The relationship between hyperlipidemia and physical activity in the elderly after controlling for demographic, health, and lifestyle variables

Abstract

In China, the number of elderly people with high blood lipids is increasing, and it is crucial to find practical methods to reduce the risk of high blood lipids in the elderly. This study explores the relationship between physical activity (PA) and hyperlipidemia in middle-aged and elderly people in China, providing new evidence for the prevention and treatment of hyperlipidemia through PA. This study investigated the association between PA and hyperlipidemia in 1779 middle-aged and elderly Chinese individuals. The Charles database from 2018 is the source of the data. This survey used a self-made personal information questionnaire, the Chinese version of the international PA questionnaire, and a self-assessment questionnaire for high blood lipids and personal information to evaluate the levels of high blood lipids and PA. Multiple logistic regression analysis is used to identify risk variables for hyperlipidemia and PA, while multi-level linear regression analysis is used to evaluate the correlation between PA and the likelihood of hyperlipidemia. The detection rate of hyperlipidemia symptoms was 13.4%, and the asymptomatic detection rate was 86.6%. 43.8% of people engage in high PA, while 50.2% engage in low PA. There is a significant correlation (P < .05) between PA and symptoms of hyperlipidemia in middle-aged and elderly people. After adjusting demographic variables (residence, education level, gender, age, widowhood or not), health status characteristics and living habits (arthritis, bad mood, diabetes, disability, asthma, self-assessment health, memory disease, stroke, depression), the correlation between PA and hyperlipidemia symptoms was still statistically significant (P < .05). The strong association between high blood lipids and PA provides information for developing targeted therapies for elderly individuals with high blood lipids in order to ensure efficacy and inclusiveness, improve PA levels, enhance the mental health of the elderly, reduce their risk of hyperlipidemia, while taking into account certain demographic and lifestyle characteristics.

1. Introduction

In recent years, with the increasing trend of population aging, the health status of the elderly has attracted more and more attention.^[1] With the development of social economy, people’s lifestyles and eating habits have changed significantly, leading to an increase in the prevalence of hyperlipidemia year by year.^[2] According to statistics, about 39% of the world’s adults are affected by hyperlipidemia, and the elderly are the high-risk group of hyperlipidemia.^[3,4] Hyperlipidemia may lead to serious complications such as atherosclerosis, coronary heart disease and stroke, and pose a serious threat to the life and health of the elderly.^[5,6] Hyperlipidemia is 1 of the common health problems of the elderly, and its main feature is the abnormal increase of cholesterol, triglyceride and lipid levels in the blood.^[7,8] Elevated blood lipid levels will not only increase the risk of atherosclerosis, but also have a negative impact on cardiovascular health, such as coronary heart disease and stroke.^[9,10] A meta-analysis showed that different forms of physical activity (PA) can reduce the levels of serum total cholesterol, triglycerides, and low-density lipoprotein cholesterol in middle-aged and elderly patients with hyperlipidemia, while increasing the level of high-density lipoprotein cholesterol.^[11] The effect of PA on blood lipid levels has also received widespread attention. A study from China shows that moderate intensity aerobic exercise has a significant impact on the levels of total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), and low-density lipoprotein cholesterol (LDL-C) in patients with hyperlipidemia.^[12] Another study shows that exercise therapy and diet control can reduce the incidence rate of hypertension and hyperlipidemia among the elderly in Beijing communities, and significantly reduce their blood pressure and blood lipid levels.^[13] Although previous studies have shown that moderate PA helps reduce blood lipid levels, there have been few studies on the relationship between PA and hyperlipidemia in the elderly.^[14,15] The results of some cross-sectional studies and randomized controlled trials have shown that increasing PA can improve cardiopulmonary function and blood lipid levels in the elderly.^[16,17] In recent years, some progress has been made in the research on the relationship between hyperlipidemia and PA in the elderly, but there are still some shortcomings. For example, the sample size of these studies is relatively small and lacks large-scale clinical data support.^[13,18] In addition, the PA methods and appropriate exercise intensities of the elderly population also need to be further explored.^[19] In previous studies, the mixed effects of demographic variables, health status, and lifestyle on hyperlipidemia and PA have not been fully investigated and need further research. The purpose of this study is to determine the relationship between hyperlipidemia and PA, and to explore how demographic variables, health status, and lifestyle affect the relationship between hyperlipidemia and PA. By providing evidence of this relationship and identifying key demographic, health, and lifestyle predictors. This study recommends the development and implementation of targeted, tailored, and sustainable public health interventions to encourage Chinese elderly people to develop positive lifestyle habits, reduce the negative effects of inactivity, and lower the risk of hyperlipidemia.

