CoChat
Sign Up
Cited by 87Health disparities and outcomesPublic Health and Social InequalitiesIntergenerational and Educational Inequality Studies

Social causation versus health selection in the life course: Does their relative importance differ by dimension of SES?

Open access
Hoffmann, Rasmus, Kröger, Hannes, Geyer, Siegfried·2019·Social Indicators Research
DOI 10.1007/s11205-018-1871-x
Open this paper in CoChat — free accountOpen PDF

Abstract

A person’s socioeconomic status (SES) can affect health (social causation) and health can affect SES (health selection). The findings for each of these pathways may depend on how SES is measured. We study (1) whether social causation or health selection is more important for overall health inequalities, (2) whether this differs between stages of the life course, and (3) between measures of SES. Using retrospective survey data from 10 European countries (SHARELIFE, n = 18,734), and structural equation models in a cross-lagged panel design, we determine the relative explanatory power of social causation and health selection through childhood, adulthood, and old age. We use three ways to measure SES: First, as a latent variable capturing different aspects of SES, second as material wealth, and third as occupational skill level. Between childhood and adulthood, social causation and health selection are equally important. In the transition from adulthood to old age, social causation becomes more important than health selection, making it the dominant mechanism in old age. The three measures of SES produce similar results. Only material wealth shows a stronger effect on health (between childhood and adulthood); it is also more affected by health (between adulthood and old age) than the other measures.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1007/s11205-018-1871-x

Cites

9 of 9 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • The pattern of caregiver characteristics is consistent with health selection (healthy worker effect): healthier grandparents remain employed and are less available for caregiving, leaving relatively less healthy grandparents overrepresented among caregivers.

    “This pattern is consistent with health selection (i.e., the healthy worker effect): healthier grandparents remain employed and are less available for caregiving, leaving relatively less healthy grandparents overrepresented among caregivers (Hoffmann et al., 2019).”

    From Grandparent Caregiving and Epigenetic Aging among Midlife and Older Adults in the United States (2026) · cites this paper as Hoffmann et al., 2019

    Split into 2 atoms — 0 confirmed, 2 partially supported, 0 disputed, 0 misattributed, 0 unverifiable. Expand the claim to see per-atom verdicts.

    Experimental — accuracy not yet measured

  • The study was unable to control for health status at a prior wave.

    “as we were unable to control for health status at a prior wave (Hoffmann et al., 2019).”

    From Grandparent Caregiving and Epigenetic Aging among Midlife and Older Adults in the United States (2026) · cites this paper as Hoffmann et al., 2019

    Section 3.1 Data says Hoffmann et al. used SHARELIFE wave 3 with retrospective health information. Section 3.3 Analysis discusses controlling for baseline health and describes a life-course approach, but neither section says the study was unable to control for health status at a prior wave. I searched for that limitation and for references to prior-wave or baseline health; the cited paper cannot establish what the citing authors meant by their own inability to control for it. (LLM, conf=0.72)

    Experimental — accuracy not yet measured

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Research works printed but not linked: 74

