Changes in hormonal profiles during competition preparation in physique athletes

This is a self-archived version of an original article. This version may differ from the original in pagination and typographic details. Author(s): Title: Year: Version: Copyright: Rights: Rights url: Please cite the original version: CC BY 4.0 https://creativecommons.org/licenses/by/4.0/ Changes in hormonal profiles during competition preparation in physique athletes © The Author(s) 2024 Published version Isola, Ville; Hulmi, Juha J.; Mbay, Theo; Kyröläinen, Heikki; Häkkinen, Keijo; Ahola, Vilho; Helms, Eric R.; Ahtiainen, Juha P. Isola, V., Hulmi, J. J., Mbay, T., Kyröläinen, H., Häkkinen, K., Ahola, V., Helms, E. R., & Ahtiainen, J. P. (2024). Changes in hormonal profiles during competition preparation in physique athletes. European Journal of Applied Physiology, Early online. https://doi.org/10.1007/s00421-02405606-z 2024 Vol.:(0123456789) European Journal of Applied Physiology https://doi.org/10.1007/s00421-024-05606-z ORIGINAL ARTICLE Changes inhormonal profiles duringcompetition preparation inphysique athletes VilleIsola1 · JuhaJ.Hulmi1· TheoMbay1,2· HeikkiKyröläinen1· KeijoHäkkinen1· VilhoAhola3· EricR.Helms4,5· JuhaP.Ahtiainen1 Received: 4 July 2024 / Accepted: 30 August 2024 © The Author(s) 2024 Abstract Purpose Physique athletes engage in rigorous competition preparation involving intense energy restriction and physical training to enhance muscle definition. This study investigates hormonal changes and their physiological and performance impacts during such preparation. Methods Participants included female (10 competing (COMP) and 10 non-dieting controls (CTRL)) and male (13 COMP and 10 CTRL) physique athletes. COMP participants were tested 23weeks before (PRE), one week before (MID), and 23weeks after the competition (POST). Non-dieting CTRL participants were tested at similar intervals. Measurements included body composition (DXA), muscle cross-sectional area (ultrasound), energy availability (EA) derived by subtracting exercise energy expenditure (EEE) from energy intake (EI) and dividing by fat-free mass (FFM), muscle strength, and various serum hormone concentrations (ACTH, cortisol, estradiol, FSH, IGF-1, IGFBP-3, insulin, and free and total testosterone and SHBG). Results During the diet, EA (p < 0.001), IGF-1 (p < 0.001), IGFBP-3 (p < 0.01), and absolute muscle strength (p < 0.01– 0.001) decreased significantly in both sexes in COMP. Decreases in IGF-1 were also associated with higher loss in FFM. In males, testosterone (p < 0.01) and free testosterone (p < 0.05) decreased, while SHBG (p < 0.001) and cortisol (p < 0.05) increased. Insulin decreased significantly only in males (p < 0.001). Mood disturbances, particularly increased fatigue in males (p < 0.05), highlighted the psychological strain of competition preparation. All these changes were restored by increased EA during the post-competition recovery period. Conclusion Significant reductions in IGF-1 and IGFBP-3 during competition preparation may serve as biomarkers for monitoring physiological stress. This study offers valuable insights into hormonal changes, muscle strength, and mood state during energy-restricted intense training. Keywords Energy availability· IGF-1· Weight loss· Bodybuilding· POMS· REDs Abbreviations ACTH Adrenocorticotropic hormone ANOVA Analysis of variance BM Body mass BMD Bone mineral density COMP Competing group COR Cortisol COVID-19 Coronavirus disease 2019 CSA Cross-sectional area CTRL Control group CV Coefficient of variation DXA Dual-energy X-ray absorptiometry EA Energy availability EEE Exercise energy expenditure EI Energy intake ELISA Enzyme-linked immunosorbent assay Communicated by William J. Kraemer. * Ville Isola [email protected] 1 Faculty ofSport andHealth Sciences, Neuromuscular Research Center, University ofJyväskylä, P.O. Box35, 40014Jyväskylä, Finland 2 Institute ofPublic Health andClinical Nutrition, University ofEastern Finland, 70211Kuopio, Finland 3 Sports andExercise Medicine, Faculty ofMedicine, University ofHelsinki, Helsinki, Finland 4 Sports Performance Research Institute New Zealand (SPRINZ), Auckland University ofTechnology, Auckland, NewZealand 5 Department ofExercise Science andHealth Promotion, Muscle Physiology Research Laboratory, Florida Atlantic University, BocaRaton, FL33431, USA European Journal of Applied Physiology FFM Fat-free mass FSH Follicle-stimulating hormone FT Free testosterone HPA Hypothalamic–pituitary–adrenal HPG Hypothalamic–pituitary–gonadal IBM International business machines IGF-1 Insulin-like growth factor 1 IGFBP-3 Insulin-like growth factor binding protein 3 LEA Low energy availability LM Lean mass MET Metabolic equivalent POMS Profile of mood states PRE Pre-competition POST Post-competition RED-S Relative energy deficiency in sport SD Standard deviation SHBG Sex hormone-binding globulin SPSS Statistical package for the social sciences T Total testosterone VL Vastus lateralis WADA World anti-doping agency Introduction Physique athletes undergo rigorous competition preparation with intense energy restriction and physical training to enhance muscle definition. This preparatory phase is followed by a recovery period of 3–4months, during which body composition and endocrine changes are typically restored (Hulmi etal. 2017; Rossow etal. 2013). The offseason focuses on muscle growth through balanced nutrition