The Psychological and Physiological Consequences of Low Energy Availability in a Male Combat Sport Athlete

Abstract

Purpose 

This study aimed to evaluate the effects of low energy availability (EA) on health and performance indices associated with the Male Athlete Triad and Relative Energy Deficiency in Sport (RED-S) models.

Methods 

Over an 8-wk period, a male combat sport athlete adhered to a phased body mass (BM) loss plan consisting of 7-wk energy intake (EI) equating to resting metabolic rate (RMR) (1700 kcal·d⁻¹) (phase 1), 5 d of reduced EI (1200–300 kcal·d⁻¹) before weigh-in (phase 2), and 1 wk of ad libitum EI postcompetition (phase 3). EA fluctuated day by day because of variations in exercise energy expenditure. Regular assessments of body composition, RMR, cardiac function, cardiorespiratory capacity, strength and power, psychological state and blood clinical chemistry for endocrine, bone turnover, hydration, electrolyte, renal, liver, and lipid profiles were performed.

Results 

BM was reduced over the 8-wk period by 13.5% (72.5 to 62.7 kg). No consequences of Male Athlete Triad or RED-S were evident during phase 1, where mean daily EA equated to 20 kcal·kg·fat free mass (FFM)⁻¹·d⁻¹ (range, 7 to 31 kcal·kg FFM⁻¹·d⁻¹) and BM and fat mass (FM) losses were 6.5 and 4.4 kg, respectively. However, consequences did present in phase 2 when mean daily EA was consistently <10 kcal·kg FFM⁻¹·d⁻¹, as evidenced by alterations to endocrine hormones (e.g., testosterone <5 nmol.L⁻¹) and reduced RMR (−257 kcal·d⁻¹).

Conclusion 

Data demonstrate that 7 wk of daily fluctuations in EA equating to a mean value of 20 kcal·kg FFM⁻¹·d⁻¹ permits reductions of BM and FM without perturbations to physiological systems associated with the Male Athlete Triad and RED-S. By contrast, a subsequent period of five consecutive days of EA <10 kcal·kg FFM⁻¹·d⁻¹ induced consequences of Male Athlete Triad and RED-S.

Combat sport athletes compete within designated weight categories that are intended to promote fair competition by matching opponents of equal stature and body mass (BM) (¹). In an attempt to qualify for lowest weight category possible (often termed “making weight”), these athletes typically engage in practices associated with acute and chronic BM loss, many of which are detrimental to health and performance (²). In the acute phase (i.e., within hours to days before official weigh-in), combat sport athletes often use combinations of active and passive dehydration techniques, where 5%–10% reductions in BM have been observed (³). These practices may cause acute kidney injury and can even lead to death in extreme situations (^4,5). As such, there is a definitive need for these athletes to adopt a more gradual approach to making weight, where BM is manipulated across longer timescales (i.e., weeks to months), therefore reducing the requirement to engage in methods of extreme dehydration.

Combat sport athletes often complete a training camp before competition, ranging in duration from 4 to 12 wk. Such timescales allow for the opportunity to reduce BM through an accumulated energy deficit, although it has been reported that these athletes may resort to dietary practices limiting energy intake (EI) to only one meal per day (⁶). These types of feeding strategies are likely to result in low energy availability (EA), thereby manifesting as consequences associated with the Male Athlete Triad or Relative Energy Deficiency in Sports (RED-S) models (^7,8). In the triad model, low EA is associated with a conservation of energy metabolism (e.g., via hypothalamic–pituitary–thyroid axis disturbance, reductions in insulin-like growth factor 1, and leptin), suppression of reproductive function (e.g., via hypothalamic–pituitary–gonadal axis disturbance and poor semen quality), and impaired bone health (⁹). In the RED-S model, these consequences are purported to further extend to impairments of metabolic rate, immunity, protein synthesis, and cardiovascular function, all of which can be causative of reduced health and performance outcomes (¹⁰). Laboratory studies on females have demonstrated that some of these systems are perturbed at a daily EA <30 kcal·kg FFM⁻¹·d⁻¹, but it is not yet clear whether the same threshold applies for males (^11,12). Furthermore, although experimental modulation of daily low EA often involves a consistent absolute value, it is possible that fluctuations in daily low EA status (i.e., via manipulation of EI and/or exercise energy expenditure [EEE]) may reduce the risk of developing consequences associated with the Male Athlete Triad and RED-S (^6,13). This approach may be particularly beneficial in male athletes given that impairments in the hypothalamic–pituitary–gonadal axis can be restored within days of increased EA (¹⁴).

On this basis, the aim of the present case report was to evaluate the effects of incorporating daily fluctuations in low EA on health and performance indices associated with the Male Athlete Triad and RED-S models. To this end, we monitored a male combat sport athlete for an 8-wk period while making weight for competition and for a 1-wk recovery period postcompetition. Importantly, we performed regular assessments of body composition, resting metabolic rate (RMR), cardiac function, maximal dynamic strength (MDS) and power (MDP), cardiorespiratory capacity, psychological state, and blood clinical chemistry to assess for biomarkers related to endocrine, bone turnover, hydration, electrolyte, renal, liver, and lipid profiles.

METHODS

Athlete Overview and Case Report Design

The athlete (age, 19 yr; stature, 1.66 m; BM, 72.5 kg; body mass index, 26.3 kg·m⁻²) was a male international standard (>5 yr experience) Taekwondo competitor, who typically competed 10 times per year in the <68-kg featherweight category, habitually losing 4–5 kg across periods of 3–4 wk before competition. For the present case report, the athlete elected to further reduce his BM to compete in the <63-kg bantamweight category at the 2018 British University Championships, therefore requiring a BM loss of >9.5 kg (>13%) over a period of 8 wk. The implementation of an intervention to achieve this aim and the assessment of health and performance consequences associated with the Male Athlete Triad and RED-S (¹⁵) were completed via a multimethodological approach, as described in the subsequent sections and highlighted in the supplemental content (see Figure, Supplemental Digital Content 1, Diagram of measurements taken throughout phases 1 & 2 intervention and phase 3 after competitive recovery periods, https://links.lww.com/MSS/C148). Measurements were taken daily and also at set intervals inclusive of 8, 4, and 1 wk before competition (−8 WK, −4 WK, and −1 WK) as well as the day before the official competition weigh-in (−1 D), the official competition weigh-in day (WI), 24 h postcompetition (+1 D), and 1 wk postcompetition (+1 WK). The athlete gave written informed consent, and this case report was approved by the Liverpool John Moores University research ethics committee.

