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Prevalence & correlates of dynapenia in elderly with low skeletal muscle mass: A hospital-based cross-sectional study
For correspondence: Dr Tejeswini C.J., Department of Geriatrics, JSS Medical College & Hospital, JSS Academy of Higher Education and Research, Mysuru 570 015, Karnataka, India e-mail: docteju27@gmail.com
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Received: ,
Accepted: ,
Abstract
Background & objectives
Dynapenia, an age-related decline in muscle strength independent of muscle mass loss, is increasingly recognised as a predictor of functional decline and adverse health outcomes. This study aimed to investigate the prevalence and predictors of dynapenia among older adults with low skeletal muscle mass.
Methods
This hospital-based cross-sectional study included 128 participants aged ≥ 60 yr with low muscle mass determined using the EWGSOP-2 criteria. Assessments included handgrip strength using a Jamar dynamometer, a 4-meter gait speed test, the geriatric depression scale, and the clinical frailty scale. Pearson’s correlation was used to assess the relationships between muscle strength parameters, gait speed, frailty scores, and depression scores, followed by multivariate logistic regression.
Results
Among individuals with low muscle mass, 66 (51.6%) had dynapenia [29 (43.9%) in females; 37 (56.06%) in males]. Handgrip strength strongly and positively correlated with knee extension strength [coefficient correlation (r) = 0.822, P<0.001] and moderately correlated with gait speed (r=0.414, P<0.001). Both strength parameters were inversely correlated with frailty scores (r=-0.367 and r=-0.316, respectively; P<0.001). Multivariable analysis identified female gender [Odds ratio (OR)=7.655, 95% confidence interval (CI): 1.616-36.264, P=0.010], lower socioeconomic status (P<0.001), and gait speed <0.8 m/s (OR=22.664, 95% CI: 2.952-174.010, P=0.003) as predictors of dynapenia. Depression was more prevalent in dynapenia patients [25.8% (n=17) vs. 3.2% (n=2), P<0.001].
Interpretations & conclusions
The prevalence of dynapenia was 51.6 per cent among elderly with low muscle mass, with female sex, lower socioeconomic status, and reduced gait speed as significant correlates. Routine strength assessment is warranted in elderly with low muscle mass.
Keywords
Dynapenia
muscle strength
older adult
physical performance
sarcopenia
South India
The global population is undergoing a demographic shift, with an increasing proportion of older adults. By 2030, one in six people worldwide will be aged 60 years or older, with those aged 80 years or older reaching 426 million by 20501. This aging trend has resulted in an increase in chronic diseases and disabilities, challenging healthcare systems2.
Among the key health issues, musculoskeletal decline significantly impacts older adults. Sarcopenia, characterised by the loss of skeletal muscle mass and strength, is strongly correlated with frailty, falls, and mortality3. Evidence shows that muscle strength is a better predictor of functional ability than muscle mass alone. This condition, dynapenia, refers to age-related muscle strength loss not solely due to low muscle mass4 and is linked to disability, cognitive impairment, and reduced quality of life5.
The relationship between muscle mass and strength is complex and is influenced by neuromuscular function, muscle quality, and metabolic health6. Studies have shown that muscle strength decline can occur independently of muscle mass changes7. Alcazar et al5 (2018) found that low muscle strength better predicted mortality than low muscle mass. Despite the importance of dynapenia, research on its prevalence remains limited in low- and middle-income countries such as India. International cutoffs for low muscle mass may not predict low muscle strength in this population. The challenges faced by older adults in India, including comorbidities and limited healthcare access, may increase this risk8. This study investigated the prevalence of dynapenia among older adults with low skeletal muscle mass and explored associated factors, including comorbidities, socioeconomic status, and psychosocial aspects.
Materials & Methods
This hospital-based cross-sectional study was undertaken by the department of Geriatrics, JSS Medical College & Hospital, Mysuru, Karnataka, India between October 2022 and April 2024. Ethical approval was obtained from the Institutional Ethics Committee, and written informed consent was obtained from the participants.
