Dropout revisited: patient- and therapist-initiated discontinuation of psychotherapy as a function of organizational instability.

PubMed

Werbart, Andrzej; Andersson, Håkan; Sandell, Rolf

2014-01-01

To explore the association between the stability or instability of services' organizational structure and patient- and therapist-initiated discontinuation of therapy in routine mental health. Three groups, comprising altogether 750 cases in routine mental health care in eight different clinics, were included: cases with patient-initiated discontinuation, therapist-initiated discontinuation, and patients remaining in treatment. Multilevel multinomial regression was used to estimate three models: An initial, unconditional intercept-only model, another one including patient variables, and a final model with significant patient and therapist variables including the organizational stability of the therapists' clinic. High between-therapist variability was noted. Odds ratios and significance tests indicated a strong association of organizational instability with patient-initiated premature termination in particular. The question of how organizational factors influence the treatment results needs further research. Future studies have to be designed in ways that permit clinically meaningful subdivision of the patients' and the therapists' decisions for premature termination.

Leveling up the analysis of the reminiscence bump in autobiographical memory: A new approach based on multilevel multinomial models.

PubMed

Zimprich, Daniel; Wolf, Tabea

2018-06-20

In many studies of autobiographical memory, participants are asked to generate more than one autobiographical memory. The resulting data then have a hierarchical or multilevel structure, in the sense that the autobiographical memories (Level 1) generated by the same person (Level 2) tend to be more similar. Transferred to an analysis of the reminiscence bump in autobiographical memory, at Level 1 the prediction of whether an autobiographical memory will fall within the reminiscence bump is based on the characteristics of that memory. At Level 2, the prediction of whether an individual will report more autobiographical memories that fall in the reminiscence bump is based on the characteristics of the individual. We suggest a multilevel multinomial model that allows for analyzing whether an autobiographical memory falls in the reminiscence bump at both levels of analysis simultaneously. The data come from 100 older participants who reported up to 33 autobiographical memories. Our results showed that about 12% of the total variance was between persons (Level 2). Moreover, at Level 1, memories of first-time experiences were more likely to fall in the reminiscence bump than were emotionally more positive memories. At Level 2, persons who reported more emotionally positive memories tended to report fewer memories from the life period after the reminiscence bump. In addition, cross-level interactions showed that the effects at Level 1 partly depended on the Level 2 effects. We discuss possible extensions of the model we present and the meaning of our findings for two prominent explanatory approaches to the reminiscence bump, as well as future directions.

The different roles of neighbourhood and individual social capital on oral health-related quality of life during pregnancy and postpartum: a multilevel analysis.

PubMed

Lamarca, Gabriela A; Leal, Maria do C; Leao, Anna T T; Sheiham, Aubrey; Vettore, Mario V

2014-04-01

Social capital incorporates neighbourhood and individual levels of interactions and influences health. The objective of this was to assess the association of neighbourhood and individual social capital with oral health-related quality of life (OHRQoL) in pregnant and postpartum women. This was a follow-up prevalence multilevel study on a representative sample of 1248 women grouped into 55 neighbourhoods. OHRQoL was assessed in the postpartum period using the Oral Health Impact Profile questionnaire (OHIP-14). Exploratory variables were gathered during the first trimester of pregnancy and included neighbourhood social capital (neighbourhood-level measure), individual social capital (social support and social networks), demographic and socio-economic variables, oral health measures, and health-related behaviours. The multilevel ordered multinomial logistic regression showed that neighbourhood social capital did not significantly affect women's OHRQoL during pregnancy and postpartum period. Individual social capital measures were independently associated with high OHRQoL. Lack of family social network increased the odds for high OHRQoL (OR = 1.44, 95% CI: 1.08-1.92). Individuals with high levels of positive social interaction were less likely to report high scores of OHRQoL (OR = 0.90, 95% CI: 0.82-0.98). Individual social capital was of greater relevance to women's OHRQoL in and after pregnancy than neighbourhood social capital. These findings suggest that quality of personal and social resources of pregnant women are more important for OHRQoL than the neighbourhoods where the women live. © 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Multinomial logistic regression in workers' health

NASA Astrophysics Data System (ADS)

Grilo, Luís M.; Grilo, Helena L.; Gonçalves, Sónia P.; Junça, Ana

2017-11-01

In European countries, namely in Portugal, it is common to hear some people mentioning that they are exposed to excessive and continuous psychosocial stressors at work. This is increasing in diverse activity sectors, such as, the Services sector. A representative sample was collected from a Portuguese Services' organization, by applying a survey (internationally validated), which variables were measured in five ordered categories in Likert-type scale. A multinomial logistic regression model is used to estimate the probability of each category of the dependent variable general health perception where, among other independent variables, burnout appear as statistically significant.

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

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

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test ofmore » the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.« less

Multinomial logistic regression modelling of obesity and overweight among primary school students in a rural area of Negeri Sembilan

NASA Astrophysics Data System (ADS)

Ghazali, Amirul Syafiq Mohd; Ali, Zalila; Noor, Norlida Mohd; Baharum, Adam

2015-10-01

Multinomial logistic regression is widely used to model the outcomes of a polytomous response variable, a categorical dependent variable with more than two categories. The model assumes that the conditional mean of the dependent categorical variables is the logistic function of an affine combination of predictor variables. Its procedure gives a number of logistic regression models that make specific comparisons of the response categories. When there are q categories of the response variable, the model consists of q-1 logit equations which are fitted simultaneously. The model is validated by variable selection procedures, tests of regression coefficients, a significant test of the overall model, goodness-of-fit measures, and validation of predicted probabilities using odds ratio. This study used the multinomial logistic regression model to investigate obesity and overweight among primary school students in a rural area on the basis of their demographic profiles, lifestyles and on the diet and food intake. The results indicated that obesity and overweight of students are related to gender, religion, sleep duration, time spent on electronic games, breakfast intake in a week, with whom meals are taken, protein intake, and also, the interaction between breakfast intake in a week with sleep duration, and the interaction between gender and protein intake.

Intermediate and advanced topics in multilevel logistic regression analysis

PubMed Central

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.

PubMed

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.

Discrete post-processing of total cloud cover ensemble forecasts

NASA Astrophysics Data System (ADS)

Hemri, Stephan; Haiden, Thomas; Pappenberger, Florian

2017-04-01

This contribution presents an approach to post-process ensemble forecasts for the discrete and bounded weather variable of total cloud cover. Two methods for discrete statistical post-processing of ensemble predictions are tested. The first approach is based on multinomial logistic regression, the second involves a proportional odds logistic regression model. Applying them to total cloud cover raw ensemble forecasts from the European Centre for Medium-Range Weather Forecasts improves forecast skill significantly. Based on station-wise post-processing of raw ensemble total cloud cover forecasts for a global set of 3330 stations over the period from 2007 to early 2014, the more parsimonious proportional odds logistic regression model proved to slightly outperform the multinomial logistic regression model. Reference Hemri, S., Haiden, T., & Pappenberger, F. (2016). Discrete post-processing of total cloud cover ensemble forecasts. Monthly Weather Review 144, 2565-2577.

Extreme Sparse Multinomial Logistic Regression: A Fast and Robust Framework for Hyperspectral Image Classification

NASA Astrophysics Data System (ADS)

Cao, Faxian; Yang, Zhijing; Ren, Jinchang; Ling, Wing-Kuen; Zhao, Huimin; Marshall, Stephen

2017-12-01

Although the sparse multinomial logistic regression (SMLR) has provided a useful tool for sparse classification, it suffers from inefficacy in dealing with high dimensional features and manually set initial regressor values. This has significantly constrained its applications for hyperspectral image (HSI) classification. In order to tackle these two drawbacks, an extreme sparse multinomial logistic regression (ESMLR) is proposed for effective classification of HSI. First, the HSI dataset is projected to a new feature space with randomly generated weight and bias. Second, an optimization model is established by the Lagrange multiplier method and the dual principle to automatically determine a good initial regressor for SMLR via minimizing the training error and the regressor value. Furthermore, the extended multi-attribute profiles (EMAPs) are utilized for extracting both the spectral and spatial features. A combinational linear multiple features learning (MFL) method is proposed to further enhance the features extracted by ESMLR and EMAPs. Finally, the logistic regression via the variable splitting and the augmented Lagrangian (LORSAL) is adopted in the proposed framework for reducing the computational time. Experiments are conducted on two well-known HSI datasets, namely the Indian Pines dataset and the Pavia University dataset, which have shown the fast and robust performance of the proposed ESMLR framework.

Direct and interactive effects of parent, friend and schoolmate drinking on alcohol use trajectories.

PubMed

Lynch, Alicia Doyle; Coley, Rebekah Levine; Sims, Jacqueline; Lombardi, Caitlin McPherran; Mahalik, James R

2015-01-01

This study considered the unique and interactive roles of social norms from parents, friends and schools in predicting developmental trajectories of adolescent drinking and intoxication. Using data from the National Longitudinal Study of Adolescent Health, which followed adolescents (N = 18,921) for 13 years, we used discrete mixture modelling to identify unique developmental trajectories of drinking and of intoxication. Next, multilevel multinomial regression models examined the role of alcohol-related social norms from parents, friends and schoolmates in the prediction of youths' trajectory group membership. Results demonstrated that social norms from parents, friends and schoolmates that were favourable towards alcohol use uniquely predicted drinking and intoxication trajectory group membership. Interactions between social norms revealed that schoolmate drinking played an important moderating role, frequently augmenting social norms from parents and friends. The current findings suggest that social norms from multiple sources (parents, friends and schools) work both independently and interactively to predict longitudinal trajectories of adolescent alcohol use. Results highlight the need to identify and understand social messages from multiple developmental contexts in efforts to reduce adolescent alcohol consumption and alcohol-related risk-taking.

Training and retaining staff to competently deliver an evidence-based practice: the role of staff attributes and perceptions of organizational functioning.

PubMed

Garner, Bryan R; Hunter, Brooke D; Godley, Susan H; Godley, Mark D

2012-03-01

Within the context of an initiative to implement evidence-based practices (EBPs) for adolescents with substance use disorders, this study examined the extent to which staff factors measured at an initial EBP training workshop were predictive of EBP competence and turnover status of staff (N = 121) measured 6, 9, and 12 months posttraining. By the final assessment point, 52.3% of staff transitioned to the employed/EBP-competent category, 26.6% transitioned to the not employed/not EBP-competent category, 4.6% transitioned to the not employed/EBP-competent category, and 16.5% had not transitioned out of the initial category. Multilevel multinomial regression analysis identified several measures that were significant predictors of staff transitions to the not employed/not EBP-competent category (e.g., program needs, job satisfaction, burnout) and transitions to the employed/EBP-competent category (e.g., months in position, pressures for change, influence). Findings have implications for the development and testing of strategies to train and retain staff to deliver EBPs in practice settings. Copyright © 2012 Elsevier Inc. All rights reserved.

Classification of Effective Soil Depth by Using Multinomial Logistic Regression Analysis

NASA Astrophysics Data System (ADS)

Chang, C. H.; Chan, H. C.; Chen, B. A.

2016-12-01

Classification of effective soil depth is a task of determining the slopeland utilizable limitation in Taiwan. The "Slopeland Conservation and Utilization Act" categorizes the slopeland into agriculture and husbandry land, land suitable for forestry and land for enhanced conservation according to the factors including average slope, effective soil depth, soil erosion and parental rock. However, sit investigation of the effective soil depth requires a cost-effective field work. This research aimed to classify the effective soil depth by using multinomial logistic regression with the environmental factors. The Wen-Shui Watershed located at the central Taiwan was selected as the study areas. The analysis of multinomial logistic regression is performed by the assistance of a Geographic Information Systems (GIS). The effective soil depth was categorized into four levels including deeper, deep, shallow and shallower. The environmental factors of slope, aspect, digital elevation model (DEM), curvature and normalized difference vegetation index (NDVI) were selected for classifying the soil depth. An Error Matrix was then used to assess the model accuracy. The results showed an overall accuracy of 75%. At the end, a map of effective soil depth was produced to help planners and decision makers in determining the slopeland utilizable limitation in the study areas.

Regression Models For Multivariate Count Data

PubMed Central

Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei

2016-01-01

Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data. PMID:28348500

Regression Models For Multivariate Count Data.

PubMed

Zhang, Yiwen; Zhou, Hua; Zhou, Jin; Sun, Wei

2017-01-01

Data with multivariate count responses frequently occur in modern applications. The commonly used multinomial-logit model is limiting due to its restrictive mean-variance structure. For instance, analyzing count data from the recent RNA-seq technology by the multinomial-logit model leads to serious errors in hypothesis testing. The ubiquity of over-dispersion and complicated correlation structures among multivariate counts calls for more flexible regression models. In this article, we study some generalized linear models that incorporate various correlation structures among the counts. Current literature lacks a treatment of these models, partly due to the fact that they do not belong to the natural exponential family. We study the estimation, testing, and variable selection for these models in a unifying framework. The regression models are compared on both synthetic and real RNA-seq data.

Predicting longitudinal trajectories of health probabilities with random-effects multinomial logit regression.

PubMed

Liu, Xian; Engel, Charles C

2012-12-20

Researchers often encounter longitudinal health data characterized with three or more ordinal or nominal categories. Random-effects multinomial logit models are generally applied to account for potential lack of independence inherent in such clustered data. When parameter estimates are used to describe longitudinal processes, however, random effects, both between and within individuals, need to be retransformed for correctly predicting outcome probabilities. This study attempts to go beyond existing work by developing a retransformation method that derives longitudinal growth trajectories of unbiased health probabilities. We estimated variances of the predicted probabilities by using the delta method. Additionally, we transformed the covariates' regression coefficients on the multinomial logit function, not substantively meaningful, to the conditional effects on the predicted probabilities. The empirical illustration uses the longitudinal data from the Asset and Health Dynamics among the Oldest Old. Our analysis compared three sets of the predicted probabilities of three health states at six time points, obtained from, respectively, the retransformation method, the best linear unbiased prediction, and the fixed-effects approach. The results demonstrate that neglect of retransforming random errors in the random-effects multinomial logit model results in severely biased longitudinal trajectories of health probabilities as well as overestimated effects of covariates on the probabilities. Copyright © 2012 John Wiley & Sons, Ltd.

Financial and Emotional Support in Close Personal Ties among Central Asian Migrant Women in Russia.

PubMed

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.

Associations between physical activity and the neighbourhood social environment: baseline results from the HABITAT multilevel study.

PubMed

Rachele, Jerome N; Ghani, Fatima; Loh, Venurs H Y; Brown, Wendy J; Turrell, Gavin

2016-12-01

Limitations have arisen when measuring associations between the neighbourhood social environment and physical activity, including same-source bias, and the reliability of aggregated neighbourhood-level social environment measures. This study examines cross-sectional associations between the neighbourhood social environment (perceptions of incivilities, crime, and social cohesion) and self-reported physical activity, while accounting for same-source bias and reliability of neighbourhood-level exposure measures, using data from a large population-based clustered sample. This investigation included 11,035 residents aged 40-65years from 200 neighbourhoods in Brisbane, Australia, in 2007. Respondents self-reported their physical activity and perceptions of the social environment (neighbourhood incivilities, crime and safety, and social cohesion). Models were adjusted for individual-level education, occupation, and household income, and neighbourhood disadvantage. Exposure measures were generated via split clusters and an empirical Bayes estimation procedure. Data were analysed in 2016 using multilevel multinomial logistic regression. Residents of neighbourhoods with the highest incivilities and crime, and lowest social cohesion were reference categories. Individuals were more likely to be in the higher physical activity categories if they were in neighbourhoods with the lowest incivilities and the lowest crime. No associations were found between social cohesion and physical activity. This study provides a basis from which to gain a clearer understanding of the relationship between the neighbourhood social environment and individual physical activity. Further work is required to explore the pathways between perceptions of the neighbourhood social environment and physical activity. Copyright © 2016 Elsevier Inc. All rights reserved.

Comparison of standard maximum likelihood classification and polytomous logistic regression used in remote sensing

Treesearch

John Hogland; Nedret Billor; Nathaniel Anderson

2013-01-01

Discriminant analysis, referred to as maximum likelihood classification within popular remote sensing software packages, is a common supervised technique used by analysts. Polytomous logistic regression (PLR), also referred to as multinomial logistic regression, is an alternative classification approach that is less restrictive, more flexible, and easy to interpret. To...

Evaluating risk factors for endemic human Salmonella Enteritidis infections with different phage types in Ontario, Canada using multinomial logistic regression and a case-case study approach

PubMed Central

2012-01-01

Background Identifying risk factors for Salmonella Enteritidis (SE) infections in Ontario will assist public health authorities to design effective control and prevention programs to reduce the burden of SE infections. Our research objective was to identify risk factors for acquiring SE infections with various phage types (PT) in Ontario, Canada. We hypothesized that certain PTs (e.g., PT8 and PT13a) have specific risk factors for infection. Methods Our study included endemic SE cases with various PTs whose isolates were submitted to the Public Health Laboratory-Toronto from January 20th to August 12th, 2011. Cases were interviewed using a standardized questionnaire that included questions pertaining to demographics, travel history, clinical symptoms, contact with animals, and food exposures. A multinomial logistic regression method using the Generalized Linear Latent and Mixed Model procedure and a case-case study design were used to identify risk factors for acquiring SE infections with various PTs in Ontario, Canada. In the multinomial logistic regression model, the outcome variable had three categories representing human infections caused by SE PT8, PT13a, and all other SE PTs (i.e., non-PT8/non-PT13a) as a referent category to which the other two categories were compared. Results In the multivariable model, SE PT8 was positively associated with contact with dogs (OR=2.17, 95% CI 1.01-4.68) and negatively associated with pepper consumption (OR=0.35, 95% CI 0.13-0.94), after adjusting for age categories and gender, and using exposure periods and health regions as random effects to account for clustering. Conclusions Our study findings offer interesting hypotheses about the role of phage type-specific risk factors. Multinomial logistic regression analysis and the case-case study approach are novel methodologies to evaluate associations among SE infections with different PTs and various risk factors. PMID:23057531

Comparing the efficiency of digital and conventional soil mapping to predict soil types in a semi-arid region in Iran

NASA Astrophysics Data System (ADS)

Zeraatpisheh, Mojtaba; Ayoubi, Shamsollah; Jafari, Azam; Finke, Peter

2017-05-01

The efficiency of different digital and conventional soil mapping approaches to produce categorical maps of soil types is determined by cost, sample size, accuracy and the selected taxonomic level. The efficiency of digital and conventional soil mapping approaches was examined in the semi-arid region of Borujen, central Iran. This research aimed to (i) compare two digital soil mapping approaches including Multinomial logistic regression and random forest, with the conventional soil mapping approach at four soil taxonomic levels (order, suborder, great group and subgroup levels), (ii) validate the predicted soil maps by the same validation data set to determine the best method for producing the soil maps, and (iii) select the best soil taxonomic level by different approaches at three sample sizes (100, 80, and 60 point observations), in two scenarios with and without a geomorphology map as a spatial covariate. In most predicted maps, using both digital soil mapping approaches, the best results were obtained using the combination of terrain attributes and the geomorphology map, although differences between the scenarios with and without the geomorphology map were not significant. Employing the geomorphology map increased map purity and the Kappa index, and led to a decrease in the 'noisiness' of soil maps. Multinomial logistic regression had better performance at higher taxonomic levels (order and suborder levels); however, random forest showed better performance at lower taxonomic levels (great group and subgroup levels). Multinomial logistic regression was less sensitive than random forest to a decrease in the number of training observations. The conventional soil mapping method produced a map with larger minimum polygon size because of traditional cartographic criteria used to make the geological map 1:100,000 (on which the conventional soil mapping map was largely based). Likewise, conventional soil mapping map had also a larger average polygon size that resulted in a lower level of detail. Multinomial logistic regression at the order level (map purity of 0.80), random forest at the suborder (map purity of 0.72) and great group level (map purity of 0.60), and conventional soil mapping at the subgroup level (map purity of 0.48) produced the most accurate maps in the study area. The multinomial logistic regression method was identified as the most effective approach based on a combined index of map purity, map information content, and map production cost. The combined index also showed that smaller sample size led to a preference for the order level, while a larger sample size led to a preference for the great group level.

The influence of the social environment on youth smoking status.

PubMed

Bellatorre, Anna; Choi, Kelvin; Bernat, Debra

2015-12-01

Youth smoking is complex with multilevel influences. While much is known about certain levels of influence on youth smoking, the lack of focus on institutional influences is notable. This study evaluated the effects of ambient smoking attitudes and behaviors in schools on individual youth smoking. Data from the 2012 Florida Youth Tobacco Survey (n=67,460) were analyzed. Multinomial logistic regression was used to investigate individual and aggregated school-level factors that were associated with a youth being classified as a "susceptible nonsmoker" (SN) or "current smoker" (CS) relative to a "non-susceptible nonsmoker" (NN). The aggregated percentage of regular smokers at a school, ambient school level positive smoking perceptions, and the standardized difference between individual and school-level positive smoking perceptions were statistically significant in the fully adjusted model. We also found an increased risk of being a SN relative to a NN for Hispanic youth. Moreover, our approach to modeling institutional-level factors raised the pseudo r-squared from 0.05 to 0.14. These findings suggest the importance of ambient smoking attitudes and behaviors on youth smoking. Prevention efforts affecting ambient smoking attitudes may be beneficial. Published by Elsevier Inc.

National economic development and disparities in body mass index: a cross-sectional study of data from 38 countries.

PubMed

Neuman, Melissa; Kawachi, Ichiro; Gortmaker, Steven; Subramanian, Sv

2014-01-01

Increases in body mass index (BMI) and the prevalence of overweight in low- and middle income countries (LMICs) are often ascribed to changes in global trade patterns or increases in national income. These changes are likely to affect populations within LMICs differently based on their place of residence or socioeconomic status (SES). Using nationally representative survey data from 38 countries and national economic indicators from the World Bank and other international organizations, we estimated ecological and multilevel models to assess the association between national levels of gross domestic product (GDP), foreign direct investment (FDI), and mean tariffs and BMI. We used linear regression to estimate the ecological association between average annual change in economic indicators and BMI, and multilevel linear or ordered multinomial models to estimate associations between national economic indicators and individual BMI or over- and underweight. We also included cross-level interaction terms to highlight differences in the association of BMI with national economic indicators by type of residence or socioeconomic status (SES). There was a positive but non-significant association of GDP and mean BMI. This positive association of GDP and BMI was greater among rural residents and the poor. There were no significant ecological associations between measures of trade openness and mean BMI, but FDI was positively associated with BMI among the poorest respondents and in rural areas and tariff levels were negatively associated with BMI among poor and rural respondents. Measures of national income and trade openness have different associations with the BMI across populations within developing countries. These divergent findings underscore the complexity of the effects of development on health and the importance of considering how the health effects of "globalizing" economic and cultural trends are modified by individual-level wealth and residence.

Is psychological membership in the classroom a function of standing out while fitting in? Implications for achievement motivation and emotions.

PubMed

Gray, DeLeon L

2017-04-01

Education researchers have consistently linked students' perceptions of "fitting in" at school with patterns of motivation and positive emotions. This study proposes that "standing out" is also helpful for producing these outcomes, and that standing out works in concert with perceptions of fitting in. In a sample of 702 high school students nested within 33 classrooms, principal components analysis and confirmatory factor analysis were each conducted on half of the sample. Results support the proposed structure of measures of standing out and fitting in. Multilevel latent profile analysis was then used to classify students into four profiles of standing out while fitting in (SOFI): Unfulfilled, Somewhat Fulfilled, Nearly Fulfilled, and Fulfilled. A multinomial logistic regression revealed that students of color and those on who paid free/reduced prices lunch were overrepresented in the Unfulfilled and Somewhat Fulfilled profiles. A multilevel path analysis was then performed to assess the direct and indirect associations of profile membership with measures of task value and achievement emotions. Relative to the other profiles, students in the Fulfilled SOFI Profile express greater psychological membership in their classrooms and, in turn, express higher valuing of academic material (i.e., intrinsic value, utility value, and attainment value) and more positive achievement emotions (i.e., more enjoyment and pride; less boredom, hopelessness, and shame). This investigation provides critical insights on the potential benefits of structuring academic learning environments to foster feelings of distinctiveness among adolescents; and has implications for cultivating identities and achievement motivation in academic settings. Copyright © 2017 Society for the Study of School Psychology. Published by Elsevier Ltd. All rights reserved.

Health at the borders: Bayesian multilevel analysis of women's malnutrition determinants in Ethiopia.

PubMed

Delbiso, Tefera Darge; Rodriguez-Llanes, Jose Manuel; Altare, Chiara; Masquelier, Bruno; Guha-Sapir, Debarati

2016-01-01

Women's malnutrition, particularly undernutrition, remains an important public health challenge in Ethiopia. Although various studies examined the levels and determinants of women's nutritional status, the influence of living close to an international border on women's nutrition has not been investigated. Yet, Ethiopian borders are regularly affected by conflict and refugee flows, which might ultimately impact health. To investigate the impact of living close to borders in the nutritional status of women in Ethiopia, while considering other important covariates. Our analysis was based on the body mass index (BMI) of 6,334 adult women aged 20-49 years, obtained from the 2011 Ethiopian Demographic and Health Survey (EDHS). A Bayesian multilevel multinomial logistic regression analysis was used to capture the clustered structure of the data and the possible correlation that may exist within and between clusters. After controlling for potential confounders, women living close to borders (i.e. ≤100 km) in Ethiopia were 59% more likely to be underweight (posterior odds ratio [OR]=1.59; 95% credible interval [CrI]: 1.32-1.90) than their counterparts living far from the borders. This result was robust to different choices of border delineation (i.e. ≤50, ≤75, ≤125, and ≤150 km). Women from poor families, those who have no access to improved toilets, reside in lowland areas, and are Muslim, were independently associated with underweight. In contrast, more wealth, higher education, older age, access to improved toilets, being married, and living in urban or lowlands were independently associated with overweight. The problem of undernutrition among women in Ethiopia is most worrisome in the border areas. Targeted interventions to improve nutritional status in these areas, such as improved access to sanitation, economic and livelihood support, are recommended.

Quality and provider choice: a multinomial logit-least-squares model with selectivity.

PubMed Central

Haas-Wilson, D; Savoca, E

1990-01-01

A Federal Trade Commission survey of contact lens wearers is used to estimate a multinomial logit-least-squares model of the joint determination of provider choice and quality of care in the contact lens industry. The effect of personal and industry characteristics on a consumer's choice among three types of providers--opticians, ophthalmologists, and optometrists--is estimated via multinomial logit. The regression model of the quality of care has two features that distinguish it from previous work in the area. First, it uses an outcome rather than a structural or process measure of quality. Quality is measured as an index of the presence of seven potentially pathological eye conditions caused by poorly fitted lenses. Second, the model controls for possible selection bias that may arise from the fact that the sample observations on quality are generated by consumers' nonrandom choices of providers. The multinomial logit estimates of provider choice indicate that professional regulations limiting the commercial practices of optometrists shift demand for contact lens services away from optometrists toward ophthalmologists. Further, consumers are more likely to have their lenses fitted by opticians in states that require the licensing of opticians. The regression analysis of variations in quality across provider types shows a strong positive selection bias in the estimate of the quality of care received by consumers of ophthalmologists' services. Failure to control for this selection bias results in an overestimate of the quality of care provided by ophthalmologists. PMID:2312308

Modeling health survey data with excessive zero and K responses.

PubMed

Lin, Ting Hsiang; Tsai, Min-Hsiao

2013-04-30

Zero-inflated Poisson regression is a popular tool used to analyze data with excessive zeros. Although much work has already been performed to fit zero-inflated data, most models heavily depend on special features of the individual data. To be specific, this means that there is a sizable group of respondents who endorse the same answers making the data have peaks. In this paper, we propose a new model with the flexibility to model excessive counts other than zero, and the model is a mixture of multinomial logistic and Poisson regression, in which the multinomial logistic component models the occurrence of excessive counts, including zeros, K (where K is a positive integer) and all other values. The Poisson regression component models the counts that are assumed to follow a Poisson distribution. Two examples are provided to illustrate our models when the data have counts containing many ones and sixes. As a result, the zero-inflated and K-inflated models exhibit a better fit than the zero-inflated Poisson and standard Poisson regressions. Copyright © 2012 John Wiley & Sons, Ltd.

Latent profile analysis of regression-based norms demonstrates relationship of compounding MS symptom burden and negative work events.

PubMed

Frndak, Seth E; Smerbeck, Audrey M; Irwin, Lauren N; Drake, Allison S; Kordovski, Victoria M; Kunker, Katrina A; Khan, Anjum L; Benedict, Ralph H B

2016-10-01

We endeavored to clarify how distinct co-occurring symptoms relate to the presence of negative work events in employed multiple sclerosis (MS) patients. Latent profile analysis (LPA) was utilized to elucidate common disability patterns by isolating patient subpopulations. Samples of 272 employed MS patients and 209 healthy controls (HC) were administered neuroperformance tests of ambulation, hand dexterity, processing speed, and memory. Regression-based norms were created from the HC sample. LPA identified latent profiles using the regression-based z-scores. Finally, multinomial logistic regression tested for negative work event differences among the latent profiles. Four profiles were identified via LPA: a common profile (55%) characterized by slightly below average performance in all domains, a broadly low-performing profile (18%), a poor motor abilities profile with average cognition (17%), and a generally high-functioning profile (9%). Multinomial regression analysis revealed that the uniformly low-performing profile demonstrated a higher likelihood of reported negative work events. Employed MS patients with co-occurring motor, memory and processing speed impairments were most likely to report a negative work event, classifying them as uniquely at risk for job loss.

Categorical Data Analysis Using a Skewed Weibull Regression Model

NASA Astrophysics Data System (ADS)

Caron, Renault; Sinha, Debajyoti; Dey, Dipak; Polpo, Adriano

2018-03-01

In this paper, we present a Weibull link (skewed) model for categorical response data arising from binomial as well as multinomial model. We show that, for such types of categorical data, the most commonly used models (logit, probit and complementary log-log) can be obtained as limiting cases. We further compare the proposed model with some other asymmetrical models. The Bayesian as well as frequentist estimation procedures for binomial and multinomial data responses are presented in details. The analysis of two data sets to show the efficiency of the proposed model is performed.

The median hazard ratio: a useful measure of variance and general contextual effects in multilevel survival analysis.

PubMed

Austin, Peter C; Wagner, Philippe; Merlo, Juan

2017-03-15

Multilevel data occurs frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models (MLRM). MLRM incorporate cluster-specific random effects which allow one to partition the total individual variance into between-cluster variation and between-individual variation. Statistically, MLRM account for the dependency of the data within clusters and provide correct estimates of uncertainty around regression coefficients. Substantively, the magnitude of the effect of clustering provides a measure of the General Contextual Effect (GCE). When outcomes are binary, the GCE can also be quantified by measures of heterogeneity like the Median Odds Ratio (MOR) calculated from a multilevel logistic regression model. Time-to-event outcomes within a multilevel structure occur commonly in epidemiological and medical research. However, the Median Hazard Ratio (MHR) that corresponds to the MOR in multilevel (i.e., 'frailty') Cox proportional hazards regression is rarely used. Analogously to the MOR, the MHR is the median relative change in the hazard of the occurrence of the outcome when comparing identical subjects from two randomly selected different clusters that are ordered by risk. We illustrate the application and interpretation of the MHR in a case study analyzing the hazard of mortality in patients hospitalized for acute myocardial infarction at hospitals in Ontario, Canada. We provide R code for computing the MHR. The MHR is a useful and intuitive measure for expressing cluster heterogeneity in the outcome and, thereby, estimating general contextual effects in multilevel survival analysis. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd.

The median hazard ratio: a useful measure of variance and general contextual effects in multilevel survival analysis

PubMed Central

Wagner, Philippe; Merlo, Juan

2016-01-01

Multilevel data occurs frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models (MLRM). MLRM incorporate cluster‐specific random effects which allow one to partition the total individual variance into between‐cluster variation and between‐individual variation. Statistically, MLRM account for the dependency of the data within clusters and provide correct estimates of uncertainty around regression coefficients. Substantively, the magnitude of the effect of clustering provides a measure of the General Contextual Effect (GCE). When outcomes are binary, the GCE can also be quantified by measures of heterogeneity like the Median Odds Ratio (MOR) calculated from a multilevel logistic regression model. Time‐to‐event outcomes within a multilevel structure occur commonly in epidemiological and medical research. However, the Median Hazard Ratio (MHR) that corresponds to the MOR in multilevel (i.e., ‘frailty’) Cox proportional hazards regression is rarely used. Analogously to the MOR, the MHR is the median relative change in the hazard of the occurrence of the outcome when comparing identical subjects from two randomly selected different clusters that are ordered by risk. We illustrate the application and interpretation of the MHR in a case study analyzing the hazard of mortality in patients hospitalized for acute myocardial infarction at hospitals in Ontario, Canada. We provide R code for computing the MHR. The MHR is a useful and intuitive measure for expressing cluster heterogeneity in the outcome and, thereby, estimating general contextual effects in multilevel survival analysis. © 2016 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. PMID:27885709

Multilevel Modeling and Ordinary Least Squares Regression: How Comparable Are They?

ERIC Educational Resources Information Center

Huang, Francis L.

2018-01-01

Studies analyzing clustered data sets using both multilevel models (MLMs) and ordinary least squares (OLS) regression have generally concluded that resulting point estimates, but not the standard errors, are comparable with each other. However, the accuracy of the estimates of OLS models is important to consider, as several alternative techniques…

School Exits in the Milwaukee Parental Choice Program: Evidence of a Marketplace?

ERIC Educational Resources Information Center

Ford, Michael

2011-01-01

This article examines whether the large number of school exits from the Milwaukee school voucher program is evidence of a marketplace. Two logistic regression and multinomial logistic regression models tested the relation between the inability to draw large numbers of voucher students and the ability for a private school to remain viable. Data on…

An investigation on fatality of drivers in vehicle-fixed object accidents on expressways in China: Using multinomial logistic regression model.

PubMed

Peng, Yong; Peng, Shuangling; Wang, Xinghua; Tan, Shiyang

2018-06-01

This study aims to identify the effects of characteristics of vehicle, roadway, driver, and environment on fatality of drivers in vehicle-fixed object accidents on expressways in Changsha-Zhuzhou-Xiangtan district of Hunan province in China by developing multinomial logistic regression models. For this purpose, 121 vehicle-fixed object accidents from 2011-2017 are included in the modeling process. First, descriptive statistical analysis is made to understand the main characteristics of the vehicle-fixed object crashes. Then, 19 explanatory variables are selected, and correlation analysis of each two variables is conducted to choose the variables to be concluded. Finally, five multinomial logistic regression models including different independent variables are compared, and the model with best fitting and prediction capability is chosen as the final model. The results showed that the turning direction in avoiding fixed objects raised the possibility that drivers would die. About 64% of drivers died in the accident were found being ejected out of the car, of which 50% did not use a seatbelt before the fatal accidents. Drivers are likely to die when they encounter bad weather on the expressway. Drivers with less than 10 years of driving experience are more likely to die in these accidents. Fatigue or distracted driving is also a significant factor in fatality of drivers. Findings from this research provide an insight into reducing fatality of drivers in vehicle-fixed object accidents.

A Multilevel Assessment of Differential Item Functioning.

ERIC Educational Resources Information Center

Shen, Linjun

A multilevel approach was proposed for the assessment of differential item functioning and compared with the traditional logistic regression approach. Data from the Comprehensive Osteopathic Medical Licensing Examination for 2,300 freshman osteopathic medical students were analyzed. The multilevel approach used three-level hierarchical generalized…

What Is Wrong with ANOVA and Multiple Regression? Analyzing Sentence Reading Times with Hierarchical Linear Models

ERIC Educational Resources Information Center

Richter, Tobias

2006-01-01

Most reading time studies using naturalistic texts yield data sets characterized by a multilevel structure: Sentences (sentence level) are nested within persons (person level). In contrast to analysis of variance and multiple regression techniques, hierarchical linear models take the multilevel structure of reading time data into account. They…

Computational Tools for Probing Interactions in Multiple Linear Regression, Multilevel Modeling, and Latent Curve Analysis

ERIC Educational Resources Information Center

Preacher, Kristopher J.; Curran, Patrick J.; Bauer, Daniel J.

2006-01-01

Simple slopes, regions of significance, and confidence bands are commonly used to evaluate interactions in multiple linear regression (MLR) models, and the use of these techniques has recently been extended to multilevel or hierarchical linear modeling (HLM) and latent curve analysis (LCA). However, conducting these tests and plotting the…

Multilevel Modeling in Psychosomatic Medicine Research

PubMed Central

Myers, Nicholas D.; Brincks, Ahnalee M.; Ames, Allison J.; Prado, Guillermo J.; Penedo, Frank J.; Benedict, Catherine

2012-01-01

The primary purpose of this manuscript is to provide an overview of multilevel modeling for Psychosomatic Medicine readers and contributors. The manuscript begins with a general introduction to multilevel modeling. Multilevel regression modeling at two-levels is emphasized because of its prevalence in psychosomatic medicine research. Simulated datasets based on some core ideas from the Familias Unidas effectiveness study are used to illustrate key concepts including: communication of model specification, parameter interpretation, sample size and power, and missing data. Input and key output files from Mplus and SAS are provided. A cluster randomized trial with repeated measures (i.e., three-level regression model) is then briefly presented with simulated data based on some core ideas from a cognitive behavioral stress management intervention in prostate cancer. PMID:23107843

Estimating multilevel logistic regression models when the number of clusters is low: a comparison of different statistical software procedures.

PubMed

Austin, Peter C

2010-04-22

Multilevel logistic regression models are increasingly being used to analyze clustered data in medical, public health, epidemiological, and educational research. Procedures for estimating the parameters of such models are available in many statistical software packages. There is currently little evidence on the minimum number of clusters necessary to reliably fit multilevel regression models. We conducted a Monte Carlo study to compare the performance of different statistical software procedures for estimating multilevel logistic regression models when the number of clusters was low. We examined procedures available in BUGS, HLM, R, SAS, and Stata. We found that there were qualitative differences in the performance of different software procedures for estimating multilevel logistic models when the number of clusters was low. Among the likelihood-based procedures, estimation methods based on adaptive Gauss-Hermite approximations to the likelihood (glmer in R and xtlogit in Stata) or adaptive Gaussian quadrature (Proc NLMIXED in SAS) tended to have superior performance for estimating variance components when the number of clusters was small, compared to software procedures based on penalized quasi-likelihood. However, only Bayesian estimation with BUGS allowed for accurate estimation of variance components when there were fewer than 10 clusters. For all statistical software procedures, estimation of variance components tended to be poor when there were only five subjects per cluster, regardless of the number of clusters.

Workplace social capital and co-occurrence of lifestyle risk factors: the Finnish Public Sector Study.

PubMed

Väänänen, A; Kouvonen, A; Kivimäki, M; Oksanen, T; Elovainio, M; Virtanen, M; Pentti, J; Vahtera, J

2009-07-01

The aim of this prospective study was to examine the link between individual and ecological workplace social capital and the co-occurrence of adverse lifestyle risk factors such as smoking, heavy drinking, physical inactivity and overweight. Data on 25 897 female and 5476 male public sector employees were analysed. Questionnaire surveys conducted in 2000-2002 (baseline) and 2004-2005 (follow-up) were used to assess workplace social capital, lifestyle risk factors and other characteristics. Multilevel multinomial logistic regression analysis was used to examine associations between individual and ecological social capital and the co-occurrence of lifestyle risk factors. In the cross-sectional analysis adjusted for age, sex, marital status and employer, low social capital at work at both the individual and ecological level was associated with at least a 1.3 times higher odds of having more than two lifestyle risk factors versus having no risk factors. Similar associations were found in the prospective setting. However, additional adjustment for the co-occurrence of risk factors and socioeconomic status at baseline attenuated the result to non-significant. Social capital at work seems to be associated with a lowered risk of co-occurrence of multiple lifestyle risk factors but does not clearly predict the future risk of this co-occurrence.

Emotional Reactions to Stress among Adolescent Boys and Girls: An Examination of the Mediating Mechanisms Proposed by General Strain Theory

ERIC Educational Resources Information Center

Sigfusdottir, Inga-Dora; Silver, Eric

2009-01-01

This study examines the effects of negative life events on anger and depressed mood among a sample of 7,758 Icelandic adolescents, measured as part of the National Survey of Icelandic Adolescents (Thorlindsson, Sigfusdottir, Bernburg, & Halldorsson, 1998). Using multiple linear regression and multinomial logit regression, we find that (a)…

Arsenic exposure and oral cavity lesions in Bangladesh.

PubMed

Syed, Emdadul H; Melkonian, Stephanie; Poudel, Krishna C; Yasuoka, Junko; Otsuka, Keiko; Ahmed, Alauddin; Islam, Tariqul; Parvez, Faruque; Slavkovich, Vesna; Graziano, Joseph H; Ahsan, Habibul; Jimba, Masamine

2013-01-01

To evaluate the relationship between arsenic exposure and oral cavity lesions among an arsenic-exposed population in Bangladesh. We carried out an analysis utilizing the baseline data of the Health Effects of Arsenic Exposure Longitudinal Study, which is an ongoing population-based cohort study to investigate health outcomes associated with arsenic exposure via drinking water in Araihazar, Bangladesh. We used multinomial regression models to estimate the risk of oral cavity lesions. Participants with high urinary arsenic levels (286.1 to 5000.0 μg/g) were more likely to develop arsenical lesions of the gums (multinomial odds ratio = 2.90; 95% confidence interval, 1.11 to 7.54), and tongue (multinomial odds ratio = 2.79; 95% confidence interval, 1.51 to 5.15), compared with those with urinary arsenic levels of 7.0 to 134.0 μg/g. Higher level of arsenic exposure was positively associated with increased arsenical lesions of the gums and tongue.

On the Usefulness of a Multilevel Logistic Regression Approach to Person-Fit Analysis

ERIC Educational Resources Information Center

Conijn, Judith M.; Emons, Wilco H. M.; van Assen, Marcel A. L. M.; Sijtsma, Klaas

2011-01-01

The logistic person response function (PRF) models the probability of a correct response as a function of the item locations. Reise (2000) proposed to use the slope parameter of the logistic PRF as a person-fit measure. He reformulated the logistic PRF model as a multilevel logistic regression model and estimated the PRF parameters from this…

Using multilevel modeling to assess case-mix adjusters in consumer experience surveys in health care.

PubMed

Damman, Olga C; Stubbe, Janine H; Hendriks, Michelle; Arah, Onyebuchi A; Spreeuwenberg, Peter; Delnoij, Diana M J; Groenewegen, Peter P

2009-04-01

Ratings on the quality of healthcare from the consumer's perspective need to be adjusted for consumer characteristics to ensure fair and accurate comparisons between healthcare providers or health plans. Although multilevel analysis is already considered an appropriate method for analyzing healthcare performance data, it has rarely been used to assess case-mix adjustment of such data. The purpose of this article is to investigate whether multilevel regression analysis is a useful tool to detect case-mix adjusters in consumer assessment of healthcare. We used data on 11,539 consumers from 27 Dutch health plans, which were collected using the Dutch Consumer Quality Index health plan instrument. We conducted multilevel regression analyses of consumers' responses nested within health plans to assess the effects of consumer characteristics on consumer experience. We compared our findings to the results of another methodology: the impact factor approach, which combines the predictive effect of each case-mix variable with its heterogeneity across health plans. Both multilevel regression and impact factor analyses showed that age and education were the most important case-mix adjusters for consumer experience and ratings of health plans. With the exception of age, case-mix adjustment had little impact on the ranking of health plans. On both theoretical and practical grounds, multilevel modeling is useful for adequate case-mix adjustment and analysis of performance ratings.

Grouped gene selection and multi-classification of acute leukemia via new regularized multinomial regression.

PubMed

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.

Comparing methods of analysing datasets with small clusters: case studies using four paediatric datasets.

PubMed

Marston, Louise; Peacock, Janet L; Yu, Keming; Brocklehurst, Peter; Calvert, Sandra A; Greenough, Anne; Marlow, Neil

2009-07-01

Studies of prematurely born infants contain a relatively large percentage of multiple births, so the resulting data have a hierarchical structure with small clusters of size 1, 2 or 3. Ignoring the clustering may lead to incorrect inferences. The aim of this study was to compare statistical methods which can be used to analyse such data: generalised estimating equations, multilevel models, multiple linear regression and logistic regression. Four datasets which differed in total size and in percentage of multiple births (n = 254, multiple 18%; n = 176, multiple 9%; n = 10 098, multiple 3%; n = 1585, multiple 8%) were analysed. With the continuous outcome, two-level models produced similar results in the larger dataset, while generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) produced divergent estimates using the smaller dataset. For the dichotomous outcome, most methods, except generalised least squares multilevel modelling (ML GH 'xtlogit' in Stata) gave similar odds ratios and 95% confidence intervals within datasets. For the continuous outcome, our results suggest using multilevel modelling. We conclude that generalised least squares multilevel modelling (ML GLS 'xtreg' in Stata) and maximum likelihood multilevel modelling (ML MLE 'xtmixed' in Stata) should be used with caution when the dataset is small. Where the outcome is dichotomous and there is a relatively large percentage of non-independent data, it is recommended that these are accounted for in analyses using logistic regression with adjusted standard errors or multilevel modelling. If, however, the dataset has a small percentage of clusters greater than size 1 (e.g. a population dataset of children where there are few multiples) there appears to be less need to adjust for clustering.

Multilevel regression analyses to investigate the relationship between two variables over time: examining the longitudinal association between intrusion and avoidance.

PubMed

Suvak, Michael K; Walling, Sherry M; Iverson, Katherine M; Taft, Casey T; Resick, Patricia A

2009-12-01

Multilevel modeling is a powerful and flexible framework for analyzing nested data structures (e.g., repeated measures or longitudinal designs). The authors illustrate a series of multilevel regression procedures that can be used to elucidate the nature of the relationship between two variables across time. The goal is to help trauma researchers become more aware of the utility of multilevel modeling as a tool for increasing the field's understanding of posttraumatic adaptation. These procedures are demonstrated by examining the relationship between two posttraumatic symptoms, intrusion and avoidance, across five assessment points in a sample of rape and robbery survivors (n = 286). Results revealed that changes in intrusion were highly correlated with changes in avoidance over the 18-month posttrauma period.

New machine-learning algorithms for prediction of Parkinson's disease

NASA Astrophysics Data System (ADS)

Mandal, Indrajit; Sairam, N.

2014-03-01

This article presents an enhanced prediction accuracy of diagnosis of Parkinson's disease (PD) to prevent the delay and misdiagnosis of patients using the proposed robust inference system. New machine-learning methods are proposed and performance comparisons are based on specificity, sensitivity, accuracy and other measurable parameters. The robust methods of treating Parkinson's disease (PD) includes sparse multinomial logistic regression, rotation forest ensemble with support vector machines and principal components analysis, artificial neural networks, boosting methods. A new ensemble method comprising of the Bayesian network optimised by Tabu search algorithm as classifier and Haar wavelets as projection filter is used for relevant feature selection and ranking. The highest accuracy obtained by linear logistic regression and sparse multinomial logistic regression is 100% and sensitivity, specificity of 0.983 and 0.996, respectively. All the experiments are conducted over 95% and 99% confidence levels and establish the results with corrected t-tests. This work shows a high degree of advancement in software reliability and quality of the computer-aided diagnosis system and experimentally shows best results with supportive statistical inference.

A general equation to obtain multiple cut-off scores on a test from multinomial logistic regression.

PubMed

Bersabé, Rosa; Rivas, Teresa

2010-05-01

The authors derive a general equation to compute multiple cut-offs on a total test score in order to classify individuals into more than two ordinal categories. The equation is derived from the multinomial logistic regression (MLR) model, which is an extension of the binary logistic regression (BLR) model to accommodate polytomous outcome variables. From this analytical procedure, cut-off scores are established at the test score (the predictor variable) at which an individual is as likely to be in category j as in category j+1 of an ordinal outcome variable. The application of the complete procedure is illustrated by an example with data from an actual study on eating disorders. In this example, two cut-off scores on the Eating Attitudes Test (EAT-26) scores are obtained in order to classify individuals into three ordinal categories: asymptomatic, symptomatic and eating disorder. Diagnoses were made from the responses to a self-report (Q-EDD) that operationalises DSM-IV criteria for eating disorders. Alternatives to the MLR model to set multiple cut-off scores are discussed.

Application of Hierarchical Linear Models/Linear Mixed-Effects Models in School Effectiveness Research

ERIC Educational Resources Information Center

Ker, H. W.

2014-01-01

Multilevel data are very common in educational research. Hierarchical linear models/linear mixed-effects models (HLMs/LMEs) are often utilized to analyze multilevel data nowadays. This paper discusses the problems of utilizing ordinary regressions for modeling multilevel educational data, compare the data analytic results from three regression…

Detecting a Change in School Performance: A Bayesian Analysis for a Multilevel Join Point Problem. CSE Technical Report 542.

ERIC Educational Resources Information Center

Thum, Yeow Meng; Bhattacharya, Suman Kumar

To better describe individual behavior within a system, this paper uses a sample of longitudinal test scores from a large urban school system to consider hierarchical Bayes estimation of a multilevel linear regression model in which each individual regression slope of test score on time switches at some unknown point in time, "kj."…

A spatially filtered multilevel model to account for spatial dependency: application to self-rated health status in South Korea

PubMed Central

2014-01-01

Background This study aims to suggest an approach that integrates multilevel models and eigenvector spatial filtering methods and apply it to a case study of self-rated health status in South Korea. In many previous health-related studies, multilevel models and single-level spatial regression are used separately. However, the two methods should be used in conjunction because the objectives of both approaches are important in health-related analyses. The multilevel model enables the simultaneous analysis of both individual and neighborhood factors influencing health outcomes. However, the results of conventional multilevel models are potentially misleading when spatial dependency across neighborhoods exists. Spatial dependency in health-related data indicates that health outcomes in nearby neighborhoods are more similar to each other than those in distant neighborhoods. Spatial regression models can address this problem by modeling spatial dependency. This study explores the possibility of integrating a multilevel model and eigenvector spatial filtering, an advanced spatial regression for addressing spatial dependency in datasets. Methods In this spatially filtered multilevel model, eigenvectors function as additional explanatory variables accounting for unexplained spatial dependency within the neighborhood-level error. The specification addresses the inability of conventional multilevel models to account for spatial dependency, and thereby, generates more robust outputs. Results The findings show that sex, employment status, monthly household income, and perceived levels of stress are significantly associated with self-rated health status. Residents living in neighborhoods with low deprivation and a high doctor-to-resident ratio tend to report higher health status. The spatially filtered multilevel model provides unbiased estimations and improves the explanatory power of the model compared to conventional multilevel models although there are no changes in the signs of parameters and the significance levels between the two models in this case study. Conclusions The integrated approach proposed in this paper is a useful tool for understanding the geographical distribution of self-rated health status within a multilevel framework. In future research, it would be useful to apply the spatially filtered multilevel model to other datasets in order to clarify the differences between the two models. It is anticipated that this integrated method will also out-perform conventional models when it is used in other contexts. PMID:24571639

[How to fit and interpret multilevel models using SPSS].

PubMed

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.

Covariate Selection for Multilevel Models with Missing Data

PubMed Central

Marino, Miguel; Buxton, Orfeu M.; Li, Yi

2017-01-01

Missing covariate data hampers variable selection in multilevel regression settings. Current variable selection techniques for multiply-imputed data commonly address missingness in the predictors through list-wise deletion and stepwise-selection methods which are problematic. Moreover, most variable selection methods are developed for independent linear regression models and do not accommodate multilevel mixed effects regression models with incomplete covariate data. We develop a novel methodology that is able to perform covariate selection across multiply-imputed data for multilevel random effects models when missing data is present. Specifically, we propose to stack the multiply-imputed data sets from a multiple imputation procedure and to apply a group variable selection procedure through group lasso regularization to assess the overall impact of each predictor on the outcome across the imputed data sets. Simulations confirm the advantageous performance of the proposed method compared with the competing methods. We applied the method to reanalyze the Healthy Directions-Small Business cancer prevention study, which evaluated a behavioral intervention program targeting multiple risk-related behaviors in a working-class, multi-ethnic population. PMID:28239457

Measures of clustering and heterogeneity in multilevel Poisson regression analyses of rates/count data

PubMed Central

Austin, Peter C.; Stryhn, Henrik; Leckie, George; Merlo, Juan

2017-01-01

Multilevel data occur frequently in many research areas like health services research and epidemiology. A suitable way to analyze such data is through the use of multilevel regression models. These models incorporate cluster‐specific random effects that allow one to partition the total variation in the outcome into between‐cluster variation and between‐individual variation. The magnitude of the effect of clustering provides a measure of the general contextual effect. When outcomes are binary or time‐to‐event in nature, the general contextual effect can be quantified by measures of heterogeneity like the median odds ratio or the median hazard ratio, respectively, which can be calculated from a multilevel regression model. Outcomes that are integer counts denoting the number of times that an event occurred are common in epidemiological and medical research. The median (incidence) rate ratio in multilevel Poisson regression for counts that corresponds to the median odds ratio or median hazard ratio for binary or time‐to‐event outcomes respectively is relatively unknown and is rarely used. The median rate ratio is the median relative change in the rate of the occurrence of the event when comparing identical subjects from 2 randomly selected different clusters that are ordered by rate. We also describe how the variance partition coefficient, which denotes the proportion of the variation in the outcome that is attributable to between‐cluster differences, can be computed with count outcomes. We illustrate the application and interpretation of these measures in a case study analyzing the rate of hospital readmission in patients discharged from hospital with a diagnosis of heart failure. PMID:29114926

National Economic Development and Disparities in Body Mass Index: A Cross-Sectional Study of Data from 38 Countries

PubMed Central

Neuman, Melissa; Kawachi, Ichiro; Gortmaker, Steven; Subramanian, SV.

2014-01-01

Background Increases in body mass index (BMI) and the prevalence of overweight in low- and middle income countries (LMICs) are often ascribed to changes in global trade patterns or increases in national income. These changes are likely to affect populations within LMICs differently based on their place of residence or socioeconomic status (SES). Objective Using nationally representative survey data from 38 countries and national economic indicators from the World Bank and other international organizations, we estimated ecological and multilevel models to assess the association between national levels of gross domestic product (GDP), foreign direct investment (FDI), and mean tariffs and BMI. Design We used linear regression to estimate the ecological association between average annual change in economic indicators and BMI, and multilevel linear or ordered multinomial models to estimate associations between national economic indicators and individual BMI or over- and underweight. We also included cross-level interaction terms to highlight differences in the association of BMI with national economic indicators by type of residence or socioeconomic status (SES). Results There was a positive but non-significant association of GDP and mean BMI. This positive association of GDP and BMI was greater among rural residents and the poor. There were no significant ecological associations between measures of trade openness and mean BMI, but FDI was positively associated with BMI among the poorest respondents and in rural areas and tariff levels were negatively associated with BMI among poor and rural respondents. Conclusion Measures of national income and trade openness have different associations with the BMI across populations within developing countries. These divergent findings underscore the complexity of the effects of development on health and the importance of considering how the health effects of “globalizing” economic and cultural trends are modified by individual-level wealth and residence. PMID:24919199

A Comparison of Methods for Detecting Differential Distractor Functioning

ERIC Educational Resources Information Center

Koon, Sharon

2010-01-01

This study examined the effectiveness of the odds-ratio method (Penfield, 2008) and the multinomial logistic regression method (Kato, Moen, & Thurlow, 2009) for measuring differential distractor functioning (DDF) effects in comparison to the standardized distractor analysis approach (Schmitt & Bleistein, 1987). Students classified as participating…

Predicting The Type Of Pregnancy Using Flexible Discriminate Analysis And Artificial Neural Networks: A Comparison Study

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

Hooman, A.; Mohammadzadeh, M

Some medical and epidemiological surveys have been designed to predict a nominal response variable with several levels. With regard to the type of pregnancy there are four possible states: wanted, unwanted by wife, unwanted by husband and unwanted by couple. In this paper, we have predicted the type of pregnancy, as well as the factors influencing it using three different models and comparing them. Regarding the type of pregnancy with several levels, we developed a multinomial logistic regression, a neural network and a flexible discrimination based on the data and compared their results using tow statistical indices: Surface under curvemore » (ROC) and kappa coefficient. Based on these tow indices, flexible discrimination proved to be a better fit for prediction on data in comparison to other methods. When the relations among variables are complex, one can use flexible discrimination instead of multinomial logistic regression and neural network to predict the nominal response variables with several levels in order to gain more accurate predictions.« less

Modeling Information Content Via Dirichlet-Multinomial Regression Analysis.

PubMed

Ferrari, Alberto

2017-01-01

Shannon entropy is being increasingly used in biomedical research as an index of complexity and information content in sequences of symbols, e.g. languages, amino acid sequences, DNA methylation patterns and animal vocalizations. Yet, distributional properties of information entropy as a random variable have seldom been the object of study, leading to researchers mainly using linear models or simulation-based analytical approach to assess differences in information content, when entropy is measured repeatedly in different experimental conditions. Here a method to perform inference on entropy in such conditions is proposed. Building on results coming from studies in the field of Bayesian entropy estimation, a symmetric Dirichlet-multinomial regression model, able to deal efficiently with the issue of mean entropy estimation, is formulated. Through a simulation study the model is shown to outperform linear modeling in a vast range of scenarios and to have promising statistical properties. As a practical example, the method is applied to a data set coming from a real experiment on animal communication.

The double burden of malnutrition in Indonesia: Social determinants and geographical variations.

PubMed

Hanandita, Wulung; Tampubolon, Gindo

2015-12-01

The presence of simultaneous under- and over-nutrition has been widely documented in low- and middle-income countries, but global nutritional research has seen only a few large-scale population studies from Indonesia. We investigate the social determinants as well as the geographical variations of under- and over-nutrition in Indonesia using the largest public health study ever conducted in the country, the National Basic Health Research 2007 (N=645,032). Multilevel multinomial logistic regression and quantile regression models are fitted to estimate the association between nutritional status and a number of socio-economic indicators at both the individual and district levels. We find that: (1) education and income reduce the odds of being underweight by 10-30% but at the same time increase those of overweight by 10-40%; (2) independent from the compositional effect of poverty, income inequality is detrimental to population health: a 0.1 increase in the Gini coefficient is associated with an 8-12% increase in the odds of an individual׳s being both under- and overweight; and (3) the effects that these determinants have upon nutritional status are not necessarily homogeneous along the continuum of body mass index. Equally important, our analysis reveals that there is substantial spatial clustering of areas with elevated risk of under- or over-nutrition across the 17,000-island archipelago. As of 2007, under-nutrition in Indonesia remains a 'disease of poverty', while over-nutrition is one of affluence. The income inequality accompanying Indonesia׳s economic growth may aggravate the dual burden of under- and over-nutrition. A more equitable economic policy and a policy that improves living standards may be effective for addressing the double burden.

The relation between indicators of low employment quality and attendance behavior in countries of the European Union.

PubMed

Janssens, Heidi; Braeckman, Lutgart; De Clercq, Bart; De Bacquer, Dirk; Clays, Els

2017-12-01

Previous research demonstrated an association between low employment quality and lower sickness absence, which may be explained by presenteeism. Therefore, this study aimed exploring the relation between three indicators of employment quality (long working hours, precarious employment, job insecurity) and attendance behavior. The association between employment quality and attendance behavior was investigated in 28.999 workers (mean age: 40.0 years, 53% males) of the fifth wave of the European Working Conditions Survey, using multilevel multinomial logistic regression analysis. Attendance behavior was operationalized as different combinations of sickness absence and presenteeism. Those working >48 h/week, had a higher risk to report presenteeism (with or without sickness absence). They had a lower risk to report sickness absence without presenteeism. Workers with a precarious contract had a lower risk to report absenteeism without presenteeism and the combination of both presenteeism and absenteeism. Finally, for workers perceiving job insecurity, the risk for presenteeism without sickness absence was significantly higher. Several indicators of low employment quality were associated with attendance behavior, suggesting a complex behavioral mechanism in workers facing low job quality employment. Therefore, policy makers are recommended to re-establish the indefinite contractual employment as the standard, avoiding long working hours. © The Author 2016. Published by Oxford University Press on behalf of Faculty of Public Health. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

Adverse Childhood Experiences and Alcohol Consumption in Midlife and Early Old-Age

PubMed Central

Leung, Jessica Pui Kei; Britton, Annie; Bell, Steven

2016-01-01

Aims To examine the individual and cumulative effects of adverse childhood experiences (ACEs) on alcohol consumption in midlife and early old-age, and the role of ACEs in 10-year drinking trajectories across midlife. Methods Data were from the Whitehall II study, a longitudinal British civil service-based cohort study (N = 7870, 69.5% male). Multinomial logistic regression was used to examine the individual and cumulative effects of ACEs on weekly alcohol consumption. Mixed-effect multilevel modelling was used to explore the relationship between ACEs and change in alcohol consumption longitudinally. Results Participants who were exposed to parental arguments/fights in childhood were 1.24 (95% CI 1.06, 1.45) times more likely to drink at hazardous levels in midlife (mean age 56 years) after controlling for covariates and other ACEs. For each additional exposure to an ACE, the risk of hazardous drinking versus moderate drinking was increased by 1.12 (95% CI 1.03, 1.21) after adjusting for sex, age, adult socio-economic status, ethnicity and marital status. No associations between ACEs and increased risk of hazardous drinking in early old-age (mean age 66 years) were found. In longitudinal analyses, ACEs did not significantly influence 10-year drinking trajectories across midlife. Conclusion The effect of exposure to parental arguments on hazardous drinking persists into midlife. PMID:26553290

Influence of municipal policy and individual characteristics on the use of informal and formal domestic help in the Netherlands.

PubMed

Marangos, Anna Maria; Waverijn, Geeke; de Klerk, Mirjam; Iedema, Jurjen; Groenewegen, Peter P

2018-05-24

The responsibility for care and social support in the Netherlands has been decentralized to the municipalities, on the assumption that they are able to organise care and social support more effectively and efficiently. Municipalities are responsible for offering citizens the social support they need. They have policy discretion to decide how and to what extent they encourage and support the use of informal help. This article explored whether the local policy focus on informal or formal help influences the actual take-up of domestic help. Data on 567 physically disabled people who use informal or formal help in the household were linked to local policy data in 167 municipalities. We performed multilevel multinomial regression analyses. Since we expected that local policy will have more influence on people with slight or moderate disabilities, cohabitees and people aged under 75, cross-level interaction terms were included between characteristics of local policy and of individuals. The findings reveal differences between municipalities in their policy on support and differences in the use of formal or informal support between municipalities. We found no relationship between local emphasis on informal help and the use of informal help. Possible explanations: some people have a small social network, people using informal help did not apply for municipality support or even do not know the possibility exists. Copyright © 2018 Elsevier B.V. All rights reserved.

Predictors of Early Termination in a University Counseling Training Clinic

ERIC Educational Resources Information Center

Lampropoulos, Georgios K.; Schneider, Mercedes K.; Spengler, Paul M.

2009-01-01

Despite the existence of counseling dropout research, there are limited predictive data for counseling in training clinics. Potential predictor variables were investigated in this archival study of 380 client files in a university counseling training clinic. Multinomial logistic regression, predictive discriminant analysis, and classification and…

Understanding Civic Identity in College

ERIC Educational Resources Information Center

Weerts, David J.; Cabrera, Alberto F.

2015-01-01

Past literature has examined ways in which college students adopt civic identities. However, little is known about characteristics of students that vary in their expression of these identities. Drawing on data from American College Testing (ACT), this study employs multinomial logistic regression to understand attributes of students who vary in…

Evaluating the Locational Attributes of Education Management Organizations (EMOs)

ERIC Educational Resources Information Center

Gulosino, Charisse; Miron, Gary

2017-01-01

This study uses logistic and multinomial logistic regression models to analyze neighborhood factors affecting EMO (Education Management Organization)-operated schools' locational attributes (using census tracts) in 41 states for the 2014-2015 school year. Our research combines market-based school reform, institutional theory, and resource…

Intergroup Relations and Predictors of Immigrant Experience

ERIC Educational Resources Information Center

Danso, Kofi; Lum, Terry

2013-01-01

Using survey data from 1,036 participants, which included 4 immigrant groups, we examined the factors that influence immigrants' experiences as they interact with nonimmigrant Americans. Logistic and multinomial regression results indicate that non-European immigrants were more likely to report negative experiences with Americans. The odds of…

The Role of Predictor Courses and Teams on Individual Student Success

ERIC Educational Resources Information Center

Baker-Eveleth, Lori Jo; O'Neill, Michele; Sisodiya, Sanjay R.

2014-01-01

Research suggests that diverse environments enhance conscious modes of thought, resulting in greater intellectual engagement and active thinking. Ordinal and multinomial logistic regression results indicate that accounting courses and business law classes are useful predictors of subsequent performance. Odds ratio estimates indicate that students…

Caregivers' Retirement Congruency: A Case for Caregiver Support

ERIC Educational Resources Information Center

Humble, Aine M.; Keefe, Janice M.; Auton, Greg M.

