for a change of the orbit inclination of the transiting extrasolar planet TrES-2b reported previously. We examine in detail possible causes for this inclination change and argue that the observed change should be interpreted as nodal regression. While the assumption of an oblate host star requires an unreasonably large second harmonic coefficient, the existence of a third body in the form of an additional planet would provide a very natural explanation for the observed secular orbit change. Given the lack of clearly observed short-term variations of transit timing and our observed secular nodal regression rate, we predict a period between approximately 50 and 100 days for a putative perturbing planet of Jovian mass. Such an object should be detectable with present-day radial velocity (RV) techniques, but would escape detection through transit timing variations. Photometric transit data are only available in electronic form at the CDS via anonymous ftp to cdsarc.u-strasbg.fr (130.79.128.5) or via http://cdsweb.u-strasbg.fr/cgi-bin/qcat?J/A+A/510/A107

The impact of maternal adiposity specialization on infant birthweight: upper versus lower body fat.

PubMed

Sundermann, Alexandra C; Abell, Troy D; Baker, Lisa C; Mengel, Mark B; Reilly, Kathryn E; Bonow, Michael A; Hoy, Gregory E; Clover, Richard D

2016-11-01

The specialization of human fat deposits is an inquiry of special importance in the study of fetal growth. It has been theorized that maternal lower-body fat is designated specifically for lactation and not for the growth of the fetus. Our goal was to compare the contributions of maternal upper-body versus lower-body adiposity to infant birth weight. We hypothesized that upper-body adiposity would be strongly associated with infant birth weight and that lower-body adiposity would be weakly or negligibly associated with infant birth weight-after adjusting for known determinants. In this prospective cohort study, 355 women initiated medical pre-natal care during the first trimester of pregnancy at The University of Oklahoma Health Sciences Center during 1990-1993. Maternal anthropometric measurements were assessed at the first clinic visit: (a) height; (b) weight; (c) circumferences of the upper arm, forearm, and thigh; and, (d) skin-fold measurements of the bicep, subscapular region, and thigh. Infant birth weight was regressed on known major determinants to create the foundational model. Maternal anthropometric variables subsequently were added one at a time into this multiple regression model. The highest contribution by a single anthropometric variable to infant birthweight was, in order: subscapular skin-fold, forearm circumference, and thigh circumference. With one upper-body (subscapular skin-fold) and one lower-body (circumference of the thigh) adiposity measure in the model, the z-score regression coefficient (s.e.) was 85.7g (30.8) [p=0.0057] for maternal subscapular skin-fold and 19.0g (31.6) [p=0.5477] for circumference of the thigh. When the second-best upper-body contributor to infant birthweight (circumference of the forearm) was entered with one lower-body measure into the model, the z-score regression coefficient (s.e.) was 77.5g (38.5) [p=0.0451] for maternal forearm circumference and 14.1g (38.5) [p=0.7146] for circumference of the thigh. When both subscapular skinfold and forearm circumference were added to the model in place of BMI, the explained variance (r 2 =0.5478) was similar to the model using BMI (r 2 =0.5487). Upper-body adiposity - whether operationalized by subscapular skin-fold or circumference of the forearm - was a markedly larger determinant of infant birth weight than lower-body adiposity. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Coherent active methods for applications in room acoustics.

PubMed

Guicking, D; Karcher, K; Rollwage, M

1985-10-01

An adjustment of reverberation time in rooms is often desired, even for low frequencies where passive absorbers fail. Among the active (electroacoustic) systems, incoherent ones permit lengthening of reverberation time only, whereas coherent active methods will allow sound absorption as well. A coherent-active wall lining consists of loudspeakers with microphones in front and adjustable control electronics. The microphones pick up the incident sound and drive the speakers in such a way that the reflection coefficient takes on prescribed values. An experimental device for the one-dimensional case allows reflection coefficients between almost zero and about 1.5 to be realized below 1000 Hz. The extension to three dimensions presents problems, especially by nearfield effects. Experiments with a 3 X 3 loudspeaker array and computer simulations proved that the amplitude reflection coefficient can be adjusted between 10% and 200% for sinusoidal waves at normal and oblique incidence. Future developments have to make the system work with broadband excitation and in more diffuse sound fields. It is also planned to combine the active reverberation control with active diffusion control.

Development of bovine serum albumin-water partition coefficients predictive models for ionogenic organic chemicals based on chemical form adjusted descriptors.

PubMed

Ding, Feng; Yang, Xianhai; Chen, Guosong; Liu, Jining; Shi, Lili; Chen, Jingwen

2017-10-01

The partition coefficients between bovine serum albumin (BSA) and water (K BSA/w ) for ionogenic organic chemicals (IOCs) were different greatly from those of neutral organic chemicals (NOCs). For NOCs, several excellent models were developed to predict their logK BSA/w . However, it was found that the conventional descriptors are inappropriate for modeling logK BSA/w of IOCs. Thus, alternative approaches are urgently needed to develop predictive models for K BSA/w of IOCs. In this study, molecular descriptors that can be used to characterize the ionization effects (e.g. chemical form adjusted descriptors) were calculated and used to develop predictive models for logK BSA/w of IOCs. The models developed had high goodness-of-fit, robustness, and predictive ability. The predictor variables selected to construct the models included the chemical form adjusted averages of the negative potentials on the molecular surface (V s-adj - ), the chemical form adjusted molecular dipole moment (dipolemoment adj ), the logarithm of the n-octanol/water distribution coefficient (logD). As these molecular descriptors can be calculated from their molecular structures directly, the developed model can be easily used to fill the logK BSA/w data gap for other IOCs within the applicability domain. Furthermore, the chemical form adjusted descriptors calculated in this study also could be used to construct predictive models on other endpoints of IOCs. Copyright © 2017 Elsevier Inc. All rights reserved.

Elevated manganese exposure and school-aged children's behavior: a gender-stratified analysis.

PubMed

Menezes-Filho, José A; de Carvalho-Vivas, Chrissie F; Viana, Gustavo F S; Ferreira, Junia R D; Nunes, Lorena S; Mergler, Donna; Abreu, Neander

2014-12-01

High levels of waterborne manganese have been associated with problematic behavior in school-aged children, however to date this has not been reported for children exposed to airborne manganese. The objective of the present study was to examine behavioral traits among children with exposure to airborne manganese from a ferro-manganese alloy plant, located in the metropolitan region of Salvador, Brazil. The study included 34 boys and 36 girls, aged 7-12 years, living in two communities within a 3-km radius from the plant. For each child, hair manganese levels (MnH) and blood lead (PbB) levels were analyzed by graphite furnace atomic absorption spectrometry. The Children's Behavior Check List (CBCL) (Portuguese version validated in Brazil) was administered to parents or caregivers, providing scale scores of internalizing (withdrawn, somatic complaints, and anxious/depressed scales), externalizing (disruptive and aggressive) behaviors and a separate scale for attention problems. Median and range for MnH and PbB were 11.48 μg/g (range: 0.52-55.74); 1.1 μg/dL (range: 0.5-6.1), respectively. Spearman correlation analyses showed that several behavioral indices were significantly correlated with MnH levels for girls, but not for boys: total externalizing behavior (rho=0.484 vs rho=0.041) and attention problem scores (rho=0.542 vs rho=0.003) coefficients were significantly at p<0.001 level, respectively for girls and boys. No significant correlation was observed with any of the internalizing sub-scales. A linear regression model was fitted with the total externalizing behavior, inattention and total CBCL scores as dependent variables, with log transformed MnH stratified by sex, adjusting for age and maternal IQ. Total externalizing behaviors and attention problem scores were significantly associated with girls' MnH levels but not with boys'. Adjusting for maternal IQ, the β-coefficients for LogMnH associations with total externalizing and attention problems are 8.85 (95%CI 2.44-15.24) and 4.03 (95%CI 1.50-6.56) for girls. For boys, after adjusting for age, the β-coefficients are 0.08 (95%CI 11.51-11.66) and -0.05 (95%CI 4.34-4.25), respectively. The findings of this study suggest a positive association between elevated Mn exposure and externalizing behavioral problems and inattention, with girls presenting more pronounced effects. Future studies on Mn exposure in children should attempt to further elucidate sex and/or gender differences in Mn exposed populations. Copyright © 2013 Elsevier Inc. All rights reserved.

Estimating forest crown area removed by selection cutting: a linked regression-GIS approach based on stump diameters

USGS Publications Warehouse

Anderson, S.C.; Kupfer, J.A.; Wilson, R.R.; Cooper, R.J.

2000-01-01

The purpose of this research was to develop a model that could be used to provide a spatial representation of uneven-aged silvicultural treatments on forest crown area. We began by developing species-specific linear regression equations relating tree DBH to crown area for eight bottomland tree species at White River National Wildlife Refuge, Arkansas, USA. The relationships were highly significant for all species, with coefficients of determination (r(2)) ranging from 0.37 for Ulmus crassifolia to nearly 0.80 for Quercus nuttalliii and Taxodium distichum. We next located and measured the diameters of more than 4000 stumps from a single tree-group selection timber harvest. Stump locations were recorded with respect to an established gl id point system and entered into a Geographic Information System (ARC/INFO). The area occupied by the crown of each logged individual was then estimated by using the stump dimensions (adjusted to DBHs) and the regression equations relating tree DBH to crown area. Our model projected that the selection cuts removed roughly 300 m(2) of basal area from the logged sites resulting in the loss of approximate to 55 000 m(2) of crown area. The model developed in this research represents a tool that can be used in conjunction with remote sensing applications to assist in forest inventory and management, as well as to estimate the impacts of selective timber harvest on wildlife.

Racial and gender discrimination, early life factors, and chronic physical health conditions in midlife.

PubMed

McDonald, Jasmine A; Terry, Mary Beth; Tehranifar, Parisa

2014-01-01

Most studies of perceived discrimination have been cross-sectional and focused primarily on mental rather than physical health conditions. We examined the associations of perceived racial and gender discrimination reported in adulthood with early life factors and self-reported physician diagnosis of chronic physical health conditions. We used data from a racially diverse birth cohort of U.S. women (n = 168; average age, 41 years) with prospectively collected early life data (e.g., parental socioeconomic factors) and adult reported data on perceived discrimination, physical health conditions, and relevant risk factors. We performed modified robust Poisson regression owing to the high prevalence of the outcomes. Fifty percent of participants reported racial and 39% reported gender discrimination. Early life factors did not have strong associations with perceived discrimination. In adjusted regression models, participants reporting at least three experiences of gender or racial discrimination had a 38% increased risk of having at least one physical health condition (relative risk, 1.38; 95% confidence interval, 1.01-1.87). Using standardized regression coefficients, the magnitude of the association of having physical health condition(s) was larger for perceived discrimination than for being overweight or obese. Our results suggest a substantial chronic disease burden associated with perceived discrimination, which may exceed the impact of established risk factors for poor physical health. Copyright © 2014 Jacobs Institute of Women's Health. Published by Elsevier Inc. All rights reserved.

An empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models

USGS Publications Warehouse

Li, Ji; Gray, B.R.; Bates, D.M.

2008-01-01

Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.

Statistical summary of selected physical, chemical, and toxicity characteristics and estimates of annual constituent loads in urban stormwater, Maricopa County, Arizona

USGS Publications Warehouse

Fossum, Kenneth D.; O'Day, Christie M.; Wilson, Barbara J.; Monical, Jim E.

2001-01-01

Stormwater and streamflow in Maricopa County were monitored to (1) describe the physical, chemical, and toxicity characteristics of stormwater from areas having different land uses, (2) describe the physical, chemical, and toxicity characteristics of streamflow from areas that receive urban stormwater, and (3) estimate constituent loads in stormwater. Urban stormwater and streamflow had similar ranges in most constituent concentrations. The mean concentration of dissolved solids in urban stormwater was lower than in streamflow from the Salt River and Indian Bend Wash. Urban stormwater, however, had a greater chemical oxygen demand and higher concentrations of most nutrients. Mean seasonal loads and mean annual loads of 11 constituents and volumes of runoff were estimated for municipalities in the metropolitan Phoenix area, Arizona, by adjusting regional regression equations of loads. This adjustment procedure uses the original regional regression equation and additional explanatory variables that were not included in the original equation. The adjusted equations had standard errors that ranged from 161 to 196 percent. The large standard errors of the prediction result from the large variability of the constituent concentration data used in the regression analysis. Adjustment procedures produced unsatisfactory results for nine of the regressions?suspended solids, dissolved solids, total phosphorus, dissolved phosphorus, total recoverable cadmium, total recoverable copper, total recoverable lead, total recoverable zinc, and storm runoff. These equations had no consistent direction of bias and no other additional explanatory variables correlated with the observed loads. A stepwise-multiple regression or a three-variable regression (total storm rainfall, drainage area, and impervious area) and local data were used to develop local regression equations for these nine constituents. These equations had standard errors from 15 to 183 percent.

Access disparities to Magnet hospitals for patients undergoing neurosurgical operations

PubMed Central

Missios, Symeon; Bekelis, Kimon

2017-01-01

Background Centers of excellence focusing on quality improvement have demonstrated superior outcomes for a variety of surgical interventions. We investigated the presence of access disparities to hospitals recognized by the Magnet Recognition Program of the American Nurses Credentialing Center (ANCC) for patients undergoing neurosurgical operations. Methods We performed a cohort study of all neurosurgery patients who were registered in the New York Statewide Planning and Research Cooperative System (SPARCS) database from 2009–2013. We examined the association of African-American race and lack of insurance with Magnet status hospitalization for neurosurgical procedures. A mixed effects propensity adjusted multivariable regression analysis was used to control for confounding. Results During the study period, 190,535 neurosurgical patients met the inclusion criteria. Using a multivariable logistic regression, we demonstrate that African-Americans had lower admission rates to Magnet institutions (OR 0.62; 95% CI, 0.58–0.67). This persisted in a mixed effects logistic regression model (OR 0.77; 95% CI, 0.70–0.83) to adjust for clustering at the patient county level, and a propensity score adjusted logistic regression model (OR 0.75; 95% CI, 0.69–0.82). Additionally, lack of insurance was associated with lower admission rates to Magnet institutions (OR 0.71; 95% CI, 0.68–0.73), in a multivariable logistic regression model. This persisted in a mixed effects logistic regression model (OR 0.72; 95% CI, 0.69–0.74), and a propensity score adjusted logistic regression model (OR 0.72; 95% CI, 0.69–0.75). Conclusions Using a comprehensive all-payer cohort of neurosurgery patients in New York State we identified an association of African-American race and lack of insurance with lower rates of admission to Magnet hospitals. PMID:28684152

Interquantile Shrinkage in Regression Models

PubMed Central

Jiang, Liewen; Wang, Huixia Judy; Bondell, Howard D.

2012-01-01

Conventional analysis using quantile regression typically focuses on fitting the regression model at different quantiles separately. However, in situations where the quantile coefficients share some common feature, joint modeling of multiple quantiles to accommodate the commonality often leads to more efficient estimation. One example of common features is that a predictor may have a constant effect over one region of quantile levels but varying effects in other regions. To automatically perform estimation and detection of the interquantile commonality, we develop two penalization methods. When the quantile slope coefficients indeed do not change across quantile levels, the proposed methods will shrink the slopes towards constant and thus improve the estimation efficiency. We establish the oracle properties of the two proposed penalization methods. Through numerical investigations, we demonstrate that the proposed methods lead to estimations with competitive or higher efficiency than the standard quantile regression estimation in finite samples. Supplemental materials for the article are available online. PMID:24363546

Associations of advanced glycation end-products with cognitive functions in individuals with and without type 2 diabetes: the maastricht study.

PubMed

Spauwen, P J J; van Eupen, M G A; Köhler, S; Stehouwer, C D A; Verhey, F R J; van der Kallen, C J H; Sep, S J S; Koster, A; Schaper, N C; Dagnelie, P C; Schalkwijk, C G; Schram, M T; van Boxtel, M P J

2015-03-01

Advanced glycation end-products (AGEs) are thought to be involved in the pathogenesis of Alzheimer's disease. AGEs are products resulting from nonenzymatic chemical reactions between reduced sugars and proteins, which accumulate during natural aging, and their accumulation is accelerated in hyperglycemic conditions such as type 2 diabetes mellitus. The objective of the study was to examine associations between AGEs and cognitive functions. This study was performed as part of the Maastricht Study, a population-based cohort study in which, by design, 215 participants (28.1%) had type 2 diabetes mellitus. We examined associations of skin autofluorescence (SAF) (n = 764), an overall estimate of skin AGEs, and specific plasma protein-bound AGEs (n = 781) with performance on tests for global cognitive functioning, information processing speed, verbal memory (immediate and delayed word recall), and response inhibition. After adjustment for demographics, diabetes, smoking, alcohol, waist circumference, total cholesterol/high-density lipoprotein cholesterol ratio, triglycerides, and lipid-lowering medication use, higher SAF was significantly associated with worse delayed word recall (regression coefficient, b = -0.44; P = .04), and response inhibition (b = 0.03; P = .04). After further adjustment for systolic blood pressure, cardiovascular disease, estimated glomerular filtration rate, and depression, associations were attenuated (delayed word recall, b = -0.38, P = .07; response inhibition, b = 0.02, P = .07). Higher pentosidine levels were associated with worse global cognitive functioning (b = -0.61; P = .04) after full adjustment, but other plasma AGEs were not. Associations did not differ between individuals with and without diabetes. We found inverse associations of SAF (a noninvasive marker for tissue AGEs) with cognitive performance, which were attenuated after adjustment for vascular risk factors and depression.

