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The role of age in the physiological adaptations and psychological responses in bikini-physique competitor contest preparation: a case series

Over the 16-week pre-contest preparation, as expected, both competitors lost ~ 4 kg of kg body weight, which was predominantly explained by a mean loss of ~ 3.7 kg of fat mass (FM) and a mean ~ 6% reduction in body fat (BF%). This suggests and assumes lean body mass (LBM) and skeletal muscle mass (SKMM) were comparatively well-conserved during contest preparation. The bikini competitor’s (BC) baseline value or starting point for both BF and BF% were both higher than the master’s bikini competitor (MPC) comparatively; however, the BC’s BF% change was much greater (~ 19%). This is concurrent with the BC’s greater reduction in ultrasound (US) assessed total subcutaneous adipose tissue (SAT) values with a − 34% reduction from baseline. Hulmi, et al. observed a ~ 7 kg fat mass loss from a higher fat mass baseline value (~ 14 kg) in their categorical division diverse female-physique population, which was more than double than seen in this bikini-physique categorical population. However, due to the diverse competitor division population assessed, it is difficult to determine the results for the bikini-physique competitors independently [12]. From our perspective, this may be explained in that these bikini-physique competitors maintained a higher BF% during their normal, non-contest preparation time periods (i.e.,offseason”) compared to other notable female-physique competitor divisions with different judging criteria. These factors may determine the female-physique competitor’s goal of required fat mass for both offseason and optimal competition performance.

Prior to competing, and at their lowest fat mass assessment, both BC and MBC maintained their BF% greater than 12% (~ 14%), which is the recommended threshold for female athletes in weight-sensitive competition and sports to reduce risks of health defects [50]. Low BF% mixed with high energy expenditure and very low kilocalorie intake would lead to an LEA status. This has shown to negatively affect menstrual function, and bone mineral density, which may have clinical manifestations including eating disorders, functional hypothalamic amenorrhea, and osteoporosis known as “The Female Athlete Triad” [47]. In assessing both competitor’s LBM and interrelated SKMM measures, both were well preserved throughout their contest preparation (<Δ − 0.5 and − 1.68% respectively). It is well known that resistance training (RT) is a potent stimulator of muscle protein synthesis and muscle hypertrophy and concurrent with an energy-restricted state reduce LBM losses [51, 52]. Additionally, preservation of LBM in athletes is further increased with the combination of RT and higher protein intake [53] where it is was recommended an intake of 2.3–3.1 g·kg− 1 of fat-free mass (FFM) per day for energy-restricted, resistance training athletes [54]. Both the BC and MBC competitors reported a very high protein dietary intake at 2.96 ± .07 and 2.72 ± .05 g·kg− 1·d− 1 respectively during their contest preparation.

Both the BC and MBC showed fairly stable MF-BIA measured TBW, ICF, and ECF measures during the contest preparation. The BC showed a higher value of ICF fluid, which is most likely explained by a higher kg LBM and it is well-identified that ~ 60% of human TBW is stored intracellularly and represents 70–75% of LBM. We did not observe any notable change in TBW, ICF, and ECF measures 5 d post-competition in either the BC or the MBC. However, we did not acquire any dietary recall data post-competition. If the BC and MBC indulged in high kilocalorie, post-competition hyperphagia [26], it did not impact immediate TBW measures.