Study design and participants
The study included older adults (aged ≥ 60 yr) who attended the geriatric outpatient department (OPD) or were admitted to the geriatric inpatient wards. Participants were recruited using consecutive sampling to ensure a representative study sample. The inclusion criteria included individuals diagnosed with low skeletal muscle mass, defined using the EWGSOP-2 criteria3: appendicular skeletal muscle mass index (ASMI) <7.0 kg/m2 for males and <5.5 kg/m2 for females. It was essential for participants to be ambulatory and clinically stable to ensure an accurate assessment of muscle strength and physical performance.
Sample size calculation
The sample size was calculated based on a 21.5 per cent prevalence of sarcodynapenia from previous literature9, yielding 116 participants (increased to 128, accounting for a 10% non-response).
Data collection
Data collection included demographics, socioeconomic status (modified Kuppuswamy scale)10, comorbidities, depression (geriatric depression scale)11, and frailty (clinical frailty scale)12 scores.
Muscle mass
Appendicular skeletal muscle mass index (ASMI) was calculated using anthropometric measurements based on Kawakami et al’s formula13, incorporating arm, thigh, and calf circumferences, weight, and height.
Muscle strength
Handgrip strength was measured using a Jamar dynamometer with the participants seated and their elbows flexed at 90°. The maximum value from three trials per hand was recorded. Dynapenia was defined as handgrip strength <27 kg for men and <16 kg for females3. Knee extension strength was measured using a handheld dynamometer at the distal tibia with the knee flexed at 90°. The highest value from three contractions per leg was normalised to body weight (knee extension strength/Wt). Dynapenia was defined as knee extension strength ≤ 0.34 kg/body weight for males and ≤ 0.24 kg/body weight for females14. Gait speed was assessed using a 4-meter walk test15. The fastest of the two trials was used, with <0.8 m/s indicating poor physical performance according to the EWGSOP-2 criteria3.
Statistical analysis
Data were entered into Microsoft Excel 2019 and analyzed using SPSS version 25 (IBM Corp., Armonk, NY, USA). Descriptive statistics were used to summarise the demographic and clinical characteristics. The prevalence of dynapenia was calculated based on handgrip strength, knee extension to body weight ratio, and gait speed. Pearson’s correlation coefficient was used to assess the relationships between muscle strength parameters, gait speed, frailty, and depression scores. Statistical significance was set at P<0.05. Odds ratios with 95 per cent confidence intervals (CI) were calculated to identify potential risk factors associated with dynapenia.
Results
The study included 128 participants. Their baseline and demographic characteristics are shown in table I.
| Characteristic | Overall (n=128) | Males (n=71) | Females (n=57) |
|---|---|---|---|
| Age (yr) | |||
| Mean±SD | 69.8±4.7 | 70.61±4.8 | 68.9±4.4 |
| Young-old (60-74), n (%) | 107 (83.6) | 55 (77.5) | 52 (91.2) |
| Middle-old (75-84), n (%) | 21 (16.4) | 16 (22.5) | 5 (8.8) |
| Socioeconomic status, n (%) | |||
| Lower (< 5) | 6 (4.7) | 6 (8.4) | - |
| Upper lower (5-10) | 31 (24.2) | 20 (28.1) | 11 (19.3) |
