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The relationship between sarcopenia and related bioindicators and changes after intensive lifestyle intervention in elderly East-China populations

BMC Musculoskeletal Disorders volume 25, Article number: 704 (2024) Cite this article

Abstract

Background

As populations live longer, there is a progressive increase in chronic degenerative diseases, particularly those related to the musculoskeletal system. Sarcopenia is characterized by loss of skeletal muscle mass, muscle strength, and loss of physical function. It is a common disease in older adults associated with various adverse health outcomes. There is a lack of bioindicators to screen for sarcopenia. Albumin and lymphocyte counts are commonly used to assess the degree of malnutrition, and blood routine, lipids, and thyroid function are relatively easy to obtain as part of a routine physical examination. Therefore, finding blood markers that can screen for sarcopenia is essential. Our primary aim was to explore whether the bioindicators of body composition, lymphocytes, albumin, lipids, and thyroid hormones are associated with sarcopenia, and a secondary aim was to investigate changes in these indicators after an intensive lifestyle intervention preliminarily.

Methods

60 subjects were selected from Runda and Bailian community health centers in Suzhou, China. They underwent body composition analysis and tested lymphocyte, albumin, lipid, and thyroid hormone levels. The 30 sarcopenia subjects underwent a 3-month intensive lifestyle intervention program. At the end of the intervention, we rechecked the bioindicators. Statistical analyses were performed in IBM SPSS v26.0.

Results

The blood indices of sarcopenia subjects were generally lower in albumin, non-high-density lipoprotein cholesterol (non-HDL-C), and free triiodothyronine (FT3). Body mass index (BMI)(r = 0.6266, p < 0.0001), fat-free mass (r = 0.8110, p < 0.0001), basal metabolism (r = 0.7782, p < 0.0001), and fat mass (r = 0.3916, p = 0.0020) were positively correlated with appendicular skeletal muscle index (ASMI). Higher BMI and FT3 were associated with lower odds of sarcopenia, while higher fat mass was associated with higher odds of sarcopenia. After a 3-month intensive intervention, sarcopenia subjects had a significant increase in BMI, ASMI, lymphocyte, and albumin levels, and an increase in FT3, but with a non-significant difference (p = 0.342).

Conclusions

Low BMI, FT3, and high fat mass were associated with sarcopenia. Intensive lifestyle intervention can significantly improve ASMI, BMI, lymphocytes, albumin, and FT3 in sarcopenia subjects, which is favorable for delaying the progression of sarcopenia.

Trial registration

This study was retrospectively registered on ClinicalTrials.gov, registration number NCT06128577, date of registration: 07/11/2023.

Peer Review reports

Background

As populations live longer, there is a progressive increase in chronic degenerative diseases, particularly those related to the musculoskeletal system. Sarcopenia is a common geriatric condition associated with a variety of adverse health outcomes, including fractures, decreased physical function, and increased mortality [1], resulting in significant healthcare expenditures that are projected to increase significantly with the growth of the elderly population globally [2].

Sarcopenia is characterized by loss of skeletal muscle mass, muscle strength, and loss of physical function, and its etiology and pathogenesis are complex and varied. Aging, chronic diseases, inflammation, chronic inactivity, and malnutrition can lead to loss of skeletal muscle mass and function [3]. Some studies have shown that dyslipidemia [4], thyroid hormone abnormalities [5], and malnutrition may be closely associated with the development of sarcopenia. Current screening and diagnostic procedures for sarcopenia are complex and costly, equipment is not portable, and there is a lack of blood indices to screen for sarcopenia. Albumin and lymphocyte counts are commonly used to assess the degree of malnutrition, and blood routine, lipids, and thyroid function are relatively easy to obtain as part of a routine physical examination. Therefore, finding blood markers that can screen for sarcopenia is essential. It not only saves many labor costs but also can provide early monitoring and intervention for patients suspected of sarcopenia through routine physical examination, reduce the incidence of sarcopenia, and thus improve the quality of life and prolong the life span of older adults in their later years.

