Attributable risk of ambient PM10 on daily mortality and years of life lost in Chengdu, China

Chen, Fei; Deng, Zibing; Deng, Ying; Qiao, Zhijiao; Lan, Lan; Meng, Qiong; Luo, Bin; Zhang, Wei; Ji, Kui; Qiao, Xue; Fan, Zhining; Zhang, Meixia; Cui, Yan; Zhao, Xing; Li, Xiaosong

doi:10.1016/j.scitotenv.2016.12.151

Cited by 50 publications

(27 citation statements)

References 37 publications

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“…We used the Spearman correlation test to identify the correlations among four air pollutants and five meteorological factors. Considering the nonlinear exposure-lag-response relationship between outdoor exposure to air pollution and health (Chen et al, 2017;Guo et al, 2017), we adopted the DLNM to control the exposure-lag-response effect. The DLNM adds a lag dimension to the relationship between exposure and response and describes the variation of dependent variables in terms of both independent variable and lag dimensions.…”

Section: Statistics Analysismentioning

confidence: 99%

“…Nonlinear exposure-lag-response relationships have been demonstrated between outdoor air pollution and multiple health outcomes (Chen et al, 2017;Guo et al, 2017). The distributed-lag nonlinear model (DLNM) is an advanced time-series analysis method proposed by Gasparrini (Gasparrini, 2011;Gasparrini et al, 2010), that has been widely used to explore the relationships between meteorological factors and health outcomes (Buteau et al, 2018;Gasparrini, 2014;Neophytou et al, 2018), but has seldom been applied to evaluate the relationship between outdoor exposure to air pollution and active TB risk.…”

Section: Introductionmentioning

confidence: 99%

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Long-term effect of exposure to ambient air pollution on the risk of active tuberculosis

Mao

et al. 2019

International Journal of Infectious Diseases

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To explore the long-term effect of exposure to ambient air pollution on the risk of active tuberculosis (TB). Methods: We constructed a distributed-lag nonlinear model (DLNM) to evaluate the relatively long-term influence of outdoor PM 2.5 , PM 10 , SO 2 and NO 2 exposure on active TB risk in the city of Lianyungang in Jiangsu Province, China. Results: There were 7,282 TB cases reported in the study area during 2014-2017, with annual median (interquartile range) concentrations of PM 2.5 , PM 10 , SO 2 and NO 2 at 45.86 (34.57-64.14) mg/m 3 , 85.43 (62.86-116.14) mg/m 3 , 22.00 (15.71-30.86) mg/m 3 and 30.00 (23.29-38.57) mg/m 3 , respectively. The single-pollutant model showed that for each 10 mg/m 3 increase in concentration, the cumulative relative risk of TB was 1.12 (lag 0-24 weeks, 95% CI: 1.03-1.22) for PM 2.5 with reference to 35 mg/m 3 ; 1.11 (lag 0-21 weeks, 95% CI: 1.06-1.17) for PM 10 with reference to 70 mg/m 3 ; 1.37 (lag 0-20 weeks, 95% CI: 1.16-1.62) for SO 2 with reference to 60 mg/m 3 ; and 1.29 (lag 0-22 weeks, 95% CI: 1.11-1.49) for NO 2 with reference to 40 mg/m 3. In the multipollutant model considering both PM 10 and NO 2 , the association remained significant. Conclusions: Our results revealed a potential association between outdoor exposure to PM 2.5 , PM 10 , SO 2 , and NO 2 and active TB. Considering that people from developing countries continue to be exposed to both severe outdoor air pollution and high rates of latent TB infection, the association between worsening air pollution and active TB deserves further attention.

