Objective We aimed to examine the temporal trends of the association between extreme temperature and schizophrenia (SCZ) hospitalisations in Hefei, China.
Methods We collected time-series data on SCZ hospitalisations for 10 years (2005–2014), with a total of 36 607 cases registered. We used quasi-Poisson regression and distributed lag non-linear model (DLNM) to assess the association between extreme temperature (cold and heat) and SCZ hospitalisations. A time-varying DLNM was then used to explore the temporal trends of the association between extreme temperature and SCZ hospitalisations in different periods. Subgroup analyses were conducted by age (0–39 and 40+ years) and gender, respectively.
Results We found that extreme cold and heat significantly increased the risk of SCZ hospitalisations (cold: 1st percentile of temperature 1.19 (95% CI 1.04 to 1.37) and 2.5th percentile of temperature 1.16 (95% CI 1.03 to 1.31); heat: 97.5th percentile of temperature 1.37 (95% CI 1.13 to 1.66) and 99th percentile of temperature 1.38 (95% CI 1.13 to 1.69)). We found a slightly decreasing trend in heat-related SCZ hospitalisations and a sharp increasing trend in cold effects from 2005 to 2014. However, the risk of heat-related hospitalisation has been rising since 2008. Stratified analyses showed that age and gender had different modification effects on temporal trends.
Conclusions The findings highlight that as temperatures rise the body’s adaptability to high temperatures may be accompanied by more threats from extreme cold. The burden of cold-related SCZ hospitalisations may increase in the future.
- environmental exposure
- risk assessment
Data availability statement
No data are available.
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Contributors RP: conceptualisation, software, writing of original draft, investigation. QW, WY: software. QW: validation, data curation. JC: writing-review and editing, methodology. HS: project administration, funding acquisition, writing-review and editing.
Funding This work was supported by the National Natural Science Foundation of China (grant number: 81773518).
Competing interests None declared.
Provenance and peer review Not commissioned; externally peer reviewed.
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