Skeletal muscle assessment in older women with osteoporosis

Avaliação da musculatura esquelética em mulheres idosas com osteoporose

Abstract

Introduction:  Older women experience higher rates of falls, musculoskeletal diseases, and muscle loss, leading to functional limitations. The relationships between different muscle assessment methods and physical function in older women with osteoporosis remain insufficiently explored.

Objective:  To explore the agreement between bioelectrical impedance analysis (BIA) and dual-energy X-ray absorptiometry (DXA) for skeletal muscle mass assessment and the associations of ultrasound-derived and anthropometric muscle measures with physical function in older women with osteoporosis. Muscle quality (MQ) was evaluated as a secondary outcome.

Methods:  This exploratory cross-sectional study included 11 older women with osteoporo-sis (76.5 ± 8.9 years). Appendicular skeletal muscle mass (ASM) was assessed using BIA and DXA. Vastus lateralis muscle architecture was evaluated by ultrasound, and thigh circumference was measured anthropometrically. Muscle strength, lower-limb power, gait speed, Timed Up and Go, and the Short Physical Performance Battery were assessed. MQ was calculated as the ratio of handgrip strength to ASM.

Results:  No agreement was observed between BIA and DXA for ASM. Muscle thickness was positively correlated with handgrip strength (ρ = 0.644; p = 0.033), and fascicle length was positively correlated with gait speed (ρ = 0.617; p = 0.043). MQ differed ac-cording to the method used to estimate muscle mass, with lower values using BIA than DXA (1.52 ± 0.47 vs. 1.81 ± 0.50; p = 0.001 ).

Conclusion:  In this exploratory sample, agreement between BIA and DXA for skeletal muscle mass assessment was low. Ultrasound-derived muscle measures showed positive associations with selected indicators of physical function, whereas MQ estimates varied according to the method used to assess muscle mass.

Keywords:
Female; Osteoporosis; Ultrasonography; Absorptiometry; Electric impedance

Resumo

Introdução:  Mulheres idosas apresentam taxas mais elevadas de quedas, doenças musculoesqueléticas e perda de massa muscular, o que resulta em limitações funcionais. No entanto, as relações entre diferentes métodos de avaliação muscular e a função física em mulheres idosas com osteoporose permanecem insuficientemente exploradas.

Objetivo:  Investigar a concordância entre a análise de bioimpedância elétrica (BIA) e a absorciometria de raios-X de dupla energia (DXA) na avaliação da massa muscular esquelética, bem como as associações entre medidas musculares obtidas por ultrassonografia e antropometria e a função física em mulheres idosas com osteoporose. A qualidade muscular (QM) foi avaliada como desfecho secundário.

Métodos:  Este estudo transversal exploratório incluiu 11 mulheres idosas com osteoporose (76,5 ± 8,9 anos). A massa muscular esquelética apendicular (MMEA) foi avaliada por meio de BIA e DXA. A arquitetura do músculo vasto lateral foi avaliada por ultrassonografia e a circunferência da coxa foi mensurada. Foram avaliados a força muscular, a potência de membros inferiores, a velocidade da marcha e os testes Timed Up and Go e Short Physical Performance Battery. A QM foi calculada como a razão entre a força de preensão manual e a MMEA.

Resultados:  Não se observou concordância entre BIA e DXA para a MMEA. A espessura muscular correlacionou-se positivamente com a força de preensão manual (ρ = 0,644; p = 0,033), e o comprimento do fascículo correlacionou-se positivamente com a velocidade da marcha (ρ = 0,617; p = 0,043). A QM diferiu conforme o método utilizado para estimar a massa muscular, apresentando valores mais baixos com a BIA em comparação à DXA (1,52 ± 0,47 vs. 1,81 ± 0,50; p = 0,001).

Conclusão:  Nesta amostra exploratória, a concordância entre BIA e DXA para a avaliação da massa muscular esquelética foi baixa. As medidas musculares obtidas por ultrassonografia apresentaram associações positivas com indicadores selecionados de função física, enquanto as estimativas de QM variaram de acordo com o método utilizado para avaliar a massa muscular.