Our exploratory US measures, while not validated, did see some changes from baseline worth evaluating and interpreting due to their relative importance to the population assessed. In analyzing the regional deltoid (DeltCSA) muscle group in both competitors we saw an average increase in CSA (Δ + 4.63%) and reduction in gluteus maximus muscle thickness (GMMT) (Δ − 19.5%) muscle group. The BC showed to have a smaller GMMT reduction (Δ-12.3%) compared to the MBC (Δ-26.7%). This dichotomy in muscular adaptations between the deltoid and the gluteus maximus is rather perplexing yet may be able to be partially explained by both exercise training and energy intake. Both competitors reported a similar mean % of lower body (LB) compared to upper body (UB) resistance training volume (BC: 52% UB; 48% LB and MBC: 49% UB; 51% LB). Overall, the BC reported having a much higher mean total RT volume (9194 ± 3499) compared to the MBC (5345 ± 1230 sets·reps). However, one session was not accurately reported and removed from the analysis. Unfortunately, we were unable to accurately relate the changes seen in DeltCSA and GMMT to the weekly volume of specific muscle group RT due to the inherent variation in both the BC’s and MBC’s self-reported training regimen (i.e., not all training days and muscle groups were reported prior to the session). Interestingly, both the BC and MBC competitors self-reported using the Stairmill/Stairmaster as their primary mode of AT during their contest preparation. Both competitors reported an aerobic exercise frequency of ~ 6 d·week− 1 and over 4 d prior to their assessment an average of 198.9 ± 31.8 (95% CI:125.5–272.3) and 105.6 ± 23.9 (95% CI:48.99–162.3) min respectively where BC had a higher volume of AT. The selection of the Stairmill/Stairmaster as the primary choice mode of AT may have increased the overall work volume for the gluteus maximus muscle group. The gluteus maximus (GMax) is the largest muscle of the hip accounting for 16% of the total CSA in the region. This muscle group is often used to accelerate the body upward and forward from a position of hip flexion ranging from 45° to 60° (e.g., pushing off into a sprint, arising from a deep squat, or climbing a very steep hill). It has been shown that the step-up exercise had the highest GMax myoelectrical activity (169.22 ± 101.47% MVIC) in comparison to other known hip exercises [55]. Although speculative, GMMT reduction or atrophy may likely be more related to local glycogen and fluid loss than muscle protein loss due to restricted carbohydrate (CHO) intakes (BC: 3.64 ± .21 and MBC: 1.35 ± .15 g·kg− 1·d− 1), RT volume, and the selection of the Stairmaster/Stairmill as primary AT exercise of choice. To support fluid loss as a potential factor and a plausible explanation, in Fig. 7 we compared monthly Δ change with dual X-ray absorptiometry (iDXA) LBM (g), FM (kg) changes, and bioimpedance analysis (MF-BIA) configured total body water (TBW), extracellular fluid (ECF), and intracellular fluid (ICF) compartment changes (mL) over the 16-week pre-contest preparation period. Relationships between both LBM and TBW (r = .64; r [2] = .41; p = .04), and ECF (r = .72; r 2 = .52; p = .01) were found. No relationships were found between LBM and ICF changes, and no relationship was found between FM and TBW changes. Moreover, both BC and MBC showed an average ECF fluid loss over the 16 weeks. It has been shown that short-term hydration and muscle glycogen status may influence DXA-LBM measures [56,57,58]. Due to the inability of DXA to differentiate between ICF and ECF compartments, it is feasible that the GMMT reduction may be potentially explained by local glycogen and fluid loss from concurrent LB exercise training volume, selected AT mode of exercise, and lower CHO intake.

In the exploration of utilizing the US to assess SAT measures and changes compared to iDXA, we found that time-course changes in the total of 7-site SAT measures correlated well with iDXA (r = .81; r2 = .66; p = .001) FM measures. Additionally, when estimating BF% using Jackson and Pollock [31] 7-site equation, we found US acquired SAT measures correlated well with iDXA configured BF% (r = .78; r2 = .60; p = .002). The US method has been previously utilized for SAT measures by Trexler, et al. that assessed physique athletes utilizing an automated program that estimated BF% [5]. However, we found no relationship between iDXA derived kg FM and US-SAT mm Δ changes. Utilizing the B-mode US as a modality to investigate SAT changes may have some practical use for individuals that do not have access to other expensive compositional measures to assess BF%.

