A GIS-based spatial correlation analysis for ambient air pollution and AECOPD hospitalizations in Jinan, China

Wang, Wenqiao; Ying, Yangyang; Wu, Quanyuan; Zhang, Haiping; Ma, Dedong; Xiao, Wei

doi:10.1016/j.rmed.2015.01.006

Cited by 48 publications

(34 citation statements)

References 15 publications

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“…or by artificial ones (biomass, coal and wood burning, traffi c, including dusty roads, industry, etc.). 2 The measured levels of PM 10 in Pleven in 2012 showed mean yearly level of 45.48 μg/m 3 and 106 days with levels of PM 10 above 50 μg/ m 3 . It makes it one of most polluted cities in the Europe.…”

Section: Levels Of Pm 10mentioning

confidence: 93%

“…The daily mean concentrations of PM 10 were found to correlate signifi cantly with the daily mean concentrations of NO 2 and SO 2 (ρ 0.34 and ρ 0.49, respectively; p=0.0001). The negative correlations between the daily mean temperature and the daily mean levels of PM 10 , NO 2 and SO 2 were also signifi cant (ρ -0.44, ρ -0.11, and ρ -0.37, respectively; p=0.0001). The daily number of AECOPD correlated with the mean levels of PM 10 in the previous six days (ρ 0.14; p=0.02) and the lower outdoor temperature (ρ -0.2; p=0.001).…”

mentioning

confidence: 93%

“…Environmental pollution can be one of the main risk factors for acute exacerbations of COPD, emergency department admissions, hospitalizations, and even death. 2 Air pollution in Bulgaria continues to be a problem of significant magnitude. The country comprises approximately 1% of the European Union population but produces 2.5% from all particulate matter (PM) emissions.…”

Section: Introductionmentioning

confidence: 99%

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Impact of Air Pollution and Outdoor Temperature on the Rate of Chronic Obstructive Pulmonary Disease Exacerbations

et al. 2017

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Citation: Krachunov II, Kyuchukov NH, Ivanova ZI, Yanev NA, Hristova PA, Borisova ED, Popova TP, Pavlov PS, Nikolova PT, Ivanov YY. Impact of air pollution and outdoor temperature on the rate of chronic obstructive pulmonary disease exacerbations.Folia Medica 2017;59(4): 423-9. doi: 10.1515/folmed-2017-0053 Background: Environmental pollution can be one of the main risk factors for acute exacerbations of chronic obstructive pulmonary disease (COPD). Aim: To study the relationship between air pollution, outdoor temperature and exacerbations of COPD. Materials and methods: COPD patients (n=1432) were followed up for one year. The levels of particulate matter up to 10 μm (PM 10 ), nitrogen dioxide (NO 2 ), sulfur dioxide (SO 2 ) and outside temperatures were collected from the Environmental Agency database.Results: A total of 309 acute COPD exacerbations (AECOPD) were recorded in the analysis. The daily mean concentrations of PM 10 were found to correlate signifi cantly with the daily mean concentrations of NO 2 and SO 2 (ρ 0.34 and ρ 0.49, respectively; p=0.0001). The negative correlations between the daily mean temperature and the daily mean levels of PM 10 , NO 2 and SO 2 were also signifi cant (ρ -0.44, ρ -0.11, and ρ -0.37, respectively; p=0.0001). The daily number of AECOPD correlated with the mean levels of PM 10 in the previous six days (ρ 0.14; p=0.02) and the lower outdoor temperature (ρ -0.2; p=0.001). The negative correlation between the daily number of AECOPD and the mean daily temperature was stronger in days with levels of PM 10 above 50 μg/m 3 (ρ -0.3 p=0.02 vs. ρ -0.18 p= 0.01). Conclusion: Lower daily mean temperatures were associated with the levels of air pollutants. The level of PM 10 correlated with the levels of the other air pollutants. The daily number of AECOPD was found to correlate weakly, but signifi cantly with the mean level of PM 10 in the previous six days. BACKGROUND