and resistance training (Mursu etal. 2023). Hormone profiles in elite athletes differ from usual reference ranges, potentially reflecting baseline differences between athletes and the general population as well as the impact of athletic training on the endocrine systems (Healy etal. 2014). We previously reported that physique athletes experience significant hormonal changes during the competition preparation. These inevitable changes, likely caused by the combined factors of weight loss, training and dieting stress, and the sustained energy deficit, include reduced leptin and T3 levels and increased ghrelin concentrations, reflecting shifts in energy metabolism (Isola etal. 2023). Weight loss also alters serum cardiometabolic profiles, such as insulin, highlighting metabolic complexities (Jouhki etal. 2024; Mäestu etal. 2010). Additionally, male athletes experience fluctuations in insulin-like growth factor 1 (IGF-1), free (FT), and total testosterone (T), while female athletes demonstrate changes in estradiol levels during the preparation (Hulmi etal. 2017; Mitchell etal. 2018). Athletes may also experience reductions in muscular function, strength, and power as the focus shifts toward achieving ideal body aesthetics sometimes at the expense of exercise performance (Robinson etal. 2015). Additionally, bone mineral density (BMD) can decrease during periods of energy deficit, but it often recovers during refeeding (Hulmi etal. 2017). The physiological stress from the competition preparation may lead to disruptions in sleep patterns, mood disturbances, and alterations in nutrient intake, which collectively contribute to diminished exercise performance (Longstrom etal. 2020). The concept of relative energy deficiency in sport (REDS) expands our understanding of low energy availability (LEA) impacts. Affecting both male and female athletes, RED-S leads to hormonal imbalances, decreased bone mineral density, and weakened immune function. Energy deficiency also reduces muscle strength, power, and endurance, and can cause mood disturbances, anxiety, and depression. These changes impair reproductive function, metabolism, and overall health, causing conditions like hypothalamic amenorrhea in females and reduced fertility in males. Ultimately, RED-S compromises health, well-being, and athletic performance (Angelidi etal. 2024). This study examined serum hormonal changes in physique athletes during the competition preparation. Understanding hormonal alterations vital to training and health outcomes is paramount, as it may inform coaching strategies. This research delves into how energy restriction and intense training impact hormone profiles, physiological performance, and psychological well-being, using the profile of mood states (POMS) to assess mood changes. We hypothesized that the competition diets would lead to changes in serum hormones, BMD, performance, and mood in both sexes. These findings may potentially improve coaching methods for supporting athletes while minimizing adverse effects from competition preparation. Materials andmethods Participants As previously detailed by Isola etal. (2023), 89 amateur physique athletes were recruited through various online platforms. Adhering to inclusion criteria, participants were amateur competitors (COMP) aiming for fat loss while maintaining muscle mass for the national championships or were non-competing controls (CTRL). The exclusion criteria ruled out individuals with chronic diseases and medication affecting the measured variables, junior or master competitors, and those not adhering to WADA guidelines. CTRL training background mirrored that of COMP. The study was ethically approved by the Ethics Committee of the Central Finland Health Care District (19U/2018), Finland European Journal of Applied Physiology and registered (ClinicalTrials.gov ID: NCT04392752), spanned from 2019 to 2020, and adhered to the Declaration of Helsinki. Study design This study spanned 46weeks, during which participants managed their own diet and exercise regimens. They attended three laboratory sessions at specific stages: 23weeks before the competitions (PRE), one week before the competitions (MID) after an average of 21weeks of dieting, and 23weeks after the competitions (POST). Testing procedures were standardized to control for time of day, an overnight fast, and abstention from physical activities before assessments. Participants were provided a standardized meal after initial tests to mitigate the influence of dietary variables. For those traveling considerable distances, overnight accommodations were provided to ensure adherence to pretest protocols, safeguarding data integrity. Resistance andaerobic training Participants documented alterations in their training diaries (see Isola etal. 2023). Resistance training was quantified in the total weekly sets for each muscle group, and aerobic training as total minutes per week. The complete training data was available for a subset of COMP across different study phases, providing insights into the training volumes undertaken during the competition and recovery periods. Energy availability Building upon the procedures delineated by Isola etal. (2023), this study further scrutinized the energy dynamics among physique athletes through EI tracking from nutrition logs and calculated EEE from detailed training logs. Participants’ weekly average training load was quantified