Psychosocial Correlates of Childhood Body Mass Index: Racial and Ethnic Differences

TL;DR

The study finds that different racial and ethnic groups of children have unique psychosocial and socioeconomic factors linked to their body mass index.

Contribution

The study reveals race/ethnicity-specific psychosocial and socioeconomic correlates of BMI in children, highlighting the need for tailored interventions.

Findings

Non-Latino White children with higher family income and parental education had lower BMI.

Latino and Asian children showed strong negative associations between family income and BMI.

Tailored interventions are needed due to significant racial/ethnic differences in BMI correlates.

Abstract

To examine racial/ethnic differences in the associations of family socioeconomic status (SES), neighborhood SES, and inhibitory control with body mass index (BMI) in 9–10-year-old children using data from the Adolescent Brain Cognitive Development (ABCD) study.

This cross-sectional study included a diverse sample of children aged 9–10 years, representing non-Latino White, Black, Latino, Asian, and Other racial/ethnic groups. BMI was the primary outcome. Key predictors were family SES, neighborhood SES, and inhibitory control. Multivariable regression models were stratified by race/ethnicity to identify group-specific associations.

Race/ethnic groups differed in psychosocial correlates of childhood BMI at age 9 and 10. Among non-Latino White children, higher family income (B = −0.086, p < 0.001), higher parental education (B = −0.069, p < 0.001), and living in a married household (B = −0.079, p < 0.001) were associated with lower BMI. Additionally, the presence of healthy food options in the zip code (B = −0.030, p = 0.032) was linked to lower BMI, while lack of planning (B = 0.032, p = 0.030) was associated with higher BMI. For non-Latino Black children, positive urgency (B = −0.068, p = 0.022) was negatively associated with BMI, while other factors such as family SES and neighborhood SES did not show significant associations. For Latino children, higher family income (B = −0.093, p = 0.001) and parental education (B = −0.099, p < 0.001) were associated with lower BMI. In this group, male gender (B = 0.043, p = 0.033) was associated with higher BMI. Among Asian children, higher family income (B = −0.199, p = 0.006) and parental education (B = −0.144, p = 0.037) were significantly associated with lower BMI. For children in the “Other” racial/ethnic category, higher family income (B = −0.101, p = 0.023), living in a married household (B = −0.076, p = 0.026), and higher median income in the zip code (B = −0.083, p = 0.013) were associated with lower BMI. In this group, male children had lower BMI compared to females (B = −0.089, p = 0.001).

The findings highlight substantial racial/ethnic differences in the psychosocial and socioeconomic correlates of BMI in children. There is a need for tailored interventions that target social determinants of childhood high BMI. One size does not fit all.

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