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• v.359; 2017

Coffee consumption and health: umbrella review of meta-analyses of multiple health outcomes

Robin poole.

1 Academic Unit of Primary Care and Population Sciences, Faculty of Medicine, University of Southampton, South Academic Block, Southampton General Hospital, Southampton, Hampshire SO16 6YD, UK

Oliver J Kennedy

Paul roderick, jonathan a fallowfield.

2 Medical Research Council/University of Edinburgh Centre for Inflammation Research, Queen’s Medical Research Institute, Edinburgh, EH16 4TJ, UK

Peter C Hayes

Julie parkes, associated data.

Objectives  To evaluate the existing evidence for associations between coffee consumption and multiple health outcomes.

Design  Umbrella review of the evidence across meta-analyses of observational and interventional studies of coffee consumption and any health outcome.

Data sources  PubMed, Embase, CINAHL, Cochrane Database of Systematic Reviews, and screening of references.

Eligibility criteria for selecting studies  Meta-analyses of both observational and interventional studies that examined the associations between coffee consumption and any health outcome in any adult population in all countries and all settings. Studies of genetic polymorphisms for coffee metabolism were excluded.

Results  The umbrella review identified 201 meta-analyses of observational research with 67 unique health outcomes and 17 meta-analyses of interventional research with nine unique outcomes. Coffee consumption was more often associated with benefit than harm for a range of health outcomes across exposures including high versus low, any versus none, and one extra cup a day. There was evidence of a non-linear association between consumption and some outcomes, with summary estimates indicating largest relative risk reduction at intakes of three to four cups a day versus none, including all cause mortality (relative risk 0.83, 95% confidence interval 0.83 to 0.88), cardiovascular mortality (0.81, 0.72 to 0.90), and cardiovascular disease (0.85, 0.80 to 0.90). High versus low consumption was associated with an 18% lower risk of incident cancer (0.82, 0.74 to 0.89). Consumption was also associated with a lower risk of several specific cancers and neurological, metabolic, and liver conditions. Harmful associations were largely nullified by adequate adjustment for smoking, except in pregnancy, where high versus low/no consumption was associated with low birth weight (odds ratio 1.31, 95% confidence interval 1.03 to 1.67), preterm birth in the first (1.22, 1.00 to 1.49) and second (1.12, 1.02 to 1.22) trimester, and pregnancy loss (1.46, 1.06 to 1.99). 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.

Introduction

Coffee is one of the most commonly consumed beverages worldwide. 1 As such, even small individual health effects could be important on a population scale. There have been mixed conclusions as to whether coffee consumption is beneficial or harmful to health, and this varies between outcomes. 2 Roasted coffee is a complex mixture of over 1000 bioactive compounds, 3 some with potentially therapeutic antioxidant, anti-inflammatory, antifibrotic, or anticancer effects that provide biological plausibility for recent epidemiological associations. Key active compounds include caffeine, chlorogenic acids, and the diterpenes, cafestol and kahweol. The biochemistry of coffee has been documented extensively elsewhere. 4 Coffee undergoes a chemical metamorphosis from the unroasted green bean, and the type of bean (Arabica versus Robusta), degree of roasting, and preparation method including coffee grind setting and brew type, will all have an influence on the biochemical composition of the final cup. 5 6 7 An individual’s genotype and gut microbiome will then determine the bioavailability and type of coffee metabolites to which that individual is exposed. 8

Existing research has explored the associations between coffee as an exposure and a range of outcomes including all cause mortality, cancer, and diseases of the cardiovascular, metabolic, neurological, musculoskeletal, gastrointestinal, and liver systems, as well as outcomes associated with pregnancy. Most of 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 have previously explored the relation between coffee consumption and liver cirrhosis 9 and hepatocellular carcinoma 10 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. Interventional research, ideally in the form of randomised controlled trials, is essential before we can fully understand coffee’s potential to prevent specific health outcomes.

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 assess 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.

Umbrella review methods

Umbrella reviews systematically search, organise, and evaluate existing evidence from multiple systematic reviews and/or meta-analyses on all health outcomes associated with a particular exposure. 11 We conducted a review of coffee consumption and multiple health outcomes by systematically searching for meta-analyses in which coffee consumption was all or part of the exposure of interest or where coffee consumption had been part of a subgroup analysis. Consumption, usually measured by cups a day, lends itself 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.

Literature search

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 search 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. 12 Two researchers (RP and OJK) independently screened the titles and abstracts and selected articles for full text review. 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.

Eligibility criteria and data extraction

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 cross sectional with binary outcomes) and interventional studies (randomised controlled trials). Meta-analyses were included 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 the 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 be 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 separately 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 included, except studies of genetic polymorphisms for coffee metabolism. We included any study with comparisons of coffee exposure, including high versus low, any versus none, and any linear or non-linear dose-responses. If an article presented separate meta-analyses for more than one health outcome, we included each of these separately.

RP and OJK independently extracted data from eligible articles. From each meta-analysis, they 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. For each eligible article they also extracted study specific exposure categories as defined by authors, risk estimates and corresponding confidence intervals, number of cases and controls (case-control studies), events, participant/person years and length of follow-up (cohort studies) or numbers in intervention and control groups (randomised controlled trials), type of risk used for pooling, and type of effect model used in the meta-analysis (fixed or random). When a meta-analysis considered a dose-response relation and published a P value for non-linearity this was also extracted. Finally, we extracted any estimate of variance between studies (τ 2 ), estimates of the proportion of variance reflecting true differences in effect size (I 2 ), and any presented measure of publication bias. Any difference in extracted data between the two researchers was resolved by consensus.

Assessment of methodological quality of included studies and quality of evidence

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 reviews and meta-analyses of both interventional and observational research. 13 14 AMSTAR includes ratings for quality in the search, analysis, and transparency of a meta-analysis. For the rating item for methodological quality in the analysis, we downgraded any study that had used a fixed rather than a random effects model for producing a summary estimate. We considered 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. 15 The GRADE approach categorises evidence from systematic reviews and meta-analyses into “high,” “moderate,” “low,” or “very low” quality. 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.

Method of analysis

We reanalysed each meta-analysis using the DerSimonian and Laird random effects model, which takes into account variance between and within studies. 16 We did this through extraction of exposure and outcome data, as published in each meta-analysis article, when these were available in sufficient detail. 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 log scale to maintain symmetry in the analysis and took the exponential to return the result to the original metric. We produced the τ 2 statistic as an estimate of true variation in the summary estimate and the I 2 statistic as an estimate of proportion of variance reflecting true differences in effect size. We also calculated an estimate for publication bias with Egger’s regression test 17 for any reanalyses that included at least 10 studies. A P value <0.1 was considered significant for Egger’s test. We did not reanalyse any of the dose-response meta-analyses because of the scarcity of published estimates for number of cases and controls/participants and estimates for each dose of coffee exposure needed for a dose-response analysis. When we were interested in the apparent effect modification by sex, we conducted a test of interaction using the method published by Altman and Bland. 18

We constructed forest plots from the extracted and/or reanalysed data to display three categories of exposure for any health outcome (high versus low (or none), any (regular) versus none, and one extra cup a day (relative to none) in which that category of exposure was available. Each article presented a meta-analysis with one or more of these exposure categories or calculated combined estimates for a range of cups a 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. We used a final tier of highest AMSTAR score if two studies published in the same period had the same number of cohort studies. When a meta-analysis included both cohort and case-control studies and when subgroup analysis was published by study design, we selected the cohort design subanalysis for inclusion in the summary forest plots or reanalysed when possible. This was deemed to represent the higher form of evidence as it was not affected by recall and selection bias and was less likely to be biased by reverse causality that can affect case-control studies. When linear dose-response analyses presented results for two or three extra cups a day we converted this to one extra cup a day by taking the square or cube root respectively (A Crippa, personal communication, 2017). We included heterogeneity, represented by the τ 2 statistic, and publication bias, represented by Egger’s test. When we could not reanalyse data from a meta-analysis we included summary data as extracted from the meta-analysis article and whichever measure of heterogeneity or publication bias, if any, was available.

Patient involvement

This study was informed by feedback from a patient and public involvement focus group and from an independent survey of patients with chronic liver disease in secondary care. This preliminary work showed enthusiasm from patients in participating in a randomised controlled trial involving coffee as an intervention and in finding out more information about the wider benefits and potential harms of increasing coffee intake. Furthermore, the results of this umbrella review were also disseminated during a recent focus group session that had been arranged to gather opinions regarding the acceptability of qualitative research to investigate patterns of coffee drinking in people with non-alcoholic fatty liver disease.

Figure 1 ​ 1 shows the results of the systematic search and selection of eligible studies. The search yielded 201 meta-analyses of observational research in 135 articles with 67 unique outcomes and 17 meta-analyses of randomised-controlled trials in six articles with nine unique outcomes. The median number of meta-analyses per outcome for observational research was two (interquartile range 1-4, range 1-11). Twenty two outcomes had only a single meta-analysis. For meta-analyses of randomised controlled trials, outcomes were limited to systolic and diastolic blood pressure, total cholesterol, low density lipoprotein (LDL) cholesterol, high density lipoprotein (HDL) cholesterol, triglyceride, and three outcomes related to pregnancy: preterm birth, small for gestational age, and birth weight. Figures 2-4 ​ 2-4 show summary data for the meta-analyses selected as the highest form of evidence for coffee consumption and each outcome for high versus low (or none) or any (regular) versus no consumption and one extra cup a day coffee consumption. These show risk estimates for each outcome from 10 most harmful associations to the 10 most beneficial associations. Full versions of the forest plots are available in appendix 1. Figure 5 ​ 5 shows the associations with consumption of decaffeinated coffee across the three exposure categories, and figures 6-9 ​ 6-9 show interventional exposures for coffee versus control for outcomes of blood pressure, lipids, and outcomes related to pregnancy. Risk estimates across different exposure categories for each outcome, grouped by body system, are available in figures A-I in appendix 2.

