Key Points
Question
Among patients undergoing metabolic bariatric surgery, what proportion meet criteria for clinical obesity under the new Lancet Diabetes and Endocrinology Commission framework, and does this definition capture differences in disease burden beyond body mass index (BMI)?
Findings
In this cross-sectional study of 2316 bariatric surgery candidates, clinical obesity was the most prevalent category across centers, although a substantial minority had preclinical obesity despite similar BMI distributions. Clinical obesity was associated with higher perioperative risk and greater baseline disease burden, including higher estimated cardiovascular risk.
Meaning
These findings suggest that BMI alone may not adequately capture disease severity among bariatric surgery candidates and support the new framework distinguishing clinical from preclinical obesity to improve patient characterization, risk stratification, treatment prioritization, and alignment of therapeutic goals.
This cross-sectional study assesses the prevalence and demographic and clinical profiles among adults with clinical and preclinical obesity at high-volume metabolic bariatric surgery centers in Europe and South America.
Abstract
Importance
Metabolic bariatric surgery (MBS) is the most effective treatment for severe obesity, yet patient selection and prioritization remain largely based on body mass index (BMI; calculated as weight in kilograms divided by height in meters squared) thresholds rather than clinical conditions. The Lancet Diabetes and Endocrinology Commission recently proposed distinguishing clinical obesity (adiposity with obesity-related organ dysfunction) from preclinical obesity (excess adiposity with preserved function). The implications of this framework for MBS practice have not been evaluated.
Objective
To assess the prevalence of clinical and preclinical obesity among MBS candidates and examine their demographic and clinical profiles, perioperative risk, and long-term prognosis.
Design, Setting, and Participants
This retrospective, multicenter, cross-sectional study audited data of adults (aged ≥18 years) undergoing primary MBS (laparoscopic gastric bypass or sleeve gastrectomy) between January 1, 2014, and December 31, 2025, at 4 high-volume tertiary centers in the UK, Spain, France, and Brazil. Patients who underwent revisional procedures or multiple bariatric operations within the same year were excluded.
Exposures
Classification of obesity as clinical or preclinical using a pragmatic operationalization.
Main Outcomes and Measures
The primary outcome was the prevalence of clinical obesity. Secondary outcomes were patterns of organ dysfunction, BMI levels, baseline American Society of Anesthesiologists classification and Charlson Comorbidity Index, estimated 10-year cardiovascular risk (Framingham risk score), and 30-day major postoperative complications (Clavien-Dindo grade ≥3). Comparative analyses between patients with clinical obesity vs those with preclinical obesity were performed only within each individual cohort. No direct statistical comparisons were performed between centers as patient-level data were not shared across cohorts.
Results
Among the 2316 patients included, 1709 (73.8%) had clinical obesity (mean [SD] age across cohorts, 45.6 [11.0] to 48.9 [11.7] years; 1149 women [67.2%]) and 607 (26.2%) had preclinical obesity (mean [SD] age across cohorts, 34.7 [10.4] to 40.0 [9.8] years; 486 women [80.1%]). Clinical obesity was the most prevalent category across all centers (from 62.7% in the Brazilian cohort to 79.3% in the UK cohort). Mean (SD) BMI ranged from 40.2 (4.9) (preclinical obesity in the Brazilian cohort) to 48.5 (9.0) (preclinical obesity in the UK cohort), and BMI levels and BMI category distributions (<40, 40-49, ≥50) were similar between clinical and preclinical obesity. Patients with clinical obesity were significantly older compared with those with preclinical obesity (UK cohort: mean [SD], 48.9 [11.7] vs 39.5 [9.7] years; French cohort: mean [SD], 45.6 [11.0] vs 34.7 [10.4] years; Spanish cohort: mean [SD], 47.1 [9.3] vs 40.0 [9.8] years; Brazilian cohort: mean [SD], 48.3 [11.7] vs 40.0 [9.4] years (all P < .001) and had a higher American Society of Anesthesiologists classification (UK cohort: median [IQR], 3 [2-3] vs 2 [2-3]; P < .001; French cohort: median [IQR], 3 [3-3] vs 2 [2-3]; P < .001; Spanish cohort: median [IQR], 2 [2-3] vs 2 [1-2]; P < .001; Brazilian cohort: median [IQR], 2 [2-2] vs 2 [2-2]; P = .02), as well as higher estimated cardiovascular Framingham risk score (Spanish cohort: median [IQR], 1.31 [0.20-4.34] vs 0.20 [0.20-1.68]; Brazilian cohort: median [IQR], 1.57 [0.20-5.28] vs 0.20 [0.20-0.20]; French cohort: median [IQR], 8.00 [3.00-13.00] vs 2.00 [1.00-4.00]) (all P < .001) and all-cause mortality risk (Charlson Comorbidity Index score) (UK cohort: median [IQR], 1 [0-2] vs 0 [0-0]; Spanish cohort: median [IQR], 1 [0-1] vs 0; Brazilian cohort: median [IQR], 1 [1-3] vs 1 [0-1]) (all P < .001). Clinical obesity was associated with increased 30-day major postoperative complications (Clavien-Dindo grade ≥3) compared with preclinical obesity in the French cohort (4.0% vs 1.1%; P = .04).