using metabolic equivalents (MET), adhering to Ainsworth etal. (2000) guidelines, and converted into daily average EEE. These figures were juxtaposed with fat-free mass (FFM) changes from dual-energy X-ray absorptiometry (DXA), to provide a comprehensive view of energy availability (EA) during the competition preparation. Muscular performance assessment The strength measurements were conducted 2–4h after participants arrived at the study site. Participants received detailed procedural instructions and performed a standardized warm-up of 20 bodyweight squats and 10 lunges per leg. Isometric and concentric maximal voluntary forces were assessed using a strain gauge sensor on an isokinetic knee extension device. The isokinetic knee extension dynamometer, custombuilt by the Faculty of Sport and Health Sciences at the University of Jyväskylä, Finland, was adjusted to fit each participant. The device’s axis was aligned with the lateral condyle of the right knee, and the shin support was positioned above the ankle. Participants were secured with four-point belts to prevent movement, and all equipment adjustments were documented for consistency in the subsequent assessments. The force measurement protocol included six dynamic repetitions and one isometric repetition. The sensor moved through a 70° range of motion (approximately 100°–170°, varying with individual proportions) at the angular velocity of 60°/s, pausing for 2s at both the top and bottom positions. The first repetition involved no force to familiarize participants with the motion. During repetitions 2–6, participants exerted maximum effort during the isometric (bottom) and concentric (upward) phases, with no force exerted at the top or during the downward motion. After these dynamic repetitions, participants performed one additional maximal isometric contraction for about 2s. Verbal instructions such as "press" for maximal effort and "stop" to cease exertion were provided throughout the measurements. Before the assessment, participants completed a familiarization session whereby they exerted no torque during the first repetition, then ~ 20% of estimated maximum voluntary torque during repetitions 2–6 and ~ 80% during repetition 7. Isokinetic knee extension data were recorded using the Spike 2™ software (Cambridge Electronic Design, Cambridge, UK), capturing torque and angle changes. Postmeasurement, raw data were processed using an IIR filter (Low pass Chebyshev 2) to remove interfering signals. The analysis focused on the maximum force produced during isometric contractions and the concentric phase, with peak torque not necessarily occurring during the first repetition. The best results for isometric maximum force and concentric torque were analyzed, along with a fatigue profile based on the performance from the first actual repetition to the last repetition. The fatigue profile was analyzed for both isometric force and concentric torque. Bone mass andmineral density Body composition and bone Z-score were estimated by dual-energy X-ray absorptiometry (DXA) (Lunar Prodigy Advance EnCore version 14.10.022, GE Medical Systems— Lunar, Madison WI USA), as described previously (Isola etal. 2023). The Z-score represents the standard deviations by which the study participants’ BMD deviates from the average BMD of a control group matched for age and sex (Carey etal. 2007). European Journal of Applied Physiology Ultrasound formuscle cross‑sectional area A muscle cross-sectional area (CSA) of vastus lateralis (VL) was examined at the mid-thigh using a B-mode axial plane ultrasound (model SSD-α10, Aloka, Tokyo, Japan) with a 10MHz linear-array probe (60mm width) in the extendedfield-of-view mode (23Hz sampling frequency). The accuracy and validity of the measurements have been confirmed in a prior study (Isola etal. 2023). Blood parameters Venous blood samples were obtained from the antecubital vein and put into serum tubes (Venosafe; Terumo Medical Co., Leuven, Hanau, Belgium). Samples were stored at room temperature for 30min before being centrifuged at 3500rpm for 10min (Megadure 1.0 R Heraeus; DJB Lab Care, Hanau, Germany). IGF-1, Insulin-like Growth Factor Binding Protein 3 (IGFBP-3), Adrenocorticotropic Hormone (ACTH), Follicle-Stimulating Hormone (FSH), Sex Hormone-Binding Globulin (SHBG), T, Free Testosterone (FT), Cortisol (C), Insulin, and Estradiol were analyzed from serum using the Siemens Immulite 2000 XPi immunoassay system (Siemens Healthineers, Erlangen, Germany). Estradiol was analyzed using Immulite® 2000 (L2KE2-17) commercial kits. FT was tested by ELISA using the DS2 automated ELISA system from Dynex Technologies (Testosterone Free ELISA, REF DE2924). The lowest detectable level of insulin was 0.042pmol/l. Participants with insulin levels below this threshold (9 out of 45) were recorded as having 0.042pmol/l. The sensitivity of the ACTH assay was 1.1pmol/L, with an intra-assay coefficient of variation (CV) of 8.7% and an inter-assay CV of 10%. The testosterone assay had a sensitivity of 0.5nmol/L, with intra-assay and inter-assay CVs of 16.3% and 24.3%, respectively. Insulin had a sensitivity of 0.042 mIU/L, with intra-assay and interassay CVs of 5.5% and 7.3%, respectively. The cortisol assay had a sensitivity of 5.5nmol/L, with an intra-assay CV of 6.1% and an inter-assay CV of 8.2%. IGF-1 was detected with a sensitivity of 2.6nmol/L, displaying intra-assay and inter-assay CVs