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Section: Statistics Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Long-term effect of exposure to ambient air pollution on the risk of active tuberculosis

Mao

et al. 2019

International Journal of Infectious Diseases

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“…2 We fitted natural cubic splines with a priori 3 df to control for meteorological variables. 3 As strong correlations between temperature and air pressure (r = -0.94 ) and between relative humidity and rainfall (r = 0.73 ) were observed in the initial analysis (see eTable 1), air pressure and rainfall were excluded from the final models to avoid collinearity.…”

Section: Section 2 Distributed Lag Nonlinear Model (Dlnm)mentioning

confidence: 99%

Association of air pollution with the risk of initial outpatient visits for tuberculosis in Wuhan, China

Liao

Yin

et al. 2019

Occup Environ Med

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ObjectivesPrevious studies suggested the association of air pollution with initial Mycobacterium tuberculosis infection and the disease development. However, few studies have been conducted on air pollution and initial tuberculosis (TB) consults using short-interval data. We investigated the weekly association between air pollution and initial TB outpatient visits.MethodsWe used a Poisson regression model combined with a distributed lag non-linear model to conduct a time-series study with weekly air pollution data and TB cases during 2014–2017 in Wuhan, China.ResultsA 10 µg/m3 increase in NO2 (nitrogen dioxide) was associated with 11.74% (95% CI: 0.70 to 23.98, lag 0–1 weeks), 21.45% (95% CI: 1.44 to 45.41, lag 0–2 weeks) and 12.8% (95% CI: 0.97 to 26.02, lag 0–1 weeks) increase in initial TB consults among all patients with TB, old patients (≥60 years old) and male ones, respectively. A 10 µg/m3 increase in SO2 (sulfur dioxide) was associated with −22.23% (95% CI: −39.23 to −0.49, lag 0–16 weeks), −28.65% (95% CI: −44.3 to −8.58, lag 0–16 weeks), −23.85 (95% CI: −41.79 to −0.37, lag 0–8 weeks) and −23.82% (95% CI: −41.31 to −1.11, lag 0–16 weeks) increase in initial TB consults among the total, young (aged 15–59 years old), old and male patients, respectively. In old patients, a 0.1 mg/m3 increase in CO (carbon monoxide) and a 10 µg/m3 increase in PM2.5 (particulate matter) were separately associated with 42.32% (95% CI: 1.16 to 100.22, lag 0–16 weeks) and 17.38% (95% CI: 0.28 to 37.38, lag 0–16 weeks) increases in TB consults.ConclusionOur study first highlighted the importance of weekly association between air pollution and the risk of initial TB consults, which is helpful for the arrangements of TB screening and medical assistance.

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“…Chen et al [ 13 ] found that as the PM 10 concentration in northern China increased by 10 mg/m 3 , lung cancer mortality increased by 3.4% to 13.6%. Furthermore, Chen et al [ 14 ] found that between 2010 and 2014, increased concentrations of PM 10 in Chengdu have resulted in increased mortality. Maleki et al [ 15 ] found that between2009 and 2014, high concentrations of PM 10 caused 3777 deaths in Ahvaz, Iran.…”

Section: Introductionmentioning

confidence: 99%

Correlation Analysis of PM10 and the Incidence of Lung Cancer in Nanchang, China

Zhou

Hu³

2017

IJERPH

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Air pollution and lung cancer are closely related. In 2013, the World Health Organization listed outdoor air pollution as carcinogenic and regarded it as the most widespread carcinogen that humans are currently exposed to. Here, grey correlation and data envelopment analysis methods are used to determine the pollution factors causing lung cancer among residents in Nanchang, China, and identify population segments which are more susceptible to air pollution. This study shows that particulate matter with particle sizes below 10 micron (PM10) is most closely related to the incidence of lung cancer among air pollution factors including annual mean concentrations of SO2, NO2, PM10, annual haze days, and annual mean Air Pollution Index/Air Quality Index (API/AQI). Air pollution has a greater impact on urban inhabitants as compared to rural inhabitants. When gender differences are considered, women are more likely to develop lung cancer due to air pollution. Smokers are more likely to suffer from lung cancer. These results provide a reference for the government to formulate policies to reduce air pollutant emissions and strengthen anti-smoking measures.

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Attributable risk of ambient PM10 on daily mortality and years of life lost in Chengdu, China

Cited by 50 publications

References 37 publications

Long-term effect of exposure to ambient air pollution on the risk of active tuberculosis

Long-term effect of exposure to ambient air pollution on the risk of active tuberculosis

Association of air pollution with the risk of initial outpatient visits for tuberculosis in Wuhan, China

Correlation Analysis of PM10 and the Incidence of Lung Cancer in Nanchang, China

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