Sex Differences in Glycemia and Self-management Strategies for Exercise in an Active Adult Cohort With Type 1 Diabetes
Bibliographic record
Abstract
OBJECTIVE: To examine potential differences in glucose levels during and after exercise between sexes in adults with type 1 diabetes. METHODS: The Type 1 Diabetes Exercise Initiative study was a prospective, 4-week free-living observational study in adults with type 1 diabetes. Ninety-one females were matched on age and insulin modality to 91 males. Participants completed exercise study videos and personal exercise sessions. Study-collected food, insulin, exercise, and glucose data surrounding exercise and on sedentary days were compared between sexes to examine how they impact glucose levels during and after exercise. RESULTS: Female participants had higher glucose levels than male participants when starting study exercise (8.5 ± 2.8 vs 8.0 ± 2.8 mmol/L, P = .01) and when starting personal exercise activities (8.4 ± 2.9 vs 7.8 ± 2.7 mmol/L; P = .05). Glucose declines during study exercise were comparable between female and male participants (adjusted mean: -0.8 vs -1.0 mmol/L, respectively; P = .11), but smaller in female participants during personal exercise (adjusted mean: -0.9 vs -1.4 mmol/L; P < .001). Twenty-four-hour mean glucose levels were also higher in female participants on sedentary days (P = .04). Daily macronutrient consumption was similar between sexes after adjusting for weight, as were food, exercise, and insulin habits surrounding exercise. CONCLUSION: Female participants had higher preexercise glucose levels compared to male participants and smaller glucose declines during personal exercise, but there were no observable differences in food, exercise, and insulin habits.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".