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Article

Long-Term Body Composition Trajectories After Bariatric Surgery: A 5-Year Comparative Study of Biliopancreatic Diversion, Roux-en-Y Gastric Bypass, and Sleeve Gastrectomy

by
María Antequera-González
1,*,
Elena González Arnáiz
1,
Diana G. Ariadel-Cobo
1,
Diana García Sastre
1,
María López Melgar
1,
Ana Urioste Fondo
1,
M. Carmen Dameto Pons
1,
María Casado Rodríguez
1,
Jesús Manuel Silva Fernández
2,
Luis González-Herráez García
2 and
María D. Ballesteros-Pomar
1,3
1
Department of Endocrinology and Nutrition, Complejo Asistencial Universitario de León (CAULE), 24008 Leon, Spain
2
Department of General Surgery, Complejo Asistencial Universitario de León (CAULE), 24008 Leon, Spain
3
Institute of Biomedicine (IBIOMED), University of León, 24071 Leon, Spain
*
Author to whom correspondence should be addressed.
J. Clin. Med. 2026, 15(6), 2354; https://doi.org/10.3390/jcm15062354
Submission received: 4 February 2026 / Revised: 2 March 2026 / Accepted: 11 March 2026 / Published: 19 March 2026
(This article belongs to the Section Endocrinology & Metabolism)
Browse Figure
Versions Notes

Abstract

Background/Objectives: Long-term comparative data on body composition (BC) trajectories following different bariatric procedures remain limited, particularly regarding potential muscle preservation after malabsorptive techniques. We aimed to compare 5-year changes in adiposity and muscle mass following biliopancreatic diversion (BPD), Roux-en-Y gastric bypass (RYGB), and sleeve gastrectomy (SG), adjusting for baseline heterogeneity. Methods: In this retrospective longitudinal study, 128 patients with severe obesity were followed for 60 months. BC was assessed annually using multi-frequency bioelectrical impedance analysis. Multivariable linear mixed-effects models adjusted for baseline BMI, age, and sex were used to evaluate trajectories of total weight loss (%WL), fat mass loss (%FML), and skeletal muscle mass (SMM). Results: BPD demonstrated a significantly superior longitudinal trajectory for %WL (β = 0.124 [95% CI: 0.013–0.235], p = 0.028) and %FML (β = 0.288 [95% CI: 0.135–0.440], p < 0.001) over 5 years. However, no statistically significant independent differences between techniques were observed at the isolated 60-month endpoint after full adjustment. Although BPD was associated with a higher percentage of muscle mass loss (p = 0.019), absolute skeletal and appendicular muscle mass did not differ significantly across procedures. Age emerged as an independent negative predictor of weight and fat loss (p < 0.001). Conclusions: After rigorous adjustment for baseline characteristics, BPD provides greater long-term adiposity reduction without evidence of disproportionate impairment of absolute muscle mass compared with RYGB or SG. These findings contribute to a more refined understanding of long-term body composition dynamics following bariatric surgery.

1. Introduction

Severe obesity is associated with profound alterations in body composition (BC), including excess adiposity and impaired muscle quality, which contribute significantly to long-term cardiometabolic and functional risk [1,2]. While bariatric surgery (BS) is established as the most effective intervention for sustained weight loss, its success should not be evaluated solely by total weight reduction or body mass index (BMI) [3,4]. The quality of weight loss—defined by the ratio of fat mass (FM) reduction to the preservation of fat-free mass (FFM) and skeletal muscle mass (SMM)—is a critical determinant of post-surgical metabolic health and long-term physical independence [5,6].
Despite the widespread use of procedures such as sleeve gastrectomy (SG) and Roux-en-Y gastric bypass (RYGB), there is significant clinical uncertainty regarding the long-term musculoskeletal safety of more aggressive techniques, such as biliopancreatic diversion (BPD) [7,8]. While BPD is renowned for its superior efficacy in fat mass reduction, it remains unclear whether this metabolic advantage comes at the cost of disproportionate muscle wasting over a five-year horizon [9,10]. Most available studies report only short- to mid-term outcomes and frequently lack the necessary multivariable adjustments to account for baseline differences in age and obesity severity, factors that may significantly bias inter-technique comparisons [11,12].
Furthermore, the longitudinal monitoring of BC trajectories faces major methodological challenges, including high attrition rates and baseline clinical heterogeneity [13,14]. These factors can lead to inaccurate estimations of surgical impact if the data are not analyzed through an integrated approach that accounts for individual patient characteristics over time [15,16]. There is a critical need for studies that isolate the true effect of surgical techniques from baseline confounders, such as age and initial BMI, to provide more reliable evidence for clinical decision-making [17,18].
Therefore, the primary objective of this study was to evaluate and compare the 5-year trajectories of body composition changes following BPD, RYGB, and SG in a cohort of patients with severe obesity. Specifically, we sought to determine whether the superior fat mass loss associated with BPD compromises skeletal and appendicular muscle mass after rigorous adjustment for baseline BMI, age, and sex, thereby ensuring a more accurate assessment of the long-term functional and metabolic safety of these surgical interventions.

2. Materials and Methods

2.1. Study Design and Participants

A retrospective longitudinal study was conducted on a cohort of patients with severe obesity who underwent bariatric surgery at a tertiary referral center between January 2005 and December 2023. Patients were followed over a 5-year period (60 months). Inclusion criteria were defined according to international clinical guidelines for metabolic surgery [15,16]: (1) BMI ≥ 40 kg/m2 or ≥ 35 kg/m2 with associated comorbidities, (2) age between 18 and 65 years, and (3) availability of complete body composition data at baseline and at least three follow-up time points. Patients undergoing revisional surgery, those with active malignancy, or severe psychiatric disorders were excluded. The study was conducted in accordance with the Declaration of Helsinki and was approved by the Institutional Ethics Committee (Protocol No.: 2104).

