用社会决定因素预测患病前低认知能力:一种机器学习方法
Lubnaa Badriyyah Abdullah1, Ibshar Khandakar2, Ashley Douglas3
1UNT Health Fort Worth, Department of Family Medicine, Institute of Translational Research, Fort Worth, TX 76107, United States.
JAR life
|February 18, 2026
概括
患病前智商 (pIQ) 低的人更容易受到健康的社会决定因素的影响. 这种与邻居剥夺和减少支持相关的脆弱性,可能会加速认知衰退路径.
科学领域:
- 暴露性研究是暴露性的研究.
- 神经科学是一个神经科学.
- 公共卫生 公共卫生
背景情况:
- 健康的社会决定因素 (SDoH) 和暴露组影响生物过程和阿尔茨海默病 (AD) 风险.
- 患病前智力能力较低的个人 (pIQ ≤70) 可能由于认知储备减少而对SDoH具有更高的脆弱性.
- 在AD风险中低pIQ和SDoH之间的相互作用仍未得到充分研究.
研究的目的:
- 调查SDoH和低PIQ之间的关联.
- 确定预测低pIQ的关键SDoH因素.
- 了解与低pIQ和SDoH相关的心理社会认知表型.
主要方法:
- 从健康和衰老大脑研究-健康差异 (n=2691) 的数据分析.
- 使用文字阅读分数将参与者分为低pIQ (≤70) 或平均pIQ (90-100) 组.
- 应用XGBoost机器学习模型来预测基于教育,收入,区域贫困指数 (ADI),社会支持,压力,健康状况和担忧的pIQ分组.
主要成果:
- 在XGBoost模型中,曲线下的面积 (AUC) 为0.72 [0.64,0.81].
- 低pIQ的关键预测因素包括担忧,ADI,收入,高中毕业和有形支持.
- 低的pIQ与更大的社区贫困,更低的收入和更少的支持资源显著相关.
结论:
- 低的pIQ与SDoH因素相结合,可以确定一个脆弱的心理社会认知表型.
- 这种表型可能会加速认知衰退,可能是通过炎症机制.
- 了解这些途径对于开发针对风险人群的有针对性的干预措施至关重要.
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