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Keywords:

  • bone;
  • muscle;
  • fat;
  • strength;
  • sex;
  • race

Abstract

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Two factors generally reported to influence bone density are body composition and muscle strength. However, it is unclear if these relationships are consistent across race and sex, especially in older persons. If differences do exist by race and/or sex, then strategies to maintain bone mass or minimize bone loss in older adults may need to be modified accordingly. Therefore, we examined the independent effects of bone mineral-free lean mass (LM), fat mass (FM), and muscle strength on regional and whole body bone mineral density (BMD) in a cohort of 2619 well-functioning older adults participating in the Health, Aging, and Body Composition (Health ABC) Study with complete measures. Participants included 738 white women, 599 black women, 827 white men, and 455 black men aged 70-79 years. BMD (g/cm2) of the femoral neck, whole body, upper and lower limb, and whole body and upper limb bone mineral-free LM and FM was assessed by dual-energy X-ray absorptiometry (DXA). Handgrip strength and knee extensor torque were determined by dynamometry. In analyses stratified by race and sex and adjusted for a number of confounders, LM was a significant (p < 0.001) determinant of BMD, except in white women for the lower limb and whole body. In women, FM also was an independent contributor to BMD at the femoral neck, and both FM and muscle strength contributed to limb BMD. The following were the respective β-weights (regression coefficients for standardized data, Std β) and percent difference in BMD per unit (7.5 kg) LM: femoral neck, 0.202-0.386 and 4.7-5.9%; lower limb, 0.209-0.357 and 2.9-3.5%; whole body, 0.239-0.484 and 3.0-4.7%; and upper limb (unit = 0.5 kg), 0.231-0.407 and 3.1-3.4%. Adjusting for bone size (bone mineral apparent density [BMAD]) or body size BMD/height) diminished the importance of LM, and the contributory effect of FM became more pronounced. These results indicate that LM and FM were associated with bone mineral depending on the bone site and bone index used. Where differences did occur, they were primarily by sex not race. To preserve BMD, maintaining or increasing LM in the elderly would appear to be an appropriate strategy, regardless of race or sex.


INTRODUCTION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

IT IS well known that bone mass and prevalence of osteoporotic fracture differ by sex and race. Males have a greater bone mass and lower risk for fracture than females,(1–6) as do those of African ancestry in the United States compared with their white counterparts.(7–11) After adjustment for body size, race, and sex differences in regional and whole body bone mass of adults remain, albeit at a reduced level.(11–13) Because bone mass is an important determinant of bone strength(14, 15) and fracture risk,(16, 17) identifying factors that influence bone mineral has important implications in the design of appropriate strategies to prevent or slow the rate of bone loss and thereby potentially reduce the risk for fracture.

Two modifiable factors associated with bone density are body composition and muscle strength. Both lean mass (LM) and fat mass (FM) increase mechanical (gravitational) load on weight-bearing bones. However, LM may have additional effects on the skeleton by reflecting physical activity levels and the associated effect of muscle contraction. FM also may be influential, especially in postmenopausal women not on hormone replacement therapy, via the conversion of adrenal androgens to estrogen.(18) To date, the importance of these tissues for bone mass at various sites has been somewhat controversial, with FM(19–22) and LM,(18, 23–25) as well as both tissues(2, 26, 27) reported to be determinants of bone mineral density (BMD). Sex may alter these relationships, with FM being a more important determinant of BMD in women than men,(5, 21) although reports to the contrary exist.(28) Only scant data exist regarding the consistency of the associations across racial groups, with Barondess et al.(11) reporting that FM may have a greater effect on bone mass in black men than in white men. In addition, to date, no one has examined the site specificity of this relationship for lower limb BMD with lower limb strength, LM, and FM.

Muscle strength also has been shown to be a predictor of bone density independent of body weight in women(4, 29, 30) and men,(3, 31, 32) although the relationship is not necessarily site specific.(33, 34) Sex may alter the association with muscle strength a more important predictor of BMD in older men than women.(3, 28) However, it is unknown if race alters the muscle strength/bone density relationship.