2. Methods

2.1. Participants and data

China Health and Retirement Longitudinal Study (CHARLS) is a large-scale, nationwide follow-up survey project targeting the elderly population in China.^[20] The main objective of the survey is to collect data on the health status, retirement behavior, social security, family support and other aspects of China’s elderly population, so as to understand the current situation and development trend of China’s aging problem and its impact on social economy. The Charls survey began in 2008 and initially covered 17,708 families in 150 counties (districts). Since then, the survey has conducted follow-up visits every 2 years to collect information on the health, economic, social and psychological aspects of the respondents. Data from CHARLS 2018 were utilized in our analysis. The CHARLS database at Peking University in China houses all the data that was gathered during CHARLS. All data can be found at http://charls.pku.edu.cn. This study was approved by the Ethics Review Board of Anshan Normal University, China. All participants of CHARLS signed informed consent forms before joining the study. The informed consent form provides a detailed explanation of the research objectives, process, potential risks, data usage methods, and the rights of participants, including the right to withdraw from the study at any time. The CHARLS team ensures that all participants participate in the study with full understanding and voluntary consent.

2.2. Variables

2.2.1. Demographic, health and lifestyle variables:

The demographic, health status and lifestyle variables of the participants were obtained through the self-made scale. Demographic variables include gender (male or female), age (50–59 years old, 60–69 years old, 70–79 years old, 80–89 years old and 90 years old and above), household registration type (urban or rural), education level (lower than high school or higher education), and widowhood (yes or no). Variables of health status include arthritis, hypertension, diabetes (yes or no), hyperlipidemia (yes or no), stroke (yes or no), depression (yes or no), and negative emotions (yes or no). Lifestyle variables include smoking (yes or no).

2.2.2. Physical activities:

We discovered through a questionnaire study that the elderly engage in physically taxing occupations such as farming, excavating, and moving heavy goods. This includes low-intensity pursuits like mahjong, Tai Chi, strolling, entertainment, and floor sweeping. After doing each physical exercise for at least 10 minutes, assess the participants’ daily activities. Each PA’s length is assessed as follows: longer than or equal to 10 minutes but less than 2 hours, longer than or equal to 0.5 hours but less than 2 hours, longer than or equal to 2 hours but less than 4 hours, and longer than or equal to 4 hours. Physical activity (PA) levels were assessed using the International physical activity questionnaire (IPAQ), a validated tool demonstrating good reliability and validity.^[21,22] Total weekly PA was calculated by summing metabolic equivalent of task (MET) values multiplied by duration (hours) for each activity, with participants categorized into 2 groups: high PA (≥23 MET·h/wk) or low PA (<23 MET·h/wk) based on established criteria.

2.2.3. Hyperlipidemia:

A questionnaire survey was conducted to investigate whether participants had been diagnosed with hyperlipidemia in the past year. In order to minimize diagnostic errors as much as possible, the questionnaire provides a clear definition of hyperlipidemia and encourages participants to consult a professional doctor to confirm the diagnosis before filling out the questionnaire.

2.3. Statistical analysis

Firstly, provide a statistical description of all variables. Secondly, multiple logistic regression analysis was used to identify risk variables for hyperlipidemia and PA. Then, using the likelihood of hyperlipidemia as the dependent variable and PA level as the independent variable, a multi-level linear regression analysis was conducted to evaluate the correlation between PA and the likelihood of hyperlipidemia. Model 1 was used to derive the P-value of PA and hyperlipidemia. Model 2 uses model 1 to predict demographic factors, such as registered resident status, education level, gender, age and widowhood. On the basis of model 2, model 3 predicts health factors (such as smoking, diabetes, stroke and hypertension). On the basis of model 3, model 4 predicted emotional factors (such as depression and bad mood). For all statistical analysis, P-value <.05 was considered statistically significant. All statistical analyses were performed using IBM SPSS statistics 27.0 (IBM SPSS Inc., Chicago).

