Physical activity levels and musculoskeletal disease risk in adults aged 45 and above: a cross-sectional study

Abstract

Background

Musculoskeletal disease (MSD) is a major cause of disability among older adults, and understanding the role of physical activity (PA) in preventing these conditions is crucial. This study aimed to explore the association between PA levels and MSD risk among adults aged 45 and above, clarify the dose‒response relationship, and provide tailored guidelines.

Methods

Using data from the China Health and Retirement Longitudinal Study (CHARLS), a cross-sectional analysis was conducted on 15,909 adults aged 45 and over. The study population was divided into MSD (n = 7014) and nMSD (n = 8895) groups based on musculoskeletal health status. PA levels were assessed using the International Physical Activity Questionnaire and categorized into low intensity physical activity (LIPA), moderate vigorous physical activity (MVPA), and vigorous physical activity (VPA). Multivariable logistic regression models and restricted cubic spline regression were used to examine the relationship between PA levels and MSD risk in middle-aged and older adults. Sensitivity analyses and stratified analyses were also performed.

Results

The main outcome measures were musculoskeletal diseases prevalence and PA levels. MVPA and VPA reduced MSD risk by 19% [OR = 0.81, 95% CI (0.72, 0.90), P < 0.001] and 12% [OR = 0.88, 95% CI (0.79, 0.98), P < 0.05], respectively. What’s more, after adjusting for confounding factors, VPA increased risk by 32% [OR = 1.32, 95% CI (1.04, 1.66), P < 0.05]. The relationship was nonlinear, showing a U-shaped pattern with age and hypertension status as significant moderators. The optimal PA energy expenditure was identified as approximately 1500 metabolic equivalents of tasks (METs) per week for adults aged 45–74, 1400 METs per week for those aged 75 and above, and 1600 METs per week for hypertensive adults aged 45 and older.

Conclusions

For adults aged 45 years and older, VPA significantly increases the risk of MSD. Adults aged 45 years and older should adjust their weekly METs based on their age. Additionally, those with hypertension should moderately increase their weekly METs to promote optimal musculoskeletal health.

Introduction

Musculoskeletal disease (MSD) is a leading cause of disability globally, with high prevalence and burden highlighted by Global Burden of Disease studies [1, 2]. According to the World Health Organization (WHO), about 1.71 billion people globally suffer from musculoskeletal conditions [3–5]. In China, MSD is a top cause of disability and often co-occur with other non-communicable diseases, heightening their risk [6–8]. Symptoms such as chronic lower back pain and severe mobility restrictions lead to early retirement, reduced quality of life, and limited social participation. Factors like work duration, poor posture, repetitive movements, and heavy lifting have been linked to MSD prevalence [9–11], but whether other factors exist still requires further research. In addition, age is also a significant factor influencing MSD. With the increasing aging population in China, exploring the factors affecting MSD in middle-aged and older adults holds substantial social value and significance [12].

Physical activity (PA) is key in preventing and alleviating MSD, yet the dose-response relationship between PA levels and MSD remains unclear. Longitudinal studies have suggested moderate vigorous physical activity (MVPA) to vigorous physical activity (VPA) benefited health more than low intensity physical activity (LIPA), with optimal benefits at recommended activity levels [13, 14]. The U.S. Department of Health and Human Services reported additional benefits from engaging in more than 300 min of MVPA per week [15] and the potential increased risk of musculoskeletal injuries associated with higher levels of PA [16]. According to WHO’s 2020 guidelines, adults can exceed 300 min of moderate-intensity aerobic activity or 150 min of vigorous-intensity aerobic activity per week, or combine both, to gain additional health benefits [17]. For middle-aged and older adults, the most effective intensity of PA to reduce the risk of MSD remains to be explored. Identifying the optimal level of PA is essential for mitigating MSD risk.

This study aimed to quantify the dose-response relationship between PA levels and MSD risk in the adults aged 45 years and older to find the optimal PA level that reduces MSD risk. The hypothesis of this study is that both LIPA and VPA do not provide significant benefits to musculoskeletal health in middle-aged and older adults.

Materials and methods

Study population

This study utilized data from the 2015 wave of CHARLS, which included participants aged 45 and older from various regions across China. The inclusion criteria for the present study were as follows: (1) aged 45 years and above and (2) provided informed consent before participation. The exclusion criteria were as follows: (1) missing MSD information (2) missing PA data (3) missing age data (4) age below 45 (5) missing body mass index (BMI) data. Ultimately, 15,909 participants were included in the analysis. Figure 1 outlines the selection process.