of 3.9% and 7.7%, respectively. IGFBP-3 had a sensitivity of 100ng/mL, with intra-assay and interassay CVs of 4.4% and 6.6%, respectively. Estradiol sensitivity was 55pmol/L, with an intra-assay CV of 9.9% and an inter-assay CV of 16%. The FSH assay exhibited a sensitivity of 0.1IU/L, with intra-assay and inter-assay CVs of 2.9% and 4.1%, respectively. The SHBG assay sensitivity was 0.2nmol/L, with intra-assay and inter-assay CVs of 2.5% and 4.2%. Finally, the free testosterone (FT) assay had a sensitivity of 0.018pg/mL, with intra-assay and inter-assay CVs of 7% and 12%, respectively. Participants with insulin levels below the threshold (0.042 mIU/L) were assigned a value of 0.042 mIU/L (nine out of 45 participants). The testosterone–cortisol ratio (T/C ratio) was calculated as [T (nmol l − 1)/C (nmol l − 1)]. We excluded female participants using any form of contraceptive from the final analyses of ACTH, FSH, estradiol, and SHBG. POMS andreproductive function questionnaires The mood and menstrual function of female participants were evaluated monthly throughout the study, focusing on aligning these assessments with laboratory visits at the PRE, MID, and POST time points for analysis. Mood states were evaluated using the Finnish adaptation (Vuoskoski and Eerola 2011) of the POMS-Adolescents (POMS-A; Terry etal. 1999). The POMS-A comprises 24 items that appraise six distinct affective dimensions: vigor, confusion, anger, fatigue, depression, and tension. Responses were provided on a 5-point Likert scale, where 1 signifies ‘not at all’ and 5 denotes ‘extremely.’ The investigation into the menstrual status and the use of hormonal contraception, including oral contraceptives and intrauterine devices, was conducted through questionnaires. The participants completed and submitted these questionnaires at the time of measurement. Statistical analysis We used IBM SPSS for statistical analysis and tested data normality with the Shapiro–Wilk test. COVID-19 impacted our ability to complete POST measurements for all participants, leading to an initial ANOVA or Mann–Whitney test to compare groups at PRE. We then assessed changes from PRE to MID and MID to POST within groups using paired t-tests or Wilcoxon tests, depending on data distribution. Subsequently, ANOVA assessed absolute differences between COMP and CTRL across these periods. Differences between female and male COMP from PRE to MID and to POST and percentage changes in hormones, Z-score, and torque variables between sexes were also examined with ANOVA. Pearson’s or Spearman’s coefficients analyzed correlations between variables of interest, setting statistical significance at p < 0.05. This approach builds on the methodologies from prior research (Isola etal. 2023). Results Body composition, energy intake andbone health Our earlier findings showed that both sexes experienced similar reductions in EI, body mass (BM) and fat mass (FM) as well as a slight decrease in muscle size throughout the 21-week competition preparation (Isola etal. 2023). However, a distinct outcome was noted among males, who uniquely exhibited a loss in lean mass (LM). Instead of LM, European Journal of Applied Physiology the present study employed FFM to calculate EA. Given that FFM’s behavior mirrored LM, we have not reported these measures separately. EA (derived by subtracting EEE from EI and dividing by FFM) decreased (p < 0.001) during the weight-loss period in both male and female COMP (from 43.9 ± 10.8 to 27.0 ± 5.28 kcal/kg and from 38.2 ± 6.9 kcal/kg to 20.8 ± 3.50kcal/kg, respectively) and the change was significant compared to CTRL (p < 0.05, Fig.1). EA increased in male CTRL (p < 0.05). Notably, EA in male COMP at MID was significantly lower than in female COMP (p < 0.01). EA increased in both COMP groups from MID to POST (p < 0.05) and recovered back to baseline. Z-scores showed no significant changes from PRE to MID in either COMP group. Scores remained stable for female COMP participants (from 0.68 ± 0.85 to 0.68 ± 0.84) and for male COMP participants (from 0.75 ± 1.13 to 0.78 ± 1.02) (Fig.1). Similarly, no significant changes were observed in any of the groups from MID to POST. Hormone profiles IGF-1 decreased significantly in both female and male COMP from PRE to MID compared to CTRL (p < 0.001, Fig.2). There was a significant difference between sexes in COMP in IGFBP-3 levels at baseline (p < 0.05). Additionally, IGFBP-3 significantly decreased in female and male COMP groups (p < 0.01). A significant correlation was found between individual changes in IGF-1 and FFM in male COMP (p < 0.05, Fig.3). The percentage change in IGF-1 and FFM measured by DXA also correlated significantly (p < 0.05). IGF-1 levels in both COMP groups did not significantly change from MID to POST. However, comparing female COMP to CTRL, the difference in IGF-1 levels was statistically significant (p < 0.05). Testosterone (T) and free testosterone (FT) levels significantly differed between male COMP and female COMP at baseline (p < 0.001, respectively, Fig.2). T and FT levels decreased in male COMP from PRE to MID (p < 0.01) Fig. 1 A, B Absolute changes in energy availability and bone mineral density in COMP and CTRL groups from PRE to MID and MID to POST. Baseline pre-test (PRE) was obtained before the dieting phase for the competition, MID one week before the competition, and POST after the recovery period. Numbers in parentheses