Abstract
The present study evaluated, through generalized linear models, the relationship between the number of hospital admissions for respiratory diseases and meteorological elements, in order to verify the regression model that best fits the data, as well as to predict the number of hospitalizations due to respiratory diseases. This is an ecological, descriptive study using secondary data, obtained from a public database. Data on respiratory diseases considered in the present study were obtained from the DATASUS website in the period from January 1998 to December 2014. The climate variables employed as explanatory variables for modeling the data were obtained from the INMET website, more specifically the Meteorological Database for Teaching and Research. From the realized evaluation, it was possible to conclude that the negative binomial regression model showed superiority in relation to the Poisson regression model, with the last regression model being the log linear negative binomial regression model. The results show a positive relationship between the variables considered in the municipality. There is an expected relative increase in the number of hospitalizations for respiratory diseases if average wind speed, total sunshine, relative humidity and season are observed.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