Fig 1  Flowchart of selection of studies for inclusion in umbrella review on coffee consumption and health

Fig 2  High versus low coffee consumption and associations with multiple health outcomes. Estimates are relative risks and effect models are random unless noted otherwise. For type 2 diabetes, P value was significant for non-linearity. No of events/total for leukaemia could not be split from other outcomes. All estimates were from our own reanalysis apart from preterm birth in first and third trimester and leukaemia

Fig 3  Any versus no coffee consumption and associations with multiple health outcomes. Estimates are relative risks and effect models are random unless noted otherwise. All estimates were from our own reanalysis apart from acute leukaemia, urinary tract cancer, and colorectal cancer

Fig 4  Consumption of one extra cup of coffee a day and associations with multiple health outcomes. Estimates are relative risks and effect models are random unless noted otherwise. No dose response analyses were re-analysed

Fig 5  Consumption of decaffeinated coffee and associations with multiple health outcomes. Estimates are relative risks and effect models are random unless noted otherwise

Fig 6  Coffee consumption in randomised controlled trials 35 and change (mean difference) in blood pressure in random effects model. Estimates are from our own analysis

Fig 7  Coffee consumption in randomised controlled trials 36 and change (mean difference) in cholesterol concentration. Effects are random unless noted otherwise

Fig 8  Coffee consumption in randomised controlled trials 86 and effects (relative risk) on birth outcomes

Fig 9  Coffee consumption in randomised controlled trials 86 and change (mean difference) in birth weight

The most commonly studied exposure was high versus low (or no) coffee consumption, and significance was reached for beneficial associations with 19 health outcomes and harmful associations with six. The 34 remaining outcomes were either negatively or positively associated but without reaching significance. Similarly, in comparisons of any (regular) with no consumption, significance was reached for beneficial associations with 11 outcomes and harmful associations with three. Finally, for one extra cup a day, significance was reached for beneficial associations with 11 outcomes and harmful associations with three. Eight out of 18 studies 19 20 21 22 23 24 25 26 27 that tested for non-linearity for the association with one extra cup a day found significant evidence for this.

All cause mortality

In the most recent meta-analysis, by Grosso and colleagues, the highest exposure category (seven cups a day) of a non-linear dose-response analysis was associated with a 10% lower risk of all cause mortality (relative risk 0.90, 95% confidence interval 0.85 to 0.96), 28 but summary estimates indicated that the largest reduction in relative risk was associated with the consumption of three cups a day (0.83, 0.83 to 0.88) compared with no consumption. Stratification by sex produced similar results. In a separate article, and despite a significant test for non-linearity (P<0.001), authors performed a linear dose-response analysis and found consumption of one extra cup a day was associated with a 4% lower risk of all cause mortality (0.96, 0.94 to 0.97). 27 The apparently beneficial association between coffee and all cause mortality was consistent across all earlier meta-analyses. High versus low intake of decaffeinated coffee was also associated with lower all cause mortality, with summary estimates indicating largest benefit at three cups a day (0.83, 0.85 to 0.89) 28 in a non-linear dose-response analysis.

Cardiovascular disease

Coffee consumption was consistently associated with a lower risk of mortality from all causes of cardiovascular disease, coronary heart disease, and stroke in a non-linear relation, with summary estimates indicating largest reduction in relative risk at three cups a day. 28 Compared with non-drinkers, risks were reduced by 19% (relative risk 0.81, 95% confidence interval 0.72 to 0.90) for mortality from cardiovascular disease, 16% (0.84, 0.71 to 0.99) for mortality from coronary heart disease, and 30% (0.70, 0.80 to 0.90) for mortality from stroke, at this level of intake. Increasing consumption to above three cups a day was not associated with harm, but the beneficial effect was less pronounced, and the estimates did not reach significance at the highest intakes. In stratification by sex within the same article, women seemed to benefit more than men at higher levels of consumption for outcomes of mortality from cardiovascular disease and coronary heart disease but less so from stroke. 28 In a separate meta-analysis, that did not test for non-linearity, an exposure of one extra cup a day was associated with a 2% reduced risk of cardiovascular mortality (0.98, 0.95 to 1.00). 29 There was also evidence of benefit in relation to high versus low coffee consumption after myocardial infarction and lower risk of mortality (hazard ratio 0.55, 95% confidence interval 0.45 to 0.67). 30

Coffee consumption was non-linearly associated with a lower risk of incident cardiovascular disease (relative risk 0.85, 95% confidence interval 0.80 to 0.90), coronary heart disease (0.90, 0.84 to 0.97), and stroke (0.80, 0.75 to 0.86), with these summary estimates indicating the largest benefits at consumptions of three to five cups a day. 19 There was no apparent modification of this association by sex. Risk was also lower for the comparison of high versus low consumption but did not reach significance. Any versus no consumption was also associated with a beneficial effect on stroke (0.89, 0.81 to 0.97). 31 High versus low coffee and one extra cup a day were both associated with a lower risk of atrial fibrillation but neither reached significance. 32 There was no significant association between consumption and risk of venous thromboembolism. 33 There was a non-linear association between consumption and heart failure, with summary estimates indicating the largest benefit at four cups a day (0.89, 0.81 to 0.99), 24 with a slightly higher risk of heart failure at consumption of 10 or more cups a day (1.01, 0.90 to 1.14), though this did not reach significance. 24 For hypertension, there were no significant estimates of risk at any level of consumption in a non-linear dose-response analysis 34 nor in comparisons of any versus none. 35 There was no clear benefit in comparisons of high with low decaffeinated consumption and cardiovascular disease. 19

In a meta-analysis of randomised controlled trials, coffee consumption had a marginally beneficial association with blood pressure when compared with control but failed to reach significance. 35 Consumption does, however, seem consistently associated with unfavourable changes to the lipid profile, with mean differences in total cholesterol (0.19 mmol/L, 95% confidence interval 0.10 mmol/L to 0.28 mmol/L), 36 low density lipoprotein cholesterol (0.14 mmol/L, 0.04 mmol/L to 0.25 mmol/L), 36 and triglyceride (0.14 mmol/L, 0.04 mmol/L to 0.24 mmol/L) 36 higher in the coffee intervention arms than the control arms (1 mmol/L cholesterol = 38.6 mg/dL, 1 mmol/L triglyceride = 88.5 mg/dL 37 ). Consumption was associated with lower high density cholesterol (−0.002 mmol/L, −0.02 mmol/L to 0.54 mol/L), but this did not reach significance. The increases in cholesterol concentration were mitigated with filtered coffee, with a marginal rise in concentration (mean difference 0.09 mmol/L, 0.02 to 0.17) 36 and no significant changes to low density lipoprotein cholesterol or triglycerides compared with unfiltered (boiled) coffee. Similarly, decaffeinated coffee seemed to have negligible effect on the lipid profile. 36

A meta-analysis of 40 cohort studies showed a lower incidence of cancer for high versus low coffee consumption (relative risk 0.82, 95% confidence interval 0.74 to 0.89), 38 any versus no consumption (0.87, 0.82 to 0.92), 38 and one extra cup a day (0.97, 0.96 to 0.98). 38 In a separate article, in non-smokers there was a 2% lower risk of mortality from cancer for exposure of one extra cup a day (0.98, 0.96 to 1.00). 28 For smokers, the article provided results only from a non-linear analysis, and the risk of mortality from cancer increased at all levels of coffee exposure, reaching significance above four cups a day.

High versus low coffee consumption was associated with a lower risk of prostate cancer, 39 endometrial cancer, 40 melanoma, 41 oral cancer, 39 leukaemia, 38 non-melanoma skin cancer, 42 and liver cancer. 43 For prostate, 44 endometrial, 39 melanoma, 45 and liver cancer 43 there were also significant linear dose-response relations indicating benefit.

There were consistent harmful associations for coffee consumption with lung cancer for high versus low consumption (odds ratio 1.59, 95% confidence interval 1.26 to 2.00), 46 any versus none (relative risk 1.28, 1.12 to 1.47), 47 and one extra cup a day (1.04, 1.03 to 1.05). 47 The effect was diminished, however, in studies that adjusted for smoking, and the association was not seen in never smokers. In the most recent meta-analysis, any versus no consumption in people who had never smoked was associated with an 8% lower risk of lung cancer (0.92, 0.75 to 1.10), 47 and in studies that adjusted for smoking the risk estimate was reduced (1.03, 0.95 to 1.12) 47 compared with the overall analysis, and neither reached significance. In contrast, a meta-analysis of two studies showed that high versus low consumption of decaffeinated coffee was associated with a lower risk of lung cancer. 48

A single meta-analysis found an association between any versus no coffee consumption and higher risk of any urinary tract cancer (odds ratio 1.18, 95% confidence interval 1.01 to 1.38). 49 In other meta-analyses of cohort studies of bladder cancer and renal cancer separately, however, associations did not reach significance. 39

No significant association was found between coffee consumption and gastric, 39 50 51 colorectal, 20 39 52 colon, 20 52 rectal, 20 52 ovarian, 39 53 thyroid, 54 55 breast, 38 39 56 pancreatic, 57 oesophageal, 39 58 or laryngeal cancers 59 and lymphoma 39 60 or glioma. 61

Liver and gastrointestinal outcomes

In addition to beneficial associations with liver cancer, all categories of coffee exposure were associated with lower risk for a range of liver outcomes. Any versus no coffee consumption was associated with a 29% lower risk of non-alcoholic fatty liver disease (relative risk 0.71, 0.60 to 0.85), 62 a 27% lower risk for liver fibrosis (odds ratio 0.73, 0.56 to 0.94), 63 and a 39% lower risk for liver cirrhosis (0.61, 0.45 to 0.84). 63 Coffee consumption was also associated with a lower risk of cirrhosis with high versus low consumption (0.69, 0.44 to 1.07) 63 and one extra cup a day (relative risk 0.83, 0.78 to 0.88). 9 Exposure to one extra cup a day was also significantly associated with a lower risk of mortality from cirrhosis (0.74, 0.59 to 0.86). 9 In a single article, 43 for meta-analyses of consumption and chronic liver disease, high versus low (0.35, 0.22 to 0.56), any versus none (0.62, 0.47 to 0.82), and one extra cup a day (0.74, 0.65 to 0.83) were all associated with benefit.

Coffee consumption was also consistently associated with significantly lower risk of gallstone disease. 25 A non-linear dose response was also apparent, though risk sequentially reduced as consumption increased from two to six cups a day. 25 High versus low consumption was associated with a marginally higher risk of gastro-oesophageal reflux disease, but this did not reach significance. 64

Metabolic disease

Coffee consumption was consistently associated with a lower risk of type 2 diabetes for high versus low consumption (relative risk 0.70, 95% confidence interval 0.65 to 0.75) 21 and one extra cup a day (0.94, 0.93 to 0.95). 65 There was some evidence for a non-linear dose-response, but the risk was still lower for each dose of increased consumption between one and six cups. 21 Consumption of decaffeinated coffee also seemed to have similar associations of comparable magnitude. 21 For metabolic syndrome high versus low coffee consumption was associated with 9% lower risk (0.91, 0.86 to 0.95). 26 High versus low consumption was also significantly associated with a lower risk of renal stones 66 and gout. 67

Renal outcomes

Coffee consumption of any versus none was associated with a lower risk of urinary incontinence 68 and chronic kidney disease, 69 but neither association reached significance, and the meta-analyses included cross sectional studies.

