Health effect of temperature change on respiratory diseases in opposite phase in semi-arid region.

Abstract

The impact of temperature variation on health has attracted increasing attention under global climate change. A distributed lag non-linear model (DLNM) was performed to estimate the risk of two indicators of temperature change (diurnal temperature range (DTR) and temperature change between neighboring days (TCN)) on respiratory hospital visits in Lanzhou, a semi-arid climate city in western China from 2012 to 2018. The whole year is divided into two different temperature change periods according to the TCN of each solar term. The results showed that extreme high DTR can apparently enlarge respiratory risk, and it indicated strong cumulative relative risk (RR) in the temperature drop period. Extreme low TCN had strong adverse effects on respiratory diseases especially in temperature rise period, with the greatest RR of 1.068 (95% CI 1.004, 1.136). The effect of extreme high TCN was more obvious in temperature drop period, with a RR of 1.082 (95% CI 1.021, 1.148) at lag 7. Females were more affected by extreme temperature changes. Young people were more vulnerable to DTR, while TCN has a greater impact on the elderly.