NASA Astrophysics Data System (ADS)
Han, W.; Stammer, D.; Meehl, G. A.; Hu, A.; Sienz, F.
2016-12-01
Sea level varies on decadal and multi-decadal timescales over the Indian Ocean. The variations are not spatially uniform, and can deviate considerably from the global mean sea level rise (SLR) due to various geophysical processes. One of these processes is the change of ocean circulation, which can be partly attributed to natural internal modes of climate variability. Over the Indian Ocean, the most influential climate modes on decadal and multi-decadal timescales are the Interdecadal Pacific Oscillation (IPO) and decadal variability of the Indian Ocean dipole (IOD). Here, we first analyze observational datasets to investigate the impacts of IPO and IOD on spatial patterns of decadal and interdecadal (hereafter decal) sea level variability & multi-decadal trend over the Indian Ocean since the 1950s, using a new statistical approach of Bayesian Dynamical Linear regression Model (DLM). The Bayesian DLM overcomes the limitation of "time-constant (static)" regression coefficients in conventional multiple linear regression model, by allowing the coefficients to vary with time and therefore measuring "time-evolving (dynamical)" relationship between climate modes and sea level. For the multi-decadal sea level trend since the 1950s, our results show that climate modes and non-climate modes (the part that cannot be explained by climate modes) have comparable contributions in magnitudes but with different spatial patterns, with each dominating different regions of the Indian Ocean. For decadal variability, climate modes are the major contributors for sea level variations over most region of the tropical Indian Ocean. The relative importance of IPO and decadal variability of IOD, however, varies spatially. For example, while IOD decadal variability dominates IPO in the eastern equatorial basin (85E-100E, 5S-5N), IPO dominates IOD in causing sea level variations in the tropical southwest Indian Ocean (45E-65E, 12S-2S). To help decipher the possible contribution of external forcing to the multi-decadal sea level trend and decadal variability, we also analyze the model outputs from NCAR's Community Earth System Model (CESM) Large Ensemble Experiments, and compare the results with our observational analyses.
Publication bias in obesity treatment trials?
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.
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.
Development of Super-Ensemble techniques for ocean analyses: the Mediterranean Sea case
NASA Astrophysics Data System (ADS)
Pistoia, Jenny; Pinardi, Nadia; Oddo, Paolo; Collins, Matthew; Korres, Gerasimos; Drillet, Yann
2017-04-01
Short-term ocean analyses for Sea Surface Temperature SST in the Mediterranean Sea can be improved by a statistical post-processing technique, called super-ensemble. This technique consists in a multi-linear regression algorithm applied to a Multi-Physics Multi-Model Super-Ensemble (MMSE) dataset, a collection of different operational forecasting analyses together with ad-hoc simulations produced by modifying selected numerical model parameterizations. A new linear regression algorithm based on Empirical Orthogonal Function filtering techniques is capable to prevent overfitting problems, even if best performances are achieved when we add correlation to the super-ensemble structure using a simple spatial filter applied after the linear regression. Our outcomes show that super-ensemble performances depend on the selection of an unbiased operator and the length of the learning period, but the quality of the generating MMSE dataset has the largest impact on the MMSE analysis Root Mean Square Error (RMSE) evaluated with respect to observed satellite SST. Lower RMSE analysis estimates result from the following choices: 15 days training period, an overconfident MMSE dataset (a subset with the higher quality ensemble members), and the least square algorithm being filtered a posteriori.
Subjective Well-being in Rural India: The Curse of Conspicuous Consumption
van Kempen, Luuk; Kraaykamp, Gerbert
2010-01-01
Using data on 697 individuals from 375 rural low income households in India, we test expectations on the effects of relative income and conspicuous consumption on subjective well-being. The results of the multi-level regression analyses show that individuals who spent more on conspicuous consumption report lower levels of subjective well-being. Surprisingly an individual’s relative income position does not affect feelings of well-being. Motivated by positional concerns, people do not passively accept their relative rank but instead consume conspicuous goods to keep up with the Joneses. Conspicuous consumption always comes at the account of the consumption of basic needs. Our analyses point at a positional treadmill effect of the consumption of status goods. PMID:21423323
Li, Ji; Gray, B.R.; Bates, D.M.
2008-01-01
Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.
Crush Analyses of Multi-Level Equipment
DOT National Transportation Integrated Search
2006-11-06
Non-linear large deformation crush analyses were conducted on a multi-level cab car typical of those in operation by the Southern California Regional Rail Authority (SCRRA) in California. The motivation for these analyses was a collision, which occur...
Arsenic levels in drinking water and mortality of liver cancer in Taiwan.
Lin, Hung-Jung; Sung, Tzu-I; Chen, Chi-Yi; Guo, How-Ran
2013-11-15
The carcinogenic effect of arsenic is well documented, but epidemiologic data on liver cancer were limited. To evaluate the dose-response relationship between arsenic in drinking water and mortality of liver cancer, we conducted a study in 138 villages in the southwest coast area of Taiwan. We assessed arsenic levels in drinking water using data from a survey conducted by the government and reviewed death certificates from 1971 to 1990 to identify liver cancer cases. Using village as the unit, we conducted multi-variate regression analyses and then performed post hoc analyses to validate the findings. During the 20-year period, 802 male and 301 female mortality cases of liver cancer were identified. After adjusting for age, arsenic levels above 0.64 mg/L were associated with an increase in the liver cancer mortality in both genders, but no significant effect was observed for lower exposure categories. Post hoc analyses and a review of literature supported these findings. We concluded that exposures to high arsenic levels in drinking water are associated with the occurrence of liver cancer, but such an effect is not prominent at exposure levels lower than 0.64 mg/L. Copyright © 2013 Elsevier B.V. All rights reserved.
NASA Astrophysics Data System (ADS)
Bernales, A. M.; Antolihao, J. A.; Samonte, C.; Campomanes, F.; Rojas, R. J.; dela Serna, A. M.; Silapan, J.
2016-06-01
The threat of the ailments related to urbanization like heat stress is very prevalent. There are a lot of things that can be done to lessen the effect of urbanization to the surface temperature of the area like using green roofs or planting trees in the area. So land use really matters in both increasing and decreasing surface temperature. It is known that there is a relationship between land use land cover (LULC) and land surface temperature (LST). Quantifying this relationship in terms of a mathematical model is very important so as to provide a way to predict LST based on the LULC alone. This study aims to examine the relationship between LST and LULC as well as to create a model that can predict LST using class-level spatial metrics from LULC. LST was derived from a Landsat 8 image and LULC classification was derived from LiDAR and Orthophoto datasets. Class-level spatial metrics were created in FRAGSTATS with the LULC and LST as inputs and these metrics were analysed using a statistical framework. Multi linear regression was done to create models that would predict LST for each class and it was found that the spatial metric "Effective mesh size" was a top predictor for LST in 6 out of 7 classes. The model created can still be refined by adding a temporal aspect by analysing the LST of another farming period (for rural areas) and looking for common predictors between LSTs of these two different farming periods.
Althaus, Rafael; Berruga, Maria Isabel; Montero, Ana; Roca, Marta; Molina, Maria Pilar
2009-01-19
To protect both, public health and the dairy industry, from the presence of antibiotic residues in milk, control programmes have been established, which include the needed screening tests. This work focuses on the application of a Microbiological Multi-Residue System in ewe milk, a method based on the use of six different plates, each seeded with one of the following bacteria: Geobacillus stearothermophilus var. calidolactis (beta-lactams), Bacillus subtilis at pH 8.0 (aminoglycosides), Kocuria rhizophila (macrolides), Escherichia coli (quinolones), B. cereus (tetracyclines) and B. subtilis at pH 7.0 (sulphonamides), respectively. Twenty-three antimicrobial substances were analysed and a logistic regression was established for each substance assayed to relate the antibiotic concentration and the zone of microbial growth inhibition. Great linearity in the response was observed (regression coefficients of over 0.97). This fact suggests the possibility of establishing a decision level of antibiotic concentrations near to the Maximum Residue Limits (MRL). Zones of inhibition were suggested as proposed action levels for the different antimicrobial groups (diameters of inhibition of 18 mm for the aminoglycoside, beta-lactam and sulphonamide plates; 19 mm for the tetracycline plate, 21 mm for the macrolide plate, and 24 mm for the quinolone plate). Specificity and cross-reactivity were also assayed.
Climate change and epidemics in Chinese history: A multi-scalar analysis.
Lee, Harry F; Fei, Jie; Chan, Christopher Y S; Pei, Qing; Jia, Xin; Yue, Ricci P H
2017-02-01
This study seeks to provide further insight regarding the relationship of climate-epidemics in Chinese history through a multi-scalar analysis. Based on 5961 epidemic incidents in China during 1370-1909 CE we applied Ordinary Least Square regression and panel data regression to verify the climate-epidemic nexus over a range of spatial scales (country, macro region, and province). Results show that epidemic outbreaks were negatively correlated with the temperature in historical China at various geographic levels, while a stark reduction in the correlational strength was observed at lower geographic levels. Furthermore, cooling drove up epidemic outbreaks in northern and central China, where population pressure reached a clear threshold for amplifying the vulnerability of epidemic outbreaks to climate change. Our findings help to illustrate the modifiable areal unit and the uncertain geographic context problems in climate-epidemics research. Researchers need to consider the scale effect in the course of statistical analyses, which are currently predominantly conducted on a national/single scale; and also the importance of how the study area is delineated, an issue which is rarely discussed in the climate-epidemics literature. Future research may leverage our results and provide a cross-analysis with those derived from spatial analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.
Zhang, Xinyan; Li, Bingzong; Han, Huiying; Song, Sha; Xu, Hongxia; Hong, Yating; Yi, Nengjun; Zhuang, Wenzhuo
2018-05-10
Multiple myeloma (MM), like other cancers, is caused by the accumulation of genetic abnormalities. Heterogeneity exists in the patients' response to treatments, for example, bortezomib. This urges efforts to identify biomarkers from numerous molecular features and build predictive models for identifying patients that can benefit from a certain treatment scheme. However, previous studies treated the multi-level ordinal drug response as a binary response where only responsive and non-responsive groups are considered. It is desirable to directly analyze the multi-level drug response, rather than combining the response to two groups. In this study, we present a novel method to identify significantly associated biomarkers and then develop ordinal genomic classifier using the hierarchical ordinal logistic model. The proposed hierarchical ordinal logistic model employs the heavy-tailed Cauchy prior on the coefficients and is fitted by an efficient quasi-Newton algorithm. We apply our hierarchical ordinal regression approach to analyze two publicly available datasets for MM with five-level drug response and numerous gene expression measures. Our results show that our method is able to identify genes associated with the multi-level drug response and to generate powerful predictive models for predicting the multi-level response. The proposed method allows us to jointly fit numerous correlated predictors and thus build efficient models for predicting the multi-level drug response. The predictive model for the multi-level drug response can be more informative than the previous approaches. Thus, the proposed approach provides a powerful tool for predicting multi-level drug response and has important impact on cancer studies.
Overweight and obesity in India: policy issues from an exploratory multi-level analysis.
Siddiqui, Md Zakaria; Donato, Ronald
2016-06-01
This article analyses a nationally representative household dataset-the National Family Health Survey (NFHS-3) conducted in 2005 to 2006-to examine factors influencing the prevalence of overweight/obesity in India. The dataset was disaggregated into four sub-population groups-urban and rural females and males-and multi-level logit regression models were used to estimate the impact of particular covariates on the likelihood of overweight/obesity. The multi-level modelling approach aimed to identify individual and macro-level contextual factors influencing this health outcome. In contrast to most studies on low-income developing countries, the findings reveal that education for females beyond a particular level of educational attainment exhibits a negative relationship with the likelihood of overweight/obesity. This relationship was not observed for males. Muslim females and all Sikh sub-populations have a higher likelihood of overweight/obesity suggesting the importance of socio-cultural influences. The results also show that the relationship between wealth and the probability of overweight/obesity is stronger for males than females highlighting the differential impact of increasing socio-economic status on gender. Multi-level analysis reveals that states exerted an independent influence on the likelihood of overweight/obesity beyond individual-level covariates, reflecting the importance of spatially related contextual factors on overweight/obesity. While this study does not disentangle macro-level 'obesogenic' environmental factors from socio-cultural network influences, the results highlight the need to refrain from adopting a 'one size fits all' policy approach in addressing the overweight/obesity epidemic facing India. Instead, policy implementation requires a more nuanced and targeted approach to incorporate the growing recognition of socio-cultural and spatial contextual factors impacting on healthy behaviours. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please email: journals.permissions@oup.com.
Murphy, Adrianna; Roberts, Bayard; Ploubidis, George B; Stickley, Andrew; McKee, Martin
2014-05-01
The purpose of this study was to assess whether alcohol-related community characteristics act collectively to influence individual-level alcohol consumption in the former Soviet Union (fSU). Using multi-level data from nine countries in the fSU we conducted a factor analysis of seven alcohol-related community characteristics. The association between any latent factors underlying these characteristics and two measures of hazardous alcohol consumption was then analysed using a population average regression modelling approach. Our factor analysis produced one factor with an eigenvalue >1 (EV=1.28), which explained 94% of the variance. This factor was statistically significantly associated with increased odds of CAGE problem drinking (OR=1.40 (1.08-1.82)). The estimated association with EHD was not statistically significant (OR=1.10 (0.85-1.44)). Our findings suggest that a high number of beer, wine and spirit advertisements and high alcohol outlet density may work together to create an 'alcogenic' environment that encourages hazardous alcohol consumption in the fSU. Copyright © 2014 Elsevier Ltd. All rights reserved.
Uddin, Shahadat
2016-02-04
A patient-centric care network can be defined as a network among a group of healthcare professionals who provide treatments to common patients. Various multi-level attributes of the members of this network have substantial influence to its perceived level of performance. In order to assess the impact different multi-level attributes of patient-centric care networks on healthcare outcomes, this study first captured patient-centric care networks for 85 hospitals using health insurance claim dataset. From these networks, this study then constructed physician collaboration networks based on the concept of patient-sharing network among physicians. A multi-level regression model was then developed to explore the impact of different attributes that are organised at two levels on hospitalisation cost and hospital length of stay. For Level-1 model, the average visit per physician significantly predicted both hospitalisation cost and hospital length of stay. The number of different physicians significantly predicted only the hospitalisation cost, which has significantly been moderated by age, gender and Comorbidity score of patients. All Level-1 findings showed significance variance across physician collaboration networks having different community structure and density. These findings could be utilised as a reflective measure by healthcare decision makers. Moreover, healthcare managers could consider them in developing effective healthcare environments.
NASA Astrophysics Data System (ADS)
Jedlikowski, Jan; Chibowski, Piotr; Karasek, Tomasz; Brambilla, Mattia
2016-05-01
Habitat selection often involves choices made at different spatial scales, but the underlying mechanisms are still poorly understood, and studies that investigate the relative importance of individual scales are rare. We investigated the effect of three spatial scales (landscape, territory, nest-site) on the occurrence pattern of little crake Zapornia parva and water rail Rallus aquaticus at 74 ponds in the Masurian Lakeland, Poland. Habitat structure, food abundance and water chemical parameters were measured at nests and random points within landscape plots (from 300-m to 50-m radius), territory (14-m) and nest-site plots (3-m). Regression analyses suggested that the most relevant scale was territory level, followed by landscape, and finally by nest-site for both species. Variation partitioning confirmed this pattern for water rail, but also highlighted the importance of nest-site (the level explaining the highest share of unique variation) for little crake. The most important variables determining the occurrence of both species were water body fragmentation (landscape), vegetation density (territory) and water depth (at territory level for little crake, and at nest-site level for water rail). Finally, for both species multi-scale models including factors from different levels were more parsimonious than single-scale ones, i.e. habitat selection was likely a multi-scale process. The importance of particular spatial scales seemed more related to life-history traits than to the extent of the scales considered. In the case of our study species, the territory level was highly important likely because both rallids have to obtain all the resources they need (nest site, food and mates) in relatively small areas, the multi-purpose territories they defend.
Gaskin, Cadeyrn J; Happell, Brenda
2014-05-01
To (a) assess the statistical power of nursing research to detect small, medium, and large effect sizes; (b) estimate the experiment-wise Type I error rate in these studies; and (c) assess the extent to which (i) a priori power analyses, (ii) effect sizes (and interpretations thereof), and (iii) confidence intervals were reported. Statistical review. Papers published in the 2011 volumes of the 10 highest ranked nursing journals, based on their 5-year impact factors. Papers were assessed for statistical power, control of experiment-wise Type I error, reporting of a priori power analyses, reporting and interpretation of effect sizes, and reporting of confidence intervals. The analyses were based on 333 papers, from which 10,337 inferential statistics were identified. The median power to detect small, medium, and large effect sizes was .40 (interquartile range [IQR]=.24-.71), .98 (IQR=.85-1.00), and 1.00 (IQR=1.00-1.00), respectively. The median experiment-wise Type I error rate was .54 (IQR=.26-.80). A priori power analyses were reported in 28% of papers. Effect sizes were routinely reported for Spearman's rank correlations (100% of papers in which this test was used), Poisson regressions (100%), odds ratios (100%), Kendall's tau correlations (100%), Pearson's correlations (99%), logistic regressions (98%), structural equation modelling/confirmatory factor analyses/path analyses (97%), and linear regressions (83%), but were reported less often for two-proportion z tests (50%), analyses of variance/analyses of covariance/multivariate analyses of variance (18%), t tests (8%), Wilcoxon's tests (8%), Chi-squared tests (8%), and Fisher's exact tests (7%), and not reported for sign tests, Friedman's tests, McNemar's tests, multi-level models, and Kruskal-Wallis tests. Effect sizes were infrequently interpreted. Confidence intervals were reported in 28% of papers. The use, reporting, and interpretation of inferential statistics in nursing research need substantial improvement. Most importantly, researchers should abandon the misleading practice of interpreting the results from inferential tests based solely on whether they are statistically significant (or not) and, instead, focus on reporting and interpreting effect sizes, confidence intervals, and significance levels. Nursing researchers also need to conduct and report a priori power analyses, and to address the issue of Type I experiment-wise error inflation in their studies. Crown Copyright © 2013. Published by Elsevier Ltd. All rights reserved.
Eren, Fatih; Agirbasli, Deniz; White, Marquitta J.; Williams, Scott M
2013-01-01
Abstract Cardiovascular risk factors and atherosclerosis precursors were examined in 365 Turkish children and adolescents. Study participants were recruited at five different state schools. We tested single and multi-locus effects of six polymorphisms from five candidate genes, chosen based on prior known association with lipid levels in adults, for association with low (≤10th percentile) high density lipoprotein cholesterol (HDL-C) and high (≥90th percentile) triglycerides (TG), and the related continuous outcomes. We observed an association between CETP variant rs708272 and low HDL-C (allelic p=0.020, genotypic p=0.046), which was supported by an independent analysis, PRAT (PRAT control p=0.027). Sex-stratified logistic regression analysis showed that the B2 allele of rs708272 decreased odds of being in the lower tenth percentile of HDL-C measurements (OR=0.36, p=0.02) in girls; this direction of effect was also seen in boys but was not significant (OR=0.64, p=0.21). Logistic regression analysis also revealed that the T allele of rs6257 (SHBG) decreased odds of being in the top tenth percentile of TG measurements in boys (OR=0.43, p=0.03). Analysis of lipid levels as a continuous trait revealed a significant association between rs708272 (CETP) and LDL-C levels in males (p=0.02) with the B2B2 genotype group having the lowest mean LDL-C; the same direction of effect was also seen in females (p=0.05). An effect was also seen between rs708272 and HDL-C levels in girls (p=0.01), with the B2B2 genotype having the highest mean HDL-C levels. Multi-locus analysis, using quantitative multifactor dimensionality reduction (qMDR) identified the previously mentioned CETP variant as the best single locus model, and overall model, for predicting HDL-C levels in children. This study provides evidence for association between CETP and low HDL-C phenotype in children, but the results appear to be weaker in children than previous results in adults and may also be subject to gender effects. PMID:23988150
NASA Astrophysics Data System (ADS)
Li, Chengen; Cai, Guobiao; Tian, Hui
2016-06-01
This paper is aimed to analyse the combustion characteristics of hybrid rocket motor with multi-section swirl injection by simulating the combustion flow field. Numerical combustion flow field and combustion performance parameters are obtained through three-dimensional numerical simulations based on a steady numerical model proposed in this paper. The hybrid rocket motor adopts 98% hydrogen peroxide and polyethylene as the propellants. Multiple injection sections are set along the axis of the solid fuel grain, and the oxidizer enters the combustion chamber by means of tangential injection via the injector ports in the injection sections. Simulation results indicate that the combustion flow field structure of the hybrid rocket motor could be improved by multi-section swirl injection method. The transformation of the combustion flow field can greatly increase the fuel regression rate and the combustion efficiency. The average fuel regression rate of the motor with multi-section swirl injection is improved by 8.37 times compared with that of the motor with conventional head-end irrotational injection. The combustion efficiency is increased to 95.73%. Besides, the simulation results also indicate that (1) the additional injection sections can increase the fuel regression rate and the combustion efficiency; (2) the upstream offset of the injection sections reduces the combustion efficiency; and (3) the fuel regression rate and the combustion efficiency decrease with the reduction of the number of injector ports in each injection section.
Zhang, Qun; Zhang, Qunzhi; Sornette, Didier
2016-01-01
We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle (at least partially) the genuine LPPLS signal and the a priori unknown complicated residuals. Second, we propose to combine the many quantile regressions with a multi-scale analysis, which aggregates and consolidates the obtained ensembles of scenarios. Third, we define and implement the so-called DS LPPLS Confidence™ and Trust™ indicators that enrich considerably the diagnostic of bubbles. Using a detailed study of the "S&P 500 1987" bubble and presenting analyses of 16 historical bubbles, we show that the quantile regression of LPPLS signals contributes useful early warning signals. The comparison between the constructed signals and the price development in these 16 historical bubbles demonstrates their significant predictive ability around the real critical time when the burst/rally occurs.
Trude, Angela Cristina Bizzotto; Kharmats, Anna Yevgenyevna; Jones-Smith, Jessica C; Gittelsohn, Joel
2018-05-22
For community interventions to be effective in real-world conditions, participants need to have sufficient exposure to the intervention. It is unclear how the dose and intensity of the intervention differ among study participants in low-income areas. We aimed to understand patterns of exposure to different components of a multi-level multi-component obesity prevention program to inform our future impact analyses. B'more Healthy Communities for Kids (BHCK) was a community-randomized controlled trial implemented in 28 low-income zones in Baltimore in two rounds (waves). Exposure to three different intervention components (corner store/carryout restaurants, social media/text messaging, and youth-led nutrition education) was assessed via post-intervention interviews with 385 low-income urban youths and their caregivers. Exposure scores were generated based on self-reported viewing of BHCK materials (posters, handouts, educational displays, and social media posts) and participating in activities, including taste tests during the intervention. For each intervention component, points were assigned for exposure to study materials and activities, then scaled (0-1 range), yielding an overall BHCK exposure score [youths: mean 1.1 (range 0-7.6 points); caregivers: 1.1 (0-6.7), possible highest score: 13]. Ordered logit regression analyses were used to investigate correlates of youths' and caregivers' exposure level (quartile of exposure). Mean intervention exposure scores were significantly higher for intervention than comparison youths (mean 1.6 vs 0.5, p < 0.001) and caregivers (mean 1.6 vs 0.6, p < 0.001). However, exposure scores were low in both groups and 10% of the comparison group was moderately exposed to the intervention. For each 1-year increase in age, there was a 33% lower odds of being highly exposed to the intervention (odds ratio 0.77, 95% confidence interval 0.69; 0.88) in the unadjusted and adjusted model controlling for youths' sex and household income. Treatment effects may be attenuated in community-based trials, as participants may be differentially exposed to intervention components and the comparison group may also be exposed. Exposure should be measured to provide context to impact evaluations in multi-level trials. Future analyses linking exposure scores to the outcome should control for potential confounders in the treatment-on-the-treated approach, while recognizing that confounding and selection bias may exist affecting causal inference. ClinicalTrials.gov, NCT02181010 . Retrospectively registered on 2 July 2014.
Chabot, Martin; Fallon, Barbara; Tonmyr, Lil; MacLaurin, Bruce; Fluke, John; Blackstock, Cindy
2013-01-01
This paper builds upon the analyses presented in two companion papers (Fluke et al., 2010; Fallon et al., 2013) using data from the 1998 and 2003 cycles of the Canadian Incidence Study of Reported Child Abuse and Neglect (CIS-1998 and CIS-2003) to examine the influence of clinical and organizational characteristics on the decision to place a child in out-of-home care at the conclusion of a child maltreatment investigation. This paper explores various model specifications to explain the effect of an agency-level factor, proportion of Aboriginal reports, which emerged as a stable and significant factor through the two data collection cycles. It addresses the issue of data comparability between the two cycles and explores various re-specifications and descriptive analyses of reported models to evaluate their solidity with regards to the sampling schemes and the precise contribution of a multi-level specification. The decision to place a child in out-of-home care was examined using data from the CIS-2003. This child welfare dataset collected information about the results of nearly 12,000 child maltreatment investigations as well as a description of the characteristics of the workers and organization responsible for conducting those investigations. Multi-level statistical models were developed using MPlus software, which can accommodate dichotomous outcome variables and are more reflective of decision-making in child welfare. The models are thus multi-level binary logistic regressions. Final models revealed that two agency-level variables, 'Education degree of majority of workers' and 'Degree of centralization in the agency' clarify the nature of the effect of 'Proportion of Aboriginal reports', a stable, key second level predictor of the placement decision. The comparability of the effect of this agency-level variable across the 1998 and 2003 cycles becomes further evident through this analysis. By using a unified database including both cycles and various specifications of models, the comparability was found to be robust, in addition to clarifying the precise contribution of a multi-level specification. This third paper in a series establishes the 'Proportion of Aboriginal reports' received by the child welfare agency as an important agency level predictor associated with a child's likelihood of being placed in the Canadian child protection system. While the more complex models give support to the notion that unequal resources subtend those results, more analyses are needed to confirm this hypothesis. Unequal resources for agencies with larger Aboriginal caseloads may explain the persistence of the results. These findings suggest that specific resource constraints related to worker education may be explanatory. Copyright © 2012 Elsevier Ltd. All rights reserved.
Mutumba, Massy; Wekesa, Eliud; Stephenson, Rob
2018-04-02
Despite investment in family planning programs and education, unmet need for family planning remains high among young women (aged 15-24) in low and middle-income countries, increasing the risk for unwanted pregnancies and adverse social and reproductive health outcomes. There is a dearth of cross-national research that identifies the differential impact of community level factors among youth in low and middle-income countries (LMICs), which is imperative for the design of structural level interventions aimed at increasing family planning use. Grounded in the socio-ecological framework, this paper utilizes Demographic and Health Survey (DHS) from 52 LMICs to examine the influence of community level reproductive, gender, fertility, literacy and economic indicators on modern contraceptive use among female youth. Analyses are conducted using multi-level logistic regressions with random community-level effects. Our findings highlight the positive influence of community level education attainment and negative influence of gender and fertility related norms on young women's contraceptive use. Additionally, increased exposure to mass media did not positively influence young women's uptake of modern contraceptive methods. Taken together, findings indicate that young women's contraceptive decision-making is greatly shaped by their social contexts. The commonalities and regional variations in community level influences provide support for both structural level interventions and tailored regional approaches to family planning interventions.
Estelles-Lopez, Lucia; Ropodi, Athina; Pavlidis, Dimitris; Fotopoulou, Jenny; Gkousari, Christina; Peyrodie, Audrey; Panagou, Efstathios; Nychas, George-John; Mohareb, Fady
2017-09-01
Over the past decade, analytical approaches based on vibrational spectroscopy, hyperspectral/multispectral imagining and biomimetic sensors started gaining popularity as rapid and efficient methods for assessing food quality, safety and authentication; as a sensible alternative to the expensive and time-consuming conventional microbiological techniques. Due to the multi-dimensional nature of the data generated from such analyses, the output needs to be coupled with a suitable statistical approach or machine-learning algorithms before the results can be interpreted. Choosing the optimum pattern recognition or machine learning approach for a given analytical platform is often challenging and involves a comparative analysis between various algorithms in order to achieve the best possible prediction accuracy. In this work, "MeatReg", a web-based application is presented, able to automate the procedure of identifying the best machine learning method for comparing data from several analytical techniques, to predict the counts of microorganisms responsible of meat spoilage regardless of the packaging system applied. In particularly up to 7 regression methods were applied and these are ordinary least squares regression, stepwise linear regression, partial least square regression, principal component regression, support vector regression, random forest and k-nearest neighbours. MeatReg" was tested with minced beef samples stored under aerobic and modified atmosphere packaging and analysed with electronic nose, HPLC, FT-IR, GC-MS and Multispectral imaging instrument. Population of total viable count, lactic acid bacteria, pseudomonads, Enterobacteriaceae and B. thermosphacta, were predicted. As a result, recommendations of which analytical platforms are suitable to predict each type of bacteria and which machine learning methods to use in each case were obtained. The developed system is accessible via the link: www.sorfml.com. Copyright © 2017 Elsevier Ltd. All rights reserved.
Schulz, Marcus; Neumann, Daniel; Fleet, David M; Matthies, Michael
2013-12-01
During the last decades, marine pollution with anthropogenic litter has become a worldwide major environmental concern. Standardized monitoring of litter since 2001 on 78 beaches selected within the framework of the Convention for the Protection of the Marine Environment of the North-East Atlantic (OSPAR) has been used to identify temporal trends of marine litter. Based on statistical analyses of this dataset a two-part multi-criteria evaluation system for beach litter pollution of the North-East Atlantic and the North Sea is proposed. Canonical correlation analyses, linear regression analyses, and non-parametric analyses of variance were used to identify different temporal trends. A classification of beaches was derived from cluster analyses and served to define different states of beach quality according to abundances of 17 input variables. The evaluation system is easily applicable and relies on the above-mentioned classification and on significant temporal trends implied by significant rank correlations. Copyright © 2013 Elsevier Ltd. All rights reserved.
Tanaka, Masayuki; Lee, Jason; Ikai, Hiroshi; Imanaka, Yuichi
2013-04-01
The efficiency of a hospital's operating room (OR) management can affect its overall profitability. However, existing indicators that assess OR management efficiency do not take into account differences in hospital size, manpower and functional characteristics, thereby rendering them unsuitable for multi-institutional comparisons. The aim of this study was to develop indicators of OR management efficiency that would take into account differences in hospital size and manpower, which may then be applied to multi-institutional comparisons. Using administrative data from 224 hospitals in Japan from 2008 to 2010, we performed four multiple linear regression analyses at the hospital level, in which the dependent variables were the number of operations per OR per month, procedural fees per OR per month, total utilization times per OR per month and total fees per OR per month for each of the models. The expected values of these four indicators were produced using multiple regression analysis results, adjusting for differences in hospital size and manpower, which are beyond the control of process owners' management. However, more than half of the variations in three of these four indicators were shown to be explained by differences in hospital size and manpower. Using the ratio of observed to expected values (OE ratio), as well as the difference between the two values (OE difference) allows hospitals to identify weaknesses in efficiency with more validity when compared to unadjusted indicators. The new indicators may support the improvement and sustainment of a high-quality health care system. © 2012 Blackwell Publishing Ltd.
Chen, Chunhui; Chen, Chuansheng; Moyzis, Robert; Stern, Hal; He, Qinghua; Li, He; Li, Jin; Zhu, Bi; Dong, Qi
2011-01-01
Traditional behavioral genetic studies (e.g., twin, adoption studies) have shown that human personality has moderate to high heritability, but recent molecular behavioral genetic studies have failed to identify quantitative trait loci (QTL) with consistent effects. The current study adopted a multi-step approach (ANOVA followed by multiple regression and permutation) to assess the cumulative effects of multiple QTLs. Using a system-level (dopamine system) genetic approach, we investigated a personality trait deeply rooted in the nervous system (the Highly Sensitive Personality, HSP). 480 healthy Chinese college students were given the HSP scale and genotyped for 98 representative polymorphisms in all major dopamine neurotransmitter genes. In addition, two environment factors (stressful life events and parental warmth) that have been implicated for their contributions to personality development were included to investigate their relative contributions as compared to genetic factors. In Step 1, using ANOVA, we identified 10 polymorphisms that made statistically significant contributions to HSP. In Step 2, these polymorphism's main effects and interactions were assessed using multiple regression. This model accounted for 15% of the variance of HSP (p<0.001). Recent stressful life events accounted for an additional 2% of the variance. Finally, permutation analyses ascertained the probability of obtaining these findings by chance to be very low, p ranging from 0.001 to 0.006. Dividing these loci by the subsystems of dopamine synthesis, degradation/transport, receptor and modulation, we found that the modulation and receptor subsystems made the most significant contribution to HSP. The results of this study demonstrate the utility of a multi-step neuronal system-level approach in assessing genetic contributions to individual differences in human behavior. It can potentially bridge the gap between the high heritability estimates based on traditional behavioral genetics and the lack of reproducible genetic effects observed currently from molecular genetic studies.
Chen, Chunhui; Chen, Chuansheng; Moyzis, Robert; Stern, Hal; He, Qinghua; Li, He; Li, Jin; Zhu, Bi; Dong, Qi
2011-01-01
Traditional behavioral genetic studies (e.g., twin, adoption studies) have shown that human personality has moderate to high heritability, but recent molecular behavioral genetic studies have failed to identify quantitative trait loci (QTL) with consistent effects. The current study adopted a multi-step approach (ANOVA followed by multiple regression and permutation) to assess the cumulative effects of multiple QTLs. Using a system-level (dopamine system) genetic approach, we investigated a personality trait deeply rooted in the nervous system (the Highly Sensitive Personality, HSP). 480 healthy Chinese college students were given the HSP scale and genotyped for 98 representative polymorphisms in all major dopamine neurotransmitter genes. In addition, two environment factors (stressful life events and parental warmth) that have been implicated for their contributions to personality development were included to investigate their relative contributions as compared to genetic factors. In Step 1, using ANOVA, we identified 10 polymorphisms that made statistically significant contributions to HSP. In Step 2, these polymorphism's main effects and interactions were assessed using multiple regression. This model accounted for 15% of the variance of HSP (p<0.001). Recent stressful life events accounted for an additional 2% of the variance. Finally, permutation analyses ascertained the probability of obtaining these findings by chance to be very low, p ranging from 0.001 to 0.006. Dividing these loci by the subsystems of dopamine synthesis, degradation/transport, receptor and modulation, we found that the modulation and receptor subsystems made the most significant contribution to HSP. The results of this study demonstrate the utility of a multi-step neuronal system-level approach in assessing genetic contributions to individual differences in human behavior. It can potentially bridge the gap between the high heritability estimates based on traditional behavioral genetics and the lack of reproducible genetic effects observed currently from molecular genetic studies. PMID:21765900
ERIC Educational Resources Information Center
Jones, Alice P.; Frederickson, Norah
2010-01-01
This study examined differential profiles of behavioural characteristics predictive of successful inclusion in mainstream education for children with autism spectrum disorders (ASD) and comparison students. Multiple regression analyses using behavioural ratings from parents, teachers and peers found some evidence for differential profiles…
NASA Astrophysics Data System (ADS)
Eyarkai Nambi, Vijayaram; Thangavel, Kuladaisamy; Manickavasagan, Annamalai; Shahir, Sultan
2017-01-01
Prediction of ripeness level in climacteric fruits is essential for post-harvest handling. An index capable of predicting ripening level with minimum inputs would be highly beneficial to the handlers, processors and researchers in fruit industry. A study was conducted with Indian mango cultivars to develop a ripeness index and associated model. Changes in physicochemical, colour and textural properties were measured throughout the ripening period and the period was classified into five stages (unripe, early ripe, partially ripe, ripe and over ripe). Multivariate regression techniques like partial least square regression, principal component regression and multi linear regression were compared and evaluated for its prediction. Multi linear regression model with 12 parameters was found more suitable in ripening prediction. Scientific variable reduction method was adopted to simplify the developed model. Better prediction was achieved with either 2 or 3 variables (total soluble solids, colour and acidity). Cross validation was done to increase the robustness and it was found that proposed ripening index was more effective in prediction of ripening stages. Three-variable model would be suitable for commercial applications where reasonable accuracies are sufficient. However, 12-variable model can be used to obtain more precise results in research and development applications.
BERARDI, CECILIA; DECKER, PAUL A.; KIRSCH, PHILLIP S.; DE ANDRADE, MARIZA; TSAI, MICHAEL Y.; PANKOW, JAMES S.; SALE, MICHELE M.; SICOTTE, HUGUES; TANG, WEIHONG; HANSON, NAOMI; POLAK, JOSEPH F.; BIELINSKI, SUZETTE J.
2014-01-01
L-selectin has been suggested to play a role in atherosclerosis. Previous studies on cardiovascular disease (CVD) and serum or plasma L-selectin are inconsistent. The association of serum L-selectin (sL-selectin) with carotid intima-media thickness, coronary artery calcium, ankle-brachial index (subclinical CVD) and incident CVD was assessed within 2403 participants in the Multi-Ethnic Study of Atherosclerosis (MESA). Regression analysis and the Tobit model were used to study subclinical disease; Cox Proportional Hazards regression for incident CVD. Mean age was 63 ± 10, 47% were males; mean sL-selectin was significantly different across ethnicities. Within each race/ethnicity, sL-selectin was associated with age and sex; among Caucasians and African Americans, it was associated with smoking status and current alcohol use. sL-selectin levels did not predict subclinical or clinical CVD after correction for multiple comparisons. Conditional logistic regression models were used to study plasma L-selectin and CVD within 154 incident CVD cases, occurred in a median follow up of 8.5 years, and 306 age-, sex-, and ethnicity-matched controls. L-selectin levels in plasma were significantly lower than in serum and the overall concordance was low. Plasma levels were not associated with CVD. In conclusion, this large multi-ethnic population, soluble L-selectin levels did not predict clinical or subclinical CVD. PMID:24631064
Zhang, Qun; Zhang, Qunzhi; Sornette, Didier
2016-01-01
We augment the existing literature using the Log-Periodic Power Law Singular (LPPLS) structures in the log-price dynamics to diagnose financial bubbles by providing three main innovations. First, we introduce the quantile regression to the LPPLS detection problem. This allows us to disentangle (at least partially) the genuine LPPLS signal and the a priori unknown complicated residuals. Second, we propose to combine the many quantile regressions with a multi-scale analysis, which aggregates and consolidates the obtained ensembles of scenarios. Third, we define and implement the so-called DS LPPLS Confidence™ and Trust™ indicators that enrich considerably the diagnostic of bubbles. Using a detailed study of the “S&P 500 1987” bubble and presenting analyses of 16 historical bubbles, we show that the quantile regression of LPPLS signals contributes useful early warning signals. The comparison between the constructed signals and the price development in these 16 historical bubbles demonstrates their significant predictive ability around the real critical time when the burst/rally occurs. PMID:27806093
Riley, Richard D; Ensor, Joie; Jackson, Dan; Burke, Danielle L
2017-01-01
Many meta-analysis models contain multiple parameters, for example due to multiple outcomes, multiple treatments or multiple regression coefficients. In particular, meta-regression models may contain multiple study-level covariates, and one-stage individual participant data meta-analysis models may contain multiple patient-level covariates and interactions. Here, we propose how to derive percentage study weights for such situations, in order to reveal the (otherwise hidden) contribution of each study toward the parameter estimates of interest. We assume that studies are independent, and utilise a decomposition of Fisher's information matrix to decompose the total variance matrix of parameter estimates into study-specific contributions, from which percentage weights are derived. This approach generalises how percentage weights are calculated in a traditional, single parameter meta-analysis model. Application is made to one- and two-stage individual participant data meta-analyses, meta-regression and network (multivariate) meta-analysis of multiple treatments. These reveal percentage study weights toward clinically important estimates, such as summary treatment effects and treatment-covariate interactions, and are especially useful when some studies are potential outliers or at high risk of bias. We also derive percentage study weights toward methodologically interesting measures, such as the magnitude of ecological bias (difference between within-study and across-study associations) and the amount of inconsistency (difference between direct and indirect evidence in a network meta-analysis).
Nam, Woo Dong; Cho, Jae Hwan
2015-03-01
There are few studies about risk factors for poor outcomes from multi-level lumbar posterolateral fusion limited to three or four level lumbar posterolateral fusions. The purpose of this study was to analyze the outcomes of multi-level lumbar posterolateral fusion and to search for possible risk factors for poor surgical outcomes. We retrospectively analyzed 37 consecutive patients who underwent multi-level lumbar or lumbosacral posterolateral fusion with posterior instrumentation. The outcomes were deemed either 'good' or 'bad' based on clinical and radiological results. Many demographic and radiological factors were analyzed to examine potential risk factors for poor outcomes. Student t-test, Fisher exact test, and the chi-square test were used based on the nature of the variables. Multiple logistic regression analysis was used to exclude confounding factors. Twenty cases showed a good outcome (group A, 54.1%) and 17 cases showed a bad outcome (group B, 45.9%). The overall fusion rate was 70.3%. The revision procedures (group A: 1/20, 5.0%; group B: 4/17, 23.5%), proximal fusion to L2 (group A: 5/20, 25.0%; group B: 10/17, 58.8%), and severity of stenosis (group A: 12/19, 63.3%; group B: 3/11, 27.3%) were adopted as possible related factors to the outcome in univariate analysis. Multiple logistic regression analysis revealed that only the proximal fusion level (superior instrumented vertebra, SIV) was a significant risk factor. The cases in which SIV was L2 showed inferior outcomes than those in which SIV was L3. The odds ratio was 6.562 (95% confidence interval, 1.259 to 34.203). The overall outcome of multi-level lumbar or lumbosacral posterolateral fusion was not as high as we had hoped it would be. Whether the SIV was L2 or L3 was the only significant risk factor identified for poor outcomes in multi-level lumbar or lumbosacral posterolateral fusion in the current study. Thus, the authors recommend that proximal fusion levels be carefully determined when multi-level lumbar fusions are considered.
Nam, Woo Dong
2015-01-01
Background There are few studies about risk factors for poor outcomes from multi-level lumbar posterolateral fusion limited to three or four level lumbar posterolateral fusions. The purpose of this study was to analyze the outcomes of multi-level lumbar posterolateral fusion and to search for possible risk factors for poor surgical outcomes. Methods We retrospectively analyzed 37 consecutive patients who underwent multi-level lumbar or lumbosacral posterolateral fusion with posterior instrumentation. The outcomes were deemed either 'good' or 'bad' based on clinical and radiological results. Many demographic and radiological factors were analyzed to examine potential risk factors for poor outcomes. Student t-test, Fisher exact test, and the chi-square test were used based on the nature of the variables. Multiple logistic regression analysis was used to exclude confounding factors. Results Twenty cases showed a good outcome (group A, 54.1%) and 17 cases showed a bad outcome (group B, 45.9%). The overall fusion rate was 70.3%. The revision procedures (group A: 1/20, 5.0%; group B: 4/17, 23.5%), proximal fusion to L2 (group A: 5/20, 25.0%; group B: 10/17, 58.8%), and severity of stenosis (group A: 12/19, 63.3%; group B: 3/11, 27.3%) were adopted as possible related factors to the outcome in univariate analysis. Multiple logistic regression analysis revealed that only the proximal fusion level (superior instrumented vertebra, SIV) was a significant risk factor. The cases in which SIV was L2 showed inferior outcomes than those in which SIV was L3. The odds ratio was 6.562 (95% confidence interval, 1.259 to 34.203). Conclusions The overall outcome of multi-level lumbar or lumbosacral posterolateral fusion was not as high as we had hoped it would be. Whether the SIV was L2 or L3 was the only significant risk factor identified for poor outcomes in multi-level lumbar or lumbosacral posterolateral fusion in the current study. Thus, the authors recommend that proximal fusion levels be carefully determined when multi-level lumbar fusions are considered. PMID:25729522
Acculturative stress and depression in an elderly Arabic sample.
Wrobel, Nancy Howells; Farrag, Mohamed F; Hymes, Robert W
2009-09-01
Acculturative stress and relevant demographic variables, including immigration status, English skills, level of education, age, gender, country of origin, and years since immigration to the U. S. are examined along with their relationship to depressive symptoms. The 200 Arab-American and recent Arab immigrant participants ranged from age 60-92 and represented eight countries of origin. Most had limited fluency in English. Arabic versions of the Multi-dimensional Acculturative Stress Inventory (MASI) and Geriatric Depression Scale were administered. MASI and GDS results indicated greater degrees of acculturative stress and depression for those with a refugee or temporary resident status. More recent entry into the U.S. also predicted greater stress, while greater levels of education and English skills predicted lower levels of stress and depression. Composite stress levels and the nature of stress varied by country of origin. Although demographic variables were predictive of depression when examined separately, multiple regression analyses revealed that perceived acculturative stress, particularly pressure to learn English, provided a notable increment in prediction of depression over the demographic variables.
Vu, Mary; Leatherdale, Scott T; Ahmed, Rashid
2011-12-01
Understanding factors associated with youth cigarette access behaviours can provide insight into the development of more effective means of preventing youth from accessing cigarettes. This cross-sectional study used self-reported data collected from 41,886 students in grades 9 to 12 who participated in the 2006-07 Youth Smoking Survey to examine the student- and school-level characteristics that differentiate youth smokers who usually access cigarettes from a social source versus buying their own from retailers. Multi-level regression analyses revealed significant between-school variability in the odds of a smoking student reporting that they usually buy their own cigarettes. Important student-level characteristics associated with how youth usually access their cigarettes included binge drinking and being asked for age or photo identification when purchasing cigarettes from a retailer. Future studies should further explore the school- and student-level characteristics associated with youth cigarette access behaviour. Copyright © 2011 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Sun, Yuan; Bhattacherjee, Anol
2011-11-01
Information technology (IT) usage within organisations is a multi-level phenomenon that is influenced by individual-level and organisational-level variables. Yet, current theories, such as the unified theory of acceptance and use of technology, describe IT usage as solely an individual-level phenomenon. This article postulates a model of organisational IT usage that integrates salient organisational-level variables such as user training, top management support and technical support within an individual-level model to postulate a multi-level model of IT usage. The multi-level model was then empirically validated using multi-level data collected from 128 end users and 26 managers in 26 firms in China regarding their use of enterprise resource planning systems and analysed using the multi-level structural equation modelling (MSEM) technique. We demonstrate the utility of MSEM analysis of multi-level data relative to the more common structural equation modelling analysis of single-level data and show how single-level data can be aggregated to approximate multi-level analysis when multi-level data collection is not possible. We hope that this article will motivate future scholars to employ multi-level data and multi-level analysis for understanding organisational phenomena that are truly multi-level in nature.
A conceptual disease model for adult Pompe disease.
Kanters, Tim A; Redekop, W Ken; Rutten-Van Mölken, Maureen P M H; Kruijshaar, Michelle E; Güngör, Deniz; van der Ploeg, Ans T; Hakkaart, Leona
2015-09-15
Studies in orphan diseases are, by nature, confronted with small patient populations, meaning that randomized controlled trials will have limited statistical power. In order to estimate the effectiveness of treatments in orphan diseases and extrapolate effects into the future, alternative models might be needed. The purpose of this study is to develop a conceptual disease model for Pompe disease in adults (an orphan disease). This conceptual model describes the associations between the most important levels of health concepts for Pompe disease in adults, from biological parameters via physiological parameters, symptoms and functional indicators to health perceptions and final health outcomes as measured in terms of health-related quality of life. The structure of the Wilson-Cleary health outcomes model was used as a blueprint, and filled with clinically relevant aspects for Pompe disease based on literature and expert opinion. Multiple observations per patient from a Dutch cohort study in untreated patients were used to quantify the relationships between the different levels of health concepts in the model by means of regression analyses. Enzyme activity, muscle strength, respiratory function, fatigue, level of handicap, general health perceptions, mental and physical component scales and utility described the different levels of health concepts in the Wilson-Cleary model for Pompe disease. Regression analyses showed that functional status was affected by fatigue, muscle strength and respiratory function. Health perceptions were affected by handicap. In turn, self-reported quality of life was affected by health perceptions. We conceptualized a disease model that incorporated the mechanisms believed to be responsible for impaired quality of life in Pompe disease. The model provides a comprehensive overview of various aspects of Pompe disease in adults, which can be useful for both clinicians and policymakers to support their multi-faceted decision making.
Dembo, Richard; Childs, Kristina; Belenko, Steven; Schmeidler, James; Wareham, Jennifer
2010-01-01
Gender and racial differences in infection rates for chlamydia and gonorrhea have been reported within community-based populations, but little is known of such differences within juvenile offending populations. Moreover, while research has demonstrated that certain individual-level and community-level factors affect risky behaviors associated with sexually transmitted disease (STD), less is known about how multi-level factors affect STD infection, particularly among delinquent populations. The present study investigated gender and racial differences in STD infection among a sample of 924 juvenile offenders. Generalized linear model regression analyses were conducted to examine the influence of individual-level factors such as age, offense history, and substance use and community-level factors such as concentrated disadvantage, ethnic heterogeneity, and family disruption on STD status. Results revealed significant racial and STD status differences across gender, as well as interaction effects for race and STD status for males only. Gender differences in individual-level and community-level predictors were also found. Implications of these findings for future research and public health policy are discussed. PMID:20700475
Influence of health providers on pediatrics' immunization rate.
Al-lela, Omer Q B; Baidi Bahari, Mohd; Al-abbassi, Mustafa G; Salih, Muhannad R M; Basher, Amena Y
2012-12-01
To identify the immunization providers' characteristics associated with immunization rate in children younger than 2 years. A cohort and a cluster sampling design were implemented; 528 children between 18 and 70 months of age were sampled in five public health clinics in Mosul-Iraq. Providers' characterizations were obtained. Immunization rate for the children was assessed. Risk factors for partial immunization were explored using both bivariate analyses and multi-level logistic regression models. Less than half of the children had one or more than one missed dose, considered as partial immunization cases. The study found significant association of immunization rate with provider's type. Two factors were found that strongly impacted on immunization rate in the presence of other factors: birthplace and immunization providers' type.
Regression and multivariate models for predicting particulate matter concentration level.
Nazif, Amina; Mohammed, Nurul Izma; Malakahmad, Amirhossein; Abualqumboz, Motasem S
2018-01-01
The devastating health effects of particulate matter (PM 10 ) exposure by susceptible populace has made it necessary to evaluate PM 10 pollution. Meteorological parameters and seasonal variation increases PM 10 concentration levels, especially in areas that have multiple anthropogenic activities. Hence, stepwise regression (SR), multiple linear regression (MLR) and principal component regression (PCR) analyses were used to analyse daily average PM 10 concentration levels. The analyses were carried out using daily average PM 10 concentration, temperature, humidity, wind speed and wind direction data from 2006 to 2010. The data was from an industrial air quality monitoring station in Malaysia. The SR analysis established that meteorological parameters had less influence on PM 10 concentration levels having coefficient of determination (R 2 ) result from 23 to 29% based on seasoned and unseasoned analysis. While, the result of the prediction analysis showed that PCR models had a better R 2 result than MLR methods. The results for the analyses based on both seasoned and unseasoned data established that MLR models had R 2 result from 0.50 to 0.60. While, PCR models had R 2 result from 0.66 to 0.89. In addition, the validation analysis using 2016 data also recognised that the PCR model outperformed the MLR model, with the PCR model for the seasoned analysis having the best result. These analyses will aid in achieving sustainable air quality management strategies.
Addressing data privacy in matched studies via virtual pooling.
Saha-Chaudhuri, P; Weinberg, C R
2017-09-07
Data confidentiality and shared use of research data are two desirable but sometimes conflicting goals in research with multi-center studies and distributed data. While ideal for straightforward analysis, confidentiality restrictions forbid creation of a single dataset that includes covariate information of all participants. Current approaches such as aggregate data sharing, distributed regression, meta-analysis and score-based methods can have important limitations. We propose a novel application of an existing epidemiologic tool, specimen pooling, to enable confidentiality-preserving analysis of data arising from a matched case-control, multi-center design. Instead of pooling specimens prior to assay, we apply the methodology to virtually pool (aggregate) covariates within nodes. Such virtual pooling retains most of the information used in an analysis with individual data and since individual participant data is not shared externally, within-node virtual pooling preserves data confidentiality. We show that aggregated covariate levels can be used in a conditional logistic regression model to estimate individual-level odds ratios of interest. The parameter estimates from the standard conditional logistic regression are compared to the estimates based on a conditional logistic regression model with aggregated data. The parameter estimates are shown to be similar to those without pooling and to have comparable standard errors and confidence interval coverage. Virtual data pooling can be used to maintain confidentiality of data from multi-center study and can be particularly useful in research with large-scale distributed data.
Predicting Negative Discipline in Traditional Families: A Multi-Dimensional Stress Model.
ERIC Educational Resources Information Center
Fisher, Philip A.
An attempt is made to integrate existing theories of family violence by introducing the concept of family role stress. Role stressors may be defined as factors inhibiting the enactment of family roles. Multiple regression analyses were performed on data from 190 families to test a hypothesis involving the prediction of negative discipline at…
A parameter estimation subroutine package
NASA Technical Reports Server (NTRS)
Bierman, G. J.; Nead, M. W.
1978-01-01
Linear least squares estimation and regression analyses continue to play a major role in orbit determination and related areas. A library of FORTRAN subroutines were developed to facilitate analyses of a variety of estimation problems. An easy to use, multi-purpose set of algorithms that are reasonably efficient and which use a minimal amount of computer storage are presented. Subroutine inputs, outputs, usage and listings are given, along with examples of how these routines can be used. The routines are compact and efficient and are far superior to the normal equation and Kalman filter data processing algorithms that are often used for least squares analyses.
Impact of Contextual Factors on Prostate Cancer Risk and Outcomes
2013-07-01
framework with random effects (“frailty models”) while the case-control analyses (Aim 4) will use multilevel unconditional logistic regression models...contextual-level SES on prostate cancer risk within racial/ethnic groups. The survival analyses (Aims 1-3) will utilize a proportional hazards regression
Thompson-Brenner, Heather; Franko, Debra L.; Thompson, Douglas R.; Grilo, Carlos M.; Boisseau, Christina L.; Roehrig, James P.; Richards, Lauren K.; Bryson, Susan W.; Bulik, Cynthia M.; Crow, Scott J.; Devlin, Michael J.; Gorin, Amy A.; Kristeller, Jean L.; Masheb, Robin; Mitchell, James E.; Peterson, Carol B.; Safer, Debra L.; Striegel, Ruth H.; Wilfley, Denise E.; Wilson, G. Terence
2014-01-01
Objective Binge eating disorder (BED) is prevalent among individuals from minority racial/ethnic groups and among individuals with lower levels of education, yet the efficacy of psychosocial treatments for these groups has not been examined in adequately powered analyses. This study investigated the relative variance in treatment retention and post-treatment symptom levels accounted for by demographic, clinical, and treatment variables as moderators and predictors of outcome. Method Data were aggregated from eleven randomized, controlled trials of psychosocial treatments for BED conducted at treatment sites across the United States. Participants were N = 1,073 individuals meeting criteria for BED including n = 946 Caucasian, n = 79 African American, and n = 48 Hispanic/Latino participants. Approximately 86% had some higher education; 85% were female. Multi-level regression analyses examined moderators and predictors of treatment retention, Eating Disorder Examination (EDE) global score, frequency of objective bulimic episodes (OBEs), and OBE remission. Results Moderator analyses of race/ethnicity and education were non-significant. Predictor analyses revealed African Americans were more likely to drop out of treatment than Caucasians, and lower level of education predicted greater post-treatment OBEs. African Americans showed a small but significantly greater reduction in EDE global score relative to Caucasians. Self-help treatment administered in a group showed negative outcomes relative to other treatment types, and longer treatment was associated with better outcome. Conclusions Observed lower treatment retention among African Americans and lesser treatment effects for individuals with lower levels of educational attainment are serious issues requiring attention. Reduced benefit was observed for shorter treatment length and self-help administered in groups. PMID:23647283
ERIC Educational Resources Information Center
Cohen, Ira L.; Liu, Xudong; Hudson, Melissa; Gillis, Jennifer; Cavalari, Rachel N. S.; Romanczyk, Raymond G.; Karmel, Bernard Z.; Gardner, Judith M.
2016-01-01
In order to improve discrimination accuracy between Autism Spectrum Disorder (ASD) and similar neurodevelopmental disorders, a data mining procedure, Classification and Regression Trees (CART), was used on a large multi-site sample of PDD Behavior Inventory (PDDBI) forms on children with and without ASD. Discrimination accuracy exceeded 80%,…
NASA Astrophysics Data System (ADS)
Masselot, Pierre; Chebana, Fateh; Bélanger, Diane; St-Hilaire, André; Abdous, Belkacem; Gosselin, Pierre; Ouarda, Taha B. M. J.
2018-01-01
In a number of environmental studies, relationships between natural processes are often assessed through regression analyses, using time series data. Such data are often multi-scale and non-stationary, leading to a poor accuracy of the resulting regression models and therefore to results with moderate reliability. To deal with this issue, the present paper introduces the EMD-regression methodology consisting in applying the empirical mode decomposition (EMD) algorithm on data series and then using the resulting components in regression models. The proposed methodology presents a number of advantages. First, it accounts of the issues of non-stationarity associated to the data series. Second, this approach acts as a scan for the relationship between a response variable and the predictors at different time scales, providing new insights about this relationship. To illustrate the proposed methodology it is applied to study the relationship between weather and cardiovascular mortality in Montreal, Canada. The results shed new knowledge concerning the studied relationship. For instance, they show that the humidity can cause excess mortality at the monthly time scale, which is a scale not visible in classical models. A comparison is also conducted with state of the art methods which are the generalized additive models and distributed lag models, both widely used in weather-related health studies. The comparison shows that EMD-regression achieves better prediction performances and provides more details than classical models concerning the relationship.
Individual relocation decisions after tornadoes: a multi-level analysis.
Cong, Zhen; Nejat, Ali; Liang, Daan; Pei, Yaolin; Javid, Roxana J
2018-04-01
This study examines how multi-level factors affected individuals' relocation decisions after EF4 and EF5 (Enhanced Fujita Tornado Intensity Scale) tornadoes struck the United States in 2013. A telephone survey was conducted with 536 respondents, including oversampled older adults, one year after these two disaster events. Respondents' addresses were used to associate individual information with block group-level variables recorded by the American Community Survey. Logistic regression revealed that residential damage and homeownership are important predictors of relocation. There was also significant interaction between these two variables, indicating less difference between homeowners and renters at higher damage levels. Homeownership diminished the likelihood of relocation among younger respondents. Random effects logistic regression found that the percentage of homeownership and of higher income households in the community buffered the effect of damage on relocation; the percentage of older adults reduced the likelihood of this group relocating. The findings are assessed from the standpoint of age difference, policy implications, and social capital and vulnerability. © 2018 The Author(s). Disasters © Overseas Development Institute, 2018.
NASA Astrophysics Data System (ADS)
Zhang, Yunpeng; Ho, Siu-lau; Fu, Weinong
2018-05-01
This paper proposes a dynamic multi-level optimal design method for power transformer design optimization (TDO) problems. A response surface generated by second-order polynomial regression analysis is updated dynamically by adding more design points, which are selected by Shifted Hammersley Method (SHM) and calculated by finite-element method (FEM). The updating stops when the accuracy requirement is satisfied, and optimized solutions of the preliminary design are derived simultaneously. The optimal design level is modulated through changing the level of error tolerance. Based on the response surface of the preliminary design, a refined optimal design is added using multi-objective genetic algorithm (MOGA). The effectiveness of the proposed optimal design method is validated through a classic three-phase power TDO problem.
Urpi-Sarda, M; Almanza-Aguilera, E; Llorach, R; Vázquez-Fresno, R; Estruch, R; Corella, D; Sorli, J V; Carmona, F; Sanchez-Pla, A; Salas-Salvadó, J; Andres-Lacueva, C
2018-02-20
To characterize the urinary metabolomic fingerprint and multi-metabolite signature associated with type 2 diabetes (T2D), and to classify the population into metabotypes related to T2D. A metabolomics analysis using the 1 H-NMR-based, non-targeted metabolomic approach was conducted to determine the urinary metabolomic fingerprint of T2D compared with non-T2D participants in the PREDIMED trial. The discriminant metabolite fingerprint was subjected to logistic regression analysis and ROC analyses to establish and to assess the multi-metabolite signature of T2D prevalence, respectively. Metabotypes associated with T2D were identified using the k-means algorithm. A total of 33 metabolites were significantly different (P<0.05) between T2D and non-T2D participants. The multi-metabolite signature of T2D comprised high levels of methylsuccinate, alanine, dimethylglycine and guanidoacetate, and reduced levels of glutamine, methylguanidine, 3-hydroxymandelate and hippurate, and had a 96.4% AUC, which was higher than the metabolites on their own and glucose. Amino-acid and carbohydrate metabolism were the main metabolic alterations in T2D, and various metabotypes were identified in the studied population. Among T2D participants, those with a metabotype of higher levels of phenylalanine, phenylacetylglutamine, p-cresol and acetoacetate had significantly higher levels of plasma glucose. The multi-metabolite signature of T2D highlights the altered metabolic fingerprint associated mainly with amino-acid, carbohydrate and microbiota metabolism. Metabotypes identified in this patient population could be related to higher risk of long-term cardiovascular events and therefore require further studies. Metabolomics is a useful tool for elucidating the metabolic complexity and interindividual variation in T2D towards the development of stratified precision nutrition and medicine. Trial registration at www.controlled-trials.com: ISRCTN35739639. Copyright © 2018 Elsevier Masson SAS. All rights reserved.
Hamer, Maria Andrada; Källén, Karin; Lidfeldt, Jonas; Samsioe, Göran; Teleman, Pia
2011-11-01
To outline serum estradiol levels in perimenopausal women with stress, mixed or urge incontinence. We believe the majority of urgency symptoms in perimenopausal women to be caused by a pelvic floor dysfunction and a hypermobility of the bladder neck. If this is the case, there would be no difference in estradiol levels between the groups. University hospital. In the observational Women's Health in the Lund Area study, a subset of 400/2221 women reporting urinary incontinence completed a detailed questionnaire regarding lower urinary tract symptoms and had their serum steroid hormone levels measured. Statistical analyses were made by Chi-square test, nonparametrical tests, ANOVA, multi- and univariate logistic regression analysis. Stress incontinence was reported by 196, mixed incontinence by 153 and urge incontinence by 43 women; in 369, serumestradiol values were available. Serum estradiol did not differ significantly between stress incontinent (median 49.5 pmo/l, range 2.63-875.4), urge incontinent (median 31.6 pmol/l, range 2.63-460.7) or mixed incontinent women (median 35.5 pmol/l, range 2.63-787.9, p=0.62). Logistic regression analysis correcting for age, parity, hormonal status, smoking, hysterectomy and BMI also failed to show any difference in estradiol levels between the groups (p=0.41-0.58). No significant differences in serum estradiol levels between stress, mixed or urge incontinent perimenopausal women could be demonstrated. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.
Roberts, Michelle R.; Sucheston-Campbell, Lara E.; Zirpoli, Gary R.; Higgins, Michael; Freudenheim, Jo L.; Bandera, Elisa V.; Ambrosone, Christine B.; Yao, Song
2017-01-01
Background Single nucleotide polymorphisms (SNPs) in pathways influencing lymph node (LN) metastasis and estrogen receptor (ER) status in breast cancer may partially explain inter-patient variability in prognosis. We examined 154 SNPs in 12 metastasis-related genes for associations with breast cancer risk, stratified by LN and ER status, in European-American (EA) and African-American (AA) women. Methods 2,671 women enrolled in the Women’s Circle of Health Study were genotyped. Pathway analyses were conducted using the adaptive rank truncated product (ARTP) method, with pARTP≤0.10 as significant. Multi-allelic risk scores were created for the ARTP-significant gene(s). Single-SNP and risk score associations were modeled using logistic regression, with false discovery rate (FDR) p-value adjustment. Results Although single-SNP associations were not significant at pFDR<0.05, several genes were significant in the ARTP analyses. In AA women, significant ARTP gene-level associations included CDH1 with LN+ (pARTP=0.10; multi-allelic OR=1.13, 95% CI 1.07–1.19, pFDR=0.0003) and SIPA1 with ER− breast cancer (pARTP=0.10; multi-allelic OR=1.16, 95% CI 1.02–1.31, pFDR=0.03). In EA women, MTA2 was associated with overall breast cancer risk (pARTP=0.004), regardless of ER status, and with LN− disease (pARTP=0.01). Also significant were SATB1 in ER− (pARTP=0.03; multi-allelic OR=1.12, 95% CI 1.05–1.20, pFDR=0.003) and KISS1 in LN− (pARTP=0.10; multi-allelic OR=1.18, 95% CI 1.08–1.29, pFDR=0.002) analyses. Among LN+ cases, significant ARTP associations were observed for SNAI1, CD82, NME1, and CTNNB1 (multi-allelic OR=1.09, 95% CI 1.04–1.14, pFDR=0.001). Conclusion Our findings suggest that variants in several metastasis genes may affect breast cancer risk by LN or ER status, although verification in larger studies is required. PMID:27597141
Hydrology and trout populations of cold-water rivers of Michigan and Wisconsin
Hendrickson, G.E.; Knutilla, R.L.
1974-01-01
Statistical multiple-regression analyses showed significant relationships between trout populations and hydrologic parameters. Parameters showing the higher levels of significance were temperature, hardness of water, percentage of gravel bottom, percentage of bottom vegetation, variability of streamflow, and discharge per unit drainage area. Trout populations increase with lower levels of annual maximum water temperatures, with increase in water hardness, and with increase in percentage of gravel and bottom vegetation. Trout populations also increase with decrease in variability of streamflow, and with increase in discharge per unit drainage area. Most hydrologic parameters were significant when evaluated collectively, but no parameter, by itself, showed a high degree of correlation with trout populations in regression analyses that included all the streams sampled. Regression analyses of stream segments that were restricted to certain limits of hardness, temperature, or percentage of gravel bottom showed improvements in correlation. Analyses of trout populations, in pounds per acre and pounds per mile and hydrologic parameters resulted in regression equations from which trout populations could be estimated with standard errors of 89 and 84 per cent, respectively.
2010-01-01
Background Given the decline in physical activity (PA) levels among youth populations it is vital to understand the factors that are associated with PA in order to inform the development of new prevention programs. Many studies have examined individual characteristics associated with PA among youth yet few have studied the relationship between the school environment and PA despite knowing that there is variability in student PA levels across schools. Methods Using multi-level logistic regression analyses we explored the school- and student-level characteristics associated with PA using data from 2,379 grade 5 to 8 students attending 30 elementary schools in Ontario, Canada as part of the PLAY-Ontario study. Results Findings indicate that there was significant between-school random variation for being moderately and highly active; school-level differences accounted for 4.8% of the variability in the odds of being moderately active and 7.3% of the variability in the odds of being highly active. Students were more likely to be moderately active if they attended a school that used PA as a reward and not as discipline, and students were more likely to be highly active if they attended a school with established community partnerships. Important student characteristics included screen time sedentary behaviour, participating in team sports, and having active friends. Conclusion Future research should evaluate if the optimal population level impact for school-based PA promotion programming might be achieved most economically if intervention selectively targeted the schools that are putting students at the greatest risk for inactivity. PMID:20181010
NASA Astrophysics Data System (ADS)
Chen, X.; Vierling, L. A.; Deering, D. W.
2004-12-01
Satellite data offer unique perspectives for monitoring and quantifying land cover change, however, the radiometric consistency among co-located multi-temporal images is difficult to maintain due to variations in sensors and atmosphere. To detect accurate landscape change using multi-temporal images, we developed a new relative radiometric normalization scheme: the temporally invariant cluster (TIC) method. Image data were acquired on 9 June 1990 (Landsat 4), 20 June 2000, and 26 August 2001 (Landsat 7) for analyses over boreal forests near the Siberian city of Krasnoyarsk. Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), and Reduced Simple Ratio (RSR) were investigated in the normalization study. The temporally invariant cluster (TIC) centers were identified through a point density map of the base image and the target image and a normalization regression line was created through all TIC centers. The target image digital data were then converted using the regression function so that the two images could be compared using the resulting common radiometric scale. We found that EVI was very sensitive to vegetation structure and could thus be used to separate conifer forests from deciduous forests and grass/crop lands. NDVI was a very effective vegetation index to reduce the influence of shadow, while EVI was very sensitive to shadowing. After normalization, correlations of NDVI and EVI with field collected total Leaf Area Index (LAI) data in 2000 and 2001 were significantly improved; the r-square values in these regressions increased from 0.49 to 0.69 and from 0.46 to 0.61, respectively. An EVI ¡°cancellation effect¡± where EVI was positively related to understory greenness but negatively related to forest canopy coverage was evident across a post fire chronosequence. These findings indicate that the TIC method provides a simple, effective and repeatable method to create radiometrically comparable data sets for remote detection of landscape change. Compared with some previous relative normalization methods, this new method can avoid subjective selection of a normalization regression line. It does not require high level programming and statistical analyses, yet remains sensitive to landscape changes occurring over seasonal and inter-annual time scales. In addition, the TIC method maintains sensitivity to subtle changes in vegetation phenology and enables normalization even when invariant features are rare.
Multiple linear regression models are often used to predict levels of fecal indicator bacteria (FIB) in recreational swimming waters based on independent variables (IVs) such as meteorologic, hydrodynamic, and water-quality measures. The IVs used for these analyses are traditiona...
Development and initial validation of a caffeine craving questionnaire.
West, Oliver; Roderique-Davies, Gareth
2008-01-01
Craving for caffeine has received little empirical attention, despite considerable research into the potential for caffeine dependence. The main aim of this study was to develop, and initially validate, a multi-item, multidimensional instrument to measure cravings for caffeine. Participants were 189 caffeine consumers who completed the Questionnaire of Caffeine Cravings, which was based on the Questionnaire of Smoking Urges (QSU), in one of five naturally occurring periods of abstinence; 1-15 min; 16-120 mins; 3-7 h; 12-48 h and +48 h. Exploratory factor analysis suggested a three-factor solution best described the data; Factor 1 reflected strong desires, intentions and positive reinforcement; Factor 2 reflected mild/general positive and negative reinforcement and Factor 3 reflected functional/mood-based negative reinforcement. Significantly higher Factor 1 and Factor 2 scores were recorded for high frequency users; significantly higher Factor 1 and Factor 3 scores were recorded as a function of increased levels of dependence. Duration of abstinence did not significantly effect cravings across all three factors. Regression analyses suggested level of dependence best predicted both current cravings and frequency of daily use. These findings suggest caffeine cravings may be conceptualized multidimensionally and further validates the use of multidimensional, multi-item instruments. Cravings for caffeine may manifest and be detected across varying levels of dependence and, frequency of use and independently of duration of abstinence.
Abimbola, Seye; Negin, Joel; Jan, Stephen; Martiniuk, Alexandra
2014-09-01
Although there is evidence that non-government health system actors can individually or collectively develop practical strategies to address primary health care (PHC) challenges in the community, existing frameworks for analysing health system governance largely focus on the role of governments, and do not sufficiently account for the broad range of contribution to PHC governance. This is important because of the tendency for weak governments in low- and middle-income countries (LMICs). We present a multi-level governance framework for use as a thinking guide in analysing PHC governance in LMICs. This framework has previously been used to analyse the governance of common-pool resources such as community fisheries and irrigation systems. We apply the framework to PHC because, like common-pool resources, PHC facilities in LMICs tend to be commonly owned by the community such that individual and collective action is often required to avoid the 'tragedy of the commons'-destruction and degradation of the resource resulting from lack of concern for its continuous supply. In the multi-level framework, PHC governance is conceptualized at three levels, depending on who influences the supply and demand of PHC services in a community and how: operational governance (individuals and providers within the local health market), collective governance (community coalitions) and constitutional governance (governments at different levels and other distant but influential actors). Using the example of PHC governance in Nigeria, we illustrate how the multi-level governance framework offers a people-centred lens on the governance of PHC in LMICs, with a focus on relations among health system actors within and between levels of governance. We demonstrate the potential impact of health system actors functioning at different levels of governance on PHC delivery, and how governance failure at one level can be assuaged by governance at another level. Published by Oxford University Press in association with The London School of Hygiene and Tropical Medicine © The Author 2014; all rights reserved.
Abimbola, Seye; Negin, Joel; Jan, Stephen; Martiniuk, Alexandra
2014-01-01
Although there is evidence that non-government health system actors can individually or collectively develop practical strategies to address primary health care (PHC) challenges in the community, existing frameworks for analysing health system governance largely focus on the role of governments, and do not sufficiently account for the broad range of contribution to PHC governance. This is important because of the tendency for weak governments in low- and middle-income countries (LMICs). We present a multi-level governance framework for use as a thinking guide in analysing PHC governance in LMICs. This framework has previously been used to analyse the governance of common-pool resources such as community fisheries and irrigation systems. We apply the framework to PHC because, like common-pool resources, PHC facilities in LMICs tend to be commonly owned by the community such that individual and collective action is often required to avoid the ‘tragedy of the commons’—destruction and degradation of the resource resulting from lack of concern for its continuous supply. In the multi-level framework, PHC governance is conceptualized at three levels, depending on who influences the supply and demand of PHC services in a community and how: operational governance (individuals and providers within the local health market), collective governance (community coalitions) and constitutional governance (governments at different levels and other distant but influential actors). Using the example of PHC governance in Nigeria, we illustrate how the multi-level governance framework offers a people-centred lens on the governance of PHC in LMICs, with a focus on relations among health system actors within and between levels of governance. We demonstrate the potential impact of health system actors functioning at different levels of governance on PHC delivery, and how governance failure at one level can be assuaged by governance at another level. PMID:25274638
NASA Astrophysics Data System (ADS)
Kumar, Vandhna; Meyssignac, Benoit; Melet, Angélique; Ganachaud, Alexandre
2017-04-01
Rising sea levels are a critical concern in small island nations. The problem is especially serious in the western south Pacific, where the total sea level rise over the last 60 years is up to 3 times the global average. In this study, we attempt to reconstruct sea levels at selected sites in the region (Suva, Lautoka, Noumea - Fiji and New Caledonia) as a mutiple-linear regression of atmospheric and oceanic variables. We focus on interannual-to-decadal scale variability, and lower (including the global mean sea level rise) over the 1979-2014 period. Sea levels are taken from tide gauge records and the ORAS4 reanalysis dataset, and are expressed as a sum of steric and mass changes as a preliminary step. The key development in our methodology is using leading wind stress curl as a proxy for the thermosteric component. This is based on the knowledge that wind stress curl anomalies can modulate the thermocline depth and resultant sea levels via Rossby wave propagation. The analysis is primarily based on correlation between local sea level and selected predictors, the dominant one being wind stress curl. In the first step, proxy boxes for wind stress curl are determined via regions of highest correlation. The proportion of sea level explained via linear regression is then removed, leaving a residual. This residual is then correlated with other locally acting potential predictors: halosteric sea level, the zonal and meridional wind stress components, and sea surface temperature. The statistically significant predictors are used in a multi-linear regression function to simulate the observed sea level. The method is able to reproduce between 40 to 80% of the variance in observed sea level. Based on the skill of the model, it has high potential in sea level projection and downscaling studies.
Adjei, David N; Stronks, Karien; Adu, Dwomoa; Snijder, Marieke B; Modesti, Pietro A; Peters, Ron J G; Vogt, Liffert; Agyemang, Charles
2017-01-01
Ethnic minority groups in high-income countries are disproportionately affected by Chronic Kidney Disease (CKD) for reasons that are unclear. We assessed the association of educational and occupational levels with CKD in a multi-ethnic population. Furthermore, we assessed to what extent ethnic inequalities in the prevalence of CKD were accounted for by educational and occupational levels. Cross-sectional analysis of baseline data from the Healthy Life in an Urban Setting (HELIUS) study of 21,433 adults (4,525 Dutch, 3,027 South-Asian Surinamese, 4,105 African Surinamese, 2,314 Ghanaians, 3,579 Turks, and 3,883 Moroccans) aged 18 to 70 years living in Amsterdam, the Netherlands. Three CKD outcomes were considered using the 2012 KDIGO (Kidney Disease: Improving Global Outcomes) severity of CKD classification. Comparisons between educational and occupational levels were made using logistic regression analyses. After adjustment for sex and age, low-level and middle-level education were significantly associated with higher odds of high to very high-risk of CKD in Dutch (Odds Ratio (OR) 2.10, 95% C.I., 1.37-2.95; OR 1.55, 95% C.I., 1.03-2.34). Among ethnic minority groups, low-level education was significantly associated with higher odds of high to very-high-risk CKD but only in South-Asian Surinamese (OR 1.58, 95% C.I., 1.06-2.34). Similar results were found for the occupational level in relation to CKD risk. The lower educational and occupational levels of ethnic minority groups partly accounted for the observed ethnic inequalities in CKD. Reducing CKD risk in ethnic minority populations with low educational and occupational levels may help to reduce ethnic inequalities in CKD and its related complications.
The Multitheoretical List of Therapeutic Interventions - 30 items (MULTI-30).
Solomonov, Nili; McCarthy, Kevin S; Gorman, Bernard S; Barber, Jacques P
2018-01-16
To develop a brief version of the Multitheoretical List of Therapeutic Interventions (MULTI-60) in order to decrease completion time burden by approximately half, while maintaining content coverage. Study 1 aimed to select 30 items. Study 2 aimed to examine the reliability and internal consistency of the MULTI-30. Study 3 aimed to validate the MULTI-30 and ensure content coverage. In Study 1, the sample included 186 therapist and 255 patient MULTI ratings, and 164 ratings of sessions coded by trained observers. Internal consistency (Chronbach's alpha and McDonald's omega) was calculated and confirmatory factor analysis was conducted. Psychotherapy experts rated content relevance. Study 2 included a sample of 644 patient and 522 therapist ratings, and 793 codings of psychotherapy sessions. In Study 3, the sample included 33 codings of sessions. A series of regression analyses was conducted to examine replication of previously published findings using the MULTI-30. The MULTI-30 was found valid, reliable, and internally consistent across 2564 ratings examined across the three studies presented. The MULTI-30 a brief and reliable process measure. Future studies are required for further validation.
Can Emotional and Behavioral Dysregulation in Youth Be Decoded from Functional Neuroimaging?
