OBJECTIVE: To investigate the effects of fine particulate matter emitted through biomass burning on hospitalizations for respiratory diseases in children living in Manaus, Northern Brazil. METHODS: Descriptive study with ecologic time series design carried out in Manaus from 2002 to 2009. Hospital admission data were obtained from the Unified Health System database. PM2.5 levels were estimated using aerosol remote sensing through the measurement of aerosol optical depth at a wavelength of 550 nm. Statistical methods were used in the data analysis, with Pearson correlation and multiple linear regression between variables, with a 95% confidence interval. RESULTS: The region of Manaus showed low PM2.5 concentrations when compared to the Southern Amazonian region. Between August and November (dry period in the region), was when the highest mean levels of PM2.5, estimated between 18 to 23 µg/m3, and the largest number of fires were observed. For the rainy season, an average of 12 µg/m3, 66% lower than the dry season measurements (20.6 µg/m3) was observed. The highest rates of hospitalization were observed during the rainy season and April was the month with the highest levels at 2.51/1,000 children. A positive association between hospital admissions and relative humidity (R = 0.126; p-value = 0.005) was observed, while the association between admissions and PM2.5 was negative and statistically significant (R = -0.168; p-value = 0.003). The R 2 of the final model (Hospitalizations = 2.19*Humidity - 1.60*PM2.5 - 0.23*Precipitation) explained 84% of hospitalizations due to respiratory disease in children living in Manaus, considering the independent variables statistically significant (humidity, PM2.5, and precipitation). CONCLUSIONS: Hospital admissions for respiratory diseases in children in Manaus, were more related to weather conditions and in particular relative humidity, than to exposure to aerosols emitted by biomass burning in the Amazonian region.
OBJECTIVE: To investigate the effects of fine particulate matter emitted through biomass burning on hospitalizations for respiratory diseases in children living in Manaus, Northern Brazil. METHODS: Descriptive study with ecologic time series design carried out in Manaus from 2002 to 2009. Hospital admission data were obtained from the Unified Health System database. PM2.5 levels were estimated using aerosol remote sensing through the measurement of aerosol optical depth at a wavelength of 550 nm. Statistical methods were used in the data analysis, with Pearson correlation and multiple linear regression between variables, with a 95% confidence interval. RESULTS: The region of Manaus showed low PM2.5 concentrations when compared to the Southern Amazonian region. Between August and November (dry period in the region), was when the highest mean levels of PM2.5, estimated between 18 to 23 µg/m3, and the largest number of fires were observed. For the rainy season, an average of 12 µg/m3, 66% lower than the dry season measurements (20.6 µg/m3) was observed. The highest rates of hospitalization were observed during the rainy season and April was the month with the highest levels at 2.51/1,000 children. A positive association between hospital admissions and relative humidity (R = 0.126; p-value = 0.005) was observed, while the association between admissions and PM2.5 was negative and statistically significant (R = -0.168; p-value = 0.003). The R 2 of the final model (Hospitalizations = 2.19*Humidity - 1.60*PM2.5 - 0.23*Precipitation) explained 84% of hospitalizations due to respiratory disease in children living in Manaus, considering the independent variables statistically significant (humidity, PM2.5, and precipitation). CONCLUSIONS: Hospital admissions for respiratory diseases in children in Manaus, were more related to weather conditions and in particular relative humidity, than to exposure to aerosols emitted by biomass burning in the Amazonian region.
Authors: Damien Dietrich; Ralitza Dekova; Stephan Davy; Guillaume Fahrni; Antoine Geissbühler Journal: J Med Internet Res Date: 2018-06-27 Impact factor: 5.428