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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 62:330-335 (2007)
© 2007 The Gerontological Society of America

Loss of Appendicular Muscle Mass and Loss of Muscle Strength in Young Postmenopausal Women

Yves M. Rolland, Horace M. Perry, III1,2, Ping Patrick, William A. Banks and John E. Morley

1 Geriatric Research, Education and Clinical Center, St. Louis VA Medical Center, Missouri.
2 Division of Geriatrics, Department of Medicine, Saint Louis University School of Medicine, Missouri.
3 Service de Médecine Interne et de Gérontologie Clinique, Hôpital La Grave-Casselardit, INSERM Unit 558, Toulouse, France.

Address correspondence to Yves Rolland, MD, Division of Geriatrics, Saint Louis University, 1402 S. Grand, St. Louis, MO 63104. E-mail: yvesmrolland{at}yahoo.fr


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. Different factors may predict loss of appendicular muscle mass (LossAMM) and loss of muscle strength (LossMS). We investigated the relationship between LossAMM or LossMS and baseline anthropometric measures, lifestyle habits, hormones, lipid profiles, and inflammatory markers in 49 healthy postmenopausal women (54.1 ± 4.3 years) in a 24–36-month prospective study.

Methods. We measured parameters of lifestyle habits, anthropometry, lipid profiles, and blood levels of testosterone, estrone, estradiol, cortisol, dihydroepiandrostenedione, luteinizing hormone, intact parathyroid hormone (iPTH), 25-hydroxyvitamin D, thyroxine, leptin, adiponectin, C-reactive protein (CRP), and interleukin-6 and interleukin-2 receptors. Percentage of loss per year of isometric knee extensor strength defined LossMS, and percentage of loss of AMM per year (dual x-ray absorptiometry) defined LossAMM.

Results. The means (standard deviation) for LossMS and LossAMM were 1.17%/y (2.03) and 0.60%/y (0.74) and did not correlate (r = –0.001; p =.99). LossMS correlated negatively with level of physical activity (r = –0.28), femoral BMD (r = –0.30), alcohol consumption (r = –0.30), and luteinizing hormone (r = –0.32) and positively with estrone (r = 0.29) and iPTH (r = 0.32) (each at p <.05). LossAMM correlated negatively with AMM (r = –0.41; p <.01). Stepwise regression analyses showed that LossMS was significantly predicted by baseline physical activity (beta = –0.39) with an explanation of variation of the model (R2) of 6%, body mass index (BMI) (–0.40; 3%), high-density lipoprotein cholesterol (–0.29; 3%), estrone (0.32; 6%), iPTH (0.27; 7%), and interleukin-2 receptor (0.32; 5%). LossAMM was predicted by baseline height (0.56; 47%), body mass index (1.04; 83%), AMM (–0.92; 76%), thyroxine (–0.33; 8%), estrone (–0.61; 30%), and dihydroepiandrostenedione (0.44; 28%).

Conclusions. LossMS and LossAMM in young postmenopausal women were not correlated with one another, and were determined by different factors.

THE loss of muscle mass and muscle strength with aging (1) results in an increased risk of functional limitation (2) and physical disability (3). Multiple mechanisms are thought to contribute to this phenomenon (4). Lifestyle habits, such as physical inactivity and aged-related changes in hormones and cytokine levels, are proposed to be the most important causes. However, the relative contribution of these factors to the loss of muscle mass or strength is not clear. Although strength is strongly correlated with muscle mass, aging muscle is also associated with metabolic and histological changes leading to a decreased muscle quality (muscle strength corrected for muscle mass). Each factor involved in the pathophysiology of sarcopenia may potentially make a relative contribution to the loss of muscle strength and/or the loss of muscle mass. The notion that muscle strength and muscle mass may be to some degree independently affected is supported by experimental and clinical studies (5–9).

Understanding mechanisms leading to the loss of muscle strength and the loss of muscle mass is important because increases in muscle mass versus muscle strength may not have the same effects on prevention of mobility, disabilities, or diseases. During the postmenopausal period, loss of muscle mass and muscle strength have been shown to be accelerated (10) and may benefit from preventive intervention (11). The aim of this prospective study was to investigate the relationship between the loss of appendicular muscle mass (LossAMM) or the loss of muscle strength (LossMS) and lifestyle habits, anthropometric measures, lipid profiles, hormones, and inflammatory markers in young, postmenopausal women.


