Differential effects of socio-demographic factors on maternal haemoglobin concentration in three sub-Saharan African Countries
Bibliographic record
Abstract
Low Haemoglobin concentration (Hb) among women of reproductive age is a severe public health problem in sub-Saharan Africa. This study investigated the effects of putative socio-demographic factors on maternal Hb at different points of the conditional distribution of Hb concentration. We utilised quantile regression to analyse the Demographic and Health Surveys data from Ghana, Democratic Republic of the Congo (DRC) and Mozambique. In Ghana, maternal schooling had a positive effect on Hb of mothers in the 5th and 10th quantiles. A one-year increase in education was associated with an increase in Hb across all quantiles in Mozambique. Conversely, a year increase in schooling was associated with a decrease in Hb of mothers in the three upper quantiles in DRC. A unit change in body mass index had a positive effect on Hb of mothers in the 5th, 10th, 50th and 90th, and 5th to 50th quantiles in Ghana and Mozambique, respectively. We observed differential effects of breastfeeding on maternal Hb across all quantiles in the three countries. The effects of socio-demographic factors on maternal Hb vary at the various points of its distribution. Interventions to address maternal anaemia should take these variations into account to identify the most vulnerable groups.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".