Anthropometric Assessment

Daily BM was measured postvoid of the bladder/bowels between 0900 and 0930 h after a 12-h fast and determined to the nearest 0.01 kg on a calibrated digital scale, with measures of stature established to the nearest 0.1 cm using a freestanding stadiometer (Seca 702 and 123; Seca GmbH, Hamburg, Germany). Body composition was assessed via dual x-ray absorptiometry (DXA-QDR Series Discovery A, software version 12:4:3; Hologic Inc., Bedford, MA), to generate fat free mass (FFM), fat mass (FM), percentage body fat (BF%), total body (minus head), and lumbar spine bone mineral content (BMC) and density (BMD) z-scores, alongside the anthropometric sum of eight skinfolds (∑_8SKf; Harpenden, Baty Int., West Sussex, UK). Measurements were collected according to the DXA best practice protocol (¹⁶), BMD, and BMC as previously described (¹⁷) and ∑_8SKf adhering to the guidelines of the International Society for the Advancement of Kinanthropometry. Laboratory technical error of measurement and coefficient of variation (CV) for DXA-derived measures of FFM, FM, and BF% are 0.44 kg:1.0%, 0.37 kg:1.9%, and 0.41:1.9%, respectively, and for BMD measures, CV is <1.5%.

RMR and RMR_ratio

Measured RMR (RMR_meas) was assessed using indirect calorimetry (GEM Open Circuit Indirect Calorimeter; GEMNutrition Ltd., Warrington, UK), calibrated via known concentrations of O₂/CO₂, a zero span gas and an ethanol burn, to confirm an established respiratory exchange ratio of 0.67. Laboratory-based technical error of measurement and CV for this system is 42 kcal·d⁻¹ and <2%, respectively. Application of measurement and subsequent analyses were conducted according to the recommendations of Bone and colleagues (¹⁸), and predicted RMR (RMR_pred) was calculated via the Cunningham equation (¹⁹). RMR_ratio was established by the division of RMR_meas and RMR_pred, where values <0.90 were classified to define instances of potential energy deficiency (²⁰). RMR_meas values below those of RMR_pred were also used to calculate instances of adaptive thermogenesis (²¹).

Blood Clinical Chemistry and Hydration Status

All blood samples were drawn from the antecubital vein of the left arm, which were collected and stored as previously described (²²). Measures of endocrine, bone turnover, electrolyte, renal, liver, and lipid-based biomarkers were conducted via immunoassay with chemiluminescence detection on Roche Cobas e601/602 and c701/702 modular analyzers, using rate A, 1, and 2 point end assays, and potentiometry ion-selective electrode on a Roche Cobas ISE analyzer (Roche Diagnostics Ltd., Burgess Hill, UK). Plasma (P_osm) osmolality was examined to establish hydration status via freezing point depression (Advanced Micro-Osmometer 3320; Advanced Instruments, Norwood, MA) as previously described (²³). Laboratory individual inter/intra-assay CV and sensitivity (replicates of the zero standard) for all biomarkers are described in the supplemental content (see Table, Supplemental Digital Content 2, CV%, range and sensitivity of measurement for all assessed blood clinical chemistry biomarkers, https://links.lww.com/MSS/C149). Measures for bone formation and reabsorption were divided to calculate a ratio, with values above or below one being indicative of positive or negative bone turnover responses, respectively.

Cardiac Screening

Cardiac scanning and subsequent analyses were conducted by a registered clinical cardiac physiologist before exercise testing via 12-lead electrocardiogram and echocardiography (²⁴). Indices of heart rate (HR), cardiac output (CO), and deformation of the left and right ventricles were established through alterations in the structure of the left ventricular end-diastolic volume and right ventricular diastolic area in parallel to function from left ventricular ejection fraction and right ventricular fractional area change. Intrameasurement CV for all assessments was <15%.

Cardiorespiratory Capacity and Substrate Utilization Assessment

Combined peak oxygen uptake (V˙O_2peak) and fat oxidation rate (FAT_peak) were measured via an online indirect calorimetry system (CPX Ultima Series; Medgraphics, Saint Paul, MN) during an incremental exercise test performed on a motorized treadmill (h/p/cosmos Pulsar; h/p/cosmos Sports & Medical gmbh, Nussdorf-Trainstein, Germany). The test began with 3-min stages at speeds of 6 to 11 km·h⁻¹, followed by 2-min stages at 12, 14, and 16 km·h⁻¹. The treadmill was then inclined by 1° each minute, until volitional exhaustion despite strong verbal encouragement. Raw V˙O₂, V˙CO₂ (L·min⁻¹), and respiratory exchange ratio data were then averaged and converted into kilocalories (kcal) (¹³), and FAT_peak was calculated as the highest fat oxidation rate, using the following equation: g·min⁻¹ = (1.695 V˙O₂) – (1.701 V˙CO₂) (²⁵). The laboratory test–retest reliability of this system using 95% limits of agreement is 0.29 ± 2.4 mL·kg⁻¹·min⁻¹. All tests took place in the same order as presented, under standard laboratory conditions (room temperature, 20.0°C ± 1.5°C; humidity, 38.5% ± 4.0%; barometric pressure, 750.2 ± 6.5 mm Hg), and were performed after a 12-h fast between 0900 and 1100 h.