Palavras-chave:
Feminino; Osteoporose; Ultrassonografia; Absorciometria; Impedância elétrica

Introduction

Older women experience a higher incidence of falls, musculoskeletal diseases such as osteoporosis, and accelerated muscle loss than older men, resulting in greater functional limitations despite their longer life expectancy.¹ Reduced muscle mass, muscle strength, muscle quality (MQ), and impaired physical performance are recognized as important risk factors for falls, fractures, and reduced quality of life in older women with osteoporosis.², ³ Women receiving treatment for osteoporosis have been shown to present lower gait speed, reduced lower-limb muscle strength, limited ankle range of motion, and increased risk of falls.², ³

Evidence suggests that muscle strength, muscle mass distribution, and body composition^{4 6 7} play an important role in the clinical manifestations and functional repercussions of osteoporosis in older women.², ³ Rikkonen et al.⁸ demonstrated that postmenopausal women with osteoporosis had lower appendicular lean mass, handgrip strength (HGS), and knee extension strength than women without the disease. Similarly, Takahashi et al.⁹ reported lower skeletal muscle mass and gait speed in individuals with osteoporosis. In Brazil, Correa et al.³ observed poorer performance in mobility and muscle strength tests, while Correa et al.² found reduced isometric plantar flexion strength and poorer physical performance in women undergoing osteoporosis treatment. Together, these findings reinforce the importance of muscle assessment as part of the clinical evaluation of older women with osteoporosis.

Although muscle strength and greater lean mass have been associated with higher bone mineral density (BMD),⁶, ¹⁰ the relationships among muscle mass, muscle strength, and osteoporosis remain incompletely understood. Taniguchi et al.⁷ reported that osteoporosis was associated with reduced skeletal muscle mass but not with muscle weakness in older women. These findings suggest that evaluating both muscle quantity and MQ may contribute to a better understanding of musculoskeletal health in this population.

Several methods are available for muscle assessment, including bioelectrical impedance analysis (BIA), dual-energy X-ray absorptiometry (DXA), ultrasound (US), and anthropometric measurements such as thigh circumference (TC).⁴ BIA and DXA estimate appendicular skeletal muscle mass (ASM), whereas US provides information on muscle architecture through measurements of muscle thickness (MT), fascicle length (FL), and pennation angle (PA).¹¹,¹² Although these methods are widely used in clinical practice and research, they assess different aspects of skeletal muscle, making direct comparisons between their measurements and their relationships with physical function challenging. Evidence simultaneously evaluating these methods in older women with osteoporosis remains scarce, particularly regarding how muscle measures obtained by different techniques relate to physical function.

Although there is no universally accepted definition of MQ, one commonly adopted approach is the ratio between muscle strength and muscle quantity, as proposed by Barbat-Artigas et al.¹³ Emerging evidence suggests that MQ may be more closely associated with physical performance than muscle mass alone, as older women with better MQ tend to demonstrate superior functional performance, whereas reduced MQ is associated with poorer functional outcomes.¹³ Despite advances in understanding the musculoskeletal consequences of osteoporosis, the relationships among different muscle assessment methods, MQ, and physical function in older women with osteoporosis remain insufficiently explored. Exploring these relationships may contribute to identifying clinically useful assessment strategies and provide preliminary evidence to guide future confirmatory studies.

Given these knowledge gaps, we aimed to explore the agreement between BIA and DXA for estimating ASM and to investigate the associations of US-derived and anthropometric muscle measures with physical function in older women with osteoporosis. MQ was evaluated as a secondary outcome.

Methods

This exploratory cross-sectional study was conducted and reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology guidelines.¹⁴ The dataset used in the present study was derived from a larger research project registered at the Brazilian Registry of Clinical Trials (registration number RBR-7d6qr5f) and approved by the Human Research Ethics Committee of the Complexo Hospital de Clínicas, Universidade Federal do Paraná (CHC-UFPR), Curitiba, Brazil (approval number 3320592). Written informed consent was obtained from all participants prior to enrollment. The data collection of the previous study was conducted in the city of Curitiba, Brazil, from March 2020 to December 2022, and the analysis for the present study was done from May 2023 to July 2024.

