Blog

Leon Neal/Getty Images

‘Support they need’

Total Knee Arthroplasty (TKA) is an orthopedic surgical procedure that replaces a damaged human joint with a prosthesis made of artificial materials. TKA aims to alleviate joint pain, instability, deformities, and severe functional impairment caused by various types of arthritis, traumatic arthritis, and non-pyogenic arthritis, thereby reconstructing a joint with near-normal functionality and enhancing joint performance. Recognized as the safest and most effective treatment for alleviating pain and improving limb function in patients with knee arthritis, the utilization of TKA has been on a steady rise, increasing annually by 5% to 17%.¹ However, systematic reviews indicate that only 3 randomized controlled trials (RCTs) with a total sample size of less than 100 participants have evaluated the efficacy of MET in post-TKA rehabilitation. These studies suggest limited evidence regarding the efficacy of MET post-TKA, warranting further investigation into its impact on functional recovery. Despite undergoing TKA, many patients still experience suboptimal functional recovery, which is primarily characterized by persistent postoperative pain, joint stiffness, and limited ability to perform daily activities.^2–4 Conventional rehabilitation methods have not significantly improved postoperative knee joint mobility, possibly due to early postoperative symptoms like pain and swelling.⁴ Hence, with the increasing number of patients undergoing TKA (growing annually by 5–17%), implementing effective early rehabilitation training is crucial for enhancing postoperative knee joint function and improving the quality of life for TKA patients.

Muscle Energy Technique (MET) is a manipulative treatment targeting disorders of the soft tissues, muscles, and skeletal system. It involves precise therapist-controlled direction and force application, coupled with active patient participation, utilizing isometric muscle contractions to mitigate pain, stretch tight muscles and fascia, reduce muscle rigidity, improve local blood circulation, strengthen weak muscles, and increase mobility in stiff joints. Common MET techniques include Reciprocal Inhibition (RI), Contract Relax (CR), Contract Relax Antagonistic Contraction (CRAC), and Annulare Muscle Energy Technique (A-MET), each serving distinct purposes. For instance, RI primarily relaxes agonist muscles through the active contraction of antagonist muscles, thereby increasing joint Range of Motion (ROM) and reducing adhesions in joints, ligaments, and fascia. CR involves isometric contraction of the agonist muscle, causing tendon tissues to stretch, passively elongating and alleviating abnormal collagen tissue adhesions, thereby releasing collagen in tendons and facilitating more freedom in muscle fiber contraction and extension, along with enhanced mobility in the connected fibrous tissue.⁵

MET has gained widespread recognition in global fields of rehabilitation medicine, rehabilitative therapy, and sports rehabilitation. Its primary treatment targets include individuals with sports injuries, post-traumatic injuries from traffic accidents, chronic injury-related pain complications, and patients with limb joint functional impairments. As China’s aging population grows, the incidence of knee arthritis is also increasing and is expected to continue to rise significantly. However, the effectiveness of existing post-TKA rehabilitation methods in China is inadequate for achieving rehabilitation goals. This study challenges traditional rehabilitation approaches by incorporating novel rehabilitation techniques. By comparing the effects of conventional rehabilitation methods (Routine Rehabilitation Treatment, RRT) and Muscle Energy Technique (MET) on knee joint functional rehabilitation in post-TKA patients, the study explores the impact of MET on functional recovery and long-term prognosis in these patients. The findings not only optimize the rehabilitation treatment pathway, providing more effective rehabilitation methods for TKA patients, but also align with the current objectives of “Healthy China 2030”, playing a significant role in improving postoperative functional recovery and the quality of life for patients.

Clinical Data and Methodology

Baseline Data Patient Records

The study selected 80 patients who underwent Total Knee Arthroplasty (TKA) between January 2021 and December 2021 at the Department of Orthopedics, The First Affiliated Hospital of Nanjing Medical University. All procedures were performed by the same team of doctors, utilizing prostheses of the same material provided by the same company, and followed a uniform postoperative treatment protocol.

Sample Size Calculation

Based on ROM data (α=0.05, β=0.2), A sample size of 36 patients per group was required to achieve adequate statistical power, with 40 patients enrolled per group to account for potential dropout. The actual study included 36 patients in the MET group and 42 patients in the RRT group, which was slightly different from the planned 36/group.

Inclusion Criteria

a. Patients diagnosed with osteoarthritis undergoing unilateral Total Knee Arthroplasty; b. Patients undergoing Total Knee Arthroplasty for the first time; c. Patients aged between 50 and 80 years; d. Patients with good compliance, capable of participating in functional exercises; e. Patients willing to participate in the study, agree to follow-up appointments, and provide signed informed consent.

Exclusion Criteria

a. Patients with a history of knee surgery or rheumatoid arthritis; b. Patients with concurrent lower limb acute infection or other joint functional impairments; c. Patients with preoperative coagulation disorders or lower limb Deep Vein Thrombosis (DVT); d. Patients with consciousness, cognitive impairments, or severe mental illness. Elimination Criteria: a. Patients who need to discontinue the treatment plan for personal reasons; b. Patients who experience severe adverse reactions and are unable to adhere to the set treatment plan; c. Patients who withdraw from the clinical study midway; d. Patients who fail to attend scheduled clinic follow-ups, resulting in incomplete follow-up or assessment data.

Research Methodology

Prospective data collection was performed from January 2021 to December 2021, involving 80 patients who met the inclusion and exclusion criteria and underwent TKA at our facility. Block randomization (size=4) via opaque envelopes was employed to allocate patients into two groups. A computerized random number sequence was generated, and the allocation sequence was concealed in opaque, sequentially numbered envelopes. The assessors, who were blinded to group allocation, opened the envelopes according to the patient’s hospital admission order, ensuring a randomized and blinded assignment. The patients, in accordance with their hospital admission order, opened these envelopes and were subsequently randomly assigned to either the Muscle Energy Technique (MET) rehabilitation group or the conventional rehabilitation group.

The conventional rehabilitation treatment methods for the control group are as follows: Preoperative rehabilitation assessment, including the evaluation of muscle strength, Range of Motion (ROM), and circumference of different parts of the operative limb. Development of a rehabilitation plan based on the assessment results, which includes ankle pump dorsiflexion and plantarflexion exercises, muscle strength training, joint ROM exercises, gait training, and Activities of Daily Living (ADL) training. Muscle strength training, encompassing quadriceps muscle strength training, hamstring muscle strength training, and straight leg raise exercises. Each exercise is held for 10 seconds, with 20 repetitions per set and two sets conducted daily. Joint ROM exercises, involving both active and passive knee flexion exercises. Each exercise is held for 5 seconds, with 20 repetitions per set and two sets conducted daily. Gait training, which includes guidance on how to perform body position transitions, stand up from the ground, and walk correctly using a walker, all within the first 24 hours post-surgery. Rehabilitation evaluation, assessing the patient’s muscle strength, joint ROM, gait, walking distance, and ADL status after undergoing the rehabilitation training. The Muscle Energy Technique (MET) intervention rehabilitation treatment methods specifically implemented in the experimental group include:

