The authors have no conflict of interest.
Low Skeletal Muscle Mass Is Associated With Poor Structural Parameters of Bone and Impaired Balance in Elderly Men—The MINOS Study†
Article first published online: 20 DEC 2004
Copyright © 2005 ASBMR
Journal of Bone and Mineral Research
Volume 20, Issue 5, pages 721–729, May 2005
How to Cite
Szulc, P., Beck, T. J., Marchand, F. and Delmas, P. D. (2005), Low Skeletal Muscle Mass Is Associated With Poor Structural Parameters of Bone and Impaired Balance in Elderly Men—The MINOS Study. J Bone Miner Res, 20: 721–729. doi: 10.1359/JBMR.041230
- Issue published online: 4 DEC 2009
- Article first published online: 20 DEC 2004
- Manuscript Accepted: 17 DEC 2004
- Manuscript Revised: 9 AUG 2004
- Manuscript Received: 15 APR 2004
- muscle mass;
- bone size;
- cortical thickness;
In 796 men, 50-85 years of age, decreased relative skeletal muscle mass index was associated with narrower bones, thinner cortices, and a consequent decreased bending strength (lower section modulus), as well as with impaired balance and an increased risk of falls.
Introduction: In men, appendicular skeletal muscle mass (ASM) is correlated positively with BMC and areal BMD (aBMD). In elderly men, low muscle mass and strength (sarcopenia) is associated with difficulties in daily living activities. The aim of this study was to evaluate if ASM is correlated with bone size, mechanical properties of bones, balance, and risk of falls in elderly men.
Materials and Methods: This study used 796 men, 50-85 years of age, belonging to the MINOS cohort. Lifestyle factors were evaluated by standardized questionnaires. Estimates of mechanical bone properties were derived from aBMD measured by DXA. ASM was estimated by DXA. The relative skeletal muscle mass index (RASM) was calculated as ASM/(body height)2.3.
Results: After adjustment for age, body size, tobacco smoking, professional physical activity, and 17β-estradiol concentration, RASM was correlated positively with BMC, aBMD, external diameter, and cortical thickness (r = 0.17-0.34, p < 0.0001) but not with volumetric BMD. Consequently, RASM was correlated with section modulus (r = 0.29-0.39, p < 0.0001). Men in the lowest quartile of RASM had section modulus of femoral neck and distal radius lower by 12-18% in comparison with men in the highest quartile of RASM. In contrast, bone width was not correlated with fat mass, reflecting the load of body weight (except for L3), which suggests that the muscular strain may exert a direct stimulatory effect on periosteal apposition. After adjustment for confounding variables, a decrease in RASM was associated with increased risk of falls and of inability to accomplish clinical tests of muscle strength, static balance, and dynamic balance (odds ratio per 1 SD decrease in RASM, 1.31-2.23; p < 0.05-0.001).
Conclusions: In elderly men, decreased RASM is associated with narrower bones and thinner cortices, which results in a lower bending strength. Low RASM is associated with impaired balance and with an increased risk of falls in elderly men. It remains to be studied whether low RASM is associated with decreased periosteal apposition and with increased fracture risk in elderly men, and whether the difference in skeletal muscle mass between men and women contributes to the between-sex difference in fracture incidence.
SKELETAL MUSCLE MASS in the elderly is determined by muscle mass acquired in young age and by its age-related decrease.(1–3) Acquisition of the skeletal muscle mass in youth is determined by genetic, ethnic, hormonal, and lifestyle factors (mainly physical activity).(4–6) The age-related decrease in skeletal muscle mass and strength is slightly faster in men than in women.(7,8) In elderly men, several risk factors for low appendicular skeletal muscle mass and strength (sarcopenia) were suggested: low testicular secretion resulting in decreased levels of bioavailable and free testosterone, vitamin D deficit, low physical activity, and sedentary lifestyle, tobacco smoking, malnutrition, and poor health status.(9–12)
Clinical studies indicate that sarcopenia is associated with a decreased walking ability, more frequent use of a cane, and difficulty in climbing, lifting, kneeling, or standing up from a chair.(2,13) In a cohort of elderly men, sarcopenia was associated with an increased risk of falls and balance abnormalities.(1) Although these data are limited, they indicate that sarcopenia can be associated with difficulty in daily-living activities and with an increased risk of falls, which may contribute to an increase in the fracture risk.
