Association of Physical Activity with Chronic Diseases: A Cross-sectional Study of 18500 Middle-aged and Elderly Chinese

doi:10.21203/rs.3.rs-4616494/v1

Download PDF

Article

Association of Physical Activity with Chronic Diseases: A Cross-sectional Study of 18500 Middle-aged and Elderly Chinese

https://doi.org/10.21203/rs.3.rs-4616494/v1

This work is licensed under a CC BY 4.0 License

You are reading this latest preprint version

Background

Regular physical activity is beneficial for both physical and mental health. However, studies on physical activity levels among middle-aged and elderly individuals in China are relatively scarce, and the health benefits of different activity levels remain unclear.

Objective

Using cross-sectional data from the 2020 China Health and Retirement Longitudinal Study (CHARLS), this study describes the prevalence of chronic diseases and examines their association with physical activity (PA).

Methods

Participants self-reported the presence of fifteen chronic health conditions: Hypertension, Dyslipidemia, Diabetes, Cancer or Malignant tumor, Chronic lung diseases, Liver disease, Heart attack, Stroke, Kidney disease, Stomach or other Digestive diseases, Emotional, Nervous, or Psychiatric problems, Memory-related diseases (such as dementia, brain atrophy), Parkinson’s disease, Arthritis or Rheumatism, and Asthma. Total physical activity was assessed using the International Physical Activity Questionnaire (IPAQ). Multivariate logistic regression was used to estimate the association between chronic diseases and PA.

Results

In China, more than a quarter of middle-aged and elderly individuals do not meet physical activity guidelines, with only about a third achieving high activity levels. Compared to those with low PA, individuals with moderate PA had a reduced risk of 4 chronic diseases (Stroke, Emotional and Mental problems, Memory-related diseases, Asthma), while those with high PA had a reduced risk of 10 chronic diseases (Hypertension, Dyslipidemia, Diabetes, Cancer, Heart attack, Stroke, Emotional, Nervous, or Psychiatric problems, Memory-related diseases such as dementia and brain atrophy, Parkinson’s disease, Asthma).

Conclusion

Higher physical activity levels are associated with lower risks of chronic diseases. Governments and organizations should encourage individuals to achieve higher activity levels (> 3000 MET-min/week), not merely meet physical activity guidelines (≥ 600 MET-min/week).

Health sciences/Diseases

Health sciences/Risk factors

Public health

Physical activity

Chronic Diseases

Middle-aged and Elderly

As the global aging trend accelerates, the health of the elderly has become a focal point of global attention^[1][2]. This is particularly evident in China, where the rapid growth of the elderly population poses significant public health challenges^[3]. Multiple studies have shown that older adults are more likely to suffer from chronic diseases, which severely impact their quality of life^[4].

Chronic diseases, including cardiovascular diseases, diabetes, and cancer, represent major public health challenges worldwide. According to reports by the World Health Organization (WHO), chronic diseases account for 68% of global deaths^[5], with approximately 6%-10% of these deaths related to coronary heart disease, diabetes, and cancer^[6]. While chronic diseases can be caused by various factors such as environmental and genetic factors, physical inactivity is recognized as one of the primary preventable factors^[7]. Numerous studies have demonstrated that a lack of physical activity can lead to an increase in the incidence of many chronic diseases, making physical inactivity the fourth leading cause of death after high blood pressure, smoking, and diabetes, accounting for 9% of mortality^[6].

In 2020, the WHO developed and released international guidelines for physical activity. These guidelines recommend that adults engage in at least 150 minutes of moderate-intensity aerobic physical activity, or at least 75 minutes of vigorous-intensity aerobic physical activity per week, or an equivalent combination of both^[8]. According to self-reported health questionnaires, 40%-60% of the global population is insufficiently active^[9]. In a nationally representative survey in Australia, approximately 40%-50% of Australians were found to be insufficiently active^[10]. In China, this proportion is 25.30%-47.44%^[11].

Research has shown that physical activity helps reduce systemic inflammation levels, improve metabolic health (for example, by increasing insulin sensitivity and improving lipid profiles), and enhance cardiovascular system function^[12][13][14]. These changes collectively reduce the risk of chronic diseases. Additionally, regular physical activity has been proven to significantly reduce symptoms of depression and anxiety, improve individuals' quality of life and sense of self-efficacy, and enhance mental health by strengthening social connections and reducing feelings of loneliness^[12]. Therefore, reducing the proportion of the population that is insufficiently active is of significant importance in the field of public health in the 21st century^[7][8][15].

Despite the widely recognized benefits of physical activity in preventing chronic diseases, current research has insufficiently explored the relationship between different levels of physical activity and health outcomes^[16]. This study aims to explore the relationship between different levels of physical activity and the incidence of chronic diseases, thereby enriching existing research and providing necessary scientific evidence for formulating effective public health strategies.