| Lower middle (11-15) | 45 (35.2) | 19 (26.8) | 26 (45.6) |
| Upper middle (16-25) | 38 (29.7) | 24 (33.8) | 14 (24.6) |
| Upper (26-29) | 8 (6.2) | 2 (2.8) | 6 (10.5) |
| Family type, n (%) | |||
| Nuclear | 50 (39.1) | 21 (29.6) | 29 (50.9) |
| Joint | 78 (60.9) | 50 (70.4) | 28 (49.1) |
| Comorbidities, n (%) | |||
| Type 2 diabetes mellitus | 52 (40.6) | 24 (33.8) | 28 (49.1) |
| Hypertension | 44 (34.4) | 27 (38.0) | 17 (29.8) |
| Chronic obstructive pulmonary disease | 26 (20.3) | 9 (12.7) | 20 (35.1) |
| Ischemic heart disease | 24 (18.8) | 21 (29.6) | 3 (5.3) |
| Hypothyroidism | 13 (10.2) | 6 (8.5) | 7 (12.3) |
| Others* | 48 (37.5) | 20 (28.2) | 30 (52.6) |
| Comorbidities absent | 12 (9.4) | 8 (11.3) | 4 (7.0) |
| No. of comorbidities, Mean±SD | 1.63±0.9 | 1.51±0.9 | 1.79±0.9 |
| Psychosocial characteristics | |||
| Depression (GDS score ≥5), n (%) | 19 (14.8) | 6 (8.5) | 13 (22.8) |
| GDS score, Mean±SD | 1.57±2.1 | 1.34±1.7 | 1.86±2.4 |
| Frailty status (CFS), n (%) | |||
| Well (2) | 10 (7.8) | 9 (12.7) | 1 (1.8) |
| Managing well (3) | 73 (57.0) | 39 (54.9) | 34 (59.7) |
| Vulnerable (4) | 37 (28.9) | 22 (31.0) | 15 (26.3) |
| Mildly frail (5) | 8 (6.3) | 1 (1.4) | 7 (12.3) |
| CFS score, Mean±SD | 3.34±0.7 | 3.21±0.7 | 3.49±0.7 |
| Anthropometric measurements | |||
| Weight (kg), Mean±SD | 50.40±7.8 | 52.53±8.6 | 47.74±5.6 |
| Height (cm), Mean±SD | 158.92±6.1 | 162.46±5.2 | 154.52±3.8 |
| BMI (kg/m2), Mean±SD | 19.92±2.6 | 19.89±3.0 | 19.96±2.0 |
| Underweight: <18.5, n (%) | 17 (13.3) | 10 (14.1) | 7 (12.3) |
| Healthy weight: 18.5 to 24.9, n (%) | 108 (84.4) | 58 (81.7) | 50 (87.7) |
| Overweight: 25.0 to 29.9, n (%) | 3 (2.3) | 3 (4.2) | 0 |
BMI, body mass index; CFS, clinical frailty scale; GDS, geriatric depression scale; SD, standard deviation
Handgrip strength was strongly correlated with the knee extension strength-to-weight ratio (r=0.8, P<0.001) and moderately correlated with gait speed [coefficient correlation (r)=0.4, P<0.001]. Both strength parameters correlated negatively with the CFS scores (r=-0.4 and r=-0.3, P<0.001). Gait speed was negatively correlated with frailty scores (r=-0.5, P<0.001). Depression scores were not significantly correlated with strength or physical performance (Supplementary Table I).
Prevalence and characteristics of dynapenia
The prevalence of dynapenia was 51.6 per cent based on the handgrip strength criteria (Table II). Age and sex distributions showed no differences between the dynapenic and non-dynapenic groups. Dynapenia was associated with a lower socioeconomic status (P=0.020) and higher depression prevalence (25.8% vs. 3.2%, P<0.001). Frailty status differed between groups (P=0.005), with CFS scores of 3.6±0.7 in the dynapenic group versus 3.03±0.54 in the non-dynapenic group. Dynapenia was more prevalent in underweight (76.5%) than in normal-weight participants (46.3%) (Table III).
| Parameter | Overall (n=128) | Males (n=71) | Females (n=57) | P value |
|---|---|---|---|---|
| Criterion 1: Low muscle strength (primary criterion) | ||||
| Handgrip strength (HGS) | < 0.001 | |||
| Mean±SD (kg) | 20.6±5.8 | 24.3±5.0 | 15.9±2.6 | |
| Low HGS^, n (%) | 66 (51.6) | 37 (52.1) | 29 (50.9) | |
| By age group, n (%) | ||||
| Young-old (60-74 yr) | 53 (41.4) | 29 (40.9) | 24 (42.1) | |