The MET intervention comprised 2 sessions per day for 6 consecutive days during inpatient rehabilitation, followed by 3 sessions per week for 8 weeks during outpatient rehabilitation. Specifically, the intervention included Post-Isometric Relaxation (PIR) and Post-Facilitation Stretch (PFS) techniques to target the quadriceps muscle. These techniques aim to enhance neuromuscular activation by engaging Type II muscle fibers and improving the extensibility of antagonist muscles, ultimately leading to enhanced knee extension function. The specific implementation is as follows: The patient lies supine with the knee passively flexed to 15 degrees. The patient is instructed to perform isometric contractions of the quadriceps against resistance, followed by relaxation, then the therapist rapidly stretches to the next resistance point. Each quadriceps isometric contraction lasts 10 seconds, performed 10 times per set, with one stretch after completing a set and two sets per day. After each stretch, the knee extension angle is remeasured to maximize the improvement of knee extension limitations. Once the patient’s knee joint can fully extend, they are guided through regular muscle strength training, including isometric contractions of the quadriceps, assessing the strength of medial muscle contractions, ensuring proper contraction and relaxation of key muscles, straight leg raise exercises, active knee flexion exercises, and bedside passive knee flexion exercises. The training starts on the second day post-TKA and continues for six consecutive days until discharge, aiming to achieve full knee extension and mastery of the isometric contraction technique of the quadriceps. Eccentric contraction of the quadriceps combined with conventional straight leg raise training, which further strengthens the muscle strength of the knee extensors, activates the power of the quadriceps, particularly the strength of the vastus medialis muscle. This approach ensures more coordinated contraction within the different muscles of the quadriceps, laying the foundation for the completion of straight leg raise exercises. The specific implementation is as follows: The patient is guided to sit at the edge of the bed, actively extending the knee, then, under the therapist’s control, passively flexing the knee to 60 degrees. The patient exerts force toward the resistance point in the direction of stretch, and the therapist provides single-handed equal resistance (isometric contraction) or uses a sequential progressive resistance. The patient is instructed to extend the knee (isotonic contraction), activating the quadriceps muscle. The therapist rapidly stretches to the next resistance point, the patient extends the knee again, and the therapist observes the contraction response, especially in the position of the vastus medialis muscle, to ensure the quadriceps are in an activated state. Each resistance contraction lasts 5 seconds, followed by one stretch, repeated 10 times per set, with two sets per day. The training begins on the second day post-TKA and continues for six consecutive days until discharge. The goal is to correctly master the force application method of the adductor muscles of the thigh, activate the quadriceps early, and complete the straight leg raise training regimen.

Conventional Range of Motion (ROM) training followed by Reciprocal Inhibition (RI) technique (knee flexor muscle training) effectively stimulates the electrical response rate of knee flexor muscles and induces neuromuscular activation. This method also alleviates pain through reciprocal inhibition and stimulation of mechanoreceptors. The specific implementation is as follows: Before starting the therapy, the patient is seated at the edge of the bed with the thigh snug against the bed edge and the leg dangling. The therapist, facing the patient, stabilizes the operative thigh with one hand and places the other hand under the distal end of the affected calf. The patient is instructed to take deep breaths; if the thigh muscles of the operative limb are tense, they are gently tapped to induce relaxation. The patient is then guided to actively flex the knee for 5 seconds. Simultaneously, the therapist, while seated, places a hand on the patient’s posterior ankle, providing equal resistance against the patient’s hamstring muscle contraction. After maintaining the knee flexion resistance for 5 seconds, the therapist relaxes the pressure. When the patient’s muscles are balanced and coordinated, the therapist continually advances the joint’s range of motion until the highest resistance point of knee flexion is reached. Each resistance contraction lasts 5 seconds, with the joint’s range of motion advanced once. This is performed 10 times per set, with two sets per day. The training begins on the second day post-TKA and continues for six consecutive days until discharge. The objective is to correctly master the hamstring muscle’s force application method, activate the hamstring muscle early, and successfully complete the active knee flexion training regimen.

Observation Indicators

Knee Joint Active Range of Motion

The goniometer is used to measure the active range of motion of the patient’s knee joint, including the flexion angle in the supine and sitting positions, and the extension angle in the sitting position. Each movement is measured twice, and the best value is taken. Measurements are taken at 3 days, 7 days, 1 month, and 3 months, with a planned follow-up at 6 months.

Time Up and Go Test (TUG)

Initially, the patient sits on a chair 45 cm high. Timing starts when the patient stands up, walks 3 meters, turns, returns to the chair, and sits down again. The total time taken for this process is recorded. This scale is simple, easy to operate, and has high reliability and validity, making it suitable for evaluating short-term and long-term rehabilitation effects post-knee arthroplasty.¹ The TUG test is performed and recorded 7 days and 1 month postoperatively.

Hospital for Special Surgery (HSS) Knee Score

The HSS knee scoring system, proposed by the Hospital for Special Surgery in the USA, includes six dimensions: pain, function, range of motion, muscle strength, knee flexion deformity, and knee instability. Each question has five multiple-choice options, with the scores converted to a 100-point scale, where 0 points indicate the most severe symptoms, and 100 points indicate the least severe. The HSS knee scores are recorded 1 month and 3 months postoperatively.

Visual Analogue Scale for Pain (VAS)

A 10 cm ruler is used, divided into ten equal parts, with the ends labeled “0” and “10”, representing no pain and unbearable extreme pain, respectively. The middle part of the scale corresponds to the respective pain levels. Subjects assess their pain level based on their sensation and mark it on the appropriate scale. VAS scoring criteria: 0–2 points are considered “excellent”, 3–5 points “good”, 6–8 points “fair”, and 8–10 points “poor”. VAS pain scores are recorded at 3 days, 7 days, 1 month, and 3 months postoperatively.

Statistical Methods

All clinical research data are recorded in a standardized observation chart created with Microsoft Excel and are managed by a dedicated person responsible for clinical data. Analysis is conducted using SPSS software version 22.0. For comparing quantitative data between two groups, repeated-measures ANOVA was employed to account for time-related effects and group differences. Paired-sample t-tests were utilized to compare pre- and post-treatment outcomes within each group, with a significance level set at P < 0.05. All measurement data should fit a normal or approximately normal distribution and are presented as mean ± standard deviation. The independent samples t-test is used for analyzing the aforementioned indicators, with P < 0.05 considered statistically significant.

Results

MET Significantly Enhances Patients’ Knee Joint ROM

The range of motion (ROM) of the knee joint can reach 135 degrees during flexion and 0 degrees during extension, with internal and external rotation angles being approximately 10 degrees each. Limited joint mobility may be a result of knee injuries or degeneration. When the quadriceps muscles are weak, complete extension of the knee joint is not possible. This study compared the intergroup effects, time effects, and interaction effects on the ROM of the knee joint post-TKA between the two patient groups. As indicated in Table 1, the experimental results were statistically significant (P < 0.001). The results of the repeated-measures ANOVA demonstrated that, over time, the active ROM of the knee joint in the experimental group was significantly superior to that in the control group (P < 0.001). Notably, on the third day post-surgery, the knee joint activity degree of the patients in the experimental group was 19.3% higher than that in the control group. These results suggest that, compared to conventional rehabilitation methods, the rehabilitation treatment utilizing MET can significantly improve the ROM of the knee joint in patients post-TKA (Figure 1).

Figure 1 Comparison results of ROM (Range of Motion) between the two groups of patients.

MET Does Not Improve Patients’ TUG Scores

This study compared the Time Up and Go (TUG) test scores post-TKA between the two patient groups, and the experimental results are presented in Table 2. The data reveal that there was no significant difference in the TUG scores between the two groups one month post-surgery (P > 0.05), indicating no statistical significance. However, the TUG scores three months post-surgery were statistically significant (P < 0.001), with the scores of the Routine Rehabilitation Treatment (RRT) group being higher than those of the MET group. These results suggest that, compared to conventional rehabilitation methods, the MET rehabilitation approach does not enhance patients’ TUG scores.