Intensive long-lasting physical activity is associated not only with an increase in appendicular skeletal muscle mass but has important skeletal effects.(14–16) Bone continually adapts throughout life to the loading forces on it from normal physical activities. Mechanically, bones are the muscle-actuated levers that provide physical movement, and the configuration of muscle actions through short-arm levers ensures that skeletal loads are dominated by muscle force. Moreover, experimental studies show that the mechanical loading stimulates directly bone formation in a site-specific way.(17,18) Clinical observations also indicate a strong positive correlation between appendicular skeletal muscle mass (ASM) and strength and BMC and areal BMD (aBMD).(6,19)
One might therefore expect that skeletal adaptation to age-related sarcopenia might be responsible for some of the decline in the strength of aged bones. The aim of this study was to evaluate if ASM is correlated with bone size, mechanical properties of bones, and with balance and risk of falls in a large group of elderly men belonging to the MINOS cohort.
MATERIALS AND METHODS
The MINOS study is a prospective study of osteoporosis and its determinants in men that was initiated in 1995.(20) It is a collaboration between INSERM (NIH and Medical Research) and Société de Secours Minière de Bourgogne (SSMB) in Montceau les Mines. Montceau les Mines is a town situated 130 km northwest of Lyon in the Department (District) of Saône et Loire. Its population is 21,000 inhabitants, including 7150 men >19 years of age. SSMB is one of the largest health insurance companies in this town. The entire cohort was described previously in detail. This analysis was performed in 796 men, 50-85 years of age, who had technically correct results of bone absorptiometry of the hip, distal radius, and whole body. All men responded to an epidemiological questionnaire covering demographic and behavioral information as well as a detailed medical history. The intensity of current and past professional physical activity was evaluated globally using a self-reported score based on the type of the daily activity as described previously.(20) Four levels of professional physical activity were included in the score: low (sitting position, little walking, no load carrying or lifting, e.g., clerk), medium (mainly standing position, extensive walking, lifting heavy objects rarely, e.g., physician, engineer, laboratory staff), high (walking upstairs and downstairs frequently, lifting heavy objects regularly, e.g., craftsman, electrician), and very high (extensive lifting heavy objects, exerting works necessitating permanent physical effort, e.g., coal miner). Current leisure physical activity was evaluated by a standardized questionnaire. Weekly individual activity was calculated on the basis of the overall amount of time spent on walking, gardening, and leisure sport activity. An annual average assessment of seasonal activities (gardening, certain kinds of exercise) was also made. The leisure physical activity was expressed as hours per week regardless of the type of activity.
Measurement of appendicular skeletal muscle mass
Whole body and regional body composition were estimated by DXA using a Hologic QDR-1500 device (Hologic, Waltham, MA, USA) as described previously.(21) The software provides the mass of lean soft tissue, fat, and bone mineral for both the whole body and specific regions. For analysis of tissue composition, a step phantom consisting of six fields of acrylic and aluminium of varying thickness with known absorptive properties is scanned with the patient and serves as external standard. ASM was calculated as the sum of lean soft tissue in both the right and left arms and legs. The limbs were isolated from the trunk using DXA regional computer-generated lines with manual adjustment. With the use of specific anatomic landmarks, the legs and arms were defined by this method as the soft tissue extending from a line drawn through and perpendicular to the axis of the femoral neck and angled with the pelvic brim to the phalanges tips and the soft tissue extending from the center of the arm socket to the phalanges tips, respectively. The relative skeletal muscle mass index (RASM) was calculated as ASM/body height)2.3. ASM is determined by three dimensions of the body (height, width, and depth), and this exponential allows to obtain the measure of muscle mass that is independent of body height in contrast to the previously used parameter ASM/body height)2.(1,22)
Bone mass measurement and estimates of structural geometry
BMC and aBMD was measured at the right hip and at the third lumbar vertebra (L3) in the antero-posterior position using pencil-beam DXA (QDR-1500; Hologic) and at the distal nondominant forearm using single-energy X-ray absorptiometry (Osteometer DTX 100).(20) The OsteoDyne Hip Positioner System (HPS) was used to minimize hip positioning error.(23) The rectangle of femoral neck was positioned manually perpendicularly to the axis of femoral neck to cover its narrowest part. When necessary, the edges of femoral neck were adjusted manually. Body composition was also measured with the Hologic scanner in total body mode. The Hologic QDR 1500 device was calibrated daily using a lumbar spine phantom, yielding a CV for aBMD of 0.33%. Twice a month, the Hologic hip phantom was measured, yielding a long-term CV of 0.94% for femoral neck aBMD and 1.05% for femoral neck projected area.