Recent studies have shown that light aerobic exercise can increase triiodothyronine (T3) levels in rat gastrocnemius muscle by 1.3-fold [6] and that long-term physical activity can upregulate the expression of genes related to the thyroid hormone signaling pathway in aging skeletal muscle [7], which may be a mechanism by which exercise stimulates skeletal muscle protein synthesis through T3 signaling. DONGES C E et al. demonstrated that concomitant resistance and aerobic exercise can stimulate muscle fiber and mitochondrial protein synthesis in sedentary middle-aged men [8]. In addition, OIKAWA S Y et al. found a significant increase in acute muscle protein synthesis after ingestion of whey protein supplements (high-quality protein) compared to collagen supplements (low-quality protein) [9]. Both protein intake and exercise are essential for maintaining and improving muscle mass. If protein intake and exercise are insufficient, muscle mass will be lost, which is detrimental to health. BüLOW J et al. showed that the results of the interaction between skeletal muscle response to exercise and hyperaminoacidemia support a combination of the two [10]. Currently, there are no clinical studies on the changes in sarcopenia-related bioindicators after intensive nutritional intervention and individually designed exercise interventions. Therefore, our primary aim was to explore whether the bioindicators of body composition, lymphocytes, albumin, lipids, and thyroid hormones are associated with sarcopenia, and a secondary aim was to investigate changes in these indicators after an intensive lifestyle intervention preliminarily. The research hypotheses were: (1) Lymphocytes, albumin, lipids, thyroid hormones, fat mass, fat-free mass, and basal metabolism are associated with sarcopenia. (2) Intensive lifestyle interventions, including intensive nutritional interventions and individually designed exercise interventions, can significantly improve ASMI and increase some bioindicators mentioned above in subjects with sarcopenia, which is beneficial in delaying the progression of sarcopenia.

Methods

Study design and participants

This study was designed to explore the relationship between sarcopenia and related bioindicators in the communities affiliated with the Suzhou Municipal Hospital and preliminarily explore the changes in these bioindicators after intensive intervention. Between March 2022 and April 2022, 178 study subjects were recruited from the community health centers of Runda and Bailian in Suzhou, China. Among them, 162 participants completed the baseline examination of questionnaires and body composition analysis, and those with incomplete information and those who refused blood collection were discarded. Finally, we collected blood samples from 32 subjects with sarcopenia and 67 normal geriatric subjects. To avoid the influence of gender composition differences on the relevant indicators of the sarcopenia group and normal control group, 15 male and 15 female subjects were selected from sarcopenia subjects and normal subjects by using the random number table method, and 30 patients with sarcopenia underwent a 3-month intensive intervention program and completed the body composition analysis and the review of blood indicators. Figure 1 shows the study flowchart. The Ethics Committee of Suzhou Municipal Hospital (NO.K-2020–051-K01) reviewed and approved this study, and all participants gave written informed consent.

Fig. 1
figure 1

Study flowchart

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Inclusion criteria

  1. 1)

    Resident elderly aged 65–90 years old in the district.

  2. 2)

    Voluntary participation in the trial and signing the informed consent form.

Exclusion criteria

  1. 1)

    People with systemic severe diseases, organ failure, malignant tumors, neuromuscular degenerative diseases, or active weight loss.

  2. 2)

    People with cognitive impairment, incapacitation, or severe mental illnesses who cannot cooperate with the test.

  3. 3)

    People with cardiac pacemakers and artificial joint implantation or others who cannot undergo the BIA test.

  4. 4)

    People with severe cardiorespiratory dysfunction and physical disabilities who cannot complete the exercise training.

  5. 5)

    5) People under treatment for thyroid dysfunction and hyperlipidemia and those taking sarcopenia-related medications, such as steroids, angiotensin-converting enzyme inhibitors, metformin, and vitamin D.

  6. 6)

    Incomplete data, refusal to participate in the survey, body composition analysis, and blood collection.

Sample size

Sample size estimation was conducted using the G*Power 3.1 software. Appendicular skeletal muscle index was the primary outcome. The sample size was calculated based on values obtained from our previous study [11], with a fixed power of 80% and an α level of 5% for the main variable. Considering the probability of attrition, the final sample size was 30 subjects for each group.

Research instruments

Research instruments included a demographic information questionnaire (patients' names, gender, age, height, weight, education level, spousal status, residency, and other baseline information). All subjects volunteered to participate in this study, were given a detailed explanation of the study's purpose, methodology, and precautions, and signed an informed consent form.