Table 2 Comparison of Time Taken for the Timed Up and Go (TUG) Test After Intervention Between Two Groups of Patients () Unit: seconds

MET Significantly Improves Patients’ HSS Scores

This study compared the differences in the Hospital for Special Surgery (HSS) scores between the two patient groups, focusing on intergroup effects, time effects, and interaction effects. The scoring results, as shown in Table 3, were statistically significant (P < 0.001). The data indicate that before the commencement of the rehabilitation treatment, the scores of both groups were similar. However, as time progressed, one month post-intervention, the HSS scores of patients in the MET group were 22.2% higher than those in the RRT group; and three months post-intervention, the HSS scores in the MET group still surpassed those in the RRT group by 14.2%. These results demonstrate that, compared to conventional treatment methods, the MET rehabilitation approach can significantly enhance patients’ postoperative HSS scores, and this improvement is sustained over time.

Table 3 Comparison of HSS Scores Before and After Intervention Between Two Groups of Patients () Unit: Points

MET Significantly Reduces Postoperative VAS in Patients

Postoperative pain management is one of the critical factors affecting early mobility in patients undergoing Total Knee Arthroplasty (TKA), and effective postoperative analgesia can reduce hospital stay duration and medical expenses. This study compared the postoperative pain conditions between the two patient groups. The differences in pain scores between the groups, considering intergroup effects, time effects, and interaction effects, were statistically significant (P < 0.001), indicating different therapeutic effects from the two intervention measures. Over time, the condition of knee joint pain in patients in the MET group was better than that in the control group. The differences in pain levels at 3 days, 7 days, one month, and three months post-surgery for both groups are presented in Table 4. The data clearly indicate that patients who underwent rehabilitation with the MET method experienced a significant reduction in knee joint pain perception. On the third day post-surgery, the pain scores in the conventional group were 1.34 times higher than those in the MET group; three months post-surgery, the pain scores in the conventional group were 3.67 times higher than those in the MET group. The results of this study indicate that using the MET method for patient rehabilitation can significantly suppress postoperative pain in patients. Moreover, this suppressive effect becomes more pronounced as the recovery time increases.

Table 4 Comparison of Knee Joint Pain Scores Between Two Groups of Patients () Unit: Points

Discussion

Currently, domestic rehabilitation techniques for Total Knee Arthroplasty (TKA) primarily include isometric muscle contraction, isometric resistance contraction, active and passive Range of Motion (ROM) training, Continuous Passive Motion (CPM) device training for sustained passive activity, gait training, and more.⁶ Singular isometric contraction training, however, may not sufficiently activate muscle strength and lacks coordination during contraction and relaxation. ROM training without resistance can lead to inadequate active knee flexion strength, failing to aid in patient recovery effectively. Additionally, post-TKA patients may exhibit exercise-induced muscle force errors due to kinesiophobia, leading to compensatory movements, making it challenging to control the direction of force application, rendering the exercise ineffective and failing to achieve the true purpose of the exercise. The hallmark of the Muscle Energy Technique (MET) is its active, gentle, and non-impactful nature. During the alternating active contraction and relaxation of muscles, the soft tissues surrounding the joint form a spiraling and unwinding effect. The therapeutic characteristic of this technique necessitates the active participation of the patient, continuous cooperation during treatment, and muscle contractions of specific degrees and directions as set by the operator. Various muscle contraction methods, including isometric, concentric, and eccentric contractions, are often combined in application. This training can improve tissue fluid metabolism, accelerate the synthesis of new cells, promote tissue fiber repair and strengthening, improve joint angles, relax tense muscles and fascia, alleviate pain, balance the muscle strength around the joint, and restore the normal biomechanics of the joint and surrounding tissues.^5,7

TKA is regarded as one of the surgeries with significant effects on severe knee joint diseases, capable of reconstructing knee joint function and alleviating knee pain. However, the incidence of severe postoperative pain after TKA can be as high as 60%, lasting 48–72 hours, and may even develop into chronic pain.⁸ Some patients experience pain, knee joint dysfunction, and muscle weakness after TKA, severely affecting their ability to walk. Postoperative pain can severely impede the recovery of knee joint function and even affect patients’ daily lives. Studies suggest that MET can alleviate patients’ pain through mechanisms such as stimulating mechanoreceptors or reciprocal inhibition, and strength training of the quadriceps can improve the motor function of the knee joint.⁹ This conclusion aligns with the experimental group’s knee joint pain score results, and our experimental findings indicate that MET significantly alleviates patients’ pain with a sustained effect (remaining significant after three months). Starting from the third day post-surgery, each test result showed that the pain scores of patients in the experimental group were significantly lower than those in the control group. Currently, MET is widely used domestically and internationally for soft tissue pain treatment, such as for muscle strains, lateral epicondylitis of the humerus,⁷ periarthritis of the shoulder¹⁰, piriformis syndrome¹¹, and elbow joint stiffness¹². Recently, MET has also been applied for functional rehabilitation training post-ACL reconstruction¹³, post-meniscus repair surgery¹⁴, and more, though the literature is sparse and further exploration in knee joint applications is needed.

This experiment has direct evidence indicating that MET can enhance active knee joint mobility, accelerate knee joint recovery, and alleviate pain. Therefore, compared to conventional rehabilitation treatments, MET is considered to have better therapeutic effects, shorter recovery periods, and higher patient satisfaction. Thus, MET can be regarded as a rehabilitation treatment method for TKA patients worthy of widespread promotion and application.

Data Sharing Statement

The experimental data used to support the findings of this study are available from the corresponding author upon request.

Ethical Approval

Approved by the Ethics Committee of The First Affiliated Hospital of Nanjing Medical University (Approval number: 2022-SR-666), informed consent obtained.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

The work was not funded by any funding.

Disclosure

The authors declared that they have no conflicts of interest regarding this work.

References

1. Mistry JB, Elmallah RDK, Bhave A, et al. Rehabilitative guidelines after total knee arthroplasty: a review. J Knee Surg. 2016;201(03):201–217. doi:10.1055/s-0036-1579670

2. Zuin M, Gentili V, Cervellati C, et al. Viral load difference between symptomatic and asymptomatic COVID-19 patients: systematic review and meta-analysis. Infect Dis Rep. 2021;13(3):645–653. doi:10.3390/idr13030061

3. Thomas E, Cavallaro AR, Mani D, et al. The efficacy of muscle energy techniques in symptomatic and asymptomatic subjects: a systematic review. Chiropr Man Therap. 2019;27(1):1–18. doi:10.1186/s12998-019-0258-7

4. Mascarenhas VV, Rego P, Dantas P, et al. Imaging prevalence of femoroacetabular impingement in symptomatic patients, athletes, and asymptomatic individuals: a systematic review. Eur J Radiol. 2016;85(1):73–95. doi:10.1016/j.ejrad.2015.10.016

5. Sbardella S, La Russa C, Bernetti A, et al. Muscle energy technique in the rehabilitative treatment for acute and chronic non-specific neck pain: a systematic review. Healthcare. 2021;9(6):746. doi:10.3390/healthcare9060746

6. Wang T, Gu H, Gao H. Research on the best evidence application of postoperative rehabilitation exercises for knee arthroplasty patients based on the concept of accelerated recovery. Chin J Mod Nurs. 2020;26(5):595–599.

7. Li J, Zhang J, Hei G, et al. Therapeutic effect observation of muscle intramuscular effect patch combined with muscle energy technique in treating lateral epicondylitis of humerus. Chin J Phys Med Rehabil. 2018;40(3):208–210.

