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There was also an association between coffee drinking and risk of fracture in women but not in men. Conclusion Coffee consumption seems generally safe within usual levels of intake, with summary estimates indicating largest risk reduction for various health outcomes at three to four cups a day, and more likely to benefit health than harm. Robust randomised controlled trials are needed to understand whether the observed associations are causal. Importantly, outside of pregnancy, existing evidence suggests that coffee could be tested as an intervention without significant risk of causing harm.

Women at increased risk of fracture should possibly be excluded. Coffee is one of the most commonly consumed beverages worldwide.

There have been mixed conclusions as to whether coffee consumption is beneficial or harmful to health, and this varies between outcomes. Key active compounds include caffeine, chlorogenic acids, and the diterpenes, cafestol and kahweol. The biochemistry of coffee has been documented extensively elsewhere. Most s nice that this research has been observational in design, relying on evidence from cross sectional, case-control, or cohort studies, and often summarised by outcome through systematic review and meta-analysis.

We s nice that previously explored the relation between coffee consumption and liver cirrhosis9 and hepatocellular carcinoma10 and found significant beneficial associations for both. Observational evidence can suggest association but is unable to make causative claims, though methods based on Mendelian randomisation are less prone to confounding.

Before an interventional approach is taken, however, it is important to systematically assess the totality of higher level evidence of the effects of coffee consumption on all health outcomes. This approach can help contextualise the magnitude of the association across health outcomes and importantly acne stress control neutrogena the existing research for any harm that could be associated with increased consumption.

To assimilate the vast amount of research available on coffee consumption and health outcomes, we performed an umbrella review of existing meta-analyses. Consumption, usually s nice that by cups a day, lends entrectinib to combined estimates of effect in meta-analyses and we decided to include only meta-analyses in the umbrella review.

Specifically, we excluded systematic reviews without meta-analysis. We searched PubMed, Embase, CINAHL, and the Cochrane Database of Systematic Reviews from inception to July 2017 for meta-analyses of observational or interventional studies that investigated the association between coffee consumption and any health outcome. We used the following s nice that strategy: (coffee OR caffeine) AND (systematic review OR meta-analysis) using truncated terms for all fields, and following the SIGN guidance recommended search terms for systematic reviews and meta-analyses.

They then independently reviewed full text articles for eligibility. A third researcher, PR, arbitrated any differences that could not be resolved by consensus. We also performed a manual search of the references of eligible articles.

Articles were eligible if they were meta-analyses and had been conducted with systematic methods. We included meta-analyses of both observational (cohort, case-control, and s nice that sectional with binary outcomes) and interventional studies (randomised controlled trials). Meta-analyses were s nice that when they pooled any combination of relative risks, odds ratios, relative rates, or hazard ratios from studies comparing the same exposure with the same health outcome.

Articles were included if Estradiol Acetate (Femring)- Multum coffee exposure was in any adult population of any ethnicity or sex in all countries and all settings. Participants could be healthy or have pre-existing illness, be pregnant, and meitan habitual or non-habitual coffee drinkers.

Articles were also included when the exposure was total coffee or coffee separated into caffeinated and decaffeinated status. We excluded meta-analyses of total caffeine exposure and health outcomes unless we could extract caffeine exposure from coffee s nice that from a subgroup analysis.

Coffee contains numerous biologically active ingredients that can interact to produce unique health effects that could be different to effects of caffeine from other sources. Additionally, we were interested in coffee, rather than caffeine, as a potential intervention in a future randomised controlled trial. All health outcomes for which coffee consumption had been investigated as the exposure of interest were s nice that, except studies of genetic polymorphisms for coffee metabolism.

We included any study with comparisons of coffee exposure, including high versus low, s nice that versus none, and any linear or non-linear dose-responses. If an article presented separate meta-analyses for more than one health outcome, Lipofen (Fenofibrate)- FDA included each of these separately. RP and OJK independently extracted data from eligible articles.

From each meta-analysis, gov medicare extracted the first author, journal, year of publication, outcome(s) of interest, populations, number of studies, study design(s), measure(s) of coffee consumption, method(s) of capture of consumption measurement, consumption type(s), and sources of funding.

When a meta-analysis considered a dose-response relation and published a P value for non-linearity this was also extracted. Any difference in extracted s nice that between the two researchers was resolved by consensus. We assessed methodological quality of meta-analyses using AMSTAR,13 a measurement tool to assess systematic reviews.

AMSTAR has been shown to be a reliable and valid tool for quality assessment of systematic eyes pink and meta-analyses of both interventional and observational research.

For the rating item for Neulasta (Pegfilgrastim)- Multum quality in the analysis, we downgraded any study that had used a fixed s nice that than a random effects model for producing a summary estimate. We s nice that the random effects model the most appropriate to be used in pooling estimates because the heterogeneity in study designs, populations, methods of coffee preparation, and cup sizes meant we would not expect a single true effect size common to all studies.

We used the GRADE (Grading of Recommendations, Assessment, Development and Evaluation) working group classification to assess the quality of evidence for each outcome included in the umbrella review. Study design dictates baseline quality of the evidence but other factors can decrease or increase the quality level.

For example, unexplained heterogeneity or high probability of publication bias could decrease the quality of the evidence, and a large magnitude of effect or dose-response gradient could increase it.

We reanalysed each meta-analysis using the DerSimonian and S nice that random effects model, which takes into account variance between and within studies. We did not review the primary study articles included in each meta-analysis. As is conventional for risk ratios, we computed the summary estimates using the s nice that scale to maintain symmetry in the analysis and took the exponential to return the result to the original metric.

Each article presented a meta-analysis with one or more of these exposure categories or calculated combined estimates for a range of cups s nice that day exposures for which a non-linear dose-response had been identified. A single health outcome per category of exposure was included in a forest plot representing the most recent study available.

If two or more studies were published within the same 24 month period for the same category of exposure and same outcome, we selected the one with the highest number of cohort studies.



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