Exercising women frequently present with a chronic energy deficiency resulting from inadequate caloric intake to compensate for energy expenditure [1, 2]. In this population, energy expenditure may be high due to the added energy cost of exercise. Therefore, when daily energy intake does not match energy expenditure, there may be inadequate fuel to support all physiological processes . As a result, the physiological consequences of an energy deficiency involve a cascade of metabolic and hormonal alterations that can suppress the reproductive axis and cause menstrual disturbances such as functional hypothalamic amenorrhea (FHA) and low bone mass [4, 5]. The optimal treatment strategy for women with exercise-associated amenorrhea and low bone mass is to target the source of the problem, i.e., the energy deficiency, by initiating a lifestyle intervention that includes an increase in energy intake, and, if necessary, a decrease in exercise energy expenditure (EEE) . Weight gain often occurs secondary to such treatment and has been observed to be a clinically positive outcome associated with resumption of menses and enhanced bone health in exercising women [7–9].
A few investigators have reported case studies of amenorrheic, exercising women who have increased caloric intake and gained weight [7–10]. Dueck et al.  and Kopp-Woodroffe et al.  described a case study of five amenorrheic athletes who increased caloric intake for 12 to 20 weeks, resulting in weight gain of 1 to 3 kg and the resumption of menses in 3 of 5 participants during the intervention. Fredericson and Kent  reported a case study of an amenorrheic athlete who gained weight over the course of 5 years, resulting in the maintenance of normal menstrual cycles and improved bone health. Similarly, Zanker et al.  followed an amenorrheic athlete for 12 years and reported increases in bone mineral density (BMD) of the proximal femur with increases in body mass index (BMI). There are, however, no case studies published to date that document the simultaneous changes in energetic and metabolic status and the associated effects on hormonal attributes of reproductive recovery and bone health in amenorrheic exercising women. Indeed, the case studies reported to date have limited their findings solely to the outcome of recovery of menses rather than the documentation of the hormonal aspects of menstrual recovery that include estrogen exposure, progesterone exposure, and ovulation over the course of 12 months of increasing calorie intake. The absence of detailed reports describing the metabolic and hormonal environment surrounding resumption of menses in exercising women with FHA has resulted in a lack of evidence on which to base effective dietary treatment strategies. As such, the value of this case report lies in the opportunity to study the manifestation and resolution of this complex problem using detailed hormonal analyses in an effort to gain a better understanding about the interplay of factors that may contribute to the induction and reversal of FHA in exercising women.
Therefore, the purpose of this case report was to compare and contrast the recovery of two exercising women with current FHA of varying duration (short-term vs. long-term) to a 12-month nutritional intervention. Thus, this case report will describe, in detail, the changes in energetic status, and the hormonal aspects of recovery of menstrual function and bone health in two amenorrheic exercising women.
Nutritional intervention methods
For the purpose of this case report, two exercising amenorrheic women (aged 19–24 years) with current amenorrhea of short (3 months) and long (11 months) duration were chosen to demonstrate the impact of increased caloric intake on the hormonal aspects of recovery of menstrual function and bone health. The two individuals were chosen because they both demonstrated good compliance to an intervention of 12 months of increased caloric intake targeted to exceed baseline total energy expenditure (TEE) needs by 20-30%, and the ongoing nature of the intervention precludes inclusion of the entire sample of women that participated in the intervention. Both women successfully resumed menses. The presence of amenorrhea at the beginning of the intervention was confirmed by the analysis of daily urinary excretion of estrone-1-glucuronide (E1G) and pregnanediol glucuronide (PdG) metabolites for one 28-day monitoring period. Both women were recreationally active, engaging in > 7 hours of exercise per week at baseline. The primary outcome variables in the 12-month intervention were indices of energy status, bone health and menstrual status.
The two women in this case report were exercising women who met the following inclusion criteria: 1) age 18–35 years, 2) BMI 16–25 kg/m2, 3) weight stable (± 2 kg) for the past 6 months, 4) no history of any serious medical conditions, 5) no current clinical diagnosis of an eating or psychiatric disorder, 6) non-smoking, 7) no medication use that would alter metabolic or reproductive hormone concentrations, 8) ≥ 3 hrs/wk aerobic exercise, 9) no menses for the past 3 months, and 10) no history of a clinical diagnosis of polycystic ovarian syndrome (PCOS), or a free androgen index (FAI), calculated as (total testosterone (nmol/L)/sex hormone binding globulin (SHBG) (nmol/L))*100), > 6 . In addition, the women in this case report presented with current amenorrhea of varying duration, i.e., short-term amenorrhea defined as the cessation of menses for <100 days and long-term amenorrhea defined as the absence of menses for >100 days .