2012-01-01

Using the concept of "retirement congruency" (RC), which takes into account greater variation in retirement decisions (low, moderate, or high RC) than a dichotomous conceptualization (forced versus chosen), multinomial logistic regression was conducted on a sample of caregivers from the 2002 Canadian General Social Survey who were…

A social–contextual investigation of smoking among rural women: multi-level factors associated with smoking status and considerations for cessation.

PubMed

Nemeth, Julianna M; Thomson, Tiffany L; Lu, Bo; Peng, Juan; Krebs, Valdis; Doogan, Nathan J; Ferketich, Amy K; Post, Douglas M; Browning, Christopher R; Paskett, Electra D; Wewers, Mary E

2018-03-01

The social-contextual model of tobacco control and the potential mechanisms of the maintenance or cessation of smoking behavior among disadvantaged women, including rural residents, have yet to be comprehensively studied. The purpose of this study was to determine the association between selected individual, interpersonal, workplace, and neighborhood characteristics and smoking status among women in Appalachia, a US region whose residents experience a disproportionate prevalence of tobacco-related health disparities. These findings may assist in efforts to design and test scientifically valid tobacco control interventions for this and other disadvantaged populations. Women, 18 years of age and older, residing in three rural Ohio Appalachian counties, were recruited using a two-phase address-based sampling methodology for a cross-sectional interview-administered survey between August 2012 and October 2013 (N=408). Multinomial logistic regression was employed to determine associations between select multilevel factors (independent variables) and smoking status (dependent variable). The sample included 82 (20.1%) current smokers, 92 (22.5%) former smokers, and 234 (57.4%) women reporting never smoking (mean age 51.7 years). In the final multivariable multinomial logistic regression model, controlling for all other significant associations, constructs at multiple social-contextual levels were associated with current versus either former or never smoking. At the individual level, for every additional year in age, the odds of being a former or never smoker increased by 7% and 6% (odds ratio (OR) (95% confidence interval(CI)): 1.07 (1.0-1.11) and 1.06 (1.02-1.09)), respectively, as compared to the odds of being a current smoker. With regard to depression, for each one unit increase in the Center for Epidemiologic Studies Depression Scale score, the odds of being a former or never smoker were 5% and 7% lower (OR(95%CI): 0.95(0.91-0.999) and 0.93(0.88-0.98)), respectively. Five interpersonal factors were associated with smoking status. As the social influence injunctive norm score increased by one unit, indicating perception of smoking to be more acceptable, the odds of being a former or never smoker decreased by 23% and 30%, respectively. For every one unit increase in the social participation score, indicating past-year engagement in one additional activity type, the odds of being a former or never smoker increased by 17% and 36%, respectively. For every 10% increase in the percentage of social ties in the participant's advice network who smoked, the odds of being a former or never smoker were 24% and 28% less, respectively. For every 0.1 unit increase in the E/I index, indicating increasing homophily on smoking in one's social network, the odds of being a former or never smoker were 20% and 24% less, respectively, in the time network, and 18% and 20% less, respectively, in the advice network. At the neighborhood level, for every one unit increase in neighborhood cohesion score, indicating increasing cohesion, the odds of being a former smoker or never smoker were 12% and 14% less, respectively. These findings indicate that a social-contextual approach to tobacco control may be useful for narrowing a widening trajectory of smoking disparity for rural women. Interpersonal context, in particular, must be considered in the development of culturally targeted cessation interventions for Ohio Appalachian women.

Race and Unemployment: Labor Market Experiences of Black and White Men, 1968-1988.

ERIC Educational Resources Information Center

Wilson, Franklin D.; And Others

1995-01-01

Estimation of multinomial logistic regression models on a sample of unemployed workers suggested that persistently higher black unemployment is due to differential access to employment opportunities by region, occupational placement, labor market segmentation, and discrimination. The racial gap in unemployment is greatest for college-educated…

Predicting the Frequency of Senior Center Attendance.

ERIC Educational Resources Information Center

Miner, Sonia; And Others

1993-01-01

Used data from 1984 Supplement on Aging of the National Health Interview Survey to examine frequency of senior center attendance. Estimated multinomial logistic regression model to distinguish between persons who rarely, sometimes, and frequently attend. Found that more frequent users are older. Greater frequency was associated with lower income…

Support vector machines classifiers of physical activities in preschoolers

USDA-ARS?s Scientific Manuscript database

The goal of this study is to develop, test, and compare multinomial logistic regression (MLR) and support vector machines (SVM) in classifying preschool-aged children physical activity data acquired from an accelerometer. In this study, 69 children aged 3-5 years old were asked to participate in a s...

Bullying and PTSD Symptoms

ERIC Educational Resources Information Center

Idsoe, Thormod; Dyregrov, Atle; Idsoe, Ella Cosmovici

2012-01-01

PTSD symptoms related to school bullying have rarely been investigated, and never in national samples. We used data from a national survey to investigate this among students from grades 8 and 9 (n = 963). The prevalence estimates of exposure to bullying were within the range of earlier research findings. Multinomial logistic regression showed that…

Diversity and Educational Benefits: Moving Beyond Self-Reported Questionnaire Data

ERIC Educational Resources Information Center

Herzog, Serge

2007-01-01

Effects of ethnic/racial diversity among students and faculty on cognitive growth of undergraduate students are estimated via a series of hierarchical linear and multinomial logistic regression models. Using objective measures of compositional, curricular, and interactional diversity based on actuarial course enrollment records of over 6,000…

Poverty and Material Hardship in Grandparent-Headed Households

ERIC Educational Resources Information Center

Baker, Lindsey A.; Mutchler, Jan E.

2010-01-01

Using the 2001 Survey of Income and Program Participation, the current study examines poverty and material hardship among children living in 3-generation (n = 486), skipped-generation (n = 238), single-parent (n = 2,076), and 2-parent (n = 6,061) households. Multinomial and logistic regression models indicated that children living in…

Victimization and Health Risk Factors among Weapon-Carrying Youth

ERIC Educational Resources Information Center

Stayton, Catherine; McVeigh, Katharine H.; Olson, E. Carolyn; Perkins, Krystal; Kerker, Bonnie D.

2011-01-01

Objective: To compare health risks of 2 subgroups of weapon carriers: victimized and nonvictimized youth. Methods: 2003-2007 NYC Youth Risk Behavior Surveys were analyzed using bivariate analyses and multinomial logistic regression. Results: Among NYC teens, 7.5% reported weapon carrying without victimization; 6.9% reported it with victimization.…

In-State Tuition Policies for Undocumented Youth

ERIC Educational Resources Information Center

Vargas, Edward D.

2011-01-01

This article is an investigation into why U.S. states have enacted, banned, or continued with the status quo regarding in-state tuition policies for unauthorized youth. Using data from multiple government and nonprofit sources, a series of multinomial logistic regressions are estimated to explain the determinants of state behavior across the…

Predicting multi-level drug response with gene expression profile in multiple myeloma using hierarchical ordinal regression.

PubMed

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.

Brief Report: Association of Myositis Autoantibodies, Clinical Features, and Environmental Exposures at Illness Onset With Disease Course in Juvenile Myositis.

PubMed

Habers, G Esther A; Huber, Adam M; Mamyrova, Gulnara; Targoff, Ira N; O'Hanlon, Terrance P; Adams, Sharon; Pandey, Janardan P; Boonacker, Chantal; van Brussel, Marco; Miller, Frederick W; van Royen-Kerkhof, Annet; Rider, Lisa G

2016-03-01

To identify early factors associated with disease course in patients with juvenile idiopathic inflammatory myopathies (IIMs). Univariable and multivariable multinomial logistic regression analyses were performed in a large juvenile IIM registry (n = 365) and included demographic characteristics, early clinical features, serum muscle enzyme levels, myositis autoantibodies, environmental exposures, and immunogenetic polymorphisms. Multivariable associations with chronic or polycyclic courses compared to a monocyclic course included myositis-specific autoantibodies (multinomial odds ratio [OR] 4.2 and 2.8, respectively), myositis-associated autoantibodies (multinomial OR 4.8 and 3.5), and a documented infection within 6 months of illness onset (multinomial OR 2.5 and 4.7). A higher overall clinical symptom score at diagnosis was associated with chronic or monocyclic courses compared to a polycyclic course. Furthermore, severe illness onset was associated with a chronic course compared to monocyclic or polycyclic courses (multinomial OR 2.1 and 2.6, respectively), while anti-p155/140 autoantibodies were associated with chronic or polycyclic courses compared to a monocyclic course (multinomial OR 3.9 and 2.3, respectively). Additional univariable associations of a chronic course compared to a monocyclic course included photosensitivity, V-sign or shawl sign rashes, and cuticular overgrowth (OR 2.2-3.2). The mean ultraviolet index and highest ultraviolet index in the month before diagnosis were associated with a chronic course compared to a polycyclic course in boys (OR 1.5 and 1.3), while residing in the Northwest was less frequently associated with a chronic course (OR 0.2). Our findings indicate that myositis autoantibodies, in particular anti-p155/140, and a number of early clinical features and environmental exposures are associated with a chronic course in patients with juvenile IIM. These findings suggest that early factors, which are associated with poorer outcomes in juvenile IIM, can be identified. © 2016, American College of Rheumatology.

Does Group-Level Commitment Predict Employee Well-Being?: A Prospective Analysis.

PubMed

Clausen, Thomas; Christensen, Karl Bang; Nielsen, Karina

2015-11-01

To investigate the links between group-level affective organizational commitment (AOC) and individual-level psychological well-being, self-reported sickness absence, and sleep disturbances. A total of 5085 care workers from 301 workgroups in the Danish eldercare services participated in both waves of the study (T1 [2005] and T2 [2006]). The three outcomes were analyzed using linear multilevel regression analysis, multilevel Poisson regression analysis, and multilevel logistic regression analysis, respectively. Group-level AOC (T1) significantly predicted individual-level psychological well-being, self-reported sickness absence, and sleep disturbances (T2). The association between group-level AOC (T1) and psychological well-being (T2) was fully mediated by individual-level AOC (T1), and the associations between group-level AOC (T1) and self-reported sickness absence and sleep disturbances (T2) were partially mediated by individual-level AOC (T1). Group-level AOC is an important predictor of employee well-being in contemporary health care organizations.

Bivariate categorical data analysis using normal linear conditional multinomial probability model.

PubMed

Sun, Bingrui; Sutradhar, Brajendra

2015-02-10

Bivariate multinomial data such as the left and right eyes retinopathy status data are analyzed either by using a joint bivariate probability model or by exploiting certain odds ratio-based association models. However, the joint bivariate probability model yields marginal probabilities, which are complicated functions of marginal and association parameters for both variables, and the odds ratio-based association model treats the odds ratios involved in the joint probabilities as 'working' parameters, which are consequently estimated through certain arbitrary 'working' regression models. Also, this later odds ratio-based model does not provide any easy interpretations of the correlations between two categorical variables. On the basis of pre-specified marginal probabilities, in this paper, we develop a bivariate normal type linear conditional multinomial probability model to understand the correlations between two categorical variables. The parameters involved in the model are consistently estimated using the optimal likelihood and generalized quasi-likelihood approaches. The proposed model and the inferences are illustrated through an intensive simulation study as well as an analysis of the well-known Wisconsin Diabetic Retinopathy status data. Copyright © 2014 John Wiley & Sons, Ltd.

Individual-Level Influences on Perceptions of Neighborhood Disorder: A Multilevel Analysis

ERIC Educational Resources Information Center

Latkin, Carl A.; German, Danielle; Hua, Wei; Curry, Aaron D.

2009-01-01

Health outcomes are associated with aggregate neighborhood measures and individual neighborhood perceptions. In this study, the authors sought to delineate individual, social network, and spatial factors that may influence perceptions of neighborhood disorder. Multilevel regression analysis showed that neighborhood perceptions were more negative…

Using Multilevel Modeling in Language Assessment Research: A Conceptual Introduction

ERIC Educational Resources Information Center

Barkaoui, Khaled

2013-01-01

This article critiques traditional single-level statistical approaches (e.g., multiple regression analysis) to examining relationships between language test scores and variables in the assessment setting. It highlights the conceptual, methodological, and statistical problems associated with these techniques in dealing with multilevel or nested…

Registered dietitian's personal beliefs and characteristics predict their teaching or intention to teach fresh vegetable food safety.

PubMed

Casagrande, Gina; LeJeune, Jeffery; Belury, Martha A; Medeiros, Lydia C

2011-04-01

The Theory of Planned Behavior was used to determine if dietitians personal characteristics and beliefs about fresh vegetable food safety predict whether they currently teach, intend to teach, or neither currently teach nor intend to teach food safety information to their clients. Dietitians who participated in direct client education responded to this web-based survey (n=327). The survey evaluated three independent belief variables: Subjective Norm, Attitudes, and Perceived Behavioral Control. Spearman rho correlations were completed to determine variables that correlated best with current teaching behavior. Multinomial logistical regression was conducted to determine if the belief variables significantly predicted dietitians teaching behavior. Binary logistic regression was used to determine which independent variable was the better predictor of whether dietitians currently taught. Controlling for age, income, education, and gender, the multinomial logistical regression was significant. Perceived behavioral control was the best predictor of whether a dietitian currently taught fresh vegetable food safety. Factors affecting whether dietitians currently taught were confidence in fresh vegetable food safety knowledge, being socially influenced, and a positive attitude toward the teaching behavior. These results validate the importance of teaching food safety effectively and may be used to create more informed food safety curriculum for dietitians. Copyright © 2011 Elsevier Ltd. All rights reserved.

College on Credit: A Multilevel Analysis of Student Loan Default

ERIC Educational Resources Information Center

Hillman, Nicholas W.

2014-01-01

This study updates and expands the literature on student loan default. By applying multilevel regression to the Beginning Postsecondary Students survey, four key findings emerge. First, attending proprietary institutions is strongly associated with default, even after accounting for students' socioeconomic and academic backgrounds. Second,…

Which Kindergarten Children Are at Greatest Risk for Attention-Deficit/Hyperactivity and Conduct Disorder Symptomatology as Adolescents?

ERIC Educational Resources Information Center

Morgan, Paul L.; Li, Hui; Cook, Michael; Farkas, George; Hillemeier, Marianne M.; Lin, Yu-chu

2016-01-01

We sought to identify which kindergarten children are simultaneously at risk of moderate or severe symptomatology in both attention-deficit/hyperactivity disorder (ADHD) and conduct disorder (CD) as adolescents. These risk factor estimates have not been previously available. We conducted multinomial logistic regression analyses of multiinformant…

Foreign Diploma versus Immigrant Background: Determinants of Labour Market Success or Failure?

ERIC Educational Resources Information Center

Storen, Liv Anne; Wiers-Jenssen, Jannecke

2010-01-01

This article compares the labour market situation of graduates with different types of international background. The authors look at four groups of graduates: immigrants and ethnic Norwegians graduated in Norway and immigrants and ethnic Norwegians graduated abroad. By employing multinomial logistic regression analyses the authors find that ethnic…

Motivations and Benefits for Attaining HR Certifications

ERIC Educational Resources Information Center

Lester, Scott W.; Dwyer, Dale J.

2012-01-01

Purpose: The aim of this paper is to examine the motivations and benefits for pursuing or not pursuing the PHR and SPHR. Design/methodology/approach: Using a sample of 1,862 participants, the study used multinomial logistic and hierarchical linear regression to test six hypotheses. Findings: Participants pursuing SPHR were more likely to report…

School Climate: The Controllable and the Uncontrollable

ERIC Educational Resources Information Center

Sulak, Tracey N.

2018-01-01

A positive school climate impacts students by promoting positive relations among students, staff and faculty of the school. The current study used latent class analysis and multinomial regression with R3STEP to analyse patterns of negative behaviours in schools and test the association of these patterns with structural variables like school size,…

An Analysis of Losses to the Southern Commercial Timberland Base

Treesearch

Ian A. Munn; David Cleaves

1998-01-01

Demographic and physical factors influencing the conversion of commercial timberland iu the south to non-forestry uses between the last two Forest Inventory Analysis (FIA) surveys were investigated. GIS techniques linked Census data and FIA plot level data. Multinomial logit regression identified factors associated with losses to the timberland base. Conversion to...

Racial Threat and White Opposition to Bilingual Education in Texas

ERIC Educational Resources Information Center

Hempel, Lynn M.; Dowling, Julie A.; Boardman, Jason D.; Ellison, Christopher G.

2013-01-01

This study examines local contextual conditions that influence opposition to bilingual education among non-Hispanic Whites, net of individual-level characteristics. Data from the Texas Poll (N = 615) are used in conjunction with U.S. Census data to test five competing hypotheses using binomial and multinomial logistic regression models. Our…

Caste, Class, and Urbanization: The Shaping of Religious Community in Contemporary India

ERIC Educational Resources Information Center

Stroope, Samuel

2012-01-01

Building on the implications of qualitative work from India and urbanism theories, I aim to understand whether religious bonding social capital in contemporary India increases with greater urbanization and whether such increases are moderated by caste or social class position. Results from multinomial logistic regression on 1,417 Hindu respondents…

American Youths' Access to Substance Abuse Treatment: Does Type of Treatment Facility Matter?

ERIC Educational Resources Information Center

Lo, Celia C.; Cheng, Tyrone C.

2013-01-01

Using data from the 2007 National Survey on Drug Use and Health, this study examines whether several social exclusion and psychological factors affect adolescents' receipt of substance abuse treatment. Multinomial logistic regression techniques were used to analyze data. The study asked how the specified factors provide pathways to receipt of…

Primary Factors Related to Multiple Placements for Children in Out-of-Home Care

ERIC Educational Resources Information Center

Eggertsen, Lars

2008-01-01

Using an ecological framework, this study identified which factors related to out-of-home placements significantly influenced multiple placements for children in Utah during 2000, 2001, and 2002. Multinomial logistic regression statistical procedures and a geographical information system (GIS) were used to analyze the data. The final model…

Institutional Discharges and Subsequent Shelter Use among Unaccompanied Adults in New York City

ERIC Educational Resources Information Center

Metraux, Stephen; Byrne, Thomas; Culhane, Dennis P.

2010-01-01

This study empirically examines the link between homelessness and discharges from other institutions. An administrative record match was undertaken to determine rates of discharge from institutional care for 9,247 unaccompanied adult shelter users in New York City. Cluster analysis and multinomial logistic regression analysis was then used to…

Predicting Teacher Value-Added Results in Non-Tested Subjects Based on Confounding Variables: A Multinomial Logistic Regression

ERIC Educational Resources Information Center

Street, Nathan Lee

2017-01-01

Teacher value-added measures (VAM) are designed to provide information regarding teachers' causal impact on the academic growth of students while controlling for exogenous variables. While some researchers contend VAMs successfully and authentically measure teacher causality on learning, others suggest VAMs cannot adequately control for exogenous…

Profiles of Supportive Alumni: Donors, Volunteers, and Those Who "Do It All"

ERIC Educational Resources Information Center

Weerts, David J.; Ronca, Justin M.

2007-01-01

In the competitive marketplace of higher education, college and university alumni are increasingly called on to support their institutions in multiple ways: political advocacy, volunteerism, and charitable giving. Drawing on alumni survey data gathered from a large research extensive university, we employ a multinomial logistic regression model to…

Impact of Perceived Risk and Friend Influence on Alcohol and Marijuana Use among Students

ERIC Educational Resources Information Center

Merianos, Ashley L.; Rosen, Brittany L.; Montgomery, LaTrice; Barry, Adam E.; Smith, Matthew Lee

2017-01-01

We performed a secondary analysis of Adolescent Health Risk Behavior Survey data (N=937), examining associations between lifetime alcohol and marijuana use with intrapersonal (i.e., risk perceptions) and interpersonal (e.g., peer approval and behavior) factors. Multinomial and binary logistic regression analyses contend students reporting lifetime…

Predicting College Success: Achievement, Demographic, and Psychosocial Predictors of First-Semester College Grade Point Average

ERIC Educational Resources Information Center

Saltonstall, Margot

2013-01-01

This study seeks to advance and expand research on college student success. Using multinomial logistic regression analysis, the study investigates the contribution of psychosocial variables above and beyond traditional achievement and demographic measures to predicting first-semester college grade point average (GPA). It also investigates if…

Profiles of internalizing and externalizing symptoms associated with bullying victimization.

PubMed

Eastman, Meridith; Foshee, Vangie; Ennett, Susan; Sotres-Alvarez, Daniela; Reyes, H Luz McNaughton; Faris, Robert; North, Kari

2018-06-01

This study identified profiles of internalizing (anxiety and depression) and externalizing (delinquency and violence against peers) symptoms among bullying victims and examined associations between bullying victimization characteristics and profile membership. The sample consisted of 1196 bullying victims in grades 8-10 (M age  = 14.4, SD = 1.01) who participated in The Context Study in three North Carolina counties in Fall 2003. Five profiles were identified using latent profile analysis: an asymptomatic profile and four profiles capturing combinations of internalizing and externalizing symptoms. Associations between bullying characteristics and membership in symptom profiles were tested using multinomial logistic regression. More frequent victimization increased odds of membership in the two high internalizing profiles compared to the asymptomatic profile. Across all multinomial logistic regression models, when the high internalizing, high externalizing profile was the reference category, adolescents who received any type of bullying (direct, indirect, or dual) were more likely to be in this category than any others. Copyright © 2018 The Foundation for Professionals in Services for Adolescents. Published by Elsevier Ltd. All rights reserved.

Prevalence of and risk factors for depressive symptoms among people living with HIV/AIDS receiving antiretroviral treatment in Wuhan, China: a short report.

PubMed

Rong, Hu; Nianhua, Xie; Jun, Xu; Lianguo, Ruan; Si, Wu; Sheng, Wei; Heng, Guo; Xia, Wang

2017-12-01

We aimed to explore the prevalence of and risk factors for depressive symptoms (DS) among people living with HIV/AIDS (PLWHA) receiving antiretroviral treatment (ART) in Wuhan, Hubei, China. A cross-sectional study evaluating adult PLWHA receiving ART in nine designated clinical hospitals was conducted from October to December 2015. The validated Beck Depression Inventory (BDI) was used to assess DS in eligible participants. Socio-demographical, epidemiological and clinical data were directly extracted from the case reporting database of the China HIV/AIDS Information Network. Multinomial regression analysis was used to explore the risk factors for DS. 394 participants were finally included in all analyses. 40.3% were found to have DS with 13.7% having mild DS and 26.6% having moderate to severe DS. The results of multinomial regression analysis suggested that being married or living with a partner, recent experience of ART-related side effects, and/or history of HCV infection were positively associated with mild DS, while increasing age was positively associated with moderate to severe DS.

The perception of the relationship between environment and health according to data from Italian Behavioural Risk Factor Surveillance System (PASSI).

PubMed

Sampaolo, Letizia; Tommaso, Giulia; Gherardi, Bianca; Carrozzi, Giuliano; Freni Sterrantino, Anna; Ottone, Marta; Goldoni, Carlo Alberto; Bertozzi, Nicoletta; Scaringi, Meri; Bolognesi, Lara; Masocco, Maria; Salmaso, Stefania; Lauriola, Paolo

2017-01-01

"OBJECTIVES: to identify groups of people in relation to the perception of environmental risk and to assess the main characteristics using data collected in the environmental module of the surveillance network Italian Behavioral Risk Factor Surveillance System (PASSI). perceptive profiles were identified using a latent class analysis; later they were included as outcome in multinomial logistic regression models to assess the association between environmental risk perception and demographic, health, socio-economic and behavioural variables. the latent class analysis allowed to split the sample in "worried", "indifferent", and "positive" people. The multinomial logistic regression model showed that the "worried" profile typically includes people of Italian nationality, living in highly urbanized areas, with a high level of education, and with economic difficulties; they pay special attention to their own health and fitness, but they have a negative perception of their own psychophysical state. the application of advanced statistical analysis enable to appraise PASSI data in order to characterize the perception of environmental risk, making the planning of interventions related to risk communication possible. ".

Socio-economic determinants of severe and moderate stunting among under-five children of rural Bangladesh.

PubMed

Mostafa, Kamal S M

2011-04-01

Malnutrition among under-five children is a chronic problem in developing countries. This study explores the socio-economic determinants of severe and moderate stunting among under-five children of rural Bangladesh. The study used data from the 2007 Bangladesh Demographic and Health Survey. Cross-sectional and multinomial logistic regression analyses were used to assess the effect of the socio-demographic variables on moderate and severe stunting over normal among the children. Findings revealed that over two-fifths of the children were stunted, of which 26.3% were moderately stunted and 15.1% were severely stunted. The multivariate multinomial logistic regression analysis yielded significantly increased risk of severe stunting (OR=2.53, 95% CI=1.34-4.79) and moderate stunting (OR=2.37, 95% CI=1.47-3.83) over normal among children with a thinner mother. Region, father's education, toilet facilities, child's age, birth order of children and wealth index were also important determinants of children's nutritional status. Development and poverty alleviation programmes should focus on the disadvantaged rural segments of people to improve their nutritional status.

Dental health services utilization and associated factors in children 6 to 12 years old in a low-income country.

PubMed

Medina-Solis, Carlo Eduardo; Maupomé, Gerardo; del Socorro, Herrera Miriam; Pérez-Núñez, Ricardo; Avila-Burgos, Leticia; Lamadrid-Figueroa, Hector

2008-01-01

To determine the factors associated with the dental health services utilization among children ages 6 to 12 in León, Nicaragua. A cross-sectional study was carried out in 1,400 schoolchildren. Using a questionnaire, we determined information related to utilization and independent variables in the previous year. Oral health needs were established by means of a dental examination. To identify the independent variables associated with dental health services utilization, two types of multivariate regression models were used, according to the measurement scale of the outcome variable: a) frequency of utilization as (0) none, (1) one, and (2) two or more, analyzed with the ordered logistic regression and b) the type of service utilized as (0) none, (1) preventive services, (2) curative services, and (3) both services, analyzed with the multinomial logistic regression. The proportion of children who received at least one dental service in the 12 months prior to the study was 27.7 percent. The variables associated with utilization in the two models were older age, female sex, more frequent toothbrushing, positive attitude of the mother toward the child's oral health, higher socioeconomic level, and higher oral health needs. Various predisposing, enabling, and oral health needs variables were associated with higher dental health services utilization. As in prior reports elsewhere, these results from Nicaragua confirmed that utilization inequalities exist between socioeconomic groups. The multinomial logistic regression model evidenced the association of different variables depending on the type of service used.

Seeing the forest and the trees: multilevel models reveal both species and community patterns

Treesearch

Michelle M. Jackson; Monica G. Turner; Scott M. Pearson; Anthony R. Ives

2012-01-01

Studies designed to understand species distributions and community assemblages typically use separate analytical approaches (e.g., logistic regression and ordination) to model the distribution of individual species and to relate community composition to environmental variation. Multilevel models (MLMs) offer a promising strategy for integrating species and community-...

Developing an Adequately Specified Model of State Level Student Achievement with Multilevel Data.

ERIC Educational Resources Information Center

Bernstein, Lawrence

Limitations of using linear, unilevel regression procedures in modeling student achievement are discussed. This study is a part of a broader study that is developing an empirically-based predictive model of variables associated with academic achievement from a multilevel perspective and examining the differences by which parameters are estimated…

Association between fast food purchasing and the local food environment.

PubMed

Thornton, Lukar E; Kavanagh, A M

2012-12-03

In this study, an instrument was created to measure the healthy and unhealthy characteristics of food environments and investigate associations between the whole of the food environment and fast food consumption. In consultation with other academic researchers in this field, food stores were categorised to either healthy or unhealthy and weighted (between +10 and -10) by their likely contribution to healthy/unhealthy eating practices. A healthy and unhealthy food environment score (FES) was created using these weightings. Using a cross-sectional study design, multilevel multinomial regression was used to estimate the effects of the whole food environment on the fast food purchasing habits of 2547 individuals. Respondents in areas with the highest tertile of the healthy FES had a lower likelihood of purchasing fast food both infrequently and frequently compared with respondents who never purchased, however only infrequent purchasing remained significant when simultaneously modelled with the unhealthy FES (odds ratio (OR) 0.52; 95% confidence interval (CI) 0.32-0.83). Although a lower likelihood of frequent fast food purchasing was also associated with living in the highest tertile of the unhealthy FES, no association remained once the healthy FES was included in the models. In our binary models, respondents living in areas with a higher unhealthy FES than healthy FES were more likely to purchase fast food infrequently (OR 1.35; 95% CI 1.00-1.82) however no association was found for frequent purchasing. Our study provides some evidence to suggest that healthier food environments may discourage fast food purchasing.

Behaviour-Related Scalar Habitat Use by Cape Buffalo (Syncerus caffer caffer)

PubMed Central

Bennitt, Emily; Bonyongo, Mpaphi Casper; Harris, Stephen

2015-01-01

Studies of habitat use by animals must consider behavioural resource requirements at different scales, which could influence the functional value of different sites. Using Cape buffalo (Syncerus caffer caffer) in the Okavango Delta, Botswana, we tested the hypotheses that behaviour affected use between and within habitats, hereafter referred to as macro- and microhabitats, respectively. We fitted GPS-enabled collars to fifteen buffalo and used the distances and turning angles between consecutive fixes to cluster the resulting data into resting, grazing, walking and relocating behaviours. Distance to water and six vegetation characteristic variables were recorded in sites used for each behaviour, except for relocating, which occurred too infrequently. We used multilevel binomial and multinomial logistic regressions to identify variables that characterised seasonally-preferred macrohabitats and microhabitats used for different behaviours. Our results showed that macrohabitat use was linked to behaviour, although this was least apparent during the rainy season, when resources were most abundant. Behaviour-related microhabitat use was less significant, but variation in forage characteristics could predict some behaviour within all macrohabitats. The variables predicting behaviour were not consistent, but resting and grazing sites were more readily identifiable than walking sites. These results highlight the significance of resting, as well as foraging, site availability in buffalo spatial processes. Our results emphasise the importance of considering several behaviours and scales in studies of habitat use to understand the links between environmental resources and animal behavioural and spatial ecology. PMID:26673623

Substance use and Violence among Youth: A Daily Calendar Analysis

PubMed Central

Stoddard, Sarah A.; Epstein-Ngo, Quyen M.; Walton, Maureen; Zimmerman, Marc; Chermack, Stephen; Blow, Frederic C; Booth, Brenda M; Cunningham, Rebecca

2014-01-01

Background While researchers have identified factors that contribute to youth violence, less is known about the details of violent incidents. In addition, substance use has been linked to youth violence; however, little is known about actual substance use on days in which violence occurs. Objective This study examined reasons for peer violence and the association between substance use and violence using daily calendar-based analyses among at-risk urban youth. Methods Data were collected from Emergency Department (ED) patients (ages 14–24; n=599; 59% male, 65% African American) who screened positive for substance use in the past 6 months. Daily data regarding past 30-day substance use and violence and reasons for violent incidents were obtained via semi-structured interviews. Multi-level multinomial regression models were conducted to test the associations between substance use and peer violence incidents (i.e., none, moderate and severe). Results Conflict over ‘personal belongings’ was a common reason for violence among males; ‘jealousy’/’rumors’ were common reasons among females. Moderate victimization was more likely to be reported on days in which participants reported alcohol and cocaine use. Severe victimization was more likely to be reported on days in which participants reported alcohol use. Moderate or severe aggression was more likely to be reported on days in which participants reported alcohol and non-medical sedative use. Conclusions Results suggest that youth violence prevention that addresses differential reasons for violence among males and females as well as substance use would be beneficial. PMID:25493643

Non-fatal gunshot trauma among a sample of adolescents in Djibouti: prevalence and sociodemographic associations.

PubMed

Wilson, Michael L; Lewis, Erin R

2014-01-01

Firearm trauma is the second most common cause of serious injury among adolescents in the Republic of Djibouti. The aim of this study was to explore the sociodemographic correlates of serious injury and non-fatal gunshot trauma among adolescents in Djibouti. Using multinomial logistic regression, we compared a sample of adolescents (N = 1,711) who self-reported a non-firearm-related serious injury (n = 587) and those who reported a firearm-related injury (n = 101) with non-injured participants (n = 1,023) during a 12-month recall period. Analyses targeted demographic, behavioral, social, mental health, and family factors. After adjusting for covariates, participants reporting a non-firearm-related serious injury were more likely to report having been involved in physical fights (relative risk ratio [RRR] = 145; confidence interval [CI] = [1.04, 2.02), being bullied (RRR = 2.83; CI = [2.24, 3.56]), feeling lonely (RRR = 1.48; CI = [1.11, 1.96]), having signs of depression (RRR = 1.27; CI = [1.02, 1.58]), and be truant from school (RRR = 1.68; CI = [1.25, 2.28]). Those who reported a gunshot injury recorded being bullied (RRR = 2.83; CI = [1.77, 4.53]) and physically attacked at higher rates (RRR = 1.78; CI = [1.09, 2.89]). Serious injuries, whether firearm related or not, are important threats to adolescent health in Djibouti with potentially serious health-related correlates. More research, particularly multilevel designs, are needed to explain context-relevant factors associated with serious trauma in Djibouti.

An empirical study of statistical properties of variance partition coefficients for multi-level logistic regression models

USGS Publications Warehouse

Li, Ji; Gray, B.R.; Bates, D.M.

2008-01-01

Partitioning the variance of a response by design levels is challenging for binomial and other discrete outcomes. Goldstein (2003) proposed four definitions for variance partitioning coefficients (VPC) under a two-level logistic regression model. In this study, we explicitly derived formulae for multi-level logistic regression model and subsequently studied the distributional properties of the calculated VPCs. Using simulations and a vegetation dataset, we demonstrated associations between different VPC definitions, the importance of methods for estimating VPCs (by comparing VPC obtained using Laplace and penalized quasilikehood methods), and bivariate dependence between VPCs calculated at different levels. Such an empirical study lends an immediate support to wider applications of VPC in scientific data analysis.

Primary and Secondary Socialization Impacts on Support for Same-Sex Marriage after Legalization in the Netherlands

ERIC Educational Resources Information Center

Lubbers, Marcel; Jaspers, Eva; Ultee, Wout

2009-01-01

Two years after the legalization of same-sex marriages in the Netherlands, 65% of the Dutch population largely or completely disagrees with the statement "gay marriage should be abolished." This article shows, by way of multinomial logistic regression analysis of survey data, which socializing agents influence one's attitude toward…

The Association between Electronic Bullying and School Absenteeism among High School Students in the United States

ERIC Educational Resources Information Center

Grinshteyn, Erin; Yang, Y. T.

2017-01-01

Background: We examined the relationship between exposure to electronic bullying and absenteeism as a result of being afraid. Methods: This multivariate, multinomial regression analysis of the 2013 Youth Risk Behavior Survey data assessed the association between experiencing electronic bullying in the past year and how often students were absent…

Perpetration of Intimate Partner Aggression by Men and Women in the Philippines: Prevalence and Associated Factors

ERIC Educational Resources Information Center

Ansara, Donna L.; Hindin, Michelle J.

2009-01-01

This study uses data from the 2002 Cebu Longitudinal Health and Nutrition Survey to examine the prevalence of and factors associated with intimate partner violence perpetration by husbands and wives in Cebu, Philippines. Multinomial logistic regression was used to identify the factors associated with wife-only, husband-only, and reciprocal…

Persistent Nonmedical Use of Prescription Stimulants among College Students: Possible Association with ADHD Symptoms

ERIC Educational Resources Information Center

Arria, Amelia M.; Garnier-Dykstra, Laura M.; Caldeira, Kimberly M.; Vincent, Kathryn B.; O'Grady, Kevin E.; Wish, Eric D.

2011-01-01

Objective: To investigate the possible association between untreated ADHD symptoms (as measured by the Adult ADHD Self-Report Scale) and persistent nonmedical use of prescription stimulants. Method: Multinomial regression modeling was used to compare ADHD symptoms among three groups of college students enrolled in a longitudinal study over 4…

Behavioral and Emotional Strengths among Youth in Systems of Care and the Effect of Race/Ethnicity

ERIC Educational Resources Information Center

Barksdale, Crystal L.; Azur, Melissa; Daniels, Amy M.

2010-01-01

Behavioral and emotional strengths are important to consider when understanding youth mental health and treatment. This study examined the association between youth strengths and functional impairment and whether this association is modified by race/ethnicity. Multinomial logistic regression models were used to estimate the effects of strengths on…

Religiosity Profiles of American Youth in Relation to Substance Use, Violence, and Delinquency

ERIC Educational Resources Information Center

Salas-Wright, Christopher P.; Vaughn, Michael G.; Hodge, David R.; Perron, Brian E.

2012-01-01

Relatively little is known in terms of the relationship between religiosity profiles and adolescents' involvement in substance use, violence, and delinquency. Using a diverse sample of 17,705 (49 % female) adolescents from the 2008 National Survey on Drug Use and Health, latent profile analysis and multinomial regression are employed to examine…

Testing an Online English Course: Lessons Learned from an Analysis of Postcourse Proficiency Change Scores

ERIC Educational Resources Information Center

Jee, Rebecca Y.

2015-01-01

Voxy, an English-language-learning company, has developed a custom, in-house proficiency exam, the Voxy Proficiency Assessment (VPA), which is given to all learners at the beginning and end of their courses. Using Multinomial Logistic Regression (MLR), the impact of covariates, such as total learning activities completed and total number of…

Using multinomial logistic regression analysis to understand anglers willingness to substitute other fishing locations

Treesearch

Woo-Yong Hyun; Robert B. Ditton

2007-01-01

The concept of recreation substitutability has been a continuing research topic for outdoor recreation researchers. This study explores the relationships among variables regarding the willingness to substitute one location for another location. The objectives of the study are 1) to ascertain and predict the extent to which saltwater anglers were willing to substitute...

So Close, yet So Far Away: Early vs. Late Dropouts

ERIC Educational Resources Information Center

Ma, Yanli; Cragg, Kristina M.

2013-01-01

While some students drop out early in their academic career, others drop out close to completion. What similarities and differences exist between these early and late dropouts? Using a sample 3,520 first-time, full-time (FTFT) students seeking a bachelor's degree at a state university, this study employs multinomial logistic regression to model…

The Relationship of Selected Supply- and Demand-Side Factors to Forms of Perceived Discrimination among Adults with Multiple Sclerosis

ERIC Educational Resources Information Center

Roessler, Richard T.; Neath, Jeanne; McMahon, Brian T.; Rumrill, Phillip D.

2007-01-01

Single-predictor and stepwise multinomial logistic regression analyses and an external validation were completed on 3,082 allegations of employment discrimination by adults with multiple sclerosis. Women filed two thirds of the allegations, and individuals between 31 and 50 made the vast majority of discrimination charges (73%). Allegations…

High School Predictors of College Persistence: The Significance of Engagement and Teacher Interaction

ERIC Educational Resources Information Center

Sciarra, Daniel T.; Seirup, Holly J.; Sposato, Elizabeth

2016-01-01

This study investigated factors from high school that might predict college persistence. The sample consisted of 7,271 participants in three waves of data collection (2002, 2004 and 2006) who participated in the Educational Longitudinal Study (ELS; U.S. Department of Education, 2008). A multinomial logistic regression mode was employed to…

Generalized Partial Least Squares Approach for Nominal Multinomial Logit Regression Models with a Functional Covariate

ERIC Educational Resources Information Center

Albaqshi, Amani Mohammed H.

2017-01-01

Functional Data Analysis (FDA) has attracted substantial attention for the last two decades. Within FDA, classifying curves into two or more categories is consistently of interest to scientists, but multi-class prediction within FDA is challenged in that most classification tools have been limited to binary response applications. The functional…

Network-constrained group lasso for high-dimensional multinomial classification with application to cancer subtype prediction.

PubMed

Tian, Xinyu; Wang, Xuefeng; Chen, Jun

2014-01-01

Classic multinomial logit model, commonly used in multiclass regression problem, is restricted to few predictors and does not take into account the relationship among variables. It has limited use for genomic data, where the number of genomic features far exceeds the sample size. Genomic features such as gene expressions are usually related by an underlying biological network. Efficient use of the network information is important to improve classification performance as well as the biological interpretability. We proposed a multinomial logit model that is capable of addressing both the high dimensionality of predictors and the underlying network information. Group lasso was used to induce model sparsity, and a network-constraint was imposed to induce the smoothness of the coefficients with respect to the underlying network structure. To deal with the non-smoothness of the objective function in optimization, we developed a proximal gradient algorithm for efficient computation. The proposed model was compared to models with no prior structure information in both simulations and a problem of cancer subtype prediction with real TCGA (the cancer genome atlas) gene expression data. The network-constrained mode outperformed the traditional ones in both cases.

When Cannabis Is Available and Visible at School--A Multilevel Analysis of Students' Cannabis Use

ERIC Educational Resources Information Center

Kuntsche, Emmanuel

2010-01-01

Aims: To investigate the links between the visibility of cannabis use in school (measured by teachers' reports of students being under the influence of cannabis on school premises), the proportion of cannabis users in the class, perceived availability of cannabis, as well as adolescent cannabis use. Methods: A multilevel regression model was…

Macroeconomic Knowledge of Higher Education Students in Germany and Japan--A Multilevel Analysis of Contextual and Personal Effects

ERIC Educational Resources Information Center

Zlatkin-Troitschanskaia, Olga; Schmidt, Susanne; Brückner, Sebastian; Förster, Manuel; Yamaoka, Michio; Asano, Tadayoshi

2016-01-01

Recent trends towards harmonising and internationalising business and economics studies in higher education are affecting the structure and content of programmes and courses, and necessitate more transparent and comparable information on students' economic knowledge and skills. In this study, we examine by linear multilevel regression modelling…

Clinicians' adherence to clinical practice guidelines for cardiac function monitoring during antipsychotic treatment: a retrospective report on 434 patients with severe mental illness.

PubMed

Manchia, Mirko; Firinu, Giorgio; Carpiniello, Bernardo; Pinna, Federica

2017-03-31

Severe mental illness (SMI) has considerable excess morbidity and mortality, a proportion of which is explained by cardiovascular diseases, caused in part by antipsychotic (AP) induced QT-related arrhythmias and sudden death by Torsade de Point (TdP). The implementation of evidence-based recommendations for cardiac function monitoring might reduce the incidence of these AP-related adverse events. To investigate clinicians' adherence to cardiac function monitoring before and after starting AP, we performed a retrospective assessment of 434 AP-treated SMI patients longitudinally followed-up for 5 years at an academic community mental health center. We classified antipsychotics according to their risk of inducing QT-related arrhythmias and TdP (Center for Research on Therapeutics, University of Arizona). We used univariate tests and multinomial or binary logistic regression model for data analysis. Univariate and multinomial regression analysis showed that psychiatrists were more likely to perform pre-treatment electrocardiogram (ECG) and electrolyte testing with AP carrying higher cardiovascular risk, but not on the basis of AP pharmacological class. Univariate and binomial regression analysis showed that cardiac function parameters (ECG and electrolyte balance) were more frequently monitored during treatment with second generation AP than with first generation AP. Our data show the presence of weaknesses in the cardiac function monitoring of AP-treated SMI patients, and might guide future interventions to tackle them.

Utility of an Abbreviated Dizziness Questionnaire to Differentiate between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study

PubMed Central

Roland, Lauren T.; Kallogjeri, Dorina; Sinks, Belinda C.; Rauch, Steven D.; Shepard, Neil T.; White, Judith A.; Goebel, Joel A.

2015-01-01

Objective Test performance of a focused dizziness questionnaire’s ability to discriminate between peripheral and non-peripheral causes of vertigo. Study Design Prospective multi-center Setting Four academic centers with experienced balance specialists Patients New dizzy patients Interventions A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Main outcomes Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and non-peripheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. Results 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and non-peripheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central and other causes were considered good as measured by c-indices of 0.75, 0.7 and 0.78, respectively. Conclusions This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from non-peripheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed. PMID:26485598

Utility of an Abbreviated Dizziness Questionnaire to Differentiate Between Causes of Vertigo and Guide Appropriate Referral: A Multicenter Prospective Blinded Study.

PubMed

Roland, Lauren T; Kallogjeri, Dorina; Sinks, Belinda C; Rauch, Steven D; Shepard, Neil T; White, Judith A; Goebel, Joel A

2015-12-01

Test performance of a focused dizziness questionnaire's ability to discriminate between peripheral and nonperipheral causes of vertigo. Prospective multicenter. Four academic centers with experienced balance specialists. New dizzy patients. A 32-question survey was given to participants. Balance specialists were blinded and a diagnosis was established for all participating patients within 6 months. Multinomial logistic regression was used to evaluate questionnaire performance in predicting final diagnosis and differentiating between peripheral and nonperipheral vertigo. Univariate and multivariable stepwise logistic regression were used to identify questions as significant predictors of the ultimate diagnosis. C-index was used to evaluate performance and discriminative power of the multivariable models. In total, 437 patients participated in the study. Eight participants without confirmed diagnoses were excluded and 429 were included in the analysis. Multinomial regression revealed that the model had good overall predictive accuracy of 78.5% for the final diagnosis and 75.5% for differentiating between peripheral and nonperipheral vertigo. Univariate logistic regression identified significant predictors of three main categories of vertigo: peripheral, central, and other. Predictors were entered into forward stepwise multivariable logistic regression. The discriminative power of the final models for peripheral, central, and other causes was considered good as measured by c-indices of 0.75, 0.7, and 0.78, respectively. This multicenter study demonstrates a focused dizziness questionnaire can accurately predict diagnosis for patients with chronic/relapsing dizziness referred to outpatient clinics. Additionally, this survey has significant capability to differentiate peripheral from nonperipheral causes of vertigo and may, in the future, serve as a screening tool for specialty referral. Clinical utility of this questionnaire to guide specialty referral is discussed.

Mapping Regional Impervious Surface Distribution from Night Time Light: The Variability across Global Cities

NASA Astrophysics Data System (ADS)

Lin, M.; Yang, Z.; Park, H.; Qian, S.; Chen, J.; Fan, P.

2017-12-01

Impervious surface area (ISA) has become an important indicator for studying urban environments, but mapping ISA at the regional or global scale is still challenging due to the complexity of impervious surface features. The Defense Meteorological Satellite Program's Operational Linescan System (DMSP-OLS) nighttime light data is (NTL) and Resolution Imaging Spectroradiometer (MODIS) are the major remote sensing data source for regional ISA mapping. A single regression relationship between fractional ISA and NTL or various index derived based on NTL and MODIS vegetation index (NDVI) data was established in many previous studies for regional ISA mapping. However, due to the varying geographical, climatic, and socio-economic characteristics of different cities, the same regression relationship may vary significantly across different cities in the same region in terms of both fitting performance (i.e. R2) and the rate of change (Slope). In this study, we examined the regression relationship between fractional ISA and Vegetation Adjusted Nighttime light Urban Index (VANUI) for 120 randomly selected cities around the world with a multilevel regression model. We found that indeed there is substantial variability of both the R2 (0.68±0.29) and slopes (0.64±0.40) among individual regressions, which suggests that multilevel/hierarchical models are needed for accuracy improvement of future regional ISA mapping .Further analysis also let us find the this substantial variability are affected by climate conditions, socio-economic status, and urban spatial structures. However, all these effects are nonlinear rather than linear, thus could not modeled explicitly in multilevel linear regression models.

Predicting Depression among Patients with Diabetes Using Longitudinal Data. A Multilevel Regression Model.

PubMed

Jin, H; Wu, S; Vidyanti, I; Di Capua, P; Wu, B

2015-01-01

This article is part of the Focus Theme of Methods of Information in Medicine on "Big Data and Analytics in Healthcare". Depression is a common and often undiagnosed condition for patients with diabetes. It is also a condition that significantly impacts healthcare outcomes, use, and cost as well as elevating suicide risk. Therefore, a model to predict depression among diabetes patients is a promising and valuable tool for providers to proactively assess depressive symptoms and identify those with depression. This study seeks to develop a generalized multilevel regression model, using a longitudinal data set from a recent large-scale clinical trial, to predict depression severity and presence of major depression among patients with diabetes. Severity of depression was measured by the Patient Health Questionnaire PHQ-9 score. Predictors were selected from 29 candidate factors to develop a 2-level Poisson regression model that can make population-average predictions for all patients and subject-specific predictions for individual patients with historical records. Newly obtained patient records can be incorporated with historical records to update the prediction model. Root-mean-square errors (RMSE) were used to evaluate predictive accuracy of PHQ-9 scores. The study also evaluated the classification ability of using the predicted PHQ-9 scores to classify patients as having major depression. Two time-invariant and 10 time-varying predictors were selected for the model. Incorporating historical records and using them to update the model may improve both predictive accuracy of PHQ-9 scores and classification ability of the predicted scores. Subject-specific predictions (for individual patients with historical records) achieved RMSE about 4 and areas under the receiver operating characteristic (ROC) curve about 0.9 and are better than population-average predictions. The study developed a generalized multilevel regression model to predict depression and demonstrated that using generalized multilevel regression based on longitudinal patient records can achieve high predictive ability.

Emergency Department Use by Nursing Home Residents: Effect of Severity of Cognitive Impairment

ERIC Educational Resources Information Center

Stephens, Caroline E.; Newcomer, Robert; Blegen, Mary; Miller, Bruce; Harrington, Charlene

2012-01-01

Purpose: To examine the 1-year prevalence and risk of emergency department (ED) use and ambulatory care-sensitive (ACS) ED use by nursing home (NH) residents with different levels of severity of cognitive impairment (CI). Design and Methods: We used multinomial logistic regression to estimate the effect of CI severity on the odds of any ED visit…

A Process View on Implementing an Antibullying Curriculum: How Teachers Differ and What Explains the Variation

ERIC Educational Resources Information Center

Haataja, Anne; Ahtola, Annarilla; Poskiparta, Elisa; Salmivalli, Christina

2015-01-01

The present study provides a person-centered view on teachers' adherence to the KiVa antibullying curriculum over a school year. Factor mixture modeling was used to examine how teachers (N = 282) differed in their implementation profiles and multinomial logistic regression was used to identify factors related to these profiles. On the basis of…

Multinomial-Regression Modeling of the Environmental Attitudes of Higher Education Students Based on the Revised New Ecological Paradigm Scale

ERIC Educational Resources Information Center

Jowett, Tim; Harraway, John; Lovelock, Brent; Skeaff, Sheila; Slooten, Liz; Strack, Mick; Shephard, Kerry

2014-01-01

Higher education is increasingly interested in its impact on the sustainability attributes of its students, so we wanted to explore how our students' environmental concern changed during their higher education experiences. We used the Revised New Ecological Paradigm Scale (NEP) with 505 students and developed and tested a multinomial…

The Effect of Participating in Indiana's Twenty-First Century Scholars Program on College Enrollments

ERIC Educational Resources Information Center

Toutkoushian, Robert K.; Hossler, Don; DesJardins, Stephen L.; McCall, Brian; Gonzalez Canche, Manuel S.

2015-01-01

Our study adds to prior work on Indiana's Twenty-first Century Scholars(TFCS) program by focusing on whether participating in--rather than completing--the program affects the likelihood of students going to college and where they initially enrolled. We first employ binary and multinomial logistic regression to obtain estimates of the impact of the…

The Design and Analysis of Salmonid Tagging Studies in the Columbia Basin; Volume XII; A Multinomial Model for Estimating Ocean Survival from Salmonid Coded Wire-Tag Data.

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

Ryding, Kristen E.; Skalski, John R.

1999-06-01

The purpose of this report is to illustrate the development of a stochastic model using coded wire-tag (CWT) release and age-at-return data, in order to regress first year ocean survival probabilities against coastal ocean conditions and climate covariates.

Sex-related perceptions associated with sexual activity status among Japanese adolescents who heavily use text messaging.

PubMed

Kawamura, Yoko

2012-01-01

This study examines the relationship between sex-related perceptions and engagement in sexual intercourse among adolescents in Japan who were heavy users of text massaging. Using the data from the 6th National Survey on Youth Sexual Behavior of 548 high school students who heavily use text messaging, multinomial logistic regression analyses on variables constructing sexual norms and gender-role attitudes were conducted to assess the relationship with sexual activity status as the first step. A backward stepwise elimination method of multinomial logistic regression was used as the second step at which variables for each set of two factors were tested, and as the third step at which variables of two factors were simultaneously tested. The study results showed that perceptions were related to engagement in sexual intercourse among adolescents who heavily used text messaging. In particular, those who perceived that sex is an act to be engaged in at an earlier stage of a relationship and that men have a stronger sex drive tended to be sexually active or have experienced sexual intercourse. These findings could be utilized to design more effective sexual health education messages for Japanese adolescents who are at an elevated risk.

Factors associated with happiness in the elderly persons living in the community.

PubMed

Luchesi, Bruna Moretti; de Oliveira, Nathalia Alves; de Morais, Daiene; de Paula Pessoa, Rebeca Mendes; Pavarini, Sofia Cristina I; Chagas, Marcos Hortes N

2018-01-01

The aim of the present study was to evaluate factors associated with happiness in a sample of Brazilian older adults. A study was conducted with 263 elderly people in the area of coverage of a family health unit located in the state of São Paulo, Brazil. The Subjective Happiness Scale was used to measure happiness, the final score of which determined one of three outcomes: not happy, intermediate, and happy. Disability, sociodemographic characteristics, and psychological, cognitive, and physical factors were considered for the multinomial logistic regression analysis. Statistically significant differences were found among the three groups regarding satisfaction with life, disability, social phobia, anxiety, depression, and frailty (p≤0.05). In the multinomial regression analysis, being "not happy" was significantly associated with satisfaction with life (RRR: 0.53), depression (RRR: 1.46), social phobia (RRR: 1.24), and age (RRR: 1.06). The present findings indicate that psychological factors and age influence the levels of happiness in older adults living in the community. Furthermore, better screening, diagnosis, and treatment of mental health disorders could increase the feeling of happiness among older adults. Copyright © 2017 Elsevier B.V. All rights reserved.

Perception of tourists regarding the smoke-free policy at Suvarnabhumi International Airport, Bangkok, Thailand.

PubMed

Sirichotiratana, Nithat; Yogi, Subash; Prutipinyo, Chardsumon

2013-08-30

This study was conducted during February-March 2012 to determine the perception and support regarding smoke-free policy among tourists at Suvarnabhumi International Airport, Bangkok, Thailand. In this cross-sectional study, 200 tourists (n = 200) were enrolled by convenience sampling and interviewed by structured questionnaire. Descriptive statistics, chi-square, and multinomial logistic regression were adopted in the study. Results revealed that half (50%) of the tourists were current smokers and 55% had visited Thailand twice or more. Three quarter (76%) of tourists indicated that they would visit Thailand again even if it had a 100% smoke-free regulation. Almost all (99%) of the tourists had supported for the smoke-free policy (partial ban and total ban), and current smokers had higher percentage of support than non-smokers. Two factors, current smoking status and knowledge level, were significantly associated with perception level. After analysis with Multinomial Logistic Regression, it was found that perception, country group, and presence of designated smoking room (DSR) were associated with smoke-free policy. Recommendation is that, at institution level effective monitoring system is needed at the airport. At policy level, the recommendation is that effective comprehensive policy needed to be emphasized to ensure smoke-free airport environment.

Evaluating the Relationship between Productivity and Quality in Emergency Departments

PubMed Central

Bastian, Nathaniel D.; Riordan, John P.

2017-01-01

Background In the United States, emergency departments (EDs) are constantly pressured to improve operational efficiency and quality in order to gain financial benefits and maintain a positive reputation. Objectives The first objective is to evaluate how efficiently EDs transform their input resources into quality outputs. The second objective is to investigate the relationship between the efficiency and quality performance of EDs and the factors affecting this relationship. Methods Using two data sources, we develop a data envelopment analysis (DEA) model to evaluate the relative efficiency of EDs. Based on the DEA result, we performed multinomial logistic regression to investigate the relationship between ED efficiency and quality performance. Results The DEA results indicated that the main source of inefficiencies was working hours of technicians. The multinomial logistic regression result indicated that the number of electrocardiograms and X-ray procedures conducted in the ED and the length of stay were significantly associated with the trade-offs between relative efficiency and quality. Structural ED characteristics did not influence the relationship between efficiency and quality. Conclusions Depending on the structural and operational characteristics of EDs, different factors can affect the relationship between efficiency and quality. PMID:29065673

Exploring the impact of different multi-level measures of physician communities in patient-centric care networks on healthcare outcomes: A multi-level regression approach.

PubMed

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.

Adherence to oral anticoagulants in patients with atrial fibrillation-a population-based retrospective cohort study linking health information systems in the Valencia region, Spain: a study protocol.

PubMed

Sanfélix-Gimeno, G; Rodríguez-Bernal, C L; Hurtado, I; Baixáuli-Pérez, C; Librero, J; Peiró, S

2015-10-19

Adherence to oral anticoagulation (OAC) treatment, vitamin K antagonists or new oral anticoagulants, is an essential element for effectiveness. Information on adherence to OAC in atrial fibrillation (AF) and the impact of adherence on clinical outcomes using real-world data barely exists. We aim to describe the patterns of adherence to OAC over time in patients with AF, estimate the associated factors and their impact on clinical events, and assess the same issues with conventional measures of primary and secondary adherence-proportion of days covered (PDC) and persistence-in routine clinical practice. This is a population-based retrospective cohort study including all patients with AF treated with OAC from 2010 to date in Valencia, Spain; data will be obtained from diverse electronic records of the Valencia Health Agency. adherence trajectories. (1) primary non-adherence; (2) secondary adherence: (a) PDC, (b) persistence. Clinical outcomes: hospitalisation for haemorrhagic or thromboembolic events and death during follow-up. (1) description of baseline characteristics, adherence patterns (trajectory models or latent class growth analysis models) and conventional adherence measures; (2) logistic or Cox multivariate regression models, to assess the associations between adherence measures and the covariates, and logistic multinomial regression models, to identify characteristics associated with each trajectory; (3) Cox proportional hazard models, to assess the relationship between adherence and clinical outcomes, with propensity score adjustment applied to further control for potential confounders; (4) to estimate the importance of different healthcare levels in the variations of adherence, logistic or Cox multilevel regression models. This study has been approved by the corresponding Clinical Research Ethics Committee. We plan to disseminate the project's findings through peer-reviewed publications and presentations at relevant health conferences. Policy reports will also be prepared in order to promote the translation of our findings into policy and clinical practice. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

Subjective Health and Mental Well-Being of Adolescents and the Health Promoting School: A Cross-Sectional Multilevel Analysis

ERIC Educational Resources Information Center

Levin, Kate; Inchley, Jo; Currie, Dorothy; Currie, Candace

2012-01-01

Purpose: The aim of this paper is to examine the impact of the health promoting school (HPS) on adolescent well-being. Design/methodology/approach: Data from the 2006 Health Behaviour in School-aged Children: WHO-collaborative Study in Scotland were analysed using multilevel linear regression analyses for outcome measures: happiness, confidence,…

Are Environmental Influences on Physical Activity Distinct for Urban, Suburban, and Rural Schools? A Multilevel Study among Secondary School Students in Ontario, Canada

ERIC Educational Resources Information Center

Hobin, Erin P.; Leatherdale, Scott; Manske, Steve; Dubin, Joel A.; Elliott, Susan; Veugelers, Paul

2013-01-01

Background: This study examined differences in students' time spent in physical activity (PA) across secondary schools in rural, suburban, and urban environments and identified the environment-level factors associated with these between school differences in students' PA. Methods: Multilevel linear regression analyses were used to examine the…

The Association between Overweight and School Policies on Physical Activity: A Multilevel Analysis among Elementary School Youth in the PLAY-On Study

ERIC Educational Resources Information Center

Leatherdale, Scott T.

2010-01-01

The objective is to examine school-level program and policy characteristics and student-level behavioural characteristics associated with being overweight. Multilevel logistic regression analysis were used to examine the school- and student-level characteristics associated with the odds of a student being overweight among 1264 Grade 5-8 students…

Lateralization of temporal lobe epilepsy by multimodal multinomial hippocampal response-driven models.

PubMed

Nazem-Zadeh, Mohammad-Reza; Elisevich, Kost V; Schwalb, Jason M; Bagher-Ebadian, Hassan; Mahmoudi, Fariborz; Soltanian-Zadeh, Hamid

2014-12-15

Multiple modalities are used in determining laterality in mesial temporal lobe epilepsy (mTLE). It is unclear how much different imaging modalities should be weighted in decision-making. The purpose of this study is to develop response-driven multimodal multinomial models for lateralization of epileptogenicity in mTLE patients based upon imaging features in order to maximize the accuracy of noninvasive studies. The volumes, means and standard deviations of FLAIR intensity and means of normalized ictal-interictal SPECT intensity of the left and right hippocampi were extracted from preoperative images of a retrospective cohort of 45 mTLE patients with Engel class I surgical outcomes, as well as images of a cohort of 20 control, nonepileptic subjects. Using multinomial logistic function regression, the parameters of various univariate and multivariate models were estimated. Based on the Bayesian model averaging (BMA) theorem, response models were developed as compositions of independent univariate models. A BMA model composed of posterior probabilities of univariate response models of hippocampal volumes, means and standard deviations of FLAIR intensity, and means of SPECT intensity with the estimated weighting coefficients of 0.28, 0.32, 0.09, and 0.31, respectively, as well as a multivariate response model incorporating all mentioned attributes, demonstrated complete reliability by achieving a probability of detection of one with no false alarms to establish proper laterality in all mTLE patients. The proposed multinomial multivariate response-driven model provides a reliable lateralization of mesial temporal epileptogenicity including those patients who require phase II assessment. Copyright © 2014 Elsevier B.V. All rights reserved.

Factors associated with treatment-seeking for malaria in urban poor communities in Accra, Ghana.

PubMed

Awuah, Raphael Baffour; Asante, Paapa Yaw; Sakyi, Lionel; Biney, Adriana A E; Kushitor, Mawuli Komla; Agyei, Francis; de-Graft Aikins, Ama

2018-04-16

In Ghana, about 3.5 million cases of malaria are recorded each year. Urban poor residents particularly have a higher risk of malaria mainly due to poor housing, low socio-economic status and poor sanitation. Alternative treatment for malaria (mainly African traditional/herbal and/or self-medication) is further compounding efforts to control the incidence of malaria in urban poor communities. This study assesses factors associated with seeking alternative treatment as the first response to malaria, relative to orthodox treatment in three urban poor communities in Accra, Ghana. This cross-sectional study was conducted in three urban poor localities in Accra, Ghana among individuals in their reproductive ages (15-59 years for men and 15-49 years for women). The analytic sample for the study was 707. A multinomial regression model was used to assess individual, interpersonal and structural level factors associated with treatment-seeking for malaria. Overall, 31% of the respondents sought orthodox treatment, 8% sought traditional/herbal treatment and 61% self-medicated as the first response to malaria. At the bivariate level, more males than females used traditional/herbal treatment and self-medicated for malaria. The results of the regression analysis showed that current health insurance status, perceived relative economic standing, level of social support, and locality of residence were associated with seeking alternative treatment for malaria relative to orthodox treatment. The findings show that many urban poor residents in Accra self-medicate as the first response to malaria. Additionally, individuals who were not enrolled in a health insurance scheme, those who perceived they had a low economic standing, those with a high level of social support, and locality of residence were significantly associated with the use of alternative treatment for malaria. Multi-level strategies should be employed to address the use of alternative forms of treatment for malaria within the context of urban poverty.

Analyzing Multilevel Data: Comparing Findings from Hierarchical Linear Modeling and Ordinary Least Squares Regression

ERIC Educational Resources Information Center

Rocconi, Louis M.

2013-01-01

This study examined the differing conclusions one may come to depending upon the type of analysis chosen, hierarchical linear modeling or ordinary least squares (OLS) regression. To illustrate this point, this study examined the influences of seniors' self-reported critical thinking abilities three ways: (1) an OLS regression with the student…

A Multilevel Multivariate Analysis of Academic Performances in College Based on NCAA Student-Athletes

ERIC Educational Resources Information Center

McArdle, John J.; Paskus, Thomas S.; Boker, Steven M.

2013-01-01

This is an application of contemporary multilevel regression modeling to the prediction of academic performances of 1st-year college students. At a first level of analysis, the data come from N greater than 16,000 students who were college freshman in 1994-1995 and who were also participants in high-level college athletics. At a second level of…

Retention of Children and Their Families in the Longitudinal Outcome Study of the Comprehensive Community Mental Health Services for Children and Their Families Program: A Multilevel Analysis

ERIC Educational Resources Information Center

Gebreselassie, Tesfayi; Stephens, Robert L.; Maples, Connie J.; Johnson, Stacy F.; Tucker, Alyce L.

2014-01-01

Predictors of retention of participants in a longitudinal study and heterogeneity between communities were investigated using a multilevel logistic regression model. Data from the longitudinal outcome study of the national evaluation of the Comprehensive Community Mental Health Services for Children and Their Families program and information on…

A Primer for Analyzing Nested Data: Multilevel Modeling in SPSS Using an Example from a REL Study. REL 2015-046

ERIC Educational Resources Information Center

O'Dwyer, Laura M.; Parker, Caroline E.

