IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v14y2017i11p1404-d119224.html
   My bibliography  Save this article

Using Gamma and Quantile Regressions to Explore the Association between Job Strain and Adiposity in the ELSA-Brasil Study: Does Gender Matter?

Author

Listed:
  • Maria De Jesus Mendes da Fonseca

    (Department of Epidemiology and Quantitative Methods in Health, National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro 21041-210, Brazil)

  • Leidjaira Lopes Juvanhol

    (Department of Nutrition and Health, Federal University of Viçosa, Viçosa 36.570-000, Brazil)

  • Lúcia Rotenberg

    (Laboratory of Health and Environment Education, Oswaldo Cruz Fundation, Rio de Janeiro 21040-900, Brazil)

  • Aline Araújo Nobre

    (Scientific Computing Program, Oswaldo Cruz Foundation, Rio de Janeiro 21040-900, Brazil)

  • Rosane Härter Griep

    (Laboratory of Health and Environment Education, Oswaldo Cruz Fundation, Rio de Janeiro 21040-900, Brazil)

  • Márcia Guimarães de Mello Alves

    (Institute of Collective Health, Fluminense Federal University, Niterói 24033-900, Brazil)

  • Letícia De Oliveira Cardoso

    (Department of Epidemiology and Quantitative Methods in Health, National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro 21041-210, Brazil)

  • Luana Giatti

    (Faculty of Medicine, Federal University of Minas Gerais, Belo Horizonte 30310-100, Brazil)

  • Maria Angélica Nunes

    (Pos graduate program in Epidemiology, Federal University of Rio Grande do Sul, Porto Alegre 90035-003, Brazil)

  • Estela M. L. Aquino

    (Institute of Collective Health, Federal University of Bahia, Salvador 40110-040, Brazil)

  • Dóra Chor

    (Department of Epidemiology and Quantitative Methods in Health, National School of Public Health, Oswaldo Cruz Foundation, Rio de Janeiro 21041-210, Brazil)

Abstract

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.