At the forearm, the distal site includes 20 mm of ulna and radius situated proximally to the site where the spacing between the medial edge of radius and the lateral edge of ulna is 8 mm. To diminish the measurement error of the ultra distal region, manual analysis was performed in all the participants, and bones edges were adjusted manually when necessary. Scans with evident error of positioning were excluded. The densitometer was calibrated daily using a calibration standard for DTX 100; its long-term CV was 0.47% for BMD and 0.15% for projected area.
Dimensions of the vertebral body of L3 were measured on the antero-posterior and lateral radiographs of the lumbar spine. The cross-sectional area of L3 was calculated based on the antero-posterior and frontal diameters measured in the narrowest site of the vertebral body. These two diameters and the average of three heights of the vertebral body (anterior, central, and posterior) were used for calculation of the volume of the vertebral body. Osteoarthritis of L3 was evaluated using the score described previously.(20)
Volumetric BMD (vBMD) of the femoral neck and distal radius was estimated based on the method described by Carter et al.(24) Volumetric BMD of L3 was calculated by dividing BMC of L3 measured in the antero-posterior projection through the volume of the vertebral body of L3 calculated as described above. Structural measures (external diameter, cortical thickness, section modulus, and average buckling ratio) were estimated according to the formulae of Beck et al.(25) as described in detail previously.
Getting up from a chair and sitting down allows evaluation of the strength of knee extensors and flexors.(26–28) The participants were seated on a hard chair and asked to stand up and sit down from a chair five times as quickly as possible. The examiner recorded the number of chair-stands, the time required to perform the test, and the degree of difficulty (pushes up with arms, moves forward in chair first, unsteady on first standing). The inability to perform the test was diagnosed when the subject got up less than five times. If the subject made this test with difficulty but managed to get up five times, irrespective of the time he required, he was classified as “able.”
Standing balance was evaluated based on standing with the feet in the side-by-side position.(27,29) Participants were evaluated for 10 s with eyes open and for 5 s with eyes closed. The timing was stopped when the participant moved his feet or grasped the examiner for support or when the time (10 or 5 s, respectively) had elapsed. The participant was scored as “able” if he could stand 10 s with eyes open or 5 s with eyes closed; otherwise, he was classified as “unable.”
To test dynamic balance, participants performed a 10-step tandem walk on the line drawn on the floor.(30) The examiner recorded the time, the number of steps really performed, and the number of errors (stepping off the line, grabbing an object, taking steps with the heel and toe visibly separated). After the subject had finished the tandem walk forward, he was asked to perform the same 10-step tandem walk backward. Similarly, the examiner recorded the time, the number of steps really performed, and the number of errors.
Participants were interviewed to determine whether they had fallen during the 12 months preceding the questionnaire. Falls were recorded if they occurred from a standing height or less. All clinical tests were performed and information on the circumstances of falls was obtained by one investigator (PS).
In all participants, blood samples were obtained in the fasting state at 8:00 a.m. to assess serum concentrations of testosterone, 17β-estradiol, and sex hormone-binding globulin (SHBG).
Serum total 17β-estradiol and total testosterone were measured by tritiated radioimmunoassay (RIA) after diethyl ether extraction.(31) For testosterone, the limit of detection is 0.06 nM/liter, and the interassay CV is 10% for a concentration of 1 nM/liter and 7.8% for 6 nM/liter. For total 17β-estradiol, the limit of detection is 11 pM/liter, and the interassay CV is 9.4% for a concentration of 169 pM/liter and 6.2% for 510 pM/liter. SHBG was measured by IRMA (125 I SBP Coatria; Bio-Mérieux, Marcy l'Etoile, France) with an interassay CV of 4.1% for a concentration of 16 nM and 5.3% for 100 nM. The limit of detection was 0.5 nM. Apparent free testosterone concentration (AFTC) was calculated as described previously by Vermeulen et al.(32) Serum 25-hydrocholecalciferol [25(OH)D] was measured by RIA (Incstar, Stillwater, MN, USA), which excludes any interference from lipids.(33) Intra- and interassay CVs were 5% and 11%, respectively. The detection limit was 7.5 nM.
All calculations were performed using SAS software. Parson's simple correlation coefficients were calculated between RASM, bone mineral, and structural parameters on one side and, on the other side, age, fat body mass, body height, physical activity, tobacco smoking, alcohol consumption, and hormonal levels [total and apparent free testosterone, 17β-estradiol, 25(OH)D]. In the final models of partial correlation coefficients, multiple linear regression, and analysis of covariance, we included as covariates age, fat body mass, body height, tobacco smoking, professional physical activity, and 17β-estradiol concentration, which entered as significant confounding variables in the majority of models. Comparisons between the quartiles of RASM were adjusted for multiple comparisons using Tukey's test. The interactions between RASM and the covariates were not significant and, consequently, not introduced in the final models. We compared the strength of association of bone mineral and structural parameters on one side, with, on the other side, RASM, body weight, and fat mass using partial correlation coefficients. To obtain comparable results, all these models were adjusted for the same confounding variables: age, body height, tobacco smoking, professional physical activity, and 17β-estradiol concentration.
