Daniel Hideki Bando, Francisco Chiaravalloti Neto, Alfredo Pereira de Queiroz
{"title":"Stroke mortality negatively associated with health, education, and safety: an ecological study, Minas Gerais, 2014-2022.","authors":"Daniel Hideki Bando, Francisco Chiaravalloti Neto, Alfredo Pereira de Queiroz","doi":"10.1590/S2237-96222025v34e20240820.en","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>To analyze the spatial-temporal pattern of stroke mortality in the Brazilian state of Minas Gerais between 2014 and 2022 and to identify its association with socioeconomic indicators. The identification of clusters of high and low mortality rates, along with their associated indicators, may assist public managers in formulating intersectoral public policies aimed at reducing social inequalities.</p><p><strong>Methods: </strong>: This study employed an ecological approach using municipal-level data. Mortality data were obtained from the Department of Information Technology of the Brazilian National Health System. The covariates were the five dimensions that compose the Minas Gerais Social Responsibility Index developed by the João Pinheiro Foundation. Scan statistics were used to detect spatial and spatio-temporal clusters of high and low stroke mortality rates. The association between stroke mortality and the indicators was estimated using a spatial autoregressive model.</p><p><strong>Results: </strong>A total of 88,429 deaths due to stroke occurred during the study period, corresponding to a rate of 47.0 per 100,000 inhabitants per year. Purely spatial analysis identified 13 dispersed clusters: eight with high mortality rates (relative risk [RR] 1.08 to 1.31) and five with low rates (RR 0.80 to 0.89). Spatial-temporal analysis identified four high-rate clusters (2014-2017; RR 1.18 to 1.48) and three low-rate clusters (2018-2022; RR 0.66 to 0.87) distributed across the state. A negative association was found between stroke mortality and the indicators for health (β = -7.64), education (β = -7.21), and safety (β = -3.43), with R² = 0.41.</p><p><strong>Conclusion: </strong>This study can support public managers in monitoring, evaluating, and formulating public health policies by promoting articulation between health and other sectors, aiming to improve the population's social well-being.</p>","PeriodicalId":520611,"journal":{"name":"Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil","volume":"34 ","pages":"e20240820"},"PeriodicalIF":2.0000,"publicationDate":"2025-09-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12479032/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1590/S2237-96222025v34e20240820.en","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives: To analyze the spatial-temporal pattern of stroke mortality in the Brazilian state of Minas Gerais between 2014 and 2022 and to identify its association with socioeconomic indicators. The identification of clusters of high and low mortality rates, along with their associated indicators, may assist public managers in formulating intersectoral public policies aimed at reducing social inequalities.
Methods: : This study employed an ecological approach using municipal-level data. Mortality data were obtained from the Department of Information Technology of the Brazilian National Health System. The covariates were the five dimensions that compose the Minas Gerais Social Responsibility Index developed by the João Pinheiro Foundation. Scan statistics were used to detect spatial and spatio-temporal clusters of high and low stroke mortality rates. The association between stroke mortality and the indicators was estimated using a spatial autoregressive model.
Results: A total of 88,429 deaths due to stroke occurred during the study period, corresponding to a rate of 47.0 per 100,000 inhabitants per year. Purely spatial analysis identified 13 dispersed clusters: eight with high mortality rates (relative risk [RR] 1.08 to 1.31) and five with low rates (RR 0.80 to 0.89). Spatial-temporal analysis identified four high-rate clusters (2014-2017; RR 1.18 to 1.48) and three low-rate clusters (2018-2022; RR 0.66 to 0.87) distributed across the state. A negative association was found between stroke mortality and the indicators for health (β = -7.64), education (β = -7.21), and safety (β = -3.43), with R² = 0.41.
Conclusion: This study can support public managers in monitoring, evaluating, and formulating public health policies by promoting articulation between health and other sectors, aiming to improve the population's social well-being.