Abstract P126: Sociodemographic Predictors of Diet Quality During Adolescence

Abstract

Introduction: Optimal nutrition is critical for near-term health, during periods of growth in childhood, and long-term health in adulthood (e.g., heart disease). The Healthy Eating Index (HEI) is an indicator of diet quality that is aligned with the Dietary Guidelines for Americans, which declines in U.S. children aged 2-18 years. Effective nutrition interventions are needed to address this decline in diet quality. Understanding sociodemographic determinants of diet quality in adolescents will help to inform such interventions. We aimed to describe changes in diet quality and to determine if sociodemographic factors associated with diet quality in adolescence. Methods: Participants of the Sleep and Growth Study (S-Grow) completed three 24-hour diet recalls in 8 th and 9 th grade. The diet data were processed using Nutrient Data System for Research software to calculate HEI-2015 score (range: 0-100, with a higher score indicating greater diet quality) using 13 food group components. Linear mixed effect models were used to assess: 1) changes in HEI-2015 score (and individual components) from 8 th to 9 th grade, 2) sociodemographic associations with HEI-2015 score (sex, race, body mass index [BMI], and household income), and 3) sociodemographic factor-by-grade interactions to determine if any associations differed in 8 th and 9 th grades. Results: The HEI-2015 score was stable from 8 th (44.6) to 9 th grade (45.3). Similarly, HEI component scores were stable from 8 th to 9 th grade, except for an increase in green vegetables (beta=0.37, P<0.05) and a decline in added sugars (beta=-0.50, P<0.05). Black (compared to White) adolescents and those living in households with <$40K (compared to >$99K) annual income were associated with lower overall diet quality (beta=-3.28, P<0.05; beta=-4.90, P<0.05; respectively). Male (compared to female) sex was associated with higher total dairy intake (beta=1.74, P<0.001); those with obesity (compared to normal weight) were more likely to have lower seafood intake (beta=-1.00, P<0.001) and higher refined grains intake (beta=1.26, P<0.05). The interaction analyses revealed that some household income and BMI associations with changes in HEI outcomes from 8 th and 9 th grades were distinct. For example, total fruit intake declined from 8 th to 9 th grade, but specifically among adolescents living in households with incomes of $40-69K (beta=-0.77, P=0.02) and for adolescents with obesity (beta=-1.03, P=0.003). Conclusion: Diet quality was consistently suboptimal in 8 th and 9 th grades (i.e., 45/100). Further, we detected sex, race, and household income disparities in diet quality. Overall, these data will help to inform future intervention efforts to improve and prevent reductions in diet quality in adolescents.