indicate the number of participants. Circles and triangles indicate individual data for the COMP and CTRL groups, respectively, and bars indicate means. ∗ indicates a statistically significant change within the group. # indicates a statistically significant difference between the COMP and CTRL groups in the change. ∗ #, ∗ ∗ ##, and ∗∗∗ ### represent p-values ranging from < 0.05 to < 0.001. The dotted line represents the EA threshold. EA levels below 30kcal/kg FFM per day are associated with significant disruptions in body systems, including hormonal alterations and bone health issues. C, D Absolute and percentage changes in female and male COMP groups from PRE to MID. Circles indicate individual data and black lines indicate the mean difference between sexes. Energy availability is expressed in kcal/kg, derived by subtracting EEE from EI and dividing by FFM. Z-score is used as an indicator of bone density European Journal of Applied Physiology and compared to CTRL (p < 0.05 and p < 0.001). There was a difference in T (p < 0.05) and FT (p < 0.01) levels between the sexes in COMP from PRE to MID. Both T (p < 0.001) and FT (p < 0.05) levels increased from MID to POST, recovering back to baseline, and these changes were also significant when compared to CTRL (p < 0.05 and p < 0.001, respectively). No significant changes were observed in the female groups across the study, except T decreased from MID to POST in female CTRL (p < 0.05). European Journal of Applied Physiology SHBG differed between sexes at baseline in COMP (p < 0.001). SHBG increased in both female (p < 0.05) and male (p < 0.001) COMP from PRE to MID (Fig.4), but only male COMP differed significantly from CTRL (p < 0.001). From MID to POST, SHBG levels decreased in male COMP (p < 0.05) and increased in male CTRL (p < 0.05), with the change being significant (p < 0.05). No significant changes were observed in female groups. No significant changes were observed in estradiol levels in female and male COMP. There was a statistically significant difference in percentage change between the sexes in COMP from PRE to MID (p < 0.05). No significant changes were observed in either female or male COMP from PRE to MID, but in male CTRL, estradiol increased (p < 0.01) significantly compared to COMP (p < 0.05). From MID to POST, estradiol significantly decreased in male COMP (p < 0.01, Fig.4). In contrast, no changes were observed in the female groups. Insulin decreased in male COMP (p < 0.001), and the change was statistically significant (p < 0.001, Fig.4) compared to CTRL from PRE to MID. There was a significant difference in insulin between female COMP and CTRL at baseline (p < 0.01). However, no significant change was observed in insulin from PRE to MID within female COMP or CTRL. In contrast, male COMP experienced a statistically significant reduction in insulin from PRE to MID (p < 0.001), which was significantly different compared to male CTRL (p < 0.001). Cortisol increased significantly in male COMP from MID to POST (p < 0.05, Fig.5), but there was no significant difference compared to CTRL. No significant changes in cortisol were observed in the female groups. The T/C ratio significantly decreased in male COMP (p < 0.001, Fig.5), and the change was significant compared to CTRL (p < 0.001). No significant changes were observed in the female groups. Male COMP experienced a decrease of -50.4 ± 17.8%, which was more pronounced (p < 0.01) compared to female COMP (6.8 ± 53.5%). From MID to POST, T/C ratio increased in male COMP (p < 0.01), and the change was significant compared to CTRL (p < 0.001). Additionally, there was a significant difference between sexes (p < 0.001) in COMP. Follicle-stimulating hormone decreased in male COMP and CTRL (p < 0.05) from PRE to MID. FSH increased in male COMP (p < 0.05) and female CTRL (p < 0.05) from MID to POST (Fig.5). No significant changes were observed in ACTH, except in female COMP from MID to POST. Strength measurements Isometric force decreased from PRE to MID in both female (p < 0.001) and male (p < 0.01) COMP and male CTRL (p < 0.05, Fig.6). Additionally, isometric force was lower in COMP compared to CTRL in both sexes (p < 0.001 and p < 0.05, respectively). Concentric torque also decreased from PRE to MID in both female and male COMP (p < 0.001 and p < 0.01, respectively) and was lower compared to CTRL (p < 0.05). The ratio of maximal isometric muscle force to CSA (F/CSA) decreased in female COMP (p < 0.05) and female CTRL (p < 0.001). No significant changes were observed in the male groups. A significant difference was noted in the changes in isometric fatigue profile between sexes from PRE to MID (p < 0.05). Isometric fatigue decreased in female COMP from MID to POST (p < 0.05). No significant changes were observed in the concentric fatigue profiles in any of the groups (data not shown). Menstrual irregularities In female COMP, 50% of participants (5/10) reported using hormonal contraception, with one experiencing a disturbed menstrual cycle between the PRE and MID phases. Additionally, three members of COMP who did not use hormonal contraception reported irregular menstruation during the same period. Thus, four participants in COMP experienced menstrual irregularities during the study period. In female CTRL, 50% of participants (6/12) were using hormonal contraception, and four experienced irregular menstrual irregularities throughout