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,…

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.

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…

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.

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.

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 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

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.

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…

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.,…

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.

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…

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

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.

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.

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…

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.

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.

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…

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).

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…

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.

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.

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.

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.

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.

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

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.

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.

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.

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…

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.

[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.

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.

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

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…

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…

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

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/.

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.

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…

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…

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 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

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.

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.

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…

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…

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.

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

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

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

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.

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.

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.

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…

On the Multilevel Nature of Meta-Analysis: A Tutorial, Comparison of Software Programs, and Discussion of Analytic Choices.

PubMed

Pastor, Dena A; Lazowski, Rory A

2018-01-01

The term "multilevel meta-analysis" is encountered not only in applied research studies, but in multilevel resources comparing traditional meta-analysis to multilevel meta-analysis. In this tutorial, we argue that the term "multilevel meta-analysis" is redundant since all meta-analysis can be formulated as a special kind of multilevel model. To clarify the multilevel nature of meta-analysis the four standard meta-analytic models are presented using multilevel equations and fit to an example data set using four software programs: two specific to meta-analysis (metafor in R and SPSS macros) and two specific to multilevel modeling (PROC MIXED in SAS and HLM). The same parameter estimates are obtained across programs underscoring that all meta-analyses are multilevel in nature. Despite the equivalent results, not all software programs are alike and differences are noted in the output provided and estimators available. This tutorial also recasts distinctions made in the literature between traditional and multilevel meta-analysis as differences between meta-analytic choices, not between meta-analytic models, and provides guidance to inform choices in estimators, significance tests, moderator analyses, and modeling sequence. The extent to which the software programs allow flexibility with respect to these decisions is noted, with metafor emerging as the most favorable program reviewed.

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.

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.

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…

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 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.

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.

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.

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.

Multi-level analysis in information systems research: the case of enterprise resource planning system usage in China

NASA Astrophysics Data System (ADS)

Sun, Yuan; Bhattacherjee, Anol

2011-11-01

Information technology (IT) usage within organisations is a multi-level phenomenon that is influenced by individual-level and organisational-level variables. Yet, current theories, such as the unified theory of acceptance and use of technology, describe IT usage as solely an individual-level phenomenon. This article postulates a model of organisational IT usage that integrates salient organisational-level variables such as user training, top management support and technical support within an individual-level model to postulate a multi-level model of IT usage. The multi-level model was then empirically validated using multi-level data collected from 128 end users and 26 managers in 26 firms in China regarding their use of enterprise resource planning systems and analysed using the multi-level structural equation modelling (MSEM) technique. We demonstrate the utility of MSEM analysis of multi-level data relative to the more common structural equation modelling analysis of single-level data and show how single-level data can be aggregated to approximate multi-level analysis when multi-level data collection is not possible. We hope that this article will motivate future scholars to employ multi-level data and multi-level analysis for understanding organisational phenomena that are truly multi-level in nature.

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.

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…

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.

A cross-sectional study of workplace social capital and blood pressure: a multilevel analysis at Japanese manufacturing companies.

PubMed

Fujino, Yoshihisa; Kubo, Tatsuhiko; Kunimoto, Masamizu; Tabata, Hidetoshi; Tsuchiya, Takuto; Kadowaki, Koji; Nakamura, Takehiro; Oyama, Ichiro

2013-01-01

We examined the contextual effect of workplace social capital on systolic blood pressure (SBP). Cross-sectional. A conglomerate from 58 workplaces in Japan. Of the 5844 workers at a Japanese conglomerate from 58 workplaces, 5368 were recruited. Individuals who received drugs for hypertension (n=531) and who lacked information on any variable (n=167) were excluded from the analyses, leaving 4735 individuals (3281 men and 1454 women) for inclusion. Systolic blood pressure. The contextual effect of workplace social capital on SBP was examined using a multilevel regression analysis with a random intercept. Coworker support had a contextual effect at the workplace level (coefficient=-1.97, p=0.043), while a lack of trust for coworkers (coefficient=0.27, p=0.039) and lack of helpfulness from coworkers were associated with SBP (coefficient=0.28, p=0.002). The present study suggested that social capital at the workplace level has beneficial effects on SBP.

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 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…

Examining the relationships between life satisfaction and alcohol, tobacco and marijuana use among school-aged children.

PubMed

Lew, D; Xian, H; Qian, Z; Vaughn, M G

2018-05-03

There are many known risk factors associated with youth substance use. Nonetheless, the impact of life satisfaction (LS) on the use of alcohol, tobacco and marijuana by adolescents still remains largely unknown. The present analysis utilized data from the Health Behavior in School-Aged Children 2009-10 US study. Multilevel logistic regression models were used to assess the relationship between LS and individual substance use. Multilevel multinomial regression models examined the relationship with total number of substances used. After controlling for numerous variables associated with substance use, individuals reporting low LS were significantly more likely to ever use tobacco (OR = 1.34, 95% CI = [1.01, 1.78]), alcohol (OR = 1.45, 95% CI = [1.10, 1.92]) and marijuana (OR = 1.98, 95% CI = [1.39, 2.82]). Additionally, students with low LS were significantly more likely to use two substances (OR = 1.90, 95% CI = [1.15, 3.14]) and three substances concurrently (OR = 2.00, 95% CI = [1.27, 3.16]). The present study identified strong associations between LS and individual, as well as concurrent, substance use among adolescents. Interventions aiming to reduce adolescent substance use may benefit from incorporating components to improve LS.

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.

Quantitative analysis of organizational culture in occupational health research: a theory-based validation in 30 workplaces of the organizational culture profile instrument.

PubMed

Marchand, Alain; Haines, Victor Y; Dextras-Gauthier, Julie

2013-05-04

This study advances a measurement approach for the study of organizational culture in population-based occupational health research, and tests how different organizational culture types are associated with psychological distress, depression, emotional exhaustion, and well-being. Data were collected over a sample of 1,164 employees nested in 30 workplaces. Employees completed the 26-item OCP instrument. Psychological distress was measured with the General Health Questionnaire (12-item); depression with the Beck Depression Inventory (21-item); and emotional exhaustion with five items from the Maslach Burnout Inventory general survey. Exploratory factor analysis evaluated the dimensionality of the OCP scale. Multilevel regression models estimated workplace-level variations, and the contribution of organizational culture factors to mental health and well-being after controlling for gender, age, and living with a partner. Exploratory factor analysis of OCP items revealed four factors explaining about 75% of the variance, and supported the structure of the Competing Values Framework. Factors were labeled Group, Hierarchical, Rational and Developmental. Cronbach's alphas were high (0.82-0.89). Multilevel regression analysis suggested that the four culture types varied significantly between workplaces, and correlated with mental health and well-being outcomes. The Group culture type best distinguished between workplaces and had the strongest associations with the outcomes. This study provides strong support for the use of the OCP scale for measuring organizational culture in population-based occupational health research in a way that is consistent with the Competing Values Framework. The Group organizational culture needs to be considered as a relevant factor in occupational health studies.

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.

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 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.

Establishing a Mathematical Equations and Improving the Production of L-tert-Leucine by Uniform Design and Regression Analysis.

PubMed

Jiang, Wei; Xu, Chao-Zhen; Jiang, Si-Zhi; Zhang, Tang-Duo; Wang, Shi-Zhen; Fang, Bai-Shan

2017-04-01

L-tert-Leucine (L-Tle) and its derivatives are extensively used as crucial building blocks for chiral auxiliaries, pharmaceutically active ingredients, and ligands. Combining with formate dehydrogenase (FDH) for regenerating the expensive coenzyme NADH, leucine dehydrogenase (LeuDH) is continually used for synthesizing L-Tle from α-keto acid. A multilevel factorial experimental design was executed for research of this system. In this work, an efficient optimization method for improving the productivity of L-Tle was developed. And the mathematical model between different fermentation conditions and L-Tle yield was also determined in the form of the equation by using uniform design and regression analysis. The multivariate regression equation was conveniently implemented in water, with a space time yield of 505.9 g L -1  day -1 and an enantiomeric excess value of >99 %. These results demonstrated that this method might become an ideal protocol for industrial production of chiral compounds and unnatural amino acids such as chiral drug intermediates.

Modeling Longitudinal Data Containing Non-Normal Within Subject Errors

NASA Technical Reports Server (NTRS)

Feiveson, Alan; Glenn, Nancy L.

2013-01-01

The mission of the National Aeronautics and Space Administration’s (NASA) human research program is to advance safe human spaceflight. This involves conducting experiments, collecting data, and analyzing data. The data are longitudinal and result from a relatively few number of subjects; typically 10 – 20. A longitudinal study refers to an investigation where participant outcomes and possibly treatments are collected at multiple follow-up times. Standard statistical designs such as mean regression with random effects and mixed–effects regression are inadequate for such data because the population is typically not approximately normally distributed. Hence, more advanced data analysis methods are necessary. This research focuses on four such methods for longitudinal data analysis: the recently proposed linear quantile mixed models (lqmm) by Geraci and Bottai (2013), quantile regression, multilevel mixed–effects linear regression, and robust regression. This research also provides computational algorithms for longitudinal data that scientists can directly use for human spaceflight and other longitudinal data applications, then presents statistical evidence that verifies which method is best for specific situations. This advances the study of longitudinal data in a broad range of applications including applications in the sciences, technology, engineering and mathematics fields.

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

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.

[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.

[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.

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.

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.

Social cohesion matters in health.

PubMed

Chuang, Ying-Chih; Chuang, Kun-Yang; Yang, Tzu-Hsuan

2013-10-28

The concept of social cohesion has invoked debate due to the vagueness of its definition and the limitations of current measurements. This paper attempts to examine the concept of social cohesion, develop measurements, and investigate the relationship between social cohesion and individual health. This study used a multilevel study design. The individual-level samples from 29 high-income countries were obtained from the 2000 World Value Survey (WVS) and the 2002 European Value Survey. National-level social cohesion statistics were obtained from Organization of Economic Cooperation and Development datasets, World Development Indicators, and Asian Development Bank key indicators for the year 2000, and from aggregating responses from the WVS. In total 47,923 individuals were included in this study. The factor analysis was applied to identify dimensions of social cohesion, which were used as entities in the cluster analysis to generate a regime typology of social cohesion. Then, multilevel regression models were applied to assess the influences of social cohesion on an individual's self-rated health. Factor analysis identified five dimensions of social cohesion: social equality, social inclusion, social development, social capital, and social diversity. Then, the cluster analysis revealed five regimes of social cohesion. A multi-level analysis showed that respondents in countries with higher social inclusion, social capital, and social diversity were more likely to report good health above and beyond individual-level characteristics. This study is an innovative effort to incorporate different aspects of social cohesion. This study suggests that social cohesion was associated with individual self-rated after controlling individual characteristics. To achieve further advancement in population health, developed countries should consider policies that would foster a society with a high level of social inclusion, social capital, and social diversity. Future research could focus on identifying possible pathways by which social cohesion influences various health outcomes.

Testing Group Mean Differences of Latent Variables in Multilevel Data Using Multiple-Group Multilevel CFA and Multilevel MIMIC Modeling.

PubMed

Kim, Eun Sook; Cao, Chunhua

2015-01-01

Considering that group comparisons are common in social science, we examined two latent group mean testing methods when groups of interest were either at the between or within level of multilevel data: multiple-group multilevel confirmatory factor analysis (MG ML CFA) and multilevel multiple-indicators multiple-causes modeling (ML MIMIC). The performance of these methods were investigated through three Monte Carlo studies. In Studies 1 and 2, either factor variances or residual variances were manipulated to be heterogeneous between groups. In Study 3, which focused on within-level multiple-group analysis, six different model specifications were considered depending on how to model the intra-class group correlation (i.e., correlation between random effect factors for groups within cluster). The results of simulations generally supported the adequacy of MG ML CFA and ML MIMIC for multiple-group analysis with multilevel data. The two methods did not show any notable difference in the latent group mean testing across three studies. Finally, a demonstration with real data and guidelines in selecting an appropriate approach to multilevel multiple-group analysis are provided.

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.

The role of the clinical departments for understanding patient heterogeneity in one-year mortality after a diagnosis of heart failure: A multilevel analysis of individual heterogeneity for profiling provider outcomes

PubMed Central

Frølich, Anne; Merlo, Juan

2017-01-01

Purpose To evaluate the general contextual effect (GCE) of the hospital department on one-year mortality in Swedish and Danish patients with heart failure (HF) by applying a multilevel analysis of individual heterogeneity. Methods Using the Swedish patient register, we obtained data on 36,943 patients who were 45–80 years old and admitted for HF to the hospital between 2007 and 2009. From the Danish Heart Failure Database (DHFD), we obtained data on 12,001 patients with incident HF who were 18 years or older and treated at hospitals between June 2010 and June2013. For each year, we applied two-step single and multilevel logistic regression models. We evaluated the general effects of the department by quantifying the intra-class correlation coefficient (ICC) and the increment in the area under the receiver operating characteristic curve (AUC) obtained by adding the random effects of the department in a multilevel logistic regression analysis. Results One-year mortality for Danish incident HF patients was low in the three audit years (around 11.1% -13.1%) and departments performed homogeneously (ICC ≈1.5% - 3.5%). The discriminatory accuracy of a model including age and gender was rather high (AUC≈ 0.71–0.73) but the increment in AUC after adding the department random effects into these models was only about 0.011–0.022 units in the three years. One-year mortality in Swedish patients with first hospitalization for heart failure, was relatively higher for 2007–2009 (≈21.3% - 22%) and departments performed homogeneously (ICC ≈ 1.5% - 3%). The discriminatory accuracy of a model including age, gender and patient risk score was rather high (AUC≈ 0.726–0.728) but the increment in AUC after adding the department random effects was only about 0.010–0.017 units in the three years. Conclusion Using the DHFD standard benchmark for one-year mortality, Danish departments had a good, homogeneous performance. In reference to literature, Swedish departments had a homogeneous performance and the mortality rates for patients with first hospitalization for heart failure were similar to those reported since 2000. Considering this, if health authorities decide to further reduce mortality rates, a comprehensive quality strategy should focus on all Swedish hospitals. Yet, a complementary assessment for the period after the study period is required to confirm whether department performance is still homogeneous or not to determine the most appropriate action. PMID:29211785

Quantitative analysis of organizational culture in occupational health research: a theory-based validation in 30 workplaces of the organizational culture profile instrument

PubMed Central

2013-01-01

Background This study advances a measurement approach for the study of organizational culture in population-based occupational health research, and tests how different organizational culture types are associated with psychological distress, depression, emotional exhaustion, and well-being. Methods Data were collected over a sample of 1,164 employees nested in 30 workplaces. Employees completed the 26-item OCP instrument. Psychological distress was measured with the General Health Questionnaire (12-item); depression with the Beck Depression Inventory (21-item); and emotional exhaustion with five items from the Maslach Burnout Inventory general survey. Exploratory factor analysis evaluated the dimensionality of the OCP scale. Multilevel regression models estimated workplace-level variations, and the contribution of organizational culture factors to mental health and well-being after controlling for gender, age, and living with a partner. Results Exploratory factor analysis of OCP items revealed four factors explaining about 75% of the variance, and supported the structure of the Competing Values Framework. Factors were labeled Group, Hierarchical, Rational and Developmental. Cronbach’s alphas were high (0.82-0.89). Multilevel regression analysis suggested that the four culture types varied significantly between workplaces, and correlated with mental health and well-being outcomes. The Group culture type best distinguished between workplaces and had the strongest associations with the outcomes. Conclusions This study provides strong support for the use of the OCP scale for measuring organizational culture in population-based occupational health research in a way that is consistent with the Competing Values Framework. The Group organizational culture needs to be considered as a relevant factor in occupational health studies. PMID:23642223

Deepening our Understanding of Quality in Australia (DUQuA): a study protocol for a nationwide, multilevel analysis of relationships between hospital quality management systems and patient factors

PubMed Central

Taylor, Natalie; Clay-Williams, Robyn; Hogden, Emily; Pye, Victoria; Li, Zhicheng; Groene, Oliver; Suñol, Rosa; Braithwaite, Jeffrey

2015-01-01

Introduction Despite the growing body of research on quality and safety in healthcare, there is little evidence of the association between the way hospitals are organised for quality and patient factors, limiting our understanding of how to effect large-scale change. The ‘Deepening our Understanding of Quality in Australia’ (DUQuA) study aims to measure and examine relationships between (1) organisation and department-level quality management systems (QMS), clinician leadership and culture, and (2) clinical treatment processes, clinical outcomes and patient-reported perceptions of care within Australian hospitals. Methods and analysis The DUQuA project is a national, multilevel, cross-sectional study with data collection at organisation (hospital), department, professional and patient levels. Sample size calculations indicate a minimum of 43 hospitals are required to adequately power the study. To allow for rejection and attrition, 70 hospitals across all Australian jurisdictions that meet the inclusion criteria will be invited to participate. Participants will consist of hospital quality management professionals; clinicians; and patients with stroke, acute myocardial infarction and hip fracture. Organisation and department-level QMS, clinician leadership and culture, patient perceptions of safety, clinical treatment processes, and patient outcomes will be assessed using validated, evidence-based or consensus-based measurement tools. Data analysis will consist of simple correlations, linear and logistic regression and multilevel modelling. Multilevel modelling methods will enable identification of the amount of variation in outcomes attributed to the hospital and department levels, and the factors contributing to this variation. Ethics and dissemination Ethical approval has been obtained. Results will be disseminated to individual hospitals in de-identified national and international benchmarking reports with data-driven recommendations. This ground-breaking national study has the potential to influence decision-making on the implementation of quality and safety systems and processes in Australian and international hospitals. PMID:26644128

A cross-sectional study of workplace social capital and blood pressure: a multilevel analysis at Japanese manufacturing companies

PubMed Central

Fujino, Yoshihisa; Kubo, Tatsuhiko; Kunimoto, Masamizu; Tabata, Hidetoshi; Tsuchiya, Takuto; Kadowaki, Koji; Nakamura, Takehiro; Oyama, Ichiro

2013-01-01

Objectives We examined the contextual effect of workplace social capital on systolic blood pressure (SBP). Design Cross-sectional. Setting A conglomerate from 58 workplaces in Japan. Participants Of the 5844 workers at a Japanese conglomerate from 58 workplaces, 5368 were recruited. Individuals who received drugs for hypertension (n=531) and who lacked information on any variable (n=167) were excluded from the analyses, leaving 4735 individuals (3281 men and 1454 women) for inclusion. Primary and secondary outcome measures Systolic blood pressure. Results The contextual effect of workplace social capital on SBP was examined using a multilevel regression analysis with a random intercept. Coworker support had a contextual effect at the workplace level (coefficient=−1.97, p=0.043), while a lack of trust for coworkers (coefficient=0.27, p=0.039) and lack of helpfulness from coworkers were associated with SBP (coefficient=0.28, p=0.002). Conclusions The present study suggested that social capital at the workplace level has beneficial effects on SBP. PMID:23386581

Using multi-level data to estimate the effect of an 'alcogenic' environment on hazardous alcohol consumption in the former Soviet Union.

PubMed

Murphy, Adrianna; Roberts, Bayard; Ploubidis, George B; Stickley, Andrew; McKee, Martin

2014-05-01

The purpose of this study was to assess whether alcohol-related community characteristics act collectively to influence individual-level alcohol consumption in the former Soviet Union (fSU). Using multi-level data from nine countries in the fSU we conducted a factor analysis of seven alcohol-related community characteristics. The association between any latent factors underlying these characteristics and two measures of hazardous alcohol consumption was then analysed using a population average regression modelling approach. Our factor analysis produced one factor with an eigenvalue >1 (EV=1.28), which explained 94% of the variance. This factor was statistically significantly associated with increased odds of CAGE problem drinking (OR=1.40 (1.08-1.82)). The estimated association with EHD was not statistically significant (OR=1.10 (0.85-1.44)). Our findings suggest that a high number of beer, wine and spirit advertisements and high alcohol outlet density may work together to create an 'alcogenic' environment that encourages hazardous alcohol consumption in the fSU. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

[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.

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

PubMed

Karabatsos, George

2017-02-01

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

Multilevel structural equation models for assessing moderation within and across levels of analysis.

PubMed

Preacher, Kristopher J; Zhang, Zhen; Zyphur, Michael J

2016-06-01

Social scientists are increasingly interested in multilevel hypotheses, data, and statistical models as well as moderation or interactions among predictors. The result is a focus on hypotheses and tests of multilevel moderation within and across levels of analysis. Unfortunately, existing approaches to multilevel moderation have a variety of shortcomings, including conflated effects across levels of analysis and bias due to using observed cluster averages instead of latent variables (i.e., "random intercepts") to represent higher-level constructs. To overcome these problems and elucidate the nature of multilevel moderation effects, we introduce a multilevel structural equation modeling (MSEM) logic that clarifies the nature of the problems with existing practices and remedies them with latent variable interactions. This remedy uses random coefficients and/or latent moderated structural equations (LMS) for unbiased tests of multilevel moderation. We describe our approach and provide an example using the publicly available High School and Beyond data with Mplus syntax in Appendix. Our MSEM method eliminates problems of conflated multilevel effects and reduces bias in parameter estimates while offering a coherent framework for conceptualizing and testing multilevel moderation effects. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

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

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.

Caregiver satisfaction with paediatric HIV treatment and care in Nigeria and equity implications for children living with HIV.

PubMed

Chamla, Dick; Asadu, Chukwuemeka; Adejuyigbe, Ebun; Davies, Abiola; Ugochukwu, Ebele; Umar, Lawal; Oluwafunke, Ilesanmi; Hassan-Hanga, Fatimah; Onubogu, Chinyere; Tunde-Oremodu, Immaculata; Madubuike, Chinelo; Umeadi, Esther; Epundu, Obed; Omosun, Adenike; Anigilaje, Emmanuel; Adeyinka, Daniel

2016-03-01

Caregiver satisfaction has the potential to promote equity for children living with HIV, by influencing health-seeking behaviour. We measured dimensions of caregiver satisfaction with paediatric HIV treatment in Nigeria, and discuss its implications for equity by conducting facility-based exit interviews for caregivers of children receiving antiretroviral therapy in 20 purposively selected facilities within 5 geopolitical zones. Descriptive analysis and factor analysis were performed. Due to the hierarchical nature of the data, multilevel regression modelling was performed to investigate relationships between satisfaction factors and socio-demographic variables. Of 1550 caregivers interviewed, 63% (95% CI: 60.6-65.4) reported being very satisfied overall; however, satisfaction varied in some dimensions: only 55.6% (53.1-58.1) of caregivers could talk privately with health workers, 56.9% (54.4-59.3) reported that queues to see health workers were too long, and 89.9% (88.4-91.4) said that some health workers did not treat patients living with HIV with sufficient respect. Based on factor analysis, two underlying factors, labelled Availability and Attitude, were identified. In multilevel regression, the satisfaction with availability of services correlated with formal employment status (p < .01), whereas caregivers receiving care in private facilities were less likely satisfied with both availability (p < .01) and attitude of health workers (p < .05). State and facility levels influenced attitudes of the health workers (p < .01), but not availability of services. We conclude that high levels of overall satisfaction among caregivers masked dissatisfaction with some aspects of services. The two underlying satisfaction factors are part of access typology critical for closing equity gaps in access to HIV treatment between adults and children, and across socio-economic groups.

Caregiver satisfaction with paediatric HIV treatment and care in Nigeria and equity implications for children living with HIV

PubMed Central

Chamla, Dick; Asadu, Chukwuemeka; Adejuyigbe, Ebun; Davies, Abiola; Ugochukwu, Ebele; Umar, Lawal; Oluwafunke, Ilesanmi; Hassan-Hanga, Fatimah; Onubogu, Chinyere; Tunde-Oremodu, Immaculata; Madubuike, Chinelo; Umeadi, Esther; Epundu, Obed; Omosun, Adenike; Anigilaje, Emmanuel; Adeyinka, Daniel

2016-01-01

ABSTRACT Caregiver satisfaction has the potential to promote equity for children living with HIV, by influencing health-seeking behaviour. We measured dimensions of caregiver satisfaction with paediatric HIV treatment in Nigeria, and discuss its implications for equity by conducting facility-based exit interviews for caregivers of children receiving antiretroviral therapy in 20 purposively selected facilities within 5 geopolitical zones. Descriptive analysis and factor analysis were performed. Due to the hierarchical nature of the data, multilevel regression modelling was performed to investigate relationships between satisfaction factors and socio-demographic variables. Of 1550 caregivers interviewed, 63% (95% CI: 60.6–65.4) reported being very satisfied overall; however, satisfaction varied in some dimensions: only 55.6% (53.1–58.1) of caregivers could talk privately with health workers, 56.9% (54.4–59.3) reported that queues to see health workers were too long, and 89.9% (88.4–91.4) said that some health workers did not treat patients living with HIV with sufficient respect. Based on factor analysis, two underlying factors, labelled Availability and Attitude, were identified. In multilevel regression, the satisfaction with availability of services correlated with formal employment status (p < .01), whereas caregivers receiving care in private facilities were less likely satisfied with both availability (p < .01) and attitude of health workers (p < .05). State and facility levels influenced attitudes of the health workers (p < .01), but not availability of services. We conclude that high levels of overall satisfaction among caregivers masked dissatisfaction with some aspects of services. The two underlying satisfaction factors are part of access typology critical for closing equity gaps in access to HIV treatment between adults and children, and across socio-economic groups. PMID:27392010

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

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

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.

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'…

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

Cancer patients use hospital-based care until death: a further analysis of the Dutch Bone Metastasis Study.

PubMed

Meeuse, Jan J; van der Linden, Yvette M; Post, Wendy J; Wanders, Rinus; Gans, Rijk O B; Leer, Jan Willem H; Reyners, Anna K L

2011-10-01

To describe health care utilization (HCU) at the end of life in cancer patients. These data are relevant to plan palliative care services, and to develop training programs for involved health care professionals. The Dutch Bone Metastasis Study (DBMS) was a nationwide study proving equal effectiveness of single fraction palliative radiotherapy compared with multiple fractions for painful bone metastases in 1157 patients. The 860 (74%) patients who died during follow-up were included in the current analysis. The main outcome was the frequency of hospital-based (outpatient contact or admission) and/or general practitioner (GP) contact during the last 12 weeks of life. Changes in HCU towards death were related to data on quality of life and pain intensity using a multilevel regression model. Hospital-based HCU was reported in 1801 (63%) returned questionnaires, whereas GP contact was stated in 1246 (43%). In 573 (20%) questionnaires, both types of HCU were reported. In multilevel regression analyses, the frequency of outpatient contacts remained constant during the weeks towards death, whereas the frequency of GP contacts increased. Lower valuation of quality of life was related to both GP- and hospital-based HCU. There was a high consumption of hospital-based HCU in the last 12 weeks of life of cancer patients with bone metastases. Hospital-based HCU did not decrease during the weeks towards death, despite an increase in GP contacts. Future planning of palliative care and training programs should encompass close collaboration between medical specialists and GPs to optimize end-of-life care.

[Relationship between perceptions of safety climate at workplace and depressive disorders in manufacturing workers].

PubMed

Liu, Xu-hua; Xiao, Ya-ni; Huang, Zhi-xiong; Huang, Shao-bin; Cao, Xiao-ou; Guan, Dong-bo; Chen, Wei-qing

2013-04-01

To investigate the risk factors for depressive disorders in manufacturing workers and to provide a basis for developing health promotion measures at workplace. A questionnaire survey was performed in 8085 front-line production workers from 33 manufacturing enterprises in Nanhai District of Foshan, Guangdong Province, China. The questionnaire contained a survey of demographic characteristics, the Safety Climate Scale, the Center for Epidemiological Studies Depression Scale, etc. The multilevel logistic regression analysis was applied to investigate the risk factors for depressive disorders in workers. A total of 6260 workers completed the survey; their mean age was 31.1 ± 8.6 years, and 53.2% of them were males. The multilevel logistic regression analysis showed that after adjustment for sociodemographic factors such as age, sex, and martial status, more depressive disorders were reported in the enterprises with higher score of "production safety training" than in those with lower score (OR = 1.46, 95%CI = 1.07 ∼ 1.97); fewer depressive disorders were reported in the enterprises with higher score of "colleagues concerned about production safety" than in those with lower score (OR = 0.08, 95%CI = 0.03 ∼ 0.26); the relationships of "safety warnings and precautions" and "managers concerned about production safety" with workers' depressive disorders were not statistically significant (OR = 0.78, 95%CI = 0.48 ∼ 1.28; OR = 1.08, 95%CI = 0.68 ∼ 1.72). Depressive disorders in manufacturing workers are related to the safety climate at workplace, which indicates that a good safety climate at workplace should be created to prevent and control depressive disorders in workers.

Perceived and Objective Measures of Neighborhood Walkability and Physical Activity among Adults in Japan: A Multilevel Analysis of a Nationally Representative Sample.

PubMed

Hanibuchi, Tomoya; Nakaya, Tomoki; Yonejima, Mayuko; Honjo, Kaori

2015-10-23

Although associations between a person's neighborhood and their health have been studied internationally, most studies have been limited to a few cities or towns. Therefore, we used a nationally representative sample to explore whether perceived and objective neighborhood walkability was associated with the physical activity of residents. Data were analyzed from the Japanese General Social Surveys of 2010 (n = 2395; 1114 men and 1281 women). Perceived walkability was scored using factor analysis for the respondents' perceptions of neighborhood conditions, while objective walkability was measured using the geographic information system approach. Finally, multilevel logistic regression analysis was performed to examine whether neighborhood walkability was associated with the frequency of leisure-time physical activity (LTPA) among respondents. We found that perceived walkability was positively associated with the frequency of LTPA (odds ratio of the highest quartile was 1.53 (1.14-2.05) compared with the lowest quartile); however, objective walkability showed no association. When stratified by gender, an association between perceived walkability and LTPA was observed among women, but only a marginally significant association was present between objective walkability and LTPA among men. We conclude that the association between neighborhood walkability and LTPA can be partially generalized across Japan.

Perceived and Objective Measures of Neighborhood Walkability and Physical Activity among Adults in Japan: A Multilevel Analysis of a Nationally Representative Sample

PubMed Central

Hanibuchi, Tomoya; Nakaya, Tomoki; Yonejima, Mayuko; Honjo, Kaori

2015-01-01

Although associations between a person’s neighborhood and their health have been studied internationally, most studies have been limited to a few cities or towns. Therefore, we used a nationally representative sample to explore whether perceived and objective neighborhood walkability was associated with the physical activity of residents. Data were analyzed from the Japanese General Social Surveys of 2010 (n = 2395; 1114 men and 1281 women). Perceived walkability was scored using factor analysis for the respondents’ perceptions of neighborhood conditions, while objective walkability was measured using the geographic information system approach. Finally, multilevel logistic regression analysis was performed to examine whether neighborhood walkability was associated with the frequency of leisure-time physical activity (LTPA) among respondents. We found that perceived walkability was positively associated with the frequency of LTPA (odds ratio of the highest quartile was 1.53 (1.14–2.05) compared with the lowest quartile); however, objective walkability showed no association. When stratified by gender, an association between perceived walkability and LTPA was observed among women, but only a marginally significant association was present between objective walkability and LTPA among men. We conclude that the association between neighborhood walkability and LTPA can be partially generalized across Japan. PMID:26512682

Micro-epidemiology and spatial heterogeneity of P. vivax parasitaemia in riverine communities of the Peruvian Amazon: A multilevel analysis.

PubMed

Carrasco-Escobar, Gabriel; Gamboa, Dionicia; Castro, Marcia C; Bangdiwala, Shrikant I; Rodriguez, Hugo; Contreras-Mancilla, Juan; Alava, Freddy; Speybroeck, Niko; Lescano, Andres G; Vinetz, Joseph M; Rosas-Aguirre, Angel; Llanos-Cuentas, Alejandro

2017-08-14

Malaria has steadily increased in the Peruvian Amazon over the last five years. This study aimed to determine the parasite prevalence and micro-geographical heterogeneity of Plasmodium vivax parasitaemia in communities of the Peruvian Amazon. Four cross-sectional active case detection surveys were conducted between May and July 2015 in four riverine communities in Mazan district. Analysis of 2785 samples of 820 individuals nested within 154 households for Plasmodium parasitaemia was carried out using light microscopy and qPCR. The spatio-temporal distribution of Plasmodium parasitaemia, dominated by P. vivax, was shown to cluster at both household and community levels. Of enrolled individuals, 47% had at least one P. vivax parasitaemia and 10% P. falciparum, by qPCR, both of which were predominantly sub-microscopic and asymptomatic. Spatial analysis detected significant clustering in three communities. Our findings showed that communities at small-to-moderate spatial scales differed in P. vivax parasite prevalence, and multilevel Poisson regression models showed that such differences were influenced by factors such as age, education, and location of households within high-risk clusters, as well as factors linked to a local micro-geographic context, such as travel and occupation. Complex transmission patterns were found to be related to human mobility among communities in the same micro-basin.

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.

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.

Social cohesion matters in health

PubMed Central

2013-01-01

Introduction The concept of social cohesion has invoked debate due to the vagueness of its definition and the limitations of current measurements. This paper attempts to examine the concept of social cohesion, develop measurements, and investigate the relationship between social cohesion and individual health. Methods This study used a multilevel study design. The individual-level samples from 29 high-income countries were obtained from the 2000 World Value Survey (WVS) and the 2002 European Value Survey. National-level social cohesion statistics were obtained from Organization of Economic Cooperation and Development datasets, World Development Indicators, and Asian Development Bank key indicators for the year 2000, and from aggregating responses from the WVS. In total 47,923 individuals were included in this study. The factor analysis was applied to identify dimensions of social cohesion, which were used as entities in the cluster analysis to generate a regime typology of social cohesion. Then, multilevel regression models were applied to assess the influences of social cohesion on an individual’s self-rated health. Results and discussion Factor analysis identified five dimensions of social cohesion: social equality, social inclusion, social development, social capital, and social diversity. Then, the cluster analysis revealed five regimes of social cohesion. A multi-level analysis showed that respondents in countries with higher social inclusion, social capital, and social diversity were more likely to report good health above and beyond individual-level characteristics. Conclusions This study is an innovative effort to incorporate different aspects of social cohesion. This study suggests that social cohesion was associated with individual self-rated after controlling individual characteristics. To achieve further advancement in population health, developed countries should consider policies that would foster a society with a high level of social inclusion, social capital, and social diversity. Future research could focus on identifying possible pathways by which social cohesion influences various health outcomes. PMID:24165541

Mixed effect Poisson log-linear models for clinical and epidemiological sleep hypnogram data

PubMed Central

Swihart, Bruce J.; Caffo, Brian S.; Crainiceanu, Ciprian; Punjabi, Naresh M.

2013-01-01

Bayesian Poisson log-linear multilevel models scalable to epidemiological studies are proposed to investigate population variability in sleep state transition rates. Hierarchical random effects are used to account for pairings of subjects and repeated measures within those subjects, as comparing diseased to non-diseased subjects while minimizing bias is of importance. Essentially, non-parametric piecewise constant hazards are estimated and smoothed, allowing for time-varying covariates and segment of the night comparisons. The Bayesian Poisson regression is justified through a re-derivation of a classical algebraic likelihood equivalence of Poisson regression with a log(time) offset and survival regression assuming exponentially distributed survival times. Such re-derivation allows synthesis of two methods currently used to analyze sleep transition phenomena: stratified multi-state proportional hazards models and log-linear models with GEE for transition counts. An example data set from the Sleep Heart Health Study is analyzed. Supplementary material includes the analyzed data set as well as the code for a reproducible analysis. PMID:22241689

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.

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.

[Effect of Adolescents' Abuse Experience on Suicidal Ideation: Focused on Moderated Mediation Effect of Self-esteem on Depression and Anxiety].

PubMed

Kim, Ji Young; Lee, Kyunghee

2015-10-01

The purpose of this study was to examine the moderating mediation effect of self-esteem on the relations among adolescents' abuse experiences, depression and anxiety, and suicidal ideation. The participants were selected using secondary data from a population in the 2012 Korea Welfare Panel Survey (KOWEPS). Data were analyzed using SPSS 15.0 and SPSS Macro, and bootstrapping and hierarchical regression analysis were performed to analyze multilevel models. First, analysis of the mediating effect of the adolescents' abuse showed that there was significant mediating influence between suicidal ideation and depression and anxiety. Second, hierarchical regression analysis showed that self-esteem had significant mediation effect on depression and anxiety in adolescents' suicidal ideation. Third, SPSS Macro showed that self-esteem also significantly moderated the mediating effect of adolescents' abuse experiences on suicidal ideation through depression and anxiety. The study results suggest that in future research on adolescent's abuse experience, the risk of suicide in depression and anxiety scores should be selected through evaluation of each individual's self-esteem scale. Coping strategies with immediate early intervention should be suggested.

Distribution and Determinants of 90-Day Payments for Multilevel Posterior Lumbar Fusion: A Medicare Analysis.

PubMed

Jain, Nikhil; Phillips, Frank M; Khan, Safdar N

2018-04-01

A retrospective, economic analysis. The objective of this article is to analyze the distribution of 90-day payments, sources of variation, and reimbursement for complications and readmissions for primary ≥3-level posterior lumbar fusion (PLF) from Medicare data. A secondary objective was to identify risk factors for complications. Bundled payments represent a single payment system to cover all costs associated with a single episode of care, typically over 90 days. The dollar amount spent on different health service providers and the variation in payments for ≥3-level PLF have not been analyzed from a bundled perspective. Administrative claims data were used to study 90-day Medicare (2005-2012) reimbursements for primary ≥3-level PLF for deformity and degenerative conditions of the lumbar spine. Distribution of payments, sources of variation, and reimbursements for managing complications were studied using linear regression models. Risk factors for complications were studied by stepwise multiple-variable logistic regression analysis. Hospital payments comprised 73.8% share of total 90-day payment. Adjusted analysis identified several factors for variation in index hospital payments. The average 90-day Medicare payment for all multilevel PLFs without complications was $35,878 per patient. The additional average cost of treating complications with/without revision surgery within 90 days period ranged from $17,284 to $68,963. A 90-day bundle for ≥3-level PLF with readmission ranges from $88,648 (3 levels) to $117,215 (8+ levels). Rates and risk factors for complications were also identified. The average 90-day payment per patient from Medicare was $35,878 with several factors such as levels of surgery, comorbidities, and development of complications influencing the cost. The study also identifies the risks and costs associated with complications and readmissions and emphasize the significant effect these would have on bundled payments (additional burden of up to 192% the cost of an average uncomplicated procedure over 90 days). Level 3.

Cluster Analysis of Campylobacter jejuni Genotypes Isolated from Small and Medium-Sized Mammalian Wildlife and Bovine Livestock from Ontario Farms.

PubMed

Viswanathan, M; Pearl, D L; Taboada, E N; Parmley, E J; Mutschall, S K; Jardine, C M

2017-05-01

Using data collected from a cross-sectional study of 25 farms (eight beef, eight swine and nine dairy) in 2010, we assessed clustering of molecular subtypes of C. jejuni based on a Campylobacter-specific 40 gene comparative genomic fingerprinting assay (CGF40) subtypes, using unweighted pair-group method with arithmetic mean (UPGMA) analysis, and multiple correspondence analysis. Exact logistic regression was used to determine which genes differentiate wildlife and livestock subtypes in our study population. A total of 33 bovine livestock (17 beef and 16 dairy), 26 wildlife (20 raccoon (Procyon lotor), five skunk (Mephitis mephitis) and one mouse (Peromyscus spp.) C. jejuni isolates were subtyped using CGF40. Dendrogram analysis, based on UPGMA, showed distinct branches separating bovine livestock and mammalian wildlife isolates. Furthermore, two-dimensional multiple correspondence analysis was highly concordant with dendrogram analysis showing clear differentiation between livestock and wildlife CGF40 subtypes. Based on multilevel logistic regression models with a random intercept for farm of origin, we found that isolates in general, and raccoons more specifically, were significantly more likely to be part of the wildlife branch. Exact logistic regression conducted gene by gene revealed 15 genes that were predictive of whether an isolate was of wildlife or bovine livestock isolate origin. Both multiple correspondence analysis and exact logistic regression revealed that in most cases, the presence of a particular gene (13 of 15) was associated with an isolate being of livestock rather than wildlife origin. In conclusion, the evidence gained from dendrogram analysis, multiple correspondence analysis and exact logistic regression indicates that mammalian wildlife carry CGF40 subtypes of C. jejuni distinct from those carried by bovine livestock. Future studies focused on source attribution of C. jejuni in human infections will help determine whether wildlife transmit Campylobacter jejuni directly to humans. © 2016 Blackwell Verlag GmbH.

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.

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.

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…

Integrative eQTL analysis of tumor and host omics data in individuals with bladder cancer.

PubMed

Pineda, Silvia; Van Steen, Kristel; Malats, Núria

2017-09-01

Integrative analyses of several omics data are emerging. The data are usually generated from the same source material (i.e., tumor sample) representing one level of regulation. However, integrating different regulatory levels (i.e., blood) with those from tumor may also reveal important knowledge about the human genetic architecture. To model this multilevel structure, an integrative-expression quantitative trait loci (eQTL) analysis applying two-stage regression (2SR) was proposed. This approach first regressed tumor gene expression levels with tumor markers and the adjusted residuals from the previous model were then regressed with the germline genotypes measured in blood. Previously, we demonstrated that penalized regression methods in combination with a permutation-based MaxT method (Global-LASSO) is a promising tool to fix some of the challenges that high-throughput omics data analysis imposes. Here, we assessed whether Global-LASSO can also be applied when tumor and blood omics data are integrated. We further compared our strategy with two 2SR-approaches, one using multiple linear regression (2SR-MLR) and other using LASSO (2SR-LASSO). We applied the three models to integrate genomic, epigenomic, and transcriptomic data from tumor tissue with blood germline genotypes from 181 individuals with bladder cancer included in the TCGA Consortium. Global-LASSO provided a larger list of eQTLs than the 2SR methods, identified a previously reported eQTLs in prostate stem cell antigen (PSCA), and provided further clues on the complexity of APBEC3B loci, with a minimal false-positive rate not achieved by 2SR-MLR. It also represents an important contribution for omics integrative analysis because it is easy to apply and adaptable to any type of data. © 2017 WILEY PERIODICALS, INC.

Do Robotic Surgical Systems Improve Profit Margins? A Cross-Sectional Analysis of California Hospitals.

PubMed

Shih, Ya-Chen Tina; Shen, Chan; Hu, Jim C

2017-09-01

The aim of this study was to examine the association between ownership of robotic surgical systems and hospital profit margins. This study used hospital annual utilization data, annual financial data, and discharge data for year 2011 from the California Office of Statewide Health Planning and Development. We first performed bivariate analysis to compare mean profit margin by hospital and market characteristics and to examine whether these characteristics differed between hospitals that had one or more robotic surgical systems in 2011 and those that did not. We applied the t test and the F test to compare mean profit margin between two groups and among three or more groups, respectively. We then conducted multilevel logistic regression to determine the association between ownership of robotic surgical systems and having a positive profit margin after controlling for other hospital and market characteristics and accounting for possible correlation among hospitals located within the same market. The study sample included 167 California hospitals with valid financial information. Hospitals with robotic surgical systems tended to report more favorable profit margins. However, multilevel logistic regression showed that this relationship (an association, not causality) became only marginally significant (odds ratio [OR] = 6.2; P = 0.053) after controlling for other hospital characteristics, such as ownership type, teaching status, bed size, and surgical volumes, and market characteristics, such as total number of robotic surgical systems owned by other hospitals in the same market area. As robotic surgical systems become widely disseminated, hospital decision makers should carefully evaluate the financial and clinical implications before making a capital investment in this technology. Copyright © 2017 International Society for Pharmacoeconomics and Outcomes Research (ISPOR). Published by Elsevier Inc. All rights reserved.

Friendship networks of inner-city adults: a latent class analysis and multi-level regression of supporter types and the association of supporter latent class membership with supporter and recipient drug use.

PubMed

Bohnert, Amy S B; German, Danielle; Knowlton, Amy R; Latkin, Carl A

2010-03-01

Social support is a multi-dimensional construct that is important to drug use cessation. The present study identified types of supportive friends among the social network members in a community-based sample and examined the relationship of supporter-type classes with supporter, recipient, and supporter-recipient relationship characteristics. We hypothesized that the most supportive network members and their support recipients would be less likely to be current heroin/cocaine users. Participants (n=1453) were recruited from low-income neighborhoods with a high prevalence of drug use. Participants identified their friends via a network inventory, and all nominated friends were included in a latent class analysis and grouped based on their probability of providing seven types of support. These latent classes were included as the dependent variable in a multi-level regression of supporter drug use, recipient drug use, and other characteristics. The best-fitting latent class model identified five support patterns: friends who provided Little/No Support, Low/Moderate Support, High Support, Socialization Support, and Financial Support. In bivariate models, friends in the High, Low/Moderate, and Financial Support were less likely to use heroin or cocaine and had less conflict with and were more trusted by the support recipient than friends in the Low/No Support class. Individuals with supporters in those same support classes compared to the Low/No Support class were less likely to use heroin or cocaine, or to be homeless or female. Multivariable models suggested similar trends. Those with current heroin/cocaine use were less likely to provide or receive comprehensive support from friends. Published by Elsevier Ireland Ltd.

Socio-demographic predictors and average annual rates of caesarean section in Bangladesh between 2004 and 2014.