A convenience sample of older women (≥ 65 years) with osteoporosis was recruited during their routine visit to the outpatient clinic in the Endocrinology and Metabolism Paraná Service at CHC-UFPR. Inclusion criteria were: diagnostic osteoporosis according to bone mineral densitometry measured using DXA, in the last 12 months, reduced by at least 2.5 standards deviations (SD) or more below the average value for young healthy women (T-score of <-2.5 SD in the lumbar spine [L1-L4] or femoral [neck or total] or wrist);¹⁵ cognitive status (score ≥ 18/19 or ≥ 24/25 according to the level of schooling); and normal body mass index (BMI).¹⁶

The exclusion criteria were acute or terminal illness; metabolic instability or decompensated cardiovascular disease; cognitive deficits; neurological disorders and/ or traumatic-orthopedic conditions that prevented the participant from conducting the evaluations; type I diabetes; taking medication that might affect muscle metabolism (e.g., corticoids); auditory deficit that prevents understanding of verbal instructions. All the criteria were proved by an endocrinologist, one of the authors of the present study (VZCB).

Study size

Given the exploratory nature of the study, no formal a priori sample size calculation was performed. A convenience sample was used, and all eligible older women with osteoporosis who met the inclusion criteria during the recruitment period were invited to participate. A total of 81 participants were initially evaluated for eligibility for the major study; however, 70 did not meet the inclusion criteria or were excluded due to the reasons mentioned in the flow chart of the study (Figure 1 ). Consequently, 11 participants completed all study assessments and were included in the analysis.

Figure 1
Flow chart of the study.

Variables

Muscle mass was the primary outcome for this study assessed by different methods: TC, DXA, BIA, and US. The secondary outcomes for this study were: muscle strength and quality and functional performance. Muscle strength was measured by handgrip; hand-held dynamometer for knee extensors and Five Times Sit to Stand (5TSTS) test. MQ was estimated by the ratio between strength and muscle mass. Moreover, fucntional performance by Timed Up and Go (TUG) test, 4-Meter Gait Speed Test, and Short Physical Performance Battery (SPPB).

Primary outcomes

Thigh circumference: TC was measured using a measuring tape of the dominant thigh at 50% of the distance between the greater trochanter and the lateral epicondyle of the femur, with the participant lying in the supine position. Values below 44 cm indicated low muscle mass.¹⁷

Dual-energy X-ray absorptiometry: body mass and height were measured using mechanical scales (Filizola, São Paulo, Brazil) and stadiometer (Tonelli, Criciúma, SC, Brazil). BMI was calculated as the ratio between body mass in kilograms and the square of height in meters (kg/m²) and calssified as underweight (< 18.5), normal (18.50 - 24.99), overweight (25 - 29.9), moderate obesity (30.0 - 39.9), and severe obesity (≥ 40).¹⁸ ASM was calculated by adding the lean mass of the lower (legs) and upper (arms) limbs in kilograms. Body composition analysis was performed using DXA with Lunar Prodigy Advance equipment (PA+302284, Lunar Radiation Corp., Madison, Wl, USA) and Encore software (version 12.10. 113, 2008; GE Medical Systems Lunar, Madison, Wl, USA), with a standard error of 1.6%. Precision errors for body composition were 0.87% for BMD, 2.32% for total fat mass, 1.67% for total lean mass, and 1.56% for percent body fat. The reference value for ASM was < 15 kg, indicating a reduction in muscle mass.¹⁹

Bioelectrical impedance analysis: BIA was performed using a tetrapolar body composition analysis device (Maltron BioScan 916/916S), with an impedance of 100 to 1000 Ω, precision of ±3 Ω, and a frequency of 50 kHz. BIA devices with 50 kHz are widely used to predict fat-free mass and, therefore, were chosen for the present study. The measurement was applied on the right side of the body, with the participant lying supine, arms positioned at a 45° angle to the body, and legs slightly apart, on a non-conducting surface. Constant hydration was assumed since older women did not present edema or signs of dehydration at the time of anthropometric and BIA assessment.

