Body fat percentage is a better predictor of obesity-related risks than BMI
Last reviewed: 02.07.2025
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In a recently published study in the Journal of Clinical Endocrinology & Metabolism, researchers evaluated percent body fat (%BF) thresholds for defining overweight and obesity, examining their association with metabolic syndrome (MetSyn) in a large sample of adults.
The study found that %BF thresholds are a more accurate indicator than body mass index (BMI) for predicting obesity -related diseases. The researchers recommend using direct measurements of body fat in clinical practice and suggest identifying overweight at 25% BF for men and 36% BF for women. Obesity can be defined at 30% BF for men and 42% BF for women.
BMI-based standards are commonly used to define obesity, overweight, and normal weight. However, BMI is considered an inaccurate measure of actual body fat or %BF.
Modern technology has improved the assessment of %BF, but outcome-based thresholds are needed to ensure that these measurements can be used effectively to manage patient health.
Obesity-related diseases are associated with excess fat, but current recommendations often rely on overall mortality statistics rather than direct links to specific health outcomes.
Now, more accurate methods of assessing %BF, such as multi-frequency bioelectrical impedance analysis (MF-BIA), are being developed and may play a significant role in preventive healthcare. Due to the relationship between %BF and MetSyn, %BF may become a more accurate tool for managing obesity-related diseases compared to BMI.
The study conducted a correlation analysis using data from the National Health and Nutrition Examination Survey (NHANES) to estimate %BF thresholds for defining overweight and obesity.
The sample included 16,918 individuals aged 18 to 85 years, with data collected from 1999 to 2018, excluding periods when dual-energy X-ray absorptiometry (DXA) measurements were not performed.
Data collected included demographics, laboratory measurements (including fasting glucose, triglycerides, HDL cholesterol, blood pressure), anthropometric measures (BMI, weight, height, waist circumference), and whole-body DXA results.
Each participant's metabolic health was classified based on the presence of MetSyn, defined as the presence of at least three of five key markers: increased waist circumference, low HDL, high fasting glucose, high blood pressure, and high triglycerides.
Data from 16,918 people (8,184 women and 8,734 men) with an average age of about 42 years, representing different ethnic groups, were analyzed.
Among individuals classified as overweight (BMI >25 kg/m²) and obese (BMI ≥30 kg/m²), 5% and 35% had MetSyn, respectively. These values were used to establish new %BF thresholds: 25% for overweight versus 30% for obesity in men and 36% for overweight versus 42% for obesity in women.
Using these %BF thresholds, 27.2% of women and 27.7% of men were classified as normal weight, 33.5% of women and 34.0% of men were classified as overweight, and 39.4% of women and 38.3% of men were classified as obese.
The study highlighted that BMI has low predictive value across individuals due to the significant variability in %BF at any given BMI.
Additionally, differences in the correlation of BMI with %BF between men and women highlight the limitations of using BMI to assess obesity and its associated health risks.
Recent advances in MF-BIA offer more reliable and accessible methods for estimating %BF compared to traditional anthropometric methods.
Although the accuracy of these devices varies, their increasing adoption in clinical practice represents a significant step towards improved epidemiological data and wider use.
Technological improvements in body composition assessment, including more accurate MF-BIA models and support from medical societies, could improve clinical use and insurance coverage, ultimately improving patient care.
Limitations include variability in the accuracy of devices and the need for further research on the relationship between body composition and metabolic disease.