Exploring the Relationship Between Physical Activity and Multimorbidity: Insights from the CHARLS Database

doi:10.21203/rs.3.rs-5277243/v1

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Exploring the Relationship Between Physical Activity and Multimorbidity: Insights from the CHARLS Database

https://doi.org/10.21203/rs.3.rs-5277243/v1

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Background

Physical activity has been widely recognized for its important role in preventing cardiovascular and other chronic diseases. However, the specific relationship between different levels of physical activity and various chronic diseases, including multimorbidity, remains unclear, which require further investigation.

Methods

This study utilized the China Health and Retirement Longitudinal Study (CHARLS) database to classify physical activity levels based on metabolic equivalents (MET). The analysis focused on the relationship between low, moderate, and high physical activity levels and various chronic diseases, as well as the co-occurrence of multiple diseases. Multivariable logistic regression models were employed to assess the association between different activity levels and the risk of chronic diseases, while stratified analyses explored the impact of demographic factors on these associations. Additionally, a restricted cubic spline (RCS) model was applied to investigate potential nonlinear relationships between total MET and chronic disease risks.

Results

The results showed that compared to low activity levels, moderate and high levels of physical activity significantly reduced the risk of cardiovascular diseases and respiratory diseases, with a nonlinear dose-response relationship. High levels of physical activity also significantly lowered the risk of multimorbidity, particularly the coexistence of three or more chronic diseases (OR = 0.55, 95% CI: 0.47, 0.65, P < 0.01). However, moderate activity levels were associated with increased risks of dyslipidemia and diabetes, while high levels of activity were linked to higher risks of arthritis and kidney diseases. Stratified analyses revealed that demographic factors influenced the association between physical activity and disease risk.

Conclusion

Moderate and high levels of physical activity provide significant protection against cardiovascular and respiratory diseases and effectively reduce the risk of multimorbidity. However, the increased risk of certain metabolic and joint diseases with higher activity levels warrants further attention. Future research should clarify the impact of physical activity on different populations and chronic diseases, with randomized controlled trials needed to verify causality.

Physical activity

Chronic diseases

Multimorbidity

Cardiovascular diseases

Metabolic diseases

Chronic diseases, particularly cardiovascular diseases, metabolic disorders, and respiratory diseases, have become major global public health issues. In 2021, ischemic heart disease, stroke, chronic obstructive pulmonary disease (COPD), diabetes, and chronic kidney disease remained among the leading causes of death globally, with mortality rates of 108.7, 87.4, 45.2, 19.6, and 18.5 per 100,000 population, respectively [1]. Cardiovascular diseases, in particular, continue to be the primary cause of death worldwide, largely associated with risk factors such as high systolic blood pressure, air pollution, smoking, and dietary habits [2]. Additionally, insufficient physical activity has been identified as a major risk factor for the global disease burden, with a summary exposure value (SEVs) of 19.8 (17.0 to 23.0) and 0.7% (0.3–1.1%) of disability-adjusted life years (DALYs) [2].

Extensive research has demonstrated that physical activity not only effectively prevents cardiovascular diseases, metabolic disorders, and respiratory diseases but also improves the health outcomes of patients with these chronic conditions [3]. For example, a study from the United States indicated that engaging in ≥ 30 minutes of moderate-intensity physical activity per day was shown to significantly reduce the incidence of cardiovascular disease, with a risk reduction ranging from 12–26%. Furthermore, performing more than 300 minutes of high-intensity physical activity per week further reduced the risk [4]. In China, regular moderate- or high-intensity physical activity was associated with a 21% reduction in the risk of type 2 diabetes [5]. However, despite the extensive research on the role of physical activity in preventing individual chronic diseases, studies exploring the association between physical activity and multimorbidity remain limited.

Multimorbidity, defined as the coexistence of two or more chronic conditions in a single patient, has emerged as a key focus in public health in recent years. Most existing studies have focused on the risk assessment of individual diseases, with relatively few investigating how different levels of physical activity influence multimorbidity [6]. Patients with multimorbidity often face higher healthcare costs and increased mortality risk, highlighting the public health significance of understanding the impact of physical activity on multimorbidity [7]. While the current literature primarily emphasizes the preventive effects of physical activity on individual diseases, it overlooks the potential benefits of physical activity in the complex context of multimorbidity and the specific dose-response relationships involved.

