Socioeconomic inequalities in underweight children: a cross-sectional analysis of trends in West Africa over two decades
Bibliographic record
Abstract
OBJECTIVE: To study trends in socioeconomic inequalities in underweight children in West Africa, and specifically to analyse the concentration index of underweight inequalities and measure inequalities in the risk of being malnourished by household wealth index. DESIGN: Cross-sectional study. SETTING: The study used 50 Demographic and Health Surveys (DHS) and Multiple Indicator Cluster Surveys conducted between 1999 and 2020 across 14 countries by the DHS and UNICEF. PARTICIPANTS: The study included 481 349 children under the age of 5 years. PRIMARY AND SECONDARY OUTCOME MEASURES: The analysis used three variables: weight-for-age index, household wealth index and household residence. The inequality concentration index for underweight children and the relative risk of being underweight between 2000 and 2020 were calculated. RESULTS: The prevalence of underweight in West Africa showed a downward trend from 2000 to 2020. Nonetheless, the prevalence of underweight children under 5 years of age is still very high in West Africa compared with other sub-Saharan African countries, and the sustainable development objective is yet to be achieved. There was a wide disparity among countries and significant socioeconomic inequalities in underweight children within countries. The proportions of underweight children were concentrated in poor households in all countries in West Africa and over all periods. Socioeconomic inequalities in underweight children were more significant in countries where the prevalence of underweight was low. These inequalities were more pronounced in urban areas in West Africa from 2000 to 2020. CONCLUSIONS AND RELEVANCE: There is a high concentration of socioeconomic inequalities in underweight children in disadvantaged households in West Africa.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".