Abstract
Context:
Little information exists about longitudinal changes in body composition and physical function in relation to sex hormone levels in older men.
Objective:
The aim of the study was to determine associations of testosterone, estradiol, and SHBG with changes in body composition and physical function.
Design and Setting:
We conducted a prospective cohort study within the Osteoporotic Fractures in Men (MrOS) study at six U.S. clinical centers.
Participants:
A total of 5994 ambulatory men aged 65 yr or older enrolled in the MrOS. We examined 1183 men with complete measures of sex steroid hormones, body composition, and some measure of physical function.
Intervention:
There were no interventions.
Main Outcome Measure(s):
Sex steroids were measured by mass spectrometry in serum collected at baseline. Measurements of body composition using dual-energy x-ray absorptiometry and physical performance (grip strength, leg power, timed chair stands, narrow walk, and 6-m walk) were performed at baseline and repeated 4.5 yr later.
Results:
Overall, men lost 1.3 kg (±4.4 sd) weight between study visits. Lean mass, especially appendicular, declined less at higher baseline testosterone levels (P < 0.05). These associations were most evident in the 40% of men who lost more than 2.0 kg during follow-up. In weight losers, higher testosterone was associated with less decline in timed chair stands. Estradiol was not related to body composition or physical function changes. Higher SHBG was associated with less loss of appendicular lean mass and grip strength.
Conclusions:
Higher endogenous testosterone is associated with reduced loss of lean mass and lower extremity function in older men losing weight. Endogenous testosterone may contribute to healthy aging.
Sex steroid levels, lean mass, and physical function tend to decline with age (1–13), yet little information exists about the relation of endogenous sex hormone levels to changes in body composition and physical function in older men. Men lose more muscle mass (8, 14–17) and strength (3, 5, 18, 19) than women as they age, suggesting that endogenous sex steroids, and testosterone in particular, may contribute to body composition and physical function changes. Also, exogenous testosterone supplementation in older men is associated with increases in lean body mass, decreases in fat mass, and improved muscle strength (20–23).
Previous longitudinal studies of body composition were conducted mostly in young and middle-aged men (24, 25) who differ from older men in body composition and sex steroid levels (11, 26, 27). In 110 Japanese-American men aged 64 yr on average, total testosterone was not associated with change in total body fat but was inversely associated with changes in intraabdominal fat (28). Lean mass changes were not reported. Some (29, 30), but not all (31), longitudinal studies of physical function report that higher testosterone levels are associated with less decline in physical performance measures or mobility. Whether changes in body composition modify this possible association of testosterone with physical performance has not been reported.
Unraveling the association between sex steroids and changes in body composition and physical function in older men is an important public health issue. Loss of muscle mass and strength contribute to frailty (32–34) and are associated with falls, mobility limitations, incident disability, and fractures (9, 10, 35, 36). Increased adiposity is associated with overall ill health, disability, and cardiovascular disease in older men (37). Loss of lean mass and loss/gain of fat mass are associated with increased mortality in older men (38). To specifically address effects of sex steroids and body composition changes in elderly men, we used data from a large cohort of U.S. men aged 65 or older from the Osteoporotic Fractures in Men (MrOS) study. We tested the hypothesis that higher baseline measures of sex steroids or SHBG are associated with lesser declines in lean mass, less gain in fat mass, and maintenance of physical performance over an average follow-up of 4.5 yr.
Subjects and Methods
Subjects
MrOS is a multicenter prospective observational study of musculoskeletal health in older men. Its design is detailed elsewhere (39, 40). The MrOS cohort was recruited from six clinical sites using mass mailing and enrolled 5994 community-dwelling, ambulatory men aged 65 yr or older without bilateral hip replacements (40). Each center's Institutional Review Board approved the study, and participants gave written informed consent.
We selected 2048 men from the cohort (n = 5995) for steroid measurements; 1602 Caucasian men were chosen at random, and we included all 446 non-Caucasian men (Fig. 1). Those taking androgens, antiandrogens, opioids, or oral corticosteroids at baseline or those missing baseline medication data (n = 205), sex steroid values (n = 42), or body composition measures (n = 14) were excluded. Of those remaining, 1272 men had both baseline and repeat body composition measurements. At the follow-up visit, men taking androgens, antiandrogens, opioids, or oral corticosteroids or missing medication data were also excluded (n = 89). The remaining 1183 men are the subject of this report.
