Fine particulate matter estimated by mathematical model and hospitalizations for pneumonia and asthma in children

Abstract

Objective:To estimate the association between exposure to fine particulate matter with an aerodynamic diameter <2.5 microns (PM2.5) and hospitalizations for pneumonia and asthma in children.Methods:An ecological study of time series was performed, with daily indicators of hospitalization for pneumonia and asthma in children up to 10 years of age, living in Taubaté (SP) and estimated concentrations of PM2.5, between August 2011 and July 2012. A generalized additive model of Poisson regression was used to estimate the relative risk, with lag zero up to five days after exposure; the single pollutant model was adjusted by the apparent temperature, as defined from the temperature and relative air humidity, seasonality and weekday.Results:The values of the relative risks for hospitalization for pneumonia and asthma were significant for lag 0 (RR=1.051, 95%CI; 1.016 to 1.088); lag 2 (RR=1.066, 95%CI: 1.023 to 1.113); lag 3 (RR=1.053, 95%CI: 1.015 to 1.092); lag 4 (RR=1.043, 95%CI: 1.004 to 1.088) and lag 5 (RR=1.061, 95%CI: 1.018 to 1.106). The increase of 5mcg/m3 in PM2.5 contributes to increase the relative risk for hospitalization from 20.3 to 38.4 percentage points; however, the reduction of 5µg/m3 in PM2.5 concentration results in 38 fewer hospital admissions.Conclusions:Exposure to PM2.5 was associated with hospitalizations for pneumonia and asthma in children younger than 10 years of age, showing the role of fine particulate matter in child health and providing subsidies for the implementation of preventive measures to decrease these outcomes.

Air pollution and respiratory diseases: ecological time series

“…Likewise, a study in Taubaté, SP, which has a population similar to that of Volta Redonda, also found an association between exposure to PM 2.5 , at concentrations similar to those of Volta Redonda, and hospitalizations due to pneumonia and asthma among children. 13 Chronic and sub-chronic exposure to fine particulate matter, among other pollutants, was shown to be a risk factor for hospitalization due to acute bronchiolitis among children in California. 19 Using logistic regression, those authors showed that there was an association between exposure to PM 2.5 and the outcome of hospitalization due to acute bronchiolitis; and that an increase in PM 2.5 concentration of 10 µg/m 3 increased the odds of hospitalization by 9% (95% CI: 1.04-1.14).…”

“…5,[12][13][14] The importance of studying how exposure to this pollutant can act on human health comes from the fact that, because of its aerodynamic diameter (less than 2.5 microns), it can remain suspended in the air for a longer time and thus be transported over longer distances and also reach deeper portions of the respiratory system.…”

Efeitos da exposição a poluentes do ar na saúde das crianças de Cuiabá, Mato Grosso, Brasil

“…This model is used operationally by the Center for Weather Forecasting and Climate Studies of the Brazilian National Institute for Space Research (CPTEC/INPE) in an operational base. It estimates PM 2.5 concentrations every three hours, resulting in eight estimates made by the model at 40m aboveground, with a resolution of 25x25km 13,14 ; Recent applications of data estimated by CCATT-BRAMS in epidemiological studies can be found in César et al 15,16 , Silva et al 17 , Nascimento et al 18 , and Carmo et al 19 .…”

Condições Climáticas E O Risco De Exacerbação Da Asma

“…César et al 22 estimaram a associação entre exposição ao material particulado fino com as internações por pneumonia e asma em crianças com até 10 anos, em Taubaté e usaram o modelo aditivo generalizado de regressão de Poisson para estimar o risco relativo, com defasagem de zero até cinco dias após a exposição; o modelo unipoluente foi ajustado pela temperatura aparente, medida definida a partir da temperatura e umidade relativa do ar, sazonalidade e dia da semana. Os valores dos riscos relativos para internações por pneumonia e asma foram significativos para lag 0 (RR=1,051; IC95% 1,016-1,088); lag 2 (RR=1,066; IC95% 1,023-1,113); lag 3 (RR=1,053; IC95% 1,015-1,092); lag 4 (RR=1,043; IC95% 1,004-1,088) e no lag 5 (RR=1,061; IC95% 1,018-1,106).…”