1.Correlation study between respiratory death and airborne particles in Beijing: Spa-tiotemporal analysis based on satellite remote sensing data
Xiaoyin WU ; Guoxing LI ; Xuying WANG ; Fengchao LIANG ; Xiaochuan PAN
Journal of Peking University(Health Sciences) 2017;49(3):409-417
Objective: To use vertical and humidity correcting method to calibrate aerosol optical depth (AOD), and to explore the feasibility of calibrated-AOD as exposure index to measure the level of air pollutants from the ground and to establish the exposure-response relationship between calibrated-AOD and people's health outcomes.Methods: First of all, we interpolated AOD, PM2.5, relative humidity and planetary boundary layer height using Kriging method to obtain data at different locations and matched different data with respiratory death in Beijing by geographical coordinates.Then, the planetary boundary layer height and aerosol hygroscopic growth factor calculated based on relative humidity was used to calbrate the AOD.To compare the effects of calibrated-AOD and PM2.5, we used standardization method to get non dimensionless calibrated-AOD and PM2.5.At last, we used the generalized additive mixed model (GAMM) to estimate the acute effects of calibrated-AOD and PM2.5 on respiratory death and chronic obstructive pulmonary disease (COPD) death, after controlling the time trend, temperature and humidity effects, days of the week effect and holiday effects.Results: The correlation coefficient between calibrated-AOD and PM2.5 was 0.72.The effects of calibrated-AOD on respiratory death and COPD death was the strongest at lag 0-3, one unit of calibrated-AOD increases was associated with 3.64% (95%CI: 0.58%-6.78%) increase of respiratory death and 4.92% (95%CI: 1.81%-8.14%) increase of COPD death.As for PM2.5, the strongest effects appeared at lag 0-1, one unit of PM2.5 (about 155 μg/m3) increases was associated with excess risks of 3.96% (95%CI: 0.82%-7.19%) and 6.12% (95%CI: 1.44%-11.02%) for respiratory death and COPD death respectively.Compared with PM2.5, the effects of calibrated-AOD on respiratory death and COPD death had narrower confidence intervals.The calibrated-AOD was sensitive to capture the lag effects, and the cumulative lag effects of calibrated-AOD were all significant on multiple lag days which indicated that the calibrated-AOD was sensitive to capture cumulative lag effects of air pollutants on respiratory death and COPD death as well.Conclusion: We believe that calibrated-AOD can be used as an index to reflect the effects of air pollutants on respiratory death in Beijing.In the absence of ground monitoring, calibrated-AOD can be used to mea-sure the relationship between air pollutants and some health outcomes.
2.Study of relationship between atmospheric fine particulate matter concentration and one grade a tertiary hospital emergency room visits during 2012 and 2013 in Beijing.
Xuying WANG ; Guoxing LI ; Xiaobin JIN ; Jing MU ; Jie PAN ; Fengchao LIANG ; Lin TIAN ; Shi CHEN ; Qun GUO ; Wentan DONG ; Xiaochuan PAN
Chinese Journal of Preventive Medicine 2016;50(1):73-78
OBJECTIVETo explore the concentration-response relationship between ambient concentration of PM2.5 and daily total hospital emergency room visits in Beijing during 2012 and 2013. This study also examined the effects of ambient PM2.5 during heavy polluted days on emergency room visits compared with the light polluted days.
METHODSWe collected the daily meteorological factors monitoring data and concentrations of air pollutants in Beijing during October 1, 2012 to December 31, 2013. We also collected the daily emergency room visits from a tertiary hospital in Beijing in the same time period. Generalized additive model was fitted to estimate the association between the ambient PM2.5 and the hospital emergency room visits, by using the smooth function to adjust long term trend of time, public holidays and day of week. In addition, constrained piecewise linear function was then used to estimate the excess risk for different segment of concentration-response function.
