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Lean mass is associated with bone mineral density (BMD) in athletes, attributable to the anabolic pull of muscle on bone. Fat mass is also important, and subcutaneous fat positively and visceral fat negatively correlates with BMD in obese adolescents. The contribution of regional body composition to low BMD in amenorrheic athletes (AA) has not been elucidated. We hypothesized that in adolescent athletes (runners), BMD is associated positively with total fat (surrogate for subcutaneous fat) and lean mass, and inversely with percent trunk fat and trunk-to-extremity fat ratio (surrogates for visceral fat).
We examined BMD and body composition using dual energy X-ray absorptiometry (DXA) in 21 AA and 19 eumenorrheic athletes (EA) (12–18 years) (runners). We report total hip and height-adjusted BMD [lumbar bone mineral apparent density (LBMAD) and whole body bone mineral content/height (WBBMC/Ht)].
AA had lower BMD than EA. Lean mass was less strongly associated with hip BMD in AA than EA; fat mass was positively associated with LBMAD in EA. Percent trunk fat and trunk-to-extremity fat ratio were inversely associated with lumbar and WB measures in AA. In a regression model, lean and fat mass were positively, and percent trunk fat and trunk-to-extremity fat ratio negatively associated with LBMAD and WBBMC/Ht for all athletes, even after controlling for serum estradiol.
DXA surrogates for visceral fat are inversely associated with bone density in athletes.
Athletes are typically expected to have higher bone mineral density (BMD) than their sedentary counterparts in body regions experiencing mechanical loading (1, 2). However, poor nutritional status and impaired menstrual function can attenuate the beneficial effects of exercise, and the female athlete triad of low energy availability, menstrual dysfunction and low bone mass is a common entity in young female athletes. Cross-sectional studies have reported that up to 24% of adolescent athletes experience menstrual irregularities (oligomenorrhea or amenorrhea) (3), and we found disordered eating patterns in up to 62% of female high school athletes with amenorrhea (4). Although menstrual irregularity and low energy intake are known predictors of low BMD, bone density also varies with type of exercise. Athletes participating in repetitive impact sports (such as running) have a higher risk of developing low BMD and subsequent fractures than those participating in activities associated with high ground reactive forces (such as gymnastics) (5).
Body composition, particularly lean body mass, is another important determinant of bone density. Lean body mass has a positive association with BMD (4, 6), likely attributable to the pull of muscle on bone having anabolic effects. At least one study indicates that compared with runners, gymnasts have higher lean mass and muscle strength, which are independent determinants of BMD and may help explain the preservation of BMD in gymnasts despite the high prevalence of amenorrhea (5). Of importance, the impact of fat mass on bone is relatively unclear, and studies examining the relationship between fat mass and bone have been inconsistent (7–9), with some showing a positive relationship between fat mass and BMD, and others finding the inverse. However, more recent studies, using larger populations and including genetic variants related to obesity, have more convincingly demonstrated a positive link between total body fat mass and BMD (10, 11). We have previously reported lower fat mass in young athletes with amenorrhea compared with eumenorrheic athletes and controls, however, our studies did not specifically examine independent associations of fat mass with BMD in these young women (4). There is also a growing body of evidence that regional fat mass [subcutaneous adipose tissue (SAT) vs. visceral adipose tissue (VAT)] can affect BMD in both healthy and obese women (12, 13). These relationships have not yet been elucidated in young female athletes, nor have they been examined based on menstrual status. While regional fat mass is best measured using expensive imaging modalities, such as CT or MRI, studies have demonstrated that dual energy X-ray absorptiometry (DXA) measures of body composition may serve as reasonable surrogates for SAT and VAT (14, 15). Total body fat, as assessed by DXA, appears to be a good surrogate for SAT, whereas percent trunk fat and trunk/extremity fat ratio serve as surrogates of VAT (4, 16–18). Absolute trunk fat is associated with both VAT and SAT, and is often more strongly associated with SAT than with VAT, and thus is not specific for VAT (18). However, trunk fat after controlling for total fat or extremity fat is more specific for VAT than for SAT (18).
We determined measures of regional body composition in a group of female endurance athletes (runners) 12–18 years old, and hypothesized that total fat mass would be an independent positive correlate and percent trunk fat and trunk to extremity fat ratio would be independent negative correlates of BMD after controlling for lean mass and menstrual status.
