Prevalence of Iron Deficiency Using 3 Definitions Among Women in the US and Canada
Bibliographic record
Abstract
Importance: The prevalence of iron deficiency varies widely according to how it is defined. Objective: To compare the prevalence of iron deficiency among women using 3 different definitions. Design, Setting, and Participants: The cross-sectional Hemochromatosis and Iron Overload Screening Study (HEIRS; 2000-2006) evaluated the prevalence, determinants, and outcomes of hemochromatosis and other iron-related disorders. Multiethnic, primary care-based screening (2001-2003) was performed at 5 field centers (4 in the US and 1 in Canada). Volunteer women aged 25 years and older were recruited at primary care venues associated with the field centers. Data were analyzed from June to December 2023. Main Outcomes and Measures: Measures included transferrin saturation, serum ferritin level, and self-reported age, pregnancy, and race and ethnicity. Three iron deficiency definitions were studied: (1) combined transferrin saturation less than 10% and serum ferritin less than 15 ng/mL (HEIRS), (2) serum ferritin less than 15 ng/mL (World Health Organization [WHO]), and (3) serum ferritin less than 25 ng/mL (a threshold for iron-deficient erythropoiesis [IDE]). Results: Among 62 685 women (mean [SD] age, 49.58 [14.27] years), 1957 women (3.12%) had iron deficiency according to the HEIRS definition, 4659 women (7.43%) had iron deficiency according to the WHO definition, and 9611 women (15.33%) had iron deficiency according to the IDE definition. Among 40 381 women aged 25 to 54 years, 1801 women (4.46%) had iron deficiency according to HEIRS, 4267 women (10.57%) had iron deficiency according to WHO, and 8573 women (21.23%) had iron deficiency according to IDE. Prevalence rates of iron deficiency among 2039 women aged 25 to 44 years who reported pregnancy were 5.44% (111 women) according to HEIRS, 18.05% (368 women) according to WHO, and 36.10% (736 women) according to IDE. Iron deficiency prevalence by the 3 respective definitions increased significantly in each racial and ethnic group and was significantly higher among Black and Hispanic participants than Asian and White participants. The relative iron deficiency prevalence among the 62 685 women increased 2.4-fold (95% CI, 2.3-2.5; P < .001) using the WHO definition and increased 4.9-fold (95% CI, 4.7-5.2; P < .001) using the IDE definition. Conclusions and Relevance: Three definitions of iron deficiency were associated with significantly different prevalence of iron deficiency in women, regardless of self-reported age, pregnancy, or race and ethnicity. Using higher serum ferritin thresholds to define iron deficiency could lead to diagnosis and treatment of more women with iron deficiency and greater reduction of related morbidity.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".