Suggested Citation

  • Maria De Jesus Mendes da Fonseca & Leidjaira Lopes Juvanhol & Lúcia Rotenberg & Aline Araújo Nobre & Rosane Härter Griep & Márcia Guimarães de Mello Alves & Letícia De Oliveira Cardoso & Luana Giatti , 2017. "Using Gamma and Quantile Regressions to Explore the Association between Job Strain and Adiposity in the ELSA-Brasil Study: Does Gender Matter?," IJERPH, MDPI, vol. 14(11), pages 1-13, November.
  • Handle: RePEc:gam:jijerp:v:14:y:2017:i:11:p:1404-:d:119224
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/14/11/1404/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/14/11/1404/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andreas Beyerlein & Rüdiger von Kries & Andrew R Ness & Ken K Ong, 2011. "Genetic Markers of Obesity Risk: Stronger Associations with Body Composition in Overweight Compared to Normal-Weight Children," PLOS ONE, Public Library of Science, vol. 6(4), pages 1-4, April.
    2. Moshe Buchinsky, 1998. "Recent Advances in Quantile Regression Models: A Practical Guideline for Empirical Research," Journal of Human Resources, University of Wisconsin Press, vol. 33(1), pages 88-126.
    3. Heikkilä, K. & Fransson, E.I. & Nyberg, S.T. & Zins, M. & Westerlund, H. & Westerholm, P. & Virtanen, M. & Vahtera, J. & Suominen, S. & Steptoe, A. & Salo, P. & Pentti, J. & Oksanen, T. & Nordin, M. &, 2013. "Job strain and health-related lifestyle: Findings from an individual-participant meta-analysis of 118 000 working adults," American Journal of Public Health, American Public Health Association, vol. 103(11), pages 2090-2097.
    4. Sunday Azagba & Mesbah Sharaf, 2012. "The relationship between job stress and body mass index using longitudinal data from Canada," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 57(5), pages 807-815, October.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. repec:rre:publsh:v:39:y:2009:i:2:p:149-69 is not listed on IDEAS
    2. Hiau Joo Kee, 2005. "Glass Ceiling or Sticky Floor? Exploring the Australian Gender Pay Gap using Quantile Regression and Counterfactual Decomposition Methods," CEPR Discussion Papers 487, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    3. O.S. Mariev & N.B. Davidson & O.S. Emelianova, 2020. "The Impact of Urbanization on Carbon Dioxide Emissions in the Regions of Russia," Journal of Applied Economic Research, Graduate School of Economics and Management, Ural Federal University, vol. 19(3), pages 286-309.
    4. Mariacristina De Nardi & Eric French & John Bailey Jones, 2016. "Medicaid Insurance in Old Age," American Economic Review, American Economic Association, vol. 106(11), pages 3480-3520, November.
    5. Lopez-Acevedo, Gladys & Salinas, Angel, 2000. "How Mexico's financial crisis affected income distribution," Policy Research Working Paper Series 2406, The World Bank.
    6. Chunbei Wang & Le Wang, 2011. "Language Skills and the Earnings Distribution Among Child Immigrants," Industrial Relations: A Journal of Economy and Society, Wiley Blackwell, vol. 50(2), pages 297-322, April.
    7. Beth A. Freeborn, 2009. "Arrest Avoidance: Law Enforcement and the Price of Cocaine," Journal of Law and Economics, University of Chicago Press, vol. 52(1), pages 19-40, February.
    8. Strike Mbulawa & Francis Nathan Okurut & Mogale Ntsosa & Narain Sinha, 2020. "Dynamics of Corporate Dividend Policy under Hyperinflation and Dollarization: A Quantile Regression Approach," International Journal of Business and Economic Sciences Applied Research (IJBESAR), Democritus University of Thrace (DUTH), Kavala Campus, Greece, vol. 13(3), pages 70-82, December.
    9. Grootaert, Christiaan, 1999. "Social capital, houshold welfare, and poverty in Indonesia," Policy Research Working Paper Series 2148, The World Bank.
    10. Masayoshi Hayashi, 2011. "The effects of medical factors on transfer deficits in Public Assistance in Japan: a quantile regression analysis," International Journal of Health Economics and Management, Springer, vol. 11(4), pages 287-307, December.
    11. Lixin Cai & Amy Y.C. Liu, 2008. "Public-Private Wage Gap in Australia: Variation Along the Distribution," CEPR Discussion Papers 581, Centre for Economic Policy Research, Research School of Economics, Australian National University.
    12. Duschl, Matthias & Schimke, Antje & Brenner, Thomas & Luxen, Dennis, 2011. "Firm growth and the spatial impact of geolocated external factors: Empirical evidence for German manufacturing firms," Working Paper Series in Economics 36, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
    13. Chiswick, Barry R. & Miller, Paul W., 2007. "Earnings and Occupational Attainment: Immigrants and the Native Born," IZA Discussion Papers 2676, Institute of Labor Economics (IZA).
    14. Agbeyegbe, Terence D., 2015. "An inverted U-shaped crude oil price return-implied volatility relationship," Review of Financial Economics, Elsevier, vol. 27(C), pages 28-45.
    15. Gaglianone, Wagner Piazza & Lima, Luiz Renato & Linton, Oliver & Smith, Daniel R., 2011. "Evaluating Value-at-Risk Models via Quantile Regression," Journal of Business & Economic Statistics, American Statistical Association, vol. 29(1), pages 150-160.
    16. G. Reza Arabsheibani & Francisco Galrao Carneiro & Andrew Henley, 2003. "Human capital and earnings inequality in Brazil, 1988-98 : quantile regression evidence," Policy Research Working Paper Series 3147, The World Bank.
    17. Mariacristina De Nardi & Eric French & John Bailey Jones & Rory McGee, 2021. "Why Do Couples and Singles Save During Retirement?," Richmond Fed Economic Brief, Federal Reserve Bank of Richmond, vol. 21(09), pages 1-65, May.
    18. Mandy van den Berge & Gerben Hulsegge & Henk F. van der Molen & Karin I. Proper & H. Roeline W. Pasman & Lea den Broeder & Sietske J. Tamminga & Carel T. J. Hulshof & Allard J. van der Beek, 2020. "Adapting Citizen Science to Improve Health in an Occupational Setting: Preliminary Results of a Qualitative Study," IJERPH, MDPI, vol. 17(14), pages 1-19, July.
    19. Duc Hong Vo & Thach Ngoc Pham, 2017. "Systematic Risk in Energy Businesses: Empirical Evidence for the ASEAN," International Journal of Economics and Financial Issues, Econjournals, vol. 7(1), pages 553-565.
    20. Mario BENASSI & Matteo LANDONI & Francesco RENTOCCHINI, 2017. "University Management Practices and Academic Spin-offs," Departmental Working Papers 2017-11, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    21. Manquilef-Bächler, Alejandra A. & Arulampalam, Wiji & Smith, Jennifer C., 2009. "Differences in Decline: Quantile Regression Analysis of Union Wage Differentials in the United Kingdom, 1991-2003," IZA Discussion Papers 4138, Institute of Labor Economics (IZA).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:14:y:2017:i:11:p:1404-:d:119224. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.