Fig. 1.

Flowchart of participant selection. Figure 1 presents the selection process for participants from the CHARLS 2015 cohort, starting with 21,095 individuals and detailing the exclusions that led to the final inclusion of 15,909 participants for the cross-sectional analysis. Abbreviations: CHARLS, China Health and Retirement Longitudinal Study; BMI, Body mass index

The initial analysis involved 21,095 individuals [18]. A total of 15,909 participants aged 45 and above were included, with most in the 45–59 and 60–74 age groups. The sample was fairly balanced by gender, and the majority had a primary education level or below. Key demographic characteristics such as age, gender, cohabitation status, and BMI are presented in Table 1.

Table 1.

Characteristics of the demographic distribution of participants (N=15909) and univariate logistic regression analyses

	nMSD (n = 8895)	MSD (n = 7014)	X2	P
Age/years			624.29	< 0.001
45–59	5064 (56.93%)	2676 (38.15%)
60–74	3373 (37.92%)	3528 (50.30%)
≥ 75	458 (5.15%)	810 (11.55%)
Genders			102.88	< 0.001
Male	4543 (51.07%)	3015 (42.99%)
Female	4352 (48.93%)	3999 (57.01%)
Cohabitation status			174.81	< 0.001
No	914 (10.28%)	1226 (17.48%)
Yes	7981 (89.72%)	5788 (82.52%)
Education			209.71	< 0.001
Primary and below	2716 (60.92%)	3389 (74.88%)
junior high school	1105 (24.79%)	784 (17.32%)
High school and above	637 (14.29%)	353 (7.80%)
BMI/kg/m2			42.43	< 0.001
< 18.5	458 (5.16%)	425 (7.40%)
18.5–24.9	5160 (58.17%)	3327 (57.91%)
25–29.9	2794 (31.50%)	1648 (28.69%)
≥ 30	458 (5.16%)	345 (6.01%)
Smoking			12.97	< 0.001
No	4885 (54.92%)	4052 (57.78%)
Yes	4009 (45.08%)	2961 (42.22%)
Alcohol			72.35	< 0.001
No	5496 (61.86%)	4790 (68.35%)
Yes	3389 (38.14%)	2218 (31.65%)
Sleep/hours			141.81	< 0.001
< 6	4079 (46.94%)	3658 (56.14%)
6–9	4190 (48.22%)	2514 (38.58%)
≥ 9	420 (4.83%)	344 (5.28%)
Hypertension			245.41	< 0.001
No	7302 (82.09%)	5025 (71.64%)
Yes	1593 (17.91%)	1989 (28.36%)
Dyslipidemia			38.00	< 0.001
No	8156 (91.69%)	6228 (88.79%)
Yes	739 (8.31%)	786 (11.21%)
Diabetes/Hyperglycemia			49.36	< 0.001
No	8499 (95.55%)	6521 (92.97%)
Yes	396 (4.45%)	493 (7.03%)
Metabolic syndrome			0.0039	0.95
No	6779 (92.99%)	4398 (93.02%)
Yes	511 (7.01%)	330 (6.98%)
Medicine			1122.78	< 0.001
No	6749 (75.87%)	3527 (50.29%)
Yes	2146 (24.13%)	3487 (49.71%)
Floors			29.56	< 0.001
1	3739 (84.44%)	3111 (88.18%)
2	132 (2.98%)	108 (3.06%)
≥ 3	557 (12.58%)	309 (8.76%)
Physical activity			1.29	0.26
No	4499 (50.58%)	3484 (49.67%)
Yes	4396 (49.42%)	3530 (50.33%)
Physical activity level			15.144	< 0.001
LIPA	1670 (37.99%)	1482 (41.98%)
MVPA	1245 (28.32%)	892 (25.27%)
VPA	1481 (33.69%)	1156 (32.75%)

Abbreviation: LIPA, Low intensity physical activity. MVPA, Moderate vigorous physical activity. VPA, Vigorous physical activity

Variable definition

Assessment of PA

Research suggested that a binary classification of PA may obscure specific U-shaped relationships with outcomes [19]. This study used a three-tier classification: (1) VPA such as carrying heavy loads, aerobic exercises; (2) MVPA such as carrying light objects, brisk walking; (3) LIPA such as walking and leisurely strolling.

