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1 From the Department of Nutrition and Dietetics, Harokopio University, Athens, Greece (AZ and DBP); and the First Cardiology Clinic, School of Medicine, University of Athens, Greece (CP, CC, and CS).
2 Supported by research grants from the Hellenic Cardiological Society (HCS2002) and the Hellenic Atherosclerosis Society (HAS2003) for the ATTICA study. 3 Address reprint requests to DB Panagiotakos, 46 Paleon Polemiston Street, Glyfada, Attica, 166 74, Greece. E-mail: d.b.panagiotakos{at}usa.net.
ABSTRACT
Background: The effect of coffee consumption on the cardiovascular system is conflicting. Inflammation is important to the development of cardiovascular disease (CVD), and several dietary factors are thought to exert significant effects on inflammation and thus on the risk of CVD.
Objective: We aimed to investigate the associations between coffee consumption and inflammatory markers.
Design: The cross-sectional survey enrolled 1514 men (
Conclusions: A relation exists between moderate-to-high coffee consumption and increased inflammation process. This relation could explain, in part, the effect of increased coffee intake on the cardiovascular system.
Key Words: Inflammation • cardiovascular disease • risk factors • coffee
INTRODUCTION
Studies have suggested that low-grade systemic inflammation participates in the pathophysiology of obesity, insulin resistance, ischemic heart disease, metabolic syndrome X, and abnormal coagulation process (1–6). An extensive body of scientific evidence also suggests that dietary factors exert their influence largely through their effects on blood pressure, lipids, and lipoproteins, as well as on markers of inflammation and coagulation (7, 8). This evidence implies that dietary interventions designed to reduce the inflammatory process could be of benefit in reducing the risk of cardiovascular disease (CVD). Furthermore, the information about the effects of coffee consumption on the cardiovascular system is conflicting. Some reported a positive association between coffee intake and ischemic heart disease (9–11), whereas others reported no relation (12–14). Because the effect of coffee consumption on various inflammatory markers was rarely investigated, we aimed to test the hypothesis that there is a dose-response relation between several inflammatory markers and coffee consumption, after we took into account the effect of several potential confounders.
SUBJECTS AND METHODS
Study population
The ATTICA study (15) is a health and nutrition survey that is being carried out in the Greek province of Attica (an area that is 78% urban and 22% rural), where Athens is located. The sampling was random and multistage and was based on the age and sex distribution in the province of Attica as provided by the National Statistical Service (census of 2001). Our study was conducted from May 2001 to December 2002. A total of 4056 inhabitants from the geographic region of Attica were randomly identified for potential inclusion. Inclusion criteria required that participants exhibit no clinical evidence of CVD, atherosclerotic disease, or chronic viral infections. Moreover, subjects did not have a cold or flu, acute respiratory infection, or dental problems; nor had they undergone any type of surgery in the week preceding the study. A total of 1514 men (
Dietary assessment was based on a food-frequency questionnaire (FFQ), which was validated by the Unit of Nutrition of Athens Medical School. Validation of the FFQ was based on 42 men and 38 women, aged 25–67 y, who completed 2 self-administered semiquantitative FFQs within 1 y and completed an interviewer-administered 24-h diet recall questionnaire. The FFQ also included validation for coffee intake (16).
Consumption of nonrefined cereals and products, vegetables, legumes, fruit, olive oil, dairy products, fish, nuts, potatoes, eggs, sweets, poultry, red meat and meat products, coffee, and alcohol was measured as an average per week during the past year. Frequency of consumption was quantified in terms of the number of times a month a food was consumed.
On the basis of the FFQ, all participants were asked about their usual frequency (average) of daily coffee consumption. According to the distribution of coffee consumption, we categorized usual daily coffee consumption as none, rare (100 mL/d), moderate (200–400 mL/d), and heavy (>400 mL/d). All reported types of coffee (instant coffee, brewed coffee, Greek-type coffee, cappuccino, or filtered coffee) were adjusted for 1 cup coffee (150 mL) and caffeine concentrations of 28 mg/cup. Thus, measurement of 1 cup coffee was equivalent to 450 mL brewed coffee or 300 mL instant coffee (17). Included in the analysis were the following dummy variables: consumption of decaffeinated coffee, tea- and caffeine-containing drinks (colas), and chocolate. Cessation of coffee consumption during the previous year (in months of abstinence) was recorded and considered as a covariate in all analyses that evaluated the association between coffee intake and inflammatory markers. According to self-reported data, none of the participants took medications (whether prescribed or over the counter) that contained caffeine. Alcohol consumption was recorded as daily ethanol intake of 100-mL wineglasses adjusted for 12% ethanol concentration).