2.2. Surgical Procedures

Patients were assigned to one of three standardized procedures: BPD, RYGB, or SG. All procedures were performed by a multidisciplinary team following standardized surgical protocols to ensure consistency in limb lengths and procedural technique [17]. The selection of the surgical technique was performed based on the patient’s metabolic profile, baseline BMI, and eating behavior.

2.3. Anthropometry and Body Composition Assessment

Anthropometric evaluations were performed at baseline and annually at 12, 24, 36, 48, and 60 months postoperatively. Weight was measured to the nearest 0.1 kg using a calibrated TANITA® (Tokyo, Japan) MC-780A scale; height to the nearest 0.1 cm with a SECA 213 stadiometer, following International Society for the Advancement of Kinanthropometry (ISAK) guidelines (13). Total weight loss percentage (%WL) and specific body composition change percentages (e.g., %FML, %MML) were calculated individually for each subject at each follow-up point relative to their specific baseline values [18].
BC was assessed through multi-frequency TANITA® MC-780A bioimpedance analyzer. To ensure reliability and minimize measurement bias related to hydration sensitivity, patients followed a standardized protocol: an 8 h fast, empty bladder, and avoidance of strenuous exercise 24 h prior to the assessment [9,10]. BIA provided data on FM, FFM, and SMM. Appendicular muscle mass (AMM) was calculated as the sum of lean mass in the extremities. The use of BIA has been validated against dual-energy X-ray absorptiometry (DXA) for monitoring bariatric patients [11,12,19].

2.4. Statistical Analysis

To analyze the longitudinal trajectories of body composition and manage the attrition rate (72.7% at 60 months), Multivariable Linear Mixed-Effects Models (LMM) were implemented [20,21,22]. This approach was chosen over repeated-measures ANOVA as it accounts for missing data under the Missing At Random (MAR) assumption, utilizing all available data points to minimize attrition bias. Time was treated as a categorical variable (annual visits). Surgical Technique, Time, and their interaction (Technique × Time) were included as fixed effects. The models were adjusted for baseline BMI, Age, and Sex as fixed-effect covariates to account for initial heterogeneity [17,23]. To model the correlation structure of repeated measures, an unstructured covariance matrix was utilized. Random intercepts per patient were included to account for individual baseline variability. Effect sizes were reported as fixed-effect coefficients (β) with their corresponding 95% Confidence Intervals (95% CI). Analyses were performed using IBM SPSS Statistics, v.28.0 (IBM Corp., Armonk, NY, USA). Statistical visualizations were generated using Python with specialized libraries (Matplotlib and Seaborn) to represent the adjusted trajectories derived from the LMM models. Statistical significance was set at p < 0.05.

3. Results

3.1. Baseline Profile and Attrition Analysis

The study included a total of 128 patients. Baseline clinical characteristics according to the surgical procedure are summarized in Table 1. Significant differences were observed at baseline regarding BMI (BPD: 52.3 ± 8.3 vs. RYGB: 43.6 ± 5.8 vs. SG: 42.7 ± 4.2 kg/m2; p < 0.001) and age (BPD: 43.1 ± 9.3 vs. RYGB: 46.8 ± 9.1 vs. SG: 48 ± 9.4 years; p = 0.024), which justifies the use of adjusted multivariable models for longitudinal comparisons.
A sensitivity analysis was performed to evaluate the impact of the attrition rate at the 60-month follow-up. As shown in Table 2, no statistically significant differences were found between patients who completed the 5-year follow-up (n = 36) and those lost to follow-up (n = 92) regarding baseline age, weight, or BMI (all p > 0.05). These findings suggest that the final sample remains representative of the initial cohort and support the MAR assumption for the longitudinal analysis.

3.2. Multivariable Analysis of Longitudinal Trajectories

To account for repeated measures and control for baseline clinical heterogeneity, a multivariable LMM with a random intercept for each subject was employed. The coefficients for the trajectories of %WL and fat mass loss (%FML) are detailed in Table 3.
The model identified a significant Time x Technique interaction for the BPD group in both %WL (beta = 0.124 [95% CI: 0.013, 0.235], p = 0.028) and %FML (beta = 0.288 [95% CI: 0.135, 0.440], p < 0.001). Adjusted trajectories are illustrated in Figure 1 (Panels A and B), showing a sustained metabolic advantage for BPD throughout the 60-month horizon compared to RYGB and SG.
Analysis of covariates confirmed that age was a significant independent negative predictor of weight loss efficacy (beta = −0.420, p < 0.001). Additionally, baseline BMI was found to be a significant predictor for %WL trajectories (beta = 0.289 [95% CI: 0.029, 0.548], p = 0.029), whereas no such significant effect was observed for %FML (p = 0.584). Sex (male) did not significantly influence weight loss or fat mass loss trajectories in this adjusted model (p = 0.893 and p = 0.137, respectively).

3.3. Five-Year Evolution of Body Composition and Muscle Health

The detailed longitudinal evolution is summarized in Table 4 and Table 5. Numerically, the BPD group showed a higher mean percentage of fat mass loss at 60 months (57.9 ± 18.3%) compared to RYGB (39.8 ± 14.3%) and SG (42.0 ± 12.5%).
Regarding musculoskeletal health, no statistically significant differences were observed in SMM (p = 0.388) or AMM (p = 0.194) across techniques in the adjusted longitudinal models. While the BPD group showed a higher percentage of total muscle mass loss (%MML, 20.6 ± 5.5%, p = 0.019), absolute functional muscle mass values remained comparable across groups. All p-values reported for longitudinal comparisons were derived from linear mixed-effects models adjusted for baseline BMI, age, and sex. Overall, these findings indicate that inter-technique differences are primarily reflected in longitudinal adiposity trajectories rather than in absolute long-term muscle mass preservation.

