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Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/59009
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dc.creatorMaria Fonsecapt_BR
dc.creatorEstela Aquinopt_BR
dc.creatorDóra Chorpt_BR
dc.creatorLeidjaira Juvanholpt_BR
dc.creatorLúcia Rotenbergpt_BR
dc.creatorAline Nobrept_BR
dc.creatorRosane Grieppt_BR
dc.creatorMárcia Alvespt_BR
dc.creatorLetícia Cardosopt_BR
dc.creatorLuana Giatti Gonçalvespt_BR
dc.creatorMaria Nunespt_BR
dc.date.accessioned2023-09-28T20:55:52Z-
dc.date.available2023-09-28T20:55:52Z-
dc.date.issued2017-11-17-
dc.citation.volume14pt_BR
dc.citation.issue1404pt_BR
dc.citation.spage1pt_BR
dc.citation.epage13pt_BR
dc.identifier.doi10.3390/ijerph14111404pt_BR
dc.identifier.issn16604601pt_BR
dc.identifier.urihttp://hdl.handle.net/1843/59009-
dc.description.resumoThis paper explores the association between job strain and adiposity, using two statistical analysis approaches and considering the role of gender. The research evaluated 11,960 active baseline participants (2008–2010) in the ELSA-Brasil study. Job strain was evaluated through a demand–control questionnaire, while body mass index (BMI) and waist circumference (WC) were evaluated in continuous form. The associations were estimated using gamma regression models with an identity link function. Quantile regression models were also estimated from the final set of co-variables established by gamma regression. The relationship that was found varied by analytical approach and gender. Among the women, no association was observed between job strain and adiposity in the fitted gamma models. In the quantile models, a pattern of increasing effects of high strain was observed at higher BMI and WC distribution quantiles. Among the men, high strain was associated with adiposity in the gamma regression models. However, when quantile regression was used, that association was found not to be homogeneous across outcome distributions. In addition, in the quantile models an association was observed between active jobs and BMI. Our results point to an association between job strain and adiposity, which follows a heterogeneous pattern. Modelling strategies can produce different results and should, accordingly, be used to complement one another.pt_BR
dc.format.mimetypepdfpt_BR
dc.languageengpt_BR
dc.publisherUniversidade Federal de Minas Geraispt_BR
dc.publisher.countryBrasilpt_BR
dc.publisher.departmentMED - DEPARTAMENTO DE MEDICINA PREVENTIVA SOCIALpt_BR
dc.publisher.initialsUFMGpt_BR
dc.relation.ispartofInternational Journal of Environmental Research and Public Health-
dc.rightsAcesso Abertopt_BR
dc.subjectQuantile regression modelspt_BR
dc.subjectAdipositypt_BR
dc.subjectJob strainpt_BR
dc.subjectBody Mass Indexpt_BR
dc.subjectWaist Circumferencept_BR
dc.subject.otherAdipositypt_BR
dc.subject.otherBody Mass Indexpt_BR
dc.subject.otherWaist Circumferencept_BR
dc.titleUsing gamma and quantile regressions to explore the association between job strain and adiposity in the elsa-brasil study: does gender matter?pt_BR
dc.typeArtigo de Periódicopt_BR
dc.url.externahttps://pubmed.ncbi.nlm.nih.gov/29149021/pt_BR
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