MDS and MDP Assessment

MDS was assessed via one-repetition maximum (1RM) upper and lower bench press and back squat exercises. The athlete performed a readiness set of 10 repetitions with a 20-kg barbell, then 10 repetitions at 50%, 5 repetitions at 75%, and 1–2 repetitions at 90% of predicted 1RM. All subsequent 1RM attempts were interspersed with a 3-min recovery, and the load was exponentially increased until failure occurred. MDP was examined via the same exercises for both upper and lower force velocity profile as previously described (²⁶) by performing three maximal attempts at 20%, 40%, 60%, and 80% of measured 1RM load. Concentric average power (W), force (N), and velocity (m·s⁻¹) were recorded by a linear encoder (MuscleLab version 4010, software version 8.31; Ergotest, Porsgrunn, Norway) mounted perpendicular to the line of exercise movement. MDS tests were performed on the same day as the anthropometric and physiological assessments between 1700 and 1800 h, whereas MDP tests were performed at the same time on the following day. Both assessments were administered under standard gymnasium conditions (room temperature, 21.0°C ± 1.5°C; humidity, 40.5% ± 5.0%; barometric pressure, 755.5 ± 3.5 mm Hg) after a minimum period of 3 h postprandial feeding.

Psychological Profile

Psychological profile was assessed by both a Profile of Moods States (POMS) (²⁷) and semistructured interviews. The POMS vigor subscale was subtracted from the other combined subscales to generate a total mood disturbance (TMD) score. Semistructured interviews and subsequent questions were generated, conducted, and analyzed in the same manner as previous investigations in combat sport athletes (²⁸) to reflect the athlete’s perceptions, thoughts, attitudes, emotions, and behaviors throughout each time phase.

Overview of Nutritional and Training Intervention

Phase 1: −8 WK to −1 WK

All meals were provided for the athlete in preprepared packages with known energy and macronutrient contents equivalent to RMR_meas (1700 kcal·d⁻¹; see Table 1) and consisting of 3.4 g·kg FFM⁻¹ carbohydrate (CHO) (748 kcal·d⁻¹), 2.3 g·kg FFM⁻¹ protein (506 kcal·d⁻¹), and 0.9 g·kg FFM⁻¹ fat (446 kcal·d⁻¹). Subsequent feedings followed a typical daily distribution of four meals periodized in line with daily training sessions (see Table 2). The athlete’s weekly training schedule consisted of three aerobic continuous running (CR), two high-intensity interval training (HIIT), two resistance training (RT), three technical/tactical, and one sparring-based sessions totaling 12–15 h·wk⁻¹. Aerobic CR was conducted after a 12-h fasting period, for 45–60 min at a running speed equating to FAT_peak. HIIT was completed on a motorized treadmill in two differing activity–recovery ratios consisting of 10 × 1:1 min at 120% V˙O_2peak and 6 × 3:1 min at 90% of V˙O_2peak, where the recovery period in both protocols was 1 min of walking. RT was structured into whole body bi/unilateral general strength/speed exercises, concurrently performed in superset, with speed/strength, ballistic, and reactive strength modalities, where volume loads and intensities were established from MDS 1RM testing.

TABLE 1 - Measurements of EI, expenditure, and 24-h WDEB/availability throughout the intervention and postcompetitive recovery phases.

TIME Phase/Measurement	Monday	Tuesday	Wednesday	Thursday	Friday	Saturday	Sunday	Time Phase Combined Average
Phase 1: −8 WK to −4 WK
EI (kcal·d−1)	1700 ± 0	1700 ± 0	1700 ± 0	1700 ± 0	1700 ± 0	1700 ± 0	1700 ± 0	1700 ± 0
DIT (kcal·d−1)	167 ± 0	170 ± 0	171 ± 0	170 ± 0	169 ± 0	171 ± 0	170 ± 0	170 ± 2
NEAT (kcal·d−1)	1794 ± 90	1270 ± 64	1235 ± 62	986 ± 49	682 ± 34	911 ± 46	1073 ± 54	1136 ± 352
EEE (kcal·d−1)	873 ± 47	584 ± 31	409 ± 22	617 ± 34	1209 ± 66	0 ± 0	376 ± 20	559 ± 370
EPOC (kcal·d−1)	70 ± 4	47 ± 2	33 ± 2	49 ± 3	97 ± 5	0 ± 0	30 ± 1	45 ± 30
24-h WDEB (kcal·d−1)	−2843 ± 94	−2034 ± 66	−1824 ± 63	−1782 ± 54	−2069 ± 53	−1091 ± 46	−1077 ± 55	−1919 ± 541
EA (kcal·kg FFM−1·d−1)	15 ± 1	20 ± 1	24 ± 0	20 ± 1	9 ± 1	31 ± 0	24 ± 0	20 ± 7
Phase 1: –4 WK to −1 WK
EI (kcal·d−1)	1700 ± 0	1700 ± 0	1700 ± 0	1700 ± 0	1700 ± 0	1700 ± 0	1700 ± 0	1700 ± 0
DIT (kcal·d−1)	167 ± 0	170 ± 0	171 ± 0	170 ± 0	169 ± 0	171 ± 0	170 ± 0	170 ± 2
NEAT (kcal·d−1)	1503 ± 75	1176 ± 59	1173 ± 59	1436 ± 72	686 ± 34	1523 ± 76	944 ± 47	1207 ± 313
EEE (kcal·d−1)	968 ± 52	527 ± 29	340 ± 18	616 ± 34	1333 ± 72	0 ± 0	430 ± 23	579 ± 418
EPOC (kcal·d−1)	77 ± 4	43 ± 2	27 ± 1	49 ± 3	107 ± 6	0 ± 0	35 ± 2	46 ± 34
24-h WDEB (kcal·d−1)	−2611 ± 82	−1846 ± 61	−1657 ± 60	−2194 ± 75	−2162 ± 57	−1667 ± 76	−1516 ± 49	−1974 ± 401
EA (kcal·kg FFM·d−1)	13 ± 1	22 ± 1	25 ± 0	20 ± 1	7 ± 1	31 ± 0	23 ± 0	20 ± 8
Phase 2: –1 WK to COMP						OCWI	COMP	a
EI (kcal·d−1)	915	915	863	863	300	3490	5185	794 ± 538*
DIT (kcal·d−1)	92	92	421	86	30	330	464	79 ± 39*
NEAT (kcal·d−1)	632	1097	903	1122	929	937	507	855 ± 289
EEE (kcal·d−1)	1120	409	421	467	474	0	337	423 ± 407
EPOC (kcal·d−1)	98	33	34	37	38	0	27	34 ± 33
24-h WDEB (kcal·d−1)	−2729	−2280	−2108	−2340	−2622	809	2394	−2165 ± 476
EA (kcal·kg FFM−1·d−1)	−4	9	8	7	−3	64	89	3 ± 7*
Phase 3: +1 D to +1 WK								b
EI (kcal·d−1)	3877	3203	4637	2978	3717	3902	5490	5211 ± 2672**
DIT (kcal·d−1)	395	352	432	332	325	451	885	567 ± 398**
NEAT (kcal·d−1)	1042	851	390	723	599	494	136	767 ± 260
EEE (kcal·d−1)	0	0	0	0	0	0	0	48 ± 127**
EPOC (kcal·d−1)	0	0	0	0	0	0	0	4 ± 10**
24-h WDEB (kcal·d−1)	879	332	2038	39	801	855	2369	1387 ± 1180**
EA (kcal·kg FFM−1·d−1)	69	57	83	53	66	70	98	73 ± 17**

