Exploring Provider-Level Socio-Demographic Determinants of Diet Quality of Preschool Aged Children Attending Family Child Care Homes

Abstract

Abstract Objectives To measure the dietary quality of meals and snacks consumed by preschool-aged children (2- to -5 years old) in family child care homes (FCCH) and explore whether dietary quality differs by sociodemographic characteristics and acculturation of FCCH providers. Methods This study used baseline data from a cluster-randomized trial, Healthy Start/Comienzos Sanos. Surveys including demographic characteristics were completed with FCCH providers. Food and beverage consumption was measured using the Dietary Observation in Child Care, then Healthy Eating Index (HEI) 2015 scores were calculated. Differences in mean HEI-2015 scores by sociodemographic characteristics were calculated using one-way ANOVAs. Multiple linear regression models were then fit for statistically significant variables. Post-hoc ANOVA's were run to explore mean differences by HEI sub-components. Results There were statistically significant differences in mean total HEI scores by income (<$25,000: HEI: 64.8 vs. $25,001-$50,000: 62.9 vs. $75,001 or more: 56.2, P = 0.03); ethnicity (Latinx: 64.4 vs. Non-Latinx: 56.6, P = 0.002); language spoken in childcare (Spanish: 64.4 vs. English: 59.6, P = 0.02); language spoken outside of childcare (Spanish: 64.3; vs. English: 58.6, P = 0.005). Results from multiple linear regression models revealed that higher provider income ($75,001 or more) was negatively and significantly associated with total HEI scores (b = −9.8, SE = 3.7, P = 0.009) vs. lower income (less than $25,000). There were also differences in the HEI greens/beans, total protein, and seafood/plant protein scores across ethnicity and language. Conclusions Provider income, ethnicity and language were important factors in what children consume in FCCH. Future studies should aim to better understand how these provider sociodemographic factors are related to meal and snack preparation/provision in order to better tailor interventions. Funding Sources National Institutes of Health- National Heart, Lung, Blood Institute, NationalInstitutes of Health, HL123016.