Insulin Sensitivity Measured With Euglycemic Clamp Is Independently Associated With Glomerular Filtration Rate in a Community-Based Cohort

PubMed Central

Nerpin, Elisabet; Risérus, Ulf; Ingelsson, Erik; Sundström, Johan; Jobs, Magnus; Larsson, Anders; Basu, Samar; Ärnlöv, Johan

2008-01-01

OBJECTIVE—To investigate the association between insulin sensitivity and glomerular filtration rate (GFR) in the community, with prespecified subgroup analyses in normoglycemic individuals with normal GFR. RESEARCH DESIGN AND METHODS—We investigated the cross-sectional association between insulin sensitivity (M/I, assessed using euglycemic clamp) and cystatin C–based GFR in a community-based cohort of elderly men (Uppsala Longitudinal Study of Adult Men [ULSAM], n = 1,070). We also investigated whether insulin sensitivity predicted the incidence of renal dysfunction at a follow-up examination after 7 years. RESULTS—Insulin sensitivity was directly related to GFR (multivariable-adjusted regression coefficient for 1-unit higher M/I 1.19 [95% CI 0.69–1.68]; P < 0.001) after adjusting for age, glucometabolic variables (fasting plasma glucose, fasting plasma insulin, and 2-h glucose after an oral glucose tolerance test), cardiovascular risk factors (hypertension, dyslipidemia, and smoking), and lifestyle factors (BMI, physical activity, and consumption of tea, coffee, and alcohol). The positive multivariable-adjusted association between insulin sensitivity and GFR also remained statistically significant in participants with normal fasting plasma glucose, normal glucose tolerance, and normal GFR (n = 443; P < 0.02). In longitudinal analyses, higher insulin sensitivity at baseline was associated with lower risk of impaired renal function (GFR <50 ml/min per 1.73 m2) during follow-up independently of glucometabolic variables (multivariable-adjusted odds ratio for 1-unit higher of M/I 0.58 [95% CI 0.40–0.84]; P < 0.004). CONCLUSIONS—Our data suggest that impaired insulin sensitivity may be involved in the development of renal dysfunction at an early stage, before the onset of diabetes or prediabetic glucose elevations. Further studies are needed in order to establish causality. PMID:18509205

Right mini-parasternotomy may be a good minimally invasive alternative to full sternotomy for cardiac valve operations-a propensity-adjusted analysis.

PubMed

Chiu, K M; Chen, R J; Lin, T Y; Chen, J S; Huang, J H; Huang, C Y; Chu, S H

2014-03-26

Limited realworld data existed for miniparasternotomy approach with good sample size in Asian cohorts and most previous studies were eclipsed by case heterogeneity. The goal of this study was to compare safety and quality outcomes of cardiac noncoronary valve operations by miniparasternotomy and full sternotomy approaches on riskadjusted basis. From our hospital database, we retrieved the cases of non-coronary valve operations from 1 January 2005 to 31 December 2012, including re-do, emergent, and combined procedures. Estimated EuroScore-II and propensity score for choosing mini-parasternotomy were adjusted for in the regression models on hospital mortality, complications (pneumonia, stroke, sepsis, etc.), and quality parameters (length of stay, ICU time, ventilator time, etc.). Non-complicated cases, defined as survival to discharge, ventilator use not over one week, and intensive care unit stay not over two weeks, were used for quality parameters. There were 283 miniparasternotomy and 177 full sternotomy cases. EuroScore-II differed significantly (medians 2.1 vs. 4.7, p<0.001). Propensity scores for choosing miniparasternotomy were higher with lower EuroScore-II (OR=0.91 per 1%, p<0.001), aortic regurgitation (OR=2.3, p=0.005), and aortic non-mitral valve disease (OR=3.9, p<0.001). Adjusted for propensity score and EuroScore-II, mini-parasternotomy group had less pneumonia (OR=0.32, p=0.043), less sepsis (OR=0.31, p=0.045), and shorter non-complicated length of stay (coefficient=7.2 (day), p<0.001) than full sternotomy group, whereas Kaplan-Meier survival, non-complicated ICU time, non-complicated ventilator time, and 30-day mortality did not differ significantly. The propensity-adjusted analysis demonstrated encouraging safety and quality outcomes for mini-parasternotomy valve operation in carefully selected patients.

Association of Marine Omega-3 Fatty Acid Levels With Telomeric Aging in Patients With Coronary Heart Disease

PubMed Central

Farzaneh-Far, Ramin; Lin, Jue; Epel, Elissa S.; Harris, William S.; Blackburn, Elizabeth H.; Whooley, Mary A.

2010-01-01

Context Increased dietary intake of marine omega-3 fatty acids is associated with prolonged survival in patients with coronary heart disease. However, the mechanisms underlying this protective effect are poorly understood. Objective To investigate the association of omega-3 fatty acid blood levels with temporal changes in telomere length, an emerging marker of biological age. Design, Setting, and Participants Prospective cohort study of 608 ambulatory outpatients in California with stable coronary artery disease recruited from the Heart and Soul Study between September 2000 and December 2002 and followed up to January 2009 (median, 6.0 years; range, 5.0-8.1 years). Main Outcome Measures We measured leukocyte telomere length at baseline and again after 5 years of follow-up. Multivariable linear and logistic regression models were used to investigate the association of baseline levels of omega-3 fatty acids (docosahexaenoic acid [DHA] and eicosapentaenoic acid [EPA]) with subsequent change in telomere length. Results Individuals in the lowest quartile of DHA3EPA experienced the fastest rate of telomere shortening (0.13 telomere-to-single-copy gene ratio [T/S] units over 5 years; 95% confidence interval [CI], 0.09-0.17), whereas those in the highest quartile experienced the slowest rate of telomere shortening (0.05 T/S units over 5 years; 95% CI, 0.02-0.08; P<.001 for linear trend across quartiles). Levels of DHA+EPA were associated with less telomere shortening before (unadjusted β coefficient × 10−3=0.06; 95% CI, 0.02-0.10) and after (adjusted β coefficient × 10−3=0.05; 95% CI, 0.01-0.08) sequential adjustment for established risk factors and potential confounders. Each 1-SD increase in DHA+EPA levels was associated with a 32% reduction in the odds of telomere shortening (adjusted odds ratio, 0.68; 95% CI, 0.47-0.98). Conclusion Among this cohort of patients with coronary artery disease, there was an inverse relationship between baseline blood levels of marine omega-3 fatty acids and the rate of telomere shortening over 5 years. PMID:20085953

Dietary benzo(a)pyrene intake during pregnancy and birth weight: associations modified by vitamin C intakes in the Norwegian Mother and Child Cohort Study (MoBa).

PubMed

Duarte-Salles, Talita; Mendez, Michelle A; Meltzer, Helle Margrete; Alexander, Jan; Haugen, Margaretha

2013-10-01

Maternal exposure to polycyclic aromatic hydrocarbons (PAH) during pregnancy has been associated with reduced fetal growth. However, the role of diet, the main source of PAH exposure among non-smokers, remains uncertain. To assess associations between maternal exposure to dietary intake of the genotoxic PAH benzo(a)pyrene [B(a)P] during pregnancy and birth weight, exploring potential effect modification by dietary intakes of vitamins C, E and A, hypothesized to influence PAH metabolism. This study included 50,651 women in the Norwegian Mother and Child Cohort Study (MoBa). Dietary B(a)P and nutrient intakes were estimated based on total consumption obtained from a food frequency questionnaire (FFQ) and estimated based on food composition data. Data on infant birth weight were obtained from the Medical Birth Registry of Norway (MBRN). Multivariate regression was used to assess associations between dietary B(a)P and birth weight, evaluating potential interactions with candidate nutrients. The multivariate-adjusted coefficient (95%CI) for birth weight associated with maternal energy-adjusted B(a)P intake was -20.5g (-31.1, -10.0) in women in the third compared with the first tertile of B(a)P intake. Results were similar after excluding smokers. Significant interactions were found between elevated intakes of vitamin C (>85mg/day) and dietary B(a)P during pregnancy for birth weight (P<0.05), but no interactions were found with other vitamins. The multivariate-adjusted coefficients (95%CI) for birth weight in women in the third compared with the first tertile of B(a)P intake were -44.4g (-76.5, -12.3) in the group with low vitamin C intakes vs. -17.6g (-29.0, -6.1) in the high vitamin C intake group. The results suggest that higher prenatal exposure to dietary B(a)P may reduce birth weight. Lowering maternal intake of B(a)P and increasing dietary vitamin C intake during pregnancy may help to reduce any adverse effects of B(a)P on birth weight. © 2013.

Remote sensing of PM2.5 from ground-based optical measurements

NASA Astrophysics Data System (ADS)

Li, S.; Joseph, E.; Min, Q.

2014-12-01

Remote sensing of particulate matter concentration with aerodynamic diameter smaller than 2.5 um(PM2.5) by using ground-based optical measurements of aerosols is investigated based on 6 years of hourly average measurements of aerosol optical properties, PM2.5, ceilometer backscatter coefficients and meteorological factors from Howard University Beltsville Campus facility (HUBC). The accuracy of quantitative retrieval of PM2.5 using aerosol optical depth (AOD) is limited due to changes in aerosol size distribution and vertical distribution. In this study, ceilometer backscatter coefficients are used to provide vertical information of aerosol. It is found that the PM2.5-AOD ratio can vary largely for different aerosol vertical distributions. The ratio is also sensitive to mode parameters of bimodal lognormal aerosol size distribution when the geometric mean radius for the fine mode is small. Using two Angstrom exponents calculated at three wavelengths of 415, 500, 860nm are found better representing aerosol size distributions than only using one Angstrom exponent. A regression model is proposed to assess the impacts of different factors on the retrieval of PM2.5. Compared to a simple linear regression model, the new model combining AOD and ceilometer backscatter can prominently improve the fitting of PM2.5. The contribution of further introducing Angstrom coefficients is apparent. Using combined measurements of AOD, ceilometer backscatter, Angstrom coefficients and meteorological parameters in the regression model can get a correlation coefficient of 0.79 between fitted and expected PM2.5.

Factors influencing psychosocial adjustment and quality of life in Parkinson patients and informal caregivers.

PubMed

Navarta-Sánchez, María Victoria; Senosiain García, Juana M; Riverol, Mario; Ursúa Sesma, María Eugenia; Díaz de Cerio Ayesa, Sara; Anaut Bravo, Sagrario; Caparrós Civera, Neus; Portillo, Mari Carmen

2016-08-01

The influence that social conditions and personal attitudes may have on the quality of life (QoL) of Parkinson's disease (PD) patients and informal caregivers does not receive enough attention in health care, as a result of it not being clearly identified, especially in informal caregivers. The aim of this study was to provide a comprehensive analysis of psychosocial adjustment and QoL determinants in PD patients and informal caregivers. Ninety-one PD patients and 83 caregivers participated in the study. Multiple regression analyses were performed including benefit finding, coping, disease severity and socio-demographic factors, in order to determine how these aspects influence the psychosocial adjustment and QoL in PD patients and caregivers. Regression models showed that severity of PD was the main predictor of psychosocial adjustment and QoL in patients. Nevertheless, multiple regression analyses also revealed that coping was a significant predictor of psychosocial adjustment in patients and caregivers. Furthermore, psychosocial adjustment was significantly related to QoL in patients and caregivers. Also, coping and benefit finding were predictors of QoL in caregivers but not in patients. Multidisciplinary interventions aimed at improving PD patients' QoL may have more effective outcomes if education about coping skills, and how these can help towards a positive psychosocial adjustment to illness, were included, and targeted not only at patients, but also at informal caregivers.

Using multilevel modeling to assess case-mix adjusters in consumer experience surveys in health care.

PubMed

Damman, Olga C; Stubbe, Janine H; Hendriks, Michelle; Arah, Onyebuchi A; Spreeuwenberg, Peter; Delnoij, Diana M J; Groenewegen, Peter P

2009-04-01

Ratings on the quality of healthcare from the consumer's perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for analyzing healthcare performance data, it has rarely been used to assess case-mix adjustment of such data. The purpose of this article is to investigate whether multilevel regression analysis is a useful tool to detect case-mix adjusters in consumer assessment of healthcare. We used data on 11,539 consumers from 27 Dutch health plans, which were collected using the Dutch Consumer Quality Index health plan instrument. We conducted multilevel regression analyses of consumers' responses nested within health plans to assess the effects of consumer characteristics on consumer experience. We compared our findings to the results of another methodology: the impact factor approach, which combines the predictive effect of each case-mix variable with its heterogeneity across health plans. Both multilevel regression and impact factor analyses showed that age and education were the most important case-mix adjusters for consumer experience and ratings of health plans. With the exception of age, case-mix adjustment had little impact on the ranking of health plans. On both theoretical and practical grounds, multilevel modeling is useful for adequate case-mix adjustment and analysis of performance ratings.

Unexpected inverse relationship between impaired glucose metabolism and lipoprotein-associated phospholipase A2 activity in patients with stable vascular disease.

PubMed

Mayer, Otto; Seidlerová, Jitka; Filipovský, Jan; Timoracká, Katarina; Bruthans, Jan; Vaněk, Jiří; Cerná, Lenka; Wohlfahrt, Peter; Renata, Cífková; Trefil, Ladislav

2014-07-01

Elevated lipoprotein-associated phospholipase A2 activity (aLp-PLA2) is associated with increased risk of cardiovascular events. In patients with stable atherovascular disease, we aimed to investigate whether impaired glucose metabolism might be associated with higher risk of elevated aLp-PLA2. We conducted a cross-sectional study in 825 stable patients after acute coronary syndrome, coronary revascularization or after first ischemic stroke (Czech part of EUROASPIRE III surveys). We measured aLp-PLA2 using diaDexus commercial kit. In multiple step-wise regression analysis, the aLp-PLA2 was significantly positively associated with male gender, current smoking, LDL cholesterol and metabolic syndrome and negatively with statin treatment, body mass index and LDL/apoB ratio. After adjustment for these confounders, we observed an inverse relationship between aLp-PLA2 and fasting glycemia [β coefficient -2.18 (p<0.0001)] or glycated hemoglobin A1c (HbA1c) [β coefficient -5.89 (p<0.0001)]. Moreover, we found a positive association between aLp-PLA2 and pancreatic β cell function [β coefficient +0.10 (p<0.0001)], but not with an insulin sensitivity. In present study, we cannot confirm any additive risk of impaired glucose metabolism in terms of increased activity of Lp-PLA2. On the contrary, presence of inadequately controlled diabetes mellitus was independently associated with lower risk of elevated aLp-PLA2 . Copyright © 2014 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Media violence exposure and physical aggression in fifth-grade children.

PubMed

Coker, Tumaini R; Elliott, Marc N; Schwebel, David C; Windle, Michael; Toomey, Sara L; Tortolero, Susan R; Hertz, Marci F; Peskin, Melissa F; Schuster, Mark A

2015-01-01

To examine the association of media violence exposure and physical aggression in fifth graders across 3 media types. We analyzed data from a population-based, cross-sectional survey of 5,147 fifth graders and their parents in 3 US metropolitan areas. We used multivariable linear regression and report partial correlation coefficients to examine associations between children's exposure to violence in television/film, video games, and music (reported time spent consuming media and reported frequency of violent content: physical fighting, hurting, shooting, or killing) and the Problem Behavior Frequency Scale. Child-reported media violence exposure was associated with physical aggression after multivariable adjustment for sociodemographics, family and community violence, and child mental health symptoms (partial correlation coefficients: TV, 0.17; video games, 0.15; music, 0.14). This association was significant and independent for television, video games, and music violence exposure in a model including all 3 media types (partial correlation coefficients: TV, 0.11; video games, 0.09; music, 0.09). There was a significant positive interaction between media time and media violence for video games and music but not for television. Effect sizes for the association of media violence exposure and physical aggression were greater in magnitude than for most of the other examined variables. The association between physical aggression and media violence exposure is robust and persistent; the strength of this association of media violence may be at least as important as that of other factors with physical aggression in children, such as neighborhood violence, home violence, child mental health, and male gender. Copyright © 2015 Academic Pediatric Association. All rights reserved.

