| Literature DB >> 31623378 |
Qucheng Deng1, Yongping Wei2, Lijuan Chen3,4, Wei Liang5, Jijun Du6, Yuling Tan7, Yinjun Zhao8.
Abstract
Air pollution has become a global environmental challenge and poses major threats to human health, particularly for the aging population. However, few studies have investigated the effects of air pollutants on human longevity, especially based on the total regional quantities and sources. Based on investigation of the spatiotemporal variations of three air pollutants (PM10, SO2, and NOx) and three longevity indicators (centenarian ratio, centenarity index, and aging tendency), this study aims to identify the relationship between air pollution and regional longevity in Guangxi Province. Air pollutant and population data from 109 counties and areas of Guangxi were collected from environmental research reports and statistical yearbooks. Cluster and outlier analysis was used to detect the regions with high and low clusters of the longevity indicators and air pollutants. Geographically weighted regression analyses were performed to determine the relationship between longevity and air pollutants. A negative relationship between the air pollutants PM10, SO2, and NOx on the aged population was observed. From a provincial level, industrial sources from the urban areas of cities located in the central province, including Liuzhou, Nanning, Laibing, Guigang and Yulin, were important contributors to the air pollutants PM10, SO2, and NOx, and thus could contribute to negative impacts on regional longevity. The key findings from this study will provide a case for management of air pollutants based on public health policies in China as well as other developing communities.Entities:
Keywords: Guangxi; Hechi; air pollutants; geographically weighted regression; longevity
Mesh:
Year: 2019 PMID: 31623378 PMCID: PMC6801524 DOI: 10.3390/ijerph16193733
Source DB: PubMed Journal: Int J Environ Res Public Health ISSN: 1660-4601 Impact factor: 3.390
Figure 1Case study of Guangxi (B), (C) in China (A).
Descriptive statistics of the air pollutants.
| Indicators | Number | Minimum | Maximum | Mean | SD |
|---|---|---|---|---|---|
| SO2 t/a | 109 | 50 | 22,410 | 2329 | 3683 |
| NOx t/a | 109 | 80 | 17,820 | 1839 | 3060 |
| PM10 t/a | 109 | 130 | 10,620 | 2061 | 2013 |
Figure 2Spatial distribution of the three air pollutants (A–C) and the results (D–F) of the cluster and outlier analysis.
Figure 3Major air pollutants (A–C) and different sources (D–F) in 14 cities of Guangxi Province.
Figure 4Spatial distribution of the three longevity indicators(A–C) and the results (D–F) of the cluster and outlier analysis.
Descriptive statistics of the longevity indicators.
| Indicator | Number | Minimum | Maximum | Mean | SD |
|---|---|---|---|---|---|
| Centenarian ratio | 109 | 0.65 | 35.61 | 6.82 | 5.81 |
| Centenarity index | 109 | 0.22 | 10.28 | 2.88 | 1.79 |
| Aging tendency | 109 | 5.7 | 12.31 | 9.65 | 1.5 |
Summary of the GWR model of longevity indicators and air pollutants.
| Dependent Variable | Independent Variable | β | R2 | Adjust R2 |
|---|---|---|---|---|
| Centenarian ratio | SO2 | −0.163 | 51 | 37 |
| PM10 | −0.256 | 52 | 39 | |
| NOX | −0.176 | 49 | 35 | |
| Centenarity index | SO2 | −0.129 | 46 | 31 |
| PM10 | −0.199 | 44 | 30 | |
| NOx | −0.127 | 43 | 29 | |
| Aging tendency | SO2 | −0.035 | 57 | 41 |
| PM10 | −0.046 | 50 | 34 | |
| NOx | −0.055 | 60 | 46 |