Using within-day hive weight changes to measure environmental effects on honey bee colonies

USDA-ARS?s Scientific Manuscript database

Patterns in within-day hive weight data from two independent datasets in Arizona and California were modeled using piecewise regression, and analyzed with respect to honey bee colony behavior and landscape effects. The regression analysis yielded information on the start and finish of a colony’s dai...

Identification of extremely premature infants at high risk of rehospitalization.

PubMed

Ambalavanan, Namasivayam; Carlo, Waldemar A; McDonald, Scott A; Yao, Qing; Das, Abhik; Higgins, Rosemary D

2011-11-01

Extremely low birth weight infants often require rehospitalization during infancy. Our objective was to identify at the time of discharge which extremely low birth weight infants are at higher risk for rehospitalization. Data from extremely low birth weight infants in Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network centers from 2002-2005 were analyzed. The primary outcome was rehospitalization by the 18- to 22-month follow-up, and secondary outcome was rehospitalization for respiratory causes in the first year. Using variables and odds ratios identified by stepwise logistic regression, scoring systems were developed with scores proportional to odds ratios. Classification and regression-tree analysis was performed by recursive partitioning and automatic selection of optimal cutoff points of variables. A total of 3787 infants were evaluated (mean ± SD birth weight: 787 ± 136 g; gestational age: 26 ± 2 weeks; 48% male, 42% black). Forty-five percent of the infants were rehospitalized by 18 to 22 months; 14.7% were rehospitalized for respiratory causes in the first year. Both regression models (area under the curve: 0.63) and classification and regression-tree models (mean misclassification rate: 40%-42%) were moderately accurate. Predictors for the primary outcome by regression were shunt surgery for hydrocephalus, hospital stay of >120 days for pulmonary reasons, necrotizing enterocolitis stage II or higher or spontaneous gastrointestinal perforation, higher fraction of inspired oxygen at 36 weeks, and male gender. By classification and regression-tree analysis, infants with hospital stays of >120 days for pulmonary reasons had a 66% rehospitalization rate compared with 42% without such a stay. The scoring systems and classification and regression-tree analysis models identified infants at higher risk of rehospitalization and might assist planning for care after discharge.

Identification of Extremely Premature Infants at High Risk of Rehospitalization

PubMed Central

Carlo, Waldemar A.; McDonald, Scott A.; Yao, Qing; Das, Abhik; Higgins, Rosemary D.

2011-01-01

OBJECTIVE: Extremely low birth weight infants often require rehospitalization during infancy. Our objective was to identify at the time of discharge which extremely low birth weight infants are at higher risk for rehospitalization. METHODS: Data from extremely low birth weight infants in Eunice Kennedy Shriver National Institute of Child Health and Human Development Neonatal Research Network centers from 2002–2005 were analyzed. The primary outcome was rehospitalization by the 18- to 22-month follow-up, and secondary outcome was rehospitalization for respiratory causes in the first year. Using variables and odds ratios identified by stepwise logistic regression, scoring systems were developed with scores proportional to odds ratios. Classification and regression-tree analysis was performed by recursive partitioning and automatic selection of optimal cutoff points of variables. RESULTS: A total of 3787 infants were evaluated (mean ± SD birth weight: 787 ± 136 g; gestational age: 26 ± 2 weeks; 48% male, 42% black). Forty-five percent of the infants were rehospitalized by 18 to 22 months; 14.7% were rehospitalized for respiratory causes in the first year. Both regression models (area under the curve: 0.63) and classification and regression-tree models (mean misclassification rate: 40%–42%) were moderately accurate. Predictors for the primary outcome by regression were shunt surgery for hydrocephalus, hospital stay of >120 days for pulmonary reasons, necrotizing enterocolitis stage II or higher or spontaneous gastrointestinal perforation, higher fraction of inspired oxygen at 36 weeks, and male gender. By classification and regression-tree analysis, infants with hospital stays of >120 days for pulmonary reasons had a 66% rehospitalization rate compared with 42% without such a stay. CONCLUSIONS: The scoring systems and classification and regression-tree analysis models identified infants at higher risk of rehospitalization and might assist planning for care after discharge. PMID:22007016

Abdominal girth, vertebral column length, and spread of spinal anesthesia in 30 minutes after plain bupivacaine 5 mg/mL.

PubMed

Zhou, Qing-he; Xiao, Wang-pin; Shen, Ying-yan

2014-07-01

The spread of spinal anesthesia is highly unpredictable. In patients with increased abdominal girth and short stature, a greater cephalad spread after a fixed amount of subarachnoidally administered plain bupivacaine is often observed. We hypothesized that there is a strong correlation between abdominal girth/vertebral column length and cephalad spread. Age, weight, height, body mass index, abdominal girth, and vertebral column length were recorded for 114 patients. The L3-L4 interspace was entered, and 3 mL of 0.5% plain bupivacaine was injected into the subarachnoid space. The cephalad spread (loss of temperature sensation and loss of pinprick discrimination) was assessed 30 minutes after intrathecal injection. Linear regression analysis was performed for age, weight, height, body mass index, abdominal girth, vertebral column length, and the spread of spinal anesthesia, and the combined linear contribution of age up to 55 years, weight, height, abdominal girth, and vertebral column length was tested by multiple regression analysis. Linear regression analysis showed that there was a significant univariate correlation among all 6 patient characteristics evaluated and the spread of spinal anesthesia (all P < 0.039) except for age and loss of temperature sensation (P > 0.068). Multiple regression analysis showed that abdominal girth and the vertebral column length were the key determinants for spinal anesthesia spread (both P < 0.0001), whereas age, weight, and height could be omitted without changing the results (all P > 0.059, all 95% confidence limits < 0.372). Multiple regression analysis revealed that the combination of a patient's 5 general characteristics, especially abdominal girth and vertebral column length, had a high predictive value for the spread of spinal anesthesia after a given dose of plain bupivacaine.

Validating the absolute reliability of a fat free mass estimate equation in hemodialysis patients using near-infrared spectroscopy.

PubMed

Kono, Kenichi; Nishida, Yusuke; Moriyama, Yoshihumi; Taoka, Masahiro; Sato, Takashi

2015-06-01

The assessment of nutritional states using fat free mass (FFM) measured with near-infrared spectroscopy (NIRS) is clinically useful. This measurement should incorporate the patient's post-dialysis weight ("dry weight"), in order to exclude the effects of any change in water mass. We therefore used NIRS to investigate the regression, independent variables, and absolute reliability of FFM in dry weight. The study included 47 outpatients from the hemodialysis unit. Body weight was measured before dialysis, and FFM was measured using NIRS before and after dialysis treatment. Multiple regression analysis was used to estimate the FFM in dry weight as the dependent variable. The measured FFM before dialysis treatment (Mw-FFM), and the difference between measured and dry weight (Mw-Dw) were independent variables. We performed Bland-Altman analysis to detect errors between the statistically estimated FFM and the measured FFM after dialysis treatment. The multiple regression equation to estimate the FFM in dry weight was: Dw-FFM = 0.038 + (0.984 × Mw-FFM) + (-0.571 × [Mw-Dw]); R(2)  = 0.99). There was no systematic bias between the estimated and the measured values of FFM in dry weight. Using NIRS, FFM in dry weight can be calculated by an equation including FFM in measured weight and the difference between the measured weight and the dry weight. © 2015 The Authors. Therapeutic Apheresis and Dialysis © 2015 International Society for Apheresis.

Spatio-temporal water quality mapping from satellite images using geographically and temporally weighted regression

NASA Astrophysics Data System (ADS)

Chu, Hone-Jay; Kong, Shish-Jeng; Chang, Chih-Hua

2018-03-01

The turbidity (TB) of a water body varies with time and space. Water quality is traditionally estimated via linear regression based on satellite images. However, estimating and mapping water quality require a spatio-temporal nonstationary model, while TB mapping necessitates the use of geographically and temporally weighted regression (GTWR) and geographically weighted regression (GWR) models, both of which are more precise than linear regression. Given the temporal nonstationary models for mapping water quality, GTWR offers the best option for estimating regional water quality. Compared with GWR, GTWR provides highly reliable information for water quality mapping, boasts a relatively high goodness of fit, improves the explanation of variance from 44% to 87%, and shows a sufficient space-time explanatory power. The seasonal patterns of TB and the main spatial patterns of TB variability can be identified using the estimated TB maps from GTWR and by conducting an empirical orthogonal function (EOF) analysis.

Nutritional status and weight gain in pregnant women.

PubMed

Sato, Ana Paula Sayuri; Fujimori, Elizabeth

2012-01-01

This study described the nutritional status of 228 pregnant women and the influence of this on birth weight. This is a retrospective study, developed in a health center in the municipality of São Paulo, with data obtained from medical records. Linear regression analysis was carried out. An association was verified between the initial and final nutritional status (p<0.001). The mean of total weight gain in the pregnant women who began the pregnancy underweight was higher compared those who started overweight/obese (p=0.005). Weight gain was insufficient for 43.4% of the pregnant women with adequate initial weight and for 36.4% of all the pregnant women studied. However, 37.1% of those who began the pregnancy overweight/obese finished with excessive weight gain, a condition that ultimately affected almost a quarter of the pregnant women. Anemia and low birth weight were uncommon, however, in the linear regression analysis, birth weight was associated with weight gain (p<0.05). The study highlights the importance of nutritional care before and during pregnancy to promote maternal-infant health.

Total body weight loss of ≥ 10 % is associated with improved hepatic fibrosis in patients with nonalcoholic steatohepatitis.

PubMed

Glass, Lisa M; Dickson, Rolland C; Anderson, Joseph C; Suriawinata, Arief A; Putra, Juan; Berk, Brian S; Toor, Arifa

2015-04-01

Given the rising epidemics of obesity and metabolic syndrome, nonalcoholic steatohepatitis (NASH) is now the most common cause of liver disease in the developed world. Effective treatment for NASH, either to reverse or prevent the progression of hepatic fibrosis, is currently lacking. To define the predictors associated with improved hepatic fibrosis in NASH patients undergoing serial liver biopsies at prolonged biopsy interval. This is a cohort study of 45 NASH patients undergoing serial liver biopsies for clinical monitoring in a tertiary care setting. Biopsies were scored using the NASH Clinical Research Network guidelines. Fibrosis regression was defined as improvement in fibrosis score ≥1 stage. Univariate analysis utilized Fisher's exact or Student's t test. Multivariate regression models determined independent predictors for regression of fibrosis. Forty-five NASH patients with biopsies collected at a mean interval of 4.6 years (±1.4) were included. The mean initial fibrosis stage was 1.96, two patients had cirrhosis and 12 patients (26.7 %) underwent bariatric surgery. There was a significantly higher rate of fibrosis regression among patients who lost ≥10 % total body weight (TBW) (63.2 vs. 9.1 %; p = 0.001) and who underwent bariatric surgery (47.4 vs. 4.5 %; p = 0.003). Factors such as age, gender, glucose intolerance, elevated ferritin, and A1AT heterozygosity did not influence fibrosis regression. On multivariate analysis, only weight loss of ≥10 % TBW predicted fibrosis regression [OR 8.14 (CI 1.08-61.17)]. Results indicate that regression of fibrosis in NASH is possible, even in advanced stages. Weight loss of ≥10 % TBW predicts fibrosis regression.

Role of anthropometric data in the prediction of 4-stranded hamstring graft size in anterior cruciate ligament reconstruction.

PubMed

Ho, Sean Wei Loong; Tan, Teong Jin Lester; Lee, Keng Thiam

2016-03-01

To evaluate whether pre-operative anthropometric data can predict the optimal diameter and length of hamstring tendon autograft for anterior cruciate ligament (ACL) reconstruction. This was a cohort study that involved 169 patients who underwent single-bundle ACL reconstruction (single surgeon) with 4-stranded MM Gracilis and MM Semi-Tendinosus autografts. Height, weight, body mass index (BMI), gender, race, age and -smoking status were recorded pre-operatively. Intra-operatively, the diameter and functional length of the 4-stranded autograft was recorded. Multiple regression analysis was used to determine the relationship between the anthropometric measurements and the length and diameter of the implanted autografts. The strongest correlation between 4-stranded hamstring autograft diameter was height and weight. This correlation was stronger in females than males. BMI had a moderate correlation with the diameter of the graft in females. Females had a significantly smaller graft both in diameter and length when compared with males. Linear regression models did not show any significant correlation between hamstring autograft length with height and weight (p>0.05). Simple regression analysis demonstrated that height and weight can be used to predict hamstring graft diameter. The following regression equation was obtained for females: Graft diameter=0.012+0.034*Height+0.026*Weight (R2=0.358, p=0.004) The following regression equation was obtained for males: Graft diameter=5.130+0.012*Height+0.007*Weight (R2=0.086, p=0.002). Pre-operative anthropometric data has a positive correlation with the diameter of 4 stranded hamstring autografts but no significant correlation with the length. This data can be utilised to predict the autograft diameter and may be useful for pre-operative planning and patient counseling for graft selection.

Use of factor scores for predicting body weight from linear body measurements in three South African indigenous chicken breeds.

PubMed

Malomane, Dorcus Kholofelo; Norris, David; Banga, Cuthbert B; Ngambi, Jones W

2014-02-01

Body weight and weight of body parts are of economic importance. It is difficult to directly predict body weight from highly correlated morphological traits through multiple regression. Factor analysis was carried out to examine the relationship between body weight and five linear body measurements (body length, body girth, wing length, shank thickness, and shank length) in South African Venda (VN), Naked neck (NN), and Potchefstroom koekoek (PK) indigenous chicken breeds, with a view to identify those factors that define body conformation. Multiple regression was subsequently performed to predict body weight, using orthogonal traits derived from the factor analysis. Measurements were obtained from 210 chickens, 22 weeks of age, 70 chickens per breed. High correlations were obtained between body weight and all body measurements except for wing length in PK. Two factors extracted after varimax rotation explained 91, 95, and 83% of total variation in VN, NN, and PK, respectively. Factor 1 explained 73, 90, and 64% in VN, NN, and PK, respectively, and was loaded on all body measurements except for wing length in VN and PK. In a multiple regression, these two factors accounted for 72% variation in body weight in VN, while only factor 1 accounted for 83 and 74% variation in body weight in NN and PK, respectively. The two factors could be used to define body size and conformation of these breeds. Factor 1 could predict body weight in all three breeds. Body measurements can be better selected jointly to improve body weight in these breeds.

Robust mislabel logistic regression without modeling mislabel probabilities.

PubMed

Hung, Hung; Jou, Zhi-Yu; Huang, Su-Yun

2018-03-01

Logistic regression is among the most widely used statistical methods for linear discriminant analysis. In many applications, we only observe possibly mislabeled responses. Fitting a conventional logistic regression can then lead to biased estimation. One common resolution is to fit a mislabel logistic regression model, which takes into consideration of mislabeled responses. Another common method is to adopt a robust M-estimation by down-weighting suspected instances. In this work, we propose a new robust mislabel logistic regression based on γ-divergence. Our proposal possesses two advantageous features: (1) It does not need to model the mislabel probabilities. (2) The minimum γ-divergence estimation leads to a weighted estimating equation without the need to include any bias correction term, that is, it is automatically bias-corrected. These features make the proposed γ-logistic regression more robust in model fitting and more intuitive for model interpretation through a simple weighting scheme. Our method is also easy to implement, and two types of algorithms are included. Simulation studies and the Pima data application are presented to demonstrate the performance of γ-logistic regression. © 2017, The International Biometric Society.

Vitrified-warmed embryo transfer is associated with mean higher singleton birth weight compared to fresh embryo transfer.

PubMed

Beyer, Daniel Alexander; Griesinger, Georg

2016-08-01

To test for differences in birth weight between singletons born after IVF with fresh embryo transfer vs. vitrified-warmed 2PN embryo transfer (vitrification protocol). Retrospective analysis of 464 singleton live births after IVF or ICSI during a 12 year period. University hospital. Fresh embryo transfer, vitrified-warmed 2PN embryo transfer (vitrification protocol). Birth weight standardized as a z-score, adjusting for gestational week at delivery and fetal sex. As a reference, birth weight means from regular deliveries from the same hospital were used. Multivariate regression analysis was used to investigate the relationship between the dependent variable z-score (fetal birth weight) and the independent predictor variables maternal age, weight, height, body mass index, RDS prophylaxis, transfer protocol, number of embryos transferred, indication for IVF treatment and sperm quality. The mean z-score was significantly lower after fresh transfer (-0.11±92) as compared to vitrification transfer (0.72±83) (p<0.001). Multivariate regression analysis indicated that only maternal height and maternal body mass index, but not type of cryopreservation protocol, was a significant predictor of birth weight. In this analysis focusing on 2PN oocytes, vitrified-warmed embryo transfer is associated with mean higher birth weight compared to fresh embryo transfer. Maternal height and body mass index are significant confounders of fetal birth weight and need to be taken into account when studying birth weight differences between ART protocols. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

Genetic analysis of body weights of individually fed beef bulls in South Africa using random regression models.

PubMed

Selapa, N W; Nephawe, K A; Maiwashe, A; Norris, D

2012-02-08

The aim of this study was to estimate genetic parameters for body weights of individually fed beef bulls measured at centralized testing stations in South Africa using random regression models. Weekly body weights of Bonsmara bulls (N = 2919) tested between 1999 and 2003 were available for the analyses. The model included a fixed regression of the body weights on fourth-order orthogonal Legendre polynomials of the actual days on test (7, 14, 21, 28, 35, 42, 49, 56, 63, 70, 77, and 84) for starting age and contemporary group effects. Random regressions on fourth-order orthogonal Legendre polynomials of the actual days on test were included for additive genetic effects and additional uncorrelated random effects of the weaning-herd-year and the permanent environment of the animal. Residual effects were assumed to be independently distributed with heterogeneous variance for each test day. Variance ratios for additive genetic, permanent environment and weaning-herd-year for weekly body weights at different test days ranged from 0.26 to 0.29, 0.37 to 0.44 and 0.26 to 0.34, respectively. The weaning-herd-year was found to have a significant effect on the variation of body weights of bulls despite a 28-day adjustment period. Genetic correlations amongst body weights at different test days were high, ranging from 0.89 to 1.00. Heritability estimates were comparable to literature using multivariate models. Therefore, random regression model could be applied in the genetic evaluation of body weight of individually fed beef bulls in South Africa.

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…

Association Between Monetary Deposits and Weight Loss in Online Commitment Contracts

PubMed Central

Lesser, Lenard I.; Thompson, Caroline A.; Luft, Harold S.

2017-01-01

Purpose To examine the characteristics of voluntary online commitment contracts that may be associated with greater weight loss. Design Retrospective analysis of weight loss commitment contracts derived from a company that provides web-based support for personal commitment contracts. Using regression, we analyzed whether percentage weight loss differed between participants who incentivized their contract using monetary deposits and those who did not. Setting Online. Participants Users (N = 3857) who voluntarily signed up online in 2013 for a weight loss contract. Intervention Participants specified their own weight loss goal, time period, and self-reported weekly weight. Deposits were available in the following 3 categories: charity, anticharity (a nonprofit one does not like), or donations made to a friend. Measures Percentage weight loss per week. Analysis Multivariable linear regressions. Results Controlling for several participant and contract characteristics, contracts with anticharity, charity, and friend deposits had greater reported weight loss than nonincentivized contracts. Weight change per week relative to those without deposits was −0.33%, −0.28%, and −0.25% for anti-charity, charity, and friend, respectively (P < 0.001). Contracts without a weight verification method claimed more weight loss than those with verification. Conclusion Voluntary use of commitment contracts may be an effective tool to assist weight loss. Those who choose to use monetary incentives report more weight loss. It is not clear whether this is due to the incentives or higher motivation. PMID:27502832

A New Global Regression Analysis Method for the Prediction of Wind Tunnel Model Weight Corrections

NASA Technical Reports Server (NTRS)

Ulbrich, Norbert Manfred; Bridge, Thomas M.; Amaya, Max A.

2014-01-01

A new global regression analysis method is discussed that predicts wind tunnel model weight corrections for strain-gage balance loads during a wind tunnel test. The method determines corrections by combining "wind-on" model attitude measurements with least squares estimates of the model weight and center of gravity coordinates that are obtained from "wind-off" data points. The method treats the least squares fit of the model weight separate from the fit of the center of gravity coordinates. Therefore, it performs two fits of "wind- off" data points and uses the least squares estimator of the model weight as an input for the fit of the center of gravity coordinates. Explicit equations for the least squares estimators of the weight and center of gravity coordinates are derived that simplify the implementation of the method in the data system software of a wind tunnel. In addition, recommendations for sets of "wind-off" data points are made that take typical model support system constraints into account. Explicit equations of the confidence intervals on the model weight and center of gravity coordinates and two different error analyses of the model weight prediction are also discussed in the appendices of the paper.

Application of geographically-weighted regression analysis to assess risk factors for malaria hotspots in Keur Soce health and demographic surveillance site.

PubMed

Ndiath, Mansour M; Cisse, Badara; Ndiaye, Jean Louis; Gomis, Jules F; Bathiery, Ousmane; Dia, Anta Tal; Gaye, Oumar; Faye, Babacar

2015-11-18

In Senegal, considerable efforts have been made to reduce malaria morbidity and mortality during the last decade. This resulted in a marked decrease of malaria cases. With the decline of malaria cases, transmission has become sparse in most Senegalese health districts. This study investigated malaria hotspots in Keur Soce sites by using geographically-weighted regression. Because of the occurrence of hotspots, spatial modelling of malaria cases could have a considerable effect in disease surveillance. This study explored and analysed the spatial relationships between malaria occurrence and socio-economic and environmental factors in small communities in Keur Soce, Senegal, using 6 months passive surveillance. Geographically-weighted regression was used to explore the spatial variability of relationships between malaria incidence or persistence and the selected socio-economic, and human predictors. A model comparison of between ordinary least square and geographically-weighted regression was also explored. Vector dataset (spatial) of the study area by village levels and statistical data (non-spatial) on malaria confirmed cases, socio-economic status (bed net use), population data (size of the household) and environmental factors (temperature, rain fall) were used in this exploratory analysis. ArcMap 10.2 and Stata 11 were used to perform malaria hotspots analysis. From Jun to December, a total of 408 confirmed malaria cases were notified. The explanatory variables-household size, housing materials, sleeping rooms, sheep and distance to breeding site returned significant t values of -0.25, 2.3, 4.39, 1.25 and 2.36, respectively. The OLS global model revealed that it explained about 70 % (adjusted R(2) = 0.70) of the variation in malaria occurrence with AIC = 756.23. The geographically-weighted regression of malaria hotspots resulted in coefficient intercept ranging from 1.89 to 6.22 with a median of 3.5. Large positive values are distributed mainly in the southeast of the district where hotspots are more accurate while low values are mainly found in the centre and in the north. Geographically-weighted regression and OLS showed important risks factors of malaria hotspots in Keur Soce. The outputs of such models can be a useful tool to understand occurrence of malaria hotspots in Senegal. An understanding of geographical variation and determination of the core areas of the disease may provide an explanation regarding possible proximal and distal contributors to malaria elimination in Senegal.

Animal models of maternal high fat diet exposure and effects on metabolism in offspring: a meta-regression analysis.

PubMed

Ribaroff, G A; Wastnedge, E; Drake, A J; Sharpe, R M; Chambers, T J G

2017-06-01

Animal models of maternal high fat diet (HFD) demonstrate perturbed offspring metabolism although the effects differ markedly between models. We assessed studies investigating metabolic parameters in the offspring of HFD fed mothers to identify factors explaining these inter-study differences. A total of 171 papers were identified, which provided data from 6047 offspring. Data were extracted regarding body weight, adiposity, glucose homeostasis and lipidaemia. Information regarding the macronutrient content of diet, species, time point of exposure and gestational weight gain were collected and utilized in meta-regression models to explore predictive factors. Publication bias was assessed using Egger's regression test. Maternal HFD exposure did not affect offspring birthweight but increased weaning weight, final bodyweight, adiposity, triglyceridaemia, cholesterolaemia and insulinaemia in both female and male offspring. Hyperglycaemia was found in female offspring only. Meta-regression analysis identified lactational HFD exposure as a key moderator. The fat content of the diet did not correlate with any outcomes. There was evidence of significant publication bias for all outcomes except birthweight. Maternal HFD exposure was associated with perturbed metabolism in offspring but between studies was not accounted for by dietary constituents, species, strain or maternal gestational weight gain. Specific weaknesses in experimental design predispose many of the results to bias. © 2017 The Authors. Obesity Reviews published by John Wiley & Sons Ltd on behalf of World Obesity Federation.

Neural Network and Regression Methods Demonstrated in the Design Optimization of a Subsonic Aircraft

NASA Technical Reports Server (NTRS)

Hopkins, Dale A.; Lavelle, Thomas M.; Patnaik, Surya

2003-01-01

The neural network and regression methods of NASA Glenn Research Center s COMETBOARDS design optimization testbed were used to generate approximate analysis and design models for a subsonic aircraft operating at Mach 0.85 cruise speed. The analytical model is defined by nine design variables: wing aspect ratio, engine thrust, wing area, sweep angle, chord-thickness ratio, turbine temperature, pressure ratio, bypass ratio, fan pressure; and eight response parameters: weight, landing velocity, takeoff and landing field lengths, approach thrust, overall efficiency, and compressor pressure and temperature. The variables were adjusted to optimally balance the engines to the airframe. The solution strategy included a sensitivity model and the soft analysis model. Researchers generated the sensitivity model by training the approximators to predict an optimum design. The trained neural network predicted all response variables, within 5-percent error. This was reduced to 1 percent by the regression method. The soft analysis model was developed to replace aircraft analysis as the reanalyzer in design optimization. Soft models have been generated for a neural network method, a regression method, and a hybrid method obtained by combining the approximators. The performance of the models is graphed for aircraft weight versus thrust as well as for wing area and turbine temperature. The regression method followed the analytical solution with little error. The neural network exhibited 5-percent maximum error over all parameters. Performance of the hybrid method was intermediate in comparison to the individual approximators. Error in the response variable is smaller than that shown in the figure because of a distortion scale factor. The overall performance of the approximators was considered to be satisfactory because aircraft analysis with NASA Langley Research Center s FLOPS (Flight Optimization System) code is a synthesis of diverse disciplines: weight estimation, aerodynamic analysis, engine cycle analysis, propulsion data interpolation, mission performance, airfield length for landing and takeoff, noise footprint, and others.

A comparative study on generating simulated Landsat NDVI images using data fusion and regression method-the case of the Korean Peninsula.

PubMed

Lee, Mi Hee; Lee, Soo Bong; Eo, Yang Dam; Kim, Sun Woong; Woo, Jung-Hun; Han, Soo Hee

2017-07-01

Landsat optical images have enough spatial and spectral resolution to analyze vegetation growth characteristics. But, the clouds and water vapor degrade the image quality quite often, which limits the availability of usable images for the time series vegetation vitality measurement. To overcome this shortcoming, simulated images are used as an alternative. In this study, weighted average method, spatial and temporal adaptive reflectance fusion model (STARFM) method, and multilinear regression analysis method have been tested to produce simulated Landsat normalized difference vegetation index (NDVI) images of the Korean Peninsula. The test results showed that the weighted average method produced the images most similar to the actual images, provided that the images were available within 1 month before and after the target date. The STARFM method gives good results when the input image date is close to the target date. Careful regional and seasonal consideration is required in selecting input images. During summer season, due to clouds, it is very difficult to get the images close enough to the target date. Multilinear regression analysis gives meaningful results even when the input image date is not so close to the target date. Average R 2 values for weighted average method, STARFM, and multilinear regression analysis were 0.741, 0.70, and 0.61, respectively.

Predictors of Dropout by Female Obese Patients Treated with a Group Cognitive Behavioral Therapy to Promote Weight Loss.

PubMed

Sawamoto, Ryoko; Nozaki, Takehiro; Furukawa, Tomokazu; Tanahashi, Tokusei; Morita, Chihiro; Hata, Tomokazu; Komaki, Gen; Sudo, Nobuyuki

2016-01-01

To investigate predictors of dropout from a group cognitive behavioral therapy (CBT) intervention for overweight or obese women. 119 overweight and obese Japanese women aged 25-65 years who attended an outpatient weight loss intervention were followed throughout the 7-month weight loss phase. Somatic characteristics, socioeconomic status, obesity-related diseases, diet and exercise habits, and psychological variables (depression, anxiety, self-esteem, alexithymia, parenting style, perfectionism, and eating attitude) were assessed at baseline. Significant variables, extracted by univariate statistical analysis, were then used as independent variables in a stepwise multiple logistic regression analysis with dropout as the dependent variable. 90 participants completed the weight loss phase, giving a dropout rate of 24.4%. The multiple logistic regression analysis demonstrated that compared to completers the dropouts had significantly stronger body shape concern, tended to not have jobs, perceived their mothers to be less caring, and were more disorganized in temperament. Of all these factors, the best predictor of dropout was shape concern. Shape concern, job condition, parenting care, and organization predicted dropout from the group CBT weight loss intervention for overweight or obese Japanese women. © 2016 S. Karger GmbH, Freiburg.

Predictors of Dropout by Female Obese Patients Treated with a Group Cognitive Behavioral Therapy to Promote Weight Loss

PubMed Central

Sawamoto, Ryoko; Nozaki, Takehiro; Furukawa, Tomokazu; Tanahashi, Tokusei; Morita, Chihiro; Hata, Tomokazu; Komaki, Gen; Sudo, Nobuyuki

2016-01-01

Objective To investigate predictors of dropout from a group cognitive behavioral therapy (CBT) intervention for overweight or obese women. Methods 119 overweight and obese Japanese women aged 25-65 years who attended an outpatient weight loss intervention were followed throughout the 7-month weight loss phase. Somatic characteristics, socioeconomic status, obesity-related diseases, diet and exercise habits, and psychological variables (depression, anxiety, self-esteem, alexithymia, parenting style, perfectionism, and eating attitude) were assessed at baseline. Significant variables, extracted by univariate statistical analysis, were then used as independent variables in a stepwise multiple logistic regression analysis with dropout as the dependent variable. Results 90 participants completed the weight loss phase, giving a dropout rate of 24.4%. The multiple logistic regression analysis demonstrated that compared to completers the dropouts had significantly stronger body shape concern, tended to not have jobs, perceived their mothers to be less caring, and were more disorganized in temperament. Of all these factors, the best predictor of dropout was shape concern. Conclusion Shape concern, job condition, parenting care, and organization predicted dropout from the group CBT weight loss intervention for overweight or obese Japanese women. PMID:26745715

Using twig diameters to estimate browse utilization on three shrub species in southeastern Montana

Treesearch

Mark A. Rumble

1987-01-01

Browse utilization estimates based on twig length and twig weight were compared for skunkbush sumac, wax currant, and chokecherry. Linear regression analysis was valid for twig length data; twig weight equations are nonlinear. Estimates of twig weight are more accurate. Problems encountered during development of a utilization model are discussed.

Effect of Workplace Weight Management on Health Care Expenditures and Quality of Life.

PubMed

Michaud, Tzeyu L; Nyman, John A; Jutkowitz, Eric; Su, Dejun; Dowd, Bryan; Abraham, Jean M

2016-11-01

We examined the effectiveness of the weight management program used by the University of Minnesota in reducing health care expenditures and improving quality of life of its employees, and also in reducing their absenteeism during a 3-year intervention. A differences-in-differences regression approach was used to estimate the effect of weight management participation. We further applied ordinary least squares regression models with fixed effects to estimate the effect in an alternative analysis. Participation in the weight management program significantly reduced health care expenditures by $69 per month for employees, spouses, and dependents, and by $73 for employees only. Quality-of-life weights were 0.0045 points higher for participating employees than for nonparticipating ones. No significant effect was found for absenteeism. The workplace weight management used by the University of Minnesota reduced health care expenditures and improved quality of life.

A reconnaissance method for delineation of tracts for regional-scale mineral-resource assessment based on geologic-map data

USGS Publications Warehouse

Raines, G.L.; Mihalasky, M.J.

2002-01-01

The U.S. Geological Survey (USGS) is proposing to conduct a global mineral-resource assessment using geologic maps, significant deposits, and exploration history as minimal data requirements. Using a geologic map and locations of significant pluton-related deposits, the pluton-related-deposit tract maps from the USGS national mineral-resource assessment have been reproduced with GIS-based analysis and modeling techniques. Agreement, kappa, and Jaccard's C correlation statistics between the expert USGS and calculated tract maps of 87%, 40%, and 28%, respectively, have been achieved using a combination of weights-of-evidence and weighted logistic regression methods. Between the experts' and calculated maps, the ranking of states measured by total permissive area correlates at 84%. The disagreement between the experts and calculated results can be explained primarily by tracts defined by geophysical evidence not considered in the calculations, generalization of tracts by the experts, differences in map scales, and the experts' inclusion of large tracts that are arguably not permissive. This analysis shows that tracts for regional mineral-resource assessment approximating those delineated by USGS experts can be calculated using weights of evidence and weighted logistic regression, a geologic map, and the location of significant deposits. Weights of evidence and weighted logistic regression applied to a global geologic map could provide quickly a useful reconnaissance definition of tracts for mineral assessment that is tied to the data and is reproducible. ?? 2002 International Association for Mathematical Geology.

Obesity and hypomagnesemia.

PubMed

Guerrero-Romero, Fernando; Flores-García, Araceli; Saldaña-Guerrero, Stephanie; Simental-Mendía, Luis E; Rodríguez-Morán, Martha

2016-10-01

Whether low serum magnesium is an epiphenomenon related with obesity or, whether obesity per se is cause of hypomagnesemia, remains to be clarified. To examine the relationship between body weight status and hypomagnesemia in apparently healthy subjects. A total of 681 healthy individuals aged 30 to 65years were enrolled in A cross-sectional study. Extreme exercise, chronic diarrhea, alcohol intake, use of diuretics, smoking, oral magnesium supplementation, diabetes, malnutrition, hypertension, liver disease, thyroid disorders, and renal damage were exclusion criteria. Based in the Body Mass Index (BMI), body weight status was defined as follows: normal weight (BMI <25kg/m 2 ); overweight (BMI ≥25<30 BMIkg/m 2 ); and obesity (BMI ≥30kg/m 2 ). Hypomagnesemia was defined by serum magnesium concentration ≤0.74mmol/L. A multiple logistic regression analysis was used to compute the odds ratio (OR) between body weight status (independent variables) and hypomagnesemia (dependent variable). The multivariate logistic regression analysis showed that dietary magnesium intake (OR 2.11; 95%CI 1.4-5.7) but no obesity (OR 1.53; 95%CI 0.9-2.5), overweight (OR 1.40; 95%CI 0.8-2.4), and normal weight (OR 0.78; 95%CI 0.6-2.09) were associated with hypomagnesemia. A subsequent logistic regression analysis adjusted by body mass index, waist circumference, total body fat, systolic and diastolic blood pressure, and triglycerides levels showed that hyperglycemia (2.19; 95%CI 1.1-7.0) and dietary magnesium intake (2.21; 95%CI 1.1-8.9) remained associated with hypomagnesemia. Our results show that body weight status is not associated with hypomagnesemia and that, irrespective of obesity, hyperglycemia is cause of hypomagnesemia in non-diabetic individuals. Copyright © 2016 European Federation of Internal Medicine. Published by Elsevier B.V. All rights reserved.

Modeling The Skeleton Weight of an Adult Caucasian Man.

PubMed

Avtandilashvili, Maia; Tolmachev, Sergei Y

2018-05-17

The reference value for the skeleton weight of an adult male (10.5 kg) recommended by the International Commission on Radiological Protection in Publication 70 is based on weights of dissected skeletons from 44 individuals, including two U.S. Transuranium and Uranium Registries whole-body donors. The International Commission on Radiological Protection analysis of anatomical data from 31 individuals with known values of body height demonstrated significant correlation between skeleton weight and body height. The corresponding regression equation, Wskel (kg) = -10.7 + 0.119 × H (cm), published in International Commission on Radiological Protection Publication 70 is typically used to estimate the skeleton weight from body height. Currently, the U.S. Transuranium and Uranium Registries holds data on individual bone weights from a total of 40 male whole-body donors, which has provided a unique opportunity to update the International Commission on Radiological Protection skeleton weight vs. body height equation. The original International Commission on Radiological Protection Publication 70 and the new U.S. Transuranium and Uranium Registries data were combined in a set of 69 data points representing a group of 33- to 95-y-old individuals with body heights and skeleton weights ranging from 155 to 188 cm and 6.5 to 13.4 kg, respectively. Data were fitted with a linear least-squares regression. A significant correlation between the two parameters was observed (r = 0.28), and an updated skeleton weight vs. body height equation was derived: Wskel (kg) = -6.5 + 0.093 × H (cm). In addition, a correlation of skeleton weight with multiple variables including body height, body weight, and age was evaluated using multiple regression analysis, and a corresponding fit equation was derived: Wskel (kg) = -0.25 + 0.046 × H (cm) + 0.036 × Wbody (kg) - 0.012 × A (y). These equations will be used to estimate skeleton weights and, ultimately, total skeletal actinide activities for biokinetic modeling of U.S. Transuranium and Uranium Registries partial-body donation cases.

Breeding value accuracy estimates for growth traits using random regression and multi-trait models in Nelore cattle.

PubMed

Boligon, A A; Baldi, F; Mercadante, M E Z; Lobo, R B; Pereira, R J; Albuquerque, L G

2011-06-28

We quantified the potential increase in accuracy of expected breeding value for weights of Nelore cattle, from birth to mature age, using multi-trait and random regression models on Legendre polynomials and B-spline functions. A total of 87,712 weight records from 8144 females were used, recorded every three months from birth to mature age from the Nelore Brazil Program. For random regression analyses, all female weight records from birth to eight years of age (data set I) were considered. From this general data set, a subset was created (data set II), which included only nine weight records: at birth, weaning, 365 and 550 days of age, and 2, 3, 4, 5, and 6 years of age. Data set II was analyzed using random regression and multi-trait models. The model of analysis included the contemporary group as fixed effects and age of dam as a linear and quadratic covariable. In the random regression analyses, average growth trends were modeled using a cubic regression on orthogonal polynomials of age. Residual variances were modeled by a step function with five classes. Legendre polynomials of fourth and sixth order were utilized to model the direct genetic and animal permanent environmental effects, respectively, while third-order Legendre polynomials were considered for maternal genetic and maternal permanent environmental effects. Quadratic polynomials were applied to model all random effects in random regression models on B-spline functions. Direct genetic and animal permanent environmental effects were modeled using three segments or five coefficients, and genetic maternal and maternal permanent environmental effects were modeled with one segment or three coefficients in the random regression models on B-spline functions. For both data sets (I and II), animals ranked differently according to expected breeding value obtained by random regression or multi-trait models. With random regression models, the highest gains in accuracy were obtained at ages with a low number of weight records. The results indicate that random regression models provide more accurate expected breeding values than the traditionally finite multi-trait models. Thus, higher genetic responses are expected for beef cattle growth traits by replacing a multi-trait model with random regression models for genetic evaluation. B-spline functions could be applied as an alternative to Legendre polynomials to model covariance functions for weights from birth to mature age.

Weight loss efficacy of a novel mobile Diabetes Prevention Program delivery platform with human coaching

PubMed Central

Michaelides, Andreas; Raby, Christine; Wood, Meghan; Farr, Kit

2016-01-01

Objective To evaluate the weight loss efficacy of a novel mobile platform delivering the Diabetes Prevention Program. Research Design and Methods 43 overweight or obese adult participants with a diagnosis of prediabetes signed-up to receive a 24-week virtual Diabetes Prevention Program with human coaching, through a mobile platform. Weight loss and engagement were the main outcomes, evaluated by repeated measures analysis of variance, backward regression, and mediation regression. Results Weight loss at 16 and 24 weeks was significant, with 56% of starters and 64% of completers losing over 5% body weight. Mean weight loss at 24 weeks was 6.58% in starters and 7.5% in completers. Participants were highly engaged, with 84% of the sample completing 9 lessons or more. In-app actions related to self-monitoring significantly predicted weight loss. Conclusions Our findings support the effectiveness of a uniquely mobile prediabetes intervention, producing weight loss comparable to studies with high engagement, with potential for scalable population health management. PMID:27651911

Height and Weight Estimation From Anthropometric Measurements Using Machine Learning Regressions

PubMed Central

Fernandes, Bruno J. T.; Roque, Alexandre

2018-01-01

Height and weight are measurements explored to tracking nutritional diseases, energy expenditure, clinical conditions, drug dosages, and infusion rates. Many patients are not ambulant or may be unable to communicate, and a sequence of these factors may not allow accurate estimation or measurements; in those cases, it can be estimated approximately by anthropometric means. Different groups have proposed different linear or non-linear equations which coefficients are obtained by using single or multiple linear regressions. In this paper, we present a complete study of the application of different learning models to estimate height and weight from anthropometric measurements: support vector regression, Gaussian process, and artificial neural networks. The predicted values are significantly more accurate than that obtained with conventional linear regressions. In all the cases, the predictions are non-sensitive to ethnicity, and to gender, if more than two anthropometric parameters are analyzed. The learning model analysis creates new opportunities for anthropometric applications in industry, textile technology, security, and health care. PMID:29651366

Weight estimation techniques for composite airplanes in general aviation industry

NASA Technical Reports Server (NTRS)

Paramasivam, T.; Horn, W. J.; Ritter, J.

1986-01-01

Currently available weight estimation methods for general aviation airplanes were investigated. New equations with explicit material properties were developed for the weight estimation of aircraft components such as wing, fuselage and empennage. Regression analysis was applied to the basic equations for a data base of twelve airplanes to determine the coefficients. The resulting equations can be used to predict the component weights of either metallic or composite airplanes.

Prediction model of critical weight loss in cancer patients during particle therapy.

PubMed

Zhang, Zhihong; Zhu, Yu; Zhang, Lijuan; Wang, Ziying; Wan, Hongwei

2018-01-01

The objective of this study is to investigate the predictors of critical weight loss in cancer patients receiving particle therapy, and build a prediction model based on its predictive factors. Patients receiving particle therapy were enroled between June 2015 and June 2016. Body weight was measured at the start and end of particle therapy. Association between critical weight loss (defined as >5%) during particle therapy and patients' demographic, clinical characteristic, pre-therapeutic nutrition risk screening (NRS 2002) and BMI were evaluated by logistic regression and decision tree analysis. Finally, 375 cancer patients receiving particle therapy were included. Mean weight loss was 0.55 kg, and 11.5% of patients experienced critical weight loss during particle therapy. The main predictors of critical weight loss during particle therapy were head and neck tumour location, total radiation dose ≥70 Gy on the primary tumour, and without post-surgery, as indicated by both logistic regression and decision tree analysis. Prediction model that includes tumour locations, total radiation dose and post-surgery had a good predictive ability, with the area under receiver operating characteristic curve 0.79 (95% CI: 0.71-0.88) and 0.78 (95% CI: 0.69-0.86) for decision tree and logistic regression model, respectively. Cancer patients with head and neck tumour location, total radiation dose ≥70 Gy and without post-surgery were at higher risk of critical weight loss during particle therapy, and early intensive nutrition counselling or intervention should be target at this population. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Estimating Available Fuel Weight Consumed by Prescribed Fires in the South

Treesearch

Walter A. Hough

1978-01-01

A method is proposed for estimating the weight of fuel burned (available fuel) by prescribed fires in southern pine stands. Weights of available fuel in litter alone and in litter plus understory materials can be estimated. Prediction equations were developed by regression analysis of data from a variety of locations and stand conditions. They are most reliable for...

Noncontact analysis of the fiber weight per unit area in prepreg by near-infrared spectroscopy.

PubMed

Jiang, B; Huang, Y D

2008-05-26

The fiber weight per unit area in prepreg is an important factor to ensure the quality of the composite products. Near-infrared spectroscopy (NIRS) technology together with a noncontact reflectance sources has been applied for quality analysis of the fiber weight per unit area. The range of the unit area fiber weight was 13.39-14.14mgcm(-2). The regression method was employed by partial least squares (PLS) and principal components regression (PCR). The calibration model was developed by 55 samples to determine the fiber weight per unit area in prepreg. The determination coefficient (R(2)), root mean square error of calibration (RMSEC) and root mean square error of prediction (RMSEP) were 0.82, 0.092, 0.099, respectively. The predicted values of the fiber weight per unit area in prepreg measured by NIRS technology were comparable to the values obtained by the reference method. For this technology, the noncontact reflectance sources focused directly on the sample with neither previous treatment nor manipulation. The results of the paired t-test revealed that there was no significant difference between the NIR method and the reference method. Besides, the prepreg could be analyzed one time within 20s without sample destruction.

A menu-driven software package of Bayesian nonparametric (and parametric) mixed models for regression analysis and density estimation.

PubMed

Karabatsos, George

2017-02-01

Most of applied statistics involves regression analysis of data. In practice, it is important to specify a regression model that has minimal assumptions which are not violated by data, to ensure that statistical inferences from the model are informative and not misleading. This paper presents a stand-alone and menu-driven software package, Bayesian Regression: Nonparametric and Parametric Models, constructed from MATLAB Compiler. Currently, this package gives the user a choice from 83 Bayesian models for data analysis. They include 47 Bayesian nonparametric (BNP) infinite-mixture regression models; 5 BNP infinite-mixture models for density estimation; and 31 normal random effects models (HLMs), including normal linear models. Each of the 78 regression models handles either a continuous, binary, or ordinal dependent variable, and can handle multi-level (grouped) data. All 83 Bayesian models can handle the analysis of weighted observations (e.g., for meta-analysis), and the analysis of left-censored, right-censored, and/or interval-censored data. Each BNP infinite-mixture model has a mixture distribution assigned one of various BNP prior distributions, including priors defined by either the Dirichlet process, Pitman-Yor process (including the normalized stable process), beta (two-parameter) process, normalized inverse-Gaussian process, geometric weights prior, dependent Dirichlet process, or the dependent infinite-probits prior. The software user can mouse-click to select a Bayesian model and perform data analysis via Markov chain Monte Carlo (MCMC) sampling. After the sampling completes, the software automatically opens text output that reports MCMC-based estimates of the model's posterior distribution and model predictive fit to the data. Additional text and/or graphical output can be generated by mouse-clicking other menu options. This includes output of MCMC convergence analyses, and estimates of the model's posterior predictive distribution, for selected functionals and values of covariates. The software is illustrated through the BNP regression analysis of real data.

Association Between Dietary Intake and Function in Amyotrophic Lateral Sclerosis.

PubMed

Nieves, Jeri W; Gennings, Chris; Factor-Litvak, Pam; Hupf, Jonathan; Singleton, Jessica; Sharf, Valerie; Oskarsson, Björn; Fernandes Filho, J Americo M; Sorenson, Eric J; D'Amico, Emanuele; Goetz, Ray; Mitsumoto, Hiroshi

2016-12-01

There is growing interest in the role of nutrition in the pathogenesis and progression of amyotrophic lateral sclerosis (ALS). To evaluate the associations between nutrients, individually and in groups, and ALS function and respiratory function at diagnosis. A cross-sectional baseline analysis of the Amyotrophic Lateral Sclerosis Multicenter Cohort Study of Oxidative Stress study was conducted from March 14, 2008, to February 27, 2013, at 16 ALS clinics throughout the United States among 302 patients with ALS symptom duration of 18 months or less. Nutrient intake, measured using a modified Block Food Frequency Questionnaire (FFQ). Amyotrophic lateral sclerosis function, measured using the ALS Functional Rating Scale-Revised (ALSFRS-R), and respiratory function, measured using percentage of predicted forced vital capacity (FVC). Baseline data were available on 302 patients with ALS (median age, 63.2 years [interquartile range, 55.5-68.0 years]; 178 men and 124 women). Regression analysis of nutrients found that higher intakes of antioxidants and carotenes from vegetables were associated with higher ALSFRS-R scores or percentage FVC. Empirically weighted indices using the weighted quantile sum regression method of "good" micronutrients and "good" food groups were positively associated with ALSFRS-R scores (β [SE], 2.7 [0.69] and 2.9 [0.9], respectively) and percentage FVC (β [SE], 12.1 [2.8] and 11.5 [3.4], respectively) (all P < .001). Positive and significant associations with ALSFRS-R scores (β [SE], 1.5 [0.61]; P = .02) and percentage FVC (β [SE], 5.2 [2.2]; P = .02) for selected vitamins were found in exploratory analyses. Antioxidants, carotenes, fruits, and vegetables were associated with higher ALS function at baseline by regression of nutrient indices and weighted quantile sum regression analysis. We also demonstrated the usefulness of the weighted quantile sum regression method in the evaluation of diet. Those responsible for nutritional care of the patient with ALS should consider promoting fruit and vegetable intake since they are high in antioxidants and carotenes.

Neither fixed nor random: weighted least squares meta-analysis.

PubMed

Stanley, T D; Doucouliagos, Hristos

2015-06-15

This study challenges two core conventional meta-analysis methods: fixed effect and random effects. We show how and explain why an unrestricted weighted least squares estimator is superior to conventional random-effects meta-analysis when there is publication (or small-sample) bias and better than a fixed-effect weighted average if there is heterogeneity. Statistical theory and simulations of effect sizes, log odds ratios and regression coefficients demonstrate that this unrestricted weighted least squares estimator provides satisfactory estimates and confidence intervals that are comparable to random effects when there is no publication (or small-sample) bias and identical to fixed-effect meta-analysis when there is no heterogeneity. When there is publication selection bias, the unrestricted weighted least squares approach dominates random effects; when there is excess heterogeneity, it is clearly superior to fixed-effect meta-analysis. In practical applications, an unrestricted weighted least squares weighted average will often provide superior estimates to both conventional fixed and random effects. Copyright © 2015 John Wiley & Sons, Ltd.

Wind Tunnel Strain-Gage Balance Calibration Data Analysis Using a Weighted Least Squares Approach

NASA Technical Reports Server (NTRS)

Ulbrich, N.; Volden, T.

2017-01-01

A new approach is presented that uses a weighted least squares fit to analyze wind tunnel strain-gage balance calibration data. The weighted least squares fit is specifically designed to increase the influence of single-component loadings during the regression analysis. The weighted least squares fit also reduces the impact of calibration load schedule asymmetries on the predicted primary sensitivities of the balance gages. A weighting factor between zero and one is assigned to each calibration data point that depends on a simple count of its intentionally loaded load components or gages. The greater the number of a data point's intentionally loaded load components or gages is, the smaller its weighting factor becomes. The proposed approach is applicable to both the Iterative and Non-Iterative Methods that are used for the analysis of strain-gage balance calibration data in the aerospace testing community. The Iterative Method uses a reasonable estimate of the tare corrected load set as input for the determination of the weighting factors. The Non-Iterative Method, on the other hand, uses gage output differences relative to the natural zeros as input for the determination of the weighting factors. Machine calibration data of a six-component force balance is used to illustrate benefits of the proposed weighted least squares fit. In addition, a detailed derivation of the PRESS residuals associated with a weighted least squares fit is given in the appendices of the paper as this information could not be found in the literature. These PRESS residuals may be needed to evaluate the predictive capabilities of the final regression models that result from a weighted least squares fit of the balance calibration data.

[Associated factors in newborns with intrauterine growth retardation].

PubMed

Thompson-Chagoyán, Oscar C; Vega-Franco, Leopoldo

2008-01-01

To identify the risk factors implicated in the intrauterine growth retardation (IUGR) of neonates born in a social security institution. Case controls design study in 376 neonates: 188 with IUGR (weight < 10 percentile) and 188 without IUGR. When they born, information about 30 variables of risk for IUGR were obtained from mothers. Risk analysis and logistical regression (stepwise) were used. Odds ratios were significant for 12 of the variables. The model obtains by stepwise regression included: weight gain at pregnancy, prenatal care attendance, toxemia, chocolate ingestion, father's weight, and the environmental house. Must of the variables included in the model are related to socioeconomic disadvantages related to the risk of RCIU in the population.

Linear regression analysis of survival data with missing censoring indicators.

PubMed

Wang, Qihua; Dinse, Gregg E

2011-04-01

Linear regression analysis has been studied extensively in a random censorship setting, but typically all of the censoring indicators are assumed to be observed. In this paper, we develop synthetic data methods for estimating regression parameters in a linear model when some censoring indicators are missing. We define estimators based on regression calibration, imputation, and inverse probability weighting techniques, and we prove all three estimators are asymptotically normal. The finite-sample performance of each estimator is evaluated via simulation. We illustrate our methods by assessing the effects of sex and age on the time to non-ambulatory progression for patients in a brain cancer clinical trial.

The Propensity Score Analytical Framework: An Overview and Institutional Research Example

ERIC Educational Resources Information Center

Herzog, Serge

2014-01-01

Estimating the effect of campus math tutoring support, this study demonstrates the use of propensity score weighted and matched-data analysis and examines the correspondence with results from parametric regression analysis.

Genetic parameters for growth characteristics of free-range chickens under univariate random regression models.

PubMed

Rovadoscki, Gregori A; Petrini, Juliana; Ramirez-Diaz, Johanna; Pertile, Simone F N; Pertille, Fábio; Salvian, Mayara; Iung, Laiza H S; Rodriguez, Mary Ana P; Zampar, Aline; Gaya, Leila G; Carvalho, Rachel S B; Coelho, Antonio A D; Savino, Vicente J M; Coutinho, Luiz L; Mourão, Gerson B

2016-09-01

Repeated measures from the same individual have been analyzed by using repeatability and finite dimension models under univariate or multivariate analyses. However, in the last decade, the use of random regression models for genetic studies with longitudinal data have become more common. Thus, the aim of this research was to estimate genetic parameters for body weight of four experimental chicken lines by using univariate random regression models. Body weight data from hatching to 84 days of age (n = 34,730) from four experimental free-range chicken lines (7P, Caipirão da ESALQ, Caipirinha da ESALQ and Carijó Barbado) were used. The analysis model included the fixed effects of contemporary group (gender and rearing system), fixed regression coefficients for age at measurement, and random regression coefficients for permanent environmental effects and additive genetic effects. Heterogeneous variances for residual effects were considered, and one residual variance was assigned for each of six subclasses of age at measurement. Random regression curves were modeled by using Legendre polynomials of the second and third orders, with the best model chosen based on the Akaike Information Criterion, Bayesian Information Criterion, and restricted maximum likelihood. Multivariate analyses under the same animal mixed model were also performed for the validation of the random regression models. The Legendre polynomials of second order were better for describing the growth curves of the lines studied. Moderate to high heritabilities (h(2) = 0.15 to 0.98) were estimated for body weight between one and 84 days of age, suggesting that selection for body weight at all ages can be used as a selection criteria. Genetic correlations among body weight records obtained through multivariate analyses ranged from 0.18 to 0.96, 0.12 to 0.89, 0.06 to 0.96, and 0.28 to 0.96 in 7P, Caipirão da ESALQ, Caipirinha da ESALQ, and Carijó Barbado chicken lines, respectively. Results indicate that genetic gain for body weight can be achieved by selection. Also, selection for body weight at 42 days of age can be maintained as a selection criterion. © 2016 Poultry Science Association Inc.

Risk profiles for weight gain among postmenopausal women: A classification and regression tree analysis approach

USDA-ARS?s Scientific Manuscript database

Risk factors for obesity and weight gain are typically evaluated individually while "adjusting for" the influence of other confounding factors, and few studies, if any, have created risk profiles by clustering risk factors. We identified subgroups of postmenopausal women homogeneous in their cluster...

Biomass estimates of eastern red cedar tree components

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

Schnell, R.L.

1976-02-01

Fresh and dry-weight relationships of species of the eastern red cedar (Juniperus virginiana L.) found in the Tennessee Valley are presented. Both wood and bark were analyzed. All fresh and dry weights tabulated were computed from predicting equations developed by multiple regression analysis of field data. (JGB)

Influence of anthropometric parameters on ultrasound measurements of Os calcis.

PubMed

Hans, D; Schott, A M; Arlot, M E; Sornay, E; Delmas, P D; Meunier, P J

1995-01-01

Few data have been published concerning the influence of height, weight and body mass index (BMI) on broadband ultrasound attenuation (BUA), speed of sound (SOS) and Lunar "stiffness" index, and always in small population samples. The first ain of the present cross-sectional study was to determine whether anthropometric factors have a significant influence on ultrasound measurements. The second objective was to establish whether these parameters have real effect on whether their influence is due only to measurement errors. We measured, in 271 healthy French women (mean age 77 +/- 11 years; range 31-97 years), the following parameters: age, height, weight, lean and fat body mass, heel width, foot length, knee height and external malleolus (HEM). Simple linear regression analyses between ultrasound and anthropometric parameters were performed. Age, height, and heel width were significant predictors of SOS; age, height, weight, foot length, heel width, HEM, fat mass and lean mass were significant predictors of BUA; age, height, weight, heel width, HEM, fat mass and lean mass were significant predictors of stiffness. In the multiple regression analysis, once the analysis had been adjusted for age, only heel width was a significant predictor for SOS (p = 0.0007), weight for BUA (p = 0.0001), and weight (p = 0.0001) and heel width (p = 0.004) for the stiffness index. Besides their statistical meaning, the regression coefficients have a more clinically relevant interpretation which is developed in the text. These results confirm the influence of anthropometric factors on the ultrasonic parameter values, because BUA and SOS were in part dependent on heel width and weight. The influence of the position of the transducer on the calcaneus should be taken into account to optimize the methods of measurement using ultrasound.

Regression Simulation Model. Appendix X. Users Manual,

DTIC Science & Technology

1981-03-01

change as the prediction equations become refined. Whereas no notice will be provided when the changes are made, the programs will be modified such that...NATIONAL BUREAU Of STANDARDS 1963 A ___,_ __ _ __ _ . APPENDIX X ( R4/ EGRESSION IMULATION ’jDEL. Ape’A ’) 7 USERS MANUA submitted to The Great River...regression analysis and to establish a prediction equation (model). The prediction equation contains the partial regression coefficients (B-weights) which

Fungible weights in logistic regression.

PubMed

Jones, Jeff A; Waller, Niels G

2016-06-01

In this article we develop methods for assessing parameter sensitivity in logistic regression models. To set the stage for this work, we first review Waller's (2008) equations for computing fungible weights in linear regression. Next, we describe 2 methods for computing fungible weights in logistic regression. To demonstrate the utility of these methods, we compute fungible logistic regression weights using data from the Centers for Disease Control and Prevention's (2010) Youth Risk Behavior Surveillance Survey, and we illustrate how these alternate weights can be used to evaluate parameter sensitivity. To make our work accessible to the research community, we provide R code (R Core Team, 2015) that will generate both kinds of fungible logistic regression weights. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Calorimetric analysis of fungal degraded wood

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

Blankenhorn, P.R.; Baldwin, R.C.; Merrill, W. Jr.

1980-01-01

Endothermic transition and gross heat of combustion of aspenwood subjected to degradation by Lenzites trabea and Polyporus versicolor were determined by using differential scanning calorimetry (DSC) and an adiabatic O bomb. Endothermic peak areas of undegraded and fungi-degraded wood differed from each other at all levels of weight loss. The regression analysis of the DSC data vs. weight loss revealed a significant relations, although not highly correlated, for P. versicolor-degraded specimens and a nonsignificant relation for L. trabea-degraded specimens; weight loss and gross heat of combustion values of degraded specimens were significantly correlated.

Selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays and impacts of using incorrect weighting factors on curve stability, data quality, and assay performance.

PubMed

Gu, Huidong; Liu, Guowen; Wang, Jian; Aubry, Anne-Françoise; Arnold, Mark E

2014-09-16

A simple procedure for selecting the correct weighting factors for linear and quadratic calibration curves with least-squares regression algorithm in bioanalytical LC-MS/MS assays is reported. The correct weighting factor is determined by the relationship between the standard deviation of instrument responses (σ) and the concentrations (x). The weighting factor of 1, 1/x, or 1/x(2) should be selected if, over the entire concentration range, σ is a constant, σ(2) is proportional to x, or σ is proportional to x, respectively. For the first time, we demonstrated with detailed scientific reasoning, solid historical data, and convincing justification that 1/x(2) should always be used as the weighting factor for all bioanalytical LC-MS/MS assays. The impacts of using incorrect weighting factors on curve stability, data quality, and assay performance were thoroughly investigated. It was found that the most stable curve could be obtained when the correct weighting factor was used, whereas other curves using incorrect weighting factors were unstable. It was also found that there was a very insignificant impact on the concentrations reported with calibration curves using incorrect weighting factors as the concentrations were always reported with the passing curves which actually overlapped with or were very close to the curves using the correct weighting factor. However, the use of incorrect weighting factors did impact the assay performance significantly. Finally, the difference between the weighting factors of 1/x(2) and 1/y(2) was discussed. All of the findings can be generalized and applied into other quantitative analysis techniques using calibration curves with weighted least-squares regression algorithm.

Capacity for Physical Activity Predicts Weight Loss After Roux-en-Y Gastric Bypass

PubMed Central

Hatoum, Ida J.; Stein, Heather K.; Merrifield, Benjamin F.; Kaplan, Lee M.

2014-01-01

Despite its overall excellent outcomes, weight loss after Roux-en-Y gastric bypass (RYGB) is highly variable. We conducted this study to identify clinical predictors of weight loss after RYGB. We reviewed charts from 300 consecutive patients who underwent RYGB from August 1999 to November 2002. Data collected included patient demographics, medical comorbidities, and diet history. Of the 20 variables selected for univariate analysis, 9 with univariate P values ≤ 0.15 were entered into a multivariable regression analysis. Using backward selection, covariates with P < 0.05 were retained. Potential confounders were added back into the model and assessed for effect on all model variables. Complete records were available for 246 of the 300 patients (82%). The patient characteristics were 75% female, 93% white, mean age of 45 years, and mean initial BMI of 52.3 kg/m2. One year after surgery, patients lost an average of 64.8% of their excess weight (s.d. = 20.5%). The multivariable regression analysis revealed that limited physical activity, higher initial BMI, lower educational level, diabetes, and decreased attendance at postoperative appointments had an adverse effect on weight loss after RYGB. A model including these five factors accounts for 41% of the observed variability in weight loss (adjusted r2 = 0.41). In this cohort, higher initial BMI and limited physical activity were the strongest predictors of decreased excess weight loss following RYGB. Limited physical activity may be particularly important because it represents an opportunity for potentially meaningful pre- and postsurgical intervention to maximize weight loss following RYGB. PMID:18997674

Maternal Active Smoking During Pregnancy and Low Birth Weight in the Americas: A Systematic Review and Meta-analysis.

PubMed

Pereira, Priscilla Perez da Silva; Da Mata, Fabiana A F; Figueiredo, Ana Claudia Godoy; de Andrade, Keitty Regina Cordeiro; Pereira, Maurício Gomes

2017-05-01

Smoking during pregnancy may negatively impact newborn birth weight. This study investigates the relationship between maternal active smoking during pregnancy and low birth weight in the Americas through systematic review and meta-analysis. A literature search was conducted through indexed databases and the grey literature. Case-control and cohort studies published between 1984 and 2016 conducted within the Americas were included without restriction regarding publication language. The article selection process and data extraction were performed by two independent investigators. A meta-analysis of random effects was conducted, and possible causes of between-study heterogeneity were evaluated by meta-regressions and subgroup analyses. Publication bias was assessed by visual inspection of Begg's funnel plot and by Egger's regression test. The literature search yielded 848 articles from which 34 studies were selected for systematic review and 30 for meta-analysis. Active maternal smoking was associated with low birth weight, OR = 2.00 (95% CI: 1.77-2.26; I2 = 66.3%). The funnel plot and Egger's test (p = .14) indicated no publication bias. Meta-regression revealed that sample size, study quality, and the number of confounders in the original studies did not account for the between-study heterogeneity. Subgroup analysis indicated no significant differences when studies were compared by design, sample size, and regions of the Americas. Low birth weight is associated with maternal active smoking during pregnancy regardless of the region in the Americas or the studies' methodological aspects. A previous search of the major electronic databases revealed that no studies appear to have been conducted to summarize the association between maternal active smoking during pregnancy and low birth weight within the Americas. Therefore, this systematic review may help to fill the information gap. The region of the Americas contains some of the most populous countries in the world; therefore, this study may provide useful data from this massive segment of the world's population. © The Author 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Excessive weight loss in exclusively breastfed full-term newborns in a Baby-Friendly Hospital.

PubMed

Mezzacappa, Maria Aparecida; Ferreira, Bruna Gil

2016-09-01

To determine the risk factors for weight loss over 8% in full-term newborns at postpartum discharge from a Baby Friendly Hospital. The cases were selected from a cohort of infants belonging to a previous study. Healthy full-term newborns with birth weight ≥2.000g, who were exclusively breastfed, and excluding twins and those undergoing phototherapy as well as those discharged after 96 hours of life, were included. The analyzed maternal variables were maternal age, parity, ethnicity, type of delivery, maternal diabetes, gender, gestational age and appropriate weight for age. Adjusted multiple and univariate Cox regression analyses were used, considering as significant p<0.05. We studied 414 newborns, of whom 107 (25.8%) had excessive weight loss. Through the univariate regression, risk factors associated with weight loss >8% were caesarean delivery and older maternal age. At the adjusted multiple regression analysis, the model to explain the weight loss was cesarean delivery (relative risk: 2.27 and 95% of confidence interval: 1.54 to 3.35). The independent predictor for weight loss >8% in exclusively breastfed full-term newborns in a Baby-Friendly Hospital was the cesarean delivery. It is possible to reduce the number of cesarean sections to minimize neonatal excessive weight loss and the resulting use of infant formula during the first week of life. Copyright © 2015 Sociedade de Pediatria de São Paulo. Publicado por Elsevier Editora Ltda. All rights reserved.

[Breast feeding and systemic blood pressure in infants].

PubMed

Hernández-González, Martha A; Díaz-De-León, Luz V; Guízar-Mendoza, Juan M; Amador-Licona, Norma; Cipriano-González, Marisol; Díaz-Pérez, Raúl; Murillo-Ortiz, Blanca O; De-la-Roca-Chiapas, José María; Solorio-Meza, Sergio Eduardo

2012-01-01

Blood pressure levels in childhood influence these levels in adulthood, and breastfeeding has been considered such as a cardioprotective. We evaluated the association between blood pressure levels and feeding type in a group of infants. We conducted a comparative cross-sectional study in term infants with appropriate weight at birth, to compare blood pressure levels in those children with exclusively breastfeeding, mixed-feeding and formula feeding. The comparison of groups was performed using ANOVA and multiple regression analysis was used to identify variables associated with mean arterial blood pressure levels. A p value < 0.05 was considered significant. We included 20 men and 24 women per group. Infant Formula Feeding had higher current weight and weight gain compared with the other two groups (p < 0.05). Systolic, diastolic and mean blood pressure levels, as well as respiratory and heart rate were higher in the groups of exclusively formula feeding and mixed-feeding than in those with exclusively breastfeeding (p < 0.05). Multiple regression analysis identified that variables associated with mean blood pressure levels were current body mass index, weight gain and formula feeding. Infants in breastfeeding show lower blood pressure, BMI and weight gain.

Customized Fetal Growth Charts for Parents' Characteristics, Race, and Parity by Quantile Regression Analysis: A Cross-sectional Multicenter Italian Study.

PubMed

Ghi, Tullio; Cariello, Luisa; Rizzo, Ludovica; Ferrazzi, Enrico; Periti, Enrico; Prefumo, Federico; Stampalija, Tamara; Viora, Elsa; Verrotti, Carla; Rizzo, Giuseppe

2016-01-01

The purpose of this study was to construct fetal biometric charts between 16 and 40 weeks' gestation that were customized for parental characteristics, race, and parity, using quantile regression analysis. In a multicenter cross-sectional study, 8070 sonographic examinations from low-risk pregnancies between 16 and 40 weeks' gestation were analyzed. The fetal measurements obtained were biparietal diameter, head circumference, abdominal circumference, and femur diaphysis length. Quantile regression was used to examine the impact of parental height and weight, parity, and race across biometric percentiles for the fetal measurements considered. Paternal and maternal height were significant covariates for all of the measurements considered (P < .05). Maternal weight significantly influenced head circumference, abdominal circumference, and femur diaphysis length. Parity was significantly associated with biparietal diameter and head circumference. Central African race was associated with head circumference and femur diaphysis length, whereas North African race was only associated with femur diaphysis length. In this study we constructed customized biometric growth charts using quantile regression in a large cohort of low-risk pregnancies. These charts offer the advantage of defining individualized normal ranges of fetal biometric parameters at each specific percentile corrected for parental height and weight, parity, and race. This study supports the importance of including these variables in routine sonographic screening for fetal growth abnormalities.

Factor weighting in DRASTIC modeling.

PubMed

Pacheco, F A L; Pires, L M G R; Santos, R M B; Sanches Fernandes, L F

2015-02-01

Evaluation of aquifer vulnerability comprehends the integration of very diverse data, including soil characteristics (texture), hydrologic settings (recharge), aquifer properties (hydraulic conductivity), environmental parameters (relief), and ground water quality (nitrate contamination). It is therefore a multi-geosphere problem to be handled by a multidisciplinary team. The DRASTIC model remains the most popular technique in use for aquifer vulnerability assessments. The algorithm calculates an intrinsic vulnerability index based on a weighted addition of seven factors. In many studies, the method is subject to adjustments, especially in the factor weights, to meet the particularities of the studied regions. However, adjustments made by different techniques may lead to markedly different vulnerabilities and hence to insecurity in the selection of an appropriate technique. This paper reports the comparison of 5 weighting techniques, an enterprise not attempted before. The studied area comprises 26 aquifer systems located in Portugal. The tested approaches include: the Delphi consensus (original DRASTIC, used as reference), Sensitivity Analysis, Spearman correlations, Logistic Regression and Correspondence Analysis (used as adjustment techniques). In all cases but Sensitivity Analysis, adjustment techniques have privileged the factors representing soil characteristics, hydrologic settings, aquifer properties and environmental parameters, by leveling their weights to ≈4.4, and have subordinated the factors describing the aquifer media by downgrading their weights to ≈1.5. Logistic Regression predicts the highest and Sensitivity Analysis the lowest vulnerabilities. Overall, the vulnerability indices may be separated by a maximum value of 51 points. This represents an uncertainty of 2.5 vulnerability classes, because they are 20 points wide. Given this ambiguity, the selection of a weighting technique to integrate a vulnerability index may require additional expertise to be set up satisfactorily. Following a general criterion that weights must be proportional to the range of the ratings, Correspondence Analysis may be recommended as the best adjustment technique. Copyright © 2014 Elsevier B.V. All rights reserved.

Skipping breakfast, overconsumption of soft drinks and screen media: longitudinal analysis of the combined influence on weight development in primary schoolchildren.

PubMed

Traub, Meike; Lauer, Romy; Kesztyüs, Tibor; Wartha, Olivia; Steinacker, Jürgen Michael; Kesztyüs, Dorothea

2018-03-16

Regular breakfast and well-balanced soft drink, and screen media consumption are associated with a lower risk of overweight and obesity in schoolchildren. The aim of this research is the combined examination of these three parameters as influencing factors for longitudinal weight development in schoolchildren in order to adapt targeted preventive measures. In the course of the Baden-Württemberg Study, Germany, data from direct measurements (baseline (2010) and follow-up (2011)) at schools was available for 1733 primary schoolchildren aged 7.08 ± 0.6 years (50.8% boys). Anthropometric measurements of the children were taken according to ISAK-standards (International Standard for Anthropometric Assessment) by trained staff. Health and lifestyle characteristics of the children and their parents were assessed in questionnaires. A linear mixed effects regression analysis was conducted to examine influences on changes in waist-to-height-ratio (WHtR), weight, and body mass index (BMI) measures. A generalised linear mixed effects regression analysis was performed to identify the relationship between breakfast, soft drink and screen media consumption with the prevalence of overweight, obesity and abdominal obesity at follow-up. According to the regression analyses, skipping breakfast led to increased changes in WHtR, weight and BMI measures. Skipping breakfast and the overconsumption of screen media at baseline led to higher odds of abdominal obesity and overweight at follow-up. No significant association between soft drink consumption and weight development was found. Targeted prevention for healthy weight status and development in primary schoolchildren should aim towards promoting balanced breakfast habits and a reduction in screen media consumption. Future research on soft drink consumption is needed. Health promoting interventions should synergistically involve children, parents, and schools. The Baden-Württemberg Study is registered at the German Clinical Trials Register (DRKS) under the DRKS-ID: DRKS00000494 .

Travel distance as factor in follow-up visit compliance in postlaparoscopic adjustable gastric banding population.

PubMed

DeNino, Walter F; Osler, Turner; Evans, Ellen G; Forgione, Patrick M

2010-01-01

Despite the 2008 "American Association of Clinical Endocrinologists, The Obesity Society, and American Society for Metabolic and Bariatric Surgery Medical Guidelines for Clinical Practice for the Perioperative Nutritional, Metabolic, and Nonsurgical Support of the Bariatric Surgery Patient," consensus does not exist for postoperative care in laparoscopic adjustable gastric banding (LAGB) patients (grade D evidence). It has been suggested that regular follow-up is related to better outcomes, specifically greater weight loss. The aim of the present study was to investigate the effects of travel distance to the clinic on the adherence to follow-up visits and weight loss in a cohort of LAGB patients in the setting of a rural, university-affiliated teaching hospital in the United States. A retrospective chart review was performed of all consecutive LAGB patients for a 1-year period. Linear regression analysis was used to identify the relationships between appointment compliance and the distance traveled and between the amount of weight loss and the distance traveled. Linear regression analysis was performed to investigate the effect of the travel distance to the clinic on the percentage of follow-up visits postoperatively. This effect was not significant (P = .4). Linear regression analysis was also performed to elucidate the effect of the travel distance to the clinic on the amount of weight loss. This effect was significant (P = .04). The travel distance to the clinic did not seem to be a significant predictor of compliance in a cohort of LAGB patients with ≤ 1 year of follow-up in a rural setting. However, a weak relationship was found between the travel distance to the clinic and weight loss, with patients who traveled further seeming to lose slightly more weight. Copyright © 2010 American Society for Metabolic and Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

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.

Predicting the ideal serum creatinine of kidney transplant recipients by a simple formula based on the balance between metabolic demands of recipients and renal mass supply from donors.

PubMed

Oh, C K; Lee, B M; Kim, H; Kim, S I; Kim, Y S

2008-09-01

Serum creatinine (Scr) is the most frequently used test to estimate graft function after kidney transplantation. Our previous study demonstrated that the independent predictors of recipient posttransplantation Scr included the ratio of graft weight to recipient body weight, the ratio of graft weight to recipient body surface area (BSA), and the ratio of graft weight to recipient body mass index (BMI). A prospective analysis about the impact of the balance between metabolic demands and renal supply on posttransplantation Scr of recipients was previously reported. We plotted the scatter graph using the X-axis as the independent predictors of Scr by linear regression and the Y-axis as the recipient Scr. To generate the predictive formula of Scr, we calculated a fit of the line of plotted cases using a linear regression method with 2 regression lines for prediction of the upper and lower 95% confidence intervals. Each line was converted into a predictive formula: Scr = -0.0033* (Graft weight(g)/Recipient BSA(m2))+1.75. Under 95% confidence, the Scr ranges from -0.0033* (Graft weight(g)/Recipient BSA(m2))+1.07 to -0.0033* (Graft weight(g)/Recipient BSA (m2))+2.44. Scr = -0.1049* (Graft weight(g)/Recipient body weight(kg))+1.72, which ranges from -0.1049* (Graft weight(g)/Recipient body weight(kg))+1.06 to -0.1049* (Graft weight(g)/Recipient body weight(kg))+2.37. Scr = -0.0158* (Graft weight(g)/Recipient BMI(kg/m2))+1.56, which ranges from -0.0158* (Graft weight(g)/Recipient BMI(kg/m2))+0.75 to -0.0158* (Graft weight(g)/Recipient BMI(kg/m2))+2.26. Prediction of posttransplantation Scr may be achieved by measuring graft weight as well as recipient weight and height. When recipient Scr is significantly higher than that predicted by the formula, a clinician should suspect an underlying graft injury.

Peak Weight and Height Velocity to Age 36 Months and Asthma Development: The Norwegian Mother and Child Cohort Study

PubMed Central

Magnus, Maria C.; Stigum, Hein; Håberg, Siri E.; Nafstad, Per; London, Stephanie J.; Nystad, Wenche

2015-01-01

Background The immediate postnatal period is the period of the fastest growth in the entire life span and a critical period for lung development. Therefore, it is interesting to examine the association between growth during this period and childhood respiratory disorders. Methods We examined the association of peak weight and height velocity to age 36 months with maternal report of current asthma at 36 months (n = 50,311), recurrent lower respiratory tract infections (LRTIs) by 36 months (n = 47,905) and current asthma at 7 years (n = 24,827) in the Norwegian Mother and Child Cohort Study. Peak weight and height velocity was calculated using the Reed1 model through multilevel mixed-effects linear regression. Multivariable log-binomial regression was used to calculate adjusted relative risks (adj.RR) and 95% confidence intervals (CI). We also conducted a sibling pair analysis using conditional logistic regression. Results Peak weight velocity was positively associated with current asthma at 36 months [adj.RR 1.22 (95%CI: 1.18, 1.26) per standard deviation (SD) increase], recurrent LRTIs by 36 months [adj.RR 1.14 (1.10, 1.19) per SD increase] and current asthma at 7 years [adj.RR 1.13 (95%CI: 1.07, 1.19) per SD increase]. Peak height velocity was not associated with any of the respiratory disorders. The positive association of peak weight velocity and asthma at 36 months remained in the sibling pair analysis. Conclusions Higher peak weight velocity, achieved during the immediate postnatal period, increased the risk of respiratory disorders. This might be explained by an influence on neonatal lung development, shared genetic/epigenetic mechanisms and/or environmental factors. PMID:25635872

Association Between Dietary Intake and Function in Amyotrophic Lateral Sclerosis

PubMed Central

Nieves, Jeri W.; Gennings, Chris; Factor-Litvak, Pam; Hupf, Jonathan; Singleton, Jessica; Sharf, Valerie; Oskarsson, Björn; Fernandes Filho, J. Americo M.; Sorenson, Eric J.; D’Amico, Emanuele; Goetz, Ray; Mitsumoto, Hiroshi

2017-01-01

IMPORTANCE There is growing interest in the role of nutrition in the pathogenesis and progression of amyotrophic lateral sclerosis (ALS). OBJECTIVE To evaluate the associations between nutrients, individually and in groups, and ALS function and respiratory function at diagnosis. DESIGN, SETTING, AND PARTICIPANTS A cross-sectional baseline analysis of the Amyotrophic Lateral Sclerosis Multicenter Cohort Study of Oxidative Stress study was conducted from March 14, 2008, to February 27, 2013, at 16 ALS clinics throughout the United States among 302 patients with ALS symptom duration of 18 months or less. EXPOSURES Nutrient intake, measured using a modified Block Food Frequency Questionnaire (FFQ). MAIN OUTCOMES AND MEASURES Amyotrophic lateral sclerosis function, measured using the ALS Functional Rating Scale–Revised (ALSFRS-R), and respiratory function, measured using percentage of predicted forced vital capacity (FVC). RESULTS Baseline data were available on 302 patients with ALS (median age, 63.2 years [interquartile range, 55.5–68.0 years]; 178 men and 124 women). Regression analysis of nutrients found that higher intakes of antioxidants and carotenes from vegetables were associated with higher ALSFRS-R scores or percentage FVC. Empirically weighted indices using the weighted quantile sum regression method of “good” micronutrients and “good” food groups were positively associated with ALSFRS-R scores (β [SE], 2.7 [0.69] and 2.9 [0.9], respectively) and percentage FVC (β [SE], 12.1 [2.8] and 11.5 [3.4], respectively) (all P < .001). Positive and significant associations with ALSFRS-R scores (β [SE], 1.5 [0.61]; P = .02) and percentage FVC (β [SE], 5.2 [2.2]; P = .02) for selected vitamins were found in exploratory analyses. CONCLUSIONS AND RELEVANCE Antioxidants, carotenes, fruits, and vegetables were associated with higher ALS function at baseline by regression of nutrient indices and weighted quantile sum regression analysis. We also demonstrated the usefulness of the weighted quantile sum regression method in the evaluation of diet. Those responsible for nutritional care of the patient with ALS should consider promoting fruit and vegetable intake since they are high in antioxidants and carotenes. PMID:27775751

Expert Coaching in Weight Loss: Retrospective Analysis

PubMed Central

Kushner, Robert F; Hill, James O; Lindquist, Richard; Brunning, Scott; Margulies, Amy

2018-01-01

Background Providing coaches as part of a weight management program is a common practice to increase participant engagement and weight loss success. Understanding coach and participant interactions and how these interactions impact weight loss success needs to be further explored for coaching best practices. Objective The purpose of this study was to analyze the coach and participant interaction in a 6-month weight loss intervention administered by Retrofit, a personalized weight management and Web-based disease prevention solution. The study specifically examined the association between different methods of coach-participant interaction and weight loss and tried to understand the level of coaching impact on weight loss outcome. Methods A retrospective analysis was performed using 1432 participants enrolled from 2011 to 2016 in the Retrofit weight loss program. Participants were males and females aged 18 years or older with a baseline body mass index of ≥25 kg/m², who also provided at least one weight measurement beyond baseline. First, a detailed analysis of different coach-participant interaction was performed using both intent-to-treat and completer populations. Next, a multiple regression analysis was performed using all measures associated with coach-participant interactions involving expert coaching sessions, live weekly expert-led Web-based classes, and electronic messaging and feedback. Finally, 3 significant predictors (P<.001) were analyzed in depth to reveal the impact on weight loss outcome. Results Participants in the Retrofit weight loss program lost a mean 5.14% (SE 0.14) of their baseline weight, with 44% (SE 0.01) of participants losing at least 5% of their baseline weight. Multiple regression model (R2=.158, P<.001) identified the following top 3 measures as significant predictors of weight loss at 6 months: expert coaching session attendance (P<.001), live weekly Web-based class attendance (P<.001), and food log feedback days per week (P<.001). Attending 80% of expert coaching sessions, attending 60% of live weekly Web-based classes, and receiving a minimum of 1 food log feedback day per week were associated with clinically significant weight loss. Conclusions Participant’s one-on-one expert coaching session attendance, live weekly expert-led interactive Web-based class attendance, and the number of food log feedback days per week from expert coach were significant predictors of weight loss in a 6-month intervention. PMID:29535082

Sensitivity analysis, calibration, and testing of a distributed hydrological model using error‐based weighting and one objective function

USGS Publications Warehouse

Foglia, L.; Hill, Mary C.; Mehl, Steffen W.; Burlando, P.