This study, based on data from the China Health and Retirement Longitudinal Study (CHARLS), aims to investigate the associations between different levels of physical activity and chronic diseases such as heart disease, stroke, hypertension, diabetes, dyslipidemia, and asthma, as well as multimorbidity. To explore potential variations across different populations, stratified analyses were conducted to assess the effects of different levels of physical activity on various demographic groups (e.g., gender, age, marital status, smoking, and drinking habits). Additionally, restricted cubic spline (RCS) models were employed to examine the potential nonlinear associations between metabolic equivalents of physical activity and chronic diseases.

2.1. Study Population

This study was based on data from the China Health and Retirement Longitudinal Study (CHARLS) database. CHARLS collected information on the health, economic, and social status of 17,708 participants from 28 provinces in China between June 2011 and March 2012. CHARLS is a national, long-term longitudinal survey aimed at understanding the health and socioeconomic status of Chinese residents aged 45 and above. The design, research methodology, and data collection procedures have been described in detail in previous literature [8]. This study was approved by the Institutional Review Board of Peking University (Approval Number: IRB00001052-11015), and all participants provided informed consent. All procedures involving human participants complied with the ethical standards of the 1964 Helsinki Declaration.

In this study, we selected individuals aged ≥ 45 years with complete data from the 17,708 participants in 2011. Variables extracted included demographic characteristics (such as ID, gender, age, marital status, place of residence, retirement status), health behaviors (such as smoking, alcohol consumption), chronic disease status (such as hypertension, dyslipidemia, diabetes or hyperglycemia), and physical activity indicators. After excluding samples with missing or unreasonable data, a total of 1,754 eligible participants were included. We also conducted longitudinal analyses using data from five waves in 2011, 2013, 2015, 2018, and 2020, with follow-ups every two to three years, resulting in a total of 15,555 observations from an average of 3,113 participants.

2.2. Assessment of Physical Activity and Chronic Diseases

In this study, participants' physical activity was assessed through self-reported data, covering three main types of activities: vigorous activity, moderate-intensity activity, and light activity/walking. Based on previous studies [9, 10], vigorous activities included weightlifting, digging, and aerobic exercises that require a large amount of physical exertion and cause rapid breathing, with the metabolic equivalent (MET) typically set at 8.0 METs. Moderate-intensity activities, such as cycling, mopping, and practicing Tai Chi, were set at 4.0 METs. Walking activities, including walking for work, household chores, and daily commuting, were assigned 3.3 METs. Each participant was asked to report the frequency and duration of each type of activity per week. The total weekly MET was calculated by multiplying the MET value of each activity by its duration (in minutes per hour) and summing these values based on weekly frequency [11]. According to the total weekly MET, participants were classified into three activity levels: low (MET-minutes/week < 600), moderate (600 ≤ MET-minutes/week ≤ 3000), and high (MET-minutes/week > 3000) [12].

This study evaluated 11 common chronic diseases, including hypertension, dyslipidemia, diabetes or hyperglycemia, chronic lung disease, liver disease, heart disease, stroke, kidney disease, stomach or other digestive diseases, arthritis or rheumatism, and asthma. These chronic disease variables were obtained through participants' self-reports and were updated in each wave based on the follow-up data.

2.3. Covariates

The covariates included in this study were age (specific age), gender (male, female), marital status (married, unmarried/divorced), place of residence (urban, rural), retirement status (retired, not retired), smoking status (smoker, non-smoker), alcohol consumption (drinker, non-drinker), and chronic disease status (with chronic disease, without chronic disease). These covariates were included in the model to control for potential confounding factors and to more accurately analyze the relationship between physical activity, chronic diseases, and multimorbidity.

2.4. Statistical Analysis

Descriptive analyses were first conducted for continuous and categorical variables. Continuous variables were expressed as mean ± standard deviation (SD), and categorical variables were presented as counts (percentages). Independent t-tests were used to compare continuous variables between groups, and Chi-square tests were used for categorical variables. Multivariable logistic regression models were employed to analyze the associations between physical activity levels (low, moderate, high) and both individual chronic diseases and multimorbidity. Models were progressively adjusted to assess the independent effects of physical activity. Model 1 included no covariates, Model 2 adjusted for demographic variables such as age, gender, marital status, and residence, and Model 3 further adjusted for other chronic disease variables. The results were reported using odds ratios (OR), 95% confidence intervals (CI), and P-values. The low activity group was used as the reference to assess the effect of moderate and high activity levels on the risk of individual chronic diseases.