8. Luo G, Wang W, Han X. Current research on postoperative analgesia after total knee arthroplasty. Gansu Med. 2017;36(11):921–923.

9. Wang L, Lv L, Zhang H, et al. Effectiveness of deep hyperthermia combined with dynamic traction in the treatment of knee osteoarthritis. J Clin Rehabil. 2021;35(3):367–377. doi:10.1177/0269215520966702

10. Yu H, Shang J, Yan Z. Clinical efficacy analysis of muscle energy technique combined with muscle intramuscular effect patch in the treatment of periarthritis of shoulder. Liaoning Sports Sci Technol. 2021;43(3):59–62.

11. Zhou Y, Gao H, Qiu J, et al. Observation on the therapeutic effect of needle knife combined with muscle energy technique on piriformis syndrome. Chin Rehabil. 2018;33(3):237–239.

12. Wang X, Xu L. Application of static progressive stretching technique combined with muscle energy technique in the rehabilitation treatment of post-traumatic elbow joint stiffness. Chin Rehabil. 2020;35(8):409–412.

13. Li J, Zhang W, Guan S, et al. Application of muscle energy technique in rehabilitation training of patients after anterior cruciate ligament reconstruction. Nurs Res Mid-Month Ed. 2017;31(8):2925–2927.

14. Ye Z, Li S. The impact of rehabilitation training nursing based on muscle energy technique on functional rehabilitation after meniscus injury surgery. China Med Herald. 2020;17(29):171–174.

Background

Metabolic syndrome (MetS) is a cluster of chronic conditions, including abdominal obesity, hyperglycemia, hypertension, and dyslipidemia,¹ and has become a major global public health concern. The prevalence of MetS varies somewhat depending on the criteria used for the definition. A meta-analysis of global data from 28 million individuals reported a prevalence between 12.5% and 31.4% among adults worldwide.² In China, the prevalence of MetS grew from 8.8% in 1991–1995 to 29.3% in 2011–2015,³ and current estimates are up to 29.2% for men and even 35.4% for women,⁴ coinciding with the steep incline in the prevalence of obesity and diabetes. These high estimates necessitate a greater focus on MetS prevention.

MetS and its components are risk factors for cardiometabolic diseases (CMDs), such as type 2 diabetes (T2D), metabolic dysfunction-associated steatotic liver disease (MASLD), and cardiovascular diseases (CVDs)^5–8 and contribute to an increased mortality risk.^8–10 Comorbidities such as chronic kidney disease (CKD),^11,12 chronic obstructive pulmonary disease (COPD),^13,14 depression,¹⁵ and cognitive impairment¹⁶ are also more prevalent in populations suffering from MetS. Given the enormous public health and economic burden of MetS, it is essential to understand the underlying pathophysiology and natural course of MetS and its consequences.

The etiology and mechanisms of MetS are heterogeneous and remain to be fully elucidated. Its development is influenced by modifiable risk factors, including obesity, sedentariness, and a high-fat diet.^17,18 However, the pathways through which these factors contribute to MetS, and their interactions with genetic predisposition, are still not fully understood. Furthermore, evidence regarding the long-term dynamic changes in risk factors and their impact on the progression and consequences of MetS remains scarce, largely due to the limited availability of prospective cohorts with repeated measurements. Mechanistic studies have suggested that defective adipocyte differentiation and excessive visceral fat accumulation can drive the sustained release of proinflammatory cytokines, which may serve as primary triggers of MetS.^19,20 Against this background, exploring novel biomarkers may provide further opportunities to better characterize the pathophysiology of MetS and its consequences; however, biomarkers suitable for early diagnosis of MetS-related diseases, such as metabolic dysfunction-associated steatohepatitis (MASH), are still lacking. Early identification of high-risk subgroups within populations with MetS is of great value for decreasing the risk of serious complications, underscoring the importance of developing such biomarkers.

Although many prospective cohorts have previously been established, they were largely community-based and focused broadly on the prevention of MetS and relevant metabolic disorders, with limited emphasis on in-depth mechanistic exploration. Several large-scale biobanks, such as UK Biobank in Europe, the China Kadoorie Biobank in China, FinnGen in Finland, and All of Us Research Program in the US, have provided valuable insights into the epidemiology, genetic architecture, and risk factors of chronic diseases, including metabolic disorders. Their success has demonstrated the power of biobank-based resources in advancing disease prevention and precision medicine. However, few of these cohorts have incorporated multiple repeated measurements during follow-up, particularly after the onset of MetS, which restricts the ability to capture dynamic changes over time. Moreover, none of these existing biobanks were specifically designed to investigate MetS as the primary focus, nor did they systematically integrate multi-omics profiling. In addition, dietary behavior is closely related to the occurrence and development of metabolic diseases. Northwest China is characterized by a high-carbohydrate diet and distinct lifestyle patterns, leading to a disease profiling that may differ from that of other regions. To date, no large-scale studies with repeated follow-up assessments and ample biological samples have been established for this specific population. The BMSC cohort was therefore established to fill this critical gap by combining longitudinal repeated measurements with multi-omics data in a uniquely underrepresented population.

To better understand the pathophysiology and natural course of MetS, it is imperative to combine studies with biomarkers and longitudinal data. Thus, we now aim to establish a comprehensive databank and biobank in Northwest China, i.e., the BMSC. This biobank is designed to 1) further understand the pathophysiology and consequences of MetS; 2) explore novel biomarkers to prevent and diagnose MetS and its consequences; and 3) supply useful information for the treatment of MetS and relevant disorders in a longitudinal observational study. By providing longitudinal multi-omics data in a well-characterized population, the BMSC may also inform personalized prevention strategies, enable early risk prediction, and guide targeted interventions for MetS-related conditions. This paper will describe the study design and the protocol of data collection in detail.

Study Population and Design

Study Population

Men and women aged 18 to 75 years are invited to participate in the BMSC study if they have been diagnosed with at least one of the following metabolic disorders: pre-diabetes or T2D, body mass index (BMI) ≥ 24.0 kg/m², hypertension, and/or dyslipidemia. The definitions of these metabolic disorders are based on established international guidelines and were applied uniformly to all participants. Specifically, pre-diabetes is defined as a fasting plasma glucose (PG) level of 5.6–6.9 mmol/L or a 2-hour PG level of 7.8–11.0 mmol/L after an oral glucose tolerance test (OGTT), while diabetes is defined as a fasting PG ≥ 7.0 mmol/L or 2-h PG ≥ 11.1 mmol/L or glycosylated hemoglobin (HbA1c) ≥ 6.5%.²¹ Hypertension is defined as systolic blood pressure ≥ 140 mm Hg, diastolic blood pressure ≥ 90 mm Hg, or the current use of antihypertensive medication, in line with the Chinese Hypertension Guidelines (2020, in Chinese). Dyslipidemia is defined as meeting any of the following criteria: total cholesterol ≥ 5.2 mmol/L, low-density lipoprotein cholesterol (LDL-C) ≥ 3.4 mmol/L, triglycerides ≥ 1.7 mmol/L, or high-density lipoprotein cholesterol (HDL-C) < 1.0 mmol/L.²² Those who have lived locally for a long time (> 1 year) and are willing to accept long-term follow-up are eligible for the BMSC study. Individuals will be excluded if they: 1) are judged to have a life expectancy of less than 5 years; 2) are addicted to drugs or have a history of drug abuse; 3) have viral hepatitis, sexually transmitted diseases such as AIDS and syphilis, and infectious diseases such as active tuberculosis; or 4) have any circumstances that could affect enrollment.