If differences in the contributory effects of soft tissue and muscle strength to bone density do exist by sex and/or race, then strategies to maintain or minimize age-related bone loss may need to be modified accordingly. This may be particularly important in the elderly, who are at an increased risk for sustaining a fracture. In addition, examining these associations by race and sex contributes to an understanding of the determinants of race and sex differences in bone mass/density. Therefore, the purpose of this study was to examine the cross-sectional independent effects of bone-free LM, FM, and muscle strength on regional and whole body BMD in a large cohort of healthy elders and to determine if these relationships are altered by sex and/or race. BMD sites assessed were the femoral neck, because of its importance for fracture, as well as the limbs and whole body to investigate the contributory effects of muscle strength and soft tissue on weight-bearing and non-weight-bearing bones.

MATERIALS AND METHODS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Subjects

Participants were 2619 well-functioning older white and black adults, aged 70-79 years, participating in the Health, Aging, and Body Composition (Health ABC) Study, a prospective cohort study investigating changes in body composition as a common pathway by which multiple diseases contribute to disability. The age group of 70-79 years was studied as the prevalence of comorbidities and functional decline rises in this age group as they transition from vigor to frailty.(35, 36) Recruitment was undertaken from a random sample of white Medicare beneficiaries and all age-eligible black community residents in designated zip codes surrounding the field centers. To be eligible for the 7-year study, participants had to report no difficulty walking a quarter of a mile, in climbing 10 steps without resting, or in activities of daily living; be free of life-threatening cancers with no active treatment within the past 3 years; and planning to remain within the study area for at least 3 years. Subjects included 738 white women, 599 black women, 827 white men, and 455 black men, recruited at the two field centers located at the University of Pittsburgh and the University of Tennessee, Memphis. The full Health ABC cohort consists of 3075 individuals; however, only those with complete data are included in this report. The primary reason for missing data was past or present cardiovascular conditions that precluded assessment of knee extensor muscle strength (n = 396). Subjects provided informed consent after the study's approval by the Institutional Review Boards of the University of Pittsburgh and the University of Tennessee, Memphis. Data presented are from the baseline examination that took place during 1997-1998.

BMD and body composition

BMD (g/cm2) of the femoral neck and whole body was assessed at both the Pittsburgh and the Memphis field centers by dual-energy X-ray absorptiometry (DXA; Hologic 4500A, version 9.03; Hologic, Inc., Waltham, MA, USA). In addition, bone mineral-free LM, FM, upper limb LM and FM, and percentage body fat were derived from the whole body scan. Dominant upper limb BMD, representing non-weight-bearing bones, and lower limb BMD, weight-bearing bones, were derived from the whole body scan. BMD is an areal density derived from a two-dimensional image and, as such, is influenced by bone size. Therefore, to adjust for differences in bone size, bone mineral apparent density (BMAD, g/cm3) was calculated for the femoral neck.(37) A second measure to adjust for bone and body size involved dividing regional and whole body BMD by height in meters.(21, 38) DXA quality assurance measurements were performed at both study sites to ensure scanner reliability and identical patient scan protocols were used for all participants. The CV for BMD measurements using the Hologic 4500A are 2.0% for the femoral neck, 0.8% for the whole body, and 2.1% and 1.8% for the upper and lower limbs, respectively. For soft tissue, the CVs are 1.0% and 2.1% for whole body LM and FM, and 4.6% and 6.5% for upper limb LM and FM, respectively.

Muscle strength

Dynamic knee extensor strength was measured at an angular velocity of 60o/s on a Kin-Com 125 AP isokinetic dynamometer (Kin-Com, Chattanooga, TN, USA). Subjects were familiarized to the testing procedure and then completed a maximum of six trials with the average maximum torque determined from three reproducible and acceptable trials. Isometric grip strength of the dominant limb was determined in duplicate by a handheld dynamometer with the maximum value reported (Jamar; TEC, Clifton, NJ, USA). Reported CVs for knee extensor strength by isokinetic dynamometry are <6.1%(39, 40) and for grip strength <2.7%.(20, 41)

Other measurements

Duplicate measures of height and weight were obtained using a Harpenden stadiometer (Holtain, Wales, UK) and a standard balance beam scale, respectively, with the mean values reported. Body mass index (BMI) was calculated as weight divided by square height (kg/m2). Smoking status, alcohol consumption, physical activity, and medication usage were determined by an interviewer-administered questionnaire. Three physical activity levels were calculated based on kilocalories per week expended on walking, stair-climbing, and moderate and vigorous physical activity. The levels were low, <1000 kcal/week; moderate, >1000 kcal/week but <2000 kcal/week; and high, >2000 kcal/week. Thiazide and estrogen usage was determined from drug data coded using the Iowa Drug Information System (IDIS) ingredient codes.(42)