A Developmental Sequence Model to University Adjustment of International Undergraduate Students

ERIC Educational Resources Information Center

Chavoshi, Saeid; Wintre, Maxine Gallander; Dentakos, Stella; Wright, Lorna

2017-01-01

The current study proposes a Developmental Sequence Model to University Adjustment and uses a multifaceted measure, including academic, social and psychological adjustment, to examine factors predictive of undergraduate international student adjustment. A hierarchic regression model is carried out on the Student Adaptation to College Questionnaire…

Spatially resolved regression analysis of pre-treatment FDG, FLT and Cu-ATSM PET from post-treatment FDG PET: an exploratory study

PubMed Central

Bowen, Stephen R; Chappell, Richard J; Bentzen, Søren M; Deveau, Michael A; Forrest, Lisa J; Jeraj, Robert

2012-01-01

Purpose To quantify associations between pre-radiotherapy and post-radiotherapy PET parameters via spatially resolved regression. Materials and methods Ten canine sinonasal cancer patients underwent PET/CT scans of [18F]FDG (FDGpre), [18F]FLT (FLTpre), and [61Cu]Cu-ATSM (Cu-ATSMpre). Following radiotherapy regimens of 50 Gy in 10 fractions, veterinary patients underwent FDG PET/CT scans at three months (FDGpost). Regression of standardized uptake values in baseline FDGpre, FLTpre and Cu-ATSMpre tumour voxels to those in FDGpost images was performed for linear, log-linear, generalized-linear and mixed-fit linear models. Goodness-of-fit in regression coefficients was assessed by R2. Hypothesis testing of coefficients over the patient population was performed. Results Multivariate linear model fits of FDGpre to FDGpost were significantly positive over the population (FDGpost~0.17 FDGpre, p=0.03), and classified slopes of RECIST non-responders and responders to be different (0.37 vs. 0.07, p=0.01). Generalized-linear model fits related FDGpre to FDGpost by a linear power law (FDGpost~FDGpre0.93, p<0.001). Univariate mixture model fits of FDGpre improved R2 from 0.17 to 0.52. Neither baseline FLT PET nor Cu-ATSM PET uptake contributed statistically significant multivariate regression coefficients. Conclusions Spatially resolved regression analysis indicates that pre-treatment FDG PET uptake is most strongly associated with three-month post-treatment FDG PET uptake in this patient population, though associations are histopathology-dependent. PMID:22682748

Bootstrap Methods: A Very Leisurely Look.

ERIC Educational Resources Information Center

Hinkle, Dennis E.; Winstead, Wayland H.

The Bootstrap method, a computer-intensive statistical method of estimation, is illustrated using a simple and efficient Statistical Analysis System (SAS) routine. The utility of the method for generating unknown parameters, including standard errors for simple statistics, regression coefficients, discriminant function coefficients, and factor…

Double-adjustment in propensity score matching analysis: choosing a threshold for considering residual imbalance.

PubMed

Nguyen, Tri-Long; Collins, Gary S; Spence, Jessica; Daurès, Jean-Pierre; Devereaux, P J; Landais, Paul; Le Manach, Yannick

2017-04-28

Double-adjustment can be used to remove confounding if imbalance exists after propensity score (PS) matching. However, it is not always possible to include all covariates in adjustment. We aimed to find the optimal imbalance threshold for entering covariates into regression. We conducted a series of Monte Carlo simulations on virtual populations of 5,000 subjects. We performed PS 1:1 nearest-neighbor matching on each sample. We calculated standardized mean differences across groups to detect any remaining imbalance in the matched samples. We examined 25 thresholds (from 0.01 to 0.25, stepwise 0.01) for considering residual imbalance. The treatment effect was estimated using logistic regression that contained only those covariates considered to be unbalanced by these thresholds. We showed that regression adjustment could dramatically remove residual confounding bias when it included all of the covariates with a standardized difference greater than 0.10. The additional benefit was negligible when we also adjusted for covariates with less imbalance. We found that the mean squared error of the estimates was minimized under the same conditions. If covariate balance is not achieved, we recommend reiterating PS modeling until standardized differences below 0.10 are achieved on most covariates. In case of remaining imbalance, a double adjustment might be worth considering.

Calculations of actual corneal astigmatism using total corneal refractive power before and after myopic keratorefractive surgery.

PubMed

Seo, Kyoung Yul; Yang, Hun; Kim, Wook Kyum; Nam, Sang Min

2017-01-01

To calculate actual corneal astigmatism using the total corneal refractive astigmatism for the 4-mm apex zone of the Pentacam (TCRP4astig) and keratometric astigmatism (Kastig) before and after photorefractive keratectomy or laser in situ keratomileusis. Uncomplicated 56 eyes after more than 6 months from the surgery were recruited by chart review. Various corneal astigmatisms were measured using the Pentacam and autokeratometer before and after surgery. Three eyes were excluded and 53 eyes of 38 subjects with with-the-rule astigmatism (WTR) were finally included. The astigmatisms were investigated using polar value analysis. When TCRP4astig was set as an actual astigmatism, the efficacy of arithmetic or coefficient adjustment of Kastig was evaluated using bivariate analysis. The difference between the simulated keratometer astigmatism of the Pentacam (SimKastig) and Kastig was strongly correlated with the difference between TCRP4astig and Kastig. TCRP4astig was different from Kastig in magnitude rather than meridian before and after surgery; the preoperative difference was due to the posterior cornea only; however, the postoperative difference was observed in both anterior and posterior parts. For arithmetic adjustment, 0.28 D and 0.27 D were subtracted from the preoperative and postoperative magnitudes of Kastig, respectively. For coefficient adjustment, the preoperative and postoperative magnitudes of Kastig were multiplied by 0.80 and 0.66, respectively. By arithmetic or coefficient adjustment, the difference between TCRP4astig and adjusted Kastig would be less than 0.75 D in magnitude for 95% of cases. Kastig was successfully adjusted to TCPR4astig before and after myopic keratorefractive surgery in cases of WTR. For use of TCRP4astig directly, SimKastig and Kastig should be matched.

Calculations of actual corneal astigmatism using total corneal refractive power before and after myopic keratorefractive surgery

PubMed Central

Seo, Kyoung Yul; Yang, Hun; Kim, Wook Kyum; Nam, Sang Min

2017-01-01

Purpose To calculate actual corneal astigmatism using the total corneal refractive astigmatism for the 4-mm apex zone of the Pentacam (TCRP4astig) and keratometric astigmatism (Kastig) before and after photorefractive keratectomy or laser in situ keratomileusis Methods Uncomplicated 56 eyes after more than 6 months from the surgery were recruited by chart review. Various corneal astigmatisms were measured using the Pentacam and autokeratometer before and after surgery. Three eyes were excluded and 53 eyes of 38 subjects with with-the-rule astigmatism (WTR) were finally included. The astigmatisms were investigated using polar value analysis. When TCRP4astig was set as an actual astigmatism, the efficacy of arithmetic or coefficient adjustment of Kastig was evaluated using bivariate analysis. Results The difference between the simulated keratometer astigmatism of the Pentacam (SimKastig) and Kastig was strongly correlated with the difference between TCRP4astig and Kastig. TCRP4astig was different from Kastig in magnitude rather than meridian before and after surgery; the preoperative difference was due to the posterior cornea only; however, the postoperative difference was observed in both anterior and posterior parts. For arithmetic adjustment, 0.28 D and 0.27 D were subtracted from the preoperative and postoperative magnitudes of Kastig, respectively. For coefficient adjustment, the preoperative and postoperative magnitudes of Kastig were multiplied by 0.80 and 0.66, respectively. By arithmetic or coefficient adjustment, the difference between TCRP4astig and adjusted Kastig would be less than 0.75 D in magnitude for 95% of cases. Conclusions Kastig was successfully adjusted to TCPR4astig before and after myopic keratorefractive surgery in cases of WTR. For use of TCRP4astig directly, SimKastig and Kastig should be matched. PMID:28403194

DOE Office of Scientific and Technical Information (OSTI.GOV)

Dierauf, Timothy; Kurtz, Sarah; Riley, Evan

This paper provides a recommended method for evaluating the AC capacity of a photovoltaic (PV) generating station. It also presents companion guidance on setting the facilitys capacity guarantee value. This is a principles-based approach that incorporates plant fundamental design parameters such as loss factors, module coefficients, and inverter constraints. This method has been used to prove contract guarantees for over 700 MW of installed projects. The method is transparent, and the results are deterministic. In contrast, current industry practices incorporate statistical regression where the empirical coefficients may only characterize the collected data. Though these methods may work well when extrapolationmore » is not required, there are other situations where the empirical coefficients may not adequately model actual performance.This proposed Fundamentals Approach method provides consistent results even where regression methods start to lose fidelity.« less

Cross-sectional study of variables associated with length of stay and ICU need in open Roux-En-Y gastric bypass surgery for morbid obese patients: an exploratory analysis based on the Public Health System administrative database (Datasus) in Brazil.

PubMed

Asano, Elio Fernando; Rasera, Irineu; Shiraga, Elisabete Cristina

2012-12-01

This is an exploratory analysis of potential variables associated with open Roux-en-Y gastric bypass (RYGB) surgery hospitalization resource use pattern. Cross-sectional study based on an administrative database (DATASUS) records. Inclusion criteria were adult patients undergoing RYGB between Jan/2008 and Jun/2011. Dependent variables were length of stay (LoS) and ICU need. Independent variables were: gender, age, region, hospital volume, surgery at certified center of excellence (CoE) by the Surgical Review Corporation (SRC), teaching hospital, and year of hospitalization. Univariate and multivariate analysis (logistic regression for ICU need and linear regression for length of stay) were performed. Data from 13,069 surgeries were analyzed. In crude analysis, hospital volume was the most impactful variable associated with log-transformed LoS (1.312 ± 0.302 high volume vs. 1.670 ± 0.581 low volume, p < 0.001), whereas for ICU need it was certified CoE (odds ratio (OR), 0.016; 95% confidence interval (CI), 0.010-0.026). After adjustment by logistic regression, certified CoE remained as the strongest predictor of ICU need (OR, 0.011; 95% CI, 0.007-0.018), followed by hospital volume (OR, 3.096; 95% CI, 2.861-3.350). Age group, male gender, and teaching hospital were also significantly associated (p < 0.001). For log-transformed LoS, final model includes hospital volume (coefficient, -0.223; 95% CI, -0.250 to -0.196) and teaching hospital (coefficient, 0.375; 95% CI, 0.351-0.398). Region of Brazil was not associated with any of the outcomes. High-volume hospital was the strongest predictor for shorter LoS, whereas SRC certification was the strongest predictor of lower ICU need. Public health policies targeting an increase of efficiency and patient access to the procedure should take into account these results.

Society of Thoracic Surgeons Risk Score predicts hospital charges and resource use after aortic valve replacement.

PubMed

Arnaoutakis, George J; George, Timothy J; Alejo, Diane E; Merlo, Christian A; Baumgartner, William A; Cameron, Duke E; Shah, Ashish S

2011-09-01

The impact of Society of Thoracic Surgeons predicted mortality risk score on resource use has not been previously studied. We hypothesize that increasing Society of Thoracic Surgeons risk scores in patients undergoing aortic valve replacement are associated with greater hospital charges. Clinical and financial data for patients undergoing aortic valve replacement at The Johns Hopkins Hospital over a 10-year period (January 2000 to December 2009) were reviewed. The current Society of Thoracic Surgeons formula (v2.61) for in-hospital mortality was used for all patients. After stratification into risk quartiles, index admission hospital charges were compared across risk strata with rank-sum and Kruskal-Wallis tests. Linear regression and Spearman's coefficient assessed correlation and goodness of fit. Multivariable analysis assessed relative contributions of individual variables on overall charges. A total of 553 patients underwent aortic valve replacement during the study period. Average predicted mortality was 2.9% (±3.4) and actual mortality was 3.4% for aortic valve replacement. Median charges were greater in the upper quartile of patients undergoing aortic valve replacement (quartiles 1-3, $39,949 [interquartile range, 32,708-51,323] vs quartile 4, $62,301 [interquartile range, 45,952-97,103], P < .01]. On univariate linear regression, there was a positive correlation between Society of Thoracic Surgeons risk score and log-transformed charges (coefficient, 0.06; 95% confidence interval, 0.05-0.07; P < .01). Spearman's correlation R-value was 0.51. This positive correlation persisted in risk-adjusted multivariable linear regression. Each 1% increase in Society of Thoracic Surgeons risk score was associated with an added $3000 in hospital charges. This is the first study to show that increasing Society of Thoracic Surgeons risk score predicts greater charges after aortic valve replacement. As competing therapies, such as percutaneous valve replacement, emerge to treat high-risk patients, these results serve as a benchmark to compare resource use. Copyright © 2011 The American Association for Thoracic Surgery. Published by Mosby, Inc. All rights reserved.

Ready-to-use supplementary food increases fat mass and BMI in Haitian school-aged children.

PubMed

Iannotti, Lora L; Henretty, Nicole M; Delnatus, Jacques Raymond; Previl, Windy; Stehl, Tom; Vorkoper, Susan; Bodden, Jaime; Maust, Amanda; Smidt, Rachel; Nash, Marilyn L; Tamimie, Courtney A; Owen, Bridget C; Wolff, Patricia B

2015-04-01

In Haiti and other countries, large-scale investments in school feeding programs have been made with marginal evidence of nutrition outcomes. We aimed to examine the effectiveness of a fortified ready-to-use supplementary food (RUSF), Mamba, on reduced anemia and improved body composition in school-aged children compared to an unfortified cereal bar, Tablet Yo, and control groups. A cluster, randomized trial with children ages 3-13 y (n = 1167) was conducted in the north of Haiti. Six schools were matched and randomized to the control group, Tablet Yo group (42 g, 165 kcal), or Mamba group (50 g, 260 kcal, and >75% of the RDA for critical micronutrients). Children in the supplementation groups received the snack daily for 100 d, and all were followed longitudinally for hemoglobin concentrations, anthropometry, and bioelectrical impedance measures: baseline (December 2012), midline (March 2013), and endline (June 2013). Parent surveys were conducted at baseline and endline to examine secondary outcomes of morbidities and dietary intakes. Longitudinal regression modeling using generalized least squares and logit with random effects tested the main effects. At baseline,14.0% of children were stunted, 14.5% underweight, 9.1% thin, and 73% anemic. Fat mass percentage (mean ± SD) was 8.1% ± 4.3% for boys and 12.5% ± 4.4% for girls. In longitudinal modeling, Mamba supplementation increased body mass index z score (regression coefficient ± SEE) 0.25 ± 0.06, fat mass 0.45 ± 0.14 kg, and percentage fat mass 1.28% ± 0.27% compared with control at each time point (P < 0.001). Among boys, Mamba increased fat mass (regression coefficient ± SEE) 0.73 ± 0.19 kg and fat-free mass 0.62 ± 0.34 kg compared with control (P < 0.001). Mamba reduced the odds of developing anemia by 28% compared to control (adjusted OR: 0.72; 95% CI: 0.57, 0.91; P < 0.001). No treatment effect was found for hemoglobin concentration. To our knowledge, this is the first study to give evidence of body composition effects from an RUSF in school-aged children. © 2015 American Society for Nutrition.

Knowledge, Perceptions, and Self-reported Performance of Hand Hygiene Among Registered Nurses at Community-based Hospitals in the Republic of Korea: A Cross-sectional Multi-center Study.

PubMed

Oh, Hyang Soon

2018-05-01

To assess the nurses' hand hygiene (HH) knowledge, perception, attitude, and self-reported performance in small- and medium-sized hospitals after Middle East Respiratory Syndrome outbreak. The structured questionnaire was adapted from the World Health Organization's survey. Data were collected between June 26 and July 14, 2017. Nurses showed scores on knowledge (17.6±2.5), perception (69.3±0.8), self-reported HH performance of non-self (86.0±11.0), self-reported performance of self (88.2±11.0), and attitude (50.5±5.5). HH performance rate of non-self was Y 1 =36.678+ 0.555X1 (HH performance rate of self) (adjusted R 2 =0.280, p <0.001). The regression model for performance was Y 4 =18.302+0.247 X 41 (peception)+0.232 X 42 (attitude)+0.875 X 42 (role model); coefficients were significant statistically except attitude, and this model significant statistically (adjusted R 2 =0.191, p <0.001). Advanced HH education program would be developed and operated continuously. Perception, attitude, role model was found to be a significant predictors of HH performance of self. So these findings could be used in future HH promotion strategies for nurses.

