# Lifecourse Approach to Developmental Repercussions of Environmental Agents on Metabolic and Respiratory Health (LA DREAMERs)

> **NIH NIH UH3** · UNIVERSITY OF SOUTHERN CALIFORNIA · 2021 · $120,232

## Abstract

ABSTRACT
Background: Prenatal diet may contribute to metabolic alterations (e.g., insulin resistance) that could
influence fetal programming and, subsequently, birth weight, a known determinant of impaired development,
morbidity, and chronic disease risk such as obesity later in life1. Prenatal overall diet, as in a dietary pattern
(DP), derived particularly in relevance to fasting plasma glucose, an intermediate variable between diet and
birth weight, was found to be associated with birth weight2. These findings, however, are specific to
predominantly non-Hispanic white women, limiting generalizability of findings to other populations such as
Hispanic/Latina women who are at disproportionately greater risk of having adverse birth outcomes and
children with childhood obesity3. Specific aims: 1) Derive prenatal DPs in a racially/ethnically diverse pooled
sample from the two cohorts using RRR alternately with gestational weight gain (GWG) and fasting plasma
glucose (FG) as intermediate response variables and characterize resulting DPs based on higher-loading
foods; 2) Identify racial/ethnic differences in DPs by using the RRR approach in Aim 1 in groups stratified by
race/ethnicity and compare racial/ethnic-specific DPs with DPs derived in the combined sample; 3) Determine
whether racial/ethnic-specific prenatal DPs (Aim 2), versus those derived in a racially/ethnically diverse pooled
sample (Aim 1), better predict birth weight and large-for-gestational age (LGA) by comparing how well they
predict the outcomes within these racial/ethnic groups. Methods: Using existing data from two ECHO
pregnancy cohorts, MyPyramid Equivalent food group daily intakes will be averaged across two or more
Automated Self-Administered 24-hr dietary recalls and used as input variables in a reduced-rank regression
model designed to derive linear combinations of foods that maximally explain the variability in two intermediate
response variables (GWG and FG) hypothesized to be on the causal pathway between prenatal diet and the
outcomes of interest (Aim 1). Additionally, DPs will be characterized based on higher-loading foods. The same
approach from Aim 1 will be used in Aim 2 stratified by race/ethnicity (non-Hispanic white, Hispanic/Latina). DP
differences by race/ethnicity will be based on higher food group factor loadings (>0.20) for similar food groups.
In each racial/ethnic group, two sets of multivariable linear regression (birth weight) and logistic regression
(LGA) adjusted for relevant covariates will be performed. The first set of models will include DPs derived from
Aim 1 in each racial/ethnic group, while the second set will include DPs derived from Aim 2 in each
racial/ethnic group. Qualitative comparisons between magnitude and strength of associations between sets of
DPs in each racial/ethnic group will be performed to determine whether there are meaningful differences in
prediction of birth weight between racial/ethnic-specific DPs and those derived from a m...

## Key facts

- **NIH application ID:** 10412804
- **Project number:** 3UH3OD023287-06S1
- **Recipient organization:** UNIVERSITY OF SOUTHERN CALIFORNIA
- **Principal Investigator:** Theresa M Bastain
- **Activity code:** UH3 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $120,232
- **Award type:** 3
- **Project period:** 2016-09-21 → 2023-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10412804

## Citation

> US National Institutes of Health, RePORTER application 10412804, Lifecourse Approach to Developmental Repercussions of Environmental Agents on Metabolic and Respiratory Health (LA DREAMERs) (3UH3OD023287-06S1). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10412804. Licensed CC0.

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