Incidence of Iron Deficiency and Iron Deficient Anemia in Elite Runners and Triathletes
Bibliographic record
Abstract
OBJECTIVE: To assess the incidence of iron deficiency (ID), and iron deficient anemia (IDA) within a cohort of highly trained runners and triathletes, and to examine the association of oral iron supplementation history with serum ferritin (sFe) and hemoglobin (Hb) concentrations. METHODS: A retrospective analysis of routine blood test data taken from 2009 to 2015 from (n = 38) elite level runners and triathletes between the ages of 21 to 36 years. Oral iron supplement intake was assessed through a questionnaire. RESULTS: Triathletes (female, FT; male, MT) and runners (female, FR; male, MR) had higher incidence of at least 1 episode of ID (FT 60.0%, MT 37.5%, FR 55.6%, MR 31.3%) compared with values reported in the literature for endurance athletes (20%-50% females, 0%-17% males). Male triathletes and runners had a higher incidence of IDA than their female teammates (25% MT, 20% FT, 6.3% for MR, 0% FR), a finding which has previously not been reported. Hemoglobin concentrations were low, with incidence of Hb <140 g/L in men occurring at least once in 87.5% of triathletes, and 31.3% of runners, and Hb <120 g/L in women occurring at least once in 20% of triathletes, but 0% of runners. Although the athletes were appropriately treated with oral iron (mean 94 ± 115 mg/d), there was no observed correlation between iron intake and sFe or Hb. CONCLUSIONS: Even with monitoring and treatment in place, ID and IDA are significant concerns for the health and performance of elite runners and triathletes, and this issue affects males and females.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".