Health impacts of a cold wave and its economic loss assessment in China's high-altitude city, Xining

Abstract

Objective: Amidst climate change, extensive research has centered on the health impacts of heatwaves, yet the consequences of cold spells, particularly in cooler, higher-altitude regions, remain under-explored.

Methods: Analyzing climatic data and non-accidental mortality in Xining, China's second-highest provincial capital, from 2016 to 2020, this study defines cold spells as daily mean temperatures below the 10th, 7.5th, or 5th percentiles for 2-4 consecutive days. A time-stratified case-crossover approach and distributional lag nonlinear modeling were used to assess the link between cold spells and mortality, calculating attributable fractions (AFs) and numbers (ANs) of deaths. The study also examined the impact of cold spells over different periods and analyzed the value of a statistical life (VSL) loss in 2018, a year with frequent cold spells. Stratified analyses by sex, age, and education level were conducted.

Results: A significant association was found between cold spells and non-accidental mortality, with a relative risk of 1.548 (95% CI: 1.300, 1.845). The AF was 33.48%, with an AN of 9,196 deaths during the study's cold period. A declining trend in mortality risk was observed from 2019-2020. The 2018 VSL was approximately 2.875 billion CNY, about 1.75% of Xining's GDP. Higher risks were noted among males, individuals aged ≥ 65, and those with lower education levels.

Conclusion: The findings underscore the vulnerability and economic losses of high-altitude cities to cold spells. Implementing interventions such as improved heating, educational programs, and community support is vital for mitigating these adverse health effects.

Keywords: Climate change; Cold spell; Non-accidental mortality; VSL; health risk.

Fig. 1

Cumulative effect of cold spells on mortality for days 0–21 under the nine cold spell definitions, stratified by sex, age, level of education and cause (Non-accidental, Circulatory disease, IHD, Stroke, Respiratory disease, COPD, Tumor, and Diabetes mellitus). Cold spells were defined by the percentile temperature threshold (5th, 7.5th, or 10th percentiles) and by the number of consecutive days below the threshold (2–4 days, indicated by D2, D3, D4). “Low” represents junior high school and below, and “High” represents high school and higher

Fig. 2

Cumulative lagged effects of the optimal cold spell on different specific causes of death (Non-accidental, Circulatory disease, IHD, Stroke, Respiratory disease, COPD, Tumor, and Diabetes mellitus) across the lags of 0–21 days

Fig. 3

Attributable proportions and attributable numbers for specific causes of death under optimal cold spell. (Non-accidental, Circulatory disease, IHD, Stroke, Respiratory disease, COPD, Tumor, and Diabetes mellitus)

Fig. 4

Attributable fraction and attributable number of the optimal cold spell, stratified by sex, age, and level of education