the study period. POMS Male COMP experienced an increase in FATIGUE (p < 0.05), and the change was significant compared to CTRL (p < 0.01, Table1). TENSION also increased (p < 0.05), but this change was not significantly different compared to CTRL. However, significant sex differences were noted in TENSION changes from PRE to MID (p < 0.01), where Fig. 2 A–D Absolute changes in IGF-1, IGFBP-3, total testosterone, and free testosterone in COMP and CTRL groups from PRE to MID and MID to POST. Baseline pre-test (PRE) was obtained before the dieting phase for the competition, MID one week before the competition, and POST after the recovery period. Numbers in parentheses indicate the number of participants. Circles and triangles indicate individual data for the COMP and CTRL groups, respectively, and bars indicate means. ∗ indicates a statistically significant change within the group. # indicates a statistically significant difference between the COMP and CTRL groups in the change. ∗ #, *∗ ##, and ∗∗ ∗ ### represent p-values ranging from < 0.05 to < 0.001. The black dotted lines represent the reference values for a normal-weight person. E–H Absolute and percentage changes in female and male COMP groups from PRE to MID. Circles indicate individual data and black lines indicate the mean. † indicates a statistically significant (p < 0.05) difference between the sexes. IGF-1, insulin-like growth factor 1; IGFBP-3, insulin-like growth factor binding protein 3. Note: No reference values are provided for free testosterone because directly measured free testosterone levels can differ significantly from calculated values ◂ European Journal of Applied Physiology female TENSION decreased. No significant difference was noted in female COMP groups. From MID to POST, FATIGUE decreased significantly (p < 0.01), and DEPRESSION decreased (p < 0.05) in male COMP, but these changes were not significantly different from CTRL. No significant changes were observed in female groups. Discussion We hypothesized that competition diets would lead to changes in serum hormones, BMD, performance, and mood in both sexes. As expected, significant changes in serum hormone levels were observed, indicating energy deficiency, and these changes were in part sex-specific. While mood and strength changes were observed, no changes in BMD were detected. A primary finding was the reduction in IGF-1 and its binding protein IGFBP-3 among both sexes during the competition preparation, suggesting that these may serve as potential biomarkers for monitoring physiological stress (Angelidi etal. 2024). Insulin-like growth factor 1, a crucial hormone for muscle development (Yoshida and Delafontaine 2020), significantly decreased in the female and male COMP groups. Similarly, IGFBP-3, which modulates IGF-1 bioavailability, also decreased. This observation aligns with Mitchell etal. (2018), who reported similar reductions in IGF-1 among male physique athletes during competition preparation. Nutrition plays a crucial role in regulating circulating IGF-1 levels, with energy restriction profoundly impacting serum concentrations (Henning etal. 2014). In this study, the reduction in IGF-1 and IGFBP-3 may be attributed to reduced EI and LEA during the competition preparation. We previously reported an association between IGF-1 levels and EA at baseline before the competition preparation among a larger sample of physique athletes (Mursu etal. 2023). We observed correlations between IGF-1 levels and changes in FFM in male and female COMP. This supports the argument that IGF-1 may be a potential biomarker to monitor physiological stress during the intense training period and nutritional changes that alter body composition, such as physique competition preparation. It also aligns with previous studies in soldiers; Nindl etal. (2007) demonstrated that IGF-1 and IGFBP-3 align with energy deficits and body composition changes, with free IGF-1 positively correlating with changes in body mass and FFM. Additionally, IGF-1 has a role in facilitating protein synthesis and muscle growth, and low levels of IGF-1 are associated with reduced BMD (Yan etal. 2016). There was LEA during competition preparation in both female and male COMP groups with no significant sex differences. Despite LEA, no significant changes were observed in BMD, aligning with findings by Schoenfeld etal. (2023) in their systematic review of competitors during preparation for physique competitions. However, a study on elite endurance athletes revealed that LEA can reduce BMD (Heikura etal. 2018). Furthermore, Ihle and Loucks (2004) conducted a 5-day intervention manipulating EI in young females, resulting in significant effects on bone formation and resorption. Our results suggest that a 21-week weight loss period may not, on average, negatively impact bone health in physique athletes despite low EI and reduced IGF-1 levels. One explanation for this may be that physique athletes engage in extensive strength training, which is known to protect bone mineral content and density by stimulating new bone formation in areas subjected to mechanical strain (Pal etal. 2023). We observed a significant reduction in insulin in male COMP, with a similar but not statistically significant trend in females. This aligns with Mäestu etal. (2010), who documented significant insulin declines in male bodybuilders during competition preparation. On the other hand, this