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Allostatic Load and Exposure Histories of Disadvantage

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  • Lucy Prior

    (School of Geographical Sciences, University of Bristol, Bristol BS8 1SS, UK)

Abstract

The stress pathway posits that those in disadvantaged circumstances are exposed to a higher degree of stressful experiences over time resulting in an accumulated biological burden which subsequently relates to poorer health. Trajectories of disadvantage, in the form of neighbourhood deprivation and structural social capital, are evaluated in their relation to allostatic load representing the cumulative “wear and tear” of chronic stress. This paper uses data from the British Household Panel Survey and Understanding Society in a latent class growth analysis. We identify groups of exposure trajectories over time using these classes to predict allostatic load at the final wave. The results show that persistent exposure to higher deprivation is related to worse allostatic load. High structural social capital over time relates to lower allostatic load, in line with a stress buffering effect, though this relationship is not robust to controlling for individual sociodemographic characteristics. By demonstrating a gradient in allostatic load by histories of deprivation, this analysis supports a biological embedding of disadvantage through chronic exposure to stressful environments as an explanation for social health inequalities.

Suggested Citation

  • Lucy Prior, 2021. "Allostatic Load and Exposure Histories of Disadvantage," IJERPH, MDPI, vol. 18(14), pages 1-17, July.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:14:p:7222-:d:589270
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    References listed on IDEAS

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    1. Johnson, Sarah C. & Cavallaro, Francesca L. & Leon, David A., 2017. "A systematic review of allostatic load in relation to socioeconomic position: Poor fidelity and major inconsistencies in biomarkers employed," Social Science & Medicine, Elsevier, vol. 192(C), pages 66-73.
    2. Vermunt, Jeroen K., 2010. "Latent Class Modeling with Covariates: Two Improved Three-Step Approaches," Political Analysis, Cambridge University Press, vol. 18(4), pages 450-469.
    3. Krieger, Nancy, 1994. "Epidemiology and the web of causation: Has anyone seen the spider?," Social Science & Medicine, Elsevier, vol. 39(7), pages 887-903, October.
    4. Riumallo-Herl, Carlos Javier & Kawachi, Ichiro & Avendano, Mauricio, 2014. "Social capital, mental health and biomarkers in Chile: Assessing the effects of social capital in a middle-income country," Social Science & Medicine, Elsevier, vol. 105(C), pages 47-58.
    5. Boardman, Jason D, 2004. "Stress and physical health: the role of neighborhoods as mediating and moderating mechanisms," Social Science & Medicine, Elsevier, vol. 58(12), pages 2473-2483, June.
    6. Yip, Winnie & Subramanian, S.V. & Mitchell, Andrew D. & Lee, Dominic T.S. & Wang, Jian & Kawachi, Ichiro, 2007. "Does social capital enhance health and well-being? Evidence from rural China," Social Science & Medicine, Elsevier, vol. 64(1), pages 35-49, January.
    7. Lemelin, Emily T. & Diez Roux, Ana V. & Franklin, Tracy G. & Carnethon, Mercedes & Lutsey, Pamela L. & Ni, Hanyu & O'Meara, Ellen & Shrager, Sandi, 2009. "Life-course socioeconomic positions and subclinical atherosclerosis in the multi-ethnic study of atherosclerosis," Social Science & Medicine, Elsevier, vol. 68(3), pages 444-451, February.
    8. Kwan, Mei-Po, 2009. "From place-based to people-based exposure measures," Social Science & Medicine, Elsevier, vol. 69(9), pages 1311-1313, November.
    9. Robinette, Jennifer W. & Charles, Susan T. & Gruenewald, Tara L., 2018. "Neighborhood cohesion, neighborhood disorder, and cardiometabolic risk," Social Science & Medicine, Elsevier, vol. 198(C), pages 70-76.
    10. Seeman, Melvin & Stein Merkin, Sharon & Karlamangla, Arun & Koretz, Brandon & Seeman, Teresa, 2014. "Social status and biological dysregulation: The “status syndrome” and allostatic load," Social Science & Medicine, Elsevier, vol. 118(C), pages 143-151.
    11. Schulz, A.J. & Mentz, G. & Lachance, L. & Johnson, J. & Gaines, C. & Israel, B.A., 2012. "Associations between socioeconomic status and allostatic load: Effects of neighborhood poverty and tests of mediating pathways," American Journal of Public Health, American Public Health Association, vol. 102(9), pages 1706-1714.
    12. Benzeval, Michaela & Davillas, Apostolos & Kumari, Meena & Lynn, Peter, 2014. "Understanding Society: The UK Household Longitudinal Study Biomarker User Guide and Glossary," MPRA Paper 114713, University Library of Munich, Germany.
    13. Ana Isabel Ribeiro & Joana Amaro & Cosima Lisi & Silvia Fraga, 2018. "Neighborhood Socioeconomic Deprivation and Allostatic Load: A Scoping Review," IJERPH, MDPI, vol. 15(6), pages 1-15, May.
    14. Gustafsson, P.E. & Miguel, S.S. & Janlert, U. & Theorell, T. & Westerlund, H. & Hammarström, A., 2014. "Life-Course accumulation of neighborhood disadvantage and allostatic load: Empirical integration of three social determinants of health frameworks," American Journal of Public Health, American Public Health Association, vol. 104(5), pages 904-910.
    15. de Vries, Sjerp & van Dillen, Sonja M.E. & Groenewegen, Peter P. & Spreeuwenberg, Peter, 2013. "Streetscape greenery and health: Stress, social cohesion and physical activity as mediators," Social Science & Medicine, Elsevier, vol. 94(C), pages 26-33.
    16. Bolck, Annabel & Croon, Marcel & Hagenaars, Jacques, 2004. "Estimating Latent Structure Models with Categorical Variables: One-Step Versus Three-Step Estimators," Political Analysis, Cambridge University Press, vol. 12(1), pages 3-27, January.
    17. Walsemann, Katrina M. & Goosby, Bridget J. & Farr, Deeonna, 2016. "Life course SES and cardiovascular risk: Heterogeneity across race/ethnicity and gender," Social Science & Medicine, Elsevier, vol. 152(C), pages 147-155.
    18. Wilkinson, Richard G. & Pickett, Kate E., 2007. "The problems of relative deprivation: Why some societies do better than others," Social Science & Medicine, Elsevier, vol. 65(9), pages 1965-1978, November.
    19. Geoffrey M. Jacquez & Clive E. Sabel & Chen Shi, 2015. "Genetic GIScience: Toward a Place-Based Synthesis of the Genome, Exposome, and Behavome," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 105(3), pages 454-472, May.
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    1. Stephen Jivraj & Owen Nicholas & Emily T. Murray & Paul Norman, 2021. "Life Course Neighbourhood Deprivation and Self-Rated Health: Does It Matter Where You Lived in Adolescence and Do Neighbourhood Effects Build Up over Life?," IJERPH, MDPI, vol. 18(19), pages 1-13, September.
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    3. Shawna Beese & Julie Postma & Janessa M. Graves, 2022. "Allostatic Load Measurement: A Systematic Review of Reviews, Database Inventory, and Considerations for Neighborhood Research," IJERPH, MDPI, vol. 19(24), pages 1-23, December.

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