PA criteria were based on CHARLS data, recording days per week participants engaged in at least 10 min of PA and the duration of daily activities. The International Physical Activity Questionnaire (IPAQ) is one of the most widely used instruments globally for measuring PA levels in adults, and empirical studies in China have demonstrated its good validity and reliability [20]. CHARLS categorized daily activity durations into five levels (0 min, 10–29 min, 30–119 min, 120–239 min, ≥ 240 min) [21]. Following Ainsworth et al. [22], metabolic equivalents of tasks (METs) were assigned: LIPA 3.3 METs, MVPA 4.0 METs, and VPA 8.0 METs. Weekly PA energy expenditure was calculated as METs × daily activity duration (min) × number of active days per week [23].PA levels were classified per the IPAQ standards: LIPA (< 600 METs per week), MVPA (600–3000 METs per week), and VPA (> 3000 METs per week) [24, 25].

Outcome variable

MSD in this study encompassed conditions affecting bones, muscles, joints, and tendons, including hip fractures, osteoarthritis, rheumatoid arthritis (RA), rheumatic diseases, and sarcopenia. Chronic musculoskeletal pain could be classified as either primary or secondary, with secondary pain stemming from underlying conditions such as osteoarthritis and RA [26, 27]. Sarcopenia, as defined by the 2019 Asian Working Group for Sarcopenia (AWGS) criteria [28], was characterized by grip strength below 28.0 kg for males or 18.0 kg for females, or a time of ≥ 12 s to stand from a chair five times. In this study, participants were classified as having MSD if they reported a physician’s diagnosis of hip fracture, arthritis, rheumatic disease, or were identified as having potential sarcopenia based on the AWGS criteria in the CHARLS dataset.

Covariates

Demographic variables

Demographic variables included gender, age, cohabitation status, and educational level.

Lifestyle variables

Lifestyle variables included smoking, alcohol consumption, BMI, sleep duration, number of floors climbed daily, and medication use. BMI categories were defined as underweight (< 18.5 kg/m²), normal (18.5–24.9 kg/m²), overweight (25–29.9 kg/m²), and obese (≥ 30.0 kg/m²). Sleep duration refered to nightly sleep time. Floor count was based on steps climbed daily. Medication use was noted for conditions such as dyslipidemia, chronic pulmonary disease, liver disease, kidney disease, gastric diseases, heart disease, memory-related diseases, arthritis, or rheumatism.

Chronic health conditions

Chronic health conditions included hypertension, dyslipidemia, diabetes/hyperglycaemia, and metabolic syndrome. Hypertension, diabetes/hyperglycaemia were reported through medical diagnosis. If the participants met three or more of the following criteria: central obesity, hyperglycemia, hypertension, high triglycerides, and low HDL-C—they were diagnosed with metabolic syndrome [29].

Statistical analyses

Data cleaning and statistical analyses were performed using R 4.3.1 and SPSS 27.0. Categorical variables were described as n (%), with group comparisons conducted using Chi-square tests or Chi-square tests for trend. Univariate logistic regression assessed initial associations between exposure factors and MSD. Multivariable logistic regression analysis was used to examine the relationship between PA levels and MSD. To verify the stability of the results, multivariable logistic regression modeling was constructed, with stepwise adjustments for confounding factors: demographic variables, lifestyle variables, and chronic disease conditions. Interaction terms between PA levels and key covariates were tested individually in separate models to assess their significance. For interaction terms that were statistically significant, we conducted stratified analyses to explore these relationships further. Restricted cubic spline (RCS) regression, fitted with six quantiles of PA levels, explored potential non-linear relationships between PA levels and MSD risk. The significance level was set at p = 0.05 for all analyses.

Results

Demographic characteristics and univariate logistic regression analyses

This study included a total of 15,909 participants, with an average age of 60.38 years. There were 7,558 males and 8,351 females. The prevalence of MSD was 44.09%, with 7,014 reported cases. Significant differences were found between participants with and without MSD in terms of age, gender, cohabitation status, education level, BMI, smoking status, alcohol consumption, sleep duration, number of floors climbed, medication use, hypertension, dyslipidemia, diabetes/hyperglycemia, and PA levels (P < 0.001). However, no significant differences were observed regarding metabolic syndrome prevalence or PA engagement between the MSD and non-MSD groups (P > 0.05). Detailed results are presented in Table 1.