Body composition, handgrip strength, and physical function

Body composition, including appendicular skeletal muscle mass, fat mass, fat-free mass, and basal metabolism, was measured using a DBA-210 body composition analyzer (Jilin Donghuayuan Medical Equipment Co., Ltd.). Subjects were fasted from food and water for two hours before measurement, wearing as little clothing as possible during the test, removing shoes and socks, applying a small amount of water to the soles of the feet and fingers, standing with both feet on the foot electrodes of the test platform, holding the handle electrodes with both hands, with the arms straightened and separated from the torso by about 30°, and not moving the body during the test.

The condition of muscle strength was assessed based on the subject's grip strength, according to the AWGS 2019 diagnostic criteria [12]. We measured grip strength with a JAMAR grip strength meter (Sammons. Preston, USA). We adjusted the grip distance in the appropriate range before the test. The subjects were in a sitting position with the feet placed naturally on the ground, the knees and hips flexed at 90°, the shoulders were in a neutral position with the shoulders internally retracted, and the elbows were bent at 90°, with the upper arms flat against the chest. The forearms in a neutral position, extend the wrist 0° ~ 30° and keep 0° ~ 15° ulnar deviation. The subjects held the grip of the instrument with maximum force. Two measurements were taken using both hands or the dominant hand, and the maximum value was taken as the result of the measurement and statistically analyzed.

We assessed physical mobility based on the subject's gait speed. AWGS 2019 recommends assessing physical mobility by measuring the 6-m walk test [12]. The participants were instructed to rest for 10 min before the test. The physician activated the timer as soon as the subjects started walking after standing at the starting point. The physician noted the time it took for the subjects to complete the 6-m walk at an average speed. Measurements were taken twice, and the results were averaged and recorded.

Diagnostic criteria for sarcopenia

In this study, a diagnosis of sarcopenia was made according to the diagnostic criteria of AWGS 2019 [12]. In this study, appendicular skeletal muscle mass was measured by bioelectrical impedance analysis. ASMI was calculated by dividing the appendicular skeletal muscle mass by the square of height(kg/m2). The diagnostic cutoff values for sarcopenia were ASMI < 7.0 kg/m2 for males or < 5.7 kg/m2 for females, accompanied by grip strength < 28 kg for males and < 18 kg for females or gait speed < 1.0 m/s.

Laboratory measurements

For collecting biological samples for laboratory tests, blood was drawn from the mid-elbow vein in the early morning from patients who had been fasting for more than eight hours. The participants abstained from alcohol and had a light diet for one day before the sample collection. In this study, blood samples were collected for lymphocyte count, albumin, triglycerides (TG), total cholesterol (TC), high-density lipoprotein cholesterol (HDL-C), low-density lipoprotein cholesterol (LDL-C), very low-density lipoprotein cholesterol (VLDL-C), thyroid stimulating hormone (TSH), free thyroxine (FT4), and free triiodothyronine (FT3). Lymphocyte counts were detected using a fully automated hematology analyzer (Mindray BC-6800, Shenzhen, China), and albumin and lipids were detected using a fully automated biochemistry analyzer (Hitachi 7600, Hitachi, Ltd., Tokyo, Japan). Thyroid hormones were measured by chemiluminescence immunoassay (Abbott I2000, Abbott, Chicago, USA). Measurements were done using standard methods in the laboratory. Specimens were sent to the Department of Laboratory Medicine of Suzhou Municipal Hospital on the same day of collection, where they were assayed by a full-time laboratory technician in the central laboratory in strict accordance with clinical testing protocols and quality control following the rules of the Clinical Chemistry Laboratory of the United States. The inter-assay coefficients of variations were less than 10.0% for all indexes.

Interventions and strategies to improve adherence

After completing screening, 30 subjects in the sarcopenia group received a 3-month intensive intervention consisting of an intensive nutritional intervention and an individually designed exercise intervention. Nutritional and exercise prescriptions were co-designed through a nutritionist and rehabilitation physician.

Intensive nutritional interventions were as follows: i) Estimation of ideal body weight according to height, calculation of calories by giving 30-40 kcal/kg/day according to BMI stratification, and calculation of daily protein requirement at 1.5 g/kg/day, which was finally converted into daily dietary recommendations according to the results of the calculations. ii) Additional protein supplementation is distributed by whey protein, with each sachet containing 15 g of whey protein (Nanjing Yirui Medical Science Technology Ltd.). Each bag was mixed with 80 mL of water at about 37℃ once a day. At baseline (T0), patients in the sarcopenia group were provided a container with 15 sachets of whey protein, accounting for 15 days of treatment. During the study period, sarcopenia group patients returned the container and received a full one every 15 days. Compliance with whey protein supplementation was evaluated through the number of sachets returned every 15 days.