  1. Adams, P., Hurd, M. D., McFadden, D., Merrill, A., & Ribeiro, T. (2003). Healthy, wealthy, and wise? Tests for direct causal paths between health and socioeconomic status. Journal of Econometrics, 112(1), 3-56.
  2. Adler, N. E., & Ostrove, J. M. (1999). Socioeconomic status and health: What we know and what we don't. Annals of the New York Academy of Sciences, 896(1), 3-15.
  3. Aittomäki, A., Martikainen, P., Laaksonen, M., Lahelma, E., & Rahkonen, O. (2012). Household economic resources, labour-market advantage and health problems-A study on causal relationships using pro- spective register data. Social Science and Medicine, 75(7), 1303-1310.
  4. Autor, D. H. (2014). Skills, education, and the rise of earnings inequality among the "other 99 percent". Sci- ence, 344(6186), 843-851.
  5. Avlund, K., Holstein, B. E., Osler, M., Damsgaard, M. T., Holm-Pedersen, P., & Rasmussen, N. K. (2003). Social position and health in old age: The relevance of different indicators of social position. Scandina- vian Journal of Public Health, 31(2), 126-136.
  6. Blane, D. (2006). Commentary: The place in life course research of validated measures of socioeconomic position. International Journal of Epidemiology, 35, 139-140.
  7. Blane, D., Davey Smith, G., & Bartley, M. (1993). Social selection: What does it contribute to social class differences in health? Sociology of Health & Illness, 15(1), 1-15.
  8. Blossfeld, H.-P. (2009). Causation as a generative process. The elaboration of an idea for the social sci- ences and an application to an analysis of an interdependent dynamic social system. In H. Engelhardt, H.-P. Kohler, & A. Fürnkranz-Prskawetz (Eds.), Causal analysis in population studies, the Springer series on demographic methods and population analysis (Vol. 23, pp. 83-109). Dordrecht: Springer Netherlands.
  9. Blossfeld, H.-P., Golsch, K., & Rohwer, G. (2007). Event history analysis with stata (1st ed.). New York: Psychology Press.
  10. Bollen, K. A. (1989). Structural equations with latent variables. New York, NY: Wiley-Interscience.
  11. Börsch-Supan, A., Brandt, M., Hunkler, C., Kneip, T., Korbmacher, J., Malter, F., et al. (2013). Data resource profile: The Survey of Health, Ageing and Retirement in Europe (SHARE). International Journal of Epidemiology, 42(4), 992-1001.
  12. Contoyannis, P., & Rice, N. (2001). The impact of health on wages: Evidence from the British Household Panel Survey. Empirical Economics, 26(4), 599-622.
  13. Corna, L. M. (2013). A life course perspective on socioeconomic inequalities in health: A critical review of conceptual frameworks. Advances in Life Course Research, 18(2), 150-159.
  14. Cunha, F., & Heckman, J. (2007). The technology of skill formation. American Economic Review, 97(2), 31-47.
  15. Dannefer, D. (2003). Cumulative advantage/disadvantage and the life course: Cross-fertilizing age and social science theory. The Journals of Gerontology, Series B: Psychological and Social Sciences, 58(6), 327-337.
  16. Eaton, W. W., Muntaner, C., Bovasso, G., & Smith, C. (2001). Socioeconomic status and depressive syn- drome: The role of inter-and intra-generational mobility, government assistance, and work environ- ment. Journal of Health and Social Behavior, 42(3), 277.
  17. Elgar, F. J., McKinnon, B., Torsheim, T., Schnohr, C. W., Mazur, J., Cavallo, F., et al. (2016). Patterns of socioeconomic inequality in adolescent health differ according to the measure of socioeconomic posi- tion. Social Indicators Research, 127(3), 1169-1180.
  18. Elo, I. T. (2009). Social class differentials in health and mortality: Patterns and explanations in comparative perspective. Annual Review of Sociology, 35, 553-572.
  19. Elovainio, M., Pulkki-Råback, L., Jokela, M., Kivimäki, M., Hintsanen, M., Hintsa, T., et al. (2012). Socio- economic status and the development of depressive symptoms from childhood to adulthood: A longi- tudinal analysis across 27 years of follow-up in the Young Finns study. Social Science and Medicine, 74(6), 923-929.
  20. Finney, S. J., & DiStefano, C. (2006). Non-normal and categorical data in structural equation modeling. In G. R. Hancock & R. O. Mueller (Eds.), Structural equation modeling: A second course (pp. 269-314). Greenwich, CT: Information Age Publishing Inc.
  21. Garrouste, C., & Paccagnella, O. (2011). Three examples of consistency across SHARE and SHARE- LIFE data. In M. Schröder (Ed.), Retrospective data collection in the Survey of Health, Ageing and Retirement in Europe-SHARELIFE methodology (pp. 62-72). Mannheim: Mannheim Research Institute for the Economics of Ageing.
  22. Geyer, S. (2008). Einzelindikator oder Index? Maße sozialer Differenzierung im Vergleich [Single indi- cator or index? Comparison of measures of social differentiation]. Das Gesundheitswesen, 70(5), 281-288.
  23. Geyer, S. (2016). Soziale Ungleichverteilungen von Gesundheit und Krankheit und ihre Erklärungen -Schulbildung, Einkommen und Beruf. In M. Jungbauer-Gans & P. Kriwy (Eds.), Handbuch Gesundheitssoziologie. Wiesbaden: Springer.