The inability to perform physical performance tests (expressed as an increase of risk per decrease of RASM by 1 SD and for the highest tertile of RASM) was evaluated using the logistic regression adjusted for age, fat body mass, professional and leisure physical activity, tobacco smoking, apparent free testosterone concentration, 25(OH)D concentration, and co-morbidities. Co-morbidities included arterial hypertension, coronary heart disease, chronic pulmonary disease necessitating corticosteroid treatment, liver cirrhosis, diabetes mellitus, vascular brain disease, hemiplegia, parkinsonism, and treatment with psychotropic medicines. Backward procedure was used: all the independent variables were introduced and removed progressively, leaving in the final model only the independent variables for which p < 0.2. The variables for which p > 0.2 did not contribute to the explanatory power of the model and did not influence the odds ratio values for RASM.
Association between muscle mass and bone morphology
Table 1 presents the descriptive data of 796 men, 50-85 years of age, participating in this study. RASM decreased with age (r = −0.29, p < 0.0001). Using simple correlation coefficients, the width of femoral neck and distal radius as well as the cross-sectional area of third lumbar vertebra correlated positively with RASM (r = 0.16-0.27, p < 0.0001). At these three sites, BMC and aBMD also correlated with RASM (r = 0.15-0.39, p < 0.0001; for L3 adjusted for arthritis). vBMD was correlated positively with RASM at the femoral neck (r = 0.16, p < 0.0001) but not at L3 or distal radius. Cortical thickness and section modulus of the femoral neck and distal radius correlated with RASM (r = 0.27-0.38, p < 0.0001). Age, height, fat body mass, and 17β-estradiol level entered as significant in the majority of multiple linear regression models evaluating the association of RASM with bone mineral, morphology, and indices of mechanical resistance. RASM was larger in men with higher levels of professional physical activity (p < 0.0001) but lower in current smokers (p < 0.02). These two variables also entered as significant in the majority of multivariate models.
AFTC, but not total testosterone concentration, correlated positively with RASM (r = 0.10, p < 0.005). In contrast, total testosterone and AFTC were not correlated with bone mineral (BMC, aBMD, and vBMD) and structural measures.
After adjustment for the significant confounding variables (age, fat body mass, body height, professional physical activity, 17β-estradiol concentration, tobacco smoking), RASM was positively correlated with BMC and aBMD of femoral neck, distal radius, and more weakly, of L3 (Table 2). RASM explained 1-16% of the variability of the studied variables. The middle column presents average change of densitometric and biomechanical parameters per 1 kg/m2.3 increase in RASM.
Using the ANOVA, men in the highest quartile of RASM (>7.31 kg/m2.3) were younger (63 versus 68 years, p < 0.0001) but not taller (p = 0.44) in comparison with men in the lowest quartile (<6.32 kg/m2.3). Men in the highest quartile of RASM had higher body mass index (BMI; 31 versus 25 kg/m2, p < 0.0001) and higher fat mass (25.5 versus 18.9 kg, p < 0.0001) in comparison with men in the lowest quartile. Adjusted difference in BMC and aBMD between the lowest and the highest quartile of RASM varied from 4.4% to 12.5%. The difference in BMC was caused by the larger bones in men with highest RASM, whereas vBMD was similar across the quartiles of RASM. Cortical thickness of both bones was also positively correlated with RASM (Fig. 1).
Consequently, RASM was correlated with section modulus. Therefore, men in the lowest quartile of RASM had section moduli of femoral neck and distal radius lower by 12-18% in comparison with men in the highest quartile of RASM (Fig. 1), which indicates a lower bending strength. In contrast, the average buckling ratio was not correlated with RASM, which indicates a similar stability of bones across quartiles of RASM. Similarly, only slightly weaker differences were found when the comparisons were adjusted for BMI instead of fat mass. Analyses adjusted for fat mass seem more appropriate because RASM is a constituent of BMI.