Conclusions and Relevance
This international, multicenter cross-sectional study found that the majority of MBS candidates met criteria for clinical obesity, while a substantial minority were classified as having preclinical obesity. Despite similar BMI distributions, patients with clinical obesity may have a greater disease burden, higher operative risk, and higher estimated cardiovascular risk, supporting its potential value as a clinically meaningful framework for surgical practice.
Introduction
Metabolic bariatric surgery (MBS) is the most effective and durable treatment for obesity, resulting in sustained weight loss, dramatic improvement of cardiometabolic risk, and reduced long-term mortality.1,2,3,4 However, patient selection for surgery and prioritization remain largely anchored in body mass index (BMI) thresholds (calculated as weight in kilograms divided by height in meters squared) and a limited set of obesity-associated diseases.5,6 This approach was originally designed as a pragmatic proxy for health risk, but it does not consistently reflect the presence, severity, or urgency of obesity-related disease in individual patients. As a result, individuals with similar BMIs can have profoundly different degrees of organ dysfunction, operative risk, and expected benefit, while others may be denied access to surgery due to the absence of narrowly defined qualifying obesity-associated diseases.7,8 The recent Lancet Diabetes and Endocrinology Commission on the Definition and Diagnosis of Clinical Obesity proposed a clinically grounded framework that distinguishes clinical obesity, defined as organ dysfunction or impaired daily functioning attributable to excess adiposity, from preclinical obesity, characterized as excess adiposity with preserved organ function and variable future risk.9 This framework shifts the diagnosis of obesity away from body size alone and toward a demonstrable health impact, aligning obesity with diagnostic principles used throughout medicine.
While the commission framework has important implications for care and policy, its practical relevance for metabolic bariatric surgical cohorts has not been directly evaluated. Surgical populations provide a particularly informative setting to test the framework. Patients referred for MBS represent an already-selected group with more severe forms of obesity but for whom the intensity and invasiveness of treatment require clear justification, proportionality, and careful risk assessment. If the commission framework meaningfully stratifies disease burden within contemporary surgical cohorts, it may help clarify the clinical rationale for surgery (disease treatment vs risk reduction), improve perioperative risk stratification, and inform prioritization strategies in settings in which surgical capacity is limited. It may also reveal the extent to which BMI thresholds fail to distinguish disease severity in the very population for whom treatment decisions carry the highest clinical and resource implications.
In this study, we applied the Lancet Commission diagnostic criteria to patients undergoing MBS in 4 high-volume bariatric centers in Europe and South America. Our primary objective was to quantify the prevalence of clinical obesity within surgical cohorts. Secondary objectives were to characterize patterns of organ dysfunction, compare baseline disease severity and estimated long-term mortality and cardiovascular risk between clinical and preclinical obesity, and explore differences in perioperative safety outcomes.
Methods
Study Design and Setting
This multicenter, cross-sectional study used prospectively maintained clinical databases and registries from 4 high-volume tertiary centers: King’s College Hospital (London, UK), Hospital del Mar (Barcelona, Spain), Centre Hospitalier Universitaire de Lille (Lille, France), and Hospital Alemão Oswaldo Cruz (São Paulo, Brazil). Participants were patients who underwent MBS between January 1, 2014, and December 31, 2025, with cohort-specific enrollment periods within this time frame across participating centers.
No new patient recruitment, intervention, or patient contact was performed for this analysis. Patients and the public were not involved in study design, recruitment, or conduct. Data were drawn from preexisting institutional databases rather than created for this study. At King’s College Hospital, the database was maintained for routine clinical audit and service evaluation purposes. Consistent with prior institutional determinations for audit reports using this database, separate ethics approval and informed consent were not required. Similarly, for the Hospital Alemão Oswaldo Cruz cohort, the database was maintained for clinical audit and service evaluation, and use of these data did not require additional ethics committee approval or informed consent according to local institutional policies. At the other contributing centers, datasets had been established for research purposes for other studies under locally approved ethical frameworks. For Hospital del Mar, data were obtained from the OBEMAR registry approved by the Clinical Research Ethics Committee of Hospital del Mar (CEIm-Parc de Salut Mar; No. N2017/7722/I), with written informed consent. For Centre Hospitalier Universitaire de Lille, data were obtained from the ABOS study approved by the Comité de Protection des Personnes Nord Ouest VI, with written informed consent.
