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São Paulo med. j ; 138(2): 126-132, Mar.-Apr. 2020. tab, graf
Artigo em Inglês | LILACS, SES-SP | ID: biblio-1139673

RESUMO

ABSTRACT BACKGROUND: Exposure to particulate material produced as a result of increased agricultural activity may increase the number of pneumonia hospitalizations among children. We hope to contribute to the knowledge base through highlighting the environmental mechanisms involved in this outcome and optimizing pollutant control policies. OBJECTIVES: To investigate the association between pneumonia hospitalizations among children and presence of environmental pollutants in a town in the Brazilian Legal Amazon region. DESIGN AND SETTING: Time series study conducted in the town of Tangará da Serra, Mato Grosso (MT), Brazil. METHODS: A total of 158 children aged 0 to 10 years participated in the study. Data on environmental variables and pollutants were extracted daily through the Coupled Chemistry-Aerosol-Tracer Transport model coupled to Brazilian Regional Atmospheric Modeling System (CCATT-BRAMS). Meteorological data were provided by the Weather Forecasting and Climate Studies Center (CPTEC). RESULTS: There was greater frequency of pneumonia hospitalizations in the months of transition between the rainy and dry seasons, with a prevalence ratio 2.4 times higher than in other periods. For environmental pollutants, there was a significant positive correlation between particulate matter (PM2.5) and pneumonia hospitalizations (correlation 0.11), with more admissions on the days when PM2.5 levels were highest (averages of 6.6 µg/m3 when there were no admissions and 13.11 µg/m3 on days with two or more admissions). CONCLUSIONS: The higher the PM2.5 level was, the greater the frequency of hospitalizations also was. Children living in peripheral areas had higher prevalence of pneumonia hospitalizations in the dry period than those who were living in the town center.


Assuntos
Humanos , Recém-Nascido , Lactente , Pré-Escolar , Criança , Pneumonia/epidemiologia , Poluentes Atmosféricos , Poluição do Ar/estatística & dados numéricos , Estações do Ano , Brasil/epidemiologia , Fatores de Risco , Material Particulado , Hospitalização/estatística & dados numéricos
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