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Occupied with classification: Which occupational classification scheme better predicts health outcomes?

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  • Eyles, Emily
  • Manley, David
  • Jones, Kelvyn

Abstract

Health inequalities continue to grow despite continuous policy intervention. Work, one domain of health inequalities, is often included as a component of social class rather than as a determinant in its own right. Many social class classifications are derived from occupation types, but there are other components within them that mean they may not be useful as proxies for occupation. This paper develops the exposome, a life-course exposure model developed by Wild (2005), into the worksome, allowing for the explicit consideration of both physical and psychosocial exposures and effects derived from work and working conditions. The interactions between and within temporal and geographical scales are strongly emphasised, and the interwoven nature of both psychosocial and physical exposures is highlighted. Individuals within an occupational type can be both affected by and effect upon occupation level characteristics and health measures. By using the worksome, occupation types are separated from value-laden social classifications. This paper will empirically examine whether occupation better predicts health measures from the European Working Conditions Survey (EWCS). Logistic regression models using Bayesian MCMC estimation were run for each classification system, for each health measure. Health measures included, for example, whether the respondent felt their work affected their health, their self-rated health, pain in upper or lower limbs, and headaches. Using the Deviance Information Criterion (DIC), a measure of predictive accuracy penalised for model complexity, the models were assessed against one another. The DIC shows empirically which classification system is most suitable for use in modelling. The 2-digit International Standard Classification of Occupations showed the best predictive accuracy for all measures. Therefore, examining the relationship between health and work should be done with classifications specific to occupation or industry rather than socio-economic class classifications. This justifies the worksome, allowing for a conceptual framework to link many forms of work-health research.

Suggested Citation

  • Eyles, Emily & Manley, David & Jones, Kelvyn, 2019. "Occupied with classification: Which occupational classification scheme better predicts health outcomes?," Social Science & Medicine, Elsevier, vol. 227(C), pages 56-62.
  • Handle: RePEc:eee:socmed:v:227:y:2019:i:c:p:56-62
    DOI: 10.1016/j.socscimed.2018.09.020
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    References listed on IDEAS

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    1. Kim, Il-Ho & Muntaner, Carles & Vahid Shahidi, Faraz & Vives, Alejandra & Vanroelen, Christophe & Benach, Joan, 2012. "Welfare states, flexible employment, and health: A critical review," Health Policy, Elsevier, vol. 104(2), pages 99-127.
    2. David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
    3. Halleröd, Björn & Gustafsson, Jan-Eric, 2011. "A longitudinal analysis of the relationship between changes in socio-economic status and changes in health," Social Science & Medicine, Elsevier, vol. 72(1), pages 116-123, January.
    4. repec:dau:papers:123456789/10510 is not listed on IDEAS
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    Cited by:

    1. Annette Meng & Emil Sundstrup & Lars L. Andersen, 2021. "What Do the Managers Think of Us? The Older-Worker-Perspective of Managers’ Attitudes," IJERPH, MDPI, vol. 18(8), pages 1-9, April.
    2. Senhu Wang & Adam Coutts & Brendan Burchell & Daiga KamerÄ de & Ursula Balderson, 2021. "Can Active Labour Market Programmes Emulate the Mental Health Benefits of Regular Paid Employment? Longitudinal Evidence from the United Kingdom," Work, Employment & Society, British Sociological Association, vol. 35(3), pages 545-565, June.

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