Mortality distribution tests.

<div> Background It is crucial to comprehend the interplay between air pollution and meteorological conditions in relation to population health within the framework of "dual-carbon" targets. The purpose of this study was to investigate the impact of intricate environmental factors, encompassing both meteorological conditions and atmospheric pollutants, on respiratory disease (RD) mortality in Qingdao, a representative coastal city in China. Methods The RD mortality cases were collected from the Chronic Disease Surveillance Monitoring System in Qingdao during Jan 1st, 2014 and Dec 31st, 2020. The distributed-lag nonlinear model and generalized additivity model were used to assess the association between daily mean temperature (DMT), air pollutant exposure and RD mortality. To ascertain the robustness of the model and further investigate this relationship, a stratified analysis and sensitivity analysis were conducted to mitigate potential confounding factors. Results A total of 19,905 mortalities from RD were recorded. The minimum mortality temperature (MMT) was determined to be 23.5°C, and DMT and RD mortality showed an N-shaped relationship. At the MMT of 23.5°C, the cumulative relative risk (cumRR) for mortality within a lag period of 0–14 days from the highest temperature (31°C) was estimated at 2.114 (95% confidence interval [CI]: 1.475 ~ 3.028). The effect value of particulate matter (PM) also increased with a longer cumulative lag time. In the single pollutant model, the highest risk of RD mortality was observed on the lag1-day of per 10 μg/m³ increase in PM_2.5 exposure, with an excess risk ratio (ER) of 0.847% (95% CI: 0.335% ~ 1.362%). The largest cumulative effect was found at a lag of 8 days, with an ER of 1.546% (95% CI: 0.483% ~ 2.621%). A similar trend was found for PM₁₀. For O₃ exposure, the highest risk was observed on the lag1-day of per 10 μg/m³ increase, with an ER of 1.073% (95% CI: 0.502% ~ 1.647%), and the largest cumulative effect occurred at a lag of 2 days with an ER of 1.113% (95%CI: 0.386% ~ 1.844%). Results from the dual-pollutants model demonstrated that the effect of PM on the risk of RD mortality remained significant and slightly increased in magnitude. Moreover, composite pollutants exhibited a higher risk effect, reaching its peak after one week; however, there was a decrease in single-day cumulative effects as more pollutant types were included. Subgroup analysis showed that females, elderly individuals, and those exposed during warm seasons demonstrated greater susceptibility to PM exposure. Conclusion The present study revealed a significant association between short-term exposure to high temperature, PM_2.5, PM₁₀ and O₃ and the risk of RD mortality in Qingdao, even in dual- and composite-pollutants models. Furthermore, our findings indicate that females, the elderly population, and warm seasons exhibit heightened sensitivity to PM exposure. </div>