Daily data for combined time phases are presented as mean ± SD with singular values representing individual daily time points within specified time phases.

*Significantly different to all other equitable measurements at phases 1 and 3 (P < 0.05).

**Significantly different to all other equitable measurements at phases 1 and 2 (P < 0.05).

^aCalculated with values before OCWI.

^bCalculated with values post-OCWI.

OCWI, official competition weigh-in day; COMP, competition day.

TABLE 2 - WDEB calculations for training day 5 during the phase 1 −8 WK period of the intervention.

	Intake	Expenditure						Hourly Calculations
Time	EI	DIT	EEE	EPOC	NEAT	SMR	RMR	TEE hr to hr	EB hr by hr	WDEB
0000–0100	0	2	0	0	0	71	0	74	−74	−8465
0100–0200	0	0	0	0	0	71	0	145	−71	−8536
0200–0300	0	0	0	0	0	71	0	216	−71	−8607
0300–0400	0	0	0	0	0	71	0	287	−71	−8679
0400–0500	0	0	0	0	0	71	0	359	−71	−8750
0500–0600	0	0	0	0	0	71	0	430	−71	−8821
0600–0700	0	0	0	0	0	71	0	501	−71	−8892
0700–0800	0	0	0	0	46	0	71	618	−117	−9009
0800–0900	0	0	0	0	46	0	71	735	−117	−9126
0900–1000	0	0	0	0	46	0	71	852	−117	−9243
1000–1100	0	0	246 a	0	46	0	71	1215	−363	−9606
1100–1200	379	11	0	12	46	0	71	1355	238	−9368
1200–1300	0	11	0	7	46	0	71	1490	−135	−9502
1300–1400	0	7	187 b	0	46	0	71	1801	−311	−9813
1400–1500	595	22	0	9	46	0	71	1098	446	−9367
1500–1600	0	19	0	6	46	0	71	2091	−142	−9509
1600–1700	0	13	0	0	46	0	71	2221	−130	−9638
1700–1800	595	25	0	0	46	0	71	873	453	−9185
1800–1900	0	21	0	0	46	0	71	2501	−138	−9323
1900–2000	0	14	364 c	0	46	0	71	2995	−495	−9818
2000–2100	0	7	364 c	18	46	0	71	3502	−506	−10,324
2100–2200	131	8	0	29	46	0	71	3656	−23	−10,347
2200–2300	0	6	0	11	0	71	0	3744	−88	−10,435
2300–0000	0	2	0	0	0	71	0	3818	−74	−10,509
24-h Total	1700	169	1162	93	684	641	1069	3818	−2118	−10,509

Measures have been rounded to whole numbers owing to 24-h totals which may not equate.

^aFasted aerobic CR.

^bRT.

^cSport-specific training.

SMR, sleeping metabolic rate; TEE hr to hr, total energy expenditure hour to hour; EB hr by hr, energy balance hour by hour.

Phase 2: −1 WK to WI

Daily EI was reduced exponentially until WI (see Table 1), which consisted of low fiber, residue, and sodium-based foods. At −5 and −4 D, macronutrient intake equated to 0.5 g·kg FFM⁻¹ CHO (110 kcal·d⁻¹), 1.8 g·kg FFM⁻¹ protein (385 kcal·d⁻¹), and 0.9 g·kg FFM⁻¹ fat (420 kcal·d⁻¹), and at −3 and −2 D, 0.3 g·kg FFM⁻¹ CHO (67 kcal·d⁻¹), 1.8 g·kg FFM⁻¹ protein (400 kcal·d⁻¹), and 0.8 g·kg FFM⁻¹ fat (396 kcal·d⁻¹), respectively. Finally, at −1 D, the athlete ate only one meal containing 1.4 g·kg FFM⁻¹ protein (300 kcal·d⁻¹). All meal timings corresponded to a periodized taper of training volume, consisting of aerobic CR and sport-specific technical/tactical noncontact sessions only. From 1200 h on −1 D until WI at 13.00 h, the athlete refrained from ingesting any food or fluids. During this period, the athlete also engaged in self-directed active and passive dehydration techniques, inclusive of a 1-h sauna session at 18.00 h and a CR at 20.00 h on −1 D, then a final 1-h sauna session at 09.00 h on WI.