3. Results

3.1. Demographic characteristic

A total of 1779 middle-aged and elderly people over 50 years old were included in this study. Among them, 879 (49.4%) were males and 900 (50.6%) were females. In terms of hyperlipidemia symptoms, the proportion of hyperlipidemia in the elderly was 13.4%. The proportion of high PA in middle-aged and elderly people was 43.8%, and the proportion of low PA in middle-aged and elderly people was 56.2%. The proportion of middle-aged and elderly participants aged 50 to 59, 60 to 69, 70 to 79, 80 to 89, 90 and above were 8.8% (156), 23.2% (413), 34.1% (607), 25.6% (456) and 8.1% (147), respectively. From the perspective of household registration type, rural household registration accounted for 73.3% (1304) and urban household registration accounted for 26.7% (475). In terms of education level, high school and above accounted for 18.8% (334 people), and junior high school and below accounted for 81.2% (1445 people). Widowed participants accounted for 13.2% (243). 28.5% (507) of the participants had smoking habits. In terms of chronic diseases, hypertension accounted for 18.8% (321), diabetes accounted for 8.0% (195), stroke accounted for 10.4% (185). In terms of emotional status, the participants with bad mood and depression were 8.0% (142) and 44.2% (750) (Table 1 and Fig. 1).

Table 1.

Characteristics of middle-aged and elderly participants of the CHARLS in 2018.

		Number of participants	%
Gender	Male	879	49.4
	Female	900	50.6
Age (yr)	50 to 59	156	8.8
	60 to 69	413	23.2
	70 to 79	607	34.1
	80 to 89	456	25.6
	≥90	147	8.1
Location of residence	City	475	26.7
	Rural	1304	73.3
Degree of education	Junior high school and below	1445	81.2
	High school and above	334	18.8
Widowed	Yes	234	13.2
	No	1545	86.8
Smoke	Yes	507	28.5
	No	1272	71.5
Hypertension	Yes	321	18.0
	No	1458	82.0
Hyperlipidemia	Yes	238	13.4
	No	1541	86.6
Diabetes	Yes	195	8.0
	No	1584	92.0
Stroke	Yes	185	10.4
	No	1594	89.6
Bad mood	Yes	142	8.0
	No	1636	92.0
Depression	Yes	750	42.2
	No	1029	57.8
Physical activity	High	780	43.8
	Low	999	56.2

CHARLS = China Health and Retirement Longitudinal Study.

Figure 1.

Flow chat of participants screening. A total of 19,752 participants participated in the 2018 CHARLS, with 3257 people excluded due to incomplete information on hyperlipidemia and PA, leaving 16,495 people. 14,716 people were excluded from 16,495 due to incomplete information on demography, physical health, mental health, and lifestyle habits. Finally, the remaining 1779 participants were included in the study. CHARLS = China Health and Retirement Longitudinal Study, PA = physical activity.

3.2. Analysis of influencing factors of physical activity

Participants’ age, hypertension, hyperlipidemia, diabetes, stroke, smoking, bad mood, depression and PA were significantly correlated (P < .05). In terms of age, older adults have lower levels of PA. In terms of health status, participants with disabilities, stroke, diabetes and arthritis had low levels of PA. In terms of mental health and lifestyle habits, participants with poor mood, depression, and smoking habits had lower levels of PA (Table 2).

Table 2.

Influencing factors of PA among elderly participants in CHARLS in 2018.