PubMed

Khan, Md Nuruzzaman; Islam, M Mofizul; Shariff, Asma Ahmad; Alam, Md Mahmudul; Rahman, Md Mostafizur

2017-01-01

Globally the rates of caesarean section (CS) have steadily increased in recent decades. This rise is not fully accounted for by increases in clinical factors which indicate the need for CS. We investigated the socio-demographic predictors of CS and the average annual rates of CS in Bangladesh between 2004 and 2014. Data were derived from four waves of nationally representative Bangladesh Demographic and Health Survey (BDHS) conducted between 2004 and 2014. Rate of change analysis was used to calculate the average annual rate of increase in CS from 2004 to 2014, by socio-demographic categories. Multi-level logistic regression was used to identify the socio-demographic predictors of CS in a cross-sectional analysis of the 2014 BDHS data. CS rates increased from 3.5% in 2004 to 23% in 2014. The average annual rate of increase in CS was higher among women of advanced maternal age (≥35 years), urban areas, and relatively high socio-economic status; with higher education, and who regularly accessed antenatal services. The multi-level logistic regression model indicated that lower (≤19) and advanced maternal age (≥35), urban location, relatively high socio-economic status, higher education, birth of few children (≤2), antenatal healthcare visits, overweight or obese were the key factors associated with increased utilization of CS. Underweight was a protective factor for CS. The use of CS has increased considerably in Bangladesh over the survey years. This rising trend and the risk of having CS vary significantly across regions and socio-economic status. Very high use of CS among women of relatively high socio-economic status and substantial urban-rural difference call for public awareness and practice guideline enforcement aimed at optimizing the use of CS.

Socio-demographic predictors and average annual rates of caesarean section in Bangladesh between 2004 and 2014

PubMed Central

Khan, Md. Nuruzzaman; Islam, M. Mofizul; Shariff, Asma Ahmad; Alam, Md. Mahmudul; Rahman, Md. Mostafizur

2017-01-01

Background Globally the rates of caesarean section (CS) have steadily increased in recent decades. This rise is not fully accounted for by increases in clinical factors which indicate the need for CS. We investigated the socio-demographic predictors of CS and the average annual rates of CS in Bangladesh between 2004 and 2014. Methods Data were derived from four waves of nationally representative Bangladesh Demographic and Health Survey (BDHS) conducted between 2004 and 2014. Rate of change analysis was used to calculate the average annual rate of increase in CS from 2004 to 2014, by socio-demographic categories. Multi-level logistic regression was used to identify the socio-demographic predictors of CS in a cross-sectional analysis of the 2014 BDHS data. Result CS rates increased from 3.5% in 2004 to 23% in 2014. The average annual rate of increase in CS was higher among women of advanced maternal age (≥35 years), urban areas, and relatively high socio-economic status; with higher education, and who regularly accessed antenatal services. The multi-level logistic regression model indicated that lower (≤19) and advanced maternal age (≥35), urban location, relatively high socio-economic status, higher education, birth of few children (≤2), antenatal healthcare visits, overweight or obese were the key factors associated with increased utilization of CS. Underweight was a protective factor for CS. Conclusion The use of CS has increased considerably in Bangladesh over the survey years. This rising trend and the risk of having CS vary significantly across regions and socio-economic status. Very high use of CS among women of relatively high socio-economic status and substantial urban-rural difference call for public awareness and practice guideline enforcement aimed at optimizing the use of CS. PMID:28493956

Institutional delivery in India, 2004-14: unravelling the equity-enhancing contributions of the public sector.

PubMed

Joe, William; Perkins, Jessica M; Kumar, Saroj; Rajpal, Sunil; Subramanian, S V

2018-06-01

To achieve faster and equitable improvements in maternal and child health outcomes, the government of India launched the National Rural Health Mission in 2005. This paper describes the equity-enhancing role of the public sector in increasing use of institutional delivery care services in India between 2004 and 2014. Information on 24 661 births from nationally representative survey data for 2004 and 2014 is analysed. Concentration index is computed to describe socioeconomic-rank-related relative inequalities in institutional delivery and decomposition is used to assess the contributions of public and private sectors in overall socioeconomic inequality. Multilevel logistic regression is applied to examine the changes in socioeconomic gradient between 2004 and 2014. The analysis finds that utilization of institutional delivery care in India increased from 43% in 2004 to 83% in 2014. The bulk of the increase was in public sector use (21% in 2004 to 53% in 2014) with a modest increase in private sector use (22% in 2004 to 30% in 2014). The shift from a pro-rich to pro-poor distribution of public sector use is confirmed. Decomposition analysis indicates that 51% of these reductions in socioeconomic inequality are associated with improved pro-poor distribution of public sector births. Multilevel logistic regressions confirm the disappearance of a wealth-based gradient in public sector births between 2004 and 2014. We conclude that public health investments in India have significantly contributed towards an equitable increase in the coverage of institutional delivery care. Sustained policy efforts are necessary, however, with an emphasis on education, sociocultural and geographical factors to ensure universal coverage of institutional delivery care services in India.

Mathematics Low Achievement in Greece: A Multilevel Analysis of the Programme for International Student Assessment (PISA) 2012 Data

ERIC Educational Resources Information Center

Karakolidis, Anastasios; Pitsia, Vasiliki; Emvalotis, Anastassios

2016-01-01

The main aim of the present study was to carry out an in-depth examination of mathematics underperformance in Greece. By applying a binary multilevel model to the PISA 2012 data, this study investigated the factors which were linked to low achievement in mathematics. The multilevel analysis revealed that students' gender, immigration status,…

Social capital and sense of insecurity in the neighbourhood: a population-based multilevel analysis in Malmö, Sweden.

PubMed

Lindström, Martin; Merlo, Juan; Ostergren, Per Olof

2003-03-01

The aim of this study was to investigate the influence of social capital on self-reported sense of insecurity in the neighbourhood. The public health survey in Malmö, Sweden in 1994 was a cross-sectional study. A total of 5600 individuals aged 20-80 years were asked to answer a postal questionnaire. The participation rate was 71%. A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second, was performed. We analysed the effect (intra-area correlation, cross-level modification and odds ratios) of individual (social participation) and neighbourhood social capital (electoral participation in the 1994 municipal election) on sense of insecurity after adjustment for compositional factors. Neighbourhood factors accounted for 7.2% of the total variance in individual insecurity. This effect was marginally reduced when the individual factors were included in the model. In contrast, it was reduced by 70% by the introduction of the contextual variable. This study suggests that social capital, measured as electoral participation, may partly explain the individual's sense of insecurity in the neighbourhood.

Social capital and neo-materialist contextual determinants of sense of insecurity in the neighbourhood: a multilevel analysis in Southern Sweden.

PubMed

Lindström, Martin; Lindström, Christine; Moghaddassi, Mahnaz; Merlo, Juan

2006-12-01

The aim of this study was to investigate the influence of contextual (social capital and neo-materialist) and individual factors on sense of insecurity in the neighbourhood. The 2000 public health survey in Scania is a cross-sectional study. A total of 13,715 persons answered a postal questionnaire, which is 59% of the random sample. A multilevel logistic regression model, with individuals at the first level and municipalities at the second, was performed. The effect (median odds ratios, intra-class correlation, cross-level modification and odds ratios) of individual and municipality/city quarter (social capital and police district) factors on sense of insecurity was analysed. The crude variance between municipalities/city quarters was not affected by individual factors. The introduction of administrative police district in the model reduced the municipality variance, although some of the significant variance between municipalities remained. The introduction of social capital did not affect the municipality variance. This study suggests that the neo-materialist factor administrative police district may partly explain the individual's sense of insecurity in the neighbourhood.

Determinants of Zambian men's extra-marital sex: a multi-level analysis.

PubMed

Benefo, Kofi D

2008-08-01

Research interest in extra-marital sex has increased as scholars have become aware of its role in sustaining epidemics of STDs in sub-Saharan Africa and elsewhere. While most research has used the socioeconomic and demographic features of individuals as determinants of extra-marital sexual behavior, this study examined the role played by community characteristics. Using data from the 2003 Zambian Sexual Behavior Survey for a sample of 1,118 men aged 15-59 and multilevel logistic regression techniques, the study analyzed the effects of community social and demographic characteristics on involvement in extra-marital sex while controlling for the men's individual-level characteristics. Men's involvement in extra-marital sex was found to vary with the characteristics of communities. The chances of men's involvement in extra-marital sex increased with community-level ethnic heterogeneity and urbanization, decreased in commercial centers, and in communities with a demographic surplus of males, health workers active in AIDS prevention, and access to the mass media. These results show that scholars trying to understand the motivations for extra-marital sex must pay attention to the characteristics of both individuals and communities.

Race, Employment Disadvantages, and Heavy Drinking: A Multilevel Model.

PubMed

Lo, Celia C; Cheng, Tyrone C

2015-01-01

We intended to determine (1) whether stress from employment disadvantages led to increased frequency of heavy drinking and (2) whether race had a role in the relationship between such disadvantages and heavy drinking. Study data came from the National Longitudinal Survey of Youth, a prospective study that has followed a representative sample of youth since 1979. Our study employed data from 11 particular years, during which the survey included items measuring respondents' heavy drinking. Our final sample numbered 10,171 respondents, which generated 75,394 person-waves for data analysis. Both of our hypotheses were supported by results from multilevel mixed-effects linear regression capturing the time-varying nature of three employment disadvantages and of the heavy-drinking outcome. Results show that more-frequent heavy drinking was associated with employment disadvantages, and that disadvantages' effects on drinking were stronger for Blacks and Hispanics than for Whites. That worsening employment disadvantages have worse effects on minority groups' heavy drinking (compared to Whites) probably contributes to the racial health disparities in our nation. Policies and programs addressing such disparities are especially important during economic downturns.

Burned Out at the Bedside: Patient Perceptions of Physician Burnout in an Internal Medicine Resident Continuity Clinic.

PubMed

Lafreniere, Justin P; Rios, Rebeca; Packer, Hillary; Ghazarian, Sharon; Wright, Scott M; Levine, Rachel B

2016-02-01

Burnout is high among resident physicians and may be associated with suboptimal patient care and reduced empathy. To investigate the relationship between patient perceptions of empathy and enablement and physician burnout in internal medicine residents. Cross-sectional, survey-based observational study between December 2012 and March 2013 in a resident continuity clinic located within a large urban academic primary care practice in Baltimore, Maryland. Study participants were 44 PGY1-3 residents and a convenience sample of their English-speaking adult primary care patients (N = 244). Patients rated their resident physicians using the Consultation and Relational Empathy Measure (CARE) and the Patient Enablement Instrument (PEI). Residents completed the Maslach Burnout Inventory (MBI). We tested for associations between resident burnout and patients' perceptions of resident empathy (CARE) and enablement (PEI) using multilevel regression analysis. Multilevel regression analyses indicated significant positive associations between physician depersonalization scores on the MBI and patient ratings of empathy (B = 0.28, SE = 0.17, p < 0.001) and enablement (B = 0.11, SE = 0.11, p = 0.02). Emotional exhaustion scores on the MBI were not significantly related to either patient outcome. Patients perceived residents who reported higher levels of depersonalization as more empathic and enabling during their patient care encounters. The relationship between physician distress and patient perceptions of care has important implications for medical education and requires further study.

Is religiosity positively associated with school connectedness: evidence from high school students in Atlantic Canada?

PubMed

Azagba, Sunday; Asbridge, Mark; Langille, Donald B

2014-12-01

School connectedness (SC) is associated with decreased student risk behavior and better health and social outcomes. While a considerable body of research has examined the factors associated with SC, there is limited evidence about the particular role of religiosity in shaping levels of SC. Employing data reported by junior and senior high school students from Atlantic Canada, this study examines whether religiosity is positively associated with SC and whether such associations differ by gender. We tested the association between SC and religiosity using a random intercept multilevel logistic regression. The between-school variability in SC was first determined by our estimating a null or empty model; three different model specifications that included covariates were estimated: in Model 1 we adjusted for gender, age, academic performance, parental education, and living arrangement; in Model 2 for sensation seeking and subjective social status in addition to Model 1 variables; and in Model 3 we added substance use to the analysis. Our multilevel regression analyses showed that religiosity was protectively associated with lower SC across the three model specifications when both genders were examined together. In gender-stratified analyses we found similar protective associations of religiosity, with lower SC for both males and females in all three models. Given the overwhelming positive impact of SC on a range of health, social and school outcomes, it is important to understand the role of religiosity, among other factors, that may be modified to enhance student's connectedness to school.

Multi-level modeling of social factors and preterm delivery in Santiago de Chile

PubMed Central

Kaufman, Jay S; Alonso, Faustino T; Pino, Paulina

2008-01-01

Background Birth before the 37th week of gestation (preterm birth) is an important cause of infant and neonatal mortality, but has been little studied outside of wealthy nations. Chile is an urbanized Latin American nation classified as "middle-income" based on its annual income per capita of about $6000. Methods We studied the relations between maternal social status and neighborhood social status on risk of preterm delivery in this setting using multilevel regression analyses of vital statistics data linked to geocoded decennial census data. The analytic data set included 56,970 births from 2004 in the metropolitan region of Santiago, which constitutes about 70% of all births in the study area and about 25% of all births in Chile that year. Dimensionality of census data was reduced using principal components analysis, with regression scoring to create a single index of community socioeconomic advantage. This was modeled along with years of maternal education in order to predict preterm birth and preterm low birthweight. Results Births in Santiago displayed an advantaged pattern of preterm risk, with only 6.4% of births delivering before 37 weeks. Associations were observed between risk of outcomes and individual and neighborhood factors, but the magnitudes of these associations were much more modest than reported in North America. Conclusion While several potential explanations for this relatively flat social gradient might be considered, one possibility is that Chile's egalitarian approach to universal prenatal care may have reduced social inequalities in these reproductive outcomes. PMID:18842145

Country of residence, gender equality and victim blaming attitudes about partner violence: a multilevel analysis in EU.

PubMed

Ivert, Anna-Karin; Merlo, Juan; Gracia, Enrique

2017-09-27

Intimate partner violence against women (IPVAW) is a global and preventable public health problem. Public attitudes, such as victim-blaming, are important for our understanding of differences in the occurrence of IPVAW, as they contribute to its justification. In this paper, we focus on victim-blaming attitudes regarding IPVAW within the EU and we apply multilevel analyses to identify contextual determinants of victim-blaming attitudes. We investigate both the general contextual effect of the country and the specific association between country level of gender equality and individual victim-blaming attitudes, as well as to what extend a possible general contextual effect was explained by county level gender equality. We analyzed data from 26 800 respondents from 27 member states of the European Union who responded to a survey on public perceptions of domestic violence. We applied multilevel logistic regression analysis and measures of variance (intra-class correlation (ICC)) were calculated, as well as the discriminatory accuracy by calculating the area under the receiver operator characteristic curve. Over and above individual characteristics, about 15% of the individual variance in the propensity for having victim-blaming attitudes was found at the country level, and country level of gender equality did not affect the general contextual effect (i.e. ICC) of the country on individual victim-blaming attitudes. The present study shows that there are important between-country differences in victim-blaming attitudes that cannot be explained by differences in individual-level demographics or in gender equality at the country level. More research on attitudes towards IPVAW is needed. © The Author 2017. Published by Oxford University Press on behalf of the European Public Health Association. All rights reserved.

Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling.

PubMed

Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio

2018-01-01

Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By "multi-level" we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization.

No effect of unemployment on intimate partner-related femicide during the financial crisis: a longitudinal ecological study in Spain.

PubMed

Torrubiano-Domínguez, J; Vives-Cases, C; San-Sebastián, M; Sanz-Barbero, B; Goicolea, I; Álvarez-Dardet, C

2015-09-30

Spain's financial crisis has been characterized by an increase in unemployment. This increase could have produced an increase in deaths of women due to intimate partner-related femicides (IPF). This study aims to determine whether the increase in unemployment among both sexes in different regions in Spain is related to an increase in the rates of IPF during the current financial crisis period. An ecological longitudinal study was carried out in Spain's 17 regions. Two study periods were defined: pre-crisis period (2005-2007) and crisis period (2008-2013). IPF rates adjusted by age and unemployment rates for men and women were calculated. We fitted multilevel linear regression models in which observations at level 1 were nested within regions according to a repeated measurements design. Rates of unemployment have progressively increased in Spain, rising above 20 % from 2008 to 2013 in some regions. IPF rates decreased in some regions during crisis period with respect to pre-crisis period. The multilevel analysis does not support the existence of a significant relationship between the increase in unemployment in men and women and the decrease in IPF since 2008. The increase in unemployment in men and women in Spain does not appear to have an effect on IPF. The results of the multilevel analysis discard the hypothesis that the increase in the rates of unemployment in women and men are related to an increase in IPF rates. The decline in IPF since 2008 might be interpreted as the result of exposure to other factors such as the lower frequency of divorces in recent years or the medium term effects of the integral protection measures of the law on gender violence that began in 2005.

Bayesian function-on-function regression for multilevel functional data.

PubMed

Meyer, Mark J; Coull, Brent A; Versace, Francesco; Cinciripini, Paul; Morris, Jeffrey S

2015-09-01

Medical and public health research increasingly involves the collection of complex and high dimensional data. In particular, functional data-where the unit of observation is a curve or set of curves that are finely sampled over a grid-is frequently obtained. Moreover, researchers often sample multiple curves per person resulting in repeated functional measures. A common question is how to analyze the relationship between two functional variables. We propose a general function-on-function regression model for repeatedly sampled functional data on a fine grid, presenting a simple model as well as a more extensive mixed model framework, and introducing various functional Bayesian inferential procedures that account for multiple testing. We examine these models via simulation and a data analysis with data from a study that used event-related potentials to examine how the brain processes various types of images. © 2015, The International Biometric Society.

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.

[Homicides involving firearms in Argentina between 1991 and 2006: a multilevel analysis].

PubMed

Zunino, Marina Gabriela; Diez Roux, Ana Victoria; de Souza, Edinilsa Ramos

2012-12-01

The influence of variables at different levels of organization and the effect of time on the occurrence of firearm-related homicides (FRH) in Argentina between 1991 and 2006 was analyzed using multilevel analysis. A three-level Poisson regression model was used. The first level corresponded to the distribution of the number of FRH by sex and age group for each administrative region and (four-year) period; the second corresponded to the variation over time in the interior of each administrative region; the third modeled the variation between administrative regions in accordance with the Level of Urbanization, Percentage of Homes with Unsatisfied Basic Needs and the Percentage of Working Adults. There were 15,067 FRH in persons aged 14 and over between 1991 and 2006 in the 493 administrative regions. The risk of death was higher in males and persons of 15 to 29 years of age; ages above that were associated with a lower risk. The influence of age was greater in central-urban zones and between 1999 and 2002 than during other periods. The level of urbanization was the socioeconomic variable most strongly associated with FRH risk. The risk of death from FRH was 1.6 times higher in central-urban zones compared with non-central zones. In both zones, the risk was highest between 1999 and 2002.

Prevalence and regional correlates of road traffic injury among Chinese urban residents: A 21-city population-based study.

PubMed

Rockett, Ian R H; Jiang, Shuhan; Yang, Qian; Yang, Tingzhong; Yang, Xiaozhao Y; Peng, Sihui; Yu, Lingwei

2017-08-18

This study estimated the prevalence of road traffic injury among Chinese urban residents and examined individual and regional-level correlates. A cross-sectional multistage process was used to sample residents from 21 selected cities in China. Survey respondents reported their history of road traffic injury in the past 12 months through a community survey. Multilevel, multivariable logistic regression analysis was used to identify injury correlates. Based on a retrospective 12-month reporting window, road traffic injury prevalence among urban residents was 13.2%. Prevalence of road traffic injury, by type, was 8.7, 8.7, 8.5, and 7.7% in the automobile, bicycle, motorcycle, and pedestrian categories, respectively. Multilevel analysis showed that prevalence of road traffic injury was positively associated with minority status, income, and mental health disorder score at the individual level. Regionally, road traffic injury was associated with geographic location of residence and prevalence of mental health disorders. Both individual and regional-level variables were associated with road traffic injury among Chinese urban residents, a finding whose implications transcend wholesale imported generic solutions. This descriptive research demonstrates an urgent need for longitudinal studies across China on risk and protective factors, in order to inform injury etiology, surveillance, prevention, treatment, and evaluation.

Race, Sex, and Discrimination in School Settings: A Multilevel Analysis of Associations With Delinquency.

PubMed

Chambers, Brittany D; Erausquin, Jennifer Toller

2018-02-01

Adolescence is a critical phase of development and experimentation with delinquent behaviors. There is a growing body of literature exploring individual and structural impacts of discrimination on health outcomes and delinquent behaviors. However, there is limited research assessing how school diversity and discrimination impact students' delinquent behaviors. In response, the purpose of this study was to assess if individual- and school-level indicators of discrimination and diversity were associated with student delinquent behaviors among African American and White students. We analyzed Wave I (1994-1995) data from the National Longitudinal Study of Adolescent Health. Our analysis was limited to 8947 African American and White students (73% White, 48% male, and 88% parent ≥ high school education). We used multilevel zero-inflated negative binomial regression to test the association of individual- and school characteristics and discrimination with the number of self-reported delinquent behaviors. Race, sex, perceived peer inclusion, and teacher discrimination were predictors of students' delinquent behaviors. The average school perceived peer inclusion and percentage of African Americans in teaching roles were associated with delinquent behaviors. Findings from this study highlight the potential for intervention at the interpersonal and school levels to reduce delinquency among African American and White students. © 2018, American School Health Association.

Determinants of immunization status among 12- to 23-month-old children in Indonesia (2008-2013): a multilevel analysis.

PubMed

Holipah; Maharani, Asri; Kuroda, Yoshiki

2018-02-27

Immunization is one of the most cost-effective public health interventions to prevent children from contracting vaccine-preventable diseases. Indonesia launched the Expanded Program for Immunization (EPI) in 1977. However, immunization coverage remains far below the United Nations International Children's Emergency Fund (UNICEF) and World Health Organization (WHO) target of 80%. This study aims to investigate the determinants of complete immunization status among children aged 12-23 months in Indonesia. We used three waves of the Indonesian National Socioeconomic Survey (2008, 2011, and 2013) and national village censuses from the same years. Multilevel logistic regression was used to conduct the analysis. The number of immunized children increased from 47.48% in 2008 to 61.83% in 2013. The presence of health professionals, having an older mother, and having more educated mothers were associated with a higher probability of a child's receiving full immunization. Increasing the numbers of hospitals, village health posts, and health workers was positively associated with children receiving full immunization. The MOR (median odds ratio) showed that children's likelihood of receiving complete immunization varied significantly among districts. Both household- and district-level determinants were found to be associated with childhood immunization status. Policy makers may take these determinants into account to increase immunization coverage in Indonesia.

Predictors of professional placement outcome: cultural background, English speaking and international student status.

PubMed

Attrill, Stacie; McAllister, Sue; Lincoln, Michelle

2016-08-01

Placements provide opportunities for students to develop practice skills in professional settings. Learning in placements may be challenging for culturally and linguistically diverse (CALD) students, international students, or those without sufficient English proficiency for professional practice. This study investigated whether these factors, which are hypothesized to influence acculturation, predict poor placement outcome. Placement outcome data were collected for 854 students who completed 2747 placements. Placement outcome was categorized into 'Pass' or 'At risk' categories. Multilevel binomial regression analysis was used to determine whether being CALD, an international student, speaking 'English as an additional language', or a 'Language other than English at home' predicted placement outcome. In multiple multilevel analysis speaking English as an additional language and being an international student were significant predictors of 'at risk' placements, but other variables tested were not. Effect sizes were small indicating untested factors also influenced placement outcome. These results suggest that students' English as an additional language or international student status influences success in placements. The extent of acculturation may explain the differences in placement outcome for the groups tested. This suggests that learning needs for placement may differ for students undertaking more acculturative adjustments. Further research is needed to understand this and to identify placement support strategies.

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.

Performance Analysis of Multilevel Parallel Applications on Shared Memory Architectures

NASA Technical Reports Server (NTRS)

Biegel, Bryan A. (Technical Monitor); Jost, G.; Jin, H.; Labarta J.; Gimenez, J.; Caubet, J.

2003-01-01

Parallel programming paradigms include process level parallelism, thread level parallelization, and multilevel parallelism. This viewgraph presentation describes a detailed performance analysis of these paradigms for Shared Memory Architecture (SMA). This analysis uses the Paraver Performance Analysis System. The presentation includes diagrams of a flow of useful computations.

Keeping in touch with children after separation: the point of view of fathers.

PubMed

Le Bourdais, Céline; Juby, Heather; Marcil-Gratton, Nicole

2002-01-01

The amount of father-child contact after separation is closely linked to the probability that father fulfill their financial obligations towards their children. Determining the factors that encourage this contact is, therefore, crucial to the process of reducing the risk of poverty to which children of separated parents are exposed. Based on data collected from fathers at the 1995 Canadian General Social Survey of the Family, this paper uses multi-level regression analysis to identify factors associated with higher levels of contact between fathers and children, including socio-demographic characteristics of children and fathers, variables associated with attitudes, and fathers' satisfaction with custody and access arrangements.

Dynamic networks of PTSD symptoms during conflict.

PubMed

Greene, Talya; Gelkopf, Marc; Epskamp, Sacha; Fried, Eiko

2018-02-28

Conceptualizing posttraumatic stress disorder (PTSD) symptoms as a dynamic system of causal elements could provide valuable insights into the way that PTSD develops and is maintained in traumatized individuals. We present the first study to apply a multilevel network model to produce an exploratory empirical conceptualization of dynamic networks of PTSD symptoms, using data collected during a period of conflict. Intensive longitudinal assessment data were collected during the Israel-Gaza War in July-August 2014. The final sample (n = 96) comprised a general population sample of Israeli adult civilians exposed to rocket fire. Participants completed twice-daily reports of PTSD symptoms via smartphone for 30 days. We used a multilevel vector auto-regression model to produce contemporaneous and temporal networks, and a partial correlation network model to obtain a between-subjects network. Multilevel network analysis found strong positive contemporaneous associations between hypervigilance and startle response, avoidance of thoughts and avoidance of reminders, and between flashbacks and emotional reactivity. The temporal network indicated the central role of startle response as a predictor of future PTSD symptomatology, together with restricted affect, blame, negative emotions, and avoidance of thoughts. There were some notable differences between the temporal and contemporaneous networks, including the presence of a number of negative associations, particularly from blame. The between-person network indicated flashbacks and emotional reactivity to be the most central symptoms. This study suggests various symptoms that could potentially be driving the development of PTSD. We discuss clinical implications such as identifying particular symptoms as targets for interventions.

Ciliary Body Thickness and Refractive Error in Children

PubMed Central

Bailey, Melissa D.; Sinnott, Loraine T.; Mutti, Donald O.

2010-01-01

Purpose To determine whether ciliary body thickness (CBT) is related to refractive error in school-age children. Methods Fifty-three children, 8 to 15 years of age, were recruited. CBT was measured from anterior segment OCT images (Visante; Carl Zeiss Meditec, Inc., Dublin, CA) at 1 (CBT1), 2 (CBT2) and 3 (CBT3) mm posterior to the scleral spur. Cycloplegic refractive error was measured with an autorefractor, and axial length was measured with an optical biometer. Multilevel regression models determined the relationship between CBT measurements and refractive error or axial length. A Bland-Altman analysis was used to assess the between-visit repeatability of the ciliary body measurements. Results The between-visits coefficients of repeatability for CBT1, -2, and -3 were 148.04, 165.68, and 110.90, respectively. Thicker measurements at CBT2 (r = −0.29, P = 0.03) and CBT3 (r = −0.38, P = 0.005) were associated with increasingly myopic refractive errors (multilevel model: P < 0.001). Thicker measurements at CBT2 (r = 0.40, P = 0.003) and CBT3 (r = 0.51, P < 0.001) were associated with longer axial lengths (multilevel model: P < 0.001). Conclusions Thicker ciliary body measurements were associated with myopia and a longer axial length. Future studies should determine whether this relationship is also present in animal models of myopia and determine the temporal relationship between thickening of the ciliary muscle and the onset of myopia. PMID:18566470

The multi-level perspective analysis: Indonesia geothermal energy transition study

NASA Astrophysics Data System (ADS)

Wisaksono, A.; Murphy, J.; Sharp, J. H.; Younger, P. L.

2018-01-01

The study adopts a multi-level perspective in technology transition to analyse how the transition process in the development of geothermal energy in Indonesia is able to compete against the incumbent fossil-fuelled energy sources. Three levels of multi-level perspective are socio-technical landscape (ST-landscape), socio-technical regime (ST-regime) and niche innovations in Indonesia geothermal development. The identification, mapping and analysis of the dynamic relationship between each level are the important pillars of the multi-level perspective framework. The analysis considers the set of rules, actors and controversies that may arise in the technological transition process. The identified geothermal resource risks are the basis of the emerging geothermal technological innovations in Indonesian geothermal. The analysis of this study reveals the transition pathway, which yields a forecast for the Indonesian geothermal technology transition in the form of scenarios and probable impacts.

Revisiting causal neighborhood effects on individual ischemic heart disease risk: a quasi-experimental multilevel analysis among Swedish siblings.

PubMed

Merlo, Juan; Ohlsson, Henrik; Chaix, Basile; Lichtenstein, Paul; Kawachi, Ichiro; Subramanian, S V

2013-01-01

Neighborhood socioeconomic disadvantage is associated to increased individual risk of ischemic heart disease (IHD). However, the value of this association for causal inference is uncertain. Moreover, neighborhoods are often defined by available administrative boundaries without evaluating in which degree these boundaries embrace a relevant socio-geographical context that condition individual differences in IHD risk. Therefore, we performed an analysis of variance, and also compared the associations obtained by conventional multilevel analyses and by quasi-experimental family-based design that provides stronger evidence for causal inference. Linking the Swedish Multi-Generation Register to several other national registers, we analyzed 184,931 families embracing 415,540 full brothers 45-64 years old in 2004, and residing in 8408 small-area market statistics (SAMS) considered as "neighborhoods" in our study. We investigated the association between low neighborhood income (categorized in groups by deciles) and IHD risk in the next four years. We distinguished between family mean and intrafamilial-centered low neighborhood income, which allowed us to investigate both unrelated individuals from different families and full brothers within families. We applied multilevel logistic regression techniques to obtain odds ratios (OR), variance partition coefficients (VPC) and 95% credible intervals (CI). In unrelated individuals a decile unit increase of low neighborhood income increased individual IHD risk (OR = 1.04, 95% CI: 1.03-1.07). In the intrafamilial analysis this association was reduced (OR = 1.02, 95% CI: 1.02-1.04). Low neighborhood income seems associated with IHD risk in middle-aged men. However, despite the family-based design, we cannot exclude residual confounding by genetic and non-shared environmental factors. Besides, the low neighborhood level VPC = 1.5% suggest that the SAMS are a rather inappropriate construct of the socio-geographic context that conditions individual variance in IHD risk. In contrast the high family level VPC = 20.1% confirms the relevance of the family context for understanding IHD risk. Copyright © 2012 Elsevier Ltd. All rights reserved.

School staff perpetration of physical violence against students in Uganda: a multilevel analysis of risk factors

PubMed Central

Merrill, Katherine G; Knight, Louise; Glynn, Judith R; Allen, Elizabeth; Naker, Dipak; Devries, Karen M

2017-01-01

Objective To conduct a multilevel analysis of risk factors for physical violence perpetration by school staff against Ugandan students. Design Multilevel logistic regression analysis of cross-sectional survey data from 499 staff and 828 caregivers of students at 38 primary schools, collected in 2012 and 2014 during the Good Schools Study. Setting Luwero District, Uganda. Main outcome measure Past-week use of physical violence by school staff against students was measured using the International Society for the Prevention of Child Abuse and Neglect ‘Child Abuse Screening Tool- Child International’ and the WHO Multi-Country Study on Women’s Health and Domestic Violence against Women. Results Of 499 staff, 215 (43%) reported perpetration of physical violence against students in the past week. Individual risk factors associated with physical violence perpetration included being a teacher versus another type of staff member (p<0.001), approving of physical discipline practices (p<0.001), having children (p<0.01), being age 30–39 years (p<0.05), using physical violence against non-students (p<0.05) and being a victim of intimate partner violence (IPV) (p<0.05). We observed weak evidence (p=0.06) that male staff members who had been a victim of IPV showed higher odds of violence perpetration compared with male staff who had not been a victim of IPV. No evidence was observed for school- or community-level risk factors. Conclusions Physical violence perpetration from school staff is widespread, and interventions are needed to address this issue. Staff who have been victims of violence and who use violence against people other than students may benefit from additional interventions. Researchers should further investigate how school and community contexts influence staff’s physical violence usage, given a lack of associations observed in this study. PMID:28821514

School staff perpetration of physical violence against students in Uganda: a multilevel analysis of risk factors.

PubMed

Merrill, Katherine G; Knight, Louise; Glynn, Judith R; Allen, Elizabeth; Naker, Dipak; Devries, Karen M

2017-08-18

To conduct a multilevel analysis of risk factors for physical violence perpetration by school staff against Ugandan students. Multilevel logistic regression analysis of cross-sectional survey data from 499 staff and 828 caregivers of students at 38 primary schools, collected in 2012 and 2014 during the Good Schools Study. Luwero District, Uganda. Past-week use of physical violence by school staff against students was measured using the International Society for the Prevention of Child Abuse and Neglect 'Child Abuse Screening Tool- Child International' and the WHO Multi-Country Study on Women's Health and Domestic Violence against Women. Of 499 staff, 215 (43%) reported perpetration of physical violence against students in the past week. Individual risk factors associated with physical violence perpetration included being a teacher versus another type of staff member (p<0.001), approving of physical discipline practices (p<0.001), having children (p<0.01), being age 30-39 years (p<0.05), using physical violence against non-students (p<0.05) and being a victim of intimate partner violence (IPV) (p<0.05). We observed weak evidence (p=0.06) that male staff members who had been a victim of IPV showed higher odds of violence perpetration compared with male staff who had not been a victim of IPV. No evidence was observed for school- or community-level risk factors. Physical violence perpetration from school staff is widespread, and interventions are needed to address this issue. Staff who have been victims of violence and who use violence against people other than students may benefit from additional interventions. Researchers should further investigate how school and community contexts influence staff's physical violence usage, given a lack of associations observed in this study. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Factors behind the success story of under-five stunting in Peru: a district ecological multilevel analysis.

PubMed

Huicho, Luis; Huayanay-Espinoza, Carlos A; Herrera-Perez, Eder; Segura, Eddy R; Niño de Guzman, Jessica; Rivera-Ch, María; Barros, Aluisio J D

2017-01-19

Stunting prevalence in children less than 5 years has remained stagnated in Peru from 1992 to 2007, with a rapid reduction thereafter. We aimed to assess the role of different predictors on stunting reduction over time and across departments, from 2000 to 2012. We used various secondary data sources to describe time trends of stunting and of possible predictors that included distal to proximal determinants. We determined a ranking of departments by annual change of stunting and of different predictors. To account for variation over time and across departments, we used an ecological hierarchical approach based on a multilevel mixed-effects regression model, considering stunting as the outcome. Our unit of analysis was one department-year. Stunting followed a decreasing trend in all departments, with differing slopes. The reduction pace was higher from 2007-2008 onwards. The departments with the highest annual stunting reduction were Cusco (-2.31%), Amazonas (-1.57%), Puno (-1.54%), Huanuco (-1.52%), and Ancash (-1.44). Those with the lowest reduction were Ica (-0.67%), Ucayali (-0.64%), Tumbes (-0.45%), Lima (-0.37%), and Tacna (-0.31%). Amazon and Andean departments, with the highest baseline poverty rates and concentrating the highest rural populations, showed the highest stunting reduction. In the multilevel analysis, when accounting for confounding, social determinants seemed to be the most important factors influencing annual stunting reduction, with significant variation between departments. Stunting reduction may be explained by the adoption of anti-poverty policies and sustained implementation of equitable crosscutting interventions, with focus on poorest areas. Inclusion of quality indicators for reproductive, maternal, neonatal and child health interventions may enable further analyses to show the influence of these factors. After a long stagnation period, Peru reduced dramatically its national and departmental stunting prevalence, thanks to a combination of social determinants and crosscutting factors. This experience offers useful lessons to other countries trying to improve their children's nutrition.

Timely immunization completion among children in Vietnam from 2000 to 2011: a multilevel analysis of individual and contextual factors

PubMed Central

Minh An, Dao Thi; Lee, Jong-Koo; Van Minh, Hoang; Trang, Nguyen Thi Huyen; Thu Huong, Nguyen Thi; Nam, You-Seon; Van Dung, Do

2016-01-01

Background Since the beginning of 2014, there have been nearly 6,000 confirmed measles cases in northern Vietnam. Of these, more than 86% had neither been immunized nor was their vaccination status confirmed. Objective To establish the likelihood that children under five in Vietnam had ‘timely immunization completion’ (2000–2011) and identify factors that account for variations in timely immunization completion. Design Secondary data from the Multiple Indicator Cluster Survey (MICS), which sampled women aged 15–49 from the 1999 Vietnamese Population and Housing Census frame, were analyzed. Multilevel analysis using Poisson regression was undertaken. Results Proportions of children under five who had timely immunization completion were low, especially for HBV dose 2 and HBV dose 3, which decreased between 2000 and 2011. Among seven vaccines used in the National Expanded Program of Immunization (EPI) in 2000, 2006, and 2011, measles dose 1 had the highest timely immunization completion at 65.3%, 66.7%, and 73.6%, respectively, and hepatitis B dose 1 had the lowest at 17.5%, 19.3%, and 45.5%, respectively. Timely immunization completion was less common among children whose mothers had relatively less household wealth, were from ethnic minorities, lived in rural areas, and had less education. At the community level, the child's region of residence was the main predictor of timely immunization completion, and the availability of hospital delivery and community prenatal care in the local community were also determinants. Conclusion The EPI should include ‘timely immunization completion’ as a quality indicator. There should also be greater focus and targeting in rural areas, and among women who have relatively low education, belong to minority groups, and have less household wealth. Further research on this topic using multilevel analysis is needed to better understand how these factors interact. PMID:26950555

Deepening our Understanding of Quality in Australia (DUQuA): a study protocol for a nationwide, multilevel analysis of relationships between hospital quality management systems and patient factors.

PubMed

Taylor, Natalie; Clay-Williams, Robyn; Hogden, Emily; Pye, Victoria; Li, Zhicheng; Groene, Oliver; Suñol, Rosa; Braithwaite, Jeffrey

2015-12-07

Despite the growing body of research on quality and safety in healthcare, there is little evidence of the association between the way hospitals are organised for quality and patient factors, limiting our understanding of how to effect large-scale change. The 'Deepening our Understanding of Quality in Australia' (DUQuA) study aims to measure and examine relationships between (1) organisation and department-level quality management systems (QMS), clinician leadership and culture, and (2) clinical treatment processes, clinical outcomes and patient-reported perceptions of care within Australian hospitals. The DUQuA project is a national, multilevel, cross-sectional study with data collection at organisation (hospital), department, professional and patient levels. Sample size calculations indicate a minimum of 43 hospitals are required to adequately power the study. To allow for rejection and attrition, 70 hospitals across all Australian jurisdictions that meet the inclusion criteria will be invited to participate. Participants will consist of hospital quality management professionals; clinicians; and patients with stroke, acute myocardial infarction and hip fracture. Organisation and department-level QMS, clinician leadership and culture, patient perceptions of safety, clinical treatment processes, and patient outcomes will be assessed using validated, evidence-based or consensus-based measurement tools. Data analysis will consist of simple correlations, linear and logistic regression and multilevel modelling. Multilevel modelling methods will enable identification of the amount of variation in outcomes attributed to the hospital and department levels, and the factors contributing to this variation. Ethical approval has been obtained. Results will be disseminated to individual hospitals in de-identified national and international benchmarking reports with data-driven recommendations. This ground-breaking national study has the potential to influence decision-making on the implementation of quality and safety systems and processes in Australian and international hospitals. 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/

Publication bias in obesity treatment trials?

PubMed

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

1996-10-01

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

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.

Multi-level tree analysis of pulmonary artery/vein trees in non-contrast CT images

NASA Astrophysics Data System (ADS)

Gao, Zhiyun; Grout, Randall W.; Hoffman, Eric A.; Saha, Punam K.

2012-02-01

Diseases like pulmonary embolism and pulmonary hypertension are associated with vascular dystrophy. Identifying such pulmonary artery/vein (A/V) tree dystrophy in terms of quantitative measures via CT imaging significantly facilitates early detection of disease or a treatment monitoring process. A tree structure, consisting of nodes and connected arcs, linked to the volumetric representation allows multi-level geometric and volumetric analysis of A/V trees. Here, a new theory and method is presented to generate multi-level A/V tree representation of volumetric data and to compute quantitative measures of A/V tree geometry and topology at various tree hierarchies. The new method is primarily designed on arc skeleton computation followed by a tree construction based topologic and geometric analysis of the skeleton. The method starts with a volumetric A/V representation as input and generates its topologic and multi-level volumetric tree representations long with different multi-level morphometric measures. A new recursive merging and pruning algorithms are introduced to detect bad junctions and noisy branches often associated with digital geometric and topologic analysis. Also, a new notion of shortest axial path is introduced to improve the skeletal arc joining two junctions. The accuracy of the multi-level tree analysis algorithm has been evaluated using computer generated phantoms and pulmonary CT images of a pig vessel cast phantom while the reproducibility of method is evaluated using multi-user A/V separation of in vivo contrast-enhanced CT images of a pig lung at different respiratory volumes.

Development and application of optimum sensitivity analysis of structures

NASA Technical Reports Server (NTRS)

Barthelemy, J. F. M.; Hallauer, W. L., Jr.

1984-01-01

The research focused on developing an algorithm applying optimum sensitivity analysis for multilevel optimization. The research efforts have been devoted to assisting NASA Langley's Interdisciplinary Research Office (IRO) in the development of a mature methodology for a multilevel approach to the design of complex (large and multidisciplinary) engineering systems. An effort was undertaken to identify promising multilevel optimization algorithms. In the current reporting period, the computer program generating baseline single level solutions was completed and tested out.

Associations of neighborhood disorganization and maternal spanking with children's aggression: A fixed-effects regression analysis.

PubMed

Ma, Julie; Grogan-Kaylor, Andrew; Lee, Shawna J

2018-02-01

This study employed fixed effects regression that controls for selection bias, omitted variables bias, and all time-invariant aspects of parent and child characteristics to examine the simultaneous associations between neighborhood disorganization, maternal spanking, and aggressive behavior in early childhood using data from the Fragile Families and Child Wellbeing Study (FFCWS). Analysis was based on 2,472 children and their mothers who participated in Wave 3 (2001-2003; child age 3) and Wave 4 (2003-2006; child age 5) of the FFCWS. Results indicated that higher rates of neighborhood crime and violence predicted higher levels of child aggression. Maternal spanking in the past year, whether frequent or infrequent, was also associated with increases in aggressive behavior. This study contributes statistically rigorous evidence that exposure to violence in the neighborhood as well as the family context are predictors of child aggression. We conclude with a discussion for the need for multilevel prevention and intervention approaches that target both community and parenting factors. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

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.

Conducting Multilevel Analyses in Medical Education

ERIC Educational Resources Information Center

Zyphur, Michael J.; Kaplan, Seth A.; Islam, Gazi; Barsky, Adam P.; Franklin, Michael S.

2008-01-01

A significant body of education literature has begun using multilevel statistical models to examine data that reside at multiple levels of analysis. In order to provide a primer for medical education researchers, the current work gives a brief overview of some issues associated with multilevel statistical modeling. To provide an example of this…

Social Context and Dental Pain in Adults of Colombian Ethnic Minority Groups: A Multilevel Cross-Sectional Study.

PubMed

Ardila, Carlos M; Agudelo-Suárez, Andrés A

2016-01-01

To estimate the effect of social context on dental pain in adults of Colombian ethnic minority groups (CEGs). Information from 34,843 participants was used. A multilevel model was constructed that had ethnic groups (ie, CEGs and non-CEGs) at level 1 and Colombian states at level 2. Contextual variables included gross domestic product (GDP), Human Development Index (HDI), and Unmet Basic Needs Index (UBNI). Dental pain was observed in 12.3% of 6,440 CEGs. In an unadjusted logistic regression model, dental pain was associated with being a CEG (odds ratio [95% confidence interval], 1.34 [1.22-1.46]; P = .0001). This association remained significant after adjusting for possible confounding variables. An unconditional multilevel analysis showed that the variance in dental pain was statistically significant at the ethnic group level (β = 0.047 ± 0.015; P = .0009) and at the state level (β = 0.038 ± 0.019; P = .02) and that the variation between ethnic groups was higher than the variation between states (55% vs 45%, respectively). In a multivariate model, the variance in dental pain was also statistically significant at the ethnic group level (β = 0.029 ± 0.012; P = .007) and the state level (β = 0.042 ± .019; P = .01), but the variation between states was higher (40% vs 60%). The results of multilevel multivariate analyses showed that dental pain was associated with increasing age (β = 0.009 ± 0.001; P = .0001), lower education level (β = 0.302 ± 0.103; P = .0001), female sex (β = 0.031 ± 0.069; P = .003), GDP (β = 5.136 ± 2.009; P = .002) and HDI (β = 6.862 ± 5.550; P = .004); however, UBNI was not associated with dental pain. The variance in dental pain was higher between states than between ethnic groups in the multivariate multilevel model. Dental pain in CEGs was associated with contextual and individual factors. Considering contextual factors, GDP and HDI may play a major role in dental pain prevalence.

