Medical and physiological complications of exercise for individuals with an eating disorder: A narrative review
Bibliographic record
Abstract
Individuals with eating disorders (ED) experience prolonged malnutrition, binge episodes, and compensatory behaviours that affect every organ system. Psychological and physiological symptoms are worsened with comorbid dysfunctional exercise, seen in up to 80% of those with an ED. Although return to exercise is an important component of treatment and recovery, little is known about the contraindications and risks of exercise engagement specific to those with an ED. This paper provides a comprehensive narrative review of the medical and physiological complications of engaging in exercise during ED treatment and outlines when exercise may be contraindicated or used in modified or cautionary ways. We conducted a literature search on MEDLINE, PubMed, and PsychArticles to identify relevant articles, which yielded six categories of medical and physiological complications of ED that may be exacerbated by exercise: energy availability, cardiovascular health, electrolyte abnormalities, biomedical function markers, sex hormones, and body composition. We summarize the evidence for these complications for readers and offer an initial set of recommendations for incorporating exercise during ED treatment based on our findings. This review may serve as a resource for members of ED treatment teams to help evaluate more readily and confidently whether exercise is safe for individual patients and when modifications and caution may be warranted.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.002 | 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".