Height and weight were measured on the same day the BIA exam was performed. The source electrodes (distal) were fixed just below the third metacarpal-phalangeal and metatarsal-phalangeal joints, and the sensor electrodes (proximal) were placed on the dorsal surface of the wrist joint and the dorsal portion of the ankle joint.²⁰ The formula proposed by Sergi et al.²¹ was used to calculate ASM via BIA: ASM (kg) = (-3.964) + (0.227 x Resistance) + (0.095 x Body mass) + (1.384 x 0) + (0.064 x Reactance). This equation was developed to estimate ASM in free-living Caucasian older adults, providing a reliable method for muscle mass assessment in this population, and the reference value for ASM was < 15 kg, indicating a reduction in muscle mass.⁴, ¹⁹

Ultrasound: muscle architecture of the vastus lateralis muscle was assessed using US equipment (Chison Eco Vet 1) in B-mode with a linear transducer (10.0 MHz), with depth adjusted to 5 cm. Although the Chison ECO Vet 1 US system is commercially marketed for veterinary applications, its imaging performance was verified before participant assessment. Image quality testing was performed using a Multi-Purpose Multi-Tissue Ultrasound Phantom (Model 040GSE; Zerdine Inside, ABS Plastic) following the protocol proposed by Brazilian Normative Instruction No. 96/2021²² for diagnostic US quality assurance. Image uniformity, sensitivity, geometric distortion, height-to-width ratio, and axial and lateral resolution were evaluated and considered satisfactory before data collection.

The assessment was conducted only on the right vastus lateralis muscle, with the participant lying supine, knees fully extended, and muscles relaxed. Three images were collected at 50% of the distance between the greater trochanter and the lateral epicondyle of the femur. The probe was parallel to the muscle fibers and coated with water-soluble transmission gel, ensuring acoustic contact without depressing the dermal surface. To obtain muscle MT, the distance between deep and superficial fascial planes was measured at five points along the US image, and their mean value was used. PA was defined as the insertion angle of muscle fiber fascicles into the deep fascial plane, and FL was defined as the length of the fascicle from the superior to deep fascial planes. If the end of the fascicle extended beyond the acquired US images, FL was estimated using a trigonometric function, according to Abellaneda et al.²³ All images were analyzed using Image J software (version 1.46r). Evaluations and measurements were performed by a single researcher who had been previously trained. The references values were MT < 15.5 mm,²⁴ FL 115 mm, and PA < 11.9° ²⁵ indicating a reduction in muscle mass.

Secondary outcomes

Handgrip strength: HGS was assessed using a handgrip dynamometer (Saehan SH5001). Participants seated on a chair lacking armrests, feet flat on the ground, with hips and knees flexed at a 90° angle. Shoulders were positioned in adduction and neutral rotation, while elbows were bent at a 90° angle, and forearms and wrists maintained a neutral position. Participants were instructed to exert maximal force with their dominant hand for three seconds, repeating the action three times with 1-2 minutes of rest between each attempt. HGS was defined as the highest among the three trials. The dynamometer's grip was adjusted individually based on the participant's hand size. A result below 16 kg indicated low muscle strength.⁴

Isometric knee extensors strength: muscle strength of the knee extensors was assessed using a hand-held dynamometer (model 01165; Lafayette Instrument Company, Lafayette, Indiana, USA). Participants seated with hips and knees flexed at 90°. The dynamometer was placed on the anterior aspect of the shin, proximal to the ankle joint. Participants performed maximal isometric contraction for five seconds with encouragement by voice command from a single experienced assessor.²⁶ Two repetitions were performed with the non-dominant limb for familiarization, followed by three repetitions with the dominant limb. There was a 30s rest between the repetitions. Values below 36 (±7) kg indicated low knee extensors strength.²⁷

Five Times Sit to Stand test: participants were instructed to stand up and sit on an armless chair five times as fast as possible, with their arms crossed on their chest, terminating in standing.²⁸ The test was repeated three times with 5-minutes interval between trials. The time to perform the test was recorded, and the three trials' average was used for analysis. A cut-off points of >15 s was adopted to indicate poor physical performance.⁴

Functional performance

Timed Up and Go: The functional mobility was assessed by test TUG. The instructions to the participants were: "Stay seated, and on the command 'go' please rise from the chair and walk at a comfortable and safe pace to the line drawn on the floor three meters away, turn around, return to your chair and sit down again".²⁹ The test was carried out once for familiarization and a second time for timing. It was scored following the reference value for an age range of 60-69 years old: 8.1 (7.1-9.0) s; 70-79 years old: 9.2 (8.2-10.2) s; 80-99 years old: 11.3 (10.0-12.7) s.²⁹ Values below those mentioned indicate muscle weakness.

