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aThe Nurses' Health Study.

bThe Health Professionals' Follow-up Study.

aThe Nurses' Health Study.

bThe Health Professionals' Follow-up Study.

Figure 5.2 (a) The age-adjusted relative risk for developing diabetes during 14 years of observation (curve) among women in different classes of body weight and the distribution of incident diabetic cases in the study (bars). Based on data from Colditz et al. (33) (b) The age-adjusted relative risk for developing diabetes during 5 years of observation (curve) among men in different classes of body weight and the distribution of incident diabetic cases in the study (bars). Based on data from Chan et al. (18)

Figure 5.2 (a) The age-adjusted relative risk for developing diabetes during 14 years of observation (curve) among women in different classes of body weight and the distribution of incident diabetic cases in the study (bars). Based on data from Colditz et al. (33) (b) The age-adjusted relative risk for developing diabetes during 5 years of observation (curve) among men in different classes of body weight and the distribution of incident diabetic cases in the study (bars). Based on data from Chan et al. (18)

not among the few having the large increase in risk. In other words, most high-risk individuals will not develop diabetes at least during a foreseeable time period and many low-risk individuals will develop diabetes (the prevention paradox).

Above Which Level of Body Mass Index is the Risk Considered as High—Results from two Prospective Studies

Figure 5.2 and Table 5.2 are based on data from two well-cited prospective studies that have explored the association between BMI and the development of type 2 diabetes in the population. In the Nurses'

Health Study more than 100000 nurses participated and were followed with respect to diabetes incidence over 14 years. More than 2000 cases of diabetes were diagnosed during 1.49 million person-years of follow-up (33). In the Health Professionals' Follow-up Study, more than 50000 male health professionals participated. During 5 years of observation, 272 cases of diabetes were diagnosed (18). Both studies show a progressively increased relative risk of getting type 2 diabetes when groups with successively higher BMIs were compared to a group with the lowest BMI.

In the Nurses' Health Study, the age-adjusted relative risk of getting diabetes during a 14-year follow-up was found to be more than 90 times higher if BMI was more than 35 kg/m2 compared to less than 22kg/m2 (33). Correspondingly, the age-adjusted relative risk for diabetes after 5 years of follow-up in men was 50 times higher if BMI was 35kg/m2 or more compared to less than 23kg/m2 (18). It was also shown that the relative risk for diabetes already started to increase in the upper range of normal weight and became ever more pronounced as body weight increased. Nevertheless, looking at the problem from another angle, more than 85% of the subjects in the highest weight class (BMI > 35 kg/m2) did not develop diabetes during the observational period (14 and 5 years, respectively).

If instead of relative risk we concentrate on the distribution of new diabetes cases during the follow-up, a pattern of increasing incidence along with higher BMI emerges. However, at a point where BMI reaches 31kg/m2 in the female study and 29 kg/m2 in the male study, the number of diabetic cases starts to fall in spite of a still increasing relative risk for the disease. As stated earlier, at more extreme levels of BMI fewer individuals are to be found, in accordance with the normal distribution curve of BMI in the population. In the Nurses' Health Study, there is one large exception to this pattern. Individuals having a BMI of 35 or more presented such a large risk increase that even though they were relatively few, they generated more than 25% of all the diabetic cases. This indicates that the relation between body weight and type 2 diabetes does not strictly follow the pattern of the preventive paradox.

By choosing different cut-off points in BMI, the proportion of a population that will be designated as high-risk individuals will vary and this in turn means that the number of potential diabetes cases that could be prevented or postponed will vary (Table 5.2). A cut-off value of 27 kg/m2 would designate more than 20% of the population as high-risk individuals, to whom a treatment programme should be offered. According to these two prospective studies, between 60 and 70% of future type 2 diabetic cases would be involved and at best prevented or postponed. A less resourceful screening programme using a cut-off of 35 kg/m2 would designate 3% of the population in the Nurses' Health Study and 0.7% of the population in the Health Professionals' Study as high-risk individuals (Table 5.2). As much as 26% of future type 2 diabetic cases would be involved in such a programme according to the Nurses' Health Study. This should be compared to 9% in the male study, which also had a shorter period of observation. A screening programme where extensive treatment is to be offered to less than 3% of the population is certainly feasible. The impact of such a programme on public health would not be large but would not be insignificant either. However, the main objective of the screening programme is to provide treatment for those found to be at high risk and the impact on these high-risk individuals may be substantial (high-risk strategy).

To sum up, to achieve a large impact on public health our preventive efforts need to be concentrated on changing attitudes and behaviour in the whole population (population approach). However, it is also evident, especially from the Nurses' Health Study, that a high-risk approach is warranted in the prevention of type 2 diabetes.

The Gain of the Game—What are the Potential Benefits?

As stated above, most would agree that a high-risk strategy certainly would be beneficial to many high-risk individuals. But the question is, may such a strategy also be justified from a public health point of view? Earlier in this chapter the prevention paradox was discussed, with its emphasis on the importance of having the whole population making small changes in lifestyle. When scrutinizing the results from the Nurses' Health Study, looking at the association between BMI and the incidence of type 2 diabetes, a surprisingly large percentage (26%) of the incident cases was found in the highest BMI group ( > 35 kg/m2).

What would the gain be, at best, using a screening programme to detect all individuals in the population with a BMI of 35 kg/m2 or more, and offering these high-risk individuals a long-term weight management programme? Hypothetically, a crude calculation on the data from the Nurses' Health Study can be made. Assuming that the whole population participates in the screening procedure and that the treatment programme is 100% effective in bringing down the body weight to a BMI between 29 and 30.9 kg/m2. As shown in Table 5.3, the incidence of diabetes in the highest BMI group would be reduced by more than 70%. Converting this figure into its effect on the whole population in the study, there would be a decrease in incident diabetic cases in the population of 19% (414/2197 fewer cases). In this example 3% of the population (i.e. 3% of observed person-years in the study) would be classified as high-risk individuals. Enlarging the screening programme to all individuals having a BMI > 31 kg/ m2, and achieving the same result concerning weight management, would reduce the incidence of type 2 diabetes on a population level by 29% (628/ 2197 fewer cases), but in this alternative 8% of the population had to be offered the treatment programme. Of course, there are many good arguments questioning the basis for this calculation. The two most obvious would perhaps be the participation rate in the screening and the effectiveness of the treatment programme. However, the point to illustrate in this calculation is that in the case of obesity and type 2 diabetes a high-risk strategy really seems worthwhile.

Table 5.3 Hypothetical calculation of reduction in number of incident diabetic cases in women during 14 years of follow-up. The assumption is that an intervention successfully achieved a weight decline to a body mass index range of 29.0-30.9 kg/m2 in all individuals. The calculations are performed on data from the Nurses' Health Study (33)

Table 5.3 Hypothetical calculation of reduction in number of incident diabetic cases in women during 14 years of follow-up. The assumption is that an intervention successfully achieved a weight decline to a body mass index range of 29.0-30.9 kg/m2 in all individuals. The calculations are performed on data from the Nurses' Health Study (33)

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