Changes in Body Composition and Neuromuscular Performance Through Preparation, 2 Competitions, and a Recovery Period in an Experienced Female Physique Athlete : The Journal of Strength & Conditioning Research

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Changes in Body Composition and Neuromuscular Performance Through Preparation, 2 Competitions, and a Recovery Period in an Experienced Female Physique Athlete

Tinsley, Grant M.1; Trexler, Eric T.2; Smith-Ryan, Abbie E.2; Paoli, Antonio3; Graybeal, Austin J.1; Campbell, Bill I.4; Schoenfeld, Brad J.5

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Journal of Strength and Conditioning Research 33(7):p 1823-1839, July 2019. | DOI: 10.1519/JSC.0000000000002758
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Although physique competitions are becoming increasingly popular, limited detailed information is available concerning the host of physiological and psychological changes that occur during the pre- and post-competition months. Three recent case studies have described the contest preparation phase of drug-free female physique competitors (19,39,40), although only one examined the post-competition phase (19). Halliday et al. (19) published an in-depth case study of physiological changes over 20 weeks before and 20 weeks after a figure competition in a first-time competitor. The athlete achieved a substantial improvement in body composition over the duration of the 20-week contest preparation (15.1–8.6% body fat [BF]). By 20-week post-contest, the competitor's body mass (BM) and composition had returned to near baseline values. In this investigation, body composition was assessed by dual-energy x-ray absorptiometry (DXA) and skinfolds, although only 3 DXA scans were conducted during the 40-week study. In addition, exercise performance was not evaluated in this investigation. Rohrig et al. (40) reported physiological and performance changes during a 5-month period in a female competitor preparing for her third competition, although the previous competitions were 2 years prior. The subject reduced BF from 30.5 to 15.9%, as estimated by hydrodensitometry. Fat-free mass (FFM) increased by 1.8 kg (+3.8%) during the 1st month of preparation and remained 1.3 kg (+2.8%) above baseline at the end of the assessment period. As acknowledged by the authors, the state of leanness achieved by this individual may not be commensurate with competitive physique athletes. The subject maintained maximal oxygen consumption (Vo2max) and anaerobic performance throughout the preparation period as assessed by a 3-minute cycle ergometry test, although no assessments of resistance exercise performance were used. Finally, Petrizzo et al. (39) assessed body composition changes in a female competitor over a 32-week contest preparation phase. The competitor's BF was reduced from 23.4 to 11.3% during this time, as assessed by DXA. Body recomposition was achieved, with concomitant reported reductions in fat mass (FM) (−55%) and increases in lean mass (+1.5%). No exercise performance variables were examined.

As competitive success in physique sports is inextricably linked to body composition, accurate assessments of body composition in physique athletes are paramount to understand changes that take place over time. Although recent case studies in female physique athletes have used common laboratory assessments of body composition (i.e., DXA and hydrodensitometry), there are potentially significant limitations to these methods. Neither DXA nor hydrodensitometry provides information concerning total body water (TBW), and both require the assumption of a constant FFM hydration (TBW:FFM) (31). However, large individual deviations in TBW:FFM have been reported (56). Body composition models that account for TBW (i.e., that do not assume TBW:FFM) may be particularly informative for research in physique athletes, in whom large body water fluctuations may be observed surrounding competition (54). In addition, when compared to a criterion 5-compartment model, Moon et al. (32) reported that both DXA and hydrodensitometry produced larger errors and wider limits of agreement in female athletes as compared to multicompartment models that include an estimate of TBW. In fact, DXA errors in BF percentage were so large that the DXA scanner and software used in the investigation were explicitly discouraged for use in female athletes (32). The researchers concluded that the ideal method for estimating body composition, particularly when assessing individuals and tracking changes in body composition, is a multicompartment model that includes an estimate of TBW. However, no previous case studies of female physique athletes have used such an assessment method. The suboptimal assessment techniques in previous investigations, as well as the infrequent evaluation of body composition, indicate that additional accurate information concerning changes during the preparation, competition, and recovery periods is needed. Furthermore, although one case study reported that body composition assessments were conducted in the fasted state (40), the others either did not report standardization procedures or used suboptimal standardization procedures before assessment (e.g., a 4-hour fast as opposed to overnight) (19,39). Multiple research groups have recently demonstrated the importance of adequate preassessment controls before body composition evaluation (4,53), and these control measures may be especially critical in case studies, which derive all information from a single subject.

Although body composition changes of the pre-competition phase have been highlighted in several reports (19,39,40,54,55), little is known about the post-competition period in female competitors, during which BM and FM invariably increase (19,54). In addition, no investigations assessing a physique competitor through multiple competitions over the course of several months are readily available in the literature. As many physique athletes compete in multiple competitions per year, examination of the inter-competition period is warranted. In addition, previous reports of female competitors have not included assessments of neuromuscular performance during the months before or after competition (19,39,54,55). Because of the importance of maintaining an adequate resistance training stimulus in physique athletes, as well as the dietary and psychological factors that may impair performance during and after competition, this is a notable gap in the existing literature. Finally, as described, there are potentially substantial limitations to body composition assessment methods used in previous case studies, and the usage of multicompartment models including estimates of TBW is warranted. Therefore, the purpose of this case study was to provide an in-depth evaluation of body composition and neuromuscular performance changes before, during, and after the competitive season of an experienced female figure competitor. To the best of our knowledge, this is the first detailed report assessing a physique competitor over the span of multiple competitions and only the second case study to include thorough information about the post-competition period in a female competitor (19).


Experimental Approach to the Problem

The 34-week assessment period (Figure 1) included 18 weeks of preparation for the first competition, a 7-week period between the first and second competitions (the inter-competition period), and a 9-week period after the second competition (the recovery period). After the second competition, assessments were conducted until BM returned to the baseline value. The assessments spanned from the beginning of February through the end of September 2017. Twelve testing sessions were conducted during this period of time, including visits exactly 3 days before and 5 days after both competitions. In addition to the pre- and post-competition visits, assessments were conducted monthly at approximately the same time of day. All testing sessions began between 6:30 and 7:00 am, with the exception of the first and third visits, which began between 8:30 and 9:00 am. At each visit, the subject reported to the laboratory after an overnight (≥8-hour) food and fluid fast. The subject was allowed ad libitum water intake after the body composition and resting metabolic rate (RMR) assessments were completed. In addition, the subject had abstained from exercise for a minimum of 12 hours before each visit. Longer abstinence from exercise was not possible given the frequent exercise sessions performed by the athlete. At each testing session, the subject performed the following assessments in the order specified: multifrequency bioelectrical impedance analysis (MF-BIA), RMR using indirect calorimetry, blood pressure and heart rate assessment, DXA scan, an eating questionnaire, isometric lower-body testing, isokinetic lower-body testing, and handgrip dynamometry.