2.1 Study Sample

The participants of this study were derived from the China Health and Retirement Longitudinal Study (CHARLS), which aims to collect high-quality microdata on households and individuals aged 45 and above in China. This data is used to analyze the aging population and promote interdisciplinary research on aging. Since 2011, the CHARLS survey has been conducted nationwide, covering 28 provinces, 150 county-level units, and 450 village-level units, initially encompassing approximately 10,000 households and 17,708 middle-aged and elderly individuals^[17]. Utilizing systematic sampling methods, the fifth round of the survey included 19,395 participants, ensuring comprehensive representativeness of the research data. This study included 18,500 samples aged 45 and above, excluding those with severe cognitive impairment, severe mobility restrictions, among other criteria.

2.2 Measures

2.2.1 Chronic Diseases

The collection of chronic disease conditions included the incidence of 15 common chronic diseases: hypertension, abnormal blood lipids, diabetes, cancer, chronic lung diseases, liver diseases, heart diseases, stroke, kidney diseases, stomach diseases, emotional and mental problems, memory-related diseases such as dementia and brain atrophy, Parkinson's disease, arthritis or rheumatism, and asthma. To gather this information, every participant was asked the following question: (1) "Has a doctor ever told [XRName] that they have [XChroDisType[i]]?" Additionally, since CHARLS is a national longitudinal survey, a portion of the 18,500 participants had already been diagnosed with diseases in the 2018 survey; hence, these specific questions were not revisited in this survey. The final sample of diagnosed individuals consisted of those confirmed to have diseases in 2020 combined with those diagnosed in 2018.

2.2.2 Physical Activity

Participants were asked to report the number of days they engaged in light, moderate, or vigorous physical activity in the past seven days, as well as the specific time spent engaging in different types of physical activity each day (only those physical activities lasting more than 10 minutes at a time were included). Following established guidelines for IPAQ data processing and analysis, total activity time was calculated by multiplying the reported duration (in minutes) of different types of physical activity by the number of days that activity was performed. The metabolic equivalents (METS) of each activity (light = 3.3, moderate = 4.0, and vigorous = 8.0) were multiplied by the number of minutes per week to provide an estimate of total MET-minutes per week. Total physical activity was then categorized as low (< 600 MET×minutes per week), moderate (600–3000 MET×minutes per week), and high (> 3000 MET×minutes per week).

2.5 Covariates

The sociodemographic characteristics of participants (gender, age, residential area, education level, sleep, drinking status, marital status, smoking status) were collected using standardized questionnaires. In this study, we adjusted for potential confounding factors in the multivariate logistic regression analysis to assess the association between physical activity levels and the risk of chronic diseases. Model 1 was the unadjusted multivariate logistic regression model. Model 2 was adjusted for age and gender. Model 3 was additionally adjusted for marital status, education level, and area. Model 4 was further adjusted for sleep, drinking status, and smoking status.

2.6 Statistical Analysis

Sample characteristics and chronic disease prevalence were presented as frequencies and percentages and stratified by low, moderate, and high overall physical activity. To examine the association between physical activity levels and demographic variables, lifestyle factors, and chronic diseases, Pearson chi-square tests and ANOVA were employed, depending on the type of variables. A p-value of less than 0.05 was defined as statistically significant. Multiple logistic regression was used to explore the association between different physical activity levels and the risk of chronic diseases. First, the low physical activity population was used as a reference, and after adjusting for all covariates, the odds ratios (OR) and 95% confidence intervals (CI) for medium and high physical activity levels were calculated. Secondly, using moderate physical activity as a reference, after adjusting for all covariates, the OR and 95% CI for high physical activity were plotted with a forest plot. All data analyses were performed using R software version 4.3.3.

This study analyzed data from 18,500 participants aged 45-92 to explore the relationship between physical activity levels and the risk of chronic diseases. Detailed demographic characteristics and lifestyle features are summarized in Table 1. In the overall sample, the average age was 61 ± 9.6 years. Females (52.4%) slightly outnumbered males (47.6%), and rural residents (63.3%) were more prevalent than urban-rural (12.3%) and urban (24.4%) residents. Among the participants, 5,305 (28.7%) reported low physical activity, 6,455 (34.9%) reported moderate physical activity, and 6,740 (36.4%) reported high physical activity, with 13,195 (71.3%) meeting the guidelines for physical activity. Among the 15 chronic diseases, the highest prevalence was found in hypertension (40.1%) and rheumatoid arthritis (38.6%), while the lowest was found in Parkinson’s disease (1.3%) and cancer (2.6%). Younger individuals, those with higher education levels, and rural populations were more likely to meet the physical activity guidelines and achieve higher levels of physical activity. Using chi-square tests and ANOVA, we found significant correlations between all sociodemographic and lifestyle variables and physical activity levels (P < 0.001).

