基于巴西数据构建中老年人痴呆预测模型，助力早期干预
Construction of a classification model for dementia among Brazilian adults aged 50 and over
- 结合随机森林与逻辑回归，筛选低门槛可干预风险因素
- 模型准确率达70.3%，对高龄、文盲等人群预测效果显著
- 适合基层医疗筛查，为公共卫生政策提供数据支持
为构建适用于50岁以上巴西中老年人的痴呆分类模型，采用Python实现，结合变量选择与多变量分析，使用低成本且可改变的风险因素。研究基于横断面设计的观察性队列，利用巴西老龄化纵向研究（ELSI-Brazil）数据，涵盖9,412名参与者。痴呆诊断依据神经心理评估及知情者报告的认知功能。采用随机森林（RF）和多变量逻辑回归分析，评估痴呆风险。总体患病率为9.6%。最显著风险包括文盲（OR=7.42）、90岁及以上（OR=11.00）、体重过低（OR=2.11）、手握力弱（OR=2.50）、自报黑皮肤（OR=1.47）、缺乏运动（OR=1.61）、听力障碍（OR=1.65）及抑郁症状（OR=1.72）。更高教育水平（OR=0.44）、生活满意度高（OR=0.72）和在职状态（OR=0.78）为保护因素。RF模型优于逻辑回归，其受试者工作特征曲线下面积（AUC）达0.776，敏感度0.708，特异度0.702，F1分数0.311，几何均数0.705，准确率0.703。结论表明，痴呆具有多维度特征，识别易获取风险因素有助于精准筛查。加强脑健康促进政策，可提升初级保健资源分配效率与痴呆预防成效。
原文摘要 · Abstract (English)
To build a dementia classification model for middle-aged and elderly Brazilians, implemented in Python, combining variable selection and multivariable analysis, using low-cost variables with modification potential. Observational study with a predictive modeling approach using a cross-sectional design, aimed at estimating the chances of developing dementia, using data from the Brazilian Longitudinal Study of Aging (ELSI-Brazil), involving 9,412 participants. Dementia was determined based on neuropsychological assessment and informant-based cognitive function. Analyses were performed using Random Forest (RF) and multivariable logistic regression to estimate the risk of dementia in the middle-aged and elderly populations of Brazil. The prevalence of dementia was 9.6%. The highest odds of dementia were observed in illiterate individuals (Odds Ratio (OR) = 7.42), individuals aged 90 years or older (OR = 11.00), low weight (OR = 2.11), low handgrip strength (OR = 2.50), self-reported black skin color (OR = 1.47), physical inactivity (OR = 1.61), self-reported hearing loss (OR = 1.65), and presence of depressive symptoms (OR = 1.72). Higher education (OR=0.44), greater life satisfaction (OR=0.72), and being employed (OR=0.78) were protective factors. The RF model outperformed logistic regression, achieving an area under the ROC curve of 0.776, with a sensitivity of 0.708, a specificity of 0.702, an F1-score of 0.311, a G-means of 0.705, and an accuracy of 0.703. Conclusion: The findings reinforce the multidimensional nature of dementia and the importance of accessible factors for identifying vulnerable individuals. Strengthening public policies focused on promoting brain health can contribute significantly to the efficient allocation of resources in primary care and dementia prevention in Brazil
Thank you to arXiv for use of its open access interoperability. PaperDance 不是 arXiv 官方产品；中文卡片由大模型生成，请以原文为准。