Evidence map›Paper›PMID 42410308›Full record

ArticleDiabetes, obesity & metabolism2026

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

Yanhan Wei, Siyi He, Huizhen Chen, Yanzhong Wang

Abstract readValidation Study
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Article in Diabetes, obesity & metabolism, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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3 · Its place in the literature

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1 citing paper in PubMed.

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5 · Who and what money

Authors and funding

4 authors.

Yanhan WeiInstitute of Health Informatics, University College London, London, UK.
Siyi HeSchool of Life Course and Population Sciences, King's College London, London, UK.
Huizhen ChenSchool of Life Course and Population Sciences, King's College London, London, UK.ORCID 0009-0008-5524-616X
Yanzhong WangSchool of Life Course and Population Sciences, King's College London, London, UK.

Funding

National Science and Technology Major Project 2024ZD0523300
6 · The paper itself

Abstract

aimsMiddle-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

methodsUsing the China Health and Retirement Longitudinal Study (CHARLS) data (2011 and 2015), 3965 overweight/obese adults with a body mass index (BMI) ≥ 24.0 kg/m

resultsCMM 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.

conclusionsThis 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.

Indexed as

Cardiovascular DiseasesNomogramsObesityOverweightAgedBody Mass IndexCardiometabolic Risk FactorsChinaFemaleHumansLongitudinal StudiesMaleMiddle AgedMultimorbidityPrevalenceUnited Statescardiometabolic multimorbidityCHARLSnomogramoverweight and obesitypredictive model

Identifiers

PMID42410308
PMCPMC13538773

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