Multivariable logistic regression

Multivariable logistic regression revealed that female participants aged ≥ 60 years with hypertension, diabetes/hyperglycaemia, dyslipidemia, and long-term medication use had a higher risk of MSD (P < 0.001). Conversely, those living with a partner, with higher education, a BMI of 18.5–29.9 kg/m², 6–9 h of sleep, and climbing ≥ 3 floors daily showed a lower MSD risk (P < 0.05). Compared to participants engaged in LIPA, those with MVPA and VPA experienced a 19% [OR = 0.81, 95% CI (0.72, 0.90), P < 0.001] and 12% [OR = 0.88, 95% CI (0.79, 0.98), P < 0.05] reduction in MSD risk, respectively. After adjusting for covariates, no significant differences in MSD risk were found for smoking, alcohol consumption, or a BMI ≥ 30 kg/m² (P > 0.05). Detailed results are shown in Table 2.

Table 2.

Results of a multivariable logistic regression of factors influencing MSD

	Statistics n(%)	OR	95%CI	P-value
Age/years
45–59	7740(48.65%)	Ref.
60–74	6901(43.38%)	1.98	1.85, 2.12	< 0.001
≥ 75	1268(7.97%)	3.35	2.96, 3.79	< 0.001
Genders
male	7558(47.51%)	Ref.
female	8351(52.49%)	1.38	1.30, 1.47	< 0.001
Cohabitation status
No	2140(13.45%)	Ref.
Yes	13,769(86.55%)	0.54	0.49, 0.59	< 0.001
Education
primary and below	6105(67.95%)	Ref.
junior high school	1889(21.03%)	0.57	0.51, 0.63	< 0.001
high school and above	990(11.02%)	0.44	0.39, 0.51	< 0.001
BMI/kg/m2
< 18.5	883(6.04%)	Ref.
18.5–24.9	8487(58.07%)	0.69	0.60, 0.80	< 0.001
25–29.9	4442(30.39%)	0.64	0.55, 0.74	< 0.001
≥ 30	803(5.49%)	0.81	0.67, 0.98	0.034
Smoking
No	8937(56.18%)	Ref.
Yes	6970(43.82%)	0.89	0.84, 0.95	< 0.001
Alcohol
No	10,286(64.72%)	Ref.
Yes	5607(35.28%)	0.75	0.70, 0.80	< 0.001
Sleep/hours
< 6	7737(50.88%)	Ref.
6–9	6704(44.09%)	0.67	0.63, 0.72	< 0.001
≥ 9	764(5.02%)	0.91	0.79, 1.06	0.234
Hypertension
No	12,327(77.48%)	Ref.
Yes	3582(22.52%)	1.81	1.68, 1.96	< 0.001
Dyslipidemia
No	14,384(90.41%)	Ref.
Yes	1525(9.59%)	1.39	1.25, 1.55	< 0.001
Diabetes/Hyperglycemia
No	15,020(94.41%)	Ref.
Yes	889(5.59%)	1.62	1.42, 1.86	< 0.001
Medicine
No	10,276(64.59%)	Ref.
Yes	5633(35.41%)	3.11	2.91, 3.33	< 0.001
Floors
1	6850(86.10%)	Ref.
2	240(3.02%)	0.98	0.76, 1.27	0.899
≥ 3	866(10.88%)	0.67	0.58, 0.77	< 0.001
PA level
LIPA	3152(39.77%)	Ref.
MVPA	2137(26.96%)	0.81	0.72, 0.90	< 0.001
VPA	2637(33.27%)	0.88	0.79, 0.98	0.016

Abbreviation: PA, Physical activity. LIPA, Low intensity physical activity. MVPA, Moderate vigorous physical activity. VPA, Vigorous physical activity

Multivariable logistic regression modeling

Using multivariable logistic regression modeling, Model I: was adjusted for demographic variables (e.g., age, gender); Model II: added lifestyle variables (e.g., smoking, alcohol consumption); Model III: incorporated chronic disease conditions (e.g., hypertension, diabetes). Results showed that adults aged 45 and older engaged in VPA had a 32% increased risk of MSD [OR = 1.32, 95% CI (1.05, 1.67), P < 0.05] compared to those engaged in LIPA. This association persisted even after adjusting for chronic disease conditions, with the same group showing a 32% increased risk [OR = 1.32, 95% CI (1.04, 1.66), P < 0.05]. The consistent results across different covariate adjustments highlight the impact of VPA on MSD risk. Full details are provided in Table 3.

Table 3.

