Lief Pagalan1,2, Celeste Bickford3, Whitney Weikum4,5, Bruce Lanphear1,6, Michael Brauer3, Nancy Lanphear3,5, Gillian E Hanley6,7, Tim F Oberlander3,4,5,6, Meghan Winters1,2. 1. Faculty of Health Sciences, Simon Fraser University, Vancouver, British Columbia, Canada. 2. Centre of Hip Health and Mobility, Vancouver Coastal Health Research Institute, Vancouver, British Columbia, Canada. 3. School of Population and Public Health, University of British Columbia, Vancouver, British Columbia, Canada. 4. Department of Pediatrics, University of British Columbia, Vancouver, British Columbia, Canada. 5. Sunny Hill Health Centre for Children, BC Children's Hospital, Vancouver, British Columbia, Canada. 6. BC Children's Hospital Research Institute, Vancouver, British Columbia, Canada. 7. Department of Obstetrics and Gynaecology, University of British Columbia, Vancouver, British Columbia, Canada.
Abstract
Importance: The etiology of autism spectrum disorder (ASD) is poorly understood, but prior studies suggest associations with airborne pollutants. Objective: To evaluate the association between prenatal exposures to airborne pollutants and ASD in a large population-based cohort. Design, Setting, and Participants: This population-based cohort encompassed nearly all births in Metro Vancouver, British Columbia, Canada, from 2004 through 2009, with follow-up through 2014. Children were diagnosed with ASD using a standardized assessment with the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule. Monthly mean exposures to particulate matter with a diameter less than 2.5 µm (PM2.5), nitric oxide (NO), and nitrogen dioxide (NO2) at the maternal residence during pregnancy were estimated with temporally adjusted, high-resolution land use regression models. The association between prenatal air pollution exposures and the odds of developing ASD was evaluated using logistic regression adjusted for child sex, birth month, birth year, maternal age, maternal birthplace, and neighborhood-level urbanicity and income band. Data analysis occurred from June 2016 to May 2018. Exposures: Mean monthly concentrations of ambient PM2.5, NO, and NO2 at the maternal residence during pregnancy, calculated retrospectively using temporally adjusted, high-resolution land use regression models. Main Outcomes and Measures: Autism spectrum disorder diagnoses based on standardized assessment of the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule. The hypothesis being tested was formulated during data collection. Results: In a cohort of 132 256 births, 1307 children (1.0%) were diagnosed with ASD by the age of 5 years. The final sample size for the PM2.5-adjusted model was 129 439 children, and for NO and NO2, it was 129 436 children; of these, 1276 (1.0%) were diagnosed with ASD. Adjusted odds ratios for ASD per interquartile range (IQR) were not significant for exposure to PM2.5 during pregnancy (1.04 [95% CI, 0.98-1.10] per 1.5 μg/m3 increase [IQR] in PM2.5) or NO2 (1.06 [95% CI, 0.99-1.12] per 4.8 ppb [IQR] increase in NO2) but the odds ratio was significant for NO (1.07 [95% CI, 1.01-1.13] per 10.7 ppb [IQR] increase in NO). Odds ratios for male children were 1.04 (95% CI, 0.98-1.10) for PM2.5; 1.09 (95% CI, 1.02-1.15) for NO; and 1.07 (95% CI, 1.00-1.13) for NO2. For female children, they were for 1.03 (95% CI, 0.90-1.18) for PM2.5; 0.98 (95% CI, 0.83-1.13) for NO; and 1.00 (95% CI, 0.86-1.16) for NO2. Conclusions and Relevance: In a population-based birth cohort, we detected an association between exposure to NO and ASD but no significant association with PM2.5 and NO2.