Table 1: Participant characteristics stratified by total physical activity

	Overall	Low physical activity	Moderate physical activity	High physical activity	P-value
	N=18500	N=5305	N=6455	N=6740
Age(years)X±SD	61.6 (9.6)	64.1 (10.3)	62.1 (9.5)	59.2 (8.5)	0.001
Male	8818 (47.6)	2452 (27.8)	3012 (34.2)	3347 (38.0)	0.001
Education					0.001
None	3961 (21.4)	1442 (36.4)	1128 (28.5)	1391 (35.1)
Primary	7968 (43.1)	2352 (29.5)	2597 (32.6)	3019 (37.9)
Secondary	6149 (33.2)	1440 (23.4)	2499 (40.6)	2210 (35.9)
College or university	422 (2.28)	71 (16.8)	231 (54.7)	120 (28.4)
Area					0.001
Town	4507 (24.4)	1183 (26.2)	2051 (45.5)	1273 (28.2)
Urban and rural	2283 (12.3)	621 (27.2)	875 (38.3)	787 (34.4)
Rural	11710 (63.3)	3501 (29.9)	3529 (30.1)	4680 (40.0)
Smoke Status					0.001
Current smoker	4775 (25.8)	1310 (27.4)	1525 (31.9)	1940 (40.6)
Quit smoking	2478 (13.4)	772 (31.2)	932 (37.6)	774 (31.2)
Never smoker	11247 (60.8)	3223 (28.7)	3998 (35.5)	4026 (35.8)
Drinking status					0.001
Table 1: Participant characteristics stratified by total physical activity
	Overall	Low physical activity	Moderate physical activity	High physical activity	P-value
>Once/per week	4961 (26.8)	1213 (24.5)	1680 (33.9)	2068 (41.7)
<Once/per week	1751 (9.5)	421 (24.0)	651 (37.2)	679 (38.8)
Never drink	11788 (63.7)	3671 (31.1)	4124 (35.0)	3993 (33.9)
Marital status					0.001
Married	15608 (84.4)	4204 (26.9)	5396 (34.6)	6008 (38.5)
Separated	89 (0.05)	28 (31.5)	23 (25.8)	38 (42.7)
Divorced	253 (1.4)	68 (26.9)	113 (44.7)	72 (28.5)
Widowed	2443 (13.2)	953 (39.0)	891 (36.5)	599 (24.5)
Never married	107 (0.6)	52 (48.6)	32 (29.9)	23 (21.5)
Chronic					0.29
Hypertension	7411 (40.1)	2418 (32.6)	2723 (36.7)	2270 (30.6)	0.001
Dyslipidemia	4958 (26.8)	1490 (30.1)	1897 (38.3)	1571 (31.7)	0.001
Diabetes	2744 (14.8)	864 (31.5)	1091 (39.8)	789 (28.8)	0.001
Cancer	472 (2.6)	157 (33.3)	199 (42.2)	116 (24.6)	0.001
Chronic lung disease	2629 (14.2)	826 (31.4)	905 (34.4)	898 (34.2)	0.002
Liver disease	1342 (7.3)	366 (27.3)	487 (36.3)	489 (36.4)	0.4
Heart disease	3859 (20.9)	1310 (33.9)	1442 (37.4)	1107 (28.7)	0.001
Stroke	1311 (7.1)	528 (40.3)	486 (37.1)	297 (22.7)	0.001
Kidney disease	1934 (10.5)	557 (28.8)	705 (36.5)	672 (34.7)	0.2
Stomach disease	5842 (31.6)	1646 (28.2)	2068 (35.4)	2128 (36.4)	0.5
Emotional and mental issues	535 (2.9)	219 (40.9)	182 (34.0)	134 (25.0)	0.001
Alzheimer's disease	745 (4.0)	287 (38.5)	258 (34.6)	200 (26.8)	0.001
Parkinson's disease	248 (1.3)	100 (40.3)	96 (38.7)	52 (21.0)	0.001
Table 1: Participant characteristics stratified by total physical activity
	Overall	Low physical activity	Moderate physical activity	High physical activity	P-value
Arthritis or rheumatism	7140 (38.6)	2085 (29.2)	2368 (33.2)	2687 (37.6)	0.001
Asthma	1119 (6.0)	420 (37.5)	387 (34.6)	312 (27.9)	0.001
Sleep					0.03
≥8hours	4172 (22.6)	1303 (31.2)	1362 (32.6)	1507 (36.1)
<8hours	14328 (77.4)	4002 (27.9)	5093 (35.6)	5233 (36.5)

^aData are mean (SD) or n (%). MET=metabolic equivalents. *Low physical activity=<600 MET×min per week. Moderate physical activity=600–3000 MET×min per week . High physical activity=>3000 MET×min per week.

