3.2 Low Energy Availability in the Etiology of the Triad: A Focus on Eating Behaviors
Similar to women, the most clinically worrisome symptoms of low energy availability in male athletes and exercising men are its effects on the hypothalamic–pituitary–gonadal (HPG) axis and on bone health. However, it must also be recognized that in men, similar to women, low energy availability may have an etiology related to poor eating behaviors [
35,
36], to include disordered eating or clinically significant eating disorders.
In general, athletes display higher rates of eating disorders compared to the general population, and eating disorders are most commonly observed in athletes who participate in sports that favor a lean body type [
35]. Notably, however, across all sport types the prevalence of male athletes identified as at-risk for an eating disorder and those with diagnosed eating disorders are lower than that observed in female athletes, 9% versus 21% and 8% versus 20%, respectively [
35]. This pattern is supported by findings in male and female distance runners, where one report found that 46% of women were identified as at-risk for an eating disorder compared to only 14% of men [
37]. It is interesting, however, that, although the prevalence of eating disorders in male athletes is lower than that of female athletes, it is similar to the prevalence of eating disorders in the general female population, suggesting that eating behaviors/eating disorders are an important concern in exercising men [
35].
It is possible that the reported prevalence of eating disorders/disordered eating in men is underestimated, since most instruments used to identify disordered eating behaviors and restricted eating patterns were developed for use in women. Moreover, since societal and cultural body ideals differ between men and women, it is likely that disordered eating behaviors may differ as well [
38]. As such, it may not be appropriate to use the same tools/subscales to identify disordered eating in men (to determine those at greatest risk for a male Triad-like syndrome) as those used in Female Athlete Triad research. Indeed, an emphasis must be placed on identifying and developing sex-specific risk factors and assessment tools for men. The disordered eating behaviors most commonly studied in exercising women at risk for the Triad include high cognitive dietary restraint [
29,
39,
40], as measured by the Three-Factor Eating Questionnaire [
41], and high drive for thinness [
28,
30], as measured by the Eating Disorders Inventory [
42], both of which have often been used as surrogate measures of energy deficiency and as screening tools to identify women at-risk for Triad-related conditions. However, there is far less information currently available on how cognitive restraint and drive for thinness relate to disordered eating and energy deficiency in exercising men. There are currently few reports of cognitive restraint in male athletes, none of which are specific to a population of exercising men. Drive for thinness, however, has often been applied to both sexes, and, generally, men tend to have lower drive for thinness subscale scores than women [
43,
44]. For example, in a clinical population of men and women receiving treatment for an eating disorder, both sexes presented with elevated drive for thinness scores compared to a healthy population [
43], but men presented with a lower drive for thinness scores compared to women (14.44 versus 20.32) [
44]. In men and women who did not have clinical eating disorders, the mean drive for thinness scores are again lower in men than women and were reported as 5.6 versus 9.9 for those in the USA, and 2.3 versus 6.6 for an international sample, respectively [
43]. Because men consistently report lower drive for thinness subscale scores than women, sex-specific cut-off values indicative of subclinical restricted eating patterns and underlying energy deficiency must be developed rather than relying on previously used definitions of high drive for thinness (≥ 7), which were developed from exercising women [
28,
30].
Alternatively, entirely different subscales or tools may be necessary for the identification of disordered eating behaviors in exercising men. One such tool is the Drive for Muscularity Scale, which represents one’s perception that they are not muscular enough and which was developed and validated by McCreary and Sasse [
45]. Drive for muscularity may be a valuable screening tool for identifying men at risk of developing eating disorders or disordered eating behaviors, since 27.5% of adolescent men and 4.9% of young women reported trying to gain weight or build muscle, with 21.9% of men and 4.5% of women exhibiting disordered eating behavior [
46]. However, the associated disordered behaviors may not necessarily be associated with restrictive eating patterns or contribute to low energy availability since many of those who reported disordered eating behaviors also reported that they ate more or differently in a manner to gain weight or build muscle [
46].
Interestingly, there may be an interaction between thinness and muscularity in the development of disordered eating—what has been referred to as a “drive for leanness” and which may be relevant to a Triad-like condition in men [
47]. The mesomorphic body type, a combination of muscular and thin, may be the most relevant in the development of disordered eating in men [
48], and drive for leanness refers to an interest in having relatively low body fat and toned muscles [
47]. Both muscularity and thinness were independently and positively associated with elevated disordered eating in college-aged men as assessed by the Eating Disorder Examination Questionnaire [
48]. One such drive-for-leanness scale was developed and significantly correlated with both drive for thinness and drive for muscularity in the entire sample, as well as in men and women independently. When looking for tools or risk factors that may be applicable to both sexes, drive for leanness may be useful particularly because there were no observed differences between men and women in drive for leanness, whereas women presented with higher drive for thinness scores and men displayed higher drive for muscularity [
47]. Additional work is required, however, to relate drive for leanness with specific restrictive eating patterns.
