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Differentiating the impacts of ambient temperature on pneumonia mortality of various infectious causes: a nationwide, individual-level, case-crossover study

肺炎 渡线 医学 环境卫生 交叉研究 重症监护医学 内科学 计算机科学 病理 替代医学 人工智能 安慰剂
作者
Qing He,Yunning Liu,Peng Yin,Ya Gao,Haidong Kan,Maigeng Zhou,Renjie Chen,Yanming Liu
出处
期刊:EBioMedicine [Elsevier]
卷期号:98: 104854-104854 被引量:4
标识
DOI:10.1016/j.ebiom.2023.104854
摘要

Summary

Background

It remains unknown how ambient temperature impact pneumonia of various infectious causes.

Methods

Based on the national death registry covering all counties in Chinese mainland, we conducted an individual-level case-crossover study in China from 2013 to 2019. Exposures were assigned at residential addresses for each decedent. Conditional logistic regression model combined with distributed lag non-linear models were used to estimate the exposure-response associations. The attributable fractions due to non-optimum temperature were calculated after accounting for spatial and temporal patterns for the excess risks.

Findings

The exposure-response curves were inversely J-shaped with both low and high temperature increasing the risks, and the effect of low temperature was stronger. Extremely low temperature was associated with higher magnitude of influenza-related pneumonia [relative risk (RR): 2.46, 95% confidence interval (CI): 1.62–3.74], than viral pneumonia (RR: 1.89, 95% CI: 1.55–2.30) and bacterial pneumonia (RR: 1.81, 95% CI: 1.56–2.09). The magnitudes of RRs associated with extremely high temperature were similar among the three categories of pneumonia. The mortality attributable fraction for influenza-related pneumonia (29.78%) was the highest. The effects were stronger in people of low education level or residence in the north.

Interpretation

This nationwide study presents findings on the varied risk and burden of pneumonia mortality of various infectious causes, and highlights the susceptibility of influenza-related pneumonia to ambient low temperature.

Funding

This study is supported by the National Key Research and Development Program (2022YFC3702701), the Shanghai Municipal Science and Technology Commission (21TQ015) and Shanghai International Science and Technology Partnership Project (21230780200).
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