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Ambient Air Quality and Emergency Hospital Admissions in Singapore: A Time-Series Analysis

Author

Listed:
  • Andrew Fu Wah Ho

    (Department of Emergency Medicine, Singapore General Hospital, Singapore 168753, Singapore
    Pre-Hospital and Emergency Research Centre, Duke-NUS Medical School, Singapore 169857, Singapore
    Joint first authors.)

  • Zhongxun Hu

    (Duke-NUS Medical School, Singapore 169857, Singapore
    Joint first authors.)

  • Ting Zhen Cheryl Woo

    (Ministry of Health Holdings, Singapore 099253, Singapore)

  • Kenneth Boon Kiat Tan

    (Department of Emergency Medicine, Singapore General Hospital, Singapore 168753, Singapore)

  • Jia Hao Lim

    (Department of Emergency Medicine, Singapore General Hospital, Singapore 168753, Singapore)

  • Maye Woo

    (Environmental Quality Monitoring Department, Environmental Monitoring and Modelling Division, National Environment Agency, Singapore 228231, Singapore)

  • Nan Liu

    (Duke-NUS Medical School, Singapore 169857, Singapore)

  • Geoffrey G. Morgan

    (Sydney School of Public Health, University of Sydney, Sydney, NSW 2006, Australia)

  • Marcus Eng Hock Ong

    (Department of Emergency Medicine, Singapore General Hospital, Singapore 168753, Singapore
    Health Services & Systems Research, Duke-NUS Medical School, Singapore 169857, Singapore
    Joint last authors.)

  • Joel Aik

    (Pre-Hospital and Emergency Research Centre, Duke-NUS Medical School, Singapore 169857, Singapore
    Environmental Epidemiology and Toxicology Division, National Environment Agency, Singapore 228231, Singapore
    Joint last authors.)

Abstract

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.

Suggested Citation

  • Andrew Fu Wah Ho & Zhongxun Hu & Ting Zhen Cheryl Woo & Kenneth Boon Kiat Tan & Jia Hao Lim & Maye Woo & Nan Liu & Geoffrey G. Morgan & Marcus Eng Hock Ong & Joel Aik, 2022. "Ambient Air Quality and Emergency Hospital Admissions in Singapore: A Time-Series Analysis," IJERPH, MDPI, vol. 19(20), pages 1-12, October.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:20:p:13336-:d:943659
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    References listed on IDEAS

    as
    1. Laura Pimpin & Lise Retat & Daniela Fecht & Laure de Preux & Franco Sassi & John Gulliver & Annalisa Belloni & Brian Ferguson & Emily Corbould & Abbygail Jaccard & Laura Webber, 2018. "Estimating the costs of air pollution to the National Health Service and social care: An assessment and forecast up to 2035," PLOS Medicine, Public Library of Science, vol. 15(7), pages 1-16, July.
    Full references (including those not matched with items on IDEAS)

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