Dataset Information

Comparing ozone metrics on associations with outpatient visits for respiratory diseases in Taipei Metropolitan area.

ABSTRACT: This study reported cumulative 6-day (lag 0-5 days) relative risks (RR) and confidence intervals (CI) of daily outpatient visits for total respiratory disease (RD), asthma, and chronic airway obstruction not otherwise classified (CAO) associated with three ozone metrics (daily 1-h maximum (O3, 1 h max), 8-h average maximum (O3, 8 h max), 24-h average (O3, 24 h avg)), and an alternative oxidant indicator (Ox) in Taipei Metropolitan, using distributed lag non-linear models after controlling for potential confounders. The Ox showed the strongest association with outpatient visits for total RD (RR = 1.10, 95% CI: 1.10, 1.11) and asthma (RR = 1.18, 95% CI: 1.00, 1.39) in the cold season. The O3, 24 h avg appeared to be the optimal ozone metric associating with total RD than O3, 1 h max and O3, 8 h max based on model selection. In conclusion, outpatient visits for total RD associated with ozone vary with ozone metrics, disease and season.

SUBMITTER: Lin YK

PROVIDER: S-EPMC7127381 | biostudies-literature | 2013 Jun

REPOSITORIES: biostudies-literature

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Comparing ozone metrics on associations with outpatient visits for respiratory diseases in Taipei Metropolitan area.

Lin Yu-Kai YK Chang Shuenn-Chin SC Lin Chitsan C Chen Yi-Chun YC Wang Yu-Chun YC

Environmental pollution (Barking, Essex : 1987) 20130117

This study reported cumulative 6-day (lag 0-5 days) relative risks (RR) and confidence intervals (CI) of daily outpatient visits for total respiratory disease (RD), asthma, and chronic airway obstruction not otherwise classified (CAO) associated with three ozone metrics (daily 1-h maximum (O3, 1 h max), 8-h average maximum (O3, 8 h max), 24-h average (O3, 24 h avg)), and an alternative oxidant indicator (Ox) in Taipei Metropolitan, using distributed lag non-linear models after controlling for po ...[more]

PMID: 23333210

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Project description:Given that fine particulate matter (? 2.5 ?m; 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.We 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.Using 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.Considering 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 17?(H),21?(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.Our 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.

Project description:BACKGROUND:Arrhythmia is a common cardiovascular event that is associated with increased cardiovascular health risks. Previous studies that have explored the association between air pollution and arrhythmia have obtained inconsistent results, and the association between the two in China is unclear. METHODS:We collected daily data on air pollutants and meteorological factors from 1st January 2014 to 31st December 2016, along with daily outpatient visits for arrhythmia in Hangzhou, China. We used a quasi-Poisson regression along with a distributed lag nonlinear model to study the association between air pollution and arrhythmia morbidity. RESULTS:The results of the single-pollutant model showed that each increase of 10??g/m3 of Fine particulate matter (PM2.5), Coarse particulate matter (PM10), Sulphur dioxide (SO2), Nitrogen dioxide (NO2), and Ozone (O3) resulted in increases of 0.6% (-?0.9, 2.2%), 0.7% (-?0.4, 1.7%), 11.9% (4.5, 19.9%), 6.7% (3.6, 9.9%), and?-?0.9% (-?2.9, 1.2%), respectively, in outpatient visits for arrhythmia; each increase of 1?mg/m3 increase of carbon monoxide (CO) resulted in increase of 11.3% (-?5.9, 31.6%) in arrhythmia. The short-term effects of air pollution on arrhythmia lasted 3?days, and the most harmful effects were observed on the same day that the pollution occurred. Results of the subgroup analyses showed that SO2 and NO2 affected both men and women, but differences between the sexes were not statistically significant. The effect of SO2 on the middle-aged population was statistically significant. The effect of NO2 was significant in both the young and middle-aged population, and no significant difference was found between them. Significant effects of air pollution on arrhythmia were only detected in the cold season. The results of the two-pollutants model and the single-pollutant model were similar. CONCLUSIONS:SO2 and NO2 may induce arrhythmia, and the harmful effects are primarily observed in the cold season. There is no evidence of PM2.5, PM10, CO and O3 increasing arrhythmia risk. Special attention should be given to sensitive populations during the high-risk period.

Project description:BackgroundBuffer analyses have shown that air pollution is associated with an increased incidence of asthma, but little is known about how air pollutants affect health outside a defined buffer. The aim of this study was to better understand how air pollutants affect asthma patient visits in a metropolitan area. The study used an integrated spatial and temporal approach that included the Kriging method and the Generalized Additive Model (GAM).ResultsWe analyzed daily outpatient and emergency visit data from the Taiwan Bureau of National Health Insurance and air pollution data from the Taiwan Environmental Protection Administration during 2000-2002. In general, children (aged 0-15 years) had the highest number of total asthma visits. Seasonal changes of PM10, NO2, O3 and SO2 were evident. However, SO2 showed a positive correlation with the dew point (r = 0.17, p < 0.01) and temperature (r = 0.22, p < 0.01). Among the four pollutants studied, the elevation of NO2 concentration had the highest impact on asthma outpatient visits on the day that a 10% increase of concentration caused the asthma outpatient visit rate to increase by 0.30% (95% CI: 0.16%~0.45%) in the four pollutant model. For emergency visits, the elevation of PM10 concentration, which occurred two days before the visits, had the most significant influence on this type of patient visit with an increase of 0.14% (95% CI: 0.01%~0.28%) in the four pollutants model. The impact on the emergency visit rate was non-significant two days following exposure to the other three air pollutants.ConclusionThis preliminary study demonstrates the feasibility of an integrated spatial and temporal approach to assess the impact of air pollution on asthma patient visits. The results of this study provide a better understanding of the correlation of air pollution with asthma patient visits and demonstrate that NO2 and PM10 might have a positive impact on outpatient and emergency settings respectively. Future research is required to validate robust spatiotemporal patterns and trends.

Dataset Information

Comparing ozone metrics on associations with outpatient visits for respiratory diseases in Taipei Metropolitan area.

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Comparing ozone metrics on associations with outpatient visits for respiratory diseases in Taipei Metropolitan area.

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