Each participating center retained responsibility for its local dataset and performed analyses locally using a harmonized protocol developed jointly by the study collaborators. No patient-level data were shared among centers. Only aggregated study results were shared for central synthesis, pooled interpretation, and comparison across cohorts. This study was reported in accordance with the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) reporting guideline for cross-sectional studies.10
Participants
Inclusion criteria were age 18 years or older and primary laparoscopic Roux-en-Y gastric bypass or laparoscopic sleeve gastrectomy. Exclusion criteria were revisional procedures (eg, gastric band removal, conversion for weight recurrence or complications) and multiple bariatric operations within the same year. Cases in which obesity-related disease status had not been formally assessed and documented as part of standard clinical care were excluded from the analysis. Race and ethnicity data were not collected because these variables were not uniformly available across the participating institutional databases and were not included among the predefined study variables. Patient selection is summarized in the eFigure in Supplement 1.
Outcomes and Variables
The primary outcome was the prevalence of clinical obesity among surgical candidates according to Lancet Commission criteria. Secondary outcomes included (1) specific prevalence of individual organ dysfunctions; (2) BMI levels and BMI category distribution (<40, 40-49, ≥50); (3) baseline disease severity and estimated long-term risk assessed using the American Society of Anesthesiologists (ASA) classification,11,12 Charlson Comorbidity Index (CCI),13 and Framingham risk score14; (4) perioperative safety assessed by 30-day major postoperative complications defined as Clavien-Dindo grade 3 or higher15; and (5) postoperative weight loss outcomes at 12 and 24 months after surgery. Availability of some secondary outcome variables differed across participating datasets. The CCI data were unavailable for the French cohort, Framingham risk score data were unavailable for the UK cohort, and perioperative complication data were unavailable for the Brazilian cohort.
Data Sources, Measurement, and Adjudication Procedures
The included datasets reflected heterogeneous, but established prospective registries, clinical audit databases, and observational cohorts across centers. Given the recent introduction of the Lancet Commission framework, retrospective diagnosis of clinical obesity required harmonized expert adjudication across datasets not originally designed for this purpose. Agreement on diagnostic criteria and adjudication principles was reached jointly by the study collaborators before analysis.
Because this study was retrospective, prospective adjudication of obesity-related organ dysfunction was not feasible. To ensure consistent operationalization of the commission framework and adjudication procedures across centers, adjudication principles were collaboratively developed and agreed upon by investigators before analysis. We applied the commission framework using a pragmatic approach based on available clinical diagnoses, laboratory measures, documented functional limitations, imaging findings, specialist follow-up, medication use, and routinely collected obesity-related variables across datasets. Eighteen adiposity-related organ dysfunction domains were retrospectively classified within each cohort using predefined criteria jointly agreed upon by the study collaborators. Pragmatic adjudication decisions for kidney dysfunction, heart failure, musculoskeletal dysfunction, daily living limitations, liver dysfunction, metabolic dysfunction, upper airway dysfunction, and other criteria were applied to allow consistent and reproducible retrospective application of the framework across heterogeneous surgical datasets.
Kidney Dysfunction and Heart Failure
Laboratory measures for kidney dysfunction were used when available, but where inconsistent, clinical diagnoses (eg, chronic kidney disease, kidney impairment) were used. For heart failure, due to incomplete echocardiography, heart failure with preserved ejection fraction and heart failure with reduced ejection fraction (both criteria for clinical obesity) were grouped within a broader cardiopathy category (eg, heart failure diagnosis, chronic fatigue, edema, or digitalis therapy).
Musculoskeletal Dysfunction and Limitations of Daily Living
Conditions reported as osteoarthritis, knee replacement, hip replacement, or severe joint pain were considered as meeting criteria for musculoskeletal dysfunction. Reported conditions of mobility limitation, impaired activities of daily living, and partial or complete dependence on walking aids or other assistive devices were grouped and adjudicated as evidence of a single functional impairment category.
Liver Dysfunction
The commission criterion for clinical obesity requires steatohepatitis with fibrosis (metabolic dysfunction–associated steatohepatitis [MASH]), not simply steatosis. We used a pragmatic approach to reflect such a level of liver dysfunction. In the French cohort, diagnosis was based on histology, and presence of fibrosis was confirmed on actual pathology. In other centers, in which biopsy or liver elastography were unavailable, this criterion was adjudicated based on a documented diagnosis of MASH where available, persistent abnormal liver enzymes, or specialist follow-up or imaging suggestive of steatohepatitis. Simple reporting of metabolic dysfunction–associated steatotic liver disease in the absence of any of the aforementioned was not considered as meeting the liver dysfunction criterion for clinical obesity.