Portugal, Liana C L; Rosa, Maria João; Rao, Anil; Bebko, Genna; Bertocci, Michele A; Hinze, Amanda K; Bonar, Lisa; Almeida, Jorge R C; Perlman, Susan B; Versace, Amelia; Schirda, Claudiu; Travis, Michael; Gill, Mary Kay; Demeter, Christine; Diwadkar, Vaibhav A; Ciuffetelli, Gary; Rodriguez, Eric; Forbes, Erika E; Sunshine, Jeffrey L; Holland, Scott K; Kowatch, Robert A; Birmaher, Boris; Axelson, David; Horwitz, Sarah M; Arnold, Eugene L; Fristad, Mary A; Youngstrom, Eric A; Findling, Robert L; Pereira, Mirtes; Oliveira, Leticia; Phillips, Mary L; Mourao-Miranda, Janaina
2016-01-01
High comorbidity among pediatric disorders characterized by behavioral and emotional dysregulation poses problems for diagnosis and treatment, and suggests that these disorders may be better conceptualized as dimensions of abnormal behaviors. Furthermore, identifying neuroimaging biomarkers related to dimensional measures of behavior may provide targets to guide individualized treatment. We aimed to use functional neuroimaging and pattern regression techniques to determine whether patterns of brain activity could accurately decode individual-level severity on a dimensional scale measuring behavioural and emotional dysregulation at two different time points. A sample of fifty-seven youth (mean age: 14.5 years; 32 males) was selected from a multi-site study of youth with parent-reported behavioral and emotional dysregulation. Participants performed a block-design reward paradigm during functional Magnetic Resonance Imaging (fMRI). Pattern regression analyses consisted of Relevance Vector Regression (RVR) and two cross-validation strategies implemented in the Pattern Recognition for Neuroimaging toolbox (PRoNTo). Medication was treated as a binary confounding variable. Decoded and actual clinical scores were compared using Pearson's correlation coefficient (r) and mean squared error (MSE) to evaluate the models. Permutation test was applied to estimate significance levels. Relevance Vector Regression identified patterns of neural activity associated with symptoms of behavioral and emotional dysregulation at the initial study screen and close to the fMRI scanning session. The correlation and the mean squared error between actual and decoded symptoms were significant at the initial study screen and close to the fMRI scanning session. However, after controlling for potential medication effects, results remained significant only for decoding symptoms at the initial study screen. Neural regions with the highest contribution to the pattern regression model included cerebellum, sensory-motor and fronto-limbic areas. The combination of pattern regression models and neuroimaging can help to determine the severity of behavioral and emotional dysregulation in youth at different time points.
Lung nodule malignancy prediction using multi-task convolutional neural network
NASA Astrophysics Data System (ADS)
Li, Xiuli; Kao, Yueying; Shen, Wei; Li, Xiang; Xie, Guotong
2017-03-01
In this paper, we investigated the problem of diagnostic lung nodule malignancy prediction using thoracic Computed Tomography (CT) screening. Unlike most existing studies classify the nodules into two types benign and malignancy, we interpreted the nodule malignancy prediction as a regression problem to predict continuous malignancy level. We proposed a joint multi-task learning algorithm using Convolutional Neural Network (CNN) to capture nodule heterogeneity by extracting discriminative features from alternatingly stacked layers. We trained a CNN regression model to predict the nodule malignancy, and designed a multi-task learning mechanism to simultaneously share knowledge among 9 different nodule characteristics (Subtlety, Calcification, Sphericity, Margin, Lobulation, Spiculation, Texture, Diameter and Malignancy), and improved the final prediction result. Each CNN would generate characteristic-specific feature representations, and then we applied multi-task learning on the features to predict the corresponding likelihood for that characteristic. We evaluated the proposed method on 2620 nodules CT scans from LIDC-IDRI dataset with the 5-fold cross validation strategy. The multitask CNN regression result for regression RMSE and mapped classification ACC were 0.830 and 83.03%, while the results for single task regression RMSE 0.894 and mapped classification ACC 74.9%. Experiments show that the proposed method could predict the lung nodule malignancy likelihood effectively and outperforms the state-of-the-art methods. The learning framework could easily be applied in other anomaly likelihood prediction problem, such as skin cancer and breast cancer. It demonstrated the possibility of our method facilitating the radiologists for nodule staging assessment and individual therapeutic planning.
Diagnostic Algorithm to Reflect Regressive Changes of Human Papilloma Virus in Tissue Biopsies
Lhee, Min Jin; Cha, Youn Jin; Bae, Jong Man; Kim, Young Tae
2014-01-01
Purpose Landmark indicators have not yet to be developed to detect the regression of cervical intraepithelial neoplasia (CIN). We propose that quantitative viral load and indicative histological criteria can be used to differentiate between atypical squamous cells of undetermined significance (ASCUS) and a CIN of grade 1. Materials and Methods We collected 115 tissue biopsies from women who tested positive for the human papilloma virus (HPV). Nine morphological parameters including nuclear size, perinuclear halo, hyperchromasia, typical koilocyte (TK), abortive koilocyte (AK), bi-/multi-nucleation, keratohyaline granules, inflammation, and dyskeratosis were examined for each case. Correlation analyses, cumulative logistic regression, and binary logistic regression were used to determine optimal cut-off values of HPV copy numbers. The parameters TK, perinuclear halo, multi-nucleation, and nuclear size were significantly correlated quantitatively to HPV copy number. Results An HPV loading number of 58.9 and AK number of 20 were optimal to discriminate between negative and subtle findings in biopsies. An HPV loading number of 271.49 and AK of 20 were optimal for discriminating between equivocal changes and obvious koilocytosis. Conclusion We propose that a squamous epithelial lesion with AK of >20 and quantitative HPV copy number between 58.9-271.49 represents a new spectrum of subtle pathological findings, characterized by AK in ASCUS. This can be described as a distinct entity and called "regressing koilocytosis". PMID:24532500
Izquierdo-Sotorrío, Eva; Holgado-Tello, Francisco P.; Carrasco, Miguel Á.
2016-01-01
This study examines the relationships between perceived parental acceptance and children’s behavioral problems (externalizing and internalizing) from a multi-informant perspective. Using mothers, fathers, and children as sources of information, we explore the informant effect and incremental validity. The sample was composed of 681 participants (227 children, 227 fathers, and 227 mothers). Children’s (40% boys) ages ranged from 9 to 17 years (M = 12.52, SD = 1.81). Parents and children completed both the Parental Acceptance Rejection/Control Questionnaire (PARQ/Control) and the check list of the Achenbach System of Empirically Based Assessment (ASEBA). Statistical analyses were based on the correlated uniqueness multitrait-multimethod matrix (model MTMM) by structural equations and different hierarchical regression analyses. Results showed a significant informant effect and a different incremental validity related to which combination of sources was considered. A multi-informant perspective rather than a single one increased the predictive value. Our results suggest that mother–father or child–father combinations seem to be the best way to optimize the multi-informant method in order to predict children’s behavioral problems based on perceived parental acceptance. PMID:27242582
Izquierdo-Sotorrío, Eva; Holgado-Tello, Francisco P; Carrasco, Miguel Á
2016-01-01
This study examines the relationships between perceived parental acceptance and children's behavioral problems (externalizing and internalizing) from a multi-informant perspective. Using mothers, fathers, and children as sources of information, we explore the informant effect and incremental validity. The sample was composed of 681 participants (227 children, 227 fathers, and 227 mothers). Children's (40% boys) ages ranged from 9 to 17 years (M = 12.52, SD = 1.81). Parents and children completed both the Parental Acceptance Rejection/Control Questionnaire (PARQ/Control) and the check list of the Achenbach System of Empirically Based Assessment (ASEBA). Statistical analyses were based on the correlated uniqueness multitrait-multimethod matrix (model MTMM) by structural equations and different hierarchical regression analyses. Results showed a significant informant effect and a different incremental validity related to which combination of sources was considered. A multi-informant perspective rather than a single one increased the predictive value. Our results suggest that mother-father or child-father combinations seem to be the best way to optimize the multi-informant method in order to predict children's behavioral problems based on perceived parental acceptance.
Zhang, L; Liu, X J
2016-06-03
With the rapid development of next-generation high-throughput sequencing technology, RNA-seq has become a standard and important technique for transcriptome analysis. For multi-sample RNA-seq data, the existing expression estimation methods usually deal with each single-RNA-seq sample, and ignore that the read distributions are consistent across multiple samples. In the current study, we propose a structured sparse regression method, SSRSeq, to estimate isoform expression using multi-sample RNA-seq data. SSRSeq uses a non-parameter model to capture the general tendency of non-uniformity read distribution for all genes across multiple samples. Additionally, our method adds a structured sparse regularization, which not only incorporates the sparse specificity between a gene and its corresponding isoform expression levels, but also reduces the effects of noisy reads, especially for lowly expressed genes and isoforms. Four real datasets were used to evaluate our method on isoform expression estimation. Compared with other popular methods, SSRSeq reduced the variance between multiple samples, and produced more accurate isoform expression estimations, and thus more meaningful biological interpretations.
Center-Within-Trial Versus Trial-Level Evaluation of Surrogate Endpoints.
Renfro, Lindsay A; Shi, Qian; Xue, Yuan; Li, Junlong; Shang, Hongwei; Sargent, Daniel J
2014-10-01
Evaluation of candidate surrogate endpoints using individual patient data from multiple clinical trials is considered the gold standard approach to validate surrogates at both patient and trial levels. However, this approach assumes the availability of patient-level data from a relatively large collection of similar trials, which may not be possible to achieve for a given disease application. One common solution to the problem of too few similar trials involves performing trial-level surrogacy analyses on trial sub-units (e.g., centers within trials), thereby artificially increasing the trial-level sample size for feasibility of the multi-trial analysis. To date, the practical impact of treating trial sub-units (centers) identically to trials in multi-trial surrogacy analyses remains unexplored, and conditions under which this ad hoc solution may in fact be reasonable have not been identified. We perform a simulation study to identify such conditions, and demonstrate practical implications using a multi-trial dataset of patients with early stage colon cancer.
Center-Within-Trial Versus Trial-Level Evaluation of Surrogate Endpoints
Renfro, Lindsay A.; Shi, Qian; Xue, Yuan; Li, Junlong; Shang, Hongwei; Sargent, Daniel J.
2014-01-01
Evaluation of candidate surrogate endpoints using individual patient data from multiple clinical trials is considered the gold standard approach to validate surrogates at both patient and trial levels. However, this approach assumes the availability of patient-level data from a relatively large collection of similar trials, which may not be possible to achieve for a given disease application. One common solution to the problem of too few similar trials involves performing trial-level surrogacy analyses on trial sub-units (e.g., centers within trials), thereby artificially increasing the trial-level sample size for feasibility of the multi-trial analysis. To date, the practical impact of treating trial sub-units (centers) identically to trials in multi-trial surrogacy analyses remains unexplored, and conditions under which this ad hoc solution may in fact be reasonable have not been identified. We perform a simulation study to identify such conditions, and demonstrate practical implications using a multi-trial dataset of patients with early stage colon cancer. PMID:25061255
Pragmatic estimation of a spatio-temporal air quality model with irregular monitoring data
NASA Astrophysics Data System (ADS)
Sampson, Paul D.; Szpiro, Adam A.; Sheppard, Lianne; Lindström, Johan; Kaufman, Joel D.
2011-11-01
Statistical analyses of health effects of air pollution have increasingly used GIS-based covariates for prediction of ambient air quality in "land use" regression models. More recently these spatial regression models have accounted for spatial correlation structure in combining monitoring data with land use covariates. We present a flexible spatio-temporal modeling framework and pragmatic, multi-step estimation procedure that accommodates essentially arbitrary patterns of missing data with respect to an ideally complete space by time matrix of observations on a network of monitoring sites. The methodology incorporates a model for smooth temporal trends with coefficients varying in space according to Partial Least Squares regressions on a large set of geographic covariates and nonstationary modeling of spatio-temporal residuals from these regressions. This work was developed to provide spatial point predictions of PM 2.5 concentrations for the Multi-Ethnic Study of Atherosclerosis and Air Pollution (MESA Air) using irregular monitoring data derived from the AQS regulatory monitoring network and supplemental short-time scale monitoring campaigns conducted to better predict intra-urban variation in air quality. We demonstrate the interpretation and accuracy of this methodology in modeling data from 2000 through 2006 in six U.S. metropolitan areas and establish a basis for likelihood-based estimation.
Decreased levels of sRAGE in follicular fluid from patients with PCOS.
Wang, BiJun; Li, Jing; Yang, QingLing; Zhang, FuLi; Hao, MengMeng; Guo, YiHong
2017-03-01
This study aimed to explore the association between soluble receptor for advanced glycation end products (sRAGE) levels in follicular fluid and the number of oocytes retrieved and to evaluate the effect of sRAGE on vascular endothelial growth factor (VEGF) in granulosa cells in patients with polycystic ovarian syndrome (PCOS). Two sets of experiments were performed in this study. In part one, sRAGE and VEGF protein levels in follicular fluid samples from 39 patients with PCOS and 35 non-PCOS patients were measured by ELISA. In part two, ovarian granulosa cells were isolated from an additional 10 patients with PCOS and cultured. VEGF and SP1 mRNA and protein levels, as well as pAKT levels, were detected by real-time PCR and Western blotting after cultured cells were treated with different concentrations of sRAGE. Compared with the non-PCOS patients, patients with PCOS had lower sRAGE levels in follicular fluid. Multi-adjusted regression analysis showed that high sRAGE levels in follicular fluid predicted a lower Gn dose, more oocytes retrieved, and a better IVF outcome in the non-PCOS group. Logistic regression analysis showed that higher sRAGE levels predicted favorably IVF outcomes in the non-PCOS group. Multi-adjusted regression analysis also showed that high sRAGE levels in follicular fluid predicted a lower Gn dose in the PCOS group. Treating granulosa cells isolated from patients with PCOS with recombinant sRAGE decreased VEGF and SP1 mRNA and protein expression and pAKT levels in a dose-dependent manner. © 2017 Society for Reproduction and Fertility.
Kumar, Dushyant; Hariharan, Hari; Faizy, Tobias D; Borchert, Patrick; Siemonsen, Susanne; Fiehler, Jens; Reddy, Ravinder; Sedlacik, Jan
2018-05-12
We present a computationally feasible and iterative multi-voxel spatially regularized algorithm for myelin water fraction (MWF) reconstruction. This method utilizes 3D spatial correlations present in anatomical/pathological tissues and underlying B1 + -inhomogeneity or flip angle inhomogeneity to enhance the noise robustness of the reconstruction while intrinsically accounting for stimulated echo contributions using T2-distribution data alone. Simulated data and in vivo data acquired using 3D non-selective multi-echo spin echo (3DNS-MESE) were used to compare the reconstruction quality of the proposed approach against those of the popular algorithm (the method by Prasloski et al.) and our previously proposed 2D multi-slice spatial regularization spatial regularization approach. We also investigated whether the inter-sequence correlations and agreements improved as a result of the proposed approach. MWF-quantifications from two sequences, 3DNS-MESE vs 3DNS-gradient and spin echo (3DNS-GRASE), were compared for both reconstruction approaches to assess correlations and agreements between inter-sequence MWF-value pairs. MWF values from whole-brain data of six volunteers and two multiple sclerosis patients are being reported as well. In comparison with competing approaches such as Prasloski's method or our previously proposed 2D multi-slice spatial regularization method, the proposed method showed better agreements with simulated truths using regression analyses and Bland-Altman analyses. For 3DNS-MESE data, MWF-maps reconstructed using the proposed algorithm provided better depictions of white matter structures in subcortical areas adjoining gray matter which agreed more closely with corresponding contrasts on T2-weighted images than MWF-maps reconstructed with the method by Prasloski et al. We also achieved a higher level of correlations and agreements between inter-sequence (3DNS-MESE vs 3DNS-GRASE) MWF-value pairs. The proposed algorithm provides more noise-robust fits to T2-decay data and improves MWF-quantifications in white matter structures especially in the sub-cortical white matter and major white matter tract regions. Copyright © 2018 Elsevier Inc. All rights reserved.
Age-Specific Prostate Specific Antigen Cutoffs for Guiding Biopsy Decision in Chinese Population
Xu, Jianfeng; Jiang, Haowen; Ding, Qiang
2013-01-01
Background Age-specific prostate specific antigen (PSA) cutoffs for prostate biopsy have been widely used in the USA and European countries. However, the application of age-specific PSA remains poorly understood in China. Methods Between 2003 and 2012, 1,848 men over the age of 40, underwent prostate biopsy for prostate cancer (PCa) at Huashan Hospital, Shanghai, China. Clinical information and blood samples were collected prior to biopsy for each patient. Men were divided into three age groups (≤60, 61 to 80, and >80) for analyses. Digital rectal examination (DRE), transrectal ultrasound (prostate volume and nodule), total PSA (tPSA), and free PSA (fPSA) were also included in the analyses. Logistic regression was used to build the multi-variate model. Results Serum tPSA levels were age-dependent (P = 0.008), while %fPSA (P = 0.051) and PSAD (P = 0.284) were age-independent. At a specificity of 80%, the sensitivities for predicting PCa were 83%, 71% and 68% with tPSA cutoff values of 19.0 ng/mL (age≤60),21.0 ng/mL (age 61–80), and 23.0 ng/mL (age≥81). Also, sensitivities at the same tPSA levels were able to reach relatively high levels (70%–88%) for predicting high-grade PCa. Area (AUC) under the receive operating curves (ROCs) of tPSA, %fPSA, PSAD and multi-variate model were different in age groups. When predicting PCa, the AUC of tPSA, %fPSA, PSAD and multi-variate model were 0.90, 0.57, 0.93 and 0.87 respectively in men ≤60 yr; 0.82, 0.70, 0.88 and 0.86 respectively in men 61–80 yr; 0.79, 0.78, 0.87 and 0.88 respectively in men>80 yr. When predicting Gleason Score ≥7 or 8 PCa, there were no significant differences between AUCs of each variable. Conclusion Age-specific PSA cutoff values for prostate biopsy should be considered in the Chinese population. Indications for prostate biopsies (tPSA, %fPSA and PSAD) should be considered based on age in the Chinese population. PMID:23825670
Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio
2018-01-01
Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By "multi-level" we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization.
Effectiveness of a worksite mindfulness-based multi-component intervention on lifestyle behaviors
2014-01-01
Introduction Overweight and obesity are associated with an increased risk of morbidity. Mindfulness training could be an effective strategy to optimize lifestyle behaviors related to body weight gain. The aim of this study was to evaluate the effectiveness of a worksite mindfulness-based multi-component intervention on vigorous physical activity in leisure time, sedentary behavior at work, fruit intake and determinants of these behaviors. The control group received information on existing lifestyle behavior- related facilities that were already available at the worksite. Methods In a randomized controlled trial design (n = 257), 129 workers received a mindfulness training, followed by e-coaching, lunch walking routes and fruit. Outcome measures were assessed at baseline and after 6 and 12 months using questionnaires. Physical activity was also measured using accelerometers. Effects were analyzed using linear mixed effect models according to the intention-to-treat principle. Linear regression models (complete case analyses) were used as sensitivity analyses. Results There were no significant differences in lifestyle behaviors and determinants of these behaviors between the intervention and control group after 6 or 12 months. The sensitivity analyses showed effect modification for gender in sedentary behavior at work at 6-month follow-up, although the main analyses did not. Conclusions This study did not show an effect of a worksite mindfulness-based multi-component intervention on lifestyle behaviors and behavioral determinants after 6 and 12 months. The effectiveness of a worksite mindfulness-based multi-component intervention as a health promotion intervention for all workers could not be established. PMID:24467802
Kim, Sun-Hee
2013-02-01
This study was done to investigate the level of transcultural self-efficacy (TSE) and related factors and educational needs for cultural competence in nursing (CCN) of Korean hospital nurses. A self-assessment instrument was used to measure TSE and educational needs for CCN. Questionnaires were completed by 285 nurses working in four Korean hospitals. Descriptive statistics, t-test, ANOVA, Pearson correlation coefficients, and multiple regression were used to analyze the data. Mean TSE score for all items was 4.54 and score for mean CCN educational needs, 5.77. Nurses with master's degrees or higher had significantly higher levels of TSE than nurses with bachelor's degrees. TSE positively correlated with English language proficiency, degrees of interest in multi-culture, degree of experience in caring for multi-cultural clients, and educational needs for CCN. The regression model explained 28% of TSE. Factors affecting TSE were degree of interest in multi-culture, degree of experience in caring for multi-cultural clients, and educational needs for CCN. The results of the study indicate a need for nurse educators to support nurses to strengthen TSE and provide educational program for TSE to provide nurses with strategies for raising interests in cultural diversity and successful experiences of cultural congruent care.
Multi-level structure in the large scale distribution of optically luminous galaxies
NASA Astrophysics Data System (ADS)
Deng, Xin-fa; Deng, Zu-gan; Liu, Yong-zhen
1992-04-01
Fractal dimensions in the large scale distribution of galaxies have been calculated with the method given by Wen et al. [1] Samples are taken from CfA redshift survey in northern and southern galactic [2] hemisphere in our analysis respectively. Results from these two regions are compared with each other. There are significant differences between the distributions in these two regions. However, our analyses do show some common features of the distributions in these two regions. All subsamples show multi-level fractal character distinctly. Combining it with the results from analyses of samples given by IRAS galaxies and results from samples given by redshift survey in pencil-beam fields, [3,4] we suggest that multi-level fractal structure is most likely to be a general and important character in the large scale distribution of galaxies. The possible implications of this character are discussed.
Zhu, Xiang; Stephens, Matthew
2017-01-01
Bayesian methods for large-scale multiple regression provide attractive approaches to the analysis of genome-wide association studies (GWAS). For example, they can estimate heritability of complex traits, allowing for both polygenic and sparse models; and by incorporating external genomic data into the priors, they can increase power and yield new biological insights. However, these methods require access to individual genotypes and phenotypes, which are often not easily available. Here we provide a framework for performing these analyses without individual-level data. Specifically, we introduce a “Regression with Summary Statistics” (RSS) likelihood, which relates the multiple regression coefficients to univariate regression results that are often easily available. The RSS likelihood requires estimates of correlations among covariates (SNPs), which also can be obtained from public databases. We perform Bayesian multiple regression analysis by combining the RSS likelihood with previously proposed prior distributions, sampling posteriors by Markov chain Monte Carlo. In a wide range of simulations RSS performs similarly to analyses using the individual data, both for estimating heritability and detecting associations. We apply RSS to a GWAS of human height that contains 253,288 individuals typed at 1.06 million SNPs, for which analyses of individual-level data are practically impossible. Estimates of heritability (52%) are consistent with, but more precise, than previous results using subsets of these data. We also identify many previously unreported loci that show evidence for association with height in our analyses. Software is available at https://github.com/stephenslab/rss. PMID:29399241
Lee, Jae Hoon; Kim, Joon Ha; Oh, Hee-Mock; An, Kwang-Guk
2013-01-01
The objectives of this study were to identify multi-level stressors at the DNA/biochemical level to the community level in fish in an urban stream and to develop an integrative health response (IHR) model for ecological health diagnosis. A pristine control site (S (c) ) and an impacted site (S (i) ) were selected from among seven pre-screened sites studied over seven years. Various chemical analyses indicated that nutrient enrichment (Nitrogen, Phosphorus) and organic pollution were significantly greater (t > 8.783, p < 0.01) at the S (i) site compared to the S (c) site. Single-cell gel electrophoresis (comet assays) of DNA-level impairment indicated significantly (t = 5.678, p < 0.01) greater tail intensity, expressed as % tail-DNA, at the S (i) site and genotoxic responses were detected in the downstream reach. Ethoxyresorufin-O-deethylase (EROD) assays, as a physiological bioindicator, were 2.8-fold higher (p < 0.05, NK-test after ANOVA) at the S (i) site. Tissue analysis using a necropsy-based health assessment index (NHAI) showed distinct internal organ disorders in three tissues, i.e., liver, kidney, and gill, at the S (i) site. Population-level analysis using the sentinel species Zacco platypus showed that the regression coefficient (b) was 3.012 for the S (i) site and 2.915 for the S (c) site, indicating population skewness in the downstream reach. Community-level health was impaired at the S (i) site based on an index of biological integrity (IBI), and physical habitat modifications were identified by a qualitative habitat evaluation index (QHEI). Overall, the model values for the integrative health response (IHR), developed using the star plot approach, were 3.22 (80.5%) at the S (c) site and 0.74 (18.5%) at the S (i) site, indicating that, overall, ecological health impairments were evident in the urban reach. Our study was based on multi-level approaches using biological organization and the results suggest that there is a pivotal point of linkage between mechanistic understanding and real ecological consequences of environmental stressors.
2013-03-01
of coarser-scale materials and structures containing Kevlar fibers (e.g., yarns, fabrics, plies, lamina, and laminates ). Journal of Materials...Multi-Length Scale-Enriched Continuum-Level Material Model for Kevlar -Fiber-Reinforced Polymer-Matrix Composites M. Grujicic, B. Pandurangan, J.S...extensive set of molecular-level computational analyses regarding the role of various microstructural/morphological defects on the Kevlar fiber
Barba-Vasseur, Marie; Bernard, Nadine; Pujol, Sophie; Sagot, Paul; Riethmuller, Didier; Thiriez, Gérard; Houot, Hélène; Defrance, Jérôme; Mariet, Anne-Sophie; Luu, Vinh-Phuc; Barbier, Alice; Benzenine, Eric; Quantin, Catherine; Mauny, Frédéric
2017-12-01
Preterm birth (PB) is an important predictor of childhood morbidity and educational performance. Beyond the known risk factors, environmental factors, such as air pollution and noise, have been implicated in PB. In urban areas, these pollutants coexist. Very few studies have examined the effects of multi-exposure on the pregnancy duration. The objective of this study was to analyse the relationship between PB and environmental chronic multi-exposure to noise and air pollution in medium-sized cities. A case-control study was conducted among women living in the city of Besançon (121 671 inhabitants) or in the urban unit of Dijon (243 936 inhabitants) and who delivered in a university hospital between 2005 and 2009. Only singleton pregnancies without associated pathologies were considered. Four controls were matched to each case in terms of the mother's age and delivery location. Residential noise and nitrogen dioxide (NO2) exposures were calculated at the mother's address. Conditional logistic regression models were applied, and sensitivity analyses were performed. This study included 302 cases and 1204 controls. The correlation between noise and NO2 indices ranged from 0.41 to 0.59. No significant differences were found in pollutant exposure levels between cases and controls. The adjusted odds ratios ranged between 0.96 and 1.08. Sensitivity analysis conducted using different temporal and spatial exposure windows demonstrated the same results. The results are in favour of a lack of connection between preterm delivery and multi-exposure to noise and air pollution in medium-sized cities for pregnant women without underlying disease. © The Author 2017; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association
Chahine, Teresa; Schultz, Bradley D.; Zartarian, Valerie G.; Xue, Jianping; Subramanian, SV; Levy, Jonathan I.
2011-01-01
Community-based cumulative risk assessment requires characterization of exposures to multiple chemical and non-chemical stressors, with consideration of how the non-chemical stressors may influence risks from chemical stressors. Residential radon provides an interesting case example, given its large attributable risk, effect modification due to smoking, and significant variability in radon concentrations and smoking patterns. In spite of this fact, no study to date has estimated geographic and sociodemographic patterns of both radon and smoking in a manner that would allow for inclusion of radon in community-based cumulative risk assessment. In this study, we apply multi-level regression models to explain variability in radon based on housing characteristics and geological variables, and construct a regression model predicting housing characteristics using U.S. Census data. Multi-level regression models of smoking based on predictors common to the housing model allow us to link the exposures. We estimate county-average lifetime lung cancer risks from radon ranging from 0.15 to 1.8 in 100, with high-risk clusters in areas and for subpopulations with high predicted radon and smoking rates. Our findings demonstrate the viability of screening-level assessment to characterize patterns of lung cancer risk from radon, with an approach that can be generalized to multiple chemical and non-chemical stressors. PMID:22016710
Burgos, P I; Vilá, L M; Reveille, J D; Alarcón, G S
2009-12-01
To determine the factors associated with peripheral vascular damage in systemic lupus erythematosus patients and its impact on survival from Lupus in Minorities, Nature versus Nurture, a longitudinal US multi-ethnic cohort. Peripheral vascular damage was defined by the Systemic Lupus International Collaborating Clinics Damage Index (SDI). Factors associated with peripheral vascular damage were examined by univariable and multi-variable logistic regression models and its impact on survival by a Cox multi-variable regression. Thirty-four (5.3%) of 637 patients (90% women, mean [SD] age 36.5 [12.6] [16-87] years) developed peripheral vascular damage. Age and the SDI (without peripheral vascular damage) were statistically significant (odds ratio [OR] = 1.05, 95% confidence interval [CI] 1.01-1.08; P = 0.0107 and OR = 1.30, 95% CI 0.09-1.56; P = 0.0043, respectively) in multi-variable analyses. Azathioprine, warfarin and statins were also statistically significant, and glucocorticoid use was borderline statistically significant (OR = 1.03, 95% CI 0.10-1.06; P = 0.0975). In the survival analysis, peripheral vascular damage was independently associated with a diminished survival (hazard ratio = 2.36; 95% CI 1.07-5.19; P = 0.0334). In short, age was independently associated with peripheral vascular damage, but so was the presence of damage in other organs (ocular, neuropsychiatric, renal, cardiovascular, pulmonary, musculoskeletal and integument) and some medications (probably reflecting more severe disease). Peripheral vascular damage also negatively affected survival.
Quantification of trace metals in infant formula premixes using laser-induced breakdown spectroscopy
NASA Astrophysics Data System (ADS)
Cama-Moncunill, Raquel; Casado-Gavalda, Maria P.; Cama-Moncunill, Xavier; Markiewicz-Keszycka, Maria; Dixit, Yash; Cullen, Patrick J.; Sullivan, Carl
2017-09-01
Infant formula is a human milk substitute generally based upon fortified cow milk components. In order to mimic the composition of breast milk, trace elements such as copper, iron and zinc are usually added in a single operation using a premix. The correct addition of premixes must be verified to ensure that the target levels in infant formulae are achieved. In this study, a laser-induced breakdown spectroscopy (LIBS) system was assessed as a fast validation tool for trace element premixes. LIBS is a promising emission spectroscopic technique for elemental analysis, which offers real-time analyses, little to no sample preparation and ease of use. LIBS was employed for copper and iron determinations of premix samples ranging approximately from 0 to 120 mg/kg Cu/1640 mg/kg Fe. LIBS spectra are affected by several parameters, hindering subsequent quantitative analyses. This work aimed at testing three matrix-matched calibration approaches (simple-linear regression, multi-linear regression and partial least squares regression (PLS)) as means for precision and accuracy enhancement of LIBS quantitative analysis. All calibration models were first developed using a training set and then validated with an independent test set. PLS yielded the best results. For instance, the PLS model for copper provided a coefficient of determination (R2) of 0.995 and a root mean square error of prediction (RMSEP) of 14 mg/kg. Furthermore, LIBS was employed to penetrate through the samples by repetitively measuring the same spot. Consequently, LIBS spectra can be obtained as a function of sample layers. This information was used to explore whether measuring deeper into the sample could reduce possible surface-contaminant effects and provide better quantifications.
Cell-phone vs microphone recordings: Judging emotion in the voice.
Green, Joshua J; Eigsti, Inge-Marie
2017-09-01
Emotional states can be conveyed by vocal cues such as pitch and intensity. Despite the ubiquity of cellular telephones, there is limited information on how vocal emotional states are perceived during cell-phone transmissions. Emotional utterances (neutral, happy, angry) were elicited from two female talkers and simultaneously recorded via microphone and cell-phone. Ten-step continua (neutral to happy, neutral to angry) were generated using the straight algorithm. Analyses compared reaction time (RT) and emotion judgment as a function of recording type (microphone vs cell-phone). Logistic regression revealed no judgment differences between recording types, though there were interactions with emotion type. Multi-level model analyses indicated that RT data were best fit by a quadratic model, with slower RT at the middle of each continuum, suggesting greater ambiguity, and slower RT for cell-phone stimuli across blocks. While preliminary, results suggest that critical acoustic cues to emotion are largely retained in cell-phone transmissions, though with effects of recording source on RT, and support the methodological utility of collecting speech samples by phone.
Green, M A; Subramanian, S V; Strong, M; Cooper, C L; Loban, A; Bissell, P
2015-03-01
To analyse whether an individual's neighbourhood influences the uptake of weight management strategies and whether there is an interaction between individual socio-economic status and neighbourhood deprivation. Data were collected from the Yorkshire Health Study (2010-2012) for 27 806 individuals on the use of the following weight management strategies: 'slimming clubs', 'healthy eating', 'increasing exercise' and 'controlling portion size'. A multi-level logistic regression was fit to analyse the use of these strategies, controlling for age, sex, body mass index, education, neighbourhood deprivation and neighbourhood population turnover (a proxy for neighbourhood social capital). A cross-level interaction term was included for education and neighbourhood deprivation. Lower Super Output Area was used as the geographical scale for the areal unit of analysis. Significant neighbourhood effects were observed for use of 'slimming clubs', 'healthy eating' and 'increasing exercise' as weight management strategies, independent of individual- and area-level covariates. A significant interaction between education and neighbourhood deprivation was observed across all strategies, suggesting that as an area becomes more deprived, individuals of the lowest education are more likely not to use any strategy compared with those of the highest education. Neighbourhoods modify/amplify individual disadvantage and social inequalities, with individuals of low education disproportionally affected by deprivation. It is important to include neighbourhood-based explanations in the development of community-based policy interventions to help tackle obesity.
Multi-country health surveys: are the analyses misleading?
Masood, Mohd; Reidpath, Daniel D
2014-05-01
The aim of this paper was to review the types of approaches currently utilized in the analysis of multi-country survey data, specifically focusing on design and modeling issues with a focus on analyses of significant multi-country surveys published in 2010. A systematic search strategy was used to identify the 10 multi-country surveys and the articles published from them in 2010. The surveys were selected to reflect diverse topics and foci; and provide an insight into analytic approaches across research themes. The search identified 159 articles appropriate for full text review and data extraction. The analyses adopted in the multi-country surveys can be broadly classified as: univariate/bivariate analyses, and multivariate/multivariable analyses. Multivariate/multivariable analyses may be further divided into design- and model-based analyses. Of the 159 articles reviewed, 129 articles used model-based analysis, 30 articles used design-based analyses. Similar patterns could be seen in all the individual surveys. While there is general agreement among survey statisticians that complex surveys are most appropriately analyzed using design-based analyses, most researchers continued to use the more common model-based approaches. Recent developments in design-based multi-level analysis may be one approach to include all the survey design characteristics. This is a relatively new area, however, and there remains statistical, as well as applied analytic research required. An important limitation of this study relates to the selection of the surveys used and the choice of year for the analysis, i.e., year 2010 only. There is, however, no strong reason to believe that analytic strategies have changed radically in the past few years, and 2010 provides a credible snapshot of current practice.
Chen, Senlin; Kim, Youngwon; Gao, Zan
2014-02-04
School physical education (PE) is considered as an effective channel for youth to accumulate moderate-to-vigorous physical activity (MVPA) and reduce sedentary time. The purpose of this study was to determine the contributing role of PE in daily MVPA and sedentary time among youth. The study recruited 67 sixth grade children (29 boys; Mean age = 11.75) from two suburban schools at a U.S. Midwest state, 48 of whom contributed ≥10 hours of physical activity (PA) data per day were included for analysis. An objective monitoring tool (i.e., Sensewear armband monitor) was used to capture the participants' MVPA and sedentary time for 7-14 days. Pearson product-moment correlation analysis (r), multi-level regression analyses, and analysis of variance were conducted for data analysis. MVPA and sedentary time in PE showed significant positive associations with daily MVPA and sedentary time, respectively (r = 0.35, p < 0.01; r = 0.55, p < 0.01). Regression analyses revealed that one minute increase in MVPA and sedentary behavior in PE was associated with 2.04 minutes and 5.30 minutes increases in daily MVPA and sedentary behavior, respectively, after controlling for sex and BMI. The participants demonstrated a significantly higher level of MVPA (p = .05) but similar sedentary time (p = 0.61) on PE days than on non-PE days. Boys had significantly more daily MVPA (p < .01) and less sedentary time (p < .01) than girls; while higher BMI was associated with more sedentary time (p < .01). PE displayed a positive contribution to increasing daily MVPA and decreasing daily sedentary time among youth. Active participation in PE classes increases the chance to be more active and less sedentary beyond PE among youth.
Bennett, Bradley C; Husby, Chad E
2008-03-28
Botanical pharmacopoeias are non-random subsets of floras, with some taxonomic groups over- or under-represented. Moerman [Moerman, D.E., 1979. Symbols and selectivity: a statistical analysis of Native American medical ethnobotany, Journal of Ethnopharmacology 1, 111-119] introduced linear regression/residual analysis to examine these patterns. However, regression, the commonly-employed analysis, suffers from several statistical flaws. We use contingency table and binomial analyses to examine patterns of Shuar medicinal plant use (from Amazonian Ecuador). We first analyzed the Shuar data using Moerman's approach, modified to better meet requirements of linear regression analysis. Second, we assessed the exact randomization contingency table test for goodness of fit. Third, we developed a binomial model to test for non-random selection of plants in individual families. Modified regression models (which accommodated assumptions of linear regression) reduced R(2) to from 0.59 to 0.38, but did not eliminate all problems associated with regression analyses. Contingency table analyses revealed that the entire flora departs from the null model of equal proportions of medicinal plants in all families. In the binomial analysis, only 10 angiosperm families (of 115) differed significantly from the null model. These 10 families are largely responsible for patterns seen at higher taxonomic levels. Contingency table and binomial analyses offer an easy and statistically valid alternative to the regression approach.
Comparison of buried sand ridges and regressive sand ridges on the outer shelf of the East China Sea
NASA Astrophysics Data System (ADS)
Wu, Ziyin; Jin, Xianglong; Zhou, Jieqiong; Zhao, Dineng; Shang, Jihong; Li, Shoujun; Cao, Zhenyi; Liang, Yuyang
2017-06-01
Based on multi-beam echo soundings and high-resolution single-channel seismic profiles, linear sand ridges in U14 and U2 on the East China Sea (ECS) shelf are identified and compared in detail. Linear sand ridges in U14 are buried sand ridges, which are 90 m below the seafloor. It is presumed that these buried sand ridges belong to the transgressive systems tract (TST) formed 320-200 ka ago and that their top interface is the maximal flooding surface (MFS). Linear sand ridges in U2 are regressive sand ridges. It is presumed that these buried sand ridges belong to the TST of the last glacial maximum (LGM) and that their top interface is the MFS of the LGM. Four sub-stage sand ridges of U2 are discerned from the high-resolution single-channel seismic profile and four strikes of regressive sand ridges are distinguished from the submarine topographic map based on the multi-beam echo soundings. These multi-stage and multi-strike linear sand ridges are the response of, and evidence for, the evolution of submarine topography with respect to sea-level fluctuations since the LGM. Although the difference in the age of formation between U14 and U2 is 200 ka and their sequences are 90 m apart, the general strikes of the sand ridges are similar. This indicates that the basic configuration of tidal waves on the ECS shelf has been stable for the last 200 ka. A basic evolutionary model of the strata of the ECS shelf is proposed, in which sea-level change is the controlling factor. During the sea-level change of about 100 ka, five to six strata are developed and the sand ridges develop in the TST. A similar story of the evolution of paleo-topography on the ECS shelf has been repeated during the last 300 ka.
Are there differences in birth weight between neighbourhoods in a Nordic welfare state?
Sellström, Eva; Arnoldsson, Göran; Bremberg, Sven; Hjern, Anders
2007-09-26
The objective of this cohort study was to examine the effect on birth weight of living in a disadvantaged neighbourhood in a Nordic welfare state. Birth weight is a health indicator known to be sensitive to political and welfare state conditions. No former studies on urban neighbourhood differences regarding mean birth weight have been carried out in a Nordic country. A register based on individual data on children's birth weight and maternal risk factors was used. A neighbourhood characteristic, i.e. an aggregated measure on income was also included. Connections between individual- and neighbourhood-level determinants and the outcome were analysed using multi-level regression technique. The study covered six hundred and ninety-six neighbourhoods in the three major cities of Sweden, Stockholm, Göteborg and Malmö, during 1992-2001. The majority of neighbourhoods had a population of 4 000-10 000 inhabitants. An average of 500 births per neighbourhood were analysed in this study. Differences in mean birth weight in Swedish urban neighbourhoods were minor. However, gestational length, parity and maternal smoking acted as modifiers of the neighbourhood effects. Most of the observed variation in mean birth weight was explained by individual risk factors. Welfare institutions and benefits in Sweden might buffer against negative infant outcomes due to adverse structural organisation of urban neighbourhoods.
Financial and Emotional Support in Close Personal Ties among Central Asian Migrant Women in Russia.
Kornienko, Olga; Agadjanian, Victor; Menjívar, Cecilia; Zotova, Natalia
2018-05-01
This study advances research on the role of personal networks as sources of financial and emotional support in immigrants' close personal ties beyond the immediate family. Because resource scarcity experienced by members of immigrant communities is likely to disrupt normatively expected reciprocal support, we explored multi-level predictors of exchange processes with personal network members that involve (1) only receiving support, (2) only providing support, and (3) reciprocal support exchanges. We focus on an understudied case of Central Asian migrant women in the Russian Federation using a sample of 607 women from three ethnic groups-Kyrgyz, Tajik, Uzbek-who were surveyed in two large Russian cities-Nizhny Novgorod and Kazan. The survey collected information on respondents' demographic, socioeconomic, and migration-related characteristics, as well as characteristics of up to five individuals with whom they had a close relationship. Multi-level multinomial regression analyses were used to account for the nested nature of the data. Our results revealed that closer social relationships (siblings and friends) and greater levels of resources (income and regularized legal status) at both ego and alter levels were positively related to providing, receiving, and reciprocally exchanging financial and emotional support. Egos were more likely to provide financial assistance to transnational alters, whereas they were more likely to engage in mutual exchanges of emotional support with their network members from other countries. Personal network size and density showed no relationship with support exchanges. These findings provide a nuanced picture of close personal ties as conduits for financial and emotional support in migrant communities in a major, yet understudied, migrant-receiving context.
Determinants of Effective Caregiver Communication After Adolescent Traumatic Brain Injury
Hobart-Porter, Laura; Wade, Shari; Minich, Nori; Kirkwood, Michael; Stancin, Terry; Taylor, Hudson Gerry
2017-01-01
Objective To characterize the effects of caregiver mental health and coping strategies on interactions with an injured adolescent acutely after traumatic brain injury (TBI). Design Multi-site, cross-sectional study. Setting Outpatient setting of 3 tertiary pediatric hospitals and 2 tertiary general medical centers. Participants Adolescents (N = 125) aged 12–17 years, 1–6 months after being hospitalized with complicated mild to severe TBI. Methods Data were collected as part of a multi-site clinical trial of family problem-solving therapy after TBI. Multiple regression analyses were used to examine the relationship of caregiver and environmental characteristics to the dimensions of effective communication, warmth, and negativity during caregiver-adolescent problem-solving discussions. Main Outcomes Measures Adolescent and caregiver interactions, as measured by the Iowa Family Interaction Rating Scales. Results Caregivers who utilized problem-focused coping strategies were rated as having higher levels of effective communication (P <.01), as were those with higher socioeconomic status (P <.01). Problem-focused coping style and higher socioeconomic status were also associated lower levels of negative interactions (P < .01 and P < .05, respectively). Female gender of the adolescent and fewer children in the home were associated with increased parental warmth during the interaction (P < .01 and P < .05, respectively). Neither adolescent TBI severity nor caregiver depression significantly influenced caregiver-teen interactions. Conclusions Problem-focused coping strategies are associated with higher levels of effective communication and lower levels of caregiver negativity during the initial months after adolescent TBI, suggesting that effective caregiver coping may facilitate better caregiver-adolescent interactions after TBI. PMID:25687111
Determinants of Effective Caregiver Communication After Adolescent Traumatic Brain Injury.
Hobart-Porter, Laura; Wade, Shari; Minich, Nori; Kirkwood, Michael; Stancin, Terry; Taylor, Hudson Gerry
2015-08-01
To characterize the effects of caregiver mental health and coping strategies on interactions with an injured adolescent acutely after traumatic brain injury (TBI). Multi-site, cross-sectional study. Outpatient setting of 3 tertiary pediatric hospitals and 2 tertiary general medical centers. Adolescents (N = 125) aged 12-17 years, 1-6 months after being hospitalized with complicated mild to severe TBI. Data were collected as part of a multi-site clinical trial of family problem-solving therapy after TBI. Multiple regression analyses were used to examine the relationship of caregiver and environmental characteristics to the dimensions of effective communication, warmth, and negativity during caregiver-adolescent problem-solving discussions. Adolescent and caregiver interactions, as measured by the Iowa Family Interaction Rating Scales. Caregivers who utilized problem-focused coping strategies were rated as having higher levels of effective communication (P < .01), as were those with higher socioeconomic status (P < .01). Problem-focused coping style and higher socioeconomic status were also associated lower levels of negative interactions (P < .01 and P < .05, respectively). Female gender of the adolescent and fewer children in the home were associated with increased parental warmth during the interaction (P < .01 and P < .05, respectively). Neither adolescent TBI severity nor caregiver depression significantly influenced caregiver-teen interactions. Problem-focused coping strategies are associated with higher levels of effective communication and lower levels of caregiver negativity during the initial months after adolescent TBI, suggesting that effective caregiver coping may facilitate better caregiver-adolescent interactions after TBI. Copyright © 2015 American Academy of Physical Medicine and Rehabilitation. Published by Elsevier Inc. All rights reserved.
The multi-level perspective analysis: Indonesia geothermal energy transition study
NASA Astrophysics Data System (ADS)
Wisaksono, A.; Murphy, J.; Sharp, J. H.; Younger, P. L.
2018-01-01
The study adopts a multi-level perspective in technology transition to analyse how the transition process in the development of geothermal energy in Indonesia is able to compete against the incumbent fossil-fuelled energy sources. Three levels of multi-level perspective are socio-technical landscape (ST-landscape), socio-technical regime (ST-regime) and niche innovations in Indonesia geothermal development. The identification, mapping and analysis of the dynamic relationship between each level are the important pillars of the multi-level perspective framework. The analysis considers the set of rules, actors and controversies that may arise in the technological transition process. The identified geothermal resource risks are the basis of the emerging geothermal technological innovations in Indonesian geothermal. The analysis of this study reveals the transition pathway, which yields a forecast for the Indonesian geothermal technology transition in the form of scenarios and probable impacts.
Person-city personality fit and entrepreneurial success: An explorative study in China.
Zhou, Mingjie; Zhou, Yixin; Zhang, Jianxin; Obschonka, Martin; Silbereisen, Rainer K
2017-08-13
While the study of personality differences is a traditional psychological approach in entrepreneurship research, economic research directs attention towards the entrepreneurial ecosystems in which entrepreneurial activity are embedded. We combine both approaches and quantify the interplay between the individual personality make-up of entrepreneurs and the local personality composition of ecosystems, with a special focus on person-city personality fit. Specifically, we analyse personality data from N = 26,405 Chinese residents across 42 major Chinese cities, including N = 1091 Chinese entrepreneurs. Multi-level polynomial regression and response surface plots revealed that: (a) individual-level conscientiousness had a positive effect and individual-level agreeableness and neuroticism had a negative effect on entrepreneurial success, (b) city-level conscientiousness had a positive, and city-level neuroticism had a negative effect on entrepreneurial success, and (c) additional person-city personality fit effects existed for agreeableness, conscientiousness and neuroticism. For example, entrepreneurs who are high in agreeableness and conduct their business in a city with a low agreeableness level show the lowest entrepreneurial success. In contrast, entrepreneurs who are low in agreeableness and conduct their business in a city with a high agreeableness level show relatively high entrepreneurial success. Implications for research and practice are discussed. © 2017 International Union of Psychological Science.
Knechtle, Beat; Bragazzi, Nicola Luigi; König, Stefan; Nikolaidis, Pantelis Theodoros; Wild, Stefanie; Rosemann, Thomas; Rüst, Christoph Alexander
2016-01-01
(1) Background: We investigated the age of swimming champions in all strokes and race distances in World Championships (1994–2013) and Olympic Games (1992–2012); (2) Methods: Changes in age and swimming performance across calendar years for 412 Olympic and world champions were analysed using linear, non-linear, multi-level regression analyses and MultiLayer Perceptron (MLP); (3) Results: The age of peak swimming performance remained stable in most of all race distances for world champions and in all race distances for Olympic champions. Longer (i.e., 200 m and more) race distances were completed by younger (~20 years old for women and ~22 years old for men) champions than shorter (i.e., 50 m and 100 m) race distances (~22 years old for women and ~24 years old for men). There was a sex difference in the age of champions of ~2 years with a mean age of ~21 and ~23 years for women and men, respectively. Swimming performance improved in most race distances for world and Olympic champions with a larger trend of increase in Olympic champions; (4) Conclusion: Swimmers at younger ages (<20 years) may benefit from training and competing in longer race distances (i.e., 200 m and longer) before they change to shorter distances (i.e., 50 m and 100 m) when they become older (>22 years). PMID:29910265
Population levels of wellbeing and the association with social capital.
Taylor, A W; Kelly, G; Dal Grande, E; Kelly, D; Marin, T; Hey, N; Burke, K J; Licinio, J
2017-07-03
This research investigates wellbeing at the population level across demographic, social and health indicators and assesses the association between wellbeing and social capital. Data from a South Australian monthly chronic disease/risk factor surveillance system of randomly selected adults (mean age 48.7 years; range 16-99) from 2014/5 (n = 5551) were used. Univariable analyses compared wellbeing/social capital indicators, socio-demographic, risk factors and chronic conditions. Multi-nominal logistic regression modelling, adjusting for multiple covariates was used to simultaneously estimate odds ratios for good wellbeing (reference category) versus neither good nor poor, and good wellbeing versus poor wellbeing. 48.6% were male, mean age 48.7 (sd 18.3), 54.3% scored well on all four of the wellbeing indicators, and positive social capital indicators ranged from 93.1% for safety to 50.8% for control over decisions. The higher level of social capital corresponded with the good wellbeing category. Modeling showed higher odds ratios for all social capital variables for the lowest level of wellbeing. These higher odds ratios remained after adjusting for confounders. The relationship between wellbeing, resilience and social capital highlights areas for increased policy focus.
Virtual Beach version 2.2 (VB 2.2) is a decision support tool. It is designed to construct site-specific Multi-Linear Regression (MLR) models to predict pathogen indicator levels (or fecal indicator bacteria, FIB) at recreational beaches. MLR analysis has outperformed persisten...
Khanna, Niharika; Shaya, Fadia T; Chirikov, Viktor V; Sharp, David; Steffen, Ben
2016-01-01
We present data on quality of care (QC) improvement in 35 of 45 National Quality Forum metrics reported annually by 52 primary care practices recognized as patient-centered medical homes (PCMHs) that participated in the Maryland Multi-Payor Program from 2011 to 2013. We assigned QC metrics to (1) chronic, (2) preventive, and (3) mental health care domains. The study used a panel data design with no control group. Using longitudinal fixed-effects regressions, we modeled QC and case mix severity in a PCMH. Overall, 35 of 45 quality metrics reported by 52 PCMHs demonstrated improvement over 3 years, and case mix severity did not affect the achievement of quality improvement. From 2011 to 2012, QC increased by 0.14 (P < .01) for chronic, 0.15 (P < .01) for preventive, and 0.34 (P < .01) for mental health care domains; from 2012 to 2013 these domains increased by 0.03 (P = .06), 0.04 (P = .05), and 0.07 (P = .12), respectively. In univariate analyses, lower National Commission on Quality Assurance PCMH level was associated with higher QC for the mental health care domain, whereas case mix severity did not correlate with QC. In multivariate analyses, higher QC correlated with larger practices, greater proportion of older patients, and readmission visits. Rural practices had higher proportions of Medicaid patients, lower QC, and higher QC improvement in interaction analyses with time. The gains in QC in the chronic disease domain, the preventive care domain, and, most significantly, the mental health care domain were observed over time regardless of patient case mix severity. QC improvement was generally not modified by practice characteristics, except for rurality. © Copyright 2016 by the American Board of Family Medicine.
Brown, C. Erwin
1993-01-01
Correlation analysis in conjunction with principal-component and multiple-regression analyses were applied to laboratory chemical and petrographic data to assess the usefulness of these techniques in evaluating selected physical and hydraulic properties of carbonate-rock aquifers in central Pennsylvania. Correlation and principal-component analyses were used to establish relations and associations among variables, to determine dimensions of property variation of samples, and to filter the variables containing similar information. Principal-component and correlation analyses showed that porosity is related to other measured variables and that permeability is most related to porosity and grain size. Four principal components are found to be significant in explaining the variance of data. Stepwise multiple-regression analysis was used to see how well the measured variables could predict porosity and (or) permeability for this suite of rocks. The variation in permeability and porosity is not totally predicted by the other variables, but the regression is significant at the 5% significance level. ?? 1993.
NASA Astrophysics Data System (ADS)
Pang, Guofei; Perdikaris, Paris; Cai, Wei; Karniadakis, George Em
2017-11-01
The fractional advection-dispersion equation (FADE) can describe accurately the solute transport in groundwater but its fractional order has to be determined a priori. Here, we employ multi-fidelity Bayesian optimization to obtain the fractional order under various conditions, and we obtain more accurate results compared to previously published data. Moreover, the present method is very efficient as we use different levels of resolution to construct a stochastic surrogate model and quantify its uncertainty. We consider two different problem set ups. In the first set up, we obtain variable fractional orders of one-dimensional FADE, considering both synthetic and field data. In the second set up, we identify constant fractional orders of two-dimensional FADE using synthetic data. We employ multi-resolution simulations using two-level and three-level Gaussian process regression models to construct the surrogates.
Blake, Khandis R; Dixson, Barnaby J W; O'Dean, Siobhan M; Denson, Thomas F
2017-04-01
Several studies report that wearing red clothing enhances women's attractiveness and signals sexual proceptivity to men. The associated hypothesis that women will choose to wear red clothing when fertility is highest, however, has received mixed support from empirical studies. One possible cause of these mixed findings may be methodological. The current study aimed to replicate recent findings suggesting a positive association between hormonal profiles associated with high fertility (high estradiol to progesterone ratios) and the likelihood of wearing red. We compared the effect of the estradiol to progesterone ratio on the probability of wearing: red versus non-red (binary logistic regression); red versus neutral, black, blue, green, orange, multi-color, and gray (multinomial logistic regression); and each of these same colors in separate binary models (e.g., green versus non-green). Red versus non-red analyses showed a positive trend between a high estradiol to progesterone ratio and wearing red, but the effect only arose for younger women and was not robust across samples. We found no compelling evidence for ovarian hormones increasing the probability of wearing red in the other analyses. However, we did find that the probability of wearing neutral was positively associated with the estradiol to progesterone ratio, though the effect did not reach conventional levels of statistical significance. Findings suggest that although ovarian hormones may affect younger women's preference for red clothing under some conditions, the effect is not robust when differentiating amongst other colors of clothing. In addition, the effect of ovarian hormones on clothing color preference may not be specific to the color red. Copyright © 2017 Elsevier Inc. All rights reserved.
Scheel, Jennifer; Reber, Sandra; Stoessel, Lisa; Waldmann, Elisabeth; Jank, Sabine; Eckardt, Kai-Uwe; Grundmann, Franziska; Vitinius, Frank; de Zwaan, Martina; Bertram, Anna; Erim, Yesim
2017-03-29
Different measures of non-adherence to immunosuppressant (IS) medication have been found to be associated with rejection episodes after successful transplantation. The aim of the current study was to investigate whether graft rejection after renal transplantation is associated with patient-reported IS medication non-adherence and IS trough level variables (IS trough level variability and percentage of sub-therapeutic IS trough levels). Patient-reported non-adherence, IS trough level variability, percentage of sub-therapeutic IS trough levels, and acute biopsy-proven late allograft rejections were assessed in 267 adult renal transplant recipients who were ≥12 months post-transplantation. The rate of rejection was 13.5%. IS trough level variability, percentage of sub-therapeutic IS trough levels as well as patient-reported non-adherence were all significantly and positively associated with rejection, but not with each other. Logistic regression analyses revealed that only the percentage of sub-therapeutic IS trough levels and age at transplantation remained significantly associated with rejection. Particularly, the percentage of sub-therapeutic IS trough levels is associated with acute rejections after kidney transplantation whereas IS trough level variability and patient-reported non-adherence seem to be of subordinate importance. Patient-reported non-adherence and IS trough level variables were not correlated; thus, non-adherence should always be measured in a multi-methodological approach. Further research concerning the best combination of non-adherence measures is needed.
Barriers to Uptake of Conservation Agriculture in southern Africa: Multi-level Analyses from Malawi
NASA Astrophysics Data System (ADS)
Dougill, Andrew; Stringer, Lindsay; Whitfield, Stephen; Wood, Ben; Chinseu, Edna
2015-04-01
Conservation agriculture is a key set of actions within the growing body of climate-smart agriculture activities being advocated and rolled out across much of the developing world. Conservation agriculture has purported benefits for environmental quality, food security and the sustained delivery of ecosystem services. In this paper, new multi-level analyses are presented, assessing the current barriers to adoption of conservation agriculture practices in Malawi. Despite significant donor initiatives that have targeted conservation agriculture projects, uptake rates remain low. This paper synthesises studies from across 3 levels in Malawi: i.) national level- drawing on policy analysis, interviews and a multi-stakeholder workshop; ii.) district level - via assessments of development plans and District Office and extension service support, and; iii) local level - through data gained during community / household level studies in Dedza District that have gained significant donor support for conservation agriculture as a component of climate smart agriculture initiatives. The national level multi-stakeholder Conservation Agriculture workshop identified three areas requiring collaborative research and outlined routes for the empowerment of the National Conservation Agriculture Task Force to advance uptake of conservation agriculture and deliver associated benefits in terms of agricultural development, climate adaptation and mitigation. District level analyses highlight that whilst District Development Plans are now checked against climate change adaptation and mitigation criteria, capacity and knowledge limitations exist at the District level, preventing project interventions from being successfully up-scaled. Community level assessments highlight the need for increased community participation at the project-design phase and identify a pressing requirement for conservation agriculture planning processes (in particular those driven by investments in climate-smart agriculture) to better accommodate, and respond to, the differentiated needs of marginalised groups (e.g. poor, elderly, carers). We identify good practices that can be used to design, plan and implement conservation agriculture projects such that the multiple benefits can be realised. We further outline changes to multi-level policy and institutional arrangements to facilitate greater adoption of conservation agriculture in Malawi, noting the vital importance of District-level institutions and amendments and capacity building required within agricultural extension services. We highlight the need for capacity building and support to ensure conservation agriculture's multiple benefits are realised more widely as a route towards sustainable land management.
Hoert, Jennifer; Herd, Ann M; Hambrick, Marion
2018-05-01
The purpose of the study was to explore the relationship between leadership support for health promotion and job stress, wellness program participation, and health behaviors. A cross-sectional survey design was used. Four worksites with a range of wellness programs were selected for this study. Participants in this study were employees (n = 618) at 4 organizations (bank, private university, wholesale supplier, and public university) in the southeastern United States, each offering an employee wellness program. Response rates in each organization ranged from 3% to 34%. Leadership support for health promotion was measured with the Leading by Example instrument. Employee participation in wellness activities, job stress, and health behaviors were measured with multi-item scales. Correlation/regression analysis and descriptive statistics were used to analyze the relationships among the scaled variables. Employees reporting higher levels of leadership support for health promotion also reported higher levels of wellness activity participation, lower job stress, and greater levels of health behavior ( P = .001). To ascertain the amount of variance in health behaviors accounted for by the other variables in the study, a hierarchical regression analysis revealed a statistically significant model (model F 7,523 = 27.28; P = .001), with leadership support for health promotion (β = .19, t = 4.39, P = .001), wellness activity participation (β = .28, t = 6.95, P < .001), and job stress (β = -.27, t = -6.75, P ≤ .001) found to be significant predictors of health behaviors in the model. Exploratory regression analyses by organization revealed the focal variables as significant model predictors for only the 2 larger organizations with well-established wellness programs. Results from the study suggest that employees' perceptions of organizational leadership support for health promotion are related to their participation in wellness activities, perceived job stress levels, and health behaviors.
Gropp, Kathleen M; Pickett, William; Janssen, Ian
2012-10-16
Active transportation to school is a method by which youth can build physical activity into their daily routines. We examined correlates of active transportation to school at both individual- (characteristics of the individual and family) and area- (school and neighborhood) levels amongst youth living within 1 mile (1.6 km) of their school. Using the 2009/10 Canadian Health Behaviour in School-Aged Children (HBSC) survey, we selected records of students (n = 3 997) from 161 schools that resided in an urban setting and lived within 1 mile from their school. Student records were compiled from: (1) individual-level HBSC student questionnaires; (2) area-level administrator (school) questionnaires; and (3) area-level geographic information system data sources. The outcome, active transportation to school, was determined via a questionnaire item describing the method of transportation that individual students normally use to get to school. Analyses focused on factors at multiple levels that potentially contribute to student decisions to engage in active transportation. Multi-level logistic regression analyses were employed. Approximately 18% of the variance in active transportation was accounted for at the area-level. Several individual and family characteristics were associated with engagement in active transportation to school including female gender (RR vs. males = 0.86, 95% CI: 0.80-0.91), having ≥2 cars in the household (RR vs. no cars = 0.87, 0.74-0.97), and family socioeconomic status (RR for 'not well off' vs. 'very well off' = 1.14, 1.01-1.26). Neighborhood characteristics most strongly related to active transportation were: the length of roads in the 1 km buffer (RR in quartile 4 vs. quartile 1 = 1.23, 1.00-1.42), the amount of litter in the neighborhood (RR for 'major problem' vs. 'no problem' = 1.47, 1.16-1.57), and relatively hot climates (RR in quartile 4 vs. quartile 1 = 1.33 CI, 1.05-1.53). Engagement in active transportation to school was related to multiple factors at multiple levels. We identified gender, perception of residential neighborhood safety, the percentage of streets with sidewalks, and the total length of roads as the most important correlates of active transportation to school.
2012-01-01
Background Active transportation to school is a method by which youth can build physical activity into their daily routines. We examined correlates of active transportation to school at both individual- (characteristics of the individual and family) and area- (school and neighborhood) levels amongst youth living within 1 mile (1.6 km) of their school. Methods Using the 2009/10 Canadian Health Behaviour in School-Aged Children (HBSC) survey, we selected records of students (n = 3 997) from 161 schools that resided in an urban setting and lived within 1 mile from their school. Student records were compiled from: (1) individual-level HBSC student questionnaires; (2) area-level administrator (school) questionnaires; and (3) area-level geographic information system data sources. The outcome, active transportation to school, was determined via a questionnaire item describing the method of transportation that individual students normally use to get to school. Analyses focused on factors at multiple levels that potentially contribute to student decisions to engage in active transportation. Multi-level logistic regression analyses were employed. Results Approximately 18% of the variance in active transportation was accounted for at the area-level. Several individual and family characteristics were associated with engagement in active transportation to school including female gender (RR vs. males = 0.86, 95% CI: 0.80-0.91), having ≥2 cars in the household (RR vs. no cars = 0.87, 0.74-0.97), and family socioeconomic status (RR for ‘not well off’ vs. ‘very well off’ = 1.14, 1.01-1.26). Neighborhood characteristics most strongly related to active transportation were: the length of roads in the 1 km buffer (RR in quartile 4 vs. quartile 1 = 1.23, 1.00-1.42), the amount of litter in the neighborhood (RR for ‘major problem’ vs. ‘no problem’ = 1.47, 1.16-1.57), and relatively hot climates (RR in quartile 4 vs. quartile 1 = 1.33 CI, 1.05-1.53). Conclusion Engagement in active transportation to school was related to multiple factors at multiple levels. We identified gender, perception of residential neighborhood safety, the percentage of streets with sidewalks, and the total length of roads as the most important correlates of active transportation to school. PMID:23067247
Berardi, Cecilia; Larson, Nicholas B.; Decker, Paul A.; Wassel, Christina L.; Kirsch, Phillip S.; Pankow, James S.; Sale, Michele M.; de Andrade, Mariza; Sicotte, Hugues; Tang, Weihong; Hanson, Naomi Q.; Tsai, Michael Y.; da Chen, Yii-Der I; Bielinski, Suzette J.
2015-01-01
L-selectin is constitutively expressed on leukocytes and mediates their interaction with endothelial cells during inflammation. Previous studies on the association of soluble L-selectin (sL-selectin) with cardiovascular disease (CVD) are inconsistent. Genetic variants associated with sL-selectin levels may be a better surrogate of levels over a lifetime. We explored the association of genetic variants and sL-selectin levels in a race/ethnicity stratified random sample of 2,403 participants in the Multi-Ethnic Study of Atherosclerosis (MESA). Through a genome-wide analysis with additive linear regression models, we found that rs12938 on the SELL gene accounted for a significant portion of the protein level variance across all four races/ethnicities. To evaluate potential additional associations, elastic net models were used for variants located in the SELL/SELP/SELE genetic region and an additional two SNPs, rs3917768 and rs4987361, were associated with sL-selectin levels in African Americans. These variants accounted for a portion of protein variance that ranged from 4% in Hispanic to 14% in African Americans. To investigate the relationship of these variants with CVD, 6,317 subjects were used. No significant association was found between any of the identified SNPs and carotid intima-media thickness or presence of carotid plaque using linear and logistic regression, respectively. Similarly no significant results were found for coronary artery calcium or coronary heart disease events. In conclusion, we found that variants within the SELL gene are associated with sL-selectin levels. Despite accounting for a significant portion of the protein level variance, none of the variants was associated with clinical or subclinical CVD. PMID:25576479
Advanced development of atmospheric models. [SEASAT Program support
NASA Technical Reports Server (NTRS)
Kesel, P. G.; Langland, R. A.; Stephens, P. L.; Welleck, R. E.; Wolff, P. M.
1979-01-01
A set of atmospheric analysis and prediction models was developed in support of the SEASAT Program existing objective analysis models which utilize a 125x125 polar stereographic grid of the Northern Hemisphere, which were modified in order to incorporate and assess the impact of (real or simulated) satellite data in the analysis of a two-day meteorological scenario in January 1979. Program/procedural changes included: (1) a provision to utilize winds in the sea level pressure and multi-level height analyses (1000-100 MBS); (2) The capability to perform a pre-analysis at two control levels (1000 MBS and 250 MBS); (3) a greater degree of wind- and mass-field coupling, especially at these controls levels; (4) an improved facility to bogus the analyses based on results of the preanalysis; and (5) a provision to utilize (SIRS) satellite thickness values and cloud motion vectors in the multi-level height analysis.
Intini, Paolo; Berloco, Nicola; Colonna, Pasquale; Ranieri, Vittorio; Ryeng, Eirin
2018-02-01
Previous research has suggested that drivers' route familiarity/unfamiliarity (using different definitions of familiarity), and the interactions between familiar and unfamiliar drivers, may affect both the driving performances and the likelihood of road crashes. The purpose of this study is to provide a contribution in the search for relationships between familiarity and crashes by: 1) introducing a measure of familiarity based on the distance from residence; 2) analyzing a traffic and accident dataset referred to rural two-lane sections of the Norwegian highways E6 and E39; 3) using a multi-level approach, based on different perspectives, from a macro analysis to more detailed levels. In the macro analyses, the accident rates computed for different seasons and for different summer traffic variation rates (used as indicators of the share of familiar drivers in the flow) were performed. At the second level, a logistic regression model was used to explain the familiarity/unfamiliarity of drivers (based on their distance from residence), through variables retrieved from the database. In the last step, an in-depth analysis considering also accident types and dynamics was conducted. In the macro analysis, no differences were found between accident rates in the different conditions. Whereas, as emerged from the detailed analyses, the factors: high traffic volume, low summer traffic variation, autumn/winter, minor intersections/driveways, speed limits <80 km/h, travel purposes (commuting/not working) are associated to higher odds of having familiar drivers involved in crashes; while the factors: high traffic volume, high summer traffic variation, summer, head on/rear end-angle crashes, heavy vehicles involved, travel purposes (not commuting), young drivers involved are associated to higher odds of finding unfamiliar drivers involved. To a minor extent, some indications arise from the in-depth analyses about crash types and dynamics, especially for familiar drivers. With regard to the definitions used in this article, the familiarity was confirmed as an influential factor on the accident risk, possibly due to distraction and dangerous behaviors, while the influence of being unfamiliar on the accident proneness has some unclarified aspects. However, crashes to unfamiliar drivers may cluster at sites showing high summer traffic variation and in summer months. Copyright © 2017 Elsevier Ltd. All rights reserved.
Karami, K; Zerehdaran, S; Barzanooni, B; Lotfi, E
2017-12-01
1. The aim of the present study was to estimate genetic parameters for average egg weight (EW) and egg number (EN) at different ages in Japanese quail using multi-trait random regression (MTRR) models. 2. A total of 8534 records from 900 quail, hatched between 2014 and 2015, were used in the study. Average weekly egg weights and egg numbers were measured from second until sixth week of egg production. 3. Nine random regression models were compared to identify the best order of the Legendre polynomials (LP). The most optimal model was identified by the Bayesian Information Criterion. A model with second order of LP for fixed effects, second order of LP for additive genetic effects and third order of LP for permanent environmental effects (MTRR23) was found to be the best. 4. According to the MTRR23 model, direct heritability for EW increased from 0.26 in the second week to 0.53 in the sixth week of egg production, whereas the ratio of permanent environment to phenotypic variance decreased from 0.48 to 0.1. Direct heritability for EN was low, whereas the ratio of permanent environment to phenotypic variance decreased from 0.57 to 0.15 during the production period. 5. For each trait, estimated genetic correlations among weeks of egg production were high (from 0.85 to 0.98). Genetic correlations between EW and EN were low and negative for the first two weeks, but they were low and positive for the rest of the egg production period. 6. In conclusion, random regression models can be used effectively for analysing egg production traits in Japanese quail. Response to selection for increased egg weight would be higher at older ages because of its higher heritability and such a breeding program would have no negative genetic impact on egg production.
Jacob, Benjamin J; Krapp, Fiorella; Ponce, Mario; Gottuzzo, Eduardo; Griffith, Daniel A; Novak, Robert J
2010-05-01
Spatial autocorrelation is problematic for classical hierarchical cluster detection tests commonly used in multi-drug resistant tuberculosis (MDR-TB) analyses as considerable random error can occur. Therefore, when MDRTB clusters are spatially autocorrelated the assumption that the clusters are independently random is invalid. In this research, a product moment correlation coefficient (i.e., the Moran's coefficient) was used to quantify local spatial variation in multiple clinical and environmental predictor variables sampled in San Juan de Lurigancho, Lima, Peru. Initially, QuickBird 0.61 m data, encompassing visible bands and the near infra-red bands, were selected to synthesize images of land cover attributes of the study site. Data of residential addresses of individual patients with smear-positive MDR-TB were geocoded, prevalence rates calculated and then digitally overlaid onto the satellite data within a 2 km buffer of 31 georeferenced health centers, using a 10 m2 grid-based algorithm. Geographical information system (GIS)-gridded measurements of each health center were generated based on preliminary base maps of the georeferenced data aggregated to block groups and census tracts within each buffered area. A three-dimensional model of the study site was constructed based on a digital elevation model (DEM) to determine terrain covariates associated with the sampled MDR-TB covariates. Pearson's correlation was used to evaluate the linear relationship between the DEM and the sampled MDR-TB data. A SAS/GIS(R) module was then used to calculate univariate statistics and to perform linear and non-linear regression analyses using the sampled predictor variables. The estimates generated from a global autocorrelation analyses were then spatially decomposed into empirical orthogonal bases using a negative binomial regression with a non-homogeneous mean. Results of the DEM analyses indicated a statistically non-significant, linear relationship between georeferenced health centers and the sampled covariate elevation. The data exhibited positive spatial autocorrelation and the decomposition of Moran's coefficient into uncorrelated, orthogonal map pattern components revealed global spatial heterogeneities necessary to capture latent autocorrelation in the MDR-TB model. It was thus shown that Poisson regression analyses and spatial eigenvector mapping can elucidate the mechanics of MDR-TB transmission by prioritizing clinical and environmental-sampled predictor variables for identifying high risk populations.
Health, policy and geography: insights from a multi-level modelling approach.
Castelli, Adriana; Jacobs, Rowena; Goddard, Maria; Smith, Peter C
2013-09-01
Improving the health and wellbeing of citizens ranks highly on the agenda of most governments. Policy action to enhance health and wellbeing can be targeted at a range of geographical levels and in England the focus has tended to shift away from the national level to smaller areas, such as communities and neighbourhoods. Our focus is to identify the potential for targeting policy interventions at the most appropriate geographical levels in order to enhance health and wellbeing. The rationale is that where variations in health and wellbeing indicators are larger, there may be greater potential for policy intervention targeted at that geographical level to have an impact on the outcomes of interest, compared with a strategy of targeting policy at those levels where relative variations are smaller. We use a multi-level regression approach to identify the degree of variation that exists in a set of health indicators at each level, taking account of the geographical hierarchical organisation of public sector organisations. We find that for each indicator, the proportion of total residual variance is greatest at smaller geographical areas. We also explore the variations in health indicators within a hierarchical level, but across the geographical areas for which public sector organisations are responsible. We show that it is feasible to identify a sub-set of organisations for which unexplained variation in health indicators is significantly greater relative to their counterparts. We demonstrate that adopting a geographical perspective to analyse the variation in indicators of health at different levels offers a potentially powerful analytical tool to signal where public sector organisations, faced increasingly with many competing demands, should target their policy efforts. This is relevant not only to the English context but also to other countries where responsibilities for health and wellbeing are being devolved to localities and communities. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.
Kelly, Ronald R; Gaustad, Martha G
2007-01-01
This study of deaf college students examined specific relationships between their mathematics performance and their assessed skills in reading, language, and English morphology. Simple regression analyses showed that deaf college students' language proficiency scores, reading grade level, and morphological knowledge regarding word segmentation and meaning were all significantly correlated with both the ACT Mathematics Subtest and National Technical Institute for the Deaf (NTID) Mathematics Placement Test scores. Multiple regression analyses identified the best combination from among these potential independent predictors of students' performance on both the ACT and NTID mathematics tests. Additionally, the participating deaf students' grades in their college mathematics courses were significantly and positively associated with their reading grade level and their knowledge of morphological components of words.
NASA Astrophysics Data System (ADS)
Panigrahi, Suraj Kumar; Mishra, Ashok Kumar
2018-02-01
White light excitation fluorescence (WLEF) is known to possess analytical advantage in terms of enhanced sensitivity and facile capture of the entire fluorescence spectral signature of multi component fluorescence systems. Using the zero order diffraction of the grating monochromator on the excitation side of a commercial spectrofluorimeter, it has been shown that WLEF spectral measurements can be conveniently carried out. Taking analyte multi-fluorophoric systems like (i) drugs and vitamins spiked in urine sample, (ii) adulteration of extra virgin olive oil with olive pomace oil and (iii) mixture of fabric dyes, it was observed that there is a significant enhancement of measurement sensitivity. The total fluorescence spectral response could be conveniently analysed using PLS2 regression. This work brings out the ease of the use of a conventional fluorimeter for WLEF measurements.
Biondi-Zoccai, Giuseppe; Mastrangeli, Simona; Romagnoli, Enrico; Peruzzi, Mariangela; Frati, Giacomo; Roever, Leonardo; Giordano, Arturo
2018-01-17
Atherosclerosis has major morbidity and mortality implications globally. While it has often been considered an irreversible degenerative process, recent evidence provides compelling proof that atherosclerosis can be reversed. Plaque regression is however difficult to appraise and quantify, with competing diagnostic methods available. Given the potential of evidence synthesis to provide clinical guidance, we aimed to review recent meta-analyses on diagnostic methods for atherosclerotic plaque regression. We identified 8 meta-analyses published between 2015 and 2017, including 79 studies and 14,442 patients, followed for a median of 12 months. They reported on atherosclerotic plaque regression appraised with carotid duplex ultrasound, coronary computed tomography, carotid magnetic resonance, coronary intravascular ultrasound, and coronary optical coherence tomography. Overall, all meta-analyses showed significant atherosclerotic plaque regression with lipid-lowering therapy, with the most notable effects on echogenicity, lipid-rich necrotic core volume, wall/plaque volume, dense calcium volume, and fibrous cap thickness. Significant interactions were found with concomitant changes in low density lipoprotein cholesterol, high density lipoprotein cholesterol, and C-reactive protein levels, and with ethnicity. Atherosclerotic plaque regression and conversion to a stable phenotype is possible with intensive medical therapy and can be demonstrated in patients using a variety of non-invasive and invasive imaging modalities.
Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio
2018-01-01
Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By “multi-level” we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization. PMID:29868515
Multi-Target Regression via Robust Low-Rank Learning.
Zhen, Xiantong; Yu, Mengyang; He, Xiaofei; Li, Shuo
2018-02-01
Multi-target regression has recently regained great popularity due to its capability of simultaneously learning multiple relevant regression tasks and its wide applications in data mining, computer vision and medical image analysis, while great challenges arise from jointly handling inter-target correlations and input-output relationships. In this paper, we propose Multi-layer Multi-target Regression (MMR) which enables simultaneously modeling intrinsic inter-target correlations and nonlinear input-output relationships in a general framework via robust low-rank learning. Specifically, the MMR can explicitly encode inter-target correlations in a structure matrix by matrix elastic nets (MEN); the MMR can work in conjunction with the kernel trick to effectively disentangle highly complex nonlinear input-output relationships; the MMR can be efficiently solved by a new alternating optimization algorithm with guaranteed convergence. The MMR leverages the strength of kernel methods for nonlinear feature learning and the structural advantage of multi-layer learning architectures for inter-target correlation modeling. More importantly, it offers a new multi-layer learning paradigm for multi-target regression which is endowed with high generality, flexibility and expressive ability. Extensive experimental evaluation on 18 diverse real-world datasets demonstrates that our MMR can achieve consistently high performance and outperforms representative state-of-the-art algorithms, which shows its great effectiveness and generality for multivariate prediction.
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.