   METHODS
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 Abstract
 Methods
Results
 Discussion
 References
 
Population
Seventy-seven Caucasian women volunteered to participate in this study. Participants were recruited by advertisement. Free follow-up and body composition assessment was the incentive for them to participate. To be included, participants had to be postmenopausal (at least 6 months since their last menses) and had to have no hormone replacement therapy, no diabetes, no treatment for lipid or thyroid disorders, no steroid treatments, and no infection in the previous 2 months. Mean length (standard deviation [SD]) since last menses was 41.50 ± 27 months (range 6–100 months).

Participants were screened at baseline and at 6, 12, 24, and 36 months with a medical history questionnaire, physical examination, physical performance assessment, dual-energy x-ray absorptiometry, and fasting blood profiles. For the present analyses, we included baseline participants reporting at least one visit at 24 and/or 36 months. Analyses were performed on baseline variables and the AMM and knee extensor strength measures at 24 or 36 months of the follow-up. Among the 77 initial participants of this ongoing study, 28 participants did not fit the inclusion criteria because of recent inclusion (no visit at 24 months). The sample population considered for the present analysis consisted of 49 women with a mean age of 54.1 ± 4.3 years (range 45–62 years) and body mass index (BMI) of 24.5 ± 3.0 kg/m2 (range 18–35 kg/m2).

This study was approved by the Institutional Review Boards of the Saint Louis VA Medical Center, Missouri. Each participant provided written informed consent to participate in the study.

Protocol
The medical history questionnaire included items about medications and months since the last menses. Lifestyle habits assessment was performed with standardized scales and questionnaires. Physical activity levels were obtained by standardized validated measurements (12). Present and previous history of smoking was obtained by direct inquiry. Alcohol intake was quantified by self-reporting in a structured interview that used a questionnaire for the previous 3 months. Lifetime alcohol consumption was estimated with a questionnaire (Lifetime Drinking History) (13).

Physical examination included anthropometric measurements using standardized techniques. BMI was defined by the weight/height2 ratio in units of kilograms per meters squared.

Direct body composition measurement.-- AMM, lean mass (LM), fat mass (FM), and femoral and lumbar spine bone mineral density (BMD) were evaluated by dual-energy x-ray absorptiometry (DXA) (Hologic QDR 4.500 W; Waltham, MA). Coefficients of variation in the laboratory and in this population for the measures of LM and AMM were 1.8% and 3.4%, respectively.

Evaluation of Muscle Strength.-- Maximum isometric knee extensor strength was measured for both legs with a Biodex apparatus (Biodex Measuring Inc., Shirley, NY). The size of an adjustable straight-back chair with the pelvis fixed by a strap was adjusted so that the participant felt comfortable. The mean coefficient of variation for the knee extensor muscle strength was 1.8% (±1.9). The maximal peak strength (expressed in Newtons) was recorded for a set of three contractions in the right leg. For analysis, we used the highest score recorded.

Serum Studies
Women were scheduled in the morning and were instructed to fast after midnight the night before evaluation. Hormonal and inflammatory marker measurements were performed by the Clinical Geriatrics Laboratory. These variables have been reported to contribute to strength or muscle mass.

Intact parathyroid hormone (iPTH) measurement was performed by radioimmunoassay (RIA) (Incstar DiaSorin, Stillwater, MN). The intraassay and interassay coefficients of variation were 4.5% and 5.1%. Measurement of serum 25 hydroxy-vitamin D (25OHD) was performed using a commercially available test kit (Incstar). The intraassay and interassay coefficients of variation were 6.2% and 12.7%. Serum estrone and serum estradiol were measured using an RIA kit (ICN Biomedicals Inc., Costa Mesa, CA, and Diagnostic Systems Laboratory, Santa Monica, CA, respectively). The intraassay and interassay coefficients of variation were 7.2% and 11.1% for serum estrone and 6.5% and 9.7% for serum estradiol. Luteinizing hormone (LH) was measured using an RIA kit (ICN Biomedicals). The intraassay and interassay coefficients of variation were 7.3%, and 8.6%. Serum cortisol was measured using an RIA kit (Diagnostic Products Corp., Los Angeles, CA). The intraassay and interassay coefficients of variation were 3.5% and 4.0%. Serum dihydroepiandrostenedione sulfate (DHEA) was measured using an RIA kit (Diagnostic Products Corp). The intraassay and interassay coefficients of variation were 5.3% and 7.0%. Testosterone was measured using an RIA kit (ICN Biomedicals). The intraassay and interassay coefficients of variation were 6.7% and 7.3%. Leptin and adiponectin measurements were determined using a commercially available RIA kit (Linco Research, St. Charles, MO). In our laboratory, leptin and adiponectin had an intraassay coefficient of variation of 4.7% and 5.3% and an interassay coefficient of variation of 5% and 8.1%, respectively.

