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Prenatal dietary quality and child health outcomes across various census tracts in Oregon and Washington

Wed, April 7, 10:15 to 11:15am EDT (10:15 to 11:15am EDT), Virtual

Abstract

OBJECTIVE: Lack of access to affordable, nutritious food is a concerning public health issue, particularly for pregnant people, as prenatal nutrition has long-term implications for prenatal and child health (Sullivan et al., 2014). Residing in “food deserts” increases obesity risk (Townsend et al., 2001) and is related to a range of pregnancy morbidities (Tipton et al., 2020). Yet the mechanisms through which food deserts adversely affect prenatal and child health remains largely untested. We hypothesize that the adverse effect of food desert proximity operates in part via prenatal dietary quality, specifically due to increased intake of pro-inflammatory foods (e.g., high in saturated fat). We will investigate this by coupling two novel types of data (in conjunction with gold-standard methods for assessing prenatal diet): geocoded data that captures proximity to food deserts (Bordor et el., 2010) and neighborhood SES (Singh et al., 2003) and dietary inflammatory index (DII) values (a novel way of quantifying the pro-inflammatory nature of an individual’s diet) (Shivappa et al., 2014). These types of data have never before been combined and applied to the study of prenatal diet. We will relate these data to birth outcomes (gestational age/weight at delivery, mode of delivery, birth complications), and child temperament (negative affect, surgency, regulation) and developmental milestone data (motor and cognitive).

STUDY DESIGN: We will present data from an ongoing longitudinal study of pregnant participants. In the 2nd and 3rd trimesters, participants complete 3 unannounced 24-hour dietary recalls, yielding information about macronutrient/micronutrient intake that will be used to calculate DII values (higher DIIs indicate more pro-inflammatory diets). Birth outcome data will come from medical records. At 1, 6, and 12 months postpartum, participants complete the Infant Behavior Questionnaire (IBQ-R; Gartstein et al., 2003) and the Ages and Stages Questionnaire (ASQ; Bricker et al., 1999) to track infant temperament and development. Participant addresses will be used to assign census tract codes using a HIPAA compliant system. Census variables will be used to determine food security and neighborhood SES based on the USDA’s Food Access Research Atlas and the Area Deprivation Index. Covariates/moderators include income, education, race/ethnicity, and birthing-parent body composition, assessed using air displacement plethysmography. Hypotheses will be tested using multiple regression and mediation analysis, where birth/child outcomes will be the dependent variables, measures of prenatal diet the mediators, and geocoded food desert data and covariates are the independent variables. Based on projected enrollment, 2nd trimester data will be available for N=300, 3rd trimester for N=282 and birth outcome data for N=264 participants by March, providing adequate statistical power for planned analyses. A correction for multiple comparisons will be applied, as appropriate. Appropriate missing data handling will be implemented.

PRELIMINARY DATA/FUTURE ANALYSES: Preliminary data (Table 1) support the hypothesized link between prenatal pro-inflammatory dietary intake (e.g., higher saturated fat, DII) and aspects of child temperament and motor and communication development. If accepted, we will complete the proposed analyses with geocoded data (to be added).

Authors