Musculoskeletal outcomes

There is inconsistency in the association between coffee consumption and musculoskeletal outcomes. There were no significant overall associations between high versus low consumption or one extra cup a day coffee and risk of fracture 70 71 or hip fracture. 72 73 In subgroup analysis by sex, however, high versus low consumption was associated with an increased risk of fracture in women (relative risk 1.14, 95% confidence interval 1.05 to 1.24) and a decreased risk in men (0.76, 0.62 to 0.94) 70 (test of interaction (ratio of relative risks (women:men) 1.50, 1.20 to 1.88; P<0.001). There was a non-significant association between high versus low consumption and risk of hip fracture in a subgroup analysis of women (relative risk 1.27, 0.94 to 1.72) 72 but not men (0.53, 0.38 to 1.00) 72 (test of interaction 2.40, 1.35 to 4.24; P<0.01). For consumption of one extra cup a day there was also an association with increased risk of fracture in women (relative risk 1.05, 1.02 to 1.07) 71 but a lower risk in men (0.91, 0.87 to 0.95) 71 (test of interaction 1.15, 1.10 to 1.21; P<0.001). These results suggest that sex might be a significant effect modifier in the association between coffee and risk of fracture. Associations were also found for total and decaffeinated coffee consumption and higher risk of rheumatoid arthritis, 74 75 but neither reached significance.

Neurological outcomes

Coffee consumption was consistently associated with a lower risk of Parkinson’s disease, even after adjustment for smoking, and across all categories of exposure. 22 76 77 Decaffeinated coffee was associated with a lower risk of Parkinson’s disease, which did not reach significance. 22 Consumption had a consistent association with lower risk of depression 78 79 and cognitive disorders, especially for Alzheimer’s disease (relative risk 0.73, 95% confidence interval 0.55 to 0.97) 80 in meta-analyses of cohort studies.

Gynaecological outcomes

Exposures of any versus no coffee consumption were associated with a higher risk of endometriosis but did not reach significance. 81

Antenatal exposure to coffee

There is some consistency in evidence for harmful associations of coffee consumption with different outcomes related to pregnancy. High versus low consumption was associated with a higher risk of low birth weight (odds ratio 1.31, 95% confidence interval 1.03 to 1.67), 82 pregnancy loss (1.46, 1.06 to 1.99), 23 first trimester preterm birth (1.22, 1.00 to 1.49), 83 and second trimester preterm birth (1.12, 1.02 to 1.22). 83 No significant association, however, was found for any category of coffee consumption and third trimester preterm birth, 83 neural tube defects, 84 and congenital malformations of the oral cleft 85 or cardiovascular system. 85 Only one study was included in a Cochrane meta-analysis of randomised controlled trials investigating coffee caffeine consumption on birth weight, preterm birth, and small for gestational age, and none of the outcomes reached significance. 86

There is also consistency in associations between high versus low coffee consumption in pregnancy and a higher risk of childhood leukaemia (odds ratio 1.57, 95% confidence interval 1.16 to 2.11) 87 and any versus no consumption (1.44, 1.07 to 1.92). 88 89

Heterogeneity of included studies

We were able to re-analyse by random effects, 83% of comparisons for high versus low and 79% for any versus none, but none for one extra cup a day. About 40% of the 83 meta-analyses that we re-analysed had significant heterogeneity, and 90% of these had an I 2 >50%. The individual studies within each meta-analysis varied by many factors, including the geography and ethnicity of the population of interest, the type of coffee consumed, the method of ascertainment of coffee consumption, the measure of coffee exposure, duration of follow-up, and outcome assessment. For the 54 that we were unable to re-analyse, 19% had significant heterogeneity, and 27% of meta-analyses did not publish heterogeneity for the studies included in the specific exposure comparison. Only four studies that we were unable to re-analyse used a fixed effects model.

Publication bias of included studies

We performed Egger’s regression test in only 40% of the meta-analyses in our reanalysis because the remaining 60% contained insufficient numbers of studies. In those that we reanalysed, 20% had statistical evidence of publication bias. This included high versus low comparisons for type 2 diabetes (P=0.049), 21 stroke (P=0.09), 19 gastro-oesophageal reflux disease (P=0.04), 64 bladder cancer (P<0.01), 39 endometrial cancer (P=0.03), 40 and hip fracture (P=0.02), 72 and in the meta-analysis of randomised controlled trials for total cholesterol (P<0.01). For meta-analyses that we were unable to reanalyse, none reported significant publication bias or they did not conduct or publish a statistical test for publication bias for the specific exposure comparison. This could have been in part because of low number of studies included in the pooling. It is possible, however, that unmeasured publication bias exists in many of the summary estimates we have presented and not assessed.

AMSTAR and GRADE classification of included studies

The median AMSTAR score achieved across all studies was 5 out of 11 (range 2-9, interquartile range 5-7). Eleven studies were downgraded on method of meta-analysis because they used a fixed, rather than random effects, model. Appendix 3 provides a breakdown of AMSTAR scores for studies representing each outcome. In terms of quality of evidence for each outcome, about 25% were rated as being of “low” and 75% as “very low” quality with the GRADE classification. Even the meta-analyses of randomised controlled trials were graded as low quality of evidence because of risk of bias, inconsistency, or imprecision. Only outcomes identified as having a significant dose-response effect, or large magnitude of effect, without significant other biases reached a GRADE classification of “low” compared with the majority rating of “very low.” Appendix 4 shows a breakdown of GRADE scores for studies representing each outcome.

Principal findings and possible explanations

Coffee consumption is more often associated with benefit than harm for a range of health outcomes across multiple measures of exposure, including high versus low, any versus none, and one extra cup a day. Exposure to coffee has been the subject of numerous meta-analyses on a diverse range of health outcomes. We carried out this umbrella review to bring this existing evidence together and draw conclusions for the overall effects of coffee consumption on health. We identified 201 meta-analyses of observational research with 67 unique outcomes and 17 meta-analyses of randomised controlled trials with nine unique outcomes.

The conclusion of benefit associated with coffee consumption was supported by significant associations with lower risk for the generic outcomes of all cause mortality, 28 cardiovascular mortality, 28 and total cancer. 38 Consumption was associated with a lower risk of specific cancers, including prostate cancer, 39 44 90 endometrial cancer, 39 40 91 melanoma, 41 45 non-melanoma skin cancer, 42 and liver cancer. 43 Consumption also had beneficial associations with metabolic conditions including type 2 diabetes, 21 65 metabolic syndrome, 26 gallstones, 25 gout, 67 and renal stones 66 and for liver conditions including hepatic fibrosis, 63 cirrhosis, 9 63 cirrhosis mortality, 9 and chronic liver disease combined. 43 The beneficial associations between consumption and liver conditions stand out as consistently having the highest magnitude compared with other outcomes across exposure categories. Finally, there seems to be beneficial associations between coffee consumption and Parkinson’s disease, 22 76 77 depression, 78 79 and Alzheimer’s disease. 80

Overall, there is no consistent evidence of harmful associations between coffee consumption and health outcomes, except for those related to pregnancy and for risk of fracture in women. After adjustment for smoking, consumption in pregnancy seems to be associated with harmful outcomes related to low birth weight, 82 preterm birth, 83 and pregnancy loss. 23 These associations were seen in subgroup analyses from articles investigating total caffeine exposure, which showed similar associations, and from a single meta-analysis for each outcome. There were also harmful associations between consumption and congenital malformations, though these did not reach significance. 85 The half life of caffeine is known to double during pregnancy, 92 and therefore the relative dose of caffeine from equivalent per cup consumption will be much higher than consumption outside pregnancy. Caffeine is also known to easily cross the placenta, 93 and activity of the caffeine metabolising enzyme, CYP1A2, is low in the fetus, resulting in prolonged fetal exposure to caffeine. 94 Though we found no significant associations between coffee exposure and neural tube defects, 84 for this outcome, all bar one of the included studies were of case-control design and therefore prone to recall bias. Maternal exposure to coffee had a harmful association with acute leukaemia of childhood, 87 88 89 but evidence for this also came from case-control studies.

The effect of the association between coffee consumption and risk of fracture was modified by sex. While there was no overall significant association with risk, the most recent meta-analyses found a 14% increased risk for high versus low consumption 70 and 0.6% increased risk for one extra cup a day 71 in women. Conversely, in men consumption was beneficially associated with a lower risk of fracture. Caffeine has been proposed as the component of coffee linked to the increased risk in women, with potential influence on calcium absorption 95 and bone mineral density. 96 A recent comprehensive systematic review of the health effects of caffeine, however, concluded, with regard to bone health, that a caffeine intake of 400 mg/day (about four cups of coffee) was not associated with adverse effects on the risk of fracture, falls, bone mineral density, or calcium metabolism. 97 There is limited evidence at higher intakes of caffeine to draw firmer conclusions. Notably, many of the studies included in the meta-analyses of coffee consumption and risk of fracture did not adjust for important confounders such as body mass index (BMI), smoking, or intakes of calcium, vitamin D, and alcohol. Some studies suggest that caffeine consumption is associated only with a lower risk of low bone mineral density in women with inadequate calcium intake, 98 and that only a small amount of milk added to coffee would be needed to offset any negative effects on calcium absorption. 95 The type of coffee consumed might therefore be an important factor. Coffee and caffeine have also been linked to oestrogen metabolism in premenopausal women 99 and increased concentrations of sex hormone binding globulin (SHBG) in observational research of postmenopausal women. 100 The increased globulin concentration was associated with lower concentrations of unbound testosterone but not unbound oestradiol. 100 Low concentrations of oestradiol and high concentrations of sex hormone binding globulin are known to be associated with risk of fracture. 101 102 An effect of coffee consumption on sex hormone binding globulin, however, has not been supported in small scale randomised controlled trials. 103 Coffee has been shown to be beneficially associated with oestrogen receptor negative, but not positive, breast cancer. 56 There is consistent evidence, however, to suggest that coffee consumption is associated with a lower risk of endometrial cancer 40 and no clear evidence for associations with ovarian cancer. 39 53 The effect of coffee consumption on endogenous sex hormones could therefore be beneficial for some hormone dependent cancers but increase the risk of fracture in women with inadequate dietary calcium 98 or with multiple risk factors for osteoporosis. 104

When meta-analyses have suggested associations between coffee consumption and higher risk of other diseases, such as lung cancer, this can largely be explained by inadequate adjustment for smoking. Smoking is known to be positively associated with coffee consumption 105 and with many health outcomes and could act as both a confounder and effect modifier. Galarraga and Boffetta examined the possible confounding by smoking in two ways in their recent meta-analysis 47 of coffee consumption and risk of lung cancer. Firstly, they performed the meta-analysis in those who had never smoked and detected no harmful association. Next, they performed the meta-analysis in only those studies that adjusted for smoking, and the magnitude of the apparent harmful association was reduced and was no longer significant. It is likely that residual confounding by smoking, despite some adjustment, can explain this apparent harmful association. A similar pattern was seen in stratification by smoking for coffee consumption and mortality from cancer in the recent meta-analysis by Grosso and colleagues. 28 The authors highlighted the positive association between coffee consumption and smoking and concluded that residual confounding by smoking was the likely explanation.