The resistance training program included 5 min of warm-up, 20 min of muscle strength training, and 5 min of slow walking, performed thrice a week. Resistance training involved a dumbbell and sandbags as weights for the major muscles of the upper and lower limbs [13]. In the study, aerobic training is brisk walking or jogging for 30 min/day five times a week. All patients underwent a specific physical exercise for two weeks under the supervision of an experienced rehabilitation physician, followed by home exercise without the guidance of a rehabilitation physician. Follow-up visits were made every 15 days during the intervention, blood was collected and body composition analysis was performed again at the end of the intervention.

Statistical analysis

Statistical analyses were performed in IBM SPSS v26.0 (IBM, Armonk, NY, USA). The normal distribution of variables was evaluated by the Shapiro–Wilk test. The results were expressed as means ± standard deviation if continuous variables conform to a normal distribution. At this time, two independent samples were compared using the independent samples t-test when the homogeneity of variance was satisfied. Otherwise, the approximate t-test was used. Two paired samples were compared using the paired samples t-test. The results were expressed as medians (25th, 75th percentiles) if the continuous variables did not conform to a normal distribution, the Mann–Whitney U test was used to compare the two independent samples, and the Wilcoxon test was used for paired samples. Categorical variables were summarized as counts and percentages, and between-group comparisons were made using the chi-square test. Pearson's correlation analysis was used to assess whether there was a linear correlation between the two variables if both continuous variables were normally or approximately normally distributed. Otherwise, Spearman correlation analysis was used. Binary Logistic regression analysis was used to screen the factors influencing sarcopenia. Significance was set at p < 0.05.

Results

Participant characteristics

Univariate analysis revealed several different baseline characteristics between the sarcopenia and normal control groups (Table 1). Levels of ASMI, BMI, fat mass, fat-free mass, and basal metabolism were significantly lower in the sarcopenia group compared to the normal control group (all p < 0.001). They also had lower levels of albumin, non-HDL-C, and FT3, while their level of HDL-C was significantly higher (all p < 0.05).

Table 1 Participants' baseline characteristics a
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Each bioindicator range was subdivided into four equal categories to form a frequency distribution for preliminary analysis. Subjects in the sarcopenia group tended to show lower BMI, fat-free mass, and fat mass. In comparison, subjects in the normal control group tended to show higher BMI, fat-free mass, and fat mass; this uneven distribution was statistically significant (p < 0.05). In addition, we could see a decreasing trend in sarcopenia rates with increasing BMI, fat-free mass, and basal metabolism in all four groups (Fig. 2). The uneven distribution of sarcopenia subjects in the lymphocyte subgroup was statistically significant (p < 0.05). In contrast, the uneven distribution in albumin, lipids, and thyroid function was not statistically significant (p > 0.05) (Fig. 3).

Fig. 2
figure 2

The frequency distributions of biological indicators of body composition and sarcopenia rates distributions among subjects. a BMI, body mass index; b fat-free mass; c fat mass; d basal metabolism. Each of the body composition indicators' ranges was further subdivided into four equal categories to form a frequency distribution for preliminary analysis. The graphs were created by GraphPad Prism

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Fig. 3
figure 3

The frequency distributions of blood bioindicators and sarcopenia rates distributions among subjects. a lymphocytes; b albumin; c TG, triglycerides; d TC, total cholesterol; e HDL-C, high-density lipoprotein cholesterol; f non-HDL-C, non-high-density lipoprotein cholesterol (this study refers to the sum of LDL-C and VLDL-C); g TSH, thyroid stimulating hormone; h FT4, free thyroxine; i FT3, free triiodothyronine. Each of the blood bioindicators' ranges was further subdivided into four equal categories to form a frequency distribution for preliminary analysis. The graphs were created by GraphPad Prism

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Correlation analysis between biological indicators and ASMI

We hypothesized that these biomarkers would show the strongest associations with sarcopenia severity during the early onset. BMI (r = 0.6266, p < 0.0001), fat-free mass (r = 0.8110, p < 0.0001), and basal metabolism (r = 0.7782, p < 0.0001) were positively and strongly correlated with ASMI (all r > 0.6), and fat mass (r = 0.3916, p = 0.0020) was also positively correlated with ASMI, but with a weaker correlation (Fig. 4). A weak but significant negative correlation was observed between HDL-C (r = -0.3579, p = 0.0050) and ASMI. It was also observed between TSH (r = -0.3218, p = 0.0122) and ASMI (Fig. 5). The other biological indicators failed to show any significant associations with ASMI in our patient cohort.

