应用高维性倾向得分方法在国家健康和衰老趋势研究中的应用
Ali G Hamedani1,2, Thanh Phuong Pham Nguyen1,2, Allison W Willis1,2
1Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
概括
高维性倾向评分 (HDPS) 在国家健康调查中成功发现了更少的混因素. 将HDPS应用于国家健康和衰老趋势研究 (NHATS) 显示,视力困难在调整后与痴呆症无关.
科学领域:
- 老年学是一门学科.
- 流行病学 流行病学
- 生物统计学 生物统计学
背景情况:
- 高维倾向评分 (HDPS) 是一种统计方法,用于识别大型医疗数据库中的潜在混因素.
- HDPS以前没有被应用于国家健康调查,如国家健康和衰老趋势研究 (NHATS).
- NHATS是老年学研究的重要资源,调查了美国的老年人.
研究的目的:
- 介绍HDPS的概述及其在国家健康调查中的应用.
- 描述在调查中使用HDPS的数据转换和分析考虑.
- 在NHATS中使用HDPS调查视觉困难和发病性痴呆症之间的关联.
主要方法:
- 将HDPS应用于NHATS数据,这是对老年人的全国代表性调查.
- 将HDPS混器选择与传统方法进行比较.
- 调查了自我报告的视觉困难和事件痴呆症之间的关联.
主要成果:
- 在未调整的模型中,视力困难与痴呆症有很强的关联 (OR 2.34).
- 在对标准共变量进行调整后,相关性减弱了 (OR 1.44).
- 添加75个HDPS优先级变量进一步减弱了相关性,使其变得无意义 (OR 0.94).
结论:
- HDPS可以有效地应用于像NHATS这样的国家卫生调查.
- 在老年学和流行病学研究中,HDPS可能会增强混调整.
- 该框架鼓励在类似的研究环境中使用HDPS.
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