Assessing the multi-dimensional effects of air pollution on maternal complications and birth outcomes: A structural equation modeling approach

Abstract

Objective

This cross-sectional study aims to investigate the direct and indirect relationships between exposure to a metal mixture in air and adverse pregnancy outcomes across gestational stages.

Methods

With 46,829 births in 2021 in two Florida counties and Air Quality System data, structural equation modeling was used to construct latent metal mixtures in PM_2.5 and unravel their effects on pregnancy complications (preeclampsia and gestational diabetes) and birth outcomes (low birth weight and preterm birth risks).

Results

A latent variable featuring seven metals (Aluminum, Calcium, Iron, Magnesium, Manganese, Silicon, Vanadium) was identified through the measurement model. The latent metal mixture exposure had direct effects on gestational diabetes and preterm birth (1st trimester, 2nd trimester), low birth weight (1st trimester), and preeclampsia (2nd trimester). When considering total effects, the effects on low birth weight in the 1st trimester and on preeclampsia in 2nd trimester were masked, and the latent metal mixture increased the low-birth-weight risk in 2nd trimester by 2 % (OR = 1.02, 95 % CI = [1.00, 1.03]).

Conclusion

This study reveals time-dependent associations between a metal mixture in PM_2.5 exposure and adverse pregnancy outcomes, highlights the need to address dust in PM_2.5, and provides additional evidence for understanding the pathway of the pollution effects on fetal health.