In addition, participants were categorized based on the number of chronic diseases they reported into two-disease, three-disease, four-disease, and five-or-more-disease groups. Multivariable logistic regression was used to analyze the relationship between physical activity levels and multimorbidity, with individuals with a single disease serving as the control group. Odds ratios (OR) and 95% confidence intervals (CI) were calculated for each group.

To explore the nonlinear relationship between total MET-h of physical activity and individual diseases, this study employed the restricted cubic spline (RCS) method, using the 10th, 50th, and 90th percentiles of MET-h as nodes. We reported the overall effect P-value for each model (assessing the overall strength of the association between physical activity and disease) and the nonlinearity P-value (testing for the presence of a nonlinear relationship).

For further investigation of differences among various subgroups, stratified analyses were conducted by gender, age group (< 65 years, ≥ 65 years), marital status (married/unmarried), place of residence (urban/rural), smoking status (smoker/non-smoker), and alcohol consumption (drinker/non-drinker). Within each stratum, we analyzed the associations between physical activity levels and both individual chronic diseases and multimorbidity, and examined the interaction effects between physical activity and both individual chronic diseases and multimorbidity.

All data processing and statistical analyses were conducted using R software, with a significance level set at a two-sided P < 0.05.

Table 1 presents the baseline characteristics of participants from the five survey waves. Participants were surveyed in 2011 (1,754 participants), 2013 (1,454 participants), 2015 (1,848 participants), 2018 (5,239 participants), and 2020 (5,260 participants), with a total of 15,555 person-times participating in the study. Overall, the average age was 63.02 ± 9.84 years, and the gender distribution was relatively balanced, with 51.92% being female and 48.08% being male. Most participants were married (83.09%), and more than 60% (64.56%) resided in rural areas, with only 35.44% living in urban areas. The majority of participants were still not retired (86.55%). Regarding lifestyle, 58.44% of participants were non-smokers, while 41.56% were smokers; 66.26% did not drink alcohol, while 33.74% reported drinking habits. In terms of physical activity, the participants' total metabolic equivalent (Total MET) gradually decreased from 7,722.48 ± 7,338.38 in 2011 to 6,432.14 ± 6,038.67 in 2020, with an average of 6,899.65 ± 6,574.28 over the study period. The participation rate in vigorous activity was 37.96%, moderate-intensity activity was 55.98%, and 81.95% of participants engaged in light activity. 62.04% did not engage in vigorous activities, while 37.96% participated in such activities; 44.02% did not perform moderate-intensity activities, while 55.98% engaged in them; and 81.95% of participants were involved in light activities. In terms of health, the prevalence of heart disease was 16.98%, stroke was 5.34%, and hypertension was 35.74%, while the rate of dyslipidemia was 18.05%. Additionally, asthma (6.07%), lung disease (16.68%), diabetes (10.77%), arthritis (46.78%), gastric diseases (33.65%), kidney disease (11.24%), and liver disease (6.8%) showed varying levels of prevalence across the different survey waves. Overall, participants' health status, lifestyle, and physical activity patterns exhibited certain trends over the five surveys, reflecting associations between these variables and various chronic diseases.