No visual differences were observed between the BC and MBC total body water changes throughout the 20-week observational period. The MBC’s TBW saw a very slight reduction (− 1.3% Δ) compared to baseline values when comparing baseline to week 16. Additionally, we sought to assess both the BC’s and MBC’s TBW changes 5 d post-competition upon their return to the laboratory. Long periods of low energy status coupled with repetitive dietary choices and increased hunger may lead to immediate post-competition hyperphagia or binge eating [14] with an acute response similar to what may be seen with carbohydrate loading schemes used by endurance athletes after a glycogen depletion phase. Typically, glycogen is stored in a 1:3–4 ratio with water [59], which may lead to changes seen in weight gain and fluid perturbations post-competition. Both the BC and MBC saw no meaningful increases of either weight or TBW alterations 5-d post-competition.

In our observation of BMD, we did not expect to see any notable changes (~ ≤1% Δ change) in bone mineral density (BMD) or bone mineral content (BMC) over the 16-week contest preparation period due to the incremental effect of exercise on BMD to be very slow (6–12 mo) [60]. It should be noted, while no meaningful BMD changes were observed, both BC and MBC maintained > 100% of their age-related Z-score with lower observed E2 range levels. Further investigations should isolate the impact of resistance training-induced mechanotransductive stress compared to LEA-induced inhibition on reproductive hormone concentration and their integrated longitudinal effect on BMD in females.

During the 16-week contest preparation, both the BC and MBC maintained a mean categorical “significant dehydrated” state [37] (Fig. 8: BC: 1.021 ± .001 g·mL− 1 and MBC: 1.025 ± .001 g·mL− 1) where MBC averaged to be slightly more dehydrated than BC. However, from a practical aspect, it is unknown how meaningful this slight difference may be. It should be noted that each competitor was asked to visit the laboratory after an 8 h fast and prior to ingesting any food or drink. This USG assessment may not be indicative of their behaviors throughout the rest of the day and between visits. It is interesting after week 12, the BC’s hydration status moved below the 1.020 g·mL− 1, which is a status of euhydration [61]. It is unknown if the nearing competition influenced BC’s fluid intake and therefore hydration status. To our knowledge, we have not observed any previous literature examining the hydration status of competitors during their competition week. During this time, there may be manipulation of fluid consumption by restricting water intake [62] and/or pharmacologically induced fluid excretion through the use of diuretics [63] to reduce fluid content that may influence their ability to present muscular detail to the judging panel. Notably, due to the judging criteria for bikini-physique competitions, these water manipulating procedures may not be as aggressively used due to less focus on muscularity and conditioning. During competition week (D1-D5), comparatively, both the BC and MBC maintained euhydrated status during their competition (Fig. 8: D3, BC: 1.015 g·mL− 1; MBC 1.018 g·mL− 1 respectively). After the competition, the BC maintained a euhydrated status while the MBC’s values elevated closer to the average. This post-competition contrast in hydration status may be explained in that the BC chose not to compete in another competition and progress to an “off-season” status while the MBC elected to continue contest preparation to compete at another competition again a few weeks later.