Soluble interleukin (IL)-6 receptor assay and soluble IL-2 receptor assay were performed using a commercially available enzyme-linked immunosorbent assay kit (INC Biomedicals and Endogen [Woburn, MA], respectively). These kits have intraassay and interassay coefficients of variation of 5.9% and 5.0% for the IL-6 receptor and 9.8% and 9.6% for the IL-2 receptor.

Blood levels of glucose, thyroxine, total cholesterol, low-density lipoprotein (LDL) cholesterol, high-density lipoprotein (HDL) cholesterol, and C-reactive protein (CRP) were performed in a commercial clinical laboratory (Smith Kline Beecham, St. Louis, MO).

Follow-Up
LossMS was defined as the mean percentage of knee extensor strength loss per year: LossMS (%) = [MSbaseline – MSfollow-up] x 12 x 100/[MSbaseline x number of months of follow-up]. LossAMM was defined as the mean percentage of AMM loss per year: LossAMM (%) = [AMMbaseline – AMMfollow-up] x 12 x 100/[AMMbaseline x number of months of follow-up].

Analysis
Study population characteristics and anthropometric and laboratory measurements were presented as proportions or mean values with their (SD), minimum and maximum, and 25th and 75th percentile. One value of leptin concentration was more than 3 SD above the mean value. This value (but not the participant) has been deleted from the analysis because all the other values from blood samples of this participant were in the normal range. LossMS and LossAMM presented a normal distribution. If appropriate, variables were normalized by transformation into their natural logarithm to improve the plots of residual analyses (physical activity, alcohol intake, triglycerides, T4, estrone, estradiol, DHEA, IL-2, leptin, CRP, testosterone). To show the associations between LossMS and LossAMM and anthropometric measurements, lifestyle habits, hormones, and inflammatory markers, Pearson's correlation coefficients were presented for the normally distributed variables and Spearman correlation for the skewed variables. To explore the relationship between LossMS and LossAMM and potential variables, linear regression analysis was applied. The initial models were composed of age, lifestyle habits (physical activity, alcohol intakes, smoking status), anthropometric measures (BMI, weight, height, waist/hip ratio, middle arm circumference, AMM, LM, FM), time since last menses, lipid profiles (total cholesterol, LDL cholesterol, HDL cholesterol), hormones (iPTH, 25OHD, estrone, estradiol, LH, cortisol, DHEA, testosterone, leptin, adiponectin, thyroxine), and inflammatory markers (CRP, IL-2 receptor, IL-6 receptor). These variables were taken into account for adjustment in the initial model to explain LossAMM and LossMS. Stepwise regression analyses with a backward selection method and a probability for stepwise removal of 0.05 were used to build the models. Results were expressed as standardized coefficients and R2, or proportion of variation explained by the predictor of interest.

Tests were two-sided, and p values lower than.05 were considered significant. Data analysis was performed with the commercially available statistical analysis program Statistica (StatSoft; Oklahoma City, OK).


   RESULTS
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 Methods
 Results
Discussion
 References
 
Characteristics of the population are presented in Table 1. Previous smoking was reported by 21% of the participants. Mean (SD) LossAMM and LossMS were 0.60%/y (0.74) and 1.17%/y (2.03), respectively, and both had a wide range of distribution (range 5.3%/y to –6.8%/y and 4.4%/y to –2.4%/y, respectively). LossMS did not correlate with LossAMM (r = –0.001, p =.99). Pearson (or Spearman if appropriate) correlations between LossMS and LossAMM and the other variables are presented in Table 2.


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  		Table 1. Physical Characteristics, Anthropometric and Body Composition Measures, Lifestyle Habits, Lipid Profiles, Hormones, and Inflammatory Marker Concentrations of the 49 Women.

 

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  		Table 2. Pearson (or Spearman) Correlation Coefficients Between Age, Lifestyle Habits, Anthropometric Measures, Lipid Profiles, Hormones, and Inflammatory Markers and Loss of Muscle Strength (LossMS) or Loss of Muscle Mass (LossAMM).