2014-01-01

Analyzing data that possess some form of nesting is often challenging for applied researchers or district staff who are involved in or in charge of conducting data analyses. This report provides a description of the challenges for analyzing nested data and provides a primer of how multilevel regression modeling may be used to resolve these…

A Pilot Test of Indicator Species to Assess Uniqueness of Oak-Dominated Ecoregions in Central Tennessee

Treesearch

W. Henry McNab; David L. Loftis; Callie J. Schweitzer; Raymond Sheffield

2004-01-01

We used tree indicator species occurring on 438 plots in the Plateau counties of Tennessee to test the uniqueness of four conterminous ecoregions. Multinomial logistic regression indicated that the presence of 14 tree species allowed classification of sample plots according to ecoregion with an average overall accuracy of 75 percent (range 45 to 94 percent). Additional...

Brief Report: Sexual Orientation in Individuals with Autistic Traits--Population Based Study of 47,000 Adults in Stockholm County

ERIC Educational Resources Information Center

Rudolph, Christiane E. S.; Lundin, Andreas; Åhs, Jill W.; Dalman, Christina; Kosidou, Kyriaki

2018-01-01

We examined the association between autistic traits and sexual orientation in a general adult population (N = 47,356). Autistic traits were measured with the ten items Autistic Quotient questionnaire using a cut-off score of = 6. Sexual orientation was assessed by self-report. Multinomial logistic regression was used to estimate odds ratios (ORs)…

Mind-Mindedness as a Multidimensional Construct: Appropriate and Nonattuned Mind-Related Comments Independently Predict Infant-Mother Attachment in a Socially Diverse Sample

ERIC Educational Resources Information Center

Meins, Elizabeth; Fernyhough, Charles; de Rosnay, Marc; Arnott, Bronia; Leekam, Susan R.; Turner, Michelle

2012-01-01

In a socially diverse sample of 206 infant-mother pairs, we investigated predictors of infants' attachment security at 15 months, with a particular emphasis on mothers' tendency to comment appropriately or in a non-attuned manner on their 8-month-olds' internal states (so-called mind-mindedness). Multinomial logistic regression analyses showed…

Food and Drug Administration tobacco regulation and product judgments.

PubMed

Kaufman, Annette R; Finney Rutten, Lila J; Parascandola, Mark; Blake, Kelly D; Augustson, Erik M

2015-04-01

The Family Smoking Prevention and Tobacco Control Act granted the Food and Drug Administration (FDA) the authority to regulate tobacco products in the U.S. However, little is known about how regulation may be related to judgments about tobacco product-related risks. To understand how FDA tobacco regulation beliefs are associated with judgments about tobacco product-related risks. The Health Information National Trends Survey is a national survey of the U.S. adult population. Data used in this analysis were collected from October 2012 through January 2013 (N=3,630) by mailed questionnaire and analyzed in 2013. Weighted bivariate chi-square analyses were used to assess associations among FDA regulation belief, tobacco harm judgments, sociodemographics, and smoking status. A weighted multinomial logistic regression was conducted where FDA regulation belief was regressed on tobacco product judgments, controlling for sociodemographic variables and smoking status. About 41% believed that the FDA regulates tobacco products in the U.S., 23.6% reported the FDA does not, and 35.3% did not know. Chi-square analyses showed that smoking status was significantly related to harm judgments about electronic cigarettes (p<0.0001). The multinomial logistic regression revealed that uncertainty about FDA regulation was associated with tobacco product harm judgment uncertainty. Tobacco product harm perceptions are associated with beliefs about tobacco product regulation by the FDA. These findings suggest the need for increased public awareness and understanding of the role of tobacco product regulation in protecting public health. Copyright © 2015. Published by Elsevier Inc.

An Approximate Approach to Automatic Kernel Selection.

PubMed

Ding, Lizhong; Liao, Shizhong

2016-02-02

Kernel selection is a fundamental problem of kernel-based learning algorithms. In this paper, we propose an approximate approach to automatic kernel selection for regression from the perspective of kernel matrix approximation. We first introduce multilevel circulant matrices into automatic kernel selection, and develop two approximate kernel selection algorithms by exploiting the computational virtues of multilevel circulant matrices. The complexity of the proposed algorithms is quasi-linear in the number of data points. Then, we prove an approximation error bound to measure the effect of the approximation in kernel matrices by multilevel circulant matrices on the hypothesis and further show that the approximate hypothesis produced with multilevel circulant matrices converges to the accurate hypothesis produced with kernel matrices. Experimental evaluations on benchmark datasets demonstrate the effectiveness of approximate kernel selection.

Implementation of Local Wellness Policies in Schools: Role of School Systems, School Health Councils, and Health Disparities.

PubMed

Hager, Erin R; Rubio, Diana S; Eidel, G Stewart; Penniston, Erin S; Lopes, Megan; Saksvig, Brit I; Fox, Renee E; Black, Maureen M

2016-10-01

Written local wellness policies (LWPs) are mandated in school systems to enhance opportunities for healthy eating/activity. LWP effectiveness relies on school-level implementation. We examined factors associated with school-level LWP implementation. Hypothesized associations included system support for school-level implementation and having a school-level wellness team/school health council (SHC), with stronger associations among schools without disparity enrollment (majority African-American/Hispanic or low-income students). Online surveys were administered: 24 systems (support), 1349 schools (LWP implementation, perceived system support, SHC). The state provided school demographics. Analyses included multilevel multinomial logistic regression. Response rates were 100% (systems)/55.2% (schools). Among schools, 44.0% had SHCs, 22.6% majority (≥75%) African-American/Hispanic students, and 25.5% majority (≥75%) low-income (receiving free/reduced-price meals). LWP implementation (17-items) categorized as none = 36.3%, low (1-5 items) = 36.3%, high (6+ items) = 27.4%. In adjusted models, greater likelihood of LWP implementation was observed among schools with perceived system support (high versus none relative risk ratio, RRR = 1.63, CI: 1.49, 1.78; low versus none RRR = 1.26, CI: 1.18, 1.36) and SHCs (high versus none RRR = 6.8, CI: 4.07, 11.37; low versus none RRR = 2.24, CI: 1.48, 3.39). Disparity enrollment did not moderate associations (p > .05). Schools with perceived system support and SHCs had greater likelihood of LWP implementation, with no moderating effect of disparity enrollment. SHCs/support may overcome LWP implementation obstacles related to disparities. © 2016, American School Health Association.

Citizen Participation in Patient Prioritization Policy Decisions: An Empirical and Experimental Study on Patients' Characteristics

PubMed Central

Diederich, Adele; Swait, Joffre; Wirsik, Norman

2012-01-01

Health systems worldwide are grappling with the need to control costs to maintain system viability. With the combination of worsening economic conditions, an aging population and reductions in tax revenues, the pressures to make structural changes are expected to continue growing. Common cost control mechanisms, e.g. curtailment of patient access and treatment prioritization, are likely to be adversely viewed by citizens. It seems therefore wise to include them in the decision making processes that lead up to policy changes. In the context of a multilevel iterative mixed-method design a quantitative survey representative of the German population (N = 2031) was conducted to probe the acceptance of priority setting in medicine and to explore the practicability of direct public involvement. Here we focus on preferences for patients' characteristics (medical aspects, lifestyle and socio-economic status) as possible criteria for prioritizing medical services. A questionnaire with closed response options was fielded to gain insight into attitudes toward broad prioritization criteria of patient groups. Furthermore, a discrete choice experiment was used as a rigorous approach to investigate citizens' preferences toward specific criteria level in context of other criteria. Both the questionnaire and the discrete choice experiment were performed with the same sample. The citizens' own health and social situation are included as explanatory variables. Data were evaluated using corresponding analysis, contingency analysis, logistic regression and a multinomial exploded logit model. The results show that some medical criteria are highly accepted for prioritizing patients whereas socio-economic criteria are rejected. PMID:22590619

Association between fast food purchasing and the local food environment

PubMed Central

Thornton, Lukar E; Kavanagh, A M

2012-01-01

Objective: In this study, an instrument was created to measure the healthy and unhealthy characteristics of food environments and investigate associations between the whole of the food environment and fast food consumption. Design and subjects: In consultation with other academic researchers in this field, food stores were categorised to either healthy or unhealthy and weighted (between +10 and −10) by their likely contribution to healthy/unhealthy eating practices. A healthy and unhealthy food environment score (FES) was created using these weightings. Using a cross-sectional study design, multilevel multinomial regression was used to estimate the effects of the whole food environment on the fast food purchasing habits of 2547 individuals. Results: Respondents in areas with the highest tertile of the healthy FES had a lower likelihood of purchasing fast food both infrequently and frequently compared with respondents who never purchased, however only infrequent purchasing remained significant when simultaneously modelled with the unhealthy FES (odds ratio (OR) 0.52; 95% confidence interval (CI) 0.32–0.83). Although a lower likelihood of frequent fast food purchasing was also associated with living in the highest tertile of the unhealthy FES, no association remained once the healthy FES was included in the models. In our binary models, respondents living in areas with a higher unhealthy FES than healthy FES were more likely to purchase fast food infrequently (OR 1.35; 95% CI 1.00–1.82) however no association was found for frequent purchasing. Conclusion: Our study provides some evidence to suggest that healthier food environments may discourage fast food purchasing. PMID:23208414

Multilevel Hierarchical Modeling of Benthic Macroinvertebrate Responses to Urbanization in Nine Metropolitan Regions across the Conterminous United States

USGS Publications Warehouse

Kashuba, Roxolana; Cha, YoonKyung; Alameddine, Ibrahim; Lee, Boknam; Cuffney, Thomas F.

2010-01-01

Multilevel hierarchical modeling methodology has been developed for use in ecological data analysis. The effect of urbanization on stream macroinvertebrate communities was measured across a gradient of basins in each of nine metropolitan regions across the conterminous United States. The hierarchical nature of this dataset was harnessed in a multi-tiered model structure, predicting both invertebrate response at the basin scale and differences in invertebrate response at the region scale. Ordination site scores, total taxa richness, Ephemeroptera, Plecoptera, Trichoptera (EPT) taxa richness, and richness-weighted mean tolerance of organisms at a site were used to describe invertebrate responses. Percentage of urban land cover was used as a basin-level predictor variable. Regional mean precipitation, air temperature, and antecedent agriculture were used as region-level predictor variables. Multilevel hierarchical models were fit to both levels of data simultaneously, borrowing statistical strength from the complete dataset to reduce uncertainty in regional coefficient estimates. Additionally, whereas non-hierarchical regressions were only able to show differing relations between invertebrate responses and urban intensity separately for each region, the multilevel hierarchical regressions were able to explain and quantify those differences within a single model. In this way, this modeling approach directly establishes the importance of antecedent agricultural conditions in masking the response of invertebrates to urbanization in metropolitan regions such as Milwaukee-Green Bay, Wisconsin; Denver, Colorado; and Dallas-Fort Worth, Texas. Also, these models show that regions with high precipitation, such as Atlanta, Georgia; Birmingham, Alabama; and Portland, Oregon, start out with better regional background conditions of invertebrates prior to urbanization but experience faster negative rates of change with urbanization. Ultimately, this urbanization-invertebrate response example is used to detail the multilevel hierarchical construction methodology, showing how the result is a set of models that are both statistically more rigorous and ecologically more interpretable than simple linear regression models.

Using GA-Ridge regression to select hydro-geological parameters influencing groundwater pollution vulnerability.

PubMed

Ahn, Jae Joon; Kim, Young Min; Yoo, Keunje; Park, Joonhong; Oh, Kyong Joo

2012-11-01

For groundwater conservation and management, it is important to accurately assess groundwater pollution vulnerability. This study proposed an integrated model using ridge regression and a genetic algorithm (GA) to effectively select the major hydro-geological parameters influencing groundwater pollution vulnerability in an aquifer. The GA-Ridge regression method determined that depth to water, net recharge, topography, and the impact of vadose zone media were the hydro-geological parameters that influenced trichloroethene pollution vulnerability in a Korean aquifer. When using these selected hydro-geological parameters, the accuracy was improved for various statistical nonlinear and artificial intelligence (AI) techniques, such as multinomial logistic regression, decision trees, artificial neural networks, and case-based reasoning. These results provide a proof of concept that the GA-Ridge regression is effective at determining influential hydro-geological parameters for the pollution vulnerability of an aquifer, and in turn, improves the AI performance in assessing groundwater pollution vulnerability.

The Role of Individual Correlates and Class Norms in Defending and Passive Bystanding Behavior in Bullying: A Multilevel Analysis

ERIC Educational Resources Information Center

Pozzoli, Tiziana; Gini, Gianluca; Vieno, Alessio

2012-01-01

This study investigates possible individual and class correlates of defending and passive bystanding behavior in bullying, in a sample of 1,825 Italian primary school (mean age = 10 years 1 month) and middle school (mean age = 13 years 2 months) students. The findings of a series of multilevel regression models show that both individual (e.g.,…

Impact of Contextual Factors on Prostate Cancer Risk and Outcomes

DTIC Science & Technology

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

Multilevel corporate environmental responsibility.

PubMed

Karassin, Orr; Bar-Haim, Aviad

2016-12-01

The multilevel empirical study of the antecedents of corporate social responsibility (CSR) has been identified as "the first knowledge gap" in CSR research. Based on an extensive literature review, the present study outlines a conceptual multilevel model of CSR, then designs and empirically validates an operational multilevel model of the principal driving factors affecting corporate environmental responsibility (CER), as a measure of CSR. Both conceptual and operational models incorporate three levels of analysis: institutional, organizational, and individual. The multilevel nature of the design allows for the assessment of the relative importance of the levels and of their components in the achievement of CER. Unweighted least squares (ULS) regression analysis reveals that the institutional-level variables have medium relationships with CER, some variables having a negative effect. The organizational level is revealed as having strong and positive significant relationships with CER, with organizational culture and managers' attitudes and behaviors as significant driving forces. The study demonstrates the importance of multilevel analysis in improving the understanding of CSR drivers, relative to single level models, even if the significance of specific drivers and levels may vary by context. Copyright © 2016 Elsevier Ltd. All rights reserved.

Classification of vegetation types in military region

NASA Astrophysics Data System (ADS)

Gonçalves, Miguel; Silva, Jose Silvestre; Bioucas-Dias, Jose

2015-10-01

In decision-making process regarding planning and execution of military operations, the terrain is a determining factor. Aerial photographs are a source of vital information for the success of an operation in hostile region, namely when the cartographic information behind enemy lines is scarce or non-existent. The objective of present work is the development of a tool capable of processing aerial photos. The methodology implemented starts with feature extraction, followed by the application of an automatic selector of features. The next step, using the k-fold cross validation technique, estimates the input parameters for the following classifiers: Sparse Multinomial Logist Regression (SMLR), K Nearest Neighbor (KNN), Linear Classifier using Principal Component Expansion on the Joint Data (PCLDC) and Multi-Class Support Vector Machine (MSVM). These classifiers were used in two different studies with distinct objectives: discrimination of vegetation's density and identification of vegetation's main components. It was found that the best classifier on the first approach is the Sparse Logistic Multinomial Regression (SMLR). On the second approach, the implemented methodology applied to high resolution images showed that the better performance was achieved by KNN classifier and PCLDC. Comparing the two approaches there is a multiscale issue, in which for different resolutions, the best solution to the problem requires different classifiers and the extraction of different features.

Knowledge and perception on tuberculosis transmission in Tanzania: Multinomial logistic regression analysis of secondary data.

PubMed

Ismail, Abbas; Josephat, Peter

2014-01-01

Tuberculosis (TB) is one of the most important public health problems in Tanzania and was declared as a national public health emergency in 2006. Community and individual knowledge and perceptions are critical factors in the control of the disease. The objective of this study was to analyze the knowledge and perception on the transmission of TB in Tanzania. Multinomial Logistic Regression analysis was considered in order to quantify the impact of knowledge and perception on TB. The data used was adopted as secondary data from larger national survey 2007-08 Tanzania HIV/AIDS and Malaria Indicator Survey. The findings across groups revealed that knowledge on TB transmission increased with an increase in age and level of education. People in rural areas had less knowledge regarding tuberculosis transmission compared to urban areas [OR = 0.7]. People with the access to radio [OR = 1.7] were more knowledgeable on tuberculosis transmission compared to those who did not have access to radio. People who did not have telephone [OR = 0.6] were less knowledgeable on tuberculosis route of transmission compared to those who had telephone. The findings showed that socio-demographic factors such as age, education, place of residence and owning telephone or radio varied systematically with knowledge on tuberculosis transmission.

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

PubMed

Dai, Huanping; Micheyl, Christophe

2012-11-01

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

Perception of Tourists Regarding the Smoke-Free Policy at Suvarnabhumi International Airport, Bangkok, Thailand

PubMed Central

Sirichotiratana, Nithat; Yogi, Subash; Prutipinyo, Chardsumon

2013-01-01

This study was conducted during February-March 2012 to determine the perception and support regarding smoke-free policy among tourists at Suvarnabhumi International Airport, Bangkok, Thailand. In this cross-sectional study, 200 tourists (n = 200) were enrolled by convenience sampling and interviewed by structured questionnaire. Descriptive statistics, chi-square, and multinomial logistic regression were adopted in the study. Results revealed that half (50%) of the tourists were current smokers and 55% had visited Thailand twice or more. Three quarter (76%) of tourists indicated that they would visit Thailand again even if it had a 100% smoke-free regulation. Almost all (99%) of the tourists had supported for the smoke-free policy (partial ban and total ban), and current smokers had higher percentage of support than non-smokers. Two factors, current smoking status and knowledge level, were significantly associated with perception level. After analysis with Multinomial Logistic Regression, it was found that perception, country group, and presence of designated smoking room (DSR) were associated with smoke-free policy. Recommendation is that, at institution level effective monitoring system is needed at the airport. At policy level, the recommendation is that effective comprehensive policy needed to be emphasized to ensure smoke-free airport environment. PMID:23999549

Who Works Among Older Black and White, Well-Functioning Adults in the Health, Aging, and Body Composition Study?

PubMed Central

Rooks, Ronica N.; Simonsick, Eleanor M.; Schulz, Richard; Rubin, Susan; Harris, Tamara

2017-01-01

Objective: The aim of this study is to examine social, economic, and health factors related to paid work in well-functioning older adults and if and how these factors vary by race. Method: We used sex-stratified logistic and multinomial logistic regression to examine cross-sectional data in the Health, Aging, and Body Composition cohort study. The sample included 3,075 community-dwelling Black (42%) and White adults aged 70 to 79 at baseline. Results: Multinomial logistic regression analyses show Black men were more likely to work full-time, and Black women were more likely to work part-time. Men with ≥US$50,000 family income were more likely to work full-time. Men with better physical functioning were more likely to work full- and part-time. Women with ≥US$50,000 family income and fewer chronic diseases were more likely to work full-time. Women who were overweight and had fewer chronic diseases were more likely to work part-time. Discussion: Results suggest that well-functioning, older Black adults were more likely to work than their White counterparts, and working relates to better health and higher income, providing support for a productive or successful aging perspective. PMID:28894767

Multilevel Models for Binary Data

ERIC Educational Resources Information Center

Powers, Daniel A.

2012-01-01

The methods and models for categorical data analysis cover considerable ground, ranging from regression-type models for binary and binomial data, count data, to ordered and unordered polytomous variables, as well as regression models that mix qualitative and continuous data. This article focuses on methods for binary or binomial data, which are…

Longitudinal analysis of the strengths and difficulties questionnaire scores of the Millennium Cohort Study children in England using M-quantile random-effects regression.

PubMed

Tzavidis, Nikos; Salvati, Nicola; Schmid, Timo; Flouri, Eirini; Midouhas, Emily

2016-02-01

Multilevel modelling is a popular approach for longitudinal data analysis. Statistical models conventionally target a parameter at the centre of a distribution. However, when the distribution of the data is asymmetric, modelling other location parameters, e.g. percentiles, may be more informative. We present a new approach, M -quantile random-effects regression, for modelling multilevel data. The proposed method is used for modelling location parameters of the distribution of the strengths and difficulties questionnaire scores of children in England who participate in the Millennium Cohort Study. Quantile mixed models are also considered. The analyses offer insights to child psychologists about the differential effects of risk factors on children's outcomes.

Oral Microbiota and Risk for Esophageal Squamous Cell Carcinoma in a High-Risk Area of China.

PubMed

Chen, Xingdong; Winckler, Björn; Lu, Ming; Cheng, Hongwei; Yuan, Ziyu; Yang, Yajun; Jin, Li; Ye, Weimin

2015-01-01

Poor oral health has been linked with an increased risk of esophageal squamous cell carcinoma (ESCC). We investigated whether alteration of oral microbiota is associated with ESCC risk. Fasting saliva samples were collected from 87 incident and histopathologicallly diagnosed ESCC cases, 63 subjects with dysplasia and 85 healthy controls. All subjects were also interviewed with a questionnaire. V3-V4 region of 16S rRNA was amplified and sequenced by 454-pyrosequencing platform. Carriage of each genus was compared by means of multivariate-adjusted odds ratios derived from logistic regression model. Relative abundance was compared using Metastats method. Beta diversity was estimated using Unifrac and weighted Unifrac distances. Principal coordinate analysis (PCoA) was applied to ordinate dissimilarity matrices. Multinomial logistic regression was used to compare the coordinates between different groups. ESCC subjects had an overall decreased microbial diversity compared to control and dysplasia subjects (P<0.001). Decreased carriage of genera Lautropia, Bulleidia, Catonella, Corynebacterium, Moryella, Peptococcus and Cardiobacterium were found in ESCC subjects compared to non-ESCC subjects. Multinomial logistic regression analyses on PCoA coordinates also revealed that ESCC subjects had significantly different levels for several coordinates compared to non-ESCC subjects. In conclusion, we observed a correlation between altered salivary bacterial microbiota and ESCC risk. The results of our study on the saliva microbiome are of particular interest as it reflects the shift in microbial communities. Further studies are warranted to verify this finding, and if being verified, to explore the underlying mechanisms.

Multilevel covariance regression with correlated random effects in the mean and variance structure.

PubMed

Quintero, Adrian; Lesaffre, Emmanuel

2017-09-01

Multivariate regression methods generally assume a constant covariance matrix for the observations. In case a heteroscedastic model is needed, the parametric and nonparametric covariance regression approaches can be restrictive in the literature. We propose a multilevel regression model for the mean and covariance structure, including random intercepts in both components and allowing for correlation between them. The implied conditional covariance function can be different across clusters as a result of the random effect in the variance structure. In addition, allowing for correlation between the random intercepts in the mean and covariance makes the model convenient for skewedly distributed responses. Furthermore, it permits us to analyse directly the relation between the mean response level and the variability in each cluster. Parameter estimation is carried out via Gibbs sampling. We compare the performance of our model to other covariance modelling approaches in a simulation study. Finally, the proposed model is applied to the RN4CAST dataset to identify the variables that impact burnout of nurses in Belgium. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Contextual determinants of neonatal mortality using two analysis methods, Rio Grande do Sul, Brazil.

PubMed

Zanini, Roselaine Ruviaro; Moraes, Anaelena Bragança de; Giugliani, Elsa Regina Justo; Riboldi, João

2011-02-01

To analyze neonatal mortality determinants using multilevel logistic regression and classic hierarchical models. Cohort study including 138,407 live births with birth certificates and 1,134 neonatal deaths recorded in 2003, in the state of Rio Grande do Sul, Southern Brazil. The Information System on Live Births and mortality records were linked for gathering information on individual-level exposures. Sociodemographic data and information on the pregnancy, childbirth care and characteristics of the children at birth were collected. The associated factors were estimated and compared by traditional and multilevel logistic regression analysis. The neonatal mortality rate was 8.19 deaths per 1,000 live births. Low birth weight, 1- and 5-minute Apgar score below eight, congenital malformation, pre-term birth and previous fetal loss were associated with neonatal death in the traditional model. Elective cesarean section had a protective effect. Previous fetal loss did not remain significant in the multilevel model, but the inclusion of a contextual variable (poverty rate) showed that 15% of neonatal mortality variation can be explained by varying poverty rates in the microregions. The use of multilevel models showed a small effect of contextual determinants on the neonatal mortality rate. There was found a positive association with the poverty rate in the general model, and the proportion of households with water supply among preterm newborns.

Risk Factors for Child Malnutrition in Bangladesh: A Multilevel Analysis of a Nationwide Population-Based Survey.

PubMed

Chowdhury, Mohammad Rocky Khan; Rahman, Mohammad Shafiur; Khan, Mohammad Mubarak Hossain; Mondal, Mohammad Nazrul Islam; Rahman, Mohammad Mosiur; Billah, Baki

2016-05-01

To identify the prevalence and risk factors of child malnutrition in Bangladesh. Data was extracted from the Bangladesh Demographic Health Survey (2011). The outcome measures were stunting, wasting, and underweight. χ(2) analysis was performed to find the association of outcome variables with selected factors. Multilevel logistic regression models with a random intercept at each of the household and community levels were used to identify the risk factors of stunting, wasting, and underweight. From the 2011 survey, 7568 children less than 5 years of age were included in the current analysis. The overall prevalence of stunting, wasting, and underweight was 41.3% (95% CI 39.0-42.9). The χ(2) test and multilevel logistic regression analysis showed that the variables age, sex, mother's body mass index, mother's educational status, father's educational status, place of residence, socioeconomic status, community status, religion, region of residence, and food security are significant factors of child malnutrition. Children with poor socioeconomic and community status were at higher risk of malnutrition. Children from food insecure families were more likely to be malnourished. Significant community- and household-level variations were found. The prevalence of child malnutrition is still high in Bangladesh, and the risk was assessed at several multilevel factors. Therefore, prevention of malnutrition should be given top priority as a major public health intervention. Copyright © 2016 Elsevier Inc. All rights reserved.

Individual and contextual characteristics of indoor and outdoor falls in older residents of São Paulo, Brazil.

PubMed

do Nascimento, Carla Ferreira; Duarte, Yeda Aparecida Oliveira; Lebrão, Maria Lúcia; Chiavegatto Filho, Alexandre Dias Porto

To analyze a representative sample of older individuals of São Paulo, Brazil, according to outdoor fallers, indoor fallers and non-fallers, and to identify biological and socioeconomic (individual and contextual) factors associated with the occurrence and place of falls. A cross-sectional study was conducted using data (n = 1345) from the 2010 wave of the Health, Wellbeing and Aging (SABE) Study, a representative sample of older residents (60 years and older) of São Paulo, Brazil. Multinomial logistic analysis was performed to identify individual factors associated with the occurrence and place of falls, and multilevel multinomial analysis to identify contextual effects (green areas, violence, presence of slums and income inequality). 29% had a fall in the last 12 months, with 59% occurring in indoor spaces. Individuals who had outdoor falls were overall not statistically different from non-fallers; on the other hand, those who had the last fall indoor had worse health status. Moderate homicide rate was a factor associated with increased presence of indoor falls, compared with non-fallers. Our results describe the importance of falls, a common problem in active and community-dwelling older adults of São Paulo, Brazil. Transforming outdoor spaces into walk-friendly areas is essential to allow socialization and autonomy with safety. Creating strategies that take into account the most vulnerable populations, as those who live in violent areas and the oldest older adults, will be a growing challenge among developing countries. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

The importance of proximal fusion level selection for outcomes of multi-level lumbar posterolateral fusion.

PubMed

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.

The Importance of Proximal Fusion Level Selection for Outcomes of Multi-Level Lumbar Posterolateral Fusion

PubMed Central

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

Analyzing Multilevel Data: An Empirical Comparison of Parameter Estimates of Hierarchical Linear Modeling and Ordinary Least Squares Regression

ERIC Educational Resources Information Center

Rocconi, Louis M.

2011-01-01

Hierarchical linear models (HLM) solve the problems associated with the unit of analysis problem such as misestimated standard errors, heterogeneity of regression and aggregation bias by modeling all levels of interest simultaneously. Hierarchical linear modeling resolves the problem of misestimated standard errors by incorporating a unique random…

Minimal intervention dentistry for early childhood caries and child dental anxiety: a randomized controlled trial.

PubMed

Arrow, P; Klobas, E

2017-06-01

To compare changes in child dental anxiety after treatment for early childhood caries (ECC) using two treatment approaches. Children with ECC were randomized to test (atraumatic restorative treatment (ART)-based approach) or control (standard care approach) groups. Children aged 3 years or older completed a dental anxiety scale at baseline and follow up. Changes in child dental anxiety from baseline to follow up were tested using the chi-squared statistic, Wilcoxon rank sum test, McNemar's test and multinomial logistic regression. Two hundred and fifty-four children were randomized (N = 127 test, N = 127 control). At baseline, 193 children completed the dental anxiety scale, 211 at follow up and 170 completed the scale on both occasions. Children who were anxious at baseline (11%) were no longer anxious at follow up, and 11% non-anxious children became anxious. Multinomial logistic regression found each increment in the number of visits increased the odds of worsening dental anxiety (odds ratio (OR), 2.2; P < 0.05), whereas each increment in the number of treatments lowered the odds of worsening anxiety (OR, 0.50; P = 0.05). The ART-based approach to managing ECC resulted in similar levels of dental anxiety to the standard treatment approach and provides a valuable alternative approach to the management of ECC in a primary dental care setting. © 2016 Australian Dental Association.

Predictive occurrence models for coastal wetland plant communities: Delineating hydrologic response surfaces with multinomial logistic regression

NASA Astrophysics Data System (ADS)

Snedden, Gregg A.; Steyer, Gregory D.

2013-02-01

Understanding plant community zonation along estuarine stress gradients is critical for effective conservation and restoration of coastal wetland ecosystems. We related the presence of plant community types to estuarine hydrology at 173 sites across coastal Louisiana. Percent relative cover by species was assessed at each site near the end of the growing season in 2008, and hourly water level and salinity were recorded at each site Oct 2007-Sep 2008. Nine plant community types were delineated with k-means clustering, and indicator species were identified for each of the community types with indicator species analysis. An inverse relation between salinity and species diversity was observed. Canonical correspondence analysis (CCA) effectively segregated the sites across ordination space by community type, and indicated that salinity and tidal amplitude were both important drivers of vegetation composition. Multinomial logistic regression (MLR) and Akaike's Information Criterion (AIC) were used to predict the probability of occurrence of the nine vegetation communities as a function of salinity and tidal amplitude, and probability surfaces obtained from the MLR model corroborated the CCA results. The weighted kappa statistic, calculated from the confusion matrix of predicted versus actual community types, was 0.7 and indicated good agreement between observed community types and model predictions. Our results suggest that models based on a few key hydrologic variables can be valuable tools for predicting vegetation community development when restoring and managing coastal wetlands.

Knowledge about tuberculosis transmission among ever-married women in Bangladesh.

PubMed

Khandoker, A; Khan, M M H; Krämer, A; Mori, M

2011-03-01

To identify the level of knowledge about TB transmission among ever-married women aged 15-49 years (n = 10 996) in Bangladesh, one of the highest tuberculosis (TB) burden countries. We analysed data from the Bangladesh Demographic and Health Survey conducted in 2007. Covariate factors included age, district, urban/rural residence, marital status, education, husband's education and access to the media (television, radio, newspaper/magazine). Bivariate and multinomial logistic regression analyses were performed to find the correlates of correct knowledge of TB transmission. Knowledge about TB transmission was correctly reported by approximately 7.0% of women, and was significantly associated with education, district and access to media using multinomial logistic regression. The likelihood of correct knowledge was 3.5 times (OR 3.5, 95%CI 2.5-4.9) higher among women with ≥11 years of education than among women with no/primary education. A significantly higher OR for correct knowledge of TB transmission (OR 1.5, 95%CI 1.2-1.9) was found among women who watched television almost every day compared to women who watched less than once a week. Correct knowledge about TB transmission was very low among married women in Bangladesh. Factors such as education and access to media, especially television, could play an important role in improving knowledge about TB transmission among women in Bangladesh.

Multinomial logistic regression analysis for differentiating 3 treatment outcome trajectory groups for headache-associated disability.

PubMed

Lewis, Kristin Nicole; Heckman, Bernadette Davantes; Himawan, Lina

2011-08-01

Growth mixture modeling (GMM) identified latent groups based on treatment outcome trajectories of headache disability measures in patients in headache subspecialty treatment clinics. Using a longitudinal design, 219 patients in headache subspecialty clinics in 4 large cities throughout Ohio provided data on their headache disability at pretreatment and 3 follow-up assessments. GMM identified 3 treatment outcome trajectory groups: (1) patients who initiated treatment with elevated disability levels and who reported statistically significant reductions in headache disability (high-disability improvers; 11%); (2) patients who initiated treatment with elevated disability but who reported no reductions in disability (high-disability nonimprovers; 34%); and (3) patients who initiated treatment with moderate disability and who reported statistically significant reductions in headache disability (moderate-disability improvers; 55%). Based on the final multinomial logistic regression model, a dichotomized treatment appointment attendance variable was a statistically significant predictor for differentiating high-disability improvers from high-disability nonimprovers. Three-fourths of patients who initiated treatment with elevated disability levels did not report reductions in disability after 5 months of treatment with new preventive pharmacotherapies. Preventive headache agents may be most efficacious for patients with moderate levels of disability and for patients with high disability levels who attend all treatment appointments. Copyright © 2011 International Association for the Study of Pain. Published by Elsevier B.V. All rights reserved.

Physical victimization, gender identity and suicide risk among transgender men and women.

PubMed

Barboza, Gia Elise; Dominguez, Silvia; Chance, Elena

2016-12-01

We investigated whether being attacked physically due to one's gender identity or expression was associated with suicide risk among trans men and women living in Virginia. The sample consisted of 350 transgender men and women who participated in the Virginia Transgender Health Initiative Survey (THIS). Multivariate multinomial logistic regression was used to explore the competing outcomes associated with suicidal risk. Thirty-seven percent of trans men and women experienced at least one physical attack since the age of 13. On average, individuals experienced 3.97 (SD = 2.86) physical attacks; among these about half were attributed to one's gender identity or expression (mean = 2.08, SD = 1.96). In the multivariate multinomial regression, compared to those with no risk, being physically attacked increased the odds of both attempting and contemplating suicide regardless of gender attribution. Nevertheless, the relative impact of physical victimization on suicidal behavior was higher among those who were targeted on the basis of their gender identity or expression. Finally, no significant association was found between multiple measures of institutional discrimination and suicide risk once discriminatory and non-discriminatory physical victimization was taken into account. Trans men and women experience high levels of physical abuse and face multiple forms of discrimination. They are also at an increased risk for suicidal tendencies. Interventions that help transindividuals cope with discrimination and physical victimization simultaneously may be more effective in saving lives.

Dominance of Sterilization and Alternative Choices of Contraception in India: An Appraisal of the Socioeconomic Impact

PubMed Central

de Oliveira, Isabel Tiago; Dias, José G.; Padmadas, Sabu S.

2014-01-01

Background The recent decline in fertility in India has been unprecedented especially in southern India, where fertility is almost exclusively controlled by means of permanent contraceptive methods, mainly female sterilization, which constitutes about two-thirds of overall contraceptive use. Many Indian women undergo sterilization at relatively young ages as a consequence of early marriage and childbearing in short birth intervals. This research aims to investigate the socioeconomic factors determining the choices for alternative contraceptive choices against the dominant preference for sterilization among married women in India. Methods Data for this study are drawn from the 2005–06 National Family Health Surveys focusing on a sample of married women who reported having used a method of contraception in the five years preceding the survey. A multilevel multinomial logit regression is used to estimate the impact of socioeconomic factors on contraceptive choices, differentiating temporary modern or traditional methods versus sterilization. Findings Religious affiliation, women's education and occupation had overarching influence on method choices amongst recent users. Muslim women were at higher odds of choosing a traditional or modern temporary method than sterilization. Higher level of women's education increased the odds of modern temporary method choices but the education effect on traditional method choices was only marginally significant. Recent users belonging to wealthier households had higher odds of choosing modern methods over sterilization. Exposure to family planning messages through radio had a positive effect on modern and traditional method choices. Community variations in method choices were highly significant. Conclusion The persistent dominance of sterilization in the Indian family planning programme is largely determined by socioeconomic conditions. Reproductive health programmes should address the socioeconomic barriers and consider multiple cost-effective strategies such as mass media to promote awareness of modern temporary methods. PMID:24489759

Built environment characteristics and parent active transportation are associated with active travel to school in youth age 12–15

PubMed Central

Carlson, Jordan A; Sallis, James F; Kerr, Jacqueline; Conway, Terry L; Cain, Kelli; Frank, Lawrence D; Saelens, Brian E

2015-01-01

Purpose To investigate the relation of factors from multiple levels of ecological models (ie, individual, interpersonal and environmental) to active travel to/from school in an observational study of young adolescents. Methods Participants were 294 12–15-year olds living within two miles of their school. Demographic, psychosocial and perceived built environment characteristics around the home were measured by survey, and objective built environment factors around home and school were assessed in Geographic Information Systems (GIS). Mixed effects multinomial regression models tested correlates of engaging in 1–4 (vs 0) and 5–10 (vs 0) active trips/week to/from school, adjusted for distance and other covariates. Results 64% of participants reported ≥1 active trip/ week to/from school. Significant correlates of occasional and/or habitual active travel to/from school included barriers (ORs=0.27 and 0.15), parent modelling of active travel (OR=3.27 for habitual), perceived street connectivity (OR=1.78 for occasional), perceived pedestrian safety around home (OR=2.04 for habitual), objective street connectivity around home (OR=0.97 for occasional), objective residential density around home (ORs=1.10 and 1.11) and objective residential density around school (OR=1.14 for habitual). Parent modelling interacted with pedestrian safety in explaining active travel to/from school. Conclusions Results supported multilevel correlates of adolescents active travel to school, consistent with ecological models. Correlates of occasional and habitual active travel to/from school were similar. Built environment attributes around schools, particularly residential density, should be considered when siting new schools and redeveloping neighbourhoods around existing schools. PMID:24659503

Marginal structural modeling of associations of occupational injuries with voluntary and involuntary job loss among nursing home workers

PubMed Central

Bacic, Janine; Velasquez, Esther; Hammer, Leslie B

2016-01-01

Objectives Qualitative studies have highlighted the possibility of job loss following occupational injuries for some workers, but prospective investigations are scant. We used a sample of nursing home workers from the Work, Family, and Health Network to prospectively investigate association between occupational injuries and job loss. Methods We merged data on 1331 workers assessed four times over an 18-month period with administrative data that include job loss from employers and publicly-available data on their workplaces. Workers self-reported occupational injuries in surveys. Multivariable logistic regression models estimated risk ratios for the impact of occupational injuries on overall job loss, whereas multinomial models were used to estimate odds ratio of voluntary and involuntary job loss. Use of marginal structural models allowed for adjustments of multilevel list of confounders that may be time-varying and/or on the causal pathway. Results By 12 months, 30.3% of workers experienced occupational injury, whereas 24.2% experienced job loss by 18 months. Comparing workers who reported occupational injuries to those reporting no injuries, risk ratio of overall job loss within subsequent 6 months was 1.31 (95% CI=0.93–1.86). Comparing the same groups, injured workers had higher odds of experiencing involuntary job loss (OR:2.19; 95% CI:1.27–3.77). Also, compared to uninjured workers, those injured more than once had higher odds of voluntary job loss (OR:1.95; 95% CI:1.03–3.67), while those injured once had higher odds of involuntary job loss (OR:2.19; 95% CI:1.18–4.05). Conclusions Despite regulatory protections, occupational injuries were associated with increased risk of voluntary and involuntary job loss for nursing home workers. PMID:26786757

Built environment characteristics and parent active transportation are associated with active travel to school in youth age 12-15.

PubMed

Carlson, Jordan A; Sallis, James F; Kerr, Jacqueline; Conway, Terry L; Cain, Kelli; Frank, Lawrence D; Saelens, Brian E

2014-12-01

To investigate the relation of factors from multiple levels of ecological models (ie, individual, interpersonal and environmental) to active travel to/from school in an observational study of young adolescents. Participants were 294 12-15-year olds living within two miles of their school. Demographic, psychosocial and perceived built environment characteristics around the home were measured by survey, and objective built environment factors around home and school were assessed in Geographic Information Systems (GIS). Mixed effects multinomial regression models tested correlates of engaging in 1-4 (vs 0) and 5-10 (vs 0) active trips/week to/from school, adjusted for distance and other covariates. 64% of participants reported ≥1 active trip/week to/from school. Significant correlates of occasional and/or habitual active travel to/from school included barriers (ORs=0.27 and 0.15), parent modelling of active travel (OR=3.27 for habitual), perceived street connectivity (OR=1.78 for occasional), perceived pedestrian safety around home (OR=2.04 for habitual), objective street connectivity around home (OR=0.97 for occasional), objective residential density around home (ORs=1.10 and 1.11) and objective residential density around school (OR=1.14 for habitual). Parent modelling interacted with pedestrian safety in explaining active travel to/from school. Results supported multilevel correlates of adolescents' active travel to school, consistent with ecological models. Correlates of occasional and habitual active travel to/from school were similar. Built environment attributes around schools, particularly residential density, should be considered when siting new schools and redeveloping neighbourhoods around existing schools. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

School environment as predictor of teacher sick leave: data-linked prospective cohort study

PubMed Central

2012-01-01

Background Poor indoor air quality (IAQ) and psychosocial problems are common in schools worldwide, yet longitudinal research on the issue is scarce. We examined whether the level of or a change in pupil-reported school environment (IAQ, school satisfaction, and bullying) predicts recorded sick leaves among teachers. Methods Changes in the school environment were assessed using pupil surveys at two time points (2001/02 and 2004/05) in 92 secondary schools in Finland. Variables indicating change were based on median values at baseline. We linked these data to individual-level records of teachers’ (n = 1678) sick leaves in 2001–02 and in 2004–05. Results Multilevel multinomial logistic regression models adjusted for baseline sick leave and covariates showed a decreased risk for short-term (one to three days) sick leaves among teachers working in schools with good perceived IAQ at both times (OR = 0.6, 95% CI: 0.5-0.9), and for those with a positive change in IAQ (OR = 0.6, 95% CI: 0.4-0.9), compared to teachers in schools where IAQ was constantly poor. Negative changes in pupil school satisfaction (OR = 1.8, 95% CI: 1.1-2.8) and bullying (OR = 1.5, 95% CI: 1.0-2.3) increased the risk for short-term leaves among teachers when compared to teachers in schools where the level of satisfaction and bullying had remained stable. School environment factors were not associated with long-term sick leaves. Conclusions Good and improved IAQ are associated with decreased teacher absenteeism. While pupil-related psychosocial factors also contribute to sick leaves, no effect modification or mediation of psychosocial factors on the association between IAQ and sick leave was observed. PMID:22966903

School environment as predictor of teacher sick leave: data-linked prospective cohort study.

PubMed

Ervasti, Jenni; Kivimäki, Mika; Kawachi, Ichiro; Subramanian, S V; Pentti, Jaana; Oksanen, Tuula; Puusniekka, Riikka; Pohjonen, Tiina; Vahtera, Jussi; Virtanen, Marianna

2012-09-11

Poor indoor air quality (IAQ) and psychosocial problems are common in schools worldwide, yet longitudinal research on the issue is scarce. We examined whether the level of or a change in pupil-reported school environment (IAQ, school satisfaction, and bullying) predicts recorded sick leaves among teachers. Changes in the school environment were assessed using pupil surveys at two time points (2001/02 and 2004/05) in 92 secondary schools in Finland. Variables indicating change were based on median values at baseline. We linked these data to individual-level records of teachers' (n = 1678) sick leaves in 2001-02 and in 2004-05. Multilevel multinomial logistic regression models adjusted for baseline sick leave and covariates showed a decreased risk for short-term (one to three days) sick leaves among teachers working in schools with good perceived IAQ at both times (OR = 0.6, 95% CI: 0.5-0.9), and for those with a positive change in IAQ (OR = 0.6, 95% CI: 0.4-0.9), compared to teachers in schools where IAQ was constantly poor. Negative changes in pupil school satisfaction (OR = 1.8, 95% CI: 1.1-2.8) and bullying (OR = 1.5, 95% CI: 1.0-2.3) increased the risk for short-term leaves among teachers when compared to teachers in schools where the level of satisfaction and bullying had remained stable. School environment factors were not associated with long-term sick leaves. Good and improved IAQ are associated with decreased teacher absenteeism. While pupil-related psychosocial factors also contribute to sick leaves, no effect modification or mediation of psychosocial factors on the association between IAQ and sick leave was observed.

Pupils with special educational needs in basic education schools and teachers' sickness absences--a register-linkage study.

PubMed

Ervasti, Jenni; Kivimäki, Mika; Kawachi, Ichiro; Subramanian, S V; Pentti, Jaana; Ahola, Kirsi; Oksanen, Tuula; Pohjonen, Tiina; Vahtera, Jussi; Virtanen, Marianna

2012-05-01

We examined whether having a high percentage of pupils with special educational needs (SEN) in basic education schools increases the risk of sickness absence among teachers and whether this risk is dependent on the pupil-teacher ratio (PTR), an indicator of teacher resources at school. We obtained register data on 8089 teachers working in 404 schools in 10 municipalities in Finland during the school year 2004-2005. We used multilevel multinomial regression models to examine the risk of teachers' short- and long-term sickness absence in relation to the percentage of SEN pupils and the PTR at school. We tested the equality of trends in groups with high and low PTR using PTR × SEN interaction term. After adjustment for teacher and school characteristics, the risk for long-term absences was higher among teachers at schools with a high percentage of SEN pupils than among teachers at schools with a low percentage of SEN pupils [odds ratio (OR) 1.5, 95% confidence interval (95% CI) 1.2-1.8). This was also the case for short-term absences (OR 1.4, 95% CI 1.2-1.7). In analyses stratified by the PTR levels, the association between the percentage of SEN pupils and long-term absences was 15% higher among teachers with a high PTR than among those with a low PTR (P for interaction=0.10). Teachers' sickness absenteeism seems to increase with a higher percentage of SEN pupils, especially when the PTR is high. Teacher resources at schools that have a high percentage of SEN pupils should be well maintained to ensure the health of teachers.

Dominance of sterilization and alternative choices of contraception in India: an appraisal of the socioeconomic impact.

PubMed

de Oliveira, Isabel Tiago; Dias, José G; Padmadas, Sabu S

2014-01-01

The recent decline in fertility in India has been unprecedented especially in southern India, where fertility is almost exclusively controlled by means of permanent contraceptive methods, mainly female sterilization, which constitutes about two-thirds of overall contraceptive use. Many Indian women undergo sterilization at relatively young ages as a consequence of early marriage and childbearing in short birth intervals. This research aims to investigate the socioeconomic factors determining the choices for alternative contraceptive choices against the dominant preference for sterilization among married women in India. Data for this study are drawn from the 2005-06 National Family Health Surveys focusing on a sample of married women who reported having used a method of contraception in the five years preceding the survey. A multilevel multinomial logit regression is used to estimate the impact of socioeconomic factors on contraceptive choices, differentiating temporary modern or traditional methods versus sterilization. Religious affiliation, women's education and occupation had overarching influence on method choices amongst recent users. Muslim women were at higher odds of choosing a traditional or modern temporary method than sterilization. Higher level of women's education increased the odds of modern temporary method choices but the education effect on traditional method choices was only marginally significant. Recent users belonging to wealthier households had higher odds of choosing modern methods over sterilization. Exposure to family planning messages through radio had a positive effect on modern and traditional method choices. Community variations in method choices were highly significant. The persistent dominance of sterilization in the Indian family planning programme is largely determined by socioeconomic conditions. Reproductive health programmes should address the socioeconomic barriers and consider multiple cost-effective strategies such as mass media to promote awareness of modern temporary methods.

The Norwegian Healthier Goats program--modeling lactation curves using a multilevel cubic spline regression model.

PubMed

Nagel-Alne, G E; Krontveit, R; Bohlin, J; Valle, P S; Skjerve, E; Sølverød, L S

2014-07-01

In 2001, the Norwegian Goat Health Service initiated the Healthier Goats program (HG), with the aim of eradicating caprine arthritis encephalitis, caseous lymphadenitis, and Johne's disease (caprine paratuberculosis) in Norwegian goat herds. The aim of the present study was to explore how control and eradication of the above-mentioned diseases by enrolling in HG affected milk yield by comparison with herds not enrolled in HG. Lactation curves were modeled using a multilevel cubic spline regression model where farm, goat, and lactation were included as random effect parameters. The data material contained 135,446 registrations of daily milk yield from 28,829 lactations in 43 herds. The multilevel cubic spline regression model was applied to 4 categories of data: enrolled early, control early, enrolled late, and control late. For enrolled herds, the early and late notations refer to the situation before and after enrolling in HG; for nonenrolled herds (controls), they refer to development over time, independent of HG. Total milk yield increased in the enrolled herds after eradication: the total milk yields in the fourth lactation were 634.2 and 873.3 kg in enrolled early and enrolled late herds, respectively, and 613.2 and 701.4 kg in the control early and control late herds, respectively. Day of peak yield differed between enrolled and control herds. The day of peak yield came on d 6 of lactation for the control early category for parities 2, 3, and 4, indicating an inability of the goats to further increase their milk yield from the initial level. For enrolled herds, on the other hand, peak yield came between d 49 and 56, indicating a gradual increase in milk yield after kidding. Our results indicate that enrollment in the HG disease eradication program improved the milk yield of dairy goats considerably, and that the multilevel cubic spline regression was a suitable model for exploring effects of disease control and eradication on milk yield. Copyright © 2014 American Dairy Science Association. Published by Elsevier Inc. All rights reserved.

Constructing and validating readability models: the method of integrating multilevel linguistic features with machine learning.

PubMed

Sung, Yao-Ting; Chen, Ju-Ling; Cha, Ji-Her; Tseng, Hou-Chiang; Chang, Tao-Hsing; Chang, Kuo-En

2015-06-01

Multilevel linguistic features have been proposed for discourse analysis, but there have been few applications of multilevel linguistic features to readability models and also few validations of such models. Most traditional readability formulae are based on generalized linear models (GLMs; e.g., discriminant analysis and multiple regression), but these models have to comply with certain statistical assumptions about data properties and include all of the data in formulae construction without pruning the outliers in advance. The use of such readability formulae tends to produce a low text classification accuracy, while using a support vector machine (SVM) in machine learning can enhance the classification outcome. The present study constructed readability models by integrating multilevel linguistic features with SVM, which is more appropriate for text classification. Taking the Chinese language as an example, this study developed 31 linguistic features as the predicting variables at the word, semantic, syntax, and cohesion levels, with grade levels of texts as the criterion variable. The study compared four types of readability models by integrating unilevel and multilevel linguistic features with GLMs and an SVM. The results indicate that adopting a multilevel approach in readability analysis provides a better representation of the complexities of both texts and the reading comprehension process.

Use of multilevel logistic regression to identify the causes of differential item functioning.

PubMed

Balluerka, Nekane; Gorostiaga, Arantxa; Gómez-Benito, Juana; Hidalgo, María Dolores

2010-11-01

Given that a key function of tests is to serve as evaluation instruments and for decision making in the fields of psychology and education, the possibility that some of their items may show differential behaviour is a major concern for psychometricians. In recent decades, important progress has been made as regards the efficacy of techniques designed to detect this differential item functioning (DIF). However, the findings are scant when it comes to explaining its causes. The present study addresses this problem from the perspective of multilevel analysis. Starting from a case study in the area of transcultural comparisons, multilevel logistic regression is used: 1) to identify the item characteristics associated with the presence of DIF; 2) to estimate the proportion of variation in the DIF coefficients that is explained by these characteristics; and 3) to evaluate alternative explanations of the DIF by comparing the explanatory power or fit of different sequential models. The comparison of these models confirmed one of the two alternatives (familiarity with the stimulus) and rejected the other (the topic area) as being a cause of differential functioning with respect to the compared groups.

Multilevel regression models describing regional patterns of invertebrate and algal responses to urbanization across the USA

USGS Publications Warehouse

Cuffney, T.F.; Kashuba, R.; Qian, S.S.; Alameddine, I.; Cha, Y.K.; Lee, B.; Coles, J.F.; McMahon, G.

2011-01-01

Multilevel hierarchical regression was used to examine regional patterns in the responses of benthic macroinvertebrates and algae to urbanization across 9 metropolitan areas of the conterminous USA. Linear regressions established that responses (intercepts and slopes) to urbanization of invertebrates and algae varied among metropolitan areas. Multilevel hierarchical regression models were able to explain these differences on the basis of region-scale predictors. Regional differences in the type of land cover (agriculture or forest) being converted to urban and climatic factors (precipitation and air temperature) accounted for the differences in the response of macroinvertebrates to urbanization based on ordination scores, total richness, Ephemeroptera, Plecoptera, Trichoptera richness, and average tolerance. Regional differences in climate and antecedent agriculture also accounted for differences in the responses of salt-tolerant diatoms, but differences in the responses of other diatom metrics (% eutraphenic, % sensitive, and % silt tolerant) were best explained by regional differences in soils (mean % clay soils). The effects of urbanization were most readily detected in regions where forest lands were being converted to urban land because agricultural development significantly degraded assemblages before urbanization and made detection of urban effects difficult. The effects of climatic factors (temperature, precipitation) on background conditions (biogeographic differences) and rates of response to urbanization were most apparent after accounting for the effects of agricultural development. The effects of climate and land cover on responses to urbanization provide strong evidence that monitoring, mitigation, and restoration efforts must be tailored for specific regions and that attainment goals (background conditions) may not be possible in regions with high levels of prior disturbance (e.g., agricultural development). ?? 2011 by The North American Benthological Society.

Health selection operating between classes and across employment statuses.

PubMed

Ki, Myung; Sacker, Amanda; Kelly, Yvonne; Nazroo, James

2011-12-01

The debate on health selection which describes the influence of health on subsequent social mobility is highly contested. The authors set out to examine the effect of health selection by looking at the effect of previous health status on changes in socio-economic position (SEP) over two time periods. Data were pooled from 13 waves (1991-2003) of the British Household Panel Survey (BHPS). Using a multilevel multinomial approach, the presence of health selection between classes and into/out of employment was concurrently tested and compared. In the descriptive analysis, poor health was consistently associated with moving downward, while the outcome was inverse for upward movement. After accounting for the data structure using multilevel analysis, health was a predictor for social mobility when leaving and entering employment, but the effect was minimal for transitions between classes for both men and women. The non-significant impact of health on mobility inside employment may reflect the presence of the significant impact of health on mobility between employment and non-employment. This implies that the effect of health was not evenly spread over all social mobility, but rather tends to concentrate on some types of mobility. The effect of each predictor on social mobility is more concentrated among specific transitions, and health and age were likely to be substantial in moving into/out of the labour force, whereas education was a relevant predictor for mobility into/out of upper classes, in particular, classes I/II.

Constitution of traditional chinese medicine and related factors in women of childbearing age.

PubMed

Jiang, Qiao-Yu; Li, Jue; Zheng, Liang; Wang, Guang-Hua; Wang, Jing

2018-04-01

This study investigates the constitution of traditional Chinese medicine (TCM) among women who want to be pregnant in one year and explores factors related to TCM constitution. This study was conducted on women who participated in free preconception check-ups provided by the Zhabei District Maternity and Child Care Center in Shanghai, China. The information regarding the female demographic characteristics, physical condition, history of pregnancy and childbearing, diet and behavior, and social psychological factors was collected, and TCM constitution assessment was performed. The Chi-square test, t-test, logistic regression analysis, and multinomial logistic regression analysis were used to explore the related factors of TCM constitution. The participants in this study were aged 28.3 ± 3.0 years. Approximately fifty-five women in this study had Unbalanced Constitution. Logistic regression analysis showed that Shanghai residence, dysmenorrhea, gum bleeding, aversion to vegetables, preference for raw meat, job stress, and economic stress were significantly and negatively associated with Balanced Constitution. Multinomial logistic analysis showed that Shanghai residence was significantly associated with Yang-deficiency, Yin-deficiency, and Stagnant Qi Constitutions; gum bleeding was significantly associated with Yin-deficiency, Stagnant Blood, Stagnant Qi, and Inherited Special Constitutions; aversion to vegetables was significantly associated with Damp-heat Constitution; job stress was significantly associated with Yang-deficiency, Phlegm-dampness, Damp-heat, Stagnant Blood, and Stagnant Qi Constitutions; and economic stress was significantly associated with Yang-deficiency, and Stagnant Qi Constitutions. The application of TCM constitution to preconception care would be beneficial for early identification of potential TCM constitution risks and be beneficial for early intervention (e.g., health education, and dietary education), especially during the women who do not have a medical condition and those who have related factors found in this study. Copyright © 2018. Published by Elsevier Taiwan LLC.

Drinking Patterns and Victimization among Male and Female Students in Mexico

PubMed Central

Strunin, Lee; Díaz-Martínez, L. Rosa; Díaz-Martínez, Alejandro; Heeren, Timothy; Winter, Michael; Kuranz, Seth; Hernández–Ávila, Carlos A.; Fernández-Varela, Héctor; Solís-Torres, Cuauhtémoc

2015-01-01

Aims: The purpose of this study is to estimate the prevalence of alcohol use and alcohol-related consequences, identify drinking profiles using latent profile analysis (LPA), and investigate associations between profiles and violent victimization among young people in Mexico. Methods: LPA identified profiles of drinking behavior in a survey of entering first year university students. Multinomial and logistic regression examined associations between drinking patterns, socio-demographic variables and violent victimization. Results: The LPA identified five profiles of behaviors and consequences among the 22,224 current, former and never drinkers: Non/Infrequent-No Consequences, Occasional-Few Consequences, Regular-Some Consequences, Heavy-Many Consequences and Excessive-Many Consequences drinkers. The Occasional-Few Consequences profile comprised the largest, and the Excessive-Many Consequences profile the smallest, group of drinkers. Multinomial regression showed males and older students more likely to be Heavy or Excessive-Many Consequences drinkers. Living alone was associated with higher odds, and higher maternal education with lower odds, of being a Non/Infrequent-No Consequences drinker. Heavier drinking profiles were more likely to experience violent victimization adverse consequences. Logistic regression showed male and female Heavy and Excessive-Many Consequences drinkers had the highest odds, and Non/Infrequent drinkers the lowest odds, of experiencing any victimization. Conclusion: Findings suggest changes in male and female drinking behavior and a continuation of the established pattern of infrequent but high consumption among Mexican youths. Both male and female Heavy and Excessive-Many Consequences drinkers were at elevated risk for experiencing victimization. Identifying cultural gender norms about drinking including drinker expectations and drinking context that contribute to these patterns can inform prevention efforts. PMID:25534933

The Relationship Between Developmental Assets and Food Security In Adolescents From A Low-Income Community

PubMed Central

Shtasel-Gottlieb, Zoë; Palakshappa, Deepak; Yang, Fanyu; Goodman, Elizabeth

2014-01-01

Purpose To explore the association between developmental assets (characteristics, experiences, and relationships that shape healthy development) and food insecurity among adolescents from a low-income, urban community. Methods This mixed methods study occurred in two phases. In Phase 1, using a census approach, 2350 6-12th graders from the public school district completed an anonymous survey that included the Development Assets Profile (DAP), youth self-report form of the Core Food Security Module, and demographic questions. Logistic and multinomial regression analyses determined independent associations between developmental assets and food security adjusting for demographics. In Phase 2, 20 adult key informant interviews and four semi-structured student focus groups were performed to explain findings from Phase 1. Results On average, DAP scores were consistent with national norms. Food insecurity was prevalent; 14.9% reported low food security and 8.6% very low food security (VLFS). Logistic regression revealed that higher DAP was associated with lower odds of food insecurity (OR=.96, 95% CI=.95-.97); family assets drove this association(OR=.93, 95% CI=.91-.95). In multinomial regression modeling, these associations persisted and, paradoxically, higher community assets were also associated with VLFS (ORVLFS=1.08, 95% CI=1.04-1.13). Qualitative analyses suggested that greater need among VLFS youth led to increased connections to community resources despite barriers to access such as stigma, home instability, and cultural differences. Conclusion Food insecurity is a pervasive problem among adolescents from low-income communities and is associated with lower developmental assets, particularly family assets. That community assets were higher among VLFS youth underscores the importance of community-level resources in struggling areas. PMID:25620305

The relationship between developmental assets and food security in adolescents from a low-income community.

PubMed

Shtasel-Gottlieb, Zoë; Palakshappa, Deepak; Yang, Fanyu; Goodman, Elizabeth

2015-02-01

To explore the association between developmental assets (characteristics, experiences, and relationships that shape healthy development) and food insecurity among adolescents from a low-income urban community. This mixed-methods study occurred in two phases. In phase 1, using a census approach, 2,350 6th to 12th graders from the public school district completed an anonymous survey that included the developmental assets profile (DAP), the youth self-report form of the Core Food Security Module, and demographic questions. Logistic and multinomial regression analyses determined independent associations between developmental assets and food security adjusting for demographics. In phase 2, 20 adult key informant interviews and four semistructured student focus groups were performed to explain findings from phase 1. On average, DAP scores were consistent with national norms. Food insecurity was prevalent; 14.9% reported low food security and 8.6% very low food security (VLFS). Logistic regression revealed that higher DAP was associated with lower odds of food insecurity (odds ratio [OR], .96; 95% confidence interval [CI], .95-.97); family assets drove this association (OR, .93; 95% CI, .91-.95). In multinomial regression modeling, these associations persisted, and paradoxically, higher community assets were also associated with VLFS (ORVLFS, 1.08; 95% CI, 1.04-1.13). Qualitative analyses suggested that greater need among VLFS youth led to increased connections to community resources despite barriers to access such as stigma, home instability, and cultural differences. Food insecurity is a pervasive problem among adolescents from low-income communities and is associated with lower developmental assets, particularly family assets. The fact that community assets were higher among VLFS youth underscores the importance of community-level resources in struggling areas. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Examining the Association between School Context, Educational Capacity, and Student Achievement: A Regression Discontinuity Approach

ERIC Educational Resources Information Center

Moriyama, Karen Ito

2009-01-01

In this era of accountability, there is a need to fairly and accurately document the ways that educational systems contribute to student achievement. This study used the regression discontinuity design within a multilevel framework as an alternative approach to estimate school effectiveness by examining the effect of the value added to students'…

Factors Associated with Substance Use in Adolescents with Eating Disorders

PubMed Central

Mann, Andrea P; Accurso, Erin C.; Stiles-Shields, Colleen; Capra, Lauren; Labuschagne, Zandre; Karnik, Niranjan S.; Grange, Daniel Le

2014-01-01

Purpose To examine the prevalence and potential risk factors associated with substance use in adolescents with eating disorders (EDs). Methods This cross-sectional study included 290 adolescents, ages 12 –18 years, who presented for an initial ED evaluation at The Eating Disorders Program at The University of Chicago Medicine (UCM) between 2001 and 2012. Several factors, including DSM-5 diagnosis, diagnostic scores, and demographic characteristics were examined. Multinomial logistic regression was used to test associations between several factors and patterns of drug use for alcohol, cannabis, tobacco, and any substance. Results Lifetime prevalence of any substance use was found to be 24.6% in those with anorexia nervosa (AN), 48.7% in bulimia nervosa (BN), and 28.6% in eating disorder not otherwise specified (EDNOS). Regular substance use (monthly, daily, and bingeing behaviors) or a substance use disorder (SUD) was found in 27.9% of all patients. Older age was the only factor associated with regular use of any substance in the final multinomial model. Older age and non-White race was associated with greater alcohol and cannabis use. Although binge-purge frequency and BN diagnosis were associated with regular substance use in bivariate analyses, gender, race and age were more robustly associated with substance use in the final multinomial models. Conclusions Co-morbid substance use in adolescents with EDs is an important issue. Interventions targeting high-risk groups reporting regular substance use or SUDs are needed. PMID:24656448

Added sugars and periodontal disease in young adults: an analysis of NHANES III data.

PubMed

Lula, Estevam C O; Ribeiro, Cecilia C C; Hugo, Fernando N; Alves, Cláudia M C; Silva, Antônio A M

2014-10-01

Added sugar consumption seems to trigger a hyperinflammatory state and may result in visceral adiposity, dyslipidemia, and insulin resistance. These conditions are risk factors for periodontal disease. However, the role of sugar intake in the cause of periodontal disease has not been adequately studied. We evaluated the association between the frequency of added sugar consumption and periodontal disease in young adults by using NHANES III data. Data from 2437 young adults (aged 18-25 y) who participated in NHANES III (1988-1994) were analyzed. We estimated the frequency of added sugar consumption by using food-frequency questionnaire responses. We considered periodontal disease to be present in teeth with bleeding on probing and a probing depth ≥3 mm at one or more sites. We evaluated this outcome as a discrete variable in Poisson regression models and as a categorical variable in multinomial logistic regression models adjusted for sex, age, race-ethnicity, education, poverty-income ratio, tobacco exposure, previous diagnosis of diabetes, and body mass index. A high consumption of added sugars was associated with a greater prevalence of periodontal disease in middle [prevalence ratio (PR): 1.39; 95% CI: 1.02, 1.89] and upper (PR: 1.42; 95% CI: 1.08, 1.85) tertiles of consumption in the adjusted Poisson regression model. The upper tertile of added sugar intake was associated with periodontal disease in ≥2 teeth (PR: 1.73; 95% CI: 1.19, 2.52) but not with periodontal disease in only one tooth (PR: 0.85; 95% CI: 0.54, 1.34) in the adjusted multinomial logistic regression model. A high frequency of consumption of added sugars is associated with periodontal disease, independent of traditional risk factors, suggesting that this consumption pattern may contribute to the systemic inflammation observed in periodontal disease and associated noncommunicable diseases. © 2014 American Society for Nutrition.

