Investigating the Role of Area Deprivation Index in Observed Differences in CT-Based Body Composition by Race.
Authors
Affiliations (5)
Affiliations (5)
- Duke University School of Medicine, Durham, NC. Electronic address: [email protected].
- Department of Radiology, Duke University, Durham, NC.
- Department of Electrical and Computer Engineering, Duke University, Durham, NC.
- Department of Radiology, Duke University, Durham, NC; Department of Electrical and Computer Engineering, Duke University, Durham, NC; Department of Radiation Oncology, Duke University, Durham, NC; Department of Pathology, Duke University, Durham, NC.
- Department of Radiology, Duke University, Durham, NC; Department of Medicine, Duke University, Durham, NC; Center for Advanced Magnetic Resonance Development, Duke University, Durham, NC.
Abstract
Differences in CT-based body composition (BC) have been observed by race. We sought to investigate whether indices reporting census block group-level disadvantage, area deprivation index (ADI) and social vulnerability index (SVI), age, sex, and/or clinical factors could explain race-based differences in body composition. The first abdominal CT exams for patients in Durham County at a single institution in 2020 were analyzed using a fully automated and open-source deep learning BC analysis workflow to generate cross-sectional areas for skeletal muscle (SMA), subcutaneous fat (SFA), and visceral fat (VFA). Patient level demographic and clinical data were gathered from the electronic health record. State ADI ranking and SVI values were linked to each patient. Univariable and multivariable models were created to assess the association of demographics, ADI, SVI, and other relevant clinical factors with SMA, SFA, and VFA. 5,311 patients (mean age, 57.4 years; 55.5% female, 46.5% Black; 39.5% White 10.3% Hispanic) were included. At univariable analysis, race, ADI, SVI, sex, BMI, weight, and height were significantly associated with all body compartments (SMA, SFA, and VFA, all p<0.05). At multivariable analyses adjusted for patient characteristics and clinical comorbidities, race remained a significant predictor, whereas ADI did not. SVI was significant in a multivariable model with SMA.