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The Link Between Childhood Adversity and Adult Health Risk Trajectories. Andrea Willson Kim Shuey The University of Western Ontario. Understanding Health from a Life Course Perspective. Health is positively associated with socioeconomic status (SES).

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The Link Between Childhood Adversity and Adult Health Risk Trajectories


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    1. The Link Between Childhood Adversity and Adult Health Risk Trajectories Andrea Willson Kim Shuey The University of Western Ontario

    2. Understanding Health from a Life Course Perspective • Health is positively associated with socioeconomic status (SES). • We know less about how health disparities are the outcome of long-term, accumulative processes. • Individual patterning of trajectories according to social statuses.

    3. Cumulative Dis/Advantage Theory • Process through which • a favorable relative position generates further gains across the life course • Initial disadvantage accumulates over time, generating further disadvantage • Results in growth of the advantage of one individual or group relative to another over time (Eg., Dannefer 1987; 2003; Merton 1968; O’Rand 1996)

    4. Cumulative Dis/Advantage & Health • Health inequalities follow a process of cumulative dis/advantage • Early life advantage/disadvantage generates diverging trajectories and widening health disparities over time • (e.g., Willson et al. 2007; Shuey & Willson 2008; MacLean 2010)

    5. Cumulative Inequality • “Life course trajectories are influenced by early and accumulated inequalities but can be modified by available resources, perceived trajectories, and human agency.” (Ferraro and Shippee 2009)

    6. Cumulative Inequality • Social systems generate inequality • Importance of childhood conditions • Influenced by genes and environment • Trajectories may be modified by resources and human agency (Ferraro and Shippee 2009)

    7. The Long-term Effects of Childhood Economic Disadvantage • Poor children have: • Higher infant mortality rates • More asthma • More physical and mental health problems • Lower self-esteem • Lower grades • Lower high school grad rates • Higher unemployment • Lower wages • Higher rates of poverty

    8. Cumulative Inequality & the Role of Childhood • Research has focused on role of childhood circumstances and cumulative processes in adulthood (Eg. Hayward & Gorman 2004; Hamil-Luker & O’Rand 2007)

    9. Measuring Childhood Economic Disadvantage • Perhaps more important than overall level of deprivation: • Persistence/duration • Timing (early or late in childhood) • Trajectory (improving or deteriorating) (Wagmiller et al. 2006)

    10. Research Questions • What is the effect of childhood disadvantage on health risk trajectories in middle age? • To what extent do adult resources and health behaviours alter the pathway between childhood disadvantage and health?

    11. Data Source • Panel Study of Income Dynamics (PSID) • 1968-present • Representative sample of U.S. households • Followed split-offs from original sample households

    12. Sample • Adult children of original PSID households • Baby Boom cohorts (born 1950-1964 in this analysis) • 2007: Ages 43-56 • N=4,241

    13. Analysis • Latent Class Analysis • Collins & Lanza 2010; Vermunt & Magidson 2005 • SAS Proc LCA (The Methodology Center, Penn State U) • Person-centered approach. • Sorts individuals into mutually exclusive groups based on responses to a set of indicators. • Detects associations among variables due to an unmeasured, latent source of variation.

    14. Analysis • Latent Class Analysis • Steps: • Estimate LCA for childhood disadvantage • Estimate baseline LCA of health risk trajectories • Use childhood disadvantage classes and other covariates to estimate multinomial logistic regression LCA of health risk trajectories

    15. Variables • DV: • Latent Class Analysis • Health risk trajectories (Hamil-Luker & O’Rand 2005 ) • 5 Physician-diagnosed health conditions, 1999-2007 • Chronic condition=1 if any diagnosis in a survey wave • Respondents ages 43-56 • Age and gender controlled

    16. Health Risk Trajectories

    17. Variables • IVs: • Latent Class Analysis: Childhood Disadvantage • Indicators • Low income (averaged income <= 150% of U.S. poverty line) • Receipt of public assistance • Unemployed father • Single parent household • Ages 13-17

    18. Childhood Disadvantage LCA

    19. Variables • IVs: • Region of childhood (ever in the South) • Childhood health fair/poor (retrospective) • Adult SES • Education (in 1999) • Below-median average income (1992-1999) • Below-median average wealth (1992-1999) • Race (Non-Hispanic White vs. Non-white) • Sex • Age in 1999 • Adult health risk behaviors (1999-2007) • Smoking, physical activity, obesity

    20. Estimated Odds Ratios for Multinomial Logistic Regression Model Predicting LCA Membership in Health Risk Trajectories (Ref=Low Risk)Model Includes: Childhood Disadv + Controls

    21. Estimated Odds Ratios for Multinomial Logistic Regression Model Predicting LCA Membership in Health Risk Trajectories (Ref=Low Health Risk)Model Includes: Childhood Disadv + Adult SES + Controls

    22. Estimated Odds Ratios for Multinomial Logistic Regression Model Predicting LCA Membership in Health Risk Trajectories (Ref=Low Health Risk)Model Includes: Childhood Disadv + Adult SES + Adult Health Behaviours + Controls

    23. Conclusions • Childhood disadvantage has long-term, negative consequences for health. • But, pathways from childhood socioeconomic conditions to adult health may be mediated by resources and health behaviours in adulthood.

    24. Conclusions • Methodological challenges: • Missing data, attrition and selection • Measurement

    25. Conclusions • Broader goals: • Further our understanding of the mechanisms through which inequalities in health are perpetuated or alleviated across the life course and across generations. • Inform policies targeting early life inputs.