Metabolic Dysfunction
The presence of a metabolic cluster was defined primarily via laboratory parameters, but retrospective data may be normalized by treatment. For this reason, we adjudicated this criterion using clinical diagnosis (documented diagnosis of diabetes or prediabetes plus dyslipidemia in history or treatment records) and laboratory evidence (fasting glucose ≥5.6 mmol/L [100.9 mg/dL] or hemoglobin A1c ≥5.8% [40 mmol/mol], triglycerides ≥2.3 mmol/L [203.5 mg/dL], high-density lipoprotein <1.0 mmol/L [38.6 mg/dL] [men] or <1.3 mmol/L [50.2 mg/dL] [women]).
Upper Airway Dysfunction and Other Criteria
According to the commission’s definition, the upper airway dysfunction criterion requires apnea or hypopnea during sleep due to increased upper airway resistance. This criterion was pragmatically adjudicated when there was documented presence of sleep apnea requiring continuous positive airway pressure. The remaining criteria were adjudicated when supported by documentation of a specific clinical diagnosis (eg, intracranial hypertension, infertility, hypertension).
Risk Assessment and Perioperative Safety
Operative risk was assessed using the ASA classification.11 Baseline long-term mortality risk was estimated using the CCI.13 Ten-year hard coronary heart disease risk was estimated using the Adult Treatment Panel III of the Framingham risk score.14 Major postoperative complications within 30 days were defined as Clavien-Dindo grade 3 or higher.15
Bias and Missing Data
Several steps were undertaken to reduce misclassification bias. Classification relied only on formally documented baseline assessments performed as part of routine bariatric surgery evaluation. Cases with missing key variables required for classification were excluded. Harmonized adjudication procedures and cross-center review of discrepant prevalence estimates were used to minimize variability in interpretation across datasets. When substantial between-center differences in the prevalence of individual criteria were observed, investigators reevaluated adjudication procedures to confirm consistent application of the criteria and ensure that observed differences reflected true clinical variation rather than differences in interpretation. Data consistency was rated as no concern, minor concern, or substantial concern based on clarity and uniformity of available information across centers (eTable in Supplement 1).
Statistical Analysis
We performed a descriptive and comparative analysis. Continuous variables are reported as mean (SD) or median (IQR) and categorical variables as counts with percentages. Comparative analyses were performed only within each individual cohort, comparing patients with clinical obesity with those with preclinical obesity. No direct statistical comparisons were performed between centers because patient-level data were not shared across cohorts. Depending on data distribution, within-cohort comparisons used t tests or Mann-Whitney U tests for continuous variables and χ2 or Fisher exact tests for categorical variables. A 2-sided P < .05 was considered significant. Analyses were performed using SPSS, version 31 (IBM Corp).
Results
Study Population
A total of 2316 patients were included across the 4 centers (clinical obesity cohort: 1709 patients [73.8%]; mean [SD] age range, 45.6 [11.0] to 48.9 [11.7] years; 1149 female [67.2%] and 560 male [32.8%]; preclinical obesity cohort: 607 patients [26.2%]; mean [SD] age range, 34.7 [10.4] to 40.0 [9.8] years; 486 female [80.1%] and 121 male [19.9%]). Baseline demographic and clinical characteristics were broadly comparable, although disease burden and organ dysfunction profiles varied across sites (Table 1; Table 2).
Table 1. Comparison of Baseline Characteristics Between Clinical Obesity and Preclinical Obesity Across 4 International Cohorts.
