美国慢性病负担的空间和时间模式,2018-2021年
Jocelyn V Hunyadi1, Kehe Zhang1, Qian Xiao2
1Department of Biostatistics and Data Science, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas; Center for Spatial-Temporal Modeling for Applications in Population Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, Texas.
American journal of preventive medicine
|September 5, 2024
概括
一项新的慢性疾病负担指数 (CDBI) 显示,美国南部县的疾病负担很高,特别是在农村地区. 该指数有助于识别针对性公共卫生干预和公平获得医疗保健的弱势群体.
科学领域:
- 公共卫生 公共卫生
- 流行病学 流行病学
- 地理信息系统 (GIS) 是指地理信息系统.
背景情况:
- 慢性疾病是美国死亡和残疾的主要原因.
- 现有的个人级别指数无法捕捉人口级别的慢性疾病负担.
- 需要一种定量工具来理解慢性疾病对公共卫生战略的地理模式和影响.
研究的目的:
- 建立一个县级的慢性疾病负担指数 (CDBI).
- 确定慢性疾病负担的地理和时间模式.
- 调查CDBI与社会脆弱性之间的联系.
主要方法:
- 从CDC的PLACES数据库 (2018-2021) 中利用了20个健康指标.
- 使用主要组件分析构建年度县级CDBI.
- 用Getis-Ord Gi*确定了地理热点,并使用后勤回归评估了与社会脆弱性的关联.
主要成果:
- 美国南部的高慢性病负担集群,在KY和WV持续负担.
- 在OH和TX.观察到增加的负担.
- CDBI与社会脆弱性指数 (OR=7.6) 之间存在显著的关联;非大都会城市县显示CDBI升高 (OR=14.6).
结论:
- 慢性疾病负担评估 (CDBI) 是评估慢性疾病负担的有效人口水平工具.
- 识别高负担,脆弱的社区对于资源分配至关重要.
- 这种方法有助于提高公平获得医疗保健的机会,并了解健康差异.
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