| Middle-old (75-84 yr) | 13 (10.2) | 8 (11.3) | 5 (8.8) | |
| Knee extension strength (KES) | < 0.001 | |||
| KES/Wt., Mean±SD | 0.3±0.06 | 0.3±0.04 | 0.2±0.03 | |
| Low KES/Wt†, n (%) | 77 (60.2) | 40 (56.3) | 37 (64.9) | |
| By age group, n (%) | ||||
| Young-old (60-74 yr) | 61 (47.7) | 29 (40.9) | 32 (56.1) | |
| Middle-old (75-84 yr) | 16 (12.5) | 11 (15.5) | 5 (8.8) | |
| Criterion 2: Low muscle quantity or quality (confirms diagnosis) | ||||
| Appendicular skeletal muscle mass (ASM) | < 0.001 | |||
| ASM (Kg), Mean±SD | 14.2±3.2 | 16.2±2.9 | 11.8±1.6 | |
| Low ASM#, n (%) | 126 (98.4) | 69 (97.2) | 57 (100.0) | |
| By age group, n (%) | ||||
| Young-old (60-74 yr) | 106 (82.8) | 54 (76.1) | 52 (91.2) | |
| Middle-old (75-84 yr) | 20 (15.6) | 15 (21.1) | 5 (8.8) | |
| Appendicular skeletal muscle index (ASMI) | < 0.001 | |||
| ASMI (kg/m2), Mean±SD | 5.6±0.1 | 6.18±0.9 | 4.9±0.6 | |
| Low ASMI¶, n (%) | 120 (93.8) | 63 (88.7) | 57 (100.0) | |
| By age group, n (%) | ||||
| Young-old (60-74 yr) | 101 (78.9) | 49 (69.0) | 52 (91.2) | |
| Middle-old (75-84 yr) | 19 (14.8) | 14 (19.7) | 5 (8.8) | |
| Criterion 3: Low physical performance (identifies severity) | ||||
| Gait Speed | 0.44 | |||
| Mean±SD (m/s) | 0.8±0.1 | 0.8±0.1 | 0.8±0.2 | |
| Low gait speed‡, n (%) | 56 (43.8) | 29 (40.9) | 27 (47.4) | |
| By age group, n (%) | ||||
| Young-old (60-74 yr) | 43 (33.6) | 21 (29.6) | 22 (38.6) | |
| Middle-old (75-84 yr) | 13 (10.2) | 8 (11.3) | 5 (8.8) | |
| Sarcopenia (HGS + ASMI + Gait) | ||||
| Severe sarcopenia§ | 34 (26.6) | 15 (21.1) | 19 (33.4) | 0.12 |
| By age group, n (%) | ||||
| Young-old (60-74 yr) | 23 (18.0) | 9 (12.7) | 14 (24.6) | |
| Middle-old (75-84 yr) | 11 (8.6) | 6 (8.5) | 5 (8.8) | |
^Hand grip strength <27 kg for males and <16 kg for females; †Knee extension strength-to-weight ratio ≤0.34 for males and ≤0.24 for females; #Appendicular skeletal muscle mass (ASM): <20 kg for men, <15kg for women; ¶ASM/height 2 : <7.0 kg/m2 for men,<5.5 kg/m2 for women; ‡Gait speed <0.8 m/s; §Presence of low muscle mass, low muscle strength, and poor physical performance (all three criteria met)
| Characteristic | Overall (n=128) | Dynapenia present (n=66) | Dynapenia absent (n=62) | P value |
|---|---|---|---|---|
| Age (yr) | 0.30 | |||
| Mean±SD | 69.8±4.7 | 70.2±4.6 | 69.5±4.8 | |
| Young-old (60-74), n (%) | 107 (83.6) | 53 (80.3) | 54 (87.1) | |
| Middle-old (75-84), n (%) | 21 (16.4) | 13 (19.7) | 8 (12.9) | |
| Gender, n (%) | 0.9 | |||
| Female | 57 (44.5) | 29 (43.9) | 28 (45.2) | |
| Male | 71 (55.5) | 37 (56.1) | 34 (54.8) | |
| Socioeconomic status, n (%) | 0.02^ | |||
| Lower (< 5) | 6 (4.7) | 6 (9.1) | ||
| Upper lower (5-10) | 31 (24.2) | 19 (28.8) | 12 (19.4) | |
| Lower middle (11-15) | 45 (35.2) | 24 (36.4) | 21 (33.9) | |
| Upper middle (16-25) | 38 (29.7) | 16 (24.2) | 22 (35.5) | |
| Upper (26-29) | 8 (6.3) | 1 (1.5) | 7 (11.3) | |
| Family type, n (%) | 0.24 | |||
| Nuclear | 50 (39.1) | 29 (43.9) | 21 (33.9) | |
| Joint | 78 (60.9) | 37 (56.1) | 41 (66.1) | |
| Comorbidities, n (%) | 0.58 | |||
| Type 2 diabetes mellitus | 52 (40.6) | 22 (33.3) | 30 (48.4) | |
| Hypertension | 44 (34.4) | 17 (25.8) | 27 (43.6) | |
| COPD | 26 (20.3) | 22 (33.3) | 4 (6.5) | |
| IHD | 24 (18.8) | 10 (15.2) | 14 (22.6) | |