A New Test of Linear Hypotheses in OLS Regression under Heteroscedasticity of Unknown Form

ERIC Educational Resources Information Center

Cai, Li; Hayes, Andrew F.

2008-01-01

When the errors in an ordinary least squares (OLS) regression model are heteroscedastic, hypothesis tests involving the regression coefficients can have Type I error rates that are far from the nominal significance level. Asymptotically, this problem can be rectified with the use of a heteroscedasticity-consistent covariance matrix (HCCM)…

[Long-term outcome analysis of subjective and objective parameters after breast reduction in 159 cases: Patients judge differently from plastic surgeons].

PubMed

Osinga, Rik; Babst, Doris; Bodmer, Elvira S; Link, Bjoern C; Fritsche, Elmar; Hug, Urs

2017-12-01

This work assessed both subjective and objective postoperative parameters after breast reduction surgery and compared between patients and plastic surgeons. After an average postoperative observation period of 6.7 ± 2.7 (2 - 13) years, 159 out of 259 patients (61 %) were examined. The mean age at the time of surgery was 37 ± 14 (15 - 74) years. The postoperative anatomy of the breast and other anthropometric parameters were measured in cm with the patient in an upright position. The visual analogue scale (VAS) values for symmetry, size, shape, type of scar and overall satisfaction both from the patient's and from four plastic surgeons' perspectives were assessed and compared. Patients rated the postoperative result significantly better than surgeons. Good subjective ratings by patients for shape, symmetry and sensitivity correlated with high scores for overall assessment. Shape had the strongest influence on overall satisfaction (regression coefficient 0.357; p < 0.001), followed by symmetry (regression coefficient 0.239; p < 0.001) and sensitivity (regression coefficient 0.109; p = 0.040) of the breast. The better the subjective rating for symmetry by the patient, the smaller the measured difference of the jugulum-mamillary distance between left and right (regression coefficient -0.773; p = 0.002) and the smaller the difference in height of the lowest part of the breast between left and right (regression coefficient -0.465; p = 0.035). There was no significant correlation between age, weight, height, BMI, resected weight of the breast, postoperative breast size or type of scar with overall satisfaction. After breast reduction surgery, long-term outcome is rated significantly better by patients than by plastic surgeons. Good subjective ratings by patients for shape, symmetry and sensitivity correlated with high scores for overall assessment. Shape had the strongest influence on overall satisfaction, followed by symmetry and sensitivity of the breast. Postoperative size of the breast, resection weight, type of scar, age or BMI was not of significant influence. Symmetry was the only assessed subjective parameter of this study that could be objectified by postoperative measurements. Georg Thieme Verlag KG Stuttgart · New York.

Comparison of regression models for estimation of isometric wrist joint torques using surface electromyography

PubMed Central

2011-01-01

Background Several regression models have been proposed for estimation of isometric joint torque using surface electromyography (SEMG) signals. Common issues related to torque estimation models are degradation of model accuracy with passage of time, electrode displacement, and alteration of limb posture. This work compares the performance of the most commonly used regression models under these circumstances, in order to assist researchers with identifying the most appropriate model for a specific biomedical application. Methods Eleven healthy volunteers participated in this study. A custom-built rig, equipped with a torque sensor, was used to measure isometric torque as each volunteer flexed and extended his wrist. SEMG signals from eight forearm muscles, in addition to wrist joint torque data were gathered during the experiment. Additional data were gathered one hour and twenty-four hours following the completion of the first data gathering session, for the purpose of evaluating the effects of passage of time and electrode displacement on accuracy of models. Acquired SEMG signals were filtered, rectified, normalized and then fed to models for training. Results It was shown that mean adjusted coefficient of determination (Ra2) values decrease between 20%-35% for different models after one hour while altering arm posture decreased mean Ra2 values between 64% to 74% for different models. Conclusions Model estimation accuracy drops significantly with passage of time, electrode displacement, and alteration of limb posture. Therefore model retraining is crucial for preserving estimation accuracy. Data resampling can significantly reduce model training time without losing estimation accuracy. Among the models compared, ordinary least squares linear regression model (OLS) was shown to have high isometric torque estimation accuracy combined with very short training times. PMID:21943179

Does Serum Homocysteine Explain the Connection Between Sexual Frequency and Cardiovascular Risk?

PubMed

Yang, Hui-Fang; Kao, Tung-Wei; Lin, Yuan-Yung; Shih, Mu-Tsun; Wu, Li-Wei; Liaw, Fang-Yih; Peng, Tao-Chun; Chen, Wei-Liang

2017-07-01

Sexual activity correlates with various health issues, and homocysteine is considered an independent risk factor for cardiovascular events and atherosclerosis. Research on the relation of sexual activity to sexual frequency and homocysteine is sparse. To examine the association between sexual frequency and homocysteine in the general population in the United States. In total, 2,267 eligible participants 20 to 59 years old who had serum homocysteine data and completed a sexual behavior questionnaire were enrolled from the National Health and Nutrition Examination Survey of 2005 to 2006. The correlation between sexual frequency and serum homocysteine levels was analyzed using a linear regression model and an extended-model approach was performed for covariate adjustment. Individuals, especially men, in the lower quartiles of sexual frequency had significantly higher serum homocysteine levels, and a sex difference was identified in subgroup analysis. In a model of quartile-based analysis after adjustment for age, sex, and race and ethnicity, the regression coefficient of the highest quartile of sexual frequency compared with the lowest quartile was -1.326 (P = .012). After further adjustment for multiple covariates, the inverse association between sexual frequency and serum homocysteine levels remained unchanged. Negative trends maintained statistical significance (P for trend < .05). In subgroup analysis by sex, a negative association between sexual frequency and serum homocysteine levels remained unchanged in men even after adjusting for multiple covariates, but not in women. Clinical physicians in primary care should support patients' sexual activity, and there are implications for health promotion programs. This is the first observational investigation stratified by sex to evaluate the correlation between sexual frequency and serum homocysteine levels. The study was a cross-sectional observational investigation and the causal relation should be evaluated in a follow-up study. Decreased sexual frequency correlated with higher homocysteine levels in a nationally representative sample of US adults, especially men; this might increase the risk of cardiovascular disease or other atherothrombotic events. Yang H-F, Kao T-W, Lin Y-Y, et al. Does Serum Homocysteine Explain the Connection Between Sexual Frequency and Cardiovascular Risk? J Sex Med 2017;14:910-917. Copyright © 2017 International Society for Sexual Medicine. Published by Elsevier Inc. All rights reserved.

The Staff Observation Aggression Scale - Revised (SOAS-R) - adjustment and validation for emergency primary health care.

PubMed

Morken, Tone; Baste, Valborg; Johnsen, Grethe E; Rypdal, Knut; Palmstierna, Tom; Johansen, Ingrid Hjulstad

2018-05-08

Many emergency primary health care workers experience aggressive behaviour from patients or visitors. Simple incident-reporting procedures exist for inpatient, psychiatric care, but a similar and simple incident-report for other health care settings is lacking. The aim was to adjust a pre-existing form for reporting aggressive incidents in a psychiatric inpatient setting to the emergency primary health care settings. We also wanted to assess the validity of the severity scores in emergency primary health care. The Staff Observation Scale - Revised (SOAS-R) was adjusted to create a pilot version of the Staff Observation Scale - Revised Emergency (SOAS-RE). A Visual Analogue Scale (VAS) was added to the form to judge the severity of the incident. Data for validation of the pilot version of SOAS-RE were collected from ten casualty clinics in Norway during 12 months. Variance analysis was used to test gender and age differences. Linear regression analysis was performed to evaluate the relative impact that each of the five SOAS-RE columns had on the VAS score. The association between SOAS-RE severity score and VAS severity score was calculated by the Pearson correlation coefficient. The SOAS-R was adjusted to emergency primary health care, refined and called The Staff Observation Aggression Scale - Revised Emergency (SOAS-RE). A total of 350 SOAS-RE forms were collected from the casualty clinics, but due to missing data, 291 forms were included in the analysis. SOAS-RE scores ranged from 1 to 22. The mean total severity score of SOAS-RE was 10.0 (standard deviation (SD) =4.1) and the mean VAS score was 45.4 (SD = 26.7). We found a significant correlation of 0.45 between the SOAS-RE total severity scores and the VAS severity ratings. The linear regression analysis showed that individually each of the categories, which described the incident, had a low impact on the VAS score. The SOAS-RE seems to be a useful instrument for research, incident-recording and management of incidents in emergency primary care. The moderate correlation between SOAS-RE severity score and the VAS severity score shows that application of both the severity ratings is valuable to follow-up of workers affected by workplace violence.

Belief in complementary and alternative medicine is related to age and paranormal beliefs in adults.

PubMed

Van den Bulck, Jan; Custers, Kathleen

2010-04-01

The use of complementary and alternative medicine (CAM) is widespread, even among people who use conventional medicine. Positive beliefs about CAM are common among physicians and medical students. Little is known about the beliefs regarding CAM among the general public. Among science students, belief in CAM was predicted by belief in the paranormal. In a cross-sectional study, 712 randomly selected adults (>18 years old) responded to the CAM Health Belief Questionnaire (CHBQ) and a paranormal beliefs scale. CAM beliefs were very prevalent in this sample of adult Flemish men and women. Zero-order correlations indicated that belief in CAM was associated with age (r = 0.173 P < 0.001) level of education (r = -0.079 P = 0.039) social desirability (r = -0.119 P = 0.002) and paranormal belief (r = 0.365 P < 0.001). In a multivariate model, two variables predicted CAM beliefs. Support for CAM increased with age (regression coefficient: 0.01; 95% confidence interval (CI): 0.006 to 0.014), but the strongest relationship existed between support for CAM and beliefs in the paranormal. Paranormal beliefs accounted for 14% of the variance of the CAM beliefs (regression coefficient: 0.376; 95%: CI 0.30-0.44). The level of education (regression coefficient: 0.06; 95% CI: -0.014-0.129) and social desirability (regression coefficient: -0.023; 95% CI: -0.048-0.026) did not make a significant contribution to the explained variance (<0.1%, P = 0.867). Support of CAM was very prevalent in this Flemish adult population. CAM beliefs were strongly associated with paranormal beliefs.

Tidal Influence on Water Quality of Kapuas Kecil River Downstream

NASA Astrophysics Data System (ADS)

Purnaini, Rizki; Sudarmadji; Purwono, Suryo

2018-02-01

The Kapuas Kecil River is strongly influenced by tidal, in the dry season the intrusion of surface water is often a problem for the WTP because it causes the change of raw water quality to be processed. The purpose of this study was to examine the effect of sea tides on water quality of the Kapuas Kecil River. The study was conducted in Kapuas River downstream along ± 30 km from the upper boundary to the estuary. Water sampling is carried out during the dry and rainy season, when the tidal conditions at 7 (seven) locations of the monitoring station. Descriptive analysis methods and regression-correlation statistics are used to determine the effect of tides on water quality in Kapuas River downstream. In general, the water quality of the Kapuas Kecil River has exceeded the criteria of first class water quality, ie water that can be used for drinking water. The status of water quality of the Kapuas Kecil River based on the pollution index calculation shows the condition of the river is "mild to medium pollutants". The result of multiple linear regression analysis got the value of coefficient of determination (adjusted R square) = 0,760, which in whole show that independent variable (tidal and distance) influence to dependent variable (value of TDS) equal to 76%.

Comparison of Subjective Refraction under Binocular and Monocular Conditions in Myopic Subjects.

PubMed

Kobashi, Hidenaga; Kamiya, Kazutaka; Handa, Tomoya; Ando, Wakako; Kawamorita, Takushi; Igarashi, Akihito; Shimizu, Kimiya

2015-07-28

To compare subjective refraction under binocular and monocular conditions, and to investigate the clinical factors affecting the difference in spherical refraction between the two conditions. We examined thirty eyes of 30 healthy subjects. Binocular and monocular refraction without cycloplegia was measured through circular polarizing lenses in both eyes, using the Landolt-C chart of the 3D visual function trainer-ORTe. Stepwise multiple regression analysis was used to assess the relations among several pairs of variables and the difference in spherical refraction in binocular and monocular conditions. Subjective spherical refraction in the monocular condition was significantly more myopic than that in the binocular condition (p < 0.001), whereas no significant differences were seen in subjective cylindrical refraction (p = 0.99). The explanatory variable relevant to the difference in spherical refraction between binocular and monocular conditions was the binocular spherical refraction (p = 0.032, partial regression coefficient B = 0.029) (adjusted R(2) = 0.230). No significant correlation was seen with other clinical factors. Subjective spherical refraction in the monocular condition was significantly more myopic than that in the binocular condition. Eyes with higher degrees of myopia are more predisposed to show the large difference in spherical refraction between these two conditions.

Comparison of Subjective Refraction under Binocular and Monocular Conditions in Myopic Subjects

PubMed Central

Kobashi, Hidenaga; Kamiya, Kazutaka; Handa, Tomoya; Ando, Wakako; Kawamorita, Takushi; Igarashi, Akihito; Shimizu, Kimiya

2015-01-01

To compare subjective refraction under binocular and monocular conditions, and to investigate the clinical factors affecting the difference in spherical refraction between the two conditions. We examined thirty eyes of 30 healthy subjects. Binocular and monocular refraction without cycloplegia was measured through circular polarizing lenses in both eyes, using the Landolt-C chart of the 3D visual function trainer-ORTe. Stepwise multiple regression analysis was used to assess the relations among several pairs of variables and the difference in spherical refraction in binocular and monocular conditions. Subjective spherical refraction in the monocular condition was significantly more myopic than that in the binocular condition (p < 0.001), whereas no significant differences were seen in subjective cylindrical refraction (p = 0.99). The explanatory variable relevant to the difference in spherical refraction between binocular and monocular conditions was the binocular spherical refraction (p = 0.032, partial regression coefficient B = 0.029) (adjusted R2 = 0.230). No significant correlation was seen with other clinical factors. Subjective spherical refraction in the monocular condition was significantly more myopic than that in the binocular condition. Eyes with higher degrees of myopia are more predisposed to show the large difference in spherical refraction between these two conditions. PMID:26218972

Is maternal nutrition knowledge more strongly associated with the diets of mothers or their school-aged children?

PubMed

Williams, Lauren; Campbell, Karen; Abbott, Gavin; Crawford, David; Ball, Kylie

2012-08-01

Maternal nutrition knowledge has frequently been identified as an important target for nutrition promotion interventions. The aim of the present study was to investigate whether maternal nutrition knowledge is more strongly associated with the mother's own diet or that of her child. Cross-sectional multivariate linear regression with interactions analyses of survey data. Socio-economically disadvantaged neighbourhoods in Victoria, Australia. Five hundred and twenty-three mothers and their children who participated in the Resilience for Eating and Physical Activity Despite Inequality (READI) study, a cross-sectional survey study conducted in 2009 among women and their children residing in socio-economically disadvantaged neighbourhoods. In adjusted models, for three (vegetable, chocolate/lollies and soft drink consumption) out of the seven dietary outcomes assessed, there was a significant association between maternal nutrition knowledge and maternal diet, whereas for the children's diets none of the seven outcomes were associated with maternal nutrition knowledge. Statistical comparison of regression coefficients showed no difference between the maternal nutrition knowledge-maternal diet association and the maternal nutrition knowledge-child diet association. Promoting maternal nutrition knowledge may represent an important avenue for improving diet in mothers from socio-economically disadvantaged neighbourhoods, but more information is needed on how and when this knowledge is translated to benefits for their children's diet.

Regression Analysis of Optical Coherence Tomography Disc Variables for Glaucoma Diagnosis.