RESULTSThe annual average concentration of PM2.5 was 90.9 µg/m(3) during October 1, 2012 and December 31, 2013. There were total 64 260 cases for total emergency room visits, of which respiratory disease had 9 849 cases and cardiovascular disease had 11 168 cases. PM2.5 was positive related with PM10, NO2 and SO2. The corresponding correlation coefficients were 0.87, 0.78 and 0.62, respectively (P<0.05). And PM2.5 was positively related with relative humidity, with correlation coefficient 0.45 (P<0.05). But PM2.5 was negatively related with mean temperature (r=-0.17, P< 0.05) and wind speed (- 0.32, P<0.05). In the single polluted model, after adjusting the effects of temperature, relative humidity and wind, every 10 µg/m(3) increase of concentration of ambient PM2.5, the corresponding excess risk of daily emergency room visits was 0.25% (95% CI: 0.07-0.43). In the two-pollutant model PM2.5+SO2 and PM2.5+NO2, every 10 µg/m(3) increase of concentration of ambient PM2.5, the corresponding excess risk of daily emergency room visits were 1.07% (95%CI:0.83-1.30) and 0.56% (95%CI: 0.32-0.80) respectively, which were higher than the effect in single pollutant model. Average concentration of ambient particulate matters (PM2.5) was 204.16 µg/m(3) during heavy pollution, higher than control period (85.24 µg/m(3)). When PM2.5 as the primary air pollutants during heavy polluted days, we observed a significant increase in emergency room visits, and the odd ratios was 1.16 (95% CI:1.09-1.22).
CONCLUSIONThere were positive correlation between high concentration of ambient particulate matters (PM2.5) and increasing daily emergency room visits. Especially during the heavy polluted days, the effects of elevated concentration of PM2.5 on hospital emergency room visits were much larger.
Air Pollutants ; analysis ; Beijing ; Cardiovascular Diseases ; diagnosis ; Emergency Service, Hospital ; statistics & numerical data ; Humans ; Meteorological Concepts ; Particulate Matter ; analysis ; Respiratory Tract Diseases ; diagnosis ; Temperature ; Tertiary Care Centers
3.Joint effects of meteorological factors and PM2.5 on age-related macular degeneration: a national cross-sectional study in China.
Jiayu HE ; Yuanyuan LIU ; Ai ZHANG ; Qianfeng LIU ; Xueli YANG ; Naixiu SUN ; Baoqun YAO ; Fengchao LIANG ; Xiaochang YAN ; Yang LIU ; Hongjun MAO ; Xi CHEN ; Nai-Jun TANG ; Hua YAN
Environmental Health and Preventive Medicine 2023;28():3-3
BACKGROUND:
Weather conditions are a possible contributing factor to age-related macular degeneration (AMD), a leading cause of irreversible loss of vision. The present study evaluated the joint effects of meteorological factors and fine particulate matter (PM2.5) on AMD.
METHODS:
Data was extracted from a national cross-sectional survey conducted across 10 provinces in rural China. A total of 36,081 participants aged 40 and older were recruited. AMD was diagnosed clinically by slit-lamp ophthalmoscopy, fundus photography, and spectral domain optical coherence tomography (OCT). Meteorological data were calculated by European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and were matched to participants' home addresses by latitude and longitude. Participants' individual PM2.5 exposure concentrations were calculated by a satellite-based model at a 1-km resolution level. Multivariable-adjusted logistic regression models paired with interaction analysis were performed to investigate the joint effects of meteorological factors and PM2.5 on AMD.
RESULTS:
The prevalence of AMD in the study population was 2.6% (95% CI 2.42-2.76%). The average annual PM2.5 level during the study period was 63.1 ± 15.3 µg/m3. A significant positive association was detected between AMD and PM2.5 level, temperature (T), and relative humidity (RH), in both the independent and the combined effect models. For PM2.5, compared with the lowest quartile, the odds ratios (ORs) with 95% confidence intervals (CIs) across increasing quartiles were 0.828 (0.674,1.018), 1.105 (0.799,1.528), and 2.602 (1.516,4.468). Positive associations were observed between AMD and temperature, with ORs (95% CI) of 1.625 (1.059,2.494), 1.619 (1.026,2.553), and 3.276 (1.841,5.830), across increasing quartiles. In the interaction analysis, the estimated relative excess risk due to interaction (RERI) and the attributable proportion (AP) for combined atmospheric pressure and PM2.5 was 0.864 (0.586,1.141) and 1.180 (0.768,1.592), respectively, indicating a synergistic effect between PM2.5 and atmospheric pressure.
CONCLUSIONS
This study is among the first to characterize the coordinated effects of meteorological factors and PM2.5 on AMD. The findings warrant further investigation to elucidate the relationship between ambient environment and AMD.
Humans
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Adult
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Middle Aged
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Cross-Sectional Studies
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Air Pollutants/analysis*
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Particulate Matter/analysis*
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China/epidemiology*
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Macular Degeneration/etiology*
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Meteorological Concepts