was not observed in the study by Mitchell etal. (2018) who Fig. 3 These scatter plots illustrate the relationship between changes in IGF-1 and changes in FFM in female (A, C) and male (B, D) COMP from PRE to MID. Each point represents an individual participant. Scatter plots A and B depict absolute changes, while scatter plots C and D depict changes in percentages European Journal of Applied Physiology Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. References Ahtiainen JP, Pakarinen A, Alen M, Kraemer WJ, Häkkinen K (2003) Muscle hypertrophy, hormonal adaptations and strength development during strength training in strength-trained and untrained men. Eur J Appl Physiol 89:555–563 Ainsworth BE, Haskell WL, Whitt MC, Irwin ML, Swartz AM, Strath SJ, O’Brien WL, Bassett J, Schmitz KH, Emplaincourt PO, Jacobs J, Leon AS (2000) Compendium of physical activities: an update of activity codes and MET intensities. Med Sci Sports Exerc. https:// doi. org/ 10. 1097/ 00005 76820000 900100009 Allen NE, Appleby PN, Davey GK, Key TJ (2002) Lifestyle and nutritional determinants of bioavailable androgens and related hormones in British men. Cancer Causes Control 13:353–363 Angelidi AM, Stefanakis K, Chou SH, Valenzuela-Vallejo L, Dipla K, Boutari C, Ntoskas K, Tokmakidis P, Kokkinos A, Goulis DG, Papadaki HA, Mantzoros CS (2024) Relative energy deficiency in sport (REDs): endocrine manifestations, pathophysiology and treatments. Endocrine Rev. https:// doi. org/ 10. 1210/ endrev/ bnae0 11 Areta JL, Taylor HL, Koehler K (2021) Low energy availability: history, definition and evidence of its endocrine, metabolic and physiological effects in prospective studies in females and males. Eur J Appl Physiol. https:// doi. org/ 10. 1007/ s0042102004516-0 Bamman MM, Hunter GR, Newton LE, Roney RK, Khaled MA (1993) Changes in body composition, diet, and strength of bodybuilders during the 12 weeks prior to competition. J Sports Med Phys Fitness 33(4):383–391 Carey JJ, Delaney MF, Love TE, Richmond BJ, Cromer BA, Miller PD, Manilla-McIntosh M, Lewis SA, Thomas CL, Licata AA (2007) DXA-generated Z-scores and T-scores may differ substantially and significantly in young adults. J Clin Densitom 10(4):351–358. https:// doi. org/ 10. 1016/j. jocd. 2007. 06. 001 De Luccia TPB (2016) Use of the testosterone/cortisol ratio variable in sports. Open Sports Sci J 9(1):104–113. https:// doi. org/ 10. 2174/ 18753 99x01 60901 0104 Häkkinen K, Pakarinen A, Alen M, Komi PV (1985) Serum hormones during prolonged training of neuromuscular performance. Eur J Appl Physiol Occup Physiol. https:// doi. org/ 10. 1007/ BF004 22840 Häkkinen K, Newton RU, Walker S, Häkkinen A, Krapi S, Rekola R, Koponen P, Kraemer WJ, Haff GG, Blazevich AJ (2022) Effects of upper body eccentric versus concentric strength training and detraining on maximal force, muscle activation, hypertrophy and serum hormones in women. J Sports Sci Med 21(2):200 Häkkinen K, Pakarinen A, Alen M, Kauhanen H, Komi PV (1987) Relationships between training volume, physical performance capacity, and serum hormone concentrations during prolonged training in elite weight lifters. Int J Sports Med 8(S1):S61–S65 Häkkinen K, Pakarinen A, Kallinen M (1992) Neuromuscular adaptations and serum hormones in women during short-term intensive strength training. Eur J Appl Physiol 64:106–111 Healy ML, Gibney J, Pentecost C, Wheeler MJ, Sonksen PH (2014) Endocrine profiles in 693 elite athletes in the postcompetition setting. Clin Endocrinol 81(2):294–305. https:// doi. org/ 10. 1111/ cen. 12445 Heikura IA, Uusitalo ALT, Stellingwerff T, Bergland D, Mero AA, Burke LM (2018) Low energy availability is difficult to assess but outcomes have large impact on bone injury rates in elite distance athletes. Int J Sport Nutr Exerc Metab 28(4):403–411. https:// doi. org/ 10. 1123/ ijsnem. 20170313 Henning PC, Scofield DE, Spiering BA, Staab JS, Matheny RW, Smith MA, Bhasin S, Nindl BC (2014) Recovery of endocrine and inflammatory mediators following an extended energy deficit. J Clin Endocrinol Metab 99(3):956–964. https:// doi. org/ 10. 1210/ jc. 20133046 Hulmi JJ, Isola V, Suonpää M, Järvinen NJ, Kokkonen M, Wennerström A, Nyman K, Perola M, Ahtiainen JP, Häkkinen K (2017) The effects of intensive weight reduction on body composition and serum hormones in female fitness competitors. Front Physiol. https:// doi. org/ 10. 3389/ fphys. 2016. 00689 Ihle R, Loucks AB (2004) Dose-response relationships between energy availability and bone turnover in young exercising women. J Bone Miner Res 19(8):1231–1240. https:// doi. org/ 10. 1359/ JBMR. 040410 Isola V, Hulmi JJ, Petäjä P, Helms ER, Karppinen JE, Ahtiainen JP (2023) Weight loss induces changes in adaptive thermogenesis in female and male physique athletes. Appl Physiol Nutr Metab 48(4):307–320. https:// doi. org/ 10. 1139/ apnm20220372 Jones EJ, Bishop PA, Woods AK, Green JM (2008) Cross-sectional area and muscular strength: a brief review. Sports Med 38:987–994 Jouhki I, Sarin HV, Jauhiainen M, O’Connell TM, Isola V, Ahtiainen JP, Hulmi JJ, Perola M (2024) Effects of fat loss and low energy availability on the serum cardiometabolic profile of physique athletes. Scand J Med Sci Sports. https:// doi. org/ 10. 