699-P: Gender Differences in Psychosocial Outcomes according to BMI and Waist Circumference among Adults Living with Type 1 Diabetes—A Cross-Sectional BETTER Analysis
Bibliographic record
Abstract
Introduction & Objective: Although the association between psychosocial outcomes and a higher BMI is well known in the general population, there are few studies among people living with type 1 diabetes (PwT1D). The aim of this study is to investigate the associations between psychosocial outcomes and BMI groups or waist circumference (WC), for men and women. Methods: A cross-sectional analysis of the BETTER registry based on patient-reported outcomes of adult PwT1D (BMI n=1028; WC n=435) stratified by gender and classified into three BMI groups: <25 (Group A); 25-29 (Group B); ≥30 (Group C) kg/m2 and WC groups: <88/<102 and ≥88/≥102cm (women/men respectively). Student’s T-tests, one-way ANOVAs, and χ2 logistic regression searched for associations between BMI or WC groups and psychosocial outcomes: depression, diabetes distress (DD), and diabetes-related stigmatization. Results: Of the 1028 PwT1D, 66% were women and the average BMI, WC, age, T1D duration were: 26 kg/m2, 92 cm, 45 years, and 24 years, respectively. For BMI classes, 460 adults (45%) were in group A, 356 (35%) group B, and 212 (21%) group C. Women in group C, compared to group A, had more symptoms of depression (p<0.001), more prescriptions for depression (p<0.001), and reported higher DD (p<0.001). Women in group B and C reported feeling more stigmatized due to their diabetes (p<0.001) than those in group A. There were no differences between BMI classes in men, and they reported fewer symptoms of depression and lower DD and diabetes stigmatization than women. In women, 148 (52%) had a WC <88 and 135 (48%) ≥88 cm, while 104 men (68%) had a WC <102 and 48 (32%) ≥102 cm. There were no differences between WC groups in women. Compared to the WC<102 group, men with a WC≥102 cm had more symptoms of depression and more prescriptions for depression (p<0.016). Conclusion: In adult PwT1D, less favorable psychosocial outcomes are associated with a BMI ≥30 kg/m2 in women and WC ≥102 cm in men. Disclosure A. Bonhoure: Consultant; Dexcom, Inc. M. Lalanne-Mistrih: Other Relationship; Novo Nordisk, SANOFI AVENTIS FRANCE, ViiV Health Care, SOS Oxygene Antilles, MEDICALIA, SEPRODOM Antilles, DINNO SANTE. M.K. Talbo: None. V. Boudreau: None. V. Messier: None. A. Bandini: None. L. Secours: None. M. Payette: None. S. Fontaine: None. A. Brazeau: Other Relationship; Dexcom, Inc. Research Support; Canadian Institutes of Health Research, Juvenile Diabetes Research Foundation (JDRF), Diabète québec, Fonds de recherche du Québec en Santé. R.P.R. Rabasa-Lhoret: Other Relationship; Abbott, AstraZeneca, Bayer Inc., Boehringer-Ingelheim, Dexcom, Inc. Research Support; Diabetes Canada. Other Relationship; Eli Lilly and Company. Research Support; Cystic Fibrosis Canada, Canadian Institutes of Health Research, FFRD - Fondation Francophone pour la Recherche du Diabète. Other Relationship; Janssen Pharmaceuticals, Inc. Research Support; Juvenile Diabetes Research Foundation (JDRF). Other Relationship; Novo Nordisk, GlaxoSmithKline plc. Consultant; HLS Therapeutics Inc., Insulet Corporation. Speaker's Bureau; CPD Networks. Other Relationship; Medtronic. Consultant; Pfizer Inc. Speaker's Bureau; Tandem Diabetes Care, Inc. Other Relationship; Sanofi. Speaker's Bureau; Vertex Pharmaceuticals Incorporated. Research Support; SFD - Société Francophone du Diabète.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".