Participants signed an informed consent approved by the Institutional Review Board at the University of Toronto or Pennsylvania State University. Height and weight were measured, and participants completed questionnaires to assess medical history, exercise and menstrual history, eating behaviors, and psychological health. A physical exam and blood sample was performed to determine overall health. A semi-structured psychological interview was conducted to ensure that the women were not experiencing major psychiatric disorders, and a registered dietitian assessed eating patterns and food preferences. Dual-energy x-ray absorptiometry (DXA) scans were performed to assess BMD and body composition.
During a 4-week baseline period, menstrual calendars and daily urine samples for the assessment of menstrual function were collected. Body weight was measured weekly. At week 3 of baseline, energetic markers (leptin, ghrelin, total triiodothyronine (TT3)), markers of bone formation and resorption, body composition, resting energy expenditure (REE), and dietary intake were assessed. Participants also completed a test of aerobic fitness.
Classification of baseline menstrual status
Upon study entry, classification of menstrual status was based on self-reported menstrual history, which was confirmed by a 28-day urinary profile of E1G, PdG, and luteinizing hormone (LH) profiles during a 4-week baseline period. FHA was assessed by confirming a negative pregnancy test, normal endocrine panel, no menses in the past 90 days, and documentation of chronically suppressed E1G and PdG profiles observed during the baseline period.
Intervention procedures for energy calculations
Both participants were asked to increase their caloric intake 20-30% above baseline TEE while maintaining their usual exercise training regimen. For the purpose of this report, baseline TEE was operationally defined as the sum of REE and purposeful EEE. Energy bars that contained approximately 250–300 kilocalories (1,046-1,255 kJ) were provided by the research staff to increase caloric intake. The target increase in caloric intake was gradually achieved by a slow increase in calories during the first several weeks of the intervention to encourage compliance. A registered dietitian met with the participants regularly to provide strategies to meet the target caloric intake. Participants also regularly met with a clinical psychologist or licensed clinical social worker to monitor general psychological health.
Assessment of menstrual function during the intervention
Menstrual function was monitored daily during the intervention by assessing urinary excretion of E1G, PdG, and LH metabolites and the presence of menses as self-reported on monthly calendars. The methods used for the assessment and categorization of menstrual cycles are detailed and have previously been published .
Recovery of menstrual function categories
To describe the recovery of menstrual function, we classified recovery using several definitions of recovery that ranged in hormonal and clinical relevance. Recovery Category 1 was described simply as “recovery of menses.” The successful recovery of menses after the baseline period was defined as the first occurrence of menstrual bleeding during the intervention. For further analysis of the recovery of menstrual function, Recovery Category 2 was described as resumption of menses preceded by ovulation based on increases in urinary E1G (above 35 ng/ml), PdG (above 2.5 μg/ml), and mid-cycle LH (above 25 mIU/ml) concentrations [2, 14]. Recovery Category 3 was described as resumption of menses followed by at least 2 menstrual cycles of less than 36 days each.
Total body weight was measured by a digital scale during each week of the baseline period and every two weeks during the intervention. Height was measured during the screening period, and BMI was calculated as a ratio of weight to height (kg/m2). Baseline values for body weight and BMI were reported as the average of all baseline and screening measurements.
Eating behavior assessment
Participants completed the Three Factor Eating Questionnaire (TFEQ) and Eating Disorder Inventory-2 (EDI-2) at screening and at months 2, 3, 6, 9, and 13 (post-study) to assess eating behavior. The TFEQ is a 51-item questionnaire with three subscales – cognitive dietary restraint (CDR), disinhibition, and hunger. Cognitive dietary restraint was evaluated according to the following ranges established by Stunkard and Messick : 0–10 indicated low CDR, 11–13 indicated high CDR, and 14–21 indicated the clinical range. The EDI-2 is a 91-item questionnaire with 8 subscales and 3 provisional subscales, as previously reported . Scores on the first 8 subscales were compared to published means and 95% confidence intervals of eating disorder patients and non-patient college females to assess for symptoms of disordered eating and associated psychological features .
Body composition and bone mineral density
DXA scans of the total body, lumbar spine, and dual femur were performed to assess body composition and BMD. Body composition was measured at screening and baseline and during months 1, 2, 3, 6, 9, and 13 (post-study). BMD was assessed at all three sites at screening, month 6, and month 13 (post-study). The participants were scanned on either a GE Lunar Prodigy or Lunar iDXA (GE Lunar Corporation, Madison, WI). Consistent with the International Society of Clinical Densitometry guidelines, a cross calibration study was performed to remove systematic bias between the systems as previously published .
Dietary energy intake
Dietary energy intake was assessed from 3-day diet logs (2 weekdays and 1 weekend-day) completed during week 3 of baseline and each month during the intervention as previously published . Participants met with a registered dietitian regularly who trained them how to record dietary intake accurately and reviewed the completed energy intake logs. Participants received written guidelines regarding proper measurement and reporting of food portions and preparation.