2009-01-01

We evaluate the utility of three interrelated means of using data to calibrate the fully distributed rainfall‐runoff model TOPKAPI as applied to the Maggia Valley drainage area in Switzerland. The use of error‐based weighting of observation and prior information data, local sensitivity analysis, and single‐objective function nonlinear regression provides quantitative evaluation of sensitivity of the 35 model parameters to the data, identification of data types most important to the calibration, and identification of correlations among parameters that contribute to nonuniqueness. Sensitivity analysis required only 71 model runs, and regression required about 50 model runs. The approach presented appears to be ideal for evaluation of models with long run times or as a preliminary step to more computationally demanding methods. The statistics used include composite scaled sensitivities, parameter correlation coefficients, leverage, Cook's D, and DFBETAS. Tests suggest predictive ability of the calibrated model typical of hydrologic models.

Using Classification and Regression Trees (CART) and random forests to analyze attrition: Results from two simulations.

PubMed

Hayes, Timothy; Usami, Satoshi; Jacobucci, Ross; McArdle, John J

2015-12-01

In this article, we describe a recent development in the analysis of attrition: using classification and regression trees (CART) and random forest methods to generate inverse sampling weights. These flexible machine learning techniques have the potential to capture complex nonlinear, interactive selection models, yet to our knowledge, their performance in the missing data analysis context has never been evaluated. To assess the potential benefits of these methods, we compare their performance with commonly employed multiple imputation and complete case techniques in 2 simulations. These initial results suggest that weights computed from pruned CART analyses performed well in terms of both bias and efficiency when compared with other methods. We discuss the implications of these findings for applied researchers. (c) 2015 APA, all rights reserved).

Using Classification and Regression Trees (CART) and Random Forests to Analyze Attrition: Results From Two Simulations

PubMed Central

Hayes, Timothy; Usami, Satoshi; Jacobucci, Ross; McArdle, John J.

2016-01-01

In this article, we describe a recent development in the analysis of attrition: using classification and regression trees (CART) and random forest methods to generate inverse sampling weights. These flexible machine learning techniques have the potential to capture complex nonlinear, interactive selection models, yet to our knowledge, their performance in the missing data analysis context has never been evaluated. To assess the potential benefits of these methods, we compare their performance with commonly employed multiple imputation and complete case techniques in 2 simulations. These initial results suggest that weights computed from pruned CART analyses performed well in terms of both bias and efficiency when compared with other methods. We discuss the implications of these findings for applied researchers. PMID:26389526

Birth weight and neonatal adiposity prediction using fractional limb volume obtained with 3D ultrasound.

PubMed

O'Connor, Clare; O'Higgins, Amy; Doolan, Anne; Segurado, Ricardo; Stuart, Bernard; Turner, Michael J; Kennelly, Máireád M

2014-01-01

The objective of this investigation was to study fetal thigh volume throughout gestation and explore its correlation with birth weight and neonatal body composition. This novel technique may improve birth weight prediction and lead to improved detection rates for fetal growth restriction. Fractional thigh volume (TVol) using 3D ultrasound, fetal biometry and soft tissue thickness were studied longitudinally in 42 mother-infant pairs. The percentages of neonatal body fat, fat mass and fat-free mass were determined using air displacement plethysmography. Correlation and linear regression analyses were performed. Linear regression analysis showed an association between TVol and birth weight. TVol at 33 weeks was also associated with neonatal fat-free mass. There was no correlation between TVol and neonatal fat mass. Abdominal circumference, estimated fetal weight (EFW) and EFW centile showed consistent correlations with birth weight. Thigh volume demonstrated an additional independent contribution to birth weight prediction when added to the EFW centile from the 38-week scan (p = 0.03). Fractional TVol performed at 33 weeks gestation is correlated with birth weight and neonatal lean body mass. This screening test may highlight those at risk of fetal growth restriction or macrosomia.

Evaluation of weighted regression and sample size in developing a taper model for loblolly pine

Treesearch

Kenneth L. Cormier; Robin M. Reich; Raymond L. Czaplewski; William A. Bechtold

1992-01-01

A stem profile model, fit using pseudo-likelihood weighted regression, was used to estimate merchantable volume of loblolly pine (Pinus taeda L.) in the southeast. The weighted regression increased model fit marginally, but did not substantially increase model performance. In all cases, the unweighted regression models performed as well as the...

[Risk factors for elevated serum total bile acid in preterm infants].

PubMed

Song, Yan-Ting; Wang, Yong-Qin; Zhao, Yue-Hua; Zhu, Hai-Ling; Liu, Qian; Zhang, Xiao; Gao, Yi-Wen; Zhang, Wei-Ye; Sang, Yu-Tong

2018-03-01

To study the risk factors for elevated serum total bile acid (TBA) in preterm infants. A retrospective analysis was performed for the clinical data of 216 preterm infants who were admitted to the neonatal intensive care unit. According to the presence or absence of elevated TBA (TBA >24.8 μmol/L), the preterm infants were divided into elevated TBA group with 53 infants and non-elevated TBA group with 163 infants. A univariate analysis and an unconditional multivariate logistic regression analysis were used to investigate the risk factors for elevated TBA. The univariate analysis showed that there were significant differences between the elevated TBA group and the non-elevated TBA group in gestational age at birth, birth weight, proportion of small-for-gestational-age infants, proportion of infants undergoing ventilator-assisted ventilation, fasting time, parenteral nutrition time, and incidence of neonatal respiratory failure and sepsis (P<0.05). The unconditional multivariate logistic regression analysis showed that low birth weight (OR=3.84, 95%CI: 1.53-9.64) and neonatal sepsis (OR=2.56, 95%CI: 1.01-6.47) were independent risk factors for elevated TBA in preterm infants. Low birth weight and neonatal sepsis may lead to elevated TBA in preterm infants.

Consistency evaluation of values of weight, height, and body mass index in Food Intake and Physical Activity of School Children: the quality control of data entry in the computerized system.

PubMed

Jesus, Gilmar Mercês de; Assis, Maria Alice Altenburg de; Kupek, Emil; Dias, Lizziane Andrade

2017-01-01

The quality control of data entry in computerized questionnaires is an important step in the validation of new instruments. The study assessed the consistency of recorded weight and height on the Food Intake and Physical Activity of School Children (Web-CAAFE) between repeated measures and against directly measured data. Students from the 2nd to the 5th grade (n = 390) had their weight and height directly measured and then filled out the Web-CAAFE. A subsample (n = 92) filled out the Web-CAAFE twice, three hours apart. The analysis included hierarchical linear regression, mixed linear regression model, to evaluate the bias, and intraclass correlation coefficient (ICC), to assess consistency. Univariate linear regression assessed the effect of gender, reading/writing performance, and computer/internet use and possession on residuals of fixed and random effects. The Web-CAAFE showed high values of ICC between repeated measures (body weight = 0.996, height = 0.937, body mass index - BMI = 0.972), and regarding the checked measures (body weight = 0.962, height = 0.882, BMI = 0.828). The difference between means of body weight, height, and BMI directly measured and recorded was 208 g, -2 mm, and 0.238 kg/m², respectively, indicating slight BMI underestimation due to underestimation of weight and overestimation of height. This trend was related to body weight and age. Height and weight data entered in the Web-CAAFE by children were highly correlated with direct measurements and with the repeated entry. The bias found was similar to validation studies of self-reported weight and height in comparison to direct measurements.

Explorative spatial analysis of traffic accident statistics and road mortality among the provinces of Turkey.

PubMed

Erdogan, Saffet

2009-10-01

The aim of the study is to describe the inter-province differences in traffic accidents and mortality on roads of Turkey. Two different risk indicators were used to evaluate the road safety performance of the provinces in Turkey. These indicators are the ratios between the number of persons killed in road traffic accidents (1) and the number of accidents (2) (nominators) and their exposure to traffic risk (denominator). Population and the number of registered motor vehicles in the provinces were used as denominators individually. Spatial analyses were performed to the mean annual rate of deaths and to the number of fatal accidents that were calculated for the period of 2001-2006. Empirical Bayes smoothing was used to remove background noise from the raw death and accident rates because of the sparsely populated provinces and small number of accident and death rates of provinces. Global and local spatial autocorrelation analyses were performed to show whether the provinces with high rates of deaths-accidents show clustering or are located closer by chance. The spatial distribution of provinces with high rates of deaths and accidents was nonrandom and detected as clustered with significance of P<0.05 with spatial autocorrelation analyses. Regions with high concentration of fatal accidents and deaths were located in the provinces that contain the roads connecting the Istanbul, Ankara, and Antalya provinces. Accident and death rates were also modeled with some independent variables such as number of motor vehicles, length of roads, and so forth using geographically weighted regression analysis with forward step-wise elimination. The level of statistical significance was taken as P<0.05. Large differences were found between the rates of deaths and accidents according to denominators in the provinces. The geographically weighted regression analyses did significantly better predictions for both accident rates and death rates than did ordinary least regressions, as indicated by adjusted R(2) values. Geographically weighted regression provided values of 0.89-0.99 adjusted R(2) for death and accident rates, compared with 0.88-0.95, respectively, by ordinary least regressions. Geographically weighted regression has the potential to reveal local patterns in the spatial distribution of rates, which would be ignored by the ordinary least regression approach. The application of spatial analysis and modeling of accident statistics and death rates at provincial level in Turkey will help to identification of provinces with outstandingly high accident and death rates. This could help more efficient road safety management in Turkey.

Quantile regression in the presence of monotone missingness with sensitivity analysis

PubMed Central

Liu, Minzhao; Daniels, Michael J.; Perri, Michael G.

2016-01-01

In this paper, we develop methods for longitudinal quantile regression when there is monotone missingness. In particular, we propose pattern mixture models with a constraint that provides a straightforward interpretation of the marginal quantile regression parameters. Our approach allows sensitivity analysis which is an essential component in inference for incomplete data. To facilitate computation of the likelihood, we propose a novel way to obtain analytic forms for the required integrals. We conduct simulations to examine the robustness of our approach to modeling assumptions and compare its performance to competing approaches. The model is applied to data from a recent clinical trial on weight management. PMID:26041008

Least median of squares and iteratively re-weighted least squares as robust linear regression methods for fluorimetric determination of α-lipoic acid in capsules in ideal and non-ideal cases of linearity.

PubMed

Korany, Mohamed A; Gazy, Azza A; Khamis, Essam F; Ragab, Marwa A A; Kamal, Miranda F

2018-06-01

This study outlines two robust regression approaches, namely least median of squares (LMS) and iteratively re-weighted least squares (IRLS) to investigate their application in instrument analysis of nutraceuticals (that is, fluorescence quenching of merbromin reagent upon lipoic acid addition). These robust regression methods were used to calculate calibration data from the fluorescence quenching reaction (∆F and F-ratio) under ideal or non-ideal linearity conditions. For each condition, data were treated using three regression fittings: Ordinary Least Squares (OLS), LMS and IRLS. Assessment of linearity, limits of detection (LOD) and quantitation (LOQ), accuracy and precision were carefully studied for each condition. LMS and IRLS regression line fittings showed significant improvement in correlation coefficients and all regression parameters for both methods and both conditions. In the ideal linearity condition, the intercept and slope changed insignificantly, but a dramatic change was observed for the non-ideal condition and linearity intercept. Under both linearity conditions, LOD and LOQ values after the robust regression line fitting of data were lower than those obtained before data treatment. The results obtained after statistical treatment indicated that the linearity ranges for drug determination could be expanded to lower limits of quantitation by enhancing the regression equation parameters after data treatment. Analysis results for lipoic acid in capsules, using both fluorimetric methods, treated by parametric OLS and after treatment by robust LMS and IRLS were compared for both linearity conditions. Copyright © 2018 John Wiley & Sons, Ltd.

Effect of overweight and obesity on weight loss and length of stay in patients with walled-off pancreatic necrosis.

PubMed

Rysgaard, Sisse; Rasmussen, Ditlev; Novovic, Srdan; Schmidt, Palle N; Gluud, Lise L

2017-06-01

The aim of this study was to assess the association between admission weight, weight loss, and length of stay (LOS) in patients with walled-off pancreatic necrosis. We classified the admission body mass index (BMI) of 18.5 to <25 kg/m 2 as normal weight, 25 to <30 kg/m 2 as overweight, and ≥30 kg/m 2 as obesity. The Nutritional Risk Screening score-2002 was calculated to identify patients at risk for undernutrition. We included 38 patients (61% men, 68% with infected necrosis; 40% normal weight; 60% overweight/obesity). Four patients (11%) required treatment at the semi-intensive care unit, 11 (29%) developed pneumonia, and 10 (26%) developed septicemia. One patient died due to respiratory failure and hemorrhage. The remaining patients were discharged after a median of 49 d (36-64 d). During admission, 14 patients (38%) achieved an energy-protein intake of at least 75% and 17 (46%) achieved ≥70% coverage. The percentage weight loss was different (P < 0.01) for patients with normal weight (4%), overweight (9%), and obesity (14%). There was no difference between groups regarding percentage of energy or protein coverage. Patients with overweight/obesity had a longer hospital LOS (P = 0.016). In univariable regression analysis, overweight, obesity, energy, and protein coverage predicted weight loss. LOS did not predict weight loss. In multivariable regression analysis, overweight and obesity were the only remaining significant predictors of weight loss. Patients with walled-off pancreatic necrosis are at considerable risk for undernutrition. A BMI >25 kg/m 2 predicts greater weight loss and longer LOS. Copyright © 2017 Elsevier Inc. All rights reserved.

Interpretation of ambiguities by schoolchildren with low birth weight from Embu das Artes, São Paulo state, Brazil.

PubMed

Pessoa, Rebeca Rodrigues; Araújo, Sarah Cueva Cândido Soares de; Isotani, Selma Mie; Puccini, Rosana Fiorini; Perissinoto, Jacy

To assess the development of language regarding the ability to recognize and interpret lexical ambiguity in low-birth-weight schoolchildren enrolled at the school system in the municipality of Embu das Artes, Sao Paulo state, compared with that of schoolchildren with normal birth weight. A case-control, retrospective, cross-sectional study conducted with 378 schoolchildren, both genders, aged 5 to 9.9 years, from the municipal schools of Embu das Artes. Study Group (SG) comprising 210 schoolchildren with birth weight < 2500 g. Control Group (CG) composed of 168 school children with birth weight ≥ 2500 g. Participants of both groups were compared with respect to the skills of recognition and verbal interpretation of sentences containing lexical ambiguity using the Test of Language Competence. Variables of interest: Age and gender of children; age and schooling of mothers. Statistical analysis: Descriptive analysis to characterize the sample and score per group; Student's t test for comparison between the total scores of each skill/subtest; Chi-square test to compare items within each subtest; multiple regression analysis for the intervening variables. Participants of the SG presented lower scores for ambiguous sentences compared with those of participants of the CG. Multiple regression analysis showed that child's current age was a predictor for all metalinguistic skills regarding interpretation of ambiguities in both groups. Participants of the SG presented lower specific and total scores than those of participants of the CG for ambiguity skills. The child's current age factor positively influenced the ambiguity skills in both groups.

Detection of gene-environment interactions in the presence of linkage disequilibrium and noise by using genetic risk scores with internal weights from elastic net regression.

PubMed

Hüls, Anke; Ickstadt, Katja; Schikowski, Tamara; Krämer, Ursula

2017-06-12

For the analysis of gene-environment (GxE) interactions commonly single nucleotide polymorphisms (SNPs) are used to characterize genetic susceptibility, an approach that mostly lacks power and has poor reproducibility. One promising approach to overcome this problem might be the use of weighted genetic risk scores (GRS), which are defined as weighted sums of risk alleles of gene variants. The gold-standard is to use external weights from published meta-analyses. In this study, we used internal weights from the marginal genetic effects of the SNPs estimated by a multivariate elastic net regression and thereby provided a method that can be used if there are no external weights available. We conducted a simulation study for the detection of GxE interactions and compared power and type I error of single SNPs analyses with Bonferroni correction and corresponding analysis with unweighted and our weighted GRS approach in scenarios with six risk SNPs and an increasing number of highly correlated (up to 210) and noise SNPs (up to 840). Applying weighted GRS increased the power enormously in comparison to the common single SNPs approach (e.g. 94.2% vs. 35.4%, respectively, to detect a weak interaction with an OR ≈ 1.04 for six uncorrelated risk SNPs and n = 700 with a well-controlled type I error). Furthermore, weighted GRS outperformed the unweighted GRS, in particular in the presence of SNPs without any effect on the phenotype (e.g. 90.1% vs. 43.9%, respectively, when 20 noise SNPs were added to the six risk SNPs). This outperforming of the weighted GRS was confirmed in a real data application on lung inflammation in the SALIA cohort (n = 402). However, in scenarios with a high number of noise SNPs (>200 vs. 6 risk SNPs), larger sample sizes are needed to avoid an increased type I error, whereas a high number of correlated SNPs can be handled even in small samples (e.g. n = 400). In conclusion, weighted GRS with weights from the marginal genetic effects of the SNPs estimated by a multivariate elastic net regression were shown to be a powerful tool to detect gene-environment interactions in scenarios of high Linkage disequilibrium and noise.

Association between summer temperature and body weight in Japanese adolescents and children: An ecological analysis.

PubMed

Yokoya, Masana; Higuchi, Yukito

2016-11-01

Several experimental studies reported evidence of a negative energy balance at higher temperatures. However, corresponding weight loss has not been noted in clinical practice. This study investigated the geographical association between outdoor temperature and body weight in Japanese adolescents and children. An ecological analysis was conducted using prefecture-level data on the mean body weight of Japanese adolescents and children over a 25-year period and Japanese mesh (regional) climatic data on the mean annual temperature, mean daily maximum temperature in August, and mean daily minimum temperature in January were also analyzed. Correlation analysis uncovered a stronger association between weight and the mean daily maximum temperature in August than with other climatic variables. Moreover, multiple regression analysis indicated that height and the mean daily maximum temperature in August were statistically significant predictors of weight. This suggests that geographical differences in weight in Japanese adolescents and children can be explained by the complementary relationship between height-associated weight gain and weight loss caused by summer heat. Summer temperatures may reduce the proportion of children who are overweight and contribute to geographical differences in body weight in Japanese adolescents and children. Am. J. Hum. Biol. 28:789-795, 2016. © 2016Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Association between gestational weight gain according to body mass index and postpartum weight in a large cohort of Danish women.

PubMed

Rode, Line; Kjærgaard, Hanne; Ottesen, Bent; Damm, Peter; Hegaard, Hanne K

2012-02-01

Our aim was to investigate the association between gestational weight gain (GWG) and postpartum weight retention (PWR) in pre-pregnancy underweight, normal weight, overweight or obese women, with emphasis on the American Institute of Medicine (IOM) recommendations. We performed secondary analyses on data based on questionnaires from 1,898 women from the "Smoke-free Newborn Study" conducted 1996-1999 at Hvidovre Hospital, Denmark. Relationship between GWG and PWR was examined according to BMI as a continuous variable and in four groups. Association between PWR and GWG according to IOM recommendations was tested by linear regression analysis and the association between PWR ≥ 5 kg (11 lbs) and GWG by logistic regression analysis. Mean GWG and mean PWR were constant for all BMI units until 26-27 kg/m(2). After this cut-off mean GWG and mean PWR decreased with increasing BMI. Nearly 40% of normal weight, 60% of overweight and 50% of obese women gained more than recommended during pregnancy. For normal weight and overweight women with GWG above recommendations the OR of gaining ≥ 5 kg (11 lbs) 1-year postpartum was 2.8 (95% CI 2.0-4.0) and 2.8 (95% CI 1.3-6.2, respectively) compared to women with GWG within recommendations. GWG above IOM recommendations significantly increases normal weight, overweight and obese women's risk of retaining weight 1 year after delivery. Health personnel face a challenge in prenatal counseling as 40-60% of these women gain more weight than recommended for their BMI. As GWG is potentially modifiable, our study should be followed by intervention studies focusing on GW.

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.

Random regression models on Legendre polynomials to estimate genetic parameters for weights from birth to adult age in Canchim cattle.

PubMed

Baldi, F; Albuquerque, L G; Alencar, M M

2010-08-01

The objective of this work was to estimate covariance functions for direct and maternal genetic effects, animal and maternal permanent environmental effects, and subsequently, to derive relevant genetic parameters for growth traits in Canchim cattle. Data comprised 49,011 weight records on 2435 females from birth to adult age. The model of analysis included fixed effects of contemporary groups (year and month of birth and at weighing) and age of dam as quadratic covariable. Mean trends were taken into account by a cubic regression on orthogonal polynomials of animal age. Residual variances were allowed to vary and were modelled by a step function with 1, 4 or 11 classes based on animal's age. The model fitting four classes of residual variances was the best. A total of 12 random regression models from second to seventh order were used to model direct and maternal genetic effects, animal and maternal permanent environmental effects. The model with direct and maternal genetic effects, animal and maternal permanent environmental effects fitted by quadric, cubic, quintic and linear Legendre polynomials, respectively, was the most adequate to describe the covariance structure of the data. Estimates of direct and maternal heritability obtained by multi-trait (seven traits) and random regression models were very similar. Selection for higher weight at any age, especially after weaning, will produce an increase in mature cow weight. The possibility to modify the growth curve in Canchim cattle to obtain animals with rapid growth at early ages and moderate to low mature cow weight is limited.

Ozone and sulfur dioxide effects on three tall fescue cultivars

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

Flagler, R.B.; Youngner, V.B.

Although many reports have been published concerning differential susceptibility of various crops and/or cultivars to air pollutants, most have used foliar injury instead of the marketable yield as the factor that determined susceptibility for the crop. In an examination of screening in terms of marketable yield, three cultivars of tall fescue (Festuca arundinacea Schreb.), 'Alta,' 'Fawn,' and 'Kentucky 31,' were exposed to 0-0.40 ppm O/sub 3/ or 0-0.50 ppm SO/sub 2/ 6 h/d, once a week, for 7 and 9 weeks, respectively. Experimental design was a randomized complete block with three replications. Statistical analysis was by standard analysis of variancemore » and regression techniques. Three variables were analyzed: top dry weight (yield), tiller number, and weight per tiller. Ozone had a significant effect on all three variables. Significant linear decreases in yield and weight per tiller occurred with increasing O/sub 3/ concentrations. Linear regressions of these variables on O/sub 3/ concentration produced significantly different regression coefficients. The coefficient for Kentucky 31 was significantly greater than Alta or Fawn, which did not differ from each other. This indicated that Kentucky 31 was more susceptible to O/sub 3/ than either of the other cultivars. Percent reductions in dry weight for the three cultivars at highest O/sub 3/ level were 35, 44, and 53%, respectively, for Fawn, Alta, and Kentucky 31. For weight per tiller, Kentucky 31 had a higher percent reduction than the other cultivars (59 vs. 46 and 44%). Tiller number was generally increased by O/sub 3/, but this variable was not useful for determining differential susceptibility to the pollutant. Sulfur dioxide treatments produced no significant effects on any of the variables analyzed.« less

Adaptation of a Weighted Regression Approach to Evaluate Water Quality Trends in an Estuary

EPA Science Inventory

To improve the description of long-term changes in water quality, we adapted a weighted regression approach to analyze a long-term water quality dataset from Tampa Bay, Florida. The weighted regression approach, originally developed to resolve pollutant transport trends in rivers...

Adaptation of a weighted regression approach to evaluate water quality trends in anestuary

EPA Science Inventory

To improve the description of long-term changes in water quality, a weighted regression approach developed to describe trends in pollutant transport in rivers was adapted to analyze a long-term water quality dataset from Tampa Bay, Florida. The weighted regression approach allows...

The impact of a standardized program on short and long-term outcomes in bariatric surgery.

PubMed

Aird, Lisa N F; Hong, Dennis; Gmora, Scott; Breau, Ruth; Anvari, Mehran

2017-02-01

The purpose of this study was to determine whether there has been an improvement in short- and long-term clinical outcomes since 2010, when the Ontario Bariatric Network led a province-wide initiative to establish a standardized system of care for bariatric patients. The system includes nine bariatric centers, a centralized referral system, and a research registry. Standardization of procedures has progressed yearly, including guidelines for preoperative assessment and perioperative care. Analysis of the OBN registry data was performed by fiscal year between April 2010 and March 2015. Three-month overall postoperative complication rates and 30 day postoperative mortality were calculated. The mean percentage of weight loss at 1, 2, and 3 years postoperative, and regression of obesity-related diseases were calculated. The analysis of continuous and nominal data was performed using ANOVA, Chi-square, and McNemar's testing. A multiple logistic regression analysis was performed for factors affecting postoperative complication rate. Eight thousand and forty-three patients were included in the bariatric registry between April 2010 and March 2015. Thirty-day mortality was rare (<0.075 %) and showed no significant difference between years. Three-month overall postoperative complication rates significantly decreased with standardization (p < 0.001), as did intra-operative complication rates (p < -0.001). Regression analysis demonstrated increasing standardization to be a predictor of 3 month complication rate OR of 0.59 (95 %CI 0.41-0.85, p = 0.00385). The mean percentage of weight loss at 1, 2, and 3 years postoperative showed stability at 33.2 % (9.0 SD), 34.1 % (10.1 SD), and 32.7 % (10.1 SD), respectively. Sustained regression in obesity-related comorbidities was demonstrated at 1, 2, and 3 years postoperative. Evidence indicates the implementation of a standardized system of bariatric care has contributed to improvements in complication rates and supported prolonged weight loss and regression of obesity-related diseases in patients undergoing bariatric surgery in Ontario.

A Simulation-Based Comparison of Several Stochastic Linear Regression Methods in the Presence of Outliers.

ERIC Educational Resources Information Center

Rule, David L.

Several regression methods were examined within the framework of weighted structural regression (WSR), comparing their regression weight stability and score estimation accuracy in the presence of outlier contamination. The methods compared are: (1) ordinary least squares; (2) WSR ridge regression; (3) minimum risk regression; (4) minimum risk 2;…

Application of least median of squared orthogonal distance (LMD) and LMD-based reweighted least squares (RLS) methods on the stock-recruitment relationship

NASA Astrophysics Data System (ADS)

Wang, Yan-Jun; Liu, Qun

1999-03-01

Analysis of stock-recruitment (SR) data is most often done by fitting various SR relationship curves to the data. Fish population dynamics data often have stochastic variations and measurement errors, which usually result in a biased regression analysis. This paper presents a robust regression method, least median of squared orthogonal distance (LMD), which is insensitive to abnormal values in the dependent and independent variables in a regression analysis. Outliers that have significantly different variance from the rest of the data can be identified in a residual analysis. Then, the least squares (LS) method is applied to the SR data with defined outliers being down weighted. The application of LMD and LMD-based Reweighted Least Squares (RLS) method to simulated and real fisheries SR data is explored.

Modeling the energy content of combustible ship-scrapping waste at Alang-Sosiya, India, using multiple regression analysis.

PubMed

Reddy, M Srinivasa; Basha, Shaik; Joshi, H V; Sravan Kumar, V G; Jha, B; Ghosh, P K

2005-01-01

Alang-Sosiya is the largest ship-scrapping yard in the world, established in 1982. Every year an average of 171 ships having a mean weight of 2.10 x 10(6)(+/-7.82 x 10(5)) of light dead weight tonnage (LDT) being scrapped. Apart from scrapped metals, this yard generates a massive amount of combustible solid waste in the form of waste wood, plastic, insulation material, paper, glass wool, thermocol pieces (polyurethane foam material), sponge, oiled rope, cotton waste, rubber, etc. In this study multiple regression analysis was used to develop predictive models for energy content of combustible ship-scrapping solid wastes. The scope of work comprised qualitative and quantitative estimation of solid waste samples and performing a sequential selection procedure for isolating variables. Three regression models were developed to correlate the energy content (net calorific values (LHV)) with variables derived from material composition, proximate and ultimate analyses. The performance of these models for this particular waste complies well with the equations developed by other researchers (Dulong, Steuer, Scheurer-Kestner and Bento's) for estimating energy content of municipal solid waste.

Genetic trends for live weight traits reflect breeding strategies in registered Charolais Farms in Mexico.

PubMed

Parra-Bracamonte, G M; Lopez-Villalobos, N; Morris, S T; Sifuentes-Rincón, A M; Lopez-Bustamante, L A

2016-12-01

Genetic trends are commonly used to verify genetic improvement; however, there are few reports on beef cattle in Mexico. Data from 1998 to 2013 from four Charolais bull breeding farms were examined to verify the genetic responses to different breeding management and selection criteria. Analysis included the comparison of regression lines of breeding values for birth (BW), weaning (WW) and yearling weights (YW), and maternal weaning weight (MWW) on the year of birth of the animals. Results revealed differential genetic progress for BW and YW and indicated that the overall analysis may have diluted the perception of genetic progress from the farmer's point of view. The use of breeding values as a tool for selection is effective to achieve genetic progress, even in negatively correlated traits, such as birth weight and yearling weight.

Expert Coaching in Weight Loss: Retrospective Analysis.

PubMed

Painter, Stefanie Lynn; Ahmed, Rezwan; Kushner, Robert F; Hill, James O; Lindquist, Richard; Brunning, Scott; Margulies, Amy

2018-03-13

Providing coaches as part of a weight management program is a common practice to increase participant engagement and weight loss success. Understanding coach and participant interactions and how these interactions impact weight loss success needs to be further explored for coaching best practices. The purpose of this study was to analyze the coach and participant interaction in a 6-month weight loss intervention administered by Retrofit, a personalized weight management and Web-based disease prevention solution. The study specifically examined the association between different methods of coach-participant interaction and weight loss and tried to understand the level of coaching impact on weight loss outcome. A retrospective analysis was performed using 1432 participants enrolled from 2011 to 2016 in the Retrofit weight loss program. Participants were males and females aged 18 years or older with a baseline body mass index of ≥25 kg/m², who also provided at least one weight measurement beyond baseline. First, a detailed analysis of different coach-participant interaction was performed using both intent-to-treat and completer populations. Next, a multiple regression analysis was performed using all measures associated with coach-participant interactions involving expert coaching sessions, live weekly expert-led Web-based classes, and electronic messaging and feedback. Finally, 3 significant predictors (P<.001) were analyzed in depth to reveal the impact on weight loss outcome. Participants in the Retrofit weight loss program lost a mean 5.14% (SE 0.14) of their baseline weight, with 44% (SE 0.01) of participants losing at least 5% of their baseline weight. Multiple regression model (R 2 =.158, P<.001) identified the following top 3 measures as significant predictors of weight loss at 6 months: expert coaching session attendance (P<.001), live weekly Web-based class attendance (P<.001), and food log feedback days per week (P<.001). Attending 80% of expert coaching sessions, attending 60% of live weekly Web-based classes, and receiving a minimum of 1 food log feedback day per week were associated with clinically significant weight loss. Participant's one-on-one expert coaching session attendance, live weekly expert-led interactive Web-based class attendance, and the number of food log feedback days per week from expert coach were significant predictors of weight loss in a 6-month intervention. ©Stefanie Lynn Painter, Rezwan Ahmed, Robert F Kushner, James O Hill, Richard Lindquist, Scott Brunning, Amy Margulies. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 13.03.2018.

Method validation using weighted linear regression models for quantification of UV filters in water samples.

PubMed

da Silva, Claudia Pereira; Emídio, Elissandro Soares; de Marchi, Mary Rosa Rodrigues

2015-01-01

This paper describes the validation of a method consisting of solid-phase extraction followed by gas chromatography-tandem mass spectrometry for the analysis of the ultraviolet (UV) filters benzophenone-3, ethylhexyl salicylate, ethylhexyl methoxycinnamate and octocrylene. The method validation criteria included evaluation of selectivity, analytical curve, trueness, precision, limits of detection and limits of quantification. The non-weighted linear regression model has traditionally been used for calibration, but it is not necessarily the optimal model in all cases. Because the assumption of homoscedasticity was not met for the analytical data in this work, a weighted least squares linear regression was used for the calibration method. The evaluated analytical parameters were satisfactory for the analytes and showed recoveries at four fortification levels between 62% and 107%, with relative standard deviations less than 14%. The detection limits ranged from 7.6 to 24.1 ng L(-1). The proposed method was used to determine the amount of UV filters in water samples from water treatment plants in Araraquara and Jau in São Paulo, Brazil. Copyright © 2014 Elsevier B.V. All rights reserved.

Refractive Status at Birth: Its Relation to Newborn Physical Parameters at Birth and Gestational Age

PubMed Central

Varghese, Raji Mathew; Sreenivas, Vishnubhatla; Puliyel, Jacob Mammen; Varughese, Sara

2009-01-01

Background Refractive status at birth is related to gestational age. Preterm babies have myopia which decreases as gestational age increases and term babies are known to be hypermetropic. This study looked at the correlation of refractive status with birth weight in term and preterm babies, and with physical indicators of intra-uterine growth such as the head circumference and length of the baby at birth. Methods All babies delivered at St. Stephens Hospital and admitted in the nursery were eligible for the study. Refraction was performed within the first week of life. 0.8% tropicamide with 0.5% phenylephrine was used to achieve cycloplegia and paralysis of accommodation. 599 newborn babies participated in the study. Data pertaining to the right eye is utilized for all the analyses except that for anisometropia where the two eyes were compared. Growth parameters were measured soon after birth. Simple linear regression analysis was performed to see the association of refractive status, (mean spherical equivalent (MSE), astigmatism and anisometropia) with each of the study variables, namely gestation, length, weight and head circumference. Subsequently, multiple linear regression was carried out to identify the independent predictors for each of the outcome parameters. Results Simple linear regression showed a significant relation between all 4 study variables and refractive error but in multiple regression only gestational age and weight were related to refractive error. The partial correlation of weight with MSE adjusted for gestation was 0.28 and that of gestation with MSE adjusted for weight was 0.10. Birth weight had a higher correlation to MSE than gestational age. Conclusion This is the first study to look at refractive error against all these growth parameters, in preterm and term babies at birth. It would appear from this study that birth weight rather than gestation should be used as criteria for screening for refractive error, especially in developing countries where the incidence of intrauterine malnutrition is higher. PMID:19214228

Applications of cluster analysis to satellite soundings

NASA Technical Reports Server (NTRS)

Munteanu, M. J.; Jakubowicz, O.; Kalnay, E.; Piraino, P.

1984-01-01

The advantages of the use of cluster analysis in the improvement of satellite temperature retrievals were evaluated since the use of natural clusters, which are associated with atmospheric temperature soundings characteristic of different types of air masses, has the potential for improving stratified regression schemes in comparison with currently used methods which stratify soundings based on latitude, season, and land/ocean. The method of discriminatory analysis was used. The correct cluster of temperature profiles from satellite measurements was located in 85% of the cases. Considerable improvement was observed at all mandatory levels using regression retrievals derived in the clusters of temperature (weighted and nonweighted) in comparison with the control experiment and with the regression retrievals derived in the clusters of brightness temperatures of 3 MSU and 5 IR channels.

Statistical approaches to account for missing values in accelerometer data: Applications to modeling physical activity.

PubMed

Yue Xu, Selene; Nelson, Sandahl; Kerr, Jacqueline; Godbole, Suneeta; Patterson, Ruth; Merchant, Gina; Abramson, Ian; Staudenmayer, John; Natarajan, Loki

2018-04-01

Physical inactivity is a recognized risk factor for many chronic diseases. Accelerometers are increasingly used as an objective means to measure daily physical activity. One challenge in using these devices is missing data due to device nonwear. We used a well-characterized cohort of 333 overweight postmenopausal breast cancer survivors to examine missing data patterns of accelerometer outputs over the day. Based on these observed missingness patterns, we created psuedo-simulated datasets with realistic missing data patterns. We developed statistical methods to design imputation and variance weighting algorithms to account for missing data effects when fitting regression models. Bias and precision of each method were evaluated and compared. Our results indicated that not accounting for missing data in the analysis yielded unstable estimates in the regression analysis. Incorporating variance weights and/or subject-level imputation improved precision by >50%, compared to ignoring missing data. We recommend that these simple easy-to-implement statistical tools be used to improve analysis of accelerometer data.

Refractive errors and refractive development in premature infants.

PubMed

Ozdemir, O; Tunay, Z Ozen; Acar, D Erginturk; Acar, U

2015-12-01

To examine refractive errors and refractive development in premature infants. Premature infants in the retinopathy of prematurity (ROP) screening program were recruited and examined longitudinally between 28 and 58 weeks postmenstrual age. For performing cycloplegic retinoscopy, 1% tropicamide was administered, two drops with a 10-minute interval, in order to paralyze accommodation and to achieve cycloplegia. Birth weight, gestational age, gender and acute ROP disease were recorded. The relationship between spherical equivalent, astigmatism and postmenstrual age was evaluated. A total of 798 readings were obtained from 258 infants (131 females, 127 males) between 28 and 58 weeks postmenstrual age. The median number of examinations was 3 (minimum 1, maximum 7). In the comparisons of birth weight, gestational age, spherical equivalent and astigmatism between genders, there were no statistically significant differences (P>0.05). Gestational age (regression analysis, r(2)=0.30, P<0.01) and birth weight (regression analysis, r(2)=0.22, P<0.01) had a significant effect on refractive error development. Preterm babies with lower birth weight and those born more prematurely had lower spherical equivalent. The spherical equivalent of the eyes correlated significantly with the postmenstrual age of the infants (r=0.512, P<0.01). Infants with low gestational age and low birth weight also had low spherical equivalent. Moreover, spherical equivalent correlated with increasing postmenstrual age. However, astigmatism did not correlate with postmenstrual age and did not associate with gestational age or birth weight. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Dynamic Density: An Air Traffic Management Metric

NASA Technical Reports Server (NTRS)

Laudeman, I. V.; Shelden, S. G.; Branstrom, R.; Brasil, C. L.

1998-01-01

The definition of a metric of air traffic controller workload based on air traffic characteristics is essential to the development of both air traffic management automation and air traffic procedures. Dynamic density is a proposed concept for a metric that includes both traffic density (a count of aircraft in a volume of airspace) and traffic complexity (a measure of the complexity of the air traffic in a volume of airspace). It was hypothesized that a metric that includes terms that capture air traffic complexity will be a better measure of air traffic controller workload than current measures based only on traffic density. A weighted linear dynamic density function was developed and validated operationally. The proposed dynamic density function includes a traffic density term and eight traffic complexity terms. A unit-weighted dynamic density function was able to account for an average of 22% of the variance in observed controller activity not accounted for by traffic density alone. A comparative analysis of unit weights, subjective weights, and regression weights for the terms in the dynamic density equation was conducted. The best predictor of controller activity was the dynamic density equation with regression-weighted complexity terms.

Acoustic-articulatory mapping in vowels by locally weighted regression

PubMed Central

McGowan, Richard S.; Berger, Michael A.

2009-01-01

A method for mapping between simultaneously measured articulatory and acoustic data is proposed. The method uses principal components analysis on the articulatory and acoustic variables, and mapping between the domains by locally weighted linear regression, or loess [Cleveland, W. S. (1979). J. Am. Stat. Assoc. 74, 829–836]. The latter method permits local variation in the slopes of the linear regression, assuming that the function being approximated is smooth. The methodology is applied to vowels of four speakers in the Wisconsin X-ray Microbeam Speech Production Database, with formant analysis. Results are examined in terms of (1) examples of forward (articulation-to-acoustics) mappings and inverse mappings, (2) distributions of local slopes and constants, (3) examples of correlations among slopes and constants, (4) root-mean-square error, and (5) sensitivity of formant frequencies to articulatory change. It is shown that the results are qualitatively correct and that loess performs better than global regression. The forward mappings show different root-mean-square error properties than the inverse mappings indicating that this method is better suited for the forward mappings than the inverse mappings, at least for the data chosen for the current study. Some preliminary results on sensitivity of the first two formant frequencies to the two most important articulatory principal components are presented. PMID:19813812

Serum eotaxin-1 is increased in extremely-low-birth-weight infants with bronchopulmonary dysplasia or death.

PubMed

Kandasamy, Jegen; Roane, Claire; Szalai, Alexander; Ambalavanan, Namasivayam

2015-11-01

Early systemic inflammation in extremely-low-birth-weight (ELBW) infants is associated with an increased risk of bronchopulmonary dysplasia (BPD). Our objective was to identify circulating biomarkers and develop prediction models for BPD/death soon after birth. Blood samples from postnatal day 1 were analyzed for C-reactive protein (CRP) by enzyme-linked immunosorbent assay and for 39 cytokines/chemokines by a multiplex assay in 152 ELBW infants. The primary outcome was physiologic BPD or death by 36 wk. CRP, cytokines, and clinical variables available at ≤24 h were used for forward stepwise regression and Classification and Regression Tree (CART) analysis to identify predictors of BPD/death. Overall, 24% developed BPD and 35% died or developed BPD. Regression analysis identified birth weight and eotaxin (CCL11) as the two most significant variables. CART identified FiO2 at 24 h (11% BPD/death if FiO2 ≤28%, 49% if >28%) and eotaxin in infants with FiO2 > 28% (29% BPD/death if eotaxin was ≤84 pg/ml; 65% if >84) as variables most associated with outcome. Eotaxin measured on the day of birth is useful for identifying ELBW infants at risk of BPD/death. Further investigation is required to determine if eotaxin is involved in lung injury and pathogenesis of BPD.

Drug treatment rates with beta-blockers and ACE-inhibitors/angiotensin receptor blockers and recurrences in takotsubo cardiomyopathy: A meta-regression analysis.

PubMed

Brunetti, Natale Daniele; Santoro, Francesco; De Gennaro, Luisa; Correale, Michele; Gaglione, Antonio; Di Biase, Matteo

2016-07-01

In a recent paper Singh et al. analyzed the effect of drug treatment on recurrence of takotsubo cardiomyopathy (TTC) in a comprehensive meta-analysis. The study found that recurrence rates were independent of clinic utilization of BB prescription, but inversely correlated with ACEi/ARB prescription: authors therefore conclude that ACEi/ARB rather than BB may reduce risk of recurrence. We aimed to re-analyze data reported in the study, now weighted for populations' size, in a meta-regression analysis. After multiple meta-regression analysis, we found a significant regression between rates of prescription of ACEi and rates of recurrence of TTC; regression was not statistically significant for BBs. On the bases of our re-analysis, we confirm that rates of recurrence of TTC are lower in populations of patients with higher rates of treatment with ACEi/ARB. That could not necessarily imply that ACEi may prevent recurrence of TTC, but barely that, for example, rates of recurrence are lower in cohorts more compliant with therapy or more prescribed with ACEi because more carefully followed. Randomized prospective studies are surely warranted. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Delay in weight bearing in surgically treated tibial shaft fractures is associated with impaired healing: a cohort analysis of 166 tibial fractures.

PubMed

Houben, I B; Raaben, M; Van Basten Batenburg, M; Blokhuis, T J

2018-04-09

The relation between timing of weight bearing after a fracture and the healing outcome is yet to be established, thereby limiting the implementation of a possibly beneficial effect for our patients. The current study was undertaken to determine the effect of timing of weight bearing after a surgically treated tibial shaft fracture. Surgically treated diaphyseal tibial fractures were retrospectively studied between 2007 and 2015. The timing of initial weight bearing (IWB) was analysed as a predictor for impaired healing in a multivariate regression. Totally, 166 diaphyseal tibial fractures were included, 86 cases with impaired healing and 80 with normal healing. The mean age was 38.7 years (range 16-89). The mean time until IWB was significantly shorter in the normal fracture healing group (2.6 vs 7.4 weeks, p < 0.001). Correlation analysis yielded four possible confounders: infection requiring surgical intervention, fracture type, fasciotomy and open fractures. Logistic regression identified IWB as an independent predictor for impaired healing with an odds ratio of 1.13 per week delay (95% CI 1.03-1.25). Delay in initial weight bearing is independently associated with impaired fracture healing in surgically treated tibial shaft fractures. Unlike other factors such as fracture type or soft tissue condition, early resumption of weight bearing can be influenced by the treating physician and this factor therefore has a direct clinical relevance. This study indicates that early resumption of weight bearing should be the treatment goal in fracture fixation. 3b.

Regression analysis of clustered failure time data with informative cluster size under the additive transformation models.

PubMed

Chen, Ling; Feng, Yanqin; Sun, Jianguo

2017-10-01

This paper discusses regression analysis of clustered failure time data, which occur when the failure times of interest are collected from clusters. In particular, we consider the situation where the correlated failure times of interest may be related to cluster sizes. For inference, we present two estimation procedures, the weighted estimating equation-based method and the within-cluster resampling-based method, when the correlated failure times of interest arise from a class of additive transformation models. The former makes use of the inverse of cluster sizes as weights in the estimating equations, while the latter can be easily implemented by using the existing software packages for right-censored failure time data. An extensive simulation study is conducted and indicates that the proposed approaches work well in both the situations with and without informative cluster size. They are applied to a dental study that motivated this study.

Multivariate Analysis, Retrieval, and Storage System (MARS). Volume 6: MARS System - A Sample Problem (Gross Weight of Subsonic Transports)

NASA Technical Reports Server (NTRS)

Hague, D. S.; Woodbury, N. W.

1975-01-01

The Mars system is a tool for rapid prediction of aircraft or engine characteristics based on correlation-regression analysis of past designs stored in the data bases. An example of output obtained from the MARS system, which involves derivation of an expression for gross weight of subsonic transport aircraft in terms of nine independent variables is given. The need is illustrated for careful selection of correlation variables and for continual review of the resulting estimation equations. For Vol. 1, see N76-10089.

Comparison of energy expenditure to walk or run a mile in adult normal weight and overweight men and women.

PubMed

Loftin, Mark; Waddell, Dwight E; Robinson, James H; Owens, Scott G

2010-10-01

We compared the energy expenditure to walk or run a mile in adult normal weight walkers (NWW), overweight walkers (OW), and marathon runners (MR). The sample consisted of 19 NWW, 11 OW, and 20 MR adults. Energy expenditure was measured at preferred walking speed (NWW and OW) and running speed of a recently completed marathon. Body composition was assessed via dual-energy x-ray absorptiometry. Analysis of variance was used to compare groups with the Scheffe's procedure used for post hoc analysis. Multiple regression analysis was used to predict energy expenditure. Results that indicated OW exhibited significantly higher (p < 0.05) mass and fat weight than NWW or MR. Similar values were found between NWW and MR. Absolute energy expenditure to walk or run a mile was similar between groups (NWW 93.9 ± 15.0, OW 98.4 ± 29.9, MR 99.3 ± 10.8 kcal); however, significant differences were noted when energy expenditure was expressed relative to mass (MR > NWW > OW). When energy expenditure was expressed per kilogram of fat-free mass, similar values were found across groups. Multiple regression analysis yielded mass and gender as significant predictors of energy expenditure (R = 0.795, SEE = 10.9 kcal). We suggest that walking is an excellent physical activity for energy expenditure in overweight individuals that are capable of walking without predisposed conditions such as osteoarthritis or cardiovascular risk factors. Moreover, from a practical perspective, our regression equation (kcal = mass (kg) × 0.789 - gender (men = 1, women = 2) × 7.634 + 51.109) allows for the prediction of energy expenditure for a given distance (mile) rather than predicting energy expenditure for a given time (minutes).

What Matters in Weight Loss? An In-Depth Analysis of Self-Monitoring

PubMed Central

Hill, James O; Kushner, Robert F; Lindquist, Richard; Brunning, Scott; Margulies, Amy

2017-01-01

Background Using technology to self-monitor body weight, dietary intake, and physical activity is a common practice used by consumers and health companies to increase awareness of current and desired behaviors in weight loss. Understanding how to best use the information gathered by these relatively new methods needs to be further explored. Objective The purpose of this study was to analyze the contribution of self-monitoring to weight loss in participants in a 6-month commercial weight-loss intervention administered by Retrofit and to specifically identify the significant contributors to weight loss that are associated with behavior and outcomes. Methods A retrospective analysis was performed using 2113 participants enrolled from 2011 to 2015 in a Retrofit weight-loss program. Participants were males and females aged 18 years or older with a starting body mass index of ≥25 kg/m2, who also provided a weight measurement at the sixth month of the program. Multiple regression analysis was performed using all measures of self-monitoring behaviors involving weight measurements, dietary intake, and physical activity to predict weight loss at 6 months. Each significant predictor was analyzed in depth to reveal the impact on outcome. Results Participants in the Retrofit Program lost a mean –5.58% (SE 0.12) of their baseline weight with 51.87% (1096/2113) of participants losing at least 5% of their baseline weight. Multiple regression model (R2=.197, P<0.001) identified the following measures as significant predictors of weight loss at 6 months: number of weigh-ins per week (P<.001), number of steps per day (P=.02), highly active minutes per week (P<.001), number of food log days per week (P<.001), and the percentage of weeks with five or more food logs (P<.001). Weighing in at least three times per week, having a minimum of 60 highly active minutes per week, food logging at least three days per week, and having 64% (16.6/26) or more weeks with at least five food logs were associated with clinically significant weight loss for both male and female participants. Conclusions The self-monitoring behaviors of self-weigh-in, daily steps, high-intensity activity, and persistent food logging were significant predictors of weight loss during a 6-month intervention. PMID:28500022

Influence diagnostics in meta-regression model.

PubMed

Shi, Lei; Zuo, ShanShan; Yu, Dalei; Zhou, Xiaohua

2017-09-01

This paper studies the influence diagnostics in meta-regression model including case deletion diagnostic and local influence analysis. We derive the subset deletion formulae for the estimation of regression coefficient and heterogeneity variance and obtain the corresponding influence measures. The DerSimonian and Laird estimation and maximum likelihood estimation methods in meta-regression are considered, respectively, to derive the results. Internal and external residual and leverage measure are defined. The local influence analysis based on case-weights perturbation scheme, responses perturbation scheme, covariate perturbation scheme, and within-variance perturbation scheme are explored. We introduce a method by simultaneous perturbing responses, covariate, and within-variance to obtain the local influence measure, which has an advantage of capable to compare the influence magnitude of influential studies from different perturbations. An example is used to illustrate the proposed methodology. Copyright © 2017 John Wiley & Sons, Ltd.

Inverse odds ratio-weighted estimation for causal mediation analysis.

PubMed

Tchetgen Tchetgen, Eric J

2013-11-20

An important scientific goal of studies in the health and social sciences is increasingly to determine to what extent the total effect of a point exposure is mediated by an intermediate variable on the causal pathway between the exposure and the outcome. A causal framework has recently been proposed for mediation analysis, which gives rise to new definitions, formal identification results and novel estimators of direct and indirect effects. In the present paper, the author describes a new inverse odds ratio-weighted approach to estimate so-called natural direct and indirect effects. The approach, which uses as a weight the inverse of an estimate of the odds ratio function relating the exposure and the mediator, is universal in that it can be used to decompose total effects in a number of regression models commonly used in practice. Specifically, the approach may be used for effect decomposition in generalized linear models with a nonlinear link function, and in a number of other commonly used models such as the Cox proportional hazards regression for a survival outcome. The approach is simple and can be implemented in standard software provided a weight can be specified for each observation. An additional advantage of the method is that it easily incorporates multiple mediators of a categorical, discrete or continuous nature. Copyright © 2013 John Wiley & Sons, Ltd.

Health behavior change counseling in surgery for degenerative lumbar spinal stenosis. Part II: patient activation mediates the effects of health behavior change counseling on rehabilitation engagement.

PubMed

Skolasky, Richard L; Maggard, Anica M; Li, David; Riley, Lee H; Wegener, Stephen T

2015-07-01

To determine the effect of health behavior change counseling (HBCC) on patient activation and the influence of patient activation on rehabilitation engagement, and to identify common barriers to engagement among individuals undergoing surgery for degenerative lumbar spinal stenosis. Prospective clinical trial. Academic medical center. Consecutive lumbar spine surgery patients (N=122) defined in our companion article (Part I) were assigned to a control group (did not receive HBCC, n=59) or HBCC group (received HBCC, n=63). Brief motivational interviewing-based HBCC versus control (significance, P<.05). We assessed patient activation before and after intervention. Rehabilitation engagement was assessed using the physical therapist-reported Hopkins Rehabilitation Engagement Rating Scale and by a ratio of self-reported physical therapy and home exercise completion. Common barriers to rehabilitation engagement were identified through thematic analysis. Patient activation predicted engagement (standardized regression weight, .682; P<.001). Postintervention patient activation was predicted by baseline patient activation (standardized regression weight, .808; P<.001) and receipt of HBCC (standardized regression weight, .444; P<.001). The effect of HBCC on rehabilitation engagement was mediated by patient activation (standardized regression weight, .079; P=.395). One-third of the HBCC group did not show improvement compared with the control group. Thematic analysis identified 3 common barriers to engagement: (1) low self-efficacy because of lack of knowledge and support (62%); (2) anxiety related to fear of movement (57%); and (3) concern about pain management (48%). The influence of HBCC on rehabilitation engagement was mediated by patient activation. Despite improvements in patient activation, one-third of patients reported low rehabilitation engagement. Addressing these barriers should lead to greater improvements in rehabilitation engagement. Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

A primer for biomedical scientists on how to execute model II linear regression analysis.

PubMed

Ludbrook, John

2012-04-01

1. There are two very different ways of executing linear regression analysis. One is Model I, when the x-values are fixed by the experimenter. The other is Model II, in which the x-values are free to vary and are subject to error. 2. I have received numerous complaints from biomedical scientists that they have great difficulty in executing Model II linear regression analysis. This may explain the results of a Google Scholar search, which showed that the authors of articles in journals of physiology, pharmacology and biochemistry rarely use Model II regression analysis. 3. I repeat my previous arguments in favour of using least products linear regression analysis for Model II regressions. I review three methods for executing ordinary least products (OLP) and weighted least products (WLP) regression analysis: (i) scientific calculator and/or computer spreadsheet; (ii) specific purpose computer programs; and (iii) general purpose computer programs. 4. Using a scientific calculator and/or computer spreadsheet, it is easy to obtain correct values for OLP slope and intercept, but the corresponding 95% confidence intervals (CI) are inaccurate. 5. Using specific purpose computer programs, the freeware computer program smatr gives the correct OLP regression coefficients and obtains 95% CI by bootstrapping. In addition, smatr can be used to compare the slopes of OLP lines. 6. When using general purpose computer programs, I recommend the commercial programs systat and Statistica for those who regularly undertake linear regression analysis and I give step-by-step instructions in the Supplementary Information as to how to use loss functions. © 2011 The Author. Clinical and Experimental Pharmacology and Physiology. © 2011 Blackwell Publishing Asia Pty Ltd.

A phenomenological biological dose model for proton therapy based on linear energy transfer spectra.

PubMed

Rørvik, Eivind; Thörnqvist, Sara; Stokkevåg, Camilla H; Dahle, Tordis J; Fjaera, Lars Fredrik; Ytre-Hauge, Kristian S

2017-06-01

The relative biological effectiveness (RBE) of protons varies with the radiation quality, quantified by the linear energy transfer (LET). Most phenomenological models employ a linear dependency of the dose-averaged LET (LET d ) to calculate the biological dose. However, several experiments have indicated a possible non-linear trend. Our aim was to investigate if biological dose models including non-linear LET dependencies should be considered, by introducing a LET spectrum based dose model. The RBE-LET relationship was investigated by fitting of polynomials from 1st to 5th degree to a database of 85 data points from aerobic in vitro experiments. We included both unweighted and weighted regression, the latter taking into account experimental uncertainties. Statistical testing was performed to decide whether higher degree polynomials provided better fits to the data as compared to lower degrees. The newly developed models were compared to three published LET d based models for a simulated spread out Bragg peak (SOBP) scenario. The statistical analysis of the weighted regression analysis favored a non-linear RBE-LET relationship, with the quartic polynomial found to best represent the experimental data (P = 0.010). The results of the unweighted regression analysis were on the borderline of statistical significance for non-linear functions (P = 0.053), and with the current database a linear dependency could not be rejected. For the SOBP scenario, the weighted non-linear model estimated a similar mean RBE value (1.14) compared to the three established models (1.13-1.17). The unweighted model calculated a considerably higher RBE value (1.22). The analysis indicated that non-linear models could give a better representation of the RBE-LET relationship. However, this is not decisive, as inclusion of the experimental uncertainties in the regression analysis had a significant impact on the determination and ranking of the models. As differences between the models were observed for the SOBP scenario, both non-linear LET spectrum- and linear LET d based models should be further evaluated in clinically realistic scenarios. © 2017 American Association of Physicists in Medicine.

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…

Censored quantile regression with recursive partitioning-based weights

PubMed Central

Wey, Andrew; Wang, Lan; Rudser, Kyle

2014-01-01

Censored quantile regression provides a useful alternative to the Cox proportional hazards model for analyzing survival data. It directly models the conditional quantile of the survival time and hence is easy to interpret. Moreover, it relaxes the proportionality constraint on the hazard function associated with the popular Cox model and is natural for modeling heterogeneity of the data. Recently, Wang and Wang (2009. Locally weighted censored quantile regression. Journal of the American Statistical Association 103, 1117–1128) proposed a locally weighted censored quantile regression approach that allows for covariate-dependent censoring and is less restrictive than other censored quantile regression methods. However, their kernel smoothing-based weighting scheme requires all covariates to be continuous and encounters practical difficulty with even a moderate number of covariates. We propose a new weighting approach that uses recursive partitioning, e.g. survival trees, that offers greater flexibility in handling covariate-dependent censoring in moderately high dimensions and can incorporate both continuous and discrete covariates. We prove that this new weighting scheme leads to consistent estimation of the quantile regression coefficients and demonstrate its effectiveness via Monte Carlo simulations. We also illustrate the new method using a widely recognized data set from a clinical trial on primary biliary cirrhosis. PMID:23975800

Studying Canonical Analysis: A Reply to Thorndike's Comments

ERIC Educational Resources Information Center

Barcikowski, Robert S.; Stevens, James P.

1976-01-01

This article is a rejoinder to TM 502 249. Each of Thorndike's comments are examined. A possible solution to the large number of subjects necessary for stable weights and variate-variable correlations using ridge regression procedures is suggested. (RC)

Aircraft wing weight build-up methodology with modification for materials and construction techniques

NASA Technical Reports Server (NTRS)

York, P.; Labell, R. W.

1980-01-01

An aircraft wing weight estimating method based on a component buildup technique is described. A simplified analytically derived beam model, modified by a regression analysis, is used to estimate the wing box weight, utilizing a data base of 50 actual airplane wing weights. Factors representing materials and methods of construction were derived and incorporated into the basic wing box equations. Weight penalties to the wing box for fuel, engines, landing gear, stores and fold or pivot are also included. Methods for estimating the weight of additional items (secondary structure, control surfaces) have the option of using details available at the design stage (i.e., wing box area, flap area) or default values based on actual aircraft from the data base.

Regression equations for estimating flood flows for the 2-, 10-, 25-, 50-, 100-, and 500-Year recurrence intervals in Connecticut

USGS Publications Warehouse

Ahearn, Elizabeth A.

2004-01-01

Multiple linear-regression equations were developed to estimate the magnitudes of floods in Connecticut for recurrence intervals ranging from 2 to 500 years. The equations can be used for nonurban, unregulated stream sites in Connecticut with drainage areas ranging from about 2 to 715 square miles. Flood-frequency data and hydrologic characteristics from 70 streamflow-gaging stations and the upstream drainage basins were used to develop the equations. The hydrologic characteristics?drainage area, mean basin elevation, and 24-hour rainfall?are used in the equations to estimate the magnitude of floods. Average standard errors of prediction for the equations are 31.8, 32.7, 34.4, 35.9, 37.6 and 45.0 percent for the 2-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals, respectively. Simplified equations using only one hydrologic characteristic?drainage area?also were developed. The regression analysis is based on generalized least-squares regression techniques. Observed flows (log-Pearson Type III analysis of the annual maximum flows) from five streamflow-gaging stations in urban basins in Connecticut were compared to flows estimated from national three-parameter and seven-parameter urban regression equations. The comparison shows that the three- and seven- parameter equations used in conjunction with the new statewide equations generally provide reasonable estimates of flood flows for urban sites in Connecticut, although a national urban flood-frequency study indicated that the three-parameter equations significantly underestimated flood flows in many regions of the country. Verification of the accuracy of the three-parameter or seven-parameter national regression equations using new data from Connecticut stations was beyond the scope of this study. A technique for calculating flood flows at streamflow-gaging stations using a weighted average also is described. Two estimates of flood flows?one estimate based on the log-Pearson Type III analyses of the annual maximum flows at the gaging station, and the other estimate from the regression equation?are weighted together based on the years of record at the gaging station and the equivalent years of record value determined from the regression. Weighted averages of flood flows for the 2-, 10-, 25-, 50-, 100-, and 500-year recurrence intervals are tabulated for the 70 streamflow-gaging stations used in the regression analysis. Generally, weighted averages give the most accurate estimate of flood flows at gaging stations. An evaluation of the Connecticut's streamflow-gaging network was performed to determine whether the spatial coverage and range of geographic and hydrologic conditions are adequately represented for transferring flood characteristics from gaged to ungaged sites. Fifty-one of 54 stations in the current (2004) network support one or more flood needs of federal, state, and local agencies. Twenty-five of 54 stations in the current network are considered high-priority stations by the U.S. Geological Survey because of their contribution to the longterm understanding of floods, and their application for regionalflood analysis. Enhancements to the network to improve overall effectiveness for regionalization can be made by increasing the spatial coverage of gaging stations, establishing stations in regions of the state that are not well-represented, and adding stations in basins with drainage area sizes not represented. Additionally, the usefulness of the network for characterizing floods can be maintained and improved by continuing operation at the current stations because flood flows can be more accurately estimated at stations with continuous, long-term record.

Alpha-lipoic acid (ALA) as a supplementation for weight loss: results from a meta-analysis of randomized controlled trials.

PubMed

Kucukgoncu, S; Zhou, E; Lucas, K B; Tek, C

2017-05-01

Obesity is associated with significant morbidity and mortality rates. Even modest weight loss may be associated with health benefits. Alpha-lipoic acid (ALA) is a naturally occurring antioxidant. Studies have suggested anti-obesity properties of ALA; however, results are inconsistent. The purpose of this study is to conduct a meta-analysis of the effect of ALA on weight and body mass index (BMI). A comprehensive, systematic literature search identified 10 articles on randomized, double-blind, placebo-controlled studies involving ALA. We conducted a meta-analysis of mean weight and BMI change differences between ALA and placebo treatment groups. Alpha-lipoic acid treatment coincided with a statistically significant 1.27 kg (confidence interval = 0.25 to 2.29) greater mean weight loss compared with the placebo group. A significant overall mean BMI difference of -0.43 kg/ m 2 (confidence interval = -0.82 to -0.03) was found between the ALA and placebo groups. Meta-regression analysis showed no significance in ALA dose on BMI and weight changes. Study duration significantly affected BMI change, but not weight change. Alpha-lipoic acid treatment showed small, yet significant short-term weight loss compared with placebo. Further research is needed to examine the effect of different doses and the long-term benefits of ALA on weight management. © 2017 World Obesity Federation.

Weight Regain, But Not Weight Loss, Is Related to Competitive Success in Real-life Mixed Martial Arts Competition.

PubMed

Coswig, Victor Silveira; Miarka, Bianca; Pires, Daniel Alvarez; da Silva, Levy Mendes; Bartel, Charles; Del Vecchio, Fabrício Boscolo

2018-05-14

We aimed to describe the nutritional and behavioural strategies for rapid weight loss (RWL), investigate the effects of RWL and weight regain (WRG) in winners and losers and verify mood state and technical-tactical/time-motion parameters in Mixed Martial Arts (MMA). The sample consisted of MMA athletes after a single real match and was separated into two groups: Winners (n=8, age: 25.4±6.1yo., height: 173.9±0.2cm, habitual body mass (BM): 89.9±17.3kg) and Losers (n=7, age: 24.4±6.8yo., height: 178.4±0.9cm, habitual BM: 90.8±19.5kg). Both groups exhibited RWL and WRG, verified their macronutrient intake, underwent weight and height assessments and completed two questionnaires (POMS and RWL) at i) 24 h before weigh-in, ii) weigh-in, iii) post-bout and iv) during a validated time-motion and technical-tactical analysis during the bout. Variance analysis, repeated measures and a logistic regression analysis were used. The main results showed significant differences between the time points in terms of total caloric intake as well as carbohydrate, protein and lipid ingestion. Statistical differences in combat analysis were observed between the winners and losers in terms of high-intensity relative time [58(10;98) s and 32(1;60) s, respectively], lower limb sequences [3.5(1.0;7.5) sequences and 1.0(0.0;1.0) sequences, respectively], and ground and pound actions [2.5(0.0;4.5) actions and 0.0(0.0;0.5) actions, respectively], and logistic regression confirmed the importance of high-intensity relative time and lower limb sequences on MMA performance. RWL and WRG strategies were related to technical-tactical and time-motion patterns as well as match outcomes. Weight management should be carefully supervised by specialized professionals to reduce health risks and raise competitive performance.

Relationships among body weight, joint moments generated during functional activities, and hip bone mass in older adults

PubMed Central

Wang, Man-Ying; Flanagan, Sean P.; Song, Joo-Eun; Greendale, Gail A.; Salem, George J.

2012-01-01

Objective To investigate the relationships among hip joint moments produced during functional activities and hip bone mass in sedentary older adults. Methods Eight male and eight female older adults (70–85 yr) performed functional activities including walking, chair sit–stand–sit, and stair stepping at a self-selected pace while instrumented for biomechanical analysis. Bone mass at proximal femur, femoral neck, and greater trochanter were measured by dual-energy X-ray absorptiometry. Three-dimensional hip moments were obtained using a six-camera motion analysis system, force platforms, and inverse dynamics techniques. Pearson’s correlation coefficients were employed to assess the relationships among hip bone mass, height, weight, age, and joint moments. Stepwise regression analyses were performed to determine the factors that significantly predicted bone mass using all significant variables identified in the correlation analysis. Findings Hip bone mass was not significantly correlated with moments during activities in men. Conversely, in women bone mass at all sites were significantly correlated with weight, moments generated with stepping, and moments generated with walking (p < 0.05 to p < 0.001). Regression analysis results further indicated that the overall moments during stepping independently predicted up to 93% of the variability in bone mass at femoral neck and proximal femur; whereas weight independently predicted up to 92% of the variability in bone mass at greater trochanter. Interpretation Submaximal loading events produced during functional activities were highly correlated with hip bone mass in sedentary older women, but not men. The findings may ultimately be used to modify exercise prescription for the preservation of bone mass. PMID:16631283

Weight Fluctuation and Postmenopausal Breast Cancer in the National Health and Nutrition Examination Survey I Epidemiologic Follow-Up Study.

PubMed

Komaroff, Marina

2016-01-01

The aim of this study is to investigate if weight fluctuation is an independent risk factor for postmenopausal breast cancer (PBC) among women who gained weight in adult years. NHANES I Epidemiologic Follow-Up Study (NHEFS) database was used in the study. Women that were cancers-free at enrollment and diagnosed for the first time with breast cancer at age 50 or greater were considered cases. Controls were chosen from the subset of cancers-free women and matched to cases by years of follow-up and status of body mass index (BMI) at 25 years of age. Weight fluctuation was measured by the root-mean-square-error (RMSE) from a simple linear regression model for each woman with their body mass index (BMI) regressed on age (started at 25 years) while women with the positive slope from this regression were defined as weight gainers. Data were analyzed using conditional logistic regression models. A total of 158 women were included into the study. The conditional logistic regression adjusted for weight gain demonstrated positive association between weight fluctuation in adult years and postmenopausal breast cancers (odds ratio/OR = 1.67; 95% confidence interval/CI: 1.06-2.66). The data suggested that long-term weight fluctuation was significant risk factor for PBC among women who gained weight in adult years. This finding underscores the importance of maintaining lost weight and avoiding weight fluctuation.

Weight Fluctuation and Postmenopausal Breast Cancer in the National Health and Nutrition Examination Survey I Epidemiologic Follow-Up Study

PubMed Central

Komaroff, Marina

2016-01-01

Objective. The aim of this study is to investigate if weight fluctuation is an independent risk factor for postmenopausal breast cancer (PBC) among women who gained weight in adult years. Methods. NHANES I Epidemiologic Follow-Up Study (NHEFS) database was used in the study. Women that were cancers-free at enrollment and diagnosed for the first time with breast cancer at age 50 or greater were considered cases. Controls were chosen from the subset of cancers-free women and matched to cases by years of follow-up and status of body mass index (BMI) at 25 years of age. Weight fluctuation was measured by the root-mean-square-error (RMSE) from a simple linear regression model for each woman with their body mass index (BMI) regressed on age (started at 25 years) while women with the positive slope from this regression were defined as weight gainers. Data were analyzed using conditional logistic regression models. Results. A total of 158 women were included into the study. The conditional logistic regression adjusted for weight gain demonstrated positive association between weight fluctuation in adult years and postmenopausal breast cancers (odds ratio/OR = 1.67; 95% confidence interval/CI: 1.06–2.66). Conclusions. The data suggested that long-term weight fluctuation was significant risk factor for PBC among women who gained weight in adult years. This finding underscores the importance of maintaining lost weight and avoiding weight fluctuation. PMID:26953120

Analysis of Friendship Network and its Role in Explaining Obesity

PubMed Central

Marathe, Achla; Pan, Zhengzheng; Apolloni, Andrea

2013-01-01

We employ Add Health data to show that friendship networks, constructed from mutual friendship nominations, are important in building weight perception, setting weight goals and measuring social marginalization among adolescents and young adults. We study the relationship between individuals’ perceived weight status, actual weight status, weight status relative to friends’ weight status and weight goals. This analysis helps us understand how individual weight perceptions might be formed, what these perceptions do to the weight goals, and how does friends’ relative weight affect weight perception and weight goals. Combining this information with individuals’ friendship network helps determine the influence of social relationships on weight related variables. Multinomial logistic regression results indicate that relative status is indeed a significant predictor of perceived status, and perceived status is a significant predictor of weight goals. We also address the issue of causality between actual weight status and social marginalization (as measured by the number of friends) and show that obesity precedes social marginalization in time rather than the other way around. This lends credence to the hypothesis that obesity leads to social marginalization not vice versa. Attributes of friendship network can provide new insights into effective interventions for combating obesity since adolescent friendships provide an important social context for weight related behaviors. PMID:25328818

A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression

PubMed Central

Jiang, Feng; Han, Ji-zhong

2018-01-01

Cross-domain collaborative filtering (CDCF) solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR). We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR) model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods. PMID:29623088

A Cross-Domain Collaborative Filtering Algorithm Based on Feature Construction and Locally Weighted Linear Regression.

PubMed

Yu, Xu; Lin, Jun-Yu; Jiang, Feng; Du, Jun-Wei; Han, Ji-Zhong

2018-01-01

Cross-domain collaborative filtering (CDCF) solves the sparsity problem by transferring rating knowledge from auxiliary domains. Obviously, different auxiliary domains have different importance to the target domain. However, previous works cannot evaluate effectively the significance of different auxiliary domains. To overcome this drawback, we propose a cross-domain collaborative filtering algorithm based on Feature Construction and Locally Weighted Linear Regression (FCLWLR). We first construct features in different domains and use these features to represent different auxiliary domains. Thus the weight computation across different domains can be converted as the weight computation across different features. Then we combine the features in the target domain and in the auxiliary domains together and convert the cross-domain recommendation problem into a regression problem. Finally, we employ a Locally Weighted Linear Regression (LWLR) model to solve the regression problem. As LWLR is a nonparametric regression method, it can effectively avoid underfitting or overfitting problem occurring in parametric regression methods. We conduct extensive experiments to show that the proposed FCLWLR algorithm is effective in addressing the data sparsity problem by transferring the useful knowledge from the auxiliary domains, as compared to many state-of-the-art single-domain or cross-domain CF methods.

[Spatial interpolation of soil organic matter using regression Kriging and geographically weighted regression Kriging].

PubMed

Yang, Shun-hua; Zhang, Hai-tao; Guo, Long; Ren, Yan

2015-06-01

Relative elevation and stream power index were selected as auxiliary variables based on correlation analysis for mapping soil organic matter. Geographically weighted regression Kriging (GWRK) and regression Kriging (RK) were used for spatial interpolation of soil organic matter and compared with ordinary Kriging (OK), which acts as a control. The results indicated that soil or- ganic matter was significantly positively correlated with relative elevation whilst it had a significantly negative correlation with stream power index. Semivariance analysis showed that both soil organic matter content and its residuals (including ordinary least square regression residual and GWR resi- dual) had strong spatial autocorrelation. Interpolation accuracies by different methods were esti- mated based on a data set of 98 validation samples. Results showed that the mean error (ME), mean absolute error (MAE) and root mean square error (RMSE) of RK were respectively 39.2%, 17.7% and 20.6% lower than the corresponding values of OK, with a relative-improvement (RI) of 20.63. GWRK showed a similar tendency, having its ME, MAE and RMSE to be respectively 60.6%, 23.7% and 27.6% lower than those of OK, with a RI of 59.79. Therefore, both RK and GWRK significantly improved the accuracy of OK interpolation of soil organic matter due to their in- corporation of auxiliary variables. In addition, GWRK performed obviously better than RK did in this study, and its improved performance should be attributed to the consideration of sample spatial locations.

Two-step estimation in ratio-of-mediator-probability weighted causal mediation analysis.

PubMed

Bein, Edward; Deutsch, Jonah; Hong, Guanglei; Porter, Kristin E; Qin, Xu; Yang, Cheng

2018-04-15

This study investigates appropriate estimation of estimator variability in the context of causal mediation analysis that employs propensity score-based weighting. Such an analysis decomposes the total effect of a treatment on the outcome into an indirect effect transmitted through a focal mediator and a direct effect bypassing the mediator. Ratio-of-mediator-probability weighting estimates these causal effects by adjusting for the confounding impact of a large number of pretreatment covariates through propensity score-based weighting. In step 1, a propensity score model is estimated. In step 2, the causal effects of interest are estimated using weights derived from the prior step's regression coefficient estimates. Statistical inferences obtained from this 2-step estimation procedure are potentially problematic if the estimated standard errors of the causal effect estimates do not reflect the sampling uncertainty in the estimation of the weights. This study extends to ratio-of-mediator-probability weighting analysis a solution to the 2-step estimation problem by stacking the score functions from both steps. We derive the asymptotic variance-covariance matrix for the indirect effect and direct effect 2-step estimators, provide simulation results, and illustrate with an application study. Our simulation results indicate that the sampling uncertainty in the estimated weights should not be ignored. The standard error estimation using the stacking procedure offers a viable alternative to bootstrap standard error estimation. We discuss broad implications of this approach for causal analysis involving propensity score-based weighting. Copyright © 2018 John Wiley & Sons, Ltd.

Optimal design application on the advanced aeroelastic rotor blade

NASA Technical Reports Server (NTRS)

Wei, F. S.; Jones, R.

1985-01-01

The vibration and performance optimization procedure using regression analysis was successfully applied to an advanced aeroelastic blade design study. The major advantage of this regression technique is that multiple optimizations can be performed to evaluate the effects of various objective functions and constraint functions. The data bases obtained from the rotorcraft flight simulation program C81 and Myklestad mode shape program are analytically determined as a function of each design variable. This approach has been verified for various blade radial ballast weight locations and blade planforms. This method can also be utilized to ascertain the effect of a particular cost function which is composed of several objective functions with different weighting factors for various mission requirements without any additional effort.

Inverse probability weighted least squares regression in the analysis of time-censored cost data: an evaluation of the approach using SEER-Medicare.

PubMed

Griffiths, Robert I; Gleeson, Michelle L; Danese, Mark D; O'Hagan, Anthony

2012-01-01

To assess the accuracy and precision of inverse probability weighted (IPW) least squares regression analysis for censored cost data. By using Surveillance, Epidemiology, and End Results-Medicare, we identified 1500 breast cancer patients who died and had complete cost information within the database. Patients were followed for up to 48 months (partitions) after diagnosis, and their actual total cost was calculated in each partition. We then simulated patterns of administrative and dropout censoring and also added censoring to patients receiving chemotherapy to simulate comparing a newer to older intervention. For each censoring simulation, we performed 1000 IPW regression analyses (bootstrap, sampling with replacement), calculated the average value of each coefficient in each partition, and summed the coefficients for each regression parameter to obtain the cumulative values from 1 to 48 months. The cumulative, 48-month, average cost was $67,796 (95% confidence interval [CI] $58,454-$78,291) with no censoring, $66,313 (95% CI $54,975-$80,074) with administrative censoring, and $66,765 (95% CI $54,510-$81,843) with administrative plus dropout censoring. In multivariate analysis, chemotherapy was associated with increased cost of $25,325 (95% CI $17,549-$32,827) compared with $28,937 (95% CI $20,510-$37,088) with administrative censoring and $29,593 ($20,564-$39,399) with administrative plus dropout censoring. Adding censoring to the chemotherapy group resulted in less accurate IPW estimates. This was ameliorated, however, by applying IPW within treatment groups. IPW is a consistent estimator of population mean costs if the weight is correctly specified. If the censoring distribution depends on some covariates, a model that accommodates this dependency must be correctly specified in IPW to obtain accurate estimates. Copyright © 2012 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Correlation Weights in Multiple Regression

ERIC Educational Resources Information Center

Waller, Niels G.; Jones, Jeff A.

2010-01-01

A general theory on the use of correlation weights in linear prediction has yet to be proposed. In this paper we take initial steps in developing such a theory by describing the conditions under which correlation weights perform well in population regression models. Using OLS weights as a comparison, we define cases in which the two weighting…

Geographically weighted regression model on poverty indicator

NASA Astrophysics Data System (ADS)

Slamet, I.; Nugroho, N. F. T. A.; Muslich

2017-12-01

In this research, we applied geographically weighted regression (GWR) for analyzing the poverty in Central Java. We consider Gaussian Kernel as weighted function. The GWR uses the diagonal matrix resulted from calculating kernel Gaussian function as a weighted function in the regression model. The kernel weights is used to handle spatial effects on the data so that a model can be obtained for each location. The purpose of this paper is to model of poverty percentage data in Central Java province using GWR with Gaussian kernel weighted function and to determine the influencing factors in each regency/city in Central Java province. Based on the research, we obtained geographically weighted regression model with Gaussian kernel weighted function on poverty percentage data in Central Java province. We found that percentage of population working as farmers, population growth rate, percentage of households with regular sanitation, and BPJS beneficiaries are the variables that affect the percentage of poverty in Central Java province. In this research, we found the determination coefficient R2 are 68.64%. There are two categories of district which are influenced by different of significance factors.

Quantification of endocrine disruptors and pesticides in water by gas chromatography-tandem mass spectrometry. Method validation using weighted linear regression schemes.

PubMed

Mansilha, C; Melo, A; Rebelo, H; Ferreira, I M P L V O; Pinho, O; Domingues, V; Pinho, C; Gameiro, P

2010-10-22

A multi-residue methodology based on a solid phase extraction followed by gas chromatography-tandem mass spectrometry was developed for trace analysis of 32 compounds in water matrices, including estrogens and several pesticides from different chemical families, some of them with endocrine disrupting properties. Matrix standard calibration solutions were prepared by adding known amounts of the analytes to a residue-free sample to compensate matrix-induced chromatographic response enhancement observed for certain pesticides. Validation was done mainly according to the International Conference on Harmonisation recommendations, as well as some European and American validation guidelines with specifications for pesticides analysis and/or GC-MS methodology. As the assumption of homoscedasticity was not met for analytical data, weighted least squares linear regression procedure was applied as a simple and effective way to counteract the greater influence of the greater concentrations on the fitted regression line, improving accuracy at the lower end of the calibration curve. The method was considered validated for 31 compounds after consistent evaluation of the key analytical parameters: specificity, linearity, limit of detection and quantification, range, precision, accuracy, extraction efficiency, stability and robustness. Copyright © 2010 Elsevier B.V. All rights reserved.

Standardization and validation of the body weight adjustment regression equations in Olympic weightlifting.

PubMed

Kauhanen, Heikki; Komi, Paavo V; Häkkinen, Keijo

2002-02-01

The problems in comparing the performances of Olympic weightlifters arise from the fact that the relationship between body weight and weightlifting results is not linear. In the present study, this relationship was examined by using a nonparametric curve fitting technique of robust locally weighted regression (LOWESS) on relatively large data sets of the weightlifting results made in top international competitions. Power function formulas were derived from the fitted LOWESS values to represent the relationship between the 2 variables in a way that directly compares the snatch, clean-and-jerk, and total weightlifting results of a given athlete with those of the world-class weightlifters (golden standards). A residual analysis of several other parametric models derived from the initial results showed that they all experience inconsistencies, yielding either underestimation or overestimation of certain body weights. In addition, the existing handicapping formulas commonly used in normalizing the performances of Olympic weightlifters did not yield satisfactory results when applied to the present data. It was concluded that the devised formulas may provide objective means for the evaluation of the performances of male weightlifters, regardless of their body weights, ages, or performance levels.