For randomised controlled trials, coffee has been given as an intervention for only short durations and limited to a small number of outcomes, including blood pressure, lipid profiles, and one trial in pregnancy. There does seem to be consistent evidence for small increases in concentrations of total cholesterol, low density lipoprotein cholesterol, and triglyceride in meta-analyses of randomised controlled trials, and this is believed to be caused by the action of diterpenes. 106 The method of preparation is an important factor as instant and filtered coffee contain negligible amounts of diterpenes compared with espresso, with even higher amounts in boiled and cafetière coffee. 106 In the meta-analysis we included in our review, the effect of filtered coffee consumption on lipids was negligible or failed to reach significance compared with unfiltered coffee. Studies also suggest, however, that the dose of diterpenes needed to cause hypercholesterolaemia is likely to be much higher than the dose needed for beneficial anticarcinogenic effects. 107 For unfiltered coffee, the clinical relevance of such small increases in total cholesterol, low density lipoprotein cholesterol, and triglyceride due to coffee are difficult to extrapolate, especially as coffee consumption does not seem to be associated with adverse cardiovascular outcomes, including mortality after myocardial infarction. 30 Changes in the lipid profile associated with coffee also reversed with abstinence. 106

When dose-response analyses have been conducted and when these have suggested non-linearity—for example in all cause mortality, cardiovascular disease mortality, cardiovascular disease, and heart failure—summary estimates indicate that the largest relative risk reduction is associated with intakes of three to four cups a day. Importantly, increase in consumption beyond this intake does not seem to be associated with increased risk of harm, rather the magnitude of the benefit is reduced. In type 2 diabetes, despite significant non-linearity, relative risk reduced sequentially from one through to six cups a day. Estimates from higher intakes are likely to include a smaller number of participants, and this could be reflected in the imprecision observed for some outcomes at these levels of consumption.

Coffee contains a complex mixture of bioactive compounds with plausible biological mechanisms for benefiting health. It has been shown to contribute a large proportion of daily intake of dietary antioxidant, greater than tea, fruit, and vegetables. 108 Chlorogenic acid is the most abundant antioxidant in coffee; though it is degraded by roasting, alternative antioxidant organic compounds are formed. 109 Caffeine also has significant antioxidant effects. The diterpenes, cafestol and kahweol, induce enzymes involved in carcinogen detoxification and stimulation of intracellular antioxidant defence, 107 contributing towards an anticarcinogenic effect. These antioxidant and anti-inflammatory effects are also likely to be responsible for the mechanism behind the beneficial associations between coffee consumption and liver fibrosis, cirrhosis, and liver cancer 110 that our umbrella review found had the greatest magnitude of effect compared with other outcomes. Additionally, caffeine could have direct antifibrotic effects by preventing hepatic stellate cell adhesion and activation. 111

Decaffeinated coffee is compositionally similar to caffeinated coffee apart from having little or no caffeine. 112 In our umbrella review we identified 16 unique outcomes for associations with decaffeinated coffee. Decaffeinated coffee was beneficially associated with all cause and cardiovascular mortality in a non-linear dose-response, with summary estimates indicating the largest relative risk reduction at intakes of two to four cups a day and of similar magnitude to caffeinated coffee. Marginal benefit in the association between decaffeinated coffee and cancer mortality did not reach significance. The associations between high versus low consumption of decaffeinated coffee and lower risk of type 2 diabetes 21 and endometrial cancer 40 were of a similar magnitude to total or caffeinated coffee, and there was a small beneficial association between decaffeinated coffee and lung cancer. 48 The other outcomes investigated for decaffeinated coffee showed no significant associations, though it should be noted that meta-analyses of consumption would have much lower power to detect an effect. Importantly, there were no convincing harmful associations between decaffeinated coffee and any health outcome. People who drink decaffeinated coffee might be different from those who drink caffeinated coffee, and most coffee assessment tools do not adequately account for people who might have switched from caffeinated to decaffeinated coffee. 113

Strengths and weaknesses and in relation to other studies

The umbrella review has systematically summarised the current evidence for coffee consumption and all health outcomes for which a previous meta-analysis had been conducted. It used systematic methods that included a robust search strategy of four scientific literature databases with independent study selection and extraction by two investigators. When possible, we repeated each meta-analysis with a standardised approach that included the use of random effects analysis and produced measures of heterogeneity and publication bias to allow better comparison across outcomes. We also used standard approaches to assess quality of methods (AMSTAR) and quality of the evidence (GRADE).

AMSTAR has good evidence of validity and reliability. 13 The AMSTAR score assisted us in identifying the highest quality of evidence for each outcome. It also allows judgment regarding quality of the meta-analysis presented for each outcome. A high AMSTAR score for a meta-analysis, however, does not equate to high quality of the original studies, and the assessment and use of quality scoring of the original studies accounts for only two of 11 possible AMSTAR points. Additionally, appropriate method of analysis, accounting for one score of quality, can be subjective. We downgraded any meta-analysis that used a fixed effects model irrespective of heterogeneity for reasons discussed previously. The AMSTAR system, however, allows only a 1 point loss for a poor analysis technique and would not capture multiple issues within an individual meta-analysis.

One recurring issue for many of the included meta-analyses was the assumption that summary relative risk could be pooled from a combination of odds ratio, relative rates, and hazard ratios so that they could combine studies with differing measures. Statistically, the odds ratio is similar to the relative risk when the outcome is uncommon 114 but will always be more extreme. 114 Similarly, for rare events, relative rates and hazard ratios are similar to the relative risk when censoring is uncommon or evenly distributed between exposed and unexposed groups. 114 Many meta-analyses stated their assumption but included insufficient information to allow us to judge the suitability of the pooling. Notably, only one meta-analysis produced a summary statistic with hazard ratios. 53 We did not downgrade the AMSTAR score when this assumption had been made, and we did not downgrade meta-analyses for failing to consider uncertainty in variance estimates as this was universally unstated. 115 Furthermore, the computation of dose-response meta-analyses should use methods that account for lack of independence in comparisons (same unexposed group), such as those proposed by Greenland and Longnecker. 116 Reassuringly, most dose-response meta-analyses we included in our summary tables cited this method.

Most of the studies we included were meta-analyses of observational studies. One strength of the umbrella review was the inclusion only of cohort studies, or subgroup analyses of cohort studies when available, in preference to summary estimates from a combination of study designs. In meta-analyses that we were unable to re-analyse and when subgroup analysis did not allow the disentanglement of study design, the presented results were from the combined estimates of all included studies. Observational research, however, is low quality in the hierarchy of evidence and with GRADE classification most outcomes are recognised as having very low or low quality of evidence where a dose-response relation exists. Large effect sizes of >2 or <0.5 can permit observational evidence to be upgraded in GRADE, and only the association between high versus low coffee consumption and both liver cancer 43 and chronic liver disease 43 reached this magnitude. In fact, associations between coffee consumption and liver outcomes consistently had larger effect sizes than other outcomes across exposure categories. Our reanalysis did not change our GRADE classification for any outcome.

A possible limitation of our review was that we did not reanalyse any of the dose-response meta-analyses as the data needed to compute these were not generally available in the articles. We did not review the primary studies included in each of the meta-analyses that would have facilitated this. We decided that reanalysing the dose-response data was unlikely to result in changes to the GRADE classification. In our reanalysis of the comparison of high versus low and any versus no coffee, we used data available in the published meta-analyses and therefore assumed the exposure and estimate data for component studies had been published accurately.

We were able to produce estimates for publication bias using Egger’s test for meta-analyses containing 10 or more studies. 17 Egger’s test is not recommended with fewer studies. We were unable to conduct alternative tests, such as Peters’ test, 117 which is more appropriate for binary outcomes, because this needed cases and non-cases for each level of exposure and this detail was largely unavailable in the meta-analyses. We did not calculate excess significance tests, which attempt to detect reporting bias by comparing the number of studies that have formally significant results with the number expected, based on the sum of the statistical powers from individual studies, and using an effect size equal to the largest study in the meta-analysis. 118 Excess significance tests, however, have not been fully evaluated and are not therefore currently recommended as an alternative to traditional tests of publication bias. 119 Further bias in methods could have occurred if the same meta-analysis authors conducted multiple meta-analyses for different health outcomes. There was also an overlap of health outcomes with data from the same original cohort studies. While the associations for different health outcomes were statistically independent, any methodological issues in design or conduct of the original cohorts could represent repeated bias filtering through the totality of evidence.

The beneficial association between coffee consumption and all cause mortality highlighted in our umbrella review is in agreement with two recently published cohort studies. The first was a large cohort study of 521 330 participants followed for a mean period of 16 years in 10 European countries, during which time there were 41 693 deaths. 120 The highest quarter of coffee consumption, when compared with no coffee consumption, was associated with a 12% lower risk of all cause mortality in men (hazard ratio 0.88, 95% confidence interval 0.82 to 0.95) and a 7% lower risk in women (0.93, 0.82 to 0.95). Coffee was also beneficially associated with a range of cause specific mortality, including mortality from digestive tract disease in men and women and from circulatory and cerebrovascular disease in women. The study was able to adjust for a large number of potential confounding factors, including education, lifestyle (smoking, alcohol, physical activity), dietary factors, and BMI. Importantly, the study found no harmful associations between coffee consumption and mortality, apart from the highest quarter versus no coffee consumption and increased risk of mortality from ovarian cancer (1.31, 1.07 to 1.61). No prevailing hypothesis was cited. In our umbrella review, high versus low coffee consumption was associated with an 8% increased risk and one extra cup a day with a 2% increased risk of incident ovarian cancer, but neither reached significance.

In the second study, a North American cohort of 185 855 participants was followed for a mean duration of 16 years, during which 58 397 participants died. 121 After adjustment for smoking and other factors, consumption of four or more cups of coffee a day was associated with an 18% lower risk of mortality (hazard ratio 0.82, 95% confidence interval 0.78 to 0.87). The findings were consistent across subgroups stratified by ethnicity that included African Americans, Japanese Americans, Latino, and white populations. Associations were also similar in men and women. Mortality from heart disease, cancer, chronic lower respiratory disease, stroke, diabetes, and kidney disease was also beneficially associated with coffee consumption. Importantly, no harmful associations were identified. Subtypes of cancer mortality, however, were not published.