4. Discussion

BS induces profound and sustained alterations in BC that extend beyond total weight loss, encompassing clinically relevant long-term modifications in FM, FFM, and SMM [1,4]. While total weight reduction remains the primary therapeutic target, contemporary metabolic research increasingly emphasizes the qualitative composition of weight loss as a determinant of long-term cardiometabolic and functional outcomes [2,3,4,5,6]. In this 5-year longitudinal cohort, we implemented multivariable LMM to isolate the independent effect of surgical technique from baseline heterogeneity in BMI and age, variables known to influence postoperative trajectories [23]. Our principal finding is that BPD confers a significantly superior long-term trajectory of adiposity reduction compared with RYGB and SG, without evidence of disproportionate impairment of absolute SMM in adjusted analyses.

4.1. Long-Term Adiposity Reduction: Trajectories Versus Isolated Endpoints

After rigorous adjustment, BPD demonstrated a significant Technique × Time interaction for both %WL (p = 0.028) and %FML (p < 0.001), indicating a sustained metabolic advantage across the 60-month horizon. Importantly, although crude 5-year means numerically favored BPD, statistical differences were attenuated at the isolated 60-month endpoint. This distinction is methodologically and clinically relevant. Long-term comparative cohorts [15,16] and randomized data such as the SLEEVEPASS trial [24] have shown that between-technique differences may narrow over time once baseline imbalances are accounted for. Similarly, Ceriani et al. [17] reported differential trajectories in weight and composition change across procedures, reinforcing that dynamic modeling better captures surgical impact than cross-sectional endpoints.
Our findings underscore the importance of repeated-measures modeling; endpoint-only analyses may obscure persistent trajectory differences, particularly when procedures are selectively allocated to patients with markedly different baseline BMI profiles.

4.2. Muscle Preservation: Proportional Versus Disproportionate Lean Mass Loss

A major concern regarding malabsorptive techniques is excessive lean tissue depletion. Consistent with prior literature [7,8,20,25,26,27,28], our cohort exhibited early reductions in FFM and SMM followed by stabilization after the first postoperative year. Davidson et al. [7] demonstrated similar patterns, with early lean mass decline and a subsequent plateau over 5 years. Although BPD was associated with higher %MML (%MML, 20.6 ± 5.5%, p = 0.019), absolute SMM (p = 0.388) and appendicular muscle mass (AMM, p = 0.194) did not differ significantly between techniques after multivariable adjustment.
This nuance is crucial: body composition modeling literature emphasizes that lean mass loss during weight reduction is strongly driven by baseline adiposity and total weight loss magnitude, reflecting a “proportional remodeling” phenomenon rather than selective tissue degradation [29]. Moreover, mechanistic studies suggest that BS may improve muscle insulin sensitivity and metabolic quality even when lean mass decreases modestly [30]. Improvements in muscle-to-fat ratio and systemic inflammatory status may offset numerical reductions in muscle quantity [27,30].

4.3. Sarcopenic Obesity and Diagnostic Variability

Sarcopenic obesity is increasingly recognized among bariatric candidates, with prevalence estimates ranging from 13% to over 20% depending on cut-offs and assessment methods [31,32,33,34]. Importantly, agreement between BIA and DXA-derived thresholds varies substantially [35,36], and reliance on FFM alone may overestimate true functional muscle mass in obesity [11]. Our study did not incorporate functional parameters such as handgrip strength, which are increasingly recommended for sarcopenia diagnosis [30,33]. Therefore, while absolute SMM was preserved longitudinally, future studies integrating functional metrics would strengthen the interpretation of long-term musculoskeletal safety.

4.4. Independent Role of Age and Baseline BMI

Age emerged as a robust independent negative predictor of weight and fat mass loss (p < 0.001), consistent with previous observational studies linking baseline characteristics to postoperative outcomes [23]. Age-related declines in anabolic responsiveness and resting energy expenditure may attenuate surgical response. Baseline BMI also significantly influenced %WL trajectories (p = 0.029), reinforcing the necessity of multivariable adjustment when comparing techniques that are selectively indicated for more severe phenotypes [15,16,17].

4.5. Methodological Considerations: Attrition and Longitudinal Modeling

Long-term bariatric cohorts are frequently characterized by substantial attrition [15,20], which reached 72.7% at 60 months in our study. However, sensitivity analyses (Table 2) revealed no significant baseline differences between completers and non-completers, supporting the plausibility of a MAR mechanism. Multivariable LMM provides a robust framework for handling repeated measures under MAR assumptions without restricting analyses to complete cases [22]. Nevertheless, informative missingness cannot be entirely excluded, and the absence of significant inter-technique differences at the isolated 60-month endpoint may partly reflect reduced statistical power in the final sample (n = 36).

4.6. Body Composition Assessment: BIA in Context

Multi-frequency BIA was used for longitudinal monitoring. Although practical and validated in bariatric populations [9,10,12,26], systematic differences between BIA and DXA have been documented, particularly for regional lean mass assessment [35,36]. Standardized pre-assessment conditions were strictly implemented to minimize hydration-related bias. Nonetheless, incorporation of DXA or imaging modalities in future prospective cohorts would enhance precision.