The Institutional Review Board has approved the study at the First Affiliated Hospital of Xi’an Jiaotong University (Xi’an, China). Investigators explain the research aims and protocol to eligible participants in a face-to-face manner, and those who agree to participate in the BMSC study need to sign the informed consent for participation, for storage of biological samples (including blood, urine, stool, and hair), and for obtaining medical records of both baseline and follow-up surveys.

The BMSC study started in August 2021 and is still ongoing. By August 2024, a total of 1589 participants were recruited. Of them, 951 were men (59.8%), and the mean age was 47 years. The characteristics of the participants are presented in Table 1.

Recruitment Strategies

Participants are recruited through two strategies. First, patients presented in the Department of Endocrinology and Metabolism at the First Affiliated Hospital of Xi’an Jiaotong University are evaluated by doctors. The patients who meet the inclusion criteria for the BMSC study are invited and referred to the investigators. Second, participants are recruited through online advertisements and posters posted in public areas.

Study Design

The BMSC study is a prospective observational study of participants aged 18–75 years. After an overnight fast for the baseline survey, eligible participants are invited to the research center or the inpatient ward. Trained researchers conduct the anthropometry according to standard methods. The participants are also asked to complete a structural questionnaire at the first visit to report the basic demographic information, history of disease and medication use, family history of disease, lifestyle and behaviors, physical activity, diet, life events, symptoms of osteoarthritis, sleep, depression, and anxiety. All participants need to provide biological samples according to the study protocol. Professional nurses collect fasted blood, while hair is collected by trained researchers. Urine and stool are collected by patients after the researchers explain the sampling methods. Extensive examinations, such as bioelectrical impedance analysis (BIA), electrocardiogram (ECG), ultrasonography, electromyography (EMG), and fundus photography, are also performed. Echocardiography is performed in a subgroup of patients who need this examination after their physician’s evaluation. The measurements are listed in Table 2.

Table 2 Overview Measurements within the BMSC Study

After successful enrollment, follow-up is conducted every 3 months thereafter until the 5-year mark. Anthropometry is performed at every follow-up, and biological samples are collected every two follow-ups. The changes in metabolic indicators and incidence of CMDs and mortality are followed up for at least 5 years (Figure 1).

Figure 1 The data framework of the Biobank for Metabolic Syndrome Consequences study. ① Height, weight, WC, BP; ② Smoking, drinking, sleeping, and dietary intake; ③ Depression, anxiety; ④ Blood, urine, stool, and hair; ⑤ CMDs, MetS-related complications; ⑥ Bioelectrical impedance analysis, electrocardiogram, and ultrasonography, etc.; ⑦ Glucose, glycosylated hemoglobin, serum lipid profile, renal function, and liver function, etc. Blue text indicates data actively collected by researchers as part of cohort requirements, whereas green text represents clinical data, with specific tests determined primarily by physicians according to patients’ conditions. Yellow and red text denote follow-up time points. Abbreviations: BP, blood pressure; CMD, cardiometabolic disease; MetS, metabolic syndrome; WC, waist circumference.

Data Collection

Questionnaires

The participants are asked to complete the structural questionnaire at the baseline survey, including questions on basic characteristics, history of diseases (including but not limited to diabetes mellitus, hypertension, hyperlipidemia, hyperuricemia, polycystic ovary syndrome, coronary heart disease, stroke, congestive heart failure, peripheral arterial disease, cancer, and thyroid disease), and medication use, disease history of first-degree relatives, lifestyle and behaviors, physical activity, life events, dietary intake, sleep, symptoms of osteoarthritis, and mental health (anxiety and depression). Socioeconomic data, including education level, occupation, household income, and insurance status, are collected through standardized, interviewer-administered questionnaires. Details on the requested information are as follows:

Physical Activity

Participants’ physical activity is evaluated by the Chinese version of the International Physical Activity Questionnaire (IPAQ)-long form, which has been well-validated in the Chinese population.^23,24

Dietary Intake

The participants report a long-term dietary intake through a semi-quantitative food frequency questionnaire (FFQ). Because the FFQ is relatively easy to use, inexpensive, and reflects a long-term dietary intake pattern, it has become the most common tool to evaluate the diet in large epidemiological studies. The FFQ used in the BMSC study covers eighteen categories: grain (11 items); beans (8 items); fresh beans (5 items); root vegetable (5 items); melon vegetable (7 items); leaf vegetable (16 items); fruit (4 items); nut (4 items); animal meat (13 items); poultry (5 items); milk (1 item); eggs (4 items); aquatic products (8 items); fungi foods (5 items); pickle (4 items); alcohol and other beverages (5 items); oil (6 items); condiments (8 items); and nutritious supplementation.

Sleep

Sleep assessment is performed via three questionnaires. Epworth sleepiness scale (ESS) is used to assess daytime sleepiness,²⁵ the Pittsburgh sleep quality index (PSQI) is used to evaluate the quality of sleep,²⁶ and the Berlin questionnaire is used for assessment of the presence of obstructive sleep apnea syndrome.²⁷

Symptoms of Osteoarthritis

Symptoms of osteoarthritis are scaled by the Knee Injury and Osteoarthritis Outcome Score (KOOS), which is developed to assess the patient’s opinion on knee health and related problems and has been validated in the Chinese population.²⁸

Mental Health

Both depression and anxiety are evaluated. The Zung Seff-rating Depression Scale (SDS) is used to determine depressive symptoms via twenty terms. Indicators of anxiety are collected using the Beck Anxiety Inventory (BAI). SDS²⁹ and BAI³⁰ have been well validated in the Chinese population.

Physical Examination

All participants undergo a physical examination at baseline survey, including anthropometry measurement, blood pressure, heart rate, subcutaneous fat, and visceral fat. Height and weight are measured using an ultrasonic height and weight meter (OMRON MEDICAL Beijing Co., Ltd. HNH-318) to the nearest 0.01 m and 0.1 kg, respectively. The waist circumference is the circumference of the midpoint line between the lowest point of the rib and the upper margin of the iliac crest (the narrowest point of the waist) measured at the end of exhalation and before the beginning of inhalation using a tape measure, with a precision of 0.1 cm. Hip circumference is measured as the maximum circumference of the buttocks. Abdomen circumference is measured at the iliac crest point at the end of exhalation but before the beginning of inhalation. The biceps circumference is measured at the upper 1/3 of the right arm, while the thigh circumference is measured at the upper 1/3 of the right thigh. An electronic blood pressure monitor (OMRON MEDICAL Beijing Co., Ltd. HEM-7121) is used to measure the blood pressure and heart rate, after the participants are asked to be quiet and rest for at least 5 minutes. The subcutaneous and visceral fat area is measured using a visceral fat detector (OMRON MEDICAL Beijing Co., Ltd. 3 DUALSCAN, HDS-2000), with a unit of cm².

Advanced examinations such as BIA, ECG, and ultrasonography are also performed. The body composition, including body fat (body fat percentage), muscle mass (skeletal muscle content), and visceral fat (visceral fat grade), is measured using the direct segmental multifrequency BIA method DSM-BIA (InBody H20) to the nearest 0.1 kg. A resting 12-lead ECG (Mortara Eli-350) is recorded and archived electronically at baseline survey. Carotid intima-media thickness is measured by color Doppler ultrasonography of the neck vessels. Peripheral arterial disease is determined with the help of color Doppler ultrasonography of lower limbs. Fundus photography of both eyes is performed to determine the presence of diabetic retinopathy. Surface EMG assessment is only performed to assist in the diagnosis of diabetic peripheral neuropathy. Echocardiography is performed in a subset of individuals needing examinations after their physicians’ evaluation.

