Adverse birth outcomes and associated factors among African grand multiparous women: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Adverse birth outcomes linked to grand multiparity are often more complex than those associated with multiparity. The primary literature on this issue reveals inconsistent findings across various studies. There is a paucity of data in systematic reviews and meta-analyses that specifically assess adverse birth outcomes in African grand multiparas. OBJECTIVES: To determine the pooled adverse birth outcomes and their associated factors among multiparous women in Africa. METHODS: PubMed/Medline, Scopus, Web of Science, ScienceDirect, African Journal Online, Google Scholar, and Wiley Online Library were searched between April 20, 2024, and June 15, 2024. The Newcastle-Ottawa Scale was used to assess methodological quality. Data extraction was performed using Excel, and analysis was conducted with Stata 11 software. Cochran’s Q test and the I² statistic assessed study heterogeneity. Subgroup analysis was conducted based on publication years, and sample sizes. Publication bias was evaluated using funnel plot symmetry and Egger’s test. The prevalence of adverse birth outcomes was estimated using a Random Effects Model, and odds ratios (ORs) with 95% confidence intervals (CIs) were used to pool associated factors. RESULTS: Eighteen studies met the eligibility criteria with a total sample size of 27,122 study participants. The pooled prevalence of adverse birth outcomes among African grand multiparas was 24.97%), 95% CI: 19.97, 31.99). Rural residence (AOR: 4.12; 95% CI: 3.12, 5.44), a history of home births (AOR: 3.30; 95% CI: 1.70, 6.40), and pregnancy-related complications (AOR: 3.17; 95% CI: 2.35, 4.28) were significantly associated with adverse birth outcomes among African grand multiparas women. CONCLUSIONS: Overall, the pooled prevalence of adverse birth outcomes among grand multiparas was comparably high. Variables such as rural residence, previous pregnancy-related complications, and a history of home births were significantly associated with adverse birth outcomes. Strengthening institutional births, providing high-quality prenatal care, and early pregnancy follow-ups are recommended to reduce adverse birth outcomes in grand multipara women. Additionally, improving the availability of comprehensive contraceptive options for rural-residing African grand multipara women is essential. PROSPERO Registration: CRD42024569768.
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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 | 0.015 | 0.036 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.019 | 0.031 |
| Bibliometrics | 0.009 | 0.009 |
| 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) | 0.003 | 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".