Figure 1.:
Study timeline. Vertical lines represent laboratory assessment sessions and asterisks represent competitions.


The subject in the present case study was a Caucasian female figure athlete (baseline characteristics: age 27 years; BM 65.0 kg; height 167.6 cm; and BF 20.3%). At the commencement of the study, the subject had 11 years of resistance training experience, both within and outside of organized sport participation, and had focused on bodybuilding-style training for 4.5 years. At study initiation, the subject had been performing regimented bodybuilding-style training continuously for approximately 3 years, with one short period of time off due to a medical procedure 9 months before study initiation. The subject was a former NCAA Division II athlete who had previously competed in 4 National Physique Committee (NPC) physique competitions (2014 [×2] in bikini division, 2015 [×2] in figure division). At the commencement of the study, she was beginning her preparation phase before participating in an NPC competition in the figure division. The subject reported that she had not used any substances contained on the World Anti-Doping Agency (WADA) Prohibited List during her lifetime, including during the time period reported in the present case study. Based on substantial personal knowledge of the subject, the researcher who conducted data collection is confident in the veracity of these claims.

Throughout the entirety of the study, the athlete was closely advised by her coach, a competitive bodybuilder with extensive coaching experience. This coach provided the nutrition, exercise, and supplementation program for the athlete; the study personnel did not influence any aspect of training or diet during the study. At study commencement, the subject reported that she did not experience a regularly occurring menstrual cycle. During the 8 months of assessments, she had one menstrual period, which took place after approximately 1 month of preparation (i.e., 3 months before the first competition). Based on self-report, ovulation resumed approximately 3 months after the second competition.

The study was conducted in accordance with the Declaration of Helsinki, and the protocol was approved by the Ethics Committee of Texas Tech University (Project identification code IRB2016-1081) in December 2016. The subject was informed of the benefits and risks of the investigation before any data collection and then chose to sign a university-approved informed consent document before study commencement and provided approval for the publication of the present report.


Dietary Intake and Supplementation

Daily energy and macronutrient intake, as well as dietary supplementation, were prescribed by the athlete's coach throughout the preparation and recovery periods. The subject provided these records to the researchers regularly throughout the study and reported absolute compliance with the program assigned by her coach.

Resistance Training Program

Over the 8-month assessment period, the subject completed 10 distinct resistance training programs. Each program was followed for an average of 3.3 weeks (range: 1.7–5.3 weeks), with program changes implemented periodically to continuously provide a novel training stimulus. Resistance training was performed approximately 4–6 days per week, with each primary muscle group targeted 1–2 times per week; in select instances, a single muscle group (such as the shoulder musculature) was trained 3 times per week to allow for increased emphasis. Training programs generally included 25–35 working sets per workout, with 10–20 sets per muscle group. The subject reported continuing the majority of working sets to the point of volitional concentric failure. Throughout the entire study, target repetition ranges typically varied from 4–20 repetitions per set (minimum: 3 repetitions, and maximum: 35–40 repetitions), with the majority being 8–15 repetitions per set. An evaluation of the overall resistance training program indicated that it did not follow a traditional linear or undulating periodization scheme; rather, the program emphasized substantial variety in exercise selection, frequent program changes, and high volume throughout the study. The duration of rest intervals between sets was not specifically assigned but was estimated by the athlete to be approximately 2 minutes on average. The programs contained a variety of upper- and lower-body single- and multijoint movements, and both free weight and machine-based exercises were incorporated into each session. The lower-body programs used numerous specific exercises, including several squat and deadlift variations, leg press, lunges, leg extensions and curls, glute bridges, hip thrusts, and glute-ham raises. The upper-body programs incorporated a wide array of exercises, including numerous variations of bench/chest press, rows and pull-downs, shoulder press, flyes, lateral and frontal raises, curls, and triceps extensions. The resistance training programs also included a variety of intensification techniques, including drop sets, partial repetitions, cluster sets, eccentrics, supersets, banded resistance, paused repetitions, and sustained isometric muscle actions (isometric holds). Complete details of the resistance training programs cannot be disclosed based on the request of the subject's coach.

Aerobic Training Program

The subject engaged in cardiorespiratory endurance training, such as cycling, walking/running, and stepping exercise, 3–6 days per week throughout the assessment period. Weekly, frequency and duration of sessions increased incrementally; initial endurance training consisted of 3 weekly workouts totaling 64 minutes, building up to roughly 250–300 minutes per week, split between 6 sessions. High-intensity interval training (HIIT) was emphasized in the first 4 months of observation, whereas predominantly steady-state cardiorespiratory training was performed thereafter. Steady-state exercise bouts were generally 30–50 minutes in duration, with target heart rates of approximately 115–150 b·min−1. Steady-state exercise included a mixture of bouts completed in the fasted state and the fed state, whereas all HIIT sessions were completed in the fed state. Leading up to the final competition, steady-state endurance training was completed daily for 16 consecutive days (60–90 minutes per day) and ceased 3 days before competition. A structured endurance training program was not implemented in the post-competition period.

Body Composition Assessment

Body composition was evaluated using a modified 4C model, as described by Wilson et al. (58). The modified 4C model uses DXA output and body water information from MF-BIA or comparable devices, as previously described (48,52). Dual-energy x-ray absorptiometry scans were performed on a calibrated GE Lunar Prodigy scanner with enCORE software (version 16.2), and positioning of the subject was conducted according to manufacturer recommendations. Dual-energy x-ray absorptiometry output was used for bone mineral content (BMC) and for the estimation of body volume (BV). Body volume was calculated from DXA lean soft tissue (LST), FM, and BMC using the following equation developed by Wilson et al. (58) for GE DXA scanners:

Multifrequency bioelectrical impedance analysis was performed using a 19-frequency octapolar device (Seca mBCA 514, Hamburg, Germany), and TBW output was used in the 4C model. The TBW prediction equation of this device was developed and validated using TBW estimates from deuterium dilution, as previously described (5). Fat-free mass hydration (FFM/TBW) was calculated as TBW was divided by DXA-derived FFM to maintain independence of TBW and FFM estimates, as recommended by Wang et al. (56). The scale function of the BIA device was used for a measure of BM. Bone mineral content from DXA was divided by 0.9582 to yield an estimate of bone mineral (Mo), and the 4C equation of Wang et al. (57) was used for estimation of FM:

Fat-free mass was calculated as BM − FM, and relative BF (i.e., BF%) was calculated as (FM/BM) × 100. Test-retest calculations of 15 active females and males in our laboratory indicated that the minimum differences (MDs) considered to be real were 2.1 kg for 4C FM, 2.2 kg for 4C FFM, 3.2% for BF%, and 2.1% for TBW:FFM. Test-retest calculations of 6 adult females indicated that the MDs for BM and TBW were 1.5 kg each, whereas the MDs for extracellular water and intracellular water (ICW) were 1.1 and 0.8 kg, respectively.