Table 1

Baseline characteristics of participants.
Variable	wave 1 (2011)	wave 2 (2013)	wave 3(2015)	wave 4 (2018)	wave 5 (2020)	Total	P
Observations, n							< 0.01
	1754	1454	1848	5239	5260	15555
Age, mean ± SD							< 0.01
	59.73 ± 9.77	60.34 ± 9.65	61.74 ± 9.42	63.44 ± 9.89	64.89 ± 9.51	63.02 ± 9.84
Total MET, mean ± SD							< 0.01
	7722.48 ± 7338.38	7245.31 ± 7116.07	7564.78 ± 6867.05	6761.69 ± 6508.19	6432.14 ± 6038.67	6899.65 ± 6574.28
Gender, n (%)							0.25
Female	936 (53.36)	786 (54.06)	951 (51.46)	2696 (51.25)	2707 (51.67)	8076 (51.92)
Male	818 (46.64)	668 (45.94)	897 (48.54)	2564 (48.75)	2532 (48.33)	7479 (48.08)
Marital Status, n (%)							< 0.01
Non-married	252 (14.37)	213 (14.65)	262 (14.18)	921 (17.51)	983 (18.76)	2631 (16.91)
Married	1502 (85.63)	1241 (85.35)	1586 (85.82)	4339 (82.49)	4256 (81.24)	12924 (83.09)
Residence, n (%)							0.04
No	580 (33.07)	537 (36.93)	623 (33.71)	1911 (36.33)	1861 (35.52)	5512 (35.44)
Yes	1174 (66.93)	917 (63.07)	1225 (66.29)	3349 (63.67)	3378 (64.48)	10043 (64.56)
Retire, n (%)							< 0.01
No	1561 (89)	1261 (86.73)	1630 (88.2)	4569 (86.86)	4442 (84.79)	13463 (86.55)
Yes	193 (11)	193 (13.27)	218 (11.8)	691 (13.14)	797 (15.21)	2092 (13.45)
Smoke, n (%)							< 0.01
No	1109 (63.23)	887 (61)	1050 (56.82)	3025 (57.51)	3020 (57.64)	9091 (58.44)
Yes	645 (36.77)	567 (39)	798 (43.18)	2235 (42.49)	2219 (42.36)	6464 (41.56)
Drinkl, n (%)							< 0.01
No	1190 (67.84)	977 (67.19)	1215 (65.75)	3553 (67.55)	3371 (64.34)	10306 (66.26)
Yes	564 (32.16)	477 (32.81)	633 (34.25)	1707 (32.45)	1868 (35.66)	5249 (33.74)
physical activity, n (%)
Vigorous-intensity							< 0.01
No	1099 (62.66)	904 (62.17)	1115 (60.34)	3420 (65.02)	3112 (59.4)	9650 (62.04)
Yes	655 (37.34)	550 (37.83)	733 (39.66)	1840 (34.98)	2127 (40.6)	5905 (37.96)
Moderate activity							< 0.01
No	738 (42.08)	605 (41.61)	739 (39.99)	2594 (49.32)	2171 (41.44)	6847 (44.02)
Yes	1016 (57.92)	849 (58.39)	1109 (60.01)	2666 (50.68)	3068 (58.56)	8708 (55.98)
Light-intensity							< 0.01
No	319 (18.19)	217 (14.92)	300 (16.23)	873 (16.6)	1098 (20.96)	2807 (18.05)
Yes	1435 (81.81)	1237 (85.08)	1548 (83.77)	4387 (83.4)	4141 (79.04)	12748 (81.95)
Disease, n (%)
hearte							< 0.01
No	1573 (89.68)	1295 (89.06)	1546 (83.66)	4292 (81.6)	4208 (80.32)	12914 (83.02)
Yes	181 (10.32)	159 (10.94)	302 (16.34)	968 (18.4)	1031 (19.68)	2641 (16.98)
stroke							< 0.01
No	1709 (97.43)	1423 (97.87)	1802 (97.51)	4911 (93.37)	4880 (93.15)	14725 (94.66)
Yes	45 (2.57)	31 (2.13)	46 (2.49)	349 (6.63)	359 (6.85)	830 (5.34)
hibpe							< 0.01
No	1317 (75.09)	1076 (74)	1255 (67.91)	3199 (60.82)	3148 (60.09)	9995 (64.26)
Yes	437 (24.91)	378 (26)	593 (32.09)	2061 (39.18)	2091 (39.91)	5560 (35.74)
dyslipe							< 0.01
No	1620 (92.36)	1297 (89.2)	1554 (84.09)	4264 (81.06)	4013 (76.6)	12748 (81.95)
Yes	134 (7.64)	157 (10.8)	294 (15.91)	996 (18.94)	1226 (23.4)	2807 (18.05)
asthmae							< 0.01
No	1676 (95.55)	1390 (95.6)	1749 (94.64)	4906 (93.27)	4890 (93.34)	14611 (93.93)
Yes	78 (4.45)	64 (4.4)	99 (5.36)	354 (6.73)	349 (6.66)	944 (6.07)
lunge							< 0.01
No	1540 (87.8)	1269 (87.28)	1553 (84.04)	4250 (80.8)	4348 (82.99)	12960 (83.32)
Yes	214 (12.2)	185 (12.72)	295 (15.96)	1010 (19.2)	891 (17.01)	2595 (16.68)
diabe							< 0.01
No	1677 (95.61)	1367 (94.02)	1681 (90.96)	4629 (88)	4526 (86.39)	13880 (89.23)
Yes	77 (4.39)	87 (5.98)	167 (9.04)	631 (12)	713 (13.61)	1675 (10.77)
arthre							< 0.01
No	1022 (58.27)	837 (57.57)	869 (47.02)	2741 (52.11)	2809 (53.62)	8278 (53.22)
Yes	732 (41.73)	617 (42.43)	979 (52.98)	2519 (47.89)	2430 (46.38)	7277 (46.78)
digeste							< 0.01
No	1291 (73.6)	1024 (70.43)	1175 (63.58)	3436 (65.32)	3395 (64.8)	10321 (66.35)
Yes	463 (26.4)	430 (29.57)	673 (36.42)	1824 (34.68)	1844 (35.2)	5234 (33.65)
kidneye							< 0.01
No	1632 (93.04)	1341 (92.23)	1637 (88.58)	4612 (87.68)	4585 (87.52)	13807 (88.76)
Yes	122 (6.96)	113 (7.77)	211 (11.42)	648 (12.32)	654 (12.48)	1748 (11.24)
livere							< 0.01
No	1688 (96.24)	1388 (95.46)	1738 (94.05)	4849 (92.19)	4834 (92.27)	14497 (93.2)
Yes	66 (3.76)	66 (4.54)	110 (5.95)	411 (7.81)	405 (7.73)	1058 (6.8)

