Do pregnant African women exercise? A meta-analysis
Bibliographic record
Abstract
INTRODUCTION: Antenatal exercise can reduce gestational weight gain, backache; pregnancy induced medical disorders, caesarean section rates, and improves pregnancy outcomes. American College of Obstetrics and Gynecology (ACOG) recommends prenatal exercise, which is associated with minimal risk and has been shown to be beneficial for pregnancy outcomes, although some exercise routines may need to be modified. Consequently, this meta-analysis is intended to verify the pooled practice of antenatal exercise in Africa using available primary articles. METHODS: Genuine search of the research articles was done via PubMed, Scopes, Cochrane library, the Web of Science; free Google databases search engines, Google Scholar, and Science Direct databases. Published and unpublished articles were searched and screened for inclusion in the final analysis and Studies without sound methodologies, and review and meta-analysis were not included in this analysis. The Newcastle-Ottawa scale was used to assess the risk of bias. If heterogeneity exceeded 40%, the random effect method was used; otherwise, the fixed-effect method was used. Meta-analysis was conducted using STATA version 14.0 software. Publication bias was checked by funnel plot and Egger test. RESULTS: This review analyzed data from 2880 women on antenatal care contact from different primary studies. The overall pooled effect estimate of antenatal exercise in Africa was 34.50(32.63-36.37). In the subgroup analysis for pooled antenatal exercise practice by country, it was 34.24 (31.41-37.08) in Ethiopia and 37.64(34.63-40.65) in Nigeria. CONCLUSION: The overall pooled effect estimate of antenatal exercise in Africa was low compared to other continent. As it was recommended by ACOG antenatal exercise to every patient in the absence of contraindications, it should be encouraged by professionals providing antenatal care service.
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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 | 0.030 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.021 | 0.059 |
| Bibliometrics | 0.007 | 0.006 |
| 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) | 0.005 | 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".