Resting energy expenditure
REE was determined by indirect calorimetry during week 3 of baseline and months 2, 3, 6, 9, and 13 (post-study) (Sensormedics Vmax metabolic cart, Yorba Linda, CA). Methods explaining the measurement of REE have been published in detail elsewhere . Predicted REE (pREE) was also calculated using the Harris Benedict equation . We compared the lab-assessed REE to the predicted REE (REE/pREE) to estimate how much the measured REE deviated from the predicted REE. A reduced ratio of measured REE to Harris-Benedict predicted REE of 0.60-0.80 has been reported during periods of low body weight and prior to refeeding in anorexic women [20–22]. We have previously published data using a ratio of REE/pREE <0.90 as the operational definition of an energy deficiency [1, 4, 16, 23]. As such, in this study, a ratio <0.90 was used to discriminate between being energy deficient and energy replete.
Purposeful exercise energy expenditure
Purposeful EEE was estimated at baseline and monthly during the intervention using a Polar heart rate monitor. Participants completed exercise logs where all purposeful exercise sessions greater than 10 minutes in duration were recorded for a 7-day period. Energy expended during these purposeful exercise sessions was measured using the OwnCal feature of the Polar S610 or RS400 heart rate monitors (Polar Electro Oy, Kempele, Finland) . The OwnCal feature has been validated for the use in calculating EEE from heart rate. The Polar S601 and RS400 hear rate monitors include rest in their estimation of energy expenditure. To estimate only EEE, we subtracted the most recently measured REE (kcal/min) from the Polar heart rate monitors’ estimation of energy expenditure. For purposeful exercise sessions in which participants did not wear the Polar S610 or RS400 heart rate monitors, the Ainsworth et al. [25, 26] compendiums of physical activities were used to determine the appropriate metabolic equivalent (MET) level for the exercise performed . To calculate the energy expended during the exercise session, the MET level was multiplied by the duration (min) of the exercise session and the measured REE (kcal/min). The MET value includes a resting component. To estimate only EEE, we subtracted the most recently measured REE (kcal/min) from this value.
Participants also recorded the type and duration of purposeful physical activity using daily exercise logs to provide a measure of exercise volume during the study.
Maximal aerobic capacity (VO2max) was measured during a progressive treadmill test to volitional exhaustion using an on-line MedGraphics Modular VO2 System (St Paul, MN) or SensorMedics Vmax metabolic cart (Yorba Linda, Calif., USA) during week 3 of baseline using methods previously published .
Urinary reproductive hormone measurements
To determine estrogen and progesterone exposure, E1G and PdG urinary metabolites were assessed using a modified trapezoidal integrated area under the curve (AUC) technique. To calculate AUC, the hormone concentrations for two consecutive days of the cycle were averaged; these averages were then summed to provide AUC for the cycle. The methods for measuring urinary reproductive hormones have been previously published . The inter-assay coefficients of variation for high and low internal controls for the E1G assay are 12.2% and 14.0%, respectively. The PdG intra- and inter-assay variability was determined in-house as 13.6% and 18.7%, respectively [2, 14]. Urinary LH was determined by coat-a-count immunoradiometric assay (Siemens Healthcare Diagnostics, Deerfield, IL). The sensitivity of the LH assay is 0.15 mIU/ml. The intra- and inter-assay coefficients of variation were 1.6% and 7.1%, respectively.
Blood was collected, processed, and stored after an overnight fast between 0700 and 1000 once during week 3 of baseline and once at the end of baseline using methods previously published in detail . The latter two samples were pooled for all baseline hormone analyses. In addition, blood samples were collected during months 2, 3, 4, 5, 6, 9, 13 (post-study).
Serum hormone analysis
The metabolic hormones TT3, leptin, and ghrelin were measured using previously published methods [18, 29]. Bone markers including pro-collagen type 1 amino-terminal propeptide (P1NP) and collagen type 1 cross-linked C-telopeptide (CTx) were also measured. P1NP was analyzed by radioimmunoassay (RIA) (Immunodiagnostic Systems, Inc., Scottsdale, AZ). The sensitivity of the assay was 2 μg/L. Intra-assay and inter-assay coefficients of variation were between 6.5-10.2% and 6.0-9.8%, respectively. CTx was analyzed by enzyme-linked immunosorbent assay (ELISA) (Immunodiagnostic Systems, Inc., Scottsdale, AZ). The sensitivity of the assay was 0.02 ng/mL. Intra-assay and inter-assay coefficients of variation for the low control were 3.0 and 10.9%, respectively. All samples from a given participant were analyzed in duplicate.