Forty adolescent athletes, 21 with amenorrhea and 19 with eumenorrhea were included in the study. Baseline characteristics only, but not regional fat mass assessments or associations of regional fat mass with bone density, have been previously reported (4). All subjects were between 12 and 18 years of age, and were endurance athletes (runners), running ≥30 miles weekly for a period of ≥6 months. Amenorrheic athletes (AA) were required to have missed ≥3 consecutive menstrual cycles after a history of regular menstruation for ≥6 months following menarche (19), or to have not reached menarche at 15.3 years of age (mean age of menarche +2SDs for girls in the United States) (20), and to have normal levels of FSH and TSH (in order to rule out primary ovarian failure and hypothyroidism as causes of amenorrhea). Eumenorrheic athletes (EA) met endurance athlete criteria but had no history of amenorrhea or menarchal delay, and reported a cycle length of 21–35 days. Exclusion criteria included past or current hormonal therapy or medications known to affect gonadal status, past or current conditions that could result in hypogonadism other than athletic activity, and low weight (BMI≤85% of ideal for age).
Subjects were recruited from the Boston area via local newspaper advertisements, and mailings to pediatricians, adolescent medicine physicians, nutritionists and therapists in New England. The study was approved by the institutional review board of Partners Health Care, and informed assent and consent obtained from all subjects and their parents, respectively.
Subjects were examined and evaluated at the Clinical Research Center of Massachusetts General Hospital. We measured height with a single Harpenden stadiometer (Holtain Ltd., Cry-mych, Wales, UK) and took the average of three measurements. Weight was measured with subjects fasting, in a hospital gown, and on an electronic scale. BMI was calculated using the formula [weight (in kilograms)]/[height (in meters)]. Bone age was assessed using the methods of Greulich and Pyle (21) and read by a single pediatric endocrinologist to minimize interobserver variation. A complete exercise history was obtained, and participants completed a modifiable activity questionnaire for the purpose of quantifying activity into a composite score for comparison across groups (22). A fasting blood sample was obtained for estradiol in all subjects, and in the early follicular phase of the cycle for menstruating subjects. Estradiol was measured using a radioimmunoassay (Diagnostic Systems Laboratories, Webster, TX, USA; intra-assay coefficient of variation 6.5%–8.9%, sensitivity 8.1 pmol/L).
DXA (Hologic 4500A fan beam densitometer, Waltham, MA, USA; software version 11.2) was used to measure BMD, bone mineral content (BMC) and areal BMD for the lumbar spine, hip and whole body (WB). The DXA scan was also used to determine body composition measures, including lean mass and regional fat measures. To correct for body size, bone mineral apparent density for L1–L4 (LBMAD) was generated from lumbar bone mineral content (BMC) and bone area (BA) measurements [Lumbar BMC/(Lumbar L1 BA1.5+L2 BA1.5 L3 BA1.5+L4 BA1.5)] (23) and measures of WB BMC/height were also examined. WB BMC included measurements of the head, however, our results did not significantly change when we repeated our analysis minus the head [WB BMC (minus head)]. The coefficients of variation for lumbar spine and WB BMD are 1.1% and 0.8%, and for fat and lean mass 2.1% and 1.0%, respectively, for our institution. The same scanner and software version were used for all participants.
We used whole body DXA to assess body composition. For regional body composition, we calculated percent trunk fat and trunk to extremity fat using the following formulae: percent trunk fat=[(trunk fat/total fat)×100] and trunk to extremity fat ratio=trunk fat/total extremity fat (13, 24, 25).
The JMP 4.0 program (SAS Institute Inc., Cary, NC, USA) was used to analyze the data, presented as means±SD. The Student t-test was used to calculate differences between means. A p-value of <0.05 was considered significant, and trends (p-values between 0.05 and 0.10) are also reported. Pairwise correlations were used to determine associations of lean mass, fat mass and regional fat mass with bone density measures. Additionally, we used stepwise regression analysis to determine independent associations of bone density measures. A p-value of 0.10 was used to enter and leave the model. We confirmed absence of autocorrelation within the chosen independent variables before entering these into the regression model. For all parameters, normality was confirmed prior to analysis.
The AA group did not differ from the EA group for chronologic age, bone age, height and activity scores (Table 1). Duration of amenorrhea was 8.3±6.7 months in the AA group. There were no differences in total lean mass between the groups. All but two athletes had a percent body weight >90%; only two had a percent weight between 85% and 90%. However, the AA subjects overall had lower weight, BMI and total fat mass than EA, and 62% of AA compared with only 11% of EA, reported a history of disordered eating behavior. Reported caloric intake (from food records) did not differ between the groups (not reported), likely because all AA were under close nutritional supervision of their medical care teams. As previously reported, the AA group had significantly lower lumbar BMD, hip BMD, WB BMD and corresponding Z-scores than EA. Similarly, the AA group exhibited lower height adjusted measures of bone density, namely, LBMAD and WB BMC/ht and corresponding Z-scores than the EA group. For subsequent analyses, we examined associations of regional fat mass with hip BMD and also height adjusted measures of bone density at the spine and for the whole body, limiting our analyses to the most relevant measures of bone density in an adolescent population.