Short Physical Performance Battery: SPPB is a set of measures that combines the results of gait speed, standing up from a chair, and balance tests. The scores range from 0 (worst performance) to 12 (best performance), and a score below or equal to 8 points indicates poor physical performance.⁴ The total SPPB score is obtained by summing the scores of each test, ranging from zero (unable or very poor performance) to 12 points (good performance). The scores can be classified as follows: unable or very poor performance (0-3 points); low performance (4-6 points); moderate performance (7-9 points); and good performance (10-12 points).³⁰

Gait speed 4 meters: a 4-meter course was marked on a flat surface to assess gait speed. The participant was instructed to start walking from a stationary position and walk at normal pace until crossing the finish line. The time taken to cover the distance was recorded with a stopwatch. Gait speed was calculated by dividing the distance (4 meters) by the recorded time (in seconds), resulting in speed in meters per second (m/s). A gait speed below 0.8 m/s was used as the cut-off point.³¹

Muscle quality: MQ was calculated as the ratio between HGS and ASM, following the operational definition proposed by Barbat-Artigas et al.,¹³ in which MQ is expressed as muscle strength per unit of muscle mass. Because ASM was estimated using both BIA and DXA, MQ was calculated separately for each method (MQ_BIA and MQ_DXA) to explore the influence of the muscle mass assessment technique on MQ estimates. MQ was classified as normal (> 1.53 kgf/kg), low (≤ 1.53 kgf/kg), and poor (≤ 1.35 kgf/kg).¹³ Because these cut-off values were originally proposed within a conceptual framework based on BIA-derived muscle mass, MQ values obtained using DXA should be interpreted as exploratory.

Bias and statistical analysis

To minimize selection bias, standardized inclusion and exclusion criteria were applied, and all participants were recruited from the same outpatient clinic during the study period. Data extraction and verification were independently performed by two trained researchers. Restricting the sample to women with normal BMI aimed to reduce potential confounding in muscle mass and MQ measurements. Because this was an exploratory study, the findings should be interpreted as hypothesis-generating rather than confirmatory.

Statistical analysis was performed using the statistics software IBM SPSS (version 21). The results were described as mean ± SD since the data presented a normal distribution, as assessed by the Shapiro-Wilk normality test. Missing data from the sample led to the exclusion of participants, as described in Figure 1.

Agreement between ASM and ASM index measurements obtained by DXA and BIA (ASM_DXA and ASM_BIA) was assessed using the intraclass correlation coefficient (ICC). A two-way mixed-effects model with absolute agreement and single measurements was adopted. Additionally, Bland-Altman analysis was performed to evaluate agreement between methods by calculating the mean difference (bias) and the 95% limits of agreement. The Pearson correlation coefficient was applied to evaluate the correlation between muscle mass, muscle architecture, muscle strength, MQ, and functional performance, as the variables presented normal distribution according to the Shapiro-Wilk test. The values from 0.90 to 1.00 were considered a very high correlation; 0.70 to 0.90, high correlation; 0.50 to 0.70, moderate correlation; 0.30 to 0.50, low correlation.³² MQ BIA and MQ DXA were compared using the paired samples t-test. A significance level of p < 0.05 was considered for all the analyses.

Results

The sample consisted of 11 older women with a mean age of 76.5 ± 8.9 years, norrmal BMI (24.9 ± 3.6 kg/m²) and osteoporosis according to lumbar spine T-score values (-3.0 ± 1.0), while femoral neck T-score values were compatible with osteopenia (-2.0 ± 1.1) (Table 1).

Table 1
Characteristics of the sample (n = 11 )

Variables	Mean (SD)	Outcomes
Age (years)	76.5(8.9)	-
Body mass (kg)	58.5(12.3)	-
Height (m)	1.5(0.10)	-
Body mass index (kg/m2)	24.9(3.6)	Normal16
L1-L4 T score	-3.0(1.0)	Osteoporosis15
Femoral neck T score	-2.0(1.1)	Osteopenia15

• Note: SD = standard deviation. Outcomes: ¹⁵Kanis et al., 2020; ¹⁶World Health Organization, 2011.

