Development and validation of a hyperlipidemia risk prediction model for middle-aged and older adult Chinese using 2015 CHARLS data

作者：Lixiang Zhang, Shiqiang Hou, Fang-fang Zhao, Tingting Wang, Ying Jiang, Xiaojuan Zhou, Jiao-yu Cao · 发表于：Frontiers in Public Health · 年份：2025 · DOI：10.3389/fpubh.2025.1420596 · 被引用次数：3 · 研究领域：Diabetes, Cardiovascular Risks, and Lipoproteins、Lipoproteins and Cardiovascular Health、Microbial Metabolism and Applications

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 p -values less than 0.05). From these findings, a nomogram prediction model was constructed to estimate the risk of hyperlipidemia for middle-aged and older adult individuals. The Area Under the Receiver Operating Characteristic (ROC) Curve (AUC) for the nomograms was 0.717 (95% Confid...