| Clinical characteristic | UK cohort | Spanish cohort | French cohort | Brazilian cohort | Across cohortsa | |||||
|---|---|---|---|---|---|---|---|---|---|---|
| Clinical obesity (n = 497) | Preclinical obesity (n = 130) | Clinical obesity (n = 301) | Preclinical obesity (n = 114) | Clinical obesity (n = 605) | Preclinical obesity (n = 181) | Clinical obesity (n = 306) | Preclinical obesity (n = 182) | Clinical obesity (n = 1709) | Preclinical obesity (n = 607) | |
| Age, mean (SD), y | 48.9 (11.7) | 39.5 (9.7)b | 47.1 (9.3) | 40.0 (9.8)b | 45.6 (11.0) | 34.7 (10.4)b | 48.3 (11.7) | 40.0 (9.4)b | 45.6-48.9 | 34.7-40.0 |
| Sex, No. (%) | ||||||||||
| Female | 350 (70.4) | 101 (77.7) | 220 (73.0) | 99 (87.0)b | 391 (64.6) | 143 (79.0)b | 188 (61.0) | 143 (78.0)b | 1149 (67.2) | 486 (80.1) |
| Male | 147 (29.6) | 29 (22.3) | 81 (27.0) | 15 (13.0) | 214 (35.4) | 38 (21.0) | 118 (39.0) | 39 (22.0) | 560 (32.8) | 121 (19.9) |
| BMI, mean (SD) | 47.5 (7.5) | 48.5 (9.0) | 44.3 (5.4) | 44.0 (5.7) | 46.5 (7.6) | 46.2 (7.3) | 41.2 (6.3) | 40.2 (4.9) | 41.2-47.5 | 40.2-48.5 |
| ASA score, median (IQR) | 3 (2-3) | 2 (2-3)b | 3 (3-3) | 2 (2-3)b | 2 (2-3) | 2 (1-2)b | 2 (2-2) | 2 (2-2)b | 2-3 | 2-2 |
| Weight loss, mean (SD), % | ||||||||||
| At 12 mo | 27.1 (8.4) | 28.3 (8.1) | 34.0 (7.9) | 36.1 (7.6)b | 28.5 (9.2) | 32.2 (10.1)b | 31.0 (8.6) | 33.5 (8.0)b | 27.1-34.0 | 28.3-36.1 |
| At 24 mo | 27.6 (10.0) | 29.1 (11.5) | 34.6 (8.1) | 35.6 (8.4) | 29.6 (11.0) | 33.6 (13.0)b | 30.3 (9.1) | 32.9 (10.1)b | 27.6-34.6 | 29.1-35.6 |
Abbreviations: ASA, American Society of Anesthesiologists; BMI, body mass index (calculated as weight in kilograms divided by height in meters squared).
Individual patient data were not shared among centers; therefore, pooled patient-level estimates were not calculated.
Significant at P < .05 for comparisons between clinical obesity and preclinical obesity groups within the cohort.
Table 2. Prevalence of Obesity-Related Organ Dysfunction Among Patients With Clinical Obesity Across Cohorts.
| Organ dysfunction | Patients, No. (%) | ||||
|---|---|---|---|---|---|
| UK cohort (n = 497) | Spanish cohort (n = 301) | French cohort (n = 605) | Brazilian cohort (n = 306) | Across cohorts (n = 1709) | |
| Hypertension | 304 (63.2) | 160 (53.0) | 332 (54.9) | 188 (61.4) | 984 (57.6) |
| Metabolic dysfunction | 231 (48.0) | 138 (45.9) | 325 (53.7) | 59 (19.3) | 753 (44.1) |
| Functional and musculoskeletal limitation | 177 (36.8) | 47 (15.6) | 61 (10.1) | 58 (19.0) | 343 (20.1) |
| Sleep apnea requiring CPAP | 126 (26.2) | 154 (51.2) | 371 (61.3) | 35 (11.4) | 686 (40.1) |
| HFPEF or HFREF | 61 (12.7) | 9 (3.0) | 49 (8.1) | 6 (2.0) | 125 (7.3) |
| MASH | 30 (6.2) | 19 (6.3) | 71 (11.7) | 52 (17.0) | 172 (10.1) |
| Kidney dysfunction (eGFR <60 mL/min/1.73 m2) | 76 (15.8) | 4 (1.3) | 45 (7.4) | 0 (0) | 125 (7.3) |
| Reproductive dysfunction | 40 (8.3) | 5 (1.7) | 63 (10.4) | 25 (5.1) | 133 (7.8) |
| Respiratory dysfunction | 18 (3.7) | 9 (3.0) | 35 (5.8) | 0 (0) | 62 (3.6) |
| DVT or PE | 32 (6.7) | 4 (1.3) | 33 (5.5) | 9 (2.9) | 78 (4.6) |
| Intracranial hypertension | 2 (0.4) | 1 (0.3) | 2 (0.3) | 4 (1.3) | 9 (0.5) |
| Lymphedema | 16 (3.3) | 1 (0.3) | 1 (0.2) | 3 (1.0) | 21 (1.2) |
| Urinary incontinence | 0 (0) | 9 (3.0) | 13 (2.1) | 0 (0) | 22 (1.3) |
| Atrial fibrillation | 16 (3.3) | 6 (2.0) | 3 (0.5) | 1 (0.3) | 26 (1.5) |
| PAH | 1 (0.2) | 0 (0) | 17 (2.8) | 1 (0.3) | 19 (1.1) |
Abbreviations: CPAP, continuous positive airway pressure; DVT, deep venous thrombosis; eGFR, estimated glomerular filtration rate; HFPEF, heart failure with preserved ejection fraction; HFREF, heart failure with reduced ejection fraction; MASH, metabolic dysfunction–associated steatohepatitis; PAH, pulmonary arterial hypertension; PE, pulmonary embolism.
Prevalence of Clinical and Preclinical Obesity
Clinical obesity was the predominant category in all centers, with prevalence ranging from 62.7% in the Brazilian cohort to 79.3% in the UK cohort (Figure 1). Preclinical obesity accounted for the remaining surgical candidates across sites.