Peripherally inserted central venous catheter-associated complications exert negative effects on body weight gain in neonatal intensive care units.

PubMed

Wen, Jie; Yu, Qun; Chen, Haiyan; Chen, Niannian; Huang, Shourong; Cai, Wei

2017-01-01

The placement of a peripherally inserted central venous catheter (PICC) is an essential procedure in neonatal intensive care units (NICU). The aim of this study was to determine the risk of PICC complications in NICU, and further identify the effects of PICC complications on body weight gain in premature infants. A total of 304 premature infants who had a PICC inserted in NICU were enrolled in this study. The weight-for-age z-score (WAZ) at the time of PICC insertion and removal were calculated, and changes of WAZ in different groups were compared using a t-test. Risk factors for PICC complications were assessed using the chi-squared test and multiple logistic regression analysis. Thirty (9.97%) PICCs were removed due to complications. Of them, 14 PICCs were removed because of non-infectious complications and 16 PICCs were removed for central-line-associated bloodstream infections (CLABSIs). Multiple logistic regression analysis showed that premature infants with birth weight >1,500 g were less likely to have PICC complications than infants with birth weight <=1,500 g (OR, 0.29; 95% CI: 0.10-0.82; p=0.020). In addition, the changes in WAZ between PICC insertion and removal were significantly different in both infectious (-0.144±0.122, p<0.005) and non-infectious (-0.65±0.528, p<0.001) complications groups, compared with the no complications group (0.291±0.552). Findings from this study suggest that birth weight is a risk factor for PICC-associated complications in the NICU, and both infectious and non-infectious PICC complications are associated with poor body weight gain in premature infants.

Enhancement of partial robust M-regression (PRM) performance using Bisquare weight function

NASA Astrophysics Data System (ADS)

Mohamad, Mazni; Ramli, Norazan Mohamed; Ghani@Mamat, Nor Azura Md; Ahmad, Sanizah

2014-09-01

Partial Least Squares (PLS) regression is a popular regression technique for handling multicollinearity in low and high dimensional data which fits a linear relationship between sets of explanatory and response variables. Several robust PLS methods are proposed to accommodate the classical PLS algorithms which are easily affected with the presence of outliers. The recent one was called partial robust M-regression (PRM). Unfortunately, the use of monotonous weighting function in the PRM algorithm fails to assign appropriate and proper weights to large outliers according to their severity. Thus, in this paper, a modified partial robust M-regression is introduced to enhance the performance of the original PRM. A re-descending weight function, known as Bisquare weight function is recommended to replace the fair function in the PRM. A simulation study is done to assess the performance of the modified PRM and its efficiency is also tested in both contaminated and uncontaminated simulated data under various percentages of outliers, sample sizes and number of predictors.

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…

Drop-Weight Impact Test on U-Shape Concrete Specimens with Statistical and Regression Analyses

PubMed Central

Zhu, Xue-Chao; Zhu, Han; Li, Hao-Ran

2015-01-01

According to the principle and method of drop-weight impact test, the impact resistance of concrete was measured using self-designed U-shape specimens and a newly designed drop-weight impact test apparatus. A series of drop-weight impact tests were carried out with four different masses of drop hammers (0.875, 0.8, 0.675 and 0.5 kg). The test results show that the impact resistance results fail to follow a normal distribution. As expected, U-shaped specimens can predetermine the location of the cracks very well. It is also easy to record the cracks propagation during the test. The maximum of coefficient of variation in this study is 31.2%; it is lower than the values obtained from the American Concrete Institute (ACI) impact tests in the literature. By regression analysis, the linear relationship between the first-crack and ultimate failure impact resistance is good. It can suggested that a minimum number of specimens is required to reliably measure the properties of the material based on the observed levels of variation. PMID:28793540

The effect of the Family Case Management Program on 1996 birth outcomes in Illinois.

PubMed

Keeton, Kristie; Saunders, Stephen E; Koltun, David

2004-03-01

The purpose of this study was to determine if birth outcomes for Medicaid recipients were improved with participation in the Illinois Family Case Management Program. Health program data files were linked with the 1996 Illinois Vital Records linked birth-death certificate file. Logistic regression was used to characterize the variation in birth outcomes as a function of Family Case Management participation while statistically controlling for measurable factors found to be confounders. Results of the logistic regression analysis show that women who participated in the Family Care Management Program were significantly less likely to give birth to very low birth weight infants (odds ratio [OR] = 0.86, 95% confidence interval [CI] = 0.75, 0.99) and low birth weight infants (OR = 0.83, CI = 0.79, 0.89). For infant mortality, however, the adjusted OR (OR = 0.98, CI = 0.82, 1.17), although under 1, was not statistically significant. These results suggest that the Family Case Management Program may be effective in reducing very low birth weight and low birth weight rates among infants born to low-income women.

Weight-related abuse: Perceived emotional impact and the effect on disordered eating.

PubMed

Salwen, Jessica K; Hymowitz, Genna F; Bannon, Sarah M; O'Leary, K Daniel

2015-07-01

The purpose of this article was to evaluate theories that (1) weight-related abuse (WRA) plays a unique role in the development of disordered eating, above and beyond general childhood verbal abuse and weight-related teasing, and (2) the perceived emotional impact of WRA mediates the relationship between WRA and current disordered eating. Self-report questionnaires on childhood trauma, weight-related teasing, WRA, and current eating behaviors were administered to a total of 383 undergraduate students. In initial regressions, WRA significantly predicted binge eating, emotional eating, night eating, and unhealthy weight control. WRA continued to significantly predict all 4 forms of disordered eating following the introduction of measures of weight-related teasing and childhood verbal abuse into the regression. Latent variable analysis confirmed that perceived emotional impact of WRA mediated the relationship between WRA and disordered eating, and tests for indirect effects yielded a significant indirect effect of WRA on disordered eating through perceived emotional impact. In sum, WRA is a unique construct and the content of childhood or adolescent maltreatment is important in determining eventual psychopathology outcomes. These findings support the necessity of incorporating information on developmental history and cognitive factors into assessment and treatment of individuals with disordered eating. Copyright © 2015 Elsevier Ltd. All rights reserved.

Measuring decision weights in recognition experiments with multiple response alternatives: comparing the correlation and multinomial-logistic-regression methods.

PubMed

Dai, Huanping; Micheyl, Christophe

2012-11-01

Psychophysical "reverse-correlation" methods allow researchers to gain insight into the perceptual representations and decision weighting strategies of individual subjects in perceptual tasks. Although these methods have gained momentum, until recently their development was limited to experiments involving only two response categories. Recently, two approaches for estimating decision weights in m-alternative experiments have been put forward. One approach extends the two-category correlation method to m > 2 alternatives; the second uses multinomial logistic regression (MLR). In this article, the relative merits of the two methods are discussed, and the issues of convergence and statistical efficiency of the methods are evaluated quantitatively using Monte Carlo simulations. The results indicate that, for a range of values of the number of trials, the estimated weighting patterns are closer to their asymptotic values for the correlation method than for the MLR method. Moreover, for the MLR method, weight estimates for different stimulus components can exhibit strong correlations, making the analysis and interpretation of measured weighting patterns less straightforward than for the correlation method. These and other advantages of the correlation method, which include computational simplicity and a close relationship to other well-established psychophysical reverse-correlation methods, make it an attractive tool to uncover decision strategies in m-alternative experiments.

Quantitative Structure Retention Relationships of Polychlorinated Dibenzodioxins and Dibenzofurans

DTIC Science & Technology

1991-08-01

be a projection onto the X-Y plane. The algorithm for this calculation can be found in Stouch and Jurs (22), but was further refined by Rohrbaugh and...throughspace distances. WPSA2 (c) Weighted positive charged surface area. MOMH2 (c) Second major moment of inertia with hydrogens attached. CSTR 3 (d) Sum...of the models. The robust regression analysis method calculates a regression model using a least median squares algorithm which is not as susceptible

[Sociodemographic context of homicide in Mexico City: a spatial analysis].

PubMed

Fuentes Flores, César; Sánchez Salinas, Omar

2015-12-01

Investigate the spatial distribution pattern of the homicide rate and its relation to sociodemographic features in the Benito Juárez, Coyoacán, and Cuauhtémoc districts of Mexico City in 2010. Inferential cross-sectional study that uses spatial analysis methods to study the spatial association of the homicide rate and demographic features. Spatial association was determined through the location quotient, multiple regression analysis, and the use of geographically weighted regression. Homicides show a heterogeneous location pattern with high rates in areas with non-residential land use, low population density, and low marginalization. Spatial analysis tools are powerful instruments for the design of prevention- and recreation-focused public safety policies that aim to reduce mortality from external causes such as homicides.

Predicting meat yields and commercial meat cuts from carcasses of young bulls of Spanish breeds by the SEUROP method and an image analysis system.

PubMed

Oliver, A; Mendizabal, J A; Ripoll, G; Albertí, P; Purroy, A

2010-04-01

The SEUROP system is currently in use for carcass classification in Europe. Image analysis and other new technologies are being developed to enhance and supplement this classification system. After slaughtering, 91 carcasses of local Spanish beef breeds were weighed and classified according to the SEUROP system. Two digital photographs (a side and a dorsal view) were taken of the left carcass sides, and a total of 33 morphometric measurements (lengths, perimeters, areas) were made. Commercial butchering of these carcasses took place 24 h postmortem, and the different cuts were grouped according to four commercial meat cut quality categories: extra, first, second, and third. Multiple regression analysis of carcass weight and the SEUROP conformation score (x variables) on meat yield and the four commercial cut quality category yields (y variables) was performed as a measure of the accuracy of the SEUROP system. Stepwise regression analysis of carcass weight and the 33 morphometric image analysis measurements (x variables) and meat yield and yields of the four commercial cut quality categories (y variables) was carried out. Higher accuracy was achieved using image analysis than using only the current SEUROP conformation score. The regression coefficient values were between R(2)=0.66 and R(2)=0.93 (P<0.001) for the SEUROP system and between R(2)=0.81 and R(2)=0.94 (P<0.001) for the image analysis method. These results suggest that the image analysis method should be helpful as a means of supplementing and enhancing the SEUROP system for grading beef carcasses. 2009 Elsevier Ltd. All rights reserved.

Associations between macrolevel economic factors and weight distributions in low- and middle-income countries: a multilevel analysis of 200,000 adults in 40 countries.

PubMed

Nandi, Arijit; Sweet, Elizabeth; Kawachi, Ichiro; Heymann, Jody; Galea, Sandro

2014-02-01

We examined associations between macrolevel economic factors hypothesized to drive changes in distributions of weight and body mass index (BMI) in a representative sample of 200,796 men and women from 40 low- and middle-income countries. We used meta-regressions to describe ecological associations between macrolevel factors and mean BMIs across countries. Multilevel regression was used to assess the relation between macrolevel economic characteristics and individual odds of underweight and overweight relative to normal weight. In multilevel analyses adjusting for individual-level characteristics, a 1-standard-deviation increase in trade liberalization was associated with 13% (95% confidence interval [CI] = 0.76, 0.99), 17% (95% CI = 0.71, 0.96), 13% (95% CI = 0.76, 1.00), and 14% (95% CI = 0.75, 0.99) lower odds of underweight relative to normal weight among rural men, rural women, urban men, and urban women, respectively. Economic development was consistently associated with higher odds of overweight relative to normal weight. Among rural men, a 1-standard-deviation increase in foreign direct investment was associated with 17% (95% CI = 1.02, 1.35) higher odds of overweight relative to normal weight. Macrolevel economic factors may be implicated in global shifts in epidemiological patterns of weight.

Associations Between Macrolevel Economic Factors and Weight Distributions in Low- and Middle-Income Countries: A Multilevel Analysis of 200 000 Adults in 40 Countries

PubMed Central

Sweet, Elizabeth; Kawachi, Ichiro; Heymann, Jody; Galea, Sandro

2014-01-01

Objectives. We examined associations between macrolevel economic factors hypothesized to drive changes in distributions of weight and body mass index (BMI) in a representative sample of 200 796 men and women from 40 low- and middle-income countries. Methods. We used meta-regressions to describe ecological associations between macrolevel factors and mean BMIs across countries. Multilevel regression was used to assess the relation between macrolevel economic characteristics and individual odds of underweight and overweight relative to normal weight. Results. In multilevel analyses adjusting for individual-level characteristics, a 1–standard-deviation increase in trade liberalization was associated with 13% (95% confidence interval [CI] = 0.76, 0.99), 17% (95% CI = 0.71, 0.96), 13% (95% CI = 0.76, 1.00), and 14% (95% CI = 0.75, 0.99) lower odds of underweight relative to normal weight among rural men, rural women, urban men, and urban women, respectively. Economic development was consistently associated with higher odds of overweight relative to normal weight. Among rural men, a 1–standard-deviation increase in foreign direct investment was associated with 17% (95% CI = 1.02, 1.35) higher odds of overweight relative to normal weight. Conclusions. Macrolevel economic factors may be implicated in global shifts in epidemiological patterns of weight. PMID:24228649

Predictors of success after laparoscopic gastric bypass: a multivariate analysis of socioeconomic factors.

PubMed

Lutfi, R; Torquati, A; Sekhar, N; Richards, W O

2006-06-01

Laparoscopic gastric bypass (LGB) has proven efficacy in causing significant and durable weight loss. However, the degree of postoperative weight loss and metabolic improvement varies greatly among individuals. Our study is aimed to identify independent predictors of successful weight loss after LGB. Socioeconomic demographics were prospectively collected on patients undergoing LGB. Primary endpoint was percent of excess weight loss (EWL) at 1-year follow-up. Insufficient weight loss was defined as EWL or=52.8%. According to this definition, 147 patients (81.7%) achieved successful weight loss 1 year after LGB. On univariate analysis, preoperative BMI had a significant effect on EWL, with patients with BMI <50 achieving a higher percentage of EWL (91.7% vs 61.6%; p = 0.001). Marriage status was also a significant predictor of successful outcome, with single patients achieving a higher percentage of EWL than married patients (89.8% vs 77.7%; p = 0.04). Race had a noticeable but not statistically significant effect, with Caucasian patients achieving a higher percentage of EWL than African Americans (82.9% vs 60%; p = 0.06). Marital status remained an independent predictor of success in the multivariate logistic regression model after adjusting for covariates. Married patients were at more than two times the risk of failure compared to those who were unmarried (OR 2.6; 95% CI: 1.1-6.5, p = 0.04). Weight loss achieved at 1 year after LGB is suboptimal in superobese patients. Single patients with BMI < 50 had the best chance of achieving greater weight loss.

Predictors of Gestational Diabetes Mellitus in Chinese Women with Polycystic Ovary Syndrome: A Cross-Sectional Study.

PubMed

Zhang, Ya-Jie; Jin, Hua; Qin, Zhen-Li; Ma, Jin-Long; Zhao, Han; Zhang, Ling; Chen, Zi-Jiang

2016-01-01

This study aims to explore the independent predictors of gestational diabetes mellitus (GDM) in Chinese women with polycystic ovary syndrome (PCOS). This cross-sectional study analyzed primigravid women with PCOS and classified them as those with and without GDM. Independent risk factors and model performance were analyzed using multivariate logistic regression and the area under the curve (AUC) of receiver operating characteristic (ROC), respectively. Maternal body mass index, waist circumference, waist-to-hip ratio (WHR), fasting glucose, insulin, sex hormone-binding globulin (SHBG), homeostasis model assessment-insulin resistance (HOMA-IR) before pregnancy, gestation weight gain before 24 weeks and the incidence of family history of diabetes were different in the 2 groups. Logistic regression analysis showed that pre-pregnancy WHR, SHBG, HOMA-IR and gestation weight gain before 24 weeks were the independent predictors of GDM. ROC curve analysis confirmed that gestation weight gain before 24 weeks (AUC 0.767, 95% CI 0.688-0.841), pre-pregnant WHR (AUC 0.725, 95% CI 0.649-0.802), HOMA-IR (AUC 0.711, 95% CI 0.632-0.790) and SHBG levels (AUC 0.709, 95% CI 0.625-0.793) were the strong risk factors. In Chinese women with PCOS, factors of gestation weight gain before 24 weeks, pre-pregnant WHR, HOMA-IR and SHBG levels are strongly associated with subsequent development of GDM. © 2015 S. Karger AG, Basel.

Effects of infants' birth order, maternal age, and socio-economic status on birth weight.

PubMed

Ghaemmaghami, Seyed J; Nikniaz, Leila; Mahdavi, Reza; Nikniaz, Zeinab; Razmifard, Farzad; Afsharnia, Farzaneh

2013-09-01

To determine the effects of infants' birth order, maternal age, and socioeconomic status (SES) on birth weight. This cross-sectional study included a sample of 858 mothers recruited over a 6-month period in 2010, in a defined population of 9 urban health centers, and who were admitted for their infants' first vaccination. Maternal clinical data, demographic data, and infants' birth weight were obtained from the interview and maternal hospital files. Multiple regression and analysis of variance were used for data analysis. First and fourth births had lower birth weights compared with second and third births in all maternal ages in controlling parity, birth weight increases with maternal age up to the early 24, and then tends to level off. Male gender, maternal age 20-24 years, second and third births had a significant positive effect on birth weight. Lower family economic status and higher educational attainment were significantly associated with lower birth weight. For women in the 15-19 and 40-44 years age groups, the second birth order was associated with the most undesirable effect on birth weight. Accessibility of health care services, parity, maternal age, and socioeconomic factors are strongly associated with infants' birth weight.

What Matters in Weight Loss? An In-Depth Analysis of Self-Monitoring.

PubMed

Painter, Stefanie Lynn; Ahmed, Rezwan; Hill, James O; Kushner, Robert F; Lindquist, Richard; Brunning, Scott; Margulies, Amy

2017-05-12

Using technology to self-monitor body weight, dietary intake, and physical activity is a common practice used by consumers and health companies to increase awareness of current and desired behaviors in weight loss. Understanding how to best use the information gathered by these relatively new methods needs to be further explored. The purpose of this study was to analyze the contribution of self-monitoring to weight loss in participants in a 6-month commercial weight-loss intervention administered by Retrofit and to specifically identify the significant contributors to weight loss that are associated with behavior and outcomes. A retrospective analysis was performed using 2113 participants enrolled from 2011 to 2015 in a Retrofit weight-loss program. Participants were males and females aged 18 years or older with a starting body mass index of ≥25 kg/m2, who also provided a weight measurement at the sixth month of the program. Multiple regression analysis was performed using all measures of self-monitoring behaviors involving weight measurements, dietary intake, and physical activity to predict weight loss at 6 months. Each significant predictor was analyzed in depth to reveal the impact on outcome. Participants in the Retrofit Program lost a mean -5.58% (SE 0.12) of their baseline weight with 51.87% (1096/2113) of participants losing at least 5% of their baseline weight. Multiple regression model (R 2 =.197, P<0.001) identified the following measures as significant predictors of weight loss at 6 months: number of weigh-ins per week (P<.001), number of steps per day (P=.02), highly active minutes per week (P<.001), number of food log days per week (P<.001), and the percentage of weeks with five or more food logs (P<.001). Weighing in at least three times per week, having a minimum of 60 highly active minutes per week, food logging at least three days per week, and having 64% (16.6/26) or more weeks with at least five food logs were associated with clinically significant weight loss for both male and female participants. The self-monitoring behaviors of self-weigh-in, daily steps, high-intensity activity, and persistent food logging were significant predictors of weight loss during a 6-month intervention. ©Stefanie Lynn Painter, Rezwan Ahmed, James O Hill, Robert F Kushner, Richard Lindquist, Scott Brunning, Amy Margulies. Originally published in the Journal of Medical Internet Research (http://www.jmir.org), 12.05.2017.

The role of environmental heterogeneity in meta-analysis of gene-environment interactions with quantitative traits.

PubMed

Li, Shi; Mukherjee, Bhramar; Taylor, Jeremy M G; Rice, Kenneth M; Wen, Xiaoquan; Rice, John D; Stringham, Heather M; Boehnke, Michael

2014-07-01

With challenges in data harmonization and environmental heterogeneity across various data sources, meta-analysis of gene-environment interaction studies can often involve subtle statistical issues. In this paper, we study the effect of environmental covariate heterogeneity (within and between cohorts) on two approaches for fixed-effect meta-analysis: the standard inverse-variance weighted meta-analysis and a meta-regression approach. Akin to the results in Simmonds and Higgins (), we obtain analytic efficiency results for both methods under certain assumptions. The relative efficiency of the two methods depends on the ratio of within versus between cohort variability of the environmental covariate. We propose to use an adaptively weighted estimator (AWE), between meta-analysis and meta-regression, for the interaction parameter. The AWE retains full efficiency of the joint analysis using individual level data under certain natural assumptions. Lin and Zeng (2010a, b) showed that a multivariate inverse-variance weighted estimator retains full efficiency as joint analysis using individual level data, if the estimates with full covariance matrices for all the common parameters are pooled across all studies. We show consistency of our work with Lin and Zeng (2010a, b). Without sacrificing much efficiency, the AWE uses only univariate summary statistics from each study, and bypasses issues with sharing individual level data or full covariance matrices across studies. We compare the performance of the methods both analytically and numerically. The methods are illustrated through meta-analysis of interaction between Single Nucleotide Polymorphisms in FTO gene and body mass index on high-density lipoprotein cholesterol data from a set of eight studies of type 2 diabetes. © 2014 WILEY PERIODICALS, INC.

A canonical correlation neural network for multicollinearity and functional data.

PubMed

Gou, Zhenkun; Fyfe, Colin

2004-03-01

We review a recent neural implementation of Canonical Correlation Analysis and show, using ideas suggested by Ridge Regression, how to make the algorithm robust. The network is shown to operate on data sets which exhibit multicollinearity. We develop a second model which not only performs as well on multicollinear data but also on general data sets. This model allows us to vary a single parameter so that the network is capable of performing Partial Least Squares regression (at one extreme) to Canonical Correlation Analysis (at the other)and every intermediate operation between the two. On multicollinear data, the parameter setting is shown to be important but on more general data no particular parameter setting is required. Finally, we develop a second penalty term which acts on such data as a smoother in that the resulting weight vectors are much smoother and more interpretable than the weights without the robustification term. We illustrate our algorithms on both artificial and real data.

Characterizing multivariate decoding models based on correlated EEG spectral features

PubMed Central

McFarland, Dennis J.

2013-01-01

Objective Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Methods Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). Results The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Conclusions Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. Significance While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. PMID:23466267

Calorie Labeling in Chain Restaurants and Body Weight: Evidence from New York.

PubMed

Restrepo, Brandon J

2017-10-01

This study analyzes the impact of local mandatory calorie labeling laws implemented by New York jurisdictions on body weight. The analysis indicates that on average the point-of-purchase provision of calorie information on chain restaurant menus reduced body mass index (BMI) by 1.5% and lowered the risk of obesity by 12%. Quantile regression results indicate that calorie labeling has similar impacts across the BMI distribution. An analysis of heterogeneity suggests that calorie labeling has a larger impact on the body weight of lower income individuals, especially lower income minorities. The estimated impacts of calorie labeling on physical activity, smoking, and the consumption of alcoholic beverages, fruits, and vegetables are small in magnitude, which suggests that other margins of adjustment drive the body-weight impacts estimated here. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

Evaluation of dietary energy intake and physical activity in dogs undergoing a controlled weight-loss program.

PubMed

Wakshlag, Joseph J; Struble, Angela M; Warren, Barbour S; Maley, Mary; Panasevich, Matthew R; Cummings, Kevin J; Long, Grace M; Laflamme, Dorothy E

2012-02-15

To quantify physical activity and dietary energy intake in dogs enrolled in a controlled weight-loss program and assess relationships between energy intake and physical activity, sex, age, body weight, and body condition score (BCS). Prospective clinical study. 35 client-owned obese dogs (BCS > 7/9). Dogs were fed a therapeutic diet with energy intake restrictions to maintain weight loss of approximately 2%/wk. Collar-mounted pedometers were used to record the number of steps taken daily as a measure of activity. Body weight and BCS were assessed at the beginning of the weight-loss program and every 2 weeks thereafter throughout the study. Relationships between energy intake and sex, age, activity, BCS, and body weight at the end of the study were assessed via multivariable linear regression. Variables were compared among dogs stratified post hoc into inactive and active groups on the basis of mean number of steps taken (< or > 7,250 steps/d, respectively). Mean ± SD daily energy intake per unit of metabolic body weight (kg(0.75)) of active dogs was significantly greater than that of inactive dogs (53.6 ± 15.2 kcal/kg(0.75) vs 42.2 ± 9.7 kcal/kg(0.75), respectively) while maintaining weight-loss goals. In regression analysis, only the number of steps per day was significantly associated with energy intake. Increased physical activity was associated with higher energy intake while maintaining weight-loss goals. Each 1,000-step interval was associated with a 1 kcal/kg(0.75) increase in energy intake.

An analysis of first-time blood donors return behaviour using regression models.

PubMed

Kheiri, S; Alibeigi, Z

2015-08-01

Blood products have a vital role in saving many patients' lives. The aim of this study was to analyse blood donor return behaviour. Using a cross-sectional follow-up design of 5-year duration, 864 first-time donors who had donated blood were selected using a systematic sampling. The behaviours of donors via three response variables, return to donation, frequency of return to donation and the time interval between donations, were analysed based on logistic regression, negative binomial regression and Cox's shared frailty model for recurrent events respectively. Successful return to donation rated at 49·1% and the deferral rate was 13·3%. There was a significant reverse relationship between the frequency of return to donation and the time interval between donations. Sex, body weight and job had an effect on return to donation; weight and frequency of donation during the first year had a direct effect on the total frequency of donations. Age, weight and job had a significant effect on the time intervals between donations. Aging decreases the chances of return to donation and increases the time interval between donations. Body weight affects the three response variables, i.e. the higher the weight, the more the chances of return to donation and the shorter the time interval between donations. There is a positive correlation between the frequency of donations in the first year and the total number of return to donations. Also, the shorter the time interval between donations is, the higher the frequency of donations. © 2015 British Blood Transfusion Society.

Relationship between phenotype, carcass characteristics and the incidence of dark cutting in heifers.

PubMed

Mahmood, S; Basarab, J A; Dixon, W T; Bruce, H L

2016-11-01

Previous research has suggested that cattle predisposed to dark cutting can be identified from live animal or carcass characteristics. This hypothesis was tested using production and phenotype data from an existing data set collected from heifers (n=467) on study at three farms. Carcasses in the data set graded Canada AAA (n=136), AA (n=296), A (n=14), and B4 (dark cutting, n=21). Farm was identified as significant (P=0.0268) by CATMOD analysis and slaughter weight and carcass weight accounted for the variation in dark cutting frequency across the farms. Analysis of variance indicated that dark cutting heifers had reduced weight at weaning (P<0.0001) and at slaughter (P<0.0001), and produced reduced weight carcasses (P<0.0001). Results of logistic regression indicated that the probability of dark cutting was decreased in heifers slaughtered at live weight greater than 550kg and in carcasses weighing greater than 325kg. Copyright © 2016 Elsevier Ltd. All rights reserved.

Weight-based discrimination: an ubiquitary phenomenon?

PubMed

Sikorski, C; Spahlholz, J; Hartlev, M; Riedel-Heller, S G

2016-02-01

Despite strong indications of a high prevalence of weight-related stigmatization in individuals with obesity, limited attention has been given to the role of weight discrimination in examining the stigma obesity. Studies, up to date, rely on a limited basis of data sets and additional studies are needed to confirm the findings of previous studies. In particular, data for Europe are lacking, and are needed in light of a recent ruling of the European Court of Justice that addressed weight-based discrimination. The data were derived from a large representative telephone survey in Germany (n=3003). The dependent variable, weight-based discrimination, was assessed with a one-item question. The lifetime prevalence of weight discrimination across different sociodemographic variables was determined. Logistic regression models were used to assess the association of independent and dependent variables. A sub-group analysis was conducted analyzing all participants with a body mass index ⩾25 kg m(-)(2). The overall prevalence of weight-based discrimination was 7.3%. Large differences, however, were observed regarding weight status. In normal weight and overweight participants the prevalence was 5.6%, but this number doubled in participants with obesity class I (10.2%), and quadrupled in participants with obesity class II (18.7%) and underweight (19.7%). In participants with obesity class III, every third participant reported accounts of weight-based discrimination (38%). In regression models, after adjustment, the associations of weight status and female gender (odds ratio: 2.59, P<0.001) remained highly significant. Discrimination seems to be an ubiquitary phenomenon at least for some groups that are at special risk, such as heavier individuals and women. Our findings therefore emphasize the need for research and intervention on weight discrimination among adults with obesity, including anti-discrimination legislation.

Individual, social and environmental factors and their association with weight in rural-dwelling women.

PubMed

Harrison, Cheryce L; Teede, Helena J; Kozica, Samantha; Zoungas, Sophia; Lombard, Catherine B

2016-11-20

Obesity is a major public health concern and women living in rural settings present a high-risk group. With contributing factors poorly explored, we evaluated their association with weight in rural Australian women. Women aged 18-50 years of any body mass index (BMI) were recruited between October 2012 and April 2013 as part of a larger, randomised controlled trial within 42 rural towns. Measured weight and height as well as self-reported measures of individual health, physical activity, dietary intake, self-management, social support and environmental perception were collected. Statistical analysis included linear regression for continuous variables as well as chi-squared and logistic regression for categorical variables with all results adjusted for clustering. 649 women with a mean baseline age and BMI of 39.6±6.7 years and 28.8±6.9 kg/m 2 respectively, were studied. Overall, 65% were overweight or obese and 60% overall reported recent weight gain. There was a high intention to self-manage weight, with 68% attempting to lose weight recently, compared to 20% of women reporting health professional engagement for weight management. Obese women reported increased weight gain, energy intake, sitting time and prevalence of pre-existing health conditions. There was an inverse relationship between increased weight and scores for self-management, social support and health environment perception. Many women in rural communities reported recent weight gain and were attempting to self-manage their weight with little external support. Implications for Public Health: Initiatives to prevent weight gain require a multifaceted approach, with self-management strategies and social support in tandem with building a positive local environmental perception. © 2016 Public Health Association of Australia.

Quantifying female bodily attractiveness by a statistical analysis of body measurements.

PubMed

Gründl, Martin; Eisenmann-Klein, Marita; Prantl, Lukas

2009-03-01

To investigate what makes a female figure attractive, an extensive experiment was conducted using high-quality photographic stimulus material and several systematically varied figure parameters. The objective was to predict female bodily attractiveness by using figure measurements. For generating stimulus material, a frontal-view photograph of a woman with normal body proportions was taken. Using morphing software, 243 variations of this photograph were produced by systematically manipulating the following features: weight, hip width, waist width, bust size, and leg length. More than 34,000 people participated in the web-based experiment and judged the attractiveness of the figures. All of the altered figures were measured (e.g., bust width, underbust width, waist width, hip width, and so on). Based on these measurements, ratios were calculated (e.g., waist-to-hip ratio). A multiple regression analysis was designed to predict the attractiveness rank of a figure by using figure measurements. The results show that the attractiveness of a woman's figure may be predicted by using her body measurements. The regression analysis explains a variance of 80 percent. Important predictors are bust-to-underbust ratio, bust-to-waist ratio, waist-to-hip ratio, and an androgyny index (an indicator of a typical female body). The study shows that the attractiveness of a female figure is the result of complex interactions of numerous factors. It affirms the importance of viewing the appearance of a bodily feature in the context of other bodily features when performing preoperative analysis. Based on the standardized beta-weights of the regression model, the relative importance of figure parameters in context of preoperative analysis is discussed.

Development of LACIE CCEA-1 weather/wheat yield models. [regression analysis

NASA Technical Reports Server (NTRS)

Strommen, N. D.; Sakamoto, C. M.; Leduc, S. K.; Umberger, D. E. (Principal Investigator)

1979-01-01

The advantages and disadvantages of the casual (phenological, dynamic, physiological), statistical regression, and analog approaches to modeling for grain yield are examined. Given LACIE's primary goal of estimating wheat production for the large areas of eight major wheat-growing regions, the statistical regression approach of correlating historical yield and climate data offered the Center for Climatic and Environmental Assessment the greatest potential return within the constraints of time and data sources. The basic equation for the first generation wheat-yield model is given. Topics discussed include truncation, trend variable, selection of weather variables, episodic events, strata selection, operational data flow, weighting, and model results.

Estimation of Covariance Matrix on Bi-Response Longitudinal Data Analysis with Penalized Spline Regression

NASA Astrophysics Data System (ADS)

Islamiyati, A.; Fatmawati; Chamidah, N.

2018-03-01

The correlation assumption of the longitudinal data with bi-response occurs on the measurement between the subjects of observation and the response. It causes the auto-correlation of error, and this can be overcome by using a covariance matrix. In this article, we estimate the covariance matrix based on the penalized spline regression model. Penalized spline involves knot points and smoothing parameters simultaneously in controlling the smoothness of the curve. Based on our simulation study, the estimated regression model of the weighted penalized spline with covariance matrix gives a smaller error value compared to the error of the model without covariance matrix.

Association of prenatal lipid-based nutritional supplementation with fetal growth in rural Gambia.

PubMed

Johnson, William; Darboe, Momodou K; Sosseh, Fatou; Nshe, Patrick; Prentice, Andrew M; Moore, Sophie E

2017-04-01

Prenatal supplementation with protein-energy (PE) and/or multiple-micronutrients (MMNs) may improve fetal growth, but trials of lipid-based nutritional supplements (LNSs) have reported inconsistent results. We conducted a post-hoc analysis of non-primary outcomes in a trial in Gambia, with the aim to test the associations of LNS with fetal growth and explore how efficacy varies depending on nutritional status. The sample comprised 620 pregnant women in an individually randomized, partially blinded trial with four arms: (a) iron and folic acid (FeFol) tablet (usual care, referent group), (b) MMN tablet, (c) PE LNS, and (d) PE + MMN LNS. Analysis of variance examined unadjusted differences in fetal biometry z-scores at 20 and 30 weeks and neonatal anthropometry z-scores, while regression tested for modification of intervention-outcome associations by season and maternal height, body mass index, and weight gain. Despite evidence of between-arm differences in some fetal biometry, z-scores at birth were not greater in the intervention arms than the FeFol arm (e.g., birth weight z-scores: FeFol -0.71, MMN -0.63, PE -0.64, PE + MMN -0.62; group-wise p = .796). In regression analyses, intervention associations with birth weight and head circumference were modified by maternal weight gain between booking and 30 weeks gestation (e.g., PE + MMN associations with birth weight were +0.462 z-scores (95% CI [0.097, 0.826]) in the highest quartile of weight gain but -0.099 z-scores (-0.459, 0.260) in the lowest). In conclusion, we found no strong evidence that a prenatal LNS intervention was associated with better fetal growth in the whole sample. © 2016 The Authors. Maternal & Child Nutrition published by John Wiley & Sons Ltd.

Maternal biomass smoke exposure and birth weight in Malawi: Analysis of data from the 2010 Malawi Demographic and Health Survey.

PubMed

Milanzi, Edith B; Namacha, Ndifanji M

2017-06-01

Use of biomass fuels has been shown to contribute to ill health and complications in pregnancy outcomes such as low birthweight, neonatal deaths and mortality in developing countries. However, there is insufficient evidence of this association in the Sub-Saharan Africa and the Malawian population. We, therefore, investigated effects of exposure to biomass fuels on reduced birth weight in the Malawian population. We conducted a cross-sectional analysis using secondary data from the 2010 Malawi Demographic Health Survey with a total of 9124 respondents. Information on exposure to biomass fuels, birthweight, and size of child at birth as well as other relevant information on risk factors was obtained through a questionnaire. We used linear regression models for continuous birth weight outcome and logistic regression for the binary outcome. Models were systematically adjusted for relevant confounding factors. Use of high pollution fuels resulted in a 92 g (95% CI: -320.4; 136.4) reduction in mean birth weight compared to low pollution fuel use after adjustment for child, maternal as well as household characteristics. Full adjusted OR (95% CI) for risk of having size below average at birth was 1.29 (0.34; 4.48). Gender and birth order of child were the significant confounders factors in our adjusted models. We observed reduced birth weight in children whose mothers used high pollution fuels suggesting a negative effect of maternal exposure to biomass fuels on birth weight of the child. However, this reduction was not statistically significant. More carefully designed studies need to be carried out to explore effects of biomass fuels on pregnancy outcomes and health outcomes in general.

Effect of Intrahepatic Cholestasis of Pregnancy on Neonatal Birth Weight: A Meta-Analysis

PubMed Central

Li, Li; Chen, Yuan-Hua; Yang, Yuan-Yuan; Cong, Lin

2018-01-01

Objective: To evaluate the effect of intrahepatic cholestasis of pregnancy (ICP) on neonatal birth weight. Methods: Potential articles were identified by searching PubMed and Web of Science databases on April 30th, 2017. Using the Mantel-Haenszel random-effects or fixed-effects model, outcomes were summarized through weighted mean difference (WMD) and 95% confidence intervals (CI). Potential publication bias was tested using a funnel plot and the methods of Egger’s regression and Begg’s test. Results: A total of eight studies were included in our meta-analysis. Six studies reported data on neonatal birth weight in ICP and control pregnancies. Pooled data from the six studies showed that the birth weight in the ICP group was significantly lighter than in the control group. The overall pooled WMD was -175 g (95% CI: -301, -48). Meanwhile, pooled data from the other two studies indicated that the birth weight in the late-onset ICP group was heavier than in the early-onset ICP group (WMD: 267 g, 95% CI: 168, 366). Conclusion: Neonatal birth weights in ICP pregnancies were lower than in normal pregnancies. Furthermore, early-onset ICP is associated with a lower birth weight than late-onset ICP. PMID:28825589

Subsonic Aircraft With Regression and Neural-Network Approximators Designed

NASA Technical Reports Server (NTRS)

Patnaik, Surya N.; Hopkins, Dale A.

2004-01-01

At the NASA Glenn Research Center, NASA Langley Research Center's Flight Optimization System (FLOPS) and the design optimization testbed COMETBOARDS with regression and neural-network-analysis approximators have been coupled to obtain a preliminary aircraft design methodology. For a subsonic aircraft, the optimal design, that is the airframe-engine combination, is obtained by the simulation. The aircraft is powered by two high-bypass-ratio engines with a nominal thrust of about 35,000 lbf. It is to carry 150 passengers at a cruise speed of Mach 0.8 over a range of 3000 n mi and to operate on a 6000-ft runway. The aircraft design utilized a neural network and a regression-approximations-based analysis tool, along with a multioptimizer cascade algorithm that uses sequential linear programming, sequential quadratic programming, the method of feasible directions, and then sequential quadratic programming again. Optimal aircraft weight versus the number of design iterations is shown. The central processing unit (CPU) time to solution is given. It is shown that the regression-method-based analyzer exhibited a smoother convergence pattern than the FLOPS code. The optimum weight obtained by the approximation technique and the FLOPS code differed by 1.3 percent. Prediction by the approximation technique exhibited no error for the aircraft wing area and turbine entry temperature, whereas it was within 2 percent for most other parameters. Cascade strategy was required by FLOPS as well as the approximators. The regression method had a tendency to hug the data points, whereas the neural network exhibited a propensity to follow a mean path. The performance of the neural network and regression methods was considered adequate. It was at about the same level for small, standard, and large models with redundancy ratios (defined as the number of input-output pairs to the number of unknown coefficients) of 14, 28, and 57, respectively. In an SGI octane workstation (Silicon Graphics, Inc., Mountainview, CA), the regression training required a fraction of a CPU second, whereas neural network training was between 1 and 9 min, as given. For a single analysis cycle, the 3-sec CPU time required by the FLOPS code was reduced to milliseconds by the approximators. For design calculations, the time with the FLOPS code was 34 min. It was reduced to 2 sec with the regression method and to 4 min by the neural network technique. The performance of the regression and neural network methods was found to be satisfactory for the analysis and design optimization of the subsonic aircraft.

The effects of mindfulness training on weight-loss and health-related behaviours in adults with overweight and obesity: A systematic review and meta-analysis.

PubMed

Ruffault, Alexis; Czernichow, Sébastien; Hagger, Martin S; Ferrand, Margot; Erichot, Nelly; Carette, Claire; Boujut, Emilie; Flahault, Cécile

The aim of this study was to conduct a comprehensive quantitative synthesis of the effects of mindfulness training interventions on weight-loss and health behaviours in adults with overweight and obesity using meta-analytic techniques. Studies included in the analysis (k=12) were randomised controlled trials investigating the effects of any form of mindfulness training on weight loss, impulsive eating, binge eating, or physical activity participation in adults with overweight and obesity. Random effects meta-analysis revealed that mindfulness training had no significant effect on weight loss, but an overall negative effect on impulsive eating (d=-1.13) and binge eating (d=-.90), and a positive effect on physical activity levels (d=.42). Meta-regression analysis showed that methodological features of included studies accounted for 100% of statistical heterogeneity of the effects of mindfulness training on weight loss (R 2 =1,00). Among methodological features, the only significant predictor of weight loss was follow-up distance from post-intervention (β=1.18; p<.05), suggesting that the longer follow-up distances were associated with greater weight loss. Results suggest that mindfulness training has short-term benefits on health-related behaviours. Future studies should explore the effectiveness of mindfulness training on long-term post-intervention weight loss in adults with overweight and obesity. Copyright © 2016 Asia Oceania Association for the Study of Obesity. Published by Elsevier Ltd. All rights reserved.

Midupper arm circumference and weight-for-length z scores have different associations with body composition: evidence from a cohort of Ethiopian infants.

PubMed

Grijalva-Eternod, Carlos S; Wells, Jonathan C K; Girma, Tsinuel; Kæstel, Pernille; Admassu, Bitiya; Friis, Henrik; Andersen, Gregers S

2015-09-01

A midupper arm circumference (MUAC) <115 mm and weight-for-height z score (WHZ) or weight-for-length z score (WLZ) less than -3, all of which are recommended to identify severe wasting in children, often identify different children. The reasons behind this poor agreement are not well understood. We investigated the association between these 2 anthropometric indexes and body composition to help understand why they identify different children as wasted. We analyzed weight, length, MUAC, fat-mass (FM), and fat-free mass (FFM) data from 2470 measurements from 595 healthy Ethiopian infants obtained at birth and at 1.5, 2.5, 3.5, 4.5, and 6 mo of age. We derived WLZs by using 2006 WHO growth standards. We derived length-adjusted FM and FFM values as unexplained residuals after regressing each FM and FFM against length. We used a correlation analysis to assess associations between length, FFM, and FM (adjusted and nonadjusted for length) and the MUAC and WLZ and a multivariable regression analysis to assess the independent variability of length and length-adjusted FM and FFM with either the MUAC or the WLZ as the outcome. At all ages, length showed consistently strong positive correlations with the MUAC but not with the WLZ. Adjustment for length reduced observed correlation coefficients of FM and FFM with the MUAC but increased those for the WLZ. At all ages, both length-adjusted FM and FFM showed an independent association with the WLZ and MUAC with higher regression coefficients for the WLZ. Conversely, length showed greater regression coefficients for the MUAC. At all ages, the MUAC was shown to be more influenced than was the WLZ by the FM variability relative to the FFM variability. The MUAC and WLZ have different associations with body composition, and length influences these associations differently. Our results suggest that the WLZ is a good marker of tissue masses independent of length. The MUAC acts more as a composite index of poor growth indexing jointly tissue masses and length. This trial was registered at www.controlled-trials.com as ISRCTN46718296. © 2015 American Society for Nutrition.

STOCK Market Differences in Correlation-Based Weighted Network

NASA Astrophysics Data System (ADS)

Youn, Janghyuk; Lee, Junghoon; Chang, Woojin

We examined the sector dynamics of Korean stock market in relation to the market volatility. The daily price data of 360 stocks for 5019 trading days (from January, 1990 to August, 2008) in Korean stock market are used. We performed the weighted network analysis and employed four measures: the average, the variance, the intensity, and the coherence of network weights (absolute values of stock return correlations) to investigate the network structure of Korean stock market. We performed regression analysis using the four measures in the seven major industry sectors and the market (seven sectors combined). We found that the average, the intensity, and the coherence of sector (subnetwork) weights increase as market becomes volatile. Except for the "Financials" sector, the variance of sector weights also grows as market volatility increases. Based on the four measures, we can categorize "Financials," "Information Technology" and "Industrials" sectors into one group, and "Materials" and "Consumer Discretionary" sectors into another group. We investigated the distributions of intrasector and intersector weights for each sector and found the differences in "Financials" sector are most distinct.

Association between overweight and characteristics of young adult students: support for nursing care1

PubMed Central

Santiago, Jênifa Cavalcante dos Santos; Moreira, Thereza Maria Magalhães; Florêncio, Raquel Sampaio

2015-01-01

OBJECTIVE: to verify associations between overweight and the characteristics of young adult students to support nursing care. METHOD: case-control study conducted with young adults from public schools. The sample was composed of 441 participants (147 cases and 294 controls, with and without excess weight, respectively). Sociodemographic and clinical characteristics were collected together with exposure factors and anthropometrics. Multiple logistic regression was used. The study received Institutional Review Board approval. RESULTS: statistically significant association with overweight: non-Caucasian, having a partner; weight gain during adolescence, mother's excess weight, the use of obesogenic medication, augmented diastolic blood pressure, of abdominal circumference and waist/hip ratio. In addition to these, schooling and weight gain during childhood were also included in the multivariate analysis. After adjustment, the final model included: having a partner, weight gain during adolescence, augmented diastolic blood pressure and abdominal circumference. CONCLUSION: the analysis of predictor variables for excess weight among young adult students supports nurses in planning and developing educational practices aimed to prevent this clinical condition, which is a risk factor for other chronic comorbidities, such as cardiovascular diseases. PMID:26039295

Simultaneous Estimation of Regression Functions for Marine Corps Technical Training Specialties.

ERIC Educational Resources Information Center

Dunbar, Stephen B.; And Others

This paper considers the application of Bayesian techniques for simultaneous estimation to the specification of regression weights for selection tests used in various technical training courses in the Marine Corps. Results of a method for m-group regression developed by Molenaar and Lewis (1979) suggest that common weights for training courses…

Centre of pressure patterns in the golf swing: individual-based analysis.

PubMed

Ball, Kevin; Best, Russell

2012-06-01

Weight transfer has been identified as important in group-based analyses. The aim of this study was to extend this work by examining the importance of weight transfer in the golf swing on an individual basis. Five professional and amateur golfers performed 50 swings with the driver, hitting a ball into a net. The golfer's centre of pressure position and velocity, parallel with the line of shot, were measured by two force plates at eight swing events that were identified from high-speed video. The relationships between these parameters and club head velocity at ball contact were examined using regression statistics. The results did support the use of group-based analysis, with all golfers returning significant relationships. However, results were also individual-specific, with golfers returning different combinations of significant factors. Furthermore, factors not identified in group-based analysis were significant on an individual basis. The most consistent relationship was a larger weight transfer range associated with a larger club head velocity (p < 0.05). All golfers also returned at least one significant relationship with rate of weight transfer at swing events (p < 0.01). Individual-based analysis should form part of performance-based biomechanical analysis of sporting skills.

[Optimization of diagnosis indicator selection and inspection plan by 3.0T MRI in breast cancer].

PubMed

Jiang, Zhongbiao; Wang, Yunhua; He, Zhong; Zhang, Lejun; Zheng, Kai

2013-08-01

To optimize 3.0T MRI diagnosis indicator in breast cancer and to select the best MRI scan program. Totally 45 patients with breast cancers were collected, and another 35 patients with benign breast tumor served as the control group. All patients underwent 3.0T MRI, including T1- weighted imaging (T1WI), fat suppression of the T2-weighted imaging (T2WI), diffusion weighted imaging (DWI), 1H magnetic resonance spectroscopy (1H-MRS) and dynamic contrast enhanced (DCE) sequence. With operation pathology results as the gold standard in the diagnosis of breast diseases, the pathological results of benign and malignant served as dependent variables, and the diagnostic indicators of MRI were taken as independent variables. We put all the indicators of MRI examination under Logistic regression analysis, established the Logistic model, and optimized the diagnosis indicators of MRI examination to further improve MRI scan of breast cancer. By Logistic regression analysis, some indicators were selected in the equation, including the edge feature of the tumor, the time-signal intensity curve (TIC) type and the apparent diffusion coefficient (ADC) value when b=500 s/mm2. The regression equation was Logit (P)=-21.936+20.478X6+3.267X7+ 21.488X3. Valuable indicators in the diagnosis of breast cancer are the edge feature of the tumor, the TIC type and the ADC value when b=500 s/mm2. Combining conventional MRI scan, DWI and dynamic enhanced MRI is a better examination program, while MRS is the complementary program when diagnosis is difficult.

Incense Burning during Pregnancy and Birth Weight and Head Circumference among Term Births: The Taiwan Birth Cohort Study.

PubMed

Chen, Le-Yu; Ho, Christine

2016-09-01

Incense burning for rituals or religious purposes is an important tradition in many countries. However, incense smoke contains particulate matter and gas products such as carbon monoxide, sulfur, and nitrogen dioxide, which are potentially harmful to health. We analyzed the relationship between prenatal incense burning and birth weight and head circumference at birth using the Taiwan Birth Cohort Study. We also analyzed whether the associations varied by sex and along the distribution of birth outcomes. We performed ordinary least squares (OLS) and quantile regressions analysis on a sample of 15,773 term births (> 37 gestational weeks; 8,216 boys and 7,557 girls) in Taiwan in 2005. The associations were estimated separately for boys and girls as well as for the population as a whole. We controlled extensively for factors that may be correlated with incense burning and birth weight and head circumference, such as parental religion, demographics, and health characteristics, as well as pregnancy-related variables. Findings from fully adjusted OLS regressions indicated that exposure to incense was associated with lower birth weight in boys (-18 g; 95% CI: -36, -0.94) but not girls (1 g; 95% CI: -17, 19; interaction p-value = 0.31). Associations with head circumference were negative for boys (-0.95 mm; 95% CI: -1.8, -0.16) and girls (-0.71 mm; 95% CI: -1.5, 0.11; interaction p-values = 0.73). Quantile regression results suggested that the negative associations were larger among the lower quantiles of birth outcomes. OLS regressions showed that prenatal incense burning was associated with lower birth weight for boys and smaller head circumference for boys and girls. The associations were more pronounced among the lower quantiles of birth outcomes. Further research is necessary to confirm whether incense burning has differential effects by sex. Chen LY, Ho C. 2016. Incense burning during pregnancy and birth weight and head circumference among term births: The Taiwan Birth Cohort Study. Environ Health Perspect 124:1487-1492; http://dx.doi.org/10.1289/ehp.1509922.

Incense Burning during Pregnancy and Birth Weight and Head Circumference among Term Births: The Taiwan Birth Cohort Study

PubMed Central

Chen, Le-Yu; Ho, Christine

2016-01-01

Background: Incense burning for rituals or religious purposes is an important tradition in many countries. However, incense smoke contains particulate matter and gas products such as carbon monoxide, sulfur, and nitrogen dioxide, which are potentially harmful to health. Objectives: We analyzed the relationship between prenatal incense burning and birth weight and head circumference at birth using the Taiwan Birth Cohort Study. We also analyzed whether the associations varied by sex and along the distribution of birth outcomes. Methods: We performed ordinary least squares (OLS) and quantile regressions analysis on a sample of 15,773 term births (> 37 gestational weeks; 8,216 boys and 7,557 girls) in Taiwan in 2005. The associations were estimated separately for boys and girls as well as for the population as a whole. We controlled extensively for factors that may be correlated with incense burning and birth weight and head circumference, such as parental religion, demographics, and health characteristics, as well as pregnancy-related variables. Results: Findings from fully adjusted OLS regressions indicated that exposure to incense was associated with lower birth weight in boys (–18 g; 95% CI: –36, –0.94) but not girls (1 g; 95% CI: –17, 19; interaction p-value = 0.31). Associations with head circumference were negative for boys (–0.95 mm; 95% CI: –1.8, –0.16) and girls (–0.71 mm; 95% CI: –1.5, 0.11; interaction p-values = 0.73). Quantile regression results suggested that the negative associations were larger among the lower quantiles of birth outcomes. Conclusions: OLS regressions showed that prenatal incense burning was associated with lower birth weight for boys and smaller head circumference for boys and girls. The associations were more pronounced among the lower quantiles of birth outcomes. Further research is necessary to confirm whether incense burning has differential effects by sex. Citation: Chen LY, Ho C. 2016. Incense burning during pregnancy and birth weight and head circumference among term births: The Taiwan Birth Cohort Study. Environ Health Perspect 124:1487–1492; http://dx.doi.org/10.1289/ehp.1509922 PMID:26967367

INNOVATIVE INSTRUMENTATION AND ANALYSIS OF THE TEMPERATURE MEASUREMENT FOR HIGH TEMPERATURE GASIFICATION

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

Seong W. Lee

During this reporting period, the literature survey including the gasifier temperature measurement literature, the ultrasonic application and its background study in cleaning application, and spray coating process are completed. The gasifier simulator (cold model) testing has been successfully conducted. Four factors (blower voltage, ultrasonic application, injection time intervals, particle weight) were considered as significant factors that affect the temperature measurement. The Analysis of Variance (ANOVA) was applied to analyze the test data. The analysis shows that all four factors are significant to the temperature measurements in the gasifier simulator (cold model). The regression analysis for the case with the normalizedmore » room temperature shows that linear model fits the temperature data with 82% accuracy (18% error). The regression analysis for the case without the normalized room temperature shows 72.5% accuracy (27.5% error). The nonlinear regression analysis indicates a better fit than that of the linear regression. The nonlinear regression model's accuracy is 88.7% (11.3% error) for normalized room temperature case, which is better than the linear regression analysis. The hot model thermocouple sleeve design and fabrication are completed. The gasifier simulator (hot model) design and the fabrication are completed. The system tests of the gasifier simulator (hot model) have been conducted and some modifications have been made. Based on the system tests and results analysis, the gasifier simulator (hot model) has met the proposed design requirement and the ready for system test. The ultrasonic cleaning method is under evaluation and will be further studied for the gasifier simulator (hot model) application. The progress of this project has been on schedule.« less

The impact of weight misperception on health-related quality of life in Korean adults (KNHANES 2007–2014): a community-based cross-sectional study

PubMed Central

Park, Susan; Lee, Sejin; Hwang, Jinseub; Kwon, Jin-Won

2017-01-01

Background/objectives Weight perception, especially misperception, might affect health-related quality of life (HRQoL); however, related research is scarce and results remain equivocal. We examined the association between HRQoL and weight misperception by comparing obesity level as measured by body mass index (BMI) and weight perception in Korean adults. Methods Study subjects were 43 883 adults aged 19 years or older from cycles IV (2007–2009), V (2010–2012) and VI (2013–2014) of the Korean National Health and Nutrition Examination Survey. Multiple regression analyses comprising both logit and tobit models were conducted to evaluate the independent effect of obesity level as measured by BMI, weight perception and weight misperception on HRQoL after adjusting for demographics, socioeconomic status and number of chronic diseases. We also performed multiple regressions to explore the association between weight misperception and HRQoL stratified by BMI status. Results Obesity level as measured by BMI and weight perception were independently associated with low HRQoL in both separate and combined analyses. Weight misperception, including underestimation and overestimation, had a significantly negative impact on HRQoL. In subgroup analysis, subjects with BMI ranges from normal to overweight who misperceived their weight also had a high risk of low HRQoL. Overestimation of weight among obese subjects associated with low HRQoL, whereas underestimation of weight showed no significant association. Conclusions Both obesity level as measured by BMI and perceiving weight as fat were significant risk factors for low HRQoL. Subjects who incorrectly perceived their weight relative to their BMI status were more likely to report impaired HRQoL, particularly subjects with BMI in the normal to overweight range. Based on these findings, we recommend political and clinical efforts to better inform individuals about healthy weight status and promote accurate weight perception. PMID:28645975

Sociodemographic risk factors associated with low birthweight in United Arab Emirates.

PubMed

Bener, A; Abdulrazzaq, Y M; Dawodu, A

1996-07-01

This case-control study was undertaken to determine sociodemographic risk factors for low birth weight in Al-Ain (United Arab Emirates) over a 12-month period in 1992-93. A total of 3485 live births occurred of which 293 (8.4%) were low birth weight. The risk factors considered were mother's occupation, house conditions, place of residence (urban or rural), maternal smoking habits, antenatal care, availability of help in the home, maternal BMI and educational status. Multiple logistic regression analysis showed that mother's occupation, maternal smoking, antenatal care, and lack of help in the home were associated with increased risk of low birth weight.

Correlation between pesticide use in agriculture and adverse birth outcomes in Brazil: an ecological study.

PubMed

de Siqueira, Marília Teixeira; Braga, Cynthia; Cabral-Filho, José Eulálio; Augusto, Lia Giraldo da Silva; Figueiroa, José Natal; Souza, Ariani Impieri

2010-06-01

This ecological study analyzed the association between pesticide use and prematurity, low weight and congenital abnormality at birth, infant death by congenital abnormality, and fetal death in Brazil in 2001. Simple linear regression analysis has determined a positive association between pesticide use and prematurity, low birth weight, and congenital abnormality. The association between pesticide use and low birth weight (p = 0.045) and, congenital abnormality (p = 0.004) and infant death rate by congenital abnormality (p = 0.039) remained after the adjustment made by the proportion of pregnant women with a low number of prenatal care visits.

Constitutional basis of longevity in the cetacea: do the whales and the terrestrial mammals obey the same laws

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

Sacher, G.A.

1978-01-01

The maximum lifespans in captivity for terrestrial mammalian species can be estimated by means of a multiple linear regression of logarithm of lifespan (L) on the logarithm of adult brain weight (E) and body weight (S). This paper describes the application of regression formulas based on data from terrestrial mammals to the estimation of odontocete and mysticete lifespans. The regression formulas predict cetacean lifespans that are in accord with the data on maximum cetacean lifespans obtained in recent years by objective age determination procedures. More remarkable is the correct prediction by the regression formulas that the odontocete species have nearlymore » constant lifespans, almost independent of body weight over a 300:1 body weight range. This prediction is a consequence of the fact, remarkable in itself, that over this body weight range the Odontoceti have a brain:body allometric slope of 1/3, as compared to a slope of 2/3 for the Mammalia as a whole.« less

Leveraging probabilistic peak detection to estimate baseline drift in complex chromatographic samples.

PubMed

Lopatka, Martin; Barcaru, Andrei; Sjerps, Marjan J; Vivó-Truyols, Gabriel

2016-01-29

Accurate analysis of chromatographic data often requires the removal of baseline drift. A frequently employed strategy strives to determine asymmetric weights in order to fit a baseline model by regression. Unfortunately, chromatograms characterized by a very high peak saturation pose a significant challenge to such algorithms. In addition, a low signal-to-noise ratio (i.e. s/n<40) also adversely affects accurate baseline correction by asymmetrically weighted regression. We present a baseline estimation method that leverages a probabilistic peak detection algorithm. A posterior probability of being affected by a peak is computed for each point in the chromatogram, leading to a set of weights that allow non-iterative calculation of a baseline estimate. For extremely saturated chromatograms, the peak weighted (PW) method demonstrates notable improvement compared to the other methods examined. However, in chromatograms characterized by low-noise and well-resolved peaks, the asymmetric least squares (ALS) and the more sophisticated Mixture Model (MM) approaches achieve superior results in significantly less time. We evaluate the performance of these three baseline correction methods over a range of chromatographic conditions to demonstrate the cases in which each method is most appropriate. Copyright © 2016 Elsevier B.V. All rights reserved.

Locally Weighted Score Estimation for Quantile Classification in Binary Regression Models

PubMed Central

Rice, John D.; Taylor, Jeremy M. G.

2016-01-01

One common use of binary response regression methods is classification based on an arbitrary probability threshold dictated by the particular application. Since this is given to us a priori, it is sensible to incorporate the threshold into our estimation procedure. Specifically, for the linear logistic model, we solve a set of locally weighted score equations, using a kernel-like weight function centered at the threshold. The bandwidth for the weight function is selected by cross validation of a novel hybrid loss function that combines classification error and a continuous measure of divergence between observed and fitted values; other possible cross-validation functions based on more common binary classification metrics are also examined. This work has much in common with robust estimation, but diers from previous approaches in this area in its focus on prediction, specifically classification into high- and low-risk groups. Simulation results are given showing the reduction in error rates that can be obtained with this method when compared with maximum likelihood estimation, especially under certain forms of model misspecification. Analysis of a melanoma data set is presented to illustrate the use of the method in practice. PMID:28018492

Field comparison of body composition techniques: hydrostatic weighing, skinfold thickness, and bioelectric impedance.

PubMed

Kirkendall, D T; Grogan, J W; Bowers, R G

1991-01-01

Body composition and appropriate playing weight are frequently requested by coaches. Numerous methods for estimating these figures are available, and each has its own limitation, be it technical or biological. A comparison of three common methods was made-underwater weighting (H2O, the criterion), skinfold thicknesses (SF), and commercial bioelectrical impedance analysis (BIA). Subjects were 29 professional football players measured by each of the three methods after an overnight fast. Data was collected 10 weeks preceding the players' formal training camp. There was no difference for percentage of weight as fat between SF (15.8%) and H2O (14.2%). Bioelectrical impedance analysis significantly (p < .05) overestimated percent fat (19.2%) compared to H20. Error rates when regressing SF on H2O were favorable, whether expressed for the whole sample (3.04%) or by race (1.78% or 3.56% for whites and blacks, respectively). Regression of BIA on H2O showed an elevated, overall error rate (14.12%) and elevated error rates for whites (11.57%) and blacks (13.81%). Of the two estimates of body composition on a racially mixed sample of males, SF provided the best estimate with the least amount of error. J Orthop Sports Phys Ther 1991;13(5):235-239.

[Retinopathy of prematurity in multiple births: risk analysis for plus disease].

PubMed

García-Serrano, J L; Ramírez-García, M C; Piñar-Molina, R

2009-04-01

To analyze the risk factors associated with plus disease in retinopathy of prematurity (ROP). Over a period of 8.5 years we carried out a prospective study of ROP in twins and triplets. Fifty-four multiple-birth infants with low birth weight (< or =1500 g) and low gestational age (32< or = weeks) were admitted to the University Hospital of Granada. Logistic regression analyses showed the following variables to be associated with an increased risk of plus disease: severe ROP, large area of avascular retina, low gestational age, low birth weight, a patent ductus arteriosus, length of mechanical ventilation, adverse events increase, low 5 min Apgar scores and poor postnatal weight gain (in the first 4 to 6 weeks of life). Using multiple logistic regression, only the grade of ROP (OR: 5.5; p < 0.009) and poor postnatal weight gain (OR: 0.58; p < 0.04) were predictive factors of development of plus disease. Infants with disease gained an average 3.9 +/- 3.1 g/day in the first 6 weeks of life, compared to a mean of 11.84 +/- 8.3 g/day for those without plus disease (p < 0.0001). Advanced ROP stages and poor weight gain were the most significant factors associated with plus disease. Twins who gained weight at more than 7 g/day in the first 4-6 weeks of life had a significantly reduced risk of plus disease. A good weight gain is an effective strategy against avoidable blindness due to ROP.

Evaluation of body weight of sea cucumber Apostichopus japonicus by computer vision

NASA Astrophysics Data System (ADS)

Liu, Hui; Xu, Qiang; Liu, Shilin; Zhang, Libin; Yang, Hongsheng

2015-01-01

A postichopus japonicus (Holothuroidea, Echinodermata) is an ecological and economic species in East Asia. Conventional biometric monitoring method includes diving for samples and weighing above water, with highly variable in weight measurement due to variation in the quantity of water in the respiratory tree and intestinal content of this species. Recently, video survey method has been applied widely in biometric detection on underwater benthos. However, because of the high flexibility of A. japonicus body, video survey method of monitoring is less used in sea cucumber. In this study, we designed a model to evaluate the wet weight of A. japonicus, using machine vision technology combined with a support vector machine (SVM) that can be used in field surveys on the A. japonicus population. Continuous dorsal images of free-moving A. japonicus individuals in seawater were captured, which also allows for the development of images of the core body edge as well as thorn segmentation. Parameters that include body length, body breadth, perimeter and area, were extracted from the core body edge images and used in SVM regression, to predict the weight of A. japonicus and for comparison with a power model. Results indicate that the use of SVM for predicting the weight of 33 A. japonicus individuals is accurate ( R 2=0.99) and compatible with the power model ( R 2 =0.96). The image-based analysis and size-weight regression models in this study may be useful in body weight evaluation of A. japonicus in lab and field study.

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.

Use of probabilistic weights to enhance linear regression myoelectric control

NASA Astrophysics Data System (ADS)

Smith, Lauren H.; Kuiken, Todd A.; Hargrove, Levi J.

2015-12-01

Objective. Clinically available prostheses for transradial amputees do not allow simultaneous myoelectric control of degrees of freedom (DOFs). Linear regression methods can provide simultaneous myoelectric control, but frequently also result in difficulty with isolating individual DOFs when desired. This study evaluated the potential of using probabilistic estimates of categories of gross prosthesis movement, which are commonly used in classification-based myoelectric control, to enhance linear regression myoelectric control. Approach. Gaussian models were fit to electromyogram (EMG) feature distributions for three movement classes at each DOF (no movement, or movement in either direction) and used to weight the output of linear regression models by the probability that the user intended the movement. Eight able-bodied and two transradial amputee subjects worked in a virtual Fitts’ law task to evaluate differences in controllability between linear regression and probability-weighted regression for an intramuscular EMG-based three-DOF wrist and hand system. Main results. Real-time and offline analyses in able-bodied subjects demonstrated that probability weighting improved performance during single-DOF tasks (p < 0.05) by preventing extraneous movement at additional DOFs. Similar results were seen in experiments with two transradial amputees. Though goodness-of-fit evaluations suggested that the EMG feature distributions showed some deviations from the Gaussian, equal-covariance assumptions used in this experiment, the assumptions were sufficiently met to provide improved performance compared to linear regression control. Significance. Use of probability weights can improve the ability to isolate individual during linear regression myoelectric control, while maintaining the ability to simultaneously control multiple DOFs.

Change with age in regression construction of fat percentage for BMI in school-age children.

PubMed

Fujii, Katsunori; Mishima, Takaaki; Watanabe, Eiji; Seki, Kazuyoshi

2011-01-01

In this study, curvilinear regression was applied to the relationship between BMI and body fat percentage, and an analysis was done to see whether there are characteristic changes in that curvilinear regression from elementary to middle school. Then, by simultaneously investigating the changes with age in BMI and body fat percentage, the essential differences in BMI and body fat percentage were demonstrated. The subjects were 789 boys and girls (469 boys, 320 girls) aged 7.5 to 14.5 years from all parts of Japan who participated in regular sports activities. Body weight, total body water (TBW), soft lean mass (SLM), body fat percentage, and fat mass were measured with a body composition analyzer (Tanita BC-521 Inner Scan), using segmental bioelectrical impedance analysis & multi-frequency bioelectrical impedance analysis. Height was measured with a digital height measurer. Body mass index (BMI) was calculated as body weight (km) divided by the square of height (m). The results for the validity of regression polynomials of body fat percentage against BMI showed that, for both boys and girls, first-order polynomials were valid in all school years. With regard to changes with age in BMI and body fat percentage, the results showed a temporary drop at 9 years in the aging distance curve in boys, followed by an increasing trend. Peaks were seen in the velocity curve at 9.7 and 11.9 years, but the MPV was presumed to be at 11.9 years. Among girls, a decreasing trend was seen in the aging distance curve, which was opposite to the changes in the aging distance curve for body fat percentage.

Epilepsy, birth weight and academic school readiness in Canadian children: Data from the national longitudinal study of children and youth.

PubMed

Prasad, A N; Corbett, B

2017-02-01

Birth weight is an important indicator of prenatal/in-utero environment. Variations in birth weight have been reportedly associated with risks for cognitive problems. The National Longitudinal Survey of Children and Youth (NLSCY) dataset was explored to examine relationships between birth weight, academic school readiness and epilepsy. A population based sample of 32,900 children of the NLSCY were analyzed to examine associations between birth weight, and school readiness scores in 4-5-year-old children. Logistic and Linear regression was used to examine associations between having epilepsy and these outcomes. Gestation data was available on 19,867 children, full-term children represented 89.67% (gestation >259days), while 10.33% of children were premature (gestation <258days). There were 20 children with reported epilepsy in the sample. Effects of confounding variables (diabetes in pregnancy, smoking in pregnancy, high blood pressure during pregnancy, and gender of the infant) on birth weight and epilepsy were controlled using a separate structural equation model. Logistic regression analysis identified an association between epilepsy and lower birth weights, as well as an association between lower birth weight, having epilepsy and lower PPVT-R Scores. Model results show the relationship between low birth weight and epilepsy remains statistically significant even when controlling for the influence of afore mentioned confounding variables. Low birth weight appears to be associated with both epilepsy and academic school readiness. The data suggest that an abnormal prenatal environment can influence both childhood onset of epilepsy and cognition. Additional studies with larger sample sizes are needed to verify this relationship in detail. Copyright © 2017 Elsevier B.V. All rights reserved.

Body weight manipulation, reinforcement value and choice between sucrose and wheel running: a behavioral economic analysis.

PubMed

Belke, Terry W; Pierce, W David

2009-02-01

Twelve female Long-Evans rats were exposed to concurrent variable (VR) ratio schedules of sucrose and wheel-running reinforcement (Sucrose VR 10 Wheel VR 10; Sucrose VR 5 Wheel VR 20; Sucrose VR 20 Wheel VR 5) with predetermined budgets (number of responses). The allocation of lever pressing to the sucrose and wheel-running alternatives was assessed at high and low body weights. Results showed that wheel-running rate and lever-pressing rates for sucrose and wheel running increased, but the choice of wheel running decreased at the low body weight. A regression analysis of relative consumption as a function of relative price showed that consumption shifted toward sucrose and interacted with price differences in a manner consistent with increased substitutability. Demand curves showed that demand for sucrose became less elastic while demand for wheel running became more elastic at the low body weight. These findings reflect an increase in the difference in relative value of sucrose and wheel running as body weight decreased. Discussion focuses on the limitations of response rates as measures of reinforcement value. In addition, we address the commonalities between matching and demand curve equations for the analysis of changes in relative reinforcement value.

Weight change in control group participants in behavioural weight loss interventions: a systematic review and meta-regression study

PubMed Central

2012-01-01

Background Unanticipated control group improvements have been observed in intervention trials targeting various health behaviours. This phenomenon has not been studied in the context of behavioural weight loss intervention trials. The purpose of this study is to conduct a systematic review and meta-regression of behavioural weight loss interventions to quantify control group weight change, and relate the size of this effect to specific trial and sample characteristics. Methods Database searches identified reports of intervention trials meeting the inclusion criteria. Data on control group weight change and possible explanatory factors were abstracted and analysed descriptively and quantitatively. Results 85 trials were reviewed and 72 were included in the meta-regression. While there was no change in control group weight, control groups receiving usual care lost 1 kg more than control groups that received no intervention, beyond measurement. Conclusions There are several possible explanations why control group changes occur in intervention trials targeting other behaviours, but not for weight loss. Control group participation may prevent weight gain, although more research is needed to confirm this hypothesis. PMID:22873682

Weight change in control group participants in behavioural weight loss interventions: a systematic review and meta-regression study.

PubMed

Waters, Lauren; George, Alexis S; Chey, Tien; Bauman, Adrian

2012-08-08

Unanticipated control group improvements have been observed in intervention trials targeting various health behaviours. This phenomenon has not been studied in the context of behavioural weight loss intervention trials. The purpose of this study is to conduct a systematic review and meta-regression of behavioural weight loss interventions to quantify control group weight change, and relate the size of this effect to specific trial and sample characteristics. Database searches identified reports of intervention trials meeting the inclusion criteria. Data on control group weight change and possible explanatory factors were abstracted and analysed descriptively and quantitatively. 85 trials were reviewed and 72 were included in the meta-regression. While there was no change in control group weight, control groups receiving usual care lost 1 kg more than control groups that received no intervention, beyond measurement. There are several possible explanations why control group changes occur in intervention trials targeting other behaviours, but not for weight loss. Control group participation may prevent weight gain, although more research is needed to confirm this hypothesis.

Determination of riverbank erosion probability using Locally Weighted Logistic Regression

NASA Astrophysics Data System (ADS)

Ioannidou, Elena; Flori, Aikaterini; Varouchakis, Emmanouil A.; Giannakis, Georgios; Vozinaki, Anthi Eirini K.; Karatzas, George P.; Nikolaidis, Nikolaos

2015-04-01

Riverbank erosion is a natural geomorphologic process that affects the fluvial environment. The most important issue concerning riverbank erosion is the identification of the vulnerable locations. An alternative to the usual hydrodynamic models to predict vulnerable locations is to quantify the probability of erosion occurrence. This can be achieved by identifying the underlying relations between riverbank erosion and the geomorphological or hydrological variables that prevent or stimulate erosion. Thus, riverbank erosion can be determined by a regression model using independent variables that are considered to affect the erosion process. The impact of such variables may vary spatially, therefore, a non-stationary regression model is preferred instead of a stationary equivalent. Locally Weighted Regression (LWR) is proposed as a suitable choice. This method can be extended to predict the binary presence or absence of erosion based on a series of independent local variables by using the logistic regression model. It is referred to as Locally Weighted Logistic Regression (LWLR). Logistic regression is a type of regression analysis used for predicting the outcome of a categorical dependent variable (e.g. binary response) based on one or more predictor variables. The method can be combined with LWR to assign weights to local independent variables of the dependent one. LWR allows model parameters to vary over space in order to reflect spatial heterogeneity. The probabilities of the possible outcomes are modelled as a function of the independent variables using a logistic function. Logistic regression measures the relationship between a categorical dependent variable and, usually, one or several continuous independent variables by converting the dependent variable to probability scores. Then, a logistic regression is formed, which predicts success or failure of a given binary variable (e.g. erosion presence or absence) for any value of the independent variables. The erosion occurrence probability can be calculated in conjunction with the model deviance regarding the independent variables tested. The most straightforward measure for goodness of fit is the G statistic. It is a simple and effective way to study and evaluate the Logistic Regression model efficiency and the reliability of each independent variable. The developed statistical model is applied to the Koiliaris River Basin on the island of Crete, Greece. Two datasets of river bank slope, river cross-section width and indications of erosion were available for the analysis (12 and 8 locations). Two different types of spatial dependence functions, exponential and tricubic, were examined to determine the local spatial dependence of the independent variables at the measurement locations. The results show a significant improvement when the tricubic function is applied as the erosion probability is accurately predicted at all eight validation locations. Results for the model deviance show that cross-section width is more important than bank slope in the estimation of erosion probability along the Koiliaris riverbanks. The proposed statistical model is a useful tool that quantifies the erosion probability along the riverbanks and can be used to assist managing erosion and flooding events. Acknowledgements This work is part of an on-going THALES project (CYBERSENSORS - High Frequency Monitoring System for Integrated Water Resources Management of Rivers). The project has been co-financed by the European Union (European Social Fund - ESF) and Greek national funds through the Operational Program "Education and Lifelong Learning" of the National Strategic Reference Framework (NSRF) - Research Funding Program: THALES. Investing in knowledge society through the European Social Fund.

Utility of inverse probability weighting in molecular pathological epidemiology.

PubMed

Liu, Li; Nevo, Daniel; Nishihara, Reiko; Cao, Yin; Song, Mingyang; Twombly, Tyler S; Chan, Andrew T; Giovannucci, Edward L; VanderWeele, Tyler J; Wang, Molin; Ogino, Shuji

2018-04-01

As one of causal inference methodologies, the inverse probability weighting (IPW) method has been utilized to address confounding and account for missing data when subjects with missing data cannot be included in a primary analysis. The transdisciplinary field of molecular pathological epidemiology (MPE) integrates molecular pathological and epidemiological methods, and takes advantages of improved understanding of pathogenesis to generate stronger biological evidence of causality and optimize strategies for precision medicine and prevention. Disease subtyping based on biomarker analysis of biospecimens is essential in MPE research. However, there are nearly always cases that lack subtype information due to the unavailability or insufficiency of biospecimens. To address this missing subtype data issue, we incorporated inverse probability weights into Cox proportional cause-specific hazards regression. The weight was inverse of the probability of biomarker data availability estimated based on a model for biomarker data availability status. The strategy was illustrated in two example studies; each assessed alcohol intake or family history of colorectal cancer in relation to the risk of developing colorectal carcinoma subtypes classified by tumor microsatellite instability (MSI) status, using a prospective cohort study, the Nurses' Health Study. Logistic regression was used to estimate the probability of MSI data availability for each cancer case with covariates of clinical features and family history of colorectal cancer. This application of IPW can reduce selection bias caused by nonrandom variation in biospecimen data availability. The integration of causal inference methods into the MPE approach will likely have substantial potentials to advance the field of epidemiology.

The Prediction Properties of Inverse and Reverse Regression for the Simple Linear Calibration Problem

NASA Technical Reports Server (NTRS)

Parker, Peter A.; Geoffrey, Vining G.; Wilson, Sara R.; Szarka, John L., III; Johnson, Nels G.

2010-01-01

The calibration of measurement systems is a fundamental but under-studied problem within industrial statistics. The origins of this problem go back to basic chemical analysis based on NIST standards. In today's world these issues extend to mechanical, electrical, and materials engineering. Often, these new scenarios do not provide "gold standards" such as the standard weights provided by NIST. This paper considers the classic "forward regression followed by inverse regression" approach. In this approach the initial experiment treats the "standards" as the regressor and the observed values as the response to calibrate the instrument. The analyst then must invert the resulting regression model in order to use the instrument to make actual measurements in practice. This paper compares this classical approach to "reverse regression," which treats the standards as the response and the observed measurements as the regressor in the calibration experiment. Such an approach is intuitively appealing because it avoids the need for the inverse regression. However, it also violates some of the basic regression assumptions.

Validation of equations and proposed reference values to estimate fat mass in Chilean university students.

PubMed

Gómez Campos, Rossana; Pacheco Carrillo, Jaime; Almonacid Fierro, Alejandro; Urra Albornoz, Camilo; Cossío-Bolaños, Marco

2018-03-01

(i) To propose regression equations based on anthropometric measures to estimate fat mass (FM) using dual energy X-ray absorptiometry (DXA) as reference method, and (ii)to establish population reference standards for equation-derived FM. A cross-sectional study on 6,713 university students (3,354 males and 3,359 females) from Chile aged 17.0 to 27.0years. Anthropometric measures (weight, height, waist circumference) were taken in all participants. Whole body DXA was performed in 683 subjects. A total of 478 subjects were selected to develop regression equations, and 205 for their cross-validation. Data from 6,030 participants were used to develop reference standards for FM. Equations were generated using stepwise multiple regression analysis. Percentiles were developed using the LMS method. Equations for men were: (i) FM=-35,997.486 +232.285 *Weight +432.216 *CC (R 2 =0.73, SEE=4.1); (ii)FM=-37,671.303 +309.539 *Weight +66,028.109 *ICE (R2=0.76, SEE=3.8), while equations for women were: (iii)FM=-13,216.917 +461,302 *Weight+91.898 *CC (R 2 =0.70, SEE=4.6), and (iv) FM=-14,144.220 +464.061 *Weight +16,189.297 *ICE (R 2 =0.70, SEE=4.6). Percentiles proposed included p10, p50, p85, and p95. The developed equations provide valid and accurate estimation of FM in both sexes. The values obtained using the equations may be analyzed from percentiles that allow for categorizing body fat levels by age and sex. Copyright © 2017 SEEN y SED. Publicado por Elsevier España, S.L.U. All rights reserved.

Integrated analysis of DNA-methylation and gene expression using high-dimensional penalized regression: a cohort study on bone mineral density in postmenopausal women.

PubMed

Lien, Tonje G; Borgan, Ørnulf; Reppe, Sjur; Gautvik, Kaare; Glad, Ingrid Kristine

2018-03-07

Using high-dimensional penalized regression we studied genome-wide DNA-methylation in bone biopsies of 80 postmenopausal women in relation to their bone mineral density (BMD). The women showed BMD varying from severely osteoporotic to normal. Global gene expression data from the same individuals was available, and since DNA-methylation often affects gene expression, the overall aim of this paper was to include both of these omics data sets into an integrated analysis. The classical penalized regression uses one penalty, but we incorporated individual penalties for each of the DNA-methylation sites. These individual penalties were guided by the strength of association between DNA-methylations and gene transcript levels. DNA-methylations that were highly associated to one or more transcripts got lower penalties and were therefore favored compared to DNA-methylations showing less association to expression. Because of the complex pathways and interactions among genes, we investigated both the association between DNA-methylations and their corresponding cis gene, as well as the association between DNA-methylations and trans-located genes. Two integrating penalized methods were used: first, an adaptive group-regularized ridge regression, and secondly, variable selection was performed through a modified version of the weighted lasso. When information from gene expressions was integrated, predictive performance was considerably improved, in terms of predictive mean square error, compared to classical penalized regression without data integration. We found a 14.7% improvement in the ridge regression case and a 17% improvement for the lasso case. Our version of the weighted lasso with data integration found a list of 22 interesting methylation sites. Several corresponded to genes that are known to be important in bone formation. Using BMD as response and these 22 methylation sites as covariates, least square regression analyses resulted in R 2 =0.726, comparable to an average R 2 =0.438 for 10000 randomly selected groups of DNA-methylations with group size 22. Two recent types of penalized regression methods were adapted to integrate DNA-methylation and their association to gene expression in the analysis of bone mineral density. In both cases predictions clearly benefit from including the additional information on gene expressions.

