Beyond BMI: The New Era of Body Fat Percentage in Defining Obesity

In the quest to better understand and manage obesity, the traditional metric of Body Mass Index (BMI) has long been used. However, recent advancements in body composition estimation suggest a shift from BMI to more direct measures, such as body fat percentage (BF%), could improve obesity management. This blog delves into the differences between BMI and BF%, and how the latter could provide a more accurate and practical approach to defining overweight and obesity (Potter et al., 2024).

 Understanding Body Mass Index (BMI)

BMI is a widely used tool to categorise individuals based on their weight in relation to their height. It is calculated by dividing a person's weight in kilograms by the square of their height in metres (kg/m²) (National Heart, Lung, and Blood Institute, 2023). The resulting value is then categorised as follows:

• Underweight: BMI < 18.5
• Normal weight: BMI 18.5 - 24.9 
• Overweight: BMI 25 - 29.9
• Obesity: BMI ≥ 30

Healthcare providers use BMI as a screening tool to estimate body fat and assess potential health risks associated with weight. While BMI is easy to calculate and provides a quick assessment, it has notable limitations such as (Nuttall, 2015):

• It doesn't distinguish between muscle mass, bone mass and fat mass, leading to potential misclassification.
• It doesn't account for body fat distribution
• It may not be accurate for athletes, elderly people, or certain ethnic groups

For example, athletes with high muscle mass may be categorised as overweight or obese despite having low body fat. Conversely, individuals with normal BMI might have high body fat and related health risks.

BMI, a measure of obesity introduced nearly two centuries ago by a Belgian mathematician, has faced criticism for not being originally intended as a diagnostic health tool. A recent study by Visaria et al. (2023) found that BMI significantly underestimates obesity prevalence compared to %BF measurements:

Using BMI, 36% of adults were classified as obese.

Using %BF, 74% of adults were classified as obese.

 The Case for Body Fat Percentage (BF%)

Body fat percentage (BF%) directly measures the proportion of fat in the body. This metric offers a clearer picture of an individual's body composition, distinguishing between fat and lean mass. 

Practical methods for estimating BF% are becoming more accessible and accurate such as:

• Bioelectrical Impedance Analysis (BIA):

BIA measures body fat by sending a weak electrical current through the body. It estimates body composition based on how the current flows through different tissues (Lyons-Reid et al., 2020).

• Skinfold Measurements:

Skinfold measurements involve using callipers to pinch and measure folds of skin at different body sites. These measurements are used to estimate the amount of subcutaneous fat beneath the skin (Silveira et al., 2020).

• Dual-Energy X-ray Absorptiometry (DEXA):

DEXA scan uses low-dose X-rays to differentiate between bone, fat tissue, and lean mass in the body. It provides precise measurements of body fat percentage and bone density (Chaves et al., 2022).

 New Thresholds for Overweight and Obesity

Based on recent studies, clinically relevant thresholds for overweight and obesity using BF% have been proposed the following:

For men: a body fat percentage of 25% is considered overweight, and 30% is classified as obese. 

For women: the thresholds are slightly higher, with 36% BF indicating overweight and 42% defining obesity. 

These values reflect differences in body composition between genders and provide a more precise measure of unhealthy fat accumulation (Potter et al., 2024).

Why BF% is a Better Metric

1. Accuracy: BF% provides a direct measurement of fat, offering a clearer indication of health risks associated with excess body fat.
2. Better correlation with health risks: BF% thresholds have been determined based on the prevalence of metabolic syndrome, a key obesity-related comorbidity that includes cardiovascular risks. This approach provides a more direct link between body composition and health outcomes.
3. Personalisation: Unlike BMI, BF% accounts for individual differences in muscle mass and fat distribution.
4. Gender-specific thresholds: BF% allows for separate thresholds for men and women, accounting for natural differences in body composition between sexes.
5. Health Focus: BF% aligns more closely with health outcomes, such as cardiovascular risk and metabolic health, which are directly influenced by body fat levels.

Potential limitations of BF% measurement:

• Variation in standardised cut-offs: There is no universal agreement on the specific BF% thresholds that define overweight and obesity across diverse populations. These thresholds may differ based on variables such as age, gender, and ethnicity.

• Age and gender disparities: BF% naturally fluctuates with age and varies between genders, necessitating distinct reference ranges for different age groups and sexes. This variability can complicate the interpretation and comparison of BF% measurements.

• Equipment constraints: Certain BF% measurement methods, like bioelectrical impedance analysis (BIA), are susceptible to factors such as hydration levels, recent food consumption, and physical activity. These variables have the potential to introduce inaccuracies in BF% assessments.

 Conclusion

Recent research indicates that transitioning from BMI to BF% for categorising overweight and obesity marks a substantial progression in health assessment. With newly established thresholds—25% and 36% BF for men and women to define overweight, and 30% and 42% BF for obesity—healthcare providers can now offer more personalised and efficient obesity management strategies. As practical techniques for measuring body composition advance, BF% is positioned to emerge as the preferred standard for evaluating and managing obesity (Potter et al., 2024).

References:

• Chaves, L.G.C. de M., Gonçalves, T.J.M., Bitencourt, A.G.V., Rstom, R.A., Pereira, T.R. and Velludo, S.F. (2022). Assessment of body composition by whole-body densitometry: what radiologists should know. Radiologia Brasileira, [online] 55, pp.305–311. doi:https://doi.org/10.1590/0100-3984.2021.0155-en.
• Jayedi A, Soltani S, Zargar MS, Khan TA, Shab-Bidar S. Central fatness and risk of all cause mortality: systematic review and dose-response meta-analysis of 72 prospective cohort studies. BMJ. 2020;370.
• Laskey, M.A. (1996). Dual-energy X-ray absorptiometry and body composition. Nutrition (Burbank, Los Angeles County, Calif.), [online] 12(1), pp.45–51. doi:https://doi.org/10.1016/0899-9007(95)00017-8.
• Lyons-Reid, J., Ward, L.C., Kenealy, T. and Cutfield, W. (2020). Bioelectrical Impedance Analysis—An Easy Tool for Quantifying Body Composition in Infancy? Nutrients, [online] 12(4). doi:https://doi.org/10.3390/nu12040920.
• National Heart, Lung, and Blood Institute (2023). Calculate your BMI - standard BMI calculator. [online] Nih.gov. Available at: https://www.nhlbi.nih.gov/health/educational/lose_wt/BMI/bmicalc.htm.
• Nuttall, F.Q. (2015). Body Mass Index. Nutrition Today, [online] 50(3), pp.117–128. doi:https://doi.org/10.1097/nt.0000000000000092.
• Potter, A.W., Chin, G.C., Looney, D.P. and Friedl, K.E. (2024). Defining Overweight and Obesity by Percent Body Fat instead of Body Mass Index. The Journal of Clinical Endocrinology and Metabolism, [online] p.dgae341. doi:https://doi.org/10.1210/clinem/dgae341.
• Silveira, E.A., Barbosa, L.S., Rodrigues, A.P.S., Noll, M. and De Oliveira, C. (2020). Body fat percentage assessment by skinfold equation, bioimpedance and densitometry in older adults. Archives of Public Health, [online] 78(1). doi:https://doi.org/10.1186/s13690-020-00449-4.
• Visaria, A., Heo, J., Jang, Y., & Yoo, S. (2023). Prevalence of Obesity Based on Body Fat Percentage vs. Body Mass Index. Presented at ENDO 2023, the Endocrine Society's annual meeting, in Chicago, IL.