Fig. 4
figure 4

Correlation analysis of biological indicators of body composition levels vs. ASMI across all subjects. a BMI, body mass index; b fat-free mass; c fat mass; d basal metabolism. a was statistically analyzed using Pearson correlation analysis, and b, c, and d were statistically analyzed using Spearman correlation analysis. The graphs were created by GraphPad Prism

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Fig. 5
figure 5

Correlation analysis of blood bioindicators levels vs. ASMI across all subjects. a lymphocytes; b albumin; c TG, triglycerides; d TC, total cholesterol; e HDL-C, high-density lipoprotein cholesterol; f non-HDL-C, non-high-density lipoprotein cholesterol (this study refers to the sum of LDL-C and VLDL-C); g TSH, thyroid stimulating hormone; h FT4, free thyroxine; i FT3, free triiodothyronine. b, d, e, f, h, and i were statistically analyzed using Pearson correlation analysis, and a, c, and g were statistically analyzed using Spearman correlation analysis. The graphs were created by GraphPad Prism

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Logistic regression analysis of factors associated with sarcopenia

We also assessed whether the biological indicators were associated with sarcopenia. A univariate binary logistic regression analysis of the above biomarkers was first performed. It showed that BMI, fat mass, fat-free mass, basal metabolism, albumin, HDL-C, and FT3 were associated with sarcopenia. Multivariate binary logistic regression model analyses showed that higher BMI and FT3 were associated with lower odds of sarcopenia, while higher fat mass was associated with higher odds of sarcopenia (Fig. 6).

Fig. 6
figure 6

Multivariate binary logistic regression analysis of biological indicators levels vs. sarcopenia risk. BMI, body mass index; HDL-C, high-density lipoprotein cholesterol; FT3, free triiodothyronine. The graph was created by GraphPad Prism

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Changes in biological indicators after intensive lifestyle interventions in human subjects

Thirty participants in the sarcopenia group completed a 3-month intensive lifestyle intervention program consisting of an intensive nutritional intervention and an individually designed exercise intervention. The study showed an increase in ASMI, BMI, fat mass, fat-free mass, basal metabolism, lymphocytes, and albumin levels, and a decrease in TG and TSH levels, all statistically significant after the intervention (Table 2).

Table 2 Changes in biological indicators after 3-month intensive lifestyle intervention a
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Discussion

In this study, our main findings were that subjects with sarcopenia had generally low levels of ASMI, BMI, fat mass, fat-free mass, basal metabolism, albumin, non-HDL-C, and FT3. BMI, fat-free mass, and basal metabolism were positively correlated with ASMI, and HDL-C and TSH were negatively correlated with ASMI. Higher BMI and FT3 were associated with lower odds of sarcopenia, while higher fat mass was associated with higher odds of sarcopenia. In addition, after a 3-month intensive intervention, subjects with sarcopenia showed a significant increase in BMI and ASMI, a significant increase in lymphocyte and albumin levels, and a significant decrease in TSH levels. In addition, the level of FT3 was increased, but the difference was not statistically significant. The levels of the above indicators in patients with sarcopenia after intensive intervention are closer to those of normal people.

Our study showed that subjects with sarcopenia generally had low BMI, fat mass, fat-free mass, and basal metabolism and that higher BMI was associated with lower odds of sarcopenia. The results of BMI on the prediction of sarcopenia were consistent. A study on risk factors for sarcopenia in nursing home elderly found that low BMI was a predictor of sarcopenia [14]. A Korean study showed that high BMI had a protective effect on ASMI in both men and women and that BMI, waist circumference, and percentage of body fat were positively correlated with a lower incidence of sarcopenia in women [15]. The sarcopenia population containing normal or low BMI type sarcopenia and high BMI type(overweight, obese) and their relationships can be further explored separately in later studies. It is necessary to focus on BMI along with a comprehensive consideration of the relative changes in fat mass and fat-free mass. In particular, a decrease in fat-free mass accompanied by increased visceral fat may accelerate skeletal muscle weakness in older adults as they age. Our findings indicated that intensive intervention improved ASMI and BMI in sarcopenia patients while increasing fat and fat-free mass.

