Impact of temperature variability on mortality during extreme heat and cold conditions over 20 years: A time-space-stratified case-crossover study

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.

Authors

Institutions

Publication Details

Journal
PLOS Climate
Published
2026-11-05
DOI
https://doi.org/10.1371/journal.pclm.0001085
Primary Topic
Climate Change and Health Impacts
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
NOV
article

Impact of temperature variability on mortality during extreme heat and cold conditions over 20 years: A time-space-stratified case-crossover study

Zihao Guo, Chao Ren, Ka Chun Chong, Conglu Li et al.
PLOS Climate
Climate Change and Health Impacts
article

Impact of temperature variability on mortality during extreme heat and cold conditions over 20 years: A time-space-stratified case-crossover study

Zihao Guo, Chao Ren, Ka Chun Chong, Conglu Li, Guozhang Lin, Yuchen Wei, Yawen Wang, Kin Fai Ho, Eng Kiong Yeoh, Fang Guo, Shi Zhao
article en

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.

PLOS ClimateVol. 5(11)
Chinese University of Hong Kong (HK), Tianjin Medical University (CN), University of Hong Kong (HK)
Openalex Percentile: Top 19%
Climate Change and Health Impacts
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Laika access coming soon