Objective and Perceived Weight: Associations with Risky Adolescent Sexual Behavior

PubMed Central

Akers, Aletha Y.; Cohen, Elan D.; Marshal, Michael P.; Roebuck, Geoff; Yu, Lan; Hipwell, Alison E.

2016-01-01

CONTEXT Studies have shown that obesity is associated with increased sexual risk-taking, particularly among adolescent females, but the relationships between obesity, perceived weight and sexual risk behaviors are poorly understood. METHODS Integrative data analysis was performed that combined baseline data from the 1994–1995 National Longitudinal Study of Adolescent Health (from 17,606 respondents in grades 7–12) and the 1997 National Longitudinal Survey of Youth (from 7,752 respondents aged 12–16). Using six sexual behaviors measured in both data sets (age at first intercourse, various measures of contraceptive use and number of partners), cluster analysis was conducted that identified five distinct behavior clusters. Multivariate ordinal logistic regression analysis examined associations between adolescents’ weight status (categorized as underweight, normal-weight, overweight or obese) and weight perception and their cluster membership. RESULTS Among males, being underweight, rather than normal-weight, was negatively associated with membership in increasingly risky clusters (odds ratio, 0.5), as was the perception of being overweight, as opposed to about the right weight (0.8). However, being overweight was positively associated with males’ membership in increasingly risky clusters (1.3). Among females, being obese, rather than normal-weight, was negatively correlated with membership in increasingly risky clusters (0.8), while the perception of being overweight was positively correlated with such membership (1.1). CONCLUSIONS Both objective and subjective assessments of weight are associated with the clustering of risky sexual behaviors among adolescents, and these behavioral patterns differ by gender. PMID:27608419

Objective and Perceived Weight: Associations with Risky Adolescent Sexual Behavior.

PubMed

Akers, Aletha Y; Cohen, Elan D; Marshal, Michael P; Roebuck, Geoff; Yu, Lan; Hipwell, Alison E

2016-09-01

Studies have shown that obesity is associated with increased sexual risk-taking, particularly among adolescent females, but the relationships between obesity, perceived weight and sexual risk behaviors are poorly understood. Integrative data analysis was performed that combined baseline data from the 1994-1995 National Longitudinal Study of Adolescent Health (from 17,606 respondents in grades 7-12) and the 1997 National Longitudinal Survey of Youth (from 7,752 respondents aged 12-16). Using six sexual behaviors measured in both data sets (age at first intercourse, various measures of contraceptive use and number of partners), cluster analysis was conducted that identified five distinct behavior clusters. Multivariate ordinal logistic regression analysis examined associations between adolescents' weight status (categorized as underweight, normal-weight, overweight or obese) and weight perception and their cluster membership. Among males, being underweight, rather than normal-weight, was negatively associated with membership in increasingly risky clusters (odds ratio, 0.5), as was the perception of being overweight, as opposed to about the right weight (0.8). However, being overweight was positively associated with males' membership in increasingly risky clusters (1.3). Among females, being obese, rather than normal-weight, was negatively correlated with membership in increasingly risky clusters (0.8), while the perception of being overweight was positively correlated with such membership (1.1). Both objective and subjective assessments of weight are associated with the clustering of risky sexual behaviors among adolescents, and these behavioral patterns differ by gender. Copyright © 2016 by the Guttmacher Institute.

Effects of artificial sweeteners on body weight, food and drink intake.

PubMed

Polyák, Eva; Gombos, K; Hajnal, B; Bonyár-Müller, K; Szabó, Sz; Gubicskó-Kisbenedek, A; Marton, K; Ember, I

2010-12-01

Artificial sweeteners are widely used all over the world. They may assist in weight management, prevention of dental caries, control of blood glucose of diabetics, and also can be used to replace sugar in foods. In the animal experimentation mice were given oral doses of water solutions of table top artificial sweeteners (saccharin, cyclamate based, acesulfame-K based, and aspartame) the amount of maximum Acceptable Daily Intake (ADI) ad libitum. The controls received only tap water with the same drinking conditions as the treated groups. The mice were fed chow ad libitum.We measured food intake and body weight once a week, water and solutions of artificial sweeteners intake twice a week. The data were analysed by statistical methods (T-probe, regression analysis).Consumption of sweeteners resulted in significantly increased body weight; however, the food intake did not change.These results question the effect of non-caloric artificial sweeteners on weight-maintenance or body weight decrease.

Sexual violence, weight perception, and eating disorder indicators in college females.

PubMed

Groff Stephens, Sara; Wilke, Dina J

2016-01-01

To examine the relationships between sexual violence experiences, inaccurate body weight perceptions, and the presence of eating disorder (ED) indicators in a sample of female US college students. Participants were 6,090 college females 25 years of age and younger. A secondary analysis of National College Health Assessment data gathered annually at one institution from 2004 to 2013 was utilized. A model predicting ED indicators was tested using logistic regression analyses with multiple categorical variables representing severity of sexual violence, accuracy of body weight perception, and an interaction between the two. Sexual violence and inaccurate body weight perception significantly predicted ED indicators; sexual violence was the strongest predictor of purging behavior, whereas inaccurate body weight perception was best predicted by underweight status. Findings provide support to the relationship between purging behavior and severity of sexual violence and also to the link between inaccurate body weight perception and being underweight.

The Digital Shoreline Analysis System (DSAS) Version 4.0 - An ArcGIS extension for calculating shoreline change

USGS Publications Warehouse

Thieler, E. Robert; Himmelstoss, Emily A.; Zichichi, Jessica L.; Ergul, Ayhan

2009-01-01

The Digital Shoreline Analysis System (DSAS) version 4.0 is a software extension to ESRI ArcGIS v.9.2 and above that enables a user to calculate shoreline rate-of-change statistics from multiple historic shoreline positions. A user-friendly interface of simple buttons and menus guides the user through the major steps of shoreline change analysis. Components of the extension and user guide include (1) instruction on the proper way to define a reference baseline for measurements, (2) automated and manual generation of measurement transects and metadata based on user-specified parameters, and (3) output of calculated rates of shoreline change and other statistical information. DSAS computes shoreline rates of change using four different methods: (1) endpoint rate, (2) simple linear regression, (3) weighted linear regression, and (4) least median of squares. The standard error, correlation coefficient, and confidence interval are also computed for the simple and weighted linear-regression methods. The results of all rate calculations are output to a table that can be linked to the transect file by a common attribute field. DSAS is intended to facilitate the shoreline change-calculation process and to provide rate-of-change information and the statistical data necessary to establish the reliability of the calculated results. The software is also suitable for any generic application that calculates positional change over time, such as assessing rates of change of glacier limits in sequential aerial photos, river edge boundaries, land-cover changes, and so on.

Predictions of biochar production and torrefaction performance from sugarcane bagasse using interpolation and regression analysis.

PubMed

Chen, Wei-Hsin; Hsu, Hung-Jen; Kumar, Gopalakrishnan; Budzianowski, Wojciech M; Ong, Hwai Chyuan

2017-12-01

This study focuses on the biochar formation and torrefaction performance of sugarcane bagasse, and they are predicted using the bilinear interpolation (BLI), inverse distance weighting (IDW) interpolation, and regression analysis. It is found that the biomass torrefied at 275°C for 60min or at 300°C for 30min or longer is appropriate to produce biochar as alternative fuel to coal with low carbon footprint, but the energy yield from the torrefaction at 300°C is too low. From the biochar yield, enhancement factor of HHV, and energy yield, the results suggest that the three methods are all feasible for predicting the performance, especially for the enhancement factor. The power parameter of unity in the IDW method provides the best predictions and the error is below 5%. The second order in regression analysis gives a more reasonable approach than the first order, and is recommended for the predictions. Copyright © 2017 Elsevier Ltd. All rights reserved.

Wolf population regulation revisited: again

USGS Publications Warehouse

McRoberts, Ronald E.; Mech, L. David

2014-01-01

The long-accepted conclusion that wolf density is regulated by nutrition was recently challenged, and the conclusion was reached that, at greater levels of prey biomass, social factors such as intraspecific strife and territoriality tend to regulate wolf density. We reanalyzed the data used in that study for 2 reasons: 1) we disputed the use of 2 data points, and 2) because of recognized heteroscedasticity, we used weighted-regression analysis instead of the unweighted regressions used in the original study. We concluded that the data do not support the hypothesis that wolf densities are regulated by social factors.

Weight gain during the first year of life in relation to maternal smoking and breast feeding in Norway.

PubMed Central

Nafstad, P; Jaakkola, J J; Hagen, J A; Pedersen, B S; Qvigstad, E; Botten, G; Kongerud, J

1997-01-01

OBJECTIVE: To assess the weight gain during the first year of life in relation to maternal smoking during pregnancy and the duration of breastfeeding. DESIGN: This was a one year cohort study. SETTING: The city of Oslo, Norway. PARTICIPANTS: Altogether 3020 children born in Oslo in 1992-93. Children were divided into three groups as follows: 2208 born to non-smoking mothers, 451 to mothers who were light smokers (< 10 cigarettes per day), and 261 to mothers who were heavy smokers (> or = 10 cigarettes per day). MAIN RESULTS: The mean birth weights were 3616 g, 3526 g, and 3382 g and 1 year body weights were 10,056 g (gain 6440 g per year), 10,141 g (6615 g), and 10,158 g (6776 g) in children of non-smoking and light and heavy smoking mothers respectively. Cox regression analysis showed that children of heavy smokers were 2.0 (95% confidence interval, 1.7, 2.3) times and children of light smokers 1.3 (1.2, 1.5) times more likely to have stopped breast feeding during their first year of life compared with children whose mothers were non-smokers. Linear regression analysis, adjusting for confounders, showed that weight gain was slower in breast fed children than in those who were not breast fed (-38 g (-50, -27) per month of breast feeding). Compared with children of non-smokers, the adjusted weight gain was 147 g (40, 255) per year greater in children of light smokers and 184 g (44, 324) per year in children of heavy smokers. CONCLUSION: Children catch up any losses in birth weight due to maternal smoking, but some of the catch up effect is caused by a shorter duration of breast feeding in children of smoking mothers. PMID:9229054

Obese Chinese Primary-School Students and Low Self-Esteem: A Cross-Sectional Study

PubMed Central

Xue-Yan, Zhang; Dong-Mei, Li; Dan-Dan, Xu; Le-Shan, Zhou

2016-01-01

Objectives The aim of this study was to examine several factors related to low self-esteem among obese Chinese primary-school students. Methods A cross-sectional study was conducted between June 2009 and June 2010. A total of 1,410 primary-school students (China grades 4 - 6) in Changsha city were divided into normal weight (n = 1,084), overweight (n = 211), and obese groups (n = 115) according to world health organization (WHO) growth standards for body mass index (BMI). The students were assessed using the self-esteem scale (SES) and a general situation questionnaire. Caregivers completed questionnaires about their child’s weight status. Self-esteem levels were explored; any factors related to low self-esteem were analyzed using logistic regression analysis. Results The average self-esteem score among overweight or obese primary-school students was found to be lower than that of normal-weight students. The proportion of students with low self-esteem in the obese group was more than that in the normal-weight and overweight groups. Multiple logistic regression analysis showed that obesity status (odds ratio [OR], 3.74; 95% confidence interval [CI], 2.25 - 6.22), overweight status (OR, 2.60; 95% CI, 1.71 - 3.95), obesity considered by children’s grandparents (OR, 1.76; 95% CI, 1.05 - 2.96), dissatisfaction with height (OR, 1.55; 95% CI, 1.11 - 2.18), and dissatisfaction with weight (OR, 1.45; 95% CI, 1.05 - 2.01) were the risk factors for low self-esteem for primary-school students, while satisfaction with academic performance was a protective factor (OR, 0.22; 95% CI, 0.07 - 0.71). Conclusions For Chinese primary-school students, low self-esteem is associated with higher weight status and self-perceived body shape and academic performance. In addition, grandparental opinion of a child’s weight also contributes to low self-esteem. PMID:27713806

Obese Chinese Primary-School Students and Low Self-Esteem: A Cross-Sectional Study.

PubMed

Xue-Yan, Zhang; Dong-Mei, Li; Dan-Dan, Xu; Le-Shan, Zhou

2016-08-01

The aim of this study was to examine several factors related to low self-esteem among obese Chinese primary-school students. A cross-sectional study was conducted between June 2009 and June 2010. A total of 1,410 primary-school students (China grades 4 - 6) in Changsha city were divided into normal weight (n = 1,084), overweight (n = 211), and obese groups (n = 115) according to world health organization (WHO) growth standards for body mass index (BMI). The students were assessed using the self-esteem scale (SES) and a general situation questionnaire. Caregivers completed questionnaires about their child's weight status. Self-esteem levels were explored; any factors related to low self-esteem were analyzed using logistic regression analysis. The average self-esteem score among overweight or obese primary-school students was found to be lower than that of normal-weight students. The proportion of students with low self-esteem in the obese group was more than that in the normal-weight and overweight groups. Multiple logistic regression analysis showed that obesity status (odds ratio [OR], 3.74; 95% confidence interval [CI], 2.25 - 6.22), overweight status (OR, 2.60; 95% CI, 1.71 - 3.95), obesity considered by children's grandparents (OR, 1.76; 95% CI, 1.05 - 2.96), dissatisfaction with height (OR, 1.55; 95% CI, 1.11 - 2.18), and dissatisfaction with weight (OR, 1.45; 95% CI, 1.05 - 2.01) were the risk factors for low self-esteem for primary-school students, while satisfaction with academic performance was a protective factor (OR, 0.22; 95% CI, 0.07 - 0.71). For Chinese primary-school students, low self-esteem is associated with higher weight status and self-perceived body shape and academic performance. In addition, grandparental opinion of a child's weight also contributes to low self-esteem.

Racial/ethnic and educational differences in the estimated odds of recent nitrite use among adult household residents in the United States: an illustration of matching and conditional logistic regression.

PubMed

Delva, J; Spencer, M S; Lin, J K

2000-01-01

This article compares estimates of the relative odds of nitrite use obtained from weighted unconditional logistic regression with estimates obtained from conditional logistic regression after post-stratification and matching of cases with controls by neighborhood of residence. We illustrate these methods by comparing the odds associated with nitrite use among adults of four racial/ethnic groups, with and without a high school education. We used aggregated data from the 1994-B through 1996 National Household Survey on Drug Abuse (NHSDA). Difference between the methods and implications for analysis and inference are discussed.

Impact of External Price Referencing on Medicine Prices – A Price Comparison Among 14 European Countries

PubMed Central

Leopold, Christine; Mantel-Teeuwisse, Aukje Katja; Seyfang, Leonhard; Vogler, Sabine; de Joncheere, Kees; Laing, Richard Ogilvie; Leufkens, Hubert

2012-01-01

Objectives: This study aims to examine the impact of external price referencing (EPR) on on-patent medicine prices, adjusting for other factors that may affect price levels such as sales volume, exchange rates, gross domestic product (GDP) per capita, total pharmaceutical expenditure (TPE), and size of the pharmaceutical industry. Methods: Price data of 14 on-patent products, in 14 European countries in 2007 and 2008 were obtained from the Pharmaceutical Price Information Service of the Austrian Health Institute. Based on the unit ex-factory prices in EURO, scaled ranks per country and per product were calculated. For the regression analysis the scaled ranks per country and product were weighted; each country had the same sum of weights but within a country the weights were proportional to its sales volume in the year (data obtained from IMS Health). Taking the scaled ranks, several statistical analyses were performed by using the program “R”, including a multiple regression analysis (including variables such as GDP per capita and national industry size). Results: This study showed that on average EPR as a pricing policy leads to lower prices. However, the large variation in price levels among countries using EPR confirmed that the price level is not only driven by EPR. The unadjusted linear regression model confirms that applying EPR in a country is associated with a lower scaled weighted rank (p=0.002). This interaction persisted after inclusion of total pharmaceutical expenditure per capita and GDP per capita in the final model. Conclusions: The study showed that for patented products, prices are in general lower in case the country applied EPR. Nevertheless substantial price differences among countries that apply EPR could be identified. Possible explanations could be found through a correlation between pharmaceutical industry and the scaled price ranks. In conclusion, we found that implementing external reference pricing could lead to lower prices. PMID:23532710

Dynamic Dimensionality Selection for Bayesian Classifier Ensembles

DTIC Science & Technology

2015-03-19

learning of weights in an otherwise generatively learned naive Bayes classifier. WANBIA-C is very cometitive to Logistic Regression but much more...classifier, Generative learning, Discriminative learning, Naïve Bayes, Feature selection, Logistic regression , higher order attribute independence 16...discriminative learning of weights in an otherwise generatively learned naive Bayes classifier. WANBIA-C is very cometitive to Logistic Regression but

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.

Incremental online learning in high dimensions.

PubMed

Vijayakumar, Sethu; D'Souza, Aaron; Schaal, Stefan

2005-12-01

Locally weighted projection regression (LWPR) is a new algorithm for incremental nonlinear function approximation in high-dimensional spaces with redundant and irrelevant input dimensions. At its core, it employs nonparametric regression with locally linear models. In order to stay computationally efficient and numerically robust, each local model performs the regression analysis with a small number of univariate regressions in selected directions in input space in the spirit of partial least squares regression. We discuss when and how local learning techniques can successfully work in high-dimensional spaces and review the various techniques for local dimensionality reduction before finally deriving the LWPR algorithm. The properties of LWPR are that it (1) learns rapidly with second-order learning methods based on incremental training, (2) uses statistically sound stochastic leave-one-out cross validation for learning without the need to memorize training data, (3) adjusts its weighting kernels based on only local information in order to minimize the danger of negative interference of incremental learning, (4) has a computational complexity that is linear in the number of inputs, and (5) can deal with a large number of-possibly redundant-inputs, as shown in various empirical evaluations with up to 90 dimensional data sets. For a probabilistic interpretation, predictive variance and confidence intervals are derived. To our knowledge, LWPR is the first truly incremental spatially localized learning method that can successfully and efficiently operate in very high-dimensional spaces.

Estimation and Selection via Absolute Penalized Convex Minimization And Its Multistage Adaptive Applications

PubMed Central

Huang, Jian; Zhang, Cun-Hui

2013-01-01

The ℓ1-penalized method, or the Lasso, has emerged as an important tool for the analysis of large data sets. Many important results have been obtained for the Lasso in linear regression which have led to a deeper understanding of high-dimensional statistical problems. In this article, we consider a class of weighted ℓ1-penalized estimators for convex loss functions of a general form, including the generalized linear models. We study the estimation, prediction, selection and sparsity properties of the weighted ℓ1-penalized estimator in sparse, high-dimensional settings where the number of predictors p can be much larger than the sample size n. Adaptive Lasso is considered as a special case. A multistage method is developed to approximate concave regularized estimation by applying an adaptive Lasso recursively. We provide prediction and estimation oracle inequalities for single- and multi-stage estimators, a general selection consistency theorem, and an upper bound for the dimension of the Lasso estimator. Important models including the linear regression, logistic regression and log-linear models are used throughout to illustrate the applications of the general results. PMID:24348100

Geographically weighted poisson regression semiparametric on modeling of the number of tuberculosis cases (Case study: Bandung city)

NASA Astrophysics Data System (ADS)

Octavianty, Toharudin, Toni; Jaya, I. G. N. Mindra

2017-03-01

Tuberculosis (TB) is a disease caused by a bacterium, called Mycobacterium tuberculosis, which typically attacks the lungs but can also affect the kidney, spine, and brain (Centers for Disease Control and Prevention). Indonesia had the largest number of TB cases after India (Global Tuberculosis Report 2015 by WHO). The distribution of Mycobacterium tuberculosis genotypes in Indonesia showed the high genetic diversity and tended to vary by geographic regions. For instance, in Bandung city, the prevalence rate of TB morbidity is quite high. A number of TB patients belong to the counted data. To determine the factors that significantly influence the number of tuberculosis patients in each location of the observations can be used statistical analysis tool that is Geographically Weighted Poisson Regression Semiparametric (GWPRS). GWPRS is an extension of the Poisson regression and GWPR that is influenced by geographical factors, and there is also variables that influence globally and locally. Using the TB Data in Bandung city (in 2015), the results show that the global and local variables that influence the number of tuberculosis patients in every sub-district.

Publication bias in obesity treatment trials?

PubMed

Allison, D B; Faith, M S; Gorman, B S

1996-10-01

The present investigation examined the extent of publication bias (namely the tendency to publish significant findings and file away non-significant findings) within the obesity treatment literature. Quantitative literature synthesis of four published meta-analyses from the obesity treatment literature. Interventions in these studies included pharmacological, educational, child, and couples treatments. To assess publication bias, several regression procedures (for example weighted least-squares, random-effects multi-level modeling, and robust regression methods) were used to regress effect sizes onto their standard errors, or proxies thereof, within each of the four meta-analysis. A significant positive beta weight in these analyses signified publication bias. There was evidence for publication bias within two of the four published meta-analyses, such that reviews of published studies were likely to overestimate clinical efficacy. The lack of evidence for publication bias within the two other meta-analyses might have been due to insufficient statistical power rather than the absence of selection bias. As in other disciplines, publication bias appears to exist in the obesity treatment literature. Suggestions are offered for managing publication bias once identified or reducing its likelihood in the first place.

Emotional eating is associated with weight loss success among adults enrolled in a weight loss program.

PubMed

Braden, Abby; Flatt, Shirley W; Boutelle, Kerri N; Strong, David; Sherwood, Nancy E; Rock, Cheryl L

2016-08-01

To examine associations between decreased emotional eating and weight loss success; and whether participation in a behavioral weight loss intervention was associated with a greater reduction in emotional eating over time compared to usual care. Secondary data analysis of a randomized controlled trial conducted at two university medical centers with 227 overweight adults with diabetes. Logistic and standard regression analyses examined associations between emotional eating change and weight loss success (i.e., weight loss of ≥7 % of body weight and decrease in BMI). After 6 months of intervention, decreased emotional eating was associated with greater odds of weight loss success (p = .05). The odds of weight loss success for subjects with decreased emotional eating at 12 months were 1.70 times higher than for subjects with increased emotional eating. No differences in change in emotional eating were found between subjects in the behavioral weight loss intervention and usual care. Strategies to reduce emotional eating may be useful to promote greater weight loss among overweight adults with diabetes.

Prediction equations for maximal respiratory pressures of Brazilian adolescents.

PubMed

Mendes, Raquel E F; Campos, Tania F; Macêdo, Thalita M F; Borja, Raíssa O; Parreira, Verônica F; Mendonça, Karla M P P

2013-01-01

The literature emphasizes the need for studies to provide reference values and equations able to predict respiratory muscle strength of Brazilian subjects at different ages and from different regions of Brazil. To develop prediction equations for maximal respiratory pressures (MRP) of Brazilian adolescents. In total, 182 healthy adolescents (98 boys and 84 girls) aged between 12 and 18 years, enrolled in public and private schools in the city of Natal-RN, were evaluated using an MVD300 digital manometer (Globalmed®) according to a standardized protocol. Statistical analysis was performed using SPSS Statistics 17.0 software, with a significance level of 5%. Data normality was verified using the Kolmogorov-Smirnov test, and descriptive analysis results were expressed as the mean and standard deviation. To verify the correlation between the MRP and the independent variables (age, weight, height and sex), the Pearson correlation test was used. To obtain the prediction equations, stepwise multiple linear regression was used. The variables height, weight and sex were correlated to MRP. However, weight and sex explained part of the variability of MRP, and the regression analysis in this study indicated that these variables contributed significantly in predicting maximal inspiratory pressure, and only sex contributed significantly to maximal expiratory pressure. This study provides reference values and two models of prediction equations for maximal inspiratory and expiratory pressures and sets the necessary normal lower limits for the assessment of the respiratory muscle strength of Brazilian adolescents.

Mining Health App Data to Find More and Less Successful Weight Loss Subgroups

PubMed Central

2016-01-01

Background More than half of all smartphone app downloads involve weight, diet, and exercise. If successful, these lifestyle apps may have far-reaching effects for disease prevention and health cost-savings, but few researchers have analyzed data from these apps. Objective The purposes of this study were to analyze data from a commercial health app (Lose It!) in order to identify successful weight loss subgroups via exploratory analyses and to verify the stability of the results. Methods Cross-sectional, de-identified data from Lose It! were analyzed. This dataset (n=12,427,196) was randomly split into 24 subsamples, and this study used 3 subsamples (combined n=972,687). Classification and regression tree methods were used to explore groupings of weight loss with one subsample, with descriptive analyses to examine other group characteristics. Data mining validation methods were conducted with 2 additional subsamples. Results In subsample 1, 14.96% of users lost 5% or more of their starting body weight. Classification and regression tree analysis identified 3 distinct subgroups: “the occasional users” had the lowest proportion (4.87%) of individuals who successfully lost weight; “the basic users” had 37.61% weight loss success; and “the power users” achieved the highest percentage of weight loss success at 72.70%. Behavioral factors delineated the subgroups, though app-related behavioral characteristics further distinguished them. Results were replicated in further analyses with separate subsamples. Conclusions This study demonstrates that distinct subgroups can be identified in “messy” commercial app data and the identified subgroups can be replicated in independent samples. Behavioral factors and use of custom app features characterized the subgroups. Targeting and tailoring information to particular subgroups could enhance weight loss success. Future studies should replicate data mining analyses to increase methodology rigor. PMID:27301853

[Eating attitudes, attitudes related to weight gain, and body satisfaction of pregnant adolescents].

PubMed

Oliboni, Carolina Marques; Alvarenga, Marle Dos Santos

2015-12-01

To assess attitudes about eating, weight gain and body image of pregnant adolescents. Pregnant adolescents (n=67) were assessed using the Body Image Questionnaire, the Attitude towards Weight Gain during Pregnancy scale (AWGP) and questions about risk behaviors for eating disorders and unhealthy weight control practices. Associations between variables were analyzed by ANOVA, Kruskal-Wallis test, Pearson and Spearman tests. The influence of the independent variables regarding skipping meals, body satisfaction and binge eating was evaluated by logistic regression. The average age of the adolescents was 15.3 years (SD=1.14) and their average gestational age was 21.9 weeks (SD=6.53). The average AWGP score was 52.6 points, indicating a positive attitude towards weight gain, and 82.1% of the pregnant girls were satisfied with their bodies. Obese girls had more body dissatisfaction (p=0.001), and overweight girls thought more about food (p=0.02) and eating (p=0.03). The frequency of reported binge eating was 41.8%, and the frequency of skipping meals was 19%. Regression analysis showed that the current Body Mass Index (p=0.03; OR=1.18) and the importance of body awareness and fitness before pregnancy (p=0.03; OR=4.63) were predictors of skipping meals. Higher socioeconomic level (p=0.04; OR=0.55) and greater concern with weight gain (p=0.03; OR=0.32) predicted binge eating. Even though the majority of the pregnant adolescents had positive attitudes toward weight gain and body satisfaction, those heavier and more concerned with weight gain had a higher risk of unhealthy attitudes, while those of lower social class, less concerned with weight gain and less embarrassed about their bodies during pregnancy, had a lower risk of unhealthy attitudes.

Factors Associated with Participation in Employment for High School Leavers with Autism

ERIC Educational Resources Information Center

Chiang, Hsu-Min; Cheung, Ying Kuen; Li, Huacheng; Tsai, Luke Y.

2013-01-01

This study aimed to identify the factors associated with participation in employment for high school leavers with autism. A secondary data analysis of the National Longitudinal Transition Study 2 (NLTS2) data was performed. Potential factors were assessed using a weighted multivariate logistic regression. This study found that annual household…

Assessing Mediation Using Marginal Structural Models in the Presence of Confounding and Moderation

ERIC Educational Resources Information Center

Coffman, Donna L.; Zhong, Wei

2012-01-01

This article presents marginal structural models with inverse propensity weighting (IPW) for assessing mediation. Generally, individuals are not randomly assigned to levels of the mediator. Therefore, confounders of the mediator and outcome may exist that limit causal inferences, a goal of mediation analysis. Either regression adjustment or IPW…

Nucleated red blood cells in growth-restricted fetuses: associations with short-term neonatal outcome.

PubMed

Minior, V K; Bernstein, P S; Divon, M Y

2000-01-01

To determine the utility of the neonatal nucleated red blood cell (NRBC) count as an independent predictor of short-term perinatal outcome in growth-restricted fetuses. Hospital charts of neonates with a discharge diagnosis indicating a birth weight <10th percentile were reviewed for perinatal outcome. We studied all eligible neonates who had a complete blood count on the first day of life. After multiple gestations, anomalous fetuses and diabetic pregnancies were excluded; 73 neonates comprised the study group. Statistical analysis included ANOVA, simple and stepwise regression. Elevated NRBC counts were significantly associated with cesarean section for non-reassuring fetal status, neonatal intensive care unit admission and duration of neonatal intensive care unit stay, respiratory distress and intubation, thrombocytopenia, hyperbilirubinemia, intraventricular hemorrhage and neonatal death. Stepwise regression analysis including gestational age at birth, birth weight and NRBC count demonstrated that in growth-restricted fetuses, NRBC count was the strongest predictor of neonatal intraventricular hemorrhage, neonatal respiratory distress and neonatal death. An elevated NRBC count independently predicts adverse perinatal outcome in growth-restricted fetuses. Copyright 2000 S. Karger AG, Basel.

Characterizing multivariate decoding models based on correlated EEG spectral features.

PubMed

McFarland, Dennis J

2013-07-01

Multivariate decoding methods are popular techniques for analysis of neurophysiological data. The present study explored potential interpretative problems with these techniques when predictors are correlated. Data from sensorimotor rhythm-based cursor control experiments was analyzed offline with linear univariate and multivariate models. Features were derived from autoregressive (AR) spectral analysis of varying model order which produced predictors that varied in their degree of correlation (i.e., multicollinearity). The use of multivariate regression models resulted in much better prediction of target position as compared to univariate regression models. However, with lower order AR features interpretation of the spectral patterns of the weights was difficult. This is likely to be due to the high degree of multicollinearity present with lower order AR features. Care should be exercised when interpreting the pattern of weights of multivariate models with correlated predictors. Comparison with univariate statistics is advisable. While multivariate decoding algorithms are very useful for prediction their utility for interpretation may be limited when predictors are correlated. Copyright © 2013 International Federation of Clinical Neurophysiology. Published by Elsevier Ireland Ltd. All rights reserved.

Neurodevelopmental Outcomes of Extremely Low Birth Weight Infants with Spontaneous Intestinal Perforation or Surgical Necrotizing Enterocolitis

PubMed Central

Wadhawan, Rajan; Oh, William; Hintz, Susan R; Blakely, Martin L; Das, Abhik; Bell, Edward F.; Saha, Shampa; Laptook, Abbot R.; Shankaran, Seetha; Stoll, Barbara J.; Walsh, Michele C.; Higgins, Rosemary D.

2013-01-01

Objective To determine if extremely low birth weight infants with surgical necrotizing enterocolitis have a higher risk of death or neurodevelopmental impairment and neurodevelopmental impairment among survivors (secondary outcome) at 18–22 months corrected age compared to infants with spontaneous intestinal perforation and infants without necrotizing enterocolitis or spontaneous intestinal perforation. Study Design Retrospective analysis of the Neonatal Research Network very low birth weight registry, evaluating extremely low birth weight infants born between 2000–2005. The study infants were designated into 3 groups: 1) Spontaneous intestinal perforation without necrotizing enterocolitis; 2) Surgical necrotizing enterocolitis (Bell's stage III); and 3) Neither spontaneous intestinal perforation nor necrotizing enterocolitis. Multivariate logistic regression analysis was performed to evaluate the association between the clinical group and death or neurodevelopmental impairment, controlling for multiple confounding factors including center. Results Infants with surgical necrotizing enterocolitis had the highest rate of death prior to hospital discharge (53.5%) and death or neurodevelopmental impairment (82.3%) compared to infants in the spontaneous intestinal perforation group (39.1% and 79.3%) and no necrotizing enterocolitis/no spontaneous intestinal perforation group (22.1% and 53.3%; p<0.001). Similar results were observed for neurodevelopmental impairment among survivors. On logistic regression analysis, both spontaneous intestinal perforation and surgical necrotizing enterocolitis were associated with increased risk of death or neurodevelopmental impairment (adjusted OR 2.21, 95% CI: 1.5, 3.2 and adjusted OR 2.11, 95% CI: 1.5, 2.9 respectively) and neurodevelopmental impairment among survivors (adjusted OR 2.17, 95% CI: 1.4, 3.2 and adjusted OR 1.70, 95% CI: 1.2, 2.4 respectively). Conclusions Spontaneous intestinal perforation and surgical necrotizing enterocolitis are associated with a similar increase in the risk of death or neurodevelopmental impairment and neurodevelopmental impairment among extremely low birth weight survivors at 18–22 months corrected age. PMID:24135709

[Growth in terms of length of Chilean infants of low socioeconomic status: 1978-1992].

PubMed

Pizarro, F; Olivares, M; Hertrampf, E; Walter, T

1996-06-01

In Chile infant malnutrition is better reflected by the length/age indicator than by weight/length. In this study we will present the progression of length during the first year of life from the year 1978 through 1992 of infants of low socioeconomic status. We selected healthy infants with > 3000 g birth weight and birth length > 0.5 z. According to type of milk feedings they were defined as CM (cow milk) those who were weaned before 4 months of life and EM (exclusive breast milk) those who continued exclusive breast milk (as only source of milk solids permitted) past 6 months. Infants CM of the 1978-80 cohort had a length at birth z +0.21 reaching 1 year with z -0.65, a loss of 0.86 z. Infants from the cohorts of 1982-86 and 1988-92 fell from z +0.15 to z -0.37 (a loss of -0.52 z) and +0.16 to -0.19 (a loss of -0.45 z) between birth and 12 months respectively. EBM infants length also fell significantly (delta z: -1.12, -0.69 and 0.59 respectively). Proteincalorie nutrition was adequate confirmed with weight/age or length/weight curves with means of +0.52 throughout the first year. Analysis of the length curves by regression shows that the slopes of the 3 cohorts are significantly different (< 0.01) for CM and EBM favoring the most recent cohorts. Multiple regression analysis identified association of length at 1 year with birth weight (p < 0.05), birth length (p < 0.01) and socioeconomic index (p < 0.01). We suggest that there is an improvement in the trend of Chilean infants growth in length for the past 20 years, likely due to improvement in socioeconomic level.

Risk factors for polyuria in a cross-section of community psychiatric lithium-treated patients.

PubMed

Kinahan, James Conor; NiChorcorain, Aoife; Cunningham, Sean; Freyne, Aideen; Cooney, Colm; Barry, Siobhan; Kelly, Brendan D

2015-02-01

Polyuria increases the risk of dehydration and lithium toxicity in lithium-treated patients. Risk factors have been inconsistently described and the variance of this adverse effect remains poorly understood. This study aimed to establish independent risk factors for polyuria in a community, secondary-level lithium-treated sample of patients. This was a cross-sectional study of the lithium-treated patients attending a general adult and an old age psychiatry service. Participants completed a 24-hour urine collection. Urine volume and the presence of polyuria were the outcomes of interest. The relationship between outcome and the participant's demographic and clinical characteristics was explored with univariable and multivariable analysis. A total of 122 participants were included in the analysis, with 38% being diagnosed with polyuria. Female gender and increased body weight independently predicted the presence of polyuria (standardized regression coefficient 1.01 and 0.94, respectively; p = 0.002 and p = 0.003, respectively). Female gender and increased body weight, lithium dose, and duration of lithium treatment independently predicted higher 24-hour urine volumes (standardized regression coefficients 0.693, p < 0.0005; 0.791, p < 0.0005; 0.276, p = 0.043; 0.181, p = 0.034, respectively). Of three different weight metrics, lean body weight was the most predictive. Female gender and increased body weight explain part of the variance of this adverse effect. Both risk factors offer fresh insights into the pathophysiology of this potentially reversible and dangerous adverse effect of lithium treatment. Future research should focus on understanding the differences between the genders and between different body compositions in terms of lithium pharmacokinetics and pharmacodynamics. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Pattern and determinants of birth weight in Oman.

PubMed

Islam, M M; ElSayed, M K

2015-12-01

The aim of this study was to analyse the pattern of birth weight (BW) and identify the factors affecting BW and the risk factors of low birth weight (LBW) in Oman. The data for the study came from the 2000 Oman National Health Survey conducted by the Ministry of Health. The survey covered a nationally representative sample of 2037 ever married Omani women of reproductive age. Data on birth weight were gathered from health cards of the infants born within five years before the survey date. The study considered 977 singleton live births for whom data on birth weights were available. LBW was defined as BW less than 2500 g. Descriptive statistics, analysis of variance, multivariate linear regression and logistic regression models were used for data analysis. The mean BW was found to be 3.09 (SD 0.51) kg. BW was found to be significantly lower among the infants with the following characteristics: born in Ad-Dhakhliyah region, born in rural areas, and whose mothers had low economic status, low parity (0-2), and late initiation of antenatal care (ANC) visit. The incidence of LBW was found to be 9% in Oman in 2000. Mother's education, economic status, region of residence, late initiation of first ANC visit and experience of pregnancy complications appeared as the significant determinants of LBW in Oman. In contrast to most other studies, this study demonstrates that mothers with an advanced level of education (secondary and above) are more likely to have infants with LBW in Oman. The study findings highlight the need of intervention for specific groups of women with higher risk of adverse BW outcomes. Copyright © 2015 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Techniques for estimating flood-peak discharges of rural, unregulated streams in Ohio

USGS Publications Warehouse

Koltun, G.F.; Roberts, J.W.

1990-01-01

Multiple-regression equations are presented for estimating flood-peak discharges having recurrence intervals of 2, 5, 10, 25, 50, and 100 years at ungaged sites on rural, unregulated streams in Ohio. The average standard errors of prediction for the equations range from 33.4% to 41.4%. Peak discharge estimates determined by log-Pearson Type III analysis using data collected through the 1987 water year are reported for 275 streamflow-gaging stations. Ordinary least-squares multiple-regression techniques were used to divide the State into three regions and to identify a set of basin characteristics that help explain station-to- station variation in the log-Pearson estimates. Contributing drainage area, main-channel slope, and storage area were identified as suitable explanatory variables. Generalized least-square procedures, which include historical flow data and account for differences in the variance of flows at different gaging stations, spatial correlation among gaging station records, and variable lengths of station record were used to estimate the regression parameters. Weighted peak-discharge estimates computed as a function of the log-Pearson Type III and regression estimates are reported for each station. A method is provided to adjust regression estimates for ungaged sites by use of weighted and regression estimates for a gaged site located on the same stream. Limitations and shortcomings cited in an earlier report on the magnitude and frequency of floods in Ohio are addressed in this study. Geographic bias is no longer evident for the Maumee River basin of northwestern Ohio. No bias is found to be associated with the forested-area characteristic for the range used in the regression analysis (0.0 to 99.0%), nor is this characteristic significant in explaining peak discharges. Surface-mined area likewise is not significant in explaining peak discharges, and the regression equations are not biased when applied to basins having approximately 30% or less surface-mined area. Analyses of residuals indicate that the equations tend to overestimate flood-peak discharges for basins having approximately 30% or more surface-mined area. (USGS)

Estimating inverse-probability weights for longitudinal data with dropout or truncation: The xtrccipw command.

PubMed

Daza, Eric J; Hudgens, Michael G; Herring, Amy H

Individuals may drop out of a longitudinal study, rendering their outcomes unobserved but still well defined. However, they may also undergo truncation (for example, death), beyond which their outcomes are no longer meaningful. Kurland and Heagerty (2005, Biostatistics 6: 241-258) developed a method to conduct regression conditioning on nontruncation, that is, regression conditioning on continuation (RCC), for longitudinal outcomes that are monotonically missing at random (for example, because of dropout). This method first estimates the probability of dropout among continuing individuals to construct inverse-probability weights (IPWs), then fits generalized estimating equations (GEE) with these IPWs. In this article, we present the xtrccipw command, which can both estimate the IPWs required by RCC and then use these IPWs in a GEE estimator by calling the glm command from within xtrccipw. In the absence of truncation, the xtrccipw command can also be used to run a weighted GEE analysis. We demonstrate the xtrccipw command by analyzing an example dataset and the original Kurland and Heagerty (2005) data. We also use xtrccipw to illustrate some empirical properties of RCC through a simulation study.

Estimating inverse-probability weights for longitudinal data with dropout or truncation: The xtrccipw command

PubMed Central

Hudgens, Michael G.; Herring, Amy H.

2017-01-01

Individuals may drop out of a longitudinal study, rendering their outcomes unobserved but still well defined. However, they may also undergo truncation (for example, death), beyond which their outcomes are no longer meaningful. Kurland and Heagerty (2005, Biostatistics 6: 241–258) developed a method to conduct regression conditioning on nontruncation, that is, regression conditioning on continuation (RCC), for longitudinal outcomes that are monotonically missing at random (for example, because of dropout). This method first estimates the probability of dropout among continuing individuals to construct inverse-probability weights (IPWs), then fits generalized estimating equations (GEE) with these IPWs. In this article, we present the xtrccipw command, which can both estimate the IPWs required by RCC and then use these IPWs in a GEE estimator by calling the glm command from within xtrccipw. In the absence of truncation, the xtrccipw command can also be used to run a weighted GEE analysis. We demonstrate the xtrccipw command by analyzing an example dataset and the original Kurland and Heagerty (2005) data. We also use xtrccipw to illustrate some empirical properties of RCC through a simulation study. PMID:29755297

Atypical antipsychotics, insulin resistance and weight; a meta-analysis of healthy volunteer studies.

PubMed

Burghardt, Kyle J; Seyoum, Berhane; Mallisho, Abdullah; Burghardt, Paul R; Kowluru, Renu A; Yi, Zhengping

2018-04-20

Atypical antipsychotics increase the risk of diabetes and cardiovascular disease through their side effects of insulin resistance and weight gain. The populations for which atypical antipsychotics are used carry a baseline risk of metabolic dysregulation prior to medication which has made it difficult to fully understand whether atypical antipsychotics cause insulin resistance and weight gain directly. The purpose of this work was to conduct a systematic review and meta-analysis of atypical antipsychotic trials in healthy volunteers to better understand their effects on insulin sensitivity and weight gain. Furthermore, we aimed to evaluate the occurrence of insulin resistance with or without weight gain and with treatment length by using subgroup and meta-regression techniques. Overall, the meta-analysis provides evidence that atypical antipsychotics decrease insulin sensitivity (standardized mean difference=-0.437, p<0.001) and increase weight (standardized mean difference=0.591, p<0.001) in healthy volunteers. It was found that decreases in insulin sensitivity were potentially dependent on treatment length but not weight gain. Decreases in insulin sensitivity occurred in multi-dose studies <13days while weight gain occurred in studies 14days and longer (max 28days). These findings provide preliminary evidence that atypical antipsychotics cause insulin resistance and weight gain directly, independent of psychiatric disease and may be associated with length of treatment. Further, well-designed studies to assess the co-occurrence of insulin resistance and weight gain and to understand the mechanisms and sequence by which they occur are required. Copyright © 2018 Elsevier Inc. All rights reserved.

The Effect of Birth Weight on Academic Performance: Instrumental Variable Analysis.

PubMed

Lin, Shi Lin; Leung, Gabriel Matthew; Schooling, C Mary

2017-05-01

Observationally, lower birth weight is usually associated with poorer academic performance; whether this association is causal or the result of confounding is unknown. To investigate this question, we obtained an effect estimate, which can have a causal interpretation under specific assumptions, of birth weight on educational attainment using instrumental variable analysis based on single nucleotide polymorphisms determining birth weight combined with results from the Social Science Genetic Association Consortium study of 126,559 Caucasians. We similarly obtained an estimate of the effect of birth weight on academic performance in 4,067 adolescents from Hong Kong's (Chinese) Children of 1997 birth cohort (1997-2016), using twin status as an instrumental variable. Birth weight was not associated with years of schooling (per 100-g increase in birth weight, -0.006 years, 95% confidence interval (CI): -0.02, 0.01) or college completion (odds ratio = 1.00, 95% CI: 0.96, 1.03). Birth weight was also unrelated to academic performance in adolescents (per 100-g increase in birth weight, -0.004 grade, 95% CI: -0.04, 0.04) using instrumental variable analysis, although conventional regression gave a small positive association (0.02 higher grade, 95% CI: 0.01, 0.03). Observed associations of birth weight with academic performance may not be causal, suggesting that interventions should focus on the contextual factors generating this correlation. © The Author 2017. 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.

Is prescribed lower extremity weight-bearing status after geriatric lower extremity trauma associated with increased mortality?

PubMed

Gitajn, Ida Leah; Connelly, Daniel; Mascarenhas, Daniel; Breazeale, Stephen; Berger, Peter; Schoonover, Carrie; Martin, Brook; O'Toole, Robert V; Pensy, Raymond; Sciadini, Marcus

2018-02-01

Evaluate whether mortality after discharge is elevated in geriatric fracture patients whose lower extremity weight-bearing is restricted. Retrospective cohort study SETTING: Urban Level 1 trauma center PATIENTS/PARTICIPANTS: 1746 patients >65 years of age INTERVENTION: Post-operative lower extremity weight-bearing status MAIN OUTCOME MEASURE: Mortality, as determined by the Social Security Death Index RESULTS: Univariate analysis demonstrated that patients who were weight-bearing as tolerated on bilateral lower extremities (BLE) had significantly higher 5-year mortality compared to patients with restricted weight-bearing on one lower extremity and restricted weight-bearing on BLE (30%, 21% and 22% respectively, p < 0.001). Cox regression analysis controlling for variables including age, Charlson Comorbidity Index, Injury Severity Scale, combined UE/LE injury, injury mechanism (high vs low), sex, BMI and GCS demonstrated that, in comparison to patients who were weight bearing as tolerated on BLE, restricted weight-bearing on one lower extremity had a hazard ratio (HR) of 0.97 (95% confidence interval 0.78 to 1.20, p = 0.76) and restricted weight-bearing in BLE had a HR of 0.91 (95% confidence interval 0.60 to 1.36, p = 0.73). In geriatric patients, prescribed weight-bearing status did not have a statistically significant association with mortality after discharge, when controlling for age, sex, body mass index, medical comorbidities, Injury Severity Scale (ISS), mechanism of injury, nonoperative treatment and admission GCS. This remained true in when the analysis was restricted to operative injuries only. Copyright © 2017 Elsevier Ltd. All rights reserved.

Risk factors for low birth weight according to the multiple logistic regression model. A retrospective cohort study in José María Morelos municipality, Quintana Roo, Mexico.

PubMed

Franco Monsreal, José; Tun Cobos, Miriam Del Ruby; Hernández Gómez, José Ricardo; Serralta Peraza, Lidia Esther Del Socorro

2018-01-17

Low birth weight has been an enigma for science over time. There have been many researches on its causes and its effects. Low birth weight is an indicator that predicts the probability of a child surviving. In fact, there is an exponential relationship between weight deficit, gestational age, and perinatal mortality. Multiple logistic regression is one of the most expressive and versatile statistical instruments available for the analysis of data in both clinical and epidemiology settings, as well as in public health. To assess in a multivariate fashion the importance of 17 independent variables in low birth weight (dependent variable) of children born in the Mayan municipality of José María Morelos, Quintana Roo, Mexico. Analytical observational epidemiological cohort study with retrospective temporality. Births that met the inclusion criteria occurred in the "Hospital Integral Jose Maria Morelos" of the Ministry of Health corresponding to the Maya municipality of Jose Maria Morelos during the period from August 1, 2014 to July 31, 2015. The total number of newborns recorded was 1,147; 84 of which (7.32%) had low birth weight. To estimate the independent association between the explanatory variables (potential risk factors) and the response variable, a multiple logistic regression analysis was performed using the IBM SPSS Statistics 22 software. In ascending numerical order values of odds ratio > 1 indicated the positive contribution of explanatory variables or possible risk factors: "unmarried" marital status (1.076, 95% confidence interval: 0.550 to 2.104); age at menarche ≤ 12 years (1.08, 95% confidence interval: 0.64 to 1.84); history of abortion(s) (1.14, 95% confidence interval: 0.44 to 2.93); maternal weight < 50 kg (1.51, 95% confidence interval: 0.83 to 2.76); number of prenatal consultations ≤ 5 (1.86, 95% confidence interval: 0.94 to 3.66); maternal age ≥ 36 years (3.5, 95% confidence interval: 0.40 to 30.47); maternal age ≤ 19 years (3.59, 95% confidence interval: 0.43 to 29.87); number of deliveries = 1 (3.86, 95% confidence interval: 0.33 to 44.85); personal pathological history (4.78, 95% confidence interval: 2.16 to 10.59); pathological obstetric history (5.01, 95% confidence interval: 1.66 to 15.18); maternal height < 150 cm (5.16, 95% confidence interval: 3.08 to 8.65); number of births ≥ 5 (5.99, 95% confidence interval: 0.51 to 69.99); and smoking (15.63, 95% confidence interval: 1.07 to 227.97). Four of the independent variables (personal pathological history, obstetric pathological history, maternal stature <150 centimeters and smoking) showed a significant positive contribution, thus they can be considered as clear risk factors for low birth weight. The use of the logistic regression model in the Mayan municipality of José María Morelos, will allow estimating the probability of low birth weight for each pregnant woman in the future, which will be useful for the health authorities of the region.

STATLIB: NSWC Library of Statistical Programs and Subroutines

DTIC Science & Technology

1989-08-01

Uncorrelated Weighted Polynomial Regression 41 .WEPORC Correlated Weighted Polynomial Regression 45 MROP Multiple Regression Using Orthogonal Polynomials ...could not and should not be con- NSWC TR 89-97 verted to the new general purpose computer (the current CDC 995). Some were designed tu compute...personal computers. They are referred to as SPSSPC+, BMDPC, and SASPC and in general are less comprehensive than their mainframe counterparts. The basic

Kinematic and ground reaction force accommodation during weighted walking.

PubMed

James, C Roger; Atkins, Lee T; Yang, Hyung Suk; Dufek, Janet S; Bates, Barry T

2015-12-01

Weighted walking is a functional activity common in daily life and can influence risks for musculoskeletal loading, injury and falling. Much information exists about weighted walking during military, occupational and recreational tasks, but less is known about strategies used to accommodate to weight carriage typical in daily life. The purposes of the study were to examine the effects of weight carriage on kinematics and peak ground reaction force (GRF) during walking, and explore relationships between these variables. Twenty subjects walked on a treadmill while carrying 0, 44.5 and 89 N weights in front of the body. Peak GRF, sagittal plane joint/segment angular kinematics, stride length and center of mass (COM) vertical displacement were measured. Changes in peak GRF and displacement variables between weight conditions represented accommodation. Effects of weight carriage were tested using analysis of variance. Relationships between peak GRF and kinematic accommodation variables were examined using correlation and regression. Subjects were classified into sub-groups based on peak GRF responses and the correlation analysis was repeated. Weight carriage increased peak GRF by an amount greater than the weight carried, decreased stride length, increased vertical COM displacement, and resulted in a more extended and upright posture, with less hip and trunk displacement during weight acceptance. A GRF increase was associated with decreases in hip extension (|r|=.53, p=.020) and thigh anterior rotation (|r|=.57, p=.009) displacements, and an increase in foot anterior rotation displacement (|r|=.58, p=.008). Sub-group analysis revealed that greater GRF increases were associated with changes at multiple sites, while lesser GRF increases were associated with changes in foot and trunk displacement. Weight carriage affected walking kinematics and revealed different accommodation strategies that could have implications for loading and stability. Copyright © 2015 Elsevier B.V. All rights reserved.

Birth weight and type 2 diabetes: A meta-analysis

PubMed Central

Mi, Donghua; Fang, Hongjuan; Zhao, Yaqun; Zhong, Liyong

2017-01-01

The prevalence of T2DM is increasing around the world on a yearly basis. A meta-analysis was conducted to analyze the association between birth weight and incidence of type 2 diabetes mellitus (T2DM). A literature search was performed from January 1990 to June 2016 in PubMed, ScienceDirect, SpringerLink, China National Knowledge Infrastructure and Chinese Biomedical Literature Database. After reviewing characteristics of all the included studies systematically, a meta-analytical method was employed to calculate the pooled odds ratios (ORs) and associated 95% confidence intervals (CI) from random-effects models. Heterogeneity was assessed by Q-statistic test. Funnel plot, Begg's and Egger's linear regression tests were applied to evaluate publication bias. A sensitivity analysis was also performed to assess the robustness of results. According to inclusion and exclusion criteria, 8 studies were selected to be included in the meta-analysis. Compared with normal birth weight (2,500–4,000 g), low birth weight (<2,500 g) was associated with an increased risk of T2DM (OR, 1.55; 95% CI, 1.39–1.73; P<0.001). No significant difference was observed between high birth weight (>4,000 g) and normal birth weight in terms of the risk of T2DM (OR, 0.98; 95% CI, 0.79–1.22). Compared with high birth weight, low birth weight was associated with an increased risk of diabetes mellitus (OR, 1.58; 95% CI, 1.30–1.93; P<0.001). These findings indicated that there may be an inverse linear association between birth weight and T2DM. PMID:29285058

Assessing the Influence of Traffic-related Air Pollution on Risk of Term Low Birth Weight on the Basis of Land-Use-based Regression Models and Measures of Air Toxics

PubMed Central

Ghosh, Jo Kay C.; Wilhelm, Michelle; Su, Jason; Goldberg, Daniel; Cockburn, Myles; Jerrett, Michael; Ritz, Beate

2012-01-01

Few studies have examined associations of birth outcomes with toxic air pollutants (air toxics) in traffic exhaust. This study included 8,181 term low birth weight (LBW) children and 370,922 term normal-weight children born between January 1, 1995, and December 31, 2006, to women residing within 5 miles (8 km) of an air toxics monitoring station in Los Angeles County, California. Additionally, land-use-based regression (LUR)-modeled estimates of levels of nitric oxide, nitrogen dioxide, and nitrogen oxides were used to assess the influence of small-area variations in traffic pollution. The authors examined associations with term LBW (≥37 weeks’ completed gestation and birth weight <2,500 g) using logistic regression adjusted for maternal age, race/ethnicity, education, parity, infant gestational age, and gestational age squared. Odds of term LBW increased 2%–5% (95% confidence intervals ranged from 1.00 to 1.09) per interquartile-range increase in LUR-modeled estimates and monitoring-based air toxics exposure estimates in the entire pregnancy, the third trimester, and the last month of pregnancy. Models stratified by monitoring station (to investigate air toxics associations based solely on temporal variations) resulted in 2%–5% increased odds per interquartile-range increase in third-trimester benzene, toluene, ethyl benzene, and xylene exposures, with some confidence intervals containing the null value. This analysis highlights the importance of both spatial and temporal contributions to air pollution in epidemiologic birth outcome studies. PMID:22586068

Assessing the influence of traffic-related air pollution on risk of term low birth weight on the basis of land-use-based regression models and measures of air toxics.

PubMed

Ghosh, Jo Kay C; Wilhelm, Michelle; Su, Jason; Goldberg, Daniel; Cockburn, Myles; Jerrett, Michael; Ritz, Beate

2012-06-15

Few studies have examined associations of birth outcomes with toxic air pollutants (air toxics) in traffic exhaust. This study included 8,181 term low birth weight (LBW) children and 370,922 term normal-weight children born between January 1, 1995, and December 31, 2006, to women residing within 5 miles (8 km) of an air toxics monitoring station in Los Angeles County, California. Additionally, land-use-based regression (LUR)-modeled estimates of levels of nitric oxide, nitrogen dioxide, and nitrogen oxides were used to assess the influence of small-area variations in traffic pollution. The authors examined associations with term LBW (≥37 weeks' completed gestation and birth weight <2,500 g) using logistic regression adjusted for maternal age, race/ethnicity, education, parity, infant gestational age, and gestational age squared. Odds of term LBW increased 2%-5% (95% confidence intervals ranged from 1.00 to 1.09) per interquartile-range increase in LUR-modeled estimates and monitoring-based air toxics exposure estimates in the entire pregnancy, the third trimester, and the last month of pregnancy. Models stratified by monitoring station (to investigate air toxics associations based solely on temporal variations) resulted in 2%-5% increased odds per interquartile-range increase in third-trimester benzene, toluene, ethyl benzene, and xylene exposures, with some confidence intervals containing the null value. This analysis highlights the importance of both spatial and temporal contributions to air pollution in epidemiologic birth outcome studies.

An Evidence-Based Approach to Defining Fetal Macrosomia.

PubMed

Froehlich, Rosemary; Simhan, Hyagriv N; Larkin, Jacob C

2016-04-01

This study aims to determine the risk of adverse outcomes associated with the current diagnostic criteria for fetal macrosomia. Study We evaluated three techniques for characterizing birth weight as a predictor of shoulder dystocia or third- or fourth-degree laceration in 79,879 vaginal deliveries. First, we compared deliveries with birth weights above or below 4,500 g. We then performed logistic regression using birth weight as a continuous predictor, both with and without fractional polynomial transformation. Finally, we calculated the number of cesarean sections required to prevent one incident of the interrogated outcomes (number needed to treat [NNT]). Rates of adverse intrapartum outcomes increase incrementally with increasing birth weight and are predicted most accurately with logistic regression following fractional polynomial transformation. The NNT for third- or fourth-degree laceration dropped from 14.3 (95% confidence interval [CI], 13.9-14.7) at a birth weight of 3,500 g to 6.4 (95% CI, 6.1-6.8) at 4,500 g and, for shoulder dystocia, from 54.9 (95% CI, 51.5-58.6) at 3,500 g to 5.6 (95% CI, 5.2-6.0) at 4,500 g. The conventional distinction between "normal" and "macrosomic" does not reflect the incremental effect of increasing birth weight on the risk of obstetric morbidity. Outcomes analysis can inform fetal growth standards to better reflect relevant thresholds of risk. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

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 validity of self-reported vs. measured body weight and height and the effect of self-perception.

PubMed

Gokler, Mehmet Enes; Bugrul, Necati; Sarı, Ahu Ozturk; Metintas, Selma

2018-01-01

The objective was to assess the validity of self-reported body weight and height and the possible influence of self-perception of body mass index (BMI) status on the actual BMI during the adolescent period. This cross sectional study was conducted on 3918 high school students. Accurate BMI perception occurred when the student's self-perception of their BMI status did not differ from their actual BMI based on measured height and weight. Agreement between the measured and self-reported body height and weight and BMI values was determined using the Bland-Altman metod. To determine the effects of "a good level of agreement", hierarchical logistic regression models were used. Among male students who reported their BMI in the normal region, 2.8% were measured as overweight while 0.6% of them were measured as obese. For females in the same group, these percentages were 1.3% and 0.4% respectively. Among male students who perceived their BMI in the normal region, 8.5% were measured as overweight while 0.4% of them were measured as obese. For females these percentages were 25.6% and 1.8% respectively. According to logistic regression analysis, residence and accurate BMI perception were significantly associated with "good agreement" ( p ≤ 0.001). The results of this study demonstrated that in determining obesity and overweight statuses, non-accurate weight perception is a potential risk for students.

The influence of place on weight gain during early childhood: a population-based, longitudinal study.

PubMed

Carter, Megan Ann; Dubois, Lise; Tremblay, Mark S; Taljaard, Monica

2013-04-01

The objective of this paper was to determine the influence of place factors on weight gain in a contemporary cohort of children while also adjusting for early life and individual/family social factors. Participants from the Québec Longitudinal Study of Child Development comprised the sample for analysis (n = 1,580). A mixed-effects regression analysis was conducted to determine the longitudinal relationship between these place factors and standardized BMI, from age 4 to 10 years. The average relationship with time was found to be quadratic (rate of weight gain increased over time). Neighborhood material deprivation was found to be positively related to weight gain. Social deprivation, social disorder, and living in a medium density area were inversely related, while no association was found for social cohesion. Early life factors and genetic proxies appeared to be important in explaining weight gain in this sample. This study suggests that residential environments may play a role in childhood weight change; however, pathways are likely to be complex and interacting and perhaps not as important as early life factors and genetic proxies. Further work is required to clarify these relationships.

Tackling missing radiographic progression data: multiple imputation technique compared with inverse probability weights and complete case analysis.

PubMed

Descalzo, Miguel Á; Garcia, Virginia Villaverde; González-Alvaro, Isidoro; Carbonell, Jordi; Balsa, Alejandro; Sanmartí, Raimon; Lisbona, Pilar; Hernandez-Barrera, Valentín; Jiménez-Garcia, Rodrigo; Carmona, Loreto

2013-02-01

To describe the results of different statistical ways of addressing radiographic outcome affected by missing data--multiple imputation technique, inverse probability weights and complete case analysis--using data from an observational study. A random sample of 96 RA patients was selected for a follow-up study in which radiographs of hands and feet were scored. Radiographic progression was tested by comparing the change in the total Sharp-van der Heijde radiographic score (TSS) and the joint erosion score (JES) from baseline to the end of the second year of follow-up. MI technique, inverse probability weights in weighted estimating equation (WEE) and CC analysis were used to fit a negative binomial regression. Major predictors of radiographic progression were JES and joint space narrowing (JSN) at baseline, together with baseline disease activity measured by DAS28 for TSS and MTX use for JES. Results from CC analysis show larger coefficients and s.e.s compared with MI and weighted techniques. The results from the WEE model were quite in line with those of MI. If it seems plausible that CC or MI analysis may be valid, then MI should be preferred because of its greater efficiency. CC analysis resulted in inefficient estimates or, translated into non-statistical terminology, could guide us into inaccurate results and unwise conclusions. The methods discussed here will contribute to the use of alternative approaches for tackling missing data in observational studies.

Bone mineral density and correlation factor analysis in normal Taiwanese children.

PubMed

Shu, San-Ging

2007-01-01

Our aim was to establish reference data and linear regression equations for lumbar bone mineral density (BMD) in normal Taiwanese children. Several influencing factors of lumbar BMD were investigated. Two hundred fifty-seven healthy children were recruited from schools, 136 boys and 121 girls, aged 4-18 years were enrolled on a voluntary basis with written consent. Their height, weight, blood pressure, puberty stage, bone age and lumbar BMD (L2-4) by dual energy x-ray absorptiometry (DEXA) were measured. Data were analyzed using Pearson correlation and stepwise regression tests. All measurements increased with age. Prior to age 8, there was no gender difference. Parameters such as height, weight, and bone age (BA) in girls surpassed boys between ages 8-13 without statistical significance (p> or =0.05). This was reversed subsequently after age 14 in height (p<0.05). BMD difference had the same trend but was not statistically significant either. The influencing power of puberty stage and bone age over BMD was almost equal to or higher than that of height and weight. All the other factors correlated with BMD to variable powers. Multiple linear regression equations for boys and girls were formulated. BMD reference data is provided and can be used to monitor childhood pathological conditions. However, BMD in those with abnormal bone age or pubertal development could need modifications to ensure accuracy.

Relationship between body composition and postural control in prepubertal overweight/obese children: A cross-sectional study.

PubMed

Villarrasa-Sapiña, Israel; Álvarez-Pitti, Julio; Cabeza-Ruiz, Ruth; Redón, Pau; Lurbe, Empar; García-Massó, Xavier

2018-02-01

Excess body weight during childhood causes reduced motor functionality and problems in postural control, a negative influence which has been reported in the literature. Nevertheless, no information regarding the effect of body composition on the postural control of overweight and obese children is available. The objective of this study was therefore to establish these relationships. A cross-sectional design was used to establish relationships between body composition and postural control variables obtained in bipedal eyes-open and eyes-closed conditions in twenty-two children. Centre of pressure signals were analysed in the temporal and frequency domains. Pearson correlations were applied to establish relationships between variables. Principal component analysis was applied to the body composition variables to avoid potential multicollinearity in the regression models. These principal components were used to perform a multiple linear regression analysis, from which regression models were obtained to predict postural control. Height and leg mass were the body composition variables that showed the highest correlation with postural control. Multiple regression models were also obtained and several of these models showed a higher correlation coefficient in predicting postural control than simple correlations. These models revealed that leg and trunk mass were good predictors of postural control. More equations were found in the eyes-open than eyes-closed condition. Body weight and height are negatively correlated with postural control. However, leg and trunk mass are better postural control predictors than arm or body mass. Finally, body composition variables are more useful in predicting postural control when the eyes are open. Copyright © 2017 Elsevier Ltd. All rights reserved.

Measurement of lower limb alignment: there are within-person differences between weight-bearing and non-weight-bearing measurement modalities.

PubMed

Schoenmakers, Daphne A L; Feczko, Peter Z; Boonen, Bert; Schotanus, Martijn G M; Kort, Nanne P; Emans, Pieter J

2017-11-01

Previous studies have compared weight-bearing mechanical leg axis (MLA) measurements to non-weight-bearing measurement modalities. Most of these studies compared mean or median values and did not analyse within-person differences between measurements. This study evaluates the within-person agreement of MLA measurements between weight-bearing full-length radiographs (FLR) and non-weight-bearing measurement modalities (computer-assisted surgery (CAS) navigation or MRI). Two independent observers measured the MLA on pre- and postoperative weight-bearing FLR in 168 patients. These measurements were compared to non-weight-bearing measurements obtained by CAS navigation or MRI. Absolute differences in individual subjects were calculated to determine the agreement between measurement modalities. Linear regression was used to evaluate the possibility that other independent variables impact the differences in measurements. A difference was found in preoperative measurements between FLR and CAS navigation (mean of 2.5° with limit of agreement (1.96 SD) of 6.4°), as well as between FLR and MRI measurements (mean of 2.4° with limit of agreement (1.96 SD) of 6.9°). Postoperatively, the mean difference between MLA measured on FLR compared to CAS navigation was 1.5° (limit of agreement (1.96 SD) of 4.6°). Linear regression analysis showed that weight-bearing MLA measurements vary significantly from non-weight-bearing MLA measurements. Differences were more severe in patients with mediolateral instability (p = 0.010), age (p = 0.049) and ≥3° varus or valgus alignment (p = 0.008). The clinical importance of this study lies in the finding that there are within-person differences between weight-bearing and non-weight-bearing measurement modalities. This has implications for preoperative planning, performing total knee arthroplasty (TKA), and clinical follow-up after TKA surgery using CAS navigation or patient-specific instrumentation. III.

Post-mortem prediction of primal and selected retail cut weights of New Zealand lamb from carcass and animal characteristics.

PubMed

Ngo, L; Ho, H; Hunter, P; Quinn, K; Thomson, A; Pearson, G

2016-02-01

Post-mortem measurements (cold weight, grade and external carcass linear dimensions) as well as live animal data (age, breed, sex) were used to predict ovine primal and retail cut weights for 792 lamb carcases. Significant levels of variance could be explained using these predictors. The predictive power of those measurements on primal and retail cut weights was studied by using the results from principal component analysis and the absolute value of the t-statistics of the linear regression model. High prediction accuracy for primal cut weight was achieved (adjusted R(2) up to 0.95), as well as moderate accuracy for key retail cut weight: tenderloins (adj-R(2)=0.60), loin (adj-R(2)=0.62), French rack (adj-R(2)=0.76) and rump (adj-R(2)=0.75). The carcass cold weight had the best predictive power, with the accuracy increasing by around 10% after including the next three most significant variables. Copyright © 2015 Elsevier Ltd. All rights reserved.

An improved geographically weighted regression model for PM2.5 concentration estimation in large areas

NASA Astrophysics Data System (ADS)

Zhai, Liang; Li, Shuang; Zou, Bin; Sang, Huiyong; Fang, Xin; Xu, Shan

2018-05-01

Considering the spatial non-stationary contributions of environment variables to PM2.5 variations, the geographically weighted regression (GWR) modeling method has been using to estimate PM2.5 concentrations widely. However, most of the GWR models in reported studies so far were established based on the screened predictors through pretreatment correlation analysis, and this process might cause the omissions of factors really driving PM2.5 variations. This study therefore developed a best subsets regression (BSR) enhanced principal component analysis-GWR (PCA-GWR) modeling approach to estimate PM2.5 concentration by fully considering all the potential variables' contributions simultaneously. The performance comparison experiment between PCA-GWR and regular GWR was conducted in the Beijing-Tianjin-Hebei (BTH) region over a one-year-period. Results indicated that the PCA-GWR modeling outperforms the regular GWR modeling with obvious higher model fitting- and cross-validation based adjusted R2 and lower RMSE. Meanwhile, the distribution map of PM2.5 concentration from PCA-GWR modeling also clearly depicts more spatial variation details in contrast to the one from regular GWR modeling. It can be concluded that the BSR enhanced PCA-GWR modeling could be a reliable way for effective air pollution concentration estimation in the coming future by involving all the potential predictor variables' contributions to PM2.5 variations.

Managing Complexity in Evidence Analysis: A Worked Example in Pediatric Weight Management.

PubMed

Parrott, James Scott; Henry, Beverly; Thompson, Kyle L; Ziegler, Jane; Handu, Deepa

2018-05-02

Nutrition interventions are often complex and multicomponent. Typical approaches to meta-analyses that focus on individual causal relationships to provide guideline recommendations are not sufficient to capture this complexity. The objective of this study is to describe the method of meta-analysis used for the Pediatric Weight Management (PWM) Guidelines update and provide a worked example that can be applied in other areas of dietetics practice. The effects of PWM interventions were examined for body mass index (BMI), body mass index z-score (BMIZ), and waist circumference at four different time periods. For intervention-level effects, intervention types were identified empirically using multiple correspondence analysis paired with cluster analysis. Pooled effects of identified types were examined using random effects meta-analysis models. Differences in effects among types were examined using meta-regression. Context-level effects are examined using qualitative comparative analysis. Three distinct types (or families) of PWM interventions were identified: medical nutrition, behavioral, and missing components. Medical nutrition and behavioral types showed statistically significant improvements in BMIZ across all time points. Results were less consistent for BMI and waist circumference, although four distinct patterns of weight status change were identified. These varied by intervention type as well as outcome measure. Meta-regression indicated statistically significant differences between the medical nutrition and behavioral types vs the missing component type for both BMIZ and BMI, although the pattern varied by time period and intervention type. Qualitative comparative analysis identified distinct configurations of context characteristics at each time point that were consistent with positive outcomes among the intervention types. Although analysis of individual causal relationships is invaluable, this approach is inadequate to capture the complexity of dietetics practice. An alternative approach that integrates intervention-level with context-level meta-analyses may provide deeper understanding in the development of practice guidelines. Copyright © 2018 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.

Combined use of susceptibility weighted magnetic resonance imaging sequences and dynamic susceptibility contrast perfusion weighted imaging to improve the accuracy of the differential diagnosis of recurrence and radionecrosis in high-grade glioma patients.

PubMed

Kim, Tae-Hyung; Yun, Tae Jin; Park, Chul-Kee; Kim, Tae Min; Kim, Ji-Hoon; Sohn, Chul-Ho; Won, Jae Kyung; Park, Sung-Hye; Kim, Il Han; Choi, Seung Hong

2017-03-21

Purpose was to assess predictive power for overall survival (OS) and diagnostic performance of combination of susceptibility-weighted MRI sequences (SWMRI) and dynamic susceptibility contrast (DSC) perfusion-weighted imaging (PWI) for differentiation of recurrence and radionecrosis in high-grade glioma (HGG). We enrolled 51 patients who underwent radiation therapy or gamma knife surgeryfollowed by resection for HGG and who developed new measurable enhancement more than six months after complete response. The lesions were confirmed as recurrence (n = 32) or radionecrosis (n = 19). The mean and each percentile value from cumulative histograms of normalized CBV (nCBV) and proportion of dark signal intensity on SWMRI (proSWMRI, %) within enhancement were compared. Multivariate regression was performed for the best differentiator. The cutoff value of best predictor from ROC analysis was evaluated. OS was determined with Kaplan-Meier method and log-rank test. Recurrence showed significantly lower proSWMRI and higher mean nCBV and 90th percentile nCBV (nCBV90) than radionecrosis. Regression analysis revealed both nCBV90 and proSWMRI were independent differentiators. Combination of nCBV90 and proSWMRI achieved 71.9% sensitivity (23/32), 100% specificity (19/19) and 82.3% accuracy (42/51) using best cut-off values (nCBV90 > 2.07 and proSWMRI≤15.76%) from ROC analysis. In subgroup analysis, radionecrosis with nCBV > 2.07 (n = 5) showed obvious hemorrhage (proSWMRI > 32.9%). Patients with nCBV90 > 2.07 and proSWMRI≤15.76% had significantly shorter OS. In conclusion, compared with DSC PWI alone, combination of SWMRI and DSC PWI have potential to be prognosticator for OS and lower false positive rate in differentiation of recurrence and radionecrosis in HGG who develop new measurable enhancement more than six months after complete response.

The quest for conditional independence in prospectivity modeling: weights-of-evidence, boost weights-of-evidence, and logistic regression

NASA Astrophysics Data System (ADS)

Schaeben, Helmut; Semmler, Georg

2016-09-01

The objective of prospectivity modeling is prediction of the conditional probability of the presence T = 1 or absence T = 0 of a target T given favorable or prohibitive predictors B, or construction of a two classes 0,1 classification of T. A special case of logistic regression called weights-of-evidence (WofE) is geologists' favorite method of prospectivity modeling due to its apparent simplicity. However, the numerical simplicity is deceiving as it is implied by the severe mathematical modeling assumption of joint conditional independence of all predictors given the target. General weights of evidence are explicitly introduced which are as simple to estimate as conventional weights, i.e., by counting, but do not require conditional independence. Complementary to the regression view is the classification view on prospectivity modeling. Boosting is the construction of a strong classifier from a set of weak classifiers. From the regression point of view it is closely related to logistic regression. Boost weights-of-evidence (BoostWofE) was introduced into prospectivity modeling to counterbalance violations of the assumption of conditional independence even though relaxation of modeling assumptions with respect to weak classifiers was not the (initial) purpose of boosting. In the original publication of BoostWofE a fabricated dataset was used to "validate" this approach. Using the same fabricated dataset it is shown that BoostWofE cannot generally compensate lacking conditional independence whatever the consecutively processing order of predictors. Thus the alleged features of BoostWofE are disproved by way of counterexamples, while theoretical findings are confirmed that logistic regression including interaction terms can exactly compensate violations of joint conditional independence if the predictors are indicators.

Modeling Fire Occurrence at the City Scale: A Comparison between Geographically Weighted Regression and Global Linear Regression.

PubMed

Song, Chao; Kwan, Mei-Po; Zhu, Jiping

2017-04-08

An increasing number of fires are occurring with the rapid development of cities, resulting in increased risk for human beings and the environment. This study compares geographically weighted regression-based models, including geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), which integrates spatial and temporal effects and global linear regression models (LM) for modeling fire risk at the city scale. The results show that the road density and the spatial distribution of enterprises have the strongest influences on fire risk, which implies that we should focus on areas where roads and enterprises are densely clustered. In addition, locations with a large number of enterprises have fewer fire ignition records, probably because of strict management and prevention measures. A changing number of significant variables across space indicate that heterogeneity mainly exists in the northern and eastern rural and suburban areas of Hefei city, where human-related facilities or road construction are only clustered in the city sub-centers. GTWR can capture small changes in the spatiotemporal heterogeneity of the variables while GWR and LM cannot. An approach that integrates space and time enables us to better understand the dynamic changes in fire risk. Thus governments can use the results to manage fire safety at the city scale.

Modeling Fire Occurrence at the City Scale: A Comparison between Geographically Weighted Regression and Global Linear Regression

PubMed Central

Song, Chao; Kwan, Mei-Po; Zhu, Jiping

2017-01-01

An increasing number of fires are occurring with the rapid development of cities, resulting in increased risk for human beings and the environment. This study compares geographically weighted regression-based models, including geographically weighted regression (GWR) and geographically and temporally weighted regression (GTWR), which integrates spatial and temporal effects and global linear regression models (LM) for modeling fire risk at the city scale. The results show that the road density and the spatial distribution of enterprises have the strongest influences on fire risk, which implies that we should focus on areas where roads and enterprises are densely clustered. In addition, locations with a large number of enterprises have fewer fire ignition records, probably because of strict management and prevention measures. A changing number of significant variables across space indicate that heterogeneity mainly exists in the northern and eastern rural and suburban areas of Hefei city, where human-related facilities or road construction are only clustered in the city sub-centers. GTWR can capture small changes in the spatiotemporal heterogeneity of the variables while GWR and LM cannot. An approach that integrates space and time enables us to better understand the dynamic changes in fire risk. Thus governments can use the results to manage fire safety at the city scale. PMID:28397745

The association of birth weight with cardiovascular risk factors and mental problems among Iranian school-aged children: the CASPIAN-III study.

PubMed

Azadbakht, Leila; Kelishadi, Roya; Saraf-Bank, Sahar; Qorbani, Mostafa; Ardalan, Gelayol; Heshmat, Ramin; Taslimi, Mahnaz; Motlagh, Mohammad Esmaeil

2014-02-01

Both high and low birth weights (HBW and LBW) are risk factors for adulthood diseases. The aim of this study was to investigate the association of birth weight with cardiovascular disease (CVD) risk factors and mental problems among Iranian school-aged children. This national multicenter study of school-aged children entitled CASPIAN III was conducted among 5528 students in ranging from ages 10 to 18 y. Biochemical indices and anthropometric measurements were collected. Mental health was assessed by questionnaire. To investigate the association between birth weight categories and CVD risk factors and mental problems, multivariate logistic regression was used. HBW adolescents were at higher risk for elevated diastolic blood pressure (DBP) (Ptrend < 0.05), low levels of high-density lipoprotein cholesterol (HDL-C) (Ptrend < 0.05), and lower risk for general obesity (Ptrend < 0.05) compared with the LBW category. HBW had no significant association with mental problems (Ptrend > 0.05) compared with LBW adolescents. The results of regression analysis, which considered normal birth weight as the reference group, showed that LBW students had lower risk for overweight and obesity (P < 0.01), as well as higher DBP (P < 0.05) but they were at higher risk for lower levels of HDL-C (P < 0.01). Furthermore, birth-weight categories had a U-shaped relationship with mental problems and sleep disorders (P < 0.05). Risk for confusion was higher among the LBW group (P < 0.05). Findings from this population-based study revealed a positive relation between birth weight categories and CVD risk factors. Compared with students born with normal weight, those born with HBW and LBW were at higher risk for mental problems, sleep disorders, and confusion. Copyright © 2014 Elsevier Inc. All rights reserved.

Seasonal Variations in Birth Weight in Suzhou Industrial Park.

PubMed

Wu, Lei; Ding, Yi; Rui, Xing Li; Mao, Cai Ping

2016-10-01

Many environmental factors have been shown to adversely influence birth weight, and new insight has been gained into 'seasonal programming'. We studied a total of 23,064 infants. The mean birth weight varied across seasons. Logistic regression analysis was used to obtain the crude and adjusted odds ratios (ORs) for dichotomous outcomes (e.g., macrosomia, low birth weight). There were significant differences in the risks for macrosomia in infants born in different seasons. Compared with those for infants born in spring, the ORs for macrosomia were 0.85 [95% confidence interval (CI): 0.75-0.98] and 0.87 (95% CI: 0.77-0.99) for infants born in summer and autumn, respectively. These findings suggest that environmental factors may have public health implications and should be considered when primary prevention programs are developed for macrosomia or low birth weight. Copyright © 2016 The Editorial Board of Biomedical and Environmental Sciences. Published by China CDC. All rights reserved.

Relationship between food insecurity and nutritional status of Brazilian children under the age of five.

PubMed

Santos, Leonardo Pozza dos; Gigante, Denise Petrucci

2013-12-01

The aim of this study was to investigate the relationship between food insecurity and nutritional status of Brazilian children. The National Demographic and Health Survey 2006 database is available on the worldwide web. Thus, the analyzed variables were obtained in this study, including nutritional indices, food insecurity and other socioeconomic and demographic variables. The height-for-age, weight-for-age and weight-for-height indices were evaluated as the Z-score of the World Health Organization reference curves. Food insecurity was defined by using the Brazilian Food Insecurity Scale. Averages of three indices according to the presence of food insecurity were analyzed, including other variables. Linear regression evaluated the effect of food insecurity on the Z-score of the three nutritional indices. The sample included 4,817 children, out of whom 7% had deficit in height, 7% were overweight and 47% had food insecurity. It was found that the average of height-for-age, weight-for-age and weight-for-height were -0.31, 0.12 and 0.40, respectively, being lower among children with food insecurity. The regression analysis showed that children living with some level of food insecurity have worse rates of height-for-age, even controlling for demographic and socioeconomic factors.

Robust Bayesian linear regression with application to an analysis of the CODATA values for the Planck constant

NASA Astrophysics Data System (ADS)

Wübbeler, Gerd; Bodnar, Olha; Elster, Clemens

2018-02-01

Weighted least-squares estimation is commonly applied in metrology to fit models to measurements that are accompanied with quoted uncertainties. The weights are chosen in dependence on the quoted uncertainties. However, when data and model are inconsistent in view of the quoted uncertainties, this procedure does not yield adequate results. When it can be assumed that all uncertainties ought to be rescaled by a common factor, weighted least-squares estimation may still be used, provided that a simple correction of the uncertainty obtained for the estimated model is applied. We show that these uncertainties and credible intervals are robust, as they do not rely on the assumption of a Gaussian distribution of the data. Hence, common software for weighted least-squares estimation may still safely be employed in such a case, followed by a simple modification of the uncertainties obtained by that software. We also provide means of checking the assumptions of such an approach. The Bayesian regression procedure is applied to analyze the CODATA values for the Planck constant published over the past decades in terms of three different models: a constant model, a straight line model and a spline model. Our results indicate that the CODATA values may not have yet stabilized.

