TENDÊNCIA TEMPORAL DE INTERNAÇÕES POR DIABETES MELLITUS NO BRASIL DURANTE O PERÍODO DE 2013 A 2022

DOI: 10.53524/lit.edt.978-65-84528-51-2/02

PALAVRAS-CHAVE: Diabetes Mellitus. Epidemiologia. Hospitalização.

KEYWORDS: Diabetes Mellitus, Epidemiology, Hospitalization.

ABSTRACT: OBJECTIVE: To analyze the temporal trend of hospitalizations for Diabetes Mellitus in Brazil from 2013 to 2022. METHODS: A quantitative cross-sectional study with time series analysis. The temporal trend analysis of hospitalization cases used Prais-Winsten linear regression, a technique that analyzes serial autocorrelation, that is, the relationship between a series of values of a measure over previous times. The Prais-Winsten method for generalized linear regression is considered more efficient than simple linear regression since it is a regression analysis procedure specifically designed for data that may be influenced by serial autocorrelation, which is quite common in population data measures. Initially, the data was organized using Excel 2016 (Microsoft Corp., USA), and statistical analyses were performed using Stata version 18 (Stata Corp LP, College Station, USA). RESULTS: Between 2013 and 2022, there were 1,338,961 hospitalizations with a primary diagnosis of DM, representing 1.143% of hospitalizations, number 117,170,629 occurring in the SUS. The study reveals a complex and diverse scenario of DM trends in Brazil. Despite the overall stability of hospitalizations, there is a concerning increase among Black, mixed-race, indigenous men, and youth, which requires specific measures. The difference between women and older men may be linked to better health and education conditions. CONCLUSION: DM represents a significant public health challenge in Brazil. Understanding the temporal trends and disparities of the disease is essential for directing effective actions and public policies for its prevention and control.

Autor

  • Adriny Silva Rodrigues

  • Francisco Lucas de Lima Fontes

  • Gizelia Araújo Cunha Porto

  • Kaio Silva Bispo

  • Mayara Macêdo Melo

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Desenvolvido por Alexsander Arcelino