During the competition, preparation saw a slight reduction in resting metabolic rate (RMR) at the 4-week time point for the BC. This may be explained by a self-reported reduction in kilocalorie intake and changes in body composition. Overall, during the contest preparation, RMR was fairly stable even with the observed body weight reduction where both BC and MBC showed mean positive Δ RMR change value. Our findings suggest that the majority of both BC’s and MBC’s kg weight loss was attributed to kg FM loss. We sought to analyze identify any relationship between change in Δ FM and Δ RMR. We found no correlation between contest preparation Δ FM change and Δ RMR change. However, it has been shown and readily accepted that the loss of both FM and LBM will impact RMR [64]. Additionally, in observing the active thyroid hormone triiodothyronine (T3) with its known relationship with metabolism, we observed no significant correlation with Δ T3 and Δ RMR change. In our results comparing baseline to week 16, we observed that both BC and MBC had a reduction in T3 hormone concentration of ~ 14 and 35% respectively. It is well established that thyroid hormone status regulates energy expenditure and therefore a factor in bodyweight changes [65]. Additionally, it has been shown that basal metabolic rate (BMR), which is ~ 10% lower than RMR is highly correlated with lean body mass. Being that LBM was mostly stable in both BC and MBC during contest preparation, this may suggest these competitor’s RMR was maintained by the factor of LBM more so than the observed T3 reduction. However, this is merely speculation being that none of these variables were assessed and isolated directly. Lastly, when comparing the BC and MBC competitors (Fig. 9) we found BC had a slightly higher mean RMR (+ 141 kcal·d− 1). However, when RMR values were normalized per kg LBM compared, a much smaller difference (~ 2.6 kcal·kgLBM− 1·d− 1) was found where BC was had a minimally higher RMR. This outcome was not entirely surprising in that there have been reports that a decline in RMR is associated with age. However, physically active older adults that maintain similar exercise training volume and energy intake maintain a similar RMR [66]. Moreover, it is known that LBM is highly correlated with RMR; however, visceral organ tissue is more metabolically active than is skeletal muscle tissue during resting conditions, which may explain some of the variances in RMR [67]. Therefore, in future studies assessing and comparing RMR in physique athletes, normalizing to LBM may reduce inherent variability. Lastly, it should be noted that the BC’s RMR increased post-competition at 20-week, after self-reporting following a “reverse dieting” protocol, a slight increase in FM (~ 1.1 kg) and reducing exercise training frequency and volume. The MBC continued a contest preparation regimen for another competition.

Our goal in observing endocrine responses in these bikini-physique competitors was to determine if age may have played a role in the responses to a restricted energy intake and increased energy expenditure. In our observation, estradiol (E2) and luteinizing hormone (LH) remained fairly stable for BC during contest preparation, with little variation in concentration from baseline to week 12. Both E2 and LH baseline values were near the lower end of both normal ranges. After the 12th week of the BC’s contest preparation, we observed a − 35% reduction of E2 at week 16, prior to competition. This concentration level fell below (~ 6 pg·mL− 1) what is considered the normal range relative to both follicular, mid-cycle, and luteal phases (10–300 pg·mL− 1). However, the BC’s mean E2 concentration over the 16-week contest preparation was 9.98 ± 1.73 pg·mL− 1 (95% CI: 5.43–14.35 pg·mL− 1). The mean average value falls within the range normally found in postmenopausal females (< 10 pg·mL− 1). Observing the BC’s LH time course, while relatively stable (3.66 ± .23 IU·L− 1; 95% CI: 3.00–4.31 IU·L− 1), LH concentration also reduced by ~ 13% at week 16 prior to the competition.

Comparatively, the MBC’s assessed E2 concentrations were more variable during the 16-week contest preparation. With the respect to the MBC’s age status of 44 y during this case series, which is close to the age of 45 y that has been shown in cross-sectional studies when endocrine changes and the onset of the perimenopause begin [68]. The MBC’s E2 concentrations reduced 24% from baseline values to week 16, prior to the competition. The mean average concentration during the 16-week pre-contest preparation was slightly less (9.31 ± 1.83 pg·mL− 1 (95% CI: 4.58–14.04 pg·mL− 1) than compared BC, yet also was observed below the normal concentration value found in postmenopausal women (< 10 pg·mL− 1).

The MBC’s LH time course concentration values seemed fairly stable until week 12 where there was a decline. There was an observed 14% reduction in LH when comparing baseline (95.9 IU·L− 1) and week 16 values (72.02 IU·L− 1). Interestingly, the MBC’s mean LH values over the 16-week pre-contest preparation were much higher than the BC (88.3 ± 13.4 vs 3.66 ± .23) IU·L− 1 respectively). This may be expected when taking into consideration that in early perimenopause, minor elevations in LH become evident [69].

