Sex-hormone induced short-term changes in body composition are paralleled by an increase in ad libitum energy intake

Sex-hormone induced short-term changes in body composition are paralleled by an increase in ad libitum energy intake | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Sex-hormone induced short-term changes in body composition are paralleled by an increase in ad libitum energy intake Martin Kaar, Pauline Zimmermann, Theresa Bokeloh, Lotta Moll, and 6 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8824402/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background. Body weight is governed by balance between energy intake and energy expenditure. Transgender individuals undergoing gender-affirming hormone therapy (GAHT) are at increased risk of overweight and obesity. A comprehensive assessment of energy expenditure and intake during GAHT is lacking. Objective. To investigate adaptations in body composition, energy expenditure, and energy intake during GAHT. Methods. In a prospective observational cohort study, body weight, body composition, ad libitum energy intake during buffet, snack food intake, energy expenditure (REE), and physical activity were assessed at baseline, after three, six, 12 months of GAHT in 17 trans men (female-to-male transgender; median±interquartile range; body mass index [BMI] 25.7 ± 7 kg/m²; age 22.9 ± 3.9 years) and 16 trans women (male-to-female transgender; BMI 22.5 ± 7.3 kg/m²; age 24.9 ± 5.8 years). Cis men (n = 7) and women (n = 10) without hormone treatment served as controls. Results . In trans men, body weight (χ²=16.27, p = 0.001; Δ median = 2.4 kg) and fat-free mass (χ²=24.95, p < 0.001; Δ median = 0.8 kg) increased over 12 months of GAHT, accompanied by a gain in fat mass over 6 months (χ²=9.14, p = 0.028; Δ median = 1.1 kg). In trans women, body weight (χ²=16.54, p < 0.001; Δ median = 3.6 kg) and fat mass (χ²=18.06, p 0.05). In both groups, energy intake was higher (trans women χ²=13.73, p = 0.003, Δ median = 132 kcal; trans men χ²=18.39, p 0.05) Conclusion. During GAHT, sex hormone–induced changes in body composition are paralleled by an increase in energy intake. Endocrinology & Metabolism Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Introduction Long-term body weight is determined by the balance between energy intake (EI) and energy expenditure (EE). Energy expenditure modulates EI through both physiological signals and behavior 1 – 3 , and mounting evidence indicates a tight coupling between an individual’s energetic demands and appetitive drive 4 , 5 . In particular, fat-free mass (FFM) — the major anthropometric determinant to resting EE — has emerged as a strong predictor of ad libitum energy intake 3 , 6 , 7 , and several studies report positive associations among FFM, measures of EE, and food consumption in humans 3 , 6 , 8 , 9 . Given the central role of EI and EE in the pathogenesis of obesity and its comorbidities, elucidating the determinants and modulators of each arm of the energy balance equation has become a priority in metabolic research 10 , 11 . Two key predictors of EE are FFM and fat mass (FM), which together account for the bulk of resting energy requirements 12 . Changes in FFM and FM over time therefore modify EE, and — through the aforementioned feedback mechanisms — may secondarily influence EI 13 . Conversely, some drivers of EI operate independently of EE, such as food palatability, social cues, and neuroendocrine factors 14 . Alterations in body composition may thus, through their impact on EE, contribute to changes in EI, while changes in intake could in turn modify body composition, illustrating the bidirectional interplay between these variables. Crucially, these relationships are not necessarily perfectly compensatory: When EE chronically exceeds EI, net weight loss ensues, whereas a sustained positive energy balance leads to body weight gain and obesity 15 , 16 . Thus, mismatches between energy demand (as reflected by FFM and EE) and actual EI can lead to gradual and sustained alterations in body mass over time. Among individuals undergoing gender-affirming hormone therapy (GAHT) the risk to develop overweight and obesity is increased 17 , 18 . Through the administration of estradiol or testosterone, GAHT induces predictable short-term alterations in FFM and FM 19 , which may contribute to body weight gain in this population. Although clinically relevant, a comprehensive assessment of both sides of the energy balance equation — EE and EI — in the setting of GAHT is lacking. To address this gap, in an exploratory approach we conducted a prospective, controlled, cohort study to investigate short-term adaptations in body composition, EE, and ad libitum EI during GAHT. Subjects and methods Subjects The current study includes data from individuals recruited between January 2021 and November 2025 at the endocrinological outpatient clinic of the University Hospital Leipzig as part of a clinical investigation designed to assess the effects of GAHT on metabolic, vascular, and behavioral outcome parameters (clinicaltrials.gov registration number NCT04838249) 20 , 21 . Following assessment of medical history, physical examination, and basic laboratory parameters, and having provided written informed consent, 50 consented volunteers were admitted to the clinical research unit to participate in the study. According to the study protocol, exclusion criteria included uncontrolled chronic diseases (e.g., hypertension, heart failure, diabetes mellitus, malignancies, inflammatory or infectious conditions), endocrine disorders (e.g., hypercortisolism, hypo-/hyperthyroidism, pituitary disease), or psychiatric illness requiring hospitalization, as determined by medical history and laboratory assessment. Transgender participants were diagnosed with gender incongruence according to ICD-10 F64.0 or ICD-11 HA60 prior to recruitment at the time of first presentation to the outpatient clinic. In total, 16 trans women (male-to-female transgender) and 17 trans men (female-to-male transgender) were included with indication to perform GAHT. Prior to the study, none of the participants had ever received hormone therapy. Ten cisgender women, and seven cisgender men served as control group and were recruited through public advertising and institutional networks. The control group did not receive GAHT (Table 1 ). Table 1 Baseline characteristics of the study population. Characteristics Trans women (male-to-female transgender) Cisgender men Trans men (female-to-male transgender) Cisgender women n = 16 n = 7 p n = 17 n = 10 p Age (years) 24.9 (5.2) 24.6 (4.4) 0.67 22.9 (4) 24.9 (4.8) 0.046 Weight (kg) 69.8 (19.4) 73.9 (10.5) 0.71 71.5 (24.1) 66.3 (23.7) 0.38 Body mass index (kg/m 2 ) 22.5 (7.3) 21.9 (3.2) 0.99 25.7 (7.0) 23.6 (3.6) 0.60 Fat mass (kg) 14.2 (13.4) 14.0 (2.5) 0.92 25.5 (13.3) 17.8 (10.1) 0.11 Fat-free mass (kg) 58.1 (8.6) 59.7 (9.1) 0.37 48.9 (11.0) 49.4 (13.9) 0.71 Resting energy expenditure (kcal/day) 1789 (364.0) 1810 (232.0) 0.72 1528 (248) 1538 (142) 0.75 Buffet energy intake (kcal) 1061 (496) 1240 (860) 0.20 718 (325) 735 (308) 0.57 Buffet carbohydrate intake (kcal) 317 (270) 590 (290) 0.06 320 (165) 303 (144) 0.68 Buffet fat intake (kcal) 411 (272) 511 (494) 0.58 329 (188) 344 (204) 0.98 Buffet protein intake (kcal) 154 (166) 138 (61) 0.18 94 (47) 105 (95) 0.79 Snack food energy intake (kcal) 347 (756) 317 (483) 0.88 364 (336) 282 (784) 0.71 Testosterone serum concentration (nmol/l) 16.6 (7.9) 18.9 (5.9) 0.53 0.9 (0.5) 0.8 (0.7) 0.46 Estradiol serum concentration (pmol/l) 92.6 (26.4) 114.5 (94.9) 0.21 284.9 (230.5) 148.0 (367.8) 0.18 Accelerometer wear time (hours/day) 16.1 (3.1) 16.4 (4.2) 0.48 16.6 (4.8) 16.2 (3.1) 0.78 Activity level sedentary (min/day) 1250.0 (115.0) 1227.0 (105.0) 0.45 1280.0 (96.0) 1218.0 (84.0) 0.06 Activity level light (min/day) 70.3 (44.7) 66.7 (20.0) 0.72 59.8 (25.6) 84. 6 (39.4) 0.14 Activity level moderate (min/day) 118.9 (82.7) 140.3 (60.4) 0.06 89.4 (62.8) 131.0 (49.2) 0.04 Activity level vigorous (min/day) 0.6 (8.7) 6.6 (25.6) 0.13 0.4 (1.2) 5.7 (6.8) 0.003 Study protocol Data was collected at four standardized timepoints: baseline (prior to GAHT initiation), and at three, six, and 12 months of ongoing GAHT (Fig. 1 ). For cisgender controls, measurements were obtained at matching intervals and except for GAHT, study protocol was identical for both patients and controls. All study visits took place in the morning after an overnight fast. Participants were instructed to refrain from vigorous physical activity, alcohol, and caffeine for at least 24 hours prior to each visit. Gender-affirming hormone therapy Hormonal treatment was administered in accordance with international guidelines 22 , 23 . Trans women received estradiol, either orally or via transdermal application, in combination with cyproterone acetate for androgen suppression. Trans men were treated with testosterone, administered either as undecanoate or enanthate esters. The specific preparations and dosages used in the study are listed in Supplemental Table S1. Serum concentrations of estradiol and testosterone were monitored throughout the study period as part of routine clinical follow-up at above mentioned time points. Dosages were individually adjusted to achieve hormone levels within the physiological target range for the perceived gender. All treatment regimens were managed by experienced endocrinologists following established standards of care 22 , 23 . To address the effect of GAHT on outcome measures, therapy was initiated upon completion of baseline assessments. Anthropometry and bioelectrical impedance analysis Anthropometric measurements were obtained under standardized conditions after an overnight fast in the morning. Body height and weight were measured using a calibrated stadiometer and a digital scale, with participants wearing light clothing and no shoes, according to site-specific standardized protocols. Body composition, including total FM and FFM, was assessed by multifrequency bioelectrical impedance analysis (BIA; Biacorpus RX 4004M, Medi Cal Healthcare GmbH, Karlsruhe, Germany), following established methodological standards 24 . After voiding the bladder, BIA was performed in the fasting state following a 10-minute horizontal rest at a controlled ambient temperature. Electrodes were placed according to manufacturer instructions, and body composition parameters were derived through the device’s integrated prediction equations using the participants biological sex 25 . Resting energy expenditure Resting energy expenditure (REE) was assessed by indirect calorimetry (Q-NRG, COSMED, Rome, Italy) using a ventilated hood system. Measurements were conducted in the morning after an overnight fast, with participants lying in a horizontal position in a thermoneutral environment (22–24°C). After at least 15 minutes of rest, respiratory gas exchange was recorded continuously for 20 minutes while participants remained awake and motionless. To minimize potential arousal, participants were allowed to watch emotionally neutral nature documentaries on a provided tablet. REE was calculated from oxygen consumption and carbon dioxide production using the Weir Eq. 2 6 . The protocol followed established recommendations for indirect calorimetry 27 , including pre-measurement abstention from caffeine, nicotine, and vigorous activity, and calibration of the device before each session. After achieving a steady state, a 10-minute interval was selected for REE calculation. The Q-NRG system has been validated for accuracy and repeatability 28 . Ad libitum food intake Buffet Energy intake was assessed using a customized ad libitum buffet paradigm, as previously described 29 . Prior to the baseline visit, participants selected their preferred food items (omnivore, vegetarian, or vegan options) via a digital questionnaire. For each participant, the selected set of buffet items was kept identical for all subsequent study visits. The buffet took place between 10:30 and 11:00 a.m. in a distraction-free room with 30-minute unrestricted access to customized food. External stimuli were reduced, and electronic devices were not permitted. All food items were weighed before and after the session to determine kilocalories consumed. Energy and macronutrient values were obtained from manufacturer-provided nutritional labels and standardized food composition databases 30 . Snack test A snack test was conducted after the end of the buffet meal to assess ad libitum energy intake of highly palatable snack foods, as previously described 31 , 32 . Participants were presented with a standardized selection of snack items (potato chips, peanuts, cookies, and candy) and instructed to taste and eat as much as they desired. They were left alone in the room for 10 minutes and unaware that energy intake was being measured. Snack food consumption (grams and kilocalories) was determined by weighing the food items before and after the session. Participants were able to customize the snacks available via a digital questionnaire (omnivore, vegetarian, or vegan options) based on individual preferences and dietary restraints. The selection was kept identical for all subsequent study visits. Physical activity monitoring via accelerometry To account for inter-individual differences in habitual physical activity potentially contributing to body weight change, participants wore a triaxial accelerometer (AX6, Axivity Ltd., Newcastle, United Kingdom) on the wrist of the non-dominant hand for seven consecutive days preceding each study visit. Devices were configured using the manufacturer’s Open Movement GUI software. Raw acceleration data were processed using the open-source R package GGIR, which applies standardized algorithms for autocalibration, data cleaning, and signal processing 33 , 34 . A minimum wear time of 16 hours per day on at least four