The coexistence of child undernutrition and maternal overweight: prevalence, hypotheses, and programme and policy implications
Bibliographic record
Abstract
The purpose of this paper is to document the prevalence of the phenomenon of the coexistence of a stunted child and an overweight mother (SCOWT) in the same household in low- and middle-income countries. We also explore whether this phenomenon is associated with a country's level of economic development and urbanization and highlight policy directions for public nutrition. Data from 36 Demographic and Health Surveys (DHS) were used (23 in Africa, 8 in Latin America, and 5 in Asia). Stunting was defined as height-for-age < -2 SD of the reference population and maternal overweight as a body mass index (BMI) of > 25 kg m(-2). World Bank and United Nations figures were used for gross national product per capita (an indicator of economic development) and for level of urbanization respectively. Descriptive statistics were derived, and multivariate linear regression analysis was used to model the association between economic development, urbanization and the prevalence of SCOWT. The prevalence of SCOWT is generally below 10%, except in four countries, of which three are in Latin America. Among our sample of countries, SCOWT is generally more prevalent in Latin America than in Africa, and is near or below 5% in all five countries of Asia. Contrary to our expectations, SCOWT is not necessarily more prevalent in urban than rural areas. We also find that when economic development is controlled for, SCOWT is associated with urbanization only in Latin America. In Africa and Asia, SCOWT is associated with economic development, but not urbanization. The concrete recognition of the SCOWT phenomenon is an important step to delineating more effective and integrated strategies to address problems of over- and undernutrition and dietary quality within countries, regions and households. This gives special importance to designing programmes and policies that will address the food and nutrition needs of each individual, rather than assuming that those needs are addressed by targeting programmes or policies to the household as a whole.
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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 | 0.014 | 0.033 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.001 | 0.004 |
| Scholarly communication | 0.003 | 0.004 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".