Physical activity		B	SE	Wald	P	OR	95% CI
							Lower	Upper
high	Gender (male)	−0.129	0.116	1.232	.267	0.879	0.701	1.103
	Age (getting older)
	50 to 59	−0.078	0.137	0.320	.571	0.925	0.707	1.211
	60 to 69	−0.182	0.182	1.008	.315	0.833	0.584	1.190
	70 to 79	−0.262	0.170	2.388	.122	0.769	0.552	1.073
	80 to 89	−0.178	0.137	1.695	.053	1.195	0.914	1.562
	≥90	−0.274	0.161	2.883	.010	0.761	0.555	1.043
	Location of residence (urban)	−0.034	0.135	0.062	.803	0.967	0.742	1.260
	Degree of education (higher education)	−0.030	0.147	0.043	.836	0.970	0.727	1.294
	Widowed (yes)	−0.053	0.174	0.092	.762	0.949	0.675	1.334
	Smoke (yes)	0.268	0.130	4.255	.039	1.307	1.013	1.687
	Hypertension (yes)	−0.592	0.204	8.403	.004	0.553	0.370	0.825
	hyperlipidemia (yes)	−0.928	0.205	20.482	<.001	0.395	0.265	0.591
	Diabetes (yes)	−2.532	0.408	38.606	<.001	0.079	0.036	0.177
	Stroke (yes)	−0.940	0.293	10.265	.001	0.391	0.220	0.694
	Bad mood (yes)	−1.213	0.454	7.127	.008	0.297	0.122	0.724
	Depression (yes)	−1.618	0.123	173.656	<.001	0.198	0.156	0.252

CHARLS = China Health and Retirement Longitudinal Study, PA = physical activity.

3.3. Analysis of influencing factors of hyperlipidemia

Gender, age, hypertension, diabetes, stroke, bad mood, low PA and hyperlipidemia were significantly correlated (P < .05). Participants with depression also had a higher risk of hyperlipidemia, but there was no significant correlation (P = .053). From a gender perspective, female participants are more likely to have hyperlipidemia. As age increases, the risk of high blood lipids in the elderly gradually increases. In terms of health status, participants with hypertension, diabetes and stroke were more likely to have hyperlipidemia. Older adults with increasing age, poor mood, depression, and low levels of PA are more likely to develop hyperlipidemia (Table 3).

Table 3.

Influencing factors of hyperlipidemia among elderly participants in CHARLS in 2018.

Hyperlipidemia		B	SE	Wald	P	OR	95% CI
							Lower	Upper
Yes	Gender (female)	0.471	0.173	7.436	.006	1.601	1.142	2.246
	Age (getting older)	0.512	0.320	2.567	.109	0.599	0.320	1.121
	50 to 59	−0.086	0.192	0.200	.655	0.918	0.630	1.337
	60 to 69	0.512	0.320	2.567	.109	0.599	0.320	1.121
	70 to 79	0.490	0.225	4.732	.030	1.633	1.050	2.540
	80 to 89	0.403	0.214	3.543	.060	1.497	0.984	2.278
	≥90	0.581	0.176	10.856	.001	1.788	1.265	2.526
	Location of residence (urban)	−0.147	0.198	0.551	.458	0.863	0.585	1.273
	Degree of education (higher education)	−0.027	0.211	0.017	.897	0.973	0.644	1.470
	Widowed (yes)	−0.349	0.261	1.784	.182	0.705	0.423	1.177
	Smoke (yes)	0.153	0.189	0.651	.420	1.165	0.804	1.688
	Hypertension (yes)	2.151	0.182	139.972	<.001	8.597	6.019	12.278
	Diabetes (yes)	1.037	0.243	18.184	<.001	2.820	1.751	4.540
	Stroke (yes)	0.794	0.256	9.646	.002	2.211	1.340	3.649
	Bad mood (yes)	2.139	0.331	41.757	<.001	8.487	4.437	16.235
	Depression (yes)	0.345	0.178	3.748	.053	1.413	0.996	2.004
	Physical activity (high)	−0.894	0.204	19.161	<.001	0.409	0.274	0.610

CHARLS = China Health and Retirement Longitudinal Study.