days was required for data inclusion, following established methodological standards 34 , 35 . Extracted metrics included time spent in light, moderate, and vigorous activity levels as well as overall physical activity volume 33 . All metrics were computed using validated classification thresholds for wrist-worn accelerometers 36 , 37 . Activity intensity was categorized according to metabolic equivalent of task (MET), using standardized intensity bands established for wrist-worn accelerometry: light (1.5 to < 4 MET; activities of daily living), moderate (4 to < 7 MET; sustained lifestyle movement), and vigorous (≥ 7 MET; high-intensity physical activity). Device-specific variability and reliability for the AX6 model have previously been reported 38 . Statistical analyses Statistical analyses were performed using GraphPad Prism version 10 (GraphPad, Boston, MA, USA). To assess baseline differences in patient characteristics between cohorts, the non-parametric Mann–Whitney U test was applied. Longitudinal changes across measurement time points were analyzed using the Friedman test. When the Friedman test indicated significant differences over time, Dunn’s multiple comparisons test was used post-hoc to identify which time points contributed to the observed changes. Test statistics are reported as chi-square values (χ²), degrees of freedom, and corresponding p-values. Kendall’s W was calculated as a measure of effect size. In addition, median values and interquartile ranges (IQR) are reported for descriptive purposes. Correlation analyses were performed using Spearman rank correlation. To address the effect of GAHT on REE and given the limited sample size, residual REE was calculated after adjustment for its primary determinant, FFM, using linear regression 12 , 39 . A two-sided alpha level of 0.05 was used throughout. Due to the limited sample sizes (maximum n = 17 in the trans men cohort, with smaller sample sizes in the trans women and control cohorts), formal tests of normality were not performed due to inherent limited power and reliability in small samples. Given the resulting uncertainty regarding distributional assumptions and the presence of visibly skewed data, all longitudinal analyses were conducted using non-parametric Friedman test, which provides a conservative and robust approach for repeated-measures data under these conditions. Data quality was monitored throughout the study period. Among trans men, two participants discontinued participation prior to study completion upon their own request. Among trans women, six participants discontinued participation, of whom three withdrew upon their own request, two discontinued due to time constraints, and one discontinued due to relocation. Within the cisgender male control cohort, three participants terminated participation for personal or logistical reasons (including time constraints). Participants who discontinued the study constituted the only cases with incomplete longitudinal data. For all statistical analyses, a complete-case approach was applied: Only individuals with data available at all predefined study visits (baseline, three, six, and 12 months) were retained. Accordingly, exclusion of dropouts yielded an analytical dataset with no missing values, thereby ensuring internal consistency and comparability across all evaluated variables. Results Population Baseline Characteristics Baseline characteristics are shown in Table 1 . No differences were observed in body weight, BMI, FM, or FFM between trans women and cisgender men, or between trans men and cisgender women ( all p > 0.05). Trans men were younger than cisgender women (median = 22.9 years, IQR = 20.6–24.6 years vs. median = 24.9 years, IQR = 23.9–28.7 years; p = 0.046). Ad libitum energy intake during the buffet and snack tests, as well as macronutrient composition (carbohydrate, fat, and protein), did not differ between trans women or men and cisgender participants ( all p > 0.05). Resting EE was also comparable between groups at baseline ( all p > 0.05). At baseline, total accelerometer wear time throughout the seven days of monitoring was similar across all groups ( all p > 0.05). The time spent at each activity level did not differ between trans women and cisgender men ( all p > 0.05), while trans men showed a shorter time spent at levels of moderate and vigorous activity compared to cisgender woman (activity level moderate: median = 89.4 min/day, IQR = 74.6–137.4 min/day vs. median = 131.0 min/day, IQR = 118.4–167.6 min/day, respectively; p = 0.04; activity level vigorous: median = 0.4 min/day, IQR = 0.00–1.2 min/day vs. median = 5.7 min/day, IQR = 3.1–9.9 min/day, respectively; p = 0.003). Serum estradiol and testosterone concentrations reach affirmed-gender reference ranges during GAHT At baseline, serum testosterone and estradiol concentrations did not differ between trans women and cisgender men, or between trans men and cisgender women ( all p > 0.05; Table 1 ). During 12 months of GAHT, serum testosterone concentrations declined in trans women (χ²[3] = 28.18, W = 0.63; median = 0.37 nmol/l, IQR = 0.31–0.47 nmol/l, p < 0.001) and serum estradiol concentrations increased (χ²[3] = 18.28, W = 0.44; median = 245.5 pmol/l, IQR = 55.8–419.5 nmol/l, p < 0.001; Fig. 2 A, C). In trans men, serum testosterone concentrations increased (χ²[3] = 28.88, W = 0.69; median = 16.94 nmol/l, IQR = 13.52–25.87 nmol/l, p 0.05; Fig. 2 B, D). Hormone concentrations at six and 12 months of GAHT did not change compared to after three months of GAHT ( all p > 0.05). In cisgender controls, serum testosterone and estradiol concentrations did not change throughout follow-up ( all p > 0.05; Fig. 2 ). At 12 months, serum testosterone concentrations were comparable between trans men and cisgender men (p > 0.05), while serum estradiol concentrations were higher in trans women compared with cisgender women (trans women: median = 245.5 pmol/l, IQR = 155.8–419.5 pmol/l; cisgender women: median = 65.2 pmol/l, IQR = 37.0–313.8 pmol/l; p = 0.046; Fig. 2 ). Increase in body weight and fat mass in trans women undergoing GAHT In trans women, body weight increased over 12 months of GAHT (χ²[3] = 16.54, W = 0.34, median = 73.4 kg, IQR = 68.1–82.5 kg, p 0.05), the change in body weight was due to an increase in FM (χ²[3] = 18.06, W = 0.38, median = 20.5 kg, IQR = 11.7–23.2 kg, p < 0.001; Fig. 3 B and C, respectively). In post-hoc analyses, the increase in FM reflected changes occurring across the entire observation period, whereas changes in body weight were largely driven by effects within the first six months of GAHT. Early changes across all body compartments predicted subsequent trajectories (body weight: r = 0.73–0.78, all p ≤ 0.002; Supplemental Figure S1A–C; FFM: r = 0.51–0.83, all p < 0.05; Supplemental Figure S1D–F; FM: r = 0.52–0.74, all p 0.05, data not shown). Body weight and fat-free mass increase in trans men undergoing GAHT In trans men undergoing 12 months of GAHT body weight (χ²[3] = 16.27, W = 0.32, median = 73.9 kg, IQR = 64.2–86.1 kg, p = 0.001), FFM (χ²[3] = 24.95, W = 0.49, median = 49.7 kg, IQR = 47.5–60.0 kg, p < 0.001), as well as FM increased (χ²[3] = 9.14, W = 0.18, median = 25.1 kg, IQR = 18.8–30.2 kg, p = 0.028; Figs. 3 D, E and F, respectively). Changes in body weight were driven by differences observed after 12 months of GAHT, as determined via post-hoc analysis. In trans men, absolute changes in body weight during GAHT showed consistent associations across timepoints. Body weight change after three months correlated with body weight change after six (r = 0.89, p < 0.001; Supplemental Figure S2A) and 12 months (r = 0.6, p = 0.012; Supplemental Figure S2B) of GAHT, as well as body weight change after six versus 12 months of GAHT (r = 0.77, p < 0.001; Supplemental Figure S2C). For FFM, absolute changes after three months were associated with changes after six months of GAHT (r = 0.64, p = 0.006; Supplemental Figure S2D), as were FFM changes after six and 12 months of GAHT (r = 0.53, p = 0.03; Supplemental Figure S2F). Comparable to body weight and FFM, changes in FM were associated during GAHT: Absolute FM changes after three months correlated with those at six months of GAHT (r = 0.89, p < 0.001; Supplemental Figure S2G). Changes in FM after six months correlated with those after 12 months of GAHT (r = 0.57, p = 0.018; Supplemental Figure S2I). Ad libitum energy intake increases during GAHT In trans women, total energy intake during the ad libitum buffet increased over 12 months of GAHT (χ²[3] = 13.73, W = 0.29, median = 1193 kcal, IQR = 974–1742 kcal, p = 0.003; Fig. 4 A). Intake of carbohydrate- and fat-derived calories did not change ( all p > 0.05; Fig. 4 B–D), whereas protein-derived calorie-intake increased (χ²[3] = 8.63, W = 0.18, median = 189 kcal, IQR = 157–240 kcal, p = 0.035; Fig. 4 D). Post-hoc analyses indicated that the increase in total caloric intake during the ad libitum buffet was attributable to changes in intake over 12 months of GAHT (p 0.05; Supplemental Figure S3A). In trans men, total energy intake during the ad libitum buffet increased over 12 months of GAHT (χ²[3] = 18.39, W = 0.36, median = 940 kcal, IQR = 784–1056 kcal, p < 0.001; Fig. 4 E). This change was primarily attributable to a higher intake of carbohydrate-derived calories (χ²[3] = 13.59, W = 0.26, median 375 kcal, IQR = 334–460 kcal, p 0.05; Fig. 4 G). Post-hoc analyses indicated that changes in caloric intake were primarily driven by differences between baseline and the 12-month endpoint (p 0.05; Supplemental Figure S3B). In cis men and cis women, total energy intake, macronutrient composition, and total energy intake during the snack test remained unchanged throughout the study ( all p > 0.05, data not shown). Body weight changes throughout the study period did not correlate with energy intake during the ad libitum buffet in any of the groups ( all p > 0.05, data not shown). Resting energy expenditure and physical activity unchanged during GAHT In trans women, REE correlated with FFM (baseline r = 0.67, p < 0.004, three months r = 0.68, p < 0.004, six months r = 0.8, p < 0.001, and 12 months r = 0.77, p 0.05; Fig. 5 A). To account for inter-individual differences in body composition, REE adjusted for FFM was calculated. Residual REE did not change during 12 months of GAHT (p > 0.05). Across all groups, baseline REE showed comparable group-level variability, with coefficients of variation (SD/mean×100) of 10.8% in trans men, 12.2% in trans women, 12.9% in cis women, and 10.4% in cis men. In trans men, REE correlated with FFM at each timepoint (baseline r = 0.63, p < 0.004, three months r = 0.71, p < 0.001, six months r = 0.76, p < 0.001, and 12 months r = 0.86, p 0.05; Fig. 5 B). Following adjustment for FFM using linear regression, residual REE did not change throughout the study (p > 0.05). In cisgender individuals during the entire study period, REE remained stable ( all p > 0.05). There were no changes in accelerometry based wear time and accelerometry-based assessment of physical activity over the 12-month period in trans women and men (Supplemental Figures S4 and S5), as well as controls ( all p > 0.05, respectively; data not shown). Discussion In this controlled, prospective study, GAHT served as a human model to examine how shifts in body composition are paralleled by changes of components of energy balance. Over 12 months, treatment-induced changes in fat-free mass and fat mass were accompanied by alterations in ad libitum energy intake, whereas resting energy expenditure and physical activity remained stable. Short-term changes in body weight and fat mass were consistent traits in trans women during GAHT. Although it remains unclear whether these alterations are independent of measurable changes in energy expenditure, paralleled dynamic changes underline the importance of fat-free mass and fat mass as determinants of energy balance control. Previous work reports that GAHT is associated with substantial, directionally consistent shifts in body composition — primarily increased fat mass and body mass index in feminizing treatment and increased fat-free mass with masculinizing treatment — while the magnitude and metabolic correlates of these changes vary across cohorts 19 , 40 – 44 . Nutritional and behavioral studies note altered dietary patterns (e.g., higher fat intake, reduced fruit/vegetable consumption, food insecurity, restrictive eating behaviors) in transgender adults, and highlight psychosocial contributors that may interact with hormonal effects to shape energy intake 42 , 45 , 46 . Together, these works indicate that GAHT provides a clinically relevant context in which hormonal, behavioral, and social factors converge to influence body composition and energy intake, but important questions remain about the proximate physiological mechanisms linking compositional change to habitual intake 45 , 46 . Given these consistent, treatment-related shifts in fat and lean tissue 19 , 40 – 44 , it becomes essential to examine how changes in body composition translate into actual energy balance. Despite a small study population which limits the ability to translate sex hormone-induced changes in body composition to direct effects on energy homeostasis, to our knowledge, the present exploratory study is the first to provide a comprehensive assessment of the effects of GAHT on energy balance. Furthermore, current work aligns with principles of energy balance regulation, that highlight the relevance of lean mass as a putative driver of energy intake: To couple intake with metabolic demand, energy expenditure has been proposed as key signal for daily energy intake, driven by fat-free mass as its principal metabolic determinant 47 , 48 . Fat-free mass, as the main contributor to resting energy intake, predicts ad libitum energy intake 6 , 47 , 49 , and multiple studies report