4.7. Limitations

Several limitations warrant consideration. First, the retrospective design precludes causal inference. Second, technique allocation was based on clinical phenotype, introducing potential residual confounding despite multivariable adjustment. Third, high attrition at 5 years limits external validity. Fourth, BIA rather than DXA was used. Fifth, dietary protein intake, supplementation adherence, and physical activity were not systematically assessed, which are known to influence lean mass preservation [14,18].

5. Conclusions

After rigorous adjustment for baseline heterogeneity, BPD provides a superior long-term trajectory of adiposity reduction compared with RYGB and SG, without evidence of disproportionate impairment of absolute skeletal muscle mass over a 5-year horizon. These findings reinforce the concept of proportional body composition remodeling following bariatric surgery and highlight the importance of longitudinal modeling and multivariable adjustment in evaluating long-term metabolic outcomes.

Author Contributions

Conceptualization, M.A.-G. and M.D.B.-P.; methodology, M.A.-G. and M.D.B.-P.; software, M.A.-G.; validation, E.G.A., D.G.A.-C. and M.D.B.-P.; formal analysis, M.A.-G.; investigation, M.A.-G., E.G.A., D.G.A.-C., D.G.S., M.L.M., A.U.F., M.C.D.P., M.C.R., J.M.S.F. and L.G.-H.G.; resources, M.D.B.-P.; data curation, M.A.-G.; writing—original draft preparation, M.A.-G.; writing—review and editing, M.A.-G., E.G.A., D.G.A.-C., D.G.S., M.L.M., A.U.F., M.C.D.P., M.C.R., J.M.S.F., L.G.-H.G. and M.D.B.-P.; visualization, M.A.-G.; supervision, M.D.B.-P.; project administration, M.D.B.-P. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

The study was conducted in accordance with the Declaration of Helsinki and approved by the Clinical Research Ethics Committee of the Complejo Asistencial Universitario de León (Internal Registration No. 2104, approval date: 26 January 2021).

Informed Consent Statement

Informed consent was obtained from all subjects involved in the study.

Data Availability Statement

The data presented in this study are available on request from the corresponding author as per European legislation on data protection.

Acknowledgments

The authors would like to thank the clinical and nursing staff of the Departments of Endocrinology and Nutrition and General Surgery of the Complejo Asistencial Universitario de León for their support in patient follow-up and data collection.

Conflicts of Interest

The authors declare no conflicts of interest.