Resting Metabolic Rate and Vascular Assessments

Resting metabolic rate and substrate utilization were assessed using indirect calorimetry (TrueOne 2400; ParvoMedics, Sandy, UT, USA). Manufacturer recommendations for daily gas and flow calibrations were followed. Pre-assessment standardization and testing were conducted according to the recommendations of Compher et al. (12). The subject was rested and fasted overnight before each assessment and was transported to the laboratory via automobile. She was instructed to remain motionless, but awake, during the assessment. A blanket was provided at each assessment to promote a comfortable body temperature, and all testing took place in the same climate-controlled room with the lights dimmed. The first 5 minutes of each test were discarded, and the assessment continued until there was a single period of 5 consecutive minutes with a coefficient of variation (CV) for Vo2 and Vco2 of ≤10% (12). The average CV for Vo2 and Vco2 in this case study was 3.5 and 4.2%, respectively, and the testing duration ranged from 10 to 13 minutes. Previous test-retest calculations performed in our laboratory on 6 adult females resulted in MDs for RMR and respiratory quotient (RQ) of 101 kcal·d−1 and 0.1 a.u., respectively. Predicted RMR values were calculated using the Katch-McArdle equation (27):

Immediately after the indirect calorimetry assessment, the subject sat quietly for several minutes before evaluation of heart rate and blood pressure using an oscillometric blood pressure monitor (BP785; Omron, Kyoto, Japan).

Muscular Performance Assessment

Isometric and isokinetic squats were performed using a mechanized squat device (Exerbotics eSq, Tulsa, OK, USA). At the first assessment, the subject's preferred foot positioning was determined using a custom grid overlaid on the foot platform of the squat device. This foot positioning was recorded and used for all visits. In addition, the subject was asked to wear the same shoes at each visit. No weight belts, knee wraps, or other aids were used by the subject during testing. Before testing, the subject's range of motion was determined. The range of motion was set to 90° between the thigh and lower leg at the bottom of the repetition and approximately 170° at the top of the repetition, as determined by a goniometer. During testing, the subject placed her hands on the handles of the mechanized squat device and oriented the torso appropriately so that the designated pads rested on the upper trapezius. The isometric testing included maximal effort pushes at 120 and 150° knee angles. The subject was instructed to attempt to push against the device as hard and fast as possible while attempting to complete a squat movement. A single isometric push was performed at each knee angle, and each effort lasted approximately 2–3 seconds. After the isometric testing, a 3-repetition maximum isokinetic force production test was completed. Each of the repetitions consisted of a 4-second eccentric phase, followed by an approximately half-second pause at the 90° knee position and a 4-second concentric phase. For the first repetition, the subject was instructed to give approximately 50% effort on the eccentric and concentric portions of the movement. The force data from this repetition were discarded. For the second and third repetitions, the subject was instructed to give maximal effort, and these data were used for analysis.

During testing, the force signal was sampled from the load cell at 1 kHz (MP100; Biopac Systems, Inc., Santa Barbara, CA, USA), stored on a personal computer, and processed offline using a custom-written software (LabVIEW, Version 11.0; National Instruments, Austin, TX, USA). The scaled force signal was low-pass filtered, with a 10-Hz cutoff (zero-phase lag, fourth-order Butterworth filter). All subsequent analyses were conducted on the scaled and filtered force signal. For the isometric force production tests, the rate of force development (RFD) was calculated for the first 200 ms by manually specifying the onset of force production within the custom LabVIEW program. For each repetition of the maximum isokinetic force production test, isokinetic peak forces (PFs) were determined as the highest mean 25-ms epoch for both concentric and eccentric testing (i.e., PFCONC and PFECC). The PFs of the second and third repetitions were averaged separately for eccentric and concentric forces. For isometric testing, RFD values for both knee angles were averaged because of the nearly identical patterns observed. The MDs for muscular performance testing using the mechanized squat device in our laboratory have previously been reported (37,49). The MDs for PFCONC and PFECC are 614 and 741 N, respectively (49), and the MDs for RFD at 120 and 150° knee angles are 1,312 and 1,318 N·s−1, respectively (37). Grip strength was assessed for the dominant hand using hydraulic handgrip dynamometry (Model J00105; Lafayette Instrument Co, Lafayette, IN, USA). Three trials were conducted, and the values were averaged.

Eating Questionnaire

The Three-Factor Eating Questionnaire–Revised 18-item version (TFEQ-R18) was completed at each assessment. This instrument contains questions that relate to 3 different components of eating behavior: restrained eating (i.e., conscious restriction of energy intake for the purpose of weight control), uncontrolled eating (i.e., loss of control of food intake associated with hunger and subsequent overeating), and emotional eating (i.e., the presence of irresistible emotional cues associated with eating) (26). Because of the different number of items for each of these components of eating behavior, raw scores were converted to a 0–100 scale. This questionnaire has been validated in the general population (26); but to the authors' knowledge, it has not been used in physique athletes.

Statistical Analyses

Changes in dependent variables were compared to the aforementioned MD values to determine whether observed changes exceeded these values. At each assessment, comparisons to the previous visit's values and baseline values were made using the appropriate MDs.


Dietary Intake

At the onset of the observation period, the subject's diet consisted of 1,610 kcal·d−1 (24.8 kcal·kg·BM−1; and 31.1 kcal·kg·FFM−1) on training days. Protein (PRO) contributed approximately 42% of total energy (∼2.6 g·kg−1), carbohydrate (CHO) contributed approximately 41% of total energy (∼2.5 g·kg−1), and fat contributed approximately 17% of total energy (∼0.46 g·kg−1). With the exception of the inter-competition period, caloric intake was typically reduced by approximately 100 kcal·d−1 on nontraining days to accommodate the reduction in exercise energy expenditure. On nontraining days, initial caloric intake was 1,500 kcal·d−1 (23.1 kcal·kg·BM−1; 29.0 kcal·kg·FFM−1; PRO: 47% energy, 2.7 g·kg−1; CHO: 29% energy, 1.7 g·kg−1; and fat: 24% energy, 0.62 g·kg−1). Energy and macronutrient intakes were adjusted as needed throughout the preparation phase to promote continued fat loss; at its most restrictive, the diet consisted of intermittent days in which 965 kcal was consumed (16.1 kcal·kg·BM−1; 18.2 kcal·kg·FFM−1; PRO: 68% energy, 2.76 g·kg−1current body mass; CHO: 8% energy, 0.33 g·kg−1; and fat: 23% energy, 0.42 g·kg−1). Single-day “refeeds” were instituted as necessary throughout competition preparation, generally occurring every 2–4 weeks. Refeeds consisted of a caloric increase of approximately 200 kcal·d−1; PRO would be reduced by 30–40 g, fat would be reduced to no more than 15 g, and the remainder of caloric intake would be achieved through an increase in CHO consumption. After the final competition of the season, caloric intake was increased in a stepwise manner until body mass was restored to its baseline value. Alterations in energy and macronutrient intake over time are presented in Figure 2. Energy content of supplements (i.e., branched-chain amino acids [BCAAs], fish oil, and exogenous ketones) was calculated separately from dietary intake and was estimated to be 76–132 kcal·d−1 throughout the assessment period.