Effects of road network on diversiform forest cover changes in the highest coverage region in China: An analysis of sampling strategies.

PubMed

Hu, Xisheng; Wu, Zhilong; Wu, Chengzhen; Ye, Limin; Lan, Chaofeng; Tang, Kun; Xu, Lu; Qiu, Rongzu

2016-09-15

Forest cover changes are of global concern due to their roles in global warming and biodiversity. However, many previous studies have ignored the fact that forest loss and forest gain are different processes that may respond to distinct factors by stressing forest loss more than gain or viewing forest cover change as a whole. It behooves us to carefully examine the patterns and drivers of the change by subdividing it into several categories. Our study includes areas of forest loss (4.8% of the study area), forest gain (1.3% of the study area) and forest loss and gain (2.0% of the study area) from 2000 to 2012 in Fujian Province, China. In the study area, approximately 65% and 90% of these changes occurred within 2000m of the nearest road and under road densities of 0.6km/km(2), respectively. We compared two sampling techniques (systematic sampling and random sampling) and four intensities for each technique to investigate the driving patterns underlying the changes using multinomial logistic regression. The results indicated the lack of pronounced differences in the regressions between the two sampling designs, although the sample size had a great impact on the regression outcome. The application of multi-model inference indicated that the low level road density had a negative significant association with forest loss and forest loss and gain, the expressway density had a positive significant impact on forest loss, and the road network was insignificantly related to forest gain. The model including socioeconomic and biophysical variables illuminated potentially different predictors of the different forest change categories. Moreover, the multiple comparisons tested by Fisher's least significant difference (LSD) were a good compensation for the multinomial logistic model to enrich the interpretation of the regression results. Copyright © 2016 Elsevier B.V. All rights reserved.

A nonparametric multiple imputation approach for missing categorical data.

PubMed

Zhou, Muhan; He, Yulei; Yu, Mandi; Hsu, Chiu-Hsieh

2017-06-06

Incomplete categorical variables with more than two categories are common in public health data. However, most of the existing missing-data methods do not use the information from nonresponse (missingness) probabilities. We propose a nearest-neighbour multiple imputation approach to impute a missing at random categorical outcome and to estimate the proportion of each category. The donor set for imputation is formed by measuring distances between each missing value with other non-missing values. The distance function is calculated based on a predictive score, which is derived from two working models: one fits a multinomial logistic regression for predicting the missing categorical outcome (the outcome model) and the other fits a logistic regression for predicting missingness probabilities (the missingness model). A weighting scheme is used to accommodate contributions from two working models when generating the predictive score. A missing value is imputed by randomly selecting one of the non-missing values with the smallest distances. We conduct a simulation to evaluate the performance of the proposed method and compare it with several alternative methods. A real-data application is also presented. The simulation study suggests that the proposed method performs well when missingness probabilities are not extreme under some misspecifications of the working models. However, the calibration estimator, which is also based on two working models, can be highly unstable when missingness probabilities for some observations are extremely high. In this scenario, the proposed method produces more stable and better estimates. In addition, proper weights need to be chosen to balance the contributions from the two working models and achieve optimal results for the proposed method. We conclude that the proposed multiple imputation method is a reasonable approach to dealing with missing categorical outcome data with more than two levels for assessing the distribution of the outcome. In terms of the choices for the working models, we suggest a multinomial logistic regression for predicting the missing outcome and a binary logistic regression for predicting the missingness probability.

Fast food purchasing and access to fast food restaurants: a multilevel analysis of VicLANES.

PubMed

Thornton, Lukar E; Bentley, Rebecca J; Kavanagh, Anne M

2009-05-27

While previous research on fast food access and purchasing has not found evidence of an association, these studies have had methodological problems including aggregation error, lack of specificity between the exposures and outcomes, and lack of adjustment for potential confounding. In this paper we attempt to address these methodological problems using data from the Victorian Lifestyle and Neighbourhood Environments Study (VicLANES) - a cross-sectional multilevel study conducted within metropolitan Melbourne, Australia in 2003. The VicLANES data used in this analysis included 2547 participants from 49 census collector districts in metropolitan Melbourne, Australia. The outcome of interest was the total frequency of fast food purchased for consumption at home within the previous month (never, monthly and weekly) from five major fast food chains (Red Rooster, McDonalds, Kentucky Fried Chicken, Hungry Jacks and Pizza Hut). Three measures of fast food access were created: density and variety, defined as the number of fast food restaurants and the number of different fast food chains within 3 kilometres of road network distance respectively, and proximity defined as the road network distance to the closest fast food restaurant.Multilevel multinomial models were used to estimate the associations between fast food restaurant access and purchasing with never purchased as the reference category. Models were adjusted for confounders including determinants of demand (attitudes and tastes that influence food purchasing decisions) as well as individual and area socio-economic characteristics. Purchasing fast food on a monthly basis was related to the variety of fast food restaurants (odds ratio 1.13; 95% confidence interval 1.02 - 1.25) after adjusting for individual and area characteristics. Density and proximity were not found to be significant predictors of fast food purchasing after adjustment for individual socio-economic predictors. Although we found an independent association between fast food purchasing and access to a wider variety of fast food restaurant, density and proximity were not significant predictors. The methods used in our study are an advance on previous analyses.

Developing soft skill training for salespersons to increase total sales

NASA Astrophysics Data System (ADS)

Mardatillah, A.; Budiman, I.; Tarigan, U. P. P.; Sembiring, A. C.; Hendi

2018-04-01

This research was conducted in the multilevel marketing industry. Unprofessional salespersons behavior and responsibility can ruin the image of the multilevel marketing industry and distrust to the multilevel marketing industry. This leads to decreased company revenue due to lack of public interest in multilevel marketing products. Seeing these conditions, researcher develop training programs to improve the competence of salespersons in making sales. It was done by looking at factors that affect the level of salespersons sales. The research analyzes several factors that influence the salesperson’s sales level: presentation skills, questioning ability, adaptability, technical knowledge, self-control, interaction involvement, sales environment, and intrapersonal skills. Through the analysis of these factors with One Sample T-Test and Multiple Linear Regression methods, researchers design a training program for salespersons to increase their sales. The developed training for salespersons is basic training and special training and before training was given, salespersons need to be assessed for the effectivity and efficiency reasons.

Multilevel poisson regression modelling for determining factors of dengue fever cases in bandung

NASA Astrophysics Data System (ADS)

Arundina, Davila Rubianti; Tantular, Bertho; Pontoh, Resa Septiani

2017-03-01

Scralatina or Dengue Fever is a kind of fever caused by serotype virus which Flavivirus genus and be known as Dengue Virus. Dengue Fever caused by Aedes Aegipty Mosquito bites who infected by a dengue virus. The study was conducted in 151 villages in Bandung. Health Analysts believes that there are two factors that affect the dengue cases, Internal factor (individual) and external factor (environment). The data who used in this research is hierarchical data. The method is used for hierarchical data modelling is multilevel method. Which is, the level 1 is village and level 2 is sub-district. According exploration data analysis, the suitable Multilevel Method is Random Intercept Model. Penalized Quasi Likelihood (PQL) approach on multilevel Poisson is a proper analysis to determine factors that affecting dengue cases in the city of Bandung. Clean and Healthy Behavior factor from the village level have an effect on the number of cases of dengue fever in the city of Bandung. Factor from the sub-district level has no effect.

Preferences for the sex-composition of children in Europe: a multilevel examination of its effect on progression to a third child.

PubMed

Mills, Melinda; Begall, Katia

2010-03-01

Comparative research on the preferred sex of children in Western societies has generally focused on women only and ignored the role of gender equity and the need for children's economic support in old age. A multilevel analysis extends existing research by examining, for both men and women and across 24 European countries, the effect of the preferred sex-composition of offspring on whether parents have or intend to have a third child. Using the European Social Survey (2004/5), a multilevel (random coefficient) ordered logit regression of that intention (N = 3,323) and a binary logistic multilevel model of the transition to a third child (N = 6,502) demonstrate the presence of a mixed-sex preference. In countries with a high risk of poverty in old age, a preference for sons is found, particularly for men. In societies where there is lower gender equity, both men and women have a significant preference for boys.

Undermet needs for assistance in personal activities of daily living among community-dwelling oldest old in China from 2005 to 2008.

PubMed

Peng, Rong; Wu, Bei; Ling, Li

2015-02-01

Based on the 2005 and 2008 Chinese Longitudinal Healthy Longevity Survey, this study examined the prevalence of undermet needs for assistance in personal activities of daily living (ADL) and its associated risk factors among the oldest old aged 80+. Multilevel multinomial logistic modeling was used to analyze the risk factors and changes of undermet needs over time. The results show that the prevalence of slightly undermet needs decreased in urban China from 2005 to 2008. However, the prevalence of undermet needs remained high; 50% or more for both rural and urban residents. Compared to 2005, the likelihood of having slightly undermet needs in 2008 significantly decreased by 28% among rural residents and 22% among urban residents. The common risk factors of undermet needs among rural and urban residents included financial dependence, living alone, having unwilling caregivers, more ADL disabilities, and having poor self-rated health. © The Author(s) 2014.

Neighbourhood food environments and obesity in southeast Louisiana.

PubMed

Hutchinson, Paul L; Nicholas Bodor, J; Swalm, Chris M; Rice, Janet C; Rose, Donald

2012-07-01

Supermarkets might influence food choices, and more distal outcomes like obesity, by increasing the availability of healthy foods. However, recent evidence about their effects is ambiguous, perhaps because supermarkets also increase the availability of unhealthy options. We develop an alternative measure of food environment quality that characterizes urban neighborhoods by the relative amounts of healthy (e.g. fruits and vegetables) to unhealthy foods (e.g. energy-dense snacks). Using data from 307 food stores and 1243 telephone interviews with residents in urban southeastern Louisiana, we estimate a multilevel multinomial logistic model for overweight status. We find that higher quality food environments - but not food store types - decrease the risk of obesity (RR 0.474, 95% CI 0.269-0.835) and overweight (RR 0.532, 95% CI 0.312-0.907). The findings suggest a need to move beyond a sole consideration of food store types to a more nuanced view of the food environment when planning for change. Copyright © 2012 Elsevier Ltd. All rights reserved.

Enrollment Management in Medical School Admissions: A Novel Evidence-Based Approach at One Institution.

PubMed

Burkhardt, John C; DesJardins, Stephen L; Teener, Carol A; Gay, Steven E; Santen, Sally A

2016-11-01

In higher education, enrollment management has been developed to accurately predict the likelihood of enrollment of admitted students. This allows evidence to dictate numbers of interviews scheduled, offers of admission, and financial aid package distribution. The applicability of enrollment management techniques for use in medical education was tested through creation of a predictive enrollment model at the University of Michigan Medical School (U-M). U-M and American Medical College Application Service data (2006-2014) were combined to create a database including applicant demographics, academic application scores, institutional financial aid offer, and choice of school attended. Binomial logistic regression and multinomial logistic regression models were estimated in order to study factors related to enrollment at the local institution versus elsewhere and to groupings of competing peer institutions. A predictive analytic "dashboard" was created for practical use. Both models were significant at P < .001 and had similar predictive performance. In the binomial model female, underrepresented minority students, grade point average, Medical College Admission Test score, admissions committee desirability score, and most individual financial aid offers were significant (P < .05). The significant covariates were similar in the multinomial model (excluding female) and provided separate likelihoods of students enrolling at different institutional types. An enrollment-management-based approach would allow medical schools to better manage the number of students they admit and target recruitment efforts to improve their likelihood of success. It also performs a key institutional research function for understanding failed recruitment of highly desirable candidates.

Monitoring stress and recovery: new insights for the prevention of injuries and illnesses in elite youth soccer players.

PubMed

Brink, Michel S; Visscher, Chris; Arends, Suzanne; Zwerver, Johannes; Post, Wendy J; Lemmink, Koen Apm

2010-09-01

Elite youth soccer players have a relatively high risk for injuries and illnesses due to increased physical and psychosocial stress. The aim of this study is to investigate how measures to monitor stress and recovery, and its analysis, provide useful information for the prevention of injuries and illnesses in elite youth soccer players. 53 elite soccer players between 15 and 18 years of age participated in this study. To determine physical stress, soccer players registered training and match duration and session rating of perceived exertion for two competitive seasons by means of daily training logs. The Dutch version of the Recovery Stress Questionnaire for athletes (RESTQ-Sport) was administered monthly to assess the psychosocial stress-recovery state of players. The medical staff collected injury and illness data using the standardised Fédération Internationale de Football Association registration system. ORs and 95% CIs were calculated for injuries and illnesses using multinomial regression analyses. The independent measures were stress and recovery. During the study period, 320 injuries and 82 illnesses occurred. Multinomial regression demonstrated that physical stress was related to both injury and illness (range OR 1.01 to 2.59). Psychosocial stress and recovery were related the occurrence of illness (range OR 0.56 to 2.27). Injuries are related to physical stress. Physical stress and psychosocial stress and recovery are important in relation to illness. Individual monitoring of stress and recovery may provide useful information to prevent soccer players from injuries and illnesses.

The status of diabetes control in Kurdistan province, west of Iran.

PubMed

Esmailnasab, Nader; Afkhamzadeh, Abdorrahim; Roshani, Daem; Moradi, Ghobad

2013-09-17

Based on some estimation more than two million peoples in Iran are affected by Type 2 diabetes. The present study was designed to evaluate the status of diabetes control among Type 2 diabetes patients in Kurdistan, west of Iran and its associated factors. In our cross sectional study conducted in 2010, 411 Type 2 diabetes patients were randomly recruited from Sanandaj, Capital of Kurdistan. Chi square test was used in univariate analysis to address the association between HgAlc and FBS status and other variables. The significant results from Univariate analysis were entered in multivariate analysis and multinomial logistic regression model. In 38% of patients, FBS was in normal range (70-130) and in 47% HgA1c was <7% which is normal range for HgA1c. In univariate analysis, FBS level was associated with educational levels (P=0.001), referral style (P=0.001), referral time (P=0.009), and insulin injection (P=0.016). In addition, HgA1c had a relationship with sex (P=0.023), age (P=0.035), education (P=0.001), referral style (P=0.001), and insulin injection (P=0.008). After using multinomial logistic regression for significant results of univariate analysis, it was found that FBS was significantly associated with referral style. In addition HgA1c was significantly associated with referral style and Insulin injection. Although some of patients were under the coverage of specialized cares, but their diabetes were not properly controlled.

Predictive occurrence models for coastal wetland plant communities: delineating hydrologic response surfaces with multinomial logistic regression

USGS Publications Warehouse

Snedden, Gregg A.; Steyer, Gregory D.

2013-01-01

Understanding plant community zonation along estuarine stress gradients is critical for effective conservation and restoration of coastal wetland ecosystems. We related the presence of plant community types to estuarine hydrology at 173 sites across coastal Louisiana. Percent relative cover by species was assessed at each site near the end of the growing season in 2008, and hourly water level and salinity were recorded at each site Oct 2007–Sep 2008. Nine plant community types were delineated with k-means clustering, and indicator species were identified for each of the community types with indicator species analysis. An inverse relation between salinity and species diversity was observed. Canonical correspondence analysis (CCA) effectively segregated the sites across ordination space by community type, and indicated that salinity and tidal amplitude were both important drivers of vegetation composition. Multinomial logistic regression (MLR) and Akaike's Information Criterion (AIC) were used to predict the probability of occurrence of the nine vegetation communities as a function of salinity and tidal amplitude, and probability surfaces obtained from the MLR model corroborated the CCA results. The weighted kappa statistic, calculated from the confusion matrix of predicted versus actual community types, was 0.7 and indicated good agreement between observed community types and model predictions. Our results suggest that models based on a few key hydrologic variables can be valuable tools for predicting vegetation community development when restoring and managing coastal wetlands.

Shared clinical decision making

PubMed Central

AlHaqwi, Ali I.; AlDrees, Turki M.; AlRumayyan, Ahmad; AlFarhan, Ali I.; Alotaibi, Sultan S.; AlKhashan, Hesham I.; Badri, Motasim

2015-01-01

Objectives: To determine preferences of patients regarding their involvement in the clinical decision making process and the related factors in Saudi Arabia. Methods: This cross-sectional study was conducted in a major family practice center in King Abdulaziz Medical City, Riyadh, Saudi Arabia, between March and May 2012. Multivariate multinomial regression models were fitted to identify factors associated with patients preferences. Results: The study included 236 participants. The most preferred decision-making style was shared decision-making (57%), followed by paternalistic (28%), and informed consumerism (14%). The preference for shared clinical decision making was significantly higher among male patients and those with higher level of education, whereas paternalism was significantly higher among older patients and those with chronic health conditions, and consumerism was significantly higher in younger age groups. In multivariate multinomial regression analysis, compared with the shared group, the consumerism group were more likely to be female [adjusted odds ratio (AOR) =2.87, 95% confidence interval [CI] 1.31-6.27, p=0.008] and non-dyslipidemic (AOR=2.90, 95% CI: 1.03-8.09, p=0.04), and the paternalism group were more likely to be older (AOR=1.03, 95% CI: 1.01-1.05, p=0.04), and female (AOR=2.47, 95% CI: 1.32-4.06, p=0.008). Conclusion: Preferences of patients for involvement in the clinical decision-making varied considerably. In our setting, underlying factors that influence these preferences identified in this study should be considered and tailored individually to achieve optimal treatment outcomes. PMID:26620990

Association of personality, neighbourhood, and civic participation with the level of perceived social support: the HUNT study, a cross-sectional survey.

PubMed

Grav, Siv; Romild, Ulla; Hellzèn, Ove; Stordal, Eystein

2013-08-01

The aim of the current study was to examine the association of personality, neighbourhood, and civic participation with the level of perceived social support if needed. The sample consists of a total of 35,797 men (16,035) and women (19,762) drawn from the Nord-Trøndelag Health Study 3 (HUNT3), aged 20-89, with a fully completed short version of the Eysenck Personality Questionnaire (EPQ) including a complete response to questions regarding perceived social support. A multinomial logistic regression model was used to investigate the association between the three-category outcomes (high, medium, and low) of perceived social support. The Chi-square test detected a significant (p < 0.001) association between personality, sense of community, civic participation, self-rated health, living arrangement, age groups, gender, and perceived social support, except between perceived social support and loss of social network, in which no significance was found. The crude and adjusted multinomial logistic regression models show a relation between medium and low scores on perceived social support, personality, and sources of social support. Interactions were observed between gender and self-rated health. There is an association between the level of perceived social support and personality, sense of community in the neighbourhood, and civic participation. Even if the interaction between men and self-reported health decreases the odds for low and medium social support, health professionals should be aware of men with poor health and their lack of social support.

Determinants of modern contraceptive use among sexually active men in Kenya.

PubMed

Ochako, Rhoune; Temmerman, Marleen; Mbondo, Mwende; Askew, Ian

2017-04-27

Research in Kenya has focussed on family planning from women's perspectives, with the aim of helping reduce the burden of unintended pregnancies. As such, the determinants of modern contraceptive use among sexually active women are well documented. However, the perspectives of men should be considered not only as women's partners, but also as individuals with distinct reproductive histories and desires of their own. This study seeks to understand the determinants of modern contraceptive use among sexually active men, by exploring factors that are correlated with modern contraceptive use. The data source is the nationally representative 2014 Kenya Demographic and Health Survey (DHS) of men aged 15-54 years. The analysis is restricted to 9,514 men who reported being sexually active in the past 12 months prior to the survey, as they were likely to report either doing something or not to avoid or delay pregnancy. We use bivariate and multinomial logistic regression to assess factors that influence modern contraceptive use among sexually active men. Findings from the bivariate and multinomial logistic regression indicate that region of residence, marital status, religion, wealth, interaction with a health care provider, fertility preference, number of sexual partners and access to media were all significantly associated with modern contraceptive use among sexually active men. Provider-client interaction as well as dissemination of information through mass media has the potential to increase knowledge and uptake of modern contraceptives. Similar efforts targeting segments of the population where contraceptive uptake is low are recommended.

Association between employee benefits and frailty in community-dwelling older adults.

PubMed

Avila-Funes, José Alberto; Paniagua-Santos, Diana Leticia; Escobar-Rivera, Vicente; Navarrete-Reyes, Ana Patricia; Aguilar-Navarro, Sara; Amieva, Hélène

2016-05-01

The phenotype of frailty has been associated with an increased vulnerability for the development of adverse health-related outcomes. The origin of frailty is multifactorial and financial issues could be implicated, as they have been associated with health status, well-being and mortality. However, the association between economic benefits and frailty has been poorly explored. Therefore, the objective was to determine the association between employee benefits and frailty. A cross-sectional study of 927 community-dwelling older adults aged 70 years and older participating in the Mexican Study of Nutritional and Psychosocial Markers of Frailty was carried out. Employee benefits were established according to eight characteristics: bonus, profit sharing, pension, health insurance, food stamps, housing credit, life insurance, and Christmas bonus. Frailty was defined according to a slightly modified version of the phenotype proposed by Fried et al. Multinomial logistic regression models were run to determine the association between employee benefits and frailty adjusting by sociodemographic and health covariates. The prevalence of frailty was 14.1%, and 4.4% of participants rated their health status as "poor." Multinomial logistic regression analyses showed that employee benefits were statistically and independently associated with the frail subgroup (OR 0.85; 95% CI 0.74-0.98; P = 0.027) even after adjusting for potential confounders. Fewer employee benefits are associated with frailty. Supporting spreading employee benefits for older people could have a positive impact on the development of frailty and its consequences. Geriatr Gerontol Int 2016; 16: 606-611. © 2015 Japan Geriatrics Society.

Many-level multilevel structural equation modeling: An efficient evaluation strategy.

PubMed

Pritikin, Joshua N; Hunter, Michael D; von Oertzen, Timo; Brick, Timothy R; Boker, Steven M

2017-01-01

Structural equation models are increasingly used for clustered or multilevel data in cases where mixed regression is too inflexible. However, when there are many levels of nesting, these models can become difficult to estimate. We introduce a novel evaluation strategy, Rampart, that applies an orthogonal rotation to the parts of a model that conform to commonly met requirements. This rotation dramatically simplifies fit evaluation in a way that becomes more potent as the size of the data set increases. We validate and evaluate the implementation using a 3-level latent regression simulation study. Then we analyze data from a state-wide child behavioral health measure administered by the Oklahoma Department of Human Services. We demonstrate the efficiency of Rampart compared to other similar software using a latent factor model with a 5-level decomposition of latent variance. Rampart is implemented in OpenMx, a free and open source software.

Robust Mediation Analysis Based on Median Regression

PubMed Central

Yuan, Ying; MacKinnon, David P.

2014-01-01

Mediation analysis has many applications in psychology and the social sciences. The most prevalent methods typically assume that the error distribution is normal and homoscedastic. However, this assumption may rarely be met in practice, which can affect the validity of the mediation analysis. To address this problem, we propose robust mediation analysis based on median regression. Our approach is robust to various departures from the assumption of homoscedasticity and normality, including heavy-tailed, skewed, contaminated, and heteroscedastic distributions. Simulation studies show that under these circumstances, the proposed method is more efficient and powerful than standard mediation analysis. We further extend the proposed robust method to multilevel mediation analysis, and demonstrate through simulation studies that the new approach outperforms the standard multilevel mediation analysis. We illustrate the proposed method using data from a program designed to increase reemployment and enhance mental health of job seekers. PMID:24079925

Multilevel Effects of Wealth on Women's Contraceptive Use in Mozambique

PubMed Central

Dias, José G.; de Oliveira, Isabel Tiago

2015-01-01

Objective This paper analyzes the impact of wealth on the use of contraception in Mozambique unmixing the contextual effects due to community wealth from the individual effects associated with the women's situation within the community of residence. Methods Data from the 2011 Mozambican Demographic and Health Survey on women who are married or living together are analyzed for the entire country and also for the rural and urban areas separately. We used single level and multilevel probit regression models. Findings A single level probit regression reveals that region, religion, age, previous fertility, education, and wealth impact contraceptive behavior. The multilevel analysis shows that average community wealth and the women’s relative socioeconomic position within the community have significant positive effects on the use of modern contraceptives. The multilevel framework proved to be necessary in rural settings but not relevant in urban areas. Moreover, the contextual effects due to community wealth are greater in rural than in urban areas and this feature is associated with the higher socioeconomic heterogeneity within the richest communities. Conclusion This analysis highlights the need for the studies on contraceptive behavior to specifically address the individual and contextual effects arising from the poverty-wealth dimension in rural and urban areas separately. The inclusion in a particular community of residence is not relevant in urban areas, but it is an important feature in rural areas. Although the women's individual position within the community of residence has a similar effect on contraceptive adoption in rural and urban settings, the impact of community wealth is greater in rural areas and smaller in urban areas. PMID:25786228

Effects of Individual Nurse and Hospital Characteristics on Patient Adverse Events and Quality of Care: A Multilevel Analysis.

PubMed

Lee, Seung Eun; Vincent, Catherine; Dahinten, V Susan; Scott, Linda D; Park, Chang Gi; Dunn Lopez, Karen

2018-06-14

This study aimed to investigate effects of individual nurse and hospital characteristics on patient adverse events and quality of care using a multilevel approach. This is a secondary analysis of a combination of nurse survey data (N = 1,053 nurses) and facility data (N = 63 hospitals) in Canada. Multilevel ordinal logistic regression was employed to examine effects of individual nurse and hospital characteristics on patient adverse events. Multilevel linear regressions were used to investigate effects of individual nurse and hospital characteristics on quality of care. Organizational safety culture was associated with patient adverse events and quality of care. Controlling for effects of nurse and hospital characteristics, nurses in hospitals with a stronger safety culture were 64% less likely to report administration of wrong medication, time, or dose; 58% less likely to report patient falls with injury; and 60% less likely to report urinary tract infections; and were more likely to report higher levels of quality of care. Additionally, the effects of individual-level baccalaureate education and years of experience on quality of care differed across hospitals, and hospital-level nurse education interacted with individual-level baccalaureate education. This study makes significant contributions to existing knowledge regarding the positive effect of organizational safety culture on patient adverse events and quality of care. Healthcare organizations should strive to improve their safety culture by creating environments where healthcare providers trust each other, work collaboratively, and share accountability for patient safety and care quality. © 2018 Sigma Theta Tau International.

Elder abuse and socioeconomic inequalities: a multilevel study in 7 European countries.

PubMed

Fraga, Sílvia; Lindert, Jutta; Barros, Henrique; Torres-González, Francisco; Ioannidi-Kapolou, Elisabeth; Melchiorre, Maria Gabriella; Stankunas, Mindaugas; Soares, Joaquim F

2014-04-01

To compare the prevalence of elder abuse using a multilevel approach that takes into account the characteristics of participants as well as socioeconomic indicators at city and country level. In 2009, the project on abuse of elderly in Europe (ABUEL) was conducted in seven cities (Stuttgart, Germany; Ancona, Italy; Kaunas, Lithuania, Stockholm, Sweden; Porto, Portugal; Granada, Spain; Athens, Greece) comprising 4467 individuals aged 60-84 years. We used a 3-level hierarchical structure of data: 1) characteristics of participants; 2) mean of tertiary education of each city; and 3) country inequality indicator (Gini coefficient). Multilevel logistic regression was used and proportional changes in Intraclass Correlation Coefficient (ICC) were inspected to assert explained variance between models. The prevalence of elder abuse showed large variations across sites. Adding tertiary education to the regression model reduced the country level variance for psychological abuse (ICC=3.4%), with no significant decrease in the explained variance for the other types of abuse. When the Gini coefficient was considered, the highest drop in ICC was observed for financial abuse (from 9.5% to 4.3%). There is a societal and community level dimension that adds information to individual variability in explaining country differences in elder abuse, highlighting underlying socioeconomic inequalities leading to such behavior. Copyright © 2014 Elsevier Inc. All rights reserved.

Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data

PubMed Central

Sharafi, Zahra

2017-01-01

Background The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF) in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts) from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. Methods The ordinal logistic regression (OLR) and hierarchical ordinal logistic regression (HOLR) were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter) with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™) 4.0 collected from 576 healthy school children were analyzed. Results Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. Conclusions The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed. PMID:29312463

Assessment of Differential Item Functioning in Health-Related Outcomes: A Simulation and Empirical Analysis with Hierarchical Polytomous Data.

PubMed

Sharafi, Zahra; Mousavi, Amin; Ayatollahi, Seyyed Mohammad Taghi; Jafari, Peyman

2017-01-01

The purpose of this study was to evaluate the effectiveness of two methods of detecting differential item functioning (DIF) in the presence of multilevel data and polytomously scored items. The assessment of DIF with multilevel data (e.g., patients nested within hospitals, hospitals nested within districts) from large-scale assessment programs has received considerable attention but very few studies evaluated the effect of hierarchical structure of data on DIF detection for polytomously scored items. The ordinal logistic regression (OLR) and hierarchical ordinal logistic regression (HOLR) were utilized to assess DIF in simulated and real multilevel polytomous data. Six factors (DIF magnitude, grouping variable, intraclass correlation coefficient, number of clusters, number of participants per cluster, and item discrimination parameter) with a fully crossed design were considered in the simulation study. Furthermore, data of Pediatric Quality of Life Inventory™ (PedsQL™) 4.0 collected from 576 healthy school children were analyzed. Overall, results indicate that both methods performed equivalently in terms of controlling Type I error and detection power rates. The current study showed negligible difference between OLR and HOLR in detecting DIF with polytomously scored items in a hierarchical structure. Implications and considerations while analyzing real data were also discussed.

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications

PubMed Central

Austin, Peter C.

2017-01-01

Summary Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log–log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata). PMID:29307954

A Tutorial on Multilevel Survival Analysis: Methods, Models and Applications.

PubMed

Austin, Peter C

2017-08-01

Data that have a multilevel structure occur frequently across a range of disciplines, including epidemiology, health services research, public health, education and sociology. We describe three families of regression models for the analysis of multilevel survival data. First, Cox proportional hazards models with mixed effects incorporate cluster-specific random effects that modify the baseline hazard function. Second, piecewise exponential survival models partition the duration of follow-up into mutually exclusive intervals and fit a model that assumes that the hazard function is constant within each interval. This is equivalent to a Poisson regression model that incorporates the duration of exposure within each interval. By incorporating cluster-specific random effects, generalised linear mixed models can be used to analyse these data. Third, after partitioning the duration of follow-up into mutually exclusive intervals, one can use discrete time survival models that use a complementary log-log generalised linear model to model the occurrence of the outcome of interest within each interval. Random effects can be incorporated to account for within-cluster homogeneity in outcomes. We illustrate the application of these methods using data consisting of patients hospitalised with a heart attack. We illustrate the application of these methods using three statistical programming languages (R, SAS and Stata).

Realist explanatory theory building method for social epidemiology: a protocol for a mixed method multilevel study of neighbourhood context and postnatal depression.

PubMed

Eastwood, John G; Jalaludin, Bin B; Kemp, Lynn A

2014-01-01

A recent criticism of social epidemiological studies, and multi-level studies in particular has been a paucity of theory. We will present here the protocol for a study that aims to build a theory of the social epidemiology of maternal depression. We use a critical realist approach which is trans-disciplinary, encompassing both quantitative and qualitative traditions, and that assumes both ontological and hierarchical stratification of reality. We describe a critical realist Explanatory Theory Building Method comprising of an: 1) emergent phase, 2) construction phase, and 3) confirmatory phase. A concurrent triangulated mixed method multilevel cross-sectional study design is described. The Emergent Phase uses: interviews, focus groups, exploratory data analysis, exploratory factor analysis, regression, and multilevel Bayesian spatial data analysis to detect and describe phenomena. Abductive and retroductive reasoning will be applied to: categorical principal component analysis, exploratory factor analysis, regression, coding of concepts and categories, constant comparative analysis, drawing of conceptual networks, and situational analysis to generate theoretical concepts. The Theory Construction Phase will include: 1) defining stratified levels; 2) analytic resolution; 3) abductive reasoning; 4) comparative analysis (triangulation); 5) retroduction; 6) postulate and proposition development; 7) comparison and assessment of theories; and 8) conceptual frameworks and model development. The strength of the critical realist methodology described is the extent to which this paradigm is able to support the epistemological, ontological, axiological, methodological and rhetorical positions of both quantitative and qualitative research in the field of social epidemiology. The extensive multilevel Bayesian studies, intensive qualitative studies, latent variable theory, abductive triangulation, and Inference to Best Explanation provide a strong foundation for Theory Construction. The study will contribute to defining the role that realism and mixed methods can play in explaining the social determinants and developmental origins of health and disease.

Growth in Reading Performance during the First Four Years in School. Research Report. ETS RR-07-39

ERIC Educational Resources Information Center

Rock, Donald A.

2007-01-01

This study addressed concerns about the potential for differential gains in reading during the first 2 years of formal schooling (K-1) versus the next 2 years of schooling (1st-3rd grade). A multilevel piecewise regression with a node at spring 1st grade was used in order to define separate regressions for the two time periods. Empirical Bayes…

Identifying the determinants of childhood immunization in the Philippines.

PubMed

Bondy, Jennifer N; Thind, Amardeep; Koval, John J; Speechley, Kathy N

2009-01-01

A key method of reducing morbidity and mortality is childhood immunization, yet in 2003 only 69% of Filipino children received all suggested vaccinations. Data from the 2003 Philippines Demographic Health Survey were used to identify risk factors for non- and partial-immunization. Results of the multinomial logistic regression analyses indicate that mothers who have less education, and who have not attended the minimally-recommended four antenatal visits are less likely to have fully immunized children. To increase immunization coverage in the Philippines, knowledge transfer to mothers must improve.

Individual and area-level socioeconomic associations with fast food purchasing.

PubMed

Thornton, Lukar E; Bentley, Rebecca J; Kavanagh, Anne M

2011-10-01

It has been suggested that those with lower socioeconomic characteristics would be more likely to seek energy-dense food options such as fast food because of cheaper prices; however, to date the evidence has been inconsistent. This study examines both individual- and area-level socioeconomic characteristics and their independent associations with chain-brand fast food purchasing. Data from the 2003 Victorian Lifestyle and Neighbourhood Environments Study (VicLANES); a multilevel study of 2,547 adults from 49 small-areas in Melbourne, Australia, were used. Multilevel multinomial models adjusted for confounders were used to assess associations between individual socioeconomic position (education, occupation and income) and area socioeconomic characteristics in relation to fast food purchasing from five major fast food chains with outcome categories: never, at least monthly and at least weekly. The study finally assessed whether any potential area-level associations were mediated by fast food access. Increased fast food purchasing was independently associated with lower education, being a blue-collar employee and decreased household income. Results for area-level disadvantage were marginally insignificant after adjustment for individual-level characteristics, although they were suggestive that living in an area with greater levels of disadvantage increased an individual's odds of more frequent fast food purchasing. This effect was further attenuated when measures of fast food restaurant access were included in the models. Independent effects of lower individual-level socioeconomic characteristics and more frequent fast food purchasing for home consumption are demonstrated. Although evidence was suggestive of an independent association with area-level disadvantage this did not reach statistical significance.

An Empirical Bayes Estimate of Multinomial Probabilities.

DTIC Science & Technology

1982-02-01

multinomial probabilities has been considered from a decision theoretic point of view by Steinhaus (1957), Trybula (1958) and Rutkowska (1977). In a recent...variate Rypergeometric and Multinomial Distributions," Zastosowania Matematyki, 16, 9-21. Steinhaus , H. (1957), "The Problem of Estimation." Annals of

Modeling abundance using multinomial N-mixture models

USGS Publications Warehouse

Royle, Andy

2016-01-01

Multinomial N-mixture models are a generalization of the binomial N-mixture models described in Chapter 6 to allow for more complex and informative sampling protocols beyond simple counts. Many commonly used protocols such as multiple observer sampling, removal sampling, and capture-recapture produce a multivariate count frequency that has a multinomial distribution and for which multinomial N-mixture models can be developed. Such protocols typically result in more precise estimates than binomial mixture models because they provide direct information about parameters of the observation process. We demonstrate the analysis of these models in BUGS using several distinct formulations that afford great flexibility in the types of models that can be developed, and we demonstrate likelihood analysis using the unmarked package. Spatially stratified capture-recapture models are one class of models that fall into the multinomial N-mixture framework, and we discuss analysis of stratified versions of classical models such as model Mb, Mh and other classes of models that are only possible to describe within the multinomial N-mixture framework.

Improvement of the Work Environment and Work-Related Stress: A Cross-Sectional Multilevel Study of a Nationally Representative Sample of Japanese Workers.

PubMed

Watanabe, Kazuhiro; Tabuchi, Takahiro; Kawakami, Norito

2017-03-01

This cross-sectional multilevel study aimed to investigate the relationship between improvement of the work environment and work-related stress in a nationally representative sample in Japan. The study was based on a national survey that randomly sampled 1745 worksites and 17,500 nested employees. The survey asked the worksites whether improvements of the work environment were conducted; and it asked the employees to report the number of work-related stresses they experienced. Multilevel multinominal logistic and linear regression analyses were conducted. Improvement of the work environment was not significantly associated with any level of work-related stress. Among men, it was significantly and negatively associated with the severe level of work-related stress. The association was not significant among women. Improvements to work environments may be associated with reduced work-related stress among men nationwide in Japan.

Role Stress and Emotional Exhaustion Among Health Care Workers: The Buffering Effect of Supportive Coworker Climate in a Multilevel Perspective.

PubMed

Portoghese, Igor; Galletta, Maura; Burdorf, Alex; Cocco, Pierluigi; D'Aloja, Ernesto; Campagna, Marcello

2017-10-01

The aim of the study was to examine the relationship between role stress, emotional exhaustion, and a supportive coworker climate among health care workers, by adopting a multilevel perspective. Aggregated data of 738 health care workers nested within 67 teams of three Italian hospitals were collected. Multilevel regression analysis with a random intercept model was used. Hierarchical linear modeling showed that a lack of role clarity was significantly linked to emotional exhaustion at the individual level. At the unit level, the cross-level interaction revealed that a supportive coworker climate moderated the relationship between lack of role clarity and emotional exhaustion. This study supports previous results of single-level burnout studies, extending the existing literature with evidence on the multidimensional and cross-level interaction associations of a supportive coworker climate as a key aspect of job resources on burnout.

Income Inequality or Performance Gap? A Multilevel Study of School Violence in 52 Countries.

PubMed

Contreras, Dante; Elacqua, Gregory; Martinez, Matias; Miranda, Álvaro

2015-11-01

The purpose of the study was to examine the association between income inequality and school violence and between the performance inequality and school violence in two international samples. The study used data from Trends in International Mathematics and Science Study 2011 and from the Central Intelligence Agency of United States which combined information about academic performance and students' victimization (physical and social) for 269,456 fourth-grade students and 261,747 eighth-grade students, with gross domestic product and income inequality data in 52 countries. Ecological correlations tested associations between income inequality and victimization and between school performance inequality and victimization among countries. Multilevel ordinal regression and multilevel regression analyses tested the strength of these associations when controlling for socioeconomic and academic performance inequality at school level and family socioeconomic status and academic achievement at student level. Income inequality was associated with victimization rates in both fourth and eighth grade (r ≈ .60). Performance inequality shows stronger association with victimization among eighth graders (r ≈ .46) compared with fourth graders (r ≈ .30). Multilevel analyses indicate that both an increase in the income inequality in the country and school corresponds with more frequent physical and social victimization. On the other hand, an increase in the performance inequality at the system level shows no consistent association to victimization. However, school performance inequality seems related to an increase in both types of victimizations. Our results contribute to the finding that income inequality is a determinant of school violence. This result holds regardless of the national performance inequality between students. Copyright © 2015 Society for Adolescent Health and Medicine. Published by Elsevier Inc. All rights reserved.

Estimating trajectories of energy intake through childhood and adolescence using linear-spline multilevel models.

PubMed

Anderson, Emma L; Tilling, Kate; Fraser, Abigail; Macdonald-Wallis, Corrie; Emmett, Pauline; Cribb, Victoria; Northstone, Kate; Lawlor, Debbie A; Howe, Laura D

2013-07-01

Methods for the assessment of changes in dietary intake across the life course are underdeveloped. We demonstrate the use of linear-spline multilevel models to summarize energy-intake trajectories through childhood and adolescence and their application as exposures, outcomes, or mediators. The Avon Longitudinal Study of Parents and Children assessed children's dietary intake several times between ages 3 and 13 years, using both food frequency questionnaires (FFQs) and 3-day food diaries. We estimated energy-intake trajectories for 12,032 children using linear-spline multilevel models. We then assessed the associations of these trajectories with maternal body mass index (BMI), and later offspring BMI, and also their role in mediating the relation between maternal and offspring BMIs. Models estimated average and individual energy intake at 3 years, and linear changes in energy intake from age 3 to 7 years and from age 7 to 13 years. By including the exposure (in this example, maternal BMI) in the multilevel model, we were able to estimate the average energy-intake trajectories across levels of the exposure. When energy-intake trajectories are the exposure for a later outcome (in this case offspring BMI) or a mediator (between maternal and offspring BMI), results were similar, whether using a two-step process (exporting individual-level intercepts and slopes from multilevel models and using these in linear regression/path analysis), or a single-step process (multivariate multilevel models). Trajectories were similar when FFQs and food diaries were assessed either separately, or when combined into one model. Linear-spline multilevel models provide useful summaries of trajectories of dietary intake that can be used as an exposure, outcome, or mediator.

Associations of financial stressors and physical intimate partner violence perpetration.

PubMed

Schwab-Reese, Laura M; Peek-Asa, Corinne; Parker, Edith

2016-12-01

Contextual factors, such as exposure to stressors, may be antecedents to IPV perpetration. These contextual factors may be amenable to modification through intervention and prevention. However, few studies have examined specific contextual factors. To begin to address this gap, we examined the associations between financial stressors and three types of physical IPV perpetration. This analysis used data from Wave IV of The National Longitudinal Study of Adolescent to Adult Health. We used logistic regression to examine the associations of financial stressors and each type of IPV (minor, severe, causing injury), and multinomial logit regression to examine the associations of financial stressors and patterns of co-occurring types of IPV perpetration (only minor; only severe; minor and severe; minor, severe, and causing injury; compared with no perpetration). Fewer men perpetrated threats/minor physical IPV (6.7 %) or severe physical IPV (3.4 %) compared with women (11.4 % and 8.8 %, respectively). However, among physical IPV perpetrators, a higher percentage of men (32.0 %) than women (21.0 %) reported their partner was injured as a result of the IPV. In logistic regression models of each type of IPV perpetration, both the number of stressors experienced and several types of financial stressors were associated with perpetrating each type of IPV. Utilities nonpayment, housing nonpayment, food insecurity, and no phone service were associated with increased odds of perpetrating each form of IPV in adjusted analysis. Eviction was associated with perpetrating severe physical IPV but not threats/minor IPV or IPV causing injury. In multinomial logit regression comparing patterns of IPV perpetration to perpetrating no physical IPV, the relationships of financial stressors were less consistent. Food insecurity was associated with perpetrating only minor physical IPV. Comparatively, overall number of financial stressors and four types of financial stressors (utilities nonpayment, housing nonpayment, food insecurity, and disconnected phone service) were associated with perpetrating all three forms of physical IPV. Combined with prior research, our results suggested interventions to improve financial well-being may be a novel way to reduce physical IPV perpetration.

Associations of financial stressors and physical intimate partner violence perpetration.

PubMed

Schwab-Reese, Laura M; Peek-Asa, Corinne; Parker, Edith

Contextual factors, such as exposure to stressors, may be antecedents to IPV perpetration. These contextual factors may be amenable to modification through intervention and prevention. However, few studies have examined specific contextual factors. To begin to address this gap, we examined the associations between financial stressors and three types of physical IPV perpetration. This analysis used data from Wave IV of The National Longitudinal Study of Adolescent to Adult Health. We used logistic regression to examine the associations of financial stressors and each type of IPV (minor, severe, causing injury), and multinomial logit regression to examine the associations of financial stressors and patterns of co-occurring types of IPV perpetration ( only minor; only severe; minor and severe; minor, severe, and causing injury; compared with no perpetration). Fewer men perpetrated threats/minor physical IPV (6.7 %) or severe physical IPV (3.4 %) compared with women (11.4 % and 8.8 %, respectively). However, among physical IPV perpetrators, a higher percentage of men (32.0 %) than women (21.0 %) reported their partner was injured as a result of the IPV. In logistic regression models of each type of IPV perpetration, both the number of stressors experienced and several types of financial stressors were associated with perpetrating each type of IPV. Utilities nonpayment, housing nonpayment, food insecurity, and no phone service were associated with increased odds of perpetrating each form of IPV in adjusted analysis. Eviction was associated with perpetrating severe physical IPV but not threats/minor IPV or IPV causing injury. In multinomial logit regression comparing patterns of IPV perpetration to perpetrating no physical IPV, the relationships of financial stressors were less consistent. Food insecurity was associated with perpetrating only minor physical IPV. Comparatively, overall number of financial stressors and four types of financial stressors (utilities nonpayment, housing nonpayment, food insecurity, and disconnected phone service) were associated with perpetrating all three forms of physical IPV. Combined with prior research, our results suggested interventions to improve financial well-being may be a novel way to reduce physical IPV perpetration.

Clusters of anthropometric indicators of body fat associated with maximum oxygen uptake in adolescents

PubMed Central

2018-01-01

Introduction The aim of this study was to evaluate different clusters of anthropometric indicators (body mass index | BMI |, waist circumference | WC |, waist-to-height ratio | WHtR |, triceps skinfold |TR SF|, subscapular skinfold |SE SF|, sum of the triceps and subscapular skinfolds | ΣTR + SE |, and sum of the triceps, subscapular and suprailiac folds | ΣTR + SE + SI|) associated with the VO2max levels in adolescents. Methods The study included 1,132 adolescents (aged 14–19 years) enrolled in public schools of São José, Santa Catarina, Brazil, in the 2014 academic year. The dependent variable was the cluster of anthropometric indicators (BMI, WC, WHtR, TR SF, SE SF, SI SF, ΣTR + SE and ΣTR + SE + SI) of excess body fat. The independent variable was maximum oxygen uptake (VO2max), estimated by the modified Canadian aerobic fitness test—mCAFT. Control variables were: age, skin color, economic level, maternal education, physical activity and sexual maturation. Multinomial logistic regression was used for associations between the dependent and independent variables. Binary logistic regression was performed to identify the association between adolescents with all anthropometric indicators in excess and independent variables. Results One in ten adolescents presented all anthropometric indicators of excess body fat. Multinomial regression showed that with each increase of one VO2max unit, the odds of adolescents having three, four, five or more anthropometric indicators of excess body fat decreased by 0.92, 0.85 and 0.73 times, respectively. In the binary regression, this fact was reconfirmed, demonstrating that with each increase of one VO2max unit, the odds of adolescents having simultaneously the eight anthropometric indicators of excess body fat decreased by 0.55. Conclusion It was concluded that with each increase of one VO2max unit, adolescents decreased the odds of simultaneously presenting three or more anthropometric indicators of excess body fat, regardless of biological, economic and lifestyle factors. In addition, the present study identified that one in ten adolescents had all anthropometric indicators of excess body fat. PMID:29534098

Clusters of anthropometric indicators of body fat associated with maximum oxygen uptake in adolescents.

PubMed

Gonçalves, Eliane Cristina de Andrade; Nunes, Heloyse Elaine Gimenes; Silva, Diego Augusto Santos

2018-01-01

The aim of this study was to evaluate different clusters of anthropometric indicators (body mass index | BMI |, waist circumference | WC |, waist-to-height ratio | WHtR |, triceps skinfold |TR SF|, subscapular skinfold |SE SF|, sum of the triceps and subscapular skinfolds | ΣTR + SE |, and sum of the triceps, subscapular and suprailiac folds | ΣTR + SE + SI|) associated with the VO2max levels in adolescents. The study included 1,132 adolescents (aged 14-19 years) enrolled in public schools of São José, Santa Catarina, Brazil, in the 2014 academic year. The dependent variable was the cluster of anthropometric indicators (BMI, WC, WHtR, TR SF, SE SF, SI SF, ΣTR + SE and ΣTR + SE + SI) of excess body fat. The independent variable was maximum oxygen uptake (VO2max), estimated by the modified Canadian aerobic fitness test-mCAFT. Control variables were: age, skin color, economic level, maternal education, physical activity and sexual maturation. Multinomial logistic regression was used for associations between the dependent and independent variables. Binary logistic regression was performed to identify the association between adolescents with all anthropometric indicators in excess and independent variables. One in ten adolescents presented all anthropometric indicators of excess body fat. Multinomial regression showed that with each increase of one VO2max unit, the odds of adolescents having three, four, five or more anthropometric indicators of excess body fat decreased by 0.92, 0.85 and 0.73 times, respectively. In the binary regression, this fact was reconfirmed, demonstrating that with each increase of one VO2max unit, the odds of adolescents having simultaneously the eight anthropometric indicators of excess body fat decreased by 0.55. It was concluded that with each increase of one VO2max unit, adolescents decreased the odds of simultaneously presenting three or more anthropometric indicators of excess body fat, regardless of biological, economic and lifestyle factors. In addition, the present study identified that one in ten adolescents had all anthropometric indicators of excess body fat.

The Potential for Elimination of Racial-Ethnic Disparities in HIV Treatment Initiation in the Medicaid Population among 14 Southern States

PubMed Central

Zhang, Shun; McGoy, Shanell L.; Dawes, Daniel; Fransua, Mesfin; Rust, George; Satcher, David

2014-01-01

Objectives The purpose of this study was to explore the racial and ethnic disparities in initiation of antiretroviral treatment (ARV treatment or ART) among HIV-infected Medicaid enrollees 18–64 years of age in 14 southern states which have high prevalence of HIV/AIDS and high racial disparities in HIV treatment access and mortality. Methods We used Medicaid claims data from 2005 to 2007 for a retrospective cohort study. We compared frequency variances of HIV treatment uptake among persons of different racial- ethnic groups using univariate and multivariate methods. The unadjusted odds ratio was estimated through multinomial logistic regression. The multinomial logistic regression model was repeated with adjustment for multiple covariates. Results Of the 23,801 Medicaid enrollees who met criteria for initiation of ARV treatment, only one third (34.6%) received ART consistent with national guideline treatment protocols, and 21.5% received some ARV medication, but with sub-optimal treatment profiles. There was no significant difference in the proportion of people who received ARV treatment between black (35.8%) and non-Hispanic whites (35.7%), but Hispanic/Latino persons (26%) were significantly less likely to receive ARV treatment. Conclusions Overall ARV treatment levels for all segments of the population are less than optimal. Among the Medicaid population there are no racial HIV treatment disparities between Black and White persons living with HIV, which suggests the potential relevance of Medicaid to currently uninsured populations, and the potential to achieve similar levels of equality within Medicaid for Hispanic/Latino enrollees and other segments of the Medicaid population. PMID:24769625

Low Sex Hormone-Binding Globulin Levels Associate with Prediabetes in Chinese Men Independent of Total Testosterone

PubMed Central

Han, Bing; Li, Qin; Chen, Yi; Zhu, Chunfang; Chen, Yingchao; Xia, Fangzhen; Cang, Zhen; Lu, Meng; Chen, Chi; Lin, Dongping; Lu, Yingli

2016-01-01

Objective The association ns between prediabetes and androgens have been rarely reported, especially in Chinese men. We aimed to investigate whether androgens were associated with the prevalence of prediabetes diagnosed with new American Diabetes Association criteria in Chinese men and then to assess which androgen value was the most relevant factor. Methods A total of 2654 men (52.6±13.4 years old) were selected. Serum total testosterone (TT), sex hormone-binding globulin (SHBG) and free testosterone (FT) were measured. Covariance analysis of different androgen values were performed in age subgroups. Multinomial logistic regression was used for the association of TT, SHBG and FT with prediabetes and diabetes, as well as prediabetes in age subgroups. Results According to ADA new criteria, normoglycemia, prediabetes, and diabetes were diagnosed in 1405, 907 and 342 men, respectively. In covariance analysis, SHBG of prediabetes were found lower than that of normoglycemia but higher than that of diabetes (P <0.05). In multinomial logistic regression, serum TT and SHBG were inversely associated with prediabetes and diabetes. While, after full adjustment for age, residence area, economic status, waist circumference, metabolic factors, other two androgen values and HOMA-IR, only the associations of SHBG with prevalence of prediabetes and diabetes persisted statistically significant, especially in the elderly with prediabetes (all P for trend <0.05). Conclusions Serum androgen was inversely associated with prediabetes and diabetes in Chinese men. Low serum SHBG was the most relevant factor for prediabetes and diabetes. Whether it is an independent predictor for incident prediabetes in Chinese men needs further explorations. PMID:27583401

Reproductive risk factors assessment for anaemia among pregnant women in India using a multinomial logistic regression model.

PubMed

Perumal, Vanamail

2014-07-01

To assess reproductive risk factors for anaemia among pregnant women in urban and rural areas of India. The International Institute of Population Sciences, India, carried out third National Family Health Survey in 2005-2006 to estimate a key indicator from a sample of ever-married women in the reproductive age group 15-49 years. Data on various dimensions were collected using a structured questionnaire, and anaemia was measured using a portable HemoCue instrument. Anaemia prevalence among pregnant women was compared between rural and urban areas using chi-square test and odds ratio. Multinomial logistic regression analysis was used to determine risk factors. Anaemia prevalence was assessed among 3355 pregnant women from rural areas and 1962 pregnant women from urban areas. Moderate-to-severe anaemia in rural areas (32.4%) is significantly more common than in urban areas (27.3%) with an excess risk of 30%. Gestational age specific prevalence of anaemia significantly increases in rural areas after 6 months. Pregnancy duration is a significant risk factor in both urban and rural areas. In rural areas, increasing age at marriage and mass media exposure are significant protective factors of anaemia. However, more births in the last five years, alcohol consumption and smoking habits are significant risk factors. In rural areas, various reproductive factors and lifestyle characteristics constitute significant risk factors for moderate-to-severe anaemia. Therefore, intensive health education on reproductive practices and the impact of lifestyle characteristics are warranted to reduce anaemia prevalence. © 2014 John Wiley & Sons Ltd.

Urinary 8-iso-prostaglandin F2α as a marker of metabolic risks in the general Japanese population: The ROAD study.

PubMed

Mure, Kanae; Yoshimura, Noriko; Hashimoto, Marowa; Muraki, Shigeyuki; Oka, Hiroyuki; Tanaka, Sakae; Kawaguchi, Hiroshi; Nakamura, Kozo; Akune, Toru; Takeshita, Tatsuya

2015-07-01

To determine whether 8-iso-prostaglandin F2α (8-iso-PGF2α) is a reliable biomarker of the accumulation of metabolic risks [e.g., overweight, hypertension, impaired glucose tolerance (IGT), and dyslipidemia]. This was a cross-sectional study of the baseline characteristics of a Japanese general population cohort study: Research on Osteoarthritis/Osteoporosis Against Disability (ROAD). Of 1,690 participants, 1,527 fulfilled all questionnaires and examinations. Free and conjugated urinary 8-iso-PGF2α levels and metabolic syndrome (MetS) components including blood pressure, HbA1c, total cholesterol, high-density lipoprotein cholesterol (HDL-C), and non-HDL-C were analyzed. The data were analyzed by ANCOVA, multiple regression analysis, and multinomial logistic analysis. 8-iso-PGF2α was significantly associated with HbA1c and significantly inversely associated with total cholesterol and non-HDL-C. Notably, IGT with an HbA1c cut-off of 5.5% was significantly associated with 8-iso-PGF2α level in participants aged ≤50 years. Multinomial logistic regression analysis revealed 8-iso-PGF2α level was significantly associated with a greater number of MetS risks present; this association was stronger in younger participants. In participants aged ≥71 years, 8-iso-PGF2α was significantly associated with a greater number of MetS risks with higher IGT cut-offs. Urinary 8-iso-PGF2α can be a reliable marker of IGT and the accumulation of MetS risks, especially in younger people. © 2015 The Obesity Society.

Vitamin D status by sociodemographic factors and body mass index in Mexican women at reproductive age.

PubMed

Contreras-Manzano, Alejandra; Villalpando, Salvador; Robledo-Pérez, Ricardo

2017-01-01

To describe the prevalence of Vitamin D deficiency (VDD) and insufficiency (VDI), and the main dietary sources of vitamin D (VD) in a probabilistic sample of Mexican women at reproductive age participating in Ensanut 2012, stratified by sociodemographic factors and body mass index (BMI) categories. Serum concentrations of 25-hydroxyvitamin-D(25-OH-D) were determined using an ELISA technique in 4162 women participants of Ensanut 2012 and classified as VDD, VDI or optimal VD status. Sociodemographic, anthropometric and dietary data were also collected. The association between VDD/VDI and sociodemographic and anthropometry factors was assessed adjusting for potential confounders through an estimation of a multinomial logistic regression model. The prevalence of VDD was 36.8%, and that of VDI was 49.8%. The mean dietary intake of VD was 2.56 μg/d. The relative risk ratio (RRR) of VDD or VDI was calculated by a multinomial logistic regression model in 4162 women. The RRR of VDD or VDI were significantly higher in women with overweight (RRR: 1.85 and 1.44, p<0.05), obesity (RRR: 2.94 and 1.93, p<0.001), urban dwelling (RRR:1.68 and 1.31, p<0.06), belonging to the 3rd tertile of income (RRR: 5.32 and 2.22, p<0.001), or of indigenous ethnicity (RRR: 2.86 and 1.70, p<0.05), respectively. The high prevalence of VDD/VDI in Mexican women calls for stronger actions from the health authorities, strengthtening the actual policy of food supplementation and recommending a reasonable amount of sun exposure.

Concern about falling in older women with a history of falls: associations with health, functional ability, physical activity and quality of life.

PubMed

Patil, Radhika; Uusi-Rasi, Kirsti; Kannus, Pekka; Karinkanta, Saija; Sievänen, Harri

2014-01-01

Fear of falling has been linked to activity restriction, functional decline, decreased quality of life and increased risk of falling. Factors that distinguish persons with a high concern about falling from those with low concern have not been systematically studied. This study aimed to expose potential health-related, functional and psychosocial factors that correlate with fear of falling among independently living older women who had fallen in the past year. Baseline data of 409 women aged 70-80 years recruited to a randomised falls prevention trial (DEX) (NCT00986466) were used. Participants were classified according to their level of concern about falling using the Falls Efficacy Scale International (FES-I). Multinomial logistic regression analyses were performed to explore associations between health-related variables, functional performance tests, amount of physical activity, quality of life and FES-I scores. 68% of the participants reported a moderate to high concern (FES-I ≥ 20) about falls. Multinomial logistic regression showed that highly concerned women were significantly more likely to have poorer health and quality of life and lower functional ability. Reported difficulties in instrumental activities of daily living, balance, outdoor mobility and poorer quality of life contributed independently to a greater concern about falling. Concern about falling was highly prevalent in our sample of community-living older women. In particular, poor perceived general health and mobility constraints contributed independently to the difference between high and low concern of falling. Knowledge of these associations may help in developing interventions to reduce fear of falling and activity avoidance in old age.

Prevalence and Determinants of Secondhand Smoke Exposure Among Women in Bangladesh, 2011

PubMed Central

Minnwegen, Martina; Kaneider, Ulrike; Kraemer, Alexander; Khan, Md. Mobarak Hossain

2015-01-01

Background and Objectives: The population of Bangladesh is highly susceptible to secondhand smoke (SHS) exposure due to high smoking rates and low awareness about the harmful effects of SHS. This study aims to determine the prevalence of SHS exposure and highlight the essential determinants in developing successful strategies to prevent adverse health effects in Bangladesh. Methods: The analysis is based on the Bangladesh Demographic Health Survey 2011, in which 17,749 women in the reproductive age group (12–49 years) were included. The information regarding SHS exposure at home was derived from the question: “How often does anyone smoke inside your house?” The variable was recoded into 3 groups: daily exposure, low exposure (exposed weekly, monthly, or less than monthly), and no SHS exposure. We performed descriptive and bivariable analyses and multinomial logistic regression. Results: A total of 46.7% of the women reported high exposure to SHS at home. According to the multinomial logistic regression model, relatively lower education and lower wealth index were significantly associated with daily SHS exposure at home. The exposure differed significantly between the divisions of Bangladesh. Having children at home (vs. not) and being Islamic (compared to other religious affiliations) were protective factors. Conclusions: The study indicates that women from socioeconomically disadvantaged households are more likely to experience daily exposure to SHS at home. Therefore, especially these groups have to be targeted to reduce tobacco consumption. In addition to aspects of legislation, future strategies need to focus educational aspects to improve the population’s health status in Bangladesh. PMID:25125322

The dynamics of injection drug users' personal networks and HIV risk behaviors.

PubMed

Costenbader, Elizabeth C; Astone, Nan M; Latkin, Carl A

2006-07-01

While studies of the social networks of injection drug users (IDUs) have provided insight into how the structures of interpersonal relationships among IDUs affect HIV risk behaviors, the majority of these studies have been cross-sectional. The present study examined the dynamics of IDUs' social networks and HIV risk behaviors over time. Using data from a longitudinal HIV-intervention study conducted in Baltimore, MD, this study assessed changes in the composition of the personal networks of 409 IDUs. We used a multi-nomial logistic regression analysis to assess the association between changes in network composition and simultaneous changes in levels of injection HIV risk behaviors. Using the regression parameters generated by the multi-nomial model, we estimated the predicted probability of being in each of four HIV risk behavior change groups. Compared to the base case, individuals who reported an entirely new set of drug-using network contacts at follow-up were more than three times as likely to be in the increasing risk group. In contrast, reporting all new non-drug-using contacts at follow-up increased the likelihood of being in the stable low-risk group by almost 50% and decreased the probability of being in the consistently high-risk group by more than 70%. The findings from this study show that, over and above IDUs' baseline characteristics, changes in their personal networks are associated with changes in individuals' risky injection behaviors. They also suggest that interventions aimed at reducing HIV risk among IDUs might benefit from increasing IDUs' social contacts with individuals who are not drug users.

Cross-Jurisdictional Resource Sharing in Changing Public Health Landscape: Contributory Factors and Theoretical Explanations.

PubMed

Shah, Gulzar H; Badana, Adrian N S; Robb, Claire; Livingood, William C

2016-01-01

Local health departments (LHDs) are striving to meet public health needs within their jurisdictions, amidst fiscal restraints and complex dynamic environment. Resource sharing across jurisdictions is a critical opportunity for LHDs to continue to enhance effectiveness and increase efficiency. This research examines the extent of cross-jurisdictional resource sharing among LHDs, the programmatic areas and organizational functions for which LHDs share resources, and LHD characteristics associated with resource sharing. Data from the National Association of County & City Health Officials' 2013 National Profile of LHDs were used. Descriptive statistics and multinomial logistic regression were performed for the 5 implementation-oriented outcome variables of interest, with 3 levels of implementation. More than 54% of LHDs shared resources such as funding, staff, or equipment with 1 or more other LHDs on a continuous, recurring basis. Results from the multinomial regression analysis indicate that economies of scale (population size and metropolitan status) had significant positive influences (at P ≤ .05) on resource sharing. Engagement in accreditation, community health assessment, community health improvement planning, quality improvement, and use of the Community Guide were associated with lower levels of engagement in resource sharing. Doctoral degree of the top executive and having 1 or more local boards of health carried a positive influence on resource sharing. Cross-jurisdictional resource sharing is a viable and commonly used process to overcome the challenges of new and emerging public health problems within the constraints of restricted budgets. LHDs, particularly smaller LHDs with limited resources, should consider increased resource sharing to address emerging challenges.

Contraceptive awareness among men in Bangladesh.