In a seminal article by Loucks, et al. the “energy availability hypothesis” explained that LEA from low energy intake and high energy expenditure may inhibit gonadotropin-releasing hormone (GnRH) [70], which is derived from GnRH nerves located in the hypothalamic-pituitary-gonadal axis (HPTA) that is a pulse generator that controls the pulsatile secretion of the gonadotropic hormone LH, which is critical for reproduction [71]. Based on the BC’s dietary recall, the average energy intake over the 16-week pre-contest preparation was 43.2 ± 3.2 g·kgLBM− 1·d− 1. This value meets the recommended energy intake range requirement shown to maintain LH pulsatility [17]. However, due to the inability to accurately capture and quantify energy expenditure during this case series and then subtracting that value from energy intake, it is feasible to suggest that the actual energy availability may be lower than the estimated energy intake. In comparison, the MBC’s mean average, self-recalled dietary intake was 28.1 ± 1.1 g·kgLBM− 1·d− 1, which is below the recommended range to maintain LH pulsatility. Additionally, the self-reported value does not take into consideration energy expenditure from exercise training. This leads to an assumption that the energy availability may be lower for the MBC also. In contrast to Louck’s theory that suggests that LEA inhibits LH pulsatility [70], the higher LH concentrations observed during the MBC’s contest preparation may suggest that perimenopausal-induced LH increases may supersede LEA status inhibition of LH pulsatility. Furthermore, it should be noted that the majority of the work assessing LEA on female reproductive systems, has been investigated in younger, female athletes (< 29 y). We feel this is a fairly novel finding that requires much more investigation to determine how LEA may impact the reproductive system and metabolism in female athletes near perimenopause status.

Additional to assessing endocrine hormones related to reproduction and metabolism, we also investigated the impact of contest preparation on leptin and ghrelin. Leptin has been reported to influence various biological mechanisms such as initiating reproductive hormones, menstruation, regulatory centers in the brain to inhibit food intake and to regulate body weight and energy homeostasis [72]. Leptin is primarily synthesized and secreted from adipocytes in white adipose tissue and is normally found in higher blood concentrations in persons with higher BMI and BF%. Additionally, factors such as hyperglycemia and hyperinsulinemia also facilitate leptin secretion. However, in contrast, factors that are related to inhibiting leptin release are increasing age (≥40 y) [72]. In our investigation, we found that the BC’s leptin concentrations reduced 4% from baseline values at the 16-week time point. The BC’s mean average leptin concentration during pre-contest preparation fell slightly below the normal range (4.1–25.0 ng·mL− 1) in respect to BMI classification (3.6 ± .17 ng·mL− 1; 95% CI: 3.13–4.09 ng·mL− 1). The BC’s baseline leptin level was near the lower range normally found; however, this may be explained by a lower BF% compared to non-athlete females. The MBC’s mean average leptin levels were also within the normal range relative to BMI (22.8 ± .98 ng·mL− 1; 95% CI: 22.81–28.28 ng·mL− 1) yet were on the higher end of the normal scale compared to the BC. The MBC’s leptin levels time course was relatively stable during pre-contest preparation. Comparing baseline to the 16-week time period, there was a small ~ 1% increase found. This outcome was very intriguing and similar to the BC, the MBC also lost BF% from baseline to 16-weeks, yet this loss of fat mass did not seem to dictate leptin concentrations. This outcome is in contrast to Longstrom, et al. who observed leptin concentrations that were responsive to fat mass changes. However, it should be noted that the female-physique competitors observed in this study were ~ 29 y [8]. It may be plausible that there is a link between the elevated leptin and LH concentrations we observed in the MBC. It has been investigated in previous research that increased leptin appears to drive the reproductive system through both the HPTA and GnRH-stimulated LH secretion. Therefore, the increase seen in both leptin and LH in the MBC may be interrelated. Leptin directly stimulates ovarian steroidogenesis [73], yet, the E2 concentrations seemed to be less affected compared to LH found in the MBC. In our observation, it appears there may be some contrasting hormonal interrelationships between fat mass loss, leptin, LH, and E2 in our observations of the MBC compared to previous investigations that are typically seen in younger, female athletes.

