Developing a comprehensive malnutrition prediction model for the elderly in nursing homes.

IF 3.4 2区医学 Q2 GERIATRICS & GERONTOLOGY

BMC Geriatrics Pub Date : 2025-05-20 DOI:10.1186/s12877-025-05863-3

Yan Wu, Wei Tan, Wenlong Yi, Yujuan Chen

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引用次数: 0

Abstract

Purpose: Malnutrition among elderly nursing home residents represents a critical public health challenge, particularly in rapidly aging societies such as China. This study aimed to develop and validate a predictive model for malnutrition risk tailored to this vulnerable population.

Methods: We analyzed clinical data from 1,023 elderly individuals (aged ≥ 65 years) across 26: nursing homes in Wuhan, China (March-October 2023). Participants were randomly divided into model-building (70%, n = 716) and internal validation cohorts (30%, n = 307). LASSO regression and logistic regression identified key predictors, and a nomogram was constructed. Model performance was assessed via AUC, calibration curves, and decision curve analysis (DCA).

Results: The malnutrition incidence was 46.37%. Five predictors were significant: feeding method (OR = 2.89, 95% CI: 1.75-4.76), dental status (OR = 0.56, 95% CI: 0.37-0.86), physical inactivity (OR = 1.75, 95% CI: 1.09-2.80), Barthel Index (OR = 0.96 per 10-point decrease), and anemia (OR = 1.91, 95% CI: 1.10-3.30). The model showed excellent discrimination (AUC = 0.90, 95% CI: 0.85-0.94) and calibration (mean absolute error = 0.026). DCA indicated clinical utility across threshold probabilities (2-97%).

Conclusion: This nomogram provides a robust tool for malnutrition risk stratification in nursing homes. Future studies should validate its generalizability across diverse populations and regions.

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开发养老院老年人营养不良综合预测模型。

目的：养老院老年人营养不良是一项重大的公共卫生挑战，特别是在中国等快速老龄化社会。本研究旨在开发和验证针对这一弱势群体的营养不良风险预测模型。方法：我们分析了2023年3月至10月中国武汉26家养老院1023名老年人（年龄≥65岁）的临床数据。参与者随机分为模型建立组（70%,n = 716）和内部验证组（30%,n = 307）。LASSO回归和logistic回归识别了关键预测因子，并构建了模态图。通过AUC、校准曲线和决策曲线分析（DCA）评估模型的性能。结果：营养不良发生率为46.37%。5个预测因子具有显著性：喂养方式（OR = 2.89, 95% CI: 1.75-4.76）、牙齿状况（OR = 0.56, 95% CI: 0.37-0.86）、缺乏运动（OR = 1.75, 95% CI: 1.09-2.80）、Barthel指数（OR = 0.96，每下降10点）和贫血（OR = 1.91, 95% CI: 1.10-3.30）。该模型具有良好的鉴别（AUC = 0.90, 95% CI: 0.85-0.94）和校准（平均绝对误差= 0.026）。DCA表明临床效用跨越阈值概率（2-97%）。结论：该nomogram为养老院营养不良风险分层提供了一个强有力的工具。未来的研究应验证其在不同人群和地区的普遍性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

BMC Geriatrics GERIATRICS & GERONTOLOGY-

CiteScore

5.70

自引率

7.30%

发文量

873

审稿时长

20 weeks

期刊介绍： BMC Geriatrics is an open access journal publishing original peer-reviewed research articles in all aspects of the health and healthcare of older people, including the effects of healthcare systems and policies. The journal also welcomes research focused on the aging process, including cellular, genetic, and physiological processes and cognitive modifications.