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Updated: Aug 25, 2026
Assessment of Child Anthropometry in a Large Epidemiologic Study
Published on: February 2, 2017
Estimating obesity phenotype features in a real-world cohort - a non-interventional pilot study using an original
Jakub Gołacki1,2, Paulina Gryń3, Martyn Kępka3
1Department of Endocrinology, Diabetology and Metabolic Diseases, Chair of Internal Medicine, Medical University of Lublin, Lublin, Poland. jakub.golacki@umlub.edu.pl.
Introduction:
Obesity is a heterogeneous chronic disease, and phenotyping may support personalized management; however, referencephenotyping tools are difficult to implement in routine care.
Material And Methods:
We conducted a retrospective real-world evidence analysis of 314 adults [206 women; mean age 48 years; mean body mass index (BMI) 38.30 ± 5.79 kg/m2] evaluated between November 2024 and May 2025 in a tertiary obesity care program. An originalquestionnaire was used to subjectively estimate phenotype features consistent with four obesity phenotypes (hungry gut, hungry brain,emotional eating, and slow burn) or their combinations. HbA1c and body composition were assessed by bioimpedance. The study wasnon-interventional and phenotype estimation did not guide pharmacotherapy selection.
Results:
In the whole cohort, no phenotype was identified in 158/314 patients (50.3%). As any-occurrence frequencies in the whole cohort, the most frequent estimated phenotype feature was slow burn (75/314, 23.9%), followed by emotional eating (66/314, 21.0%), hungry brain (52/314, 16.6%), and hungry gut (42/314, 13.4%). Because overlaps were allowed, phenotype frequencies represent any occurrenceand do not sum to 100%. The slow burn phenotype was associated with lower skeletal muscle mass (mean difference ~4.5 kg vs. otherphenotypes). Hungry gut occurred more frequently in individuals with HbA1c ≥ 6.5%, whereas hungry brain was least frequent in thatgroup; in patients with obesity and type 2 diabetes, higher HbA1c was associated with a greater number of estimated phenotype features.
Conclusions:
Questionnaire-based estimation of obesity phenotype features was feasible in routine care, but the high proportion ofundetermined cases indicates insufficient sensitivity for clinical use at the current stage. Therefore, LOPEQ should be regarded as an exploratory, hypothesis-generating tool requiring formal validation against objective reference methods before any treatment-guiding application.
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