3.4. Linear hierarchical expression model of hyperlipidemia and physical activity level of participants

Model 1 showed that there was statistical significance between hyperlipidemia and PA (P < .05). Model 2 adjusted the demographic characteristic variables (gender, household registration type, education level, age, whether widowed) according to the amount of PA, and the results were also statistically significant (P < .05). After adjusting the health status and living habits (hypertension, diabetes, stroke, and smoking) on the basis of model 2, model 3 still showed statistical significance (P < .05). After adjusting the emotional status (bad mood and depression) on the basis of model 3, model 4 still showed statistical significance (P < .05) (Table 4).

Table 4.

Linear hierarchical regression model of hyperlipidemia and PA level of participants.

Model	R	R 2	Adjusted R2	Variation statistics
				F variation	P
1	.301*	.091	.090	177.216	<.001
2	.321†	.103	.099	28.983	<.001
3	.632‡	.399	.396	117.326	<.001
4	.654§	.428	.424	109.857	<.001

PA = physical activity.

^* Predictive variables: (constant), PA level.

^† Predictive variables: (constant), PA, gender, household registration type, age, education level, smoking, widowhood.

^‡ Predictors: (constant), PA, gender, household type, age, education level, smoking, widowhood, stroke, hypertension, diabetes.

^§ Predictors: (constant), PA, gender, household type, age, education level, smoking, widowhood, stroke, hypertension, diabetes, depression, and poor mood.

The sensitivity test of the linear stratified regression model between hyperlipidemia and participants’ PA levels was conducted using multiple logistic regression. The results showed that the results of Model 1, Model 2, Model 3, and Model 4 were still significant (P < .01) (Table 5), indicating the reliability of the linear stratified regression model between hyperlipidemia and participants’ PA levels.

Table 5.

Multiple logistic regression model of participants’ hyperlipidemia and PA level.

	B	SE	W	P	OR	95% CI
						Lower	Upper
Model 1*	2.926	0.305	91.896	<.001	0.054	0.029	0.098
Model 2†	0.108	0.011	91.486	<.001	1.114	1.089	1.138
Model 3‡	0.021	0.003	56.034	<.001	0.979	0.973	0.984
Model 4§	0.001	0.000	6.886	.009	0.999	0.998	1.000

PA = physical activity.

^* Predictive variables: (constant), PA.

^† Predictive variables: (constant), PA, gender, household registration type, age, education level, smoking, widowhood.

^‡ Predictors: (constant), PA, gender, household type, age, education level, smoking, widowhood, stroke, hypertension, diabetes.

^§ Predictors: (constant), PA, gender, household type, age, education level, smoking, widowhood, stroke, hypertension, diabetes, depression, and poor mood.

4. Discussion

This study used logistic regression model and linear hierarchical regression model to analyze the relationship between hyperlipidemia and PA level in middle-aged and elderly people over 50 years old (P < .05), which was still statistically significant after adjusting demographic variables, health status characteristics, living habits and emotional status (P < .05). Overall, our results showed that the proportion of hyperlipidemia in the middle-aged and elderly people over 50 years old was 13.4%; The proportion of high PA in middle-aged and elderly people was 43.8%, and the proportion of low PA in middle-aged and elderly people was 56.2%. The number of hyperlipidemia cases in middle-aged and elderly people with high PA level was significantly lower than that with low PA level, which indicated that there was an inverse relationship between high PA and hyperlipidemia subtypes in the elderly. By using a hierarchical regression model, we emphasize that even among people with complications such as hypertension or diabetes, PA can independently promote lipid regulation.

