Association between short-term ambient temperature variability and depressive symptoms: using staggered adoption of low-carbon city program in China as a quasi-natural experiment

Abstract

Growing epidemiological evidence has shown that ambient temperature variability (TV) contributes to multiple health problems. However, whether short-term TV affects mental health remains unclear. Based on a nationally representative cohort sample from 2011 to 2018 in China, this study linked monthly TV with depressive symptoms. City-level data on daily temperature for 1 month prior to the survey date were collected. The TV in 1 month for each participant, measured by the standard deviations (SDs) of daily humidex, daily mean temperature, daily minimum temperature, and daily maximum temperature, was calculated based on the above daily data. The 10-item Center for Epidemiologic Studies Depression Scale (CES-D) was used to measure depressive symptoms. Random effects models and difference-in-difference models based on the introduction of low-carbon cities (LCCs) were applied. A one-point increase in the 1-month SDs of daily humidex and mean temperature was associated with 0.096 (95% confidence interval (CI): 0.040–0.152) and 0.178 (95% CI: 0.081–0.276) increases in CES-D scores. Similar associations were found when temperature variability was measured by the SDs of the daily minimum temperature and maximum temperature. In addition, a positive and statistically significant mental health effect of changes in TV was found after the introduction of the LCCs. A one-point increase in monthly TV, measured by daily humidex, was associated with an increase in the CES-D score of 0.148 (95% CI: 0.018–0.277) for those experiencing the introduction of LCCs. Our results suggest that mental health improvements should account for ambient TV in China.