Verification regarding changing construction in accumulation of fat for BMI based on change with age estimated from body composition balance.

PubMed

Fujii, Katsunori; Tanaka, Nozomi; Mishima, Takaaki

2013-12-01

In the present study, a regression analysis of BMI and body fat percentage in each school year was performed with cross-sectional data in school-aged children. The qualitative changes in physique during the school-age years were examined by showing the changes in the level of body fat accu- mulation with age. The subjects were 789 boys and girls (469 boys, 320 girls) aged 7 to 14 years who participated in regular sports activities. Height, weight and body fat percentage were measured. Fat free mass was calculated by subtracting fat mass from body weight. BMI was calculated as body weight (kg) divided by the square of height (m). Regression analysis was conducted for fat percentage against BMI in boys and girls of all school years, and the level of body fat accumulation was considered, the distributions of the frequency of age change were examined. As a result, in the frequency distribution charts there was a shift from excessive fat to low fat from age 7 to 14 years. A χ2 test was then performed for these frequency distribution charts, and the results showed a significant difference in the frequency distribution in each year (P < 0.01). This trend was clearly in boys, and meaning was found in clarifying the changes with age in the body composition balance in boys and girls.

Positive effect of human milk feeding during NICU hospitalization on 24 month neurodevelopment of very low birth weight infants: an Italian cohort study.

PubMed

Gibertoni, Dino; Corvaglia, Luigi; Vandini, Silvia; Rucci, Paola; Savini, Silvia; Alessandroni, Rosina; Sansavini, Alessandra; Fantini, Maria Pia; Faldella, Giacomo

2015-01-01

The aim of this study was to determine the effect of human milk feeding during NICU hospitalization on neurodevelopment at 24 months of corrected age in very low birth weight infants. A cohort of 316 very low birth weight newborns (weight ≤ 1500 g) was prospectively enrolled in a follow-up program on admission to the Neonatal Intensive Care Unit of S. Orsola Hospital, Bologna, Italy, from January 2005 to June 2011. Neurodevelopment was evaluated at 24 months corrected age using the Griffiths Mental Development Scale. The effect of human milk nutrition on neurodevelopment was first investigated using a multiple linear regression model, to adjust for the effects of gestational age, small for gestational age, complications at birth and during hospitalization, growth restriction at discharge and socio-economic status. Path analysis was then used to refine the multiple regression model, taking into account the relationships among predictors and their temporal sequence. Human milk feeding during NICU hospitalization and higher socio-economic status were associated with better neurodevelopment at 24 months in both models. In the path analysis model intraventricular hemorrhage-periventricular leukomalacia and growth restriction at discharge proved to be directly and independently associated with poorer neurodevelopment. Gestational age and growth restriction at birth had indirect significant effects on neurodevelopment, which were mediated by complications that occurred at birth and during hospitalization, growth restriction at discharge and type of feeding. In conclusion, our findings suggest that mother's human milk feeding during hospitalization can be encouraged because it may improve neurodevelopment at 24 months corrected age.

Estimating an area-level socioeconomic status index and its association with colonoscopy screening adherence.

PubMed

Wheeler, David C; Czarnota, Jenna; Jones, Resa M

2017-01-01

Socioeconomic status (SES) is often considered a risk factor for health outcomes. SES is typically measured using individual variables of educational attainment, income, housing, and employment variables or a composite of these variables. Approaches to building the composite variable include using equal weights for each variable or estimating the weights with principal components analysis or factor analysis. However, these methods do not consider the relationship between the outcome and the SES variables when constructing the index. In this project, we used weighted quantile sum (WQS) regression to estimate an area-level SES index and its effect in a model of colonoscopy screening adherence in the Minnesota-Wisconsin Metropolitan Statistical Area. We considered several specifications of the SES index including using different spatial scales (e.g., census block group-level, tract-level) for the SES variables. We found a significant positive association (odds ratio = 1.17, 95% CI: 1.15-1.19) between the SES index and colonoscopy adherence in the best fitting model. The model with the best goodness-of-fit included a multi-scale SES index with 10 variables at the block group-level and one at the tract-level, with home ownership, race, and income among the most important variables. Contrary to previous index construction, our results were not consistent with an assumption of equal importance of variables in the SES index when explaining colonoscopy screening adherence. Our approach is applicable in any study where an SES index is considered as a variable in a regression model and the weights for the SES variables are not known in advance.

The Impact of Maternal Obesity and Excessive Gestational Weight Gain on Maternal and Infant Outcomes in Maine: Analysis of Pregnancy Risk Assessment Monitoring System Results from 2000 to 2010.

PubMed

Baugh, Nancy; Harris, David E; Aboueissa, AbouEl-Makarim; Sarton, Cheryl; Lichter, Erika

2016-01-01

The objective of this study is to understand the relationships between prepregnancy obesity and excessive gestational weight gain (GWG) and adverse maternal and fetal outcomes. Pregnancy risk assessment monitoring system (PRAMS) data from Maine for 2000-2010 were used to determine associations between demographic, socioeconomic, and health behavioral variables and maternal and infant outcomes. Multivariate logistic regression analysis was performed on the independent variables of age, race, smoking, previous live births, marital status, education, BMI, income, rurality, alcohol use, and GWG. Dependent variables included maternal hypertension, premature birth, birth weight, infant admission to the intensive care unit (ICU), and length of hospital stay of the infant. Excessive prepregnancy BMI and excessive GWG independently predicted maternal hypertension. A high prepregnancy BMI increased the risk of the infant being born prematurely, having a longer hospital stay, and having an excessive birth weight. Excessive GWG predicted a longer infant hospital stay and excessive birth weight. A low pregnancy BMI and a lower than recommended GWG were also associated with poor outcomes: prematurity, low birth weight, and an increased risk of the infant admitted to ICU. These findings support the importance of preconception care that promotes achievement of a healthy weight to enhance optimal reproductive outcomes.

Replication of a Genome-Wide Association Study of Birth Weight in Preterm Neonates

PubMed Central

Ryckman, Kelli K; Feenstra, Bjarke; Shaffer, John R.; Bream, Elise NA; Geller, Frank; Feingold, Eleanor; Weeks, Daniel E; Gadow, Enrique; Cosentino, Viviana; Saleme, Cesar; Simhan, Hyagriv N; Merrill, David; Fong, Chin-To; Busch, Tamara; Berends, Susan K; Comas, Belen; Camelo, Jorge L; Boyd, Heather; Laurie, Cathy; Crosslin, David; Zhang, Qi; Doheny, Kim F; Pugh, Elizabeth; Melbye, Mads; Marazita, Mary L; Dagle, John M; Murray, Jeffrey C

2011-01-01

Objective To examine associations in a preterm population between rs9883204 in ADCY5 and rs900400 near LEKR1 and CCNL1 with birth weight. Both markers were associated with birth weight in a term population in a recent genome-wide association (GWA) study by Freathy et al. Study design A meta-analysis of mother and infant samples was performed for associations of rs900400 and rs9883204 with birth weight in 393 families from the U.S., 265 families from Argentina and 735 mother-infant pairs from Denmark. Z scores adjusted for infant sex and gestational age were generated for each population separately and regressed on allele counts. Association evidence was combined across sites by inverse-variance weighted meta-analysis. Results Each additional C allele of rs900400 (LEKR1/CCNL1) in infants was marginally associated with a 0.069 standard deviation (SD) lower birth weight (95% CI = −0.159 – 0.022, P = 0.068). This result was slightly more pronounced after adjusting for smoking (P = 0.036). There were no significant associations identified with rs9883204 or in maternal samples. Conclusions These results indicate the potential importance of this marker on birth weight irrespective of gestational age. PMID:21885063

Gastric cancer, nutritional status, and outcome.

PubMed

Liu, Xuechao; Qiu, Haibo; Kong, Pengfei; Zhou, Zhiwei; Sun, Xiaowei

2017-01-01

We aim to investigate the prognostic value of several nutrition-based indices, including the prognostic nutritional index (PNI), performance status, body mass index, serum albumin, and preoperative body weight loss in patients with gastric cancer (GC). We retrospectively analyzed the records of 1,330 consecutive patients with GC undergoing curative surgery between October 2000 and September 2012. The relationship between nutrition-based indices and overall survival (OS) was examined using Kaplan-Meier analysis and Cox regression model. Following multivariate analysis, the PNI and preoperative body weight loss were the only nutritional-based indices independently associated with OS (hazard ratio [HR]: 1.356, 95% confidence interval [CI]: 1.051-1.748, P =0.019; HR: 1.152, 95% CI: 1.014-1.310, P =0.030, retrospectively). In stage-stratified analysis, multivariate analysis revealed that preoperative body weight loss was identified as an independent prognostic factor only in patients with stage III GC (HR: 1.223, 95% CI: 1.065-1.405, P =0.004), while the prognostic significance of PNI was not significant (all P >0.05). In patients with stage III GC, preoperative body weight loss stratified 5-year OS from 41.1% to 26.5%. When stratified by adjuvant chemotherapy, the prognostic significance of preoperative body weight loss was maintained in patients treated with surgery plus adjuvant chemotherapy and in patients treated with surgery alone ( P <0.001; P =0.003). Preoperative body weight loss is an independent prognostic factor for OS in patients with GC, especially in stage III disease. Preoperative body weight loss appears to be a superior predictor of outcome compared with other established nutrition-based indices.

Guidance for the utility of linear models in meta-analysis of genetic association studies of binary phenotypes.

PubMed

Cook, James P; Mahajan, Anubha; Morris, Andrew P

2017-02-01

Linear mixed models are increasingly used for the analysis of genome-wide association studies (GWAS) of binary phenotypes because they can efficiently and robustly account for population stratification and relatedness through inclusion of random effects for a genetic relationship matrix. However, the utility of linear (mixed) models in the context of meta-analysis of GWAS of binary phenotypes has not been previously explored. In this investigation, we present simulations to compare the performance of linear and logistic regression models under alternative weighting schemes in a fixed-effects meta-analysis framework, considering designs that incorporate variable case-control imbalance, confounding factors and population stratification. Our results demonstrate that linear models can be used for meta-analysis of GWAS of binary phenotypes, without loss of power, even in the presence of extreme case-control imbalance, provided that one of the following schemes is used: (i) effective sample size weighting of Z-scores or (ii) inverse-variance weighting of allelic effect sizes after conversion onto the log-odds scale. Our conclusions thus provide essential recommendations for the development of robust protocols for meta-analysis of binary phenotypes with linear models.

Factors associated with postpartum weight retention in a Brazilian cohort.

PubMed

Zanotti, Joana; Capp, Edison; Wender, Maria Celeste Osório

2015-04-01

To identify the factors associated with weight retention after pregnancy. A cohort study was performed with 145 women receiving maternity care at a hospital in Caxias do Sul, Rio Grande do Sul, Brazil, aged 19 to 45 years, between weeks 38 and 42 of pregnancy. The patients were evaluated at one month, three months, and six months after delivery. Student's t-test or one-way analysis of variance (ANOVA) was used to compare groups, as indicated; correlations were assessed with Pearson's and Spearman's tests, as indicated; to identify and evaluate confounders independently associated with total weight loss, a multivariate linear regression analysis was performed and statistical significance was set at p ≤ 0.05. There was a significant positive association between total weight gain - and a negative association with physical exercise during pregnancy - with total weight loss. Higher parity, inter-pregnancy interval, calorie intake, pre-pregnancy body mass index (BMI), weight gain related to pre-pregnancy BMI, presence and severity of depression, and lack of exclusive breastfeeding were directly associated with lower weight loss. Among nominal variables, level of education and marital status were significantly associated with total weight loss. In the present study, lower weight retention in the postpartum period was associated with higher educational attainment and with being married. Normal or below-normal pre-pregnancy BMI, physical activity and adequate weight gain during pregnancy, lower parity, exclusive breastfeeding for a longer period, appropriate or low calorie intake, and absence of depression were also determinants of reduced weight retention.

Trajectories of maternal weight from before pregnancy through postpartum and associations with childhood obesity.

PubMed

Leonard, Stephanie A; Rasmussen, Kathleen M; King, Janet C; Abrams, Barbara

2017-11-01

Background: Prepregnancy body mass index [BMI (in kg/m 2 )], gestational weight gain, and postpartum weight retention may have distinct effects on the development of child obesity, but their combined effect is currently unknown. Objective: We described longitudinal trajectories of maternal weight from before pregnancy through the postpartum period and assessed the relations between maternal weight trajectories and offspring obesity in childhood. Design: We analyzed data from 4436 pairs of mothers and their children in the National Longitudinal Survey of Youth 1979 (1981-2014). We used latent-class growth modeling in addition to national recommendations for prepregnancy BMI, gestational weight gain, and postpartum weight retention to create maternal weight trajectory groups. We used modified Poisson regression models to assess the associations between maternal weight trajectory group and offspring obesity at 3 age periods (2-5, 6-11, and 12-19 y). Results: Our analysis using maternal weight trajectories based on either latent-class results or recommendations showed that the risk of child obesity was lowest in the lowest maternal weight trajectory group. The differences in obesity risk were largest after 5 y of age and persisted into adolescence. In the latent-class analysis, the highest-order maternal weight trajectory group consisted almost entirely of women who were obese before pregnancy and was associated with a >2-fold increase in the risk of offspring obesity at ages 6-11 y (adjusted RR: 2.39; 95% CI: 1.97, 2.89) and 12-19 y (adjusted RR: 2.74; 95% CI: 2.13, 3.52). In the analysis with maternal weight trajectory groups based on recommendations, the risk of child obesity was consistently highest for women who were overweight or obese at the beginning of pregnancy. Conclusion: These findings suggest that high maternal weight across the childbearing period increases the risk of obesity in offspring during childhood, but high prepregnancy BMI has a stronger influence than either gestational weight gain or postpartum weight retention. © 2017 American Society for Nutrition.

[The effect of pre-pregnancy weight and the increase of gestational weight on fetal growth restriction: a cohort study].

PubMed

Shi, M Y; Wang, Y F; Huang, K; Yan, S Q; Ge, X; Chen, M L; Hao, J H; Tong, S L; Tao, F B

2017-12-06

Objective: To investigate the effect of pre-pregnancy weight and the increase of gestational weight on fetal growth restriction. Methods: From May 2013 to September 2014, a total of 3 474 pregnant women who took their first antenatal care and willing to undergo their prenatal care and delivery in Ma 'anshan Maternity and Child Care Centers were recruited in the cohort study. Excluding subjects without weight data before delivery ( n= 54), pregnancy termination ( n= 162), twins live births ( n= 39), without fetal birth weight data ( n= 7), 3 212 maternal-singleton pairs were enrolled for the final data analysis. Demographic information of pregnant woman, pregnancy history, disease history, height and weight were collected. In the 24(th)-28(th), 32(nd)-36(th) gestational week and childbirth, three follow-up visits were undertaken to collect data of pregnancy weight, pregnancy vomiting, gestational hypertension, gestational diabetes mellitus, newborn gender and birth weight. χ(2) test was used to compare the detection rate of fetal growth restriction in different groups. Multivariate unconditional logistic regression model and spreadsheet were used to analyze the independent and interaction effect of pre-pregnancy weight and the increase of gestational weight on fetal growth restriction. Results: The incidence of fetal growth restriction was 9.7%(311/3 212). The incidence of fetal growth restriction in pre-pregnancy underweight group was 14.9% (90/603), higher than that in normal pre-pregnancy weight group (8.7% (194/2 226)) (χ(2)=24.37, P< 0.001). The incidence of fetal growth restriction in inadequate increase of gestational weight group was 17.9% (50/279), higher than the appropriate increase of weight group (11.8% (110/932)) (χ(2)=36.89, P< 0.001). Multivariate unconditional logistic regression analysis showed that compared with normal pre-pregnancy weight group, pre-pregnancy underweightwas a risk factor for fetal growth restriction, with RR (95 %CI ) at 1.76 (1.34-2.32); Compared with the appropriate increase of gestational weight group, inadequate weight increase during pregnancy was a risk factor for fetal growth restriction, with the RR (95 %CI ) at 1.70 (1.17-2.48). No additive model interaction [relative excess risk of interaction, attributable proportions of interaction, the synergy index and their 95 %CI were 0.75 (-2.14-3.63), 0.21 (-0.43-0.86) and 1.43 (0.45-4.53), respectively] or multiplication model interaction ( RR (95 %CI ): 1.00 (0.44-2.29)) existed between pre-pregnancy underweight and inadequate increase of gestational weight on fetal growth restriction. Conclusion: Pre-pregnancy underweight and inadequate increase of gestational weight would increase the risk of fetal growth restriction without interaction.

Effectiveness of Social Media-based Interventions on Weight-related Behaviors and Body Weight Status: Review and Meta-analysis.

PubMed

An, Ruopeng; Ji, Mengmeng; Zhang, Sheng

2017-11-01

We reviewed scientific literature regarding the effectiveness of social media-based interventions about weight-related behaviors and body weight status. A keyword search were performed in May 2017 in the Clinical-Trials.gov, Cochrane Library, PsycINFO, PubMed, and Web of Science databases. We conducted a meta-analysis to estimate the pooled effect size of social media-based interventions on weight-related outcome measures. We identified 22 interventions from the keyword and reference search, including 12 randomized controlled trials, 6 pre-post studies and 3 cohort studies conducted in 9 countries during 2010-2016. The majority (N = 17) used Facebook, followed by Twitter (N = 4) and Instagram (N = 1). Intervention durations averaged 17.8 weeks with a mean sample size of 69. The meta-analysis showed that social media-based interventions were associated with a statistically significant, but clinically modest reduction of body weight by 1.01 kg, body mass index by 0.92 kg/m2, and waist circumstance by 2.65 cm, and an increase of daily number of steps taken by 1530. In the meta-regression there was no doseresponse effect with respect to intervention duration. The boom of social media provides an unprecedented opportunity to implement health promotion programs. Future interventions should make efforts to improve intervention scalability and effectiveness.

Robust and efficient estimation with weighted composite quantile regression

NASA Astrophysics Data System (ADS)

Jiang, Xuejun; Li, Jingzhi; Xia, Tian; Yan, Wanfeng

2016-09-01

In this paper we introduce a weighted composite quantile regression (CQR) estimation approach and study its application in nonlinear models such as exponential models and ARCH-type models. The weighted CQR is augmented by using a data-driven weighting scheme. With the error distribution unspecified, the proposed estimators share robustness from quantile regression and achieve nearly the same efficiency as the oracle maximum likelihood estimator (MLE) for a variety of error distributions including the normal, mixed-normal, Student's t, Cauchy distributions, etc. We also suggest an algorithm for the fast implementation of the proposed methodology. Simulations are carried out to compare the performance of different estimators, and the proposed approach is used to analyze the daily S&P 500 Composite index, which verifies the effectiveness and efficiency of our theoretical results.

Poverty and Algebra Performance: A Comparative Spatial Analysis of a Border South State

ERIC Educational Resources Information Center

Tate, William F.; Hogrebe, Mark C.

2015-01-01

This research uses two measures of poverty, as well as mobility and selected education variables to study how their relationships vary across 543 Missouri high school districts. Using Missouri and U.S. Census American Community Survey (ACS) data, local R[superscript 2]'s from geographically weighted regressions are spatially mapped to demonstrate…

Post-fire tree establishment patterns at the alpine treeline ecotone: Mount Rainier National Park, Washington, USA

Treesearch

Kirk M. Stueve; Dawna L. Cerney; Regina M. Rochefort; Laurie L. Kurth

2009-01-01

We performed classification analysis of 1970 satellite imagery and 2003 aerial photography to delineate establishment. Local site conditions were calculated from a LIDAR-based DEM, ancillary climate data, and 1970 tree locations in a GIS. We used logistic regression on a spatially weighted landscape matrix to rank variables.

Novel point estimation from a semiparametric ratio estimator (SPRE): long-term health outcomes from short-term linear data, with application to weight loss in obesity.

PubMed

Weissman-Miller, Deborah

2013-11-02

Point estimation is particularly important in predicting weight loss in individuals or small groups. In this analysis, a new health response function is based on a model of human response over time to estimate long-term health outcomes from a change point in short-term linear regression. This important estimation capability is addressed for small groups and single-subject designs in pilot studies for clinical trials, medical and therapeutic clinical practice. These estimations are based on a change point given by parameters derived from short-term participant data in ordinary least squares (OLS) regression. The development of the change point in initial OLS data and the point estimations are given in a new semiparametric ratio estimator (SPRE) model. The new response function is taken as a ratio of two-parameter Weibull distributions times a prior outcome value that steps estimated outcomes forward in time, where the shape and scale parameters are estimated at the change point. The Weibull distributions used in this ratio are derived from a Kelvin model in mechanics taken here to represent human beings. A distinct feature of the SPRE model in this article is that initial treatment response for a small group or a single subject is reflected in long-term response to treatment. This model is applied to weight loss in obesity in a secondary analysis of data from a classic weight loss study, which has been selected due to the dramatic increase in obesity in the United States over the past 20 years. A very small relative error of estimated to test data is shown for obesity treatment with the weight loss medication phentermine or placebo for the test dataset. An application of SPRE in clinical medicine or occupational therapy is to estimate long-term weight loss for a single subject or a small group near the beginning of treatment.

Association of weight loss with improved disease activity in patients with rheumatoid arthritis: A retrospective analysis using electronic medical record data

PubMed Central

Kreps, David J.; Halperin, Florencia; Desai, Sonali P.; Zhang, Zhi Z.; Losina, Elena; Olson, Amber T.; Karlson, Elizabeth W.; Bermas, Bonnie L.; Sparks, Jeffrey A.

2018-01-01

Objective To evaluate the association between weight loss and rheumatoid arthritis (RA) disease activity. Methods We conducted a retrospective cohort study of RA patients seen at routine clinic visits at an academic medical center, 2012–2015. We included patients who had ≥2 clinical disease activity index (CDAI) measures. We identified visits during follow-up where the maximum and minimum weights occurred and defined weight change and CDAI change as the differences of these measures at these visits. We defined disease activity improvement as CDAI decrease of ≥5 and clinically relevant weight loss as ≥5 kg. We performed logistic regression analyses to establish the association between improved disease activity and weight loss and baseline BMI category (≥25 kg/m2 or <25 kg/m2). We built linear regression models to investigate the association between continuous weight loss and CDAI change among patients who were overweight/obese at baseline and who lost weight during follow-up. Results We analyzed data from 174 RA patients with a median follow-up of 1.9 years (IQR 1.3–2.4); 117 (67%) were overweight/obese at baseline, and 53 (31%) lost ≥5 kg during follow-up. Patients who were overweight/obese and lost ≥5 kg had three-fold increased odds of disease activity improvement compared to those who did not (OR 3.03, 95%CI 1.18–7.83). Among those who were overweight/obese at baseline, each kilogram weight loss was associated with CDAI improvement of 1.15 (95%CI 0.42–1.88). Our study was limited by using clinical data from a single center without fixed intervals for assessments. Conclusion Clinically relevant weight loss (≥5 kg) was associated with improved RA disease activity in the routine clinical setting. Further studies are needed for replication and to evaluate the effect of prospective weight loss interventions on RA disease activity. PMID:29606976

Spatial interpolation schemes of daily precipitation for hydrologic modeling

USGS Publications Warehouse

Hwang, Y.; Clark, M.R.; Rajagopalan, B.; Leavesley, G.

2012-01-01

Distributed hydrologic models typically require spatial estimates of precipitation interpolated from sparsely located observational points to the specific grid points. We compare and contrast the performance of regression-based statistical methods for the spatial estimation of precipitation in two hydrologically different basins and confirmed that widely used regression-based estimation schemes fail to describe the realistic spatial variability of daily precipitation field. The methods assessed are: (1) inverse distance weighted average; (2) multiple linear regression (MLR); (3) climatological MLR; and (4) locally weighted polynomial regression (LWP). In order to improve the performance of the interpolations, the authors propose a two-step regression technique for effective daily precipitation estimation. In this simple two-step estimation process, precipitation occurrence is first generated via a logistic regression model before estimate the amount of precipitation separately on wet days. This process generated the precipitation occurrence, amount, and spatial correlation effectively. A distributed hydrologic model (PRMS) was used for the impact analysis in daily time step simulation. Multiple simulations suggested noticeable differences between the input alternatives generated by three different interpolation schemes. Differences are shown in overall simulation error against the observations, degree of explained variability, and seasonal volumes. Simulated streamflows also showed different characteristics in mean, maximum, minimum, and peak flows. Given the same parameter optimization technique, LWP input showed least streamflow error in Alapaha basin and CMLR input showed least error (still very close to LWP) in Animas basin. All of the two-step interpolation inputs resulted in lower streamflow error compared to the directly interpolated inputs. ?? 2011 Springer-Verlag.

Salting-out assisted liquid-liquid extraction and partial least squares regression to assay low molecular weight polycyclic aromatic hydrocarbons leached from soils and sediments

NASA Astrophysics Data System (ADS)

Bressan, Lucas P.; do Nascimento, Paulo Cícero; Schmidt, Marcella E. P.; Faccin, Henrique; de Machado, Leandro Carvalho; Bohrer, Denise

2017-02-01

A novel method was developed to determine low molecular weight polycyclic aromatic hydrocarbons in aqueous leachates from soils and sediments using a salting-out assisted liquid-liquid extraction, synchronous fluorescence spectrometry and a multivariate calibration technique. Several experimental parameters were controlled and the optimum conditions were: sodium carbonate as the salting-out agent at concentration of 2 mol L- 1, 3 mL of acetonitrile as extraction solvent, 6 mL of aqueous leachate, vortexing for 5 min and centrifuging at 4000 rpm for 5 min. The partial least squares calibration was optimized to the lowest values of root mean squared error and five latent variables were chosen for each of the targeted compounds. The regression coefficients for the true versus predicted concentrations were higher than 0.99. Figures of merit for the multivariate method were calculated, namely sensitivity, multivariate detection limit and multivariate quantification limit. The selectivity was also evaluated and other polycyclic aromatic hydrocarbons did not interfere in the analysis. Likewise, high performance liquid chromatography was used as a comparative methodology, and the regression analysis between the methods showed no statistical difference (t-test). The proposed methodology was applied to soils and sediments of a Brazilian river and the recoveries ranged from 74.3% to 105.8%. Overall, the proposed methodology was suitable for the targeted compounds, showing that the extraction method can be applied to spectrofluorometric analysis and that the multivariate calibration is also suitable for these compounds in leachates from real samples.

Assessment of triglyceride and cholesterol in overweight people based on multiple linear regression and artificial intelligence model.

PubMed

Ma, Jing; Yu, Jiong; Hao, Guangshu; Wang, Dan; Sun, Yanni; Lu, Jianxin; Cao, Hongcui; Lin, Feiyan

2017-02-20

The prevalence of high hyperlipemia is increasing around the world. Our aims are to analyze the relationship of triglyceride (TG) and cholesterol (TC) with indexes of liver function and kidney function, and to develop a prediction model of TG, TC in overweight people. A total of 302 adult healthy subjects and 273 overweight subjects were enrolled in this study. The levels of fasting indexes of TG (fs-TG), TC (fs-TC), blood glucose, liver function, and kidney function were measured and analyzed by correlation analysis and multiple linear regression (MRL). The back propagation artificial neural network (BP-ANN) was applied to develop prediction models of fs-TG and fs-TC. The results showed there was significant difference in biochemical indexes between healthy people and overweight people. The correlation analysis showed fs-TG was related to weight, height, blood glucose, and indexes of liver and kidney function; while fs-TC was correlated with age, indexes of liver function (P < 0.01). The MRL analysis indicated regression equations of fs-TG and fs-TC both had statistic significant (P < 0.01) when included independent indexes. The BP-ANN model of fs-TG reached training goal at 59 epoch, while fs-TC model achieved high prediction accuracy after training 1000 epoch. In conclusions, there was high relationship of fs-TG and fs-TC with weight, height, age, blood glucose, indexes of liver function and kidney function. Based on related variables, the indexes of fs-TG and fs-TC can be predicted by BP-ANN models in overweight people.

Effect of caffeic acid phenethyl ester on the regression of endometrial explants in an experimental rat model.

PubMed

Güney, Mehmet; Nasir, Serdar; Oral, Baha; Karahan, Nermin; Mungan, Tamer

2007-04-01

The objective of this study is to determine the effects of antioxidant and anti-inflammatory caffeic acid phenethyl ester (CAPE) on experimental endometriosis, peritoneal superoxide dismutase (SOD) and catalase (CAT) activities, and malondialdehyde (MDA) levels in the rat endometriosis model. Thirty rats with experimentally induced endometriosis were randomly divided into 2 groups and treated for 4 weeks with intraperitoneal CAPE (CAPE-treated group; 10 micromol/kg/d, n = 13) or vehicle (control group; n = 13). The volume and weight changes of the implants were calculated. Immunohistochemical and histologic examinations of endometriotic explants by semiquantitative analysis and measurements of peritoneal SOD, CAT, and MDA levels were made. Following 4 weeks of treatment with CAPE, there were significant differences in posttreatment spherical volumes (37.4 +/- 14.7 mm(3) vs 147.5 +/- 41.2 mm(3)) and explant weights (49.1 +/- 28.5 mg vs 158.9 +/- 50.3 mg) between the CAPE-treated groups and controls. The mean evaluation nomogram levels in glandular epithelium for COX-2 positivity by scoring system were 2.1 +/- 0.3 in the CAPE-treated group and 3.9 +/- 0.3 in the control group. In the CAPE-treated group, peritoneal levels of MDA and activities of SOD and CAT significantly decreased when compared with the control group (P < .01). Histologic analysis of the explants demonstrated mostly atrophy and regression in the treatment group, and semiquantitative analysis showed significantly lower scores in rats treated with CAPE compared with the control group. CAPE appeared to cause regression of experimental endometriosis.

A regression approach to the mapping of bio-physical characteristics of surface sediment using in situ and airborne hyperspectral acquisitions

NASA Astrophysics Data System (ADS)

Ibrahim, Elsy; Kim, Wonkook; Crawford, Melba; Monbaliu, Jaak

2017-02-01

Remote sensing has been successfully utilized to distinguish and quantify sediment properties in the intertidal environment. Classification approaches of imagery are popular and powerful yet can lead to site- and case-specific results. Such specificity creates challenges for temporal studies. Thus, this paper investigates the use of regression models to quantify sediment properties instead of classifying them. Two regression approaches, namely multiple regression (MR) and support vector regression (SVR), are used in this study for the retrieval of bio-physical variables of intertidal surface sediment of the IJzermonding, a Belgian nature reserve. In the regression analysis, mud content, chlorophyll a concentration, organic matter content, and soil moisture are estimated using radiometric variables of two airborne sensors, namely airborne hyperspectral sensor (AHS) and airborne prism experiment (APEX) and and using field hyperspectral acquisitions by analytical spectral device (ASD). The performance of the two regression approaches is best for the estimation of moisture content. SVR attains the highest accuracy without feature reduction while MR achieves good results when feature reduction is carried out. Sediment property maps are successfully obtained using the models and hyperspectral imagery where SVR used with all bands achieves the best performance. The study also involves the extraction of weights identifying the contribution of each band of the images in the quantification of each sediment property when MR and principal component analysis are used.

Selective Weighted Least Squares Method for Fourier Transform Infrared Quantitative Analysis.

PubMed

Wang, Xin; Li, Yan; Wei, Haoyun; Chen, Xia

2017-06-01

Classical least squares (CLS) regression is a popular multivariate statistical method used frequently for quantitative analysis using Fourier transform infrared (FT-IR) spectrometry. Classical least squares provides the best unbiased estimator for uncorrelated residual errors with zero mean and equal variance. However, the noise in FT-IR spectra, which accounts for a large portion of the residual errors, is heteroscedastic. Thus, if this noise with zero mean dominates in the residual errors, the weighted least squares (WLS) regression method described in this paper is a better estimator than CLS. However, if bias errors, such as the residual baseline error, are significant, WLS may perform worse than CLS. In this paper, we compare the effect of noise and bias error in using CLS and WLS in quantitative analysis. Results indicated that for wavenumbers with low absorbance, the bias error significantly affected the error, such that the performance of CLS is better than that of WLS. However, for wavenumbers with high absorbance, the noise significantly affected the error, and WLS proves to be better than CLS. Thus, we propose a selective weighted least squares (SWLS) regression that processes data with different wavenumbers using either CLS or WLS based on a selection criterion, i.e., lower or higher than an absorbance threshold. The effects of various factors on the optimal threshold value (OTV) for SWLS have been studied through numerical simulations. These studies reported that: (1) the concentration and the analyte type had minimal effect on OTV; and (2) the major factor that influences OTV is the ratio between the bias error and the standard deviation of the noise. The last part of this paper is dedicated to quantitative analysis of methane gas spectra, and methane/toluene mixtures gas spectra as measured using FT-IR spectrometry and CLS, WLS, and SWLS. The standard error of prediction (SEP), bias of prediction (bias), and the residual sum of squares of the errors (RSS) from the three quantitative analyses were compared. In methane gas analysis, SWLS yielded the lowest SEP and RSS among the three methods. In methane/toluene mixture gas analysis, a modification of the SWLS has been presented to tackle the bias error from other components. The SWLS without modification presents the lowest SEP in all cases but not bias and RSS. The modification of SWLS reduced the bias, which showed a lower RSS than CLS, especially for small components.

Children's weight changes according to maternal perception of the child's weight and health: A prospective cohort of Peruvian children.

PubMed

Carrillo-Larco, Rodrigo M; Bernabe-Ortiz, Antonio; Miranda, J Jaime; Xue, Hong; Wang, Youfa

2017-01-01

The aim of the study was to estimate the association between maternal perception of their child's health status and (mis)classification of their child's actual weight with future weight change. We present cross-sectional and longitudinal analyses from the Peruvian younger cohort of the Young Lives Study. For cross-sectional analysis, the exposure was maternal perception of child health status (better, same or worse); the outcome was underestimation or overestimation of the child's actual weight. Mothers were asked about their perception of their child's weight (same, lighter or heavier than other children). Actual weight status was defined with IOTF BMI cut-off points. For longitudinal analysis, the exposure was (mis)classification of the child's actual weight; the outcome was the standardized mean difference between follow-up and baseline BMI. A Generalized Linear Model with Poisson family and log-link was used to report the prevalence ratio (PR) and 95% confidence intervals (95% CI) for cross-sectional analyses. A Linear Regression Model was used to report the longitudinal analysis as coefficient estimates (β) and 95% CI. Normal weight children who were perceived as more healthy than other children were more likely to have their weight overestimated (PR = 2.06); conversely, those who were perceived as less healthy than other children were more likely to have their weight underestimated (PR = 2.17). Mean follow-up time was 2.6 (SD: 0.3) years. Overall, underweight children whose weight was overestimated were more likely to gain BMI (β = 0.44); whilst overweight children whose weight was considered to be the same of their peers (β = -0.55), and those considered to be lighter than other children (β = -0.87), lost BMI. Maternal perception of the child's health status seems to influence both overestimation and underestimation of the child's actual weight status. Such weight (mis)perception may influence future BMI.

Children’s weight changes according to maternal perception of the child’s weight and health: A prospective cohort of Peruvian children

PubMed Central

Carrillo-Larco, Rodrigo M.; Bernabe-Ortiz, Antonio; Miranda, J. Jaime; Xue, Hong; Wang, Youfa

2017-01-01

The aim of the study was to estimate the association between maternal perception of their child’s health status and (mis)classification of their child’s actual weight with future weight change. We present cross-sectional and longitudinal analyses from the Peruvian younger cohort of the Young Lives Study. For cross-sectional analysis, the exposure was maternal perception of child health status (better, same or worse); the outcome was underestimation or overestimation of the child’s actual weight. Mothers were asked about their perception of their child’s weight (same, lighter or heavier than other children). Actual weight status was defined with IOTF BMI cut-off points. For longitudinal analysis, the exposure was (mis)classification of the child’s actual weight; the outcome was the standardized mean difference between follow-up and baseline BMI. A Generalized Linear Model with Poisson family and log-link was used to report the prevalence ratio (PR) and 95% confidence intervals (95% CI) for cross-sectional analyses. A Linear Regression Model was used to report the longitudinal analysis as coefficient estimates (β) and 95% CI. Normal weight children who were perceived as more healthy than other children were more likely to have their weight overestimated (PR = 2.06); conversely, those who were perceived as less healthy than other children were more likely to have their weight underestimated (PR = 2.17). Mean follow-up time was 2.6 (SD: 0.3) years. Overall, underweight children whose weight was overestimated were more likely to gain BMI (β = 0.44); whilst overweight children whose weight was considered to be the same of their peers (β = -0.55), and those considered to be lighter than other children (β = -0.87), lost BMI. Maternal perception of the child’s health status seems to influence both overestimation and underestimation of the child’s actual weight status. Such weight (mis)perception may influence future BMI. PMID:28422975

Genetic Contributions to The Association Between Adult Height and Head and Neck Cancer: A Mendelian Randomization Analysis.

PubMed

Pastorino, Roberta; Puggina, Anna; Carreras-Torres, Robert; Lagiou, Pagona; Holcátová, Ivana; Richiardi, Lorenzo; Kjaerheim, Kristina; Agudo, Antonio; Castellsagué, Xavier; Macfarlane, Tatiana V; Barzan, Luigi; Canova, Cristina; Thakker, Nalin S; Conway, David I; Znaor, Ariana; Healy, Claire M; Ahrens, Wolfgang; Zaridze, David; Szeszenia-Dabrowska, Neonilia; Lissowska, Jolanta; Fabianova, Eleonora; Mates, Ioan Nicolae; Bencko, Vladimir; Foretova, Lenka; Janout, Vladimir; Brennan, Paul; Gaborieau, Valérie; McKay, James D; Boccia, Stefania

2018-03-14

With the aim to dissect the effect of adult height on head and neck cancer (HNC), we use the Mendelian randomization (MR) approach to test the association between genetic instruments for height and the risk of HNC. 599 single nucleotide polymorphisms (SNPs) were identified as genetic instruments for height, accounting for 16% of the phenotypic variation. Genetic data concerning HNC cases and controls were obtained from a genome-wide association study. Summary statistics for genetic association were used in complementary MR approaches: the weighted genetic risk score (GRS) and the inverse-variance weighted (IVW). MR-Egger regression was used for sensitivity analysis and pleiotropy evaluation. From the GRS analysis, one standard deviation (SD) higher height (6.9 cm; due to genetic predisposition across 599 SNPs) raised the risk for HNC (Odds ratio (OR), 1.14; 95% Confidence Interval (95%CI), 0.99-1.32). The association analyses with potential confounders revealed that the GRS was associated with tobacco smoking (OR = 0.80, 95% CI (0.69-0.93)). MR-Egger regression did not provide evidence of overall directional pleiotropy. Our study indicates that height is potentially associated with HNC risk. However, the reported risk could be underestimated since, at the genetic level, height emerged to be inversely associated with smoking.

Adherence of pregnant women to Nordic dietary guidelines in relation to postpartum weight retention: results from the Norwegian Mother and Child Cohort Study.

PubMed

von Ruesten, Anne; Brantsæter, Anne Lise; Haugen, Margaretha; Meltzer, Helle Margrete; Mehlig, Kirsten; Winkvist, Anna; Lissner, Lauren

2014-01-24

Pregnancy is a major life event for women and often connected with changes in diet and lifestyle and natural gestational weight gain. However, excessive weight gain during pregnancy may lead to postpartum weight retention and add to the burden of increasing obesity prevalence. Therefore, it is of interest to examine whether adherence to nutrient recommendations or food-based guidelines is associated with postpartum weight retention 6 months after birth. This analysis is based on data from the Norwegian Mother and Child Cohort Study (MoBa) conducted by the Norwegian Institute of Public Health. Diet during the first 4-5 months of pregnancy was assessed by a food-frequency questionnaire and maternal weight before pregnancy as well as in the postpartum period was assessed by questionnaires. Two Healthy Eating Index (HEI) scores were applied to measure compliance with either the official Norwegian food-based guidelines (HEI-NFG) or the Nordic Nutrition Recommendations (HEI-NNR) during pregnancy. The considered outcome, i.e. weight retention 6 months after birth, was modelled in two ways: continuously (in kg) and categorically (risk of substantial postpartum weight retention, i.e. ≥ 5% gain to pre-pregnancy weight). Associations between the HEI-NFG and HEI-NNR score with postpartum weight retention on the continuous scale were estimated by linear regression models. Relationships of both HEI scores with the categorical outcome variable were evaluated using logistic regression. In the continuous model without adjustment for gestational weight gain (GWG), the HEI-NFG score but not the HEI-NNR score was inversely related to postpartum weight retention. However, after additional adjustment for GWG as potential intermediate the HEI-NFG score was marginally inversely and the HEI-NNR score was inversely associated with postpartum weight retention. In the categorical model, both HEI scores were inversely related with risk of substantial postpartum weight retention, independent of adjustment for GWG. Higher adherence to either the official Norwegian food guidelines or possibly also to Nordic Nutrition Recommendations during pregnancy appears to be associated with lower postpartum weight retention.

Adherence of pregnant women to Nordic dietary guidelines in relation to postpartum weight retention: results from the Norwegian Mother and Child Cohort Study

PubMed Central

2014-01-01

Background Pregnancy is a major life event for women and often connected with changes in diet and lifestyle and natural gestational weight gain. However, excessive weight gain during pregnancy may lead to postpartum weight retention and add to the burden of increasing obesity prevalence. Therefore, it is of interest to examine whether adherence to nutrient recommendations or food-based guidelines is associated with postpartum weight retention 6 months after birth. Methods This analysis is based on data from the Norwegian Mother and Child Cohort Study (MoBa) conducted by the Norwegian Institute of Public Health. Diet during the first 4-5 months of pregnancy was assessed by a food-frequency questionnaire and maternal weight before pregnancy as well as in the postpartum period was assessed by questionnaires. Two Healthy Eating Index (HEI) scores were applied to measure compliance with either the official Norwegian food-based guidelines (HEI-NFG) or the Nordic Nutrition Recommendations (HEI-NNR) during pregnancy. The considered outcome, i.e. weight retention 6 months after birth, was modelled in two ways: continuously (in kg) and categorically (risk of substantial postpartum weight retention, i.e. ≥ 5% gain to pre-pregnancy weight). Associations between the HEI-NFG and HEI-NNR score with postpartum weight retention on the continuous scale were estimated by linear regression models. Relationships of both HEI scores with the categorical outcome variable were evaluated using logistic regression. Results In the continuous model without adjustment for gestational weight gain (GWG), the HEI-NFG score but not the HEI-NNR score was inversely related to postpartum weight retention. However, after additional adjustment for GWG as potential intermediate the HEI-NFG score was marginally inversely and the HEI-NNR score was inversely associated with postpartum weight retention. In the categorical model, both HEI scores were inversely related with risk of substantial postpartum weight retention, independent of adjustment for GWG. Conclusions Higher adherence to either the official Norwegian food guidelines or possibly also to Nordic Nutrition Recommendations during pregnancy appears to be associated with lower postpartum weight retention. PMID:24456804

Dipyrone use during pregnancy and adverse perinatal events.

PubMed

da Silva Dal Pizzol, Tatiane; Schüler-Faccini, Lavínia; Mengue, Sotero Serrate; Fischer, Maria Isabel

2009-03-01

To evaluate the risk of adverse perinatal events among newborns exposed to dipyrone during gestation. The present study is a secondary analysis of Brazilian study of gestational diabetes (EBDG), a cohort of women attended at healthcare units of the Brazilian national health system (SUS) located in six Brazilian state capitals, between February 1991 and June 1995. A total number of 5,564 women aged 20 years and over who were between their 21st and 28th week of pregnancy were followed up. A structured questionnaire was used to obtain data on the pregnant women, their pregnancies, and their use of medications. Other data and the outcomes congenital abnormalities, intrauterine death, preterm birth, or low birth weight were obtained from the medical records. To estimate the odds ratios after adjustment for the potential confounding factors, logistic regression modeling was developed. Congenital abnormalities, intrauterine death, preterm birth, and low birth weight. Dipyrone use was reported by 555 pregnant women (11.5%). Their exposure to this medication did not present any association with the outcomes of congenital abnormalities (OR 1.11; 95% CI, 0.58-2.10), intrauterine death (OR 0.69; 95% CI, 0.33-1.43), preterm birth (OR 0.94; 95% CI, 0.73-1.20), or low birth weight (OR 0.88; 95% CI, 0.64-1.22), in the crude analysis. This absence of associations was maintained after performing logistic regression analysis. The data suggest that the exposure to dipyrone during pregnancy does not increase the risk of congenital abnormalities and other adverse events as outcomes from pregnancy.

Use of birth weight threshold for macrosomia to identify fetuses at risk of shoulder dystocia among Chinese populations.

PubMed

Cheng, Yvonne K-Y; Lao, Terence T; Sahota, Daljit S; Leung, Viola K-T; Leung, Tak Y

2013-03-01

To assess the incidence of macrosomia and the influence of birth weight on shoulder dystocia risk among a cohort of Chinese women. A retrospective analysis was conducted of 80953 singleton deliveries recorded at the Prince of Wales Hospital, Hong Kong, between 1995 and 2009. The incidences of macrosomia (birth weight ≥ 4000 g) and shoulder dystocia were assessed by birth weight; risk factors for shoulder dystocia were examined by multiple logistic regression analysis. The incidence of macrosomia was 3.4%. The overall incidence of shoulder dystocia was 0.3%; however, the incidence rose with increasing birth weight. The odds ratio (OR) for a birth weight of 4000-4199 g was 22.40, while the OR for a birth weight of 4200 g or above was 76.10. Other independent risk factors for shoulder dystocia included instrumental delivery (OR 12.11), short stature (OR 2.16), maternal diabetes mellitus (OR 1.78), and obesity (OR 1.58). Although the overall incidences of macrosomia and shoulder dystocia were low, the risk of shoulder dystocia was strongly linked to increasing birth weight. International guidelines for elective cesarean delivery in suspected cases of macrosomia may not, therefore, apply to Chinese women. Copyright © 2012 International Federation of Gynecology and Obstetrics. Published by Elsevier Ireland Ltd. All rights reserved.

Biometric studies on the bivalves Astarte elliptica, A. borealis and A. montagui in Kiel Bay (Western Baltic Sea)

NASA Astrophysics Data System (ADS)

Schaefer, R.; Trutschler, K.; Rumohr, H.

1985-09-01

The three Astarte species were studied in June 1983 at two sites in Kiel Bay, “Süderfahrt” and “Schleimünde”, at 20 m depth. Shell length to live wet weight correlations are given for all three species; for A. elliptica also shell-free dry weight, shell dry weight, ash-free dry weight of the soft body and ash-free dry weight of the shell are recorded as functions of the shell length. In the logarithmic length/weight regression analysis the coefficients of slope for A. elliptica and A. borealis are 3. For A. montagui, that coefficient is significantly greater than 3. Weight conversion factors, calculated for A. elliptica, revealed a mean weight composition of 31.5 % water in the mantle cavity and tissue water, 64.5 % shell ash, 2.1 % organic content of shell, 1.7 % organic content of the soft body and 0.4 % ash of the soft body. An isometric growth of shell length and shell breadth is confirmed for A. borealis, while A. montagui exhibits positive allometric shell growth and changes its shape during life.

Transmission of linear regression patterns between time series: From relationship in time series to complex networks

NASA Astrophysics Data System (ADS)

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

2014-07-01

The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.

Transmission of linear regression patterns between time series: from relationship in time series to complex networks.

PubMed

Gao, Xiangyun; An, Haizhong; Fang, Wei; Huang, Xuan; Li, Huajiao; Zhong, Weiqiong; Ding, Yinghui

2014-07-01

The linear regression parameters between two time series can be different under different lengths of observation period. If we study the whole period by the sliding window of a short period, the change of the linear regression parameters is a process of dynamic transmission over time. We tackle fundamental research that presents a simple and efficient computational scheme: a linear regression patterns transmission algorithm, which transforms linear regression patterns into directed and weighted networks. The linear regression patterns (nodes) are defined by the combination of intervals of the linear regression parameters and the results of the significance testing under different sizes of the sliding window. The transmissions between adjacent patterns are defined as edges, and the weights of the edges are the frequency of the transmissions. The major patterns, the distance, and the medium in the process of the transmission can be captured. The statistical results of weighted out-degree and betweenness centrality are mapped on timelines, which shows the features of the distribution of the results. Many measurements in different areas that involve two related time series variables could take advantage of this algorithm to characterize the dynamic relationships between the time series from a new perspective.

Robust geographically weighted regression of modeling the Air Polluter Standard Index (APSI)

NASA Astrophysics Data System (ADS)

Warsito, Budi; Yasin, Hasbi; Ispriyanti, Dwi; Hoyyi, Abdul

2018-05-01

The Geographically Weighted Regression (GWR) model has been widely applied to many practical fields for exploring spatial heterogenity of a regression model. However, this method is inherently not robust to outliers. Outliers commonly exist in data sets and may lead to a distorted estimate of the underlying regression model. One of solution to handle the outliers in the regression model is to use the robust models. So this model was called Robust Geographically Weighted Regression (RGWR). This research aims to aid the government in the policy making process related to air pollution mitigation by developing a standard index model for air polluter (Air Polluter Standard Index - APSI) based on the RGWR approach. In this research, we also consider seven variables that are directly related to the air pollution level, which are the traffic velocity, the population density, the business center aspect, the air humidity, the wind velocity, the air temperature, and the area size of the urban forest. The best model is determined by the smallest AIC value. There are significance differences between Regression and RGWR in this case, but Basic GWR using the Gaussian kernel is the best model to modeling APSI because it has smallest AIC.

Fish measurement using Android smart phone: the example of swamp eel

NASA Astrophysics Data System (ADS)

Chen, Baisong; Fu, Zhuo; Ouyang, Haiying; Sun, Yingze; Ge, Changshui; Hu, Jing

The body length and weight are critical physiological parameters for fishes, especially eel-like fishes like swamp eel(Monopterusalbus).Fast and accurate measuring of body length is significant for swamp eel culturing as well as its resource investigation and protection. This paper presents an Android smart phone-based photogrammetry technology for measuring and estimating the length and weight of swamp eel. This method utilizes the feature that the ratio of lengths of two objects within an image is equal to that of in reality to measure the length of swamp eels. And then, it estimates the weight via a pre-built length-weight regression model. Analysis and experimental results have indicated that this method is a fast and accurate method for length and weight measurements of swamp eel. The cross-validation results shows that the RMSE (root-mean-square error) of total length measurement of swamp eel is0.4 cm, and the RMSE of weight estimation is 11 grams.

Visceral organ weights, digestion and carcass characteristics of beef bulls differing in residual feed intake offered a high concentrate diet.

PubMed

Fitzsimons, C; Kenny, D A; McGee, M

2014-06-01

This study examined the relationship of residual feed intake (RFI) with digestion, body composition, carcass traits and visceral organ weights in beef bulls offered a high concentrate diet. Individual dry matter (DM) intake (DMI) and growth were measured in a total of 67 Simmental bulls (mean initial BW 431 kg (s.d.=63.7)) over 3 years. Bulls were offered concentrates (860 g/kg rolled barley, 60 g/kg soya bean meal, 60 g/kg molasses and 20 g/kg minerals per vitamins) ad libitum plus 0.8 kg grass silage DM daily for 105 days pre-slaughter. Ultrasonic muscle and fat depth, body condition score (BCS), muscularity score, skeletal measurements, blood metabolites, rumen fermentation and total tract digestibility (indigestible marker) were determined. After slaughter, carcasses and perinephric and retroperitoneal fat were weighed, carcasses were graded for conformation and fat score and weight of non-carcass organs, liver, heart, kidneys, lungs, gall bladder, spleen, reticulo-rumen full and empty and intestines full, were determined. The residuals of the regression of DMI on average daily gain (ADG), mid-test metabolic BW (BW0.75) and the fixed effect of year, using all animals, were used to compute individual RFI coefficients. Animals were ranked on RFI and assigned to high (inefficient), medium or low groupings. Overall mean ADG and daily DMI were 1.6 kg (s.d.=0.36) and 9.4 kg (s.d.=1.16), respectively. High RFI bulls consumed 7 and 14% more DM than medium and low RFI bulls, respectively (P<0.001). No differences between high and low RFI bulls were detected (P>0.05) for ADG, BW, BCS, skeletal measurements, muscularity scores, ultrasonic measurements, carcass weight, perinephric and retroperitoneal fat weight, kill-out proportion and carcass conformation and fat score. However, regression analysis indicated that a 1 kg DM/day increase in RFI was associated with a decrease in kill-out proportion of 20 g/kg (P<0.05) and a decrease in carcass conformation of 0.74 units (P<0.05). Weight of non-carcass organs did not differ (P>0.05) between RFI groups except for the empty weight of reticulo-rumen, which was 8% lighter (P=0.05) in low RFI compared with high RFI bulls. Regression analysis indicated that a 1 kg DM/day increase in RFI was associated with a 1 kg increase in reticulo-rumen empty weight (P<0.05). Of the visceral organs measured, the reticulo-rumen may be a biologically significant contributory factor to variation in RFI in beef bulls finished on a high concentrate diet.

Regional Regression Equations to Estimate Flow-Duration Statistics at Ungaged Stream Sites in Connecticut

USGS Publications Warehouse

Ahearn, Elizabeth A.

2010-01-01

Multiple linear regression equations for determining flow-duration statistics were developed to estimate select flow exceedances ranging from 25- to 99-percent for six 'bioperiods'-Salmonid Spawning (November), Overwinter (December-February), Habitat Forming (March-April), Clupeid Spawning (May), Resident Spawning (June), and Rearing and Growth (July-October)-in Connecticut. Regression equations also were developed to estimate the 25- and 99-percent flow exceedances without reference to a bioperiod. In total, 32 equations were developed. The predictive equations were based on regression analyses relating flow statistics from streamgages to GIS-determined basin and climatic characteristics for the drainage areas of those streamgages. Thirty-nine streamgages (and an additional 6 short-term streamgages and 28 partial-record sites for the non-bioperiod 99-percent exceedance) in Connecticut and adjacent areas of neighboring States were used in the regression analysis. Weighted least squares regression analysis was used to determine the predictive equations; weights were assigned based on record length. The basin characteristics-drainage area, percentage of area with coarse-grained stratified deposits, percentage of area with wetlands, mean monthly precipitation (November), mean seasonal precipitation (December, January, and February), and mean basin elevation-are used as explanatory variables in the equations. Standard errors of estimate of the 32 equations ranged from 10.7 to 156 percent with medians of 19.2 and 55.4 percent to predict the 25- and 99-percent exceedances, respectively. Regression equations to estimate high and median flows (25- to 75-percent exceedances) are better predictors (smaller variability of the residual values around the regression line) than the equations to estimate low flows (less than 75-percent exceedance). The Habitat Forming (March-April) bioperiod had the smallest standard errors of estimate, ranging from 10.7 to 20.9 percent. In contrast, the Rearing and Growth (July-October) bioperiod had the largest standard errors, ranging from 30.9 to 156 percent. The adjusted coefficient of determination of the equations ranged from 77.5 to 99.4 percent with medians of 98.5 and 90.6 percent to predict the 25- and 99-percent exceedances, respectively. Descriptive information on the streamgages used in the regression, measured basin and climatic characteristics, and estimated flow-duration statistics are provided in this report. Flow-duration statistics and the 32 regression equations for estimating flow-duration statistics in Connecticut are stored on the U.S. Geological Survey World Wide Web application ?StreamStats? (http://water.usgs.gov/osw/streamstats/index.html). The regression equations developed in this report can be used to produce unbiased estimates of select flow exceedances statewide.

Body composition and cross-sectional areas of limb lean tissues in Olympic weight lifters.

PubMed

Kanehisa, H; Ikegawa, S; Fukunaga, T

1998-10-01

The cross-sectional area (CSAs) of bone and muscle tissues in the forearm, upper arm, lower leg, and thigh and body composition were determined by B-mode ultrasound and underwater weighing methods, respectively for 56 college Olympic weight lifters and 28 age-matched non-athletes to investigate the magnitude of musculoskeletal development in the strength-trained athletes belonging to the weight-classified sports event. The average value of fat-free mass (FFM) for the weight lifters ranked 12.6 kg above the regression line of FFM on stature for untrained subjects. In the weight lifters, however, the percentage of fat mass to body mass was also highly correlated to body mass index. Bone and muscle CSAs in every site were significantly larger in the weight lifter than in the untrained subjects with relative differences of 22 to 58% and 17 to 56%, respectively. Moreover, as a result of regression analysis for the mixed data from weight lifters and untrained subjects, significant correlation was found between bone and muscle CSAs in every site (r = 0.620 to 0.791, P < 0.05). The differences in lean (bone + muscle) CSA were still significant in all sites except for the lower leg even when the difference in body size was statistically controlled. The comparisons between the weight lifters and untrained subjects on the lean CSA ratios of site to site and muscle CSA ratios of flexors to extensors indicated that the weight lifters had achieved a high relative distribution of lean tissues in the arms and a dominant development in elbow and knee extensors. Thus, the present results suggested that participation in weight lifting exercises for a long period could increase bone CSA as well as muscle CSA, and induce in the participants a noticeable enlargement in given sites and muscle groups responsible for performing the Olympic lifts.

Fatigue design of a cellular phone folder using regression model-based multi-objective optimization

NASA Astrophysics Data System (ADS)

Kim, Young Gyun; Lee, Jongsoo

2016-08-01

In a folding cellular phone, the folding device is repeatedly opened and closed by the user, which eventually results in fatigue damage, particularly to the front of the folder. Hence, it is important to improve the safety and endurance of the folder while also reducing its weight. This article presents an optimal design for the folder front that maximizes its fatigue endurance while minimizing its thickness. Design data for analysis and optimization were obtained experimentally using a test jig. Multi-objective optimization was carried out using a nonlinear regression model. Three regression methods were employed: back-propagation neural networks, logistic regression and support vector machines. The AdaBoost ensemble technique was also used to improve the approximation. Two-objective Pareto-optimal solutions were identified using the non-dominated sorting genetic algorithm (NSGA-II). Finally, a numerically optimized solution was validated against experimental product data, in terms of both fatigue endurance and thickness index.

Relation between birth weight and weight and height at the age of 2 in children born preterm.

PubMed

Olson, Gayle; Weiner, Steven J; Rouse, Dwight J; Reddy, Uma M; Mercer, Brian M; Varner, Michael W; Leveno, Kenneth J; Iams, Jay D; Wapner, Ronald J; Ramin, Susan M; Malone, Fergal D; Carpenter, Marshall W; O'Sullivan, Mary J; Dinsmoor, Mara J; Hankins, Gary D V; Caritis, Steve N

2015-05-01

The aim of the study was to evaluate associations between fetal growth and weight at 2 years in infants born preterm using a customized approach for birth weight. This is a secondary analysis of a multicenter trial that included a 2-year follow-up of children born prematurely. Customized birth weight percentiles were calculated using the Gardosi model for a U.S. population, and the relation between customized percentile and weight and height at 2 years (adjusted for gender using z-score) was determined using regression analysis and by comparing z-scores for children with birth weight <10th versus ≥10th percentile. Weight z-score at 2 years was significantly lower in the <10th than in the ≥10th percentile group (median [interquartile range, IQR]: -0.66 [-1.58, -0.01] vs. -0.23 [-1.05, 0.55]; p < 0.001), and remained after adjusting for maternal education (p < 0.001). A similar relationship was noted for height z-score between groups (median [IQR]: -0.56 [-1.29, 0.19] vs. -0.24 [-0.99, 0.37]; p < 0.001). Positive relationships between customized birth weight percentile and weight and height at 2 years were noted (p < 0.001 for both), but were not strong (R (2) = 0.04 and 0.02, respectively). Customized birth weight percentile is a minor determinant of weight at 2 years among children born preterm. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Culture media influenced laboratory outcomes but not neonatal birth weight in assisted reproductive technology.

PubMed

Yin, Tai-lang; Zhang, Yi; Li, Sai-jiao; Zhao, Meng; Ding, Jin-li; Xu, Wang-ming; Yang, Jing

2015-12-01

Whether the type of culture media utilized in assisted reproductive technology has impacts on laboratory outcomes and birth weight of newborns in in-vitro fertilization (IVF)/intracytoplasmic sperm injection (ICSI) was investigated. A total of 673 patients undergoing IVF/ICSI and giving birth to live singletons after fresh embryo transfer on day 3 from Jan. 1, 2010 to Dec. 31, 2012 were included. Three types of culture media were used during this period: Quinn's Advantage (QA), Single Step Medium (SSM), and Continuous Single Culture medium (CSC). Fertilization rate (FR), normal fertilization rate (NFR), cleavage rate (CR), normal cleavage rate (NCR), good-quality embryo rate (GQER) and neonatal birth weight were compared using one-way ANOVA and χ (2) tests. Multiple linear regression analysis was performed to determine the impact of culture media on laboratory outcomes and birth weight. In IVF cycles, GQER was significantly decreased in SSM medium group as compared with QA or CSC media groups (63.6% vs. 69.0% in QA; vs. 71.3% in CSC, P=0.011). In ICSI cycles, FR, NFR and CR were significantly lower in CSC medium group than in other two media groups. No significant difference was observed in neonatal birthweight among the three groups (P=0.759). Multiple linear regression analyses confirmed that the type of culture medium was correlated with FR, NFR, CR and GQER, but not with neonatal birth weight. The type of culture media had potential influences on laboratory outcomes but did not exhibit an impact on the birth weight of singletons in ART.

C-reactive protein, platelets, and patent ductus arteriosus.

PubMed

Meinarde, Leonardo; Hillman, Macarena; Rizzotti, Alina; Basquiera, Ana Lisa; Tabares, Aldo; Cuestas, Eduardo

2016-12-01

The association between inflammation, platelets, and patent ductus arteriosus (PDA) has not been studied so far. The purpose of this study was to evaluate whether C-reactive protein (CRP) is related to low platelet count and PDA. This was a retrospective study of 88 infants with a birth weight ≤1500 g and a gestational age ≤30 weeks. Platelet count, CRP, and an echocardiogram were assessed in all infants. The subjects were matched by sex, gestational age, and birth weight. Differences were compared using the χ 2 , t-test, or Mann-Whitney U-test, as appropriate. Significant variables were entered into a logistic regression model. The association between CRP and platelets was evaluated by correlation and regression analysis. Platelet count (167 000 vs. 213 000 µl -1 , p = 0.015) was lower and the CRP (0.45 vs. 0.20 mg/dl, p = 0.002) was higher, and the platelet count correlated inversely with CRP (r = -0.145, p = 0.049) in the infants with vs. without PDA. Only CRP was independently associated with PDA in a logistic regression model (OR 64.1, 95% confidence interval 1.4-2941, p = 0.033).

[A dose-response analysis on the association of gestational weight gain rate and the normal term neonate birth weight].

PubMed

Mao, Yuanyuan; Hu, Wenbin; Liu, Qin; Liu, Li; Li, Yuanming; Shen, Yueping

2015-08-01

To examine the dose-response relationship between gestational weight gain rate and the neonate birth weight. A total of 18 868 women with singleton gestations who delivered between January 2006 and December 2013 were included in this study. Maternal and neonate details of these women were drawn from the Perinatal Monitoring System database. Gestational weight gain rate was defined as the total weight gain during the last and first prenatal care visits divided by the interval weeks. Both Multiple logistic regression analysis and restricted cubic spline methods were performed. Confounding factors included maternal age, education, pre-pregnancy body mass index (BMI), state of residence, parity, gestational weeks of prenatal care entry, and sex of the neonate. The adjusted odds ratio for macrosomia was associated with gestational weight gain rate in lower pre-pregnancy BMI (OR = 3.15, 95% CI: 1.40-7.07), normal (OR = 3.64, 95% CI: 2.84-4.66) or overweight (OR = 2.37, 95% CI: 1.71-3.27). The odds ratios of low birth weight appeared a decrease in those women with lower pre-pregnancy BMI (OR = 0.28, 95% CI: 0.13-0.61) while the normal weight (OR = 0.37, 95% CI: 0.22-0.64) group with gestational weight gain, the rate showed an increase. Association of gestational weight gain rate for macrosomia was found a S-curve in those term delivery women (non-linearity test P < 0.000 1). However, L-curve was observed for low birth weight and gestational weight gain rate in term births (non-linearity test P < 0.000 1). A S-curve was seen between gestational weight gain rate and term delivered macrosomia while L-curve was observed among term delivered low birth weight neonates.

Modifiable lifestyle factors affecting bone health using calcaneus quantitative ultrasound in adolescent girls.

PubMed

Robinson, M L; Winters-Stone, K; Gabel, K; Dolny, D

2007-08-01

One hundred and fourteen girls were measured for calcaneus QUS (stiffness index score), calcium intake, weight, and total hours spent in physical activity (moderate to high-impact activities and low to no-impact activities). Multiple regression analysis indicated that hours spent in moderate to high-impact activities, current calcium intake, and weight significantly predicted SI. To determine the influence of modifiable lifestyle factors on adolescent girls' bone health measured by calcaneus quantitative ultrasound (QUS). One hundred and fourteen girls, ages 14-18 (15.97 +/- .7), enrolled in high school physical education classes, were measured for calcaneus QUS (stiffness index score), height, weight, current calcium intake from 2-3 day food records, and estimated total hours spent in physical activity from kindergarten to present. Cumulative physical activity hours were separated into two classifications (according to their estimated strain from ground reaction force): moderate to high-impact activities and low to no-impact activities. Pearson correlations between stiffness index (SI) and age, height, weight, current calcium intake, and hours spent in moderate to high-impact versus low to no-impact activities indicated a positive relationships between SI and weight (r = .259, p = .005), current calcium intake (r = .286, p = .002), and hours spent in moderate to high-impact activities (r = .451, p < .001). Multiple regression between SI and the above independent variables indicated that collectively, hours spent in moderate to high-impact activities, current calcium intake, and weight (r (2) = .363, p = <.001) significantly predicted SI. Our data indicate that moderate to high-impact activities, current calcium intake, and weight positively influence bone properties of the calcaneus in adolescent girls.

Maternal weight status and responsiveness to preterm infant behavioral cues during feeding.

PubMed

Arianas, Evanthia A; Rankin, Kristin M; Norr, Kathleen F; White-Traut, Rosemary C

2017-04-11

Parental obesity is highly predictive of child obesity, and preterm infants are at greater risk of obesity, but little is known about obese and non-obese mothers' responsiveness to preterm infant cues during feeding. The relationship between maternal weight status and response to preterm infant behavioral cues during feeding at 6-weeks corrected age was examined. This secondary analysis used data from a randomized clinical trial. Maternal weight was coded during a play session. Mother-infant interaction during feeding was coded using the Nursing Child Assessment Satellite Training Feeding Scale (NCAST). We used multivariate linear regressions to examine NCAST scores and multivariate logistic regressions for the two individual items, satiation cues and termination of feeding. Of the 139 mothers, 56 (40.3%) were obese, two underweight women were excluded. Obese mothers did not differ from overweight/normal weight mothers for overall NCAST scores, but they had higher scores on response to infant's distress subscale (mean = 10.2 vs. 9.6, p = 0.01). The proportion of infants who exhibited satiation cues did not differ by maternal weight. Obese mothers were more likely than overweight/normal weight mothers to terminate the feeding when the infant showed satiation cues (82.1% vs. 66.3%, p = 0.04, adjusted OR = 2.31, 95% CI = 0.97, 5.48). Limitations include lack of BMI measures and small sample size. Additional research is needed about maternal weight status and whether it influences responsiveness to preterm infant satiation cues. Results highlight the need for educating all mothers of preterm infants regarding preterm infant cues. NCT02041923 . Feeding and Transition to Home for Preterms at Social Risk (H-HOPE). Registered 15 January 2014.

Analysis of Binary Adherence Data in the Setting of Polypharmacy: A Comparison of Different Approaches

PubMed Central

Esserman, Denise A.; Moore, Charity G.; Roth, Mary T.

2009-01-01

Older community dwelling adults often take multiple medications for numerous chronic diseases. Non-adherence to these medications can have a large public health impact. Therefore, the measurement and modeling of medication adherence in the setting of polypharmacy is an important area of research. We apply a variety of different modeling techniques (standard linear regression; weighted linear regression; adjusted linear regression; naïve logistic regression; beta-binomial (BB) regression; generalized estimating equations (GEE)) to binary medication adherence data from a study in a North Carolina based population of older adults, where each medication an individual was taking was classified as adherent or non-adherent. In addition, through simulation we compare these different methods based on Type I error rates, bias, power, empirical 95% coverage, and goodness of fit. We find that estimation and inference using GEE is robust to a wide variety of scenarios and we recommend using this in the setting of polypharmacy when adherence is dichotomously measured for multiple medications per person. PMID:20414358

Robust Methods for Moderation Analysis with a Two-Level Regression Model.

PubMed

Yang, Miao; Yuan, Ke-Hai

2016-01-01

Moderation analysis has many applications in social sciences. Most widely used estimation methods for moderation analysis assume that errors are normally distributed and homoscedastic. When these assumptions are not met, the results from a classical moderation analysis can be misleading. For more reliable moderation analysis, this article proposes two robust methods with a two-level regression model when the predictors do not contain measurement error. One method is based on maximum likelihood with Student's t distribution and the other is based on M-estimators with Huber-type weights. An algorithm for obtaining the robust estimators is developed. Consistent estimates of standard errors of the robust estimators are provided. The robust approaches are compared against normal-distribution-based maximum likelihood (NML) with respect to power and accuracy of parameter estimates through a simulation study. Results show that the robust approaches outperform NML under various distributional conditions. Application of the robust methods is illustrated through a real data example. An R program is developed and documented to facilitate the application of the robust methods.

Using existing case-mix methods to fund trauma cases.

PubMed

Monakova, Julia; Blais, Irene; Botz, Charles; Chechulin, Yuriy; Picciano, Gino; Basinski, Antoni

2010-01-01

Policymakers frequently face the need to increase funding in isolated and frequently heterogeneous (clinically and in terms of resource consumption) patient subpopulations. This article presents a methodologic solution for testing the appropriateness of using existing grouping and weighting methodologies for funding subsets of patients in the scenario where a case-mix approach is preferable to a flat-rate based payment system. Using as an example the subpopulation of trauma cases of Ontario lead trauma hospitals, the statistical techniques of linear and nonlinear regression models, regression trees, and spline models were applied to examine the fit of the existing case-mix groups and reference weights for the trauma cases. The analyses demonstrated that for funding Ontario trauma cases, the existing case-mix systems can form the basis for rational and equitable hospital funding, decreasing the need to develop a different grouper for this subset of patients. This study confirmed that Injury Severity Score is a poor predictor of costs for trauma patients. Although our analysis used the Canadian case-mix classification system and cost weights, the demonstrated concept of using existing case-mix systems to develop funding rates for specific subsets of patient populations may be applicable internationally.

The Uncertain Geographic Context Problem in the Analysis of the Relationships between Obesity and the Built Environment in Guangzhou

PubMed Central

Zhao, Pengxiang; Zhou, Suhong

2018-01-01

Traditionally, static units of analysis such as administrative units are used when studying obesity. However, using these fixed contextual units ignores environmental influences experienced by individuals in areas beyond their residential neighborhood and may render the results unreliable. This problem has been articulated as the uncertain geographic context problem (UGCoP). This study investigates the UGCoP through exploring the relationships between the built environment and obesity based on individuals’ activity space. First, a survey was conducted to collect individuals’ daily activity and weight information in Guangzhou in January 2016. Then, the data were used to calculate and compare the values of several built environment variables based on seven activity space delineations, including home buffers, workplace buffers (WPB), fitness place buffers (FPB), the standard deviational ellipse at two standard deviations (SDE2), the weighted standard deviational ellipse at two standard deviations (WSDE2), the minimum convex polygon (MCP), and road network buffers (RNB). Lastly, we conducted comparative analysis and regression analysis based on different activity space measures. The results indicate that significant differences exist between variables obtained with different activity space delineations. Further, regression analyses show that the activity space delineations used in the analysis have a significant influence on the results concerning the relationships between the built environment and obesity. The study sheds light on the UGCoP in analyzing the relationships between obesity and the built environment. PMID:29439392

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region.

PubMed

Li, Tianyu; Meng, Qingmin

2017-05-01

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

Forest dynamics to precipitation and temperature in the Gulf of Mexico coastal region

NASA Astrophysics Data System (ADS)

Li, Tianyu; Meng, Qingmin

2017-05-01

The forest is one of the most significant components of the Gulf of Mexico (GOM) coast. It provides livelihood to inhabitant and is known to be sensitive to climatic fluctuations. This study focuses on examining the impacts of temperature and precipitation variations on coastal forest. Two different regression methods, ordinary least squares (OLS) and geographically weighted regression (GWR), were employed to reveal the relationship between meteorological variables and forest dynamics. OLS regression analysis shows that changes in precipitation and temperature, over a span of 12 months, are responsible for 56% of NDVI variation. The forest, which is not particularly affected by the average monthly precipitation in most months, is observed to be affected by cumulative seasonal and annual precipitation explicitly. Temperature and precipitation almost equally impact on NDVI changes; about 50% of the NDVI variations is explained in OLS modeling, and about 74% of the NDVI variations is explained in GWR modeling. GWR analysis indicated that both precipitation and temperature characterize the spatial heterogeneity patterns of forest dynamics.

Isolating and Examining Sources of Suppression and Multicollinearity in Multiple Linear Regression.

PubMed

Beckstead, Jason W

2012-03-30

The presence of suppression (and multicollinearity) in multiple regression analysis complicates interpretation of predictor-criterion relationships. The mathematical conditions that produce suppression in regression analysis have received considerable attention in the methodological literature but until now nothing in the way of an analytic strategy to isolate, examine, and remove suppression effects has been offered. In this article such an approach, rooted in confirmatory factor analysis theory and employing matrix algebra, is developed. Suppression is viewed as the result of criterion-irrelevant variance operating among predictors. Decomposition of predictor variables into criterion-relevant and criterion-irrelevant components using structural equation modeling permits derivation of regression weights with the effects of criterion-irrelevant variance omitted. Three examples with data from applied research are used to illustrate the approach: the first assesses child and parent characteristics to explain why some parents of children with obsessive-compulsive disorder accommodate their child's compulsions more so than do others, the second examines various dimensions of personal health to explain individual differences in global quality of life among patients following heart surgery, and the third deals with quantifying the relative importance of various aptitudes for explaining academic performance in a sample of nursing students. The approach is offered as an analytic tool for investigators interested in understanding predictor-criterion relationships when complex patterns of intercorrelation among predictors are present and is shown to augment dominance analysis.

High weight or body mass index increase the risk of vertebral fractures in postmenopausal osteoporotic women.

PubMed

Pirro, Matteo; Fabbriciani, Gianluigi; Leli, Christian; Callarelli, Laura; Manfredelli, Maria Rosaria; Fioroni, Claudio; Mannarino, Massimo Raffaele; Scarponi, Anna Maria; Mannarino, Elmo

2010-01-01

In the general population, low body weight and body mass index (BMI) are significant risk factors for any fracture, but the specific association between body weight, BMI, and prevalence of vertebral fractures in osteoporotic women is not fully recognized. Hence, the association between body weight, BMI, and prevalent vertebral fractures was investigated in 362 women with never-treated postmenopausal osteoporosis. All participants underwent measurement of BMI, bone mineral density (BMD), and semiquantitative assessment of vertebral fractures. Thirty percent of participants had > or =1 vertebral fracture. Body weight and BMI were associated with L1-L4 BMD (R = 0.29, P < 0.001 and R = 0.17, P = 0.009, respectively). In logistic regression analysis, BMI was positively associated with the presence of vertebral fractures independent of age and other traditional risk factors for fractures. Including weight and height instead of BMI in the multivariate model, showed weight as a positive and significant covariate of the presence of vertebral fractures (OR = 1.045; P = 0.016; 95% CI 1.008-1.084). BMI was associated with the number of vertebral fractures (rho = 0.18; P = 0.001), this association being confirmed also in the multivariate analysis (beta = 0.14; P = 0.03) after correction for smoking, early menopause, family history of fragility fractures and BMD. In conclusion, among postmenopausal women with osteoporosis, body weight and BMI are associated with a higher likelihood of having a vertebral fracture, irrespective of the positive association between weight and BMD.

Association between weight perception and psychological distress.

PubMed

Atlantis, E; Ball, K

2008-04-01

Obesity is a well-known cause of cardiovascular disease burden and premature death, but effects on depressive symptoms remain equivocal. Depressive symptoms may be more common among the obese individuals who perceive themselves as overweight, rather than those who perceive themselves as having an acceptable weight. Our aim was to determine whether weight status and weight perceptions are independently associated with psychological distress. We conducted a cross-sectional study using data from the Australian National Health Survey 2004-2005 (N=17 253). All variables were collected by self-report. Adjusted multinomial logistic regression analysis was conducted to generate prevalence odds ratios with 95% confidence intervals (95% CI) for medium (Kessler Psychological Distress Scale (K10) scores of 20-29) and high (K10 scores of 30-50) psychological distress (compared with K10 scores of 10-19 as the reference) associated with weight status (standard body mass index (BMI) cutoffs for underweight, overweight and obesity vs normal weight), weight perception (perceived underweight and overweight vs acceptable weight) and weight misperception (incorrect with BMI vs correct with BMI) adjusting for numerous important covariates. Overweight and underweight perception increased the odds of medium (40 and 50%) and high (50 and 120%) psychological distress, whereas weight status and weight misperception were not associated with psychological distress in adjusted analysis. Gender, alcohol consumed per week and post-school education were not significant covariates (at P<0.10 level). Overweight and underweight perception rather than weight status or weight misperception are significant risk factors associated with medium and high psychological distress prevalence and effects appear to be uniform for men and women. Well-designed prospective studies are still needed to determine whether weight perceptions cause psychological distress, and if so, whether symptoms are significantly reduced following effective intervention.

Maternal fat free mass during pregnancy is associated with birth weight.

PubMed

Wang, Yanxia; Mao, Jie; Wang, Wenling; Qiou, Jie; Yang, Lan; Chen, Simin

2017-03-28

The relationship between maternal body compositions and birth weight was not definite. Fat Mass (FM) and Fat Free Mass (FFM) can accurately reflect the maternal body fat compositions and have been considered as better predictors of birth weight. Despite its potential role, no studies have been described the maternal compositions during pregnancy in East Asian women previously. We investigated the correlation between birth weight and Maternal body composition including fat mass (FM) and fat free mass (FFM). To determine whether birth weight is associated with maternal body fat FM and FFM during pregnancy and, if so, which trimester and parameter is more critical in determining birth weight. A longitudinal prospective observational study performed, 348, 481 and 321 non-diabetics Han Chinese women with a singleton live birth attending a routine visit in their first, second and third trimesters were recruited. Maternal body composition was measured using segmental multi-frequency bioelectrical impedance analysis. Data of the pre-pregnancy body mass index (BMI), maternal BMI, the gestational weight gain (GWG), and placental and birth weight were collected. A significant correlation exists between maternal FFM in the process of pregnancy, placental weight, GWG at delivery, and birth weight (P < 0.05). On stepwise multiple linear regression analysis, material's FFM was the most important factor associated with the birth weight. After adjustment, there was significantly associated with 2.47-fold increase in risk for birth weight more than 4 kg when FFM ≥ 40.76 kg (Upper quartile of participants). The increased maternal age became a protective factor (OR = 0.69) while the increased pre-pregnancy BMI (OR = 1.50) remained predictors to birth weight more than 4 kg. The change of maternal FFM during pregnancy is independently affected the birth weight.

Weight Management Belief is the Leading Influential Factor of Weight Monitoring Compliance in Congestive Heart Failure Patients.

PubMed

Lu, Min-Xia; Zhang, Yan-Yun; Jiang, Jun-Fang; Ju, Yang; Wu, Qing; Zhao, Xin; Wang, Xiao-Hua

2016-11-01

Daily weight monitoring is frequently recommended as a part of heart failure self-management to prevent exacerbations. This study is to identify factors that influence weight monitoring compliance of congestive heart failure patients at baseline and after a 1-year weight management (WM) program. This was a secondary analysis of an investigative study and a randomized controlled study. A general information questionnaire assessed patient demographics and clinical variables such as medicine use and diagnoses, and the weight management scale evaluated their WM abilities. Good and poor compliance based on abnormal weight gain from the European Society of Cardiology (> 2 kg in 3 days) were compared, and hierarchical multiple logistic regression analysis was used to identify factors influencing weight monitoring compliance. A total of 316 patients were enrolled at baseline, and 66 patients were enrolled after the 1-year WM program. Of them, 12.66% and 60.61% had good weight monitoring compliance at baseline and after 1 year of WM, respectively. A high WM-related belief score indicated good weight monitoring compliance at both time points [odds ratio (OR), 1.043, 95% confidence interval (CI), 1.023-1.063, p < 0.001; and OR, 2.054, 95% CI, 1.209-3.487, p < 0.001, respectively). Patients with a high WM-related practice score had good weight monitoring compliance at baseline (OR, 1.046, 95% CI, 1.027-1.065, p < 0.001), and patients who had not monitored abnormal weight had poor weight monitoring compliance after the 1-year WM program (OR, 0.244, 95% CI, 0.006-0.991, p = 0.049). Data from this study suggested that belief related to WM plays an important role in weight monitoring compliance.

Aripiprazole treatment of irritability associated with autistic disorder and the relationship between prior antipsychotic exposure, adverse events, and weight change.

