Network relationship analysis of the influencing factors and disease risk prediction for hyperlipidemia in the elderly population of Henan province based on a Bayesian network model

Abstract

ObjectiveTo understand the network relationship of influencing factors for hyperlipidemia in the elderly population of Henan province and predict their disease risk, providing a reference basis for formulating prevention and intervention measures for hyperlipidemia. MethodsFrom July to December 2022, a multi-stage random sampling method was used to select 123 741 elderly individuals aged ≥ 60 years old in Henan province for questionnaire surveys, physical examinations, and laboratory tests. Based on multivariate unconditional logistic regression analysis, a hyperlipidemia Bayesian network model was constructed using the Max-Min Hill-Climbing (MMHC) algorithm to analyze the network relationship of influencing factors for hyperlipidemia in the local elderly population and predict their disease risk. ResultsAmong the 116 091 elderly individuals in Henan province finally included in the analysis, 33 023 had hyperlipidemia, with a prevalence rate of 28.45%; 9 873, 13 738, 14 765, and 4 338 individuals had high total cholesterol (TC), high triglyceride (TG), low high-density lipoprotein cholesterol (HDL-C), and high low-density lipoprotein cholesterol (LDL-C), respectively, with prevalence rates of 8.50%, 11.83%, 12.72%, and 3.74%, respectively. Multivariate unconditional logistic regression analysis showed that female gender, waist-to-height ratio (WHtR) ≥ 0.5, body mass index (BMI) ≥ 18.5, central obesity, hypertension, and diabetes were risk factors for hyperlipidemia in the elderly population of Henan province, while age ≥ 80 years old and junior high school education or above were protective factors. Bayesian network model analysis showed that gender, BMI, hypertension, and diabetes were directly associated with hyperlipidemia, while age, education level, WHtR, and central obesity were indirectly associated. Risk inference results showed that the highest risk of hyperlipidemia was 41.6% for elderly male hypertensive individuals with BMI ≥ 28.0, 38.8% for obese elderly individuals, and 37.0% for the elderly individuals with hypertension and diabetes.ConclusionThe prevalence of hyperlipidemia in the elderly population of Henan province was relatively low. Gender, age, education level, BMI, WHtR, central obesity, hypertension, and diabetes were the main influencing factors for hyperlipidemia in the local elderly population. In the prevention and control of hyperlipidemia, attention should be particularly paid to the elderly male hypertensive individuals with BMI ≥ 28.0.

Keywords

• hyperlipidemia
• influencing factors
• network relationship
• disease risk prediction
• bayesian network model
• elderly population
• henan province