Figure 1. Bar Graph of Prevalence of Clinical and Preclinical Obesity Among Metabolic Bariatric Surgery Candidates Across International Metabolic Bariatric Surgery Centers.
Proportion of patients meeting criteria for clinical obesity (presence of adiposity-related organ dysfunction) and preclinical obesity (excess adiposity with preserved function) classified according to Lancet Diabetes and Endocrinology Commission criteria. Across cohorts, 1709 of 2316 patients (73.8%) met criteria for clinical obesity and 607 of 2316 patients (26.2%) met criteria for preclinical obesity.
Baseline Characteristics and Anesthetic Risk
Across all centers, patients with clinical obesity were consistently older than those with preclinical obesity (UK cohort: mean [SD], 48.9 [11.7] vs 39.5 [9.7] years; French cohort: mean [SD], 45.6 [11.0] vs 34.7 [10.4] years; Spanish cohort: mean [SD], 47.1 [9.3] vs 40.0 [9.8] years; Brazilian cohort: mean [SD], 48.3 [11.7] vs 40.0 [9.4]) (P < .001 for all comparisons). Although women represented the majority of patients in both groups across cohorts, the proportion of women was higher among patients with preclinical obesity, reaching 87.0% (99 patients) vs 73.0% (220 patients) (P = .003) in the Spanish cohort; however, this difference was not statistically significant in the UK cohort. Patients with clinical obesity had higher ASA scores than those with preclinical obesity across all cohorts (UK cohort: median [IQR], 3 [2-3] vs 2 [2-3]; P < .001; French cohort: median [IQR], 3 [3-3] vs 2 [2-3]; P < .001; Spanish cohort: median [IQR], 2 [2-3] vs 2 [1-2]; P < .001; Brazilian cohort: median [IQR], 2 [2-2] vs 2 [2-2]; P = .02) (Table 1), consistent with greater systemic disease burden and operative risk. Mean (SD) BMI levels varied across sites, ranging from 40.2 (4.9) (preclinical obesity in the Brazilian cohort) to 48.5 (9.0) (preclinical obesity in the UK cohort). Notably, however, within each center, BMI levels were similar between clinical and preclinical obesity, with no statistically significant differences. The BMI category distributions (<40, 40-49, ≥50) were also comparable between clinical and preclinical obesity (Figure 2), reinforcing that BMI alone may not discriminate for the presence of ongoing, obesity-induced disease among surgical candidates.
Figure 2. Bar Graphs of the Distribution of Body Mass Index (BMI) Categories Among Patients With Clinical and Preclinical Obesity Across International Metabolic Bariatric Centers.
Proportion of patients within each BMI (calculated as weight in kilograms divided by height in meters squared) category.
Organ Dysfunction Patterns
Across centers, the most prevalent obesity-related dysfunctions were hypertension (from 260 patients [53.0%] in the Spanish cohort to 304 patients [63.2%] in the UK cohort), metabolic dysfunction (from 59 patients [19%] in the Brazilian cohort to 325 patients [53.7%] in the French cohort), functional and musculoskeletal limitation (from 61 patients [10.1%] in the French cohort to 177 patients [36.8%] in the UK cohort), and sleep apnea requiring continuous positive airway pressure (from 35 patients [11.4%] in the Brazilian cohort to 371 patients [61.3%] in the French cohort). Substantial intercenter variability was observed (Table 2), which may reflect differences in practice setting (ie, academic vs private), underlying disease prevalence, referral patterns, and the extent of systematic vs clinically driven assessment of obesity-associated diseases among surgical candidates.
Baseline Mortality and Cardiovascular Risk Stratification
Data for full measurement of CCI were available for the UK, Spanish, and Brazilian cohorts. In all 3 centers, patients with clinical obesity had higher CCI scores than those with preclinical obesity (UK cohort: median [IQR], 1 [0-2] vs 0 [0-0]; Spanish cohort: median [IQR], 1 [0-1] vs 0; Brazilian cohort: median [IQR], 1 [1-3] vs 1 [0-1]) (all P < .001). Data for calculation of Framingham risk scores were available for the Spanish, French, and Brazilian cohorts. These scores were also higher among patients with clinical obesity compared with preclinical obesity (Spanish cohort: median [IQR], 1.31 [0.20-4.34] vs 0.20 [0.20-1.68]; Brazilian cohort: median [IQR], 1.57 [0.20-5.28] vs 0.20 [0.20-0.20]; French cohort: median [IQR], 8.00 [3.00-13.00] vs 2.00 [1.00-4.00]) (all P < .001) (Figure 3).
Figure 3. Bar Graphs of Baseline Risk Stratification and Perioperative Baseline Disease Severity and Perioperative Safety Outcomes by Clinical or Preclinical Obesity.
