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Ambient Air Quality and Emergency Hospital Admissions in Singapore: A Time-Series Analysis
Air pollution exposure may increase the demand for emergency healthcare services, particularly in South-East Asia, where the burden of air-pollution-related health impacts is high. This article aims to investigate the association between air quality and emergency hospital admissions in Singapore. Qu...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9603816/ https://www.ncbi.nlm.nih.gov/pubmed/36293917 http://dx.doi.org/10.3390/ijerph192013336 |
Sumario: | Air pollution exposure may increase the demand for emergency healthcare services, particularly in South-East Asia, where the burden of air-pollution-related health impacts is high. This article aims to investigate the association between air quality and emergency hospital admissions in Singapore. Quasi-Poisson regression was applied with a distributed lag non-linear model (DLNM) to assess the short-term associations between air quality variations and all-cause, emergency admissions from a major hospital in Singapore, between 2009 and 2017. Higher concentrations of SO(2), PM(2.5), PM(10), NO(2), and CO were positively associated with an increased risk of (i) all-cause, (ii) cardiovascular-related, and (iii) respiratory-related emergency admissions over 7 days. O(3) concentration increases were associated with a non-linear decrease in emergency admissions. Females experienced a higher risk of emergency admissions associated with PM(2.5), PM(10), and CO exposure, and a lower risk of admissions with NO(2) exposure, compared to males. The older adults (≥65 years) experienced a higher risk of emergency admissions associated with SO(2) and O(3) exposure compared to the non-elderly group. We found significant positive associations between respiratory disease- and cardiovascular disease-related emergency hospital admissions and ambient SO(2), PM(2.5), PM(10), NO(2), and CO concentrations. Age and gender were identified as effect modifiers of all-cause admissions. |
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