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Relationship between different muscle mass indices and physical performance measures in Turkish older adults

BMC Geriatrics volume 24, Article number: 875 (2024) Cite this article

Abstract

Background

Sarcopenia, characterized by the loss of skeletal muscle, is assessed using appendicular skeletal muscle mass indices (ASMI). Various international groups propose different ASMI thresholds for assessing sarcopenia. However, the optimal ASMI that correlates best with physical performance measures in older Turkish adults remains unexplored. This study aims to determine which ASMI is most closely associated with physical performance measures, particularly low handgrip strength (dynapenia), in Turkish older adults.

Methods

The study included 326 individuals aged 60 and above. Comprehensive geriatric assessments were conducted on all participants, along with anthropometric evaluations and body composition analyses. ASMI was calculated by adjusting height squared, weight, and body mass index (BMI). Physical performance was assessed through handgrip strength, gait speed, and the chair stand test.

Results

The mean age of the participants was 74 ± 5.77 years, with 59.8% being women and 37.5% having dynapenia. Height-squared adjusted ASMI was not significantly associated with gait speed or the chair stand test. Weight-adjusted ASMI correlated with handgrip strength and gait speed but not with the chair stand test. Both height and weight-adjusted ASMI did not differ significantly between participants with and without dynapenia (p > 0.05). BMI-adjusted ASMI significantly correlated with all physical performance parameters (p < 0.05). Furthermore, in multivariate regression analysis, BMI-adjusted ASMI (OR = 0.028, 95% CI = 0.01–0.31, p = 0.006) was independently associated with dynapenia.

Conclusion

The study indicates that ASMI adjusted for BMI shows stronger correlations with all physical performance parameters and is independently associated with dynapenia. Utilizing ASMI adjusted for BMI may improve sarcopenia diagnosis in Turkish older adults.

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Introduction

Physiological changes in organ systems are an inevitable consequence of the aging process. Skeletal muscle, which comprises a significant portion of total body weight, progressively decreases with age [1]. Sarcopenia, characterized by a gradual decline in skeletal muscle mass and strength [2], is a significant geriatric syndrome closely associated with various adverse health outcomes, including an increased risk of frailty, hospitalization, falls, and mortality [2].

Recent studies have demonstrated that muscle strength is a more reliable predictor of adverse outcomes than muscle mass. This is especially evident with commonly used tests such as handgrip strength, the chair stand test, and gait speed [3, 4]. Therefore, determining which muscle mass index is more closely related to muscle strength and using that index in diagnosing sarcopenia will be valuable in predicting the risk of possible adverse outcomes.

Given the significance of sarcopenia, various international research groups have recommended different skeletal muscle mass indices to assess the low muscle mass component of sarcopenia. These indices include appendicular skeletal muscle mass indices (ASMI) and total skeletal muscle mass indices (SMMI) adjusted for height, weight, and body mass index (BMI). The height-adjusted ASMI (ASM/height²) was first proposed by Baumgartner et al. [5]. This index correlates significantly with impaired physical activity or frailty, though the correlation is weaker in women [5]. However, individuals with a higher BMI may not be classified as sarcopenic using the index of ASM/height² due to the increased presence of adipose tissue [6]. On these grounds, in 2002, the weight-adjusted SMMI was proposed by Janssen et al. [7]. The weight-adjusted model was later adapted to appendicular muscle mass adjusted by weight and is employed as an alternative index in combination with the index adjusted by height proposed by Baumgartner et al. In addition to these indices, the BMI-adjusted ASMI was recommended by the National Institutes of Health Sarcopenia Project Foundation (FNIH) to diagnose sarcopenia in 2014 [8].

With the rising prevalence of obesity in Türkiye [9], the current height-adjusted muscle mass index recommended by the European Working Group on Sarcopenia in Older People (EWGSOP-2) [2] may not accurately detect low muscle mass in Turkish individuals. Therefore, determining the optimal population-specific indices for the diagnosis of sarcopenia becomes increasingly essential. Among the different indices proposed for use in other populations, it is not yet adequately clarified which skeletal muscle index correlates better with physical performance measures in detail for the Turkish population.

In a study by Bahat et al., the use of BMI-adjusted SMMI to identify low muscle mass showed stronger associations with functional parameters (handgrip strength, gait speed, activity of daily living score) compared to height and weight-adjusted SMMI [10]. To our knowledge, no research has examined which ASMI used in the diagnosis of sarcopenia has a better relationship with physical performance measures, including low handgrip strength (dynapenia), gait speed, and chair-stand test in older adults in Türkiye.

