Influência das variáveis meteorológicas nas morbidades respiratórias prevalentes em crianças hospitalizadas no município de Campina Grande-PB.

Abstract

The changes in the meteorological variables compete effectively for the occurrence of respiratory diseases in humans. There is a prevalence in hospital records of respiratory diseases, especially in children. The objective of this research was to analyze the influence of meteorological variables on respiratory morbidities prevalent in hospitalized children in Campina Grande-PB. The current research is an epidemiological, cross-sectional descriptive study with quantitative and descriptive approach, meteorological data were obtained from the National Institute of Meteorology (INMET) and epidemiological data in the Hospital Information System of SUS (SIH / SUS) , made available by the Statistics Department of SUS (Datasus). For the statistical analysis of the data the negative binomial model belonging to the class of the generalized linear models was adjusted, adopting a level of significance of 5%, based on the statistical platform R. It has been estimated that the average number of cases of pneumonia increases by approximately 48% at each degree centigrade increase in mean air temperature and decreases by approximately 32% at each degree centigrade of maximum air temperature increase, also decreasing by about 3% at every 1% increase above the mean of the relative humidity, in relation to the wind variable, the number of cases of pneumonia is expected to increase by around 36% with the increase in wind speed. For bronchitis / bronchiolitis it is expected that there will be an increase of approximately 11% at each degree centigrade increase in mean air temperature, also increasing approximately 21% at each degree centigrade decrease in maximum air temperature and decreasing by about 32 % at each degree centigrade of maximum air temperature increase. It has been estimated that the average number of cases of pneumonia increases by approximately 48% at each degree centigrade increase in mean air temperature and decreases by approximately 32% at each degree centigrade of maximum air temperature increase, also decreasing by about 3% at every 1% increase above the mean of the relative humidity. Assessing the health risk of the population due to climate data is an important step in planning and implementing actions. Public health managers can use the predictive model to prepare health services to receive children in periods when larger case records occur.