Using gamma and quantile regressions to explore the association between job strain and adiposity in the elsa-brasil study: does gender matter?
Autor(a) principal: | |
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Data de Publicação: | 2017 |
Outros Autores: | , , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Institucional da UFMG |
Texto Completo: | http://hdl.handle.net/1843/59009 |
Resumo: | This 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. |
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Using gamma and quantile regressions to explore the association between job strain and adiposity in the elsa-brasil study: does gender matter?Quantile regression modelsAdiposityJob strainBody Mass IndexWaist CircumferenceAdiposityBody Mass IndexWaist CircumferenceThis 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.Universidade Federal de Minas GeraisBrasilMED - DEPARTAMENTO DE MEDICINA PREVENTIVA SOCIALUFMG2023-09-28T20:55:52Z2023-09-28T20:55:52Z2017-11-17info:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articlepdfapplication/pdf10.3390/ijerph1411140416604601http://hdl.handle.net/1843/59009engInternational Journal of Environmental Research and Public HealthMaria FonsecaEstela AquinoDóra ChorLeidjaira JuvanholLúcia RotenbergAline NobreRosane GriepMárcia AlvesLetícia CardosoLuana Giatti GonçalvesMaria Nunesinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMG2023-10-02T20:35:29Zoai:repositorio.ufmg.br:1843/59009Repositório InstitucionalPUBhttps://repositorio.ufmg.br/oairepositorio@ufmg.bropendoar:2023-10-02T20:35:29Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false |
dc.title.none.fl_str_mv |
Using gamma and quantile regressions to explore the association between job strain and adiposity in the elsa-brasil study: does gender matter? |
title |
Using gamma and quantile regressions to explore the association between job strain and adiposity in the elsa-brasil study: does gender matter? |
spellingShingle |
Using gamma and quantile regressions to explore the association between job strain and adiposity in the elsa-brasil study: does gender matter? Maria Fonseca Quantile regression models Adiposity Job strain Body Mass Index Waist Circumference Adiposity Body Mass Index Waist Circumference |
title_short |
Using gamma and quantile regressions to explore the association between job strain and adiposity in the elsa-brasil study: does gender matter? |
title_full |
Using gamma and quantile regressions to explore the association between job strain and adiposity in the elsa-brasil study: does gender matter? |
title_fullStr |
Using gamma and quantile regressions to explore the association between job strain and adiposity in the elsa-brasil study: does gender matter? |
title_full_unstemmed |
Using gamma and quantile regressions to explore the association between job strain and adiposity in the elsa-brasil study: does gender matter? |
title_sort |
Using gamma and quantile regressions to explore the association between job strain and adiposity in the elsa-brasil study: does gender matter? |
author |
Maria Fonseca |
author_facet |
Maria Fonseca Estela Aquino Dóra Chor Leidjaira Juvanhol Lúcia Rotenberg Aline Nobre Rosane Griep Márcia Alves Letícia Cardoso Luana Giatti Gonçalves Maria Nunes |
author_role |
author |
author2 |
Estela Aquino Dóra Chor Leidjaira Juvanhol Lúcia Rotenberg Aline Nobre Rosane Griep Márcia Alves Letícia Cardoso Luana Giatti Gonçalves Maria Nunes |
author2_role |
author author author author author author author author author author |
dc.contributor.author.fl_str_mv |
Maria Fonseca Estela Aquino Dóra Chor Leidjaira Juvanhol Lúcia Rotenberg Aline Nobre Rosane Griep Márcia Alves Letícia Cardoso Luana Giatti Gonçalves Maria Nunes |
dc.subject.por.fl_str_mv |
Quantile regression models Adiposity Job strain Body Mass Index Waist Circumference Adiposity Body Mass Index Waist Circumference |
topic |
Quantile regression models Adiposity Job strain Body Mass Index Waist Circumference Adiposity Body Mass Index Waist Circumference |
description |
This 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. |
publishDate |
2017 |
dc.date.none.fl_str_mv |
2017-11-17 2023-09-28T20:55:52Z 2023-09-28T20:55:52Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
10.3390/ijerph14111404 16604601 http://hdl.handle.net/1843/59009 |
identifier_str_mv |
10.3390/ijerph14111404 16604601 |
url |
http://hdl.handle.net/1843/59009 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
International Journal of Environmental Research and Public Health |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
pdf application/pdf |
dc.publisher.none.fl_str_mv |
Universidade Federal de Minas Gerais Brasil MED - DEPARTAMENTO DE MEDICINA PREVENTIVA SOCIAL UFMG |
publisher.none.fl_str_mv |
Universidade Federal de Minas Gerais Brasil MED - DEPARTAMENTO DE MEDICINA PREVENTIVA SOCIAL UFMG |
dc.source.none.fl_str_mv |
reponame:Repositório Institucional da UFMG instname:Universidade Federal de Minas Gerais (UFMG) instacron:UFMG |
instname_str |
Universidade Federal de Minas Gerais (UFMG) |
instacron_str |
UFMG |
institution |
UFMG |
reponame_str |
Repositório Institucional da UFMG |
collection |
Repositório Institucional da UFMG |
repository.name.fl_str_mv |
Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG) |
repository.mail.fl_str_mv |
repositorio@ufmg.br |
_version_ |
1816829919158599680 |