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Understanding cognitive impairment in the U.S. through the lenses of intersectionality and (un)conditional cumulative (dis)advantage

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Listed:
  • Jo M. Hale

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Daniel C. Schneider

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Neil K. Mehta
  • Mikko Myrskylä

    (Max Planck Institute for Demographic Research, Rostock, Germany)

Abstract

Grounded in theories of intersectionality and cumulative (dis)advantage, we develop complementary formalizations of (dis)advantage to study disparities in cognitive impairment: Conditional Cumulative (Dis)Advantage that reflects inequalities in outcomes and Unconditional Cumulative (Dis)Advantage that additionally accounts for inequalities in opportunities. We study the properties of these formalizations and show that cumulative disadvantage does not imply cumulative advantage. Using these formalizations and incidence-based multistate models, we analyze the Health and Retirement Study to assess how racial/ethnic, nativity, gender, early-life adversity, and educational (dis)advantages accumulate into three important metrics for characterizing later-life cognitive impairment—lifetime risk, mean age at first impairment, and cognitive health expectancies. We find that the benefits and penalties of one (dis)advantage depend on positionality on the other axes of inequality. Black women and Latinas experience Conditional Cumulative Disadvantage in cognitive impairment: they are penalized more from having lower education than Whites. White men experience Conditional Cumulative Advantage: they benefit more from higher education than Blacks or Latinx. However, when accounting for racial/ethnic inequities in educational opportunities, results ubiquitously show Unconditional Cumulative Disadvantage. Our formalization provides a mathematical grounding for cumulative (dis)advantage, and the empirical results comprehensively document the multi-dimensional, intersecting axes of stratification that perpetuate inequities in cognitive impairment.

Suggested Citation

  • Jo M. Hale & Daniel C. Schneider & Neil K. Mehta & Mikko Myrskylä, 2022. "Understanding cognitive impairment in the U.S. through the lenses of intersectionality and (un)conditional cumulative (dis)advantage," MPIDR Working Papers WP-2022-029, Max Planck Institute for Demographic Research, Rostock, Germany.
    • Handle: RePEc:dem:wpaper:wp-2022-029
    DOI: 10.4054/MPIDR-WP-2022-029
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    References listed on IDEAS

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    1. Bauer, Greta R., 2014. "Incorporating intersectionality theory into population health research methodology: Challenges and the potential to advance health equity," Social Science & Medicine, Elsevier, vol. 110(C), pages 10-17.
    2. Angelo Lorenti & Christian Dudel & Jo M. Hale & Mikko Myrskylä, 2020. "Working and disability expectancies at old ages: the role of childhood circumstances and education," MPIDR Working Papers WP-2020-006, Max Planck Institute for Demographic Research, Rostock, Germany.
    3. Lisa L. Barnes & Robert S. Wilson & Liesi E. Hebert & Paul A. Scherr & Denis A. Evans & Carlos F. Mendes de Leon, 2011. "Racial Differences in the Association of Education With Physical and Cognitive Function in Older Blacks and Whites," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 66(3), pages 354-363.
    4. Mark Hayward & Bridget Gorman, 2004. "The long arm of childhood: The influence of early-life social conditions on men’s mortality," Demography, Springer;Population Association of America (PAA), vol. 41(1), pages 87-107, February.
    5. Gkiouleka, Anna & Huijts, Tim & Beckfield, Jason & Bambra, Clare, 2018. "Understanding the micro and macro politics of health: Inequalities, intersectionality & institutions - A research agenda," Social Science & Medicine, Elsevier, vol. 200(C), pages 92-98.
    6. Lorenti, Angelo & Dudel, Christian & Hale, Jo Mhairi & Myrskylä, Mikko, 2020. "Working and disability expectancies at older ages: the role of childhood circumstances and education," LSE Research Online Documents on Economics 106194, London School of Economics and Political Science, LSE Library.
    7. Eileen M. Crimmins & Jung Ki Kim & Kenneth M. Langa & David R. Weir, 2011. "Assessment of Cognition Using Surveys and Neuropsychological Assessment: The Health and Retirement Study and the Aging, Demographics, and Memory Study," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 66(suppl_1), pages 162-171.
    8. Jennifer Montez & Mark Hayward, 2014. "Cumulative Childhood Adversity, Educational Attainment, and Active Life Expectancy Among U.S. Adults," Demography, Springer;Population Association of America (PAA), vol. 51(2), pages 413-435, April.
    9. Gavin Turrell & John W. Lynch & George A. Kaplan & Susan A. Everson & Eeva-Liisa Helkala & Jussi Kauhanen & Jukka T. Salonen, 2002. "Socioeconomic Position Across the Lifecourse and Cognitive Function in Late Middle Age," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 57(1), pages 43-51.
    10. Kenneth F Ferraro & Patricia M Morton, 2018. "What Do We Mean by Accumulation? Advancing Conceptual Precision for a Core Idea in Gerontology," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 73(2), pages 269-278.
    11. Jo Mhairi Hale, 2017. "Cognitive Disparities: The Impact of the Great Depression and Cumulative Inequality on Later-Life Cognitive Function," Demography, Springer;Population Association of America (PAA), vol. 54(6), pages 2125-2158, December.
    12. Mehta, Neil & Preston, Samuel, 2016. "Are major behavioral and sociodemographic risk factors for mortality additive or multiplicative in their effects?," Social Science & Medicine, Elsevier, vol. 154(C), pages 93-99.
    13. Millimet, Daniel L. & Nieswiadomy, Michael & Ryu, Hang & Slottje, Daniel, 2003. "Estimating worklife expectancy: an econometric approach," Journal of Econometrics, Elsevier, vol. 113(1), pages 83-113, March.
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    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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