Temperature-related emergency injury visits in Hanoi, Vietnam

Vu Thuy Huong Le, Jesse D. Berman, Elizabeth V. Wattenberg, Toan Van Ngo, Quynh Anh Tran, Bruce H. Alexander

Research output: Contribution to journalArticlepeer-review

3 Scopus citations

Abstract

Background The short-term association between increasing temperatures and injury has been described in high-income countries, but less is known for low-income and-middle-income countries, including Vietnam. Methods We used emergency injury visits (EIV) data for 2017-2019 from 733 hospitals and clinics in Hanoi, Vietnam to examine the effects of daily temperature on EIV. Time-series analysis with quasi-Poisson models was used to estimate a linear relative risk increase (RRI) for overall populations and ones stratified by age and sex. Exposure-response curves estimated non-linear associations as an RR between daily temperature and injury. Models were adjusted for the day of week, holidays, daily relative humidity, daily particulate matter, and long-term and seasonal trends. Results and conclusions A total of 39 313 EIV were recorded averaging 36 injuries daily. Injuries more likely occurred in males and those aged 15-44, and aged 44-60. For linear effects, a 5°C increase in same day mean temperature was associated with an overall increased EIV (RRI 4.8; 95% CI 2.3 to 7.3) with males (RRI 5.9; 95% CI 3.0 to 8.9) experiencing a greater effect than females (RRI 3.0; 95% CI -0.5 to 6.5). Non-linear effects showed an increase in EIV at higher temperatures compared with the threshold temperature of 15°C, with the greatest effect at 33°C (RR 1.3; 95% CI 1.2 to 1.6). Further research to investigate temperature-injury among different populations and by the cause of injury is warranted.

Original languageEnglish (US)
Pages (from-to)33-38
Number of pages6
JournalInjury Prevention
Volume30
Issue number1
DOIs
StatePublished - Oct 20 2023

Bibliographical note

Publisher Copyright:
© 2023 BMJ Publishing Group. All rights reserved.

Keywords

  • Epidemiology
  • Public Health
  • Risk Factor Research
  • Time series

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