In this study, we aimed to explore the ASMI most closely associated with physical performance measures, particularly dynapenia, in Turkish older adults.

Material –methods

Study population

This cross-sectional study included community-dwelling older adults who visited a university geriatrics outpatient clinic for routine health check-ups between January 2022 and January 2023. This clinic is accessible to all older adults aged 60 years and older. The participants were not selected based on specific disease diagnoses but attended the clinic for general health assessments. A total of 357 older adults who were able to comply with verbal commands were assessed for recruitment in this study. Participants with edema (n = 9), decompensated heart failure (n = 8), cerebrovascular disease (n = 3), rheumatological conditions (n = 5), cancer (n = 2), or those taking medications that impact muscle function, such as steroids (n = 4), were excluded from the study. After exclusions, 326 participants were included. The institutional ethics committee approved the study protocol with a decision number of 897, and informed consent was obtained from all participants before the study entry.

Demographic and clinical data were collected, and disease history was obtained. Weight, height, arm, calf, and waist circumferences were measured. Weight was assessed using a bioelectrical impedance analysis (BIA) device while participants wore light clothing and stood barefoot on the plate electrodes. Height was measured using an ultrasonic height stadiometer. BMI was calculated by dividing weight in kilograms by the square of height in meters. Mid-arm circumference was measured at the mid-point between the tip of the olecranon process and the acromion. Waist circumference was measured at the midpoint between the lower border of the rib cage and the iliac crest. Calf circumference was assessed using a non-elastic band measured at the widest part of the calf.

Comprehensive geriatric assessments

All participants underwent a comprehensive geriatric assessment, including the evaluation of daily living activities with the Katz Basic and Lawton- Brody Instrumental Activities of Daily Living Scale (ADL, IADL [11]), nutritional assessment with the Mini Nutritional Assessment-short form (MNA) [12], mood assessment with the Yesavage Geriatric Depression Scale-short form (GDS) [13] and frailty assessment with the Fried Frailty Phenotype (FFP) [14]. All tests have Turkish reliability and validity studies; Turkish versions of all tests were used in the study.

Body composition analysis

Appendicular skeletal muscle (ASM) and fat-free mass (FFM) were measured using the Jawon x-contact 357 multi-frequency bioelectrical impedance analyzer (BIA). ASM was determined as the total skeletal muscle mass in the arms and legs, assuming all non-fat and non-bone tissues represent skeletal muscle. Total skeletal muscle mass (SMM) was calculated using the following formula: SMM(kg) = 0.566×FFM (kg) [15]. ASMI and SMMI values were adjusted by height squared (ASM(kg)/m2; SMM(kg)/m2), weight (ASM(kg)×100/weight; SSM(kg)×100/weight) [7], and BMI (ASM(kg) /BMI; SMM(kg)/BMI) [8].

Functional parameters

Due to the fact that muscle strength is a better predictor of adverse outcomes than muscle mass [3], we investigated the muscle mass indices that are more closely related to low muscle strength. Handgrip strength is an easy-to-use, low-cost screening tool that effectively predicts future morbidity and mortality in individuals of all ages, including older adults [16]. The participants’ muscle strength was measured using the Takei handgrip strength dynamometer. Three measurements were obtained from the dominant hand, and the highest value for each patient was recorded. Low muscle strength (dynapenia) is defined as a hand grip strength of < 16 kg in women and < 27 kg in men, according to the EWGSOP-2 consensus [2]. This specific definition was used in our study because it provides a standardized and widely accepted measure of muscle weakness. By using these established thresholds, we ensure the reliability and comparability of our findings with other studies.

Physical performance was evaluated with the 6-meter walking test and chair stand test. For the 6-meter walking test, participants were instructed to walk six meters at their normal gait pace, and the time taken was recorded with a stopwatch. According to the EWGSOP-2 criteria, a walking speed of less than 0.8 m/s is considered poor physical performance [2]. In the chair stand test, participants were asked to sit and stand up five times with their hands on their chest. The time taken was recorded with a stopwatch, and more than 15 s was classified as poor physical performance [2].

