Population patterns of hair zinc, dietary and socio-demographic determinants
Bibliographic record
Abstract
Marginal zinc deficiency (MZD) exists in children of industrialized societies and can impair growth and development. Presently there are no data available on its global prevalence. It is believed that MZD is one of the most common hidden deficiencies throughout the world. This is partly because of the lack of sensitivity and specificity of serum zinc, the most commonly used biomarker of zinc status, to detect MZD . This deficiency in children is always accompanied by a decrease in hair zinc . Although in research settings hair zinc is a recognized biomarker of MZD in children, health practitioners do not presently use it. These cross-sectional studies were designed to examine the hair zinc status of preschoolers in Vancouver . They also aimed at exploring some dietary and non-dietary factors associated with hair zinc status in an attempt to construct and validate a screening tool for detection of MZD. Our first study indicated a mean hair zinc of 75±30 μg/g, with 46% below the cutoff (<70μg/g) for a group (n=87) of low-income preschoolers (Chapter II). Among these children we observed negative associations between the hair zinc and consumption of dairy (R² =0.09, P=0 .01) and milk (R² =0.08, P=0.01), being described as "often sick" (R² =0.55, P=0 .00) and "eating unhealthy" (R² =0.16 P=0.00), and prolonged breastfeeding (R² =0.11, P=0.01). Our citywide survey (n=719) indicated a mean hair zinc of 116±43 μg/g with 17% below the cutoff (Chapter III). Logistic regression analysis indicated sex, age, maternal education, the number of adults at home, consumption frequency of milk, "scores of activity level", "being described as frequently sick" and "taking supplements containing iron" as the significant predictors of hair zinc status . However, the final model had 16% sensitivity while having 98 .3% specificity, indicating its lack of usefulness as a screening tool. Our study provides important information on the hair zinc status of Vancouver preschoolers. Although we did not accomplish our primary goal of constructing and validating a screening tool, we did identify some factors in children and their environment associated with hair zinc, which may help in better understanding of hair zinc as a biomarker of MZD .
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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 | 0.000 | 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) | 0.002 | 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".