Many of the associations between coffee consumption and health outcomes, which are largely from cohort studies, could be affected by residual confounding. Smoking, age, BMI, and alcohol consumption are all associated with coffee consumption and a considerable number of health outcomes. These relations might differ in magnitude and even direction between populations. Residual confounding by smoking could reduce a beneficial association or increase a harmful association when smoking is also associated with an outcome. Coffee could also be a surrogate marker for factors that are associated with beneficial health such as higher income, education, or lower deprivation, which could be confounding the observed beneficial associations. The design of randomised controlled trials can reduce the risk of confounding because the known and unknown confounders are distributed randomly between intervention and control groups. Mendelian randomisation studies can also help to reduce the effects of confounding from random distribution of confounders between genotypes of known function related to the outcome of interest. The association between coffee consumption and lower risk of type 2 diabetes 122 and all cause and cardiovascular mortality 123 was found to have no genetic evidence for a causal relation in Mendelian randomisation studies, suggesting residual confounding could result in the observed associations in other studies. The authors point out, however, that the Mendelian randomisation approach relies on the assumption of linearity between all categories of coffee intake and might not capture non-linear differences. The same genetic variability in coffee and caffeine metabolism could influence the magnitude, frequency, and duration of exposure to caffeine and other coffee bioactive compounds. Palatini and colleagues found that the risk of hypertension associated with coffee varied depending on the CYP1A2 genotype. 124 Those with alleles for slow caffeine metabolism were at increased risk of hypertension compared with those with alleles for fast caffeine metabolism.

Bias from reverse causality can also occur in observational studies. In case-control studies, symptoms from disease might have led people to reduce their intake of coffee. When possible, we included meta-analyses of cohort studies or cohort subgroup analyses in our review as they are less prone to this type of bias. Even prospective cohort studies, however, can be affected by reverse causality bias, in which participants who were apparently healthy at recruitment might have reduced their coffee intake because of early symptoms of a disease.

Most meta-analyses produced summary effects from individual studies that measured coffee exposure by number of cups a day. Some individual studies, however, used number of times a day, servings a day, millilitres a day, cups a week, times a week, cups a month, and drinkers versus non-drinkers to measure coffee consumption. There is no universally recognised standard coffee cup size, and the bioactive components of coffee in a single cup will vary depending on the type of bean (such as Arabica or Robusta), degree of roasting, and method of preparation, including the quantity of bean, grind setting, and brew type used. Therefore, studies that are comparing coffee consumption by cup measures could be comparing ranges of exposures. The range of number of cups a day classified as both high and low consumption from different individual studies varied substantially for inclusion in each meta-analysis. High versus low consumption was the most commonly used measure of exposure. Consistent results across meta-analyses and categories of exposure, however, suggest that measurement of cups a day produces a reasonable differential in exposure. Additionally, any misclassification in exposure is likely to be non-differential and would more likely dilute any risk estimate rather than strengthen it, pushing it towards the null.

The inclusion criteria for the umbrella review meant that some systematic reviews were omitted when they did not do any pooled analysis. Meta-analyses in relation to coffee consumption, however, have been done on most health outcomes for which there is also a systematic review, except for respiratory outcomes 125 and sleep disturbance. 126 There could also be important well conducted studies that have assessed coffee consumption in relation to outcomes for which no investigators have attempted to perform any combined review, whether pooling the estimate or not. Additionally, the umbrella review has investigated defined health outcomes rather than physiological outcomes. This means there could be physiological effects of coffee such as increased heart rate, stimulation of the central nervous system, and feelings of anxiety that have not been captured in this review and must be considered should individuals be taking drugs that have similar physiological effects or in those trying to avert anxiety.

Despite our broad inclusion criteria, we identified only one meta-analysis that focused on a population of people with established disease. This was a meta-analysis of two small cohort studies investigating risk of mortality in people who had experienced a myocardial infarction. 30 In contrast, most meta-analyses estimated the association between coffee consumption and outcomes in general population cohorts rather than those selected by pre-existing disease. Our summation of the existing body of evidence should therefore be viewed in this context and suggests that the association of coffee consumption in modifying the natural history of established disease remains unclear.

We extracted details of conflicts of interest and funding declarations from articles selected in the umbrella review. Only one article declared support from an organisation linked to the coffee industry, and a second article stated that their authors contributed to the same organisation. Neither of these articles was selected to represent the respective outcome in the summary figures, and all references for studies not included in the summary tables are available on request. We did not review the primary studies included in each meta-analysis and cannot comment on whether any of these studies were funded by organisations linked to the coffee industry.

Conclusions and recommendations

Coffee consumption has been investigated for associations with a diverse range of health outcomes. This umbrella review has systematically assimilated this vast amount of existing evidence where it has been published in a meta-analysis. Most of this evidence comes from observational research that provides only low or very low quality evidence. Beneficial associations between coffee consumption and liver outcomes (fibrosis, cirrhosis, chronic liver disease, and liver cancer) have relatively large and consistent effect sizes compared with other outcomes. Consumption is also beneficially associated with a range of other health outcomes and importantly does not seem to have definitive harmful associations with any outcomes outside of pregnancy. The association between consumption and risk of fracture in women remains uncertain but warrants further investigation. Residual confounding could explain some of the observed associations, and Mendelian randomisation studies could be applied to a range of outcomes, including risk of fracture, to help examine this issue. Randomised controlled trials that change long term behaviour, and with valid proxies of outcomes important to patients, could offer more definitive conclusions and could be especially useful in relation to coffee consumption and chronic liver disease. Reassuringly, our analysis indicates that future randomised controlled trials in which the intervention is increasing coffee consumption, within usual levels of intake, possibly optimised at three to four cups a day, would be unlikely to result in significant harm to participants. Pregnancy, or risk of pregnancy, and women with higher a risk of fracture, however, would be justified exclusion criteria for participation in a coffee treatment study.

What is already known on this topic

• Coffee is highly consumed worldwide and could have positive health benefits, especially in chronic liver disease
• Beneficial or harmful associations of drinking coffee seem to vary between health outcomes of interest
• Understanding associations of coffee and health is important, especially in relation to exploring harmful associations, before interventional research is conducted

What this study adds

• Coffee drinking seems safe within usual patterns of consumption, except during pregnancy and in women at increased risk of fracture
• Existing evidence is observational and of lower quality, and randomised controlled trials are needed
• A future randomised controlled trial in which the intervention is increasing coffee consumption would be unlikely to result in significant harm to participants

Web Extra. 

Extra material supplied by the author

Appendix 1: Full versions of forest plots

Appendix 2: Coffee consumption and outcome groups

Appendix 3: AMSTAR scores for individual studies

Appendix 4: GRADE classification of quality of evidence

Contributors: RP conceptualised the umbrella review, conducted the search, study selection, data extraction, and drafted and revised the paper. OJK conceptualised the umbrella review, conducted the study selection and data extraction, and revised the draft paper. JP conceptualised the umbrella review and revised the draft paper. JAF revised the draft paper. PCH revised the draft paper. PR conceptualised the umbrella review, arbitrated the study selection, and revised the draft paper. All authors reviewed and approved the final version of the manuscript. RP is guarantor.

Funding: This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors; the authors remain independent of any funding influence.

Competing interests: All authors have completed the ICMJE uniform disclosure form at www.icmje.org/coi_disclosure.pdf and declare: no support from any organisation for the submitted work; JAF reports research grants from GlaxoSmithKline and from Intercept Pharmaceuticals, and personal fees from Novartis and from Merck, outside the submitted work; PCH reports personal fees from MSD, personal fees from Gilead, personal fees from Abbvie, personal fees from Jannsen, personal fees from BMS, personal fees from Pfizer, grants and personal fees from Roche, personal fees from Novartis, outside the submitted work; no other relationships or activities that could appear to have influenced the submitted work.

Ethical approval: Not required.

Data sharing: References for studies included in the umbrella review but not selected to represent the outcome in the summary figures are available on request.

Transparency: The lead author affirms that the manuscript is an honest, accurate, and transparent account of the study being reported; that no important aspects of the study have been omitted; and that any discrepancies from the study as planned have been explained.

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Coffee consumption, health benefits and side effects: a narrative review and update for dietitians and nutritionists

Affiliations.

• 1 Dipartimento di Scienze Umanistiche, Università Telematica Pegaso, Via Porzio, Centro Direzionale, isola F2, 80143 Napoli, Italy.
• 2 Centro Italiano per la cura e il Benessere del paziente con Obesità (C.I.B.O), Endocrinology Unit, Department of Clinical Medicine and Surgery, University Medical School of Naples, Via Sergio Pansini 5, 80131 Naples, Italy.
• 3 Dipartimento di Medicina Clinica e Chirurgia, Unit of Endocrinology, Federico II University Medical School of Naples, Via Sergio Pansini 5, 80131 Naples, Italy.
• 4 School of Medicine, Universidad Católica Santiago de Guayaquil, Guayaquil, Ecuador.
• 5 Department of Nutrition and Dietetics, Faculty of Health Sciences, Beirut Arab University, P.O. Box 11-5020 Riad El Solh, Beirut 11072809, Lebanon.
• 6 Universidad de Buenos Aires, Facultad de Medicina, Departamento de Bioquímica Humana, Buenos Aires, Argentina.
• 7 Hospital Británico de Buenos Aires, Departamento de Terapia Intensiva, Buenos Aires, Argentina.
• 8 Intensive Care Unit, Sanatorio Franchín, Bartolomé Mitre 3565, Ciudad Autonoma de Buenos Aires, Argentina.
• 9 Cattedra Unesco "Educazione alla salute e allo sviluppo sostenibile", University Federico II, Naples, Italy.
• PMID: 34455881
• DOI: 10.1080/10408398.2021.1963207

Coffee is one of the most popular beverages worldwide; however, its impact on health outcomes and adverse effects is not fully understood. The current review aims to establish an update about the benefits of coffee consumption on health outcomes highlighting its side effects, and finally coming up with an attempt to provide some recommendations on its doses. A literature review using the PubMed/Medline database was carried out and the data were summarized by applying a narrative approach using the available evidence based on the literature. The main findings were the following: first, coffee may contribute to the prevention of inflammatory and oxidative stress-related diseases, such as obesity, metabolic syndrome and type 2 diabetes; second, coffee consumption seems to be associated with a lower incidence of several types of cancer and with a reduction in the risk of all-cause mortality; finally, the consumption of up to 400 mg/day (1-4 cups per day) of caffeine is safe. However, the time gap between coffee consumption and some drugs should be taken into account in order to avoid interaction. However, most of the data were based on cross-sectional or/and observational studies highlighting an association of coffee intake and health outcomes; thus, randomized controlled studies are needed in order to identify a causality link.

