Wildland fire smoke and birth defects in California

Abstract

Birth defects are a leading cause of infant mortality and an important contributor to childhood and adult morbidity. Major structural birth defects are diagnosed in 2 to 4% of infants in the United States. Environmental contaminants, including air pollution, have been suggested as potential risk factors for these anomalies. This study investigates the association between wildfire smoke exposure, specifically fine particulate matter (PM2.5), and the risk of selected structural birth defects in the San Joaquin Valley of California. Data were collected from participants in the California Center of the National Birth Defects Prevention Study and the Birth Defects Study to Evaluate Pregnancy exposureS from 2000 to 2018. The study included 3005 participants, comprising livebirths, stillbirths, and pregnancy terminations. Wildfire smoke exposure was assessed using two estimates: fire density PM2.5 and fire increment PM2.5. Logistic regression was used to analyze the odds of 14 birth defects in relation to quartile-based exposure metrics during the first 8 weeks of pregnancy, adjusting for relevant covariates. Increased risk for several birth defects was observed with higher quartiles of wildfire smoke exposure. Notably, the third quartile of average fire density PM2.5 was associated with increased odds of cleft lip (OR = 2.29; 95% CI: 1.12, 4.69), and the highest quartile of maximum fire density PM2.5 was associated with increased risk of coarctation of the aorta (OR = 2.26; 95% CI: 1.02, 4.99). Spina bifida was consistently associated with higher exposure across multiple metrics, including a significant association with the highest quartile of maximum fire increment PM2.5 (OR = 2.76; 95% CI: 1.14, 6.66). Exposure to wildfire smoke during the first 8 weeks of pregnancy may contribute to the occurrence of certain structural birth defects in California’s San Joaquin Valley. These results highlight the need for further research to corroborate these findings and to understand the mechanisms underlying these associations.