Biochemical analyses
During enrollment, blood samples from the antecubital vein of each participant were collected between 0800 and 1000 and after a 12-h overnight fast. Subjects were supine for 10 min before blood collection. All samples were collected without occlusion. Collection tubes were iced until analyzed, then centrifuged within 2–4 h of collection at 3000 rpm for 10 min at 4°C (Eppendorf Multipurpose Centrifuge 5810; Eppendorf, Westbury, NY). Biochemical evaluations were conducted in the same laboratory according to the criteria of the World Health Organization Lipid Reference Laboratories.
C-reactive protein (CRP) and serum amyloid-A (SAA) were assayed by particle-enhanced immunonephelometry (N Latex; Dade Behring Marburg GmbH, Marburg, Germany) with a range from 0.175 to 1100 mg/L and 0.75 to 1000 mg/L, respectively. Interleukin 6 (IL-6) was measured by using a high-sensitivity enzyme-linked immunoassay (R & D Systems Europe Ltd, Abingdon, United Kingdom) with a range from 0.156 to 10 pg/mL. The intraassay and interassay CV was <5% for CRP and SAA and <10% for IL-6. We used the enzyme-linked immunosorbent assay method for the quantitative determination of human tumor necrosis factor (TNF-) in duplicate in serum samples of the participants by using a Quantikine HS/human TNF- immunoassay kit (R & D Systems Inc, Minneapolis). We also measured white blood cell (WBC) counts by using a Medicon analyzer (Medicon Ltd, Athens). Total and HDL-cholesterol, blood glucose, and triacylglycerol concentrations were also measured in all participants, by using a chromatographic enzymic method in a Technicon automatic analyzer (RA-1000; Dade Behring Marburg GmbH). LDL cholesterol was calculated with use of the Friedewald formula: total cholesterol – HDL cholesterol – 1/5 x (triacylglycerols). An internal quality control was in place for assessing the validity of cholesterol, triacylglycerol, and HDL methods. The intraassay and interassay CVs of cholesterol concentrations did not exceed 4%, triacylglycerols 4%, and HDL 4%.
Demographic, lifestyle, and clinical characteristics
The study’s questionnaire also included demographic characteristics such as age, sex, financial status (average annual income during the past 3 y), and education level (in school years). Moreover, current smokers were defined as those who smoked 1 cigarette/d, never smokers were defined as those who have never smoked a cigarette, and former smokers were defined as those who had stopped smoking 1 y before the beginning of the study. For the multivariate statistical analyses, cigarette smoking was quantified in number of cigarettes smoked per day and adjusted for a nicotine content of 0.8 mg/cigarette. Physical activity was defined as leisure-time activity of a certain intensity and duration, conducted 1 time/wk during the past year, and was graded in qualitative terms such as light (expended calories: < 4 kcal/min), moderate (expended calories: 4–7 kcal/min), and vigorous (expended calories: > 7 kcal/min). The rest of the subjects were defined as physically inactive. Body mass index (BMI) was calculated as weight (in kg) divided by standing height (in m2). Obesity was defined as a BMI > 29.9.
Arterial blood pressure was measured 3 times by using the right arm (ELKA aneroid sphygmomanometer; Von Schlieben Co, Munich, Germany). All measurements were made at the end of the physical examination while subjects were in a sitting position for at least 30 min. Patients whose average blood pressure was 140/90 mm Hg or those under antihypertensive medication were classified as hypertensives. Hypercholesterolemia was defined as total serum cholesterol concentrations > 200 mg/dL or the use of lipid-lowering agents. Diabetes mellitus was defined as a blood glucose > 125 mg/dL or the use of antidiabetic medications.
Statistical analysis
Continuous variables are presented as means ± SDs, whereas qualitative variables are presented as absolute and relative frequencies. Associations between categorical variables were tested by using contingency tables and chi-square test. Correlations between inflammatory biomarkers and other cofactors were evaluated by calculation of Pearson’s correlation coefficient for the normally distributed variables and of Spearman’s correlation coefficient for skewed variables. Comparisons between normally distributed continuous variables and coffee-consuming groups were performed by analysis of covariance or multiway analysis of covariance, after testing for equality of variances (homoscedacity), and taking into account the effect of age, sex, BMI, smoking habits, physical activity, education status, food items consumed, and use of medications. The Kolmogorov-Smirnov test was applied to assess normality. CRP values were log transformed because of their skewed distribution. In the case of education (years of schooling that could not be transformed to normal distributions), the nonparametric test suggested by Kruskal and Wallis was used. Differences in inflammation markers between particular subgroups according to coffee consumption were tested by using post hoc analysis, after correcting the P value for multiple comparisons by using Bonferroni’s correction.
