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巴西帕拉纳州缺血性心脏病住院和死亡的空间风险的贝叶斯建模与估计。

Bayesian Modeling and Estimation of Spatial Risk for Hospitalization and Mortality from Ischemic Heart Disease in Paraná, Brazil.

机构信息

Post-Graduation Program in Health Sciences, State University of Maringa, Parana, Brazil.

Department of Emergency Medicine, Duke University School of Medicine, Durham, North Carolina, United States of America.

出版信息

Glob Heart. 2024 Aug 5;19(1):63. doi: 10.5334/gh.1347. eCollection 2024.

DOI:10.5334/gh.1347
PMID:39132013
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11312845/
Abstract

OBJECTIVE

Despite significant advancements in understanding risk factors and treatment strategies, ischemic heart disease (IHD) remains the leading cause of mortality worldwide, particularly within specific regions in Brazil, where the disease is a burden. Therefore, the aim of this study was to estimate the risk of hospitalization and mortality from IHD in the state of Paraná (Brazil), using spatial analysis to identify areas with higher risk based on socioeconomic, demographic and health variables.

METHODS

This is an ecological study based on secondary and retrospective IHD hospitalization and mortality data obtained from the Brazilian Hospitalization and Mortality Information Systems during the 2010-2021 period. Data were analyzed for 399 municipalities and 22 health regions in the state of Paraná. To assess the spatial patterns of the disease and identify relative risk (RR) areas, we constructed a risk model by Bayesian inference using the R-INLA and SpatialEpi packages in R software.

RESULTS

A total of 333,229 hospitalizations and 73,221 deaths occurred in the analyzed period, and elevated RR of hospitalization (RR = 27.412, CI 21.801; 34.466) and mortality (RR = 15.673, CI 2.148; 114.319) from IHD occurred in small-sized municipalities. In addition, medium-sized municipalities also presented elevated RR of hospitalization (RR = 6.533, CI 1.748; 2.006) and mortality (RR = 6.092, CI 1.451; 2.163) from IHD. Hospitalization and mortality rates were higher in white men aged 40-59 years. A negative association was found between Municipal Performance Index (IPDM) and IHD hospitalization and mortality.

CONCLUSION

Areas with increased risk of hospitalization and mortality from IHD were found in small and medium-sized municipalities in the state of Paraná, Brazil. These results suggest a deficit in health care attention for IHD cases in these areas, potentially due to a low distribution of health care resources.

摘要

目的

尽管在了解风险因素和治疗策略方面取得了重大进展，但缺血性心脏病（IHD）仍然是全球范围内导致死亡的主要原因，特别是在巴西的特定地区，该疾病负担沉重。因此，本研究旨在使用空间分析来确定基于社会经济、人口和健康变量的高风险区域，以估计巴西巴拉那州（巴西）IHD 住院和死亡的风险。

方法

这是一项基于二级和回顾性 IHD 住院和死亡率数据的生态研究，这些数据来自巴西住院和死亡率信息系统在 2010-2021 年期间的数据。对巴拉那州的 399 个市和 22 个卫生区进行了数据分析。为了评估疾病的空间模式并确定相对风险（RR）区域，我们使用 R 软件中的 R-INLA 和 SpatialEpi 包通过贝叶斯推断构建了风险模型。

结果

在所分析的期间内，共发生了 333229 例住院和 73221 例死亡，IHD 住院（RR = 27.412，CI 21.801；34.466）和死亡率（RR = 15.673，CI 2.148；114.319）的 RR 升高，发生在小市。此外，中型市的 IHD 住院（RR = 6.533，CI 1.748；2.006）和死亡率（RR = 6.092，CI 1.451；2.163）的 RR 也升高。40-59 岁的白人男性住院和死亡率较高。市政绩效指数（IPDM）与 IHD 住院和死亡率呈负相关。

结论

在巴西巴拉那州的小市和中型市中发现了 IHD 住院和死亡率增加的风险区域。这些结果表明，这些地区对 IHD 病例的医疗保健关注不足，可能是由于医疗保健资源分布不均所致。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/6ad15e1ca6a1/gh-19-1-1347-g6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/b1d37ac33d52/gh-19-1-1347-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/5433b2f7cab1/gh-19-1-1347-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/013f65b4dd46/gh-19-1-1347-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/2f74e61ce763/gh-19-1-1347-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/e974350aa5e6/gh-19-1-1347-g5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/6ad15e1ca6a1/gh-19-1-1347-g6.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/b1d37ac33d52/gh-19-1-1347-g1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/5433b2f7cab1/gh-19-1-1347-g2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/013f65b4dd46/gh-19-1-1347-g3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/2f74e61ce763/gh-19-1-1347-g4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/e974350aa5e6/gh-19-1-1347-g5.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd19/11312845/6ad15e1ca6a1/gh-19-1-1347-g6.jpg

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