Fine Particulate Matter, Its Constituents, and Spontaneous Preterm Birth

作者：Anqi Jiao, Alexa N. Reilly, Tarik Benmarhnia, Yi Sun, Chantal Avila, Vicki Y. Chiu, Jeff Slezak, David A. Sacks, John Molitor, Mengyi Li, Jiu‐Chiuan Chen, Jun Wu, Darios Getahun · 发表于：JAMA Network Open · 年份：2024 · DOI：10.1001/jamanetworkopen.2024.44593 · 被引用次数：30 · 研究领域：Air Quality and Health Impacts、Energy and Environment Impacts、Neonatal Respiratory Health Research

Importance: The associations of exposure to fine particulate matter (PM2.5) and its constituents with spontaneous preterm birth (sPTB) remain understudied. Identifying subpopulations at increased risk characterized by socioeconomic status and other environmental factors is critical for targeted interventions. Objective: To examine associations of PM2.5 and its constituents with sPTB. Design, Setting, and Participants: This population-based retrospective cohort study was conducted from 2008 to 2018 within a large integrated health care system, Kaiser Permanente Southern California. Singleton live births with recorded residential information of pregnant individuals during pregnancy were included. Data were analyzed from December 2023 to March 2024. Exposures: Daily total PM2.5 concentrations and monthly data on 5 PM2.5 constituents (sulfate, nitrate, ammonium, organic matter, and black carbon) in California were assessed, and mean exposures to these pollutants during pregnancy and by trimester were calculated. Exposures to total green space, trees, low-lying vegetation, and grass were estimated using street view images. Wildfire-related exposure was measured by the mean concentration of wildfire-specific PM2.5 during pregnancy. Additionally, the mean exposure to daily maximum temperature during pregnancy was calculated. Main Outcomes and Measures: The primary outcome was sPTB identified through a natural language processing algorithm. Discrete-time survival models were used to ...