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).
• We know less about how health disparities are
the outcome of long-term, accumulative
processes.
• Individual patterning of trajectories according to
social statuses.
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)
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)
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)
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)
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
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)
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)
Research Questions
1. What is the effect of childhood disadvantage
on health risk trajectories in middle age?
2. To what extent do adult resources and health
behaviours alter the pathway between
childhood disadvantage and health?
Data Source
• Panel Study of Income Dynamics (PSID)
▫ 1968-present
▫ Representative sample of U.S. households
▫ Followed split-offs from original sample
households
Sample
• Adult children of original PSID households
• Baby Boom cohorts (born 1950-1964 in this analysis)
▫ 2007: Ages 43-56
• N=4,241
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.
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
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
Health Risk Trajectories
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
Childhood Disadvantage LCA
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
Estimated Odds Ratios for Multinomial Logistic Regression Model Predicting
LCA Membership in Health Risk Trajectories (Ref=Low Risk)
Model Includes: Childhood Disadv + Controls
3
2.81
2.5
2.25
2
1.5
1.44
1.41
1.39
1
1
0.5
0
High Risk
Childhood Disadv
Increasing Risk
Child health poor
South
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
3
2.49
2.5
2.05
2
1.7
1.63
1.5
1.41 1.42
N.S.
1.3
1.39
1.38 1.35
N.S.
1
High Risk
Increasing Risk
0.5
Childhood Disadv
Child health poor
South
Income below med
Wealth below med
< High school
High School
1.2
1.09
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
3
2.85
2.5
1.94
2
1.5
1.52
N.S.
1.31
1.24
0.59
1.23
0.8
N.S.
1
High Risk
Increasing Risk
0.5
Childhood Disadv
Child health poor
South
Exercise
Obesity
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.
Conclusions
• Methodological challenges:
▫ Missing data, attrition and selection
▫ Measurement
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.