Prevalence of Adverse Childhood Experiences by Income, Race/Ethnicity, and Gender: An Intersectional Analysis

• In Event: Ethnic Racial Identity

Abstract

Background and Purpose: Research has shown that adverse childhood experiences (ACEs) are widely distributed in the United States. Less is known about disparities in ACEs among population subgroups, and no known studies have taken an intersectional approach to analyzing the distribution of ACEs across overlapping social positions such as class, race/ethnicity, and gender. To address this gap, this study applied conventional statistical modeling and a novel intercategorical approach called multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) to examine variation in the prevalence of ACEs by poverty status, race/ethnicity, and gender.

Methods: Data were derived from the National Longitudinal Study of Adolescent to Adult Health (Add Health), a nationally representative panel study that was launched in 1994. Survey data collected at waves 1, 2, and 4 were used to create 11 dichotomous ACE variables, including five forms of child maltreatment (physical abuse, sexual abuse, emotional abuse, physical neglect, emotional neglect) and six related forms of adversity (alcohol/drug abuse, mental illness, incarceration, divorce/separation, violent crime victimization, parent/sibling death). Participant responses were used to code Hispanic ethnicity and four non-Hispanic groups: American Indian, Asian/Pacific Islander, Black, and White. Poverty status was defined by an income-to-needs ratio below the 1994 national poverty threshold or receipt of means-tested public benefits (e.g., food stamps). Descriptive analyses were performed to estimate the prevalence of each ACE and a cumulative ACE score in each social and economic category. Interactions among social positions were tested using conventional methods of two-way ANOVAs and ordinary least squares (OLS) regressions. Finally, MAIHDA using Bayesian multilevel modeling was conducted to estimate variation in ACEs across 20 social strata composed of intersections among two income groups (poor/non-poor), five racial/ethnic groups, and two gender groups.

Results: In the full sample (N = 15,719), 71.9% reported at least one ACE and 44.7% reported multiple ACEs. The mean cumulative ACE score was highest among American Indians (M = 2.33), followed by Blacks (M = 2.00), Hispanics (M = 1.86), Asians/Pacific Islanders (M = 1.59), and Whites (M = 1.55). Poor participants reported 2.40 ACEs on average, while non-poor participants reported 1.49. There was no difference in ACE scores between males and females (M = 1.68). However, among female participants, there was a significant interaction effect indicating that disparities in ACEs between poor and non-poor participants were greater among Whites than other racial/ethnic groups. OLS regressions confirmed significant poverty-by-race/ethnicity interactions; no gender-by-poverty or gender-by-race interactions were observed. MAIHDA results indicated that 9.9% of total variance in ACEs was attributable to between-stratum (i.e., intersectional) effects over and above the main effects of poverty, race/ethnicity, and gender. The strata comprised of poor, white females had significantly higher ACE scores than their predicted values.

Conclusions and Implications: This study illustrates the importance of applying intersectional methods when analyzing disparities in the general population. Potential explanations for the findings will be reviewed, including the differential assortment hypothesis, which reverses the implied causal order and posits that exposure to childhood adversity may increase the risk of poverty—especially among Whites.

Authors

• Changyong Choi, University of Wisconsin - Milwaukee
  Presenting Author

• Joshua Mersky, University of Wisconsin - Milwaukee
  Non-Presenting Author

• Colleen Janczewski, University of Wisconsin - Milwaukee
  Non-Presenting Author