Importance: The etiology of autism spectrum disorder (ASD) is poorly understood, but prior studies suggest associations with airborne pollutants. Objective: To evaluate the association between prenatal exposures to airborne pollutants and ASD in a large population-based cohort. Design, Setting, and Participants: This population-based cohort encompassed nearly all births in Metro Vancouver, British Columbia, Canada, from 2004 through 2009, with follow-up through 2014. Children were diagnosed with ASD using a standardized assessment with the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule. Monthly mean exposures to particulate matter with a diameter less than 2.5 µm (PM2.5), nitric oxide (NO), and nitrogen dioxide (NO2) at the maternal residence during pregnancy were estimated with temporally adjusted, high-resolution land use regression models. The association between prenatal air pollution exposures and the odds of developing ASD was evaluated using logistic regression adjusted for child sex, birth month, birth year, maternal age, maternal birthplace, and neighborhood-level urbanicity and income band. Data analysis occurred from June 2016 to May 2018. Exposures: Mean monthly concentrations of ambient PM2.5, NO, and NO2 at the maternal residence during pregnancy, calculated retrospectively using temporally adjusted, high-resolution land use regression models. Main Outcomes and Measures: Autism spectrum disorder diagnoses based on standardized assessment of the Autism Diagnostic Interview-Revised and Autism Diagnostic Observation Schedule. The hypothesis being tested was formulated during data collection. Results: In a cohort of 132 256 births, 1307 children (1.0%) were diagnosed with ASD by the age of 5 years. The final sample size for the PM2.5-adjusted model was 129 439 children, and for NO and NO2, it was 129 436 children; of these, 1276 (1.0%) were diagnosed with ASD. Adjusted odds ratios for ASD per interquartile range (IQR) were not significant for exposure to PM2.5 during pregnancy (1.04 [95% CI, 0.98-1.10] per 1.5 μg/m3 increase [IQR] in PM2.5) or NO2 (1.06 [95% CI, 0.99-1.12] per 4.8 ppb [IQR] increase in NO2) but the odds ratio was significant for NO (1.07 [95% CI, 1.01-1.13] per 10.7 ppb [IQR] increase in NO). Odds ratios for male children were 1.04 (95% CI, 0.98-1.10) for PM2.5; 1.09 (95% CI, 1.02-1.15) for NO; and 1.07 (95% CI, 1.00-1.13) for NO2. For female children, they were for 1.03 (95% CI, 0.90-1.18) for PM2.5; 0.98 (95% CI, 0.83-1.13) for NO; and 1.00 (95% CI, 0.86-1.16) for NO2. Conclusions and Relevance: In a population-based birth cohort, we detected an association between exposure to NO and ASD but no significant association with PM2.5 and NO2.
Authors: Katja M Lampi; Liisa Lehtonen; Phuong Lien Tran; Auli Suominen; Venla Lehti; P Nina Banerjee; Mika Gissler; Alan S Brown; Andre Sourander Journal: J Pediatr Date: 2012-06-05 Impact factor: 4.406
Authors: Amy E Kalkbrenner; Gayle C Windham; Marc L Serre; Yasuyuki Akita; Xuexia Wang; Kate Hoffman; Brian P Thayer; Julie L Daniels Journal: Epidemiology Date: 2015-01 Impact factor: 4.822
Authors: Raanan Raz; Andrea L Roberts; Kristen Lyall; Jaime E Hart; Allan C Just; Francine Laden; Marc G Weisskopf Journal: Environ Health Perspect Date: 2014-12-18 Impact factor: 9.031
Authors: Charlotte Clark; Hind Sbihi; Lillian Tamburic; Michael Brauer; Lawrence D Frank; Hugh W Davies Journal: Environ Health Perspect Date: 2017-08-31 Impact factor: 9.031
Authors: Sarah A Carter; Md Mostafijur Rahman; Jane C Lin; Yu-Hsiang Shu; Ting Chow; Xin Yu; Mayra P Martinez; Sandrah P Eckel; Jiu-Chiuan Chen; Zhanghua Chen; Joel Schwartz; Nathan Pavlovic; Frederick W Lurmann; Rob McConnell; Anny H Xiang Journal: Environ Int Date: 2021-10-06 Impact factor: 9.621
Authors: Battsetseg Ulziikhuu; Enkhjargal Gombojav; Chimeglkham Banzrai; Sarangerel Batsukh; Enkhtuul Enkhtuya; Buyantushig Boldbaatar; David C Bellinger; Bruce P Lanphear; Lawrence C McCandless; Sukhpreet K Tamana; Ryan W Allen Journal: Environ Health Perspect Date: 2022-06-22 Impact factor: 11.035
Authors: Deborah H Bennett; Stefanie A Busgang; Kurunthachalam Kannan; Patrick J Parsons; Mari Takazawa; Christopher D Palmer; Rebecca J Schmidt; John T Doucette; Julie B Schweitzer; Chris Gennings; Irva Hertz-Picciotto Journal: Environ Int Date: 2022-01-24 Impact factor: 13.352
Authors: Omar Hahad; Jos Lelieveld; Frank Birklein; Klaus Lieb; Andreas Daiber; Thomas Münzel Journal: Int J Mol Sci Date: 2020-06-17 Impact factor: 5.923