Figure 2.:
Nutritional intake during the assessment period. Asterisks indicate competitions.


The subject reported the use of various dietary supplements, which were selectively administered and removed from her regimen at specific times throughout the tracking period. For the full duration of the assessment period, the subject reported the use of fish oil (4 g·d−1 taken with meals), BCAAs (10 g intraworkout), glutamine (10 g post-workout), a B-complex supplement (2·d−1), vitamin D3 (5,000 IU·d−1), vitamin K2 (1 mg·d−1), chelated magnesium (800 mg·d−1 total, split between post-workout and pre-bed), a woman's probiotic supplement (≥25 billion colony-forming units per day), and 2 multi-ingredient enzyme supplements (Bio-Gest, Thorne Research; RejuvenZyme, Source Naturals). Beginning in the first 2 months of contest preparation and continuing throughout the rest of the tracking period, the subject added soluble fiber (10 g·d−1), curcumin-sunflower phospholipids (1,000 mg·d−1), calcium d-gluconate (2,000 mg·d−1), and diindolylmethane (200 mg·d−1).

Beginning approximately 2 months before the first competition, the subject began consuming a fat-burning supplement (Lipocalypse, Granite Supplements; 4 capsules per day) consisting of cocoa extract (550 mg·d−1), Teacrine (250 mg·d−1), alpha-glyceryl phosphoryl choline (200 mg·d−1), caffeine anhydrous (200 mg·d−1), Rhodiola rosea (130 mg·d−1), dicaffeine malate (68 mg·d−1), cayenne pepper extract (100 mg·d−1), grains of paradise extract (80 mg·d−1), and black pepper extract (5 mg·d−1). Beginning 1 month before the first competition and continuing until after the second competition, the subject began consuming yohimbine hydrochloride (10 mg·d−1 30 minutes before endurance exercise sessions), l-tyrosine (3 g·d−1 30 minutes before endurance exercise), and 1 packet per day (56 kcal·d−1) of an exogenous ketone supplement containing beta-hydroxybutyrate (Keto OS 3.0, Pruvit). This supplement was taken 30-minute pre-workout on exercise days and when subjective energy was lowest on nonexercise days. During the inter-competition period, a purported anticortisol supplement containing 1,600 mg·d−1 phosphatidylserine was consumed after workout.

In addition to orally administered dietary supplements, the subject used several transdermal creams that purportedly reduce FM or remove water at the administration sites (Vasoburn, Vasoseven, and Vasodry, MPA). These creams were administered topically to the gluteal region, quadriceps, hamstrings, and lower back twice per day each. One of the purported fat-burning creams (Vasoburn) was used during the entire preparation period for the first competition, whereas the other (Vasoseven) was only used during the inter-competition period leading up to the second competition. Immediately before the second competition only, the subject used the purported water-removing agent (Vasodry), as well as taking a diuretic (3 capsules per day; Xpel, MHP) and purported glucose-disposal agent (1 capsule per meal; Matador, Project AD).

Body Composition

At baseline, the subject weighed 65.0 kg. During the 4 months of preparation before the first competition, the scale body mass of the subject decreased by 4.8 kg (7.4%). The lowest BM was achieved 3 days before the second competition (−6.0 kg; −9.2%). After the 2-month recovery period, BM slightly exceeded baseline mass (65.8 kg). The rate of weight loss ranged from 0.1 to 0.7% per week leading up to the first competition. After a weight increase of 1.8% in the 5 days after the first competition, weight loss resumed at a rate of 0.3–0.6% per week until the second competition. Thereafter, BM increased by approximately 1% per week until the end of the assessment period.

Fat mass decreased from 13.2 to 7.3 kg during the 4 months of preparation leading up to the first competition. After a slight increase in the 5 days after the competition, FM continued to decrease. The lowest value (6.8 kg) was reached 3 weeks before the second competition and was maintained through the post-competition assessment. Overall, the subject lost 44.7% of baseline FM during the first 4 months leading up to the first contest, and FM was 48.5% lower than baseline immediately before the second competition. The rate of FM loss per week ranged from 1.3 to 4.5% per week leading up to the first competition. After an FM increase of 2.7% in the 5 days after the first competition, FM loss resumed at a rate of 2.3% per week for 1 month, but no FM reduction was observed in the past month before the second competition. During the recovery period, FM increased at a rate of 8.1–9.2% per week. During the first 2 months of preparation, FFM remained constant at approximately 51.8 kg. Fat-free mass then increased to 52.9 kg (+2.1%) before the first competition and was 52.1 kg immediately before the second competition. During the recovery period, FFM increased and peaked at 54.2 kg (+4.6% relative to baseline). After 2 months of recovery, FFM was 3.1% higher than baseline (i.e., 53.4 kg). Because of the concomitant decreases in FM and increases in FFM, BF% decreased from 20.3% at baseline to 12.2% immediately before the first competition. Immediately before the second competition, this value was reduced to 11.6%. The lowest BF% value of the tracking period (11.2%) was observed immediately after the second competition. Fat-free mass index ranged from 18.4 kg·m−2 (baseline value) to 19.3 (immediately after the second competition). Major body composition results are presented in Table 1, and progress photographs are shown in Figure 3.

Table 1.:
Body composition and metabolic changes throughout the assessment period.*
Figure 3.:
Progress photographs depicting, from left to right, the competitor's physique at baseline, before the first competition, before the second competition, and at the end of the tracking period.

Resting Metabolic Rate and Vascular Function

Resting metabolic rate decreased from 1,345 kcal·d−1 at baseline to 1,202 kcal·d−1 immediately before the first competition. A partial recovery in RMR was observed 5 days post-competition (1,274 kcal·d−1), but RMR decreased to its lowest value of 1,119 kcal·d−1 in the inter-competition period. One month after the second competition, RMR returned to baseline levels (1,363 kcal·d−1), then increased further to 1,435 kcal·d−1 at the end of the recovery period. Respiratory quotient averaged 0.74 in the months leading up to the first competition and increased to 0.82 five days after the first competition. Respiratory quotient again averaged 0.74 in the inter-competition period, but was 0.85 on average after the second competition and during the recovery period. Changes in RMR and comparisons with predicted values are depicted in Figure 4.