 
LossMS
Correlations between LossMS and the other variables are presented in Table 2. To further investigate LossMS, linear regression models were built with LossMS as the dependent variable and potential predictors as independent variables. In the initial model, various variables were significantly associated with LossMS: waist/hip ratio (beta = –0.49; standard error [SE] = 0.21, p =.04), physical activity (beta = –0.58, SE = 0.17, p =.005), estrone (beta = 0.80, SE = 0.25, p =.006) and IL-2 receptor (beta = 0.73, SE = 0.26, p =.01). Among the other variables, CRP was the only variable close to significant (beta = 0.35, SE = 0.19, p =.08). The final model was built by using the stepwise regression procedure. Results of the final models are presented in Table 3. When LossAMM was included in the initial model as explicative variable, LossMS was not significantly associated with LossAMM, and neither remained in the final model.


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  		Table 3. Results From Stepwise Regression Analyses With Loss of Muscle Strength as Dependent Variable and Potential Predictors as Independent Variables.

 
LossAMM
Pearson (or Spearman, if appropriate) correlations between LossAMM and the other variables are presented in Table 2. LossAMM correlated negatively with AMM (r = –0.41, p =.003). To further investigate LossAMM, linear regression models were built with LossAMM as the dependent variable and potential predictors as independent variables. In the initial models, AMM was the only variable significantly associated with LossAMM (beta = –0.96; SE = 0.42, p =.03). Other variables were close to significant (DHEA [beta = 0.46, SE = 0.24, p =.07], estrone [beta = –0.43, SE = 0.21, p =.06], testosterone [beta = –0.46, SE = 0.26, p =.09], triglycerides [beta = 1.13, SE = 0.73, p =.09]). The final model was built by using the stepwise regression procedure. Results of the final models are presented in Table 4.


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  		Table 4. Results From Stepwise Regression Analyses With Loss of Appendicular Muscle Mass as Dependent Variable and Potential Predictors as Independent Variables.

 

   DISCUSSION
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 Abstract
 Methods
 Results
 Discussion
References
 
In this study of young postmenopausal women, our results suggest that a high level of physical activity, markers of fatness (high BMI and HDL cholesterol), hormones (low concentration of estrone and low concentration of iPTH), and a low concentration of IL-2 receptor are associated with less LossMS. In contrast, less LossAMM seemed to be associated with anthropometric measures (low height, high AMM, low BMI) and hormones (high concentration of estrone and thyroxine and low concentration of DHEA).

Understanding the mechanisms associated with LossMS and LossAMM is relevant in young postmenopausal women, because this transition period is associated with an accelerated change in body composition (10) and muscle strength (11). With a yearly decline of 1.17% for muscle strength and 0.6% for AMM, LossMS and LossAMM in our population were consistent with previously reported muscle strength (14) and muscle mass decline (15). The lack of correlation between LossMS and LossAMM in our study is consistent with the literature indicating that muscle mass and quality of muscle may be independently affected. This result suggested that each relied on differing mechanisms.

Physical activity is a well-recognized means to prevent the muscle aging process (16) and a major determinant of both muscle strength and muscle mass (6). However, rates of LossMS and LossAMM differ during inactivity. Inactivity results first in a decrease in muscle strength and second in a decrease in muscle size. In bed-rest studies, loss of strength is more significant than loss of muscle mass (17) and, conversely, muscle quality (strength adjusted based on muscle mass) has been shown to improve significantly with resistance training in older people (18). We found that low physical activity was a significant and independent predictor of LossMS but not of LossAMM. This result may be related to the initial consequence of a decreased level of physical activity during this period. Because a low level of physical activity results in muscle weakness that, in turn, generally results in reduced activity levels, changes in lifestyle habits during the postmenopausal period may be an important determinant of both LossMS and LossAMM in the long term.