positive associations between fat-free mass, energy expenditure and energy intake 6 , 9 , 49 . However, it remains debated whether the proximate cue is fat-free mass per se or the energy expenditure it generates: Mediation analyses indicate that much of the association of fat-free mass with intake is transmitted via resting or 24-h energy expenditure 50 , 51 , whereas direct effects of fat-free mass are small. Finally, the role of energy expenditure in longitudinal weight change is inconsistent across populations 52 : Lower 24-h energy expenditure predicts weight gain in some cohorts 52 , 53 , but higher resting energy expenditure has been associated with weight gain in others 54 , suggesting that individual differences in how intake adapts to basal energy requirements critically modulate long-term energy balance. Our study is limited to describe a change in energy intake that is paralleled by the increase in fat-free mass – and no change in resting energy expenditure or physical activity-related energy expenditure. Nonetheless, these results support the relevance of fat-free mass as a metabolic determinant of energy intake in an understudied population. Regulation of energy homeostasis is complex and integrates humoral, neural and behavioral mechanisms: Adipose tissue provides a tonic signal of energy stores and gut-brain peptides together with central and vagal circuits modulate hunger and satiety 55 , 56 . Eating behavior — shaped by internal cues, hedonic processes, learned associations, and environmental cues — is a primary regulator of human energy intake 57 – 62 . Thus, besides coupling of metabolic demand with energy expenditure, a more complex assessment of energy homeostasis needs to integrate multiple determinants. In the present study, this may be primarily underlined by observed changes in energy intake during GAHT in trans women: Despite its role as a determinant of energy expenditure in humans 48 , notably, in this subgroup changes in energy intake were accompanied by altered fat mass, and not fat-free mass. Irrespective of the mechanisms driving the observed increases in ad libitum energy intake during GAHT, our findings highlight that early changes in body weight and fat mass represent consistent short-term traits in trans women. Given the elevated prevalence of overweight and obesity in transgender populations 17 , 18 , identifying and monitoring these shifts at the outset of therapy may allow for timely interventions aimed at preventing unfavorable weight trajectories. Although limited in sample size, our study provides a comprehensive assessment of both sides of the energy balance equation under free-living conditions, leveraging repeated intra-individual measurements to characterize early physiological adaptations during gender-affirming hormone therapy. By focusing on the initial phase of treatment — when phenotypic changes first emerge 63 — this predictive approach may offer clinically meaningful insight into the development of body weight trajectories and opportunities to mitigate related metabolic risk. Despite the strengths of a controlled study design, repeated measurements, intra-individual comparisons, and multiple follow-ups, certain limitations need to be considered: Future investigations in this population would benefit from assessment of 24-hour energy expenditure, allowing for the detection of more subtle changes relative to alterations in fat-free and fat mass. Notably, variation in resting energy expenditure assessment may have limited the ability to detect changes within this measure. Likewise, more precise measures of body composition, such as dual-energy X-ray absorptiometry, could enhance the characterization of anthropometric determinants of energy expenditure. While our assessment of ad libitum energy intake provides an initial insight, the buffet or snack-based setting represents a controlled and artificial environment. More naturalistic or prolonged assessments of spontaneous energy intake may therefore be necessary, particularly to disentangle homeostatic from hedonic drivers of food consumption. Given the exploratory nature of our findings, especially regarding potential differences between trans women versus trans men, a more detailed investigation of snack intake patterns may yield further mechanistic understanding. Taken together, our results indicate that sex-hormone treatment-induced compositional shifts can be accompanied by increased energy intake in the absence of detectable changes in measured energy expenditure, implying that alterations in fat and lean mass may modulate appetitive behavior and short-term energy balance. These findings underscore the value of early monitoring of body composition and intake during periods of rapid phenotypic change and motivate longer, mechanistic studies to delineate homeostatic versus hedonic drivers and their relevance for long-term weight trajectories. Declarations I hereby confirm that the study entitled “Hormones and Health Study” (Investigation of the effects of testosterone and estrogen on eating behavior, metabolism, and the cardiovascular system in transsexual patients undergoing cross-sex hormone therapy) was reviewed and approved by the Ethics Committee of the Medical Faculty of the University of Leipzig, Germany (reference number: 023/20-ek) . The Ethics Committee reviewed the submitted study documents and raised no objections to the conduct of the study Sources of support Helmholtz Institute for Metabolic, Obesity and Vascular Research Intramural Research Fund; HS received financial support for this study from Besins Healthcare, Berlin, Germany. The funder had no role in the study design, data collection, data analysis, interpretation of results, or the writing of the manuscript. Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany´s Excellence Strategy – EXC-3105/1–533765739. Conflict of Interest: Haiko Schlögl received third party funding for this study from Besins Healthcare. Matthias Blüher received honoraria as a consultant and speaker from Amgen, AstraZeneca, Bayer, Boehringer-Ingelheim, Lilly, Novo Nordisk, Novartis, and Sanofi. All other authors declare no conflict of interest. Author contributions Martin Kaar: data analysis, conduct of the study, writing, reviewing and editing of the manuscript; Pauline Zimmermann: conduct of the study, reviewing and editing of the manuscript; Theresa Bokeloh: conduct of the study, reviewing and editing of the manuscript; Lotta Moll: conduct of the study, reviewing and editing of the manuscript; Franziska Labinski: conduct of the study, reviewing and editing of the manuscript; Florian Woehlecke: conduct of the study, reviewing and editing of the manuscript; Matthias Blüher: funding acquisition, resources, reviewing and editing of the manuscript; Michael Stumvoll: funding acquisition, resources, reviewing and editing of the manuscript; Haiko Schlögl: conceptualization, funding acquisition, conduct of the study, project administration, writing, reviewing and editing of the manuscript; Sascha Heinitz: conceptualization, conduct of the study, project administration, writing, reviewing and editing of the manuscript. Acknowledgements We thank all participants for their participation in the study. We also thank Natalia Schischkarjow, Björn Drechsler-Kryst, Lotte Oldenburg, Mathilda Klammt, and Antonia Stengler for their assistance in conducting the study. References Hall KD, Heymsfield SB, Kemnitz JW, Klein S, Schoeller DA, Speakman JR (2012) Energy balance and its components: implications for body weight regulation. Am J Clin Nutr 95(4):989–994 Blundell J, Gibbons C, Caudwell P, Finlayson G, Hopkins M (2015) Appetite control and energy balance: impact of exercise. Obes Rev 16:67–76 Weise CM, Hohenadel MG, Krakoff J, Votruba SB (2014) Body composition and energy expenditure predict ad-libitum food and macronutrient intake in humans. Int J Obes 38(2):243–251 Piaggi P, Vinales KL, Basolo A, Santini F, Krakoff J (2018) Energy expenditure in the etiology of human obesity: spendthrift and thrifty metabolic phenotypes and energy-sensing mechanisms. 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Scand J Med Sci Sports 27(12):1814–1823. 10.1111/sms.12795 Echevarría-Polo M, Marín PJ, Pueyo E, Ramos Maqueda J, Garatachea N (2025) Variability and Reliability of the Axivity AX6 Accelerometer in Technical and Human Motion Conditions. Sensors 25(8):2480. 10.3390/s25082480 Weyer C, Snitker S, Rising R, Bogardus C, Ravussin E (1999) Determinants of energy expenditure and fuel utilization in man: effects of body composition, age, sex, ethnicity and glucose tolerance in 916 subjects. Int J Obes 23(7):715–722. 10.1038/sj.ijo.0800910 Gois Í, Rodrigues FB, Pereira M, Dias-da-Silva MR, Gomes SM (2025) Body mass index and body composition changes in transgender people undergoing gender-affirming hormone therapy: a systematic review and meta-analysis. Reviews Endocr Metabolic Disorders. :1–17 Ford K, Huggins E, Sheean P (2022) Characterising body composition and bone health in transgender individuals receiving gender-affirming hormone therapy. 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Adv Clin Experimental Med 34(5):663–667 Ravussin E, Lillioja S, Anderson TE, Christin L, Bogardus C (1986) Determinants of 24-hour energy expenditure in man. Methods and results using a respiratory chamber. J Clin Invest 78(6):1568–1587 Weyer C, Snitker S, Rising R, Bogardus C, Ravussin E (1999) Determinants of energy expenditure and fuel utilization in man: effects of body composition, age, sex, ethnicity and glucose tolerance in 916 subjects. Int J Obes Relat Metabolic Disorders 23(7):715–722 Weise CM, Hohenadel MG, Krakoff J, Votruba SB (2014) Body composition and energy expenditure predict ad-libitum food and macronutrient intake in humans. Int J Obes (Lond) Feb 38(2):243–251. 10.1038/ijo.2013.85 Piaggi P, Thearle MS, Krakoff J, Votruba SB (2015) Higher Daily Energy Expenditure and Respiratory Quotient, Rather Than Fat-Free Mass, Independently Determine Greater ad Libitum Overeating. 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J Clin Investig 121(6):2087–2093 Berthoud H-R, Morrison C (2008) The brain, appetite, and obesity. Annu Rev Psychol 59(1):55–92 French SA, Epstein LH, Jeffery RW, Blundell JE, Wardle J (2012) Eating behavior dimensions. Associations with energy intake and body weight. A review. Appetite 59(2):541–549 Higgins KA, Hudson JL, Hayes AM et al (2022) Systematic review and meta-analysis on the effect of portion size and ingestive frequency on energy intake and body weight among adults in randomized controlled feeding trials. Adv Nutr 13(1):248–268 Gladding JM, Bradfield LA, Kendig MD (2023) Diet and obesity effects on cue-driven food-seeking: insights from studies of Pavlovian-instrumental transfer in rodents and humans. Front Behav Neurosci 17:1199887 Robinson E, Almiron-Roig E, Rutters F et al (2014) A systematic review and meta-analysis examining the effect of eating rate on energy intake and hunger. Am J Clin Nutr 100(1):123–151 Stubbs JR, Horgan G, Robinson E, Hopkins M, Dakin C, Finlayson G (2023) Diet composition and energy intake in humans. Philosophical Trans Royal Soc B 378(1888):20220449 Chamorro R, Jouffe C, Oster H, Uhlenhaut NH, Meyhöfer SM (2023) When should I eat: a circadian view on food intake and metabolic regulation. Acta Physiol 237(3):e13936 Meyer G, Boczek U, Bojunga J (2020) Hormonal gender reassignment treatment for gender dysphoria. Deutsches Ärzteblatt international 117(43):725 Additional Declarations The authors declare potential competing interests as follows: Haiko Schlögl received third party funding for this study from Besins Healthcare. Matthias Blüher received honoraria as a consultant and speaker from Amgen, AstraZeneca, Bayer, Boehringer-Ingelheim, Lilly, Novo Nordisk, Novartis, and Sanofi. All other authors declare no conflict of interest Supplementary Files SupFigure1.png Supplemental figure S1. Consistent trajectories of body composition change during hormone therapy in trans women. Changes in body weight after three months predicted subsequent changes at six and 12 months of GAHT (A and B, respectively), and weight changes at six months predicted changes at 12 months (C). Fat-free mass showed consistent associations between three and six months, three and 12 months, and between six and 12 months of GAHT (D, E, and F, respectively). Fat mass changes correlated across the same intervals (G–I). After exclusion of two outliers for body weight, the overall correlation patterns remained consistent across all intervals (three to six months r=0.60, p=0.02; three to 12 months r=0.60, p=0.022; six to 12 months r=0.67, p=0.01). Abbreviation: GAHT, gender-affirming hormone therapy. SupFigure2.png Supplemental figure S2. Consistent trajectories of body composition change during hormone therapy in trans men.Changes in body weight after three months predicted subsequent changes at six and 12 months of GAHT (A and B, respectively). Similarly, weight changes at six months predicted changes at 12 months (C). Changes in fat-free mass were positively correlated between three and six months and between six and 12 months (D, F), and fat mass changes showed consistent associations across the same time intervals (G, I). After exclusion of one outlier, results were robust to this exclusion, with consistent associations for body weight (3 to 6 months: r=0.87, p<0.001; 3 to 12 months: r=0.52, p<0.04; 6 to 12 months: r=0.73, p=0.02). Abbreviation: GAHT, gender-affirming hormone therapy. SupFigure3.png Supplemental figure S3. Snack test energy intake remained unchanged during hormone therapy. Snack test energy intake remained stable across all timepoints in trans women (A, p>0.05). Comparably, trans men showed no change in snack food energy intake during 12 months of gender-affirming hormone therapy (B, p>0.05). Error bars representing the median and interquartile range (IQR). SupFigure4.png Supplemental figure S4. Accelerometry wear time. In trans women and men, valid daily wear-time (hours/day) remained stable across all study visits (p>0.05). Error bars representing the median and interquartile range (IQR). SupFigure5.png Supplemental figure S5. Accelerometry-derived weekly hours at distinct activity intensities. Activity intensities were classified using metabolic equivalent of task (MET) cut-points established for wrist-mounted AX6 accelerometry and summarized into conventional intensity bands: light (1.5 to <4 MET), moderate (4 to 0.05). Cisgender control groups also exhibited no temporal differences across the same observation window ( all p>0.05, data not shown). Error bars representing the median and interquartile range (IQR). SupTable1.png Supplemental Table S1. Preparations and dosages used by transgender patients undergoing gender-affirming hormone therapy. Hormone therapy was administered in accordance with established international guidelines. The decision, estradiol gel or patch and testosterone gel or i.m. injection was based on individual patient preferences. Cyproterone acetate was provided in oral tablet form. I.m., intramuscularly. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8824402","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":587843643,"identity":"c53273f2-784e-41a4-bb69-7a77fa0de7bb","order_by":0,"name":"Martin Kaar","email":"","orcid":"https://orcid.org/0009-0004-3064-9094","institution":"Department of Gynecology and Obstetrics, TU Dresden Medical Faculty Carl Gustav Carus, Dresden, 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1","display":"","copyAsset":false,"role":"figure","size":95197,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 1. Study outline of the four identical outpatient visits performed over a 12-month period. \u003c/strong\u003eFor seven days prior to each visit, patients wore an activity monitor (Axivity AX3). During the outpatient visits, anthropometric measurements were obtained, resting energy expenditure was assessed using indirect calorimetry, and body composition was measured using bioelectrical impedance analysis. Ad libitum food intake and snack food intake were assessed at each visit. Abbreviation: GAHT, gender-affirming hormone therapy.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8824402/v1/5a6a76d536dd8e66d70e1f41.png"},{"id":104975108,"identity":"28e1d098-e538-4fdf-826b-06c41eebf23d","added_by":"auto","created_at":"2026-03-19 11:56:45","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":174845,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 2. Serum hormone trajectories during the 12 months of the study.\u003c/strong\u003eSerum testosterone concentrations decreased, and serum estradiol concentrations increased in trans women undergoing GAHT (A, C), whereas serum testosterone increased, and serum estradiol remained unchanged in trans men (B, D). Compared to cisgender individuals, differences in serum hormone concentrations after 12 months were observed for serum testosterone in both trans women and men. Serum estradiol concentrations differed after 12 months of GAHT in trans women compared to cisgender individuals. Exclusion of four participants using oral contraceptives did not affect the observed results, with no relevant changes in effect estimates or statistical significance (\u003cem\u003eall\u003c/em\u003e p≥0.05). *** p\u0026lt;0.001. Error bars representing median and interquartile range (IQR). Abbreviation: GAHT, gender-affirming hormone therapy.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8824402/v1/2aa7de623ddc40fb725ecdcb.png"},{"id":104975116,"identity":"af1878a5-00de-4628-919b-aa24a8ff116c","added_by":"auto","created_at":"2026-03-19 11:56:47","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":127947,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 3. Body weight and body composition during 12 months of hormone therapy. \u003c/strong\u003eIn trans women, body weight and fat mass increased, with no change in fat-free mass over time (A–C). Relative to baseline, body weight and fat-free mass increased in trans men, whereas fat mass did not change (D–F). *p\u0026lt;0.05, **p\u0026lt;0.01, ***p\u0026lt;0.001. Error bars representing median and interquartile range (IQR).\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8824402/v1/f045013c19bb75a1f2359399.png"},{"id":104975111,"identity":"74cb7a37-74b2-4c6c-8562-96853de489f4","added_by":"auto","created_at":"2026-03-19 11:56:46","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":114903,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 4. Total energy intake during 30-minute \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ead libitum \u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003ebuffet. \u003c/strong\u003eIn trans women, the increase in total energy intake (A) was accompanied by a relative increase in protein intake (D). In trans men, total energy intake (E) increased during 12 months of hormone therapy, driven by an increase in carbohydrate (F) and protein (D) intake. *p\u0026lt;0.05). **p\u0026lt;0.01, ***p\u0026lt;0.001. Error bars representing median and interquartile range (IQR).\u003c/p\u003e","description":"","filename":"Figure4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8824402/v1/5d1d90a43397911843629f28.jpg"},{"id":104975085,"identity":"83959b5a-60d2-4519-9a67-73d84cfc2916","added_by":"auto","created_at":"2026-03-19 11:56:44","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":74766,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eFigure 5. Resting energy expenditure remained unchanged during hormone therapy. \u003c/strong\u003eThere were no changes in resting energy expenditure across all timepoints in trans women or trans men (\u003cem\u003eall\u003c/em\u003ep\u0026gt;0.05). Error bars representing median and interquartile range (IQR).\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8824402/v1/47adff0f4dce85d7236d6508.png"},{"id":104975160,"identity":"b462095c-8b5c-490e-a486-48363c9eff30","added_by":"auto","created_at":"2026-03-19 11:57:03","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1726374,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8824402/v1/a736d6d9-e7db-48af-afaa-969670115a82.pdf"},{"id":104975130,"identity":"23ad4c8b-e006-4b59-967e-b4aa19a33c3f","added_by":"auto","created_at":"2026-03-19 11:56:57","extension":"png","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":266593,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental figure S1. Consistent trajectories of body composition change during hormone therapy in trans women.\u003c/strong\u003e Changes in body weight after three months predicted subsequent changes at six and 12 months of GAHT (A and B, respectively), and weight changes at six months predicted changes at 12 months (C). Fat-free mass showed consistent associations between three and six months, three and 12 months, and between six and 12 months of GAHT (D, E, and F, respectively). Fat mass changes correlated across the same intervals (G–I). After exclusion of two outliers for body weight, the overall correlation patterns remained consistent across all intervals (three to six months r=0.60, p=0.02; three to 12 months r=0.60, p=0.022; six to 12 months r=0.67, p=0.01). Abbreviation: GAHT, gender-affirming hormone therapy.\u003c/p\u003e","description":"","filename":"SupFigure1.png","url":"https://assets-eu.researchsquare.com/files/rs-8824402/v1/06e4cfa554e0a4ae967b3e36.png"},{"id":104975113,"identity":"1dc98d58-8f93-498f-ae34-c7f85971ad1c","added_by":"auto","created_at":"2026-03-19 11:56:46","extension":"png","order_by":2,"title":"","display":"","copyAsset":false,"role":"supplement","size":263822,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental figure S2. Consistent trajectories of body composition change during hormone therapy in trans men.\u003c/strong\u003eChanges in body weight after three months predicted subsequent changes at six and 12 months of GAHT (A and B, respectively). Similarly, weight changes at six months predicted changes at 12 months (C). Changes in fat-free mass were positively correlated between three and six months and between six and 12 months (D, F), and fat mass changes showed consistent associations across the same time intervals (G, I). After exclusion of one outlier, results were robust to this exclusion, with consistent associations for body weight (3 to 6 months: r=0.87, p\u0026lt;0.001; 3 to 12 months: r=0.52, p\u0026lt;0.04; 6 to 12 months: r=0.73, p=0.02). Abbreviation: GAHT, gender-affirming hormone therapy.\u003c/p\u003e","description":"","filename":"SupFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8824402/v1/f92b157bd45fae85e84197ab.png"},{"id":104975117,"identity":"883f1914-e152-41db-bfb9-4acb09fc1201","added_by":"auto","created_at":"2026-03-19 11:56:47","extension":"png","order_by":3,"title":"","display":"","copyAsset":false,"role":"supplement","size":96554,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental figure S3. Snack test energy intake remained unchanged during hormone therapy. \u003c/strong\u003eSnack test energy intake remained stable across all timepoints in trans women (A, p\u0026gt;0.05). Comparably, trans men showed no change in snack food energy intake during 12 months of gender-affirming hormone therapy (B, p\u0026gt;0.05). Error bars representing the median and interquartile range (IQR).\u003c/p\u003e","description":"","filename":"SupFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8824402/v1/05f3fa0979e4cf49a8d0a37d.png"},{"id":104975114,"identity":"16af8557-83ba-4b47-bbd4-2b90df6bdba0","added_by":"auto","created_at":"2026-03-19 11:56:47","extension":"png","order_by":4,"title":"","display":"","copyAsset":false,"role":"supplement","size":90989,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental figure S4. Accelerometry wear time. \u003c/strong\u003eIn trans women and men, valid daily wear-time (hours/day) remained stable across all study visits (p\u0026gt;0.05). Error bars representing the median and interquartile range (IQR).\u003c/p\u003e","description":"","filename":"SupFigure4.png","url":"https://assets-eu.researchsquare.com/files/rs-8824402/v1/7752c91b0cbed2baa19d8efb.png"},{"id":104975120,"identity":"e8508d77-b72e-45a0-bde3-e0c14f3e6751","added_by":"auto","created_at":"2026-03-19 11:56:48","extension":"png","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":215716,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental figure S5. Accelerometry-derived weekly hours at distinct activity intensities. \u003c/strong\u003eActivity intensities were classified using metabolic equivalent of task (MET) cut-points established for wrist-mounted AX6 accelerometry and summarized into conventional intensity bands: light (1.5 to \u0026lt;4 MET), moderate (4 to \u0026lt;7 MET), and vigorous (≥7 MET). Trans women and men demonstrated stable minutes per day spent in light (A and D), moderate (B and E), and vigorous (C and F) activity across all study visits (\u003cem\u003eall\u003c/em\u003e p\u0026gt;0.05). Cisgender control groups also exhibited no temporal differences across the same observation window (\u003cem\u003eall\u003c/em\u003e p\u0026gt;0.05, data not shown). Error bars representing the median and interquartile range (IQR).\u003c/p\u003e","description":"","filename":"SupFigure5.png","url":"https://assets-eu.researchsquare.com/files/rs-8824402/v1/090b2590cf56aca008f7d0cb.png"},{"id":104975129,"identity":"b6b2cc7f-44b0-4653-b473-54dbc4adade7","added_by":"auto","created_at":"2026-03-19 11:56:56","extension":"png","order_by":6,"title":"","display":"","copyAsset":false,"role":"supplement","size":114580,"visible":true,"origin":"","legend":"\u003cp\u003e\u003cstrong\u003eSupplemental Table S1. Preparations and dosages used by transgender patients undergoing gender-affirming hormone therapy. \u003c/strong\u003eHormone therapy was administered in accordance with established international guidelines. The decision, estradiol gel or patch and testosterone gel or i.m. injection was based on individual patient preferences. Cyproterone acetate was provided in oral tablet form. I.m., intramuscularly.