Comments on Brønnum-Hansen: Predicting the effect of prevention of ischaemic heart disease

Brù nnum-Hansen compares the effects of different preventive strategies in four risk factors for ischaemic heart disease (IHD): smoking, high level of serum cholesterol, hypertension, and physical inactivity. He uses a mathematical model, which includes for each risk factor some background parameters: prevalence of the risk factor, relative risk (RR) between exposure groups, and a hypothetical reduction in exposure level. The aim of the calculations is that priority setting in public health policy should be based on knowledge about the effect on IHD from the different preventions. A prediction model is not better than the data on which it is based, and there are great problems with all the key parameters that Brù nnum-Hansen has selected for the ``Prevent model’ ’ . Relative risk and prevalence are related to each other because when you have chosen cut-off points in a risk factor, these two parameters will follow each other. When comparing IHD rates between extreme groups one will get a high RR, but only few subjects at risk. Thus, it is essential that the RR and prevalence used are from the same study or if different studies are used that they at least have a well-de ned exposure level, from which both parameters are calculated. Also, if extreme values are used as cut-off points, the con dence interval of the RR will be huge because few endpoints are included in the extreme group. In Brù nnum-Hansen’ s study all prevalence and RRs are obtained from different studies. For three of the risk factors, RRs are obtained from the Framingham studies and prevalence from different Danish surveys. Physical activity prevalence is obtained from a Danish survey (Danish Health Interview Survey (DHIS), 1994) and RR from a meta-analysis of Berlin and Colditz (1). These studies are incomparable and we wonder why Brù nnum-Hansen did not use data from the MONICA studies or from the Danish Health Interview Survey in 1987, which was conducted by his own institute. The latter two studies include exposure levels (for all four risk factors in MONICA, and for smoking and physical activity in DHIS) and endpoints, and Brù nnum-Hansen has actually used prevalence from MONICA in three of the risk factors in the present study. The greatest discrepancy is found in regard to physical activity. In MONICA (pooled data from 1984 ± 91 including almost 7,000 subjects), 23% of the males answered that they were sedentary, and they had a RR of 2.66 compared with the highly physically active, and 29% of the females were sedentary, with a RR of 3.06. The moderately active had RR values of 1.70 and 1.86 and a prevalence of 54% and 59% for males and females, respectively. The remaining were sedentary. The MONICA data have been summarized in a report from the Danish Heart Foundation (2) and a paper by Sjù l et al. in Scand J Med Sci Sports Exerc (3). It is obvious that not only the prevalence but also the RR is extremely different from the data that Brù nnum-Hansen used in the Prevent model. In Berlin and Colditz’ s meta-analysis the difference in IHD rates between the sedentary and the `̀ slightly’ ’ active was only 12%, which is  ve times less than in MONICA, and the prevalence of being sedentary in DHIS is about 10% (depending on age group), which is one-third of what was found in MONICA. Thus, there is an approximately 20-fold underestimation in the Prevent model in relation to physical activity with the other parameters being held constant. For unknown reasons Brù nnum-Hansen chose a scenario in which all sedentary people should increase their physical activity level to `̀ light activity’’ . If only 25% of the subjects at risk should change as in the other risk factors, the underestimation would still