ArticleWorld journal of psychiatry2023
Meteorological factors, ambient air pollution, and daily hospital admissions for depressive disorder in Harbin: A time-series study.
Article in World journal of psychiatry, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- The effects of outdoor air pollution on University students' mental health: a within-group repeated-measures study.BMC psychiatry · 2026Article
- A short-term association between hospitalizations for mental disorders and ambient temperature in Japan: an ecological study using the LIFE Study data.Environmental health and preventive medicine · 2026Article
- Article
- Evaluating short-term air pollution-related mental health resilience using a directional network.BMC public health · 2025Article
- Long-term exposure to air pollutants, meteorological factors, and mental health status: a nationwide population-based study with multilevel regression analysis.Archives of public health = Archives belges de sante publique · 2025Article
- The Impact of Seasonality on Mental Health Disorders: A Narrative Review and Extension of the Immunoseasonal Theory.Journal of clinical medicine · 2025Review
- Climate change, ambient air pollution, and students' mental health.World journal of psychiatry · 2024Article
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Authors and funding
5 authors.
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Abstract
backgroundThe literature has discussed the relationship between environmental factors and depressive disorders; however, the results are inconsistent in different studies and regions, as are the interaction effects between environmental factors. We hypothesized that meteorological factors and ambient air pollution individually affect and interact to affect depressive disorder morbidity.
aimTo investigate the effects of meteorological factors and air pollution on depressive disorders, including their lagged effects and interactions.
methodsThe samples were obtained from a class 3 hospital in Harbin, China. Daily hospital admission data for depressive disorders from January 1, 2015 to December 31, 2022 were obtained. Meteorological and air pollution data were also collected during the same period. Generalized additive models with quasi-Poisson regression were used for time-series modeling to measure the non-linear and delayed effects of environmental factors. We further incorporated each pair of environmental factors into a bivariate response surface model to examine the interaction effects on hospital admissions for depressive disorders.
resultsData for 2922 d were included in the study, with no missing values. The total number of depressive admissions was 83905. Medium to high correlations existed between environmental factors. Air temperature (AT) and wind speed (WS) significantly affected the number of admissions for depression. An extremely low temperature (-29.0 ℃) at lag 0 caused a 53% [relative risk (RR)= 1.53, 95% confidence interval (CI): 1.23-1.89] increase in daily hospital admissions relative to the median temperature. Extremely low WSs (0.4 m/s) at lag 7 increased the number of admissions by 58% (RR = 1.58, 95%CI: 1.07-2.31). In contrast, atmospheric pressure and relative humidity had smaller effects. Among the six air pollutants considered in the time-series model, nitrogen dioxide (NO
conclusionMeteorological factors and the air pollutant NO
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