Recently, my government has increased it’s focus on its citizens adopting a healthy lifestyle. Today, I decided to look into one metric that is commonly used to determine a population’s health.
What is BMI?
Body Mass Index (BMI) is a person’s weight in kilograms divided by the square of height in meters. A high BMI can be an indicator of high body fatness. BMI can be used to screen for weight categories that may lead to health problems but it is not diagnostic of the body fatness or health of an individual.
What is it used for?
BMI is mainly used to assess weight status of a population. It is a simple screening tool to estimate a person’s body fat, but should be used in conjunction with other body composition tests before a diagnosis is to be made. This is because BMI is unable to discern between body fat percentage and lean mass.
How accurate is it?
This is a tricky question to answer. It’s accuracy differs between populations.
For example, in the USA and Singapore, the use of BMI actually under-diagnoses the prevalence of obesity.
In this study, it was observed that the use of BMI underdiagnosed obesity by 30%!
Accuracy of Body Mass Index to Diagnose Obesity In the US Adult Population
BMI-defined obesity (≥ 30 kg/m2) was present in 21% of men and 31% of women, while BF %-defined obesity was present in 50% and 62%, respectively.
Our findings also suggest that the magnitude of the obesity epidemic may be greatly underestimated by the use of BMI as the marker of obesity 35. In our results, BMI showed an unacceptable low sensitivity for detecting body fatness, with more than half of obese subjects (by body fat measurement) being labeled as normal or overweight by BMI. The true prevalence of obesity might be strikingly higher than that estimated by BMI.
In Singapore, it was observed that the accuracy of BMI differs between ethnic groups.
The paradox of low body mass index and high body fat percentage among Chinese, Malays and Indians in Singapore
RESULTS: Compared with body fat percentage (BF%) obtained using the reference method, BF% for the Singaporean Chinese, Malays and Indians were under-predicted by BMI, sex and age when an equation developed in a Caucasian population was used. The mean prediction error ranged from 2.7% to 5.6% body fat. The BMI/BF% relationship was also different among the three Singaporean groups, with Indians having the highest BF% and Chinese the lowest for the same BMI. These differences could be ascribed to differences in body build. It was also found that for the same amount of body fat as Caucasians who have a body mass index (BMI) of 30 kg/m2 (cut-off for obesity as defined by WHO), the BMI cut-off points for obesity would have to be about 27 kg/m2 for Chinese and Malays and 26 kg/m2 for Indians.
If obesity is defined as excess body fat rather than excess weight, the obesity cut-off point for Singaporeans should be 27 kg/m2 instead of 30 kg/m2. The lowering of the cut-off point for obesity would more than double the prevalence figures in Singapore.
In addition, the study authors also noted that the use of BMI underdiagnosed the prevalence of obesity in Singapore by at least 10%.
Generally, if the cut-off point for obesity in Singapore were lowered to 27 kg/m2, this would have immense impact on the prevalence of obesity among the adult Singapore population. Compared to a BMI cut-off point of 30 kg/m2 the prevalence would increase in females from 6.5% to 15.4% and in males from 5.2% to 17.3%.
Interestingly, it is the opposite for Korea. The use of BMI actually over-diagnosed obesity.
Diagnostic Performance of Body Mass Index Using the Western Pacific Regional Office of World Health Organization Reference Standards for Body Fat Percentage
In the present study, obesity was identified in 38.7% of men and 28.1% of women using body mass index (≥25 kg/m2) and in 25.2% of men and 31.1% of women using body fat percentage. A body mass index cut-off ≥25 kg/m2 had high specificity (89%, men; 84%, women) but poor sensitivity (56%, men; 72%, women).
On the basis of BF%, 25.2% of men and 31.1% of women were classified as obese in the present study compared to 50% of men and 62% of women in American populations (10). Thus, BF% better reflects the current status than population-specific cut-off points for BMI for international comparisons of the prevalence of obesity. The prevalence of BF%-defined obesity was higher in women than in men in Korea, which suggests that Korean women have less lean mass than do Korean men.
What is the significance of BMI?
As mentioned earlier it is mainly used a health indicator of a population but not an individual.
High and low BMI have been correlated with increased mortality rates. However, the increased risk of mortality observed in underweight people could at least partly be caused by residual confounding from prediagnostic disease. i.e. It’s a reverse causation, people are underweight due to their pre-existing conditions (eg. cancer).
An increase in BMI has been correlated with an increased risk for a myriad of diseases such as heart disease and diabetes.