In this study, we adjusted for all covariates in the multivariate logistic regression analysis to assess the association between physical activity levels and the risk of chronic diseases. Compared with low physical activity, moderate physical activity showed significantly lower disease risk in 4 out of the 15 chronic diseases (stroke, emotional and mental problems, memory-related diseases, asthma), but an increased risk of stomach disease (OR=1.10, 95% CI:1.01-1.19). For the moderate physical activity group, the largest reduction in disease risk was observed for mental and emotional problems (OR=0.73, 95% CI: 0.60-0.90). Those with high physical activity had a lower risk for 10 diseases (hypertension, dyslipidemia, diabetes, cancer, heart attack, stroke, emotional, nervous, or psychiatric problems, memory-related diseases such as dementia and brain atrophy, Parkinson’s disease, asthma). However, the risk of arthritis and rheumatism increased (OR=1.18, 95% CI: 1.09-1.28). For the high physical activity group, the greatest risk reductions were observed for mental and emotional problems (OR=0.52, 95% CI: 0.42-0.65), stroke (OR=0.54, 95% CI: 0.46-0.63), and Parkinson’s disease (OR=0.60, 95% CI: 0.42-0.85), as shown in Table 2 and Figure 1.

Table 2. Prevalence of chronic diseases in 18,500 middle-aged and elderly people according to physical activity level

	N	Model 1	Model 2	Model 3	Model 4
Hypertension
Low physical activity	2418	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	2723	0.87 (0.81-0.94)	0.95 (0.88-1.02)	0.95 (0.88-1.02)	0.95 (0.88-1.02)
High physical activity	2270	0.61 (0.57-0.66)	0.74 (0.69-0.80)	0.75 (0.69-0.81)	0.75 (0.70-0.81)
Table 2. Prevalence of chronic diseases in 18,500 middle-aged and elderly people according to physical activity level
	N	Model 1	Model 2	Model 3	Model 4
Dyslipidemia
Low physical activity	1490	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	1897	1.06 (0.98-1.15)	1.09 (1.01-1.18)	1.00 (0.92-1.08)	1.00 (0.92-1.08)
High physical activity	1571	0.78 (0.72-0.76)	0.83 (0.76-0.90)	0.84 (0.77-0.91)	0.84 (0.77-0.92)
Diabetes
Low physical activity	864	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	1091	1.05 (0.95-1.16)	1.09 (0.98-1.20)	1.03 (0.93-1.14)	1.04 (0.94-1.15)
High physical activity	789	0.68 (0.68-0.76)	0.75 (0.67-0.83)	0.76 (0.68-0.84)	0.77 (0.69-0.85)
Cancer
Low physical activity	157	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	199	1.05 (0.85-1.30)	1.07 (0.87-1.33)	1.01 (0.82-1.26)	1.03 (0.83-1.28)
High physical activity	116	0.58 (0.45-0.73)	0.61 (0.48-0.79)	0.62 (0.48-0.80)	0.64 (0.50-0.82)
Chronic lung disease
Low physical activity	826	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	905	0.88 (0.79-0.97)	0.95 (0.86-1.05)	0.98 (0.88-1.08)	0.99 (0.89-1.10)
High physical activity	898	0.83 (0.75-0.92)	0.99 (0.89-1.10)	0.99 (0.89-1.10)	1.01 (0.91-1.12)
Liver disease
Low physical activity	366	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	487	1.09 (0.95-1.26)	1.11 (0.97-1.28)	1.07 (0.93-1.23)	1.07 (0.93-1.24)
High physical activity	489	1.05 (0.92-1.21)	1.07 (0.93-1.24)	1.09 (0.94-1.25)	1.10 (0.95-1.27)
Heart disease
Low physical activity	1310	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	1442	0.88 (0.80-0.95)	0.95 (0.87-1.04)	0.91 (0.83-0.99)	0.92 (0.84-1.00)
High physical activity	1107	0.60 (0.55-0.66)	0.73 (0.67-0.80)	0.74 (0.67-0.81)	0.76 (0.69-0.83)
Stroke
Low physical activity	528	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	486	0.74 (0.65-0.84)	0.81 (0.71-0.92)	0.82 (0.72-0.93)	0.83 (0.73-0.95)
High physical activity	297	0.42 (0.36-0.48)	0.52 (0.45-0.61)	0.52 (0.45-0.61)	0.54 (0.46-0.63)
Kidney disease
Low physical activity	557	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	705	1.04 (0.93-1.18)	1.08 (0.96-1.22)	1.05 (0.93-1.19)	1.07 (0.95-1.20)
High physical activity	672	0.94 (0.84-1.06)	1.02 (0.90-1.15)	1.02 (0.90-1.15)	1.05 (0.93-1.18)
Stomach disease
Low physical activity	1646	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	2068	1.04 (0.97-1.13)	1.06 (0.98-1.14)	1.09 (1.00-1.18)	1.10 (1.01-1.19)
High physical activity	2128	1.02 (0.95-1.11)	1.05 (0.97-1.14)	1.05 (0.97-1.14)	1.06 (0.98-1.15)
Emotional and mental issues
Low physical activity	219	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	182	0.67 (0.55-0.82)	0.69 (0.56-0.84)	0.72 (0.59-0.88)	0.73 (0.60-0.90)
High physical activity	134	0.47 (0.38-0.58)	0.50 (0.40-0.62)	0.51 (0.40-0.63)	0.52 (0.42-0.65)
Memory-related diseases
Low physical activity	287	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	258	0.72 (0.60-0.85)	0.84 (0.71-1.00)	0.81 (0.68-0.96)	0.82 (0.69-0.98)
High physical activity	200	0.53 (0.44-0.64)	0.76 (0.62-0.92)	0.76 (0.63-0.92)	0.79 (0.65-0.96)
Parkinson's disease
Low physical activity	100	1.00(Ref)	1.00(Ref)	1.00(Ref)	1.00(Ref)
Moderate physical activity	96	0.78 (0.59-1.04)	0.91 (0.68-1.21)	0.87 (0.66-1.17)	0.88 (0.66-1.18)
High physical activity	52	0.41 (0.29-0.57)	0.57 (0.40-0.81)	0.58 (0.41-0.83)	0.60 (0.42-0.85)
Arthritis or rheumatism
Low physical activity	2085	1	1	1	1
Moderate physical activity	2368	0.90 (0.83-0.97)	0.95 (0.88-1.02)	1.01 (0.94-1.09)	1.01 (0.94-1.09)
High physical activity	2687	1.03 (0.96-1.11)	1.19 (1.10-1.28)	1.18 (1.09-1.28)	1.18 (1.09-1.28)
Asthma
Low physical activity	420	1	1	1	1
Moderate physical activity	387	0.73 (0.64-0.75)	0.81 (0.70-0.93)	0.84 (0.73-0.97)	0.86 (0.74-0.99)
High physical activity	312	0.56 (0.48-0.65)	0.69 (0.59-0.81)	0.69 (0.59-0.81)	0.71 (0.61-0.83)

