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WEDNESDAY, Jan. 18 (HealthDay News) -- The Clinica Universidad de Navarra body adiposity estimator (CUN-BAE) is an effective clinical tool for the prediction of body fat percentage (BF%), according to a study published online Dec. 16 in Diabetes Care.
Javier Gómez-Ambrosi, Ph.D., of the CUN in Pamplona, Spain, and colleagues compared the clinical usefulness of the CUN-BAE with other methods of measuring BF% in a cohort of 6,510 predominantly female white participants, aged 18 to 80 years, with a wide range of adiposity. The equation was validated in a separate cohort of 1,149 participants, and the clinical value of its association with cardiometabolic risk factors was assessed in 634 participants.
In the overall patient cohort, the researchers found that the mean BF% based on CUN-BAE prediction was 39.3 percent, compared with 39.9 percent based on air displacement plethysmography. The highest correlation with actual BF% was seen with the BF% calculated using the CUN-BAE (r = 0.89), compared with other anthropometric measures or estimators of BF%. A similar correlation was seen in the validation cohort. In the subset of 634 participants, BF% predicted by CUN-BAE had a better correlation with cardiometabolic risk factors than body mass index (BMI) or waist circumference.
"Because the possibility of measuring BF% is not always available and the relation between BMI and BF% is highly dependent on sex and age, we have developed and validated an easy-to-apply predictive equation that may be used as a first screening tool in medical practice," the authors write.
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