Keywords: Coffee; caffeine; metabolic syndrome; nutritionist; obesity.

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• Published: 20 April 2021

Habitual coffee drinkers display a distinct pattern of brain functional connectivity

• Ricardo Magalhães 1 , 2 , 3 , 4   na1 ,
• Maria Picó-Pérez   ORCID: orcid.org/0000-0002-1573-2445 1 , 2 , 3   na1 ,
• Madalena Esteves 1 , 2 , 3   na1 ,
• Rita Vieira   ORCID: orcid.org/0000-0001-6762-406X 1 , 2 , 3 ,
• Teresa C. Castanho 1 , 2 , 3 ,
• Liliana Amorim 1 , 2 , 3 ,
• Mafalda Sousa 1 , 2 , 3 ,
• Ana Coelho 1 , 2 , 3 ,
• Henrique M. Fernandes 5 ,
• Joana Cabral   ORCID: orcid.org/0000-0002-6715-0826 1 , 2 , 3 , 5 ,
• Pedro S. Moreira 1 , 2 , 3 , 6 &
• Nuno Sousa   ORCID: orcid.org/0000-0002-8755-5126 1 , 2 , 3 , 7  

Molecular Psychiatry volume  26 ,  pages 6589–6598 ( 2021 ) Cite this article

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Coffee is the most widely consumed source of caffeine worldwide, partly due to the psychoactive effects of this methylxanthine. Interestingly, the effects of its chronic consumption on the brain’s intrinsic functional networks are still largely unknown. This study provides the first extended characterization of the effects of chronic coffee consumption on human brain networks. Subjects were recruited and divided into two groups: habitual coffee drinkers (CD) and non-coffee drinkers (NCD). Resting-state functional magnetic resonance imaging (fMRI) was acquired in these volunteers who were also assessed regarding stress, anxiety, and depression scores. In the neuroimaging evaluation, the CD group showed decreased functional connectivity in the somatosensory and limbic networks during resting state as assessed with independent component analysis. The CD group also showed decreased functional connectivity in a network comprising subcortical and posterior brain regions associated with somatosensory, motor, and emotional processing as assessed with network-based statistics; moreover, CD displayed longer lifetime of a functional network involving subcortical regions, the visual network and the cerebellum. Importantly, all these differences were dependent on the frequency of caffeine consumption, and were reproduced after NCD drank coffee. CD showed higher stress levels than NCD, and although no other group effects were observed in this psychological assessment, increased frequency of caffeine consumption was also associated with increased anxiety in males. In conclusion, higher consumption of coffee and caffeinated products has an impact in brain functional connectivity at rest with implications in emotionality, alertness, and readiness to action.

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Introduction.

Coffee is the most widely consumed beverage, with particular interest for human health in view of its short-term effects on attention, sleep, and memory and its long-term impact on the appearance of different diseases and on healthy span of ageing [ 1 , 2 ]. Coffee has several constituents able to impact on human health, amongst which stems caffeine, which is the most widely consumed psychostimulant in the world [ 3 ]. Despite its widespread use it is surprising to note that a thorough characterization of the chronic effects of coffee upon the human brain is still lacking. In the present work we aim to begin addressing that issue.

In the brain, caffeine acts as an antagonist of adenosine A1 and A2A receptors, leading to hyperexcitability of the central nervous system [ 3 , 4 ]. This induces acute effects in diverse domains, such as physical endurance [ 1 , 5 ], vigilance, dexterity [ 6 ], mood [ 7 , 8 ], memory [ 9 ], and cognitive function [ 1 , 8 , 10 ]. There is also evidence that coffee/caffeine intake can normalize anxiety [ 11 ], although higher doses of caffeine may be anxiogenic [ 1 , 12 ] by disrupting the HPA axis [ 13 ]. On the other hand, epidemiological and animal studies converge in concluding that coffee, caffeine and adenosine receptor antagonists attenuate the burden of neurodegenerative disorders such as Alzheimer’s [ 14 ], or psychiatric disorders such as depression [ 15 ]. Indeed, chronic antagonism of either A1 or A2 receptors seems to induce an upregulation of the former, but not the latter. The resulting altered receptor ratio may explain the shift from the acute psychomotor effects (e.g., attention, vigilance) to the longer-term actions of coffee (e.g., stress resistance, neuroprotection) effects [ 4 , 16 ].

Functional magnetic resonance imaging (fMRI) allows studying, in a noninvasive way, the function of the human brain during execution of different tasks or at rest [ 17 ]. So far, most studies using fMRI were focused on measuring the acute effects of caffeine intake in the brain. Briefly, they have reported caffeine-related increases in blood oxygenation-dependent-level (BOLD) signal in different cortical and subcortical areas during a visuomotor task [ 18 ]; an impact in working memory and perfusion in elderly subjects [ 19 , 20 ]; an increase in BOLD activation in the frontopolar and cingulate cortex during a 2-back verbal working memory task [ 21 , 22 ]; and a global caffeine-induced increase in brain entropy, possibly representing an increased processing capacity [ 23 ]. Very few studies, however, were performed to study the acute effects of caffeine in functional connectivity (FC) at rest [ 24 , 25 ]. Those few studies reveal a general trend for a caffeine-induced reduction in FC, associated with neuro-electric power fluctuations as measured through magnetoencephalography and exacerbated anticorrelations. Despite this existing literature, many aspects of the characterization of the impact of caffeine on the brain remain unexplored. Critical amongst these is the characterization of the chronic effects of habitual coffee and caffeine consumption upon the functional architecture of the brain. We are only aware of a single study that touched on this subject [ 26 ]. That work revealed an association between different habits of coffee consumption and the magnitude of BOLD signals in the visual cortex; however, it did not address possible effects on the functional connectome or resting state networks. Pursuit of the latter can present significant challenges in finding and recruiting participants with sufficient variation in consumption habits and who are willing to undergo necessary, even if short, abstinence procedures.

To tackle this gap, herein we will use whole brain approaches [ 27 , 28 , 29 ], as well as the study of brain functional dynamics [ 30 ] to compare FC and its dynamics between habitual and non-habitual coffee consumers. In addition, and because of the potential anxiogenic and HPA-disrupting role of caffeine, measures of psychological state (depression, anxiety, and stress) will also be acquired, in order to explore the potential association of habitual coffee consumption with these variables.

Subject recruitment and assessment

Participants were recruited through advertisement on the Institute’s social media, institutional e-mail, and press releases distributed among Portuguese local and national newspapers. Exclusion criteria included the presence of neurological or psychiatric disorders, habitual consumption of mind-altering substances, and the inability to undergo MRI. Two experimental groups were created according to participants’ coffee consumption habits: coffee drinkers (CD), who drank a minimum of one cup of caffeinated coffee per day; and non-coffee drinkers (NCD), who had no habits of regular consumption of coffee (less than one cup per week). Consumption of coffee as well as other caffeinated products was confirmed in a structured interview. Participants were instructed to abstain from caffeinated products for 3 h before the assessment, in order to avoid acute influence of caffeine. Fifty-six subjects were recruited (32 CD and 24 NCD). One participant from the CD group was excluded due to imaging artifacts, rendering a final sample of 31 CD and 24 NCD. Characterization of subjects was done in two (CD) or three (NCD) parts within a 3 h time-period: participants were first interviewed by a certified psychologist. This was followed by an MRI scanning session, and, in the case of the NCD, the first scanning session was followed by ingestion of coffee (Nespresso ® Ristretto, ~50 cc) before a rs-fMRI scan ~30 min thereafter. During the interview, the following data were gathered: demographic data; habits of coffee and other caffeinated products consumption; and assessment of depression, anxiety, and stress scores through the Depression, Anxiety and Stress Scales (DASS-21, [ 31 , 32 ]).

Demographic and psychological data analysis

CD and NCD groups were compared in terms of sociodemographic variables, frequency of consumption of caffeinated products, and psychological variables. Since the variables did not follow a normal distribution, nonparametric tests were applied (Wilcoxon test). Moreover, multiple regression analyses were performed, aiming to determine the association between daily consumption of caffeinated products such as coffee, tea, chocolate, etc. (0 = <1/day; 1 = 1/day; 2 = 2/day; 3 = 3 or more/day) and the psychological data measured with the DASS-21 questionnaire (controlled for sex, age, and education), independently of the groups. These analyses were performed on Matlab2020a software (The Mathworks, Inc.) and p  < 0.05 was considered the threshold for statistical significance. Linear regression representations were generated in Prism 7 software (GraphPad Software, Inc.).

MRI brain imaging

Magnetic resonance imaging scans were conducted using a Siemens Verio 3T (Siemens, Erlangen, Germany) located in Hospital de Braga (Braga, Portugal) using a 32-channel head antenna. The scanning session included as an anatomical acquisition a T1-weighted sagittal magnetization-prepared rapid acquisition with gradient echo (TE/TR = 2420/4.12 ms, FA = 9°, 1 mm 3 isometric voxel size, Field-of-View = 176 × 256 × 256 mm 3 ). The resting-state fMRI (rs-fMRI) acquisition used a multi-band echo planar imaging sequence, CMRR EPI 2D (R2016A, Center for Magnetic Resonance Research, University of Minnesota, Minnesota, USA [ 33 , 34 , 35 ]) sensitive to fluctuations in the BOLD contrast (TR/TE = 1000/27 ms, FA = 62°, 2 mm 3 isometric voxel size, 64 axial slices over an in plane matrix of 100 × 100). The rs-fMRI acquisition had a duration of 7.5 min, during which subjects were instructed to remain with their eyes closed, relaxed, and let their minds wander freely.

Preprocessing of MRI data

MRI results included in this manuscript were preprocessed using fMRIPrep 1.4.1 ([ 36 ]; RRID:SCR_016216), which is based on Nipype 1.2.0 ([ 37 , 38 ]; RRID:SCR_002502). A full description of the preprocessing pipeline can be found in the Supplementary material.

Resting-state analysis

Independent component analysis.

Resting-state network (RSN) maps were analyzed voxel-wise through a probabilistic independent component analysis (ICA) as implemented in Multivariate Exploratory Linear Optimized Decomposition into Independent Components, distributed with FSL [ 39 ]. For further details check the Supplementary material.

The RSNs FC was compared between CD and NCD groups, using a nonparametric permutation procedure implemented in the randomize tool from FSL [ 40 ]. Threshold-free cluster enhancement (TFCE) was used to detect widespread significant differences and control the family-wise error rate (FWE-R) at α  = 0.05. In total, 5000 permutations were performed.