Lean mass was positively associated with bone density measures and their Z-scores for all athletes (Table 2), and associations were stronger for hip BMD and WB BMC/Ht (and corresponding Z-scores) than for LBMAD and its Z-score. Within the subgroups of AA and EA, total lean mass was more strongly associated with Z-scores for hip BMD and WB BMC/Ht in EA than in AA.
Total fat mass was positively associated with LBMAD and its Z-score for all athletes and the EA subgroup, but not in AA. Weak positive associations were also observed of total fat mass with WB BMC/Ht for the group as a whole (Table 2). In contrast, percent trunk fat and trunk to extremity fat ratio were inversely associated with LBMAD and WB BMC/Ht and their Z-scores in the AA group, with similar trends observed for the groups taken together for LBMAD Z-score.
We next performed regression modeling to determine independent associations of bone density for the groups combined (Tables 3 and and4).4). Independent variables entered into the model included total lean mass, total fat mass (as a surrogate for subcutaneous fat) and either percent trunk fat (as a surrogate for visceral fat) (Table 3) or trunk to extremity fat ratio (as a surrogate for visceral fat) (Table 4). Lean mass and fat mass were independently and positively associated with LBMAD and its Z-score and of WB BMC/Ht, contributing together to 39%, 37% and 46% of the variability, respectively, of these bone density measures. Additionally, percent trunk fat was independently and inversely associated with these measures, contributing an additional 16%, 21% and 10% to the variability of LBMAD, LBMAD Z-score and WB BMC/Ht, respectively. The direction of these associations did not change when we replaced WB BMC with WB BMC (minus head); lean mass, fat mass and percent trunk fat contributed to 63% of the variability of WB BMC (minus head) after controlling for height. Hip BMD and its Z-scores and WB BMC/Ht Z-scores were associated solely with lean mass in this model for the groups taken together, with lean mass contributing to 28%, 25% and 28% of the variability of these measures. Very similar associations were seen when we replaced percent trunk fat with trunk to extremity fat ratio in the model, with trunk to extremity fat ratio being a negative predictor of LBMAD, LBMAD Z-scores and WB BMC/Ht, and contributing to 15%, 19% and 9%, respectively, of the variability in these measures (Table 4).
We next added estradiol (after log conversion) to the regression model in order to determine whether estrogen status could explain the negative impact of trunk fat on bone density measures. In this model, estradiol was positively associated with LBMAD, hip BMD, WB BMC/Ht Z-score contributing an additional 3%, 8% and 6%, respectively, of the variability of these measures, and replaced total fat mass as a determinant of WB BMC/Ht, contributing to 16% of the variability. However, even after addition of estradiol to the model, percent trunk fat remained significantly and negatively associated with LBMAD, LBMAD Z-scores, WB BMC/Ht contributing to 15%, 21% and 8% of the variability, respectively, of these measures (and to 8% of the variability of WB BMC (minus head) after controlling for height). Similarly, when we replaced percent trunk fat with trunk to extremity fat ratio in the model, estradiol was positively associated with LBMAD, hip BMD, WB BMC/Ht and WB BMC/Ht Z-scores contributing an additional 7%, 8%, 15% and 6%, respectively, of the variability. Trunk to extremity fat ratio remained a significant negative predictor of bone density measures in this model, contributing to 5%, 16% and 8% of the variability in LBMAD, LBMAD Z-scores and WB BMC/Ht, respectively.
Within AA, total lean mass was positively and independently associated with LBMAD, hip BMD and WB BMC/Ht, contributing to 21%, 20% and 41%, respectively, of the variability in these measures. Percent trunk fat was independently and inversely associated with LBMAD, LBMAD Z-scores, WB BMC/Ht and WB BMC/Ht Z-scores, contributing to 20%, 25%, 19% and 20% of the variability of these measures, respectively. Total fat mass was not independently associated with bone density measures within AA. WB BMC (minus head) was inversely associated with percent trunk fat and positively with lean mass, which contributed to 11% of its variability after controlling for height. Similarly, percent trunk fat remained negatively associated with LBMAD Z-scores, WB BMC/Ht and WB BMC (minus head) in AA even after adding estradiol to the regression model.
