Coffee Consumption and Risk of Myocardial Infarction among Older Swedish Women

SA Rosner, A Akesson,MJ. Stampfer, A Wolk;

AJE; 2007 165:288-293

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

Study PopulationSwedish 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

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

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

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

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

Table 1 continued….

Crude RR

1

1.05

0.85

0.82

0.87

Potential Residual Confounding by Smoking? Restrict to Non-Smokers - 320 cases; 133,014 person-years of follow-up;full covariate adjustment

Coffee Consumption RR§ 95% CI§

0-4 / week 1 -

5-7 / week 0.90 0.52, 1.56

2-3 / day 0.62 0.37, 1.03

4-5 / day 0.58 0.34, 1.01

>6 / day 0.80 0.42, 1.52

P for trend=0.10

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

Coffee Consumption RR§ 95% CI§

0-4 / week 1 -

5-7 / week 0.71 0.42, 1.20

2-3 / day 0.57 0.35, 0.91

4-5 / day 0.57 0.35, 0.94

>6 / day 0.55 0.31, 0.98

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

Normal weight Overweight/Obese

Coffee Consumpt

ionRR§ 95% CI§ RR§ 95% CI§

0-4 / week 1 - 1 -

5-7 / week 0.88 0.41, 1.89 0.68 0.34, 1.37

2-3 / day 0.77 0.38, 1.56 0.49 0.26, 0.94

4-5 / day 0.79 0.38, 1.63 0.50 0.25, 0.98

>6 / day 0.56 0.24, 1.34 0.64 0.30, 1.37

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

Normal weight Overweight/Obese

Coffee Consumpt

ionRR§ 95% CI§ RR§ 95% CI§

0-4 / week 1 - 1 -

5-7 / week 0.98 0.60, 1.89 0.75 0.45, 1.47

2-3 / day 1.01 0.92, 1.25 0.59 0.26, 0.90

4-5 / day 1.02 0.85, 1.50 0.45 0.25, 0.98

>6 / day 1.10 0.99, 1.34 0.54 0.30, 0.98

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)

Recorded exposure

True exposure (gold standard) Total

+ -

+ a (TP) b (FP) a+b

- c (FN) d (TN) c+d

total a+c b+d a+b+c+d

Validity of Exposure Measurement

Recorded exposure

True exposure (gold standard) Total

+ -

+ a (TP) b (FP) a+b

- c (FN) d (TN) c+d

total a+c b+d a+b+c+d

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)

Example: caffeine intake

Recorded coffee drinker

True coffee drinker (gold standard= urine metabolite levels)

Total

+ -

+ 62 22 84

- 7 359 366

total 69 (15%) 381

(85%)

450

Sensitivity= 62/69= 90%

Specificity= 359/381= 94%

Pred value pos= 62/84= 74%

Pred value neg= 359/366= 98%

Recorded coffee drinker

True coffee drinker (gold standard= urine metabolite levels)

Total

+ -

+ 21 26 47

- 2 401 403

total 23

(5%)

427

(95%)

450

Sensitivity= 21/23= 91%

Specificity= 401/427= 94%

Pred value pos= 21/47= 45%

Pred value neg= 401/403= 100%

Example: MI incidence

Recorded MI

True MI Total

+ -

+ 360 9 369

- 21 60 81

total 381 (85%) 69

(15%)

450

Sensitivity= 360/381= 94%

Specificity= 60/69= 87%

Pred value pos= 360/369= 98%

Pred value neg= 60/81= 74%

Recorded MI

True MI Total

+ -

+ 401 2 403

- 26 21 47

total 427

(95%)

23

(5%)

450

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