Meta Analysis: Effect of Oral Contraceptives on Obesity in Fertile Age Women in Asia
Bibliographic record
Abstract
Background: Obesity is a disease with a complex (multi-causal) cause because it involves genetic and environmental factors. Some of them are heredity, individual socio-economic factors, eating patterns (habits), food consumption, physical activity, hormonal, nutritional knowledge, and perception. This study aimed to analyze the effect of oral contraceptives on obesity in women of childbearing age. Subjects and Method: This was a meta analysis and systematic review from several observational studies. The articles were collected from PubMed, Google Scholar, and Springerlink databases, published from 2000-2020. Data collection used eligibility criteria, including population (P): women of reproductive age, intervention (I): oral contraceptive, comparison (C): non oral contraceptive, and outcome (O): obesity. Keywords used “pil contraception” OR “Pil Contraceptive” AND “Oral Contraceptive” OR “Oral Contraception” AND “Obesity” OR “Overweight” AND“ Cross sectional” AND “Cohort” AND “Adjusted Odds Ratio”. Selected articles were full text of observational study. These articles were selected by PRISMA flow diagram. Quantitative synthesis was conducted using Review Manager 5.3 program. Results: A total of 3 articles reviewed in a meta-analysis with subgroup analysis using an observational cohort design showed that oral contraceptives increased the risk of obesity in women of reproductive age (aOR= 1.14, 95% CI= 1.03-1.26, p<0.001). A meta-analysis of 4 articles that conducted a subgroup analysis with a cross sectional observational design also showed that oral contraceptives increased the risk of obesity in women of childbearing age (aOR= 1.52; 95% CI= 0.78-298; p <0.001). This meta-analysis combines primary research from Korea, India, Canada, Congo, and the United States of America. Conclusion: Oral contraceptives increase the risk of obesity. Keywords: oral contraception, obesity Correspondence: Muhammad Zia Ulhaq. Masters Program in Public Health, Universitas Sebelas Maret, Jl. Ir. Sutami 36A, Surakarta 57126, Central Java. Email: kandaulhaq@gmail.com. Journal of Maternal and Child Health (2020), 05(06): 673-682 https://doi.org/10.26911/thejmch.2020.05.06.07.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".