Statistical analysis

Data were analyzed using the SPSS (SPSS, Inc., Chicago, IL, USA) statistical software package. Analysis of variance (ANOVA) and χ2 analysis were used to compare differences in baseline characteristics by race and sex. To adjust BMD and muscle strength for body size, analysis of covariance was used with height and weight as covariates. Where appropriate, the Fisher least significant difference (LSD) test was used to locate the source of significant differences. Multiple regression analysis was used to examine the independent effects of LM, FM, and muscle strength on regional and whole body BMD. Regression models were stratified by race and sex and adjusted for age, height (except where BMD/ht was the dependent variable), site (Pittsburgh or Memphis), current smoking status, alcohol consumption (0, three or less drinks per week during the past 12 months; 1, four or more drinks per week during the past 12 months), physical activity (1 = low, 2 = moderate, and 3 = high), thiazide diuretic usage, and estrogen usage (women). Body weight was not included in the multiple regression analyses because fat and bone mineral-free lean tissue mass effectively equals body weight (bone mineral, the third component of body weight partitioned by DXA, being the dependent variable). Knee extensor strength was the muscle strength variable used in analyses of the femoral neck, lower limb, and whole body, while grip strength was used for the upper limb. Variables within each model were examined for multicollinearity using the variance inflation factor (VIF). According to Chatterjee and Price,(43) evidence of multicollinearity exists if the largest VIF is >10 and/or the mean of all the VIFs is considerably >1.

Regression analysis also was performed for the entire cohort, with race and sex terms included, to test for interactions using product terms. Predictive importance of the independent variables is indicated by their β-weights (regression coefficients for standardized data, Std β), which have a mean of 0 and an SD of 1. Regression coefficients derived from the race and sex stratified regression models were used to calculate percent change in BMD per unit change in the variable of interest. To adjust for the large number of comparisons, we selected a level of p < 0.001 for statistical significance. Results are given as the mean ± SD.

RESULTS

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Men were taller, heavier, had a greater LM, and lower absolute and relative FM than women (p < 0.001), with LM and FM higher in blacks (Table 1). Similar sex and race effects were observed for upper limb LM and FM. Regional and whole body BMD was greater in men than women and in blacks than whites, even after adjustment for height and body weight. Further, race and sex differences for upper and lower limb BMD were independent of LM and FM or age, study site, height, LM, and FM. However, both adjustments resulted in no difference between black women and white men for whole body BMD or between white women and white men for femoral neck BMD. Handgrip strength and knee extensor torque were higher in men than in women and higher in blacks than in whites (p < 0.001). After adjustment for body size or LM, sex differences remained in muscle strength. Regarding members of the Health ABC cohort who did not have complete measures, they were not distinguished from those included in this report with regard to body composition, muscle strength, hip, or upper limb BMD; however, whole body and lower limb BMD were higher in white men and white women with incomplete measures as was lower limb BMD in black women.

Table Table 1.. Descriptive Characteristics by Sex and Race (Mean ± SD)
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Physical activity energy expenditure was lowest in black women and highest in white men, with approximately one-quarter of white men expending >2000 kcal/week (Table 1). White men also had the lowest prevalence of thiazide usage and only 5% were current smokers. However, when categorized as either ever or never smokers, 71% of white men had smoked compared with 69% for black men, 41% for white women, and 44% for black women. Alcohol consumption was highest in white men, with 29% having four or more drinks per week, and lowest in black women. Estrogen replacement was higher in white women than black women, with an overall prevalence rate of 19%.

Correlations between study variables for the entire cohort, controlling for race and sex, are shown in Table 2. Age was negatively associated and height and weight were positively associated with each study variable. The partial correlations were stronger for LM and BMD than for FM and BMD. However, when stratified by race and sex, the principal difference among the groups was the stronger correlation between FM and BMD in black women at each skeletal site (femoral neck, LM r = 0.45 and FM r = 0.48; whole body, LM r = 0.35 and FM r = 0.30; upper limb, LM r = 0.47 and FM r = 0.34; lower limb, LM r = 0.41 and FM r = 0.39; p < 0.001 for all).