Bars represent mean values, and error bars indicate standard deviations. A Clavien-Dindo grade of 3 or higher indicates severe complications. CCI indicates Charlson Comorbidity Index.
Perioperative Safety
Major 30-day postoperative complication data (Clavien-Dindo grade ≥3) were unavailable for the Brazilian cohort. In the French cohort, patients with clinical obesity had a higher rate of major postoperative complications compared with those with preclinical obesity (4.0% vs 1.1%, P = .04). In the UK and Spanish cohorts, differences in major complication rates were modest but not statistically significant (UK cohort: 1.8% vs 1.5%; P = .83; Spanish cohort: 3.0% vs 2.6%; P = .85).
Weight Loss Outcomes
Patients with clinical obesity had lower postoperative weight loss at 12 and 24 months compared with those with preclinical obesity. Differences were statistically significant in the Spanish cohort at 12 months (mean [SD], 34.0% [7.9%] vs 36.1% [7.6%]; P = .02), the French cohort at 12 months (mean [SD], 28.5% [9.2%] vs 32.2% [10.1%]; P < .001) and 24 months (mean [SD], 29.6% [11.0%] vs 33.6% [13.0%]; P < .001), and the Brazilian cohort at 12 months (mean [SD], 31.0% [8.6%] vs 33.5% [8.0%]; P = .002) and 24 months (30.3% [9.1%] vs 32.9 [10.1%]; P = .009) (Table 1).
The eAppendix in Supplement 1 summarizes the implications for surgeons based on our findings. These implications are discussed in detail in the next section.
Discussion
This international, multicenter, cross-sectional study investigated the implications of applying the recent Lancet Diabetes and Endocrinology Commission diagnostic framework to MBS cohorts. The key finding was that clinical obesity accounts for most surgical candidates, suggesting that current MBS practice predominantly treats established obesity-related disease rather than serving solely as an intervention aimed at risk reduction. At the same time, a substantial preclinical obesity subgroup highlighted that a significant number of patients undergo surgery without demonstrable obesity-related organ dysfunction at baseline. This finding does not imply inappropriateness of surgery in preclinical obesity but underscores the importance of aligning surgical goals, timing, and proportionality with clinical phenotype.
Our findings validate the distinction between clinical and preclinical obesity even within a selected population with high BMI levels, such as candidates for MBS. A meaningful proportion of patients in all cohorts of this study met criteria for preclinical obesity despite BMI levels typically associated with surgical eligibility. This finding underscores the new framework’s capacity to meaningfully inform clinical prioritization and practice, even in higher-risk surgical populations.
Our data show that BMI may not discriminate between clinical and preclinical obesity in surgical cohorts with similar BMI distributions across phenotypes, reinforcing the commission’s premise that BMI thresholds do not reliably capture disease status,9 even at very high BMI levels, and challenges their continued use as the primary criterion for assessment of surgical eligibility and prioritization.5,6 In surgical practice, in which operative risk and benefit must be carefully balanced, the commission’s framework offers a more clinically meaningful and appropriate basis for guiding MBS than current BMI-based approaches.
Patients with clinical obesity exhibited greater systemic disease burden, as reflected by higher ASA classifications, CCI scores, and Framingham risk scores, and markedly increased long-term risks of cardiovascular events and all-cause mortality. The introduction of the concepts of clinical obesity and preclinical obesity, along with corresponding management strategies, may enable earlier intervention, improve surveillance, and reduce the risk of future complications. Importantly, this approach reinforces the recognition of obesity as a chronic disease rather than merely a condition defined by excess body weight.
Differences in major postoperative complications were modest but directionally consistent with higher baseline disease severity. The commission framework, therefore, represents a better system for risk stratification of surgical candidates by providing a disease-centered rationale for clinical urgency, operative planning, and perioperative surveillance. To our knowledge, our study is the first to evaluate acute postoperative complications according to the newly proposed obesity classification. Additional studies are needed to determine whether obesity stage should be incorporated into future benchmarking strategies.
In resource-constrained systems, the distinction between clinical and preclinical obesity may allow medically meaningful prioritization of patients with demonstrable adiposity-related dysfunction. For instance, patients with clinical obesity undergoing surgery as disease treatment may warrant proportional prioritization, potentially including differentiated waiting lists akin to surgical treatment of benign colonic conditions vs colon cancer.
Distinguishing clinical from preclinical obesity may provide a practical basis for defining the role of surgery in obesity care. In preclinical obesity, MBS may serve as a preventive strategy for selected higher-risk individuals, whereas in clinical obesity, it represents treatment of established disease. This distinction may become increasingly important as pharmacologic therapies expand,16,17 supporting surgery as a second-line option for stepwise risk reduction in preclinical obesity but a first-line or early intervention for many patients with clinical obesity.
