Predictors of exclusive breastfeeding: a systematic review and meta-analysis
Bibliographic record
Abstract
Breast milk is the ideal and complete food for infants. Demographic, social, economic and clinical factors affect exclusive breastfeeding (EBF). Identifying and understanding these factors can improve breastfeeding success. This study systematically reviews and analyzes the predictors of EBF. This study is a systematic review and meta-analysis. we searched electronic databases including PubMed/MEDLINE, Web of Science, PsycINFO, Cochrane, Scopus, EMBASE, Google Scholar, SID, and Magiran. we examined articles published between 2000 to 2023 using keywords like "risk factors", "related factors", "predictive factors", "exclusive breastfeeding ", and "women". The review included observational studies. Two reviewers independently selected the studies extracted data. Quality assessment was based on the Newcastle–Ottawa Scale. The association between predictive factors and breastfeeding was combined in a meta-analysis using a restricted maximum likelihood method (REML). Heterogeneity was quantified using I 2 and investigated through meta-regression, subgroup, and sensitivity analyses, while publication bias was assessed via a funnel plot. Thirty eight articles were included in this review. Predictive factors in EBF were categorized into seven groups: mother’s awareness of breastfeeding benefits, support received in breastfeeding and child-rearing, early breastfeeding after birth, mother’s education level, annual income, mother’s age, and prenatal care. Nineteen articles with a sample size of 70,183 were included in the meta-analysis. Results showed that a mother's awareness of breastfeeding benefits increases the odds of EBF by 2.70 times, support in child-rearing by 2.57 times, early breastfeeding (< 24 h) by 1.853 times, higher education level by 1.44 times, self-efficacy by 1.067, multiparity ≥ 2 by 1.50 times, having upper-middle annual income was associated with 28.3% higher than odds of EBF (95% CI 1.68, 1.54), female sex of infant by 1.07 times, and one to three antenatal visits by 0.108 times, (95% CI 1.27, 4.18). In normal vaginal delivery (NVD), the odds increased 2.22 fold, all statistically significant (95% CI 0.91, 5.43). The maternal awareness of the benefits of breastfeeding, maternal support, early breastfeeding, high education level, and improved family economic conditions are associated with EBF. Therefore, improving the educational, social, and economic levels of mothers improves EBF. PROSPERO CRD42023483049.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.040 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".