Lutomski, Jennifer E; Baars, Maria A E; Boter, Han; Buurman, Bianca M; den Elzen, Wendy P J; Jansen, Aaltje P D; Kempen, Gertrudis I J M; Steunenberg, Bas; Steyerberg, Ewout W; Olde Rikkert, Marcel G M; Melis, René J F
2014-01-01
To assess the independent and combined impact of frailty, multi-morbidity, and activities of daily living (ADL) limitations on self-reported quality of life and healthcare costs in elderly people. Cross-sectional, descriptive study. Data came from The Older Persons and Informal Caregivers Minimum DataSet (TOPICS-MDS), a pooled dataset with information from 41 projects across the Netherlands from the Dutch national care for the Elderly programme. Frailty, multi-morbidity and ADL limitations, and the interactions between these domains, were used as predictors in regression analyses with quality of life and healthcare costs as outcome measures. Analyses were stratified by living situation (independent or care home). Directionality and magnitude of associations were assessed using linear mixed models. A total of 11,093 elderly people were interviewed. A substantial proportion of elderly people living independently reported frailty, multi-morbidity, and/or ADL limitations (56.4%, 88.3% and 41.4%, respectively), as did elderly people living in a care home (88.7%, 89.2% and 77,3%, respectively). One-third of elderly people living at home (31.9%) reported all three conditions compared with two-thirds of elderly people living in a care home (68.3%). In the multivariable analysis, frailty had a strong impact on outcomes independently of multi-morbidity and ADL limitations. Elderly people experiencing problems across all three domains reported the poorest quality-of-life scores and the highest healthcare costs, irrespective of their living situation. Frailty, multi-morbidity and ADL limitations are complementary measurements, which together provide a more holistic understanding of health status in elderly people. A multi-dimensional approach is important in mapping the complex relationships between these measurements on the one hand and the quality of life and healthcare costs on the other.
Gulla, Christine; Selbaek, Geir; Flo, Elisabeth; Kjome, Reidun; Kirkevold, Øyvind; Husebo, Bettina S
2016-06-01
Neuropsychiatric symptoms, such as affective symptoms, psychosis, agitation, and apathy are common among nursing home patients with and without dementia. Treatment with one or more psychotropic drug is often without explicit clinical indication, despite low treatment efficacy, and potential side effects. We aim to investigate the multi-psychotropic drug use to identify factors and patient characteristics associated with multi-use. We analysed three cohorts from 129 Norwegian nursing homes, collected between 2004 and 2011. Patients (N = 4739) were assessed with the Neuropsychiatric Inventory - Nursing Home version (NPI-NH), Clinical Dementia Rating scale, and Physical Self Maintenance Scale. We used ordinal logistic regression to analyse associations between psychotropics (antidepressants, antipsychotics, anxiolytics, hypnotics, and anti-dementia drugs), patient characteristics, and neuropsychiatric symptoms. Patients used on average 6.6 drugs; 27 % used no psychotropics, 32 % one, and 41 % multiple psychotropic drugs (24 % two, 17 % ≥3). Thirty-nine percent were prescribed antidepressants, 30 % sedatives, 24 % anxiolytics, and 20 % antipsychotics. The total NPI-NH score was associated with multi-use (OR 1.02, 95 % CI 1.02-1.03), and increased from a mean of 13.5 (SD 16.3) for patients using none, to 25.5 (21.8) for patients using ≥3 psychotropics. Affective symptoms (depression and anxiety) were most strongly associated with multi-psychotropic drug use (OR 1.10, 95 % CI: 1.09-1.12). Female gender, independency in daily living, younger age, dementia, and many regular drugs were also associated with multi-use. Forty-one percent were exposed to multi-psychotropic drug prescriptions. Contrary to current evidence and guidelines, there is an extensive use of multiple psychotropic drugs in patients with severe NPS and dementia.
Monsalve, Irene F.; Pérez, Alejandro; Molinaro, Nicola
2014-01-01
During language comprehension, semantic contextual information is used to generate expectations about upcoming items. This has been commonly studied through the N400 event-related potential (ERP), as a measure of facilitated lexical retrieval. However, the associative relationships in multi-word expressions (MWE) may enable the generation of a categorical expectation, leading to lexical retrieval before target word onset. Processing of the target word would thus reflect a target-identification mechanism, possibly indexed by a P3 ERP component. However, given their time overlap (200–500 ms post-stimulus onset), differentiating between N400/P3 ERP responses (averaged over multiple linguistically variable trials) is problematic. In the present study, we analyzed EEG data from a previous experiment, which compared ERP responses to highly expected words that were placed either in a MWE or a regular non-fixed compositional context, and to low predictability controls. We focused on oscillatory dynamics and regression analyses, in order to dissociate between the two contexts by modeling the electrophysiological response as a function of item-level parameters. A significant interaction between word position and condition was found in the regression model for power in a theta range (~7–9 Hz), providing evidence for the presence of qualitative differences between conditions. Power levels within this band were lower for MWE than compositional contexts when the target word appeared later on in the sentence, confirming that in the former lexical retrieval would have taken place before word onset. On the other hand, gamma-power (~50–70 Hz) was also modulated by predictability of the item in all conditions, which is interpreted as an index of a similar “matching” sub-step for both types of contexts, binding an expected representation and the external input. PMID:25161630
NASA Astrophysics Data System (ADS)
Linard, J.; Leib, K.; Colorado Water Science Center
2010-12-01
Elevated levels of salinity and dissolved selenium can detrimentally effect the quality of water where anthropogenic and natural uses are concerned. In areas, such as the lower Gunnison Basin of western Colorado, salinity and selenium are such a concern that control projects are implemented to limit their mobilization. To prioritize the locations in which control projects are implemented, multi-parameter regression models were developed to identify subbasins in the lower Gunnison River Basin that were most likely to have elevated salinity and dissolved selenium levels. The drainage area is about 5,900 mi2 and is underlain by Cretaceous marine shale, which is the most common source of salinity and dissolved selenium. To characterize the complex hydrologic and chemical processes governing constituent mobilization, geospatial variables representing 70 different environmental characteristics were correlated to mean seasonal (irrigation and nonirrigation seasons) salinity and selenium yields estimated at 154 sampling sites. The variables generally represented characteristics of the physical basin, precipitation, soil, geology, land use, and irrigation water delivery systems. Irrigation and nonirrigation seasons were selected due to documented effects of irrigation on constituent mobilization. Following a stepwise approach, combinations of the geospatial variables were used to develop four multi-parameter regression models. These models predicted salinity and selenium yield, within a 95 percent confidence range, at individual points in the Lower Gunnison Basin for irrigation and non-irrigation seasons. The corresponding subbasins were ranked according to their potential to yield salinity and selenium and rankings were used to prioritize areas that would most benefit from control projects.
Mujahid, Mahasin S; Diez Roux, Ana V; Cooper, Richard C; Shea, Steven; Williams, David R
2011-02-01
The reasons for racial/ethnic disparities in hypertension (HTN) prevalence in the United States are poorly understood. Using data from the Multi-Ethnic Study of Atherosclerosis (MESA), we investigated whether individual- and neighborhood-level chronic stressors contribute to these disparities in cross-sectional analyses. The sample consisted of 2,679 MESA participants (45-84 years) residing in Baltimore, New York, and North Carolina. HTN was defined as systolic or diastolic blood pressure ≥140 or 90 mm Hg, or taking antihypertensive medications. Individual-level chronic stress was measured by self-reported chronic burden and perceived major and everyday discrimination. A measure of neighborhood (census tract) chronic stressors (i.e., physical disorder, violence) was developed using data from a telephone survey conducted with other residents of MESA neighborhoods. Binomial regression was used to estimate associations between HTN and race/ethnicity before and after adjustment for individual and neighborhood stressors. The prevalence of HTN was 59.5% in African Americans (AAs), 43.9% in Hispanics, and 42.0% in whites. Age- and sex-adjusted relative prevalences of HTN (compared to whites) were 1.30 (95% confidence interval (CI): 1.22-1.38) for AA and 1.16 (95% CI: 1.04-1.31) for Hispanics. Adjustment for neighborhood stressors reduced these to 1.17 (95% CI: 1.11-1.22) and 1.09 (95% CI: 1.00-1.18), respectively. Additional adjustment for individual-level stressors, acculturation, income, education, and other neighborhood features only slightly reduced these associations. Neighborhood chronic stressors may contribute to race/ethnic differences in HTN prevalence in the United States.
Braun, Lindsay M; Rodríguez, Daniel A; Evenson, Kelly R; Hirsch, Jana A; Moore, Kari A; Diez Roux, Ana V
2016-05-01
We used data from 3227 older adults in the Multi-Ethnic Study of Atherosclerosis (2004-2012) to explore cross-sectional and longitudinal associations between walkability and cardiometabolic risk factors. In cross-sectional analyses, linear regression was used to estimate associations of Street Smart Walk Score® with glucose, triglycerides, HDL and LDL cholesterol, systolic and diastolic blood pressure, and waist circumference, while logistic regression was used to estimate associations with odds of metabolic syndrome. Econometric fixed effects models were used to estimate longitudinal associations of changes in walkability with changes in each risk factor among participants who moved residential locations between 2004 and 2012 (n=583). Most cross-sectional and longitudinal associations were small and statistically non-significant. We found limited evidence that higher walkability was cross-sectionally associated with lower blood pressure but that increases in walkability were associated with increases in triglycerides and blood pressure over time. Further research over longer time periods is needed to understand the potential for built environment interventions to improve cardiometabolic health. Copyright © 2016 Elsevier Ltd. All rights reserved.
Fagan, Abigail A; Wright, Emily M; Pinchevsky, Gillian M
2015-08-01
This paper examined the effects of neighborhood structural (i.e., economic disadvantage, immigrant concentration, residential stability) and social (e.g., collective efficacy, social network interactions, intolerance of drug use, legal cynicism) factors on the likelihood of any adolescent tobacco, alcohol, and marijuana use. Analyses drew upon information from the Project on Human Development in Chicago Neighborhoods (PHDCN). Data were obtained from a survey of adult residents of 79 Chicago neighborhoods, two waves of interviews with 1657 to 1664 care-givers and youth aged 8 to 16 years, and information from the 1990 U.S. Census Bureau. Hierarchical Bernoulli regression models estimated the impact of neighborhood factors on substance use controlling for individual-level demographic characteristics and psycho-social risk factors. Few neighborhood factors had statistically significant direct effects on adolescent tobacco, alcohol or marijuana use, although youth living in neighborhoods with greater levels of immigrant concentration were less likely to report any drinking. Additional theorizing and more empirical research are needed to better understand the ways in which contextual influences affect adolescent substance use and delinquency. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Wright, Emily M.; Pinchevsky, Gillian M.
2015-01-01
Background This paper examined the effects of neighborhood structural (i.e., economic disadvantage, immigrant concentration, residential stability) and social (e.g., collective efficacy, social network interactions, intolerance of drug use, legal cynicism) factors on the likelihood of any adolescent tobacco, alcohol, and marijuana use. Methods Analyses drew upon information from the Project on Human Development in Chicago Neighborhoods (PHDCN). Data were obtained from a survey of adult residents of 79 Chicago neighborhoods, two waves of interviews with 1,657 to 1,664 care-givers and youth aged 8 to 16 years, and information from the 1990 U.S. Census Bureau. Hierarchical Bernoulli regression models estimated the impact of neighborhood factors on substance use controlling for individual-level demographic characteristics and psycho-social risk factors. Results Few neighborhood factors had statistically significant direct effects on adolescent tobacco, alcohol or marijuana use, although youth living in neighborhoods with greater levels of immigrant concentration were less likely to report any drinking. Conclusion Additional theorizing and more empirical research are needed to better understand the ways in which contextual influences affect adolescent substance use and delinquency. PMID:26049206
ESTIMATING GROUND LEVEL PM 2.5 IN THE EASTERN UNITED STATES USING SATELLITE REMOTE SENSING
An empirical model based on the regression between daily average final particle (PM2.5) concentrations and aerosol optical thickness (AOT) measurements from the Multi-angle Imaging SpectroRadiometer (MISR) was developed and tested using data from the eastern United States during ...
Optimal Design for Regression Discontinuity Studies with Clustering
ERIC Educational Resources Information Center
Rhoads, Christopher; Dye, Charles
2014-01-01
Recent years have seen an increased interest in quantitative educational research studies that use random assignment (RA) to evaluate the causal impacts of educational interventions (Angrist, 2004). The multi-level structure of the public education system in the United States often leads to experimental designs where naturally occurring clusters…
Tanaka, Haruka; Ogata, Soshiro; Omura, Kayoko; Honda, Chika; Kamide, Kei; Hayakawa, Kazuo
2016-03-01
The aim of this study was to investigate the association between subjective memory complaints (SMCs) and depressive symptoms, with and without adjustment for genetic and family environmental factors. We conducted a cross-sectional study using twins and measured SMCs and depressive symptoms as outcomes and explanatory variables, respectively. First, we performed regression analyses using generalized estimating equations to investigate the associations between SMCs and depressive symptoms without adjustment for genetic and family environmental factors (individual-level analyses). We then performed regression analyses for within-pair differences using monozygotic (MZ) and dizygotic (DZ) twin pairs and MZ twin pairs to investigate these associations with adjustment for genetic and family environmental factors by subtracting the values of one twin from those of co-twin variables (within-pair level analyses). Therefore, differences between the associations at individual- and within-pair level analyses suggested confounding by genetic factors. We included 556 twins aged ≥ 20 years. In the individual-level analyses, SMCs were significantly associated with depressive symptoms in both males and females [standardized coefficients: males, 0.23 (95% CI 0.08-0.38); females, 0.35 (95% CI 0.23-0.46)]. In the within-pair level analyses using MZ and same-sex DZ twin pairs, SMCs were significantly associated with depressive symptoms. In the within-pair level analyses using the MZ twin pairs, SMCs were significantly associated with depressive symptoms [standardized coefficients: males, 0.32 (95% CI 0.08-0.56); females, 0.24 (95% CI 0.13-0.42)]. This study suggested that SMCs were significantly associated with depressive symptoms after adjustment for genetic and family environmental factors.
USDA-ARS?s Scientific Manuscript database
Multi-locus genome-wide association studies has become the state-of-the-art procedure to identify quantitative trait loci (QTL) associated with traits simultaneously. However, implementation of multi-locus model is still difficult. In this study, we integrated least angle regression with empirical B...
Investigating the relationship between iron and depression.
Mills, Natalie T; Maier, Robert; Whitfield, John B; Wright, Margaret J; Colodro-Conde, Lucia; Byrne, Enda M; Scott, James G; Byrne, Gerard J; Hansell, Narelle K; Vinkhuyzen, Anna A E; CouvyDuchesne, Baptiste; Montgomery, Grant W; Henders, Anjali K; Martin, Nicholas G; Wray, Naomi R; Benyamin, Beben
2017-11-01
Lower levels of circulating iron have been associated with depression. Our objective was to investigate the phenotypic and genetic relationship between measures of circulating levels of iron (serum iron, transferrin, transferrin saturation, and ferritin) and depressive symptoms. Data were available from ongoing studies at QIMR Berghofer Medical Research Institute (QIMRB), including twin adolescents (mean age 15.1 years, standard deviation (SD) 3.2 years), and twin adults (mean age 23.2 years, SD 2.2 years). In the adolescent cohort, there were 3416 participants from 1688 families. In the adult cohort there were 9035 participants from 4533 families. We estimated heritabilities of, and phenotypic and genetic correlations between, traits. We conducted analyses that linked results from published large-scale genome-wide association studies (including iron and Major Depressive Disorder) with our study samples using single SNP and multi-SNP genetic risk score analyses, and LD score regression analyses. In both cohorts, measures of iron, transferrin, transferrin saturation, and log 10 of ferritin (L10Fer) were all highly heritable, while depressive measures were moderately heritable. In adolescents, depression measures were higher in those in the middle 10th versus top 10th percentile of transferrin saturation measures (p = 0.002). Genetic profile risk scores of the iron measures were not significantly associated with depression in study participants. LD score analyses showed no significant genetic relationship between iron and depression. Genetic factors strongly influence iron measures in adolescents and adults. Using several different strategies we find no evidence for a genetic contribution to the relationship between blood measures of iron and measures of depression. Copyright © 2017 Elsevier Ltd. All rights reserved.
Branch, Andrea D; Barin, Burc; Rahman, Adeeb; Stock, Peter; Schiano, Thomas D
2014-02-01
An optimal vitamin D status may benefit liver transplantation (LT) patients. Higher levels of 25-hydroxyvitamin D [25(OH)D] mitigate steroid-induced bone loss after LT, correlate with better hepatitis C virus treatment responses, and increase graft survival. This study investigated 25(OH)D levels and assessed strategies for vitamin D deficiency prevention in human immunodeficiency virus (HIV)-positive patients with advanced liver disease who were enrolled in the Solid Organ Transplantation in HIV: Multi-Site Study. 25(OH)D was measured in banked specimens from 154 LT candidates/recipients with the DiaSorin assay; deficiency was defined as a 25(OH)D level < 20 ng/mL. Information about vitamin D supplement use after LT was obtained from medication logs and via surveys. Logistic regression, Cox regression, and linear repeated measures analyses were performed with SAS software. We found that none of the 17 academic medical centers in the United States routinely recommended vitamin D supplements before LT, and only a minority (4/17) recommended vitamin D supplements to all patients after LT. Seventy-one percent of the 139 patients with pre-LT values had vitamin D deficiency, which was significantly associated with cirrhosis (P = 0.01) but no other variable. The vitamin D status improved modestly after LT; however, the status was deficient for 40% of the patients 1 year after LT. In a multivariate linear repeated measures model, a higher pre-LT 25(OH)D level (P < 0.001), specimen collection in the summer (P < 0.001), a routine vitamin D supplementation strategy after LT (P < 0.001), and the time elapsing since LT (P = 0.01) were significantly associated with increases in the post-LT 25(OH)D level; black race was associated with a decreased level (P = 0.02). In conclusion, the majority of patients awaiting LT were vitamin D deficient, and approximately half were vitamin D deficient after LT. More extensive use of vitamin D supplements, more sun exposure, or both are needed to prevent this deficiency in HIV-positive LT candidates and recipients. © 2013 American Association for the Study of Liver Diseases.
Multi-scaling allometric analysis for urban and regional development
NASA Astrophysics Data System (ADS)
Chen, Yanguang
2017-01-01
The concept of allometric growth is based on scaling relations, and it has been applied to urban and regional analysis for a long time. However, most allometric analyses were devoted to the single proportional relation between two elements of a geographical system. Few researches focus on the allometric scaling of multielements. In this paper, a process of multiscaling allometric analysis is developed for the studies on spatio-temporal evolution of complex systems. By means of linear algebra, general system theory, and by analogy with the analytical hierarchy process, the concepts of allometric growth can be integrated with the ideas from fractal dimension. Thus a new methodology of geo-spatial analysis and the related theoretical models emerge. Based on the least squares regression and matrix operations, a simple algorithm is proposed to solve the multiscaling allometric equation. Applying the analytical method of multielement allometry to Chinese cities and regions yields satisfying results. A conclusion is reached that the multiscaling allometric analysis can be employed to make a comprehensive evaluation for the relative levels of urban and regional development, and explain spatial heterogeneity. The notion of multiscaling allometry may enrich the current theory and methodology of spatial analyses of urban and regional evolution.
Comparison of multi-subject ICA methods for analysis of fMRI data
Erhardt, Erik Barry; Rachakonda, Srinivas; Bedrick, Edward; Allen, Elena; Adali, Tülay; Calhoun, Vince D.
2010-01-01
Spatial independent component analysis (ICA) applied to functional magnetic resonance imaging (fMRI) data identifies functionally connected networks by estimating spatially independent patterns from their linearly mixed fMRI signals. Several multi-subject ICA approaches estimating subject-specific time courses (TCs) and spatial maps (SMs) have been developed, however there has not yet been a full comparison of the implications of their use. Here, we provide extensive comparisons of four multi-subject ICA approaches in combination with data reduction methods for simulated and fMRI task data. For multi-subject ICA, the data first undergo reduction at the subject and group levels using principal component analysis (PCA). Comparisons of subject-specific, spatial concatenation, and group data mean subject-level reduction strategies using PCA and probabilistic PCA (PPCA) show that computationally intensive PPCA is equivalent to PCA, and that subject-specific and group data mean subject-level PCA are preferred because of well-estimated TCs and SMs. Second, aggregate independent components are estimated using either noise free ICA or probabilistic ICA (PICA). Third, subject-specific SMs and TCs are estimated using back-reconstruction. We compare several direct group ICA (GICA) back-reconstruction approaches (GICA1-GICA3) and an indirect back-reconstruction approach, spatio-temporal regression (STR, or dual regression). Results show the earlier group ICA (GICA1) approximates STR, however STR has contradictory assumptions and may show mixed-component artifacts in estimated SMs. Our evidence-based recommendation is to use GICA3, introduced here, with subject-specific PCA and noise-free ICA, providing the most robust and accurate estimated SMs and TCs in addition to offering an intuitive interpretation. PMID:21162045
Are there differences in birth weight between neighbourhoods in a Nordic welfare state?
Sellström, Eva; Arnoldsson, Göran; Bremberg, Sven; Hjern, Anders
2007-01-01
Background The objective of this cohort study was to examine the effect on birth weight of living in a disadvantaged neighbourhood in a Nordic welfare state. Birth weight is a health indicator known to be sensitive to political and welfare state conditions. No former studies on urban neighbourhood differences regarding mean birth weight have been carried out in a Nordic country. Methods A register based on individual data on children's birth weight and maternal risk factors was used. A neighbourhood characteristic, i.e. an aggregated measure on income was also included. Connections between individual- and neighbourhood-level determinants and the outcome were analysed using multi-level regression technique. The study covered six hundred and ninety-six neighbourhoods in the three major cities of Sweden, Stockholm, Göteborg and Malmö, during 1992–2001. The majority of neighbourhoods had a population of 4 000–10 000 inhabitants. An average of 500 births per neighbourhood were analysed in this study. Results Differences in mean birth weight in Swedish urban neighbourhoods were minor. However, gestational length, parity and maternal smoking acted as modifiers of the neighbourhood effects. Most of the observed variation in mean birth weight was explained by individual risk factors. Conclusion Welfare institutions and benefits in Sweden might buffer against negative infant outcomes due to adverse structural organisation of urban neighbourhoods. PMID:17897453
Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh
2017-09-01
Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale. Copyright © 2017 Elsevier Ltd. All rights reserved.
Multi-variant study of obesity risk genes in African Americans: The Jackson Heart Study.
Liu, Shijian; Wilson, James G; Jiang, Fan; Griswold, Michael; Correa, Adolfo; Mei, Hao
2016-11-30
Genome-wide association study (GWAS) has been successful in identifying obesity risk genes by single-variant association analysis. For this study, we designed steps of analysis strategy and aimed to identify multi-variant effects on obesity risk among candidate genes. Our analyses were focused on 2137 African American participants with body mass index measured in the Jackson Heart Study and 657 common single nucleotide polymorphisms (SNPs) genotyped at 8 GWAS-identified obesity risk genes. Single-variant association test showed that no SNPs reached significance after multiple testing adjustment. The following gene-gene interaction analysis, which was focused on SNPs with unadjusted p-value<0.10, identified 6 significant multi-variant associations. Logistic regression showed that SNPs in these associations did not have significant linear interactions; examination of genetic risk score evidenced that 4 multi-variant associations had significant additive effects of risk SNPs; and haplotype association test presented that all multi-variant associations contained one or several combinations of particular alleles or haplotypes, associated with increased obesity risk. Our study evidenced that obesity risk genes generated multi-variant effects, which can be additive or non-linear interactions, and multi-variant study is an important supplement to existing GWAS for understanding genetic effects of obesity risk genes. Copyright © 2016 Elsevier B.V. All rights reserved.
Andrews, Jeannette O; Mueller, Martina; Dooley, Mary; Newman, Susan D; Magwood, Gayenell S; Tingen, Martha S
2016-09-01
To evaluate the effectiveness of a community based participatory research (CBPR) developed, multi-level smoking cessation intervention among women in subsidized housing neighborhoods in the Southeastern US. A total of n=409 women in 14 subsidized housing neighborhoods in Georgia and South Carolina participated in this group randomized controlled trial conducted from 2009 to 2013. Intervention neighborhoods received a 24-week intervention with 1:1 community health worker contact, behavioral peer group sessions, and nicotine replacement. Control neighborhoods received written cessation materials at weeks 1, 6, 12, 18. Random coefficient models were used to compare smoking abstinence outcomes at 6 and 12months. Significance was set a p<0.05. The majority of participants (91.2%) were retained during the 12-month intervention period. Smoking abstinence rates at 12months for intervention vs. control were 9% vs. 4.3%, p=0.05. Additional analyses accounting for passive smoke exposure in these multi-unit housing settings demonstrated 12month abstinence rates of 12% vs. 5.3%, p=0.016. However, in the multivariate regression analyses, there was no significant effect of the intervention on the odds of being a non-smoker (OR=0.44, 95% CI: 0.18-1.07). Intervention participants who kept coach visits, attended group sessions, and used patches were more likely to remain abstinent. This CBPR developed intervention showed potential to engage smokers and reduce smoking among women in these high-poverty neighborhoods. Effectiveness in promoting cessation in communities burdened with fiscal, environmental and social inequities remains a public health priority. Copyright © 2016 Elsevier Inc. All rights reserved.
Preventing youth access to alcohol: outcomes from a multi-community time-series trial*.
Wagenaar, Alexander C; Toomey, Traci L; Erickson, Darin J
2005-03-01
AIMS/INTERVENTION: The Complying with the Minimum Drinking Age project (CMDA) is a community trial designed to test effects of two interventions designed to reduce alcohol sales to minors: (1) training for management of retail alcohol establishments and (2) enforcement checks of alcohol establishments. CMDA is a multi-community time-series quasi-experimental trial with a nested cohort design. CMDA was implemented in 20 cities in four geographic areas in the US Midwest. The core outcome, propensity for alcohol sales to minors, was directly tested with research staff who attempted to purchase alcohol without showing age identification using a standardized protocol in 602 on-premise and 340 off-premise alcohol establishments. Data were collected every other week in all communities over 4 years. Mixed-model regression and Box-Jenkins time-series analyses were used to assess short- and long-term establishment-specific and general community-level effects of the two interventions. Effects of the training intervention were mixed. Specific deterrent effects were observed for enforcement checks, with an immediate 17% reduction in likelihood of sales to minors. These effects decayed entirely within 3 months in off-premise establishments and to an 8.2% reduction in on-premise establishments. Enforcement checks prevent alcohol sales to minors. At the intensity levels tested, enforcement primarily affected specific establishments checked, with limited diffusion to the whole community. Finally, most of the enforcement effect decayed within 3 months, suggesting that a regular schedule of enforcement is necessary to maintain deterrence.
Brismée, J M; Yang, S; Lambert, M E; Chyu, M C; Tsai, P; Zhang, Y; Han, J; Hudson, C; Chung, Eunhee; Shen, C L
2016-04-26
Very few studies have investigated differences in musculoskeletal health due to gender in a large rural population. The aim of this study is to investigate factors affecting musculoskeletal health in terms of hand grip strength, musculoskeletal discomfort, and gait disturbance in a rural-dwelling, multi-ethnic cohort. Data for 1117 participants (40 years and older, 70% female) of an ongoing rural healthcare study, Project FRONTIER, were analyzed. Subjects with a history of neurological disease, stroke and movement disorder were excluded. Dominant hand grip strength was assessed by dynamometry. Gait disturbance including stiff, spastic, narrow-based, wide-based, unstable or shuffling gait was rated. Musculoskeletal discomfort was assessed by self-reported survey. Data were analyzed by linear, logistic regression and negative binomial regressions as appropriate. Demographic and socioeconomic factors were adjusted in the multiple variable analyses. In both genders, advanced age was a risk factor for weaker hand grip strength; arthritis was positively associated with musculoskeletal discomfort, and fair or poor health was significantly associated with increased risk of gait disturbance. Greater waist circumference was associated with greater musculoskeletal discomfort in males only. In females, advanced age is the risk factor for musculoskeletal discomfort as well as gait disturbance. Females with fair or poor health had weaker hand grip strength. Higher C-reactive protein and HbA1c levels were also positively associated with gait disturbance in females, but not in males. This cross-sectional study demonstrates how gender affects hand grip strength, musculoskeletal discomfort, and gait in a rural-dwelling multi-ethnic cohort. Our results suggest that musculoskeletal health may need to be assessed differently between males and females.
Chia, Phee-Phee; Fan, Sook-Ha; Say, Yee-How
2015-11-05
This study aimed to investigate the association of peroxisome proliferator-activated receptor (PPAR) genes PPARα L162V, PPARγ2 C161T and PPARδ T294C single nucleotide polymorphisms (SNPs) with obesity and metabolic syndrome (Met-S) in a multi-ethnic population in Kampar, Malaysia. Socio-demographic data, anthropometric and biochemical measurements (plasma lipid profile, adiponectin and interleukin-6 [IL-6] levels) were taken from 307 participants (124 males; 180 obese; 249 Met-S; 97 Malays, 85 ethnic Chinese, 55 ethnic Indians). The overall minor allele frequencies were .08, .22 and .30 for PPAR α L162V, γ C161T, δ T294C, respectively. All SNPs were not associated with obesity, Met-S and obesity with/without Met-S by χ(2) analysis, ethnicity-stratified and logistic regression analyses. Nevertheless, participants with V162 allele of PPARα had significantly higher IL-6, while those with T161 allele of PPARγ2 had significantly lower HOMA-IR. All PPAR SNPs were not associated with obesity and Met-S in the suburban population of Kampar, Malaysia, where only PPARα V162 and PPARγ2 T161 alleles were associated with plasma IL-6 and HOMA-IR, respectively.
Pomerantsev, Alexey L; Kutsenova, Alla V; Rodionova, Oxana Ye
2017-02-01
A novel non-linear regression method for modeling non-isothermal thermogravimetric data is proposed. Experiments for several heating rates are analyzed simultaneously. The method is applicable to complex multi-stage processes when the number of stages is unknown. Prior knowledge of the type of kinetics is not required. The main idea is a consequent estimation of parameters when the overall model is successively changed from one level of modeling to another. At the first level, the Avrami-Erofeev functions are used. At the second level, the Sestak-Berggren functions are employed with the goal to broaden the overall model. The method is tested using both simulated and real-world data. A comparison of the proposed method with a recently published 'model-free' deconvolution method is presented.
Hahn, Sowon; Buttaccio, Daniel R; Hahn, Jungwon; Lee, Taehun
2015-01-01
The present study demonstrates that levels of extraversion and neuroticism can predict attentional performance during a change detection task. After completing a change detection task built on the flicker paradigm, participants were assessed for personality traits using the Revised Eysenck Personality Questionnaire (EPQ-R). Multiple regression analyses revealed that higher levels of extraversion predict increased change detection accuracies, while higher levels of neuroticism predict decreased change detection accuracies. In addition, neurotic individuals exhibited decreased sensitivity A' and increased fixation dwell times. Hierarchical regression analyses further revealed that eye movement measures mediate the relationship between neuroticism and change detection accuracies. Based on the current results, we propose that neuroticism is associated with decreased attentional control over the visual field, presumably due to decreased attentional disengagement. Extraversion can predict increased attentional performance, but the effect is smaller than the relationship between neuroticism and attention.
The Oklahoma's Promise Program: A National Model to Promote College Persistence
ERIC Educational Resources Information Center
Mendoza, Pilar; Mendez, Jesse P.
2013-01-01
Using a multi-method approach involving fixed effects and logistic regressions, this study examined the effect of the Oklahoma's Promise Program on student persistence in relation to the Pell and Stafford federal programs and according to socio-economic characteristics and class level. The Oklahoma's Promise is a hybrid state program that pays…
Self-rated health and health-strengthening factors in community-living frail older people.
Ebrahimi, Zahra; Dahlin-Ivanoff, Synneve; Eklund, Kajsa; Jakobsson, Annika; Wilhelmson, Katarina
2015-04-01
The aim of this study was to analyse the explanatory power of variables measuring health-strengthening factors for self-rated health among community-living frail older people. Frailty is commonly constructed as a multi-dimensional geriatric syndrome ascribed to the multi-system deterioration of the reserve capacity in older age. Frailty in older people is associated with decreased physical and psychological well-being. However, knowledge about the experiences of health in frail older people is still limited. The design of the study was cross-sectional. The data were collected between October 2008 and November 2010 through face-to-face structured interviews with older people aged 65-96 years (N = 161). Binary logistic regression was used to analyse whether a set of explanatory relevant variables is associated with self-rated health. The results from the final model showed that satisfaction with one's ability to take care of oneself, having 10 or fewer symptoms and not feeling lonely had the best explanatory power for community-living frail older peoples' experiences of good health. The results indicate that a multi-disciplinary approach is desirable, where the focus should not only be on medical problems but also on providing supportive services to older people to maintain their independence and experiences of health despite frailty. © 2014 John Wiley & Sons Ltd.
Multi-system influences on adolescent risky sexual behavior.
Chen, Angela Chia-Chen; Thompson, Elaine Adams; Morrison-Beedy, Dianne
2010-12-01
We examined multi-system influences on risky sexual behavior measured by cumulative sexual risk index and number of nonromantic sexual partners among 4,465 single, sexually experienced adolescents. Hierarchical Poisson regression analyses were conducted with Wave I-II data from the National Longitudinal Study of Adolescent Health. Individual and family factors predicted both outcome measures. Neighborhood set predicted cumulative sexual risk index only, and peer factors predicted the number of nonromantic sexual partners only. School set did not predict either outcome. There were significant associations among risky sexual behavior, drug use, and delinquent behaviors. The results highlight the need for multifaceted prevention programs that address relevant factors related to family, peer and neighborhood influence as well as individual factors among sexually active adolescents. Copyright © 2010 Wiley Periodicals, Inc.
Tan, Kok Chooi; Lim, Hwee San; Matjafri, Mohd Zubir; Abdullah, Khiruddin
2012-06-01
Atmospheric corrections for multi-temporal optical satellite images are necessary, especially in change detection analyses, such as normalized difference vegetation index (NDVI) rationing. Abrupt change detection analysis using remote-sensing techniques requires radiometric congruity and atmospheric correction to monitor terrestrial surfaces over time. Two atmospheric correction methods were used for this study: relative radiometric normalization and the simplified method for atmospheric correction (SMAC) in the solar spectrum. A multi-temporal data set consisting of two sets of Landsat images from the period between 1991 and 2002 of Penang Island, Malaysia, was used to compare NDVI maps, which were generated using the proposed atmospheric correction methods. Land surface temperature (LST) was retrieved using ATCOR3_T in PCI Geomatica 10.1 image processing software. Linear regression analysis was utilized to analyze the relationship between NDVI and LST. This study reveals that both of the proposed atmospheric correction methods yielded high accuracy through examination of the linear correlation coefficients. To check for the accuracy of the equation obtained through linear regression analysis for every single satellite image, 20 points were randomly chosen. The results showed that the SMAC method yielded a constant value (in terms of error) to predict the NDVI value from linear regression analysis-derived equation. The errors (average) from both proposed atmospheric correction methods were less than 10%.
A successful backward step correlates with hip flexion moment of supporting limb in elderly people.
Takeuchi, Yahiko
2018-01-01
The objective of this study was to determine the positional relationship between the center of mass (COM) and the center of pressure (COP) at the time of step landing, and to examine their relationship with the joint moments exerted by the supporting limb, with regard to factors of the successful backward step response. The study population comprised 8 community-dwelling elderly people that were observed to take successive multi steps after the landing of a backward stepping. Using a motion capture system and force plate, we measured the COM, COP and COM-COP deviation distance on landing during backward stepping. In addition, we measured the moment of the supporting limb joint during backward stepping. The multi-step data were compared with data from instances when only one step was taken (single-step). Variables that differed significantly between the single- and multi-step data were used as objective variables and the joint moments of the supporting limb were used as explanatory variables in single regression analyses. The COM-COP deviation in the anteroposterior was significantly larger in the single-step. A regression analysis with COM-COP deviation as the objective variable obtained a significant regression equation in the hip flexion moment (R2 = 0.74). The hip flexion moment of supporting limb was shown to be a significant explanatory variable in both the PS and SS phases for the relationship with COM-COP distance. This study found that to create an appropriate backward step response after an external disturbance (i.e. the ability to stop after 1 step), posterior braking of the COM by a hip flexion moment are important during the single-limbed standing phase.
Multi-level functionality of social media in the aftermath of the Great East Japan Earthquake.
Jung, Joo-Young; Moro, Munehito
2014-07-01
This study examines the multi-level functionalities of social media in the aftermath of the Great East Japan Earthquake of 11 March 2011. Based on a conceptual model of multi-level story flows of social media (Jung and Moro, 2012), the study analyses the multiple functionalities that were ascribed to social media by individuals, organisations, and macro-level social systems (government and the mass media) after the earthquake. Based on survey data, a review of Twitter timelines and secondary sources, the authors derive five functionalities of social media: interpersonal communications with others (micro level); channels for local governments; organisations and local media (meso level); channels for mass media (macro level); information sharing and gathering (cross level); and direct channels between micro-/meso- and macro-level agents. The study sheds light on the future potential of social media in disaster situations and suggests how to design an effective communication network to prepare for emergency situations. © 2014 The Author(s). Disasters © Overseas Development Institute, 2014.
Multivariate decoding of brain images using ordinal regression.
Doyle, O M; Ashburner, J; Zelaya, F O; Williams, S C R; Mehta, M A; Marquand, A F
2013-11-01
Neuroimaging data are increasingly being used to predict potential outcomes or groupings, such as clinical severity, drug dose response, and transitional illness states. In these examples, the variable (target) we want to predict is ordinal in nature. Conventional classification schemes assume that the targets are nominal and hence ignore their ranked nature, whereas parametric and/or non-parametric regression models enforce a metric notion of distance between classes. Here, we propose a novel, alternative multivariate approach that overcomes these limitations - whole brain probabilistic ordinal regression using a Gaussian process framework. We applied this technique to two data sets of pharmacological neuroimaging data from healthy volunteers. The first study was designed to investigate the effect of ketamine on brain activity and its subsequent modulation with two compounds - lamotrigine and risperidone. The second study investigates the effect of scopolamine on cerebral blood flow and its modulation using donepezil. We compared ordinal regression to multi-class classification schemes and metric regression. Considering the modulation of ketamine with lamotrigine, we found that ordinal regression significantly outperformed multi-class classification and metric regression in terms of accuracy and mean absolute error. However, for risperidone ordinal regression significantly outperformed metric regression but performed similarly to multi-class classification both in terms of accuracy and mean absolute error. For the scopolamine data set, ordinal regression was found to outperform both multi-class and metric regression techniques considering the regional cerebral blood flow in the anterior cingulate cortex. Ordinal regression was thus the only method that performed well in all cases. Our results indicate the potential of an ordinal regression approach for neuroimaging data while providing a fully probabilistic framework with elegant approaches for model selection. Copyright © 2013. Published by Elsevier Inc.
Racial differences in natriuretic peptide levels: the Dallas Heart Study
Gupta, Deepak K.; de Lemos, James A.; Ayers, Colby R.; Berry, Jarett D.; Wang, Thomas J.
2015-01-01
Background Natriuretic peptides (NP) are hormones with natriuretic, diuretic, and vasodilatory effects. Experimental NP deficiency promotes salt-sensitive hypertension and cardiac hypertrophy, conditions that are more common among black individuals. We hypothesized that black individuals have lower N-terminal pro B-type natriuretic peptide (Nt-proBNP) levels than white and Hispanic individuals. Objectives To assess whether Nt-proBNP levels differ according to race/ethnicity. Methods We examined plasma Nt-proBNP levels according to race/ethnicity in 3,148 individuals (51% black, 31% white, 18% Hispanic) free of prevalent cardiovascular disease in the Dallas Heart Study. Nt-proBNP values in the bottom sex-specific quartile were defined as low. Multivariable linear and logistic regression analyses were performed adjusting for clinical covariates and MRI measurements of cardiac structure and function. Results Hypertension was present in 41%, 25%, and 16% of black, white, and Hispanic individuals, respectively. Unadjusted Nt-proBNP levels were lowest in blacks (median 24 pg/ml; IQR 10, 52) as compared with Hispanic (30 pg/ml; IQR 14, 59) and white individuals (32 pg/ml; IQR 16, 62), P < 0.0001. In multivariable-adjusted models, black individuals still had significantly lower Nt-proBNP levels (-39% [95%CI -46%, -31%]; P < 0.0001) and greater odds of having low Nt-proBNP (OR: 2.46, [95% CI 1.86, 3.26]), compared with whites. In contrast, Nt-proBNP levels did not significantly differ between Hispanic and white individuals (P = 0.28). The finding of lower Nt-proBNP levels in blacks was similar when analyses were restricted to healthy participants without cardiovascular risk factors. Conclusions In this multi-ethnic cohort, Nt-proBNP levels differ substantially according to race/ethnicity. Despite a higher prevalence of hypertension, blacks had significantly lower NP levels than white and Hispanic individuals. A relative NP “deficiency” among black individuals may lead to greater susceptibility to salt retention and hypertension. PMID:26071618
The value of urban open space: meta-analyses of contingent valuation and hedonic pricing results.
Brander, Luke M; Koetse, Mark J
2011-10-01
Urban open space provides a number of valuable services to urban populations, including recreational opportunities, aesthetic enjoyment, environmental functions, and may also be associated with existence values. In separate meta-analyses of the contingent valuation (CV) and hedonic pricing (HP) literature we examine which physical, socio-economic, and study characteristics determine the value of open space. The dependent variable in the CV meta-regression is defined as the value of open space per hectare per year in 2003 US$, and in the HP model as the percentage change in house price for a 10 m decrease in distance to open space. Using a multi-level modelling approach we find in both the CV and HP analyses that there is a positive and significant relationship between the value of urban open space and population density, indicating that scarcity and crowdedness matter, and that the value of open space does not vary significantly with income. Further, urban parks are more highly valued than other types of urban open space (forests, agricultural and undeveloped land) and methodological differences in study design have a large influence on estimated values from both CV and HP. We also find important regional differences in preferences for urban open space, which suggests that the potential for transferring estimated values between regions is likely to be limited. Copyright © 2011 Elsevier Ltd. All rights reserved.
Bozorgmehr, Kayvan; San Sebastian, Miguel
2014-01-01
Background Trade liberalization is promoted by the World Trade Organization (WTO) through a complex architecture of binding trade agreements. This type of trade, however, has the potential to modify the upstream and proximate determinants of tuberculosis (TB) infection. We aimed to analyse the association between trade liberalization and TB incidence in 22 high-burden TB countries between 1990 and 2010. Methods and findings A longitudinal multi-level linear regression analysis was performed using five different measures of trade liberalization as exposure [WTO membership, duration of membership, trade as % of gross domestic product, and components of both the Economic Freedom of the World Index (EFI4) and the KOF Index of Globalization (KOF1)]. We adjusted for a wide range of factors, including differences in human development index (HDI), income inequality, debts, polity patterns, conflict, overcrowding, population stage transition, health system financing, case detection rates and HIV prevalence. None of the five trade indicators was significantly associated with TB incidence in the crude analysis. Any positive effect of EFI4 on (Log-) TB incidence over time was confounded by differences in socio-economic development (HDI), HIV prevalence and health financing indicators. The adjusted TB incidence rate ratio of WTO member countries was significantly higher [RR: 1.60; 95% confidence interval (CI): 1.12–2.29] when compared with non-member countries. Conclusion We found no association between specific aggregate indicators of trade liberalization and TB incidence. Our analyses provide evidence of a significant association between WTO membership and higher TB incidence, which suggests a possible conflict between the architecture of WTO agreements and TB-related Millennium Development Goals. Further research is needed, particularly on the relation between the aggregate trade indices used in this study and the hypothesized mediators and also on sector-specific indices, specific trade agreements and other (non-TB) health outcomes. PMID:23595571
Bozorgmehr, Kayvan; San Sebastian, Miguel
2014-05-01
Trade liberalization is promoted by the World Trade Organization (WTO) through a complex architecture of binding trade agreements. This type of trade, however, has the potential to modify the upstream and proximate determinants of tuberculosis (TB) infection. We aimed to analyse the association between trade liberalization and TB incidence in 22 high-burden TB countries between 1990 and 2010. and findings A longitudinal multi-level linear regression analysis was performed using five different measures of trade liberalization as exposure [WTO membership, duration of membership, trade as % of gross domestic product, and components of both the Economic Freedom of the World Index (EFI4) and the KOF Index of Globalization (KOF1)]. We adjusted for a wide range of factors, including differences in human development index (HDI), income inequality, debts, polity patterns, conflict, overcrowding, population stage transition, health system financing, case detection rates and HIV prevalence. None of the five trade indicators was significantly associated with TB incidence in the crude analysis. Any positive effect of EFI4 on (Log-) TB incidence over time was confounded by differences in socio-economic development (HDI), HIV prevalence and health financing indicators. The adjusted TB incidence rate ratio of WTO member countries was significantly higher [RR: 1.60; 95% confidence interval (CI): 1.12-2.29] when compared with non-member countries. We found no association between specific aggregate indicators of trade liberalization and TB incidence. Our analyses provide evidence of a significant association between WTO membership and higher TB incidence, which suggests a possible conflict between the architecture of WTO agreements and TB-related Millennium Development Goals. Further research is needed, particularly on the relation between the aggregate trade indices used in this study and the hypothesized mediators and also on sector-specific indices, specific trade agreements and other (non-TB) health outcomes.
Duration of Mechanical Ventilation in the Emergency Department.
Angotti, Lauren B; Richards, Jeremy B; Fisher, Daniel F; Sankoff, Jeffrey D; Seigel, Todd A; Al Ashry, Haitham S; Wilcox, Susan R
2017-08-01
Due to hospital crowding, mechanically ventilated patients are increasingly spending hours boarding in emergency departments (ED) before intensive care unit (ICU) admission. This study aims to evaluate the association between time ventilated in the ED and in-hospital mortality, duration of mechanical ventilation, ICU and hospital length of stay (LOS). This was a multi-center, prospective, observational study of patients ventilated in the ED, conducted at three academic Level I Trauma Centers from July 2011 to March 2013. All consecutive adult patients on invasive mechanical ventilation were eligible for enrollment. We performed a Cox regression to assess for a mortality effect for mechanically ventilated patients with each hour of increasing LOS in the ED and multivariable regression analyses to assess for independently significant contributors to in-hospital mortality. Our primary outcome was in-hospital mortality, with secondary outcomes of ventilator days, ICU LOS and hospital LOS. We further commented on use of lung protective ventilation and frequency of ventilator changes made in this cohort. We enrolled 535 patients, of whom 525 met all inclusion criteria. Altered mental status without respiratory pathology was the most common reason for intubation, followed by trauma and respiratory failure. Using iterated Cox regression, a mortality effect occurred at ED time of mechanical ventilation > 7 hours, and the longer ED stay was also associated with a longer total duration of intubation. However, adjusted multivariable regression analysis demonstrated only older age and admission to the neurosciences ICU as independently associated with increased mortality. Of interest, only 23.8% of patients ventilated in the ED for over seven hours had changes made to their ventilator. In a prospective observational study of patients mechanically ventilated in the ED, there was a significant mortality benefit to expedited transfer of patients into an appropriate ICU setting.
Aircraft Anomaly Detection Using Performance Models Trained on Fleet Data
NASA Technical Reports Server (NTRS)
Gorinevsky, Dimitry; Matthews, Bryan L.; Martin, Rodney
2012-01-01
This paper describes an application of data mining technology called Distributed Fleet Monitoring (DFM) to Flight Operational Quality Assurance (FOQA) data collected from a fleet of commercial aircraft. DFM transforms the data into aircraft performance models, flight-to-flight trends, and individual flight anomalies by fitting a multi-level regression model to the data. The model represents aircraft flight performance and takes into account fixed effects: flight-to-flight and vehicle-to-vehicle variability. The regression parameters include aerodynamic coefficients and other aircraft performance parameters that are usually identified by aircraft manufacturers in flight tests. Using DFM, the multi-terabyte FOQA data set with half-million flights was processed in a few hours. The anomalies found include wrong values of competed variables, (e.g., aircraft weight), sensor failures and baises, failures, biases, and trends in flight actuators. These anomalies were missed by the existing airline monitoring of FOQA data exceedances.
Hoch, Jeffrey S; Dewa, Carolyn S
2014-04-01
Economic evaluations commonly accompany trials of new treatments or interventions; however, regression methods and their corresponding advantages for the analysis of cost-effectiveness data are not well known. To illustrate regression-based economic evaluation, we present a case study investigating the cost-effectiveness of a collaborative mental health care program for people receiving short-term disability benefits for psychiatric disorders. We implement net benefit regression to illustrate its strengths and limitations. Net benefit regression offers a simple option for cost-effectiveness analyses of person-level data. By placing economic evaluation in a regression framework, regression-based techniques can facilitate the analysis and provide simple solutions to commonly encountered challenges. Economic evaluations of person-level data (eg, from a clinical trial) should use net benefit regression to facilitate analysis and enhance results.
NASA Astrophysics Data System (ADS)
Arsyah, D. M.; Kardena, E.; Helmy, Q.
2018-01-01
The study adopts a multi-level perspective in technology transition to analyse how the transition process in the development of geothermal energy in Indonesia is able to compete against the incumbent fossil-fuelled energy sources. Three levels of multi-level perspective are socio-technical landscape (ST-landscape), socio-technical regime (ST-regime) and niche innovations in Indonesia geothermal development. The identification, mapping and analysis of the dynamic relationship between each level are the important pillars of the multi-level perspective framework. The analysis considers the set of rules, actors and controversies that may arise in the technological transition process. The identified geothermal resource risks are the basis of the emerging geothermal technological innovations in Indonesian geothermal. The analysis of this study reveals the transition pathway, which yields a forecast for the Indonesian geothermal technology transition in the form of scenarios and probable impacts.
Mosing, Martina; Waldmann, Andreas D.; MacFarlane, Paul; Iff, Samuel; Auer, Ulrike; Bohm, Stephan H.; Bettschart-Wolfensberger, Regula; Bardell, David
2016-01-01
This study evaluated the breathing pattern and distribution of ventilation in horses prior to and following recovery from general anaesthesia using electrical impedance tomography (EIT). Six horses were anaesthetised for 6 hours in dorsal recumbency. Arterial blood gas and EIT measurements were performed 24 hours before (baseline) and 1, 2, 3, 4, 5 and 6 hours after horses stood following anaesthesia. At each time point 4 representative spontaneous breaths were analysed. The percentage of the total breath length during which impedance remained greater than 50% of the maximum inspiratory impedance change (breath holding), the fraction of total tidal ventilation within each of four stacked regions of interest (ROI) (distribution of ventilation) and the filling time and inflation period of seven ROI evenly distributed over the dorso-ventral height of the lungs were calculated. Mixed effects multi-linear regression and linear regression were used and significance was set at p<0.05. All horses demonstrated inspiratory breath holding until 5 hours after standing. No change from baseline was seen for the distribution of ventilation during inspiration. Filling time and inflation period were more rapid and shorter in ventral and slower and longer in most dorsal ROI compared to baseline, respectively. In a mixed effects multi-linear regression, breath holding was significantly correlated with PaCO2 in both the univariate and multivariate regression. Following recovery from anaesthesia, horses showed inspiratory breath holding during which gas redistributed from ventral into dorsal regions of the lungs. This suggests auto-recruitment of lung tissue which would have been dependent and likely atelectic during anaesthesia. PMID:27331910
Suzuki, Hideaki; Tabata, Takahisa; Koizumi, Hiroki; Hohchi, Nobusuke; Takeuchi, Shoko; Kitamura, Takuro; Fujino, Yoshihisa; Ohbuchi, Toyoaki
2014-12-01
This study aimed to create a multiple regression model for predicting hearing outcomes of idiopathic sudden sensorineural hearing loss (ISSNHL). The participants were 205 consecutive patients (205 ears) with ISSNHL (hearing level ≥ 40 dB, interval between onset and treatment ≤ 30 days). They received systemic steroid administration combined with intratympanic steroid injection. Data were examined by simple and multiple regression analyses. Three hearing indices (percentage hearing improvement, hearing gain, and posttreatment hearing level [HLpost]) and 7 prognostic factors (age, days from onset to treatment, initial hearing level, initial hearing level at low frequencies, initial hearing level at high frequencies, presence of vertigo, and contralateral hearing level) were included in the multiple regression analysis as dependent and explanatory variables, respectively. In the simple regression analysis, the percentage hearing improvement, hearing gain, and HLpost showed significant correlation with 2, 5, and 6 of the 7 prognostic factors, respectively. The multiple correlation coefficients were 0.396, 0.503, and 0.714 for the percentage hearing improvement, hearing gain, and HLpost, respectively. Predicted values of HLpost calculated by the multiple regression equation were reliable with 70% probability with a 40-dB-width prediction interval. Prediction of HLpost by the multiple regression model may be useful to estimate the hearing prognosis of ISSNHL. © The Author(s) 2014.
Fujishiro, Kaori; Stukovsky, Karen D Hinckley; Roux, Ana Diez; Landsbergis, Paul; Burchfiel, Cecil
2012-01-01
Objectives This study examines associations of occupation with smoking status, amount smoked among current- and former-smokers (number of cigarettes/day and lifetime cigarette consumption (pack-years)), and workplace exposure to environmental tobacco smoke (ETS) independent from income and education. Methods This is a cross-sectional analysis of data from a community sample (n=6355, age range: 45–84) using logistic and multinomial regression. All analyses were stratified by sex and adjusted for socio-demographic variables. Results Male blue-collar and sales/office workers had higher odds of having consumed >20 pack-years of cigarettes than managers/professionals. For both male and female current- or former-smokers, exposure to workplace ETS was consistently and strongly associated with heavy smoking and greater pack-years. Conclusions Blue-collar workplaces are associated with intense smoking and ETS exposure. Smoking must be addressed at both the individual- and workplace-levels especially in blue-collar workplaces. PMID:22261926
Rawat, Vinita; Singh, Rajesh Kumar; Kumar, Ashok; Saxena, Sandip R; Varshney, Umesh; Kumar, Mukesh
2018-04-01
We analysed the epidemiology, clinical and laboratory data of the 168 scrub typhus cases confirmed by a combination of any one of the following: real time polymerase chain reaction (RT-PCR) and/or immunofluorescence assay (IFA) (IgM and/or IgG). The peak season for scrub typhus was from July to October. By multivariate binary logistic regression analysis, the risk of scrub typhus was about four times in those working in occupation related to forest work. Major clinical manifestations were fever (100%), myalgia (65%), cough (51%) and vomiting (46%); major complications were meningitis/meningoencephatilitis (12.5%) and multi-organ failure (MOF) and pneumonia (5.3% each). Laboratory investigations revealed raised aminotranferase levels and thrombocytopenia in most confirmed cases. We conclude that scrub typhus is an important cause of febrile illness in the Kumaon hills of Uttarakhand where this disease had not previously been considered to exist.
Fujishiro, Kaori; Stukovsky, Karen D Hinckley; Roux, Ana Diez; Landsbergis, Paul; Burchfiel, Cecil
2012-02-01
This study examines associations of occupation with smoking status, amount smoked among current and former smokers (number of cigarettes per day and lifetime cigarette consumption (pack-years)), and workplace exposure to environmental tobacco smoke (ETS) independent from income and education. This is a cross-sectional analysis of data from a community sample (n = 6355, age range: 45-84) using logistic and multinomial regression. All analyses were stratified by sex and adjusted for socio-demographic variables. Male blue-collar and sales/office workers had higher odds of having consumed more than 20 pack-years of cigarettes than managers/professionals. For both male and female current or former smokers, exposure to workplace ETS was consistently and strongly associated with heavy smoking and greater pack-years. Blue-collar workplaces are associated with intense smoking and ETS exposure. Smoking must be addressed at both the individual and workplace levels especially in blue-collar workplaces.
Intermediate and advanced topics in multilevel logistic regression analysis
Merlo, Juan
2017-01-01
Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher‐level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within‐cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population‐average effect of covariates measured at the subject and cluster level, in contrast to the within‐cluster or cluster‐specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster‐level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:28543517
Intermediate and advanced topics in multilevel logistic regression analysis.
Austin, Peter C; Merlo, Juan
2017-09-10
Multilevel data occur frequently in health services, population and public health, and epidemiologic research. In such research, binary outcomes are common. Multilevel logistic regression models allow one to account for the clustering of subjects within clusters of higher-level units when estimating the effect of subject and cluster characteristics on subject outcomes. A search of the PubMed database demonstrated that the use of multilevel or hierarchical regression models is increasing rapidly. However, our impression is that many analysts simply use multilevel regression models to account for the nuisance of within-cluster homogeneity that is induced by clustering. In this article, we describe a suite of analyses that can complement the fitting of multilevel logistic regression models. These ancillary analyses permit analysts to estimate the marginal or population-average effect of covariates measured at the subject and cluster level, in contrast to the within-cluster or cluster-specific effects arising from the original multilevel logistic regression model. We describe the interval odds ratio and the proportion of opposed odds ratios, which are summary measures of effect for cluster-level covariates. We describe the variance partition coefficient and the median odds ratio which are measures of components of variance and heterogeneity in outcomes. These measures allow one to quantify the magnitude of the general contextual effect. We describe an R 2 measure that allows analysts to quantify the proportion of variation explained by different multilevel logistic regression models. We illustrate the application and interpretation of these measures by analyzing mortality in patients hospitalized with a diagnosis of acute myocardial infarction. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2017 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.
The Effect of Organizational Citizenship Behaviours of Primary School Teachers on Their Burnout
ERIC Educational Resources Information Center
Inandi, Yusuf; Buyukozkan, Ayse Sezin
2013-01-01
It was examined in this study whether organizational citizenship behaviours of primary school teachers predict the level of their burnout. Correlation and multi regression analysis were used for this. Survey model was used in this descriptive study. Data were collected from 1699 primary school teachers working in Mersin. Maslach Burnout Inventory…
ERIC Educational Resources Information Center
Dixon, L. Quentin; Chuang, Hui-Kai; Quiroz, Blanca
2012-01-01
To test the lexical restructuring hypothesis among bilingual English-language learners, English phonological awareness (PA), English vocabulary and ethnic language vocabulary (Mandarin Chinese, Malay or Tamil) were assessed among 284 kindergarteners (168 Chinese, 71 Malays and 45 Tamils) in Singapore. A multi-level regression analysis showed that…
2012-01-01
Background Emerging evidence indicates that there is an association between vitamin D and obesity. The aim of this study was to investigate whether the level of serum 25-hydroxyvitamin D3 [25(OH)D3] in the elderly is influenced by parameters of anthropometry and body composition independent of potential confounding lifestyle factors and the level of serum intact parathyroid hormone (iPTH). Methods Cross-sectional data of 131 independently living participants (90 women, 41 men; aged 66–96 years) of the longitudinal study on nutrition and health status in senior citizens of Giessen, Germany were analysed. Concentrations of 25(OH)D3 and iPTH were ascertained by an electrochemiluminescence immunoassay. Body composition was measured by a bioelectrical impedance analysis. We performed univariate and multiple regression analyses to examine the influence of body composition on 25(OH)D3 with adjustments for age, iPTH and lifestyle factors. Results In univariate regression analyses, 25(OH)D3 was associated with body mass index (BMI), hip circumference and total body fat (TBF) in women, but not in men. Using multiple regression analyses, TBF was shown to be a negative predictor of 25(OH)D3 levels in women even after controlling for age, lifestyle and iPTH (ß = −0.247; P = 0.016), whereas the associations between BMI, hip circumference and 25(OH)D3 lost statistical significance after adjusting for iPTH. In men, 25(OH)D3 was not affected by anthropometric or body composition variables. Conclusions The results indicate that 25(OH)D3 levels are affected by TBF, especially in elderly women, independent of lifestyle factors and iPTH. PMID:22607088
Samah, Asnarulkhadi Abu; Ahmadian, Maryam
2012-01-01
The rates of breast cancer have increased over the past two decades, and this raises concern about physical, psychological and social well-being of women with breast cancer. Further, few women really want to do breast cancer screening. We here investigated the socio-demographic correlates of mammography participation among 400 asymptomatic Iranian women aged between 35 and 69. A cross-sectional survey was conducted at the four outpatient clinics of general hospitals in Tehran during the period from July through October, 2009. Bi-variate analyses and multi-variate binary logistic regression were employed to find the socio- demographic predictors of mammography utilization among participants. The rate of mammography participation was 21.5% and relatively high because of access to general hospital services. More women who had undergone mammography were graduates from university or college, had full-time or part-time employment, were insured whether public or private, reported a positive family history of breast cancer, and were in the middle income level (P <0.01).The largest number of participating women was in the age range of 41 to 50 years. The results of multivariate logistic regression further showed that education (95%CI: 0.131-0.622), monthly income (95%CI: 0.038-0.945), and family history of breast cancer (95%CI: 1.97-9.28) were significantly associated (all P <0.05)with mammography participation. The most important issue for a successful screening program is participation. Using a random sample, this study found that the potential predictor variables of mammography participation included a higher education level, a middle income level, and a positive family history of breast cancer for Iranian women after adjusting for all other demographic variables in the model.
Miller, Nathan; Prevatt, Frances
2017-10-01
The purpose of this study was to reexamine the latent structure of ADHD and sluggish cognitive tempo (SCT) due to issues with construct validity. Two proposed changes to the construct include viewing hyperactivity and sluggishness (hypoactivity) as a single continuum of activity level, and viewing inattention as a separate dimension from activity level. Data were collected from 1,398 adults using Amazon's MTurk. A new scale measuring activity level was developed, and scores of Inattention were regressed onto scores of Activity Level using curvilinear regression. The Activity Level scale showed acceptable levels of internal consistency, normality, and unimodality. Curvilinear regression indicates that a quadratic (curvilinear) model accurately explains a small but significant portion of the variance in levels of inattention. Hyperactivity and hypoactivity may be viewed as a continuum, rather than separate disorders. Inattention may have a U-shaped relationship with activity level. Linear analyses may be insufficient and inaccurate for studying ADHD.
Ngeo, Jimson; Tamei, Tomoya; Shibata, Tomohiro
2014-01-01
Surface electromyographic (EMG) signals have often been used in estimating upper and lower limb dynamics and kinematics for the purpose of controlling robotic devices such as robot prosthesis and finger exoskeletons. However, in estimating multiple and a high number of degrees-of-freedom (DOF) kinematics from EMG, output DOFs are usually estimated independently. In this study, we estimate finger joint kinematics from EMG signals using a multi-output convolved Gaussian Process (Multi-output Full GP) that considers dependencies between outputs. We show that estimation of finger joints from muscle activation inputs can be improved by using a regression model that considers inherent coupling or correlation within the hand and finger joints. We also provide a comparison of estimation performance between different regression methods, such as Artificial Neural Networks (ANN) which is used by many of the related studies. We show that using a multi-output GP gives improved estimation compared to multi-output ANN and even dedicated or independent regression models.
Sabes-Figuera, Ramon; McCrone, Paul; Kendricks, Antony
2013-04-01
Economic evaluation analyses can be enhanced by employing regression methods, allowing for the identification of important sub-groups and to adjust for imperfect randomisation in clinical trials or to analyse non-randomised data. To explore the benefits of combining regression techniques and the standard Bayesian approach to refine cost-effectiveness analyses using data from randomised clinical trials. Data from a randomised trial of anti-depressant treatment were analysed and a regression model was used to explore the factors that have an impact on the net benefit (NB) statistic with the aim of using these findings to adjust the cost-effectiveness acceptability curves. Exploratory sub-samples' analyses were carried out to explore possible differences in cost-effectiveness. Results The analysis found that having suffered a previous similar depression is strongly correlated with a lower NB, independent of the outcome measure or follow-up point. In patients with previous similar depression, adding an selective serotonin reuptake inhibitors (SSRI) to supportive care for mild-to-moderate depression is probably cost-effective at the level used by the English National Institute for Health and Clinical Excellence to make recommendations. This analysis highlights the need for incorporation of econometric methods into cost-effectiveness analyses using the NB approach.
Musuku, Adrien; Tan, Aimin; Awaiye, Kayode; Trabelsi, Fethi
2013-09-01
Linear calibration is usually performed using eight to ten calibration concentration levels in regulated LC-MS bioanalysis because a minimum of six are specified in regulatory guidelines. However, we have previously reported that two-concentration linear calibration is as reliable as or even better than using multiple concentrations. The purpose of this research is to compare two-concentration with multiple-concentration linear calibration through retrospective data analysis of multiple bioanalytical projects that were conducted in an independent regulated bioanalytical laboratory. A total of 12 bioanalytical projects were randomly selected: two validations and two studies for each of the three most commonly used types of sample extraction methods (protein precipitation, liquid-liquid extraction, solid-phase extraction). When the existing data were retrospectively linearly regressed using only the lowest and the highest concentration levels, no extra batch failure/QC rejection was observed and the differences in accuracy and precision between the original multi-concentration regression and the new two-concentration linear regression are negligible. Specifically, the differences in overall mean apparent bias (square root of mean individual bias squares) are within the ranges of -0.3% to 0.7% and 0.1-0.7% for the validations and studies, respectively. The differences in mean QC concentrations are within the ranges of -0.6% to 1.8% and -0.8% to 2.5% for the validations and studies, respectively. The differences in %CV are within the ranges of -0.7% to 0.9% and -0.3% to 0.6% for the validations and studies, respectively. The average differences in study sample concentrations are within the range of -0.8% to 2.3%. With two-concentration linear regression, an average of 13% of time and cost could have been saved for each batch together with 53% of saving in the lead-in for each project (the preparation of working standard solutions, spiking, and aliquoting). Furthermore, examples are given as how to evaluate the linearity over the entire concentration range when only two concentration levels are used for linear regression. To conclude, two-concentration linear regression is accurate and robust enough for routine use in regulated LC-MS bioanalysis and it significantly saves time and cost as well. Copyright © 2013 Elsevier B.V. All rights reserved.
A parameter estimation subroutine package
NASA Technical Reports Server (NTRS)
Bierman, G. J.; Nead, M. W.
1978-01-01
Linear least squares estimation and regression analyses continue to play a major role in orbit determination and related areas. In this report we document a library of FORTRAN subroutines that have been developed to facilitate analyses of a variety of estimation problems. Our purpose is to present an easy to use, multi-purpose set of algorithms that are reasonably efficient and which use a minimal amount of computer storage. Subroutine inputs, outputs, usage and listings are given along with examples of how these routines can be used. The following outline indicates the scope of this report: Section (1) introduction with reference to background material; Section (2) examples and applications; Section (3) subroutine directory summary; Section (4) the subroutine directory user description with input, output, and usage explained; and Section (5) subroutine FORTRAN listings. The routines are compact and efficient and are far superior to the normal equation and Kalman filter data processing algorithms that are often used for least squares analyses.
Liese, Angela D; Schulz, Mandy; Moore, Charity G; Mayer-Davis, Elizabeth J
2004-12-01
Epidemiological investigations increasingly employ dietary-pattern techniques to fully integrate dietary data. The present study evaluated the relationship of dietary patterns identified by cluster analysis with measures of insulin sensitivity (SI) and adiposity in the multi-ethnic, multi-centre Insulin Resistance Atherosclerosis Study (IRAS, 1992-94). Cross-sectional data from 980 middle-aged adults, of whom 67 % had normal and 33 % had impaired glucose tolerance, were analysed. Usual dietary intake was obtained by an interviewer-administered, validated food-frequency questionnaire. Outcomes included SI, fasting insulin (FI), BMI and waist circumference. The relationship of dietary patterns to log(SI+1), log(FI), BMI and waist circumference was modelled with multivariable linear regressions. Cluster analysis identified six distinct diet patterns--'dark bread', 'wine', 'fruits', 'low-frequency eaters', 'fries' and 'white bread'. The 'white bread' and the 'fries' patterns over-represented the Hispanic IRAS population predominantly from two centres, while the 'wine' and 'dark bread' groups were dominated by non-Hispanic whites. The dietary patterns were associated significantly with each of the outcomes first at the crude, clinical level (P<0.001). Furthermore, they were significantly associated with FI, BMI and waist circumference independent of age, sex, race or ethnicity, clinic, family history of diabetes, smoking and activity (P<0.004), whereas significance was lost for SI. Studying the total dietary behaviour via a pattern approach allowed us to focus both on the qualitative and quantitative dimensions of diet. The present study identified highly consistent associations of distinct dietary patterns with measures of insulin resistance and adiposity, which are risk factors for diabetes and heart disease.
Stab, Nicole; Hacker, Winfried; Weigl, Matthias
2016-09-01
Ward organization is a major determinant for nurses' well-being on the job. The majority of previous research on this relationship is based on single source methods, which have been criticized as skewed estimations mainly due to subjectivity of the ratings and due to common source bias. To investigate the association of ward organization characteristics and nurses' exhaustion by combining observation-based assessments with nurses' self-reports. Cross-sectional study on 25 wards of four hospitals and 245 nurses. Our multi-method approach to evaluate hospital ward organization consisted of on-site observations with a standardized assessment tool and of questionnaires to evaluate nurses' self-reports and exhaustion. After establishing the reliability of our measures, we applied multi-level regression analyses to determine associations between determinant and outcome variables. We found substantial convergence in ward organization between the observation-based assessments and nurses' self-reports, which supports the validity of our external assessments. Furthermore, two observation-based characteristics, namely participation and patient-focused care, were significantly associated with lower emotional exhaustion among the nurses. Our results suggest that observation-based assessments are a valid and feasible way to assess ward organization in hospitals. Nurses' self-reported as well as observation-based ratings on ward organization were associated with nurses' emotional exhaustion. This is of interest mainly for identifying alternative measures in evaluating nurses' work environments, to inform health promotion activities and to evaluate job redesign intervention. Copyright © 2016 Elsevier Ltd. All rights reserved.
Feuerhahn, Nicolas; Stamov-Roßnagel, Christian; Wolfram, Maren; Bellingrath, Silja; Kudielka, Brigitte M
2013-10-01
We investigate how emotional exhaustion (EE), the core component of burnout, relates to cognitive performance, job performance and health. Cognitive performance was assessed by self-rated cognitive stress symptoms, self-rated and peer-rated cognitive impairments in everyday tasks and a neuropsychological test of learning and memory (LGT-3); job performance and physical health were gauged by self-reports. Cross-sectional linear regression analyses in a sample of 100 teachers confirm that EE is negatively related to cognitive performance as assessed by self-rating and peer-rating as well as neuropsychological testing (all p < .05). Longitudinal linear regression analyses confirm similar trends (p < .10) for self-rated and peer-rated cognitive performance. Executive control deficits might explain impaired cognitive performance in EE. In longitudinal analyses, EE also significantly predicts physical health. Contrary to our expectations, EE does not affect job performance. When reversed causation is tested, none of the outcome variables at Time 1 predict EE at Time 2. This speaks against cognitive dysfunctioning serving as a vulnerability factor for exhaustion. In sum, results underpin the negative consequences of EE for cognitive performance and health, which are relevant for individuals and organizations alike. In this way, findings might contribute to the understanding of the burnout syndrome. Copyright © 2012 John Wiley & Sons, Ltd.
Rosero, Eric B; Peshock, Ronald M; Khera, Amit; Clagett, Patrick; Lo, Hao; Timaran, Carlos H
2011-04-01
Reference values and age-related changes of the wall thickness of the abdominal aorta have not been described in the general population. We characterized age-, race-, and gender-specific distributions, and yearly rates of change of mean aortic wall thickness (MAWT), and associations between MAWT and cardiovascular risk factors in a multi-ethnic population-based probability sample. Magnetic resonance imaging measurements of MAWT were performed on 2466 free-living white, black, and Hispanic adult subjects. MAWT race/ethnicity- and gender-specific percentile values across age were estimated using regression analyses. MAWT was greater in men than in women and increased linearly with age in all the groups and across all the percentiles. Hispanic women had the thinnest and black men the thickest aortas. Black men had the highest and white women the lowest age-related MAWT increase. Age, gender, ethnicity, smoking status, systolic blood pressure, low-density lipoprotein-cholesterol levels, high-density lipoprotein-cholesterol levels, and fasting glucose levels were independent predictors of MAWT. Age, gender, and racial/ethnic differences in MAWT distributions exist in the general population. Such differences should be considered in future investigations assessing aortic atherosclerosis and the effects of anti-atherosclerotic therapies. Published by Mosby, Inc.
An, Ning; Yang, Xue; Cheng, Shujun; Wang, Guiqi; Zhang, Kaitai
2015-01-01
Carcinogenesis is an exceedingly complicated process, which involves multi-level dysregulations, including genomics (majorly caused by somatic mutation and copy number variation), DNA methylomics, and transcriptomics. Therefore, only looking into one molecular level of cancer is not sufficient to uncover the intricate underlying mechanisms. With the abundant resources of public available data in the Cancer Genome Atlas (TCGA) database, an integrative strategy was conducted to systematically analyze the aberrant patterns of colorectal cancer on the basis of DNA copy number, promoter methylation, somatic mutation and gene expression. In this study, paired samples in each genomic level were retrieved to identify differentially expressed genes with corresponding genetic or epigenetic dysregulations. Notably, the result of gene ontology enrichment analysis indicated that the differentially expressed genes with corresponding aberrant promoter methylation or somatic mutation were both functionally concentrated upon developmental process, suggesting the intimate association between development and carcinogenesis. Thus, by means of random walk with restart, 37 significant development-related genes were retrieved from a priori-knowledge based biological network. In five independent microarray datasets, Kaplan–Meier survival and Cox regression analyses both confirmed that the expression of these genes was significantly associated with overall survival of Stage III/IV colorectal cancer patients. PMID:26691761
An, Ning; Yang, Xue; Cheng, Shujun; Wang, Guiqi; Zhang, Kaitai
2015-12-22
Carcinogenesis is an exceedingly complicated process, which involves multi-level dysregulations, including genomics (majorly caused by somatic mutation and copy number variation), DNA methylomics, and transcriptomics. Therefore, only looking into one molecular level of cancer is not sufficient to uncover the intricate underlying mechanisms. With the abundant resources of public available data in the Cancer Genome Atlas (TCGA) database, an integrative strategy was conducted to systematically analyze the aberrant patterns of colorectal cancer on the basis of DNA copy number, promoter methylation, somatic mutation and gene expression. In this study, paired samples in each genomic level were retrieved to identify differentially expressed genes with corresponding genetic or epigenetic dysregulations. Notably, the result of gene ontology enrichment analysis indicated that the differentially expressed genes with corresponding aberrant promoter methylation or somatic mutation were both functionally concentrated upon developmental process, suggesting the intimate association between development and carcinogenesis. Thus, by means of random walk with restart, 37 significant development-related genes were retrieved from a priori-knowledge based biological network. In five independent microarray datasets, Kaplan-Meier survival and Cox regression analyses both confirmed that the expression of these genes was significantly associated with overall survival of Stage III/IV colorectal cancer patients.
Capasso, Roberto; Zurlo, Maria Clelia; Smith, Andrew P
2018-02-01
This study integrates different aspects of ethnicity and work-related stress dimensions (based on the Demands-Resources-Individual-Effects model, DRIVE [Mark, G. M., and A. P. Smith. 2008. "Stress Models: A Review and Suggested New Direction." In Occupational Health Psychology, edited by J. Houdmont and S. Leka, 111-144. Nottingham: Nottingham University Press]) and aims to test a multi-dimensional model that combines individual differences, ethnicity dimensions, work characteristics, and perceived job satisfaction/stress as independent variables in the prediction of subjectives reports of health by workers differing in ethnicity. A questionnaire consisting of the following sections was submitted to 900 workers in Southern Italy: for individual and cultural characteristics, coping strategies, personality behaviours, and acculturation strategies; for work characteristics, perceived job demands and job resources/rewards; for appraisals, perceived job stress/satisfaction and racial discrimination; for subjective reports of health, psychological disorders and general health. To test the reliability and construct validity of the extracted factors referred to all dimensions involved in the proposed model and logistic regression analyses to evaluate the main effects of the independent variables on the health outcomes were conducted. Principal component analysis (PCA) yielded seven factors for individual and cultural characteristics (emotional/relational coping, objective coping, Type A behaviour, negative affectivity, social inhibition, affirmation/maintenance culture, and search identity/adoption of the host culture); three factors for work characteristics (work demands, intrinsic/extrinsic rewards, and work resources); three factors for appraisals (perceived job satisfaction, perceived job stress, perceived racial discrimination) and three factors for subjective reports of health (interpersonal disorders, anxious-depressive disorders, and general health). Logistic regression analyses showed main effects of specific individual and cultural differences, work characteristics and perceived job satisfaction/stress on the risk of suffering health problems. The suggested model provides a strong framework that illustrates how psychosocial and individual variables can influence occupational health in multi-cultural workplaces.
Kern, David M; Auchincloss, Amy H; Stehr, Mark F; Roux, Ana V Diez; Moore, Latetia V; Kanter, Genevieve P; Robinson, Lucy F
2017-11-16
It is known that the price of food influences the purchasing and consumption decisions of individuals; however, little work has examined if the price of healthier food relative to unhealthier food in an individual's neighborhood is associated with overall dietary quality while using data from multiple regions in the United States. Cross-sectional person-level data came from The Multi-Ethnic Study of Atherosclerosis (exam 5, 2010-2012 n = 2765); a food frequency questionnaire assessed diet. Supermarket food/beverage prices came from Information Resources Inc. (n = 794 supermarkets). For each individual, the average price of select indicators of healthier foods (vegetables, fruits, dairy) and unhealthier foods (soda, sweets, salty snacks), as well as their ratio, was computed for supermarkets within three miles of the person's residential address. Logistic regression estimated odds ratios of a high-quality diet (top quintile of Healthy Eating Index 2010) associated with healthy-to-unhealthy price ratio, adjusted for individual and neighborhood characteristics. Sensitivity analyses used an instrumental variable (IV) approach. Healthier foods cost nearly twice as much as unhealthier foods per serving on average (mean healthy-to-unhealthy ratio = 1.97 [SD 0.14]). A larger healthy-to-unhealthy price ratio was associated with lower odds of a high-quality diet (OR = 0.76 per SD increase in the ratio, 95% CI = [0.64-0.9]). IV analyses largely confirmed these findings although-as expected with IV adjustment-confidence intervals were wide (OR = 0.82 [0.57-1.19]). Policies to address the large price differences between healthier and unhealthy foods may help improve diet quality in the United States.