References

  1. Andolfi, C.; Fisichella, P.M. Epidemiology of Obesity and Associated Comorbidities. J. Laparoendosc. Adv. Surg. Tech. A 2018, 28, 919–924. [Google Scholar] [CrossRef]
  2. Maimoun, L.; Lefebvre, P.; Jaussent, A.; Nocca, D.; Meziane, J.; Picot, M.C.; Mariano-Goulart, D.; Sultan, A. Acute and Longer-Term Body Composition Changes after Bariatric Surgery. Surg. Obes. Relat. Dis. 2019, 15, 1965–1973. [Google Scholar] [CrossRef]
  3. Ashtary-Larky, D.; Ghanavati, M.; Lamuchi-Deli, N.; Adibi, B.; Azizidoost, S.; Miabi, M.S.; Mohammadi, R.; Alipour, M. Effects of Gradual Versus Rapid Weight Loss on Body Composition and Resting Metabolic Rate. Br. J. Nutr. 2020, 124, 1121–1132. [Google Scholar] [CrossRef] [PubMed]
  4. Mulla, C.M.; Middelbeek, R.J.W.; Patti, M.E. Mechanisms of weight loss and improved metabolism following bariatric surgery. Obesity 2018, 26, 1168–1177. [Google Scholar] [CrossRef]
  5. Sylivris, A.; Mesinovic, J.; Scott, D.; Jansons, P. Body composition changes at 12 months following different surgical weight loss interventions in adults with obesity: A systematic review and meta-analysis of randomized controlled trials. Obes. Rev. 2022, 23, e13442. [Google Scholar] [CrossRef]
  6. Sivakumar, J.; Chen, Q.; Sutherland, T.R.; Read, M.; Ward, S.; Chong, L.; Hii, M.W. Body composition differences between excess weight loss ≥50% and <50% at 12 months following bariatric surgery. Obes. Surg. 2022, 32, 2556–2566. [Google Scholar] [CrossRef]
  7. Davidson, L.E.; Yu, W.; Goodpaster, B.H.; DeLany, J.P.; Widen, E.; Lemos, T.; Strain, G.W.; Pomp, A.; Courcoulas, A.P.; Lin, S.X.; et al. Fat-free mass and skeletal muscle mass five years after bariatric surgery. Obesity 2018, 26, 1130–1136. [Google Scholar] [CrossRef] [PubMed]
  8. Nuijten, M.A.H.; Eijsvogels, T.M.H.; Monpellier, V.M.; Janssen, I.M.C.; Hazebroek, E.J.; Hopman, M.T.E. The magnitude and progress of lean body mass, fat-free mass, and skeletal muscle mass loss following bariatric surgery: A systematic review and meta-analysis. Obes. Rev. 2022, 23, e13370. [Google Scholar] [CrossRef]
  9. Savastano, S.; Belfiore, A.; Di Somma, C.; Mauriello, C.; Rossi, A.; Pizza, G.; De Rosa, A.; Prestieri, G.; Angrisani, L.; Colao, A. Validity of bioelectrical impedance analysis to estimate body composition changes after bariatric surgery in premenopausal morbidly obese women. Obes. Surg. 2010, 20, 332–339. [Google Scholar] [CrossRef] [PubMed]
  10. Widen, E.M.; Strain, G.; King, W.C.; Yu, W.; Lin, S.; Goodpaster, B.; Thornton, J.; Courcoulas, A.; Pomp, A.; Gallagher, D. Validity of bioelectrical impedance analysis for measuring changes in body water and percent fat after bariatric surgery. Obes. Surg. 2014, 24, 847–854. [Google Scholar] [CrossRef]
  11. Jensen, B.; Braun, W.; Geisler, C.; Both, M.; Klückmann, K.; Müller, M.J.; Bosy-Westphal, A. Limitations of fat-free mass for the assessment of muscle mass in obesity. Obes. Facts 2019, 12, 307–315. [Google Scholar] [CrossRef]
  12. Ballesteros-Pomar, M.D.; González de Francisco, T.; Calleja-Fernández, A.; de la Iglesia-López, A.; Pintor de la Maza, B.; Vidal-Casariego, A.; de Luis-Román, D.A. Bioelectrical impedance analysis as an alternative to DXA in the assessment of fat mass and appendicular lean mass in severe obesity. Nutrition 2022, 93, 111442. [Google Scholar]
  13. Stewart, A.; Marfell-Jones, M.; Olds, T.; de Ridder, H. International standards for anthropometric assessment; ISAK: Lower Hutt, New Zealand, 2011. [Google Scholar]
  14. Abiri, B.; Valizadeh, M.; Seifi, Z.; Amini, S.; Haidari, F. The role of nutritional factors in fat-free mass preservation and body composition changes after bariatric surgery: A systematic review of the available evidence. Eat. Weight Disord. 2025, 30, 51. [Google Scholar]
  15. Maciejewski, M.L.; Arterburn, D.E.; Van Scoyoc, L.; Smith, V.A.; Yancy, W.S., Jr.; Weidenbacher, H.J.; Livingston, E.H.; Olsen, M.K. Bariatric surgery and long-term durability of weight loss. JAMA Surg. 2016, 151, 1046–1055. [Google Scholar] [CrossRef]
  16. Arterburn, D.E.; Wellman, R.; Emiliano, A.; Smith, S.R.; Odegaard, A.O.; Murali, S.; Williams, N.; Coleman, K.J.; Courcoulas, A.; Coley, R.Y.; et al. Comparative effectiveness and safety of bariatric procedures for weight loss: A PCORnet cohort study. Ann. Intern. Med. 2018, 169, 741–750. [Google Scholar] [CrossRef] [PubMed]
  17. Ceriani, V.; Pinna, F.; Galantino, A.; Zakaria, A.S.; Manfrini, R.; Pontiroli, A.E.; Folli, F. Biliopancreatic diversion (BPD), long common limb revisional biliopancreatic diversion (BPD + LCL-R), Roux-en-Y gastric bypass (RYGB) and sleeve gastrectomy (SG) mediate differential quantitative changes in body weight and qualitative modifications in body composition: A 5-year study. Acta Diabetol. 2022, 59, 39–48. [Google Scholar] [PubMed]
  18. Alba, D.L.; Wu, L.; Cawthon, P.M.; Mulligan, K.; Lang, T.; Patel, S.; King, N.J.; Carter, J.T.; Rogers, S.J.; Posselt, A.M.; et al. Changes in lean mass, absolute and relative muscle strength, and physical performance after gastric bypass surgery. J. Clin. Endocrinol. Metab. 2019, 104, 711–720. [Google Scholar] [CrossRef]
  19. Palacio, A.; Quintiliano, D.; Lira, I.; Navarro, P.; Orellana, V.; Reyes, A.; Henriquez, D. Changes in body composition in patients following bariatric surgery: Gastric bypass and sleeve gastrectomy. Nutr. Hosp. 2019, 36, 334–349. [Google Scholar] [PubMed]