Concurrent with assessing leptin responses in both BC and MBC, we sought to observe any differences in the hormone ghrelin, which is an orexigenic gut peptide. The fasted elevation of ghrelin levels and its decline after food ingestion led to its relevance as a ‘hunger’ hormone responsible for meal initiation, which is involved in the short-term regulation of food intake and long-term regulation of body weight through decreasing fat utilization [74]. Ghrelin has an impact on numerous physiological functions, although our focus was to observe any interrelationships with food intake and energy metabolism. In our observation of the BC’s ghrelin response was fairly stable throughout the 16-week pre-contest preparation. There was a notable − 36% drop in the BC’s ghrelin measure at week 4. This may be explained by the ~ 59% increase (kcal·kgLBM− 1·d− 1) that was self-reported from baseline to week 4 due to the ghrelin secretion being regulated by nutritional status. Interestingly, the BC’s mean ghrelin hormone concentration levels remained higher than the MBC throughout the 16-week pre-contest preparation (BC: 91.6 ± 8.1 vs MBC: 40.0 ± 5.7 pg·mL− 1; p = .0008) concurrent with a higher mean kcal·kgLBM− 1·d− 1 than the MBC. The MBC’s ghrelin level increased from ~ 70% from week 4 to week 8. However, there were no changes in self-reported dietary intake (kcal·kgLBM− 1·d− 1). Age is a factor that influences ghrelin secretion, which may assist in explaining the differences seen. However, the variations at certain time points may have other confounding factors influencing ghrelin concentration outside the parameters of our study. Our ghrelin findings and interpretations should be considered with much caution. It should be noted that the concentrations found in these bikini-physique competitors that were assessed using ELISA analysis were much lower than previous work assessing total ghrelin (both active acyl-ghrelin and inactive des-acyl-ghrelin) hormone with similar ELISA methodology (baseline ~ 500 pg·mL− 1) [75] and differing radioimmunoassay (~ 1625 pg·mL− 1) [76] protocol in healthy, normal, and similar BMI values as our bikini-physique competitors. Additionally, another factor that may explain such low values we observed is the half-life of acyl-ghrelin in human plasma without a stabilizer or deacylation inhibitor. Per our methodology, we used K2 EDTA vacutainer tubes for blood collection and stored plasma samples in a − 80 °C environment. However, previous investigations showed that fasting levels of plasma-derived-acyl-ghrelin collected in K2 EDTA vacutainers decreased approximately five-fold from prior storage measurements [77]. Future research that would like to investigate the gut-derived hunger’ hormone ghrelin in the blood may add this protocol to standard manufacturer ELISA methodology. To maintain sample integrity, the vacutainers may be treated with 4-(2-Aminoethyl) benzenesulfonyl fluoride hydrochloride (AEBSF) to reduce the degradation of ghrelin [77] to improve the accuracy of results.

In our psychometric findings, we observed that the MBC showed to have a higher mean average score of perceived stress (PSS) and a lower mean average score in the body image satisfactory (BISS) when compared to the BC. With notable environmental (e.g., lifestyle, competition experience) and inherent psychological factors that could influence these measures, it is unknown if age has may have impacted these responses. The BAS-2 assessment pre- and post-contest preparation were stable for BC. In comparison, the MBC’s response declined from baseline to post-contest preparation. This difference found may be partially explained in that the MBC continued with contest preparation for another competition while the BC elected to progress into an “off-season” status. The eating attitude analysis (EAT-26) showed both BC and MBC increase post-competition when compared to baseline. This difference may be partially explained and influenced by post-competition hyperphagia. Lastly, the measures of social anxiety both increased from baseline to post-contest in the BC and MBC. The anxiety related to contest performance may play a role in this assessment.

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