Table Table 2.. Partial Correlations Between Study Variablesa
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Table 3 displays the standardized regression coefficients and percent difference in regional and whole body BMD per unit change in muscle strength, LM, and FM. At the femoral neck, LM was a significant independent contributor to BMD across race and sex, with a unit (7.5 kg) increase in LM associated with a 4.7-5.9% increase in BMD. However, in women, but not men, FM had a similar independent effect on bone, with a unit (7.5 kg) increase in FM associated with a 4.0-4.4% increase in BMD. Similar results also were obtained if the total hip was substituted for the femoral neck.

Table Table 3.. Standardized Regression Coefficients (β-Weights, Std β) and Percentage Change BMD (g/cm2) per Unit Change in Soft Tissue and Muscle Strength by Race and Sex
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For the upper limb, limb LM was the dominant independent contributor to BMD in each group with grip strength and FM independently contributing to bone density in black women. A unit (0.5 kg) increase in upper limb LM was associated with a 3.0-3.4% increase in upper limb BMD. In comparison, a unit increase in strength (7.5 kg) and upper limb FM (0.5 kg) was associated with a 0.9% and 1.5% increase in BMD in black women, respectively. Upper limb soft tissue was entered in the multiple regressions because the upper limb is a non-weight-bearing bone. To explore the potential hormonal effect of total adipose mass, whole body FM was entered in the regressions as a substitute for upper limb FM; however, the results essentially were unaltered.

A significant sex interaction with FM (p < 0.001) emerged for lower limb BMD when all subjects were included in the regression model. FM and muscle strength were significantly related to bone in women but not in men. In women, a unit increase in FM and muscle strength was associated with a 1.7-2.0% and 1.9-2.2% increase in BMD, respectively. LM also was an independent contributor to lower limb BMD in all groups except white women. Similarly, for the whole body, with all subjects included in the regression model, there was a sex × FM interaction (p < 0.001) with FM inversely associated to BMD in men. For all groups, except white women, LM was the dominant significant contributor to whole body BMD; a unit increase in LM was associated with a 3.0-4.7% increase in BMD.

When BMD was divided by height in an attempt to factor out bone size, the importance of LM diminished and FM increased (Table 4). At the femoral neck, FM became a significant contributor in white men while the independent effect of LM in men and women was no longer important. A similar pattern also emerged for femoral neck BMAD, with the importance of LM reduced in all groups (Std β = −0.050-0.066; p > 0.001) and FM a significant contributor in women (Std β = 0.287-0.342; p < 0.001) and white men (Std β = 0.187; p < 0.001). Similarly, for lower limb and whole body BMD divided by height, the effect of LM was significantly reduced, while the effect of FM became stronger at the lower limb in women. However, for the upper limb, the effect of LM, although diminished, remained a significant contributor in men and white women. In calculating BMD/ht, the importance and contribution of muscle strength at each site remained substantially unaltered.

Table Table 4.. Standardized Regression Coefficients (β-Weights, Std β) and Percentage Change BMD/Height per Unit Change in Soft Tissue and Muscle Strength by Race and Sex
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Regarding multicollinearity of the independent variables in the regression models, the VIF ranged from 1.57 to 3.04 for LM and FM and 1.23 to 1.91 for upper limb soft tissue, with an average VIF for all the variables entered in the models of 1.16-1.42.

DISCUSSION

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

Although bone density has a strong genetic component,(44, 45) multiple factors interact to modify bone mineral status. Two such factors are the components of body composition, LM and FM, as well as muscle strength. The present study was undertaken to determine if sex and/or race alters the relationship between these variables and BMD in a cohort of well-functioning elders. As expected, regional and whole body BMD was greater in men than women and in blacks than whites, even after adjustment for body size. Differences in the relationship between muscle strength and soft tissue with BMD did occur; however, these differences were by sex, not race. In men, bone mineral-free LM was the dominant independent contributor to BMD at the femoral neck, upper and lower limbs, and for the whole body. However, in women, FM also was a significant contributor to BMD at the femoral neck and lower limb while muscle strength contributed to limb BMD. When BMD was divided by height to adjust for body and bone size, the importance of LM diminished in all groups.

