China&#x02019;s elderly population identification model of metabolic syndrome-a study based on CHARLS database

ZENG Yiqun; LI Wei; CHEN Ruipeng; LIANG Chenzhao; LIANG Yanfang; LIU Chongmei

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Journal of Hunan Normal University(Medical Science) ›› 2024, Vol. 21 ›› Issue (5) : 143-150.

Preventive Medicine

China’s elderly population identification model of metabolic syndrome-a study based on CHARLS database

ZENG Yiqun, LI Wei, CHEN Ruipeng, LIANG Chenzhao, LIANG Yanfang, LIU Chongmei

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Abstract

Objective The incidence of Metabolic syndrome (MetS) is increasing year by year, which is threatening human health worldwide. The aim of this study is to construct a simple and efficient metabolic syndrome identification model. Methods This study used anthropometric data from the China Health and Retirement Longitudinal Survey (2011). A total of 7552 subjects aged 45 years and over were included and randomly divided into training set and validation set according to the ratio of 7∶3. Multivariate stepwise logistic regression analysis was used to construct a MetS identification model and a nomogram. The screening performance of the nomogram was evaluated by the area under the ROC curve, and the net benefit of the model was calculated by decision curve analysis. Results The age-standardized prevalence of MetS was 42.22% among Chinese middle-aged and elderly people over 45 years old. The model showed that female, hyperlipidemia, diabetes, smoking, high systolic blood pressure, fast pulse, wide waist circumference, and high BMI were risk factors for MetS. The C-index of the model was 0.864. The optimal threshold probability of the nomogram was 0.407. The AUC of ROC curve in training set was 0.864(0.854-0.874), and the AUC of ROC curve in validation set was 0.857(0.842-0.873). When the threshold probability was set to 0.407, the sensitivity of the model was 80% (95%CI: 78.35%-81.67%), and the specificity was 78% (95%CI: 76.57%-79.51%). Decision curve analysis showed that 33 persons per 100 persons could be exempted from unnecessary MetS confirmatory tests when MetS screening was performed by using this model. Conclusion The prevalence of MetS is high in middle-aged and elderly people in China. The identification model constructed in this study is helpful for the early screening of mets in Chinese people over 45 years old.

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the metabolic syndrome / risk factors / model of identification / nomogram / decision curve

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ZENG Yiqun, LI Wei, CHEN Ruipeng, LIANG Chenzhao, LIANG Yanfang, LIU Chongmei. China’s elderly population identification model of metabolic syndrome-a study based on CHARLS database[J]. Journal of Hunan Normal University(Medical Science). 2024, 21(5): 143-150

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