3-Dimensional Optical Imaging Improves the Prediction of Metabolic Syndrome Over Body Mass Index

• Published in: Obesity (Silver Spring, Md.) Vol. 29; p. 48
• Main Authors: Bennett, Jon, Cataldi, Devon, Quon, Brandon, En Liu, Yong, Kelly, Nisa, Smith, Brooke, Heymsfield, Steven, Shepherd, John
• Format: Journal Article
• Language: English
• Published: Silver Spring Blackwell Publishing Ltd 01.12.2021
• Subjects: Body mass index; Demographics; Metabolic syndrome
• ISSN: 1930-7381; 1930-739X

Background: Metabolic syndrome (MetS), defined as a cluster of biochemical and physiological abnormalities associated with cardiovascular disease (CVD), has been shown to increase the risk of CVD-related mortality. Though weight is associated with the risk of MetS, normal weight individuals are also experience MetS, highlighting a key limitation of using body mass index (BMI) to predict incidence. Body shape provides a more accurate reflection of fat and muscle distribution and should be evaluated for its ability to predict MetS. The purpose of this study was to explore the use of body shape scans from a 3-dimensional optical (3DO) scanner to improve the prediction of MetS. Methods: 463 adults were recruited as part of the Shape Up! Adults study. Each subject underwent a 3DO scan, anthropometry and a fasting blood draw to assess the prevalence of MetS. Using linear regression, the prevalence of MetS was predicted using a demographics + 3DO model and compared to a standard demographics model. The area under the curve (AUC) for predicting MetS was compared, while the 3DO variables used in the prediction model were assessed for their prediction of each MetS diagnostic parameter. Results: In this sample, 77 participants met the criteria for MetS. Using the demographics + 3DO model, waist-to-hip ratio was the strongest predictor variable for MetS and was significantly associated with blood glucose, triglycerides, and systolic and diastolic blood pressure (all p < 0.0001). Overall, the 3DO model improved the AUC c-stat for predicting MetS from 0.841 to 0.913. Conclusions: 3DO scans provide measures of body shape more closely associated with MetS than BMI alone. The ability for 3DO to significantly improve the prediction of MetS provides practitioners with an accessible, non- i nvasive method for providing routine assessments of body composition change and quantifiable metrics for assessing MetS disease risk.