Phase 3: WI to +1 WK

In the postcompetitive period, the athlete consumed food and fluids ad libitum and reported these via the remote food photography method (²⁹). These data were assessed using dietary analysis software (Nutritics V5; Nutritics Ltd., Swords, Co. Dublin, Ireland) as previously described (³⁰) to establish respective energy and macronutrient values and with systematic bias of measurements via independent t-tests highlighting no significant differences (P < 0.05). This resulted in varying daily EI intakes (see Table 1) with macronutrient contents equating to averages of 7.9 g·kg FFM⁻¹ CHO, 2.8 g·kg FFM⁻¹ protein, and 3.1 g·kg FFM⁻¹ fat, respectively. Other than the competition day, exercise was completely ceased during this time phase. No dietary supplements were implemented or allowed throughout any time phase, to limit potential ergogenic effects on subsequent performance-based testing. Fluid consumption throughout all time phases equated to an average of 2 L·d⁻¹ and was reduced to 500 mL until 1200 h on −1 D.

Assessment of Daily Well-being, Training Load, EA, Within-Day Energy Balance, and Weekly Accumulated Energy Deficit

The athlete was requested to report perception of wellness via a daily well-being score (³¹). Training load was assessed internally via the session RPE method (³²) and externally via HR chest strap (Polar V800; Polar Electro UK Ltd., Warwick, UK), with specific profiles and zones created for each type of training modality, based on percentages of V˙O_2peak. The HR wristwatch triaxial accelerometer unit also acted as an activity monitor and was worn continuously for estimations of non–exercise activity thermogenesis (NEAT). Estimated EEE was assessed via an Actiheart combined HR and accelerometry actigraphy unit (CamNtech Ltd., Papworth, UK) as previously described (³³). Within-day energy balance (WDEB) was calculated to examine the total daily fluctuations in 24-h energy balance (EB), using the methodology of Torstveit and colleagues (²⁰), which includes additional estimations of diet-induced thermogenesis (DIT) and excess post oxygen consumption (EPOC), respectively (see Table 2). Each daily WDEB measurement was added to the subsequent day, to calculate an estimated weekly accumulated energy deficit (WAED) across all intervention and recovery periods (see Fig. 1A). Daily EA was also calculated as described by Loucks (³⁴), where measures of EI were subtracted from EEE values (EEE Actiheart − NEAT + RMR_meas/60 × training in minutes) and divided by FFM established by DXA (see Table 1).

FIGURE 1: Changes in estimated WAED and EI (A), BM (B), FM (C), FFM (D), BF% (E), and Σ_8SKf (F) measurements throughout the intervention and postcompetitive recovery phases.

Statistical Analysis

In Table 1, descriptive statistics are presented as mean ± SD, where appropriate. Time phase combined averages for EI, DIT, NEAT, EEE, EPOC, 24-h EB, and EA were assessed via a within-participant one-way ANOVA using SPSS 26 (PASW, Chicago, IL). Bonferroni post hoc analysis was used for pairwise comparisons, and statistical significance was set at an alpha of P < 0.05.

RESULTS

Overview of intervention and recovery periods on athlete well-being, training load, EA, WDEB, and WAED

Throughout phases 1 and 2 of the intervention period, the athlete completed all assigned sport-specific, aerobic CR, HIIT, and RT sessions to meet the assigned training load, and daily well-being score did not fall below a minimum threshold. Time phase assessments of EI, expenditure, balance, and availability are presented in Table 1, highlighting main effects between phases when comparing measurements of EI (P = 0.04), DIT (P = 0.02), EEE (P = 0.02), EPOC (P = 0.02), 24-h EB, and EA (P < 0.001). Low EA status was established throughout phase 1, with values ranging from 7 to 31 kcal·kg FFM⁻¹·d⁻¹ equating to an average of 20 kcal·kg FFM⁻¹·d⁻¹. During phase 2, low EA status was further evident with values ranging from −4 to 9 kcal·kg FFM⁻¹·d⁻¹ and considerably lower than all other periods (P = 0.03), due to reductions in EI (P = 0.03), which in turn was causative of reductions in DIT (P = 0.03). In phase 3, EA was increased substantially in comparison to all other time phases (P < 0.001) with daily values ranging between 53 and 98 kcal·kg FFM⁻¹·d⁻¹, accompanied by significant increases in measures of EI, DIT, and 24-h EB and decreases in EEE and EPOC (P < 0.001). Figure 1A highlights estimated WAED, demonstrating a net energy deficit of −105,757 kcal throughout phases 1 and 2, with weekly EI ranging from 11,900 to 3856 kcal·wk⁻¹ in parallel to mean total energy expenditures of 25,100 kcal·wk⁻¹, resulting in average deficits of −13,200 kcal·wk⁻¹. In phase 3, estimated WAED is only rescued to a −95,984-kcal deficit, despite a considerable increase in EI totaling 36,477 kcal·wk⁻¹ and after a cessation of all training activity.

Changes in anthropometric measurements

Time phase changes of BM, Σ_8SKf, FM, FFM, and BF% are shown in Figure 1B–F. The athlete recorded an official weight of 62.7 kg, successfully achieving the limit for the elected weight category. This represented an overall BM reduction of 9.8 kg (<13.5%), consisting of a loss of 4.9 kg (<6.8%) FM and 3.6 kg (<5.0%) FFM across the phase 1 and phase 2 intervention periods. In the phase 3 postcompetitive recovery period, the athlete increased BM by 8.3 kg (>13.2%), FM by 1.0 kg (>1.6%), and FFM by 7.0 kg (>11.2%). Σ_8SKf was reduced by 28.5 mm across phases 1 and 2, with a 10.4-mm increase throughout phase 3. Finally, at the cessation of phase 2, body mass index was reduced to 22.8 kg·m⁻², with an increase to 25.8 kg·m⁻² at the end of the phase 3 postcompetitive recovery period.

