Definition Of Obesity And Bmi Cutoff Points

The WHO (30) defines obesity as a condition with excess body fat to the extent that health and well-being are adversely affected. The body mass index is used for the purpose of classification. The suggested cutoff points for overweight (BMI >25 kg/m2) and obesity (BMI >30 kg/ m2) are based on observational studies on the relationship between morbidity and mortality and BMI primar ily in Caucasians from Europe and the United States. In Caucasians, a BMI of 30 kg/m2 corresponds to a BF% of ~25% in young adult males and ~35% in young adult females (29), although there are variations around those estimates.

In cross-country or cross-ethnic group comparisons on obesity, two factors should be kept in mind: the body composition part, i.e., the level of body fatness; and the health risks related to overweight/obesity. Because of the differences in the BMI/BF% relationship among ethnic groups, it is clear that a general BMI cutoff point can be questioned. More specifically, a comparison between groups should be based on comparable levels of body fatness, which could be at different levels of BMI. Figure 4 shows calculated BMI cutoff points for obesity in different ethnic groups having the same body fat percent (40). According to this, the cutoff points for obesity might be considerably lower in many ethnic groups than the advocated level of 30 kg/m2 in Caucasians. The main limitation of the data in Figure 4 is that BF% in the different populations was determined using different techniques, of which the validity in the population under study is not sure. For a comparative study on the relationship between BF% and BMI among (ethnic) groups, a prerequisite is that the reference method to determine body fat percent is valid. As discussed earlier in this chapter, such a method should ideally be a multicompartment model or, alternatively, deuterium oxide dilution.

A recent study in Singapore using a four-compartment model clearly showed differences in BMI/BF% relationship among Chinese, Malays, Indians, also in comparison to Caucasians (39). The cutoff point that was calculated based on this study was 27 kg/m2, which is similar to that suggested by Guricci et al. (22) and currently used in Indonesia. This BMI cutoff point is slightly higher than the one suggested by Ko et al. (41) for Hong Kong Chinese, which is 26 kg/m2. Unfortunately, in the study of Ko et al. (41) BF% was assessed by impedance. Although the methodology was validated against DXA, no correction was made for the slight overestimation of impedance against DXA. Moreover, DXA cannot be regarded as a reference technique, and there are numerous studies showing either an under- or overestimation (9,42,43) of BF% from DXA, in some studies also ethnic dependent (9,44). Studies on the relationship between BMI and BF% from impedance were published earlier (45,46). The validity of those studies remains obscure, BIA is too much affected by body build factors (that may differ among groups) to be a reliable reference method. A study showing that the relationship between weight and impedance among some different ethnic groups has similar slopes has been published (47), but this study does not allow any conclusion as the different groups may have differed in body composition. More information on the relationship between BMI and BF% in different (ethnic) groups is needed and ideally multi-centre studies have to be carried out with strict standardisation of methodologies. Those studies should include parameters of body build to enable explanations of possible differences and perhaps to enable corrections of BMI for differences in body build. Implementation of these lower BMI cut-off points for obesity in the population will result in a much

Figure 4 Adjustments to be made in BMI to reflect equal levels of body fat percent compared to Caucasians of the same age and sex. (From Refs. 39, 40.)

Figure 4 Adjustments to be made in BMI to reflect equal levels of body fat percent compared to Caucasians of the same age and sex. (From Refs. 39, 40.)

higher prevalence of obesity in many countries/ethnic groups, whereas in other groups the prevalence might become lower.

However, a lowering of cutoff point is not appropriate if there would be no elevated health risk at those lower levels of body mass index. This second aspect should also be carefully studied among different ethnic groups. It is known that in several Asian populations, cardiovascular morbidity and mortality are high and that the risk factors for CVD are high already at very low levels of BMI. For example, Ko et al. (48) showed that Hong Kong Chinese have at a very low BMI a high odds ratio for diabetes, hypertension, dyslipide-mia, and albuminuria. Similarly, Figure 5 shows that in Singapore, the odds ratio of having at least one CVD risk factor is high at very low levels of BMI (49,50). Currently the International Obesity Task Force (IOTF) (51) is discussing a revision of BMI-based cutoff points for obesity in the Asian region, suggesting a BMI cutoff as low as 23 kg/m2 for overweight and a BMI of 25 kg/m2 for obesity. It seems necessary that redefining cutoff points should be extended to other ethnic groups as well. In the earlier-mentioned meta-analyses (40), it was shown not only that there are differences among clearly different ethnic groups (as Caucasians and Asians), but also that within the "same" ethnic group there might be differences in the BMI/BF% relationship. For example, American Cau-

Figure 5 Risk factors: elevated serum cholesterol (>6.2 mmol/L), elevated total cholesterol/HDL cholesterol ratio (>4.4), elevated triglyceride (>1.8 mmol/L), elevated blood pressure (>140/90mmHg), diabetes mellitus (OGGT >11.1 mmol/L). Data are corrected for age, ethnicity, educational level, occupation, physical activity, smoking, and waist/hip ratio. (From Ref. 20.)

Figure 5 Risk factors: elevated serum cholesterol (>6.2 mmol/L), elevated total cholesterol/HDL cholesterol ratio (>4.4), elevated triglyceride (>1.8 mmol/L), elevated blood pressure (>140/90mmHg), diabetes mellitus (OGGT >11.1 mmol/L). Data are corrected for age, ethnicity, educational level, occupation, physical activity, smoking, and waist/hip ratio. (From Ref. 20.)

casians apparently have a lower body fat percent at the same BMI than do Caucasians in Europe (33,40). As both the American and the European data came from various laboratories, most of them using densitometry, it is unlikely that this difference is due to differences in methodology. The black populations groups studied by Luke et al. (46) differed as well, which is confirmed by a study of Long et al. (52). Also, Northern and Southern Chinese differ (38,40), a difference that could be ascribed to body build differences. Wagner et al. (16), in a recent review also stress the need for in-depth studies in blacks to avoid biased estimations of obesity prevalence.

With regard to the relationship between BMI and body composition in different ethnic groups, there are two other interesting points to consider. There is first the definition of underweight. Many Asian populations have a large number of people with a BMI lower than 20 kg/m2 or even lower than 18. 5 kg/M2, the BMI value that is suggested by the WHO as cutoff for underweight (30). Those low BMI values are hardly prevalent in adult Western (Caucasian) populations. In the recent (1998) National Health Survey in Singapore, as many 11% of the females and 7% of the males had a BMI below 18.5 kg/m2. The proportion of Singaporeans with a BMI <20 kg/km2 were 25% and l5% for females and males, respectively (50). There is no reason at all to assume that undernutrition is epidemic among Singaporeans. This suggests that "healthy" BMI values in those populations could be shifted to the left, causing on the one hand higher obesity prevalences, and on the other hand lower undernutrition prevalences.

A second point is that if some ethnic groups have higher body fat percent at a given BMI, their fat-free mass will be lower, resulting in lower metabolic rates for a given weight and height (age and sex). This may shed new light on some reported low values of resting metabolic rate and total daily energy expenditure in certain population groups (53).

Keep Your Weight In Check During The Holidays

Keep Your Weight In Check During The Holidays

A time for giving and receiving, getting closer with the ones we love and marking the end of another year and all the eating also. We eat because the food is yummy and plentiful but we don't usually count calories at this time of year. This book will help you do just this.

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