1111/ sms. 14553 Karila TAM, Sarkkinen P, Marttinen M, Seppälä T, Mero A, Tallroth K (2008) Rapid weight loss decreases serum testosterone. Int J Sports Med 29:872–877 Longstrom JM, Colenso-Semple LM, Waddell BJ, Mastrofini G, Trexler ET, Campbell BI (2020) Physiological, psychological and performance-related changes following physique competition: a case-series. J Funct Morphol Kinesiol 5(2):27. https:// doi. org/ 10. 3390/ jfmk5 020027 Mäestu J, Eliakim A, Jürimäe J, Valter I, Jürimäe T (2010) Anabolic and catabolic hormones and energy balance of the male bodybuilders during the preparation for the competition. J Strength Cond Res 24(4):1074–1081 Mero AA, Huovinen H, Matintupa O, Hulmi JJ, Puurtinen R, Hohtari H, Karila TAM (2010) Moderate energy restriction with high protein diet results in healthier outcome in women. J Int Soc Sports Nutr. https:// doi. org/ 10. 1186/ 15502783-7-4 Mitchell L, Slater G, Hackett D, Johnson N, O’connor H (2018) Physiological implications of preparing for a natural male bodybuilding competition. Eur J Sport Sci 18(5):619–629. https:// doi. org/ 10. 1080/ 17461 391. 2018. 14440 95 Mountjoy M, Ackerman KE, Bailey DM, Burke LM, Constantini N, Hackney AC, Heikura IA, Melin A, Pensgaard AM, Stellingwerff T, Sundgot-Borgen JK, Torstveit MK, Jacobsen AU, Verhagen E, Budgett R, Engebretsen L, Erdener UU (2023) 2023 International Olympic Committee’s (IOC) consensus statement on relative energy deficiency in sport (REDs). Br J Sports Med 57(17):1073–1097. https:// doi. org/ 10. 1136/ bjspo rts2023106994 Mursu J, Ristimäki M, Malinen I, Petäjä P, Isola V, Ahtiainen JP, Hulmi JJ (2023) Dietary intake, serum hormone concentrations, European Journal of Applied Physiology amenorrhea and bone mineral density of physique athletes and active gym enthusiasts. Nutrients. https:// doi. org/ 10. 3390/ nu150 20382 Newton LE, Hunter G, Bammon M, Roney R (1993) Changes in psychological state and self-reported diet during various phases of training in competitive bodybuilders. J Strength Cond Res 7(3):153–158 Nindl BC, Barnes BR, Alemany JA, Frykman PN, Shippee RL, Friedl KE (2007) Physiological consequences of U.S. army ranger training. Med Sci Sports Exerc 39(8):1380–1387. https:// doi. org/ 10. 1249/ MSS. 0b013 e3180 67e2f7 Pal C, Agarwal V, Srivastav R, Gupta M, Singh S (2023) Physiological adaptations of skeletal muscle and bone to resistance training and its applications in orthopedics: a review. J Bone Joint Dis 38(1):3. https:// doi. org/ 10. 4103/ jbjd. jbjd_9_ 23 Pasiakos SM, Berryman CE, Karl JP, Lieberman HR, Orr JS, Margolis LM, Caldwell JA, Young AJ, Montano MA, Evans WJ, Vartanian O, Carmichael OT, Gadde KM, Johannsen NM, Beyl RA, Harris MN, Rood JC (2019) Effects of testosterone supplementation on body composition and lower-body muscle function during severe exerciseand diet-induced energy deficit: a proof-of-concept, single centre, randomised, double-blind, controlled trial. EBioMedicine 46:411–422. https:// doi. org/ 10. 1016/j. ebiom. 2019. 07. 059 Robinson SL, Lambeth-Mansell A, Gillibrand G, Smith-Ryan A, Bannock L (2015) A nutrition and conditioning intervention for natural bodybuilding contest preparation: case study. J Int Soc Sports Nutr. https:// doi. org/ 10. 1186/ s129700150083-x Rossow LM, Fukuda DH, Fahs CA, Loenneke JP, Stout JR (2013) Natural bodybuilding competition preparation and recovery: a 12-month case study. Int J Sports Physiol Perform 8(5):582–592. https:// doi. org/ 10. 1123/ ijspp.8. 5. 582 Sarin HV, Hulmi JJ, Qin Y, Inouye M, Ritchie SC, Cheng S, Watrous JD, Nguyen TTC, Lee JH, Jin Z, Terwilliger JD, Niiranen T, Havulinna A, Salomaa V, Pietiläinen KH, Isola V, Ahtiainen JP, Häkkinen K, Jain M, Perola M (2022) Substantial fat loss in physique competitors is characterized by increased levels of bile acids, very-long chain fatty acids, and oxylipins. Metabolites. https:// doi. org/ 10. 3390/ metab o1210 0928 Schoenfeld BJ, Androulakis-Korakakis P, Piñero A, Burke R, Coleman M, Mohan AE, Escalante G, Rukstela A, Campbell B, Helms E (2023) Alterations in measures of body composition, neuromuscular performance, hormonal levels, physiological adaptations, and psychometric outcomes during preparation for physique competition: a systematic review of case studies. J Funct Morphol Kinesiol. https:// doi. org/ 10. 3390/ jfmk8 020059 Terry PC, Lane AM, Lane HJ, Keohane L (1999) Development and validation of a mood measure for adolescents. J Sports Sci 17(11):861–872 Vuoskoski JK, Eerola T (2011) The role of mood and personality in the perception of emotions represented by music. Cortex 47(9):1099– 1106. https:// doi. org/ 10. 1016/j. cortex. 2011. 04. 011 Wackerhage H, Schoenfeld BJ, Hamilton DL, Lehti M, Hulmi JJ (2019) Stimuli and sensors that initiate skeletal muscle hypertrophy following resistance exercise. J Appl Physiol. https:// doi. org/ 10. 1152/ jappl physi ol. 00685. 2018 Williams RL, Wood LG, Collins CE, Callister R (2015) Effectiveness of weight loss interventions—is there a difference between men and women: a systematic review. Obes Rev 16(2):171–186. https:// doi. org/ 10. 1111/ obr. 12241 Yan J, Herzog JW, Tsang K, Brennan CA, Bower MA, Garrett WS, Sartor BR, Aliprantis AO, Charles JF (2016) Gut microbiota induce IGF-1 and promote bone formation and growth. Proc Natl Acad Sci USA 113(47):E7554–E7563. https:// doi. org/ 10. 1073/ pnas. 16072 35113 Yoshida T, Delafontaine P (2020) Mechanisms of IGF-1-mediated regulation of skeletal muscle hypertrophy and atrophy. Cells. https:// doi. org/ 10. 3390/ cells 90919 70 Publisher's Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.