Heat and Cold Wave-Related Mortality Risk among United States Veterans with Chronic Obstructive Pulmonary Disease: A Case-Crossover Study

美国患有慢性阻塞性肺病的退伍军人中与热浪和寒浪相关的死亡风险:一项病例交叉研究

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Abstract

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is a heterogeneous pulmonary disease affecting 16 million Americans. Individuals with COPD are susceptible to environmental disturbances including heat and cold waves that can exacerbate disease symptoms. OBJECTIVE: Our objective was to estimate heat and cold wave-associated mortality risks within a population diagnosed with a chronic respiratory disease. METHODS: We collected individual level data with geocoded residential addresses from the Veterans Health Administration on 377,545 deceased patients with COPD (2016 to 2021). A time stratified case-crossover study was designed to estimate the incidence rate ratios (IRR) of heat and cold wave mortality risks using conditional logistic regression models examining lagged effects up to 7 d. Attributable risks (AR) were calculated for the lag day with the strongest association for heat and cold waves, respectively. Effect modification by age, gender, race, and ethnicity was also explored. RESULTS: Heat waves had the strongest effect on all-cause mortality at lag day 0 [IRR: 1.04; 95% confidence interval (CI): 1.02, 1.06] with attenuated effects by lag day 1. The AR at lag day 0 was 651 (95% CI: 326, 975) per 100,000 veterans. The effect of cold waves steadily increased from lag day 2 and plateaued at lag day 4 (IRR: 1.04; 95% CI: 1.02, 1.07) with declining but still elevated effects over the remaining 7-d lag period. The AR at lag day 4 was 687 (95% CI: 344, 1,200) per 100,000 veterans. Differences in risk were also detected upon stratification by gender and race. DISCUSSION: Our study demonstrated harmful associations between heat and cold waves among a high-risk population of veterans with COPD using individual level health data. Future research should emphasize using individual level data to better estimate the associations between extreme weather events and health outcomes for high-risk populations with chronic medical conditions. https://doi.org/10.1289/EHP13176.

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