Statistical analysis

The statistical analysis was conducted using SPSS version 26.0 for Windows (SPSS, Chicago). The normality of data distribution was assessed through visual methods, including histograms and probability graphs, and analytical methods, such as Kolmogorov-Smirnov and Shapiro-Wilk tests. Categorical variables were presented as numbers and percentages. In contrast, continuous variables were expressed as mean (SD) for normally distributed data and median and the interquartile range (IQR) for non-normally distributed data. For the comparison of non-parametric and parametric continuous variables between participants with and without dynapenia, the Mann-Whitney U test and Student’s t-test were employed, respectively. Proportions in the groups were compared using the Chi-square test or Fisher’s exact test. The correlation between physical performance parameters and muscle mass indices was examined through Pearson correlation analysis. A multivariate logistic (binary) regression analysis was conducted to investigate the association between muscle mass indices (ASM/height2, ASM/weight, ASM/BMI, and SMM/BMI) and dynapenia, employing four models for evaluation. Model 1 was adjusted for age, sex (female), Fried frailty score, number of drugs used, and ASM/height². Model 2 was adjusted for age, sex (female), Fried frailty score, number of medicines used, and ASM/weight. Model 3 was adjusted for age, sex (female), Fried frailty score, number of drugs used, and ASM/BMI. Model 4 was adjusted for age, sex (female), Fried frailty score, number of medicines used, and SMM/BMI. Odds ratios (OR), 95% confidence intervals (CI), and β values were calculated for each predictor. Subgroup regression analysis, stratified by sex (women and men) and BMI categories (BMI ≥ 25 kg/m² and BMI < 25 kg/m²), was conducted to ascertain whether the independent association between BMI-adjusted skeletal muscle mass indices and dynapenia in our population was influenced by the high prevalence of overweight individuals or females, or if it was indeed an independent association. Model fit was evaluated using the Hosmer-Lemeshow goodness of fit statistics. In this study, statistical significance was set at p < 0.05.

Results

A total of 326 participants (aged 74 ± 5.7 years) were included in the study, comprising 196 women (59.8%) and 132 men (40.2%). The flowchart of the study population is presented in Fig. 1. According to the EWGSOP-2 criteria, 37.5% of the participants had dynapenia, and 44 individuals (13.4%) were classified as frail based on the Fried Frailty Phenotype.

Fig. 1
figure 1

Flowchart of the study population

Full size image

A statistical relationship was observed between sex and all skeletal muscle mass indices, which were significantly lower in women than men (p < 0.001). Similarly, all physical performance parameters were significantly lower in women (p < 0.05) (Table 1).

Table 1 General characteristics, anthropometric measurements, and skeletal muscle mass indices of the participants by sex
Full size table

Moderate correlations were found between ASM/height² and SMM/height² with handgrip strength, while no significant correlations were observed with gait speed and chair stand test. ASM/BMI and SMM/BMI showed strong correlations with handgrip strength and moderate correlations with gait speed and the chair stand test (Table 2).

Table 2 Correlations between muscle mass indices and physical performance
Full size table

All skeletal muscle mass indices significantly correlated with ADL scores; however, only ASM/BMI and SMM/BMI demonstrated significant correlations with both ADL and IADL (Table S1).

There was no significant difference in weight-adjusted and height-adjusted skeletal muscle mass indices between the sarcopenic and non-sarcopenic groups. However, there was a significant difference between the two groups in terms of BMI-adjusted skeletal muscle mass indices (Table S2).

SMM/BMI and ASM/BMI were found to be independently associated with dynapenia. This association remained significant after adjusting for age, sex (female), Fried Frailty Phenotype score, and the number of medicines used (for SMM/BMI: OR = 0.04, 95% CI = 0.01–0.38, p = 0.004; for ASM/BMI: OR = 0.028, 95% CI = 0.01–0.31, p = 0.006) (Table 3).

Table 3 Logistic regression analyses of skeletal muscle mass indices for dynapenia
Full size table

Subgroup regression analysis for sex and BMI categories (BMI ≥ 25 kg/m² and BMI < 25 kg/m²) revealed that the BMI-adjusted muscle mass indices were independently associated with dynapenia in the Turkish population, irrespective of sex, and particularly in individuals with a BMI > 25 kg/m² (Table 4).

Table 4 Subgroup regression analysis of the association between BMI-adjusted skeletal muscle mass indices and dynapenia
Full size table

Discussion

This study is the first in Türkiye to investigate the relationship between appendicular muscle mass indices and physical performance measures. Our results reveal that the ASM/BMI index significantly correlates with all physical performance parameters and serves as an independent predictor of dynapenia. While ASM/weight showed correlations with gait speed and handgrip strength, it was not significantly associated with the chair stand test. In contrast, ASM/height² did not significantly correlate with gait speed or the chair stand test. All skeletal muscle mass indices were significantly correlated with activities of daily living (ADL) scores. However, only ASM/BMI and SMM/BMI were notably associated with both ADL and IADL. Additionally, the independent relationship between BMI-adjusted indices and dynapenia was consistent across genders but varied with BMI status, showing a significant association in individuals with a BMI > 25 kg/m².