These distinctions also may influence how MBS is perceived by patients, clinicians, and policymakers. Reliance on BMI thresholds and the traditional framing of MBS as weight loss surgery have reinforced its indication as a preventive intervention rather than treatment for active disease, potentially contributing to persistent underuse despite strong evidence of efficacy, safety, and cost-effectiveness. A clinically grounded framework positions MBS as disease-directed therapy, aligns access with objective clinical need rather than BMI proxies, and may support more equitable resource allocation and appropriate surgical prioritization.
The framework also has implications for outcome assessment and value-based care. In clinical obesity, outcomes should extend beyond weight loss to include organ function, morbidity, and prevention of adverse events. In preclinical obesity, success should be defined by prevention or delay of disease progression. Routine assessment of obesity-related organ dysfunction and outcome stratification by disease stage are therefore important for interpreting effectiveness across centers and procedures.
Economic value may also differ by disease status. Clinical obesity may yield earlier return on investment through reduced morbidity, medication use, and hospitalizations, whereas surgery in preclinical obesity should be evaluated as a preventive intervention with longer time horizons and potentially different cost-effectiveness thresholds. Future health economic analyses should therefore distinguish clinical from preclinical obesity. Recent population studies applying the same framework reported clinical obesity in 57.5% to 79.4% of people with obesity,18,19 but these estimates may overstate prevalence because they do not account for background disease rates in populations without obesity. The true prevalence of clinical obesity in nonsurgical populations is therefore plausibly lower than observed in our surgical cohorts.
Limitations
This study had several limitations. First, the UK and Brazilian datasets were derived from clinical audit databases rather than complete institutional registries. Consequently, total institutional surgical volumes were not available to the study team, and the full extent of potential selection bias could not be quantified. Second, as a retrospective audit of routine practice using databases established prior to the publication of the commission’s report, ascertainment of organ dysfunction relied on International Classification of Diseases coding and clinical documentation, introducing potential intercenter variability. Some dysfunctions required pragmatic grouping, and liver disease assessment varied by histologic availability. Importantly, obstructive sleep apnea treated with continuous positive airway pressure was used as a proxy for clinically significant obesity-related hypoventilation due to upper airway obstruction, which is one of the criteria for diagnosis of clinical obesity. This definition was meant to avoid overclassification, recognizing that mild obstructive sleep apnea is common among surgical candidates but not invariably associated with hypoventilation or major risk.20 Similarly, liver fibrosis in MASH is a commission criterion for clinical obesity, but fibrosis has not been routinely assessed in historical surgical cohorts. The audit design also precluded definitive causal attribution of organ dysfunction to obesity, which is a prerequisite for the diagnosis of clinical obesity (ie, just as not all joint inflammation reflects rheumatoid arthritis, so too not all joint problems are associated with clinical obesity), raising the possibility of overattribution and, therefore, potential overestimation of clinical obesity. Finally, additional anthropometric measures recommended by the commission9 for confirmation of excess adiposity in individuals with BMI less than 40 were unavailable, although this requirement applies to a minority of surgical candidates. As an audit of routinely recorded data, we could not investigate clinical outcomes beyond just weight loss. Prospective studies incorporating standardized clinical assessments and commission-recommended measures are needed to refine exact prevalence estimates of clinical and preclinical obesity and to evaluate long-term surgical outcomes across disease stages.
Conclusions
This cross-sectional study of 2316 MBS candidates across 4 international centers found that clinical obesity was the predominant category, while a meaningful minority of patients had preclinical obesity despite similar BMI distributions, suggesting that disease status could not be inferred from BMI alone. Patients with clinical obesity had greater comorbidity burden and higher estimated long-term cardiovascular and mortality risk. These findings support implementation of the new definitions of clinical and preclinical obesity in surgical practice to improve patient selection, prioritization, and alignment of treatment goals with clinical need. Metabolic bariatric surgical services should systematically assess obesity-related organ dysfunction; report the prevalence of clinical and preclinical obesity; and interpret safety, efficacy, and cost-effectiveness within the appropriate clinical context, distinguishing when surgery is used for treatment of established disease vs risk reduction.
eFigure. Cohort Selection and Baseline Characteristics of Included Participants Across the 4 International Metabolic Bariatric Surgery Cohorts
eTable. Operationalization of Lancet Commission Criteria for Retrospective Diagnosis of Clinical Obesity
eAppendix. Implications for Surgeons
Data Sharing Statement
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
eFigure. Cohort Selection and Baseline Characteristics of Included Participants Across the 4 International Metabolic Bariatric Surgery Cohorts
eTable. Operationalization of Lancet Commission Criteria for Retrospective Diagnosis of Clinical Obesity
eAppendix. Implications for Surgeons
Data Sharing Statement
