Background: The relationship between temperature and mental disorders is still unclear. This study aims to assess the short-term effect of apparent temperature (AT) on daily emergency visits of mental and behavioral disorders (MDs) in Beijing, China.
Methods: Daily counts of emergency visits related to MDs in Beijing from 2016 to 2018 were obtained. A quasi-Poisson generalized additive model combined with a distributed lag non-linear model (DLNM) was applied to analyze the lag-exposure-response relationship between AT and emergency admissions related to MDs. Sunshine duration, precipitation, PM2.5, SO2, O3, time trend, day of week and holiday were adjusted in the model.
Results: Total daily emergency visits for MDs during the study period were 16,606. With the reference of -2.4 °C (temperature with the minimum emergency visit risk), the single day effects of low AT (-8.6 °C, 10th percentile) and high AT (9.2 °C, 90th percentile) on MDs emergency visits reached a relative risk peak of 1.043 (95%CI: 1.017-1.069) on lag day 4 and 1.105 (95%CI: 1.006-1.215) on lag day 1, respectively. The greatest cumulative effect of high AT emerged on lag 0-5 days and reached a relative risk of 1.435 (95%CI: 1.048-1.965), while no significant cumulative effect of low AT was observed. There was a significant effect of high AT on emergency visits of MDs due to psychoactive substance use and male patients.
Conclusions: Both low and high AT are demonstrated to be the significant risk factors of MDs, which highlights the need of strengthening the health interventions, patient medical services and early warning for patients.
Keywords: Apparent temperature; Distributed lag non-linear model; Emergency visits; Mental and behavioral disorders.
Copyright © 2020 The Authors. Published by Elsevier B.V. All rights reserved.