Sex inequality in early initiation of breastfeeding in 24 sub-Saharan African countries: A multi-country analysis of Demographic and Health Surveys
Bibliographic record
Abstract
BACKGROUND: The Sustainable Development Goal (SDG) 3 aims at reducing neonatal and under-5 mortality to below 12 per 1000 and 25 per 1000 live births, respectively, globally by 2030. Studies have found that initiation of breastfeeding within one hour of birth and continuous breastfeeding for over 12 months can positively impact neonatal and infant health. However, there is evidence that the sex of a child may influence the breastfeeding practices of a mother. Thus, we examined sex inequality in early breastfeeding initiation in sub-Saharan Africa. MATERIALS AND METHODS: Data from Demographic and Health Surveys conducted in 24 sub-Saharan African countries between January 2010 and December 2019 were pooled and analysed. A total of 137,677 women of reproductive age (15-49 years) were considered in this study. Bivariate and multivariable regression analyses were performed, and the results were presented using crude odds ratio (cOR) and adjusted odds ratio (aOR) with statistical significance at a p-value less than 0.05. RESULTS: The highest inequality in early initiation of breastfeeding was reported in Togo with a difference of 5.21% between the female and male children, while the lowest inequality was reported in Guinea with 0.48% difference between the female and male children. A higher odds of breastfeeding within 1 hour was observed among female children [cOR = 1.05; 95%(CI = 1.02-1.09)] compared to male children, and this persisted after controlling for the confounders included in this study [aOR = 1.05; 95%(CI = 1.02-1.08)]. CONCLUSION: We found higher odds for early breastfeeding initiation of female children compared to male children in sub-Saharan Africa. To reduce breastfeeding initiation inequalities, programmes that educate and encourage early initiation of breastfeeding irrespective of the child sex should be promoted among mothers.
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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 | 0.005 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| 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".