Kern, David M.; Stehr, Mark F.; Diez Roux, Ana V.; Moore, Latetia V.; Kanter, Genevieve P.; Robinson, Lucy F.
2017-01-01
It is known that the price of food influences the purchasing and consumption decisions of individuals; however, little work has examined if the price of healthier food relative to unhealthier food in an individual’s neighborhood is associated with overall dietary quality while using data from multiple regions in the United States. Cross-sectional person-level data came from The Multi-Ethnic Study of Atherosclerosis (exam 5, 2010–2012, n = 2765); a food frequency questionnaire assessed diet. Supermarket food/beverage prices came from Information Resources Inc. (n = 794 supermarkets). For each individual, the average price of select indicators of healthier foods (vegetables, fruits, dairy) and unhealthier foods (soda, sweets, salty snacks), as well as their ratio, was computed for supermarkets within three miles of the person’s residential address. Logistic regression estimated odds ratios of a high-quality diet (top quintile of Healthy Eating Index 2010) associated with healthy-to-unhealthy price ratio, adjusted for individual and neighborhood characteristics. Sensitivity analyses used an instrumental variable (IV) approach. Healthier foods cost nearly twice as much as unhealthier foods per serving on average (mean healthy-to-unhealthy ratio = 1.97 [SD 0.14]). A larger healthy-to-unhealthy price ratio was associated with lower odds of a high-quality diet (OR = 0.76 per SD increase in the ratio, 95% CI = [0.64–0.9]). IV analyses largely confirmed these findings although—as expected with IV adjustment—confidence intervals were wide (OR = 0.82 [0.57–1.19]). Policies to address the large price differences between healthier and unhealthy foods may help improve diet quality in the United States. PMID:29144387
Kwon, Jin-Woo; Choi, Jin A; La, Tae Yoon
2016-11-01
The aim of this article was to assess the associations of serum 25-hydroxyvitamin D [25(OH)D] and daily sun exposure time with myopia in Korean adults.This study is based on the Korea National Health and Nutrition Examination Survey (KNHANES) of Korean adults in 2010-2012; multiple logistic regression analyses were performed to examine the associations of serum 25(OH)D levels and daily sun exposure time with myopia, defined as spherical equivalent ≤-0.5D, after adjustment for age, sex, household income, body mass index (BMI), exercise, intraocular pressure (IOP), and education level. Also, multiple linear regression analyses were performed to examine the relationship between serum 25(OH)D levels with spherical equivalent after adjustment for daily sun exposure time in addition to the confounding factors above.Between the nonmyopic and myopic groups, spherical equivalent, age, IOP, BMI, waist circumference, education level, household income, and area of residence differed significantly (all P < 0.05). Compared with subjects with daily sun exposure time <2 hour, subjects with sun exposure time ≥2 to <5 hour, and those with sun exposure time ≥5 hour had significantly less myopia (P < 0.001). In addition, compared with subjects were categorized into quartiles of serum 25(OH)D, the higher quartiles had gradually lower prevalences of myopia after adjustment for confounding factors (P < 0.001). In multiple linear regression analyses, spherical equivalent was significantly associated with serum 25(OH)D concentration after adjustment for confounding factors (P = 0.002).Low serum 25(OH)D levels and shorter daily sun exposure time may be independently associated with a high prevalence of myopia in Korean adults. These data suggest a direct role for vitamin D in the development of myopia.
Sport Commitment among Competitive Female Gymnasts: A Developmental Perspective
ERIC Educational Resources Information Center
Weiss, Windee M.; Weiss, Maureen R.
2007-01-01
The purpose of this study was to examine age and competitive level differences in the relationship between determinants and level of sport commitment. Gymnasts (N = 304) comprised three age groups (8-11, 11-14.5, and 14.5-18 years) and two competitive levels (Levels 5-6 and 8-10). Multiple regression analyses revealed: (a) perceived costs and…
Ye, Jiang-Feng; Zhao, Yu-Xin; Ju, Jian; Wang, Wei
2017-10-01
To discuss the value of the Bedside Index for Severity in Acute Pancreatitis (BISAP), Modified Early Warning Score (MEWS), serum Ca2+, similarly hereinafter, and red cell distribution width (RDW) for predicting the severity grade of acute pancreatitis and to develop and verify a more accurate scoring system to predict the severity of AP. In 302 patients with AP, we calculated BISAP and MEWS scores and conducted regression analyses on the relationships of BISAP scoring, RDW, MEWS, and serum Ca2+ with the severity of AP using single-factor logistics. The variables with statistical significance in the single-factor logistic regression were used in a multi-factor logistic regression model; forward stepwise regression was used to screen variables and build a multi-factor prediction model. A receiver operating characteristic curve (ROC curve) was constructed, and the significance of multi- and single-factor prediction models in predicting the severity of AP using the area under the ROC curve (AUC) was evaluated. The internal validity of the model was verified through bootstrapping. Among 302 patients with AP, 209 had mild acute pancreatitis (MAP) and 93 had severe acute pancreatitis (SAP). According to single-factor logistic regression analysis, we found that BISAP, MEWS and serum Ca2+ are prediction indexes of the severity of AP (P-value<0.001), whereas RDW is not a prediction index of AP severity (P-value>0.05). The multi-factor logistic regression analysis showed that BISAP and serum Ca2+ are independent prediction indexes of AP severity (P-value<0.001), and MEWS is not an independent prediction index of AP severity (P-value>0.05); BISAP is negatively related to serum Ca2+ (r=-0.330, P-value<0.001). The constructed model is as follows: ln()=7.306+1.151*BISAP-4.516*serum Ca2+. The predictive ability of each model for SAP follows the order of the combined BISAP and serum Ca2+ prediction model>Ca2+>BISAP. There is no statistical significance for the predictive ability of BISAP and serum Ca2+ (P-value>0.05); however, there is remarkable statistical significance for the predictive ability using the newly built prediction model as well as BISAP and serum Ca2+ individually (P-value<0.01). Verification of the internal validity of the models by bootstrapping is favorable. BISAP and serum Ca2+ have high predictive value for the severity of AP. However, the model built by combining BISAP and serum Ca2+ is remarkably superior to those of BISAP and serum Ca2+ individually. Furthermore, this model is simple, practical and appropriate for clinical use. Copyright © 2016. Published by Elsevier Masson SAS.
Boermans, S M; Kamphuis, W; Delahaij, R; van den Berg, C; Euwema, M C
2014-12-01
This article prospectively explores the effects of collective team work engagement and organizational constraints during military deployment on individual-level psychological outcomes afterwards. Participants were 971 Dutch peacekeepers within 93 teams who were deployed between the end of 2008 and beginning of 2010, for an average of 4 months, in the International Security Assistance Force. Surveys were administered 2 months into deployment and 6 months afterwards. Multi-level regression analyses demonstrated that team work engagement during deployment moderated the relation between organizational constraints and post-deployment fatigue symptoms. Team members reported less fatigue symptoms after deployment if they were part of highly engaged teams during deployment, particularly when concerns about organizational constraints during deployment were high. In contrast, low team work engagement was related to more fatigue symptoms, particularly when concerns about organizational constraints were high. Contrary to expectations, no effects for team work engagement or organizational constraints were found for post-traumatic growth. The present study highlights that investing in team work engagement is important for those working in highly demanding jobs. © 2014 John Wiley & Sons, Ltd.
Danzig, Allison P.; Dyson, Margaret W.; Olino, Thomas M.; Laptook, Rebecca S.; Klein, Daniel N.
2017-01-01
This study examined the effects of parents’ positive and negative affect and behavior while interacting with their preschool child and the moderating role of child temperament in predicting children’s subsequent difficulty with socially appropriate behavior around school-entry. Independent observational measures were used to assess child temperament (dysphoria; exuberance) and parenting at age 3, and multi-informant reports of child socially appropriate behavior were collected at age 6 (N = 219). Hierarchical multiple regression analyses revealed that children’s temperamental dysphoria moderated the relationship between positive parenting and later socially appropriate behavior. High- and low-dysphoric children trended in opposite directions; highly dysphoric children experienced greater difficulty with socially appropriate behavior as levels of positive parenting increased, whereas low-dysphoric children experienced less difficulty with socially appropriate behavior with higher levels of positive parenting. There was also an interaction between positive and negative parenting, whereby the combination of elevated positive and negative parenting predicted children’s later difficulty with socially appropriate behavior. The findings suggest that positive parenting interacts with early child temperament and negative parenting to impact the development of children’s socially appropriate behavior. PMID:28824223
Kahnert, Kathrin; Alter, Peter; Welte, Tobias; Huber, Rudolf M; Behr, Jürgen; Biertz, Frank; Watz, Henrik; Bals, Robert; Vogelmeier, Claus F; Jörres, Rudolf A
2018-06-04
Recent investigations showed single associations between uric acid levels, functional parameters, exacerbations and mortality in COPD patients. The aim of this study was to describe the role of uric acid within the network of multiple relationships between function, exacerbation and comorbidities. We used baseline data from the German COPD cohort COSYCONET which were evaluated by standard multiple regression analyses as well as path analysis to quantify the network of relations between parameters, particularly uric acid. Data from 1966 patients were analyzed. Uric acid was significantly associated with reduced FEV 1 , reduced 6-MWD, higher burden of exacerbations (GOLD criteria) and cardiovascular comorbidities, in addition to risk factors such as BMI and packyears. These associations remained significant after taking into account their multiple interdependences. Compared to uric acid levels the diagnosis of hyperuricemia and its medication played a minor role. Within the limits of a cross-sectional approach, our results strongly suggest that uric acid is a biomarker of high impact in COPD and plays a genuine role for relevant outcomes such as physical capacity and exacerbations. These findings suggest that more attention should be paid to uric acid in the evaluation of COPD disease status.
NASA Astrophysics Data System (ADS)
Lian See, Tan; Zulazlan Shah Zulkifli, Ahmad; Mook Tzeng, Lim
2018-04-01
Ozone is a reactant which can be applied for various environmental treatment processes. It can be generated via atmospheric air non-thermal plasmas when sufficient voltages are applied through a combination of electrodes and dielectric materials. In this study, the concentration of ozone generated via two different configurations of multi-cylinder dielectric barrier discharge (DBD) reactor (3 x 40 mm and 10 x 10 mm) was investigated. The influence of the voltage and the duty cycle to the concentration of ozone generated by each configuration was analysed using response surface methodology. Voltage was identified as significant factor to the ozone production process. However, the regressed model was biased towards one of the configuration, leaving the predicted results of another configuration to be out of range.
Hjarsbech, Pernille U; Christensen, Karl Bang; Bjorner, Jakob B; Madsen, Ida E H; Thorsen, Sannie V; Carneiro, Isabella G; Christensen, Ulla; Rugulies, Reiner
2014-03-01
Mental health problems are strong predictors of long-term sickness absence (LTSA). In this study, we investigated whether organizational justice at work - fairness in resolving conflicts and distributing work - prevents risk of LTSA among employees with depressive symptoms. In a longitudinal study with five waves of data collection, we examined a cohort of 1034 employees with depressive symptoms. Depressive symptoms and organizational justice were assessed by self-administered questionnaires and information on LTSA was derived from a national register. Using Poisson regression analyses, we calculated rate ratios (RR) for the prospective association of organizational justice and change in organizational justice with time to onset of LTSA. All analyses were sex stratified. Among men, intermediate levels of organizational justice were statistically significantly associated with a decreased risk of subsequent LTSA after adjustment for covariates [RR 0.49, 95% confidence interval (95% CI) 0.26-0.91]. There was also a decreased risk for men with high levels of organizational justice although these estimates did not reach statistical significance after adjustment (RR 0.47, 95% CI 0.20-1.10). We found no such results for women. In both sexes, neither favorable nor adverse changes in organizational justice were statistically significantly associated with the risk of LTSA. This study shows that organizational justice may have a protective effect on the risk of LTSA among men with depressive symptoms. A protective effect of favorable changes in organizational justice was not found.
ERIC Educational Resources Information Center
Balfanz, Robert; Mac Iver, Douglas J.; Byrnes, Vaughan
2006-01-01
This article reports on the first 4 years of an effort to develop comprehensive and sustainable mathematics education reforms in high poverty middle schools. In four related analyses, we examine the levels of implementation achieved and impact of the reforms on various measures of achievement in the first 3 schools to implement the Talent…
Piao, Hui-Hong; He, Jiajia; Zhang, Keqin; Tang, Zihui
2015-01-01
Our research aims to investigate the associations between education level and osteoporosis (OP) in Chinese postmenopausal women. A large-scale, community-based, cross-sectional study was conducted to examine the associations between education level and OP. A self-reported questionnaire was used to access the demographical information and medical history of the participants. A total of 1905 postmenopausal women were available for data analysis in this study. Multiple regression models controlling for confounding factors to include education level were performed to investigate the relationship with OP. The prevalence of OP was 28.29% in our study sample. Multivariate linear regression analyses adjusted for relevant potential confounding factors detected significant associations between education level and T-score (β = 0.025, P-value = 0.095, 95% CI: -0.004-0.055 for model 1; and β = 0.092, P-value = 0.032, 95% CI: 0.008-0.175 for model 2). Multivariate logistic regression analyses detected significant associations between education level and OP in model 1 (P-value = 0.070 for model 1, Table 5), while no significant associations was reported in model 2 (P value = 0.131). In participants with high education levels, the OR for OP was 0.914 (95% CI: 0.830-1.007). The findings indicated that education level was independently and significantly associated with OP. The prevalence of OP was more frequent in Chinese postmenopausal women with low educational status.
Synthesis, spectral studies and antimicrobial activities of some 2-naphthyl pyrazoline derivatives
NASA Astrophysics Data System (ADS)
Sakthinathan, S. P.; Vanangamudi, G.; Thirunarayanan, G.
A series of 2-naphthyl pyrazolines were synthesized by the cyclization of 2-naphthyl chalcones and phenylhydrazine hydrochloride in the presence of sodium acetate. The yields of pyrazoline derivatives are more than 80%. The synthesized pyrazolines were characterized by their physical constants, IR, 1H, 13C and MS spectra. From the IR and NMR spectra the Cdbnd N (cm-1) stretches, the pyrazoline ring proton chemical shifts (ppm) of δ, Hb and Hc and also the carbon chemical shifts (ppm) of δCdbnd N are correlated with Hammett substituent constants, F and R, and Swain-Lupton's parameters using single and multi-regression analyses. From the results of linear regression analysis, the effect of substituents on the group frequencies has been predicted. The antimicrobial activities of all synthesized pyrazolines have been studied.
Primary laws and fine levels are associated with increases in seat belt use, 1997-2008
DOT National Transportation Integrated Search
2010-11-01
Increasing fine levels is a strategy that has potential to further raise seat belt use, in addition to primary law upgrades and high-visibility enforcement. Although the regression analyses did not find a statistically significant effect associated w...
J. Stephen Brewer
2010-01-01
Quantifying per capita impacts of invasive species on resident communities requires integrating regression analyses with experiments under natural conditions. Using multivariate and univariate approaches, I regressed the abundance of 105 resident species of groundcover plants and tree seedlings against the abundance and height of an invasive grass, Microstegium...
Examination of the Gender-Student Engagement Relationship at One University
ERIC Educational Resources Information Center
Tison, Emilee B.; Bateman, Tanner; Culver, Steven M.
2011-01-01
Research examining the relationship between gender and student engagement at the post secondary level has provided mixed results. The current study explores two possible reasons for lack of clarity regarding this relationship: improper parameter estimation resulting from a lack of multi-level analyses and inconsistent conceptions/measures of…
USDA-ARS?s Scientific Manuscript database
Secondary metabolite phenotypes in nine species of the Hamigera clade were analysed to assess their correlations to a multi-gene species-level phylogeny. High-pressure-liquid-chromatography-based chemical analysis revealed three distinctive patterns of secondary metabolite production: (1) the nine s...
An Exploration of Teacher Attrition and Mobility in High Poverty Racially Segregated Schools
ERIC Educational Resources Information Center
Djonko-Moore, Cara M.
2016-01-01
The purpose of this study was to examine the mobility (movement to a new school) and attrition (quitting teaching) patterns of teachers in high poverty, racially segregated (HPRS) schools in the US. Using 2007-9 survey data from the National Center for Education Statistics, a multi-level multinomial logistic regression was performed to examine the…
Approximate l-fold cross-validation with Least Squares SVM and Kernel Ridge Regression
DOE Office of Scientific and Technical Information (OSTI.GOV)
Edwards, Richard E; Zhang, Hao; Parker, Lynne Edwards
2013-01-01
Kernel methods have difficulties scaling to large modern data sets. The scalability issues are based on computational and memory requirements for working with a large matrix. These requirements have been addressed over the years by using low-rank kernel approximations or by improving the solvers scalability. However, Least Squares Support VectorMachines (LS-SVM), a popular SVM variant, and Kernel Ridge Regression still have several scalability issues. In particular, the O(n^3) computational complexity for solving a single model, and the overall computational complexity associated with tuning hyperparameters are still major problems. We address these problems by introducing an O(n log n) approximate l-foldmore » cross-validation method that uses a multi-level circulant matrix to approximate the kernel. In addition, we prove our algorithm s computational complexity and present empirical runtimes on data sets with approximately 1 million data points. We also validate our approximate method s effectiveness at selecting hyperparameters on real world and standard benchmark data sets. Lastly, we provide experimental results on using a multi-level circulant kernel approximation to solve LS-SVM problems with hyperparameters selected using our method.« less
Evolahti, Annika; Hultcrantz, Malou; Collins, Aila
2006-11-01
The aim of the present study was to investigate whether there is an association between serum cortisol and work-related stress, as defined by the demand-control model in a longitudinal design. One hundred ten women aged 47-53 years completed a health questionnaire, including the Swedish version of the Job Content Scale, and participated in a psychological interview at baseline and in a follow-up session 2 years later. Morning blood samples were drawn for analyses of cortisol. Multiple stepwise regression analyses and logistic regression analyses showed that work demands and lack of social support were significantly associated with cortisol. The results of this study showed that negative work characteristics in terms of high demands and low social support contributed significantly to the biological stress levels in middle-aged women. Participation in the study may have served as an intervention, increasing the women's awareness and thus improving their health profiles on follow-up.
Land use, residential density, and walking. The multi-ethnic study of atherosclerosis.
Rodríguez, Daniel A; Evenson, Kelly R; Diez Roux, Ana V; Brines, Shannon J
2009-11-01
The neighborhood environment may play a role in encouraging sedentary patterns, especially for middle-aged and older adults. The aim of this study was to examine the associations between walking and neighborhood population density, retail availability, and land-use distribution using data from a cohort of adults aged 45 to 84 years. Data from a multi-ethnic sample of 5529 adult residents of Baltimore MD, Chicago IL, Forsyth County NC, Los Angeles CA, New York NY, and St. Paul MN enrolled in the Multi-Ethnic Study of Atherosclerosis in 2000-2002 were linked to secondary land-use and population data. Participant reports of access to destinations and stores and objective measures of the percentage of land area in parcels devoted to retail land uses, the population divided by land area in parcels, and the mixture of uses for areas within 200 m of each participant's residence were examined. Multinomial logistic regression was used to investigate associations of self-reported and objective neighborhood characteristics with walking. All analyses were conducted in 2008 and 2009. After adjustment for individual-level characteristics and neighborhood connectivity, it was found that higher density, greater land area devoted to retail uses, and self-reported proximity of destinations and ease of walking to places were each related to walking. In models including all land-use measures, population density was positively associated with walking to places and with walking for exercise for more than 90 minutes/week, both relative to no walking. Availability of retail was associated with walking to places relative to not walking, and having a more proportional mix of land uses was associated with walking for exercise for more than 90 minutes/week, while self-reported ease of access to places was related to higher levels of exercise walking, both relative to not walking. Residential density and the presence of retail uses are related to various walking behaviors. Efforts to increase walking may benefit from attention to the intensity and type of land development.
Clinical associations of anti-Smith antibodies in PROFILE: a multi-ethnic lupus cohort.
Arroyo-Ávila, Mariangelí; Santiago-Casas, Yesenia; McGwin, Gerald; Cantor, Ryan S; Petri, Michelle; Ramsey-Goldman, Rosalind; Reveille, John D; Kimberly, Robert P; Alarcón, Graciela S; Vilá, Luis M; Brown, Elizabeth E
2015-07-01
The aim of this study was to determine the association of anti-Sm antibodies with clinical manifestations, comorbidities, and disease damage in a large multi-ethnic SLE cohort. SLE patients (per American College of Rheumatology criteria), age ≥16 years, disease duration ≤10 years at enrollment, and defined ethnicity (African American, Hispanic or Caucasian), from a longitudinal US cohort were studied. Socioeconomic-demographic features, cumulative clinical manifestations, comorbidities, and disease damage (as per the Systemic Lupus International Collaborating Clinics Damage Index [SDI]) were determined. The association of anti-Sm antibodies with clinical features was examined using multivariable logistic regression analyses adjusting for age, gender, ethnicity, disease duration, level of education, health insurance, and smoking. A total of 2322 SLE patients were studied. The mean (standard deviation, SD) age at diagnosis was 34.4 (12.8) years and the mean (SD) disease duration was 9.0 (7.9) years; 2127 (91.6%) were women. Anti-Sm antibodies were present in 579 (24.9%) patients. In the multivariable analysis, anti-Sm antibodies were significantly associated with serositis, renal involvement, psychosis, vasculitis, Raynaud's phenomenon, hemolytic anemia, leukopenia, lymphopenia, and arterial hypertension. No significant association was found for damage accrual. In this cohort of SLE patients, anti-Sm antibodies were associated with several clinical features including serious manifestations such as renal, neurologic, and hematologic disorders as well as vasculitis.
Loneliness, Depression, and Inflammation: Evidence from the Multi-Ethnic Study of Atherosclerosis.
Mezuk, Briana; Choi, Moon; DeSantis, Amy S; Rapp, Stephen R; Diez Roux, Ana V; Seeman, Teresa
2016-01-01
Both objective and subjective aspects of social isolation have been associated with alterations in immune markers relevant to multiple chronic diseases among older adults. However, these associations may be confounded by health status, and it is unclear whether these social factors are associated with immune functioning among relatively healthy adults. The goal of this study was to examine the associations between perceived loneliness and circulating levels of inflammatory markers among a diverse sample of adults. Data come from a subset of the Multi-Ethnic Study of Atherosclerosis (n = 441). Loneliness was measured by three items derived from the UCLA Loneliness Scale. The association between loneliness and C-reactive protein (CRP) and fibrinogen was assessed using multivariable linear regression analyses. Models were adjusted for demographic and health characteristics. Approximately 50% of participants reported that they hardly ever felt lonely and 17.2% felt highly lonely. Individuals who were unmarried/unpartnered or with higher depressive symptoms were more likely to report being highly lonely. There was no relationship between perceived loneliness and ln(CRP) (β = -0.051, p = 0.239) adjusting for demographic and health characteristics. Loneliness was inversely associated with ln(fibrinogen) (β = -0.091, p = 0.040), although the absolute magnitude of this relationship was small. These results indicate that loneliness is not positively associated with fibrinogen or CRP among relatively healthy middle-aged adults.
Loneliness, Depression, and Inflammation: Evidence from the Multi-Ethnic Study of Atherosclerosis
Mezuk, Briana; Choi, Moon; DeSantis, Amy S.; Rapp, Stephen R.; Diez Roux, Ana V.; Seeman, Teresa
2016-01-01
Objective Both objective and subjective aspects of social isolation have been associated with alterations in immune markers relevant to multiple chronic diseases among older adults. However, these associations may be confounded by health status, and it is unclear whether these social factors are associated with immune functioning among relatively healthy adults. The goal of this study was to examine the associations between perceived loneliness and circulating levels of inflammatory markers among a diverse sample of adults. Methods Data come from a subset of the Multi-Ethnic Study of Atherosclerosis (n = 441). Loneliness was measured by three items derived from the UCLA Loneliness Scale. The association between loneliness and C-reactive protein (CRP) and fibrinogen was assessed using multivariable linear regression analyses. Models were adjusted for demographic and health characteristics. Results Approximately 50% of participants reported that they hardly ever felt lonely and 17.2% felt highly lonely. Individuals who were unmarried/unpartnered or with higher depressive symptoms were more likely to report being highly lonely. There was no relationship between perceived loneliness and ln(CRP) (β = -0.051, p = 0.239) adjusting for demographic and health characteristics. Loneliness was inversely associated with ln(fibrinogen) (β = -0.091, p = 0.040), although the absolute magnitude of this relationship was small. Conclusion These results indicate that loneliness is not positively associated with fibrinogen or CRP among relatively healthy middle-aged adults. PMID:27367428
Intimate Partner Violence in Interracial and Monoracial Couples
ERIC Educational Resources Information Center
Martin, Brittny A.; Cui, Ming; Ueno, Koji; Fincham, Frank D.
2013-01-01
This study, using a nationally representative sample, investigated intimate partner violence (IPV) in interracial and monoracial relationships. Regression analyses indicated that interracial couples demonstrated a higher level of mutual IPV than monoracial White couples but a level similar to monoracial Black couples. There were significant gender…
NASA Astrophysics Data System (ADS)
Scalia, C.; Leone, F.; Gangi, M.; Giarrusso, M.; Stift, M. J.
2017-12-01
One method for the determination of integrated longitudinal stellar fields from low-resolution spectra is the so-called slope method, which is based on the regression of the Stokes V signal against the first derivative of Stokes I. Here we investigate the possibility of extending this technique to measure the magnetic fields of cool stars from high-resolution spectra. For this purpose we developed a multi-line modification to the slope method, called the multi-line slope method. We tested this technique by analysing synthetic spectra computed with the COSSAM code and real observations obtained with the high-resolution spectropolarimeters Narval, HARPSpol and the Catania Astrophysical Observatory Spectropolarimeter (CAOS). We show that the multi-line slope method is a fast alternative to the least squares deconvolution technique for the measurement of the effective magnetic fields of cool stars. Using a Fourier transform on the effective magnetic field variations of the star ε Eri, we find that the long-term periodicity of the field corresponds to the 2.95-yr period of the stellar dynamo, revealed by the variation of the activity index.
NASA Astrophysics Data System (ADS)
Holburn, E. R.; Bledsoe, B. P.; Poff, N. L.; Cuhaciyan, C. O.
2005-05-01
Using over 300 R/EMAP sites in OR and WA, we examine the relative explanatory power of watershed, valley, and reach scale descriptors in modeling variation in benthic macroinvertebrate indices. Innovative metrics describing flow regime, geomorphic processes, and hydrologic-distance weighted watershed and valley characteristics are used in multiple regression and regression tree modeling to predict EPT richness, % EPT, EPT/C, and % Plecoptera. A nested design using seven ecoregions is employed to evaluate the influence of geographic scale and environmental heterogeneity on the explanatory power of individual and combined scales. Regression tree models are constructed to explain variability while identifying threshold responses and interactions. Cross-validated models demonstrate differences in the explanatory power associated with single-scale and multi-scale models as environmental heterogeneity is varied. Models explaining the greatest variability in biological indices result from multi-scale combinations of physical descriptors. Results also indicate that substantial variation in benthic macroinvertebrate response can be explained with process-based watershed and valley scale metrics derived exclusively from common geospatial data. This study outlines a general framework for identifying key processes driving macroinvertebrate assemblages across a range of scales and establishing the geographic extent at which various levels of physical description best explain biological variability. Such information can guide process-based stratification to avoid spurious comparison of dissimilar stream types in bioassessments and ensure that key environmental gradients are adequately represented in sampling designs.
Viana, Andres G; Gratz, Kim L; Bierman, Karen L
2013-01-01
Temperamental vulnerabilities (e.g., behavioral inhibition, anxiety sensitivity) and cognitive biases (e.g., interpretive and judgment biases) may exacerbate feelings of stress and anxiety, particularly among late adolescents during the early years of college. The goal of the present study was to apply person-centered analyses to explore possible heterogeneity in the patterns of these four risk factors in late adolescence, and to examine associations with several anxiety outcomes (i.e., worry, anxiety symptoms, and trait anxiety). Cluster analyses in a college sample of 855 late adolescents revealed a Low-Risk group, along with four reliable clusters with distinct profiles of risk factors and anxiety outcomes (Inhibited, Sensitive, Cognitively-Biased, and Multi-Risk). Of the risk profiles, Multi-Risk youth experienced the highest levels of anxiety outcomes, whereas Inhibited youth experienced the lowest levels of anxiety outcomes. Sensitive and Cognitively-Biased youth experienced comparable levels of anxiety-related outcomes, despite different constellations of risk factors. Implications for interventions and future research are discussed.
Lee, Chia Ee; Vincent-Chong, Vui King; Ramanathan, Anand; Kallarakkal, Thomas George; Karen-Ng, Lee Peng; Ghani, Wan Maria Nabillah; Rahman, Zainal Ariff Abdul; Ismail, Siti Mazlipah; Abraham, Mannil Thomas; Tay, Keng Kiong; Mustafa, Wan Mahadzir Wan; Cheong, Sok Ching; Zain, Rosnah Binti
2015-01-01
BACKGROUND: Collagen Triple Helix Repeat Containing 1 (CTHRC1) is a protein often found to be over-expressed in various types of human cancers. However, correlation between CTHRC1 expression level with clinico-pathological characteristics and prognosis in oral cancer remains unclear. Therefore, this study aimed to determine mRNA and protein expression of CTHRC1 in oral squamous cell carcinoma (OSCC) and to evaluate the clinical and prognostic impact of CTHRC1 in OSCC. METHODS: In this study, mRNA and protein expression of CTHRC1 in OSCCs were determined by quantitative PCR and immunohistochemistry, respectively. The association between CTHRC1 and clinico-pathological parameters were evaluated by univariate and multivariate binary logistic regression analyses. Correlation between CTHRC1 protein expressions with survival were analysed using Kaplan-Meier and Cox regression models. RESULTS: Current study demonstrated CTHRC1 was significantly overexpressed at the mRNA level in OSCC. Univariate analyses indicated a high-expression of CTHRC1 that was significantly associated with advanced stage pTNM staging, tumour size ≥ 4 cm and positive lymph node metastasis (LNM). However, only positive LNM remained significant after adjusting with other confounder factors in multivariate logistic regression analyses. Kaplan-Meier survival analyses and Cox model demonstrated that patients with high-expression of CTHRC1 protein were associated with poor prognosis and is an independent prognostic factor in OSCC. CONCLUSION: This study indicated that over-expression of CTHRC1 potentially as an independent predictor for positive LNM and poor prognosis in OSCC. PMID:26664254
Skordis-Worrall, Jolene; Manandhar, Dharma S.; Strachan, Daniel; Morrison, Joanna; Saville, Naomi; Osrin, David; Tumbahangphe, Kirti M.; Costello, Anthony; Heys, Michelle
2018-01-01
Women’s groups practicing participatory learning and action (PLA) in rural areas have been shown to improve maternal and newborn survival in low-income countries, but the pathways from intervention to impact remain unclear. We assessed the long-term impact of a PLA intervention in rural Nepal on women’s agency in the household. In 2014, we conducted a follow-up study to a cluster randomised controlled trial on the impact of PLA women’s groups from 2001–2003. Agency was measured using the Relative Autonomy Index (RAI) and its subdomains. Multi-level regression analyses were performed adjusting for baseline socio-demographic characteristics. We additionally adjusted for potential exposure to subsequent PLA groups based on women’s pregnancy status and conduct of PLA groups in areas of residence. Sensitivity analyses were performed using two alternative measures of agency. We analysed outcomes for 4030 mothers (66% of the cohort) who survived and were recruited to follow-up at mean age 39.6 years. Across a wide range of model specifications, we found no association between exposure to the original PLA intervention with women’s agency in the household approximately 11.5 years later. Subsequent exposure to PLA groups was not associated with greater agency in the household at follow-up, but some specifications found evidence for reduced agency. Household agency may be a prerequisite for actualising the benefits of PLA groups rather than a consequence. PMID:29758071
Rüst, Christoph Alexander; Rosemann, Thomas; Lepers, Romuald; Knechtle, Beat
2015-01-01
We analysed (i) the gender difference in cycling speed and (ii) the age of winning performers in the 508-mile "Furnace Creek 508". Changes in cycling speeds and gender differences from 1983 to 2012 were analysed using linear, non-linear and hierarchical multi-level regression analyses for the annual three fastest women and men. Cycling speed increased non-linearly in men from 14.6 (s = 0.3) km · h(-1) (1983) to 27.1 (s = 0.7) km · h(-1) (2012) and non-linearly in women from 11.0 (s = 0.3) km · h(-1) (1984) to 24.2 (s = 0.2) km · h(-1) (2012). The gender difference in cycling speed decreased linearly from 26.2 (s = 0.5)% (1984) to 10.7 (s = 1.9)% (2012). The age of winning performers increased from 26 (s = 2) years (1984) to 43 (s = 11) years (2012) in women and from 33 (s = 6) years (1983) to 50 (s = 5) years (2012) in men. To summarise, these results suggest that (i) women will be able to narrow the gender gap in cycling speed in the near future in an ultra-endurance cycling race such as the "Furnace Creek 508" due to the linear decrease in gender difference and (ii) the maturity of these athletes has changed during the last three decades where winning performers become older and faster across years.
Dahl, Espen; Ivar Elstad, Jon; Hofoss, Dag; Martin-Mollard, Melissa
2006-11-01
This study investigates the degree to which contextual income inequality in economic regions in Norway affected mortality during the 1990s, above the effects of mean regional income and individual-level confounders. A further objective is to explore whether income inequality effects on mortality differed between socioeconomic groups. Data were constructed by linkages of administrative registers encompassing all Norwegian inhabitants. The outcome variable was all-cause mortality during 6 years (i.e., died 1994-1999 or alive end of 1999). Men and women aged 25-66 in 1993 were analysed. Regions' mean income and income inequality (in terms of gini coefficients) were calculated from consumption-units-adjusted family disposable income. Individual-level variables included sex, age, marital status, individual income, education, and being a recipient of health-related welfare benefits. Multilevel logistic regression models were fitted for 2,197,231 individuals nested within 88 regions. After adjusting for regional mean income and individual-level variables, the odds ratio (OR) for mortality 1994-1999 was 1.028 (95% CI 1.023-1.033) on the gini variable multiplied by 100. Analyses of cross-level interactions indicated some, albeit modest, income inequality effects on mortality in the upper income and educational categories. Among those with low individual income, low education, and among recipients of health-related welfare benefits, mortality effects of higher regional income inequality were significantly stronger than among those more advantageously placed in the social structure. The results of this study differ from previous studies which have suggested that contextual income inequality has a minor impact on population health in egalitarian countries. The results indicate that in Norway, neither a comparatively egalitarian income distribution nor generous and comprehensive welfare institutions hindered the emergence of regional-level income inequality effects on mortality, and these effects were particularly marked among socioeconomically disadvantaged groups. Explanations for the results are discussed.
Predictors of job satisfaction among academic family medicine faculty
Krueger, Paul; White, David; Meaney, Christopher; Kwong, Jeffrey; Antao, Viola; Kim, Florence
2017-01-01
Abstract Objective To identify predictors of job satisfaction among academic family medicine faculty members. Design A comprehensive Web-based survey of all faculty members in an academic department of family medicine. Bivariate and multivariable analyses (logistic regression) were used to identify variables associated with job satisfaction. Setting The Department of Family and Community Medicine at the University of Toronto in Ontario and its 15 affiliated community teaching hospitals and community-based teaching practices. Participants All 1029 faculty members in the Department of Family and Community Medicine were invited to complete the survey. Main outcome measures Faculty members’ demographic and practice information; teaching, clinical, administration, and research activities; leadership roles; training needs and preferences; mentorship experiences; health status; stress levels; burnout levels; and job satisfaction. Faculty members’ perceptions about supports provided, recognition, communication, retention, workload, teamwork, respect, resource distribution, remuneration, and infrastructure support. Faculty members’ job satisfaction, which was the main outcome variable, was obtained from the question, “Overall, how satisfied are you with your job?” Results Of the 1029 faculty members, 687 (66.8%) responded to the survey. Bivariate analyses revealed 26 predictors as being statistically significantly associated with job satisfaction, including faculty members’ ratings of their local department and main practice setting, their ratings of leadership and mentorship experiences, health status variables, and demographic variables. The multivariable analyses identified the following 5 predictors of job satisfaction: the Maslach Burnout Inventory subscales of emotional exhaustion and personal accomplishment; being born in Canada; the overall quality of mentorship that was received being rated as very good or excellent; and teamwork being rated as very good or excellent. Conclusion The findings from this study show that job satisfaction among academic family medicine faculty members is a multi-dimensional construct. Future improvement in overall level of job satisfaction will therefore require multiple strategies. PMID:28292815
Krueger, Paul; White, David; Meaney, Christopher; Kwong, Jeffrey; Antao, Viola; Kim, Florence
2017-03-01
To identify predictors of job satisfaction among academic family medicine faculty members. A comprehensive Web-based survey of all faculty members in an academic department of family medicine. Bivariate and multivariable analyses (logistic regression) were used to identify variables associated with job satisfaction. The Department of Family and Community Medicine at the University of Toronto in Ontario and its 15 affiliated community teaching hospitals and community-based teaching practices. All 1029 faculty members in the Department of Family and Community Medicine were invited to complete the survey. Faculty members' demographic and practice information; teaching, clinical, administration, and research activities; leadership roles; training needs and preferences; mentorship experiences; health status; stress levels; burnout levels; and job satisfaction. Faculty members' perceptions about supports provided, recognition, communication, retention, workload, teamwork, respect, resource distribution, remuneration, and infrastructure support. Faculty members' job satisfaction, which was the main outcome variable, was obtained from the question, "Overall, how satisfied are you with your job?" Of the 1029 faculty members, 687 (66.8%) responded to the survey. Bivariate analyses revealed 26 predictors as being statistically significantly associated with job satisfaction, including faculty members' ratings of their local department and main practice setting, their ratings of leadership and mentorship experiences, health status variables, and demographic variables. The multivariable analyses identified the following 5 predictors of job satisfaction: the Maslach Burnout Inventory subscales of emotional exhaustion and personal accomplishment; being born in Canada; the overall quality of mentorship that was received being rated as very good or excellent; and teamwork being rated as very good or excellent. The findings from this study show that job satisfaction among academic family medicine faculty members is a multi-dimensional construct. Future improvement in overall level of job satisfaction will therefore require multiple strategies. Copyright© the College of Family Physicians of Canada.
ERIC Educational Resources Information Center
Nafukho, Fredrick Muyia; Hinton, Barbara E.
2003-01-01
Multiple regression analyses of data from 143 public transportation drivers in Kenya indicated that driver experience and hours worked were significantly related to rates of traffic accidents. Educational level, training, salary, and average speed were not related. (Contains 45 references.) (SK)
ERIC Educational Resources Information Center
Kelly, Ronald R.; Gaustad, Martha G.
2007-01-01
This study of deaf college students examined specific relationships between their mathematics performance and their assessed skills in reading, language, and English morphology. Simple regression analyses showed that deaf college students' language proficiency scores, reading grade level, and morphological knowledge regarding word segmentation and…
Ethnic Identity as a Predictor of Problem Behaviors among Korean American Adolescents
ERIC Educational Resources Information Center
Shrake, Eunai K.; Rhee, Siyon
2004-01-01
This study examined three dimensions of ethnic identity (level of ethnic identity, attitudes toward other groups, and perceived discrimination) as predictors of adolescent problem behaviors among Korean American adolescents. Multiple regression analyses were carried out, and the results indicated that level of ethnic identity, perceived…
Bilano, Ver Luanni; Ota, Erika; Ganchimeg, Togoobaatar; Mori, Rintaro; Souza, João Paulo
2014-01-01
Pre-eclampsia has an immense adverse impact on maternal and perinatal health especially in low- and middle-income settings. We aimed to estimate the associations between pre-eclampsia/eclampsia and its risk factors, and adverse maternal and perinatal outcomes. We performed a secondary analysis of the WHO Global Survey on Maternal and Perinatal Health. The survey was a multi-country, facility-based cross-sectional study. A global sample consisting of 24 countries from three regions and 373 health facilities was obtained via a stratified multi-stage cluster sampling design. Maternal and offspring data were extracted from records using standardized questionnaires. Multi-level logistic regression modelling was conducted with random effects at the individual, facility and country levels. Data for 276,388 mothers and their infants was analysed. The prevalence of pre-eclampsia/eclampsia in the study population was 10,754 (4%). At the individual level, sociodemographic characteristics of maternal age ≥30 years and low educational attainment were significantly associated with higher risk of pre-eclampsia/eclampsia. As for clinical and obstetric variables, high body mass index (BMI), nulliparity (AOR: 2.04; 95%CI 1.92-2.16), absence of antenatal care (AOR: 1.41; 95%CI 1.26-1.57), chronic hypertension (AOR: 7.75; 95%CI 6.77-8.87), gestational diabetes (AOR: 2.00; 95%CI 1.63-2.45), cardiac or renal disease (AOR: 2.38; 95%CI 1.86-3.05), pyelonephritis or urinary tract infection (AOR: 1.13; 95%CI 1.03-1.24) and severe anemia (AOR: 2.98; 95%CI 2.47-3.61) were found to be significant risk factors, while having >8 visits of antenatal care was protective (AOR: 0.90; 95%CI 0.83-0.98). Pre-eclampsia/eclampsia was found to be a significant risk factor for maternal death, perinatal death, preterm birth and low birthweight. Chronic hypertension, obesity and severe anemia were the highest risk factors of preeclampsia/eclampsia. Implementation of effective interventions prioritizing risk factors, provision of quality health services during pre-pregnancy and during pregnancy for joint efforts in the areas of maternal health are recommended.
Secondary School Socio-Cultural Context Influencing ICT Integration: A Case Study Approach
ERIC Educational Resources Information Center
Divaharan, Shanti; Ping, Lim Cher
2010-01-01
This paper proposes the use of activity theory and multi-level activity systems as a framework to analyse the effectiveness of ICT integration in Singapore secondary school classrooms. Three levels of activity systems are developed to study the effectiveness of ICT integration at the classroom: the classroom activity system, the department…
Garimella, Pranav S; Ix, Joachim H; Katz, Ronit; Shlipak, Michael G; Criqui, Michael H; Siscovick, David S; Kramer, Holly; Sibley, Christopher T; Sarnak, Mark J
2015-01-01
Low ankle-brachial index (ABI) is a reflection of atherosclerotic disease, and high ABI is an indicator of calcified vessels. The associations of albuminuria and cystatin C level with incidence of either low or high ABI are unknown. Prospective longitudinal cohort study. MESA (Multi-Ethnic Study of Atherosclerosis) enrolled community-dwelling adults (N=6,814) aged 45-84 years who were free of clinical cardiovascular disease at baseline. Baseline albumin-creatinine ratio (ACR) and serum cystatin C level. Development of low (<0.90), and high (>1.40) ABI using multinomial regression among persons with ABI of 0.90-1.40 at baseline. During 9.8 years of follow-up, 221 and 89 participants progressed to low and high ABIs, respectively. Baseline ACR and cystatin C level were higher among progressors compared with nonprogressors. In multivariable analyses, doubling of ACR was associated with increased risk of progression to low (OR, 1.08; 95% CI, 0.99-1.20) and high (OR, 1.16; 95% CI, 1.01-1.32) ABIs. Compared to the lowest quintile, the highest quintile of ACR had a significantly increased risk of progression to low (OR, 1.79; 95% CI, 1.03-3.12) and high (OR, 2.76; 95% CI, 1.32-5.77) ABIs. Higher cystatin C levels were associated with progression to low (OR per 1-SD greater, 1.12; 95% CI, 1.00-1.26) but not high (OR per 1-SD greater, 1.01; 95% CI, 0.81-1.25) ABI, but the highest quintile of cystatin C was not associated independently with either outcome. Single measure of albuminuria and low number of progressors to high ABI. In adults free of clinical cardiovascular disease, albuminuria was a strong independent risk factor for the development of both high and low ABIs, important and different measures of peripheral artery disease. Copyright © 2014 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.
McCarrier, Kelly P; Martin, Diane P; Ralston, James D; Zimmerman, Frederick J
2010-05-01
Minimum wage policies have been advanced as mechanisms to improve the economic conditions of the working poor. Both positive and negative effects of such policies on health care access have been hypothesized, but associations have yet to be thoroughly tested. To examine whether the presence of minimum wage policies in excess of the federal standard of $5.15 per hour was associated with health care access indicators among low-skilled adults of working age, a cross-sectional analysis of 2004 Behavioral Risk Factor Surveillance System data was conducted. Self-reported health insurance status and experience with cost-related barriers to needed medical care were adjusted in multi-level logistic regression models to control for potential confounding at the state, county, and individual levels. State-level wage policy was not found to be associated with insurance status or unmet medical need in the models, providing early evidence that increased minimum wage rates may neither strengthen nor weaken access to care as previously predicted.
Learning to Predict Combinatorial Structures
NASA Astrophysics Data System (ADS)
Vembu, Shankar
2009-12-01
The major challenge in designing a discriminative learning algorithm for predicting structured data is to address the computational issues arising from the exponential size of the output space. Existing algorithms make different assumptions to ensure efficient, polynomial time estimation of model parameters. For several combinatorial structures, including cycles, partially ordered sets, permutations and other graph classes, these assumptions do not hold. In this thesis, we address the problem of designing learning algorithms for predicting combinatorial structures by introducing two new assumptions: (i) The first assumption is that a particular counting problem can be solved efficiently. The consequence is a generalisation of the classical ridge regression for structured prediction. (ii) The second assumption is that a particular sampling problem can be solved efficiently. The consequence is a new technique for designing and analysing probabilistic structured prediction models. These results can be applied to solve several complex learning problems including but not limited to multi-label classification, multi-category hierarchical classification, and label ranking.
Chung, Seungjoon; Seo, Chang Duck; Choi, Jae-Hoon; Chung, Jinwook
2014-01-01
Membrane distillation (MD) is an emerging desalination technology as an energy-saving alternative to conventional distillation and reverse osmosis method. The selection of appropriate membrane is a prerequisite for the design of an optimized MD process. We proposed a simple approximation method to evaluate the performance of membranes for MD process. Three hollow fibre-type commercial membranes with different thicknesses and pore sizes were tested. Experimental results showed that one membrane was advantageous due to the highest flux, whereas another membrane was due to the lowest feed temperature drop. Regression analyses and multi-stage calculations were used to account for the trade-offeffects of flux and feed temperature drop. The most desirable membrane was selected from tested membranes in terms of the mean flux in a multi-stage process. This method would be useful for the selection of the membranes without complicated simulation techniques.
VanderEnde, Kristin E; Sibley, Lynn M; Cheong, Yuk Fai; Naved, Ruchira Tabassum; Yount, Kathryn M
2015-06-01
In this research, we used a multi-level contextual-effects analysis to disentangle the household- and community-level associations between income and intimate partner violence (IPV) against women in Bangladesh. Our analyses of data from 2,668 women interviewed as part of the World Health Organization (WHO) multi-country study on women's health and domestic violence against women showed that household income was negatively associated with women's risk of experiencing IPV. Controlling for residence in a low-income household, living in a low-income community was not associated with women's risk of experiencing IPV. These results support a household-level, not community-level, relationship between income and IPV in Bangladesh. © The Author(s) 2015.
Lin, Hualiang; Guo, Yanfei; Di, Qian; Zheng, Yang; Kowal, Paul; Xiao, Jianpeng; Liu, Tao; Li, Xing; Zeng, Weilin; Howard, Steven W.; Nelson, Erik J.; Qian, Zhengmin (Min); Ma, Wenjun; Wu, Fan
2017-01-01
Background and Purpose Short-term exposure to ambient fine particulate pollution (PM2.5) has been linked to increased stroke. Few studies, however, have examined the effects of long-term exposure. Methods A total of 45,625 participants were interviewed and included in this study, the participants came from the Study on Global AGEing and Adult Health, a prospective cohort in six low- and middle-income countries. Ambient PM2.5 levels were estimated for participants’ communities using satellite data. A multi-level logistic regression model was used to examine the association between long-term PM2.5 exposure and stroke. Potential effect modification by physical activity and consumption of fruit and vegetables was assessed. Results The odds of stroke were 1.13 (95% CI: 1.04, 1.22) for each 10 μg/m3 increase in PM2.5. This effect remained after adjustment for confounding factors including age, sex, smoking and indoor air pollution (adjusted OR=1.12, 95% CI: 1.04, 1.21). Further stratified analyses suggested that participants with higher levels of physical activity had greater odds of stroke, while those with higher consumption of fruit and vegetables had lower odds of stroke. These effects remained robust in sensitivity analyses. We further estimated that 6.55% (95% CI: 1.97%, 12.01%) of the stroke cases could be attributable to ambient PM2.5 in the study population. Conclusions This study suggests that ambient PM2.5 may increase the risk of stroke, and may be responsible for the astounding stroke burden in low- and middle-income countries. Additionally, greater physical activity may enhance, whereas greater consumption of fruit and vegetables may mitigate the effect. PMID:28386038
Shiue, Ivy
2014-10-01
Studies looking into neighbourhood satisfaction including prevalence, risk correlates, and impacts are very scarce. Therefore, it was aimed to provide recent evidence on prevalence and psychiatric correlates of neighbourhood satisfaction and its impact on individual behaviours and life aspects in adolescents in a national and population-based setting. Data were retrieved and analysed in the UK Longitudinal Household Survey in 2011-2012. Information on demographics, lifestyle factors, urbanisation level, and behavioural and emotional development was obtained by household interview. Analyses included descriptive statistics, chi-square test and usual and multi-level logistic regression modelling. Of 491 (11.2%) out of 4427 adolescents were dissatisfied with their neighbourhoods and 6.8% (n=297) were classified as having abnormal psychiatric state. Smoking status (both current and past) and alcohol status (both current and past) were associated with neighbourhood dissatisfaction but not sex, urbanisation level or country of residence. Compared to people who were classified as normal, others with borderline or abnormal mental state tended to express dissatisfaction toward their current neighbourhoods. In addition, these people reported more "troublesome" individual behaviours for about 18 types out of 24 types in total and had poor perception toward life in many aspects including family, friends, school, and even personal appearance. One in five adolescents were dissatisfied with their current neighbourhoods leading to worrying individual behaviours and negative impacts on life. Neighbourhood renewal strategy or place-making to facilitate self-efficacy could be considered as priority to be integrated into future public health programs and/or put onto public health policy agenda. Copyright © 2014 Elsevier Inc. All rights reserved.
Takaoka, Motoko; Suzuki, Kyoko; Norbäck, Dan
2017-08-01
To study associations between the school and home environment and current asthma, respiratory symptoms and airway infections among Japanese students. Japanese students (12-15 y) (N = 1048) in four schools responded to a questionnaire on respiratory health, allergy and the home environment. Temperature, relative air humidity (RH) and student density (students/m 2 floor area) was measured in the classrooms: dust was collected from floors and in classroom air and analysed for cat (Fel d 1) and dog (Can f 1) allergens. Health associations were analysed by multi-level logistic regression. Doctor's diagnosed asthma was common (13.4%), 8.8% reported cat allergy and 6.1% dog allergy. The median level in floor dust was 41 ng/g (IQR 23-92) for Fel d 1 and 101 ng/g (IQR 54-101) for Can f 1. The median level in air was 18.6 ng/ m 2 / day (IQR5.9-25.1) for Fel d 1 and 18.6 ng/ m 2 / day (IQR 6.0-13.3) for Can f 1. High RH, high student density and airborne cat allergen was associated with airway infections. In the home environment, recent indoor painting, new floor materials, odour, having cats as pets, window pane condensation in winter, and dampness in floor construction were associated with respiratory illness. High relative air humidity, high student density and airborne cat allergens at school may increase the risk of airway infections. Having cats as pets, chemical emissions from paint and new floor materials, odour and dampness can constitute domestic risk factors for respiratory symptoms while having dogs as pets could be protective.
Shin, Sang Soo; Shin, Young-Jeon
2016-01-01
With an increasing number of studies highlighting regional social capital (SC) as a determinant of health, many studies are using multi-level analysis with merged and averaged scores of community residents' survey responses calculated from community SC data. Sufficient examination is required to validate if the merged and averaged data can represent the community. Therefore, this study analyzes the validity of the selected indicators and their applicability in multi-level analysis. Within and between analysis (WABA) was performed after creating community variables using merged and averaged data of community residents' responses from the 2013 Community Health Survey in Korea, using subjective self-rated health assessment as a dependent variable. Further analysis was performed following the model suggested by WABA result. Both E-test results (1) and WABA results (2) revealed that single-level analysis needs to be performed using qualitative SC variable with cluster mean centering. Through single-level multivariate regression analysis, qualitative SC with cluster mean centering showed positive effect on self-rated health (0.054, p<0.001), although there was no substantial difference in comparison to analysis using SC variables without cluster mean centering or multi-level analysis. As modification in qualitative SC was larger within the community than between communities, we validate that relational analysis of individual self-rated health can be performed within the group, using cluster mean centering. Other tests besides the WABA can be performed in the future to confirm the validity of using community variables and their applicability in multi-level analysis.
Ecologic regression analysis and the study of the influence of air quality on mortality.
Selvin, S; Merrill, D; Wong, L; Sacks, S T
1984-01-01
This presentation focuses entirely on the use and evaluation of regression analysis applied to ecologic data as a method to study the effects of ambient air pollution on mortality rates. Using extensive national data on mortality, air quality and socio-economic status regression analyses are used to study the influence of air quality on mortality. The analytic methods and data are selected in such a way that direct comparisons can be made with other ecologic regression studies of mortality and air quality. Analyses are performed by use of two types of geographic areas, age-specific mortality of both males and females and three pollutants (total suspended particulates, sulfur dioxide and nitrogen dioxide). The overall results indicate no persuasive evidence exists of a link between air quality and general mortality levels. Additionally, a lack of consistency between the present results and previous published work is noted. Overall, it is concluded that linear regression analysis applied to nationally collected ecologic data cannot be used to usefully infer a causal relationship between air quality and mortality which is in direct contradiction to other major published studies. PMID:6734568
Effects of neighbourhood-level educational attainment on HIV prevalence among young women in Zambia.
Kayeyi, Nkomba; Sandøy, Ingvild F; Fylkesnes, Knut
2009-08-25
Investigations of the association between socio-economic position indicators and HIV in East, Central and Southern Africa have chiefly focused on factors that pertain to individual-level characteristics. This study investigated the effect of neighbourhood educational attainment on HIV prevalence among young women in selected urban and rural areas in Zambia. This study re-analysed data from a cross-sectional population survey conducted in Zambia in 2003. The analyses were restricted to women aged 15-24 years (n = 1295). Stratified random cluster sampling was used to select 10 urban and 10 rural clusters. A measure for neighbourhood-level educational attainment was constructed by aggregating individual-level years-in-school. Multi-level mixed effects regression models were run to examine the neighbourhood-level educational effect on HIV prevalence after adjusting for individual-level underlying variables (education, currently a student, marital status) and selected proximate determinants (ever given birth, sexual activity, lifetime sexual partners). HIV prevalence among young women aged 15-24 years was 12.5% in the urban and 6.8% in the rural clusters. Neighbourhood educational attainment was found to be a strong determinant of HIV infection in both urban and rural population, i.e. HIV prevalence decreased substantially by increasing level of neighbourhood education. The likelihood of infection in low vs. high educational attainment of neighbourhoods was 3.4 times among rural women and 1.8 times higher among the urban women after adjusting for age and other individual-level underlying variables, including education. However, the association was not significant for urban young women after this adjustment. After adjusting for level of education in the neighbourhood, the effect of the individual-level education differed by residence, i.e. a strong protective effect among urban women whereas tending to be a risk factor among rural women. The findings suggested structural effects on HIV prevalence. Future research should include more detailed mapping of neighbourhood factors of relevance to HIV transmission as part of the effort to better understand the causal mechanisms involved.
Foong, Hui Foh; Hamid, Tengku Aizan; Ibrahim, Rahimah; Haron, Sharifah Azizah
2018-04-01
Research has found that depression in later life is associated with cognitive impairment. Thus, the mechanism to reduce the effect of depression on cognitive function is warranted. In this paper, we intend to examine whether intrinsic religiosity mediates the association between depression and cognitive function. The study included 2322 nationally representative community-dwelling elderly in Malaysia, randomly selected through a multi-stage proportional cluster random sampling from Peninsular Malaysia. The elderly were surveyed on socio-demographic information, cognitive function, depression and intrinsic religiosity. A four-step moderated hierarchical regression analysis was employed to test the moderating effect. Statistical analyses were performed using SPSS (version 15.0). Bivariate analyses showed that both depression and intrinsic religiosity had significant relationships with cognitive function. In addition, four-step moderated hierarchical regression analysis revealed that the intrinsic religiosity moderated the association between depression and cognitive function, after controlling for selected socio-demographic characteristics. Intrinsic religiosity might reduce the negative effect of depression on cognitive function. Professionals who are working with depressed older adults should seek ways to improve their intrinsic religiosity as one of the strategies to prevent cognitive impairment.
Habitat features and predictive habitat modeling for the Colorado chipmunk in southern New Mexico
Rivieccio, M.; Thompson, B.C.; Gould, W.R.; Boykin, K.G.
2003-01-01
Two subspecies of Colorado chipmunk (state threatened and federal species of concern) occur in southern New Mexico: Tamias quadrivittatus australis in the Organ Mountains and T. q. oscuraensis in the Oscura Mountains. We developed a GIS model of potentially suitable habitat based on vegetation and elevation features, evaluated site classifications of the GIS model, and determined vegetation and terrain features associated with chipmunk occurrence. We compared GIS model classifications with actual vegetation and elevation features measured at 37 sites. At 60 sites we measured 18 habitat variables regarding slope, aspect, tree species, shrub species, and ground cover. We used logistic regression to analyze habitat variables associated with chipmunk presence/absence. All (100%) 37 sample sites (28 predicted suitable, 9 predicted unsuitable) were classified correctly by the GIS model regarding elevation and vegetation. For 28 sites predicted suitable by the GIS model, 18 sites (64%) appeared visually suitable based on habitat variables selected from logistic regression analyses, of which 10 sites (36%) were specifically predicted as suitable habitat via logistic regression. We detected chipmunks at 70% of sites deemed suitable via the logistic regression models. Shrub cover, tree density, plant proximity, presence of logs, and presence of rock outcrop were retained in the logistic model for the Oscura Mountains; litter, shrub cover, and grass cover were retained in the logistic model for the Organ Mountains. Evaluation of predictive models illustrates the need for multi-stage analyses to best judge performance. Microhabitat analyses indicate prospective needs for different management strategies between the subspecies. Sensitivities of each population of the Colorado chipmunk to natural and prescribed fire suggest that partial burnings of areas inhabited by Colorado chipmunks in southern New Mexico may be beneficial. These partial burnings may later help avoid a fire that could substantially reduce habitat of chipmunks over a mountain range.
Predictors of attachment security in preschool children from intact and divorced families.
Nair, Hira; Murray, Ann D
2005-09-01
The authors selected 58 mother-child dyads from divorced and intact families to participate in a study on the impact of divorce on preschoolers' attachment security. The authors explored pathways that lead to security of attachment. They found that mothers from divorced families were younger, had lower income levels, and had lower levels of education compared with their intact counterparts. Divorced mothers also reported significantly higher levels of stress, depression, need for social support, and conflict with their spouses. Mothers from intact families were more likely to use positive (authoritative) parenting styles compared with divorced mothers. Children in the divorced group had lower security scores on the Attachment Q-Set instrument (E. Waters, 1995). Regression analyses indicated that parenting style made a direct (independent) contribution to attachment security. In addition, temperament was related to attachment security, but temperament did not diminish the association of parenting style with attachment security. Furthermore, regression analyses indicated that the relationship of divorce to attachment security was mediated by parenting style.
Agreement between methods of measurement of mean aortic wall thickness by MRI.
Rosero, Eric B; Peshock, Ronald M; Khera, Amit; Clagett, G Patrick; Lo, Hao; Timaran, Carlos
2009-03-01
To assess the agreement between three methods of calculation of mean aortic wall thickness (MAWT) using magnetic resonance imaging (MRI). High-resolution MRI of the infrarenal abdominal aorta was performed on 70 subjects with a history of coronary artery disease who were part of a multi-ethnic population-based sample. MAWT was calculated as the mean distance between the adventitial and luminal aortic boundaries using three different methods: average distance at four standard positions (AWT-4P), average distance at 100 automated positions (AWT-100P), and using a mathematical computation derived from the total vessel and luminal areas (AWT-VA). Bland-Altman plots and Passing-Bablok regression analyses were used to assess agreement between methods. Bland-Altman analyses demonstrated a positive bias of 3.02+/-7.31% between the AWT-VA and the AWT-4P methods, and of 1.76+/-6.82% between the AWT-100P and the AWT-4P methods. Passing-Bablok regression analyses demonstrated constant bias between the AWT-4P method and the other two methods. Proportional bias was, however, not evident among the three methods. MRI methods of measurement of MAWT using a limited number of positions of the aortic wall systematically underestimate the MAWT value compared with the method that calculates MAWT from the vessel areas. Copyright (c) 2009 Wiley-Liss, Inc.
Terrelonge, Dion N; Fugard, Andrew Jb
2017-10-01
The rated severity of child mental health problems depends on who is doing the rating, whether child, carer or clinician. It is important to know how these ratings relate to each other. To investigate to what extent clinicians' views are associated with carers' and young people's views in routine care in the United Kingdom. Ratings of clinician and parent/child viewpoints from a large Child and Adolescent Mental Health Services (CAMHS) sample ( ns 1773-47,299), as measured by the Children's Global Assessment Scale (CGAS) and Strengths and Difficulties Questionnaire (SDQ) respectively, were analysed. The parent SDQ added value score (AVS), which adjusts for regression to the mean and other non-treatment change, was also included in the analyses. Small-to-medium correlations were found between family and clinician ratings; however, ratings diverged for the lowest-function CGAS bands. Regression analyses showed that pro-social ratings from both child and parent contributed to clinician ratings. Knowing child-reported emotional problem severity made parent ratings of emotions irrelevant to clinician judgements. There was a positive association between SDQ AVS and CGAS; as hypothesised, CGAS showed more change than the SDQ AVS, suggesting that clinicians over-estimate change. This study shows the importance of multi-informant data gathering and the integration of multiple views by clinicians when monitoring outcomes.
Dietary phytoestrogens and plasma lipids in Dutch postmenopausal women; a cross-sectional study.
Kreijkamp-Kaspers, Sanne; Kok, Linda; Bots, Michiel L; Grobbee, Diederick E; van der Schouw, Yvonne T
2005-01-01
Isoflavone supplementation in high doses is associated with plasma lipid, glucose and insulin levels. Little is known about the effects of intake within the range of western diets on these endpoints. We conducted a population-based cross-sectional study in 301 women aged 60-75 years. Dietary isoflavone and lignan intake was assessed with a food frequency questionnaire covering habitual diet during the year preceding enrollment. The outcome measures were total cholesterol, LDL-cholesterol, HDL-cholesterol, triglycerides, Lp(a), fasting glucose and insulin levels. Data were analysed using linear regression and logistic regression models. In the analyses we adjusted for a wide range of potential confounders. High intake of isoflavones was associated with lower Lp(a) levels (tertile three versus tertile one: odds ratio 0.36, 95% CI 0.16; 0.80). No relation was found between blood levels and the other plasma lipids, glucose or insulin was found. The results of this study suggest that an effect of dietary phytoestrogen intake at low levels on plasma lipid levels is of limited magnitude. It is premature to advise postmenopausal women with low phytoestrogen intake to change their diet towards a phytoestrogen rich diet with the sole aim to prevent cardiovascular disease.
Improving patient survival with the colorectal cancer multi-disciplinary team.
MacDermid, E; Hooton, G; MacDonald, M; McKay, G; Grose, D; Mohammed, N; Porteous, C
2009-03-01
There is little information on the impact of the colorectal multi-disciplinary team (MDT) in the United Kingdom. Our single operator presented his patients before and after the inception of an MDT meeting in June 2002. The aim of this study was to assess the effect of this on his patients' survival, and trends in the use of adjuvant chemotherapy. Data were collected on all patients (n = 310) undergoing colectomy for colorectal cancer by one surgeon. Excluding patients with Dukes A stage, the pre-MDT cohort from January 1997 to May 2002 was 176 and the post-MDT cohort from June 2002 to December 2005 was 134. Three-year survival rates were calculated using Kaplan-Meier life table analysis. Prognostic factors were analysed using Cox-proportional hazard regression, and chemotherapy data analysed using the chi-squared test. Independent prognostic indicators of chemotherapy prescription were examined using binary logistic testing. MDT status was shown to be an independent predictor of survival on hazard regression analysis (P = 0.044). A significantly greater number of patients were prescribed adjuvant chemotherapy in the post-MDT cohort (P = 0.0002). MDT status was shown to be a significant prognostic indicator of chemotherapy prescription (P < 0.0001). Three-year survival for Dukes C patients was 58% in the pre-MDT group, and 66% in the post-MDT group (P = 0.023). There was a significant increase in patients undergoing adjuvant postoperative chemotherapy after the inception of the MDT. This was associated with a significant survival benefit in patients with Dukes C disease. The data suggest that the MDT process has resulted in an increase in the prescription of adjuvant chemotherapy, with 3-year survival being greater after its inception.
Are Women More Likely to Be Hired or Promoted into Management Positions?
ERIC Educational Resources Information Center
Lyness, Karen S.; Judiesch, Michael K.
1999-01-01
In a three-year study of 30,996 financial-services managers, logistic regression analyses showed that women were more likely to be promoted rather than hired into management positions. Relative to men, women in higher-level positions received fewer promotions than women in lower-level positions. (63 references) (SK)
Converting positive and negative symptom scores between PANSS and SAPS/SANS.
van Erp, Theo G M; Preda, Adrian; Nguyen, Dana; Faziola, Lawrence; Turner, Jessica; Bustillo, Juan; Belger, Aysenil; Lim, Kelvin O; McEwen, Sarah; Voyvodic, James; Mathalon, Daniel H; Ford, Judith; Potkin, Steven G; Fbirn
2014-01-01
The Scale for the Assessment of Positive Symptoms (SAPS), the Scale for the Assessment of Negative Symptoms (SANS), and the Positive and Negative Syndrome Scale for Schizophrenia (PANSS) are the most widely used schizophrenia symptom rating scales, but despite their co-existence for 25 years no easily usable between-scale conversion mechanism exists. The aim of this study was to provide equations for between-scale symptom rating conversions. Two-hundred-and-five schizophrenia patients [mean age±SD=39.5±11.6, 156 males] were assessed with the SANS, SAPS, and PANSS. Pearson's correlations between symptom scores from each of the scales were computed. Linear regression analyses, on data from 176 randomly selected patients, were performed to derive equations for converting ratings between the scales. Intraclass correlations, on data from the remaining 29 patients, not part of the regression analyses, were performed to determine rating conversion accuracy. Between-scale positive and negative symptom ratings were highly correlated. Intraclass correlations between the original positive and negative symptom ratings and those obtained via conversion of alternative ratings using the conversion equations were moderate to high (ICCs=0.65 to 0.91). Regression-based equations may be useful for conversion between schizophrenia symptom severity as measured by the SANS/SAPS and PANSS, though additional validation is warranted. This study's conversion equations, implemented at http:/converteasy.org, may aid in the comparison of medication efficacy studies, in meta- and mega-analyses examining symptoms as moderator variables, and in retrospective combination of symptom data in multi-center data sharing projects that need to pool symptom rating data when such data are obtained using different scales. Copyright © 2013 Elsevier B.V. All rights reserved.
Alexander, Paul E; Bonner, Ashley J; Agarwal, Arnav; Li, Shelly-Anne; Hariharan, Abishek; Izhar, Zain; Bhatnagar, Neera; Alba, Carolina; Akl, Elie A; Fei, Yutong; Guyatt, Gordon H; Beyene, Joseph
2016-06-01
Prior studies regarding whether single-center trial estimates are larger than multi-center are equivocal. We examined the extent to which single-center trials yield systematically larger effects than multi-center trials. We searched the 119 core clinical journals and the Cochrane Database of Systematic Reviews for meta-analyses (MAs) of randomized controlled trials (RCTs) published during 2012. In this meta-epidemiologic study, for binary variables, we computed the pooled ratio of ORs (RORs), and for continuous outcomes mean difference in standardized mean differences (SMDs), we conducted weighted random-effects meta-regression and random-effects MA modeling. Our primary analyses were restricted to MAs that included at least five RCTs and in which at least 25% of the studies used each of single trial center (SC) and more trial center (MC) designs. We identified 81 MAs for the odds ratio (OR) and 43 for the SMD outcome measures. Based on our analytic plan, our primary analysis (core) is based on 25 MAs/241 RCTs (binary outcome) and 18 MAs/173 RCTs (continuous outcome). Based on the core analysis, we found no difference in magnitude of effect between SC and MC for binary outcomes [RORs: 1.02; 95% confidence interval (CI): 0.83, 1.24; I(2) 20.2%]. Effect sizes were systematically larger for SC than MC for the continuous outcome measure (mean difference in SMDs: -0.13; 95% CI: -0.21, -0.05; I(2) 0%). Our results do not support prior findings of larger effects in SC than MC trials addressing binary outcomes but show a very similar small increase in effect in SC than MC trials addressing continuous outcomes. Authors of systematic reviews would be wise to include all trials irrespective of SC vs. MC design and address SC vs. MC status as a possible explanation of heterogeneity (and consider sensitivity analyses). Copyright © 2015 Elsevier Inc. All rights reserved.
Radon-222 concentrations in ground water and soil gas on Indian reservations in Wisconsin
DeWild, John F.; Krohelski, James T.
1995-01-01
For sites with wells finished in the sand and gravel aquifer, the coefficient of determination (R2) of the regression of concentration of radon-222 in ground water as a function of well depth is 0.003 and the significance level is 0.32, which indicates that there is not a statistically significant relation between radon-222 concentrations in ground water and well depth. The coefficient of determination of the regression of radon-222 in ground water and soil gas is 0.19 and the root mean square error of the regression line is 271 picocuries per liter. Even though the significance level (0.036) indicates a statistical relation, the root mean square error of the regression is so large that the regression equation would not give reliable predictions. Because of an inadequate number of samples, similar statistical analyses could not be performed for sites with wells finished in the crystalline and sedimentary bedrock aquifers.
Lee, Jung-Seok
2015-01-01
Background The rise in dengue fever cases and the absence of dengue vaccines will likely cause governments to consider various types of effective means for controlling the disease. Given strong public interests in potential dengue vaccines, it is essential to understand the private economic benefits of dengue vaccines for accelerated introduction of vaccines into the public sector program and private markets of high-risk countries. Methodology/Principal Findings A contingent valuation study for a hypothetical dengue vaccine was administered to 400 households in a multi-country setting: Vietnam, Thailand, and Colombia. All respondents received a description of the hypothetical dengue vaccine scenarios of 70% or 95% effectiveness for 10 or 30 years with a three dose series. Five price points were determined after pilot tests in order to reflect different local situations such as household income levels and general perceptions towards dengue fever. We adopted either Poisson or negative binomial regression models to calculate average willingness-to-pay (WTP), as well as median WTP. We found that there is a significant demand for dengue vaccines. The parametric median WTP is $26.4 ($8.8 per dose) in Vietnam, $70.3 ($23.4 per dose) in Thailand, and $23 ($7.7 per dose) in Colombia. Our study also suggests that respondents place more value on vaccinating young children than school age children and adults. Conclusions/Significance Knowing that dengue vaccines are not yet available, our study provides critical information to both public and private sectors. The study results can be used to ensure broad coverage with an affordable price and incorporated into cost benefit analyses, which can inform prioritization of alternative health interventions at the national level. PMID:26030922
Factors associated with sexual and reproductive health stigma among adolescent girls in Ghana.
Hall, Kelli Stidham; Morhe, Emmanuel; Manu, Abubakar; Harris, Lisa H; Ela, Elizabeth; Loll, Dana; Kolenic, Giselle; Dozier, Jessica L; Challa, Sneha; Zochowski, Melissa K; Boakye, Andrew; Adanu, Richard; Dalton, Vanessa K
2018-01-01
Using our previously developed and tested Adolescent Sexual and Reproductive Health (SRH) Stigma Scale, we investigated factors associated with perceived SRH stigma among adolescent girls in Ghana. We drew upon data from our survey study of 1,063 females 15-24yrs recruited from community- and clinic-based sites in two Ghanaian cities. Our Adolescent SRH Stigma Scale comprised 20 items and 3 sub-scales (Internalized, Enacted, Lay Attitudes) to measure stigma occurring with sexual activity, contraceptive use, pregnancy, abortion and family planning service use. We assessed relationships between a comprehensive set of demographic, health and social factors and SRH Stigma with multi-level multivariable linear regression models. In unadjusted bivariate analyses, compared to their counterparts, SRH stigma scores were higher among girls who were younger, Accra residents, Muslim, still in/dropped out of secondary school, unemployed, reporting excellent/very good health, not in a relationship, not sexually experienced, never received family planning services, never used contraception, but had been pregnant (all p-values <0.05). In multivariable models, higher SRH stigma scores were associated with history of pregnancy (β = 1.53, CI = 0.51,2.56) and excellent/very good self-rated health (β = 0.89, CI = 0.20,1.58), while lower stigma scores were associated with older age (β = -0.17, 95%CI = -0.24,-0.09), higher educational attainment (β = -1.22, CI = -1.82,-0.63), and sexual intercourse experience (β = -1.32, CI = -2.10,-0.55). Findings provide insight into factors contributing to SRH stigma among this young Ghanaian female sample. Further research disentangling the complex interrelationships between SRH stigma, health, and social context is needed to guide multi-level interventions to address SRH stigma and its causes and consequences for adolescents worldwide.
Factors associated with sexual and reproductive health stigma among adolescent girls in Ghana
Morhe, Emmanuel; Manu, Abubakar; Harris, Lisa H.; Ela, Elizabeth; Loll, Dana; Kolenic, Giselle; Dozier, Jessica L.; Challa, Sneha; Zochowski, Melissa K.; Boakye, Andrew; Adanu, Richard; Dalton, Vanessa K.
2018-01-01
Objective Using our previously developed and tested Adolescent Sexual and Reproductive Health (SRH) Stigma Scale, we investigated factors associated with perceived SRH stigma among adolescent girls in Ghana. Methods We drew upon data from our survey study of 1,063 females 15-24yrs recruited from community- and clinic-based sites in two Ghanaian cities. Our Adolescent SRH Stigma Scale comprised 20 items and 3 sub-scales (Internalized, Enacted, Lay Attitudes) to measure stigma occurring with sexual activity, contraceptive use, pregnancy, abortion and family planning service use. We assessed relationships between a comprehensive set of demographic, health and social factors and SRH Stigma with multi-level multivariable linear regression models. Results In unadjusted bivariate analyses, compared to their counterparts, SRH stigma scores were higher among girls who were younger, Accra residents, Muslim, still in/dropped out of secondary school, unemployed, reporting excellent/very good health, not in a relationship, not sexually experienced, never received family planning services, never used contraception, but had been pregnant (all p-values <0.05). In multivariable models, higher SRH stigma scores were associated with history of pregnancy (β = 1.53, CI = 0.51,2.56) and excellent/very good self-rated health (β = 0.89, CI = 0.20,1.58), while lower stigma scores were associated with older age (β = -0.17, 95%CI = -0.24,-0.09), higher educational attainment (β = -1.22, CI = -1.82,-0.63), and sexual intercourse experience (β = -1.32, CI = -2.10,-0.55). Conclusions Findings provide insight into factors contributing to SRH stigma among this young Ghanaian female sample. Further research disentangling the complex interrelationships between SRH stigma, health, and social context is needed to guide multi-level interventions to address SRH stigma and its causes and consequences for adolescents worldwide. PMID:29608595
Lee, Jung-Seok; Mogasale, Vittal; Lim, Jacqueline K; Carabali, Mabel; Sirivichayakul, Chukiat; Anh, Dang Duc; Lee, Kang-Sung; Thiem, Vu Dinh; Limkittikul, Kriengsak; Tho, Le Huu; Velez, Ivan D; Osorio, Jorge E; Chanthavanich, Pornthep; da Silva, Luiz J; Maskery, Brian A
2015-01-01
The rise in dengue fever cases and the absence of dengue vaccines will likely cause governments to consider various types of effective means for controlling the disease. Given strong public interests in potential dengue vaccines, it is essential to understand the private economic benefits of dengue vaccines for accelerated introduction of vaccines into the public sector program and private markets of high-risk countries. A contingent valuation study for a hypothetical dengue vaccine was administered to 400 households in a multi-country setting: Vietnam, Thailand, and Colombia. All respondents received a description of the hypothetical dengue vaccine scenarios of 70% or 95% effectiveness for 10 or 30 years with a three dose series. Five price points were determined after pilot tests in order to reflect different local situations such as household income levels and general perceptions towards dengue fever. We adopted either Poisson or negative binomial regression models to calculate average willingness-to-pay (WTP), as well as median WTP. We found that there is a significant demand for dengue vaccines. The parametric median WTP is $26.4 ($8.8 per dose) in Vietnam, $70.3 ($23.4 per dose) in Thailand, and $23 ($7.7 per dose) in Colombia. Our study also suggests that respondents place more value on vaccinating young children than school age children and adults. Knowing that dengue vaccines are not yet available, our study provides critical information to both public and private sectors. The study results can be used to ensure broad coverage with an affordable price and incorporated into cost benefit analyses, which can inform prioritization of alternative health interventions at the national level.
Prakash, Ravi; Beattie, Tara; Javalkar, Prakash; Bhattacharjee, Parinita; Ramanaik, Satyanarayana; Thalinja, Raghavendra; Murthy, Srikanta; Davey, Calum; Blanchard, James; Watts, Charlotte; Collumbien, Martine; Moses, Stephen; Heise, Lori; Isac, Shajy
2017-12-01
Secondary education among lower caste adolescent girls living in rural Karnataka, South India, is characterized by high rates of school drop-out and absenteeism. A cross-sectional baseline survey (N=2275) was conducted in 2014 as part of a cluster-randomized control trial among adolescent girls (13-14 year) and their families from marginalized communities in two districts of north Karnataka. Bivariate and multivariate logistic regression models were used. Overall, 8.7% girls reported secondary school dropout and 8.1% reported frequent absenteeism (past month). In adjusted analyses, economic factors (household poverty; girls' work-related migration), social norms and practices (child marriage; value of girls' education), and school-related factors (poor learning environment and bullying/harassment at school) were associated with an increased odds of school dropout and absenteeism. Interventions aiming to increase secondary school retention among marginalized girls may require a multi-level approach, with synergistic components that address social, structural and economic determinants of school absenteeism and dropout. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.
