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

Autor/inn/en	Mustillo, Sarah; Li, Miao; Ferraro, Kenneth F.
Titel	Evaluating the Cumulative Impact of Childhood Misfortune: A Structural Equation Modeling Approach
Quelle	In: Sociological Methods & Research, 50 (2021) 3, S.1073-1109 (37 Seiten) PDF als Volltext Verfügbarkeit
Zusatzinformation	ORCID (Mustillo, Sarah)
Sprache	englisch
Dokumenttyp	gedruckt; online; Zeitschriftenaufsatz
ISSN	0049-1241
DOI	10.1177/0049124119875957
Schlagwörter	Structural Equation Models; Child Neglect; Trauma; Disadvantaged; Risk; Measurement; Comparative Analysis; Child Development; Validity; Depression (Psychology); Symptoms (Individual Disorders); Social Differences; Rewards; Correlation; Health; Retirement; Socioeconomic Status; Disabilities; Adults; Parent Child Relationship; Child Abuse; Smoking; Social Support Groups; Physical Activities; Religious Factors; Prediction; Followup Studies; Longitudinal Studies + Suchen Sie Ihr Suchwort? Kindesvernachlässigung; Risiko; Messverfahren; Kindesentwicklung; Gültigkeit; Psychiatrische Symptomatik; Sozialer Unterschied; Reward; Belohnung; Korrelation; Gesundheit; Pensionierung; Socio-economic status; Sozioökonomischer Status; Handicap; Behinderung; Parents-child relationship; Parent-child-relation; Parent-child relationship; Eltern-Kind-Beziehung; Abuse of children; Abuse; Child; Children; Kindesmissbrauch; Missbrauch; Kind; Kinder; Rauchen; Social support; Soziale Unterstützung; Vorhersage; Follow-up studies; Kontaktstudium; Longitudinal study; Longitudinal method; Longitudinal methods; Längsschnittuntersuchung
Abstract	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. (As Provided).
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Erfasst von	ERIC (Education Resources Information Center), Washington, DC
Update	2024/1/01