Fig. 1.
Outline of participant inclusion.
Questionnaire data
Participants completed two study visits, 4.5 yr apart. At baseline, race/ethnicity, smoking/alcohol consumption, self-reported health status, and medical history were determined by questionnaire. All prescription medications validated by the clinics were recorded in an electronic medications inventory database (San Francisco Coordinating Center, San Francisco, CA). Each medication was matched to its ingredient(s) based on the Iowa Drug Information Service (IDIS) Drug Vocabulary (College of Pharmacy, University of Iowa, Iowa City, IA) (41). Physical activity was assessed with the Physical Activity Score for the Elderly (PASE) (42). Mental functioning and physical health were measured with the Medical Outcomes Study 12-Item Short Form (SF-12) (43).
Body composition measures
Weight was measured in indoor clothing without shoes using a calibrated balance beam scale. Body composition was measured using dual-energy x-ray absorptiometry (DXA) (QDR 4500W; Hologic Inc., Bedford, MA) as previously described (39, 44). A central quality control laboratory, certification of DXA operators, and standardized procedures for scanning ensured reproducibility of DXA measurements. At baseline, a Hologic whole body phantom was circulated at the six clinical sites. Variability across clinics was within acceptable limits, and cross-calibration correction factors were not required. Each clinic scanned a Hologic whole body phantom throughout the study to monitor longitudinal changes, and correction factors were applied to participant data as appropriate. Validity of these DXA measures for assessing body composition in the elderly has been reported (45, 46).
Physical performance measures
Grip strength was assessed in each hand using a Jamar handheld dynamometer (47). The maximum score of two trials for the dominant hand was used for analysis. Lower extremity power was measured with the Nottingham Power Rig (48, 49), a very reliable measure of leg power in the MrOS cohort (50). Walking speed was determined by timing completion of a 6-m course performed at the participant's usual walking speed. The time to complete a tandem-walking course of 6 m × 20 cm was used to determine balance. A trial was considered successful if the participant had no more than two deviations from the lane. Participants' ability to rise from a chair without use of arms, along with their ability to complete five chair stands, and the time required to complete the task were determined. Participants who could not complete a physical function measure were classified as “unable” and were assigned a value from the lowest end of the cohort distribution. Participants missing a value were excluded from analyses. All participants had data for at least two physical function measures, and 98% had data for at least four physical function measurements at both visits.
Sex steroid measurements
Baseline fasting morning blood was collected: serum was prepared immediately after phlebotomy and stored at −70 C. Total serum testosterone (total T) and estradiol (total E) were measured using combined gas chromatographic negative ionization tandem mass spectrometry (GC/NCI/MS/MS) and liquid chromatographic electrospray tandem mass spectrometry (LC/ESI/MS/MS) bioanalytical methods (Taylor Technology, Princeton, NJ). A 1/(concentration)2 weighted least squares regression procedure was used to fit a linear function to the calibration data. The lower limit of detection for estradiol was 0.625 pg/ml (2.29 pmol/liter) and for testosterone was 25.0 pg/ml (0.09 nmol/liter). Duplicate aliquots from each participant were assayed and averaged. Intra- and interassay coefficients of variation (CV) were 2.5 and 6.0%, respectively, for testosterone and 6.4 and 10.1%, respectively, for estradiol. Serum SHBG concentrations were measured using an Immulite Analyzer with chemiluminescent substrate (Diagnostic Products Corp., Los Angeles, CA). The standard curve ranged from 0.2 to 180 nm/liter. The SHBG intraassay CV was 4.4%, and interassay CV was 6.0%. Albumin values for free hormone calculations were obtained from baseline serum using routine colorimetric methods (Roche COBAS Integra 800 automated analyzer; Roche Diagnostics, Indianapolis, IN; interassay CV, 2.0%). Bioavailable fractions of testosterone (bioT) and estradiol (bioE) were calculated using the method of Södergård et al. (51).
Statistical analysis
Baseline characteristics were compared by total T quartiles using χ2 for categorical variables and ANOVA F-test or Kruskal-Wallis tests for continuous variables.
