| 摘要: |
| 基于2004—2016年的全球地表PM2.5数据和中国31个省级行政区（不含港澳台地区）的传染病年发病率数据，探究了PM2.5质量浓度与9种传染病（百日咳、猩红热、流脑、麻疹、肺结核、风疹、流行性腮腺炎、急性出血性结膜炎以及流行性感冒）发病率的相关关系。研究发现PM2.5质量浓度整体呈现东高西低、北高南低的空间分布特征。EOF分析显示浓度变化有着北增南减、东增西减的趋势。同时，PM2.5浓度在北方的变化程度要远大于南方，在欠发达地区的变化程度要大于发达地区，但年际变化特征并不明显。选择了三类地区分析PM2.5和传染病发病率的关系，发现在华北和东北地区与PM2.5浓度显著相关的传染病类型高达5种，在所有传染病中，百日咳与PM2.5浓度的相关性最为显著。最后针对三类地区，通过线性拟合得到了部分传染病发病率与PM2.5浓度的关系式，指出PM2.5浓度每上升100 μg∙m−3时，与PM2.5浓度显著正相关的传染病发病率会出现不同程度的上升。 |
| 关键词: PM2.5浓度 传染病发病率 Pearson相关 |
| DOI：10.7515/JEE192047 |
| CSTR：32259.14.JEE192047 |
| 分类号: |
| 基金项目:国家自然科学基金项目（41775003，91837103） |
| 英文基金项目:National Natural Science Foundation of China (41775003, 91837103) |
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| The correlation analysis of PM2.5 mass concentrations with infectious diseases in China |
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LUO Yuan, XIE Li, CHEN Siyu, ZANG Zhou, WU Dongyou
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1. College of Atmospheric Sciences, Lanzhou University, Key Laboratory for Semi-Arid Climate Change, Ministry of Education, Lanzhou 730000, China
2. Gansu Provincial Hospital, Lanzhou 730000, China
3. Beijing Normal University, Beijing 100875, China
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| Abstract: |
| Background, aim, and scope In the past two decades, voluminous epidemiological studies and clinical literature have documented the harm of air pollution to human health, among which PM2.5 has been widely considered as the main pollutant in the air. PM2.5 is closely related to various kinds of epidemics. The incidence rate, mortality rate, pollutant emission, and health care resources display significant spatial heterogeneity across China. The impact of PM2.5 on human health shows large discrepancies among different regions. Therefore, in view of the spatial difference in disease incidence rate in China, high-resolution correlation analysis is conducted using data of PM2.5 and infectious diseases in the sub-region scale. Materials and methods In this study, global surface PM2.5 data from 2004 to 2016 and the annual incidence of infectious diseases in 31 provincial-level administrative regions in China (excluding Hong Kong, Macao and Taiwan) are used. The correlation between PM2.5 concentration and the incidence of 9 kinds of infectious diseases is explored by using Theil-Sen slope estimation and empirical orthogonal function (EOF) analysis. In this study, the correlation between the incidence of some infectious diseases and PM2.5 concentration was obtained by the linear fitting. Results In China, the PM2.5 mass concentration in the east is higher than the west, while the concentration in the north is higher compared with the concentration in the south. EOF analysis reveals that the concentration rises in northern and eastern China, whereas in southern and western China it shows a decreasing trend from 2004 to 2016. Discussion This study defines three areas with high incidence of infectious diseases and PM2.5 mass concentrations, and finds that up to 5 types of infectious diseases are significantly correlated with PM2.5 concentration in northern China and northeastern China. Of all the infectious diseases, the incidence of pertussis shows the strongest correlation with PM2.5 concentrations. It is pointed out that for every 100 μg·m−3 increase in PM2.5 concentration, the incidence of infectious diseases that are significantly positively correlated with PM2.5 concentration will increase to varying degrees. Conclusions The areas with close correlation between the incidence of infectious diseases and PM2.5 concentration are mainly concentrated in the areas with high PM2.5 concentration, among which the incidence of pertussis has the most significant correlation with PM2.5. The rise in PM2.5 concentration can potentially lead to an increase in the incidence of diseases, thus posing a certain impact on human health. Recommendations and perspectives In future research, the meteorological factors, economic development level, and population density can be taken into account to improve the reliability and accuracy of the study. |
| Key words: the concentration of PM2.5 the morbidity of infectious diseases Pearson correlation |