Sex and racial differences in bone density and body composition were expected. Numerous reports in the literature propose various biochemical mechanisms for racial differences in bone density,(10, 46–49) including a lower mechanostat setpoint in blacks.(50) In addition, sex and race differences in muscle strength also were apparent, with men stronger than women and blacks stronger than whites. Sex differences remained after adjustment for LM, inferring differences in muscle quality, although the nature of the strength test, that is, maximal voluntary strength, may have been a contributing factor.

Across race and sex, LM was a significant determinant of BMD, except for the lower limb and whole body in white women. Several lines of evidence support this relationship. Doyle et al.(51) showed a strong association between vertebral dry ash weight and psoas muscle weight, as did Vico et al.(52) for psoas muscle parameters by computer tomography and spine mineral density. With age, men experience similar rates of bone and lean tissue loss whereas FM increases,(53) and in women menopause is associated with an accelerated loss of fat-free tissue and skeletal mass.(24) Moreover, after hip fracture, Karlsson et al.(54) reported an increased rate of bone and muscle mass loss whereas FM increased. Our results in women are compatible to those of Chen et al.(18) who reported LM a significant independent predictor of hip and spine BMD and whole body bone mass in postmenopausal white women. Similarly, Aloia et al.(25) found fat-free mass predictive of total body calcium in black and white pre- and postmenopausal women. In addition, we found the same relationship to be true for white and black men in our cohort.

In contrast, Reid and colleagues(20–22) reported FM to be an independent predictor of regional and whole body BMD in pre- and postmenopausal women, with LM not contributing. We also found FM to be a significant contributor to BMD at the femoral neck in women but not men, with BMD increasing 4.0-4.4% per unit increase in FM. It appears that regional differences for the dependence of BMD on FM may be greater at weight-bearing locations than other skeletal sites, as proposed by Reid et al.(38) For the lower limb, FM in women but not men was a significant contributor to BMD. Several studies support both tissues having important effects on bone,(2, 26, 27) with the effects of adiposity becoming more important in postmenopausal women.(25, 26) The conversion of androstenedione to estrone, which occurs predominantly in adipose tissue,(55) is the proposed mechanism that would help maintain bone mass by reducing bone remodeling.(56) It also has been proposed that hyperinsulinemia(38) and alterations in the vitamin D-endocrine system(27, 57) associated with obesity may contribute to the FM-BMD relationship.

Of particular interest is that several studies reported sex differences in the relationship of soft tissue to bone. Baumgartner et al.,(5) Visser et al.,(6) and Reid et al.(21) reported body fatness to be more important to bone mineral in women than men. In contrast, Bevier et al.(28) found LM to be an independent predictor of lumbar spine bone density in older women but not men. We found sex and FM interactions for the lower limb as well as for the whole body, with FM having a positive influence on BMD in women. Reid et al.(21, 38) have proposed that the fat-BMD relationship is more marked in women because testosterone may dissociate fat and bone mass in men, despite the presence of the above mechanisms. Although a decline in gonadal function occurs with age, mean plasma testosterone levels in 75-year-old men are 65% of that in young adults, and 25% of men over 75 years have circulating levels within the upper quartile of values present in young men.(58)

In comparison with LM, the independent effect of muscle strength on bone density was negligible, significantly contributing only to limb BMD in women. When muscle strength was entered into the regression models without LM and FM, it contributed significantly to BMD in both sexes at all sites. Adding FM to the regressions did not alter this relationship; however, the addition of LM diminished the effect of muscle strength on bone, which is to be expected because muscle strength is proportional to the cross-sectional area of the muscle. Therefore, once the commonality shared with LM is taken into account, muscle strength contributed very little additional effect to BMD. Several studies have reported muscle strength to predict bone density at various skeletal sites in young and older men and women(3, 29, 31–33); however, these effects were independent of body weight not LM.