In summary, much additional work must be conducted to better understand disordered eating behaviors in men, especially those that are related to restrictive eating patterns and therefore likely contribute to the development of low energy availability. Similar to women, the men at greatest risk for having disordered eating and eating disorders are those who participate in leanness sports [
35], and tools aimed at identifying subclinical disordered eating must be developed for application in the population of exercising men.
3.3 Low Energy Availability in the Etiology of the Triad: A Focus on Reproduction
Cross-sectional reports of hypogonadotropic hypogonadism have been reported in male athletes, particularly in those athletes participating in endurance sports, and include evidence of low testosterone [
49‐
52], poor semen quality/oligospermia [
53,
54], and low libido [
55,
56]. As of 2019, only two investigators have tried to evaluate the effects of modulating exercise and dietary intake to vary the levels of energy availability from low to adequate in men [
22,
23] as has been done in women [
15]. Koehler et al. [
23] manipulated energy availability to a level of 15 kcal/kg FFM/day versus 40 kcal/kg FFM/day in exercise trained males aged 25.2 ± 1.0 years. At an energy availability of 15 kcal/kg FFM/day, reductions in serum leptin and insulin were observed, but no reductions in serum TT
3, IGF-1, or testosterone were observed irrespective of whether the low energy availability conditions were achieved by restricting dietary intake or by increasing energy expenditure [
23]. Papageorgiou et al. [
22] conducted a somewhat similar study in men and reported that at an energy availability of 15 kcal/kg FFM/day no reductions in serum TT
3, insulin, leptin, or IGF-1 were observed. These findings are in stark contrast to those observed in the Loucks et al. [
15,
16] studies in women where TT
3, insulin, leptin, and IGF-1 were all suppressed at mild to modest levels of low energy availability ranging from 10 to 30 kcal/kg FFM/day.
Interestingly, it is primarily in “extreme” situations consisting of high intensity, long duration exercise or simultaneous exposure to multiple stressors that significant reductions in metabolic and reproductive hormones are observed. For example, during Army Ranger training where men were exposed to sleep deprivation and psychosocial stress, in addition to the primary stressor of energy deficiency, significant reductions in metabolic and reproductive hormones were observed [
57]. Specifically, 8 weeks of training resulted in significant energetic changes including declines in total body mass, fat mass, and FFM, reductions in the concentrations of TT
3, IGF-1, and insulin, and increases in the concentrations of cortisol and GH. Additionally, reproductive suppression was also observed, including decreased concentrations of testosterone, which fell below the normative range of values, as well as a reduction in LH concentration in a subgroup of men who underwent more severe caloric restriction [
57]. There are also several examples of single bouts of prolonged, strenuous, outdoor exercise, such as ~ 160–1200 km running and cycling races, which induced hypogonadal states marked by reduced testosterone [
58‐
60] and LH [
59] concentrations, as well as metabolic hormone alterations including suppression of leptin and IGF-1 [
58] and increases in cortisol [
59,
60] and GH [
60].
In cross-sectional studies of chronic strenuous exercise training, it seems that very high training loads are required for impairments to be translated to the HPG axis, presumably through poor energetic status. We found that high mileage runners (108.0 ± 4.5 km/week), compared to moderate distance runners (54.2 ± 3.7 km/week) and controls, had lower testosterone levels as well as poor semen quality, including decreased sperm motility, an increased immature sperm number, and decreased bovine cervical mucus penetration, all of which are associated with infertility [
53]. It is important to note that the moderate mileage runners in our study maintained a gonadal and semen profile that was similar to that of the sedentary control group, despite running approximately 40–60 km/week. We concluded that in male athletes participating in high-volume training, the findings of decreased testosterone and abnormal semen profiles (Table
1) likely reflect the failure of these athletes to increase energy intake in a manner that accommodates the increased energy expenditure associated with a high training volume [
53,
54].
Table 1
Comparison of semen characteristics in male runners.