PubMed

Richter, Grace M; Zhang, Xinbo; Tan, Ou; Francis, Brian A; Chopra, Vikas; Greenfield, David S; Varma, Rohit; Schuman, Joel S; Huang, David

2016-08-01

To report diagnostic accuracy of optical coherence tomography (OCT) disc variables using both time-domain (TD) and Fourier-domain (FD) OCT, and to improve the use of OCT disc variable measurements for glaucoma diagnosis through regression analyses that adjust for optic disc size and axial length-based magnification error. Observational, cross-sectional. In total, 180 normal eyes of 112 participants and 180 eyes of 138 participants with perimetric glaucoma from the Advanced Imaging for Glaucoma Study. Diagnostic variables evaluated from TD-OCT and FD-OCT were: disc area, rim area, rim volume, optic nerve head volume, vertical cup-to-disc ratio (CDR), and horizontal CDR. These were compared with overall retinal nerve fiber layer thickness and ganglion cell complex. Regression analyses were performed that corrected for optic disc size and axial length. Area-under-receiver-operating curves (AUROC) were used to assess diagnostic accuracy before and after the adjustments. An index based on multiple logistic regression that combined optic disc variables with axial length was also explored with the aim of improving diagnostic accuracy of disc variables. Comparison of diagnostic accuracy of disc variables, as measured by AUROC. The unadjusted disc variables with the highest diagnostic accuracies were: rim volume for TD-OCT (AUROC=0.864) and vertical CDR (AUROC=0.874) for FD-OCT. Magnification correction significantly worsened diagnostic accuracy for rim variables, and while optic disc size adjustments partially restored diagnostic accuracy, the adjusted AUROCs were still lower. Axial length adjustments to disc variables in the form of multiple logistic regression indices led to a slight but insignificant improvement in diagnostic accuracy. Our various regression approaches were not able to significantly improve disc-based OCT glaucoma diagnosis. However, disc rim area and vertical CDR had very high diagnostic accuracy, and these disc variables can serve to complement additional OCT measurements for diagnosis of glaucoma.

Characteristics of low-slope streams that affect O2 transfer rates

USGS Publications Warehouse

Parker, Gene W.; Desimone, Leslie A.

1991-01-01

Multiple-regression techniques were used to derive the reaeration coefficients estimating equation for low sloped streams: K2 = 3.83 MBAS-0.41 SL0.20 H-0.76, where K2 is the reaeration coefficient in base e units per day; MBAS is the methylene blue active substances concentration in milligrams per liter; SL is the water-surface slope in foot per foot; and H is the mean-flow depth in feet. Fourteen hydraulic, physical, and water-quality characteristics were regressed against 29 measured-reaeration coefficients for low-sloped (water surface slopes less than 0.002 foot per foot) streams in Massachusetts and New York. Reaeration coefficients measured from May 1985 to October 1988 ranged from 0.2 to 11.0 base e units per day for 29 low-sloped tracer studies. Concentration of methylene blue active substances is significant because it is thought to be an indicator of concentration of surfactants which could change the surface tension at the air-water interface.

Adjusted regression trend test for a multicenter clinical trial.

PubMed

Quan, H; Capizzi, T

1999-06-01

Studies using a series of increasing doses of a compound, including a zero dose control, are often conducted to study the effect of the compound on the response of interest. For a one-way design, Tukey et al. (1985, Biometrics 41, 295-301) suggested assessing trend by examining the slopes of regression lines under arithmetic, ordinal, and arithmetic-logarithmic dose scalings. They reported the smallest p-value for the three significance tests on the three slopes for safety assessments. Capizzi et al. (1992, Biometrical Journal 34, 275-289) suggested an adjusted trend test, which adjusts the p-value using a trivariate t-distribution, the joint distribution of the three slope estimators. In this paper, we propose an adjusted regression trend test suitable for two-way designs, particularly for multicenter clinical trials. In a step-down fashion, the proposed trend test can be applied to a multicenter clinical trial to compare each dose with the control. This sequential procedure is a closed testing procedure for a trend alternative. Therefore, it adjusts p-values and maintains experimentwise error rate. Simulation results show that the step-down trend test is overall more powerful than a step-down least significant difference test.

Moderation analysis using a two-level regression model.

PubMed

Yuan, Ke-Hai; Cheng, Ying; Maxwell, Scott

2014-10-01

Moderation analysis is widely used in social and behavioral research. The most commonly used model for moderation analysis is moderated multiple regression (MMR) in which the explanatory variables of the regression model include product terms, and the model is typically estimated by least squares (LS). This paper argues for a two-level regression model in which the regression coefficients of a criterion variable on predictors are further regressed on moderator variables. An algorithm for estimating the parameters of the two-level model by normal-distribution-based maximum likelihood (NML) is developed. Formulas for the standard errors (SEs) of the parameter estimates are provided and studied. Results indicate that, when heteroscedasticity exists, NML with the two-level model gives more efficient and more accurate parameter estimates than the LS analysis of the MMR model. When error variances are homoscedastic, NML with the two-level model leads to essentially the same results as LS with the MMR model. Most importantly, the two-level regression model permits estimating the percentage of variance of each regression coefficient that is due to moderator variables. When applied to data from General Social Surveys 1991, NML with the two-level model identified a significant moderation effect of race on the regression of job prestige on years of education while LS with the MMR model did not. An R package is also developed and documented to facilitate the application of the two-level model.

A comparison of time dependent Cox regression, pooled logistic regression and cross sectional pooling with simulations and an application to the Framingham Heart Study.

PubMed

Ngwa, Julius S; Cabral, Howard J; Cheng, Debbie M; Pencina, Michael J; Gagnon, David R; LaValley, Michael P; Cupples, L Adrienne

2016-11-03

Typical survival studies follow individuals to an event and measure explanatory variables for that event, sometimes repeatedly over the course of follow up. The Cox regression model has been used widely in the analyses of time to diagnosis or death from disease. The associations between the survival outcome and time dependent measures may be biased unless they are modeled appropriately. In this paper we explore the Time Dependent Cox Regression Model (TDCM), which quantifies the effect of repeated measures of covariates in the analysis of time to event data. This model is commonly used in biomedical research but sometimes does not explicitly adjust for the times at which time dependent explanatory variables are measured. This approach can yield different estimates of association compared to a model that adjusts for these times. In order to address the question of how different these estimates are from a statistical perspective, we compare the TDCM to Pooled Logistic Regression (PLR) and Cross Sectional Pooling (CSP), considering models that adjust and do not adjust for time in PLR and CSP. In a series of simulations we found that time adjusted CSP provided identical results to the TDCM while the PLR showed larger parameter estimates compared to the time adjusted CSP and the TDCM in scenarios with high event rates. We also observed upwardly biased estimates in the unadjusted CSP and unadjusted PLR methods. The time adjusted PLR had a positive bias in the time dependent Age effect with reduced bias when the event rate is low. The PLR methods showed a negative bias in the Sex effect, a subject level covariate, when compared to the other methods. The Cox models yielded reliable estimates for the Sex effect in all scenarios considered. We conclude that survival analyses that explicitly account in the statistical model for the times at which time dependent covariates are measured provide more reliable estimates compared to unadjusted analyses. We present results from the Framingham Heart Study in which lipid measurements and myocardial infarction data events were collected over a period of 26 years.

Measurement of effective air diffusion coefficients for trichloroethene in undisturbed soil cores.

PubMed

Bartelt-Hunt, Shannon L; Smith, James A

2002-06-01

In this study, we measure effective diffusion coefficients for trichloroethene in undisturbed soil samples taken from Picatinny Arsenal, New Jersey. The measured effective diffusion coefficients ranged from 0.0053 to 0.0609 cm2/s over a range of air-filled porosity of 0.23-0.49. The experimental data were compared to several previously published relations that predict diffusion coefficients as a function of air-filled porosity and porosity. A multiple linear regression analysis was developed to determine if a modification of the exponents in Millington's [Science 130 (1959) 100] relation would better fit the experimental data. The literature relations appeared to generally underpredict the effective diffusion coefficient for the soil cores studied in this work. Inclusion of a particle-size distribution parameter, d10, did not significantly improve the fit of the linear regression equation. The effective diffusion coefficient and porosity data were used to recalculate estimates of diffusive flux through the subsurface made in a previous study performed at the field site. It was determined that the method of calculation used in the previous study resulted in an underprediction of diffusive flux from the subsurface. We conclude that although Millington's [Science 130 (1959) 100] relation works well to predict effective diffusion coefficients in homogeneous soils with relatively uniform particle-size distributions, it may be inaccurate for many natural soils with heterogeneous structure and/or non-uniform particle-size distributions.

Truncation of Spherical Harmonic Series and its Influence on Gravity Field Modelling

NASA Astrophysics Data System (ADS)

Fecher, T.; Gruber, T.; Rummel, R.

2009-04-01

Least-squares adjustment is a very common and effective tool for the calculation of global gravity field models in terms of spherical harmonic series. However, since the gravity field is a continuous field function its optimal representation by a finite series of spherical harmonics is connected with a set of fundamental problems. Particularly worth mentioning here are cut off errors and aliasing effects. These problems stem from the truncation of the spherical harmonic series and from the fact that the spherical harmonic coefficients cannot be determined independently of each other within the adjustment process in case of discrete observations. The latter is shown by the non-diagonal variance-covariance matrices of gravity field solutions. Sneeuw described in 1994 that the off-diagonal matrix elements - at least if data are equally weighted - are the result of a loss of orthogonality of Legendre polynomials on regular grids. The poster addresses questions arising from the truncation of spherical harmonic series in spherical harmonic analysis and synthesis. Such questions are: (1) How does the high frequency data content (outside the parameter space) affect the estimated spherical harmonic coefficients; (2) Where to truncate the spherical harmonic series in the adjustment process in order to avoid high frequency leakage?; (3) Given a set of spherical harmonic coefficients resulting from an adjustment, what is the effect of using only a truncated version of it?

Validation of questionnaire on the Spiritual Needs Assessment for Patients (SNAP) questionnaire in Brazilian Portuguese

PubMed Central

de Araujo Toloi, Diego; Uema, Deise; Matsushita, Felipe; da Silva Andrade, Paulo Antonio; Branco, Tiago Pugliese; de Carvalho Chino, Fabiana Tomie Becker; Guerra, Raquel Bezerra; Pfiffer, Túlio Eduardo Flesch; Chiba, Toshio; Guindalini, Rodrigo Santa Cruz; Sulmasy, Daniel P; Riechelmann, Rachel P

2016-01-01

Summary Objectives Spirituality is related to the care and the quality of life of cancer patients. Thus, it is very important to assess their needs. The objective of this study was the translation and cultural adjustment of the Spiritual Needs Assessment for Patients (SNAP) questionnaire to the Brazilian Portuguese language. Methodology The translation and cultural adjustment of the SNAP questionnaire involved six stages: backtranslation, revision of backtranslation, translation to the original language and adjustments, pre-test on ten patients, and test and retest with 30 patients after three weeks. Adult patients, with a solid tumour and literate with a minimum of four years schooling were included. For analysis and consistency we used the calculation of the Cronbach alpha coefficient and the Pearson linear correlation. Results The final questionnaire had some language and content adjustments compared to the original version in English. The correlation analysis of each item with the total score of the questionnaire showed coefficients above 0.99. The calculation of the Cronbach alpha coefficient was 0.9. The calculation of the Pearson linear correlation with the test and retest of the questionnaire was equal to 0.95. Conclusion The SNAP questionnaire translated into Brazilian Portuguese is adequately reliable and consistent. This instrument allows adequate access to spiritual needs and can help patient care. PMID:28101137

Towards the inversion of GRACE gravity fields for present-day ice-mass changes and glacial-isostatic adjustment in North America and Greenland

NASA Astrophysics Data System (ADS)

Sasgen, Ingo; Klemann, Volker; Martinec, Zdeněk

2012-09-01

We perform an inversion of gravity fields from the Gravity Recovery and Climate Experiment (GRACE) (August 2002 to August 2009) of four processing centres for glacial-isostatic adjustment (GIA) over North America and present-day ice-mass change in Alaska and Greenland. We apply a statistical filtering approach to reduce noise in the GRACE data by confining our investigations to GRACE coefficients containing a statistically significant linear trend. Selecting the subset of reliable coefficients in all GRACE time series (GFZ RL04, ITG 2010, JPL RL04 and CSR RL04) results in a non-isotropic smoothing of the GRACE gravity fields, which is effective in reducing the north-south oriented striping associated with correlated errors in GRACE coefficients. In a next step, forward models of GIA induced by the glacial history NAWI (Zweck and Huybrechts, 2005), as well as present-day ice mass changes in Greenland from ICESat (Sørensen et al., 2011) and Alaska from airborne laser altimetry (Arendt et al., 2002) are simultaneously adjusted in scale to minimize the misfit to the filtered GRACE trends. From the adjusted models, we derive the recent sea-level contributions for Greenland and Alaska (August 2002 to August 2009), and, interpret the residual misfit over the GIA-dominated region around the Hudson Bay, Canada, in terms of mantle viscosities beneath North America.

Smooth Scalar-on-Image Regression via Spatial Bayesian Variable Selection

PubMed Central

Goldsmith, Jeff; Huang, Lei; Crainiceanu, Ciprian M.

2013-01-01

We develop scalar-on-image regression models when images are registered multidimensional manifolds. We propose a fast and scalable Bayes inferential procedure to estimate the image coefficient. The central idea is the combination of an Ising prior distribution, which controls a latent binary indicator map, and an intrinsic Gaussian Markov random field, which controls the smoothness of the nonzero coefficients. The model is fit using a single-site Gibbs sampler, which allows fitting within minutes for hundreds of subjects with predictor images containing thousands of locations. The code is simple and is provided in less than one page in the Appendix. We apply this method to a neuroimaging study where cognitive outcomes are regressed on measures of white matter microstructure at every voxel of the corpus callosum for hundreds of subjects. PMID:24729670

The relationship between effectiveness and costs measured by a risk-adjusted case-mix system: multicentre study of Catalonian population data bases.

PubMed

Sicras-Mainar, Antoni; Navarro-Artieda, Ruth; Blanca-Tamayo, Milagrosa; Velasco-Velasco, Soledad; Escribano-Herranz, Esperanza; Llopart-López, Josep Ramon; Violan-Fors, Concepción; Vilaseca-Llobet, Josep Maria; Sánchez-Fontcuberta, Encarna; Benavent-Areu, Jaume; Flor-Serra, Ferran; Aguado-Jodar, Alba; Rodríguez-López, Daniel; Prados-Torres, Alejandra; Estelrich-Bennasar, Jose

2009-06-25

The main objective of this study is to measure the relationship between morbidity, direct health care costs and the degree of clinical effectiveness (resolution) of health centres and health professionals by the retrospective application of Adjusted Clinical Groups in a Spanish population setting. The secondary objectives are to determine the factors determining inadequate correlations and the opinion of health professionals on these instruments. We will carry out a multi-centre, retrospective study using patient records from 15 primary health care centres and population data bases. The main measurements will be: general variables (age and sex, centre, service [family medicine, paediatrics], and medical unit), dependent variables (mean number of visits, episodes and direct costs), co-morbidity (Johns Hopkins University Adjusted Clinical Groups Case-Mix System) and effectiveness.The totality of centres/patients will be considered as the standard for comparison. The efficiency index for visits, tests (laboratory, radiology, others), referrals, pharmaceutical prescriptions and total will be calculated as the ratio: observed variables/variables expected by indirect standardization.The model of cost/patient/year will differentiate fixed/semi-fixed (visits) costs of the variables for each patient attended/year (N = 350,000 inhabitants). The mean relative weights of the cost of care will be obtained. The effectiveness will be measured using a set of 50 indicators of process, efficiency and/or health results, and an adjusted synthetic index will be constructed (method: percentile 50).The correlation between the efficiency (relative-weights) and synthetic (by centre and physician) indices will be established using the coefficient of determination. The opinion/degree of acceptance of physicians (N = 1,000) will be measured using a structured questionnaire including various dimensions. multiple regression analysis (procedure: enter), ANCOVA (method: Bonferroni's adjustment) and multilevel analysis will be carried out to correct models. The level of statistical significance will be p < 0.05.

Two-station comparison of peak flows to improve flood-frequency estimates for seven streamflow-gaging stations in the Salmon and Clearwater River Basins, Central Idaho

USGS Publications Warehouse

Berenbrock, Charles

2003-01-01

Improved flood-frequency estimates for short-term (10 or fewer years of record) streamflow-gaging stations were needed to support instream flow studies by the U.S. Forest Service, which are focused on quantifying water rights necessary to maintain or restore productive fish habitat. Because peak-flow data for short-term gaging stations can be biased by having been collected during an unusually wet, dry, or otherwise unrepresentative period of record, the data may not represent the full range of potential floods at a site. To test whether peak-flow estimates for short-term gaging stations could be improved, the two-station comparison method was used to adjust the logarithmic mean and logarithmic standard deviation of peak flows for seven short-term gaging stations in the Salmon and Clearwater River Basins, central Idaho. Correlation coefficients determined from regression of peak flows for paired short-term and long-term (more than 10 years of record) gaging stations over a concurrent period of record indicated that the mean and standard deviation of peak flows for all short-term gaging stations would be improved. Flood-frequency estimates for seven short-term gaging stations were determined using the adjusted mean and standard deviation. The original (unadjusted) flood-frequency estimates for three of the seven short-term gaging stations differed from the adjusted estimates by less than 10 percent, probably because the data were collected during periods representing the full range of peak flows. Unadjusted flood-frequency estimates for four short-term gaging stations differed from the adjusted estimates by more than 10 percent; unadjusted estimates for Little Slate Creek and Salmon River near Obsidian differed from adjusted estimates by nearly 30 percent. These large differences probably are attributable to unrepresentative periods of peak-flow data collection.