Multivariable logistic regression modeling of the effect of PA levels on MSD in adults aged 45 years and older

Exposure	Non-adjustment		Model I		Model II		Model III
	OR(95%CI)	P-value	OR(95%CI)	P-value	OR(95%CI)	P-value	OR(95%CI)	P-value
PA level
LIPA	Ref.		Ref.		Ref.		Ref.
MVPA	0.81 (0.72,0.90)	< 0.001	1.08 (0.93,1.26)	0.319	1.25 (1.00,1.58)	0.054	1.26 (1.00,1.58)	0.052
VPA	0.88(0.79,0.98)	0.016	1.16 (1.00,1.34)	0.055	1.32 (1.05,1.67)	0.018	1.32 (1.04,1.66)	0.021

Model I adjusted for: Age, Gender, Cohabitation status, Education

Model II adjusted for: Age, Gender, Cohabitation status, Education, BMI, Smoking, Alcohol, Medicine, Floors, Sleep

Model III adjusted for: Age, Gender, Cohabitation status, Education, BMI, Smoking, Alcohol, Medicine, Floors, Sleep, Hypertension, Dyslipidaemia, Diabetes/Hyperglycemia

Abbreviation: PA, Physical activity. LIPA, Low intensity physical activity. MVPA, Moderate vigorous physical activity. VPA, Vigorous physical activity

Interaction and stratified analysis of the relationship between PA and MSD

Interaction analysis revealed that age (P = 0.037) and hypertension (P = 0.014) significantly moderated the relationship between PA levels and MSD risk. However, no significant interactions were found for genders, cohabitation status, education, BMI, smoking, alcohol, floors, medicine, dyslipidemia, diabetes/hyperglycaemia (P > 0.05). Results are summarized in Table 4.

Table 4.

Interaction analysis of different variables on PA levels and MSD

Modifier	Min P.terms	P-interaction
Hypertension	< 0.0001	0.014*
Age	< 0.0001	0.037*
Alcohol	< 0.0001	0.075
Diabetes/Hyperglycemia	< 0.0001	0.193
Cohabitation status	< 0.0001	0.204
Medicine	< 0.0001	0.276
BMI	< 0.0001	0.312
Dyslipidemia	< 0.0001	0.448
Education	< 0.0001	0.732
Smoking	0.0001	0.789
Floors	0.0017	0.867
Sleep	< 0.0001	0.949
Genders	< 0.0001	0.965

*P < 0.05 Abbreviations: BMI, Body mass index

In the stratified age analysis, individuals aged 60–74 engaged in VPA showed a 49% higher risk of MSD compared to those engaged in LIPA [OR = 1.49, 95% CI (1.09, 2.05),P < 0.05]. No significant associations were observed for PA levels and MSD risk in the 45–59 or 75 + age groups (P > 0.05). Among those with normal blood pressure, MVPA and VPA were associated with a 38% [OR = 1.38, 95% CI (1.04, 1.81), P < 0.05] and 35% [OR = 1.35, 95% CI (1.03, 1.76), P < 0.05] increased MSD risk, respectively, compared to LIPA. However, PA levels did not significantly impact MSD risk in hypertensive individuals (P > 0.05). These findings, illustrated in Fig. 2, underscore the complex relationship between PA, age, and blood pressure in MSD risk.

Fig. 2.

Stratified analysis of the effect of age and hypertension on PA levels MSD. Abbreviations: PA, Physical activity; LIPA, Low intensity physical activity; MVPA, Moderate vigorous physical activity; VPA, Vigorous physical activity; OR, Odds ratio; CI, Confidence interval; Adjusted for Genders, Cohabitation status, Education, BMI, Smoking, Alcohol, Sleep, Dyslipidemia, Diabetes/Hyperglycemia, Medicine, and Floors

RCS analysis stratified by age and blood pressure status

RCS analysis indicated a nonlinear relationship between PA and MSD risk. Categorizing PA energy expenditure into six quantiles and analyzing age and blood pressure revealed varying effects across age groups.

Adjusting for covariates, RCS analysis showed a nonlinear relationship between PA and MSD risk across 0-6000 METs per week. The 45–59 and 60–74 age groups reached the lowest OR at 1500 METs per week, while those aged 75 and above had their lowest OR at 1400 METs per week. Figure 3 illustrates these interactions between PA and MSD risk.

Fig. 3.

