Evidence map›Paper›PMID 41189966›Full record

ArticleFrontiers in public health2025

Differentiating the impact of ambient temperature on hospitalization due to cause-specific pneumonias: an individual-level, case-crossover study.

Xiaozhen Su, Lu Zhou, Yingmin Tao, Renjie Chen, Juan Xie

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Xiaozhen Su *Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, Fudan University, Shanghai, China.
Lu Zhou *Department of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, Fudan University, Shanghai, China.
Yingmin Tao *Division of General Practice, The Fifth People's Hospital of Shanghai, Fudan University, Shanghai, China.
Renjie ChenDepartment of Environmental Health, School of Public Health, Key Lab of Public Health Safety of the Ministry of Education, Fudan University, Shanghai, China.
Juan XieDivision of General Practice, The Fifth People's Hospital of Shanghai, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Associations between exposure to ambient temperature and the risks of hospital admission for overall or a specific type of pneumonia were reported in prior studies. However, few studies have systematically explored the potentially differential impacts of ambient temperature on hospitalization for cause-specific pneumonias. Methods: We performed a time-stratified, case-crossover study based on individual-level pneumonia-related hospital data with pathogen identification results in Shanghai, the largest metropolis in China from 2013 to 2019. Conditional logistic regression combined with distributed lag non-linear model was used to estimate effects of extreme temperature. Results: We included a total of 6,277 hospitalized cases of pneumonias with various causes. The observed exposure-response curve for the association between temperature and pneumonias was nonlinear, with significantly elevated risks in high temperature. The hot-related risk appeared on lag 0-1 day, and became non-significant on lag 5-10 day, with differential lag patterns in various subtypes of pneumonias. Extreme high temperature exhibited the largest effect estimate in hospitalization from infectious pneumonia [relative risk: 2.55, 95% confidence interval (CI): 1.58, 4.13], followed by bacterial pneumonia (2.16, 95% CI, 1.15, 4.04), and total pneumonia (1.96, 95% CI, 1.40, 2.74). Stronger relationships were observed in females in stratified analyses. The effect estimates remain robust after adjusting for air pollutants and various model parameters. Discussion: As pneumonias cause a huge disease burden worldwide, our study adds heat-related risk assessments on hospitalization due to cause-specific pneumonias, which is beneficial for prevention and management of patients with specific subtypes of pneumonia in urban areas.

Indexed as

HospitalizationHot TemperaturePneumoniaAdultAgedChinaCross-Over StudiesFemaleHumansMaleMiddle Agedambient temperaturecase-crossover studyclimate changehospital admissionpneumonia

Identifiers

PMID41189966
PMCPMC12580377

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.