Total body or appendicular muscle mass is closely associated with body size parameters such as height, weight, or BMI [17]. Adjusting muscle mass measurements according to population-specific anthropometric criteria is crucial for accurately diagnosing the low muscle mass component of sarcopenia, given the variations in anthropometric measures across different ethnic groups. For instance, Asians typically have a lower BMI and higher body fat than Europeans, who generally have a taller average height; these differences can be attributed to distinct dietary and genetic factors [18]. Additionally, Turkish individuals have a higher BMI and greater body fat compared to Asian populations [19]. Therefore, differences in body composition among various ethnic groups and populations necessitate adjustments for skeletal muscle mass to be adapted to reflect these differences.

In the study conducted by Janssen et al. on participants aged 65 years and older in the United States, there was a significant association between severe sarcopenia and disability compared to moderate sarcopenia, as defined by height-adjusted SMM [20]. Another study in older adults found that the height-adjusted SMM index was better related to muscle function than the weight-adjusted SMM index [21]. However, the important striking detail of the study was that the prevalence of sarcopenia was higher in men than in women using the height-adjusted SMM index, which was attributed to the shortening of women’s height due to physiological changes and osteoporosis in the postmenopausal period [22, 23]. In contrast, Kittiskulnam et al. reported in a study with hemodialysis participants that a low weight-adjusted SMM was better associated with walking speed than a low height-adjusted SMM [24]. Moreover, in the same study, Kittiskulnam et al. found that BMI-adjusted SMM had a stronger correlation with hand grip strength and gait speed compared to weight-adjusted and height-adjusted SMM [24]. In a recent study involving pre-frail individuals with obesity, a significant association was observed between ASM/BMI and the short physical performance battery (SPPB) and handgrip strength [25]. Considering that all these studies were conducted among different populations and patient groups, these findings underscore the importance of selecting appropriate muscle mass indices tailored to the specific population.

The present study demonstrated a significant correlation between BMI-adjusted skeletal muscle mass indices (including ASM/BMI and SMM/BMI) and SMM/kg with all physical function parameters. Moreover, BMI-adjusted muscle mass indices were identified as independently related to dynapenia. These results align with those conducted by Bahat et al., who found that BMI-adjusted SMM was more strongly associated with functional parameters than other indices (SMM/height2, SMM/weight) [10]. We also found that all skeletal muscle mass indices were weakly but significantly correlated with ADL, whereas only BMI-adjusted skeletal muscle mass indices were associated with IADL. In contrast, weight- and height-adjusted skeletal muscle mass indices showed no association. This differs from the findings of Bahat et al. [10], where BMI-adjusted SMM showed stronger correlations with both ADL and IADL, while height-adjusted muscle mass index was associated explicitly with IADL. These results suggest that BMI-adjusted indices may be more reliable for evaluating functional status in older adults, suggesting that using height- or weight-adjusted indices may be inadequate for accurately assessing functional status.

Unlike the research by Bahat et al., which used single-frequency BIA to assess muscle mass, our study stands out as the first to utilize multi-frequency BIA specifically to assess appendicular muscle mass. In addition, the multi-frequency BIA device shows a stronger correlation with handgrip strength and DEXA than the single-frequency BIA device [26, 27]. This distinction is significant as appendicular muscle mass offers a more holistic evaluation of muscle mass in older adults.

Identifying sarcopenia in obese older adults continues to pose a challenge, primarily due to the absence of a universally accepted gold standard for both muscle mass and muscle quality. Research has demonstrated that BMI-adjusted appendicular skeletal muscle mass (ASM) is strongly associated with visceral obesity and metabolic syndrome [28]. Additionally, recent studies have highlighted a significant correlation between BMI-adjusted ASM and visceral fat area [29]. However, Newman et al. reported that the skeletal muscle mass indexed by height² strongly correlates with BMI [6], which can lead to the misclassification of predominantly lean individuals as having sarcopenia, thus underestimating the condition in overweight or obese individuals [30]. Graf et al. similarly reported a low prevalence of reduced muscle mass in older adults with a BMI > 30 kg/m² when muscle mass was defined using ASM/height [31]. This suggests that using height-adjusted muscle mass to define sarcopenia may result in misdiagnosis among obese individuals. Given these varied findings, the Foundation’s National Institutes of Health group (FNIH) recommended in 2014 that ASM should be adjusted according to BMI [8]. This recommendation implies that individuals with higher BMI and increased fat mass are more likely to be accurately diagnosed with sarcopenia [32]. While the EWGSOP-2 recommended ASM-derived muscle mass indices (adjusted for height², weight, or BMI) to detect low muscle mass in older adults accurately, specific cut-off values are only provided for height-adjusted appendicular muscle mass. Consequently, given the increasing prevalence of obesity in Türkiye, it remains unclear which muscle mass index is most appropriate for older adults in this population.