Regression models were applied for all inflammatory markers (dependent variables) on coffee consumption (independent variable) after adjustment for potential confounders, whereas the interaction of coffee with previously identified factors was assessed by using likelihood ratio tests. Because of their skewed distribution of CRP concentrations, these data were log transformed.
All reported P values were based on two-sided tests. SPSS statistical software (version 11.0; SPSS Inc, Chicago) was used for all the statistical calculations.
RESULTS
Demographic and clinical characteristics of the participants by coffee consumption status
Most of the participants (91% of men and 76% of women) reported that they drank 1 cup of coffee/d. Of the participants who drank coffee, 12% of men and 8% of women reported that they drank only filtered coffee; 9% of men and 5% of women drank only unfiltered coffee; and the remainder (79% of men and 87% of women) reported that they drank both types of coffee. Various demographic, clinical, and behavioral characteristics of the participants are presented in Table 1. Data are presented separately for men and women, because there were significant interactions between sex and years of school, physical activity, obesity, hypertension, hypercholesterolemia, and family history, but not between sex and smoking and diabetes. Therefore, data for smoking and diabetes were not analyzed separately in men and women but were analyzed only after adjustment for sex (Table 1).
View this table:
TABLE 1. Participants’ demographic, lifestyle, and clinical characteristics1
Note that a variant association between coffee intake and blood pressure was observed. Particularly, moderate consumption was associated with higher blood pressure values in men than in men who consumed no coffee or higher amounts of coffee, whereas moderate intake was associated with lower blood pressure values in women (Table 1
Mean concentrations of investigated markers by coffee consumption are shown in Table 2. Data are reported separately for men and women because there were significant interactions between sex and all inflammatory markers except WBCs. Therefore, data for WBCs were analyzed after adjustment for sex. All inflammatory markers showed a linear dose-response relation (P < 0.01) with coffee consumption. Compared with coffee nondrinking men, those men who consumed >200 mL coffee/d had on average 30% higher CRP, 50% higher IL-6, 12% higher SAA, and 28% higher TNF- concentrations and only 3% higher WBC counts (NS). Similarly, women who consumed >200 mL coffee/d had on average 38% higher CRP, 54% higher IL-6, 28% higher SAA, and 28% higher TNF- concentrations and only 4% higher WBC counts (NS) than did coffee nondrinkers. All previous associations were also tested after adjustment for the potential confounding effects of age, various lifestyle habits (eg, smoking), physical activity, and BMI, as well as the presence or absence of hypertension, hypercholesterolemia, and diabetes and the frequency of the participants’ consumption of major food groups.
View this table:
TABLE 2. Inflammatory markers and daily coffee consumption1
Post hoc analysis revealed significant differences between groups with regard to coffee intake in both men and women. In particular, compared with coffee nondrinking, the consumption of 200 mL coffee was associated with substantial increases in CRP, SAA, IL-6, and TNF- (Table 2). With regard to WBC counts, differences were significant when we compared high coffee intake (ie, >400 mL/d) with no intake but not when we compared low coffee intake (ie, <200 mL/d) with no intake (Table 2).
BMI was positively correlated with all inflammatory markers (P < 0.05). In contrast, BMI was inversely correlated with daily coffee intake (r = –0.04, P = 0.03). However, no differences were observed regarding the effect of coffee consumption on the investigated biomarkers when the data were stratified and analyzed by obesity status.
Associations between inflammatory markers and quantities of coffee consumed, after adjustment for several potential confounders, are presented in Table 3. To show how much variability was explained by coffee intake alone and consequently how much variability could be attributed to covariates, adjusted R2 values are included. No significant differences were observed in these biomarkers when we stratified our analysis by types of coffee consumed (ie, filtered or unfiltered).
View this table:
Table 3. Inflammatory markers and daily coffee consumption
DISCUSSION
The effect of coffee consumption on inflammation marker concentrations was investigated in 3042 randomly selected men and women from the region of Attica in Greece. Coffee drinking was associated with an increase in all inflammatory markers investigated, but the difference was significant only when participants who consumed >200 mL coffee/d were compared with participants who did not drink coffee. A variant association of coffee intake with blood pressure levels was also observed. A positive association between coffee consumption and presence of hypercholesterolemia in both sexes was found. In contrast to these findings, we observed an inverse association with obesity only in women. Nevertheless, after adjustment for confounding variables, the associations between coffee consumption and inflammatory markers remained the same.