The positive correlation of RASM with bone mineral and structure can be determined by the mechanical strain but also by the body load (reflected by fat mass and body weight). Therefore, association between bone mineral and structural parameters on one side, and, on the other side, RASM, body weight, and fat body mass, were analyzed using partial correlation coefficients adjusted for age, body height, professional physical activity, tobacco smoking, and 17β-estradiol level (Table 3). Bone size was correlated more strongly with RASM than with fat mass, indicating the importance of mechanical strain. At the three sites, RASM was correlated with bone size even after additional adjustment for body weight (r = 0.12-0.29, p < 0.002-0.0001). In contrast, after adjustment for body weight, fat mass was no longer correlated with the cross-sectional area of L3. RASM and body weight were correlated positively with BMC, aBMD, cortical thickness, and section modulus at the femoral neck and distal radius, and more weakly, with BMC and aBMD of L3. Fat body mass correlated with aBMD, vBMD, and cortical thickness only at the femoral neck. This correlation coefficient had the same value whether it had been adjusted for 17β-estradiol level or not.
Lower RASM was associated with balance disturbances and with an increased risk of falls (Table 4). After adjustment for confounding variables, a decrease in RASM by 1 SD was associated with an increase in the risk of inability to perform clinical tests of muscle strength (five stands from chair), of static balance (standing with the feet in side by side position), and of dynamic balance (tandem walk). In contrast, higher RASM had a protective effect, and men in the highest tertile of RASM had lower risks of decreased physical function, falls, and of impaired static and dynamic balance. Different thresholds were tested, and that of the third tertile best discriminated the men with a lower risk of inability to perform the clinical tests.
Our data indicate that, in elderly men, RASM is correlated positively with bone size but not with vBMD. Consequently, elderly men with lower RASM have lower BMC, lower cortical thickness, and decreased bending strength (lower section modulus). Moreover, in this cohort, low muscle mass is associated with an impairment of balance and with an increased risk of falls.
Our results confirm previous studies showing that men with sarcopenia had lower cortical area of tubular bones, impaired gait and balance, and an increased risk of falls.(1–2,13,34) In contrast, Visser et al.(35–37) did not find any association between muscle mass and self-reported disability or lower extremity performance. However, grip strength remained a significant determinant of the lower extremity performance.(37)
The discordance between studies can be related to the age range and methodological differences. Fat-free mass is comprised not only the skeletal muscle mass but also other organs, extracellular fluid, and bone. In the elderly, decrease in muscle strength can exceed that of muscle mass because of a deteriorated function of neuromuscular junction,(38) and muscle mass may not be a sufficient predictor of muscle strength and physical performance. Finally, muscle mass is influenced by body size, and the height-adjusted parameters better reflect the degree of sarcopenia.
High physical activity results in an increase of muscle mass and BMC.(4,6,16) Higher BMC is determined mainly by larger bones, rather than change in vBMD, and results in improved bone mechanical resistance.(14–15,39) Higher bone size and BMC can be associated with improved mechanical resistance in bones for which compression is the main mechanism of fracture (vertebrae, long bones with low buckling ratio, e.g., radius). At the femoral neck, higher RASM is associated with better resistance to bending (higher section modulus), whereas bone stability in case of trauma is not changed (stable buckling ratio). Fat mass was correlated with cortical thickness and vBMD (even adjusted for the level of 17β-estradiol) at the weight-bearing femoral neck but not at distal radius. This suggests that fat mass may exert an inhibitory effect on the endocortical resorption through a direct mechanical load.
Several hypotheses can be raised to explain our results. Higher physical activity results in an increase in muscle mass and strength. Consequently, the increased muscular strain can induce periosteal apposition. Periosteal apposition can be also stimulated directly by the mechanical strain as indicated by experimental studies.(17,40,41)
Discordant results can be caused by different intensity of physical exercise and its local effect. In men, BMC and aBMD are more strongly correlated with skeletal muscle mass or lean body mass than with fat mass.(19,42–46) In a longitudinal analysis, fat-free mass determined the changes in BMC and aBMD of the lumbar spine.(47) In contrast, aBMD and size were weakly correlated with muscle mass and strength in young men participating in high-intensity training programs.(6,15,48,49) However, such training is focused on specific groups of muscles and mechanical stimulation is transferred only on corresponding parts of the skeleton.
The association between muscle mass and bone size can be partly determined by genetic factors. Slender men can have lower muscle mass and thinner bone compared with men who have larger size. Poor nutritional status during growth might result in lower muscle mass and smaller bones in later life.
