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Impact of Coffee Consumption on Myocardial Infarction Risk in Elderly Swedish Women

Explore the association between coffee intake and coronary heart disease risk among older Swedish women, mentioning case-control and cohort studies, antioxidant properties, and cohort analysis outcomes.

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Impact of Coffee Consumption on Myocardial Infarction Risk in Elderly Swedish Women

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  1. Coffee Consumption and Risk of Myocardial Infarction among Older Swedish Women SA Rosner, A Akesson,MJ. Stampfer, A Wolk; AJE; 2007 165:288-293

  2. Does coffee consumption increase coronary heart disease (CHD) risk? • Case control studies suggested YES • Majority of cohort studies suggested NO • Most recent cohort studies have shown both increased risk and decreased risk • Plausibility of decreased risk: • Coffee has anti-oxidant properties and improves insulin sensitivity

  3. Study Population Swedish Mammography Cohort established 1987-1990 • All women in Uppsala & Vastmanland counties, ages 40-74 were invited to participate in screening • Initial 6-page questionnaire (74% response rate) asking about: • diet • parity • age a first birth • height and weight • educational level • follow-up questionnaire (70% response rate) in 1997 • diet • multi-vitamin/supplement use • aspirin use • cigarette smoking • hormone replacement therapy use • history of diabetes, hypertension, and hypercholesterolemia • family history of CHD • physical activity

  4. Study Population • Considered as baseline 1997! • Smoking status not elicited in 1987 questionnaire and smoking is an important confounder of coffee-CHD association • Of the 38,984 women who responded to the 1997 questionnaire, 6,334 were excluded at baseline due to • history of MI, ischemic heart disease, stroke, cancer • implausible answer to any of the open-ended diet questions • implausible caloric intake • missing coffee-consumption data • or an outcome event during the first month of follow-up

  5. Diet and CHD assessment • Diet: • 96 item, self administered food frequency questionnaire (‘how often on average do you consume…”) • Validation with 4 one week diet records: spearman correlations for coffee were 0.61 • CHD (fatal and non-fatal) assessed by linkage to • Swedish Hospital Discharge Register and • Swedish Causes of Death Register (99% completeness in these registers) Diagnostic Criteria according to Swedish National Board of health and Welfare • Validation of registry revealed high sensitivity (94%) and a high positive predictive value (86%) for MI compared to other countries

  6. Cohort Analyses • Person time started accruing • Sept 15, 1997 • until date of diagnosis of MI, stroke, or cancer (=censored at time of cancer diagnosis) • date of death or • Dec 31 2002 • whichever occurred first • Time scale = calendar time for Cox proportional hazard model • 4 indicator variables for coffee consumption (0-4 cups/week=referent) {Note: too few non drinkers to compare ever/never} • Test for trend using ordinal variable

  7. Results • Person time 165,896 years (in 32,650 women with coffee consumption data) • 459 cases of MI • 391 non-fatal • 68 fatal Heavy coffee consumers: • current smokers • HRT use • Multivitamin use • education

  8. Table 1 continued….

  9. Potential Residual Confounding by Smoking?Restrict to Non-Smokers - 320 cases; 133,014 person-years of follow-up;full covariate adjustment P for trend=0.10

  10. Cox Model Stratified by Diabetes StatusNon-diabetics, 400 MI cases; 160,472 person-years

  11. Cox Model Stratified by BMInormal weight BMI=18.5-24-9 kg/m² (225 cases) and BMI >25 kg/m², (210 cases)

  12. Hypothetical Model Stratified by BMInormal weight BMI=18.5-24-9 kg/m² (225 cases) and BMI >25 kg/m², (210 cases)

  13. Validity of Exposure Measurement TP=true positive, FP= false positive, FN=false negative, TN=true negative Sensitivity= prop. of subjects truly exposed (or classified as exposed by gold standard) who are identified by test/record as exposed Sensitivity = a / (a+c) Specificity = prop. of subjects truly unexposed (or classified as unexposed by gold standard) who are identified by test/record as unexposed Specificity = d / (b+d)

  14. Validity of Exposure Measurement TP=true positive, FP= false positive, FN=false negative, TN=true negative Predictive Value pos.= prop. of subjects with test/record positive is truely exposed (or classified as exposed by gold standard) PV pos = a / (a+b) Predictive Value neg.= prop. of subjects with test/record negative is truely unexposed (or classified as unexposed by gold standard) PV neg. = d / (c+d)

  15. Example: caffeine intake Sensitivity= 62/69= 90% Specificity= 359/381= 94% Pred value pos= 62/84= 74% Pred value neg= 359/366= 98% Sensitivity= 21/23= 91% Specificity= 401/427= 94% Pred value pos= 21/47= 45% Pred value neg= 401/403= 100%

  16. Example: MI incidence Sensitivity= 360/381= 94% Specificity= 60/69= 87% Pred value pos= 360/369= 98% Pred value neg= 60/81= 74% Sensitivity= 401/427= 94% Specificity= 21/23= 91% Pred value pos= 401/403= 100% Pred value neg= 21/47= 45% Note: predictive values depend strongly on the prevalence of the exposure/ disease (i.e. the numbers in both columns), while sensitivity and specificity do not

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