Rekker, Roderik; Keijsers, Loes; Branje, Susan; Koot, Hans; Meeus, Wim
2017-08-01
This six-wave multi-informant longitudinal study on Dutch adolescents (N = 824; age 12-18) examined the interplay of socioeconomic status with parental monitoring in predicting minor delinquency. Fixed-effects negative binomial regression analyses revealed that this interplay is different within adolescents across time than between adolescents. Between individuals, parental solicitation and control were not significantly associated with delinquency after controlling for SES: Adolescents whose parents exercised more monitoring did not offend less than others. Within individuals, higher levels of parental control were unexpectedly associated with more delinquency, but this relation was dependent on SES: Low-SES adolescents, but not high-SES adolescents, offended more during periods in which their parents exercised more control than during other periods with less control. In contrast to earlier work, this finding suggests that monitoring could be least effective when needed most. Low-SES parents might not use monitoring effectively and become overcontrolling when their child goes astray. Copyright © 2017 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.
Factors associated with interest in novel interfaces for upper limb prosthesis control
Engdahl, Susannah M.; Chestek, Cynthia A.; Kelly, Brian; Davis, Alicia
2017-01-01
Background Surgically invasive interfaces for upper limb prosthesis control may allow users to operate advanced, multi-articulated devices. Given the potential medical risks of these invasive interfaces, it is important to understand what factors influence an individual’s decision to try one. Methods We conducted an anonymous online survey of individuals with upper limb loss. A total of 232 participants provided personal information (such as age, amputation level, etc.) and rated how likely they would be to try noninvasive (myoelectric) and invasive (targeted muscle reinnervation, peripheral nerve interfaces, cortical interfaces) interfaces for prosthesis control. Bivariate relationships between interest in each interface and 16 personal descriptors were examined. Significant variables from the bivariate analyses were then entered into multiple logistic regression models to predict interest in each interface. Results While many of the bivariate relationships were significant, only a few variables remained significant in the regression models. The regression models showed that participants were more likely to be interested in all interfaces if they had unilateral limb loss (p ≤ 0.001, odds ratio ≥ 2.799). Participants were more likely to be interested in the three invasive interfaces if they were younger (p < 0.001, odds ratio ≤ 0.959) and had acquired limb loss (p ≤ 0.012, odds ratio ≥ 3.287). Participants who used a myoelectric device were more likely to be interested in myoelectric control than those who did not (p = 0.003, odds ratio = 24.958). Conclusions Novel prosthesis control interfaces may be accepted most readily by individuals who are young, have unilateral limb loss, and/or have acquired limb loss However, this analysis did not include all possible factors that may have influenced participant’s opinions on the interfaces, so additional exploration is warranted. PMID:28767716
Factors associated with interest in novel interfaces for upper limb prosthesis control.
Engdahl, Susannah M; Chestek, Cynthia A; Kelly, Brian; Davis, Alicia; Gates, Deanna H
2017-01-01
Surgically invasive interfaces for upper limb prosthesis control may allow users to operate advanced, multi-articulated devices. Given the potential medical risks of these invasive interfaces, it is important to understand what factors influence an individual's decision to try one. We conducted an anonymous online survey of individuals with upper limb loss. A total of 232 participants provided personal information (such as age, amputation level, etc.) and rated how likely they would be to try noninvasive (myoelectric) and invasive (targeted muscle reinnervation, peripheral nerve interfaces, cortical interfaces) interfaces for prosthesis control. Bivariate relationships between interest in each interface and 16 personal descriptors were examined. Significant variables from the bivariate analyses were then entered into multiple logistic regression models to predict interest in each interface. While many of the bivariate relationships were significant, only a few variables remained significant in the regression models. The regression models showed that participants were more likely to be interested in all interfaces if they had unilateral limb loss (p ≤ 0.001, odds ratio ≥ 2.799). Participants were more likely to be interested in the three invasive interfaces if they were younger (p < 0.001, odds ratio ≤ 0.959) and had acquired limb loss (p ≤ 0.012, odds ratio ≥ 3.287). Participants who used a myoelectric device were more likely to be interested in myoelectric control than those who did not (p = 0.003, odds ratio = 24.958). Novel prosthesis control interfaces may be accepted most readily by individuals who are young, have unilateral limb loss, and/or have acquired limb loss However, this analysis did not include all possible factors that may have influenced participant's opinions on the interfaces, so additional exploration is warranted.
Parathyroid Hormone Levels and Cognition
NASA Technical Reports Server (NTRS)
Burnett, J.; Smith, S.M.; Aung, K.; Dyer, C.
2009-01-01
Hyperparathyroidism is a well-recognized cause of impaired cognition due to hypercalcemia. However, recent studies have suggested that perhaps parathyroid hormone itself plays a role in cognition, especially executive dysfunction. The purpose of this study was to explore the relationship of parathyroid hormone levels in a study cohort of elders with impaied cognition. Methods: Sixty community-living adults, 65 years of age and older, reported to Adult Protective Services for self-neglect and 55 controls matched (on age, ethnicity, gender and socio-economic status) consented and participated in this study. The research team conducted in-home comprehensive geriatric assessments which included the Mini-mental state exam (MMSE), the 15-item geriatric depression scale (GDS) , the Wolf-Klein clock test and a comprehensive nutritional panel, which included parathyroid hormone and ionized calcium. Students t tests and linear regression analyses were performed to assess for bivariate associations. Results: Self-neglecters (M = 73.73, sd=48.4) had significantly higher PTH levels compared to controls (M =47.59, sd=28.7; t=3.59, df=98.94, p<.01). There was no significant group difference in ionized calcium levels. Overall, PTH was correlated with the MMSE (r=-.323, p=.001). Individual regression analyses revealed a statistically significant correlation between PTH and MMSE in the self-neglect group (r=-.298, p=.024) and this remained significant after controlling for ionized calcium levels in the regression. No significant associations were revealed in the control group or among any of the other cognitive measures. Conclusion: Parathyroid hormone may be associated with cognitive performance.
Friedrich, Miriam; Rüst, Christoph A.; Rosemann, Thomas; Knechtle, Patrizia; Barandun, Ursula; Lepers, Romuald; Knechtle, Beat
2013-01-01
Purpose Lower limb skin-fold thicknesses have been differentially associated with sex in elite runners. Front thigh and medial calf skin-fold appear to be related to 1,500m and 10,000m time in men but 400m time in women. The aim of the present study was to compare anthropometric and training characteristics in recreational female and male half-marathoners. Methods The association between both anthropometry and training characteristics and race time was investigated in 83 female and 147 male recreational half marathoners using bi- and multi-variate analyses. Results In men, body fat percentage (β=0.6), running speed during training (β=-3.7), and body mass index (β=1.9) were related to half-marathon race time after multi-variate analysis. After exclusion of body mass index, r2 decreased from 0.51 to 0.49, but body fat percentage (β=0.8) and running speed during training (β=-4.1) remained predictive. In women, body fat percentage (β=0.75) and speed during training (β=-6.5) were related to race time (r2=0.73). For women, the exclusion of body mass index had no consequence on the predictive variables for half-marathon race time. Conclusion To summarize, in both female and male recreational half-marathoners, both body fat percentage and running speed during training sessions were related to half-marathon race times when corrected with co-variates after multi-variate regression analyses. PMID:24868427
Friedrich, Miriam; Rüst, Christoph A; Rosemann, Thomas; Knechtle, Patrizia; Barandun, Ursula; Lepers, Romuald; Knechtle, Beat
2014-03-01
Lower limb skin-fold thicknesses have been differentially associated with sex in elite runners. Front thigh and medial calf skin-fold appear to be related to 1,500m and 10,000m time in men but 400m time in women. The aim of the present study was to compare anthropometric and training characteristics in recreational female and male half-marathoners. The association between both anthropometry and training characteristics and race time was investigated in 83 female and 147 male recreational half marathoners using bi- and multi-variate analyses. In men, body fat percentage (β=0.6), running speed during training (β=-3.7), and body mass index (β=1.9) were related to half-marathon race time after multi-variate analysis. After exclusion of body mass index, r (2) decreased from 0.51 to 0.49, but body fat percentage (β=0.8) and running speed during training (β=-4.1) remained predictive. In women, body fat percentage (β=0.75) and speed during training (β=-6.5) were related to race time (r (2) =0.73). For women, the exclusion of body mass index had no consequence on the predictive variables for half-marathon race time. To summarize, in both female and male recreational half-marathoners, both body fat percentage and running speed during training sessions were related to half-marathon race times when corrected with co-variates after multi-variate regression analyses.
Koblin, Beryl; Chin, John; Beard, John; Blaney, Shannon; Halkitis, Perry; Vlahov, David; Galea, Sandro
2014-01-01
There is growing evidence that the neighborhood environment influences sexual behavior and related outcomes, but little work has focused specifically on men who have sex with men (MSM). Using interview data from a probability sample of 385 young MSM living in New York City, recruited at public venues in 1999 and 2000 as part of the Young Men’s Survey-New York City, and data on neighborhood characteristics obtained from the U.S. Census 2000, we conducted multi-level analyses of the associations between neighborhood-level characteristics and consistent condom use during anal intercourse, while controlling for individual-level sociodemographic and other factors. After adjusting for individual-level factors, neighborhood-level gay presence remained significantly and positively associated with consistent condom use during anal intercourse. This finding suggests that neighborhoods with a significant gay presence may have norms that act to discourage high risk sexual activity. PMID:18712593
Howarth, Ana; Quesada, Jose; Mills, Peter R
2017-01-01
Health risk assessments (HRA) are used by many organisations as a basis for developing relevant and targeted employee health and well-being interventions. However, many HRA's have a western-centric focus and therefore it is unclear whether the results can be directly extrapolated to those from non-western countries. More information regarding the differences in the associations between country status and health risks is needed along with a more global perspective of employee health risk factors and well-being overall. Therefore we aimed to i) quantify and compare associations for a number of health risk factors based on country status, and then ii) explore which characteristics can aid better prediction of well-being levels and in turn workplace productivity globally. Online employee HRA data collected from 254 multi-national companies, for the years 2013 through 2016 was analysed (n = 117,274). Multiple linear regression models were fitted, adjusting for age and gender, to quantify associations between country status and health risk factors. Separate regression models were used to assess the prediction of well-being measures related to productivity. On average, the developing countries were comprised of younger individuals with lower obesity rates and markedly higher job satisfaction compared to their developed country counterparts. However, they also reported higher levels of anxiety and depression, a greater number of health risks and lower job effectiveness. Assessment of key factors related to productivity found that region of residency was the biggest predictor of presenteeism and poor pain management was the biggest predictor of absenteeism. Clear differences in health risks exist between employees from developed and developing countries and these should be considered when addressing well-being and productivity in the global workforce.
Alcohol Control Policies and Alcohol Consumption by Youth: A Multi-National Study
Paschall, Mallie J.; Grube, Joel W.; Kypri, Kypros
2009-01-01
Aims The study examined relationships between alcohol control policies and adolescent alcohol use in 26 countries. Design Cross-sectional analyses of alcohol policy ratings based on the Alcohol Policy Index (API), per capita consumption, and national adolescent survey data. Setting Data are from 26 countries. Participants Adolescents (15-17 years old) who participated in the 2003 ESPAD (European countries) or national secondary school surveys in Spain, Canada, Australia, New Zealand and the USA. Measurements Alcohol control policy ratings based on the API; prevalence of alcohol use, heavy drinking, and first drink by age 13 based on national secondary school surveys; per capita alcohol consumption for each country in 2003. Analysis Correlational and linear regression analyses were conducted to examine relationships between alcohol control policy ratings and past-30-day prevalence of adolescent alcohol use, heavy drinking, and having first drink by age 13. Per capita consumption of alcohol was included as a covariate in regression analyses. Findings More comprehensive API ratings and alcohol availability and advertising control ratings were inversely related to the past-30-day prevalence of alcohol use and prevalence rates for drinking 3-5 times and 6 or more times in the past 30 days. Alcohol advertising control was also inversely related to the prevalence of past-30-day heavy drinking and having first drink by age 13. Most of the relationships between API, alcohol availability and advertising control and drinking prevalence rates were attenuated and no longer statistically significant when controlling for per capita consumption in regression analyses, suggesting that alcohol use in the general population may confound or mediate observed relationships between alcohol control policies and youth alcohol consumption. Several of the inverse relationships remained statistically significant when controlling for per capita consumption. Conclusions More comprehensive and stringent alcohol control policies, particularly policies affecting alcohol availability and marketing, are associated with lower prevalence and frequency of adolescent alcohol consumption and age of first alcohol use. PMID:19832785
Monitoring Building Deformation with InSAR: Experiments and Validation.
Yang, Kui; Yan, Li; Huang, Guoman; Chen, Chu; Wu, Zhengpeng
2016-12-20
Synthetic Aperture Radar Interferometry (InSAR) techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS) regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE) indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated.
Design and Fabrication of Orthotropic Deck Details
DOT National Transportation Integrated Search
2016-02-01
The objectives of the research were to verify the design and fabrication of the orthotropic deck details proposed for the lift bridge, for infinite fatigue life. Multi-level 3D finite element analyses (FEA) of the proposed deck were performed to dete...
Markowitz, Sara; Komro, Kelli A; Livingston, Melvin D; Lenhart, Otto; Wagenaar, Alexander C
2017-12-01
The purpose of this paper is to investigate the effects of state-level Earned Income Tax Credit (EITC) laws in the U.S. on maternal health behaviors and infant health outcomes. Using multi-state, multi-year difference-in-differences analyses, we estimated effects of state EITC generosity on maternal health behaviors, birth weight and gestation weeks. We find little difference in maternal health behaviors associated with state-level EITC. In contrast, results for key infant health outcomes of birth weight and gestation weeks show small improvements in states with EITCs, with larger effects seen among states with more generous EITCs. Our results provide evidence for important health benefits of state-level EITC policies. Copyright © 2017 Elsevier Ltd. All rights reserved.
Valle, M; Witt, L A
2001-06-01
By using regression analyses on data from 355 full-time employees of a customer-service organization in the eastern United States, the authors tested the hypothesis that perceptions of organizational politics are more strongly related to job dissatisfaction among individuals who perceive low levels of teamwork importance than among those who perceive high levels of teamwork importance. Hierarchical moderated regression analysis of the data revealed that the moderating effect of teamwork importance was most relevant at average-to-high levels of perceived politics. That finding supports the assertion that one way to address the negative impact of organizational politics is to try to ensure that employees value teamwork.
Harmonic regression based multi-temporal cloud filtering algorithm for Landsat 8
NASA Astrophysics Data System (ADS)
Joshi, P.
2015-12-01
Landsat data archive though rich is seen to have missing dates and periods owing to the weather irregularities and inconsistent coverage. The satellite images are further subject to cloud cover effects resulting in erroneous analysis and observations of ground features. In earlier studies the change detection algorithm using statistical control charts on harmonic residuals of multi-temporal Landsat 5 data have been shown to detect few prominent remnant clouds [Brooks, Evan B., et al, 2014]. So, in this work we build on this harmonic regression approach to detect and filter clouds using a multi-temporal series of Landsat 8 images. Firstly, we compute the harmonic coefficients using the fitting models on annual training data. This time series of residuals is further subjected to Shewhart X-bar control charts which signal the deviations of cloud points from the fitted multi-temporal fourier curve. For the process with standard deviation σ we found the second and third order harmonic regression with a x-bar chart control limit [Lσ] ranging between [0.5σ < Lσ < σ] as most efficient in detecting clouds. By implementing second order harmonic regression with successive x-bar chart control limits of L and 0.5 L on the NDVI, NDSI and haze optimized transformation (HOT), and utilizing the seasonal physical properties of these parameters, we have designed a novel multi-temporal algorithm for filtering clouds from Landsat 8 images. The method is applied to Virginia and Alabama in Landsat8 UTM zones 17 and 16 respectively. Our algorithm efficiently filters all types of cloud cover with an overall accuracy greater than 90%. As a result of the multi-temporal operation and the ability to recreate the multi-temporal database of images using only the coefficients of the fourier regression, our algorithm is largely storage and time efficient. The results show a good potential for this multi-temporal approach for cloud detection as a timely and targeted solution for the Landsat 8 research community, catering to the need for innovative processing solutions in the infant stage of the satellite.
Effects of the X:IT smoking intervention: a school-based cluster randomized trial.
Andersen, Anette; Krølner, Rikker; Bast, Lotus Sofie; Thygesen, Lau Caspar; Due, Pernille
2015-12-01
Uptake of smoking in adolescence is still of major public health concern. Evaluations of school-based programmes for smoking prevention show mixed results. The aim of this study was to examine the effect of X:IT, a multi-component school-based programme to prevent adolescent smoking. Data from a Danish cluster randomized trial included 4041 year-7 students (mean age: 12.5) from 51 intervention and 43 control schools. Outcome measure 'current smoking' was dichotomized into smoking daily, weekly, monthly or more seldom vs do not smoke. Analyses were adjusted for baseline covariates: sex, family socioeconomic position (SEP), best friend's smoking and parental smoking. We performed multilevel, logistic regression analyses of available cases and intention-to-treat (ITT) analyses, replacing missing outcome values by multiple imputation. At baseline, 4.7% and 6.8% of the students at the intervention and the control schools smoked, respectively. After 1 year of the intervention, the prevalence was 7.9% and 10.7%, respectively. At follow-up, 553 students (13.7%) did not answer the question on smoking. Available case analyses: crude odds ratios (OR) for smoking at intervention schools compared with control schools: 0.65 (0.48-0.88) and adjusted: 0.70 (0.47-1.04). ITT analyses: crude OR for smoking at intervention schools compared with control schools: 0.67 (0.50-0.89) and adjusted: 0.61 (0.45-0.82). Students at intervention schools had a lower risk of smoking after a year of intervention in year 7. This multi-component intervention involving educational, parental and context-related intervention components seems to be efficient in lowering or postponing smoking uptake in Danish adolescents. © The Author 2015; all rights reserved. Published by Oxford University Press on behalf of the International Epidemiological Association.
Robust Face Recognition via Multi-Scale Patch-Based Matrix Regression.
Gao, Guangwei; Yang, Jian; Jing, Xiaoyuan; Huang, Pu; Hua, Juliang; Yue, Dong
2016-01-01
In many real-world applications such as smart card solutions, law enforcement, surveillance and access control, the limited training sample size is the most fundamental problem. By making use of the low-rank structural information of the reconstructed error image, the so-called nuclear norm-based matrix regression has been demonstrated to be effective for robust face recognition with continuous occlusions. However, the recognition performance of nuclear norm-based matrix regression degrades greatly in the face of the small sample size problem. An alternative solution to tackle this problem is performing matrix regression on each patch and then integrating the outputs from all patches. However, it is difficult to set an optimal patch size across different databases. To fully utilize the complementary information from different patch scales for the final decision, we propose a multi-scale patch-based matrix regression scheme based on which the ensemble of multi-scale outputs can be achieved optimally. Extensive experiments on benchmark face databases validate the effectiveness and robustness of our method, which outperforms several state-of-the-art patch-based face recognition algorithms.
Grieve, Richard; Nixon, Richard; Thompson, Simon G
2010-01-01
Cost-effectiveness analyses (CEA) may be undertaken alongside cluster randomized trials (CRTs) where randomization is at the level of the cluster (for example, the hospital or primary care provider) rather than the individual. Costs (and outcomes) within clusters may be correlated so that the assumption made by standard bivariate regression models, that observations are independent, is incorrect. This study develops a flexible modeling framework to acknowledge the clustering in CEA that use CRTs. The authors extend previous Bayesian bivariate models for CEA of multicenter trials to recognize the specific form of clustering in CRTs. They develop new Bayesian hierarchical models (BHMs) that allow mean costs and outcomes, and also variances, to differ across clusters. They illustrate how each model can be applied using data from a large (1732 cases, 70 primary care providers) CRT evaluating alternative interventions for reducing postnatal depression. The analyses compare cost-effectiveness estimates from BHMs with standard bivariate regression models that ignore the data hierarchy. The BHMs show high levels of cost heterogeneity across clusters (intracluster correlation coefficient, 0.17). Compared with standard regression models, the BHMs yield substantially increased uncertainty surrounding the cost-effectiveness estimates, and altered point estimates. The authors conclude that ignoring clustering can lead to incorrect inferences. The BHMs that they present offer a flexible modeling framework that can be applied more generally to CEA that use CRTs.
Hobin, Erin P; Leatherdale, Scott T; Manske, Steve R; Robertson-Wilson, Jennifer
2010-01-01
Schools represent an important environment for physical activity (PA) promotion among youth. Schools can promote PA through policies and programs but our understanding of how these school characteristics associate with student PA levels is largely unknown. Developing this understanding is critical for implementing new prevention interventions. The aim of this study was to identify the school- and student-related characteristics associated with moderate and high levels of PA in a sample of Ontario elementary schools. Using multi-level logistic regression analyses, we explored the school- and student-level characteristics associated with being moderately and highly active using data collected from administrators and from students in grades 5 to 8 at 30 elementary schools in Ontario. Students' PA levels, sex, grade, and the number of physical education classes per week were linked to school environment data--specifically, a school's chosen implementation model for daily physical activity and whether it offers intramural and interschool PA programming. Findings indicate that there was significant between-school variation for being moderately and highly active. Students were less likely to be moderately or highly active if they attended a school offering interschool PA programming. An important student characteristic positively associated with student PA levels included participating in at least two physical education classes per week. The residual differences in PA by school suggest that school-level characteristics facilitate higher levels of student PA beyond individual-level factors. Although most variation in student PA lies between students within schools, there is sufficient between-school variation to be of interest to practitioners and policy-makers.
The crystallization behavior of amorphous Ge2Sb2Te5 films induced by a multi-pulsed nanosecond laser
NASA Astrophysics Data System (ADS)
Fan, T.; Liu, F. R.; Li, W. Q.; Guo, J. C.; Wang, Y. H.; Sun, N. X.; Liu, F.
2017-09-01
In this paper, accumulated crystallization of amorphous Ge2Sb2Te5 (a-GST) films induced by a multi-pulsed nanosecond (ns) excimer laser was investigated by x-ray diffraction (XRD), atomic force microscopy, field-emission scanning electron microscopy, x-ray photoelectron spectroscopy (XPS) and a spectrophotometer. XRD analyses revealed that detectable crystallization was firstly observed in the preferred orientation (200), followed by the orientations (220) and (111) after two pulses. Optical contrast, determined by crystallinity as well as surface roughness, was found to retain a linear relation within the first three pulses. A layered growth mechanism from the top surface to the interior of a-GST films was used to explain the crystallization behavior induced by the multi-pulse ns laser. XPS analyses for bond rearrangement and electronic structure further suggested that the crystallization process was performed by generating new bonds of Ge-Te and Sb-Te after laser irradiations. This paper presents the potential of multi-level devices and tunable thermal emitters based on controllable crystallization of phase-change materials.
Meuwese, Julia D.I.; Towgood, Karren J.; Frith, Christopher D.; Burgess, Paul W.
2009-01-01
Multi-voxel pattern analyses have proved successful in ‘decoding’ mental states from fMRI data, but have not been used to examine brain differences associated with atypical populations. We investigated a group of 16 (14 males) high-functioning participants with autism spectrum disorder (ASD) and 16 non-autistic control participants (12 males) performing two tasks (spatial/verbal) previously shown to activate medial rostral prefrontal cortex (mrPFC). Each task manipulated: (i) attention towards perceptual versus self-generated information and (ii) reflection on another person's mental state (‘mentalizing'versus ‘non-mentalizing’) in a 2 × 2 design. Behavioral performance and group-level fMRI results were similar between groups. However, multi-voxel similarity analyses revealed strong differences. In control participants, the spatial distribution of activity generalized significantly between task contexts (spatial/verbal) when examining the same function (attention/mentalizing) but not when comparing different functions. This pattern was disrupted in the ASD group, indicating abnormal functional specialization within mrPFC, and demonstrating the applicability of multi-voxel pattern analysis to investigations of atypical populations. PMID:19174370
Lim, Travis W; Frangakis, Constantine; Latkin, Carl; Ha, Tran Viet; Minh, Nguyen Le; Zelaya, Carla; Quan, Vu Minh; Go, Vivian F
2014-01-01
Socioeconomic status has a robust positive relationship with several health outcomes at the individual and population levels, but in the case of HIV prevalence, income inequality may be a better predictor than absolute level of income. Most studies showing a relationship between income inequality and HIV have used entire countries as the unit of analysis. In this study, we examine the association between income inequality at the community level and HIV prevalence in a sample of persons who inject drugs (PWID) in a concentrated epidemic setting. We recruited PWID and non-PWID community participants in Thai Nguyen, Vietnam, and administered a cross-sectional questionnaire; PWID were tested for HIV. We used ecologic regression to model HIV burden in our PWID study population on GINI indices of inequality calculated from total reported incomes of non-PWID community members in each commune. We also modeled HIV burden on interaction terms between GINI index and median commune income, and finally used a multi-level model to control for community level inequality and individual level income. HIV burden among PWID was significantly correlated with the commune GINI coefficient (r = 0.53, p = 0.002). HIV burden was also associated with GINI coefficient (β = 0.082, p = 0.008) and with median commune income (β = -0.018, p = 0.023) in ecological regression. In the multi-level model, higher GINI coefficient at the community level was associated with higher odds of individual HIV infection in PWID (OR = 1.46 per 0.01, p = 0.003) while higher personal income was associated with reduced odds of infection (OR = 0.98 per $10, p = 0.022). This study demonstrates a context where income inequality is associated with HIV prevalence at the community level in a concentrated epidemic. It further suggests that community level socioeconomic factors, both contextual and compositional, could be indirect determinants of HIV infection in PWID.
Lim, Travis W.; Frangakis, Constantine; Latkin, Carl; Ha, Tran Viet; Minh, Nguyen Le; Zelaya, Carla; Quan, Vu Minh; Go, Vivian F.
2014-01-01
Socioeconomic status has a robust positive relationship with several health outcomes at the individual and population levels, but in the case of HIV prevalence, income inequality may be a better predictor than absolute level of income. Most studies showing a relationship between income inequality and HIV have used entire countries as the unit of analysis. In this study, we examine the association between income inequality at the community level and HIV prevalence in a sample of persons who inject drugs (PWID) in a concentrated epidemic setting. We recruited PWID and non-PWID community participants in Thai Nguyen, Vietnam, and administered a cross-sectional questionnaire; PWID were tested for HIV. We used ecologic regression to model HIV burden in our PWID study population on GINI indices of inequality calculated from total reported incomes of non-PWID community members in each commune. We also modeled HIV burden on interaction terms between GINI index and median commune income, and finally used a multi-level model to control for community level inequality and individual level income. HIV burden among PWID was significantly correlated with the commune GINI coefficient (r = 0.53, p = 0.002). HIV burden was also associated with GINI coefficient (β = 0.082, p = 0.008) and with median commune income (β = −0.018, p = 0.023) in ecological regression. In the multi-level model, higher GINI coefficient at the community level was associated with higher odds of individual HIV infection in PWID (OR = 1.46 per 0.01, p = 0.003) while higher personal income was associated with reduced odds of infection (OR = 0.98 per $10, p = 0.022). This study demonstrates a context where income inequality is associated with HIV prevalence at the community level in a concentrated epidemic. It further suggests that community level socioeconomic factors, both contextual and compositional, could be indirect determinants of HIV infection in PWID. PMID:24618892
NASA Astrophysics Data System (ADS)
Poyatos, Rafael; Sus, Oliver; Badiella, Llorenç; Mencuccini, Maurizio; Martínez-Vilalta, Jordi
2018-05-01
The ubiquity of missing data in plant trait databases may hinder trait-based analyses of ecological patterns and processes. Spatially explicit datasets with information on intraspecific trait variability are rare but offer great promise in improving our understanding of functional biogeography. At the same time, they offer specific challenges in terms of data imputation. Here we compare statistical imputation approaches, using varying levels of environmental information, for five plant traits (leaf biomass to sapwood area ratio, leaf nitrogen content, maximum tree height, leaf mass per area and wood density) in a spatially explicit plant trait dataset of temperate and Mediterranean tree species (Ecological and Forest Inventory of Catalonia, IEFC, dataset for Catalonia, north-east Iberian Peninsula, 31 900 km2). We simulated gaps at different missingness levels (10-80 %) in a complete trait matrix, and we used overall trait means, species means, k nearest neighbours (kNN), ordinary and regression kriging, and multivariate imputation using chained equations (MICE) to impute missing trait values. We assessed these methods in terms of their accuracy and of their ability to preserve trait distributions, multi-trait correlation structure and bivariate trait relationships. The relatively good performance of mean and species mean imputations in terms of accuracy masked a poor representation of trait distributions and multivariate trait structure. Species identity improved MICE imputations for all traits, whereas forest structure and topography improved imputations for some traits. No method performed best consistently for the five studied traits, but, considering all traits and performance metrics, MICE informed by relevant ecological variables gave the best results. However, at higher missingness (> 30 %), species mean imputations and regression kriging tended to outperform MICE for some traits. MICE informed by relevant ecological variables allowed us to fill the gaps in the IEFC incomplete dataset (5495 plots) and quantify imputation uncertainty. Resulting spatial patterns of the studied traits in Catalan forests were broadly similar when using species means, regression kriging or the best-performing MICE application, but some important discrepancies were observed at the local level. Our results highlight the need to assess imputation quality beyond just imputation accuracy and show that including environmental information in statistical imputation approaches yields more plausible imputations in spatially explicit plant trait datasets.
2013-01-01
fabricated today are based on polymer matrix composites containing Kevlarw KM2 reinforcements , the present work will deal with generic PPTA fibers . In...Multi-length scale enriched continuum-level material model for Kevlarw- fiber reinforced polymer-matrix composites”, Journal of Materials...mechanical transverse behavior of p-phenylene terephthalamide (PPTA) fibers Purpose – A series of all-atom molecular-level computational analyses is
Xia, Qing; Liu, Changhong; Liu, Jinxia; Pan, Wenjuan; Lu, Xuzhong; Yang, Jianbo; Chen, Wei; Zheng, Lei
2016-03-30
Rancidity is an important attribute for quality assessment of butter cookies, while traditional methods for rancidity measurement are usually laborious, destructive and prone to operational error. In the present paper, the potential of applying multi-spectral imaging (MSI) technology with 19 wavelengths in the range of 405-970 nm to evaluate the rancidity in butter cookies was investigated. Moisture content, acid value and peroxide value were determined by traditional methods and then related with the spectral information by partial least squares regression (PLSR) and back-propagation artificial neural network (BP-ANN). The optimal models for predicting moisture content, acid value and peroxide value were obtained by PLSR. The correlation coefficient (r) obtained by PLSR models revealed that MSI had a perfect ability to predict moisture content (r = 0.909), acid value (r = 0.944) and peroxide value (r = 0.971). The study demonstrated that the rancidity level of butter cookies can be continuously monitored and evaluated in real-time by the multi-spectral imaging, which is of great significance for developing online food safety monitoring solutions. © 2015 Society of Chemical Industry.
Multi-model ensemble combinations of the water budget in the East/Japan Sea
NASA Astrophysics Data System (ADS)
HAN, S.; Hirose, N.; Usui, N.; Miyazawa, Y.
2016-02-01
The water balance of East/Japan Sea is determined mainly by inflow and outflow through the Korea/Tsushima, Tsugaru and Soya/La Perouse Straits. However, the volume transports measured at three straits remain quantitatively unbalanced. This study examined the seasonal variation of the volume transport using the multiple linear regression and ridge regression of multi-model ensemble (MME) methods to estimate physically consistent circulation in East/Japan Sea by using four different data assimilation models. The MME outperformed all of the single models by reducing uncertainties, especially the multicollinearity problem with the ridge regression. However, the regression constants turned out to be inconsistent with each other if the MME was applied separately for each strait. The MME for a connected system was thus performed to find common constants for these straits. The estimation of this MME was found to be similar to the MME result of sea level difference (SLD). The estimated mean transport (2.42 Sv) was smaller than the measurement data at the Korea/Tsushima Strait, but the calibrated transport of the Tsugaru Strait (1.63 Sv) was larger than the observed data. The MME results of transport and SLD also suggested that the standard deviation (STD) of the Korea/Tsushima Strait is larger than the STD of the observation, whereas the estimated results were almost identical to that observed for the Tsugaru and Soya/La Perouse Straits. The similarity between MME results enhances the reliability of the present MME estimation.
Multi-model ensemble estimation of volume transport through the straits of the East/Japan Sea
NASA Astrophysics Data System (ADS)
Han, Sooyeon; Hirose, Naoki; Usui, Norihisa; Miyazawa, Yasumasa
2016-01-01
The volume transports measured at the Korea/Tsushima, Tsugaru, and Soya/La Perouse Straits remain quantitatively inconsistent. However, data assimilation models at least provide a self-consistent budget despite subtle differences among the models. This study examined the seasonal variation of the volume transport using the multiple linear regression and ridge regression of multi-model ensemble (MME) methods to estimate more accurately transport at these straits by using four different data assimilation models. The MME outperformed all of the single models by reducing uncertainties, especially the multicollinearity problem with the ridge regression. However, the regression constants turned out to be inconsistent with each other if the MME was applied separately for each strait. The MME for a connected system was thus performed to find common constants for these straits. The estimation of this MME was found to be similar to the MME result of sea level difference (SLD). The estimated mean transport (2.43 Sv) was smaller than the measurement data at the Korea/Tsushima Strait, but the calibrated transport of the Tsugaru Strait (1.63 Sv) was larger than the observed data. The MME results of transport and SLD also suggested that the standard deviation (STD) of the Korea/Tsushima Strait is larger than the STD of the observation, whereas the estimated results were almost identical to that observed for the Tsugaru and Soya/La Perouse Straits. The similarity between MME results enhances the reliability of the present MME estimation.
Two studies on participation in decision-making and equity among FAA personnel.
DOT National Transportation Integrated Search
1991-07-01
Study 1 Moderated multiple regression analyses on data collected from 2,177 FAA air traffic controller specialists indicated that equity perceptions moderated the relationship between participation in decision-making and level of job satisfaction. Sp...
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.
Demographic responses of Pinguicula ionantha to prescribed fire: a regression-design LTRE approach.
Kesler, Herbert C; Trusty, Jennifer L; Hermann, Sharon M; Guyer, Craig
2008-06-01
This study describes the use of periodic matrix analysis and regression-design life table response experiments (LTRE) to investigate the effects of prescribed fire on demographic responses of Pinguicula ionantha, a federally listed plant endemic to the herb bog/savanna community in north Florida. Multi-state mark-recapture models with dead recoveries were used to estimate survival and transition probabilities for over 2,300 individuals in 12 populations of P. ionantha. These estimates were applied to parameterize matrix models used in further analyses. P. ionantha demographics were found to be strongly dependent on prescribed fire events. Periodic matrix models were used to evaluate season of burn (either growing or dormant season) for fire return intervals ranging from 1 to 20 years. Annual growing and biannual dormant season fires maximized population growth rates for this species. A regression design LTRE was used to evaluate the effect of number of days since last fire on population growth. Maximum population growth rates calculated using standard asymptotic analysis were realized shortly following a burn event (<2 years), and a regression design LTRE showed that short-term fire-mediated changes in vital rates translated into observed increases in population growth. The LTRE identified fecundity and individual growth as contributing most to increases in post-fire population growth. Our analyses found that the current four-year prescribed fire return intervals used at the study sites can be significantly shortened to increase the population growth rates of this rare species. Understanding the role of fire frequency and season in creating and maintaining appropriate habitat for this species may aid in the conservation of this and other rare herb bog/savanna inhabitants.
A multi-criteria spatial deprivation index to support health inequality analyses.
Cabrera-Barona, Pablo; Murphy, Thomas; Kienberger, Stefan; Blaschke, Thomas
2015-03-20
Deprivation indices are useful measures to analyze health inequalities. There are several methods to construct these indices, however, few studies have used Geographic Information Systems (GIS) and Multi-Criteria methods to construct a deprivation index. Therefore, this study applies Multi-Criteria Evaluation to calculate weights for the indicators that make up the deprivation index and a GIS-based fuzzy approach to create different scenarios of this index is also implemented. The Analytical Hierarchy Process (AHP) is used to obtain the weights for the indicators of the index. The Ordered Weighted Averaging (OWA) method using linguistic quantifiers is applied in order to create different deprivation scenarios. Geographically Weighted Regression (GWR) and a Moran's I analysis are employed to explore spatial relationships between the different deprivation measures and two health factors: the distance to health services and the percentage of people that have never had a live birth. This last indicator was considered as the dependent variable in the GWR. The case study is Quito City, in Ecuador. The AHP-based deprivation index show medium and high levels of deprivation (0,511 to 1,000) in specific zones of the study area, even though most of the study area has low values of deprivation. OWA results show deprivation scenarios that can be evaluated considering the different attitudes of decision makers. GWR results indicate that the deprivation index and its OWA scenarios can be considered as local estimators for health related phenomena. Moran's I calculations demonstrate that several deprivation scenarios, in combination with the 'distance to health services' factor, could be explanatory variables to predict the percentage of people that have never had a live birth. The AHP-based deprivation index and the OWA deprivation scenarios developed in this study are Multi-Criteria instruments that can support the identification of highly deprived zones and can support health inequalities analysis in combination with different health factors. The methodology described in this study can be applied in other regions of the world to develop spatial deprivation indices based on Multi-Criteria analysis.
CyTOF workflow: differential discovery in high-throughput high-dimensional cytometry datasets
Nowicka, Malgorzata; Krieg, Carsten; Weber, Lukas M.; Hartmann, Felix J.; Guglietta, Silvia; Becher, Burkhard; Levesque, Mitchell P.; Robinson, Mark D.
2017-01-01
High dimensional mass and flow cytometry (HDCyto) experiments have become a method of choice for high throughput interrogation and characterization of cell populations.Here, we present an R-based pipeline for differential analyses of HDCyto data, largely based on Bioconductor packages. We computationally define cell populations using FlowSOM clustering, and facilitate an optional but reproducible strategy for manual merging of algorithm-generated clusters. Our workflow offers different analysis paths, including association of cell type abundance with a phenotype or changes in signaling markers within specific subpopulations, or differential analyses of aggregated signals. Importantly, the differential analyses we show are based on regression frameworks where the HDCyto data is the response; thus, we are able to model arbitrary experimental designs, such as those with batch effects, paired designs and so on. In particular, we apply generalized linear mixed models to analyses of cell population abundance or cell-population-specific analyses of signaling markers, allowing overdispersion in cell count or aggregated signals across samples to be appropriately modeled. To support the formal statistical analyses, we encourage exploratory data analysis at every step, including quality control (e.g. multi-dimensional scaling plots), reporting of clustering results (dimensionality reduction, heatmaps with dendrograms) and differential analyses (e.g. plots of aggregated signals). PMID:28663787
The Effects of Social Capital Elements on Job Satisfaction and Motivation Levels of Teachers
ERIC Educational Resources Information Center
Boydak Özan, Mukadder; Yavuz Özdemir, Tuncay; Yaras, Zübeyde
2017-01-01
The purpose of this study is to examine the effects of social capital elements' on job satisfaction and motivation levels of teachers. The mixed method was used in the study. The quantitative data were analyzed through Correlation and Multiple Regression analyses. An interview form developed by the researchers was used for analyzing the…
ERIC Educational Resources Information Center
Beardslee, Edward C.; Jerman, Max E.
Five structural, four linguistic and twelve topic variables are used in regression analyses on results of a 50-item achievement test. The test items are related to 12 topics from the third-grade mathematics curriculum. The items reflect one of two cases of the structural variable, cognitive level; the two levels are characterized, inductive…
A Multi-Institutional Analysis of the Socioeconomic Determinants of Breast Reconstruction
Christian, Caprice K.; Niland, Joyce; Edge, Stephen B.; Ottesen, Rebecca A.; Hughes, Melissa E.; Theriault, Richard; Wilson, John; Hergrueter, Charles A.; Weeks, Jane C.
2006-01-01
Objective: To determine the rate of postmastectomy reconstruction and investigate the impact of socioeconomic status on the receipt of reconstruction. Summary Background Data: The National Comprehensive Cancer Network (NCCN) Outcomes Project is a prospective, multi-institutional database that contains data on all newly diagnosed breast cancer patients treated at one of the participating comprehensive cancer centers. Methods: The study cohort consisted of 2174 patients with DCIS and stage I, II, and III invasive breast cancer who underwent mastectomy at one of 8 NCCN centers. Rates of reconstruction were determined. Logistic regression analyses were used to evaluate whether socioeconomic characteristics are associated with breast reconstruction. Results: Overall, 42% of patients had breast reconstruction following mastectomy. Patients with Medicaid and Medicare were less likely to undergo reconstruction than those with managed care insurance; however, there was no difference for indemnity versus managed care insurance. Homemakers and retired patients had fewer reconstructions than those employed outside the home. Patients with a high school education or less were less likely to have reconstruction than those with more education. Race and ethnicity were not significant predictors of reconstruction. Conclusions: The reconstruction rate in this study (42%) is markedly higher than those previously reported. The type of insurance, education level, and employment status of a patient, but not her race or ethnicity, appear to influence the use of breast reconstruction. Because all patients were treated at an NCCN institution, these socioeconomic differences cannot be explained by access to care. PMID:16432358
Multi-fidelity machine learning models for accurate bandgap predictions of solids
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab
Here, we present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model that enables low-cost accurate predictions of the bandgaps at the highest fidelity level. Additionally, the adopted Gaussian process regression formulation allows us to predict the underlying uncertainties as a measure of our confidence in the predictions. In using a set of 600 elpasolite compounds as an example dataset and using semi-local and hybrid exchange correlation functionals within density functional theory as two levels of fidelities, we demonstrate the excellent learning performance of the method against actual high fidelitymore » quantum mechanical calculations of the bandgaps. The presented statistical learning method is not restricted to bandgaps or electronic structure methods and extends the utility of high throughput property predictions in a significant way.« less
Multi-fidelity machine learning models for accurate bandgap predictions of solids
Pilania, Ghanshyam; Gubernatis, James E.; Lookman, Turab
2016-12-28
Here, we present a multi-fidelity co-kriging statistical learning framework that combines variable-fidelity quantum mechanical calculations of bandgaps to generate a machine-learned model that enables low-cost accurate predictions of the bandgaps at the highest fidelity level. Additionally, the adopted Gaussian process regression formulation allows us to predict the underlying uncertainties as a measure of our confidence in the predictions. In using a set of 600 elpasolite compounds as an example dataset and using semi-local and hybrid exchange correlation functionals within density functional theory as two levels of fidelities, we demonstrate the excellent learning performance of the method against actual high fidelitymore » quantum mechanical calculations of the bandgaps. The presented statistical learning method is not restricted to bandgaps or electronic structure methods and extends the utility of high throughput property predictions in a significant way.« less
Aydan, Seda; Kaya, Sidika
2018-01-01
Objectives: To reveal the effect of perception of ethical climate by nurses and secretaries and their level of organizational trust on their whistleblowing intention. Methods: Nurses and secretaries working in a University Hospital in Ankara, Turkey, were enrolled in the study conducted in 2016. Responses were received from 369 nurses and secretaries working at Clinics and Polyclinics. Path analysis, investigation of structural equation models used while multi-regression analysis was also applied. Results: According to the regression model, ethical climate dimensions, profession, gender, and work place had significant impact on the whistleblowing intention. According to Path analysis, ethical climate had direct impact of 69% on whistleblowing intention. It was seen that organizational trust had an indirect impact of 27% on the whistleblowing score when ethical climate had a moderator role. Conclusion: In order to promote whistleblowing in organizations, it is important to keep the ethical climate perception of employees and the level of their organizational trust at high levels. PMID:29805421
Aydan, Seda; Kaya, Sidika
2018-01-01
To reveal the effect of perception of ethical climate by nurses and secretaries and their level of organizational trust on their whistleblowing intention. Nurses and secretaries working in a University Hospital in Ankara, Turkey, were enrolled in the study conducted in 2016. Responses were received from 369 nurses and secretaries working at Clinics and Polyclinics. Path analysis, investigation of structural equation models used while multi-regression analysis was also applied. According to the regression model, ethical climate dimensions, profession, gender, and work place had significant impact on the whistleblowing intention. According to Path analysis, ethical climate had direct impact of 69% on whistleblowing intention. It was seen that organizational trust had an indirect impact of 27% on the whistleblowing score when ethical climate had a moderator role. In order to promote whistleblowing in organizations, it is important to keep the ethical climate perception of employees and the level of their organizational trust at high levels.
Wan, Shibiao; Mak, Man-Wai; Kung, Sun-Yuan
2015-03-15
Proteins located in appropriate cellular compartments are of paramount importance to exert their biological functions. Prediction of protein subcellular localization by computational methods is required in the post-genomic era. Recent studies have been focusing on predicting not only single-location proteins but also multi-location proteins. However, most of the existing predictors are far from effective for tackling the challenges of multi-label proteins. This article proposes an efficient multi-label predictor, namely mPLR-Loc, based on penalized logistic regression and adaptive decisions for predicting both single- and multi-location proteins. Specifically, for each query protein, mPLR-Loc exploits the information from the Gene Ontology (GO) database by using its accession number (AC) or the ACs of its homologs obtained via BLAST. The frequencies of GO occurrences are used to construct feature vectors, which are then classified by an adaptive decision-based multi-label penalized logistic regression classifier. Experimental results based on two recent stringent benchmark datasets (virus and plant) show that mPLR-Loc remarkably outperforms existing state-of-the-art multi-label predictors. In addition to being able to rapidly and accurately predict subcellular localization of single- and multi-label proteins, mPLR-Loc can also provide probabilistic confidence scores for the prediction decisions. For readers' convenience, the mPLR-Loc server is available online (http://bioinfo.eie.polyu.edu.hk/mPLRLocServer). Copyright © 2014 Elsevier Inc. All rights reserved.
Hantke, Simone; Weninger, Felix; Kurle, Richard; Ringeval, Fabien; Batliner, Anton; Mousa, Amr El-Desoky; Schuller, Björn
2016-01-01
We propose a new recognition task in the area of computational paralinguistics: automatic recognition of eating conditions in speech, i. e., whether people are eating while speaking, and what they are eating. To this end, we introduce the audio-visual iHEARu-EAT database featuring 1.6 k utterances of 30 subjects (mean age: 26.1 years, standard deviation: 2.66 years, gender balanced, German speakers), six types of food (Apple, Nectarine, Banana, Haribo Smurfs, Biscuit, and Crisps), and read as well as spontaneous speech, which is made publicly available for research purposes. We start with demonstrating that for automatic speech recognition (ASR), it pays off to know whether speakers are eating or not. We also propose automatic classification both by brute-forcing of low-level acoustic features as well as higher-level features related to intelligibility, obtained from an Automatic Speech Recogniser. Prediction of the eating condition was performed with a Support Vector Machine (SVM) classifier employed in a leave-one-speaker-out evaluation framework. Results show that the binary prediction of eating condition (i. e., eating or not eating) can be easily solved independently of the speaking condition; the obtained average recalls are all above 90%. Low-level acoustic features provide the best performance on spontaneous speech, which reaches up to 62.3% average recall for multi-way classification of the eating condition, i. e., discriminating the six types of food, as well as not eating. The early fusion of features related to intelligibility with the brute-forced acoustic feature set improves the performance on read speech, reaching a 66.4% average recall for the multi-way classification task. Analysing features and classifier errors leads to a suitable ordinal scale for eating conditions, on which automatic regression can be performed with up to 56.2% determination coefficient. PMID:27176486
Changing response of the North Atlantic/European winter climate to the 11 year solar cycle
NASA Astrophysics Data System (ADS)
Ma, Hedi; Chen, Haishan; Gray, Lesley; Zhou, Liming; Li, Xing; Wang, Ruili; Zhu, Siguang
2018-03-01
Recent studies have presented conflicting results regarding the 11 year solar cycle (SC) influences on winter climate over the North Atlantic/European region. Analyses of only the most recent decades suggest a synchronized North Atlantic Oscillation (NAO)-like response pattern to the SC. Analyses of long-term climate data sets dating back to the late 19th century, however, suggest a mean sea level pressure (mslp) response that lags the SC by 2-4 years in the southern node of the NAO (i.e. Azores region). To understand the conflicting nature and cause of these time dependencies in the SC surface response, the present study employs a lead/lag multi-linear regression technique with a sliding window of 44 years over the period 1751-2016. Results confirm previous analyses, in which the average response for the whole time period features a statistically significant 2-4 year lagged mslp response centered over the Azores region. Overall, the lagged nature of Azores mslp response is generally consistent in time. Stronger and statistically significant SC signals tend to appear in the periods when the SC forcing amplitudes are relatively larger. Individual month analysis indicates the consistent lagged response in December-January-February average arises primarily from early winter months (i.e. December and January), which has been associated with ocean feedback processes that involve reinforcement by anomalies from the previous winter. Additional analysis suggests that the synchronous NAO-like response in recent decades arises primarily from late winter (February), possibly reflecting a result of strong internal noise.
Multi-level modeling of social factors and preterm delivery in Santiago de Chile
Kaufman, Jay S; Alonso, Faustino T; Pino, Paulina
2008-01-01
Background Birth before the 37th week of gestation (preterm birth) is an important cause of infant and neonatal mortality, but has been little studied outside of wealthy nations. Chile is an urbanized Latin American nation classified as "middle-income" based on its annual income per capita of about $6000. Methods We studied the relations between maternal social status and neighborhood social status on risk of preterm delivery in this setting using multilevel regression analyses of vital statistics data linked to geocoded decennial census data. The analytic data set included 56,970 births from 2004 in the metropolitan region of Santiago, which constitutes about 70% of all births in the study area and about 25% of all births in Chile that year. Dimensionality of census data was reduced using principal components analysis, with regression scoring to create a single index of community socioeconomic advantage. This was modeled along with years of maternal education in order to predict preterm birth and preterm low birthweight. Results Births in Santiago displayed an advantaged pattern of preterm risk, with only 6.4% of births delivering before 37 weeks. Associations were observed between risk of outcomes and individual and neighborhood factors, but the magnitudes of these associations were much more modest than reported in North America. Conclusion While several potential explanations for this relatively flat social gradient might be considered, one possibility is that Chile's egalitarian approach to universal prenatal care may have reduced social inequalities in these reproductive outcomes. PMID:18842145
Hao, Yongping; Strosnider, Heather; Balluz, Lina; Qualters, Judith R
2016-02-01
Studies on the association between prenatal exposure to fine particulate matter ≤ 2.5 μm in aerodynamic diameter (PM2.5) and term low birth weight (LBW) have resulted in inconsistent findings. Most studies were conducted in snapshots of small geographic areas and no national study exists. We investigated geographic variation in the associations between ambient PM2.5 during pregnancy and term LBW in the contiguous United States. A total of 3,389,450 term singleton births in 2002 (37-44 weeks gestational age and birth weight of 1,000-5,500 g) were linked to daily PM2.5 via imputed birth days. We generated average daily PM2.5 during the entire pregnancy and each trimester. Multi-level logistic regression models with county-level random effects were used to evaluate the associations between term LBW and PM2.5 during pregnancy. Without adjusting for covariates, the odds of term LBW increased 2% [odds ratio (OR) = 1.02; 95% CI: 1.00, 1.03] for every 5-μg/m(3) increase in PM2.5 exposure during the second trimester only, which remained unchanged after adjusting for county-level poverty (OR = 1.02; 95% CI: 1.01, 1.04). The odds did change to null after adjusting for individual-level predictors (OR = 1.00; 95% CI: 0.99, 1.02). Multi-level analyses, stratified by census division, revealed significant positive associations of term LBW and PM2.5 exposure (during the entire pregnancy or a specific trimester) in three census divisions of the United States: Middle Atlantic, East North Central, and West North Central, and significant negative association in the Mountain division. Our study provided additional evidence on the associations between PM2.5 exposure during pregnancy and term LBW from a national perspective. The magnitude and direction of the estimated associations between PM2.5 exposure and term LBW varied by geographic locations in the United States.
Area-level poverty, race/ethnicity & dialysis star ratings.
Kshirsagar, Abhijit V; Manickam, Raj N; Mu, Yi; Flythe, Jennifer E; Chin, Andrew I; Bang, Heejung
2017-01-01
The Centers for Medicare and Medicaid Services recently released a five star rating system as part of 'Dialysis Facility Compare' to help patients identify and choose high performing clinics in the US. Eight dialysis-related measures determine ratings. Little is known about the association between surrounding community sociodemographic characteristics and star ratings. Using data from the U.S. Census and over 6000 dialysis clinics across the country, we examined the association between dialysis clinic star ratings and characteristics of the local population: 1) proportion of population below the federal poverty level (FPL); 2) proportion of black individuals; and 3) proportion of Hispanic individuals, by correlation and regression analyses. Secondary analyses with Quality Incentive Program (QIP) scores and population characteristics were also performed. We observed a negligible correlation between star ratings and the proportion of local individuals below FPL; Spearman coefficient, R = -0.09 (p<0.0001), and a stronger correlation between star ratings and the proportion of black individuals; R = -0.21 (p<0.0001). Ordered logistic regression analyses yielded adjusted odds ratio of 0.91 (95% confidence interval [0.80-1.30], p = 0.12) and 0.55 ([0.48-0.63], p<0.0001) for high vs. low level of proportion below FPL and proportion of black individuals, respectively. In contrast, a near-zero correlation was observed between star ratings and the proportion of Hispanic individuals. Correlations varied substantially by country region, clinic profit status and clinic size. Analyses using clinic QIP scores provided similar results. Sociodemographic characteristics of the surrounding community, factors typically outside of providers' direct control, have varying levels of association with clinic dialysis star ratings.
Chen, Brian K; Seligman, Benjamin; Farquhar, John W; Goldhaber-Fiebert, Jeremy D
2011-12-16
Cardiovascular diseases represent an increasing share of the global disease burden. There is concern that increased consumption of palm oil could exacerbate mortality from ischemic heart disease (IHD) and stroke, particularly in developing countries where it represents a major nutritional source of saturated fat. The study analyzed country-level data from 1980-1997 derived from the World Health Organization's Mortality Database, U.S. Department of Agriculture international estimates, and the World Bank (234 annual observations; 23 countries). Outcomes included mortality from IHD and stroke for adults aged 50 and older. Predictors included per-capita consumption of palm oil and cigarettes and per-capita Gross Domestic Product as well as time trends and an interaction between palm oil consumption and country economic development level. Analyses examined changes in country-level outcomes over time employing linear panel regressions with country-level fixed effects, population weighting, and robust standard errors clustered by country. Sensitivity analyses included further adjustment for other major dietary sources of saturated fat. In developing countries, for every additional kilogram of palm oil consumed per-capita annually, IHD mortality rates increased by 68 deaths per 100,000 (95% CI [21-115]), whereas, in similar settings, stroke mortality rates increased by 19 deaths per 100,000 (95% CI [-12-49]) but were not significant. For historically high-income countries, changes in IHD and stroke mortality rates from palm oil consumption were smaller (IHD: 17 deaths per 100,000 (95% CI [5.3-29]); stroke: 5.1 deaths per 100,000 (95% CI [-1.2-11.0])). Inclusion of other major saturated fat sources including beef, pork, chicken, coconut oil, milk cheese, and butter did not substantially change the differentially higher relationship between palm oil and IHD mortality in developing countries. Increased palm oil consumption is related to higher IHD mortality rates in developing countries. Palm oil consumption represents a saturated fat source relevant for policies aimed at reducing cardiovascular disease burdens.
Ding, Xuejie; Billari, Francesco C; Gietel-Basten, Stuart
2017-11-01
To document the association between economic development, income inequality, and health-related public infrastructure, and health outcomes among Chinese adults in midlife and older age. We use a series of multi-level regression models with individual-level baseline data from the China Health and Retirement Longitudinal Survey (CHARLS). Provincial-level data are obtained both from official statistics and from CHARLS itself. Multi-level models are estimated with different subjective and objective health outcomes. Economic growth is associated with better self-rated health, but also with obesity. Better health infrastructure tends to be negatively associated with health outcomes, indicating the likely presence of reverse causality. No supportive evidence is found for the hypothesis that income inequality leads to worse health outcomes. Our study shows that on top of individual characteristics, provincial variations in economic development, income inequality, and health infrastructure are associated with a range of health outcomes for Chinese midlife and older adults. Economic development in China might also bring adverse health outcomes for this age group; as such specific policy responses need to be developed.
Jordans, M J D; Komproe, I H; Tol, W A; Susanty, D; Vallipuram, A; Ntamatumba, P; Lasuba, A C; De Jong, J T V M
2011-06-01
Psychosocial and mental health service delivery frameworks for children in low-income countries are scarce. This paper presents a practice-driven evaluation of a multi-layered community-based care package in Burundi, Indonesia, Sri Lanka and Sudan, through a set of indicators; (a) perceived treatment gains; (b) treatment satisfaction; (c) therapist burden; (d) access to care; (e) care package costs. Across four settings (n = 29,292 children), beneficiaries reported high levels of client satisfaction and moderate post-treatment problem reductions. Service providers reported significant levels of distress related to service delivery. Cost analyses demonstrated mean cost per service user to vary from 3.46 to 17.32
Examining gender salary disparities: an analysis of the 2003 multistate salary survey.
Brown, Lawrence M; Schommer, Jon C; Mott, Dave; Gaither, Caroline A; Doucette, William R; Zgarrick, Dave P; Droege, Marcus
2006-09-01
Pharmacist salary and wage surveys have been conducted at the state and national level for more than 20 years; however, it is not known to what extent, if any, wage disparities due to gender still exist. The overall objective of this study was to determine if wage disparities exist among male and female pharmacists at the multistate and individual state level for each of 6 states studied. A secondary objective was to explore the effect of various demographic variables on the hourly wages of pharmacists. Data were collected from 1,688 pharmacists in 6 states during 2003 using a cross-sectional descriptive survey design. A multiple regression analysis on hourly wage testing the effects of state of practice, practice setting, position, terminal degree, and years in practice was conducted. Subsequent multiple regression analyses were conducted individually for each of the 6 states to test the effects of the above variables on hourly wage for both male and female pharmacists, followed by state-level analyses for male and female pharmacists, respectively. For the pooled data, all variables were found to be significant predictors of hourly wage, except for earning a PharmD degree without a residency or graduate degree. Gender was not a significant predictor of wage disparities in the state-level analyses. Position was the only significant predictor of wage disparities in all states (except Tennessee) such that pharmacists in management positions make significantly higher salaries than those in staff positions. The results of these analyses suggest that wage disparities due to gender do not exist at the state level for the 6 states surveyed, when controlling for practice setting, position, terminal degree, and years in practice. The larger number of men in management positions may explain lower wages for female pharmacists.
Meisenkothen, Frederick; Steel, Eric B; Prosa, Ty J; Henry, Karen T; Prakash Kolli, R
2015-12-01
In atom probe tomography (APT), some elements tend to field evaporate preferentially in multi-hit detection events. Boron (B) is one such element. It is thought that a large fraction of the B signal may be lost during data acquisition and is not reported in the mass spectrum or in the 3-D APT reconstruction. Understanding the relationship between the field evaporation behavior of B and the limitations for detecting multi-hit events can provide insight into the signal loss mechanism for B and may suggest ways to improve B detection accuracy. The present work reports data for nominally pure B and for B-implanted silicon (Si) (NIST-SRM2137) at dose levels two-orders of magnitude lower than previously studied by Da Costa, et al. in 2012. Boron concentration profiles collected from SRM2137 specimens qualitatively confirmed a signal loss mechanism is at work in laser pulsed atom probe measurements of B in Si. Ion correlation analysis was used to graphically demonstrate that the detector dead-time results in few same isotope, same charge-state (SISCS) ion pairs being properly recorded in the multi-hit data, explaining why B is consistently under-represented in quantitative analyses. Given the important role of detector dead-time as a signal loss mechanism, the results from three different methods of estimating the detector dead-time are presented. The findings of this study apply to all quantitative analyses that involve multi-hit data, but the dead-time will have the greatest effect on the elements that have a significant quantity of ions detected in multi-hit events. Published by Elsevier B.V.
Andrews, Arthur R.; Bridges, Ana J.; Gomez, Debbie
2014-01-01
Purpose The aims of the study were to evaluate the orthogonality of acculturation for Latinos. Design Regression analyses were used to examine acculturation in two Latino samples (N = 77; N = 40). In a third study (N = 673), confirmatory factor analyses compared unidimensional and bidimensional models. Method Acculturation was assessed with the ARSMA-II (Studies 1 and 2), and language proficiency items from the Children of Immigrants Longitudinal Study (Study 3). Results In Studies 1 and 2, the bidimensional model accounted for slightly more variance (R2Study 1 = .11; R2Study 2 = .21) than the unidimensional model (R2Study 1 = .10; R2Study 2 = .19). In Study 3, the bidimensional model evidenced better fit (Akaike information criterion = 167.36) than the unidimensional model (Akaike information criterion = 1204.92). Discussion/Conclusions Acculturation is multidimensional. Implications for Practice Care providers should examine acculturation as a bidimensional construct. PMID:23361579
Vego, Goran; Kucar-Dragicević, Savka; Koprivanac, Natalija
2008-11-01
The efficiency of providing a waste management system in the coastal part of Croatia consisting of four Dalmatian counties has been modelled. Two multi-criteria decision-making (MCDM) methods, PROMETHEE and GAIA, were applied to assist with the systematic analysis and evaluation of the alternatives. The analysis covered two levels; first, the potential number of waste management centres resulting from possible inter-county cooperation; and second, the relative merits of siting of waste management centres in the coastal or hinterland zone was evaluated. The problem was analysed according to several criteria; and ecological, economic, social and functional criteria sets were identified as relevant to the decision-making process. The PROMETHEE and GAIA methods were shown to be efficient tools for analysing the problem considered. Such an approach provided new insights to waste management planning at the strategic level, and gave a reason for rethinking some of the existing strategic waste management documents in Croatia.
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.
Abnormal dynamics of language in schizophrenia.
Stephane, Massoud; Kuskowski, Michael; Gundel, Jeanette
2014-05-30
Language could be conceptualized as a dynamic system that includes multiple interactive levels (sub-lexical, lexical, sentence, and discourse) and components (phonology, semantics, and syntax). In schizophrenia, abnormalities are observed at all language elements (levels and components) but the dynamic between these elements remains unclear. We hypothesize that the dynamics between language elements in schizophrenia is abnormal and explore how this dynamic is altered. We, first, investigated language elements with comparable procedures in patients and healthy controls. Second, using measures of reaction time, we performed multiple linear regression analyses to evaluate the inter-relationships among language elements and the effect of group on these relationships. Patients significantly differed from controls with respect to sub-lexical/lexical, lexical/sentence, and sentence/discourse regression coefficients. The intercepts of the regression slopes increased in the same order above (from lower to higher levels) in patients but not in controls. Regression coefficients between syntax and both sentence level and discourse level semantics did not differentiate patients from controls. This study indicates that the dynamics between language elements is abnormal in schizophrenia. In patients, top-down flow of linguistic information might be reduced, and the relationship between phonology and semantics but not between syntax and semantics appears to be altered. Published by Elsevier Ireland Ltd.
NASA Astrophysics Data System (ADS)
Song, Lu-Kai; Wen, Jie; Fei, Cheng-Wei; Bai, Guang-Chen
2018-05-01
To improve the computing efficiency and precision of probabilistic design for multi-failure structure, a distributed collaborative probabilistic design method-based fuzzy neural network of regression (FR) (called as DCFRM) is proposed with the integration of distributed collaborative response surface method and fuzzy neural network regression model. The mathematical model of DCFRM is established and the probabilistic design idea with DCFRM is introduced. The probabilistic analysis of turbine blisk involving multi-failure modes (deformation failure, stress failure and strain failure) was investigated by considering fluid-structure interaction with the proposed method. The distribution characteristics, reliability degree, and sensitivity degree of each failure mode and overall failure mode on turbine blisk are obtained, which provides a useful reference for improving the performance and reliability of aeroengine. Through the comparison of methods shows that the DCFRM reshapes the probability of probabilistic analysis for multi-failure structure and improves the computing efficiency while keeping acceptable computational precision. Moreover, the proposed method offers a useful insight for reliability-based design optimization of multi-failure structure and thereby also enriches the theory and method of mechanical reliability design.
NASA Astrophysics Data System (ADS)
Sahoo, Sasmita; Jha, Madan K.
2013-12-01
The potential of multiple linear regression (MLR) and artificial neural network (ANN) techniques in predicting transient water levels over a groundwater basin were compared. MLR and ANN modeling was carried out at 17 sites in Japan, considering all significant inputs: rainfall, ambient temperature, river stage, 11 seasonal dummy variables, and influential lags of rainfall, ambient temperature, river stage and groundwater level. Seventeen site-specific ANN models were developed, using multi-layer feed-forward neural networks trained with Levenberg-Marquardt backpropagation algorithms. The performance of the models was evaluated using statistical and graphical indicators. Comparison of the goodness-of-fit statistics of the MLR models with those of the ANN models indicated that there is better agreement between the ANN-predicted groundwater levels and the observed groundwater levels at all the sites, compared to the MLR. This finding was supported by the graphical indicators and the residual analysis. Thus, it is concluded that the ANN technique is superior to the MLR technique in predicting spatio-temporal distribution of groundwater levels in a basin. However, considering the practical advantages of the MLR technique, it is recommended as an alternative and cost-effective groundwater modeling tool.
Improved score statistics for meta-analysis in single-variant and gene-level association studies.
Yang, Jingjing; Chen, Sai; Abecasis, Gonçalo
2018-06-01
Meta-analysis is now an essential tool for genetic association studies, allowing them to combine large studies and greatly accelerating the pace of genetic discovery. Although the standard meta-analysis methods perform equivalently as the more cumbersome joint analysis under ideal settings, they result in substantial power loss under unbalanced settings with various case-control ratios. Here, we investigate the power loss problem by the standard meta-analysis methods for unbalanced studies, and further propose novel meta-analysis methods performing equivalently to the joint analysis under both balanced and unbalanced settings. We derive improved meta-score-statistics that can accurately approximate the joint-score-statistics with combined individual-level data, for both linear and logistic regression models, with and without covariates. In addition, we propose a novel approach to adjust for population stratification by correcting for known population structures through minor allele frequencies. In the simulated gene-level association studies under unbalanced settings, our method recovered up to 85% power loss caused by the standard methods. We further showed the power gain of our methods in gene-level tests with 26 unbalanced studies of age-related macular degeneration . In addition, we took the meta-analysis of three unbalanced studies of type 2 diabetes as an example to discuss the challenges of meta-analyzing multi-ethnic samples. In summary, our improved meta-score-statistics with corrections for population stratification can be used to construct both single-variant and gene-level association studies, providing a useful framework for ensuring well-powered, convenient, cross-study analyses. © 2018 WILEY PERIODICALS, INC.
Analysis Commons, A Team Approach to Discovery in a Big-Data Environment for Genetic Epidemiology
Brody, Jennifer A.; Morrison, Alanna C.; Bis, Joshua C.; O'Connell, Jeffrey R.; Brown, Michael R.; Huffman, Jennifer E.; Ames, Darren C.; Carroll, Andrew; Conomos, Matthew P.; Gabriel, Stacey; Gibbs, Richard A.; Gogarten, Stephanie M.; Gupta, Namrata; Jaquish, Cashell E.; Johnson, Andrew D.; Lewis, Joshua P.; Liu, Xiaoming; Manning, Alisa K.; Papanicolaou, George J.; Pitsillides, Achilleas N.; Rice, Kenneth M.; Salerno, William; Sitlani, Colleen M.; Smith, Nicholas L.; Heckbert, Susan R.; Laurie, Cathy C.; Mitchell, Braxton D.; Vasan, Ramachandran S.; Rich, Stephen S.; Rotter, Jerome I.; Wilson, James G.; Boerwinkle, Eric; Psaty, Bruce M.; Cupples, L. Adrienne
2017-01-01
Summary paragraph The exploding volume of whole-genome sequence (WGS) and multi-omics data requires new approaches for analysis. As one solution, we have created a cloud-based Analysis Commons, which brings together genotype and phenotype data from multiple studies in a setting that is accessible by multiple investigators. This framework addresses many of the challenges of multi-center WGS analyses, including data sharing mechanisms, phenotype harmonization, integrated multi-omics analyses, annotation, and computational flexibility. In this setting, the computational pipeline facilitates a sequence-to-discovery analysis workflow illustrated here by an analysis of plasma fibrinogen levels in 3996 individuals from the National Heart, Lung, and Blood Institute (NHLBI) Trans-Omics for Precision Medicine (TOPMed) WGS program. The Analysis Commons represents a novel model for transforming WGS resources from a massive quantity of phenotypic and genomic data into knowledge of the determinants of health and disease risk in diverse human populations. PMID:29074945
Chae, Heejoon; Lee, Sangseon; Seo, Seokjun; Jung, Daekyoung; Chang, Hyeonsook; Nephew, Kenneth P; Kim, Sun
2016-12-01
Measuring gene expression, DNA sequence variation, and DNA methylation status is routinely done using high throughput sequencing technologies. To analyze such multi-omics data and explore relationships, reliable bioinformatics systems are much needed. Existing systems are either for exploring curated data or for processing omics data in the form of a library such as R. Thus scientists have much difficulty in investigating relationships among gene expression, DNA sequence variation, and DNA methylation using multi-omics data. In this study, we report a system called BioVLAB-mCpG-SNP-EXPRESS for the integrated analysis of DNA methylation, sequence variation (SNPs), and gene expression for distinguishing cellular phenotypes at the pairwise and multiple phenotype levels. The system can be deployed on either the Amazon cloud or a publicly available high-performance computing node, and the data analysis and exploration of the analysis result can be conveniently done using a web-based interface. In order to alleviate analysis complexity, all the process are fully automated, and graphical workflow system is integrated to represent real-time analysis progression. The BioVLAB-mCpG-SNP-EXPRESS system works in three stages. First, it processes and analyzes multi-omics data as input in the form of the raw data, i.e., FastQ files. Second, various integrated analyses such as methylation vs. gene expression and mutation vs. methylation are performed. Finally, the analysis result can be explored in a number of ways through a web interface for the multi-level, multi-perspective exploration. Multi-level interpretation can be done by either gene, gene set, pathway or network level and multi-perspective exploration can be explored from either gene expression, DNA methylation, sequence variation, or their relationship perspective. The utility of the system is demonstrated by performing analysis of phenotypically distinct 30 breast cancer cell line data set. BioVLAB-mCpG-SNP-EXPRESS is available at http://biohealth.snu.ac.kr/software/biovlab_mcpg_snp_express/. Copyright © 2016 Elsevier Inc. All rights reserved.
Supersonic unstalled flutter. [aerodynamic loading of thin airfoils induced by cascade motion
NASA Technical Reports Server (NTRS)
Adamczyk, J. J.; Goldstein, M. E.; Hartmann, M. J.
1978-01-01
Flutter analyses were developed to predict the onset of supersonic unstalled flutter of a cascade of two-dimensional airfoils. The first of these analyzes the onset of supersonic flutter at low levels of aerodynamic loading (i.e., backpressure), while the second examines the occurrence of supersonic flutter at moderate levels of aerodynamic loading. Both of these analyses are based on the linearized unsteady inviscid equations of gas dynamics to model the flow field surrounding the cascade. These analyses are utilized in a parametric study to show the effects of cascade geometry, inlet Mach number, and backpressure on the onset of single and multi degree of freedom unstalled supersonic flutter. Several of the results are correlated against experimental qualitative observation to validate the models.
Robustness of meta-analyses in finding gene × environment interactions
Shi, Gang; Nehorai, Arye
2017-01-01
Meta-analyses that synthesize statistical evidence across studies have become important analytical tools for genetic studies. Inspired by the success of genome-wide association studies of the genetic main effect, researchers are searching for gene × environment interactions. Confounders are routinely included in the genome-wide gene × environment interaction analysis as covariates; however, this does not control for any confounding effects on the results if covariate × environment interactions are present. We carried out simulation studies to evaluate the robustness to the covariate × environment confounder for meta-regression and joint meta-analysis, which are two commonly used meta-analysis methods for testing the gene × environment interaction or the genetic main effect and interaction jointly. Here we show that meta-regression is robust to the covariate × environment confounder while joint meta-analysis is subject to the confounding effect with inflated type I error rates. Given vast sample sizes employed in genome-wide gene × environment interaction studies, non-significant covariate × environment interactions at the study level could substantially elevate the type I error rate at the consortium level. When covariate × environment confounders are present, type I errors can be controlled in joint meta-analysis by including the covariate × environment terms in the analysis at the study level. Alternatively, meta-regression can be applied, which is robust to potential covariate × environment confounders. PMID:28362796
ERIC Educational Resources Information Center
Jiao, Qun G.; DaRos-Voseles, Denise A.; Collins, Kathleen M. T.; Onwuegbuzie, Anthony J.
2011-01-01
This study examined the extent to which academic procrastination predicted the performance of cooperative groups in graduate-level research methods courses. A total of 28 groups was examined (n = 83 students), ranging in size from 2 to 5 (M = 2.96, SD = 1.10). Multiple regression analyses revealed that neither within-group mean nor within-group…
Lithium in drinking water and suicide mortality.
Kapusta, Nestor D; Mossaheb, Nilufar; Etzersdorfer, Elmar; Hlavin, Gerald; Thau, Kenneth; Willeit, Matthäus; Praschak-Rieder, Nicole; Sonneck, Gernot; Leithner-Dziubas, Katharina
2011-05-01
There is some evidence that natural levels of lithium in drinking water may have a protective effect on suicide mortality. To evaluate the association between local lithium levels in drinking water and suicide mortality at district level in Austria. A nationwide sample of 6460 lithium measurements was examined for association with suicide rates per 100,000 population and suicide standardised mortality ratios across all 99 Austrian districts. Multivariate regression models were adjusted for well-known socioeconomic factors known to influence suicide mortality in Austria (population density, per capita income, proportion of Roman Catholics, as well as the availability of mental health service providers). Sensitivity analyses and weighted least squares regression were used to challenge the robustness of the results. The overall suicide rate (R(2) = 0.15, β = -0.39, t = -4.14, P = 0.000073) as well as the suicide mortality ratio (R(2) = 0.17, β = -0.41, t = -4.38, P = 0.000030) were inversely associated with lithium levels in drinking water and remained significant after sensitivity analyses and adjustment for socioeconomic factors. In replicating and extending previous results, this study provides strong evidence that geographic regions with higher natural lithium concentrations in drinking water are associated with lower suicide mortality rates.
An Exploratory Study of Religion and Trust in Ghana
ERIC Educational Resources Information Center
Addai, Isaac; Opoku-Agyeman, Chris; Ghartey, Helen Tekyiwa
2013-01-01
Based on individual-level data from 2008 Afro-barometer survey, this study explores the relationship between religion (religious affiliation and religious importance) and trust (interpersonal and institutional) among Ghanaians. Employing hierarchical multiple regression technique, our analyses reveal a positive relationship between religious…
Mathematics Readiness of First-Year University Students
ERIC Educational Resources Information Center
Atuahene, Francis; Russell, Tammy A.
2016-01-01
The majority of high school students, particularly underrepresented minorities (URMs) from low socioeconomic backgrounds are graduating from high school less prepared academically for advanced-level college mathematics. Using 2009 and 2010 course enrollment data, several statistical analyses (multiple linear regression, Cochran Mantel Haenszel…
NASA Astrophysics Data System (ADS)
Granger, Victoria; Fromentin, Jean-Marc; Bez, Nicolas; Relini, Giulio; Meynard, Christine N.; Gaertner, Jean-Claude; Maiorano, Porzia; Garcia Ruiz, Cristina; Follesa, Cristina; Gristina, Michele; Peristeraki, Panagiota; Brind'Amour, Anik; Carbonara, Pierluigi; Charilaou, Charis; Esteban, Antonio; Jadaud, Angélique; Joksimovic, Aleksandar; Kallianiotis, Argyris; Kolitari, Jerina; Manfredi, Chiara; Massuti, Enric; Mifsud, Roberta; Quetglas, Antoni; Refes, Wahid; Sbrana, Mario; Vrgoc, Nedo; Spedicato, Maria Teresa; Mérigot, Bastien
2015-01-01
Increasing human pressures and global environmental change may severely affect the diversity of species assemblages and associated ecosystem services. Despite the recent interest in phylogenetic and functional diversity, our knowledge on large spatio-temporal patterns of demersal fish diversity sampled by trawling remains still incomplete, notably in the Mediterranean Sea, one of the most threatened marine regions of the world. We investigated large spatio-temporal diversity patterns by analysing a dataset of 19,886 hauls from 10 to 800 m depth performed annually during the last two decades by standardised scientific bottom trawl field surveys across the Mediterranean Sea, within the MEDITS program. A multi-component (eight diversity indices) and multi-scale (local assemblages, biogeographic regions to basins) approach indicates that only the two most traditional components (species richness and evenness) were sufficient to reflect patterns in taxonomic, phylogenetic or functional richness and divergence. We also put into question the use of widely computed indices that allow comparing directly taxonomic, phylogenetic and functional diversity within a unique mathematical framework. In addition, demersal fish assemblages sampled by trawl do not follow a continuous decreasing longitudinal/latitudinal diversity gradients (spatial effects explained up to 70.6% of deviance in regression tree and generalised linear models), for any of the indices and spatial scales analysed. Indeed, at both local and regional scales species richness was relatively high in the Iberian region, Malta, the Eastern Ionian and Aegean seas, meanwhile the Adriatic Sea and Cyprus showed a relatively low level. In contrast, evenness as well as taxonomic, phylogenetic and functional divergences did not show regional hotspots. All studied diversity components remained stable over the last two decades. Overall, our results highlight the need to use complementary diversity indices through different spatial scales when developing conservation strategies and defining delimitations for protected areas.
