Profile and Trends in Hospitalizations for Respiratory Diseases in Ananindeua-PA: Epidemiological Analysis (2013-2022)

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Aims: This study aimed to analyze the epidemiological profile of hospital admissions for respiratory system diseases in the municipality of Ananindeua-PA, between 2013 and 2022, highlighting morbidity, mortality patterns, and associated factors. Study Design: The research was descriptive, retrospective, and quantitative, based on the analysis of secondary data. Place and Duration of Study: The study was conducted in Ananindeua, Pará, Brazil, covering the period from January 2013 to December 2022. Methodology: Data were collected from the Hospital Information System (SIH/SUS) using the TabNet/DATASUS platform. Variables analyzed included year of care, sex, age group, color/race, nature of admission (urgent or elective), and number of deaths. Descriptive statistical analysis was performed using Microsoft Excel-2019, with results presented in tables and graphs. Results: Between 2013 and 2022, Ananindeua recorded 35,281 hospital admissions for respiratory diseases, with pneumonia being the leading cause (22,804 cases). Most hospitalizations were urgent (99%). Women accounted for 53% of admissions, while men had the highest death rates (55.12%). The most affected age group was 1 to 4 years (17.46%), followed by young adults aged 20 to 39. Regarding color/race, 70.41% of the records lacked this information, but among the reported cases, brown individuals were the most prevalent (27.81%). The total number of deaths during the period was 1,290, with the highest occurrence among those aged 80 and over (26.74%). Conclusion: The study revealed that respiratory diseases remain a significant public health challenge in Ananindeua, primarily affecting young children, young adults, and the elderly. Urgent hospitalizations were predominant, and higher mortality rates were observed among men and older populations. Strengthening Primary Health Care (PHC) is crucial to prevent avoidable hospitalizations, and further research is needed to explore racial and social disparities observed in the data.

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