Assessment of low EA on markers of Male Athlete Triad and RED-S

Assessment of the athlete’s RMR is presented in Figure 2. During phases 1 and 2, there was a gradual reduction in RMR_meas values by −36 kcal·d⁻¹ at −4 WK, −72 kcal·d⁻¹ at −1 WK, and −149 kcal·d⁻¹ at −1 D, representing an overall reduction from baseline of −257 kcal·d⁻¹. This recovers within the phase 3 postcompetitive recovery period by an increase of 648 kcal·d⁻¹ at +1 WK. Adaptive thermogenesis occurred at a rate of −36 kcal·d⁻¹ at −4 WK, −99 kcal·d⁻¹ at −1 WK, and a larger decrease of −213 kcal·d⁻¹ at −1 D. In relation to RMR_ratio, most values remained within an acceptable range, with a gradual decrease across phases 1 and 2, followed by a substantial increase at +1 WK in phase 3. However, there was a marked reduction in RMR_ratio at −1 D of phase 2, indicating RMR suppression and potential energy deficiency.

FIGURE 2: Changes in RMR measurement, prediction, and ratio assessments throughout the intervention and postcompetitive recovery phases.

Blood clinical chemistry biomarkers and BMD/BMC measurements are presented in Table 3. Hypothalamic–pituitary–gonadal axis hormones remained relatively stable throughout phase 1, although markers were outside clinical reference ranges (testosterone, <5 nmol·L⁻¹; luteinizing hormone, <1.2 U·L⁻¹; follicle-stimulating hormone, <1.5 U·L⁻¹; sex hormone–binding globulin, >78 nmol·L⁻¹) in phase 2 at WI. However, these were all rescued within 48 h by −1 D of the phase 3 postcompetitive recovery period. Fasting insulin was consistent within phases 1 and 2, but it substantially increased above clinical reference ranges (>48 pmol·L⁻¹) throughout phase 3. Bone turnover markers procollagen type 1N-terminal propeptide and β-carboxy-terminal cross-linked telopeptide were both above the highest clinical reference ranges across all phases (procollagen type 1N-terminal propeptide, >80 μg·L⁻¹; β-carboxy-terminal cross-linked telopeptide, >0.6 μg·L⁻¹) but generating positive ratios (>1.0) at all time points. In addition, DXA assessment of total body (minus head) and lumbar spine BMD were also within acceptable reference z-scores, with no change across time phases as expected based on the time course of measurements. Predominantly all biomarkers of hydration, electrolyte, renal, liver, and blood lipids remained stable throughout the phase 1, despite elevations in albumin above clinical reference ranges (>50 g·L⁻¹) across all measurement points. Within phase 2, P_osm examined in parallel with sodium, urea, creatinine, and LDL was indicative of moderate hypohydration (>300 mOsm·kg H₂O⁻¹) and hypernatremia (sodium, >145 mmol·L⁻¹; urea, >7.8 mmol·L⁻¹; creatinine, >110 μmol·L⁻¹; LDL, >3.0 mmol·L⁻¹) at WI; however, this was rescued to normative values by phase 3 at +1 D. Finally, total cholesterol values were elevated above clinical reference ranges (>5.0 mmol·L⁻¹) in phases 2 and 3 at WI and +1 WK.

TABLE 3 - Changes in blood clinical chemistry and DXA BMD and BMC measurement throughout the intervention and postcompetitive recovery phases.

	Phase 1			Phase 2		Phase 3
	−8 WK	−4 WK	−1 WK	−1 D	WI	+1 D	+1 WK
Endocrine responses
Cortisol (nmol·L−1)	501	465	498	482	571	407	407
Testosterone (nmol·L−1)	21.5	18.7	11.2	9.4	4.0 ↓	9.7	19.8
IGF-1 (nmol·L−1)	32	30	25	22	21	21	30
Luteinizing hormone (U·L−1)	3.4	3.2	2.1	1.8	1.0 ↓	3.1	4.0
Follicle-stimulating hormone (U·L−1)	1.9	1.9	1.9	1.7	1.4 ↓	2.0	2.1
SHBG (nmol·L−1)	43	57	57	72	82 ↑	72	46
Insulin (pmol·L−1)	26	34	28	26	21	142 ↑	77 ↑
Bone turnover and DXA BMD/BMC
P1NP (μg·L−1)	112 ↑	159 ↑	131 ↑	124 ↑	112 ↑	132 ↑	139 ↑
β-Ctx (μg·L−1)	0.7 ↑	0.9 ↑	1.0 ↑	0.9 ↑	0.9 ↑	0.6 ↑	1.0 ↑
Total body (minus head) BMD/BMC (z-score/g·cm−2)	0.4 (1.123)	0.5 (1.135)	0.4 (1.130)	0.7 (1.155)	-	-	0.4 (1.122)
Lumbar spine BMD/BMC (z-score/g·cm−2)	0.8 (1.144)	0.8 (1.154)	1.0 (1.175)	1.0 (1.169)	-	-	0.9 (1.166)
Electrolyte, renal, and liver function
Posm (mOsm·kg H2O−1)	288	294	294	299	307 ↑	297	289
Sodium (mmol·L−1)	144	143	143	142	147 ↑	143	142
Urea (mmol·L−1)	4.2	5.8	5.6	6.6	8.3 ↑	4.8	4.2
Creatinine (μmol·L−1)	93	94	99	109	119 ↑	92	93
Albumin (g·L−1)	56 ↑	57 ↑	52 ↑	55 ↑	59 ↑	53 ↑	52 ↑
Globulin (g·L−1)	25	23	22	22	25	21	22
Total protein (g·L−1)	78	80	74	77	84 ↑	72	71
Lipid profiles
Total cholesterol (mmol·L−1)	3.6	3.8	4.3	4.6	5.2 ↑	3.9	5.1 ↑
HDL (mmol·L−1)	1.3	1.2	1.3	1.4	1.6	1.3	1.7
LDL (mmol·L−1)	2.1	2.3	2.7	2.9	3.3 ↑	2.0	2.9
Triglyceride (mmol·L−1)	0.5	0.7	0.6	0.6	0.6	1.5	1.5

BMC values are in parentheses.

