4.4 Article

Evaluating the Cumulative Impact of Childhood Misfortune: A Structural Equation Modeling Approach

Journal

SOCIOLOGICAL METHODS & RESEARCH
Volume 50, Issue 3, Pages 1073-1109

Publisher

SAGE PUBLICATIONS INC
DOI: 10.1177/0049124119875957

Keywords

structural equation modeling; childhood adversity; latent variable; formative construct; cumulative disadvantage

Funding

  1. National Institute on Aging [R01AG043544]

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This study introduces an alternative approach within the structural equation modeling framework to examine the impact of childhood misfortune on adult health outcomes. Results suggest that the traditional method may underestimate the effects of childhood misfortune on adult health. This approach also allows for testing the mediating effects of variables and the moderating effects of protective factors on childhood misfortune.
Most studies of the early origins of adult health rely on summing dichotomously measured negative exposures to measure childhood misfortune (CM), neglect, adversity, or trauma. There are several limitations to this approach, including that it assumes each exposure carries the same level of risk for a particular outcome. Further, it often leads researchers to dichotomize continuous measures for the sake of creating an additive variable from similar indicators. We propose an alternative approach within the structural equation modeling (SEM) framework that allows differential weighting of the negative exposures and can incorporate dichotomous and continuous observed variables as well as latent variables. Using the Health and Retirement Study data, our analyses compare the traditional approach (i.e., adding indicators) with alternative models and assess their prognostic validity on adult depressive symptoms. Results reveal that parameter estimates using the conventional model likely underestimate the effects of CM on adult health outcomes. Additionally, while the conventional approach inhibits testing for mediation, our model enables testing mediation of both individual CM variables and the cumulative variable. Further, we test whether cumulative CM is moderated by the accumulation of protective factors, which facilitates theoretical advances in life course and social inequality research. The approach presented here is one way to examine the cumulative effects of early exposures while attending to diversity in the types of exposures experienced. Using the SEM framework, this versatile approach could be used to model the accumulation of risk or reward in many other areas of sociology and the social sciences beyond health.

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