Adapted from De Souza and Miller [
54], with permission
|
Sperm density (× 106/mL) | 78 ± 12 | | 176 ± 25 | 0.003 |
Forward progression (%) | 40.8 ± 4.7 | | 58.7 ± 2.4 | 0.005 |
Nonmotile (%) | 54.2 ± 4.9 | | 39.3 ± 1.9 | 0.005 |
Normal sperm (%) | 40.2 ± 2.1 | | 47.0 ± 3.3 | < 0.05 |
Immature sperm (%) | 17.2 ± 2.4 | | 10.9 ± 1.2 | 0.035 |
Round cells (× 106) | 8.3 ± 1.7 | | 2.5 ± 0.9 | 0.001 |
Sperm penetration (mm) | 22 ± 5 | | 43 ± 7 | 0.036 |
Bagatell and Bremmer [ 84] |
Sperm count (× 106/mL) | | 119.9 ± 64.4 | 108.9 ± 91.7 | NS |
Total sperm/ejaculate (× 106) | | 436.8 ± 64.6 | 316.1 ± 79.8 | NS |
Oval forms (%) | | 81.1 ± 1.8 | 78.9 ± 2.7 | NS |
Motility (%) | | 82.0 ± 4.6 | 73.2 ± 3.5 | NS |
|
Sperm count (× 106) | | 108 ± 56 | 77 ± 61 | NS |
|
Semen volume (mL) | 2.7 ± 1.4 | 2.8 ± 1.4 | | NS |
Count (× 106/mL) | 133 ± 141 | 71 ± 65 | | 0.001 |
Motility (%) | 54 ± 9 | 55 ± 8 | | NS |
Morphology (%) | 15 ± 6 | 11 ± 7 | | 0.001 |
|
Sperm density (× 106/mL) | 88.5 ± 14.8c | 127.2 ± 32.2 | 175.5 ± 24.9 | 0.045 |
Normal motile count (× 106) | 58.5 ± 10.8d | 118.8 ± 20.3 | 106.7 ± 22.3 | 0.052 |
Motile count (× 106) | 134.5 ± 23.9c | 240.1 ± 45.3 | 224.7 ± 39.1 | 0.037 |
Forward progression (%) | 40.3 ± 4.3c | 48.8 ± 4.5e | 58.7 ± 2.4 | 0.006 |
Nonprogressive (%) | 6.1 ± 1.4f | 7.3 ± 1.1f | 2.0 ± 1.0 | 0.014 |
Nonmotile (%) | 53.6 ± 4.4c | 43.9 ± 3.9 | 39.3 ± 1.9 | 0.023 |
Immature sperm (%) | 16.8 ± 2.2d | 10.1 ± 2.0 | 10.9 ± 1.2 | 0.031 |
Round cells (× 106) | 8.0 ± 1.6d | 2.5 ± 1.1 | 2.5 ± 0.9 | 0.004 |
Sperm penetration (mm) | 26.8 ± 6.3c | 37.5 ± 7.2 | 43.2 ± 7.0 | 0.024 |
Notably, although highly trained men often have testosterone concentrations that are lower compared to untrained men, they often still fall within the normal physiological range, and these findings are consistent across a range of training volumes [
49,
50,
52]. Runners averaging > 64 km/week had lower free and total testosterone concentrations compared to sedentary controls, with only one of the 31 runners (3%) falling below the normal range [
50]. Runners averaging ~ 80 km/week were also within the normal range, albeit at the lower end [
49], and a group of trained men averaging > 450 min of exercise per week of predominately endurance activities had lower concentrations of total and free testosterone compared to sedentary controls, but were again within the normal range [
52].
Commensurate with alterations in testosterone and semen profiles, LH pulse frequency is significantly decreased in highly trained male runners (125–200 km/week) when compared to untrained controls [
51]. In runners with a lower training load (~ 80 km/week), no difference in LH pulse frequency was observed compared to non-runner controls [
49,
61], although one study reported that runners had lower LH pulse amplitude and area under the curve [
49]. Similarly, no differences in LH pulse characteristics were observed between endurance-trained men averaging > 450 min/week of exercise compared to sedentary controls, including LH pulse frequency and amplitude [
52].
Although many of the reported reproductive findings are from cross-sectional studies that observed reproductive suppression coincident with high training volumes, there is also evidence from experimental models of caloric restriction alone, which reduced LH pulse frequency in both men and male monkeys [
62,
63]. We propose that poor energetic status is underlying the suppression of the HPG axis, and those who are participating in particularly high volumes of training may not be increasing their energy intake in a sufficient manner to match the increased energy expenditure associated with their training volume. It is likely that very high training loads present an energetic challenge, what we referred to as a “volume-threshold effect” over 20 years ago [
53,
54]. It also appears to be difficult to consume the energy required to overcome such an energetic challenge, which, presumably, results in energy deficiency, which when extreme and chronic, translates into outcomes affecting the HPG axis.
Due to the absence of an overt clinical sign, such as a change in menstrual cycle frequency, reproductive suppression will likely be more difficult to assess in men than in women. But interestingly, male sexual function has been related to testosterone concentration [
64] and changes in libido may be a helpful cue when trying to identify reproductive suppression secondary to energy deficiency in exercising men. For example, trained men reported higher scores on the Aging Male Symptoms questionnaire compared to controls [
65], and a lower training volume has been associated with an increased likelihood of having high/normal libido based on a modified questionnaire comprising questions from the Aging Male Symptoms, Androgen Deficiency in the Aging Male, and Sexual Desire Inventory questionnaires [
55].