Restricted cubic spline models were used to visualize the shape of the association between baseline measures of sex steroids and absolute change in body composition measures to test for nonlinearity in the associations (52). These assessments provided evidence that effects were linear. Therefore, linear regression models were used to compare change in body composition and physical function measures, with results presented as adjusted means and P values for trend across quartiles of total T, total E, and SHBG. Initial models were adjusted for study site, age group, and race only, and then for multiple potential confounders. Analyses were repeated using bioavailable sex steroid levels. Total and bioavailable fractions of the sex steroids were highly correlated (r = 0.88 for correlation between bioT and total T; r = 0.92 for correlation between bioE and total E).
We evaluated several potential confounding factors known to influence sex steroid measures, body composition, and physical function including demographic (age group, study clinic site, race/ethnicity), lifestyle (alcohol use/smoking), physical activity (PASE) (42), physical and mental health (SF-12) (53), and self-reported clinician-diagnosed medical conditions (diabetes, non-skin cancer) (39). During descriptive analyses, we determined which factors varied according to both sex steroid levels and body composition or physical function. These factors were then added into the model individually in the multivariable analysis, and those models were compared with the crude model that contained only baseline sex steroid quartiles. Variables were retained in the final model if they altered the association between any sex steroid and any body composition (for body composition models) or physical function (for physical function models) measure by 10% or more (54).
We also examined change in lean mass models adjusted for fat mass change and change in fat mass models adjusted for lean mass change. Finally, we tested whether the association between body composition measures and sex steroids depended significantly on age (>75 vs. ≤75 yr), self-reported health status (excellent/good vs. fair/poor/very poor), and weight change (gain = >2.0 kg body weight gain; stable = ≤2.0 kg change in body weight; loss = >2.0 kg body weight loss). An interaction term was included in the multivariate analysis of covariance, and stratification analysis was performed when the interaction term was significant (P < 0.05).
Statistical analyses were completed using SAS v9.2 (SAS Inc., Cary, NC).
Results
Baseline characteristics
We included 1183 men with an average age of 72.3 yr at baseline (Fig. 1). Almost three fourths were Caucasian. Men with higher total T levels had better self-rated health status (P = 0.0004), fewer (non-skin) cancer diagnoses (P = 0.005), better physical health (measured by the SF-12's physical summary score; P = 0.05), and were less likely to report diabetes (P < 0.0001) than those with lower total T levels (Table 1). Men in the analysis were younger (P < 0.0001), healthier (P < 0.0001 on several measures of health), more physically active (P < 0.0001), and more likely to be white (P = 0.006) and nonsmokers (P = 0.02), compared with those excluded from the analysis because they did not return for the second visit. Men in the analysis had higher baseline lean mass (57.1 vs. 55.7 kg; P = 0.0004) but not different baseline fat mass compared with those who did not return.
Table 1.
Demographics by baseline total T quartiles