[Two-level logistic modeling analysis on the factors that influence birth in hospitals in poor rural areas of Sichuan province].

PubMed

Yu, Chuan; Li, Xiao-song

2008-11-01

To identify the determinants of birth in hospitals in the poor rural areas. A questionnaire survey in eight poor counties in Sichuan province was conducted. Multilevel logistic regression analysis was performed to identify the factors that influenced birth in hospitals. Hospitals delivered 61.4% of babies in the selected counties. Education, eligibility to poverty relief, numbers of pre-natal examinations and abnormalities found in pre-natal examinations had a significant impact on birth in hospitals. Education of women and medical relief in the poor rural areas need to be strengthened to increase the proportion of babies delivered in hospitals in the poor rural areas. Systematic management of pregnant women and increased pre-natal examinations could also contribute to hospital delivery of babies.

Finite Volume Element (FVE) discretization and multilevel solution of the axisymmetric heat equation

NASA Astrophysics Data System (ADS)

Litaker, Eric T.

1994-12-01

The axisymmetric heat equation, resulting from a point-source of heat applied to a metal block, is solved numerically; both iterative and multilevel solutions are computed in order to compare the two processes. The continuum problem is discretized in two stages: finite differences are used to discretize the time derivatives, resulting is a fully implicit backward time-stepping scheme, and the Finite Volume Element (FVE) method is used to discretize the spatial derivatives. The application of the FVE method to a problem in cylindrical coordinates is new, and results in stencils which are analyzed extensively. Several iteration schemes are considered, including both Jacobi and Gauss-Seidel; a thorough analysis of these schemes is done, using both the spectral radii of the iteration matrices and local mode analysis. Using this discretization, a Gauss-Seidel relaxation scheme is used to solve the heat equation iteratively. A multilevel solution process is then constructed, including the development of intergrid transfer and coarse grid operators. Local mode analysis is performed on the components of the amplification matrix, resulting in the two-level convergence factors for various combinations of the operators. A multilevel solution process is implemented by using multigrid V-cycles; the iterative and multilevel results are compared and discussed in detail. The computational savings resulting from the multilevel process are then discussed.

Alternatives to Multilevel Modeling for the Analysis of Clustered Data

ERIC Educational Resources Information Center

Huang, Francis L.

2016-01-01

Multilevel modeling has grown in use over the years as a way to deal with the nonindependent nature of observations found in clustered data. However, other alternatives to multilevel modeling are available that can account for observations nested within clusters, including the use of Taylor series linearization for variance estimation, the design…

The Effects of Autonomy and Empowerment on Employee Turnover: Test of a Multilevel Model in Teams

ERIC Educational Resources Information Center

Liu, Dong; Zhang, Shu; Wang, Lei; Lee, Thomas W.

2011-01-01

Extending research on voluntary turnover in the team setting, this study adopts a multilevel self-determination theoretical approach to examine the unique roles of individual and social-contextual motivational precursors, autonomy orientation and autonomy support, in reducing team member voluntary turnover. Analysis of multilevel time-lagged data…

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…

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…

Relationships between community social capital and injury in Canadian adolescents: a multilevel analysis

PubMed Central

Vafaei, Afshin; Pickett, William; Alvarado, Beatriz E

2015-01-01

Background Characteristics of social environments are potential risk factors for adolescent injury. Impacts of social capital on the occurrence of such injuries have rarely been explored. Methods General health questionnaires were completed by 8910 youth aged 14 years and older as part of the 2010 Canadian Health Behaviour in School-Aged Children study. These were supplemented with community-level data from the 2006 Canada Census of Population. Multilevel logistic regression models with random intercepts were fit to examine associations of interest. The reliability and validity of variables used in this analysis had been established in past studies, or in new analyses that employed factor analysis. Results Between school differences explained 2% of the variance in the occurrence of injuries. After adjustment for all confounders, community social capital did not have any impact on the occurrence of injuries in boys: OR: 1.01, 95% CI 0.80 to 1.29. However, living in areas with low social capital was associated with lower occurrence of injuries in girls (OR 0.78, 95% CI 0.63 to 0.96). Other factors that were significantly related to injuries in both genders were younger age, engagement in more risky behaviours, and negative behavioural influences from peers. Conclusions After simultaneously taking into account the influence of community-level and individual-level factors, community levels of social capital remained a relatively strong predictor of injury among girls but not boys. Such gender effects provide important clues into the social aetiology of youth injury. PMID:26294708

Passive Suicide Ideation Among Older Adults in Europe: A Multilevel Regression Analysis of Individual and Societal Determinants in 12 Countries (SHARE).

PubMed

Stolz, Erwin; Fux, Beat; Mayerl, Hannes; Rásky, Éva; Freidl, Wolfgang

2016-09-01

Passive suicide ideation (PSI) is common among older adults, but prevalences have been reported to vary considerably across European countries. The goal of this study was to assess the role of individual-level risk factors and societal contextual factors associated with PSI in old age. We analyzed longitudinal data from the Survey of Health, Ageing, and Retirement in Europe (SHARE) on 6,791 community-dwelling respondents (75+) from 12 countries. Bayesian logistic multilevel regression models were used to assess variance components, individual-level and country-level risk factors. About 4% of the total variance of PSI was located at the country level, a third of which was attributable to compositional effects of individual-level predictors. Predictors for the development of PSI at the individual level were female gender, depression, older age, poor health, smaller social network size, loneliness, nonreligiosity, and low perceived control (R (2) = 25.8%). At the country level, cultural acceptance of suicide, religiosity, and intergenerational cohabitation were associated with the rates of PSI. Cross-national variation in old-age PSI is mostly attributable to individual-level determinants and compositional differences, but there is also evidence for contextual effects of country-level characteristics. Suicide prevention programs should be intensified in high-risk countries and attitudes toward suicide should be addressed in information campaigns. © The Author 2016. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

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

Phantom Effects in Multilevel Compositional Analysis: Problems and Solutions

ERIC Educational Resources Information Center

Pokropek, Artur

2015-01-01

This article combines statistical and applied research perspective showing problems that might arise when measurement error in multilevel compositional effects analysis is ignored. This article focuses on data where independent variables are constructed measures. Simulation studies are conducted evaluating methods that could overcome the…

Multilevel Interventions: Measurement and Measures

PubMed Central

Charns, Martin P.; Alligood, Elaine C.; Benzer, Justin K.; Burgess, James F.; Mcintosh, Nathalie M.; Burness, Allison; Partin, Melissa R.; Clauser, Steven B.

2012-01-01

Background Multilevel intervention research holds the promise of more accurately representing real-life situations and, thus, with proper research design and measurement approaches, facilitating effective and efficient resolution of health-care system challenges. However, taking a multilevel approach to cancer care interventions creates both measurement challenges and opportunities. Methods One-thousand seventy two cancer care articles from 2005 to 2010 were reviewed to examine the state of measurement in the multilevel intervention cancer care literature. Ultimately, 234 multilevel articles, 40 involving cancer care interventions, were identified. Additionally, literature from health services, social psychology, and organizational behavior was reviewed to identify measures that might be useful in multilevel intervention research. Results The vast majority of measures used in multilevel cancer intervention studies were individual level measures. Group-, organization-, and community-level measures were rarely used. Discussion of the independence, validity, and reliability of measures was scant. Discussion Measurement issues may be especially complex when conducting multilevel intervention research. Measurement considerations that are associated with multilevel intervention research include those related to independence, reliability, validity, sample size, and power. Furthermore, multilevel intervention research requires identification of key constructs and measures by level and consideration of interactions within and across levels. Thus, multilevel intervention research benefits from thoughtful theory-driven planning and design, an interdisciplinary approach, and mixed methods measurement and analysis. PMID:22623598

A multilevel model for comorbid outcomes: obesity and diabetes in the US.

PubMed

Congdon, Peter

2010-02-01

Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk.

Relationship Between T1 Slope and Cervical Alignment Following Multilevel Posterior Cervical Fusion Surgery: Impact of T1 Slope Minus Cervical Lordosis.

PubMed

Hyun, Seung-Jae; Kim, Ki-Jeong; Jahng, Tae-Ahn; Kim, Hyun-Jib

2016-04-01

Retrospective study. To assess the relationship between sagittal alignment of the cervical spine and patient-reported health-related quality-of-life scores following multilevel posterior cervical fusion, and to explore whether an analogous relationship exists in the cervical spine using T1 slope minus C2-C7 lordosis (T1S-CL). A recent study demonstrated that, similar to the thoracolumbar spine, the severity of disability increases with sagittal malalignment following cervical reconstruction surgery. From 2007 to 2013, 38 consecutive patients underwent multilevel posterior cervical fusion for cervical stenosis, myelopathy, and deformities. Radiographic measurements included C0-C2 lordosis, C2-C7 lordosis, C2-C7 sagittal vertical axis (SVA), T1 slope, and T1S-CL. Pearson correlation coefficients were calculated between pairs of radiographic measures and health-related quality-of-life. C2-C7 SVA positively correlated with neck disability index (NDI) scores (r = 0.495). C2-C7 lordosis (P = 0.001) and T1S-CL (P = 0.002) changes correlated with NDI score changes after surgery. For significant correlations between C2-C7 SVA and NDI scores, regression models predicted a threshold C2-C7 SVA value of 50 mm, beyond which correlations were most significant. The T1S-CL also correlated positively with C2-C7 SVA and NDI scores (r = 0.871 and r = 0.470, respectively). Results of the regression analysis indicated that a C2-C7 SVA value of 50 mm corresponded to a T1S-CL value of 26.1°. This study showed that disability of the neck increased with cervical sagittal malalignment following surgical reconstruction and a greater T1S-CL mismatch was associated with a greater degree of cervical malalignment. Specifically, a mismatch greater than 26.1° corresponded to positive cervical sagittal malalignment, defined as C2-C7 SVA greater than 50 mm. 3.

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.

Exploring unobserved household living conditions in multilevel choice modeling: An application to contraceptive adoption by Indian women.

PubMed

Dias, José G; de Oliveira, Isabel Tiago

2018-01-01

This research analyzes the effect of the poverty-wealth dimension on contraceptive adoption by Indian women when no direct measures of income/expenditures are available to use as covariates. The index-Household Living Conditions (HLC)-is based on household assets and dwelling characteristics and is computed by an item response model simultaneously with the choice model in a new single-step approach. That is, the HLC indicator is treated as a latent covariate measured by a set of items, it depends on a set of concomitant variables, and explains contraceptive choices in a probit regression. Additionally, the model accounts for complex survey design and sample weights in a multilevel framework. Regarding our case study on contraceptive adoption by Indian women, results show that women with better household living conditions tend to adopt contraception more often than their counterparts. This effect is significant after controlling other factors such as education, caste, and religion. The external validation of the indicator shows that it can also be used at aggregate levels of analysis (e.g., county or state) whenever no other indicators of household living conditions are available.

Individual self-reported health, social participation and neighbourhood: a multilevel analysis in Malmö, Sweden.

PubMed

Lindström, Martin; Moghaddassi, Mahnaz; Merlo, Juan

2004-07-01

The influence of neighbourhood and individual factors on self-reported health was investigated. The public health survey in Malmö 1994 is a cross-sectional study. A total of 3,602 individuals aged 20-80 living in 75 neighbourhoods answered a postal questionnaire. The participation rate was 71%. A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second, was performed. We analysed the effect (intra-area correlation, cross-level modification and odds ratios) of neighbourhood on self-reported health after adjustment for individual factors. The neighbourhoods accounted for 2.8% of the crude total variance in self-reported health status. This effect was significantly reduced when individual factors such as country of origin, education and social participation were included in the model. In fact, no significant variance in self-reported health remained after the introduction of the individual factors in the model. In Malmö, the neighbourhood variance in self-reported health is mainly affected by individual factors, especially country of origin, socioeconomic status measured as level of education and individual social participation. Copyright 2004 The Institute for Cancer Prevention and Elsevier Inc.

Individual and contextual determinants of self-reported poor psychological health: a population-based multilevel analysis in southern Sweden.

PubMed

Lindström, Martin; Moghaddassi, Mahnaz; Merlo, Juan

2006-01-01

To investigate the influence of contextual and individual factors on self-reported psychological health. The 2000 public health survey in Scania is a cross-sectional postal questionnaire study with a 59% participation rate. A total of 13,715 persons aged 18-80 answered the questionnaire. A multilevel logistic regression model, with individuals at the first level and municipalities/city quarters at the second, was performed. The effect (intra-class correlation, cross-level modification, and odds ratios) of individual and municipality/city quarter factors on self-reported psychological health was analysed. The crude variance between municipalities/city quarters was small but significant. It was particularly affected and lowered by individual civil status, country of origin, economic stress, and social participation. The inclusion of all individual factors age, sex, civil status, country of origin, education, economic stress, and social participation lowered the between municipality variance to not-significant levels, which is the reason why no contextual variables were included in the calculations. The results of this study suggest that poor self-reported psychological health is affected mainly by individual characteristics of the population and not by contextual factors at the municipality/city quarter level.

Social capital and leisure time physical activity: a population based multilevel analysis in Malmö, Sweden

PubMed Central

Lindstrom, M; Moghaddassi, M; Merlo, J

2003-01-01

Objective: To investigate the influence of social capital and individual factors on the level of leisure time physical inactivity in the neighbourhoods. Methods: The public health survey in Malmö 1994 is a cross sectional study. A total of 5600 people aged 20–80 years were invited to answer a postal questionnaire. The participation rate was 71%. A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second, was performed. The effect (intra-area correlation, cross level modification, and odds ratios) was analysed of individual and neighbourhood (the 1993 migration out of an area as a proxy for social capital) factors on leisure time physical inactivity after adjustment for individual factors. Results: Neighbourhood factors accounted for 5.0% of the crude total variance in physical inactivity. This effect was significantly reduced when the individual factors, especially country of origin, education, and social participation, were included in the model. In contrast, it was not reduced by the introduction of the contextual social capital variable. Conclusion: This study suggests that in the neighbourhoods of Malmö leisure time physical inactivity is mainly affected by individual factors. PMID:12490644

Travel time to maternity care and its effect on utilization in rural Ghana: a multilevel analysis.

PubMed

Masters, Samuel H; Burstein, Roy; Amofah, George; Abaogye, Patrick; Kumar, Santosh; Hanlon, Michael

2013-09-01

Rates of neonatal and maternal mortality are high in Ghana. In-facility delivery and other maternal services could reduce this burden, yet utilization rates of key maternal services are relatively low, especially in rural areas. We tested a theoretical implication that travel time negatively affects the use of in-facility delivery and other maternal services. Empirically, we used geospatial techniques to estimate travel times between populations and health facilities. To account for uncertainty in Ghana Demographic and Health Survey cluster locations, we adopted a novel approach of treating the location selection as an imputation problem. We estimated a multilevel random-intercept logistic regression model. For rural households, we found that travel time had a significant effect on the likelihood of in-facility delivery and antenatal care visits, holding constant education, wealth, maternal age, facility capacity, female autonomy, and the season of birth. In contrast, a facility's capacity to provide sophisticated maternity care had no detectable effect on utilization. As the Ghanaian health network expands, our results suggest that increasing the availability of basic obstetric services and improving transport infrastructure may be important interventions. Copyright © 2013 Elsevier Ltd. All rights reserved.

Psychological distress in the workforce: a multilevel and longitudinal analysis of the case of regulated occupations in Canada.

PubMed

Cadieux, Nathalie; Marchand, Alain

2014-08-07

This study uses a multidimensional theoretical model to evaluate the role of regulated occupations and working conditions in explaining psychological distress. Various multilevel regression analyses were conducted on longitudinal data for which measures repeated over time (n1 = 36,166) were nested in individuals (n2 = 7007). Results showed that when we controlled for working conditions, family situation, the social network outside the workplace, and personal characteristics, the level of psychological distress was significantly lower among professional workers in regulated occupations than among professionals not in regulated occupations. Among the working conditions studied, skill utilisation, psychological demands, and job insecurity were positively associated with psychological distress levels, whereas social support in the workplace was inversely related to distress. Finally, our results suggest that self-esteem reduced the effect of social support in the workplace on psychological distress levels in the workforce. These results support our hypothesis that working in regulated occupations exerts a direct effect on mental health. These results also make clear the importance of developing new tools for measuring psychological distress among upper-level professional workers. Such tools will be much better suited to the realities characterising today's knowledge-based economies.

Does the density of the health workforce predict adolescent health? A cross-sectional, multilevel study of 38 countries.

PubMed

Riehm, Kira E; Latimer, Eric; Quesnel-Vallée, Amélie; Stevens, Gonneke W J M; Gariépy, Geneviève; Elgar, Frank J

2018-06-11

Scant evidence exists on the relation between the availability of health professionals and adolescent health, and whether the size of the health workforce equally benefits adolescents across socioeconomic strata. We conducted a cross-sectional analysis of adolescent health in 38 countries. Data from 218 790 adolescents were drawn from the 2013/2014 Health Behavior in School-aged Children survey. We used multilevel regression analyses to examine the association between the density of the health workforce and psychosomatic and mental health symptoms with differences in country wealth and income inequality controlled. A higher density of psychologists was associated with better self-reported mental health in adolescents (P = 0.047); however, this finding was not robust to sensitivity analyses. The densities of physicians and psychiatrists were not significantly associated with better adolescent psychosomatic or mental health. Cross-level interactions between the health workforce and socioeconomic status did not relate to health, indicating that larger health workforces did not reduce socioeconomic differences in adolescent health. This study found that adolescents in countries with a higher density of health providers do not report better psychosomatic or mental health. Other social or structural factors may play larger roles in adolescent health.

Exploring unobserved household living conditions in multilevel choice modeling: An application to contraceptive adoption by Indian women

PubMed Central

2018-01-01

This research analyzes the effect of the poverty-wealth dimension on contraceptive adoption by Indian women when no direct measures of income/expenditures are available to use as covariates. The index–Household Living Conditions (HLC)–is based on household assets and dwelling characteristics and is computed by an item response model simultaneously with the choice model in a new single-step approach. That is, the HLC indicator is treated as a latent covariate measured by a set of items, it depends on a set of concomitant variables, and explains contraceptive choices in a probit regression. Additionally, the model accounts for complex survey design and sample weights in a multilevel framework. Regarding our case study on contraceptive adoption by Indian women, results show that women with better household living conditions tend to adopt contraception more often than their counterparts. This effect is significant after controlling other factors such as education, caste, and religion. The external validation of the indicator shows that it can also be used at aggregate levels of analysis (e.g., county or state) whenever no other indicators of household living conditions are available. PMID:29385187

Syringe Sharing in Drug Injecting Dyads: A Cross-Classified Multilevel Analysis of Social Networks.

PubMed

Shahesmaeili, Armita; Mirzazadeh, Ali; McFarland, Willi; Sharifi, Hamid; Haghdoost, Ali Akbar; Soori, Hamid

2018-05-15

We examined the association of dyadic-level factors with syringe sharing among people who inject drugs (PWID) in Kerman, Iran. In a cross-sectional study, we collected data on 329 drug-injecting dyads by individual face-to-face interviews. An injecting dyad was defined as 2 PWID who knew each other and injected drugs together during the last 6 months. If they reported at least 1 occasion of syringe sharing, the dyad was considered high-risk. Dyadic-level factors associated with syringe sharing were assessed using cross-classified multilevel logistic regression. The rate of syringe sharing was significantly higher for dyads who were more intimate (adjusted odds ratio [AOR] 4.5, CI 95%, 2.3-8.6), who had instrumental support (AOR 2.1, 95% CI 1.1-4.5), and who pooled money for drugs (AOR 4.1, 95% CI 2.0-8.3). The rate was lower in same-sex dyads (AOR 0.4, 95% CI 0.2-0.9) and in dyads who shared health information (AOR 0.5, 95% CI 0.2-0.9). Findings highlight close-peer influences on syringe-sharing behavior.

Using Visual Analysis to Evaluate and Refine Multilevel Models of Single-Case Studies

ERIC Educational Resources Information Center

Baek, Eun Kyeng; Petit-Bois, Merlande; Van den Noortgate, Wim; Beretvas, S. Natasha; Ferron, John M.

2016-01-01

In special education, multilevel models of single-case research have been used as a method of estimating treatment effects over time and across individuals. Although multilevel models can accurately summarize the effect, it is known that if the model is misspecified, inferences about the effects can be biased. Concern with the potential for model…

Therapist adherence is associated with outcome in cognitive-behavioral therapy for bulimia nervosa.

PubMed

Folke, Sofie; Daniel, Sarah I F; Gondan, Matthias; Lunn, Susanne; Tækker, Louise; Poulsen, Stig

2017-06-01

Studies of therapist adherence in relation to treatment outcome have produced mixed results. The aim of the present study was to investigate change in therapist adherence to cognitive-behavioral therapy (CBT) for bulimia nervosa over time, and to investigate the relationship between adherence and client outcome in early, middle, and late phases of treatment. Thirty-six clients received the focused form of "enhanced" CBT (CBT-E) for bulimia nervosa. Trained observers rated audiotapes of 92 full-length therapy sessions from early (Session 3), middle (Session 11), and late phases (Session 20) of treatment using the Cognitive-Behavioral Therapy Treatment Protocol Adherence Scale. Change in adherence across the 3 treatment phases was examined using multilevel analysis. The relationship between early, middle, and late adherence levels and end-of-treatment binging frequency was examined using multilevel Poisson regression analysis. Adherence decreased significantly over the course of treatment. Higher levels of therapist adherence in early and middle phases of treatment were associated with reduced binging frequency, whereas higher levels of adherence measured late in treatment was not. Results indicate that therapists' adherence to the CBT-E treatment protocol decreases over time and that high levels of protocol adherence in early and middle phases of treatment are more important for positive client outcomes than high levels of adherence in the end of treatment. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

A multilevel analysis of individual and community effect on chronic childhood malnutrition in rural Nigeria.

PubMed

Uthman, Olalekan A

2009-04-01

Protein energy malnutrition is the second most important cause of childhood morbidity and mortality in Nigeria after infections. The purpose of this article was to develop and test a model of childhood malnutrition that includes individual-level characteristics along with contextual characteristics defined at the community level. Multilevel logistic regression analysis. A total of 4007 children resident in 96 rural villages in Nigeria. Stunting: height-for-age that is less than the international reference value by >2 standard deviations (SDs). Independent of other factors, children born to underweight mothers were 1.32-times more likely to be stunted [adjusted odds ratio (aOR) 1.32; 95% confidence interval (CI) 1.07-1.64]. For each additional month of breastfeeding the odds of being stunted increased by 4% (aOR 1.04; 95% CI 1.03-1.06). Each SD increase in the household wealth index and maternal health-seeking behaviour index decreased the odds of being stunted by 16% (aOR 0.84; 95% CI 0.76-0.94) and 29% (aOR 0.71; 95% CI 0.60 -0.82), respectively. The study has provided evidence that both individual and community characteristics are important predictors of childhood malnutrition in rural Nigeria; and that scholars trying to understand variation in childhood malnutrition should pay attention to the characteristics of both children and place of residence.

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.

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.

Individual and contextual socioeconomic determinants of knowledge of the ABC approach of preventing the sexual transmission of HIV in Nigeria: a multilevel analysis.

PubMed

Uthman, Olalekan A; Kayode, Gbenga A; Adekanmbi, Victor T

2013-12-01

Nigeria has the highest number of people living with HIV/AIDS in the world after India and South Africa. HIV/AIDS places a considerable burden on society's resources, and its prevention is a cost-beneficial solution to address these consequences. To the best of our knowledge, there has been no multilevel study performed to date that examined the separate and independent associations of individual and community socioeconomic status (SES) with HIV prevention knowledge in Nigeria. Multilevel linear regression models were applied to the 2008 Nigeria Demographic and Health Survey on 48871 respondents (Level 1) nested within 886 communities (Level 2) from 37 districts (Level 3). Approximately one-fifth (20%) of respondents were not aware of any of the Abstinence, Being faithful and Condom use (ABC) approach of preventing the sexual transmission of HIV. However, the likelihood of being aware of the ABC approach of preventing the sexual transmission of HIV increased with older age, male gender, greater education attainment, a higher wealth index, living in an urban area and being from least socioeconomically disadvantaged communities. There were significant community and district variations in respondents' knowledge of the ABC approach of preventing the sexual transmission of HIV. The present study provides evidence that both individual- and community-level SES factors are important predictors of knowledge of the ABC approach of preventing the sexual transmission of HIV in Nigeria. The findings underscore the need to implement public health prevention strategies not only at the individual level, but also at the community level.

Places, people and mental health: a multilevel analysis of economic inactivity.

PubMed

Fone, David; Dunstan, Frank; Williams, Gareth; Lloyd, Keith; Palmer, Stephen

2007-02-01

This paper investigates multilevel associations between the common mental disorders of anxiety, depression and economic inactivity measured at the level of the individual and the UK 2001 census ward. The data set comes from the Caerphilly Health & Social Needs study, in which a representative survey of adults aged 18-74 years was carried out to collect a wide range of information which included mental health status (using the Mental Health Inventory (MHI-5) scale of the Short Form-36 health status questionnaire), and socio-economic status (including employment status, social class, household income, housing tenure and property value). Ward level economic inactivity was measured using non-means tested benefits data from the Department of Work and Pensions (DWP) on long-term Incapacity Benefit and Severe Disablement Allowance. Estimates from multilevel linear regression models of 10,653 individuals nested within 36 census wards showed that individual mental health status was significantly associated with ward-level economic inactivity, after adjusting for individual-level variables, with a moderate effect size of -0.668 (standard error=0.258). There was a significant cross-level interaction between ward-level and individual economic inactivity from permanent sickness or disability, such that the effect of permanent sickness or disability on mental health was significantly greater for people living in wards with high levels of economic inactivity. This supports the hypothesis that living in a deprived neighbourhood has the most negative health effects on poorer individuals and is further evidence for a substantive effect of the place where you live on mental health.

Streaming, Tracking and Reading Achievement: A Multilevel Analysis of Students in 40 Countries

ERIC Educational Resources Information Center

Chiu, Ming Ming; Chow, Bonnie Wing-Yin; Joh, Sung Wook

2017-01-01

Grouping similar students together within schools ("streaming") or classrooms ("tracking") based on past literacy skills (reported by parents), family socioeconomic status (SES) or reading attitudes might affect their reading achievement. Our multilevel analysis of the reading tests of 208,057 fourth-grade students across 40…

Single-Level and Multilevel Mediation Analysis

ERIC Educational Resources Information Center

Tofighi, Davood; Thoemmes, Felix

2014-01-01

Mediation analysis is a statistical approach used to examine how the effect of an independent variable on an outcome is transmitted through an intervening variable (mediator). In this article, we provide a gentle introduction to single-level and multilevel mediation analyses. Using single-level data, we demonstrate an application of structural…

(En)gendering Racial Disparities in Health Trajectories: A Life Course and Intersectional Analysis.

PubMed

Richardson, Liana J; Brown, Tyson H

2016-12-01

Historically, intersectionality has been an underutilized framework in sociological research on racial/ethnic and gender inequalities in health. To demonstrate its utility and importance, we conduct an intersectional analysis of the social stratification of health using the exemplar of hypertension-a health condition in which racial/ethnic and gender differences have been well-documented. Previous research has tended to examine these differences separately and ignore how the interaction of social status dimensions may influence health over time. Using seven waves of data from the Health and Retirement Study and multilevel logistic regression models, we found a multiplicative effect of race/ethnicity and gender on hypertension risk trajectories, consistent with both an intersectionality perspective and persistent inequality hypothesis. Group differences in past and contemporaneous socioeconomic and behavioral factors did not explain this effect.

The Impact of Misspecifying the Within-Subject Covariance Structure in Multiwave Longitudinal Multilevel Models: A Monte Carlo Study

ERIC Educational Resources Information Center

Kwok, Oi-man; West, Stephen G.; Green, Samuel B.

2007-01-01

This Monte Carlo study examined the impact of misspecifying the [big sum] matrix in longitudinal data analysis under both the multilevel model and mixed model frameworks. Under the multilevel model approach, under-specification and general-misspecification of the [big sum] matrix usually resulted in overestimation of the variances of the random…

National Profiles of Classroom Quality and Family Involvement: A Multilevel Examination of Proximal Influences on Head Start Children's School Readiness

ERIC Educational Resources Information Center

Bulotsky-Shearer, Rebecca J.; Wen, Xiaoli; Faria, Ann-Marie; Hahs-Vaughn, Debbie L.; Korfmacher, Jon

2012-01-01

Guided by a developmental and ecological model, the study employed latent profile analysis to identify a multilevel typology of family involvement and Head Start classroom quality. Using the nationally representative Head Start Family and Child Experiences Survey (FACES 1997; N = 1870), six multilevel latent profiles were estimated, characterized…

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…

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

Translating multilevel theory into multilevel research: Challenges and opportunities for understanding the social determinants of psychiatric disorders

PubMed Central

Dunn, Erin C.; Masyn, Katherine E.; Yudron, Monica; Jones, Stephanie M.; Subramanian, S.V.

2014-01-01

The observation that features of the social environment, including family, school, and neighborhood characteristics, are associated with individual-level outcomes has spurred the development of dozens of multilevel or ecological theoretical frameworks in epidemiology, public health, psychology, and sociology, among other disciplines. Despite the widespread use of such theories in etiological, intervention, and policy studies, challenges remain in bridging multilevel theory and empirical research. This paper set out to synthesize these challenges and provide specific examples of methodological and analytical strategies researchers are using to gain a more nuanced understanding of the social determinants of psychiatric disorders, with a focus on children’s mental health. To accomplish this goal, we begin by describing multilevel theories, defining their core elements, and discussing what these theories suggest is needed in empirical work. In the second part, we outline the main challenges researchers face in translating multilevel theory into research. These challenges are presented for each stage of the research process. In the third section, we describe two methods being used as alternatives to traditional multilevel modeling techniques to better bridge multilevel theory and multilevel research. These are: (1) multilevel factor analysis and multilevel structural equation modeling; and (2) dynamic systems approaches. Through its review of multilevel theory, assessment of existing strategies, and examination of emerging methodologies, this paper offers a framework to evaluate and guide empirical studies on the social determinants of child psychiatric disorders as well as health across the lifecourse. PMID:24469555

Is There an Association Between the “Critical Shoulder Angle” and Clinical Outcome After Rotator Cuff Repair?

PubMed Central

Kirsch, Jacob M.; Nathani, Amit; Robbins, Christopher B.; Gagnier, Joel J.; Bedi, Asheesh; Miller, Bruce S.

2017-01-01

Background: Variations in scapular morphology have been associated with the development of atraumatic rotator cuff tears (RCTs). The critical shoulder angle (CSA) accounts for both glenoid inclination and lateral extension of the acromion. The impact of the CSA on outcomes after rotator cuff repair (RCR) has not been investigated previously. Hypothesis: Our hypothesis was that individuals with smaller CSAs will have better patient-reported outcome scores over time compared with those with larger CSAs. Theoretically, a smaller CSA minimizes the biomechanical forces favoring superior translation of the humeral head, which may be advantageous after RCR. This is the first study to examine the relationship between the CSA and clinical outcomes after RCR. Study Design: Cohort study; Level of evidence, 2. Methods: Fifty-three patients (mean age, 61 years) with atraumatic full-thickness RCTs who underwent arthroscopic RCR were prospectively evaluated. Demographic data as well as the Western Ontario Rotator Cuff Index (WORC) score, American Shoulder and Elbow Surgeons (ASES) score, and a visual analog scale (VAS) for pain were prospectively collected at various time points up to 24 months postoperatively. Statistical analysis included longitudinal multilevel regression modeling to investigate the association between the CSA and the WORC, ASES, and VAS scores. Results: The overall clinical outcome, as measured by the WORC, ASES, and VAS, improved significantly (P < .0001). Controlling for demographic and clinical characteristics, a multilevel regression analysis demonstrated that the CSA was not a significant independent predictor for change in WORC (P = .581), ASES (P = .458), or VAS (P = .859) scores at 24 months after arthroscopic RCR. Interobserver and intraobserver reliability for CSA measurements resulted in interclass correlation coefficients of 0.986 and 0.982, respectively (P < .001), indicating excellent agreement. Conclusion: The CSA did not appear to be a significant predictor of patient-reported outcomes after arthroscopic repair of atraumatic full-thickness RCTs. PMID:28451621

Multivariate functional response regression, with application to fluorescence spectroscopy in a cervical pre-cancer study.

PubMed

Zhu, Hongxiao; Morris, Jeffrey S; Wei, Fengrong; Cox, Dennis D

2017-07-01

Many scientific studies measure different types of high-dimensional signals or images from the same subject, producing multivariate functional data. These functional measurements carry different types of information about the scientific process, and a joint analysis that integrates information across them may provide new insights into the underlying mechanism for the phenomenon under study. Motivated by fluorescence spectroscopy data in a cervical pre-cancer study, a multivariate functional response regression model is proposed, which treats multivariate functional observations as responses and a common set of covariates as predictors. This novel modeling framework simultaneously accounts for correlations between functional variables and potential multi-level structures in data that are induced by experimental design. The model is fitted by performing a two-stage linear transformation-a basis expansion to each functional variable followed by principal component analysis for the concatenated basis coefficients. This transformation effectively reduces the intra-and inter-function correlations and facilitates fast and convenient calculation. A fully Bayesian approach is adopted to sample the model parameters in the transformed space, and posterior inference is performed after inverse-transforming the regression coefficients back to the original data domain. The proposed approach produces functional tests that flag local regions on the functional effects, while controlling the overall experiment-wise error rate or false discovery rate. It also enables functional discriminant analysis through posterior predictive calculation. Analysis of the fluorescence spectroscopy data reveals local regions with differential expressions across the pre-cancer and normal samples. These regions may serve as biomarkers for prognosis and disease assessment.

Theoretical and software considerations for nonlinear dynamic analysis

NASA Technical Reports Server (NTRS)

Schmidt, R. J.; Dodds, R. H., Jr.

1983-01-01

In the finite element method for structural analysis, it is generally necessary to discretize the structural model into a very large number of elements to accurately evaluate displacements, strains, and stresses. As the complexity of the model increases, the number of degrees of freedom can easily exceed the capacity of present-day software system. Improvements of structural analysis software including more efficient use of existing hardware and improved structural modeling techniques are discussed. One modeling technique that is used successfully in static linear and nonlinear analysis is multilevel substructuring. This research extends the use of multilevel substructure modeling to include dynamic analysis and defines the requirements for a general purpose software system capable of efficient nonlinear dynamic analysis. The multilevel substructuring technique is presented, the analytical formulations and computational procedures for dynamic analysis and nonlinear mechanics are reviewed, and an approach to the design and implementation of a general purpose structural software system is presented.

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.

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.

Design and Analysis of an Axisymmetric Phased Array Fed Gregorian Reflector System for Limited Scanning

DTIC Science & Technology

2016-01-22

Numerical electromagnetic simulations based on the multilevel fast multipole method (MLFMM) were used to analyze and optimize the antenna...and are not necessarily endorsed by the United States Government. numerical simulations with the multilevel fast multipole method (MLFMM...and optimized using numerical simulations conducted with the multilevel fast multipole method (MLFMM) using FEKO software (www.feko.info). The

Help Seeking in Online Collaborative Groupwork: A Multilevel Analysis

ERIC Educational Resources Information Center

Du, Jianxia; Xu, Jianzhong; Fan, Xitao

2015-01-01

This study examined predictive models for students' help seeking in the context of online collaborative groupwork. Results from multilevel analysis revealed that most of the variance in help seeking was at the individual student level, and multiple variables at the individual level were predictive of help-seeking behaviour. Help seeking was…

Neighborhoods, Social Support, and African American Adolescents' Mental Health Outcomes: A Multilevel Path Analysis

ERIC Educational Resources Information Center

Hurd, Noelle M.; Stoddard, Sarah A.; Zimmerman, Marc A.

2013-01-01

This study explored how neighborhood characteristics may relate to African American adolescents' internalizing symptoms via adolescents' social support and perceptions of neighborhood cohesion. Participants included 571 urban, African American adolescents (52% female; "M" age = 17.8). A multilevel path analysis testing both direct and…

Using Multilevel Analysis to Monitor Test Performance across Administrations. Research Report. ETS RR-14-29

ERIC Educational Resources Information Center

Wei, Youhua; Qu, Yanxuan

2014-01-01

For a testing program with frequent administrations, it is important to understand and monitor the stability and fluctuation of test performance across administrations. Different methods have been proposed for this purpose. This study explored the potential of using multilevel analysis to understand and monitor examinees' test performance across…

Multilevel Structural Equation Models for the Analysis of Comparative Data on Educational Performance

ERIC Educational Resources Information Center

Goldstein, Harvey; Bonnet, Gerard; Rocher, Thierry

2007-01-01

The Programme for International Student Assessment comparative study of reading performance among 15-year-olds is reanalyzed using statistical procedures that allow the full complexity of the data structures to be explored. The article extends existing multilevel factor analysis and structural equation models and shows how this can extract richer…

Multilevel Factor Analysis by Model Segregation: New Applications for Robust Test Statistics

ERIC Educational Resources Information Center

Schweig, Jonathan

2014-01-01

Measures of classroom environments have become central to policy efforts that assess school and teacher quality. This has sparked a wide interest in using multilevel factor analysis to test measurement hypotheses about classroom-level variables. One approach partitions the total covariance matrix and tests models separately on the…

Evaluating Technical Efficiency of Nursing Care Using Data Envelopment Analysis and Multilevel Modeling.

PubMed

Min, Ari; Park, Chang Gi; Scott, Linda D

2016-05-23

Data envelopment analysis (DEA) is an advantageous non-parametric technique for evaluating relative efficiency of performance. This article describes use of DEA to estimate technical efficiency of nursing care and demonstrates the benefits of using multilevel modeling to identify characteristics of efficient facilities in the second stage of analysis. Data were drawn from LTCFocUS.org, a secondary database including nursing home data from the Online Survey Certification and Reporting System and Minimum Data Set. In this example, 2,267 non-hospital-based nursing homes were evaluated. Use of DEA with nurse staffing levels as inputs and quality of care as outputs allowed estimation of the relative technical efficiency of nursing care in these facilities. In the second stage, multilevel modeling was applied to identify organizational factors contributing to technical efficiency. Use of multilevel modeling avoided biased estimation of findings for nested data and provided comprehensive information on differences in technical efficiency among counties and states. © The Author(s) 2016.

Multilevel sparse functional principal component analysis.

PubMed

Di, Chongzhi; Crainiceanu, Ciprian M; Jank, Wolfgang S

2014-01-29

We consider analysis of sparsely sampled multilevel functional data, where the basic observational unit is a function and data have a natural hierarchy of basic units. An example is when functions are recorded at multiple visits for each subject. Multilevel functional principal component analysis (MFPCA; Di et al. 2009) was proposed for such data when functions are densely recorded. Here we consider the case when functions are sparsely sampled and may contain only a few observations per function. We exploit the multilevel structure of covariance operators and achieve data reduction by principal component decompositions at both between and within subject levels. We address inherent methodological differences in the sparse sampling context to: 1) estimate the covariance operators; 2) estimate the functional principal component scores; 3) predict the underlying curves. Through simulations the proposed method is able to discover dominating modes of variations and reconstruct underlying curves well even in sparse settings. Our approach is illustrated by two applications, the Sleep Heart Health Study and eBay auctions.

Analyzing Multiple Outcomes in Clinical Research Using Multivariate Multilevel Models

PubMed Central

Baldwin, Scott A.; Imel, Zac E.; Braithwaite, Scott R.; Atkins, David C.

2014-01-01

Objective Multilevel models have become a standard data analysis approach in intervention research. Although the vast majority of intervention studies involve multiple outcome measures, few studies use multivariate analysis methods. The authors discuss multivariate extensions to the multilevel model that can be used by psychotherapy researchers. Method and Results Using simulated longitudinal treatment data, the authors show how multivariate models extend common univariate growth models and how the multivariate model can be used to examine multivariate hypotheses involving fixed effects (e.g., does the size of the treatment effect differ across outcomes?) and random effects (e.g., is change in one outcome related to change in the other?). An online supplemental appendix provides annotated computer code and simulated example data for implementing a multivariate model. Conclusions Multivariate multilevel models are flexible, powerful models that can enhance clinical research. PMID:24491071

Predicting Falls and When to Intervene in Older People: A Multilevel Logistical Regression Model and Cost Analysis

PubMed Central

Smith, Matthew I.; de Lusignan, Simon; Mullett, David; Correa, Ana; Tickner, Jermaine; Jones, Simon

2016-01-01

Introduction Falls are the leading cause of injury in older people. Reducing falls could reduce financial pressures on health services. We carried out this research to develop a falls risk model, using routine primary care and hospital data to identify those at risk of falls, and apply a cost analysis to enable commissioners of health services to identify those in whom savings can be made through referral to a falls prevention service. Methods Multilevel logistical regression was performed on routinely collected general practice and hospital data from 74751 over 65’s, to produce a risk model for falls. Validation measures were carried out. A cost-analysis was performed to identify at which level of risk it would be cost-effective to refer patients to a falls prevention service. 95% confidence intervals were calculated using a Monte Carlo Model (MCM), allowing us to adjust for uncertainty in the estimates of these variables. Results A risk model for falls was produced with an area under the curve of the receiver operating characteristics curve of 0.87. The risk cut-off with the highest combination of sensitivity and specificity was at p = 0.07 (sensitivity of 81% and specificity of 78%). The risk cut-off at which savings outweigh costs was p = 0.27 and the risk cut-off with the maximum savings was p = 0.53, which would result in referral of 1.8% and 0.45% of the over 65’s population respectively. Above a risk cut-off of p = 0.27, costs do not exceed savings. Conclusions This model is the best performing falls predictive tool developed to date; it has been developed on a large UK city population; can be readily run from routine data; and can be implemented in a way that optimises the use of health service resources. Commissioners of health services should use this model to flag and refer patients at risk to their falls service and save resources. PMID:27448280

Determinants of unmet need for family planning in rural Burkina Faso: a multilevel logistic regression analysis.

PubMed

Wulifan, Joseph K; Jahn, Albrecht; Hien, Hervé; Ilboudo, Patrick Christian; Meda, Nicolas; Robyn, Paul Jacob; Saidou Hamadou, T; Haidara, Ousmane; De Allegri, Manuela

2017-12-19

Unmet need for family planning has implications for women and their families, such as unsafe abortion, physical abuse, and poor maternal health. Contraceptive knowledge has increased across low-income settings, yet unmet need remains high with little information on the factors explaining it. This study assessed factors associated with unmet need among pregnant women in rural Burkina Faso. We collected data on pregnant women through a population-based survey conducted in 24 rural districts between October 2013 and March 2014. Multivariate multilevel logistic regression was used to assess the association between unmet need for family planning and a selection of relevant demand- and supply-side factors. Of the 1309 pregnant women covered in the survey, 239 (18.26%) reported experiencing unmet need for family planning. Pregnant women with more than three living children [OR = 1.80; 95% CI (1.11-2.91)], those with a child younger than 1 year [OR = 1.75; 95% CI (1.04-2.97)], pregnant women whose partners disapproves contraceptive use [OR = 1.51; 95% CI (1.03-2.21)] and women who desired fewer children compared to their partners preferred number of children [OR = 1.907; 95% CI (1.361-2.672)] were significantly more likely to experience unmet need for family planning, while health staff training in family planning logistics management (OR = 0.46; 95% CI (0.24-0.73)] was associated with a lower probability of experiencing unmet need for family planning. Findings suggest the need to strengthen family planning interventions in Burkina Faso to ensure greater uptake of contraceptive use and thus reduce unmet need for family planning.

Revascularization Treatment of Emergency Patients with Acute ST-Segment Elevation Myocardial Infarction in Switzerland: Results from a Nationwide, Cross-Sectional Study in Switzerland for 2010-2011.

PubMed

Berlin, Claudia; Jüni, Peter; Endrich, Olga; Zwahlen, Marcel

2016-01-01

Cardiovascular diseases are the leading cause of death worldwide and in Switzerland. When applied, treatment guidelines for patients with acute ST-segment elevation myocardial infarction (STEMI) improve the clinical outcome and should eliminate treatment differences by sex and age for patients whose clinical situations are identical. In Switzerland, the rate at which STEMI patients receive revascularization may vary by patient and hospital characteristics. To examine all hospitalizations in Switzerland from 2010-2011 to determine if patient or hospital characteristics affected the rate of revascularization (receiving either a percutaneous coronary intervention or a coronary artery bypass grafting) in acute STEMI patients. We used national data sets on hospital stays, and on hospital infrastructure and operating characteristics, for the years 2010 and 2011, to identify all emergency patients admitted with the main diagnosis of acute STEMI. We then calculated the proportion of patients who were treated with revascularization. We used multivariable multilevel Poisson regression to determine if receipt of revascularization varied by patient and hospital characteristics. Of the 9,696 cases we identified, 71.6% received revascularization. Patients were less likely to receive revascularization if they were female, and 80 years or older. In the multivariable multilevel Poisson regression analysis, there was a trend for small-volume hospitals performing fewer revascularizations but this was not statistically significant while being female (Relative Proportion = 0.91, 95% CI: 0.86 to 0.97) and being older than 80 years was still associated with less frequent revascularization. Female and older patients were less likely to receive revascularization. Further research needs to clarify whether this reflects differential application of treatment guidelines or limitations in this kind of routine data.