Our results suggest that markers of fatness (high BMI and HDL cholesterol) were independent protectors of LossMS. This result gives rise to several different hypotheses: First, in the Health, Aging, and Body Composition Study, body fat of women 70 years old and older was significantly and inversely associated with strength and muscle quality (19). However, in active elderly individuals, we previously found that obesity improves muscle quality (20). Because higher weight increases mechanical (gravitational) load on weight-bearing extremities, physical activity may result in lower limb resistance training in our healthy women with a higher BMI, and finally results in higher knee extensor strength (6,20). It needs to be stressed that these assumptions are speculative, as the mean BMI placed this group of women in the normal category. Second, BMI and lipid profiles may be markers of higher nutritional intake. Food intake was not assessed in our study. However, higher caloric intake, which is usually associated with a higher BMI, may prevent LossMS. HDL cholesterol may also be affected by other factors such as physical activity, and higher BMI could also be an indicator of low physical activity level. Our results also suggest that anthropometric measures (BMI, height, AMM) are associated with LossAMM. In our sample, being a small woman with a high amount of AMM appears to have a preventive effect on LossAMM. This anthropometric profile may be associated with a more active lifestyle. A higher AMM may both promote and result from higher levels of activity. This anthropometric profile may also be associated with genetic determinants. The amount of muscle synthesis in response to physical activity may be under hereditary control.

There is growing evidence linking age-related hormonal changes to loss of muscle mass and muscle strength. However, controversy exists regarding the role of hormones on skeletal muscle in postmenopausal women.

Low levels of vitamin D have been shown to decrease muscle anabolism (21) and may result in higher levels of iPTH. However, when both 25-OHD and iPTH were included into the initial model, only iPTH remained a protective factor for LossMS after adjustment for potential predictors. Our results are supported by recent epidemiological studies reporting an independent association between high iPTH blood levels and reduction of muscle strength with aging (22).

In our population, estrone levels were found to prevent LossAMM. This result is in accordance with most of the findings of epidemiological and interventional studies (13,23). Estrogen may have anabolic effects on muscle, possibly in association with strength training (24) at replacement levels. In our participants, we found no interaction between serum levels of estrogen and levels of physical activity. Effects of estrogen on muscle strength and function are more controversial (25). Our results also suggested that estrone levels predicted LossMS. Estrone may have a greater effect on muscle mass than on muscle strength. In the Health, Aging, and Body Composition Study, estrogen replacement was associated with increased quadriceps cross-sectional area but not with increased knee extensor strength (25). Adjusted for muscle mass, our model suggests that estrone may reduce muscle strength. Another explanation may be that none of our participants had hormone replacement therapy, so the correlation was found with low levels of estrone. It may be that low levels of estrogens exert paradoxic effects on muscle strength or that endogenous estrogens have different effects than exogenous estrogens.

Our results regarding the effect of DHEA are in contrast with the assumption that reduced production of DHEA with aging results in decline of muscle strength and mass (26). However, DHEA replacement therapy did not result in increased muscle mass or muscle strength in one study (26).

Muscle is an important target organ for thyroid hormone. During hypothyroidism, muscle weakness is linearly related to thyroid hormone levels (27), and type II fiber atrophy has been described during hypothyroidism (28). However, experimental studies suggest that thyroxine affects predominantly muscle contractility (29). Although none of our participants had hypothyroidism, our results suggested that thyroxine levels may prevent LossAMM.

Increased levels of catabolic cytokines may result in loss of muscle mass (8). Our results suggested that a high level of soluble IL-2 receptor is related to LossMS. Our results add to previous work that even in healthy postmenopausal women, an inflammatory process leading to LossMS may already be involved.

Our work has several limitations. First, because this is a study of young Caucasian postmenopausal women and because loss of muscle mass and loss of muscle strength are in part related to the levels of sex hormones, generalization to men is not easy. Similar studies should be performed in different racial groups and in men. Second, loss of strength was limited to one specific muscle group (knee extensor). Other muscle groups may have different predictors of loss of muscle strength. Finally, many other hormones not tested in our study, such as insulin or growth hormone, or other lifestyle habits, such as intake of macronutrients and micronutrients, may modulate LossMS and LossAMM. Our final model explained only 34% of the variance for LossMS and 47% for LossAMM.

This longitudinal study suggests that underlying mechanisms of LossAMM and LossMS are multiple and different. We suggest that the relative contribution of each of these factors on muscle strength and/or muscle mass needs to be clarified in prospective preventive intervention studies.


   Acknowledgments
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 Abstract
 Methods
 Results
 Discussion
 References
 
This study was supported by National Institutes of Health grants R01AA12743 (to W.A.B.), R01NS41863 (to W.A.B.), and AA11130 (to W.A.B.), and by a VA Merit Review.


   Footnotes
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 Methods
 Results
 Discussion
 References
 
Decision Editor: Luigi Ferrucci, MD, PhD

Received September 16, 2005

Accepted May 30, 2006


   References
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 Results
 Discussion
 References
 

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