A Cross‐Nationally Validated Nomogram for Cardiometabolic Multimorbidity in Overweight/Obese Older Adults: CHARLS and HRS Cohorts

医学 列线图 逻辑回归 队列 人口 物理疗法 队列研究 预测效度 纵向研究 老年学 临床试验 外部有效性 老人忧郁量表 超重 萧条(经济学) 曲线下面积 概化理论 风险评估 接收机工作特性 预测建模 试验预测值 生活质量(医疗保健) 弗雷明翰风险评分 日常生活活动 健康与退休研究 流行病学 逐步回归 内科学 线性回归 前瞻性队列研究
作者
Yanhan Wei,Siyi He,Huizhen Chen,Yanzhong Wang
出处
期刊:Diabetes, Obesity and Metabolism [Wiley]
卷期号:28 (10): 8825-8835
标识
DOI:10.1111/dom.71077
摘要

AIMS: Middle-aged and older adults with overweight or obesity are at increased risk of cardiometabolic multimorbidity (CMM), yet validated prediction tools tailored to this population remain limited. This study aimed to develop and validate a multidimensional nomogram integrating metabolic, functional and psychological predictors. MATERIALS AND METHODS: were randomly split into development (n = 2775) and validation (n = 1190) sets. Candidate predictors spanned socio-demographic, lifestyle, functional, psychological and biochemical factors. External validation included 8180 overweight/obese participants from the US Health and Retirement Study (HRS). Least absolute shrinkage and selection operator and multivariable logistic regression were applied to build a nomogram. Performance was assessed by area under the curve (AUC), calibration and decision curve analysis. RESULTS: CMM prevalence was 3.91%. Eight variables were retained: residence, Activities of daily living (ADL) score, the Center for Epidemiologic Studies Depression Scale (CESD-10) score, haemoglobin A1c (HbA1c), hypertension, arthritis, dyslipidaemia and memory disorder. AUCs were 0.871 (95% CI: 0.838-0.905) (development), 0.817 (95% CI: 0.768-0.867) (validation) and 0.733 (95% CI: 0.714-0.751) in HRS external validation, with acceptable calibration in CHARLS and evidence of underestimation in HRS that improved after intercept recalibration, and clear net benefit. Positive predictive values were additionally reported to support clinical interpretation under the low CMM prevalence. CONCLUSIONS: This nomogram integrating metabolic, functional and psychological predictors demonstrated strong discrimination in the CHARLS cohort and maintained adequate discriminative performance in a cross-national external validation using the US HRS cohort despite differences in population characteristics and measurement instruments, supporting its potential utility for early CMM risk stratification in overweight/obese older adults. The external HRS validation showed fair discrimination, suggesting that model recalibration may be necessary before broad cross-national implementation.
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