Fasting Blood Sampling

A total of 20 mL peripheral venous blood is taken after an overnight fast of at least 8 hours, and used for the collection of serum, EDTA-plasma, RNA, and DNA, all stored in a −80°C freezer for future multi-omics analyses. Separate blood samples are taken for immediate tests, such as glucose, HbA1c levels, serum lipid profile (total cholesterol, triglycerides, HDL-C, LDL-C, apolipoprotein A1, total apolipoprotein B, and apolipoprotein E), indicators of liver function (aspartate transaminase, alanine transaminase, total protein, albumin, globulin, total bile acids, alkaline phosphatase, γ-glutamyltranspeptidase, total bilirubin, direct bilirubin, and indirect bilirubin), indicators of renal function (urea, cystatin C, uric acid, creatinine, glycated albumin, and retinol-binding protein), indicators of thyroid function (serum thyroid stimulating hormone, total and free thyroxine, total and free triiodothyronine), and blood cell count, mean red blood cell (RBC) volume, platelet concentration, platelet distribution width, mean platelet volume, and high-sensitivity C-reactive protein (CRP). Insulin release test, C-peptide release test, and serum insulin and C-peptide measurements are only performed in a subset of individuals who need these examinations according to the disease.

Urine Sampling

A tube of 15 mL urine is obtained from all participants at enrollment. The participants are asked to fast for at least 8 hours before the collection of midstream urine. Collected urine samples are stored in a −80°C freezer for future analyses. The urine samples used for routine analyses are separately collected. Creatinine and urinary microalbumin are tested using standard methods at the clinical laboratory.

Stool Sampling

After urination, two tubes of fecal samples are collected. After receiving the fecal samples, the researchers put them into liquid nitrogen for rapid freezing and then store them at −80°C freezer for future analyses.

Hair Sampling

Using blunt curved scissors, the researchers collect 30 to 50 hairs from the occipital bone, as close as possible to the root of the hair, taking 3 cm. The hair sample is rolled in tinfoil and stored at room temperature.

Ascertainment of Incident Diseases During Follow-Up

The primary endpoints of the BMSC study include major CMDs, such as CVDs (coronary heart disease, stroke, myocardial infarction, and congestive heart failure), MASLD, mortality, and other MetS-related diseases (T2D, depression, and osteoarthritis). Endpoints are ascertained through three complementary sources: (1) standardized questionnaires administered annually, including self-reported physician diagnoses; (2) biochemical indicators collected every six months, with prespecified thresholds (e.g., fasting glucose, HbA1c, lipid profile, liver function tests) used to define disease onset or progression; and (3) electronic medical records from the First Affiliated Hospital of Xi’an Jiatong University, linked and extracted two years after enrollment and subsequently at 1-year intervals. Diagnoses from medical records will be verified using ICD-10 codes and clinical criteria, and, where necessary, adjudicated by an independent panel of physicians to ensure accuracy. This multi-source and standardized approach is designed to enhance both the validity and reliability of endpoint determination, thereby improving the robustness of event-based analysis.

Biological Sample Processing Methods

As mentioned above, common clinical biomarkers, such as blood type and counts, glucose, HbA1c, lipids, indicators of liver function, kidney function, and thyroid function, are tested using automatic equipment in the hospital laboratory (Table 3). Other advanced assays are performed as follows:

Table 3 Laboratory Analyses at Baseline within the BMSC Study

Blood samples are used for genomics according to the standard protocols. After DNA is extracted from white cells, the samples are delivered to a professional sequencing company for high-throughput genotyping after strict quality control such as gel electrophoresis, NanoDrop, and Bioanalyzer (Infinium CoreExome-24 BeadChip is intended to be selected).

Plasma concentrations of cholesterol and its precursors, including desmosterol, are measured using rapid gas chromatogramtography-mass spectrometry (GC-MS). Plasma inflammatory factors such as ICAM-1, TNF-α, IL-6, and TGF-β are assessed by ELISA kits.

Fecal samples are mainly intended for microbiome analysis, according to established protocols. Genomic DNA is extracted from fecal samples using the QIAamp DNA Stool Mini Kit (Qiagen, Germany) according to the manufacturer’s instructions and then used for 16S rRNA gene sequencing.

Plasma and fecal samples are also intended for assessing metabolomics and lipidomics. Levels of steroid hormones in hair samples are determined through liquid chromatography-mass spectrometry (LC-MS).

Quality Control

Several strategies are conducted to ensure the quality of the BMSC study (Figure 2). First, the BMSC study is led by a professional data collection team, and every data collector must have attended a professional training program. Additionally, a handbook for data collection has been developed to facilitate the daily work. Second, both artificial and system queries are performed to ensure the quality of the investigation and collection of anthropometry data. Third, the biological sample should be sent to the Biobank as soon as possible to ensure the quality of the samples after they have been withdrawn. Last, in the laboratory where the analysis of samples takes place, researchers should operate with strict experimental methods to ensure the validity of experimental data.

Figure 2 The process of data collection and quality control of the Biobank for Metabolic Syndrome Consequences study. The blue texts and arrows represent the data and sample collection process, while the red color indicates the quality control process during data collection.

Statistical Analysis

The BMSC study encompasses multiple research aims and involves a wide range of exposures and outcomes. To ensure adequate statistical power, we performed a sample size estimation using T2D as the exposure and stroke as the outcome. Based on results from the Jinchang Cohort Study in Gansu Province, the incidence of stroke was estimated to be 5.26% among participants with T2D and 1.71% among those without T2D. Assuming a two-sided significance level (α) of 0.05, statistical power (1-β) of 80%, and a 1:1 matching ratio, the required sample size to detect a significant difference between groups was calculated to be 840. To account for potential loss to follow-up and withdrawal during long-term observation, we increased the sample size by 20%, resulting in 1008 participants. Considering that the study aims to investigate multiple outcomes beyond stroke, we determined that a baseline sample size of approximately 2000 participants would be appropriate.

Appropriate statistical methods will be used to analyze and present the basic characteristics. Regression models (e.g., logistic regression model) will be fitted to analyze the cross-sectional associations between influence factors and metabolic disorders, while potential prospective associations between endpoint diseases and influence factors will be assessed by linear mixed-effects models combined with Cox regression. Since BMSC is an open, prospective cohort, the baseline dates differ among participants based on their recruitment date. The variation in follow-up duration is fully acknowledged and will be addressed through time-to-event analysis. Most core covariates (age, sex, anthropometrics) are fully recorded at baseline. For questionnaire-derived data (e.g., lifestyle, socioeconomic status), missing covariates will be handled via multiple imputation where appropriate.

For microbiome measurements, the Kruskal–Wallis test or regression analysis will be conducted to compare the α-diversity index, such as the Shannon index, Observed feature, and the Gini-Simpson Index. Species-level analysis will be performed using MaAsLin or multiple regression.

For metabolomics and lipidomics data, the least absolute shrinkage and selection operator and principal component analysis will be used to reduce the dimensionality of the data. Correlation analysis, regression analysis, and machine learning methods (e.g., Light Gradient Boosting Machine) will be applied to identify associations between omics features and clinical outcomes. To integrate multi-omics datasets (genomics, metabolomics, microbiome) with epidemiological and clinical variables, we will employ data fusion approaches such as multi-view learning and network-based methods, enabling the identification of cross-omics biomarkers and molecular signatures. Pathway enrichment analysis will further aid in interpreting the biological relevance. This integrative framework is expected to support biomarker discovery, risk prediction, and provide mechanistic insights into the pathophysiology of MetS and its consequences.

