Health facility delivery and early initiation of breastfeeding: Cross‐sectional survey of 11 sub‐Saharan African countries
Bibliographic record
Abstract
Background and Aims: Early initiation of breastfeeding (EIB) remains one of the promising interventions for preventing neonatal and child deaths. EIB is positively associated with healthcare delivery or childbirth. Meanwhile, no study in sub-Saharan Africa (SSA) appears to have investigated the relationship between health facility delivery and EIB; thus, we assessed the correlation between health facility delivery and EIB. Methods: We used data from the Demographic and Health Survey (DHS) of 64,506 women from 11 SSA countries. The outcome variable was whether the respondent had early breastfeeding or not. Two logistic regression models were used in the inferential analysis. With a 95% confidence interval (CI), the adjusted odds ratios (aORs) for each variable were calculated. The data set was stored, managed, and analyzed using Stata version 13. Results: The overall percentage of women who initiated early breastfeeding was 59.22%. Rwanda recorded the highest percentage of early initiation of breastfeeding (86.34%), while Gambia recorded the lowest (39.44%). The adjusted model revealed a significant association between health facility delivery and EIB (aOR = 1.80, CI = 1.73-1.87). Compared with urban women, rural women had higher likelihood of initiating early breastfeeding (aOR = 1.22, CI = 1.16-1.27). Women with a primary education (aOR = 1.26, CI = 1.20-1.32), secondary education (aOR = 1.12, CI = 1.06-1.17), and higher (aOR = 1.13, CI = 1.02-1.25), all had higher odds of initiating early breastfeeding. Women with the richest wealth status had the highest odds of initiating early breastfeeding as compared to the poorest women (aOR = 1.33, CI = 1.23-1.43). Conclusion: Based on our findings, we strongly advocate for the integration of EIB policies and initiatives with healthcare delivery advocacy. Integration of these efforts can result in drastic reduction in infant and child mortality. Essentially, Gambia and other countries with a lower proclivity for EIB must reconsider their current breastfeeding interventions and conduct the necessary reviews and modifications that can lead to an increase in EIB.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".