PubMed

Islam, Mohammad Amirul; Padmadas, Sabu S; Smith, Peter W F

2006-04-01

A considerable gap exists between contraceptive awareness and use. Traditional approaches to measuring awareness are inadequate to properly understand the linkages between awareness and use. The objective of this study was to examine the degree of men's modern contraceptive awareness in Bangladesh and the associated determinants and further testing of a hypothesis that current contraceptive use confers a high degree of method awareness. This study used the couple data set from the Bangladesh Demographic and Health Survey (1999-2000). A two-level, multinomial logistic regression was used with the degree of contraceptive awareness as the dependent variable. The degree of awareness was measured by the reported number of modern contraceptive methods known among men aged 15-59 years. Men's responses on method awareness were classified according to those reported spontaneously and probed. Nearly 100% of the study participants reported having heard of at least one method and about half reported awareness of at least eight different methods of contraception. Multinomial logistic regression analyses showed that older and educated men were more likely to have reported a high degree of awareness. The findings confirmed our hypothesis that current contraceptive use is likely to confer a high degree of modern method awareness among men (p<0.001), after controlling for other important characteristics. Men who had a low degree of contraceptive awareness seem not properly informed of the wide range of contraceptive options. It is imperative that family planning intervention strategies in Bangladesh should focus on the degree and functional knowledge of contraceptive methods to improve the uptake of especially male-based modern methods.

Inequality in the hepatitis B awareness level in rural residents from 7 provinces in China.

PubMed

Zheng, Juan; Li, Quan; Wang, Jian; Zhang, Guojie; Wangen, Knut R

2017-05-04

The hepatitis B (HB) awareness level is an important factor affecting the rates of HB virus vaccination. To better understand income-related inequalities in the HB awareness level, it is imperative to identify the sources of inequalities and assess the contribution rates of these influential factors. This study analyzed the unequal distribution of the HB awareness level and the contributions of various influential factors. We performed a cross-sectional household survey with questionnaire-based, face-to-face interviews in 7 Chinese provinces. Responses from 7271 respondents were used in this analysis. Multinomial logistic regression was used for the analysis of contributing factors, and the concentration index was used as a measure of HB awareness inequalities. The HB awareness level varied across participants with different characteristics. Multinomial logistic regression of the explanatory factors of the HB awareness level showed that several estimated coefficients and relative risk ratios were statistically significant for middle- and high-level awareness, except for sex, occupation, and household income. The concentration index of the HB knowledge score was 0.140, indicating inequality gradients disadvantageous to the poor. The contribution rate of socioeconomic factors was the largest (60.8%), followed by demographic characteristics (29.0%) and geographic factors (4.3%). Demographic, socioeconomic, and geographic factors are associated with the HB awareness inequality. Therefore, to reduce inequality, HB-related health education targeting individuals with low socioeconomic status should be performed. Less-developed provinces, especially with high proportions of poor residents, warrant particular attention. Our findings may be beneficial to improve the HB virus vaccination rate for individuals with low socioeconomic status.

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

PubMed

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

2014-02-01

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

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

PubMed Central

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

2014-01-01

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

Individual relocation decisions after tornadoes: a multi-level analysis.

PubMed

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.

[Associations between dormitory environment/other factors and sleep quality of medical students].

PubMed

Zheng, Bang; Wang, Kailu; Pan, Ziqi; Li, Man; Pan, Yuting; Liu, Ting; Xu, Dan; Lyu, Jun

2016-03-01

To investigate the sleep quality and related factors among medical students in China, understand the association between dormitory environment and sleep quality, and provide evidence and recommendations for sleep hygiene intervention. A total of 555 undergraduate students were selected from a medical school of an university in Beijing through stratified-cluster random-sampling to conduct a questionnaire survey by using Chinese version of Pittsburgh Sleep Quality Index (PSQI) and self-designed questionnaire. Analyses were performed by using multiple logistic regression model as well as multilevel linear regression model. The prevalence of sleep disorder was 29.1%(149/512), and 39.1%(200/512) of the students reported that the sleep quality was influenced by dormitory environment. PSQI score was negatively correlated with self-reported rating of dormitory environment (γs=-0.310, P<0.001). Logistic regression analysis showed the related factors of sleep disorder included grade, sleep regularity, self-rated health status, pressures of school work and employment, as well as dormitory environment. RESULTS of multilevel regression analysis also indicated that perception on dormitory environment (individual level) was associated with sleep quality with the dormitory level random effects under control (b=-0.619, P<0.001). The prevalence of sleep disorder was high in medical students, which was associated with multiple factors. Dormitory environment should be taken into consideration when the interventions are taken to improve the sleep quality of students.

Caregiver Burdens and Preventive Dental Care for Children with Autism Spectrum Disorder, Developmental Disability and/or Mental Health Conditions: National Survey of CSHCN, 2009-2010.

PubMed

Wiener, R Constance; Vohra, Rini; Sambamoorthi, Usha; Madhavan, S Suresh

2016-12-01

Objective The purpose of this study is to examine the burdens of caregivers on perception of the need and receipt of preventive dental care for a subset of children with special health care needs-children with Autism Spectrum disorder, developmental disability and/or mental health conditions (CASD/DD/MHC). Methods The authors used the 2009-2010 National Survey of CSHCN. The survey included questions addressing preventive dental care and caregivers' financial, employment, and time-related burdens. The associations of these burdens on perceptions and receipt of preventive dental care use were analyzed with bivariate Chi square analyses and multinomial logistic regressions for CASD/DD/MHC (N = 16,323). Results Overall, 16.3 % of CASD/DD/MHC had an unmet preventive dental care need. There were 40.0 % of caregivers who reported financial burden, 20.3 % who reported employment burden, and 10.8 % who reported time burden. A higher percentage of caregivers with financial burden, employment burden, and time-related burden reported that their CASD/DD/MHC did not receive needed preventive dental care (14.1, 16.5, 17.7 % respectively) compared to caregivers without financial, employment, or time burdens (9.0, 9.6 %, 11.0 % respectively). Caregivers with financial burden (adjusted multinomial odds ratio, 1.38 [95 % CI 1.02, 1.86] and employment burden (adjusted multinomial odds ratio, 1.45 [95 % CI 1.02, 2.06] were more likely to report that their child did not receive preventive dental care despite perceived need compared to caregivers without financial or employment burdens. Conclusions for practice Unmet needs for preventive dental care were associated with employment and financial burdens of the caregivers of CASD/DD/MHC.

Caregiver Burdens and Preventive Dental Care for Children with Autism Spectrum disorder, developmental disability and/or mental health conditions: National Survey of CSHCN, 2009–10

PubMed Central

Vohra, Rini; Sambamoorthi, Usha; Madhavan, S. Suresh

2016-01-01

Objective The purpose of this study is to examine the burdens of caregivers on one perception of the need and receipt of preventive dental care for a subset of children with special health care needs—children with Autism Spectrum disorder, developmental disability and/or mental health conditions (CASD/DD/MHC). Methods The authors used the 2009–2010 National Survey of CSHCN. The survey included questions addressing preventive dental care and caregivers’ financial, employment, and time-related burdens. The associations of these burdens on perceptions and receipt of preventive dental care use were analyzed with bivariate Chi square analyses and multinomial logistic regressions for CASD/DD/MHC (N=16,323). Results Overall, 16.3% of CASD/DD/MHC had an unmet preventive dental care need. There were 40.0% of caregivers who reported financial burden, 20.3% who reported employment burden, and 10.8% who reported time burden. A higher percentage of caregivers with financial burden, employment burden, and time-related burden reported that their CASD/DD/MHC did not receive needed preventive dental care (14.1 %, 16.5%, 17.7% respectively) compared to caregivers without financial, employment, or time burdens (9.0%, 9.6%, 11.0% respectively). Caregivers with financial burden (adjusted multinomial odds ratio, 1.38 [95%CI: 1.02, 1.86]) and employment burden (adjusted multinomial odds ratio, 1.45 [95%CI: 1.02, 2.06]) were more likely to report that their child did not receive preventive dental care despite perceived need compared to caregivers without financial or employment burdens. Conclusions for practice Unmet needs for preventive dental care were associated with employment and financial burdens of the caregivers of CASD/DD/MHC. PMID:27465058

Surgical and Functional Outcomes After Multilevel Cervical Fusion for Degenerative Disc Disease Compared With Fusion for Radiculopathy: A Study of Workers' Compensation Population.

PubMed

Faour, Mhamad; Anderson, Joshua T; Haas, Arnold R; Percy, Rick; Woods, Stephen T; Ahn, Uri M; Ahn, Nicholas U

2017-05-01

Retrospective cohort comparative study. To evaluate presurgical and surgical factors that affect return to work (RTW) status after multilevel cervical fusion, and to compare outcomes after multilevel cervical fusion for degenerative disc disease (DDD) versus radiculopathy. Cervical fusion provides more than 90% of symptomatic relief for radiculopathy and myelopathy. However, cervical fusion for DDD without radiculopathy is considered controversial. In addition, multilevel fusion is associated with poorer surgical outcomes with increased levels fused. Data of cervical comorbidities was collected from Ohio Bureau of Workers' Compensation for subjects with work-related injuries. The study population included subjects who underwent multilevel cervical fusion. Patients with radiculopathy or DDD were identified. Multivariate logistic regression was performed to identify factors that affect RTW status. Surgical and functional outcomes were compared between groups. Stable RTW status within 3 years after multilevel cervical fusion was negatively affected by: fusion for DDD, age > 55 years, preoperative opioid use, initial psychological evaluation before surgery, injury-to-surgery > 2 years and instrumentation.DDD group had lower rate of achieving stable RTW status (P= 0.0001) and RTW within 1 year of surgery (P= 0.0003) compared with radiculopathy group. DDD patients were less likely to have a stable RTW status [odds ratio, OR = 0.63 (0.50-0.79)] or RTW within 1 year after surgery [OR = 0.65 (0.52-0.82)].DDD group had higher rate of opioid use (P= 0.001), and higher rate of disability after surgery (P= 0.002). Multiple detriments affect stable RTW status after multilevel cervical fusion including DDD. DDD without radiculopathy was associated with lower RTW rates, less likelihood to return to work, higher disability, and higher opioid use after surgery. Multilevel cervical fusion for DDD may be counterproductive. Future studies should investigate further treatment options of DDD, and optimize patient selection criteria for surgical intervention. 3.

Fast food purchasing and access to fast food restaurants: a multilevel analysis of VicLANES

PubMed Central

Thornton, Lukar E; Bentley, Rebecca J; Kavanagh, Anne M

2009-01-01

Background While previous research on fast food access and purchasing has not found evidence of an association, these studies have had methodological problems including aggregation error, lack of specificity between the exposures and outcomes, and lack of adjustment for potential confounding. In this paper we attempt to address these methodological problems using data from the Victorian Lifestyle and Neighbourhood Environments Study (VicLANES) – a cross-sectional multilevel study conducted within metropolitan Melbourne, Australia in 2003. Methods The VicLANES data used in this analysis included 2547 participants from 49 census collector districts in metropolitan Melbourne, Australia. The outcome of interest was the total frequency of fast food purchased for consumption at home within the previous month (never, monthly and weekly) from five major fast food chains (Red Rooster, McDonalds, Kentucky Fried Chicken, Hungry Jacks and Pizza Hut). Three measures of fast food access were created: density and variety, defined as the number of fast food restaurants and the number of different fast food chains within 3 kilometres of road network distance respectively, and proximity defined as the road network distance to the closest fast food restaurant. Multilevel multinomial models were used to estimate the associations between fast food restaurant access and purchasing with never purchased as the reference category. Models were adjusted for confounders including determinants of demand (attitudes and tastes that influence food purchasing decisions) as well as individual and area socio-economic characteristics. Results Purchasing fast food on a monthly basis was related to the variety of fast food restaurants (odds ratio 1.13; 95% confidence interval 1.02 – 1.25) after adjusting for individual and area characteristics. Density and proximity were not found to be significant predictors of fast food purchasing after adjustment for individual socio-economic predictors. Conclusion Although we found an independent association between fast food purchasing and access to a wider variety of fast food restaurant, density and proximity were not significant predictors. The methods used in our study are an advance on previous analyses. PMID:19473503

The relationship between multilevel models and non-parametric multilevel mixture models: Discrete approximation of intraclass correlation, random coefficient distributions, and residual heteroscedasticity.

PubMed

Rights, Jason D; Sterba, Sonya K

2016-11-01

Multilevel data structures are common in the social sciences. Often, such nested data are analysed with multilevel models (MLMs) in which heterogeneity between clusters is modelled by continuously distributed random intercepts and/or slopes. Alternatively, the non-parametric multilevel regression mixture model (NPMM) can accommodate the same nested data structures through discrete latent class variation. The purpose of this article is to delineate analytic relationships between NPMM and MLM parameters that are useful for understanding the indirect interpretation of the NPMM as a non-parametric approximation of the MLM, with relaxed distributional assumptions. We define how seven standard and non-standard MLM specifications can be indirectly approximated by particular NPMM specifications. We provide formulas showing how the NPMM can serve as an approximation of the MLM in terms of intraclass correlation, random coefficient means and (co)variances, heteroscedasticity of residuals at level 1, and heteroscedasticity of residuals at level 2. Further, we discuss how these relationships can be useful in practice. The specific relationships are illustrated with simulated graphical demonstrations, and direct and indirect interpretations of NPMM classes are contrasted. We provide an R function to aid in implementing and visualizing an indirect interpretation of NPMM classes. An empirical example is presented and future directions are discussed. © 2016 The British Psychological Society.

Multilevel modeling and panel data analysis in educational research (Case study: National examination data senior high school in West Java)

NASA Astrophysics Data System (ADS)

Zulvia, Pepi; Kurnia, Anang; Soleh, Agus M.

2017-03-01

Individual and environment are a hierarchical structure consist of units grouped at different levels. Hierarchical data structures are analyzed based on several levels, with the lowest level nested in the highest level. This modeling is commonly call multilevel modeling. Multilevel modeling is widely used in education research, for example, the average score of National Examination (UN). While in Indonesia UN for high school student is divided into natural science and social science. The purpose of this research is to develop multilevel and panel data modeling using linear mixed model on educational data. The first step is data exploration and identification relationships between independent and dependent variable by checking correlation coefficient and variance inflation factor (VIF). Furthermore, we use a simple model approach with highest level of the hierarchy (level-2) is regency/city while school is the lowest of hierarchy (level-1). The best model was determined by comparing goodness-of-fit and checking assumption from residual plots and predictions for each model. Our finding that for natural science and social science, the regression with random effects of regency/city and fixed effects of the time i.e multilevel model has better performance than the linear mixed model in explaining the variability of the dependent variable, which is the average scores of UN.

Association of comorbid mental health symptoms and physical health conditions with employee productivity.

PubMed

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.

Victimization and health risk factors among weapon-carrying youth.

PubMed

Stayton, Catherine; McVeigh, Katharine H; Olson, E Carolyn; Perkins, Krystal; Kerker, Bonnie D

2011-11-01

To compare health risks of 2 subgroups of weapon carriers: victimized and nonvictimized youth. 2003-2007 NYC Youth Risk Behavior Surveys were analyzed using bivariate analyses and multinomial logistic regression. Among NYC teens, 7.5% reported weapon carrying without victimization; 6.9% reported it with victimization. Both subgroups were more likely than non-weapon carriers to binge drink, use marijuana, smoke, fight, and have multiple sex partners; weapon carriers with victimization also experienced persistent sadness and attempted suicide. Subgroups of weapon carriers have distinct profiles. Optimal response should pair disciplinary action with screening for behavioral and mental health concerns and victimization.

The choice of facilitators in medical tourism.

PubMed

Gan, Lydia L; Frederick, James R

2018-01-01

The study identified which of the four facilitators (themselves, agents, insurers, or doctors) consumers are most likely to use when they travel for various medical procedures. A survey conducted between 2011 and 2014 yielded 964 responses. The multinomial logistic regression results showed that being 51-64 years old was positively related to going on their own or using agents to arrange for knee replacements. Having a high school education or less was positively linked to using both agents and insurers to facilitate knee replacements, whereas having a bachelor's degree was negatively associated with going on their own for stem cell therapy.

Workplace Determinants of Social Capital: Cross-Sectional and Longitudinal Evidence from a Finnish Cohort Study

PubMed Central

Oksanen, Tuula; Kawachi, Ichiro; Kouvonen, Anne; Takao, Soshi; Suzuki, Etsuji; Virtanen, Marianna; Pentti, Jaana; Kivimäki, Mika; Vahtera, Jussi

2013-01-01

Objective To examine which contextual features of the workplace are associated with social capital. Methods This is a cohort study of 43,167 employees in 3090 Finnish public sector workplaces who responded to a survey of individual workplace social capital in 2000–02 (response rate 68%). We used ecometrics approach to estimate social capital of work units. Features of the workplace were work unit's demographic and employment patterns and size, obtained from employers' administrative records. We used multilevel-multinomial logistic regression models to examine cross-sectionally whether these features were associated with social capital between individuals and work units. Fixed effects models were used for longitudinal analyses in a subsample of 12,108 individuals to examine the effects of changes in workplace characteristics on changes in social capital between 2000 and 2004. Results After adjustment for individual characteristics, an increase in work unit size reduced the odds of high levels of individual workplace social capital (odds ratio 0.94, 95% confidence interval 0.91–0.98 per 30-person-year increase). A 20% increase in the proportion of manual and male employees reduced the odds of high levels of social capital by 8% and 23%, respectively. A 30% increase in temporary employees and a 20% increase in employee turnover were associated with 11% (95% confidence interval 1.04–1.17) and 24% (95% confidence interval 1.18–1.30) higher odds of having high levels of social capital respectively). Results from fixed effects models within individuals, adjusted for time-varying covariates, and from social capital of the work units yielded consistent results. Conclusions These findings suggest that workplace social capital is contextually patterned. Workplace demographic and employment patterns as well as the size of the work unit are important in understanding variations in workplace social capital between individuals and workplaces. PMID:23776555

Relationships between academic performance, SES school type and perceptual-motor skills in first grade South African learners: NW-CHILD study.

PubMed

Pienaar, A E; Barhorst, R; Twisk, J W R

2014-05-01

Perceptual-motor skills contribute to a variety of basic learning skills associated with normal academic success. This study aimed to determine the relationship between academic performance and perceptual-motor skills in first grade South African learners and whether low SES (socio-economic status) school type plays a role in such a relationship. This cross-sectional study of the baseline measurements of the NW-CHILD longitudinal study included a stratified random sample of first grade learners (n = 812; 418 boys and 394 boys), with a mean age of 6.78 years ± 0.49 living in the North West Province (NW) of South Africa. The Beery-Buktenica Developmental Test of Visual-Motor Integration-4 (VMI) was used to assess visual-motor integration, visual perception and hand control while the Bruininks Oseretsky Test of Motor Proficiency, short form (BOT2-SF) assessed overall motor proficiency. Academic performance in math, reading and writing was assessed with the Mastery of Basic Learning Areas Questionnaire. Linear mixed models analysis was performed with spss to determine possible differences between the different VMI and BOT2-SF standard scores in different math, reading and writing mastery categories ranging from no mastery to outstanding mastery. A multinomial multilevel logistic regression analysis was performed to assess the relationship between a clustered score of academic performance and the different determinants. A strong relationship was established between academic performance and VMI, visual perception, hand control and motor proficiency with a significant relationship between a clustered academic performance score, visual-motor integration and visual perception. A negative association was established between low SES school types on academic performance, with a common perceptual motor foundation shared by all basic learning areas. Visual-motor integration, visual perception, hand control and motor proficiency are closely related to basic academic skills required in the first formal school year, especially among learners in low SES type schools. © 2013 John Wiley & Sons Ltd.

Associations between the purchase of healthy and fast foods and restrictions to food access: a cross-sectional study in Melbourne, Australia.

PubMed

Burns, Cate; Bentley, Rebecca; Thornton, Lukar; Kavanagh, Anne

2015-01-01

To examine the associations between financial, physical and transport conditions that may restrict food access (which we define as food security indicators) and the purchase of fast foods and nutritious staples such as bread and milk. Multilevel logistic and multinomial regression analysis of cross-sectional survey data to assess associations between the three indicators of food insecurity and household food shopping adjusted for sociodemographic and socio-economic variables. Random selection of households (n 3995) from fifty Census Collector Districts in Melbourne, Australia, in 2003. The main food shoppers in each household (n 2564). After adjustment for confounders, analysis showed that a greater likelihood of purchasing chain-brand fast food on a weekly basis compared with never was associated with running out of money to buy food (OR = 1·59; 95 % CI 1·08, 2·34) and reporting difficulties lifting groceries (OR = 1·77; 95 % CI 1·23, 2·54). Respondents without regular access to a car to do food shopping were less likely to purchase bread types considered more nutritious than white bread (OR = 0·75; 95 % CI 0·59, 0·95) and milk types considered more nutritious than full-cream milk (OR = 0·62; 95 % CI 0·47, 0·81). The food insecurity indicators were not associated with the purchasing of fruits, vegetables or non-chain fast food. Householders experiencing financial and physical barriers were more likely to frequently purchase chain fast foods while limited access to a car resulted in a lower likelihood that the nutritious options were purchased for two core food items (bread and milk). Policies and interventions that improve financial access to food and lessen the effect of physical limitations to carrying groceries may reduce the purchasing of fast foods. Further research is required on food sourcing and dietary quality among those with food access restrictions.

Studying Individual Differences in Predictability with Gamma Regression and Nonlinear Multilevel Models

ERIC Educational Resources Information Center

Culpepper, Steven Andrew

2010-01-01

Statistical prediction remains an important tool for decisions in a variety of disciplines. An equally important issue is identifying factors that contribute to more or less accurate predictions. The time series literature includes well developed methods for studying predictability and volatility over time. This article develops…

Administrative Climate and Novices' Intent to Remain Teaching

ERIC Educational Resources Information Center

Pogodzinski, Ben; Youngs, Peter; Frank, Kenneth A.; Belman, Dale

2012-01-01

Using survey data from novice teachers at the elementary and middle school level across 11 districts, multilevel logistic regressions were estimated to examine the association between novices' perceptions of the administrative climate and their desire to remain teaching within their schools. We find that the probability that a novice teacher…

Foreign-Born Concentration and Acculturation to Volunteering among Immigrant Youth

ERIC Educational Resources Information Center

Tong, Yuying

2010-01-01

Using children of immigrants sample from National Longitudinal Study of Adolescent Health, this study investigates how immigrant youth acculturating to the American social norm of volunteering and how the acculturation is modified by living in immigrant neighborhoods. Multilevel logistic regression produces distinct patterns for children living in…

A Noncentral "t" Regression Model for Meta-Analysis

ERIC Educational Resources Information Center

Camilli, Gregory; de la Torre, Jimmy; Chiu, Chia-Yi

2010-01-01

In this article, three multilevel models for meta-analysis are examined. Hedges and Olkin suggested that effect sizes follow a noncentral "t" distribution and proposed several approximate methods. Raudenbush and Bryk further refined this model; however, this procedure is based on a normal approximation. In the current research literature, this…

Student and School SES, Gender, Strategy Use, and Achievement

ERIC Educational Resources Information Center

Callan, Gregory L.; Marchant, Gregory J.; Finch, W. Holmes; Flegge, Lindsay

2017-01-01

A multilevel mediated regression model was fit to Programme for International Student Assessment achievement, strategy use, gender, and family- and school-level socioeconomic status (SES). Two metacognitive strategies (i.e., understanding and summarizing) and one learning strategy (i.e., control strategies) were found to relate significantly and…

Collegial Climate and Novice Teachers' Intent to Remain Teaching

ERIC Educational Resources Information Center

Pogodzinski, Ben; Youngs, Peter; Frank, Kenneth A.

2013-01-01

Using survey data from novice teachers across 99 schools, we estimated multilevel regressions to identify the association between novices' intent to remain teaching within their schools and their perceptions of the collegial climate. The results suggest that novice teachers who perceive a more positive collegial climate marked by higher degrees…

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…

Optimal Design for Two-Level Random Assignment and Regression Discontinuity Studies

ERIC Educational Resources Information Center

Rhoads, Christopher H.; Dye, Charles

2016-01-01

An important concern when planning research studies is to obtain maximum precision of an estimate of a treatment effect given a budget constraint. When research designs have a "multilevel" or "hierarchical" structure changes in sample size at different levels of the design will impact precision differently. Furthermore, there…

Modeling Joint Exposures and Health Outcomes for Cumulative Risk Assessment: The Case of Radon and Smoking

PubMed Central

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

The Association of Workplace Social Capital With Work Engagement of Employees in Health Care Settings: A Multilevel Cross-Sectional Analysis.

PubMed

Fujita, Sumiko; Kawakami, Norito; Ando, Emiko; Inoue, Akiomi; Tsuno, Kanami; Kurioka, Sumiko; Kawachi, Ichiro

2016-03-01

The aim of the study was to examine the cross-sectional multilevel association between unit-level workplace social capital and individual-level work engagement among employees in health care settings. The data were collected from employees of a Japanese health care corporation using a questionnaire. The analyses were limited to 440 respondents from 35 units comprising five or more respondents per unit. Unit-level workplace social capital was calculated as an average score of the Workplace Social Capital Scale for each unit. Multilevel regression analysis with a random intercept model was conducted. After adjusting for demographic variables, unit-level workplace social capital was significantly and positively associated with respondents' work engagement (P < 0.001). The association remained significant after additionally adjusting for individual-level perceptions of workplace social capital (P < 0.001). Workplace social capital might exert a positive contextual effect on work engagement of employees in health care settings.

Multilevel Correlates of Satisfaction with Neighborhood Availability of Fresh Fruits and Vegetables

PubMed Central

Zenk, Shannon N.; Schulz, Amy J.; Lachance, Laurie L.; Mentz, Graciela; Kannan, Srimathi; Ridella, William; Galea, Sandro

2009-01-01

Background Little is known about influences on perceptions of neighborhood food environments, despite their relevance for food-shopping behaviors and food choices. Purpose This study examined relationships between multilevel factors (neighborhood structure, independently observed neighborhood food environment, individual socioeconomic position) and satisfaction with neighborhood availability of fruits and vegetables. Methods The multilevel regression analysis drew on data from a community survey of urban adults, in-person audit and mapping of food stores, and the 2000 Census. Results Satisfaction with neighborhood availability of fruits and vegetables was lower in neighborhoods that were further from a supermarket and that had proportionately more African-American residents. Neighborhood poverty and independently observed neighborhood fruit and vegetable characteristics (variety, prices, quality) were not associated with satisfaction. Individual education modified relationships between neighborhood availability of smaller food stores (small grocery stores, convenience stores, liquor stores) and satisfaction. Conclusions Individual-level and neighborhood-level factors affect perceptions of neighborhood food environments. PMID:19809859

Immigrants' health in Europe: a cross-classified multilevel approach to examine origin country, destination country, and community effects.

PubMed

Huijts, Tim; Kraaykamp, Gerbert

2012-01-01

In this study, we examined origin, destination, and community effects on first- and second-generation immigrants' health in Europe. We used information from the European Social Surveys (2002–2008) on 19,210 immigrants from 123 countries of origin, living in 31 European countries. Cross-classified multilevel regression analyses reveal that political suppression in the origin country and living in countries with large numbers of immigrant peers have a detrimental influence on immigrants' health. Originating from predominantly Islamic countries and good average health among natives in the destination country appear to be beneficial. Additionally, the results point toward health selection mechanisms into migration.

ACUTE LOWER RESPIRATORY INFECTION IN GUARANI INDIGENOUS CHILDREN, BRAZIL.

PubMed

Souza, Patricia Gomes de; Cardoso, Andrey Moreira; Sant'Anna, Clemax Couto; March, Maria de Fátima Bazhuni Pombo

2018-03-29

To describe the clinical profile and treatment of Brazilian Guarani indigenous children aged less than five years hospitalized for acute lower respiratory infection (ALRI), living in villages in the states from Rio de Janeiro to Rio Grande do Sul. Of the 234 children, 23 were excluded (incomplete data). The analysis was conducted in 211 children. Data were extracted from charts by a form. Based on record of wheezing and x-ray findings, ALRI was classified as bacterial, viral and viral-bacterial. A bivariate analysis was conducted using multinomial regression. Median age was 11 months. From the total sample, the ALRI cases were classified as viral (40.8%), bacterial (35.1%) and viral-bacterial (24.1%). It was verified that 53.1% of hospitalizations did not have clinical-radiological-laboratorial evidence to justify them. In the multinomial regression analysis, the comparison of bacterial and viral-bacterial showed the likelihood of having a cough was 3.1 times higher in the former (95%CI 1.11-8.70), whereas having chest retractions was 61.0% lower (OR 0.39, 95%CI 0.16-0.92). Comparing viral with viral-bacterial, the likelihood of being male was 2.2 times higher in the viral (95%CI 1.05-4.69), and of having tachypnea 58.0% lower (OR 0.42, 95%CI 0.19-0.92). Higher proportion of viral processes was identified, as well as viral-bacterial co-infections. Coughing was a symptom indicative of bacterial infection, whereas chest retractions and tachypnea showed viral-bacterial ALRI. Part of the resolution of non-severe ALRI still occurs at hospital level; therefore, we concluded that health services need to implement their programs in order to improve indigenous primary care.

Childhood abuse and late-life depression: Mediating effects of psychosocial factors for early- and late-onset depression.

PubMed

Wielaard, Ilse; Hoyer, Mathijs; Rhebergen, Didi; Stek, Max L; Comijs, Hannie C

2018-03-01

Childhood abuse makes people vulnerable to developing depression, even in late life. Psychosocial factors that are common in late life, such as loneliness or lack of a partner, may explain this association. Our aim was to investigate whether the association between childhood abuse and depression in older adults can be explained by psychosocial factors. Cross-sectional data were derived from the Netherlands Study of Depression in Older Persons (aged 60-93), including 132 without lifetime depression, 242 persons with an early-onset depression (<60 years), and 125 with a late-onset (≥60 years) depression. Childhood abuse (yes/no) and a frequency-based childhood abuse index were included. Multinomial regression and multivariable mediation analyses were used to examine the association between childhood abuse and the onset of depression, and the influence of loneliness, social network, and partner status. Multinomial regression analyses showed a significant association between childhood abuse and the childhood abuse index with early- and late-onset depression. Multivariable mediation analyses showed that the association between childhood abuse and early-onset depression was partly mediated by social network size and loneliness. This was particularly present for emotional neglect and psychological abuse, but not for physical and sexual abuse. No psychosocial mediators were found for the association between childhood abuse and late-onset depression. A smaller social network and feelings of loneliness mediate the association between childhood abuse and early-onset depression in older adults. Our findings show the importance of detecting childhood abuse as well as the age at depression onset and mapping of relevant psychosocial factors in the treatment of late-life depression. Copyright © 2018 John Wiley & Sons, Ltd.

Frequencies of apolipoprotein E alleles in depressed patients undergoing hemodialysis--a case-control study.

PubMed

Su, Yan-yan; Zhang, Yun-fang; Yang, Shen; Wang, Jie-lin; Hua, Bao-jun; Luo, Jie; Wang, Qi; Zeng, De-wang; Lin, Yan-qun; Li, Hong-yan

2015-06-01

To explore the relation between the frequencies of apolipoprotein E (ApoE) alleles and the occurrence of depression in patients undergoing hemodialysis in a Chinese population. We examined the ApoE alleles in a sample of 288 subjects: 72 patients with depression under hemodialysis, 74 patients without depression under hemodialysis, 75 patients with depression under nondialytic treatment and 67 patients without depression under nondialytic treatment. The depression state was assessed using the Center for Epidemiological Studies Depression (CES-D) scale. Associations between the occurrence of depression and the frequencies of ApoE alleles were examined using multinomial logistic regression models with adjustment of relevant covariates. Information about sociodemographics, clinical data, vascular risk factors and cognitive function was also collected and evaluated. The frequencies of ApoE-ɛ2 were significantly different between depressed and non-depressed patients irrespective of dialysis (p < 0.05), but no significant difference was found in the frequencies of ApoE-ɛ4 (p > 0.05). Serum ApoE levels were significantly different between depressed and non-depressed patients in the whole sample (p < 0.05). Multinomial logistic regression models showed significant association between the frequency of ApoE-ɛ2 and the occurrence of depression in the Chinese population after control of relevant covariates, including age, sex, educational level, history of smoking and drinking, vascular risk factors and cognitive function. No association between the frequency of ApoE-ɛ4 and the occurrence of depression was found in patients undergoing hemodialysis. Further research is needed to find out if ApoE-ɛ2 acts as a protective factor in Chinese dialysis population since it might decrease the prevalence of depression and delay the onset age.

Inequality in the hepatitis B awareness level in rural residents from 7 provinces in China

PubMed Central

Zheng, Juan; Li, Quan; Wang, Jian; Zhang, Guojie; Wangen, Knut R.

2017-01-01

ABSTRACT The hepatitis B (HB) awareness level is an important factor affecting the rates of HB virus vaccination. To better understand income-related inequalities in the HB awareness level, it is imperative to identify the sources of inequalities and assess the contribution rates of these influential factors. This study analyzed the unequal distribution of the HB awareness level and the contributions of various influential factors. We performed a cross-sectional household survey with questionnaire-based, face-to-face interviews in 7 Chinese provinces. Responses from 7271 respondents were used in this analysis. Multinomial logistic regression was used for the analysis of contributing factors, and the concentration index was used as a measure of HB awareness inequalities. The HB awareness level varied across participants with different characteristics. Multinomial logistic regression of the explanatory factors of the HB awareness level showed that several estimated coefficients and relative risk ratios were statistically significant for middle- and high-level awareness, except for sex, occupation, and household income. The concentration index of the HB knowledge score was 0.140, indicating inequality gradients disadvantageous to the poor. The contribution rate of socioeconomic factors was the largest (60.8%), followed by demographic characteristics (29.0%) and geographic factors (4.3%). Demographic, socioeconomic, and geographic factors are associated with the HB awareness inequality. Therefore, to reduce inequality, HB-related health education targeting individuals with low socioeconomic status should be performed. Less-developed provinces, especially with high proportions of poor residents, warrant particular attention. Our findings may be beneficial to improve the HB virus vaccination rate for individuals with low socioeconomic status. PMID:28277091

Opinions About Electronic Cigarette Use in Smoke-Free Areas Among U.S. Adults, 2012

PubMed Central

Dube, Shanta R.; Sterling, Kymberle; Whitney, Carrie; Eriksen, Michael P.

2015-01-01

Introduction: In the United States, electronic cigarettes (e-cigarettes) are currently unregulated, extensively marketed, and experiencing a rapid increase in use. The purpose of this study was to examine the opinions of U.S. adults about e-cigarette use in smoke-free public areas. Methods: Data were obtained from the online HealthStyle survey administered to a probability sample of a nationally representative online panel. The study included 4,043U.S. adults, aged 18 years or older who responded to this question, “Do you think e-cigarette should be allowed to be used in public areas where tobacco smoking is prohibited?” Multinomial logistic regression analyses were used to examine opinions on e-cigarette use in smoke-free areas by sex, age, race/ethnicity, household income, education, census region, and cigarette smoking status and e-cigarette awareness and ever use. Results: Overall, about 40% of adults were uncertain whether e-cigarettes should be allowed in smoke-free areas, 37% opposed, while 23% favored their use in smoke-free public places. Multinomial logistic regression analyses showed that adults who were aware, ever used e-cigarettes, and current cigarette smokers were more likely to express an “in favor” opinion than adults who expressed an uncertain opinion (don’t know). Conclusion: Over 75% of U.S. adults reported uncertainty or disapproval of the use of e-cigarettes in smoke-free areas. Current cigarette smokers, adults aware or have ever used e-cigarettes were more supportive to exempting e-cigarettes from smoking restrictions. With impending regulation and the changing e-cigarette landscape, continued monitoring and research on public opinions about e-cigarette use in smoke-free places are needed. PMID:25358659

Trajectories of Childbearing among HIV Infected Indian Women: A Sequence Analysis Approach

PubMed Central

Darak, Shrinivas; Mills, Melinda; Kulkarni, Vinay; Kulkarni, Sanjeevani; Hutter, Inge; Janssen, Fanny

2015-01-01

Background HIV infection closely relates to and deeply affects the reproductive career of those infected. However, little is known about the reproductive career trajectories, specifically the interaction of the timing of HIV diagnosis with the timing and sequencing of reproductive events among HIV infected women. This is the first study to describe and typify this interaction. Methods Retrospective calendar data of ever married HIV infected women aged 15-45 attending a HIV clinic in Pune, Maharashtra, Western India (N=622) on reproductive events such as marriage, cohabitation with the partner, use of contraception, pregnancy, childbirth and HIV diagnosis were analyzed using sequence analysis and multinomial logistic regression. Results Optimal matching revealed three distinct trajectories: 1) HIV diagnosis concurrent with childbearing (40.7%), 2) HIV diagnosis after childbearing (32.1%), and 3) HIV diagnosis after husband’s death (27.2%). Multinomial logistic regression (trajectory 1 = baseline) showed that women who got married before the age of 21 years and who had no or primary level education had a significantly higher risk of knowing their HIV status either after childbearing or close to their husband’s death. The risk of HIV diagnosis after husband’s death was also higher among rural women and those who were diagnosed before 2005. Conclusions Three distinct patterns of interaction of timing of HIV diagnosis with timing and sequencing of events in the reproductive career were observed that have clear implications for (i) understanding of the individual life planning process in the context of HIV, (ii) formulation of assumptions for estimating HIV infected women in need of PMTCT services, and (iii) provision of care services. PMID:25906185

No compelling positive association between ovarian hormones and wearing red clothing when using multinomial analyses.

PubMed

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.

Risk factors associated with recurrent homelessness after a first homeless episode.

PubMed

McQuistion, Hunter L; Gorroochurn, Prakash; Hsu, Eustace; Caton, Carol L M

2014-07-01

Alcohol and drug use are commonly associated with the experience of homelessness. In order to better understand this, we explored the prevalence of drug and alcohol use as it related to successful re-housing within a sample of first-time single homeless adults at municipal shelters. From within this sample, we compared the features of recurrent homelessness with those of chronic homelessness and of being stably housed. We interviewed 344 subjects upon shelter entry and followed each one every six months for 18 months using standardized social and mental health measures. We analyzed baseline assessments relative to housing experiences during follow-up using Chi square and multinomial logistic regression. Eighty-one percent (N = 278) obtained housing over 18 months, of which 23.7 % (N = 66) experienced homelessness again. Recurrent homelessness was more common among those with a high school education and if initially re-housed with family. Bivariate analysis resulted in the observation of the highest rate of alcohol and other drug use among this recurrent group and multinomial logistic regression supported this only with the coupling of arrest history and diagnosed antisocial personality disorder. With relatively high rates of recurrent homelessness, there were differences between subjects who experienced recurrent homelessness compared to those who were stably housed and with chronic homelessness. That alcohol and other substance use disorders were associated with recurrent homelessness only if they were linked to other risk factors highlights the complexity of causes for homelessness and a resultant need to organize them into constellations of causal risk factors. Consistent with this, there should be initiatives that span bureaucratic boundaries so as to flexibly meet multiple complex service needs, thus improving outcomes concerning episodes of recurrent homelessness.

Associations Between Perceived Race-based Discrimination and Contraceptive Use Among Women Veterans in the ECUUN Study.

PubMed

MacDonald, Serena; Hausmann, Leslie R M; Sileanu, Florentina E; Zhao, Xinhua; Mor, Maria K; Borrero, Sonya

2017-09-01

To describe perceived race-based discrimination in Veterans Affairs (VA) health care settings and assess its associations with contraceptive use among a sample of women Veterans. This study used data from a national telephone survey of women Veterans aged 18-44 receiving health care in VA who were at risk of unintended pregnancy. Participants were asked about their perceptions of race-based discrimination while seeking VA health care and about their contraceptive use at last heterosexual intercourse. Logistic and multinomial regression analyses were used to examine associations between perceived race-based discrimination with use of prescription contraception. In our sample of 1341 women Veterans, 7.9% report perceived race-based discrimination when receiving VA care, with blacks and Hispanics reporting higher levels of perceived discrimination than white women (11.3% and 11.2% vs. 4.4%; P<0.001). In logistic and multinomial regression analyses adjusting for race/ethnicity, age, income, marital status, parity, and insurance, women who perceived race-based discrimination were less likely to use any prescription birth control than women who did not (odds ratio, 0.65; 95% confidence interval, 0.42-1.00), with the largest difference seen in rates of intrauterine device or implant use (odds ratio, 0.40; 95% confidence interval, 0.20-0.79). In this national sample of women Veterans, over 10% of racial/ethnic minority women perceived race-based discrimination when receiving care in VA settings, and perceived racial/ethnic discrimination was associated with lower likelihood of prescription contraception use, especially intrauterine devices and implants. VA efforts to enhance respectful interactions may not only improve patient health care experiences, but also represent an opportunity to improve reproductive health outcomes for women Veterans.

The heterogeneous health latent classes of elderly people and their socio-demographic characteristics in Taiwan.

PubMed

Liu, Li-Fan; Tian, Wei-Hua; Yao, Hui-Ping

2014-01-01

The health care needs of elderly people were influenced by their heterogeneity. This study aimed to identify the health latent classes of elderly people by using latent class analysis to deal with heterogeneity and examine their socio-demographic characteristics. Data came from the 2005 National Health Interview Survey (NHIS) in Taiwan. In total, 2449 elderly individuals with available health indicators were examined in latent class analysis (LCA), and 2217 elderly community-dwellings with complete socio-demographic data were analyzed by multinomial logistic regression. Four health latent classes were identified which included 1066 (43.5%) people in the High Comorbidity (HC), 152 (6.2%) in the Functional Impairment (FI), 252 (10.3%) in the Frail (FR), and 979 (40.0%) in the Relatively Healthy (RH) group. Multinomial logistic regressions revealed socio-demographic characteristics among health classes. The variables associated with an increased likelihood of being in the FR group were age, female, and living with families. They were also correlated to ethnicity and educations. Apart from age and gender, the Functional Impairment group was less likely to be ethnicity of Hakka, more likely to live with others than were the RH group. The HC group tended to be younger, with higher educations, and more likely to live in urban area than the Functional Impairment group. The correlations between health classes and socio-demographic factors were discussed. The health status of elderly people includes a variety of health indicators. A person-centered approach is critical to identify the health heterogeneity of elderly people and manage their care needs by targeting differential aging. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

A cross-sectional study of the association of age, race and ethnicity, and body mass index with sex steroid hormone marker profiles among men in the National Health and Nutrition Examination Survey (NHANES III)

PubMed Central

Ritchey, Jamie; Karmaus, Wilfried; Sabo-Attwood, Tara; Steck, Susan E; Zhang, Hongmei

2012-01-01

Objectives Since sex hormone markers are metabolically linked, examining sex steroid hormones singly may account for inconsistent findings by age, race/ethnicity and body mass index (BMI) across studies. First, these markers were statistically combined into profiles to account for the metabolic relationship between markers. Then, the relationships between sex steroid hormone profiles and age, race/ethnicity and BMI were explored in multinomial logistic regression models. Design Cross-sectional survey. Setting The US Third National Health and Nutrition Examination Survey (NHANES III). Participants 1538 Men, >17 years. Primary outcome measure Sex hormone profiles. Results Cluster analysis was used to identify four statistically determined profiles with Blom-transformed T, E, sex hormone binding globulin (SHBG), and 3-α diol G. We used these four profiles with multinomial logistic regression models to examine differences by race/ethnicity, age and BMI. Mexican American men >50 years were associated with the profile that had lowest T, E and 3-α diol G levels compared to other profiles (p<0.05). Non-Hispanic Black, overweight (25–29.9 kg/m2) and obese (>30 kg/m2) men were most likely to be associated with the cluster with the lowest SHBG (p<0.05). Conclusion The associations of sex steroid hormone profiles by race/ethnicity are novel, while the findings by age and BMI groups are largely consistent with observations from single hormone studies. Future studies should validate these hormone profile groups and investigate these profiles in relation to chronic diseases and certain cancers. PMID:23043125

Inequitable childhood immunization uptake in Nigeria: a multilevel analysis of individual and contextual determinants

PubMed Central

2009-01-01

Background Immunization coverage in many parts of Nigeria is far from optimal, and far from equitable. Nigeria accounts for half of the deaths from Measles in Africa, the highest prevalence of circulating wild poliovirus in the world, and the country is among the ten countries in the world with vaccine coverage below 50 percent. Studies focusing on community-level determinants therefore have serious policy implications Methods Multilevel multivariable regression analysis was used on a nationally-representative sample of women aged 15-49 years from the 2003 Nigeria Demographic and Health Survey. Multilevel regression analysis was performed with children (level 1) nested within mothers (level 2), who were in turn nested within communities (level 3). Results Results show that the pattern of full immunization clusters within families and communities, and that socio-economic characteristics are important in explaining the differentials in full immunization among the children in the study. At the individual level, ethnicity, mothers' occupation, and mothers' household wealth were characteristics of the mothers associated with full immunization of the children. At the community level, the proportion of mothers that had hospital delivery was a determinant of full immunization status. Conclusion Significant community-level variation remaining after having controlled for child- and mother-level characteristics is indicative of a need for further research on community-levels factors, which would enable extensive tailoring of community-level interventions aimed at improving full immunization and other child health outcomes. PMID:19930573

Stages of syphilis in South China - a multilevel analysis of early diagnosis.

PubMed

Wong, Ngai Sze; Huang, Shujie; Zheng, Heping; Chen, Lei; Zhao, Peizhen; Tucker, Joseph D; Yang, Li Gang; Goh, Beng Tin; Yang, Bin

2017-01-31

Early diagnosis of syphilis and timely treatment can effectively reduce ongoing syphilis transmission and morbidity. We examined the factors associated with the early diagnosis of syphilis to inform syphilis screening strategic planning. In an observational study, we analyzed reported syphilis cases in Guangdong Province, China (from 2014 to mid-2015) accessed from the national case-based surveillance system. We categorized primary and secondary syphilis cases as early diagnosis and categorized latent and tertiary syphilis as delayed diagnosis. Univariate analyses and multivariable logistic regressions were performed to identify the factors associated with early diagnosis. We also examined the factors associated with early diagnosis at the individual and city levels in multilevel logistic regression models with cases nested by city (n = 21), adjusted for age at diagnosis and gender. Among 83,944 diagnosed syphilis cases, 22% were early diagnoses. The city-level early diagnosis rate ranged from 7 to 46%, consistent with substantial geographic variation as shown in the multilevel model. Early diagnosis was associated with cases presenting to specialist clinics for screening, being male and attaining higher education level. Cases received syphilis testing in institutions and hospitals, and diagnosed in hospitals were less likely to be in early diagnosis. At the city-level, cases living in a city equipped with more hospitals per capita were less likely to be early diagnosis. To enhance early diagnosis of syphilis, city-specific syphilis screening strategies with a mix of passive and client/provider-initiated testing might be a useful approach.

Regional contextual influences on short sleep duration: a 50 universities population-based multilevel study in China.

PubMed

Yang, Tingzhong; Peng, Sihui; Barnett, Ross; Zhang, Chichen

2018-01-01

Ecological models have emphasized that short sleep duration (SSD) is influenced by both individual and environmental variables. However, few studies have considered the latter. The present study explores the influence of urban and regional contextual factors, net of individual characteristics, on the prevalence of SSD among university students in China. Participants were 11,954 students, who were identified through a multistage survey sampling process conducted in 50 universities. Individual data were obtained through a self-administered questionnaire, and contextual variables were retrieved from a national database. Multilevel logistic regression models were used to examine urban and regional variations in high and moderate levels of SSD. Overall the prevalence of high SSD (<6 hours sleep duration) was 2.8% (95% CI: 1.7%,3.9%) and moderate SSD (<7 hours) 24.7% (95% CI: 19.5%, 29.8%). Multilevel logistic regressions confirmed that home region gross domestic product (GDP) and the university regional unemployment rate were associated with SSD, net of other individual- and city-level covariates. Students attending high-level universities also recorded the highest levels of SSD. Of the individual characteristcs, only mother's occupation and student mental health status were related to SSD. The results of this study add important insights about the role of contextual factors affecting SSD among young adults and indicate the need to take into account both past, as well as present, environmental influences to control SSD.

Markov switching multinomial logit model: An application to accident-injury severities.

PubMed

Malyshkina, Nataliya V; Mannering, Fred L

2009-07-01

In this study, two-state Markov switching multinomial logit models are proposed for statistical modeling of accident-injury severities. These models assume Markov switching over time between two unobserved states of roadway safety as a means of accounting for potential unobserved heterogeneity. The states are distinct in the sense that in different states accident-severity outcomes are generated by separate multinomial logit processes. To demonstrate the applicability of the approach, two-state Markov switching multinomial logit models are estimated for severity outcomes of accidents occurring on Indiana roads over a four-year time period. Bayesian inference methods and Markov Chain Monte Carlo (MCMC) simulations are used for model estimation. The estimated Markov switching models result in a superior statistical fit relative to the standard (single-state) multinomial logit models for a number of roadway classes and accident types. It is found that the more frequent state of roadway safety is correlated with better weather conditions and that the less frequent state is correlated with adverse weather conditions.

Multilevel lumbar fusion and postoperative physiotherapy rehabilitation in a patient with persistent pain.

PubMed

Pons, Tracey; Shipton, Edward A

2011-04-01

There are no comparative randomised controlled trials of physiotherapy modalities for chronic low back and radicular pain associated with multilevel fusion. Physiotherapy-based rehabilitation to control pain and improve activation levels for persistent pain following multilevel fusion can be challenging. This is a case report of a 68-year-old man who was referred for physiotherapy intervention 10 months after a multilevel spinal fusion for spinal stenosis. He reported high levels of persistent postoperative pain with minimal activity as a consequence of his pain following the surgery. The physiotherapy interventions consisted of three phases of rehabilitation starting with pool exercise that progressed to land-based walking. These were all combined with transcutaneous electrical nerve stimulation (TENS) that was used consistently for up to 8 hours per day. As outcome measures, daily pain levels and walking distances were charted once the pool programme was completed (in the third phase). Phase progression was determined by shuttle test results. The pain level was correlated with the distance walked using linear regression over a 5-day average. Over a 5-day moving average, the pain level reduced and walking distance increased. The chart of recorded pain level and walking distance showed a trend toward decreased pain with the increased distance walked. In a patient undergoing multilevel lumbar fusion, the combined use of TENS and a progressive walking programme (from pool to land) reduced pain and increased walking distance. This improvement was despite poor medication compliance and a reported high level of postsurgical pain.

Expenditures on family dental care by active duty soldiers.

PubMed

Chisick, M C

1996-01-01

Expenditures on family dental care by U.S. active duty soldiers were explored in this 1992 worldwide survey. Of 9,560 respondents (62% response rate), 7,187 claimed dependents and 5,569 provided reliable data. Mean annual expenditures and multinomial regression on a distribution of expenditures were calculated. Results show average family dental care expenditures were as follows: total sample, $135; childless couples, $59; couples with children, $154; and single parents, $120. Between 72 and 83% of families spent $0 on dental care. Excluding non-spenders, overall expenditures averaged as follows: total sample, $531; childless couples, $354; couples with children, $560; and single parents, $470. Regression results show that expenditures on family dental care by soldiers are influenced by different factors depending on family composition. Policy measures to encourage optimal dental care by families of active duty soldiers should focus on increasing insurance coverage and use.

Work performance decrements are associated with Australian working conditions, particularly the demand to work longer hours.

PubMed

Holden, Libby; Scuffham, Paul A; Hilton, Michael F; Vecchio, Nerina N; Whiteford, Harvey A

2010-03-01

To demonstrate the importance of including a range of working conditions in models exploring the association between health- and work-related performance. The Australian Work Outcomes Research Cost-benefit study cross-sectional screening data set was used to explore health-related absenteeism and work performance losses on a sample of approximately 78,000 working Australians, including available demographic and working condition factors. Data collected using the World Health Organization Health and Productivity Questionnaire were analyzed with negative binomial logistic regression and multinomial logistic regressions for absenteeism and work performance, respectively. Hours expected to work, annual wage, and job insecurity play a vital role in the association between health- and work-related performance for both work attendance and self-reported work performance. Australian working conditions are contributing to both absenteeism and low work performance, regardless of health status.

Husband/Partner Intoxication and Intimate Partner Violence Against Women in the Philippines.

PubMed

Kerridge, Bradley T; Tran, Phu

2016-09-01

This study examined husband/partner intoxication and experience with physical, sexual, and emotional intimate partner violence against women (IPVAW) using data derived from a nationally representative survey conducted in the Philippines in 2013. Multivariate logistic regression analyses were used to examine the association between intoxication and 3 different types of intimate partner violence against women. Multinomial logistic regression was used to examine intoxication and severity of violence. In this sample, 28.8% of women reported experiencing any form of intimate partner violence and 92.9% of women reported their partner being intoxicated at least sometimes. Intoxication was significantly associated with all 3 types of intimate partner violence, while the odds of experiencing one form of IPVAW versus no form of IPVAW and 2 forms of IPVAW versus 1 form of IPVAW was greater among women reporting frequency of husband/partner intoxication as often. © 2016 APJPH.

Consistency in reporting condom use between husbands and wives in Bangladesh.

PubMed

Islam, Mohammad Amirul; Padmadas, Sabu S; Smith, Peter W F

2010-07-01

Consistency in reporting contraceptive use between spouses is little understood, especially in developing settings. This research challenges the accuracy of measuring contraceptive prevalence rate, which is traditionally calculated based on women's responses. Multinomial logistic regression techniques are employed on a couple dataset from the 1999-2000 Bangladesh Demographic and Health Survey (DHS) to investigate the consistency in reporting condom use between husbands and wives. The level of inconsistency in reporting condom use was about 46%, of which about 32% was explained by husbands reporting condom use while wives did not, and 14% by wives reporting condom use while husbands did not. Regression analysis showed that couple education and age difference between the spouses are significant determinants of inconsistent reporting behaviour. The findings suggest the need for alternative approaches (questions) in the DHS to ensure consistency in the collection of data related to use of family planning methods.

Perceived health status and daily activity participation of older Malaysians.

PubMed

Ng, Sor Tho; Tengku-Aizan, Hamid; Tey, Nai Peng

2011-07-01

This article investigates the influence of perceived health status on the daily activity participation of older Malaysians. Data from the Survey on Perceptions of Needs and Problems of the Elderly, which was conducted in 1999, were used. The negative binomial regression results show that older persons with good perceived health status reported more varieties of daily activity participation, especially among the uneducated and those with below-average self-esteem. The multinomial logistic regression model suggests that older persons with good perceived health status tended to engage daily in paid work only or with leisure activities, whereas those perceived to have poor health were more likely to engage in leisure activities only or leisure and family role activities. Promotion of a healthy lifestyle at a younger age encourages every person to monitor and take responsibility for their own health, which is a necessary strategy to ensure active participation at an older age, and thus improve their well-being.

Family and School Influences on Adolescent Smoking Behaviour

ERIC Educational Resources Information Center

Wiium, Nora; Wold, Bente

2006-01-01

Purpose: This paper aims to examine how influences at home and school interact to predict smoking among adolescents. Design/methodology/approach: Data were collected from 15-year-old pupils from Norway (n=1,404 in 73 Grade 10 school classes). Multilevel logistic regression analysis was used to determine how family and school influences interact to…

Does the "Pupil Enterprise Programme" Influence Grades among Pupils with Special Needs?

ERIC Educational Resources Information Center

Johansen, Vegard; Somby, Hege M.

2016-01-01

This paper asks whether the Pupil Enterprise Programme (PEP) is a suitable working method for improving academic performance among pupils with special needs. Overall, 20% of pupils participate in PEP at some point during lower secondary school. Results from multilevel regression modelling indicate that pupils with special needs who have…

Beyond the United States and Japan: Testing Yamagishi's Emancipation Theory of Trust across 31 Nations

ERIC Educational Resources Information Center

Gheorghiu, Mirona A.; Vignoles, Vivian L.; Smith, Peter B.

2009-01-01

We examined the relationship between Individualism/Collectivism and generalized social trust across 31 European nations participating in the European Social Survey. Using multilevel regression analyses, the current study provides the first empirical investigation of the effects of cultural norms of Individualism/Collectivism on generalized social…

Influence of Misaligned Parents' Aspirations on Long-Term Student Academic Performance

ERIC Educational Resources Information Center

de Boer, Hester; van der Werf, Margaretha P. C.

2015-01-01

This article deals with the concept of misaligned parents' aspirations, its relationship with student background characteristics, and its effects on long-term student performance. It is defined as the difference between parents' educational ambitions for their child and the child's actual capacities. Multilevel regression analyses on a sample of…

Freshman Year Dropouts: Interactions between Student and School Characteristics and Student Dropout Status

ERIC Educational Resources Information Center

Zvoch, Keith

2006-01-01

Data from a large school district in the southwestern United States were analyzed to investigate relations between student and school characteristics and high school freshman dropout patterns. Application of a multilevel logistic regression model to student dropout data revealed evidence of school-to-school differences in student dropout rates and…

Examining Relations between Mathematics Teachers' Instructional Vision and Knowledge and Change in Practice

ERIC Educational Resources Information Center

Munter, Charles; Correnti, Richard

2017-01-01

This article provides a longitudinal examination of how changes in more than 200 middle-grades mathematics teachers' instructional practices related to their (a) mathematical knowledge for teaching (MKT) and (b) instructional vision. Results of this multilevel regression analysis suggest that MKT and instructional vision are related to instruction…

Using Cluster Bootstrapping to Analyze Nested Data With a Few Clusters.

PubMed

Huang, Francis L

2018-04-01

Cluster randomized trials involving participants nested within intact treatment and control groups are commonly performed in various educational, psychological, and biomedical studies. However, recruiting and retaining intact groups present various practical, financial, and logistical challenges to evaluators and often, cluster randomized trials are performed with a low number of clusters (~20 groups). Although multilevel models are often used to analyze nested data, researchers may be concerned of potentially biased results due to having only a few groups under study. Cluster bootstrapping has been suggested as an alternative procedure when analyzing clustered data though it has seen very little use in educational and psychological studies. Using a Monte Carlo simulation that varied the number of clusters, average cluster size, and intraclass correlations, we compared standard errors using cluster bootstrapping with those derived using ordinary least squares regression and multilevel models. Results indicate that cluster bootstrapping, though more computationally demanding, can be used as an alternative procedure for the analysis of clustered data when treatment effects at the group level are of primary interest. Supplementary material showing how to perform cluster bootstrapped regressions using R is also provided.

Impact of high-performance work systems on individual- and branch-level performance: test of a multilevel model of intermediate linkages.

PubMed

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.

Addictive internet use among Korean adolescents: a national survey.

PubMed

Heo, Jongho; Oh, Juhwan; Subramanian, S V; Kim, Yoon; Kawachi, Ichiro

2014-01-01

A psychological disorder called 'Internet addiction' has newly emerged along with a dramatic increase of worldwide Internet use. However, few studies have used population-level samples nor taken into account contextual factors on Internet addiction. We identified 57,857 middle and high school students (13-18 year olds) from a Korean nationally representative survey, which was surveyed in 2009. To identify associated factors with addictive Internet use, two-level multilevel regression models were fitted with individual-level responses (1st level) nested within schools (2nd level) to estimate associations of individual and school characteristics simultaneously. Gender differences of addictive Internet use were estimated with the regression model stratified by gender. Significant associations were found between addictive Internet use and school grade, parental education, alcohol use, tobacco use, and substance use. Female students in girls' schools were more likely to use Internet addictively than those in coeducational schools. Our results also revealed significant gender differences of addictive Internet use in its associated individual- and school-level factors. Our results suggest that multilevel risk factors along with gender differences should be considered to protect adolescents from addictive Internet use.

Assessing a multilevel model of young children’s oral health with national survey data

PubMed Central

Bramlett, Matthew D.; Soobader, Mah-J; Fisher-Owens, Susan A.; Weintraub, Jane A.; Gansky, Stuart A.; Platt, Larry J.; Newacheck, Paul W.

2010-01-01

Objectives To empirically test a multilevel conceptual model of children’s oral health incorporating 22 domains of children’s oral health across four levels: child, family, neighborhood and state. Data source The 2003 National Survey of Children’s Health, a module of the State and Local Area Integrated Telephone Survey conducted by the Centers for Disease Control and Prevention’s National Center for Health Statistics, is a nationally representative telephone survey of caregivers of children. Study design We examined child-, family-, neighborhood-, and state-level factors influencing parent’s report of children’s oral health using a multilevel logistic regression model, estimated for 26 736 children ages 1–5 years. Principal findings Factors operating at all four levels were associated with the likelihood that parents rated their children’s oral health as fair or poor, although most significant correlates are represented at the child or family level. Of 22 domains identified in our conceptual model, 15 domains contained factors significantly associated with young children’s oral health. At the state level, access to fluoridated water was significantly associated with favorable oral health for children. Conclusions Our results suggest that efforts to understand or improve children’s oral health should consider a multilevel approach that goes beyond solely child-level factors. PMID:20370808

Social factors, weight perception, and weight control practices among adolescents in Mexico.

PubMed

Bojorquez, Ietza; Villatoro, Jorge; Delgadillo, Marlene; Fleiz, Clara; Fregoso, Diana; Unikel, Claudia

2018-06-01

We evaluated the association of social factors and weight control practices in adolescents, and the mediation of this association by weight perception, in a national survey of students in Mexico ( n = 28,266). We employed multinomial and Poisson regression models and Sobel's test to assess mediation. Students whose mothers had a higher level of education were more likely to perceive themselves as overweight and also to engage in weight control practices. After adjusting for body weight perception, the effect of maternal education on weight control practices remained significant. Mediation tests were significant for boys and non-significant for girls.

Objectively measured sedentary time and academic achievement in schoolchildren.

PubMed

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

2017-03-01

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

Extended opening hours and patient experience of general practice in England: multilevel regression analysis of a national patient survey

PubMed Central

Cowling, Thomas E; Harris, Matthew; Majeed, Azeem

2017-01-01

Background The UK government plans to extend the opening hours of general practices in England. The ‘extended hours access scheme’ pays practices for providing appointments outside core times (08:00 to 18.30, Monday to Friday) for at least 30 min per 1000 registered patients each week. Objective To determine the association between extended hours access scheme participation and patient experience. Methods Retrospective analysis of a national cross-sectional survey completed by questionnaire (General Practice Patient Survey 2013–2014); 903 357 survey respondents aged ≥18 years old and registered to 8005 general practices formed the study population. Outcome measures were satisfaction with opening hours, experience of making an appointment and overall experience (on five-level interval scales from 0 to 100). Mean differences between scheme participation groups were estimated using multilevel random-effects regression, propensity score matching and instrumental variable analysis. Results Most patients were very (37.2%) or fairly satisfied (42.7%) with the opening hours of their general practices; results were similar for experience of making an appointment and overall experience. Most general practices participated in the extended hours access scheme (73.9%). Mean differences in outcome measures between scheme participants and non-participants were positive but small across estimation methods (mean differences ≤1.79). For example, scheme participation was associated with a 1.25 (95% CI 0.96 to 1.55) increase in satisfaction with opening hours using multilevel regression; this association was slightly greater when patients could not take time off work to see a general practitioner (2.08, 95% CI 1.53 to 2.63). Conclusions Participation in the extended hours access scheme has a limited association with three patient experience measures. This questions expected impacts of current plans to extend opening hours on patient experience. PMID:27343274

Extended opening hours and patient experience of general practice in England: multilevel regression analysis of a national patient survey.

PubMed

Cowling, Thomas E; Harris, Matthew; Majeed, Azeem

2017-05-01

The UK government plans to extend the opening hours of general practices in England. The 'extended hours access scheme' pays practices for providing appointments outside core times (08:00 to 18.30, Monday to Friday) for at least 30 min per 1000 registered patients each week. To determine the association between extended hours access scheme participation and patient experience. Retrospective analysis of a national cross-sectional survey completed by questionnaire (General Practice Patient Survey 2013-2014); 903 357 survey respondents aged ≥18 years old and registered to 8005 general practices formed the study population. Outcome measures were satisfaction with opening hours, experience of making an appointment and overall experience (on five-level interval scales from 0 to 100). Mean differences between scheme participation groups were estimated using multilevel random-effects regression, propensity score matching and instrumental variable analysis. Most patients were very (37.2%) or fairly satisfied (42.7%) with the opening hours of their general practices; results were similar for experience of making an appointment and overall experience. Most general practices participated in the extended hours access scheme (73.9%). Mean differences in outcome measures between scheme participants and non-participants were positive but small across estimation methods (mean differences ≤1.79). For example, scheme participation was associated with a 1.25 (95% CI 0.96 to 1.55) increase in satisfaction with opening hours using multilevel regression; this association was slightly greater when patients could not take time off work to see a general practitioner (2.08, 95% CI 1.53 to 2.63). Participation in the extended hours access scheme has a limited association with three patient experience measures. This questions expected impacts of current plans to extend opening hours on patient experience. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Availability and quality of coronary heart disease family history in primary care medical records: implications for cardiovascular risk assessment.