Is physician adherence to prescription guidelines a general trait of health care practices or dependent on drug type?--a multilevel logistic regression analysis in South Sweden.

PubMed

Ohlsson, Henrik; Merlo, Juan

2009-08-01

Therapeutic traditions at health care practices (HCPs) influence physicians' adherence to prescription guidelines for specific drugs, however, it is not known if such traditions affect all kinds of prescriptions or only specific types of drug. Our goal was to determine whether adherence to prescription guidelines is a common trait of HCPs or dependent on drug type. We fitted separate multi-level logistic regression models to all patients in the Skåne region who received a prescription for a statin drug (ATC: C10AA, n = 6232), an agent acting on the renin-angiotensin system (ATC: C09, n = 7222) or a proton pump inhibitor (ATC: A02BC, n = 11 563) at 198 HCPs from July 2006 to December 2006. There was a high clustering of adherence to prescription guidelines at HCPs for the different drug types (MOR(agents acting on the renin-angiotensin system) = 4.72 [95% CI: 3.90-5.92], MOR(Statins) = 2.71 [95% CI: 2.23-3.39] and MOR(Proton pump inhibitors) = 2.16 [95% CI: 1.95-2.45]). Compared with HCPs with low adherence to guidelines in two drug types, those HCPs with the highest level of adherence for these two drug types also showed a higher probability of adherence for the third drug type. Physicians' decisions to follow prescription guidelines seem to be influenced by therapeutic traditions at the HCP. Moreover, these therapeutic traditions seem to affect all kinds of prescriptions. This information can be used as basis for interventions to support rational and cost-effective medication use. Copyright 2009 John Wiley & Sons, Ltd.

A Multilevel Study of Students' Motivations of Studying Accounting: Implications for Employers

ERIC Educational Resources Information Center

Law, Philip; Yuen, Desmond

2012-01-01

Purpose: The purpose of this study is to examine the influence of factors affecting students' choice of accounting as a study major in Hong Kong. Design/methodology/approach: Multinomial logistic regression and Hierarchical Generalized Linear Modeling (HGLM) are used to analyze the survey data for the level one and level two data, which is the…

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…

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…

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.

Multi-level stressor analysis from the DNA/biochemical level to community levels in an urban stream and integrative health response (IHR) assessments.

PubMed

Lee, Jae Hoon; Kim, Joon Ha; Oh, Hee-Mock; An, Kwang-Guk

2013-01-01

The objectives of this study were to identify multi-level stressors at the DNA/biochemical level to the community level in fish in an urban stream and to develop an integrative health response (IHR) model for ecological health diagnosis. A pristine control site (S (c) ) and an impacted site (S (i) ) were selected from among seven pre-screened sites studied over seven years. Various chemical analyses indicated that nutrient enrichment (Nitrogen, Phosphorus) and organic pollution were significantly greater (t > 8.783, p < 0.01) at the S (i) site compared to the S (c) site. Single-cell gel electrophoresis (comet assays) of DNA-level impairment indicated significantly (t = 5.678, p < 0.01) greater tail intensity, expressed as % tail-DNA, at the S (i) site and genotoxic responses were detected in the downstream reach. Ethoxyresorufin-O-deethylase (EROD) assays, as a physiological bioindicator, were 2.8-fold higher (p < 0.05, NK-test after ANOVA) at the S (i) site. Tissue analysis using a necropsy-based health assessment index (NHAI) showed distinct internal organ disorders in three tissues, i.e., liver, kidney, and gill, at the S (i) site. Population-level analysis using the sentinel species Zacco platypus showed that the regression coefficient (b) was 3.012 for the S (i) site and 2.915 for the S (c) site, indicating population skewness in the downstream reach. Community-level health was impaired at the S (i) site based on an index of biological integrity (IBI), and physical habitat modifications were identified by a qualitative habitat evaluation index (QHEI). Overall, the model values for the integrative health response (IHR), developed using the star plot approach, were 3.22 (80.5%) at the S (c) site and 0.74 (18.5%) at the S (i) site, indicating that, overall, ecological health impairments were evident in the urban reach. Our study was based on multi-level approaches using biological organization and the results suggest that there is a pivotal point of linkage between mechanistic understanding and real ecological consequences of environmental stressors.

Multilevel Latent Class Analysis: An Application of Adolescent Smoking Typologies with Individual and Contextual Predictors

ERIC Educational Resources Information Center

Henry, Kimberly L.; Muthen, Bengt

2010-01-01

Latent class analysis (LCA) is a statistical method used to identify subtypes of related cases using a set of categorical or continuous observed variables. Traditional LCA assumes that observations are independent. However, multilevel data structures are common in social and behavioral research and alternative strategies are needed. In this…

Multilevel Confirmatory Factor Analysis of a Scale Measuring Interagency Collaboration of Children's Mental Health Agencies

ERIC Educational Resources Information Center

Dedrick, Robert F.; Greenbaum, Paul E.

2011-01-01

Multilevel confirmatory factor analysis was used to evaluate the factor structure underlying the 12-item, three-factor "Interagency Collaboration Activities Scale" (ICAS) at the informant level and at the agency level. Results from 378 professionals (104 administrators, 201 service providers, and 73 case managers) from 32 children's mental health…

Institutional Disparities in the Cost Effectiveness of GCE A-Level Provision: A Multi-Level Approach.

ERIC Educational Resources Information Center

Fielding, A.

1995-01-01

Reanalyzes H. Thomas's 1980s data, which used teaching group as the unit of analysis and illuminated some institutional disparities in provision of General Certificate of Education (GCE) A-levels. Uses multilevel analysis to focus on individual students in a hierarchical framework. Among the study institutions, school sixth forms appear less…

A Multilevel Analysis of Japanese Middle School Student and School Socioeconomic Status Influence on Mathematics Achievement

ERIC Educational Resources Information Center

Takashiro, Naomi

2017-01-01

The author examined the simultaneous influence of Japanese middle school student and school socioeconomic status (SES) on student math achievement with two-level multilevel analysis models by utilizing the Trends in International Mathematics and Science Study (TIMSS) Japan data sets. The theoretical framework used in this study was…

Combining Multilevel Analysis with National Value-Added Data Sets - A Case Study to Explore the Effects of School Diversity

ERIC Educational Resources Information Center

Schagen, Ian; Schagen, Sandie

2005-01-01

The advent of large-scale matched data sets, linking pupils' attainment across key stages, gives new opportunities to explore the effects of school organisational factors on pupil performance. Combined with currently available sophisticated and efficient software for multilevel analysis, it offers educational researchers the chance to develop…

Examining the Influence of Campus Climate on Students' Time to Degree: A Multilevel Discrete-Time Survival Analysis

ERIC Educational Resources Information Center

Zhou, Ji; Castellanos, Michelle

2013-01-01

Utilizing longitudinal data of 3477 students from 28 institutions, we examine the effects of structural diversity and quality of interracial relation on students' persistence towards graduation within six years. We utilize multilevel discrete-time survival analysis to account for the longitudinal persistence patterns as well as the nested…

Illustration of a Multilevel Model for Meta-Analysis

ERIC Educational Resources Information Center

de la Torre, Jimmy; Camilli, Gregory; Vargas, Sadako; Vernon, R. Fox

2007-01-01

In this article, the authors present a multilevel (or hierarchical linear) model that illustrates issues in the application of the model to data from meta-analytic studies. In doing so, several issues are discussed that typically arise in the course of a meta-analysis. These include the presence of non-zero between-study variability, how multiple…

Brief Report: Multilevel Analysis of School Smoking Policy and Pupil Smoking Behaviour in Wales

ERIC Educational Resources Information Center

Wiium, Nora; Burgess, Stephen; Moore, Laurence

2011-01-01

A multilevel analysis of cross-sectional data from a survey involving 1941 pupils (in grades 10 and 11) and policy indicators developed from interviews with staff from 45 secondary schools in Wales examined the hypotheses that pupil smoking prevalence would be associated with: restrictive staff and pupil smoking policies; dissemination of school…

Three-Level Models for Indirect Effects in School- and Class-Randomized Experiments in Education

ERIC Educational Resources Information Center

Pituch, Keenan A.; Murphy, Daniel L.; Tate, Richard L.

2009-01-01

Due to the clustered nature of field data, multi-level modeling has become commonly used to analyze data arising from educational field experiments. While recent methodological literature has focused on multi-level mediation analysis, relatively little attention has been devoted to mediation analysis when three levels (e.g., student, class,…

Predicting Performance on State Achievement Tests Using Curriculum-Based Measurement in Reading: A Multilevel Meta-Analysis

ERIC Educational Resources Information Center

Yeo, Seungsoo

2010-01-01

The purpose of this synthesis was to examine the relationship between Curriculum-Based Measurement (CBM) and statewide achievement tests in reading. A multilevel meta-analysis was used to calculate the correlation coefficient of the population for 27 studies that met the inclusion criteria. Results showed an overall large correlation coefficient…

Explaining Technology Integration in K-12 Classrooms: A Multilevel Path Analysis Model

ERIC Educational Resources Information Center

Liu, Feng; Ritzhaupt, Albert D.; Dawson, Kara; Barron, Ann E.

2017-01-01

The purpose of this research was to design and test a model of classroom technology integration in the context of K-12 schools. The proposed multilevel path analysis model includes teacher, contextual, and school related variables on a teacher's use of technology and confidence and comfort using technology as mediators of classroom technology…

Multiple imputation by chained equations for systematically and sporadically missing multilevel data.

PubMed

Resche-Rigon, Matthieu; White, Ian R

2018-06-01

In multilevel settings such as individual participant data meta-analysis, a variable is 'systematically missing' if it is wholly missing in some clusters and 'sporadically missing' if it is partly missing in some clusters. Previously proposed methods to impute incomplete multilevel data handle either systematically or sporadically missing data, but frequently both patterns are observed. We describe a new multiple imputation by chained equations (MICE) algorithm for multilevel data with arbitrary patterns of systematically and sporadically missing variables. The algorithm is described for multilevel normal data but can easily be extended for other variable types. We first propose two methods for imputing a single incomplete variable: an extension of an existing method and a new two-stage method which conveniently allows for heteroscedastic data. We then discuss the difficulties of imputing missing values in several variables in multilevel data using MICE, and show that even the simplest joint multilevel model implies conditional models which involve cluster means and heteroscedasticity. However, a simulation study finds that the proposed methods can be successfully combined in a multilevel MICE procedure, even when cluster means are not included in the imputation models.

Social Capital and Suicidal Ideation in Community-Dwelling Older Residents: A Multilevel Analysis of 10,094 Subjects in Japan.

PubMed

Noguchi, Masayuki; Kobayashi, Tomoko; Iwase, Toshihide; Suzuki, Etsuji; Kawachi, Ichiro; Takao, Soshi

2017-01-01

Social capital, the collective resources of groups including perceptions of trust and reciprocity, is recognized as an important contributor to suicide. We examined the association of individual- and community-level social capital with suicidal ideation after adjusting for social support among older adults living in the community. In August 2010 we sent questionnaires to all residents aged 65 years and older living in 3 rural municipalities (N = 21,232) in Okayama Prefecture, Japan; 13,919 questionnaires were returned (response rate: 65.6%). The final analysis included 10,094 participants. The outcome variable was suicidal ideation. Exposure variables were individual-level mistrust and lack of reciprocity (level 1), and the aggregated responses of these variables from 35 communities in the municipalities (level 2). Covariates included age, sex, educational attainment, marital status, the number of cohabitants, years of residence, self-rated socioeconomic status, disability, social support, and psychological distress. Multilevel logistic regression analysis was performed to obtain odds ratios (ORs) and 95% confidence intervals (CIs). After adjusting for social support and psychological distress, we found that mistrust and lack of reciprocity were only associated with suicidal ideation at the individual level. Stratified analysis showed that among subjects with psychological distress, mistrust was associated with suicidal ideation at individual (OR: 1.88; 95% CI: 1.42-2.51) and community levels (OR: 1.98; 95% CI: 1.02-3.81). Our findings show that individual- and community-level social capital is a possible protective factor for suicidal ideation, particularly for people with psychological distress. Copyright © 2017 American Association for Geriatric Psychiatry. Published by Elsevier Inc. All rights reserved.

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.

A Multilevel Model for Comorbid Outcomes: Obesity and Diabetes in the US

PubMed Central

Congdon, Peter

2010-01-01

Multilevel models are overwhelmingly applied to single health outcomes, but when two or more health conditions are closely related, it is important that contextual variation in their joint prevalence (e.g., variations over different geographic settings) is considered. A multinomial multilevel logit regression approach for analysing joint prevalence is proposed here that includes subject level risk factors (e.g., age, race, education) while also taking account of geographic context. Data from a US population health survey (the 2007 Behavioral Risk Factor Surveillance System or BRFSS) are used to illustrate the method, with a six category multinomial outcome defined by diabetic status and weight category (obese, overweight, normal). The influence of geographic context is partly represented by known geographic variables (e.g., county poverty), and partly by a model for latent area influences. In particular, a shared latent variable (common factor) approach is proposed to measure the impact of unobserved area influences on joint weight and diabetes status, with the latent variable being spatially structured to reflect geographic clustering in risk. PMID:20616977

Hospitalization Risk Before and After Employment Among Adults With Schizophrenia, Bipolar Disorder, or Major Depression.

PubMed

Luciano, Alison; Metcalfe, Justin D; Bond, Gary R; Xie, Haiyi; Miller, Alexander L; Riley, Jarnee; O'Malley, A James; Drake, Robert E

2016-10-01

The influence of employment on subsequent psychiatric hospitalization for people with serious mental illness is unclear. This study examined whether unemployed people with serious mental illness were more or less likely to experience psychiatric hospitalization after gaining employment. A secondary analysis was conducted of data from the Mental Health Treatment Study. Two years of prospective employment and psychiatric hospital outcomes were examined for 2,055 adults with schizophrenia, bipolar disorder, or major depression. The analyses examined associations between employment and psychiatric hospitalization via multilevel regression by using time-lagged modeling. Employment was associated with a lower subsequent three-month risk of psychiatric hospitalization (odds ratio=.65, 95% confidence interval=.50-.84) after the analysis adjusted for baseline characteristics, including previous psychiatric hospitalizations and self-reported physical health. Unemployed outpatients with serious mental illness were less likely to experience psychiatric hospitalization after gaining employment.

Availability of convenience stores and adolescent alcohol use in Taiwan: a multi-level analysis of national surveys.

PubMed

Wang, Shi-Heng; Lin, I-Chin; Chen, Chuan-Yu; Chen, Duan-Rung; Chan, Ta-Chien; Chen, Wei J

2013-12-01

To examine the association between alcohol in school environments and adolescent alcohol use over the previous 6 months. A multi-level logistic regression analysis was performed of cross-sectional surveys conducted in 2004, 2005 and 2006. A total of 52 214 students aged 11-19 years from 387 middle or high schools were selected from a nationally representative, multi-stage, stratified probability sampling across Taiwan. Information on socio-demographic features and substance use experiences was collected using self-administered questionnaires. The alcohol in the environment was measured using the availability of convenience stores surrounding the schools. Using geographical information systems, the weighted numbers of convenience stores within 1 km, a 12-15-minute walk, of a school were calculated. The schools were later categorized into three subgroups via the tertile of nearby convenience stores. Considering the compositional characteristics, the availability of convenience stores was found to account for 1.5% of the school-level variance of youthful drinking. The odds ratios (95% confidence interval) of alcohol use over the previous 6 months among youth attending schools with medium and high availability were 1.04 (0.96-1.13) and 1.08 (1.00-1.17), respectively, with a P-value of 0.04 in the trend test. The greater availability of convenience stores near a school is associated with an increased risk of alcohol use among adolescents over the previous 6 months. © 2013 Society for the Study of Addiction.

The role of healthcare system in dental check-ups in 27 European countries: multilevel analysis.

PubMed

Kino, Shiho; Bernabé, Eduardo; Sabbah, Wael

2017-06-01

To examine whether public expenditure on health and Euro Health Consumer Index (EHCI) are associated with dental check-ups in European countries. Individual data were from Eurobarometer 72.3, 2009 a cross-national survey of 27 European countries. Eligible participants were those aged 18 years and older in 27 European countries. Dental check-ups reflected dental visits for oral examination and getting advice on oral health in the last 12 months. Individual factors included age, gender, marital status, urbanisation, education, subjective social status, and difficulty in paying bills. Public expenditure on health as a percentage of gross domestic product (GDP) and EHCI were used as contextual factors. A set of multilevel logistic regression models was used to examine the relationship between dental check-ups and each of healthcare expenditure and EHCI adjusting for demographic factors, GDP per capita and socioeconomic indicators. Total number included in the analysis was 23,842. Participants in countries with greater healthcare expenditure and higher score of EHCI were significantly 1.17 (95% CI: 1.03, 1.32) and 1.30 times (95% CI: 1.04, 1.64) more likely to report dental check-ups within the past 12 months after accounting for demographic characteristics, GDP per capita, and all socioeconomic indicators. The findings suggest that greater governmental support for the healthcare and better characteristics of healthcare system are positively associated with routine dental attendance. © 2017 American Association of Public Health Dentistry.

Understanding adherence to therapeutic guidelines: a multilevel analysis of statin prescription in the Skaraborg Primary Care Database.

PubMed

Hjerpe, Per; Ohlsson, Henrik; Lindblad, Ulf; Boström, Kristina Bengtsson; Merlo, Juan

2011-04-01

In Skaraborg, Sweden, the economic responsibility for tax-financed prescription drug costs was transferred from the regional administrative level to the local level (health care centre; HCC) in 2003. The aim of this study was to investigate the impact of this decentralization of economic responsibility on adherence to guidelines for prescribing lipid-lowering drugs. Data from all 24 public HCCs in Skaraborg on prescriptions for lipid-lowering drugs during 2003 and 2005 were extracted from the Skaraborg Primary Care Database (SPCD). Multilevel regression analysis (MLRA) was used to disentangle the variances at different levels of data (patient, physician, HCC). The outcome variable on the patient level was the prescription of the recommended statin (yes/no). Sex and age of the patients and sex, age and occupational status of the physician were included as fixed effects. The variance was expressed as the median odds ratio (MOR). The prevalence of adherence to guidelines for the prescription of statins increased from 77% in 2003 to 84% in 2005. The MLRA showed that in 2003 the variance was equally distributed between the HCC and physician levels (MOR(HCC2003)=1.89 vs. MOR(PHYSICIAN2003)=1.88). The variance between physicians and between HCCs decreased considerably between 2003 and 2005. The inclusion of individual and physician characteristics did not explain any of the remaining variance. The decentralized budget appears to have increased adherence to guidelines and reduced inefficient variation in prescribing.

Minimum Wage and Overweight and Obesity in Adult Women: A Multilevel Analysis of Low and Middle Income Countries.

PubMed

Conklin, Annalijn I; Ponce, Ninez A; Frank, John; Nandi, Arijit; Heymann, Jody

2016-01-01

To describe the relationship between minimum wage and overweight and obesity across countries at different levels of development. A cross-sectional analysis of 27 countries with data on the legislated minimum wage level linked to socio-demographic and anthropometry data of non-pregnant 190,892 adult women (24-49 y) from the Demographic and Health Survey. We used multilevel logistic regression models to condition on country- and individual-level potential confounders, and post-estimation of average marginal effects to calculate the adjusted prevalence difference. We found the association between minimum wage and overweight/obesity was independent of individual-level SES and confounders, and showed a reversed pattern by country development stage. The adjusted overweight/obesity prevalence difference in low-income countries was an average increase of about 0.1 percentage points (PD 0.075 [0.065, 0.084]), and an average decrease of 0.01 percentage points in middle-income countries (PD -0.014 [-0.019, -0.009]). The adjusted obesity prevalence difference in low-income countries was an average increase of 0.03 percentage points (PD 0.032 [0.021, 0.042]) and an average decrease of 0.03 percentage points in middle-income countries (PD -0.032 [-0.036, -0.027]). This is among the first studies to examine the potential impact of improved wages on an important precursor of non-communicable diseases globally. Among countries with a modest level of economic development, higher minimum wage was associated with lower levels of obesity.

The association between neighborhood social capital and self-reported dentate status in elderly Japanese--the Ohsaki Cohort 2006 Study.

PubMed

Aida, J; Kuriyama, S; Ohmori-Matsuda, K; Hozawa, A; Osaka, K; Tsuji, I

2011-06-01

Little is known about the influence of social capital on dental health. The aim of the present cross-sectional study was to determine the association between neighborhood social capital, individual social networks and social support and the number of remaining teeth in elderly Japanese. In December 2006, self-administered questionnaires were sent to 31,237 eligible community-dwelling individuals (response rate: 73.9%). Included in the analysis were 21,736 participants. Five neighborhood social capital variables were calculated from individual civic networks, sports and hobby networks, volunteer networks, friendship networks and social support variables. We used multilevel logistic regression models to estimate the odds ratio (OR) of having 20 or more teeth according to neighborhood social capital variables with adjustment for sex, age, individual social networks and social support, educational attainment, neighborhood educational level, dental health behavior, smoking status, history of diabetes and self-rated health. The average age of the participants was 74.9 (standard deviation; 6.6) years, and 28.5% of them had 20 or more teeth. In the univariate multilevel model, there were statistically significant associations between neighborhood sports and hobby networks, friendship networks and self-reported dentate status. In the multivariable multilevel model, compared with participants living in lowest friendship network neighborhoods, those living in highest friendship network neighborhoods had an OR 1.17 (95% confidence interval, 1.04-1.30) times higher for having 20 or more teeth. There is a significant association between one network aspect of neighborhood social capital and individual dentate status regardless of individual social networks and social support. © 2010 John Wiley & Sons A/S.

Does Social Context Matter? Income Inequality, Racialized Identity, and Health Among Canada's Aboriginal Peoples Using a Multilevel Approach.

PubMed

Spence, Nicholas D

2016-03-01

Debates surrounding the importance of social context versus individual level processes have a long history in public health. Aboriginal peoples in Canada are very diverse, and the reserve communities in which they reside are complex mixes of various cultural and socioeconomic circumstances. The social forces of these communities are believed to affect health, in addition to individual level determinants, but no large scale work has ever probed their relative effects. One aspect of social context, relative deprivation, as indicated by income inequality, has greatly influenced the social determinants of health landscape. An investigation of relative deprivation in Canada's Aboriginal population has never been conducted. This paper proposes a new model of Aboriginal health, using a multidisciplinary theoretical approach that is multilevel. This study explored the self-rated health of respondents using two levels of determinants, contextual and individual. Data were from the 2001 Aboriginal Peoples Survey. There were 18,890 Registered First Nations (subgroup of Aboriginal peoples) on reserve nested within 134 communities. The model was assessed using a hierarchical generalized linear model. There was no significant variation at the contextual level. Subsequently, a sequential logistic regression analysis was run. With the sole exception culture, demographics, lifestyle factors, formal health services, and social support were significant in explaining self-rated health. The non-significant effect of social context, and by extension relative deprivation, as indicated by income inequality, is noteworthy, and the primary role of individual level processes, including the material conditions, social support, and lifestyle behaviors, on health outcomes is illustrated. It is proposed that social structure is best conceptualized as a dynamic determinant of health inequality and more multilevel theoretical models of Aboriginal health should be developed and tested.

Area-level socioeconomic inequalities in the use of mammography screening: A multilevel analysis of the Health of Houston Survey

PubMed Central

Calo, William A.; Vernon, Sally W.; Lairson, David R.; Linder, Stephen H.

2015-01-01

Background An emerging literature reports that women who reside in socioeconomically deprived communities are less likely to adhere to mammography screening. This study explored associations between area-level socioeconomic measures and mammography screening among a racially and ethnically diverse sample of women in Texas. Methods We conducted a cross-sectional multilevel study linking individual-level data from the 2010 Health of Houston Survey and contextual data from the U.S. Census. Women ages 40–74 years (N=1,541) were included in the analyses. We examined tract-level poverty, unemployment, education, Hispanic and Black composition, female-headed householder families, and crowding as contextual measures. Using multilevel logistic regression modeling, we compared most disadvantaged tracts (quartiles 2–4) to the most advantaged tract (quartile 1). Results Overall, 64% of the sample was adherent to mammography screening. Screening rates were lower (P<.05) among Hispanics, those foreign born, women aged 40–49 years, and those with low educational attainment, unemployed, and without health insurance coverage. Women living in areas with high levels of poverty (quartile 2 vs. quartile 1: OR=0.50; 95% CI: 0.30–0.85), Hispanic composition (quartile 3 vs. quartile 1: OR=0.54; 95% CI: 0.32–0.90), and crowding (quartile 4 vs. quartile 1: OR=0.53; 95% CI: 0.29–0.96) were less likely to have up-to-date mammography screening, net of individual-level factors. Conclusion Our findings highlight the importance of examining area-level socioeconomic inequalities in mammography screening. The study represents an advance on previous research because we examined multiple area measures, controlled for key individual-level covariates, used data aggregated at the tract level, and accounted for the nested structure of the data. PMID:26809487

Parental supply of alcohol and adolescent drinking: a multilevel analysis of nationally representative data.

PubMed

Chan, Gary C K; Leung, Janni; Connor, Jason; Hall, Wayne; Kelly, Adrian B

2017-06-09

Existing research on parental supply of alcohol analyses the effects of self-reported parental supply on adolescent drinking using individual level data. This study examined the contextual effect of parental supply of alcohol on adolescent alcohol use by examining the association between the prevalence of parental supply in each Australian state and adolescent alcohol use using a multilevel analytic framework. Adolescent samples (Age: 12-17) were drawn from the four National Drug Strategy Household Surveys (2004, 2007, 2010 and 2013; N = 6803). The prevalence of parental supply of alcohol, defined as the weighted percentage of sample who reported obtaining alcohol from their parents, was estimated in each state and territory across the four surveys. Three multilevel logistic regressions were used to examine the contextual effects of parental supply prevalence on adolescents' alcohol use in the past 12 months, weekly drinking and heavy drinking. Overall, adolescents' rates of past 12 months alcohol use, heavy drinking and weekly drinking between 2004 and 2013 were 40.1, 14.4 and 6.4% respectively. The prevalence of parental supply was significantly associated with past 12 months alcohol use (OR = 1.06, p < .001) and heavy drinking (OR = 1.04, p < .001) but not with weekly drinking (OR = 1.03, p = .189). The results were adjusted for gender, age, socio-economic index for area, place of birth, survey year and prevalence of peer supply. A high prevalence of parental supply in a region was associated with heavier adolescent drinking, regardless of whether adolescents primarily obtained their alcohol from their own parents.

Multilevel Examination of Job Satisfaction and Career Intentions of Collegiate Athletic Trainers: A Quantitative Approach.

PubMed

Eason, Christianne M; Mazerolle, Stephanie M; Denegar, Craig R; Pitney, William A; McGarry, Jennifer

2018-01-01

  Recent employment data from collegiate athletic training settings have demonstrated departure trends among men and women. These trends have been hypothesized to be related to work-life balance. However, work-life balance is only 1 aspect of a myriad of factors. Due to the complex nature of the work-life interface, a multilevel examination is needed to better understand the precipitators of departure.   To quantitatively examine factors that may influence collegiate athletic trainers' (ATs') job satisfaction and career intentions via a multilevel examination of the work-life interface.   Cross-sectional study.   Web-based questionnaire.   Athletic trainers employed in National Collegiate Athletic Association Division I, II, or III or National Association of Intercollegiate Athletics colleges or universities (N = 299: 56.5% female, 43.5% male). The average age of participants was 33.6 ± 8.3 years, and their average experience was 10.3 ± 7.6 years.   Participants responded to an online questionnaire consisting of demographic questions, 9 Likert-scale surveys, and open-ended questions. Job-satisfaction Scores (JSSs) and intention-to-leave scores (ITLSs) served as the dependent variables and factors from individual, organizational, and sociocultural levels were the independent variables. Hierarchical regression analysis was run to determine the predictability of factors.   No sex differences in ITLS or JSS were found in our sample. Independent variables explained 68.5% of the variance in JSS and 28.8% of the variance in ITLS. Additions of factor levels increased the percentage of explained variance in both scores.   A combination of individual-, organizational-, and sociocultural-level factors was able to best predict JSS and ITLS among collegiate ATs.

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.

Trimethoprim and ciprofloxacin resistance and prescribing in urinary tract infection associated with Escherichia coli: a multilevel model.

PubMed

Vellinga, Akke; Tansey, Sana; Hanahoe, Belinda; Bennett, Kathleen; Murphy, Andrew W; Cormican, Martin

2012-10-01

Individual and group level factors associated with the probability of antimicrobial resistance of uropathogenic Escherichia coli were analysed in a multilevel model. Adult patients consulting with a suspected urinary tract infection (UTI) in 22 general practices over a 9 month period supplied a urine sample for laboratory analysis. Cases were patients with a UTI associated with a resistant E. coli. Previous antimicrobial exposure and other patient characteristics were recorded from the medical files. Six hundred and thirty-three patients with an E. coli UTI and a full record for all variables were included. Of the E. coli isolates, 36% were resistant to trimethoprim and 12% to ciprofloxacin. A multilevel logistic regression model was fitted. The odds that E. coli was resistant increased with increasing number of prescriptions over the previous year for trimethoprim from 1.4 (0.8-2.2) for one previous prescription to 4.7 (1.9-12.4) for two and 6.4 (2.0-25.4) for three or more. For ciprofloxacin the ORs were 2.7 (1.2-5.6) for one and 6.5 (2.9-14.8) for two or more. The probability that uropathogenic E. coli was resistant showed important variation between practices and a difference of 17% for trimethoprim and 33% for ciprofloxacin was observed for an imaginary patient moving from a practice with low to a practice with high probability. This difference could not be explained by practice prescribing or practice resistance levels. Previous antimicrobial use and the practice visited affect the risk that a patient with a UTI will be diagnosed with an E. coli resistant to this agent, which was particularly important for ciprofloxacin.

Classroom relationship qualities and social-cognitive correlates of defending and passive bystanding in school bullying in Sweden: A multilevel analysis.

PubMed

Thornberg, Robert; Wänström, Linda; Hong, Jun Sung; Espelage, Dorothy L

2017-08-01

Using the social-ecological and social cognitive theories as integrated guiding frameworks, the present study examined whether moral disengagement and defender self-efficacy at the individual level, and moral disengagement, quality of teacher-student relationships and quality of student-student relationships at the classroom level were associated with passive bystanding and defending in bullying situations. Participants were 900 Swedish students from 43 classrooms, ranging in age from 9 to 13years. Multilevel regression analyses revealed that passive reactions by bystanders were associated with greater moral disengagement and less defender self-efficacy. Defending, in turn, was associated with less moral disengagement and greater defender self-efficacy and classroom student-student relationship quality. Furthermore, students who scored high in moral disengagement were even less prone to defend victims when the classroom student-student relationship quality was low, but more prone to act as defenders when the classroom student-student relationship quality was high. In addition, the negative association between defender self-efficacy and passive bystanding was stronger both in classrooms with higher student-student relationship quality and in those with lower class moral disengagement. Implications for prevention are discussed. Copyright © 2017 Society for the Study of School Psychology. All rights reserved.

Variability in adherence to clinical practice guidelines and recommendations in COPD outpatients: a multi-level, cross-sectional analysis of the EPOCONSUL study.

PubMed

Calle Rubio, Myriam; López-Campos, José Luis; Soler-Cataluña, Juan J; Alcázar Navarrete, Bernardino; Soriano, Joan B; Rodríguez González-Moro, José Miguel; Fuentes Ferrer, Manuel E; Rodríguez Hermosa, Juan Luis

2017-12-02

Clinical audits have reported considerable variability in COPD medical care and frequent inconsistencies with recommendations. The objectives of this study were to identify factors associated with a better adherence to clinical practice guidelines and to explore determinants of this variability at the the hospital level. EPOCONSUL is a Spanish nationwide clinical audit that evaluates the outpatient management of COPD. Multilevel logistic regression with two levels was performed to assess the relationships between individual and disease-related factors, as well as hospital characteristics. A total of 4508 clinical records of COPD patients from 59 Spanish hospitals were evaluated. High variability was observed among hospitals in terms of medical care. Some of the patient's characteristics (airflow obstruction, degree of dyspnea, exacerbation risk, presence of comorbidities), the hospital factors (size and respiratory nurses available) and treatment at a specialized COPD outpatient clinic were identified as factors associated with a better adherence to recommendations, although this only explains a small proportion of the total variance. To be treated at a specialized COPD outpatient clinic and some intrinsic patient characteristics were factors associated with a better adherence to guideline recommendations, although these variables were only explaining part of the high variability observed among hospitals in terms of COPD medical care.

Advanced analytical methodologies for measuring healthy ageing and its determinants, using factor analysis and machine learning techniques: the ATHLOS project

PubMed Central

Félix Caballero, Francisco; Soulis, George; Engchuan, Worrawat; Sánchez-Niubó, Albert; Arndt, Holger; Ayuso-Mateos, José Luis; Haro, Josep Maria; Chatterji, Somnath; Panagiotakos, Demosthenes B.

2017-01-01

A most challenging task for scientists that are involved in the study of ageing is the development of a measure to quantify health status across populations and over time. In the present study, a Bayesian multilevel Item Response Theory approach is used to create a health score that can be compared across different waves in a longitudinal study, using anchor items and items that vary across waves. The same approach can be applied to compare health scores across different longitudinal studies, using items that vary across studies. Data from the English Longitudinal Study of Ageing (ELSA) are employed. Mixed-effects multilevel regression and Machine Learning methods were used to identify relationships between socio-demographics and the health score created. The metric of health was created for 17,886 subjects (54.6% of women) participating in at least one of the first six ELSA waves and correlated well with already known conditions that affect health. Future efforts will implement this approach in a harmonised data set comprising several longitudinal studies of ageing. This will enable valid comparisons between clinical and community dwelling populations and help to generate norms that could be useful in day-to-day clinical practice. PMID:28281663

Social participation, social capital and daily tobacco smoking: a population-based multilevel analysis in Malmö, Sweden.

PubMed

Lindström, Martin; Moghaddassi, Mahnaz; Bolin, Kristian; Lindgren, Björn; Merlo, Juan

2003-01-01

The aim of this study was to investigate the influence of contextual and individual factors on daily tobacco smoking. The public-health survey in Malmö 1994 is a cross-sectional study. A total of 5600 individuals aged 20-80 years were invited to answer a postal questionnaire. The participation rate was 71%. A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second, was performed. We analysed the effect (intra-area correlation, cross-level modification and odds ratios) of individual and neighbourhood factors on smoking after adjustment for individual factors. Neighbourhood factors accounted for 2.5% of the crude total variance in daily tobacco smoking. This effect was significantly reduced when the individual factors such as education were included in the model. However, individual social capital, measured by social participation, only marginally affected the total neighbourhood variance in daily tobacco smoking. In fact, no significant variance in daily tobacco smoking remained after the introduction of the individual factors other than individual social capital in the model. In Malmö, the neighbourhood variance in daily tobacco smoking is mainly affected by individual factors other than individual social capital, especially socioeconomic status measured as level of education.

School Leadership and Cyberbullying—A Multilevel Analysis

PubMed Central

Låftman, Sara B.; Östberg, Viveca; Modin, Bitte

2017-01-01

Cyberbullying is a relatively new form of bullying, with both similarities and differences to traditional bullying. While earlier research has examined associations between school-contextual characteristics and traditional bullying, fewer studies have focused on the links to students’ involvement in cyberbullying behavior. The aim of the present study is to assess whether school-contextual conditions in terms of teachers’ ratings of the school leadership are associated with the occurrence of cyberbullying victimization and perpetration among students. The data are derived from two separate data collections performed in 2016: The Stockholm School Survey conducted among students in the second grade of upper secondary school (ages 17–18 years) in Stockholm municipality, and the Stockholm Teacher Survey which was carried out among teachers in the same schools. The data include information from 6067 students distributed across 58 schools, linked with school-contextual information based on reports from 1251 teachers. Cyberbullying victimization and perpetration are measured by students’ self-reports. Teachers’ ratings of the school leadership are captured by an index based on 10 items; the mean value of this index was aggregated to the school level. Results from binary logistic multilevel regression models show that high teacher ratings of the school leadership are associated with less cyberbullying victimization and perpetration. We conclude that a strong school leadership potentially prevents cyberbullying behavior among students. PMID:29036933

School Leadership and Cyberbullying-A Multilevel Analysis.

PubMed

Låftman, Sara B; Östberg, Viveca; Modin, Bitte

2017-10-15

Cyberbullying is a relatively new form of bullying, with both similarities and differences to traditional bullying. While earlier research has examined associations between school-contextual characteristics and traditional bullying, fewer studies have focused on the links to students' involvement in cyberbullying behavior. The aim of the present study is to assess whether school-contextual conditions in terms of teachers' ratings of the school leadership are associated with the occurrence of cyberbullying victimization and perpetration among students. The data are derived from two separate data collections performed in 2016: The Stockholm School Survey conducted among students in the second grade of upper secondary school (ages 17-18 years) in Stockholm municipality, and the Stockholm Teacher Survey which was carried out among teachers in the same schools. The data include information from 6067 students distributed across 58 schools, linked with school-contextual information based on reports from 1251 teachers. Cyberbullying victimization and perpetration are measured by students' self-reports. Teachers' ratings of the school leadership are captured by an index based on 10 items; the mean value of this index was aggregated to the school level. Results from binary logistic multilevel regression models show that high teacher ratings of the school leadership are associated with less cyberbullying victimization and perpetration. We conclude that a strong school leadership potentially prevents cyberbullying behavior among students.

Inequalities in mortality by socioeconomic factors and Roma ethnicity in the two biggest cities in Slovakia: a multilevel analysis.

PubMed

Rosicova, Katarina; Reijneveld, Sijmen A; Madarasova Geckova, Andrea; Stewart, Roy E; Rosic, Martin; Groothoff, Johan W; van Dijk, Jitse P

2015-11-05

The socioeconomic and ethnic composition of urban neighbourhoods may affect mortality, but evidence on Central European cities is lacking. The aim of this study was to assess the associations between socioeconomic and ethnic neighbourhood indicators and the mortality of individuals aged 20-64 years old in the two biggest cities of the Slovak Republic. We obtained data on the characteristics of neighbourhoods and districts (educational level, unemployment, income and share of Roma) and on individual mortality of residents aged 20-64 years old, for the two largest cities in the Slovak Republic (Bratislava and Kosice) in the period 2003-2005. We performed multilevel Poisson regression analyses adjusted for age and gender on the individual (mortality), neighbourhood (education level and share of Roma in population) and district levels (unemployment and income). The proportions of Roma and of low-educated residents were associated with mortality at the neighbourhood level in both cities. Mutually adjusted, only the association with the proportion of Roma remained in the model (risk ratio 1.02; 95 % confidence interval 1.01-1.04). The area indicators - high education, income and unemployment - were not associated with mortality. The proportion of Roma is associated with early mortality in the two biggest cities in the Slovak Republic.

Insular pathways to health care in the city: a multilevel analysis of access to hospital care in urban Kerala, India.

PubMed

Levesque, Jean-Frédéric; Haddad, Slim; Narayana, Delampady; Fournier, Pierre

2007-07-01

To identify individual and urban unit characteristics associated with access to inpatient care in public and private sectors in urban Kerala, and to discuss policy implications of inequalities in access. We analysed the NSSO survey (1995-1996) for urban Kerala with regard to source and trajectories of hospitalization. Multinomial multilevel regression models were built for 695 cases nested in 24 urban units. Private sector accounts for 62% of hospitalizations. Only 31% of hospitalizations are in free wards and 20% of public hospitalizations involve payment. Hospitalization pathways suggest a segmentation of public and private health markets. Members of poor and casual worker households have lower propensity of hospitalization in paying public wards or private hospitals. There were important variations between cities, with higher odds of private hospitalization in towns with fewer hospital beds overall and in districts with high private-public bed ratios. Cities from districts with better economic indicators and dominance of private services have higher proportion of private hospitalizations. The private sector is the predominant source of inpatient care in urban Kerala. The public sector has an important role in providing access to care for the poor. Investing in the quality of public services is essential to ensure equity in access.

Effects of individual characteristics and school environment on cigarette smoking among students ages 13-15: A multilevel analysis of the 2007 Global Youth Tobacco Survey (GYTS) data from Vietnam.

PubMed

Van Minh, Hoang; Hai, Phan Thi; Giang, Kim Bao; Nga, Pham Quynh; Khanh, Pham Huyen; Lam, Nguyen Tuan; Kinh, Ly Ngoc

2011-01-01

This paper aims to estimate the prevalence of cigarette smoking among students in Vietnam ages 13-15 and examines its relationship with compositional and contextual factors. The data used in this paper were obtained from the 2007 Global Youth Tobacco Survey conducted in nine provinces in Vietnam. A multilevel logistic regression model was applied to analyse the association between the current incidence of cigarette smoking and factors on both the individual and school level. The prevalence of cigarette smoking among students was 3.3% overall. The prevalence of smoking among male students (5.9%) was higher than that among females (1.2%). Parental smoking was a significant risk factor for smoking among the students. Having a friend who smoked was the strongest predictor of smoking status among the study subjects. We have demonstrated that school-level factors appeared to impact the prevalence of cigarette smoking among students ages 13-15. This paper highlights the importance of utilising an extensive range of actions to prevent students from using tobacco in Vietnam. These actions should include providing specific curricula for students that address both individual characteristics and the school environment. Further, prevention programmes should also target both parental- and peer-smoking issues.

Can economic deprivation protect health? Paradoxical multilevel effects of poverty on Hispanic children's wheezing.

PubMed

Collins, Timothy W; Kim, Young-an; Grineski, Sara E; Clark-Reyna, Stephanie

2014-08-06

Prior research suggests that economic deprivation has a generally negative influence on residents' health. We employ hierarchical logistic regression modeling to test if economic deprivation presents respiratory health risks or benefits to Hispanic children living in the City of El Paso (Texas, USA) at neighborhood- and individual-levels, and whether individual-level health effects of economic deprivation vary based on neighborhood-level economic deprivation. Data come from the US Census Bureau and a population-based survey of El Paso schoolchildren. The dependent variable is children's current wheezing, an established respiratory morbidity measure, which is appropriate for use with economically-deprived children with an increased likelihood of not receiving a doctor's asthma diagnosis. Results reveal that economic deprivation (measured based on poverty status) at both neighborhood- and individual-levels is associated with reduced odds of wheezing for Hispanic children. A sensitivity analysis revealed similar significant effects of individual- and neighborhood-level poverty on the odds of doctor-diagnosed asthma. Neighborhood-level poverty did not significantly modify the observed association between individual-level poverty and Hispanic children's wheezing; however, greater neighborhood poverty tends to be more protective for poor (as opposed to non-poor) Hispanic children. These findings support a novel, multilevel understanding of seemingly paradoxical effects of economic deprivation on Hispanic health.

Authoritative School Climate and High School Student Risk Behavior: A Cross-sectional Multi-level Analysis of Student Self-Reports.

PubMed

Cornell, Dewey; Huang, Francis

2016-11-01

Many adolescents engage in risk behaviors such as substance use and aggression that jeopardize their healthy development. This study tested the hypothesis that an authoritative school climate characterized by strict but fair discipline and supportive teacher-student relationships is conducive to lower risk behavior for high school students. Multilevel logistic regression models were used to analyze cross-sectional, student-report survey data from a statewide sample of 47,888 students (50.6 % female) in 319 high schools. The students included ninth (26.6 %), tenth (25.5 %), eleventh (24.1 %) and twelfth (23.8 %) grade with a racial/ethnic breakdown of 52.2 % White, 18.0 % Black, 13.1 % Hispanic, 5.9 % Asian, and 10.8 % reporting another or two or more race/ethnicities. Schools with an authoritative school climate had lower levels of student-reported alcohol and marijuana use; bullying, fighting, and weapon carrying at school; interest in gang membership; and suicidal thoughts and behavior. These results controlled for demographic variables of student gender, race, grade, and parent education level as well as school size, percentage of minority students, and percentage of low income students. Overall, these findings add new evidence that an authoritative school climate is associated with positive student outcomes.

Can Economic Deprivation Protect Health? Paradoxical Multilevel Effects of Poverty on Hispanic Children’s Wheezing

PubMed Central

Collins, Timothy W.; Kim, Young-an; Grineski, Sara E.; Clark-Reyna, Stephanie

2014-01-01

Prior research suggests that economic deprivation has a generally negative influence on residents’ health. We employ hierarchical logistic regression modeling to test if economic deprivation presents respiratory health risks or benefits to Hispanic children living in the City of El Paso (Texas, USA) at neighborhood- and individual-levels, and whether individual-level health effects of economic deprivation vary based on neighborhood-level economic deprivation. Data come from the US Census Bureau and a population-based survey of El Paso schoolchildren. The dependent variable is children’s current wheezing, an established respiratory morbidity measure, which is appropriate for use with economically-deprived children with an increased likelihood of not receiving a doctor’s asthma diagnosis. Results reveal that economic deprivation (measured based on poverty status) at both neighborhood- and individual-levels is associated with reduced odds of wheezing for Hispanic children. A sensitivity analysis revealed similar significant effects of individual- and neighborhood-level poverty on the odds of doctor-diagnosed asthma. Neighborhood-level poverty did not significantly modify the observed association between individual-level poverty and Hispanic children’s wheezing; however, greater neighborhood poverty tends to be more protective for poor (as opposed to non-poor) Hispanic children. These findings support a novel, multilevel understanding of seemingly paradoxical effects of economic deprivation on Hispanic health. PMID:25101769

Do doctors' attachment styles and emotional intelligence influence patients' emotional expressions in primary care consultations? An exploratory study using multilevel analysis.