\u003c/p\u003e","description":"","filename":"SupTable1.png","url":"https://assets-eu.researchsquare.com/files/rs-8824402/v1/c9ae4615972e34a973a75dcc.png"}],"financialInterests":"The authors declare potential competing interests as follows: Haiko Schlögl received third party funding for this study from Besins Healthcare. Matthias Blüher received honoraria as a consultant and speaker from Amgen, AstraZeneca, Bayer, Boehringer-Ingelheim, Lilly, Novo Nordisk, Novartis, and Sanofi. All other authors declare no conflict of interest","formattedTitle":"\u003cp\u003e\u003cstrong\u003eSex-hormone induced short-term changes in body composition are paralleled by an increase in \u003c/strong\u003e\u003cem\u003e\u003cstrong\u003ead libitum\u003c/strong\u003e\u003c/em\u003e\u003cstrong\u003e energy intake\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eLong-term body weight is determined by the balance between energy intake (EI) and energy expenditure (EE). Energy expenditure modulates EI through both physiological signals and behavior \u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e, and mounting evidence indicates a tight coupling between an individual\u0026rsquo;s energetic demands and appetitive drive \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e,\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. In particular, fat-free mass (FFM) \u0026mdash; the major anthropometric determinant to resting EE \u0026mdash; has emerged as a strong predictor of \u003cem\u003ead libitum\u003c/em\u003e energy intake \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e, and several studies report positive associations among FFM, measures of EE, and food consumption in humans \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e,\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eGiven the central role of EI and EE in the pathogenesis of obesity and its comorbidities, elucidating the determinants and modulators of each arm of the energy balance equation has become a priority in metabolic research \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e,\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. Two key predictors of EE are FFM and fat mass (FM), which together account for the bulk of resting energy requirements \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e. Changes in FFM and FM over time therefore modify EE, and \u0026mdash; through the aforementioned feedback mechanisms \u0026mdash; may secondarily influence EI \u003csup\u003e13\u003c/sup\u003e. Conversely, some drivers of EI operate independently of EE, such as food palatability, social cues, and neuroendocrine factors \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Alterations in body composition may thus, through their impact on EE, contribute to changes in EI, while changes in intake could in turn modify body composition, illustrating the bidirectional interplay between these variables. Crucially, these relationships are not necessarily perfectly compensatory: When EE chronically exceeds EI, net weight loss ensues, whereas a sustained positive energy balance leads to body weight gain and obesity \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e,\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e. Thus, mismatches between energy demand (as reflected by FFM and EE) and actual EI can lead to gradual and sustained alterations in body mass over time.\u003c/p\u003e \u003cp\u003eAmong individuals undergoing gender-affirming hormone therapy (GAHT) the risk to develop overweight and obesity is increased \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. Through the administration of estradiol or testosterone, GAHT induces predictable short-term alterations in FFM and FM \u003csup\u003e19\u003c/sup\u003e, which may contribute to body weight gain in this population. Although clinically relevant, a comprehensive assessment of both sides of the energy balance equation \u0026mdash; EE and EI \u0026mdash; in the setting of GAHT is lacking. To address this gap, in an exploratory approach we conducted a prospective, controlled, cohort study to investigate short-term adaptations in body composition, EE, and \u003cem\u003ead libitum\u003c/em\u003e EI during GAHT.\u003c/p\u003e"},{"header":"Subjects and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eSubjects\u003c/h2\u003e \u003cp\u003eThe current study includes data from individuals recruited between January 2021 and November 2025 at the endocrinological outpatient clinic of the University Hospital Leipzig as part of a clinical investigation designed to assess the effects of GAHT on metabolic, vascular, and behavioral outcome parameters (clinicaltrials.gov registration number NCT04838249) \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e,\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e. Following assessment of medical history, physical examination, and basic laboratory parameters, and having provided written informed consent, 50 consented volunteers were admitted to the clinical research unit to participate in the study. According to the study protocol, exclusion criteria included uncontrolled chronic diseases (e.g., hypertension, heart failure, diabetes mellitus, malignancies, inflammatory or infectious conditions), endocrine disorders (e.g., hypercortisolism, hypo-/hyperthyroidism, pituitary disease), or psychiatric illness requiring hospitalization, as determined by medical history and laboratory assessment.\u003c/p\u003e \u003cp\u003eTransgender participants were diagnosed with gender incongruence according to ICD-10 F64.0 or ICD-11 HA60 prior to recruitment at the time of first presentation to the outpatient clinic. In total, 16 trans women (male-to-female transgender) and 17 trans men (female-to-male transgender) were included with indication to perform GAHT. Prior to the study, none of the participants had ever received hormone therapy. Ten cisgender women, and seven cisgender men served as control group and were recruited through public advertising and institutional networks. The control group did not receive GAHT (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eBaseline characteristics of the study population.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"7\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eCharacteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTrans women (male-to-female transgender)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eCisgender men\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eTrans men (female-to-male transgender)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eCisgender\u003c/p\u003e \u003cp\u003ewomen\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;16\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;7\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;17\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003en\u0026thinsp;=\u0026thinsp;10\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003ep\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAge (years)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e24.9 (5.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e24.6 (4.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e22.9 (4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e24.9 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003e0.046\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eWeight (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69.8 (19.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e73.9 (10.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e71.5 (24.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e66.3 (23.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.38\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBody mass index (kg/m\u003csup\u003e2\u003c/sup\u003e)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e22.5 (7.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21.9 (3.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.7 (7.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e23.6 (3.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.60\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e14.2 (13.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e14.0 (2.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e25.5 (13.3)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e17.8 (10.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eFat-free mass (kg)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e58.1 (8.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e59.7 (9.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.37\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48.9 (11.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49.4 (13.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eResting energy expenditure (kcal/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1789 (364.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1810 (232.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1528 (248)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1538 (142)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.75\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuffet energy intake (kcal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1061 (496)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1240 (860)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e718 (325)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e735 (308)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuffet carbohydrate intake (kcal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e317 (270)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e590 (290)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e320 (165)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e303 (144)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.68\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuffet fat intake (kcal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e411 (272)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e511 (494)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.58\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e329 (188)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e344 (204)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBuffet protein intake (kcal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e154 (166)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e138 (61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e94 (47)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e105 (95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.79\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSnack food energy intake (kcal)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e347 (756)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e317 (483)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e364 (336)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e282 (784)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.71\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTestosterone serum concentration (nmol/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.6 (7.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18.9 (5.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.9 (0.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e0.8 (0.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.46\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEstradiol serum concentration (pmol/l)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e92.6 (26.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e114.5 (94.9)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.21\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e284.9 (230.5)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e148.0 (367.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.18\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAccelerometer wear time (hours/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e16.1 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e16.4 (4.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e16.6 (4.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e16.2 (3.1)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActivity level sedentary (min/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1250.0 (115.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1227.0 (105.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.45\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1280.0 (96.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1218.0 (84.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActivity level light (min/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e70.3 (44.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.7 (20.0)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e59.8 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e84. 6 (39.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActivity level moderate (min/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e118.9 (82.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e140.3 (60.4)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e89.4 (62.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e131.0 (49.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003e0.04\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eActivity level vigorous (min/day)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.6 (8.7)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e6.6 (25.6)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c4\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e0.4 (1.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.7 (6.8)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e \u003cp\u003e\u003cem\u003e0.003\u003c/em\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy protocol\u003c/h3\u003e\n\u003cp\u003eData was collected at four standardized timepoints: baseline (prior to GAHT initiation), and at three, six, and 12 months of ongoing GAHT (Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e1\u003c/span\u003e). For cisgender controls, measurements were obtained at matching intervals and except for GAHT, study protocol was identical for both patients and controls. All study visits took place in the morning after an overnight fast. Participants were instructed to refrain from vigorous physical activity, alcohol, and caffeine for at least 24 hours prior to each visit.\u003c/p\u003e\n\u003ch3\u003eGender-affirming hormone therapy\u003c/h3\u003e\n\u003cp\u003eHormonal treatment was administered in accordance with international guidelines \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. Trans women received estradiol, either orally or via transdermal application, in combination with cyproterone acetate for androgen suppression. Trans men were treated with testosterone, administered either as undecanoate or enanthate esters. The specific preparations and dosages used in the study are listed in Supplemental Table S1.\u003c/p\u003e \u003cp\u003eSerum concentrations of estradiol and testosterone were monitored throughout the study period as part of routine clinical follow-up at above mentioned time points. Dosages were individually adjusted to achieve hormone levels within the physiological target range for the perceived gender. All treatment regimens were managed by experienced endocrinologists following established standards of care \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e,\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e. To address the effect of GAHT on outcome measures, therapy was initiated upon completion of baseline assessments.