Our research results are consistent with previous studies by Korean scholars. Their study reported a similar association between PA and hyperlipidemia in the Korean population, supporting the universality of our findings. Kun et al^[23] compared the differences between the prevalence of hyperlipidemia and the level of PA in adults, as well as the differences in annual personal medical expenses, hospitalization expenses, emergency and outpatient expenses, and PA levels among hyperlipidemia patients. They used the 2018 Korean medical panel data (14,489 adults and 2559 patients with hyperlipidemia). Physical activity was measured by IPAQ short table and converted to met minutes per week. The hospitalization days and personal medical expenses of the 2 groups were compared, and frequency analysis, logistic regression analysis, analysis of variance and chi square test were performed. The results showed that compared with low PA, moderate and high PA significantly reduced the prevalence of hyperlipidemia. And PA has a positive impact on hospitalization and reduction of emergency use. In our prevention and treatment of hyperlipidemia in the elderly, it is not recommended to directly use a variety of drugs for prevention and treatment. The elderly should be encouraged to take part in more sports activities. Physical exercise can help prevent metabolic syndrome in the elderly and reduce the risk of hyperlipidemia. Kim et al^[24] used the 2009 Korean community health survey data and 212,584 participants in this study to investigate the relationship between parks and green spaces and hyperlipidemia in adults and grouped moderate PA as behavior correction. After classifying the risk of hyperlipidemia according to whether moderate PA is carried out or not, people who participate in moderate PA are less likely to suffer from hyperlipidemia than those who do not. They concluded that sports activities may benefit from the presence of parks and green spaces, which can reduce the risk of hyperlipidemia. The study also believes that high-level PA can reduce the risk of hyperlipidemia in the elderly.

The above research suggests that PA is very important for the prevention and treatment of hyperlipidemia in the elderly. Elderly people should strengthen physical exercise, improve their health, and reduce the risk of hyperlipidemia.

Our research results are also consistent with previous studies by Chinese scholars. Their research reports the similar relationship between sports activities and hyperlipidemia in Chinese people, which supports the universality of our research results. Jieying^[25] explored the characteristics of PA and sedentary behavior among elderly people in Chinese cities, as well as their relationship with body composition and chronic diseases. The results showed that increasing PA can reduce the risk of hyperlipidemia, while sedentary behavior increases the risk of developing hyperlipidemia. Shutong^[26] assessed the correlation between PA and blood glucose control and the risk of diabetes in community population in Shanghai, China. The results showed that compared with nonmanual workers, low-intensity manual labor significantly reduced the detection rate of central obesity, hypertension, hyperlipidemia, and diabetes high-risk scores, and medium and high-intensity manual labor improved hyperlipidemia most significantly.

Our study suggests implementing a comprehensive strategy of personalized exercise plans, community sports activities, and health education promotion, aimed at effectively increasing PA levels and potentially reducing the risk of hyperlipidemia by providing customized exercise programs, promoting a PA atmosphere among elderly people in the community, and raising their awareness of healthy behaviors.

Hyperlipidemia refers to the abnormal increase of cholesterol and triglyceride levels in the blood, which is a common metabolic disease. Long term hyperlipidemia will not only increase the risk of cardiovascular disease, but also cause other health problems.^[27] Therefore, how to regulate blood lipid levels has become the focus of attention. In recent years, more and more studies have shown that high PA plays a significant role in reducing the risk of hyperlipidemia.^[28,29] High PA, especially aerobic exercise, such as jogging and swimming, can improve blood circulation and accelerate the consumption and decomposition of blood lipids. This effect is mainly achieved by increasing energy consumption and promoting fat oxidation. During exercise, the demand of muscle tissue for energy increases, resulting in the release of fatty acids from adipose tissue and oxidation to energy. This process not only reduces the storage of adipose tissue, but also reduces the level of triglycerides in the blood. In addition, aerobic exercise can also improve the level of high-density lipoprotein cholesterol (HDL-C). HDL-C is called “good cholesterol” because it can help transport cholesterol from the arterial wall back to the liver for metabolism. Therefore, the increase of HDL-C level helps to reduce the risk of cardiovascular disease.^[30–32] High PA can increase the elasticity and stability of vascular endothelial cells. Vascular endothelial cells are an important part of the vascular wall, and their abnormal function will lead to vascular inflammatory response and atherosclerosis and other cardiovascular diseases. By increasing the elasticity and stability of vascular endothelial cells, high PA can reduce the risk of cardiovascular disease, thereby reducing the risk of hyperlipidemia.^[33,34] High PA can also regulate inflammatory response and oxidative stress. Inflammatory response and oxidative stress are 1 of the important pathogenesis of cardiovascular disease. High PA can reduce the degree of inflammatory reaction and oxidative stress by reducing the production of inflammatory factors and increasing the activity of antioxidant enzymes, thereby reducing the risk of cardiovascular disease and hyperlipidemia.^[35,36] High PA can reduce the risk of hyperlipidemia by promoting lipid metabolism, improving the activity of enzymes related to lipid metabolism, regulating hormone levels and reducing abdominal fat accumulation. These mechanisms interact to reduce the risk of hyperlipidemia and improve cardiovascular health.^[36]

