High prevalence of iron deficiency and socioeconomic disparities in laboratory screening of <scp>non‐pregnant</scp> females of reproductive age: A retrospective cohort study
Bibliographic record
Abstract
Iron deficiency anemia (IDA) and non-anemic iron deficiency (NAID) are highly prevalent among non-pregnant females of reproductive age. Canada has no national screening guidelines for this population. Screening, when performed, is often with a complete blood count alone without ferritin or iron indices. The primary objective was to determine the prevalence of screening for NAID and IDA over a 3-year period in non-pregnant females of reproductive age who had tests performed at outpatient laboratories in Ontario, Canada. Retrospective cohort study of non-pregnant females ages 15-54 in Ontario, from 2017 to 2019. NAID was defined as ferritin <30 μg/L, anemia as hemoglobin <120 g/L, and IDA as ferritin <30 μg/L and hemoglobin <120 g/L. Annual household income was estimated using patient postal codes. A total of 784 132 non-pregnant females were included. The 82.1% were screened for iron deficiency, 38.3% had NAID and 13.1% had IDA; 55.6% with IDA had normal mean corpuscular volumes. The median household income was $89454.80 compared with a provincial median of $65285.00. Patients in the lowest income quintile had the highest odds of being anemic, and the lowest odds of having a ferritin checked. A large proportion of non-pregnant females of reproductive age in this cohort were screened for iron deficiency. In this relatively privileged cohort, NAID affected nearly 40%, and IDA 13%. Most patients with IDA did not have microcytosis. Low household income was associated with the greatest odds of anemia and the lowest odds of being screened, highlighting inequitable access to screening for IDA in Ontario, Canada.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".