↓, decrease outside normative clinical reference ranges; ↑, increase outside normative clinical reference ranges; IGF-1, insulin-like growth factor 1; SHBG, sex hormone–binding globulin; P1NP, procollagen type 1N-terminal propeptide; β-Ctx, β-carboxy-terminal cross-linked telopeptide; P_osm, plasma osmolality.

Cardiac assessments measured via ECG/echocardiography are presented in Figure 3. Despite an increased left ventricular end-diastolic volume response exhibited at −1 D, there were no major changes in either structure or function of the left (Fig. 3A) or right (Fig. 3B) ventricles across all phases. As highlighted in Figure 3C, both CO and HR reduced consistently across phases 1 and 2 with a large increase in both measures within 24 h from −1 D to WI, which plateaued by the end of the phase 3 postcompetitive recovery period at +1 WK.

FIGURE 3: Changes in left (A) and right (B) ventricular structure/function and CO/HR (C) throughout the intervention and postcompetitive recovery phases.

There were no major psychological fluctuations in POMS or TMD scores across the majority of all time phases as highlighted in Table 4. This is with the exception of WI, where reductions in vigor and increases in fatigue resulted in an elevated TMD, yet this remained well within normative values for athletic populations. In all semistructured interviews and despite relevant probing, the athlete made no comments in regard to any gastrointestinal distresses and reported no incidences of illness or injury. Excerpts ascertained from these interviews highlight throughout phase 1, the athlete displayed feelings of “fear” and “perceived” losing such a large volume of BM would negatively affect his health and performance. In phase 2, there were continued emotions of “anxiety” over his potential to make the required weight category, yet a “realization” and “confidence” that he will achieve his goal. Finally, post-WI, the athlete describes his “exhilaration” and sense of “accomplishment” in meeting the targeted weight category, reinforced by a renewed sense of “focus” on competitive performance.

TABLE 4 - Changes in profile of mood states and TMD scores throughout the intervention and postcompetitive recovery phases.

	Phase 1			Phase 2		Phase 3
	−8 WK	−4 WK	−1 WK	−1 D	WI	+1 D	+1 WK
Tension (AU)	5	7	9	5	8	13	1
Depression (AU)	3	6	8	4	4	2	0
Anger (AU)	3	6	9	10	9	7	1
Vigor (AU)	22	24	21	22	11	19	24
Fatigue (AU)	3	6	1	3	12	0	7
Confusion (AU)	6	6	6	5	6	3	1
TMD score (AU)	−2	7	12	5	28	6	−14

Physical performance assessments of both absolute and relative upper and lower MDS, MDP, and cardiorespiratory capacity are highlighted in Figure 4. As demonstrated in Figure 4A, across time phases, both upper and lower MDS increased relatively by 18%–19% and absolutely by 6%–9% (n.b., bench press was not completed during phase 3 at +1 WK due to the athlete fracturing his left hand in competition). Within phase 1 from −8 WK to −1 WK, MDP improved in both upper absolute and lower relative force/velocity and power curve profiles (see Fig. 4B and C). Figure 4D highlights that across phases, both relative and absolute V˙O_2peak values increased by 19% and 13% at −1 WK before competition, respectively. There was also an improvement in the athlete’s FAT_peak oxidation profile throughout the phase 1 intervention period from 0.62 g·min⁻¹ at 44% to 0.72 g·min⁻¹ at 60% V˙O_2peak. However, this is significantly reduced to 0.42 g·min⁻¹ at 30% V˙O_2peak within the end of the postcompetitive recovery phase 3 at +1 WK.

FIGURE 4: Changes in absolute and relative upper/lower MDS (A), upper (B), and lower (C) MDS and cardiorespiratory capacity (D) throughout the intervention and postcompetitive recovery phases.

DISCUSSION

The aim of this case report was to evaluate the effects of incorporating daily fluctuations in low EA on health and performance indices associated with Male Athlete Triad and RED-S. In studying a male combat sport athlete making weight for competition, we provide novel data by demonstrating that 7 wk of low EA (equating to a mean daily value of 20 kcal·kg FFM⁻¹·d⁻¹) permits a reduction of BM and FM without perturbations to physiological systems associated with Male Athlete Triad and RED-S. By contrast, a subsequent period of five consecutive days of EA <10 kcal·kg FFM⁻¹·d⁻¹ induced Male Athlete Triad and RED-S consequences, as evidenced by disruptions to hormones of the hypothalamic–pituitary–gonadal axis, RMR_meas, and RMR_ratio. Although such negative outcomes were quickly reversed during the rebound hyperphagic response that occurred in the 1–7 d postcompetition, this period of excessive EI also induced fasting hyperinsulinemia and hyperlipidemia, thus suggesting impaired substrate handling and insulin resistance.

During the 7 wk of phase 1, the athlete adhered to a daily EI that was equivalent to RMR and consumed a macronutrient intake representative of high protein (2.3 g·kg FFM⁻¹), low CHO (3.4 g·kg FFM⁻¹), and low fat (0.9 g·kg FFM⁻¹). However, given that absolute EEE fluctuated day by day during each weekly microcycle, this gave rise to a daily EA ranging from 7 to 31 kcal·kg FFM⁻¹·d⁻¹ and a mean EA of 20 kcal·kg FFM⁻¹·d⁻¹. Despite the classification of low EA status during this phase, it is noteworthy that the athlete presented with none of the classic consequences associated with the Male Athlete Triad or RED-S. Indeed, we observed no reductions in RMR, impairments to cardiac function, or clinically relevant changes in blood clinical chemistry. In agreement with previous case/cohort study accounts (^5,13) and randomized control trials (³⁵), our data also suggest that the combination of RT and daily protein intake equivalent to 2–3 × recommended daily allowance is sufficient to maintain (or increase) FFM. Such findings are likely underpinned by the observation that the combination of increased protein intake and RT can maintain high rates of muscle protein synthesis despite low EA (³⁶). In addition, changes in bone turnover markers were consistent with normative ranges occurring in young athletic males performing high-intensity exercise (³⁷), findings that also appear consistent with the observation that 5 d of EA equaling 15 kcal·kg FFM⁻¹·d⁻¹ did not affect bone resorption or formation in healthy young males (³⁸). In addition, it is noteworthy that the athlete also presented with normal BMD values where, in conjunction with markers of bone turnover, such data agree with previous observations from male amateur boxers and suggest that the physical loading associated with combat sport training may provide a sufficient osteogenic stimulus (³⁹).

