Gender differences in psychosocial outcomes according to BMI among adults living with type 1 diabetes: A cross-sectional BETTER analysis
Bibliographic record
Abstract
Aims The prevalence of overweight and obesity in people with type 1 diabetes has increased significantly, presenting additional psychosocial challenges that vary by gender. This study investigates the relationship between BMI and psychosocial outcomes in adult men and women with type 1 diabetes. Methods This cross-sectional analysis used data from people with type 1 diabetes in the BETTER registry, stratified by gender and categorized into BMI groups (<25, 25–29.9, ≥ 30 kg/m 2 ). Psychosocial outcomes included depression, diabetes distress, and stigmatization related to diabetes. One-way ANOVA assessed differences between BMI groups by gender. Multivariable logistic regression then analyzed gender differences within each BMI group, adjusting for age and HbA1c. Results Among 1028 participants (66 % women, mean BMI 26.4 ± 5.1 kg/m 2 , mean age 45.4 ± 15.0 years), 460 adults (45 %) had a BMI < 25, 356 (35 %) between 25–29.9, and 212 (21 %) ≥ 30 kg/m 2 . Women in the ≥ 30 kg/m 2 group, compared to the < 25 kg/m 2 group, had more symptoms of depression, more drug prescriptions for depression/anxiety, and higher diabetes distress (p < 0.001 for all). In men, psychosocial outcomes did not differ significantly across BMI groups. Multivariable regression showed women were more likely than men to report prescriptions for depression/anxiety and high diabetes distress, particularly in the higher BMI groups. Conclusions In adults living with type 1 diabetes, higher BMI is associated with adverse psychosocial outcomes, particularly in women. Gender-specific interventions addressing mental health, stigma, and weight management could be beneficial to improve overall well-being.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".