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4 reasons why BMI isn't the perfect tool for assessing individual metabolic health

Updated: Sep 3, 2021



If you have ever tried to assess your health and weight, you must have come across the term BMI (body mass index). It is important to understand what BMI represents and whether it is an accurate indicator of metabolic health. BMI is an estimate of body fat based on height and weight. It was primarily designed by mathematician Adolphe Jacques Quetelet for measuring the degree of obesity in the general population to assist the government, insurance companies, and medical professionals. BMI is not a direct measure of body fat but an easy screening method for categorizing people’s global obesity across a range of categories.


How is BMI calculated?

BMI is calculated by dividing a person’s weight in kilograms by their height in meters squared. For adults, the weight categories are the same for men and women, regardless of body types and ages. BMI for children and teenagers is calculated using the same formula as adults but is interpreted differently according to age and gender.

BMI in kg/m² is broken down into four categories:

  • Below 18.5 – Underweight

  • Between 18.5 and 24.9 – Healthy weight

  • Between 25 and 29.9 – Overweight

  • Between 30 and 39.9 – Obese


Is BMI an accurate indicator of metabolic health?

While BMI may be a rapid and inexpensive tool to screen for a person's health, it has limitations that make it less useful when used to predict an individual's health rather than as a statistical assessment for groups at a population level.


1. BMI does not take into account body fat and muscle mass.

One of the primary problems with BMI is that it does not distinguish between muscle and fat mass. Due to this, many sportsmen and bodybuilders usually appear overweight because of their higher muscle mass. Most pregnant women are also classified as overweight while being in good physical condition.

2. BMI does not account for distribution and type of body fat.

Studies indicated that the location or distribution of fat, rather than the amount of fat in our body, may increase the risk of diseases such as heart attack, stroke, and diabetes. Upper body fat around the waist and visceral fat is more associated with health issues including cardiovascular disease than lower body fat around the thighs and buttocks. For example, excess ectopic fat, which is the accumulation of lipid droplets in the liver, muscle, heart, and pancreas, increases the risk of cardio-metabolic diseases. Thus, two individuals with the same BMI might have varied risk profiles depending on their lifestyle, gender, fat type, and fat distribution on their bodies.

3. BMI does not account for ethnic differences.

BMI was essentially created based on the data from the white male population. As a result, it is not necessarily an accurate assessment of health for various ethnicities. Asians, for example, have a higher risk of weight-related disease with lower BMIs (figure 1). In a study conducted by the NHS, it was found that for a given BMI level, Asian individuals had more than double the risk of developing type 2 diabetes than their white counterparts. Therefore, lower cut-offs for BMI are needed to identify Asians who are at high risk of diabetes, hypertension, and cardiovascular diseases.




Figure 1: Association between the incidence rate of diabetes and BMI by ethnic group.


4. BMI does not take into account physical characteristics.

BMI does not take into account the fact that a person’s weight tends to grow with their height. Oxford Prof. Nick Trefethen argues thatBMI divides the weight by too large a number for short people and too small a number for tall people. As a result, short individuals are led to believe they are thinner than they are, whereas tall people are led to believe they are fatter. The professor proposed a new formula: to rectify this issue.

Other indicators of cardio-metabolic health


While BMI is an efficient screening tool, at the individual level doctors use a complex set of information and tests to assess one's health. If you suspect that you are at risk, seek a medical professional for an accurate assessment and proper treatment. However, if you want to monitor your health you can use it in conjunction with other simple measurements that can be made at home, like the following:


1. Waist circumference:

Studies have found that waist circumference is substantially and independently positively associated with type 2 diabetes risk. A study reported that a non-obese, overweight male with a waist circumference of at least 40.2 inches and a woman with a waist circumference of 34.6 inches or above have the same or greater risk of type 2 diabetes, cardiovascular diseases, or death due to cancer as an obese person.

Here's a link to how to measure your waist circumference correctly: https://www.cdc.gov/healthyweight/assessing/index.html


2. Blood pressure

People with high blood pressure or hypertension are at risk of developing heart problems and damage to the walls of the blood vessels.


3. Blood glucose level

The accumulation of extra glucose in the bloodstream is referred to as hyperglycemia or high blood sugar. The American Diabetes Association recommends that asymptomatic people over age 45 should get tested at a minimum every three years. But you might want to check your blood sugar more often if you have any of the following risk factors:

  • Being overweight

  • Having a high risk of diabetes due to family history

  • Lipid disorders i.e. high blood levels of low-density lipoprotein (LDL) cholesterol, and fats called triglycerides, or both

Blood sugar levels regularly higher than 125 mg/dL or 7 mmol/l can be an indicator of health issues.


Conclusion

BMI is a general principle used to broadly categorize a person as underweight, healthy weight, overweight, or obese based on weight and height. It is used as a screening tool to detect and do additional bio-clinical tests. It is easy to calculate, and it can steer you in the right direction to better understand where your health is and where it should be. While BMI is a great screening tool, it must be used in combination with other measures to provide a comprehensive view of a person's health.


Disclaimer: The content is not intended to be a substitute for professional medical advice, diagnosis, or treatment, and does not constitute medical or other professional advice.


References

1. Canoy, D., Boekholdt, S. M., Wareham, N., Luben, R., Welch, A., Bingham, S., Buchan, I., Day, N., & Khaw, K. T. (2007). Body Fat Distribution and Risk of Coronary Heart Disease in Men and Women in the European Prospective Investigation Into Cancer and Nutrition in Norfolk Cohort. Circulation, 116(25), 2933–2943. https://doi.org/10.1161/circulationaha.106.673756

2. Kissebah AH, Vydelingum N, Murray R, Evans DJ, Hartz AJ, Kalkhoff RK, Adams PW. Relation of body fat distribution to metabolic complications of obesity. J Clin Endocrinol Metab. 1982; 54: 254–260.

3. Yajnik, C. S., & Yudkin, J. S. (2004). The Y-Y paradox. The Lancet, 363(9403), 163. https://doi.org/10.1016/s0140-6736(03)15269-5

4. Shai I, Jiang R, Manson JE, et al. Ethnicity, obesity, and risk of type 2 diabetes in women: a 20-year follow-up study. Diabetes Care. 2006;29:1585-90.=

5. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. (2004). The Lancet, 363(9403), 157–163. https://doi.org/10.1016/s0140-6736(03)15268-3

6. Chiu, M., Austin, P. C., Manuel, D. G., Shah, B. R., & Tu, J. V. (2011). Deriving Ethnic-Specific BMI Cutoff Points for Assessing Diabetes Risk. Diabetes Care, 34(8), 1741–1748. https://doi.org/10.2337/dc10-2300

7. Trefethen, N. (2013). New BMI (New Body Mass Index). Www.People.Maths.Ox.Ac.Uk. https://people.maths.ox.ac.uk/trefethen/bmi.html

8. Zhang C, Rexrode KM, van Dam RM, Li TY, Hu FB. Abdominal obesity and the risk of all-cause, cardiovascular, and cancer mortality: sixteen years of follow-up in US women. Circulation. 2008;117:1658-67.

9. 2. Classification and Diagnosis of Diabetes. (2016). Diabetes Care, 40(Supplement 1), S11–S24. https://doi.org/10.2337/dc17-s005






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