PubMed

Cherry, M Gemma; Fletcher, Ian; Berridge, Damon; O'Sullivan, Helen

2018-04-01

To investigate whether and how doctors' attachment styles and emotional intelligence (EI) might influence patients' emotional expressions in general practice consultations. Video recordings of 26 junior doctors consulting with 173 patients were coded using the Verona Coding Definition of Emotional Sequences (VR-CoDES). Doctors' attachment style was scored across two dimensions, avoidance and anxiety, using the Experiences in Close Relationships: Short Form questionnaire. EI was assessed with the Mayer-Salovey-Caruso Emotional Intelligence Test. Multilevel Poisson regressions modelled the probability of patients' expressing emotional distress, considering doctors' attachment styles and EI and demographic and contextual factors. Both attachment styles and EI were significantly associated with frequency of patients' cues, with patient- and doctor-level explanatory variables accounting for 42% of the variance in patients' cues. The relative contribution of attachment styles and EI varied depending on whether patients' presenting complaints were physical or psychosocial in nature. Doctors' attachment styles and levels of EI are associated with patients' emotional expressions in primary care consultations. Further research is needed to investigate how these two variables interact and influence provider responses and patient outcomes. Understanding how doctors' psychological characteristics influence PPC may help to optimise undergraduate and postgraduate medical education. Copyright © 2017 Elsevier B.V. All rights reserved.

Has decentralisation affected child immunisation status in Indonesia?

PubMed

Maharani, Asri; Tampubolon, Gindo

2014-01-01

The past two decades have seen many countries, including a number in Southeast Asia, decentralising their health system with the expectation that this reform will improve their citizens' health. However, the consequences of this reform remain largely unknown. This study analyses the effects of fiscal decentralisation on child immunisation status in Indonesia. We used multilevel logistic regression analysis to estimate these effects, and multilevel multiple imputation to manage missing data. The 2011 publication of Indonesia's national socio-economic survey (Susenas) is the source of household data, while the Podes village census survey from the same year provides village-level data. We supplement these with local government fiscal data from the Ministry of Finance. The findings show that decentralising the fiscal allocation of responsibilities to local governments has a lack of association with child immunisation status and the results are robust. The results also suggest that increasing the number of village health centres (posyandu) per 1,000 population improves probability of children to receive full immunisation significantly, while increasing that of hospitals and health centres (puskesmas) has no significant effect. These findings suggest that merely decentralising the health system does not guarantee improvement in a country's immunisation coverage. Any successful decentralisation demands good capacity and capability of local governments.

Neighbourhood environments and obesity among adults: A multilevel analysis of an urban Brazilian context.

PubMed

Matozinhos, Fernanda Penido; Gomes, Crizian Saar; Andrade, Amanda Cristina de Souza; Mendes, Larissa Loures; Pessoa, Milene Cristine; Friche, Amélia Augusta de Lima; Velasquez-Melendez, Gustavo

2015-01-01

Objective. This study identified environmental variables associated with obesity in the adult population of a city in Brazil. Methods. It was conducted using the Surveillance System for Risk and Protective Factors for Chronic Diseases by Telephone Survey from 2008 to 2010. The body mass index (BMI) was calculated from the participants' self-reported weight and height. Obesity was defined as a BMI ≥ 30 kg/m2. The food establishments, georeferenced areas conducive to physical activity, total income of the neighbourhood, homicide rate and population density were used to characterise the environment. In addition, individual variables were considered. A multilevel logistic regression was performed. Results. A total of 5273 individuals were evaluated. The odds of obesity was found to be significantly decreased with increases in the number of establishments that sell healthy food, number of restaurants, number of places for physical activity and total income - in different models. In addition, these associations remained significant after adjustment for age, gender, education and consumption of meat with visible fat. Conclusions. This study contributes to a better understanding of the complex interaction between environmental and individual determinants of obesity and may aid in the development of effective interventions, such as the expansion of obesity control programmes.

Investigating the relationship between costs and outcomes for English mental health providers: a bi-variate multi-level regression analysis.

PubMed

Moran, Valerie; Jacobs, Rowena

2018-06-01

Provider payment systems for mental health care that incentivize cost control and quality improvement have been a policy focus in a number of countries. In England, a new prospective provider payment system is being introduced to mental health that should encourage providers to control costs and improve outcomes. The aim of this research is to investigate the relationship between costs and outcomes to ascertain whether there is a trade-off between controlling costs and improving outcomes. The main data source is the Mental Health Minimum Data Set (MHMDS) for the years 2011/12 and 2012/13. Costs are calculated using NHS reference cost data while outcomes are measured using the Health of the Nation Outcome Scales (HoNOS). We estimate a bivariate multi-level model with costs and outcomes simultaneously. We calculate the correlation and plot the pairwise relationship between residual costs and outcomes at the provider level. After controlling for a range of demographic, need, social, and treatment variables, residual variation in costs and outcomes remains at the provider level. The correlation between residual costs and outcomes is negative, but very small, suggesting that cost-containment efforts by providers should not undermine outcome-improving efforts under the new payment system.

Has decentralisation affected child immunisation status in Indonesia?

PubMed Central

Maharani, Asri; Tampubolon, Gindo

2014-01-01

Background The past two decades have seen many countries, including a number in Southeast Asia, decentralising their health system with the expectation that this reform will improve their citizens’ health. However, the consequences of this reform remain largely unknown. Objective This study analyses the effects of fiscal decentralisation on child immunisation status in Indonesia. Design We used multilevel logistic regression analysis to estimate these effects, and multilevel multiple imputation to manage missing data. The 2011 publication of Indonesia's national socio-economic survey (Susenas) is the source of household data, while the Podes village census survey from the same year provides village-level data. We supplement these with local government fiscal data from the Ministry of Finance. Results The findings show that decentralising the fiscal allocation of responsibilities to local governments has a lack of association with child immunisation status and the results are robust. The results also suggest that increasing the number of village health centres (posyandu) per 1,000 population improves probability of children to receive full immunisation significantly, while increasing that of hospitals and health centres (puskesmas) has no significant effect. Conclusion These findings suggest that merely decentralising the health system does not guarantee improvement in a country's immunisation coverage. Any successful decentralisation demands good capacity and capability of local governments. PMID:25160515

Individual and contextual factors influencing dental health care utilization by preschool children: a multilevel analysis

PubMed

Piovesan, Chaiana; Ardenghi, Thiago Machado; Mendes, Fausto Medeiros; Agostini, Bernardo Antonio; Michel-Crosato, Edgard

2017-03-30

The effect of contextual factors on dental care utilization was evaluated after adjustment for individual characteristics of Brazilian preschool children. This cross-sectional study assessed 639 preschool children aged 1 to 5 years from Santa Maria, a town in Rio Grande do Sul State, located in southern Brazil. Participants were randomly selected from children attending the National Children's Vaccination Day and 15 health centers were selected for this research. Visual examinations followed the ICDAS criteria. Parents answered a questionnaire about demographic and socioeconomic characteristics. Contextual influences on children's dental care utilization were obtained from two community-related variables: presence of dentists and presence of workers' associations in the neighborhood. Unadjusted and adjusted multilevel logistic regression models were used to describe the association between outcome and predictor variables. A prevalence of 21.6% was found for regular use of dental services. The unadjusted assessment of the associations of dental health care utilization with individual and contextual factors included children's ages, family income, parents' schooling, mothers' participation in their children's school activities, dental caries, and presence of workers' associations in the neighborhood as the main outcome covariates. Individual variables remained associated with the outcome after adding contextual variables in the model. In conclusion, individual and contextual variables were associated with dental health care utilization by preschool children.

Advanced analytical methodologies for measuring healthy ageing and its determinants, using factor analysis and machine learning techniques: the ATHLOS project.

PubMed

Caballero, Francisco Félix; Soulis, George; Engchuan, Worrawat; Sánchez-Niubó, Albert; Arndt, Holger; Ayuso-Mateos, José Luis; Haro, Josep Maria; Chatterji, Somnath; Panagiotakos, Demosthenes B

2017-03-10

A most challenging task for scientists that are involved in the study of ageing is the development of a measure to quantify health status across populations and over time. In the present study, a Bayesian multilevel Item Response Theory approach is used to create a health score that can be compared across different waves in a longitudinal study, using anchor items and items that vary across waves. The same approach can be applied to compare health scores across different longitudinal studies, using items that vary across studies. Data from the English Longitudinal Study of Ageing (ELSA) are employed. Mixed-effects multilevel regression and Machine Learning methods were used to identify relationships between socio-demographics and the health score created. The metric of health was created for 17,886 subjects (54.6% of women) participating in at least one of the first six ELSA waves and correlated well with already known conditions that affect health. Future efforts will implement this approach in a harmonised data set comprising several longitudinal studies of ageing. This will enable valid comparisons between clinical and community dwelling populations and help to generate norms that could be useful in day-to-day clinical practice.

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.

Multilevel Latent Class Analysis for Large-Scale Educational Assessment Data: Exploring the Relation between the Curriculum and Students' Mathematical Strategies

ERIC Educational Resources Information Center

Fagginger Auer, Marije F.; Hickendorff, Marian; Van Putten, Cornelis M.; Béguin, Anton A.; Heiser, Willem J.

2016-01-01

A first application of multilevel latent class analysis (MLCA) to educational large-scale assessment data is demonstrated. This statistical technique addresses several of the challenges that assessment data offers. Importantly, MLCA allows modeling of the often ignored teacher effects and of the joint influence of teacher and student variables.…

Multilevel Analysis of the Impact of School-Level Tobacco Policies on Adolescent Smoking: The Case of Michigan

ERIC Educational Resources Information Center

Paek, Hye-Jin; Hove, Thomas; Oh, Hyun Jung

2013-01-01

Background: In efforts to curb and prevent youth smoking, school tobacco policies have become an important and effective strategy. This study explores the degrees and types of tobacco-free school policy (TFSP) enforcement that are associated with adolescent smoking. Methods: A multilevel analysis was performed using 983 students who are nested in…

Employees' Willingness to Participate in Work-Related Learning: A Multilevel Analysis of Employees' Learning Intentions

ERIC Educational Resources Information Center

Kyndt, Eva; Onghena, Patrick; Smet, Kelly; Dochy, Filip

2014-01-01

The current study focuses on employees' learning intentions, or the willingness to undertake formal work-related learning. This cross-sectional survey study included a sample of 1,243 employees that are nested within 21 organisations. The results of the multilevel analysis show that self-directedness in career processes, time management,…

A Multilevel Shape Fit Analysis of Neutron Transmission Data

NASA Astrophysics Data System (ADS)

Naguib, K.; Sallam, O. H.; Adib, M.; Ashry, A.

A multilevel shape fit analysis of neutron transmission data is presented. A multilevel computer code SHAPE is used to analyse clean transmission data obtained from time-of-flight (TOF) measurements. The shape analysis deduces the parameters of the observed resonances in the energy region considered in the measurements. The shape code is based upon a least square fit of a multilevel Briet-Wigner formula and includes both instrumental resolution and Doppler broadenings. Operating the SHAPE code on a test example of a measured transmission data of 151Eu, 153Eu and natural Eu in the energy range 0.025-1 eV accquired a good result for the used technique of analysis.Translated AbstractAnalyse von Neutronentransmissionsdaten mittels einer VielniveauformanpassungNeutronentransmissionsdaten werden in einer Vielniveauformanpassung analysiert. Dazu werden bereinigte Daten aus Flugzeitmessungen mit dem Rechnerprogramm SHAPE bearbeitet. Man erhält die Parameter der beobachteten Resonanzen im gemessenen Energiebereich. Die Formanpassung benutzt eine Briet-Wignerformel und berücksichtigt Linienverbreiterungen infolge sowohl der Meßeinrichtung als auch des Dopplereffekts. Als praktisches Beispiel werden 151Eu, 153Eu und natürliches Eu im Energiebereich 0.025 bis 1 eV mit guter Übereinstimmung theoretischer und experimenteller Werte behandelt.

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

Multilevel selection analysis of a microbial social trait

PubMed Central

de Vargas Roditi, Laura; Boyle, Kerry E; Xavier, Joao B

2013-01-01

The study of microbial communities often leads to arguments for the evolution of cooperation due to group benefits. However, multilevel selection models caution against the uncritical assumption that group benefits will lead to the evolution of cooperation. We analyze a microbial social trait to precisely define the conditions favoring cooperation. We combine the multilevel partition of the Price equation with a laboratory model system: swarming in Pseudomonas aeruginosa. We parameterize a population dynamics model using competition experiments where we manipulate expression, and therefore the cost-to-benefit ratio of swarming cooperation. Our analysis shows that multilevel selection can favor costly swarming cooperation because it causes population expansion. However, due to high costs and diminishing returns constitutive cooperation can only be favored by natural selection when relatedness is high. Regulated expression of cooperative genes is a more robust strategy because it provides the benefits of swarming expansion without the high cost or the diminishing returns. Our analysis supports the key prediction that strong group selection does not necessarily mean that microbial cooperation will always emerge. PMID:23959025

An Exploration of Teacher Attrition and Mobility in High Poverty Racially Segregated Schools

ERIC Educational Resources Information Center

Djonko-Moore, Cara M.

2016-01-01

The purpose of this study was to examine the mobility (movement to a new school) and attrition (quitting teaching) patterns of teachers in high poverty, racially segregated (HPRS) schools in the US. Using 2007-9 survey data from the National Center for Education Statistics, a multi-level multinomial logistic regression was performed to examine the…

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)…

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…

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

Factors Associated With Care Workers' Intention to Leave Employment in Nursing Homes: A Secondary Data Analysis of the Swiss Nursing Homes Human Resources Project.

PubMed

Gaudenz, Clergia; De Geest, Sabina; Schwendimann, René; Zúñiga, Franziska

2017-07-01

The emerging care personnel shortage in Swiss nursing homes is aggravated by high turnover rates. As intention to leave is a predictor of turnover, awareness of its associated factors is essential. This study applied a secondary data analysis to evaluate the prevalence and variability of 3,984 nursing home care workers' intention to leave. Work environment factors and care worker outcomes were tested via multiple regression analysis. Although 56% of care workers reported intention to leave, prevalences varied widely between facilities. Overall, intention to leave showed strong inverse relationships with supportive leadership and affective organizational commitment and weaker positive relationships with stress due to workload, emotional exhaustion, and care worker health problems. The strong direct relationship of nursing home care workers' intention to leave with affective organizational commitment and perceptions of leadership quality suggest that multilevel interventions to improve these factors might reduce intention to leave.

Weighted graph cuts without eigenvectors a multilevel approach.

PubMed

Dhillon, Inderjit S; Guan, Yuqiang; Kulis, Brian

2007-11-01

A variety of clustering algorithms have recently been proposed to handle data that is not linearly separable; spectral clustering and kernel k-means are two of the main methods. In this paper, we discuss an equivalence between the objective functions used in these seemingly different methods--in particular, a general weighted kernel k-means objective is mathematically equivalent to a weighted graph clustering objective. We exploit this equivalence to develop a fast, high-quality multilevel algorithm that directly optimizes various weighted graph clustering objectives, such as the popular ratio cut, normalized cut, and ratio association criteria. This eliminates the need for any eigenvector computation for graph clustering problems, which can be prohibitive for very large graphs. Previous multilevel graph partitioning methods, such as Metis, have suffered from the restriction of equal-sized clusters; our multilevel algorithm removes this restriction by using kernel k-means to optimize weighted graph cuts. Experimental results show that our multilevel algorithm outperforms a state-of-the-art spectral clustering algorithm in terms of speed, memory usage, and quality. We demonstrate that our algorithm is applicable to large-scale clustering tasks such as image segmentation, social network analysis and gene network analysis.

The Psychosocial Work Environment, Employee Mental Health and Organizational Interventions: Improving Research and Practice by Taking a Multilevel Approach.

PubMed

Martin, Angela; Karanika-Murray, Maria; Biron, Caroline; Sanderson, Kristy

2016-08-01

Although there have been several calls for incorporating multiple levels of analysis in employee health and well-being research, studies examining the interplay between individual, workgroup, organizational and broader societal factors in relation to employee mental health outcomes remain an exception rather than the norm. At the same time, organizational intervention research and practice also tends to be limited by a single-level focus, omitting potentially important influences at multiple levels of analysis. The aims of this conceptual paper are to help progress our understanding of work-related determinants of employee mental health by the following: (1) providing a rationale for routine multilevel assessment of the psychosocial work environment; (2) discussing how a multilevel perspective can improve related organizational interventions; and (3) highlighting key theoretical and methodological considerations relevant to these aims. We present five recommendations for future research, relating to using appropriate multilevel research designs, justifying group-level constructs, developing group-level measures, expanding investigations to the organizational level and developing multilevel approaches to intervention design, implementation and evaluation. Copyright © 2014 John Wiley & Sons, Ltd. Copyright © 2014 John Wiley & Sons, Ltd.

Multi-Level Discourse Analysis in a Physics Teaching Methods Course from the Psychological Perspective of Activity Theory

ERIC Educational Resources Information Center

Vieira, Rodrigo Drumond; Kelly, Gregory J.

2014-01-01

In this paper, we present and apply a multi-level method for discourse analysis in science classrooms. This method is based on the structure of human activity (activity, actions, and operations) and it was applied to study a pre-service physics teacher methods course. We argue that such an approach, based on a cultural psychological perspective,…

The Role of School and Individual Differences in the Academic Attainment of Learners with Special Educational Needs and Disabilities: A Multi-Level Analysis

ERIC Educational Resources Information Center

Humphrey, Neil; Wigelsworth, Michael; Barlow, Alexandra; Squires, Garry

2013-01-01

Students with special educational needs and disabilities (SEND) are at a greatly increased risk of poor academic outcomes. Understanding the factors that influence their attainment is a crucial first step towards developing more effective provision. In the current study we present a multi-level, natural variation analysis which highlights…

The Quadratic Relationship between Socioeconomic Status and Learning Performance in China by Multilevel Analysis: Implications for Policies to Foster Education Equity

ERIC Educational Resources Information Center

Zhao, Ningning; Valcke, Martin; Desoete, Annemie; Verhaeghe, JeanPierre

2012-01-01

The purpose of the present study is to explore the relationship between family socioeconomic status and mathematics performance on the base of a multi-level analysis involving a large sample of Chinese primary school students. A weak relationship is found between socioeconomic status and performance in the Chinese context. The relationship does…

The Number of Feedbacks Needed for Reliable Evaluation. A Multilevel Analysis of the Reliability, Stability and Generalisability of Students' Evaluation of Teaching

ERIC Educational Resources Information Center

Rantanen, Pekka

2013-01-01

A multilevel analysis approach was used to analyse students' evaluation of teaching (SET). The low value of inter-rater reliability stresses that any solid conclusions on teaching cannot be made on the basis of single feedbacks. To assess a teacher's general teaching effectiveness, one needs to evaluate four randomly chosen course implementations.…

A Multilevel Analysis of the Compositional and Contextual Association of Social Capital and Subjective Well-Being in Seoul, South Korea

ERIC Educational Resources Information Center

Han, Sehee; Kim, Heaseung; Lee, Hee-Sun

2013-01-01

The purpose of this study is to examine the association between social capital and subjective well-being (life satisfaction) by using multilevel analysis considering both individual and area-level social capital while adjusting for various control variables at multiple-levels in Seoul, South Korea. The data was from the 2010 (Wave 2) Seoul Welfare…

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.

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.

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.

Multilevel Green's function interpolation method for scattering from composite metallic and dielectric objects.

PubMed

Shi, Yan; Wang, Hao Gang; Li, Long; Chan, Chi Hou

2008-10-01

A multilevel Green's function interpolation method based on two kinds of multilevel partitioning schemes--the quasi-2D and the hybrid partitioning scheme--is proposed for analyzing electromagnetic scattering from objects comprising both conducting and dielectric parts. The problem is formulated using the surface integral equation for homogeneous dielectric and conducting bodies. A quasi-2D multilevel partitioning scheme is devised to improve the efficiency of the Green's function interpolation. In contrast to previous multilevel partitioning schemes, noncubic groups are introduced to discretize the whole EM structure in this quasi-2D multilevel partitioning scheme. Based on the detailed analysis of the dimension of the group in this partitioning scheme, a hybrid quasi-2D/3D multilevel partitioning scheme is proposed to effectively handle objects with fine local structures. Selection criteria for some key parameters relating to the interpolation technique are given. The proposed algorithm is ideal for the solution of problems involving objects such as missiles, microstrip antenna arrays, photonic bandgap structures, etc. Numerical examples are presented to show that CPU time is between O(N) and O(N log N) while the computer memory requirement is O(N).

Self-defeating behaviors in organizations: the relationship between thwarted belonging and interpersonal work behaviors.

PubMed

Thau, Stefan; Aquino, Karl; Poortvliet, P Marijn

2007-05-01

This multisource field study applied belongingness theory to examine whether thwarted belonging, defined as the perceived discrepancy between one's desired and actual levels of belonging with respect to one's coworkers, predicts interpersonal work behaviors that are self-defeating. Controlling for demographic variables, job type, justice constructs, and trust in organization in a multilevel regression analysis using data from 130 employees of a clinical chemical laboratory and their supervisors, the authors found that employees who perceive greater levels of desired coworker belonging than actual levels of coworker belonging were more likely to engage in interpersonally harmful and less likely to engage in interpersonally helpful behaviors. Implications for the application of belongingness theory to explain self-defeating behaviors in organizations are discussed. 2007 APA, all rights reserved

Multilevel Interventions: Study Design and Analysis Issues

PubMed Central

Gross, Cary P.; Zaslavsky, Alan M.; Taplin, Stephen H.

2012-01-01

Multilevel interventions, implemented at the individual, physician, clinic, health-care organization, and/or community level, increasingly are proposed and used in the belief that they will lead to more substantial and sustained changes in behaviors related to cancer prevention, detection, and treatment than would single-level interventions. It is important to understand how intervention components are related to patient outcomes and identify barriers to implementation. Designs that permit such assessments are uncommon, however. Thus, an important way of expanding our knowledge about multilevel interventions would be to assess the impact of interventions at different levels on patients as well as the independent and synergistic effects of influences from different levels. It also would be useful to assess the impact of interventions on outcomes at different levels. Multilevel interventions are much more expensive and complicated to implement and evaluate than are single-level interventions. Given how little evidence there is about the value of multilevel interventions, however, it is incumbent upon those arguing for this approach to do multilevel research that explicates the contributions that interventions at different levels make to the desired outcomes. Only then will we know whether multilevel interventions are better than more focused interventions and gain greater insights into the kinds of interventions that can be implemented effectively and efficiently to improve health and health care for individuals with cancer. This chapter reviews designs for assessing multilevel interventions and analytic ways of controlling for potentially confounding variables that can account for the complex structure of multilevel data. PMID:22623596

Multilevel analysis of facial expressions of emotion and script: self-report (arousal and valence) and psychophysiological correlates.

PubMed

Balconi, Michela; Vanutelli, Maria Elide; Finocchiaro, Roberta

2014-09-26

The paper explored emotion comprehension in children with regard to facial expression of emotion. The effect of valence and arousal evaluation, of context and of psychophysiological measures was monitored. Indeed subjective evaluation of valence (positive vs. negative) and arousal (high vs. low), and contextual (facial expression vs. facial expression and script) variables were supposed to modulate the psychophysiological responses. Self-report measures (in terms of correct recognition, arousal and valence attribution) and psychophysiological correlates (facial electromyography, EMG, skin conductance response, SCR, and heart rate, HR) were observed when children (N = 26; mean age = 8.75 y; range 6-11 y) looked at six facial expressions of emotions (happiness, anger, fear, sadness, surprise, and disgust) and six emotional scripts (contextualized facial expressions). The competencies about the recognition, the evaluation on valence and arousal was tested in concomitance with psychophysiological variations. Specifically, we tested for the congruence of these multiple measures. Log-linear analysis and repeated measure ANOVAs showed different representations across the subjects, as a function of emotion. Specifically, children' recognition and attribution were well developed for some emotions (such as anger, fear, surprise and happiness), whereas some other emotions (mainly disgust and sadness) were less clearly represented. SCR, HR and EMG measures were modulated by the evaluation based on valence and arousal, with increased psychophysiological values mainly in response to anger, fear and happiness. As shown by multiple regression analysis, a significant consonance was found between self-report measures and psychophysiological behavior, mainly for emotions rated as more arousing and negative in valence. The multilevel measures were discussed at light of dimensional attribution model.

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.

Multilevel analysis of facial expressions of emotion and script: self-report (arousal and valence) and psychophysiological correlates

PubMed Central

2014-01-01

Background The paper explored emotion comprehension in children with regard to facial expression of emotion. The effect of valence and arousal evaluation, of context and of psychophysiological measures was monitored. Indeed subjective evaluation of valence (positive vs. negative) and arousal (high vs. low), and contextual (facial expression vs. facial expression and script) variables were supposed to modulate the psychophysiological responses. Methods Self-report measures (in terms of correct recognition, arousal and valence attribution) and psychophysiological correlates (facial electromyography, EMG, skin conductance response, SCR, and heart rate, HR) were observed when children (N = 26; mean age = 8.75 y; range 6-11 y) looked at six facial expressions of emotions (happiness, anger, fear, sadness, surprise, and disgust) and six emotional scripts (contextualized facial expressions). The competencies about the recognition, the evaluation on valence and arousal was tested in concomitance with psychophysiological variations. Specifically, we tested for the congruence of these multiple measures. Results Log-linear analysis and repeated measure ANOVAs showed different representations across the subjects, as a function of emotion. Specifically, children’ recognition and attribution were well developed for some emotions (such as anger, fear, surprise and happiness), whereas some other emotions (mainly disgust and sadness) were less clearly represented. SCR, HR and EMG measures were modulated by the evaluation based on valence and arousal, with increased psychophysiological values mainly in response to anger, fear and happiness. Conclusions As shown by multiple regression analysis, a significant consonance was found between self-report measures and psychophysiological behavior, mainly for emotions rated as more arousing and negative in valence. The multilevel measures were discussed at light of dimensional attribution model. PMID:25261242

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…

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

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.

Correlation analysis between change in thoracic kyphosis and multilevel facetectomy and screw density in main thoracic adolescent idiopathic scoliosis surgery.

PubMed

Sudo, Hideki; Abe, Yuichiro; Kokabu, Terufumi; Ito, Manabu; Abumi, Kuniyoshi; Ito, Yoichi M; Iwasaki, Norimasa

2016-09-01

Controversy exists regarding the effects of multilevel facetectomy and screw density on deformity correction, especially thoracic kyphosis (TK) restoration in adolescent idiopathic scoliosis (AIS) surgery. This study aimed to evaluate the effects of multilevel facetectomy and screw density on sagittal plane correction in patients with main thoracic (MT) AIS curve. A retrospective correlation and comparative analysis of prospectively collected, consecutive, non-randomized series of patients at a single institution was undertaken. Sixty-four consecutive patients with Lenke type 1 AIS treated with posterior correction and fusion surgery using simultaneous double-rod rotation technique were included. Patient demographics and preoperative and 2-year postoperative radiographic measurements were the outcome measures for this study. Multiple stepwise linear regression analysis was conducted between change in TK (T5-T12) and the following factors: age at surgery, Risser sign, number of facetectomy level, screw density, preoperative main thoracic curve, flexibility in main thoracic curve, coronal correction rate, preoperative TK, and preoperative lumbar lordosis. Patients were classified into two groups: TK<15° group defined by preoperative TK below the mean degree of TK for the entire cohort (<15°) and the TK≥15° group, defined by preoperative TK above the mean degree of kyphosis (≥15°). Independent sample t tests were used to compare demographic data as well as radiographic outcomes between the two groups. There were no study-specific biases related to conflicts of interest. The average preoperative TK was 14.0°, which improved significantly to 23.1° (p<.0001) at the 2-year final follow-up. Greater change in TK was predicted by a low preoperative TK (p<.0001). The TK <15° group showed significant correlation between change in TK and number of facetectomy level (r=0.492, p=.002). Similarly, significant correlation was found between change in TK and screw density (r=0.333, p=.047). Conversely, in the TK ≥15° group, correlation was found neither between change in TK and number of facetectomy level (r=0.047, p=.812), nor with screw density (r=0.030, p=.880). Furthermore, in patients with preoperative TK<15°, change in TK was significantly correlated with screw density at the concave side (r=0.351, p=.036) but not at the convex side (r=0.144, p=.402). In patients with hypokyphotic thoracic spine, significant positive correlation was found between change in TK and multilevel facetectomy or screw density at the concave side. This indicates that in patients with AIS who have thoracic hypokyphosis as part of their deformity, the abovementioned factors must be considered in preoperative planning to correct hypokyphosis. Copyright © 2016 Elsevier Inc. All rights reserved.

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.

Social deprivation and adverse perinatal outcomes among Western and non-Western pregnant women in a Dutch urban population.

PubMed

Poeran, Jashvant; Maas, Arno F G; Birnie, Erwin; Denktas, Semiha; Steegers, Eric A P; Bonsel, Gouke J

2013-04-01

Social deprivation is considered a key factor in adverse perinatal outcomes. Rotterdam, the second largest city in The Netherlands, has large inequalities in perinatal health and a high number of deprived neighbourhoods. Social deprivation is measured here through a composite variable: 'Social Index' (SI). We studied the impact of the SI (2008-2009; 5 categories) in terms of perinatal mortality, congenital anomalies, preterm birth, small for gestational age (SGA) and low 5-minute Apgar score as registered in The Netherlands Perinatal Registry (Rotterdam 2000-2007, n = 56,443 singleton pregnancies). We applied ethnic dichotomisation as Western (European/North-American/Australian) vs. Non-Western (all others) ethnicity was expected to interact with the impact of SI. Tests for trend and multilevel regression analysis were applied. Gradually decreasing prevalence of adverse perinatal outcomes was observed in Western women from the lowest SI category (low social quality) to the highest SI category (high social quality). In Western women the low-high SI gradient for prevalence of spontaneous preterm birth (per 1000) changed from 57.2 to 34.1, for iatrogenic preterm birth from 35.2 to 19.0, for SGA from 119.6 to 59.4, for low Apgar score from 10.9 to 8.2, and for perinatal mortality from 14.9 to 7.6. These trends were statistically confirmed by Chi2-tests for trend (p < 0.001). For non-Western women such trends were absent. These strong effects for Western women were confirmed by significant odds ratios for almost all adverse perinatal outcomes estimated from multilevel regression analysis. We conclude social deprivation to play a different role among Western vs. non-Western women. Our results suggest that improvements in social quality may improve perinatal outcomes in Western women, but alternative approaches may be necessary for non-Western groups. Suggested explanations for non-Western 'migrant' groups include the presence of 'protective' effects through knowledge systems or intrinsic resilience. Implications concern both general and targeted policies. Copyright © 2013 Elsevier Ltd. All rights reserved.

[Hospital variation in anastomotic leakage after rectal cancer surgery in the Spanish Association of Surgeons project: The contribution of hospital volume].

PubMed

Ortiz, Héctor; Biondo, Sebastiano; Codina, Antonio; Ciga, Miguel Á; Enríquez-Navascués, José; Espín, Eloy; García-Granero, Eduardo; Roig, José Vicente

2016-04-01

This multicentre observational study aimed to determine the anastomotic leak rate in the hospitals included in the Rectal Cancer Project of the Spanish Society of Surgeons and examine whether hospital volume may contribute to any variation between hospitals. Hospital variation was quantified using a multilevel approach on prospective data derived from the multicentre database of all adenocarcinomas of the rectum operated by an anterior resection at 84 surgical departments from 2006 to 2013. The following variables were included in the analysis; demographics, American Society of Anaesthesiologists classification, use of defunctioning stoma, tumour location and stage, administration of neoadjuvant treatment, and annual volume of elective surgical procedures. A total of 7231 consecutive patients were included. The rate of anastomotic leak was 10.0%. Stratified by annual surgical volume hospitals varied from 9.9 to 11.3%. In multilevel regression analysis, the risk of anastomotic leak increased in male patients, in patients with tumours located below 12 cm from the anal verge, and advanced tumour stages. However, a defunctioning stoma seemed to prevent this complication. Hospital surgical volume was not associated with anastomotic leak (OR: 0.852, [0.487-1.518]; P=.577). Furthermore, there was a statistically significant variation in anastomotic leak between all departments (MOR: 1.475; [1.321-1.681]; P<0.001). Anastomotic leak varies significantly among hospitals included in the project and this difference cannot be attributed to the annual surgical volume. Copyright © 2015 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.

Minimum Wage and Overweight and Obesity in Adult Women: A Multilevel Analysis of Low and Middle Income Countries

PubMed Central

Conklin, Annalijn I.; Ponce, Ninez A.; Frank, John; Nandi, Arijit; Heymann, Jody

2016-01-01

Objectives To describe the relationship between minimum wage and overweight and obesity across countries at different levels of development. Methods A cross-sectional analysis of 27 countries with data on the legislated minimum wage level linked to socio-demographic and anthropometry data of non-pregnant 190,892 adult women (24–49 y) from the Demographic and Health Survey. We used multilevel logistic regression models to condition on country- and individual-level potential confounders, and post-estimation of average marginal effects to calculate the adjusted prevalence difference. Results We found the association between minimum wage and overweight/obesity was independent of individual-level SES and confounders, and showed a reversed pattern by country development stage. The adjusted overweight/obesity prevalence difference in low-income countries was an average increase of about 0.1 percentage points (PD 0.075 [0.065, 0.084]), and an average decrease of 0.01 percentage points in middle-income countries (PD -0.014 [-0.019, -0.009]). The adjusted obesity prevalence difference in low-income countries was an average increase of 0.03 percentage points (PD 0.032 [0.021, 0.042]) and an average decrease of 0.03 percentage points in middle-income countries (PD -0.032 [-0.036, -0.027]). Conclusion This is among the first studies to examine the potential impact of improved wages on an important precursor of non-communicable diseases globally. Among countries with a modest level of economic development, higher minimum wage was associated with lower levels of obesity. PMID:26963247

Multilevel analysis of the role of human factors in regional disparities in crash outcomes.

PubMed

Adanu, Emmanuel Kofi; Smith, Randy; Powell, Lars; Jones, Steven

2017-12-01

A growing body of research has examined the disparities in road traffic safety among population groups and geographic regions. These studies reveal disparities in crash outcomes between people and regions with different socioeconomic characteristics. A critical aspect of the road traffic crash epidemic that has received limited attention is the influence of local characteristics on human elements that increase the risk of getting into a crash. This paper applies multilevel logistic regression modeling techniques to investigate the influence of driver residential factors on driver behaviors in an attempt to explain the area-based differences in the severity of road crashes across the State of Alabama. Specifically, the paper reports the effects of characteristics attributable to drivers and the geographic regions they reside on the likelihood of a crash resulting in serious injuries. Model estimation revealed that driver residence (postal code or region) accounted for about 7.3% of the variability in the probability of a driver getting into a serious injury crash, regardless of driver characteristics. The results also reveal disparities in serious injury crash rate as well as significant proportions of serious injury crashes involving no seatbelt usage, driving under influence (DUI), unemployed drivers, young drivers, distracted driving, and African American drivers among some regions. The average credit scores, average commute times, and populations of driver postal codes are shown to be significant predictors for risk of severe injury crashes. This approach to traffic crash analysis presented can serve as the foundation for evidence-based policies and also guide the implementation of targeted countermeasures. Copyright © 2017 Elsevier Ltd. All rights reserved.

Multilevel Analysis Methods for Partially Nested Cluster Randomized Trials

ERIC Educational Resources Information Center

Sanders, Elizabeth A.

2011-01-01

This paper explores multilevel modeling approaches for 2-group randomized experiments in which a treatment condition involving clusters of individuals is compared to a control condition involving only ungrouped individuals, otherwise known as partially nested cluster randomized designs (PNCRTs). Strategies for comparing groups from a PNCRT in the…

Characterization of biosurfactant produced by petrofilic bacteria isolated from hydrocarbon impacted soil and its potential application in bioremediation

NASA Astrophysics Data System (ADS)

Arsyah, D. M.; Kardena, E.; Helmy, Q.

2018-01-01

The study adopts a multi-level perspective in technology transition to analyse how the transition process in the development of geothermal energy in Indonesia is able to compete against the incumbent fossil-fuelled energy sources. Three levels of multi-level perspective are socio-technical landscape (ST-landscape), socio-technical regime (ST-regime) and niche innovations in Indonesia geothermal development. The identification, mapping and analysis of the dynamic relationship between each level are the important pillars of the multi-level perspective framework. The analysis considers the set of rules, actors and controversies that may arise in the technological transition process. The identified geothermal resource risks are the basis of the emerging geothermal technological innovations in Indonesian geothermal. The analysis of this study reveals the transition pathway, which yields a forecast for the Indonesian geothermal technology transition in the form of scenarios and probable impacts.

Interviewer effects on non-response propensity in longitudinal surveys: a multilevel modelling approach

PubMed Central

Vassallo, Rebecca; Durrant, Gabriele B; Smith, Peter W F; Goldstein, Harvey

2015-01-01

The paper investigates two different multilevel approaches, the multilevel cross-classified and the multiple-membership models, for the analysis of interviewer effects on wave non-response in longitudinal surveys. The models proposed incorporate both interviewer and area effects to account for the non-hierarchical structure, the influence of potentially more than one interviewer across waves and possible confounding of area and interviewer effects arising from the non-random allocation of interviewers across areas. The methods are compared by using a data set: the UK Family and Children Survey. PMID:25598587

The influence of compositional and contextual factors on non-receipt of basic vaccines among children of 12-23-month old in India: a multilevel analysis.

PubMed

Sissoko, Daouda; Trottier, Helen; Malvy, Denis; Johri, Mira

2014-01-01

Children unreached by vaccination are at higher risk of poor health outcomes and India accounts for nearly a quarter of unvaccinated children worldwide. The objective of this study was to investigate compositional and contextual determinants of non-receipt of childhood vaccines in India using multilevel modelling. We studied characteristics of unvaccinated children using the District Level Health and Facility Survey 3, a nationally representative probability sample containing 65 617 children aged 12-23 months from 34 Indian states and territories. We developed four-level Bayesian binomial regression models to examine the determinants of non-vaccination. The analysis considered two outcomes: completely unvaccinated (CUV) children who had not received any of the eight vaccine doses recommended by India's Universal Immunization Programme, and children who had not received any dose from routine immunisation services (no RI). The no RI category includes CUV children and those who received only polio doses administered via mass campaigns. Overall, 4.83% (95% CI: 4.62-5.06) of children were CUV while 12.01% (11.68-12.35) had received no RI. Individual compositional factors strongly associated with CUV were: non-receipt of tetanus immunisation for mothers during pregnancy (OR = 3.65 [95% CrI: 3.30-4.02]), poorest household wealth index (OR = 2.44 [1.81-3.22] no maternal schooling (OR = 2.43 [1.41-4.05]) and no paternal schooling (OR = 1.83 [1.30-2.48]). In rural settings, the influence of maternal illiteracy disappeared whereas the role of household wealth index was reinforced. Factors associated with no RI were similar to those for CUV, but effect sizes for individual compositional factors were generally larger. Low maternal education was the strongest risk factor associated with no RI in all models. All multilevel models found significant variability at community, district, and state levels net of compositional factors. Non-vaccination in India is strongly related to compositional characteristics and is geographically distinct. Tailored strategies are required to overcome current barriers to immunisation.

Does the Neighborhood Area of Residence Influence Non-Attendance in an Urban Mammography Screening Program? A Multilevel Study in a Swedish City

PubMed Central

Lagerlund, Magdalena; Merlo, Juan; Vicente, Raquel Pérez; Zackrisson, Sophia

2015-01-01

Background and aim The public health impact of population-based mammography screening programs depends on high participation rates. Thus, monitoring participation rates, as well as understanding and considering the factors influencing attendance, is important. With the goal to acquire information on the appropriate level of intervention for increasing screening participation our study aimed to (1) examine whether, over and above individual factors, the neighborhood of residence influences a woman’s mammography non-attendance, and (2) evaluate, whether knowing a woman’s neighborhood of residence would be sufficient to predict non-attendance. Methods We analyze all women invited to mammography screening in 2005–09, residing in the city of Malmö, Sweden. Information regarding mammography screening attendance was linked to data on area of residence, demographic and socioeconomic characteristics available from Statistics Sweden. The influence of individual and neighborhood factors was assessed by multilevel logistic regression analysis with 29,901 women nested within 212 neighborhoods. Results The prevalence of non-attendance among women was 18.3%. After adjusting for individual characteristics, the prevalence in the 212 neighborhoods was 3.6%. Neighborhood of residence had little influence on non-attendance. The multilevel analysis indicates that 8.4% of the total individual differences in the propensity of non-attendance were at the neighborhood level. However, when adjusting for specific individual characteristics this general contextual effect decreased to 1.8%. This minor effect was explained by the sociodemographic characteristic of the neighborhoods. The discriminatory accuracy of classifying women according to their non-attendance was 0.747 when considering only individual level variables, and 0.760 after including neighborhood level as a random effect. Conclusion Our results suggest that neighborhoods of residence in Malmö, Sweden (as defined by small-area market statistics (SAMS) areas) do not condition women’s participation in population based mammography screening. Thus, interventions should be directed to the whole city and target women with a higher risk of non-attendance. PMID:26460609

Significant variations in the cervical cancer screening rate in China by individual-level and geographical measures of socioeconomic status: a multilevel model analysis of a nationally representative survey dataset.

PubMed

Bao, Heling; Zhang, Lei; Wang, Limin; Zhang, Mei; Zhao, Zhenping; Fang, Liwen; Cong, Shu; Zhou, Maigeng; Wang, Linhong

2018-05-01

Variations in cervical cancer screening rates in China have rarely been studied in depth. This study aimed to investigate cervical cancer screening rates in relation to both individual-level and geographical measures of socioeconomic status (SES). Data were obtained from women aged 21 years or older by face-to-face interviews between August 2013 and July 2014 as part of the Chinese Chronic Diseases and Risk Factors Surveillance. The geographical variables were obtained from the 2010 Chinese population census. The cervical cancer screening rates and 95% confidence interval (CI) were estimated and mapped. Multilevel logistic regression models were fitted. Overall, only 21.4% (95% CI: 19.6-23.1%) of 91,816 women aged ≥21 years reported having ever been screened for cervical cancer and significant geographical variations at both province and county levels were identified (P < 0.01). The cervical cancer screening rates were the lowest among the poor [13.9% (95% CI: 12.1-15.7%)], uninsured [14.4% (95% CI: 10.3-18.4%)], less-educated [16.0% (95% CI: 14.3-17.6%)], and agricultural employment [18.1% (95% CI: 15.8-20.4%)] women along with those residing in areas of low economic status [15.0% (95% CI: 11.8-18.2%)], of low urbanization [15.6% (95% CI: 13.4-17.7%)], and of low education status [16.0% (95% CI: 14.0-18.1%)]. The multilevel analysis also indicated that women with lower individual-level measures of SES residing in areas with low geographical measures of SES were significantly less likely to receive cervical cancer screening (P < 0.0001). Despite the launch of an organized cancer screening program in China, cervical cancer screening rates remain alarmingly low and significant variations based on geographical regions and measures of SES still exist. It is therefore essential to adopt strategies to better direct limited available public resources to priority groups. © 2018 The Authors. Cancer Medicine published by John Wiley & Sons Ltd.

Multivariate Longitudinal Analysis with Bivariate Correlation Test

PubMed Central

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model’s parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated. PMID:27537692

Multivariate Longitudinal Analysis with Bivariate Correlation Test.

PubMed

Adjakossa, Eric Houngla; Sadissou, Ibrahim; Hounkonnou, Mahouton Norbert; Nuel, Gregory

2016-01-01

In the context of multivariate multilevel data analysis, this paper focuses on the multivariate linear mixed-effects model, including all the correlations between the random effects when the dimensional residual terms are assumed uncorrelated. Using the EM algorithm, we suggest more general expressions of the model's parameters estimators. These estimators can be used in the framework of the multivariate longitudinal data analysis as well as in the more general context of the analysis of multivariate multilevel data. By using a likelihood ratio test, we test the significance of the correlations between the random effects of two dependent variables of the model, in order to investigate whether or not it is useful to model these dependent variables jointly. Simulation studies are done to assess both the parameter recovery performance of the EM estimators and the power of the test. Using two empirical data sets which are of longitudinal multivariate type and multivariate multilevel type, respectively, the usefulness of the test is illustrated.

Environment and subjective well-being of rural Chinese elderly: a multilevel analysis.

