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Geographic and Environmental Differences in Associations Between Food Insecurity and Nutritional and Inflammatory Biomarkers Among Pregnant Participants in the All of Us Research Program

Sep 2026 · Nutrients · Vol 18, pp. 2965 · 0 citations · 71 references
Medicine

TL;DR

This study found that FI was more prevalent among rural participants than urban participants, and was associated with higher body mass index, higher non-fasting glucose, higher C-reactive protein, and lower high-density lipoprotein cholesterol.

Abstract

Background/Objectives: Food insecurity (FI) affects a substantial proportion of pregnant individuals in the United States and varies across geographic contexts. Rural and urban communities differ in food access, socioeconomic conditions, and environmental exposures, yet how these differences relate to maternal biology remain misunderstood. Methods: This study examined associations between FI, geographic context, and metabolic, nutritional, and inflammatory biomarkers among pregnant participants in the Southeastern United States (SE-US) using data from the All of Us (AoU) Research Program. Survey, clinical, and laboratory data were integrated with ZIP3-level geographic and food environment indicators. Analyses were conducted using biomarker-specific complete-case cohorts and multivariable regression models. Results: This study found that FI was more prevalent among rural participants than urban participants. However, in the overall cohort, FI was associated with higher body mass index, higher non-fasting glucose, higher C-reactive protein, and lower high-density lipoprotein cholesterol. Pregnant food-insecure participants also exhibited lower concentrations of vitamin B12, albumin, vitamin D, and folate, while ferritin did not differ. Stratified analyses demonstrated variability in these associations by urbanicity, with stronger and more consistent differences observed in urban populations and fewer significant differences in rural settings. Conclusions: Limitations of this study include potential residual confounding, EHR-related selection bias, exposure misclassification, and limited generalizability. Despite the limitations, recent self-reported household FI, assessed at enrollment and referring to the preceding 12 months, was associated with differences in several metabolic and nutritional biomarkers, with patterns varying by geographic context. Further longitudinal research is needed to clarify these associations and inform targeted interventions.

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