| Hypothyroidism | 13 (10.2) | 7 (10.6) | 6 (9.7) | |
| Others* | 48 (37.5) | 24 (36.4) | 26 (41.9) | |
| Comorbidities absent | 12 (9.4) | 5 (7.6) | 7 (11.3) | |
| No. of comorbidities, Mean±SD | 1.63±0.9 | 1.55±0.8 | 1.73±1.0 | |
| Psychosocial characteristics | 0.00^ | |||
| Depression (GDS score ≥5), n (%) | 19 (14.8) | 17 (25.8) | 2 (3.2) | |
| GDS score, Mean±SD | 1.6±2.1 | 2.1±2.5 | 1.0±1.3 | |
| Frailty status (CFS), n (%) | 0.005^ | |||
| Well (2) | 10 (7.8) | 2 (3.0) | 8 (12.9) | |
| Managing well (3) | 73 (57) | 29 (43.9) | 44 (71.) | |
| Vulnerable (4) | 37 (28.9) | 27 (40.9) | 10 (16.1) | |
| Mildly frail (5) | 8 (6.3) | 8 (12.1) | - | |
| CFS score, Mean±SD | 3.3±0.7 | 3.6±0.7 | 3.0±0.5 | |
| Anthropometric measurements | ||||
| Weight (kg), Mean±SD | 50.4±7.8 | 49.5±9.6 | 51.4±5.1 | 0.2 |
| Height (cm), Mean±SD | 158.9±6.1 | 158.3±6.3 | 159.5±5.9 | 0.38 |
| BMI (kg/m2), Mean±SD | 19.9±2.6 | 19.7±3.4 | 20.2±1.4 | 0.016^ |
| Underweight:<18.5, n (%) | 17 (13.3) | 13 (19.7) | 4 (6.5) | |
| Healthy weight: 18.5 to 24.9, n (%) | 108 (84.4) | 50 (75.8) | 58 (93.6) | |
| Overweight: 25.0 to 29.9, n (%) | 3 (2.3) | 3 (4.6) |
CFS, clinical frailty scale; GDS, geriatric depression scale; IHD, ischemic heart disease
Multivariate analysis
Logistic regression identified four independent predictors of dynapenia: female sex (P=0.010), socioeconomic status (lower middle and upper middle classes; P<0.001 and P=0.011, respectively), and gait speed <0.8 m/s (P=0.003). Age, family structure, comorbidity, depression, and frailty scores showed no independent associations. Confidence intervals for some variables could not be estimated because of insufficient sample sizes (Supplementary Table II).
Discussion
This cross-sectional study provides insights into the prevalence and predictors of dynapenia in older adults with low skeletal muscle mass. Geriatric research has shifted from focusing on muscle mass to emphasising muscle strength and function in older adults. Our findings support this shift, showing that muscle strength correlates better with physical performance than muscle mass alone, aligning with the findings of Newman et al16 who showed that muscle strength better predicts mobility limitations and mortality.
The prevalence of dynapenia in our study [66 (51.6%)] exceeded that reported in high-income countries. Bae et al17 found rates of 19.2 per cent, 29.1 per cent, and 42.3 per cent among the age groups 20–39, 40–64, and ≥ 65 yr in Korea18, while Pérez-Sousa et al19 reported 46.5 per cent probable sarcopenia in Colombian older adults. Chinese rural population is 69.6 per cent prevalence19, while those in the Japanese, Brazilian, and Mexican populations are 10.3 per cent, 17.2 per cent, and 33.9 per cent, respectively20-22. This disparity stems from our focus on individuals with low skeletal muscle mass and the socioeconomic differences between high- and middle-income countries. Our findings align with other middle-income country studies, such as Southern India’s age-wise prevalence of 72.21 per cent23, and Brazilian older adults’ rates of 13.4 per cent for sarcopenia and 29.5 per cent for dynapenia24. These variations highlight the need for region-specific reference values and underscore the influence of population-specific factors on muscle strength during aging.