\u003c/p\u003e\n\u003ch3\u003eAnthropometry and bioelectrical impedance analysis\u003c/h3\u003e\n\u003cp\u003eAnthropometric measurements were obtained under standardized conditions after an overnight fast in the morning. Body height and weight were measured using a calibrated stadiometer and a digital scale, with participants wearing light clothing and no shoes, according to site-specific standardized protocols. Body composition, including total FM and FFM, was assessed by multifrequency bioelectrical impedance analysis (BIA; Biacorpus RX 4004M, Medi Cal Healthcare GmbH, Karlsruhe, Germany), following established methodological standards \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e. After voiding the bladder, BIA was performed in the fasting state following a 10-minute horizontal rest at a controlled ambient temperature. Electrodes were placed according to manufacturer instructions, and body composition parameters were derived through the device\u0026rsquo;s integrated prediction equations using the participants biological sex \u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003ch3\u003eResting energy expenditure\u003c/h3\u003e\n\u003cp\u003eResting energy expenditure (REE) was assessed by indirect calorimetry (Q-NRG, COSMED, Rome, Italy) using a ventilated hood system. Measurements were conducted in the morning after an overnight fast, with participants lying in a horizontal position in a thermoneutral environment (22\u0026ndash;24\u0026deg;C). After at least 15 minutes of rest, respiratory gas exchange was recorded continuously for 20 minutes while participants remained awake and motionless. To minimize potential arousal, participants were allowed to watch emotionally neutral nature documentaries on a provided tablet.\u003c/p\u003e \u003cp\u003eREE was calculated from oxygen consumption and carbon dioxide production using the Weir Eq.\u0026nbsp;2\u003csup\u003e6\u003c/sup\u003e. The protocol followed established recommendations for indirect calorimetry \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e, including pre-measurement abstention from caffeine, nicotine, and vigorous activity, and calibration of the device before each session. After achieving a steady state, a 10-minute interval was selected for REE calculation. The Q-NRG system has been validated for accuracy and repeatability \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003e \u003cb\u003eAd libitum\u003c/b\u003e \u003cb\u003efood intake\u003c/b\u003e\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eBuffet\u003c/h2\u003e \u003cp\u003eEnergy intake was assessed using a customized \u003cem\u003ead libitum\u003c/em\u003e buffet paradigm, as previously described \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. Prior to the baseline visit, participants selected their preferred food items (omnivore, vegetarian, or vegan options) via a digital questionnaire. For each participant, the selected set of buffet items was kept identical for all subsequent study visits. The buffet took place between 10:30 and 11:00 a.m. in a distraction-free room with 30-minute unrestricted access to customized food. External stimuli were reduced, and electronic devices were not permitted. All food items were weighed before and after the session to determine kilocalories consumed. Energy and macronutrient values were obtained from manufacturer-provided nutritional labels and standardized food composition databases \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eSnack test\u003c/h3\u003e\n\u003cp\u003eA snack test was conducted after the end of the buffet meal to assess \u003cem\u003ead libitum\u003c/em\u003e energy intake of highly palatable snack foods, as previously described \u003csup\u003e\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e,\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Participants were presented with a standardized selection of snack items (potato chips, peanuts, cookies, and candy) and instructed to taste and eat as much as they desired. They were left alone in the room for 10 minutes and unaware that energy intake was being measured. Snack food consumption (grams and kilocalories) was determined by weighing the food items before and after the session. Participants were able to customize the snacks available via a digital questionnaire (omnivore, vegetarian, or vegan options) based on individual preferences and dietary restraints. The selection was kept identical for all subsequent study visits.\u003c/p\u003e\n\u003ch3\u003ePhysical activity monitoring via accelerometry\u003c/h3\u003e\n\u003cp\u003eTo account for inter-individual differences in habitual physical activity potentially contributing to body weight change, participants wore a triaxial accelerometer (AX6, Axivity Ltd., Newcastle, United Kingdom) on the wrist of the non-dominant hand for seven consecutive days preceding each study visit. Devices were configured using the manufacturer\u0026rsquo;s Open Movement GUI software. Raw acceleration data were processed using the open-source R package GGIR, which applies standardized algorithms for autocalibration, data cleaning, and signal processing \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e,\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. A minimum wear time of 16 hours per day on at least four days was required for data inclusion, following established methodological standards \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e,\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e. Extracted metrics included time spent in light, moderate, and vigorous activity levels as well as overall physical activity volume \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. All metrics were computed using validated classification thresholds for wrist-worn accelerometers \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e,\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. Activity intensity was categorized according to metabolic equivalent of task (MET), using standardized intensity bands established for wrist-worn accelerometry: light (1.5 to \u0026lt;\u0026thinsp;4 MET; activities of daily living), moderate (4 to \u0026lt;\u0026thinsp;7 MET; sustained lifestyle movement), and vigorous (\u0026ge;\u0026thinsp;7 MET; high-intensity physical activity). Device-specific variability and reliability for the AX6 model have previously been reported \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cdiv id=\"Sec11\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analyses\u003c/h2\u003e \u003cp\u003eStatistical analyses were performed using GraphPad Prism version 10 (GraphPad, Boston, MA, USA). To assess baseline differences in patient characteristics between cohorts, the non-parametric Mann\u0026ndash;Whitney U test was applied. Longitudinal changes across measurement time points were analyzed using the Friedman test. When the Friedman test indicated significant differences over time, Dunn\u0026rsquo;s multiple comparisons test was used \u003cem\u003epost-hoc\u003c/em\u003e to identify which time points contributed to the observed changes. Test statistics are reported as chi-square values (χ\u0026sup2;), degrees of freedom, and corresponding p-values. Kendall\u0026rsquo;s W was calculated as a measure of effect size. In addition, median values and interquartile ranges (IQR) are reported for descriptive purposes. Correlation analyses were performed using Spearman rank correlation. To address the effect of GAHT on REE and given the limited sample size, residual REE was calculated after adjustment for its primary determinant, FFM, using linear regression \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e,\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. A two-sided alpha level of 0.05 was used throughout.\u003c/p\u003e \u003cp\u003eDue to the limited sample sizes (maximum n\u0026thinsp;=\u0026thinsp;17 in the trans men cohort, with smaller sample sizes in the trans women and control cohorts), formal tests of normality were not performed due to inherent limited power and reliability in small samples. Given the resulting uncertainty regarding distributional assumptions and the presence of visibly skewed data, all longitudinal analyses were conducted using non-parametric Friedman test, which provides a conservative and robust approach for repeated-measures data under these conditions.\u003c/p\u003e \u003cp\u003eData quality was monitored throughout the study period. Among trans men, two participants discontinued participation prior to study completion upon their own request. Among trans women, six participants discontinued participation, of whom three withdrew upon their own request, two discontinued due to time constraints, and one discontinued due to relocation. Within the cisgender male control cohort, three participants terminated participation for personal or logistical reasons (including time constraints). Participants who discontinued the study constituted the only cases with incomplete longitudinal data. For all statistical analyses, a complete-case approach was applied: Only individuals with data available at all predefined study visits (baseline, three, six, and 12 months) were retained. Accordingly, exclusion of dropouts yielded an analytical dataset with no missing values, thereby ensuring internal consistency and comparability across all evaluated variables.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec13\" class=\"Section2\"\u003e \u003ch2\u003ePopulation Baseline Characteristics\u003c/h2\u003e \u003cp\u003eBaseline characteristics are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. No differences were observed in body weight, BMI, FM, or FFM between trans women and cisgender men, or between trans men and cisgender women (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Trans men were younger than cisgender women (median\u0026thinsp;=\u0026thinsp;22.9 years, IQR\u0026thinsp;=\u0026thinsp;20.6\u0026ndash;24.6 years vs. median\u0026thinsp;=\u0026thinsp;24.9 years, IQR\u0026thinsp;=\u0026thinsp;23.9\u0026ndash;28.7 years; p\u0026thinsp;=\u0026thinsp;0.046).\u003c/p\u003e \u003cp\u003e \u003cem\u003eAd libitum\u003c/em\u003e energy intake during the buffet and snack tests, as well as macronutrient composition (carbohydrate, fat, and protein), did not differ between trans women or men and cisgender participants (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Resting EE was also comparable between groups at baseline (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eAt baseline, total accelerometer wear time throughout the seven days of monitoring was similar across all groups (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). The time spent at each activity level did not differ between trans women and cisgender men (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), while trans men showed a shorter time spent at levels of moderate and vigorous activity compared to cisgender woman (activity level moderate: median\u0026thinsp;=\u0026thinsp;89.4 min/day, IQR\u0026thinsp;=\u0026thinsp;74.6\u0026ndash;137.4 min/day vs. median\u0026thinsp;=\u0026thinsp;131.0 min/day, IQR\u0026thinsp;=\u0026thinsp;118.4\u0026ndash;167.6 min/day, respectively; p\u0026thinsp;=\u0026thinsp;0.04; activity level vigorous: median\u0026thinsp;=\u0026thinsp;0.4 min/day, IQR\u0026thinsp;=\u0026thinsp;0.00\u0026ndash;1.2 min/day vs. median\u0026thinsp;=\u0026thinsp;5.7 min/day, IQR\u0026thinsp;=\u0026thinsp;3.1\u0026ndash;9.9 min/day, respectively; p\u0026thinsp;=\u0026thinsp;0.003).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec14\" class=\"Section2\"\u003e \u003ch2\u003eSerum estradiol and testosterone concentrations reach affirmed-gender reference ranges during GAHT\u003c/h2\u003e \u003cp\u003eAt baseline, serum testosterone and estradiol concentrations did not differ between trans women and cisgender men, or between trans men and cisgender women (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). During 12 months of GAHT, serum testosterone concentrations declined in trans women (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;28.18, W\u0026thinsp;=\u0026thinsp;0.63; median\u0026thinsp;=\u0026thinsp;0.37 nmol/l, IQR\u0026thinsp;=\u0026thinsp;0.31\u0026ndash;0.47 nmol/l, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and serum estradiol concentrations increased (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;18.28, W\u0026thinsp;=\u0026thinsp;0.44; median\u0026thinsp;=\u0026thinsp;245.5 pmol/l, IQR\u0026thinsp;=\u0026thinsp;55.8\u0026ndash;419.5 nmol/l, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003eA, C). In trans men, serum testosterone concentrations increased (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;28.88, W\u0026thinsp;=\u0026thinsp;0.69; median\u0026thinsp;=\u0026thinsp;16.94 nmol/l, IQR\u0026thinsp;=\u0026thinsp;13.52\u0026ndash;25.87 nmol/l, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), whereas serum estradiol concentrations remained unchanged (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003eB, D). Hormone concentrations at six and 12 months of GAHT did not change compared to after three months of GAHT (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eIn cisgender controls, serum testosterone and estradiol concentrations did not change throughout follow-up (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003e). At 12 months, serum testosterone concentrations were comparable between trans men and cisgender men (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), while serum estradiol concentrations were higher in trans women compared with cisgender women (trans women: median\u0026thinsp;=\u0026thinsp;245.5 pmol/l, IQR\u0026thinsp;=\u0026thinsp;155.8\u0026ndash;419.5 pmol/l; cisgender women: median\u0026thinsp;=\u0026thinsp;65.2 pmol/l, IQR\u0026thinsp;=\u0026thinsp;37.0\u0026ndash;313.8 pmol/l; p\u0026thinsp;=\u0026thinsp;0.046; Fig.