Prevalence of exclusive breastfeeding practice in the first six months of life and its determinants in Iran: a systematic review and meta-analysis
Bibliographic record
Abstract
Abstract Background Exclusive breastfeeding (EBF) in the first 6 months of life is the best and most complete option for an infant, in that supplies the vitamins and minerals the baby needs. Several studies in Iran have been conducted concerning the prevalence of EBF. The aim of this study was to determine the prevalence of EBF in the first 6 months of life and associated factors in Iran synthesizing published studies. Methods We searched PubMed/MEDLINE, Embase, Scopus, ISI/Web of Science, the Cochrane Library, Directory of Open Access Journals Directory (DOAJ) and Google Scholar as well as Iranian databases (Barakathns, MagIran and the Scientific Information Database or SID) up to November 2018. The Newcastle-Ottawa Scale was used to assess the quality of studies. Analyses were performed by pooling together studies using DerSimonian-Laird random-effects model with 95% confidence interval. To test for heterogeneity, I2test was used. The Egger’s regression test and funnel plot were used to evaluate the publication bias. The strength of EBF determinants was assessed computing the Odds-ratios (OR) using the Mantel–Haenszel method. Results In the initial search 725 records were found. Finally, 32 studies were selected based on inclusion/exclusion criteria. The sample size of studies varied between 50 and 63,071 subjects. The overall prevalence of EBF in Iran was 53% (CI 95%; 44–62). The OR for breastfeeding education received before pregnancy was 1.13 (0.94–1.36), for mother’s job 1.01 (0.81–1.27), for education level 1.12 (0.89–1.42), for type of delivery 1.16 (0.98–1.37), and for gender of child 1.03 (0.83–1.28). Conclusion In Iran health policy- and decision-makers should try to take interventions that encourage mothers to use their milk to breastfeed the infants.
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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 | 0.010 | 0.024 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.026 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".