Prevalence of eating disorders in aquatic athletes: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Aquatic athletes may face unique pressures related to body aesthetics and weight management, potentially increasing their risk of eating disorders (EDs). This systematic review and meta-analysis aimed to estimate the prevalence of EDs in aquatic athletes and assess the quality of the available evidence. METHODS: A systematic search was conducted in PubMed, Embase, and Web of Science for studies published in English that reported on the prevalence of EDs among aquatic athletes. After screening and eligibility assessments, eight studies met the inclusion criteria, comprising a total of 715 athletes from various countries, including Poland, Canada, Brazil, Norway, the United States, and the United Kingdom. Quality assessment was performed using an adapted Newcastle-Ottawa Scale (NOS), and a random-effects meta-analysis was conducted to estimate pooled prevalence. Sensitivity analysis and a Doi plot were utilized to evaluate the publication bias. RESULTS: The meta-analysis estimated a pooled prevalence of EDs in aquatic athletes at 27.56% (95% CI: 14.27-46.50%), with a heterogeneity (I²) of 76%, indicating substantial variability in study designs and participant characteristics. Sensitivity analysis confirmed the robustness of the findings, and the Doi plot indicated significant asymmetry (LFK index = -3.44), suggesting potential publication bias or variability across studies. CONCLUSION: This study revealed a high prevalence of EDs among aquatic athletes. Further research is required on the factors associated with these disorders. Standardized assessment tools and routine screening in aquatic sports settings are recommended to promote early detection and prevention of EDs, ultimately enhancing athlete well-being and performance.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.009 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".