Right miniparasternotomy may be a good minimally invasive alternative to full sternotomy for cardiac valve operations: a propensity-adjusted analysis.

PubMed

Chiu, Kuan M; Chen, Robert J; Lin, Tzu Y; Chen, Jer S; Huang, Jin H; Huang, Chun Y; Chu, Shu H

2016-02-01

Limited real-world data existed for mini-parasternotomy approach with good sample size in Asian cohorts and most previous studies were eclipsed by case heterogeneity. The goal of this study was to compare safety and quality outcomes of cardiac non-coronary valve operations by mini-parasternotomy and full sternotomy approaches on risk-adjusted basis. METHODS From our hospital database, we retrieved the cases of non-coronary valve operations from 1 January 2005 to 31 December 2012, including re-do, emergent, and combined procedures. Estimated EuroScore-II and propensity score for choosing mini-parasternotomy were adjusted for in the regression models on hospital mortality, complications (pneumonia, stroke, sepsis, etc.), and quality parameters (length of stay, ICU time, ventilator time, etc.). Non-complicated cases, defined as survival to discharge, ventilator use not over one week, and intensive care unit stay not over two weeks, were used for quality parameters. There were 283 mini-parasternotomy and 177 full sternotomy cases. EuroScore-II differed significantly (medians 2.1 vs. 4.7, P<0.001). Propensity scores for choosing mini-parasternotomy were higher with lower EuroScore-II (OR=0.91 per 1%, P<0.001), aortic regurgitation (OR=2.3, P=0.005), and aortic non-mitral valve disease (OR=3.9, P<0.001). Adjusted for propensity score and EuroScore-II, mini-parasternotomy group had less pneumonia (OR=0.32, P=0.043), less sepsis (OR=0.31, P=0.045), and shorter non-complicated length of stay (coefficient=-7.2 (day), P<0.001) than full sternotomy group, whereas Kaplan-Meier survival, non-complicated ICU time, non-complicated ventilator time, and 30-day mortality did not differ significantly. The propensity-adjusted analysis demonstrated encouraging safety and quality outcomes for mini-parasternotomy valve operation in carefully selected patients.

The power grid AGC frequency bias coefficient online identification method based on wide area information

NASA Astrophysics Data System (ADS)

Wang, Zian; Li, Shiguang; Yu, Ting

2015-12-01

This paper propose online identification method of regional frequency deviation coefficient based on the analysis of interconnected grid AGC adjustment response mechanism of regional frequency deviation coefficient and the generator online real-time operation state by measured data through PMU, analyze the optimization method of regional frequency deviation coefficient in case of the actual operation state of the power system and achieve a more accurate and efficient automatic generation control in power system. Verify the validity of the online identification method of regional frequency deviation coefficient by establishing the long-term frequency control simulation model of two-regional interconnected power system.

The Geometry of Enhancement in Multiple Regression

ERIC Educational Resources Information Center

Waller, Niels G.

2011-01-01

In linear multiple regression, "enhancement" is said to occur when R[superscript 2] = b[prime]r greater than r[prime]r, where b is a p x 1 vector of standardized regression coefficients and r is a p x 1 vector of correlations between a criterion y and a set of standardized regressors, x. When p = 1 then b [is congruent to] r and…

A Comparison between the Use of Beta Weights and Structure Coefficients in Interpreting Regression Results

ERIC Educational Resources Information Center

Tong, Fuhui

2006-01-01

Background: An extensive body of researches has favored the use of regression over other parametric analyses that are based on OVA. In case of noteworthy regression results, researchers tend to explore magnitude of beta weights for the respective predictors. Purpose: The purpose of this paper is to examine both beta weights and structure…

Estimation Methods for Non-Homogeneous Regression - Minimum CRPS vs Maximum Likelihood

NASA Astrophysics Data System (ADS)

Gebetsberger, Manuel; Messner, Jakob W.; Mayr, Georg J.; Zeileis, Achim

2017-04-01

Non-homogeneous regression models are widely used to statistically post-process numerical weather prediction models. Such regression models correct for errors in mean and variance and are capable to forecast a full probability distribution. In order to estimate the corresponding regression coefficients, CRPS minimization is performed in many meteorological post-processing studies since the last decade. In contrast to maximum likelihood estimation, CRPS minimization is claimed to yield more calibrated forecasts. Theoretically, both scoring rules used as an optimization score should be able to locate a similar and unknown optimum. Discrepancies might result from a wrong distributional assumption of the observed quantity. To address this theoretical concept, this study compares maximum likelihood and minimum CRPS estimation for different distributional assumptions. First, a synthetic case study shows that, for an appropriate distributional assumption, both estimation methods yield to similar regression coefficients. The log-likelihood estimator is slightly more efficient. A real world case study for surface temperature forecasts at different sites in Europe confirms these results but shows that surface temperature does not always follow the classical assumption of a Gaussian distribution. KEYWORDS: ensemble post-processing, maximum likelihood estimation, CRPS minimization, probabilistic temperature forecasting, distributional regression models

The consequences of ignoring measurement invariance for path coefficients in structural equation models

PubMed Central

Guenole, Nigel; Brown, Anna

2014-01-01

We report a Monte Carlo study examining the effects of two strategies for handling measurement non-invariance – modeling and ignoring non-invariant items – on structural regression coefficients between latent variables measured with item response theory models for categorical indicators. These strategies were examined across four levels and three types of non-invariance – non-invariant loadings, non-invariant thresholds, and combined non-invariance on loadings and thresholds – in simple, partial, mediated and moderated regression models where the non-invariant latent variable occupied predictor, mediator, and criterion positions in the structural regression models. When non-invariance is ignored in the latent predictor, the focal group regression parameters are biased in the opposite direction to the difference in loadings and thresholds relative to the referent group (i.e., lower loadings and thresholds for the focal group lead to overestimated regression parameters). With criterion non-invariance, the focal group regression parameters are biased in the same direction as the difference in loadings and thresholds relative to the referent group. While unacceptable levels of parameter bias were confined to the focal group, bias occurred at considerably lower levels of ignored non-invariance than was previously recognized in referent and focal groups. PMID:25278911

Essays in applied macroeconomics: Asymmetric price adjustment, exchange rate and treatment effect

NASA Astrophysics Data System (ADS)

Gu, Jingping

This dissertation consists of three essays. Chapter II examines the possible asymmetric response of gasoline prices to crude oil price changes using an error correction model with GARCH errors. Recent papers have looked at this issue. Some of these papers estimate a form of error correction model, but none of them accounts for autoregressive heteroskedasticity in estimation and testing for asymmetry and none of them takes the response of crude oil price into consideration. We find that time-varying volatility of gasoline price disturbances is an important feature of the data, and when we allow for asymmetric GARCH errors and investigate the system wide impulse response function, we find evidence of asymmetric adjustment to crude oil price changes in weekly retail gasoline prices. Chapter III discusses the relationship between fiscal deficit and exchange rate. Economic theory predicts that fiscal deficits can significantly affect real exchange rate movements, but existing empirical evidence reports only a weak impact of fiscal deficits on exchange rates. Based on US dollar-based real exchange rates in G5 countries and a flexible varying coefficient model, we show that the previously documented weak relationship between fiscal deficits and exchange rates may be the result of additive specifications, and that the relationship is stronger if we allow fiscal deficits to impact real exchange rates non-additively as well as nonlinearly. We find that the speed of exchange rate adjustment toward equilibrium depends on the state of the fiscal deficit; a fiscal contraction in the US can lead to less persistence in the deviation of exchange rates from fundamentals, and faster mean reversion to the equilibrium. Chapter IV proposes a kernel method to deal with the nonparametric regression model with only discrete covariates as regressors. This new approach is based on recently developed least squares cross-validation kernel smoothing method. It can not only automatically smooth the irrelevant variables out of the nonparametric regression model, but also avoid the problem of loss of efficiency related to the traditional nonparametric frequency-based method and the problem of misspecification based on parametric model.

Linear regression metamodeling as a tool to summarize and present simulation model results.

PubMed

Jalal, Hawre; Dowd, Bryan; Sainfort, François; Kuntz, Karen M

2013-10-01

Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.

Employing the Gini coefficient to measure participation inequality in treatment-focused Digital Health Social Networks.

PubMed

van Mierlo, Trevor; Hyatt, Douglas; Ching, Andrew T

2016-01-01

Digital Health Social Networks (DHSNs) are common; however, there are few metrics that can be used to identify participation inequality. The objective of this study was to investigate whether the Gini coefficient, an economic measure of statistical dispersion traditionally used to measure income inequality, could be employed to measure DHSN inequality. Quarterly Gini coefficients were derived from four long-standing DHSNs. The combined data set included 625,736 posts that were generated from 15,181 actors over 18,671 days. The range of actors (8-2323), posts (29-28,684), and Gini coefficients (0.15-0.37) varied. Pearson correlations indicated statistically significant associations between number of actors and number of posts (0.527-0.835, p  < .001), and Gini coefficients and number of posts (0.342-0.725, p  < .001). However, the association between Gini coefficient and number of actors was only statistically significant for the addiction networks (0.619 and 0.276, p  < .036). Linear regression models had positive but mixed R 2 results (0.333-0.527). In all four regression models, the association between Gini coefficient and posts was statistically significant ( t  = 3.346-7.381, p  < .002). However, unlike the Pearson correlations, the association between Gini coefficient and number of actors was only statistically significant in the two mental health networks ( t  = -4.305 and -5.934, p  < .000). The Gini coefficient is helpful in measuring shifts in DHSN inequality. However, as a standalone metric, the Gini coefficient does not indicate optimal numbers or ratios of actors to posts, or effective network engagement. Further, mixed-methods research investigating quantitative performance metrics is required.

Linking patient satisfaction with nursing care: the case of care rationing - a correlational study.

PubMed

Papastavrou, Evridiki; Andreou, Panayiota; Tsangari, Haritini; Merkouris, Anastasios

2014-01-01

Implicit rationing of nursing care is the withholding of or failure to carry out all necessary nursing measures due to lack of resources. There is evidence supporting a link between rationing of nursing care, nurses' perceptions of their professional environment, negative patient outcomes, and placing patient safety at risk. The aims of the study were: a) To explore whether patient satisfaction is linked to nurse-reported rationing of nursing care and to nurses' perceptions of their practice environment while adjusting for patient and nurse characteristics. b) To identify the threshold score of rationing by comparing the level of patient satisfaction factors across rationing levels. A descriptive, correlational design was employed. Participants in this study included 352 patients and 318 nurses from ten medical and surgical units of five general hospitals. Three measurement instruments were used: the BERNCA scale for rationing of care, the RPPE scale to explore nurses' perceptions of their work environment and the Patient Satisfaction scale to assess the level of patient satisfaction with nursing care. The statistical analysis included the use of Kendall's correlation coefficient to explore a possible relationship between the variables and multiple regression analysis to assess the effects of implicit rationing of nursing care together with organizational characteristics on patient satisfaction. The mean score of implicit rationing of nursing care was 0.83 (SD = 0.52, range = 0-3), the overall mean of RPPE was 2.76 (SD = 0.32, range = 1.28 - 3.69) and the two scales were significantly correlated (τ = -0.234, p < 0.001). The regression analysis showed that care rationing and work environment were related to patient satisfaction, even after controlling for nurse and patient characteristics. The results from the adjusted regression models showed that even at the lowest level of rationing (i.e. 0.5) patients indicated low satisfaction. The results support the relationships between organizational and environmental variables, care rationing and patient satisfaction. The identification of thresholds at which rationing starts to influence patient outcomes in a negative way may allow nurse managers to introduce interventions so as to keep rationing at a level at which patient safety is not jeopardized.

Coastal climate is associated with elevated solar irradiance and higher 25(OH)D level.

PubMed

Cherrie, M P C; Wheeler, B W; White, M P; Sarran, C E; Osborne, N J

2015-04-01

There is evidence that populations living close to the coast have improved health and wellbeing. Coastal environments are linked to promotion of physical activity through provision of safe, opportune, aesthetic and accessible spaces for recreation. Exposure to coastal environments may also reduce stress and induce positive mood. We hypothesised that coastal climate may influence the vitamin D status of residents and thus partly explain benefits to health. Ecological and cross-sectional analyses were designed to elucidate the connection between coastal residence and vitamin D status. We divided residential data, from developed land use areas and the Lower Super Output Areas or Data Zones (Scotland) of the 1958 Birth Cohort participants, into the following coastal bands: <1 km, 1-5 km, 5-20 km, 20-50 km and over 50 km. In the ecological analysis we used a multiple regression model to describe the relationship between UV vitd and coastal proximity adjusted for latitude. Subsequently, using the residential information of the participants of the 1958 Birth Cohort we developed a multiple regression model to understand the relationship between serum 25(OH)D (a marker of vitamin D status) and coastal proximity adjusted for several factors related to vitamin D status (e.g. diet, outdoor activity). We found that coastal proximity was associated with solar irradiance; on average a 99.6 (96.1-103.3)J/m(2)/day regression coefficient was recorded for settlements <1 km from the coast compared with those at >50 km. This relationship was modified by latitude with settlements at a lower latitude exhibiting a greater effect. Individuals living closer to the coast in England had higher vitamin D levels than those inland, particularly in autumn. Geographic location may influence biochemistry and health outcomes due to environmental factors. This can provide benefits in terms of vitamin D status but may also pose a risk due to higher skin cancer risk. We provide further evidence in support of the claim that coastal environments can provide opportunities for health and wellbeing. Copyright © 2015 Elsevier Ltd. All rights reserved.

Optimal Congestion Management in Electricity Market Using Particle Swarm Optimization with Time Varying Acceleration Coefficients

NASA Astrophysics Data System (ADS)

Boonyaritdachochai, Panida; Boonchuay, Chanwit; Ongsakul, Weerakorn

2010-06-01

This paper proposes an optimal power redispatching approach for congestion management in deregulated electricity market. Generator sensitivity is considered to indicate the redispatched generators. It can reduce the number of participating generators. The power adjustment cost and total redispatched power are minimized by particle swarm optimization with time varying acceleration coefficients (PSO-TVAC). The IEEE 30-bus and IEEE 118-bus systems are used to illustrate the proposed approach. Test results show that the proposed optimization scheme provides the lowest adjustment cost and redispatched power compared to the other schemes. The proposed approach is useful for the system operator to manage the transmission congestion.

A Method of Determining Aerodynamic-Influence Coefficients from Wind-Tunnel Data for Wings at Supersonic Speeds

NASA Technical Reports Server (NTRS)

Gainer, Patrick A.

1961-01-01

A method is described for determining aerodynamic-influence coefficients from wind-tunnel data for calculating the steady-state load distribution on a wing with arbitrary angle-of-attack distribution at supersonic speeds. The method combines linearized theory with empirical adjustments in order to give accurate results over a wide range of angles of attack. The experimented data required are pressure distributions measured on a flat wing of the desired planform at the desired Mach number and over the desired range of angles of attack. The method has been tested by applying it to wind-tunnel data measured at Mach numbers of 1.61 and 2.01 on wings of the same planform but of different surface shapes. Influence coefficients adjusted to fit the flat wing gave good predictions of the spanwise and chord-wise distributions of loadings measured on twisted and cambered wings.

The Study of Rain Specific Attenuation for the Prediction of Satellite Propagation in Malaysia

NASA Astrophysics Data System (ADS)

Mandeep, J. S.; Ng, Y. Y.; Abdullah, H.; Abdullah, M.

2010-06-01

Specific attenuation is the fundamental quantity in the calculation of rain attenuation for terrestrial path and slant paths representing as rain attenuation per unit distance (dB/km). Specific attenuation is an important element in developing the predicted rain attenuation model. This paper deals with the empirical determination of the power law coefficients which allow calculating the specific attenuation in dB/km from the knowledge of the rain rate in mm/h. The main purpose of the paper is to obtain the coefficients of k and α of power law relationship between specific attenuation. Three years (from 1st January 2006 until 31st December 2008) rain gauge and beacon data taken from USM, Nibong Tebal have been used to do the empirical procedure analysis of rain specific attenuation. The data presented are semi-empirical in nature. A year-to-year variation of the coefficients has been indicated and the empirical measured data was compared with ITU-R provided regression coefficient. The result indicated that the USM empirical measured data was significantly vary from ITU-R predicted value. Hence, ITU-R recommendation for regression coefficients of rain specific attenuation is not suitable for predicting rain attenuation at Malaysia.