PubMed

Dhiman, Paula; Kai, Joe; Horsfall, Laura; Walters, Kate; Qureshi, Nadeem

2014-01-01

The potential to use data on family history of premature disease to assess disease risk is increasingly recognised, particularly in scoring risk for coronary heart disease (CHD). However the quality of family health information in primary care records is unclear. To assess the availability and quality of family history of CHD documented in electronic primary care records. Cross-sectional study. 537 UK family practices contributing to The Health Improvement Network database. Data were obtained from patients aged 20 years or more, registered with their current practice between 1(st) January 1998 and 31(st) December 2008, for at least one year. The availability and quality of recorded CHD family history was assessed using multilevel logistic and ordinal logistic regression respectively. In a cross-section of 1,504,535 patients, 19% had a positive or negative family history of CHD recorded. Multilevel logistic regression showed patients aged 50-59 had higher odds of having their family history recorded compared to those aged 20-29 (OR:1.23 (1.21 to 1.25)), however most deprived patients had lower odds compared to those least deprived (OR: 0.86 (0.85 to 0.88)). Of the 140,058 patients with a positive family history recorded (9% of total cohort), age of onset was available in 45%; with data specifying both age of onset and relative affected available in only 11% of records. Multilevel ordinal logistic regression confirmed no statistical association between the quality of family history recording and age, gender, deprivation and year of registration. Family history of CHD is documented in a small proportion of primary care records; and where positive family history is documented the details are insufficient to assess familial risk or populate cardiovascular risk assessment tools. Data capture needs to be improved particularly for more disadvantaged patients who may be most likely to benefit from CHD risk assessment.

The outcome of tuberculosis treatment in subjects with chronic kidney disease in Brazil: a multinomial analysis*

PubMed Central

Reis-Santos, Barbara; Gomes, Teresa; Horta, Bernardo Lessa; Maciel, Ethel Leonor Noia

2013-01-01

OBJECTIVE: To analyze the association between clinical/epidemiological characteristics and outcomes of tuberculosis treatment in patients with concomitant tuberculosis and chronic kidney disease (CKD) in Brazil. METHODS: We used the Brazilian Ministry of Health National Case Registry Database to identify patients with tuberculosis and CKD, treated between 2007 and 2011. The tuberculosis treatment outcomes were compared with epidemiological and clinical characteristics of the subjects using a hierarchical multinomial logistic regression model, in which cure was the reference outcome. RESULTS: The prevalence of CKD among patients with tuberculosis was 0.4% (95% CI: 0.37-0.42%). The sample comprised 1,077 subjects. The outcomes were cure, in 58%; treatment abandonment, in 7%; death from tuberculosis, in 13%; and death from other causes, in 22%. The characteristics that differentiated the ORs for treatment abandonment or death were age; alcoholism; AIDS; previous noncompliance with treatment; transfer to another facility; suspected tuberculosis on chest X-ray; positive results in the first smear microscopy; and indications for/use of directly observed treatment, short-course strategy. CONCLUSIONS: Our data indicate the importance of sociodemographic characteristics for the diagnosis of tuberculosis in patients with CKD and underscore the need for tuberculosis control strategies targeting patients with chronic noncommunicable diseases, such as CKD. PMID:24310632

Assessing coastal plain wetland composition using advanced spaceborne thermal emission and reflection radiometer imagery

NASA Astrophysics Data System (ADS)

Pantaleoni, Eva

Establishing wetland gains and losses, delineating wetland boundaries, and determining their vegetative composition are major challenges that can be improved through remote sensing studies. We used the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) to separate wetlands from uplands in a study of 870 locations on the Virginia Coastal Plain. We used the first five bands from each of two ASTER scenes (6 March 2005 and 16 October 2005), covering the visible to the short-wave infrared region (0.52-2.185mum). We included GIS data layers for soil survey, topography, and presence or absence of water in a logistic regression model that predicted the location of over 78% of the wetlands. While this was slightly less accurate (78% vs. 86%) than current National Wetland Inventory (NWI) aerial photo interpretation procedures of locating wetlands, satellite imagery analysis holds great promise for speeding wetland mapping, lowering costs, and improving update frequency. To estimate wetland vegetation composition classes, we generated a classification and regression tree (CART) model and a multinomial logistic regression (logit) model, and compared their accuracy in separating woody wetlands, emergent wetlands and open water. The overall accuracy of the CART model was 73.3%, while for the logit model was 76.7%. The CART producer's accuracy of the emergent wetlands was higher than the accuracy from the multinomial logit (57.1% vs. 40.7%). However, we obtained the opposite result for the woody wetland category (68.7% vs. 52.6%). A McNemar test between the two models and NWI maps showed that their accuracies were not statistically different. We conducted a subpixel analysis of the ASTER images to estimate canopy cover of forested wetlands. We used top-of-atmosphere reflectance from the visible and near infrared bands, Delta Normalized Difference Vegetation Index, and a tasseled cap brightness, greenness, and wetness in linear regression model with canopy cover as the dependent variable. The model achieved an adjusted-R 2 of 0.69 (RMSE = 2.7%) for canopy cover less than 16%, and an adjusted-R 2 of 0.04 (RMSE = 19.8%) for higher canopy cover values. Taken together, these findings suggest that satellite remote sensing, in concert with other spatial data, has strong potential for mapping both wetland presence and type.

Mathematical models application for mapping soils spatial distribution on the example of the farm from the North of Udmurt Republic of Russia

NASA Astrophysics Data System (ADS)

Dokuchaev, P. M.; Meshalkina, J. L.; Yaroslavtsev, A. M.

2018-01-01

Comparative analysis of soils geospatial modeling using multinomial logistic regression, decision trees, random forest, regression trees and support vector machines algorithms was conducted. The visual interpretation of the digital maps obtained and their comparison with the existing map, as well as the quantitative assessment of the individual soil groups detection overall accuracy and of the models kappa showed that multiple logistic regression, support vector method, and random forest models application with spatial prediction of the conditional soil groups distribution can be reliably used for mapping of the study area. It has shown the most accurate detection for sod-podzolics soils (Phaeozems Albic) lightly eroded and moderately eroded soils. In second place, according to the mean overall accuracy of the prediction, there are sod-podzolics soils - non-eroded and warp one, as well as sod-gley soils (Umbrisols Gleyic) and alluvial soils (Fluvisols Dystric, Umbric). Heavy eroded sod-podzolics and gray forest soils (Phaeozems Albic) were detected by methods of automatic classification worst of all.

An Airline-Based Multilevel Analysis of Airfare Elasticity for Passenger Demand

NASA Technical Reports Server (NTRS)

Castelli, Lorenzo; Ukovich, Walter; Pesenti, Raffaele

2003-01-01

Price elasticity of passenger demand for a specific airline is estimated. The main drivers affecting passenger demand for air transportation are identified. First, an Ordinary Least Squares regression analysis is performed. Then, a multilevel analysis-based methodology to investigate the pattern of variation of price elasticity of demand among the various routes of the airline under study is proposed. The experienced daily passenger demands on each fare-class are grouped for each considered route. 9 routes were studied for the months of February and May in years from 1999 to 2002, and two fare-classes were defined (business and economy). The analysis has revealed that the airfare elasticity of passenger demand significantly varies among the different routes of the airline.

Insights into the latent multinomial model through mark-resight data on female grizzly bears with cubs-of-the-year

USGS Publications Warehouse

Higgs, Megan D.; Link, William; White, Gary C.; Haroldson, Mark A.; Bjornlie, Daniel D.

2013-01-01

Mark-resight designs for estimation of population abundance are common and attractive to researchers. However, inference from such designs is very limited when faced with sparse data, either from a low number of marked animals, a low probability of detection, or both. In the Greater Yellowstone Ecosystem, yearly mark-resight data are collected for female grizzly bears with cubs-of-the-year (FCOY), and inference suffers from both limitations. To overcome difficulties due to sparseness, we assume homogeneity in sighting probabilities over 16 years of bi-annual aerial surveys. We model counts of marked and unmarked animals as multinomial random variables, using the capture frequencies of marked animals for inference about the latent multinomial frequencies for unmarked animals. We discuss undesirable behavior of the commonly used discrete uniform prior distribution on the population size parameter and provide OpenBUGS code for fitting such models. The application provides valuable insights into subtleties of implementing Bayesian inference for latent multinomial models. We tie the discussion to our application, though the insights are broadly useful for applications of the latent multinomial model.

Burden and predictors of Staphylococcus aureus and S. pseudintermedius infections among dogs presented at an academic veterinary hospital in South Africa (2007–2012)

PubMed Central

Oguttu, James Wabwire; Sithole, Fortune

2017-01-01

Background Staphylococci are commensals of the mucosal surface and skin of humans and animals, but have been implicated in infections such as otitis externa, pyoderma, urinary tract infections and post-surgical complications. Laboratory records provide useful information to help investigate these infections. Therefore, the objective of this study was to investigate the burdens of these infections and use multinomial regression to examine the associations between various Staphylococcus infections and demographic and temporal factors among dogs admitted to an academic veterinary hospital in South Africa. Methods Records of 1,497 clinical canine samples submitted to the bacteriology laboratory at a veterinary academic hospital between 2007 and 2012 were included in this study. Proportions of staphylococcal positive samples were calculated, and a multinomial logistic regression model was used to identify predictors of staphylococcal infections. Results Twenty-seven percent of the samples tested positive for Staphylococcus spp. The species of Staphylococcus identified were S. pseudintermedius (19.0%), S. aureus (3.8%), S. epidermidis (0.7%) and S. felis (0.1%). The remaining 2.87% consisted of unspeciated Staphylococcus. Distribution of the species by age of dog showed that S. pseudintermedius was the most common (25.6%) in dogs aged 2–4 years while S. aureus was most frequent (6.3%) in dogs aged 5–6 years. S. pseudintermedius (34.1%) and S. aureus (35.1%) were the most frequently isolated species from skin samples. The results of the multivariable multinomial logistic regression model identified specimen, year and age of the dog as significant predictors of the risk of infection with Staphylococcus. There was a significant temporal increase (RRR = 1.17; 95% CI [1.06–1.29]) in the likelihood of a dog testing positive for S. pseudintermedius compared to testing negative. Dogs ≤ 8 years of age were significantly more likely to test positive for S. aureus than those >8 years of age. Similarly, dogs between 2–8 years of age were significantly more likely to test positive for S. pseudintermedius than those >8 years of age. In addition, dogs 2–4 years of age (RRR = 1.83; 1.09–3.06) were significantly more likely to test positive for S. pseudintermedius compared to those <2 years of age. The risk of infection with S. pseudintermedius or S. aureus was significantly higher in ear canal and skin specimens compared to other specimens. Conclusions The findings suggest that S. pseudintermedius and S. aureus were the most commonly isolated species from dogs presented at the study hospital. Age of the dog and the location of infection were significant predictors of infection with both Staphylococcus species investigated. Significant increasing temporal trend was observed for S. pseudintermedius but not S. aureus. This information is useful for guiding clinical decisions as well as future research. PMID:28417060

Assessment of Malawian Mothers’ Malaria Knowledge, Healthcare Preferences and Timeliness of Seeking Fever Treatments for Children Under Five

PubMed Central

Oyekale, Abayomi Samuel

2015-01-01

Malaria is one of the major public health problems in Malawi, contributing to the majority of morbidity and mortality among children under five. Ignorance of malaria symptoms results in delayed treatment, which often degenerates into fatal emergencies. This study analyzed the impact of maternal malaria knowledge on healthcare preferences and timeliness of treating children with reported fever. The Malaria Indicator Survey data for 2012, which were adequately weighted, were analyzed using multinomial logit and Poisson regression models. The results showed low maternal average years of formal education (3.52) and average mothers’ age was 27.97 years. Majority of the women (84.98%) associated fever with malaria, while 44.17% associated it with chilling. Also, 54.42% and 32.43% of the children were treated for fever on the same day and the following day that fever started, respectively. About 9.70% paid for fever treatment from their regular incomes, while 51.38% sought treatment from either public or private health centers. Multinomial Logit regression results showed that relative to using of other treatments, probabilities of selecting private hospitals and public health centers increased with age of the household heads, resident in urban areas, mothers’ years of education, number of days taken off for treatment, paying medical bills from regular, occasional and borrowed incomes, and knowledge of diarrhea and shivering as symptoms of malaria. In the Poisson regression results, timeliness of seeking treatment was significantly enhanced by knowledge of fever as malaria symptom, residence in northern and central regions of Malawi and use of income from sale of assets to pay medical bills (p < 0.10).However, delays in treating children was motivated by age of the household heads, number of days taken off to care for sick child and usage of regular, borrowed and other incomes to pay medical bills. (p < 0.05). It was concluded that efficiency of public sector in treating malaria holds significant prospects for fighting malaria in Malawi. However, adequate efforts should be channeled in enhancing the knowledge of women on malaria symptoms, among others. PMID:25584420

Assessment of Malawian mothers' malaria knowledge, healthcare preferences and timeliness of seeking fever treatments for children under five.

PubMed

Oyekale, Abayomi Samuel

2015-01-09

Malaria is one of the major public health problems in Malawi, contributing to the majority of morbidity and mortality among children under five. Ignorance of malaria symptoms results in delayed treatment, which often degenerates into fatal emergencies. This study analyzed the impact of maternal malaria knowledge on healthcare preferences and timeliness of treating children with reported fever. The Malaria Indicator Survey data for 2012, which were adequately weighted, were analyzed using multinomial logit and Poisson regression models. The results showed low maternal average years of formal education (3.52) and average mothers' age was 27.97 years. Majority of the women (84.98%) associated fever with malaria, while 44.17% associated it with chilling. Also, 54.42% and 32.43% of the children were treated for fever on the same day and the following day that fever started, respectively. About 9.70% paid for fever treatment from their regular incomes, while 51.38% sought treatment from either public or private health centers. Multinomial Logit regression results showed that relative to using of other treatments, probabilities of selecting private hospitals and public health centers increased with age of the household heads, resident in urban areas, mothers' years of education, number of days taken off for treatment, paying medical bills from regular, occasional and borrowed incomes, and knowledge of diarrhea and shivering as symptoms of malaria. In the Poisson regression results, timeliness of seeking treatment was significantly enhanced by knowledge of fever as malaria symptom, residence in northern and central regions of Malawi and use of income from sale of assets to pay medical bills (p < 0.10).However, delays in treating children was motivated by age of the household heads, number of days taken off to care for sick child and usage of regular, borrowed and other incomes to pay medical bills. (p < 0.05). It was concluded that efficiency of public sector in treating malaria holds significant prospects for fighting malaria in Malawi. However, adequate efforts should be channeled in enhancing the knowledge of women on malaria symptoms, among others.

English Phonological Awareness in Bilinguals: A Cross-Linguistic Study of Tamil, Malay and Chinese English-Language Learners

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…

Does the Perceived Neighborhood Reputation Contribute to Neighborhood Differences in Social Trust and Residential Wellbeing?

ERIC Educational Resources Information Center

Kullberg, Agneta; Timpka, Toomas; Svensson, Tommy; Karlsson, Nadine; Lindqvist, Kent

2010-01-01

The authors used a mixed methods approach to examine if the reputation of a housing area has bearing on residential wellbeing and social trust in three pairs of socioeconomically contrasting neighborhoods in a Swedish urban municipality. Multilevel logistic regression analyses were performed to examine associations between area reputation and…

Educational Investment, Family Context, and Children's Math and Reading Growth from Kindergarten through the Third Grade

ERIC Educational Resources Information Center

Cheadle, Jacob E.

2008-01-01

Drawing on longitudinal data from the Early Childhood Longitudinal Study, Kindergarten Class of 1998-1999, this study used IRT modeling to operationalize a measure of parental educational investments based on Lareau's notion of concerted cultivation. It used multilevel piece-wise growth models regressing children's math and reading achievement…

Using Generalized Additive Models to Analyze Single-Case Designs

ERIC Educational Resources Information Center

Shadish, William; Sullivan, Kristynn

2013-01-01

Many analyses for single-case designs (SCDs)--including nearly all the effect size indicators-- currently assume no trend in the data. Regression and multilevel models allow for trend, but usually test only linear trend and have no principled way of knowing if higher order trends should be represented in the model. This paper shows how Generalized…

Couples at Risk Following the Death of Their Child: Predictors of Grief versus Depression

ERIC Educational Resources Information Center

Wijngaards-de Meij, Leoniek; Stroebe, Margaret; Schut, Henk; Stroebe, Wolfgang; van den Bout, Jan; van der Heijden, Peter; Dijkstra, Iris

2005-01-01

This longitudinal study examined the relative impact of major variables for predicting adjustment (in terms of both grief and depression) among bereaved parents following the death of their child. Couples (N = 219) participated 6, 13, and 20 months postloss. Use of multilevel regression analyses enabled assessment of the impact of several…

Family Structure and Child Mortality in Sub-Saharan Africa: Cross-National Effects of Polygyny

ERIC Educational Resources Information Center

Omariba, D. Walter Rasugu; Boyle, Michael H.

2007-01-01

This study applies multilevel logistic regression to Demographic and Health Survey data from 22 sub-Saharan African countries to examine whether the relationship between child mortality and family structure, with a specific emphasis on polygyny, varies cross-nationally and over time. Hypotheses were developed on the basis of competing theories on…

Evaluating the Effect of a Television Public Service Announcement about Epilepsy

ERIC Educational Resources Information Center

Martiniuk, Alexandra L. C.; Secco, Mary; Yake, Laura; Speechley, Kathy N.

2010-01-01

Public service announcements (PSAs) are non-commercial advertisements aiming to improve knowledge, attitudes and/or behavior. No evaluations of epilepsy PSAs exist. This study sought to evaluate a televised PSA showing first aid for a seizure. A multilevel regression analysis was used to determine the effect of the PSA on epilepsy knowledge and…

Exploring Person Fit with an Approach Based on Multilevel Logistic Regression

ERIC Educational Resources Information Center

Walker, A. Adrienne; Engelhard, George, Jr.

2015-01-01

The idea that test scores may not be valid representations of what students know, can do, and should learn next is well known. Person fit provides an important aspect of validity evidence. Person fit analyses at the individual student level are not typically conducted and person fit information is not communicated to educational stakeholders. In…

A multilevel analysis of lifestyle variations in symptoms of acute respiratory infection among young children under five in Nigeria.

PubMed

Adesanya, Oluwafunmilade A; Chiao, Chi

2016-08-25

Nigeria has the second highest estimated number of deaths due to acute respiratory infection (ARI) among children under five in the world. A common hypothesis is that the inequitable distribution of socioeconomic resources shapes individual lifestyles and health behaviors, which leads to poorer health, including symptoms of ARI. This study examined whether lifestyle factors are associated with ARI risk among Nigerian children aged less than 5 years, taking individual-level and contextual-level risk factors into consideration. Data were obtained from the nationally representative 2013 Nigeria Demographic and Health Survey. A total of 28,596 surviving children aged 5 years or younger living in 896 communities were analyzed. We employed two-level multilevel logistic regressions to model the relationship between lifestyle factors and ARI symptoms. The multivariate results from multilevel regressions indicated that the odds of having ARI symptoms were increased by a number of lifestyle factors such as in-house biomass cooking (OR = 2.30; p < 0.01) and no hand-washing (OR = 1.66; p < 0.001). An increased risk of ARI symptoms was also significantly associated with living in the North West region and the community with a high proportion of orphaned/vulnerable children (OR = 1.74; p < 0.001). Our findings underscore the importance of Nigerian children's lifestyle within the neighborhoods where they reside above their individual characteristics. Program-based strategies that are aimed at reducing ARI symptoms should consider policies that embrace making available basic housing standards, providing improved cooking stoves and enhancing healthy behaviors.

The relationship between session frequency and psychotherapy outcome in a naturalistic setting.

PubMed

Erekson, David M; Lambert, Michael J; Eggett, Dennis L

2015-12-01

The dose-response relationship in psychotherapy has been examined extensively, but few studies have included session frequency as a component of psychotherapy "dose." Studies that have examined session frequency have indicated that it may affect both the speed and the amount of recovery. No studies were found examining the clinical significance of this construct in a naturalistic setting, which is the aim of the current study. Using an archival database of session-by-session Outcome Questionnaire 45 (OQ-45) measures over 17 years, change trajectories of 21,488 university counseling center clients (54.9% female, 85.0% White, mean age = 22.5) were examined using multilevel modeling, including session frequency at the occasion level. Of these clients, subgroups that attended therapy approximately weekly or fortnightly were compared to each other for differences in speed of recovery (using multilevel Cox regression) and clinically significant change (using multilevel logistic regression). Results indicated that more frequent therapy was associated with steeper recovery curves (Cohen's f2 = 0.07; an effect size between small and medium). When comparing weekly and fortnightly groups, clinically significant gains were achieved faster for those attending weekly sessions; however, few significant differences were found between groups in total amount of change in therapy. Findings replicated previous session frequency literature and supported a clinically significant effect, where higher session frequency resulted in faster recovery. Session frequency appears to be an impactful component in delivering more efficient psychotherapy, and it is important to consider in individual treatment planning, institutional policy, and future research. (c) 2015 APA, all rights reserved).

Determinants of Exclusive Breast Feeding in sub-Saharan Africa: A Multilevel Approach.

PubMed

Yalçin, Siddika Songül; Berde, Anselm S; Yalçin, Suzan

2016-09-01

The study aimed to provide an overall picture of the general pattern of exclusive breast feeding (EBF) in sub-Saharan Africa (SSA) by examining maternal sociodemographic, antenatal and postnatal factors associated with EBF in the region, as well as explore countries variations in EBF rates. We utilised cross-sectional data from the Demographic Health Surveys in 27 SSA countries. Our study sample included 25 084 infants under 6 months of age. The key outcome variable was EBF in the last 24 h. Due to the hierarchical structure of the data, a multilevel logistic regression model was used to explore factors associated with EBF. The overall prevalence of EBF in SSA was 36.0%, the prevalence was highest in Rwanda and lowest in Gabon. In the multilevel regression model, factors that were associated with increased likelihood of EBF included secondary and above maternal education, mothers within the ages of 25-34 years, rural residence, richer household wealth quantile, 4+ antenatal care visit, delivering in a health facility, singleton births, female infants, early initiation of breast feeding (EIBF), and younger infants. However, countries with higher gross national income per capita had lower EBF rates. To achieve a substantial increase in EBF rates in SSA, breast-feeding interventions and policies should target all women but with more emphasis to mothers with younger age, low educational status, urban residence, poor status, multiple births, and male infants. In addition, there is a need to promote antenatal care utilisation, hospital deliveries, and EIBF. © 2016 John Wiley & Sons Ltd.

Neighborhood contextual factors, maternal smoking, and birth outcomes: multilevel analysis of the South Carolina PRAMS survey, 2000-2003.

PubMed

Nkansah-Amankra, Stephen

2010-08-01

Previous studies investigating relationships among neighborhood contexts, maternal smoking behaviors, and birth outcomes (low birth weight [LBW] or preterm births) have produced mixed results. We evaluated independent effects of neighborhood contexts on maternal smoking behaviors and risks of LBW or preterm birth outcomes among mothers participating in the South Carolina Pregnancy Risk Assessment and Monitoring System (PRAMS) survey, 2000-2003. The PRAMS data were geocoded to 2000 U.S. Census data to create a multilevel data structure. We used a multilevel regression analysis (SAS PROC GLIMMIX) to estimate odds ratios (OR) and corresponding 95% confidence intervals (CI). In multivariable logistic regression models, high poverty, predominantly African American neighborhoods, upper quartiles of low education, and second quartile of neighborhood household crowding were significantly associated with LBW. However, only mothers resident in predominantly African American Census tract areas were statistically significantly at an increased risk of delivering preterm (OR 2.2, 95% CI 1.29-3.78). In addition, mothers resident in medium poverty neighborhoods remained modestly associated with smoking after adjustment for maternal-level covariates. The results also indicated that maternal smoking has more consistent effects on LBW than preterm births, particularly for mothers living in deprived neighborhoods. Interventions seeking to improve maternal and child health by reducing smoking during pregnancy need to engage specific community factors that encourage maternal quitting behaviors and reduce smoking relapse rates. Inclusion of maternal-level covariates in neighborhood models without careful consideration of the causal pathway might produce misleading interpretation of the results.

The importance of contextual, relational and cognitive factors for novice nurses' emotional state and affective commitment to the profession. A multilevel study.

PubMed

Hoeve, Yvonne Ten; Brouwer, Jasperina; Roodbol, Petrie F; Kunnen, Saskia

2018-05-13

This study explored the effects of contextual, relational and cognitive factors derived from novice nurses' work experiences on emotions and affective commitment to the profession. With an increasing demand for well-trained nurses, it is imperative to investigate which work-related factors most affect their commitment to develop effective strategies to improve work conditions, work satisfaction and emotional attachment. A repeated-measures within subjects design. From September 2013 - September 2014 eighteen novice nurses described work-related experiences in unstructured diaries and scored their emotional state and affective commitment on a scale. The themes that emerged from the 18 diaries (with 580 diary entries) were quantified as contextual, relational and cognitive factors. Contextual factors refer to complexity of care and existential events; relational factors to experiences with patients, support from colleagues, supervisors and physicians; cognitive factors to nurses' perceived competence. The first multilevel regression analysis, based on the 18 diaries with 580 entries, showed that complexity of care, lack of support and lack of competence were negatively related to novice nurses' affective commitment, whereas received support was positively related. The next multilevel regression analyses showed that all contextual, relational and cognitive factors were either related to negative or positive emotions. To retain novice nurses in the profession, it is important to provide support and feedback. This enables novice nurses to deal with the complexity of care and feelings of incompetence and to develop a professional commitment. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Neck/upper back and low back pain in parents and their adult offspring: Family linkage data from the Norwegian HUNT Study.

PubMed

Lier, R; Nilsen, T I L; Vasseljen, O; Mork, P J

2015-07-01

Chronic pain in the neck and low back is highly prevalent. Although heritable components have been identified, knowledge about generational transmission of spinal pain between parents and their adult offspring is sparse. This study examined the intergenerational association of spinal pain using data from 11,081 parent-offspring trios participating in the population-based HUNT Study in Norway. Logistic regression was used to calculate adjusted odds ratios (ORs) with 95% confidence intervals (CIs) for offspring spinal pain associated with parental spinal pain. In total, 3654 (33%) offspring reported spinal pain at participation. Maternal and paternal spinal pain was consistently associated with higher ORs for offspring spinal pain. The results suggest a slightly stronger association for parental multilevel spinal pain (i.e., both neck/upper back pain and low back pain) than for pain localized to the neck/upper back or low back. Multilevel spinal pain in both parents was associated with ORs of 2.6 (95% CI, 2.1-3.3), 2.4 (95% CI, 1.9-3.1) and 3.1 (95% CI, 2.2-4.4) for offspring neck/upper back, low back and multilevel spinal pain, respectively. Parental chronic spinal pain was consistently associated with increased occurrence of chronic spinal pain in their adult offspring, and this association was particularly strong for multilevel spinal pain. © 2014 European Pain Federation - EFIC®

Relations of alpine plant communities across environmental gradients: Multilevel versus multiscale analyses

USGS Publications Warehouse

Malanson, George P.; Zimmerman, Dale L.; Kinney, Mitch; Fagre, Daniel B.

2017-01-01

Alpine plant communities vary, and their environmental covariates could influence their response to climate change. A single multilevel model of how alpine plant community composition is determined by hierarchical relations is compared to a separate examination of those relations at different scales. Nonmetric multidimensional scaling of species cover for plots in four regions across the Rocky Mountains created dependent variables. Climate variables are derived for the four regions from interpolated data. Plot environmental variables are measured directly and the presence of thirty-seven site characteristics is recorded and used to create additional independent variables. Multilevel and best subsets regressions are used to determine the strength of the hypothesized relations. The ordinations indicate structure in the assembly of plant communities. The multilevel analyses, although revealing significant relations, provide little explanation; of the site variables, those related to site microclimate are most important. In multiscale analyses (whole and separate regions), different variables are better explanations within the different regions. This result indicates weak environmental niche control of community composition. The weak relations of the structure in the patterns of species association to the environment indicates that either alpine vegetation represents a case of the neutral theory of biogeography being a valid explanation or that it represents disequilibrium conditions. The implications of neutral theory and disequilibrium explanations are similar: Response to climate change will be difficult to quantify above equilibrium background turnover.

Development and Validation of a Multidimensional Measure of Family Supportive Supervisor Behaviors (FSSB)

PubMed Central

Hammer, Leslie B.; Kossek, Ellen Ernst; Yragui, Nanette L.; Bodner, Todd E.; Hanson, Ginger C.

2011-01-01

Due to growing work-family demands, supervisors need to effectively exhibit family supportive supervisor behaviors (FSSB). Drawing on social support theory and using data from two samples of lower wage workers, the authors develop and validate a measure of FSSB, defined as behaviors exhibited by supervisors that are supportive of families. FSSB is conceptualized as a multidimensional superordinate construct with four subordinate dimensions: emotional support, instrumental support, role modeling behaviors, and creative work-family management. Results from multilevel confirmatory factor analyses and multilevel regression analyses provide evidence of construct, criterion-related, and incremental validity. The authors found FSSB to be significantly related to work-family conflict, work-family positive spillover, job satisfaction, and turnover intentions over and above measures of general supervisor support. PMID:21660254

A dynamic multi-level optimal design method with embedded finite-element modeling for power transformers

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.

Hospitalization of Nursing Home Residents with Cognitive Impairments: The Influence of Organizational Features and State Policies

ERIC Educational Resources Information Center

Gruneir, Andrea; Miller, Susan C.; Intrator, Orna; Mor, Vincent

2007-01-01

Purpose: The purpose of this study was to quantify the effect of specific nursing home features and state Medicaid policies on the risk of hospitalization among cognitively impaired nursing home residents. Design and Methods: We used multilevel logistic regression to estimate the odds of hospitalization among long-stay (greater than 90 days)…

Implications of Interactions among Society, Education and Technology: A Comparison of Multiple Linear Regression and Multilevel Modeling in Mathematics Achievement Analyses

ERIC Educational Resources Information Center

Deering, Pamela Rose

2014-01-01

This research compares and contrasts two approaches to predictive analysis of three years' of school district data to investigate relationships between student and teacher characteristics and math achievement as measured by the state-mandated Maryland School Assessment mathematics exam. The sample for the study consisted of 3,514 students taught…

Exploring the Ups and Downs of Mathematics Engagement in the Middle Years of School

ERIC Educational Resources Information Center

Martin, Andrew J.; Way, Jennifer; Bobis, Janette; Anderson, Judy

2015-01-01

This study of 1,601 students in the middle years of schooling (Grades 5-8, each student measured twice, 1 year apart) from 200 classrooms in 44 schools sought to identify factors explaining gains and declines in mathematics engagement at key transition points. In multilevel regression modeling, findings showed that compared with Grade 6 students…

The Contribution of Organized Youth Sport to Antisocial and Prosocial Behavior in Adolescent Athletes

ERIC Educational Resources Information Center

Rutten, Esther A.; Stams, Geert Jan J. M.; Biesta, Gert J. J.; Schuengel, Carlo; Dirks, Evelien; Hoeksma, Jan B.

2007-01-01

In this study, we investigated the contribution of organized youth sport to antisocial and prosocial behavior in adolescent athletes. The sample consisted of N = 260 male and female soccer players and competitive swimmers, 12 to 18 years of age. Multilevel regression analysis revealed that 8% of the variance in antisocial behavior and 7% of the…

A Comparison of Individual-Level and Community-Level Predictors of Marijuana and Cocaine Use among a Sample of Newly Arrested Juvenile Offenders

ERIC Educational Resources Information Center

Childs, Kristina; Dembo, Richard; Belenko, Steven; Wareham, Jennifer; Schmeidler, James

2011-01-01

Variations in drug use have been found across individual-level factors and community characteristics, and by type of drug used. Relatively little research, however, has examined this variation among juvenile offenders. Based on a sample of 924 newly arrested juvenile offenders, two multilevel logistic regression models predicting marijuana test…

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

Addictive Internet Use among Korean Adolescents: A National Survey

PubMed Central

Heo, Jongho; Oh, Juhwan; Subramanian, S. V.; Kim, Yoon; Kawachi, Ichiro

2014-01-01

Background A psychological disorder called ‘Internet addiction’ has newly emerged along with a dramatic increase of worldwide Internet use. However, few studies have used population-level samples nor taken into account contextual factors on Internet addiction. Methods and Findings We identified 57,857 middle and high school students (13–18 year olds) from a Korean nationally representative survey, which was surveyed in 2009. To identify associated factors with addictive Internet use, two-level multilevel regression models were fitted with individual-level responses (1st level) nested within schools (2nd level) to estimate associations of individual and school characteristics simultaneously. Gender differences of addictive Internet use were estimated with the regression model stratified by gender. Significant associations were found between addictive Internet use and school grade, parental education, alcohol use, tobacco use, and substance use. Female students in girls' schools were more likely to use Internet addictively than those in coeducational schools. Our results also revealed significant gender differences of addictive Internet use in its associated individual- and school-level factors. Conclusions Our results suggest that multilevel risk factors along with gender differences should be considered to protect adolescents from addictive Internet use. PMID:24505318

Alcohol use among university students: Considering a positive deviance approach.

PubMed

Tucker, Maryanne; Harris, Gregory E

2016-09-01

Harmful alcohol consumption among university students continues to be a significant issue. This study examined whether variables identified in the positive deviance literature would predict responsible alcohol consumption among university students. Surveyed students were categorized into three groups: abstainers, responsible drinkers and binge drinkers. Multinomial logistic regression modelling was significant (χ(2) = 274.49, degrees of freedom = 24, p < .001), with several variables predicting group membership. While the model classification accuracy rate (i.e. 71.2%) exceeded the proportional by chance accuracy rate (i.e. 38.4%), providing further support for the model, the model itself best predicted binge drinker membership over the other two groups. © The Author(s) 2015.

A Typology of Violence against Self and Others and Its Associations with Drinking and Other Drug Use among High School Students in a U.S. General Population Survey

PubMed Central

Harford, Thomas C.; Yi, Hsiao-ye; Freeman, Robert C.

2015-01-01

This study examined associations between binge drinking and other substance use and perpetration of violence against self and others. Data were pooled from the 2003, 2005, and was constructed to reflect four categories of behaviors: other-directed violence only, self-directed violence only, combined other- and self-directed violence, and no violence. Results from multinomial logistic regressions show that the frequency of binge drinking and other substance use were significant risk factors for each of the violence categories relative to no-violence. However, the strengths of these associations varied across the violence categories. PMID:26478688

Dietary and exercise change following acute cardiac syndrome onset: A latent class growth modelling analysis.

PubMed

Bennett, Paul; Gruszczynska, Ewa; Marke, Victoria

2016-10-01

The present study aim determine sub-group trajectories of change on measures of diet and exercise following acute coronary syndrome. 150 participants were assessed in hospital, 1 month and 6 months subsequently on measures including physical activity, diet, illness beliefs, coping and mood. Change trajectories were measured using latent class growth modelling. Multinomial logistic regression was used to predict class membership. These analyses revealed changes in exercise were confined to a sub-group of participants already reporting relatively high exercise levels; those eating less healthily evidenced modest dietary improvements. Coping, gender, depression and perceived control predicted group membership to a modest degree. © The Author(s) 2015.

Poverty and Material Hardship in Grandparent-Headed Households.

PubMed

Baker, Lindsey A; Mutchler, Jan E

2010-08-01

Using the 2001 Survey of Income and Program Participation, the current study examines poverty and material hardship among children living in 3-generation (n = 486), skipped-generation (n = 238), single-parent (n = 2,076), and 2-parent (n = 6,061) households. Multinomial and logistic regression models indicated that children living in grandparent-headed households experience elevated risk of health insecurity (as measured by receipt of public insurance and uninsurance)-a disproportionate risk given rates of poverty within those households. Children living with single parents did not share this substantial risk. Risk of food and housing insecurity did not differ significantly from 2-parent households once characteristics of the household and caregivers were taken into account.

Multinomial mixture model with heterogeneous classification probabilities

USGS Publications Warehouse

Holland, M.D.; Gray, B.R.

2011-01-01

Royle and Link (Ecology 86(9):2505-2512, 2005) proposed an analytical method that allowed estimation of multinomial distribution parameters and classification probabilities from categorical data measured with error. While useful, we demonstrate algebraically and by simulations that this method yields biased multinomial parameter estimates when the probabilities of correct category classifications vary among sampling units. We address this shortcoming by treating these probabilities as logit-normal random variables within a Bayesian framework. We use Markov chain Monte Carlo to compute Bayes estimates from a simulated sample from the posterior distribution. Based on simulations, this elaborated Royle-Link model yields nearly unbiased estimates of multinomial and correct classification probability estimates when classification probabilities are allowed to vary according to the normal distribution on the logit scale or according to the Beta distribution. The method is illustrated using categorical submersed aquatic vegetation data. ?? 2010 Springer Science+Business Media, LLC.

High depressive symptomatology among older community-dwelling Mexican Americans: the impact of immigration.

PubMed

Gerst, Kerstin; Al-Ghatrif, Majd; Beard, Holly A; Samper-Ternent, Rafael; Markides, Kyriakos S

2010-04-01

This analysis explores nativity differences in depressive symptoms among very old (75+) community-dwelling Mexican Americans. Cross-sectional analysis using the fifth wave (2004-2005) of the Hispanic Established Population for the Epidemiological Study of the Elderly (Hispanic EPESE). The sample consisted of 1699 non-institutionalized Mexican American men and women aged 75 years and above. Depressive symptoms were measured by the Center for Epidemiological Studies Depression Scale (CES-D). Logistic regression was used to predict high depressive symptoms (CES-D score 16 or higher) and multinomial logistic regression was used to predict sub-threshold, moderate, and high depressive symptoms. Results showed that elders born in Mexico had higher odds of more depressive symptoms compared to otherwise similar Mexican Americans born in the US. Age of arrival, gender, and other covariates did not modify that risk. The findings suggest that older Mexican American immigrants are at higher risk of depressive symptomatology compared to persons born in the US, which has significant implications for research, policy, and clinical practice.

Characteristics in the first vaginal birth and their association with mode of delivery in the subsequent birth.

PubMed

Chen, Jian Sheng; Ford, Jane B; Ampt, Amanda; Simpson, Judy M; Roberts, Christine L

2013-03-01

The extent to which complications or adverse outcomes in a first vaginal birth may contribute to mode of delivery in the next birth remains unclear. This study examines the impact of the first birth on subsequent mode of delivery. The study population included women with a first vaginal birth and a consecutive second birth. Data were obtained from linked birth and hospital records for the state of New South Wales, Australia 2000-09. The primary outcome was the mode of delivery for the second birth. Planned caesarean was modelled using logistic regression; intrapartum caesarean and instrumental delivery were modelled using multinomial logistic regression. Of the 114 287 second births, 4.2% were planned caesarean, 3.0% were intrapartum caesarean and 4.8% were instrumental deliveries. Adjusted risk factors from the first birth for a planned second birth caesarean were third to fourth degree tear [odds ratio (OR) = 5.0 [95% confidence interval (CI) 4.6, 5.4

Cognitive overload? An exploration of the potential impact of cognitive functioning in discrete choice experiments with older people in health care.

PubMed

Milte, Rachel; Ratcliffe, Julie; Chen, Gang; Lancsar, Emily; Miller, Michelle; Crotty, Maria

2014-07-01

This exploratory study sought to investigate the effect of cognitive functioning on the consistency of individual responses to a discrete choice experiment (DCE) study conducted exclusively with older people. A DCE to investigate preferences for multidisciplinary rehabilitation was administered to a consenting sample of older patients (aged 65 years and older) after surgery to repair a fractured hip (N = 84). Conditional logit, mixed logit, heteroscedastic conditional logit, and generalized multinomial logit regression models were used to analyze the DCE data and to explore the relationship between the level of cognitive functioning (specifically the absence or presence of mild cognitive impairment as assessed by the Mini-Mental State Examination) and preference and scale heterogeneity. Both the heteroscedastic conditional logit and generalized multinomial logit models indicated that the presence of mild cognitive impairment did not have a significant effect on the consistency of responses to the DCE. This study provides important preliminary evidence relating to the effect of mild cognitive impairment on DCE responses for older people. It is important that further research be conducted in larger samples and more diverse populations to further substantiate the findings from this exploratory study and to assess the practicality and validity of the DCE approach with populations of older people. Copyright © 2014 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Exploratory multinomial logit model-based driver injury severity analyses for teenage and adult drivers in intersection-related crashes.

PubMed

Wu, Qiong; Zhang, Guohui; Ci, Yusheng; Wu, Lina; Tarefder, Rafiqul A; Alcántara, Adélamar Dely

2016-05-18

Teenage drivers are more likely to be involved in severely incapacitating and fatal crashes compared to adult drivers. Moreover, because two thirds of urban vehicle miles traveled are on signal-controlled roadways, significant research efforts are needed to investigate intersection-related teenage driver injury severities and their contributing factors in terms of driver behavior, vehicle-infrastructure interactions, environmental characteristics, roadway geometric features, and traffic compositions. Therefore, this study aims to explore the characteristic differences between teenage and adult drivers in intersection-related crashes, identify the significant contributing attributes, and analyze their impacts on driver injury severities. Using crash data collected in New Mexico from 2010 to 2011, 2 multinomial logit regression models were developed to analyze injury severities for teenage and adult drivers, respectively. Elasticity analyses and transferability tests were conducted to better understand the quantitative impacts of these factors and the teenage driver injury severity model's generality. The results showed that although many of the same contributing factors were found to be significant in the both teenage and adult driver models, certain different attributes must be distinguished to specifically develop effective safety solutions for the 2 driver groups. The research findings are helpful to better understand teenage crash uniqueness and develop cost-effective solutions to reduce intersection-related teenage injury severities and facilitate driver injury mitigation research.

Trauma cognitions are related to symptoms up to 10 years after cognitive behavioral treatment for posttraumatic stress disorder.

PubMed

Scher, Christine D; Suvak, Michael K; Resick, Patricia A

2017-11-01

This study examined (a) relationships between trauma-related cognitions and posttraumatic stress disorder (PTSD) symptoms from pretreatment through a long-term period after cognitive-behavioral therapy (CBT) for PTSD and (b) whether these relationships were impacted by treatment type. Participants were 171 women randomized into treatment for PTSD after rape. Measures of self-reported trauma-related cognitions and interviewer-assessed PTSD symptoms (i.e., Posttraumatic Maladaptive Beliefs Scale, Trauma-Related Guilt Inventory, and Clinician-Administered PTSD Scale) were obtained at pretreatment, posttreatment, and 3-month, 9-month, and 5-10 year follow-ups. Multilevel regression analyses were used to examine relationships between trauma-related cognitions and PTSD symptoms throughout the study period and whether these relationships differed as a function of treatment type (i.e., Cognitive Processing Therapy or Prolonged Exposure). Initial multilevel regression analyses that examined mean within-participant associations suggested that beliefs regarding Reliability and Trustworthiness of Others, Self-Worth and Judgment, Threat of Harm, and Guilt were related to PTSD symptoms throughout follow-up. Growth curve modeling suggested that patterns of belief change throughout follow-up were similar to those previously observed in PTSD symptoms over the same time period. Finally, multilevel mediation analyses that incorporated time further suggested that change in beliefs was related to change in symptoms throughout follow-up. With 1 minor exception, relationships between beliefs and symptoms were not moderated by treatment type. These data suggest that trauma-related cognitions are a potential mechanism for long-term maintenance of treatment gains after CBT for PTSD. Moreover, these cognitions may be a common, rather than specific, treatment maintenance mechanism. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Ideal cardiovascular health and inflammation in European adolescents: The HELENA study.

PubMed

González-Gil, E M; Santabárbara, J; Ruiz, J R; Bel-Serrat, S; Huybrechts, I; Pedrero-Chamizo, R; de la O, A; Gottrand, F; Kafatos, A; Widhalm, K; Manios, Y; Molnar, D; De Henauw, S; Plada, M; Ferrari, M; Palacios Le Blé, G; Siani, A; González-Gross, M; Gómez-Martínez, S; Marcos, A; Moreno Aznar, L A

2017-05-01

Inflammation plays a key role in atherosclerosis and this process seems to appear in childhood. The ideal cardiovascular health index (ICHI) has been inversely related to atherosclerotic plaque in adults. However, evidence regarding inflammation and ICHI in adolescents is scarce. The aim is to assess the association between ICHI and inflammation in European adolescents. As many as 543 adolescents (251 boys and 292 girls) from the Healthy Lifestyle in Europe by Nutrition in Adolescence (HELENA) study, a cross-sectional multi-center study including 9 European countries, were measured. C-reactive protein (CRP), complement factors C3 and C4, leptin and white blood cell counts were used to compute an inflammatory score. Multilevel linear models and multilevel logistic regression were used to assess the association between ICHI and inflammation controlling by covariates. Higher ICHI was associated with a lower inflammatory score, as well as with several individual components, both in boys and girls (p < 0.01). In addition, adolescents with at least 4 ideal components of the ICHI had significantly lower inflammatory score and lower levels of the study biomarkers, except CRP. Finally, the multilevel logistic regression showed that for every unit increase in the ICHI, the probability of having an inflammatory profile decreased by 28.1% in girls. Results from this study suggest that a better ICHI is associated with a lower inflammatory profile already in adolescence. Improving these health behaviors, and health factors included in the ICHI, could play an important role in CVD prevention. Copyright © 2016 The Italian Society of Diabetology, the Italian Society for the Study of Atherosclerosis, the Italian Society of Human Nutrition, and the Department of Clinical Medicine and Surgery, Federico II University. Published by Elsevier B.V. All rights reserved.

High Maternal Body Mass Index Is Associated with an Early-Onset of Overweight/Obesity in Pre-School-Aged Children in Malawi. A Multilevel Analysis of the 2015-16 Malawi Demographic and Health Survey.

PubMed

Ntenda, Peter Austin Morton; Mhone, Thomas Gabriel; Nkoka, Owen

2018-05-25

Overweight/obesity in young children is one of the most serious public health issues globally. We examined whether individual- and community-level maternal nutritional status is associated with an early onset of overweight/obesity in pre-school-aged children in Malawi. Data were obtained from the 2015-16 Malawi Demographic and Health Survey (MDHS). The maternal nutritional status as body mass index and childhood overweight/obesity status was assessed by using the World Health Organization (WHO) recommendations. To examine whether the maternal nutritional status is associated with overweight/obesity in pre-school-aged children, two-level multilevel logistic regression models were constructed on 4023 children of age less than five years dwelling in 850 different communities. The multilevel regression analysis showed that children born to overweight/obese mothers had increased odds of being overweight/obese [adjusted odds ratio (aOR) = 3.11; 95% confidence interval (CI): 1.13-8.54]. At the community level, children born to mothers from the middle (aOR: 1.68; 95% CI: 1.02-2.78) and high (aOR: 1.69; 95% CI: 1.00-2.90) percentage of overweight/obese women had increased odds of being overweight/obese. In addition, there were significant variations in the odds of childhood overweight/obesity in the communities. Strategies aimed at reducing childhood overweight/obesity in Malawi should address not only women and their children but also their communities. Appropriate choices of nutrition, diet and physical activity patterns should be emphasized upon in overweight/obese women of childbearing age throughout pregnancy and beyond.

Anthropometry and blood pressure changes in a Caribbean adolescent population of African ancestry: an evaluation of longitudinal data using a multilevel mixed regression approach.

PubMed

Nichols, S; Cadogan, F

2012-10-01

The aim of this study was to determine the effect of growth pattern on blood pressure changes in an adolescent population of African ancestry based on longitudinal data and to compare this with estimates derived from cross-sectional data. Participants had measurements of weight, height, blood pressure and percentage body fat taken annually using standardized procedures. Annual blood pressure and anthropometry velocities as well as one- and three-year interval gender specific tracking coefficients were computed. We investigated whether changes in blood pressure could be explained by measures of growth using a multilevel mixed regression approach. The results showed that systolic blood pressure (SBP) increased by 1.27 and 3.09 mmHg per year among females and males, respectively. Similarly, diastolic blood pressure (DBP) increased by 1.16 and 1.92 mmHg per year among females and males, respectively. Multilevel analyses suggested that weight, body mass index, percentage body fat and height were the strongest anthropometric determinants of blood pressure change in this population. The results also suggest that there are gender differences in the relative importance of these anthropometric measures with height playing a minor role in predicting blood pressure changes among adolescent females. With the exception of DBP at 18 years among females, there were no significant differences between mean blood pressure generated from cross-sectional and longitudinal data by age in both males and females. Anthropometric measures are important covariates of age-related blood pressure changes and cross-sectional data may provide a more cost-effective and useful proxy for generating age-related blood pressure estimates in this population.

[Nursing Workforce Characteristics and Control of Diabetes Mellitus in Primary Care: a Multilevel Analysis].

PubMed

Parro Moreno, Ana; Santiago Pérez, M Isolina; Abraira Santos, Victor; Aréjula Torres, José Luis Aréjula Torres; Díaz Holgado, Antonio; Gandarillas Grande, Ana; Morales Asencio, José Miguel; Serrano Gallardo, Pilar

2016-03-04

Nurse activity is determined by the characteristics of nursing staff. The objective was to determine the impact of Primary Health Care (PHC) nursing workforce characteristics on the control of Diabetes Mellitus (DM) in adults. Cross-sectional analytical study. Administrative and clinical registries and questionnaire PES-Nursing Work Index from PHC nurses. Participants 44.214 diabetic patients in two health zones within the Community of Madrid, North-West Zone (NWZ) with higher socioeconomic situation and South-West Zone (SWZ) with lower socioeconomic situation, and their 507 reference nurses. Analyses were performed to multivariate multilevel logistic regression models. Poor DM control (figures equal or higher than 7% HbA1c). The prevalence of poor DM control was 40.1% [CI95%: 38.2-42.1]. There was a risk of 25% more of poor control if the patient changed centre and of 27% if changed of doctor-nurse pair. In the multilevel multivariate regression models: in SWZ increasing the ratio of patients over 65 years per nurse increased the poor control (OR=1.00008 [CI95%:1.00006-1.001]); and higher proportion of patients whose Hb1Ac was not measured at the centre contributed to poor DM control (OR=5.1 [CI95%:1.6-15.6]). In two models for health zone, the economic immigration condition increased poor control, in SWZ (OR=1.3 [CI95%:1.03-1.7]); and in NWZ (OR=1.29 [CI95%:1.03-1.6]). Higher 65 years old patients ratio per nurse, economic immigration condition and a higher proportion of patients whose Hb1Ac was not measured contribute to worse DM control.

Adolescents' psychological health complaints and the economic recession in late 2007: a multilevel study in 31 countries.

PubMed

Pfoertner, Timo-Kolja; Rathmann, Katharina; Elgar, Frank J; de Looze, Margaretha; Hofmann, Felix; Ottova-Jordan, Veronika; Ravens-Sieberer, Ulrike; Bosakova, Lucia; Currie, Candace; Richter, Matthias

2014-12-01

The recent economic recession, which began in 2007, has had a detrimental effect on the health of the adult population, but no study yet has investigated the impact of this downturn on adolescent health. This article uniquely examines the effect of the crisis on adolescents' psychological health complaints in a cross-national comparison. Data came from the World Health Organization collaborative 'Health Behaviour in School-aged Children' study in 2005-06 and 2009-10. We measured change in psychological health complaints from before to during the recession in the context of changing adult and adolescent unemployment rates. Furthermore, we used logistic multilevel regression to model the impact of absolute unemployment in 2010 and its change rate between 2005-06 and 2009-10 on adolescents' psychological health complaints in 2010. Descriptive results showed that although youth and adult unemployment has increased during the economic crisis, rates of psychological health complaints among adolescents were unaffected in some countries and even decreased in others. Multilevel regression models support this finding and reveal that only youth unemployment in 2010 increased the likelihood of psychological health complaints, whereas its change rate in light of the recession as well as adult unemployment did not relate to levels of psychological health complaints. In contrast to recent findings, our study indicates that the negative shift of the recent recession on the employment market in several countries has not affected adolescents' psychological health complaints. Adolescents' well-being instead seems to be influenced by the current situation on the labour market that shapes their occupational outlook. © The Author 2014. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Cross-national differences in the gender gap in subjective health in Europe: does country-level gender equality matter?

PubMed

Dahlin, Johanna; Härkönen, Juho

2013-12-01

Multiple studies have found that women report being in worse health despite living longer. Gender gaps vary cross-nationally, but relatively little is known about the causes of comparative differences. Existing literature is inconclusive as to whether gender gaps in health are smaller in more gender equal societies. We analyze gender gaps in self-rated health (SRH) and limiting longstanding illness (LLI) with five waves of European Social Survey data for 191,104 respondents from 28 countries. We use means, odds ratios, logistic regressions, and multilevel random slopes logistic regressions. Gender gaps in subjective health vary visibly across Europe. In many countries (especially in Eastern and Southern Europe), women report distinctly worse health, while in others (such as Estonia, Finland, and Great Britain) there are small or no differences. Logistic regressions ran separately for each country revealed that individual-level socioeconomic and demographic variables explain a majority of these gaps in some countries, but contribute little to their understanding in most countries. In yet other countries, men had worse health when these variables were controlled for. Cross-national variation in the gender gaps exists after accounting for individual-level factors. Against expectations, the remaining gaps are not systematically related to societal-level gender inequality in the multilevel analyses. Our findings stress persistent cross-national variability in gender gaps in health and call for further analysis. Copyright © 2013 Elsevier Ltd. All rights reserved.

Contributions of sociodemographic factors to criminal behavior

PubMed Central

Mundia, Lawrence; Matzin, Rohani; Mahalle, Salwa; Hamid, Malai Hayati; Osman, Ratna Suriani

2016-01-01

We explored the extent to which prisoner sociodemographic variables (age, education, marital status, employment, and whether their parents were married or not) influenced offending in 64 randomly selected Brunei inmates, comprising both sexes. A quantitative field survey design ideal for the type of participants used in a prison context was employed to investigate the problem. Hierarchical multiple regression analysis with backward elimination identified prisoner marital status and age groups as significantly related to offending. Furthermore, hierarchical multinomial logistic regression analysis with backward elimination indicated that prisoners’ age, primary level education, marital status, employment status, and parental marital status as significantly related to stealing offenses with high odds ratios. All 29 nonrecidivists were false negatives and predicted to reoffend upon release. Similarly, all 33 recidivists were projected to reoffend after release. Hierarchical binary logistic regression analysis revealed age groups (24–29 years and 30–35 years), employed prisoner, and primary level education as variables with high likelihood trends for reoffending. The results suggested that prisoner interventions (educational, counseling, and psychotherapy) in Brunei should treat not only antisocial personality, psychopathy, and mental health problems but also sociodemographic factors. The study generated offending patterns, trends, and norms that may inform subsequent investigations on Brunei prisoners. PMID:27382342

Clinical, biomarker, and genetic predictors of specific types of atrial fibrillation in a community-based cohort: data of the PREVEND study.

PubMed

Hobbelt, Anne H; Siland, Joylene E; Geelhoed, Bastiaan; Van Der Harst, Pim; Hillege, Hans L; Van Gelder, Isabelle C; Rienstra, Michiel

2017-02-01

Atrial fibrillation (AF) may present variously in time, and AF may progress from self-terminating to non-self-terminating AF, and is associated with impaired prognosis. However, predictors of AF types are largely unexplored. We investigate the clinical, biomarker, and genetic predictors of development of specific types of AF in a community-based cohort. We included 8042 individuals (319 with incident AF) of the PREVEND study. Types of AF were compared, and multivariate multinomial regression analysis determined associations with specific types of AF. Mean age was 48.5 ± 12.4 years and 50% were men. The types of incident AF were ascertained based on electrocardiograms; 103(32%) were classified as AF without 2-year recurrence, 158(50%) as self-terminating AF, and 58(18%) as non-self-terminating AF. With multivariate multinomial logistic regression analysis, advancing age (P< 0.001 for all three types) was associated with all AF types, male sex was associated with AF without 2-year recurrence and self-terminating AF (P= 0.031 and P= 0.008, respectively). Increasing body mass index and MR-proANP were associated with both self-terminating (P= 0.009 and P< 0.001) and non-self-terminating AF (P= 0.003 and P< 0.001). The only predictor associated with solely self-terminating AF is prescribed anti-hypertensive treatment (P= 0.019). The following predictors were associated with non-self-terminating AF; lower heart rate (P= 0.018), lipid-lowering treatment prescribed (P= 0.009), and eGFR <60 mL/min/1.73 m2 (P= 0.006). Three known AF-genetic variants (rs6666258, rs6817105, and rs10821415) were associated with self-terminating AF. We found clinical, biomarker and genetic predictors of specific types of incident AF in a community-based cohort. The genetic background seems to play a more important role than modifiable risk factors in self-terminating AF.

Associations between the home environment and children's sweet beverage consumption at 2-year follow-up: the 'Be active, eat right' study.

PubMed

van Grieken, A; Renders, C M; van de Gaar, V M; Hirasing, R A; Raat, H

2015-04-01

This study evaluates the association between home environmental characteristics and sweet beverage consumption (i.e. beverages that contain sugar) of 7-year-old children. The population for analysis consisted of n = 2047 parents and their children from the population-based 'Be active, eat right' study. Data on sociodemographic characteristics, parental beliefs, parenting practices and child's sweet beverage consumption were obtained by parental report with questionnaires. We performed linear and multinomial regression analyses evaluating associations between characteristics at age 5 years and (i) consumption at 7 years and (ii) consumption patterns between age 5 and 7 years with reference category 'low consumption'. Based on the report from their parents, 5-year-old children drank on average 3.0 (SD:1.4) sweet beverage per day. Children consumed less sweet beverages at age 7 years (beta -0.16, 95% confidence interval [CI] -0.24 to -0.09) when there were less sweet beverages available at home. The multinomial regression model showed that children with parents who discouraged sweet beverage consumption were more likely to decrease their sweet beverage consumption over the study period (odds ratio: 1.24, 95% CI 1.07 to 1.43). Moreover, when there were less sweet beverages available at home, children were less likely to increase their consumption or have a high consumption over the study period (odds ratio: 0.70, 95% CI 0.59 to 0.83 and 0.61, 95% CI 0.54 to 0.70, respectively). The results showed that characteristics of the home environment are associated with the consumption of sweet beverages among children. Specifically, the availability of sweet beverages at home is associated with the child's sweet beverage consumption. © 2014 The Authors. Pediatric Obesity © 2014 World Obesity.

Enzymatic Activity of Glutathione S-Transferase and Dental Fluorosis Among Children Receiving Two Different Levels of Naturally Fluoridated Water.

PubMed

Bonola-Gallardo, Irvin; Irigoyen-Camacho, María Esther; Vera-Robles, Liliana; Campero, Antonio; Gómez-Quiroz, Luis

2017-03-01

This study was conducted to measure the activity of the enzyme glutathione S-transferase (GST) in saliva and to compare the activity of this enzyme in children with and without dental fluorosis in communities with different concentrations of naturally fluoridated water. A total of 141 schoolchildren participated in this cross-sectional study. Children were selected from two communities: one with a low (0.4 ppm) and the other with a high (1.8 ppm) water fluoride concentration. Dental fluorosis was evaluated by applying the Thylstrup and Fejerskov Index (TFI) criteria. Stimulated saliva was obtained, and fluoride concentration and GST activity were measured. The GST activity was compared among children with different levels of dental fluorosis using multinomial logistic regression models and odds ratios (OR). The mean age of the children was 10.6 (±1.03) years. Approximately half of the children showed dental fluorosis (52.5 %). The average GST activity was 0.5678 (±0.1959) nmol/min/μg. A higher concentration of fluoride in the saliva was detected in children with a higher GST activity (p = 0.039). A multinomial logistic regression model used to evaluate the GST activity and the dental fluorosis score identified a strong association between TFI = 2-3 (OR = 15.44, p = 0.007) and TFI ≥ 4 (OR = 55.40, p = 0.026) and the GST activity level, compared with children showing TFI = 0-1, adjusted for age and sex. Schoolchildren with higher levels of dental fluorosis and a higher fluoride concentration in the saliva showed greater GST activity. The increased GST activity most likely was the result of the body's need to inactivate free radicals produced by exposure to fluoride.

Help-seeking in people with exceptional experiences: results from a general population sample.

PubMed

Landolt, Karin; Wittwer, Amrei; Wyss, Thomas; Unterassner, Lui; Fach, Wolfgang; Krummenacher, Peter; Brugger, Peter; Haker, Helene; Kawohl, Wolfram; Schubiger, Pius August; Folkers, Gerd; Rössler, Wulf

2014-01-01

Exceptional experiences (EE) are experiences that deviate from ordinary experiences, for example precognition, supernatural appearances, or déjà vues. In spite of the high frequency of EE in the general population, little is known about their effect on mental health and about the way people cope with EE. This study aimed to assess the quality and quantity of EE in persons from the Swiss general population, to identify the predictors of their help-seeking, and to determine how many of them approach the mental health system. An on-line survey was used to evaluate a quota sample of 1580 persons representing the Swiss general population with respect to gender, age, and level of education. Multinomial logistic regression was applied to integrate help-seeking, self-reported mental disorder, and other variables in a statistical model designed to identify predictors of help-seeking in persons with EE. Almost all participants (91%) experienced at least one EE. Generally, help-seeking was more frequent when the EE were of negative valence. Help-seeking because of EE was less frequent in persons without a self-reported mental disorder (8.6%) than in persons with a disorder (35.1%) (OR = 5.7). Even when frequency and attributes of EE were controlled for, people without a disorder sought four times less often help because of EE than expected. Persons with a self-reported diagnosis of mental disorder preferred seeing a mental health professional. Multinomial regression revealed a preference for healers in women with less education, who described themselves as believing and also having had more impressive EE. Persons with EE who do not indicate a mental disorder less often sought help because of EE than persons who indicated a mental disorder. We attribute this imbalance to a high inhibition threshold to seek professional help. Moreover, especially less educated women did not approach the mental health care system as often as other persons with EE, but preferred seeing a healer.

Can integrated health services delivery have an impact on hypertension management? A cross-sectional study in two cities of China.

PubMed

Li, Haitao; Sun, Ying; Qian, Dongfu

2016-11-30

Policy makers require information regarding performance of different primary care delivery models in managing hypertension, which can be helpful for better hypertension management. This study aims to compare continuity of care among hypertensive patients between Direct Management (DM) Model of community health centers (CHCs) in Wuhan and Loose Collaboration (LC) Model in Nanjing. A cross-sectional questionnaire survey was conducted. Four CHCs in each city were randomly selected as study settings. 386 patients in Nanjing and 396 in Wuhan completed face-to-face interview surveys and were included in the final analysis. The relational continuity and coordination continuity (including both information continuity and management continuity) were measured and analyzed. Binary or multinomial logistic regression models were used for comparison between the two cities. Participants from Nanjing had better relational continuity with primary care providers as compared with those from Wuhan, including more likely to be familiar with a CHC physician (OR = 2.762; 95%CI: 1.878 to 4.061), taken care of by the same CHC physician (OR = 1.846; 95%CI: 1.262 to 2.700), and known well by a CHC physician (OR = 1.762; 95%CI: 1.206 to 2.572). Multinomial logistic regression analyses showed there were significant differences between the two cities in reported frequency of communications between hospital and CHC physicians (P = 0.001), whether hospital and CHC physicians gave same treatment suggestions (P = 0.016), as well as how treatment strategy was formulated (P < 0.001). Participants in Wuhan were less likely than those in Nanjing to consider there was continuum regarding health services provided by hospital and CHC physicians (OR = 3.932; 95%CI: 2.394 to 6.459). Our study shows that continuity of care is better for LC Model in Nanjing than DM Model in Wuhan. Our study suggests there is room for improvement regarding relational and information continuity in both cities.

A site specific model and analysis of the neutral somatic mutation rate in whole-genome cancer data.

PubMed

Bertl, Johanna; Guo, Qianyun; Juul, Malene; Besenbacher, Søren; Nielsen, Morten Muhlig; Hornshøj, Henrik; Pedersen, Jakob Skou; Hobolth, Asger

2018-04-19

Detailed modelling of the neutral mutational process in cancer cells is crucial for identifying driver mutations and understanding the mutational mechanisms that act during cancer development. The neutral mutational process is very complex: whole-genome analyses have revealed that the mutation rate differs between cancer types, between patients and along the genome depending on the genetic and epigenetic context. Therefore, methods that predict the number of different types of mutations in regions or specific genomic elements must consider local genomic explanatory variables. A major drawback of most methods is the need to average the explanatory variables across the entire region or genomic element. This procedure is particularly problematic if the explanatory variable varies dramatically in the element under consideration. To take into account the fine scale of the explanatory variables, we model the probabilities of different types of mutations for each position in the genome by multinomial logistic regression. We analyse 505 cancer genomes from 14 different cancer types and compare the performance in predicting mutation rate for both regional based models and site-specific models. We show that for 1000 randomly selected genomic positions, the site-specific model predicts the mutation rate much better than regional based models. We use a forward selection procedure to identify the most important explanatory variables. The procedure identifies site-specific conservation (phyloP), replication timing, and expression level as the best predictors for the mutation rate. Finally, our model confirms and quantifies certain well-known mutational signatures. We find that our site-specific multinomial regression model outperforms the regional based models. The possibility of including genomic variables on different scales and patient specific variables makes it a versatile framework for studying different mutational mechanisms. Our model can serve as the neutral null model for the mutational process; regions that deviate from the null model are candidates for elements that drive cancer development.

