Population Iron Status in Canada: Results from the Canadian Health Measures Survey 2012–2019
Bibliographic record
Abstract
BACKGROUND: In Canada, population iron status estimates are dated (2009-2011) and did not consider the presence of inflammation. OBJECTIVES: This study aimed to update iron status estimates in Canada using serum ferrin (SF) and evaluate different correction methods for inflammation based on c-reactive protein (CRP). METHODS: Data from the Canadian Health Measures Survey cycles 3-6 (2012-2019) formed a multiyear, cross-sectional, nationally representative sample (3-79 y) (n = 21,453). WHO cutoffs for SF and hemoglobin were used to estimate iron deficiency (ID), iron deficiency anemia (IDA), anemia, and elevated iron stores. ID was first estimated without considering inflammation. Correction approaches evaluated were excluding individuals with CRP >5 mg/L, using modified SF cutoffs, and regression correction. RESULTS: Total population uncorrected prevalence estimates were 7% (95% CI: 6.2, 7.9) ID, 6.1% (95% CI: 5.2, 7.0) anemia, and 2.0% (95% CI: 1.6, 2.4) IDA. The uncorrected prevalence of ID was the highest among females of reproductive age with 21.3% (95% CI: 17.6, 25.0) and 18.2% (95% CI: 15.4, 21.1) in 14-18 y and 19-50 y, respectively. Corrected ID estimates were higher than the uncorrected values, independent of the correction approach. Regression correction led to a moderate increase in the prevalence to 10.5% for the total population, whereas applying the higher modified SF cutoffs (70 μg/L for those older than 5 y) led to the largest increases in the prevalence, to 12.6%. Applying modified cutoffs led to implausibly high ID estimates among those with inflammation. Elevated iron stores were identified in 17.2% (95% CI: 16.2, 18.2) of the population, mostly in adult males. CONCLUSIONS: Correction methods for estimating population iron status need further research. Considering the fundamental drawbacks of each method, uncorrected and regression-corrected estimates provide a reasonable range for ID in the Canadian population. Important sex-based differences in iron status and a public health ID problem of moderate magnitude among females of reproductive age are evident in 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".