Our analysis identified female sex as a predictor of dynapenia (OR=7.7, 95% CI: 1.6-36.3, P=0.010). This sex disparity aligns with previous studies and may be attributed to lower baseline muscle mass, hormonal differences, and varying physical activity levels25. Indian sociocultural factors, including gender-based differences in nutrition and physical activity, may contribute to these disparities. Socioeconomic status was another significant predictor, with higher odds in the lower middle (OR=243.9, P<0.001) and upper middle classes (OR=20.2, P=0.011) compared to the upper class. Limited access to nutrition, healthcare, and physical activity opportunities among lower socioeconomic groups may accelerate muscle strength decline26. Health promotion initiatives often fail to reach lower socioeconomic groups27.
The association between gait speed and dynapenia (OR=22.7, 95% CI: 3.0-174.0, P=0.003) demonstrated the functional impact of reduced muscle strength. Handgrip strength showed a moderate positive correlation with gait speed (r=0.4, P<0.001), indicating the utility of muscle strength assessment in predicting mobility limitations. The correlation between strength parameters and frailty scores (handgrip: r=-0.4, P<0.001; knee extension: r=-0.3, P<0.001) supports the role of dynapeniain frailty syndrome, aligning with the framework proposed by Fried et al28, which identifies weakness as a key frailty component. Depression was significantly more prevalent among patients with dynapenia (25.8% vs. 3.2%, P<0.001). The relationship between depression and diminished muscle strength may be bidirectional. Depression can lead to decreased physical activity, poor nutrition, and altered neuroendocrine function, contributing to muscle weakness29. Conversely, dynapenia may reduce social participation and cause psychological distress, consistent with the findings of Hsu et al’s findings30.
Our study showed a significant association between BMI and dynapenia (P=0.016), with a higher prevalence in underweight patients (76.5%) than in those with normal weight (46.3%). Although BMI was not a predictor in the multivariate analysis, the bivariate association highlights the role of nutritional status in preserving muscle strength. This aligns with research linking undernutrition to diminished muscle strength in older adults31.The high prevalence of dynapenia among older adults with low muscle mass has key clinical implications. Regular muscle strength evaluation is essential during geriatric assessments, particularly in at-risk individuals. Handgrip dynamometry may serve as a practical proxy for overall muscle strength when advanced assessment tools are unavailable32.The association between dynapenia and modifiable factors suggests opportunities for targeted interventions, such as exercise programs, nutritional education, and social support. The co-occurrence of dynapenia and other geriatric syndromes necessitates a comprehensive multidisciplinary approach to care.
The strength of our study lies in its comprehensive evaluation of muscle strength, physical performance, and associated factors in a population understudied for dynapenia in South India. However, this study has several limitations. The cross-sectional design prevented causal inferences about the relationship between dynapenia and associated factors. Hospital-based sampling may have introduced selection bias, limiting generalisability to the broader community-dwelling older adult population. Our sample from a tertiary care hospital may have had more comorbidities than the general elderly population. The use of anthropometric measurements for muscle mass assessment, rather than DXA or BIA, may have limited precision, although the equation used has been validated in Asian populations. The small sample size resulted in wide confidence intervals and constrained assessment of the association between some variables and dynapenia. Furthermore, medications prescribed for the management of diabetes mellitus and hypertension, along with any previous surgical procedures, might have influenced the outcomes related to muscle strength. These medications can impact muscle function through various mechanisms, such as metabolic effects, electrolyte imbalances, and exercise capacity. Additionally, surgical interventions may affect physical function and recovery. These factors are potential confounders that should be taken into account when interpreting the results.
This study found a significant prevalence of dynapenia among older adults, particularly in women, lower socioeconomic groups, and those with poor physical performance. These findings highlight the multifactorial nature of dynapenia, emphasising the need to address the biological and social determinants of muscle strength in older adults. Regular strength assessment and targeted interventions may help mitigate the effects of dynapenia and promote healthy aging.
Financial support & sponsorship
None.
Conflicts of Interest
None.
Use of Artificial Intelligence (AI)-Assisted Technology for manuscript preparation
The authors confirm that there was no use of AI-assisted technology for assisting in the writing of the manuscript and no images were manipulated using AI.
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