Air pollution and respiratory diseases: ecological time series

被引:16
作者
Costa Nascimento, Luiz Fernando [1 ,2 ,3 ]
Pompeo Ferreira Vieira, Luciana Cristina [1 ,4 ]
Cota Mantovani, Katia Cristina [1 ,4 ]
Moreira, Demerval Soares [1 ,5 ]
机构
[1] Univ Taubat UNITAU, Taubate, SP, Brazil
[2] Univ Estadual Paulista UNESP, Dept Energy, Guaratingueta, SP, Brazil
[3] Univ Taubate UNITAU, Dept Med, Taubate, SP, Brazil
[4] Univ Estadual Paulista UNESP, Dept Energy, Guaratingueta, SP, Brazil
[5] Univ Estadual Paulista Unesp, Fac Sci, Dept Phys, Bauru, SP, Brazil
来源
SAO PAULO MEDICAL JOURNAL | 2016年 / 134卷 / 04期
关键词
Particulate matter; Air pollution; Pneumonia; Bronchiolitis; Mathematical models; TRACER TRANSPORT MODEL; SYSTEM CATT-BRAMS; HOSPITAL ADMISSIONS; CARDIOVASCULAR-DISEASES; BRAZILIAN DEVELOPMENTS; COUPLED AEROSOL; FINE; POLLUTANTS; HEALTH; EXPOSURE;
D O I
10.1590/1516-3180.2015.0237250216
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
CONTEXT AND OBJECTIVE: Exposure to air pollutants is one of the factors responsible for hospitalizations due to respiratory diseases. The objective here was to estimate the effect of exposure to particulate matter (such as PM2.5) on hospitalizations due to certain respiratory diseases among residents in Volta Redonda (RJ). DESIGN AND SETTING: Ecological time series study using data from Volta Redonda (RJ). METHODS: Data on hospital admissions among residents of Volta Redonda (RJ), between January 1, 2012, and December 31, 2012, due to pneumonia, acute bronchitis, bronchiolitis and asthma, were analyzed. Daily data on PM2.5 concentrations were estimated through the CCATT-BRAMS model. The generalized additive Poisson regression model was used, taking the daily number of hospitalizations to be the dependent variable and the PM2.5 concentration to be the independent variable, with adjustment for temperature, relative humidity, seasonality and day of the week, and using lags of zero to seven days. Excess hospitalization and its cost were calculated in accordance with increases in PM2.5 concentration of 5 mu g/m(3). RESULTS: There were 752 hospitalizations in 2012; the average concentration of PM 2.5 was 17.2 mu g/m(3); the effects of exposure were significant at lag 2 (RR = 1.017), lag 5 (RR = 1.022) and lag 7 (RR = 1,020). A decrease in PM2.5 concentration of 5 mu g/m(3) could reduce admissions by up to 76 cases, with a decrease in spending of R$ 84,000 a year. CONCLUSION: The findings from this study provide support for implementing public health policies in this municipality, which is an important steelmaking center.
引用
收藏
页码:315 / 321
页数:7
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