The body mass index (BMI) is a widely used metric for categorizing individuals based on their weight relative to their height. is calculated by dividing a person's weight in kilograms by the square of their height in meters. Despite its widespread use, BMI has several limitations affecting its accuracy and utility in clinical and research settings. In contrast, the body roundness index (BRI) has been proposed as an alternative to BMI to provide a more accurate representation of body shape. This essay critically evaluates the BMI and BRI, considers their strengths and weaknesses, and includes links to calculators.
What is the Body Mass Index (BMI)?
Body mass index (BMI) is calculated as weight in kilograms divided by height in meters squared (kg/m²). The World Health Organization (WHO) classifies BMI into several categories: underweight (BMI < 18.5), normal weight (18.5 ≤ BMI < 24.9), overweight (25 ≤ BMI < 29.9), and obesity (BMI ≥ 30) (World Health Organization, 2020). The CDC provides an adult BMI calculator. BMI graphic © Elnur/Shutterstock.com.
Strengths of BMI
BMI is popular due to its simplicity and cost-effectiveness. It is a straightforward measure that can be easily calculated without requiring specialized equipment, making it accessible for large-scale epidemiological studies and routine clinical assessments (Daniels, 2009). It provides a quick, non-invasive method to estimate potential health risks, such as cardiovascular diseases and type 2 diabetes, based on body weight. Additionally, BMI has been instrumental in tracking the global obesity epidemic, providing a standardized measure that can be used internationally (Bray, 2023).
Limitations of BMI
However, BMI has significant limitations that undermine its effectiveness as a measure of body fat and health risk. One of the primary criticisms is that BMI does not account for body fat distribution. This is crucial because fat distribution, particularly visceral fat, predicts metabolic and cardiovascular risks more accurately than overall body fat (Bray, 2023; Gonzalez et al., 2017). For instance, individuals with the same BMI can have vastly different health outcomes depending on whether their fat is distributed around the abdomen or the hips (Després, 2012).
Another limitation is that BMI does not differentiate between muscle and fat mass. This can lead to misclassification, particularly in individuals with high muscle mass, such as athletes, who may be categorized as overweight or obese despite having low body fat (Després, 2012; et al., 1986; Romero-Corral et al., 2008). Conversely, older adults may have a normal BMI but high body fat due to muscle loss, a condition known as sarcopenic obesity, which BMI fails to identify (Gonzalez et al., 2017). BMI does not adjust for body composition differences associated with gender (Prentice & Jebb, 2001).
BMI also fails to provide insights into obesity's heterogeneity. It does not consider genetic, metabolic, physiological, or psychological factors that contribute to obesity, limiting its utility in understanding the condition's complex nature (Bray, 2023). This lack of specificity can lead to inadequate or inappropriate treatment plans for individuals with different obesity phenotypes (Müller et al., 2016).
Measurement Errors and Misclassification
The accuracy of BMI is further compromised when based on self-reported height and weight, which are often inaccurate. Studies have shown that self-reported BMI tends to underestimate actual BMI, leading to misclassifying individuals into incorrect weight categories (Gosse, 2014). This misclassification can skew research findings and public health policies, as the true prevalence of obesity may be underreported.
What is the Body Roundness Index (BRI)?
The Body Roundness Index (BRI) is a relatively new anthropometric measure to predict body fat and visceral adipose tissue. It has been proposed as a potentially superior alternative to traditional indices like the BMI, Waist Circumference (WC), and Waist-to-Height Ratio (WHtR) for predicting various health conditions, including metabolic syndrome (MetS) and hypertension. WebFCE provides a free adult BRI calculator.
The BRI runs from 1-20 (1 = narrow, 20 = more rounded). Zhang and colleagues (2024) found individuals with BRI scores of 6.9 or higher — representing the roundest body shapes — had the greatest risk of death from cancer, heart disease, and other illnesses. Their overall risk of mortality was nearly 50 percent higher than those with BRI scores between 4.5 and 5.5, which fell within the sample's midrange. Meanwhile, those with BRI scores between 5.46 and 6.9 had a 25 percent higher risk than the midrange group.
Those with the least round body shapes were also at increased risk. People with BRI scores below 3.41 faced a 25 percent higher mortality risk compared to those in the midrange, according to the study.
Strengths of the Body Roundness Index
Unlike BMI, RI includes waist circumference, which is a key indicator of central adiposity. This allows for a better assessment of the health risks associated with fat distribution (Nahas, 2019).