| Baseline characteristics | Quartiles of total T |
||||
|---|---|---|---|---|---|
| 1 (lowest) | 2 | 3 | 4 (highest) | P valuea | |
| n | 296 | 296 | 296 | 295 | |
| Total T range (nmol/liter)b | 5.5–303.0 | 304.0–394.0 | 395.0–495.0 | 496.0–1340.0 | |
| Age (yr) | 0.78 | ||||
| 65–69 | 106 (35.8) | 121 (40.9) | 103 (34.8) | 117 (39.7) | |
| 70–74 | 86 (29.1) | 82 (27.7) | 86 (29.1) | 88 (29.8) | |
| 75–79 | 74 (25.0) | 65 (22.0) | 76 (25.7) | 58 (19.7) | |
| 80+ | 30 (10.1) | 28 (9.5) | 31 (10.5) | 32 (10.9) | |
| Study site | 0.25 | ||||
| Birmingham | 47 (15.9) | 45 (15.2) | 29 (9.8) | 34 (11.5) | |
| Minneapolis | 46 (15.5) | 44 (14.9) | 39 (13.2) | 39 (13.2) | |
| Palo Alto | 67 (22.6) | 54 (18.2) | 70 (23.7) | 67 (22.7) | |
| Pittsburgh | 48 (16.2) | 43 (14.5) | 48 (16.2) | 38 (12.9) | |
| Portland | 47 (15.9) | 63 (21.3) | 57 (19.3) | 54 (18.3) | |
| San Diego | 41 (13.9) | 47 (15.9) | 53 (17.9) | 63 (21.4) | |
| Caucasian race | 213 (72.0) | 211 (71.3) | 217 (73.3) | 203 (68.8) | 0.67 |
| Alcohol consumption | |||||
| None | 95 (32.1) | 91 (30.7) | 90 (30.4) | 94 (31.9) | 0.52 |
| <14 drinks/wk | 170 (57.4) | 165 (55.7) | 169 (57.1) | 177 (60.0) | |
| ≥14 drinks/wk | 31 (10.5) | 40 (13.5) | 37 (12.5) | 24 (8.1) | |
| Ever smoked | 191 (64.5) | 178 (60.1) | 182 (61.5) | 168 (57.0) | 0.30 |
| Self-rated health | 0.0004 | ||||
| Excellent | 89 (30.1) | 104 (35.1) | 118 (40.0) | 128 (43.4) | |
| Good | 159 (53.7) | 156 (52.7) | 159 (53.7) | 143 (48.5) | |
| Fair/poor/very poor | 48 (16.2) | 36 (12.2) | 19 (6.4) | 24 (8.1) | |
| Non-skin cancer | 61 (20.6) | 48 (16.2) | 37 (12.5) | 32 (10.9) | 0.005 |
| Self-reported history of diabetes | 51 (17.2) | 30 (10.1) | 24 (8.1) | 17 (5.8) | <0.0001 |
| Physical summary scale, median (IQR)c | 53.0 (45.3–56.6) | 55.4 (48.5–56.8) | 55.5 (48.4–56.8) | 54.5 (46.7–56.7) | 0.05 |
| Mental summary scale, median (IQR)c | 57.5 (53.9–59.5) | 57.9 (54.3–59.8) | 57.9 (55.2–59.8) | 57.9 (55.2–59.9) | 0.11 |
| Physical activity (PASE), mean (sd)d | 152.0 (68.6) | 152.3 (65.8) | 154.7 (66.9) | 156.6 (65.1) | 0.82 |
Data are expressed as number of subjects (%), unless described otherwise.
P values for categorical variables were compared using χ2 tests for categorical variables; P values for continuous variables with normal distributions were calculated using one-way ANOVA; P values for variables with skewed distributions were calculated using Kruskal-Wallis tests.
To convert metric units (ng/dl) to SI (nmol/liter), multiply the concentrations of testosterone by 0.0347.
Physical health and mental functioning were measured with the Medical Outcomes Study 12-Item Short Form (SF-12). A higher score indicates better functioning (43).
Total PASE score was computed by multiplying the amount of time spent in each activity (hours/week) or participation (yes/no) in an activity by the empirically derived item weights and summing over all activities. Therefore, higher PASE score means more physical activity participation (42).
Overall change in body composition
On average, participants in the MrOS study lost 1.0 kg (±4.2 sd) of body weight during the 4.5 yr of study follow-up; 426 (36%) lost more than 2 kg, 241 (20%) gained more than 2 kg, and 516 (44%) had stable weight (≤2 kg weight loss). Lean body mass declined [−1.16 (±2.12) kg] without a significant change in fat mass [0.17 (±3.03) kg].
Baseline sex hormones and change in weight
Neither total T, nor total E, nor SHBG was associated with subsequent change in weight (Table 2).
Table 2.
