Sex differences and associations between zinc deficiency and anemia among hospitalized adolescents and young adults with eating disorders
Bibliographic record
Abstract
PURPOSE: To determine sex differences in and associations between zinc deficiency and anemia among adolescents and young adults hospitalized for medical complications of eating disorders. METHODS: We retrospectively reviewed electronic medical records of 601 patients aged 9-25 years admitted to the University of California, San Francisco Eating Disorders Program for medical instability, between May 2012 and August 2020. Descriptive statistics, crude, and adjusted logistic regression models were used to assess the association between zinc deficiency (< 55 mcg/dL) and anemia (< 13.6 g/dL in males [M] and < 11.8 g/dL in females [F]). RESULTS: A total of 87 males and 450 females met eligibility criteria (age 15.98 ± 2.81, 59.4% anorexia nervosa; admission body mass index 17.49 ± 2.82). In unadjusted comparisons, plasma zinc in males and females were not statistically different (M 64.88 ± 14.89 mcg/dL vs F 63.81 ± 13.96 mcg/dL, p = 0.517); moreover, there were no differences in the percentage of males and females with zinc deficiency (M 24.14% vs F 24.89%). However, a greater percentage of males than females were anemic (M 50.00% vs F 17.61%, p < 0.001), with similar findings in the subgroup with anorexia nervosa. In logistic regression models stratified by sex and eating disorder diagnosis, zinc deficiency was significantly associated with anemia in males (AOR 3.43, 95% CI 1.16, 10.13), but not females (AOR 1.47, 95% CI 0.86, 2.54). CONCLUSIONS: For the first time, we demonstrate that zinc deficiency is equally severe in males compared to females hospitalized with medical complications from eating disorders, with nearly a quarter of inpatients experiencing zinc deficiency. Anemia is more common in males than females hospitalized with eating disorders. LEVEL OF EVIDENCE: Level V: descriptive cross-sectional study.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".