Therefore, for patients with hyperlipidemia, actively participating in high PA is an effective way to manage and prevent hyperlipidemia. At the same time, we should also pay attention to reasonable diet and maintain good living habits to further reduce the risk of hyperlipidemia.

The results of our model also quantify the impact of demographic variables on the relationship between PA and hyperlipidemia. The results showed that the middle-aged and elderly men had a higher risk of hyperlipidemia. This is consistent with previous studies by Yang et al,^[37] who found that the 10-year risk of cardiovascular diseases such as hyperlipidemia was significantly higher in men aged 65 or older, smoking, drinking or chewing betel nut; Those with metabolic syndrome and its components also had a significantly higher 10-year risk of cardiovascular disease. Logistic regression analysis showed that with the increase of hypertension, hyperglycemia and hyperlipidemia, the 10-year risk of cardiovascular disease increased, and the odds ratios were 3.44, 8.13 and 16.64, respectively. In conclusion, hypertension, hyperglycemia and hyperlipidemia are risk factors for cardiovascular disease in men and women in the past 10 years. If men suffer from the above diseases, the risk is higher.

In order to reduce the incidence of cardiovascular disease, it is necessary to carry out strict and active treatment and control. Female estrogen protection is also an advantage of longevity.^[38] Estrogen is conducive to regulating blood lipid metabolism, so that the incidence of hyperlipidemia in premenopausal women is less than that in men, and the incidence of cardiovascular and cerebrovascular diseases such as heart disease and coronary heart disease is also lower.^[39]

This study found that the risk of other chronic diseases and diabetes in the elderly was significantly increased. Hypertension, hyperlipidemia and diabetes often coexist in the elderly. The relationship between them is mainly reflected in the following aspects. Hypertension can lead to vascular intimal damage, which makes blood lipids more likely to deposit on the vascular wall, forming atherosclerotic plaques, and further aggravate hypertension.^[40] At the same time, hyperlipidemia can also increase the blood viscosity, blood flow resistance and blood pressure. Long term hyperglycemia can damage vascular endothelial cells, leading to dysfunction of vasomotor function and elevated blood pressure.^[41] At the same time, hypertension can also aggravate the vascular disease of diabetic patients, such as diabetic nephropathy, retinopathy and so on. Hyperlipidemia can lead to insulin resistance, reducing the sensitivity of the body to insulin and increasing blood glucose. At the same time, hyperglycemia can also promote lipid synthesis and aggravate hyperlipidemia.^[4] This interaction makes hyperlipidemia and diabetes aggravate each other in the elderly. There are many common pathogenic factors of hypertension and hyperlipidemia in the elderly, such as genetic factors, environmental factors, bad living habits, age, genetics, obesity, lack of exercise and so on. These factors work together to make hypertension and diabetes present a high correlation in the elderly. The pathogenic factors of hyperlipidemia and diabetes in the elderly also have many things in common, such as heredity, diet, lifestyle and so on. These factors work together to make hyperlipidemia and diabetes present a high correlation in the elderly.^[42] In addition, the results of this study show that the middle-aged and elderly people with depression and poor mood have a higher risk of hyperlipidemia. This result is partially consistent with the previous study of Yanchun et al.^[43] The relationship between hyperlipidemia and bad mood is a complex and interactive process. As 1 of the common chronic diseases of the elderly, hyperlipidemia is not only related to diet, living habits, genetic factors, but also affected by bad emotions.^[43] Chronic negative emotions, such as tension, anxiety and depression, may lead to endocrine disorders in the elderly. This disorder will further affect the normal function of the liver, resulting in abnormal lipid metabolism, which will lead to the occurrence of hyperlipidemia.^[44]