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Section: Levels Of Pm 10mentioning

confidence: 93%

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confidence: 93%

Section: Introductionmentioning

confidence: 99%

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Impact of Air Pollution and Outdoor Temperature on the Rate of Chronic Obstructive Pulmonary Disease Exacerbations

et al. 2017

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“…Previous studies have used this method to examine the health effects of air pollutants (Sun et al 2013;Wang et al 2015). Some studies also indicated that the kriging method provided the more accurate exposure estimates and could affect the evaluation of the health effects in an epidemiological study (Son et al 2010).…”

Section: Introductionmentioning

confidence: 99%

Spatiotemporal analysis for the effect of ambient particulate matter on cause-specific respiratory mortality in Beijing, China

Wang

Guo

et al. 2016

Environ Sci Pollut Res

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This study explored the association between particulate matter with an aerodynamic diameter of less than 10 μm (PM10) and the cause-specific respiratory mortality. We used the ordinary kriging method to estimate the spatial characteristics of ambient PM10 at 1-km × 1-km resolution across Beijing during 2008-2009 and subsequently fit the exposure-response relationship between the estimated PM10 and the mortality due to total respiratory disease, chronic lower respiratory disease, chronic obstructive pulmonary disease (COPD), and pneumonia at the street or township area levels using the generalized additive mixed model (GAMM). We also examined the effects of age, gender, and season in the stratified analysis. The effects of ambient PM10 on the cause-specific respiratory mortality were the strongest at lag0-5 except for pneumonia, and an inter-quantile range increase in PM10 was associated with an 8.04 % (95 % CI 4.00, 12.63) increase in mortality for total respiratory disease, a 6.63 % (95 % CI 1.65, 11.86) increase for chronic lower respiratory disease, and a 5.68 % (95 % CI 0.54, 11.09) increase for COPD, respectively. Higher risks due to the PM10 exposure were observed for females and elderly individuals. Seasonal stratification analysis showed that the effects of PM10 on mortality due to pneumonia were stronger during spring and autumn. While for COPD, the effect of PM10 in winter was statistically significant (15.54 %, 95 % CI 5.64, 26.35) and the greatest among the seasons. The GAMM model evaluated stronger associations between concentration of PM10. There were significant associations between PM10 and mortality due to respiratory disease at the street or township area levels. The GAMM model using high-resolution PM10 could better capture the association between PM10 and respiratory mortality. Gender, age, and season also acted as effect modifiers for the relationship between PM10 and respiratory mortality.

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“…Some scholars used GIS in their studies. Therefore, many methods including geographically weighted regression [33] and spatial correlation analysis [34] were introduced. Dujardin et al [35] analyzed the impact of territorial structures upon energy consumption in the Wakkoon Region and revealed that some rural settlements characterized by low density show good performance in terms of energy efficiency.…”

Section: Related Studiesmentioning

confidence: 99%

Spatial Distribution of Energy Consumption and Carbon Emission of Regional Logistics

Fan

Wang

et al. 2015

Sustainability

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Facing serious energy-related constraints and environmental stress, the development of the green logistics industry is restricted by degrees of logistics energy utilization and carbon emissions. Considering different logistics spatial distributions, this paper uses the degree of regional logistics energy utilization and the spatial distribution of carbon emissions as two indicators of green logistics to investigate the regional differences and changes in spatiotemporal logistics energy efficiency. We firstly measure the regional logistics in terms of energy consumption and carbon emission, then further measure the logistics by energy intensity and carbon intensity. Based on these four indicators, the relations between spatiotemporal logistics and regional logistics development are analyzed. Through studying the spatial and temporal evolution trends of the above indicators, we found that a certain convergence exists. Finally, based on the analysis, the suggestions for energy saving and emission reduction are proposed according to regional conditions. The results benefit to narrow the efficiency gap between regions and achieve the goal of improving logistics energy efficiency. OPEN ACCESSSustainability 2015, 7 9141

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A GIS-based spatial correlation analysis for ambient air pollution and AECOPD hospitalizations in Jinan, China

Cited by 48 publications

References 15 publications

Impact of Air Pollution and Outdoor Temperature on the Rate of Chronic Obstructive Pulmonary Disease Exacerbations

Impact of Air Pollution and Outdoor Temperature on the Rate of Chronic Obstructive Pulmonary Disease Exacerbations

Spatiotemporal analysis for the effect of ambient particulate matter on cause-specific respiratory mortality in Beijing, China

Spatial Distribution of Energy Consumption and Carbon Emission of Regional Logistics

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