Basic Characteristics of the Participants at Recruitment

Up to August 2024, a total of 1589 participants have been included in the BMSC study. Of them, 951 are men (59.8%) and 1420 (89.4%) are enrolled in the hospital. The age of participants ranged from 18 to 74 [mean = 47, standard deviation (SD): 14]. The average BMI was 27.0 kg/m² (SD: 5.6) for men and 29.2 kg/m² (SD: 6.9) for women. The total rate of biological sample collection was at least 78.5%. Hyperglycemia was the most prevalent metabolic disorder in the participants (80.9%). 37.6% of participants were obese, and the prevalence of MetS was 65.8%. Among the study population, the proportions of participants with 0, 1, 2, 3, 4, and 5 MetS components were 0.8%, 11.6%, 21.8%, 26.8%, 25.6%, and 13.5%, respectively (Table 1). Table 4 presents the distribution of several cardiometabolic biomarkers. Fasting plasma glucose, HbA1c, TyG, triglycerides, systolic blood pressure, diastolic blood pressure, and serum uric acid were higher in males, while total cholesterol, HDL-C, and LDL-C were higher in females (all P values ≤ 0.026).

Table 4 Cardiometabolic Biomarkers of Study Participants in the BMSC Study

Strengths and Limitations

The BMSC study is an ongoing prospective observational study of approximately 2000 adults with metabolic disorders. It has several strengths. First, the study’s deep phenotyping yields profiles of individual characteristics in many dimensions, including anthropometry, lifestyle factors, psychosocial characteristics, medical records, clinical biomarkers, and multi-omics profiles. Second, strict measures adopted during the project ensure high-quality data collection. Third, the standardized Biobank procedure guarantees the quality of biological samples, which is one of the distinctive strengths of the BMSC study. Fourth, repeated measurements and biological sampling across multiple time points make it possible to assess the dynamic change of influencing factors and biomarkers. However, some limitations should be acknowledged. First, participants in the BMSC study are recruited in Northwest China; hence, extrapolation of results to other regions or countries requires caution. Second, only participants with metabolic disorders meet the inclusion criteria of the BMSC study, which precludes the recruitment of healthy participants as controls. The absence of a control group limits the ability to determine whether the observed alterations are disease-specific or reflect normal variations, thereby reducing the capacity to infer causality and restricting the generalizability of our findings to broader populations. To address this limitation, we have initiated the recruitment of metabolically healthy individuals from the Department of Health Medicine of our hospital, who may serve as an appropriate control group in future analyses. This will allow us to better delineate disease-specific alterations and strengthen the robustness of our conclusions. Third, while observational cohort designs inherently limit causal inference, the BMSC study aims to elucidate potential mechanistic pathways and identify clinically relevant associations, rather than assert definitive causal relationships. In addition, the current sample size is modest compared to national mega-cohorts in China. However, the BMSC study especially focuses on deeply phenotyped, metabolically characterized individuals, with integrated multi-omics datasets and long-term biobanked biospecimens. Finally, several practical challenges should also be acknowledged. First, maintaining participant retention over a 5-year follow-up may be difficult, and loss to follow-up could reduce statistical power. Second, the management and analysis of high-dimensional multi-omics data are complex and will require rigorous bioinformatics pipelines and quality control procedures. Third, as the study is conducted in a single regional population, the generalizability of findings to other geographic or ethnic groups may be limited. These challenges will be carefully considered in the implementation and interpretation of the BMSC study.

Prospective Contributions of the BMSC Study

Although no study results are yet available, the BMSC protocol has several distinctive features that may provide novel insights into the etiology and progression of MetS and related chronic diseases. The repeated biospecimen collection combined with multi-omics profiling and clinical data enables comprehensive characterization of biological pathways. Moreover, the relatively high-frequency follow-up (every 3 months) enhances the granularity of longitudinal assessments, which is uncommon in large cohort studies. Together, these features make the BMSC study a valuable resource with strong potential to contribute to precision medicine research and to inform prevention and intervention strategies for metabolic and cardiovascular diseases. Beyond scientific discovery, the BMSC study may also have important implications for public health and clinical practice. For example, longitudinal biomarker profiling could help to refine risk stratification tools for MetS and related CMDs, thereby informing clinical guidelines for earlier detection and more personalized prevention strategies. In addition, the integration of multi-omics data with lifestyle and clinical outcomes may identify novel therapeutic targets, which could ultimately support the development of precision interventions for metabolic disorders. These potential applications highlight the translational value of the BMSC study beyond research contexts.

Conclusion

The BMSC study provides a new framework for a prospective MetS biobank with multi-dimensional information in an underrepresented population. This resource is expected to contribute to disease prediction, early diagnosis, and mechanistic understanding, thereby informing precision medicine and public health strategies. While we recognize practical challenges such as long-term participant retention, management of complex data, and limited generalizability beyond the study region, these can be addressed through rigorous methodology, robust infrastructure, and collaboration efforts. Continued stakeholder support and open opportunities for data sharing and collaboration will be critical to maximizing the value of the BMSC and ensuring its long-term impact.

Abbreviations

BAI, Beck Anxiety Inventory; BIA, Bioelectrical impedance analysis; BMSC, Biobank for Metabolic Syndrome Consequences; CKD, Chronic kidney disease; CMD, Cardiometabolic diseases; COPD, Chronic obstructive pulmonary disease; CRP, C-reactive protein; CVD, Cardiovascular disease; ECG, Electrocardiogram; EMG, Electromyography; ESS, Epworth sleepiness scale; FFQ, Food frequency questionnaire; HbA1c, Glycosylated hemoglobin; HDL-C, High-density lipoprotein cholesterol; IPAQ, International Physical Activity Questionnaire; KOOS, Knee Injury and Osteoarthritis Outcome Score; LDL-C, Low-density lipoprotein cholesterol; MASH, Metabolic dysfunction-associated steatohepatitis; MASLD, Metabolic dysfunction-associated steatotic liver disease; MetS, Metabolic syndrome; OGTT, Oral glucose tolerance test; PSQI, Pittsburgh sleep quality index; RBC, Red blood cell; SDS, Seff-rating Depression Scale; T2D, Type 2 diabetes.

Data Sharing Statement

All data used in this study are from the BMSC study and are available from the corresponding author (Prof. Yanan Wang) upon reasonable request.

Ethical Approval and Consent to Participate

This is an observational study. The Institutional Review Board of the First Affiliated Hospital of Xi’an Jiaotong University (Xi’an, China) has approved the study, and the institutional review board (IRB) reference number is No.XJTU1AF2021LSK-193. All participants provided informed consent. The study was conducted in accordance with the Declaration of Helsinki.

Acknowledgments

The BMSC study is supported by the Department of Endocrinology and Metabolism, Department of Hepatological Survey, and Biobank of First Affiliated Hospital of Xi’an Jiaotong University. We thank all contributing individuals who participate in the BMSC study. We also express our gratitude to all doctors who invite eligible participants.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Funding

The study is sponsored by the National Science and Technology Major Project of the Ministry of Science and Technology of China (No. 2024ZD0531702), the Fundamental Research Funds for the Central Universities (No. xtr052023011), the Plan for Strengthening Basic Disciplines of Xi’an (No. 21YXYJ0111), the China Postdoctoral Science Foundation (2024M762615), the National Natural Science Foundation of China (82170876), and the Key Research and Development Program of Shaanxi Province (No. 2025SF-YBXM-367).

Disclosure

The authors report no conflicts of interest in this work.