An Assessment of Correlation between Dermatoglyphic Patterns and Sagittal Skeletal Discrepancies

PubMed Central

Philip, Biju; Madathody, Deepika; Mathew, Manu; Paul, Jose; Dlima, Johnson Prakash

2017-01-01

Introduction Investigators over years have been fascinated by dermatoglyphic patterns which has led to the development of dermatoglyphics as a science with numerous applications in various fields other than being the best and most widely used method for personal identification. Aim To assess the correlation between dermatoglyphic patterns and sagittal skeletal discrepancies. Materials and Methods A total of 180 patients, aged 18-40 years, were selected from those who attended the outpatient clinic of the Deparment of Orthodontics and Dentofacial Orthopedics, Mar Baselios Dental College, Kothamangalam, Kerala, India. The fingerprints of both hands were taken by ink and stamp method after proper hand washing. The patterns of arches, loops and whorls in fingerprints were assessed. The total ridge count was also evaluated. Data was also sent to the fingerprint experts for expert evaluation. The sagittal jaw relation was determined from the patient’s lateral cephalogram. The collected data was then statistically analyzed using Chi-square tests, ANOVA and Post-hoc tests and a Multinomial regression prediction was also done. Results A significant association was observed between the dermatoglyphic pattern exhibited by eight fingers and the sagittal skeletal discrepancies (p<0.05). An increased distribution of whorl pattern was observed in the skeletal Class II with maxillary excess group and skeletal Class II with mandibular deficiency group while an increased distribution of loop pattern was seen in the skeletal Class III with mandibular excess group and skeletal Class III with maxillary deficiency group. Higher mean of total ridge count was also seen in the groups of skeletal Class II with maxillary excess and skeletal Class II with mandibular deficiency. Multinomial regression predicting skeletal pattern with respect to the fingerprint pattern showed that the left thumb impression fits the best model for predicting the skeletal pattern. Conclusion There was a significant association between dermatoglyphic patterns and sagittal skeletal discrepancies. Dermatoglyphics could serve as a cost effective screening tool of these craniofacial problems. PMID:28511506

Determinants of postnatal care non-utilization among women in Nigeria.

PubMed

Somefun, Oluwaseyi Dolapo; Ibisomi, Latifat

2016-01-11

Although, there are several programs in place in Nigeria to ensure maternal and child health, maternal and neonatal mortality rates remain high with maternal mortality rates being 576/100,000 and neonatal mortality rates at 37/1000 live births (NDHS, 2013). While there are many studies on the utilization of maternal health services such as antenatal care and skilled delivery at birth, studies on postnatal care are limited. Therefore, the aim of this study is to examine the factors associated with the non-utilization of postnatal care among mothers in Nigeria using the Nigeria Demographic and Health Survey (NDHS) 2013. For analysis, the postnatal care uptake for 19,418 children born in the 5 years preceding the survey was considered. The dependent variable was a composite variable derived from a list of questions on postnatal care. A multinomial logistic regression model was applied to examine the adjusted and unadjusted determinants of non-utilization of postnatal care. Results from this study showed that 63% of the mothers of the 19,418 children did not utilize postnatal care services in the period examined. About 42% of the study population between 25 and 34 years did not utilize postnatal care and 61% of the women who did not utilize postnatal care had no education. Results from multinomial logistic regression show that antenatal care use, distance, education, place of delivery, region and wealth status are significantly associated with the non-utilization of postnatal care services. This study revealed the low uptake of postnatal care service in Nigeria. To increase mothers' utilization of postnatal care services and improve maternal and child health in Nigeria, interventions should be targeted at women in remote areas who don't have access to services and developing mobile clinics. In addition, it is crucial that steps should be taken on educating women. This would have a significant influence on their perceptions about the use of postnatal care services in Nigeria.

Does Smoke from Biomass Fuel Contribute to Anemia in Pregnant Women in Nagpur, India? A Cross-Sectional Study

PubMed Central

Page, Charlotte M.; Patel, Archana; Hibberd, Patricia L.

2015-01-01

Background Anemia affects upwards of 50% of pregnant women in developing countries and is associated with adverse outcomes for mother and child. We hypothesized that exposure to smoke from biomass fuel – which is widely used for household energy needs in resource-limited settings – could exacerbate anemia in pregnancy, possibly as a result of systemic inflammation. Objective To evaluate whether exposure to smoke from biomass fuel (wood, straw, crop residues, or dung) as opposed to clean fuel (electricity, liquefied petroleum gas, natural gas, or biogas) is an independent risk factor for anemia in pregnancy, classified by severity. Methods A secondary analysis was performed using data collected from a rural pregnancy cohort (N = 12,782) in Nagpur, India in 2011-2013 as part of the NIH-funded Maternal and Newborn Health Registry Study. Multinomial logistic regression was used to estimate the effect of biomass fuel vs. clean fuel use on anemia in pregnancy, controlling for maternal age, body mass index, education level, exposure to household tobacco smoke, parity, trimester when hemoglobin was measured, and receipt of prenatal iron and folate supplements. Results The prevalence of any anemia (hemoglobin < 11 g/dl) was 93% in biomass fuel users and 88% in clean fuel users. Moderate-to-severe anemia (hemoglobin < 10 g/dl) occurred in 53% and 40% of the women, respectively. Multinomial logistic regression showed higher relative risks of mild anemia in pregnancy (hemoglobin 10-11 g/dl; RRR = 1.38, 95% CI = 1.19-1.61) and of moderate-to-severe anemia in pregnancy (RRR = 1.79, 95% CI = 1.53-2.09) in biomass fuel vs. clean fuel users, after adjusting for covariates. Conclusion In our study population, exposure to biomass smoke was associated with higher risks of mild and moderate-to-severe anemia in pregnancy, independent of covariates. Trial Registration ClinicalTrials.gov NCT 01073475 PMID:26024473

Adrenal venous sampling in primary aldosteronism: multinomial regression modeling to detect aldosterone secretion lateralization when right adrenal sampling is missing.

PubMed

Durivage, Camille; Blanchette, Rémi; Soulez, Gilles; Chagnon, Miguel; Gilbert, Patrick; Giroux, Marie-France; Bourdeau, Isabelle; Oliva, Vincent L; Lacroix, André; Therasse, Eric

2017-02-01

Difficulty to recognize or canulate the right adrenal vein is the most frequent cause of adrenal venous sampling (AVS) failure. We aimed to assess multinomial regression modeling (MRM) of peripheral and left adrenal vein samplings to detect lateralization of aldosterone secretion when the right AVS is missing. Simultaneous bilateral AVS samplings were performed before (basal) and after intravenous cosyntropin injection in 188 consecutive patients between December 1989 and September 2015. Different reference standards for lateralization of aldosterone secretion were defined for basal and for postcosyntropin AVS and according to lateralization index cutoffs at least 2 and at least 4. MRMs were built to detect lateralization of aldosterone secretion according to these reference standards using only peripheral and left adrenal veins samplings (without the right AVS). Detection accuracy was assessed by the area under the receiver operating characteristic (AUROC) curves and detection sensitivities were reported for specificity at least 95%. For basal AVS with lateralization index at least 2, AUROC were respectively 0.931 [95% confidence interval (CI) 0.894-0.968] and 0.922 (95% CI 0.882-0.962) for right and left lateralization of aldosterone secretion detection and MRM could detect respectively 65.5 and 62.7% of the right and left lateralization of aldosterone secretion. For AVS after cosyntropin with lateralization index at least 4, AUROC were respectively 0.964 (95% CI: 0.940-0.987) and 0.955 (95% CI: 0.927-0.983) for right and left lateralization of aldosterone secretion, and MRM could detect respectively 77.2 and 72.9% of the right and left lateralization of aldosterone secretion. MRM can detect lateralization of aldosterone secretion without the right AVS in most patients and could eliminate the need for repeat AVS when right adrenal vein canulation is nonselective or impossible.

The Association between Adolescent Life Satisfaction, Family Structure, Family Affluence and Gender Differences in Parent-Child Communication

ERIC Educational Resources Information Center

Levin, Kate Ann; Dallago, Lorenza; Currie, Candace

2012-01-01

The study sought to examine young people's life satisfaction in the context of the family environment, using data from the 2006 HBSC: WHO-collaborative Study in Scotland (N = 5,126). Multilevel linear regression analyses were carried out for 11-, 13- and 15-year old boys and girls, with outcome measure ridit-transformed life satisfaction. The…

Smoking in young adolescents: an approach with multilevel discrete choice models

PubMed Central

Pinilla, J; Gonzalez, B; Barber, P; Santana, Y

2002-01-01

Design: Cross sectional analysis performed by multilevel logistic regression with pupils at the first level and schools at the second level. The data came from a stratified sample of students surveyed on their own, their families' and their friends' smoking habits, their schools, and their awareness of cigarette prices and advertising. Setting: The study was performed in the Island of Gran Canaria, Spain. Participants: 1877 students from 30 secondary schools in spring of 2000 (model's effective sample sizes 1697 and 1738) . Main results: 14.2% of the young teenagers surveyed use tobacco, almost half of them (6.3% of the total surveyed) on a daily basis. According to the ordered logistic regression model, to have a smoker as the best friend increases significantly the probability of smoking (odds ratio: 6.96, 95% confidence intervals (CI) (4.93 to 9.84), and the same stands for one smoker living at home compared with a smoking free home (odds ratio: 2.03, 95% CI 1.22 to 3.36). Girls smoke more (odds ratio: 1.85, 95% CI 1.33 to 2.59). Experience with alcohol, and lack of interest in studies are also significant factors affecting smoking. Multilevel models of logistic regression showed that factors related to the school affect the smoking behaviour of young teenagers. More specifically, whether a school complies with antismoking rules or not is the main factor to predict smoking prevalence in schools. The remainder of the differences can be attributed to individual and family characteristics, tobacco consumption by parents or other close relatives, and peer group. Conclusions: A great deal of the individual differences in smoking are explained by factors at the school level, therefore the context is very relevant in this case. The most relevant predictors for smoking in young adolescents include some factors related to the schools they attend. One variable stood out in accounting for the school to school differences: how well they enforced the no smoking rule. Therefore we can prevent or delay tobacco smoking in adolescents not only by publicising health risks, but also by better enforcing no smoking rules in schools. PMID:11854347

A crash-prediction model for multilane roads.

PubMed

Caliendo, Ciro; Guida, Maurizio; Parisi, Alessandra

2007-07-01

Considerable research has been carried out in recent years to establish relationships between crashes and traffic flow, geometric infrastructure characteristics and environmental factors for two-lane rural roads. Crash-prediction models focused on multilane rural roads, however, have rarely been investigated. In addition, most research has paid but little attention to the safety effects of variables such as stopping sight distance and pavement surface characteristics. Moreover, the statistical approaches have generally included Poisson and Negative Binomial regression models, whilst Negative Multinomial regression model has been used to a lesser extent. Finally, as far as the authors are aware, prediction models involving all the above-mentioned factors have still not been developed in Italy for multilane roads, such as motorways. Thus, in this paper crash-prediction models for a four-lane median-divided Italian motorway were set up on the basis of accident data observed during a 5-year monitoring period extending between 1999 and 2003. The Poisson, Negative Binomial and Negative Multinomial regression models, applied separately to tangents and curves, were used to model the frequency of accident occurrence. Model parameters were estimated by the Maximum Likelihood Method, and the Generalized Likelihood Ratio Test was applied to detect the significant variables to be included in the model equation. Goodness-of-fit was measured by means of both the explained fraction of total variation and the explained fraction of systematic variation. The Cumulative Residuals Method was also used to test the adequacy of a regression model throughout the range of each variable. The candidate set of explanatory variables was: length (L), curvature (1/R), annual average daily traffic (AADT), sight distance (SD), side friction coefficient (SFC), longitudinal slope (LS) and the presence of a junction (J). Separate prediction models for total crashes and for fatal and injury crashes only were considered. For curves it is shown that significant variables are L, 1/R and AADT, whereas for tangents they are L, AADT and junctions. The effect of rain precipitation was analysed on the basis of hourly rainfall data and assumptions about drying time. It is shown that a wet pavement significantly increases the number of crashes. The models developed in this paper for Italian motorways appear to be useful for many applications such as the detection of critical factors, the estimation of accident reduction due to infrastructure and pavement improvement, and the predictions of accidents counts when comparing different design options. Thus this research may represent a point of reference for engineers in adjusting or designing multilane roads.

Three frameworks to predict physical activity behavior in middle school inclusive physical education: a multilevel analysis.

PubMed

Jin, Jooyeon; Yun, Joonkoo

2013-07-01

The purpose of this study was to examine three frameworks, (a) process-product, (b) student mediation, and (c) classroom ecology, to understand physical activity (PA) behavior of adolescents with and without disabilities in middle school inclusive physical education (PE). A total of 13 physical educators teaching inclusive PE and their 503 students, including 22 students with different disabilities, participated in this study. A series of multilevel regression analyses indicated that physical educators' teaching behavior and students' implementation intentions play important roles in promoting the students' PA in middle school inclusive PE settings when gender, disability, lesson content, instructional model, and class location are considered simultaneously. The findings suggest that the ecological framework should be considered to effectively promote PA of adolescents with and without disabilities in middle school PE classes.

Racial/Ethnic Differences in Cigarette Smoking Initiation and Progression to Daily Smoking: A Multilevel Analysis

PubMed Central

Kandel, Denise B.; Kiros, Gebre-Egziabher; Schaffran, Christine; Hu, Mei-Chen

2004-01-01

Objectives. We sought to identify individual and contextual predictors of adolescent smoking initiation and progression to daily smoking by race/ethnicity. Methods. We used data from the National Longitudinal Study of Adolescent Health to estimate the effects of individual (adolescent, family, peer) and contextual (school and state) factors on smoking onset among nonsmokers (n = 5374) and progression to daily smoking among smokers (n = 4474) with multilevel regression models. Results. Individual factors were more important predictors of smoking behaviors than were contextual factors. Predictors of smoking behaviors were mostly common across racial/ethnic groups. Conclusions. The few identified racial/ethnic differences in predictors of smoking behavior suggest that universal prevention and intervention efforts could reach most adolescents regardless of race/ethnicity. With 2 exceptions, important contextual factors remain to be identified. PMID:14713710

A Dirichlet-Multinomial Bayes Classifier for Disease Diagnosis with Microbial Compositions.

PubMed

Gao, Xiang; Lin, Huaiying; Dong, Qunfeng

2017-01-01

Dysbiosis of microbial communities is associated with various human diseases, raising the possibility of using microbial compositions as biomarkers for disease diagnosis. We have developed a Bayes classifier by modeling microbial compositions with Dirichlet-multinomial distributions, which are widely used to model multicategorical count data with extra variation. The parameters of the Dirichlet-multinomial distributions are estimated from training microbiome data sets based on maximum likelihood. The posterior probability of a microbiome sample belonging to a disease or healthy category is calculated based on Bayes' theorem, using the likelihood values computed from the estimated Dirichlet-multinomial distribution, as well as a prior probability estimated from the training microbiome data set or previously published information on disease prevalence. When tested on real-world microbiome data sets, our method, called DMBC (for Dirichlet-multinomial Bayes classifier), shows better classification accuracy than the only existing Bayesian microbiome classifier based on a Dirichlet-multinomial mixture model and the popular random forest method. The advantage of DMBC is its built-in automatic feature selection, capable of identifying a subset of microbial taxa with the best classification accuracy between different classes of samples based on cross-validation. This unique ability enables DMBC to maintain and even improve its accuracy at modeling species-level taxa. The R package for DMBC is freely available at https://github.com/qunfengdong/DMBC. IMPORTANCE By incorporating prior information on disease prevalence, Bayes classifiers have the potential to estimate disease probability better than other common machine-learning methods. Thus, it is important to develop Bayes classifiers specifically tailored for microbiome data. Our method shows higher classification accuracy than the only existing Bayesian classifier and the popular random forest method, and thus provides an alternative option for using microbial compositions for disease diagnosis.

Neighborhood Predictors of Dating Violence Victimization and Perpetration in Young Adulthood: A Multilevel Study

PubMed Central

Buka, Stephen L.; Subramanian, S. V.; Molnar, Beth E.

2010-01-01

Objectives. We examined whether social processes of neighborhoods, such as collective efficacy, during individual's adolescent years affect the likelihood of being involved in physical dating violence during young adulthood. Methods. Using longitudinal data on 633 urban youths aged 13 to 19 years at baseline and data from their neighborhoods (collected by the Project on Human Development in Chicago Neighborhoods), we ran multilevel linear regression models separately by gender to assess the association between collective efficacy and physical dating violence victimization and perpetration, controlling for individual covariates, neighborhood poverty, and perceived neighborhood violence. Results. Females were significantly more likely than were males to be perpetrators of dating violence during young adulthood (38% vs 19%). Multilevel analyses revealed some variation in dating violence at the neighborhood level, partly accounted for by collective efficacy. Collective efficacy was predictive of victimization for males but not females after control for confounders; it was marginally associated with perpetration (P = .07). The effects of collective efficacy varied by neighborhood poverty. Finally, a significant proportion (intraclass correlation = 14%–21%) of the neighborhood-level variation in male perpetration remained unexplained after modeling. Conclusions. Community-level strategies may be useful in preventing dating violence. PMID:20634470

[Ecological Correlates of Cardiovascular Disease Risk in Korean Blue-collar Workers: A Multi-level Study].

PubMed

Hwang, Won Ju; Park, Yunhee

2015-12-01

The purpose of this study was to investigate individual and organizational level of cardiovascular disease (CVD) risk factors associated with CVD risk in Korean blue-collar workers working in small sized companies. Self-report questionnaires and blood sampling for lipid and glucose were collected from 492 workers in 31 small sized companies in Korea. Multilevel modeling was conducted to estimate effects of related factors at the individual and organizational level. Multilevel regression analysis showed that workers in the workplace having a cafeteria had 1.81 times higher CVD risk after adjusting for factors at the individual level (p=.022). The explanatory power of variables related to organizational level variances in CVD risk was 17.1%. The results of this study indicate that differences in the CVD risk were related to organizational factors. It is necessary to consider not only individual factors but also organizational factors when planning a CVD risk reduction program. The factors caused by having cafeteria in the workplace can be reduced by improvement in the CVD-related risk environment, therefore an organizational-level intervention approach should be available to reduce CVD risk of workers in small sized companies in Korea.

The multilevel determinants of workers' mental health: results from the SALVEO study.

PubMed

Marchand, Alain; Durand, Pierre; Haines, Victor; Harvey, Steve

2015-03-01

This study examined the contribution of work, non-work and individual factors on workers' symptoms of psychological distress, depression and emotional exhaustion based on the multilevel determinants of workers' mental health model. Data from the SALVEO Study were collected in 2009-2012 from a sample of 1,954 employees nested in 63 workplaces in the province of Quebec (Canada). Multilevel regression models were used to analyse the data. Altogether, variables explain 32.2 % of psychological distress, 48.4 % of depression and 48.8 % of emotional exhaustion. Mental health outcomes varied slightly between workplaces and skill utilisation, physical and psychological demands, abusive supervision, interpersonal conflicts and job insecurity are related to the outcomes. Living in couple, having young children at home, family-to-work conflict, work-to-family conflict, strained marital and parental relations, and social support outside the workplace associated with the outcomes. Most of the individual characteristics also correlated with the three outcomes. Importantly, non-work and individual factors modulated the number and type of work factors related to the three outcomes. The results of this study suggest expanding perspectives on occupational mental health that fully recognise the complexity of workers' mental health determinants.

Immigrant maternal depression and social networks. A multilevel Bayesian spatial logistic regression in South Western Sydney, Australia.

PubMed

Eastwood, John G; Jalaludin, Bin B; Kemp, Lynn A; Phung, Hai N; Barnett, Bryanne E W

2013-09-01

The purpose is to explore the multilevel spatial distribution of depressive symptoms among migrant mothers in South Western Sydney and to identify any group level associations that could inform subsequent theory building and local public health interventions. Migrant mothers (n=7256) delivering in 2002 and 2003 were assessed at 2-3 weeks after delivery for risk factors for depressive symptoms. The binary outcome variables were Edinburgh Postnatal Depression Scale scores (EPDS) of >9 and >12. Individual level variables included were: financial income, self-reported maternal health, social support network, emotional support, practical support, baby trouble sleeping, baby demanding and baby not content. The group level variable reported here is aggregated social support networks. We used Bayesian hierarchical multilevel spatial modelling with conditional autoregression. Migrant mothers were at higher risk of having depressive symptoms if they lived in a community with predominantly Australian-born mothers and strong social capital as measured by aggregated social networks. These findings suggest that migrant mothers are socially isolated and current home visiting services should be strengthened for migrant mothers living in communities where they may have poor social networks. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Composite Measures of Individual and Area-Level Socio-Economic Status Are Associated with Visual Impairment in Singapore

PubMed Central

Wah, Win; Earnest, Arul; Sabanayagam, Charumathi; Cheng, Ching-Yu; Ong, Marcus Eng Hock; Wong, Tien Y.; Lamoureux, Ecosse L.

2015-01-01

Purpose To investigate the independent relationship of individual- and area-level socio-economic status (SES) with the presence and severity of visual impairment (VI) in an Asian population. Methods Cross-sectional data from 9993 Chinese, Malay and Indian adults aged 40–80 years who participated in the Singapore Epidemiology of eye Diseases (2004–2011) in Singapore. Based on the presenting visual acuity (PVA) in the better-seeing eye, VI was categorized into normal vision (logMAR≤0.30), low vision (logMAR>0.30<1.00), and blindness (logMAR≥1.00). Any VI was defined as low vision/blindness in the PVA of better-seeing eye. Individual-level low-SES was defined as a composite of primary-level education, monthly income<2000 SGD and residing in 1 or 2-room public apartment. An area-level SES was assessed using a socio-economic disadvantage index (SEDI), created using 12 variables from the 2010 Singapore census. A high SEDI score indicates a relatively poor SES. Associations between SES measures and presence and severity of VI were examined using multi-level, mixed-effects logistic and multinomial regression models. Results The age-adjusted prevalence of any VI was 19.62% (low vision = 19%, blindness = 0.62%). Both individual- and area-level SES were positively associated with any VI and low vision after adjusting for confounders. The odds ratio (95% confidence interval) of any VI was 2.11(1.88–2.37) for low-SES and 1.07(1.02–1.13) per 1 standard deviation increase in SEDI. When stratified by unilateral/bilateral categories, while low SES showed significant associations with all categories, SEDI showed a significant association with bilateral low vision only. The association between low SES and any VI remained significant among all age, gender and ethnic sub-groups. Although a consistent positive association was observed between area-level SEDI and any VI, the associations were significant among participants aged 40–65 years and male. Conclusion In this community-based sample of Asian adults, both individual- and area-level SES were independently associated with the presence and severity of VI. PMID:26555141

Feasibility and effectiveness of the baby friendly community initiative in rural Kenya: study protocol for a randomized controlled trial.

PubMed

Kimani-Murage, Elizabeth W; Kimiywe, Judith; Kabue, Mark; Wekesah, Frederick; Matiri, Evelyn; Muhia, Nelson; Wanjohi, Milka; Muriuki, Peterrock; Samburu, Betty; Kanyuira, James N; Young, Sera L; Griffiths, Paula L; Madise, Nyovani J; McGarvey, Stephen T

2015-09-28

Interventions promoting optimal infant and young child nutrition could prevent a fifth of under-5 deaths in countries with high mortality. Poor infant and young child feeding practices are widely documented in Kenya, with potential detrimental effects on child growth, health and survival. Effective strategies to improve these practices are needed. This study aims to pilot implementation of the Baby Friendly Community Initiative (BFCI), a global initiative aimed at promoting optimal infant and young child feeding practices, to determine its feasibility and effectiveness with regards to infant feeding practices, nutrition and health outcomes in a rural setting in Kenya. The study, employing a cluster-randomized trial design, will be conducted in rural Kenya. A total of 12 clusters, constituting community units within the government's Community Health Strategy, will be randomized, with half allocated to the intervention and the other half to the control arm. A total of 812 pregnant women and their respective children will be recruited into the study. The mother-child pairs will be followed up until the child is 6 months old. Recruitment will last approximately 1 year from January 2015, and the study will run for 3 years, from 2014 to 2016. The intervention will involve regular counseling and support of mothers by trained community health workers and health professionals on maternal, infant and young child nutrition. Regular assessment of knowledge, attitudes and practices on maternal, infant and young child nutrition will be done, coupled with assessment of nutritional status of the mother-child pairs and morbidity for the children. Statistical methods will include analysis of covariance, multinomial logistic regression and multilevel modeling. The study is funded by the NIH and USAID through the Program for Enhanced Research (PEER) Health. Findings from the study outlined in this protocol will inform potential feasibility and effectiveness of a community-based intervention aimed at promoting optimal breastfeeding and other infant feeding practices. The intervention, if proved feasible and effective, will inform policy and practice in Kenya and similar settings, particularly regarding implementation of the baby friendly community initiative. ISRCTN03467700 ; Date of Registration: 24 September 2014.

Gender differences in body consciousness and substance use among high-risk adolescents.

PubMed

Black, David Scott; Sussman, Steve; Unger, Jennifer; Pokhrel, Pallav; Sun, Ping

2010-08-01

This study explores the association between private and public body consciousness and past 30-day cigarette, alcohol, marijuana, and hard drug use among adolescents. Self-reported data from alterative high school students in California were analyzed (N = 976) using multilevel regression models to account for student clustering within schools. Separate regression analyses were conducted for males and females. Both cross-sectional baseline data and one-year longitudinal prediction models indicated that body consciousness is associated with specific drug use categories differentially by gender. Findings suggest that body consciousness accounts for additional variance in substance use etiology not explained by previously recognized dispositional variables.

Modeling Unconscious Gender Bias in Fame Judgments: Finding the Proper Branch of the Correct (Multinomial) Tree

PubMed

Draine; Greenwald; Banaji

1996-03-01

In the preceding article, Buchner and Wippich used a guessing-corrected, multinomial process-dissociation analysis to test whether a gender bias in fame judgments reported by Banaji and Greenwald (Journal of Personality and Social Psychology, 1995, 68, 181-198) was unconscious. In their two experiments, Buchner and Wippich found no evidence for unconscious mediation of this gender bias. Their conclusion can be questioned by noting that (a) the gender difference in familiarity of previously seen names that Buchner and Wippich modeled was different from the gender difference in criterion for fame judgments reported by Banaji and Greenwald, (b) the assumptions of Buchner and Wippich's multinomial model excluded processes that are plausibly involved in the fame judgment task, and (c) the constructs of Buchner and Wippich's model that corresponded most closely to Banaji and Greenwald's gender-bias interpretation were formulated so as to preclude the possibility of modeling that interpretation. Perhaps a more complex multinomial model can model the Banaji and Greenwald interpretation.

Modeling unconscious gender bias in fame judgments: finding the proper branch of the correct (multinomial) tree.

PubMed

Draine, S C; Greenwald, A G; Banaji, M R

1996-01-01

In the preceding article, Buchner and Wippich used a guessing-corrected, multinomial process-dissociation analysis to test whether a gender bias in fame judgements reported by Banaji and Greenwald (Journal of Personality and Social Psychology, 1995, 68, 181-198) was unconscious. In their two experiments, Buchner and Wippich found no evidence for unconscious mediation of this gender bias. Their conclusion can be questioned by noting that (a) the gender difference in familiarity of previously seen names that Buchner and Wippich modeled was different from the gender difference in criterion for fame judgements reported by Banaji and Greenwald, (b) the assumptions of Buchner and Wippich's multinomial model excluded processes that are plausibly involved in the fame judgement task, and (c) the constructs of Buchner and Wippich's model that corresponded most closely to Banaji and Greenwald's gender-bias interpretation were formulated so as to preclude the possibility of modeling that interpretation. Perhaps a more complex multinomial model can model the Banaji and Greenwald interpretation.

Analysis of multinomial models with unknown index using data augmentation

USGS Publications Warehouse

Royle, J. Andrew; Dorazio, R.M.; Link, W.A.

2007-01-01

Multinomial models with unknown index ('sample size') arise in many practical settings. In practice, Bayesian analysis of such models has proved difficult because the dimension of the parameter space is not fixed, being in some cases a function of the unknown index. We describe a data augmentation approach to the analysis of this class of models that provides for a generic and efficient Bayesian implementation. Under this approach, the data are augmented with all-zero detection histories. The resulting augmented dataset is modeled as a zero-inflated version of the complete-data model where an estimable zero-inflation parameter takes the place of the unknown multinomial index. Interestingly, data augmentation can be justified as being equivalent to imposing a discrete uniform prior on the multinomial index. We provide three examples involving estimating the size of an animal population, estimating the number of diabetes cases in a population using the Rasch model, and the motivating example of estimating the number of species in an animal community with latent probabilities of species occurrence and detection.

Estimation from incomplete multinomial data. Ph.D. Thesis - Harvard Univ.

NASA Technical Reports Server (NTRS)

Credeur, K. R.

1978-01-01

The vector of multinomial cell probabilities was estimated from incomplete data, incomplete in that it contains partially classified observations. Each such partially classified observation was observed to fall in one of two or more selected categories but was not classified further into a single category. The data were assumed to be incomplete at random. The estimation criterion was minimization of risk for quadratic loss. The estimators were the classical maximum likelihood estimate, the Bayesian posterior mode, and the posterior mean. An approximation was developed for the posterior mean. The Dirichlet, the conjugate prior for the multinomial distribution, was assumed for the prior distribution.

History of family violence, childhood behavior problems, and adolescent high-risk behaviors as predictors of girls' repeated patterns of dating victimization in two developmental periods.

PubMed

Vézina, Johanne; Hébert, Martine; Poulin, François; Lavoie, Francine; Vitaro, Frank; Tremblay, Richard E

2015-04-01

This study aims to document the prevalence of repeated patterns of dating victimization and to examine, within the frameworks of an ecological model and lifestyle/routine activities theories, associations between such patterns and family, peer, and individual factors. Dating victimization in adolescence (age 15) and early adulthood (age 21) was evaluated in 443 female participants. Multinomial logistic regression analyses revealed that history of family violence, childhood behavior problems, and adolescent high-risk behaviors were associated with an increased risk for girls of being victimized (psychologically and/or physically/sexually) in their dating relationships, either in adolescence or early adulthood, or at both developmental periods. © The Author(s) 2015.

The effect of major income sources on rural household food (in)security: Evidence from Swaziland and implications for policy.

PubMed

Mabuza, Majola L; Ortmann, Gerald F; Wale, Edilegnaw; Mutenje, Munyaradzi J

2016-01-01

The aim of this article was to investigate the food (in)security effect of household income generated from major economic activities in rural Swaziland. From a sample of 979 households, the results of a multinomial treatment regression model indicated that gender of household head, labor endowment, education, size of arable land, and location significantly influenced the households' choice of primary economic activity. Further results suggested that off-farm-income-dependent households were less likely to be food insecure when compared with on-farm-income-dependent households. However, on-farm-income-dependent households had a better food security status than their counterparts who depended on remittances and nonfarm economic activities.

Domestic Violence Reported to the Police: Correlates of Victims' Reporting Behavior and Support to Legal Proceedings.

PubMed

Boivin, Rémi; Leclerc, Chloé

2016-01-01

This article analyzes reported incidents of domestic violence according to the source of the complaint and whether the victim initially supported judicial action against the offender. Almost three quarters of incidents studied were reported by the victim (72%), and a little more than half of victims initially wanted to press charges (55%). Using multinomial logistic regression models, situational and individual factors are used to distinguish 4 incident profiles. Incidents in which the victim made the initial report to the police and wished to press charges are the most distinct and involve partners who were already separated at the time of the incident or had a history of domestic violence. The other profiles also show important differences.

Factors Associated with Alcohol Use Before or During Sex Among Men Who Have Sex with Men in a Large Internet Sample from Asia.

PubMed

Yang, Cui; Guadamuz, Thomas E; Lim, Sin How; Koe, Stuart; Wei, Chongyi

2016-04-01

We explored factors associated with alcohol use before or during sex among a sample of 10,861 men who have sex with men (MSM) in Asia who were recruited online for the study. Multinomial logistic regression analysis indicated that having sex under the influence of alcohol was associated with having multiple male partners, seeking partners primarily through gay bar/gym/dance party/friends, selling sex and using multiple drugs during the past 6 months, and unprotected anal sex. More efforts are needed to better assess alcohol use and misuse among MSM in Asia and understand contextual influences on alcohol use and HIV-related behaviors in order to implement culturally-specific interventions.

The View From the Bottom: Relative Deprivation and Bullying Victimization in Canadian Adolescents.

PubMed

Napoletano, Anthony; Elgar, Frank J; Saul, Grace; Dirks, Melanie; Craig, Wendy

2016-12-01

We investigated the relation between relative deprivation (RD)-disparity in affluence between adolescents and their more affluent schoolmates-and involvement in bullying among 23,383 students (aged 9-19) in 413 schools that participated in the 2010 Canadian Health Behavior in School-Aged Children survey. Students reported family affluence and frequency of bullying victimization and perpetration during the previous 2 months. Using the Yitzhaki index of RD and multinomial logistic regression analysis, we found that RD positively related to three types of bullying victimization (physical, relational, and cyberbullying) and to two types of perpetration (relational and cyberbullying) after differences in absolute affluence were held constant. These findings suggest that RD uniquely contributes to risk of bullying involvement. © The Author(s) 2015.

Prediction of Nursing Workload in Hospital.

PubMed

Fiebig, Madlen; Hunstein, Dirk; Bartholomeyczik, Sabine

2018-01-01

A dissertation project at the Witten/Herdecke University [1] is investigating which (nursing sensitive) patient characteristics are suitable for predicting a higher or lower degree of nursing workload. For this research project four predictive modelling methods were selected. In a first step, SUPPORT VECTOR MACHINE, RANDOM FOREST, and GRADIENT BOOSTING were used to identify potential predictors from the nursing sensitive patient characteristics. The results were compared via FEATURE IMPORTANCE. To predict nursing workload the predictors identified in step 1 were modelled using MULTINOMIAL LOGISTIC REGRESSION. First results from the data mining process will be presented. A prognostic determination of nursing workload can be used not only as a basis for human resource planning in hospital, but also to respond to health policy issues.

Promoting Informal and Professional Help-Seeking for Adolescent Dating Violence

PubMed Central

Hedge, Jasmine M.; Hudson-Flege, Matthew D.; McDonell, James R.

2016-01-01

The present study examined factors that differentiate adolescents with varied intentions of informal and professional help-seeking for dating violence. Help-seeking intentions among 518 ethnically diverse adolescents from a rural, southern county who participated in a longitudinal study of teen dating violence were categorized into three groups: adolescents unlikely to seek any help, adolescents likely to seek only informal help, and adolescents likely to seek informal and professional help. Multinomial logistic regression found that gender, family functioning, problem-solving competency, dating status, having an adult to talk to about a dating relationship, and acceptability of family violence significantly predicted membership in the help-seeking groups. Implications for promoting informal and professional help-seeking and recommendations for future research are discussed. PMID:28584387

Promoting Informal and Professional Help-Seeking for Adolescent Dating Violence.

PubMed

Hedge, Jasmine M; Hudson-Flege, Matthew D; McDonell, James R

2017-05-01

The present study examined factors that differentiate adolescents with varied intentions of informal and professional help-seeking for dating violence. Help-seeking intentions among 518 ethnically diverse adolescents from a rural, southern county who participated in a longitudinal study of teen dating violence were categorized into three groups: adolescents unlikely to seek any help, adolescents likely to seek only informal help, and adolescents likely to seek informal and professional help. Multinomial logistic regression found that gender, family functioning, problem-solving competency, dating status, having an adult to talk to about a dating relationship, and acceptability of family violence significantly predicted membership in the help-seeking groups. Implications for promoting informal and professional help-seeking and recommendations for future research are discussed.

The association between maternal antioxidant levels in midpregnancy and preeclampsia.

PubMed

Cohen, Jacqueline M; Kramer, Michael S; Platt, Robert W; Basso, Olga; Evans, Rhobert W; Kahn, Susan R

2015-11-01

We sought to determine whether midpregnancy antioxidant levels are associated with preeclampsia, overall and by timing of onset. We carried out a case-control study, nested within a cohort of 5337 pregnant women in Montreal, Quebec, Canada. Blood samples obtained at 24-26 weeks were assayed for nonenzymatic antioxidant levels among cases of preeclampsia (n = 111) and unaffected controls (n = 441). We excluded women diagnosed with gestational hypertension only. We used logistic regression with the z-score of each antioxidant level as the main predictor variable for preeclampsia risk. We further stratified early-onset (<34 weeks) and late-onset preeclampsia and carried out multinomial logistic regression. Finally, we assessed associations between antioxidant biomarkers and timing of onset (in weeks) by Cox regression, with appropriate selection weights. We summed levels of correlated biomarkers (r(2) > 0.3) and log-transformed positively skewed distributions. We adjusted for body mass index, nulliparity, preexisting diabetes, hypertension, smoking, and proxies for ethnicity and socioeconomic status. The odds ratios for α-tocopherol, α-tocopherol:cholesterol, lycopene, lutein, and carotenoids (sum of α-carotene, β-carotene, anhydrolutein, α-cryptoxanthin, and β-cryptoxanthin) suggested an inverse association between antioxidant levels and overall preeclampsia risk; however, only lutein was significantly associated with overall preeclampsia in adjusted models (odds ratio, 0.60; 95% confidence interval, 0.46-0.77) per SD. In multinomial logistic models, the relative risk ratio (RRR) estimates for the early-onset subgroup were farther from the null than those for the late-onset subgroup. The ratio of α-tocopherol to cholesterol and retinol were significantly associated with early- but not late-onset preeclampsia: RRRs (95% confidence intervals) for early-onset preeclampsia 0.67 (0.46-0.99) and 1.61 (1.12-2.33), respectively. Lutein was significantly associated with both early- and late-onset subtypes in adjusted models; RRRs 0.53 (0.35-0.80) and 0.62 (0.47-0.82), respectively. Survival analyses confirmed these trends. Most antioxidants were more strongly associated with early-onset preeclampsia, suggesting that oxidative stress may play a greater role in the pathophysiology of early-onset preeclampsia. Alternatively, reverse causality may explain this pattern. Lutein was associated with both early- and late-onset preeclampsia and may be a promising nutrient to consider in preeclampsia prevention trials, if this finding is corroborated. Copyright © 2015 Elsevier Inc. All rights reserved.

Individual- and Neighbourhood-Level Indicators of Subjective Well-Being in a Small and Poor Eastern Cape Township: The Effect of Health, Social Capital, Marital Status, and Income

ERIC Educational Resources Information Center

Cramm, J. M.; Moller, V.; Nieboer, A. P.

2012-01-01

Our study used multilevel regression analysis to identify individual- and neighbourhood-level factors that determine individual-level subjective well-being in Rhini, a deprived suburb of Grahamstown in the Eastern Cape province of South Africa. The Townsend index and Gini coefficient were used to investigate whether contextual neighbourhood-level…

Work stress and patient safety: observer-rated work stressors as predictors of characteristics of safety-related events reported by young nurses.

PubMed

Elfering, A; Semmer, N K; Grebner, S

This study investigates the link between workplace stress and the 'non-singularity' of patient safety-related incidents in the hospital setting. Over a period of 2 working weeks 23 young nurses from 19 hospitals in Switzerland documented 314 daily stressful events using a self-observation method (pocket diaries); 62 events were related to patient safety. Familiarity of safety-related events and probability of recurrence, as indicators of non-singularity, were the dependent variables in multilevel regression analyses. Predictor variables were both situational (self-reported situational control, safety compliance) and chronic variables (job stressors such as time pressure, or concentration demands and job control). Chronic work characteristics were rated by trained observers. The most frequent safety-related stressful events included incomplete or incorrect documentation (40.3%), medication errors (near misses 21%), delays in delivery of patient care (9.7%), and violent patients (9.7%). Familiarity of events and probability of recurrence were significantly predicted by chronic job stressors and low job control in multilevel regression analyses. Job stressors and low job control were shown to be risk factors for patient safety. The results suggest that job redesign to enhance job control and decrease job stressors may be an important intervention to increase patient safety.

Transgenerational effect of neighborhood poverty on low birth weight among African Americans in Cook County, Illinois.

PubMed

Collins, James W; David, Richard J; Rankin, Kristin M; Desireddi, Jennifer R

2009-03-15

In perinatal epidemiology, transgenerational risk factors are defined as conditions experienced by one generation that affect the pregnancy outcomes of the next generation. The authors investigated the transgenerational effect of neighborhood poverty on infant birth weight among African Americans. Stratified and multilevel logistic regression analyses were performed on an Illinois transgenerational data set with appended US Census income information. Singleton African-American infants (n = 40,648) born in 1989-1991 were considered index births. The mothers of index infants had been born in 1956-1976. The maternal grandmothers of index infants were identified. Rates of infant low birth weight (<2,500 g) rose as maternal grandmother's residential environment during her pregnancy deteriorated, independently of mother's residential environment during her pregnancy. In a multilevel logistic regression model that accounted for clustering by maternal grandmother's residential environment, the adjusted odds ratio (controlling for mother's age, education, prenatal care, cigarette smoking status, and residential environment) for infant low birth weight for maternal grandmother's residence in a poor neighborhood (compared with an affluent neighborhood) equaled 1.3 (95% confidence interval: 1.1, 1.4). This study suggests that maternal grandmother's exposure to neighborhood poverty during her pregnancy is a risk factor for infant low birth weight among African Americans.

Depressive Symptoms among Young Breast Cancer Survivors: The Importance of Reproductive Concerns

PubMed Central

Gorman, Jessica R; Malcarne, Vanessa L; Roesch, Scott C; Madlensky, Lisa; Pierce, John P

2010-01-01

Purpose Breast cancer diagnosis and treatment can negatively impact fertility in premenopausal women and influence reproductive planning. This study investigates whether concerns about reproduction after breast cancer treatment were associated with long-term depressive symptoms. Patients and Methods Participants include 131 women diagnosed with early-stage breast cancer at age 40 or younger participating in the Women's Healthy Eating and Living (WHEL) Survivorship Study. Participants were enrolled an average of 1.5 years post-diagnosis and depressive symptoms were monitored 6 times throughout the average additional 10 year follow-up period. Detailed recall of reproductive concerns after treatment was collected an average of 12 years post-diagnosis. Multilevel regression was used to evaluate whether mean long-term depressive symptoms differed as a function of reproductive concerns and significant covariates. Results Multilevel regression identified greater recalled reproductive concerns as an independent predictor of consistent depressive symptoms after controlling for both social support and physical health (B= 0.02, SE= 0.01, p=0.04). In bivariate analyses, being nulliparous at diagnosis and reporting treatment-related ovarian damage were both strongly associated with higher reproductive concerns and with depressive symptoms. Conclusion Reported reproductive concerns after breast cancer treatment were a significant contributor to consistent depressive symptoms. Younger survivors would benefit from additional information and support related to reproductive issues. PMID:20130979

Bayesian multinomial probit modeling of daily windows of susceptibility for maternal PM2.5 exposure and congenital heart defects

EPA Science Inventory

Past epidemiologic studies suggest maternal ambient air pollution exposure during critical periods of the pregnancy is associated with fetal development. We introduce a multinomial probit model that allows for the joint identification of susceptible daily periods during the pregn...

Pig Data and Bayesian Inference on Multinomial Probabilities

ERIC Educational Resources Information Center

Kern, John C.

2006-01-01

Bayesian inference on multinomial probabilities is conducted based on data collected from the game Pass the Pigs[R]. Prior information on these probabilities is readily available from the instruction manual, and is easily incorporated in a Dirichlet prior. Posterior analysis of the scoring probabilities quantifies the discrepancy between empirical…

Explaining the demand for pharmaceuticals in Spain: are there differences in drug consumption between foreigners and the Spanish population?

PubMed

Jiménez-Rubio, Dolores; Hernández-Quevedo, Cristina

2010-10-01

The aim of this study is to examine the factors driving the demand for drugs in Spain, focusing on the existence of disparities in pharmaceutical consumption between the Spanish and the foreign population. Our analysis is based on a multilevel multinomial probit model that compares three consumption options (no consumption, prescribed consumption and self-medicated consumption) on the five most consumed drugs in Spain. Data is taken from the adult sample of the 2006 Spanish National Health Survey, including 29,478 individuals over 15 years old. Overall, the findings show a lower consumption of medicines by some immigrants categories relative to Spaniards. In addition, the results indicate that the consumption of medicines is mainly related to variables associated to the specific cost sharing structure in Spain, such as health limitations and retirement status. Other variables found to explain the demand for drugs were: private health insurance, age, sex, alcohol and cigarette consumption and drug class. Further understanding of the reasons for the observed differences in drug consumption on the basis of country of birth would allow the health system to design more effective health policies aimed at ensuring equality of access to health resources to all population groups. Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.

Return to Work and Multilevel Versus Single-Level Cervical Fusion for Radiculopathy in a Workers' Compensation Setting.

PubMed

Faour, Mhamad; Anderson, Joshua T; Haas, Arnold R; Percy, Rick; Woods, Stephen T; Ahn, Uri M; Ahn, Nicholas U

2017-01-15

Retrospective comparative cohort study. Examine the impact of multilevel fusion on return to work (RTW) status and compare RTW status after multi- versus single-level cervical fusion for patients with work-related injury. Patients with work-related injuries in the workers' compensation systems have less favorable surgical outcomes. Cervical fusion provides a greater than 90% likelihood of relieving radiculopathy and stabilizing or improving myelopathy. However, more levels fused at index surgery are reportedly associated with poorer surgical outcomes than single-level fusion. Data was collected from the Ohio Bureau of Workers' Compensation (BWC) between 1993 and 2011. The study population included patients who underwent cervical fusion for radiculopathy. Two groups were constructed (multilevel fusion [MLF] vs. single-level fusion [SLF]). Outcomes measures evaluated were: RTW criteria, RTW <1year, reoperation, surgical complication, disability, and legal litigation after surgery. After accounting for a number of independent variables in the regression model, multilevel fusion was a negative predictor of successful RTW status within 3-year follow-up after surgery (OR = 0.82, 95% CI: 0.70-0.95, P <0.05).RTW criteria were met 62.9% of SLF group compared with 54.8% of MLF group. The odds of having a stable RTW for MLF patients were 0.71% compared with the SLF patients (95% CI: 0.61-0.83; P: 0.0001).At 1 year after surgery, RTW rate was 53.1% for the SLF group compared with 43.7% for the MLF group. The odds of RTW within 1 year after surgery for the MLF group were 0.69% compared with SLF patients (95% CI: 0.59-0.80; P: 0.0001).Higher rate of disability after surgery was observed in the MLF group compared with the SLF group (P: 0.0001) CONCLUSION.: Multilevel cervical fusion for radiculopathy was associated with poor return to work profile after surgery. Multilevel cervical fusion was associated with lower RTW rates, less likelihood of achieving stable return to work, and higher rate of disability after surgery. 3.

Tobacco advertising, environmental smoking bans, and smoking in Chinese urban areas.

PubMed

Yang, Tingzhong; Rockett, Ian R H; Li, Mu; Xu, Xiaochao; Gu, Yaming

2012-07-01

To evaluate whether cigarette smoking in Chinese urban areas was respectively associated with exposure to tobacco advertising and smoking bans in households, workplaces, and public places. Participants were 4735 urban residents aged 15 years and older, who were identified through multi-stage quota-sampling conducted in six Chinese cities. Data were collected on individual sociodemographics and smoking status, and regional tobacco control measures. The sample was characterized in terms of smoking prevalence, and multilevel logistic models were employed to analyze the association between smoking and tobacco advertising and environmental smoking restrictions, respectively. Smoking prevalence was 30%. Multilevel logistic regression analysis showed that smoking was positively associated with exposure to tobacco advertising, and negatively associated with workplace and household smoking bans. The association of smoking with both tobacco advertising and environmental smoking bans further justifies implementation of comprehensive smoking interventions and tobacco control programs in China. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Effects of Youth Participation in Extra-Curricular Sport Programs on Perceived Self-Efficacy: A Multilevel Analysis.

PubMed

Reverdito, Riller S; Carvalho, Humberto M; Galatti, Larissa R; Scaglia, Alcides J; Gonçalves, Carlos E; Paes, Roberto R

2017-06-01

The present study examined extracurricular sport participation variables and developmental context in relationship to perceived self-efficacy among underserved adolescents. Participants ( n = 821, 13.6 ± 1.5 years) completed the Youth Experience in Sport questionnaire and General Self-Efficacy Scale. We used the Human Development Index (HDI) to characterize developmental contexts. Multilevel regression models were used to explore the relative contributions of age, sex, years of participation in extracurricular sport, HDI, and perceived positive experience in sport. Our results highlight that positive experience alone and in interaction with length of participation in the program fostered perceived self-efficacy. Participants from higher HDI contexts remained longer in the program. An implication of our research is that variables linked to positive sport experiences and perceived self-efficacy can be used as markers to evaluate the outcomes and impact of sport participation programs aimed at promoting positive youth development.

Placing Families in Context: Challenges for Cross-National Family Research

PubMed Central

Yu, Wei-hsin

2015-01-01

Cross-national comparisons constitute a valuable strategy to assess how broader cultural, political, and institutional contexts shape family outcomes. One typical approach of cross-national family research is to use comparable data from a limited number of countries, fit similar regression models for each country, and compare results across country-specific models. Increasingly, researchers are adopting a second approach, which requires merging data from many more societies and testing multilevel models using the pooled sample. Although the second approach has the advantage of allowing direct estimates of the effects of nation-level characteristics, it is more likely to suffer from the problems of omitted-variable bias, influential cases, and measurement and construct nonequivalence. I discuss ways to improve the first approach's ability to infer macrolevel influences, as well as how to deal with challenges associated with the second one. I also suggest choosing analytical strategies according to whether the data meet multilevel models’ assumptions. PMID:25999603

Giant multilevel thoracic hemangioma with spinal cord compression in a patient with Klippel-Weber-Trenaunay syndrome: case report.

PubMed

Grau, Stefan J; Holtmannspoetter, Markus; Seelos, Klaus; Tonn, Joerg-Christian; Siefert, Axel

2009-06-15

Case report and clinical discussion. We intend to report a very rare case of a giant spinal hemangioma causing myelopathy. Multilevel symptomatic spinal hemangiomas causing acute neurologic symptoms are rare disorders. We found only sporadic reports in English literature. We describe a very rare case in which Klippel-Trenaunay-Weber syndrome is associated with a multisegmental vertebral hemangioma causing a rapidly progressing thoracic myelopathy. Because of the extension of the disease, surgical intervention was not feasible, the patient was treated by radiotherapy. The patient showed a complete regression of symptoms with stable condition after 3 months. In extensive spinal hemangiomas, radiotherapy may represent a safe treatment modality with rapid clinical improvement even in cases with spinal cord compression. This report contributes to a wide range of known vascular abnormalities in Klippel-Trenaunay-Weber syndrome and supports the need for a careful multisystemic evaluation of these patients.

[Prevalence of common mental disorders and the relationship to the social context: multilevel analysis of the São Paulo Ageing & Health Study (SPAH)].

PubMed

Coutinho, Letícia Maria Silva; Matijasevich, Alícia; Scazufca, Márcia; Menezes, Paulo Rossi

2014-09-01

Social context can play a important role in the etiology and prevalence of mental disorders. The aim of the present study was to investigate risk factors for common mental disorders (CMD), considering different contextual levels: individual, household, and census tract. The study used a population-based sample of 2,366 respondents from the São Paulo Ageing & Health Study. Presence of CMD was identified by the SRQ-20. Sex, age, education, and occupation were individual characteristics associated with prevalence of CMD. Multilevel logistic regression models showed that part of the variance in prevalence of CMD was associated with the household level, showing associations between crowding, family income, and CMD, even after controlling for individual characteristics. These results suggest that characteristics of the environment where people live can influence their mental health status.

A multilevel analysis of social ties and social cohesion among Latinos and their neighborhoods: results from Chicago.

PubMed

Almeida, Joanna; Kawachi, Ichiro; Molnar, Beth E; Subramanian, S V

2009-09-01

Research suggests that, among Latinos, there are health benefits associated with living in a neighborhood populated with coethnics. While social networks and social cohesion are the proposed explanation for the salubrious effect and are assumed to be characteristics of Latino immigrant enclaves, evidence for this is limited. We used multilevel regression to test the relative contribution of individual race/ethnicity and neighborhood concentration of Mexican Americans as predictors of social networks and social cohesion. After accounting for personal characteristics, we found a negative association between neighborhood concentration of Mexican Americans and social cohesion. Among Latinos, living in a neighborhood with increased coethnics was associated with increased social ties. Compared to non-Latino whites, Mexican Americans reported more social ties but lower social cohesion. Contrary to the assumption that Mexican immigrant enclaves beget social cohesion, we did not find this to be true in Chicago neighborhoods.

On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices

PubMed Central

Ye, Xin; Pendyala, Ram M.; Zou, Yajie

2017-01-01

A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper. The resulting semi-nonparametric function can represent a probability density function for a large family of multimodal distributions. The model has a closed-form log-likelihood function that facilitates model estimation. The proposed method is applied to model commute mode choice among four alternatives (auto, transit, bicycle and walk) using travel behavior data from Argau, Switzerland. Comparisons between the multinomial logit model and the proposed semi-nonparametric model show that violations of the standard Gumbel distribution assumption lead to considerable inconsistency in parameter estimates and model inferences. PMID:29073152

On the development of a semi-nonparametric generalized multinomial logit model for travel-related choices.

PubMed

Wang, Ke; Ye, Xin; Pendyala, Ram M; Zou, Yajie

2017-01-01

A semi-nonparametric generalized multinomial logit model, formulated using orthonormal Legendre polynomials to extend the standard Gumbel distribution, is presented in this paper. The resulting semi-nonparametric function can represent a probability density function for a large family of multimodal distributions. The model has a closed-form log-likelihood function that facilitates model estimation. The proposed method is applied to model commute mode choice among four alternatives (auto, transit, bicycle and walk) using travel behavior data from Argau, Switzerland. Comparisons between the multinomial logit model and the proposed semi-nonparametric model show that violations of the standard Gumbel distribution assumption lead to considerable inconsistency in parameter estimates and model inferences.

Public funding of pharmaceuticals in The Netherlands: investigating the effect of evidence, process and context on CVZ decision-making.

PubMed

Cerri, Karin H; Knapp, Martin; Fernandez, Jose-Luis

2014-09-01

The College Voor Zorgverzekeringen (CVZ) provides guidance to the Dutch healthcare system on funding and use of new pharmaceutical technologies. This study examined the impact of evidence, process and context factors on CVZ decisions in 2004-2009. A data set of CVZ decisions pertaining to pharmaceutical technologies was created, including 29 variables extracted from published information. A three-category outcome variable was used, defined as the decision to 'recommend', 'restrict' or 'not recommend' a technology. Technologies included in list 1A/1B or on the expensive drug list were considered recommended; those included in list 2 or for which patient co-payment is required were considered restricted; technologies not included on any reimbursement list were classified as 'not recommended'. Using multinomial logistic regression, the relative contribution of explanatory variables on CVZ decisions was assessed. In all, 244 technology appraisals (256 technologies) were analysed, with 51%, of technologies recommended, 33% restricted and 16% not recommended by CVZ for funding. The multinomial model showed significant associations (p ≤ 0.10) between CVZ outcome and several variables, including: (1) use of an active comparator and demonstration of statistical superiority of the primary endpoint in clinical trials, (2) pharmaceutical budget impact associated with introduction of the technology, (3) therapeutic indication and (4) prevalence of the target population. Results confirm the value of a comprehensive and multivariate approach to understanding CVZ decision-making.

A General Family of Limited Information Goodness-of-Fit Statistics for Multinomial Data

ERIC Educational Resources Information Center

Joe, Harry; Maydeu-Olivares, Alberto

2010-01-01

Maydeu-Olivares and Joe (J. Am. Stat. Assoc. 100:1009-1020, "2005"; Psychometrika 71:713-732, "2006") introduced classes of chi-square tests for (sparse) multidimensional multinomial data based on low-order marginal proportions. Our extension provides general conditions under which quadratic forms in linear functions of cell residuals are…

Hierarchical Multinomial Processing Tree Models: A Latent-Trait Approach

ERIC Educational Resources Information Center

Klauer, Karl Christoph

2010-01-01

Multinomial processing tree models are widely used in many areas of psychology. A hierarchical extension of the model class is proposed, using a multivariate normal distribution of person-level parameters with the mean and covariance matrix to be estimated from the data. The hierarchical model allows one to take variability between persons into…

A Multinomial Model of Event-Based Prospective Memory

ERIC Educational Resources Information Center

Smith, Rebekah E.; Bayen, Ute J.

2004-01-01

Prospective memory is remembering to perform an action in the future. The authors introduce the 1st formal model of event-based prospective memory, namely, a multinomial model that includes 2 separate parameters related to prospective memory processes. The 1st measures preparatory attentional processes, and the 2nd measures retrospective memory…

Introducing the Event Related Fixed Interval Area (ERFIA) Multilevel Technique: a Method to Analyze the Complete Epoch of Event-Related Potentials at Single Trial Level

PubMed Central

Vossen, Catherine J.; Vossen, Helen G. M.; Marcus, Marco A. E.; van Os, Jim; Lousberg, Richel

2013-01-01

In analyzing time-locked event-related potentials (ERPs), many studies have focused on specific peaks and their differences between experimental conditions. In theory, each latency point after a stimulus contains potentially meaningful information, regardless of whether it is peak-related. Based on this assumption, we introduce a new concept which allows for flexible investigation of the whole epoch and does not primarily focus on peaks and their corresponding latencies. For each trial, the entire epoch is partitioned into event-related fixed-interval areas under the curve (ERFIAs). These ERFIAs, obtained at single trial level, act as dependent variables in a multilevel random regression analysis. The ERFIA multilevel method was tested in an existing ERP dataset of 85 healthy subjects, who underwent a rating paradigm of 150 painful and non-painful somatosensory electrical stimuli. We modeled the variability of each consecutive ERFIA with a set of predictor variables among which were stimulus intensity and stimulus number. Furthermore, we corrected for latency variations of the P2 (260 ms). With respect to known relationships between stimulus intensity, habituation, and pain-related somatosensory ERP, the ERFIA method generated highly comparable results to those of commonly used methods. Notably, effects on stimulus intensity and habituation were also observed in non-peak-related latency ranges. Further, cortical processing of actual stimulus intensity depended on the intensity of the previous stimulus, which may reflect pain-memory processing. In conclusion, the ERFIA multilevel method is a promising tool that can be used to study event-related cortical processing. PMID:24224018

Validity analysis on merged and averaged data using within and between analysis: focus on effect of qualitative social capital on self-rated health.

PubMed

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.

Income inequality and mortality: a multilevel prospective study of 521 248 individuals in 50 US states.

PubMed

Backlund, Eric; Rowe, Geoff; Lynch, John; Wolfson, Michael C; Kaplan, George A; Sorlie, Paul D

2007-06-01

Some of the most consistent evidence in favour of an association between income inequality and health has been among US states. However, in multilevel studies of mortality, only two out of five studies have reported a positive relationship with income inequality after adjustment for the compositional characteristics of the state's inhabitants. In this study, we attempt to clarify these mixed results by analysing the relationship within age-sex groups and by applying a previously unused analytical method to a database that contains more deaths than any multilevel study to date. The US National Longitudinal Mortality Study (NLMS) was used to model the relationship between income inequality in US states and mortality using both a novel and previously used methodologies that fall into the general framework of multilevel regression. We adjust age-sex specific models for nine socioeconomic and demographic variables at the individual level and percentage black and region at the state level. The preponderance of evidence from this study suggests that 1990 state-level income inequality is associated with a 40% differential in state level mortality rates (95% CI = 26-56%) for men 25-64 years and a 14% (95% CI = 3-27%) differential for women 25-64 years after adjustment for compositional factors. No such relationship was found for men or women over 65. The relationship between income inequality and mortality is only robust to adjustment for compositional factors in men and women under 65. This explains why income inequality is not a major driver of mortality trends in the United States because most deaths occur at ages 65 and over. This analysis does suggest, however, the certain causes of death that occur primarily in the population under 65 may be associated with income inequality. Comparison of analytical techniques also suggests coefficients for income inequality in previous multilevel mortality studies may be biased, but further research is needed to provide a definitive answer.

A Multilevel Study of Students in Vietnam: Drinking Motives and Drinking Context as Predictors of Alcohol Consumption

PubMed Central

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

Disentangling WTP per QALY data: different analytical approaches, different answers.

PubMed

Gyrd-Hansen, Dorte; Kjaer, Trine

2012-03-01

A large random sample of the Danish general population was asked to value health improvements by way of both the time trade-off elicitation technique and willingness-to-pay (WTP) using contingent valuation methods. The data demonstrate a high degree of heterogeneity across respondents in their relative valuations on the two scales. This has implications for data analysis. We show that the estimates of WTP per QALY are highly sensitive to the analytical strategy. For both open-ended and dichotomous choice data we demonstrate that choice of aggregated approach (ratios of means) or disaggregated approach (means of ratios) affects estimates markedly as does the interpretation of the constant term (which allows for disproportionality across the two scales) in the regression analyses. We propose that future research should focus on why some respondents are unwilling to trade on the time trade-off scale, on how to interpret the constant value in the regression analyses, and on how best to capture the heterogeneity in preference structures when applying mixed multinomial logit. Copyright © 2011 John Wiley & Sons, Ltd.

The association between second-hand smoke exposure and depressive symptoms among pregnant women.

PubMed

Huang, Jingya; Wen, Guoming; Yang, Weikang; Yao, Zhenjiang; Wu, Chuan'an; Ye, Xiaohua

2017-10-01

Tobacco smoking and depression are strongly associated, but the possible association between second-hand smoke (SHS) exposure and depression is unclear. This study aimed to examine the possible relation between SHS exposure and depressive symptoms among pregnant women. A cross-sectional survey was conducted in Shenzhen, China, using a multistage sampling method. The univariable and multivariable logistic regression models were used to explore the associations between SHS exposure and depressive symptoms. Among 2176 pregnant women, 10.5% and 2.0% were classified as having probable and severe depressive symptoms. Both binary and multinomial logistic regression revealed that there were significantly increased risks of severe depressive symptoms corresponding to SHS exposure in homes or regular SHS exposure in workplaces using no exposure as reference. In addition, greater frequency of SHS exposure was significantly associated with the increased risk of severe depressive symptoms. Our findings suggest that SHS exposure is positively associated with depressive symptoms in a dose-response manner among the pregnant women. Copyright © 2017 Elsevier B.V. All rights reserved.

The Association Between Perceived Discrimination and Obesity in a Population-Based Multiracial and Multiethnic Adult Sample

PubMed Central

Williams, David R.

2009-01-01

Objectives. We examined whether perceived chronic discrimination was related to excess body fat accumulation in a random, multiethnic, population-based sample of US adults. Methods. We used multivariate multinomial logistic regression and logistic regression analyses to examine the relationship between interpersonal experiences of perceived chronic discrimination and body mass index and high-risk waist circumference. Results. Consistent with other studies, our analyses showed that perceived unfair treatment was associated with increased abdominal obesity. Compared with Irish, Jewish, Polish, and Italian Whites who did not experience perceived chronic discrimination, Irish, Jewish, Polish, and Italian Whites who perceived chronic discrimination were 2 to 6 times more likely to have a high-risk waist circumference. No significant relationship between perceived discrimination and the obesity measures was found among the other Whites, Blacks, or Hispanics. Conclusions. These findings are not completely unsupported. White ethnic groups including Polish, Italians, Jews, and Irish have historically been discriminated against in the United States, and other recent research suggests that they experience higher levels of perceived discrimination than do other Whites and that these experiences adversely affect their health. PMID:18923119

Gender differences in social support and leisure-time physical activity.

PubMed

Oliveira, Aldair J; Lopes, Claudia S; Rostila, Mikael; Werneck, Guilherme Loureiro; Griep, Rosane Härter; Leon, Antônio Carlos Monteiro Ponce de; Faerstein, Eduardo

2014-08-01

To identify gender differences in social support dimensions' effect on adults' leisure-time physical activity maintenance, type, and time. Longitudinal study of 1,278 non-faculty public employees at a university in Rio de Janeiro, RJ, Southeastern Brazil. Physical activity was evaluated using a dichotomous question with a two-week reference period, and further questions concerning leisure-time physical activity type (individual or group) and time spent on the activity. Social support was measured with the Medical Outcomes Study Social Support Scale. For the analysis, logistic regression models were adjusted separately by gender. A multinomial logistic regression showed an association between material support and individual activities among women (OR = 2.76; 95%CI 1.2;6.5). Affective support was associated with time spent on leisure-time physical activity only among men (OR = 1.80; 95%CI 1.1;3.2). All dimensions of social support that were examined influenced either the type of, or the time spent on, leisure-time physical activity. In some social support dimensions, the associations detected varied by gender. Future studies should attempt to elucidate the mechanisms involved in these gender differences.

