Analysis Of Factors Influencing The Prevalence Of Dyslipidemia In The Elderly In China

Dyslipidemia is one of the most common diseases in the world,and it is also the predisposing factor of many diseases,which has great harm to human health.Observing the data in recent years,we can see that the prevalence of dyslipidemia is related to age,and its prevalence shows the characteristics of increasing with age.With the continuous deepening of aging in China in recent years,the proportion of the elderly population is increasing,and the incidence of dyslipidemia is also increasing.Dyslipidemia has become a disease that cannot be ignored as it damages human health.Dyslipidemia accounts for more than half of the elderly population,so we should focus on the prevalence of this disease.Therefore,the influencing factors of the prevalence of dyslipidemia in the elderly in China require more comprehensive and diverse in-depth research and exploration.This article selected the survey data of China Health and Retirement Longitudinal Study(CHARLS)in 2018,which covers all counties in China’s mainland excluding Tibet,from which a sample of elderly people aged 60 years or older was selected to form the data base and index system of this paper.The research on the factors influencing the prevalence of dyslipidemia in the elderly in China started from three categories,including basic personal situation,personal health situation and living area situation,and established a more comprehensive and systematic index system based on this.On the basis of the data,descriptive analyses of each variable were firstly conducted to complete the preliminary exploration of the factors influencing the prevalence of dyslipidemia in China;next,multivariate logistic regression models,decision tree models and random forest models were established to investigate the factors influencing the prevalence of dyslipidemia in elderly people in China,and the results obtained from the decision tree and random forest models were used to supplement the multivariate logistic regression model and to establish a multivariate logistic regression model with new variables.In addition,the four models were compared,the optimal model was selected,and the factors influencing the prevalence of dyslipidemia in the elderly were analyzed based on the screening results of the model.Finally,the results of this data were used to propose targeted recommendations and countermeasures for the prevention and treatment of dyslipidemia in the elderly,and to make feasible suggestions for promoting the reduction of the prevalence of dyslipidemia in the elderly from a practical point of view.The conclusions of this paper are as follows: a.Multiple logistic regression models,decision tree models,random forest models,and multiple logistic regression models with new variables were established to study the factors influencing the prevalence of dyslipidemia among the elderly in China,and the four models were compared to obtain the optimal model--multiple logistic regression model with new variables.b.The results of data analysis showed that the factors influencing the prevalence of dyslipidemia in the elderly in China were mainly divided into three categories: basic personal situation,personal health situation and living area situation,elderly,male,no spouse,smoking,drinking,do not exercise,stroke,high blood pressure,high blood sugar,and older people living in cities and towns are more likely to suffer from dyslipidemia.Based on the above conclusions,this article gives recommendations from both the individual and the government levels to reduce the prevalence of dyslipidemia.At the individual level,First of all,it is necessary to conduct publicity and education on blood lipids related knowledge for the elderly with different blood lipids,enhance the success rate of hospital inspections and self-examinations,correct and standardize the living habits of the elderly,and cultivate the elderly Healthy eating habits and good fitness habits.At the governmental level,it is recommended to establish a macroscopic health record to monitor the prevalence of dyslipidemia and to focus on high-risk groups of dyslipidemia in order to control the prevalence of dyslipidemia.