  24. Geyer, S., Hemström, Ö., Peter, R., & Vågerö, D. (2006). Education, income, and occupational class cannot be used interchangeably in social epidemiology. Empirical evidence against a common prac- tice. Journal of Epidemiology and Community Health, 60(9), 804-810.
  25. Goldman, N. (2001a). Social inequalities in health: Disentangling the underlying mechanisms. Annals of the New York Academy of Sciences, 954, 118-139.
  26. Goldman, N. (2001b). Mortality differentials: Selection and causation. In N. J. Smelser & P. B. Baltes (Eds.) International encyclopedia of social and behavioral sciences (pp. 10068-10070). Amster- dam: Elsevier.
  27. Goldthorpe, J. H. (2001). Causation, statistics, and sociology. European Sociological Review, 17, 1-20.
  28. Haan, M. N., Kaplan, G. A., & Syme, S. L. (1989). Socioeconomic status and health: Old observations and new thoughts. In D. S. Bunker, B. H. Gomby & B. H. Kehrer (Eds.), Pathways to health (pp. 76-135). Menlo Park, CA: The Henry J. Kaiser Family Foundation.
  29. Haas, S. A., Glymour, M. M., & Berkman, L. F. (2011). Childhood health and labor market inequality over the life course. Journal of Health and Social Behavior, 52(3), 298-313.
  30. Headey, B., & Muffels, R. (2016). Towards a theory of medium term life satisfaction: Two-way causation partly explains persistent satisfaction or dissatisfaction. Social Indicators Research, 129(2), 937-960.
  31. Heckman, J. J. (1981). The incidental parameters problem and the problem of initial conditions in esti- mating a discrete time-discrete data stochastic process. In C. F. Manski & D. L. McFadden (Eds.), Structural analysis of discrete data and econometric applications. Cambridge: MIT Press.
  32. Hertzman, C., Frank, J., & Evans, R. G. (1994). Heterogeneities in health status and the determinants of population health. In R. G. Evans, M. L. Barer, & T. R. Marmor (Eds.), Why are some peo- ple healthy and others not? determinants of health and populations, social institutions and social change series (pp. 67-92). New York: Aldine de Gruyter.
  33. Hoffmann, R. (2008). Socioeconomic differences in old age mortality, the Springer series on demo- graphic methods and population analysis (Vol. 25). Dordrecht: Springer.
  34. Huurre, T., Rahkonen, O., Komulainen, E., & Aro, H. (2005). Socioeconomic status as a cause and consequence of psychosomatic symptoms from adolescence to adulthood. Social Psychiatry and Psychiatric Epidemiology, 40(7), 580-587.
  35. Kröger, H. (2015b). Newspell-Easy management of complex spell data. Stata Journal, 15, 155-172.
  36. Kröger, H., Fritzell, J., & Hoffmann, R. (2016a). 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.
  37. Kröger, H., Hoffmann, R., & Pakpahan, E. (2016b). Consequences of measurement error for inference in cross-lagged panel design-The example of the reciprocal causal relationship between subjective health and SES. Journal of the Royal Statistical Society. Series A, 179, 607-628.
  38. Kröger, H., Pakpahan, E., & Hoffmann, R. (2015). What causes health inequality? A systematic review on the relative importance of social causation and health selection. European Journal of Public Health, 25(6), 951-960.
  39. Lahelma, E., Laaksonen, M., Martikainen, P., & Rahkonen, O. (2008). Die Mehrdimensionalität der sozi- oökonomischen Lage-Konsequenzen für die Analysen gesundheitlicher Ungleichheit. In U. Bauer, U. H. Bittlingmayer, & M. Richter (Eds.), Health Inequalities-Erklärungsansätze gesundheitlicher Ungleichheit (pp. 143-166). Wiesbaden: VS-Verlag.
  40. Lahelma, E., Laaksonen, M., Martikainen, P., Rahkonen, O., & Sarlio-Lähteenkorva, S. (2006). Multiple measures of socioeconomic circumstances and common mental disorders. Social Science and Medi- cine, 63(5), 1383-1399.
  41. Laurijssen, I., & Spruyt, B. (2015). Not for people like us? A 6-year panel study of the mutual relation- ship between feelings of relative deprivation and occupational status among young adults in Flanders. Social Indicators Research, 124(2), 617-635.
  42. Lundberg, O. (1991). Childhood living conditions, health status, and social mobility: A contribution to the health selection debate. European Sociological Review, 7, 149-162.
  43. Lynch, J., & Kaplan, G. (2000). Socioeconomic position. In L. F. Berkman & I. Kawachi (Eds.), Social epi- demiology (pp. 13-35). Oxford: Oxford University Press.
  44. Mackenbach, J. P., Kulhánová, I., Menvielle, G., Bopp, M., Borrell, C., Costa, G., et al. (2015b). Trends in inequalities in premature mortality: A study of 3.2 million deaths in 13 European countries. Journal of Epidemiology and Community Health, 69(3), 207-217.
  45. Mackenbach, J. P., Meerding, W. J., & Kunst, A. E. (2011). Economic costs of health inequalities in the European Union. Journal of Epidemiology and Community Health, 65(5), 412-419.
  46. Manor, O., Matthews, S., & Power, C. (2003). Health selection: the role of inter-and intra-generational mobility on social inequalities in health. Social Science and Medicine, 57(11), 2217-2227.
  47. Marks, G. N. (2011). Issues in the conceptualisation and measurement of socioeconomic background: Do different measures generate different conclusions? Social Indicators Research, 104(2), 225-251.