Change in body composition measures in relation to baseline sex steroid and SHBG quartiles in older men
| Quartiles |
Fully adjusteda | Adjusted for lean or fat changeb | ||||
|---|---|---|---|---|---|---|
| 1 (Lowest) | 2 | 3 | 4 (Highest) | |||
| Total T quartiles | ||||||
| Range (ng/dl)c | 5.5–303.0 | 304.0–394.0 | 395.0–495.0 | 496.0–1340.0 | ||
| n | 296 | 296 | 296 | 295 | ||
| Absolute change in weight | −1.41 (−2.09, −0.73) | −0.80 (−1.51, −0.09) | −0.59 (−1.32, 0.14) | −0.75 (−1.50, 0.01) | 0.09 | |
| Absolute change in lean mass | −1.42 (−1.75, −1.10) | −0.99 (−1.33, −0.65) | −1.05 (−1.39, −0.70) | −0.99 (−1.35, −0.63) | 0.04 | 0.07 |
| Absolute change in fat mass | 0.34 (−0.13, 0.80) | 0.53 (0.05, 1.02) | 0.83 (0.33, 1.33) | 0.58 (0.06, 1.10) | 0.29 | 0.65 |
| Total E quartiles | ||||||
| Range (pg/dl)c | 1.3–17.7 | 17.8–21.9 | 22.0–27.0 | 27.1–97.6 | ||
| n | 296 | 297 | 295 | 295 | ||
| Absolute change in weight | −0.57 (−1.28, 0.13) | −1.03 (−1.75, −0.32) | −1.19 (−1.90, −0.47) | −1.10 (−1.82, −0.38) | 0.16 | |
| Absolute change in lean mass | −1.02 (−1.36, −0.68) | −1.15 (−1.50, −0.81) | −1.24 (−1.58, −0.90) | −1.23 (−1.57, −0.89) | 0.21 | 0.32 |
| Absolute change in fat mass | 0.78 (0.29, 1.26) | 0.41 (−0.08, 0.90) | 0.45 (−0.04, 0.94) | 0.48 (−0.01, 0.97) | 0.32 | 0.52 |
| Baseline SHBG quartiles | ||||||
| Range (nmol/liter)c | 13.5–34.2 | 34.3–44.8 | 44.9–57.3 | 57.4–179.0 | ||
| n | 295 | 297 | 296 | 295 | ||
| Absolute change in weight | −1.18 (−1.86, −0.49) | −0.98 (−1.69, −0.26) | −0.85 (−1.59, −0.10) | −0.69 (−1.43, 0.04) | 0.19 | |
| Absolute change in lean mass | −1.19 (−1.52, −0.87) | −1.26 (−1.60, −0.92) | −1.05 (−1.40, −0.69) | −1.06 (−1.41, −0.71) | 0.28 | 0.40 |
| Absolute change in fat mass | 0.38 (−0.09, 0.84) | 0.71 (0.22, 1.20) | 0.39 (−0.12, 0.90) | 0.71 (0.21, 1.21) | 0.38 | 0.56 |
Data are expressed as adjusted mean in kilograms (95% CI). Means are fully adjusted.
P value for model adjusted for clinic site, age group, race, serum selection method, self-reported history of diabetes, self-reported history of non-skin cancer, and alcohol.
Full model + further adjusted for change in opposite body composition measure (i.e. for change in lean mass, model adjusted for change in fat mass; for change in fat mass, model adjusted for change in lean mass).
To convert metric units (ng/dl) to SI (nmol/liter), multiply the concentrations of testosterone by 0.0347 and multiply the concentrations of estradiol by 3.671.
Baseline sex hormones and change in lean body mass
Men with higher total T levels had less loss of total lean body mass compared with men with lower total T levels (−0.99 vs. −1.42 kg for highest vs. lowest total T quartile; P = 0.04; Table 2). However, this association was no longer significant after adjusting for change in fat mass (P = 0.07). Higher testosterone levels were more clearly related to reduced loss of appendicular lean mass (−0.63 vs. −0.96 kg for highest vs. lowest quartile; P = 0.003); this association persisted after adjustment for fat mass (P = 0.006). BioT had similar associations with lean mass measures. Neither total E nor bioE was associated with change in lean body mass. SHBG was not associated with total lean mass, but higher SHBG was associated with less loss of appendicular lean mass (−0.66 vs. −0.82 for highest vs. lowest SHBG quartile; P = 0.04).
Baseline sex hormones and change in fat mass
Neither total T, nor total E, nor SHBG was associated with change in total fat or trunk fat mass (Table 2).
Association between sex steroids and change in body composition by age, health status, and weight change
We examined whether the observed associations between sex steroids and change in body composition varied by age (>75 yr vs. ≤75 yr), health status (excellent/good vs. fair/poor/very poor), or body weight change category [gain (>2.0 kg increase), stable (≤2.0 kg change), loss (>2.0 kg decrease)]. Neither age nor health status influenced the association between sex steroids and body composition (P > 0.07 for each).