Bad emotions often lead to loss of appetite or preference for high-fat, high sugar foods in the elderly. This change in dietary choice may increase the fat content in the blood, and then aggravate the situation of hyperlipidemia. According to the research, the elderly who have been in bad mood for a long time are more likely to have hyperlipidemia.^[45] Bad emotions may also lead to changes in the living habits of the elderly, such as lack of exercise and lack of sleep. These bad living habits will further affect lipid metabolism and increase the risk of hyperlipidemia.^[46]

4.1. Deviation consideration

In this study, we used cross-sectional survey data from CHARLS. Although these data provide us with rich information to explore the relationship between PA levels and hyperlipidemia, we must acknowledge that there may be certain biases in the survey data itself, which may have an impact on the research results. Due to the fact that our sample was selected from the population using a certain sampling method, there may be sampling bias. This deviation may be due to factors such as incomplete sampling boxes, insufficient randomness in the sampling process, or insufficient sample representativeness. Answer bias is also a potential issue. During the survey process, respondents may give inaccurate or biased answers due to various reasons such as memory blur, misunderstanding, and social expectation effects. Data interpretation bias may also have an impact on research results. Due to the fact that survey data is usually based on subjective responses from respondents, there may be subjectivity and uncertainty in the data interpretation process.

5. Conclusion and limitations

The PA level of middle-aged and elderly people is closely related to the status of hyperlipidemia, but the research on PA and stroke status of middle-aged and elderly people in China is still in its infancy. In this study, the high level of PA in the elderly can significantly reduce the risk of hyperlipidemia compared with low PA. At the same time, the middle-aged and elderly people are more likely to have hyperlipidemia symptoms, such as low education level, poor self-evaluation of health status, disability, hyperlipidemia, memory impairment, arthritis, asthma, and the difference of walking 1 km. This study helps to better understand the relationship between hyperlipidemia and PA in middle-aged and elderly people and provides a new basis for formulating scientific and effective exercise prescriptions to prevent and treat hyperlipidemia in middle-aged and elderly people. This study suggests implementing a comprehensive strategy of personalized exercise plans, community sports activities, and health education promotion, aimed at effectively increasing PA levels and potentially reducing the risk of hyperlipidemia by providing customized exercise programs, promoting a PA atmosphere among elderly people in the community, and raising their awareness of healthy behaviors.

Some limitations also affect our research. First, after adjusting the population characteristics and variables related to physical and mental health, this study only revealed the relationship between PA and hyperlipidemia. The dependence of this study on self-reported data of PA. In future research, it is necessary to use PA instruments to accurately record PA levels; It is necessary to use objective measurement tools, such as biochemical markers (such as cholesterol and triglyceride levels), to determine the accuracy of diagnosing hyperlipidemia. Secondly, we proved that there was a correlation between PA and hyperlipidemia in middle-aged and elderly people in China. Because there may be regional differences in the correlation between sports activities and hyperlipidemia, it is necessary to expand the sample size of the survey, and further explore the relationship between sports activities and hyperlipidemia in various ethnic groups, so as to determine the effectiveness of this research conclusion. Third, this study did not measure the possibility of confounding factors (such as nutritional status, drug use). Fourthly, this study employed a cross-sectional design, which means we collected participants’ PA and hyperlipidemia data at the same time point. Although this design approach can reveal the correlation between the 2, it cannot directly infer a causal relationship.

Acknowledgments

The authors thank all the participants in CHARLS team for their time and effort devoted to the project.

Author contributions

Conceptualization: Zhengri Quan, Hang Yin.

Data curation: Zhengri Quan, Hang Yin, Yaqun Zhang.

Funding acquisition: Yaqun Zhang.

Investigation: Zhengri Quan, Hang Yin, Yaqun Zhang.

Methodology: Zhengri Quan, Hang Yin, Yaqun Zhang.

Project administration: Zhengri Quan, Yaqun Zhang.

Resources: Hang Yin.

Supervision: Hang Yin.

Writing – original draft: Zhengri Quan, Yaqun Zhang.

Writing – review & editing: Zhengri Quan, Yaqun Zhang.