OBJECTIVE: To determine whether climate variability influences the number of hospitalizations for respiratory diseases in infants, children, and adults in the city of Campo Grande, Brazil. METHODS: We used daily data on admissions for respiratory diseases, precipitation, air temperature, humidity, and wind speed for the 2004-2008 period. We calculated the thermal comfort index, effective temperature, and effective temperature with wind speed (wind-chill or heat index) using the meteorological data obtained. Generalized linear models, with Poisson multiple regression, were used in order to predict hospitalizations for respiratory disease. RESULTS: The variables studied were (collectively) found to show relatively high correlation coefficients in relation to hospital admission for pneumonia in children (R² = 68.4%), infants (R² = 71.8%), and adults (R² = 81.8%). CONCLUSIONS: Our results indicate a quantitative risk for an increase in the number of hospitalizations of children, infants, and adults, according to the increase or decrease in temperature, humidity, precipitation, wind speed, and thermal comfort index in the city under study.
OBJECTIVE: To determine whether climate variability influences the number of hospitalizations for respiratory diseases in infants, children, and adults in the city of Campo Grande, Brazil. METHODS: We used daily data on admissions for respiratory diseases, precipitation, air temperature, humidity, and wind speed for the 2004-2008 period. We calculated the thermal comfort index, effective temperature, and effective temperature with wind speed (wind-chill or heat index) using the meteorological data obtained. Generalized linear models, with Poisson multiple regression, were used in order to predict hospitalizations for respiratory disease. RESULTS: The variables studied were (collectively) found to show relatively high correlation coefficients in relation to hospital admission for pneumonia in children (R² = 68.4%), infants (R² = 71.8%), and adults (R² = 81.8%). CONCLUSIONS: Our results indicate a quantitative risk for an increase in the number of hospitalizations of children, infants, and adults, according to the increase or decrease in temperature, humidity, precipitation, wind speed, and thermal comfort index in the city under study.
Authors: Maria Elisa Di Cicco; Giuliana Ferrante; Doriana Amato; Antonino Capizzi; Carlo De Pieri; Valentina Agnese Ferraro; Maria Furno; Valentina Tranchino; Stefania La Grutta Journal: Int J Environ Res Public Health Date: 2020-07-24 Impact factor: 3.390