^aLow physical activity=<600 MET×min per week. Moderate physical activity=600–3000 MET×min per week.

High physical activity=>3000 MET×min per week.

^bModel 1 is the unadjusted association. Model 2 is adjusted for age and gender. Model 3 is additionally adjusted for marital status, education level and area. Model 4 is additionally adjusted sleep,drinking status and smoking status.

Figure 1: Odds ratios and 95% CIs for 15 chronic diseases based on low to moderate to high physical activity levels

^aData adjusted for age, sex, education, sleep, area, and smoking status; drinking status, and marital status.

^bLow physical activity=<600 MET×min per week. Moderate physical activity=600–3000 MET×min per week. High physical activity=>3000 MET×min per week.

To understand how higher levels of physical activity are associated with the risk of chronic disease, we used the moderate physical activity group as a reference in a multivariate logistic regression analysis to compare the differences in 15 chronic diseases with the high physical activity group. The fully adjusted model results showed that the high physical activity group had a further reduced risk for 9 diseases, with the largest decrease observed for cancer (OR=0.62, 95% CI: 0.49-0.79). However, the risk of arthritis and rheumatism also increased (OR=1.17, 95% CI: 1.09-1.26), as shown in Figure 2.

This study conducted a systematic cross-sectional analysis using a nationally representative sample to explore the correlation between physical activity levels and the risk of chronic diseases among middle-aged and elderly populations in urban and rural China. We found that over a quarter of the middle-aged and elderly did not meet the recommended levels of physical activity, consistent with the World Health Organization’s physical activity guidelines report and similar to previous domestic studies in China^[8][11]. Our study also found that the proportion of those engaging in physical activity and meeting the guidelines decreased with age, confirming that this phenomenon also exists in the middle-aged and elderly population^[18]. Additionally, as education levels increased, so did the proportion of people meeting the physical activity guidelines, with rural populations more likely to meet the guidelines than urban and suburban populations. Non-smokers had a higher proportion than smokers, and married individuals had a higher proportion than other groups^[10][19]. These findings are consistent with previous research, indicating a general trend. In our study, women were more likely than men to achieve higher physical activity equivalents. A study using the UK Biobank database found that men spent more time than women in low-level or sedentary physical activity, while women spent more time in moderate-level activity^[20]. Another study from the UK came to the exact opposite conclusion^[21]. Therefore, gender differences in physical activity may be affected by age, region and other conditions. Interestingly, we found that drinkers had higher levels of physical activity than nondrinkers, which may be related to the greater number of drinkers engaged in manual labor. Previous research has shown that people working in manual skills occupations and in the construction industry are more likely to be dependent on alcohol^[22][23].

