Air pollution and respiratory diseases: ecological time series

• Published in: São Paulo medical journal Vol. 134; no. 4; pp. 315 - 321
• Main Authors: Nascimento, Luiz Fernando Costa, Vieira, Luciana Cristina Pompeo Ferreira, Mantovani, Kátia Cristina Cota, Moreira, Demerval Soares
• Format: Journal Article
• Language: English
• Published: Brazil Associação Paulista de Medicina - APM 01-07-2016; Associação Paulista de Medicina
• Subjects: Air Pollutants - adverse effects; Air Pollutants - analysis; Air Pollutants - economics; Air pollution; Brazil; Bronchiolitis; Female; Humans; Inhalation Exposure - adverse effects; Inhalation Exposure - economics; Male; Mathematical models; MEDICINE, GENERAL & INTERNAL; Particulate matter; Particulate Matter - adverse effects; Particulate Matter - analysis; Particulate Matter - economics; Patient Admission - economics; Patient Admission - statistics & numerical data; Pneumonia; Poisson Distribution; Reference Values; Respiratory Tract Diseases - economics; Respiratory Tract Diseases - etiology; Risk Assessment; Risk Factors; Time Factors; Weather; Pneumonia; Particulate matter; Material particulado; Modelos matemáticos; Air pollution; Mathematical models; Bronquiolite; Poluição do ar; Bronchiolitis
• ISSN: 1516-3180; 1806-9460; 1806-9460
• DOI: 10.1590/1516-3180.2015.0237250216

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).
Ecological time series study using data from Volta Redonda (RJ).
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 µg/m3.
There were 752 hospitalizations in 2012; the average concentration of PM2.5 was 17.2 µg/m3; 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 µg/m3 could reduce admissions by up to 76 cases, with a decrease in spending of R$ 84,000 a year.
The findings from this study provide support for implementing public health policies in this municipality, which is an important steelmaking center.