Socioeconomic Status and Health: Disentangling causal pathways in a life course perspective

Research Focus

People with lower income or lower educational level have worse health and higher mortality. This project addresses the two basic underlying questions for this finding: How does your socioeconomic status determine your health? And how does your health determine your socioeconomic status? The project studies life courses of persons aged 50+ at the time of the interview who were surveyed prospectively, and also retrospectively for their entire life history starting at childhood. Our results will provide important new insight into the dual relationship between SES and health and will help to understand and to tackle social differences in health.

Scientific Background

We will use data from the Survey of Health Aging and Retirement in Europe (SHARE) from 30,000 individuals in 14 European countries, and the English Longitudinal Study of Ageing (ELSA) that offers the same data for more than 7,000 persons. This data contains exact information on periods and events of ill health and periods and events of change in socioeconomic status. In addition, there is explicit information on the consequences of poor health in childhood in terms of schooling, or, later in life, in terms of working hours or career perspectives. Life histories from childhood to old age are the ideal basis for disentangling causality between SES and health because confounding of the key variables prior to measurement is minimal.

Methodology

By applying simultaneous equation models for hazards (survival analysis), the correlated processes of health deterioration (influenced by SES) and the development of SES (influenced by health) can be disentangled. This will produce unbiased estimates of the effect sizes for both causation directions and answer the question of causation and selection in a life course perspective taking into account endogeneity and confounders. We will also reveal if common background factors are influencing both SES and health and we will identify possible differences in the causation direction between life stages.

Research Goals

• To integrate disparate theories, causal models and research traditions from epidemiology and economics by reviewing recent empirical findings, theoretical developments and reasons for disciplinary differences in order to use and develop further an interdisciplinary theoretical and empirical basis for studying the interdisciplinary problem of SES and health.

• To address the problem of endogeneity in the question of causality between SES and health by empirically analyzing complete records of life histories from the Survey of Health Aging and Retirement in Europe (SHARE) and the English Longitudinal Study of Ageing (ELSA).

• To disentangle the direction of causality by analyzing the correlated processes of health deterioration (influenced by SES) and change of SES (influenced by health) using multi-process modeling (simultaneous equation models) for hazards.

• To compare the relative contribution of social causation and social selection between age groups in order to show the life course pattern of causality between SES and health and its dependency on other determinants.

• To estimate the impact of observed and unobserved background factors (unobserved heterogeneity), the latter by letting error terms on the individual level correlate between the two processes under study. This will reveal to what extent both SES and health are caused by common background factors.

Publications

Kröger H., Hoffmann R. (2018) "The association between CVD-related biomarkers and mortality in the Health and Retirement Survey", Demographic Research, 38(62), 1933-2002.                                             

Hoffmann R., Kröger H., Geyer S. (2018) "Social causation versus health selection in the life course – does their relative importance differ by dimension of SES?", Social Indicators Research, online first and open access.

Hoffmann R., Kröger H., Pakpahan E. (2018) "Pathways between socioeconomic status and health: Does health selection or social causation dominate in Europe?", Advances in Life Course Research, online first and open access. 

Hoffmann, R., Kröger, H., Pakpahan, E. (2018) "The reciprocal relationship between material factors and health in the life course – evidence from SHARE and ELSA", European Journal of Ageing, online first and open access.

Kröger H., Hoffmann R., Tarkiainen L., Martikainen P. (2017) ”Comparing Observed and Unobserved Components of Childhood: Evidence From Finnish Register Data on Midlife Mortality From Siblings and Their Parents”, published in Demography and online first, DOI: 10.1007/s13524-017-0635-6

Pakpahan E., Hoffmann R., Kröger H. (2017) „The long arm of childhood circumstances on health in old age: Evidence from SHARELIFE”, Advances in Life Course Research, 31, 1-10. http://www.sciencedirect.com/science/article/pii/S1040260816300569

Pakpahan E., Hoffmann R., Kröger H. (2017) „Retrospective life course data from European countries on how early life experiences determine health in old age and possible mid-life mediators”, Data in Brief, 10, 288-282. http://www.sciencedirect.com/science/article/pii/S2352340916307545

Hoffmann R., H. Kröger, E. Pakpahan (2017) “Health inequalities and the interplay of socioeconomic factors and health in the life course” in: Handbook of Biology and Society, M. Meloni et al. (Eds.), Palgrave MacMillan 

Hoffmann R., H. Kröger, E. Pakpahan (2016), “Kausale Beziehungen zwischen sozialem Status und Gesundheit aus einer Lebensverlaufsperspektive”, Handbuch Gesundheitssoziologie, M. Jungbauer-Gans and P. Kriwy (Eds.), Springer, Wiesbaden, DOI: 10.1007/978-3-658-06477-8_24-1.

Kröger, H., J. Fritzell, R. Hoffmann (2016), "The Association of Levels of and Decline in Grip Strength in Old Age with Trajectories of Life Course Occupational Position". PLoS ONE 11(5): e0155954.

Kröger, H. (2015), “Newspell - Easy Management of Complex Spell Data.”, Stata Journal 15 (1): 155–72.

Pakpahan, E., R. Hoffmann, H. Kröger (2015), “Statistical Methods for Causal Analysis in Life Course Research: An illustration of a Cross Lagged Structural Equation Model and a Latent Growth Model”, International Journal of Social Research Methodology, 1-19

Kröger, H., R. Hoffmann, E. Pakpahan (2016), “Consequences of measurement error for inference in cross-lagged panel design - The example of the reciprocal causal relationship between subjective health and socio-economic status”, Journal of the Royal Statistical Society: Series A (Statistics in Society), 179(2), 607-628..

Kröger, H., E. Pakpahan, R. Hoffmann (2015), “What Causes Health Inequality? A systematic Review on the Relative Importance of Social Causation and Health Selection”, The European Journal of Public Health, 25(6), 951-960.

Kröger, H., R. Hoffmann (2015), “Who can realise their retirement plans? Poor health and employment crises as factors of exclusion”, Ageing in Europe - Supporting Policies for an Inclusive Society. SHARE Wave 5 First Results Book, A. Börsch-Supan et al. (Hgs.), De Gruyter, Berlin, 115 (Open Access)

Gross, C., T. Schübel and R. Hoffmann (2014). "Picking up the Pieces – Applying the DISEASE FILTER to Health Data”, Health Policy, 119(4), 549-557.

To see the complete of publications of Rasmus Hoffmann, please see his detailed profile here.