Efeito da sazonalidade climática na ocorrência de sistomas respiratórios em indivíduos de uma cidade de clima tropical

• Autor(a) principal: SILVA JÚNIOR, José Laerte Rodrigues da
• Data de Publicação: 2011
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• dARK ID: ark:/38995/00130000061rk
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tde/1812
• topic: Clima; Sinais e Sintomas Respiratórios; Centros de Saúde; Doenç resp-clim tropical; Sinais e sint resp; Centros de Saúd; Climate; Signs and Symptoms; Respiratory; Ambulatory Care Facilities; CNPQ::CIENCIAS DA SAUDE::MEDICINA

Objectives: To evaluate the effect of the climate seasonality on the occurrence of respiratory symptoms in patients attending a primary health unit in a tropical city. Methods: We conducted a cross-sectional study on subjects attending an out-patient primary health unit in relation with meteorological data collected daily. During one year, forty-four cross-sectional observations categorized by season were made. The observations were chosen randomly, in twelve-hour intervals (7am to 7pm). Analysis of variance was used to compare means across seasons. Pairwise correlation was conducted to verify the association between the number of patients and each meteorological variable. A model of autoregressive moving average with exogenous variables was conducted to evaluate the ability of the meteorological variables to predict the proportions of subjects with respiratory symptoms on each season. Results: Among the 3,354 subjects enrolled, 14.6% had respiratory symptoms. The temperature variation was not enough to change the number of individuals with respiratory symptoms, however there was an increase of subjects with respiratory symptoms coinciding with low levels of humidity during winter, with a statistically significant difference between seasons (p=0,01). Correlation showed that the mean of previous three days minimum air humidity correlates negatively with the number of respiratory subjects (p < 0.04). An ARMAX model that included the same variable showed a statistically significant coefficient (p < 0.0001). Conclusion: In a Brazilian city with tropical weather, the number of subjects with respiratory symptoms attending a primary health unit is increased with the reduction of air humidity and it is possible that this increase could be predicted by meteorological data.