Geographical variation in lung cancer risk associated with road traffics in Jiading District, Shanghai

Shao, Yueqin; Wang, Yingjian; Yu, Hong-jie; Zhang, Yiying; Xiang, Fang; Yang, Ya; Yu, Yang; Li, Linhan; Dong, Shurong; Yang, Dongjian; Cheng, Wan Ling; Chen, Yue; Jiang, Qingwu; Xie, Juan; Sun, Weishan; Zhou, Yibiao

doi:10.1016/j.scitotenv.2018.10.266

Cited by 21 publications

(23 citation statements)

References 41 publications

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“…When the exposure concentration was highly spatially and geographically heterogeneous, mis-estimation of exposures would be introduced into analysis (9). In recent years, multi-pollutant indicators have been adopted to investigate the association with health outcomes to better evaluate realworld exposure to pollutants such as residential distance to the closest roads (10), factory density (11), and traffic density (12). Residential proximity to road has been found to be a good proxy for traffic-related air pollutant concentrations (13).…”

Section: Introductionmentioning

confidence: 99%

Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai

Peng¹,

Zhang

Yu³

et al. 2021

Front. Public Health

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Background: Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death in China. Although numerous studies have been conducted to determine the risk factors for COPD mortality such as ambient air pollution, the results are not fully consistent.Methods: This study included mortality analysis and a case-control design by using the data extracted from the Mortality Registration System in Jiading District, Shanghai. Traditional logistic regression, geographically weighted logistic regression (GWLR), and spatial scan statistical analysis were performed to explore the geographic variation of COPD mortality and the possible influencing factors.Results: Traditional logistic regression showed that extreme lower temperature in the month prior to death, shorter distance to highway, lower GDP level were associated with increased COPD mortality. GWRL model further demonstrated obvious geographical discrepancies for the above associations. We additionally identified a significant cluster of low COPD mortality (OR = 0.36, P = 0.002) in the southwest region of Jiading District with a radius of 3.55 km by using the Bernoulli model. The geographical variation in age-standardized mortality rate for COPD in Jiading District was explained to a certain degree by these factors.Conclusion: The risk of COPD mortality in Jiading District showed obvious geographical variation, which were partially explained by the geographical variations in effects of the extreme low temperature in the month prior to death, residential proximity to highway, and GDP level.

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Section: Introductionmentioning

confidence: 99%

Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai

Peng¹,

Zhang

Yu³

et al. 2021

Front. Public Health

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“…For example, Richardson et al utilized an ecological design in the U.S. that covered 43 millions of city residents to examine relationship between greenness and lung cancer mortality, and findings showed no such relationship [21]. A recent case-control study conducted in Shanghai, China uncovered a null association between NDVI and lung cancer incidence [22].…”

Section: Discussionmentioning

confidence: 99%

Association between Surrounding Greenness and Mortality: An Ecological Study in Taiwan

Lee

Chang

et al. 2020

IJERPH

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Exposure to surrounding greenness is associated with reduced mortality in Caucasian populations. Little is known however about the relationship between green vegetation and the risk of death in Asian populations. Therefore, we opted to evaluate the association of greenness with mortality in Taiwan. Death information was retrieved from the Taiwan Death Certificate database between 2006 to 2014 (3287 days). Exposure to green vegetation was based on the normalized difference vegetation index (NDVI) collected by the Moderate Resolution Imagine Spectroradiometer (MODIS). A generalized additive mixed model was utilized to assess the association between NDVI exposure and mortality. A total of 1,173,773 deaths were identified from 2006 to 2014. We found one unit increment on NDVI was associated with a reduced mortality due to all-cause (risk ratio [RR] = 0.901; 95% confidence interval = 0.862–0.941), cardiovascular diseases (RR = 0.892; 95% CI = 0.817–0.975), respiratory diseases (RR = 0.721; 95% CI = 0.632–0.824), and lung cancer (RR = 0.871; 95% CI = 0.735–1.032). Using the green land cover as the alternative green index showed the protective relationship on all-cause mortality. Exposure to surrounding greenness was negatively associated with mortality in Taiwan. Further research is needed to uncover the underlying mechanism.

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“…Furthermore, some studies have demonstrated that built environments substantially impact air quality and further impact respiratory diseases [ 16 ]. Urban planning layout [ 17 ], land use [ 18 ], road traffic [ 19 ], green space [ 20 ] and other spatial elements affect the concentration and dispersion of air pollutants [ 21 ]. Wang and Chen’s study confirmed that population density, land use, road and transport, and urban planning were the main factors related to the spatial distribution of air pollution in Hangzhou [ 22 ].…”

Section: Introductionmentioning

confidence: 99%

Impacts of Built Environment on Risk of Women’s Lung Cancer: A Case Study of China

Xie

Shao

Yang

et al. 2022

IJERPH

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Built environment factors such as air pollution are associated with the risk of respiratory disease, but few studies have carried out profound investigation. We aimed to evaluate the association between the built environment and Chinese women’s lung cancer incidence data from the China Cancer Registry Annual Report 2017, which covered 345,711,600 people and 449 qualified cancer registries in mainland China. The air quality indicator (PM2.5) and other built environment data are obtained from the China Statistical Yearbook and other official approved materials. An exploratory regression tool is applied by using Chinese women’s lung cancer incidence data (Segi population) as the dependent variable, PM2.5 index and other built environment factors as the independent variables. An apparent clustering region with a high incidence of women’s lung cancer was discovered, including regions surrounding Bohai bay and the three Chinese northeastern provinces, Heilongjiang, Liaoning and Inner Mongolia. Besides air quality, built environment factors were found to have a weak but clear impact on lung cancer incidence. Land-use intensity and the greening coverage ratio were positive, and the urbanization rate and population density were negatively correlated with lung cancer incidence. The role of green spaces in Chinese women’s lung cancer incidence has not been proven.

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Geographical variation in lung cancer risk associated with road traffics in Jiading District, Shanghai

Cited by 21 publications

References 41 publications

Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai

Geographical Variation of COPD Mortality and Related Risk Factors in Jiading District, Shanghai

Association between Surrounding Greenness and Mortality: An Ecological Study in Taiwan

Impacts of Built Environment on Risk of Women’s Lung Cancer: A Case Study of China

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