背景:不同等级的社会内部和社会之间存在健康不平等。尽管欧盟国家的健康状况总体上有所改善,社会之间的差距仍然存在,经济上,和社会上处于不利地位的个人。这项研究旨在建立一个健康决定因素的整体模型,研究健康不平等的各种决定因素及其与健康状况的关联之间的复杂关系。
方法:在捷克共和国的地方行政单位(LAU1)的领土一级评估了健康不平等和状况。创建了57个指标的数据集,分为七个健康决定因素和一个健康状况类别。必要的数据从公开可用的数据库获得。2001-2003年和2016-2019年进行了比较。采用了各种方法,包括复合指标创建,相关分析,Wilcoxon试验,总指数计算,聚类分析,和使用LISA方法的数据可视化。
结果:相关矩阵揭示了两个时期健康不平等类别之间的强关系。在第一阶段,经济地位与社会保护和教育之间存在最重要的联系。然而,依赖性在后期减弱,接近大约0.50的值。Wilcoxon检验证实了行列式值随时间的变化,除了三个特定的决定因素。数据可视化确定了特定LAU1中持续不利或恶化的健康不平等,侧重于经济地位和社会保护等类别,教育,人口统计情况,环境状况,个人生活状况,道路安全和犯罪。健康状况指数显示随着时间的推移没有显著变化,而健康不平等的综合指数随着差异的扩大而有所改善。
结论:捷克共和国的健康空间不平等仍然存在,受经济影响,社会,人口统计学,和环境因素,以及当地医疗保健的可及性。内外周边都表现出不良的健康结果,挑战城市地区票价更好的假设。贫困和脆弱性的结合加剧了这些不平等。尽管社会排斥和贫困率很低,区域卫生不平等现象长期存在。有效解决健康不平等需要跨学科合作和循证政策干预。努力应侧重于创造有利的社会和物质环境,加强医疗系统,促进与非医学学科的合作。
Health inequities exist within and between societies at different hierarchical levels. Despite overall improvements in health status in European Union countries, disparities persist among socially, economically, and societally disadvantaged individuals. This study aims to develop a holistic model of health determinants, examining the complex relationship between various determinants of health inequalities and their association with health condition.
Health inequalities and conditions were assessed at the territorial level of Local Administrative Units (LAU1) in the Czech Republic. A dataset of 57 indicators was created, categorized into seven determinants of health and one health condition category. The necessary data were obtained from publicly available databases. Comparisons were made between 2001-2003 and 2016-2019. Various methods were employed, including composite indicator creation, correlation analysis, the Wilcoxon test, aggregate index calculation, cluster analysis, and data visualization using the LISA method.
The correlation matrix revealed strong relationships between health inequality categories in both periods. The most significant associations were observed between Economic status and social protection and Education in the first period. However, dependencies weakened in the later period, approaching values of approximately 0.50. The Wilcoxon test confirmed variations in determinant values over time, except for three specific determinants. Data visualization identified persistently adverse or worsening health inequalities in specific LAU1, focusing on categories such as Economic status and social protection, Education, Demographic situation, Environmental status, Individual living status, and Road safety and crime. The health condition indices showed no significant change over time, while the aggregate index of health inequalities improved with widened differences.
Spatial inequalities in health persist in the Czech Republic, influenced by economic, social, demographic, and environmental factors, as well as local healthcare accessibility. Both inner and outer peripheries exhibit poor health outcomes, challenging the assumption that urban areas fare better. The combination of poverty and vulnerabilities exacerbates these inequalities. Despite the low rates of social exclusion and poverty, regional health inequalities persist in the long term. Effectively addressing health inequalities requires interdisciplinary collaboration and evidence-based policy interventions. Efforts should focus on creating supportive social and physical environments, strengthening the healthcare system, and fostering cooperation with non-medical disciplines.