The correlation of number of parity and bone mineral density (BMD) in women: A systematic review and meta-analysis
Bibliographic record
Abstract
Introduction: Osteoporosis is a major health problem in women throughout the world. Based on the available evidence, delivery can play an important role in women's bone mineral density. Therefore, this study was performed with aim to determine the correlation between parity and bone mineral density through systematic review and. Methods: In this systematic review and meta-analysis study, for finding the related articles, the databases of PubMed, Scopus, Cochran library and Web of Science databases were searched without time limitation and with English language restriction by using of the keywords of Parity and Bone Mineral Density (BMD) or Bone Mineral Content or bone density. The adapted Newcastle-Ottawa Scale was used to assess the quality of the cross-sectional articles. Funnel plot and Egger's test was used for publication bias assessing. Q-test and I2 index were used for evaluation of heterogeneity. Fisher’s 𝑟-to-𝑧 transformation was calculated for the studies. Results: In this study, a total of 1336 papers were reviewed and 11 studies involving 5141 women were included in this meta-analysis. The decreasing trend in lumbar spine, femur and total hip BMD was observed in women with parity ≥5 compared to non-parity women. In nulliparous women, the mean of BMD in lumbar spine was (M:0.93 ,95%CI;0.75-1.11, Phetrogeneity <0.001), in femur (M:0.84 95%CI;0.60-1.09, Phetrogeneity <0.001) and in hip (M:0.86, 95%CI;0.84-0.89, Phetrogeneity =0.001). The mean of BMD in postmenopausal women was lower in lumbar, femur and hip. In African women, the mean of BMD in three sites were higher. There was no reverse moderate correlation between parity and lumbar BMD -0.22 (95% CI -0.14, -0.30) and hip BMD -0.21 (95% CI -0.12, -0.29). Conclusion: The mean BMD was higher in nulliparous women. There was inverse correlation between lumbar BMD and hip BMD with parity, but because of high heterogeneity in analyzed subgroups, performing cohort studies is 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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.018 | 0.035 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".