Figure 4.:
Resting metabolic rate presented in absolute values (A) and as a percentage of predicted values (B), as calculated using the Katch-McArdle equation (27). Asterisks indicate competitions. RMR = resting metabolic rate.

Systolic blood pressure was 112 mm Hg at baseline and decreased to a low of 97 mm Hg immediately before the second competition. All values were between 97 and 114 mm Hg. Diastolic blood pressure decreased from 86 mm Hg at baseline to a low of 67 mm Hg 3 weeks before the second competition. All values were between 67 and 89 mm Hg. Heart rate was 58 b·min−1 at baseline and increased to a high of 69 b·min−1 immediately before the second competition. All heart rates were between 53 and 69 b·min−1.

Muscular Performance

PFCONC remained within −4 to +5% of the baseline value during the first 2 months of contest preparation but began declining thereafter. By the first competition, PFCONC was 15% lower than baseline and remained 17–25% below baseline for the following month. The value returned to near baseline before the second competition but fell again to 22–24% below baseline after the second competition. At the end of the study, PFCONC was only 5% lower than baseline. PFECC was 7–15% higher than baseline during the first 3.5 months of contest preparation but fell to 7% below baseline immediately before the first competition. Thereafter, PFECC remained 4–13% lower than baseline, with the lowest value observed immediately after the second competition.

The baseline value for RFD was greater than all subsequent visits. Rate of force development declined throughout the first 4 months of preparation and reached its lowest value immediately before the first competition (−57% relative to baseline). A partial recovery took place during the inter-competition period, but the value fell to 45% below baseline immediately after the second competition. Again, a partial recovery took place after competition, but RFD remained 39% below baseline at the final assessment. Lower-body muscular performance outcomes are presented in Table 2 and Figure 5.

Table 2.:
Lower-body muscular performance throughout the assessment period.*
Figure 5.:
Changes in lower-body muscular performance. Lines represent changes in peak force production or rate of force development compared with baseline values. aVisit took place 3 days before competition; bVisit took place 5 days after competition; PFECC = eccentric peak force from isokinetic testing; PFCON = concentric peak force from isokinetic testing; RFD200 = rate of force development from 0 to 200 ms during isometric testing.

Isometric handgrip strength was 38 kg at baseline and decreased stepwise to a low of 31 kg (−19%) immediately after the second competition. Handgrip increased to the baseline value during the inter-competition period, then fell after the second competition. At the end of the assessment period, handgrip strength remained 8% below the baseline value.

Three-Factor Eating Questionnaire

When expressed from 0 to 100, the score for cognitive restraint at the beginning of the preparation period was 67. After 1 month of contest preparation, this value increased to 83 (+24%). At all subsequent assessments, the cognitive restraint score remained steady between 89 and 94 (33–40% above baseline). Uncontrollable eating had a baseline score of 44 and reached a low value of 33 (−25%) 3 days before the first competition. However, this value increased between competitions and was 56 (27% above baseline) 3 days before the second competition. Furthermore, uncontrollable eating continued to increase during the 1st month of the recovery period. After 1 month of recovery, the score was 67 (52% above baseline). Uncontrollable eating remained 18% greater than baseline (i.e., a score of 52) after 2 months of recovery. The baseline emotional eating score was 11, but the subject produced a score of 0 for all the remaining assessments.


The purpose of this case study was to evaluate changes in body composition and neuromuscular performance before, during, and after the competitive season of an experienced female figure competitor. The competitor's energy intake was progressively reduced throughout contest preparation and increased after competition. A high-protein diet was maintained throughout the assessment period, and a variety of dietary supplements with purported ergogenic value were used. High-volume resistance training was completed for the entirety of the assessment period, and the frequency and duration of aerobic training increased during the pre-competition phase. As a result of these lifestyle modifications, FM substantially declined throughout contest preparation, while small increases in FFM were observed. Resting metabolic rate decreased during contest preparation, but fully recovered thereafter. Decrements in neuromuscular performance were observed throughout the competition period and persisted 2 months after the final competition.

The subject followed a high-protein diet throughout contest preparation, beginning with a daily intake of 170 g·d−1 (2.6 g·kg−1), with minimal change throughout the preparation and recovery period. High-protein diets have previously been recommended for competitive physique athletes (20), largely because of favorable effects on satiety, lean mass retention, and the thermic effect of feeding. The protein intake observed in the current study seems to be fairly typical of female physique sport competitors, as recent survey data indicated that female competitors consumed an average of 2.7–2.8 g·kg−1 throughout contest preparation (10). This consistently high protein consumption by the competitor may help to explain the small improvement in FFM seen throughout the preparation period. In addition, high protein intake may have facilitated the observed recovery of RMR after competition, as post-competition protein intake has previously been associated with RMR recovery after competition in a sample of male and female physique athletes (54).

By contrast, the subject consumed less carbohydrate compared with recently reported averages for females; a recent survey documented a reduction in daily carbohydrate intake from 3.9 to 3.3 g·kg−1 in female competitors (10). The current subject started with a daily intake of 2.5 g·kg−1, which dropped to 0.33 g·kg−1 at the most restrictive point before competition. Although efficacious for FM reduction, this low carbohydrate approach may have contributed to observed neuromuscular decrements throughout contest preparation, as localized glycogen depletion within myofibrils has been shown to inhibit calcium release from the sarcoplasmic reticulum during fatigue (35).

Total caloric intake in this study followed a similar pattern of reduced intake as compared to previously reported values; the current subject reduced intake from 24.8 kcal·kg−1 to a minimum value of 16.1 kcal·kg−1, in comparison with recently published averages in female competitors of 33.8–29.7 kcal·kg−1 (10). This discrepancy may be attributed, in part, to differences in preparation timelines. Average values were obtained from female athletes that prepared for competition over an average of 23.3 weeks (10), whereas the current subject completed the first competition after approximately 18 weeks, followed by a modest increase in caloric intake, then a short-term reduction in preparation for the second competition. Dietary fat intakes observed in the current case study (0.46–0.42 g·kg−1) are also less than reported averages (0.8–0.6 g·kg−1) (10).