Monitoring Building Deformation with InSAR: Experiments and Validation
Yang, Kui; Yan, Li; Huang, Guoman; Chen, Chu; Wu, Zhengpeng
2016-01-01
Synthetic Aperture Radar Interferometry (InSAR) techniques are increasingly applied for monitoring land subsidence. The advantages of InSAR include high accuracy and the ability to cover large areas; nevertheless, research validating the use of InSAR on building deformation is limited. In this paper, we test the monitoring capability of the InSAR in experiments using two landmark buildings; the Bohai Building and the China Theater, located in Tianjin, China. They were selected as real examples to compare InSAR and leveling approaches for building deformation. Ten TerraSAR-X images spanning half a year were used in Permanent Scatterer InSAR processing. These extracted InSAR results were processed considering the diversity in both direction and spatial distribution, and were compared with true leveling values in both Ordinary Least Squares (OLS) regression and measurement of error analyses. The detailed experimental results for the Bohai Building and the China Theater showed a high correlation between InSAR results and the leveling values. At the same time, the two Root Mean Square Error (RMSE) indexes had values of approximately 1 mm. These analyses show that a millimeter level of accuracy can be achieved by means of InSAR technique when measuring building deformation. We discuss the differences in accuracy between OLS regression and measurement of error analyses, and compare the accuracy index of leveling in order to propose InSAR accuracy levels appropriate for monitoring buildings deformation. After assessing the advantages and limitations of InSAR techniques in monitoring buildings, further applications are evaluated. PMID:27999403
[How to fit and interpret multilevel models using SPSS].
Pardo, Antonio; Ruiz, Miguel A; San Martín, Rafael
2007-05-01
Hierarchic or multilevel models are used to analyse data when cases belong to known groups and sample units are selected both from the individual level and from the group level. In this work, the multilevel models most commonly discussed in the statistic literature are described, explaining how to fit these models using the SPSS program (any version as of the 11 th ) and how to interpret the outcomes of the analysis. Five particular models are described, fitted, and interpreted: (1) one-way analysis of variance with random effects, (2) regression analysis with means-as-outcomes, (3) one-way analysis of covariance with random effects, (4) regression analysis with random coefficients, and (5) regression analysis with means- and slopes-as-outcomes. All models are explained, trying to make them understandable to researchers in health and behaviour sciences.
NASA Astrophysics Data System (ADS)
Wang, Jiangbo; Liu, Junhui; Li, Tiantian; Yin, Shuo; He, Xinhui
2018-01-01
The monthly electricity sales forecasting is a basic work to ensure the safety of the power system. This paper presented a monthly electricity sales forecasting method which comprehensively considers the coupled multi-factors of temperature, economic growth, electric power replacement and business expansion. The mathematical model is constructed by using regression method. The simulation results show that the proposed method is accurate and effective.
Kang, Bo-Kyeong; Yu, Eun Sil; Lee, Seung Soo; Lee, Youngjoo; Kim, Namkug; Sirlin, Claude B; Cho, Eun Yoon; Yeom, Suk Keu; Byun, Jae Ho; Park, Seong Ho; Lee, Moon-Gyu
2012-06-01
The aims of this study were to assess the confounding effects of hepatic iron deposition, inflammation, and fibrosis on hepatic steatosis (HS) evaluation by magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) and to assess the accuracies of MRI and MRS for HS evaluation, using histology as the reference standard. In this institutional review board-approved prospective study, 56 patients gave informed consents and underwent chemical-shift MRI and MRS of the liver on a 1.5-T magnetic resonance scanner. To estimate MRI fat fraction (FF), 4 analysis methods were used (dual-echo, triple-echo, multiecho, and multi-interference), and MRS FF was calculated with T2 correction. Degrees of HS, iron deposition, inflammation, and fibrosis were analyzed in liver resection (n = 37) and biopsy (n = 19) specimens. The confounding effects of histology on fat quantification were assessed by multiple linear regression analysis. Using the histologic degree of HS as the reference standard, the accuracies of each method in estimating HS and diagnosing an HS of 5% or greater were determined by linear regression and receiver operating characteristic analyses. Iron deposition significantly confounded estimations of FF by the dual-echo (P < 0.001) and triple-echo (P = 0.033) methods, whereas no histologic feature confounded the multiecho and multi-interference methods or MRS. The MRS (r = 0.95) showed the strongest correlation with histologic degree of HS, followed by the multiecho (r = 0.92), multi-interference (r = 0.91), triple-echo (r = 0.90), and dual-echo (r = 0.85) methods. For diagnosing HS, the areas under the curve tended to be higher for MRS (0.96) and the multiecho (0.95), multi-interference (0.95), and triple-echo (0.95) methods than for the dual-echo method (0.88) (P ≥ 0.13). The multiecho and multi-interference MRI methods and MRS can accurately quantify hepatic fat, with coexisting histologic abnormalities having no confounding effects.
Stability of Early EEG Background Patterns After Pediatric Cardiac Arrest.
Abend, Nicholas S; Xiao, Rui; Kessler, Sudha Kilaru; Topjian, Alexis A
2018-05-01
We aimed to determine whether EEG background characteristics remain stable across discrete time periods during the acute period after resuscitation from pediatric cardiac arrest. Children resuscitated from cardiac arrest underwent continuous conventional EEG monitoring. The EEG was scored in 12-hour epochs for up to 72 hours after return of circulation by an electroencephalographer using a Background Category with 4 levels (normal, slow-disorganized, discontinuous/burst-suppression, or attenuated-featureless) or 2 levels (normal/slow-disorganized or discontinuous/burst-suppression/attenuated-featureless). Survival analyses and mixed-effects ordinal logistic regression models evaluated whether the EEG remained stable across epochs. EEG monitoring was performed in 89 consecutive children. When EEG was assessed as the 4-level Background Category, 30% of subjects changed category over time. Based on initial Background Category, one quarter of the subjects changed EEG category by 24 hours if the initial EEG was attenuated-featureless, by 36 hours if the initial EEG was discontinuous or burst-suppression, by 48 hours if the initial EEG was slow-disorganized, and never if the initial EEG was normal. However, regression modeling for the 4-level Background Category indicated that the EEG did not change over time (odds ratio = 1.06, 95% confidence interval = 0.96-1.17, P = 0.26). Similarly, when EEG was assessed as the 2-level Background Category, 8% of subjects changed EEG category over time. However, regression modeling for the 2-level category indicated that the EEG did not change over time (odds ratio = 1.02, 95% confidence interval = 0.91-1.13, P = 0.75). The EEG Background Category changes over time whether analyzed as 4 levels (30% of subjects) or 2 levels (8% of subjects), although regression analyses indicated that no significant changes occurred over time for the full cohort. These data indicate that the Background Category is often stable during the acute 72 hours after pediatric cardiac arrest and thus may be a useful EEG assessment metric in future studies, but that some subjects do have EEG changes over time and therefore serial EEG assessments may be informative.
Berlin, Conny; Blanch, Carles; Lewis, David J; Maladorno, Dionigi D; Michel, Christiane; Petrin, Michael; Sarp, Severine; Close, Philippe
2012-06-01
The detection of safety signals with medicines is an essential activity to protect public health. Despite widespread acceptance, it is unclear whether recently applied statistical algorithms provide enhanced performance characteristics when compared with traditional systems. Novartis has adopted a novel system for automated signal detection on the basis of disproportionality methods within a safety data mining application (Empirica™ Signal System [ESS]). ESS uses two algorithms for routine analyses: empirical Bayes Multi-item Gamma Poisson Shrinker and logistic regression (LR). A model was developed comprising 14 medicines, categorized as "new" or "established." A standard was prepared on the basis of safety findings selected from traditional sources. ESS results were compared with the standard to calculate the positive predictive value (PPV), specificity, and sensitivity. PPVs of the lower one-sided 5% and 0.05% confidence limits of the Bayes geometric mean (EB05) and of the LR odds ratio (LR0005) almost coincided for all the drug-event combinations studied. There was no obvious difference comparing the PPV of the leading Medical Dictionary for Regulatory Activities (MedDRA) terms to the PPV for all terms. The PPV of narrow MedDRA query searches was higher than that for broad searches. The widely used threshold value of EB05 = 2.0 or LR0005 = 2.0 together with more than three spontaneous reports of the drug-event combination produced balanced results for PPV, sensitivity, and specificity. Consequently, performance characteristics were best for leading terms with narrow MedDRA query searches irrespective of applying Multi-item Gamma Poisson Shrinker or LR at a threshold value of 2.0. This research formed the basis for the configuration of ESS for signal detection at Novartis. Copyright © 2011 John Wiley & Sons, Ltd.
von Elm, Erik; Röllin, Alexandra; Blümle, Anette; Huwiler, Karin; Witschi, Mark; Egger, Matthias
2008-04-05
Not all clinical trials are published, which may distort the evidence that is available in the literature. We studied the publication rate of a cohort of clinical trials and identified factors associated with publication and nonpublication of results. We analysed the protocols of randomized clinical trials of drug interventions submitted to the research ethics committee of University Hospital (Inselspital) Bern, Switzerland from 1988 to 1998. We identified full articles published up to 2006 by searching the Cochrane CENTRAL database (issue 02/2006) and by contacting investigators. We analyzed factors associated with the publication of trials using descriptive statistics and logistic regression models. 451 study protocols and 375 corresponding articles were analyzed. 233 protocols resulted in at least one publication, a publication rate of 52%. A total of 366 (81%) trials were commercially funded, 47 (10%) had non-commercial funding. 346 trials (77%) were multi-centre studies and 272 of these (79%) were international collaborations. In the adjusted logistic regression model non-commercial funding (Odds Ratio [OR] 2.42, 95% CI 1.14-5.17), multi-centre status (OR 2.09, 95% CI 1.03-4.24), international collaboration (OR 1.87, 95% CI 0.99-3.55) and a sample size above the median of 236 participants (OR 2.04, 95% CI 1.23-3.39) were associated with full publication. In this cohort of applications to an ethics committee in Switzerland, only about half of clinical drug trials were published. Large multi-centre trials with non-commercial funding were more likely to be published than other trials, but most trials were funded by industry.
Opdahl, Anders; Venkatesh, Bharath Ambale; Fernandes, Veronica R. S.; Wu, Colin O.; Nasir, Khurram; Choi, Eui-Young; Almeida, Andre L. C.; Rosen, Boaz; Carvalho, Benilton; Edvardsen, Thor; Bluemke, David A.; Lima, Joao A. C.
2014-01-01
OBJECTIVE To investigate the relationship between baseline resting heart rate and incidence of heart failure (HF) and global and regional left ventricular (LV) dysfunction. BACKGROUND The association of resting heart rate to HF and LV function is not well described in an asymptomatic multi-ethnic population. METHODS Participants in the Multi-Ethnic Study of Atherosclerosis had resting heart rate measured at inclusion. Incident HF was registered (n=176) during follow-up (median 7 years) in those who underwent cardiac MRI (n=5000). Changes in ejection fraction (ΔEF) and peak circumferential strain (Δεcc) were measured as markers of developing global and regional LV dysfunction in 1056 participants imaged at baseline and 5 years later. Time to HF (Cox model) and Δεcc and ΔEF (multiple linear regression models) were adjusted for demographics, traditional cardiovascular risk factors, calcium score, LV end-diastolic volume and mass in addition to resting heart rate. RESULTS Cox analysis demonstrated that for 1 bpm increase in resting heart rate there was a 4% greater adjusted relative risk for incident HF (Hazard Ratio: 1.04 (1.02, 1.06 (95% CI); P<0.001). Adjusted multiple regression models demonstrated that resting heart rate was positively associated with deteriorating εcc and decrease in EF, even in analyses when all coronary heart disease events were excluded from the model. CONCLUSION Elevated resting heart rate is associated with increased risk for incident HF in asymptomatic participants in MESA. Higher heart rate is related to development of regional and global LV dysfunction independent of subclinical atherosclerosis and coronary heart disease. PMID:24412444
Introduction--Understanding Education, Fragility and Conflict
ERIC Educational Resources Information Center
Buchert, Lene
2013-01-01
This Introduction discusses approaches to and perspectives on analyzing the complex relationship between education, fragility, and conflict and its underlying causes and dynamics. It argues for the need for contextual and time-bound multi-level analyses of interlinked societal dimensions in order to address the ultimate purposes of education…
Charles, Luenda E; Fekedulegn, Desta; Landsbergis, Paul; Burchfiel, Cecil M; Baron, Sherry; Kaufman, Joel D; Stukovsky, Karen Hinckley; Fujishiro, Kaori; Foy, Capri G; Andrew, Michael E; Diez Roux, Ana V
2014-11-01
To investigate associations of work hours, job control, job demands, job strain, and occupational category with brachial artery flow-mediated dilation (FMD) in 1499 Multi-Ethnic Study of Atherosclerosis participants. Flow-mediated dilation was obtained using high-resolution ultrasound. Mean values of FMD were examined across categories of occupation, work hours, and the other exposures using regression analyses. Occupational category was significantly associated with FMD overall, with blue-collar workers showing the lowest mean values-management/professional = 4.97 ± 0.22%; sales/office = 5.19 ± 0.28%; services = 4.73 ± 0.29%; and blue-collar workers = 4.01 ± 0.26% (adjusted P < 0.001). There was evidence of effect modification by sex (interaction P = 0.031)-significant associations were observed among women (adjusted P = 0.002) and nearly significant results among men (adjusted P = 0.087). Other exposures were not significantly associated with FMD. Differences in endothelial function may account for some of the variation in cardiovascular disease across occupational groups.
Bohnert, Amy S B; German, Danielle; Knowlton, Amy R; Latkin, Carl A
2010-03-01
Social support is a multi-dimensional construct that is important to drug use cessation. The present study identified types of supportive friends among the social network members in a community-based sample and examined the relationship of supporter-type classes with supporter, recipient, and supporter-recipient relationship characteristics. We hypothesized that the most supportive network members and their support recipients would be less likely to be current heroin/cocaine users. Participants (n=1453) were recruited from low-income neighborhoods with a high prevalence of drug use. Participants identified their friends via a network inventory, and all nominated friends were included in a latent class analysis and grouped based on their probability of providing seven types of support. These latent classes were included as the dependent variable in a multi-level regression of supporter drug use, recipient drug use, and other characteristics. The best-fitting latent class model identified five support patterns: friends who provided Little/No Support, Low/Moderate Support, High Support, Socialization Support, and Financial Support. In bivariate models, friends in the High, Low/Moderate, and Financial Support were less likely to use heroin or cocaine and had less conflict with and were more trusted by the support recipient than friends in the Low/No Support class. Individuals with supporters in those same support classes compared to the Low/No Support class were less likely to use heroin or cocaine, or to be homeless or female. Multivariable models suggested similar trends. Those with current heroin/cocaine use were less likely to provide or receive comprehensive support from friends. Published by Elsevier Ireland Ltd.
Aging village doctors in five counties in rural China: situation and implications
2014-01-01
Background The aging population, rapid urbanization, and epidemiology transition in China call for the improvement and adaptation of the health workforce, especially in underserved rural areas. The aging of village doctors (the former “barefoot doctors”) who have served the rural residents for many decades has become a warning signal for the human resources for health in China. This study aims to investigate the village doctors’ aging situation and its implications in rural China. Methods The data reviewed were obtained from the baseline survey of a longitudinal study of rural health workforce in five counties in rural China in 2011. Using a stratified multi-stage cluster sampling process, the baseline data was collected through the self-administered structured Village Doctor Questionnaire. Descriptive analyses, correlation analyses, and multivariate linear regression with interaction terms were conducted with the statistics software Stata 12.0. Results The average age of the 1,927 village doctors was 49.3 years (95% CI 48.8 to 49.9), 870 (45.2%) of whom were aging (50 years or older). Both the age and the recruitment time of the village doctors were demonstrated to have a bimodal distribution. A greater proportion of the male village doctors were aging. Furthermore, aging of the village doctors was significantly correlated to their education level, type of qualification, practicing methods, and their status as village clinic directors (P <0.05, respectively). As shown in the regression models, aging village doctors provided significantly more outpatient services to rural residents (P <0.01) but without an increase in income, and their expected pension was lower (P <0.01), compared with their non-aging counterparts. Conclusions Aging of village doctors is a serious and imperative issue in China, which has a complex and profound impact on the rural health system. Greater attention should be paid to the construction of the pension system and the replenishment of the village doctors with qualified medical graduates. PMID:24973946
A cross-sectional analysis of green space prevalence and mental wellbeing in England.
Houlden, Victoria; Weich, Scott; Jarvis, Stephen
2017-05-17
With urbanisation increasing, it is important to understand how to design changing environments to promote mental wellbeing. Evidence suggests that local-area proportions of green space may be associated with happiness and life satisfaction; however, the available evidence on such associations with more broadly defined mental wellbeing in still very scarce. This study aimed to establish whether the amount of neighbourhood green space was associated with mental wellbeing. Data were drawn from Understanding Society, a national survey of 30,900 individuals across 11,096 Census Lower-Layer Super Output Areas (LSOAs) in England, over the period 2009-2010. Measures included the multi-dimensional Warwick-Edinburgh Mental Well-Being Scale (SWEMWBS) and LSOA proportion of green space, which was derived from the General Land Use Database (GLUD), and were analysed using linear regression, while controlling for individual, household and area-level factors. Those living in areas with greater proportions of green space had significantly higher mental wellbeing scores in unadjusted analyses (an expected increase of 0.17 points (95% CI 0.11, 0.23) in the SWEMWBS score for a standard deviation increase of green space). However, after adjustment for confounding by respondent sociodemographic characteristics and urban/rural location, the association was attenuated to the null (regression coefficient B = - 0.01, 95% CI -0.08, 0.05, p = 0.712). While the green space in an individual's local area has been shown through other research to be related to aspects of mental health such as happiness and life satisfaction, the association with multidimensional mental wellbeing is much less clear from our results. While we did not find a statistically significant association between the amount of green space in residents' local areas and mental wellbeing, further research is needed to understand whether other features of green space, such as accessibility, aesthetics or use, are important for mental wellbeing.
Aging village doctors in five counties in rural China: situation and implications.
Xu, Huiwen; Zhang, Weijun; Gu, Linni; Qu, Zhiyong; Sa, Zhihong; Zhang, Xiulan; Tian, Donghua
2014-06-28
The aging population, rapid urbanization, and epidemiology transition in China call for the improvement and adaptation of the health workforce, especially in underserved rural areas. The aging of village doctors (the former "barefoot doctors") who have served the rural residents for many decades has become a warning signal for the human resources for health in China. This study aims to investigate the village doctors' aging situation and its implications in rural China. The data reviewed were obtained from the baseline survey of a longitudinal study of rural health workforce in five counties in rural China in 2011. Using a stratified multi-stage cluster sampling process, the baseline data was collected through the self-administered structured Village Doctor Questionnaire. Descriptive analyses, correlation analyses, and multivariate linear regression with interaction terms were conducted with the statistics software Stata 12.0. The average age of the 1,927 village doctors was 49.3 years (95% CI 48.8 to 49.9), 870 (45.2%) of whom were aging (50 years or older). Both the age and the recruitment time of the village doctors were demonstrated to have a bimodal distribution. A greater proportion of the male village doctors were aging. Furthermore, aging of the village doctors was significantly correlated to their education level, type of qualification, practicing methods, and their status as village clinic directors (P <0.05, respectively). As shown in the regression models, aging village doctors provided significantly more outpatient services to rural residents (P <0.01) but without an increase in income, and their expected pension was lower (P <0.01), compared with their non-aging counterparts. Aging of village doctors is a serious and imperative issue in China, which has a complex and profound impact on the rural health system. Greater attention should be paid to the construction of the pension system and the replenishment of the village doctors with qualified medical graduates.
Nazari, Seyed Saeed Hashemi; Mokhayeri, Yaser; Mansournia, Mohammad Ali; Khodakarim, Soheila; Soori, Hamid
2018-05-21
Some studies shed light on the association between dietary patterns and stroke, though, none of them applied reduced rank regression (RRR). Therefore, we sought to extract dietary patterns using RRR, and showed how well the extracted scores by RRR predict stroke in comparison to those scores produced by partial least squares (PLS) and principal components regression (PCR). Diet data at baseline with four response variables including body mass index (BMI), fibrinogen, IL-6, low-density lipoprotein (LDL) cholesterol were used to extract dietary patterns. Analyses were based on 5468 men and women aged 45-84 y who had no clinical cardiovascular diseases (CVD) from Multi-Ethnic Study of Atherosclerosis (MESA). Dietary patterns were created by three methods RRR, PLS, and PCR. The RRR1 was positively associated with stroke incidence in both models (for model 1 hazard ratio (HR): 7.49; 95% CI: 1.66, 33.69 P for trend = 0.01 and for model 2 HR: 6.83; 95% CI: 1.51, 30.87 for quintile 5 compared with the reference category P for trend = 0.02). The RRR1, PLS1, and PCR1 were high in fats and oils, poultry, tomatoes, fried potato and processed meat. Additionally, RRR1 and PLS1 were high in dark-yellow and cruciferous vegetables which negatively were correlated with the first dietary pattern. Mainly according to the RRR, we identified that a dietary pattern high in fats and oil, poultry, non-diet soda, processed meat, tomatoes, legumes, chicken, tuna and egg salad, fried potato and low in dark-yellow and cruciferous vegetables may increase the incidence of stroke.
Wang, Ningjian; Han, Bing; Li, Qin; Chen, Yi; Chen, Yingchao; Xia, Fangzhen; Lin, Dongping; Jensen, Michael D; Lu, Yingli
2015-07-16
To date, no study has explored the association between androgen levels and 25-hydroxyvitamin D (25(OH)D) levels in Chinese men. We aimed to investigate the relationship between 25(OH)D levels and total and free testosterone (T), sex hormone binding globulin (SHBG), estradiol, and hypogonadism in Chinese men. Our data, which were based on the population, were collected from 16 sites in East China. There were 2,854 men enrolled in the study, with a mean (SD) age of 53.0 (13.5) years. Hypogonadism was defined as total T <11.3 nmol/L or free T <22.56 pmol/L. The 25(OH)D, follicle-stimulating hormone, luteinizing hormone, total T, estradiol and SHBG were measured using chemiluminescence and free T by enzyme-linked immune-sorbent assay. The associations between 25(OH)D and reproductive hormones and hypogonadism were analyzed using linear regression and binary logistic regression analyses, respectively. A total of 713 (25.0 %) men had hypogonadism with significantly lower 25(OH)D levels but greater BMI and HOMA-IR. Using linear regression, after fully adjusting for age, residence area, economic status, smoking, BMI, HOMA-IR, diabetes and systolic pressure, 25(OH)D was associated with total T and estradiol (P < 0.05). In the logistic regression analyses, increased quartiles of 25(OH)D were associated with significantly decreased odds ratios of hypogonadism (P for trend <0.01). This association, which was considerably attenuated by BMI and HOMA-IR, persisted in the fully adjusted model (P for trend <0.01) in which for the lowest compared with the highest quartile of 25(OH)D, the odds ratio of hypogonadism was 1.50 (95 % CI, 1.14, 1.97). A lower vitamin D level was associated with a higher prevalence of hypogonadism in Chinese men. This association might, in part, be explained by adiposity and insulin resistance and warrants additional investigation.
Incorporating Measurement Error from Modeled Air Pollution Exposures into Epidemiological Analyses.
Samoli, Evangelia; Butland, Barbara K
2017-12-01
Outdoor air pollution exposures used in epidemiological studies are commonly predicted from spatiotemporal models incorporating limited measurements, temporal factors, geographic information system variables, and/or satellite data. Measurement error in these exposure estimates leads to imprecise estimation of health effects and their standard errors. We reviewed methods for measurement error correction that have been applied in epidemiological studies that use model-derived air pollution data. We identified seven cohort studies and one panel study that have employed measurement error correction methods. These methods included regression calibration, risk set regression calibration, regression calibration with instrumental variables, the simulation extrapolation approach (SIMEX), and methods under the non-parametric or parameter bootstrap. Corrections resulted in small increases in the absolute magnitude of the health effect estimate and its standard error under most scenarios. Limited application of measurement error correction methods in air pollution studies may be attributed to the absence of exposure validation data and the methodological complexity of the proposed methods. Future epidemiological studies should consider in their design phase the requirements for the measurement error correction method to be later applied, while methodological advances are needed under the multi-pollutants setting.
Methodological uncertainties in multi-regression analyses of middle-atmospheric data series.
Kerzenmacher, Tobias E; Keckhut, Philippe; Hauchecorne, Alain; Chanin, Marie-Lise
2006-07-01
Multi-regression analyses have often been used recently to detect trends, in particular in ozone or temperature data sets in the stratosphere. The confidence in detecting trends depends on a number of factors which generate uncertainties. Part of these uncertainties comes from the random variability and these are what is usually considered. They can be statistically estimated from residual deviations between the data and the fitting model. However, interferences between different sources of variability affecting the data set, such as the Quasi-Biennal Oscillation (QBO), volcanic aerosols, solar flux variability and the trend can also be a critical source of errors. This type of error has hitherto not been well quantified. In this work an artificial data series has been generated to carry out such estimates. The sources of errors considered here are: the length of the data series, the dependence on the choice of parameters used in the fitting model and the time evolution of the trend in the data series. Curves provided here, will permit future studies to test the magnitude of the methodological bias expected for a given case, as shown in several real examples. It is found that, if the data series is shorter than a decade, the uncertainties are very large, whatever factors are chosen to identify the source of the variability. However the errors can be limited when dealing with natural variability, if a sufficient number of periods (for periodic forcings) are covered by the analysed dataset. However when analysing the trend, the response to volcanic eruption induces a bias, whatever the length of the data series. The signal to noise ratio is a key factor: doubling the noise increases the period for which data is required in order to obtain an error smaller than 10%, from 1 to 3-4 decades. Moreover, if non-linear trends are superimposed on the data, and if the length of the series is longer than five years, a non-linear function has to be used to estimate trends. When applied to real data series, and when a breakpoint in the series occurs, the study reveals that data extending over 5 years are needed to detect a significant change in the slope of the ozone trends at mid-latitudes.
Walk Score® and Transit Score® and Walking in the Multi-Ethnic Study of Atherosclerosis
Hirsch, Jana A.; Moore, Kari A.; Evenson, Kelly R.; Rodriguez, Daniel A; Diez Roux, Ana V.
2013-01-01
Background Walk Score® and Transit Score® are open-source measures of the neighborhood built environment to support walking (“walkability”) and access to transportation. Purpose To investigate associations of Street Smart Walk Score and Transit Score with self-reported transport and leisure walking using data from a large multi-city and diverse population-based sample of adults. Methods Data from a sample of 4552 residents of Baltimore MD; Chicago IL; Forsyth County NC; Los Angeles CA; New York NY; and St. Paul MN from the Multi-Ethnic Study of Atherosclerosis (2010–2012) were linked to Walk Score and Transit Score (collected in 2012). Logistic and linear regression models estimated ORs of not walking and mean differences in minutes walked, respectively, associated with continuous and categoric Walk Score and Transit Score. All analyses were conducted in 2012. Results After adjustment for site, key sociodemographic, and health variables, a higher Walk Score was associated with lower odds of not walking for transport and more minutes/week of transport walking. Compared to those in a “walker’s paradise,” lower categories of Walk Score were associated with a linear increase in odds of not transport walking and a decline in minutes of leisure walking. An increase in Transit Score was associated with lower odds of not transport walking or leisure walking, and additional minutes/week of leisure walking. Conclusions Walk Score and Transit Score appear to be useful as measures of walkability in analyses of neighborhood effects. PMID:23867022
The role of action planning and plan enactment for smoking cessation
2013-01-01
Background Several studies have reemphasized the role of action planning. Yet, little attention has been paid to the role of plan enactment. This study assesses the determinants and the effects of action planning and plan enactment on smoking cessation. Methods One thousand and five participants completed questionnaires at baseline and at follow-ups after one and six months. Factors queried were part of the I-Change model. Descriptive analyses were used to assess which plans were enacted the most. Multivariate linear regression analyses were used to assess whether the intention to quit smoking predicted action planning and plan enactment, and to assess which factors would predict quitting behavior. Subsequently, both multivariate and univariate regression analyses were used to assess which particular action plans would be most effective in predicting quitting behavior. Similar analyses were performed among a subsample of smokers prepared to quit within one month. Results Smokers who intended to quit smoking within the next month had higher levels of action planning than those intending to quit within a year. Additional predictors of action planning were being older, being female, having relatively low levels of cigarette dependence, perceiving more positive and negative consequences of quitting, and having high self-efficacy toward quitting. Plan enactment was predicted by baseline intention to quit and levels of action planning. Regression analysis revealed that smoking cessation after six months was predicted by low levels of depression, having a non-smoking partner, the intention to quit within the next month, and plan enactment. Only 29% of the smokers who executed relatively few plans had quit smoking versus 59% of the smokers who executed many plans. The most effective preparatory plans for smoking cessation were removing all tobacco products from the house and choosing a specific date to quit. Conclusion Making preparatory plans to quit smoking is important because it also predicts plan enactment, which is predictive of smoking cessation. Not all action plans were found to be predictive of smoking cessation. The effects of planning were not very much different between the total sample and smokers prepared to quit within one month. PMID:23622256
Bozorgmehr, Kayvan; San Sebastian, Miguel; Brenner, Hermann; Razum, Oliver; Maier, Werner; Saum, Kai-Uwe; Holleczek, Bernd; Miksch, Antje; Szecsenyi, Joachim
2015-03-10
Disease Management Programmes (DMPs) have been introduced in Germany ten years ago with the aim to improve effectiveness and equity of care, but little is known about the degree to which enrolment in the programme meets the principles of equity in health care. We aimed to analyse horizontal equity in DMP enrolment among patients with coronary heart disease (CHD). Cross-sectional analysis of horizontal inequities in physician-reported enrolment in the DMP for CHD in a large population-based cohort-study in Germany (2008-2010). We calculated horizontal inequity indices (HII) and their 95% confidence intervals [95%CI] for predicted need-standardised DMP enrolment across two measures of socio-economic status (SES) (educational attainment, regional deprivation) stratified by sex. Need-standardised DMP enrolment was predicted in multi-level logistic regression models. Among N = 1,280 individuals aged 55-84 years and diagnosed with CHD, DMP enrolment rates were 22.2% (women) and 35.0% (men). Education-related inequities in need-standardised DMP enrolment favoured groups with lower education, but HII estimates were not significant. Deprivation-related inequities among women significantly favoured groups with higher SES (HII = 0.086 [0.007 ; 0.165]. No such deprivation-related inequities were seen among men (HII = 0.014 [-0.048 ; 0.077]). Deprivation-related inequities across the whole population favoured groups with higher SES (HII estimates not significant). Need-standardised DMP enrolment was fairly equitable across educational levels. Deprivation-related inequities in DMP enrolment favoured women living in less deprived areas relative to those living in areas with higher deprivation. Further research is needed to gain a better understanding of the mechanisms that contribute to deprivation-related horizontal inequities in DMP enrolment among women.
Grigsby-Toussaint, Diana S; Turi, Kedir N; Krupa, Mark; Williams, Natasha J; Pandi-Perumal, Seithikurippu R; Jean-Louis, Girardin
2015-09-01
Exposure to the natural environment may improve health behaviors and mental health outcomes such as increased levels of physical activity and lower levels of depression associated with sleep quality. Little is known about the relationship between insufficient sleep and the natural environment. To determine whether exposure to attributes of the natural environment (e.g., greenspace) attenuates the likelihood of reporting insufficient sleep among US adults. Multiple logistic regression models were used to explore the association between self-reported days of insufficient sleep (in the past 30days) and access to the natural environment in a multi-ethnic, nationally representative sample (n=255,171) of US adults ≥18years of age enrolled in the 2010 Behavioral Risk Factor Surveillance System. Using 1-to-6days of insufficient sleep as the referent group for all analyses, lower odds of exposure to natural amenities were observed for individuals reporting 21-to-29days (OR=0.843, 95% confidence interval (CI)=0.747, 0.951) of insufficient sleep. In stratified analyses, statistically significant lower odds of exposure to natural amenities were found among men reporting 7-to-13-days (OR=0.911, 95% CI=0.857, 0.968), 21-to-29-days (OR=0.838, 95% CI=0.759, 0.924), and 30-days (OR=0.860, 95% CI=0.784, 0.943) of insufficient sleep. Greenspace access was also protective against insufficient sleep for men and individuals aged 65+. In a representative sample of US adults, access to the natural environment attenuated the likelihood of reporting insufficient sleep, particularly among men. Additional studies are needed to examine the impact of natural environment exposure on sleep insufficiency across various socio-demographic groups. Copyright © 2015 Elsevier Inc. All rights reserved.
Oguri, Tomoko; Yoshinaga, Jun; Toshima, Hiroki; Mizumoto, Yoshifumi; Hatakeyama, Shota; Tokuoka, Susumu
2016-01-01
Inorganic arsenic (iAs) has been known as a testicular toxicant in experimental rodents. Possible association between iAs exposure and semen quality (semen volume, sperm concentration, and sperm motility) was explored in male partners of couples (n = 42) who visited a gynecology clinic in Tokyo for infertility consultation. Semen parameters were measured according to WHO guideline at the clinic, and urinary iAs and methylarsonic acid (MMA), and dimethylarsinic acid concentrations were determined by liquid chromatography-hydride generation-ICP mass spectrometry. Biological attributes, dietary habits, and exposure levels to other chemicals with known effects on semen parameters were taken into consideration as covariates. Multiple regression analyses and logistic regression analyses did not find iAs exposure as significant contributor to semen parameters. Lower exposure level of subjects (estimated to be 0.5 μg kg(-1) day(-1)) was considered a reason of the absence of adverse effects on semen parameters, which were seen in rodents dosed with 4-7.5 mg kg(-1).
Effects of perceived stress and uplifts on inflammation and coagulability.
Jain, Shamini; Mills, Paul J; von Känel, Roland; Hong, Suzi; Dimsdale, Joel E
2007-01-01
We investigated whether depressed mood and chronic hassles and uplifts predicted levels of hemostasis markers D-Dimer and type-1 plasminogen activator inhibitor (PAI-1), as well as the proinflammatory markers interleukin-6 (IL-6) and soluble intercellular adhesion molecule-1 (sICAM-1) in 108 healthy individuals. One hundred eight African-American and Euro-American men and women were studied (58 men, 50 women; mean age = 36.5 +/- 8 years). D-Dimer, PAI-1, IL-6, and sICAM-1 plasma levels were analyzed from fasting venous blood samples. Data were analyzed via hierarchical linear regression and followed with partial correlation analysis. Regression analyses combined with partial correlation analyses suggested that increases in hassle frequency predicted elevated levels of sICAM-1 (p= .034), and increases in hassle severity predicted elevated levels of D-Dimer (p= .017). Increases in uplift intensity predicted lower levels of PAI-1 (p= .004) as well as showed a trend for decreased IL-6 (p= .069). Depressed mood did not significantly predict any dependent variable. These results were independent of sociodemographic, biological, and other related mood variables. The findings suggest that for even relatively healthy persons, increased perceptions of hassles are independently associated with greater inflammation and hypercoagulability, whereas increased perceptions of uplifts are independently associated with decreased hypercoagulability.
Bilano, Ver Luanni; Ota, Erika; Ganchimeg, Togoobaatar; Mori, Rintaro; Souza, João Paulo
2014-01-01
Background Pre-eclampsia has an immense adverse impact on maternal and perinatal health especially in low- and middle-income settings. We aimed to estimate the associations between pre-eclampsia/eclampsia and its risk factors, and adverse maternal and perinatal outcomes. Methods We performed a secondary analysis of the WHO Global Survey on Maternal and Perinatal Health. The survey was a multi-country, facility-based cross-sectional study. A global sample consisting of 24 countries from three regions and 373 health facilities was obtained via a stratified multi-stage cluster sampling design. Maternal and offspring data were extracted from records using standardized questionnaires. Multi-level logistic regression modelling was conducted with random effects at the individual, facility and country levels. Results Data for 276,388 mothers and their infants was analysed. The prevalence of pre-eclampsia/eclampsia in the study population was 10,754 (4%). At the individual level, sociodemographic characteristics of maternal age ≥30 years and low educational attainment were significantly associated with higher risk of pre-eclampsia/eclampsia. As for clinical and obstetric variables, high body mass index (BMI), nulliparity (AOR: 2.04; 95%CI 1.92–2.16), absence of antenatal care (AOR: 1.41; 95%CI 1.26–1.57), chronic hypertension (AOR: 7.75; 95%CI 6.77–8.87), gestational diabetes (AOR: 2.00; 95%CI 1.63–2.45), cardiac or renal disease (AOR: 2.38; 95%CI 1.86–3.05), pyelonephritis or urinary tract infection (AOR: 1.13; 95%CI 1.03–1.24) and severe anemia (AOR: 2.98; 95%CI 2.47–3.61) were found to be significant risk factors, while having >8 visits of antenatal care was protective (AOR: 0.90; 95%CI 0.83–0.98). Pre-eclampsia/eclampsia was found to be a significant risk factor for maternal death, perinatal death, preterm birth and low birthweight. Conclusion Chronic hypertension, obesity and severe anemia were the highest risk factors of preeclampsia/eclampsia. Implementation of effective interventions prioritizing risk factors, provision of quality health services during pre-pregnancy and during pregnancy for joint efforts in the areas of maternal health are recommended. PMID:24657964
Cunningham, Shannon N; Vandiver, Donna M
2016-03-06
Research has demonstrated that co-offending dyads and groups often use more violence than individual offenders. Despite the attention given to co-offending by the research community, kidnapping remains understudied. Stranger kidnappings are more likely than non-stranger kidnappings to involve the use of a weapon. Public fear of stranger kidnapping warrants further examination of this specific crime, including differences between those committed by solo and multi-offender groups. The current study uses National Incident-Based Reporting System (NIBRS) data to assess differences in use of violence among 4,912 stranger kidnappings by solo offenders and multi-offender groups using cross-tabulations, ordinal regression, and logistic regression. The results indicate that violent factors are significantly more common in multi-offender incidents, and that multi-offender groups have fewer arrests than solo offenders. The implications of these findings are discussed. © The Author(s) 2016.
Li, Juntao; Wang, Yanyan; Jiang, Tao; Xiao, Huimin; Song, Xuekun
2018-05-09
Diagnosing acute leukemia is the necessary prerequisite to treating it. Multi-classification on the gene expression data of acute leukemia is help for diagnosing it which contains B-cell acute lymphoblastic leukemia (BALL), T-cell acute lymphoblastic leukemia (TALL) and acute myeloid leukemia (AML). However, selecting cancer-causing genes is a challenging problem in performing multi-classification. In this paper, weighted gene co-expression networks are employed to divide the genes into groups. Based on the dividing groups, a new regularized multinomial regression with overlapping group lasso penalty (MROGL) has been presented to simultaneously perform multi-classification and select gene groups. By implementing this method on three-class acute leukemia data, the grouped genes which work synergistically are identified, and the overlapped genes shared by different groups are also highlighted. Moreover, MROGL outperforms other five methods on multi-classification accuracy. Copyright © 2017. Published by Elsevier B.V.
Modak, Nabanita; Spence, Kelley; Sood, Saloni; Rosati, Jacky Ann
2015-01-01
Air emissions from the U.S. pulp and paper sector have been federally regulated since 1978; however, regulations are periodically reviewed and revised to improve efficiency and effectiveness of existing emission standards. The Industrial Sectors Integrated Solutions (ISIS) model for the pulp and paper sector is currently under development at the U.S. Environmental Protection Agency (EPA), and can be utilized to facilitate multi-pollutant, sector-based analyses that are performed in conjunction with regulatory development. The model utilizes a multi-sector, multi-product dynamic linear modeling framework that evaluates the economic impact of emission reduction strategies for multiple air pollutants. The ISIS model considers facility-level economic, environmental, and technical parameters, as well as sector-level market data, to estimate the impacts of environmental regulations on the pulp and paper industry. Specifically, the model can be used to estimate U.S. and global market impacts of new or more stringent air regulations, such as impacts on product price, exports and imports, market demands, capital investment, and mill closures. One major challenge to developing a representative model is the need for an extensive amount of data. This article discusses the collection and processing of data for use in the model, as well as the methods used for building the ISIS pulp and paper database that facilitates the required analyses to support the air quality management of the pulp and paper sector.
Modak, Nabanita; Spence, Kelley; Sood, Saloni; Rosati, Jacky Ann
2015-01-01
Air emissions from the U.S. pulp and paper sector have been federally regulated since 1978; however, regulations are periodically reviewed and revised to improve efficiency and effectiveness of existing emission standards. The Industrial Sectors Integrated Solutions (ISIS) model for the pulp and paper sector is currently under development at the U.S. Environmental Protection Agency (EPA), and can be utilized to facilitate multi-pollutant, sector-based analyses that are performed in conjunction with regulatory development. The model utilizes a multi-sector, multi-product dynamic linear modeling framework that evaluates the economic impact of emission reduction strategies for multiple air pollutants. The ISIS model considers facility-level economic, environmental, and technical parameters, as well as sector-level market data, to estimate the impacts of environmental regulations on the pulp and paper industry. Specifically, the model can be used to estimate U.S. and global market impacts of new or more stringent air regulations, such as impacts on product price, exports and imports, market demands, capital investment, and mill closures. One major challenge to developing a representative model is the need for an extensive amount of data. This article discusses the collection and processing of data for use in the model, as well as the methods used for building the ISIS pulp and paper database that facilitates the required analyses to support the air quality management of the pulp and paper sector. PMID:25806516
Van de Voorde, Tim; Vlaeminck, Jeroen; Canters, Frank
2008-01-01
Urban growth and its related environmental problems call for sustainable urban management policies to safeguard the quality of urban environments. Vegetation plays an important part in this as it provides ecological, social, health and economic benefits to a city's inhabitants. Remotely sensed data are of great value to monitor urban green and despite the clear advantages of contemporary high resolution images, the benefits of medium resolution data should not be discarded. The objective of this research was to estimate fractional vegetation cover from a Landsat ETM+ image with sub-pixel classification, and to compare accuracies obtained with multiple stepwise regression analysis, linear spectral unmixing and multi-layer perceptrons (MLP) at the level of meaningful urban spatial entities. Despite the small, but nevertheless statistically significant differences at pixel level between the alternative approaches, the spatial pattern of vegetation cover and estimation errors is clearly distinctive at neighbourhood level. At this spatially aggregated level, a simple regression model appears to attain sufficient accuracy. For mapping at a spatially more detailed level, the MLP seems to be the most appropriate choice. Brightness normalisation only appeared to affect the linear models, especially the linear spectral unmixing. PMID:27879914
ERIC Educational Resources Information Center
Mulford, Bill; Silins, Halia
2011-01-01
Purpose: This study aims to present revised models and a reconceptualisation of successful school principalship for improved student outcomes. Design/methodology/approach: The study's approach is qualitative and quantitative, culminating in model building and multi-level statistical analyses. Findings: Principals who promote both capacity building…
Decision-makers at all scales are faced with setting priorities for both use of limited resources and for risk management. While there are all kinds of monitoring data and models to project conditions at different spatial and temporal scales, synthesized information to establish ...
Gamal El-Dien, Omnia; Ratcliffe, Blaise; Klápště, Jaroslav; Chen, Charles; Porth, Ilga; El-Kassaby, Yousry A
2015-05-09
Genomic selection (GS) in forestry can substantially reduce the length of breeding cycle and increase gain per unit time through early selection and greater selection intensity, particularly for traits of low heritability and late expression. Affordable next-generation sequencing technologies made it possible to genotype large numbers of trees at a reasonable cost. Genotyping-by-sequencing was used to genotype 1,126 Interior spruce trees representing 25 open-pollinated families planted over three sites in British Columbia, Canada. Four imputation algorithms were compared (mean value (MI), singular value decomposition (SVD), expectation maximization (EM), and a newly derived, family-based k-nearest neighbor (kNN-Fam)). Trees were phenotyped for several yield and wood attributes. Single- and multi-site GS prediction models were developed using the Ridge Regression Best Linear Unbiased Predictor (RR-BLUP) and the Generalized Ridge Regression (GRR) to test different assumption about trait architecture. Finally, using PCA, multi-trait GS prediction models were developed. The EM and kNN-Fam imputation methods were superior for 30 and 60% missing data, respectively. The RR-BLUP GS prediction model produced better accuracies than the GRR indicating that the genetic architecture for these traits is complex. GS prediction accuracies for multi-site were high and better than those of single-sites while multi-site predictability produced the lowest accuracies reflecting type-b genetic correlations and deemed unreliable. The incorporation of genomic information in quantitative genetics analyses produced more realistic heritability estimates as half-sib pedigree tended to inflate the additive genetic variance and subsequently both heritability and gain estimates. Principle component scores as representatives of multi-trait GS prediction models produced surprising results where negatively correlated traits could be concurrently selected for using PCA2 and PCA3. The application of GS to open-pollinated family testing, the simplest form of tree improvement evaluation methods, was proven to be effective. Prediction accuracies obtained for all traits greatly support the integration of GS in tree breeding. While the within-site GS prediction accuracies were high, the results clearly indicate that single-site GS models ability to predict other sites are unreliable supporting the utilization of multi-site approach. Principle component scores provided an opportunity for the concurrent selection of traits with different phenotypic optima.
Kumar, Santosh; Calvo, Rocio; Avendano, Mauricio; Sivaramakrishnan, Kavita; Berkman, Lisa F
2012-03-01
High levels of social capital and social integration are associated with self-rated health in many developed countries. However, it is not known whether this association extends to non-western and less economically advanced countries. We examine associations between social support, volunteering, and self-rated health in 139 low-, middle- and high-income countries. Data come from the Gallup World Poll, an internationally comparable survey conducted yearly from 2005 to 2009 for those 15 and over. Volunteering was measured by self-reports of volunteering to an organization in the past month. Social support was based on self-reports of access to support from relatives and friends. We started by estimating random coefficient (multi-level) models and then used multivariate logistic regression to model health as a function of social support and volunteering, controlling for age, gender, education, marital status, and religiosity. We found statistically significant evidence of cross-national variation in the association between social capital variables and self-rated health. In the multivariate logistic model, self-rated health were significantly associated with having social support from friends and relatives and volunteering. Results from stratified analyses indicate that these associations are strikingly consistent across countries. Our results indicate that the link between social capital and health is not restricted to high-income countries but extends across many geographical regions regardless of their national-income level. Copyright © 2012 Elsevier Ltd. All rights reserved.
Managing fever in children: a national survey of parents' knowledge and practices in France.
Bertille, Nathalie; Fournier-Charrière, Elisabeth; Pons, Gérard; Chalumeau, Martin
2013-01-01
Identifying targets to improve parental practices for managing fever in children is the first step to reducing the overloaded healthcare system related to this common symptom. We aimed to study parents' knowledge and practices and their determinants in managing fever symptoms in children in France as compared with current recommendations. We conducted an observational national study between 2007 and 2008 of French general practitioners, primary care pediatricians and pharmacists. These healthcare professionals (HPs) were asked to include 5 consecutive patients from 1 month to 12 years old with fever for up to 48 hr who were accompanied by a family member. Parents completed a questionnaire about their knowledge of fever in children and their attitudes about the current fever episode. We used a multilevel logistic regression model to assess the joint effects of patient- and HP-level variables. In all, 1,534 HPs (participation rate 13%) included 6,596 children. Parental concordance with current recommendations for temperature measurement methods, the threshold for defining fever, and physical (oral hydration, undressing, room temperature) and drug treatment was 89%, 61%, 15%, and 23%, respectively. Multivariate multi-level analyses revealed a significant HP effect. In general, high concordance with recommendations was associated with high educational level of parents and the HP consulted being a pediatrician. In France, parents' knowledge and practices related to managing fever symptoms in children frequently differ from recommendations. Targeted health education interventions are needed to effectively manage fever symptoms in children.
Managing Fever in Children: A National Survey of Parents' Knowledge and Practices in France
Bertille, Nathalie; Fournier-Charrière, Elisabeth; Pons, Gérard; Chalumeau, Martin
2013-01-01
Introduction Identifying targets to improve parental practices for managing fever in children is the first step to reducing the overloaded healthcare system related to this common symptom. We aimed to study parents' knowledge and practices and their determinants in managing fever symptoms in children in France as compared with current recommendations. Methods We conducted an observational national study between 2007 and 2008 of French general practitioners, primary care pediatricians and pharmacists. These healthcare professionals (HPs) were asked to include 5 consecutive patients from 1 month to 12 years old with fever for up to 48 hr who were accompanied by a family member. Parents completed a questionnaire about their knowledge of fever in children and their attitudes about the current fever episode. We used a multilevel logistic regression model to assess the joint effects of patient- and HP-level variables. Results In all, 1,534 HPs (participation rate 13%) included 6,596 children. Parental concordance with current recommendations for temperature measurement methods, the threshold for defining fever, and physical (oral hydration, undressing, room temperature) and drug treatment was 89%, 61%, 15%, and 23%, respectively. Multivariate multi-level analyses revealed a significant HP effect. In general, high concordance with recommendations was associated with high educational level of parents and the HP consulted being a pediatrician. Conclusions In France, parents' knowledge and practices related to managing fever symptoms in children frequently differ from recommendations. Targeted health education interventions are needed to effectively manage fever symptoms in children. PMID:24391772
Sin, Jacqueline; Murrells, Trevor; Spain, Debbie; Norman, Ian; Henderson, Claire
2016-09-01
The wellbeing and caregiving experiences of family carers supporting people with psychosis has garnered increasing interest. Evidence indicates that the burden of caregiving can adversely impact on parents' wellbeing, few studies have investigated whether this is also the case for siblings, who often take on caregiving responsibilities. This exploratory study investigated the wellbeing, mental health knowledge, and appraisals of caregiving in siblings of individuals with psychosis. Using a cross-sectional design, 90 siblings completed three validated questionnaires: Warwick-Edinburgh Mental Wellbeing Scale (WEMWBS), Mental Health Knowledge Schedule (MAKS), and Experience of Caregiving Inventory (ECI). Data obtained were compared to general population norms and parent-carers' scores. Multi-variable regression analyses were conducted to examine relationships between questionnaire scores and demographic characteristics including age, sex, birth order, marital status, accommodation and educational level. Siblings, especially sisters, had significantly poorer mental wellbeing, compared to normative scores. Conversely, they had better mental health knowledge. Siblings and parent-carers had comparable high levels of negative appraisals of caregiving experiences, but siblings reported more satisfaction with personal experiences and relationships. Education level was a significant predictor for better mental health knowledge; there were no other relationships between siblings' demographic factors and outcomes. Study findings suggest that siblings have overlapping as well as distinct needs, compared to parent-carers. Further research is required to better understand siblings' experiences so as to inform development of targeted interventions that enhance wellbeing and caregiving capacity.
Drescher, Olivia; Dewailly, Eric; Diorio, Caroline; Ouellet, Nathalie; Sidi, Elhadji Anassour Laouan; Abdous, Belkacem; Valera, Beatriz; Ayotte, Pierre
2014-11-01
There is growing evidence that cardiovascular health can be affected by exposure to methylmercury (MeHg), by a mechanism involving oxidative stress. Paraoxonase 1 (PON1) is a high-density lipoprotein-bound enzyme that hydrolyzes toxic oxidized lipids and protects against cardiovascular diseases. Evidence from in vitro studies indicates that MeHg can inhibit PON1 activity but little is known regarding this effect in humans. We investigated whether increased blood mercury levels are associated with decreased serum PON1 activity in Cree people who are exposed to MeHg by fish consumption. We conducted a multi-community study of 881 Cree adults living in Eastern James Bay communities (Canada). Multivariate analyses considered sociodemographic, anthropometric, clinical, dietary and lifestyle variables and six PON1 gene variants (rs705379 (-108C/T), rs662 (Q192R), rs854560 (L55M), rs854572 (-909C/G), rs854571 (-832C/T) and rs705381 (-162C/T)). In a multiple regression model adjusted for all potential confounding factors and the rs854560 PON1 variant, a statistically significant MeHg*rs705379 interaction was observed. Blood mercury levels were inversely associated with serum PON1 activities in individual homozygous for the -108T allele (P=0.009). Our results suggest a gene-environment interaction between the rs705379 polymorphism and MeHg exposure on PON1 activity levels in this aboriginal population. This finding will need to be replicated in other population studies.
NASA Astrophysics Data System (ADS)
Jonker, C. M.; Snoep, J. L.; Treur, J.; Westerhoff, H. V.; Wijngaards, W. C. A.
Within the areas of Computational Organisation Theory and Artificial Intelligence, techniques have been developed to simulate and analyse dynamics within organisations in society. Usually these modelling techniques are applied to factories and to the internal organisation of their process flows, thus obtaining models of complex organisations at various levels of aggregation. The dynamics in living cells are often interpreted in terms of well-organised processes, a bacterium being considered a (micro)factory. This suggests that organisation modelling techniques may also benefit their analysis. Using the example of Escherichia coli it is shown how indeed agent-based organisational modelling techniques can be used to simulate and analyse E.coli's intracellular dynamics. Exploiting the abstraction levels entailed by this perspective, a concise model is obtained that is readily simulated and analysed at the various levels of aggregation, yet shows the cell's essential dynamic patterns.
Finlay, Nessa; Hahnel, Sebastian; Dowling, Adam H; Fleming, Garry J P
2013-04-01
To investigate the short- and long-term in vitro wear resistance of experimental resin-based composites (RBCs) derived from a commercial formulation. Six experimental RBCs were manufactured by manipulating the monomeric resin composition and the filler characteristics of Grandio (Voco GmbH, Cuxhaven, Germany). The Oregon Health Sciences University (OHSU) oral wear simulator was used in the presence of a food-like slurry to simulate three-body abrasion and attrition wear for 50,000, 150,000 and 300,000 cycles. A three-dimensional image of each wear facet was created and the total volumetric wear (mm(3)) and maximum wear depth (μm) were quantified for the RBC and antagonist. Statistical analyses of the total volumetric wear and maximum wear depth data (two- and one-way analyses of variance (ANOVA), with Tukey's post hoc tests where required) and regression analyses, were conducted at p=0.05. Two-way ANOVAs identified a significant effect of RBC material×wear cycles, RBC material and wear cycles (all p<0.0001). Regression analyses showed significant increases in the total volumetric wear (p≤0.001) and maximum wear depth data (p≤0.004) for all RBCs with increasing wear cycles. Differences between all RBC materials were evident after ≥150,000 wear cycles and antagonist wear provided valuable information to support the experimental findings. Wear simulating machines can provide an indication of the clinical performance but clinical performance is multi-factorial and wear is only a single facet. Employing experimental RBCs provided by a dental manufacturer rather than using self-manufactured RBCs or dental products provides increased experimental control by limiting the variables involved. Copyright © 2013 Academy of Dental Materials. Published by Elsevier Ltd. All rights reserved.
PREDICTING INDIVIDUAL WELL-BEING THROUGH THE LANGUAGE OF SOCIAL MEDIA.
Schwartz, H Andrew; Sap, Maarten; Kern, Margaret L; Eichstaedt, Johannes C; Kapelner, Adam; Agrawal, Megha; Blanco, Eduardo; Dziurzynski, Lukasz; Park, Gregory; Stillwell, David; Kosinski, Michal; Seligman, Martin E P; Ungar, Lyle H
2016-01-01
We present the task of predicting individual well-being, as measured by a life satisfaction scale, through the language people use on social media. Well-being, which encompasses much more than emotion and mood, is linked with good mental and physical health. The ability to quickly and accurately assess it can supplement multi-million dollar national surveys as well as promote whole body health. Through crowd-sourced ratings of tweets and Facebook status updates, we create message-level predictive models for multiple components of well-being. However, well-being is ultimately attributed to people, so we perform an additional evaluation at the user-level, finding that a multi-level cascaded model, using both message-level predictions and userlevel features, performs best and outperforms popular lexicon-based happiness models. Finally, we suggest that analyses of language go beyond prediction by identifying the language that characterizes well-being.
Oosterom-Calo, Rony; Te Velde, Saskia J; Stut, Wim; Drory, Yaacov; Brug, Johannes; Gerber, Yariv
2016-10-12
Leisure time physical activity (LTPA) is inversely related to mortality risk among patients with a history of myocardial infarction (MI). The aims were to explore if heart failure (HF) status and psychosocial variables moderate the association. Participants (n = 1169) were from a multi-center prospective cohort study. Information on LTPA (none, irregular,1-150, 151-300 and >300 weekly minutes), depression, social support and other prognostic indicators were collected 10-13 years after index MI. Cox regressions were conducted, adjusting for potential confounders. In case of significant moderation by HF-status or psychosocial variables, stratified analyses were performed. During follow-up (M = 8.4 years), 25.6 % of the sample had died. LTPA was inversely associated with mortality (p for trend < 0.01 in all models). HF did not, but psychosocial variables did, moderate the association. In the LTPA category 1-150 weekly minutes, patients with a high level of depression had a lower mortality risk in comparison to those with a low level (hazard ratios (95 % confidence intervals) were 0.43 (0.25, 0.75) versus 0.69 (0.36, 1.32)), and patients with a low level of social support had a lower mortality risk in comparison to those with a high level (0.40 (0.21, 0.77) versus 0.71 (0.39, 1.27)). In the category >300 min, patients with a high level of social support had a lower mortality risk than those with a low level (0.38 (0.19, 0.79) versus 0.51 (0.30, 0.87)). LTPA was inversely related to mortality risk of post-MI patients. HF did not moderate the relationship; depression and social support partially did.
Allometry of sexual size dimorphism in turtles: a comparison of mass and length data.
Regis, Koy W; Meik, Jesse M
2017-01-01
The macroevolutionary pattern of Rensch's Rule (positive allometry of sexual size dimorphism) has had mixed support in turtles. Using the largest carapace length dataset and only large-scale body mass dataset assembled for this group, we determine (a) whether turtles conform to Rensch's Rule at the order, suborder, and family levels, and (b) whether inferences regarding allometry of sexual size dimorphism differ based on choice of body size metric used for analyses. We compiled databases of mean body mass and carapace length for males and females for as many populations and species of turtles as possible. We then determined scaling relationships between males and females for average body mass and straight carapace length using traditional and phylogenetic comparative methods. We also used regression analyses to evalutate sex-specific differences in the variance explained by carapace length on body mass. Using traditional (non-phylogenetic) analyses, body mass supports Rensch's Rule, whereas straight carapace length supports isometry. Using phylogenetic independent contrasts, both body mass and straight carapace length support Rensch's Rule with strong congruence between metrics. At the family level, support for Rensch's Rule is more frequent when mass is used and in phylogenetic comparative analyses. Turtles do not differ in slopes of sex-specific mass-to-length regressions and more variance in body size within each sex is explained by mass than by carapace length. Turtles display Rensch's Rule overall and within families of Cryptodires, but not within Pleurodire families. Mass and length are strongly congruent with respect to Rensch's Rule across turtles, and discrepancies are observed mostly at the family level (the level where Rensch's Rule is most often evaluated). At macroevolutionary scales, the purported advantages of length measurements over weight are not supported in turtles.
Zheng, Jie; Erzurumluoglu, A Mesut; Elsworth, Benjamin L; Kemp, John P; Howe, Laurence; Haycock, Philip C; Hemani, Gibran; Tansey, Katherine; Laurin, Charles; Pourcain, Beate St; Warrington, Nicole M; Finucane, Hilary K; Price, Alkes L; Bulik-Sullivan, Brendan K; Anttila, Verneri; Paternoster, Lavinia; Gaunt, Tom R; Evans, David M; Neale, Benjamin M
2017-01-15
LD score regression is a reliable and efficient method of using genome-wide association study (GWAS) summary-level results data to estimate the SNP heritability of complex traits and diseases, partition this heritability into functional categories, and estimate the genetic correlation between different phenotypes. Because the method relies on summary level results data, LD score regression is computationally tractable even for very large sample sizes. However, publicly available GWAS summary-level data are typically stored in different databases and have different formats, making it difficult to apply LD score regression to estimate genetic correlations across many different traits simultaneously. In this manuscript, we describe LD Hub - a centralized database of summary-level GWAS results for 173 diseases/traits from different publicly available resources/consortia and a web interface that automates the LD score regression analysis pipeline. To demonstrate functionality and validate our software, we replicated previously reported LD score regression analyses of 49 traits/diseases using LD Hub; and estimated SNP heritability and the genetic correlation across the different phenotypes. We also present new results obtained by uploading a recent atopic dermatitis GWAS meta-analysis to examine the genetic correlation between the condition and other potentially related traits. In response to the growing availability of publicly accessible GWAS summary-level results data, our database and the accompanying web interface will ensure maximal uptake of the LD score regression methodology, provide a useful database for the public dissemination of GWAS results, and provide a method for easily screening hundreds of traits for overlapping genetic aetiologies. The web interface and instructions for using LD Hub are available at http://ldsc.broadinstitute.org/ CONTACT: jie.zheng@bristol.ac.ukSupplementary information: Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
Zenebe, Chernet Baye; Adefris, Mulat; Yenit, Melaku Kindie; Gelaw, Yalemzewod Assefa
2017-09-06
Despite the fact that long acting family planning methods reduce population growth and improve maternal health, their utilization remains poor. Therefore, this study assessed the prevalence of long acting and permanent family planning method utilization and associated factors among women in reproductive age groups who have decided not to have more children in Gondar city, northwest Ethiopia. An institution based cross-sectional study was conducted from August to October, 2015. Three hundred seventeen women who have decided not to have more children were selected consecutively into the study. A structured and pretested questionnaire was used to collect data. Both bivariate and multi-variable logistic regressions analyses were used to identify factors associated with utilization of long acting and permanent family planning methods. The multi-variable logistic regression analysis was used to investigate factors associated with the utilization of long acting and permanent family planning methods. The Adjusted Odds Ratio (AOR) with the corresponding 95% Confidence Interval (CI) was used to show the strength of associations, and variables with a P-value of <0.05 were considered statistically significant. In this study, the overall prevalence of long acting and permanent contraceptive (LAPCM) method utilization was 34.7% (95% CI: 29.5-39.9). According to the multi-variable logistic regression analysis, utilization of long acting and permanent contraceptive methods was significantly associated with women who had secondary school, (AOR: 2279, 95% CI: 1.17, 4.44), college, and above education (AOR: 2.91, 95% CI: 1.36, 6.24), history of previous utilization (AOR: 3.02, 95% CI: 1.69, 5.38), and information about LAPCM (AOR: 8.85, 95% CI: 2.04, 38.41). In this study the prevalence of long acting and permanent family planning method utilization among women who have decided not to have more children was high compared with previous studies conducted elsewhere. Advanced educational status, previous utilization of LAPCM, and information on LAPCM were significantly associated with the utilization of LAPCM. As a result, strengthening behavioral change communication channels to make information accessible is highly recommended.
Peng, Tingting; Yue, Fujuan; Wang, Fang; Feng, Yongliang; Wu, Weiwei; Wang, Suping; Zhang, Yawei; Yang, Hailan
2015-06-01
To investigate the relationship between maternal pre-pregnancy body mass index, weight gain during pregnancy and small for gestational age (SGA) birth so as to provide evidence for the development of comprehensive prevention programs on SGA birth. Between March, 2012 and July, 2014, 4 754 pregnant women were asked to fill in the questionnaires which were collected from the First Affiliated Hospital of Shanxi Medical University. Data related to general demographic characteristics, pregnancy and health status of those pregnant women was collected and maternal pre-pregnancy body mass index and maternal weight gain were calculated. Subjects were divided into different groups before the effect of maternal pre-pregnancy body mass index and weight gain during pregnancy on SGA birth were estimated. The overall incidence of SGA birth was 9.26% (440/4 754). Proportions of SGA birth from pre-pregnant, underweight group, normal weight group, overweight and obese groups were 9.85%, 8.54% and 9.45%, respectively. Results from multi-factor logistic regression analyses showed that after adjusting the confounding factors as age, history on pregnancies etc., women with high pre-pregnancy BMI showed a lower incidence of SGA than those under normal pre-pregnancy BMI (OR = 0.714, 95% CI: 0.535-0.953). Different weight gains during pregnancy were statistically significant (χ(2) = 8.811, P = 0.012). Incidence of SGA birth that was below the recommended range in the 2009 Institute of Medicine Guidelines (12.20%) was higher than those within (9.23%) or beyond (8.45%) the recommended range. Results from the multi-factor logistic regression analyses showed that, after adjusting the confounding factors as age, pregnancy history etc., factor as weight gain below the recommended level could increase the risk of SGA (OR = 1.999, 95% CI: 1.487-2.685). In the underweight, normal weight, overweight or obese groups, with weight gain during pregnancy below the range, the incidence of SGA showed an increase (OR = 2.558, 95% CI: 1.313-4.981, OR = 1.804, 95% CI: 1.258-2.587, OR = 3.108, 95% CI: 1.237-7.811). There was no interaction of addictive or multiplicative models between these two factors under 'interaction analysis'. Women with high pre-pregnancy BMI presented a lower incidence of SGA than those within the normal range. Insufficient weight gain during pregnancy could increase the risk of SGA delivery. These findings called for attention to be paid to the gestational weight gain, in order to decrease the risk of SGA.
Neighborhood Characteristics and the Social Control of Registered Sex Offenders
ERIC Educational Resources Information Center
Socia, Kelly M.; Stamatel, Janet P.
2012-01-01
This study uses geospatial and regression analyses to examine the relationships among social disorganization, collective efficacy, social control, residence restrictions, spatial autocorrelation, and the neighborhood distribution of registered sex offenders (RSOs) in Chicago. RSOs were concentrated in neighborhoods that had higher levels of social…
Wired: Energy Drinks, Jock Identity, Masculine Norms, and Risk Taking
ERIC Educational Resources Information Center
Miller, Kathleen E.
2008-01-01
Objective: The author examined gendered links among sport-related identity, endorsement of conventional masculine norms, risk taking, and energy-drink consumption. Participants: The author surveyed 795 undergraduate students enrolled in introductory-level courses at a public university. Methods: The author conducted linear regression analyses of…
NASA Astrophysics Data System (ADS)
Kita, N. T.; Ushikubo, T.; Valley, J. W.
2008-05-01
The CAMECA IMS-1280 large radius, multicollector ion microprobe at the Wisc-SIMS National Facility is capable of high accuracy and precision for in situ analysis of isotope ratios. With improved hardware stability and software capability, high precision isotope analyses are routinely performed, typically 5 min per spot. We have developed analytical protocols for stable isotope analyses of oxygen, carbon, Mg, Si and Sulfur using multi-collector Faraday Cups (MCFC) and achieved precision of 0.1-0.2 ‰ (1SD) from a typically 10μm spot analyses. A number of isotopically homogeneous mineral standards have been prepared and calibrated in order to certify the accuracy of analyses in the same level. When spatial resolution is critical, spot size is reduced down to sub- μm for δ 18O to obtain better than 0.5‰ (1SD) precision by using electron multiplier (EM) on multi-collection system. Multi-collection EM analysis is also applied at 10 ppm level to Li isotope ratios in zircon with precision better than 2‰ (1SD). A few applications will be presented. (1) Oxygen three isotope analyses of chondrules in ordinary chondrites revealed both mass dependent and mass independent oxygen isotope fractionations among chondrules as well as within individual chondrules. The results give constraints on the process of chondrule formation and origin of isotope reservoirs in the early solar system. (2) High precision 26Al-26Mg (half life of 0.73 Ma) chronology is applied to zoned melilite and anorthite from Ca, Al-rich inclusions (CAI) in Leoville meteorite, and a well-defined internal isochron is obtained. The results indicate the Al- Mg system was remained closed within 40ky of the crystallization of melilite and anorthite in this CAI. (3) Sub- μm spot analyses of δ18O in isotopically zoned zircon from high-grade metamorphism reveals a diffusion profile of ~6‰ over 2μm, indicating slow diffusion of oxygen in zircon. This result also implies that old Archean detrital zircons (> 4Ga) might preserve their primary oxygen isotopic records, which allows us to trace the geological processes of the early earth [1]. Lithium isotope analyses of pre- 4Ga zircon from Jack Hills show high Li abundance and low δ 7Li, indicating existence of highly weathered crustal material as early as 4.3Ga. In conclusion, these new techniques allow us to study small natural variations of stable isotopes at μm-scale that permit exciting and fundamental research where samples are small, precious, or zoned. [1] Page FZ et al. (2007) Am Min 92, 1772-1775.
Zhang, Nana; Yang, Xin; Zhu, Xiaolin; Zhao, Bin; Huang, Tianyi; Ji, Qiuhe
2017-04-01
Objectives To determine whether the associations with key risk factors in patients with diagnosed and undiagnosed type 2 diabetes mellitus (T2DM) are different using data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2010. Methods The study analysed the prevalence and association with risk factors of undiagnosed and diagnosed T2DM using a regression model and a multinomial logistic regression model. Data from the NHANES 1999-2010 were used for the analyses. Results The study analysed data from 10 570 individuals. The overall prevalence of diagnosed and undiagnosed T2DM increased significantly from 1999 to 2010. The prevalence of undiagnosed T2DM was significantly higher in non-Hispanic whites, in individuals <30 years old and in those with near optimal (130-159 mg/dl) or very high (≥220 mg/dl) non-high-density lipoprotein cholesterol levels compared with diagnosed T2DM. Body mass index, low economic status or low educational level had no effect on T2DM diagnosis rates. Though diagnosed T2DM was associated with favourable diet/carbohydrate intake behavioural changes, it had no effect on physical activity levels. Conclusion The overall T2DM prevalence increased between 1999 and 2010, particularly for undiagnosed T2DM in patients that were formerly classified as low risk.
Zhang, Nana; Yang, Xin; Zhu, Xiaolin; Zhao, Bin; Huang, Tianyi
2017-01-01
Objectives To determine whether the associations with key risk factors in patients with diagnosed and undiagnosed type 2 diabetes mellitus (T2DM) are different using data from the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2010. Methods The study analysed the prevalence and association with risk factors of undiagnosed and diagnosed T2DM using a regression model and a multinomial logistic regression model. Data from the NHANES 1999–2010 were used for the analyses. Results The study analysed data from 10 570 individuals. The overall prevalence of diagnosed and undiagnosed T2DM increased significantly from 1999 to 2010. The prevalence of undiagnosed T2DM was significantly higher in non-Hispanic whites, in individuals <30 years old and in those with near optimal (130–159 mg/dl) or very high (≥220 mg/dl) non-high-density lipoprotein cholesterol levels compared with diagnosed T2DM. Body mass index, low economic status or low educational level had no effect on T2DM diagnosis rates. Though diagnosed T2DM was associated with favourable diet/carbohydrate intake behavioural changes, it had no effect on physical activity levels. Conclusion The overall T2DM prevalence increased between 1999 and 2010, particularly for undiagnosed T2DM in patients that were formerly classified as low risk. PMID:28415936
Faggion, Clovis Mariano; Wu, Yun-Chun; Scheidgen, Moritz; Tu, Yu-Kang
2015-01-01
Risk of bias (ROB) may threaten the internal validity of a clinical trial by distorting the magnitude of treatment effect estimates, although some conflicting information on this assumption exists. The objective of this study was evaluate the effect of ROB on the magnitude of treatment effect estimates in randomized controlled trials (RCTs) in periodontology and implant dentistry. A search for Cochrane systematic reviews (SRs), including meta-analyses of RCTs published in periodontology and implant dentistry fields, was performed in the Cochrane Library in September 2014. Random-effect meta-analyses were performed by grouping RCTs with different levels of ROBs in three domains (sequence generation, allocation concealment, and blinding of outcome assessment). To increase power and precision, only SRs with meta-analyses including at least 10 RCTs were included. Meta-regression was performed to investigate the association between ROB characteristics and the magnitudes of intervention effects in the meta-analyses. Of the 24 initially screened SRs, 21 SRs were excluded because they did not include at least 10 RCTs in the meta-analyses. Three SRs (two from periodontology field) generated information for conducting 27 meta-analyses. Meta-regression did not reveal significant differences in the relationship of the ROB level with the size of treatment effect estimates, although a trend for inflated estimates was observed in domains with unclear ROBs. In this sample of RCTs, high and (mainly) unclear risks of selection and detection biases did not seem to influence the size of treatment effect estimates, although several confounders might have influenced the strength of the association.
NASA Astrophysics Data System (ADS)
Abdikan, S.; Sekertekin, A.; Ustunern, M.; Balik Sanli, F.; Nasirzadehdizaji, R.
2018-04-01
Temporal monitoring of crop types is essential for the sustainable management of agricultural activities on both national and global levels. As a practical and efficient tool, remote sensing is widely used in such applications. In this study, Sentinel-1 Synthetic Aperture Radar (SAR) imagery was utilized to investigate the performance of the sensor backscatter image on crop monitoring. Multi-temporal C-band VV and VH polarized SAR images were acquired simultaneously by in-situ measurements which was conducted at Konya basin, central Anatolia Turkey. During the measurements, plant height of maize plant was collected and relationship between backscatter values and plant height was analysed. The maize growth development was described under Biologische Bundesanstalt, bundessortenamt und CHemische industrie (BBCH). Under BBCH stages, the test site was classified as leaf development, stem elongation, heading and flowering in general. The correlation coefficient values indicated high correlation for both polarimetry during the early stages of the plant, while late stages indicated lower values in both polarimetry. As a last step, multi-temporal coverage of crop fields was analysed to map seasonal land use. To this aim, object based image classification was applied following image segmentation. About 80 % accuracies of land use maps were created in this experiment. As preliminary results, it is concluded that Sentinel-1 data provides beneficial information about plant growth. Dual-polarized Sentinel-1 data has high potential for multi-temporal analyses for agriculture monitoring and reliable mapping.
Schümberg, Katharina; Polyakova, Maryna; Steiner, Johann; Schroeter, Matthias L.
2016-01-01
S100B has been linked to glial pathology in several psychiatric disorders. Previous studies found higher S100B serum levels in patients with schizophrenia compared to healthy controls, and a number of covariates influencing the size of this effect have been proposed in the literature. Here, we conducted a meta-analysis and meta-regression analysis on alterations of serum S100B in schizophrenia in comparison with healthy control subjects. The meta-analysis followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement to guarantee a high quality and reproducibility. With strict inclusion criteria 19 original studies could be included in the quantitative meta-analysis, comprising a total of 766 patients and 607 healthy control subjects. The meta-analysis confirmed higher values of the glial serum marker S100B in schizophrenia if compared with control subjects. Meta-regression analyses revealed significant effects of illness duration and clinical symptomatology, in particular the total score of the Positive and Negative Syndrome Scale (PANSS), on serum S100B levels in schizophrenia. In sum, results confirm glial pathology in schizophrenia that is modulated by illness duration and related to clinical symptomatology. Further studies are needed to investigate mechanisms and mediating factors related to these findings. PMID:26941608
Visscher, Corine M; van Wesemael-Suijkerbuijk, Erin A; Lobbezoo, Frank
2016-10-01
The aim of this study was to explore the association between the presence of comorbidities and the pain experience in individual patients with temporomandibular disorder (TMD). This clinical trial comprised 112 patients with TMD pain. For all participants the presence of the following comorbid factors was assessed: pain in the neck; somatization; impaired sleep; and depression. Pain experience was evaluated using the McGill Pain Questionnaire (MPQ). For each subject the TMD-pain experience was assessed for three dimensions - sensory, affective, and evaluative - as specified in the MPQ. The association between comorbid factors and these three dimensions of TMD-pain experience was then evaluated using linear regression models. Univariable regression analyses showed that all comorbid factors, except for one factor, were positively associated with the level of pain, as rated by the sensory description of pain, the affective component of pain, and the evaluative experience of pain. The multivariable regression analyses showed that for all MPQ dimensions, depression showed the strongest associations with pain experience. It was found that in the presence of comorbid disorders, patients with TMD experience elevated levels of TMD pain. This information should be taken into consideration in the diagnostic process, as well as in the choice of treatment. © 2016 Eur J Oral Sci.
Estimation of potential bridge scour at bridges on state routes in South Dakota, 2003-07
Thompson, Ryan F.; Fosness, Ryan L.
2008-01-01
Flowing water can erode (scour) soils and cause structural failure of a bridge by exposing or undermining bridge foundations (abutments and piers). A rapid scour-estimation technique, known as the level-1.5 method and developed by the U.S. Geological Survey, was used to evaluate potential scour at bridges in South Dakota in a study conducted in cooperation with the South Dakota Department of Transportation. This method was used during 2003-07 to estimate scour for the 100-year and 500-year floods at 734 selected bridges managed by the South Dakota Department of Transportation on State routes in South Dakota. Scour depths and other parameters estimated from the level-1.5 analyses are presented in tabular form. Estimates of potential contraction scour at the 734 bridges ranged from 0 to 33.9 feet for the 100-year flood and from 0 to 35.8 feet for the 500-year flood. Abutment scour ranged from 0 to 36.9 feet for the 100-year flood and from 0 to 45.9 feet for the 500-year flood. Pier scour ranged from 0 to 30.8 feet for the 100-year flood and from 0 to 30.7 feet for the 500-year flood. The scour depths estimated by using the level-1.5 method can be used by the South Dakota Department of Transportation and others to identify bridges that may be susceptible to scour. Scour at 19 selected bridges also was estimated by using the level-2 method. Estimates of contraction, abutment, and pier scour calculated by using the level-1.5 and level-2 methods are presented in tabular and graphical formats. Compared to level-2 scour estimates, the level-1.5 method generally overestimated scour as designed, or in a few cases slightly underestimated scour. Results of the level-2 analyses were used to develop regression equations for change in head and average velocity through the bridge opening. These regression equations derived from South Dakota data are compared to similar regression equations derived from Montana and Colorado data. Future level-1.5 scour investigations in South Dakota may benefit from the use of these South Dakota-specific regression equations for estimating change in stream head and average velocity at the bridge.
Analysis of Low Bidding and Change Order Rates for Navy Facilities Construction Contracts.
