Impact of temperature variability on mortality during extreme heat and cold conditions over 20 years: A time-space-stratified case-crossover study
- 1School of Public Health and Primary Care, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China
- 2Division of Landscape Architecture, Department of Architecture, Faculty of Architecture, The University of Hong Kong, Hong Kong Special Administrative Region, China
- 3School of Public Health, Tianjin Medical University, Tianjin, China
Abstract
Background: Climate change-induced temperature variability poses growing health risks. The effects of this variability on mortality are well established; however, its specific impact during extreme heat and cold conditions remains understudied. This represents a knowledge gap, as the human body’s physiological capacity to adapt to sudden temperature shifts is compromised when ambient temperatures are extreme. To address this, our study examined the relationship between mortality and temperature variability in Hong Kong for a 21-year period. Methods: A time-space-stratified case-crossover design was used in this study. Daily weather data from ERA5-Land and PM2.5 levels from ChinaHighPM2.5 were combined with mortality records in Hong Kong from 2000 to 2020. Diurnal temperature range (DTR) and temperature changes between consecutive days (TCN) were used as the temperature variability metrics. Extreme hot and cold conditions were defined by annual temperature percentiles: > 75%, > 90%, > 95%, > 97.5% for hot seasons, and <25%, < 10%, < 5%, < 2.5% for cold seasons. A conditional logistic regression was used to examine the association between temperature variability metrics and mortality, adjusting for other environmental factors. Subgroup analyses by age and cause-specific mortality were performed. Results: DTR and TCN were strongly associated with mortality during heat extremes. For temperatures >97.5th percentile, DTR (odds ratio [OR] = 1.99, 95% confidence interval [CI]: 1.90-2.08) and TCN (OR = 2.24, 95% CI: 2.09-2.40) showed increased risks for all-cause mortality. During cold extremes (<2.5th percentile), DTR showed an inverse association (OR = 0.93, 95% CI: 0.90-0.95), while TCN was associated with increased odds of all-cause mortality (OR = 1.06, 95% CI: 1.04-1.08). Conclusion: Temperature variability was associated with an increased risk of mortality during extreme heat conditions, with mortality risk rising alongside higher extreme temperature levels, while during extreme cold, the associations were generally smaller. At temperatures above the 97.5th percentile, each 1°C increase in DTR and TCN was associated with approximately 99% and 124% higher odds of all-cause mortality, respectively. These findings highlight the need for targeted public health strategies to protect vulnerable populations from climate-induced temperature fluctuations.
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BibTeX
@article{wei2026impact,
title = {{Impact of temperature variability on mortality during extreme heat and cold conditions over 20 years: A time-space-stratified case-crossover study}},
author = {Yuchen Wei and Fang Guo and Yawen Wang and Zihao Guo and Guozhang Lin and Conglu Li and Shi Zhao and Chao Ren and Kin Fai Ho and Eng Kiong Yeoh and Ka Chun Chong},
journal = {PLOS Climate},
year = {2026},
month = nov,
doi = {10.1371/journal.pclm.0001085},
url = {https://journals.plos.org/climate/article?id=10.1371/journal.pclm.0001085},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Impact of temperature variability on mortality during extreme heat and cold conditions over 20 years: A time-space-stratified case-crossover study
AU - Yuchen Wei
AU - Fang Guo
AU - Yawen Wang
AU - Zihao Guo
AU - Guozhang Lin
AU - Conglu Li
AU - Shi Zhao
AU - Chao Ren
AU - Kin Fai Ho
AU - Eng Kiong Yeoh
AU - Ka Chun Chong
PY - 2026
DA - 2026/11/05
JO - PLOS Climate
DO - 10.1371/journal.pclm.0001085
UR - https://journals.plos.org/climate/article?id=10.1371/journal.pclm.0001085
AB - Background: Climate change-induced temperature variability poses growing health risks. The effects of this variability on mortality are well established; however, its specific impact during extreme heat and cold conditions remains understudied. This represents a knowledge gap, as the human body’s physiological capacity to adapt to sudden temperature shifts is compromised when ambient temperatures are extreme. To address this, our study examined the relationship between mortality and temperature variability in Hong Kong for a 21-year period. Methods: A time-space-stratified case-crossover design was used in this study. Daily weather data from ERA5-Land and PM2.5 levels from ChinaHighPM2.5 were combined with mortality records in Hong Kong from 2000 to 2020. Diurnal temperature range (DTR) and temperature changes between consecutive days (TCN) were used as the temperature variability metrics. Extreme hot and cold conditions were defined by annual temperature percentiles: > 75%, > 90%, > 95%, > 97.5% for hot seasons, and <25%, < 10%, < 5%, < 2.5% for cold seasons. A conditional logistic regression was used to examine the association between temperature variability metrics and mortality, adjusting for other environmental factors. Subgroup analyses by age and cause-specific mortality were performed. Results: DTR and TCN were strongly associated with mortality during heat extremes. For temperatures >97.5th percentile, DTR (odds ratio [OR] = 1.99, 95% confidence interval [CI]: 1.90-2.08) and TCN (OR = 2.24, 95% CI: 2.09-2.40) showed increased risks for all-cause mortality. During cold extremes (<2.5th percentile), DTR showed an inverse association (OR = 0.93, 95% CI: 0.90-0.95), while TCN was associated with increased odds of all-cause mortality (OR = 1.06, 95% CI: 1.04-1.08). Conclusion: Temperature variability was associated with an increased risk of mortality during extreme heat conditions, with mortality risk rising alongside higher extreme temperature levels, while during extreme cold, the associations were generally smaller. At temperatures above the 97.5th percentile, each 1°C increase in DTR and TCN was associated with approximately 99% and 124% higher odds of all-cause mortality, respectively. These findings highlight the need for targeted public health strategies to protect vulnerable populations from climate-induced temperature fluctuations.
SN - 2767-3200
ER -