BMJ open · 2022
Effects of short-term exposure to air pollution on hospital admissions for autism spectrum disorder in Korean school-aged children: a nationwide time-series study.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Kim Kyoung-Nam, Sohn Ji Hoon, Cho Sung Joon, Seo Hwo Yeon, Kim Soontae, Hong Yun-Chul
Аннотация
OBJECTIVES: This study explored the effects of short-term exposure to air pollution on hospital admissions for autism spectrum disorder (ASD), a proxy for symptom aggravation, among Korean children aged 5-14 years.
DESIGN: Time-series study.
SETTING, PARTICIPANTS AND OUTCOME MEASURES: We used data from the National Health Insurance Service (2011-2015). Daily concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2) and ozone (O3) levels in each region were used as exposures. ASD cases were defined based on a principal admission diagnosis of the claims data. We applied distributed lag non-linear models and a generalised difference-in-differences method to the quasi-Poisson models to estimate the causal effects of air pollution for up to 6 days. We also performed weighted quantile sum regression analyses to assess the combined effects of air pollution mixtures.
RESULTS: PM2.5 levels at lag day 1, NO2 levels at lag day 5 and O3 levels at lag day 4 increased the risks of hospital admissions for ASD (relative risk (RR)=1.17, 95% CI 1.10 to 1.25 for PM2.5; RR=1.09, 95% CI 1.01 to 1.18 for NO2 and RR=1.03, 95% CI 1.00 to 1.06 for O3). The mean daily count of hospital admissions for ASD was 8.5, and it would be 7.3, 7.8 and 8.3 when the PM2.5 levels would be decreased by 10.0 µg/m3, NO2 by 10 ppb and O3 by 10 ppb, respectively. The weighted quantile sum index, constructed from PM2.5, NO2 and O3 levels, was associated with a higher risk of hospital admissions for ASD (RR 1.29, 95% CI 1.14 to 1.46), where NO2 was found to contribute to the effects most (the weight of 0.80).
CONCLUSIONS: These results emphasise that reduction of air pollution exposure should be considered for ASD symptom management, with important implications for the quality of life and economic costs.
DESIGN: Time-series study.
SETTING, PARTICIPANTS AND OUTCOME MEASURES: We used data from the National Health Insurance Service (2011-2015). Daily concentrations of fine particulate matter (PM2.5), nitrogen dioxide (NO2) and ozone (O3) levels in each region were used as exposures. ASD cases were defined based on a principal admission diagnosis of the claims data. We applied distributed lag non-linear models and a generalised difference-in-differences method to the quasi-Poisson models to estimate the causal effects of air pollution for up to 6 days. We also performed weighted quantile sum regression analyses to assess the combined effects of air pollution mixtures.
RESULTS: PM2.5 levels at lag day 1, NO2 levels at lag day 5 and O3 levels at lag day 4 increased the risks of hospital admissions for ASD (relative risk (RR)=1.17, 95% CI 1.10 to 1.25 for PM2.5; RR=1.09, 95% CI 1.01 to 1.18 for NO2 and RR=1.03, 95% CI 1.00 to 1.06 for O3). The mean daily count of hospital admissions for ASD was 8.5, and it would be 7.3, 7.8 and 8.3 when the PM2.5 levels would be decreased by 10.0 µg/m3, NO2 by 10 ppb and O3 by 10 ppb, respectively. The weighted quantile sum index, constructed from PM2.5, NO2 and O3 levels, was associated with a higher risk of hospital admissions for ASD (RR 1.29, 95% CI 1.14 to 1.46), where NO2 was found to contribute to the effects most (the weight of 0.80).
CONCLUSIONS: These results emphasise that reduction of air pollution exposure should be considered for ASD symptom management, with important implications for the quality of life and economic costs.