Environment International (Sep 2022)
The association between prenatal greenspace exposure and Autism spectrum disorder, and the potentially mediating role of air pollution reduction: A population-based birth cohort study
Abstract
Background: Autism spectrum disorder (ASD) incidence has increased in past decades. ASD etiology remains inconclusive, but research suggests genetic, epigenetic, and environmental contributing factors and likely prenatal origins. Few studies have examined modifiable environmental risk factors for ASD, and far fewer have examined protective exposures. Greenspace has been associated with positive child development, but very limited greenspace research has examined ASD risk or prenatal exposures. Only one ecological study in 2017 has evaluated the association between greenspace and ASD, observing protective benefits. Greenspace may have direct effects on ASD risk and indirect effects by reducing air pollution exposure, a growing suspected ASD risk factor. Objectives: To measure the association between prenatal greenspace exposure and ASD risk and examine if reduced air pollution levels in areas of higher greenspace mediate this association. Methods: We linked a population-based birth cohort of all deliveries in Metro Vancouver, Canada, from 2004 to 2009, with follow-up to 2014. Diagnoses were based on Autism Diagnostic Observation Schedule and Autism Diagnostic Interview-Revised instruments. Greenspace was quantified as the average of the annual mean Normalized Difference Vegetation Index (NDVI) within a 250 m buffer of a residential postal code. Air pollutant exposures—particulate matter with a diameter less than 2.5 µm (PM2.5), nitric oxide (NO), and nitrogen dioxide (NO2)—were derived from previously developed and temporally adjusted land use regression models. We estimated air pollutant exposures as the mean concentration per month during pregnancy. We calculated odds ratios (ORs) using logistic regression per NDVI interquartile range (IQR) increase, adjusting for child sex, birth month and year, maternal age and birthplace, and neighborhood-level urbanicity and income. To estimate the health impact of greenspace on ASD at the population level, we used the logistic regression model and marginal standardization to derive risk differences (RDs). Lastly, to quantify the mediating effect of greenspace on ASD risk through air pollution reduction, we used marginal structural models and a potential outcomes framework to calculate marginal risk differences (RDs) to decompose the total effect of greenspace on ASD into natural direct and indirect effects. Results: Of 129,222 births, 1,921 (1.5 %) children were diagnosed with ASD. The adjusted OR for ASD per NDVI IQR (0.12) increase was 0.96 (95 % CI: 0.90, 1.02) in 250 m buffer zones and 0.94 (95 % CI: 0.89, 1.00) in 100 m buffer zones. On the additive scale, the adjusted RDs were null. Natural direct, natural indirect, and total effect RDs were null for PM2.5, NO, and NO2 mediation models. Conclusion: Prenatal greenspace exposure was associated with reduced odds of ASD, but in the additive scale, this effect was null at the population level. No mediating effect was observed through reduced air pollution, suggesting that air pollution may act as a confounder rather than as a mediator.