Gridded sunshine duration climate data record for Germany based on combined satellite and in situ observations

NASA Astrophysics Data System (ADS)

Walawender, Jakub; Kothe, Steffen; Trentmann, Jörg; Pfeifroth, Uwe; Cremer, Roswitha

2017-04-01

The purpose of this study is to create a 1 km2 gridded daily sunshine duration data record for Germany covering the period from 1983 to 2015 (33 years) based on satellite estimates of direct normalised surface solar radiation and in situ sunshine duration observations using a geostatistical approach. The CM SAF SARAH direct normalized irradiance (DNI) satellite climate data record and in situ observations of sunshine duration from 121 weather stations operated by DWD are used as input datasets. The selected period of 33 years is associated with the availability of satellite data. The number of ground stations is limited to 121 as there are only time series with less than 10% of missing observations over the selected period included to keep the long-term consistency of the output sunshine duration data record. In the first step, DNI data record is used to derive sunshine hours by applying WMO threshold of 120 W/m2 (SDU = DNI ≥ 120 W/m2) and weighting of sunny slots to correct the sunshine length between two instantaneous image data due to cloud movement. In the second step, linear regression between SDU and in situ sunshine duration is calculated to adjust the satellite product to the ground observations and the output regression coefficients are applied to create a regression grid. In the last step regression residuals are interpolated with ordinary kriging and added to the regression grid. A comprehensive accuracy assessment of the gridded sunshine duration data record is performed by calculating prediction errors (cross-validation routine). "R" is used for data processing. A short analysis of the spatial distribution and temporal variability of sunshine duration over Germany based on the created dataset will be presented. The gridded sunshine duration data are useful for applications in various climate-related studies, agriculture and solar energy potential calculations.

Linear models for calculating digestibile energy for sheep diets.

PubMed

Fonnesbeck, P V; Christiansen, M L; Harris, L E

1981-05-01

Equations for estimating the digestible energy (DE) content of sheep diets were generated from the chemical contents and a factorial description of diets fed to lambs in digestion trials. The diet factors were two forages (alfalfa and grass hay), harvested at three stages of maturity (late vegetative, early bloom and full bloom), fed in two ingredient combinations (all hay or a 50:50 hay and corn grain mixture) and prepared by two forage texture processes (coarsely chopped or finely chopped and pelleted). The 2 x 3 x 2 x 2 factorial arrangement produced 24 diet treatments. These were replicated twice, for a total of 48 lamb digestion trials. In model 1 regression equations, DE was calculated directly from chemical composition of the diet. In model 2, regression equations predicted the percentage of digested nutrient from the chemical contents of the diet and then DE of the diet was calculated as the sum of the gross energy of the digested organic components. Expanded forms of model 1 and model 2 were also developed that included diet factors as qualitative indicator variables to adjust the regression constant and regression coefficients for the diet description. The expanded forms of the equations accounted for significantly more variation in DE than did the simple models and more accurately estimated DE of the diet. Information provided by the diet description proved as useful as chemical analyses for the prediction of digestibility of nutrients. The statistics indicate that, with model 1, neutral detergent fiber and plant cell wall analyses provided as much information for the estimation of DE as did model 2 with the combined information from crude protein, available carbohydrate, total lipid, cellulose and hemicellulose. Regression equations are presented for estimating DE with the most currently analyzed organic components, including linear and curvilinear variables and diet factors that significantly reduce the standard error of the estimate. To estimate De of a diet, the user utilizes the equation that uses the chemical analysis information and diet description most effectively.

Risk of suicide in male prison inmates.

PubMed

Saavedra, Javier; López, Marcelino

2015-01-01

Many studies have demonstrated that the risk of suicide in prison is higher than in the general population. This study has two aims. First, to explore the risk of suicide in men sentenced in Andalusian prisons. And second, to study the sociodemographic, criminal and, especially, psychopathological factors associated with this risk. An assessment was made of 472 sentenced inmates in two Andalusian prisons, and included a sociodemographic interview, the IPDE personality disorders questionnaire, the SCID-I diagnostic interview (DSMIV), and the Plutchick suicide risk questionnaire. The interviewers were experienced clinical psychologists with training in prison environments. Adjusted ORs were calculated using a logistic regression. A risk of committing suicide was detected in 33.5% of the sample. The diagnoses (lifetime prevalence) of affective disorder (adjusted OR 3329), substance dependence disorders (adjusted OR 2733), personality disorders (adjusted OR 3115) and anxiety disorder (adjusted OR 1650), as well as a family psychiatric history (adjusted OR 1650), were the predictors that remained as risk factors after the regression analysis. No socio-demographic risk factor was significant in the regression analysis. The psychopathological variables are essential and the most powerful factors to explain suicide risk in prisons. A correct and systematic diagnosis, and an appropriate treatment by mental health professionals during the imprisonment are essential to prevent the risk of suicide. Copyright © 2013 SEP y SEPB. Published by Elsevier España. All rights reserved.

Merchantable sawlog and bole-length equations for the Northeastern United States

Treesearch

Daniel A. Yaussy; Martin E. Dale; Martin E. Dale

1991-01-01

A modified Richards growth model is used to develop species-specific coefficients for equations estimating the merchantable sawlog and bole lengths of trees from 25 species groups common to the Northeastern United States. These regression coefficients have been incorporated into the growth-and-yield simulation software, NE-TWIGS.

Advanced statistics: linear regression, part II: multiple linear regression.

PubMed

Marill, Keith A

2004-01-01

The applications of simple linear regression in medical research are limited, because in most situations, there are multiple relevant predictor variables. Univariate statistical techniques such as simple linear regression use a single predictor variable, and they often may be mathematically correct but clinically misleading. Multiple linear regression is a mathematical technique used to model the relationship between multiple independent predictor variables and a single dependent outcome variable. It is used in medical research to model observational data, as well as in diagnostic and therapeutic studies in which the outcome is dependent on more than one factor. Although the technique generally is limited to data that can be expressed with a linear function, it benefits from a well-developed mathematical framework that yields unique solutions and exact confidence intervals for regression coefficients. Building on Part I of this series, this article acquaints the reader with some of the important concepts in multiple regression analysis. These include multicollinearity, interaction effects, and an expansion of the discussion of inference testing, leverage, and variable transformations to multivariate models. Examples from the first article in this series are expanded on using a primarily graphic, rather than mathematical, approach. The importance of the relationships among the predictor variables and the dependence of the multivariate model coefficients on the choice of these variables are stressed. Finally, concepts in regression model building are discussed.

Association between Stereotactic Radiotherapy and Death from Brain Metastases of Epithelial Ovarian Cancer: a Gliwice Data Re-Analysis with Penalization

PubMed

Tukiendorf, Andrzej; Mansournia, Mohammad Ali; Wydmański, Jerzy; Wolny-Rokicka, Edyta

2017-04-01

Background: Clinical datasets for epithelial ovarian cancer brain metastatic patients are usually small in size. When adequate case numbers are lacking, resulting estimates of regression coefficients may demonstrate bias. One of the direct approaches to reduce such sparse-data bias is based on penalized estimation. Methods: A re- analysis of formerly reported hazard ratios in diagnosed patients was performed using penalized Cox regression with a popular SAS package providing additional software codes for a statistical computational procedure. Results: It was found that the penalized approach can readily diminish sparse data artefacts and radically reduce the magnitude of estimated regression coefficients. Conclusions: It was confirmed that classical statistical approaches may exaggerate regression estimates or distort study interpretations and conclusions. The results support the thesis that penalization via weak informative priors and data augmentation are the safest approaches to shrink sparse data artefacts frequently occurring in epidemiological research. Creative Commons Attribution License

REGRES: A FORTRAN-77 program to calculate nonparametric and ``structural'' parametric solutions to bivariate regression equations

NASA Astrophysics Data System (ADS)

Rock, N. M. S.; Duffy, T. R.

REGRES allows a range of regression equations to be calculated for paired sets of data values in which both variables are subject to error (i.e. neither is the "independent" variable). Nonparametric regressions, based on medians of all possible pairwise slopes and intercepts, are treated in detail. Estimated slopes and intercepts are output, along with confidence limits, Spearman and Kendall rank correlation coefficients. Outliers can be rejected with user-determined stringency. Parametric regressions can be calculated for any value of λ (the ratio of the variances of the random errors for y and x)—including: (1) major axis ( λ = 1); (2) reduced major axis ( λ = variance of y/variance of x); (3) Y on Xλ = infinity; or (4) X on Y ( λ = 0) solutions. Pearson linear correlation coefficients also are output. REGRES provides an alternative to conventional isochron assessment techniques where bivariate normal errors cannot be assumed, or weighting methods are inappropriate.

Regression approaches in the test-negative study design for assessment of influenza vaccine effectiveness.

PubMed

Bond, H S; Sullivan, S G; Cowling, B J

2016-06-01

Influenza vaccination is the most practical means available for preventing influenza virus infection and is widely used in many countries. Because vaccine components and circulating strains frequently change, it is important to continually monitor vaccine effectiveness (VE). The test-negative design is frequently used to estimate VE. In this design, patients meeting the same clinical case definition are recruited and tested for influenza; those who test positive are the cases and those who test negative form the comparison group. When determining VE in these studies, the typical approach has been to use logistic regression, adjusting for potential confounders. Because vaccine coverage and influenza incidence change throughout the season, time is included among these confounders. While most studies use unconditional logistic regression, adjusting for time, an alternative approach is to use conditional logistic regression, matching on time. Here, we used simulation data to examine the potential for both regression approaches to permit accurate and robust estimates of VE. In situations where vaccine coverage changed during the influenza season, the conditional model and unconditional models adjusting for categorical week and using a spline function for week provided more accurate estimates. We illustrated the two approaches on data from a test-negative study of influenza VE against hospitalization in children in Hong Kong which resulted in the conditional logistic regression model providing the best fit to the data.

Evaluation and modification of five techniques for estimating stormwater runoff for watersheds in west-central Florida

USGS Publications Warehouse

Trommer, J.T.; Loper, J.E.; Hammett, K.M.

1996-01-01

Several traditional techniques have been used for estimating stormwater runoff from ungaged watersheds. Applying these techniques to water- sheds in west-central Florida requires that some of the empirical relationships be extrapolated beyond tested ranges. As a result, there is uncertainty as to the accuracy of these estimates. Sixty-six storms occurring in 15 west-central Florida watersheds were initially modeled using the Rational Method, the U.S. Geological Survey Regional Regression Equations, the Natural Resources Conservation Service TR-20 model, the U.S. Army Corps of Engineers Hydrologic Engineering Center-1 model, and the Environmental Protection Agency Storm Water Management Model. The techniques were applied according to the guidelines specified in the user manuals or standard engineering textbooks as though no field data were available and the selection of input parameters was not influenced by observed data. Computed estimates were compared with observed runoff to evaluate the accuracy of the techniques. One watershed was eliminated from further evaluation when it was determined that the area contributing runoff to the stream varies with the amount and intensity of rainfall. Therefore, further evaluation and modification of the input parameters were made for only 62 storms in 14 watersheds. Runoff ranged from 1.4 to 99.3 percent percent of rainfall. The average runoff for all watersheds included in this study was about 36 percent of rainfall. The average runoff for the urban, natural, and mixed land-use watersheds was about 41, 27, and 29 percent, respectively. Initial estimates of peak discharge using the rational method produced average watershed errors that ranged from an underestimation of 50.4 percent to an overestimation of 767 percent. The coefficient of runoff ranged from 0.20 to 0.60. Calibration of the technique produced average errors that ranged from an underestimation of 3.3 percent to an overestimation of 1.5 percent. The average calibrated coefficient of runoff for each watershed ranged from 0.02 to 0.72. The average values of the coefficient of runoff necessary to calibrate the urban, natural, and mixed land-use watersheds were 0.39, 0.16, and 0.08, respectively. The U.S. Geological Survey regional regression equations for determining peak discharge produced errors that ranged from an underestimation of 87.3 percent to an over- estimation of 1,140 percent. The regression equations for determining runoff volume produced errors that ranged from an underestimation of 95.6 percent to an overestimation of 324 percent. Regression equations developed from data used for this study produced errors that ranged between an underestimation of 82.8 percent and an over- estimation of 328 percent for peak discharge, and from an underestimation of 71.2 percent to an overestimation of 241 percent for runoff volume. Use of the equations developed for west-central Florida streams produced average errors for each type of watershed that were lower than errors associated with use of the U.S. Geological Survey equations. Initial estimates of peak discharges and runoff volumes using the Natural Resources Conservation Service TR-20 model, produced average errors of 44.6 and 42.7 percent respectively, for all the watersheds. Curve numbers and times of concentration were adjusted to match estimated and observed peak discharges and runoff volumes. The average change in the curve number for all the watersheds was a decrease of 2.8 percent. The average change in the time of concentration was an increase of 59.2 percent. The shape of the input dimensionless unit hydrograph also had to be adjusted to match the shape and peak time of the estimated and observed flood hydrographs. Peak rate factors for the modified input dimensionless unit hydrographs ranged from 162 to 454. The mean errors for peak discharges and runoff volumes were reduced to 18.9 and 19.5 percent, respectively, using the average calibrated input parameters for ea

Self-reported Slower Eating Is Associated with a Lower Salt Intake: A Population-based Cross-sectional Study.

PubMed

Wakasugi, Minako; James Kazama, Junichiro; Narita, Ichiei

2018-06-01

Objective Evidence suggests that the eating rate is positively associated with the body weight and blood pressure. Furthermore, people who are overweight or obese tend to have higher salt intakes than those of normal weight. To investigate whether or not the eating rate is also associated with the salt intake, a cross-sectional study was conducted using health examination survey data collected in 2014 from 7,941 residents of Sado City, Niigata, Japan. Methods The eating rates were evaluated using a questionnaire; 11.7% of participants rated themselves as slow eaters, 65.6% as normal eaters, and 22.7% as fast eaters. The salt intake was estimated from sodium and creatinine spot urine measurements using Tanaka's formula. Associations with eating rate were evaluated using multivariate linear regression analyses, with normal eaters as the reference (set at 0). Results Self-reported eating rates were positively associated with the salt intake after adjustment for age and sex [β coefficient (95% confidence interval) for slow -0.51 (-0.67, -0.35); fast 0.18 (0.05, 0.30) ]. Further adjustment for the body mass index showed that slower eaters had lower salt intakes than normal eaters, but there was no marked difference in the salt intake between normal and fast eaters. The association between slower eating and a lower salt intake persisted after further adjustment for comorbidities [slow -0.33 (-0.49, -0.18) ]. Conclusion Our results suggest that reducing eating rates may be an effective strategy for reducing dietary salt intake as well as preventing obesity.

Application of Temperature Sensitivities During Iterative Strain-Gage Balance Calibration Analysis

NASA Technical Reports Server (NTRS)

Ulbrich, N.

2011-01-01

A new method is discussed that may be used to correct wind tunnel strain-gage balance load predictions for the influence of residual temperature effects at the location of the strain-gages. The method was designed for the iterative analysis technique that is used in the aerospace testing community to predict balance loads from strain-gage outputs during a wind tunnel test. The new method implicitly applies temperature corrections to the gage outputs during the load iteration process. Therefore, it can use uncorrected gage outputs directly as input for the load calculations. The new method is applied in several steps. First, balance calibration data is analyzed in the usual manner assuming that the balance temperature was kept constant during the calibration. Then, the temperature difference relative to the calibration temperature is introduced as a new independent variable for each strain--gage output. Therefore, sensors must exist near the strain--gages so that the required temperature differences can be measured during the wind tunnel test. In addition, the format of the regression coefficient matrix needs to be extended so that it can support the new independent variables. In the next step, the extended regression coefficient matrix of the original calibration data is modified by using the manufacturer specified temperature sensitivity of each strain--gage as the regression coefficient of the corresponding temperature difference variable. Finally, the modified regression coefficient matrix is converted to a data reduction matrix that the iterative analysis technique needs for the calculation of balance loads. Original calibration data and modified check load data of NASA's MC60D balance are used to illustrate the new method.