Muscle mass and bone size can have common hormonal determinants. Bone size is similar in prepubertal boys and girls, and the difference develops during puberty.(50) However, in multivariate models, lean body mass and body height were determinants of bone width in adolescent boys, whereas the pubertal stage was not.(43) Thus, during puberty, the direct effect of testosterone on bone width may be limited. In elderly men, AFTC correlated with muscle mass (in certain cohorts) but not with bone size.(12,25,51) In hypogonadal patients, testosterone treatment increased muscle mass and aBMD but not bone width.(52,53)
Data on IGF-I are similar. In children, IGF-I level was correlated with the width of femoral neck but not with lean body mass.(54,55) In adult men, IGF-I level was correlated neither with bone width nor with lean body mass.(56,57) In children and adult men with growth hormone (GH) deficiency, exogenous GH increased lean body mass and aBMD.(58,59) As far as we know, the effect of GH treatment on bone width has not been adequately evaluated. Thus, the hypothesis suggesting common hormonal determinants of muscle mass and bone size in men lacks compelling evidence.
Several questions remain to be answered. Studies need to check prospectively if low RASM predict falls and fractures in elderly men. Bone width increases with aging in men, and we showed that higher RASM is associated with larger bones.(60,61) It should be verified in a longitudinal study if low RASM is associated with decreased periosteal apposition and with lower increase of bone width. Finally, after adjustment for body size, men have higher muscle mass and larger bones but lower fracture incidence than women.(62,64) Thus, the lower fracture incidence in men might be partly explained by a higher muscle mass.
Our study has several limitations. Cross-sectional associations cannot be considered as proof of mechanism or causation. They do not distinguish between genetic determination of muscle and bone mass, effect of muscle mass during the growth, and effect of muscle mass on periosteal apposition during aging. The cohort comprises mainly low-middle class men and may not be representative of the French population. Lifestyle factors were evaluated by a self-reported questionnaire, and answers could be subjective. For professional physical activity, we used a four-level grading. For leisure physical activity, only current status was evaluated.
A major limitation of our study is the lack of data on muscle strength. Muscle strength and mass are strongly correlated in the elderly; loss of muscle strength exceeds that of muscle mass. It has been shown that muscle mass and muscle strength disclose a similar association with the cortical area.(34)
DXA scans present some limitations in the evaluation of bone width. In very old men, subperiosteal bone mass can be low and not recognized by the edge detection system. This artifact can underestimate the bone width in elderly men. The projected area of femoral neck may be overestimated because of calcifications in fibrous tissue. The measured site of radius is established by the device. According to the individual anatomy, this site can be more distal (larger and more trabecular) or more proximal (narrower and cortical). The calculation of vBMD of L3 overestimates vBMD because BMC of the entire vertebra is divided by volume of the vertebral body. The analysis of structural parameters is based on derived parameters that are not directly measured, and the equations are based on several assumptions (e.g., cylindrical shape of tubular bones and constant fraction of cortical bone).
Another limitation is accuracy of the evaluation of ASM by DXA, which underestimates the age-related decrease of the muscle mass. DXA measures lean mass of limbs comprising skeletal muscle protein (decreasing with age), as well as connective tissue and water, whose content increases with age.(65) Functional degradation of muscles is not apparent with DXA measurement. Measurement errors of ASM, aBMD, and area can explain, at least partly, low coefficients of correlation between RASM and bone mineral and structural parameters.
In conclusion, in elderly men, decreased RASM is associated with narrower bones and thinner cortices, even after adjustment for age, body size, tobacco smoking, professional physical activity, and 17β-estradiol concentration, which results in a lower bending strength. Low RASM is also associated with impaired balance and with an increased risk of falls in elderly men. These data suggest that low RASM might be an important determinant of the risk of fragility fractures in men, a mechanism that needs to be prospectively assessed.
This study was supported by a contract from INSERM/Merck Sharp Dohme Chibret.
