健康衰老的社会决定因素:使用"我们所有人"队列的调查
Wei-Han Chen1, Yao-An Lee2, Huilin Tang1
1Department of Pharmaceutical Outcomes and Policy, University of Florida, Gainesville, Florida, United States of America.
PloS one
|March 6, 2026
概括
医疗保险类型是健康衰老的关键预测因素. 一个XGBoost模型准确地识别了实现健康衰老的个体,突出了老年人保险的重要性.
科学领域:
- 老年学与公共卫生
- 计算生物学和生物信息学
- 医疗保健服务研究 医疗服务研究
背景情况:
- 人口老龄化给维持健康和功能带来了挑战.
- 了解健康的社会决定因素 (SDOH) 对于促进健康的衰老至关重要.
- 连接SDOH与健康衰老结果的途径需要进一步调查.
研究的目的:
- 使用SDOH数据开发和评估健康衰老的预测模型.
- 确定与健康衰老相关的关键SDOH因素.
- 评估跨人口群体的模式公平性.
主要方法:
- 使用我们所有人研究计划 (AoURP) 数据集的回顾性队列研究.
- 训练后勤回归 (LR),多层感知子 (MLP) 和极端梯度增强 (XGBoost) 模型.
- 通过并发症,认知功能和移动性来定义健康的衰老;使用AUROC和预测平价来评估模型;用SHAP值分析特征重要性.
主要成果:
- 包括99935名参与者 (平均年龄74岁);44.1%被归类为健康老龄化.
- XGBoost模型表现出强大的预测性能 (AUROC:0.793).
- 医疗保险类型,就业状况和物质使用是重要的预测因素;模型实现了跨种族和性别的预测均等.
结论:
- XGBoost模型准确地预测了健康的衰老.
- 医疗保险状态是影响健康衰老的关键因素.
- 调查结果强调需要解决SDOH,特别是医疗保险,以支持健康老龄化倡议.
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