Copyright © 2003 by the European Society of Cardiology.
Clinical research
Re-assessing the contribution of serum total cholesterol, blood pressure and cigarette smoking to the aetiology of coronary heart disease: impact of regression dilution bias
a Department of Primary Care and Population Sciences, Royal Free and University College Medical School, London, UK
b Department of Community Health Sciences, St George’s Hospital Medical School, London, UK
* Correspondence to: Dr J. R. Emberson, Royal Free and University College Medical School, Primary Care and Population Sciences, Rowland Hill Street, London NW3 2PF, UK. Tel: +44 20 7830 2239; Fax: +44 20 7794 1224
E-mail address: j.emberson{at}pcps.ucl.ac.uk
Received 8 May 2003; revised 1 July 2003; accepted 9 July 2003
Abstract
Aims To estimate the combined contribution of serum total cholesterol, blood pressure and cigarette smoking to coronary heart disease (CHD) risk after adjustment for regression dilution bias.
Methods and results Six thousand, five hundred and thirteen middle-aged British men without CHD were followed for major CHD events over 10 years. The population attributable risk fraction (PARF) was predicted for a range of risk factor thresholds before and after adjustment for regression dilution of serum total cholesterol and blood pressure. Defining ‘low-risk’ individuals as being in the bottom tenth of the population distributions of serum total cholesterol (<5.2mmol/l) and diastolic blood pressure (<70mmHg) and a non-cigarette smoker, the PARF was 75%, increasing to 86% after adjustment for regression dilution. Regardless of the threshold criteria chosen, the PARF was substantially greater than 65% before adjustment for regression dilution and greater than 75% after adjustment. Exclusion of ex-smokers and passive smokers from the low-risk group increased estimates further. Adjustment for other coronary risk factors had little effect on the results.
Conclusions At least 80% of major CHD events in middle-aged men can be attributed to the three strongest risk factors. Population-wide control of these factors is crucial for effective CHD prevention.
Key Words: Coronary heart disease • Risk factor assessment • Population attributable risk fraction • Regression dilution bias • Logistic regression
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