Figure 1 and Table S1 presents the associations between different physical activity levels, categorized by metabolic equivalents, and various chronic diseases. In the analysis of Model 3, compared to low physical activity levels, moderate and high physical activity significantly reduced the risk of multiple chronic diseases. Specifically, moderate physical activity significantly reduced the risk of heart disease, stroke, and asthma, with ORs of 0.84 (95% CI: 0.74, 0.97, P = 0.02), 0.67 (95% CI: 0.55, 0.82, P < 0.01), and 0.75 (95% CI: 0.60, 0.93, P = 0.02), respectively. However, moderate physical activity was associated with an increased risk of dyslipidemia and diabetes, with ORs of 1.51 (95% CI: 1.31, 1.74, P < 0.01) and 1.22 (95% CI: 1.03, 1.44, P = 0.02). With high levels of physical activity, the risks of heart disease, stroke, asthma, and hypertension further decreased, with ORs of 0.66 (95% CI: 0.58, 0.75, P < 0.01), 0.50 (95% CI: 0.41, 0.60, P < 0.01), 0.61 (95% CI: 0.51, 0.75, P < 0.01), and 0.79 (95% CI: 0.71, 0.87, P < 0.01), respectively. However, high levels of physical activity were associated with an increased risk of arthritis and kidney disease, with ORs of 1.18 (95% CI: 1.07, 1.30, P < 0.01) and 1.32 (95% CI: 1.13, 1.55, P < 0.01). Overall, moderate and high levels of physical activity significantly reduced the risks of cardiovascular and respiratory diseases, although increased physical activity levels were also associated with higher risks of metabolic and joint-related diseases in some cases.

Figure 2 and Table S2 shows the associations between moderate and high physical activity levels and multimorbidity, with participants having one disease serving as the baseline group. At moderate levels of physical activity, the risks of having two, three, four, and five or more diseases did not significantly differ from the baseline group, with ORs of 1.04 (95% CI: 0.88, 1.22, P = 0.70), 0.97 (95% CI: 0.81, 1.15, P = 0.66), 1.03 (95% CI: 0.84, 1.25, P = 0.84), and 0.85 (95% CI: 0.70, 1.02, P = 0.06), respectively. However, with high levels of physical activity, the risks of having three or more diseases significantly decreased. Specifically, the risks for having three, four, and five or more diseases were 0.82 (95% CI: 0.70, 0.95, P < 0.01), 0.79 (95% CI: 0.66, 0.94, P < 0.01), and 0.55 (95% CI: 0.47, 0.65, P < 0.01), respectively. In summary, high levels of physical activity significantly reduced the risk of multimorbidity, particularly for three or more diseases, while the impact of moderate activity in this area was relatively small.

