在研究中使用威尔士多重贫困指数:估计排除域在例行健康数据研究中的影响
Shamsudeen Mohammed1, Grace A Bailey1, Ian W Farr1
1SAIL Databank, Population Data Science, Swansea University Medical School, Swansea University, Swansea, Wales.
BMC public health
|March 29, 2025
概括
从威尔士多重贫困指数 (WIMD) 中删除健康领域,改变了17.28%的LSOA的区域排名. 仅使用收入领域改变了超过50%的LSOA的排名,影响了贫困研究.
科学领域:
- 健康的社会经济决定因素
- 地理空间分析的研究.
- 公共卫生研究方法论研究方法论
背景情况:
- 威尔士多重贫困指数 (WIMD) 是威尔士使用的基于面积的贫困指标.
- WIMD包括一个健康领域,在健康结果研究中存在内源性偏差的风险.
- 评估了替代WIMD构造以减轻潜在的偏差.
研究的目的:
- 评估从WIMD中删除健康领域对区域贫困排名的影响.
- 评估仅使用WIMD的收入领域作为剥夺措施的影响.
- 使用替代WIMD测量方法量化贫困和糖尿病患病率之间的关联变化.
主要方法:
- 在SAIL数据库中将WIMD 2019分数链接到2,760,731个人.
- 创建了两个替代WIMD措施:一个排除健康领域,另一个仅使用收入领域.
- 使用斯皮尔曼相关性和科恩卡帕评估排名协议;分析了糖尿病患病率与二进制逻辑回归的关联.
主要成果:
- 除了健康领域外,LSOA的十位数排名转移了17.28%,五位数排名转移了9.00%.
- 仅使用收入领域,LSOA的十位数排名转移了50.49%,五位数排名转移了29.65%.
- 所有WIMD测量都显示出与糖尿病患病率有显著关联,但置信区间显示方法之间的结果不同.
结论:
- 研究人员应仔细考虑与研究结果相关的WIMD领域,以避免偏见的估计.
- 修改WIMD结构,特别是通过删除健康领域或仅使用收入来修改WIMD结构,可以显著改变贫困排名.
- 为研究人员提供了一种方法来量化他们自己的研究中的潜在偏差,使用WIMD.
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