Trends plots of age versus PA energy expenditure and MSD. Adjusted for Genders, Cohabitation status, Education, BMI, Smoking, Alcohol, Sleep, Dyslipidemia, Hypertension, Diabetes/Hyperglycemia, Medicine, and Floors. Abbreviations: OR, Odd ratio; METs: Metabolic equivalents of tasks

After adjusting for covariates, the no hypertension group aged 45 and above reached the lowest OR at 1400 METs per week, while the hypertension group had the lowest OR at 1600 METs per week. Figure 4 illustrates these dynamics between PA and MSD risk by blood pressure status.

Fig. 4.

Trends in blood pressure versus PA energy expenditure and MSD. Adjusted for Age, Genders, Cohabitation status, Education, BMI, Smoking, Alcohol, Sleep, Dyslipidemia, Diabetes/Hyperglycaemia, Medicine, and Floors. Abbreviations: OR, Odd ratio; METs: Metabolic equivalents of tasks

Discussion

The findings of this study generally supported the proposed hypothesis. For adults aged 45 years and older, engaging in VPA was associated with an increased risk of MSD, particularly in certain age groups. Therefore, individuals may consider adjusting their weekly METs according to their age. In addition, those with hypertension might benefit from moderately increasing their weekly METs to promote optimal musculoskeletal health, though further studies are needed to confirm this recommendation. The large, nationally representative sample in this study enhanced the reliability of our findings. This study using restricted cubic spline analysis allowed us to explore nonlinear relationships between PA and MSD, offering deeper insights into the data. The results of this study could serve as a reference guide for preventing MSD among the older population in China, providing a basis for selecting appropriate levels of physical activity.

In this study, data from the 2015 wave of CHARLS included a total of 15,909 participants aged 45 and above, with an MSD prevalence of 44.09%. This rate was slightly higher than the 40.6% reported by Feng Yang et al. among manufacturing workers [9] and the 37.9% reported by Bukhari Putsa et al. among office staff [11]. The MSD prevalence of 44.09% in this study may be attributed to the relatively older age of the participants, which could explain the difference. Studies have demonstrated that even minor changes, such as replacing sedentary time with MVPA, or VPA, can yield significant health benefits, with the greatest impact observed when VPA replaces sedentary behavior [30–32].

Our findings indicated that VPA significantly increases the risk of MSD. Previous research also suggested that both VPA and MVPA are associated with a higher risk of lumbar pain [33]. Bukhari Putsa et al. identified MVPA ≥ 150 min/week and working ≥ 4 h/day as risk factors for MSD [11]. Conversely, frequent transitions from sitting to standing can reduce MSD risk by over 30%. Moderate PA levels have also been shown to reduce non-specific low back pain [34]. However, some studies have also found that MVPA could improve health-related quality of life in older adults with MSD [35]. The observed discrepancies may be attributed to variations in the definitions of MVPA and VPA across different studies. Niederstrasser et al. highlighted inconsistencies in time accounting for MVPA [13]. Additionally, other variables in this study may have influenced the MSD risk factors.

This study identified significant interactions between age (P = 0.037) and hypertension (P = 0.014) with PA levels affecting MSD risk. Subgroup analysis showed that compared to LIPA, MVPA and VPA significantly increased MSD risk in adults aged 60–74. This counterintuitive finding may be attributed to several factors. First, the aging process is associated with decreased muscle mass, bone density, and recovery capacity, potentially amplifying the stress of VPA on the musculoskeletal system [36]. Second, older adults may lack proper exercise techniques or guidance, leading to improper form and increased injury risk [37]. Third, pre-existing health conditions common in this age group, may predispose individuals to MSD when engaging in VPA [38]. Finally, insufficient rest and recovery time between VPA may contribute to overuse injuries in this population [39]. No significant associations were found between PA levels and MSD risk in the 45–59 or 75 + age groups. This may be because the 45–59 group retains better physical function, reducing the differential impact of varying PA intensities on the musculoskeletal system [40, 41]. For individuals aged 75 and older, the impact of PA on health outcomes may differ due to age-related changes in physical function [42]. In this age group, PA’s primary effects might shift towards other physiological systems as physical function declines [43]. Concurrently, underlying health conditions often associated with advanced age can reduce tolerance for VPA. This decreased capacity for VPA may further modulate the relationship between PA intensity and health outcomes in this population [44–46]. Therefore, we suspected that the relationship between PA and MSD was not linear.