One of the primary strengths of the BRI is its ability to predict metabolic syndrome (MetS) and hypertension with a high degree of accuracy (Rico-Martin et al., 2020). According to a systematic review and meta-analysis, the BRI demonstrated a higher area under the curve (AUC) for predicting MetS compared to BMI, Waist-to-Hip Ratio (WHR), A Body Shape Index (ABSI), and Body Adiposity Index (BAI).
This suggests that BRI is a better indicator of MetS than these traditional measures. Additionally, the BRI showed good discriminatory power for MetS in diverse populations, with AUC values greater than 0.7 (Rico-Martin et al., 2020).
Similarly, another study found that the BRI had a higher AUC for predicting hypertension compared to ABSI and was comparable to BMI, WC, and WHtR (Calderón‐García et al., 2021).
This indicates that BRI is a robust predictor of hypertension, making it a valuable tool for early diagnosis and intervention.
Moreover, the BRI has been shown to correlate significantly with various cardiovascular risk factors. For instance, in a study involving South African rural young adults, BRI was significantly correlated with insulin levels, homeostatic model assessment (HOMA)-β, and triglycerides (TG; Nkwana et al., 2021). This further underscores its utility in assessing cardiovascular health.
Limitations of the Body Roundness Index
Despite its strengths, the BRI is not without limitations. One of the main drawbacks is that its predictive power for MetS and hypertension is not significantly different from that of WC and WHtR. The differences in AUC values between BRI and these traditional measures were statistically non-significant (Calderón‐García et al., 2021; Rico-Martin et al., 2020). This raises questions about the added value of BRI over more established indices.
Another limitation is the variability in its predictive accuracy across different populations. For example, the pooled AUCs for BRI were higher in non-Chinese populations compared to Chinese populations for all indices (Rico-Martin et al., 2020). This suggests that the BRI may not be universally applicable and require population-specific adjustments.
Additionally, while the BRI is a good predictor of certain health conditions, it is not the best. For instance, WC and WHtR performed best when screening for MetS and hypertension. While BRI is useful, it may not always be the most effective measure (Calderón‐García et al., 2021; Rico-Martin et al., 2020).
Conclusion
In conclusion, while BMI remains widely used for its simplicity and accessibility, it is increasingly recognized as an imperfect tool for assessing body fat and related health risks. The introduction of the Body Roundness Index offers a more nuanced approach by incorporating waist circumference and body shape, which improves its predictive power for certain conditions. However, BRI also has limitations, particularly when compared to established measures like waist-to-height ratio (WHtR). BMI and BRI have roles in clinical and research settings, and their effectiveness may vary across populations. Further refinement of these tools and personalized assessments may address individual health risks better.
Glossary
a body shape index (ABSI): an anthropometric measure that incorporates waist circumference, height, and weight to assess body shape and predict health risks. Unlike BMI, ABSI accounts for waist circumference relative to height and weight, offering insights into the risk of obesity-related conditions such as cardiovascular disease, independent of body mass.
body adiposity index (BAI): a measure used to estimate an individual’s body fat percentage. BAI is calculated using hip circumference and height, rather than weight, providing an alternative to BMI for assessing body fat without requiring body weight measurements. It is primarily used to evaluate obesity and related health risks.
body fat: the total mass of fat tissue in the body, including both essential fat (necessary for normal bodily functions) and storage fat (fat stored in adipose tissue). Body fat percentage can be used to assess overall health, with too little or too much body fat associated with health risks.
body mass index (BMI): a metric calculated by dividing a person's weight in kilograms by the square of their height in meters (kg/m²). It is used to classify individuals into categories based on their weight relative to height.
body roundness index (BRI): an anthropometric measure designed to predict body fat and visceral adiposity, based on waist circumference and body shape.
central adiposity: the accumulation of excess fat in the abdominal area. It is often associated with an increased risk of metabolic conditions such as insulin resistance, cardiovascular diseases, and type 2 diabetes. Central adiposity is commonly measured using waist circumference or waist-to-hip ratio.
homeostatic model assessment (HOMA)-β: a method used to assess pancreatic β-cell function and insulin resistance.
metabolic syndrome (MetS): a cluster of conditions, including high blood pressure, high blood sugar, excess body fat around the waist, and abnormal cholesterol levels, increasing the risk of heart disease and diabetes.