Static functional connectomics analysis

To assess differences between the two groups in the functional connectome, the mean time series of the 268 regions of the Shen Atlas [ 41 ] were extracted. The Pearson correlation between time series, followed by Fisher r-to-Z transformation, were calculated to obtain matrices of FC for each subject. To overcome the issue of multiple comparisons induced by the large number of connections in the network, we applied the network-based statistics (NBS) approach [ 42 ]. A total of 5000 permutations were used, together with a FWE corrected network significance of 0.05. For more details check the Supplementary material.

Dynamic functional analysis

We applied the leading eigenvector dynamics analysis (LEiDA, [ 30 ]) approach to study the changes in the functional dynamics associated with habitual caffeine consumption. Instantaneous FC was calculated for each subject at each time point for all 268 regions of interest of the Shen atlas, using the time series extracted for the static analysis. To help visually identify phase locked (PL) states, the overlap between each anatomical region of each state to the 7 Yeo RSN’s [ 43 ], plus two other labels for the cerebellum and subcortical units, was calculated and anatomical units color coded in accordance to the best match. For more details check the reference paper or the Supplementary material.

Effects of acute coffee consumption and frequency of caffeine consumption

The significant findings obtained with ICA, NBS, and LEiDA were further explored, aiming to assess the effects of acute coffee consumption in NCD and of frequency of consumption of caffeinated products in both groups. The first were assessed by comparing NCD after coffee consumption with data from CD (independent sample t -test) and NCD (before coffee consumption; paired sample t -test). The second were evaluated by performing multiple regression analyses following the same approach described for the DASS-21 questionnaire.

Demographic analysis

CD and NCD groups did not differ in terms of age (range 19–57; p  = 0.28; Z  = 1.09; r  = 0.15) or number of formal years of education (range 12–25; p  = 0.07; Z  = 1.84; r  = 0.25). Frequency of consumption of caffeinated products was, as expected, higher in the CD group ( p  < 0.001; Z  = 6.17; r  = 0.83). Sex distribution was not significantly different between groups ( χ 2 (1, N  = 55) = 0.52, p  = 0.42), despite the CD group presenting a slightly higher proportion of males (41.94%) in comparison with the NCD group (33.33%). Descriptive statistics can be found in Table  1 .

Effect of habitual caffeine consumption on rs-fMRI data

Independent components analysis.

Thirty components were obtained from the probabilistic ICA of CD and NCD (before consuming coffee). Fifteen of these components were found to be representative of the most typical RSNs. A tendency toward lower FC patterns in the CD group can be seen in most of these networks (see Supplementary Fig.  1 ). Despite this, we only found significant FWE-R TFCE corrected between-group differences in two of them, namely, in the somatosensory network and the limbic network (Fig.  1 ). Regarding the somatosensory network, NCD presented a pattern of higher connectivity with the right precuneus (MNI coordinates = 30, −72, 38; 7 voxels; peak t value = 4.4). Moreover, for the limbic network, NCD had higher FC in the right insula compared to CD (MNI coordinates = 42, −12, 2; 4 voxels; peak t value = 5.09). Of note, these effects were also linearly associated with the caffeinated products’ frequency of consumption. Negative correlations were found for both right precuneus ( p  = 0.003; β  = −1.433; adjusted R 2  = 0.162; Fig.  1B ) and right insula ( p  < 0.001; β  = −2.384; adjusted R 2  = 0.267; Fig.  1B ). Detailed statistics can be found in Supplementary Table  1 .

A Sagittal, coronal, and axial view of the clusters showing significant between-group differences in the connectivity between the somatosensory network and the right precuneus (top) and the limbic network and the right insula (bottom). The FWE-R TFCE corrected clusters are shown in dark blue overlaid over a more extended non-significant after multiple comparison correction cluster in hot color scale scheme, for visualization purposes. B Associations of frequency of consumption of caffeinated beverages with the mean FC of the right precuneus and the right insula. C Scatter plots showing the mean FC of the right precuneus and the right insula for the NCD before drinking coffee (NCD), the NCD after drinking coffee (NCD pos), and the CD.

Importantly, the group differences described were reduced after NCD drank coffee (see Fig.  1C ; somatosensory network: pre vs post NCD t value = 1.86, p  = 0.075, post NCD vs CD t value = −2.89, p  = 0.006; limbic network: pre vs post NCD t value = 3.88, p  < 0.001, post NCD vs CD t value = −1.46, p  = 0.15). This points to a potential causality link between coffee drinking and the above-described changes in lower connectivity in the somatosensory and in the limbic networks.

Connectomics analysis

From the connectomics analysis done using NBS, a single network of significantly higher connectivity was found in the NCD group (pre-coffee) between the thresholds of 0.005 and 0.0005 (for statistics of all thresholds see Supplementary Table  2 ). For ease of visualization, we present only the results found at the highest significant threshold of p  = 0.0005 ( t (threshold) = 3.71, df = 54, p (network) = 0.043, Hedge’s g  = 1.08 (large effect size), 24 nodes, 46 edges; Fig.  2A ). The full list of nodes with significant different edges between groups across all thresholds can be found in Supplementary Table  3 . Of these we highlight the Thalamus (nodes #262 and #126), the Cerebellum (left anterior Culmen #245 and bilateral Tonsils #238 and #119), the right Postcentral Gyrus (#33), the left Middle Temporal Gyrus (#197), the left Precentral Gyrus (#160), and the bilateral Caudate (#260 and #122) and Putamen (#124 and #261) as having the most strongly affected connections within the network.

A Sagittal, coronal, and axial view of the network with nodes and edges colored in red–yellow color scheme representing the statistical t value of the difference between groups. B Scatter plot of the mean FC within the significant network for each experimental group. C Associations of frequency of consumption of caffeinated beverages with the mean FC of the network found in NBS.

When observing the average network connectivity from this network, NCD post-coffee drink displayed a significant reduction in connectivity (Fig.  2B ), leading to a profile more similar to CD ( p  = 0.037, t  = 2.13, df = 54) than to NCD pre-coffee drink ( p  = 1.3 × 10 −7 , t  = 7.4, df = 23). NBS mean FC was negatively associated with frequency of caffeine consumption ( p  < 0.001; β  = −0.101; adjusted R 2  = 0.506; Fig.  2C ). Detailed statistics can be found in Supplementary Table  1 .

From the dynamic FC analysis, one functional subsystem (Fig.  3A , PL state 4) was found to last significantly longer in CD (Fig.  3B , 17.95 ± 18.32 s) compared to pre-coffee NCD (8.95 ± 6.13 s) surviving correction for multiple comparisons with a corrected p  = 0.038 and a medium effect size with Hedge’s g  = 0.62. No BOLD phase-locking state was found to significantly differ in terms of probability of occurrence (see Supplementary Table  4 for all p values for all partition models).

A sagittal and axial views representing the state anatomical areas of each phase locked (PL) state. B Bar plot representing the group differences between coffee and non-coffee drinkers. Differences of p  < 0.05 are indicated in red, while multiple comparison surviving effects are indicated in green. C Associations of frequency of consumption of caffeinated beverages with the average duration (in seconds) of PL state 4. D Bar plot of the probability of state 4 for the CD, NCD, and NCD post caffeine consumption groups. E Life time of state 4 for the CD, NCD, and NCD post caffeine consumption groups. F Colored labels used to match each anatomical area of the PL states to different resting state networks.

This BOLD phase-locking state, corresponding to the fourth most probable state when partitioning the data into nine states, comprises a large number of nodes in the cerebellum, visual network as well as several subcortical nodes such as the bilateral thalamus and parahippocampal gyrus (mapped and color coded through the reference shown in Fig.  3F ). While this was the only result that survived correction for multiple comparisons, it is relevant to note that the equivalent LEiDA state for k  = 10 is just below the threshold ( p  = 0.051, Supplementary Table  4 and Supplementary Figs.  2 and 3 ). Furthermore, LEiDA lifetime results were positively correlated with frequency of caffeine consumption ( p  = 0.012; β  = 2.176; adjusted R 2  = 0.083; Fig.  3C ).

After drinking coffee, both the lifetime and the probability of this state in NCD became closer to the values observed in CD, with the probability not being significantly different from CD ( p  = 0.5, t  = 0.67, df = 54), while being significantly higher than NCD pre-coffee ( p  = 0.037, t  = 2.31, df = 23, Fig.  3D ). For the life time of state 4, post-coffee drink NCD were not significantly different from CD ( p  = 0.177, t  = 1.37, df = 54) nor the pre-drink NCD ( p  = 0.107, t  = 1.68, df = 23, Fig.  3E ). All results across the different k’ s can be found in Supplementary Figs.  2 and 3 and Supplementary Table  4 .

Effect of habitual caffeine consumption on psychological data

The association between coffee consumption and stress, anxiety, and depression (DASS-21) was assessed. When comparing CD and NCD groups, only stress was significantly different between groups (stress— p  = 0.025; Z  = 2.237; r  = 0.307; anxiety— p  = 0.851; Z  = −0.188; r  = −0.026; depression— p  = 0.085; Z  = 1.724; r  = 0.237), with CD showing higher levels of stress than NCD (median (Med) = 6.0; interquartile range (IQR) = 6.0 vs Med = 4.0; IQR = 4.0, respectively). Of notice, particular items of the DASS-21 Stress subscale that can be related to arousal were increased in CD. Items #1 and #12, which measure difficulty to relax, presented statistically significant differences ( p  = 0.007, Mann–Whitney test), while item #8, that relates to nervous arousal, presented a trend in the same direction ( p  = 0.083). Interestingly, item #7 (Anxiety subscale), that is associated with skeletal musculature, despite not achieving a statistically significant difference between groups, tended to be lower in CD ( p  = 0.113), suggesting a segregation between the motor and arousal loops.

When assessing the effects of frequency of caffeine consumption in self-reported variables (controlling for sex, age, and education), the positive correlation with stress was maintained ( p  = 0.004; β  = 1.292; adjusted R 2  = 0.135; Fig.  4A ). Moreover, a sex by anxiety interaction was found ( p  = 0.023; β  = 0.683; adjusted R 2  = 0.085; Fig.  4B ), which seems to be driven by a positive correlation in males. No significant effects were found for the depression subscale ( p  = 0.128; β  = 0.450; adjusted R 2  = 0.108; Fig.  4C ). Detailed statistics can be found in Supplementary Table  1 .

Associations of frequency of consumption of caffeinated products with the DASS-21 subscales of stress ( A ) and anxiety ( B ), and non-significant association with the depression subscale ( C ).