In recent years, clinical and observational studies reported that coffee consumption was associated with cardiac arrhythmia, heart rate, serum cholesterol, blood pressure, and consequently cardiovascular risk (18). Still, no metabolic study investigated the effects of coffee consumption on inflammatory markers in either healthy human participants or patients with ischemic artery disease. An animal study suggested that coffee diets are not associated with differences in IL-6 and TNF- concentrations (19). However, in that specific study, the 2 coffee-diet groups of Wistar rats consumed the equivalent (for human consumption) of 9 and 20 cups instant coffee/d, respectively, which is an unrealistic daily pattern for humans. In contrast, an in vitro study suggested that caffeine induction of CRP in human hepatoma cell lines might require IL-6 and IL-1, but changes in SAA synthesis were minimally affected by caffeine (20). However, others suggested that IL-6 controls not only CRP but also SAA hepatic synthesis (21, 22).
In the present work, we report a positive association between coffee consumption and IL-6 concentrations. It could be hypothesized that coffee increases IL-6 synthesis, which then affects CRP and SAA production in the liver. TNF is also involved in the acute-phase protein synthesis, but it was suggested that only IL-6 can stimulate synthesis of all acute-phase proteins involved in the inflammatory response—namely CRP, SAA, fibrinogen, and others (23). Although it was suggested previously that the production of TNF-, IL-1, and IL-6 might be beneficial in response to infection, overproduction that can occur as a result of an inflammatory response might have pathologic implications (24).
Note that the association observed in the present study between coffee consumption and the inflammatory markers was linear, reaching statistical significance only when >200 mL coffee/d was consumed. Coffee intake of 200 mL represents 1 cup; therefore, the results presented here suggest that the increase in the inflammatory markers could be evident even with 2 cups coffee/d.
In the present study, the small number of participants in the categories of filtered and unfiltered coffee did not allow us to make further statistical comparisons between types of coffee. However, it should be mentioned that some investigators reported that consumption of unfiltered, but not filtered, coffee has a hypercholesterolemic effect (25). A possible explanation for this difference is that 2 of the substances in unfiltered coffee—cafestol and kahweol, which are known to have hypercholesterolemic effects (26, 27)—are largely trapped during filtration. We also observed that coffee drinking was associated with the increased likelihood of hypercholesterolemia, but we were unable to account for the differences because of the various types of coffee consumed. Elevated plasma homocysteine concentrations are also observed with the consumption of unfiltered coffee (28), but a possible proinflammatory effect of these substances remains to be elucidated.
Several limitations in the present study should be noted. Our study design was cross-sectional; therefore, assumptions for causal relations cannot be drawn. The blood sampling was performed at only one visit. Coffee drinking was evaluated by self-reports through FFQs. Thus, the information retrieved about the amount of coffee consumed could be overestimated or underestimated. Another potential limitation is that the effects of various psychological symptoms or other behavioral characteristics of the participants on relations between coffee consumption and inflammatory markers were not evaluated. However, the results about coffee consumption and human behavior or the inflammation process presented in the literature are controversial and provide no evidence for strong relations (18). Another limitation of the present study was the small number of subjects who drank >400 mL coffee, especially when that number was used in multivariate analysis.
Caffeine could be the most frequently ingested pharmacologically active substance globally. Because of its wide consumption at different amounts by most segments of the population, evaluation of the effect of coffee consumption on various cardiovascular markers should be of great importance from a public health perspective. We observed here that even moderate consumption of unfiltered coffee increases the amounts of proinflammatory markers of ischemic heart disease. These findings might suggest another pathobiological mechanism by which coffee consumption could influence coronary risk. Metabolic studies are needed to confirm our findings, with the outcome being a stronger public health message.
ACKNOWLEDGMENTS
We thank the field investigators of the ATTICA study: Natasa Katinioti (physical examination), Akis Zeimbekis (physical examination), Spiros Vellas (physical examination), Efi Tsetsekou (physical and psychological evaluation), Dina Masoura (physical examination), and Lambros Papadimitriou (physical examination). We also thank the technical team: Marina Toutouza (senior investigator and biochemical analysis), Carmen Vasiliadou (genetic analysis), Manolis Kambaxis (nutritional evaluation), Konstadina Palliou (nutritional evaluation), Constadina Tselika (biochemical evaluation), Sia Poulopoulou (biochemical evaluation), and Maria Toutouza (database management).
The contributions of the authors were as follows: AZ developed the initial idea and drafted the manuscript; DP designed the study, performed the data analysis, and interpreted the results; CP and CC designed the study and drafted the manuscript; and CS drafted the manuscript. The authors had no conflicts of interest.
REFERENCES