Air Pollution Exposure and Birth Weight in the ECHO Cohort.
Abstract
IMPORTANCE: Prior studies report negative associations between prenatal exposure to fine particulate matter (ie, aerodynamic diameter <2.5 µg; PM2.5) and birth weight, but have typically averaged exposure across pregnancy, which may not reveal windows of susceptibility. OBJECTIVE: To identify windows of prenatal susceptibility to PM2.5. DESIGN, SETTING, AND PARTICIPANTS: This was a retrospective analysis of a prospectively enrolled cohort study. Participants were enrolled at 1 of 50 sites participating in the US Environmental Influences on Child Health Outcomes Cohort. The study included full-term, singleton births occurring between September 2003 and December 2021. Statistical analyses were conducted from March 2024 to February 2025. EXPOSURES: Daily residential PM2.5 exposure was estimated using a machine-learning model covering the contiguous US and mean exposure estimates were calculated for each week of pregnancy. MAIN OUTCOMES AND MEASURES: Bayesian distributed lag interaction models were used to examine cumulative and week-specific associations between PM2.5 exposure and birth weight for gestational age (BWGA) z scores. Interactions with sex, race and ethnicity, and region were also examined. RESULTS: The sample of 16 868 mother-newborn pairs (maternal mean [SD] age, 30.4 [5.5] years; 605 [3.6%] Asian, 2197 [13.0%] Black or Black-Hispanic, 3407 [20.2%] Hispanic, 9251 [54.8%] non-Hispanic White, and 1408 [8.4%] other) included 15 806 unique mothers and 1062 mothers with 2 or more children in the study. Mean (SD) weekly PM2.5 exposure during pregnancy was relatively low, at 8.03 (2.3) µg/m3, and overall mean (SD) birth weight was 3410.7 (464.5) g. In the sample overall, there was a negative association between PM2.5 exposure and BWGA z score (β = -0.06; 95% credible interval [CrI], -0.10 to -0.03), with a critical window in early gestation (weeks 1-5) that persisted only among males (β = -0.06; 95% CrI, -0.10 to -0.02). When examining differences by region, there were negative associations in the Northeast (β = -0.09; 95% CrI, -0.15 to -0.03), Midwest (β = -0.11; 95% CrI, -0.17 to -0.05; critical window, 12-18 weeks), and South (β = -0.18; 95% CrI, -0.17 to -0.05; critical window, 3-9 weeks). CONCLUSIONS AND RELEVANCE: In this cohort study, higher PM2.5 exposure was associated with lower BWGA z score, with critical windows identified during early pregnancy to midpregnancy; however, findings varied by sex and region. Understanding windows of susceptibility to environmental exposures can help guide research on underlying biological processes and can inform strategies for limiting exposure during certain periods of pregnancy.
AI evidence extraction
Main findings
In 16,868 mother-newborn pairs, higher prenatal PM2.5 exposure was negatively associated with BWGA z score (β = -0.06; 95% CrI, -0.10 to -0.03). A critical window was identified in early gestation (weeks 1–5) that persisted only among males; associations also varied by US region with region-specific critical windows reported.
Outcomes measured
- Birth weight for gestational age (BWGA) z score
View raw extracted JSON
{
"study_type": "cohort",
"exposure": {
"band": null,
"source": null,
"frequency_mhz": null,
"sar_wkg": null,
"duration": "Prenatal (daily residential estimates; weekly means across pregnancy)"
},
"population": "Full-term, singleton births in the US Environmental Influences on Child Health Outcomes (ECHO) cohort (US; births September 2003–December 2021)",
"sample_size": 16868,
"outcomes": [
"Birth weight for gestational age (BWGA) z score"
],
"main_findings": "In 16,868 mother-newborn pairs, higher prenatal PM2.5 exposure was negatively associated with BWGA z score (β = -0.06; 95% CrI, -0.10 to -0.03). A critical window was identified in early gestation (weeks 1–5) that persisted only among males; associations also varied by US region with region-specific critical windows reported.",
"effect_direction": "harm",
"limitations": [],
"evidence_strength": "moderate",
"confidence": 0.7800000000000000266453525910037569701671600341796875,
"peer_reviewed_likely": "yes",
"keywords": [
"PM2.5",
"fine particulate matter",
"prenatal exposure",
"pregnancy",
"birth weight",
"BWGA z score",
"distributed lag model",
"ECHO cohort",
"sex differences",
"regional differences"
],
"suggested_hubs": []
}
AI can be wrong. Always verify against the paper.
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