Characterisation of anaemia and associated factors among infants and pre-schoolers from rural India
Bibliographic record
Abstract
OBJECTIVE: In India, national databases indicate anaemia prevalence of 80 % among 6-35-month-old children and 58 % among 36-59-month-old children. The present study aimed to characterise anaemia and the associated factors among infants and pre-schoolers living in rural India. DESIGN: Multivariate logistic regression analysis of data collected prior to an intervention trial. Fe-deficiency with anaemia (IDA), Fe deficiency with no anaemia (IDNA) and anaemia without Fe deficiency were defined. Serum ferritin, soluble transferrin receptor (sTfR) and sTfR/log ferritin index were used to indicate Fe status. SETTING: Twenty-six villages of Nalgonda district, Telangana, India. Data were collected in community sites. Participants Four hundred and seventy-six infants (aged 6-12 months), 316 pre-schoolers (aged 29-56 months) and their mothers. RESULTS: Prevalence of anaemia among infants and pre-schoolers was 66·4 and 47·8 %, prevalence of IDA was 52·2 and 42·1 %, prevalence of IDNA was 22·2 and 29·8 %, prevalence of anaemia without Fe deficiency was 14·2 and 5·7 %. Among infants, anaemia was positively associated with maternal anaemia (OR=3·31; 95 % CI 2·10, 5·23; P<0·001), and sTfR/log ferritin index (OR=2·21; 95 % CI 1·39, 3·54; P=0·001). Among pre-schoolers, anaemia was positively associated with maternal anaemia (OR=3·77; 95 % CI 1·94, 7·30; P<0·001), sTfR/log ferritin index (OR=5·29; 95 % CI 2·67, 10·50; P<0·001), high C-reactive protein (OR=4·39; 95 % CI 1·91, 10·06, P<0·001) and young age (29-35 months: OR=1·92; 05 % CI 1·18, 3·13, P=0·009). CONCLUSIONS: Anaemia prevalence continues to be high among infants and pre-schoolers in rural India. Based on sTfR/ferritin index, Fe deficiency is a major factor associated with anaemia. Anaemia is also associated with inflammation among pre-schoolers and with maternal anaemia among infants and pre-schoolers, illustrating the importance of understanding the aetiology of anaemia in designing effective control strategies.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.000 | 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".