  20. Haghighat, N.; Kazemi, A.; Asbaghi, O.; Jafarian, F.; Moeinvaziri, N.; Hosseini, B.; Amini, M. Long-term effect of bariatric surgery on body composition in patients with morbid obesity: A systematic review and meta-analysis. Clin. Nutr. 2021, 40, 1755–1766. [Google Scholar] [CrossRef]
  21. Silva, L.B.; de Oliveira, L.P.M.; Guedes de Oliveira, T.; Canut de Campos, V.; de Souza Rocha, R.; de Castro Antunes, A. Evolution of body composition of obese patients undergoing bariatric surgery. Clin. Nutr. ESPEN 2019, 31, 95–99. [Google Scholar] [CrossRef]
  22. Gabrio, A.; Plumpton, C.; Banerjee, S.; Leurent, B. Linear mixed models to handle missing at random data in trial-based evaluations. Health Econ. 2022, 31, 1276–1287. [Google Scholar] [PubMed]
  23. Sans, A.; Bailly, L.; Anty, R.; Sielezenef, I.; Gugenheim, J.; Tran, A.; Gual, P.; Iannelli, A. Baseline anthropometric and metabolic parameters correlate with weight loss in women 1-year after laparoscopic Roux-en-Y gastric bypass. Obes. Surg. 2017, 27, 2940–2949. [Google Scholar] [CrossRef]
  24. Grönroos, S.; Helmiö, M.; Juuti, A.; Tiusanen, R.; Hurme, S.; Löyttyniemi, E.; Ovaska, J.; Leivonen, M.; Peromaa-Haavisto, P.; Mäklin, S.; et al. Effect of laparoscopic sleeve gastrectomy vs Roux-en-Y gastric bypass at 7 years: The SLEEVEPASS randomized clinical trial. JAMA Surg. 2021, 156, 137–146. [Google Scholar]
  25. Jassil, F.C.; Yu, E.W.; Bouxsein, M.L.; Roy, A.E.; Sayer, A.A.; Fielding, R.A.; Johnson, D.D.; LeBoff, M.S.; Muschitz, C. One-year changes in body composition and musculoskeletal health following metabolic/bariatric surgery. J. Clin. Endocrinol. Metab. 2024, 109, e1598–e1608. [Google Scholar] [CrossRef]
  26. Carrasco, F.; Carrasco Navarro, G.N.; Rojas Moncada, P.; Papapietro, K.; Salazar, G. Body composition assessment before and after weight loss following a Roux-en-Y gastric bypass. Are bioimpedanciometry estimations reliable? Nutr. Hosp. 2020, 37, 1150–1156. [Google Scholar] [CrossRef]
  27. Oliveira, S.C.; Neves, J.S.; Souteiro, P.; Magalhães, D.; Guerreiro, V.; Bettencourt-Silva, R.; Costa, M.M.; Varela, A.; Queirós, J.; Freitas, P.; et al. Impact of bariatric surgery on long-term cardiovascular risk: Comparative effectiveness of different surgical procedures. Obes. Surg. 2020, 30, 673–680. [Google Scholar]
  28. Martínez, M.C.; Fidilio Meli, E.; Palmas Candia, F.; Filippi, F.; Vilallonga, R.; Cordero, E.; Hernández, I.; Zabalegui Eguinoa, A.; Burgos, R.; Vila, A.; et al. The impact of bariatric surgery on the muscle mass in patients with obesity: 2-year follow-up. Obes. Surg. 2022, 32, 625–633. [Google Scholar] [CrossRef]
  29. Bosy-Westphal, A.; Müller, M.J. Diagnosis of obesity based on body composition-associated health risks—Time for a change in paradigm. Obes. Rev. 2021, 22, e13190. [Google Scholar] [CrossRef] [PubMed]
  30. Orioli, L.; Thissen, J.-P.; Loumaye, A. Changes in body composition, muscle function, and muscle insulin sensitivity induced by obesity and bariatric surgery: Implications for sarcopenic obesity. Clin. Nutr. 2026, 56, 106547. [Google Scholar] [PubMed]
  31. Molero, J.; Olbeyra, R.; Flores, L.; Jiménez, A.; de Hollanda, A.; Andreu, A.; Ibarzabal, A.; Moizé, V.; Cañizares, S.; Balibrea, J.M.; et al. Prevalence of low skeletal muscle mass following bariatric surgery. Clin. Nutr. ESPEN 2022, 49, 436–441. [Google Scholar] [CrossRef]
  32. Vieira, F.T.; Godziuk, K.; Lamarca, F.; Melendez-Araújo, M.S.; Lima, R.M.; Prado, C.M.; de Carvalho, K.M.B.; Dutra, E.S. Sarcopenic obesity diagnosis by different criteria mid- to long-term post-bariatric surgery. Clin. Nutr. 2022, 41, 1932–1941. [Google Scholar] [CrossRef]
  33. Vieira, F.T.; Prado, C.M.; Thorlakson, J.; Stoklossa, C.J.; Jin, J.; Donini, L.M.; Gramlich, L.; Bielawska, B. Sarcopenic obesity in metabolic and bariatric surgery: A scoping review. Obes. Rev. 2025, 26, e13973. [Google Scholar] [CrossRef]
  34. González Arnáiz, E.; Ariadel Cobo, D.; Estébanez, B.; Barajas Galindo, D.; Pintor de la Maza, B.; Urioste Fondo, A.; Dameto Pons, C.; Cuevas, M.J.; Ballesteros Pomar, M.D. Prevalence of sarcopenic obesity according to different diagnostic methods and cut-off points in candidates for bariatric surgery. Clin. Nutr. 2024, 43, 1087–1093. [Google Scholar] [CrossRef] [PubMed]
  35. Feng, Q.; Bešević, J.; Conroy, M.; Omiyale, W.; Lacey, B.; Allen, N. Comparison of body composition measures assessed by bioelectrical impedance analysis versus dual-energy X-ray absorptiometry in UK Biobank. Clin. Nutr. ESPEN 2024, 63, 214–225. [Google Scholar] [CrossRef] [PubMed]
  36. Cailleaux, P.-E.; Achamrah, N.; Folope, V.; Grigioni, S.; Déchelotte, P.; Coëffier, M. Comparison of dual X-ray absorptiometry and bioelectrical impedance analysis for fat-free mass and muscle mass assessment in obese older adults. Clin. Nutr. ESPEN 2025, 70, 345–351. [Google Scholar] [CrossRef] [PubMed]
Jcm 15 02354 g001
Figure 1. Long-term (5-year) trajectories of body composition following BPD, RYGB, and SG. (A) Percentage of total weight loss (%WL). (B) Percentage of fat mass loss (%FML). (C) Absolute skeletal muscle mass (SMM) in kilograms. Solid lines represent adjusted mean estimates from multivariable linear mixed-effects models (LMM) adjusted for baseline BMI, age, and sex. BPD: Biliopancreatic Diversion; RYGB: Roux-en-Y Gastric Bypass; SG: Sleeve Gastrectomy.
Figure 1. Long-term (5-year) trajectories of body composition following BPD, RYGB, and SG. (A) Percentage of total weight loss (%WL). (B) Percentage of fat mass loss (%FML). (C) Absolute skeletal muscle mass (SMM) in kilograms. Solid lines represent adjusted mean estimates from multivariable linear mixed-effects models (LMM) adjusted for baseline BMI, age, and sex. BPD: Biliopancreatic Diversion; RYGB: Roux-en-Y Gastric Bypass; SG: Sleeve Gastrectomy.
