![]() ![]() Other adipose tissue depots such as the deep subcutaneous abdominal adipose tissue, which could destabilise metabolism, are more in Asian Indians than white Caucasians 14. Excess liver fat may occur in non-obese south Asians as well, and has been shown to be almost double the amount recorded in Caucasians when matched for weight and is associated strongly with insulin resistance 9, 13. 1, reach similar conclusions in South Korean populations, using body fat as comparator.Īsians, and South Asians in particular, have more severe inflammation, insulin resistance, and liver fat even when non-obese by BMI standards used for Caucasians 9, 12. In a sample of 1513 Hong Kong Chinese men and women, the risk of having diabetes mellitus or hypertension was at lower BMI or waist circumference levels in Chinese than in Caucasians 11. In such situations where excess body fat predominates but body weight is not very high relative to Caucasians, BMI may fail to classify obesity or may underestimate it 2, 10. At a given BMI, the amount of total body fat and ectopic fat is different between Caucasians and Asians 8, 9. Rising obesity seems to be a main contributor and dysmetabolic state is mainly linked with excess body fat and ectopic fat deposition in various organs 7. In 2017, 72.9 million Asian Indians in India (prevalence 8.8%) had diabetes and 24 million had prediabetes 6. Obesity-related diseases, primarily type 2 diabetes in India and South Korea pose grim picture in 2016, 4.8 million 30 y or older South Koreans (prevalence 13.7%) had diabetes, and about a quarter of population had prediabetes 5. Moreover, the study provides confidence to further research a very important health issue in South East Asian population. 1 is important as it validates the use of BMI to study at least the Asian Indian and South Korean populations. These thresholds are lower than the current BMI cut-offs applicable to Caucasian populations. 1 calculated BMI thresholds for South Korean males and females, respectively, as 22 and 18 kg/m 2 for overweight and 26 and 23 kg/m 2 for obesity. Finally, using available percent body fat cut-offs and cardiometabolic risk factors, Hood et al. But also, there was a segment of Asian Indian population that was smaller in weight as well as height compared to South Korean population. Next, they used the Korean National Health and Nutrition Examination Survey (KNHANES) data and observed an overlap between South Korean and Asian Indian population for weight and height. Hence, it would be appropriate to use current formula for calculation of BMI in Asian Indian population. 1 concluded that BMI, as defined, does normalise weight for height in Asian Indians. Even the tribal population, known for its smaller body size and stature compared to general population, showed similar scaling. ![]() 1 used a dataset of 43,880 adult Asian Indian males of age 15–54 y, including 5549 members of various tribes to conclude that weight does scale close to 2 (squared) in this geographically, socio-economically, culturally and ethnically diverse population. between Asian Indians and South Koreans)? and (3) Do BMI thresholds for overweight and obesity for South Koreans differ from those for Caucasians?” In this issue of the journal, a team of researchers 1 including obesity researchers, mathematicians and anthropologist asked following three questions: “(1) Does weight scale to height squared in Asian Indians? (2) Does the weight-height relationship differ within different Asian populations (i.e. This assumption, as well as the thresholds for defining overweight (BMI between 25 to <30 kg/m 2) or obesity (BMI ≥ 30 kg/m 2) have been derived from studying Caucasian population, hence may or may not apply to various other groups globally. Hence, to adjust for the proportion between height and weight, the use of BMI assumes that in a given population, weight scales to height squared. It is obvious that weight and height are linked. Body mass index (BMI, ratio of height and weight, expressed as kg/m 2) is widely used to define overweight and obesity across many countries, populations, races and ethnicities. ![]()
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