PubMed

Yeatts, Dale E; Cready, Cynthia M; Pei, Xiaomei; Shen, Yuying; Luo, Hao

2014-11-01

The purpose of this study was to examine the effects of environment on the subjective well-being (SWB) of older Chinese villagers after controlling for personal and social characteristics. Data collected from the Chinese Health and Retirement Longitudinal Survey Pilot Study were used to examine the relationship between (a) SWB (i.e., happiness and depressive symptoms) of Chinese rural elderly and (b) environmental characteristics, controlling for personal and social characteristics. A total of 850 older villagers from 2 Chinese provinces were analyzed using multilevel regression models. Five of the 8 environmental variables had significant effects on SWB: A natural disaster in the past 5 years, rainy days, and use of coal in the home were associated with lower SWB, whereas village wealth and sewer system were associated with higher SWB. Personal and social characteristics of importance included health, age, place of birth, perception that future help is available if needed, and providing help to others. The proposition that the environment of older Chinese villagers is associated with their SWB was supported after accounting for personal and social characteristics. SWB may be improved by improving environments as well as by changes to personal and social conditions. © The Author 2014. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

A multilevel analysis on the relationship between neighbourhood poverty and public hospital utilization: is the high Indigenous morbidity avoidable?

PubMed Central

2011-01-01

Background The estimated life expectancy at birth for Indigenous Australians is 10-11 years less than the general Australian population. The mean family income for Indigenous people is also significantly lower than for non-Indigenous people. In this paper we examine poverty or socioeconomic disadvantage as an explanation for the Indigenous health gap in hospital morbidity in Australia. Methods We utilised a cross-sectional and ecological design using the Northern Territory public hospitalisation data from 1 July 2004 to 30 June 2008 and socio-economic indexes for areas (SEIFA) from the 2006 census. Multilevel logistic regression models were used to estimate odds ratios and confidence intervals. Both total and potentially avoidable hospitalisations were investigated. Results This study indicated that lifting SEIFA scores for family income and education/occupation by two quintile categories for low socio-economic Indigenous groups was sufficient to overcome the excess hospital utilisation among the Indigenous population compared with the non-Indigenous population. The results support a reframing of the Indigenous health gap as being a consequence of poverty and not simplistically of ethnicity. Conclusions Socio-economic disadvantage is a likely explanation for a substantial proportion of the hospital morbidity gap between Indigenous and non-Indigenous populations. Efforts to improve Indigenous health outcomes should recognise poverty as an underlying determinant of the health gap. PMID:21951514

Social capital and administrative contextual determinants of lack of access to a regular doctor: a multilevel analysis in southern Sweden.

PubMed

Lindström, Martin; Axén, Elin; Lindström, Christine; Beckman, Anders; Moghaddassi, Mahnaz; Merlo, Juan

2006-12-01

The aim of this study was to investigate the influence of contextual (social capital and administrative/neo-materialist) and individual factors on lack of access to a regular doctor. The 2000 public health survey in Scania is a cross-sectional study. A total of 13,715 persons answered a postal questionnaire, which is 59% of the random sample. A multilevel logistic regression model, with individuals at the first level and municipalities at the second, was performed. The effect (intra-class correlations, cross-level modification and odds ratios) of individual and municipality (social capital and health care district) factors on lack of access to a regular doctor was analysed using simulation method. The Deviance Information Criterion (DIC) was used as information criterion for the models. The second level municipality variance in lack of access to a regular doctor is substantial even in the final models with all individual and contextual variables included. The model that results in the largest reduction in DIC is the model including age, sex and individual social participation (which is a network aspect of social capital), but the models which include administrative and social capital second level factors also reduced the DIC values. This study suggests that both administrative health care district and social capital may partly explain the individual's self reported lack of access to a regular doctor.

STATE-LEVEL DIETARY DIVERSITY AS A CONTEXTUAL DETERMINANT OF NUTRITIONAL STATUS OF CHILDREN IN INDIA: A MULTILEVEL APPROACH.

PubMed

Borkotoky, Kakoli; Unisa, Sayeed; Gupta, Ashish Kumar

2018-01-01

This study aimed to identify the determinants of nutritional status of children in India with a special focus on dietary diversity at the state level. Household-level consumption data from three rounds of the Consumer Expenditure Survey of the National Sample Survey Organization (1993-2012) were used. Information on the nutritional status of children was taken from the National Family Health Survey (2005-06). Dietary diversity indices were constructed at the state level to examine diversity in quantity of food consumed and food expenditure. Multilevel regression analysis was applied to examine the association of state-level dietary diversity and other socioeconomic factors with the nutritional status of children. It was observed that significant variation in childhood stunting, wasting and underweight could be explained by community- and state-level factors. The results indicate that dietary diversity has increased in India over time, and that dietary diversity at the state level is significantly associated with the nutritional status of children. Moreover, percentage of households with a regular salaried income in a state, percentage of educated mothers and mothers receiving antenatal care in a community are important factors for improving the nutritional status of children. Diversity in complementary child feeding is another significant determinant of nutritional status of children. The study thus concludes that increasing dietary diversity at the state level is an effective measure to reduce childhood malnutrition in India.

Geographic remoteness, area-level socioeconomic disadvantage and inequalities in colorectal cancer survival in Queensland: a multilevel analysis

PubMed Central

2013-01-01

Background To explore the impact of geographical remoteness and area-level socioeconomic disadvantage on colorectal cancer (CRC) survival. Methods Multilevel logistic regression and Markov chain Monte Carlo simulations were used to analyze geographical variations in five-year all-cause and CRC-specific survival across 478 regions in Queensland Australia for 22,727 CRC cases aged 20–84 years diagnosed from 1997–2007. Results Area-level disadvantage and geographic remoteness were independently associated with CRC survival. After full multivariate adjustment (both levels), patients from remote (odds Ratio [OR]: 1.24, 95%CrI: 1.07-1.42) and more disadvantaged quintiles (OR = 1.12, 1.15, 1.20, 1.23 for Quintiles 4, 3, 2 and 1 respectively) had lower CRC-specific survival than major cities and least disadvantaged areas. Similar associations were found for all-cause survival. Area disadvantage accounted for a substantial amount of the all-cause variation between areas. Conclusions We have demonstrated that the area-level inequalities in survival of colorectal cancer patients cannot be explained by the measured individual-level characteristics of the patients or their cancer and remain after adjusting for cancer stage. Further research is urgently needed to clarify the factors that underlie the survival differences, including the importance of geographical differences in clinical management of CRC. PMID:24152961

Is educational differentiation associated with smoking and smoking inequalities in adolescence? A multilevel analysis across 27 European and North American countries.

PubMed

Rathmann, Katharina; Moor, Irene; Kunst, Anton E; Dragano, Nico; Pförtner, Timo-Kolja; Elgar, Frank J; Hurrelmann, Klaus; Kannas, Lasse; Baška, Tibor; Richter, Matthias

2016-09-01

This study aims to determine whether educational differentiation (i.e. early and long tracking to different school types) relate to socioeconomic inequalities in adolescent smoking. Data were collected from the WHO-Collaborative 'Health Behaviour in School-aged Children (HBSC)' study 2005/2006, which included 48,025 15-year-old students (Nboys = 23,008, Ngirls = 25,017) from 27 European and North American countries. Socioeconomic position was measured using the HBSC family affluence scale. Educational differentiation was determined by the number of different school types, age of selection, and length of differentiated curriculum at the country-level. We used multilevel logistic regression to assess the association of daily smoking and early smoking initiation predicted by family affluence, educational differentiation, and their interactions. Socioeconomic inequalities in both smoking outcomes were larger in countries that are characterised by a lower degree of educational differentiation (e.g. Canada, Scandinavia and the United Kingdom) than in countries with higher levels of educational differentiation (e.g. Austria, Belgium, Hungary and The Netherlands). This study found that high educational differentiation does not relate to greater relative inequalities in smoking. Features of educational systems are important to consider as they are related to overall prevalence in smoking and smoking inequalities in adolescence. © 2016 Foundation for the Sociology of Health & Illness.

Violence Among Men and Women in Substance Use Disorder Treatment: A Multi-level Event-based Analysis

PubMed Central

Chermack, Stephen T.; Grogan-Kaylor, Andy; Perron, Brian E.; Murray, Regan L.; De Chavez, Peter; Walton, Maureen A.

2010-01-01

Background This study examined associations between acute alcohol and drug use and violence towards others in conflict incidents (overall, partner, and non-partner conflict incidents) by men and women recruited from substance use disorder (SUD) treatment. Methods Semi-structured interviews were used to obtain details about interpersonal conflict incidents (substance use, whether specific conflicts were with intimate partners or non-partners) in the 180 days pre-treatment. Participants for this study were selected for screening positive for past-year violence (N = 160; 77% men, 23% women). Results Multilevel multinomial regression models showed that after adjusting for clustering within individual participants, the most consistent predictors of violence across models were acute cocaine use (significant for overall, intimate partner and non-partner models), acute heavy alcohol use (significant for overall and non-partner models), and male gender (significant in all models). Conclusions This study was the first to explicitly examine the role of acute alcohol and drug use across overall, partner and non-partner conflict incidents. Consistent with prior studies using a variety of methodologies, alcohol, cocaine use and male gender were most consistently and positively related to violence severity (e.g., resulting in injury). The results provide important and novel event-level information regarding the relationship between acute alcohol and specific drug use and the severity of violence in interpersonal conflict incidents. PMID:20667666

Health related social exclusion in Europe: a multilevel study of the role of welfare generosity

PubMed Central

2013-01-01

Introduction The aim of this paper was to investigate the association between health, social position, social participation and the welfare state. Extending recent research on the social consequences of poor health, we asked whether and how welfare generosity is related to the risk of social exclusion associated with combinations of poor health, low education and economic inactivity. Methods Our analyses are based on data from the European Social Survey, round 3 (2006/7), comprising between 21,205 and 21,397 individuals, aged 25–59 years, within 21 European welfare states. The analyses were conducted by means of multilevel logistic regression analysis in STATA 12. Results The results demonstrated that the risk of non-participation in social networks decreased as welfare generosity increased. The risk of social exclusion, i.e. non-participation in social networks among disadvantaged groups, seldom differed from the overall association, and in absolute terms it was invariably smaller in more generous welfare state contexts. Conclusions The results showed that there were no indications of higher levels of non-participation among disadvantaged groups in more generous welfare states. On the contrary, resources made available by the welfare state seemed to matter to all individuals in terms of overall lower levels of non-participation. As such, these results demonstrate the importance of linking health related social exclusion to the social policy context. PMID:24073744

Health related social exclusion in Europe: a multilevel study of the role of welfare generosity.

PubMed

Saltkjel, Therese; Dahl, Espen; van der Wel, Kjetil A

2013-09-28

The aim of this paper was to investigate the association between health, social position, social participation and the welfare state. Extending recent research on the social consequences of poor health, we asked whether and how welfare generosity is related to the risk of social exclusion associated with combinations of poor health, low education and economic inactivity. Our analyses are based on data from the European Social Survey, round 3 (2006/7), comprising between 21,205 and 21,397 individuals, aged 25-59 years, within 21 European welfare states. The analyses were conducted by means of multilevel logistic regression analysis in STATA 12. The results demonstrated that the risk of non-participation in social networks decreased as welfare generosity increased. The risk of social exclusion, i.e. non-participation in social networks among disadvantaged groups, seldom differed from the overall association, and in absolute terms it was invariably smaller in more generous welfare state contexts. The results showed that there were no indications of higher levels of non-participation among disadvantaged groups in more generous welfare states. On the contrary, resources made available by the welfare state seemed to matter to all individuals in terms of overall lower levels of non-participation. As such, these results demonstrate the importance of linking health related social exclusion to the social policy context.

Relationship between a Centers for Disease Control and Prevention expanded HIV testing initiative and past-year testing by race/ethnicity: a multilevel analysis of the Behavioral Risk Factor Surveillance System.

PubMed

Gaines, Tommi L; Caldwell, Julia T; Ford, Chandra L; Mulatu, Mesfin S; Godette, Dionne C

2016-01-01

The Centers for Disease Control and Prevention's (CDC) expanded testing initiative (ETI) aims to bolster HIV testing among populations disproportionately affected by the HIV epidemic by providing additional funding to health departments serving these communities. ETI prioritizes testing in clinical settings; therefore, we examined the relationship between state-level ETI participation and past-year HIV testing among a racially/ethnically diverse sample of adult respondents to the 2012 Behavioral Risk Factor Surveillance System who accessed health services within the 12 months prior to being interviewed. Controlling for individual- and state-level characteristics in a multilevel logistic regression model, ETI participation was independently and positively associated with past-year testing, but this association varied by race/ethnicity. Hispanics had higher odds (adjusted odds ratio [AOR]: 1.49; 95% CI: 1.11-2.02) and American Indian/Alaska Natives had lower odds (AOR: 0.66; 95% CI: 0.43-0.99) of testing if they resided in states with (vs. without) ETI participation. State-level ETI participation did not significantly alter past-year testing among other racial/ethnic groups. Prioritizing public health resources in states most affected by HIV can improve testing patterns, but other mechanisms likely influence which racial/ethnic groups undergo testing.

Spousal Violence in 5 Transitional Countries: A Population-Based Multilevel Analysis of Individual and Contextual Factors.

PubMed

Ismayilova, Leyla

2015-11-01

I examined the individual- and community-level factors associated with spousal violence in post-Soviet countries. I used population-based data from the Demographic and Health Survey conducted between 2005 and 2012. My sample included currently married women of reproductive age (n = 3932 in Azerbaijan, n = 4053 in Moldova, n = 1932 in Ukraine, n = 4361 in Kyrgyzstan, and n = 4093 in Tajikistan). I selected respondents using stratified multistage cluster sampling. Because of the nested structure of the data, multilevel logistic regressions for survey data were fitted to examine factors associated with spousal violence in the last 12 months. Partner's problem drinking was the strongest risk factor associated with spousal violence in all 5 countries. In Moldova, Ukraine, and Kyrgyzstan, women with greater financial power than their spouses were more likely to experience violence. Effects of community economic deprivation and of empowerment status of women in the community on spousal violence differed across countries. Women living in communities with a high tolerance of violence faced a higher risk of spousal violence in Moldova and Ukraine. In more traditional countries (Azerbaijan, Kyrgyzstan, and Tajikistan), spousal violence was lower in conservative communities with patriarchal gender beliefs or higher financial dependency on husbands. My findings underscore the importance of examining individual risk factors in the context of community-level factors and developing individual- and community-level interventions.

A multilevel study of area socio-economic status and food purchasing behaviour.

PubMed

Turrell, Gavin; Bentley, Rebecca; Thomas, Lyndal R; Jolley, Damien; Subramanian, Sv; Kavanagh, Anne M

2009-11-01

The present study examined the association between area socio-economic status (SES) and food purchasing behaviour. Data were collected by mail survey (64.2 % response rate). Area SES was indicated by the proportion of households in each area earning less than $AUS 400 per week, and individual-level socio-economic position was measured using education, occupation and household income. Food purchasing was measured on the basis of compliance with dietary guideline recommendations (for grocery foods) and variety of fruit and vegetable purchase. Multilevel regression analysis examined the association between area SES and food purchase after adjustment for individual-level demographic (age, sex, household composition) and socio-economic factors. Melbourne city, Australia, 2003. Residents of 2564 households located in fifty small areas. Residents of low-SES areas were significantly less likely than their counterparts in advantaged areas to purchase grocery foods that were high in fibre and low in fat, salt and sugar; and they purchased a smaller variety of fruits. There was no evidence of an association between area SES and vegetable variety. In Melbourne, area SES was associated with some food purchasing behaviours independent of individual-level factors, suggesting that areas in this city may be differentiated on the basis of food availability, accessibility and affordability, making the purchase of some types of foods more difficult in disadvantaged areas.

Geographic variation in work injuries: a multilevel analysis of individual-level data and area-level factors within Canada.

PubMed

Morassaei, Sara; Breslin, F Curtis; Ibrahim, Selahadin A; Smith, Peter M; Mustard, Cameron A; Amick, Benjamin C; Shankardass, Ketan; Petch, Jeremy

2013-05-01

This study sought to examine provincial variation in work injuries and to assess whether contextual factors are associated with geographic variation in work injuries. Individual-level data from the 2003 and 2005 Canadian Community Health Survey was obtained for a representative sample of 89,541 Canadians aged 15 to 75 years old who reported working in the past 12 months. A multilevel regression model was conducted to identify geographic variation and contextual factors associated with the likelihood of reporting an activity limiting work injury [corrected], while adjusting for demographic and work variables. Provincial differences in work injuries were observed, even after controlling for other risk factors. Workers in western provinces such as Saskatchewan (adjusted odds ratio [AOR], 1.30; 95% confidence interval [CI], 1.09-1.55), Alberta (AOR, 1.31; 95% CI, 1.13-1.51), and British Columbia (AOR, 1.46; 95% CI, 1.26-1.71) had a higher risk of work injuries compared with Ontario workers. Indicators of area-level material and social deprivation were not associated with work injury risk. Provincial differences in work injuries suggest that broader factors acting as determinants of work injuries are operating across workplaces at a provincial level. Future research needs to identify the provincial determinants and whether similar large area-level factors are driving work injuries in other countries. Copyright © 2013 Elsevier Inc. All rights reserved.

Health worker performance in rural health organizations in low- and middle-income countries: do organizational factors predict non-task performance?

PubMed

Jayasuriya, Rohan; Jayasinghe, Upali W; Wang, Qian

2014-07-01

Health worker (HW) performance is a critical issue facing many low- and middle-income countries (LMICs). The aim of this study was to test the effects of factors in the work environment, such as organizational culture and climate, on HW non-task performance in rural health work settings in a LMIC. The data for the study is from a sample of 963 HWs from rural health centres (HCs) in 16 of the 20 provinces in Papua New Guinea. The reliability and validity of measures for organizational citizenship behaviour (OCB), counterproductive work behaviour (CWB) and work climate (WC) were tested. Multilevel linear regression models were used to test the relationship of individual and HC level factors with non-task performance. The survey found that 62 per cent of HCs practised OCB "often to always" and 5 percent practised CWB "often to always". Multilevel analysis revealed that WC had a positive effect on organizational citizenship behaviour (OCB) and a negative effect on CWB. The mediation analyses provided evidence that the relationship between WC and OCB was mediated through CWB. Human resource policies that improve WC in rural health settings would increase positive non-task behaviour and improve the motivation and performance of HWs in rural settings in LMICs. Copyright © 2014 Elsevier Ltd. All rights reserved.

EFFECT OF INDIVIDUAL AND COMMUNITY FACTORS ON MATERNAL HEALTH CARE SERVICE USE IN INDIA: A MULTILEVEL APPROACH.

PubMed

Yadav, Awdhesh; Kesarwani, Ranjana

2016-01-01

This study aimed to assess empirically the influence of individual and community (neighbourhood) factors on the use of maternal health care services in India through three outcomes: utilization of full antenatal care (ANC) services, safe delivery and utilization of postnatal care services. Data were from the third round of the National Family Health Survey (2005-06). The study sample constituted ever-married women aged 15-49 from 29 Indian states. Multilevel logistic regression analysis was performed for the three outcomes of interest accounting for individual- and community-level factors associated with the use of maternal health care services. A substantial amount of variation was observed at the community level. About 45%, 51% and 62% of the total variance in the use of full ANC, safe delivery and postnatal care, respectively, could be attributed to differences across the community. There was significant variation in the use of maternal health care services at the individual level, with socioeconomic status and mother's education being the most prominent factors associated with the use of maternal health care services. At the community level, urban residence and poverty concentration were found to be significantly associated with maternal health care service use. The results suggest that an increased focus on community-level interventions could lead to an increase in the utilization of maternal health care services in India.

The effects of sports participation on the development of left ventricular mass in adolescent boys.

PubMed

Valente-Dos-Santos, João; Coelho-E-Silva, Manuel J; Castanheira, Joaquim; Machado-Rodrigues, Aristides M; Cyrino, Edilson S; Sherar, Lauren B; Esliger, Dale W; Elferink-Gemser, Marije T; Malina, Robert M

2015-01-01

To examine the contribution of body size, biological maturation, and nonelite sports participation to longitudinal changes of left ventricular mass (LVM) in healthy boys. One hundred and ten boys (11.0-14.5 years at baseline) were assessed biannually for 2 years. Stature, body mass, and four skinfolds were measured. Lean body mass (LBM) was estimated. Biological maturation was assessed as years from age at peak height velocity (APHV). Sports participation was assessed by questionnaire. LVM was obtained from M-mode echocardiograms using two-dimensional images. To account for the repeated measures within individual nature of longitudinal data, multilevel random effects regression analyses were used in the analysis. LVM increased on average 42 ± 18 g from 11 to 15 years (P < 0.05) and 76 ± 14 g from 3.5 years pre-APHV to 1.5 years post-APHV (P < 0.05). The multilevel model with the best statistical fit (Model B) showed that changes of 1 cm in stature, 1 year post-APHV, and 1 kg of LBM predicts 4.7, 0.5, and 1 g of LVM (P < 0.05), respectively. Among healthy, male adolescents aged 11-15 years individual differences in growth and biological maturation influence growth of LVM. Subcutaneous adiposity and sports participation were not associated with greater LVM. © 2015 Wiley Periodicals, Inc.

Performance Analysis of Multilevel Parallel Applications on Shared Memory Architectures

NASA Technical Reports Server (NTRS)

Jost, Gabriele; Jin, Haoqiang; Labarta, Jesus; Gimenez, Judit; Caubet, Jordi; Biegel, Bryan A. (Technical Monitor)

2002-01-01

In this paper we describe how to apply powerful performance analysis techniques to understand the behavior of multilevel parallel applications. We use the Paraver/OMPItrace performance analysis system for our study. This system consists of two major components: The OMPItrace dynamic instrumentation mechanism, which allows the tracing of processes and threads and the Paraver graphical user interface for inspection and analyses of the generated traces. We describe how to use the system to conduct a detailed comparative study of a benchmark code implemented in five different programming paradigms applicable for shared memory

Prevalence and correlates of hypertension in Maharashtra, India: A multilevel analysis

PubMed Central

Bhise, Mahadev D.

2018-01-01

Background and aim In the last few decades, the prevalence of hypertension has been drastically increased in India. The present study estimates the current prevalence of hypertension and its correlates in the state of Maharashtra. The variation in the prevalence of hypertension associated with individual-level characteristics is explained at the community and district level. Methods Data is used from the recent round of District Level Household & Facility Survey (DLHS-4), 2012–13. The DLHS-4 has used the nationally representative sample, collected through multistage stratified sampling procedure. A similar sampling frame, used in NSSO-2007-08, has been followed. The chi-square test is used to show the significance level of the association between the estimated prevalence of hypertension and its correlates. Multilevel regression analysis is carried out to investigate the effects of individual and community level factors on the prevalence of hypertension. Results The overall prevalence of hypertension is 25% in Maharashtra, and a huge variation in the prevalence of hypertension is found across the districts. Dhule, Gadchiroli (with a low HDI rank), Mumbai and Satara (with higher HDI rank) are the districts with the higher (above 30%) prevalence of high blood pressure. The prevalence also significantly varies according to different correlates. The prevalence of high blood pressure is higher among elderly population (40%), among males (28%), in the urban areas (27%) and in the richest wealth quintile (28%). The prevalence is also higher among cigarette smokers (31%), alcohol consumers (30%) and people with obesity (38%) as compared to their counterparts. The results of the multilevel analysis show that the older and obese persons are at four-time higher risk of hypertension. Again, age, sex, marital status, place of residence, wealth status, unhealthy habits (i.e. smoking and alcohol consumption) and BMI are significantly associated with hypertension. The results of VPC statistics show that 14% of hypertension prevalence could be attributed to differences at the community level. Conclusion The prevalence of hypertension largely varies in the districts of Maharashtra irrespective of their level of socio-economic development (i.e. HDI rank). The variation in the rate of prevalence of hypertension is higher in the community (PSU) level as compared to the variation in the prevalence rate at the district level. Hypertension is attributable to the modifiable factors like risky lifestyle practices. PMID:29401464

Prevalence and correlates of hypertension in Maharashtra, India: A multilevel analysis.

PubMed

Bhise, Mahadev D; Patra, Shraboni

2018-01-01

In the last few decades, the prevalence of hypertension has been drastically increased in India. The present study estimates the current prevalence of hypertension and its correlates in the state of Maharashtra. The variation in the prevalence of hypertension associated with individual-level characteristics is explained at the community and district level. Data is used from the recent round of District Level Household & Facility Survey (DLHS-4), 2012-13. The DLHS-4 has used the nationally representative sample, collected through multistage stratified sampling procedure. A similar sampling frame, used in NSSO-2007-08, has been followed. The chi-square test is used to show the significance level of the association between the estimated prevalence of hypertension and its correlates. Multilevel regression analysis is carried out to investigate the effects of individual and community level factors on the prevalence of hypertension. The overall prevalence of hypertension is 25% in Maharashtra, and a huge variation in the prevalence of hypertension is found across the districts. Dhule, Gadchiroli (with a low HDI rank), Mumbai and Satara (with higher HDI rank) are the districts with the higher (above 30%) prevalence of high blood pressure. The prevalence also significantly varies according to different correlates. The prevalence of high blood pressure is higher among elderly population (40%), among males (28%), in the urban areas (27%) and in the richest wealth quintile (28%). The prevalence is also higher among cigarette smokers (31%), alcohol consumers (30%) and people with obesity (38%) as compared to their counterparts. The results of the multilevel analysis show that the older and obese persons are at four-time higher risk of hypertension. Again, age, sex, marital status, place of residence, wealth status, unhealthy habits (i.e. smoking and alcohol consumption) and BMI are significantly associated with hypertension. The results of VPC statistics show that 14% of hypertension prevalence could be attributed to differences at the community level. The prevalence of hypertension largely varies in the districts of Maharashtra irrespective of their level of socio-economic development (i.e. HDI rank). The variation in the rate of prevalence of hypertension is higher in the community (PSU) level as compared to the variation in the prevalence rate at the district level. Hypertension is attributable to the modifiable factors like risky lifestyle practices.

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

A multilevel control system for the large space telescope. [numerical analysis/optimal control

NASA Technical Reports Server (NTRS)

Siljak, D. D.; Sundareshan, S. K.; Vukcevic, M. B.

1975-01-01

A multilevel scheme was proposed for control of Large Space Telescope (LST) modeled by a three-axis-six-order nonlinear equation. Local controllers were used on the subsystem level to stabilize motions corresponding to the three axes. Global controllers were applied to reduce (and sometimes nullify) the interactions among the subsystems. A multilevel optimization method was developed whereby local quadratic optimizations were performed on the subsystem level, and global control was again used to reduce (nullify) the effect of interactions. The multilevel stabilization and optimization methods are presented as general tools for design and then used in the design of the LST Control System. The methods are entirely computerized, so that they can accommodate higher order LST models with both conceptual and numerical advantages over standard straightforward design techniques.

TEMPEST in a gallimaufry: applying multilevel systems theory to person-in-context research.

PubMed

Peck, Stephen C

2007-12-01

Terminological ambiguity and inattention to personal and contextual multilevel systems undermine personality, self, and identity theories. Hierarchical and heterarchical systems theories are used to describe contents and processes existing within and across three interrelated multilevel systems: levels of organization, representation, and integration. Materially nested levels of organization are used to distinguish persons from contexts and personal from social identity. Functionally nested levels of representation are used to distinguish personal identity from the sense of identity and symbolic (belief) from iconic (schema) systems. Levels of integration are hypothesized to unfold separately but interdependently across levels of representation. Multilevel system configurations clarify alternative conceptualizations of traits and contextualized identity. Methodological implications for measurement and analysis (e.g., integrating variable- and pattern-centered methods) are briefly described.

Engineering applications of heuristic multilevel optimization methods

NASA Technical Reports Server (NTRS)

Barthelemy, Jean-Francois M.

1988-01-01

Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.

Engineering applications of heuristic multilevel optimization methods

NASA Technical Reports Server (NTRS)

Barthelemy, Jean-Francois M.

1989-01-01

Some engineering applications of heuristic multilevel optimization methods are presented and the discussion focuses on the dependency matrix that indicates the relationship between problem functions and variables. Coordination of the subproblem optimizations is shown to be typically achieved through the use of exact or approximate sensitivity analysis. Areas for further development are identified.

School Climate for Academic Success: A Multilevel Analysis of School Climate and Student Outcomes

ERIC Educational Resources Information Center

Kwong, Darren; Davis, Jonathan Ryan

2015-01-01

This multilevel study examined the relationship between school climate and academic achievement. Using the Educational Longitudinal Survey (ELS, 2002), and a sample of 16,258 students and 1954 schools nationwide, we found that student-level perception of school climate--especially the student learning environment--was highly predictive of academic…

Using Multilevel Factor Analysis with Clustered Data: Investigating the Factor Structure of the Positive Values Scale

ERIC Educational Resources Information Center

Huang, Francis L.; Cornell, Dewey G.

2016-01-01

Advances in multilevel modeling techniques now make it possible to investigate the psychometric properties of instruments using clustered data. Factor models that overlook the clustering effect can lead to underestimated standard errors, incorrect parameter estimates, and model fit indices. In addition, factor structures may differ depending on…

Introduction to Multilevel Item Response Theory Analysis: Descriptive and Explanatory Models

ERIC Educational Resources Information Center

Sulis, Isabella; Toland, Michael D.

2017-01-01

Item response theory (IRT) models are the main psychometric approach for the development, evaluation, and refinement of multi-item instruments and scaling of latent traits, whereas multilevel models are the primary statistical method when considering the dependence between person responses when primary units (e.g., students) are nested within…

"Using Power Tables to Compute Statistical Power in Multilevel Experimental Designs"

ERIC Educational Resources Information Center

Konstantopoulos, Spyros

2009-01-01

Power computations for one-level experimental designs that assume simple random samples are greatly facilitated by power tables such as those presented in Cohen's book about statistical power analysis. However, in education and the social sciences experimental designs have naturally nested structures and multilevel models are needed to compute the…

A Multilevel Analysis of Phase II of the Louisiana School Effectiveness Study.

ERIC Educational Resources Information Center

Kennedy, Eugene; And Others

This paper presents findings of a study that used conventional modeling strategies (student- and school-level) and a new multilevel modeling strategy, Hierarchical Linear Modeling, to investigate school effects on student-achievement outcomes for data collected as part of Phase 2 of the Louisiana School Effectiveness Study. The purpose was to…

Pre- and Postnatal Women's Leisure Time Physical Activity Patterns: A Multilevel Longitudinal Analysis

ERIC Educational Resources Information Center

Cramp, Anita G.; Bray, Steven R.

2009-01-01

The purpose of this study was to examine women's leisure time physical activity (LTPA) before pregnancy, during pregnancy, and through the first 7 months postnatal. Pre- and postnatal women (n = 309) completed the 12-month Modifiable Activity Questionnaire and demographic information. Multilevel modeling was used to estimate a growth curve…

Does the Organization Matter? A Multilevel Analysis of Organizational Effects in Homeless Service Innovations

ERIC Educational Resources Information Center

Cronley, Courtney; Patterson, David A.

2012-01-01

This study examined the effects of organizational culture on staff members' use of management information systems ("N" = 142) within homeless service organizations ("N" = 24), using a multilevel model. The Organizational Social Context Questionnaire was used to measure organizational culture, defined by three sub-constructs: (1) proficiency, (2)…

Newly occurred L4 spondylolysis in the lumbar spine with pre-existence L5 spondylolysis among sports players: case reports and biomechanical analysis.

PubMed

Sairyo, Koichi; Sakai, Toshinori; Yasui, Natsuo; Kiapour, Ali; Biyani, Ashok; Ebraheim, Nabil; Goel, Vijay K

2009-10-01

Case series and a biomechanical study using a finite element (FE) analysis. To report three cases with multi-level spondylolysis and to understand the mechanism biomechanically. Multi-level spondylolysis is a very rare condition. There have been few reports in the literature on multi-level spondylolysis among sports players. We reviewed three cases of the condition, clinically. These patients were very active young sports players and had newly developed fresh L4 spondylolysis and pre-existing L5 terminal stage spondylolysis. Thus, we assumed that L5 spondylolysis may have increased the pars stress at the cranial adjacent levels, leading to newly developed spondylolysis at these levels. Biomechanically, we investigated pars stress at L4 with or without spondylolysis at L5 using the finite element technique. L4 pars stress decreased in the presence of L5 spondylolysis, which does not support our first hypothesis. It seems that multi-level spondylolysis may occur due to genetic and not biomechanical reasons.

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.

Individual and areal risk factors for road traffic injury deaths: nationwide study in South Korea.

PubMed

Park, Kunhee; Hwang, Seung-Sik; Lee, Jin-Seok; Kim, Yoon; Kwon, Soonman

2010-07-01

This study determines the individual and areal risk factors for road traffic injury deaths in South Korea. The risk factors that influence road traffic injury deaths are defined by multilevel Poisson regression analysis. It is seen that not only demographic factors but also individual educational level, which represents socioeconomic status, influences road traffic injury deaths. The material deprivation index, which represents areal socioeconomic status, and W statistics, as a measure of the quality of the emergency medical system in an area, also influence road traffic injury deaths. Based on this study, the most vulnerable group for road traffic injury deaths is elderly men with a low level of education who live in the most deprived areas.Therefore, preventive policies focusing on both these areas and this population demographic should be established.

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.

Multilevel model of safety climate for furniture industries.

PubMed

Rodrigues, Matilde A; Arezes, Pedro M; Leão, Celina P

2015-01-01

Furniture companies can analyze their safety status using quantitative measures. However, the data needed are not always available and the number of accidents is under-reported. Safety climate scales may be an alternative. However, there are no validated Portuguese scales that account for the specific attributes of the furniture sector. The current study aims to develop and validate an instrument that uses a multilevel structure to measure the safety climate of the Portuguese furniture industry. The Safety Climate in Wood Industries (SCWI) model was developed and applied to the safety climate analysis using three different scales: organizational, group and individual. A multilevel exploratory factor analysis was performed to analyze the factorial structure. The studied companies' safety conditions were also analyzed. Different factorial structures were found between and within levels. In general, the results show the presence of a group-level safety climate. The scores of safety climates are directly and positively related to companies' safety conditions; the organizational scale is the one that best reflects the actual safety conditions. The SCWI instrument allows for the identification of different safety climates in groups that comprise the same furniture company and it seems to reflect those groups' safety conditions. The study also demonstrates the need for a multilevel analysis of the studied instrument.

Community-level income inequality and HIV prevalence among persons who inject drugs in Thai Nguyen, Vietnam.

PubMed

Lim, Travis W; Frangakis, Constantine; Latkin, Carl; Ha, Tran Viet; Minh, Nguyen Le; Zelaya, Carla; Quan, Vu Minh; Go, Vivian F

2014-01-01

Socioeconomic status has a robust positive relationship with several health outcomes at the individual and population levels, but in the case of HIV prevalence, income inequality may be a better predictor than absolute level of income. Most studies showing a relationship between income inequality and HIV have used entire countries as the unit of analysis. In this study, we examine the association between income inequality at the community level and HIV prevalence in a sample of persons who inject drugs (PWID) in a concentrated epidemic setting. We recruited PWID and non-PWID community participants in Thai Nguyen, Vietnam, and administered a cross-sectional questionnaire; PWID were tested for HIV. We used ecologic regression to model HIV burden in our PWID study population on GINI indices of inequality calculated from total reported incomes of non-PWID community members in each commune. We also modeled HIV burden on interaction terms between GINI index and median commune income, and finally used a multi-level model to control for community level inequality and individual level income. HIV burden among PWID was significantly correlated with the commune GINI coefficient (r = 0.53, p = 0.002). HIV burden was also associated with GINI coefficient (β = 0.082, p = 0.008) and with median commune income (β = -0.018, p = 0.023) in ecological regression. In the multi-level model, higher GINI coefficient at the community level was associated with higher odds of individual HIV infection in PWID (OR = 1.46 per 0.01, p = 0.003) while higher personal income was associated with reduced odds of infection (OR = 0.98 per $10, p = 0.022). This study demonstrates a context where income inequality is associated with HIV prevalence at the community level in a concentrated epidemic. It further suggests that community level socioeconomic factors, both contextual and compositional, could be indirect determinants of HIV infection in PWID.

Community-Level Income Inequality and HIV Prevalence among Persons Who Inject Drugs in Thai Nguyen, Vietnam

PubMed Central

Lim, Travis W.; Frangakis, Constantine; Latkin, Carl; Ha, Tran Viet; Minh, Nguyen Le; Zelaya, Carla; Quan, Vu Minh; Go, Vivian F.

2014-01-01

Socioeconomic status has a robust positive relationship with several health outcomes at the individual and population levels, but in the case of HIV prevalence, income inequality may be a better predictor than absolute level of income. Most studies showing a relationship between income inequality and HIV have used entire countries as the unit of analysis. In this study, we examine the association between income inequality at the community level and HIV prevalence in a sample of persons who inject drugs (PWID) in a concentrated epidemic setting. We recruited PWID and non-PWID community participants in Thai Nguyen, Vietnam, and administered a cross-sectional questionnaire; PWID were tested for HIV. We used ecologic regression to model HIV burden in our PWID study population on GINI indices of inequality calculated from total reported incomes of non-PWID community members in each commune. We also modeled HIV burden on interaction terms between GINI index and median commune income, and finally used a multi-level model to control for community level inequality and individual level income. HIV burden among PWID was significantly correlated with the commune GINI coefficient (r = 0.53, p = 0.002). HIV burden was also associated with GINI coefficient (β = 0.082, p = 0.008) and with median commune income (β = −0.018, p = 0.023) in ecological regression. In the multi-level model, higher GINI coefficient at the community level was associated with higher odds of individual HIV infection in PWID (OR = 1.46 per 0.01, p = 0.003) while higher personal income was associated with reduced odds of infection (OR = 0.98 per $10, p = 0.022). This study demonstrates a context where income inequality is associated with HIV prevalence at the community level in a concentrated epidemic. It further suggests that community level socioeconomic factors, both contextual and compositional, could be indirect determinants of HIV infection in PWID. PMID:24618892

Variability in the prescription of biological drugs in rheumatoid arthritis in Spain: a multilevel analysis.

PubMed

López-Longo, Francisco Javier; Seoane-Mato, Daniel; Martín-Martínez, María A; Sánchez-Alonso, Fernando

2018-04-01

To describe variability in the prescription of biologics (B-DMARDs) for patients with rheumatoid arthritis (RA) in hospitals in Spain, and to explore which characteristics of the patient, the doctor and the hospital are associated with this variability. Cross-sectional multicentric study in 46 rheumatology services of the National Health System. Medical records of 1188 randomly selected patients were reviewed. The association of each variable with B-DMARD prescription was analyzed using simple logistic regressions. Multilevel logistic regression models were created to analyze variability among centers. 36.8% of patients had received B-DMARD. The proportion of patients being treated with B-DMARDs varied between 3.6 and 71.4% depending on the center. Association of prescription of B-DMARD with patient age (OR = 0.958, 95% CI = 0.947-0.968, p < 0.001), longer disease duration (OR = 1.05, 95% CI = 1.032-1.069, p < 0.001), higher CRP levels (OR = 1.022, 95% CI = 1.003-1.042, p = 0.023), and higher number of hospitalizations (OR = 1.286, 95% CI = 1.145-1.446, p < 0.001) was observed. With regard to the center characteristics, the existence of telephone consultations (OR = 1.438, 95% CI = 1.037-1.994, p = 0.03) and the number of beds (OR = 1.045, 95% CI = 1.001-1.091, p = 0.044) were positively associated with prescription of B-DMARDs. Patient variables explained 34.04% of the variability among centers. By adjusting for patient and hospital characteristics, it went up to 83.71%. There is variability in the prescription of B-DMARDs for patients with RA among hospitals which is associated, to a greater extent, with the center characteristics. B-DMARDs prescription could be partly explained by other factors not covered by the current study including the provider's attitudes towards biologics and other hospital characteristics.

Adolescent Substance Use Following Participation in a Universal Drug Prevention Program: Examining Relationships With Program Recall and Baseline Use Status.

PubMed

Bavarian, Niloofar; Duncan, Robert; Lewis, Kendra M; Miao, Alicia; Washburn, Isaac J

2015-01-01

The study examined whether adolescents receiving a universal, school based, drug prevention program in Grade 7 varied, by student profile, in substance use behaviors post program implementation. Profiles were a function of recall of program receipt and substance use at baseline. A secondary analysis was conducted on data from the Adolescent Substance Abuse Prevention Study, a large, geographically diverse, longitudinal school-based cluster-randomized controlled trial of the Take Charge of Your Life drug prevention program. Profiles were created using self-reported substance use (preintervention) and program recall (postintervention) at Grade 7. First, characteristics of each of the 4 profiles of treatment students who varied by program recall and baseline substance use were explored. Then, multilevel logistic regression analyses were used to examine differences in the odds of substance use (alcohol, tobacco, and marijuana) among student profiles at the 6 additional study waves (Time 2 [Grade 7] through Time 7 [Grade 11]). Pearson's chi-square tests showed sample characteristics varied by student profile. Multilevel logistic regression results were consistent across all examined substance use behaviors at all time points. Namely, as compared with students who had no baseline substance use and had program recall (No Use, Recall), each of the remaining 3 profiles (No Use, No Recall; Use, Recall; Use, No Recall) were more likely to engage in substance use. Post hoc analyses showed that for the 2 subprofiles of baseline substance users, there were only 2 observed, and inconsistent, differences in the odds of subsequent substance use by recall status. Findings suggest that for students who were not baseline substance users, program recall significantly decreased the likelihood of subsequent substance use. For students who were baseline substance users, program recall did not generally influence subsequent substance use. Implications for school-based drug prevention programs are discussed.

Associations between homocysteine metabolism related SNPs and carotid intima-media thickness: a Chinese sib pair study.

PubMed

Sun, Kexin; Song, Jing; Liu, Kuo; Fang, Kai; Wang, Ling; Wang, Xueyin; Li, Jing; Tang, Xun; Wu, Yiqun; Qin, Xueying; Wu, Tao; Gao, Pei; Chen, Dafang; Hu, Yonghua

2017-04-01

Carotid intima-media thickness (CIMT) is a good surrogate for atherosclerosis. Hyperhomocysteinemia is an independent risk factor for cardiovascular diseases. We aim to investigate the relationships between homocysteine (Hcy) related biochemical indexes and CIMT, the associations between Hcy related SNPs and CIMT, as well as the potential gene-gene interactions. The present study recruited full siblings (186 eligible families with 424 individuals) with no history of cardiovascular events from a rural area of Beijing. We examined CIMT, intima-media thickness for common carotid artery (CCA-IMT) and carotid bifurcation, tested plasma levels for Hcy, vitamin B6 (VB6), vitamin B12 (VB12) and folic acid (FA), and genotyped 9 SNPs on MTHFR, MTR, MTRR, BHMT, SHMT1, CBS genes. Associations between SNPs and biochemical indexes and CIMT indexes were analyzed using family-based association test analysis. We used multi-level mixed-effects regression model to verify SNP-CIMT associations and to explore the potential gene-gene interactions. VB6, VB12 and FA were negatively correlated with CIMT indexes (p < 0.05). rs2851391 T allele was associated with decreased plasma VB12 levels (p = 0.036). In FABT, CBS rs2851391 was significantly associated with CCA-IMT (p = 0.021) and CIMT (p = 0.019). In multi-level mixed-effects regression model, CBS rs2851391 was positively significantly associated with CCA-IMT (Coef = 0.032, se = 0.009, raw p < 0.001) after Bonferoni correction (corrected α = 0.0056). Gene-gene interactions were found between CBS rs2851391 and BHMT rs10037045 for CCA-IMT (p = 0.011), as well as between CBS rs2851391 and MTR rs1805087 for CCA-IMT (p = 0.007) and CIMT (p = 0.022). Significant associations are found between Hcy metabolism related genetic polymorphisms, biochemical indexes and CIMT indexes. There are complex interactions between genetic polymorphisms for CCA-IMT and CIMT.

Using iMCFA to Perform the CFA, Multilevel CFA, and Maximum Model for Analyzing Complex Survey Data.

PubMed

Wu, Jiun-Yu; Lee, Yuan-Hsuan; Lin, John J H

2018-01-01

To construct CFA, MCFA, and maximum MCFA with LISREL v.8 and below, we provide iMCFA (integrated Multilevel Confirmatory Analysis) to examine the potential multilevel factorial structure in the complex survey data. Modeling multilevel structure for complex survey data is complicated because building a multilevel model is not an infallible statistical strategy unless the hypothesized model is close to the real data structure. Methodologists have suggested using different modeling techniques to investigate potential multilevel structure of survey data. Using iMCFA, researchers can visually set the between- and within-level factorial structure to fit MCFA, CFA and/or MAX MCFA models for complex survey data. iMCFA can then yield between- and within-level variance-covariance matrices, calculate intraclass correlations, perform the analyses and generate the outputs for respective models. The summary of the analytical outputs from LISREL is gathered and tabulated for further model comparison and interpretation. iMCFA also provides LISREL syntax of different models for researchers' future use. An empirical and a simulated multilevel dataset with complex and simple structures in the within or between level was used to illustrate the usability and the effectiveness of the iMCFA procedure on analyzing complex survey data. The analytic results of iMCFA using Muthen's limited information estimator were compared with those of Mplus using Full Information Maximum Likelihood regarding the effectiveness of different estimation methods.