Figure 3 and Fig. 4 illustrate potential nonlinear dose-response relationships between total physical activity (Total MET) and various chronic diseases. Overall, cardiovascular diseases, including heart disease (hearte), stroke (stroke), and hypertension (hibpe), showed significant decreases with increasing physical activity levels, exhibiting similar nonlinear associations (P overall < 0.01, P nonlinear < 0.01). The increase in Total MET significantly reduced the risk of these diseases, especially at lower activity levels (< 10,000 MET-h), after which the reduction plateaued. For respiratory diseases, asthma (asthmae) and lung disease (lunge) displayed different trends. The increase in Total MET was significantly negatively correlated with asthma risk (P overall < 0.01, P nonlinear = 0.02), indicating that physical activity helps reduce asthma risk. However, for lung disease, the curve did not show a clear dose-response relationship (P overall = 0.23, P nonlinear = 0.62), suggesting a weaker impact of physical activity on lung disease risk. Metabolic diseases, such as dyslipidemia (dyslipe) and diabetes (diabe), also showed different patterns. The relationship between Total MET and dyslipidemia remained relatively stable, with no significant nonlinear effect (P nonlinear = 0.97). In contrast, the risk of diabetes decreased with increased activity levels, showing a significant association (P overall < 0.01, P nonlinear = 0.74), indicating the protective role of physical activity against diabetes. Moreover, the risks of arthritis (arthre) and kidney disease (kidney) increased with high levels of physical activity (arthritis: P overall = 0.09, P nonlinear = 0.34; kidney disease: P overall = 0.19, P nonlinear = 0.26). In summary, there is a significant dose-response relationship between total physical activity and various chronic diseases, particularly for cardiovascular and respiratory diseases, where increased physical activity levels significantly reduced disease risk. However, for some diseases, such as arthritis and kidney disease, higher activity levels were associated with an increased risk.

Table S3-8 present the results of stratified analyses of moderate and high physical activity levels and their associations with various chronic diseases, stratified by gender, age, marital status, place of residence, retiremalet status, smoking, and drinking habits. In these stratified analyses, moderate and high physical activity levels were significantly associated with the risk of various chronic diseases, with the association varying by gender, age, marital status, residence, retiremalet status, smoking, and drinking habits. Overall, the risks of heart disease and stroke were significantly reduced across different strata. For both male and female, high physical activity significantly reduced the risks of heart disease (male, OR = 0.54, 95% CI: 0.45, 0.64; female, OR = 0.64, 95% CI: 0.55, 0.75) and stroke (male, OR = 0.46, 95% CI: 0.36, 0.60; female, OR = 0.40, 95% CI: 0.31, 0.51). Stratified by age, the protective effects of high physical activity on heart disease (OR = 0.53, 95% CI: 0.44, 0.63) and stroke (OR = 0.38, 95% CI: 0.28, 0.51) were particularly pronounced in those under 65 years old. In those aged ≥ 65 years, while the effects were weaker, they still significantly reduced the risks of heart disease (OR = 0.57, 95% CI: 0.49, 0.66) and stroke (OR = 0.41, 95% CI: 0.33, 0.51).

Table 2 and Table S9 present the stratified analysis results of the relationship between moderate and high levels of physical activity and multimorbidity (two, three, four, and five or more diseases) according to gender, age, marital status, residence, retirement status, smoking, and drinking habits. At moderate activity levels, gender, age, marital status, and residence did not show significant differences, but retirement status had a significant effect in the strata with three or more diseases, with the non-retired group having a lower OR (OR = 0.44, 95% CI: 0.28, 0.69, p < 0.01). At high activity levels, the effect of retirement status was even more pronounced, with non-retired individuals having a significantly lower OR than retired ones. Meanwhile, differences in smoking and drinking habits were not significant. For those with high activity levels, the risk of multimorbidity was significantly reduced among unmarried individuals, those under 65 years of age, rural residents, and non-retired individuals, especially in the strata with five or more diseases. For example, the OR for those under 65 was 0.44 (95% CI: 0.35, 0.55, p < 0.01). These results suggest that the relationship between physical activity levels and multimorbidity varies across different demographic characteristics, particularly in the stratified analysis of retirement status and age.

