Evidence map›Paper›PMID 41691346›Full record

ArticleArchives of public health = Archives belges de sante publique2026

Separate and combined associations of heatwaves, air pollution, green spaces, and blue spaces with depressive symptoms: a national cohort study.

Kang Wu, Guang-Li Hu, Jin-Zhong Cai, Bei Li, Yi-Li Zhang

Abstract read
In one paragraph

Article in Archives of public health = Archives belges de sante publique, 2026. 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

What it found

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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.

Kang Wu *School of Health Management, Southern Medical University, Guangzhou, 510515, China.
Guang-Li HuSchool of Graduate, Southern Medical University, Guangzhou, 510515, China.
Jin-Zhong CaiShenzhen People's Hospital, Shenzhen, 518000, China.
Bei Li *School of Health Management, Southern Medical University, Guangzhou, 510515, China. libeijt27@163.com.
Yi-Li Zhang *School of Health Management, Southern Medical University, Guangzhou, 510515, China. zhangyi1223882953@163.com.

Funding

2023 Guangdong Provincial Philosophy and Social Sciences Planning General Project GD23CGL092024 Guangdong Provincial Basic and Applied Basic Research General Project 2024A15150107612025 Guangdong Provincial Basic and Applied Basic Research General Project 2025A15150109702025 Guangdong Provincial Philosophy and Social Sciences Planning General Project GD25CGG19
6 · The paper itself

Abstract

backgroundDepressive symptoms are among the most prevalent mental disorders globally, and identifying their combined risk factors is crucial for promoting population mental health. Extreme heat exposure, air pollution, green spaces, and blue spaces are common environmental exposures, yet their separate effects and interactions on the risk of depressive symptom onset remain unclear. This study aims to investigate the individual and interactive effects of extreme heat exposure and the aforementioned environmental factors on the risk of depressive symptoms.

methodsUsing five waves of data from the China Health and Retirement Longitudinal Study (CHARLS) from 2011 to 2020. Nine heatwave definitions were employed as indicators of high-temperature exposure in the year preceding the onset of depressive symptoms. PM2.5, NDVI, and the average proportion of open water areas represented exposure levels to air pollution, green space, and blue space, respectively. Using Cox proportional hazards regression models incorporating time-varying variables, we assessed the effects of heatwave combined with air pollution, green space, and blue space on depressive symptoms across three dimensions: separate effects, multiplicative interactions, and additive interactions.

resultsExtreme high-temperature exposure, high levels of air pollution, lack of green space and blue space are all significantly associated with increased depressive symptoms risk. Heterogeneity exists across different genders, age groups, and educational levels in terms of individual associations. On both multiplicative and additive interaction scales, synergistic effects were demonstrated between heatwave and high levels of air pollution, as well as low levels of green and blue space, collectively amplifying the risk of depressive symptoms.

conclusionExtreme high-temperature, elevated air pollution, and insufficient green and blue spaces are all significant environmental risk factors for depressive symptoms among middle-aged and older adults. Furthermore, air pollution and a lack of green and blue spaces amplify the adverse effects of high temperatures on depressive symptoms.

Indexed as

Air pollutionBlue spaceDepression symptomsGreen spaceHeatwaves

Identifiers

PMID41691346
PMCPMC13011302

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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.