Herein we describe for the first time the effects of habitual coffee consumption on the human brain networks. We show that habitual CD have different patterns of FC in comparison with NCD. Our rs-fMRI analysis revealed decreased FC of the somatosensory and limbic networks in CD that correlated with the frequency of consumption of caffeinated products. Such changes were replicated in NCD after a single coffee, suggesting possible causality between coffee intake and altered patterns of brain network connectivity. Previous studies have described a reduction of similar RSN connectivity after acute caffeine ingestion [ 25 , 44 ].

Decreased FC in somatosensory and related networks in CD likely represents a more efficient and beneficial pattern of connections with respect to motor control and alertness; importantly this fits our findings of trends of increased scores in CD in the specific items of the DASS-21 scale that measure these dimensions. The other network impacted by coffee intake was the limbic network, which is involved in processing the sensory input from the external and internal environment which, by modulating memory and motivation, determine emotional, autonomic, motor, and cognitive responses [ 45 ]. A previous resting-state PET study showed reduced metabolic activity in components of this network after caffeine ingestion [ 18 ] and a study using a hedonic fMRI task showed decreased activation in neuronal areas associated with memory and reward [ 46 ] in caffeine consumers compared to non-consumers; the present FC data are consistent with those reports.

Analysis of the global functional connectome using NBS revealed a network impacted by the habitual consumption of caffeine. This widespread network of reduced FC comprised cerebellar, subcortical (striatal and thalamic), and motor cortex regions, partially matching previously reported effects of acute caffeine ingestion [ 24 , 25 ]. Interestingly, there is a clear bilateral involvement of striatal nodes and of the thalamus which, respectively, have the highest densities of A2A and A1 receptors in the brain [ 47 , 48 ]. The action of caffeine in these regions has an influence on cortico-striatal-thalamic and cerebellar-thalamocortical loops that are relevant for a variety of neuronal processes. Thus, the observed decrease in FC at rest in this network in regular caffeine-ingesting individuals reveals greater segregation of these areas with less inter-regional dependencies, favoring greater efficiency within these loops. It is relevant to note here that, even though A1 and A2A receptors are thought to mediate differential actions [ 49 ], similar effects were observed in both loops. This likely reflects the fact that fMRI provides proxy aggregate measurements of functional connections among a network of brain areas.

A previous study reported that caffeine increases brain entropy, indicating higher information processing capacity across the cerebral cortex [ 23 ]. Our LEiDA analysis revealed a dynamic state involving several cerebellar and subcortical areas, with a longer average lifetime in habitual CD. This network comprises several nodes, including the cerebellum, thalamus, and parahipocampal, lingual, and inferior occipital gyri which are relevant in the context of caffeine consumption—caffeine is known to decrease mind wandering [ 50 ] and to increase attention, alertness, and arousal [ 51 ]. In fact, the nodes implicated in this network are linked by visual processing; among these, the thalamus is critical for distributing cognitive control [ 52 ]. The lingual and inferior occipital gyrus are also implicated in visual processing, while the parahippocampus is involved in memory encoding and retrieval [ 20 , 21 ]; the latter may explain why caffeine reportedly facilitates memory processes [ 9 ]. Lastly, evidence of strong rsFC between the cerebellum, known to be also implicated in sensory processing [ 53 ] and a number of sensorial cortices [ 54 ], explains the observed increased visual alertness/attention and readiness to sensorial perception among CD individuals. While similar findings have been previously reported [ 6 ], only one other study assessed habitual CD using MRI, and did not characterize changes in FC [ 26 ]. Importantly, similarly to the other neuroimaging findings, a common pattern of connectivity dynamics was found in CD individuals and NCD subjects who drank a single coffee before scanning.

In order to provide a link with other neuropsychologic dimensions, we also assessed our subjects in the DASS-21. Interestingly, we observed habitual CD to display increased levels of stress; there was a clear positive association between the indices of stress and the amount of consumption of caffeinated drinks. Interestingly, items of the DASS-21 sub-score that showed greater variance between CD vs NCD were those related with difficulty to relax (items #1 and #12), and those related to nervous arousal (item #8), consistent with the common attribution of alertness and arousal to coffee intake. It also deserves to be mentioned that, despite the display of a higher anxiety among CD (particularly in males), there was a decrease in DASS-21 item (#7) which matches the effects on the skeletal muscles in CD; this, in turn, fits the findings of better segregation of the above-described loops. The present results extend previous studies that described an association between coffee/caffeine consumption and stress and anxiety [ 1 , 13 , 16 , 55 ] and sex [ 13 , 16 ]. It is important to note, however, that causality cannot be inferred from our study design. Our results are open to two interpretations: higher coffee/caffeine consumption leads to increased stress and anxiety; or, alternatively, higher stress and anxiety induce higher coffee/caffeine consumption. Moreover, given that resting-state studies using stress and anxiety samples have shown both decreases and increases in FC [ 56 , 57 , 58 ], the possibility that coffee/caffeine consumption elicits decreases in FC or compensates for FC beyond a certain threshold, must also be considered. While the first possibility is in line with studies showing increased anxiety upon both acute caffeine administration in humans [ 1 , 12 ] and prolonged ingestion in rodents [ 59 ] reports that greater caffeine consumption under periods of stress may help maintain synaptic homeostasis [ 60 ] as well as prevent mood disorders warrant further study in future.

The methodologies applied in the present study do not allow us to draw precise relationships between the psychological and neuroimaging results and the dosage and metabolism of caffeine among individual subjects. To study the individual responses to the acute and chronic effects of caffeinated product intake would be a complex undertaking, requiring subjects to adapt their daily habits and strict abstinence regimens. Based on our experience, recruitment of subjects for a properly balanced study is also difficult since NCD subjects are insufficiently motivated to engage in studies on the actions of caffeine. Nevertheless, we are currently developing alternative strategies that would allow us to deliver calibrated doses of caffeine during fMRI scanning sessions to better discriminate its effects from other factors (e.g., stress). Our future work will also examine inter-individual differences in response to caffeine consumption, the subjective experience of coffee consumption, as well as the influence of additional factors as the consumption of alcohol and tobacco. Despite such gaps, the data presented here represent a contribution to the knowledge of the “caffeinated brain” and how these changes underlie the behavioral effects triggered by coffee intake, with implications for physiological and pathological conditions.

Code availability

In-house scripts used in the NBS analysis are fully available online at open science framework website ( https://osf.io/qepc8/ ) and LEiDA scripts at github ( https://github.com/juanitacabral/LEiDA ).

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This study was funded by the Institute for the Scientific Information on Coffee (ISIC) (ISIC_2017_NS); ISIC did not influence the experimental design or data analysis/interpretation. The laboratory was also supported by the project NORTE‐01‐0145‐FEDER000013 through the Northern Portugal Regional Operational Programme (NORTE 2020), under the Portugal 2020 Partnership Agreement, through the European Regional Development Fund (FEDER). RM, MP-P, and ME were supported by post-doctoral grants from the project ISIC_2017_NS. PSM was supported by a fellowship grant from the Fundação para a Ciência e a Tecnologia (FCT; grant number PDE/BDE/113601/2015) from the PhD-iHES program. RV was supported by a research fellowship of the project funded by FCT (UMINHO/BI/340/2018). AC was supported by a scholarship from the project NORTE-08-5639-FSE-000041 (NORTE 2020; UMINHO/BD/51/2017).

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Life and Health Sciences Research Institute (ICVS), School of Medicine, University of Minho, Campus de Gualtar, Braga, Portugal

Ricardo Magalhães, Maria Picó-Pérez, Madalena Esteves, Rita Vieira, Teresa C. Castanho, Liliana Amorim, Mafalda Sousa, Ana Coelho, Joana Cabral, Pedro S. Moreira & Nuno Sousa

ICVS/3B’s, PT Government Associate Laboratory, Braga/Guimarães, Portugal

Clinical Academic Center - Braga, Braga, Portugal

NeuroSpin, CEA, CNRS, Paris-Saclay University, Gif-sur-Yvette, France

Ricardo Magalhães

Center for Music in the Brain, Department of Clinical Medicine, Aarhus University, Aarhus, Denmark

Henrique M. Fernandes & Joana Cabral

Psychological Neuroscience Lab, CIPsi, School of Psychology, University of Minho, Braga, Portugal

Pedro S. Moreira

P5 Medical Center, Braga, Portugal

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Magalhães, R., Picó-Pérez, M., Esteves, M. et al. Habitual coffee drinkers display a distinct pattern of brain functional connectivity. Mol Psychiatry 26 , 6589–6598 (2021). https://doi.org/10.1038/s41380-021-01075-4

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Coffee – Production and Research presents a diversity of important issues related to coffee, with an emphasis on the science of coffee growing. Coffee is one of the highest value commodities traded worldwide. Cultivated and consumed widely, it generates progress for both the economy and society. Divided into six sections, this book examines two coffee species of commercial importance, Coffea arabi...

Coffee – Production and Research presents a diversity of important issues related to coffee, with an emphasis on the science of coffee growing. Coffee is one of the highest value commodities traded worldwide. Cultivated and consumed widely, it generates progress for both the economy and society. Divided into six sections, this book examines two coffee species of commercial importance, Coffea arabica L. and Coffea canephora Pierre ex. A. Froehner. Chapters cover such topics as biotechnology, growing, harvesting, post-harvest handling, quality, chemistry, commercialization, and byproducts of coffee.

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Roasting conditions and coffee flavor: a multi-study empirical investigation.

1. Introduction

2. materials and methods, 2.1. overview of studies, 2.2. roasting conditions, 2.3. sensory descriptive analysis, 2.3.1. sample preparation, 2.3.2. experimental procedures, 2.4. data analysis, 3. results and discussion, 3.1. relative impact of roast colour and timing on coffee flavour, 3.2. impact of timing variation: which roasting phase is most important, 3.3. limitations and future research, 4. conclusions, author contributions, acknowledgments, conflicts of interest.

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Münchow, M.; Alstrup, J.; Steen, I.; Giacalone, D. Roasting Conditions and Coffee Flavor: A Multi-Study Empirical Investigation. Beverages 2020 , 6 , 29. https://doi.org/10.3390/beverages6020029

Münchow M, Alstrup J, Steen I, Giacalone D. Roasting Conditions and Coffee Flavor: A Multi-Study Empirical Investigation. Beverages . 2020; 6(2):29. https://doi.org/10.3390/beverages6020029

Münchow, Morten, Jesper Alstrup, Ida Steen, and Davide Giacalone. 2020. "Roasting Conditions and Coffee Flavor: A Multi-Study Empirical Investigation" Beverages 6, no. 2: 29. https://doi.org/10.3390/beverages6020029

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