Abstract P125: Eating Behaviour Profiles of Severely Obese People Differ in Regard to Gender and Hypertension Status
Bibliographic record
Abstract
INTRODUCTION: The prevalence of severe obesity has tripled in Canada in the past few decades. Nevertheless, cognitions and eating behaviours in this population have not been extensively studied as for their relationships with anthropometric characteristics and comorbidities. Therefore, the aim of this study was to link 3 factors related to cognitions and eating behaviours: restraint, disinhibition and susceptibility to hunger, according to gender, body composition and hypertension (HTA) status. HYPOTHESIS: Cognitive and behavioural profiles of severely obese people differ in regard to gender and HTA status. METHODS: A total of 125 severely obese people [Body Mass Index (BMI) of ≥ 40 or ≥ 35 kg/m 2 with comorbidities] were recruited through the bariatric surgery clinic of our institution. They were invited to complete a validated French version of the Three-Factor Eating Questionnaire (51-items). Weight, fat-free mass, and body fat mass of participants were measured using a bioelectric impedance balance and HTA status was recorded. RESULTS: Participants were 41 ± 10 years, weighted 133.9 ± 27.4 kg with a BMI of 48.7 ± 7.6 kg/m 2 , a lean mass of 66.0 ± 14.1 kg, a fat mass of 32.6 ± 17.9 kg and a fat percentage of 50.3 ± 5.7%. Age and BMI were similar between men and women, but men’s weight, body fat, and fat-free mass were higher than in women. In the entire cohort, a negative correlation was observed between susceptibility to hunger and fat mass (r=-0.273; p=0.035). In men, positive correlations were observed between restraint vs. weight (r=0.394; p=0.016) and BMI (r=0.459; p=0.004). In women, negative correlations were observed between restraint vs. weight (r=-0.215; p=0.044) and lean mass (r=-0.278; p=0.009), while positive correlations were observed between disinhibition vs. weight (r=0.211; p=0.049) and fat mass (r=0.215; p=0.044). Overall, 56% (70/125) of all participants showed HTA. A greater proportion of participants with a higher restraint score suffered from HTA than in participants presenting a lower restraint score (67 vs. 48%; p=0.027). Restraint profile also differed between women suffering with HTA vs. without HTA (p=0.008). A greater proportion of participants showing a lower disinhibition score suffered from HTA than those with a higher disinhibition score (64 vs. 48%; p=0.051). CONCLUSION: Higher score of susceptibility to hunger observed in severely obese individuals is linked to a lower body fat mass. Despite similar eating behaviour profiles, different associations coexist according to gender between restraint vs. disinhibition factors and anthropometric characteristics. Among women, those suffering with HTA present a higher level of restraint, but lower disinhibition score. These findings in severely obese people differ from actual literature in overweight and obese people.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".