老年医学研究

目的 探讨老年人失能的潜在剖面，分析不同潜在剖面分型的影响因素。方法 采用便利抽样法，选取湖南省的5所养老机构的244例老年人为研究对象，利用一般资料调查表及世界卫生组织残疾评定量表2.0对老年人进行问卷调查，使用徒手肌力检查法判断肌力情况。通过潜在剖面分析确定老年人失能的潜在剖面，并基于单因素分析结果有意义的变量进行无序多分类logistic分析，同时构建决策树、随机森林模型，以探究不同潜在剖面分型预测的影响因素及其重要性排序。结果 老年人失能评分为（96.20±25.29）分，可分为低活动—高认知型极重度失能组（31.6%）、低活动—高自理型重度失能组（23.8%）、低活动型中度失能组（30.7%）与均衡型轻度失能组（13.9%）4个潜在剖面。老年人失能不同潜在剖面的影响因素包括肌力、婚姻状况、心血管疾病与手术史。决策树模型与随机森林模型结果显示，肌力对失能状况分型的影响程度最高。结论 老年人的失能存在群体异质性，影响因素为肌力、婚姻状况、心血管疾病与手术史。医护人员应根据不同潜在剖面及影响因素对老年人进行个体化干预，以改善失能。

Objective To explore the latent profiles of elderly disability and analyze the influencing factors of different latent profile classifications. Methods Convenience sampling was used to select 244 elderly individuals from 5 elderly care institutions in Hunan Province as research subjects. A general information questionnaire and the World Health Organization Disability Assessment Schedule 2. 0(WHODAS 2. 0) were utilized to survey the elderly participants, while manual muscle testing method was conducted to assess their muscle strength. Latent profiles of disability among elderly were identified using latent profile analysis. Variables that showed significance in univariate analyses were then included in multivariate analysis. Additionally, decision tree model and random forest models were constructed to explore the predictors of different latent profile classes and to rank their relative importance. Results The disability score of the elderly was 96. 20±25. 29, which could be categorized into four latent profiles: the extremely severe disability group with low activity and high cognition(31. 6%), the severe disability group with low activity and high self-care ability(23. 8%), the moderate disability group with low activity(30. 7%), and the mild disability group with balanced function(13. 9%). The influencing factors of different latent profiles of disability in the elderly included muscle strength, marital status, cardiovascular diseases, and surgical history. Results from the decision tree model and random forest model indicated that muscle strength has the highest importance in influencing the classification of disability status. Conclusions The disability among the elderly exhibits group heterogeneity, with muscle strength, marital status, cardiovascular diseases, and surgical history as influencing factors. Healthcare providers should implement personalized interventions for the elderly based on different latent profiles and influencing factors to improve their disability status.