Evaluation of Retinol Level Among Preschool Children, Pregnant and Lactating Women Attending Primary Health Care Centres in Baghdad
Bibliographic record
Abstract
Background: Vitamin A deficiency (VAD) is a major public health nutrition problem in the developing world. There have been no studies on this topic in Iraq. This study was designed to evaluate the serum retinol levels of preschool children, pregnant and lactating women. Objectives: The present study is an attempt to estimate the prevalence of vitamin A deficiency among preschool children, pregnant and lactating women attending primary health care centers in Baghdad, in addition to figure out the relation between vitamin A deficiency with some demographical, clinical, variables. Subjects and Methods: The study was conducted during the period from October to December 2009. The sample was comprised of 490 subjects, Lactating women pregnant women and under 6 year's old children attending ten primary health care centers in Baghdad. The data were collected through direct interview; blood samples were taken and analyze for serum retinol (SR) by HPLC analysis and hemoglobin (Hb) level, anthropometric measurement were obtained for the study sample. Results: The study showed that the prevalence of vitamin A deficiency in preschool aged children (below 6 years) was (38.3 %); and that for lactating women and pregnant women were (7.1 %) and (25 %) respectively. Forty percent of pregnant women, (25.8 %) of lactating women and a total of (58.6 %) preschool children were anemic, A correlation coefficient between SR and Hb concentrations was significant (N=490, r=0.533, P<0.0001). Conclusion: Vitamin A deficiency is a public health problem, this study shows that subjects in the 3 groups (preschool children, pregnant and lactating women) are at risk of VAD and anemia; nearly half of them had the co-occurrence of VAD and anemia. A close association between vitamin A deficiency and anemia with a correlation coefficient between SR and Hb concentrations was significant.
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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 | 0.000 | 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".