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Three Exposure Metrics for Fine Particulate Matter Associated With Outpatient Visits for Acute Lower Respiratory Infection Among Children in Guangzhou, China.

ABSTRACT: Ambient fine particulate matter (PM_2.5) is associated with an elevated risk of acute lower respiratory infections (ALRI). However, this association has not been examined using alternative exposure metrics. We collected outpatient data of patients with ALRI aged <14 years from the administrative database of a large tertiary hospital in Guangzhou, China, from 2013 to 2019. Ambient PM_2.5 was measured using three metrics: (a) daily mean, (b) daily excessive concentration hours (DECH), and (c) hourly peak. Generalized additive models were fitted to estimate the excess risk (ER) associated with PM_2.5. A total of 105,639 ALRI (35,310 pneumonia and 68,218 bronchiolitis) outpatient visits were identified during the study period. An interquartile range increment in PM_2.5 DECH was consistently associated with the highest ER of ALRI-related outpatient visits: 12.30% (95% confidence interval [CI]: 9.49-15.18%), compared with 11.20% (95% CI: 8.34-14.13%) for daily mean and 9.73% (95% CI: 6.97-12.55%) for hourly peak. The associations between the three metrics of PM_2.5 and ALRI-related outpatient visits were stronger in the cold season than in the warm season. Future studies should consider PM_2.5 DECH as an alternative method of exposure measurement, in addition to daily mean and hourly peak concentrations of PM_2.5.

SUBMITTER: Xiao D

PROVIDER: S-EPMC9218103 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:The burden of lower respiratory infections is primarily evident in the developing countries. However, the association between size-specific particulate matter and acute lower respiratory infection (ALRI) outpatient visits in the developing countries has been less studied. We obtained data on ALRI outpatient visits (N = 105,639) from a tertiary hospital in Guangzhou, China between 2013 and 2019. Over-dispersed generalized additive Poisson models were employed to evaluate the excess risk (ER) associated with the size-specific particulate matter, such as inhalable particulate matter (PM10), coarse particulate matter (PMc), and fine particulate matter (PM2.5). Counterfactual analyses were used to examine the potential percent reduction of ALRI outpatient visits if the levels of air pollution recommended by the WHO were followed. There were 35,310 pneumonia, 68,218 bronchiolitis, and 2,111 asthma outpatient visits included. Each 10 μg/m3 increase of 3-day moving averages of particulate matter was associated with a significant ER (95% CI) of outpatient visits of pneumonia (PM2.5: 3.71% [2.91, 4.52%]; PMc: 9.19% [6.94, 11.49%]; PM10: 4.36% [3.21, 5.52%]), bronchiolitis (PM2.5: 3.21% [2.49, 3.93%]; PMc: 9.13% [7.09, 11.21%]; PM10: 3.12% [2.10, 4.15%]), and asthma (PM2.5: 3.45% [1.18, 5.78%]; PMc: 11.69% [4.45, 19.43%]; PM10: 3.33% [0.26, 6.49%]). The association between particulate matter and pneumonia outpatient visits was more evident in men patients and in the cold seasons. Counterfactual analyses showed that PM2.5 was associated with a larger potential decline of ALRI outpatient visits compared with PMc and PM10 (pneumonia: 11.07%, 95% CI: [7.99, 14.30%]; bronchiolitis: 6.30% [4.17, 8.53%]; asthma: 8.14% [2.65, 14.33%]) if the air pollutants were diminished to the level of the reference guidelines. In conclusion, short-term exposures to PM2.5, PMc, and PM10 are associated with ALRI outpatient visits, and PM2.5 is associated with the highest potential decline in outpatient visits if it could be reduced to the levels recommended by the WHO.

Project description:Short-term exposure to ambient fine particulate matter (PM2.5) concentrations has been associated with increased mortality and morbidity. Determining which sources of PM2.5 are most toxic can help guide targeted reduction of PM2.5. However, conducting multicity epidemiologic studies of sources is difficult because source-specific PM2.5 is not directly measured, and source chemical compositions can vary between cities.We determined how the chemical composition of primary ambient PM2.5 sources varies across cities. We estimated associations between source-specific PM2.5 and respiratory disease emergency department (ED) visits and examined between-city heterogeneity in estimated associations.We used source apportionment to estimate daily concentrations of primary source-specific PM2.5 for four U.S. cities. For sources with similar chemical compositions between cities, we applied Poisson time-series regression models to estimate associations between source-specific PM2.5 and respiratory disease ED visits.We found that PM2.5 from biomass burning, diesel vehicle, gasoline vehicle, and dust sources was similar in chemical composition between cities, but PM2.5 from coal combustion and metal sources varied across cities. We found some evidence of positive associations of respiratory disease ED visits with biomass burning PM2.5; associations with diesel and gasoline PM2.5 were frequently imprecise or consistent with the null. We found little evidence of associations with dust PM2.5.We introduced an approach for comparing the chemical compositions of PM2.5 sources across cities and conducted one of the first multicity studies of source-specific PM2.5 and ED visits. Across four U.S. cities, among the primary PM2.5 sources assessed, biomass burning PM2.5 was most strongly associated with respiratory health. Citation: Krall JR, Mulholland JA, Russell AG, Balachandran S, Winquist A, Tolbert PE, Waller LA, Sarnat SE. 2017. Associations between source-specific fine particulate matter and emergency department visits for respiratory disease in four U.S. cities. Environ Health Perspect 125:97-103;?http://dx.doi.org/10.1289/EHP271.

Project description:BackgroundGiven that fine particulate matter (≤ 2.5 μm; PM2.5) is a mixture of multiple components, it has been of high interest to identify its specific health-relevant physical and/or chemical features.ObjectivesWe conducted a time-series study of PM2.5 and cardiorespiratory emergency department (ED) visits in the St. Louis, Missouri-Illinois metropolitan area, using 2 years of daily PM2.5 and PM2.5 component measurements (including ions, carbon, particle-phase organic compounds, and elements) made at the St. Louis-Midwest Supersite, a monitoring site of the U.S. Environmental Protection Agency Supersites ambient air monitoring research program.MethodsUsing Poisson generalized linear models, we assessed short-term associations between daily cardiorespiratory ED visit counts and daily levels of 24 selected pollutants. Associations were estimated for interquartile range changes in each pollutant. To allow comparison of relationships among multiple pollutants and outcomes with potentially different lag structures, we used 3-day unconstrained distributed lag models controlling for time trends and meteorology.ResultsConsidering results of our primary models, as well as sensitivity analyses and models assessing co-pollutant confounding, we observed robust associations of cardiovascular disease visits with 17α(H),21β(H)-hopane and congestive heart failure visits with elemental carbon. We also observed a robust association of respiratory disease visits with ozone. For asthma/wheeze, associations were strongest with ozone and nitrogen dioxide; observed associations of asthma/wheeze with PM2.5 and its components were attenuated in two-pollutant models with these gases. Differential measurement error due to differential patterns of spatiotemporal variability may have influenced patterns of observed associations across pollutants.ConclusionsOur findings add to the growing field examining the health effects of PM2.5 components. Combustion-related components of the pollutant mix showed particularly strong associations with cardiorespiratory ED visit outcomes.

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Three Exposure Metrics for Fine Particulate Matter Associated With Outpatient Visits for Acute Lower Respiratory Infection Among Children in Guangzhou, China.

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