Variação temporal e espacial da pneumonia em Fortaleza: relação com o clima e variáveis socioeconômicas

Abstract

The present study addresses the climate links with the proliferation of respiratory diseases in the urban environment of Fortaleza-CE. Therefore, it aims to analyze the correlations between the climatic conditions of Fortaleza-CE and the hospitalizations of children due to pneumonia, as well as to relate the diseases to the socioeconomic conditions of the capital of Ceará. This is because the proposal of correlation between these elements, from a geographical perspective, is still incipient in the city of Fortaleza. It uses data from the Pici (UFC) meteorological station, from average temperature, average maximum temperatures, average minimum temperatures, relative humidity and thermal amplitude in the period 1998-2016. On the other hand, data from hospitalizations for Pneumonia were collected through the Hospital Information System (SIH) of the online platform (DATASUS) and the health secretariats of the State of Ceará (SESA). The data acquired in the SESA, for each neighborhood with the data of HDI and population density of Fortaleza, spatializing them in maps of the city, through a Choropleth map and the models of interpolation IDW and Krigagem. In the three specialized models, it was observed that the highest cases of pneumonia in children aged 1 to 4 years occurred in those neighborhoods with the worst HDI's and highest demographic densities. The meteorological data were also correlated with those of hospitalizations for pneumonia of children aged 1 to 4 years, using Pearson (R) correlation coefficients and determination (R²). It should be noted that some of the results indicated strong correlation degrees, with a highlight for the average minimum temperatures, especially in the second half of the year, as in 2005, with R = -0,95 and 91% of their determination on hospitalizations. The greatest correlation of the time series occurred with the thermal amplitude, with R = 0.99 and 98% of significance on hospitalizations. With the average temperature and the relative air humidity, the correlations were less frequent, but were evidenced, respectively, with R = - 0,92 (85%) and R = 0,93 in the years of 2005 and 2006. It was evidenced that correlations of hospitalizations with mean maximum temperatures were not as significant in the historical series, except in the second half of 2005, with R = -0,8 and R² = 66%. Finally, the correlations were higher when done per semester, not per year. It is concluded that more studies should be done in this bias, because besides the climate, other factors are fundamental in the development of the disease.