Relative efficacy of topical non-steroidal anti-inflammatory drugs and topical capsaicin in osteoarthritis: protocol for an individual patient data meta-analysis.

PubMed

Persson, Monica S M; Fu, Yu; Bhattacharya, Archan; Goh, Siew-Li; van Middelkoop, Marienke; Bierma-Zeinstra, Sita M A; Walsh, David; Doherty, Michael; Zhang, Weiya

2016-09-29

Pain is the most troubling issue to patients with osteoarthritis (OA), yet current pharmacological treatments offer only small-to-moderate pain reduction. Current guidelines therefore emphasise the need to identify predictors of treatment response. In line with these recommendations, an individual patient data (IPD) meta-analysis will be conducted. The study aims to investigate the relative treatment effects of topical non-steroidal anti-inflammatory drugs (NSAIDs) and topical capsaicin in OA and to identify patient-level predictors of treatment response. IPD will be collected from randomised controlled trials (RCTs) of topical NSAIDs and capsaicin in OA. Multilevel regression modelling will be conducted to determine predictors for the specific and the overall treatment effect. Through the identification of treatment responders, this IPD meta-analysis may improve the current understanding of the pain mechanisms in OA and guide clinical decision-making. Identifying and prescribing the treatment most likely to be beneficial for an individual with OA will improve the efficiency of patient management. CRD42016035254.

Sample size estimation for alternating logistic regressions analysis of multilevel randomized community trials of under-age drinking.

PubMed

Reboussin, Beth A; Preisser, John S; Song, Eun-Young; Wolfson, Mark

2012-07-01

Under-age drinking is an enormous public health issue in the USA. Evidence that community level structures may impact on under-age drinking has led to a proliferation of efforts to change the environment surrounding the use of alcohol. Although the focus of these efforts is to reduce drinking by individual youths, environmental interventions are typically implemented at the community level with entire communities randomized to the same intervention condition. A distinct feature of these trials is the tendency of the behaviours of individuals residing in the same community to be more alike than that of others residing in different communities, which is herein called 'clustering'. Statistical analyses and sample size calculations must account for this clustering to avoid type I errors and to ensure an appropriately powered trial. Clustering itself may also be of scientific interest. We consider the alternating logistic regressions procedure within the population-averaged modelling framework to estimate the effect of a law enforcement intervention on the prevalence of under-age drinking behaviours while modelling the clustering at multiple levels, e.g. within communities and within neighbourhoods nested within communities, by using pairwise odds ratios. We then derive sample size formulae for estimating intervention effects when planning a post-test-only or repeated cross-sectional community-randomized trial using the alternating logistic regressions procedure.

Using SEM to Analyze Complex Survey Data: A Comparison between Design-Based Single-Level and Model-Based Multilevel Approaches

ERIC Educational Resources Information Center

Wu, Jiun-Yu; Kwok, Oi-man

2012-01-01

Both ad-hoc robust sandwich standard error estimators (design-based approach) and multilevel analysis (model-based approach) are commonly used for analyzing complex survey data with nonindependent observations. Although these 2 approaches perform equally well on analyzing complex survey data with equal between- and within-level model structures…

DIF Analysis with Multilevel Data: A Simulation Study Using the Latent Variable Approach

ERIC Educational Resources Information Center

Jin, Ying; Eason, Hershel

2016-01-01

The effects of mean ability difference (MAD) and short tests on the performance of various DIF methods have been studied extensively in previous simulation studies. Their effects, however, have not been studied under multilevel data structure. MAD was frequently observed in large-scale cross-country comparison studies where the primary sampling…

School Process and Teacher Job Satisfaction at Alternative Schools: A Multilevel Study Using SASS 2007-08 Data

ERIC Educational Resources Information Center

Xia, Jiangang; Izumi, Masashi; Gao, Xingyuan

2015-01-01

This study examined the associations between public alternative schools' teacher job satisfaction and school processes. Based on a multilevel analysis of the national School and Staffing Survey 2007-08 data, we found that among the seven school processes, public alternative schools' administrative support, staff collegiality, career and working…

A Multilevel Analysis of the Relationship between Shared Leadership and Creativity in Inter-Organizational Teams

ERIC Educational Resources Information Center

Gu, Jibao; Chen, Zhi; Huang, Qian; Liu, Hefu; Huang, Shenglan

2018-01-01

An inter-organizational team, which consists of diverse members from different organizations to conduct an initiative, has been widely treated as a critical method to improve organizational innovation. This study proposes a multilevel model to test the relationship between shared leadership and creativity at both team- and individual level in the…

Role of Linguistic and Sociocultural Diversity in Reading Literacy Achievement: A Multilevel Approach

ERIC Educational Resources Information Center

Netten, Andrea; Luyten, Hans; Droop, Mienke; Verhoeven, Ludo

2016-01-01

This study examined how linguistic and sociocultural diversity have an impact on the reading literacy outcomes of a representative sample of 3,549 first-language (L1) and 208 second-language (L2) fourth-grade students in the Netherlands. A multilevel modelling analysis was conducted using Progress in International Reading Literacy Study 2006 data…

The Dubious Benefits of Multi-Level Modeling

ERIC Educational Resources Information Center

Gorard, Stephen

2007-01-01

This paper presents an argument against the wider adoption of complex forms of data analysis, using multi-level modeling (MLM) as an extended case study. MLM was devised to overcome some deficiencies in existing datasets, such as the bias caused by clustering. The paper suggests that MLM has an unclear theoretical and empirical basis, has not led…

Cross-National Differences in the Association between Parental Work Hours and Time with Children in Europe: A Multilevel Analysis

ERIC Educational Resources Information Center

Roeters, Anne

2013-01-01

This study investigates cross-national differences in the association between parental work hours and parent-child interaction time and explains differences in this individual-level association on the basis of country characteristics. It extends prior research by testing the moderating effects of country characteristics through multilevel analyses…

Marital Status, Marital Process, and Parental Resources in Predicting Adolescents' Emotional Adjustment: A Multilevel Analysis

ERIC Educational Resources Information Center

Vandervalk, Inge; Spruijt, Ed; De Goede, Martijn; Meeus, Wim; Maas, Cora

2004-01-01

This study examined the relationship between adolescent emotional adjustment and the family environment (i.e., family status, family process, and parental resources). This was done by way of multilevel analyses, with a sample of 2,636 parent-child couples of both intact and divorced families. The results indicated that adolescent emotional…

School Climate as a Predictor of Incivility and Bullying among Public School Employees: A Multilevel Analysis

ERIC Educational Resources Information Center

Powell, Joshua E.; Powell, Anna L.; Petrosko, Joseph M.

2015-01-01

We surveyed public school educators on the workplace incivility and workplace bullying they experienced and obtained their ratings of the organizational climate of the school. We used multilevel modeling to determine the effects of individual-level and school-level predictors. Ratings of school climate were significantly related to incivility and…

Workplace social capital and mental health among Chinese employees: a multi-level, cross-sectional study.

PubMed

Gao, Junling; Weaver, Scott R; Dai, Junming; Jia, Yingnan; Liu, Xingdi; Jin, Kezhi; Fu, Hua

2014-01-01

Whereas the majority of previous research on social capital and health has been on residential neighborhoods and communities, the evidence remains sparse on workplace social capital. To address this gap in the literature, we examined the association between workplace social capital and health status among Chinese employees in a large, multi-level, cross-sectional study. By employing a two-stage stratified random sampling procedure, 2,796 employees were identified from 35 workplaces in Shanghai during March to November 2012. Workplace social capital was assessed using a validated and psychometrically tested eight-item measure, and the Chinese language version of the WHO-Five Well-Being Index (WHO-5) was used to assess mental health. Control variables included sex, age, marital status, education level, occupation status, smoking status, physical activity, and job stress. Multilevel logistic regression analysis was conducted to explore whether individual- and workplace-level social capital was associated with mental health status. In total, 34.9% of workers reported poor mental health (WHO-5<13). After controlling for individual-level socio-demographic and lifestyle variables, compared to workers with the highest quartile of personal social capital, workers with the third, second, and lowest quartiles exhibited 1.39 to 3.54 times greater odds of poor mental health, 1.39 (95% CI: 1.10-1.75), 1.85 (95% CI: 1.38-2.46) and 3.54 (95% CI: 2.73-4.59), respectively. Corresponding odds ratios for workplace-level social capital were 0.95 (95% CI: 0.61-1.49), 1.14 (95% CI: 0.72-1.81) and 1.63 (95% CI: 1.05-2.53) for the third, second, and lowest quartiles, respectively. Higher workplace social capital is associated with lower odds of poor mental health among Chinese employees. Promoting social capital at the workplace may contribute to enhancing employees' mental health in China.

Workplace Social Capital and Mental Health among Chinese Employees: A Multi-Level, Cross-Sectional Study

PubMed Central

Gao, Junling; Weaver, Scott R.; Dai, Junming; Jia, Yingnan; Liu, Xingdi; Jin, Kezhi; Fu, Hua

2014-01-01

Background Whereas the majority of previous research on social capital and health has been on residential neighborhoods and communities, the evidence remains sparse on workplace social capital. To address this gap in the literature, we examined the association between workplace social capital and health status among Chinese employees in a large, multi-level, cross-sectional study. Methods By employing a two-stage stratified random sampling procedure, 2,796 employees were identified from 35 workplaces in Shanghai during March to November 2012. Workplace social capital was assessed using a validated and psychometrically tested eight-item measure, and the Chinese language version of the WHO-Five Well-Being Index (WHO-5) was used to assess mental health. Control variables included sex, age, marital status, education level, occupation status, smoking status, physical activity, and job stress. Multilevel logistic regression analysis was conducted to explore whether individual- and workplace-level social capital was associated with mental health status. Results In total, 34.9% of workers reported poor mental health (WHO-5<13). After controlling for individual-level socio-demographic and lifestyle variables, compared to workers with the highest quartile of personal social capital, workers with the third, second, and lowest quartiles exhibited 1.39 to 3.54 times greater odds of poor mental health, 1.39 (95% CI: 1.10–1.75), 1.85 (95% CI: 1.38–2.46) and 3.54 (95% CI: 2.73–4.59), respectively. Corresponding odds ratios for workplace-level social capital were 0.95 (95% CI: 0.61–1.49), 1.14 (95% CI: 0.72–1.81) and 1.63 (95% CI: 1.05–2.53) for the third, second, and lowest quartiles, respectively. Conclusions Higher workplace social capital is associated with lower odds of poor mental health among Chinese employees. Promoting social capital at the workplace may contribute to enhancing employees’ mental health in China. PMID:24404199

Individual schooling and women's community-level media exposure: a multilevel analysis of normative influences associated with women's justification of wife beating in Bangladesh.

PubMed

Krause, Kathleen H; Haardörfer, Regine; Yount, Kathryn M

2017-02-01

Our objective was to examine the multilevel correlates of women's justification of wife beating in Bangladesh, a form of intimate partner violence (IPV). We focus on individual-level schooling, community-level media exposure among women and their interaction. A cross-sectional study using data from the 2011 Bangladesh Demographic and Health Survey. Our sample included 17 749 ever-married women 15-49 years in 600 communities. We fit 6 multilevel logistic regression models to examine factors associated with justifying IPV; focusing on a woman's completed grades of schooling; frequent (at least once weekly) community-level media exposure among women via newspaper/magazine, television and radio; and their cross-level interaction. At the individual level, completing more grades of schooling than the community average was negatively associated with justifying IPV (0.95, 95% CI 0.94 to 0.97). The main effects of women's community-level media exposure were not significant, but suggested that frequent exposure to newspaper/magazine or television was negatively associated with justifying IPV, while exposure to radio was positively associated. In cross-level interactions, a woman's completed grades of schooling above the community average was protective against justifying IPV, even in communities where women's exposure to radio would otherwise increase the odds of justifying IPV. Different forms of media likely send different messages about gender and IPV. Girls' schooling should remain a priority, given its protective effect against justifying wife beating. Targeting girls and women who do not receive any schooling for intervention may yield the most benefit in terms of normative change regarding IPV against women. 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/.

A multilevel analysis of the effects of the Practice Environment Scale of the Nursing Work Index on nurse outcomes.

PubMed

Gabriel, Allison S; Erickson, Rebecca J; Moran, Christina M; Diefendorff, James M; Bromley, Gail E

2013-12-01

Few researchers have examined how the components of the Practice Environment Scale of the Nursing Work Index (PES-NWI) relate to nurses' well-being at multiple organizational levels. The objective of the study was to perform a multilevel assessment of the relationships of the PES-NWI subscales with three nurse outcomes: job satisfaction, emotional exhaustion, and turnover intentions. Additionally, we tested the multilevel factor structure of the PES-NWI. In a sample of 699 full-time registered nurses in 79 units and 9 branches of a hospital system, relationships of the NWI with nurse outcomes were fairly consistent across levels of analysis. However, subscales contributed differently to the three outcomes, demonstrating the complexity of environmental influences on nurses' work experience. © 2013 Wiley Periodicals, Inc.

Analyzing average and conditional effects with multigroup multilevel structural equation models

PubMed Central

Mayer, Axel; Nagengast, Benjamin; Fletcher, John; Steyer, Rolf

2014-01-01

Conventionally, multilevel analysis of covariance (ML-ANCOVA) has been the recommended approach for analyzing treatment effects in quasi-experimental multilevel designs with treatment application at the cluster-level. In this paper, we introduce the generalized ML-ANCOVA with linear effect functions that identifies average and conditional treatment effects in the presence of treatment-covariate interactions. We show how the generalized ML-ANCOVA model can be estimated with multigroup multilevel structural equation models that offer considerable advantages compared to traditional ML-ANCOVA. The proposed model takes into account measurement error in the covariates, sampling error in contextual covariates, treatment-covariate interactions, and stochastic predictors. We illustrate the implementation of ML-ANCOVA with an example from educational effectiveness research where we estimate average and conditional effects of early transition to secondary schooling on reading comprehension. PMID:24795668

Experimental studies of a prototype model of the multilevel 6KW-power inverter at supply by 12 accumulators

NASA Astrophysics Data System (ADS)

Taissariyeva, K.; Issembergenov, N.; Dzhobalaeva, G.; Usembaeva, S.

2016-09-01

The given paper considers the multilevel 6 kW-power transistor inverter at supply by 12 accumulators for transformation of solar battery energy to the electric power. At the output of the multilevel transistor inverter, it is possible to receive voltage close to a sinusoidal form. The main objective of this inverter is transformation of solar energy to the electric power of industrial frequency. The analysis of the received output curves of voltage on harmonicity has been carried out. In this paper it is set forth the developed scheme of the multilevel transistor inverter (DC-to-ac converter) which allows receiving at the output the voltage close to sinusoidal form, as well as to regulation of the output voltage level. In the paper, the results of computer modeling and experimental studies are presented.

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China

PubMed Central

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-01-01

Background: In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. Methods: As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6–12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. Results: The prevalence of anemia was 12.60% with a range of 3.47%–40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. Conclusions: The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities. PMID:27174328

Chi-squared Automatic Interaction Detection Decision Tree Analysis of Risk Factors for Infant Anemia in Beijing, China.

PubMed

Ye, Fang; Chen, Zhi-Hua; Chen, Jie; Liu, Fang; Zhang, Yong; Fan, Qin-Ying; Wang, Lin

2016-05-20

In the past decades, studies on infant anemia have mainly focused on rural areas of China. With the increasing heterogeneity of population in recent years, available information on infant anemia is inconclusive in large cities of China, especially with comparison between native residents and floating population. This population-based cross-sectional study was implemented to determine the anemic status of infants as well as the risk factors in a representative downtown area of Beijing. As useful methods to build a predictive model, Chi-squared automatic interaction detection (CHAID) decision tree analysis and logistic regression analysis were introduced to explore risk factors of infant anemia. A total of 1091 infants aged 6-12 months together with their parents/caregivers living at Heping Avenue Subdistrict of Beijing were surveyed from January 1, 2013 to December 31, 2014. The prevalence of anemia was 12.60% with a range of 3.47%-40.00% in different subgroup characteristics. The CHAID decision tree model has demonstrated multilevel interaction among risk factors through stepwise pathways to detect anemia. Besides the three predictors identified by logistic regression model including maternal anemia during pregnancy, exclusive breastfeeding in the first 6 months, and floating population, CHAID decision tree analysis also identified the fourth risk factor, the maternal educational level, with higher overall classification accuracy and larger area below the receiver operating characteristic curve. The infant anemic status in metropolis is complex and should be carefully considered by the basic health care practitioners. CHAID decision tree analysis has demonstrated a better performance in hierarchical analysis of population with great heterogeneity. Risk factors identified by this study might be meaningful in the early detection and prompt treatment of infant anemia in large cities.

A new rational-based optimal design strategy of ship structure based on multi-level analysis and super-element modeling method

NASA Astrophysics Data System (ADS)

Sun, Li; Wang, Deyu

2011-09-01

A new multi-level analysis method of introducing the super-element modeling method, derived from the multi-level analysis method first proposed by O. F. Hughes, has been proposed in this paper to solve the problem of high time cost in adopting a rational-based optimal design method for ship structural design. Furthermore, the method was verified by its effective application in optimization of the mid-ship section of a container ship. A full 3-D FEM model of a ship, suffering static and quasi-static loads, was used as the analyzing object for evaluating the structural performance of the mid-ship module, including static strength and buckling performance. Research results reveal that this new method could substantially reduce the computational cost of the rational-based optimization problem without decreasing its accuracy, which increases the feasibility and economic efficiency of using a rational-based optimal design method in ship structural design.

Comparative assessment of analytical approaches to quantify the risk for introduction of rare animal diseases: the example of avian influenza in Spain.

PubMed

Sánchez-Vizcaíno, Fernando; Perez, Andrés; Martínez-López, Beatriz; Sánchez-Vizcaíno, José Manuel

2012-08-01

Trade of animals and animal products imposes an uncertain and variable risk for exotic animal diseases introduction into importing countries. Risk analysis provides importing countries with an objective, transparent, and internationally accepted method for assessing that risk. Over the last decades, European Union countries have conducted probabilistic risk assessments quite frequently to quantify the risk for rare animal diseases introduction into their territories. Most probabilistic animal health risk assessments have been typically classified into one-level and multilevel binomial models. One-level models are more simple than multilevel models because they assume that animals or products originate from one single population. However, it is unknown whether such simplification may result in substantially different results compared to those obtained through the use of multilevel models. Here, data used on a probabilistic multilevel binomial model formulated to assess the risk for highly pathogenic avian influenza introduction into Spain were reanalyzed using a one-level binomial model and their outcomes were compared. An alternative ordinal model is also proposed here, which makes use of simpler assumptions and less information compared to those required by traditional one-level and multilevel approaches. Results suggest that, at least under certain circumstances, results of the one-level and ordinal approaches are similar to those obtained using multilevel models. Consequently, we argue that, when data are insufficient to run traditional probabilistic models, the ordinal approach presented here may be a suitable alternative to rank exporting countries in terms of the risk that they impose for the spread of rare animal diseases into disease-free countries. © 2012 Society for Risk Analysis.

Analysis of Anterior Cervical Discectomy and Fusion Healthcare Costs via the Value-Driven Outcomes Tool.

PubMed

Reese, Jared C; Karsy, Michael; Twitchell, Spencer; Bisson, Erica F

2018-04-11

Examining the costs of single- and multilevel anterior cervical discectomy and fusion (ACDF) is important for the identification of cost drivers and potentially reducing patient costs. A novel tool at our institution provides direct costs for the identification of potential drivers. To assess perioperative healthcare costs for patients undergoing an ACDF. Patients who underwent an elective ACDF between July 2011 and January 2017 were identified retrospectively. Factors adding to total cost were placed into subcategories to identify the most significant contributors, and potential drivers of total cost were evaluated using a multivariable linear regression model. A total of 465 patients (mean, age 53 ± 12 yr, 54% male) met the inclusion criteria for this study. The distribution of total cost was broken down into supplies/implants (39%), facility utilization (37%), physician fees (14%), pharmacy (7%), imaging (2%), and laboratory studies (1%). A multivariable linear regression analysis showed that total cost was significantly affected by the number of levels operated on, operating room time, and length of stay. Costs also showed a narrow distribution with few outliers and did not vary significantly over time. These results suggest that facility utilization and supplies/implants are the predominant cost contributors, accounting for 76% of the total cost of ACDF procedures. Efforts at lowering costs within these categories should make the most impact on providing more cost-effective care.

Negative mood states and related factors in a sample of adolescent secondary-school students in Barcelona (Spain).

PubMed

Ahonen, Emily Q; Nebot, Manel; Giménez, Emmanuel

2007-01-01

Poor mental health is a common problem in adolescence. Little information is available, however, about the factors influencing negative mood states in otherwise healthy adolescents. We aimed to describe the mood states and related factors in a sample of adolescents in the city of Barcelona (Spain). We administered a health survey to a sample of 2,727 students from public, subsidized, and private schools in Barcelona, aged approximately 14, 16, and 18 years old. To analyze the associations among moods and related factors, we used bivariate logistic regression, and fitted multivariate logistic regressions using the statistically significant variables from the bivariate analysis. To examine the possible group effects of the school on individual students, we employed multilevel analysis. The frequencies of negative mood states increased with age, with girls consistently reporting more frequent negative mood states than boys. The factors associated with negative mood states were problematic alcohol use, perceived mistreatment or abuse, antisocial behavior, intention to use or current use of illegal drugs (not including cannabis), lower perceived academic performance, and feeling isolated. Mood states are influenced by lifestyle and social factors, about which there is little local information. To plan and implement appropriate public health interventions, more complete information about the possible areas of influence is required. To complement the information obtained from studies such as the present study, longitudinal and qualitative studies would be desirable.

Zero-Profile Spacer Versus Cage-Plate Construct in Anterior Cervical Diskectomy and Fusion for Multilevel Cervical Spondylotic Myelopathy: Systematic Review and Meta-Analysis.

PubMed

Tong, Min-Ji; Xiang, Guang-Heng; He, Zi-Li; Chen, De-Heng; Tang, Qian; Xu, Hua-Zi; Tian, Nai-Feng

2017-08-01

Anterior cervical diskectomy and fusion with plate-screw construct has been gradually applied for multilevel cervical spondylotic myelopathy in recent years. However, long cervical plate was associated with complications including breakage or loosening of plate and screws, trachea-esophageal injury, neurovascular injury, and postoperative dysphagia. To reduce these complications, the zero-profile spacer has been introduced. This meta-analysis was performed to compare the clinical and radiologic outcomes of zero-profile spacer versus cage-plate construct for the treatment of multilevel cervical spondylotic myelopathy. We systematically searched MEDLINE, Springer, and Web of Science databases for relevant studies that compared the clinical and radiologic outcomes of zero-profile spacer versus cage and plate for multilevel cervical spondylotic myelopathy. Risk of bias in included studies was assessed. Pooled estimates and corresponding 95% confidence intervals were calculated. On the basis of predefined inclusion criteria, 7 studies with a total of 409 patients were included in this analysis. The pooled data revealed that zero-profile spacer was associated with a decreased dysphagia rate at 2, 3, and 6 months postoperatively when compared with the cage-plate group. Both techniques had similar perioperative outcomes, functional outcome, radiologic outcome, and dysphagia rate immediately and at >1-year after operation. On the basis of available evidence, zero-profile spacer was more effective in reducing postoperative dysphagia rate for multilevel cervical spondylotic myelopathy. Both devices were safe in anterior cervical surgeries, and they had similar efficacy in improving the functional and radiologic outcomes. More randomized controlled trials are needed to compare these 2 devices. Copyright © 2017 Elsevier Inc. All rights reserved.

Contract and ownership type of general practices and patient experience in England: multilevel analysis of a national cross-sectional survey

PubMed Central

Laverty, Anthony A; Harris, Matthew J; Watt, Hilary C; Greaves, Felix; Majeed, Azeem

2017-01-01

Objective To examine associations between the contract and ownership type of general practices and patient experience in England. Design Multilevel linear regression analysis of a national cross-sectional patient survey (General Practice Patient Survey). Setting All general practices in England in 2013–2014 (n = 8017). Participants 903,357 survey respondents aged 18 years or over and registered with a general practice for six months or more (34.3% of 2,631,209 questionnaires sent). Main outcome measures Patient reports of experience across five measures: frequency of consulting a preferred doctor; ability to get a convenient appointment; rating of doctor communication skills; ease of contacting the practice by telephone; and overall experience (measured on four- or five-level interval scales from 0 to 100). Models adjusted for demographic and socioeconomic characteristics of respondents and general practice populations and a random intercept for each general practice. Results Most practices had a centrally negotiated contract with the UK government (‘General Medical Services’ 54.6%; 4337/7949). Few practices were limited companies with locally negotiated ‘Alternative Provider Medical Services’ contracts (1.2%; 98/7949); these practices provided worse overall experiences than General Medical Services practices (adjusted mean difference −3.04, 95% CI −4.15 to −1.94). Associations were consistent in direction across outcomes and largest in magnitude for frequency of consulting a preferred doctor (−12.78, 95% CI −15.17 to −10.39). Results were similar for practices owned by large organisations (defined as having ≥20 practices) which were uncommon (2.2%; 176/7949). Conclusions Patients registered to general practices owned by limited companies, including large organisations, reported worse experiences of their care than other patients in 2013–2014. PMID:29096580

Risk factors for prelacteal feeding in sub-Saharan Africa: a multilevel analysis of population data from twenty-two countries.

PubMed

Berde, Anselm S; Ozcebe, Hilal

2017-08-01

To examine the risk factors of prelacteal feeding (PLF) among mothers in sub-Saharan Africa (SSA). We pooled data from Demographic and Health Surveys in twenty-two SSA countries. The key outcome variable was PLF. A multilevel logistic regression model was used to explore factors associated with PLF. Demographic and Health Surveys in twenty-two SSA countries. Mother-baby pairs (n 95348). Prevalence of PLF in SSA was 32·2 %. Plain water (22·1 %), milk other than breast milk (5·0 %) and sugar or glucose water (4·1 %) were the predominant prelacteal feeds. In the multivariable analysis, mothers who had caesarean section delivery had 2·25 times the odds of giving prelacteal feeds compared with mothers who had spontaneous vaginal delivery (adjusted OR=2·25; 95 % CI 2·06, 2·46). Other factors that were significantly associated with increased likelihood of PLF were mother's lower educational status, first birth rank, fourth or above birth rank with preceding birth interval less than or equal to 24 months, lower number of antenatal care visits, home delivery, multiple birth, male infant, as well as having an average or small sized baby at birth. Mothers aged 20-34 years were less likely to give prelacteal feeds compared with mothers aged ≤19 years. Belonging to the second, middle or fourth wealth quintile was associated with lower likelihood of PLF compared with the highest quintile. To achieve optimal breast-feeding, there is a need to discourage breast-feeding practices such as PLF. Breast-feeding promotion programmes should target the at-risk sub-population groups discovered in our study.

Bacterial Adherence and Dwelling Probability: Two Drivers of Early Alveolar Infection by Streptococcus pneumoniae Identified in Multi-Level Mathematical Modeling

PubMed Central

Santos, Guido; Lai, Xin; Eberhardt, Martin; Vera, Julio

2018-01-01

Pneumococcal infection is the most frequent cause of pneumonia, and one of the most prevalent diseases worldwide. The population groups at high risk of death from bacterial pneumonia are infants, elderly and immunosuppressed people. These groups are more vulnerable because they have immature or impaired immune systems, the efficacy of their response to vaccines is lower, and antibiotic treatment often does not take place until the inflammatory response triggered is already overwhelming. The immune response to bacterial lung infections involves dynamic interactions between several types of cells whose activation is driven by intracellular molecular networks. A feasible approach to the integration of knowledge and data linking tissue, cellular and intracellular events and the construction of hypotheses in this area is the use of mathematical modeling. For this paper, we used a multi-level computational model to analyse the role of cellular and molecular interactions during the first 10 h after alveolar invasion of Streptococcus pneumoniae bacteria. By “multi-level” we mean that we simulated the interplay between different temporal and spatial scales in a single computational model. In this instance, we included the intracellular scale of processes driving lung epithelial cell activation together with the scale of cell-to-cell interactions at the alveolar tissue. In our analysis, we combined systematic model simulations with logistic regression analysis and decision trees to find genotypic-phenotypic signatures that explain differences in bacteria strain infectivity. According to our simulations, pneumococci benefit from a high dwelling probability and a high proliferation rate during the first stages of infection. In addition to this, the model predicts that during the very early phases of infection the bacterial capsule could be an impediment to the establishment of the alveolar infection because it impairs bacterial colonization. PMID:29868515

Does it really matter where women live? A multilevel analysis of the determinants of postnatal care in Nigeria.

PubMed

Ononokpono, Dorothy N; Odimegwu, Clifford O; Imasiku, Eunice N S; Adedini, Sunday A

2014-05-01

Although postnatal care is one of the major interventions recommended for the reduction of maternal and newborn deaths worldwide, almost two-third (56 %) of women in Nigeria do not receive postnatal care. Attempts to explain this situation have focused on individual and household level factors, but the role of community characteristics has received less attention.This study examines community factors associated with the receipt of postnatal care in Nigeria and the moderating effects of community factors on the association between individual factors and postnatal care. Data was drawn from the 2008 Nigeria Demographic and Health Survey, and a sample of 17,846 women aged 15-49 years was selected. We employed a multilevel logistic regression analysis to identify community factors associated with postnatal care. Our findings showed that significant variations in receiving postnatal care exist across communities. Specifically, Nigerian women's likelihood of receiving postnatal care is a function of where they reside. Living in communities with a high proportion of educated women (OR = 2.04; 95 % CI = 1.32-3.16; p < 0.001) and a high proportion of those who have had a health facility delivery (OR = 17.86; 95 % CI = 8.34-38.24; p < 0.001) was significantly associated with an increased likelihood of receiving postnatal care. Community women's education moderated the association between ethnic origin and postnatal care. Community variance in postnatal care was significant (τ = 10.352, p = 0.001). Community interventions aimed at improving postnatal care should take into account the community context in which women live. To close the gap in community variations in postnatal care, secondary and higher education for women, and health facility delivery should be increased in disadvantaged communities.

Hospital variability in postoperative mortality after rectal cancer surgery in the Spanish Association of Surgeons project: The impact of hospital volume.

PubMed

Ortiz, Héctor; Biondo, Sebastiano; Codina, Antonio; Ciga, Miguel Á; Enríquez-Navascués, José M; Espín, Eloy; García-Granero, Eduardo; Roig, José Vicente

2016-01-01

This multicentre observational study examines variation between hospitals in postoperative mortality after elective surgery in the Rectal Cancer Project of the Spanish Society of Surgeons and explores whether hospital volume and patient characteristics contribute to any variation between hospitals. Hospital variation was quantified using a multilevel approach on prospective data derived from the multicentre database of all rectal adenocarcinomas operated by an anterior resection or an abdominoperineal excision at 84 surgical departments from 2006 to 2013. The following variables were included in the analysis; demographics, American Society of Anaesthesiologists classification, tumour location and stage, administration of neoadjuvant treatment, and annual volume of surgical procedures. A total of 9809 consecutive patients were included. The rate of 30-day postoperative mortality was 1.8% Stratified by annual surgical volume hospitals varied from 1.4 to 2.0 in 30-day mortality. In the multilevel regression analysis, male gender (OR 1.623 [1.143; 2.348]; P<.008), increased age (OR: 5.811 [3.479; 10.087]; P<.001), and ASA score (OR 10.046 [3.390; 43.185]; P<.001) were associated with 30-day mortality. However, annual surgical volume was not associated with mortality (OR 1.309 [0.483; 4.238]; P=.619). Besides, there was a statistically significant variation in mortality between all departments (MOR 1.588 [1.293; 2.015]; P<.001). Postoperative mortality varies significantly among hospitals included in the project and this difference cannot be attributed to the annual surgical volume. Copyright © 2015 AEC. Publicado por Elsevier España, S.L.U. All rights reserved.

Undertreatment of acute pain (oligoanalgesia) and medical practice variation in prehospital analgesia of adult trauma patients: a 10 yr retrospective study.

PubMed

Albrecht, E; Taffe, P; Yersin, B; Schoettker, P; Decosterd, I; Hugli, O

2013-01-01

Prehospital oligoanalgesia is prevalent among trauma victims, even when the emergency medical services team includes a physician. We investigated if not only patients' characteristics but physicians' practice variations contributed to prehospital oligoanalgesia. Patient records of conscious adult trauma victims transported by our air rescue helicopter service over 10 yr were reviewed retrospectively. Oligoanalgesia was defined as a numeric rating scale (NRS) >3 at hospital admission. Multilevel logistic regression analysis was used to predict oligoanalgesia, accounting first for patient case-mix, and then physician-level clustering. The intraclass correlation was expressed as the median odds ratio (MOR). A total of 1202 patients and 77 physicians were included in the study. NRS at the scene was 6.9 (1.9). The prevalence of oligoanalgesia was 43%. Physicians had a median of 5.7 yr (inter-quartile range: 4.2-7.5) of post-graduate training and 27% were female. In our multilevel analysis, significant predictors of oligoanalgesia were: no analgesia [odds ratio (OR) 8.8], National Advisory Committee for Aeronautics V on site (OR 4.4), NRS on site (OR 1.5 per additional NRS unit >4), female physician (OR 2.0), and years of post-graduate experience [>4.0 to ≤5.0 (OR 1.3), >3.0 to ≤4.0 (OR 1.6), >2.0 to ≤3.0 (OR 2.6), and ≤2.0 yr (OR 16.7)]. The MOR was 2.6, and was statistically significant. Physicians' practice variations contributed to oligoanalgesia, a factor often overlooked in analyses of prehospital pain management. Further exploration of the sources of these variations may provide innovative targets for quality improvement programmes to achieve consistent pain relief for trauma victims.

Shared environments: a multilevel analysis of community context and child nutritional status in Bangladesh.

PubMed

Corsi, Daniel J; Chow, Clara K; Lear, Scott A; Rahman, M Omar; Subramanian, S V; Teo, Koon K

2011-06-01

The goal of the present study was to examine the influence of community environment on the nutritional status (weight-for-age and height-for-age) of children (aged 0-59 months) in Bangladesh. In addition, we tested the association between specific characteristics of community environments and child nutritional status. Cross-sectional survey. The data are from the nationally representative 2004 Bangladesh Demographic and Health Survey. Respondents were ever-married women (aged 15-49 years) and their children (n 5731), residing in 361 communities. Child nutritional outcomes are physical measurements of weight-for-age and height-for-age in sd units. We considered the following attributes of community environments potentially related to child nutrition: (i) community water and sanitation infrastructure; (ii) availability of community health and education services; (iii) community employment and social participation; and (iv) education level of the community. Multilevel regression analysis showed that the spatial distribution of maternal and child covariates did not entirely explain the between-community variation in child nutritional status. The education level of the community emerged as the strongest community-level predictor of child height-for-age (highest v. lowest tertile, β = 0.18 (SE 0.07)) and weight-for-age (highest v. lowest tertile, β = 0.21 (SE 0.06)). In the height-for-age model, community employment and social participation also emerged as being statistically significant (highest v. lowest tertile, β = 0.13 (SE = 0.06)). The community environment influences child nutrition in Bangladesh, and maternal- and child-level covariates may fail to capture the entire influence of communities. Interventions to reduce child undernutrition in developing countries should take into consideration the wider community context.

Associations of all-cause mortality with census-based neighbourhood deprivation and population density in Japan: a multilevel survival analysis.

PubMed

Nakaya, Tomoki; Honjo, Kaori; Hanibuchi, Tomoya; Ikeda, Ai; Iso, Hiroyasu; Inoue, Manami; Sawada, Norie; Tsugane, Shoichiro

2014-01-01

Despite evidence that neighbourhood conditions affect residents' health, no prospective studies of the association between neighbourhood socio-demographic factors and all-cause mortality have been conducted in non-Western societies. Thus, we examined the effects of areal deprivation and population density on all-cause mortality in Japan. We employed census and survival data from the Japan Public Health Center-based Prospective Study, Cohort I (n = 37,455), consisting of middle-aged residents (40 to 59 years at the baseline in 1990) living in four public health centre districts. Data spanned between 1990 and 2010. A multilevel parametric proportional-hazard regression model was applied to estimate the hazard ratios (HRs) of all-cause mortality by two census-based areal variables--areal deprivation index and population density--as well as individualistic variables such as socioeconomic status and various risk factors. We found that areal deprivation and population density had moderate associations with all-cause mortality at the neighbourhood level based on the survival data with 21 years of follow-ups. Even when controlling for individualistic socio-economic status and behavioural factors, the HRs of the two areal factors (using quartile categorical variables) significantly predicted mortality. Further, this analysis indicated an interaction effect of the two factors: areal deprivation prominently affects the health of residents in neighbourhoods with high population density. We confirmed that neighbourhood socio-demographic factors are significant predictors of all-cause death in Japanese non-metropolitan settings. Although further study is needed to clarify the cause-effect relationship of this association, the present findings suggest that health promotion policies should consider health disparities between neighbourhoods and possibly direct interventions towards reducing mortality in densely populated and highly deprived neighbourhoods.

The effect of contextual factors on unintentional injury hospitalization: from the Korea National Hospital Discharge Survey.

PubMed

Lee, Hye Ah; Han, Hyejin; Lee, Seonhwa; Park, Bomi; Park, Bo Hyun; Lee, Won Kyung; Park, Ju Ok; Hong, Sungok; Kim, Young Taek; Park, Hyesook

2018-03-13

It has been suggested that health risks are affected by geographical area, but there are few studies on contextual effects using multilevel analysis, especially regarding unintentional injury. This study investigated trends in unintentional injury hospitalization rates over the past decade in Korea, and also examined community-level risk factors while controlling for individual-level factors. Using data from the 2004 to 2013 Korea National Hospital Discharge Survey (KNHDS), trends in age-adjusted injury hospitalization rate were conducted using the Joinpoint Regression Program. Based on the 2013 KNHDS, we collected community-level factors by linking various data sources and selected dominant factors related to injury hospitalization through a stepwise method. Multilevel analysis was performed to assess the community-level factors while controlling for individual-level factors. In 2004, the age-adjusted unintentional injury hospitalization rate was 1570.1 per 100,000 population and increased to 1887.1 per 100,000 population in 2013. The average annual percent change in rate of hospitalizations due to unintentional injury was 2.31% (95% confidence interval: 1.8-2.9). It was somewhat higher for females than for males (3.25% vs. 1.64%, respectively). Both community- and individual-level factors were found to significantly influence unintentional injury hospitalization risk. As community-level risk factors, finance utilization capacity of the local government and neighborhood socioeconomic status, were independently associated with unintentional injury hospitalization after controlling for individual-level factors, and accounted for 19.9% of community-level variation in unintentional injury hospitalization. Regional differences must be considered when creating policies and interventions. Further studies are required to evaluate specific factors related to injury mechanism.

The role of individual, community and societal gender inequality in forming women's attitudes toward intimate-partner violence against women: a multilevel analysis.

PubMed

Uthman, Olalekan A; Lawoko, Stephen; Moradi, Tahereh

2010-01-01

Establishing risk factors for intimate partner violence against women (IPVAW) is crucial for addressing women's health and development. Acceptance of IPVAW has been suggested as one of the strongest predictors of IPVAWs. The aim of this study was to examine the independent contributions of individual, community, and societal measures of gender inequality in forming women's attitudes toward IPVAW. We applied multivariable multilevel logistic regression analysis to Demographic and Health Survey data for 120,467 women nested within 7463 communities from 17 countries in sub-Saharan Africa. We found that women whose husband had higher education (odds ratio [OR] =1.06; 95% confidence interval [CI] 1.02 to 1.10) and women whose husband had more than one wife (OR=1.14; 95% CI 1.09 to 1.19) were more likely to accept IPVAW than other women. Unemployed women with an unemployed partner were more likely to justify IPVAW than employed women with working partners (OR=1.32; 95% CI 1.08 to 1.61). Both community and societal measures of gender inequality were associated with women's attitudes toward IPVAW, even after controlling for gender inequality at the individual level. There was evidence of clustering of women's attitudes within communities and within countries. We provide evidence that community and societal forms of gender inequality influence women's attitudes toward IPVAW beyond individual factors. Choices women make are important, but community and society also impose restraints on women's attitudes toward IPVAW. Thus, policies and programs aimed at reducing or eliminating IPVAW must address people, the communities and societies in which they live in order to be successful.

Do personality traits assessed on medical school admission predict exit performance? A UK-wide longitudinal cohort study.

PubMed

MacKenzie, R K; Dowell, J; Ayansina, D; Cleland, J A

2017-05-01

Traditional methods of assessing personality traits in medical school selection have been heavily criticised. To address this at the point of selection, "non-cognitive" tests were included in the UK Clinical Aptitude Test, the most widely-used aptitude test in UK medical education (UKCAT: http://www.ukcat.ac.uk/ ). We examined the predictive validity of these non-cognitive traits with performance during and on exit from medical school. We sampled all students graduating in 2013 from the 30 UKCAT consortium medical schools. Analysis included: candidate demographics, UKCAT non-cognitive scores, medical school performance data-the Educational Performance Measure (EPM) and national exit situational judgement test (SJT) outcomes. We examined the relationships between these variables and SJT and EPM scores. Multilevel modelling was used to assess the relationships adjusting for confounders. The 3343 students who had taken the UKCAT non-cognitive tests and had both EPM and SJT data were entered into the analysis. There were four types of non-cognitive test: (1) libertariancommunitarian, (2) NACE-narcissism, aloofness, confidence and empathy, (3) MEARS-self-esteem, optimism, control, self-discipline, emotional-nondefensiveness (END) and faking, (4) an abridged version of 1 and 2 combined. Multilevel regression showed that, after correcting for demographic factors, END predicted SJT and EPM decile. Aloofness and empathy in NACE were predictive of SJT score. This is the first large-scale study examining the relationship between performance on non-cognitive selection tests and medical school exit assessments. The predictive validity of these tests was limited, and the relationships revealed do not fit neatly with theoretical expectations. This study does not support their use in selection.

Associations of All-Cause Mortality with Census-Based Neighbourhood Deprivation and Population Density in Japan: A Multilevel Survival Analysis

PubMed Central

Nakaya, Tomoki; Honjo, Kaori; Hanibuchi, Tomoya; Ikeda, Ai; Iso, Hiroyasu; Inoue, Manami; Sawada, Norie; Tsugane, Shoichiro

2014-01-01

Background Despite evidence that neighbourhood conditions affect residents' health, no prospective studies of the association between neighbourhood socio-demographic factors and all-cause mortality have been conducted in non-Western societies. Thus, we examined the effects of areal deprivation and population density on all-cause mortality in Japan. Methods We employed census and survival data from the Japan Public Health Center-based Prospective Study, Cohort I (n = 37,455), consisting of middle-aged residents (40 to 59 years at the baseline in 1990) living in four public health centre districts. Data spanned between 1990 and 2010. A multilevel parametric proportional-hazard regression model was applied to estimate the hazard ratios (HRs) of all-cause mortality by two census-based areal variables —areal deprivation index and population density—as well as individualistic variables such as socioeconomic status and various risk factors. Results We found that areal deprivation and population density had moderate associations with all-cause mortality at the neighbourhood level based on the survival data with 21 years of follow-ups. Even when controlling for individualistic socio-economic status and behavioural factors, the HRs of the two areal factors (using quartile categorical variables) significantly predicted mortality. Further, this analysis indicated an interaction effect of the two factors: areal deprivation prominently affects the health of residents in neighbourhoods with high population density. Conclusions We confirmed that neighbourhood socio-demographic factors are significant predictors of all-cause death in Japanese non-metropolitan settings. Although further study is needed to clarify the cause-effect relationship of this association, the present findings suggest that health promotion policies should consider health disparities between neighbourhoods and possibly direct interventions towards reducing mortality in densely populated and highly deprived neighbourhoods. PMID:24905731

A regional multilevel analysis: can skilled birth attendants uniformly decrease neonatal mortality?

PubMed

Singh, Kavita; Brodish, Paul; Suchindran, Chirayath

2014-01-01

Globally 40 % of deaths to children under-five occur in the very first month of life with three-quarters of these deaths occurring during the first week of life. The promotion of delivery with a skilled birth attendant (SBA) is being promoted as a strategy to reduce neonatal mortality. This study explored whether SBAs had a protective effect against neonatal mortality in three different regions of the world. The analysis pooled data from nine diverse countries for which recent Demographic and Health Survey data were available. Multilevel logistic regression was used to understand the influence of skilled delivery on two outcomes-neonatal mortality during the first week of life and during the first day of life. Control variables included age, parity, education, wealth, residence (urban/rural), geographic region (Africa, Asia and Latin America/Caribbean), antenatal care and tetanus immunization. The direction of the effect of skilled delivery on neonatal mortality was dependent on geographic region. While having a SBA at delivery was protective against neonatal mortality in Latin America/Caribbean, in Asia there was only a protective effect for births in the first week of life. In Africa SBAs were associated with higher neonatal mortality for both outcomes, and the same was true for deaths on the first day of life in Asia. Many women in Africa and Asia deliver at home unless a complication occurs, and thus skilled birth attendants may be seeing more women with complications than their unskilled counterparts. In addition there are issues with the definition of a SBA with many attendants in both Africa and Asia not actually having the needed training and equipment to prevent neonatal mortality. Considerable investment is needed in terms of training and health infrastructure to enable these providers to save the youngest lives.

