Exercise and Glycemic Management in Females and Women With Diabetes: The Role of Sex and Gender Across the Lifespan
Bibliographic record
Abstract
The benefits of exercise and physical activity (PA) for people living with diabetes are clear. However, current exercise recommendations do not take into consideration the potential impact of female-specific hormonal changes across the lifespan on the glycemic response to exercise. Moreover, the impact of life phases on barriers to participation in exercise and PA for women compared to men with diabetes is not well described. In this narrative review we have synthesized the literature to date regarding the interaction of female sex hormone variations (menarche and the menstrual cycle, pregnancy, and the menopausal transition) with glycemic management in the context of exercise for females with type 1 and type 2 diabetes. We also evaluated PA behaviours and barriers to participation in exercise and PA among individuals with diabetes identifying as women. We observed a lack of evidence regarding the impact of female-specific hormonal changes on the glycemic response to exercise among females with diabetes, with a particular paucity of studies during pregnancy and postpartum and for the menopausal transition. In this study we demonstrate that additional research is required to understand the influence of exercise on glucose management for females with diabetes across the lifespan, with the aim to provide safe and effective exercise recommendations and to encourage equitable participation in exercise and PA for females and women with diabetes throughout life.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".