Regarding muscle-related outcomes, low values were observed for MT, FL, ASM_DXA, ASM_BIA, and peak isometric knee extensor strength. In contrast, PA, TC, HGS, gait speed, SPPB scores, and lower-limb strength/power assessed by 5TSTS were within the expected reference values. ASM_DXA was classified as low, whereas ASM_ BIA was classified as appropriate (Table 2).

Table 2
Variables assessing functional performance and muscle mass, architecture, and strength (n = 11)

Variables	Mean (SD)	Reference values	Outcomes
Ultrasound
Muscle thickness (mm)	12.9(2.3)	15.524	Low
Fascicle length (mm)	37.4(15.4)	115.024	Low
Pennation angle (°)	13.0(3.4)	11.925	Appropriate
Bioelectrical impedance analysis (BIA)
ASM_BIA (kg)	14.2(2.9)	1 5.04.19	Low
ASM_BIA index (kg)	6.0(0.8)	5.5 4 19	Appropriate
Dual-energy X-ray absorptiometry (DXA)
ASM_DXA(kg)	11.8(2.2)	15.0 4.19	Low
ASM_DXA index (kg)	5.0(0.7)	5.54 19	Low
Anthropometric measurements (perimetry)
Thigh circumference (cm)	48.5(7.1)	44.017	Appropriate
Muscle strength, and functional performance
Handgrip strength (kgf)	20.7(2.2)	16.027	Appropriate
Peak of isometric knee extensors strength (kgf)	13.1 (4.0)	36.026	Low
Lower Limb Strength/Power (5TSTS) (s)	11.6(2.2)	15.028	Appropriate
Timed up and go (TUG) (s)	9.6(1.4)	9 2 29	Reduced
Gait speed 4 meters (m/s)	1.0(0.2)	0.831	Appropriate
Short Physical Performance Battery (points)	10.0(1.0)	8.030	Good performance

• Note: SD = standard deviation; ASM = appendicular muscle mass measured; 5TSTS = Five Times Sit to Stand test. Reference values: ⁴Cruz-Jentoft et al., 201 9; ¹⁷Mienche et al., 201 9; ¹⁹Baumgartner et al., 1 998; ²⁴Minetto et al., 201 6; ²⁵Raj et al., 2017; ²⁶Meldrum et al., 2007; ²⁷Bohannon, 1 997; ²⁸Bohannon et al., 201 0; ²⁹Bohannon et al., 2006; ³⁰Guralnik et al., 1994; ³¹Guralnik et al., 2000.

Agreement between ASM_BIA and ASM_DXA was moderate (ICC = 0.614; 95% confidence interval [CI]: -0.093 to 0.904; p < 0.001). For the ASM index, agreement was lower and classified as poor (ICC = 0.445; 95% CI: -0.089 to 0.831 ; p = 0.001 ). Bland-Altman analysis showed that BIA overestimated muscle mass compared with DXA, with a mean difference of 2.4 ± 1.3 kg (95% CI: 1.5 to 3.3 kg) for ASM and 1.0 ± 0.5 kg/m² (95% CI: 0.7 to 1.3 kg/m²) for the ASM index. The magnitude of the differences between BIA and DXA measurements was quantified using Cohen's d. Very large effect sizes were observed for both ASM (d = 1.80) and ASM index (d = 2.02), indicating substantial systematic differences between methods.

As shown in Figure 2A, there was a positive correlation between vastus lateralis MT and HGS (p = 0.644; p = 0.033). Similarly, longer FL was associated with faster gait(p = 0.617; p = 0.043) (Figure 2B). No significant correlations were observed between muscle mass assessed by DXA, BIA, or TC and measures of muscle strength or functional performance (p > 0.05).

Figure 2
Correlation between muscle thickness and hand grip strength (A), and fascicle length and gait speed (B) in older women with osteoporosis (n = 11 ).