There was a significant interaction of weight change category with the association between total T and change in total lean mass (P = 0.03) and total fat mass (P = 0.04). An association between total T and change in total lean and appendicular lean mass occurred only in the 426 men who lost more than 2.0 kg of body weight (−2.26 vs. −3.18 kg lean mass loss in highest vs. lowest total T quartile; P = 0.001; Fig. 2). No significant associations between total T and change in lean mass were detected in men who either gained weight or had stable weight (P > 0.20 for each). Among men with stable weight, those in the highest total T quartile gained slightly less total fat mass (0.80 vs. 1.12 kg fat mass gain in highest vs. lowest total T quartile; P = 0.05; Fig. 2). Total T was not associated with fat mass change in those who lost or gained weight.
Fig. 2.
Association between total T and body composition changes by weight change category. Models are adjusted for clinic site, age group, race, serum selection method, self-reported history of diabetes, self-reported history of non-skin cancer, and alcohol use.
There were no significant associations between total E and body composition by weight change category (P > 0.07 for each). Among men losing weight, higher SHBG was associated with less loss of appendicular lean mass (P = 0.03), but not total lean mass (P = 0.07). However, the SHBG association with appendicular lean mass change was not independent of sex hormone levels. There was no association between fat mass change and SHBG in any weight change group.
Baseline sex hormones and change in physical function
Overall, total T was not related to change in any physical function measure. However, when we limited our analysis to those men who had lost weight (where interaction between lean mass and total T was strongest), higher total T was associated with a smaller increase in chair stands time (P = 0.02; Table 3). However, total T was not associated with any of the remaining four physical function measures in men who lost weight. Although SHBG was not associated with any physical function measures in the entire cohort, higher SHBG was associated with a smaller decline in grip strength (P = 0.04) in those men who lost weight. However, the SHBG association with decline in grip strength was not independent of sex hormone levels. Further adjusting the models for change in lean mass attenuated the associations that had been noted between testosterone and chair stands (adjusted P = 0.05). Total E was not associated with change in any physical function measure (P > 0.15 for each).
Table 3.
Change in physical function measures in relation to baseline sex steroid and SHBG quartiles in men losing weight (≥2.0 kg body weight loss)
| Quartiles |
P valuea | ||||
|---|---|---|---|---|---|
| 1 (lowest) | 2 | 3 | 4 (highest) | ||
| Total T quartiles | |||||
| Range (ng/dl)b | 5.5–303.0 | 304.0–394.0 | 395.0–495.0 | 496.0–1340.0 | |
| n | 121 | 102 | 104 | 99 | |
| Absolute change in grip strength (kg) | −5.1 (−6.7, −3.4) | −3.9 (−5.6, −2.1) | −3.9 (−5.7, −2.0) | −3.4 (−5.4, −1.5) | 0.11 |
| Absolute change in leg power (watts) | −57.9 (−76.4, −39.4) | 46.3 (−660, −26.5) | −41.4 (−61.8, −20.9) | −49.6 (−70.7, −28.5) | 0.36 |
| Absolute change in time to complete five chair stands (sec) | 4.6 (3.2, 6.0) | 2.9 (1.4, 4.4) | 3.1 (1.5, 4.6) | 2.5 (0.9, 4.1) | 0.02 |
| Absolute change in 6-m normal walk pace (m/sec) | −0.17 (−0.23, −0.11) | −0.12 (−0.19, −0.06) | −0.11 (−0.17, −0.04) | −0.12 (−0.19, −0.05) | 0.17 |
| Absolute change in 20-cm narrow walk (m/sec) | −0.35 (−0.46, −0.25) | −0.29 (−0.40, −0.17) | −0.32 (−0.43, −0.20) | −0.25 (−0.37, −0.12) | 0.10 |
| Total E quartiles | |||||