Table 2

Stratified analysis of the effect of high physical activity on multimorbidity (two, three, four, or five or more diseases), categorized by gender, age, marital status, place of residence, retirement status, smoking, and drinking habits.
Character	Multimorbidity Category (OR [95% CI], p-value)
Character	Two Diseases	P_int	Three Diseases	P_int	Four Diseases	P_int	Five or More Diseases	P_int
Gender		0.83		0.37		0.13		0.28
Female	0.93 (0.76, 1.15), 0.52		0.88 (0.70, 1.10), 0.26		0.63 (0.49, 0.83), < 0.01		0.49 (0.38, 0.62), < 0.01
Male	0.94 (0.78, 1.14), 0.54		0.78 (0.63, 0.95), 0.02		0.92 (0.73, 1.18), 0.52		0.6 (0.48, 0.75), < 0.01
Age		0.26		0.28		0.05		0.90
< 65	0.77 (0.63, 0.95), 0.01		0.65 (0.52, 0.80), < 0.01		0.67 (0.53, 0.86), < 0.01		0.44 (0.35, 0.55), < 0.01
≥ 65	1.02 (0.83, 1.24), 0.85		0.89 (0.71, 1.12), 0.33		0.78 (0.59, 1.03), 0.08		0.55 (0.42, 0.71), < 0.01
Marital Status		0.34		0.81		0.30		0.67
Non-married	0.97 (0.83, 1.15), 0.76		0.80 (0.68, 0.96), 0.01		0.76 (0.62, 0.94), 0.01		0.56 (0.46, 0.68), < 0.01
Married	0.76 (0.56, 1.02), 0.07		0.73 (0.52, 1.01), 0.06		0.79 (0.55, 1.13), 0.20		0.46 (0.33, 0.64), < 0.01
Residence		0.66		0.43		0.69		0.38
Urban	0.91 (0.77, 1.09), 0.31		0.83 (0.69, 0.99), 0.05		0.79 (0.64, 0.98), 0.03		0.58 (0.48, 0.72), < 0.01
Rural	0.99 (0.77, 1.27), 0.92		0.76 (0.58, 0.99), 0.04		0.76 (0.55, 1.05), 0.09		0.48 (0.36, 0.64), < 0.01
Retire		0.17		0.06		0.07		0.09
No	0.70 (0.45, 1.08), 0.11		0.55 (0.35, 0.86), 0.01		0.50 (0.31, 0.82), 0.01		0.38 (0.24, 0.59), < 0.01
Yes	0.97 (0.84, 1.13), 0.70		0.86 (0.73, 1.01), 0.06		0.84 (0.69, 1.02), 0.08		0.58 (0.49, 0.70), < 0.01
Smoke		0.90		0.77		0.65		0.41
No	0.97 (0.78, 1.21), 0.80		0.84 (0.66, 1.07), 0.16		0.73 (0.55, 0.98), 0.03		0.49 (0.38, 0.64), < 0.01
Yes	0.92 (0.76, 1.10), 0.36		0.8 (0.65, 0.97), 0.03		0.82 (0.65, 1.03), 0.09		0.59 (0.47, 0.73), < 0.01
Drink		0.76		0.37		0.72		0.77
No	0.93 (0.78, 1.10), 0.39		0.93 (0.69, 1.25), 0.63		0.84 (0.59, 1.20), 0.34		0.62 (0.44, 0.88), 0.01
Yes	0.97 (0.75, 1.26), 0.83		0.78 (0.65, 0.93), 0.01		0.78 (0.63, 0.96), 0.02		0.54 (0.45, 0.65), < 0.01

Our study, based on metabolic equivalent levels, evaluated the association between low, moderate, and high levels of physical activity and various chronic diseases. The results showed that compared to low levels of physical activity, moderate and high levels significantly reduced the risk of multiple chronic diseases, particularly cardiovascular diseases (heart disease, stroke) and respiratory diseases (asthma), where the protective effect was particularly notable. However, in metabolic diseases such as dyslipidemia and diabetes, as well as in joint and kidney-related diseases, increased physical activity levels were associated with higher risks. Additionally, the study revealed the significant role of high levels of physical activity in preventing multimorbidity, especially the coexistence of three or more chronic conditions.

This study found that moderate and high levels of physical activity significantly reduced the risk of cardiovascular and respiratory diseases, particularly in the prevention of heart disease and stroke, showing a nonlinear dose-response relationship. This is consistent with existing literature, which indicates that moderate to high-intensity physical activity provides substantial protective benefits for cardiovascular health [13, 14]. For example, A Danish study found that increased physical activity significantly lowered cardiovascular disease risk in men, with a reduction of more than 40% [13]. Furthermore, a meta-analysis highlighted that regular physical activity can reduce cardiovascular mortality by 27% [14]. Physiologically, the reduction in cardiovascular disease risk may be due to physical activity’s ability to regulate blood pressure, improve lipid metabolism, and enhance endothelial function, thereby reducing atherosclerosis and other cardiovascular events [15, 16]. Physical activity also enhances lung function and reduces airway inflammation, contributing to the prevention of respiratory diseases such as asthma [17].

