Abstract:
Objective To analyze the correlation between extreme high temperature weather and non-accidental deaths among residents in Yichang city, Hubei province, and to provide a reference for reducing the risk of non-accidental deaths.
Methods Data on 46 170 non-accidental deaths in urban areas of Yichang from 2014 to 2022 were collected from the death registration system of the Yichang Center for Disease Control and Prevention. Daily air pollution monitoring data from five national automatic air quality monitoring stations, as well as urban meteorological data during the same period, were also collected. A time-stratified case-crossover design with a conditional logistic regression model was used to analyze the effects of nine extreme high temperature events on the risk of non-accidental death among Yichang residents. These events included daily mean ambient air temperatures not lower than the 92.5th/95.0th/97.5th percentile during the study period and lasting 1, 2, or 3 days, abbreviated as P92.5/95.0/97.5-1/2/3 d.
Results The analysis included 46 170 case days and 157 134 matched control days. Of the 46 170 non-accidental deaths registered during the period, 3 371 (7.30%) occurred during the P92.5-1 d event, followed by 3 041 (6.59%) during P92.5-2 d, 2 597 (5.62%) during P92.5-3 d, 2 436 (5.28%) during P95.0-1 d, 2 205 (4.78%) during P95.0-2 d, 1 960 (4.25%) during P95.0-3 d, 1 343 (2.91%) during P97.5-1 d, 1 148 (2.49%) during P97.5-2 d, and 882 (1.91%) during P97.5-3 d, respectively. After controlling for relative humidity (RH), fine particulate matter ≤ 2.5 μm in aerodynamic diameter (PM2.5), inhalable particulate matter ≤ 10 μm in aerodynamic diameter (PM10), sulfur dioxide (SO2), nitrogen dioxide (NO2), ozone (O3), carbon monoxide (CO), and the gender and age of the deceased, the time-stratified case-crossover analysis showed that all nine extreme high temperature events were positively correlated with increased risk of non-accidental deaths among Yichang residents, with a lag effect Except for the P92.5-2 d and P92.5-3 d events, which lasted until lag day 3, the effects of the other seven extreme high temperature events lasted until lag day 1. The maximum effect values for all nine extreme high temperature events were at lag day 0, with odds ratios (OR) and their 95% confidence intervals (CI) of 1.09 (1.04 – 1.14) for P92.5-1 d, 1.08 (1.03 – 1.14) for P92.5-2 d, 1.11 (1.05 – 1.16) for P92.5-3 d, 1.15 (1.09 – 1.22) for P95.0-1 d, 1.17, (1.10 – 1.24) for P95.0-2 d, 1.17 (1.10 – 1. 25) for P95.0-3 d, 1.23 (1.15 – 1.32) for P97.5-1 d, 1.27 (1.18 – 1.38) for P97.5-2 d, and 1.31(1.19 – 1.43) for P97.5-3 d. Stratified analysis showed that the effects of extreme high temperature events on non-accidental deaths persisted in different sex and age subgroups. For both male and female subgroups, the effect of P97.5-3 d was strongest at lag day 0, with ORs (95%CI) of 1.36 (1.21 – 1.54) for males and 1.24 (1.08 – 1.43) for females. Older residents were more sensitive to extreme high temperature events. The P92.5-1 d, P92.5-2 d, and P92.5-3 d events had significant effects on non-accidental deaths only in residents aged 70 – 79 and ≥ 80 years, with the ORs (95%CI) of 1.17 (1.06 – 1.29) and 1.19 (1.10 – 1.29) for P92.5-1 d at lag day 0 for residents aged 70 – 79 and ≥ 80 years, followed by 1.15 (1.05 – 1.28) and 1.19 (1.10 – 1.29) for P92.5-2 d, 1.15 (1.04 – 1.29) and 1.23 (1.13 – 1.34) for P92.5-3 d.
Conclusion Extremely high temperatures may increase the risk of non-accidental deaths among Yichang residents.