According to 2022 data from the Turkish Statistical Institute, 41.6% of individuals aged 65 and older in Türkiye have a BMI ≥ 25 kg/m², classifying them as overweight [9]. Similarly, the World Health Organization’s 2022 data indicates that 43% of adults aged 18 and older globally are overweight [33]. These figures underscore a significant trend of obesity that extends beyond Türkiye, reflecting a broader global issue. As obesity rates continue to rise worldwide, it becomes crucial to adjust for body weight or BMI when diagnosing sarcopenia in older adults. Our study found that BMI-adjusted skeletal muscle mass indices (SMM/BMI and ASM/BMI) are independently associated with dynapenia in overweight individuals. These results support the utility of BMI-adjusted indices for sarcopenia assessment, highlighting their relevance not only within the Turkish context but also in line with global trends in managing both obesity and sarcopenia. By incorporating these indices globally, we can improve the accuracy of sarcopenia diagnosis across populations facing similar obesity trends.

The present study has both strengths and limitations. One limitation is that participants were recruited from a geriatric outpatient clinic rather than a population-based sample of community-dwelling older adults. Although our sample includes individuals who attend health check-ups, which may offer insights into the general older adult population, the representativeness of this sample may be influenced by selection bias. Future studies should aim to include a more representative, population-based sample to enhance the generalizability of the findings. Another limitation is that, as a cross-sectional study, we were unable to establish the relationship between longitudinal changes in physical function and body composition. While our study provides valuable information on the relationship between BMI-adjusted ASMI and physical performance in older Turkish adults, the generalizability of these findings to other populations may be limited due to differences in anthropometric and body composition characteristics, ethnic diversity, and measurement techniques. The height-adjusted muscle mass index proposed by the EWGSOP-2 may not be universally applicable. Further research involving diverse populations is necessary to validate and adapt these findings for a globally accurate diagnosis of sarcopenia.

One of the strengths of our study is its practical applicability to clinical practice. By employing bioelectrical impedance analysis (BIA) to estimate body composition, we utilized a method that is both straightforward and readily adaptable for routine clinical use. However, further research is needed to determine the predictive value of different appendicular muscle mass indices for functional adverse outcomes.

Conclusion

In summary, this study highlights that BMI–adjusted ASMI and BMI–adjusted SMMI exhibit strong correlations with functional parameters and are independently associated with dynapenia in older Turkish adults. Although our study does not directly diagnose sarcopenia, the correlation between these indices and functional measures provides valuable information regarding their potential utility in detecting sarcopenia. Further research is needed to explore their role in diagnosing sarcopenia and better understand their applicability in clinical practice.

Data availability

All data generated or analyzed during this study is available for requests and can be obtained from the corresponding author.

Abbreviations

ADL:

Activity of daily living

ASM:

Appendicular skeletal muscle mass

ASMI:

Appendicular skeletal muscle mass index

BMI:

Body mass index

FFP:

Fried frailty phenotype

GDS:

Geriatric depression scale

IADL:

Instrumental activity of daily living

MNA:

Mini nutritional assessment short form

SMM:

Skeletal muscle mass

SMMI:

Skeletal muscle mass index

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Authors and Affiliations

  1. Faculty of Medicine, Department of Geriatric Medicine, Gazi University, Ankara, 06560, Türkiye

    Esra Cataltepe, Eda Ceker, Ayse Fadiloglu & Hacer Dogan Varan

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  1. Esra Cataltepe
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Contributions

E.C. contributed to the concept and design of the study, acquisition, analysis, and drafting of the manuscript; E.C. and A.F. equally contributed to the acquisition and analysis of data; H.D.V. contributed to the statistical analysis with data interpretation, auditing and reviewing the manuscript. All authors critically revised the manuscript, agreed to be fully accountable for ensuring the integrity and accuracy of the work, and read and approved the final manuscript.

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Correspondence to Esra Cataltepe.

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Cataltepe, E., Ceker, E., Fadiloglu, A. et al. Relationship between different muscle mass indices and physical performance measures in Turkish older adults. BMC Geriatr 24, 875 (2024). https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-024-05418-y

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  • DOI: https://doiorg.publicaciones.saludcastillayleon.es/10.1186/s12877-024-05418-y

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BMC Geriatrics

ISSN: 1471-2318

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