The study also found that high levels of physical activity significantly reduced the risk of multimorbidity, particularly the coexistence of three or more diseases. Dhalwani et al. reported that higher levels of physical activity can significantly reduce the incidence of multimorbidity in the elderly [18]. These findings suggest that physical activity not only helps reduce the risk of individual diseases but also effectively delays or prevents the coexistence of multiple chronic diseases, especially in the elderly population.

However, this study found that moderate-intensity physical activity was associated with an increased risk of dyslipidemia and diabetes. This may be related to individual metabolic responses to moderate-intensity activity, potentially leading to fluctuations in blood glucose and lipid metabolism [18, 19]. The increased risk of metabolic diseases (such as dyslipidemia and diabetes) may be related to imbalances in energy metabolism or lipid metabolism caused by excessive exercise. Additionally, some studies suggest that certain individuals may experience higher levels of inflammation during moderate-intensity activity, increasing the risk of metabolic disorders [20, 21]. Furthermore, high levels of physical activity were associated with increased risks of arthritis and kidney disease, indicating that excessive physical load might have adverse effects on these systems [22]. For joint and kidney diseases, long-term high-intensity physical activity may impose excessive mechanical stress on the joints or increase the metabolic burden on the kidneys, thereby increasing the risk of these chronic diseases [23].

Stratified analyses further showed that different population groups exhibited varying risks in terms of multimorbidity. For instance, in non-retired individuals, the protective effect of physical activity on multimorbidity was more pronounced, with a significant reduction in the risk of three or more coexisting diseases. These results indicate that physical activity is particularly important for preventing multimorbidity in middle-aged and older adults who are still working, highlighting its public health significance [24]. Regarding the reduction in heart disease and stroke risks, there were some gender differences in the protective effects of physical activity. Women exhibited a greater reduction in heart disease risk with high-intensity activity than men, while the difference in stroke risk reduction between men and women was smaller. Previous studies have shown that women’s hormone levels (such as estrogen) are closely linked to cardiovascular protection, especially before menopause when women have a significantly lower incidence of cardiovascular disease compared to men [25]. Additionally, physical activity can further enhance cardiovascular protection in women by regulating lipid metabolism and the endocrine system [26].

Despite the important findings of this study, several limitations remain. First, physical activity data were primarily self-reported, which may introduce information bias. Second, although multiple potential confounding factors were adjusted for in the analysis, certain factors, such as diet and psychological stress, may still have influenced the results. Moreover, as this study was observational, it cannot establish a causal relationship between physical activity and chronic diseases. Future randomized controlled trials could help clarify the causal pathways more effectively.

This study found that moderate and high levels of physical activity are significantly associated with a reduced risk of multiple chronic diseases, particularly offering strong protective effects against cardiovascular and respiratory diseases. However, the health benefits of physical activity vary according to individual factors such as gender, age, marital status, place of residence, smoking, and alcohol consumption. These findings suggest that future public health policies should consider personalized physical activity recommendations tailored to individual characteristics.

CHARLS: China Health and Retirement Longitudinal Study.

CVDs: cardiovascular diseases

SD: standard deviation

ORs: odds ratios.

95% CIs: 95% confidence intervals.

8.Acknowledgements

The authors would like to thank the China Health and Retirement Longitudinal Study team for providing data.

9.Funding

10.Author Contributions Statement

Authors and Affiliations

Contributions

CM: Conceptualization, Methodology, Visualization, Software, Writing - Original Draft. ZF: Conceptualization, Funding Acquisition, Writing - Review & Editing. ZH: Investigation, Formal Analysis, Resources, Supervision.

Corresponding author

Zhihua Wang

11．Ethics declarations

Ethics approval and consent to participate

This study was performed in line with the principles of the Declaration of Helsinki and all participants signed informed consents before participation. Approval was granted by the Ethical Review Committee at Peking University (IRB00001052-11015). Informed consent was obtained from all individual participants enrolled in the study.

Consent for publication

Not applicable.

Competing interests

The authors declare no competing interests.

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No competing interests reported.

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Exploring the Relationship Between Physical Activity and Multimorbidity: Insights from the CHARLS Database

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1. Introduction

2. Study Methods and Materials

2.1. Study Population

2.2. Assessment of Physical Activity and Chronic Diseases

2.3. Covariates

2.4. Statistical Analysis

3. Results

4. Discussion

Conclusion

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