- 11998 Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 147: 755–763., , , , , , ,
- 22000 Epidemiology of sarcopenia. J Am Geriatr Soc 48: 625–630., , , , ,
- 32001 Muscle function in 164 men and women aged 20–84 yr. Med Sci Sports Exerc 33: 220–226., , , , , , ,
- 42001 Characterization of genetic and lifestyle factors for determining variation in body mass index, fat mass, percentage of fat mass, and lean mass. J Clin Densitom 4: 353–361., , , , , ,
- 51997 Appendicular skeletal muscle mass: Effects of age, gender and ethnicity. Am J Physiol 83: 229–239., , , , , , ,
- 61999 A comparison of bone mineral density and muscle strength in young male adults with different exercise levels. Calcif Tissue Int 64: 490–498., ,
- 72001 Longitudinal muscle strength changes in older adults: Influence of muscle mass, physical activity, and health. J Gerontol A Biol Sci Med Sci 56: B209–B217., , , , , ,
- 82000 Changes in bone mineral, lean body mass and fat content as measured by dual energy X-ray absorptiometry: A longitudinal study. Calcif Tissue Int 66: 97–99., , ,
- 91999 Predictors of skeletal muscle mass in elderly men and women. Mech Ageing Dev 107: 123–136., , , ,
- 102002 Interrelationships of serum testosterone and free testosterone index with FFM and strength in aging men. Am J Physiol 283: E284–E294., , , , ,
- 111999 Low serum calcidiol concentration in older adults with reduced muscular function. J Am Geriatr Soc 47: 220–226., ,
- 122004 Hormonal and lifestyle determinants of appendicular skeletal muscle mass in men the MINOS study. Am J Clin Nutr 80: 496–503., , ,
- 132002 Low relative skeletal muscle mass (sarcopenia) in older persons is associated with functional impairment and physical disability. J Am Geriatr Soc 50: 889–896., ,
- 142000 Exercise-induced bone gain is due to enlargement in bone size without a change in volumetric bone density: A peripheral quantitative computed tomography study of the upper arms of male tennis players. Bone 27: 351–357., , , , ,
- 151998 Professional football (soccer) players have a markedly greater skeletal mineral content, density and size than age- and BMI-matched controls. Calcif Tissue Int 63: 112–117., , , , ,
- 161996 Dimensions and estimated mechanical characteristics of the humerus after long-term tennis loading. J Bone Miner Res 11: 864–872., , , , ,
- 171997 Strain gradients correlate with sites of exercise-induced bone-forming surfaces in the adult skeleton. J Bone Miner Res 12: 1737–1745., ,
- 182000 Time course for bone formation with long-term external mechanical loading. J Appl Physiol 88: 1943–1948., ,
- 191996 Associations of fat and muscle masses with bone mineral in elderly men and women. Am J Clin Nutr 63: 365–372., , , ,
- 202000 Cross-sectional assessment of age-related bone loss in men. Bone 26: 123–129., , ,
- 212002 Total-body skeletal muscle mass: Estimation by a new dual-energy X-ray absorptiometry method. Am J Clin Nutr 76: 378–383., , , ,
- 221996 Skeletal muscle mass: Evaluation of neutron activation and dual-energy X-ray absorptiometry methods. J Appl Physiol 80: 824–831., , , , , ,
- 231997 Effects of a new positioner on the precision of hip bone mineral density measurements. J Bone Miner Res 12: 1289–1294., , , , , ,
- 241992 New approaches for interpreting projected bone densitometry data. J Bone Miner Res 7: 137–145., ,
- 252004 The role of sex steroids in the regulation of bone morphology in men. The MINOS study. Osteoporos Int 15: 909–917., , , , ,
- 261988 Identifying mobility dysfunctions in elderly patients. Standard neuromuscular examination or direct assessment? JAMA 259: 1190–1193.,
- 271994 A short physical performance battery assessing lower extremity function: Association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol A Med Sci Biol Sci 49: M85–M94., , , , , , ,
- 281999 Comparison of performance-based and self-rated functional capacity in Spanish elderly. Am J Epidemiol 149: 228–235., , ,
- 291995 Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability. N Engl J Med 332: 556–561., , , ,
- 301989 Risk factors for recurrent nonsyncopal falls. A prospective study. JAMA 261: 2663–2668., , ,
- 311982 Estradiol, androstenedione, and dehydroepiandrosterone sulfate in the ovarian and peripheral blood of postmenopausal patients with and without endometrial cancer. Gynecol Oncol 14: 119–124., , , ,
- 321999 A critical evaluation of simple methods for the estimation of free testosterone in serum. J Clin Endocrinol Metab 84: 3666–3672., ,
- 331997 Prevalence of vitamin D insufficiency in an adult normal population. Osteoporos Int 7: 439–443., , , , , ,
- 342002 Muscle size, strength, and bone geometry in the upper limbs of young and old men. J Gerontol A Med Sci Biol Sci 57: M455–M459., , ,
- 351998 Body fat and skeletal muscle mass in relation to physical disability in very old men and women of the Framingham Heart Study. J Gerontol A Biol Sci Med Sci 53: M214–M221., , , , , , ,
- 361998 High body fatness, but not low fat-free mass, predicts disability in older men and women: The Cardiovascular Health Study. Am J Clin Nutr 68: 584–589., , , , , ,
- 372000 Skeletal muscle mass and muscle strength in relation to lower-extremity performance in older men and women. J Am Geriatr Soc 48: 381–386., , , ,
- 382001 Sarcopenia. J Lab Clin Med 137: 231–243., , , ,
- 391977 Humeral hypertrophy in response to exercise. J Bone Jt Surg 59A: 204–208., , , ,
- 402001 Mechanical loading of diaphyseal bone in vivo: The strain threshold for an osteogenic responses varies with location. J Bone Miner Res 16: 2291–2297., , , ,
- 411994 Mechanical loading stimulates rapid changes in periosteal gene expression. Calcif Tissue Int 55: 475–478., , , ,
- 421997 Body composition of a young, multiethnic, male population. Am J Clin Nutr 66: 1323–1331.
