Mother–child dyads of overnutrition and undernutrition in sub-Saharan Africa
Bibliographic record
Abstract
BACKGROUND: Malnutrition remains one of the major public health concerns globally. To achieve the Sustainable Development Goal 2 which seeks to ensure that hunger and malnutrition are reduced by 2030, it is imperative to ascertain the factors influencing their occurrence. This study examined the prevalence and factors associated with mother-child dyads of overnutrition and undernutrition in sub-Saharan Africa. METHODS: Demographic and Health Survey data from 25 sub-Saharan African countries were used for the study. The sample was made up of 125,280 mother-child dyads. Descriptive analysis was performed to determine the prevalence of overweight or obese mother (OWOBM) with a stunted child (OWOBM-SC), OWOBM with an underweight child (OWOBM-UC), OWOBM with a wasted child (OWOBM-WC), and OWOBM with any form of child's undernutrition indicators (OWOBM-SUWC). Multilevel regression models were developed to examine the factors associated with these indicators. The results were presented using an adjusted odds ratio (AOR) with their respective 95% confidence interval (CI). RESULTS: Higher likelihood of OWOBM-SUWC was found among women aged 45-49 [AOR 2.20, 95% CI 1.70, 2.85], those with primary [AOR 1.32, 95% CI 1.21, 1.44] or secondary education [AOR 1.21, 95% CI 1.09, 1.35], and divorced women [AOR 1.32, 95% CI 1.02, 1.73]. However, lower odds of OWOBM-SUWC were observed among women who were working [AOR 0.82, 95% CI 0.76, 0.89] and those breastfeeding [AOR 0.75, 95% CI 0.70, 0.82]. The odds of OWOBM-SUWC was lower among females compared to male children [AOR 0.85, 95% CI 0.80, 0.90]. Compared to children aged <1 year, children of all other age groups were more likely to have OWOBM-SUWC. Other child characteristics significantly associated with OWOBM-SUWC were low birth weight [AOR 1.50, 95% CI 1.32, 1.71], having diarrhea [AOR 1.13, 95% CI 1.04, 1.24], and higher birth order [AOR 1.37, 95% CI 1.13, 1.66]. Children whose mothers used unimproved toilet facilities [AOR 0.90, 95% CI 0.83, 0.98], those who lived in rural areas [AOR 0.79, 95% CI 0.71, 0.87], and children from the Central [AOR 0.55, 95% CI 0.46, 0.65], Eastern [AOR 0.44, 95% CI 0.38, 0.52] and Western [AOR 0.76, 95% CI 0.65, 0.89] sub-Saharan Africa were less likely to have OWOBM-SUWC. CONCLUSION: Combination of child, maternal, and contextual factors could explain mother-child dyads of overnutrition and undernutrition in sub-Saharan Africa. Addressing this situation requires multidimensional policies and interventions that empower women through education and economic engagement. The observed sub-regional differences in policies and commitments related to addressing malnutrition suggest the need for comprehensive and coordinated efforts to implement and strengthen multisectoral comprehensive nutrition plans across sub-Saharan Africa. Sharing best practices and lessons learned can help improve the effectiveness and comprehensiveness of nutrition interventions and contribute to reducing the prevalence of malnutrition.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".