| Range (pg/dl)b | 1.3–17.7 | 17.8–21.9 | 22.0–27.0 | 27.1–97.6 | |
| n | 97 | 111 | 109 | 109 | |
| Absolute change in grip strength (kg) | −4.2 (−6.0, −2.3) | −4.8 (−6.5, −3.0) | −4.0 (−5.8, −2.2) | −3.8 (−5.7, −1.9) | 0.49 |
| Absolute change in leg power (watts) | −51.3 (−71.8, −30.7) | −52.3 (−71.4, −33.2) | −48.9 (−68.4, −29.4) | −48.6 (−69.6, −27.7) | 0.69 |
| Absolute change in time to complete five chair stands (sec) | 4.3 (2.8, 5.9) | 3.6 (2.1, 5.0) | 2.8 (1.3, 4.3) | 3.4 (1.8, 4.9) | 0.20 |
| Absolute change in 6-m normal walk pace (m/sec) | −0.19 (−0.26, −0.12) | −0.11 (−0.17, −0.05) | −0.11 (−0.17, −0.04) | −0.16 (−0.23, −0.09) | 0.61 |
| Absolute change in 20-cm narrow walk (m/sec) | −0.33 (−0.45, −0.21) | −0.34 (−0.45, −0.23) | −0.28 (−0.39, −0.16) | −0.30 (−0.42, −0.18) | 0.53 |
| Baseline SHBG quartiles | |||||
| Range (nmol/liter)b | 13.5–34.2 | 34.3–44.8 | 44.9–57.3 | 57.4–179.0 | |
| n | 107 | 109 | 109 | 101 | |
| Absolute change in grip strength (kg) | −5.5 (−7.2, −3.8) | −4.0 (−5.7, −2.2) | −3.2 (−5.0, −1.3) | −3.5 (−5.4, −1.6) | 0.04 |
| Absolute change in leg power (watts) | −55.0 (−74.2, −35.8) | −52.5 (−71.6, −33.3) | −42.7 (−62.9, −22.5) | −46.4 (−67.7, −25.1) | 0.25 |
| Absolute change in time to complete 5 chair stands (sec) | 4.4 (2.9, 5.8) | 3.5 (2.0, 4.9) | 2.7 (1.2, 4.2) | 2.8 (1.2, 4.5) | 0.06 |
| Absolute change in 6-m normal walk pace (m/sec) | −0.17 (−0.23, −0.11) | −0.12 (−0.19, −0.06) | −0.11 (−0.17, −0.04) | −0.13 (−0.20, −0.06) | 0.31 |
| Absolute change in 20 cm narrow walk (m/sec) | −0.32 (−0.43, −0.21) | −0.36 (−0.47, −0.25) | −0.29 (−0.41, −0.18) | −0.23 (−0.35, −0.11) | 0.07 |
Data are expressed as adjusted mean (95% CI). Means are fully adjusted.
P value for model adjusted for clinic site, age group, race, serum selection method, self-reported history of diabetes, self-rated health, and physical summary scale.
To convert metric units (ng/dl) to SI (nmol/liter), multiply the concentrations of testosterone by 0.0347 and multiply the concentrations of estradiol by 3.671.
Discussion
Men aged 65 and older with higher testosterone levels had less loss of lean body mass over 4.5 yr compared with men with lower testosterone levels, but testosterone was less clearly related to preservation of physical function. The associations did not differ by age or self-reported health status but were most apparent in those who lost more than 2.0 kg of body weight. Thus, in the 40% of MrOS men who lost weight over 4.5 yr, higher testosterone levels were associated with relative preservation of lean mass and some attenuation in lower extremity functional decline.
This report provides new details about the association between sex steroids and body composition changes in a large cohort of community-dwelling older men. In younger men, lower endogenous testosterone has been associated with a greater increase in body mass index, waist circumference, and intraabdominal fat (24, 25, 28). However, body composition changes are different in older than younger men. Older men tend to lose lean mass as they age, but the magnitude of decline varies (8–10). Although lean mass decreases in older men who lose weight as well as in those whose weight is stable, the losses are greatest in men who lose weight (9, 10, 16). When we stratified our results by weight change category, the association between testosterone and loss of lean mass was only significant in men who had lost weight. We may have been able to detect the association between testosterone and lean mass only in this subgroup because they were the men who lost the most lean mass. Alternatively, testosterone may be associated only with changes in lean mass during negative energy balance.