- 431998 Type of physical activity, muscle strength, and pubertal stage as determinants of bone mineral density and bone area in adolescent boys. J Bone Miner Res 13: 1141–1148., ,
- 442001 Determinants of bone mineral density in older men and women: Body composition as mediator. J Bone Miner Res 16: 2142–2151., , , , ,
- 451996 Body mass is the primary determinant of midfemoral bone acquisition during adolescent growth. Bone 19: 519–526., , , , ,
- 461997 Whole body bone, fat, and lean mass in black and white men. J Bone Miner Res 12: 967–971., ,
- 472003 Fat-free body mass is the most important body composition determinant of 10-yr longitudinal development of lumbar bone in adult men and women. J Clin Endocrinol Metab 88: 2607–2613., , ,
- 481994 The site-specific effects of long-term unilateral activity on bone mineral density and content. Bone 15: 279–284., , , ,
- 491998 Effects of high-intensity resistance training on bone mineral density in young male powerlifters. Calcif Tissue Int 63: 283–286., ,
- 502001 Modeling of cross-sectional bone size, mass and geometry at the proximal radius: A study of normal bone development using peripheral quantitative computed tomography. Osteoporos Int 12: 538–547., , ,
- 512002 Prevalence of sarcopenia and predictors of skeletal muscle mass in healthy, older men and women. J Gerontol A Med Sci Biol Sci 57: M772–M777., ,
- 521996 Increase in bone density and lean body mass during testosterone administration in men with acquired hypogonadism. J Clin Endocrinol Metab 81: 4358–4365., , , , ,
- 531998 Effects of testosterone replacement therapy on cortical and trabecular bone mineral density, vertebral body area and paraspinal muscle area in hypogonadal men. Eur J Endocrinol 138: 51–58., , , , ,
- 541999 Serum levels of insulin-like growth factor I and the density, volume, and cross-sectional area of cortical bone in children. J Clin Endocrinol Metab 84: 2780–2783., , ,
- 551999 The relation between bone mineral density, insulin-like growth factor I, lipoprotein (a), body composition, and muscle strength in adolescent males. J Clin Endocrinol Metab 84: 3025–3029., , ,
- 562004 Insulin-like growth factor I is a determinant of hip bone mineral density in men less than 60 years of age: MINOS study. Calcif Tissue Int 74: 322–329., , ,
- 571994 Relations of endogenous anabolic hormones and physical activity to bone mineral density and lean body mass in elderly men. Clin Endocrinol 40: 653–661., , , , , ,
- 581999 Long-term effects of growth hormone (GH) replacement in men with childhood-onset GH deficiency. J Clin Endocrinol Metab 84: 2373–2380., , , ,
- 591997 Changes in bone mineral density, body composition, and lipid metabolism during growth hormone (GH) treatment in children with GH deficiency. J Clin Endocrinol Metab 82: 2423–2428., , , ,
- 602000 Structural trends in the aging femoral neck and proximal shaft: Analysis of the Third National Health and Nutrition examination survey dual-energy X-ray absorptiometry data. J Bone Miner Res 15: 2297–2304., , , ,
- 611992 Continuing bone expansion and increasing bone loss over a two-decade period in men and women from a total community sample. Am J Human Biol 4: 57–67., , , ,
- 622003 Effects of gender, anthropometric variables, and aging on the evolution of hip strength in men and women aged over 65. Bone 32: 561–570., , , , ,
- 632001 Does body size account for gender differences in femur bone density and geometry. J Bone Miner Res 16: 1291–1299., ,
- 641994 Gender differences in vertebral sizes in adults: Biomechanical implications. Radiology 190: 678–682., , , , ,
- 651999 Comparison of techniques to estimate total body skeletal muscle mass in people of different age groups. Am J Physiol 277: E489–E495., , ,