The subject in the current study also took several dietary supplements with purported ergogenic effects, per recommendations from her coach. Several of these supplements are commonly consumed within this population; a recent survey in female competitors indicated that an average of 5.4 total supplements was used in the contest preparation period, with 53.5% of respondents using BCAAs, 46.6% using an omega-3 fatty acid supplement, 36.5% using fat burners, 31.0% using individual amino acids, and 11.1% using vitamin D (10). Although there are limited human data available to evaluate the efficacy of several of the supplements consumed in the current case study, some have been studied to determine their effects on body composition and performance. As reviewed by Helms et al. (20), previous research has demonstrated that leucine stimulates protein synthesis, and that supplementation of all 3 BCAAs (leucine, isoleucine, and valine) prevents depletion of any single BCAA. However, BCAAs are apparently inferior to the full spectrum of essential amino acids (EAAs) or whole proteins for promoting anabolism within skeletal muscle (59). Regarding body composition, an abstract has reported enhanced performance and body composition adaptations in response to resistance training with BCAA supplementation (50), but these data were not published as a peer-reviewed article. A separate study showed that BCAA supplementation enhanced the retention of lean mass and strength during hypocaloric conditions in resistance-trained males (15), but key limitations of this study have been noted elsewhere (14). Although the relative utility of BCAA supplementation may be increased in hypocaloric conditions, it is unclear whether such supplementation is warranted in the context of a high-protein diet, such as the diet in the current case study. The subject also supplemented with glutamine, a conditionally EAA for which dietary intake becomes increasingly important in the context of severe physiological stress, muscle wasting, or protein-deficient diets. Although research has shown promising effects of glutamine supplementation in clinical populations subjected to considerable physiological stressors inducing catabolism, research in young, healthy adults documented no benefits of glutamine supplementation for performance or body composition during a resistance training program (9). In addition, a high-protein diet typically provides ample dietary glutamine, which may further limit the utility of glutamine supplementation for competitive physique athletes.

The subject in the current case study supplemented with both vitamin D3 and vitamin K2. As reviewed by Dahlquist et al. (13), there are several plausible connections between vitamin D and muscle function, force production, and recovery, and a synergistic relationship between vitamin D and vitamin K has been identified. A meta-analysis by Beaudart et al. (3) concluded that vitamin D supplementation significantly enhanced strength, but not muscle mass or muscle power. However, it is important to note that most of this pooled research were conducted in older populations. To determine the efficacy of vitamin D supplementation for physique athletes, more research is needed in young, athletic populations. There is growing evidence to suggest that supplementation with fish oil, or its primary constituent fatty acids, eicosapentaenoic acid, and docosahexaenoic acid, may support muscle mass and function (47). However, much of this evidence is drawn from observational studies, animal model research, and studies conducted in sarcopenic populations, so extrapolation of these findings to young, athletic populations must be done cautiously. To promote further reduction of FM, the subject also consumed a thermogenic supplement and yohimbine before aerobic exercise. Although exact formulations vary between products, research in caffeinated thermogenic supplements has documented significant acute increases in energy expenditure (8), and yohimbine has been shown to enhance fat loss in male professional athletes (36).

Taken together, the subject exhibited supplementation practices that seem to be common among female physique athletes (10). However, because of the inherent limitations of case studies, it is impossible to conclusively determine whether these supplements were truly efficacious or to quantify the effects attributable to each supplement. As such, speculation regarding the effects of supplementation in the current case study requires caution.

Analysis of the subject's exercise program provides insights as to how the practices of physique competition preparation align with current evidence. With respect to the resistance training variables, the subject's program was consistent with those generally performed by other physique athletes. A survey of 127 competitive male bodybuilders by Hackett et al. (18) found that the majority of respondents reported performing 4–5 sets per exercise during the pre-contest phase of training, using a repetition range of 4–15 repetitions per set with a weekly training frequency of 5–6 days. The subject in the present case performed a multiset routine whereby each muscle group was trained with 10–20 weekly sets. This is consistent with a recent meta-analysis by Schoenfeld et al. (45), who found that the performance of at least 10 sets per muscle per week was needed to maximize the hypertrophic response to resistance training. The repetition range of the subject of 4–20 repetitions per set was slightly wider than that reported in the survey by Hackett et al. (18). However, these values are consistent with a recent meta-analysis showing that hypertrophy can be maximized across a spectrum of loading zones (44). When considering repetition volume (sets × repetitions) per muscle group, an evidence-based review of training strategies for natural bodybuilders during pre-contest preparation advocated performance of 40–70 repetitions per session per muscle group (21). Although the subject's values were somewhat higher than those recommended, Helms et al. (21) acknowledged that advanced physique athletes may require greater repetition volumes to maximize hypertrophic adaptations. Moreover, the additional volume performed by the subject to bring up “lagging” muscle groups is in line with evidence-based recommendations (21). The subject's use of intensification techniques such as eccentric overload, supersets, and partial repetitions also mirrors that of general practices reported by competitive bodybuilders (18), as well as having some basis in evidence-based practice (42). Finally, the subject used a form of periodization to manipulate training variables, which has been recommended in the literature as an important pre-contest strategy to optimize results (21).

The subject's aerobic training program showed similarities with those previously reported by physique athletes, with the majority of competitive bodybuilders spending 120–150+ minutes per week performing aerobic exercise (18). The subject in the current case study performed incrementally increasing amounts of cardio beginning with 64 minutes per week and culminating with 250–300 minutes per week. In addition, the subject used a combination of HIIT and steady-state exercise early in the pre-competition period. Helms et al. (21) postulated that although HIIT could have increased benefits from a fat loss standpoint for physique competitors, there may be detrimental effects on recovery. Thus, the subject's strategy of transitioning to steady-state exercise would seem to have merit given that her energy intake was substantially curtailed as she got closer to competition. The subject's use of fasted cardiovascular training has not been validated as a superior fat loss strategy in recreationally active women (43); anecdotal claims as to potential benefits of this approach in athletes with low BF remains speculative. There is evidence of a chronic interference effect when high volumes of aerobic exercise and resistance training are performed in tandem, whereby muscular gains are ultimately compromised because of alterations in intracellular signaling and fatigue (11). Given the subject's concomitant increase in FFM and loss of FM, this does not appear to have been the case here.

Guidelines for physique athletes have recommended rates of weight loss of 0.5–1.0% per week (20), and it is believed that slower rates of weight loss promote greater preservation of FFM (1). The rate of weight loss in the present investigation ranged from 0.1–0.7% per week, which could have contributed to the small amount of FFM accretion. As anticipated, FM was substantially reduced during the contest preparation period. The rate of fat loss was approximately 1.5–2% per week during the first 2 months of contest preparation but increased to approximately 4% per week during the 3rd and 4th months. This acceleration of fat loss may have been due to the increasingly aggressive reduction in energy intake and greater quantity of aerobic exercise. During the recovery period, FM increased at a rate of approximately 8.5% per week. Overall, BF% was nearly halved during the contest preparation phase, from approximately 20% at baseline to 11% at the second competition. This is relatively similar to the reductions reported by Halliday et al. (19) (15% to 9%), Rohrig et al. (40) (30% to 16%), and Petrizzo et al. (39) (23% to 11%) over 20–32 weeks. These results were also similar to the reductions in BF reported by Hulmi et al. (23) in a group of 27 females preparing for physique competitions (23% to 13% using DXA).