When we replaced percent trunk fat with trunk to extremity fat ratio in this model, the latter was a significant and negative predictor of LBMAD, LBMAD Z-scores, WB BMC/Ht and WB BMC/Ht Z-scores contributing to 20%, 23%, 18% and 17%, respectively, of the variability, while lean mass was a positive predictor of LBMAD, hip BMD and WB BMC/Ht contributing to 21%, 21% and 41% of the variability, respectively. Fat mass did not predict bone density measures within AA girls. Similarly, trunk to extremity fat ratio remained negatively associated with LBMAD, LBMAD Z-scores, WB BMC/Ht and WB BMC/Ht Z-scores even after adding estradiol to the regression model.
Within EA, total fat mass was positively associated with LBMAD and its Z-scores (41% and 23% of variability explained), whereas percent trunk fat emerged as an independent and inverse correlate with these measures (28% and 36% of the variability explained). In contrast, hip BMD and its Z-score and WB BMC/Ht and its Z-score were positively associated with total lean mass (25%, 28%, 36% and 39% of the variability explained, respectively). WB BMC (minus head) was predicted positively by total lean mass (56% of variability), after controlling for height. Percent trunk fat remained negatively associated with LBMAD, LBMAD Z-scores and WB BMC/Ht in EA after controlling for estradiol levels.
When we replaced percent trunk fat with trunk to extremity fat ratio in this model, the latter was a significant and negative predictor of LBMAD and LBMAD Z-scores contributing to 27% and 33% of the variability, while lean mass was a positive predictor of hip BMD, hip BMD Z-scores, WB BMC/Ht and WB BMC/Ht Z-scores contributing to 25%, 28%, 36% and 39% of the variability, respectively. Fat mass was a positive predictor of LBMAD and LBMAD Z-scores, contributing to 41% and 23% of the variability of these measures. Similarly, trunk to extremity fat ratio remained negatively associated with LBMAD and LBMAD Z-scores even after adding estradiol to the regression model.
In this study, we demonstrate strong positive associations of total lean mass and fat mass with bone density measures in adolescent athletes, particularly EA, and inverse associations of percent trunk fat and trunk to extremity fat ratio (surrogates for visceral fat) with bone density in AA, even after controlling for estrogen status. These data support recent observations of negative associations of visceral fat with bone density in obese adolescents (13), and extend this finding to a population of young athletes.
Lower BMD in AA in comparison to EA has been well-documented in adult and adolescent studies and has been attributed to a state of estrogen deficiency in amenorrheic women. We have shown that in adolescent athletes, menstrual dysfunction and disordered eating behavior are important determinants of low bone density (4). In addition, previous studies have demonstrated associations of total fat mass and lean mass with bone density measures (4, 26). However, the impact of site-specific fat mass on bone has not been thoroughly examined in adolescent athletes, particularly after controlling for lean mass and estrogen status. Total lean mass correlated positively with BMD measurements throughout the body, but in AA, total lean mass was more weakly associated with BMD Z-scores of the hip and WB BMC/Ht than in EA. This suggests that estrogen may be permissive for the positive effects of exercise on bone in athletes. A permissive effect of supplemental estrogen for the beneficial effects of mechanical loading on bone has been similarly reported in post-menopausal women, who are also estrogen deficient (27, 28)
We hypothesized that our surrogate measures of subcutaneous fat (total fat mass) and visceral fat (percent trunk fat and trunk to extremity fat ratio) would be positively and negatively associated with BMD, respectively, in our study population. The predicted relationship between total fat mass and BMD was only seen for the lumbar spine and WB BMC/Ht for the group as a whole, and for the lumbar spine in EA. It is possible that the relationship between total fat mass and BMD was attenuated in AA secondary to very low total fat in AA. Additionally, as hypothesized, we found an inverse association of percent trunk fat and trunk to extremity fat ratio with bone density measures in our subjects. Regression modeling supported the independent positive associations of total lean mass and total fat mass, and independent negative associations of percent trunk fat and trunk to extremity fat ratio, with height adjusted bone measures for the whole group.