In our study, higher testosterone levels were even more strongly associated with preservation of appendicular lean mass, which may be highly related to health outcomes such as strength and frailty. However, it was less clear that higher testosterone levels translated into less decline in physical function in our cohort. Testosterone was not associated with change in physical function in the entire cohort. This is consistent with previous studies which found that total T was not associated with decline in physical performance (walking speed, chair stands, tandem stand) or strength (handgrip strength) or development of frailty (29, 30, 55). Lower free testosterone levels have been associated with higher frailty and a greater risk of mobility limitations 5 to 6 yr after the sex steroid measurement (29, 30). However, free testosterone measurements may be less accurate and reproducible than total T measures (56). We did find that in men who were losing weight (where the association between testosterone and lean mass was strongest), higher testosterone levels were associated with less loss of lower extremity function, as evidenced by a smaller increase in time to complete five chair stands. Adjustment for lean mass change slightly attenuated this association, suggesting that effects of testosterone on lean muscle mass may mediate the positive association between testosterone and lower extremity function in men losing weight. Consistent with previous reports (3, 5), our results suggest that physical function decline is likely a multifactorial process. The association between testosterone and change in physical function may depend on how body composition is changing in the population being studied. Further research should examine these associations more closely because preserving physical function could ultimately have important health implications through decreased risk of falls, risk of mobility limitations, incident disability, and fractures (9, 35).
Our study has several strengths. It is the first well-powered study to prospectively address the longitudinal association between body composition, physical function, and sex steroids in older men. We used gas chromatography/mass spectrometry to measure sex steroids; gas chromatography/mass spectrometry is accurate at the low sex hormone concentrations seen in older men (57, 58). Body composition was carefully measured with DXA, and potential confounding variables, including age, race/ethnicity, medications, medical history, mental functioning, alcohol, physical activity, and physical health, were evaluated. Many men were more than 80 yr old, a population sector that is increasing steadily but whose sex hormone distribution and body composition changes have not been well studied.
There are also several limitations. We made multiple comparisons and examined five sex steroid measures and numerous body composition outcomes. We could not determine whether weight loss was intentional or unintentional. This distinction may be important and should be further evaluated in future studies. Although we evaluated many factors known to influence sex steroid measures and body composition or physical function, we may not have controlled for every comorbid condition or medication that might lower testosterone levels. We also did not examine diurnal variations in testosterone levels, but all samples were obtained in the morning and diurnal variation is limited in older men (59). Sex hormones were measured only at baseline. Studies with longitudinal measurements of sex steroid hormones are needed to establish an association between longitudinal changes in sex steroids and changes in body composition and physical function.
In conclusion, higher testosterone levels were associated with less lean mass loss in older men, especially those who were losing weight. This was accompanied by evidence of attenuation in the decline in lower extremity performance in those losing weight. Maintaining lean mass, particularly appendicular lean mass, is an important component of healthy aging. The association between higher endogenous testosterone and less lean mass and lower extremity performance loss is consistent with our previous reports that higher testosterone levels are associated with a lower incidence of falls and less frailty (32, 60). Our study adds evidence to the growing body of literature that higher levels of endogenous testosterone may be favorably associated with some components of healthy aging in men.
Acknowledgments
We thank Martie Sucec for her editorial assistance and Desirée Pheister and Terresa Fair for their assistance with manuscript preparation.
The Osteoporotic Fractures in Men (MrOS) Study is supported by National Institutes of Health funding. The following institutes provide support: the National Institute of Arthritis and Musculoskeletal and Skin Diseases, the National Institute on Aging, the National Center for Research Resources, and NIH Roadmap for Medical Research under the following grant numbers: U01 AR45580, U01 AR45614, U01 AR45632, U01 AR45647, U01 AR45654, U01 AR45583, U01 AG18197, U01-AG027810, and UL1 RR024140. In addition, E.S.L. is supported by K23-RR020049, and L.M.M. is supported by R01HL084184 and P60AR05473101.
Disclosure Summary: E.B.-C. has received grants from Merck, Arena, Roche, and Pfizer pharmaceuticals. J.A.C. has received research grants and consulting fees from Novartis, Inc. These financial supports do not represent a conflict of interest. The remaining authors have no financial disclosures.
Footnotes
- bioE
- Bioavailable estrogen
- bioT
- bioavailable testosterone
- CV
- coefficients of variation
- DXA
- dual-energy x-ray absorptiometry
- total E
- total estradiol
- total T
- total testosterone.
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