Assessment of temperature on mortality burden and economic impacts in a basin-located mega-city.

OBJECTIVE

This study aimed to examine the association between ambient temperature and non-accidental mortality, and to systematically quantify the mortality burden and economic impacts attributable to non-optimum temperatures in Chengdu in 2022.

METHODS

We collected daily non-accidental mortality records for 23 counties from the Chengdu Center for Disease Control and Prevention from January 1, 2015, to December 31, 2021, along with potential effect modifiers covering demographic, air quality, and socioeconomic indicators. A Poisson-based distributed lag non-linear model (DLNM) was used to estimate the temperature-non-accidental mortality association, followed by quantification of non-optimal temperature-related mortality risk and burden. We further evaluated the excess deaths and associated economic burden of non-optimal temperatures in Chengdu in 2022 using the value of statistical life (VSL) method.

RESULTS

During the study period, 584,063 non-accidental deaths were recorded, and a stable U-shaped temperature-mortality association was identified. In total, non-optimal temperatures accounted for 7.24% of non-accidental mortality, with a higher AF for cold temperatures (5.82%) than for hot temperatures (1.42%). The AFs for cardiovascular and respiratory disease mortality were 10.59% and 7.63%, respectively. More significant mortality burdens related to non-optimal temperatures were found in females, the elderly (≥75 years), and groups with low education or alternative marital status. In 2022, non-optimal temperature exposure led to 11,316 excess deaths in Chengdu, translating into a VSL-based mortality economic loss of 21.428 billion RMB.

CONCLUSIONS

Given ongoing global climate change, the mortality burden and economic losses caused by non-optimal temperatures in this basin-located mega-city merit urgent attention. Corresponding adaptive strategies are therefore required to protect the general public, especially vulnerable populations, from worsening climate-related health risks.