Body fat percentage is a better predictor of obesity-related risks than BMI

In a recently published study in the Journal of Clinical Endocrinology & Metabolismresearchers assessed percentage 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 were a more accurate indicator than body mass index (BMI) for predicting diseases associated with obesity. The researchers recommend the use of direct body fat measurements in clinical practice and suggest that overweight is defined 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 typically used to define obesity, overweight, and normal weight. However, BMI is considered an inaccurate measure of actual body fat or %BF.

Modern technologies have improved the estimation of %BF, but outcome-based thresholds are needed so 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 general mortality statistics rather than direct links to specific health outcomes.

Now, more accurate methods for estimating %BF, such as multifrequency bioelectrical impedance testing (MF-BIA), are being developed and may play a significant role in preventive healthcare. Due to the relationship between %BF and MetSyn, %BF may provide a more accurate tool for the management of 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 people aged 18 to 85 years, with data collected from 1999 to 2018, excluding periods when dual-energy X-ray absorptiometry (DXA) measurements were not taken.

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 by 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 various 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 figures were used to establish new %BF thresholds: 25% for overweight compared to 30% for obese men and 36% for overweight compared to 42% for obese 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% women and 38.3% of men are considered obese.

The study highlighted that BMI has low predictive value for 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 toward improved epidemiological data and wider use.

Technological improvements in body composition assessment, including more accurate MF-BIA models and support from medical societies, may improve clinical use and insurance coverage, ultimately improving patient care.

Limitations include variability in device accuracy and the need for further research into the relationship between body composition and metabolic disease.