1984-06-01
examine his motives and strategies prior to bidding. Several measures of " level cf competitiveness" are introduced from bidding theory literature that...bidders of fixed-price Government construction contracts have on contract prices when the level FORM, 1473 EDITION OF INOV 6 o IS OBSOLETE S N 0 102...conventional measures of the . level of competition intensity are applied in regression and variance analyses. en, z e ., . , 144 , UNCLASSIFIED 2 SgCURITlY
Goldman, S A
1996-10-01
Neurotoxicity in relation to concomitant administration of lithium and neuroleptic drugs, particularly haloperidol, has been an ongoing issue. This study examined whether use of lithium with neuroleptic drugs enhances neurotoxicity leading to permanent sequelae. The Spontaneous Reporting System database of the United States Food and Drug Administration and extant literature were reviewed for spectrum cases of lithium/neuroleptic neurotoxicity. Groups taking lithium alone (Li), lithium/haloperidol (LiHal) and lithium/ nonhaloperidol neuroleptics (LiNeuro), each paired for recovery and sequelae, were established for 237 cases. Statistical analyses included pairwise comparisons of lithium levels using the Wilcoxon Rank Sum procedure and logistic regression to analyze the relationship between independent variables and development of sequelae. The Li and Li-Neuro groups showed significant statistical differences in median lithium levels between recovery and sequelae pairs, whereas the LiHal pair did not differ significantly. Lithium level was associated with sequelae development overall and within the Li and LiNeuro groups; no such association was evident in the LiHal group. On multivariable logistic regression analysis, lithium level and taking lithium/haloperidol were significant factors in the development of sequelae, with multiple possibly confounding factors (e.g., age, sex) not statistically significant. Multivariable logistic regression analyses with neuroleptic dose as five discrete dose ranges or actual dose did not show an association between development of sequelae and dose. Database limitations notwithstanding, the lack of apparent impact of serum lithium level on the development of sequelae in patients treated with haloperidol contrasts notably with results in the Li and LiNeuro groups. These findings may suggest a possible effect of pharmacodynamic factors in lithium/neuroleptic combination therapy.
NASA Technical Reports Server (NTRS)
Tomberlin, T. J.
1985-01-01
Research studies of residents' responses to noise consist of interviews with samples of individuals who are drawn from a number of different compact study areas. The statistical techniques developed provide a basis for those sample design decisions. These techniques are suitable for a wide range of sample survey applications. A sample may consist of a random sample of residents selected from a sample of compact study areas, or in a more complex design, of a sample of residents selected from a sample of larger areas (e.g., cities). The techniques may be applied to estimates of the effects on annoyance of noise level, numbers of noise events, the time-of-day of the events, ambient noise levels, or other factors. Methods are provided for determining, in advance, how accurately these effects can be estimated for different sample sizes and study designs. Using a simple cost function, they also provide for optimum allocation of the sample across the stages of the design for estimating these effects. These techniques are developed via a regression model in which the regression coefficients are assumed to be random, with components of variance associated with the various stages of a multi-stage sample design.
Chou, Wen-Jiun; Liu, Tai-Ling; Yang, Pinchen; Yen, Cheng-Fang; Hu, Huei-Fan
2015-01-30
This study examined the associations of the severity of Internet addiction symptoms with reinforcement sensitivity, family factors, Internet activities, and attention-deficit/hyperactivity disorder (ADHD) symptoms among adolescents in Taiwan diagnosed with ADHD. A total of 287 adolescents diagnosed with ADHD and aged between 11 and 18 years participated in this study. Their levels of Internet addiction symptoms, ADHD symptoms, reinforcement sensitivity, family factors, and various Internet activities in which the participants engaged were assessed. The correlates of the severities of Internet addiction symptoms were determined using multiple regression analyses. The results indicated that low satisfaction with family relationships was the strongest factor predicting severe Internet addiction symptoms, followed by using instant messaging, watching movies, high Behavioral Approach System (BAS) fun seeking, and high Behavioral Inhibition System scores. Meanwhile, low paternal occupational SES, low BAS drive, and online gaming were also significantly associated with severe Internet addiction symptoms. Multiple factors are significantly associated with the severity of Internet addiction symptoms among adolescents with ADHD. Clinicians, educational professionals, and parents of adolescents with ADHD should monitor the Internet use of adolescents who exhibit the factors identified in this study. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
Childhood physical abuse predicts stressor-evoked activity within central visceral control regions
Sheu, Lei K.; Midei, Aimee J.; Gianaros, Peter J.
2015-01-01
Early life experience differentially shapes later stress reactivity, as evidenced by both animal and human studies. However, early experience-related changes in the function of central visceral neural circuits that control stress responses have not been well characterized, particularly in humans. The paraventricular nucleus of the hypothalamus (PVN), bed nucleus of the stria terminalis (BNST), amygdala (Amyg) and subgenual anterior cingulate cortex (sgACC) form a core visceral stress-responsive circuit. The goal of this study is to examine how childhood emotional and physical abuse relates to adulthood stressor-evoked activity within these visceral brain regions. To evoke acute states of mental stress, participants (n = 155) performed functional magnetic resonance imaging (fMRI)-adapted versions of the multi-source interference task (MSIT) and the Stroop task with simultaneous monitoring of mean arterial pressure (MAP) and heart rate. Regression analyses revealed that childhood physical abuse correlated positively with stressor-evoked changes in MAP, and negatively with unbiased, a priori extractions of fMRI blood-oxygen level-dependent signal change values within the sgACC, BNST, PVN and Amyg (n = 138). Abuse-related changes in the function of visceral neural circuits may reflect neurobiological vulnerability to adverse health outcomes conferred by early adversity. PMID:24847113
Liu, Chaoqun; Zhong, Chunrong; Zhou, Xuezhen; Chen, Renjuan; Wu, Jiangyue; Wang, Weiye; Li, Xiating; Ding, Huisi; Guo, Yanfang; Gao, Qin; Hu, Xingwen; Xiong, Guoping; Yang, Xuefeng; Hao, Liping; Xiao, Mei; Yang, Nianhong
2017-01-01
Bilirubin concentrations have been recently reported to be negatively associated with type 2 diabetes mellitus. We examined the association between bilirubin concentrations and gestational diabetes mellitus. In a prospective cohort study, 2969 pregnant women were recruited prior to 16 weeks of gestation and were followed up until delivery. The value of bilirubin was tested and oral glucose tolerance test was conducted to screen gestational diabetes mellitus. The relationship between serum bilirubin concentration and gestational weeks was studied by two-piecewise linear regression. A subsample of 1135 participants with serum bilirubin test during 16-18 weeks gestation was conducted to research the association between serum bilirubin levels and risk of gestational diabetes mellitus by logistic regression. Gestational diabetes mellitus developed in 8.5 % of the participants (223 of 2969). Two-piecewise linear regression analyses demonstrated that the levels of bilirubin decreased with gestational week up to the turning point 23 and after that point, levels of bilirubin were increased slightly. In multiple logistic regression analysis, the relative risk of developing gestational diabetes mellitus was lower in the highest tertile of direct bilirubin than that in the lowest tertile (RR 0.60; 95 % CI, 0.35-0.89). The results suggested that women with higher serum direct bilirubin levels during the second trimester of pregnancy have lower risk for development of gestational diabetes mellitus.
Elevated blood pressure, race/ethnicity, and C-reactive protein levels in children and adolescents.
Lande, Marc B; Pearson, Thomas A; Vermilion, Roger P; Auinger, Peggy; Fernandez, Isabel D
2008-12-01
Adult hypertension is independently associated with elevated C-reactive protein levels, after controlling for obesity and other cardiovascular risk factors. The objective of this study was to determine, with a nationally representative sample of children, whether the relationship between elevated blood pressure and C-reactive protein levels may be evident before adulthood. Cross-sectional data for children 8 to 17 years of age who participated in the National Health and Nutrition Examination Survey between 1999 and 2004 were analyzed. Bivariate analyses compared children with C-reactive protein levels of >3 mg/L versus
NASA Astrophysics Data System (ADS)
Haris, A.; Nastria, N.; Soebandrio, D.; Riyanto, A.
2017-07-01
Geochemical and geophysical analyses of shale gas have been carried out in Brown Shale, Middle Pematang Formation, Central Sumatra Basin. The paper is aimed at delineating the sweet spot distribution of potential shale gas reservoir, which is based on Total Organic Carbon (TOC), Maturity level data, and combined with TOC modeling that refers to Passey and Regression Multi Linear method. We used 4 well data, side wall core and 3D pre-stack seismic data. Our analysis of geochemical properties is based on well log and core data and its distribution are constrained by a framework of 3D seismic data, which is transformed into acoustic impedance. Further, the sweet spot of organic-rich shale is delineated by mapping TOC, which is extracted from inverted acoustic impedance. Our experiment analysis shows that organic materials contained in the formation of Middle Pematang Brown Shale members have TOC range from 0.15 to 2.71 wt.%, which is classified in the quality of poor to very good. In addition, the maturity level of organic material is ranging from 373°C to 432°C, which is indicated by vitrinite reflectance (Ro) of 0.58. In term of kerogen type, this Brown shale formation is categorized as kerogen type of II I III, which has the potential to generate a mixture of gasIoil on the environment.
Broderick, Joan E.; Junghaenel, Doerte U.; Schneider, Stefan; Bruckenthal, Patricia; Keefe, Francis J.
2010-01-01
Objectives This study examined predictors of treatment expectation among osteoarthritis (OA) patients in a multi-site clinical trial of pain coping strategies training (CST). Methods Patients (N=171) completed a pre-treatment assessment battery that asked questions about treatment expectations, pain coping variables, pain, physical function, psychological distress, quality of life, and depression as well as background demographic and medical variables. Results Regression analyses indicated that several variables accounted for 21% of the variance in treatment expectations (p < .0001). Patients who were classified as adaptive copers, reported higher self efficacy and social interaction, had higher quality of life, and who had lower levels of affective distress and depression had more positive expectations about engaging in pain coping skills training. Variables that were not associated with treatment expectation were level of pain and physical dysfunction, duration of disease, and disability status as well as demographic variables. Discussion Thus, while many OA patients will approach pain coping skills training with positive expectations, others have lower expectations. This study suggests that a multidimensional assessment of OA patients with chronic pain can identify those who have higher expectations versus lower expectations. The results suggest that patients who are psychologically distressed are less optimistic about engaging in treatment and that these patients, in particular, may benefit from and need pre-treatment motivational interviewing to enhance their uptake of pain coping skills PMID:21178591
Menon, Chloe; Westervelt, Holly James; Jahn, Danielle R.; Dressel, Jeffrey A.; O’Bryant, Sid E.
2013-01-01
The Brief Smell Identification Test (BSIT) is a commonly used measure of olfactory functioning in elderly populations. Few studies have provided normative data for this measure, and minimal data are available regarding the impact of sociodemographic factors on test scores. This study presents normative data for the BSIT in a sample of English- and Spanish-speaking Hispanic and non-Hispanic Whites. A Rasch analysis was also conducted to identify the items that best discriminated between varying levels of olfactory functioning, as measured by the BSIT. The total sample included 302 older adults seen as part of an ongoing study of rural cognitive aging, Project FRONTIER. Hierarchical regression analyses revealed that BSIT scores require adjustment by age and gender, but years of education, ethnicity, and language did not significantly influence BSIT performance. Four items best discriminated between varying levels of smell identification, accounting for 59.44% of total information provided by the measure. However, items did not represent a continuum of difficulty on the BSIT. The results of this study indicate that the BSIT appears to be well-suited for assessing odor identification deficits in older adults of diverse backgrounds, but that fine-tuning of this instrument may be recommended in light of its items’ difficulty and discrimination parameters. Clinical and empirical implications are discussed. PMID:23634698
Van de Velde, Sarah; Bambra, Clare; Van der Bracht, Koen; Eikemo, Terje Andreas; Bracke, Piet
2014-11-01
This study examines whether health inequalities exist between lone and cohabiting mothers across Europe, and how these may differ by welfare regime. Data from the European Social Survey were used to compare self-rated general health, limiting long-standing illness and depressive feelings by means of a multi-level logistic regression. The 27 countries included in the analyses are classified into six welfare regimes (Anglo-Saxon, Bismarckian, Southern, Nordic, Central East Europe (CEE) (new EU) and CEE (non-EU). Lone motherhood is defined as mothers not cohabiting with a partner, regardless of their legal marital status. The results indicate that lone mothers are more at risk of poor health than cohabiting mothers. This is most pronounced in the Anglo-Saxon regime for self-rated general health and limiting long-standing illness, while for depressive feelings it is most pronounced in the Bismarckian welfare regime. While the risk difference is smallest in the CEE regimes, both lone and cohabiting mothers also reported the highest levels of poor health compared with the other regimes. The results also show that a vulnerable socioeconomic position is associated with ill-health in lone mothers and that welfare regimes differ in the degree to which they moderate this association. © 2014 The Authors. Sociology of Health & Illness © 2014 Foundation for the Sociology of Health & Illness/John Wiley & Sons Ltd.
Bianchi, F; Careri, M; Maffini, M; Mangia, A; Mucchino, C
2003-01-01
A sensitive method for the simultaneous determination of (7)Li, (27)Al and (56)Fe by cold plasma ICP-MS was developed and validated. Experimental design was used to investigate the effects of torch position, torch power, lens 2 voltage, and coolant flow. Regression models and desirability functions were applied to find the experimental conditions providing the highest global sensitivity in a multi-elemental analysis. Validation was performed in terms of limits of detection (LOD), limits of quantitation (LOQ), linearity and precision. LODs were 1.4 and 159 ng L(-1) for (7)Li and (56)Fe, respectively; the highest LOD found being that for (27)Al (425 ng L(-1)). Linear ranges of 5 orders of magnitude for Li and 3 orders for Fe were statistically verified for each compound. Precision was evaluated by testing two concentration levels, and good results in terms of both intra-day repeatability and intermediate precision were obtained. RSD values lower than 4.8% at the lowest concentration level were calculated for intra-day repeatability. Commercially available soft drinks and alcoholic beverages contained in different packaging materials (TetraPack, polyethylene terephthalate (PET), commercial cans and glass) were analysed, and all the analytes were detected and quantitated. Copyright 2002 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan
2017-05-01
In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability.
Selmer, Randi; Haglund, Bengt; Furu, Kari; Andersen, Morten; Nørgaard, Mette; Zoëga, Helga; Kieler, Helle
2016-10-01
Compare analyses of a pooled data set on the individual level with aggregate meta-analysis in a multi-database study. We reanalysed data on 2.3 million births in a Nordic register based cohort study. We compared estimated odds ratios (OR) for the effect of selective serotonin reuptake inhibitors (SSRI) and venlafaxine use in pregnancy on any cardiovascular birth defect and the rare outcome right ventricular outflow tract obstructions (RVOTO). Common covariates included maternal age, calendar year, birth order, maternal diabetes, and co-medication. Additional covariates were added in analyses with country-optimized adjustment. Country adjusted OR (95%CI) for any cardiovascular birth defect in the individual-based pooled analysis was 1.27 (1.17-1.39), 1.17 (1.07-1.27) adjusted for common covariates and 1.15 (1.05-1.26) adjusted for all covariates. In fixed effects meta-analyses pooled OR was 1.29 (1.19-1.41) based on crude country specific ORs, 1.19 (1.09-1.29) adjusted for common covariates, and 1.16 (1.06-1.27) for country-optimized adjustment. In a random effects model the adjusted OR was 1.07 (0.87-1.32). For RVOTO, OR was 1.48 (1.15-1.89) adjusted for all covariates in the pooled data set, and 1.53 (1.19-1.96) after country-optimized adjustment. Country-specific adjusted analyses at the substance level were not possible for RVOTO. Results of fixed effects meta-analysis and individual-based analyses of a pooled dataset were similar in this study on the association of SSRI/venlafaxine and cardiovascular birth defects. Country-optimized adjustment attenuated the estimates more than adjustment for common covariates only. When data are sparse pooled data on the individual level are needed for adjusted analyses. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.
Statistical power analyses using G*Power 3.1: tests for correlation and regression analyses.
Faul, Franz; Erdfelder, Edgar; Buchner, Axel; Lang, Albert-Georg
2009-11-01
G*Power is a free power analysis program for a variety of statistical tests. We present extensions and improvements of the version introduced by Faul, Erdfelder, Lang, and Buchner (2007) in the domain of correlation and regression analyses. In the new version, we have added procedures to analyze the power of tests based on (1) single-sample tetrachoric correlations, (2) comparisons of dependent correlations, (3) bivariate linear regression, (4) multiple linear regression based on the random predictor model, (5) logistic regression, and (6) Poisson regression. We describe these new features and provide a brief introduction to their scope and handling.
Correlation Between Hierarchical Bayesian and Aerosol ...
Tools to estimate PM2.5 mass have expanded in recent years, and now include: 1) stationary monitor readings, 2) Community Multi-Scale Air Quality (CMAQ) model estimates, 3) Hierarchical Bayesian (HB) estimates from combined stationary monitor readings and CMAQ model output; and, 4) calibrated Aerosol Optical Depth (AOD) readings from two Moderate Resolution Imaging Spetroradiometer (MODIS) units on National Aeronautics and Space Administration’s (NASA) Terra and Aqua satellites. Case-crossover design and conditional logistic regression were used to determine concentration response (CR) functions for three different PM2.5 levels on asthma emergency department (ED) visits and acute myocardial infarction (MI) inpatient hospitalizations in ninety-nine, 12 km2 grids in Baltimore, MD (2005 data). HB analyses for asthma ED visits produced significant results at 3-day lags for the main effect (OR=1.002, 95% CI=1.000-1.005), and two effect modifiers for females (OR=1.003, 95% CI=1.000-1.006), and non-Caucasian/non-African American persons (OR=1.010, 95% CI=1.001-1.019). HB analyses for acute MI inpatient hospitalizations also consistently produced a significant outcome for persons of other race (OR=1.031, 95% CI=1.006-1.056). Correlation coefficients computed between stationary monitor and satellite AOD PM2.5 values were significant for both asthma (rxy=0.944) and acute MI (rxy=0.940). Both monitor and AOD PM2.5 values were higher in February and June through Aug
Yang, Tingzhong; Yang, Xiaozhao Y; Cottrell, Randall R; Wu, Dan; Jiang, Shuhan; Anderson, James G
2016-06-01
Ecological models depict violent injuries against women being influenced by both individual and environmental characteristics. However, only few studies examined the association between regional variables and the likelihood of violent injuries. Our study is a preliminary assessment of the impact of regional variables on the likelihood that a woman has experienced violent injuries. Participants were 16 866 urban residents, who were identified through a multi-stage sampling process conducted in 21 Chinese cities. Out of the sampled population, 8071 respondents were female. Subsequent analyses focused solely on the female sample. Multilevel logistic regression analyses were performed to examine regional variation in violent injuries. Prevalence of violent injuries against women is 10.7% (95% CI: 7.8%, 15.5%). After controlling for individual-level characteristics, higher regional male-female ratio (OR: 1.97, P < 0.05), population growth rate (OR: 4.12, P < 0.01) and unemployment rate (OR: 2.45, P < 0.01) were all associated with an elevated risk of violent injuries among Chinese women caused by physical attack. The results suggest violent injuries among Chinese women caused by physical attack have become an important social and public health problem. The findings point to the importance of developing effective health policies, laws and interventions that focuses on the unequal economic development between different regions. © The Author 2015. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.
Vereecken, Carine; Haerens, Leen; De Bourdeaudhuij, Ilse; Maes, Lea
2010-10-01
To identify the correlates of the home food environment (parents' intake, availability and food-related parenting practices) at the age of 10 years with dietary patterns during childhood and in adolescence. Primary-school children of fifty-nine Flemish elementary schools completed a questionnaire at school in 2002. Four years later they completed a questionnaire by e-mail or mail at home. Their parents completed a questionnaire on food-related parenting practices at baseline. Longitudinal study. The analyses included 609 matched questionnaires. Multi-level regression analyses were used to identify baseline parenting practices (pressure, reward, negotiation, catering on demand, permissiveness, verbal praise, avoiding negative modelling, availability of healthy/unhealthy food items and mothers' fruit and vegetable (F&V) and excess scores) associated with children's dietary patterns (F&V and excess scores). Mother's F&V score was a significant positive independent predictor for children's F&V score at baseline and follow-up, whereas availability of unhealthy foods was significantly negatively associated with both scores. Negotiation was positively associated with children's follow-up score of F&V, while permissiveness was positively associated with children's follow-up excess score. Availability of unhealthy foods and mother's excess score were positively related to children's excess score at baseline and follow-up. Parental intake and restricting the availability of unhealthy foods not only appeared to have a consistent impact on children's and adolescents' diets, but also negotiating and less permissive food-related parenting practices may improve adolescents' diets.
Lamm, Steven H; Ferdosi, Hamid; Dissen, Elisabeth K; Li, Ji; Ahn, Jaeil
2015-12-07
High levels (> 200 µg/L) of inorganic arsenic in drinking water are known to be a cause of human lung cancer, but the evidence at lower levels is uncertain. We have sought the epidemiological studies that have examined the dose-response relationship between arsenic levels in drinking water and the risk of lung cancer over a range that includes both high and low levels of arsenic. Regression analysis, based on six studies identified from an electronic search, examined the relationship between the log of the relative risk and the log of the arsenic exposure over a range of 1-1000 µg/L. The best-fitting continuous meta-regression model was sought and found to be a no-constant linear-quadratic analysis where both the risk and the exposure had been logarithmically transformed. This yielded both a statistically significant positive coefficient for the quadratic term and a statistically significant negative coefficient for the linear term. Sub-analyses by study design yielded results that were similar for both ecological studies and non-ecological studies. Statistically significant X-intercepts consistently found no increased level of risk at approximately 100-150 µg/L arsenic.
Visual abilities distinguish pitchers from hitters in professional baseball.
Klemish, David; Ramger, Benjamin; Vittetoe, Kelly; Reiter, Jerome P; Tokdar, Surya T; Appelbaum, Lawrence Gregory
2018-01-01
This study aimed to evaluate the possibility that differences in sensorimotor abilities exist between hitters and pitchers in a large cohort of baseball players of varying levels of experience. Secondary data analysis was performed on 9 sensorimotor tasks comprising the Nike Sensory Station assessment battery. Bayesian hierarchical regression modelling was applied to test for differences between pitchers and hitters in data from 566 baseball players (112 high school, 85 college, 369 professional) collected at 20 testing centres. Explanatory variables including height, handedness, eye dominance, concussion history, and player position were modelled along with age curves using basis regression splines. Regression analyses revealed better performance for hitters relative to pitchers at the professional level in the visual clarity and depth perception tasks, but these differences did not exist at the high school or college levels. No significant differences were observed in the other 7 measures of sensorimotor capabilities included in the test battery, and no systematic biases were found between the testing centres. These findings, indicating that professional-level hitters have better visual acuity and depth perception than professional-level pitchers, affirm the notion that highly experienced athletes have differing perceptual skills. Findings are discussed in relation to deliberate practice theory.
Lamm, Steven H.; Ferdosi, Hamid; Dissen, Elisabeth K.; Li, Ji; Ahn, Jaeil
2015-01-01
High levels (> 200 µg/L) of inorganic arsenic in drinking water are known to be a cause of human lung cancer, but the evidence at lower levels is uncertain. We have sought the epidemiological studies that have examined the dose-response relationship between arsenic levels in drinking water and the risk of lung cancer over a range that includes both high and low levels of arsenic. Regression analysis, based on six studies identified from an electronic search, examined the relationship between the log of the relative risk and the log of the arsenic exposure over a range of 1–1000 µg/L. The best-fitting continuous meta-regression model was sought and found to be a no-constant linear-quadratic analysis where both the risk and the exposure had been logarithmically transformed. This yielded both a statistically significant positive coefficient for the quadratic term and a statistically significant negative coefficient for the linear term. Sub-analyses by study design yielded results that were similar for both ecological studies and non-ecological studies. Statistically significant X-intercepts consistently found no increased level of risk at approximately 100–150 µg/L arsenic. PMID:26690190
Shi, Lei; Zhang, Danyang; Zhou, Chenyu; Yang, Libin; Sun, Tao; Hao, Tianjun; Peng, Xiangwen; Gao, Lei; Liu, Wenhui; Mu, Yi; Han, Yuzhen; Fan, Lihua
2017-01-01
Objectives The purpose of the present study was to explore the characteristics of workplace violence that Chinese nurses at tertiary and county–level hospitals encountered in the 12 months from December 2014 to January 2016, to identify and analyse risk factors for workplace violence, and to establish the basis for future preventive strategies. Design A cross–sectional study. Setting A total of 44 tertiary hospitals and 90 county–level hospitals in 16 provinces (municipalities or autonomous regions) in China. Methods We used stratified random sampling to collect data from December 2014 to January 2016. We distributed 21 360 questionnaires, and 15 970 participants provided valid data (effective response rate=74.77%). We conducted binary logistic regression analyses on the risk factors for workplace violence among the nurses in our sample and analysed the reasons for aggression. Results The prevalence of workplace violence was 65.8%; of this, 64.9% was verbal violence, and physical violence and sexual harassment accounted for 11.8% and 3.9%, respectively. Frequent workplace violence occurred primarily in emergency and paediatric departments. Respondents reported that patients’ relatives were the main perpetrators in tertiary and county–level hospitals. Logistic regression analysis showed that respondents’ age, department, years of experience and direct contact with patients were common risk factors at different levels of hospitals. Conclusions Workplace violence is frequent in China’s tertiary and county–level hospitals; its occurrence is especially frequent in the emergency and paediatric departments. It is necessary to cope with workplace violence by developing effective control strategies at individual, hospital and national levels. PMID:28647719
Shi, Lei; Zhang, Danyang; Zhou, Chenyu; Yang, Libin; Sun, Tao; Hao, Tianjun; Peng, Xiangwen; Gao, Lei; Liu, Wenhui; Mu, Yi; Han, Yuzhen; Fan, Lihua
2017-06-24
The purpose of the present study was to explore the characteristics of workplace violence that Chinese nurses at tertiary and county-level hospitals encountered in the 12 months from December 2014 to January 2016, to identify and analyse risk factors for workplace violence, and to establish the basis for future preventive strategies. A cross-sectional study. A total of 44 tertiary hospitals and 90 county-level hospitals in 16 provinces (municipalities or autonomous regions) in China. We used stratified random sampling to collect data from December 2014 to January 2016. We distributed 21 360 questionnaires, and 15 970 participants provided valid data (effective response rate=74.77%). We conducted binary logistic regression analyses on the risk factors for workplace violence among the nurses in our sample and analysed the reasons for aggression. The prevalence of workplace violence was 65.8%; of this, 64.9% was verbal violence, and physical violence and sexual harassment accounted for 11.8% and 3.9%, respectively. Frequent workplace violence occurred primarily in emergency and paediatric departments. Respondents reported that patients' relatives were the main perpetrators in tertiary and county-level hospitals. Logistic regression analysis showed that respondents' age, department, years of experience and direct contact with patients were common risk factors at different levels of hospitals. Workplace violence is frequent in China's tertiary and county-level hospitals; its occurrence is especially frequent in the emergency and paediatric departments. It is necessary to cope with workplace violence by developing effective control strategies at individual, hospital and national levels. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.
Lehto, Elviira; Ray, Carola; Haukkala, Ari; Yngve, Agneta; Thorsdottir, Inga; Roos, Eva
2016-01-14
We examined whether there are sex differences in children's fruit and vegetable (FV) intake and in descriptive norms (i.e. perceived FV intake) related to parents and friends. We also studied whether friends' impact is as important as that of parents on children's FV intake. Data from the PRO GREENS project in Finland were obtained from 424 children at the age 11 years at baseline. At baseline, 2009 children filled in a questionnaire about descriptive norms conceptualised as perceived FV intake of their parents and friends. They also filled in a validated FFQ that assessed their FV intake both at baseline and in the follow-up in 2010. The associations were examined with multi-level regression analyses with multi-group comparisons. Girls reported higher perceived FV intake of friends and higher own fruit intake at baseline, compared with boys, and higher vegetable intake both at baseline and in the follow-up. Perceived FV intake of parents and friends was positively associated with both girls' and boys' FV intake in both study years. The impact of perceived fruit intake of the mother was stronger among boys. The change in children's FV intake was affected only by perceived FV intake of father and friends. No large sex differences in descriptive norms were found, but the impact of friends on children's FV intake can generally be considered as important as that of parents. Future interventions could benefit from taking into account friends' impact as role models on children's FV intake.
Jelenkovic, Aline; Yokoyama, Yoshie; Sund, Reijo; Pietiläinen, Kirsi H; Hur, Yoon-Mi; Willemsen, Gonneke; Bartels, Meike; van Beijsterveldt, Toos CEM; Ooki, Syuichi; Saudino, Kimberly J; Stazi, Maria A; Fagnani, Corrado; D’Ippolito, Cristina; Nelson, Tracy L; Whitfield, Keith E; Knafo-Noam, Ariel; Mankuta, David; Abramson, Lior; Heikkilä, Kauko; Cutler, Tessa L; Hopper, John L; Wardle, Jane; Llewellyn, Clare H; Fisher, Abigail; Corley, Robin P; Huibregtse, Brooke M; Derom, Catherine A; Vlietinck, Robert F; Loos, Ruth JF; Bjerregaard-Andersen, Morten; Beck-Nielsen, Henning; Sodemann, Morten; Tarnoki, Adam D; Tarnoki, David L; Burt, S Alexandra; Klump, Kelly L; Ordoñana, Juan R; Sánchez-Romera, Juan F; Colodro-Conde, Lucia; Dubois, Lise; Boivin, Michel; Brendgen, Mara; Dionne, Ginette; Vitaro, Frank; Harris, Jennifer R; Brandt, Ingunn; Nilsen, Thomas Sevenius; Craig, Jeffrey M; Saffery, Richard; Rasmussen, Finn; Tynelius, Per; Bayasgalan, Gombojav; Narandalai, Danshiitsoodol; Haworth, Claire MA; Plomin, Robert; Ji, Fuling; Ning, Feng; Pang, Zengchang; Rebato, Esther; Krueger, Robert F; McGue, Matt; Pahlen, Shandell; Boomsma, Dorret I; Sørensen, Thorkild IA; Kaprio, Jaakko; Silventoinen, Karri
2017-01-01
Abstract Background There is evidence that birthweight is positively associated with body mass index (BMI) in later life, but it remains unclear whether this is explained by genetic factors or the intrauterine environment. We analysed the association between birthweight and BMI from infancy to adulthood within twin pairs, which provides insights into the role of genetic and environmental individual-specific factors. Methods This study is based on the data from 27 twin cohorts in 17 countries. The pooled data included 78 642 twin individuals (20 635 monozygotic and 18 686 same-sex dizygotic twin pairs) with information on birthweight and a total of 214 930 BMI measurements at ages ranging from 1 to 49 years. The association between birthweight and BMI was analysed at both the individual and within-pair levels using linear regression analyses. Results At the individual level, a 1-kg increase in birthweight was linearly associated with up to 0.9 kg/m2 higher BMI (P < 0.001). Within twin pairs, regression coefficients were generally greater (up to 1.2 kg/m2 per kg birthweight, P < 0.001) than those from the individual-level analyses. Intra-pair associations between birthweight and later BMI were similar in both zygosity groups and sexes and were lower in adulthood. Conclusions These findings indicate that environmental factors unique to each individual have an important role in the positive association between birthweight and later BMI, at least until young adulthood. PMID:28369451
Association between state school nutrition laws and subsequent child obesity.
Palakshappa, Deepak; Fiks, Alexander G; Faerber, Jennifer A; Feudtner, Chris
2016-09-01
Many states have enacted laws to improve school nutrition. We tested whether stronger state nutrition laws are associated with subsequently decreased obesity. We conducted a retrospective national multi-year panel data study (analyzed 2014-2016 at the Children's Hospital of Philadelphia). The predictors were 2010 laws regarding 9 nutrition categories from the Classification of Laws Associated with School Students, which grades the strength of state laws (none, weak, or strong). The outcome was weight status (healthy weight, overweight, or obese) in elementary, middle, and high school from the 2011/2012 National Survey of Children's Health. We tested the association between the strength of laws and weight using multinomial logistic regression. To further evaluate our main results, we conducted state-level longitudinal analyses testing the association between competitive food and beverage laws on the change in obesity from 2003-2011. In main analyses of 40,177 children ages 10-17years, we found strong state laws restricting the sale of competitive food and beverages in elementary school (OR: 0.68; 95% CI: 0.48, 0.96) and strong advertising laws across all grades (OR: 0.63; 95% CI: 0.46, 0.86) were associated with reduced odds of obesity. In longitudinal analyses, states with strong competitive food and beverage laws from 2003-2010 had small but significant decreases in obesity, compared to states with no laws. Although further research is needed to determine the causal effect of these laws, this study suggests that strong state laws limiting the sale and advertising of unhealthy foods and beverages in schools are associated with decreased obesity rates. Copyright © 2016 Elsevier Inc. All rights reserved.
Castrillo Sanz, A; Andrés Calvo, M; Repiso Gento, I; Izquierdo Delgado, E; Gutierrez Ríos, R; Rodríguez Herrero, R; Rodríguez Sanz, F; Tola-Arribas, M A
2016-06-01
Anosognosia is a frequent symptom in Alzheimer disease (AD). The objective of this article is to describe prevalence of this condition at time of diagnosis and analyse any predisposing factors and their influence on disease progression. Observational, prospective, and analytical multi-centre study in an outpatient setting. Patients recently diagnosed with AD (NINCDS-ADRDA criteria) were included. Each patient underwent two cognitive, functional, and neuropsychiatric assessments separated by an interval of 18 months. The Clinical Insight Rating Scale was employed as a measure of anosognosia (CIR, scored 0-8). Progression was defined as an increase in the Clinical Dementia Rating Scale-sum of boxes of more than 2.5 points. The predictor variables were analysed using binary logistic regression. The study included 127 patients, and 94 completed both assessments. Of the total, 31.5% displayed severe anosognosia (CIR 7-8); 39.4%, altered level of consciousness (CIR 3-6); and 29.1%, normal awareness (CIR 0-2). The median baseline CIR in this cohort was 4 (Q1-Q3: 1-7), and at 18 months, 6 (Q1-Q3: 3-8), P<.001. Advanced age (odds ratio (OR) 2.43; CI 95%:1.14-5.19), lower educational level (OR 2.15; CI 95%:1.01-4.58), and more marked neuropsychiatric symptoms (OR 2.66; CI 95%:1.23-5.74) were predictor variables of anosognosia. Baseline CIR was similar in the groups with and without significant clinical progression. The large majority of patients with AD at the time of diagnosis showed significant anosognosia, and this condition was associated with advanced age, lower educational level, and more marked behavioural symptoms. Our results did not show that anosognosia had an effect on the initial clinical progression of AD after diagnosis. Copyright © 2014 Sociedad Española de Neurología. Published by Elsevier España, S.L.U. All rights reserved.
Cruz, Antonio M; Barr, Cameron; Puñales-Pozo, Elsa
2008-01-01
This research's main goals were to build a predictor for a turnaround time (TAT) indicator for estimating its values and use a numerical clustering technique for finding possible causes of undesirable TAT values. The following stages were used: domain understanding, data characterisation and sample reduction and insight characterisation. Building the TAT indicator multiple linear regression predictor and clustering techniques were used for improving corrective maintenance task efficiency in a clinical engineering department (CED). The indicator being studied was turnaround time (TAT). Multiple linear regression was used for building a predictive TAT value model. The variables contributing to such model were clinical engineering department response time (CE(rt), 0.415 positive coefficient), stock service response time (Stock(rt), 0.734 positive coefficient), priority level (0.21 positive coefficient) and service time (0.06 positive coefficient). The regression process showed heavy reliance on Stock(rt), CE(rt) and priority, in that order. Clustering techniques revealed the main causes of high TAT values. This examination has provided a means for analysing current technical service quality and effectiveness. In doing so, it has demonstrated a process for identifying areas and methods of improvement and a model against which to analyse these methods' effectiveness.
The Coopersmith Self-Esteem Inventory: A Construct Validation Study.
ERIC Educational Resources Information Center
Johnson, Brian W.
1983-01-01
Regression analyses indicated that the Coopersmith Self-Esteem Inventory has convergent validity with regard to the Piers-Harris Children's Self-Concept Scale and the Coopersmith Behavioral Academic Assessment Scale, has discriminant validity with regard to the Children's Social Desirability Scale, is sensitive to differences in achievement level,…
ERIC Educational Resources Information Center
Cavior, Norman; And Others
1975-01-01
Tenth and twelfth grade males and females who knew each other judged, within grade levels, their classmates on physical attractiveness (PA), perceived attitude similarity (PAS), and interpersonal attraction (IA). Regression analyses supported the hypotheses that PA and PAS are positively correlated. (Author)
The Role of Parental Influences on Young Adolescents' Career Development
ERIC Educational Resources Information Center
Keller, Briana K.; Whiston, Susan C.
2008-01-01
The relationship between specific parental behaviors and the career development of young adolescents was assessed. Regression analyses revealed that parental behaviors did relate to the career development of middle school students, after controlling for student grade level and gender. Parental behaviors tended to relate more to career…
Hansen, Niklas; Sverke, Magnus; Näswall, Katharina
2009-01-01
Health care organizations have changed dramatically over the last decades, with hospitals undergoing restructurings and privatizations. The aim of this study is to enhance the understanding of the origin and prevalence of burnout in health care by investigating factors in the psychosocial work environment and comparing three Swedish emergency hospitals with different types of ownership. A cross-sectional design was used. We selected a total sample of 1800 registered nurses from three acute care hospitals, one private for-profit, one private non-profit and one publicly administered. A total of 1102 questionnaires were included in the analyses. The examined ownership types were a private for-profit, a private non-profit and a traditional publicly administered hospital. All were situated in the Stockholm region, Sweden. Data were collected by questionnaires using validated instruments, in accordance with the Job Demands-Resources Model and Maslach's Burnout Inventory. Descriptive statistics, correlation analyses, multivariate covariance analyses and multiple regression analyses were conducted. The results showed that the burnout levels were the highest at the private for-profit hospital and lowest at the publicly administered hospital. However, in contrast to expectations the demands were not higher overall at the for-profit organization or lowest at the public administration unit, and overall, resources were not better in the private for-profit or worse at the publicly administered hospital. Multiple regression analyses showed that several of the demands included were related to higher burnout levels. Job resources were linked to lower burnout levels, but not for all variables. Profit orientation in health care seems to result in higher burnout levels for registered nurses compared to a publicly administered hospital. In general, demands were more predictive of burnout than resources, and there were only marginal differences in the pattern of predictors across hospitals.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yang, Qichun; Zhang, Xuesong; Xu, Xingya
Riverine carbon cycling is an important, but insufficiently investigated component of the global carbon cycle. Analyses of environmental controls on riverine carbon cycling are critical for improved understanding of mechanisms regulating carbon processing and storage along the terrestrial-aquatic continuum. Here, we compile and analyze riverine dissolved organic carbon (DOC) concentration data from 1402 United States Geological Survey (USGS) gauge stations to examine the spatial variability and environmental controls of DOC concentrations in the United States (U.S.) surface waters. DOC concentrations exhibit high spatial variability, with an average of 6.42 ± 6.47 mg C/ L (Mean ± Standard Deviation). In general,more » high DOC concentrations occur in the Upper Mississippi River basin and the Southeastern U.S., while low concentrations are mainly distributed in the Western U.S. Single-factor analysis indicates that slope of drainage areas, wetlands, forests, percentage of first-order streams, and instream nutrients (such as nitrogen and phosphorus) pronouncedly influence DOC concentrations, but the explanatory power of each bivariate model is lower than 35%. Analyses based on the general multi-linear regression models suggest DOC concentrations are jointly impacted by multiple factors. Soil properties mainly show positive correlations with DOC concentrations; forest and shrub lands have positive correlations with DOC concentrations, but urban area and croplands demonstrate negative impacts; total instream phosphorus and dam density correlate positively with DOC concentrations. Notably, the relative importance of these environmental controls varies substantially across major U.S. water resource regions. In addition, DOC concentrations and environmental controls also show significant variability from small streams to large rivers, which may be caused by changing carbon sources and removal rates by river orders. In sum, our results reveal that general multi-linear regression analysis of twenty one terrestrial and aquatic environmental factors can partially explain (56%) the DOC concentration variation. In conclusion, this study highlights the complexity of the interactions among these environmental factors in determining DOC concentrations, thus calls for processes-based, non-linear methodologies to constrain uncertainties in riverine DOC cycling.« less
Baheiraei, Azam; Bakouei, Fatemeh; Bakouei, Sareh; Eskandari, Narges; Ahmari Tehran, Hoda
2015-07-19
Recognition of the factors related to women's health is necessary. Evidence is available that the social structure including social capital plays an important role in the shaping people's health. The aim of the current study was to investigate the association between self-rated health and social capital in women of reproductive age. This study is a population-based cross-sectional survey on 770 women of reproductive age, residing in any one of the 22 municipality areas across Tehran (capital of Iran) with the multi stage sampling technique. Self-rated health (Dependent variable), social capital (Independent variable) and covariates were studied. Analysis of data was done by one-way ANOVA test and multiple linear regressions. Depending on logistic regression analyses, the significant associations were found between self-rated health and age, educational level, crowding index, sufficiency of income for expenses and social cohesion. Data show that women with higher score in social cohesion as an outcome dimension of social capital have better self-rated health (PV = 0.001). Given the findings of this study, the dimensions of social capital manifestations (groups and networks, trust and solidarity, collective action and cooperation) can potentially lead to the dimensions of social capital outcomes (social cohesion and inclusion, and empowerment and political action). Following that, social cohesion as a dimension of social capital outcomes has positively relationship with self- rated health after controlling covariates. Therefore, it is required to focus on the social capital role on health promotion and health policies.
Bidirectional relationship between renal function and periodontal disease in older Japanese women.
Yoshihara, Akihiro; Iwasaki, Masanori; Miyazaki, Hideo; Nakamura, Kazutoshi
2016-09-01
The purpose of this study was to evaluate the reciprocal effects of chronic kidney disease (CKD) and periodontal disease. A total of 332 postmenopausal never smoking women were enrolled, and their serum high-sensitivity C-reactive protein, serum osteocalcin and serum cystatin C levels were measured. Poor renal function was defined as serum cystatin C > 0.91 mg/l. Periodontal disease markers, including clinical attachment level and the periodontal inflamed surface area (PISA), were also evaluated. Logistic regression analysis was conducted to evaluate the relationships between renal function and periodontal disease markers, serum osteocalcin level and hsCRP level. The prevalence-rate ratios (PRRs) on multiple Poisson regression analyses were determined to evaluate the relationships between periodontal disease markers and serum osteocalcin, serum cystatin C and serum hsCRP levels. On logistic regression analysis, PISA was significantly associated with serum cystatin C level. The odds ratio for serum cystatin C level was 2.44 (p = 0.011). The PRR between serum cystatin C level and periodontal disease markers such as number of sites with clinical attachment level ≥6 mm was significantly positive (3.12, p < 0.001). Similar tendencies were shown for serum osteocalcin level. This study suggests that CKD and periodontal disease can have reciprocal effects. © 2016 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.
Keeping in touch with children after separation: the point of view of fathers.
Le Bourdais, Céline; Juby, Heather; Marcil-Gratton, Nicole
2002-01-01
The amount of father-child contact after separation is closely linked to the probability that father fulfill their financial obligations towards their children. Determining the factors that encourage this contact is, therefore, crucial to the process of reducing the risk of poverty to which children of separated parents are exposed. Based on data collected from fathers at the 1995 Canadian General Social Survey of the Family, this paper uses multi-level regression analysis to identify factors associated with higher levels of contact between fathers and children, including socio-demographic characteristics of children and fathers, variables associated with attitudes, and fathers' satisfaction with custody and access arrangements.
Using TIMSS and PISA Results to Inform Educational Policy: A Study of Russia and Its Neighbours
ERIC Educational Resources Information Center
Carnoy, Martin; Khavenson, Tatiana; Ivanova, Alina
2015-01-01
In this paper, we develop a multi-level comparative approach to analyse Trends in International Mathematics and Science Survey (TIMSS) and Programme of International Student Achievement (PISA) mathematics results for a country, Russia, where the two tests provide contradictory information about students' relative performance. Russian students do…
After-School Programs as a Prosocial Setting for Bonding between Peers
ERIC Educational Resources Information Center
Wright, Robin; John, Lindsay; Duku, Eric; Burgos, Giovani; Krygsman, Amanda; Esposto, Charlene
2009-01-01
This study reports on the longitudinal analysis of a structured after-school arts program for Canadian youth, ages 9 to 15 years, from low-income communities where the relationship of peer social support, family interactions, and psychosocial outcomes is evaluated. Multi-level growth curve analyses suggest an increase in prosocial development with…
Pupil Performance, Absenteeism and School Drop-out: A Multi-dimensional Analysis.
ERIC Educational Resources Information Center
Smyht, Emer
1999-01-01
Assesses whether second-level schools in Ireland are equally effective regarding examination performance, absenteeism, and potential dropouts, using multivariate analyses of data from 15- and 16-year-olds in 116 schools. Absenteeism and potential dropout rates are lower in schools that enhance pupils' academic progress. (Contains 22 references.)…
Bottom-Up Analysis of Single-Case Research Designs
ERIC Educational Resources Information Center
Parker, Richard I.; Vannest, Kimberly J.
2012-01-01
This paper defines and promotes the qualities of a "bottom-up" approach to single-case research (SCR) data analysis. Although "top-down" models, for example, multi-level or hierarchical linear models, are gaining momentum and have much to offer, interventionists should be cautious about analyses that are not easily understood, are not governed by…
Method of Grassland Information Extraction Based on Multi-Level Segmentation and Cart Model
NASA Astrophysics Data System (ADS)
Qiao, Y.; Chen, T.; He, J.; Wen, Q.; Liu, F.; Wang, Z.
2018-04-01
It is difficult to extract grassland accurately by traditional classification methods, such as supervised method based on pixels or objects. This paper proposed a new method combing the multi-level segmentation with CART (classification and regression tree) model. The multi-level segmentation which combined the multi-resolution segmentation and the spectral difference segmentation could avoid the over and insufficient segmentation seen in the single segmentation mode. The CART model was established based on the spectral characteristics and texture feature which were excavated from training sample data. Xilinhaote City in Inner Mongolia Autonomous Region was chosen as the typical study area and the proposed method was verified by using visual interpretation results as approximate truth value. Meanwhile, the comparison with the nearest neighbor supervised classification method was obtained. The experimental results showed that the total precision of classification and the Kappa coefficient of the proposed method was 95 % and 0.9, respectively. However, the total precision of classification and the Kappa coefficient of the nearest neighbor supervised classification method was 80 % and 0.56, respectively. The result suggested that the accuracy of classification proposed in this paper was higher than the nearest neighbor supervised classification method. The experiment certificated that the proposed method was an effective extraction method of grassland information, which could enhance the boundary of grassland classification and avoid the restriction of grassland distribution scale. This method was also applicable to the extraction of grassland information in other regions with complicated spatial features, which could avoid the interference of woodland, arable land and water body effectively.
Self-efficacy and physical activity in adolescent and parent dyads.
Rutkowski, Elaine M; Connelly, Cynthia D
2012-01-01
The study examined the relationships between self-efficacy and physical activity in adolescent and parent dyads. A cross-sectional, correlational design was used to explore the relationships among levels of parent physical activity, parent-adolescent self-efficacy, and adolescent physical activity. Descriptive and multivariate regression analyses were conducted in a purposive sample of 94 adolescent/parent dyads. Regression results indicated the overall model significantly predicted adolescent physical activity (R(2) = .20, R(2)(adj) = .14, F[5, 70]= 3.28, p= .01). Only one of the five predictor variables significantly contributed to the model. Higher levels of adolescent self-efficacy was positively related to greater levels of adolescent physical activity (β= .29, p= .01). Practitioners are encouraged to examine the level of self-efficacy and physical activity in families in an effort to develop strategies that impact these areas and ultimately to mediate obesity-related challenges in families seeking care. © 2011, Wiley Periodicals, Inc.
Modeling of bromate formation by ozonation of surface waters in drinking water treatment.
Legube, Bernard; Parinet, Bernard; Gelinet, Karine; Berne, Florence; Croue, Jean-Philippe
2004-04-01
The main objective of this paper is to try to develop statistically and chemically rational models for bromate formation by ozonation of clarified surface waters. The results presented here show that bromate formation by ozonation of natural waters in drinking water treatment is directly proportional to the "Ct" value ("Ctau" in this study). Moreover, this proportionality strongly depends on many parameters: increasing of pH, temperature and bromide level leading to an increase of bromate formation; ammonia and dissolved organic carbon concentrations causing a reverse effect. Taking into account limitation of theoretical modeling, we proposed to predict bromate formation by stochastic simulations (multi-linear regression and artificial neural networks methods) from 40 experiments (BrO(3)(-) vs. "Ctau") carried out with three sand filtered waters sampled on three different waterworks. With seven selected variables we used a simple architecture of neural networks, optimized by "neural connection" of SPSS Inc./Recognition Inc. The bromate modeling by artificial neural networks gives better result than multi-linear regression. The artificial neural networks model allowed us classifying variables by decreasing order of influence (for the studied cases in our variables scale): "Ctau", [N-NH(4)(+)], [Br(-)], pH, temperature, DOC, alkalinity.
Jeanjean, Maxime; Bind, Marie-Abele; Roux, Jonathan; Ongagna, Jean-Claude; de Sèze, Jérôme; Bard, Denis; Leray, Emmanuelle
2018-05-01
Triggers of multiple sclerosis (MS) relapses are essentially unknown. PM 10 exposure has recently been associated with an increased risk of relapses. We further explore the short-term associations between PM 10 , NO 2 , benzene (C 6 H 6 ), O 3 , and CO exposures, and the odds of MS relapses' occurrence. Using a case-crossover design, we studied 424 MS patients living in the Strasbourg area, France between 2000 and 2009 (1783 relapses in total). Control days were chosen to be ± 35 days relative to the case (relapse) day. Exposure was modeled through ADMS-Urban software at the census block scale. We consider single-pollutant and multi-pollutant conditional logistic regression models coupled with a distributed-lag linear structure, stratified by season ("hot" vs. "cold"), and adjusted for meteorological parameters, pollen count, influenza-like epidemics, and holidays. The single-pollutant analyses indicated: 1) significant associations between MS relapse incidence and exposures to NO 2 , PM 10 , and O 3 , and 2) seasonality in these associations. For instance, an interquartile range increase in NO 2 (lags 0-3) and PM 10 exposure were associated with MS relapse incidence (OR = 1.08; 95%CI: [1.03-1.14] and OR = 1.06; 95%CI: [1.01-1.11], respectively) during the "cold" season (i.e., October-March). We also observed an association with O 3 and MS relapse incidence during "hot" season (OR = 1.16; 95%CI: [1.07-1.25]). C 6 H 6 and CO were not significantly related to MS relapse incidence. However, using multi-pollutant models, only O 3 remained significantly associated with the odds of relapse triggering during "hot" season. We observed significant single-pollution associations between the occurrence of MS relapses and exposures to NO 2 , O 3 and PM 10 , only O 3 remained significantly associated with occurrence of MS relapses in the multi-pollutant model. Copyright © 2018. Published by Elsevier Inc.
Mussen, Lauren; Boyd, Tristan; Bykerk, Vivian; de Leon, Faye; Li, Lihua; Boire, Gilles; Hitchon, Carol; Haraoui, Boulos; Thorne, J Carter; Pope, Janet
2013-02-01
We determined the prevalence of work disability in early rheumatoid arthritis (ERA) and undifferentiated early inflammatory arthritis (EIA) patients at first enrollment into the Canadian Early Arthritis Cohort (CATCH) who met the 2010 ACR criteria versus those not meeting criteria, to determine the impact of meeting new criteria on work disability status. Data at first visit into the cohort were analyzed. Descriptive statistics and logistic regression analyses were performed to investigate the association of other variables in our database with work disability. 1,487 patients were enrolled in the CATCH study, a multi-site observational, prospective cohort of patients with EIA. 934 patients were excluded (505 based on missing criteria for ACR 2010 classification, as anti-CCP was absent, and 429 were not working for other reasons). Of the 553 patients included, 71 % were female with mean disease duration of 6.4 months. 524 (94.8 %) were employed while 29 (5.2 %) reported work disability at first visit. There were no differences between those meeting 2010 ACR criteria versus those who did not. Baseline characteristics associated with work disability were male gender, age, education, income, HAQ, and positive RF status. The mean HAQ score in work disabled patients was 1.4 versus 0.9 in those who were working (p < 0.001). Disease activity score (DAS28) was not associated with work disability (p = 0.069), nor was tender joint count, swollen joint count, anti-CCP, patient global assessment, or SF-12v2. In the regression model, work disability was associated with lower income levels (p = 0.01) and worse HAQ scores (OR 2.33; p = 0.001), but not significantly associated with male gender (p = 0.08), older age (>50 years; p = 0.3), lower education (p = 0.3) or RF positivity (p = 0.6). We found rates of work disability to be low at entry into this EIA cohort compared to previous studies. There may be potential for intervention in ERA to prevent the development of work disability.
Linear regression metamodeling as a tool to summarize and present simulation model results.
Jalal, Hawre; Dowd, Bryan; Sainfort, François; Kuntz, Karen M
2013-10-01
Modelers lack a tool to systematically and clearly present complex model results, including those from sensitivity analyses. The objective was to propose linear regression metamodeling as a tool to increase transparency of decision analytic models and better communicate their results. We used a simplified cancer cure model to demonstrate our approach. The model computed the lifetime cost and benefit of 3 treatment options for cancer patients. We simulated 10,000 cohorts in a probabilistic sensitivity analysis (PSA) and regressed the model outcomes on the standardized input parameter values in a set of regression analyses. We used the regression coefficients to describe measures of sensitivity analyses, including threshold and parameter sensitivity analyses. We also compared the results of the PSA to deterministic full-factorial and one-factor-at-a-time designs. The regression intercept represented the estimated base-case outcome, and the other coefficients described the relative parameter uncertainty in the model. We defined simple relationships that compute the average and incremental net benefit of each intervention. Metamodeling produced outputs similar to traditional deterministic 1-way or 2-way sensitivity analyses but was more reliable since it used all parameter values. Linear regression metamodeling is a simple, yet powerful, tool that can assist modelers in communicating model characteristics and sensitivity analyses.
Estimation of potential scour at bridges on local government roads in South Dakota, 2009-12
Thompson, Ryan F.; Wattier, Chelsea M.; Liggett, Richard R.; Truax, Ryan A.
2014-01-01
In 2009, the U.S. Geological Survey and South Dakota Department of Transportation (SDDOT) began a study to estimate potential scour at selected bridges on local government (county, township, and municipal) roads in South Dakota. A rapid scour-estimation method (level-1.5) and a more detailed method (level-2) were used to develop estimates of contraction, abutment, and pier scour. Data from 41 level-2 analyses completed for this study were combined with data from level-2 analyses completed in previous studies to develop new South Dakota-specific regression equations: four regional equations for main-channel velocity at the bridge contraction to account for the widely varying stream conditions within South Dakota, and one equation for head change. Velocity data from streamgages also were used in the regression for average velocity through the bridge contraction. Using these new regression equations, scour analyses were completed using the level-1.5 method on 361 bridges on local government roads. Typically, level-1.5 analyses are completed at flows estimated to have annual exceedance probabilities of 1 percent (100-year flood) and 0.2 percent (500-year flood); however, at some sites the bridge would not pass these flows. A level-1.5 analysis was then completed at the flow expected to produce the maximum scour. Data presented for level-1.5 scour analyses at the 361 bridges include contraction, abutment, and pier scour. Estimates of potential contraction scour ranged from 0 to 32.5 feet for the various flows evaluated. Estimated potential abutment scour ranged from 0 to 40.9 feet for left abutments, and from 0 to 37.7 feet for right abutments. Pier scour values ranged from 2.7 to 31.6 feet. The scour depth estimates provided in this report can be used by the SDDOT to compare with foundation depths at each bridge to determine if abutments or piers are at risk of being undermined by scour at the flows evaluated. Replicate analyses were completed at 24 of the 361 bridges to provide quality-assurance/quality-control measures for the level-1.5 scour estimates. An attempt was made to use the same flows among replicate analyses. Scour estimates do not necessarily have to be in numerical agreement to give the same results. For example, if contraction scour replicate analyses are 18.8 and 30.8 feet, both scour depths can indicate susceptibility to scour for which countermeasures may be needed, even though one number is much greater than the other number. Contraction scour has perhaps the greatest potential for being estimated differently in replicate visits. For contraction scour estimates at the various flows analyzed, differences between results ranged from -7.8 to 5.5 feet, with a median difference of 0.4 foot and an average difference of 0.2 foot. Abutment scour appeared to be nearly as reproducible as contraction scour. For abutment scour estimates at the varying flows analyzed, differences between results ranged from -17.4 to 11 feet, with a median difference of 1.4 feet and an average difference of 1.7 feet. Estimates of pier scour tended to be the most consistently reproduced in replicate visits, with differences between results ranging from -0.3 to 0.5 foot, with a median difference of 0.0 foot and an average difference of 0.0 foot. The U.S. Army Corps of Engineers Hydraulics Engineering Center River Analysis Systems (HEC-RAS) software package was used to model stream hydraulics at the 41 sites with level-2 analyses. Level-1.5 analyses also were completed at these sites, and the performance of the level-1.5 method was assessed by comparing results to those from the more rigorous level-2 method. The envelope curve approach used in the level-1.5 method is designed to overestimate scour relative to the estimate from the level-2 scour analysis. In cases where the level-1.5 method estimated less scour than the level-2 method, the amount of underestimation generally was less than 3 feet. The level-1.5 method generally overestimated contraction, abutment, and pier scour relative to the level-2 method, as intended. Although the level-1.5 method is designed to overestimate scour relative to more involved analysis methods, many assumptions, uncertainties, and estimations are involved. If the envelope curves are adjusted such that the level-1.5 method never underestimates scour relative to the level-2 method, an accompanying result may be excessive overestimation.
Functional classification of grasp strategies used by hemiplegic patients
Roby-Brami, Agnès; Robertson, Johanna; Roche, Nicolas
2017-01-01
This study aimed to identify and qualify grasp-types used by patients with stroke and determine the clinical parameters that could explain the use of each grasp. Thirty-eight patients with chronic stroke-related hemiparesis and a range of motor and functional capacities (17 females and 21 males, aged 25–78), and 10 healthy subjects were included. Four objects were used (tissue packet, teaspoon, bottle and tennis ball). Participants were instructed to “grasp the object as if you are going to use it”. Three trials were video-recorded for each object. A total of 456 grasps were analysed and rated using a custom-designed Functional Grasp Scale. Eight grasp-types were identified from the analysis: healthy subjects used Multi-pulpar, Pluri-digital, Lateral-pinch and Palmar grasps (Standard Grasps). Patients used the same grasps with in addition Digito-palmar, Raking, Ulnar and Interdigital grasps (Alternative Grasps). Only patients with a moderate or relatively good functional ability used Standard grasps. The correlation and regression analyses showed this was conditioned by sufficient finger and elbow extensor strength (Pluri-digital grasp); thumb extensor and wrist flexor strength (Lateral pinch) or in forearm supinator strength (Palmar grasp). By contrast, the patients who had severe impairment used Alternative grasps that did not involve the thumb. These strategies likely compensate specific impairments. Regression and correlation analyses suggested that weakness had a greater influence over grasp strategy than spasticity. This would imply that treatment should focus on improving hand strength and control although reducing spasticity may be useful in some cases. PMID:29125855
Probabilistic Estimates of Global Mean Sea Level and its Underlying Processes
NASA Astrophysics Data System (ADS)
Hay, C.; Morrow, E.; Kopp, R. E.; Mitrovica, J. X.
2015-12-01
Local sea level can vary significantly from the global mean value due to a suite of processes that includes ongoing sea-level changes due to the last ice age, land water storage, ocean circulation changes, and non-uniform sea-level changes that arise when modern-day land ice rapidly melts. Understanding these sources of spatial and temporal variability is critical to estimating past and present sea-level change and projecting future sea-level rise. Using two probabilistic techniques, a multi-model Kalman smoother and Gaussian process regression, we have reanalyzed 20th century tide gauge observations to produce a new estimate of global mean sea level (GMSL). Our methods allow us to extract global information from the sparse tide gauge field by taking advantage of the physics-based and model-derived geometry of the contributing processes. Both methods provide constraints on the sea-level contribution of glacial isostatic adjustment (GIA). The Kalman smoother tests multiple discrete models of glacial isostatic adjustment (GIA), probabilistically computing the most likely GIA model given the observations, while the Gaussian process regression characterizes the prior covariance structure of a suite of GIA models and then uses this structure to estimate the posterior distribution of local rates of GIA-induced sea-level change. We present the two methodologies, the model-derived geometries of the underlying processes, and our new probabilistic estimates of GMSL and GIA.
Applying Regression Analysis to Problems in Institutional Research.
ERIC Educational Resources Information Center
Bohannon, Tom R.
1988-01-01
Regression analysis is one of the most frequently used statistical techniques in institutional research. Principles of least squares, model building, residual analysis, influence statistics, and multi-collinearity are described and illustrated. (Author/MSE)
Comparison of alternative approaches for analysing multi-level RNA-seq data
Mohorianu, Irina; Bretman, Amanda; Smith, Damian T.; Fowler, Emily K.; Dalmay, Tamas
2017-01-01
RNA sequencing (RNA-seq) is widely used for RNA quantification in the environmental, biological and medical sciences. It enables the description of genome-wide patterns of expression and the identification of regulatory interactions and networks. The aim of RNA-seq data analyses is to achieve rigorous quantification of genes/transcripts to allow a reliable prediction of differential expression (DE), despite variation in levels of noise and inherent biases in sequencing data. This can be especially challenging for datasets in which gene expression differences are subtle, as in the behavioural transcriptomics test dataset from D. melanogaster that we used here. We investigated the power of existing approaches for quality checking mRNA-seq data and explored additional, quantitative quality checks. To accommodate nested, multi-level experimental designs, we incorporated sample layout into our analyses. We employed a subsampling without replacement-based normalization and an identification of DE that accounted for the hierarchy and amplitude of effect sizes within samples, then evaluated the resulting differential expression call in comparison to existing approaches. In a final step to test for broader applicability, we applied our approaches to a published set of H. sapiens mRNA-seq samples, The dataset-tailored methods improved sample comparability and delivered a robust prediction of subtle gene expression changes. The proposed approaches have the potential to improve key steps in the analysis of RNA-seq data by incorporating the structure and characteristics of biological experiments. PMID:28792517
Fuzzy multinomial logistic regression analysis: A multi-objective programming approach
NASA Astrophysics Data System (ADS)
Abdalla, Hesham A.; El-Sayed, Amany A.; Hamed, Ramadan
2017-05-01
Parameter estimation for multinomial logistic regression is usually based on maximizing the likelihood function. For large well-balanced datasets, Maximum Likelihood (ML) estimation is a satisfactory approach. Unfortunately, ML can fail completely or at least produce poor results in terms of estimated probabilities and confidence intervals of parameters, specially for small datasets. In this study, a new approach based on fuzzy concepts is proposed to estimate parameters of the multinomial logistic regression. The study assumes that the parameters of multinomial logistic regression are fuzzy. Based on the extension principle stated by Zadeh and Bárdossy's proposition, a multi-objective programming approach is suggested to estimate these fuzzy parameters. A simulation study is used to evaluate the performance of the new approach versus Maximum likelihood (ML) approach. Results show that the new proposed model outperforms ML in cases of small datasets.
Taylor, Robert Joseph; Chatters, Linda M.; Jackson, James S.
2010-01-01
The present study examined differences in reports of spirituality among African Americans, Caribbean Blacks (Black Caribbeans), and non-Hispanic whites using data from the National Survey of American Life (NSAL). Bivariate analyses indicated that African Americans were most likely to endorse statements regarding the importance of spirituality in their lives (“How important is spirituality in your life?”) and self-assessments of spirituality (“How spiritual would you say you are?”), followed by Caribbean Blacks and non-Hispanic whites. Regression analyses indicated that African Americans and Caribbean Blacks had significantly higher levels of spirituality than did non-Hispanic whites. However, there were no significant differences in spirituality between African Americans and Caribbean Blacks. Separate regression analyses for African Americans and Caribbean Blacks indicated distinctive patterns of sociodemographic and denominational correlates of spiritual sentiments. Findings are discussed in relation to available survey and ethnographic data on self-assessments of spirituality. PMID:21031157
Perceived Risk of Burglary and Fear of Crime: Individual- and Country-Level Mixed Modeling.
Chon, Don Soo; Wilson, Mary
2016-02-01
Given the scarcity of prior studies, the current research introduced country-level variables, along with individual-level ones, to test how they are related to an individual's perceived risk of burglary (PRB) and fear of crime (FC), separately, by using mixed-level logistic regression analyses. The analyses of 104,218 individuals, residing in 50 countries, showed that country-level poverty was positively associated with FC only. However, individual-level variables, such as prior property crime victimization and female gender, had consistently positive relationships with both PRB and FC. However, age group and socioeconomic status were inconsistent between those two models, suggesting that PRB and FC are two different concepts. Finally, no significant difference in the pattern of PRB and FC was found between a highly developed group of countries and a less developed one. © The Author(s) 2014.
Teo, Boon Wee; Toh, Qi Chun; Xu, Hui; Yang, Adonsia Y T; Lin, Tingxuan; Li, Jialiang; Lee, Evan J C
2015-04-01
Clinical practice guidelines recommend different levels of dietary protein intake in predialysis chronic kidney disease (CKD) patients. It is unknown how effectively these recommendations perform in a multi-ethnic Asian population, with varied cultural beliefs and diets. We assess the profi le of protein intake in a multi-ethnic Asian population, comparing healthy participants and CKD patients. We analysed the 24-hour urine collections of the Asian Kidney Disease Study (AKDS) and the Singapore Kidney Function Study (SKFS) to estimate total protein intake (TPI; g/day). We calculated ideal body weight (IDW; kg): 22.99 × height2 (m). Standard statistical tests were applied where appropriate, and linear regression was used to assess associations of continuous variables with protein intake. There were 232 CKD patients and 103 healthy participants with 35.5% diabetics. The mean TPI in healthy participants was 58.89 ± 18.42 and the mean TPI in CKD patients was 53.64 ± 19.39. By US National Kidney Foundation (NKF) guidelines, 29/232 (12.5%) of CKD patients with measured glomerular filtration rate (GFR) <25 (in mL/min/1.73 m2) had a TPI-IDW of <0.6 g/kg/day. By Caring for Australasians with Renal Impairment (CARI) guidelines, 76.3% (177/232) of CKD patients had TPI-IDW >0.75g/kg/ day. By American Dietetic Association (ADA) guidelines, 34.7% (44/127) of CKD patients with GFR <50 had TPI-IDW between 0.6 to 0.8 g/kg/day. Only 1/6 non-diabetic CKD patients with GFR <20 had a protein intake of between 0.3 to 0.5 g/kg/day. A total of 21.9% (25/114) of diabetic CKD patients had protein intake between 0.8 to 0.9 g/kg/day. On average, the protein intake of most CKD patients exceeds the recommendations of guidelines. Diabetic CKD patients should aim to have higher protein intakes.
Work characteristics predict the development of multi-site musculoskeletal pain.
Oakman, Jodi; de Wind, Astrid; van den Heuvel, Swenne G; van der Beek, Allard J
2017-10-01
Musculoskeletal pain in more than one body region is common and a barrier to sustaining employment. We aimed to examine whether work characteristics predict the development of multi-site pain (MSP), and to determine differences in work-related predictors between age groups. This study is based on 5136 employees from the Study on Transitions in Employment, Ability and Motivation (STREAM) who reported no MSP at baseline. Measures included physical, emotional, mental, and psychological job demands, social support and autonomy. Predictors of MSP were studied by logistic regression analyses. Univariate and multivariate analyses with age stratification (45-49, 50-54, 55-59, and 60-64 years) were done to explore differences between age groups. All work characteristics with the exception of autonomy were predictive of the development of MSP, with odds ratios varying from 1.21 (95% CI 1.04-1.40) for mental job demands to 1.63 (95% CI 1.43-1.86) for physical job demands. No clear pattern of age-related differences in the predictors of MSP emerged, with the exception of social support, which was predictive of MSP developing in all age groups except for the age group 60-64 years. Adverse physical and psychosocial work characteristics are associated with MSP. Organisations need to comprehensively assess work environments to ensure that all relevant workplace hazards, physical and psychosocial, are identified and then controlled for across all age groups.
Idilman, Ilkay S; Keskin, Onur; Elhan, Atilla Halil; Idilman, Ramazan; Karcaaltincaba, Musturay
2014-05-01
To determine the utility of sequential MRI-estimated proton density fat fraction (MRI-PDFF) for quantification of the longitudinal changes in liver fat content in individuals with nonalcoholic fatty liver disease (NAFLD). A total of 18 consecutive individuals (M/F: 10/8, mean age: 47.7±9.8 years) diagnosed with NAFLD, who underwent sequential PDFF calculations for the quantification of hepatic steatosis at two different time points, were included in the study. All patients underwent T1-independent volumetric multi-echo gradient-echo imaging with T2* correction and spectral fat modeling. A close correlation for quantification of hepatic steatosis between the initial MRI-PDFF and liver biopsy was observed (rs=0.758, p<0.001). The median interval between two sequential MRI-PDFF measurements was 184 days. From baseline to the end of the follow-up period, serum GGT level and homeostasis model assessment score were significantly improved (p=0.015, p=0.006, respectively), whereas BMI, serum AST, and ALT levels were slightly decreased. MRI-PDFFs were significantly improved (p=0.004). A good correlation between two sequential MRI-PDFF calculations was observed (rs=0.714, p=0.001). With linear regression analyses, only delta serum ALT levels had a significant effect on delta MRI-PDFF calculations (r2=38.6%, p=0.006). At least 5.9% improvement in MRI-PDFF is needed to achieve a normalized abnormal ALT level. The improvement of MRI-PDFF score was associated with the improvement of biochemical parameters in patients who had improvement in delta MRI-PDFF (p<0.05). MRI-PDFF can be used for the quantification of the longitudinal changes of hepatic steatosis. The changes in serum ALT levels significantly reflected changes in MRI-PDFF in patients with NAFLD.
Murray, Louis C.
2012-01-01
A study to examine the influences of climatic and anthropogenic stressors on groundwater levels, lake stages, and surface-water discharge at selected sites in northern Volusia County, Florida, was conducted in 2009 by the U.S. Geological Survey. Water-level data collected at 20 monitoring sites (17 groundwater and 3 lake sites) in the vicinity of a wetland area were analyzed with multiple linear regression to examine the relative influences of precipitation and groundwater withdrawals on changes in groundwater levels and lake stage. Analyses were conducted across varying periods of record between 1995 and 2010 and included the effects of groundwater withdrawals aggregated from municipal water-supply wells located within 12 miles of the project sites. Surface-water discharge data at the U.S. Geological Survey Tiger Bay canal site were analyzed for changes in flow between 1978 and 2001. As expected, water-level changes in monitoring wells located closer to areas of concentrated groundwater withdrawals were more highly correlated with withdrawals than were water-level changes measured in wells further removed from municipal well fields. Similarly, water-level changes in wells tapping the Upper Floridan aquifer, the source of municipal supply, were more highly correlated with groundwater withdrawals than were water-level changes in wells tapping the shallower surficial aquifer system. Water-level changes predicted by the regression models over precipitation-averaged periods of record were underestimated for observations having large positive monthly changes (generally greater than 1.0 foot). Such observations are associated with high precipitation and were identified as points in the regression analyses that produced large standardized residuals and/or observations of high influence. Thus, regression models produced by multiple linear regression analyses may have better predictive capability in wetland environments when applied to periods of average or below average precipitation conditions than during wetter than average conditions. For precipitation-averaged hydrologic conditions, water-level changes in the surficial aquifer system were statistically correlated solely with precipitation or were more highly correlated with precipitation than with groundwater withdrawals. Changes in Upper Floridan aquifer water levels and in water-surface stage (stage) at Indian and Scoggin Lakes tended to be highly correlated with both precipitation and withdrawals. The greater influence of withdrawals on stage changes, relative to changes in nearby surficial aquifer system water levels, indicates that these karstic lakes may be better connected hydraulically with the underlying Upper Floridan aquifer than is the surficial aquifer system at the other monitoring sites. At most sites, and for both aquifers, the 2-month moving average of precipitation or groundwater withdrawals included as an explanatory variable in the regression models indicates that water-level changes are not only influenced by stressor conditions across the current month, but also by those of the previous month. The relations between changes in water levels, precipitation, and groundwater withdrawals varied seasonally and in response to a period of drought. Water-level changes tended to be most highly correlated with withdrawals during the spring, when relatively large increases contributed to water-level declines, and during the fall when reduced withdrawal rates contributed to water-level recovery. Water-level changes tended to be most highly (or solely) correlated with precipitation in the winter, when withdrawals are minimal, and in the summer when precipitation is greatest. Water-level changes measured during the drought of October 2005 to June 2008 tended to be more highly correlated with groundwater withdrawals at Upper Floridan aquifer sites than at surficial aquifer system sites, results that were similar to those for precipitation-averaged conditions. Also, changes in stage at Indian and Scoggin Lakes were highly correlated with precipitation and groundwater withdrawals during the drought. Groundwater-withdrawal rates during the drought were, on average, greater than those for precipitation-averaged conditions. Accounting only for withdrawals aggregated from pumping wells located within varying radial distances of less than 12 miles of each site produced essentially the same relation between water-level changes and groundwater withdrawals as that determined for withdrawals aggregated within 12 miles of the site. Similarly, increases in withdrawals aggregated over distances of 1 to 12 miles of the sites had little effect on adjusted R-squared values. Analyses of streamflow measurements collected between 1978 and 2001 at the U.S. Geological Survey Tiger Bay canal site indicate that significant changes occurred during base-flow conditions during that period. Hypothesis and trend testing, together with analyses of flow duration, the number of zero-flow days, and double-mass curves indicate that, after 1988, when a municipal well field began production, base flow was statistically lower than the period before 1988. This decrease in base flow could not be explained by variations in precipitation between these two periods.
Aryee, Samuel; Walumbwa, Fred O; Seidu, Emmanuel Y M; Otaye, Lilian E
2012-03-01
We proposed and tested a multilevel model, underpinned by empowerment theory, that examines the processes linking high-performance work systems (HPWS) and performance outcomes at the individual and organizational levels of analyses. Data were obtained from 37 branches of 2 banking institutions in Ghana. Results of hierarchical regression analysis revealed that branch-level HPWS relates to empowerment climate. Additionally, results of hierarchical linear modeling that examined the hypothesized cross-level relationships revealed 3 salient findings. First, experienced HPWS and empowerment climate partially mediate the influence of branch-level HPWS on psychological empowerment. Second, psychological empowerment partially mediates the influence of empowerment climate and experienced HPWS on service performance. Third, service orientation moderates the psychological empowerment-service performance relationship such that the relationship is stronger for those high rather than low in service orientation. Last, ordinary least squares regression results revealed that branch-level HPWS influences branch-level market performance through cross-level and individual-level influences on service performance that emerges at the branch level as aggregated service performance.
Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan
2011-01-01
Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications. PMID:22096600
Zaritsky, Assaf; Natan, Sari; Horev, Judith; Hecht, Inbal; Wolf, Lior; Ben-Jacob, Eshel; Tsarfaty, Ilan
2011-01-01
Confocal microscopy analysis of fluorescence and morphology is becoming the standard tool in cell biology and molecular imaging. Accurate quantification algorithms are required to enhance the understanding of different biological phenomena. We present a novel approach based on image-segmentation of multi-cellular regions in bright field images demonstrating enhanced quantitative analyses and better understanding of cell motility. We present MultiCellSeg, a segmentation algorithm to separate between multi-cellular and background regions for bright field images, which is based on classification of local patches within an image: a cascade of Support Vector Machines (SVMs) is applied using basic image features. Post processing includes additional classification and graph-cut segmentation to reclassify erroneous regions and refine the segmentation. This approach leads to a parameter-free and robust algorithm. Comparison to an alternative algorithm on wound healing assay images demonstrates its superiority. The proposed approach was used to evaluate common cell migration models such as wound healing and scatter assay. It was applied to quantify the acceleration effect of Hepatocyte growth factor/scatter factor (HGF/SF) on healing rate in a time lapse confocal microscopy wound healing assay and demonstrated that the healing rate is linear in both treated and untreated cells, and that HGF/SF accelerates the healing rate by approximately two-fold. A novel fully automated, accurate, zero-parameters method to classify and score scatter-assay images was developed and demonstrated that multi-cellular texture is an excellent descriptor to measure HGF/SF-induced cell scattering. We show that exploitation of textural information from differential interference contrast (DIC) images on the multi-cellular level can prove beneficial for the analyses of wound healing and scatter assays. The proposed approach is generic and can be used alone or alongside traditional fluorescence single-cell processing to perform objective, accurate quantitative analyses for various biological applications.
Parental education predicts change in intelligence quotient after childhood epilepsy surgery.
Meekes, Joost; van Schooneveld, Monique M J; Braams, Olga B; Jennekens-Schinkel, Aag; van Rijen, Peter C; Hendriks, Marc P H; Braun, Kees P J; van Nieuwenhuizen, Onno
2015-04-01
To know whether change in the intelligence quotient (IQ) of children who undergo epilepsy surgery is associated with the educational level of their parents. Retrospective analysis of data obtained from a cohort of children who underwent epilepsy surgery between January 1996 and September 2010. We performed simple and multiple regression analyses to identify predictors associated with IQ change after surgery. In addition to parental education, six variables previously demonstrated to be associated with IQ change after surgery were included as predictors: age at surgery, duration of epilepsy, etiology, presurgical IQ, reduction of antiepileptic drugs, and seizure freedom. We used delta IQ (IQ 2 years after surgery minus IQ shortly before surgery) as the primary outcome variable, but also performed analyses with pre- and postsurgical IQ as outcome variables to support our findings. To validate the results we performed simple regression analysis with parental education as the predictor in specific subgroups. The sample for regression analysis included 118 children (60 male; median age at surgery 9.73 years). Parental education was significantly associated with delta IQ in simple regression analysis (p = 0.004), and also contributed significantly to postsurgical IQ in multiple regression analysis (p = 0.008). Additional analyses demonstrated that parental education made a unique contribution to prediction of delta IQ, that is, it could not be replaced by the illness-related variables. Subgroup analyses confirmed the association of parental education with IQ change after surgery for most groups. Children whose parents had higher education demonstrate on average a greater increase in IQ after surgery and a higher postsurgical--but not presurgical--IQ than children whose parents completed at most lower secondary education. Parental education--and perhaps other environmental variables--should be considered in the prognosis of cognitive function after childhood epilepsy surgery. Wiley Periodicals, Inc. © 2015 International League Against Epilepsy.