PubMed

Mankoski, Raymond; Stockton, Gwen; Manos, George; Marler, Sabrina; McQuade, Robert; Forbes, Robert A; Marcus, Ronald

2013-10-01

The purpose of this study was to evaluate the impact of prior antipsychotic exposure (PAE) on safety and tolerability outcomes in pediatric subjects receiving aripiprazole treatment. This study was a post-hoc analysis of pooled data from two 8-week, double-blind, randomized, placebo-controlled studies evaluating aripiprazole for the treatment of irritability in pediatric subjects with autistic disorder, aged 6-17 years. Subjects were stratified by PAE; adverse events (AEs), and changes in weight, and metabolic measures were evaluated. For subjects receiving aripiprazole, regardless of PAE, baseline weight, age, gender, and symptom severity were evaluated in a regression model predicting body weight change. Of 316 randomized subjects, 259 (82.0%) were antipsychotic naïve (AN) and 57 (18.0%) had a PAE. Aripiprazole-treated AN subjects were more likely than PAE subjects to report somnolence (11.9% vs. 2.8%), sedation (22.7% vs. 11.1%), or fatigue (17.0% vs. 13.9%). Rates of extrapyramidal disorder and drooling, but not akathisia or tremor, were marginally higher in AN subjects. Overall, 10.8% of aripiprazole-treated AN subjects had at least one AE leading to discontinuation compared with 8.3% of aripiprazole-treated PAE subjects. AN subjects receiving aripiprazole had a larger change in weight from baseline to endpoint compared with those receiving placebo (1.9 vs. 0.7 kg; treatment difference 1.2 kg, 95% CI: 0.5, 1.9) than PAE subjects receiving aripiprazole compared with subjects receiving placebo (0.4 vs. -0.4 kg; treatment difference 0.9 kg, 95% CI: -0.6, 2.4). Regression analysis identified that younger subjects with higher baseline weight z-score were at highest risk for weight gain. There were no significant changes in metabolic measures compared with placebo in either group. Weight gain was more pronounced in AN subjects and more likely to occur in younger subjects with a higher baseline weight z-score. AN subjects were more likely to experience AEs related to somnolence. However, based on discontinuations rates from AEs, overall tolerability was good for both AN and PAE groups. Study of aripiprazole in the treatment of children and adolescents with autistic disorder. Registry: www.clinicaltrials.gov . Identifiers: NCT00332241 and NCT00337571.

Impact of Weight-Related Discrimination, Body Dissatisfaction and Self-Stigma on the Desire to Weigh Less.

PubMed

Jung, Franziska; Spahlholz, Jenny; Hilbert, Anja; Riedel-Heller, Steffi G; Luck-Sikorski, Claudia

2017-01-01

Currently, health care professionals plead for stabilization of weight and improving health conditions rather than focusing on weight loss only. Individuals with obesity have been shown to report weight loss goals that are much higher than what has been suggested by guidelines. The aim was to determine whether weight discrimination and body dissatisfaction have an impact on how much weight an individual with obesity wants to lose. In this representative telephone survey, 878 participants with obesity were asked about their experiences with weight stigma, their body image concerns, and about the amount of weight they would like to weigh using random digital dialing and Kish selection grid to ensure random selection of participants. Regression analysis reveals that being female, having a higher BMI, being younger, and trying to lose weight was related to a greater discrepancy between current weight and desired weight. The discrepancy between current weight and desired weight was greater when participants reported discrimination due to their weight as well as internalized stigma and body image concerns. Independent on the weight loss method, treating obesity should include realistic weight loss goals without being affected by social pressure or weight stigma, especially since stigma can result in further weight gain and decline health issues related to obesity and overweight. © 2017 The Author(s) Published by S. Karger GmbH, Freiburg.

The PILI@Work Program: a translation of the diabetes prevention program to Native Hawaiian-serving worksites in Hawai'i.

PubMed

Townsend, Claire K M; Miyamoto, Robin E S; Antonio, Mapuana; Zhang, Guangxing; Paloma, Diane; Basques, DeAnna; Braun, Kathryn L; Kaholokula, Joseph Keawe'aimoku

2016-06-01

A previously translated Diabetes Prevention Program Lifestyle Intervention (DPP-LI) was adapted for delivery as a worksite-based intervention, called PILI@Work, to address obesity disparities in Native Hawaiians/Pacific Islanders. This study examined the effectiveness of PILI@Work and factors associated with weight loss at post-intervention. Overweight/obese employees of 15 Native Hawaiian-serving organizations received the 3-month component of PILI@Work. Assessments included weight, systolic/diastolic blood pressure, physical activity and functioning, fat intake, locus of weight control, social support, and self-efficacy. Weight, systolic/diastolic blood pressure, physical functioning, physical activity frequency, fat intake, family support, and eating self-efficacy improved from pre- to post-intervention. Regression analysis indicated that worksite type, decreased diastolic blood pressure, increased physical activity, and more internalized locus of weight control were significantly associated with 3-month weight loss. PILI@Work initiated weight loss in Native Hawaiians/Pacific Islanders. DPP-LI translated to worksite settings and tailored for specific populations can be effective for addressing obesity.

Perception of Child Weight and Feeding Styles in Parents of Chinese-American Preschoolers.

PubMed

Chang, Lucy Y; Mendelsohn, Alan L; Fierman, Arthur H; Au, Loretta Y; Messito, Mary Jo

2017-04-01

Parent perception of weight and feeding styles are associated with obesity in other racial groups but have not been explored in-depth in Chinese-American preschoolers. Cross-sectional survey of 253 Chinese-American parents with preschoolers was performed in a community clinic. Regression analysis was used to assess relationships between parental perception of weight and feeding styles. Parent under-perception of weight was common but more likely in boys than girls (χ 2  = 4.91, p = 0.03). Pressuring was also greater in boys [adjusted mean difference (95% CI) 0.24 (0.004, 0.49)]. In girls, pressuring was lower for children perceived as overweight [adjusted mean difference in CFQ scores -0.75 (-1.27, -0.23)]; in boys, pressuring was high regardless of perceived child weight. Weight perceptions and feeding styles related to childhood obesity in other groups were identified in Chinese-American families. Parent under-perception of child weight and pressure to eat were more common in boys. These factors should be addressed in Chinese-American preschooler obesity prevention programs.

Weighted SGD for ℓ p Regression with Randomized Preconditioning.

PubMed

Yang, Jiyan; Chow, Yin-Lam; Ré, Christopher; Mahoney, Michael W

2016-01-01

In recent years, stochastic gradient descent (SGD) methods and randomized linear algebra (RLA) algorithms have been applied to many large-scale problems in machine learning and data analysis. SGD methods are easy to implement and applicable to a wide range of convex optimization problems. In contrast, RLA algorithms provide much stronger performance guarantees but are applicable to a narrower class of problems. We aim to bridge the gap between these two methods in solving constrained overdetermined linear regression problems-e.g., ℓ 2 and ℓ 1 regression problems. We propose a hybrid algorithm named pwSGD that uses RLA techniques for preconditioning and constructing an importance sampling distribution, and then performs an SGD-like iterative process with weighted sampling on the preconditioned system.By rewriting a deterministic ℓ p regression problem as a stochastic optimization problem, we connect pwSGD to several existing ℓ p solvers including RLA methods with algorithmic leveraging (RLA for short).We prove that pwSGD inherits faster convergence rates that only depend on the lower dimension of the linear system, while maintaining low computation complexity. Such SGD convergence rates are superior to other related SGD algorithm such as the weighted randomized Kaczmarz algorithm.Particularly, when solving ℓ 1 regression with size n by d , pwSGD returns an approximate solution with ε relative error in the objective value in (log n ·nnz( A )+poly( d )/ ε 2 ) time. This complexity is uniformly better than that of RLA methods in terms of both ε and d when the problem is unconstrained. In the presence of constraints, pwSGD only has to solve a sequence of much simpler and smaller optimization problem over the same constraints. In general this is more efficient than solving the constrained subproblem required in RLA.For ℓ 2 regression, pwSGD returns an approximate solution with ε relative error in the objective value and the solution vector measured in prediction norm in (log n ·nnz( A )+poly( d ) log(1/ ε )/ ε ) time. We show that for unconstrained ℓ 2 regression, this complexity is comparable to that of RLA and is asymptotically better over several state-of-the-art solvers in the regime where the desired accuracy ε , high dimension n and low dimension d satisfy d ≥ 1/ ε and n ≥ d 2 / ε . We also provide lower bounds on the coreset complexity for more general regression problems, indicating that still new ideas will be needed to extend similar RLA preconditioning ideas to weighted SGD algorithms for more general regression problems. Finally, the effectiveness of such algorithms is illustrated numerically on both synthetic and real datasets, and the results are consistent with our theoretical findings and demonstrate that pwSGD converges to a medium-precision solution, e.g., ε = 10 -3 , more quickly.

Weighted SGD for ℓp Regression with Randomized Preconditioning*

PubMed Central

Yang, Jiyan; Chow, Yin-Lam; Ré, Christopher; Mahoney, Michael W.

2018-01-01

In recent years, stochastic gradient descent (SGD) methods and randomized linear algebra (RLA) algorithms have been applied to many large-scale problems in machine learning and data analysis. SGD methods are easy to implement and applicable to a wide range of convex optimization problems. In contrast, RLA algorithms provide much stronger performance guarantees but are applicable to a narrower class of problems. We aim to bridge the gap between these two methods in solving constrained overdetermined linear regression problems—e.g., ℓ2 and ℓ1 regression problems. We propose a hybrid algorithm named pwSGD that uses RLA techniques for preconditioning and constructing an importance sampling distribution, and then performs an SGD-like iterative process with weighted sampling on the preconditioned system.By rewriting a deterministic ℓp regression problem as a stochastic optimization problem, we connect pwSGD to several existing ℓp solvers including RLA methods with algorithmic leveraging (RLA for short).We prove that pwSGD inherits faster convergence rates that only depend on the lower dimension of the linear system, while maintaining low computation complexity. Such SGD convergence rates are superior to other related SGD algorithm such as the weighted randomized Kaczmarz algorithm.Particularly, when solving ℓ1 regression with size n by d, pwSGD returns an approximate solution with ε relative error in the objective value in 𝒪(log n·nnz(A)+poly(d)/ε2) time. This complexity is uniformly better than that of RLA methods in terms of both ε and d when the problem is unconstrained. In the presence of constraints, pwSGD only has to solve a sequence of much simpler and smaller optimization problem over the same constraints. In general this is more efficient than solving the constrained subproblem required in RLA.For ℓ2 regression, pwSGD returns an approximate solution with ε relative error in the objective value and the solution vector measured in prediction norm in 𝒪(log n·nnz(A)+poly(d) log(1/ε)/ε) time. We show that for unconstrained ℓ2 regression, this complexity is comparable to that of RLA and is asymptotically better over several state-of-the-art solvers in the regime where the desired accuracy ε, high dimension n and low dimension d satisfy d ≥ 1/ε and n ≥ d2/ε. We also provide lower bounds on the coreset complexity for more general regression problems, indicating that still new ideas will be needed to extend similar RLA preconditioning ideas to weighted SGD algorithms for more general regression problems. Finally, the effectiveness of such algorithms is illustrated numerically on both synthetic and real datasets, and the results are consistent with our theoretical findings and demonstrate that pwSGD converges to a medium-precision solution, e.g., ε = 10−3, more quickly. PMID:29782626

PERIOD2 variants are associated with abdominal obesity, psycho-behavioral factors, and attrition in the dietary treatment of obesity.

PubMed

Garaulet, Marta; Corbalán-Tutau, M Dolores; Madrid, Juan A; Baraza, Juan C; Parnell, Laurence D; Lee, Yu-Chi; Ordovas, Jose M

2010-06-01

The purpose of this research was to test for association between polymorphisms in the circadian clock-related gene PERIOD2 (PER2) and attrition in patients prone to withdrawal from a behavioral weight-reduction program based on the Mediterranean diet. A total of 454 overweight/obese participants (women=380, men=74), aged 20 to 65 years, who attended outpatient clinics specializing in obesity between January and December 2008, were studied. Anthropometric, biochemical, and dietary-intake variables were analyzed. Effectiveness of the program was assessed, and a questionnaire of barriers to weight loss was considered. Multivariate analysis and logistic regression models were performed. Results indicate that PER2 polymorphisms rs2304672C>G and rs4663302C>T were associated with abdominal obesity (P<0.05). Participants who withdrew from treatment were significantly more obese and had more barriers to lose weight (P<0.05). They also displayed a lower likelihood of planning eating in advance and experiencing stress with dieting than those who completed treatment. Frequency of rs4663307 minor allele was significantly greater in withdrawers than in those who successfully completed treatment (P<0.05). Logistic regression analysis showed that rs2304672 C>G minor allele carriers had a greater probability of dropping out, displaying extreme snacking, experiencing stress with dieting, eating when bored, and skipping breakfast than noncarriers. PER2 is implicated in attrition in weight-loss treatment and may modulate eating-behavior-related phenotypes. These findings could represent a step toward personalized health care and nutrition based on a combination of genotyping and psycho-behavioral characterization. 2010 American Dietetic Association. Published by Elsevier Inc. All rights reserved.

Screening for retinopathy of prematurity and treatment outcome in a tertiary hospital in Hong Kong.

PubMed

Iu, L Pl; Lai, C Hy; Fan, M Cy; Wong, I Yh; Lai, J Sm

2017-02-01

Studies on the prevalence and severity of retinopathy of prematurity in the local population are scarce. This study aimed to evaluate the prevalence, screening, and treatment outcome of retinopathy of prematurity in a tertiary hospital in Hong Kong. This cross-sectional study with internal comparison was conducted at Queen Mary Hospital, Hong Kong. The study evaluated 89 premature infants who were born at the hospital and were screened for retinopathy of prematurity, in accordance with the 2008 British Guidelines, between January 2013 and December 2013. The prevalences of retinopathy of prematurity and severe retinopathy requiring treatment were studied. The mean (± standard deviation) gestational age at birth was 30 +2 weeks ± 16.5 days (range, 24 +1 to 35 +5 weeks). The mean birth weight was 1285 g ± 328 g (range, 580 g to 2030 g). A total of 15 (16.9%) infants developed retinopathy of prematurity and three (3.4%) required treatment. In a subgroup analysis of extremely-low-birth-weight infants of <1000 g, 70.6% developed retinopathy of prematurity and 17.6% required treatment. Multivariate logistic regression analysis suggested low birth weight and patent ductus arteriosus were significantly associated with development of retinopathy of prematurity (P<0.001 and P=0.035, respectively). Among the three infants who received treatment for severe retinopathy of prematurity, all regressed successfully after one laser treatment. Retinopathy of prematurity is a significant problem among premature infants in Hong Kong, especially those with extremely low birth weight. Our screening service for retinopathy of prematurity was satisfactory and treatment results were good. Strict adherence to international screening guidelines and vigilance in infants at risk are key to successful management of retinopathy of prematurity.

The association of self-esteem, depression and body satisfaction with obesity among Turkish adolescents

PubMed Central

Ozmen, Dilek; Ozmen, Erol; Ergin, Dilek; Cetinkaya, Aynur Cakmakci; Sen, Nesrin; Dundar, Pinar Erbay; Taskin, E Oryal

2007-01-01

Background The purpose of this study was to determine the prevalence of overweight and obesity and to examine the effects of actual weight status, perceived weight status and body satisfaction on self-esteem and depression in a high school population in Turkey. Methods A cross-sectional survey of 2101 tenth-grade Turkish adolescents aged 15–18 was conducted. Body mass index (BMI) was calculated using weight and height measures. The overweight and obesity were based on the age- and gender-spesific BMI cut-off points of the International Obesity Task Force values. Self-esteem was measured using the Rosenberg Self-Esteem Scale, and depression was measured using Children's Depression Inventory. Logistic regression analysis was used to examine relationships among the variables. Results Based on BMI cut-off points, 9.0% of the students were overweight and 1.1% were obese. Logistic regression analysis indicated that (1) being male and being from a higher socio-economical level were important in the prediction of overweight based on BMI; (2) being female and being from a higher socio-economical level were important in the prediction of perceived overweight; (3) being female was important in the prediction of body dissatisfaction; (4) body dissatisfaction was related to low self-esteem and depression, perceived overweight was related only to low self-esteem but actual overweight was not related to low self-esteem and depression in adolescents. Conclusion The results of this study suggest that school-based adolescents in urban Turkey have a lower risk of overweight and obesity than adolescents in developed countries. The findings of this study suggest that psychological well-being of adolescents is more related to body satisfaction than actual and perceived weight status is. PMID:17506879

Food intake and gestational weight gain in Swedish women.

PubMed

Bärebring, Linnea; Brembeck, Petra; Löf, Marie; Brekke, Hilde K; Winkvist, Anna; Augustin, Hanna

2016-01-01

The objective of this study was to investigate if food intake (dairy, snacks, caloric beverages, bread, cheese, margarine/butter, potato/rice/pasta/grains, red meat, fish and fruit/berries/vegetables) is associated with gestational weight gain (GWG) in Swedish women. Four day food records from 95 pregnant Swedish women were collected in the last trimester. GWG was calculated as weighed body weight in the last trimester (median gestational week 36) minus self-reported pre-pregnancy body weight. Excessive GWG was defined according to the guidelines by the Institute of Medicine. Food groups tested for association with GWG were dairy (milk, yoghurt and sour milk), snacks (sweets, crisps, popcorn, ice cream and cookies, but not nuts and seeds), caloric beverages (soft drinks, juice, lemonade and non-alcoholic beer), bread, cheese, margarine/butter, potato/rice/pasta/grains, red meat, fish and fruit/berries/vegetables. Median (lower-upper quartiles) GWG was 12.1 kg (10.0-15.3). In total, 28 % had an excessive GWG. Excessive GWG was most common among pre-pregnancy overweight and obese women, where 69 % had an excessive GWG. Median daily intake of fruits and vegetables was 352 g (212-453), caloric beverages was 238 g (100-420) and snacks was 111 g (69-115). Multivariable linear regression analysis showed that intake of caloric beverages, snacks, fish, bread and dairy in the last trimester of pregnancy were positively related to GWG (R(2) = 0.32). Multivariable logistic regression analysis showed that intake of caloric beverages, snacks, fish, and bread was associated with higher odds ratios for excessive GWG. Intake of caloric beverages, snacks, fish and bread were positively related to excessive GWG. Thus, these results indicate that maternal dietary intake should be given higher attention in the antenatal care.

Dimensions of socioeconomic position related to body mass index and obesity among Danish women and men.

PubMed

Groth, M V; Fagt, S; Stockmarr, A; Matthiessen, J; Biltoft-Jensen, A

2009-06-01

The aim of this study was to examine the association between different dimensions of socioeconomic position, body mass index (BMI) and obesity in the Danish population. Possible interactions between the different dimensions and gender differences were also investigated. This was a cross-sectional survey conducted in 2000-2002 including a simple random sample from the civil registration system, comprising 1953 males and 2167 females aged 4-75 years. Information about different dimensions of socioeconomic position, height and weight was obtained by face-to-face interview. Associations between dimensions of socioeconomic position and weight status were examined by use of linear multiple regression analysis and logistic regression analysis. BMI and prevalence of obesity were significantly associated with education for both men and women. Odds ratios (ORs) for obesity were 2.9 (95% confidence interval (CI) 1.4-5.9) and 6.5 (95% CI 2.3-18.7) for those with basic school as compared with those with long higher education for men and women, respectively. Women outside the labour market had higher BMIs and a greater prevalence of obesity (OR 2.5 (95% CI 1.6-3.9)) after adjustment for educational level. Education was the dimension most consistently associated with BMI and obesity, indicating the importance of cultural capital for weight status. The gender-specific pattern showed a stronger social gradient for women, and indicated that a high relative body weight was associated with less favourable social and material conditions for women, but not for men. A public health strategy to prevent and reduce obesity should be gender-specific, focus on groups with short education, and incorporate cultural norms.

Insurance-mandated medical weight management before bariatric surgery.

PubMed

Horwitz, Daniel; Saunders, John K; Ude-Welcome, Akuezunkpa; Parikh, Manish

2016-01-01

Many insurance companies require a medical weight management (MWM) program as a prerequisite for approval for bariatric surgery. There is debate regarding the benefit of this requirement. The objective of this study is to assess the effect of insurance-mandated MWM programs on weight loss outcomes in our bariatric surgery population. To assess the effect of insurance-mandated MWM programs on weight loss outcomes in our bariatric surgery population. University. A retrospective review of all bariatric surgery cases performed between 2009 and 2013 was conducted. Patients were stratified by payor mix based on whether the insurance company required MWM. To control for differences between groups, a bucket matching algorithm was used to match patients based on gender, age, body mass index (BMI), and surgery type (sleeve gastrectomy, gastric bypass, or gastric band). A repeated-measures regression model was created to estimate percent excess weight loss, percent excess BMI loss, and percent total weight loss. A total of 1432 bariatric surgery patients were reviewed. The bucket-matching algorithm resulted in 560 patients for final analysis. Mean age and BMI were 41 years and 43 kg/m(2), respectively, and 91% were female. The regression model found no significant differences in weight loss outcomes between the MWM group and the comparison group at 1 year and 2 years-percent total weight loss: 21.3% [95% confidence interval [CI] 20.6%-22.1%] versus 20.2% [95%CI 19.7%-20.6%) at 1 year and 23.4% [95%CI 22.6%-24.3%] versus 21.5% [95%CI 21.0%-22.0%] at 2 years. There was no difference in weight loss outcomes up to 2 years in patients who required insurance-mandated MWM programs. Longer-term studies are needed to determine the benefit of this insurance requirement. Copyright © 2016 American Society for Bariatric Surgery. Published by Elsevier Inc. All rights reserved.

Weight Gain in Survivors Living in Temporary Housing in the Tsunami-Stricken Area during the Recovery Phase following the Great East Japan Earthquake and Tsunami.

PubMed

Takahashi, Shuko; Yonekura, Yuki; Sasaki, Ryohei; Yokoyama, Yukari; Tanno, Kozo; Sakata, Kiyomi; Ogawa, Akira; Kobayashi, Seichiro; Yamamoto, Taro

2016-01-01

Survivors who lost their homes in the Great East Japan Earthquake and Tsunami were forced to live in difficult conditions in temporary housing several months after the disaster. Body weights of survivors living in temporary housing for a long period might increase due to changes in their life style and psychosocial state during the medium-term and long-term recovery phases. The aim of this study was to determine whether there were differences between body weight changes of people living in temporary housing and those not living in temporary housing in a tsunami-stricken area during the medium-term and long-term recovery phases. Health check-ups were performed about 7 months after the disaster (in 2011) and about 18 months after the disaster (in 2012) for people living in a tsunami-stricken area (n = 6,601, mean age = 62.3 y). We compared the changes in body weight in people living in temporary housing (TH group, n = 2,002) and those not living in temporary housing (NTH group, n = 4,599) using a multiple linear regression model. While there was no significant difference between body weights in the TH and NTH groups in the 2011 survey, there was a significant difference between the mean changes in body weight in both sexes. We found that the changes in body weight were significantly greater in the TH group than in the NTH group in both sexes. The partial regression coefficients of mean change in body weight were +0.52 kg (P-value < 0.001) in males in the TH group and +0.56 kg (P-value < 0.001) in females in the TH group (reference: NTH group). Analysis after adjustment for life style, psychosocial factors and cardiovascular risk factors found that people living in temporary housing in the tsunami- stricken area had a significant increase in body weight.

Weight Gain in Survivors Living in Temporary Housing in the Tsunami-Stricken Area during the Recovery Phase following the Great East Japan Earthquake and Tsunami

PubMed Central

Yonekura, Yuki; Sasaki, Ryohei; Yokoyama, Yukari; Tanno, Kozo; Sakata, Kiyomi; Ogawa, Akira; Kobayashi, Seichiro; Yamamoto, Taro

2016-01-01

Introduction Survivors who lost their homes in the Great East Japan Earthquake and Tsunami were forced to live in difficult conditions in temporary housing several months after the disaster. Body weights of survivors living in temporary housing for a long period might increase due to changes in their life style and psychosocial state during the medium-term and long-term recovery phases. The aim of this study was to determine whether there were differences between body weight changes of people living in temporary housing and those not living in temporary housing in a tsunami-stricken area during the medium-term and long-term recovery phases. Materials and methods Health check-ups were performed about 7 months after the disaster (in 2011) and about 18 months after the disaster (in 2012) for people living in a tsunami-stricken area (n = 6,601, mean age = 62.3 y). We compared the changes in body weight in people living in temporary housing (TH group, n = 2,002) and those not living in temporary housing (NTH group, n = 4,599) using a multiple linear regression model. Results While there was no significant difference between body weights in the TH and NTH groups in the 2011 survey, there was a significant difference between the mean changes in body weight in both sexes. We found that the changes in body weight were significantly greater in the TH group than in the NTH group in both sexes. The partial regression coefficients of mean change in body weight were +0.52 kg (P-value < 0.001) in males in the TH group and +0.56 kg (P-value < 0.001) in females in the TH group (reference: NTH group). Conclusion Analysis after adjustment for life style, psychosocial factors and cardiovascular risk factors found that people living in temporary housing in the tsunami- stricken area had a significant increase in body weight. PMID:27907015

The Impact of Maternal Obesity and Excessive Gestational Weight Gain on Maternal and Infant Outcomes in Maine: Analysis of Pregnancy Risk Assessment Monitoring System Results from 2000 to 2010

PubMed Central

Sarton, Cheryl; Lichter, Erika

2016-01-01

The objective of this study is to understand the relationships between prepregnancy obesity and excessive gestational weight gain (GWG) and adverse maternal and fetal outcomes. Pregnancy risk assessment monitoring system (PRAMS) data from Maine for 2000–2010 were used to determine associations between demographic, socioeconomic, and health behavioral variables and maternal and infant outcomes. Multivariate logistic regression analysis was performed on the independent variables of age, race, smoking, previous live births, marital status, education, BMI, income, rurality, alcohol use, and GWG. Dependent variables included maternal hypertension, premature birth, birth weight, infant admission to the intensive care unit (ICU), and length of hospital stay of the infant. Excessive prepregnancy BMI and excessive GWG independently predicted maternal hypertension. A high prepregnancy BMI increased the risk of the infant being born prematurely, having a longer hospital stay, and having an excessive birth weight. Excessive GWG predicted a longer infant hospital stay and excessive birth weight. A low pregnancy BMI and a lower than recommended GWG were also associated with poor outcomes: prematurity, low birth weight, and an increased risk of the infant admitted to ICU. These findings support the importance of preconception care that promotes achievement of a healthy weight to enhance optimal reproductive outcomes. PMID:27747104

[Association between mothers' body mass index before pregnancy or weight gain during pregnancy and autism in children].

PubMed

Ling, Ziyu; Wang, Jianmin; Li, Xia; Zhong, Yan; Qin, Yuanyuan; Xie, Shengnan; Yang, Senbei; Zhang, Jing

2015-09-01

To explore the relationship between mothers' body mass index (BMI) before pregnancy or weight gain during pregnancy and autism in children. From 2013 to 2014, the 181 children with autism and 181 healthy children matched by sex and age from same area were included in this study. According to mothers' BMI before pregnancy, the selected cases were divided into 3 groups: low, normal and high group. Then 3 groups were divided into 3 subgroups based on mother' s weight gain during pregnancy: low, normal and high group, according to the recommendations of Institute of Medicine. Logistic regression analysis and χ(2) test were conducted with SPSS 18.0 software to analysis the relationship between mothers' BMI before pregnancy or weight gain during pregnancy and autism in children. The age and sex distributions of case group and control group were consistent (χ(2)=0.434, P>0.05). The mothers' BMI before pregnancy of case group was higher than that of control group (χ(2)=9.580, P<0.05) ,which was (21.28±3.80) kg/m(2) for case group and (19.87±2.83) kg/m(2) for control group. The proportion of cases in high BMI group (10.5%) was much higher than that in control group (2.8%) . The risk of children with autism in high BMI group was 3.7 times higher than that in normal BMI group (OR=3.71, 95% CI: 1.34-10.24). In normal BMI group, the proportion of mothers who had excessive weight gain during pregnancy was higher in case group (44.1%) than in control group (33.9%). In high BMI group, the proportion of mothers who had excessive weight gain was higher in case group (52.6%) than in control group (20.0%) . In normal BMI group (χ(2) =8.690, P<0.05) and high BMI group (χ(2)=4.775, P<0.05), the weight gain during pregnancy was associated with autism in children. Logistic regression analysis showed that mothers' BMI before pregnancy (unadjusted OR=1.89, 95% CI: 1.26-2.85, adjusted OR=1.52, 95% CI: 1.19-2.27) and weight gain during pregnancy were the risk factors for autism in children (unadjusted OR=1.63, 95% CI: 1.08-1.25, adjusted OR=1.64, 95% CI: 1.21-2.21). Overweight or obesity before pregnancy and excessive weight gain during pregnancy were associated with autism in children, suggesting that women who plan to be pregnant should pay attention to body weight control.

Low-molecular-weight heparin for prevention of placenta-mediated pregnancy complications: protocol for a systematic review and individual patient data meta-analysis (AFFIRM)

PubMed Central

2014-01-01

Background Placenta-mediated pregnancy complications include pre-eclampsia, late pregnancy loss, placental abruption, and the small-for-gestational age newborn. They are leading causes of maternal, fetal, and neonatal morbidity and mortality in developed nations. Women who have experienced these complications are at an elevated risk of recurrence in subsequent pregnancies. However, despite decades of research no effective strategies to prevent recurrence have been identified, until recently. We completed a pooled summary-based meta-analysis that strongly suggests that low-molecular-weight heparin reduces the risk of recurrent placenta-mediated complications. The proposed individual patient data meta-analysis builds on this successful collaboration. The project is called AFFIRM, An individual patient data meta-analysis oF low-molecular-weight heparin For prevention of placenta-medIated pRegnancy coMplications. Methods/Design We conducted a systematic review to identify randomized controlled trials with a low-molecular-weight heparin intervention for the prevention of recurrent placenta-mediated pregnancy complications. Investigators and statisticians representing eight trials met to discuss the outcomes and analysis plan for an individual patient data meta-analysis. An additional trial has since been added for a total of nine eligible trials. The primary analyses from the original trials will be replicated for quality assurance prior to recoding the data from each trial and combining it into a common dataset for analysis. Using the anonymized combined data we will conduct logistic regression and subgroup analyses aimed at identifying which women with previous pregnancy complications benefit most from treatment with low-molecular-weight heparin during pregnancy. Discussion The goal of the proposed individual patient data meta-analysis is a thorough estimation of treatment effects in patients with prior individual placenta-mediated pregnancy complications and exploration of which complications are specifically prevented by low-molecular-weight heparin. Systematic review registration PROSPERO (International Prospective Registry of Systematic Reviews) 23 December 2013, CRD42013006249 PMID:24969227

Body Weight Misperception and Its Association with Unhealthy Eating Behaviors among Adolescents in China.

PubMed

Yan, Hanyi; Wu, Yingru; Oniffrey, Theresa; Brinkley, Jason; Zhang, Rui; Zhang, Xinge; Wang, Yueqiao; Chen, Guoxun; Li, Rui; Moore, Justin B

2018-05-08

This study aims to examine associations between body weight misperception and eating behaviors among Chinese adolescents. Students ( N = 2641) from a middle school and a high school in Wuhan, China participated in a cross-sectional study in May 2016. A questionnaire based on the World Health Organization’s Global School-Based Student Health Survey was employed to assess responses. Self-reported data, including weight, height, body weight perception, and eating habits, were collected. Body Mass Index (BMI) for age z-score was calculated from self-reported height and weight using WHO AnthroPlus. We used descriptive, logistic regression analysis and a Kappa test to analyze the data using SPSS. Overall, 56.6% of participants did not correctly categorize their weight status; these were much more likely to be girls. Compared with the correctly-perceived group, those who underestimated their weight tended to report eating late at night, having dinners with family, and checking nutrition labels. In contrast, weight overestimating students were less likely to report eating late at night, having breakfasts with family, having dinners with family, and discussing nutrition topics over meals. Body weight misperception was associated with unhealthy eating behaviors among Chinese adolescents.

Dietary and psych predictors of weight loss after gastric bypass.

PubMed

Fox, Benjamin; Chen, Ellie; Suzo, Andrew; Jolles, Sally; Greenberg, Jacob A; Campos, Guilherme M; Voils, Corrine I; Funk, Luke M

2015-08-01

Identifying severely obese patients who will succeed after bariatric surgery remains challenging. Although numerous studies have attempted to identify preoperative patient characteristics associated with weight loss, the roles of many dietary and psychological characteristics are unclear. The purpose of this study was to examine preoperative dietary and psychological predictors of successful weight loss after bariatric surgery. This retrospective cohort study included all patients who underwent laparoscopic Roux-en-Y gastric bypass from September 2011-June 2013 at a single institution (n = 124). Patient demographics, comorbidities, dietary and psychological factors, and weight loss outcomes were extracted from the electronic medical record. Bivariate associations between these factors and successful weight loss (≥50% excess body weight) were examined. Factors significant at P ≤ 0.1 were included in a multivariate logistic regression model. On bivariate analysis, absence of either type 2 diabetes or hypertension, preoperative weight <270 lbs, no intentional past weight loss >50 lbs, no previous purging or family history of obesity, and no soda consumption preoperatively were associated with successful weight loss (P < 0.1). On multivariate analysis, successful weight loss was inversely associated with the presence of type 2 diabetes (odds ratio [OR], 0.22, 95% confidence interval [CI], 0.06-0.73), maximum intentional past weight loss >50 lbs (OR, 0.12 [95% CI, 0.04-0.43]), and decreasing soda consumption by >50% (OR, 0.27 [95% CI, 0.08-0.99]). Patients with type 2 diabetes mellitus, significant previous weight loss, and poor soda consumption habits are more likely to experience suboptimal weight loss after bariatric surgery. Additional preoperative counseling and close postoperative follow-up is warranted for these patients. Copyright © 2015 Elsevier Inc. All rights reserved.

Analysis of the streamflow-gaging station network in Ohio for effectiveness in providing regional streamflow information

USGS Publications Warehouse

Straub, D.E.

1998-01-01

The streamflow-gaging station network in Ohio was evaluated for its effectiveness in providing regional streamflow information. The analysis involved application of the principles of generalized least squares regression between streamflow and climatic and basin characteristics. Regression equations were developed for three flow characteristics: (1) the instantaneous peak flow with a 100-year recurrence interval (P100), (2) the mean annual flow (Qa), and (3) the 7-day, 10-year low flow (7Q10). All active and discontinued gaging stations with 5 or more years of unregulated-streamflow data with respect to each flow characteristic were used to develop the regression equations. The gaging-station network was evaluated for the current (1996) condition of the network and estimated conditions of various network strategies if an additional 5 and 20 years of streamflow data were collected. Any active or discontinued gaging station with (1) less than 5 years of unregulated-streamflow record, (2) previously defined basin and climatic characteristics, and (3) the potential for collection of more unregulated-streamflow record were included in the network strategies involving the additional 5 and 20 years of data. The network analysis involved use of the regression equations, in combination with location, period of record, and cost of operation, to determine the contribution of the data for each gaging station to regional streamflow information. The contribution of each gaging station was based on a cost-weighted reduction of the mean square error (average sampling-error variance) associated with each regional estimating equation. All gaging stations included in the network analysis were then ranked according to their contribution to the regional information for each flow characteristic. The predictive ability of the regression equations developed from the gaging station network could be improved for all three flow characteristics with the collection of additional streamflow data. The addition of new gaging stations to the network would result in an even greater improvement of the accuracy of the regional regression equations. Typically, continued data collection at stations with unregulated streamflow for all flow conditions that had less than 11 years of record with drainage areas smaller than 200 square miles contributed the largest cost-weighted reduction to the average sampling-error variance of the regional estimating equations. The results of the network analyses can be used to prioritize the continued operation of active gaging stations or the reactivation of discontinued gaging stations if the objective is to maximize the regional information content in the streamflow-gaging station network.

Breast-feeding and postpartum weight retention: a systematic review and meta-analysis.

PubMed

He, Xiujie; Zhu, Meng; Hu, Chuanlai; Tao, Xingyong; Li, Yingchun; Wang, Qiuwei; Liu, Yue

2015-12-01

Weight gained during pregnancy and postpartum weight retention might contribute to obesity in women of childbearing age. Whether breast-feeding (BF) may decrease postpartum weight retention (PPWR) is still controversial. The purpose of our systematic review and meta-analysis was to investigate the relationship between BF and PPWR. Three databases were systematically reviewed and the reference lists of relevant articles were checked. Meta-analysis was performed to quantify the pooled standardized mean differences (SMD) of BF on PPWR by using a random-effect model. Heterogeneity was tested using the χ 2 test and I 2 statistics. Publication bias was estimated from Egger's test (linear regression method) or Begg's test (rank correlation method). Among 349 search hits, eleven studies met the inclusion criteria for the meta-analysis. Seven studies were conducted in the USA, one in Brazil, one in France, one in Georgia and one in Croatia. Compared with formula-feeding, BF for 3 to ≤6 months seemed to have a negative influence on PPWR and if BF continued for >6 months had little or no influence on PPWR. In a subgroup meta-analysis, the results did not change substantially after the analysis had been classified by available confounding factors. There was no indication of a publication bias from the result of either Egger's test or Begg's test. Although the available evidence held belief that BF decreases PPWR, more robust studies are needed to reliably assess the impact of patterns and duration of BF on PPWR.

Economic injury level of the psyllid, Agonoscena pistaciae, on Pistachio, Pistacia vera cv. Ohadi.

PubMed

Reza Hassani, Mohammad; Nouri-Ganbalani, Gadir; Izadi, Hamzeh; Shojai, Mahmoud; Basirat, Mehdi

2009-01-01

The pistachio psylla, Agonoscena pistaciae Burckhardt and Lauterer (Hemiptera: Psyllidae) is a major pest of pistachio trees, Pistacia vera L. (Sapindalis: Anacardiaceae) throughout pistachio-producing regions in Iran. Different density levels of A. pistaciae nymphs were maintained on pistachio trees by different insecticide dosages to evaluate the relationship between nymph density and yield loss (weight of 1000 nuts). Psylla nymph densities were monitored weekly by counting nymphs on pistachio terminal leaflets. There was a significant reduction in weight of 1000 nuts as seasonal averages of nymphs increased. Regression analysis was used to determine the relationship between nymph density and weight of 1000 nuts. The economic injury levels varied as a function of market values, management costs, insecticide efficiency and yield loss rate and ranged from 7.7 to 30.7 nymphal days per terminal leaflet, based on weight of 1000 nuts.

Economic Injury Level of the Psyllid, Agonoscena pistaciae, on Pistachio, Pistacia vera cv. Ohadi

PubMed Central

Reza Hassani, Mohammad; Nouri-Ganbalani, Gadir; Izadi, Hamzeh; Basirat, Mehdi

2009-01-01

The pistachio psylla, Agonoscena pistaciae Burckhardt and Lauterer (Hemiptera: Psyllidae) is a major pest of pistachio trees, Pistacia vera L. (Sapindalis: Anacardiaceae) throughout pistachio-producing regions in Iran. Different density levels of A. pistaciae nymphs were maintained on pistachio trees by different insecticide dosages to evaluate the relationship between nymph density and yield loss (weight of 1000 nuts). Psylla nymph densities were monitored weekly by counting nymphs on pistachio terminal leaflets. There was a significant reduction in weight of 1000 nuts as seasonal averages of nymphs increased. Regression analysis was used to determine the relationship between nymph density and weight of 1000 nuts. The economic injury levels varied as a function of market values, management costs, insecticide efficiency and yield loss rate and ranged from 7.7 to 30.7 nymphal days per terminal leaflet, based on weight of 1000 nuts. PMID:19619034

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis

PubMed Central

Rahman, Md. Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D. W.; Labrique, Alain B.; Rashid, Mahbubur; Christian, Parul; West, Keith P.

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 − -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset. PMID:29261760

Identifying maternal and infant factors associated with newborn size in rural Bangladesh by partial least squares (PLS) regression analysis.

PubMed

Kabir, Alamgir; Rahman, Md Jahanur; Shamim, Abu Ahmed; Klemm, Rolf D W; Labrique, Alain B; Rashid, Mahbubur; Christian, Parul; West, Keith P

2017-01-01

Birth weight, length and circumferences of the head, chest and arm are key measures of newborn size and health in developing countries. We assessed maternal socio-demographic factors associated with multiple measures of newborn size in a large rural population in Bangladesh using partial least squares (PLS) regression method. PLS regression, combining features from principal component analysis and multiple linear regression, is a multivariate technique with an ability to handle multicollinearity while simultaneously handling multiple dependent variables. We analyzed maternal and infant data from singletons (n = 14,506) born during a double-masked, cluster-randomized, placebo-controlled maternal vitamin A or β-carotene supplementation trial in rural northwest Bangladesh. PLS regression results identified numerous maternal factors (parity, age, early pregnancy MUAC, living standard index, years of education, number of antenatal care visits, preterm delivery and infant sex) significantly (p<0.001) associated with newborn size. Among them, preterm delivery had the largest negative influence on newborn size (Standardized β = -0.29 - -0.19; p<0.001). Scatter plots of the scores of first two PLS components also revealed an interaction between newborn sex and preterm delivery on birth size. PLS regression was found to be more parsimonious than both ordinary least squares regression and principal component regression. It also provided more stable estimates than the ordinary least squares regression and provided the effect measure of the covariates with greater accuracy as it accounts for the correlation among the covariates and outcomes. Therefore, PLS regression is recommended when either there are multiple outcome measurements in the same study, or the covariates are correlated, or both situations exist in a dataset.

[Relationship between body weight status in early adulthood and body weight change at middle age in adults and type 2 diabetes mellitus].

PubMed

Zhou, Long; Zhao, Liancheng; Li, Ying; Guo, Min; Wu, Yangfeng

2016-03-01

To explore the relationship between weight status in early adulthood and body weight change at middle age in adults and type 2 diabetes mellitus (T2DM). The data of 14 population samples from China Multicenter Collaborative Study of Cardiovascular Epidemiology conducted in 1998 were used. Approximately 1 000 men and women in each sample were surveyed for cardiovascular disease risk factors, including body weight at age 25 years. The body mass index (BMI) at the age 25 years was calculated. The association between body weight in early adulthood and body weight change at middle age and T2DM was examined by using logistic regression model. The incidence of T2DM in low weight group (BMI<18.5 kg/m(2)), normal weight group (BMI: 18.5-23.9 kg/m(2)), overweight group (BMI: 24.0-27.9 kg/m(2)) and obese group (BMI:≥28.0 kg/m(2)) at 25 years old were 2.4%(30/1263), 2.8%(266/9562), 4.0%(70/1739) and 6.4% (7/110), respectively (P value for trend<0.01). The incidence of T2DM for adults with weight change <-7.5 kg, -7.5--2.6 kg, -2.5-2.5 kg, 2.6-7.5 kg, 7.6-12.5 kg and >12.5 kg at middle age were 2.5% (18/712), 1.3%(21/1629), 2.1%(48/2330), 2.3%(59/2585), 3.7%(94/2518), and 4.6% (133/2900) respectively. (P value for trend <0.01), Multivariate logistic regression analysis showed that overweight and obesity at age 25 years and subsequent weight gain were positively correlated with T2DM after adjusted other risk factors (all P values for trend <0.01). Overweight and obesity in early adulthood and weight gain at middle age were both independently associated with the increased risk of T2DM in middle-aged men and women.

Comparative effectiveness of a portion-controlled meal replacement program for weight loss in adults with and without diabetes/high blood sugar.

PubMed

Coleman, C D; Kiel, J R; Mitola, A H; Arterburn, L M

2017-07-10

Individuals with type 2 diabetes (DM2) may be less successful at achieving therapeutic weight loss than their counterparts without diabetes. This study compares weight loss in a cohort of adults with DM2 or high blood sugar (D/HBS) to a cohort of adults without D/HBS. All were overweight/obese and following a reduced or low-calorie commercial weight-loss program incorporating meal replacements (MRs) and one-on-one behavioral support. Demographic, weight, body composition, anthropometric, pulse and blood pressure data were collected as part of systematic retrospective chart review studies. Differences between cohorts by D/HBS status were analyzed using Mann-Whitney U-tests and mixed model regression. A total of 816 charts were included (125 with self-reported D/HBS). The cohort with D/HBS had more males (40.8 vs 25.6%), higher BMI (39.0 vs 36.3 kg m - 2 ) and was older (56 vs 48 years). Among clients continuing on program, the cohorts with and without D/HBS lost, on average, 5.6 vs 5.8 kg (NS) (5.0 vs 5.6%; P=0.005) of baseline weight at 4 weeks, 11.0 vs 11.6 kg (NS) (9.9 vs 11.1%; P=0.027) at 12 weeks and 16.3 vs 17.1 kg (13.9 vs 15.7%; NS) at 24 weeks, respectively. In a mixed model regression controlling for baseline weight, gender and meal plan, and an intention-to-treat analysis, there was no significant difference in weight loss between the cohorts at any time point. Over 70% in both cohorts lost ⩾5% of their baseline weight by the final visit on their originally assigned meal plan. Both cohorts had significant reductions from baseline in body fat, blood pressure, pulse and abdominal circumference. Adults who were overweight/obese and with D/HBS following a commercial weight-loss program incorporating MRs and one-on-one behavioral support achieved therapeutic weight loss. The program was equally effective for weight loss and reductions in cardiometabolic risk factors among adults with and without D/HBS.

Determinants of amikacin first peak concentration in critically ill patients.

PubMed

Boidin, Clément; Jenck, Sophie; Bourguignon, Laurent; Torkmani, Sejad; Roussey-Jean, Aurore; Ledochowski, Stanislas; Marry, Lucie; Ammenouche, Nacim; Dupont, Hervé; Marçon, Frédéric; Allaouchiche, Bernard; Bohé, Julien; Lepape, Alain; Goutelle, Sylvain; Friggeri, Arnaud

2018-04-16

Amikacin antimicrobial effect has been correlated with the ratio of the peak concentration (C max ) to the minimum inhibitory concentration. A target C max ≥ 60-80 mg/L has been suggested. It has been shown that such target is not achieved in a large proportion of critically ill patients in intensive care units. A retrospective analysis was performed to examine the determinants of C max ≥ 80 mg/L on the first peak in 339 critically ill patients treated by amikacin. The influence of available variables on C max target attainment was analyzed using a classification and regression tree (CART) and logistic regression. Mean C max in the 339 patients was 73.0 ± 23.9 mg/L, with a target attainment rate (TAR, C max ≥ 80 mg/L) of 37.5%. In CART analysis, the strongest predictor of amikacin target peak attainment was dose per kilogram of lean body weight (dose/LBW). TAR was 60.1% in patients with dose/LBW ≥ 37.8 vs. 19.9% in patients with lower dose/LBW (OR = 6.0 (95% CI: 3.6-10.2)). Renal function was a secondary predictor of C max . Logistic regression analysis identified dose per kilogram of ideal body weight (OR = 1.13 (95% CI: 1.09-1.17)) and creatinine clearance (OR = 0.993 (95% CI: 0.988-0.998)) as predictors of target peak achievement. Based on our results, an amikacin dose ≥ 37.8 mg/kg of LBW should be used to optimize the attainment of C max ≥ 80 mg/L after the first dose in critically ill patients. An even higher dose may be necessary in patients with normal renal function. © 2018 Société Française de Pharmacologie et de Thérapeutique.

A computer tool for a minimax criterion in binary response and heteroscedastic simple linear regression models.

PubMed

Casero-Alonso, V; López-Fidalgo, J; Torsney, B

2017-01-01

Binary response models are used in many real applications. For these models the Fisher information matrix (FIM) is proportional to the FIM of a weighted simple linear regression model. The same is also true when the weight function has a finite integral. Thus, optimal designs for one binary model are also optimal for the corresponding weighted linear regression model. The main objective of this paper is to provide a tool for the construction of MV-optimal designs, minimizing the maximum of the variances of the estimates, for a general design space. MV-optimality is a potentially difficult criterion because of its nondifferentiability at equal variance designs. A methodology for obtaining MV-optimal designs where the design space is a compact interval [a, b] will be given for several standard weight functions. The methodology will allow us to build a user-friendly computer tool based on Mathematica to compute MV-optimal designs. Some illustrative examples will show a representation of MV-optimal designs in the Euclidean plane, taking a and b as the axes. The applet will be explained using two relevant models. In the first one the case of a weighted linear regression model is considered, where the weight function is directly chosen from a typical family. In the second example a binary response model is assumed, where the probability of the outcome is given by a typical probability distribution. Practitioners can use the provided applet to identify the solution and to know the exact support points and design weights. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Application of multi-criteria decision-making to risk prioritisation in tidal energy developments

NASA Astrophysics Data System (ADS)

Kolios, Athanasios; Read, George; Ioannou, Anastasia

2016-01-01

This paper presents an analytical multi-criterion analysis for the prioritisation of risks for the development of tidal energy projects. After a basic identification of risks throughout the project and relevant stakeholders in the UK, classified through a political, economic, social, technological, legal and environmental analysis, relevant questionnaires provided scores to each risk and corresponding weights for each of the different sectors. Employing an extended technique for order of preference by similarity to ideal solution as well as the weighted sum method based on the data obtained, the risks identified are ranked based on their criticality, drawing attention of the industry in mitigating the ones scoring higher. Both methods were modified to take averages at different stages of the analysis in order to observe the effects on the final risk ranking. A sensitivity analysis of the results was also carried out with regard to the weighting factors given to the perceived expertise of participants, with different results being obtained whether a linear, squared or square root regression is used. Results of the study show that academics and industry have conflicting opinions with regard to the perception of the most critical risks.

Weighted linear regression using D2H and D2 as the independent variables

Treesearch

Hans T. Schreuder; Michael S. Williams

1998-01-01

Several error structures for weighted regression equations used for predicting volume were examined for 2 large data sets of felled and standing loblolly pine trees (Pinus taeda L.). The generally accepted model with variance of error proportional to the value of the covariate squared ( D2H = diameter squared times height or D...

Species identification and vitamin A level in lutjanid fish implicated in vitamin A poisoning.

PubMed

Hwang, Deng-Fwu; Lu, Chi-Huan; Lin, Wen-Feng

2010-04-01

One outbreak of food poisoning associated with ingestion of the liver of a large lutjanid fish was investigated in this study. The symptoms in three patients primarily included headache, nausea, vomiting, fever, vertigo, and visual disorientation and later included peeling of the skin. The species of fish implicated in this incident was Etelis carbunculus (family Lutjanidae) as determined by direct sequence analysis and PCR plus restriction fragment length polymorphism analysis for detection of the cytochrome b gene. Subsequently, several specimens of E. carbunculus of different body weights were collected, and the level of vitamin A in the muscle and liver was determined by high-performance liquid chromatography. The average level of vitamin A in E. carbunculus muscle was 12 +/- 2 IU/g and that in the liver was 9,844 +/- 7,812 IU/g. Regression models indicate that E. carbunculus with higher body weight and liver weight will have higher levels of vitamin A levels in the liver.

Personality characteristics as predictors of underreporting of energy intake on 24-hour dietary recall interviews.

PubMed

Novotny, Janet A; Rumpler, William V; Riddick, Howard; Hebert, James R; Rhodes, Donna; Judd, Joseph T; Baer, David J; McDowell, Margaret; Briefel, Ronette

2003-09-01

To identify characteristics associated with misreporting of energy intake during 24-hour dietary recalls (24 HR). Ninety-eight subjects were administered two 24 HRs. Energy expenditure was determined by doubly labeled water (44 subjects) or intake balance (54 subjects). Data on subjects' physical, lifestyle, and psychosocial characteristics were also collected. Subjects/setting At the Beltsville Human Nutrition Research Center 52 women and 46 men were administered 24HR and completed lifestyle and personality questionnaires and a memory test. Physical characteristics such as weight, percent body fat, and total energy expenditure were measured. Statistical analysis The influences of subject parameters on energy misreporting were assessed by linear regression and Pearson product-moment correlation analysis for continuous variables and by ANOVA for discrete variables. Stepwise regression was used to identify key factors in underreporting. Factors particularly important in predicting underreporting of energy intake include factors indicating dissatisfaction with body image; for example, a 398 kcal/day underreport in subjects attempting weight loss during the past year with a nearly 500 kcal/day underreport in women. Overall, women underreported by 393 kcal/day relative to men and women evinced a social desirability bias amounting to a 26 kcal underreport for each point on the social desirability scale. Gender differences also were evident in the effect of percent body fat (with men underreporting about 16 kcal/day/percent body fat) and in departure from self-reported ideal body weight (with women underreporting about 21 kcal/day/kg). Body image and fatness are key factors on which health professionals should focus when seeking predictors of underreporting of dietary intake. Dietary interviews must be conducted to minimize bias related to subjects' tendencies to win approval and avoid censure by the interviewer. In addition, dissatisfaction with body image may lead to underestimation of food intake, therefore reducing likelihood of success in weight loss. Thus, health care professionals involved in weight loss counseling may achieve better success if treatment includes generating a more positive body image.

Operational Weight Estimations of Commercial Jet Transport Aircraft

NASA Technical Reports Server (NTRS)

Anderson, Joseph L.

1972-01-01

In evaluating current or proposed commercial transport airplanes, there has not been available a ready means to determine weights so as to compare airplanes within this particular class. This paper describes the development of and presents such comparative tools. The major design characteristics of current American jet transport airplanes were collected, and these data were correlated by means of regression analysis to develop weight relationships for these airplanes as functions of their operational requirements. The characteristics for 23 airplanes were assembled and examined in terms of the effects of the number of people carried, the cargo load, and the operating range. These airplane characteristics were correlated for the airplanes as one of three subclasses, namely the small, twin-engine jet transport, the conventional three- and four-engine jets, and the new wide-body jets.

Prospective cohort study of factors influencing the relative weights of the placenta and the newborn infant.

PubMed

Williams, L A; Evans, S F; Newnham, J P

1997-06-28

To determine the demographic, environmental, and medical factors that influence the relative weights of the newborn infant and the placenta and compare this ratio with other factors known to predispose to adult ill health. Prospective cohort study. The tertiary referral centre for perinatal care in Perth, Western Australia. 2507 pregnant women who delivered a single live infant at term. Placental weight, birth weight, and the ratio of placental weight to birth weight. By multiple regression analysis the placental weight to birthweight ratio was significantly and positively associated with gestational age, female sex, Asian parentage, increasing maternal body mass index, increased maternal weight at booking, lower socioeconomic status, maternal anaemia, and increasing number of cigarettes smoked daily. There were no consistent relations between the placental weight to birthweight ratio and measures of newborn size. The ratio of placental weight to birth weight is not an accurate marker of fetal growth. In its role as a predictor of adult disease the ratio may be acting as a surrogate for other factors which are already known to influence health and may act before or after birth. Determining the role that relative growth rates of the fetus and placenta have in predisposing to adult disease requires prospective study to account for the many confounding variables which complicate this hypothesis.

Trends and determinants of weight gains among OECD countries: an ecological study.

PubMed

Nghiem, S; Vu, X-B; Barnett, A

2018-06-01

Obesity has become a global issue with abundant evidence to indicate that the prevalence of obesity in many nations has increased over time. The literature also reports a strong association between obesity and economic development, but the trend that obesity growth rates may converge over time has not been examined. We propose a conceptual framework and conduct an ecological analysis on the relationship between economic development and weight gain. We also test the hypothesis that weight gain converges among countries over time and examine determinants of weight gains. This is a longitudinal study of 34 Organisation for Economic Cooperation and Development (OECD) countries in the years 1980-2008 using publicly available data. We apply a dynamic economic growth model to test the hypothesis that the rate of weight gains across countries may converge over time. We also investigate the determinants of weight gains using a longitudinal regression tree analysis. We do not find evidence that the growth rates of body weight across countries converged for all countries. However, there were groups of countries in which the growth rates of body weight converge, with five groups for males and seven groups for females. The predicted growth rates of body weight peak when gross domestic product (GDP) per capita reaches US$47,000 for males and US$37,000 for females in OECD countries. National levels of consumption of sugar, fat and alcohol were the most important contributors to national weight gains. National weight gains follow an inverse U-shape curve with economic development. Excessive calorie intake is the main contributor to weight gains. Copyright © 2018 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Prostate weight: an independent predictor for positive surgical margins during robotic-assisted laparoscopic radical prostatectomy.

PubMed

Msezane, Lambda P; Gofrit, Ofer N; Lin, Shang; Shalhav, Arieh L; Zagaja, Gregory P; Zorn, Kevin C

2007-10-01

Pre-operative prediction of pathological stage represents the cornerstone of prostate cancer management. Patient counseling is routinely based on pre-operative PSA, Gleason score and clinical stage. In this study, we evaluated whether prostate weight (PW) is an independent predictor of extracapsular extension (ECE) and positive surgical margin (PSM). Between February 2003 and November 2006, 709 men underwent robotic-assisted laparoscopic radical prostatectomy (RLRP). Pre-operative parameters (patient age, pre-operative PSA, biopsy Gleason score, clinical stage) as well as pathological data (prostate weight, pathological stage) were prospectively gathered after internal-review board (IRB) approval. Evaluation of the influence of these variables on ECE and PSM outcomes were assessed using both univariate and multivariate logistic regression analysis. Mean overall patient age, pre-operative PSA and PW were 59.6 years, 6.5 ng/ml and 52.9 g (range 5.5 g-198.7 g), respectively. Of the 393, 209 and 107 men with PW < 50 g, 50 g-< 70 g and < 70 g, ECE was observed in 20.1%, 15.3% and 9.3%, respectively (p = 0.015). In the same patient cohorts, PSM was observed in 25.4%, 14.4% and 7.5%, respectively (p < 0.001). In a multivariate logistic regression analysis, PW, in addition to pre-operative PSA, biopsy Gleason score and clinical stage, was an independent risk factor for ECE (p < 0.001). Similarly, in multi-variate analysis, PW was observed to be a risk factor for PSM (p < 0.001). PW is an independent predictor of both ECE and PSM, with an inverse relationship having been demonstrated between both variables. PW should be considered when counseling patients with prostate cancer treatment.

Bark yields of 11-year-old loblolly pine as influenced by competition control and fertilization

Treesearch

Allan E. Tiarks; James D. Haywood

1992-01-01

Bolts cut from 11-year-old loblolly pines (Pinus taeda L.) were measured to determine the effects of applications of fertilizer and competition control treatments on the amount of pine bark produced. Bark thickness at breast height was not significantly affected by any of the treatments. Regression analysis showed that the dry weight of bark per unit...

Methods for estimating annual exceedance probability discharges for streams in Arkansas, based on data through water year 2013

USGS Publications Warehouse

Wagner, Daniel M.; Krieger, Joshua D.; Veilleux, Andrea G.

2016-08-04

In 2013, the U.S. Geological Survey initiated a study to update regional skew, annual exceedance probability discharges, and regional regression equations used to estimate annual exceedance probability discharges for ungaged locations on streams in the study area with the use of recent geospatial data, new analytical methods, and available annual peak-discharge data through the 2013 water year. An analysis of regional skew using Bayesian weighted least-squares/Bayesian generalized-least squares regression was performed for Arkansas, Louisiana, and parts of Missouri and Oklahoma. The newly developed constant regional skew of -0.17 was used in the computation of annual exceedance probability discharges for 281 streamgages used in the regional regression analysis. Based on analysis of covariance, four flood regions were identified for use in the generation of regional regression models. Thirty-nine basin characteristics were considered as potential explanatory variables, and ordinary least-squares regression techniques were used to determine the optimum combinations of basin characteristics for each of the four regions. Basin characteristics in candidate models were evaluated based on multicollinearity with other basin characteristics (variance inflation factor < 2.5) and statistical significance at the 95-percent confidence level (p ≤ 0.05). Generalized least-squares regression was used to develop the final regression models for each flood region. Average standard errors of prediction of the generalized least-squares models ranged from 32.76 to 59.53 percent, with the largest range in flood region D. Pseudo coefficients of determination of the generalized least-squares models ranged from 90.29 to 97.28 percent, with the largest range also in flood region D. The regional regression equations apply only to locations on streams in Arkansas where annual peak discharges are not substantially affected by regulation, diversion, channelization, backwater, or urbanization. The applicability and accuracy of the regional regression equations depend on the basin characteristics measured for an ungaged location on a stream being within range of those used to develop the equations.

Prevalence and determinants of overweight and obesity in old age in Germany.

PubMed

Hajek, André; Lehnert, Thomas; Ernst, Annette; Lange, Carolin; Wiese, Birgitt; Prokein, Jana; Weyerer, Siegfried; Werle, Jochen; Pentzek, Michael; Fuchs, Angela; Luck, Tobias; Bickel, Horst; Mösch, Edelgard; Heser, Kathrin; Wagner, Michael; Maier, Wolfgang; Scherer, Martin; Riedel-Heller, Steffi G; König, Hans-Helmut

2015-07-14

Mean body weight gradually increases with age. Yet, little data exists on the prevalence of excess weight in populations aged 80 years or older. Moreover, little is known about predictors of overweight and obesity in old age. Thus, the purpose of this study was: To present data on the prevalence of excess weight in old age in Germany, to investigate predictors of excess weight in a cross-sectional approach and to examine factors affecting excess weight in a longitudinal approach. Subjects consisted of 1,882 individuals aged 79 years or older. The course of excess weight was observed over 3 years. Excess weight was defined as follows: Overweight (25 kg/m(2) ≤ BMI < 30 kg/m(2)) and obesity (BMI ≥ 30 kg/m(2)). We used fixed effects regressions to estimate effects of time dependent variables on BMI, and overweight or obesity, respectively. The majority was overweight (40.0%) or obese (13.7%). Cross-sectional regressions revealed that BMI was positively associated with younger age, severe walking impairments and negatively associated with cognitive impairments. Excess weight was positively associated with younger age, elementary education, walking impairments and physical inactivity, while excess weight was negatively associated with cognitive impairment. Longitudinal regressions showed that age and severely impaired walking disabilities reduced BMI. The probability of transitions to excess weight decreased considerably with older age and occurrence of severe walking impairments (overweight). Marked differences between predictors in cross- and longitudinal setting exist, underlining the complex nature of excess weight in old age.

[Analysis of the influence factors of school-age children's refractive status].

PubMed

Chen, Z G; Chen, M C; Zhang, J Y; Cai, D Q; Wang, Q; Lin, S S; Chen, J W; Zhong, H L

2016-11-11

Objective: To analyze the influence of the eye biological parameters, height, and weight on the school-age children's refractive status. Methods: Cross-sectional study. A total of 1 656 children (1 656 eyes), aged from 7 to 14 years, were selected from 8 schools in Wenzhou during June 2012 and June 2013. The height and weight of each child were measured, and the body mass index (BMI) was calculated. The eye biological parameters, including axial length (AL), corneal power (C=1/CR), anterior chamber depth (ACD), and white to white (WTW), were measured by IOLMaster (version 5.0, Carl Zeiss, Germany), and the AL/CR was calculated. Refraction was measured by fast cycloplegic retinoscopy, and the spherical equivalent (SE) was calculated. Only right eyes were included in the analysis. SPSS16.0 was used to analyze the data. The correlations of the equivalent spherical power, the eye biological parameters, height, weight, and BMI were evaluated. Linear regression analysis was used for the SE, AL, and AL/CR. Results: The prevalence of myopia in 7- to 14-year-old school-age children was 50.2% on the average, 48.4% in boys, and 51.7% in girls. The average SE was (-1.07±1.74) D. With adjustment of the age, gender, urban and rural areas, there was an association between the SE and AL, AL/CR, ACD, height and weight. The correlation coefficient was -0.663, -0.730, -0.416, -0.365, and -0.281, respectively ( P< 0.05). There was no significant correlation between the SE and WTW, corneal power and BMI. Regarding the different refractive statuses, there was a stronger correlation between the SE and AL, AL/CR in children with hyperopia, moderate myopia or high myopia than those with emmetropia or mild myopia ( P< 0.01). In the older children, the correlation between the SE and AL, AL/CR was stronger. Linear regression analysis showed SE= 26.55-9.11·AL/CR and 23.0-1.02·AL. Conclusions: There was an association between the SE and AL, AL/CR, ACD, height and weight in school-age children. In children with hyperopia, moderate myopia, high myopia or at an older age, the correlation was more significant between the SE and AL, AL/CR. (Chin J Ophthalmol, 2016, 52:831-835) .

Bias and uncertainty in regression-calibrated models of groundwater flow in heterogeneous media

USGS Publications Warehouse

Cooley, R.L.; Christensen, S.

2006-01-01

Groundwater models need to account for detailed but generally unknown spatial variability (heterogeneity) of the hydrogeologic model inputs. To address this problem we replace the large, m-dimensional stochastic vector ?? that reflects both small and large scales of heterogeneity in the inputs by a lumped or smoothed m-dimensional approximation ????*, where ?? is an interpolation matrix and ??* is a stochastic vector of parameters. Vector ??* has small enough dimension to allow its estimation with the available data. The consequence of the replacement is that model function f(????*) written in terms of the approximate inputs is in error with respect to the same model function written in terms of ??, ??,f(??), which is assumed to be nearly exact. The difference f(??) - f(????*), termed model error, is spatially correlated, generates prediction biases, and causes standard confidence and prediction intervals to be too small. Model error is accounted for in the weighted nonlinear regression methodology developed to estimate ??* and assess model uncertainties by incorporating the second-moment matrix of the model errors into the weight matrix. Techniques developed by statisticians to analyze classical nonlinear regression methods are extended to analyze the revised method. The analysis develops analytical expressions for bias terms reflecting the interaction of model nonlinearity and model error, for correction factors needed to adjust the sizes of confidence and prediction intervals for this interaction, and for correction factors needed to adjust the sizes of confidence and prediction intervals for possible use of a diagonal weight matrix in place of the correct one. If terms expressing the degree of intrinsic nonlinearity for f(??) and f(????*) are small, then most of the biases are small and the correction factors are reduced in magnitude. Biases, correction factors, and confidence and prediction intervals were obtained for a test problem for which model error is large to test robustness of the methodology. Numerical results conform with the theoretical analysis. ?? 2005 Elsevier Ltd. All rights reserved.

Maintenance energy requirements in miniature colony dogs.

PubMed

Serisier, S; Weber, M; Feugier, A; Fardet, M-O; Garnier, F; Biourge, V; German, A J

2013-05-01

There are numerous reports of maintenance energy requirements (MER) in dogs, but little information is available about energy requirements of miniature dog breeds. In this prospective, observational, cohort study, we aimed to determine MER in dogs from a number of miniature breeds and to determine which factors were associated with it. Forty-two dogs participated in the study. MER was calculated by determining daily energy intake (EI) during a period of 196 days (28-359 days) when body weight did not change significantly (e.g. ±2% in 12 weeks). Estimated median MER was 473 kJ/kg(0.75) /day (285-766 kJ/kg(0.75) /day), that is, median 113 kcal/kg(0.75) /day (68-183 kcal/kg(0.75) /day). In the obese dogs that lost weight, median MER after weight loss was completed was 360 kJ/kg(0.75) /day (285-515 kJ/kg(0.75) /day), that is, 86 kcal/kg(0.75) /day, (68-123 kcal/kg(0.75) /day). Simple linear regression analysis suggested that three breeds (e.g. Chihuahua, p = 0.002; Yorkshire terrier, p = 0.039; dachshund, p = 0.035) had an effect on MER. In addition to breed, simple linear regression revealed that neuter status (p = 0.079) and having previously been overweight (p = 0.002) were also of significance. However, with multiple linear regression analysis, only previous overweight status (MER less in dogs previously overweight p = 0.008) and breed (MER greater in Yorkshire terriers [p = 0.029] and less in Chihuahuas [p = 0.089]) remained in the final model. This study is the first to estimate MER in dogs of miniature breeds. Although further information from pet dogs is now needed, the current work will be useful for setting energy and nutrient requirement in such dogs for the future. Journal of Animal Physiology and Animal Nutrition © 2013 Blackwell Verlag GmbH.

Neural network uncertainty assessment using Bayesian statistics: a remote sensing application

NASA Technical Reports Server (NTRS)

Aires, F.; Prigent, C.; Rossow, W. B.

2004-01-01

Neural network (NN) techniques have proved successful for many regression problems, in particular for remote sensing; however, uncertainty estimates are rarely provided. In this article, a Bayesian technique to evaluate uncertainties of the NN parameters (i.e., synaptic weights) is first presented. In contrast to more traditional approaches based on point estimation of the NN weights, we assess uncertainties on such estimates to monitor the robustness of the NN model. These theoretical developments are illustrated by applying them to the problem of retrieving surface skin temperature, microwave surface emissivities, and integrated water vapor content from a combined analysis of satellite microwave and infrared observations over land. The weight uncertainty estimates are then used to compute analytically the uncertainties in the network outputs (i.e., error bars and correlation structure of these errors). Such quantities are very important for evaluating any application of an NN model. The uncertainties on the NN Jacobians are then considered in the third part of this article. Used for regression fitting, NN models can be used effectively to represent highly nonlinear, multivariate functions. In this situation, most emphasis is put on estimating the output errors, but almost no attention has been given to errors associated with the internal structure of the regression model. The complex structure of dependency inside the NN is the essence of the model, and assessing its quality, coherency, and physical character makes all the difference between a blackbox model with small output errors and a reliable, robust, and physically coherent model. Such dependency structures are described to the first order by the NN Jacobians: they indicate the sensitivity of one output with respect to the inputs of the model for given input data. We use a Monte Carlo integration procedure to estimate the robustness of the NN Jacobians. A regularization strategy based on principal component analysis is proposed to suppress the multicollinearities in order to make these Jacobians robust and physically meaningful.

The transverse diameter of the chest on routine radiographs reliably estimates gestational age and weight in premature infants.

PubMed

Dietz, Kelly R; Zhang, Lei; Seidel, Frank G

2015-08-01

Prior to digital radiography it was possible for a radiologist to easily estimate the size of a patient on an analog film. Because variable magnification may be applied at the time of processing an image, it is now more difficult to visually estimate an infant's size on the monitor. Since gestational age and weight significantly impact the differential diagnosis of neonatal diseases and determine the expected size of kidneys or appearance of the brain by MRI or US, this information is useful to a pediatric radiologist. Although this information may be present in the electronic medical record, it is frequently not readily available to the pediatric radiologist at the time of image interpretation. To determine if there was a correlation between gestational age and weight of a premature infant with their transverse chest diameter (rib to rib) on admission chest radiographs. This retrospective study was approved by the institutional review board, which waived informed consent. The maximum transverse chest diameter outer rib to outer rib was measured on admission portable chest radiographs of 464 patients admitted to the neonatal intensive care unit (NICU) during the 2010 calendar year. Regression analysis was used to investigate the association between chest diameter and gestational age/birth weight. Quadratic term of chest diameter was used in the regression model. Chest diameter was statistically significantly associated with both gestational age (P < 0.0001) and birth weight (P < 0.0001). An infant's gestational age and birth weight can be reliably estimated by comparing a simple measurement of the transverse chest diameter on digital chest radiograph with the tables and graphs in our study.

Survey on eating disorder-related thoughts, behaviors, and their relationship with food intake and nutritional status in female high school students in Taiwan.

PubMed

Chang, Yu-Jhen; Lin, Wei; Wong, Yueching

2011-02-01

Eating disorders are now a global health problem for adolescents and young female adults. The level of eating disorders among young female adults is growing in Asian countries. Therefore, the purpose of this study was to investigate body image, weight concerns, eating attitudes, dietary intake, and nutritional status related to eating disorders of female high school students in Taiwan. A total of 1605 female high school students participated in this study. The written questionnaire included respondents' demographics and weight concerns, the Eating Attitudes Test-26 (EAT-26), and 24-hour dietary recall. Blood chemistry data were also collected. The data were analyzed using a Student t test, χ(2) analysis, and logistic regression. Disturbed eating attitudes and behaviors were found in 17.11% of participants (measured by an EAT-26 score ≥20). Logistic regression analyses showed that disturbed eating attitudes/behaviors were significantly associated with overestimation of body weight, unrealistic body weight goal, dissatisfaction with body weight, and weight loss experiences. The reported intakes of energy, protein, carbohydrate, zinc, and vitamins B6 and B12 were significantly lower in participants with disturbed eating patterns than in participants without disturbance issues. Conversely, participants with disturbed eating patterns had higher dietary and crude fiber intake than participants without disturbed eating issues. The percentage of participants with abnormal values of total iron-binding capacity and serum iron was significantly higher in those with disturbed eating patterns than in those without disturbed eating patterns. Disturbed eating attitudes/behaviors exist among female adolescents in Taiwan, and these behaviors jeopardize their nutritional status. The possibility of using the EAT-26 as a reference to predict the quality and quantity of food intake among female adolescents is worthy of further study.

Longitudinal study of the socio-demographic determinants of changes in body weight and waist circumference in a multi-ethnic Asian population.

PubMed

Ong, S K; Fong, C W; Ma, S; Lee, J; Heng, D; Deurenberg-Yap, M; Low, Y-L; Tan, M; Lim, W-Y; Tai, E S

2009-11-01

To examine the changes in weight and waist circumference of adult Singaporeans between 1998 and 2005-2007, and the associations of these changes with demographic and socio-economic factors. A prospective study, which followed up participants aged 18-69 years from the 1998 National Health Survey. Analysis was performed on data from 2483 individuals (53% of original sample) who returned for follow-up in 2005-2007. Body weight and waist circumference were measured both at baseline and follow-up. Logistic regression was used to examine factors associated with being overweight and obese at baseline. Linear regression was used to examine changes in weight and waist circumference over time. The variables examined were age, gender, ethnicity, marital status, educational level, housing and employment status, smoking, alcohol consumption and sports activities. Mean weight for the population increased over the follow-up period by 1.48 kg (s.d.=4.95) and mean waist circumference increased by 3.32 cm (s.d.=7.92). Cross-sectionally, those who were overweight or obese were more likely to be Malays or Indians, married, homemakers and have lower educational level. Prospectively, individuals who gained the most weight were younger, more likely to be ethnic minority groups and have the lowest body mass index (BMI) at baseline. They also appeared to be of higher socio-economic status (SES) based on housing type. These associations were statistically significant even after adjusting for other variables. Obesity prevention should start early in the younger age. Preventive programs need to reach out to Malay and Indian ethnic groups and those with higher SES. These findings should be used in designing messaging of preventive strategies.

Effect of a Modest Weight Loss in Normalizing Blood Pressure in Obese Subjects on Antihypertensive Drugs.

PubMed

Gilardini, Luisa; Redaelli, Gabriella; Croci, Marina; Conti, Antonio; Pasqualinotto, Lucia; Invitti, Cecilia

2016-01-01

To assess the effect of a lifestyle intervention in lowering/normalizing blood pressure (BP) levels in hypertensive (controlled or not) obese patients. In this prospective observational study, 490 obese hypertensive patients, 389 controlled (BP < 140/90 mm Hg; CH) and 101 uncontrolled (BP ≥ 140/90 mm Hg; UH) attended a 3-month lifestyle intervention. Before and after the intervention we assessed weight, waist circumference, fat mass, BP, metabolic and renal variables, and physical activity. A multivariate regression model was used to determine the predictors of BP changes. 18.9% of CH and 20.0% of UH were on ≥ 3 antihypertensive drugs. Weight change (average -4.9 ± 2.7%) was independent of the antihypertensive drugs employed. Systolic BP (SBP) decreased by 23 mm Hg and diastolic BP (DBP) by 9 mm Hg, in patients with UH most of whom (89%) normalized BP levels (in 49% after a weight loss < 5%). Age, gender, whole and central obesity, concomitance of type 2 diabetes, chronic renal disease, physical activity intensification, and pharmacological therapy did not affect BP lowering. In the regression analysis with SBP change as dependent variable, weight reduction (β = 0.523, p = 0.005) and group (UH vs. CH, β = -19.40, p = 0.0005) remained associated with SBP reduction. When DBP change was entered as dependent variable, baseline uric acid remained associated with DBP reduction (β = 0.824, p < 0.05). Lifestyle interventions are useful for all obese hypertensive patients in most of whom a modest weight loss is sufficient to normalize BP levels avoiding the aggressive use of multiple antihypertensive drugs. © 2016 The Author(s) Published by S. Karger GmbH, Freiburg.

Effect of a Modest Weight Loss in Normalizing Blood Pressure in Obese Subjects on Antihypertensive Drugs

PubMed Central

Gilardini, Luisa; Redaelli, Gabriella; Croci, Marina; Conti, Antonio; Pasqualinotto, Lucia; Invitti, Cecilia

2016-01-01

Objective To assess the effect of a lifestyle intervention in lowering/normalizing blood pressure (BP) levels in hypertensive (controlled or not) obese patients. Methods In this prospective observational study, 490 obese hypertensive patients, 389 controlled (BP < 140/90 mm Hg; CH) and 101 uncontrolled (BP ≥ 140/90 mm Hg; UH) attended a 3-month lifestyle intervention. Before and after the intervention we assessed weight, waist circumference, fat mass, BP, metabolic and renal variables, and physical activity. A multivariate regression model was used to determine the predictors of BP changes. Results 18.9% of CH and 20.0% of UH were on ≥ 3 antihypertensive drugs. Weight change (average −4.9 ± 2.7%) was independent of the antihypertensive drugs employed. Systolic BP (SBP) decreased by 23 mm Hg and diastolic BP (DBP) by 9 mm Hg, in patients with UH most of whom (89%) normalized BP levels (in 49% after a weight loss < 5%). Age, gender, whole and central obesity, concomitance of type 2 diabetes, chronic renal disease, physical activity intensification, and pharmacological therapy did not affect BP lowering. In the regression analysis with SBP change as dependent variable, weight reduction (β = 0.523, p = 0.005) and group (UH vs. CH, β = −19.40, p = 0.0005) remained associated with SBP reduction. When DBP change was entered as dependent variable, baseline uric acid remained associated with DBP reduction (β = 0.824, p < 0.05). Conclusion Lifestyle interventions are useful for all obese hypertensive patients in most of whom a modest weight loss is sufficient to normalize BP levels avoiding the aggressive use of multiple antihypertensive drugs. PMID:27454447

Low birth weight among term newborns in Wolaita Sodo town, South Ethiopia: a facility based cross-sectional study.

PubMed

Kastro, Samson; Demissie, Tsegaye; Yohannes, Bereket

2018-05-11

In low income countries, many low birth weight newborns often miss the chance for survival sooner or later. Others who survive would also face increased risks in later life. Though not adequately documented in Ethiopia, maternal factors pose the main risk. This study was aimed to estimate the proportion of low birth weight among term singletons without congenital malformations and factors associated with it in Wolaita Sodo town in South Ethiopia. We did a facility based survey involving 432 postpartum women with their term newborns. Data was collected through face to face interview from March to April in 2016. The outcome measure was newborn birth weight. Bivariate logistic regression was applied to look for crude associations. Multivariate logistic regression analysis was done to adjust for potential confounders to identify independent predictors. Adjusted Odds Ratio (AOR) and 95% confidence intervals (CI), and statistical significance at P < 0.05 were reported. The proportion of term low birth weight was 8.1% in the study area. Women who had less education (AOR = 6.23; 95% CI = 1.68, 23.1), house wives (AOR = 5.85; 95% CI = 1.40, 24.3) and not frequently consuming fruits during pregnancy (AOR 11.3; 95% CI = 1.98, 64.9) had a higher risk of having term low birth weight newborns. We documented a lesser odds of those from rural settings to have low birth weight newborns as compared to their counter urban equivalents (AOR = 0.06; 95% CI = 0.006, 0.6). Dietary counselling to pregnant mothers specific diet and nutrition including fruit diets in particular might contribute to reduce the risk of term low birth weight. Better education might have enabled women to prefer diets and their job engagements might also have capacitated them to decide on dietary preferences.

The effect of an automated clinical reminder on weight loss in primary care.

PubMed

O'Grady, Jason S; Thacher, Tom D; Chaudhry, Rajeev

2013-01-01

Overweight and obese individuals have increased health risks. Clinical reminders positively affect health outcomes in diabetes and osteoporosis, but the effect of automated prompts on weight loss in obesity has not been studied. Our objective was to determine whether an automatic prompt for the clinician to recommend lifestyle changes to patients with a body mass index (BMI) >25 kg/m(2) led to greater weight loss over a 3- to 6-month interval compared with the absence of a clinical reminder. We conducted a retrospective analysis of electronic medical records of obese adult patients with a BMI >25 kg/m(2) who were seen in 2009 and 2010, before and after implementation of an automated printed clinical reminder, respectively. We evaluated 1600 patients in each of the control and intervention groups. The primary outcome was the mean change in BMI between the control and intervention groups. Multiple linear regression was used to assess the effect of the clinical reminder on the change in BMI while adjusting for baseline BMI and potential confounding factors. The reduction in BMI (mean ± standard deviation) in the group with the clinical reminder (-0.084 ± 1.56 kg/m(2)) was not significantly greater than the control group (-0.053 ± 1.49 kg/m(2); P = .56). A regression model incorporating the clinical reminder, age, baseline BMI, obesity diagnosis, diabetes, and hyperlipidemia found that baseline BMI (P < .001), obesity diagnosis (P < .001), age (P = .001), and hyperlipidemia diagnosis (P = .02) were significant predictors of weight loss, but the clinical reminder was not (P = .78). There was a significant interaction between the clinical reminder and baseline BMI (P = .005), as the prompt increased weight loss more in those with lower baseline BMI. Automated clinical reminders alone do not improve weight loss in overweight and obese patients. Physician diagnoses of obesity or hyperlipidemia were associated with weight loss, suggesting that formally noting these diagnoses contributes to successful weight loss.