  48. Martikainen, P., Valkonen, T., & Moustgaard, H. (2009). The effects of individual taxable income, house- hold taxable income, and household disposable income on mortality in Finland, 1998-2004. Popula- tion Studies, 63(2), 147-162.
  49. Mayer, K. U. (2009). New directions in life course research. Annual Review of Sociology, 35, 413-433.
  50. Miething, A., Lundberg, O., & Geyer, S. (2013). Income and health in different welfare contexts: A com- parison of Sweden, East and West Germany. Scandinavian Journal of Public Health, 41(3), 260-268.
  51. Mirowsky, J., & Ross, C. E. (2003). Education, social status, and health. New York: De Gruyter.
  52. Mulatu, M. S., & Schooler, C. (2002). Causal connections between socio-economic status and health: Reciprocal effects and mediating mechanisms. Journal of Health and Social Behavior, 43, 22-41.
  53. Muthen, L. K., & Muthen, B. O. (2015). Mplus User's Guide (7th ed.). Los Angeles: Muthén & Muthén.
  54. Pakpahan, E., Kröger, H., & Hoffmann, R. (2015). Statistical methods for causal analysis in life course research: An illustration of a cross lagged structural equation model and a latent growth model. Inter- national Journal of Social Research Methodology, 20(1), 1-19.
  55. Phelan, J. C., Link, B. G., Diez-Roux, A., Kawachi, I., & Levin, B. (2004). "Fundamental Causes" of Social inequalities in mortality: A test of the theory. Journal of Health and Social Behavior, 45(3), 265-285.
  56. Power, C., Manor, O., & Li, L. (2002). Are inequalities in height underestimated by adult social position? Effects of changing social structure and height selection in a cohort study. BMJ, 325(7356), 131-134.
  57. Robeyns, I. (2011). Capability approach. In J. Pell & I. V. Staveren (Eds.), Handbook of economics and eth- ics (pp. 39-46). Cheltenham: Edward Elgar.
  58. Rubin, D. B. (2005). Causal inference using potential outcomes. Journal of the American Statistical Asso- ciation, 100, 322-331.
  59. Schrijvers, C. T. M., Stronks, K., van de Mheen, D., & Mackenbach., J. P. (1999). Explaining educational differences in mortality: the role of behavioral and material factors. American Journal of Public Health, 89(4), 535-540.
  60. Schröder, M. (2011). Concepts and Topcis. In M. Schröder (Ed.), Retrospective data collection in the Sur- vey of Health, Ageing and Retirement in Europe. SHARELIFE Methodology (pp. 11-19). Mannheim: MEA
  61. Schwarz, N. (2007). Retrospective and concurrent self-reports: The rationale for real-time data capture. In A. Stone, S. S. Shiffman, & A. Atienza (Eds.), The science of real-time data capture: Self-reports in health research (pp. 11-26). New York: Oxford University Press.
  62. Sen, A. (1999). Health in development. Bulletin of the World Health Organization, 77(8), 619.
  63. Siegrist, J., & Wahrendorf, M. (2016). Work stress and health in a globalized economy. The model of effort- reward imbalance. Berlin: Springer.
  64. Smith, J. P. (1998). Socioeconomic status and health. The American Economic Review, 88(2), 192-196.
  65. Smith, J. P. (1999). Healthy bodies and thick wallets: The dual relation between health and economic status. Journal of Economic Perspectives, 13(2), 145-166.
  66. Smith, J. P. (2004). Unraveling the SES-health connection. Population and Development Review, 30(supplement(Aging, health, and public policy: demographic and economic perspectives)), 108-132.
  67. Smith, J. P., & Thomas, D. (2003). Remembrances of things past: test-retest reliability of retrospective migration histories. Journal of the Royal Statistical Society Series A, 166, 23-49.
  68. Stansfeld, S. A., Clark, C., Rodgers, B., Caldwell, T., & Power, C. (2011). Repeated exposure to socio- economic disadvantage and health selection as life course pathways to mid-life depressive and anxiety disorders. Social Psychiatry and Psychiatric Epidemiology, 46(7), 549-558.
  69. Stowasser, T., Heiss, F., McFadden, D., & Winter, J. (2011). "Healthy, wealthy and wise?" Revisited: An analysis of the causal pathways from socioeconomic status to health. In A. W. David (Ed.), Investiga- tions in the economics of aging (pp. 267-317). Chicago: University of Chicago Press.
  70. Syddall, H. E., Westbury, L. D., Dodds, R., Dennison, E., Cooper, C., & Sayer, A. A. (2017). Mortality in the Hertfordshire Ageing Study: Association with level and loss of hand grip strength in later life. Age and Ageing, 46(3), 407-412.
  71. Tarkiainen, L., Martikainen, P., Laaksonen, M., & Valkonen, T. (2012). Trends in life expectancy by income from 1988 to 2007: Decomposition by age and cause of death. Journal of Epidemiology and Commu- nity Health, 66(7), 573-578.
  72. Torssander, J., & Erikson, R. (2010). Stratification and mortality-A comparison of education, class, status, and income. European Sociological Review, 26(4), 465-474.
  73. Warren, J. R., & Kuo, H.-H. (2003). How to measure "What People do for a Living" in research on the socioeconomic correlates of health. Annals of Epidemiology, 13, 325-334.
  74. Weiss, C. T. (2012). Two measures of lifetime resources for Europe using SHARELIFE. SHARE Working Paper (Vol. 06-2012).

