RT Journal Article
SR Electronic
T1 Estimation of effects of extreme temperature on the risk of hospitalisation in Taiwan
JF Journal of Epidemiology and Community Health
JO J Epidemiol Community Health
FD BMJ Publishing Group Ltd
SP 375
OP 383
DO 10.1136/jech-2022-220142
VO 77
IS 6
A1 Ayushi Sharma
A1 Liwen Deng
A1 Yu-Chun Wang
YR 2023
UL http://jech.bmj.com/content/77/6/375.abstract
AB Background Extreme temperatures are triggering and exacerbating hospital admissions and health burdens; however, it is still understudied. Therefore, we evaluated the effects of the average temperature on overall hospitalisation and the average length of hospital stay.Methods Daily area-specific age-sex stratified hospitalisation records from 2006 to 2020 were collected from the National Health Research Institutes of Taiwan. The distributed lag non-linear model was used to estimate the area-specific relative risk (RR) and 95% CI associated with daily average temperature. Overall cumulative RR was pooled from area-specific RRs using random effects meta-analysis. Temperature effects of extreme high and low thresholds were also evaluated based on the 99th (32°C) and 5th (14°C) percentiles, respectively.Results Our findings suggested that the elderly (age ≥65 years) are vulnerable to temperature effects, while differential gender effects are not explicit in Taiwan. A higher risk of in-patient visits was seen among the elderly during extreme low temperatures (RR 1.08; 95% CI 1.04 to 1.11) compared with extreme high temperatures (RR 1.07; 95% CI 1.05 to 1.10). Overall, high-temperature extremes increased the risk of hospitalisation with an RR of 1.05 (95% CI 1.03 to 1.07) among the all-age-sex population in Taiwan. Additionally, lag-specific analysis of the study revealed that high-temperature effects on in-patient visits are effective on the same day of exposure, while cold effects occurred after 0–2 days of exposure. The average length of hospital stays can also increase with high-temperature extremes among age group 41–64 years and the elderly.Conclusion Public health preparedness should consider the increased load on health facilities and health expenditures during extreme temperatures.No data are available. Data used is confidential and is not available due to privacy concerns.