Blood lead level association with lower body weight in NHANES 1999–2006

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

Scinicariello, Franco, E-mail: fes6@cdc.gov; Buser, Melanie C.; Mevissen, Meike

Background: Lead exposure is associated with low birth-weight. The objective of this study is to determine whether lead exposure is associated with lower body weight in children, adolescents and adults. Methods: We analyzed data from NHANES 1999–2006 for participants aged ≥ 3 using multiple logistic and multivariate linear regression. Using age- and sex-standardized BMI Z-scores, overweight and obese children (ages 3–19) were classified by BMI ≥ 85th and ≥ 95th percentiles, respectively. The adult population (age ≥ 20) was classified as overweight and obese with BMI measures of 25–29.9 and ≥ 30, respectively. Blood lead level (BLL) was categorized bymore » weighted quartiles. Results: Multivariate linear regressions revealed a lower BMI Z-score in children and adolescents when the highest lead quartile was compared to the lowest lead quartile (β (SE) = − 0.33 (0.07), p < 0.001), and a decreased BMI in adults (β (SE) = − 2.58 (0.25), p < 0.001). Multiple logistic analyses in children and adolescents found a negative association between BLL and the percentage of obese and overweight with BLL in the highest quartile compared to the lowest quartile (OR = 0.42, 95% CI: 0.30–0.59; and OR = 0.67, 95% CI: 0.52–0.88, respectively). Adults in the highest lead quartile were less likely to be obese (OR = 0.42, 95% CI: 0.35–0.50) compared to those in the lowest lead quartile. Further analyses with blood lead as restricted cubic splines, confirmed the dose-relationship between blood lead and body weight outcomes. Conclusions: BLLs are associated with lower body mass index and obesity in children, adolescents and adults. - Highlights: • NHANES analysis of BLL and body weight outcomes • Increased BLL associated with decreased body weight in children and adolescent • Increased BLL associated with decreased body weight in adults.« less

Overweight in children and adolescents associated with TV viewing and parental weight: Project HeartBeat!

PubMed

Steffen, Lyn M; Dai, Shifan; Fulton, Janet E; Labarthe, Darwin R

2009-07-01

Parental obesity and TV viewing are risk factors for childhood obesity. This study assessed the association of children's TV viewing and computer use with body mass and examined whether parental weight status modified the association. Cross-sectional associations of parental weight status, hours of TV viewing and computer use, and children's body composition were studied in a subsample of 526 black and nonblack children, aged 8, 11, and 14 years at baseline, enrolled in Project HeartBeat!, a longitudinal study of cardiovascular disease risk factors, 1991-1995. BMI, fat-free mass (FFM), and percent body fat (PBF) were calculated from children's body composition measured at baseline. Children's TV viewing and computer use habits and parental height and weight were self-reported. Multivariate regression analysis was used in assessing inter-relations of parental weight status and child's TV viewing and computer use habits with BMI, FFM, PBF, and risk for overweight status (BMI > or =85th percentile), adjusting for age, gender, race, and Tanner stage. Children of one or two overweight/obese parents watched an average of 22+/-6 minutes or 30+/-11 minutes more TV per day than children of normal-weight parents, respectively (both p<0.01). In multivariate regression analyses, BMI and PBF increased significantly by 0.42 kg/m(2) and 1.14% (both p<0.001), respectively, for each hour of TV watched among children with overweight parents, but not for those with normal-weight parents (p(interaction)<0.05). Similar results were observed for total screen time. These study findings are consistent with a genetic contribution of parental weight; however, overweight/obese parents may also exhibit behavior patterns that negatively influence children's TV viewing and have an impact on child overweight status. The effect of parental BMI on children's BMI may have both a genetic and an environmental linkage.

Contributions of fat mass and fat distribution to hip bone strength in healthy postmenopausal Chinese women.

PubMed

Shao, Hong Da; Li, Guan Wu; Liu, Yong; Qiu, Yu You; Yao, Jian Hua; Tang, Guang Yu

2015-09-01

The fat and bone connection is complicated, and the effect of adipose tissue on hip bone strength remains unclear. The aim of this study was to clarify the relative contribution of body fat accumulation and fat distribution to the determination of proximal femur strength in healthy postmenopausal Chinese women. This cross-sectional study enrolled 528 healthy postmenopausal women without medication history or known diseases. Total lean mass (LM), appendicular LM (ALM), percentage of lean mass (PLM), total fat mass (FM), appendicular FM (AFM), percentage of body fat (PBF), android and gynoid fat amount, android-to-gynoid fat ratio (AOI), bone mineral density (BMD), and proximal femur geometry were measured by dual energy X-ray absorptiometry. Hip structure analysis was used to compute some variables as geometric strength-related parameters by analyzing the images of the hip generated from DXA scans. Correlation analyses among anthropometrics, variables of body composition and bone mass, and geometric indices of hip bone strength were performed with stepwise linear regression analyses as well as Pearson's correlation analysis. In univariate analysis, there were significantly inverse correlations between age, years since menopause (YSM), hip BMD, and hip geometric parameters. Bone data were positively related to height, body weight, LM, ALM, FM, AFM, and PBF but negatively related to AOI and amount of android fat (all P < 0.05). AFM and AOI were significantly related to most anthropometric parameters. AFM was positively associated with height, body weight, and BMI. AFM was negatively associated with age and YSM. AOI was negatively associated with height, body weight, and BMI. AOI positively associated with age and YSM. LM, ALM, and FM had a positive relationship with anthropometric parameters (P < 0.05 for all). PLM had a negative relationship with those parameters. The correlation between LM, ALM, FM, PLM, ALM, age, and YSM was not significant. In multivariate linear regression analysis, the hip bone strength was observed to have a consistent and unchanged positive association with AFM and a negative association with AOI, whereas its association with other variables of body composition was not significant after adjusting for age, years since menopause, height, body weight, and BMI. AFM may be a positively protective effect for hip bone strength while AOI, rather than android fat, shows a strong negative association with hip bone strength after making an adjustment for confounders (age, YSM, height, body weight, and BMI) in healthy postmenopausal Chinese women. Rational weight control and AOI reduction during menopause may have vital clinical significance in decreasing postmenopausal osteoporosis.

Comparing women pharmacy consumers’ experiences with weight loss treatment in Victoria and Nottingham: a cross-sectional study

PubMed Central

2014-01-01

Background There has been a recent increase in weight management services available in pharmacies across Australia and England. The aim of this study was to determine the following between women in Victoria and Nottingham: similarities and differences of what weight management options are preferred by women pharmacy consumers; how they feel about pharmacists providing advice in this area; and what they desire in a weight management program. Method Women pharmacy consumers were randomly approached by a researcher in community pharmacies in Victoria and Nottingham and asked to complete a questionnaire regarding their own weight management experiences. The questionnaire was self-completed or researcher-administered and was comprised of four main sections that focused on the participant’s general health, previous weight loss experiences, their ideal weight management program and their demographics. Data was entered in SPSS 19 and logistic regression was used to identify any differences in weight loss experiences between women. Results The participant rates were high: 86% (n = 395/460) in Victoria and 98% in Nottingham (n = 215/220). Overall, women in Victoria and Nottingham were similar with comparable demographics. Approximately 50% (250/507) of women were in the overweight or obese body mass index category, with over 70% (n = 436/610) of women having attempted to lose weight in the past. The majority of women (n = 334/436) felt comfortable receiving advice from pharmacists. In the logistic regression analysis women in Nottingham were found to be significantly less likely to have utilised a pharmacy weight management program in the last five years (OR: 0.23 CI: 0.08, 0.63) and were significantly less likely to want an ideal weight management program located in a pharmacy (OR: 0.49 CI: 0.30, 0.82) compared to women in Victoria. No significant associations between location and feeling comfortable with a pharmacist advising on weight loss or wanting a pharmacist in an ideal weight management program were seen. Conclusion Results from this study have provided information on possible ideal pharmacy weight management programs in both Victoria and Nottingham. Although differences were seen between the two populations, similarities between ideal weight management programs and comfort level with pharmacist interaction were noted. PMID:24972611

A Weighted Least Squares Approach To Robustify Least Squares Estimates.

ERIC Educational Resources Information Center

Lin, Chowhong; Davenport, Ernest C., Jr.

This study developed a robust linear regression technique based on the idea of weighted least squares. In this technique, a subsample of the full data of interest is drawn, based on a measure of distance, and an initial set of regression coefficients is calculated. The rest of the data points are then taken into the subsample, one after another,…

A multiple linear regression analysis of hot corrosion attack on a series of nickel base turbine alloys

NASA Technical Reports Server (NTRS)

Barrett, C. A.

1985-01-01

Multiple linear regression analysis was used to determine an equation for estimating hot corrosion attack for a series of Ni base cast turbine alloys. The U transform (i.e., 1/sin (% A/100) to the 1/2) was shown to give the best estimate of the dependent variable, y. A complete second degree equation is described for the centered" weight chemistries for the elements Cr, Al, Ti, Mo, W, Cb, Ta, and Co. In addition linear terms for the minor elements C, B, and Zr were added for a basic 47 term equation. The best reduced equation was determined by the stepwise selection method with essentially 13 terms. The Cr term was found to be the most important accounting for 60 percent of the explained variability hot corrosion attack.

Relationship between health services, socioeconomic variables and inadequate weight gain among Brazilian children.

PubMed Central

de Souza, A. C.; Peterson, K. E.; Cufino, E.; Gardner, J.; Craveiro, M. V.; Ascherio, A.

1999-01-01

This ecological analysis assessed the relative contribution of behavioural, health services and socioeconomic variables to inadequate weight gain in infants (0-11 months) and children (12-23 months) in 140 municipalities in the State of Ceara, north-east Brazil. To assess the total effect of selected variables, we fitted three unique sets of multivariate linear regression models to the prevalence of inadequate weight gain in infants and in children. The final predictive models included variables from the three sets. Findings showed that participation in growth monitoring and urbanization were inversely and significantly associated with the prevalence of inadequate weight gain in infants, accounting for 38.3% of the variation. Female illiteracy rate, participation in growth monitoring and degree of urbanization were all positively associated with prevalence of inadequate weight gain in children. Together, these factors explained 25.6% of the variation. Our results suggest that efforts to reduce the average municipality-specific female illiteracy rate, in combination with participation in growth monitoring, may be effective in reducing municipality-level prevalence of inadequate weight gain in infants and children in Ceara. PMID:10612885

Associations between working environment and weight control efforts among workers with obesity in Korea.

PubMed

Hyun, Hye Sun; Kim, Yunyoung

2018-06-01

Objective The aim of this study was to investigate the relationship between working environment and weight control efforts among obese workers in Korea. Methods This study was based on the 2011 3rd Korean Working Conditions Survey, which was conducted on workers aged 15 years or older. A sample of 484 obese workers was included in the study. Multivariable logistic regression analysis was used to investigate the relationship between working environment and weight control efforts after controlling for individual variables. Adjusted odds ratios (ORs) and 95% confidence intervals were calculated. Results Of the participants, 63.4% reported that they made efforts to control their weight. After controlling for personal factors, the OR of weight control efforts for individuals working 40-49 hours per week was 2.4 times that for individuals working 60 hours or more per week. The OR of regular employment workers was 2.2 times that of non-regular workers. Conclusion We established that working hours and employment type were significantly related to weight control efforts. Therefore, we recommend that working conditions should be considered in designing effective workplace health promotion programs.

Relationship between health services, socioeconomic variables and inadequate weight gain among Brazilian children.

PubMed

de Souza, A C; Peterson, K E; Cufino, E; Gardner, J; Craveiro, M V; Ascherio, A

1999-01-01

This ecological analysis assessed the relative contribution of behavioural, health services and socioeconomic variables to inadequate weight gain in infants (0-11 months) and children (12-23 months) in 140 municipalities in the State of Ceara, north-east Brazil. To assess the total effect of selected variables, we fitted three unique sets of multivariate linear regression models to the prevalence of inadequate weight gain in infants and in children. The final predictive models included variables from the three sets. Findings showed that participation in growth monitoring and urbanization were inversely and significantly associated with the prevalence of inadequate weight gain in infants, accounting for 38.3% of the variation. Female illiteracy rate, participation in growth monitoring and degree of urbanization were all positively associated with prevalence of inadequate weight gain in children. Together, these factors explained 25.6% of the variation. Our results suggest that efforts to reduce the average municipality-specific female illiteracy rate, in combination with participation in growth monitoring, may be effective in reducing municipality-level prevalence of inadequate weight gain in infants and children in Ceara.

Applications of Some Artificial Intelligence Methods to Satellite Soundings

NASA Technical Reports Server (NTRS)

Munteanu, M. J.; Jakubowicz, O.

1985-01-01

Hard clustering of temperature profiles and regression temperature retrievals were used to refine the method using the probabilities of membership of each pattern vector in each of the clusters derived with discriminant analysis. In hard clustering the maximum probability is taken and the corresponding cluster as the correct cluster are considered discarding the rest of the probabilities. In fuzzy partitioned clustering these probabilities are kept and the final regression retrieval is a weighted regression retrieval of several clusters. This method was used in the clustering of brightness temperatures where the purpose was to predict tropopause height. A further refinement is the division of temperature profiles into three major regions for classification purposes. The results are summarized in the tables total r.m.s. errors are displayed. An approach based on fuzzy logic which is intimately related to artificial intelligence methods is recommended.

Excess weight loss in first-born breastfed newborns relates to maternal intrapartum fluid balance.

PubMed

Chantry, Caroline J; Nommsen-Rivers, Laurie A; Peerson, Janet M; Cohen, Roberta J; Dewey, Kathryn G

2011-01-01

The objectives were to describe weight loss in a multiethnic population of first-born, predominantly breastfed, term infants and to identify potentially modifiable risk factors for excess weight loss (EWL). Data on prenatal breastfeeding intentions, demographic characteristics, labor and delivery interventions and outcomes, breastfeeding behaviors, formula and pacifier use, onset of lactogenesis, and nipple type and pain were collected prospectively. Logistic regression analyses identified independent predictors of EWL (≥10% of birth weight) by using a preplanned theoretical model. EWL occurred for 18% of infants who received no or minimal (≤60 mL total since birth) formula (n = 229), including 19% of exclusively breastfed infants (n = 134) and 16% of infants who received minimal formula (n = 95). In bivariate analyses, EWL was associated (P < .05) with higher maternal age, education, and income levels, hourly intrapartum fluid balance, postpartum edema, delayed lactogenesis (>72 hours), fewer infant stools, and infant birth weight. In multivariate logistic regression analysis, only 2 variables predicted EWL significantly, namely, intrapartum fluid balance (adjusted relative risk for EWL of 3.18 [95% confidence interval [CI]: 1.35-13.29] and 2.80 [95% CI: 1.17-11.68] with net intrapartum fluid balance of >200 and 100-200 mL/hour, respectively, compared with <100 mL/hour) and delayed lactogenesis (adjusted relative risk: 3.35 [95% CI: 1.74-8.10]). EWL was more common in this population than reported previously and was independently related to intrapartum fluid balance. This suggests that intrapartum fluid administration can cause fetal volume expansion and greater fluid loss after birth, although other mechanisms are possible.

An increase in visceral fat is associated with a decrease in the taste and olfactory capacity

PubMed Central

Fernandez-Garcia, Jose Carlos; Alcaide, Juan; Santiago-Fernandez, Concepcion; Roca-Rodriguez, MM.; Aguera, Zaida; Baños, Rosa; Botella, Cristina; de la Torre, Rafael; Fernandez-Real, Jose M.; Fruhbeck, Gema; Gomez-Ambrosi, Javier; Jimenez-Murcia, Susana; Menchon, Jose M.; Casanueva, Felipe F.; Fernandez-Aranda, Fernando; Tinahones, Francisco J.; Garrido-Sanchez, Lourdes

2017-01-01

Introduction Sensory factors may play an important role in the determination of appetite and food choices. Also, some adipokines may alter or predict the perception and pleasantness of specific odors. We aimed to analyze differences in smell–taste capacity between females with different weights and relate them with fat and fat-free mass, visceral fat, and several adipokines. Materials and methods 179 females with different weights (from low weight to morbid obesity) were studied. We analyzed the relation between fat, fat-free mass, visceral fat (indirectly estimated by bioelectrical impedance analysis with visceral fat rating (VFR)), leptin, adiponectin and visfatin. The smell and taste assessments were performed through the "Sniffin’ Sticks" and "Taste Strips" respectively. Results We found a lower score in the measurement of smell (TDI-score (Threshold, Discrimination and Identification)) in obese subjects. All the olfactory functions measured, such as threshold, discrimination, identification and the TDI-score, correlated negatively with age, body mass index (BMI), leptin, fat mass, fat-free mass and VFR. In a multiple linear regression model, VFR mainly predicted the TDI-score. With regard to the taste function measurements, the normal weight subjects showed a higher score of taste functions. However a tendency to decrease was observed in the groups with greater or lesser BMI. In a multiple linear regression model VFR and age mainly predicted the total taste scores. Discussion We show for the first time that a reverse relationship exists between visceral fat and sensory signals, such as smell and taste, across a population with different body weight conditions. PMID:28158237

Eat, sleep, work, play: associations of weight status and health-related behaviors among young adult college students.

PubMed

Quick, Virginia; Byrd-Bredbenner, Carol; White, Adrienne A; Brown, Onikia; Colby, Sarah; Shoff, Suzanne; Lohse, Barbara; Horacek, Tanya; Kidd, Tanda; Greene, Geoffrey

2014-01-01

To examine relationships of sleep, eating, and exercise behaviors; work time pressures; and sociodemographic characteristics by weight status (healthy weight [body mass index or BMI < 25] vs. overweight [BMI ≥ 25]) of young adults. Cross-sectional. Nine U.S. universities. Enrolled college students (N = 1252; 18-24 years; 80% white; 59% female). Survey included the Pittsburgh Sleep Quality Index (PSQI), Three-Factor Eating Questionnaire (TFEQ), Satter Eating Competence Inventory (ecSI), National Cancer Institute Fruit/Vegetable Screener, International Physical Activity Questionnaire, Work Time Pressure items, and sociodemographic characteristics. Chi-square and t-tests determined significant bivariate associations of sociodemographics, sleep behaviors, eating behaviors, physical activity behavior, and work time pressures with weight status (i.e., healthy vs. overweight/obese). Statistically significant bivariate associations with weight status were then entered into a multivariate logistic regression model that estimated associations with being overweight/obese. Sex (female), race (nonwhite), older age, higher Global PSQI score, lower ecSI total score, and higher TFEQ Emotional Eating Scale score were significantly (p < .05) associated with overweight/obesity in bivariate analyses. Multivariate logistic regression analysis showed that sex (female; odds ratio [OR] = 2.05, confidence interval [CI] = 1.54-2.74), older age (OR = 1.35, CI = 1.21-1.50), higher Global PSQI score (OR = 1.07, CI = 1.01-1.13), and lower ecSI score (OR = .96, CI = .94-.98), were significantly (p < .05) associated with overweight/obesity. Findings suggest that obesity prevention interventions for college students should include an education component to emphasize the importance of overall sleep quality and improving eating competence.

Does body image perception relate to quality of life in middle-aged women?

PubMed Central

Medeiros de Morais, Maria Socorro; Vieira, Mariana Carmem Apolinário; Moreira, Mayle Andrade; da Câmara, Saionara Maria Aires; Campos Cavalcanti Maciel, Álvaro; Almeida, Maria das Graças

2017-01-01

Objective In Brazil, information about the influence of body image on the various life domains of women in menopausal transition is scarce. Thus, the objective of the study was to analyze the relationship between body image and quality of life in middle-aged Brazilian women. Methods This was a cross-sectional study of 250 women between 40 and 65 years old, living in Parnamirim/RN, Brazil, who were evaluated in relation to body image and quality of life. For body image, women were classified as: dissatisfied due to low weight, satisfied (with their body weight) and dissatisfied due to being overweight. Quality of life was assessed through a questionnaire in which higher values indicate higher quality of life. Multiple linear regression was performed to analyze the relationship between body image and quality of life, adjusted for covariates that presented p<0.20 in the bivariate analysis. Results The average age was 52.1 (± 5.6) years, 82% of the women reported being dissatisfied due to being overweight, and 4.4% were dissatisfied due to having low weight. After multiple linear regression analyzes, body image remained associated with health (p<0.001), emotional (p = 0.016), and sexual (p = 0.048) domains of quality of life, as well as total score of the questionnaire (p<0.001). Conclusion Women who reported being dissatisfied with their body image due to having low weight or overweight had worse quality of life in comparison to those who were satisfied (with their body weight). PMID:28926575

Effect of breastfeeding on weight retention from one pregnancy to the next: results from the North Carolina WIC program.

PubMed

Østbye, Truls; Krause, Katrina M; Swamy, Geeta K; Lovelady, Cheryl A

2010-11-01

Pregnancy-related weight retention can contribute to obesity, and breastfeeding may facilitate postpartum weight loss. We investigated the effect of breastfeeding on long-term postpartum weight retention. Using data from the North Carolina Special Supplemental Nutrition Program for Women, Infants, and Children (WIC; 1996-2004), weight retention was assessed in women aged 18 years or older who had more than one pregnancy available for analysis (n=32,920). Using multivariable linear regression, the relationship between duration of breastfeeding after the first pregnancy and change in pre-pregnancy weight from the first pregnancy to the second pregnancy was estimated, controlling for demographic and weight-related covariates. Mean time between pregnancies was 2.8 years (standard deviation (SD) 1.5), and mean weight retention from the first to the second pregnancy was 4.9kg (SD 8.7). In covariate-adjusted analyses, breastfeeding for 20 weeks or more resulted in 0.39kg (standard error (SE) 0.18) less weight retention at the beginning of the second pregnancy relative to no breastfeeding (p=0.025). In this large, racially diverse sample of low-income women, long-term weight retention was lower among those who breastfed for at least 20 weeks. Copyright © 2010 Elsevier Inc. All rights reserved.

Low weight gain at the start of a family-based intervention for adolescent girls with restrictive eating disorders predicted emergency hospital admission.

PubMed

Swenne, Ingemar; Ros, Helena Salonen

2017-10-01

This study examined predictors of emergency hospitalisation of adolescent girls with restrictive eating disorders and weight loss treated by a family-based intervention programme. We studied 339 girls aged 10-17 years treated in a specialist unit at Uppsala University Children's Hospital, Sweden, from August 2010 to December 2015. Historical weight data were obtained from school health services, and other weight data were determined at presentation. Weight controlling behaviour was recorded, and patients were evaluated using the Eating Disorder Examination Questionnaire. A family-based intervention started after assessment and the early weight gain after one week, one month and three months was assessed. There were 17 emergency admissions of 15 patients for refusing food, progressive weight loss and medical instability. Logistic regression analysis showed that emergency admissions were predicted by a low body mass index standard deviation score at presentation (odds ratio 2.57), a high rate of weight loss before presentation (odds ratio 4.38) and a low rate of weight gain at the start of treatment (odds ratio 4.59). Poor weight gain at the start of a family-based intervention for adolescent girls with restrictive eating disorders predicted emergency hospital admission. ©2017 Foundation Acta Paediatrica. Published by John Wiley & Sons Ltd.

Weight Misperceptions and Racial and Ethnic Disparities in Adolescent Female Body Mass Index

PubMed Central

Krauss, Ramona C.; Powell, Lisa M.; Wada, Roy

2012-01-01

This paper investigated weight misperceptions as determinants of racial/ethnic disparities in body mass index (BMI) among adolescent females using data from the National Survey of Youth 1997. Compared to their white counterparts, higher proportions of black and Hispanic adolescent females underperceived their weight status; that is, they misperceived themselves to have lower weight status compared to their clinically defined weight status. Compared to their black counterparts, higher proportions of white and Hispanic adolescent females misperceived themselves to be heavier than their clinical weight status. Oaxaca-Blinder decomposition analysis showed that accounting for weight misperceptions, in addition to individual and contextual factors, increased the total explained portion of the black-white female BMI gap from 44.7% to 54.3% but only slightly increased the total explained portion of the Hispanic-white gap from 62.8% to 63.1%. Weight misperceptions explained 13.0% of the black-white female BMI gap and 3.3% of the Hispanic-white female BMI gap. The regression estimates showed that weight underperceptions were important determinants of adolescent female BMI, particularly among black and Hispanic adolescents. Education regarding identification and interpretation of weight status may play an important role to help reduce the incidence and racial disparity of female adolescent obesity. PMID:22701166

Birth weight trends in England and Wales (1986–2012): babies are getting heavier

PubMed Central

Berild, Jacob Dag; Sterrantino, Anna Freni; Toledano, Mireille B; Hansell, Anna L

2018-01-01

Introduction Birth weight is a strong predictor of infant mortality, morbidity and later disease risk. Previous work from the 1980s indicated a shift in the UK towards heavier births; this descriptive analysis looks at more recent trends. Methods Office for National Statistics (ONS) registration data on 17.2 million live, single births from 1986 to 2012 were investigated for temporal trends in mean birth weight, potential years of birth weight change and changes in the proportions of very low (<1500 g), low (<2500 g) and high (≥4000 g) birth weight. Analysis used multiple linear and logistic regression adjusted for maternal age, marital status, area-level deprivation and ethnicity. Additional analyses used the ONS NHS Numbers for Babies data set for 2006–2012, which has information on individual ethnicity and gestational age. Results Over 27 years there was an increase in birth weight of 43 g (95% CI 42 to 44) in females and 44 g (95% CI 43 to 45) in males, driven by birth weight increases between 1986–1990 and 2007–2012. There was a concurrent decreased risk of having low birth weight but an 8% increased risk in males and 10% increased risk in females of having high birth weight. For 2006–2012 the birth weight increase was greater in preterm as compared with term births. Conclusions Since 1986 the birth weight distribution of live, single births in England and Wales has shifted towards heavier births, partly explained by increases in maternal age and non-white ethnicity, as well as changes in deprivation levels. Other potential influences include increases in maternal obesity and reductions in smoking prevalence particularly following the introduction of legislation restricting smoking in public places in 2007. PMID:28780501

Changes in weight and weight-related quality of life in a multicentre, randomized trial of aripiprazole versus standard of care.

PubMed

Kolotkin, Ronette L; Corey-Lisle, Patricia K; Crosby, Ross D; Kan, Hong J; McQuade, Robert D

2008-12-01

This is a secondary analysis of clinical trial data collected in 12 European countries. We examined changes in weight and weight-related quality of life among community patients with schizophrenia treated with aripiprazole (ARI) versus standard of care (SOC), consisting of other marketed atypical antipsychotics (olanzapine, quetiapine, and risperidone). Five-hundred and fifty-five patients whose clinical symptoms were not optimally controlled and/or experienced tolerability problems with current medication were randomized to ARI (10-30 mg/day) or SOC. Weight and weight-related quality of life (using the IWQOL-Lite) were assessed at baseline, and weeks 8, 18 and 26. Random regression analysis across all time points using all available data was used to compare groups on changes in weight and IWQOL-Lite. Meaningful change from baseline was also assessed. Participants were 59.7% male, with a mean age of 38.5 years (SD 10.9) and mean baseline body mass index of 27.2 (SD 5.1). ARI participants lost an average of 1.7% of baseline weight in comparison to a gain of 2.1% by SOC participants (p<0.0001) at 26 weeks. ARI participants experienced significantly greater increases in physical function, self-esteem, sexual life, and IWQOL-Lite total score. At 26 weeks, 20.7% of ARI participants experienced meaningful improvements in IWQOL-Lite score, versus 13.5% of SOC participants. A clinically meaningful change in weight was also associated with a meaningful change in quality of life (p<0.001). A potential limitation of this study was its funding by a pharmaceutical company. Compared to standard of care, patients with schizophrenia treated with aripiprazole experienced decreased weight and improved weight-related quality of life over 26 weeks. These changes were both statistically and clinically significant.

Body weight loss reverts obesity-associated hypogonadotropic hypogonadism: a systematic review and meta-analysis.

PubMed

Corona, Giovanni; Rastrelli, Giulia; Monami, Matteo; Saad, Farid; Luconi, Michaela; Lucchese, Marcello; Facchiano, Enrico; Sforza, Alessandra; Forti, Gianni; Mannucci, Edoardo; Maggi, Mario

2013-06-01

Few randomized clinical studies have evaluated the impact of diet and physical activity on testosterone levels in obese men with conflicting results. Conversely, studies on bariatric surgery in men generally have shown an increase in testosterone levels. The aim of this study is to perform a systematic review and meta-analysis of available trials on the effect of body weight loss on sex hormones levels. Meta-analysis. An extensive Medline search was performed including the following words: 'testosterone', 'diet', 'weight loss', 'bariatric surgery', and 'males'. The search was restricted to data from January 1, 1969 up to August 31, 2012. Out of 266 retrieved articles, 24 were included in the study. Of the latter, 22 evaluated the effect of diet or bariatric surgery, whereas two compared diet and bariatric surgery. Overall, both a low-calorie diet and bariatric surgery are associated with a significant (P<0.0001) increase in plasma sex hormone-binding globulin-bound and -unbound testosterone levels (total testosterone (TT)), with bariatric surgery being more effective in comparison with the low-calorie diet (TT increase: 8.73 (6.51-10.95) vs 2.87 (1.68-4.07) for bariatric surgery and the low-calorie diet, respectively; both P<0.0001 vs baseline). Androgen rise is greater in those patients who lose more weight as well as in younger, non-diabetic subjects with a greater degree of obesity. Body weight loss is also associated with a decrease in estradiol and an increase in gonadotropins levels. Multiple regression analysis shows that the degree of body weight loss is the best determinant of TT rise (B=2.50±0.98, P=0.029). These data show that weight loss is associated with an increase in both bound and unbound testosterone levels. The normalization of sex hormones induced by body weight loss is a possible mechanism contributing to the beneficial effects of surgery in morbid obesity.

Estimates of Flow Duration, Mean Flow, and Peak-Discharge Frequency Values for Kansas Stream Locations

USGS Publications Warehouse

Perry, Charles A.; Wolock, David M.; Artman, Joshua C.

2004-01-01

Streamflow statistics of flow duration and peak-discharge frequency were estimated for 4,771 individual locations on streams listed on the 1999 Kansas Surface Water Register. These statistics included the flow-duration values of 90, 75, 50, 25, and 10 percent, as well as the mean flow value. Peak-discharge frequency values were estimated for the 2-, 5-, 10-, 25-, 50-, and 100-year floods. Least-squares multiple regression techniques were used, along with Tobit analyses, to develop equations for estimating flow-duration values of 90, 75, 50, 25, and 10 percent and the mean flow for uncontrolled flow stream locations. The contributing-drainage areas of 149 U.S. Geological Survey streamflow-gaging stations in Kansas and parts of surrounding States that had flow uncontrolled by Federal reservoirs and used in the regression analyses ranged from 2.06 to 12,004 square miles. Logarithmic transformations of climatic and basin data were performed to yield the best linear relation for developing equations to compute flow durations and mean flow. In the regression analyses, the significant climatic and basin characteristics, in order of importance, were contributing-drainage area, mean annual precipitation, mean basin permeability, and mean basin slope. The analyses yielded a model standard error of prediction range of 0.43 logarithmic units for the 90-percent duration analysis to 0.15 logarithmic units for the 10-percent duration analysis. The model standard error of prediction was 0.14 logarithmic units for the mean flow. Regression equations used to estimate peak-discharge frequency values were obtained from a previous report, and estimates for the 2-, 5-, 10-, 25-, 50-, and 100-year floods were determined for this report. The regression equations and an interpolation procedure were used to compute flow durations, mean flow, and estimates of peak-discharge frequency for locations along uncontrolled flow streams on the 1999 Kansas Surface Water Register. Flow durations, mean flow, and peak-discharge frequency values determined at available gaging stations were used to interpolate the regression-estimated flows for the stream locations where available. Streamflow statistics for locations that had uncontrolled flow were interpolated using data from gaging stations weighted according to the drainage area and the bias between the regression-estimated and gaged flow information. On controlled reaches of Kansas streams, the streamflow statistics were interpolated between gaging stations using only gaged data weighted by drainage area.

A scoping review of spatial cluster analysis techniques for point-event data.

PubMed

Fritz, Charles E; Schuurman, Nadine; Robertson, Colin; Lear, Scott

2013-05-01

Spatial cluster analysis is a uniquely interdisciplinary endeavour, and so it is important to communicate and disseminate ideas, innovations, best practices and challenges across practitioners, applied epidemiology researchers and spatial statisticians. In this research we conducted a scoping review to systematically search peer-reviewed journal databases for research that has employed spatial cluster analysis methods on individual-level, address location, or x and y coordinate derived data. To illustrate the thematic issues raised by our results, methods were tested using a dataset where known clusters existed. Point pattern methods, spatial clustering and cluster detection tests, and a locally weighted spatial regression model were most commonly used for individual-level, address location data (n = 29). The spatial scan statistic was the most popular method for address location data (n = 19). Six themes were identified relating to the application of spatial cluster analysis methods and subsequent analyses, which we recommend researchers to consider; exploratory analysis, visualization, spatial resolution, aetiology, scale and spatial weights. It is our intention that researchers seeking direction for using spatial cluster analysis methods, consider the caveats and strengths of each approach, but also explore the numerous other methods available for this type of analysis. Applied spatial epidemiology researchers and practitioners should give special consideration to applying multiple tests to a dataset. Future research should focus on developing frameworks for selecting appropriate methods and the corresponding spatial weighting schemes.

Body composition in childhood inflammatory bowel disease.

PubMed

Wiskin, Anthony E; Wootton, Stephen A; Hunt, Toby M; Cornelius, Victoria R; Afzal, Nadeem A; Jackson, Alan A; Beattie, R Mark

2011-02-01

Little is known about the impact of disease and treatment on the pattern of growth in children with Inflammatory Bowel Disease (IBD). Significant deficits in height and weight in children with Crohn's disease have been reported but changes in fat and fat free mass are less well defined. This study aims to describe the height, weight and body composition of a cohort of children with IBD. Height, weight, skinfold thicknesses and bioelectrical impedance analysis was performed. Disease activity was assessed with clinical scoring systems. 55 children, median age 13.7 years (range 6.5-17.7) were studied. Median (25th, 75th percentile) Standard Deviation Score for BMI, Height and Weight were - 0.3 (- 0.97, 0.65), - 0.56 (- 1.42, 0.06), - 0.62 (- 1.43, 0.19). In Crohn's disease, using multiple regression analysis disease activity measured by PCDAI was significantly inversely related to fat free mass (β - 0.2, 95% CI -0.17, -0.03, p 0.005). Children with IBD were both under and overweight. Nutritional deficits were more common in Crohn's disease. Fat free mass was related to disease activity in children with Crohn's disease regardless of changes in weight. Weight or BMI may mask deficits in lean tissue in the presence of normal or increased proportions of body fat. Copyright © 2010 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

Beak measurements of octopus ( Octopus variabilis) in Jiaozhou Bay and their use in size and biomass estimation

NASA Astrophysics Data System (ADS)

Xue, Ying; Ren, Yiping; Meng, Wenrong; Li, Long; Mao, Xia; Han, Dongyan; Ma, Qiuyun

2013-09-01

Cephalopods play key roles in global marine ecosystems as both predators and preys. Regressive estimation of original size and weight of cephalopod from beak measurements is a powerful tool of interrogating the feeding ecology of predators at higher trophic levels. In this study, regressive relationships among beak measurements and body length and weight were determined for an octopus species ( Octopus variabilis), an important endemic cephalopod species in the northwest Pacific Ocean. A total of 193 individuals (63 males and 130 females) were collected at a monthly interval from Jiaozhou Bay, China. Regressive relationships among 6 beak measurements (upper hood length, UHL; upper crest length, UCL; lower hood length, LHL; lower crest length, LCL; and upper and lower beak weights) and mantle length (ML), total length (TL) and body weight (W) were determined. Results showed that the relationships between beak size and TL and beak size and ML were linearly regressive, while those between beak size and W fitted a power function model. LHL and UCL were the most useful measurements for estimating the size and biomass of O. variabilis. The relationships among beak measurements and body length (either ML or TL) were not significantly different between two sexes; while those among several beak measurements (UHL, LHL and LBW) and body weight (W) were sexually different. Since male individuals of this species have a slightly greater body weight distribution than female individuals, the body weight was not an appropriate measurement for estimating size and biomass, especially when the sex of individuals in the stomachs of predators was unknown. These relationships provided essential information for future use in size and biomass estimation of O. variabilis, as well as the estimation of predator/prey size ratios in the diet of top predators.

Temporally-Constrained Group Sparse Learning for Longitudinal Data Analysis in Alzheimer’s Disease

PubMed Central

Jie, Biao; Liu, Mingxia; Liu, Jun

2016-01-01

Sparse learning has been widely investigated for analysis of brain images to assist the diagnosis of Alzheimer’s disease (AD) and its prodromal stage, i.e., mild cognitive impairment (MCI). However, most existing sparse learning-based studies only adopt cross-sectional analysis methods, where the sparse model is learned using data from a single time-point. Actually, multiple time-points of data are often available in brain imaging applications, which can be used in some longitudinal analysis methods to better uncover the disease progression patterns. Accordingly, in this paper we propose a novel temporally-constrained group sparse learning method aiming for longitudinal analysis with multiple time-points of data. Specifically, we learn a sparse linear regression model by using the imaging data from multiple time-points, where a group regularization term is first employed to group the weights for the same brain region across different time-points together. Furthermore, to reflect the smooth changes between data derived from adjacent time-points, we incorporate two smoothness regularization terms into the objective function, i.e., one fused smoothness term which requires that the differences between two successive weight vectors from adjacent time-points should be small, and another output smoothness term which requires the differences between outputs of two successive models from adjacent time-points should also be small. We develop an efficient optimization algorithm to solve the proposed objective function. Experimental results on ADNI database demonstrate that, compared with conventional sparse learning-based methods, our proposed method can achieve improved regression performance and also help in discovering disease-related biomarkers. PMID:27093313

Characterizing nonconstant instrumental variance in emerging miniaturized analytical techniques.

PubMed

Noblitt, Scott D; Berg, Kathleen E; Cate, David M; Henry, Charles S

2016-04-07

Measurement variance is a crucial aspect of quantitative chemical analysis. Variance directly affects important analytical figures of merit, including detection limit, quantitation limit, and confidence intervals. Most reported analyses for emerging analytical techniques implicitly assume constant variance (homoskedasticity) by using unweighted regression calibrations. Despite the assumption of constant variance, it is known that most instruments exhibit heteroskedasticity, where variance changes with signal intensity. Ignoring nonconstant variance results in suboptimal calibrations, invalid uncertainty estimates, and incorrect detection limits. Three techniques where homoskedasticity is often assumed were covered in this work to evaluate if heteroskedasticity had a significant quantitative impact-naked-eye, distance-based detection using paper-based analytical devices (PADs), cathodic stripping voltammetry (CSV) with disposable carbon-ink electrode devices, and microchip electrophoresis (MCE) with conductivity detection. Despite these techniques representing a wide range of chemistries and precision, heteroskedastic behavior was confirmed for each. The general variance forms were analyzed, and recommendations for accounting for nonconstant variance discussed. Monte Carlo simulations of instrument responses were performed to quantify the benefits of weighted regression, and the sensitivity to uncertainty in the variance function was tested. Results show that heteroskedasticity should be considered during development of new techniques; even moderate uncertainty (30%) in the variance function still results in weighted regression outperforming unweighted regressions. We recommend utilizing the power model of variance because it is easy to apply, requires little additional experimentation, and produces higher-precision results and more reliable uncertainty estimates than assuming homoskedasticity. Copyright © 2016 Elsevier B.V. All rights reserved.

Plasma beta-endorphin levels in obese and non-obese patients with polycystic ovary disease.

PubMed

Martínez-Guisasola, J; Guerrero, M; Alonso, F; Díaz, F; Cordero, J; Ferrer, J

2001-02-01

The aim of this study was to determine the influence of body weight on circulating plasma levels of beta-endorphin and insulin in women with polycystic ovary disease (PCOD), as well as the correlation between the plasma levels of beta-endorphin and insulin. One-hundred and sixty-seven consecutive subjects with PCOD were recruited, 117 of whom had normal weight (body mass index (BMI) < 25) while 50 were obese (BMI > 25). A venous blood sample was taken and plasma concentrations of beta-endorphin, insulin, gonadotropins, prolactin, progesterone, 17 beta-estradiol, estrone, androgens, dehydroepiandrosterone sulfate and sex hormone-binding globulin (SHBG) were measured. Mean beta-endorphin and insulin plasma levels were significantly higher (p < 0.05) in obese PCOD women than in non-obese ones. Correlation analysis showed a positive association between insulin and beta-endorphin, beta-endorphin and BMI (and weight), insulin and BMI (and weight), and a negative correlation was found between insulin and SHBG. A weak association was found between beta-endorphin and luteinizing hormone (LH) in peripheral plasma. Stratified and linear regression analysis showed that plasma beta-endorphin concentrations correlate more with BMI than with insulinemia.

Diagnosis of intrauterine growth restriction: comparison of ultrasound parameters.

PubMed

Ott, William J

2002-04-01

The objective of this study is an attempt to evaluate the best ultrasonic method of diagnosing intrauterine growth restriction (IUGR); a retrospective study of patients with singleton pregnancies who had been scanned at the author's institution within 2 weeks of their delivery was undertaken. Estimated fetal weight, abdominal circumference, head circumference/abdominal circumference ratio, abdominal circumference/femur length ratio, and umbilical artery S/D ratio were compared for accuracy in prediction IUGR in the neonate using both univariant and multivariant statistical analysis. Five hundred one (501) patients were analyzed. One hundred fourteen (114) neonates were classified as IUGR (22.8%). Doppler evaluation of the umbilical artery showed the best sensitivity while both abdominal circumference alone and estimated fetal weight showed similar specificity, positive and negative predictive value, and lowest false-positive and -negative results. Logistic regression analysis confirmed the univariant results and showed that, when used in combination, abdominal circumference and Doppler, or estimated fetal weight and Doppler resulted in the best predictive values. Either estimated fetal weight or abdominal circumference (alone) are accurate predictors of IUGR. Combined with Doppler studies of the umbilical artery either method will provide accurate evaluation of suspected IUGR.

Statistical Optimality in Multipartite Ranking and Ordinal Regression.

PubMed

Uematsu, Kazuki; Lee, Yoonkyung

2015-05-01

Statistical optimality in multipartite ranking is investigated as an extension of bipartite ranking. We consider the optimality of ranking algorithms through minimization of the theoretical risk which combines pairwise ranking errors of ordinal categories with differential ranking costs. The extension shows that for a certain class of convex loss functions including exponential loss, the optimal ranking function can be represented as a ratio of weighted conditional probability of upper categories to lower categories, where the weights are given by the misranking costs. This result also bridges traditional ranking methods such as proportional odds model in statistics with various ranking algorithms in machine learning. Further, the analysis of multipartite ranking with different costs provides a new perspective on non-smooth list-wise ranking measures such as the discounted cumulative gain and preference learning. We illustrate our findings with simulation study and real data analysis.

Prognostic value of perfusion-weighted magnetic resonance imaging in acute intracerebral hemorrhage.

PubMed

Hu, Xibin; Bai, Xueqin; Zai, Ning; Sun, Xinhai; Zhu, Laimin; Li, Xian

2016-07-01

This study intends to investigate the prognostic value of perfusion-weighted magnetic resonance imaging in acute intracerebral hemorrhage. Demographic, clinical and biochemical data between acute intracerebral hemorrhage (AICH) and healthy volunteer groups were assessed in this study, such as rCBV and MTT values. The optimal cutoff values of rCBV and MTT for diagnosing AICH were determined by the ROC curves. Apart from that, we also investigated the association between rCBV/MTT values and cerebral hematoma volumes of AICH patients. The unconditional logistic regression was conducted to determine significant risk factors for AICH. AICH patients have significantly lower rCBV and higher MTT compared to the control group (all P < 0.05). As suggested by the relatively high sensitivity and specificity, both rCBV and MTT values could be utilized for AICH diagnosis. Moreover, rCBV and MTT were significantly associated with the cerebral hematoma volumes of AICH patients (all P < 0.05). Results from unconditional logistic regression analysis revealed that MTT was a significant risk factor for AICH (P < 0.05 and OR > 1), while rCBV is considered as a protective factor (P < 0.05 and OR < 1). Perfusion-weighted magnetic resonance imaging produces a high prognostic value for diagnosing AICH.

Preliminary bioelectrical impedance analysis (BIA) equation for body composition assessment in young females from Colombia

NASA Astrophysics Data System (ADS)

Caicedo-Eraso, J. C.; González-Correa, C. H.; González-Correa, C. A.

2013-04-01

A previous study showed that reported BIA equations for body composition are not suitable for Colombian population. The purpose of this study was to develop and validate a preliminary BIA equation for body composition assessment in young females from Colombia, using hydrodensitometry as reference method. A sample of 30 young females was evaluated. Inclusion and exclusion criteria were defined to minimize the variability of BIA. Height, weight, BIA, residual lung volume (RV) and underwater weight (UWW) were measured. A preliminary BIA equation was developed (r2 = 0.72, SEE = 2.48 kg) by stepwise multiple regression with fat-free mass (FFM) as dependent variable and weight, height and impedance measurements as independent variables. The quality of regression was evaluated and a cross-validation against 50% of sample confirmed that results obtained with the preliminary BIA equation is interchangeable with results obtained with hydrodensitometry (r2 = 0.84, SEE = 2.62 kg). The preliminary BIA equation can be used for body composition assessment in young females from Colombia until a definitive equation is developed. The next step will be increasing the sample, including a second reference method, as deuterium oxide dilution (D2O), and using multi-frequency BIA (MF-BIA). It would also be desirable to develop equations for males and other ethnic groups in Colombia.

Lean Mass Loss Is Associated with Low Protein Intake during Dietary-Induced Weight Loss in Postmenopausal Women

PubMed Central

BOPP, MELANIE J.; HOUSTON, DENISE K.; LENCHIK, LEON; EASTER, LINDA; KRITCHEVSKY, STEPHEN B.; NICKLAS, BARBARA J.

2013-01-01

The health and quality-of-life implications of overweight and obesity span all ages in the United States. We investigated the association between dietary protein intake and loss of lean mass during weight loss in postmenopausal women through a retrospective analysis of a 20-week randomized, controlled diet and exercise intervention in women aged 50 to 70 years. Weight loss was achieved by differing levels of caloric restriction and exercise. The diet-only group reduced caloric intake by 2,800 kcal/week, and the exercise groups reduced caloric intake by 2,400 kcal/week and expended ~400 kcal/week through aerobic exercise. Total and appendicular lean mass was measured using dual energy x-ray absorptiometry. Linear regression analysis was used to examine the association between changes in lean mass and appendicular lean mass and dietary protein intake. Average weight loss was 10.8±4.0 kg, with an average of 32% of total weight lost as lean mass. Protein intake averaged 0.62 g/kg body weight/day (range=0.47 to 0.8 g/kg body weight/day). Participants who consumed higher amounts of dietary protein lost less lean mass and appendicular lean mass r(=0.3, P=0.01 and r=0.41, P<0.001, respectively). These associations remained significant after adjusting for intervention group and body size. Therefore, inadequate protein intake during caloric restriction may be associated with adverse body-composition changes in postmenopausal women. PMID:18589032

Guidance for deriving and presenting percentage study weights in meta-analysis of test accuracy studies.

PubMed

Burke, Danielle L; Ensor, Joie; Snell, Kym I E; van der Windt, Danielle; Riley, Richard D

2018-06-01

Percentage study weights in meta-analysis reveal the contribution of each study toward the overall summary results and are especially important when some studies are considered outliers or at high risk of bias. In meta-analyses of test accuracy reviews, such as a bivariate meta-analysis of sensitivity and specificity, the percentage study weights are not currently derived. Rather, the focus is on representing the precision of study estimates on receiver operating characteristic plots by scaling the points relative to the study sample size or to their standard error. In this article, we recommend that researchers should also provide the percentage study weights directly, and we propose a method to derive them based on a decomposition of Fisher information matrix. This method also generalises to a bivariate meta-regression so that percentage study weights can also be derived for estimates of study-level modifiers of test accuracy. Application is made to two meta-analyses examining test accuracy: one of ear temperature for diagnosis of fever in children and the other of positron emission tomography for diagnosis of Alzheimer's disease. These highlight that the percentage study weights provide important information that is otherwise hidden if the presentation only focuses on precision based on sample size or standard errors. Software code is provided for Stata, and we suggest that our proposed percentage weights should be routinely added on forest and receiver operating characteristic plots for sensitivity and specificity, to provide transparency of the contribution of each study toward the results. This has implications for the PRISMA-diagnostic test accuracy guidelines that are currently being produced. Copyright © 2017 John Wiley & Sons, Ltd.

Parenchymal texture measures weighted by breast anatomy: preliminary optimization in a case-control study

NASA Astrophysics Data System (ADS)

Gastounioti, Aimilia; Keller, Brad M.; Hsieh, Meng-Kang; Conant, Emily F.; Kontos, Despina

2016-03-01

Growing evidence suggests that quantitative descriptors of the parenchymal texture patterns hold a valuable role in assessing an individual woman's risk for breast cancer. In this work, we assess the hypothesis that breast cancer risk factors are not uniformly expressed in the breast parenchymal tissue and, therefore, breast-anatomy-weighted parenchymal texture descriptors, where different breasts ROIs have non uniform contributions, may enhance breast cancer risk assessment. To this end, we introduce an automated breast-anatomy-driven methodology which generates a breast atlas, which is then used to produce a weight map that reinforces the contributions of the central and upper-outer breast areas. We incorporate this methodology to our previously validated lattice-based strategy for parenchymal texture analysis. In the framework of a pilot case-control study, including digital mammograms from 424 women, our proposed breast-anatomy-weighted texture descriptors are optimized and evaluated against non weighted texture features, using regression analysis with leave-one-out cross validation. The classification performance is assessed in terms of the area under the curve (AUC) of the receiver operating characteristic. The collective discriminatory capacity of the weighted texture features was maximized (AUC=0.87) when the central breast area was considered more important than the upperouter area, with significant performance improvement (DeLong's test, p-value<0.05) against the non-weighted texture features (AUC=0.82). Our results suggest that breast-anatomy-driven methodologies have the potential to further upgrade the promising role of parenchymal texture analysis in breast cancer risk assessment and may serve as a reference in the design of future studies towards image-driven personalized recommendations regarding women's cancer risk evaluation.

Is the economic crisis affecting birth outcome in Spain? Evaluation of temporal trend in underweight at birth (2003-2012).

PubMed

Varea, Carlos; Terán, José Manuel; Bernis, Cristina; Bogin, Barry; González-González, Antonio

2016-01-01

There is growing evidence of the impact of the current European economic crisis on health. In Spain, since 2008, there have been increasing levels of impoverishment and inequality, and important cuts in social services. The objective is to evaluate the impact of the economic crisis on underweight at birth in Spain. Trends in underweight at birth were examined between 2003 and 2012. Underweight at birth is defined as a singleton, term neonatal weight lesser than -2 SD from the median weight at birth for each sex estimated by the WHO Standard Growth Reference. Using data from the Statistical Bulletin of Childbirth, 2 933 485 live births born to Spanish mothers have been analysed. Descriptive analysis, seasonal decomposition analysis and crude and adjusted logistic regression including individual maternal and foetal variables as well as exogenous economic indicators have been performed. Results demonstrate a significant increase in the prevalence of underweight at birth from 2008. All maternal-foetal categories were affected, including those showing the lowest prevalence before the crisis. In the full adjusted logistic regression, year-on-year GDP per capita remains predictive on underweight at birth risk. Previous trends in maternal socio-demographic profiles and a direct impact of the crisis are discussed to explain the trends described.

Spatial patterns and origins of heavy metals in Sheyang River catchment in Jiangsu, China based on geographically weighted regression.

PubMed

Wu, Shan-Shan; Yang, Hao; Guo, Fei; Han, Rui-Ming

2017-02-15

Multivariate statistical analyses combined with geographically weighted regression (GWR) were used to identify spatial variations of heavy metals in sediments and to examine relationships between metal pollution and land use practices in watersheds, including urban land, agriculture land, forest and water bodies. Seven metals (Cu, Zn, Pb, Cr, Ni, Mn and Fe) of sediments were measured at 31 sampling sites in Sheyang River. Most metals were under a certain degree enrichment based on the enrichment factors. Cluster analysis grouped all sites into four statistically significant cluster, severely contaminated areas were concentrated in areas with intensive human activities. Correlation analysis and PCA indicated Cu, Zn and Pb were derived from anthropogenic activities, while the sources of Cr and Ni were complicated. However, Fe and Mn originated from natural sources. According to results of GWR, there are stronger association between metal pollution with urban land than agricultural land and forest. Moreover, the relationships between land use and metal concentration were affected by the urbanization level of watersheds. Agricultural land had a weak associated with heavy metal pollution and the relationships might be stronger in less-urbanized. This study provided useful information for the assessment and management of heavy metal hazards in studied area. Copyright © 2016 Elsevier B.V. All rights reserved.

Factors predicting weight-bearing asymmetry 1month after unilateral total knee arthroplasty: a cross-sectional study.

PubMed

Christiansen, Cory L; Bade, Michael J; Weitzenkamp, David A; Stevens-Lapsley, Jennifer E

2013-03-01

Factors predicting weight-bearing asymmetry (WBA) after unilateral total knee arthroplasty (TKA) are not known. However, identifying modifiable and non-modifiable predictors of WBA is needed to optimize rehabilitation, especially since WBA is negatively correlated to poor functional performance. The purpose of this study was to identify factors predictive of WBA during sit-stand transitions for people 1month following unilateral TKA. Fifty-nine people were tested preoperatively and 1month following unilateral TKA for WBA using average vertical ground reaction force under each foot during the Five Times Sit-to-Stand Test. Candidate variables tested in the regression analysis represented physical impairments (strength, muscle activation, pain, and motion), demographics, anthropometrics, and movement compensations. WBA, measured as the ratio of surgical/non-surgical limb vertical ground reaction force, was 0.69 (0.18) (mean (SD)) 1month after TKA. Regression analysis identified preoperative WBA (β=0.40), quadriceps strength ratio (β=0.31), and hamstrings strength ratio (β=0.19) as factors predictive of WBA 1month after TKA (R(2)=0.30). Greater amounts of WBA 1month after TKA are predicted by modifiable factors including habitual movement pattern and asymmetry in quadriceps and hamstrings strength. Copyright © 2012 Elsevier B.V. All rights reserved.

Random forest regression for magnetic resonance image synthesis.

PubMed

Jog, Amod; Carass, Aaron; Roy, Snehashis; Pham, Dzung L; Prince, Jerry L

2017-01-01

By choosing different pulse sequences and their parameters, magnetic resonance imaging (MRI) can generate a large variety of tissue contrasts. This very flexibility, however, can yield inconsistencies with MRI acquisitions across datasets or scanning sessions that can in turn cause inconsistent automated image analysis. Although image synthesis of MR images has been shown to be helpful in addressing this problem, an inability to synthesize both T 2 -weighted brain images that include the skull and FLuid Attenuated Inversion Recovery (FLAIR) images has been reported. The method described herein, called REPLICA, addresses these limitations. REPLICA is a supervised random forest image synthesis approach that learns a nonlinear regression to predict intensities of alternate tissue contrasts given specific input tissue contrasts. Experimental results include direct image comparisons between synthetic and real images, results from image analysis tasks on both synthetic and real images, and comparison against other state-of-the-art image synthesis methods. REPLICA is computationally fast, and is shown to be comparable to other methods on tasks they are able to perform. Additionally REPLICA has the capability to synthesize both T 2 -weighted images of the full head and FLAIR images, and perform intensity standardization between different imaging datasets. Copyright © 2016 Elsevier B.V. All rights reserved.

Plan View Pattern Control for Steel Plates through Constrained Locally Weighted Regression

NASA Astrophysics Data System (ADS)

Shigemori, Hiroyasu; Nambu, Koji; Nagao, Ryo; Araki, Tadashi; Mizushima, Narihito; Kano, Manabu; Hasebe, Shinji

A technique for performing parameter identification in a locally weighted regression model using foresight information on the physical properties of the object of interest as constraints was proposed. This method was applied to plan view pattern control of steel plates, and a reduction of shape nonconformity (crop) at the plate head end was confirmed by computer simulation based on real operation data.

Using data mining to predict success in a weight loss trial.

PubMed

Batterham, M; Tapsell, L; Charlton, K; O'Shea, J; Thorne, R

2017-08-01

Traditional methods for predicting weight loss success use regression approaches, which make the assumption that the relationships between the independent and dependent (or logit of the dependent) variable are linear. The aim of the present study was to investigate the relationship between common demographic and early weight loss variables to predict weight loss success at 12 months without making this assumption. Data mining methods (decision trees, generalised additive models and multivariate adaptive regression splines), in addition to logistic regression, were employed to predict: (i) weight loss success (defined as ≥5%) at the end of a 12-month dietary intervention using demographic variables [body mass index (BMI), sex and age]; percentage weight loss at 1 month; and (iii) the difference between actual and predicted weight loss using an energy balance model. The methods were compared by assessing model parsimony and the area under the curve (AUC). The decision tree provided the most clinically useful model and had a good accuracy (AUC 0.720 95% confidence interval = 0.600-0.840). Percentage weight loss at 1 month (≥0.75%) was the strongest predictor for successful weight loss. Within those individuals losing ≥0.75%, individuals with a BMI (≥27 kg m -2 ) were more likely to be successful than those with a BMI between 25 and 27 kg m -2 . Data mining methods can provide a more accurate way of assessing relationships when conventional assumptions are not met. In the present study, a decision tree provided the most parsimonious model. Given that early weight loss cannot be predicted before randomisation, incorporating this information into a post randomisation trial design may give better weight loss results. © 2017 The British Dietetic Association Ltd.

DETECTION OF MALNUTRITION IN PATIENTS UNDERGOING MAINTENANCE HAEMODIALYSIS: A QUANTITATIVE DATA ANALYSIS ON 12 PARAMETERS.

PubMed

Nafzger, Sonja; Fleury, Lea-Angelica; Uehlinger, Dominik E; Plüss, Petra; Scura, Ninetta; Kurmann, Silvia

2015-09-01

Protein-energy-malnutrition (PEM) is common in people with end stage kidney disease (ESKD) undergoing maintenance haemodialysis (MHD) and correlates strongly with mortality. To this day, there is no gold standard for detecting PEM in patients on MHD. The aim of this study was to evaluate if Nutritional Risk Screening 2002 (NRS-2002), handgrip strength measurement, mid-upper arm muscle area (MUAMA), triceps skin fold measurement (TSF), serum albumin, normalised protein catabolic rate (nPCR), Kt/V and eKt/V, dry body weight, body mass index (BMI), age and time since start on MHD are relevant for assessing PEM in patients on MHD. The predictive value of the selected parameters on mortality and mortality or weight loss of more than 5% was assessed. Quantitative data analysis of the 12 parameters in the same patients on MHD in autumn 2009 (n = 64) and spring 2011 (n = 40) with paired statistical analysis and multivariate logistic regression analysis was performed. Paired data analysis showed significant reduction of dry body weight, BMI and nPCR. Kt/Vtot did not change, eKt/v and hand grip strength measurements were significantly higher in spring 2011. No changes were detected in TSF, serum albumin, NRS-2002 and MUAMA. Serum albumin was shown to be the only predictor of death and of the combined endpoint "death or weight loss of more than 5%". We now screen patients biannually for serum albumin, nPCR, Kt/V, handgrip measurement of the shunt-free arm, dry body weight, age and time since initiation of MHD. © 2015 European Dialysis and Transplant Nurses Association/European Renal Care Association.

Do climate variables and human density affect Achatina fulica (Bowditch) (Gastropoda: Pulmonata) shell length, total weight and condition factor?

PubMed

Albuquerque, F S; Peso-Aguiar, M C; Assunção-Albuquerque, M J T; Gálvez, L

2009-08-01

The length-weight relationship and condition factor have been broadly investigated in snails to obtain the index of physical condition of populations and evaluate habitat quality. Herein, our goal was to describe the best predictors that explain Achatina fulica biometrical parameters and well being in a recently introduced population. From November 2001 to November 2002, monthly snail samples were collected in Lauro de Freitas City, Bahia, Brazil. Shell length and total weight were measured in the laboratory and the potential curve and condition factor were calculated. Five environmental variables were considered: temperature range, mean temperature, humidity, precipitation and human density. Multiple regressions were used to generate models including multiple predictors, via model selection approach, and then ranked with AIC criteria. Partial regressions were used to obtain the separated coefficients of determination of climate and human density models. A total of 1.460 individuals were collected, presenting a shell length range between 4.8 to 102.5 mm (mean: 42.18 mm). The relationship between total length and total weight revealed that Achatina fulica presented a negative allometric growth. Simple regression indicated that humidity has a significant influence on A. fulica total length and weight. Temperature range was the main variable that influenced the condition factor. Multiple regressions showed that climatic and human variables explain a small proportion of the variance in shell length and total weight, but may explain up to 55.7% of the condition factor variance. Consequently, we believe that the well being and biometric parameters of A. fulica can be influenced by climatic and human density factors.

Unhealthy and healthy weight control behaviours among bus operators.

PubMed

Escoto, K H; French, S A

2012-03-01

Urban bus operators are an occupational group with high rates of overweight and obesity. Understanding methods bus operators use for weight control may be important; there may be increased risk for these workers to engage in less healthy weight management behaviours due to stressful working conditions. To examine the prevalence of unhealthy and healthy weight control behaviours used by bus operators and examine associations between use of unhealthy weight control behaviours and work-related and sociodemographic variables. Bus operators from four different transit garages were invited to complete a self-administered survey; height and weight were measured by research staff. Unhealthy and healthy weight control behaviours, work hours, work schedule and social support were measured with self-report items on the employee survey. Logistic regression analysis was conducted to estimate associations. Nearly 60% of bus operators endorsed at least one unhealthy method; over 50% reported skipping meals, 30% fasted and 10% reported taking diet pills in the past year. Bus operator gender, race, body mass index status and hours worked per week showed significant associations with using at least one unhealthy weight control behaviour. Worksite interventions should emphasize the benefit of healthy eating and physical activity but should also address the use of less healthy methods for weight control for individuals employed in transportation occupations.

Quantitative trait loci that control body weight in DDD/Sgn and C57BL/6J inbred mice.

PubMed

Suto, Jun-Ichi; Kojima, Misaki

2017-02-01

Inbred DDD/Sgn mice are heavier than inbred C57BL/6J mice. In the present study, we performed quantitative trait loci (QTL) mapping for body weight using R/qtl in reciprocal F 2 male populations between the two strains. We identified four significant QTL on Chrs 1, 2, 5, and 17 (proximal region). The DDD/Sgn allele was associated with increased body weight at QTL on Chrs 1 and 5, and the DDD/Sgn allele was associated with decreased body weight at QTL on Chrs 2 and 17. A multiple regression analysis indicated that the detected QTL explain 30.94 % of the body weight variation. Because DDD/Sgn male mice have extremely high levels of circulating testosterone relative to other inbred mouse strains, we performed QTL mapping for plasma testosterone level to examine the effect of testosterone levels on body weight. We identified one suggestive QTL on Chr 5, which overlapped with body weight QTL. The DDD/Sgn allele was associated with increased testosterone level. Thus, we confirmed that there was a genetic basis for the changes in body weight and testosterone levels in male mice. These findings provide insights into the genetic mechanism by which body weight is controlled in male mice.

A Deformable Atlas of the Laboratory Mouse

PubMed Central

Wang, Hongkai; Stout, David B.; Chatziioannou, Arion F.

2015-01-01

Purpose This paper presents a deformable mouse atlas of the laboratory mouse anatomy. This atlas is fully articulated and can be positioned into arbitrary body poses. The atlas can also adapt body weight by changing body length and fat amount. Procedures A training set of 103 micro-CT images was used to construct the atlas. A cage-based deformation method was applied to realize the articulated pose change. The weight-related body deformation was learned from the training set using a linear regression method. A conditional Gaussian model and thin-plate spline mapping were used to deform the internal organs following the changes of pose and weight. Results The atlas was deformed into different body poses and weights, and the deformation results were more realistic compared to the results achieved with other mouse atlases. The organ weights of this atlas matched well with the measurements of real mouse organ weights. This atlas can also be converted into voxelized images with labeled organs, pseudo CT images and tetrahedral mesh for phantom studies. Conclusions With the unique ability of articulated pose and weight changes, the deformable laboratory mouse atlas can become a valuable tool for preclinical image analysis. PMID:25049072

Meal patterns among children and adolescents and their associations with weight status and parental characteristics.

PubMed

Würbach, Ariane; Zellner, Konrad; Kromeyer-Hauschild, Katrin

2009-08-01

To describe the meal patterns of Jena schoolchildren and their associations with children's weight status and parental characteristics. Cross-sectional study. Twenty schools in Jena (100,000 inhabitants), south-east Germany. A total of 2054 schoolchildren aged 7-14 years with information on BMI standard deviation score (BMI-SDS) and weight status (based on German reference values), of whom 1571 had additional information about their parents (parental education and employment status, weight status according to WHO guidelines) and meal patterns (school lunch participation rate, meal frequencies, breakfast consumption and frequency of family meals). Weight status of the children was associated with weight status, education and employment status of the parents. Meal patterns were strongly dependent on children's age and parental employment. As age increased, the frequency of meal consumption, participation rate in school lunches and the number of family meals decreased. Using linear regression analysis, a high inverse association between BMI-SDS and meal frequency was observed, in addition to relationships with parental weight status and paternal education. Age-specific prevention programmes should encourage greater meal frequency. The close involvement of parents is essential in any strategy for improving children's (families') diets.

Improving the accuracy of hyaluronic acid molecular weight estimation by conventional size exclusion chromatography.

PubMed

Shanmuga Doss, Sreeja; Bhatt, Nirav Pravinbhai; Jayaraman, Guhan

2017-08-15

There is an unreasonably high variation in the literature reports on molecular weight of hyaluronic acid (HA) estimated using conventional size exclusion chromatography (SEC). This variation is most likely due to errors in estimation. Working with commercially available HA molecular weight standards, this work examines the extent of error in molecular weight estimation due to two factors: use of non-HA based calibration and concentration of sample injected into the SEC column. We develop a multivariate regression correlation to correct for concentration effect. Our analysis showed that, SEC calibration based on non-HA standards like polyethylene oxide and pullulan led to approximately 2 and 10 times overestimation, respectively, when compared to HA-based calibration. Further, we found that injected sample concentration has an effect on molecular weight estimation. Even at 1g/l injected sample concentration, HA molecular weight standards of 0.7 and 1.64MDa showed appreciable underestimation of 11-24%. The multivariate correlation developed was found to reduce error in estimations at 1g/l to <4%. The correlation was also successfully applied to accurately estimate the molecular weight of HA produced by a recombinant Lactococcus lactis fermentation. Copyright © 2017 Elsevier B.V. All rights reserved.

Resistance of nickel-chromium-aluminum alloys to cyclic oxidation at 1100 C and 1200 C

NASA Technical Reports Server (NTRS)

Barrett, C. A.; Lowell, C. E.

1976-01-01

Nickel-rich alloys in the Ni-Cr-Al system were evaluated for cyclic oxidation resistance in still air at 1,100 and 1,200 C. A first approximation oxidation attack parameter Ka was derived from specific weight change data involving both a scaling growth constant and a spalling constant. An estimating equation was derived with Ka as a function of the Cr and Al content by multiple linear regression and translated into countour ternary diagrams showing regions of minimum attack. An additional factor inferred from the regression analysis was that alloys melted in zirconia crucibles had significantly greater oxidation resistance than comparable alloys melted otherwise.

Improving Space Project Cost Estimating with Engineering Management Variables

NASA Technical Reports Server (NTRS)

Hamaker, Joseph W.; Roth, Axel (Technical Monitor)

2001-01-01

Current space project cost models attempt to predict space flight project cost via regression equations, which relate the cost of projects to technical performance metrics (e.g. weight, thrust, power, pointing accuracy, etc.). This paper examines the introduction of engineering management parameters to the set of explanatory variables. A number of specific engineering management variables are considered and exploratory regression analysis is performed to determine if there is statistical evidence for cost effects apart from technical aspects of the projects. It is concluded that there are other non-technical effects at work and that further research is warranted to determine if it can be shown that these cost effects are definitely related to engineering management.

Egg production of turbot, Scophthalmus maximus, in the Baltic Sea

NASA Astrophysics Data System (ADS)

Nissling, Anders; Florin, Ann-Britt; Thorsen, Anders; Bergström, Ulf

2013-11-01

In the brackish water Baltic Sea turbot spawn at ~ 6-9 psu along the coast and on offshore banks in ICES SD 24-29, with salinity influencing the reproductive success. The potential fecundity (the stock of vitellogenic oocytes in the pre-spawning ovary), egg size (diameter and dry weight of artificially fertilized 1-day-old eggs) and gonad dry weight were assessed for fish sampled in SD 25 and SD 28. Multiple regression analysis identified somatic weight, or total length in combination with Fulton's condition factor, as main predictors of fecundity and gonad dry weight with stage of maturity (oocyte packing density or leading cohort) as an additional predictor. For egg size, somatic weight was identified as main predictor while otolith weight (proxy for age) was an additional predictor. Univariate analysis using GLM revealed significantly higher fecundity and gonad dry weight for turbot from SD 28 (3378-3474 oocytes/g somatic weight) compared to those from SD 25 (2343 oocytes/g somatic weight), with no difference in egg size (1.05 ± 0.03 mm diameter and 46.8 ± 6.5 μg dry weight; mean ± sd). The difference in egg production matched egg survival probabilities in relation to salinity conditions suggesting selection for higher fecundity as a consequence of poorer reproductive success at lower salinities. This supports the hypothesis of higher size-specific fecundity towards the limit of the distribution of a species as an adaptation to harsher environmental conditions and lower offspring survival probabilities. Within SD 28 comparisons were made between two major fishing areas targeting spawning aggregations and a marine protected area without fishing. The outcome was inconclusive and is discussed with respect to potential fishery induced effects, effects of the salinity gradient, effects of specific year-classes, and effects of maturation status of sampled fish.

Geographically weighted regression and geostatistical techniques to construct the geogenic radon potential map of the Lazio region: A methodological proposal for the European Atlas of Natural Radiation.

PubMed

Ciotoli, G; Voltaggio, M; Tuccimei, P; Soligo, M; Pasculli, A; Beaubien, S E; Bigi, S

2017-01-01

In many countries, assessment programmes are carried out to identify areas where people may be exposed to high radon levels. These programmes often involve detailed mapping, followed by spatial interpolation and extrapolation of the results based on the correlation of indoor radon values with other parameters (e.g., lithology, permeability and airborne total gamma radiation) to optimise the radon hazard maps at the municipal and/or regional scale. In the present work, Geographical Weighted Regression and geostatistics are used to estimate the Geogenic Radon Potential (GRP) of the Lazio Region, assuming that the radon risk only depends on the geological and environmental characteristics of the study area. A wide geodatabase has been organised including about 8000 samples of soil-gas radon, as well as other proxy variables, such as radium and uranium content of homogeneous geological units, rock permeability, and faults and topography often associated with radon production/migration in the shallow environment. All these data have been processed in a Geographic Information System (GIS) using geospatial analysis and geostatistics to produce base thematic maps in a 1000 m × 1000 m grid format. Global Ordinary Least Squared (OLS) regression and local Geographical Weighted Regression (GWR) have been applied and compared assuming that the relationships between radon activities and the environmental variables are not spatially stationary, but vary locally according to the GRP. The spatial regression model has been elaborated considering soil-gas radon concentrations as the response variable and developing proxy variables as predictors through the use of a training dataset. Then a validation procedure was used to predict soil-gas radon values using a test dataset. Finally, the predicted values were interpolated using the kriging algorithm to obtain the GRP map of the Lazio region. The map shows some high GRP areas corresponding to the volcanic terrains (central-northern sector of Lazio region) and to faulted and fractured carbonate rocks (central-southern and eastern sectors of the Lazio region). This typical local variability of autocorrelated phenomena can only be taken into account by using local methods for spatial data analysis. The constructed GRP map can be a useful tool to implement radon policies at both the national and local levels, providing critical data for land use and planning purposes. Copyright © 2016 Elsevier Ltd. All rights reserved.

Maternal autonomy and low birth weight in India.

PubMed

Chakraborty, Priyanka; Anderson, Alex K

2011-09-01

The prevalence of low birth weight (LBW) is a major public health issue in India (30.0%) and is the highest among South-Asian countries. Maternal autonomy or the mother's status in the household indicates her decision-making power with respect to movement, finance, healthcare use, and other household activities. Evidence suggests that autonomy of the mother is significantly associated with the child's nutritional status. Although previous studies in India reported the determinants of LBW, literature on the association between mother's autonomy and birth weight are lacking. This study, therefore, aims to examine the influence of maternal autonomy on birth weight of the newborn. The study, a secondary data analysis, examined data from the 2005-2006 National Health and Family Survey (NFHS 3) of India. A maternal autonomy score was created through proximal component factor analysis and categorized as high, medium, and low autonomy levels. The main outcome variable included birth weight of the index child obtained from health cards and mother's recall. Descriptive and logistic regression analyses were performed. Results from the study indicate that 20.0% of the index children included in the analysis were born at LBW. Low maternal autonomy was an independent predictor of LBW (odds ratio [OR] 1.28, 95% confidence interval [CI] 1.07-1.53, p=0.007) after adjusting for other factors, and medium autonomy level was not significant. These findings clearly indicate the importance of empowering women in India to combat the high incidence of LBW.

Prospective relationships between body weight and physical activity: an observational analysis from the NAVIGATOR study.

PubMed

Preiss, David; Thomas, Laine E; Wojdyla, Daniel M; Haffner, Steven M; Gill, Jason M R; Yates, Thomas; Davies, Melanie J; Holman, Rury R; McMurray, John J; Califf, Robert M; Kraus, William E

2015-08-14

While bidirectional relationships exist between body weight and physical activity, direction of causality remains uncertain and previous studies have been limited by self-reported activity or weight and small sample size. We investigated the prospective relationships between weight and physical activity. Observational analysis of data from the Nateglinide And Valsartan in Impaired Glucose Tolerance Outcomes Research (NAVIGATOR) study, a double-blinded randomised clinical trial of nateglinide and valsartan, respectively. Multinational study of 9306 participants. Participants with biochemically confirmed impaired glucose tolerance had annual measurements of both weight and step count using research grade pedometers, worn for 7 days consecutively. Along with randomisation to valsartan or placebo plus nateglinide or placebo, participants took part in a lifestyle modification programme. Longitudinal regression using weight as response value and physical activity as predictor value was conducted, adjusted for baseline covariates. Analysis was then repeated with physical activity as response value and weight as predictor value. Only participants with a response value preceded by at least three annual response values were included. Adequate data were available for 2811 (30%) of NAVIGATOR participants. Previous weight (χ(2)=16.8; p<0.0001), but not change in weight (χ(2)=0.1; p=0.71) was inversely associated with subsequent step count, indicating lower subsequent levels of physical activity in heavier individuals. Change in step count (χ(2)=5.9; p=0.02) but not previous step count (χ(2)=0.9; p=0.34) was inversely associated with subsequent weight. However, in the context of trajectories already established for weight (χ(2) for previous weight measurements 747.3; p<0.0001) and physical activity (χ(2) for previous step count 432.6; p<0.0001), these effects were of limited clinical importance. While a prospective bidirectional relationship was observed between weight and physical activity, the magnitude of any effect was very small in the context of natural trajectories already established for these variables. NCT00097786. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Radiographic changes and factors associated with subsequent progression of damage in weight-bearing joints of patients with rheumatoid arthritis under TNF-blocking therapies-three-year observational study.

PubMed

Matsushita, Isao; Motomura, Hiraku; Seki, Eiko; Kimura, Tomoatsu

2017-07-01

The long-term effects of tumor necrosis factor (TNF)-blocking therapies on weight-bearing joints in patients with rheumatoid arthritis (RA) have not been fully characterized. The purpose of this study was to assess the radiographic changes of weight-bearing joints in patients with RA during 3-year of TNF-blocking therapies and to identify factors related to the progression of joint damage. Changes in clinical variables and radiological findings in 243 weight-bearing joints (63 hips, 54 knees, 71 ankles, and 55 subtalar joints) in 38 consecutive patients were investigated during three years of treatment with TNF-blocking agents. Multivariate logistic regression analysis was used to identify risk factors for the progression of weight-bearing joint damage. Seventeen (14.5%) of proximal weight-bearing joints (hips and knees) showed apparent radiographic progression during three years of treatment, whereas none of the proximal weight-bearing joints showed radiographic evidence of improvement or repair. In contrast, distal weight-bearing joints (ankle and subtalar joints) displayed radiographic progression and improvement in 20 (15.9%) and 8 (6.3%) joints, respectively. Multivariate logistic analysis for proximal weight-bearing joints identified the baseline Larsen grade (p < 0.001, OR:24.85, 95%CI: 5.07-121.79) and disease activity at one year after treatment (p = 0.003, OR:3.34, 95%CI:1.50-7.46) as independent factors associated with the progression of joint damage. On the other hand, multivariate analysis for distal weight-bearing joints identified disease activity at one year after treatment (p < 0.001, OR:2.13, 95%CI:1.43-3.18) as an independent factor related to the progression of damage. Baseline Larsen grade was strongly associated with the progression of damage in the proximal weight-bearing joints. Disease activity after treatment was an independent factor for progression of damage in proximal and distal weight-bearing joints. Early treatment with TNF-blocking agents and tight control of disease activity are necessary to prevent the progression of damage of the weight-bearing joints.

Dose-Dependent Effects of Statins for Patients with Aneurysmal Subarachnoid Hemorrhage: Meta-Regression Analysis.

PubMed

To, Minh-Son; Prakash, Shivesh; Poonnoose, Santosh I; Bihari, Shailesh

2018-05-01

The study uses meta-regression analysis to quantify the dose-dependent effects of statin pharmacotherapy on vasospasm, delayed ischemic neurologic deficits (DIND), and mortality in aneurysmal subarachnoid hemorrhage. Prospective, retrospective observational studies, and randomized controlled trials (RCTs) were retrieved by a systematic database search. Summary estimates were expressed as absolute risk (AR) for a given statin dose or control (placebo). Meta-regression using inverse variance weighting and robust variance estimation was performed to assess the effect of statin dose on transformed AR in a random effects model. Dose-dependence of predicted AR with 95% confidence interval (CI) was recovered by using Miller's Freeman-Tukey inverse. The database search and study selection criteria yielded 18 studies (2594 patients) for analysis. These included 12 RCTs, 4 retrospective observational studies, and 2 prospective observational studies. Twelve studies investigated simvastatin, whereas the remaining studies investigated atorvastatin, pravastatin, or pitavastatin, with simvastatin-equivalent doses ranging from 20 to 80 mg. Meta-regression revealed dose-dependent reductions in Freeman-Tukey-transformed AR of vasospasm (slope coefficient -0.00404, 95% CI -0.00720 to -0.00087; P = 0.0321), DIND (slope coefficient -0.00316, 95% CI -0.00586 to -0.00047; P = 0.0392), and mortality (slope coefficient -0.00345, 95% CI -0.00623 to -0.00067; P = 0.0352). The present meta-regression provides weak evidence for dose-dependent reductions in vasospasm, DIND and mortality associated with acute statin use after aneurysmal subarachnoid hemorrhage. However, the analysis was limited by substantial heterogeneity among individual studies. Greater dosing strategies are a potential consideration for future RCTs. Copyright © 2018 Elsevier Inc. All rights reserved.

Maternal dietary intake and pregnancy outcome.

PubMed

Ferland, Suzanne; O'Brien, Huguette Turgeon

2003-02-01

To study the relationship between maternal diet and infant anthropometric measurements in 56 women, aged 28 +/- 5.1 years, with singleton pregnancies. The overall quality of the diet (three 24-hour recalls), including supplementation, was evaluated at 34 +/- 1.3 weeks using a total mean adequacy ratio (TMAR) of 12 nutrients. Specific interviewing techniques were used to minimize social desirability bias. Anthropometric measurements of both parents and maternal lifestyle practices were also obtained. Infant weight, crown-heel length and head circumference were measured 14.6 +/- 4.4 days after birth. Stepwise multiple regression analysis revealed that maternal diet quality (TMAR) was significantly related to infant weight (r = .039, P = .036) and crown-heel length (r = .071, P = .007). Other significant predictors included gestational age, maternal height, sex, smoking and physical activity. Maternal diet was positively associated with infant weight and crown-heel length.

Mass production of polyhedral occlusion bodies of NPV of Helicoverpa armigera in relation to dose, age and larval weight.

PubMed

Narayanan, K; Jayaraj, S

2002-07-01

A significant difference was noticed in the yield of polyhedral occlusion bodies (POBs) in various larval instars of H. armigera when three different doses of the nuclear polyhedrosis virus (NPV) were administered. The yield of POBs from a single larva ranged from 0.35 x 10(6) to 25033.33 x 10(6) with a mean of 18422.33 x 10(6) for fourth instar inoculated. Positive correlation existed between larval weight and number of POBs recovered. The regression analysis indicated POBs recovered responded with predictable manner to the weight of different larval instars and the various concentration of virus administered. The medium lethal time increased in the instars of the larva advanced with a minimum of 3.5 and maximum of 8 days in the first and fifth instars respectively.