MQ calculated as HGS/ASM_BIA was 1.52 ± 0.47 kgf/kg, classified as low, while MQ calculated as HGS/ ASM_DXA was 1.81 ± 0.50 kgf/kg, classified as normal.¹² The difference between MQ_BIA and MQ_DXA was statistically significant (p = 0.001, paired t-test). No significant associations were observed between MQ and US-derived muscle architecture parameters.

Discussion

The present study investigated the agreement between different methods for skeletal muscle assessment and their associations with physical function in older women with osteoporosis. The main findings were: limited agreement between BIA and DXA for estimating ASM; reduced muscle architecture despite preserved performance in most functional tests; positive associations between US-derived muscle architecture and selected indicators of physical function; and differences in MQ according to the method used to estimate muscle mass.

Although US, BIA, and DXA identified a similar overall pattern of reduced muscle mass, agreement between BIA and DXA was limited. Studies comparing different methods and diagnostic criteria for sarcopenia have also reported variability in muscle mass classification, indicating that these methods should not be considered equivalent.³³, ³⁴ In the present study, BIA overestimated ASM compared with DXA, consistent with previous reports in older adults.^{33 34 35} This discrepancy is likely explained by the different principles underlying each technique, as DXA directly estimates lean soft tissue mass, whereas BIA relies on prediction equations influenced by hydration status and body composition.²¹ Although participants presented a normal BMI,¹⁶ body mass index does not necessarily reflect body composition in older adults.³⁶

Anthropometric assessment also differed from imaging-based methods. TC was the only indicator within the expected reference range, whereas US and both imaging methods identified reduced muscle mass. Because TC includes muscle, subcutaneous adipose tissue, skin, and other soft tissues,²⁰ it may not accurately reflect skeletal muscle mass. In contrast, previous studies have shown that US-derived measurements are more sensitive than anthropometric indicators for detecting muscle loss,³⁷ suggesting that anthropometric measurements should be interpreted cautiously when used in isolation.¹⁷

US assessment demonstrated reduced MT and FL, whereas PA remained within the expected range.²⁴, ²⁵ Similar findings have been reported in older adults with osteoporosis.³⁷ Aagaard et al.³⁸ suggested that preservation of PA may represent an adaptive architectural response to reductions in MT, helping maintain muscle force despite structural changes. Although this mechanism was not investigated in the present study, the muscle architecture pattern observed in our sample is consistent with previous reports.³⁷, ³⁸ Taken together, these findings suggest that DXA, BIA, US, and anthropometric measurements provide complementary rather than equivalent information regarding skeletal muscle assessment in older women with osteoporosis. While DXA and BIA primarily estimate muscle quantity, US adds information on muscle architecture that may contribute to a more comprehensive evaluation of skeletal muscle in this population. While ASM and muscle architecture were reduced, muscle function was not uniformly impaired. HGS remained within the reference range, whereas maximal isometric knee extensor strength was reduced. Likewise, performance in 5TSTS, gait speed, and SPPB remained within the expected range, while TUG performance was slightly below the adopted reference value. These findings indicate that different functional tests evaluate distinct physiological domains and should not be interpreted as equivalent.

HGS is widely recognized as a practical indicator of overall muscle strength and is recommended in current sarcopenia diagnostic algorithms.³⁹ However, previous studies have cautioned against extrapolating handgrip performance to represent total body muscle strength, particularly in community-dwelling older women.⁴⁰ In the present study, reliance on HGS alone would have suggested preserved muscle strength, whereas assessment of the knee extensors identified reduced maximal isometric strength. Similar findings have been reported by Palombaro et al.,⁴¹ reinforcing the importance of evaluating lower-limb muscle function in women with osteoporosis.