References

1. Eckel RH, Alberti KG, Grundy SM, Zimmet PZ. The metabolic syndrome. Lancet. 2010;375:181–183. doi:10.1016/S0140-6736(09)61794-3

2. Noubiap JJ, Nansseu JR, Lontchi-Yimagou E, et al. Geographic distribution of metabolic syndrome and its components in the general adult population: a meta-analysis of global data from 28 million individuals. Diabet Res Clin Pract. 2022;188:109924. doi:10.1016/j.diabres.2022.109924

3. Huang J, Huang AL, Withers M, et al. Prevalence of metabolic syndrome in Chinese women and men: a systematic review and meta-analysis of data from 734511 individuals. Lancet. 2018;392:S14.

4. Huang Y, Zhang L, Wang Z, et al. The prevalence and characteristics of metabolic syndrome according to different definitions in China: a nationwide cross-sectional study, 2012–2015. BMC Public Health. 2022;22:1869. doi:10.1186/s12889-022-14263-w

5. Wilson PW, D’Agostino RB, Parise H, Sullivan L, Meigs JB. Metabolic syndrome as a precursor of cardiovascular disease and type 2 diabetes mellitus. Circulation. 2005;112:3066–3072. doi:10.1161/CIRCULATIONAHA.105.539528

6. Shin JA, Lee JH, Lim SY, et al. Metabolic syndrome as a predictor of type 2 diabetes, and its clinical interpretations and usefulness. J Diabetes Investig. 2013;4:334–343. doi:10.1111/jdi.12075

7. Paschos P, Paletas K. Non alcoholic fatty liver disease and metabolic syndrome. Hippokratia. 2009;13:9–19.

8. Pammer LM, Lamina C, Schultheiss UT, et al. Association of the metabolic syndrome with mortality and major adverse cardiac events: a large chronic kidney disease cohort. J Intern Med. 2021;290:1219–1232. doi:10.1111/joim.13355

9. Malik S, Wong ND, Franklin SS, et al. Impact of the metabolic syndrome on mortality from coronary heart disease, cardiovascular disease, and all causes in United States adults. Circulation. 2004;110:1245–1250. doi:10.1161/01.CIR.0000140677.20606.0E

10. Iseki K, Konta T, Asahi K, et al. Impact of metabolic syndrome on the mortality rate among participants in a specific health check and guidance program in Japan. Intern Med. 2020;59:2671–2678. doi:10.2169/internalmedicine.4975-20

11. Scurt FG, Ganz MJ, Herzog C, Bose K, Mertens PR, Chatzikyrkou C. Association of metabolic syndrome and chronic kidney disease. Obes Rev. 2024;25:e13649. doi:10.1111/obr.13649

12. Stefansson VTN, Schei J, Solbu MD, Jenssen TG, Melsom T, Eriksen BO. Metabolic syndrome but not obesity measures are risk factors for accelerated age-related glomerular filtration rate decline in the general population. Kidney Int. 2018;93:1183–1190. doi:10.1016/j.kint.2017.11.012

13. Chan SMH, Selemidis S, Bozinovski S, Vlahos R. Pathobiological mechanisms underlying metabolic syndrome (MetS) in chronic obstructive pulmonary disease (COPD): clinical significance and therapeutic strategies. Pharmacol Ther. 2019;198:160–188. doi:10.1016/j.pharmthera.2019.02.013

14. Li S, Zhang T, Yang H, et al. Metabolic syndrome, genetic susceptibility, and risk of chronic obstructive pulmonary disease: the UK Biobank Study. Diabetes Obes Metab. 2023;26(2):482–494. doi:10.1111/dom.15334

15. Pan A, Keum N, Okereke OI, et al. Bidirectional association between depression and metabolic syndrome: a systematic review and meta-analysis of epidemiological studies. Diabetes Care. 2012;35:1171–1180. doi:10.2337/dc11-2055

16. Wang X, Ji L, Tang Z, et al. The association of metabolic syndrome and cognitive impairment in Jidong of China: a cross-sectional study. BMC Endocr Disord. 2021;21:40. doi:10.1186/s12902-021-00705-w

17. Codazzi V, Frontino G, Galimberti L, Giustina A, Petrelli A. Mechanisms and risk factors of metabolic syndrome in children and adolescents. Endocrine. 2024;84:16–28. doi:10.1007/s12020-023-03642-x

18. Dang AK, Le HT, Nguyen GT, et al. Prevalence of metabolic syndrome and its related factors among Vietnamese people: a systematic review and meta-analysis. Diabetol Metab Syndr. 2022;16:102477. doi:10.1016/j.dsx.2022.102477

19. Matsuzawa Y, Funahashi T, Nakamura T. The concept of metabolic syndrome: contribution of visceral fat accumulation and its molecular mechanism. J Atheroscler Thromb. 2011;18:629–639. doi:10.5551/jat.7922

20. Reddy P, Lent-Schochet D, Ramakrishnan N, McLaughlin M, Jialal I. Metabolic syndrome is an inflammatory disorder: a conspiracy between adipose tissue and phagocytes. Clin Chim Acta. 2019;496:35–44. doi:10.1016/j.cca.2019.06.019

21. Association AD. 2. Classification and diagnosis of diabetes: standards of medical care in diabetes—2021. Diabetes Care. 2021;44:S15–S33. doi:10.2337/dc21-S002

22. Joint Committee Issued Chinese Guideline for the Management of Dyslipidemia in Adults. [2016 Chinese guideline for the management of dyslipidemia in adults]. Zhonghua xin xue guan bing za zhi. 2016;44:833–853. Polish. doi:10.3760/cma.j.issn.0253-3758.2016.10.005

23. Macfarlane D, Chan A, Cerin E. Examining the validity and reliability of the Chinese version of the International Physical Activity Questionnaire, long form (IPAQ-LC). Public Health Nutr. 2011;14:443–450. doi:10.1017/S1368980010002806

24. Jia YJ, Xu LZ, Kang DY, Tang Y. Reliability and validity regarding the Chinese version of the International Physical Activity Questionnaires (long self-administrated format) on women in Chengdu, China. Zhonghua Liu Xing Bing Xue Za Zhi. 2008;29:1078–1082.

25. Johns MW. A new method for measuring daytime sleepiness: the Epworth sleepiness scale. Sleep. 1991;14:540–545. doi:10.1093/sleep/14.6.540

26. Buysse DJ, Reynolds CF, Monk TH, Berman SR, Kupfer DJ. The Pittsburgh Sleep Quality Index: a new instrument for psychiatric practice and research. Psychiatry Res. 1989;28:193–213. doi:10.1016/0165-1781(89)90047-4

27. Netzer NC, Stoohs RA, Netzer CM, Clark K, Strohl KP. Using the Berlin Questionnaire to identify patients at risk for the sleep apnea syndrome. Ann Intern Med. 1999;131:485–491. doi:10.7326/0003-4819-131-7-199910050-00002

28. Cheung RT, Ngai SP, Ho KK. Chinese adaptation and validation of the Knee Injury and Osteoarthritis Outcome Score (KOOS) in patients with knee osteoarthritis. Rheumatol Int. 2016;36:1449–1454. doi:10.1007/s00296-016-3539-7

29. Lee HC, Chiu HF, Wing YK, Leung CM, Kwong PK, Chung DW. The Zung self-rating depression scale: screening for depression among the Hong Kong Chinese elderly. J Geriatr Psychiatry Neurol. 1994;7:216–220. doi:10.1177/089198879400700404

30. Che -H-H, Lu M-L, Chen H-C, Chang S-W, Lee Y-J. Validation of the Chinese version of the Beck Anxiety Inventory. Formos J Med. 2006;10:451–452.