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Table 1. Baseline clinical characteristics of the study population.
Table 1. Baseline clinical characteristics of the study population.
BPD (n = 55)RYGB (n = 31)SG (n = 42)p-Value
Age (years)43.1 ± 9.346.8 ± 9.148 ± 9.40.029
Female (%)43.6% (24/55)29% (9/31)23.8% (10/42)0.101
Weight (kg)148.4 ± 28.1119.8 ± 17.7113.9 ± 15.6<0.001
BMI (kg/m2)52.3 ± 8.343.6 ± 5.842.7 ± 4.2<0.001
FM (kg)/(%)70.9 ± 15.8/47.6 ± 4.153.5 ± 11.4/44.5 ± 5.449.9 ± 7.7/43.8 ± 3.9<0.001
FFM (kg)/(%)76.8 ± 14.7/51.9 ± 5.165.8 ± 10.5/55.1 ± 5.263.0 ± 11.4/55.1 ± 5.3<0.001
MM (kg)73.7 ± 13.863.1 ± 10.360.8 ± 9.9<0.001
SMM (kg)28.7(22.1–34.1)24.1(21.3–28.6)23.1(20–26.6)<0.001
AMM (kg)34.8 (25.5–44.1)28.2 (23.5–33.8)24.4 (21.7–29.2)<0.001
Values are expressed as mean ± standard deviation. BPD: Biliopancreatic Diversion; RYGB: Roux-en-Y Gastric Bypass; SG: Sleeve Gastrectomy; BMI: Body Mass Index. p-values derived from one-way ANOVA (continuous variables) and Chi-square test (categorical variables).
Table 2. Sensitivity analysis: Comparison between Completers and Non-completers.
Table 2. Sensitivity analysis: Comparison between Completers and Non-completers.
Completers (n = 36)Non-Completers (n = 92)p-Value
Age (years)44.3 ± 10.145.6 ± 9.40.487
Baseline BMI (kg/m2)46.5 ± 7.047.3 ± 8.40.626
Initial weight (kg)125.4 ± 25.5132.1 ± 27.90.208
Sex (female, %)63.9%67.4%0.866
Technique (BPD/RYGB/SG)13/11/1242/20/300.501
Values are expressed as mean ± standard deviation at baseline. Completers are defined as patients with a minimum of 60 months of follow-up. p-values derived from independent samples t-test.
Table 3. Multivariable LMM Coefficients for %WL and %FML Trajectories.
Table 3. Multivariable LMM Coefficients for %WL and %FML Trajectories.
PredictorBeta (%WL) [95% CI]p-ValueBeta (%FML) [95% CI]p-Value
BPD × Time interaction0.124 [0.013, 0.235]0.0280.288 [0.135, 0.440]<0.001
RYGB × Time interaction−0.058 [−0.175, 0.059]0.329−0.079 [−0.239, 0.081]0.333
Baseline BMI (kg/m2)0.289 [0.029, 0.548]0.0290.117 [−0.301, 0.534]0.584
Age (years)−0.420 [−0.601, −0.240]<0.001−0.630 [−0.920, −0.339]<0.001
Sex (Male)−0.239 [−3.717, 3.239]0.8934.244 [−1.348, 9.837]0.137
Beta represents the fixed-effect coefficient from the Linear Mixed-Effects Model (LMM). %WL: percentage of total weight loss; %FML: percentage of fat mass loss. Models were adjusted for sex as a covariate. Baseline BMI and Age refer to pre-surgical values. Reference category for technique: Sleeve Gastrectomy.
Table 4. Longitudinal Evolution of Anthropometric and Fat Mass Parameters.
Table 4. Longitudinal Evolution of Anthropometric and Fat Mass Parameters.
VariableTechnique12 m24 m36 m48 m60 mp-Value 1
Weight (kg)BPD100.4 ± 22.493.4 ± 19.293.7 ± 19.293.7 ± 20.688.8 ± 19.4<0.001
RYGB78.6 ± 14.280.2 ± 15.283.9 ± 14.285.4 ± 14.884.8 ± 11.1
SG80.7 ± 16.782.1 ± 20.980.8 ± 14.180.9 ± 14.782.2 ± 14.7
BMI (kg/m2)BPD35.5 ± 7.133.4 ± 6.433.5 ± 5.933.7 ± 6.132.3 ± 5.6<0.001
RYGB29.1 ± 5.629.5 ± 5.830.9 ± 5.532.2 ± 5.931.2 ± 3.8
SG29.7 ± 3.929.4 ± 3.429.5 ± 4.430.8 ± 3.530.9 ± 3.5
%WL (%)BPD32.1 ± 10.836.1 ± 9.137.5 ± 11.435.1 ± 14.138.5 ± 11.10.028
RYGB33.1 ± 8.231.8 ± 9.128.6 ± 8.427.7 ± 9.825.5 ± 7.8
SG30.0 ± 9.327.7 ± 16.129.5 ± 9.927.7 ± 9.327.3 ± 8.2
FM (kg)BPD34.5 ± 14.230.5 ± 12.131.2 ± 12.331.5 ± 13.528.9 ± 14.2<0.001
RYGB23.5 ± 10.125.2 ± 10.431.3 ± 12.530.9 ± 10.328.6 ± 6.1
SG25.1 ± 7.425.2 ± 5.826.5 ± 6.328.5 ± 6.229.4 ± 6.6
%FML(%)BPD51.2 ± 17.656.4 ± 17.256.9 ± 18.253.8 ± 21.757.9 ± 18.30.011
RYGB55.7 ± 14.152.1 ± 14.639.3 ± 20.941.6 ± 15.339.8 ± 14.3
SG50.1 ± 12.648.7 ± 12.147.2 ± 14.742.6 ± 13.842.0 ± 12.5
1 p-values in this table refer to the overall longitudinal effect of ‘Time’ within the adjusted LMM. Comparative analysis between surgical techniques is reported via the coefficients in Table 3.
Table 5. Longitudinal Evolution of Muscle Mass and Fat-Free Mass Parameters.
Table 5. Longitudinal Evolution of Muscle Mass and Fat-Free Mass Parameters.
VariableTechnique12 m24 m36 m48 m60 mp-Value 1
FFM (kg)BPD65.9 ± 11.463.1 ± 10.261.4 ± 12.162.2 ± 13.462.6 ± 15.10.499
RYGB55.1 ± 8.756.4 ± 10.155.8 ± 8.854.5 ± 8.756.1 ± 9.3
SG55.6 ± 11.255.0 ± 9.454.3 ± 10.252.3 ± 10.452.8 ± 10.5
%FFML(%)BPD13.8 (10.5–20.2)18.1 (13.0–21.9)19.3 (16.1–23.9)16.9 (12.1–23.8)20.5 (13.5–23.8)0.606
RYGB14.2 (11.6–17.7)14.9 (11.2–18.4)15.1 (11.3–17.5)16.1 (12.4–19.2)15.7 (11.4–16.9)
SG15.4 (10.9–18.3)16.1 (11.9–18.1)14.7 (11.4–17.1)14.7 (11.9–17.6)13.7 (11.4–16.8)
MM (kg)BPD62.5 ± 11.159.8 ± 10.160.0 ± 10.259.1 ± 12.456.9 ± 11.40.043
RYGB52.2 ± 8.352.5 ± 8.653.1 ± 8.451.7 ± 8.353.3 ± 8.8
SG52.8 ± 10.450.8 ± 9.151.5 ± 9.849.7 ± 10.150.1 ± 9.8
%MML(%)BPD14.9 ± 6.517.8 ± 5.718.3 ± 8.317.4 ± 10.220.6 ± 5.50.019
RYGB15.9 ± 5.115.9 ± 5.115.6 ± 5.416.8 ± 6.215.3 ± 3.8
SG14.2 ± 7.516.2 ± 4.415.6 ± 6.315.7 ± 5.415.5 ± 5.3
SMM (kg)BPD27.6 (21.3–33.5)25.7 (21.2–31.9)25.5 (22.8–32.2)25.8 (20.3–32.1)24.8 (21.7–32.9)0.088
RYGB22.1 (19.4–28.2)21.8 (20.2–25.8)21.0 (20.1–27.5)20.5 (19.2–23.4)22.1 (20.2–27.1)
SG21.7 (18.6–28.6)20.7 (18.1–25.6)21.1 (18.5–25.6)18.7 (17.5–22.4)19.4 (17.7–23.3)
1 p-values in this table refer to the overall longitudinal effect of ‘Time’ within the adjusted LMM. Comparative analysis between surgical techniques is reported via the coefficients in Table 3.
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MDPI and ACS Style