An Original Stepwise Multilevel Logistic Regression Analysis of Discriminatory Accuracy: The Case of Neighbourhoods and Health

PubMed Central

Wagner, Philippe; Ghith, Nermin; Leckie, George

2016-01-01

Background and Aim Many multilevel logistic regression analyses of “neighbourhood and health” focus on interpreting measures of associations (e.g., odds ratio, OR). In contrast, multilevel analysis of variance is rarely considered. We propose an original stepwise analytical approach that distinguishes between “specific” (measures of association) and “general” (measures of variance) contextual effects. Performing two empirical examples we illustrate the methodology, interpret the results and discuss the implications of this kind of analysis in public health. Methods We analyse 43,291 individuals residing in 218 neighbourhoods in the city of Malmö, Sweden in 2006. We study two individual outcomes (psychotropic drug use and choice of private vs. public general practitioner, GP) for which the relative importance of neighbourhood as a source of individual variation differs substantially. In Step 1 of the analysis, we evaluate the OR and the area under the receiver operating characteristic (AUC) curve for individual-level covariates (i.e., age, sex and individual low income). In Step 2, we assess general contextual effects using the AUC. Finally, in Step 3 the OR for a specific neighbourhood characteristic (i.e., neighbourhood income) is interpreted jointly with the proportional change in variance (i.e., PCV) and the proportion of ORs in the opposite direction (POOR) statistics. Results For both outcomes, information on individual characteristics (Step 1) provide a low discriminatory accuracy (AUC = 0.616 for psychotropic drugs; = 0.600 for choosing a private GP). Accounting for neighbourhood of residence (Step 2) only improved the AUC for choosing a private GP (+0.295 units). High neighbourhood income (Step 3) was strongly associated to choosing a private GP (OR = 3.50) but the PCV was only 11% and the POOR 33%. Conclusion Applying an innovative stepwise multilevel analysis, we observed that, in Malmö, the neighbourhood context per se had a negligible influence on individual use of psychotropic drugs, but appears to strongly condition individual choice of a private GP. However, the latter was only modestly explained by the socioeconomic circumstances of the neighbourhoods. Our analyses are based on real data and provide useful information for understanding neighbourhood level influences in general and on individual use of psychotropic drugs and choice of GP in particular. However, our primary aim is to illustrate how to perform and interpret a multilevel analysis of individual heterogeneity in social epidemiology and public health. Our study shows that neighbourhood “effects” are not properly quantified by reporting differences between neighbourhood averages but rather by measuring the share of the individual heterogeneity that exists at the neighbourhood level. PMID:27120054

Composite Linear Models | Division of Cancer Prevention

Cancer.gov

By Stuart G. Baker The composite linear models software is a matrix approach to compute maximum likelihood estimates and asymptotic standard errors for models for incomplete multinomial data. It implements the method described in Baker SG. Composite linear models for incomplete multinomial data. Statistics in Medicine 1994;13:609-622. The software includes a library of thirty

The Source of Adult Age Differences in Event-Based Prospective Memory: A Multinomial Modeling Approach

ERIC Educational Resources Information Center

Smith, Rebekah E.; Bayen, Ute J.

2006-01-01

Event-based prospective memory involves remembering to perform an action in response to a particular future event. Normal younger and older adults performed event-based prospective memory tasks in 2 experiments. The authors applied a formal multinomial processing tree model of prospective memory (Smith & Bayen, 2004) to disentangle age differences…

Examining the association between race, ethnicity, and health status: do assets matter?

PubMed

Boyas, Javier; Shobe, Marcia A; Hannam, Holly M

2009-10-01

The current study employs data from the 2004 Immigration and Intergenerational Mobility in Metropolitan Los Angeles (IIMMLA) study to examine the degree to which observed differences in self-reported health status between African Americans, Asians, Latinos, and non-Hispanic Whites in the United States can be attributed to differences in various indicators of socioeconomic status. Results of the multinomial logistic regression techniques suggest that socioeconomic indicators had varying significant effects in predicting self-reported health status among all racial and ethnic groups. Among African Americans, homeownership, income, and age played a significant role. Among Asian Americans, only income and age significantly predicted health status. Among Latinos, income, having a checking account, and age significantly shaped health status, while education, age, and homeownership significantly predicted health status among non-Hispanic Whites.

Planning for health: a community-based spatial analysis of park availability and chronic disease across the lifespan.

PubMed

Besenyi, Gina M; Kaczynski, Andrew T; Stanis, Sonja A Wilhelm; Bergstrom, Ryan D; Lightner, Joseph S; Hipp, J Aaron

2014-05-01

The purpose of this study was to explore the spatial relationship between park availability and chronic health conditions (CHCs) across age groups in Kansas City, MO. Multinomial logistic regression examined the association between having a park within one-half mile from home and the likelihood of having 0, 1, or 2 or more CHCs. Among respondents aged 40-59, those without a park within one-half mile from home were more than twice as likely to have 2 or more CHCs compared to respondents that had a park nearby. Parks may be an important protective factor for chronic diseases, especially among middle-aged adults among whom access to neighborhood recreational environments may be particularly important. Copyright © 2014 Elsevier Ltd. All rights reserved.

Sleep duration and health correlates among university students in 26 countries.

PubMed

Peltzer, Karl; Pengpid, Supa

2016-01-01

The aim of this study was to investigate sleep duration and its health correlates in university students from 26 low-, middle- and high-income countries. Using anonymous questionnaires and anthropometric measurements, data were collected from 19417 undergraduate university students (mean age 20.8, SD = 2.8) from 27 universities from 26 countries across Asia, Africa and the Americas. Results indicate that the average number of self-reported hours of sleep was 7.07 (CI = 7.04-7.09), with the prevalence of reporting ≤ 6, 7-8, and ≥ 9 h sleep duration of 39.2, 46.9, and 13.9%, respectively. Multinomial logistic regression found that sociodemographic variables, health risk behaviour and health status variables were found to be associated with short and long sleep duration.

Ecstasy Use and Suicidal Behavior Among Adolescents: Findings from a National Survey

PubMed Central

Kim, Jueun; Fan, Bin; Liu, Xinhua; Kerner, Nancy; Wu, Ping

2011-01-01

This study examines the relationship between ecstasy use and suicidal behaviors among adolescents in the United States. Data from the adolescent subsample (ages 12–17, N=19,301) of the 2000 NHSDA were used in the analyses. Information on adolescent substance use, suicidal behaviors and related socio-demographic, family and individual factors was obtained in the survey. The rate of past year suicide attempt among adolescents with lifetime ecstasy use was almost double that of adolescents who had used other drugs only, and nine times that of adolescents with no history of illicit drug use. In multinomial logistic regression analyses, controlling for related factors, the effect of ecstasy use remained significant. Adolescent ecstasy users may require enhanced suicide prevention and intervention efforts. PMID:21631573

Women's labor force participation in later life: the effects of early work and family experiences.

PubMed

Pienta, A M; Burr, J A; Mutchler, J E

1994-09-01

The purpose of this study was to develop and evaluate a model of labor force participation among a group of older women in the United States. A comprehensive measure of women's combined work and family experiences across the adult life course was created. Employing data from the 1984 Survey of Income and Program Participation, we applied multinomial logistic regression techniques to examine the association between work-family experiences and later life labor supply. Our findings generally support an attachment hypothesis, showing that women who were the most work-oriented throughout the life course were more likely than women who experienced family-related spells of nonlabor-market activity to participate in the labor force, either full-time or part-time, later in life.

Factors Associated with Alcohol Use Before or During Sex Among Men Who Have Sex with Men in a Large Internet Sample from Asia

PubMed Central

Guadamuz, Thomas E.; Lim, Sin How; Koe, Stuart; Wei, Chongyi

2016-01-01

Abstract We explored factors associated with alcohol use before or during sex among a sample of 10,861 men who have sex with men (MSM) in Asia who were recruited online for the study. Multinomial logistic regression analysis indicated that having sex under the influence of alcohol was associated with having multiple male partners, seeking partners primarily through gay bar/gym/dance party/friends, selling sex and using multiple drugs during the past 6 months, and unprotected anal sex. More efforts are needed to better assess alcohol use and misuse among MSM in Asia and understand contextual influences on alcohol use and HIV-related behaviors in order to implement culturally-specific interventions. PMID:26789393

Smoking, alcohol consumption and betal-quid chewing among young adult Myanmar laborers in Thailand.

PubMed

Htin, Kyaw; Howteerakull, Nopporn; Suwannapong, Nawarat; TipayamongkholgulI, Mathuros

2014-07-01

Health-risk behaviors among young adults are a serious public health problem. This cross sectional study aimed to estimate the prevalence of single and concurrent multiple health-risk behaviors: smoking tobacco, consuming alcohol, and chewing betel quid among young adult Myanmar laborers in Mae Sot District, Tak Province, Thailand. Three hundred Myanmar laborers, aged 18-24 years, were interviewed using a structured questionnaire. About 33.6% reported no risk behaviors, 24.7% had one, and 41.7% had two or three risk behaviors. Multinomial logistic regression analysis showed six variables were significantly associated with health-risk behaviors: male gender, high/moderate custom/traditional influences, friends who smoked/consumed alcohol/chewed betel quid, and exposure to betel-quid chewing by other family members.

Unmarried Mothers’ Postnatal School Enrollment: The Role and Intersection of Demographic and Socioeconomic Characteristics

PubMed Central

Radey, Melissa

2017-01-01

Drawing from a theoretical model of educational decisions and intersectionality theory, this study examined demographic, socioeconomic, and public assistance characteristics that influence unmarried mothers’ postnatal enrollment. Using the Fragile Families and Child Wellbeing Study (FFCWS), binomial and multinomial regression techniques were used to examine unmarried mothers’ enrollment in their child’s first nine years. Results showed unmarried mothers’ educational commitment coupled with the influence of race and class indicate that they need additional opportunities to optimize their educations and job opportunities. Targeting outreach and enrollment assistance to underrepresented groups can reduce social-origin inequalities. Important directions for future research include understanding unmarried mothers’ rationale for school enrollment and considering how race and class work in combination to support or deter enrollment. PMID:29151656

Neighborhood social capital and crime victimization: comparison of spatial regression analysis and hierarchical regression analysis.

PubMed

Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro

2012-11-01

Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan. Copyright © 2012 Elsevier Ltd. All rights reserved.

Area-level poverty and preterm birth risk: A population-based multilevel analysis

PubMed Central

DeFranco, Emily A; Lian, Min; Muglia, Louis A; Schootman, Mario

2008-01-01

Background Preterm birth is a complex disease with etiologic influences from a variety of social, environmental, hormonal, genetic, and other factors. The purpose of this study was to utilize a large population-based birth registry to estimate the independent effect of county-level poverty on preterm birth risk. To accomplish this, we used a multilevel logistic regression approach to account for multiple co-existent individual-level variables and county-level poverty rate. Methods Population-based study utilizing Missouri's birth certificate database (1989–1997). We conducted a multilevel logistic regression analysis to estimate the effect of county-level poverty on PTB risk. Of 634,994 births nested within 115 counties in Missouri, two levels were considered. Individual-level variables included demographics factors, prenatal care, health-related behavioral risk factors, and medical risk factors. The area-level variable included the percentage of the population within each county living below the poverty line (US census data, 1990). Counties were divided into quartiles of poverty; the first quartile (lowest rate of poverty) was the reference group. Results PTB < 35 weeks occurred in 24,490 pregnancies (3.9%). The rate of PTB < 35 weeks was 2.8% in counties within the lowest quartile of poverty and increased through the 4th quartile (4.9%), p < 0.0001. High county-level poverty was significantly associated with PTB risk. PTB risk (< 35 weeks) was increased for women who resided in counties within the highest quartile of poverty, adjusted odds ratio (adjOR) 1.18 (95% CI 1.03, 1.35), with a similar effect at earlier gestational ages (< 32 weeks), adjOR 1.27 (95% CI 1.06, 1.52). Conclusion Women residing in socioeconomically deprived areas are at increased risk of preterm birth, above other underlying risk factors. Although the risk increase is modest, it affects a large number of pregnancies. PMID:18793437

Area-level poverty and preterm birth risk: a population-based multilevel analysis.

PubMed

DeFranco, Emily A; Lian, Min; Muglia, Louis A; Schootman, Mario

2008-09-15

Preterm birth is a complex disease with etiologic influences from a variety of social, environmental, hormonal, genetic, and other factors. The purpose of this study was to utilize a large population-based birth registry to estimate the independent effect of county-level poverty on preterm birth risk. To accomplish this, we used a multilevel logistic regression approach to account for multiple co-existent individual-level variables and county-level poverty rate. Population-based study utilizing Missouri's birth certificate database (1989-1997). We conducted a multilevel logistic regression analysis to estimate the effect of county-level poverty on PTB risk. Of 634,994 births nested within 115 counties in Missouri, two levels were considered. Individual-level variables included demographics factors, prenatal care, health-related behavioral risk factors, and medical risk factors. The area-level variable included the percentage of the population within each county living below the poverty line (US census data, 1990). Counties were divided into quartiles of poverty; the first quartile (lowest rate of poverty) was the reference group. PTB < 35 weeks occurred in 24,490 pregnancies (3.9%). The rate of PTB < 35 weeks was 2.8% in counties within the lowest quartile of poverty and increased through the 4th quartile (4.9%), p < 0.0001. High county-level poverty was significantly associated with PTB risk. PTB risk (< 35 weeks) was increased for women who resided in counties within the highest quartile of poverty, adjusted odds ratio (adj OR) 1.18 (95% CI 1.03, 1.35), with a similar effect at earlier gestational ages (< 32 weeks), adj OR 1.27 (95% CI 1.06, 1.52). Women residing in socioeconomically deprived areas are at increased risk of preterm birth, above other underlying risk factors. Although the risk increase is modest, it affects a large number of pregnancies.

Risk of maternal mortality in women with severe anaemia during pregnancy and post partum: a multilevel analysis.

PubMed

Daru, Jahnavi; Zamora, Javier; Fernández-Félix, Borja M; Vogel, Joshua; Oladapo, Olufemi T; Morisaki, Naho; Tunçalp, Özge; Torloni, Maria Regina; Mittal, Suneeta; Jayaratne, Kapila; Lumbiganon, Pisake; Togoobaatar, Ganchimeg; Thangaratinam, Shakila; Khan, Khalid S

2018-05-01

Anaemia affects as many as half of all pregnant women in low-income and middle-income countries, but the burden of disease and associated maternal mortality are not robustly quantified. We aimed to assess the association between severe anaemia and maternal death with data from the WHO Multicountry Survey on maternal and newborn health. We used multilevel and propensity score regression analyses to establish the relation between severe anaemia and maternal death in 359 health facilities in 29 countries across Latin America, Africa, the Western Pacific, eastern Mediterranean, and southeast Asia. Severe anaemia was defined as antenatal or postnatal haemoglobin concentrations of less than 70 g/L in a blood sample obtained before death. Maternal death was defined as death any time after admission until the seventh day post partum or discharge. In regression analyses, we adjusted for post-partum haemorrhage, general anaesthesia, admission to intensive care, sepsis, pre-eclampsia or eclampsia, thrombocytopenia, shock, massive transfusion, severe oliguria, failure to form clots, and severe acidosis as confounding variables. These variables were used to develop the propensity score. 312 281 women admitted in labour or with ectopic pregnancies were included in the adjusted multilevel logistic analysis, and 12 470 were included in the propensity score regression analysis. The adjusted odds ratio for maternal death in women with severe anaemia compared with those without severe anaemia was 2·36 (95% CI 1·60-3·48). In the propensity score analysis, severe anaemia was also associated with maternal death (adjusted odds ratio 1·86 [95% CI 1·39-2·49]). Prevention and treatment of anaemia during pregnancy and post partum should remain a global public health and research priority. Barts and the London Charity. Copyright This is an Open Access article published under the CC BY 3.0 IGO license which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. In any use of this article, there should be no suggestion that WHO endorses any specific organisation, products or services. The use of the WHO logo is not permitted. This notice should be preserved along with the article's original URL.

A Regression Framework for Effect Size Assessments in Longitudinal Modeling of Group Differences

PubMed Central

Feingold, Alan

2013-01-01

The use of growth modeling analysis (GMA)--particularly multilevel analysis and latent growth modeling--to test the significance of intervention effects has increased exponentially in prevention science, clinical psychology, and psychiatry over the past 15 years. Model-based effect sizes for differences in means between two independent groups in GMA can be expressed in the same metric (Cohen’s d) commonly used in classical analysis and meta-analysis. This article first reviews conceptual issues regarding calculation of d for findings from GMA and then introduces an integrative framework for effect size assessments that subsumes GMA. The new approach uses the structure of the linear regression model, from which effect sizes for findings from diverse cross-sectional and longitudinal analyses can be calculated with familiar statistics, such as the regression coefficient, the standard deviation of the dependent measure, and study duration. PMID:23956615

Who Is Overeducated and Why? Probit and Dynamic Mixed Multinomial Logit Analyses of Vertical Mismatch in East and West Germany

ERIC Educational Resources Information Center

Boll, Christina; Leppin, Julian Sebastian; Schömann, Klaus

2016-01-01

Overeducation potentially signals a productivity loss. With Socio-Economic Panel data from 1984 to 2011 we identify drivers of educational mismatch for East and West medium and highly educated Germans. Addressing measurement error, state dependence and unobserved heterogeneity, we run dynamic mixed multinomial logit models for three different…

Sex, price and preferences: accounting for unsafe sexual practices in prostitution markets.

PubMed

Adriaenssens, Stef; Hendrickx, Jef

2012-06-01

Unsafe sexual practices are persistent in prostitution interactions: one in four contacts can be called unsafe. The determinants of this are still matter for debate. We account for the roles played by clients' preferences and the hypothetical price premium of unsafe sexual practices with the help of a large dataset of clients' self-reported commercial sexual transactions in Belgium and The Netherlands. Almost 25,000 reports were collected, representing the whole gamut of prostitution market segments. The first set of explanations consists of an analysis of the price-fixing elements of paid sex. With the help of the so-called hedonic pricing method we test for the existence of a price incentive for unsafe sex. In accordance with the results from studies in some prostitution markets in the developing world, the study replicates a significant wage penalty for condom use of an estimated 7.2 per cent, confirmed in both multilevel and fixed-effects regressions. The second part of the analysis reconstructs the demand side basis of this wage penalty: the consistent preference of clients of prostitution for unsafe sex. This study is the first to document empirically clients' preference for intercourse without a condom, with the help of a multilevel ordinal regression. © 2011 The Authors. Sociology of Health & Illness © 2011 Foundation for the Sociology of Health & Illness/Blackwell Publishing Ltd.

Multilevel regularized regression for simultaneous taxa selection and network construction with metagenomic count data.

PubMed

Liu, Zhenqiu; Sun, Fengzhu; Braun, Jonathan; McGovern, Dermot P B; Piantadosi, Steven

2015-04-01

Identifying disease associated taxa and constructing networks for bacteria interactions are two important tasks usually studied separately. In reality, differentiation of disease associated taxa and correlation among taxa may affect each other. One genus can be differentiated because it is highly correlated with another highly differentiated one. In addition, network structures may vary under different clinical conditions. Permutation tests are commonly used to detect differences between networks in distinct phenotypes, and they are time-consuming. In this manuscript, we propose a multilevel regularized regression method to simultaneously identify taxa and construct networks. We also extend the framework to allow construction of a common network and differentiated network together. An efficient algorithm with dual formulation is developed to deal with the large-scale n ≪ m problem with a large number of taxa (m) and a small number of samples (n) efficiently. The proposed method is regularized with a general Lp (p ∈ [0, 2]) penalty and models the effects of taxa abundance differentiation and correlation jointly. We demonstrate that it can identify both true and biologically significant genera and network structures. Software MLRR in MATLAB is available at http://biostatistics.csmc.edu/mlrr/. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Individual and Area Level Socioeconomic Status and Its Association with Cognitive Function and Cognitive Impairment (Low MMSE) among Community-Dwelling Elderly in Singapore.

PubMed

Wee, Liang En; Yeo, Wei Xin; Yang, Gui Rong; Hannan, Nazirul; Lim, Kenny; Chua, Christopher; Tan, Mae Yue; Fong, Nikki; Yeap, Amelia; Chen, Lionel; Koh, Gerald Choon-Huat; Shen, Han Ming

2012-01-01

Neighborhood socioeconomic status (SES) can affect cognitive function. We assessed cognitive function and cognitive impairment among community-dwelling elderly in a multi-ethnic urban low-SES Asian neighborhood and compared them with a higher-SES neighborhood. The study population involved all residents aged ≥60 years in two housing estates comprising owner-occupied housing (higher SES) and rental flats (low SES) in Singapore in 2012. Cognitive impairment was defined as <24 on the Mini Mental State Examination. Demographic/clinical details were collected via questionnaire. Multilevel linear regression was used to evaluate factors associated with cognitive function, while multilevel logistic regression determined predictors of cognitive impairment. Participation was 61.4% (558/909). Cognitive impairment was found in 26.2% (104/397) of residents in the low-SES community and in 16.1% (26/161) of residents in the higher-SES community. After adjusting for other sociodemographic variables, living in a low-SES community was independently associated with poorer cognitive function (β = -1.41, SD = 0.58, p < 0.01) and cognitive impairment (adjusted odds ratio 5.13, 95% CI 1.98-13.34). Among cognitively impaired elderly in the low-SES community, 96.2% (100/104) were newly detected. Living in a low-SES community is independently associated with cognitive impairment in an urban Asian society.

Prediction models for solitary pulmonary nodules based on curvelet textural features and clinical parameters.

PubMed

Wang, Jing-Jing; Wu, Hai-Feng; Sun, Tao; Li, Xia; Wang, Wei; Tao, Li-Xin; Huo, Da; Lv, Ping-Xin; He, Wen; Guo, Xiu-Hua

2013-01-01

Lung cancer, one of the leading causes of cancer-related deaths, usually appears as solitary pulmonary nodules (SPNs) which are hard to diagnose using the naked eye. In this paper, curvelet-based textural features and clinical parameters are used with three prediction models [a multilevel model, a least absolute shrinkage and selection operator (LASSO) regression method, and a support vector machine (SVM)] to improve the diagnosis of benign and malignant SPNs. Dimensionality reduction of the original curvelet-based textural features was achieved using principal component analysis. In addition, non-conditional logistical regression was used to find clinical predictors among demographic parameters and morphological features. The results showed that, combined with 11 clinical predictors, the accuracy rates using 12 principal components were higher than those using the original curvelet-based textural features. To evaluate the models, 10-fold cross validation and back substitution were applied. The results obtained, respectively, were 0.8549 and 0.9221 for the LASSO method, 0.9443 and 0.9831 for SVM, and 0.8722 and 0.9722 for the multilevel model. All in all, it was found that using curvelet-based textural features after dimensionality reduction and using clinical predictors, the highest accuracy rate was achieved with SVM. The method may be used as an auxiliary tool to differentiate between benign and malignant SPNs in CT images.

Is an index of co-occurring unhealthy lifestyles suitable for understanding migrant health?

PubMed

Feng, Xiaoqi; Astell-Burt, Thomas; Kolt, Gregory S

2014-12-01

This study investigated variation in unhealthy lifestyles within Australia according to where people were born. Multilevel linear regression models were used to explore variation in co-occurring unhealthy lifestyles (from 0 to 8) constructed from responses to tobacco smoking, alcohol consumption, moderate-to-vigorous physical activity and a range of dietary indicators for 217,498 adults born in 22 different countries now living in Australia. Models were adjusted for socio-economic variables. Data was from the 45 and Up Study (2006-2009). Further analyses involved multilevel logistic regression to examine country-of-birth patterning of each individual unhealthy lifestyle. Small differences in the co-occurrence of unhealthy lifestyles were observed by country of birth, ranging from 3.1 (Philippines) to 3.8 (Russia). More substantial variation was observed for each individual unhealthy lifestyle. Smoking and alcohol ranged from 7.3% and 4.2% (both China) to 28.5% (Lebanon) and 30.8% (Ireland) respectively. Non-adherence to physical activity guidelines was joint-highest among participants born in Japan and China (both 74.5%), but lowest among those born in Scandinavian countries (52.5%). Substantial variation in meeting national dietary guidelines was also evident between participants born in different countries. The growing trend for constructing unhealthy lifestyle indices can hide important variation in individual unhealthy lifestyles by country of birth. Copyright © 2014. Published by Elsevier Inc.

The nonmedical use of prescription medicines among high school students: a cross-sectional study in Southern China.

PubMed

Wang, Hui; Deng, Jianxiong; Zhou, Xiaolan; Lu, Ciyong; Huang, Jinghui; Huang, Guoliang; Gao, Xue; He, Yuan

2014-08-01

The objective of this study was to examine the prevalence of the nonmedical use of prescription medicines (NMUPM) and the association between NMUPM and demographic, family and school factors. A cross-sectional study was conducted from 2007 to 2009. A total of 21,672 middle and high school students were surveyed in seven cities of Guangdong Province. Self-reported NMUPM and information regarding family and school factors were collected. Multilevel logistic regression analyses were used to explore potentially influential factors. Of the total sample, the mean age was 16 (±1.9) years. Approximately 6.0% of respondents reported lifetime NMUPM. The most common nonmedically used prescription drug among NMUPM users was scattered analgesics, at approximately 3.9%, followed by cough medicine with codeine (2.1%). Multilevel logistic regression analysis indicated that living arrangements, available money, social friends, and smoking were significantly correlated with NMUPM among boys and girls. Academic achievement and family relationships were only significantly correlated with NMUPM among girls, and communication with parents was only associated with NMUPM among boys. These results indicate that NMUPM represented a considerable problem for particular subgroups of adolescents. A well-established surveillance system and target intervention programs are needed given the potential long-term negative outcomes of NMUPM. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Linking Health System Responsiveness to Political Rights and Civil Liberties: A Multilevel Analysis Using Data From 44 Countries.

PubMed

Witvliet, Margot I; Stronks, Karien; Kunst, Anton E; Mahapatra, Tanmay; Arah, Onyebuchi A

2015-01-01

Responsiveness is a dimension of health system functioning and might be dependent upon contextual factors related to politics. Given this, we performed cross-national comparisons with the aim of investigating: 1) the associations of political factors with patients' reports of health system responsiveness and 2) the extent to which health input and output might explain these associations. World Health Survey data were analyzed for 44 countries (n = 103 541). Main outcomes included, respectively, 8 and 7 responsiveness domains for inpatient and outpatient care. Linear multilevel regressions were used to assess the associations of politics (namely, civil liberties and political rights), socioeconomic development, health system input, and health system output (measured by maternal mortality) with responsiveness domains, adjusted for demographic factors. Political rights showed positive associations with dignity (regression coefficient = 0.086 [standard error = 0.039]), quality (0.092 [0.049]), and support (0.113 [0.048]) for inpatient care and with dignity (0.075 [0.040]), confidentiality (0.089 [0.043]), and quality (0.124 [0.053]) for outpatient care. Positive associations were observed for civil liberties as well. Health system input and output reduced observed associations. Results tentatively suggest that strengthening political rights and, to a certain extent, civil liberties might improve health system responsiveness, in part through their effect on health system input and output. © The Author(s) 2015.

Association of Brain-Derived Neurotrophic Factor and Vitamin D with Depression and Obesity: A Population-Based Study.

PubMed

Goltz, Annemarie; Janowitz, Deborah; Hannemann, Anke; Nauck, Matthias; Hoffmann, Johanna; Seyfart, Tom; Völzke, Henry; Terock, Jan; Grabe, Hans Jörgen

2018-06-19

Depression and obesity are widespread and closely linked. Brain-derived neurotrophic factor (BDNF) and vitamin D are both assumed to be associated with depression and obesity. Little is known about the interplay between vitamin D and BDNF. We explored the putative associations and interactions between serum BDNF and vitamin D levels with depressive symptoms and abdominal obesity in a large population-based cohort. Data were obtained from the population-based Study of Health in Pomerania (SHIP)-Trend (n = 3,926). The associations of serum BDNF and vitamin D levels with depressive symptoms (measured using the Patient Health Questionnaire) were assessed with binary and multinomial logistic regression models. The associations of serum BDNF and vitamin D levels with obesity (measured by the waist-to-hip ratio [WHR]) were assessed with binary logistic and linear regression models with restricted cubic splines. Logistic regression models revealed inverse associations of vitamin D with depression (OR = 0.966; 95% CI 0.951-0.981) and obesity (OR = 0.976; 95% CI 0.967-0.985). No linear association of serum BDNF with depression or obesity was found. However, linear regression models revealed a U-shaped association of BDNF with WHR (p < 0.001). Vitamin D was inversely associated with depression and obesity. BDNF was associated with abdominal obesity, but not with depression. At the population level, our results support the relevant roles of vitamin D and BDNF in mental and physical health-related outcomes. © 2018 S. Karger AG, Basel.

The role of perceived social support in loneliness and self-esteem among children affected by HIV/AIDS: a longitudinal multilevel analysis in rural China.

PubMed

Qiao, Shan; Li, Xiaoming; Zhao, Guoxiang; Zhao, Junfeng; Stanton, Bonita

2014-07-01

To delineate the trajectories of loneliness and self-esteem over time among children affected by parental HIV and AIDS, and to examine how their perceived social support (PSS) influenced initial scores and change rates of these two psychological outcomes. We collected longitudinal data from children affected by parental HIV/AIDS in rural central China. Children 6-18 years of age at baseline were eligible to participate in the study and were assessed annually for 3 years. Multilevel regression models for change were used to assess the effect of baseline PSS on the trajectories of loneliness and self-esteem over time. We employed maximum likelihood estimates to fit multilevel models and specified the between-individual covariance matrix as 'unstructured' to allow correlation among the different sources of variance. Statistics including -2 Log Likelihood, Akaike Information Criterion and Bayesian Information Criterion were used in evaluating the model fit. The results of multilevel analyses indicated that loneliness scores significantly declined over time. Controlling for demographic characteristics, children with higher PSS reported significantly lower baseline loneliness score and experienced a slower rate of decline in loneliness over time. Children with higher PSS were more likely to report higher self-esteem scores at baseline. However, the self-esteem scores remained stable over time controlling for baseline PSS and all the other variables. The positive effect of PSS on psychological adjustment may imply a promising approach for future intervention among children affected by HIV/AIDS, in which efforts to promote psychosocial well being could focus on children and families with lower social support. We also call for a greater understanding of children's psychological adjustment process in various contexts of social support and appropriate adaptations of evidence-based interventions to meet their diverse needs.

Overweight and obesity in India: policy issues from an exploratory multi-level analysis.

PubMed

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.

Multinomial Logistic Regression & Bootstrapping for Bayesian Estimation of Vertical Facies Prediction in Heterogeneous Sandstone Reservoirs

NASA Astrophysics Data System (ADS)

Al-Mudhafar, W. J.

2013-12-01

Precisely prediction of rock facies leads to adequate reservoir characterization by improving the porosity-permeability relationships to estimate the properties in non-cored intervals. It also helps to accurately identify the spatial facies distribution to perform an accurate reservoir model for optimal future reservoir performance. In this paper, the facies estimation has been done through Multinomial logistic regression (MLR) with respect to the well logs and core data in a well in upper sandstone formation of South Rumaila oil field. The entire independent variables are gamma rays, formation density, water saturation, shale volume, log porosity, core porosity, and core permeability. Firstly, Robust Sequential Imputation Algorithm has been considered to impute the missing data. This algorithm starts from a complete subset of the dataset and estimates sequentially the missing values in an incomplete observation by minimizing the determinant of the covariance of the augmented data matrix. Then, the observation is added to the complete data matrix and the algorithm continues with the next observation with missing values. The MLR has been chosen to estimate the maximum likelihood and minimize the standard error for the nonlinear relationships between facies & core and log data. The MLR is used to predict the probabilities of the different possible facies given each independent variable by constructing a linear predictor function having a set of weights that are linearly combined with the independent variables by using a dot product. Beta distribution of facies has been considered as prior knowledge and the resulted predicted probability (posterior) has been estimated from MLR based on Baye's theorem that represents the relationship between predicted probability (posterior) with the conditional probability and the prior knowledge. To assess the statistical accuracy of the model, the bootstrap should be carried out to estimate extra-sample prediction error by randomly drawing datasets with replacement from the training data. Each sample has the same size of the original training set and it can be conducted N times to produce N bootstrap datasets to re-fit the model accordingly to decrease the squared difference between the estimated and observed categorical variables (facies) leading to decrease the degree of uncertainty.

Exploring consumers’ attitudes towards informal patient payments using the combined method of cluster and multinomial regression analysis - the case of Hungary

PubMed Central

2013-01-01

Background Previous studies on informal patient payments have mostly focused on the magnitude and determinants of these payments while the attitudes of health care actors towards these payments are less well known. This study aims to reveal the attitudes of Hungarian health care consumers towards informal payments to provide a better understanding of this phenomenon. Methods For the analysis, we use data from a survey carried out in 2010 in Hungary involving a representative sample of 1037 respondents. We use cluster analysis to identify the main attitude groups related to informal payments based on the respondents’ perception of and behavior related to informal payments. Multinomial logistic regression is applied to examine the differences between these groups in terms of socio-demographic characteristics, as well as past utilization and informal payments paid for health care services. Results We identified three main different attitudes towards informal payments: accepting informal payments, doubting about informal payments and opposing informal payments. Those who accept informal payments (mostly young or elderly people, living in the capital) consider these payments as an expression of gratitude and perceive them as inevitable due to the low funding of the health care system. Those who doubt about informal payments (mostly respondents outside the capital, with higher education and higher household income) are not certain whether these payments are inevitable, perceive them as similar to corruption rather than gratitude, and would rather use private services to avoid these payments. We find that the opposition to informal payments (mostly among men from small households and low income households) can be explained by their lower ability and willingness to pay. Conclusions A large share of Hungarian health care consumers has a rather positive attitude towards informal payments, perceiving them as “inevitable due to the low funding of the health care system”. From a policy point-of-view, the change of this consumer attitude will be essential to deal with these payments in addition to other policy strategies. PMID:23414488

The Inaccuracy of Patient Recall for COPD Exacerbation Rate Estimation and Its Implications: Results from Central Adjudication.

PubMed

Frei, Anja; Siebeling, Lara; Wolters, Callista; Held, Leonhard; Muggensturm, Patrick; Strassmann, Alexandra; Zoller, Marco; Ter Riet, Gerben; Puhan, Milo A

2016-10-01

COPD exacerbation incidence rates are often ascertained retrospectively through patient recall and self-reports. We compared exacerbation ascertainment through patient self-reports and single-physician chart review to central adjudication by a committee and explored determinants and consequences of misclassification. Self-reported exacerbations (event-based definition) in 409 primary care patients with COPD participating in the International Collaborative Effort on Chronic Obstructive Lung Disease: Exacerbation Risk Index Cohorts (ICE COLD ERIC) cohort were ascertained every 6 months over 3 years. Exacerbations were adjudicated by single experienced physicians and an adjudication committee who had information from patient charts. We assessed the accuracy (sensitivities and specificities) of self-reports and single-physician chart review against a central adjudication committee (AC) (reference standard). We used multinomial logistic regression and bootstrap stability analyses to explore determinants of misclassifications. The AC identified 648 exacerbations, corresponding to an incidence rate of 0.60 ± 0.83 exacerbations/patient-year and a cumulative incidence proportion of 58.9%. Patients self-reported 841 exacerbations (incidence rate, 0.75 ± 1.01; incidence proportion, 59.7%). The sensitivity and specificity of self-reports were 84% and 76%, respectively, those of single-physician chart review were between 89% and 96% and 87% and 99%, respectively. The multinomial regression model and bootstrap selection showed that having experienced more exacerbations was the only factor consistently associated with underreporting and overreporting of exacerbations (underreporters: relative risk ratio [RRR], 2.16; 95% CI, 1.76-2.65 and overreporters: RRR, 1.67; 95% CI, 1.39-2.00). Patient 6-month recall of exacerbation events are inaccurate. This may lead to inaccurate estimates of incidence measures and underestimation of treatment effects. The use of multiple data sources combined with event adjudication could substantially reduce sample size requirements and possibly cost of studies. www.ClinicalTrials.gov, NCT00706602. Copyright © 2016 American College of Chest Physicians. Published by Elsevier Inc. All rights reserved.

Help-Seeking in People with Exceptional Experiences: Results from a General Population Sample

PubMed Central

Landolt, Karin; Wittwer, Amrei; Wyss, Thomas; Unterassner, Lui; Fach, Wolfgang; Krummenacher, Peter; Brugger, Peter; Haker, Helene; Kawohl, Wolfram; Schubiger, Pius August; Folkers, Gerd; Rössler, Wulf

2014-01-01

Background: Exceptional experiences (EE) are experiences that deviate from ordinary experiences, for example precognition, supernatural appearances, or déjà vues. In spite of the high frequency of EE in the general population, little is known about their effect on mental health and about the way people cope with EE. This study aimed to assess the quality and quantity of EE in persons from the Swiss general population, to identify the predictors of their help-seeking, and to determine how many of them approach the mental health system. Methods: An on-line survey was used to evaluate a quota sample of 1580 persons representing the Swiss general population with respect to gender, age, and level of education. Multinomial logistic regression was applied to integrate help-seeking, self-reported mental disorder, and other variables in a statistical model designed to identify predictors of help-seeking in persons with EE. Results: Almost all participants (91%) experienced at least one EE. Generally, help-seeking was more frequent when the EE were of negative valence. Help-seeking because of EE was less frequent in persons without a self-reported mental disorder (8.6%) than in persons with a disorder (35.1%) (OR = 5.7). Even when frequency and attributes of EE were controlled for, people without a disorder sought four times less often help because of EE than expected. Persons with a self-reported diagnosis of mental disorder preferred seeing a mental health professional. Multinomial regression revealed a preference for healers in women with less education, who described themselves as believing and also having had more impressive EE. Conclusion: Persons with EE who do not indicate a mental disorder less often sought help because of EE than persons who indicated a mental disorder. We attribute this imbalance to a high inhibition threshold to seek professional help. Moreover, especially less educated women did not approach the mental health care system as often as other persons with EE, but preferred seeing a healer. PMID:24904915

Determinants of financial performance of home-visit nursing agencies in Japan.

PubMed

Fukui, Sakiko; Yoshiuchi, Kazuhiro; Fujita, Junko; Ikezaki, Sumie

2014-01-09

Japan has the highest aging population in the world and promotion of home health services is an urgent policy issue. As home-visit nursing plays a major role in home health services, the Japanese government began promotion of this activity in 1994. However, the scale of home-visit nursing agencies has remained small (the average numbers of nursing staff and other staff were 4.2 and 1.7, respectively, in 2011) and financial performance (profitability) is a concern in such small agencies. Additionally, the factors related to profitability in home-visit nursing agencies in Japan have not been examined multilaterally and in detail. Therefore, the purpose of the study was to examine the determinants of financial performance of home-visit nursing agencies. We performed a nationwide survey of 2,912 randomly selected home-visit nursing agencies in Japan. Multinomial logistic regression was used to clarify the determinants of profitability of the agency (profitable, stable or unprofitable) based on variables related to management of the agency (operating structure, management by a nurse manager, employment, patient utilization, quality control, regional cooperation, and financial condition). Among the selected home-visit nursing agencies, responses suitable for analysis were obtained from 1,340 (effective response rate, 46.0%). Multinomial logistic regression analysis showed that both profitability and unprofitability were related to multiple variables in management of the agency when compared to agencies with stable financial performance. These variables included the number of nursing staff/rehabilitation staff/patients, being owned by a hospital, the number of cooperative hospitals, home-death rate among terminal patients, controlling staff objectives by nurse managers, and income going to compensation. The results suggest that many variables in management of a home-visit nursing agency, including the operating structure of the agency, regional cooperation, staff employment, patient utilization, and quality control of care, have an influence in both profitable and unprofitable agencies. These findings indicate the importance of consideration of management issues in achieving stable financial performance in home-visit nursing agencies in Japan. The findings may also be useful in other countries with growing aging populations.

Association of childhood abuse with homeless women's social networks.

PubMed

Green, Harold D; Tucker, Joan S; Wenzel, Suzanne L; Golinelli, Daniela; Kennedy, David P; Ryan, Gery W; Zhou, Annie J

2012-01-01

Childhood abuse has been linked to negative sequelae for women later in life including drug and alcohol use and violence as victim or perpetrator and may also affect the development of women's social networks. Childhood abuse is prevalent among at-risk populations of women (such as the homeless) and thus may have a stronger impact on their social networks. We conducted a study to: (a) develop a typology of sheltered homeless women's social networks; (b) determine whether childhood abuse was associated with the social networks of sheltered homeless women; and (c) determine whether those associations remained after accounting for past-year substance abuse and recent intimate partner abuse. A probability sample of 428 homeless women from temporary shelter settings in Los Angeles County completed a personal network survey that provided respondent information as well as information about their network members' demographics and level of interaction with each other. Cluster analyses identified groups of women who shared specific social network characteristics. Multinomial logistic regressions revealed variables associated with group membership. We identified three groups of women with differing social network characteristics: low-risk networks, densely connected risky networks (dense, risky), and sparsely connected risky networks (sparse, risky). Multinomial logistic regressions indicated that membership in the sparse, risky network group, when compared to the low-risk group, was associated with history of childhood physical abuse (but not sexual or emotional abuse). Recent drug abuse was associated with membership in both risky network groups; however, the association of childhood physical abuse with sparse, risky network group membership remained. Although these findings support theories proposing that the experience of childhood abuse can shape women's social networks, they suggest that it may be childhood physical abuse that has the most impact among homeless women. The effects of childhood physical abuse should be more actively investigated in clinical settings, especially those frequented by homeless women, particularly with respect to the formation of social networks in social contexts that may expose these women to greater risks. Copyright © 2012. Published by Elsevier Ltd.

The prevalence of underweight, overweight and obesity and their related socio-demographic and lifestyle factors among adult women in Myanmar, 2015-16

PubMed Central

Hong, Seo Ah; Lwin, Kyi Tun; Aung, La Seng

2018-01-01

Background The aim of the study was to estimate the prevalence of underweight and overweight or obesity and their socio-demographic and lifestyle factors in a female adult population in Myanmar. Material and methods In a national cross-sectional population-based survey in the 2015–16 Myanmar Demographic and Health Survey, 12,160 women aged 18–49 years and not currently pregnant completed questionnaires and anthropometric measurements. Nutritional status was determined using Asian body mass index cut-offs: underweight (BMI<18.5 kg/m2), overweight (23.0–27.4 kg/m2), and obesity (≥27.5 kg/m2). Multinomial logistic regression modelling was used to determine the association between socio-demographic and lifestyle factors and weight status. Results The prevalence of underweight was 14.1%, overweight 28.1% and obesity 13.1%. Among different age groups, the prevalence of underweight was the highest among 18 to 29 year-olds (20.2%), while overweight or obesity was the highest in the age group 30 to 49 years (around 50%). In multinomial logistic regression, being 30 to 49 years old, poorer and richer wealth status, living in all the other regions of Myanmar and ever contraceptive use were inversely and current tobacco use, not working and having less than two children ever born were positively associated with underweight relative to normal weight. Older age, having secondary education, urban residence, wealthier economic status, living with a partner, living in the Northern and Southern regions of Myanmar, having less than two children ever born and having ever used contraceptives were positively and current tobacco use was negatively associated with overweight or obesity relative to normal weight. Conclusions A dual burden of both underweight and overweight or obesity among female adults was found in Myanmar. Sociodemographic and health risk behaviour factors were identified for underweight and overweight or obesity that can guide public health interventions to address both of these conditions. PMID:29547655

The relationship between red blood cell distribution width and blood pressure abnormal dipping in patients with essential hypertension: a cross-sectional study.

PubMed

Su, Dan; Guo, Qi; Gao, Ya; Han, Jin; Yan, Bin; Peng, Liyuan; Song, Anqi; Zhou, Fuling; Wang, Gang

2016-02-23

To investigate whether red blood cell distribution width (RDW) is associated with the blood pressure (BP) reverse-dipper pattern in patients with hypertension. Cross-sectional study. Single centre. Patients with essential hypertension were included in our study (n=708). The exclusion criteria included age <18 or >90 years, incomplete clinical data, night workers, diagnosis of secondary hypertension, under antihypertensive treatment, intolerance for the 24 h ambulatory BP monitoring (ABPM) and BP reading success rate <70%. Physical examination and ABPM were performed for all patients in our study. The value of RDW was measured using an automated haematology analyser. The distribution of RDW in patients with hypertension among different circadian BP pattern groups was analyzed using analysis of variance (ANOVA). Multinomial logistic regression was applied to explore the associations of RDW and other relevant variables with ABPM results. There was significantly increased RDW in reverse dippers (13.52 ± 1.05) than dippers (13.25 ± 0.85) of hypertension (p=0.012). Moreover, multinomial logistic regression analysis showed that RDW (OR 1.325, 95% CI 1.037 to 1.692, p=0.024) and diabetes mellitus (OR 2.286, 95% CI 1.380 to 3.788, p=0.001) were significantly different when comparing the reverse-dipper BP pattern with the dipper pattern. However, there was no difference of RDW between the non-dipper pattern and the reverse-dipper pattern (OR 1.036, 95% CI 0.867 to 1.238, p=0.693). In addition to this, RDW was negatively correlated with the decline rate of nocturnal systolic BP (r=-0.113; p=0.003) and diastolic BP (r=-0.101; p=0.007). Our results suggested that RDW might associate with the abnormal dipper BP patterns of either reverse dipping or non-dipping homogeneously examined with 24 h ABPM. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Determinants of financial performance of home-visit nursing agencies in Japan

PubMed Central

2014-01-01

Background Japan has the highest aging population in the world and promotion of home health services is an urgent policy issue. As home-visit nursing plays a major role in home health services, the Japanese government began promotion of this activity in 1994. However, the scale of home-visit nursing agencies has remained small (the average numbers of nursing staff and other staff were 4.2 and 1.7, respectively, in 2011) and financial performance (profitability) is a concern in such small agencies. Additionally, the factors related to profitability in home-visit nursing agencies in Japan have not been examined multilaterally and in detail. Therefore, the purpose of the study was to examine the determinants of financial performance of home-visit nursing agencies. Methods We performed a nationwide survey of 2,912 randomly selected home-visit nursing agencies in Japan. Multinomial logistic regression was used to clarify the determinants of profitability of the agency (profitable, stable or unprofitable) based on variables related to management of the agency (operating structure, management by a nurse manager, employment, patient utilization, quality control, regional cooperation, and financial condition). Results Among the selected home-visit nursing agencies, responses suitable for analysis were obtained from 1,340 (effective response rate, 46.0%). Multinomial logistic regression analysis showed that both profitability and unprofitability were related to multiple variables in management of the agency when compared to agencies with stable financial performance. These variables included the number of nursing staff/rehabilitation staff/patients, being owned by a hospital, the number of cooperative hospitals, home-death rate among terminal patients, controlling staff objectives by nurse managers, and income going to compensation. Conclusions The results suggest that many variables in management of a home-visit nursing agency, including the operating structure of the agency, regional cooperation, staff employment, patient utilization, and quality control of care, have an influence in both profitable and unprofitable agencies. These findings indicate the importance of consideration of management issues in achieving stable financial performance in home-visit nursing agencies in Japan. The findings may also be useful in other countries with growing aging populations. PMID:24400964

Relation of socio-economic status to impaired fasting glucose and Type 2 diabetes: findings based on a large population-based cross-sectional study in Tianjin, China.

PubMed

Zhang, H; Xu, W; Dahl, A K; Xu, Z; Wang, H-X; Qi, X

2013-05-01

Studies on the relationship between socio-economic status and Type 2 diabetes mellitus in the Chinese population are sparse. We aimed to examine the relation of socio-economic status as represented by income, education and occupation to impaired fasting glucose, Type 2 diabetes, and the control of Type 2 diabetes in a large Chinese population. This study included 7315 individuals who were aged 20-79 years and living in Tianjin, China. Impaired fasting glucose and Type 2 diabetes were ascertained according to the 1999 World Health Organization criteria. Data were analysed using multinomial and binary logistic regression, with adjustment for potential confounders. Among all participants, 532 (7.3%) persons had impaired fasting glucose, 688 (9.4%) persons had Type 2 diabetes, including 288 (3.9%) previously undiagnosed Type 2 diabetes. In fully adjusted multinomial logistic regression, compared with higher income (≥ 2000 yuan, $243.3/month), lower income (< 1000 yuan, $121.70/month) showed odds ratios (95% confidence intervals) of 3.31 (2.48-4.41) for impaired fasting glucose, 4.50 (3.07-6.61) for undiagnosed Type 2 diabetes and 4.56 (3.20-6.48) for diagnosed Type 2 diabetes. These results remained significant in the analysis stratified by education and occupation. Furthermore, persons who were retired were more likely to have impaired fasting glucose [odds ratio 1.91 (1.40-2.45)], undiagnosed Type 2 diabetes [odds ratio 2.01) 1.40-2.89] and diagnosed Type 2 diabetes [odds ratio 3.02 (2.12-4.22)]. Among the patients with Type 2 diabetes previously diagnosed, lower education (less than senior high school), non-manual work and unemployment were related to worse glycaemic control (fasting blood glucose level > 8.5 mmol/l). Lower income and retirement are associated with increased odds of impaired fasting glucose and Type 2 diabetes in Tianjin, China. Education and occupation may play a role in glycaemic control among patients with Type 2 diabetes. © 2013 The Authors. Diabetic Medicine © 2013 Diabetes UK.

Infection and Co-infection with Helminths and Plasmodium among School Children in Côte d’Ivoire: Results from a National Cross-Sectional Survey

PubMed Central

Yapi, Richard B.; Hürlimann, Eveline; Houngbedji, Clarisse A.; Ndri, Prisca B.; Silué, Kigbafori D.; Soro, Gotianwa; Kouamé, Ferdinand N.; Vounatsou, Penelope; Fürst, Thomas; N’Goran, Eliézer K.; Utzinger, Jürg; Raso, Giovanna

2014-01-01

Background Helminth infection and malaria remain major causes of ill-health in the tropics and subtropics. There are several shared risk factors (e.g., poverty), and hence, helminth infection and malaria overlap geographically and temporally. However, the extent and consequences of helminth-Plasmodium co-infection at different spatial scales are poorly understood. Methodology This study was conducted in 92 schools across Côte d’Ivoire during the dry season, from November 2011 to February 2012. School children provided blood samples for detection of Plasmodium infection, stool samples for diagnosis of soil-transmitted helminth (STH) and Schistosoma mansoni infections, and urine samples for appraisal of Schistosoma haematobium infection. A questionnaire was administered to obtain demographic, socioeconomic, and behavioral data. Multinomial regression models were utilized to determine risk factors for STH-Plasmodium and Schistosoma-Plasmodium co-infection. Principal Findings Complete parasitological and questionnaire data were available for 5,104 children aged 5-16 years. 26.2% of the children were infected with any helminth species, whilst the prevalence of Plasmodium infection was 63.3%. STH-Plasmodium co-infection was detected in 13.5% and Schistosoma-Plasmodium in 5.6% of the children. Multinomial regression analysis revealed that boys, children aged 10 years and above, and activities involving close contact to water were significantly and positively associated with STH-Plasmodium co-infection. Boys, wells as source of drinking water, and water contact were significantly and positively associated with Schistosoma-Plasmodium co-infection. Access to latrines, deworming, higher socioeconomic status, and living in urban settings were negatively associated with STH-Plasmodium co-infection; whilst use of deworming drugs and access to modern latrines were negatively associated with Schistosoma-Plasmodium co-infection. Conclusions/Significance More than 60% of the school children surveyed were infected with Plasmodium across Côte d’Ivoire, and about one out of six had a helminth-Plasmodium co-infection. Our findings provide a rationale to combine control interventions that simultaneously aim at helminthiases and malaria. PMID:24901333

Dental caries clusters among adolescents.

PubMed

Warren, John J; Van Buren, John M; Levy, Steven M; Marshall, Teresa A; Cavanaugh, Joseph E; Curtis, Alexandra M; Kolker, Justine L; Weber-Gasparoni, Karin

2017-12-01

There have been very few longitudinal studies of dental caries in adolescents, and little study of the caries risk factors in this age group. The purpose of this study was to describe different caries trajectories and associated risk factors among members of the Iowa Fluoride Study (IFS) cohort. The IFS recruited a birth cohort from 1992 to 1995, and has gathered dietary, fluoride and behavioural data at least twice yearly since recruitment. Examinations for dental caries were completed when participants were ages 5, 9, 13 and 17 years. For this study, only participants with decayed and filled surface (DFS) caries data at ages 9, 13 and 17 were included (N=396). The individual DFS counts at age 13 and the DFS increment from 13 to 17 were used to identify distinct caries trajectories using Ward's hierarchical clustering algorithm. A number of multinomial logistic regression models were developed to predict trajectory membership, using longitudinal dietary, fluoride and demographic/behavioural data from 9 to 17 years. Model selection was based on the akaike information criterion (AIC). Several different trajectory schemes were considered, and a three-trajectory scheme-no DFS at age 17 (n=142), low DFS (n=145) and high DFS (n=109)-was chosen to balance sample sizes and interpretability. The model selection process resulted in use of an arithmetic average for dietary variables across the period from 9 to 17 years. The multinomial logistic regression model with the best fit included the variables maternal education level, 100% juice consumption, brushing frequency and sex. Other favoured models also included water and milk consumption and home water fluoride concentration. The high caries cluster was most consistently associated with lower maternal education level, lower 100% juice consumption, lower brushing frequency and being female. The use of a clustering algorithm and use of Akaike's Information Criterion (AIC) to determine the best representation of the data were useful means in presenting longitudinal caries data. Findings suggest that high caries incidence in adolescence is associated with lower maternal educational level, less frequent tooth brushing, lower 100% juice consumption and being female. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Contraceptive Sterilization: Introducing A Couple Perspective to Examine Sociodemographic Differences in Use.

PubMed

Eeckhaut, Mieke C W

2017-09-01

Most studies of contraceptive use have relied solely on the woman's perspective, but because men's attitudes and preferences are also important, analytic approaches based on couples should also be explored. Data from the 2006-2010 and 2011-2013 rounds of the National Survey of Family Growth yielded a sample of 4,591 men and women who were married or cohabiting with an opposite-sex partner and who had completed their intended childbearing. Respondents' reports of both their own and their partners' characteristics and behaviors were employed in two sets of analyses examining educational and racial and ethnic differences in contraceptive use: an individualistic approach (using multinomial logistic regression) and a couple approach (using multinomial logistic diagonal reference models). In the full model using the individualistic approach, respondents with less than a high school education were less likely than those with at least a college degree to rely on male sterilization (odds ratios, 0.1-0.2) or a reversible method (0.4-0.5), as opposed to female sterilization. Parallel analyses limited to couples in which partners had the same educational levels (i.e., educationally homogamous couples) showed an even greater difference between those with the least and those with the most schooling (0.03 for male sterilization and 0.2 for a reversible method). When race and ethnicity, which had a much higher level of homogamy, were examined, the approaches yielded more similar results. Research on contraceptive use can benefit from a couple approach, particularly when focusing on partners' characteristics for which homogamy is relatively low. Copyright © 2017 by the Guttmacher Institute.

Hospital financial position and the adoption of electronic health records.

PubMed

Ginn, Gregory O; Shen, Jay J; Moseley, Charles B

2011-01-01

The objective of this study was to examine the relationship between financial position and adoption of electronic health records (EHRs) in 2442 acute care hospitals. The study was cross-sectional and utilized a general linear mixed model with the multinomial distribution specification for data analysis. We verified the results by also running a multinomial logistic regression model. To measure our variables, we used data from (1) the 2007 American Hospital Association (AHA) electronic health record implementation survey, (2) the 2006 Centers for Medicare and Medicaid Cost Reports, and (3) the 2006 AHA Annual Survey containing organizational and operational data. Our dependent variable was an ordinal variable with three levels used to indicate the extent of EHR adoption by hospitals. Our independent variables were five financial ratios: (1) net days revenue in accounts receivable, (2) total margin, (3) the equity multiplier, (4) total asset turnover, and (5) the ratio of total payroll to total expenses. For control variables, we used (1) bed size, (2) ownership type, (3) teaching affiliation, (4) system membership, (5) network participation, (6) fulltime equivalent nurses per adjusted average daily census, (7) average daily census per staffed bed, (8) Medicare patients percentage, (9) Medicaid patients percentage, (10) capitation-based reimbursement, and (11) nonconcentrated market. Only liquidity was significant and positively associated with EHR adoption. Asset turnover ratio was significant but, unexpectedly, was negatively associated with EHR adoption. However, many control variables, most notably bed size, showed significant positive associations with EHR adoption. Thus, it seems that hospitals adopt EHRs as a strategic move to better align themselves with their environment.

Drivers of multidimensional eco-innovation: empirical evidence from the Brazilian industry.

PubMed

da Silva Rabêlo, Olivan; de Azevedo Melo, Andrea Sales Soares

2018-03-08

The study analyses the relationships between the main drivers of eco-innovation introduced by innovative industries, focused on cooperation strategy. Eco-innovation is analysed by means of a multidimensional identification strategy, showing the relationships between the independent variables and the variable of interest. The literature discussing environmental innovation is different from the one discussing other types of innovation inasmuch as it seeks to grasp its determinants and to mostly highlight the relevance of environmental regulation. The key feature of this paper is that it ascribes special relevance to cooperation strategy with external partners and to the propensity of innovative industry introducing eco-innovation. A sample of 35,060 Brazilian industries were analysed, between 2003 and 2011, by means of Binomial, Multinomial and Ordinal logistic regressions with microdata collected with the research and innovation department (PINTEC) from the Brazilian Institute of Geography and Statistics (Instituto Brasileiro de Geografia e Estatística). The econometric results estimated by the Logit Multinomial method suggest that the cooperation with external partners practiced by innovative industries facilitates the adoption of eco-innovation in dimension 01 with probability of 64.59%, 57.63% in dimension 02 and 81.02% in dimension 03. The data reveal that the higher the degree of eco-innovation complexity, the harder industries seek to obtain cooperation with external partners. When calculating with the Logit Ordinal and Binomial models, cooperation increases the probability that the industry is eco-innovative in 65.09% and 89.34%, respectively. Environmental regulation and innovation in product and information management were also positively correlated as drivers of eco-innovation.

Occupational outcomes of adult childhood cancer survivors: A report from the Childhood Cancer Survivor Study

PubMed Central

Kirchhoff, Anne C.; Krull, Kevin R.; Ness, Kirsten K.; Park, Elyse R.; Oeffinger, Kevin C.; Hudson, Melissa M.; Stovall, Marilyn; Robison, Leslie L.; Wickizer, Thomas; Leisenring, Wendy

2010-01-01

Background We examined whether survivors from the Childhood Cancer Survivor Study were less likely to be in higher skill occupations than a sibling comparison and whether certain survivors were at higher risk. Methods We created three mutually-exclusive occupational categories for participants aged ≥25 years: Managerial/Professional and Non-Physical and Physical Service/Blue Collar. We examined currently employed survivors (N=4845) and siblings (N=1727) in multivariable generalized linear models to evaluate the likelihood of being in the three occupational categories. Among all participants, we used multinomial logistic regression to examine the likelihood of these outcomes in comparison to being unemployed (survivors N=6671; siblings N=2129). Multivariable linear models were used to assess survivor occupational differences by cancer and treatment variables. Personal income was compared by occupation. Results Employed survivors were less often in higher skilled Managerial/Professional occupations (Relative Risk=0.93, 95% Confidence Interval 0.89–0.98) than siblings. Survivors who were Black, were diagnosed at a younger age, or had high-dose cranial radiation were less likely to hold Professional occupations than other survivors. In multinomial models, female survivors’ likelihood of being in full-time Professional occupations (27%) was lower than male survivors (42%) and female (41%) and male (50%) siblings. Survivors’ personal income was lower than siblings within each of the three occupational categories in models adjusted for sociodemographic variables. Conclusions Adult childhood cancer survivors are employed in lower skill jobs than siblings. Survivors with certain treatment histories are at higher risk and may require vocational assistance throughout adulthood. PMID:21246530

Maintaining Continuity of Care for Nursing Home Residents: Effect of States’ Medicaid Bed-Hold Policies and Reimbursement Rates

PubMed Central

Intrator, Orna; Schleinitz, Mark; Grabowski, David C; Zinn, Jacqueline; Mor, Vincent

2009-01-01

Objective Recent public concern in response to states’ intended repeal of Medicaid bed-hold policies and report of their association with higher hospitalization rates prompts examination of these policies in ensuring continuity of care within the broader context of Medicaid policies. Data Sources/Study Design Minimum Data Set assessments of long-stay nursing home residents in April–June 2000 linked to Medicare claims enabled tracking residents’ hospitalizations during the ensuing 5 months and determining hospital discharge destination. Multinomial multilevel models estimated the effect of state policies on discharge destination controlling for resident, hospitalization, nursing home, and market characteristics. Results Among 77,955 hospitalizations, 5,797 (7.4 percent) were not discharged back to the baseline nursing home. Bed-hold policies were associated with lower odds of transfer to another nursing home (AOR=0.55, 95 percent CI 0.52–0.58) and higher odds of hospitalization (AOR=1.36), translating to 9.5 fewer nursing home transfers and 77.9 more hospitalizations per 1,000 residents annually, and costing Medicaid programs about $201,311. Higher Medicaid reimbursement rates were associated with lower odds of transfer. Conclusions Bed-hold policies were associated with greater continuity of NH care; however, their high cost compared with their small impact on transfer but large impact on increased hospitalizations suggests that they may not be effective. PMID:18783452

Perceptions of community, social capital, and how they affect self-reported health: a multilevel analysis.

PubMed

Dziadkowiec, O; Meissen, G J; Merkle, E C

2017-11-01

The link between social capital and self-reported health has been widely explored. On the other hand, we know less about the relationship between social capital, community socioeconomic characteristics, and non-social capital-related individual differences, and about their impact on self-reported health in community settings. Cross-sectional study design with a proportional sample of 7965 individuals from 20 US communities were analyzed using multilevel linear regression models, where individuals were nested within communities. The response rates ranged from 13.5% to 25.4%. Findings suggest that perceptions of the community and individual level socioeconomic characteristics were stronger predictors of self-reported health than were social capital or community socioeconomic characteristics. Policy initiatives aimed at increasing social capital should first assess community member's perceptions of their communities to uncover potential assets to help increase social capital. Copyright © 2017 The Royal Society for Public Health. Published by Elsevier Ltd. All rights reserved.

Does workplace social capital buffer the effects of job stress? A cross-sectional, multilevel analysis of cigarette smoking among U.S. manufacturing workers

PubMed Central

Sapp, Amy L.; Kawachi, Ichiro; Sorensen, Glorian; LaMontagne, Anthony D.; Subramanian, S.V.

2010-01-01

Objective To investigate whether workplace social capital buffers the association between job stress and smoking status. Methods As part of the Harvard Cancer Prevention Project’s Healthy Directions-Small Business Study, interviewer-administered questionnaires were completed by 1740 workers and 288 managers in 26 manufacturing firms (84% and 85% response). Social capital was assessed by multiple items measured at the individual-level among workers, and contextual-level among managers. Job stress was operationalized by the demand-control model. Multilevel logistic regression was used to estimate associations between job stressors and smoking, and test for effect modification by social capital measures. Results Workplace social capital (both summary measures) buffered associations between high job demands and smoking. One compositional item—worker trust in managers—buffered associations between job strain and smoking. Conclusion Workplace social capital may modify the effects of psychosocial working conditions on health behaviors. PMID:20595910

Associations between state minimum wage policy and health care access: a multi-level analysis of the 2004 Behavioral Risk Factor survey.

PubMed

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.

Lean production tools and decision latitude enable conditions for innovative learning in organizations: a multilevel analysis.

PubMed

Fagerlind Ståhl, Anna-Carin; Gustavsson, Maria; Karlsson, Nadine; Johansson, Gun; Ekberg, Kerstin

2015-03-01

The effect of lean production on conditions for learning is debated. This study aimed to investigate how tools inspired by lean production (standardization, resource reduction, visual monitoring, housekeeping, value flow analysis) were associated with an innovative learning climate and with collective dispersion of ideas in organizations, and whether decision latitude contributed to these associations. A questionnaire was sent out to employees in public, private, production and service organizations (n = 4442). Multilevel linear regression analyses were used. Use of lean tools and decision latitude were positively associated with an innovative learning climate and collective dispersion of ideas. A low degree of decision latitude was a modifier in the association to collective dispersion of ideas. Lean tools can enable shared understanding and collective spreading of ideas, needed for the development of work processes, especially when decision latitude is low. Value flow analysis played a pivotal role in the associations. Copyright © 2014 Elsevier Ltd and The Ergonomics Society. All rights reserved.