Research on the cascading mechanism of “urban built environment-air pollution-respiratory diseases”
A case of Wuhan city
Bibliographic Data
| ID | 22076102 |
|---|---|
| Authors | Zhiqi Zhang (0000-0002-7988-3680, Wuhan Engineering Science & Technology Institute), Yue Ding (0000-0002-4478-1262, Wuhan Engineering Science & Technology Institute), Ruifeng Guo (0009-0000-9075-1884, Wuhan Engineering Science & Technology Institute), Qi Wang (0000-0003-0464-2118), Weimin Qi (0000-0002-6744-9326, Tongji Hospital, corresponding author), Yanfei Jia (Wuhan Engineering Science & Technology Institute, corresponding author) |
| Year | 2024 |
| Volume | 12 |
| Pages | 1333077-1333077 |
| Publication date | 2024-03-22 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Frontiers in Public Health (JOURNAL) |
| Journal identifiers | ISSN: 2296-2565 • E-ISSN: 2296-2565 |
| Publisher | Frontiers Media SA (PUBLISHER • CH) |
| DOI | 10.3389/fpubh.2024.1333077 |
| PMID | 38584928 |
| OpenAlex | W4393077066 |
| Language | EN |
| References cited | 62 |
Background Most existing studies have only investigated the direct effects of the built environment on respiratory diseases. However, there is mounting evidence that the built environment of cities has an indirect influence on public health via influencing air pollution. Exploring the “urban built environment-air pollution-respiratory diseases” cascade mechanism is important for creating a healthy respiratory environment, which is the aim of this study. Methods The study gathered clinical data from 2015 to 2017 on patients with respiratory diseases from Tongji Hospital in Wuhan. Additionally, daily air pollution levels (sulfur dioxide (SO 2 ), nitrogen dioxide (NO 2 ), particulate matter (PM 2.5 , PM 10 ), and ozone (O 3 )), meteorological data (average temperature and relative humidity), and data on urban built environment were gathered. We used Spearman correlation to investigate the connection between air pollution and meteorological variables; distributed lag non-linear model (DLNM) was used to investigate the short-term relationships between respiratory diseases, air pollutants, and meteorological factors; the impacts of spatial heterogeneity in the built environment on air pollution were examined using the multiscale geographically weighted regression model (MGWR). Results During the study period, the mean level of respiratory diseases (average age 54) was 15.97 persons per day, of which 9.519 for males (average age 57) and 6.451 for females (average age 48); the 24 h mean levels of PM 10 , PM 2.5 , NO 2 , SO 2 and O 3 were 78.056 μg/m 3 , 71.962 μg/m 3 , 54.468 μg/m 3 , 12.898 μg/m 3 , and 46.904 μg/m 3 , respectively; highest association was investigated between PM 10 and SO 2 ( r = 0.762, p < 0.01), followed by NO 2 and PM 2.5 ( r = 0.73, p < 0.01), and PM 10 and PM 2.5 ( r = 0.704, p < 0.01). We observed a significant lag effect of NO 2 on respiratory diseases, for lag 0 day and lag 1 day, a 10 μg/m 3 increase in NO 2 concentration corresponded to 1.009% (95% CI: 1.001, 1.017%) and 1.005% (95% CI: 1.001, 1.011%) increase of respiratory diseases. The spatial distribution of NO 2 was significantly influenced by high-density urban development (population density, building density, number of shopping service facilities, and construction land, the bandwidth of these four factors are 43), while green space and parks can effectively reduce air pollution ( R 2 = 0.649). Conclusion Previous studies have focused on the effects of air pollution on respiratory diseases and the effects of built environment on air pollution, while this study combines these three aspects and explores the relationship between them. Furthermore, the theory of the “built environment-air pollution-respiratory diseases” cascading mechanism is practically investigated and broken down into specific experimental steps, which has not been found in previous studies. Additionally, we observed a lag effect of NO 2 on respiratory diseases and spatial heterogeneity of built environment in the distribution of NO 2
Air pollutants · Air pollution · Biology · Environmental health · Geography · Meteorology · Nitrogen dioxide · Particulates · Pollutant · Respiratory system · Air Quality and Health Impacts · Climate Change and Health Impacts · Environmental Science · Medicine · Noise Effects and Management · Ecology · Pollution
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| Highly cited | No |
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