Author(s): BUTTERICK, B., KASOFSKY, L., SIEGLER, J., DE CRISTOFARO, A., DE CRISTOFARO, P., SANTELLO, M., Institution: ARIZONA STATE UNIVERSITY, Country: UNITED STATES, Abstract-ID: 1501

INTRODUCTION:
The gold standard for measuring body fat percentage is dual-energy X-ray absorptiometry (DXA), characterized by a 3% margin of error. The primary drawback of DXA is its reliance on expensive equipment, making it unsuitable for large groups of athletes, clinical outpatients, and/or routine patient management. Employing surrogate methods such as plicometry or bioelectrical impedance analysis, known to have measurement errors compared to DXA, does not offer reliability, which is integral to these populations. Recently, Nubentech SRL has developed a non-invasive algorithm-based measurement technique (MorphogramTM) that uses anthropometric measurements to estimate body composition and score risks of cardiovascular disease and metabolic syndrome risks. To date, however, this technique has yet to be validated against a gold standard.
METHODS:
In a pilot study aiming to validate the accuracy of body composition estimation by Morphogram compared to DXA, we recruited 52 participants (mean age 39.42 ±8.6 years; 26 females) with a body mass index (BMI) between 25 and 34.9. On the same day, participants had body composition assessed via DXA and Morphogram techniques, with DXA assumed as the reference standard for comparing body composition (fat mass, fat-free mass) to Morphogram (Full and Smart Analyses, FA and SA, the difference between these two analyses being the use of 8 and 3 body circumferences, respectively).
RESULTS:
In relation to DXA, Morphogram FA and SA under-estimated fat mass (on average –2.62 and –2.31 kg, respectively) and over-estimated fat-free mass (2.55 and 2.27 kg, respectively). The differences in measurement techniques between DXA and Morphogram were statistically significant (fat mass: F = 28.693, p < 0.001; fat-free mass: F = 24.346, p < 0.001). The comparison between Morphogram FA and SA revealed no significant difference in fat and fat-free mass estimation (both p > 0.05). Linear regression analysis was performed to examine body composition estimated by the three techniques (DXA, Morphogram FA, and SA) on a subject-by-subject basis. Both Morphogram analyses strongly agreed with DXA-estimated fat mass, with variances accounted for (R2) of 89% for FA and 87% for SA, respectively. Similar findings were observed when comparing DXA-estimated fat-free mass with Morphogram FA and SA (R2 = 90% and 88%, respectively).
CONCLUSION:
Further analyses of the DXA-Morphogram discrepancies of body composition estimation revealed that most of the differences (65%) were relatively small (within ±5% of body fat percentage) for both FA and SA. Ongoing work is examining factors underlying the larger discrepancies, including the presence of subcutaneous fat. In conclusion, the Morphogram technique has great potential for offering practical, accurate, and alternative estimates for fat-free and fat mass when compared to DXA.