In recent years, research on physical activity has mainly focused on the association between guideline-compliant physical activity and the risk of certain chronic diseases, as well as the optimal time periods for physical activity and its health-promoting effects^[10][24]. We noted that few studies have examined the impact of different levels of physical activity on the risk of multiple chronic diseases, especially in the middle-aged and elderly population. Our study explored the association between different levels of physical activity and 15 common chronic diseases. Initially, using the low physical activity group as a reference, we found that the odds ratio (OR) and 95% confidence interval (CI) for four chronic diseases were less than 1 for the moderate physical activity group, indicating that moderate physical activity is a protective factor for these four chronic diseases. The high physical activity group was a protective factor for ten chronic diseases. Further, using the moderate physical activity group as a reference, we found that the high physical activity group still had a reduced risk of nine chronic diseases. The results of the PURE study, which included 130,000 people from 17 countries, showed that the more physical activity, the lower the prevalence of hypertension and diabetes. Compared to moderate intensity (600–3000 MET-min/per week), the high physical activity group (> 3000 MET-min/per week) had a lower all-cause mortality rate and a reduced risk of major cardiovascular diseases^[25]. Therefore, although moderate levels of physical activity can bring significant health benefits, higher levels of physical activity bring greater benefits. Hence, governments and organizations should encourage the public to engage in more physical activity to achieve higher levels.

In a systematic review, the authors considered physical activity as an exercise therapy for 26 chronic diseases and summarized the possible biological mechanisms. The mechanisms by which physical activity prevents cancer may include reducing tumor growth through various mechanisms, including (a) vascularization and blood perfusion, (b) immune function, (c) tumor metabolism, and (d) interactions between muscles and cancer. The blood pressure-lowering mechanisms of physical activity include neurohormonal, vascular, and structural adaptations. Anti-allergic effects include reduced vasoconstriction induced by the sympathetic nervous system and lower catecholamine levels in a healthy state. The risk of type 2 diabetes is reduced by increasing insulin sensitivity in trained muscles and muscle glucose uptake induced by muscle contractions. At the cellular level, aerobic exercise has been shown to have various anti-atherosclerotic benefits, including lowering serum triglycerides, increasing high-density lipoprotein, and lowering low-density lipoprotein, thereby reducing the risk of chronic diseases^[26].

In past research, physical activity has been a protective factor for most chronic diseases, but the relationship between some chronic diseases and physical activity has not been unified. A study using data from the Spanish National Health Survey (2017) showed that weekly physical activity levels below 600 MET-min were significantly associated with the risk of 19 chronic diseases, while the lowest prevalence of chronic diseases was observed in people who exercised more than 1200 MET-minutes per week^[27]. However, this trend was not observed in chronic allergies and prostate issues. In our study, we found that after adjusting for relevant covariates, the high physical activity group did not show the expected decrease in the risk of chronic lung diseases, liver diseases, kidney diseases, stomach diseases, and arthritis or rheumatism. Moreover, in model 4, which fully adjusted for confounding factors, we found that compared to the low physical activity group, the moderate physical activity group had an increased risk of stomach diseases, and the high physical activity group had an increased risk of arthritis and rheumatism, suggesting that higher levels of physical activity may be risk factors for these two diseases. Latest cross-sectional study showed that the prevalence of arthritis in middle-aged and elderly patients was related to metabolic syndrome risk factors but not to physical activity^[28]. Another prospective cohort study found that the risk of rheumatoid arthritis continued to decrease with increasing weekly physical activity time, with the highest risk reduction of up to 33% when weekly physical activity time was seven hours or more^[29]. The discrepancy with previous studies may be due to different types of physical activity. Studies have shown that mechanical heavy physical activity may increase the risk of arthritis^[30], and many people in our study were from rural areas, inevitably engaging in heavy physical labor such as farming. Additionally, related physical activity research has shown that exercise can alleviate pain and improve physical function in patients with different types of arthritis^[31], reducing cartilage damage^[32]. Therefore, we still recommend that middle-aged and elderly people with arthritis engage in physical activity under scientific guidance, participating more in swimming and other joint-friendly exercises, as swimming puts less compression on the joints ^[33].

The key advantage of this study is the use of nationally representative data to analyze the association between different levels of physical activity and the risk of 15 common chronic diseases, whereas previous studies focused more on a single chronic disease. However, our study has some limitations worth noting. First, as it relies on self-reported questionnaire data rather than objective measurement tools (such as accelerometers or pedometers), our results may be subject to memory bias and social desirability bias, which could lead to overestimation or underestimation of physical activity levels^[34]. However, in the field of public health, standardized questionnaires are often the preferred method for measuring physical activity due to their low cost and certain reliability and validity^[35]. Second, due to the cross-sectional study design, we cannot determine the causal relationship between physical activity and chronic diseases. Although we observed a significant association between the two, this design limits our interpretation of whether physical activity directly leads to a reduced risk of chronic diseases. Therefore, future longitudinal or interventional studies are needed to further explore this relationship.

