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Study Title and Description
Coffee drinking is dose-dependently related to the risk of acute coronary events in middle-aged men.
Key Questions Addressed
| 1 | For [population], is caffeine intake above [exposure dose], compared to intakes [exposure dose] or less, associated with adverse effects on cardiovascular outcomes? |
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Primary Publication Information
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| Title | Coffee drinking is dose-dependently related to the risk of acute coronary events in middle-aged men. |
| Author | P Happonen,S Voutilainen,JT Salonen, |
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| Year | 2004 |
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Secondary Publication Information
There are currently no secondary publications defined for this study.
Extraction Form: Cardiovascular Design
| Question... Follow Up | Answer | Follow-up Answer | |
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| What outcome is being evaluated in this paper? | Cardiovascular |
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| What is the objective of the study (as reported by the authors)? | We examined the dose-response relationship of the consumption of caffeine-containing coffee with the incidence of acute myocardial infarction or death from CHD in a cohort of middle-aged eastern Finnish men initially free from symptomatic CHD. |
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| Provide a general description of the methods as reported by the authors. Information should be extracted based on relevance to the SR (i.e., caffeine related methods) | Study Population The Kuopio Ischaemic Heart Disease Risk Factor Study is a population-based cohort study of 2682 men aged 42, 48, 54, or 60 y at the baseline examination carried out in 1984–1989. We excluded 677 men with prevalent CHD at baseline. Of the remaining 2005 men, data on coffee consumption and smoking were available from 1971 participants. Assessment of Coffee Intake and Diet Consumption of foods and beverages was assessed with an instructed and interview-checked 4-d food recording by household measures, including cups of coffee and tea. In a subsample of 1002 men, the usual method of brewing coffee was determined during an interview of coffee-drinking habits. Dietary intake of foods and nutrients was calculated using NUTRICA software (National Public Health Institute). Measurement of Covariates A participant was defined as a current smoker if he had ever smoked on a regular basis and had smoked within the past 30 d. The lifelong exposure to smoking was estimated as the product of years smoked and the number of cigarettes, cigars, and pipefuls smoked at baseline examination. Height and weight were measured in light clothing without shoes and BMI was calculated by dividing weight in kilograms by the square of the height in meters. Alcohol intake was measured with a recall of the frequency and usual amounts of alcoholic beverages consumed in the past 12 mo. Annual income was obtained from a self-administered questionnaire. Diabetes was defined as self-reported diabetes mellitus or fasting blood glucose of 6.1 mmol/L or more. Waist-hip ratio was defined as waist girth/hip circumference measured at the trochanter major. The collection of blood specimens and assessment of blood glucose and leukocytes, serum lipids, blood pressure, and ischemia during the maximal exercise tolerance test; conditioning leisure-time physical activity and maximal oxygen uptake; and vitamin C concentration in plasma was carried out as described previously. Plasma fibrinogen concentrations were determined based on clotting of diluted plasma with excess thrombin. The rate of the ADP-induced phase of aggregation was used as a measure of platelet aggregability. Serum insulin was determined with a commercial radioimmunoassay test kit (Novo Nordisk). Ascertainment of CHD events The collection of data on and classification of possible acute myocardial infarction and coronary death (here referred to as "acute coronary events") until the end of 1992 was previously described. From 1993, data on acute coronary events were obtained by computer linkage to the national hospital discharge registry; diagnostic information was collected from the hospitals and classified using identical diagnostic criteria. There were no losses to follow-up. In the case of multiple events in the same participant, the first event was considered the endpoint. Statistical analysis All analyses were performed with SPSS version 11.5 (SPSS). Data on the following were missing: cumulative smoking "dose" (cigarette years) for 39 men, physical activity for 8, BMI for 6, blood pressure for 11, LDL cholesterol for 39, HDL cholesterol for 28, serum insulin for 58, and maximal oxygen uptake for 195. In multivariate analyses, missing values were replaced with the respective mean; for diabetes, 18 missing values were coded as nondiabetic. Mean daily coffee intake was divided into 4 categories: 0 (nondrinkers), 1 to 375 mL (light drinkers), 376 to 813 mL (moderate drinkers), and 814 mL and over (heavy drinkers). ANOVA and the chi-square test were used for testing for baseline differences in continuous and categorical variables, respectively, among the coffee intake categories. Cox proportional hazards regression was used to assess the association between coffee consumption and acute coronary events, using both the categorized and the continuous representations of coffee intake. For the latter analyses, coffee intake was scaled into cups by dividing by 125 mL, which is the coffee content in the most common cup size in this population. The appropriateness of the model was checked graphically by plotting the log[-log(survival)] curves versus log(time). Variable selection was done backward, based on change in any coffee estimate; if <10%, the variable was deleted, unless it contributed to model fit (P < 0.10 in the likelihood ratio test). To reduce multicollinearity, continuous variables were centered around their respective means; an eigenanalysis of the predictor correlation matrix did not indicate near collinearities. Modification of the coffee effect by smoking was examined by adding product terms and performing separate analyses in current smokers and nonsmokers. Statistical inference was based on 95% Wald CIs or two-sided P values. |
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| How many outcome-specific endpoints are evaluated? | 1 |
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| What is the (or one of the) endpoint(s) evaluated? (Each endpoint listed separately) | Acute coronary events (incidence of acute myocardial infarction or coronary [CHD] death |
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| List additional health endpoints (separately). 2 |
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| List additional health endpoints (separately).3 |
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| List additional health endpoints (separately).4 |
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| List additional health endpoints (separately).5 |
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| List additional health endpoints (separately).6 |
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| Clinical, physiological, other | Clinical |
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| What is the study design? | Cohort |
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| Randomized or Non-Randomized? |
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| What were the diagnostics or methods used to measure the outcome? | Objective |
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| Optional: Name of Method or short description | Method prior to 1993 discussed in another publication. From 1993, data on acute coronary events were obtained by computer linkage to the national hospital discharge registry; diagnostic information was collected from the hospitals and classified using identical diagnostic criteria. There were no losses to follow-up. In the case of multiple events in the same participant, the first event was considered the endpoint. |
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| Caffeine (general) |
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| Coffee, Chocolate, energy drink, gum, medicine/supplement, soda, tea, other? | coffee |
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| Measured or self reported? | Self-report |
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| Children, adolescents, adults, or pregnant included? | Adults |
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| What was the reference, comparison, or control group(s)? (e.g. high vs low consumption, number of cups, etc.) | Because of a j-shaped response curve, the moderate case category served as the referent group (as compared to none, light, or heavy coffee consumptions) |
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| What were the listed confounders or modifying factors as stated by the authors? (e.g. multi-variable components of models. Copy from methods) | Age, packyears of smoking, ischemia in exercise test, diabetes, income, and serum insulin concentration. Physical activity; family history of CHD; intake of alcohol, tea, saturated fat, total energy, and total water; serum glucose and plasma vitamin C concentration; and year of baseline examination did not influence estimates for coffee or model fit. |
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| What conflicts of interest were reported? | No information provided |
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| Refid | 15333732 |
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| What were the sources of funding? | Supported by research grants from the Academy of Finland (201688 and 80185, S.V.), the Ministry of Education of Finland, the city of Kuopio, and the National Heart, Lung, and Blood Institute of the United States. Additional support was provided by the Juho Vainio Foundation, the Finnish Cultural Fund/North Savo Fund, the Yrjo¨ Jahnsson Foundation, and the Finnish Foundation for Medical Science (P.H.). |
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Results & Comparisons
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