Sharma, Ravi K; Donekal, Sirisha; Rosen, Boaz D; Tattersall, Matthew C; Volpe, Gustavo J; Ambale-Venkatesh, Bharath; Nasir, Khurram; Wu, Colin O; Polak, Joseph F; Korcarz, Claudia E; Stein, James H; Carr, James; Watson, Karol E; Bluemke, David A; Lima, João A C
2015-04-01
The role of atherosclerosis in the progression of global left ventricular dysfunction and cardiovascular events has been well recognized. Left ventricular (LV) dyssynchrony is a measure of regional myocardial dysfunction. Our objective was to investigate the relationship of subclinical atherosclerosis with mechanical LV dyssynchrony in a population-based asymptomatic multi-ethnic cohort. Participants of the Multi-Ethnic Study of Atherosclerosis (MESA) at exam 5 were evaluated using 1.5T cardiac magnetic resonance (CMR) imaging, carotid ultrasound (n = 2062) for common carotid artery (CCA) and internal carotid artery (ICA) intima-media thickness (IMT), and cardiac computed tomography (n = 2039) for coronary artery calcium (CAC) assessment (Agatston method). Dyssynchrony indices were defined as the standard deviation of time to peak systolic circumferential strain (SD-TPS) and the difference between maximum and minimum (max-min) time to peak strain using harmonic phase imaging in 12 segments (3-slices × 4 segments). Multivariable regression analyses were performed to assess associations after adjusting for participant demographics, cardiovascular risk factors, LV mass, and ejection fraction. In multivariable analyses, SD-TPS was significantly related to measures of atherosclerosis, including CCA-IMT (8.7 ms/mm change in IMT, p = 0.020), ICA-IMT (19.2 ms/mm change in IMT, p < 0.001), carotid plaque score (1.2 ms/unit change in score, p < 0.001), and log transformed CAC+1 (0.66 ms/unit log-CAC+1, p = 0.018). These findings were consistent with other parameter of LV dyssynchrony i.e. max-min. In the MESA cohort, measures of atherosclerosis are associated with parameters of subclinical LV dyssynchrony in the absence of clinical coronary event and left-bundle-branch block. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.
Laforest, Sophie; Lorthios-Guilledroit, Agathe; Nour, Kareen; Parisien, Manon; Fournier, Michel; Ellemberg, Dave; Guay, Danielle; Desgagn�s-Cyr, Charles-�mile; Bier, Nathalie
2017-01-01
Abstract This study examined the effects on attitudes and lifestyle behavior of Jog your Mind, a multi-factorial community-based program promoting cognitive vitality among seniors with no known cognitive impairment. A quasi-experimental study was conducted. Twenty-three community organizations were assigned either to the experimental group (offering the program) or to the control group (creating a waiting list). They recruited 294 community-dwelling seniors. The aims of the study were to verify the effects of the program on attitudes and behaviors related to cognitive vitality and to explore its effects on cognitive vitality. Data was collected at baseline and after the program. Regression analyses revealed that, following their participation in the program, experimental group participants reported: (i) in terms of attitudes, having a greater feeling of control concerning their cognitive capacities, (ii) in terms of behaviors, using significantly more memory strategies and practicing more physical activity and stimulating activities than control group participants. However, the program had no significant effects on measures of cognitive vitality. This study supports the fact that a multi-factorial community-based program can have significant effects on seniors’ attitudes and lifestyle behaviors related to cognitive vitality but at short term, no effects on cognitive vitality it-self were found. PMID:28334988
Multidimensional Predictors of Fatigue among Octogenarians and Centenarians
Cho, Jinmyoung; Martin, Peter; Margrett, Jennifer; MacDonald, Maurice; Johnson, Mary Ann; Poon, Leonard W.
2012-01-01
Background Fatigue is a common and frequently observed complaint among older adults. However, knowledge about the nature and correlates of fatigue in old age is very limited. Objective: This study examined the relationship of functional indicators, psychological and situational factors and fatigue for 210 octogenarians and centenarians from the Georgia Centenarian Study. Methods Three indicators of functional capacity (self-rated health, instrumental activities of daily living, physical activities of daily living), two indicators of psychological well-being (positive and negative affect), two indicators of situational factors (social network and social support), and a multidimensional fatigue scale were used. Blocked multiple regression analyses were computed to examine significant factors related to fatigue. In addition, multi-group analysis in structural equation modeling was used to investigate residential differences (i.e., long-term care facilities vs. private homes) in the relationship between significant factors and fatigue. Results Blocked multiple regression analyses indicated that two indicators of functional capacity, self-rated health and instrumental activities of daily living, both positive and negative affect, and social support were significant predictors of fatigue among oldest-old adults. The multiple group analysis in structural equation modeling revealed a significant difference among oldest-old adults based on residential status. Conclusion The results suggest that we should not consider fatigue as merely an unpleasant physical symptom, but rather adopt a perspective that different factors such as psychosocial aspects can influence fatigue in advanced later life. PMID:22094445
Multidimensional predictors of fatigue among octogenarians and centenarians.
Cho, Jinmyoung; Martin, Peter; Margrett, Jennifer; MacDonald, Maurice; Johnson, Mary Ann; Poon, Leonard W; Jazwinski, S M; Green, R C; Gearing, M; Woodard, J L; Tenover, J S; Siegler, I C; Rott, C; Rodgers, W L; Hausman, D; Arnold, J; Davey, A
2012-01-01
Fatigue is a common and frequently observed complaint among older adults. However, knowledge about the nature and correlates of fatigue in old age is very limited. This study examined the relationship of functional indicators, psychological and situational factors and fatigue for 210 octogenarians and centenarians from the Georgia Centenarian Study. Three indicators of functional capacity (self-rated health, instrumental activities of daily living, physical activities of daily living), two indicators of psychological well-being (positive and negative affect), two indicators of situational factors (social network and social support), and a multidimensional fatigue scale were used. Blocked multiple regression analyses were computed to examine significant factors related to fatigue. In addition, multi-group analysis in structural equation modeling was used to investigate residential differences (i.e., long-term care facilities vs. private homes) in the relationship between significant factors and fatigue. Blocked multiple regression analyses indicated that two indicators of functional capacity, self-rated health and instrumental activities of daily living, both positive and negative affect, and social support were significant predictors of fatigue among oldest-old adults. The multiple group analysis in structural equation modeling revealed a significant difference among oldest-old adults based on residential status. The results suggest that we should not consider fatigue as merely an unpleasant physical symptom, but rather adopt a perspective that different factors such as psychosocial aspects can influence fatigue in advanced later life. Copyright © 2011 S. Karger AG, Basel.
Jungheim, Emily S; Macones, George A; Odem, Randall R; Patterson, Bruce W; Moley, Kelle H
2011-10-01
To analyze relationships between serum free fatty acid (FFA) concentrations and pregnancy. Prospective cohort. University hospital. Ninety-one women undergoing IVF. Serum was analyzed for total and specific serum FFAs, including myristic, palmitic, stearic, oleic, linoleic, and α-linolenic acids. Univariate analyses were used to identify specific FFAs and other factors associated with pregnancy after IVF. Logistic regression was performed modeling relationships between identified factors and chance of pregnancy. In unadjusted analyses, women with elevated serum α-linolenic acid (ALA) levels (highest quartile) demonstrated a decreased chance of pregnancy compared with women with the lowest levels (odds ratio 0.24, 95% confidence interval 0.052-0.792). No associations between other FFAs and pregnancy were identified. In a multivariable regression model, associations between elevated serum ALA levels and decreased chance of pregnancy remained after adjusting for patient age, body mass index, and history of endometriosis or previous live birth (adjusted odds ratio 0.139, 95% confidence interval 0.028-0.686). Elevated serum ALA levels are associated with decreased chance of pregnancy in women undergoing IVF. Further work is needed to determine whether ALA is involved in early reproductive processes and whether the relationship between ALA and pregnancy is associated with excess ALA intake, impaired ALA metabolism, or both. Copyright © 2011 American Society for Reproductive Medicine. Published by Elsevier Inc. All rights reserved.
Tobón-Arroyave, Sergio I; Isaza-Guzmán, Diana M; Restrepo-Cadavid, Eliana M; Zapata-Molina, Sandra M; Martínez-Pabón, María C
2012-12-01
To determine the variations in salivary concentrations of sRANKL, osteoprotegerin (OPG) and its ratio, regarding the periodontal status. Ninety-seven chronic periodontitis (CP) subjects and 43 healthy controls were selected. Periodontal status was assessed based on full-mouth clinical periodontal measurements. sRANKL and OPG salivary levels were analysed by ELISA. The association between these analytes and its ratio with CP was analysed individually and adjusted for confounding using a binary logistic regression model. sRANKL and sRANKL/OPG ratio were increased, whereas OPG was decreased in CP compared with healthy controls subjects. Although univariate analysis revealed a positive association of sRANKL salivary levels ≥6 pg/ml, OPG salivary levels ≤131 pg/ml and sRANKL/OPG ratio ≥0.062 with CP, after logistic regression analysis only the latter parameter was strongly and independently associated with disease status. Confounding and interaction effects of ageing and smoking habit on sRANKL and OPG levels could be noted. Although salivary concentrations of sRANKL, OPG and its ratio may act as indicators of the amount/extent of periodontal breakdown, the mutual confounding and synergistic biological interactive effects related to ageing and smoking habit of the susceptible host may also promote the tissue destruction in CP. © 2012 John Wiley & Sons A/S.
Predictive models of energy consumption in multi-family housing in College Station, Texas
NASA Astrophysics Data System (ADS)
Ali, Hikmat Hummad
Patterns of energy consumption in apartment buildings are different than those in single-family houses. Apartment buildings have different physical characteristics, and their inhabitants have different demographic attributes. This study develops models that predict energy usage in apartment buildings in College Station. This is accomplished by analyzing and identifying the predictive variables that affect energy usage, studying the consumption patterns, and creating formulas based on combinations of these variables. According to the hypotheses and the specific research context, a cross-sectional design strategy is adopted. This choice implies analyses across variations within a sample of fourplex apartments in College Station. The data available for analysis include the monthly billing data along with the physical characteristics of the building, climate data for College Station, and occupant demographic characteristics. A simple random sampling procedure is adopted. The sample size of 176 apartments is drawn from the population in such a way that every possible sample has the same chance of being selected. Statistical methods used to interpret the data include univariate analysis (mean, standard deviation, range, and distribution of data), correlation analysis, regression analysis, and ANOVA (analyses of variance). The results show there are significant differences in cooling efficiency and actual energy consumption among different building types, but there are no significant differences in heating consumption. There are no significant differences in actual energy consumption between student and non-student groups or among ethnic groups. The findings indicate that there are significant differences in actual energy consumption among marital status groups and educational level groups. The multiple regression procedures show there is a significant relationship between normalized annual consumption and the combined variables of floor area, marital status, dead band, construction material, summer thermostat setting, heating, slope, and base load, as well as a relationship between cooling slope and the combined variables of share wall, floor level, summer thermostat setting, external wall, and American household. In addition, there is a significant relationship between heating slope and the combined variables of winter thermostat setting, market value, student, and rent. The results also indicate there is a relationship between base load and the combined variables of floor area, market value, age of the building, marital status, student, and summer thermostat setting.
Barberio, Amanda M; Hosein, F Shaun; Quiñonez, Carlos; McLaren, Lindsay
2017-01-01
Background There are concerns that altered thyroid functioning could be the result of ingesting too much fluoride. Community water fluoridation (CWF) is an important source of fluoride exposure. Our objectives were to examine the association between fluoride exposure and (1) diagnosis of a thyroid condition and (2) indicators of thyroid functioning among a national population-based sample of Canadians. Methods We analysed data from Cycles 2 and 3 of the Canadian Health Measures Survey (CHMS). Logistic regression was used to assess associations between fluoride from urine and tap water samples and the diagnosis of a thyroid condition. Multinomial logistic regression was used to examine the relationship between fluoride exposure and thyroid-stimulating hormone (TSH) level (low/normal/high). Other available variables permitted additional exploratory analyses among the subset of participants for whom we could discern some fluoride exposure from drinking water and/or dental products. Results There was no evidence of a relationship between fluoride exposure (from urine and tap water) and the diagnosis of a thyroid condition. There was no statistically significant association between fluoride exposure and abnormal (low or high) TSH levels relative to normal TSH levels. Rerunning the models with the sample constrained to the subset of participants for whom we could discern some source(s) of fluoride exposure from drinking water and/or dental products revealed no significant associations. Conclusion These analyses suggest that, at the population level, fluoride exposure is not associated with impaired thyroid functioning in a time and place where multiple sources of fluoride exposure, including CWF, exist. PMID:28839078
NASA Astrophysics Data System (ADS)
Pan, Yanqiao; Huang, YongAn; Guo, Lei; Ding, Yajiang; Yin, Zhouping
2015-04-01
It is critical and challenging to achieve the individual jetting ability and high consistency in multi-nozzle electrohydrodynamic jet printing (E-jet printing). We proposed multi-level voltage method (MVM) to implement the addressable E-jet printing using multiple parallel nozzles with high consistency. The fabricated multi-nozzle printhead for MVM consists of three parts: PMMA holder, stainless steel capillaries (27G, outer diameter 400 μm) and FR-4 extractor layer. The key of MVM is to control the maximum meniscus electric field on each nozzle. The individual jetting control can be implemented when the rings under the jetting nozzles are 0 kV and the other rings are 0.5 kV. The onset electric field for each nozzle is ˜3.4 kV/mm by numerical simulation. Furthermore, a series of printing experiments are performed to show the advantage of MVM in printing consistency than the "one-voltage method" and "improved E-jet method", by combination with finite element analyses. The good dimension consistency (274μm, 276μm, 280μm) and position consistency of the droplet array on the hydrophobic Si substrate verified the enhancements. It shows that MVM is an effective technique to implement the addressable E-jet printing with multiple parallel nozzles in high consistency.
On the equivalence of case-crossover and time series methods in environmental epidemiology.
Lu, Yun; Zeger, Scott L
2007-04-01
The case-crossover design was introduced in epidemiology 15 years ago as a method for studying the effects of a risk factor on a health event using only cases. The idea is to compare a case's exposure immediately prior to or during the case-defining event with that same person's exposure at otherwise similar "reference" times. An alternative approach to the analysis of daily exposure and case-only data is time series analysis. Here, log-linear regression models express the expected total number of events on each day as a function of the exposure level and potential confounding variables. In time series analyses of air pollution, smooth functions of time and weather are the main confounders. Time series and case-crossover methods are often viewed as competing methods. In this paper, we show that case-crossover using conditional logistic regression is a special case of time series analysis when there is a common exposure such as in air pollution studies. This equivalence provides computational convenience for case-crossover analyses and a better understanding of time series models. Time series log-linear regression accounts for overdispersion of the Poisson variance, while case-crossover analyses typically do not. This equivalence also permits model checking for case-crossover data using standard log-linear model diagnostics.
Land Use, Residential Density, and Walking
Rodríguez, Daniel A.; Evenson, Kelly R.; Diez Roux, Ana V.; Brines, Shannon J.
2009-01-01
Background The neighborhood environment may play a role in encouraging sedentary patterns, especially for middle-aged and older adults. Purpose Associations between walking and neighborhood population density, retail availability, and land use distribution were examined using data from a cohort of adults aged 45 to 84 years old. Methods Data from a multi-ethnic sample of 5529 adult residents of Baltimore MD, Chicago IL, Forsyth County NC, Los Angeles CA, New York NY, and St. Paul MN, enrolled in the Multi-Ethnic Study of Atherosclerosis in 2000–2002 were linked to secondary land use and population data. Participant reports of access to destinations and stores and objective measures of the percentage of land area in parcels devoted to retail land uses, the population divided by land area in parcels, and the mixture of uses for areas within 200m of each participant's residence were examined. Multinomial logistic regression was used to investigate associations of self-reported and objective neighborhood characteristics with walking. All analyses were conducted in 2008 and 2009. Results After adjustment for individual-level characteristics and neighborhood connectivity, higher density, greater land area devoted to retail uses, and self-reported measures of proximity of destinations and ease of walking to places were each related to walking. In models including all land use measures, population density was positively associated with walking to places and with walking for exercise for more than 90 min/wk both relative to no walking. Availability of retail was associated with walking to places relative to not walking, having a more proportional mix of land uses was associated with walking for exercise for more than 90 min/wk, while self-reported ease of access to places was related to higher levels of exercise walking both relative to not walking. Conclusions Residential density and the presence of retail uses are related to various walking behaviors. Efforts to increase walking may benefit from attention to the intensity and type of land development. PMID:19840694
Diep, Pham Bich; Tan, Frans E. S.; Knibbe, Ronald A.; De Vries, Nanne
2016-01-01
Background: This study used multi-level analysis to estimate which type of factor explains most of the variance in alcohol consumption of Vietnamese students. Methods: Data were collected among 6011 students attending 12 universities/faculties in four provinces in Vietnam. The three most recent drinking occasions were investigated per student, resulting in 12,795 drinking occasions among 4265 drinkers. Students reported on 10 aspects of the drinking context per drinking occasion. A multi-level mixed-effects linear regression model was constructed in which aspects of drinking context composed the first level; the age of students and four drinking motives comprised the second level. The dependent variable was the number of drinks. Results: Of the aspects of context, drinking duration had the strongest association with alcohol consumption while, at the individual level, coping motive had the strongest association. The drinking context characteristics explained more variance than the individual characteristics in alcohol intake per occasion. Conclusions: These findings suggest that, among students in Vietnam, the drinking context explains a larger proportion of the variance in alcohol consumption than the drinking motives. Therefore, measures that reduce the availability of alcohol in specific drinking situations are an essential part of an effective prevention policy. PMID:27420089
Independent Prognostic Factors for Acute Organophosphorus Pesticide Poisoning.
Tang, Weidong; Ruan, Feng; Chen, Qi; Chen, Suping; Shao, Xuebo; Gao, Jianbo; Zhang, Mao
2016-07-01
Acute organophosphorus pesticide poisoning (AOPP) is becoming a significant problem and a potential cause of human mortality because of the abuse of organophosphate compounds. This study aims to determine the independent prognostic factors of AOPP by using multivariate logistic regression analysis. The clinical data for 71 subjects with AOPP admitted to our hospital were retrospectively analyzed. This information included the Acute Physiology and Chronic Health Evaluation II (APACHE II) scores, 6-h post-admission blood lactate levels, post-admission 6-h lactate clearance rates, admission blood cholinesterase levels, 6-h post-admission blood cholinesterase levels, cholinesterase activity, blood pH, and other factors. Univariate analysis and multivariate logistic regression analyses were conducted to identify all prognostic factors and independent prognostic factors, respectively. A receiver operating characteristic curve was plotted to analyze the testing power of independent prognostic factors. Twelve of 71 subjects died. Admission blood lactate levels, 6-h post-admission blood lactate levels, post-admission 6-h lactate clearance rates, blood pH, and APACHE II scores were identified as prognostic factors for AOPP according to the univariate analysis, whereas only 6-h post-admission blood lactate levels, post-admission 6-h lactate clearance rates, and blood pH were independent prognostic factors identified by multivariate logistic regression analysis. The receiver operating characteristic analysis suggested that post-admission 6-h lactate clearance rates were of moderate diagnostic value. High 6-h post-admission blood lactate levels, low blood pH, and low post-admission 6-h lactate clearance rates were independent prognostic factors identified by multivariate logistic regression analysis. Copyright © 2016 by Daedalus Enterprises.
Allelic variation contributes to bacterial host specificity
Yue, Min; Han, Xiangan; Masi, Leon De; ...
2015-10-30
Understanding the molecular parameters that regulate cross-species transmission and host adaptation of potential pathogens is crucial to control emerging infectious disease. Although microbial pathotype diversity is conventionally associated with gene gain or loss, the role of pathoadaptive nonsynonymous single-nucleotide polymorphisms (nsSNPs) has not been systematically evaluated. Here, our genome-wide analysis of core genes within Salmonella enterica serovar Typhimurium genomes reveals a high degree of allelic variation in surface-exposed molecules, including adhesins that promote host colonization. Subsequent multinomial logistic regression, MultiPhen and Random Forest analyses of known/suspected adhesins from 580 independent Typhimurium isolates identifies distinct host-specific nsSNP signatures. Moreover, population andmore » functional analyses of host-associated nsSNPs for FimH, the type 1 fimbrial adhesin, highlights the role of key allelic residues in host-specific adherence in vitro. In conclusion, together, our data provide the first concrete evidence that functional differences between allelic variants of bacterial proteins likely contribute to pathoadaption to diverse hosts.« less
NASA Astrophysics Data System (ADS)
Subramanian, M.; Vanangamudi, G.; Thirunarayanan, G.
2013-06-01
A series of 2,5-dimethyl-3-furyl chalcones [2E-1-(2,5-dimethyl-3-furyl)-3-(substituted phenyl)-2-propen-1-ones] have been synthesized by Hydrotalcite catalyzed aldol condensation between 3-acetyl-2,5-dimethylfuron and substituted benzaldehydes. Yields of chalcones are more than 80%. These chalcones were characterized by their physical constants and spectral data. The group frequencies of infrared ν(cm-1) of CO s-cis and s-trans, CH in-plane and out of plane, CHdbnd CH out of plane, lbond2 Cdbnd Crbond2 out of plane modes, NMR chemical shifts δ(ppm) of Hα, Hβ, CO, Cα and Cβ of these chalcones were correlated with Hammett substituent constants, F and R parameters using single and multi-regression analyses. From the results of statistical analyses, the effects of substituents on the group frequencies are explained. Antibacterial, antifungal and insect antifeedant activities of these chalcones have been studied.
Parent-Child Agreement on Parent-to-Child Maltreatment.
Compier-de Block, Laura H C G; Alink, Lenneke R A; Linting, Mariëlle; van den Berg, Lisa J M; Elzinga, Bernet M; Voorthuis, Alexandra; Tollenaar, Marieke S; Bakermans-Kranenburg, Marian J
2017-01-01
Parent-child agreement on child maltreatment was examined in a multigenerational study. Questionnaires on perpetrated and experienced child maltreatment were completed by 138 parent-child pairs. Multi-level analyses were conducted to explore whether parents and children agreed about levels of parent-to-child maltreatment (convergence), and to examine whether parents and children reported equal levels of child maltreatment (absolute differences). Direct and moderating effects of age and gender were examined as potential factors explaining differences between parent and child report. The associations between parent- and child-reported maltreatment were significant for all subtypes, but the strength of the associations was low to moderate. Moreover, children reported more parent-to-child neglect than parents did. Older participants reported more experienced maltreatment than younger participants, without evidence for differences in actual exposure. These findings support the value of multi-informant assessment of child maltreatment to improve accuracy, but also reveal the divergent perspectives of parents and children on child maltreatment.
An overview of longitudinal data analysis methods for neurological research.
Locascio, Joseph J; Atri, Alireza
2011-01-01
The purpose of this article is to provide a concise, broad and readily accessible overview of longitudinal data analysis methods, aimed to be a practical guide for clinical investigators in neurology. In general, we advise that older, traditional methods, including (1) simple regression of the dependent variable on a time measure, (2) analyzing a single summary subject level number that indexes changes for each subject and (3) a general linear model approach with a fixed-subject effect, should be reserved for quick, simple or preliminary analyses. We advocate the general use of mixed-random and fixed-effect regression models for analyses of most longitudinal clinical studies. Under restrictive situations or to provide validation, we recommend: (1) repeated-measure analysis of covariance (ANCOVA), (2) ANCOVA for two time points, (3) generalized estimating equations and (4) latent growth curve/structural equation models.
Parker, Kristin M; Wilson, Mark G; Vandenberg, Robert J; DeJoy, David M; Orpinas, Pamela
2009-10-01
This study tests the hypothesis that employees with comorbid physical health conditions and mental health symptoms are less productive than other employees. Self-reported health status and productivity measures were collected from 1723 employees of a national retail organization. chi2, analysis of variance, and linear contrast analyses were conducted to evaluate whether health status groups differed on productivity measures. Multivariate linear regression and multinomial logistic regression analyses were conducted to analyze how predictive health status was of productivity. Those with comorbidities were significantly less productive on all productivity measures compared with all other health status groups and those with only physical health conditions or mental health symptoms. Health status also significantly predicted levels of employee productivity. These findings provide evidence for the relationship between health statuses and productivity, which has potential programmatic implications.
Faggion, Clovis Mariano; Wu, Yun-Chun; Scheidgen, Moritz; Tu, Yu-Kang
2015-01-01
Background Risk of bias (ROB) may threaten the internal validity of a clinical trial by distorting the magnitude of treatment effect estimates, although some conflicting information on this assumption exists. Objective The objective of this study was evaluate the effect of ROB on the magnitude of treatment effect estimates in randomized controlled trials (RCTs) in periodontology and implant dentistry. Methods A search for Cochrane systematic reviews (SRs), including meta-analyses of RCTs published in periodontology and implant dentistry fields, was performed in the Cochrane Library in September 2014. Random-effect meta-analyses were performed by grouping RCTs with different levels of ROBs in three domains (sequence generation, allocation concealment, and blinding of outcome assessment). To increase power and precision, only SRs with meta-analyses including at least 10 RCTs were included. Meta-regression was performed to investigate the association between ROB characteristics and the magnitudes of intervention effects in the meta-analyses. Results Of the 24 initially screened SRs, 21 SRs were excluded because they did not include at least 10 RCTs in the meta-analyses. Three SRs (two from periodontology field) generated information for conducting 27 meta-analyses. Meta-regression did not reveal significant differences in the relationship of the ROB level with the size of treatment effect estimates, although a trend for inflated estimates was observed in domains with unclear ROBs. Conclusion In this sample of RCTs, high and (mainly) unclear risks of selection and detection biases did not seem to influence the size of treatment effect estimates, although several confounders might have influenced the strength of the association. PMID:26422698
Li, Li; Nguyen, Kim-Huong; Comans, Tracy; Scuffham, Paul
2018-04-01
Several utility-based instruments have been applied in cost-utility analysis to assess health state values for people with dementia. Nevertheless, concerns and uncertainty regarding their performance for people with dementia have been raised. To assess the performance of available utility-based instruments for people with dementia by comparing their psychometric properties and to explore factors that cause variations in the reported health state values generated from those instruments by conducting meta-regression analyses. A literature search was conducted and psychometric properties were synthesized to demonstrate the overall performance of each instrument. When available, health state values and variables such as the type of instrument and cognitive impairment levels were extracted from each article. A meta-regression analysis was undertaken and available covariates were included in the models. A total of 64 studies providing preference-based values were identified and included. The EuroQol five-dimension questionnaire demonstrated the best combination of feasibility, reliability, and validity. Meta-regression analyses suggested that significant differences exist between instruments, type of respondents, and mode of administration and the variations in estimated utility values had influences on incremental quality-adjusted life-year calculation. This review finds that the EuroQol five-dimension questionnaire is the most valid utility-based instrument for people with dementia, but should be replaced by others under certain circumstances. Although no utility estimates were reported in the article, the meta-regression analyses that examined variations in utility estimates produced by different instruments impact on cost-utility analysis, potentially altering the decision-making process in some circumstances. Copyright © 2018 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.
Matsumoto, Kazumasa; Novara, Giacomo; Gupta, Amit; Margulis, Vitaly; Walton, Thomas J; Roscigno, Marco; Ng, Casey; Kikuchi, Eiji; Zigeuner, Richard; Kassouf, Wassim; Fritsche, Hans-Martin; Ficarra, Vincenzo; Martignoni, Guido; Tritschler, Stefan; Rodriguez, Joaquin Carballido; Seitz, Christian; Weizer, Alon; Remzi, Mesut; Raman, Jay D; Bolenz, Christian; Bensalah, Karim; Koppie, Theresa M; Karakiewicz, Pierre I; Wood, Christopher G; Montorsi, Francesco; Iwamura, Masatsugu; Shariat, Shahrokh F
2011-10-01
•To assess the impact of differences in ethnicity on clinico-pathological characteristics and outcomes of patients with upper urinary tract urothelial carcinoma (UTUC) in a large multi-center series of patients treated with radical nephroureterectomy (RNU). •We retrospectively collected the data of 2163 patients treated with RNU at 20 academic centres in America, Asia, and Europe. •Univariable and multivariable Cox regression models addressed recurrence-free survival (RFS) and cancer-specific survival (CSS). •In all, 1794 (83%) patients were Caucasian and 369 (17%) were Japanese. All the main clinical and pathological features were significantly different between the two ethnicities. •The median follow-up of the whole cohort was 36 months. At last follow-up, 554 patients (26%) developed disease recurrence and 461 (21%) were dead from UTUC. •The 5-year RFS and CSS estimates were 71.5% and 74.2%, respectively, for Caucasian patients compared with 68.8% and 75.4%, respectively, for Japanese patients. •On univariable Cox regression analyses, ethnicity was not significantly associated with either RFS (P= 0.231) or CSS (P= 0.752). •On multivariable Cox regression analyses that adjusted for the effects of age, gender, surgical type, T stage, grade, tumour architecture, presence of concomitant carcinoma in situ, lymphovascular invasion, tumour necrosis, and lymph node status, ethnicity was not associated with either RFS (hazard ratio [HR] 1.1; P= 0.447) or CSS (HR 1.0; P= 0.908). •There were major differences in the clinico-pathological characteristics of Caucasian and Japanese patients. •However, RFS and CSS probabilities were not affected by ethnicity and race was not an independent predictor of either recurrence or cancer-related death. © 2011 THE AUTHORS; BJU INTERNATIONAL © 2011 BJU INTERNATIONAL.
A bioavailable strontium isoscape for Western Europe: A machine learning approach
von Holstein, Isabella C. C.; Laffoon, Jason E.; Willmes, Malte; Liu, Xiao-Ming; Davies, Gareth R.
2018-01-01
Strontium isotope ratios (87Sr/86Sr) are gaining considerable interest as a geolocation tool and are now widely applied in archaeology, ecology, and forensic research. However, their application for provenance requires the development of baseline models predicting surficial 87Sr/86Sr variations (“isoscapes”). A variety of empirically-based and process-based models have been proposed to build terrestrial 87Sr/86Sr isoscapes but, in their current forms, those models are not mature enough to be integrated with continuous-probability surface models used in geographic assignment. In this study, we aim to overcome those limitations and to predict 87Sr/86Sr variations across Western Europe by combining process-based models and a series of remote-sensing geospatial products into a regression framework. We find that random forest regression significantly outperforms other commonly used regression and interpolation methods, and efficiently predicts the multi-scale patterning of 87Sr/86Sr variations by accounting for geological, geomorphological and atmospheric controls. Random forest regression also provides an easily interpretable and flexible framework to integrate different types of environmental auxiliary variables required to model the multi-scale patterning of 87Sr/86Sr variability. The method is transferable to different scales and resolutions and can be applied to the large collection of geospatial data available at local and global levels. The isoscape generated in this study provides the most accurate 87Sr/86Sr predictions in bioavailable strontium for Western Europe (R2 = 0.58 and RMSE = 0.0023) to date, as well as a conservative estimate of spatial uncertainty by applying quantile regression forest. We anticipate that the method presented in this study combined with the growing numbers of bioavailable 87Sr/86Sr data and satellite geospatial products will extend the applicability of the 87Sr/86Sr geo-profiling tool in provenance applications. PMID:29847595
ERIC Educational Resources Information Center
Reeve, Charlie L.; Basalik, Debra
2011-01-01
The current study examines the degree to which state intellectual capital, state religiosity and reproductive health form a meaningful nexus of ecological relations. Though the specific magnitude of effects vary across outcomes, results from hierarchical regression analyses were consistent with the hypothesized path model indicating that a state's…
Determinants of Student Attitudes toward Team Exams
ERIC Educational Resources Information Center
Reinig, Bruce A.; Horowitz, Ira; Whittenburg, Gene
2014-01-01
We examine how student attitudes toward their group, learning method, and perceived development of professional skills are initially shaped and subsequently evolve through multiple uses of team exams. Using a Tobit regression model to analyse a sequence of 10 team quizzes given in a graduate-level tax accounting course, we show that there is an…
Vocabulary Is Important for Some, but Not All Reading Skills
ERIC Educational Resources Information Center
Ricketts, Jessie; Nation, Kate; Bishop, Dorothy V. M.
2007-01-01
Although there is evidence for a close link between the development of oral vocabulary and reading comprehension, less clear is whether oral vocabulary skills relate to the development of word-level reading skills. This study investigated vocabulary and literacy in 81 children aged 8 to 10 years. In regression analyses, vocabulary accounted for…
Reading Cooperatively or Independently? Study on ELL Student Reading Development
ERIC Educational Resources Information Center
Liu, Siping; Wang, Jian
2015-01-01
This study examines the effectiveness of cooperative reading teaching activities and independent reading activities for English language learner (ELL) students at 4th grade level. Based on simple linear regression and correlational analyses of data collected from two large data bases, PIRLS and NAEP, the study found that cooperative reading…
What Is the Relationship between Teacher Quality and Student Achievement? An Exploratory Study
ERIC Educational Resources Information Center
Stronge, James H.; Ward, Thomas J.; Tucker, Pamela D.; Hindman, Jennifer L.
2007-01-01
The major purpose of the study was to examine what constitutes effective teaching as defined by measured increases in student learning with a focus on the instructional behaviors and practices. Ordinary least squares (OLS) regression analyses and hierarchical linear modeling (HLM) were used to identify teacher effectiveness levels while…
Predictors of Parenting and Infant Outcomes for Impoverished Adolescent Parents
ERIC Educational Resources Information Center
Whitson, Melissa L.; Martinez, Andrew; Ayala, Carmen; Kaufman, Joy S.
2011-01-01
Adolescent mothers and their children are at risk for a myriad of negative outcomes. This study examined risk and protective factors and their impact on a sample (N = 172) of impoverished adolescent mothers. Multiple regression analyses revealed that depressed adolescent mothers report higher levels of parenting stress and that their children are…
The Impact of Teasing and Bullying on Schoolwide Academic Performance
ERIC Educational Resources Information Center
Lacey, Anna; Cornell, Dewey
2013-01-01
Hierarchical regression analyses conducted at the school level found that the perceived prevalence of teasing and bullying was predictive of schoolwide passing rates on state-mandated achievement testing used to meet No Child Left Behind requirements. These findings could not be attributed to the proportion of minority students in the school,…
Fossati, Andrea; Somma, Antonella; Borroni, Serena; Maffei, Cesare; Markon, Kristian E; Krueger, Robert F
2016-02-01
In order to evaluate if measures of DSM-5 Alternative PD Model domains predicted interview-based scores of general personality pathology when compared to self-report measures of DSM-IV Axis II/DSM-5 Section II PD criteria, 300 Italian community adults were administered the Iowa Personality Disorder Screen (IPDS) interview, the Personality Inventory for DSM-5 (PID-5), and the Personality Diagnostic Questionnaire-4+ (PDQ-4+). Multiple regression analyses showed that the five PID-5 domain scales collectively explained an adequate rate of the variance of the IPDS interview total score. This result was slightly lower than the amount of variance in the IPDS total score explained by the 10 PDQ-4+ scales. The PID-5 traits scales performed better than the PDQ-4+, although the difference was marginal. Hierarchical regression analyses revealed that the PID-5 domain and trait scales provided a moderate, but significant increase in the prediction of the general level of personality pathology above and beyond the PDQ-4+ scales.
Family conflict and depression in HIV-negative heterosexuals: the role of methamphetamine use.
Semple, Shirley J; Strathdee, Steffanie A; Zians, Jim; Patterson, Thomas L
2009-06-01
Previous research has reported elevated levels of depressive symptoms among methamphetamine users, but little attention has been paid to possible links between family environment and psychological distress. This study examined relationships between family conflict, substance use, and depressive symptoms in a sample of 104 heterosexual methamphetamine users in San Diego, California. Eighty-nine percent of the sample reported conflict with a family member in the past year. Conflict was reported most often with parents and siblings. Sources of conflict included drug use, lifestyle issues, interpersonal and communication issues, and concern for other family members. In regression analyses, being female, being a polydrug user, and facing social and legal stressors were associated with higher levels of family conflict. Multiple regression analyses also revealed a positive association between family conflict and depressive symptoms. Contrary to expectation, methamphetamine dose did not moderate the relationship between family conflict and depressive symptoms. Reducing family conflict may be an important first step toward ameliorating depressive symptoms and creating more supportive environments for methamphetamine users who are in urgent need of effective interventions. Copyright (c) 2009 APA, all rights reserved.
Demand analysis of flood insurance by using logistic regression model and genetic algorithm
NASA Astrophysics Data System (ADS)
Sidi, P.; Mamat, M. B.; Sukono; Supian, S.; Putra, A. S.
2018-03-01
Citarum River floods in the area of South Bandung Indonesia, often resulting damage to some buildings belonging to the people living in the vicinity. One effort to alleviate the risk of building damage is to have flood insurance. The main obstacle is not all people in the Citarum basin decide to buy flood insurance. In this paper, we intend to analyse the decision to buy flood insurance. It is assumed that there are eight variables that influence the decision of purchasing flood assurance, include: income level, education level, house distance with river, building election with road, flood frequency experience, flood prediction, perception on insurance company, and perception towards government effort in handling flood. The analysis was done by using logistic regression model, and to estimate model parameters, it is done with genetic algorithm. The results of the analysis shows that eight variables analysed significantly influence the demand of flood insurance. These results are expected to be considered for insurance companies, to influence the decision of the community to be willing to buy flood insurance.
Family conflict and depression in HIV-negative heterosexuals: The role of methamphetamine use
Semple, Shirley J.; Strathdee, Steffanie A.; Zians, Jim; Patterson, Thomas L.
2009-01-01
Previous research has reported elevated levels of depressive symptoms among methamphetamine users, but little attention has been paid to possible links between family environment and psychological distress. This study examined relationships between family conflict, substance use, and depressive symptoms in a sample of 104 heterosexual methamphetamine users in San Diego, CA. Eighty-nine percent of the sample reported conflict with a family member in the past year. Conflict was reported most often with parents and siblings. Sources of conflict included drug use, lifestyle issues, interpersonal and communication issues, and concern for other family members. In regression analyses, being female, being a polydrug user, and facing social and legal stressors were associated with higher levels of family conflict. Multiple regression analyses also revealed a positive association between family conflict and depressive symptoms. Contrary to expectation, methamphetamine dose did not moderate the relationship between family conflict and depressive symptoms. Reducing family conflict may be an important first step toward ameliorating depressive symptoms and creating more supportive environments for methamphetamine users who are in urgent need of effective interventions. PMID:19586151
Hanney, Steve; Greenhalgh, Trisha; Blatch-Jones, Amanda; Glover, Matthew; Raftery, James
2017-03-28
We sought to analyse the impacts found, and the methods used, in a series of assessments of programmes and portfolios of health research consisting of multiple projects. We analysed a sample of 36 impact studies of multi-project research programmes, selected from a wider sample of impact studies included in two narrative systematic reviews published in 2007 and 2016. We included impact studies in which the individual projects in a programme had been assessed for wider impact, especially on policy or practice, and where findings had been described in such a way that allowed them to be collated and compared. Included programmes were highly diverse in terms of location (11 different countries plus two multi-country ones), number of component projects (8 to 178), nature of the programme, research field, mode of funding, time between completion and impact assessment, methods used to assess impact, and level of impact identified. Thirty-one studies reported on policy impact, 17 on clinician behaviour or informing clinical practice, three on a combined category such as policy and clinician impact, and 12 on wider elements of impact (health gain, patient benefit, improved care or other benefits to the healthcare system). In those multi-programme projects that assessed the respective categories, the percentage of projects that reported some impact was policy 35% (range 5-100%), practice 32% (10-69%), combined category 64% (60-67%), and health gain/health services 27% (6-48%). Variations in levels of impact achieved partly reflected differences in the types of programme, levels of collaboration with users, and methods and timing of impact assessment. Most commonly, principal investigators were surveyed; some studies involved desk research and some interviews with investigators and/or stakeholders. Most studies used a conceptual framework such as the Payback Framework. One study attempted to assess the monetary value of a research programme's health gain. The widespread impact reported for some multi-project programmes, including needs-led and collaborative ones, could potentially be used to promote further research funding. Moves towards greater standardisation of assessment methods could address existing inconsistencies and better inform strategic decisions about research investment; however, unresolved issues about such moves remain.
Hansen, Karina E; Kesmodel, Ulrik S; Baldursson, Einar B; Schultz, Rikke; Forman, Axel
2013-07-01
Little is known about the implications of endometriosis on women's work life. This study aimed at examining the relation between endometriosis-related symptoms and work ability in employed women with endometriosis. In a cohort study, 610 patients with diagnosed endometriosis and 751 reference women completed an electronic survey based on the Endometriosis Health Profile 30-questionnaire and the Work Ability Index (short form). Percentages were reported for all data. Binary and multivariate logistic regression analyses were used to assess risk factors for low work ability. The level of statistical significance was set at p<0.025 in all analyses. In binary analyses a diagnosis of endometriosis was associated with more sick days, work disturbances due to symptoms, lower work ability and a wide number of other implications on work life in employed women. Moreover, a higher pain level and degree of symptoms were associated with low work ability. Full regression analysis indicated that tiredness, frequent pain, a higher daily pain level, a higher number of sick days and feeling depressed at work were associated with low work ability. A long delay from symptom onset to diagnosis was associated with low work ability. These data indicate a severe impact of endometriosis on the work ability of employed women with endometriosis and add to the evidence that this disease represents a significant socio-economic burden. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.
Coherent Power Analysis in Multi-Level Studies Using Design Parameters from Surveys
ERIC Educational Resources Information Center
Rhoads, Christopher
2016-01-01
Current practice for conducting power analyses in hierarchical trials using survey based ICC and effect size estimates may be misestimating power because ICCs are not being adjusted to account for treatment effect heterogeneity. Results presented in Table 1 show that the necessary adjustments can be quite large or quite small. Furthermore, power…
Effects of Inequality, Family and School on Mathematics Achievement: Country and Student Differences
ERIC Educational Resources Information Center
Chiu, Ming Ming
2010-01-01
Inequality, family and school characteristics were linked to student achievement as shown by multi-level analyses of 107,975 15 year olds' mathematics tests and questionnaires in 41 countries. Equal distribution of country and school resources were linked to higher mathematics scores. Students scored higher in families or schools with more…
The Industrial Sectors Integrated Solutions (ISIS) model for the pulp and paper sector is currently under development at the U.S. Environmental Protection Agency (EPA), and can be utilized to facilitate multi-pollutant sector-based analyses that are performed in conjunction with ...
ERIC Educational Resources Information Center
Linde, Ann C.; Toomey, Traci L.; Wolfson, Julian; Lenk, Kathleen M.; Jones-Webb, Rhonda; Erickson, Darin J.
2016-01-01
We explored potential associations between the strength of state Responsible Beverage Service (RBS) laws and self-reported binge drinking and alcohol-impaired driving in the U.S. A multi-level logistic mixed-effects model was used, adjusting for potential confounders. Analyses were conducted on the overall BRFSS sample and drinkers only. Seven…
Rural-Urban Analyses of Health-Related Quality of Life among People with Multiple Sclerosis
ERIC Educational Resources Information Center
Buchanan, Robert J.; Zhu, Li; Schiffer, Randolph; Radin, Dagmar; James, Wesley
2008-01-01
Context: Health-related quality of life (HRQOL) is a multi-dimensional construct including aspects of life quality or function that are affected by physical health and symptoms, psychosocial factors, and psychiatric conditions. HRQOL gives a broader measure of the burden of disease than physical impairment or disability levels. Purpose: To…
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.
2015-01-01
Background Although children of lower socio-economic status (SES) in the United States have generally been found to be at greater risk for obesity, the SES-obesity association varies when stratified by racial/ethnic groups-with no consistent association found for African American and Hispanic children. Research on contextual and setting-related factors may provide further insights into ethnic and SES disparities in obesity. We examined whether obesity levels among central Texas 8th grade students (n=2682) vary by school-level economic disadvantage across individual-level family SES and racial/ethnicity groups. As a secondary aim, we compared the association of school-level economic disadvantage and obesity by language spoken with parents (English or Spanish) among Hispanic students. Methods Multilevel regression models stratified by family SES and ethnicity were run using cross-sectional baseline data from five school districts participating in the Central Texas CATCH Middle School project. For family SES, independent multi-level logistic regression models were run for total sample and by gender for each family SES stratum (poor/near poor/just getting by, living comfortably, and very well off), adjusting for age, ethnicity, and gender. Similarly, multi-level regression models were run by race/ethnic group (African American, Hispanic, and White), adjusting for age, family SES, and gender. Results Students attending highly economically disadvantaged (ED) schools were between 1.7 (95% CI: 1.1-2.6) and 2.4 (95% CI: 1.2-4.8) times more likely to be obese as students attending low ED schools across family SES groups (p<.05). African American (ORAdj =3.4, 95% CI: 1.1-11.4), Hispanic (ORAdj=1.8, 95% CI 1.1-3.0) and White (ORAdj=3.8, 95% CI: 1.6-8.9) students attending high ED schools were more likely to be obese as counterparts at low ED schools (p<.05). Gender-stratified findings were similar to findings for total sample, although fewer results reached significance. While no obesity differences across school ED categories were found for Hispanic Spanish-speaking students, Hispanic English-speaking students (HES) attending high ED schools were 2.4 times more likely to be obese as HES students at low ED schools (p=.003). Conclusion Findings support the need to prioritize economically disadvantaged schools for obesity prevention efforts and support further exploration of school SES context in shaping children’s physical activity and dietary behaviors. PMID:26222099
Javaheri, Sogol; Sharma, Ravi K; Bluemke, David A; Redline, Susan
2017-08-01
We assessed whether the presence of central sleep apnea is associated with adverse left ventricular structural changes. We analysed 1412 participants from the Multi-Ethnic Study of Atherosclerosis who underwent both overnight polysomnography and cardiac magnetic resonance imaging. Subjects had been recruited 10 years earlier when free of cardiovascular disease. Our main exposure is the presence of central sleep apnea as defined by central apnea-hypopnea index = 5 or the presence of Cheyne-Stokes breathing. Outcome variables were left ventricular mass/height, left ventricular ejection fraction, and left ventricular mass/volume ratio. Multivariate linear regression models adjusted for age, gender, race, waist circumference, tobacco use, hypertension, and the obstructive apnea-hypopnea index were fit for the outcomes. Of the 1412 participants, 27 (2%) individuals had central sleep apnea. After adjusting for covariates, the presence of central sleep apnea was significantly associated with elevated left ventricular mass/volume ratio (β = 0.11 ± 0.04 g mL -1 , P = 0.0071), an adverse cardiac finding signifying concentric remodelling. © 2017 European Sleep Research Society.
Yaghoubian, Arezou; de Virgilio, Christian; Dauphine, Christine; Lewis, Roger J; Lin, Matthew
2007-09-01
Simple admission laboratory values can be used to classify patients with necrotizing soft-tissue infection (NSTI) into high and low mortality risk groups. Chart review. Public teaching hospital. All patients with NSTI from 1997 through 2006. Variables analyzed included medical history, admission vital signs, laboratory values, and microbiologic findings. Data analyses included univariate and classification and regression tree analyses. Mortality. One hundred twenty-four patients were identified with NSTI. The overall mortality rate was 21 of 124 (17%). On univariate analysis, factors associated with mortality included a history of cancer (P = .03), intravenous drug abuse (P < .001), low systolic blood pressure on admission (P = .03), base deficit (P = .009), and elevated white blood cell count (P = .06). On exploratory classification and regression tree analysis, admission serum lactate and sodium levels were predictors of mortality, with a sensitivity of 100%, specificity of 28%, positive predictive value of 23%, and negative predictive value of 100%. A serum lactate level greater than or equal to 54.1 mg/dL (6 mmol/L) alone was associated with a 32% mortality, whereas a serum sodium level greater than or equal to 135 mEq/L combined with a lactate level less than 54.1 mg/dL was associated with a mortality of 0%. Mortality for NSTIs remains high. A simple model, using admission serum lactate and serum sodium levels, may help identify patients at greatest risk for death.
Jelenkovic, Aline; Yokoyama, Yoshie; Sund, Reijo; Pietiläinen, Kirsi H; Hur, Yoon-Mi; Willemsen, Gonneke; Bartels, Meike; van Beijsterveldt, Toos C E M; Ooki, Syuichi; Saudino, Kimberly J; Stazi, Maria A; Fagnani, Corrado; D'Ippolito, Cristina; Nelson, Tracy L; Whitfield, Keith E; Knafo-Noam, Ariel; Mankuta, David; Abramson, Lior; Heikkilä, Kauko; Cutler, Tessa L; Hopper, John L; Wardle, Jane; Llewellyn, Clare H; Fisher, Abigail; Corley, Robin P; Huibregtse, Brooke M; Derom, Catherine A; Vlietinck, Robert F; Loos, Ruth J F; Bjerregaard-Andersen, Morten; Beck-Nielsen, Henning; Sodemann, Morten; Tarnoki, Adam D; Tarnoki, David L; Burt, S Alexandra; Klump, Kelly L; Ordoñana, Juan R; Sánchez-Romera, Juan F; Colodro-Conde, Lucia; Dubois, Lise; Boivin, Michel; Brendgen, Mara; Dionne, Ginette; Vitaro, Frank; Harris, Jennifer R; Brandt, Ingunn; Nilsen, Thomas Sevenius; Craig, Jeffrey M; Saffery, Richard; Rasmussen, Finn; Tynelius, Per; Bayasgalan, Gombojav; Narandalai, Danshiitsoodol; Haworth, Claire M A; Plomin, Robert; Ji, Fuling; Ning, Feng; Pang, Zengchang; Rebato, Esther; Krueger, Robert F; McGue, Matt; Pahlen, Shandell; Boomsma, Dorret I; Sørensen, Thorkild I A; Kaprio, Jaakko; Silventoinen, Karri
2017-10-01
There is evidence that birthweight is positively associated with body mass index (BMI) in later life, but it remains unclear whether this is explained by genetic factors or the intrauterine environment. We analysed the association between birthweight and BMI from infancy to adulthood within twin pairs, which provides insights into the role of genetic and environmental individual-specific factors. This study is based on the data from 27 twin cohorts in 17 countries. The pooled data included 78 642 twin individuals (20 635 monozygotic and 18 686 same-sex dizygotic twin pairs) with information on birthweight and a total of 214 930 BMI measurements at ages ranging from 1 to 49 years. The association between birthweight and BMI was analysed at both the individual and within-pair levels using linear regression analyses. At the individual level, a 1-kg increase in birthweight was linearly associated with up to 0.9 kg/m2 higher BMI (P < 0.001). Within twin pairs, regression coefficients were generally greater (up to 1.2 kg/m2 per kg birthweight, P < 0.001) than those from the individual-level analyses. Intra-pair associations between birthweight and later BMI were similar in both zygosity groups and sexes and were lower in adulthood. These findings indicate that environmental factors unique to each individual have an important role in the positive association between birthweight and later BMI, at least until young adulthood. © The Author 2017. Published by Oxford University Press on behalf of the International Epidemiological Association
Ouyang, Qi; Lu, Wenxi; Hou, Zeyu; Zhang, Yu; Li, Shuai; Luo, Jiannan
2017-05-01
In this paper, a multi-algorithm genetically adaptive multi-objective (AMALGAM) method is proposed as a multi-objective optimization solver. It was implemented in the multi-objective optimization of a groundwater remediation design at sites contaminated by dense non-aqueous phase liquids. In this study, there were two objectives: minimization of the total remediation cost, and minimization of the remediation time. A non-dominated sorting genetic algorithm II (NSGA-II) was adopted to compare with the proposed method. For efficiency, the time-consuming surfactant-enhanced aquifer remediation simulation model was replaced by a surrogate model constructed by a multi-gene genetic programming (MGGP) technique. Similarly, two other surrogate modeling methods-support vector regression (SVR) and Kriging (KRG)-were employed to make comparisons with MGGP. In addition, the surrogate-modeling uncertainty was incorporated in the optimization model by chance-constrained programming (CCP). The results showed that, for the problem considered in this study, (1) the solutions obtained by AMALGAM incurred less remediation cost and required less time than those of NSGA-II, indicating that AMALGAM outperformed NSGA-II. It was additionally shown that (2) the MGGP surrogate model was more accurate than SVR and KRG; and (3) the remediation cost and time increased with the confidence level, which can enable decision makers to make a suitable choice by considering the given budget, remediation time, and reliability. Copyright © 2017 Elsevier B.V. All rights reserved.
Determining the response of sea level to atmospheric pressure forcing using TOPEX/POSEIDON data
NASA Technical Reports Server (NTRS)
Fu, Lee-Lueng; Pihos, Greg
1994-01-01
The static response of sea level to the forcing of atmospheric pressure, the so-called inverted barometer (IB) effect, is investigated using TOPEX/POSEIDON data. This response, characterized by the rise and fall of sea level to compensate for the change of atmospheric pressure at a rate of -1 cm/mbar, is not associated with any ocean currents and hence is normally treated as an error to be removed from sea level observation. Linear regression and spectral transfer function analyses are applied to sea level and pressure to examine the validity of the IB effect. In regions outside the tropics, the regression coefficient is found to be consistently close to the theoretical value except for the regions of western boundary currents, where the mesoscale variability interferes with the IB effect. The spectral transfer function shows near IB response at periods of 30 degrees is -0.84 +/- 0.29 cm/mbar (1 standard deviation). The deviation from = 1 cm /mbar is shown to be caused primarily by the effect of wind forcing on sea level, based on multivariate linear regression model involving both pressure and wind forcing. The regression coefficient for pressure resulting from the multivariate analysis is -0.96 +/- 0.32 cm/mbar. In the tropics the multivariate analysis fails because sea level in the tropics is primarily responding to remote wind forcing. However, after removing from the data the wind-forced sea level estimated by a dynamic model of the tropical Pacific, the pressure regression coefficient improves from -1.22 +/- 0.69 cm/mbar to -0.99 +/- 0.46 cm/mbar, clearly revealing an IB response. The result of the study suggests that with a proper removal of the effect of wind forcing the IB effect is valid in most of the open ocean at periods longer than 20 days and spatial scales larger than 500 km.
Absolute order-of-magnitude reasoning applied to a social multi-criteria evaluation framework
NASA Astrophysics Data System (ADS)
Afsordegan, A.; Sánchez, M.; Agell, N.; Aguado, J. C.; Gamboa, G.
2016-03-01
A social multi-criteria evaluation framework for solving a real-case problem of selecting a wind farm location in the regions of Urgell and Conca de Barberá in Catalonia (northeast of Spain) is studied. This paper applies a qualitative multi-criteria decision analysis approach based on linguistic labels assessment able to address uncertainty and deal with different levels of precision. This method is based on qualitative reasoning as an artificial intelligence technique for assessing and ranking multi-attribute alternatives with linguistic labels in order to handle uncertainty. This method is suitable for problems in the social framework such as energy planning which require the construction of a dialogue process among many social actors with high level of complexity and uncertainty. The method is compared with an existing approach, which has been applied previously in the wind farm location problem. This approach, consisting of an outranking method, is based on Condorcet's original method. The results obtained by both approaches are analysed and their performance in the selection of the wind farm location is compared in aggregation procedures. Although results show that both methods conduct to similar alternatives rankings, the study highlights both their advantages and drawbacks.
The role of attitudes and culture in family caregiving for older adults.
Anngela-Cole, Linda; Hilton, Jeanne M
2009-01-01
This study evaluated cultural differences in attitudes toward caregiving and the stress levels of family caregivers. Participants included 98 Japanese American and 86 Caucasian American family caregivers caring for frail elders. Analyses using MANOVA and multiple regression analyses revealed that the Caucasian caregivers had more positive attitudes and provided more hours of care than the Japanese caregivers but that both groups had elevated levels of caregiver stress. The stress that family caregivers currently experience could lead to a future generation of care recipients who enter old age in worse condition than their predecessors. Professionals need to work together to develop culturally appropriate, evidence-based interventions to address this issue.
Dynamic whole body PET parametric imaging: II. Task-oriented statistical estimation
Karakatsanis, Nicolas A.; Lodge, Martin A.; Zhou, Y.; Wahl, Richard L.; Rahmim, Arman
2013-01-01
In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15–20cm) of a single bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study, was employed along with extensive Monte Carlo simulations and an initial clinical FDG patient dataset to validate and demonstrate the potential of the proposed statistical estimation methods. Both simulated and clinical results suggest that hybrid regression in the context of whole-body Patlak Ki imaging considerably reduces MSE without compromising high CNR. Alternatively, for a given CNR, hybrid regression enables larger reductions than OLS in the number of dynamic frames per bed, allowing for even shorter acquisitions of ~30min, thus further contributing to the clinical adoption of the proposed framework. Compared to the SUV approach, whole body parametric imaging can provide better tumor quantification, and can act as a complement to SUV, for the task of tumor detection. PMID:24080994
Dynamic whole-body PET parametric imaging: II. Task-oriented statistical estimation.
Karakatsanis, Nicolas A; Lodge, Martin A; Zhou, Y; Wahl, Richard L; Rahmim, Arman
2013-10-21
In the context of oncology, dynamic PET imaging coupled with standard graphical linear analysis has been previously employed to enable quantitative estimation of tracer kinetic parameters of physiological interest at the voxel level, thus, enabling quantitative PET parametric imaging. However, dynamic PET acquisition protocols have been confined to the limited axial field-of-view (~15-20 cm) of a single-bed position and have not been translated to the whole-body clinical imaging domain. On the contrary, standardized uptake value (SUV) PET imaging, considered as the routine approach in clinical oncology, commonly involves multi-bed acquisitions, but is performed statically, thus not allowing for dynamic tracking of the tracer distribution. Here, we pursue a transition to dynamic whole-body PET parametric imaging, by presenting, within a unified framework, clinically feasible multi-bed dynamic PET acquisition protocols and parametric imaging methods. In a companion study, we presented a novel clinically feasible dynamic (4D) multi-bed PET acquisition protocol as well as the concept of whole-body PET parametric imaging employing Patlak ordinary least squares (OLS) regression to estimate the quantitative parameters of tracer uptake rate Ki and total blood distribution volume V. In the present study, we propose an advanced hybrid linear regression framework, driven by Patlak kinetic voxel correlations, to achieve superior trade-off between contrast-to-noise ratio (CNR) and mean squared error (MSE) than provided by OLS for the final Ki parametric images, enabling task-based performance optimization. Overall, whether the observer's task is to detect a tumor or quantitatively assess treatment response, the proposed statistical estimation framework can be adapted to satisfy the specific task performance criteria, by adjusting the Patlak correlation-coefficient (WR) reference value. The multi-bed dynamic acquisition protocol, as optimized in the preceding companion study, was employed along with extensive Monte Carlo simulations and an initial clinical (18)F-deoxyglucose patient dataset to validate and demonstrate the potential of the proposed statistical estimation methods. Both simulated and clinical results suggest that hybrid regression in the context of whole-body Patlak Ki imaging considerably reduces MSE without compromising high CNR. Alternatively, for a given CNR, hybrid regression enables larger reductions than OLS in the number of dynamic frames per bed, allowing for even shorter acquisitions of ~30 min, thus further contributing to the clinical adoption of the proposed framework. Compared to the SUV approach, whole-body parametric imaging can provide better tumor quantification, and can act as a complement to SUV, for the task of tumor detection.
Knowledge and perception towards net care and repair practice in Ethiopia.
Zewde, Ayele; Irish, Seth; Woyessa, Adugna; Wuletaw, Yonas; Nahusenay, Honelgn; Abdelmenan, Semira; Demissie, Meaza; Gulema, Hanna; Dissanayake, Gunawardena; Chibsa, Sheleme; Solomon, Hiwot; Yenehun, Meseret A; Kebede, Amha; Lorenz, Lena M; Ponce-de-Leon, Gabriel; Keating, Joseph; Worku, Alemayehu; Berhane, Yemane
2017-10-02
Long-lasting insecticidal nets (LLINs) are a key malaria control intervention. Although LLINs are presumed to be effective for 3 years under field or programmatic conditions, net care and repair approaches by users influence the physical and chemical durability. Understanding how knowledge, perception and practices influence net care and repair practices could guide the development of targeted behavioural change communication interventions related to net care and repair in Ethiopia and elsewhere. This population-based, household survey was conducted in four regions of Ethiopia [Amhara, Oromia, Tigray, Southern Nations Nationalities Peoples Region (SNNPR)] in June 2015. A total of 1839 households were selected using multi-stage sampling procedures. The household respondents were the heads of households. A questionnaire was administered and the data were captured electronically. STATA software version 12 was used to analyse the data. Survey commands were used to account for the multi-stage sampling approach. Household descriptive statistics related to characteristics and levels of knowledge and perception on net care and repair are presented. Ordinal logistic regression was used to identify factors associated with net care and repair perceptions. Less than a quarter of the respondents (22.3%: 95% CI 20.4-24.3%) reported adequate knowledge of net care and repair; 24.6% (95% CI 22.7-26.5%) of the respondents reported receiving information on net care and repair in the previous 6 months. Thirty-five per cent of the respondents (35.1%: 95% CI 32.9-37.4%) reported positive perceptions towards net care and repair. Respondents with adequate knowledge on net care and repair (AOR 1.58: 95% CI 1.2-2.02), and those who discussed net care and repair with their family (AOR 1.47: 95% CI 1.14-1.89) had higher odds of having positive perceptions towards net care and repair. The low level of reported knowledge on net care and repair, as well as the low level of reported positive perception towards net repair need to be addressed. Targeted behavioural change communication campaigns could be used to target specific groups; increased net care and repair would lead to longer lasting nets.
Mobashsher, Ahmed Toaha; Abbosh, A M
2016-11-29
Rapid, on-the-spot diagnostic and monitoring systems are vital for the survival of patients with intracranial hematoma, as their conditions drastically deteriorate with time. To address the limited accessibility, high costs and static structure of currently used MRI and CT scanners, a portable non-invasive multi-slice microwave imaging system is presented for accurate 3D localization of hematoma inside human head. This diagnostic system provides fast data acquisition and imaging compared to the existing systems by means of a compact array of low-profile, unidirectional antennas with wideband operation. The 3D printed low-cost and portable system can be installed in an ambulance for rapid on-site diagnosis by paramedics. In this paper, the multi-slice head imaging system's operating principle is numerically analysed and experimentally validated on realistic head phantoms. Quantitative analyses demonstrate that the multi-slice head imaging system is able to generate better quality reconstructed images providing 70% higher average signal to clutter ratio, 25% enhanced maximum signal to clutter ratio and with around 60% hematoma target localization compared to the previous head imaging systems. Nevertheless, numerical and experimental results demonstrate that previous reported 2D imaging systems are vulnerable to localization error, which is overcome in the presented multi-slice 3D imaging system. The non-ionizing system, which uses safe levels of very low microwave power, is also tested on human subjects. Results of realistic phantom and subjects demonstrate the feasibility of the system in future preclinical trials.
Lomsky-Feder, Edna; Sasson-Levy, Orna
2015-03-01
With the growing elusiveness of the state apparatus in late modernity, military service is one of the last institutions to be clearly identified with the state, its ideologies and its policies. Therefore, negotiations between the military and its recruits produce acting subjects of citizenship with long-lasting consequences. Arguing that these negotiations are regulated by multi-level (civic, group, and individual) contracts, we explore the various meanings that these contracts obtain at the intersectionality of gender, class, and ethnicity; and examine how they shape the subjective experience of soldierhood and citizenship. More particularly, we analyse the meaning of military service in the retrospective life stories of Israeli Jewish women from various ethno-class backgrounds who served as army secretaries - a low-status, feminine gender-typed occupation within a hyper-masculine organization. Findings reveal that for women of the lower class, the organizing cultural schema of the multi-level contract is that of achieving respectability through military service, which means being included in the national collective. Conversely, for middle-class women, it is the sense of entitlement that shapes their contract with the military, which they expect to signify and maintain their privileged status. Thus, while for the lower class, the multi-level contract is about inclusion within the boundaries of the national collective, for the dominant groups, this contract is about reproducing social class hierarchies within national boundaries. © London School of Economics and Political Science 2014.
Diamond-Smith, Nadia; Sudhinaraset, May
2015-01-16
In the past few decades many countries have worked to increase the number of women delivering in facilities, with the goal of improving maternal and neonatal health outcomes. The purpose of this study is to explore the current situation of facility deliveries in Africa and Asia to understand where and with whom women deliver. Furthermore, we aim to test potential drivers of facility delivery at the individual, household, and community-level. Demographic and Health Survey data collected since 2003 from 43 countries in Africa and Asia is explored to understand the patterns of where women are delivering. We look at patterns by region and wealth quintile and urban/rural status. We then run a series of multi-level models looking at relationships between individual, household and community-level factors and the odds of a woman delivering in a facility. We explore this for Asia and Africa separately. We also look at correlates of delivery with a trained provider, in a public facility, in a private facility, with a doctor and in a hospital. The majority of women deliver in a facility and with a provider; however, about 20% of deliveries are still with no one or a friend/relative or alone. Rates of facility delivery are lower in Asia overall, and a greater proportion of deliveries take place in private facilities in Asia compared to Africa. Most of the individual level factors that have been found in past studies to be associated with delivering in a facility hold true for the multi-country-level analyses, and small differences exist between Asia and Africa. Women who deliver in private facilities differ from women who deliver in public facilities or at home. Most women in Africa and Asia are delivering in a facility, and drivers of facility delivery identified in smaller level or country specific studies hold true in multi-country national level data. More data and research is needed on other drivers, especially at the country-level and relating to the quality of care and maternal health complications.
McKinney, P A; Feltbower, R G; Stephenson, C R; Reynolds, C
2008-11-01
To provide a population-based clinical audit of children and young people with diabetes, reporting outcomes, including glycaemic control, for named individual units. Clinical audit data on care processes and glycated haemoglobin (HbA(1c)) were collected for 1742 children and young people treated in 16 paediatric units in Yorkshire, from January 2005 to March 2006. The Yorkshire Register of Diabetes in Children and Young People provided information technology support and validation that enhanced data quality. Multi-level linear regression modelling investigated factors affecting glycaemic control. An HbA(1c) measure was recorded for 91.6% of patients. The National Institute for Clinical Excellence-recommended target level for HbA(1c) of < 7.5% was achieved for 14.7% of patients. HbA(1c) was positively associated with duration of diabetes and later age at diagnosis. Patients living in deprived areas had significantly poorer control compared with those from affluent areas. Significant between-unit variation in HbA(1c) was not reflected by any association with unit size. Our population-based clinical audit of children with diabetes is the product of an effective collaboration between those who deliver care and health services researchers. High levels of recording the key care process measuring diabetes control, compared with national figures, suggests collaboration has translated into improved services. The interesting association between poor diabetes control and higher deprivation is noteworthy and requires further investigation. Future audits require recording of clinical management and clinic structures, in addition to resources to record, assemble and analyse data.
Panic Attack History and Smoking Topography
Farris, Samantha G.; Brown, Lily A.; Goodwin, Renee D.; Zvolensky, Michael J.
2016-01-01
Background Little is known about panic attacks and puffing topography, a behavioral index of the value of smoking reinforcement. This study examined smoking style during the course of smoking of a single cigarette among adult daily smokers with and without a history of panic attacks. Method Participants (n = 124, Mage = 43.9, SD = 9.7; 44.4% female) were non-treatment seeking daily smokers. Lifetime panic attack history was assessed via diagnostic assessment; 28.2% (n = 35) of the sample had a panic attack history. Participants smoked one cigarette during an ad libitum smoking trial. Puff volume, duration, and inter-puff interval were measured using the Clinical Research Support System (CReSS) pocket device. Results Regression analyses revealed that panic attack status was not associated with significant differences in average puff volume, duration, or inter-puff interval. Multi-level modeling was used to examine puffing trajectories. Puff-level data revealed that there was a significant quadratic time x panic effect for puff volume and duration. Those with a panic attack history demonstrated relatively sustained levels of both puff volume and duration over time, whereas those without a history of panic attacks demonstrated an increase followed by a decrease in volume and duration over time. These effects were not accounted for by the presence of general psychopathology. Discussion Smokers with a panic attack history demonstrate more persistent efforts to self-regulate the delivery of nicotine, and thus may be at risk for continued smoking and dependence. Tailored treatment may be needed to address unique vulnerabilities among this group. PMID:28033542
Panic attack history and smoking topography.
Farris, Samantha G; Brown, Lily A; Goodwin, Renee D; Zvolensky, Michael J
2017-02-01
Little is known about panic attacks and puffing topography, a behavioral index of the value of smoking reinforcement. This study examined smoking style during the course of smoking of a single cigarette among adult daily smokers with and without a history of panic attacks. Participants (n=124, M age =43.9, SD=9.7; 44.4% female) were non-treatment seeking daily smokers. Lifetime panic attack history was assessed via diagnostic assessment; 28.2% (n=35) of the sample had a panic attack history. Participants smoked one cigarette during an ad libitum smoking trial. Puff volume, duration, and inter-puff interval were measured using the Clinical Research Support System (CReSS) pocket device. Regression analyses revealed that panic attack status was not associated with significant differences in average puff volume, duration, or inter-puff interval. Multi-level modeling was used to examine puffing trajectories. Puff-level data revealed that there was a significant quadratic time x panic effect for puff volume and duration. Those with a panic attack history demonstrated relatively sustained levels of both puff volume and duration over time, whereas those without a history of panic attacks demonstrated an increase followed by a decrease in volume and duration over time. These effects were not accounted for by the presence of general psychopathology. Smokers with a panic attack history demonstrate more persistent efforts to self-regulate the delivery of nicotine, and thus may be at risk for continued smoking and dependence. Tailored treatment may be needed to address unique vulnerabilities among this group. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.
Delay discounting rates: a strong prognostic indicator of smoking relapse.
Sheffer, Christine E; Christensen, Darren R; Landes, Reid; Carter, Larry P; Jackson, Lisa; Bickel, Warren K
2014-11-01
Recent evidence suggests that several dimensions of impulsivity and locus of control are likely to be significant prognostic indicators of relapse. One-hundred and thirty-one treatment seeking smokers were enrolled in six weeks of multi-component cognitive-behavioral therapy with eight weeks of nicotine replacement therapy. Cox proportional hazard regressions were used to model days to relapse with each of the following: delay discounting of $100, delay discounting of $1000, six subscales of the Barratt Impulsiveness Scale (BIS), Rotter's Locus of Control (RLOC), Fagerstrom's Test for Nicotine Dependence (FTND), and the Perceived Stress Scale (PSS). Hazard ratios for a one standard deviation increase were estimated with 95% confidence intervals for each explanatory variable. Likelihood ratios were used to examine the level of association with days to relapse for different combinations of the explanatory variables while accounting for nicotine dependence and stress level. These analyses found that the $100 delay discounting rate had the strongest association with days to relapse. Further, when discounting rates were combined with the FTND and PSS, the associations remained significant. When the other measures were combined with the FTND and PSS, their associations with relapse non-significant. These findings indicate that delay discounting is independently associated with relapse and adds to what is already accounted for by nicotine dependence and stress level. They also signify that delay discounting is a productive new target for enhancing treatment for tobacco dependence. Consequently, adding an intervention designed to decrease discounting rates to a comprehensive treatment for tobacco dependence has the potential to decrease relapse rates. Copyright © 2014 Elsevier Ltd. All rights reserved.
Borda, Alfredo; Sanz, Belén; Otero, Laura; Blasco, Teresa; García-Gómez, Francisco J; de Andrés, Fuencisla
2011-01-01
To analyze the association between travel time and participation in a breast cancer screening program adjusted for contextual variables in the province of Segovia (Spain). We performed an ecological study using the following data sources: the Breast Cancer Early Detection Program of the Primary Care Management of Segovia, the Population and Housing Census for 2001 and the municipal register for 2006-2007. The study period comprised January 2006 to December 2007. Dependent variables consisted of the municipal participation rate and the desired level of municipal participation (greater than or equal to 70%). The key independent variable was travel time from the municipality to the mammography unit. Covariables consisted of the municipalities' demographic and socioeconomic factors. We performed univariate and multivariate Poisson regression analyses of the participation rate, and logistic regression of the desired participation level. The sample was composed of 178 municipalities. The mean participation rate was 75.2%. The desired level of participation (≥ 70%) was achieved in 119 municipalities (67%). In the multivariate Poisson and logistic regression analyses, longer travel time was associated with a lower participation rate and with lower participation after adjustment was made for geographic density, age, socioeconomic status and dependency ratio, with a relative risk index of 0.88 (95% CI: 0.81-0.96) and an odds ratio of 0.22 (95% CI: 0.1-0.47), respectively. Travel time to the mammography unit may help to explain participation in breast cancer screening programs. Copyright © 2010 SESPAS. Published by Elsevier Espana. All rights reserved.
Cummings, E. Mark; George, Melissa R. W.; McCoy, Kathleen P.; Davies, Patrick T.
2012-01-01
Advancing the long-term prospective study of explanations for the effects of marital conflict on children’s functioning, relations were examined between interparental conflict in kindergarten, children’s emotional insecurity in the early school years, and subsequent adolescent internalizing and externalizing problems. Based on a community sample of 235 mothers, fathers and children (M = 6.00, 8.02, 12.62 years), and multi-method and multi-reporter assessments, structural equation model (SEM) tests provided support for emotional insecurity in early childhood as an intervening process related to adolescent internalizing and externalizing problems, even with stringent auto-regressive controls over prior levels of functioning for both mediating and outcome variables. Discussion considers implications for understanding pathways between interparental conflict, emotional insecurity and adjustment in childhood and adolescence. PMID:22694264
Wei, Chang-Na; Zhou, Qing-He; Wang, Li-Zhong
2017-01-01
Abstract Currently, there is no consensus on how to determine the optimal dose of intrathecal bupivacaine for an individual undergoing an elective cesarean section. In this study, we developed a regression equation between intrathecal 0.5% hyperbaric bupivacaine volume and abdominal girth and vertebral column length, to determine a suitable block level (T5) for elective cesarean section patients. In phase I, we analyzed 374 parturients undergoing an elective cesarean section that received a suitable dose of intrathecal 0.5% hyperbaric bupivacaine after a combined spinal-epidural (CSE) was performed at the L3/4 interspace. Parturients with T5 blockade to pinprick were selected for establishing the regression equation between 0.5% hyperbaric bupivacaine volume and vertebral column length and abdominal girth. Six parturient and neonatal variables, intrathecal 0.5% hyperbaric bupivacaine volume, and spinal anesthesia spread were recorded. Bivariate line correlation analyses, multiple line regression analyses, and 2-tailed t tests or chi-square test were performed, as appropriate. In phase II, another 200 parturients with CSE for elective cesarean section were enrolled to verify the accuracy of the regression equation. In phase I, a total of 143 parturients were selected to establish the following regression equation: YT5 = 0.074X1 − 0.022X2 − 0.017 (YT5 = 0.5% hyperbaric bupivacaine volume for T5 block level; X1 = vertebral column length; and X2 = abdominal girth). In phase II, a total of 189 participants were enrolled in the study to verify the accuracy of the regression equation, and 155 parturients with T5 blockade were deemed eligible, which accounted for 82.01% of all participants. This study evaluated parturients with T5 blockade to pinprick after a CSE for elective cesarean section to establish a regression equation between parturient vertebral column length and abdominal girth and 0.5% hyperbaric intrathecal bupivacaine volume. This equation can accurately predict the suitable intrathecal hyperbaric bupivacaine dose for elective cesarean section. PMID:28834913
Wei, Chang-Na; Zhou, Qing-He; Wang, Li-Zhong
2017-08-01
Currently, there is no consensus on how to determine the optimal dose of intrathecal bupivacaine for an individual undergoing an elective cesarean section. In this study, we developed a regression equation between intrathecal 0.5% hyperbaric bupivacaine volume and abdominal girth and vertebral column length, to determine a suitable block level (T5) for elective cesarean section patients.In phase I, we analyzed 374 parturients undergoing an elective cesarean section that received a suitable dose of intrathecal 0.5% hyperbaric bupivacaine after a combined spinal-epidural (CSE) was performed at the L3/4 interspace. Parturients with T5 blockade to pinprick were selected for establishing the regression equation between 0.5% hyperbaric bupivacaine volume and vertebral column length and abdominal girth. Six parturient and neonatal variables, intrathecal 0.5% hyperbaric bupivacaine volume, and spinal anesthesia spread were recorded. Bivariate line correlation analyses, multiple line regression analyses, and 2-tailed t tests or chi-square test were performed, as appropriate. In phase II, another 200 parturients with CSE for elective cesarean section were enrolled to verify the accuracy of the regression equation.In phase I, a total of 143 parturients were selected to establish the following regression equation: YT5 = 0.074X1 - 0.022X2 - 0.017 (YT5 = 0.5% hyperbaric bupivacaine volume for T5 block level; X1 = vertebral column length; and X2 = abdominal girth). In phase II, a total of 189 participants were enrolled in the study to verify the accuracy of the regression equation, and 155 parturients with T5 blockade were deemed eligible, which accounted for 82.01% of all participants.This study evaluated parturients with T5 blockade to pinprick after a CSE for elective cesarean section to establish a regression equation between parturient vertebral column length and abdominal girth and 0.5% hyperbaric intrathecal bupivacaine volume. This equation can accurately predict the suitable intrathecal hyperbaric bupivacaine dose for elective cesarean section.
NASA Astrophysics Data System (ADS)
Muller, Sybrand Jacobus; van Niekerk, Adriaan
2016-07-01
Soil salinity often leads to reduced crop yield and quality and can render soils barren. Irrigated areas are particularly at risk due to intensive cultivation and secondary salinization caused by waterlogging. Regular monitoring of salt accumulation in irrigation schemes is needed to keep its negative effects under control. The dynamic spatial and temporal characteristics of remote sensing can provide a cost-effective solution for monitoring salt accumulation at irrigation scheme level. This study evaluated a range of pan-fused SPOT-5 derived features (spectral bands, vegetation indices, image textures and image transformations) for classifying salt-affected areas in two distinctly different irrigation schemes in South Africa, namely Vaalharts and Breede River. The relationship between the input features and electro conductivity measurements were investigated using regression modelling (stepwise linear regression, partial least squares regression, curve fit regression modelling) and supervised classification (maximum likelihood, nearest neighbour, decision tree analysis, support vector machine and random forests). Classification and regression trees and random forest were used to select the most important features for differentiating salt-affected and unaffected areas. The results showed that the regression analyses produced weak models (<0.4 R squared). Better results were achieved using the supervised classifiers, but the algorithms tend to over-estimate salt-affected areas. A key finding was that none of the feature sets or classification algorithms stood out as being superior for monitoring salt accumulation at irrigation scheme level. This was attributed to the large variations in the spectral responses of different crops types at different growing stages, coupled with their individual tolerances to saline conditions.