Evidence suggests a U-shaped relationship between PA levels and MSD risk in adults aged 45 years and older. In normotensive individuals, MVPA and VPA were associated with increased MSD risk [30–32]. Similarly, Hans Heneweer et al. observed a U-shaped correlation between PA and chronic low back pain [47]. Optimal PA levels appear to vary with age and health status: approximately 1500 METs per week for adults aged 45–74, 1400 METs per week for those 75 and older, and 1600 METs per week for adults aged 45 and older with hypertension. In both age and hypertension groups, the results indicated a similar decreasing trend in OR within the range of 3000–5000 METs. However, these levels significantly exceeded the WHO recommendations. Engaging in such high METs per week may increase the health burden on other systems, making it less feasible. This U-shaped trend suggested that PA exerted a threshold effect on MSD risk, with benefits peaking within a specific range but potentially increasing risk when these levels were exceeded [9, 46, 48–50].

This study explored the varying effects of different PA levels on MSD risk. MVPA can reduce the risk of MSD and improve the general health status of the population, whereas excessive PA heightens the risk of muscle and joint injuries. The findings of this study could serve as a supplement to some extent to the WHO guidelines and help fill gaps in the existing research on MSD. According to the WHO’s 2020 guidelines, adults could engage in more than 300 min of MVPA or 150 min of VPA per week, or an equivalent combination of both, to attain additional health benefits [17]. While PA generally benefits overall health, excessive levels may increase the risk of MSD, especially in certain populations [51–53]. Therefore, appropriate activity selection was crucial for optimizing musculoskeletal health outcomes.To address this, stakeholders should promote a balanced approach to exercise. Healthcare providers and fitness professionals can develop personalized, MVPA plans with regular assessments of joint health.

This study has certain limitations. First, the cross-sectional design of this study limits causal inference between PA levels and MSD. Second, self-reported PA estimates and MSD diagnoses may introduce bias, although the IPAQ is considered reliable [54–57]. Potential recall bias or misreporting could affect data accuracy, highlighting the need for future studies to incorporate objective clinical assessments. Moreover, our study did not differentiate between types of VPA, which may have varying impacts on musculoskeletal health [58]. Finally, the findings may be generalizable to similar populations of adults aged 45 years and older. In the future, more research could be conducted on different age groups.

Conclusions

Based on these findings, adults aged 45 years and older with MSD should generally avoid VPA and opt for MVPA instead. The optimal dosage of weekly METs for improving MSD may vary for different age groups. Individuals aged 45–74 should aim for approximately 1500 METs per week, while those aged 75 and older should target around 1400 METs per week, taking into account their potentially decreased tolerance for higher activity levels. For adults aged 45 years and older with hypertension, slightly higher activity levels of around 1600 METs per week may be the most appropriate threshold. These MSD-specific recommendations are designed to optimize health benefits while minimizing the risk of exacerbating musculoskeletal conditions. It is important to note that these guidelines are tailored for individuals with MSD and may not be applicable to the general population with other diseases.

Abbreviations

CHARLS

China health and retirement longitudinal study

MSD

Musculoskeletal disease

WHO

World Health Organization

PA

Physical activity

LIPA

Low intensity physical activity

MVPA

Moderate vigorous physical activity

VPA

Vigorous physical activity

IPAQ

International physical activity questionnaire

RA

Rheumatoid arthritis

AWGS

Asian Working Group for Sarcopenia

BMI

Body mass index

RCS

Restricted cubic spline

OR

Odds ratio

HRQoL

Health-related quality of life

CLBP

Chronic low back pain

METs

Metabolic equivalents of tasks

Author contributions

ZJP and ZT are co-first authors responsible for the study concept, design, and writing of this manuscript. SLQ, LZX, and LKL were responsible for the study concept, design, oversight, and revision. HCY, LCY, and other team members contributed to the concept, design, and editing of the manuscript. All authors participated in the conduct of the study and have approved the final version of the manuscript. SLQ is the guarantor.

Funding

No funding was received for this study.

Data availability

This study used data from the 2015 wave of the CHARLS. The dataset is publicly available through the CHARLS project website (https://charls.charlsdata.com/pages/Data/2015-charls-wave4/zh-cn.html).

Declarations

Ethics approval and consent to participate

The original CHARLS survey data were approved by the Peking University Institutional Review Board (No. IRB00001052-11015), with all participants having provided informed consent.

Consent for publication

Not Applicable.

Competing interests

The authors declare no competing interests.