Association between coffee or caffeine consumption and fecundity and fertility: a systematic review and dose–response meta-analysis
Bibliographic record
Abstract
Objective: The aim was to investigate whether coffee or caffeine consumption is associated with reproductive endpoints among women with natural fertility (ie, time to pregnancy [TTP] and spontaneous abortion [SAB]) and among women in fertility treatment (ie, clinical pregnancy rate or live birth rate). Design: This study was a systematic review and dose–response meta-analysis including data from case–control and cohort studies. Methods: An extensive literature search was conducted in MEDLINE and Embase, with no time and language restrictions. Also, reference lists were searched manually. Two independent reviewers assessed the manuscript quality using the Newcastle–Ottawa Scale (NOS). A two-stage dose–response meta-analysis was applied to assess a potential association between coffee/caffeine consumption and the outcomes: TTP, SAB, clinical pregnancy, and live birth. Heterogeneity between studies was assessed using Cochrane Q -test and I2 statistics. Publication bias was assessed using Egger’s regression test. Results: The pooled results showed that coffee/caffeine consumption is associated with a significantly increased risk of SAB for 300 mg caffeine/day (relative risk [RR]: 1.37, 95% confidence interval [95% CI]: 1.19; 1.57) and for 600 mg caffeine/day (RR: 2.32, 95% CI: 1.62; 3.31). No association was found between coffee/caffeine consumption and outcomes of fertility treatment (based on two studies). No clear association was found between exposure to coffee/caffeine and natural fertility as measured by fecundability odds ratio (based on three studies) or waiting TTP (based on two studies). Conclusion: Results from this meta-analysis support the growing evidence of an association between coffee/caffeine intake and the risk of SAB. However, viewing the reproductive capacity in a broader perspective, there seems to be little, if any, association between coffee/caffeine consumption and fecundity. In general, results from this study are supportive of a precautionary principle advised by health organizations such as European Food Safety Authority (EFSA) and World Health Organization (WHO), although the advised limit of a maximum of two to three cups of coffee/200–300 mg caffeine per day may be too high. Keywords: coffee, caffeine, fecundity, fertility, spontaneous abortion, assisted reproduction
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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 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.052 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".