\u0026nbsp;\u003cspan refid=\"Fig7\" class=\"InternalRef\"\u003e2\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec15\" class=\"Section2\"\u003e \u003ch2\u003eIncrease in body weight and fat mass in trans women undergoing GAHT\u003c/h2\u003e \u003cp\u003eIn trans women, body weight increased over 12 months of GAHT (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;16.54, W\u0026thinsp;=\u0026thinsp;0.34, median\u0026thinsp;=\u0026thinsp;73.4 kg, IQR\u0026thinsp;=\u0026thinsp;68.1\u0026ndash;82.5 kg, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). While FFM did not change (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), the change in body weight was due to an increase in FM (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;18.06, W\u0026thinsp;=\u0026thinsp;0.38, median\u0026thinsp;=\u0026thinsp;20.5 kg, IQR\u0026thinsp;=\u0026thinsp;11.7\u0026ndash;23.2 kg, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003eB and C, respectively). In \u003cem\u003epost-hoc\u003c/em\u003e analyses, the increase in FM reflected changes occurring across the entire observation period, whereas changes in body weight were largely driven by effects within the first six months of GAHT.\u003c/p\u003e \u003cp\u003eEarly changes across all body compartments predicted subsequent trajectories (body weight: r\u0026thinsp;=\u0026thinsp;0.73\u0026ndash;0.78, \u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026le;\u0026thinsp;0.002; Supplemental Figure S1A\u0026ndash;C; FFM: r\u0026thinsp;=\u0026thinsp;0.51\u0026ndash;0.83, \u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Supplemental Figure S1D\u0026ndash;F; FM: r\u0026thinsp;=\u0026thinsp;0.52\u0026ndash;0.74, \u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026lt;\u0026thinsp;0.05; Supplemental Figure S1G\u0026ndash;I).\u003c/p\u003e \u003cp\u003eIn cisgender men and women, body weight, FM, and FFM remained stable during the entire study period (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, data not shown).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec16\" class=\"Section2\"\u003e \u003ch2\u003eBody weight and fat-free mass increase in trans men undergoing GAHT\u003c/h2\u003e \u003cp\u003eIn trans men undergoing 12 months of GAHT body weight (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;16.27, W\u0026thinsp;=\u0026thinsp;0.32, median\u0026thinsp;=\u0026thinsp;73.9 kg, IQR\u0026thinsp;=\u0026thinsp;64.2\u0026ndash;86.1 kg, p\u0026thinsp;=\u0026thinsp;0.001), FFM (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;24.95, W\u0026thinsp;=\u0026thinsp;0.49, median\u0026thinsp;=\u0026thinsp;49.7 kg, IQR\u0026thinsp;=\u0026thinsp;47.5\u0026ndash;60.0 kg, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001), as well as FM increased (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;9.14, W\u0026thinsp;=\u0026thinsp;0.18, median\u0026thinsp;=\u0026thinsp;25.1 kg, IQR\u0026thinsp;=\u0026thinsp;18.8\u0026ndash;30.2 kg, p\u0026thinsp;=\u0026thinsp;0.028; Figs.\u0026nbsp;\u003cspan refid=\"Fig8\" class=\"InternalRef\"\u003e3\u003c/span\u003eD, E and F, respectively). Changes in body weight were driven by differences observed after 12 months of GAHT, as determined via \u003cem\u003epost-hoc\u003c/em\u003e analysis.\u003c/p\u003e \u003cp\u003eIn trans men, absolute changes in body weight during GAHT showed consistent associations across timepoints. Body weight change after three months correlated with body weight change after six (r\u0026thinsp;=\u0026thinsp;0.89, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Supplemental Figure S2A) and 12 months (r\u0026thinsp;=\u0026thinsp;0.6, p\u0026thinsp;=\u0026thinsp;0.012; Supplemental Figure S2B) of GAHT, as well as body weight change after six versus 12 months of GAHT (r\u0026thinsp;=\u0026thinsp;0.77, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Supplemental Figure S2C). For FFM, absolute changes after three months were associated with changes after six months of GAHT (r\u0026thinsp;=\u0026thinsp;0.64, p\u0026thinsp;=\u0026thinsp;0.006; Supplemental Figure S2D), as were FFM changes after six and 12 months of GAHT (r\u0026thinsp;=\u0026thinsp;0.53, p\u0026thinsp;=\u0026thinsp;0.03; Supplemental Figure S2F). Comparable to body weight and FFM, changes in FM were associated during GAHT: Absolute FM changes after three months correlated with those at six months of GAHT (r\u0026thinsp;=\u0026thinsp;0.89, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Supplemental Figure S2G). Changes in FM after six months correlated with those after 12 months of GAHT (r\u0026thinsp;=\u0026thinsp;0.57, p\u0026thinsp;=\u0026thinsp;0.018; Supplemental Figure S2I).\u003c/p\u003e \u003cp\u003e \u003cb\u003eAd libitum\u003c/b\u003e \u003cb\u003eenergy intake increases during GAHT\u003c/b\u003e\u003c/p\u003e \u003cp\u003eIn trans women, total energy intake during the \u003cem\u003ead libitum\u003c/em\u003e buffet increased over 12 months of GAHT (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;13.73, W\u0026thinsp;=\u0026thinsp;0.29, median\u0026thinsp;=\u0026thinsp;1193 kcal, IQR\u0026thinsp;=\u0026thinsp;974\u0026ndash;1742 kcal, p\u0026thinsp;=\u0026thinsp;0.003; Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003eA). Intake of carbohydrate- and fat-derived calories did not change (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003eB\u0026ndash;D), whereas protein-derived calorie-intake increased (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;8.63, W\u0026thinsp;=\u0026thinsp;0.18, median\u0026thinsp;=\u0026thinsp;189 kcal, IQR\u0026thinsp;=\u0026thinsp;157\u0026ndash;240 kcal, p\u0026thinsp;=\u0026thinsp;0.035; Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003eD). \u003cem\u003ePost-hoc\u003c/em\u003e analyses indicated that the increase in total caloric intake during the \u003cem\u003ead libitum\u003c/em\u003e buffet was attributable to changes in intake over 12 months of GAHT (p\u0026thinsp;\u0026lt;\u0026thinsp;0.009) and were driven by the increase in protein-derived calorie-intake. Energy intake during the snack test remained unchanged throughout the observation period (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Supplemental Figure S3A).\u003c/p\u003e \u003cp\u003eIn trans men, total energy intake during the \u003cem\u003ead libitum\u003c/em\u003e buffet increased over 12 months of GAHT (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;18.39, W\u0026thinsp;=\u0026thinsp;0.36, median\u0026thinsp;=\u0026thinsp;940 kcal, IQR\u0026thinsp;=\u0026thinsp;784\u0026ndash;1056 kcal, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003eE). This change was primarily attributable to a higher intake of carbohydrate-derived calories (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;13.59, W\u0026thinsp;=\u0026thinsp;0.26, median 375 kcal, IQR\u0026thinsp;=\u0026thinsp;334\u0026ndash;460 kcal, p\u0026thinsp;\u0026lt;\u0026thinsp;0.004; Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003eF). Protein intake also increased (χ\u0026sup2;[3]\u0026thinsp;=\u0026thinsp;9.49, W\u0026thinsp;=\u0026thinsp;0.18, median\u0026thinsp;=\u0026thinsp;114 kcal, IQR\u0026thinsp;=\u0026thinsp;87\u0026ndash;169 kcal, p\u0026thinsp;=\u0026thinsp;0.02; Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003eH), whereas fat intake remained stable (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig9\" class=\"InternalRef\"\u003e4\u003c/span\u003eG). \u003cem\u003ePost-hoc\u003c/em\u003e analyses indicated that changes in caloric intake were primarily driven by differences between baseline and the 12-month endpoint (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Energy intake during the snack test did not change (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Supplemental Figure S3B).\u003c/p\u003e \u003cp\u003eIn cis men and cis women, total energy intake, macronutrient composition, and total energy intake during the snack test remained unchanged throughout the study (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, data not shown). Body weight changes throughout the study period did not correlate with energy intake during the \u003cem\u003ead libitum\u003c/em\u003e buffet in any of the groups (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, data not shown).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec17\" class=\"Section2\"\u003e \u003ch2\u003eResting energy expenditure and physical activity unchanged during GAHT\u003c/h2\u003e \u003cp\u003eIn trans women, REE correlated with FFM (baseline r\u0026thinsp;=\u0026thinsp;0.67, p\u0026thinsp;\u0026lt;\u0026thinsp;0.004, three months r\u0026thinsp;=\u0026thinsp;0.68, p\u0026thinsp;\u0026lt;\u0026thinsp;0.004, six months r\u0026thinsp;=\u0026thinsp;0.8, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, and 12 months r\u0026thinsp;=\u0026thinsp;0.77, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; data not shown). In a longitudinal analysis of unadjusted REE there was no change over the 12 months of GAHT (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003eA). To account for inter-individual differences in body composition, REE adjusted for FFM was calculated. Residual REE did not change during 12 months of GAHT (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). Across all groups, baseline REE showed comparable group-level variability, with coefficients of variation (SD/mean\u0026times;100) of 10.8% in trans men, 12.2% in trans women, 12.9% in cis women, and 10.4% in cis men.\u003c/p\u003e \u003cp\u003eIn trans men, REE correlated with FFM at each timepoint (baseline r\u0026thinsp;=\u0026thinsp;0.63, p\u0026thinsp;\u0026lt;\u0026thinsp;0.004, three months r\u0026thinsp;=\u0026thinsp;0.71, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, six months r\u0026thinsp;=\u0026thinsp;0.76, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, and 12 months r\u0026thinsp;=\u0026thinsp;0.86, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; data not shown). In this group, unadjusted REE did not change over the course of the study (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05; Fig.\u0026nbsp;\u003cspan refid=\"Fig10\" class=\"InternalRef\"\u003e5\u003c/span\u003eB). Following adjustment for FFM using linear regression, residual REE did not change throughout the study (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eIn cisgender individuals during the entire study period, REE remained stable (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003eThere were no changes in accelerometry based wear time and accelerometry-based assessment of physical activity over the 12-month period in trans women and men (Supplemental Figures S4 and S5), as well as controls (\u003cem\u003eall\u003c/em\u003e p\u0026thinsp;\u0026gt;\u0026thinsp;0.05, respectively; data not shown).\u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this controlled, prospective study, GAHT served as a human model to examine how shifts in body composition are paralleled by changes of components of energy balance. Over 12 months, treatment-induced changes in fat-free mass and fat mass were accompanied by alterations in \u003cem\u003ead libitum\u003c/em\u003e energy intake, whereas resting energy expenditure and physical activity remained stable. Short-term changes in body weight and fat mass were consistent traits in trans women during GAHT. Although it remains unclear whether these alterations are independent of measurable changes in energy expenditure, paralleled dynamic changes underline the importance of fat-free mass and fat mass as determinants of energy balance control.\u003c/p\u003e \u003cp\u003ePrevious work reports that GAHT is associated with substantial, directionally consistent shifts in body composition \u0026mdash; primarily increased fat mass and body mass index in feminizing treatment and increased fat-free mass with masculinizing treatment \u0026mdash; while the magnitude and metabolic correlates of these changes vary across cohorts \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan additionalcitationids=\"CR41 CR42 CR43\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e. Nutritional and behavioral studies note altered dietary patterns (e.g., higher fat intake, reduced fruit/vegetable consumption, food insecurity, restrictive eating behaviors) in transgender adults, and highlight psychosocial contributors that may interact with hormonal effects to shape energy intake \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e,\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Together, these works indicate that GAHT provides a clinically relevant context in which hormonal, behavioral, and social factors converge to influence body composition and energy intake, but important questions remain about the proximate physiological mechanisms linking compositional change to habitual intake \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Given these consistent, treatment-related shifts in fat and lean tissue \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e,\u003cspan additionalcitationids=\"CR41 CR42 CR43\" citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e, it becomes essential to examine how changes in body composition translate into actual energy balance.