Environmental health : a global access science source · 2024
The changing health effects of air pollution exposure for respiratory diseases: a multicity study during 2017-2022.
СтатьяНазвание и аннотация: Перевод в очереди
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Jiang Siyu, Tang Longjuan, Lou Zhe, Wang Haowei, Huang Ling, Zhao Wei, Wang Qingqing, Li Ruiyun, Ding Zhen
Аннотация
BACKGROUND: Multifaceted SARS-CoV-2 interventions have modified exposure to air pollution and dynamics of respiratory diseases. Identifying the most vulnerable individuals requires effort to build a complete picture of the dynamic health effects of air pollution exposure, accounting for disparities across population subgroups.
METHODS: We use generalized additive model to assess the likely changes in the hospitalisation and mortality rate as a result of exposure to PM2.5 and O3 over the course of COVID-19 pandemic. We further disaggregate the population into detailed age categories and illustrate a shifting age profile of high-risk population groups. Additionally, we apply multivariable logistic regression to integrate demographic, socioeconomic and climatic characteristics with the pollution-related excess risk.
RESULTS: Overall, a total of 1,051,893 hospital admissions and 34,954 mortality for respiratory disease are recorded. The findings demonstrate a transition in the association between air pollutants and hospitalisation rates over time. For every 10 µg/m3 increase of PM2.5, the rate of hospital admission increased by 0.2% (95% CI: 0.1-0.7%) and 1.4% (1.0-1.7%) in the pre-pandemic and dynamic zero-COVID stage, respectively. Conversely, O3-related hospitalization rate would be increased by 0.7% (0.5-0.9%) in the pre-pandemic stage but lowered to 1.7% (1.5-1.9%) in the dynamic zero-COVID stage. Further assessment indicates a shift of high-risk people from children and young adolescents to the old, primarily the elevated hospitalization rates among the old people in Lianyungang (RR: 1.53, 95%CI: 1.46, 1.60) and Nantong (RR: 1.65, 95%CI: 1.57, 1.72) relative to those for children and young adolescents. Over the course of our study period, people with underlying diseases would have 26.5% (22.8-30.3%) and 12.7% (10.8-14.6%) higher odds of having longer hospitalisation and over 6 times higher odds of deaths after hospitalisation.
CONCLUSIONS: Our estimates provide the first comprehensive evidence on the dynamic pollution-health associations throughout the pandemic. The results suggest that age and underlying diseases collectively determines the disparities of pollution-related health effect across population subgroups, underscoring the urgency to identifying the most vulnerable individuals to air pollution.
METHODS: We use generalized additive model to assess the likely changes in the hospitalisation and mortality rate as a result of exposure to PM2.5 and O3 over the course of COVID-19 pandemic. We further disaggregate the population into detailed age categories and illustrate a shifting age profile of high-risk population groups. Additionally, we apply multivariable logistic regression to integrate demographic, socioeconomic and climatic characteristics with the pollution-related excess risk.
RESULTS: Overall, a total of 1,051,893 hospital admissions and 34,954 mortality for respiratory disease are recorded. The findings demonstrate a transition in the association between air pollutants and hospitalisation rates over time. For every 10 µg/m3 increase of PM2.5, the rate of hospital admission increased by 0.2% (95% CI: 0.1-0.7%) and 1.4% (1.0-1.7%) in the pre-pandemic and dynamic zero-COVID stage, respectively. Conversely, O3-related hospitalization rate would be increased by 0.7% (0.5-0.9%) in the pre-pandemic stage but lowered to 1.7% (1.5-1.9%) in the dynamic zero-COVID stage. Further assessment indicates a shift of high-risk people from children and young adolescents to the old, primarily the elevated hospitalization rates among the old people in Lianyungang (RR: 1.53, 95%CI: 1.46, 1.60) and Nantong (RR: 1.65, 95%CI: 1.57, 1.72) relative to those for children and young adolescents. Over the course of our study period, people with underlying diseases would have 26.5% (22.8-30.3%) and 12.7% (10.8-14.6%) higher odds of having longer hospitalisation and over 6 times higher odds of deaths after hospitalisation.
CONCLUSIONS: Our estimates provide the first comprehensive evidence on the dynamic pollution-health associations throughout the pandemic. The results suggest that age and underlying diseases collectively determines the disparities of pollution-related health effect across population subgroups, underscoring the urgency to identifying the most vulnerable individuals to air pollution.