Liron S McCauley1,2, Ryan M Sumrell1,2, Ashraf S Gorgey1,2. 1. Spinal Cord Injury and Disorders, Hunter Holmes McGuire VA Medical Center, Richmond, VA. 2. Physical Medicine and Rehabilitation, Virginia Commonwealth University, Richmond, VA; Spinal Cord Injury and Disorders, Hunter Holmes McGuire VA Medical Center, 1201 Broad Rock Blvd, Richmond, VA 23249.
Abstract
BACKGROUND: Spinal cord injury (SCI) results in increased accumulation of visceral adipose tissue (VAT). Anthropometrics may provide an alternative to estimate VAT cross-section area (CSA) compared to magnetic resonance imaging (MRI). OBJECTIVE: To validate the use of anthropometrics, including abdominal circumference and skinfold thickness (SFT) measurements against MRI to predict subcutaneous adipose tissue (SAT) and VAT cross-sectional areas in persons with SCI. DESIGN: Cross-sectional. SETTING: Clinical research center PARTICIPANT: Twenty-two men with motor complete SCI METHODS: Anthropometric measurements and MRI were taken during a single visit. Abdominal circumference and SFT were used to derive prediction equations for subcutaneous adipose tissue (SATAnthro-CSA) and VAT (VATAnthro-CSA). Three-axial MRI at the level of umbilicus was used to establish the prediction equations. VATAnthro-CSA was compared against body mass index (BMI), waist circumference, and SFT. Bland-Altman plots were used to determine limits of agreement between prediction equations and MRI. MAIN OUTCOME MEASUREMENTS: SAT and VAT cross-sectional areas. RESULTS: SATAnthro-CSA explained 76% of the variance in SAT cross-sectional area (r2 = 0.76, standard error of the estimate [SEE] = 49.5 cm2, P <.001). VATAnthro-CSA explained 72% of VAT cross-sectional area (r2 = 0.72, SEE = 45.8 cm2, P <.001). Compared to VATAnthro-CSA, BMI, waist circumference, and SFT explained only 37%, 63%, and 31%, respectively, in the variance of VAT MRI. CONCLUSION: Abdominal circumference and SFT demonstrated an alternative way to predict VAT CSA. VATAnthro-CSA estimated VATMRI more accurately than BMI, waist circumference, and SFT in individuals with chronic SCI. LEVEL OF EVIDENCE: I.
BACKGROUND:Spinal cord injury (SCI) results in increased accumulation of visceral adipose tissue (VAT). Anthropometrics may provide an alternative to estimate VAT cross-section area (CSA) compared to magnetic resonance imaging (MRI). OBJECTIVE: To validate the use of anthropometrics, including abdominal circumference and skinfold thickness (SFT) measurements against MRI to predict subcutaneous adipose tissue (SAT) and VAT cross-sectional areas in persons with SCI. DESIGN: Cross-sectional. SETTING: Clinical research center PARTICIPANT: Twenty-two men with motor complete SCI METHODS: Anthropometric measurements and MRI were taken during a single visit. Abdominal circumference and SFT were used to derive prediction equations for subcutaneous adipose tissue (SATAnthro-CSA) and VAT (VATAnthro-CSA). Three-axial MRI at the level of umbilicus was used to establish the prediction equations. VATAnthro-CSA was compared against body mass index (BMI), waist circumference, and SFT. Bland-Altman plots were used to determine limits of agreement between prediction equations and MRI. MAIN OUTCOME MEASUREMENTS: SAT and VAT cross-sectional areas. RESULTS: SATAnthro-CSA explained 76% of the variance in SAT cross-sectional area (r2 = 0.76, standard error of the estimate [SEE] = 49.5 cm2, P <.001). VATAnthro-CSA explained 72% of VAT cross-sectional area (r2 = 0.72, SEE = 45.8 cm2, P <.001). Compared to VATAnthro-CSA, BMI, waist circumference, and SFT explained only 37%, 63%, and 31%, respectively, in the variance of VAT MRI. CONCLUSION: Abdominal circumference and SFT demonstrated an alternative way to predict VAT CSA. VATAnthro-CSA estimated VATMRI more accurately than BMI, waist circumference, and SFT in individuals with chronic SCI. LEVEL OF EVIDENCE: I.
Authors: Jan W van der Scheer; Julia O Totosy de Zepetnek; Cheri Blauwet; Katherine Brooke-Wavell; Terri Graham-Paulson; Amber N Leonard; Nick Webborn; Victoria L Goosey-Tolfrey Journal: PLoS One Date: 2021-05-07 Impact factor: 3.240