This study used a time-series model to investigate the relationship between exposure of air pollutants (PM2.5 and O3) and non-accidental mortality and respiratory mortality in Lishui district, Jiangsu Province, China from 2015 to 2019. Research results showed that short-term exposure to PM2.5 and O3 was positively correlated with an increased risk of non-accidental and respiratory mortality.
The daily average concentration of PM2.5 in Lishui district is 43.57µg/m3, which was higher than the National Ambient Air Quality Standard (NAAQS) first-level standard, but lower than the second-level standard (the first-level standard is 35µg/m3, the second-level standard is 75µg /m3). The MDA8 O3 was 100.13µg/m3, which was also higher than the NAAQS first-level standard, but lower than the second-level standard (the first-level standard is 100µg/m3 and the second-level standard is 160µg/m). The seasonal fluctuation of pollutant concentration was mainly manifested as follows. PM2.5 was higher in spring and winter than in summer and autumn and reached its peak in summer. O3 was higher in summer and autumn than in spring and winter, and peaks in winter. A seasonal pattern in the number of daily mortalities was also observed, with higher mortality in winter. This observed seasonal fluctuation may be related to the increase in sources of pollutants and meteorological factors. In winter, industrial production, motor vehicle, and combustion emissions (such as coal, biofuels) are the most direct factors that produce PM2.5. High temperature and sufficient sunshine in summer are favorable conditions for photochemical reaction to produce O3. Using chemical industrial solvents and emitting the volatile organic compounds and nitrogen oxides from automobile exhaust may cause high levels of O3.
In this study, we found that in the single pollutant model, PM2.5 had acute effects on non-accidental mortality. Every 10µg/m3 increase in PM2.5 was associated with a 0.94 % (95%CI: 0.05%-1.83%) increase in non-accidental mortality at lag0. A study conducted in a highly polluted area in China found that 10µg/m3 increase in PM2.5 was associated with 0.36% (95% CI: 0.10%-0.63%) increase of non-accidental mortality. Lin found that every 10µg/m3 increase in PM2.5 was associated with 1.5% (95% CI: 0.5%-2.5%) of non-accidental mortality among the elderly over 65 years old . A study conducted in 75 cities in the United States showed that for every 10µg/m3 increase in PM2.5, the non-accidental mortality rate increased by 1.18% (95% CI: 0.93%-1.44%). Another large-scale study involving multiple countries and regions found that for every 10µg/m3 increase in PM2.5, the daily non-accidental mortality rate increased by 0.68% (95% CI: 0.59–0.77%). Although our data analysis results showed that the impact of PM2.5 on non-accidental mortality in Lishui district was slightly higher, it was generally consistent with the results of previous research reports in China. This difference may be mainly related to the age difference of the exposed population. Moreover, the sources and chemical composition of PM2.5 in different regions are different, which may also lead to different effects on mortality.
Besides, we also found that O3 had acute effects on respiratory mortality. Every 10µg/m3 increase in O3 was associated with an increase in respiratory disease mortality by 1.35% (95%CI: 0.05%-2.66%) at lag7. A study in Jinan showed that Every 10µg/m3 increase in O3 was associated with a 0.975% (95% CI: 0.463, 1.489) increase in respiratory mortality at lag3. Another study in Hefei showed that every 10µg/m3 increase in O3 led to a 2.22% (95%CI: 0.56%-3.90%) increase in respiratory mortality. A Sichuan study found that every 10µg/m3 increase in O3 led to a 0.78% (95%CI: 0.12%-1.44%) increase in respiratory mortality. Since the middle-aged and elderly population was the research object this time, the impact of O3 in Lishui district on respiratory mortality would be slightly higher, but it was consistent with the results of domestic and foreign research[35–37]. With the rapid development of the economic level and the acceleration of the urbanization process, the output of industrial manufacturing was also increasing, which may lead to the increase of volatile organic compounds (VOCs) emissions. This may be one of the reasons that O3 in Lishui district had a greater impact on the respiratory mortality of the middle-aged and elderly. In this study, the impact of multi-day moving average lag was higher than that of single-day lag, but the effect was not statistically significant, which was consistent with Costa’s research results.
Subgroup analysis showed that air pollutants were significantly related to non-accidental and respiratory mortality in different genders and seasons. Women were more sensitive to be affected by PM2.5 on non-accidental mortality. This was consistent with the research of Shinand Hu. Because women may have stronger airway responsiveness, combined with hormones or other factors, and therefore had a stronger physiological response to air pollutants[42, 43]. However, there was also conflicting research evidence that men were more susceptible to the impact of PM2.5 on non-accidental mortality[44, 45]. In contrast, we found that men were more susceptible to the effects of O3 on respiratory mortality than women. A research carried out in Shenzhen also found the same result. This can be explained by the fact that pneumonia and bronchitis were more common in men, and many men have a smoking history and different occupational exposures, which may exacerbate the impact of O3 on respiratory mortality.
As far as the seasonal effect is concerned, the O3 concentration in summer had a statistically significant effect on non-accidental mortality. This is consistent with the research of Zanobetti. In summer, as the temperature rises, the ozone precursor substances in the air produce O3 faster, which has harmed the health of the population. Arch also found that although the concentration of O3 in winter is at the lowest level throughout the year, the effect of O3 on non-accidental mortality was also great. Wang's research results were consistent with ours. A study in Nanjing found that the concentration of indoor O3 in winter may be greater than that of outdoor O3, and indoor O3 produced by electrical equipment is harmful to people’s health. This may be because the middle-aged and elderly spend more time indoors in winter, and outdoor O3 exposure cannot represent the actual O3 exposure of them. Our research also found that ozone in spring and autumn had an effect on non-accidental mortality but was not statistically significant. Research conducted in many regions of East Asia found that O3 levels in different seasons have varying degrees of impact on non-accidental mortality. This may be due to geographical heterogeneity. To identify susceptible groups, we also explored the potential modification effects of age, but in our study, we did not observe significant modification effects of age groups.
In the two-pollutant model, after O3 was included in the PM2.5 model, the effect of PM2.5 on non-accidental and respiratory mortality was reduced. After PM2.5 was included in the O3 model, the effect of O3 on non-accidental and respiratory mortality was reduced too. The results of this study were the opposite of previous studies[29, 53]. From our time-series analysis of PM2.5 and O3, it can be seen that PM2.5 was higher in winter, and O3 was higher in summer in Lishui district. The seasonal difference between PM2.5 and O3 may be the main reason for the reduction of the effect in the two-pollutant model.
In the attributable fraction analysis, nearly 0.84% of non-accidental mortality can be attributable to PM2.5, and reducing the concentration of PM2.5 could save 122(95%CI:6-237) lives of the middle-aged and elderly. In addition, 0.14% respiratory mortality,can be attributable to O3༌and reducing the concentration of O3 could save 20(95%CI:1–38) lives of middle-aged and elderly. This finding highlights the deleterious effects of air pollution on people. Therefore, Lishui district authorities take measures to improve the atmospheric environment, which has a positive role in promoting the construction of the senior care demonstration zone.
This study has some limitations. First, we used the average concentration of air pollutants at the monitoring station as the population exposure level, without considering the indoor exposure. This would lead to exposure measurement errors and deviations in the accuracy and intensity of risk estimates. Secondly, time-series analysis was an ecological study that requires a large sample size. The sample size of respiratory mortality in this study was relatively small, which may lead to unstable results. Finally, this study did not collect information on smoking history, body mass index, drug history, and educational level. These potential confounding factors may also have a potential impact on the association between air pollution and mortality.