Cited by

Sorted by citations

Authors
Hoffmann, R., Kröger, H., & Geyer, S.
Affiliations
  • Max Planck Institute for Demographic Research (DE)
  • German Institute for Economic Research (DE)
  • Medizinische Hochschule Hannover (DE)
Corresponding author
Hoffmann, Rasmus
ORCID
Venue
Social Indicators Research
Publisher
Springer Science and Business Media LLC
Published
2018-03-13
Volume
141
Issue
3
Pages
1341-1367
ISSN
  • 0303-8300 (ISSN-L)
  • 1573-0921
DOI
10.1007/s11205-018-1871-x
OpenAlex
W2791126951
Cited by
87
References
9
Citations by year
2026: 6 · 2025: 18 · 2024: 13 · 2023: 11 · 2022: 17 · 2021: 8 · 2020: 7 · 2019: 5 · 2018: 2
FWCI
5.89
Type
journal article
Language
en
Open access
Licence
Locations
  • Social Indicators Research (publishedVersion, cc-by)
  • RePEc: Research Papers in Economics (submittedVersion)
  • Cadmus - EUI Research Repository (European University Institute) (submittedVersion, cc-by)
  • Econstor (Econstor) (submittedVersion, cc-by)
Funders
H2020 European Research Council (313532)
Topics
  • Social Sciences › Health › Health disparities and outcomes
  • Social Sciences › Health › Public Health and Social Inequalities
  • Social Sciences › Sociology and Political Science › Intergenerational and Educational Inequality Studies
Keywords
social causation, health selection, socioeconomic status, health disparities, life course, material wealth, vocational skills, old age, health transition, SHARELIFE

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review