obesity phenotypes: classifying individuals based on body fat distribution and associated metabolic conditions. Some common phenotypes include:
metabolically healthy obesity (MHO): individuals who have a high body BMI but do not exhibit typical metabolic disturbances like insulin resistance or inflammation.
metabolically unhealthy obesity (MUO): individuals who have obesity along with metabolic disorders such as insulin resistance, dyslipidemia, or hypertension.
abdominal or central obesity: excess fat in the abdominal region, often assessed using waist circumference or waist-to-hip ratio.
peripheral obesity: the accumulation of fat in areas such as the hips, thighs, and buttocks, which may have different metabolic implications compared to central obesity.
triglycerides (TG): a type of fat (lipid) found in the blood, elevated levels of which can increase the risk of cardiovascular disease.
visceral fat: a specific type of body fat stored within the abdominal cavity, surrounding internal organs such as the liver, pancreas, and intestines. Visceral fat is more metabolically active than subcutaneous fat and is closely linked to conditions like heart disease, type 2 diabetes, and inflammation.
waist circumference (WC): A measurement around the narrowest part of the waist, used to
assess central fat distribution and associated health risks.
waist-to-height ratio (WHtR): the ratio of an individual’s waist circumference to their height, often used to assess health risks related to fat distribution.
References
Bray, G. (2023). Beyond BMI. Nutrients, 15. https://doi.org/10.3390/nu15102254
Calderón‐García, J., Roncero‐Martín, R., Rico-Martín, S., Nicolás-Jiménez, J., López-Espuela, F., Santano-Mogena, E., Alfageme-García, P., & Muñoz-Torrero, J. (2021). Effectiveness of Body Roundness Index (BRI) and a Body Shape Index (ABSI) in predicting hypertension: A systematic review and meta-analysis of observational studies. International Journal of Environmental Research and Public Health, 18. https://doi.org/10.3390/ijerph182111607
Daniels, S. (2009). The use of BMI in the clinical setting. Pediatrics, 124, S35 - S41. https://doi.org/10.1542/peds.2008-3586F
Després, J. P. (2012). Body fat distribution and risk of cardiovascular disease: An update. Circulation, 126(10), 1301-1313. https://doi.org/10.1161/CIRCULATIONAHA.111.067264
Garn, S., Leonard, W., & Hawthorne, V. (1986). Three limitations of the body mass index. The American Journal of Clinical Nutrition, 44(6), 996-997 . https://doi.org/10.1093/AJCN/44.6.996
Gonzalez, M., Correia, M., & Heymsfield, S. (2017). A requiem for BMI in the clinical setting. Current Opinion in Clinical Nutrition and Metabolic Care, 20, 314–321. https://doi.org/10.1097/MCO.0000000000000395
Gosse, M. (2014). How accurate is self-reported BMI? Nutrition Bulletin, 39, 105-114. https://doi.org/10.1111/NBU.12075
Müller, M., Braun, W., Enderle, J., & Bosy-Westphal, A. (2016). Beyond BMI: Conceptual issues related to overweight and obese patients. Obesity Facts, 9, 193 - 205. https://doi.org/10.1159/000445380
Nahas, G. (2019). Body roundness index: A new anthropometric indicator for obesity research. International Journal of Obesity, 43(7), 1310-1314. https://doi.org/10.1038/s41366-019-0350-6
Nkwana, M., Monyeki, K., & Lebelo, S. (2021). Body roundness index, a body shape index, conicity index, and their association with nutritional status and cardiovascular risk factors in South African rural young adults. International Journal of Environmental Research and Public Health, 18. https://doi.org/10.3390/ijerph18010281
Prentice, A. M., & Jebb, S. A. (2001). Beyond body mass index. Obesity Reviews, 2(3), 141-147. https://doi.org/10.1046/j.1467-789x.2001.00031.x
Rico-Martín, S., Calderón‐García, J., Sánchez-Rey, P., Franco-Antonio, C., Alvarez, M., & Muñoz-Torrero, J. (2020). Effectiveness of body roundness index in predicting metabolic syndrome: A systematic review and meta‐analysis. Obesity Reviews, 21. https://doi.org/10.1111/obr.13023
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Zhang, X., Ma, N., Lin, Q., Chen, K., Zheng, F., Wu, J., Dong, X., & Niu, W. (2024). Body roundness index and all-cause mortality among US adults. JAMA Network Oopen, 7(6), e2415051. https://doi.org/10.1001/jamanetworkopen.2024.15051
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