Studies have found that both moderate (600–3000 MET-minutes per week) and high physical activity (> 3000 MET-minutes per week) can reduce the risk of some chronic diseases, but high levels of physical activity are protective factors for a broader range of chronic diseases. Compared to those with moderate activity levels, individuals with high levels of physical activity experience a greater reduction in disease risk. However, in China, only one-third of middle-aged and elderly people achieve high levels of physical activity. In the future, the Chinese government and social organizations should take measures to further improve the physical activity levels of middle-aged and elderly people to achieve greater health benefits.

Author Contribution

Yongyu Huang designed the study, performed the experiments, analyzed the data, wrote the manuscript and participated in constructive discussions and analyzed the data. Zuosheng Lu prepared the manuscript. Yongyu Huang helped perform the analyses, participated in constructive discussions and contributed to the conception of the study. All authors read and approved the final manuscript.

Data Availability

The datasets used and analysed during the current study available from the corresponding author on reasonable request.The data used in the study can be obtained from https://charls.pku.edu.cn/Login account：[email protected] password：rnc123...

Christensen K, Doblhammer G, Rau R, et al. Ageing populations: the challenges ahead[J]. The lancet, 2009, 374(9696): 1196–1208.
Partridge L, Deelen J, Slagboom P E. Facing up to the global challenges of ageing[J]. Nature, 2018, 561(7721): 45–56.
Yanan Luo, Binbin Su, Xiaoying Zheng. Trends and Challenges for Population and Health During Population Aging — China, 2015–2050[J]. China CDC Weekly, 2021, 3(28): 593–598. doi: 10.46234/ccdcw2021.158
Barnett K, Mercer S W, Norbury M, et al. Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study[J]. The Lancet, 2012, 380(9836): 37–43.
World Health Organization. Global status report on noncommunicable diseases 2014[M]. World Health Organization, 2014.
Lee I M, Shiroma E J, Lobelo F, et al. Effect of physical inactivity on major non-communicable diseases worldwide: an analysis of burden of disease and life expectancy[J]. The lancet, 2012, 380(9838): 219–229.
Blair S N. Physical inactivity: the biggest public health problem of the 21st century[J]. British journal of sports medicine, 2009, 43(1): 1–2.
Bull F C, Al-Ansari S S, Biddle S, et al. World Health Organization 2020 guidelines on physical activity and sedentary behaviour[J]. British journal of sports medicine, 2020, 54(24): 1451–1462.
Hallal P C, Andersen L B, Bull F C, et al. Global physical activity levels: surveillance progress, pitfalls, and prospects[J]. The lancet, 2012, 380(9838): 247–257.
Bennie, J.A., Pedisic, Z., van Uffelen, J.G.Z. et al. The descriptive epidemiology of total physical activity, muscle-strengthening exercises and sedentary behaviour among Australian adults – results from the National Nutrition and Physical Activity Survey. BMC Public Health 16, 73 (2015). https://doi.org/10.1186/s12889-016-2736-3
Zhu W, Chi A, Sun Y. Physical activity among older Chinese adults living in urban and rural areas: a review[J]. Journal of Sport and Health Science, 2016, 5(3): 281–286.
Westcott W L. Resistance training is medicine: effects of strength training on health[J]. Current sports medicine reports, 2012, 11(4): 209–216.
Churilla J R, Magyari P M, Ford E S, et al. Muscular strengthening activity patterns and metabolic health risk among US adults[J]. Journal of diabetes, 2012, 4(1): 77–84.
Grøntved A, Rimm E B, Willett W C, et al. A prospective study of weight training and risk of type 2 diabetes mellitus in men[J]. Archives of internal medicine, 2012, 172(17): 1306–1312.
Booth F W, Gordon S E, Carlson C J, et al. Waging war on modern chronic diseases: primary prevention through exercise biology[J]. Journal of applied physiology, 2000, 88(2): 774–787.
Wen C P, Wai J P M, Tsai M K, et al. Minimum amount of physical activity for reduced mortality and extended life expectancy: a prospective cohort study[J]. The lancet, 2011, 378(9798): 1244–1253.
Yaohui Zhao, Yisong Hu, James P Smith, John Strauss, Gonghuan Yang, Cohort Profile: The China Health and Retirement Longitudinal Study (CHARLS), International Journal of Epidemiology, Volume 43, Issue 1, February 2014, Pages 61–68, https://doi.org/10.1093/ije/dys203
Moreno-Agostino, D., Daskalopoulou, C., Wu, YT. et al. The impact of physical activity on healthy ageing trajectories: evidence from eight cohort studies. Int J Behav Nutr Phys Act 17, 92 (2020). https://doi.org/10.1186/s12966-020-00995-8