The discrepancy between reduced knee extensor strength and preserved performance in the 5TSTS may be explained by the different neuromuscular domains assessed by each test. While maximal isometric strength quantifies peak force production, 5TSTS reflects the combined contribution of muscle strength, power, coordination, movement strategy, and muscular endurance.²⁸, ⁴² Likewise, gait speed and SPPB evaluate global functional performance and are influenced by balance, motor control, and coordination in addition to muscle strength.³¹, ³², ⁴³ Conversely, the slightly reduced TUG performance²⁶ may indicate subtle impairments in functional mobility, as this test requires the integration of balance, mobility, and executive function.⁴⁴

Positive associations were observed between US-derived muscle architecture and selected indicators of physical function. MT was positively associated with HGS, whereas FL was associated with gait speed. In contrast, no significant associations were observed between muscle mass estimated by DXA or BIA and functional outcomes. These findings are consistent with previous evidence suggesting that US-derived muscle parameters may better reflect muscle performance than estimates of muscle quantity alone.¹⁰, ³⁷

MQ has been proposed as an operational indicator of musculoskeletal health because it incorporates both muscle strength and muscle quantity.¹³ However, no universally accepted definition or assessment method currently exists. In the present study, MQ differed according to the method used to estimate ASM. Values calculated using BIA were classified as low, whereas those obtained using DXA remained within the normal range. This difference is likely explained by the systematic overestimation of muscle mass by BIA, highlighting that MQ estimates are directly influenced by the method used to assess muscle mass. Because the cut-off values proposed by Barbat-Artigas et al.¹³ were originally based on BIA-derived muscle mass, the interpretation of MQ estimated using DXA should be made with caution.

No significant associations were observed between MQ and US-derived muscle architecture or functional performance. Although previous studies have suggested that MQ may be more closely related to physical performance than muscle quantity alone,¹³ our findings indicate that its interpretation should consider the muscle mass assessment method. In addition, MQ in the present study was calculated using HGS and ASM, which may not fully represent the relationship between muscle structure and function in lower limbs. Future studies should investigate MQ using strength and muscle mass measurements obtained from the same anatomical region, such as quadriceps strength and quadriceps MT or volume. Furthermore, although the cut-off values proposed by Barbat-Artigas et al.¹³ are widely used, they were established in a younger and healthier population and should therefore be interpreted cautiously in older women with osteoporosis.

The present findings support a multidimensional approach to skeletal muscle assessment in older women with osteoporosis. While DXA and BIA primarily quantify muscle mass, US provides additional information on muscle architecture and demonstrated associations with selected functional outcomes. These observations suggest that different assessment methods provide complementary information regarding skeletal muscle health and may contribute to a more comprehensive clinical evaluation.

Some limitations should be considered. The cross-sectional design precludes causal inferences, and the retrospective analysis without a control group limits comparisons with older women without osteoporosis. In addition, the small sample size reduced the precision of the agreement estimates and may have limited the detection of moderate associations. Therefore, both significant and non-significant findings should be interpreted cautiously and considered preliminary. Despite these limitations, this study simultaneously evaluated DXA, BIA, US-derived muscle architecture, anthropometric measurements, MQ, and functional performance, providing an integrated characterization of skeletal muscle in older women with osteoporosis.

Another limitation concerns the assessment of MQ. Although the operational definition proposed by Barbat-Artigas et al.¹³ was adopted, no universally accepted definition or method for MQ assessment currently exists. Furthermore, because muscle mass was estimated using two different techniques, the resulting MQ values were method-dependent and should be interpreted cautiously.

Conclusion

This study demonstrated limited agreement between BIA and DXA for estimating ASM in older women with osteoporosis. US-derived muscle architecture parameters were associated with selected indicators of muscle function, whereas MQ varied according to the method used to estimate muscle mass. These findings suggest that different assessment methods provide complementary information regarding skeletal muscle health. However, because of the exploratory design and limited sample size, these results should be interpreted as hypothesis-generating and confirmed in larger, adequately powered prospective studies before informing clinical decision-making.

Acknowledgments

This study was partially funded by the Coordination for the Improvement of Higher Education Personnel - Brazil Coordination for the Improvement of Higher Education Personnel (CAPES), National Council for Scientific and Technological Development (CNPQ) No. 06/ 2019 and Pontifícia Universidade Católica do Paraná.

Data availability statement

Data are available from the corresponding author on reasonable request, subject to institutional ethics approval and execution of a data sharing agreement, to protect participant privacy.

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*Correspondence:

[e-mail]

Associate editor:

Ana Paula Cunha Loureiro

Publication Dates

• Publication in this collection
  26 Oct 2026
• Date of issue
  2026

History

• Received
  19 Sept 2025
• Reviewed
  16 July 2026
• Accepted
  11 Sept 2026