\u003c/p\u003e \u003cp\u003eDespite a small study population which limits the ability to translate sex hormone-induced changes in body composition to direct effects on energy homeostasis, to our knowledge, the present exploratory study is the first to provide a comprehensive assessment of the effects of GAHT on energy balance. Furthermore, current work aligns with principles of energy balance regulation, that highlight the relevance of lean mass as a putative driver of energy intake: To couple intake with metabolic demand, energy expenditure has been proposed as key signal for daily energy intake, driven by fat-free mass as its principal metabolic determinant \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Fat-free mass, as the main contributor to resting energy intake, predicts \u003cem\u003ead libitum\u003c/em\u003e energy intake \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e, and multiple studies report positive associations between fat-free mass, energy expenditure and energy intake \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e,\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e,\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. However, it remains debated whether the proximate cue is fat-free mass \u003cem\u003eper se\u003c/em\u003e or the energy expenditure it generates: Mediation analyses indicate that much of the association of fat-free mass with intake is transmitted via resting or 24-h energy expenditure \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e, whereas direct effects of fat-free mass are small. Finally, the role of energy expenditure in longitudinal weight change is inconsistent across populations \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e: Lower 24-h energy expenditure predicts weight gain in some cohorts \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, but higher resting energy expenditure has been associated with weight gain in others \u003csup\u003e\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e\u003c/sup\u003e, suggesting that individual differences in how intake adapts to basal energy requirements critically modulate long-term energy balance. Our study is limited to describe a change in energy intake that is paralleled by the increase in fat-free mass \u0026ndash; and no change in resting energy expenditure or physical activity-related energy expenditure. Nonetheless, these results support the relevance of fat-free mass as a metabolic determinant of energy intake in an understudied population.\u003c/p\u003e \u003cp\u003eRegulation of energy homeostasis is complex and integrates humoral, neural and behavioral mechanisms: Adipose tissue provides a tonic signal of energy stores and gut-brain peptides together with central and vagal circuits modulate hunger and satiety \u003csup\u003e\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e,\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e\u003c/sup\u003e. Eating behavior \u0026mdash; shaped by internal cues, hedonic processes, learned associations, and environmental cues \u0026mdash; is a primary regulator of human energy intake \u003csup\u003e\u003cspan additionalcitationids=\"CR58 CR59 CR60 CR61\" citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e\u003c/sup\u003e. Thus, besides coupling of metabolic demand with energy expenditure, a more complex assessment of energy homeostasis needs to integrate multiple determinants. In the present study, this may be primarily underlined by observed changes in energy intake during GAHT in trans women: Despite its role as a determinant of energy expenditure in humans \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e, notably, in this subgroup changes in energy intake were accompanied by altered fat mass, and not fat-free mass.\u003c/p\u003e \u003cp\u003eIrrespective of the mechanisms driving the observed increases in \u003cem\u003ead libitum\u003c/em\u003e energy intake during GAHT, our findings highlight that early changes in body weight and fat mass represent consistent short-term traits in trans women. Given the elevated prevalence of overweight and obesity in transgender populations \u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e,\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e, identifying and monitoring these shifts at the outset of therapy may allow for timely interventions aimed at preventing unfavorable weight trajectories. Although limited in sample size, our study provides a comprehensive assessment of both sides of the energy balance equation under free-living conditions, leveraging repeated intra-individual measurements to characterize early physiological adaptations during gender-affirming hormone therapy. By focusing on the initial phase of treatment \u0026mdash; when phenotypic changes first emerge \u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e \u0026mdash; this predictive approach may offer clinically meaningful insight into the development of body weight trajectories and opportunities to mitigate related metabolic risk.\u003c/p\u003e \u003cp\u003eDespite the strengths of a controlled study design, repeated measurements, intra-individual comparisons, and multiple follow-ups, certain limitations need to be considered: Future investigations in this population would benefit from assessment of 24-hour energy expenditure, allowing for the detection of more subtle changes relative to alterations in fat-free and fat mass. Notably, variation in resting energy expenditure assessment may have limited the ability to detect changes within this measure. Likewise, more precise measures of body composition, such as dual-energy X-ray absorptiometry, could enhance the characterization of anthropometric determinants of energy expenditure. While our assessment of \u003cem\u003ead libitum\u003c/em\u003e energy intake provides an initial insight, the buffet or snack-based setting represents a controlled and artificial environment. More naturalistic or prolonged assessments of spontaneous energy intake may therefore be necessary, particularly to disentangle homeostatic from hedonic drivers of food consumption. Given the exploratory nature of our findings, especially regarding potential differences between trans women versus trans men, a more detailed investigation of snack intake patterns may yield further mechanistic understanding.\u003c/p\u003e \u003cp\u003eTaken together, our results indicate that sex-hormone treatment-induced compositional shifts can be accompanied by increased energy intake in the absence of detectable changes in measured energy expenditure, implying that alterations in fat and lean mass may modulate appetitive behavior and short-term energy balance. These findings underscore the value of early monitoring of body composition and intake during periods of rapid phenotypic change and motivate longer, mechanistic studies to delineate homeostatic versus hedonic drivers and their relevance for long-term weight trajectories.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eI hereby confirm that the study entitled \u0026ldquo;Hormones and Health Study\u0026rdquo; (Investigation of the effects of testosterone and estrogen on eating behavior, metabolism, and the cardiovascular system in transsexual patients undergoing cross-sex hormone therapy) was reviewed and approved by the Ethics Committee of the Medical Faculty of the University of Leipzig, Germany (reference number: 023/20-ek) .\u003c/p\u003e\n\u003cp\u003eThe Ethics Committee reviewed the submitted study documents and raised no objections to the conduct of the study\u003c/p\u003e\u003ch2\u003eSources of support\u003c/h2\u003e\n\u003cp\u003eHelmholtz Institute for Metabolic, Obesity and Vascular Research Intramural Research Fund; HS received financial support for this study from Besins Healthcare, Berlin, Germany. The funder had no role in the study design, data collection, data analysis, interpretation of results, or the writing of the manuscript. Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany\u0026acute;s Excellence Strategy \u0026ndash; EXC-3105/1\u0026ndash;533765739.\u003c/p\u003e\n\u003ch2\u003eConflict of Interest:\u003c/h2\u003e\n\u003cp\u003eHaiko Schl\u0026ouml;gl received third party funding for this study from Besins Healthcare. Matthias Bl\u0026uuml;her received honoraria as a consultant and speaker from Amgen, AstraZeneca, Bayer, Boehringer-Ingelheim, Lilly, Novo Nordisk, Novartis, and Sanofi. All other authors declare no conflict of interest.\u003c/p\u003e\n\u003ch2\u003eAuthor contributions\u003c/h2\u003e\n\u003cp\u003eMartin Kaar: data analysis, conduct of the study, writing, reviewing and editing of the manuscript; Pauline Zimmermann: conduct of the study, reviewing and editing of the manuscript; Theresa Bokeloh: conduct of the study, reviewing and editing of the manuscript; Lotta Moll: conduct of the study, reviewing and editing of the manuscript; Franziska Labinski: conduct of the study, reviewing and editing of the manuscript; Florian Woehlecke: conduct of the study, reviewing and editing of the manuscript; Matthias Bl\u0026uuml;her: funding acquisition, resources, reviewing and editing of the manuscript; Michael Stumvoll: funding acquisition, resources, reviewing and editing of the manuscript; Haiko Schl\u0026ouml;gl: conceptualization, funding acquisition, conduct of the study, project administration, writing, reviewing and editing of the manuscript; Sascha Heinitz: conceptualization, conduct of the study, project administration, writing, reviewing and editing of the manuscript.\u003c/p\u003e\n\u003ch2\u003eAcknowledgements\u003c/h2\u003e\n\u003cp\u003eWe thank all participants for their participation in the study. We also thank Natalia Schischkarjow, Bj\u0026ouml;rn Drechsler-Kryst, Lotte Oldenburg, Mathilda Klammt, and Antonia Stengler for their assistance in conducting the study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eHall KD, Heymsfield SB, Kemnitz JW, Klein S, Schoeller DA, Speakman JR (2012) Energy balance and its components: implications for body weight regulation. Am J Clin Nutr 95(4):989\u0026ndash;994\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBlundell J, Gibbons C, Caudwell P, Finlayson G, Hopkins M (2015) Appetite control and energy balance: impact of exercise. Obes Rev 16:67\u0026ndash;76\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWeise CM, Hohenadel MG, Krakoff J, Votruba SB (2014) Body composition and energy expenditure predict ad-libitum food and macronutrient intake in humans. 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Deutsches \u0026Auml;rzteblatt international 117(43):725\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University Hospital Leipzig","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-8824402/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8824402/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground.\u003c/h2\u003e \u003cp\u003eBody weight is governed by balance between energy intake and energy expenditure. Transgender individuals undergoing gender-affirming hormone therapy (GAHT) are at increased risk of overweight and obesity. A comprehensive assessment of energy expenditure and intake during GAHT is lacking.\u003c/p\u003e\u003ch2\u003eObjective.\u003c/h2\u003e \u003cp\u003eTo investigate adaptations in body composition, energy expenditure, and energy intake during GAHT.\u003c/p\u003e\u003ch2\u003eMethods.\u003c/h2\u003e \u003cp\u003eIn a prospective observational cohort study, body weight, body composition, \u003cem\u003ead libitum\u003c/em\u003e energy intake during buffet, snack food intake, energy expenditure (REE), and physical activity were assessed at baseline, after three, six, 12 months of GAHT in 17 trans men (female-to-male transgender; median\u0026plusmn;interquartile range; body mass index [BMI] 25.7\u0026thinsp;\u0026plusmn;\u0026thinsp;7 kg/m\u0026sup2;; age 22.9\u0026thinsp;\u0026plusmn;\u0026thinsp;3.9 years) and 16 trans women (male-to-female transgender; BMI 22.5\u0026thinsp;\u0026plusmn;\u0026thinsp;7.3 kg/m\u0026sup2;; age 24.9\u0026thinsp;\u0026plusmn;\u0026thinsp;5.8 years). Cis men (n\u0026thinsp;=\u0026thinsp;7) and women (n\u0026thinsp;=\u0026thinsp;10) without hormone treatment served as controls.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e. In trans men, body weight (χ\u0026sup2;=16.27, p\u0026thinsp;=\u0026thinsp;0.001; Δ median\u0026thinsp;=\u0026thinsp;2.4 kg) and fat-free mass (χ\u0026sup2;=24.95, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Δ median\u0026thinsp;=\u0026thinsp;0.8 kg) increased over 12 months of GAHT, accompanied by a gain in fat mass over 6 months (χ\u0026sup2;=9.14, p\u0026thinsp;=\u0026thinsp;0.028; Δ median\u0026thinsp;=\u0026thinsp;1.1 kg). In trans women, body weight (χ\u0026sup2;=16.54, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Δ median\u0026thinsp;=\u0026thinsp;3.6 kg) and fat mass (χ\u0026sup2;=18.06, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001; Δ median\u0026thinsp;=\u0026thinsp;4.7 kg) increased, whereas fat-free mass remained stable (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05). In both groups, energy intake was higher (trans women χ\u0026sup2;=13.73, p\u0026thinsp;=\u0026thinsp;0.003, Δ median\u0026thinsp;=\u0026thinsp;132 kcal; trans men χ\u0026sup2;=18.39, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, Δ median\u0026thinsp;=\u0026thinsp;222 kcal). Snack food intake, REE, physical activity, and controls remained unchanged (all p\u0026thinsp;\u0026gt;\u0026thinsp;0.05)\u003c/p\u003e\u003ch2\u003eConclusion.\u003c/h2\u003e \u003cp\u003eDuring GAHT, sex hormone\u0026ndash;induced changes in body composition are paralleled by an increase in energy intake.\u003c/p\u003e","manuscriptTitle":"Sex-hormone induced short-term changes in body composition are paralleled by an increase in ad libitum energy intake","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-19 11:55:12","doi":"10.21203/rs.3.rs-8824402/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"adcf6971-3537-49a3-a44f-4a61ef43b6b6","owner":[],"postedDate":"March 19th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":64077038,"name":"Endocrinology \u0026 Metabolism"}],"tags":[],"updatedAt":"2026-03-19T11:55:12+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-19 11:55:12","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8824402","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8824402","identity":"rs-8824402","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}