Distribuição espaço-temporal da produção ambulatorial para  incontinência urinária em homens, Brasil, 2010-201

Fernanda Vieira Nicolato; Alfredo  Chaoubah; Maria do Socorro Lina van Keulen; Marcio Fernandes dos Reis; Graziela Liebel

doi:10.1590/s1679-49742022000200025

##article.authors##

Fernanda Vieira Nicolato Universidade Federal de Juiz de Fora https://orcid.org/0000-0002-3828-2918
Alfredo Chaoubah Universidade Federal de Juiz de Fora https://orcid.org/0000-0002-2459-9164
Maria do Socorro Lina van Keulen Universidade Federal de Juiz de Fora https://orcid.org/0000-0002-9286-7175
Marcio Fernandes dos Reis Universidade Federal de Juiz de Fora https://orcid.org/0000-0002-7945-750X
Graziela Liebel Universidade do Vale do Itajaí https://orcid.org/0000-0002-1994-7785

DOI:

https://doi.org/10.1590/s1679-49742022000200025

Keywords:

Urinary Incontinence, Men's Health, Time Series Studies, Geographic Mapping

Abstract

Objective: To estimate the temporal trend and spatial distribution of outpatient production for urinary incontinence in men in Brazil. Methods: Time-series ecological study for Brazil and regions, from 2010-2019. These data were obtained in the Unified
Health System Outpatient Information System. Prais-Winsten regression was used to analyze the temporal trend in the country and by region. To forecast the trend until 2024 the integrated autoregressive model of moving averages was used. Results: There were 3,457 outpatient care for urinary incontinence in men registered in 2010 to 16,765 in 2019, an increasing temporal trend was observed in Brazil, with an annual percent change of 50.37% and a confidence interval of 95% (37.54%;63.62%); and a growth forecast between the years 2020-2024, by the final model ARIMA (1, 1, 0). The spatial distribution of urinary incontinence presented variation in rates for the geographic regions of Brazil. Conclusion: There was an increasing temporal trend in outpatient production for urinary incontinence in men in Brazil between 2010-2019 and a growth forecast until 2024. The highest rates occurred in the Southeast region and the highest increase in the South region.