Recent studies have documented deleterious effects of visceral fat on bone in normal and obese populations (8, 29, 30), consistent with our findings of the negative correlations of percent trunk fat and trunk to extremity fat ratio (surrogates for visceral fat) with bone density in AA. This is likely a consequence of adipokines and inflammatory fat products secreted by visceral fat that are deleterious to bone (13). Greater visceral or trunk fat predicts not only a higher risk of the metabolic syndrome, but also lower bone density (30, 31). Percent trunk fat and trunk to extremity fat ratio did not differ between AA and EA in our study, likely a consequence of similar relative decreases in trunk fat and extremity fat in AA. However, in anorexia nervosa, a more severe energy deficiency state than AA associated with marked reductions in bone density, percent trunk fat and trunk to extremity fat ratio are lower than in controls, indicative of greater relative reductions in trunk fat than in extremity fat (32).
One may thus speculate that a decrease in percent trunk fat in conditions of extreme energy deficiency and low bone density may be a protective phenomenon to prevent further decreases in bone density. Decreases in percent trunk fat may not be evident in AA, who are energy deficient, but not to the extent seen in anorexia nervosa. Of note, higher cortisol levels have been associated with higher trunk fat in adult women with anorexia nervosa (33), and it will be important to examine cortisol levels in adolescent AA to determine whether similar associations are evident in this population, contributing to a preservation of percent trunk fat. Some studies have reported higher levels of cortisol in adolescents who have exercise-induced amenorrhea, compared with eumenorrheic girls (34). We did not measure cortisol levels in this study; however, this will be important to assess in future studies.
Of importance, our data indicate that measures of trunk fat (both percent trunk fat and trunk to extremity fat ratio) are deleterious to BMD in AA more than in EA. These findings suggest that menstrual status may impact the site-specific effects of fat mass on bone density, with estrogen deficiency in AA unmasking the inverse association between trunk fat and bone. Estrogen is known to inhibit osteoclastic activity by inhibiting secretion of proinflammatory cytokines (35), and one may speculate that in the absence of estrogen, there is an increased secretion of these proinflammatory cytokines from visceral fat, contributing to impaired bone metabolism in AA, but not EA. However, even after controlling for estradiol levels, percent trunk fat was negatively associated with many bone density measures, suggesting that percent trunk fat may have an impact on bone that may `trump' the effects of estrogen. Of note, because we obtained estradiol levels in the early follicular phase of the cycle in eumenorrheic athletes when estrogen levels are the lowest, these levels may not reflect overall estrogen status. Felding and colleagues have indicated that there may also be a “threshold” level of estrogen that is too low to support menses, but high enough to support some anabolic effects of exercise on bone (36). Low bone density in our AA group suggests that these girls had estrogen levels that were even lower than this `threshold' level, and as a consequence, anabolic effects of exercise on bone were lost.
Regardless of the mechanisms that underlie the impact of regional body composition on BMD, our study clearly illustrates the importance of lean and fat mass in athletes and further elucidates the mechanism whereby amenorrhea has strong deleterious effects on bone. Amenorrhea may simply indicate overtraining and poor energy balance, both associated with decreased gonadal function and increased cortisol and cytokine levels. Amenorrhea is certainly not a healthy response to exercise and can have long-term consequences on bone health if not addressed. Our study highlights the necessity of understanding the mechanisms underlying exercise-induced amenorrhea and methods of preventing or reversing both the menstrual irregularity and consequent bone loss.
There were certain limitations of our study, including the size of the study cohort. Replication of the study with a greater sample size could yield more significant relationships between site-specific measures of body composition and BMD. Furthermore, although DXA measures are validated surrogate markers for body composition, and are fast, cost-effective, and emit much less radiation than computed tomography, MRI or CT measurements are the most accurate and precise methods of assessing body composition. Although we did not assess visceral fat using CT or MRI, studies have indicated that certain DXA measures of body composition, such as total fat, are good surrogates for subcutaneous fat, while estimates of percent trunk fat and trunk to extremity fat ratio are good surrogates for visceral fat. An additional limitation is that our study was cross-sectional and does not establish causality. To more accurately assess the interrelationship between site-specific body composition, weight-bearing exercise and bone density in the adolescent athlete, a longitudinal study over several years (menarche to adulthood) would yield more confirmatory results. Importantly, our study provides preliminary data indicating the need and rationale for such future studies.
Our study illustrates that amenorrhea may sometimes override the bone anabolic effects of lean mass on mechanical loading, and may also unmask the deleterious impact of visceral fat on bone. Further research is necessary to elucidate the mechanisms underlying the impact of amenorrhea on muscle, fat, bone, and overall health. For now, education of both athletes and coaches is necessary to underscore awareness of the female athlete triad and its important health consequences.
This study was supported in part by NIH grants 1 UL1 RR025758-01 and 1 R01 HD060827-01A1.
Authors' conflict of interest disclosure: Nothing to declare.