Iron status and anaemia in Sri Lankan secondary school children: A cross-sectional survey
Bibliographic record
Abstract
BACKGROUND: Iron deficiency, the most common micronutrient disorder and cause of anaemia globally, impairs growth, cognition, behaviour and resistance to infection. METHODS/RESULTS: As part of a national survey of inherited haemoglobin variants in 7526 students from 72 secondary schools purposefully selected from the 25 districts of Sri Lanka, we studied 5912 students with a normal haemoglobin genotype. Median age was 16.0 (IQR 15.0-17.0) years and 3189 (53.9%) students were males. Most students were Sinhalese (65.7%), with fewer Tamils (23.1%) and Muslims (11.2%). Anaemia occurred in 470 students and was more common in females (11.1%) than males (5.6%). Haemoglobin, serum ferritin, transferrin receptor and iron were determined in 1196 students with low red cell indices and a structured sample of those with normal red cell indices (n = 513). The findings were weighted to estimate the frequencies of iron deficiency and iron deficiency anaemia classified according to WHO criteria. Iron depletion (serum ferritin <15ug/ml) occurred in 19.2% and cellular iron deficiency (low serum ferritin and transferrin receptor >28.1 nmol/l) in 11.6% students. Iron deficiency anaemia (cellular iron deficiency with low haemoglobin) occurred in only 130/2794 (4.6%) females and 28/2789 (1.0%) males. Iron biomarkers were normal in 83/470 (14.6%) students with anaemia. In multiple regression analysis, the odds for iron depletion and cellular iron deficiency were about one-third in males compared with females, and the odds for iron deficiency anaemia were about one fifth in males compared to females. Tamil ethnicity and age <16 years increased the risk of all three stages of iron deficiency and living at high altitude significantly reduced the risk of iron depletion. CONCLUSIONS: Low iron status and anaemia remain common problems in Sri Lankan secondary school students especially females, younger students and the socioeconomically disadvantaged Tamil population. More research is needed to identify factors other than low iron status that contribute to anaemia in adolescents.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".