It is well known that lymphocytes are not only a nutrition-related indicator but also an inflammation-related indicator. Our data showed that sarcopenia subjects tended to be distributed in groups with lower and higher lymphocytes (exceeding the upper limit of normal values). Albumin was generally lower in sarcopenia subjects, suggesting that both our malnutrition and inflammatory status may increase the incidence of sarcopenia. ASMI, BMI, fat mass, fat-free mass, basal metabolism, lymphocytes, and albumin significantly improved in sarcopenia subjects after three months of intensive lifestyle intervention, suggesting that the nutritional status of the subjects was improved. Intensive lifestyle intervention with nutritional supplementation and exercise can reduce the subclinical pro-inflammatory state [13]. Lactalbumin, a major component of whey protein, inhibits the production of pro-inflammatory cytokines in monocytes [16]. LIBERMAN K et al. [17] demonstrated that 13 weeks of supplementation with vitamin D and a leucine-rich whey protein nutritional supplement reduced chronic low-grade inflammation in older adults with sarcopenic frailty. Whey protein also contains high-branched-chain amino acids, which can stimulate skeletal muscle protein synthesis via the mammalian target of rapamycin (mTOR) signaling pathway [18]. Early nutritional support for malnourished patients may prevent further development of sarcopenia. Resistance exercise induces the release of important hormones and hypertrophic factors, thereby increasing protein synthesis, which helps improve muscle mass and function [19]. Some studies have shown that aerobic exercise training can improve sarcopenia by improving maximal oxygen consumption, mitochondrial density and activity, and insulin sensitivity [20,21,22]. In summary, these studies and our clinical data suggest that exercise combined with nutritional intervention is recommended for treating sarcopenia.

Our data showed that the sarcopenia group was accompanied by a reduction in total lipid levels (TG, TC) compared to normal controls (but p > 0.05), with lower non-HDL-C and higher HDL-C levels (p < 0.05). Further divided into four groups according to HDL-C level, the results showed that the rate of sarcopenia tended to increase with increasing HDL-C, but the difference was not statistically significant. We concluded that HDL-C was negatively correlated with ASMI based on Pearson's correlation analysis. WANG N et al. [23] showed that TG was negatively correlated with sarcopenia prevalence and HDL-C was positively correlated with it among adults in the Chinese community, respectively, which was in line with our findings, but the exact mechanism was not precise, which could be further explored in later studies. Our study showed a statistically significant difference in TG level reduction after intensive intervention, which may be related to the increased fat mobilization after exercise.

Our study showed that FT3 was generally lower in the sarcopenia group compared to the normal control group. In addition, the correlation between blood indices and ASMI showed a negative correlation between TSH and ASMI. Finally, binary logistic regression analysis showed that high FT3 was a protective factor for sarcopenia. An Italian study [24] found that FT3 and FT3/FT4 levels tended to decrease with age, while FT4 and TSH tended to increase. Sarcopenia is also an aging disorder, which may explain why FT3 was generally lower in the sarcopenia group. The biological activity of FT3 is much higher than that of FT4, which may be why we did not find any correlation between FT4 and sarcopenia in the present study, and the findings of Zhang et al. [25] agree with ours. SHENG Y et al. [26] found a positive correlation between FT3 and appendicular skeletal muscle mass and no significant correlation between FT4, TSH and appendicular skeletal muscle mass. FANG L N et al. [27], in their study of the association between thyroid hormones and skeletal muscle and bone in euthyroid type 2 diabetes patients, found that FT3/FT4 were positively correlated with ASM and ASMI. In our study, after giving intensive intervention, TSH decreased with a statistically significant difference, and FT3 increased compared to before, but the difference was not statistically significant (P = 0.342), which may be related to the insufficient duration of intervention. Skeletal muscle is one of the primary target tissues for thyroid hormone, stimulating protein synthesis and degradation. Intracellular thyroid hormone concentration is regulated in skeletal muscle by deiodinase, in which deiodinase type 2 (D2) and type 3 (D3) are present. D2 converts T4 to active T3. However, D3 inactivates both T4 and T3 by removing the endocyclic iodine, and T3 exerts its biological activity by binding to the nuclear thyroxine hormone receptor or by binding to cytoplasmic proteins [28]. D3 is highly expressed in activated and proliferating satellite cells and is downregulated during differentiation. At the same time, D2 is upregulated, increasing the intracellular concentration of thyroid hormone, which drives the terminal differentiation of myoblasts into tubules/myofibers [29]. More studies are needed on the changes in thyroid hormone levels and appendicular skeletal muscle mass in patients with sarcopenia after intensive intervention. Our results showed a significant decrease in TSH levels and an increase in FT3, but the difference was not statistically significant and may be related to the duration of the intervention and the subjects' compliance. If there were a significant increase in FT3 and ASMI after intensive intervention, then it would be possible to increase the level of active T3 in our body by regulating deiodinase activity, thus delaying the progression of sarcopenia.

