The Association of Assisted Reproductive Technology and Breastfeeding Rates: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
Background: There is an inconsistent result regarding the mode of fertilization and breastfeeding. Objective: This systematic review and meta-analysis aimed to determine the association between the mode of conception and breastfeeding continuity. Materials and Methods: The English electronic databases were searched for up to May 20, 2022. The Newcastle-Ottawa Quality Assessment Scale was used to evaluate the quality of the included studies. Publication bias was assessed using a funnel plot. The heterogeneity of studies was evaluated using I2 statistics. Results of the random-effects meta-analysis were presented using odds ratios (ORs)/relative ratio (RR) and 95% confidence intervals (CIs). Results: A total of 12 articles with 4,929 subjects were included in this systematic review and meta-analysis. The pool estimates of the meta-analysis show that spontaneous conception is associated with breastfeeding continuity up to 6 months (OR/RR = 0.66, 95% CI: 0.46–0.87) and more than 6 months after childbirth (OR/RR = 0.65, 95% CI: 0.32–0.98) compared to the Assisted reproductive technology (ART) conception. The heterogeneity among the studies was high. The level of breastfeeding, plurality, gestational age, and country were confounding factors that affect the heterogeneity of studies. Conclusion: Our findings confirm an inverse association between ART conception and breastfeeding continuity. Due to the importance of breast milk in improving the health of infants who are born in this way, it is recommended to take appropriate interventions in this field. Possible interaction between ART and breastfeeding continuity in different regions is important to point and future studies on this topic were recommended.
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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 | 0.016 | 0.040 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.042 |
| Bibliometrics | 0.008 | 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 | 0.002 |
| 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".