Fat-free mass increased by 2.7% after 3 months of contest preparation, was 2.1% greater than baseline before the first competition, and fell to only 0.6% above baseline before the second competition. Fat-free mass then increased in the early recovery period and was maintained thereafter. However, the gains did not exceed the MD until immediately after the second competition. Therefore, the apparent increases in FFM during the contest preparation period should be viewed cautiously. Furthermore, it is highly likely that the acute increases in FFM observed after each competition were at least partially due to bolstering of glycogen stores and associated water. A recent investigation indicated that multifrequency impedance techniques may be able to detect increases in ICW in response to carbohydrate loading (46), and we observed an increase in ICW that exceeded the MD when comparing values from 3 days before 5 days after each competition. This is in agreement with previous reports that acute bolstering of muscular glycogen content can increase TBW and FFM estimates (4,53). Furthermore, the increase in reported energy intake and measured RQ after competition supports the contention that the increased FFM immediately after contest could have been due to carbohydrate stores and water.

Although it is postulated that the loss of FFM during a hypocaloric diet may be directly proportional to the size of the energy deficit (21), the subject in the present case study maintained FFM while decreasing energy intake by up to 40% below baseline intake. The current body of literature in physique athletes preparing for competition indicates that a longer dieting phase—and consequently a slower rate of weight loss—is a successful strategy for FFM retention in both males (38,54) and females (19,39,40). Halliday et al. (19) observed no changes in DXA lean mass during the contest preparation period, whereas Petrizzo et al. (39) reported a 1.5% increase in DXA lean mass, and Rohrig et al. (40) reported a 2.8% increase in FFM as assessed by hydrodensitometry. In addition, Hulmi et al. (23) reported maintenance of DXA lean mass (+1.1 ± 3.1%) after a 20-week contest preparation period in 27 amateur female fitness competitors. However, FFM estimated from MF-BIA and skinfolds decreased by 3.0–3.9%, and the reported deviations in DXA and MF-BIA FFM estimates indicate that some competitors increased lean mass during the contest preparation, whereas others experienced decreases. Recently, Campbell et al. (7) reported a mean gain in lean mass of 2.1 kg with a corresponding decrease in BF of 1.1 kg in a cohort of aspiring female physique competitors consuming a high-protein diet (2.5 g·kg−1·d−1). These findings lend support for the ability to simultaneously increase FFM and decrease BF when combining regimented resistance training with high-protein intake, as seen in our case study. Interestingly, at certain points during the study, total energy availability for the subject was below the levels proposed to be necessary to maintain muscle mass in male bodybuilders (i.e., 25 kcal·kg·FFM−1) (16). Based on our findings and other case studies in the literature (39,40), it is possible that this estimate is not generalizable to female physique competitors.

Importantly, many of the aforementioned investigations have potentially meaningful limitations in body composition assessment methodology. The assessment methods used in these studies (e.g., DXA, hydrodensitometry, and skinfolds) necessitate the assumption of TBW:FFM and have questionable accuracy as compared to criterion methods in athletic populations, particularly when used at the individual level (31). A multicompartment model containing an estimate of TBW has been reported to produce the lowest total error (<1% fat) in female athletes, whereas the use of DXA alone has been discouraged because of high error (32). In addition, van der Ploeg et al. (55) reported that, in a sample of 5 competitive female bodybuilders, DXA underestimated BF by approximately 3% as compared to a 4C model because of a concomitant overestimation of FFM and underestimation of FM. The same investigation found that although hydrodensitometry only produced average differences in BF% of 0.6% as compared to the 4C model, greater variability in BF estimates was observed (55). The importance of including a TBW estimate in body composition models becomes more important as TBW:FFM deviates from expected values. In the present investigation, TBW:FFM fluctuated from 69.9 to 74.3% using independent TBW and FFM estimates. A previous investigation of competitive female bodybuilders reported TBW:FFM values ranging from approximately 71.5–76.5%, using TBW estimates from deuterium dilution (55). Therefore, because of these methodological considerations, the inclusion of TBW estimates in the present body composition assessment model likely strengthens the veracity of our results. Despite this strength, there are also potential limitations of the methods used in the present investigation. Although the use of DXA for BV has recently been validated in several populations, including the physically active (34,48,58), it has not been specifically validated in athletes with atypical body compositions. As such, the use of predicted BV is a limitation of our assessment method.

The observed reduction in RMR is consistent with previous observations of male and female physique athletes preparing for competition (19,38–40,54). The subject's RMR decreased by 143 kcal·d−1 leading into the first competition and decreased by an additional 83 kcal·d−1 (226 kcal·d−1 relative to baseline RMR) during the time period between the 2 competitions. Rohrig et al. (40) documented a similar reduction of 155 kcal·d−1 in RMR leading up to a competition. The greater rate of decline in RMR observed between competitions could be due to maintaining a larger energy deficit for several weeks through a combination of the lowest energy intakes and highest quantity of aerobic exercise observed during the tracking period.

Although it is often stated that FFM is the best single predictor of measured RMR (30), this observation is likely more applicable to male athletes than female athletes (2). Furthermore, the strength of this association was not reflected in the longitudinal changes observed in the present investigation. In this study, RMR decreased by over 200 kcal·d−1, but this occurred without any loss of FFM. In fact, when RMR was at its nadir, FFM was actually 1.2 kg higher relative to pre-diet levels. Given the observed maintenance of FFM, the negative shift in energy balance and subsequent physiological adaptations are likely the primary variables responsible for the reductions in RMR. Caloric intake was reduced by approximately 40% at its most restrictive level, which corresponded to the lowest observed RMR value. This aligns with a report from Thompson and Manore (51), indicating that the best single predictor of RMR in female endurance athletes is energy intake. Furthermore, it has previously been reported that females with exercise-induced amenorrhea display reduced RMR relative to exercising females with ovulatory menstrual cycles, and the RMR reduction is due to metabolic and endocrine adaptations rather than reductions in the mass of metabolically active tissue (25). This demonstrates the importance of factors other than FFM as determinants of RMR and indicates that the relationship between FFM and RMR may be dissociated in some contexts, including exercising females with amenorrhea (25).