National Fitness Monitoring Center. The 2020 National Fitness Activity Survey Report. https://www.sport.gov.cn/n315/n329/c24335053/content.html.(In Chinese).
Doherty A, Jackson D, Hammerla N, et al. Large scale population assessment of physical activity using wrist worn accelerometers: the UK biobank study[J]. PloS one, 2017, 12(2): e0169649.
Berkemeyer K, Wijndaele K, White T, et al. The descriptive epidemiology of accelerometer-measured physical activity in older adults[J]. International Journal of Behavioral nutrition and Physical activity, 2016, 13: 1–10.
Mandell W, Eaton W W, Anthony J C, et al. Alcoholism and occupations: a review and analysis of 104 occupations[J]. Alcoholism: Clinical and Experimental Research, 1992, 16(4): 734–746.
Cheng W J, Cheng Y, Huang M C, et al. Alcohol dependence, consumption of alcoholic energy drinks and associated work characteristics in the Taiwan working population[J]. Alcohol and alcoholism, 2012, 47(4): 372–379.
Oftedal S, Holliday E G, Reynolds A C, et al. Prevalence, trends, and correlates of joint patterns of aerobic and muscle-strengthening activity and sleep duration: A pooled analysis of 359,019 adults in the National Health Interview Survey 2004–2018[J]. Journal of Physical Activity and Health, 2022, 19(4): 246–255.
Lear S A, Hu W, Rangarajan S, et al. The effect of physical activity on mortality and cardiovascular disease in 130 000 people from 17 high-income, middle-income, and low-income countries: the PURE study[J]. The Lancet, 2017, 390(10113): 2643–2654.
Pedersen B K, Saltin B. Exercise as medicine–evidence for prescribing exercise as therapy in 26 different chronic diseases[J]. Scandinavian journal of medicine & science in sports, 2015, 25: 1–72.
López Sánchez G F, Mendiola Olivares J, Torres Cantero A M. Association between physical activity and 32 chronic conditions among Spanish adults[J]. International Journal of Environmental Research and Public Health, 2022, 19(20): 13596.
Qiu F, Li J, Gan L, et al. Arthritis prevalence is associated with metabolic syndrome risk factors but not with physical activity in middle-aged and older patients-a cross-sectional study[J]. BMC geriatrics, 2024, 24(1): 242.
Liu X, Tedeschi S K, Lu B, et al. Long-term physical activity and subsequent risk for rheumatoid arthritis among women: a prospective cohort study[J]. Arthritis & Rheumatology, 2019, 71(9): 1460–1471.
Griffin T M, Guilak F. The role of mechanical loading in the onset and progression of osteoarthritis[J]. Exercise and sport sciences reviews, 2005, 33(4): 195–200.
Roos E M, Dahlberg L. Positive effects of moderate exercise on glycosaminoglycan content in knee cartilage: a four-month, randomized, controlled trial in patients at risk of osteoarthritis[J]. Arthritis & Rheumatism, 2005, 52(11): 3507–3514.(ruangu)
Gwinnutt J M, Wieczorek M, Cavalli G, et al. Effects of physical exercise and body weight on disease-specific outcomes of people with rheumatic and musculoskeletal diseases (RMDs): systematic reviews and meta-analyses informing the 2021 EULAR recommendations for lifestyle improvements in people with RMDs[J]. RMD open, 2022, 8(1): e002168.(tt)
Lo G H, Ikpeama U E, Driban J B, et al. Evidence that swimming may be protective of knee osteoarthritis: data from the osteoarthritis initiative[J]. PM&R, 2020, 12(6): 529–537.(yy)
Prince S A, Adamo K B, Hamel M E, et al. A comparison of direct versus self-report measures for assessing physical activity in adults: a systematic review[J]. International journal of behavioral nutrition and physical activity, 2008, 5: 1–24.
Pedišić Ž, Bauman A. Accelerometer-based measures in physical activity surveillance: current practices and issues[J]. British journal of sports medicine, 2015, 49(4): 219–223.

No competing interests reported.

Download PDF

Editorial decision: Revision requested
10 Sep, 2024
Reviews received at journal
28 Aug, 2024
Reviewers agreed at journal
28 Aug, 2024
Reviews received at journal
20 Jul, 2024
Reviewers agreed at journal
11 Jul, 2024
Reviewers invited by journal
27 Jun, 2024
Editor assigned by journal
27 Jun, 2024
Editor invited by journal
27 Jun, 2024
Submission checks completed at journal
26 Jun, 2024
First submitted to journal
21 Jun, 2024

You are reading this latest preprint version

Association of Physical Activity with Chronic Diseases: A Cross-sectional Study of 18500 Middle-aged and Elderly Chinese

Status:

Version 1

Abstract

Background

Objective

Methods

Results

Conclusion

Figures

1. Introduction

2. Methods

2.1 Study Sample

2.2 Measures

2.2.1 Chronic Diseases

2.2.2 Physical Activity

2.5 Covariates

2.6 Statistical Analysis

3. Results

4. Discussion

Conclusion

Declarations

Author Contribution

Data Availability

References

Additional Declarations

Status:

Version 1