Sensitivity analysis of a multilayer, finite-difference model of the Southeastern Coastal Plain regional aquifer system; Mississippi, Alabama, Georgia, and South Carolina

USGS Publications Warehouse

Pernik, Meribeth

1987-01-01

The sensitivity of a multilayer finite-difference regional flow model was tested by changing the calibrated values for five parameters in the steady-state model and one in the transient-state model. The parameters that changed under the steady-state condition were those that had been routinely adjusted during the calibration process as part of the effort to match pre-development potentiometric surfaces, and elements of the water budget. The tested steady-state parameters include: recharge, riverbed conductance, transmissivity, confining unit leakance, and boundary location. In the transient-state model, the storage coefficient was adjusted. The sensitivity of the model to changes in the calibrated values of these parameters was evaluated with respect to the simulated response of net base flow to the rivers, and the mean value of the absolute head residual. To provide a standard measurement of sensitivity from one parameter to another, the standard deviation of the absolute head residual was calculated. The steady-state model was shown to be most sensitive to changes in rates of recharge. When the recharge rate was held constant, the model was more sensitive to variations in transmissivity. Near the rivers, the riverbed conductance becomes the dominant parameter in controlling the heads. Changes in confining unit leakance had little effect on simulated base flow, but greatly affected head residuals. The model was relatively insensitive to changes in the location of no-flow boundaries and to moderate changes in the altitude of constant head boundaries. The storage coefficient was adjusted under transient conditions to illustrate the model 's sensitivity to changes in storativity. The model is less sensitive to an increase in storage coefficient than it is to a decrease in storage coefficient. As the storage coefficient decreased, the aquifer drawdown increases, the base flow decreased. The opposite response occurred when the storage coefficient was increased. (Author 's abstract)

Gas-film coefficients for streams

USGS Publications Warehouse

Rathbun, R.E.; Tai, D.Y.

1983-01-01

Equations for predicting the gas-film coefficient for the volatilization of organic solutes from streams are developed. The film coefficient is a function of windspeed and water temperature. The dependence of the coefficient on windspeed is determined from published information on the evaporation of water from a canal. The dependence of the coefficient on temperature is determined from laboratory studies on the evaporation of water. Procedures for adjusting the coefficients for different organic solutes are based on the molecular diffusion coefficient and the molecular weight. The molecular weight procedure is easiest to use because of the availability of molecular weights. However, the theoretical basis of the procedure is questionable. The diffusion coefficient procedure is supported by considerable data. Questions, however, remain regarding the exact dependence of the film coefficint on the diffusion coefficient. It is suggested that the diffusion coefficient procedure with a 0.68-power dependence be used when precise estimate of the gas-film coefficient are needed and that the molecular weight procedure be used when only approximate estimates are needed.

Influence of socio-demographic, labour and professional factors on nursing perception concerning practice environment in Primary Health Care.

PubMed

Parro Moreno, Ana; Serrano Gallardo, Pilar; Ferrer Arnedo, Carmen; Serrano Molina, Lucía; de la Puerta Calatayud, M Luisa; Barberá Martín, Aurora; Morales Asencio, José Miguel; de Pedro Gómez, Joan

2013-11-01

To analyze the perception of nursing professionals of the Madrid Primary Health Care environment in which they practice, as well as its relationship with socio-demographic, work-related and professional factors. Cross-sectional, analytical, observational study. Questionnaire sent to a total of 475 nurses in Primary Health Care in Madrid (former Health Care Areas 6 and 9), in 2010. Perception of the practice environment using the Practice Environment Scale of the Nursing Work Index (PES-NWI) questionnaire, as well as; age; sex; years of professional experience; professional category; Health Care Area; employment status and education level. There was a response rate of 69.7% (331). The raw score for the PES-NWI was: 81.04 [95%CI: 79.18-82.91]. The factor with the highest score was "Support from Managers" (2.9 [95%CI: 2.8-3]) and the lowest "Workforce adequacy" (2.3 [95%CI: 2.2-2.4]). In the regression model (dependent variable: raw score in PES-NWI), adjusted by age, sex, employment status, professional category (coefficient B=6.586), and years worked at the centre (coefficient B=2.139, for a time of 0-2 years; coefficient B=7.482, for 3-10 years; coefficient B=7.867, for over 20 years) remained at p≤0.05. The support provided by nurse managers is the most highly valued factor in this practice environment, while workforce adequacy is perceived as the lowest. Nurses in posts of responsibility and those possessing a higher degree of training perceive their practice environment more favourably. Knowledge of the factors in the practice environment is a key element for health care organizations to optimize provision of care and to improve health care results. Copyright © 2012 Elsevier España, S.L. All rights reserved.

The longitudinal association between social functioning and theory of mind in first-episode psychosis.

PubMed

Sullivan, Sarah; Lewis, Glyn; Mohr, Christine; Herzig, Daniela; Corcoran, Rhiannon; Drake, Richard; Evans, Jonathan

2014-01-01

There is some cross-sectional evidence that theory of mind ability is associated with social functioning in those with psychosis but the direction of this relationship is unknown. This study investigates the longitudinal association between both theory of mind and psychotic symptoms and social functioning outcome in first-episode psychosis. Fifty-four people with first-episode psychosis were followed up at 6 and 12 months. Random effects regression models were used to estimate the stability of theory of mind over time and the association between baseline theory of mind and psychotic symptoms and social functioning outcome. Neither baseline theory of mind ability (regression coefficients: Hinting test 1.07 95% CI -0.74, 2.88; Visual Cartoon test -2.91 95% CI -7.32, 1.51) nor baseline symptoms (regression coefficients: positive symptoms -0.04 95% CI -1.24, 1.16; selected negative symptoms -0.15 95% CI -2.63, 2.32) were associated with social functioning outcome. There was evidence that theory of mind ability was stable over time, (regression coefficients: Hinting test 5.92 95% CI -6.66, 8.92; Visual Cartoon test score 0.13 95% CI -0.17, 0.44). Neither baseline theory of mind ability nor psychotic symptoms are associated with social functioning outcome. Further longitudinal work is needed to understand the origin of social functioning deficits in psychosis.

Association between physical activity and major depressive disorder among current or former smokers with pulmonary disease.

PubMed

Loprinzi, Paul D; Kane, Christy; Walker, Jerome F

2013-11-01

To examine the association between physical activity and major depressive disorder (MDD) in a nationally representative sample of current or former smokers with pulmonary impairments. The analyzed sample from the National Health and Nutrition Examination Survey (NHANES) 2007-2010 included 536 adults who indicated that they were current or former smokers, had at least mild pulmonary impairment (FEV1/FVC<0.70), and provided depression and physical activity data. After controlling for asthma status, pulmonary impairment, age, poverty-to-income ratio (PIR), education, gender, marital status, body mass index (BMI), cotinine, comorbidity index, race-ethnicity, and smoking status, those who met physical activity guidelines had a 59% (odds ratio (OR)=0.41; 95% confidence interval (CI): 0.18-0.94) lower odds of having MDD. Using multivariate linear regression with depression symptoms as the outcome variable, and after adjustments, physical activity was inversely associated with depression symptoms in a dose-response manner; lowest tertile was the referent group, middle tertile coefficient: -1.06 (95% CI: -1.98 to -0.14), and highest tertile coefficient: -1.10 (95% CI: -1.84 to -0.34). Physical activity inversely associates with MDD in adults with pulmonary impairments, and does so in a dose-response manner. This suggests that individuals with pulmonary impairments should be encouraged to engage in enjoyable, safe forms of physical activity in a progressive manner. © 2013.

[Evaluation of estimation of prevalence ratio using bayesian log-binomial regression model].

PubMed

Gao, W L; Lin, H; Liu, X N; Ren, X W; Li, J S; Shen, X P; Zhu, S L

2017-03-10

To evaluate the estimation of prevalence ratio ( PR ) by using bayesian log-binomial regression model and its application, we estimated the PR of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea in their infants by using bayesian log-binomial regression model in Openbugs software. The results showed that caregivers' recognition of infant' s risk signs of diarrhea was associated significantly with a 13% increase of medical care-seeking. Meanwhile, we compared the differences in PR 's point estimation and its interval estimation of medical care-seeking prevalence to caregivers' recognition of risk signs of diarrhea and convergence of three models (model 1: not adjusting for the covariates; model 2: adjusting for duration of caregivers' education, model 3: adjusting for distance between village and township and child month-age based on model 2) between bayesian log-binomial regression model and conventional log-binomial regression model. The results showed that all three bayesian log-binomial regression models were convergence and the estimated PRs were 1.130(95 %CI : 1.005-1.265), 1.128(95 %CI : 1.001-1.264) and 1.132(95 %CI : 1.004-1.267), respectively. Conventional log-binomial regression model 1 and model 2 were convergence and their PRs were 1.130(95 % CI : 1.055-1.206) and 1.126(95 % CI : 1.051-1.203), respectively, but the model 3 was misconvergence, so COPY method was used to estimate PR , which was 1.125 (95 %CI : 1.051-1.200). In addition, the point estimation and interval estimation of PRs from three bayesian log-binomial regression models differed slightly from those of PRs from conventional log-binomial regression model, but they had a good consistency in estimating PR . Therefore, bayesian log-binomial regression model can effectively estimate PR with less misconvergence and have more advantages in application compared with conventional log-binomial regression model.

Alternative evaluation metrics for risk adjustment methods.

PubMed

Park, Sungchul; Basu, Anirban

2018-06-01

Risk adjustment is instituted to counter risk selection by accurately equating payments with expected expenditures. Traditional risk-adjustment methods are designed to estimate accurate payments at the group level. However, this generates residual risks at the individual level, especially for high-expenditure individuals, thereby inducing health plans to avoid those with high residual risks. To identify an optimal risk-adjustment method, we perform a comprehensive comparison of prediction accuracies at the group level, at the tail distributions, and at the individual level across 19 estimators: 9 parametric regression, 7 machine learning, and 3 distributional estimators. Using the 2013-2014 MarketScan database, we find that no one estimator performs best in all prediction accuracies. Generally, machine learning and distribution-based estimators achieve higher group-level prediction accuracy than parametric regression estimators. However, parametric regression estimators show higher tail distribution prediction accuracy and individual-level prediction accuracy, especially at the tails of the distribution. This suggests that there is a trade-off in selecting an appropriate risk-adjustment method between estimating accurate payments at the group level and lower residual risks at the individual level. Our results indicate that an optimal method cannot be determined solely on the basis of statistical metrics but rather needs to account for simulating plans' risk selective behaviors. Copyright © 2018 John Wiley & Sons, Ltd.

Waste generated in high-rise buildings construction: a quantification model based on statistical multiple regression.

PubMed

Parisi Kern, Andrea; Ferreira Dias, Michele; Piva Kulakowski, Marlova; Paulo Gomes, Luciana

2015-05-01

Reducing construction waste is becoming a key environmental issue in the construction industry. The quantification of waste generation rates in the construction sector is an invaluable management tool in supporting mitigation actions. However, the quantification of waste can be a difficult process because of the specific characteristics and the wide range of materials used in different construction projects. Large variations are observed in the methods used to predict the amount of waste generated because of the range of variables involved in construction processes and the different contexts in which these methods are employed. This paper proposes a statistical model to determine the amount of waste generated in the construction of high-rise buildings by assessing the influence of design process and production system, often mentioned as the major culprits behind the generation of waste in construction. Multiple regression was used to conduct a case study based on multiple sources of data of eighteen residential buildings. The resulting statistical model produced dependent (i.e. amount of waste generated) and independent variables associated with the design and the production system used. The best regression model obtained from the sample data resulted in an adjusted R(2) value of 0.694, which means that it predicts approximately 69% of the factors involved in the generation of waste in similar constructions. Most independent variables showed a low determination coefficient when assessed in isolation, which emphasizes the importance of assessing their joint influence on the response (dependent) variable. Copyright © 2015 Elsevier Ltd. All rights reserved.

Bayesian dose-response analysis for epidemiological studies with complex uncertainty in dose estimation.

PubMed

Kwon, Deukwoo; Hoffman, F Owen; Moroz, Brian E; Simon, Steven L

2016-02-10

Most conventional risk analysis methods rely on a single best estimate of exposure per person, which does not allow for adjustment for exposure-related uncertainty. Here, we propose a Bayesian model averaging method to properly quantify the relationship between radiation dose and disease outcomes by accounting for shared and unshared uncertainty in estimated dose. Our Bayesian risk analysis method utilizes multiple realizations of sets (vectors) of doses generated by a two-dimensional Monte Carlo simulation method that properly separates shared and unshared errors in dose estimation. The exposure model used in this work is taken from a study of the risk of thyroid nodules among a cohort of 2376 subjects who were exposed to fallout from nuclear testing in Kazakhstan. We assessed the performance of our method through an extensive series of simulations and comparisons against conventional regression risk analysis methods. When the estimated doses contain relatively small amounts of uncertainty, the Bayesian method using multiple a priori plausible draws of dose vectors gave similar results to the conventional regression-based methods of dose-response analysis. However, when large and complex mixtures of shared and unshared uncertainties are present, the Bayesian method using multiple dose vectors had significantly lower relative bias than conventional regression-based risk analysis methods and better coverage, that is, a markedly increased capability to include the true risk coefficient within the 95% credible interval of the Bayesian-based risk estimate. An evaluation of the dose-response using our method is presented for an epidemiological study of thyroid disease following radiation exposure. Copyright © 2015 John Wiley & Sons, Ltd.

Association of Stressful Life Events with Psychological Problems: A Large-Scale Community-Based Study Using Grouped Outcomes Latent Factor Regression with Latent Predictors

PubMed Central

Hassanzadeh, Akbar; Heidari, Zahra; Hassanzadeh Keshteli, Ammar; Afshar, Hamid

2017-01-01

Objective The current study is aimed at investigating the association between stressful life events and psychological problems in a large sample of Iranian adults. Method In a cross-sectional large-scale community-based study, 4763 Iranian adults, living in Isfahan, Iran, were investigated. Grouped outcomes latent factor regression on latent predictors was used for modeling the association of psychological problems (depression, anxiety, and psychological distress), measured by Hospital Anxiety and Depression Scale (HADS) and General Health Questionnaire (GHQ-12), as the grouped outcomes, and stressful life events, measured by a self-administered stressful life events (SLEs) questionnaire, as the latent predictors. Results The results showed that the personal stressors domain has significant positive association with psychological distress (β = 0.19), anxiety (β = 0.25), depression (β = 0.15), and their collective profile score (β = 0.20), with greater associations in females (β = 0.28) than in males (β = 0.13) (all P < 0.001). In addition, in the adjusted models, the regression coefficients for the association of social stressors domain and psychological problems profile score were 0.37, 0.35, and 0.46 in total sample, males, and females, respectively (P < 0.001). Conclusion Results of our study indicated that different stressors, particularly those socioeconomic related, have an effective impact on psychological problems. It is important to consider the social and cultural background of a population for managing the stressors as an effective approach for preventing and reducing the destructive burden of psychological problems. PMID:29312459

Attitudes Toward Nursing Students With Disabilities: Promoting Social Inclusion.

PubMed

Shpigelman, Carmit-Noa; Zlotnick, Cheryl; Brand, Rachel

2016-08-01

Nursing education programs rarely refer to individuals with disabilities as potential nursing students; more often, the assumption is that they are patients. Thus, this study aimed to capture nursing students' perspectives of social inclusion through examination of their attitudes toward nursing student colleagues with disabilities. Paper-and-pencil structured surveys containing two validated scales were collected from Israeli nursing students (N = 270). Analyses included measuring associations using Pearson's correlation coefficient and general linear regression models. Nursing students held relatively negative attitudes toward colleagues with disabilities, and these negative attitudes were correlated to attitudes toward people with disabilities in general, even after adjusting for noted confounders. Nurse educators and nursing students should be aware of prejudicial attitudes with their respective communities toward nursing student colleagues with disabilities, and they should work toward a better understanding that cultural competence and awareness extends not only to patients but also to one's colleagues. [J Nurs Educ. 2016;55(8):441-449.]. Copyright 2016, SLACK Incorporated.

[Influence of income on food expenditures away from home among Brazilian families, 2002-2003].

PubMed

Claro, Rafael Moreira; Levy, Renata Bertazzi; Bandoni, Daniel Henrique

2009-11-01

This study describes and evaluates the influence of income on the percentage of food expenditures away from home for Brazilian families. Food acquisition data from the National Household Budget Survey conducted from 2002 to 2003 (POF 2002/2003) by the Brazilian Institute of Geography and Statistics (IBGE) or National Census Bureau was used in the analysis. Information on food-and-drink expenditures away from home was analyzed. The influence of income on the share of food purchased away from home in the household budget, adjusted for socio-demographic variables, was analyzed through elasticity coefficients estimated in multiple linear regression. Food purchased away from home accounted for 21% of total food expenditures by Brazilian households. A 10% increase in income increased the share of food purchased away from home by 3%. Income elasticity was high, especially for the lowest income families. The results demonstrate an important influence of income on food expenditures away from home, and higher income is associated with a greater share of food purchased away from home.