Of note, the metabolic and reproductive perturbations observed in men also appear to recover more quickly following a reduction in exercise or increased caloric intake. Within 1 month of completing Army Ranger training all metabolic and reproductive hormones returned to normal levels, with most hormones recovering in a single week, and testosterone appeared to be highly responsive to refeeding [
57]. In fact, following the aforementioned acute endurance events, testosterone concentrations rebounded towards baseline levels within 12 h of race completion [
58], and were fully recovered within 2–3 days [
59,
66]. One case study has been reported of an adolescent male athlete who presented with hypogonadotropic hypogonadism associated with energy deficiency through a combination of excessive exercise and undernutrition and in whom testosterone concentration was normalized within the 1-year follow-up period following reduced training volume and increased caloric intake [
56]. Lastly, in non-human primates, refeeding after a single day of fasting resulted in an increase in both LH pulsatility and testosterone concentration, such that hormonal recovery progressively improved as the size of the refeed meal increased, thereby supporting that reversal of HPG axis suppression following a period of energy deficiency is likely due to an increase in hypothalamic central drive [
67].
In summary from the data published to date, it seems apparent that the energetic and reproductive presentation of the Triad in men is different from that in women, whereby women are impacted more aggressively than men by low energy availability and that men are more resistant to the effects of low energy availability [
15,
22,
23]. The reproductive axis of women also appears to recover more slowly than the rapid recovery observed for the reproductive axis in men [
56‐
58,
66,
67].
3.4 Low Energy Availability in the Etiology of the Triad: An Overview of Impaired Bone Health in Exercising Men
Most of the data in support of impaired bone health in male athletes are the product of cross-sectional investigations in leanness sports. Overall, longitudinal data or controlled and intervention-based investigations on the effect of energy restriction on bone mineral density (BMD) in male athletes are scarce. Similarly, reports on bone strength, geometry, and structure in exercising men with low BMD and bone stress injuries are not yet available. However, there is evidence that particular subsets of male athletes, such as male distance runners, who are at high risk for having low energy availability are also reported to have low BMD scores [
8,
68] and a high prevalence of bone stress injuries [
7,
69]. Additionally, there is evidence that bone turnover markers are influenced by periods of energy restriction [
22,
70].
Low BMD scores have consistently been reported in men who participate in leanness sports, i.e., distance runners, cyclists, and jockeys [
71‐
75]. For example, of 42 adolescent runners, 21% had
Z scores ≤ − 1.0 at the lumbar spine and 5% had Z-scores ≤ − 2.0 [
68]. In adolescent runners, 24% had a BMD Z-score < -1.0 and 4% had a BMD
Z score of ≤ − 2.0; this is in contrast to only 6% and 0% of non-runner athletes having
Z scores < − 1.0 and < − 2.0, respectively [
8]. Similarly, one study reports that 32% of competitive cyclists had
Z scores of ≤ − 2.0 [
75], while 29% of a sample of 79 male flat jockeys and 13% of a sample of 69 male jump jockeys had spine BMD
Z scores ≤ − 2.0 [
76]. Although most investigations of bone health in male athletes did not assess energetic status, endurance and weight class athletes have been reported to have low energy availability/energy deficiency. Notably, energy availability has been reported as low as 18.8 ± 12.1 kcal/kg lean body mass (LBM)/day in competitive male cyclists (
n = 6, age 29–49 years) with low BMD (
Z scores ≤ − 1.0) [
77], and as low as 19 kcal/kg LBM/day in jockeys [
78]. Lastly, risk factors for low BMD in exercising men have been identified and include low body weight (< 85% expected), average weekly running mileage > 30, and previous stress fracture [
8].
In addition to low BMD scores, male athletes are also reported to have a high incidence of bone stress injuries [
7,
69]. Among 80 collegiate runners, 27% sustained at least one bone stress injury over a prospective 2-year period [
7]. Further, bone stress injuries were predicted by a modified version of the Female Athlete Triad Cumulative Risk Assessment tool that was adapted in a manner to be applicable to male athletes and included low energy availability, low body mass index (BMI), prior bone stress injury, and low BMD as risk factors [
7]. Additional positive risk factors identified in adolescent male runners include previous fracture and participation in a greater number of competitive seasons [
69].
With respect to bone turnover markers, restricting energy by ~ 50% for 3 days decreased bone formation in trained runners [
70]. Alternatively, 5 days of restricted energy availability (15 kcal/kg FFM/day) did not affect markers of bone turnover (N-terminal propeptide of type I collagen and C-terminal telopeptide type I collagen) in men [
22]. The non-significant finding in men, compared to a significant 13% reduction in bone formation and 19% increase in bone resorption in women, suggests that, similar to the metabolic and reproductive systems, the effects of low energy availability on bone turnover in men are different to those in women whereby women are impacted more aggressively than men in response to low energy availability [
22].