Dietary exposure and health risk assessment for 11 minerals and trace elements in Yaoundé: the Cameroonian Total Diet Study
Bibliographic record
Abstract
Dietary exposure to 11 elements was assessed by the Total Diet Study (TDS) method. Sixty-four pooled samples representing 96.5% of the diet in Yaoundé, Cameroon, were prepared as consumed before analysis. Consumption data were sourced from a household budget survey. Dietary exposures were compared with nutritional or health-based guidance values (HBGV) and to worldwide TDS results. Elevated prevalence of inadequate intake was estimated for calcium (71.6%), iron (89.7%), magnesium (31.8%), zinc (46.9%) and selenium (87.3%). The percentage of the study population exceeding the tolerable upper intake levels was estimated as <3.2% for calcium, iron, magnesium, zinc and cobalt; 19.1% of the population exceeded the HBGV for sodium. No exceedance of the HBGV for inorganic mercury was predicted in the population. The margin of exposure ranged from 0.91 to 25.0 for inorganic arsenic depending on the reference point. The "Fish" food group was the highest contributor to intake for calcium (65%), cobalt (32%) and selenium (96%). This group was the highest contributor to the exposure to total arsenic (71%) and organic mercury (96%). The "Cereals and cereal products" highly contributed to iron (26%), zinc (26%) and chromium (25%) intakes. The "Tubers and starches" highly contributed to magnesium (39%) and potassium (52%) intakes. This study highlights the dietary deficiency of some essential elements and a low dietary exposure to toxic elements in Yaoundé.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".