The subjects were selected from the Danish Diet, Cancer and Health study, an ongoing prospective cohort study . Between December 1993 and May 1997, 160,725 individuals aged 50 to 64 years, born in Denmark, living in the Copenhagen and Aarhus areas were invited to participate in the study. A total of 57 053 persons accepted the invitation. At enrolment, detailed information on diet, lifestyle, weight, height, reproduction status, medical treatment, and other socio-economic characteristics and environmental exposures were registered. The questionnaire is described in detail elsewhere . Blood, urine, and fat tissue was sampled and stored at -150°C.
A case-cohort study was designed using incident ACS, which includes unstable angina pectoris, fatal and non-fatal myocardial infarction as the outcome [14, 15]. Information on the disease endpoint was obtained by linkage with central Danish registries via the unique identification number assigned to all Danish citizens. Hospital records of potential cases were retrieved for participants who were registered with a first-time discharge diagnosis of ACS (ICD-8 codes 410–410.99, 427.27 and ICD-10 codes I20.0, I21.×, I46.×) in The Danish National Register of Patients, which covers all hospital discharge diagnoses since 1977 and all discharge diagnosis from out-patient clinics since 1995 (until Jan 1, 2004). Cases were classified according to symptoms, signs, coronary biomarkers, ECGs and/or autopsy findings in accordance with the current recommendations of the American Heart Association and the European Society of Cardiology (AHA/ECS) .
Further, linkage to the Cause of Death Register allowed for identification of participants with ACS coded as a primary or secondary cause of death (until Jan 1, 2004). In total, 1144 cases of ACS were identified and validated. The cohort sample included 1816 participants selected as a random sample of the entire cohort. This sample included 36 ASC cases. 183 samples were excluded because the last cases were identified after the time of sample retrieval or due to missing blood samples, and two participants were excluded due to failed genotyping. Thirteen cases and 13 controls were excluded due to lack of information on questionnaire data, leaving 1031 case subjects and 1703 participants in the sub-cohort including 34 cases who were also sub-cohort members for the analysis.
Alcohol, NSAID, and other lifestyle variables
In the food-frequency questionnaire, alcohol intake was recorded as the average frequency of intake of six types of alcoholic beverage over the preceding year: the frequency of consumption of three strengths of beer was recorded in bottles (330 ml), wine in glasses (125 ml), fortified wine in drinks (60 ml) and spirits in drinks (30 ml). The predefined responses were in twelve categories, ranging from "never" to "eight or more times a day". The alcohol content was calculated as follows: one bottle of light beer, 8.9 g ethanol; regular beer, 12.2 g ethanol; strong beer, 17.5 g ethanol; one glass of wine, 12.2 g ethanol; one drink of fortified wine, 9.3 g ethanol; and one drink of spirits, 9.9 g ethanol.
The lifestyle questionnaire included the following question regarding use of NSAID: Have you taken more than one pain relieving pill per month during the last year? If the answer was yes, the participant was asked to record how frequent they took each of the following types of medications: "Aspirin", "Paracetamol", "Ibuprofen", or "Other pain relievers". The latter category included NSAID preparations other than aspirin and ibuprofen. Based on all records, we classified study subjects according to their use of "any NSAID" (≥ 2 pills per month during one year) at baseline.
Data on hormone replacement therapy (HRT) was obtained from the lifestyle questionnaire and the participants were classified according to use HRT (never, past or current). Smoking status was recorded in three categories: never smoker, current smoker and former smoker.
At the study clinics, anthropometric measurements, including height and weight were obtained by professional staff members. BMI was calculated as weight (kg) per height squared (m).
Blood sampling and storage
From each non-fasting participant a total of 30 ml blood was collected in citrated (2 × 10 ml) and plain (1 × 10 ml) Venojects. Plasma, serum, lymphocytes, and erythrocytes were isolated and frozen at -20°C within 2 hours. At the end of the day of collection, all samples were stored in liquid nitrogen at -150°C.
DNA was isolated from frozen lymphocytes as described by Miller et al . Generally, 100 μg DNA were obtained from 107 lymphocytes. PPAR2γ Pro12Ala (rs1801282) was genotyped as previously described . Laboratory staff was blinded to the case/subcohort status of the subjects. Twenty ng of DNA were used for genotyping in 5 μl containing 1× Mastermix (Applied Biosystems, Nærum, Denmark), 100 nM probes, and 900 nM primers. Controls were included in each run, and repeated genotyping of a random 10% subset yielded 100% identical genotypes.
Measurement of blood lipids
Total Cholesterol and other blood lipids were measured on an Advia 1650 from Bayer Diagnostics, NY, USA. For total cholesterol kits ref. 01482198 were used. The interseriel variation was 1.1%. For triglyceride kits ref. 09580156 was used with an interserial variation of 4.5%. For HDL-cholesterol kits ref. 08058065 with an interseriel variation of 2.0%. LDL-cholesterol was calculated by Friedewald's formula.
We used a case-cohort design with a sub-cohort of 1703 subjects drawn randomly, stratified on gender from the whole cohort with 57,053 subjects. A Cox proportional hazards model was used for analyses, as if the full cohort were included, modified by a weighting scheme described  and using a robust variance estimate. In the case-cohort design, weights are assigned to each subject, one for cases and N/n for non-cases in the sub-cohort, where N (n) is the number of non-cases in the cohort (sub-cohort). For women, N/n = 29,289/797 and for men, N/n = 26,012/906.
Age was used as the time scale in the Cox regression model. All models were sex specific and adjusted for baseline values of established risk factors for ACS including status of BMI, HRT, smoking status, NSAID use and alcohol intake.
We investigated possible interactions between polymorphism and alcohol intake, NSAID use, smoking status and BMI using the likelihood ratio test. Analyses were done using Stata version 9.2 (Stata Corporation, College Station, Texas, US).
Diet, Cancer and Health and the present sub-study were approved by the regional Ethics Committees on Human Studies in Copenhagen and Aarhus (File nos.(KF)11-037/01 and HKF-01-345/93), and by the Danish Data Protection Agency.