Dataset Information

Spatiotemporal analysis of air pollution and asthma patient visits in Taipei, Taiwan.

ABSTRACT:

Background

Buffer 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).

Results

We 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.

Conclusion

This 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.

SUBMITTER: Chan TC

PROVIDER: S-EPMC2694149 | biostudies-literature | 2009 May

REPOSITORIES: biostudies-literature

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Publications

Spatiotemporal analysis of air pollution and asthma patient visits in Taipei, Taiwan.

Chan Ta-Chien TC Chen Mei-Lien ML Lin I-Feng IF Lee Cheng-Hua CH Chiang Po-Huang PH Wang Da-Wei DW Chuang Jen-Hsiang JH

International journal of health geographics 20090507

<h4>Background</h4>Buffer 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).<h4>Results</h4>We analyzed daily outpatient ...[more]

PMID: 19419585

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Project description:Ambient air pollution was known to cause central nervous system diseases and depressive symptoms. In this study, we examined the associations between air pollution exposure and the prevalence of insomnia in Taipei City of Taiwan. We applied the health information system of electrical medical records of Taipei City Hospital to collect a total of 5108 study subjects (insomniacs N = 912 and non-insomniacs N = 4196) over 18 years old from the family medicine and internal medicine outpatients of six branches of Taipei City Hospital. These patients were grouped into insomniacs and non-insomniacs following the primary insomnia diagnosis (ICD9:780.52, 780.54, 307.41, 307.42, ICD10: G47.00, G47.01, G47.09, F51.01, F51.09) and the prescription times of anxiolytics and hypnotics. We estimated one-year average concentrations of PM2.5, ozone, and NOx before the first date of insomnia diagnosis and the last date of outpatient visit for insomniacs and non-insomniacs, respectively, by using the data of nearest air quality monitoring stations relative to study subjects' residential addresses. Logistic regression analysis was employed to examine the independent effects of air pollution concentrations on the risk of insomnia. One-year average PM2.5, ozone, and NOx levels for insomniacs was significantly higher than those of non-insomniacs. After adjusting for confounding factors, increase each 1(μg/m3) in one-year average PM2.5 showed a statistically significant association with insomnia (the odds ratio 1.610, 95% CI [1.562,1.660]). As to multi pollutants, one-year average PM2.5 (1.624, [1.570, 1.681] and ozone (1.198, [1.094, 1.311]) exposure showed a significant association with insomnia. Subgroup analysis revealed that the influence of PM2.5 and ozone on insomnia have significant risks in people with major chronic disease. This study demonstrated a positive association between PM2.5 and ozone exposure and the prevalence of hypnotic-treated insomnia. Especially, the people with major chronic diseases were with obvious effect of PM2.5 and ozone on risk of insomnia.

Project description:BACKGROUND/OBJECTIVES: There is evidence that exposure to air pollution affects asthma, but the effect of air pollution on asthma severity has not been addressed. The aim was to assess the relation between asthma severity during the past 12 months and home outdoor concentrations of air pollution. METHODS: Asthma severity over the past 12 months was assessed in two complementary ways among 328 adult asthmatics from the French Epidemiological study on the Genetics and Environment of Asthma (EGEA) examined between 1991 and 1995. The four-class severity score integrated clinical events and type of treatment. The five-level asthma score is based only on the occurrence of symptoms. Nitrogen dioxide (NO(2)), sulphur dioxide (SO(2)) and ozone (O(3)) concentrations were assigned to each residence using two different methods. The first was based on the closest monitor data from 1991 to 1995. The second consisted of spatial models that used geostatistical interpolations and then assigned air pollutants to the geo-coded residences (1998). RESULTS: Higher asthma severity score was significantly related to the 8-hour average of ozone during April-September (O(3)-8 h) and the number of days (O(3)-days) with 8-hour ozone averages above 110 microg.m(-3) (for a 36-day increase, equivalent to the interquartile range, in O(3)-days, odds ratio 2.22 (95% confidence interval 1.61 to 3.07) for one class difference in score). Adjustment for age, sex, smoking habits, occupational exposure, and educational level did not alter results. Asthma severity was unrelated to NO(2). Both exposure assessment methods and severity scores resulted in very similar findings. SO(2) correlated with severity but reached statistical significance only for the model-based assignment of exposure. CONCLUSIONS: The observed associations between asthma severity and air pollution, in particular O(3), support the hypothesis that air pollution at levels far below current standards increases asthma severity.

Dataset Information

Spatiotemporal analysis of air pollution and asthma patient visits in Taipei, Taiwan.

Background

Results

Conclusion

Publications

Spatiotemporal analysis of air pollution and asthma patient visits in Taipei, Taiwan.

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