Our study has some limitations. First, we did not study the factors affecting sarcopenia separately according to BMI stratification but included both the general sarcopenia population and the obese sarcopenia population in our study. Future studies will address these limitations by categorizing sarcopenia subjects and reducing the impact of confounding factors on the results. Second, although we tested for multiple blood markers, it is inevitable that we may have missed other relevant blood markers in sarcopenia and reduced the accuracy of early monitoring of sarcopenia through routine physical examination.

Conclusions

Our findings conclude that higher BMI and FT3 were associated with lower odds of sarcopenia, while higher fat mass was associated with higher odds of sarcopenia. A high BMI benefits sarcopenia in older adults, while the relative changes in fat and fat-free mass must be considered together. Our findings support the idea that intensive lifestyle interventions, including intensive nutritional interventions and individually designed exercise interventions, can significantly improve ASMI and increase BMI, lymphocytes, albumin, and FT3 in subjects with sarcopenia, which is beneficial in delaying the progression of sarcopenia.

Availability of data and materials

The datasets supporting the conclusions of this article are available by contacting the author in the Science Data Bank repository: https://doi.org/https://doi.org/10.57760/sciencedb.13317.

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Acknowledgements

We thank the participants for making their data available.

Funding

The research leading to these results received funding from Suzhou Municipal Health Commission under Suzhou Municipal Health Commission Science and Technology Project No. LCZX201911.

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Authors and Affiliations

  1. Department of Geriatric Medicine, The Affiliated Suzhou Hospital of Nanjing Medical University (Suzhou Municipal Hospital), Suzhou, Jiangsu, China

    Lijun Yang, Minhong Wang, Liya Mo, Yunlong Yang, Yan Cui & Yonghua Wu

Authors
  1. Lijun Yang
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  2. Minhong Wang
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  3. Liya Mo
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  4. Yunlong Yang
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  5. Yan Cui
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  6. Yonghua Wu
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Contributions

L.Y.: Design of the Study, Recruitment of Subjects, Data collection, Data analysis, Writing - Original Draft; M.W.: Writing - Study Proposal, Funding Acquisition, Intervention, Data collection; L.M.: Data collection, Supervision, Writing - Original Draft; Y.Y.: Recruitment of Subjects, Data collection, Data analysis; Y.C.: Data collection, Writing - Original Draft; Y.W. (Corresponding Author): Writing - Study Proposal, Data collection, Data analysis, Supervision, Writing - Review & Editing.

Corresponding author

Correspondence to Yonghua Wu.

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Ethics approval and consent to participate

All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Ethics Committee of Suzhou Municipal Hospital (No. K-2020–051-K01). Informed consent was obtained from all participants in the study.

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Not applicable.

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The authors declare no competing interests.

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Yang, L., Wang, M., Mo, L. et al. The relationship between sarcopenia and related bioindicators and changes after intensive lifestyle intervention in elderly East-China populations. BMC Musculoskelet Disord 25, 704 (2024). https://doi.org/10.1186/s12891-024-07835-x

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  • DOI: https://doi.org/10.1186/s12891-024-07835-x

Keywords

BMC Musculoskeletal Disorders

ISSN: 1471-2474

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