ArticleFrontiers in public health2025
Development and validation of a hyperlipidemia risk prediction model for middle-aged and older adult Chinese using 2015 CHARLS data.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- Development and Validation of a Predictive Model for Mild Cognitive Impairment in Older Adults with Multimorbidity.Clinical interventions in aging · 2026Article
- Construction and validation of a risk prediction model for extensive abdominal aortic calcification in hypertensive patients aged 40 and above: a cross-sectional study based on the 2013-2014 NHANES database.BMC cardiovascular disorders · 2025Article
- Patterns and Factors of Intrinsic Capacity Impairment in Older Adults with Chronic Diseases: A Latent Class Analysis.Clinical interventions in aging · 2025Article
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Authors and funding
7 authors.
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Abstract
Objective: To develop and validate a predictive model for hyperlipidemia risk among middle-aged and older adult individuals in China, this study aims to offer an effective screening tool for identifying those at risk. Methods: In this study, we included 6,629 middle-aged and older adult individuals, aged 45 and above, who met the inclusion criteria from the 2015 China Health and Retirement Longitudinal Study (CHARLS) as our research subjects. Utilizing the LASSO regression and multivariate Logistic regression method, we analyzed the independent risk factors associated with hyperlipidemia among these subjects. Subsequently, we established a risk prediction model for hyperlipidemia in the middle-aged and older adult population using statistical software Stata 17.0. Results: The prevalence rate of hyperlipidemia among the 6,629 middle-aged and older adult participants was 26.32% (1,745 out of 6,629). The LASSO regression and multivariate Logistic regression analysis all revealed that Body Mass Index (BMI), fasting blood glucose, serum uric acid, C-reactive protein, and white blood cell count were independent risk factors for hyperlipidemia in this demographic (with Odds Ratios (OR) greater than 1 and Conclusion: The nomogram model, which incorporates the identified risk factors for hyperlipidemia in middle-aged and older adult individuals, has demonstrated good predictive efficiency and clinical applicability. It can serve as a valuable tool to assist healthcare professionals in screening for high-risk groups and implementing targeted preventive interventions. By doing so, it has the potential to significantly reduce the incidence of hyperlipidemia among this demographic.
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