When taken together, our data therefore suggest that the classification of low EA as <30 kcal·kg FFM⁻¹·d⁻¹, a value commonly cited for females (^40,41), may not be representative of a threshold to induce health and performance consequences associated with both the Male Athlete Triad and the RED-S models, a view recently supported by De Souza and colleagues (^7,9). Although we obviously cannot ascertain such a threshold within the present case report, it is also tempting to speculate that it is the daily fluctuations in EA as opposed to a consistent absolute daily EA (subsequently giving rise to a mean daily EA of 20 kcal·kg FFM⁻¹·d⁻¹), which may have preserved physiological function during this phase. Indeed, such a hypothesis is supported by the observation that impairments in the hypothalamic–pituitary–gonadal axis can be restored within days of increased EA (¹⁴).

During phase 2, the athlete underwent a tapering of EEE and consumed a reduced EI (1200–300 kcal·d⁻¹) such that absolute EA was consistently <10 kcal·kg FFM·d⁻¹ for five consecutive days. It is noteworthy that during this short time, the athlete subsequently presented with classic consequences associated with low EA that are considered indicative of Male Athlete Triad and RED-S, as evidenced by clinically relevant reductions to hormones of the hypothalamic–pituitary–gonadal axis, reduced RMR_meas (−257 kcal·d⁻¹), and RMR_ratio (<0.90) (⁸). The combination of limited EI and likely associated changes to muscle glycogen concentration and acute dehydration also presented as a reduction in FFM of approximately 3 kg when assessed via DXA. The acute dehydration period in the final 13 h before WI also increased plasma osmolality, sodium, urea, creatinine, and LDL. Although this magnitude of hypohydration and hypernatremia would not serve to cause acute kidney injury (⁵), these biomarkers are still markedly high considering the limited acute BM loss via dehydration (<3%). Additionally, in accordance with previous accounts of athletes engaging in low EA and acute dehydration, the final 24 h before weigh-in was associated with decreased vigor and increased tension and fatigue (^42,43). Nonetheless, although this increased both resting CO and HR, overall cardiac structure and function remain largely unchanged throughout all time phases, further indicating a minimal effect of acute short-term low EA on cardiovascular function.

Despite daily low EA and the estimated WAED incurred across the intervention period (i.e., >105,000 kcal), it should be noted that the athlete was able to complete all prescribed training sessions and there were no reported incidences of illness or injury. In addition, the athlete improved his MDS, MDP, V˙O_2peak, and rates of lipid oxidation, while also not reporting any impairments to mood profile. The qualitative responses of the athlete during all time phases consistently highlighted how the intervention was deemed a major improvement on previous practice, while also reporting feeling more prepared than he had ever been in his competitive career. This was further supported by the athlete achieving the gold medal at the championships, after successfully winning four contests and qualifying for his elected weight category to represent the national team at the 2018 European University Games.

Despite the perceived success of the intervention, it is noteworthy that in the 7-d postcompetitive period (phase 3), the athlete still remained in an estimated WAED of >95,000 kcal when compared with baseline, despite consuming an ad libitum EI >36,000 kcal·wk⁻¹ resulting in a BM gain of 8.3 kg. This level of EI is indicative of rebound hyperphagia (⁴⁴), and although not resulting in FM overshoot (⁴⁵), there were clear signs of impaired substrate handling. Indeed, this period of excessive EI induced fasting hyperinsulinemia and hyperlipidemia, thus suggestive of insulin resistance (⁴⁶). In addition, the athlete’s peak rate of fat oxidation during exercise decreased from 0.72 to 0.42 g·min⁻¹ and occurred at a lower relative training intensity (60% to 30% V˙O_2peak). Such periods of rebound hyperphagia are of particular concern, given that “weight cycling” athletes typically gain more BM upon retirement when compared with non–weight cycling athletes (^47,48).

Although this examination highlights novel data in relation to the effects of low EA on the health and performance-related consequences within the Male Athlete Triad and RED-S models, it should be noted that this is only indicative of a single participant case report and cannot be immediately extrapolated to wider populations. In addition, further studies examining this demographic need to focus on the effects of repeated exposure to these levels of EA, considering combat sport athletes consistently make weight numerous times per year across long spanning careers.

In summary, we provide novel data by demonstrating in a male combat sport athlete that 7 wk of day-to-day fluctuations in EA (equating to a mean value 20 kcal·kg FFM·d⁻¹) permits a reduction of BM and FM without perturbations to physiological systems associated with the Male Athlete Triad and RED-S. Importantly, the athlete was able to complete all prescribed training sessions during this time and improved his physical performance capacity without any impairment to mood profiles. By contrast, a subsequent period of five consecutive days of EA consistently <10 kcal·kg FFM·d⁻¹ and acute dehydration induced markers of Male Athlete Triad and RED-S, as evidenced by reductions in hormones of the hypothalamic–pituitary–gonadal axis and lowered RMR. Again, these data are only indicative of a single participant case report, and caution should be considered when extrapolating these conclusions to wider populations without the support of ongoing longitudinal and cohort-based investigations. In addition, further studies are now required using randomized control trials to ascertain the threshold and time course of EA that induces impairments in physiological function of male athletes. Finally, we encourage all athletes who engage in BM reduction to do so with the guidance of qualified sport dieticians/nutritionists, to reduce the potential for health and performance consequences of low EA across both acute and chronic timeframes.