Short-term variability in body weight predicts long-term weight gain1

PubMed Central

Lowe, Michael R; Feig, Emily H; Winter, Samantha R; Stice, Eric

2015-01-01

Background: Body weight in lower animals and humans is highly stable despite a very large flux in energy intake and expenditure over time. Conversely, the existence of higher-than-average variability in weight may indicate a disruption in the mechanisms responsible for homeostatic weight regulation. Objective: In a sample chosen for weight-gain proneness, we evaluated whether weight variability over a 6-mo period predicted subsequent weight change from 6 to 24 mo. Design: A total of 171 nonobese women were recruited to participate in this longitudinal study in which weight was measured 4 times over 24 mo. The initial 3 weights were used to calculate weight variability with the use of a root mean square error approach to assess fluctuations in weight independent of trajectory. Linear regression analysis was used to examine whether weight variability in the initial 6 mo predicted weight change 18 mo later. Results: Greater weight variability significantly predicted amount of weight gained. This result was unchanged after control for baseline body mass index (BMI) and BMI change from baseline to 6 mo and for measures of disinhibition, restrained eating, and dieting. Conclusions: Elevated weight variability in young women may signal the degradation of body weight regulatory systems. In an obesogenic environment this may eventuate in accelerated weight gain, particularly in those with a genetic susceptibility toward overweight. Future research is needed to evaluate the reliability of weight variability as a predictor of future weight gain and the sources of its predictive effect. The trial on which this study is based is registered at clinicaltrials.gov as NCT00456131. PMID:26354535

Short-term variability in body weight predicts long-term weight gain.

PubMed

Lowe, Michael R; Feig, Emily H; Winter, Samantha R; Stice, Eric

2015-11-01

Body weight in lower animals and humans is highly stable despite a very large flux in energy intake and expenditure over time. Conversely, the existence of higher-than-average variability in weight may indicate a disruption in the mechanisms responsible for homeostatic weight regulation. In a sample chosen for weight-gain proneness, we evaluated whether weight variability over a 6-mo period predicted subsequent weight change from 6 to 24 mo. A total of 171 nonobese women were recruited to participate in this longitudinal study in which weight was measured 4 times over 24 mo. The initial 3 weights were used to calculate weight variability with the use of a root mean square error approach to assess fluctuations in weight independent of trajectory. Linear regression analysis was used to examine whether weight variability in the initial 6 mo predicted weight change 18 mo later. Greater weight variability significantly predicted amount of weight gained. This result was unchanged after control for baseline body mass index (BMI) and BMI change from baseline to 6 mo and for measures of disinhibition, restrained eating, and dieting. Elevated weight variability in young women may signal the degradation of body weight regulatory systems. In an obesogenic environment this may eventuate in accelerated weight gain, particularly in those with a genetic susceptibility toward overweight. Future research is needed to evaluate the reliability of weight variability as a predictor of future weight gain and the sources of its predictive effect. The trial on which this study is based is registered at clinicaltrials.gov as NCT00456131. © 2015 American Society for Nutrition.

Age- and sex-dependent regression models for predicting the live weight of West African Dwarf goat from body measurements.

PubMed

Sowande, O S; Oyewale, B F; Iyasere, O S

2010-06-01

The relationships between live weight and eight body measurements of West African Dwarf (WAD) goats were studied using 211 animals under farm condition. The animals were categorized based on age and sex. Data obtained on height at withers (HW), heart girth (HG), body length (BL), head length (HL), and length of hindquarter (LHQ) were fitted into simple linear, allometric, and multiple-regression models to predict live weight from the body measurements according to age group and sex. Results showed that live weight, HG, BL, LHQ, HL, and HW increased with the age of the animals. In multiple-regression model, HG and HL best fit the model for goat kids; HG, HW, and HL for goat aged 13-24 months; while HG, LHQ, HW, and HL best fit the model for goats aged 25-36 months. Coefficients of determination (R(2)) values for linear and allometric models for predicting the live weight of WAD goat increased with age in all the body measurements, with HG being the most satisfactory single measurement in predicting the live weight of WAD goat. Sex had significant influence on the model with R(2) values consistently higher in females except the models for LHQ and HW.

[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.

Over, under, or about right: misperceptions of body weight among food stamp participants.

PubMed

Ver Ploeg, Michele L; Chang, Hung-Hao; Lin, Biing-Hwan

2008-09-01

The purpose of this research was to investigate the associations between misperception of body weight and sociodemographic factors such as food stamp participation status, income, education, and race/ethnicity. National Health and Nutrition Examination Survey (NHANES) data from 1999-2004 and multivariate logistic regression are used to estimate how sociodemographic factors are associated with (i) the probability that overweight adults misperceive themselves as healthy weight; (ii) the probability that healthy-weight adults misperceive themselves as underweight; and (iii) the probability that healthy-weight adults misperceive themselves as overweight. NHANES data are representative of the US civilian noninstitutionalized population. The analysis included 4,362 men and 4,057 women. BMI derived from measured weight and height was used to classify individuals as healthy weight or overweight. These classifications were compared with self-reported categorical weight status. We find that differences across sociodemographic characteristics in the propensity to underestimate or overestimate weight status were more pronounced for women than for men. Overweight female food stamp participants were more likely to underestimate weight status than income-eligible nonparticipants. Among healthy-weight and overweight women, non-Hispanic black and Mexican-American women, and women with less education were more likely to underestimate actual weight status. We found few differences across sociodemographic characteristics for men. Misperceptions of weight are common among both overweight and healthy-weight individuals and vary across socioeconomic and demographic groups. The nutrition education component of the Food Stamp Program could increase awareness of healthy body weight among participants.

Reduced bone density in androgen-deficient women with acquired immune deficiency syndrome wasting.

PubMed

Huang, J S; Wilkie, S J; Sullivan, M P; Grinspoon, S

2001-08-01

Women with acquired immune deficiency syndrome wasting are at an increased risk of osteopenia because of low weight, changes in body composition, and hormonal alterations. Although women comprise an increasing proportion of human immunodeficiency virus-infected patients, prior studies have not investigated bone loss in this expanding population of patients. In this study we investigated bone density, bone turnover, and hormonal parameters in 28 women with acquired immune deficiency syndrome wasting and relative androgen deficiency (defined as free testosterone < or =3.0 pg/ml, weight < or =90% ideal body weight, weight loss > or =10% from preillness maximum weight, or weight <100% ideal body weight with weight loss > or =5% from preillness maximum weight). Total body (1.04 +/- 0.08 vs. 1.10 +/- 0.07 g/cm2, human immunodeficiency virus-infected vs. control respectively; P < 0.01), anteroposterior lumbar spine (0.94 +/- 0.12 vs. 1.03 +/- 0.09 g/cm2; P = 0.005), lateral lumbar spine (0.71 +/- 0.14 vs. 0.79 +/- 0.09 g/cm2; P = 0.02), and hip (Ward's triangle; 0.68 +/- 0.14 vs. 0.76 +/- 0.12 g/cm2; P = 0.05) bone density were reduced in the human immunodeficiency virus-infected compared with control subjects. Serum N-telopeptide, a measure of bone resorption, was increased in human immunodeficiency virus-infected patients, compared with control subjects (14.6 +/- 5.8 vs. 11.3 +/- 3.8 nmol/liter bone collagen equivalents, human immunodeficiency virus-infected vs. control respectively; P = 0.03). Although body mass index was similar between the groups, muscle mass was significantly reduced in the human immunodeficiency virus-infected vs. control subjects (16 +/- 4 vs. 21 +/- 4 kg, human immunodeficiency virus-infected vs. control, respectively; P < 0.0001). In univariate regression analysis, muscle mass (r = 0.53; P = 0.004) and estrogen (r = 0.51; P = 0.008), but not free testosterone (r = -0.05, P = 0.81), were strongly associated with lumbar spine bone density in the human immunodeficiency virus-infected patients. The association between muscle mass and bone density remained significant, controlling for body mass index, hormonal status, and age (P = 0.048) in multivariate regression analysis. These data indicate that both hormonal and body composition factors contribute to reduced bone density in women with acquired immune deficiency syndrome wasting. Anabolic strategies to increase muscle mass may be useful to increase bone density among osteopenic women with acquired immune deficiency syndrome wasting.

Improving Global Models of Remotely Sensed Ocean Chlorophyll Content Using Partial Least Squares and Geographically Weighted Regression

NASA Astrophysics Data System (ADS)

Gholizadeh, H.; Robeson, S. M.

2015-12-01

Empirical models have been widely used to estimate global chlorophyll content from remotely sensed data. Here, we focus on the standard NASA empirical models that use blue-green band ratios. These band ratio ocean color (OC) algorithms are in the form of fourth-order polynomials and the parameters of these polynomials (i.e. coefficients) are estimated from the NASA bio-Optical Marine Algorithm Data set (NOMAD). Most of the points in this data set have been sampled from tropical and temperate regions. However, polynomial coefficients obtained from this data set are used to estimate chlorophyll content in all ocean regions with different properties such as sea-surface temperature, salinity, and downwelling/upwelling patterns. Further, the polynomial terms in these models are highly correlated. In sum, the limitations of these empirical models are as follows: 1) the independent variables within the empirical models, in their current form, are correlated (multicollinear), and 2) current algorithms are global approaches and are based on the spatial stationarity assumption, so they are independent of location. Multicollinearity problem is resolved by using partial least squares (PLS). PLS, which transforms the data into a set of independent components, can be considered as a combined form of principal component regression (PCR) and multiple regression. Geographically weighted regression (GWR) is also used to investigate the validity of spatial stationarity assumption. GWR solves a regression model over each sample point by using the observations within its neighbourhood. PLS results show that the empirical method underestimates chlorophyll content in high latitudes, including the Southern Ocean region, when compared to PLS (see Figure 1). Cluster analysis of GWR coefficients also shows that the spatial stationarity assumption in empirical models is not likely a valid assumption.

Reader reaction to "a robust method for estimating optimal treatment regimes" by Zhang et al. (2012).

PubMed

Taylor, Jeremy M G; Cheng, Wenting; Foster, Jared C

2015-03-01

A recent article (Zhang et al., 2012, Biometrics 168, 1010-1018) compares regression based and inverse probability based methods of estimating an optimal treatment regime and shows for a small number of covariates that inverse probability weighted methods are more robust to model misspecification than regression methods. We demonstrate that using models that fit the data better reduces the concern about non-robustness for the regression methods. We extend the simulation study of Zhang et al. (2012, Biometrics 168, 1010-1018), also considering the situation of a larger number of covariates, and show that incorporating random forests into both regression and inverse probability weighted based methods improves their properties. © 2014, The International Biometric Society.

Provider communication quality: influence of patients' weight and race.

PubMed

Wong, Michelle S; Gudzune, Kimberly A; Bleich, Sara N

2015-04-01

To examine the relationship between patient weight and provider communication quality and determine whether patient race/ethnicity modifies this association. We conducted a cross-sectional analysis with 2009-2010 medical expenditures panel survey-household component (N=25,971). Our dependent variables were patient report of providers explaining well, listening, showing respect, and spending time. Our independent variables were patient weight status and patient weight-race/ethnicity groups. Using survey weights, we performed multivariate logistic regression to examine the adjusted association between patient weight and patient-provider communication measures, and whether patient race/ethnicity modifies this relationship. Compared to healthy weight whites, obese blacks were less likely to report that their providers explained things well (OR 0.78; p=0.02) or spent enough time with them (OR 0.81; p=0.04), and overweight blacks were also less likely to report that providers spent enough time with them (OR 0.78; p=0.02). Healthy weight Hispanics were also less likely to report adequate provider explanations (OR 0.74; p=0.04). Our study provides preliminary evidence that overweight/obese black and healthy weight Hispanic patients experience disparities in provider communication quality. Curricula on weight bias and cultural competency might improve communication between providers and their overweight/obese black and healthy weight Hispanic patients. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Evaluation of the effect of alternative measurements of body weight gain and dry matter intake for the calculation of residual feed intake in growing purebred Charolais and Red Angus cattle.

PubMed

Kayser, W; Glaze, J B; Welch, C M; Kerley, M; Hill, R A

2015-07-01

The objective of this study was to determine the effects of alternative-measurements of body weight and DMI used to evaluate residual feed intake (RFI). Weaning weight (WW), ADG, and DMI were recorded on 970 growing purebred Charolais bulls (n = 519) and heifers (n = 451) and 153 Red Angus growing steers (n = 69) and heifers (n = 84) using a GrowSafe (GrowSafe, Airdrie, Alberta, Canada) system. Averages of individual DMI were calculated in 10-d increments and compared to the overall DMI to identify the magnitude of the errors associated with measuring DMI. These incremental measurements were also used in calculation of RFI, computed from the linear regression of DMI on ADG and midtest body weight0.75 (MMWT). RFI_Regress was calculated using ADG_Regress (ADG calculated as the response of BW gain and DOF) and MMWT_PWG (metabolic midweight calculated throughout the postweaning gain test), considered the control in Red Angus. A similar calculation served as control for Charolais; RFI was calculated using 2-d consecutive start and finish weights (RFI_Calc). The RFI weaning weight (RFI_WW) was calculated using ADG_WW (ADG from weaning till the final out weight of the postweaning gain test) and MMWT_WW, calculated similarly. Overall average estimated DMI was highly correlated to the measurements derived over shorter periods, with 10 d being the least correlated and 60 d being the most correlated. The ADG_Calc (calculated using 2-d consecutive start and finish weight/DOF) and ADG_WW were highly correlated in Charolais. The ADG_Regress and ADG_Calc were highly correlated, and ADG_Regress and ADG_WW were moderately correlated in Red Angus. The control measures of RFI were highly correlated with the RFI_WW in Charolais and Red Angus. The outcomes of including abbreviated period DMI in the model with the weaning weight gain measurements showed that the model using 10 d of intake (RFI WW_10) was the least correlated with the control measures. The model with 60 d of intake had the largest correlation with the control measures. The fewest measured intake days coupled with the weaning weight values providing acceptable predictive value was RFI_WW_40, being highly correlated with the control measures. As established in the literature, at least 70 d is required to accurately measure ADG. However, we conclude that a shorter period, possibly as few as 40 d is needed to accurately estimate DMI for a reliable calculation of RFI.

Intentional Weight Loss and Changes in Symptoms of Depression: A Systematic Review and Meta-Analysis

PubMed Central

Fabricatore, Anthony N.; Wadden, Thomas A.; Higginbotham, Allison J.; Faulconbridge, Lucy F.; Nguyen, Allison M.; Heymsfield, Steven B.; Faith, Myles S.

2011-01-01

Objective Obesity is related to increased risk of several health complications, including depression. Many studies have reported improvements in mood with weight loss, but results have been equivocal. The present meta-analysis examined changes in symptoms of depression that were reported in trials of weight loss interventions. Between-groups comparisons of different weight loss methods (e.g., lifestyle modification, diet alone, pharmacotherapy) were examined, as were within-group changes for each treatment type. Method MEDLINE was searched for articles published between 1950 and January 2009. Several obesity-related terms were intersected with terms related to depression. Results were filtered to return only studies of human subjects, published in English. Of 5971 articles, 394 were randomized controlled trials. Articles were excluded if they did not report mean changes in weight or symptoms of depression, included children or persons with psychiatric disorders (other than depression), or provided insufficient data for analysis. Thirty-one studies (n = 7937) were included. Two authors independently extracted a description of each study treatment, sample characteristics, assessment methods, and changes in weight and symptoms of depression. Treatments were categorized as: lifestyle modification, non-dieting, dietary counseling, diet-alone, exercise-alone, pharmacotherapy, placebo, or control interventions. Results Random effects models found that lifestyle modification was superior to control and non-dieting interventions for reducing symptoms of depression, and marginally better than dietary counseling and exercise-alone programs. Exercise-alone programs were superior to controls. No differences were found for comparisons of pharmacologic agents and placebos. Within-group analyses found significant reductions in symptoms of depression for nearly all active interventions. A meta-regression found no relationship between changes in weight and changes in symptoms of depression in lifestyle modification interventions. Conclusions On average, obese individuals in weight loss trials experienced reductions in symptoms of depression. Future studies should examine incidence and resolution of clinically significant depressive disorders with weight loss interventions. PMID:21343903

High doses of folic acid in the periconceptional period and risk of low weight for gestational age at birth in a population based cohort study.

PubMed

Navarrete-Muñoz, Eva María; Valera-Gran, Desirée; Garcia-de-la-Hera, Manuela; Gonzalez-Palacios, Sandra; Riaño, Isolina; Murcia, Mario; Lertxundi, Aitana; Guxens, Mònica; Tardón, Adonina; Amiano, Pilar; Vrijheid, Martine; Rebagliato, Marisa; Vioque, Jesus

2017-11-27

We investigated the association between maternal use of folic acid (FA) during pregnancy and child anthropometric measures at birth. We included 2302 mother-child pairs from a population-based birth cohort in Spain (INMA Project). FA dosages at first and third trimester of pregnancy were assessed using a specific battery questionnaire and were categorized in non-user, < 1000, 1000-4999, and ≥ 5000 µg/day. Anthropometric measures at birth (weight in grams, length and head circumference in centimetres) were obtained from medical records. Small for gestational age according to weight (SGA-w), length (SGA-l) and head circumference (SGA-hc) were defined using the 10th percentile based on Spanish standardized growth reference charts. Multiple linear and logistic regression analyses were used to explore the association between FA dosages in different stages of pregnancy and child anthropometric measures at birth. In the multiple linear regression analysis, we found a tendency for a negative association between the use of high dosages of FA (≥ 5000 µg/day) in the periconceptional period of pregnancy and weight at birth compared to mothers who were non-users of FA (β = - 73.83; 95% CI - 151.71, 4.06). In the multiple logistic regression, a greater risk of SGA-w was also evident among children whose mothers took FA dosages of 1000-4999 (OR = 2.21; 95% CI 1.17, 4.19) and of ≥ 5000 µg/day (OR = 2.32; 95% CI 1.06, 5.08) compared to mothers non-users of FA in the periconceptional period of pregnancy. Our findings suggest that a high dosage of FA (≥ 1000 µg/day) may be associated with an increased risk of SGA-w at birth.

Influence of the blood glucose level on the development of retinopathy of prematurity in extremely premature children.

PubMed

Nicolaeva, Galina V; Sidorenko, Evgenyj I; Iosifovna, Amkhanitskaya Lyubov

2015-01-01

To investigate the influence of the blood glucose level on the development of retinopathy of prematurity (ROP) in extremely premature infants. Sixty-four premature infants with a gestational age of less than 30 weeks and a birth weight of less than 1500 g were included in the study. Children without ROP were allocated to Group 1 (n=14, gestational age 28.6 ± 1.4 weeks, birth weight 1162 ± 322 g), and children with spontaneous regression of ROP were allocated to Group 2 (n=32, gestational age 26.5 ± 1.2 weeks, birth weight 905 ± 224 g). Children with progressive ROP who underwent laser treatment were included in Group 3 (n=18, gestational age 25.4 ± 0.7 weeks, birth weight 763 ± 138 g). The glucose level in the capillary blood of the premature infants was monitored daily during the first 3 weeks of life. A complete ophthalmological screening was performed from the age of 1 month. The nonparametric signed-rank Wilcoxon-Mann-Whitney test was used for statistical analysis. The mean blood glucose level was 7.43 ± 2.6 mmol/L in Group 1, 7.8 ± 2.7 mmol/L in Group 2, and 6.7 ± 2.6 mmol/L in Group 3. There were no significant differences in the blood glucose levels between children with and without ROP, and also between children with spontaneously regressing ROP and progressive ROP (p>0.05). Additionally, there were no significant differences in the blood glucose levels measured at the first, second, and third weeks of life (p>0.05). The blood glucose level is not related to the development of ROP nor with its progression or regression. The glycemic level cannot be considered as a risk factor for ROP, but reflects the severity of newborns' somatic condition and morphofunctional immaturity.

Gender orientation and alcohol-related weight control behavior among male and female college students.

PubMed

Peralta, Robert L; Barr, Peter B

2017-01-01

We examine weight control behavior used to (a) compensate for caloric content of heavy alcohol use; and (b) enhance the psychoactive effects of alcohol among college students. We evaluate the role of gender orientation and sex. Participants completed an online survey (N = 651; 59.9% women; 40.1% men). Weight control behavior was assessed via the Compensatory-Eating-and-Behaviors-in Response-to-Alcohol-Consumption-Scale. Control variables included sex, race/ethnicity, age, and depressive symptoms. Gender orientation was measured by the Bem Sex Role Inventory. The prevalence and probability of alcohol-related weight control behavior using ordinal logistic regression are reported. Men and women do not significantly differ in compensatory-weight-control-behavior. However, regression models suggest that recent binge drinking, other substance use, and masculine orientation are positively associated with alcohol-related weight control behavior. Sex was not a robust predictor of weight control behavior. Masculine orientation should be considered a possible risk factor for these behaviors and considered when designing prevention and intervention strategies.

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.

Local regression type methods applied to the study of geophysics and high frequency financial data

NASA Astrophysics Data System (ADS)

Mariani, M. C.; Basu, K.

2014-09-01

In this work we applied locally weighted scatterplot smoothing techniques (Lowess/Loess) to Geophysical and high frequency financial data. We first analyze and apply this technique to the California earthquake geological data. A spatial analysis was performed to show that the estimation of the earthquake magnitude at a fixed location is very accurate up to the relative error of 0.01%. We also applied the same method to a high frequency data set arising in the financial sector and obtained similar satisfactory results. The application of this approach to the two different data sets demonstrates that the overall method is accurate and efficient, and the Lowess approach is much more desirable than the Loess method. The previous works studied the time series analysis; in this paper our local regression models perform a spatial analysis for the geophysics data providing different information. For the high frequency data, our models estimate the curve of best fit where data are dependent on time.

Extension of the Haseman-Elston regression model to longitudinal data.

PubMed

Won, Sungho; Elston, Robert C; Park, Taesung

2006-01-01

We propose an extension to longitudinal data of the Haseman and Elston regression method for linkage analysis. The proposed model is a mixed model having several random effects. As response variable, we investigate the sibship sample mean corrected cross-product (smHE) and the BLUP-mean corrected cross product (pmHE), comparing them with the original squared difference (oHE), the overall mean corrected cross-product (rHE), and the weighted average of the squared difference and the squared mean-corrected sum (wHE). The proposed model allows for the correlation structure of longitudinal data. Also, the model can test for gene x time interaction to discover genetic variation over time. The model was applied in an analysis of the Genetic Analysis Workshop 13 (GAW13) simulated dataset for a quantitative trait simulating systolic blood pressure. Independence models did not preserve the test sizes, while the mixed models with both family and sibpair random effects tended to preserve size well. Copyright 2006 S. Karger AG, Basel.

Mixed geographically weighted regression (MGWR) model with weighted adaptive bi-square for case of dengue hemorrhagic fever (DHF) in Surakarta

NASA Astrophysics Data System (ADS)

Astuti, H. N.; Saputro, D. R. S.; Susanti, Y.

2017-06-01

MGWR model is combination of linear regression model and geographically weighted regression (GWR) model, therefore, MGWR model could produce parameter estimation that had global parameter estimation, and other parameter that had local parameter in accordance with its observation location. The linkage between locations of the observations expressed in specific weighting that is adaptive bi-square. In this research, we applied MGWR model with weighted adaptive bi-square for case of DHF in Surakarta based on 10 factors (variables) that is supposed to influence the number of people with DHF. The observation unit in the research is 51 urban villages and the variables are number of inhabitants, number of houses, house index, many public places, number of healthy homes, number of Posyandu, area width, level population density, welfare of the family, and high-region. Based on this research, we obtained 51 MGWR models. The MGWR model were divided into 4 groups with significant variable is house index as a global variable, an area width as a local variable and the remaining variables vary in each. Global variables are variables that significantly affect all locations, while local variables are variables that significantly affect a specific location.

Indirect Measurement Of Nitrogen In A Multi-Component Gas By Measuring The Speed Of Sound At Two States Of The Gas.

DOEpatents

Morrow, Thomas B.; Behring, II, Kendricks A.

2004-10-12

A methods of indirectly measuring the nitrogen concentration in a gas mixture. The molecular weight of the gas is modeled as a function of the speed of sound in the gas, the diluent concentrations in the gas, and constant values, resulting in a model equation. Regression analysis is used to calculate the constant values, which can then be substituted into the model equation. If the speed of sound in the gas is measured at two states and diluent concentrations other than nitrogen (typically carbon dioxide) are known, two equations for molecular weight can be equated and solved for the nitrogen concentration in the gas mixture.

Models of subjective response to in-flight motion data

NASA Technical Reports Server (NTRS)

Rudrapatna, A. N.; Jacobson, I. D.

1973-01-01

Mathematical relationships between subjective comfort and environmental variables in an air transportation system are investigated. As a first step in model building, only the motion variables are incorporated and sensitivities are obtained using stepwise multiple regression analysis. The data for these models have been collected from commercial passenger flights. Two models are considered. In the first, subjective comfort is assumed to depend on rms values of the six-degrees-of-freedom accelerations. The second assumes a Rustenburg type human response function in obtaining frequency weighted rms accelerations, which are used in a linear model. The form of the human response function is examined and the results yield a human response weighting function for different degrees of freedom.

WALLY 1 ...A large, principal components regression program with varimax rotation of the factor weight matrix

Treesearch

James R. Wallis

1965-01-01

Written in Fortran IV and MAP, this computer program can handle up to 120 variables, and retain 40 principal components. It can perform simultaneous regression of up to 40 criterion variables upon the varimax rotated factor weight matrix. The columns and rows of all output matrices are labeled by six-character alphanumeric names. Data input can be from punch cards or...

The relationship between resting energy expenditure and weight loss in benign and malignant disease.

PubMed Central

Hansell, D T; Davies, J W; Burns, H J

1986-01-01

The relationship between cancer, weight loss, and resting energy expenditure (REE) has been investigated in 136 patients using indirect calorimetry. Ninety-one patients had gastric, colorectal, or nonsmall cell bronchial neoplasm, seven patients had other malignancies, and 38 patients had nonmalignant illness. Four groups were studied: weight stable cancer patients (CWS: N = 56), weight losing cancer patients (CWL: N = 42), weight stable patients with nonmalignant illness (NCWS: N = 22), and weight losing patients with nonmalignant illness (NCWL: N = 16). In each group REE correlated significantly with body weight, metabolic body size, and lean body mass (LBM: estimated from total body water measurements). The closest correlation was between REE and lean body mass, with the slope of the CWL regression line differing significantly from that of the CWS (p less than 0.05) and NCWS (p less than 0.02) groups. However, there was no difference in REE expressed as kcal/kg LBM/d between the groups. The slopes of the regressions between REE and LBM were almost identical when all cancer patients were compared with all patients with nonmalignant illness. However, when all weight stable patients were compared with all weight losing patients, there was a highly significant difference between the slopes of the regressions (p less than 0.005). This indicates that the weight losing state rather than the presence or absence of cancer is responsible for an alteration in the relationship between REE and LBM. There were no differences in REE between the different tumor types. It is concluded that REE is not elevated in patients with gastric, colorectal, or nonsmall cell bronchial cancer. Elevation of REE contributes very little to the etiology of cancer cachexia. PMID:3082302

An improved partial least-squares regression method for Raman spectroscopy

NASA Astrophysics Data System (ADS)

Momenpour Tehran Monfared, Ali; Anis, Hanan

2017-10-01

It is known that the performance of partial least-squares (PLS) regression analysis can be improved using the backward variable selection method (BVSPLS). In this paper, we further improve the BVSPLS based on a novel selection mechanism. The proposed method is based on sorting the weighted regression coefficients, and then the importance of each variable of the sorted list is evaluated using root mean square errors of prediction (RMSEP) criterion in each iteration step. Our Improved BVSPLS (IBVSPLS) method has been applied to leukemia and heparin data sets and led to an improvement in limit of detection of Raman biosensing ranged from 10% to 43% compared to PLS. Our IBVSPLS was also compared to the jack-knifing (simpler) and Genetic Algorithm (more complex) methods. Our method was consistently better than the jack-knifing method and showed either a similar or a better performance compared to the genetic algorithm.

Regional regression equations to estimate peak-flow frequency at sites in North Dakota using data through 2009

USGS Publications Warehouse

Williams-Sether, Tara

2015-08-06

Annual peak-flow frequency data from 231 U.S. Geological Survey streamflow-gaging stations in North Dakota and parts of Montana, South Dakota, and Minnesota, with 10 or more years of unregulated peak-flow record, were used to develop regional regression equations for exceedance probabilities of 0.5, 0.20, 0.10, 0.04, 0.02, 0.01, and 0.002 using generalized least-squares techniques. Updated peak-flow frequency estimates for 262 streamflow-gaging stations were developed using data through 2009 and log-Pearson Type III procedures outlined by the Hydrology Subcommittee of the Interagency Advisory Committee on Water Data. An average generalized skew coefficient was determined for three hydrologic zones in North Dakota. A StreamStats web application was developed to estimate basin characteristics for the regional regression equation analysis. Methods for estimating a weighted peak-flow frequency for gaged sites and ungaged sites are presented.

Individual and community risk factors and sexually transmitted diseases among arrested youths: a two level analysis.

PubMed

Dembo, Richard; Belenko, Steven; Childs, Kristina; Wareham, Jennifer; Schmeidler, James

2009-08-01

High rates of infection for chlamydia and gonorrhea have been noted among youths involved in the juvenile justice system. Although both individual and community-level factors have been found to be associated with sexually transmitted disease (STD) risk, their relative importance has not been tested in this population. A two-level logistic regression analysis was completed to assess the influence of individual-level and community-level predictors on STD test results among arrested youths processed at a centralized intake facility. Results from weighted two level logistic regression analyses (n = 1,368) indicated individual-level factors of gender (being female), age, race (being African American), and criminal history predicted the youths' positive STD status. For the community-level predictors, concentrated disadvantage significantly and positively predicted the youths' STD status. Implications of these findings for future research and public health policy are discussed.

Associations Among Obesity, Acute Weight Gain, and Response to Treatment with Olanzapine in Adolescent Schizophrenia

PubMed Central

Correll, Christoph U.; Tohen, Mauricio; DelBello, Melissa P.; Ganocy, Stephen J.; Findling, Robert L.; Chang, Kiki

2013-01-01

Abstract Objective The purpose of this study was to investigate associations between body weight and illness characteristics, including weight gain and therapeutic efficacy, in adolescents with schizophrenia. Methods Adolescents ages 13–17 years (n=107) with American Psychiatric Association, Diagnostic and Statistical Manual of Mental Disorders, 4th ed. (DSM-IV) schizophrenia enrolled in a 6 week, double-blind, placebo-controlled trial comparing olanzapine and placebo. Therapeutic response was assessed by the Brief Psychiatric Rating Scale for Children (BPRS-C). Secondary outcomes included the Clinical Global Impressions-Severity (CGI-S) scale and Positive and Negative Syndrome Scale (PANSS). Obesity was defined as sex-/age-adjusted body mass index (BMI)≥95th percentile. Linear regression was used to analyze the relationship between weight gain and psychiatric symptom improvement; logistic regression was conducted to identify predictors of baseline obesity. Results Weight gain was significantly correlated with greater BPRS-C reduction among olanzapine-treated subjects (r=−0.31, p<0.01), whereas a trend was observed among placebo-treated subjects (r=−0.31, p=0.08). However, this relationship became nonsignificant when analyses were controlled for duration of olanzapine treatment (p=0.12), and a treatment by weight gain interaction did not emerge in a repeated-measures mixed model analysis that included time in the study (t=1.27, p=0.21). Additionally, weight gain ≥7% was not significantly associated with response or remission. Among 17 adolescents (16%) with obesity at study entry, obesity was not significantly associated with endpoint BPRS-C illness severity. However, girls (p=0.03), individuals hospitalized within the past year (p=0.02), and those with less severe overall (p=0.03) and negative symptoms (p=0.003) according to the CGI-S and PANSS negative subscale, respectively, were more likely to be obese at baseline. Conclusion Baseline obesity was associated with lower illness severity, which could be mediated by greater treatment adherence, leading to more weight gain. Olanzapine-related weight gain was not independently associated with symptomatic outcome when controlling for treatment duration. Additional studies are needed to extend these findings to other disorders and medications. PMID:24111982

Comparative effectiveness of a portion-controlled meal replacement program for weight loss in adults with and without diabetes/high blood sugar

PubMed Central

Coleman, C D; Kiel, J R; Mitola, A H; Arterburn, L M

2017-01-01

Background: Individuals with type 2 diabetes (DM2) may be less successful at achieving therapeutic weight loss than their counterparts without diabetes. This study compares weight loss in a cohort of adults with DM2 or high blood sugar (D/HBS) to a cohort of adults without D/HBS. All were overweight/obese and following a reduced or low-calorie commercial weight-loss program incorporating meal replacements (MRs) and one-on-one behavioral support. Subjects/Methods: Demographic, weight, body composition, anthropometric, pulse and blood pressure data were collected as part of systematic retrospective chart review studies. Differences between cohorts by D/HBS status were analyzed using Mann–Whitney U-tests and mixed model regression. Results: A total of 816 charts were included (125 with self-reported D/HBS). The cohort with D/HBS had more males (40.8 vs 25.6%), higher BMI (39.0 vs 36.3 kg m−2) and was older (56 vs 48 years). Among clients continuing on program, the cohorts with and without D/HBS lost, on average, 5.6 vs 5.8 kg (NS) (5.0 vs 5.6% P=0.005) of baseline weight at 4 weeks, 11.0 vs 11.6 kg (NS) (9.9 vs 11.1% P=0.027) at 12 weeks and 16.3 vs 17.1 kg (13.9 vs 15.7% NS) at 24 weeks, respectively. In a mixed model regression controlling for baseline weight, gender and meal plan, and an intention-to-treat analysis, there was no significant difference in weight loss between the cohorts at any time point. Over 70% in both cohorts lost ⩾5% of their baseline weight by the final visit on their originally assigned meal plan. Both cohorts had significant reductions from baseline in body fat, blood pressure, pulse and abdominal circumference. Conclusion: Adults who were overweight/obese and with D/HBS following a commercial weight-loss program incorporating MRs and one-on-one behavioral support achieved therapeutic weight loss. The program was equally effective for weight loss and reductions in cardiometabolic risk factors among adults with and without D/HBS. PMID:28692020

Approximate median regression for complex survey data with skewed response.

PubMed

Fraser, Raphael André; Lipsitz, Stuart R; Sinha, Debajyoti; Fitzmaurice, Garrett M; Pan, Yi

2016-12-01

The ready availability of public-use data from various large national complex surveys has immense potential for the assessment of population characteristics using regression models. Complex surveys can be used to identify risk factors for important diseases such as cancer. Existing statistical methods based on estimating equations and/or utilizing resampling methods are often not valid with survey data due to complex survey design features. That is, stratification, multistage sampling, and weighting. In this article, we accommodate these design features in the analysis of highly skewed response variables arising from large complex surveys. Specifically, we propose a double-transform-both-sides (DTBS)'based estimating equations approach to estimate the median regression parameters of the highly skewed response; the DTBS approach applies the same Box-Cox type transformation twice to both the outcome and regression function. The usual sandwich variance estimate can be used in our approach, whereas a resampling approach would be needed for a pseudo-likelihood based on minimizing absolute deviations (MAD). Furthermore, the approach is relatively robust to the true underlying distribution, and has much smaller mean square error than a MAD approach. The method is motivated by an analysis of laboratory data on urinary iodine (UI) concentration from the National Health and Nutrition Examination Survey. © 2016, The International Biometric Society.

Approximate Median Regression for Complex Survey Data with Skewed Response

PubMed Central

Fraser, Raphael André; Lipsitz, Stuart R.; Sinha, Debajyoti; Fitzmaurice, Garrett M.; Pan, Yi

2016-01-01

Summary The ready availability of public-use data from various large national complex surveys has immense potential for the assessment of population characteristics using regression models. Complex surveys can be used to identify risk factors for important diseases such as cancer. Existing statistical methods based on estimating equations and/or utilizing resampling methods are often not valid with survey data due to complex survey design features. That is, stratification, multistage sampling and weighting. In this paper, we accommodate these design features in the analysis of highly skewed response variables arising from large complex surveys. Specifically, we propose a double-transform-both-sides (DTBS) based estimating equations approach to estimate the median regression parameters of the highly skewed response; the DTBS approach applies the same Box-Cox type transformation twice to both the outcome and regression function. The usual sandwich variance estimate can be used in our approach, whereas a resampling approach would be needed for a pseudo-likelihood based on minimizing absolute deviations (MAD). Furthermore, the approach is relatively robust to the true underlying distribution, and has much smaller mean square error than a MAD approach. The method is motivated by an analysis of laboratory data on urinary iodine (UI) concentration from the National Health and Nutrition Examination Survey. PMID:27062562

Changes in aerobic power of men, ages 25-70 yr

NASA Technical Reports Server (NTRS)

Jackson, A. S.; Beard, E. F.; Wier, L. T.; Ross, R. M.; Stuteville, J. E.; Blair, S. N.

1995-01-01

This study quantified and compared the cross-sectional and longitudinal influence of age, self-report physical activity (SR-PA), and body composition (%fat) on the decline of maximal aerobic power (VO2peak). The cross-sectional sample consisted of 1,499 healthy men ages 25-70 yr. The 156 men of the longitudinal sample were from the same population and examined twice, the mean time between tests was 4.1 (+/- 1.2) yr. Peak oxygen uptake was determined by indirect calorimetry during a maximal treadmill exercise test. The zero-order correlations between VO2peak and %fat (r = -0.62) and SR-PA (r = 0.58) were significantly (P < 0.05) higher that the age correlation (r = -0.45). Linear regression defined the cross-sectional age-related decline in VO2peak at 0.46 ml.kg-1.min-1.yr-1. Multiple regression analysis (R = 0.79) showed that nearly 50% of this cross-sectional decline was due to %fat and SR-PA, adding these lifestyle variables to the multiple regression model reduced the age regression weight to -0.26 ml.kg-1.min-1.yr-1. Statistically controlling for time differences between tests, general linear models analysis showed that longitudinal changes in aerobic power were due to independent changes in %fat and SR-PA, confirming the cross-sectional results.

Low birth weight in Kansas.

PubMed

Guillory, V James; Lai, Sue Min; Suminski, R; Crawford, G

2015-05-01

Low birth weight (LBW) is associated with infant morbidity and mortality. This is the first study of LBW in Kansas using vital statistics to determine maternal and health care system factors associated with LBW. Low birth weight. Determine if prenatal care, maternal socio-demographic or medical factors, or insurance status were associated with LBW. Birth certificate data were merged with Medicaid eligibility data and subjected to logistic regression analysis. Of the 37,081 single vaginal births, LBW rates were 5.5% overall, 10.8% for African Americans, and 5% for White Americans. Lacking private insurance was associated with 34% more LBW infants (AOR 1.34; 95% CI 1.13-1.58), increased comorbidity, and late or less prenatal care. Low birth weight was associated with maternal medical comorbidity and with previous adverse birth outcomes. Insurance status, prenatal care, and maternal health during pregnancy are associated with LBW. Private insurance was consistently associated with more prenatal care and better outcomes. This study has important implications regarding health care reform.

Unfavourable family characteristics and their associations with childhood obesity: a cross-sectional study.

PubMed

Moens, Ellen; Braet, Caroline; Bosmans, Guy; Rosseel, Yves

2009-07-01

This cross-sectional study explores the influence of multiple familial factors on children's weight status and the interaction between parenting stress and unfavourable family characteristics. A total of 197 families with children between 6 and 14 years participated in this study. Of this group, 97 families had a child with normal weight and 100 families had a child with overweight. Parents reported on seven family factors (maternal BMI, number of children, family structure, socioeconomic position, life events, parental psychopathology and parenting stress). Families with overweight children experience more parenting stress. A regression analysis revealed that familial factors explain 27% in the variance in child's weight status. The hypothesis that a combination of familial factors will be more able to explain child's adiposity could not be confirmed. Familial factors have moderate ability to predict children's weight status. There is a need to identify other familial mechanisms taking into account developmental and temporal evolutions over the past decade. 2009 John Wiley & Sons, Ltd and Eating Disorders Association

Familial correlates of extreme weight control behaviors among adolescents.

PubMed

Fonseca, Helena; Ireland, Marjorie; Resnick, Michael D

2002-12-01

To identify familial factors associated with extreme weight control among adolescents. Analysis of a comprehensive 1996 health survey of Connecticut students. Familial factors among extreme dieters who deliberately vomited, took diet pills, laxatives, or diuretics were compared with youth reporting none of these behaviors, using logistic regression controlling for age and body mass index. Nearly 7% of adolescents reported engaging in extreme weight control behaviors. Boys' risk factors included high parental supervision/monitoring and sexual abuse history. Protective factors included high parental expectations, maternal presence, and connectedness with friends and other adults. The only significant risk factor for girls was sexual abuse history. Protective factors included family connectedness, positive family communication, parental supervision/monitoring, and maternal presence. Extreme dieting appears to be less an expression of body composition than of psychosocial issues. That connectedness to family, other adults, and friends is protective further demonstrates interrelationships of extreme weight control behaviors with family/social issues. Copyright 2002 by Wiley Periodicals, Inc. Int J Eat Disord 32: 441-448, 2002.

Young adults with very low birth weight: leaving the parental home and sexual relationships--Helsinki Study of Very Low Birth Weight Adults.

PubMed

Kajantie, Eero; Hovi, Petteri; Räikkönen, Katri; Pesonen, Anu-Katriina; Heinonen, Kati; Järvenpää, Anna-Liisa; Eriksson, Johan G; Strang-Karlsson, Sonja; Andersson, Sture

2008-07-01

Although most children and adults who are born very preterm live healthy lives, they have, on average, lower cognitive scores, more internalizing behaviors, and deficits in social skills. This could well affect their transition to adulthood. We studied the tempo of first leaving the parental home and starting cohabitation with an intimate partner and sexual experience of young adults with very low birth weight (<1500 g). In conjunction with the Helsinki Study of Very Low Birth Weight Adults, 162 very low birth weight individuals and 188 individuals who were born at term (mean age: 22.3 years [range: 18.5-27.1]) and did not have any major disability filled out a questionnaire. For analysis of their ages at events which had not occurred in all subjects, we used survival analysis (Cox regression), adjusted for gender, current height, parents' ages at the birth, maternal smoking during pregnancy, parental educational attainment, number of siblings, and parental divorce/death. During their late teens and early adulthood, these very low birth weight adults were less likely to leave the parental home and to start cohabiting with an intimate partner. In gender-stratified analyses, these hazard ratios were similar between genders, but the latter was statistically significant for women only. These very low birth weight adults were also less likely to experience sexual intercourse. This relationship was statistically significant for women but not for men; however, very low birth weight women and men both reported a smaller lifetime number of sex partners than did control subjects. Healthy young adults with very low birth weight show a delay in leaving the parental home and starting sexual activity and partnerships.

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.

Relationship of a desire of thinness and eating behavior among Japanese underweight female students.

PubMed

Mase, Tomoki; Miyawaki, Chiemi; Kouda, Katsuyasu; Fujita, Yuki; Ohara, Kumiko; Nakamura, Harunobu

2013-06-01

We conducted a questionnaire survey among Japanese female students to explore the influence of a desire for thinness and dietary behaviors on the development of eating disorders. Self-reported measures of socio-demographic characteristics, body weight perception, height and weight, and dietary and exercise behavior were completed by 631 female university students at 6 universities in Kyoto, Japan. Many students had a desire for thinness (underweight students, 51.7 %; normal-weight students, 88.8 %), whereas ideal weight and body mass index were lower in the students with a desire for thinness than the students without a desire for thinness, and were also lower in the underweight students than the normal-weight students. The eating attitude test (EAT-26) scores of underweight students with a desire for thinness were higher than those of the normal-weight students with a desire for thinness. As a result of a logistic regression analysis, underweight, desire for thinness, and experience with weight control were positively associated with eating problems. Further, the association of eating problems increased along with the increase in the number of factors (underweight, desire for thinness, and experience with weight control). These results indicate that underweight females have strong associations with eating problems.

Maternal education, birth weight, and infant mortality in the United States.

PubMed

Gage, Timothy B; Fang, Fu; O'Neill, Erin; Dirienzo, Greg

2013-04-01

This research determines whether the observed decline in infant mortality with socioeconomic level, operationalized as maternal education (dichotomized as college or more, versus high school or less), is due to its "indirect" effect (operating through birth weight) and/or to its "direct" effect (independent of birth weight). The data used are the 2001 U.S. national African American, Mexican American, and European American birth cohorts by sex. The analysis explores the birth outcomes of infants undergoing normal and compromised fetal development separately by using covariate density defined mixture of logistic regressions (CDDmlr). Among normal births, mean birth weight increases significantly (by 27-108 g) with higher maternal education. Mortality declines significantly (by a factor of 0.40-0.96) through the direct effect of education. The indirect effect of education among normal births is small but significant in three cohorts. Furthermore, the indirect effect of maternal education tends to increase mortality despite improved birth weight. Among compromised births, education has small and inconsistent effects on birth weight and infant mortality. Overall, our results are consistent with the view that the decrease in infant death by socioeconomic level is not mediated by improved birth weight. Interventions targeting birth weight may not result in lower infant mortality.

The weighted priors approach for combining expert opinions in logistic regression experiments

DOE PAGES

Quinlan, Kevin R.; Anderson-Cook, Christine M.; Myers, Kary L.

2017-04-24

When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration.more » While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.« less

Prediction of Vancomycin Dose for Recommended Trough Concentrations in Pediatric Patients With Cystic Fibrosis.

PubMed

Amin, Raid W; Guttmann, Rodney P; Harris, Quianna R; Thomas, Janesha W

2018-05-01

Vancomycin is a key antibiotic used in the treatment of multiple conditions including infections associated with cystic fibrosis and methicillin-resistant Staphylococcus aureus. The present study sought to develop a model based on empirical evidence of optimal vancomycin dose as judged by clinical observations that could accelerate the achievement of desired trough level in children with cystic fibrosis. Transformations of dose and trough were used to arrive at regression models with excellent fit for dose based on weight or age for a target trough. Results of this study indicate that the 2 proposed regression models are robust to changes in age or weight, suggesting that the daily dose on a per-kilogram basis is determined primarily by the desired trough level. The results show that to obtain a vancomycin trough level of 20 μg/mL, a dose of 80 mg/kg/day is needed. This analysis should improve the efficiency of vancomycin usage by reducing the number of titration steps, resulting in improved patient outcome and experience. © 2018, The American College of Clinical Pharmacology.

The weighted priors approach for combining expert opinions in logistic regression experiments

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

Quinlan, Kevin R.; Anderson-Cook, Christine M.; Myers, Kary L.

When modeling the reliability of a system or component, it is not uncommon for more than one expert to provide very different prior estimates of the expected reliability as a function of an explanatory variable such as age or temperature. Our goal in this paper is to incorporate all information from the experts when choosing a design about which units to test. Bayesian design of experiments has been shown to be very successful for generalized linear models, including logistic regression models. We use this approach to develop methodology for the case where there are several potentially non-overlapping priors under consideration.more » While multiple priors have been used for analysis in the past, they have never been used in a design context. The Weighted Priors method performs well for a broad range of true underlying model parameter choices and is more robust when compared to other reasonable design choices. Finally, we illustrate the method through multiple scenarios and a motivating example. Additional figures for this article are available in the online supplementary information.« less

Effects of dietary methionine on performance, egg quality and glutathione redox system in egg-laying ducks.

PubMed

Fouad, A M; Ruan, D; Lin, Y C; Zheng, C T; Zhang, H X; Chen, W; Wang, S; Xia, W G; Li, Y

2016-12-01

In this study, 6 dietary DL-methionine (Met) levels (2.5, 3.0, 3.5, 4.0, 4.5 and 5.0 g/kg) were tested to estimate the dietary Met requirements of Longyan ducks from 19 to 46 weeks of age, and to investigate its effect on the glutathione redox system. In total, 1080 Longyan ducks aged 19 weeks were allocated randomly to the 6 dietary treatments, where each treatment comprised 6 replicate pens with 30 ducks per pen. Met had no effects on egg production, yolk weight, yolk colour or the glutathione redox system, but the egg weight, egg mass and feed conversion ratio (FCR) were improved significantly by dietary Met supplementation. As the dietary Met concentration increased, the eggshell thickness and breaking strength decreased significantly, whereas the albumen weight increased significantly. According to broken-line regression analysis, the optimum Met requirements for egg weight, egg mass, FCR and albumen weight are 686, 661, 658 and 731 mg/bird/d, respectively, with a dietary crude protein level of 170 g/kg.

“Decrease in television viewing predicts lower BMI at one year follow up in adolescents but not adults”

PubMed Central

French, Simone A.; Mitchell, Nathan R.; Hannan, Peter J.

2012-01-01

Objective To examine associations between television viewing, sugar-sweetened beverage consumption, eating out, physical activity and body weight change over 1 year. Design Secondary data analysis from randomized intervention trial. Setting Households in the community. Participants Adults (n=153) and adolescents (n=72) from the same households. Intervention(s) Households were randomized to a home-based obesity prevention intervention or to a no-intervention control group for a one-year period. Main Outcome Measure(s) Self-reported television viewing hours, diet and physical activity. Body mass index computed from measured weight and height (primary outcome measure). Analysis Mixed-model regression. Results Among adolescents, a significant prospective association was observed between decreases in television viewing hours and lower BMI z-score at one year follow-up (decreased TV hours: BMI z-score mean = 0.65; no change or increase TV hrs: BMI zscore = 0.92; p < .02). No significant prospective associations were observed among adults. Conclusions and Implications Reducing television viewing may be an effective strategy to prevent excess weight gain among adolescents. PMID:22591582

Relationship between body mass index and perceived insufficient sleep among U.S. adults: an analysis of 2008 BRFSS data.

PubMed

Wheaton, Anne G; Perry, Geraldine S; Chapman, Daniel P; McKnight-Eily, Lela R; Presley-Cantrell, Letitia R; Croft, Janet B

2011-05-10

Over the past 50 years, the average sleep duration for adults in the United States has decreased while the prevalence of obesity and associated outcomes has increased. The objective of this study was to determine whether perceived insufficient sleep was associated with body mass index (BMI) in a national sample. We analyzed data from the 2008 Behavioral Risk Factor Surveillance System (BRFSS) survey (N=384,541) in which respondents were asked, "During the past 30 days, for about how many days have you felt you did not get enough rest or sleep?" We divided respondents into six BMI categories and used multivariable linear regression and logistic regression analyses to assess the association between BMI categories and days of insufficient sleep after adjusting for sociodemographic variables, smoking, physical activity, and frequent mental distress. Adjusted mean days of insufficient sleep ranged from 7.9 (95% confidence interval [CI]: 7.8, 8.0) days for people of normal weight to 10.5 (95% CI: 10.2, 10.9) days for those in the highest weight category (BMI≥40). Days of perceived insufficient sleep followed a linear trend across BMI categories. The likelihood of reporting ≥14 days of insufficient sleep in the previous 30 days was higher for respondents in the highest weight category than for those who were normal weight (34.9% vs. 25.2%; adjusted odds ratio=1.7 (95% CI: 1.5, 1.8]). Among U.S. adults, days of insufficient rest or sleep strongly correlated with BMI. Sleep sufficiency should be an important consideration in the assessment of the health of overweight and obese people and should be considered by developers of weight-reduction programs.

Metformin for treatment of antipsychotic-induced amenorrhea and weight gain in women with first-episode schizophrenia: a double-blind, randomized, placebo-controlled study.

PubMed

Wu, Ren-Rong; Jin, Hua; Gao, Keming; Twamley, Elizabeth W; Ou, Jian-Jun; Shao, Ping; Wang, Juan; Guo, Xiao-Feng; Davis, John M; Chan, Philip K; Zhao, Jing-Ping

2012-08-01

Data on the treatment of antipsychotic-induced amenorrhea, particularly when occurring with weight gain, are limited. The authors investigated the efficacy and safety of metformin in the treatment of antipsychotic-induced amenorrhea and weight gain in women with first-episode schizophrenia. Eighty-four women (ages 18-40 years) with first-episode schizophrenia who suffered from amenorrhea during antipsychotic treatment were randomly assigned, in a double-blind study design, to receive 1000 mg/day of metformin or placebo in addition to their antipsychotic treatment for 6 months. The primary outcome measures were restoration of menstruation and change in body weight and body mass index (BMI). Secondary outcome measures were changes in levels of prolactin, luteinizing hormone (LH), follicle-stimulating hormone (FSH), estradiol, and testosterone; in fasting levels of insulin and glucose; in LH/FSH ratio; and in insulin resistance index. Repeated mixed models with repeated-measures regression analyses and binary logistic regression were used in the analysis. A total of 76 patients completed the 6-month trial. Significantly more patients in the metformin group (N=28, 66.7%) than in placebo group (N=2, 4.8%) resumed their menstruation. Among patients treated with metformin, BMI decreased by a mean of 0.93 and the insulin resistance index by 2.04. In contrast, patients who received placebo had a mean increase in BMI of 0.85. The prolactin, LH, and testosterone levels and LH/FSH ratio decreased significantly in the metformin group at months 2, 4, and 6, but these levels did not change in the placebo group. Metformin was effective in reversing antipsychotic-induced adverse events, including restoration of menstruation, promotion of weight loss, and improvement in insulin resistance in female patients with schizophrenia.

Preoperative Determinants of Outcomes of Infant Heart Surgery in a Limited-Resource Setting.

PubMed

Reddy, N Srinath; Kappanayil, Mahesh; Balachandran, Rakhi; Jenkins, Kathy J; Sudhakar, Abish; Sunil, G S; Raj, R Benedict; Kumar, R Krishna

2015-01-01

We studied the effect of preoperative determinants on early outcomes of 1028 consecutive infant heart operations in a limited-resource setting. Comprehensive data on pediatric heart surgery (January 2010-December 2012) were collected prospectively. Outcome measures included in-hospital mortality, prolonged ventilation (>48 hours), and bloodstream infection (BSI) after surgery. Preoperative variables that showed significant individual association with outcome measures were entered into a logistic regression model. Weight at birth was low in 224 infants (21.8%), and failure to thrive was common (mean-weight Z score at surgery was 2.72 ± 1.7). Preoperatively, 525 infants (51%) needed intensive care, 69 infants (6.7%) were ventilated, and 80 infants (7.8%) had BSI. In-hospital mortality (4.1%) was significantly associated with risk adjustment for congenital heart surgery-1 (RACHS-1) risk category (P < 0.001). Neonatal status, preoperative BSI, and requirement of preoperative intensive care and ventilation had significant individual association with adverse outcomes, whereas low birth weight, prematurity, and severe failure to thrive (weight Z score <-3) were not associated with adverse outcomes. On multivariable logistic regression analysis, preoperative sepsis (odds ratio = 2.86; 95% CI: 1.32-6.21; P = 0.008) was associated with mortality. Preoperative intensive care unit stay, ventilation, BSI, and RACHS-1 category were associated with prolonged postoperative ventilation and postoperative sepsis. Neonatal age group was additionally associated with postoperative sepsis. Although severe failure to thrive was common, it did not adversely affect outcomes. In conclusions, preoperative BSI, preoperative intensive care, and mechanical ventilation are strongly associated with adverse outcomes after infant cardiac surgery in this large single-center experience from a developing country. Failure to thrive and low birth weight do not appear to adversely affect surgical outcomes. Copyright © 2015 Elsevier Inc. All rights reserved.

Errors in weight estimation in the emergency department: comparing performance by providers and patients.

PubMed

Hall, William L; Larkin, Gregory L; Trujillo, Mauricio J; Hinds, Jackie L; Delaney, Kathleen A

2004-10-01

To examine biases in weight estimation by Emergency Department (ED) providers and patients, a convenience sample of ED providers (faculty, residents, interns, nurses, medical students, paramedics) and patients was studied. Providers (n = 33), blinded to study hypothesis and patient data, estimated their own weight as well as the weight of 11-20 patients each. An independent sample of patients (n = 95) was used to assess biases in patients' estimation of their own weight. Data are represented as over, under, or within +/- 5 kg, the dose tolerance standard for thrombolytics. Logistic regression analysis revealed that patients are almost nine times more likely to accurately estimate their own weight than providers; yet 22% of patients were unable to estimate their own weight within 5 kg. Of all providers, paramedics were significantly worse estimators of patient weight than other providers. Providers were no better at guessing their own weight than were patients. Though there was no systematic estimate bias by weight, experience level (except paramedic), or gender for providers, those providers under 30 years of age were significantly better estimators of patient weight than older providers. Although patient gender did not create a bias in provider estimation accuracy, providers were more likely to underestimate women's weights than men's. In conclusion, patient self-estimates of weight are significantly better than estimates by providers. Inaccurate estimates by both groups could potentially contribute to medication dosing errors in the ED.

Accounting for measurement error in log regression models with applications to accelerated testing.

PubMed

Richardson, Robert; Tolley, H Dennis; Evenson, William E; Lunt, Barry M

2018-01-01

In regression settings, parameter estimates will be biased when the explanatory variables are measured with error. This bias can significantly affect modeling goals. In particular, accelerated lifetime testing involves an extrapolation of the fitted model, and a small amount of bias in parameter estimates may result in a significant increase in the bias of the extrapolated predictions. Additionally, bias may arise when the stochastic component of a log regression model is assumed to be multiplicative when the actual underlying stochastic component is additive. To account for these possible sources of bias, a log regression model with measurement error and additive error is approximated by a weighted regression model which can be estimated using Iteratively Re-weighted Least Squares. Using the reduced Eyring equation in an accelerated testing setting, the model is compared to previously accepted approaches to modeling accelerated testing data with both simulations and real data.

Unified Heat Kernel Regression for Diffusion, Kernel Smoothing and Wavelets on Manifolds and Its Application to Mandible Growth Modeling in CT Images

PubMed Central

Chung, Moo K.; Qiu, Anqi; Seo, Seongho; Vorperian, Houri K.

2014-01-01

We present a novel kernel regression framework for smoothing scalar surface data using the Laplace-Beltrami eigenfunctions. Starting with the heat kernel constructed from the eigenfunctions, we formulate a new bivariate kernel regression framework as a weighted eigenfunction expansion with the heat kernel as the weights. The new kernel regression is mathematically equivalent to isotropic heat diffusion, kernel smoothing and recently popular diffusion wavelets. Unlike many previous partial differential equation based approaches involving diffusion, our approach represents the solution of diffusion analytically, reducing numerical inaccuracy and slow convergence. The numerical implementation is validated on a unit sphere using spherical harmonics. As an illustration, we have applied the method in characterizing the localized growth pattern of mandible surfaces obtained in CT images from subjects between ages 0 and 20 years by regressing the length of displacement vectors with respect to the template surface. PMID:25791435

Prediction of reported consumption of selected fat-containing foods.

PubMed

Tuorila, H; Pangborn, R M

1988-10-01

A total of 100 American females (mean age = 20.8 years) completed a questionnaire, in which their beliefs, evaluations, liking and consumption (frequency, consumption compared to others, intention to consume) of milk, cheese, ice cream, chocolate and "high-fat foods" were measured. For the design and analysis, the basic frame of reference was the Fishbein-Ajzen model of reasoned action, but the final analyses were carried out with stepwise multiple regression analysis. In addition to the components of the Fishbein-Ajzen model, beliefs and evaluations were used as independent variables. On the average, subjects reported liking all the products but not "high-fat foods", and thought that milk and cheese were "good for you" whereas the remaining items were "bad for you". Principal component analysis for beliefs revealed factors related to pleasantness/benefit aspects, to health and weight concern and to the "functionality" of the foods. In stepwise multiple regression analyses, liking was the predominant predictor of reported consumption for all the foods, but various belief factors, particularly those related to concern with weight, also significantly predicted consumption. Social factors played only a minor role. The multiple R's of the predictive functions varied from 0.49 to 0.74. The fact that all four foods studied elicited individual sets of beliefs and belief structures, and that none of them was rated similar to the generic "high-fat foods", emphasizes that consumers attach meaning to integrated food entities rather than to ingredients.

Weight gain and nutritional efficacy in anorexia nervosa.

PubMed

Dempsey, D T; Crosby, L O; Pertschuk, M J; Feurer, I D; Buzby, G P; Mullen, J L

1984-02-01

To evaluate the usefulness of interval weight change in assessing nutritional support efficacy, we studied four anorexia nervosa patients (52% ideal body weight) requiring long-term total parenteral nutrition (TPN) for 63 +/- 18 days. Fluid and electrolyte deficits were corrected before the initiation of nutritional support. Resting energy expenditure was measured before the initiation of TPN and weekly thereafter, using indirect calorimetry. Daily caloric expenditure was estimated at 1.1 X resting energy expenditure, based on previous studies of continuous heart rate monitoring in this patient population. Daily excess calories were calculated as caloric intake minus caloric expenditure. Each patient was weighed daily and linear regression analysis (excess calories versus weight change) was performed for individual patients and the group over intervals of varying length. There was no individual or group correlation between excess calories and weight gain on a daily or weekly interval basis. Cumulative weight changes over the long-term course of TPN correlated significantly with cumulative excess calories for each patient and the whole group (r = +0.82, p less than 0.01). The excess calories required to gain a kilogram body weight ranged from 5569 to 15619 kcal/kg with a mean of 9768. Cumulative long-term weight changes during nutritional repletion in anorexia nervosa are meaningful indicators of caloric balance, but short interval weight changes (daily, weekly) are not. The caloric cost of weight gain is variable in this population.

Relationship between body composition and vertical ground reaction forces in obese children when walking.

PubMed

Villarrasa-Sapiña, Israel; Serra-Añó, Pilar; Pardo-Ibáñez, Alberto; Gonzalez, Luis-Millán; García-Massó, Xavier

2017-01-01

Obesity is now a serious worldwide challenge, especially in children. This condition can cause a number of different health problems, including musculoskeletal disorders, some of which are due to mechanical stress caused by excess body weight. The aim of this study was to determine the association between body composition and the vertical ground reaction force produced during walking in obese children. Sixteen children participated in the study, six females and ten males [11.5 (1.2) years old, 69.8 (15.5) kg, 1.56 (0.09) m, and 28.36 (3.74) kg/m 2 of body mass index (BMI)]. Total weight, lean mass and fat mass were measured by dual-energy X-ray absorptiometry and vertical forces while walking were obtained by a force platform. The vertical force variables analysed were impact and propulsive forces, and the rate of development of both. Multiple regression models for each vertical force parameter were calculated using the body composition variables as input. The impact force regression model was found to be positively related to the weight of obese children and negatively related to lean mass. The regression model showed lean mass was positively related to the propulsive rate. Finally, regression models for impact and propulsive force showed a direct relationship with body weight. Impact force is positively related to the weight of obese children, but lean mass helps to reduce the impact force in this population. Exercise could help obese persons to reduce their total body weight and increase their lean mass, thus reducing impact forces during sports and other activities. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multiplex network analysis of employee performance and employee social relationships

NASA Astrophysics Data System (ADS)

Cai, Meng; Wang, Wei; Cui, Ying; Stanley, H. Eugene

2018-01-01

In human resource management, employee performance is strongly affected by both formal and informal employee networks. Most previous research on employee performance has focused on monolayer networks that can represent only single categories of employee social relationships. We study employee performance by taking into account the entire multiplex structure of underlying employee social networks. We collect three datasets consisting of five different employee relationship categories in three firms, and predict employee performance using degree centrality and eigenvector centrality in a superimposed multiplex network (SMN) and an unfolded multiplex network (UMN). We use a quadratic assignment procedure (QAP) analysis and a regression analysis to demonstrate that the different categories of relationship are mutually embedded and that the strength of their impact on employee performance differs. We also use weighted/unweighted SMN/UMN to measure the predictive accuracy of this approach and find that employees with high centrality in a weighted UMN are more likely to perform well. Our results shed new light on how social structures affect employee performance.

Trauma injury in adult underweight patients

PubMed Central

Hsieh, Ching-Hua; Lai, Wei-Hung; Wu, Shao-Chun; Chen, Yi-Chun; Kuo, Pao-Jen; Hsu, Shiun-Yuan; Hsieh, Hsiao-Yun

2017-01-01

Abstract The aim of this study was to investigate and compare the injury characteristics, severity, and outcome between underweight and normal-weight patients hospitalized for the treatment of all kinds of trauma injury. This study was based on a level I trauma center Taiwan. The detailed data of 640 underweight adult trauma patients with a body mass index (BMI) of <18.5 kg/m2 and 6497 normal-weight adult patients (25 > BMI ≥ 18.5 kg/m2) were retrieved from the Trauma Registry System between January 1, 2009, and December 31, 2014. Pearson's chi-square test, Fisher's exact test, and independent Student's t-test were performed to compare the differences. Propensity score matching with logistic regression was used to evaluate the effect of underweight on mortality. Underweight patients presented a different bodily injury pattern and a significantly higher rate of admittance to the intensive care unit (ICU) than did normal-weight patients; however, no significant differences in the Glasgow Coma Scale (GCS) score, injury severity score (ISS), in-hospital mortality, and hospital length of stay were found between the two groups. However, further analysis of the patients stratified by two major injury mechanisms (motorcycle accident and fall injury) revealed that underweight patients had significantly lower GCS scores (13.8 ± 3.0 vs 14.5 ± 2.0, P = 0.020), but higher ISS (10.1 ± 6.9 vs 8.4 ± 5.9, P = 0.005), in-hospital mortality (odds ratio, 4.4; 95% confidence interval, 1.69–11.35; P = 0.006), and ICU admittance rate (24.1% vs 14.3%, P = 0.007) than normal-weight patients in the fall accident group, but not in the motorcycle accident group. However, after propensity score matching, logistic regression analysis of well-matched pairs of patients with either all trauma, motorcycle accident, or fall injury did not show a significant influence of underweight on mortality. Exploratory data analysis revealed that underweight patients presented a different bodily injury pattern from that of normal-weight patients, specifically a higher incidence of pneumothorax in those with penetrating injuries and of femoral fracture in those with struck on/against injuries; however, the injury severity and outcome of underweight patients varied depending on the injury mechanism. PMID:28272241

Evidence in support of foster care during acute refugee crises.

PubMed

Duerr, Ann; Posner, Samuel F; Gilbert, Mark

2003-11-01

The United Nations High Commissioner on Refugees (UNHCR) and United Nations Children's Fund (UNICEF) policy encourages foster care during refugee emergencies. We examined evidence to support this policy using data from the 1994 Rwandan refugee crisis. The association of weight gain and acute illness with family status (foster children vs children living with their biological families) was examined using latent growth curve and repeated measures logistic regression analysis. Weight gain for all children averaged 0.40 kg/month and was associated with child's age but not with family status, child's or caregiver's sex, caregiver's marital status, possession of blankets or plastic sheeting, severe malnutrition, month of enrollment, or acute illness. Illness was not more common among foster children than among children living with their biological families. This analysis supports the UNHCR/UNICEF recommendation of fostering for unaccompanied children during an acute refugee crisis.

Spatial Durbin model analysis macroeconomic loss due to natural disasters

NASA Astrophysics Data System (ADS)

Kusrini, D. E.; Mukhtasor

2015-03-01

Magnitude of the damage and losses caused by natural disasters is huge for Indonesia, therefore this study aimed to analyze the effects of natural disasters for macroeconomic losses that occurred in 115 cities/districts across Java during 2012. Based on the results of previous studies it is suspected that it contains effects of spatial dependencies in this case, so that the completion of this case is performed using a regression approach to the area, namely Analysis of Spatial Durbin Model (SDM). The obtained significant predictor variable is population, and predictor variable with a significant weighting is the number of occurrences of disasters, i.e., disasters in the region which have an impact on other neighboring regions. Moran's I index value using the weighted Queen Contiguity also showed significant results, meaning that the incidence of disasters in the region will decrease the value of GDP in other.

Analyzing Health-Related Quality of Life Data to Estimate Parameters for Cost-Effectiveness Models: An Example Using Longitudinal EQ-5D Data from the SHIFT Randomized Controlled Trial.

PubMed

Griffiths, Alison; Paracha, Noman; Davies, Andrew; Branscombe, Neil; Cowie, Martin R; Sculpher, Mark

2017-03-01

The aim of this article is to discuss methods used to analyze health-related quality of life (HRQoL) data from randomized controlled trials (RCTs) for decision analytic models. The analysis presented in this paper was used to provide HRQoL data for the ivabradine health technology assessment (HTA) submission in chronic heart failure. We have used a large, longitudinal EuroQol five-dimension questionnaire (EQ-5D) dataset from the Systolic Heart Failure Treatment with the I f Inhibitor Ivabradine Trial (SHIFT) (clinicaltrials.gov: NCT02441218) to illustrate issues and methods. HRQoL weights (utility values) were estimated from a mixed regression model developed using SHIFT EQ-5D data (n = 5313 patients). The regression model was used to predict HRQoL outcomes according to treatment, patient characteristics, and key clinical outcomes for patients with a heart rate ≥75 bpm. Ivabradine was associated with an HRQoL weight gain of 0.01. HRQoL weights differed according to New York Heart Association (NYHA) class (NYHA I-IV, no hospitalization: standard care 0.82-0.46; ivabradine 0.84-0.47). A reduction in HRQoL weight was associated with hospitalizations within 30 days of an HRQoL assessment visit, with this reduction varying by NYHA class [-0.07 (NYHA I) to -0.21 (NYHA IV)]. The mixed model explained variation in EQ-5D data according to key clinical outcomes and patient characteristics, providing essential information for long-term predictions of patient HRQoL in the cost-effectiveness model. This model was also used to estimate the loss in HRQoL associated with hospitalizations. In SHIFT many hospitalizations did not occur close to EQ-5D visits; hence, any temporary changes in HRQoL associated with such events would not be captured fully in observed RCT evidence, but could be predicted in our cost-effectiveness analysis using the mixed model. Given the large reduction in hospitalizations associated with ivabradine this was an important feature of the analysis. The Servier Research Group.

The impact assessment of weight loss on an aggressive behavior and satisfaction with the connubial or cohabitation relationship in patients after Roux-en-Y gastric-by-pass surgery performed laparoscopically.

PubMed

Bielecka, Ilona; Osemek, Paweł; Paśnik, Krzysztof

2012-09-01

was an assesment the impact of weight loss in patients undergoing gastric by-pass surgery on an aggressive behavior affecting the satisfaction with the connubial or cohabitation relationship The study included a total number of 100 people (50 people with morbid obesity underwent gastric-bypass surgery and their male or female partners). The study was conducted by using two questionnaires: the Psychological Inventory of Aggression Syndrome-1 authorship by Z.B. Gaś as well as Extinguishes and the Chosen Marriage Questionnaire-2 developed by M. Plop and J. Rostowski The analysis of the results showed the influence of the weight loss on the aggressive behaviour at the examined group. Important differences were shown in the first phase of the examination among the examined group and the control group on scales: emotional self-aggression, the hostility towards surroundings and directed outside aggression. Regression analysis showed a statistical relationship between outward aggression and disappointment, 0.346 p<0.01, intimacy 0.943 p<0.01, and the result of general satisfaction with the relationship 0.832 p<0.05.While self-realization is negatively correlated with a displaced aggression -0.342 p<0.01 and the intermediate one -0.225 p<0.01. Hostility towards the environment correlates positively with intimacy 0.326 p<0.01. Indirect aggression correlates negatively with a disappointment -0.324 for p <0.05. Important differences were shown in the second stage of the examination among groups examined on the scale inspection of the aggressive behaviour. Substantial results weren't demonstrated on scales: emotional self-aggression, hostility towards the environment and directed outside aggression In the regression analysis we received a statistically significant result: controlling an aggressive behavior correlates negatively with disappointment -0, 355 p <0,01. However, no statistically significant results were received from the partners of obese people. Weight loss after gastric-by-pass surgery has the significant impact on the rarer occurrence of an aggressive behavior, which improving the quality of the connubial or cohabitation relationship.

Participant Characteristics in the Kumamoto University Regional Center of Japan Environment and Children's Study (JECS): Association of Pregnancy Outcomes with Pregestational Maternal Body Mass Index and Maternal Weight Gain during Pregnancy.

PubMed

Kaimura, Michiko; Oda, Masako; Mitsubuchi, Hiroshi; Ohba, Takashi; Katoh, Takahiko

2017-01-01

The purpose of this study was to identify participant characteristics in the Kumamoto University Regional Center of the Japan Environment and Children's Study (K-JECS) and to investigate the association of pregnancy outcomes with pregestational maternal body mass index (BMI) and maternal weight gain during pregnancy (MWG). The subjects were women with singleton birth, who had been recruited by the K-JECS, and were registered in the data systems for the first and second questionnaires and transcripts of medical records. The subjects were categorized by BMI with further classification by MWG. The chi-squared test and one-way analysis of variance were performed to determine the correlations of BMI and MWG with perinatal outcomes. Logistic regression analysis was performed to examine perinatal outcome risks. The subject characteristics were similar to the trends observed in the Japanese general population. The odds ratio for natural delivery was low in the overweight groups (OW) and normal weight groups (NW) with excessive weight gain. On the other hand, the risk of cesarean section was high in the OW, and risk of induced or accelerated delivery was high in the NW with excessive weight gain. The risks of preterm birth and LBW were high in the insufficient weight gain groups regardless of BMI. The risks of pregnancy-induced hypertension and gestational diabetes were high in the OW.

Anthropometric measurements and vertebral deformities. European Vertebral Osteoporosis Study (EVOS) Group.

PubMed

Johnell, O; O'Neill, T; Felsenberg, D; Kanis, J; Cooper, C; Silman, A J

1997-08-15

To investigate the association between anthropometric indices and morphometrically determined vertebral deformity, the authors carried out a cross-sectional study using data from the European Vertebral Osteoporosis Study (EVOS), a population-based study of vertebral osteoporosis in 36 European centers from 19 countries. A total of 16,047 EVOS subjects were included in this analysis, of whom 1,973 subjects (915 males, 1,058 females) (12.3%) aged 50 years or over had one or more vertebral deformities ("cases"). The cases were compared with the 14,074 subjects (6,539 males, 7,535 females) with morphometrically normal spines ("controls"). Data were collected on self-reported height at age 25 years and minimum weight after age 25 years, as well as on current measured height and weight. Body mass index (BMI) and height and weight change were calculated from these data. The relations between these variables and vertebral deformity were examined separately by sex with logistic regression adjusting for age, smoking, and physical activity. In females, there was a significant trend of decreasing risk with increasing quintile of current weight, current BMI, and weight gain since age 25 years. In males, subjects in the lightest quintile for these measures were at increased risk but there was no evidence of a trend. An ecologic analysis by country revealed a negative correlation between mean BMI and the prevalence of deformity in females but not in males. The authors conclude that low body weight is associated with presence of vertebral deformity.

Effectiveness of the New Hampshire stream-gaging network in providing regional streamflow information

USGS Publications Warehouse

Olson, Scott A.

2003-01-01

The stream-gaging network in New Hampshire was analyzed for its effectiveness in providing regional information on peak-flood flow, mean-flow, and low-flow frequency. The data available for analysis were from stream-gaging stations in New Hampshire and selected stations in adjacent States. The principles of generalized-least-squares regression analysis were applied to develop regional regression equations that relate streamflow-frequency characteristics to watershed characteristics. Regression equations were developed for (1) the instantaneous peak flow with a 100-year recurrence interval, (2) the mean-annual flow, and (3) the 7-day, 10-year low flow. Active and discontinued stream-gaging stations with 10 or more years of flow data were used to develop the regression equations. Each stream-gaging station in the network was evaluated and ranked on the basis of how much the data from that station contributed to the cost-weighted sampling-error component of the regression equation. The potential effect of data from proposed and new stream-gaging stations on the sampling error also was evaluated. The stream-gaging network was evaluated for conditions in water year 2000 and for estimated conditions under various network strategies if an additional 5 years and 20 years of streamflow data were collected. The effectiveness of the stream-gaging network in providing regional streamflow information could be improved for all three flow characteristics with the collection of additional flow data, both temporally and spatially. With additional years of data collection, the greatest reduction in the average sampling error of the regional regression equations was found for the peak- and low-flow characteristics. In general, additional data collection at stream-gaging stations with unregulated flow, relatively short-term record (less than 20 years), and drainage areas smaller than 45 square miles contributed the largest cost-weighted reduction to the average sampling error of the regional estimating equations. The results of the network analyses can be used to prioritize the continued operation of active stations, the reactivation of discontinued stations, or the activation of new stations to maximize the regional information content provided by the stream-gaging network. Final decisions regarding altering the New Hampshire stream-gaging network would require the consideration of the many uses of the streamflow data serving local, State, and Federal interests.

Random regression models for the prediction of days to weight, ultrasound rib eye area, and ultrasound back fat depth in beef cattle.

PubMed

Speidel, S E; Peel, R K; Crews, D H; Enns, R M

2016-02-01

Genetic evaluation research designed to reduce the required days to a specified end point has received very little attention in pertinent scientific literature, given that its economic importance was first discussed in 1957. There are many production scenarios in today's beef industry, making a prediction for the required number of days to a single end point a suboptimal option. Random regression is an attractive alternative to calculate days to weight (DTW), days to ultrasound back fat (DTUBF), and days to ultrasound rib eye area (DTUREA) genetic predictions that could overcome weaknesses of a single end point prediction. The objective of this study was to develop random regression approaches for the prediction of the DTW, DTUREA, and DTUBF. Data were obtained from the Agriculture and Agri-Food Canada Research Centre, Lethbridge, AB, Canada. Data consisted of records on 1,324 feedlot cattle spanning 1999 to 2007. Individual animals averaged 5.77 observations with weights, ultrasound rib eye area (UREA), ultrasound back fat depth (UBF), and ages ranging from 293 to 863 kg, 73.39 to 129.54 cm, 1.53 to 30.47 mm, and 276 to 519 d, respectively. Random regression models using Legendre polynomials were used to regress age of the individual on weight, UREA, and UBF. Fixed effects in the model included an overall fixed regression of age on end point (weight, UREA, and UBF) nested within breed to account for the mean relationship between age and weight as well as a contemporary group effect consisting of breed of the animal (Angus, Charolais, and Charolais sired), feedlot pen, and year of measure. Likelihood ratio tests were used to determine the appropriate random polynomial order. Use of the quadratic polynomial did not account for any additional genetic variation in days for DTW ( > 0.11), for DTUREA ( > 0.18), and for DTUBF ( > 0.20) when compared with the linear random polynomial. Heritability estimates from the linear random regression for DTW ranged from 0.54 to 0.74, corresponding to end points of 293 and 863 kg, respectively. Heritability for DTUREA ranged from 0.51 to 0.34 and for DTUBF ranged from 0.55 to 0.37. These estimates correspond to UREA end points of 35 and 125 cm and UBF end points of 1.53 and 30 mm, respectively. This range of heritability shows DTW, DTUREA, and DTUBF to be highly heritable and indicates that selection pressure aimed at reducing the number of days to reach a finish weight end point can result in genetic change given sufficient data.

Estimation of liver T₂ in transfusion-related iron overload in patients with weighted least squares T₂ IDEAL.

PubMed

Vasanawala, Shreyas S; Yu, Huanzhou; Shimakawa, Ann; Jeng, Michael; Brittain, Jean H

2012-01-01

MRI imaging of hepatic iron overload can be achieved by estimating T(2) values using multiple-echo sequences. The purpose of this work is to develop and clinically evaluate a weighted least squares algorithm based on T(2) Iterative Decomposition of water and fat with Echo Asymmetry and Least-squares estimation (IDEAL) technique for volumetric estimation of hepatic T(2) in the setting of iron overload. The weighted least squares T(2) IDEAL technique improves T(2) estimation by automatically decreasing the impact of later, noise-dominated echoes. The technique was evaluated in 37 patients with iron overload. Each patient underwent (i) a standard 2D multiple-echo gradient echo sequence for T(2) assessment with nonlinear exponential fitting, and (ii) a 3D T(2) IDEAL technique, with and without a weighted least squares fit. Regression and Bland-Altman analysis demonstrated strong correlation between conventional 2D and T(2) IDEAL estimation. In cases of severe iron overload, T(2) IDEAL without weighted least squares reconstruction resulted in a relative overestimation of T(2) compared with weighted least squares. Copyright © 2011 Wiley-Liss, Inc.

Analysis of Skeletal Muscle Metrics as Predictors of Functional Task Performance

NASA Technical Reports Server (NTRS)

Ryder, Jeffrey W.; Buxton, Roxanne E.; Redd, Elizabeth; Scott-Pandorf, Melissa; Hackney, Kyle J.; Fiedler, James; Ploutz-Snyder, Robert J.; Bloomberg, Jacob J.; Ploutz-Snyder, Lori L.

2010-01-01

PURPOSE: The ability to predict task performance using physiological performance metrics is vital to ensure that astronauts can execute their jobs safely and effectively. This investigation used a weighted suit to evaluate task performance at various ratios of strength, power, and endurance to body weight. METHODS: Twenty subjects completed muscle performance tests and functional tasks representative of those that would be required of astronauts during planetary exploration (see table for specific tests/tasks). Subjects performed functional tasks while wearing a weighted suit with additional loads ranging from 0-120% of initial body weight. Performance metrics were time to completion for all tasks except hatch opening, which consisted of total work. Task performance metrics were plotted against muscle metrics normalized to "body weight" (subject weight + external load; BW) for each trial. Fractional polynomial regression was used to model the relationship between muscle and task performance. CONCLUSION: LPMIF/BW is the best predictor of performance for predominantly lower-body tasks that are ambulatory and of short duration. LPMIF/BW is a very practical predictor of occupational task performance as it is quick and relatively safe to perform. Accordingly, bench press work best predicts hatch-opening work performance.