Lifestyle variables and the risk of myocardial infarction in the General Practice Research Database

被引：26

作者：

Delaney J.A.C. ^{[1
,2
]}

Daskalopoulou S.S. ^{[2
,5
]}

Brophy J.M. ^{[1
,2
,3
]}

Steele R.J. ^{[4
]}

Opatrny L. ^{[2
,5
]}

Suissa S. ^{[1
,2
]}

机构：

[1] Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, ON

[2] Division of Clinical Epidemiology, McGill University Health Center, Montreal, ON

[3] Division of Cardiology, Royal Victoria Hospital, McGill University Health Center, Montreal, QC

[4] Department of Mathematics and Statistics, McGill University, Montreal, ON

[5] Division of Internal Medicine, McGill University Health Center, Montreal, ON

来源：

BMC Cardiovascular Disorders | / 7卷 / 1期

关键词：

Body Mass Index; Acute Myocardial Infarction; Multiple Imputation; Normal Body Mass Index; Body Mass Index Category;

D O I：

10.1186/1471-2261-7-38

中图分类号：

学科分类号：

摘要：

Background: The primary objective of this study is to estimate the association between body mass index (BMI) and the risk of first acute myocardial infarction (AMI). As a secondary objective, we considered the association between other lifestyle variables, smoking and heavy alcohol use, and AMI risk. Methods: This study was conducted in the general practice research database (GPRD) which is a database based on general practitioner records and is a representative sample of the United Kingdom population. We matched cases of first AMI as identified by diagnostic codes with up to 10 controls between January 1st, 2001 and December 31st, 2005 using incidence density sampling. We used multiple imputation to account for missing data. Results: We identified 19,353 cases of first AMI which were matched on index date, GPRD practice and age to 192,821 controls. There was a modest amount of missing data in the database, and the patients with missing data had different risks than those with recorded values. We adjusted our analysis for each lifestyle variable jointly and also for age, sex, and number of hospitalizations in the past year. Although a record of underweight (BMI <18.0 kg/m2) did not alter the risk for AMI (adjusted odds ratio (OR): 1.00; 95% confidence interval (CI): 0.87-1.11) when compared with normal BMI (18.0-24.9 kg/m2), obesity (BMI ≥30 kg/m2) predicted an increased risk (adjusted OR: 1.41; 95% CI: 1.35-1.47). A history of smoking also predicted an increased risk of AMI (adjusted OR: 1.81; 95% CI: 1.75-1.87) as did heavy alcohol use (adjusted OR: 1.15; 95% CI: 1.06-1.26). Conclusion: This study illustrates that obesity, smoking and heavy alcohol use, as recorded during routine care by a general practitioner, are important predictors of an increased risk of a first AMI. In contrast, low BMI does not increase the risk of a first AMI. © 2007 Delaney et al; licensee BioMed Central Ltd.

引用

共 30 条

[11]

The Use and Interpretation of Anthopometry. Report of WHO Expert Committee, WHO Technical Report Series 854 Geneva: World Health Organization, (1995)

[12]

Moons K.G., Donders R.A., Stijnen T., Harrell Jr. F.E., Using the outcome for imputation of missing predictor values was preferred, J Clin Epidemiol, 59, pp. 1092-1101, (2006)

[13]

Schafer J.L., Multiple imputation: A primer, Stat Methods Med Res, 8, pp. 3-15, (1999)

[14]

Minutello R.M., Chou E.T., Hong M.K., Bergman G., Parikh M., Iacovone F., Wong S.C., Impact of body mass index on in-hospital outcomes following percutaneous coronary intervention (report from the New York State Angioplasty Registry), Am J Cardiol, 93, pp. 1229-1232, (2004)

[15]

Powell B.D., Lennon R.J., Lerman A., Bell M.R., Berger P.B., Higano S.T., Holmes Jr. D.R., Rihal C.S., Association of body mass index with outcome after percutaneous coronary intervention, Am J Cardiol, 91, pp. 472-476, (2003)

[16]

Reeves B.C., Ascione R., Chamberlain M.H., Angelini G.D., Effect of body mass index on early outcomes in patients undergoing coronary artery bypass surgery, J Am Coll Cardiol, 42, pp. 668-676, (2003)

[17]

Diercks D.B., Roe M.T., Mulgund J., Pollack Jr. C.V., Kirk J.D., Gibler W.B., Ohman E.M., Smith Jr. S.C., Boden W.E., Peterson E.D., The obesity paradox in non-ST-segment elevation acute coronary syndromes: Results from the Can Rapid risk stratification of Unstable angina patients Suppress ADverse outcomes with Early implementation of the American College of Cardiology/American Heart Association Guidelines Quality Improvement Initiative, Am Heart J, 152, pp. 140-148, (2006)

[18]

Kragelund C., Hassager C., Hildebrandt P., Torp-Pedersen C., Kober L., Impact of obesity on long-term prognosis following acute myocardial infarction, Int J Cardiol, 98, pp. 123-131, (2005)

[19]

Dudas K.A., Wilhelmsen L., Rosengren A., Predictors of coronary bypass grafting in a population of middle-aged men, Eur J Cardiovasc Prev Rehabil, 14, pp. 122-127, (2007)

[20]

Calle E.E., Thun M.J., Petrelli J.M., Rodriguez C., Heath Jr. C.W., Body-mass index and mortality in a prospective cohort of U.S. adults, N Engl J Med, 341, pp. 1097-1105, (1999)

← 1 2 3 →