Contract and ownership type of general practices and patient experience in England: multilevel analysis of a national cross-sectional survey.

PubMed

Cowling, Thomas E; Laverty, Anthony A; Harris, Matthew J; Watt, Hilary C; Greaves, Felix; Majeed, Azeem

2017-11-01

Objective To examine associations between the contract and ownership type of general practices and patient experience in England. Design Multilevel linear regression analysis of a national cross-sectional patient survey (General Practice Patient Survey). Setting All general practices in England in 2013-2014 ( n = 8017). Participants 903,357 survey respondents aged 18 years or over and registered with a general practice for six months or more (34.3% of 2,631,209 questionnaires sent). Main outcome measures Patient reports of experience across five measures: frequency of consulting a preferred doctor; ability to get a convenient appointment; rating of doctor communication skills; ease of contacting the practice by telephone; and overall experience (measured on four- or five-level interval scales from 0 to 100). Models adjusted for demographic and socioeconomic characteristics of respondents and general practice populations and a random intercept for each general practice. Results Most practices had a centrally negotiated contract with the UK government ('General Medical Services' 54.6%; 4337/7949). Few practices were limited companies with locally negotiated 'Alternative Provider Medical Services' contracts (1.2%; 98/7949); these practices provided worse overall experiences than General Medical Services practices (adjusted mean difference -3.04, 95% CI -4.15 to -1.94). Associations were consistent in direction across outcomes and largest in magnitude for frequency of consulting a preferred doctor (-12.78, 95% CI -15.17 to -10.39). Results were similar for practices owned by large organisations (defined as having ≥20 practices) which were uncommon (2.2%; 176/7949). Conclusions Patients registered to general practices owned by limited companies, including large organisations, reported worse experiences of their care than other patients in 2013-2014.

The Role of School Culture and Basic Psychological Needs on Iranian Adolescents' Academic Alienation: A Multi-Level Examination

ERIC Educational Resources Information Center

Mahmoudi, Hojjat; Brown, Monica R.; Amani Saribagloo, Javad; Dadashzadeh, Shiva

2018-01-01

This aim of this current research was a multi-level analysis of the relationship between school culture, basic psychological needs, and adolescents' academic alienation. One thousand twenty-nine (N = 1,029) high school students from Qom City were randomly selected through a multi-phase cluster sampling method and answered questions regarding…

Multi-level optimization of a beam-like space truss utilizing a continuum model

NASA Technical Reports Server (NTRS)

Yates, K.; Gurdal, Z.; Thangjitham, S.

1992-01-01

A continuous beam model is developed for approximate analysis of a large, slender, beam-like truss. The model is incorporated in a multi-level optimization scheme for the weight minimization of such trusses. This scheme is tested against traditional optimization procedures for savings in computational cost. Results from both optimization methods are presented for comparison.

Community Social and Place Predictors of Sense of Community: A Multilevel and Longitudinal Analysis

ERIC Educational Resources Information Center

Long, D. Adam; Perkins, Douglas D.

2007-01-01

Sense of community (SOC) is empirically "unpacked" as a multilevel construct with place and social elements. SOC has been studied primarily at the individual level despite researchers acknowledging its effects at the community level. Little attention has been given to the roles of place and place attitudes in SOC. We argue that place and…

Multilevel Analysis of the Effects of Antidiscrimination Policies on Earnings by Sexual Orientation

ERIC Educational Resources Information Center

Klawitter, Marieka

2011-01-01

This study uses the 2000 U.S. Census data to assess the impact of antidiscrimination policies for sexual orientation on earnings for gays and lesbians. Using a multilevel model allows estimation of the effects of state and local policies on earnings and of variation in the effects of sexual orientation across local labor markets. The results…

Estimating Multi-Level Discrete-Time Hazard Models Using Cross-Sectional Data: Neighborhood Effects on the Onset of Adolescent Cigarette Use.

ERIC Educational Resources Information Center

Reardon, Sean F.; Brennan, Robert T.; Buka, Stephen L.

2002-01-01

Developed procedures for constructing a retrospective person-period data set from cross-sectional data and discusses modeling strategies for estimating multilevel discrete-time event history models. Applied the methods to the analysis of cigarette use by 1,979 urban adolescents. Results show the influence of the racial composition of the…

Exploring the Association between Transformational Leadership and Teacher's Self-Efficacy in Greek Education System: A Multilevel SEM Model

ERIC Educational Resources Information Center

Gkolia, Aikaterini; Koustelios, Athanasios; Belias, Dimitrios

2018-01-01

The main aim of this study is to examine the effect of principals' transformational leadership on teachers' self-efficacy across 77 different Greek elementary and secondary schools based on a centralized education system. For the investigation of the above effect multilevel Structural Equation Modelling analysis was conducted, recognizing the…

A Multilevel Analysis of Student Perceptions of School Climate: The Effect of Social and Academic Risk Factors

ERIC Educational Resources Information Center

Fan, Weihua; Williams, Cathy M.; Corkin, Danya Marie

2011-01-01

This multilevel study examines the extent to which individual- and school-level variables are predictive of three aspects of students' perceived school climate (order, safety, and discipline; fairness and clarity of school rules; and teacher-student relationship) by using a nationally representative sample. A wide range of social and academic risk…

Soft-decision decoding techniques for linear block codes and their error performance analysis

NASA Technical Reports Server (NTRS)

Lin, Shu

1996-01-01

The first paper presents a new minimum-weight trellis-based soft-decision iterative decoding algorithm for binary linear block codes. The second paper derives an upper bound on the probability of block error for multilevel concatenated codes (MLCC). The bound evaluates difference in performance for different decompositions of some codes. The third paper investigates the bit error probability code for maximum likelihood decoding of binary linear codes. The fourth and final paper included in this report is concerns itself with the construction of multilevel concatenated block modulation codes using a multilevel concatenation scheme for the frequency non-selective Rayleigh fading channel.

Economic and Sociological Correlates of Suicides: Multilevel Analysis of the Time Series Data in the United Kingdom.

PubMed

Sun, Bruce Qiang; Zhang, Jie

2016-03-01

For the effects of social integration on suicides, there have been different and even contradictive conclusions. In this study, the selected economic and social risks of suicide for different age groups and genders in the United Kingdom were identified and the effects were estimated by the multilevel time series analyses. To our knowledge, there exist no previous studies that estimated a dynamic model of suicides on the time series data together with multilevel analysis and autoregressive distributed lags. The investigation indicated that unemployment rate, inflation rate, and divorce rate are all significantly and positively related to the national suicide rates in the United Kingdom from 1981 to 2011. Furthermore, the suicide rates of almost all groups above 40 years are significantly associated with the risk factors of unemployment and inflation rate, in comparison with the younger groups. © 2016 American Academy of Forensic Sciences.

A Multilevel Multiset Time-Series Model for Describing Complex Developmental Processes

PubMed Central

Ma, Xin; Shen, Jianping

2017-01-01

The authors sought to develop an analytical platform where multiple sets of time series can be examined simultaneously. This multivariate platform capable of testing interaction effects among multiple sets of time series can be very useful in empirical research. The authors demonstrated that the multilevel framework can readily accommodate this analytical capacity. Given their intention to use the multilevel multiset time-series model to pursue complicated research purposes, their resulting model is relatively simple to specify, to run, and to interpret. These advantages make the adoption of their model relatively effortless as long as researchers have the basic knowledge and skills in working with multilevel growth modeling. With multiple potential extensions of their model, the establishment of this analytical platform for analysis of multiple sets of time series can inspire researchers to pursue far more advanced research designs to address complex developmental processes in reality. PMID:29881094

Machine Learning-Augmented Propensity Score-Adjusted Multilevel Mixed Effects Panel Analysis of Hands-On Cooking and Nutrition Education versus Traditional Curriculum for Medical Students as Preventive Cardiology: Multisite Cohort Study of 3,248 Trainees over 5 Years

PubMed Central

Dart, Lyn; Vanbeber, Anne; Smith-Barbaro, Peggy; Costilla, Vanessa; Samuel, Charlotte; Terregino, Carol A.; Abali, Emine Ercikan; Dollinger, Beth; Baumgartner, Nicole; Kramer, Nicholas; Seelochan, Alex; Taher, Sabira; Deutchman, Mark; Evans, Meredith; Ellis, Robert B.; Oyola, Sonia; Maker-Clark, Geeta; Budnick, Isadore; Tran, David; DeValle, Nicole; Shepard, Rachel; Chow, Erika; Petrin, Christine; Razavi, Alexander; McGowan, Casey; Grant, Austin; Bird, Mackenzie; Carry, Connor; McGowan, Glynis; McCullough, Colleen; Berman, Casey M.; Dotson, Kerri; Sarris, Leah; Harlan, Timothy S.; Co-investigators, on behalf of the CHOP

2018-01-01

Background Cardiovascular disease (CVD) annually claims more lives and costs more dollars than any other disease globally amid widening health disparities, despite the known significant reductions in this burden by low cost dietary changes. The world's first medical school-based teaching kitchen therefore launched CHOP-Medical Students as the largest known multisite cohort study of hands-on cooking and nutrition education versus traditional curriculum for medical students. Methods This analysis provides a novel integration of artificial intelligence-based machine learning (ML) with causal inference statistics. 43 ML automated algorithms were tested, with the top performer compared to triply robust propensity score-adjusted multilevel mixed effects regression panel analysis of longitudinal data. Inverse-variance weighted fixed effects meta-analysis pooled the individual estimates for competencies. Results 3,248 unique medical trainees met study criteria from 20 medical schools nationally from August 1, 2012, to June 26, 2017, generating 4,026 completed validated surveys. ML analysis produced similar results to the causal inference statistics based on root mean squared error and accuracy. Hands-on cooking and nutrition education compared to traditional medical school curriculum significantly improved student competencies (OR 2.14, 95% CI 2.00–2.28, p < 0.001) and MedDiet adherence (OR 1.40, 95% CI 1.07–1.84, p = 0.015), while reducing trainees' soft drink consumption (OR 0.56, 95% CI 0.37–0.85, p = 0.007). Overall improved competencies were demonstrated from the initial study site through the scale-up of the intervention to 10 sites nationally (p < 0.001). Discussion This study provides the first machine learning-augmented causal inference analysis of a multisite cohort showing hands-on cooking and nutrition education for medical trainees improves their competencies counseling patients on nutrition, while improving students' own diets. This study suggests that the public health and medical sectors can unite population health management and precision medicine for a sustainable model of next-generation health systems providing effective, equitable, accessible care beginning with reversing the CVD epidemic. PMID:29850526

Machine Learning-Augmented Propensity Score-Adjusted Multilevel Mixed Effects Panel Analysis of Hands-On Cooking and Nutrition Education versus Traditional Curriculum for Medical Students as Preventive Cardiology: Multisite Cohort Study of 3,248 Trainees over 5 Years.

PubMed

Monlezun, Dominique J; Dart, Lyn; Vanbeber, Anne; Smith-Barbaro, Peggy; Costilla, Vanessa; Samuel, Charlotte; Terregino, Carol A; Abali, Emine Ercikan; Dollinger, Beth; Baumgartner, Nicole; Kramer, Nicholas; Seelochan, Alex; Taher, Sabira; Deutchman, Mark; Evans, Meredith; Ellis, Robert B; Oyola, Sonia; Maker-Clark, Geeta; Dreibelbis, Tomi; Budnick, Isadore; Tran, David; DeValle, Nicole; Shepard, Rachel; Chow, Erika; Petrin, Christine; Razavi, Alexander; McGowan, Casey; Grant, Austin; Bird, Mackenzie; Carry, Connor; McGowan, Glynis; McCullough, Colleen; Berman, Casey M; Dotson, Kerri; Niu, Tianhua; Sarris, Leah; Harlan, Timothy S; Co-Investigators, On Behalf Of The Chop

2018-01-01

Cardiovascular disease (CVD) annually claims more lives and costs more dollars than any other disease globally amid widening health disparities, despite the known significant reductions in this burden by low cost dietary changes. The world's first medical school-based teaching kitchen therefore launched CHOP-Medical Students as the largest known multisite cohort study of hands-on cooking and nutrition education versus traditional curriculum for medical students. This analysis provides a novel integration of artificial intelligence-based machine learning (ML) with causal inference statistics. 43 ML automated algorithms were tested, with the top performer compared to triply robust propensity score-adjusted multilevel mixed effects regression panel analysis of longitudinal data. Inverse-variance weighted fixed effects meta-analysis pooled the individual estimates for competencies. 3,248 unique medical trainees met study criteria from 20 medical schools nationally from August 1, 2012, to June 26, 2017, generating 4,026 completed validated surveys. ML analysis produced similar results to the causal inference statistics based on root mean squared error and accuracy. Hands-on cooking and nutrition education compared to traditional medical school curriculum significantly improved student competencies (OR 2.14, 95% CI 2.00-2.28, p < 0.001) and MedDiet adherence (OR 1.40, 95% CI 1.07-1.84, p = 0.015), while reducing trainees' soft drink consumption (OR 0.56, 95% CI 0.37-0.85, p = 0.007). Overall improved competencies were demonstrated from the initial study site through the scale-up of the intervention to 10 sites nationally ( p < 0.001). This study provides the first machine learning-augmented causal inference analysis of a multisite cohort showing hands-on cooking and nutrition education for medical trainees improves their competencies counseling patients on nutrition, while improving students' own diets. This study suggests that the public health and medical sectors can unite population health management and precision medicine for a sustainable model of next-generation health systems providing effective, equitable, accessible care beginning with reversing the CVD epidemic.

Multi-level significance of vulnerability indicators. Case study: Eastern Romania

NASA Astrophysics Data System (ADS)

Stanga, I. C.; Grozavu, A.

2012-04-01

Vulnerability assessment aims, most frequently, to emphasize internal fragility of a system comparing to a reference standard, to similar systems or in relation to a given hazard. Internal fragility, either biophysical or structural, may affect the capacity to predict, to prepare for, to cope with or to recover from a disaster. Thus, vulnerability is linked to resilience and adaptive capacity. From local level to global one, vulnerability factors and corresponding indicators are different and their significance must be tested and validated in a well-structured conceptual and methodological framework. In this paper, the authors aim to show the real vulnerability of rural settlements in Eastern Romania in a multi-level approach. The research area, Tutova Hills, counts about 3421 sq.km and more than 200.000 inhabitants in 421 villages characterized by deficient accessibility, lack of endowments, subsistential agriculture, high pressure on natural environment (especially on forest and soil resources), poverty and aging process of population. Factors that could influence the vulnerability of these rural settlements have been inventoried and assigned into groups through a cluster analysis: habitat and technical urban facilities, infrastructure, economical, social and demographical indicators, environment quality, management of emergency situations etc. Firstly, the main difficulty was to convert qualitative variable in quantitative indicators and to standardize all values to make possible mathematical and statistical processing of data. Secondly, the great variability of vulnerability factors, their different measuring units and their high amplitude of variation require different method of standardization in order to obtain values between zero (minimum vulnerability) and one (maximum vulnerability). Final vulnerability indicators were selected and integrated in a general scheme, according to their significance resulted from an appropriate factor analysis: linear and logistic regression, varimax rotation, multiple-criteria decision analysis, weight of evidence, multi-criteria evaluation method etc. The approach started from the local level which allows a functional and structural analysis and was progressively translated to an upper level and to a spatial analysis. The model shows that changing the level of analysis diminishes the functional significance of some indicators and increases the capacity of discretization in the case of others, highlighting the spatial and functional complexity of vulnerability.

Patterns of attachment and parents' adjustment to the death of their child.

PubMed

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

2007-04-01

The impact of adult attachment on psychological adjustment among bereaved parents and the mediating effect of relationship satisfaction were examined among a sample of 219 couples of parents. Data collection took place 6, 13, and 20 months after loss. Use of the actor partner interdependence model in multilevel regression analysis enabled exploration of both individual as well as partner attachment as predictors of grief and depression. Results indicated that the more insecurely attached parents were (on both avoidance and anxiety attachment), the higher the symptoms of grief and depression. Neither the attachment pattern of the partner nor similarity of attachment within the couple had any influence on psychological adjustment of the parent. Marital satisfaction partially mediated the association of anxious attachment with symptomatology. Contrary to previous research findings, avoidant attachment was associated with high grief intensity. These findings challenge the notion that the avoidantly attached are resilient.

National income and environmental concern: Observations from 35 countries.

PubMed

Lo, Alex Y

2016-10-01

National income produces mixed impacts on public environmental concern. In a cross-national survey, environmental concern was measured in terms of propensity to act and environmental risk perception. Results of a multilevel regression analysis show that these two measures respond to gross domestic product per capita in opposite ways. Citizens of advanced industrial countries are more likely than those of lower-income countries to contribute to environmental protection. However, they are less likely to see the harmful impacts on the environment as very dangerous. Using an indicator of national adaptive capacity, this article demonstrates that environmental risk perception is a function of a country's estimated capacity for coping with condition changes. The stronger sense of collective security among citizens of wealthier nations offers a possible explanation for the negative effects of national income. These results indicate the complex relationship between development and public environmental concern across countries. © The Author(s) 2015.

Comparing relative effects of education and economic resources on infant mortality in developing countries.

PubMed

Pamuk, Elsie R; Fuchs, Regina; Lutz, Wolfgang

2011-01-01

Research on the social determinants of health has often considered education and economic resources as separate indicators of socioeconomic status. From a policy perspective, however, it is important to understand the relative strength of the effect of these social factors on health outcomes, particularly in developing countries. It is also important to examine not only the impact of education and economic resources of individuals, but also whether community and country levels of these factors affect health outcomes. This analysis uses multilevel regression models to assess the relative effects of education and economic resources on infant mortality at the family, community, and country level using data from demographic and Health Surveys in 43 low-and lower-middle-income countries. We find strong effects for both per capita gross national income and completed secondary education at the country level, but a greater impact of education within families and communities.

Collective-efficacy as a mediator of the relationship of leaders' personality traits and team performance: A cross-level analysis.

PubMed

Li, Xiaoshan; Zhou, Mingjie; Zhao, Na; Zhang, Shanshan; Zhang, Jianxin

2015-06-01

The relationship between a leader's personality and his team's performance has been established in organisational research, but the underlying process and mechanism responsible for this effect have not been fully explored. Both the traditional multiple linear regression and the multilevel structural equation model approaches were used in this study to test a proposed mediating model of subordinates' perception of collective efficacy between leader personality and team performance. The results show that the team leader's extraversion and conscientiousness personality traits were related positively to both the team-average (individual) perception of collective efficacy and team performance, and the collective efficacy mediated the relationship of the leader's personality traits and team performance. This study also discusses how Chinese cultural elements play a role in such a mediating model. © 2014 International Union of Psychological Science.

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.

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.

International students' enrollment in IPTA by using multilevel analysis

NASA Astrophysics Data System (ADS)

Wai, Phoong Seuk; Ismail, Mohd Tahir; Karim, Samsul Ariffin Abdul

2012-09-01

The increases of demand on knowledge-based and production-based market force the growth of higher education. International students' enrollment contributes to economic growth and increase country's income, university reputation and name; promote the competitive of education and training markets. This paper used multilevel analysis to study the international students' enrollment in Malaysia public university. Student's background variables and institution background variables were study in this paper and the relationship among them also been investigated. Result shows that institution type is a significance factor on international students' enrollment in Malaysia public university.

Image-based Multilevel Subdivision of M1 Category in TNM Staging System for Metastatic Nasopharyngeal Carcinoma.

PubMed

Shen, Lujun; Li, Wang; Wang, Siyang; Xie, Guofeng; Zeng, Qi; Chen, Chen; Shi, Feng; Zhang, Ying; Wu, Ming; Shu, Wanhong; Pan, Changchuan; Xia, Yunfei; Wu, Peihong

2016-09-01

Purpose To establish an image-based M1 category subdivision system for personalized prognosis prediction and treatment planning in patients with metastatic nasopharyngeal carcinoma (NPC). Materials and Methods A total of 1172 patients with metachronous metastasic NPC were retrospectively enrolled (the dataset is from Sun Yat-sen University Cancer Center for derivation, and the combined datasets are from Guangzhou Medical University Cancer Center and the Fifth Affiliated Hospital of Sun Yat-sen University for validation). The Ethics Committee of the three centers approved this study. A general subdivision system of the M1 category was established on the basis of the most influential metastatic features for overall survival (OS). The following multilevel subdivision system for precise subdivision of the M1 category was designed: M [number of locations]-Location [number of lesions], with B indicating bone, L indicating the lung, H indicating the liver, and N indicating a node. The correlation of the M1 subdivisions with OS was determined with Cox regression. The best treatment response was assessed with Response Evaluation Criteria in Solid Tumors 1.1 guidelines and modified Response Evaluation Criteria in Solid Tumors criteria. Results Multivariate analysis in the derivation cohort showed that the number of metastatic lesions (multiple or single), the number of metastatic locations (multiple or single), liver involvement, and bone involvement were independent prognostic factors for OS. In general, subdividing the cohort by the number of metastatic lesions and the number of metastatic locations resulted in three subcategories of differential OS: M1a, a single lesion in a single organ or location; M1b, multiple lesions in a single organ or location; and M1c, metastases in multiple locations (for M1b vs M1a, hazard ratio [HR] = 2.28, 95% confidence interval [CI]: 1.71, 3.05; for M1c vs M1a, HR = 3.65, 95% CI: 2.75, 4.85); these subdivisions were externally validated. The multilevel subdivision system could be further used to discriminate among subgroups of differential OS under the M1b subcategory. Findings from analysis of multilevel subgroups suggested that patients with a single metastatic lesion (M1-B1, M1-L1, M1-H1, M1-N1) or two lesions in the liver only (M1-H2) had high rates of complete response (CR) or complete surgical resection (CSR) and 3-year OS after treatment (CR plus CSR rates >30%, and 3-year OS rates >50%); there were high 3-year OS rates (>50%) in patients with stage M1-B2, M1-L2, or M1-H3 disease but relatively low rates of CR or CSR. Conclusion Use of the multilevel M1 subdivision system in patients with NPC could facilitate more precise prognosis prediction and better identification of patients who will respond well to treatment than the conventional subdivision strategy. (©) RSNA, 2016 Online supplemental material is available for this article.

Exploring alternate specifications to explain agency-level effects in placement decisions regarding aboriginal children: further analysis of the Canadian Incidence Study of Reported Child Abuse and Neglect Part B.

PubMed

Chabot, Martin; Fallon, Barbara; Tonmyr, Lil; MacLaurin, Bruce; Fluke, John; Blackstock, Cindy

2013-01-01

This paper builds upon the analyses presented in two companion papers (Fluke et al., 2010; Fallon et al., 2013) using data from the 1998 and 2003 cycles of the Canadian Incidence Study of Reported Child Abuse and Neglect (CIS-1998 and CIS-2003) to examine the influence of clinical and organizational characteristics on the decision to place a child in out-of-home care at the conclusion of a child maltreatment investigation. This paper explores various model specifications to explain the effect of an agency-level factor, proportion of Aboriginal reports, which emerged as a stable and significant factor through the two data collection cycles. It addresses the issue of data comparability between the two cycles and explores various re-specifications and descriptive analyses of reported models to evaluate their solidity with regards to the sampling schemes and the precise contribution of a multi-level specification. The decision to place a child in out-of-home care was examined using data from the CIS-2003. This child welfare dataset collected information about the results of nearly 12,000 child maltreatment investigations as well as a description of the characteristics of the workers and organization responsible for conducting those investigations. Multi-level statistical models were developed using MPlus software, which can accommodate dichotomous outcome variables and are more reflective of decision-making in child welfare. The models are thus multi-level binary logistic regressions. Final models revealed that two agency-level variables, 'Education degree of majority of workers' and 'Degree of centralization in the agency' clarify the nature of the effect of 'Proportion of Aboriginal reports', a stable, key second level predictor of the placement decision. The comparability of the effect of this agency-level variable across the 1998 and 2003 cycles becomes further evident through this analysis. By using a unified database including both cycles and various specifications of models, the comparability was found to be robust, in addition to clarifying the precise contribution of a multi-level specification. This third paper in a series establishes the 'Proportion of Aboriginal reports' received by the child welfare agency as an important agency level predictor associated with a child's likelihood of being placed in the Canadian child protection system. While the more complex models give support to the notion that unequal resources subtend those results, more analyses are needed to confirm this hypothesis. Unequal resources for agencies with larger Aboriginal caseloads may explain the persistence of the results. These findings suggest that specific resource constraints related to worker education may be explanatory. Copyright © 2012 Elsevier Ltd. All rights reserved.

Multilevel evaluation of 'China Healthy Lifestyles for All', a nationwide initiative to promote lower intakes of salt and edible oil.

PubMed

Zhang, Juan; Astell-Burt, Thomas; Seo, Dong-Chul; Feng, Xiaoqi; Kong, Lingzhi; Zhao, Wenhua; Li, Nicole; Li, Yuan; Yu, Shicheng; Feng, Guoshuang; Ren, Duofu; Lv, Yuebin; Wang, Jinglei; Shi, Xiaoming; Liang, Xiaofeng; Chen, Chunming

2014-10-01

To evaluate the impact of 'China Healthy Lifestyle for All' on levels of knowledge, taste and intentions to modify future consumption of salt and edible oil. Between May and August 2012, a face-to-face survey carried out in all 31 provinces, autonomous regions, and municipalities in mainland China, achieved a 98.1% response. Intention-To-Treat analysis via multilevel logistic regression was used to examine differences in outcomes between 31,396 non-institutionalised individuals aged > 18 years from 31 'intervention' (i.e. participating) and 26 'control' (i.e. non-participating) counties respectively. Adjusting for socioeconomic confounders, participants in 'intervention' counties were more likely to know the limit of salt (Odds Ratio 3.14, 95% Confidence Interval (95% CI) 1.98, 4.96) and oil consumption (3.67, 95% CI 2.31, 5.82), and were more intent to modify their consumption (salt 1.98, 95% CI 1.41, 2.76; oil OR 1.99, 95% CI 1.41, 2.81) and to report a change in taste (salt 1.90, 95% CI 1.31, 2.75; oil 2.07, 95% CI 1.38, 3.10). 'Intervention' effects were consistent regardless of income or education, but women and older participants benefited disproportionately. Outcomes were 2.8 and 4.7 times more likely among those with better recall. Place-based health promotion interventions have an important role to play in addressing non-communicable disease in China. Copyright © 2014 Elsevier Inc. All rights reserved.

Both trait and state mindfulness predict lower aggressiveness via anger rumination: A multilevel mediation analysis

PubMed Central

Eisenlohr-Moul, Tory A.; Peters, Jessica R.; Pond, Richard S.; DeWall, C. Nathan

2016-01-01

Trait mindfulness, or the capacity for nonjudgmental, present-centered attention, predicts lower aggression in cross-sectional samples, an effect mediated by reduced anger rumination. Experimental work also implicates state mindfulness (i.e., fluctuations around one's typical mindfulness) in aggression. Despite evidence that both trait and state mindfulness predict lower aggression, their relative impact and their mechanisms remain unclear. Higher trait mindfulness and state increases in mindfulness facets may reduce aggression-related outcomes by (1) limiting the intensity of anger, or (2) limiting rumination on anger experiences. The present study tests two hypotheses: First, that both trait and state mindfulness contribute unique variance to lower aggressiveness, and second, that the impact of both trait and state mindfulness on aggressiveness will be uniquely partially mediated by both anger intensity and anger rumination. 86 participants completed trait measures of mindfulness, anger intensity, and anger rumination, then completed diaries for 35 days assessing mindfulness, anger intensity, anger rumination, anger expression, and self-reported and behavioral aggressiveness. Using multilevel zero-inflated regression, we examined unique contributions of trait and state mindfulness facets to daily anger expression and aggressiveness. We also examined the mediating roles of anger intensity and anger rumination at both trait and state levels. Mindfulness facets predicted anger expression and aggressiveness indirectly through anger rumination after controlling for indirect pathways through anger intensity. Individuals with high or fluctuating aggression may benefit from mindfulness training to reduce both intensity of and rumination on anger. PMID:27429667

Contextual and individual determinants of periodontal disease: Multilevel analysis based on Andersen's model.

PubMed

Valente, Maria I B; Vettore, Mario V

2018-04-01

To investigate the relationship of contextual and individual factors with periodontal disease in dentate adults and older people using the Andersen's behavioural model. Secondary individual data from 6011 adults and 2369 older people from the Brazilian Oral Health Survey (2010) were combined with contextual data for 27 cities. Attachment loss (AL) categories for each sextant were coded and summed to obtain the periodontal disease measure. The association of predisposing, enabling and need characteristics at city and individual level with periodontal disease was assessed using an adapted version of the Andersen's behavioural model. Multilevel Poisson regression was used to estimate rate ratios (RR) and 95% CIs. Periodontal disease was associated with contextual predisposing (RR 0.93; 95% CI = 0.87-0.99) and enabling factors (RR 0.99; 95% CI = 0.98-0.99) in adults. Contextual predisposing was also associated with periodontal disease in older people (RR 0.82; 95% CI = 0.73-0.92). Individual predisposing (age, sex and schooling) and need characteristics (perceived treatment need) were common predictors of periodontal disease in adults and older people. Periodontal disease was also associated with behaviours in the latter age group. Contextual predisposing factors and individual characteristics influenced periodontal disease experience in adults and older people. Contextual enabling factors were also meaningful determinants of periodontal disease in the former age group. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Community Influences on Married Women's Safer Sex Negotiation Attitudes in Bangladesh: A Multilevel Analysis.

PubMed

Jesmin, Syeda S; Cready, Cynthia M

2016-02-01

The influence of disadvantaged or deprived community on individuals' health risk-behaviors is increasingly being documented in a growing body of literature. However, little is known about the effects of community characteristics on women's sexual attitudes and behaviors. To examine community effects on married women's safer sex negotiation attitudes, we analyzed cross-sectional data from the 2011 Bangladesh Demographic and Health Surveys on a sample of 15,134 married women in 600 communities. We estimated two multilevel logistic regression models. Model 1, which included only individual-level variables, showed that women's autonomy/empowerment, age, and HIV knowledge had significant associations with their safer sex negotiation attitudes. We did not find any socioeconomic status gradient in safer sex negotiation attitudes at the individual level. Adding community-level variables in Model 2 significantly improved the fit of the model. Strikingly, we found that higher community-level poverty was associated with greater positive safer sex negotiation attitudes. Prevailing gender norms and overall women's empowerment in the community also had significant effects. While research on community influences calls for focusing on disadvantaged communities, our research highlights the importance of not underestimating the challenges that married women in economically privileged communities may face in negotiating safer sex. To have sufficient and equitable impact on married women's sexual and reproductive health, sexual and reproductive health promotion policies and programs need to be directed to women in wealthier communities as well.

Associations Between Peer Network Gender Norms and the Perpetration of Intimate Partner Violence Among Urban Tanzanian Men: a Multilevel Analysis.

PubMed

Mulawa, Marta I; Reyes, H Luz McNaughton; Foshee, Vangie A; Halpern, Carolyn T; Martin, Sandra L; Kajula, Lusajo J; Maman, Suzanne

2018-05-01

Male perpetration of intimate partner violence (IPV) against women in sub-Saharan Africa is widespread. Theory and empirical evidence suggest peer networks may play an important role in shaping IPV perpetration, though research on this topic in the region is limited. We assessed the degree to which peer network gender norms are associated with Tanzanian men's perpetration of IPV and examined whether the social cohesion of peer networks moderates this relationship. Using baseline data from sexually active men (n = 1103) nested within 59 peer networks enrolled in an on-going cluster-randomized HIV and IPV prevention trial, we fit multilevel logistic regression models to examine peer network-level factors associated with past-year physical IPV perpetration. Peer network gender norms were significantly associated with men's risk of perpetrating IPV, even after adjusting for their own attitudes toward gender roles (OR = 1.53 , p =  . 04). Peer network social cohesion moderated this relationship (OR = 1.50 , p =  . 04); the positive relationship between increasingly inequitable (i.e., traditional) peer network gender norms and men's risk of perpetrating IPV became stronger, as peer network social cohesion increased. Characteristics of the peer network context are associated with men's IPV perpetration and should be targeted in future interventions. While many IPV prevention interventions focus on changing individual attitudes, our findings support a unique approach, focused on transforming the peer context.

Individual and neighbourhood determinants of social participation and social capital: a multilevel analysis of the city of Malmö, Sweden.

PubMed

Lindström, Martin; Merlo, Juan; Ostergren, Per-Olof

2002-06-01

The aim of this study was to analyse the impact of neighbourhood on individual social capital (measured as social participation). The study population consisted of 14,390 individuals aged 45-73 that participated in the Malmö diet and cancer study in 1992-1994, residing in 90 neighbourhoods of Malmö, Sweden (population 250,000). A multilevel logistic regression model, with individuals at the first level and neighbourhoods at the second level, was performed. The study analysed the effect (intra-area correlation and cross-level modification) of the neighbourhood on individual social capital after adjustment for compositional factors (e.g. age, sex, educational level, occupational status, disability pension, living alone, sick leave, unemployment) and, finally, one contextual migration factor. The prevalence of low social participation varied from 23.0% to 39.7% in the first and third neighbourhood quartiles, respectively. Neighbourhood factors accounted for 6.3% of the total variance in social participation, and this effect was reduced but not eliminated when adjusting for all studied variables (-73%), especially the occupational composition of the neighbourhoods (-58%). The contextual migration variable further reduced the variance in social participation at the neighbourhood level to some extent. Our study supports Putnam's notion that social capital, which is suggested to be an important factor for population health and possibly for health equity, is an aspect that is partly contextual in its nature.

Interest in health screening as a predictor of long-term overall mortality: multilevel analysis of a Japanese national cohort study.

PubMed

Fujino, Yoshihisa; Tanabe, Naohito; Honjo, Kaori; Suzuki, Sadao; Iso, Hiroyasu; Tamakoshi, Akiko

2011-01-01

In Japan, screening programmes have been widely implemented as a public health practice. We investigated the effect of the area-level interest in health screening on mortality using data from a large cohort in Japan. A baseline survey was conducted between 1988 and 1990 among 110,792 residents of 45 areas, aged 40-79 years. Area-level interest in health screening was defined as the proportion of people with high and moderate interest in health screening in an area. Multilevel Poisson regression was employed in a two-level structure of individuals nested within the areas. During 15 years of follow-up (1,035,617 person-years), 13,184 deaths were observed. The reduction in mortality rate was (a) 2% in both men (p=0.009) and women (p=0.038) for each percent increase in area-level interest in screening, and (b) 10% in men (p=0.001) and 9% in women (p=0.001) for individual attendance to screening in the year before follow-up. There was no interaction between area-level interest in screening, individual-level attendance at screening and overall mortality. Area-level and individual interest for health screening appear to be independent predictor of 15-year mortality in this national Japanese study. The present findings may support public health practices to promote knowledge and participation in screening programmes. Copyright © 2010 Elsevier Inc. All rights reserved.

The gender gap in self-rated health and education in Spain. A multilevel analysis.

PubMed

Pinillos-Franco, Sara; García-Prieto, Carmen

2017-01-01

Women tend to report poorer self-rated health than men. It is also well established that education has a positive effect on health. However, the issue of how the benefits of education on health differ between men and women has not received enough attention and the few existing studies which do focus on the subject do not draw a clear conclusion. Therefore, this study aims to analyse whether the positive influence of educational attainment on health is higher for women and whether education helps to overcome the gender gap in self-rated health. We analyse cross-sectional data from the 2012 European Union statistics on income and living conditions. We use a logit regression model with odds ratios and a multilevel perspective to carry out a study which includes several individual and contextual control variables. We focused our study on the working population in Spain aged between 25 and 65. The final sample considered is composed of 14,120 subjects: 7,653 men and 6,467 women. There is a gender gap in self-rated health only for the less educated. This gap is not statistically significant among more highly educated individuals. Attaining a high level of education has the same positive effect on both women's and men's self-rated health. Although we did not find gender disparities when considering the effect of education on health, we show that women's health is poorer among the less educated, mainly due to labour precariousness and household conditions.

Spousal Violence in 5 Transitional Countries: A Population-Based Multilevel Analysis of Individual and Contextual Factors

PubMed Central

2015-01-01

Objectives. I examined the individual- and community-level factors associated with spousal violence in post-Soviet countries. Methods. I used population-based data from the Demographic and Health Survey conducted between 2005 and 2012. My sample included currently married women of reproductive age (n = 3932 in Azerbaijan, n = 4053 in Moldova, n = 1932 in Ukraine, n = 4361 in Kyrgyzstan, and n = 4093 in Tajikistan). I selected respondents using stratified multistage cluster sampling. Because of the nested structure of the data, multilevel logistic regressions for survey data were fitted to examine factors associated with spousal violence in the last 12 months. Results. Partner’s problem drinking was the strongest risk factor associated with spousal violence in all 5 countries. In Moldova, Ukraine, and Kyrgyzstan, women with greater financial power than their spouses were more likely to experience violence. Effects of community economic deprivation and of empowerment status of women in the community on spousal violence differed across countries. Women living in communities with a high tolerance of violence faced a higher risk of spousal violence in Moldova and Ukraine. In more traditional countries (Azerbaijan, Kyrgyzstan, and Tajikistan), spousal violence was lower in conservative communities with patriarchal gender beliefs or higher financial dependency on husbands. Conclusions. My findings underscore the importance of examining individual risk factors in the context of community-level factors and developing individual- and community-level interventions. PMID:26378858

Assessment of Material Solutions of Multi-level Garage Structure Within Integrated Life Cycle Design Process

NASA Astrophysics Data System (ADS)

Wałach, Daniel; Sagan, Joanna; Gicala, Magdalena

2017-10-01

The paper presents an environmental and economic analysis of the material solutions of multi-level garage. The construction project approach considered reinforced concrete structure under conditions of use of ordinary concrete and high-performance concrete (HPC). Using of HPC allowed to significant reduction of reinforcement steel, mainly in compression elements (columns) in the construction of the object. The analysis includes elements of the methodology of integrated lice cycle design (ILCD). By making multi-criteria analysis based on established weight of the economic and environmental parameters, three solutions have been evaluated and compared within phase of material production (information modules A1-A3).

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

PubMed

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

2016-12-01

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

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

PubMed Central

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

2015-01-01

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

Level and Change of Bullying Behavior during High School: A Multilevel Growth Curve Analysis

ERIC Educational Resources Information Center

Nocentini, Annalaura; Menesini, Ersilia; Salmivalli, Christina

2013-01-01

The development of bullying behavior was examined across three years in a sample of 515 adolescents (46% females) from 41 classrooms. At time 1, the students were in grades 9 and 10 (mean age = 14.5 years; SD = 0.54). Results of a multilevel growth model showed that both baseline level and change of bullying varied significantly across individuals…

Psychosocial Working Conditions, School Sense of Coherence and Subjective Health Complaints. A Multilevel Analysis of Ninth Grade Pupils in the Stockholm Area

ERIC Educational Resources Information Center

Modin, Bitte; Ostberg, Viveca; Toivanen, Susanna; Sundell, Knut

2011-01-01

This study explores the psychosocial working conditions of 7930 Swedish 9th grade students, distributed over 475 classes and 130 schools, in relation to their subjective health using multilevel modeling. At the individual level, students with "strained" working conditions in school (i.e. those experiencing a high level of demands in…

A Multilevel Analysis of Diverse Learners Playing Life Science Video Games: Interactions between Game Content, Learning Disability Status, Reading Proficiency, and Gender

ERIC Educational Resources Information Center

Israel, Maya; Wang, Shuai; Marino, Matthew T.

2016-01-01

Extant research reports differential effects related to the efficacy of video games as a means to enhance science instruction. However, there are very few studies examining differences in learning outcomes across student-level independent variables. This study used multilevel modeling to examine the effects of three video game-enhanced life…

National and School Policies on Restrictions of Teacher Smoking: A Multilevel Analysis of Student Exposure to Teacher Smoking in Seven European Countries

ERIC Educational Resources Information Center

Wold, Bente; Torsheim, Torbjorn; Currie, Candace; Roberts, Chris

2004-01-01

The paper examines the association between restrictions on teacher tobacco smoking at school and student exposure to teachers who smoke during school hours. The data are taken from a European Commission-funded study "Control of Adolescent Smoking" (the CAS study) in seven European countries. Multilevel modelling analyses were applied to…

Equity in the Turkish Education System: A Multilevel Analysis of Social Background Influences on the Mathematics Performance of 15-Year-Old Students

ERIC Educational Resources Information Center

Özdemir, Caner

2016-01-01

This paper aims to discover the level of equity in the Turkish education system using maths outcomes of 15-year-old students in the Programme for International Student Assessment (PISA) exam. In order to do that, associations between various social background variables and student performance are analysed via multilevel models. Female pupils,…

Trade liberalization and tuberculosis incidence: a longitudinal multi-level analysis in 22 high burden countries between 1990 and 2010

PubMed Central

Bozorgmehr, Kayvan; San Sebastian, Miguel

2014-01-01

Background Trade liberalization is promoted by the World Trade Organization (WTO) through a complex architecture of binding trade agreements. This type of trade, however, has the potential to modify the upstream and proximate determinants of tuberculosis (TB) infection. We aimed to analyse the association between trade liberalization and TB incidence in 22 high-burden TB countries between 1990 and 2010. Methods and findings A longitudinal multi-level linear regression analysis was performed using five different measures of trade liberalization as exposure [WTO membership, duration of membership, trade as % of gross domestic product, and components of both the Economic Freedom of the World Index (EFI4) and the KOF Index of Globalization (KOF1)]. We adjusted for a wide range of factors, including differences in human development index (HDI), income inequality, debts, polity patterns, conflict, overcrowding, population stage transition, health system financing, case detection rates and HIV prevalence. None of the five trade indicators was significantly associated with TB incidence in the crude analysis. Any positive effect of EFI4 on (Log-) TB incidence over time was confounded by differences in socio-economic development (HDI), HIV prevalence and health financing indicators. The adjusted TB incidence rate ratio of WTO member countries was significantly higher [RR: 1.60; 95% confidence interval (CI): 1.12–2.29] when compared with non-member countries. Conclusion We found no association between specific aggregate indicators of trade liberalization and TB incidence. Our analyses provide evidence of a significant association between WTO membership and higher TB incidence, which suggests a possible conflict between the architecture of WTO agreements and TB-related Millennium Development Goals. Further research is needed, particularly on the relation between the aggregate trade indices used in this study and the hypothesized mediators and also on sector-specific indices, specific trade agreements and other (non-TB) health outcomes. PMID:23595571

Trade liberalization and tuberculosis incidence: a longitudinal multi-level analysis in 22 high burden countries between 1990 and 2010.

PubMed

Bozorgmehr, Kayvan; San Sebastian, Miguel

2014-05-01

Trade liberalization is promoted by the World Trade Organization (WTO) through a complex architecture of binding trade agreements. This type of trade, however, has the potential to modify the upstream and proximate determinants of tuberculosis (TB) infection. We aimed to analyse the association between trade liberalization and TB incidence in 22 high-burden TB countries between 1990 and 2010. and findings A longitudinal multi-level linear regression analysis was performed using five different measures of trade liberalization as exposure [WTO membership, duration of membership, trade as % of gross domestic product, and components of both the Economic Freedom of the World Index (EFI4) and the KOF Index of Globalization (KOF1)]. We adjusted for a wide range of factors, including differences in human development index (HDI), income inequality, debts, polity patterns, conflict, overcrowding, population stage transition, health system financing, case detection rates and HIV prevalence. None of the five trade indicators was significantly associated with TB incidence in the crude analysis. Any positive effect of EFI4 on (Log-) TB incidence over time was confounded by differences in socio-economic development (HDI), HIV prevalence and health financing indicators. The adjusted TB incidence rate ratio of WTO member countries was significantly higher [RR: 1.60; 95% confidence interval (CI): 1.12-2.29] when compared with non-member countries. We found no association between specific aggregate indicators of trade liberalization and TB incidence. Our analyses provide evidence of a significant association between WTO membership and higher TB incidence, which suggests a possible conflict between the architecture of WTO agreements and TB-related Millennium Development Goals. Further research is needed, particularly on the relation between the aggregate trade indices used in this study and the hypothesized mediators and also on sector-specific indices, specific trade agreements and other (non-TB) health outcomes.

Structural synthesis: Precursor and catalyst

NASA Technical Reports Server (NTRS)

Schmit, L. A.

1984-01-01

More than twenty five years have elapsed since it was recognized that a rather general class of structural design optimization tasks could be properly posed as an inequality constrained minimization problem. It is suggested that, independent of primary discipline area, it will be useful to think about: (1) posing design problems in terms of an objective function and inequality constraints; (2) generating design oriented approximate analysis methods (giving special attention to behavior sensitivity analysis); (3) distinguishing between decisions that lead to an analysis model and those that lead to a design model; (4) finding ways to generate a sequence of approximate design optimization problems that capture the essential characteristics of the primary problem, while still having an explicit algebraic form that is matched to one or more of the established optimization algorithms; (5) examining the potential of optimum design sensitivity analysis to facilitate quantitative trade-off studies as well as participation in multilevel design activities. It should be kept in mind that multilevel methods are inherently well suited to a parallel mode of operation in computer terms or to a division of labor between task groups in organizational terms. Based on structural experience with multilevel methods general guidelines are suggested.