Few studies have investigated the time course of RMR recovery after a competition period. Resting metabolic rate in the present case study recovered to its baseline value (89% of the predicted value) approximately 5 weeks after the second competition. Previous data (54) demonstrated a nearly complete restoration of RMR (99.6% of the predicted value) in male and female competitors approximately 5 weeks after a physique competition. The present case study is unique in that RMR was assessed for a longer recovery period after the second competition. At approximately 9 weeks after the second competition, RMR increased to 1,435 kcal·d−1 (94% of the predicted value) and was 6.7% higher than the pre-diet RMR (1,345 kcal·d−1). To the best of our knowledge, this is the first case study to present a comprehensive assessment of RMR throughout the pre-, inter-, and post-competition periods.

In addition to the information they provide about substrate oxidation, RQ values have been used to describe energy intake, with lower RQ values corresponding to underfeeding and higher values corresponding to overfeeding (28). In agreement with these designations, we observed low RQ values (≤0.76 a.u.) during periods of underfeeding, whereas higher RQ values (≥0.82 a.u.) were observed during periods of increased energy and carbohydrate intake (i.e., post-competition and during the recovery period). The RQ values indicate that a greater proportion of cellular energy was derived from lipids during the periods of underfeeding and carbohydrate restriction, whereas more cellular energy was derived from carbohydrate when energy and carbohydrate intake increased.

In relation to heart rate and blood pressure, with the exception of baseline diastolic blood pressure, all hemodynamic assessments were within normal clinical ranges. At baseline, diastolic blood pressure was 86 mm Hg, and subsequently declined to normal levels throughout the competition preparation period, reaching a low of 67 mm Hg between competitions.

The subject showed substantial decreases in muscular performance over the course of the competition period. Through the initial months, PFCON was relatively unchanged, but declined by 15–25% by the time of the first competition and the succeeding month thereafter. Similarly, PFECC decreased to 7% below baseline immediately before the first competition. Rate of force development showed the greatest alteration, declining 57% just before the first competition. Isometric handgrip strength decreased by as much as 19% immediately after the second competition. All performance-related values remained below baseline at the end of the study period, despite slightly elevated FFM relative to baseline. These data are consistent with observations in previous case studies demonstrating persistent performance decrements after competition, although the 9-week post-competition recovery period in the present investigation was shorter than the 5- to 6-month periods used in previous investigations (38,41). Rossow et al. (41) showed marked decreases in various measures of strength and power throughout the pre-competition period in a male bodybuilder, despite only a small reduction in FFM, with some of these values remaining suppressed 6 months after competition. Specifically, strength on the squat and deadlift exercises and critical power were not recovered until 4 months after competition, whereas bench press strength and anaerobic working capacity remained below baseline 6 months after competition. Rossow et al. (41) posited that alterations in mood states, particularly a persistent reduction in vigor, could be potential explanations for the observed reductions in performance. They found that fatigue assessed by the Profile of Mood States questionnaire remained above baseline levels for at least 2 months after competition, whereas vigor remained far below baseline at the end of the tracking period (i.e., 6 months after competition). Although speculative, it is possible that similar enduring changes in mood states impacted performance during recovery in the present investigation. However, previous studies have also reported decreases in FFM (38,41), which could indicate that reductions in performance were partially attributable to loss of contractile proteins in skeletal muscle. Unlike these studies, performance decrements were observed in this study, despite a small gain in FFM. This may suggest that the observed reductions in muscular performance were due to impairment of neural aspects of force production rather than reductions in the quantity of contractile proteins in skeletal muscle.

Several additional mechanistic explanations can be hypothesized to account for the performance-related decrements noted in our study. For one, energy intake progressively decreased over the course of the pre-competition period with total energy consumed reaching a nadir of 965 kcal·d−1. Low-energy availability may bring about fatigue and lethargy through various physiological and psychological changes that ultimately impairs one's ability to produce force (33). In a study of competitive male judokas, Filaire et al. (17) demonstrated that a reduction of 1,000 kcal over 7 days significantly decreased anaerobic performance, and these findings occurred in tandem with altered mood states including those of confusion, anger, fatigue, and tension. Similar findings were shown in a group of well-trained subjects after the loss of 6% BM from adherence to a hypocaloric diet, with evidence of significantly impaired anaerobic capacity and cognition immediately after diet (22). Moreover, a progressive decrease in the subject's carbohydrate consumption was noted concomitant with her reduction in energy intake. Carbohydrate intake declined to 20 g·d−1 at its most restrictive time point, which necessarily would deplete muscle glycogen stores. Training in a low glycogen state reduces the ability to train at high intensities and increases the perception of effort while decreasing power output (6). In addition, the combination of low-energy intake, low glycogen stores, and high exercise volumes has been implicated in overtraining syndrome (29). Although we did not attempt to qualify markers of overtraining in the subject, there is strong evidence that its onset leads to decreases in performance (29). The fact that the subject persistently trained to failure may have exacerbated the condition by altering her anabolic hormonal profile (24).

There are several limitations of this study, the foremost of which is the case study nature of this investigation. Because of the multifaceted nature of the contest preparation program and the variability in individual responses to such lifestyle interventions, it would be inappropriate to categorically apply the observations made in the present investigation to all physique athletes. Furthermore, the many components of the contest preparation strategy clearly preclude the determination of the relative contribution of each component to the observed outcomes. Some relevant physiological variables were not assessed, notably hormones and other blood-borne markers. Finally, the recovery period was shorter than some previous investigations in male physique athletes, and assessments were not continued until the point of full muscular performance recovery.

Practical Applications

The present case study provides an in-depth evaluation of the time course of body composition and neuromuscular performance changes in an experienced female figure competitor during the contest preparation, 2 competitions, and a post-competition recovery period. Using a more advanced method of body composition assessment than previous investigations (i.e., a multicompartment model including body water estimates), substantial reductions in FM, and small increases in FFM were observed during the contest preparation. However, neuromuscular performance decrements were observed throughout the contest preparation. Furthermore, force production and RFD remained below baseline after 2 months of recovery, despite the competitor's return to baseline energy intake, RMR, and BM. The growing body of research in physique athletes can be used to understand the current practices of competitors and refine strategies used by coaches and practitioners to promote superior maintenance of neuromuscular performance during and after periods of substantial energy restriction.


No funding was received for this study. Costs associated with data collection were paid by the Department of Kinesiology & Sport Management at Texas Tech University. The authors declare no conflict of interest. G.M. Tinsley conceived and designed the experiment; G.M. Tinsley performed the experiment; G.M. Tinsley, E.T. Trexler, and A.E. Smith-Ryan analyzed the data; all authors contributed to interpreting the data and writing the manuscript; and all authors read and approved the final manuscript.


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resistance training; energy intake; dieting; bodybuilding; fat loss

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