Intergenerational influences on childhood anaemia
Bibliographic record
Abstract
Prior research on assessing intergenerational influences on child anaemia has largely approached it from purely maternal perspective. Although there is much merit to focus on that, it is an extremely limited/reductionist view of understanding intergenerational influences. We expanded the intergenerational influences to include the fathers and overall of intergenerational household transfers. We analysed a sample of 19,619 mother-father-offspring trios from the 2015-2016 Indian National Fertility and Health Survey with available data on haemoglobin (Hb). Multinomial logistic regression models were used to establish associations between parent anaemia, household characteristics, and categories of offspring anaemia. Maternal and paternal Hb was measured as in children using a finger prick blood sample. The primary outcome was child's Hb level (in g/dl) and grades of anaemia defined as mild (10-10.9 g/dl), moderate (7-9.9 g/dl), and severe (<7 g/dl). Mean Hb was 10.1 g/dl for children, 14.2 g/dl among fathers, and 11.4 g/dl among mothers. Hb correlation was 0.1 between fathers and offspring and 0.2 between mothers and offspring (P < 0.001 for all correlations). Maternal-paternal Hb correlations were consistent across quintiles of wealth index. Maternal anaemia was associated with odds ratio of 1.3 (95% CI [1.1, 1.4]) and 1.6 (95% CI [1.4, 1.7]) for childhood mild and moderate/severe anaemia, respectively. Paternal mild anaemia was associated with an odds ratio of 1.1 (95% CI [0.9, 1.4]) and 1.4 (95% CI [1.2, 1.7]) for child moderate/severe anaemia. The clustering of poor circumstances suggests that public health strategies target social deprivation at the household level. A comprehensive perspective will provide holistic interventions to control childhood anaemia.
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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".