Dietary Iron Intakes in Men in Europe Are Distinctly Above the Recommendations: A Review of 39 National Studies From 20 Countries in the Period 1995 - 2016
Bibliographic record
Abstract
The objective of this review was to assess whether dietary iron intake in men in Europe is in symphony with the dietary recommendations. A literature search of national dietary surveys reporting the intake of iron using PubMed, Google Scholar, National Nutrient Databases and previous literature on dietary reviews was performed. The subjects were men aged 18 - 70 years. A total of 39 national dietary surveys in 20 European countries in the period 1995 - 2016 were included. There were considerable differences between median/mean iron dietary intake in the 20 countries. Seven countries/regions, UK-Northern Ireland, UK-Wales, Sweden, Belgium, UK-Scotland, UK-England and Serbia reported median/mean iron intake ranging from 10.5 to 11.6 mg/day. Ten countries, Norway, Finland, Lithuania, Italy, Hungary, Portugal, The Netherlands, Denmark, Iceland and Austria reported iron intake from 12.0 to 13.5 mg/day. France, Germany, Ireland and Spain reported iron intake from 14.8 to 16.0 mg/day, while Poland and Slovakia reported the highest intake of 17.2 and 22.7 mg/day. In surveys from France and The Netherlands, intake of heme iron constituted 11% of total dietary iron intake. Nutrient density for iron, reported in five countries, varied from median 11.6 mg iron/10 MJ in Denmark to 16.0 in France. In all countries, the majority of men had a dietary iron intake markedly above a recommended intake of 9 mg/day. In Europe, 75-87% of men have a dietary iron intake above 9 mg/day. A high iron intake together with relatively high intakes of meat and alcohol contributes to a high iron status and a high frequency of body iron overload in many men. We need consensus on common European standardized dietary methods, uniform dietary reference values and uniform statistical methods to perform inter-country comparisons.
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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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| 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".