Our results showing an independent effect of LM on bone mass support the significant role that muscle has on bone, even in an elderly biracial population. However, the question is, Why is LM more important for the skeleton than FM? It is well recognized that the distribution of bone mass is regulated by mechanical loading,(59) which is shown clearly in studies involving athletes(60, 61) and those subjected to prolonged bed rest(62) or engaged in space flight.(63) For mechanical strain induced by gravity, it would appear inconsequential to the skeleton whether it is fat or lean tissue.(64) However, LM also directly loads the skeleton via muscle contractions that result from performing everyday activities as well as recreational and structured physical activity. Indeed, Frost(65) and Burr(66) maintain that the greatest loads on the skeleton come from muscle forces and these forces primarily are the result of muscle contraction. Both skeletal and muscle tissue respond to increased and decreased physical loading by hypertrophying and atrophying, respectively. In addition, both tissues respond to intrinsic factors such as somatotrophic and sex hormones.(64) These common hormonal effects are not only important during the rapid growth stage of adolescence, in which dramatic gains in bone and muscle mass are observed,(67) but also throughout adult life. Finally, twin studies suggest a modest genetic component may contribute to the covariance in BMD and LM,(44) although environmental factors predominantly mediate the association.(45)

The large biracial population in the present study consisted of well-functioning older men and women reporting no difficulties in performing activities of daily living, stair climbing, or in walking one-quarter of a mile. As such, the distribution of muscle strength, LM, and BMD may have been skewed toward higher values compared with a diverse population of elders with varying levels of independence; nevertheless, subject criteria for entry into the study describe approximately 70% of men and women in the 70- to 79-year age group.(68) This narrower range in values may have reduced the magnitude of the associations. Further, the narrow age range of our cohort and the cross-sectional nature of the study prevent extrapolation to other age groups or in making causal inferences.

In addition, the current investigation used the common bone parameter BMD, which adjusts bone mineral content (BMI) for the projected area of bone scanned. However, it has been proposed that the association found between soft tissue and bone mineral is dependent on the bone index used.(21, 27) Further, Baumgartner et al.(5) suggest that the positive associations found between fat-free mass and bone mineral may be a result of failing to control for body size and including bone mineral in fat-free mass. In the present analysis, LM excluded bone mineral content. Adjusting for bone or body size did not substantially alter the effect of muscle strength on bone; however, the importance of LM diminished and the contributing effect of FM increased, as indicated by the percent change in BMD/ht per unit change in FM. Nevertheless, as Khosla et al.(27) point out, in attempting to correct bone mass for bone and body size by using BMAD or BMD/height, the analysis actually may bias against the effects of LM on bone. In addition, these corrections result in only an estimate of volumetric density,(69) not the true volumetric density, which would need to be obtained to address this issue fully. Last, despite the theoretical advantages of adjusting for bone size, such as calculating BMAD, they do not appear to be superior to areal BMD for prediction of bone strength(70) or fracture risk.(71–73) Thus, examining the relationship of potential modifiers to BMD would appear to be of clinical importance.

In conclusion, among the measures studied, both LM and FM were associated with bone mineral depending on the skeletal region as well as the bone index used. LM was a significant determinant of regional and whole body BMD across race and sex, except for the lower limb and whole body in white women, with FM a significant contributor at the femoral neck and lower limb in women. In contrast, when bone mineral was expressed as BMD/ht, the associations with LM were diminished. The influence of muscle strength on BMD, significant in women for the limbs, appears to be mediated by LM. Although LM, FM, muscle strength, and BMD are under strong genetic control,(44, 45) all are amenable to environmental influences.(74, 75) As such, alterations in lifestyle resulting in the maintenance or increase in LM with age may have a positive effect on BMD in older adults, irrespective of race or sex.

Acknowledgements

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES

The following are the Health ABC principal investigators: Epidemiology, Demography, and Biometry Program, National Institute on Aging (Project Office), Tamara B. Harris, M.D., M.S., senior project officer, and Eleanor Simonsick, Ph.D., project officer; University of Pittsburgh, PA (Field Center), Anne B. Newman, M.D., M.P.H., principal investigator; University of Tennessee, Memphis, TN (Field Center), Stephen B. Kritchevsky, Ph.D., principal investigator; University of California, San Francisco (Coordinating Center), Steven R. Cummings, M.D., principal investigator. This study was funded by National Institutes on Aging (NIA) contract numbers N01-AG-6-2102, N01-AG-6-2103, and N01-AG-6-2106.

REFERENCES

  1. Top of page
  2. Abstract
  3. INTRODUCTION
  4. MATERIALS AND METHODS
  5. RESULTS
  6. DISCUSSION
  7. Acknowledgements
  8. REFERENCES
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