Antequera-González, M.; González Arnáiz, E.; Ariadel-Cobo, D.G.; García Sastre, D.; López Melgar, M.; Urioste Fondo, A.; Dameto Pons, M.C.; Casado Rodríguez, M.; Silva Fernández, J.M.; González-Herráez García, L.; et al. Long-Term Body Composition Trajectories After Bariatric Surgery: A 5-Year Comparative Study of Biliopancreatic Diversion, Roux-en-Y Gastric Bypass, and Sleeve Gastrectomy. J. Clin. Med. 2026, 15, 2354. https://doi.org/10.3390/jcm15062354

AMA Style

Antequera-González M, González Arnáiz E, Ariadel-Cobo DG, García Sastre D, López Melgar M, Urioste Fondo A, Dameto Pons MC, Casado Rodríguez M, Silva Fernández JM, González-Herráez García L, et al. Long-Term Body Composition Trajectories After Bariatric Surgery: A 5-Year Comparative Study of Biliopancreatic Diversion, Roux-en-Y Gastric Bypass, and Sleeve Gastrectomy. Journal of Clinical Medicine. 2026; 15(6):2354. https://doi.org/10.3390/jcm15062354

Chicago/Turabian Style

Antequera-González, María, Elena González Arnáiz, Diana G. Ariadel-Cobo, Diana García Sastre, María López Melgar, Ana Urioste Fondo, M. Carmen Dameto Pons, María Casado Rodríguez, Jesús Manuel Silva Fernández, Luis González-Herráez García, and et al. 2026. "Long-Term Body Composition Trajectories After Bariatric Surgery: A 5-Year Comparative Study of Biliopancreatic Diversion, Roux-en-Y Gastric Bypass, and Sleeve Gastrectomy" Journal of Clinical Medicine 15, no. 6: 2354. https://doi.org/10.3390/jcm15062354

APA Style

Antequera-González, M., González Arnáiz, E., Ariadel-Cobo, D. G., García Sastre, D., López Melgar, M., Urioste Fondo, A., Dameto Pons, M. C., Casado Rodríguez, M., Silva Fernández, J. M., González-Herráez García, L., & Ballesteros-Pomar, M. D. (2026). Long-Term Body Composition Trajectories After Bariatric Surgery: A 5-Year Comparative Study of Biliopancreatic Diversion, Roux-en-Y Gastric Bypass, and Sleeve Gastrectomy. Journal of Clinical Medicine, 15(6), 2354. https://doi.org/10.3390/jcm15062354

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