Abdominal Body Composition Reference Ranges and Association With Chronic Conditions in an Age- and Sex-Stratified Representative Sample of a Geographically Defined American Population

Author:

Weston Alexander D1ORCID,Grossardt Brandon R2,Garner Hillary W3,Kline Timothy L4,Chamberlain Alanna M56,Allen Alina M7,Erickson Bradley J8,Rocca Walter A59ORCID,Rule Andrew D510,St. Sauver Jennifer L511

Affiliation:

1. Digital Innovation Lab, Department of Quantitative Health Sciences, Mayo Clinic , Jacksonville, Florida , USA

2. Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic , Rochester, Minnesota , USA

3. Division of Musculoskeletal Radiology, Department of Radiology, Mayo Clinic , Jacksonville, Florida , USA

4. Department of Radiology, Mayo Clinic , Rochester, Minnesota , USA

5. Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic , Rochester, Minnesota , USA

6. Department of Cardiovascular Medicine, Mayo Clinic , Rochester, Minnesota , USA

7. Division of Gastroenterology and Hepatology, Mayo Clinic , Rochester, Minnesota , USA

8. Mayo Artificial Intelligence Laboratory, Department of Radiology, Mayo Clinic , Rochester Minnesota , USA

9. Department of Neurology, Mayo Clinic , Rochester, Minnesota , USA

10. Department of Medicine, Mayo Clinic , Rochester, Minnesota , USA

11. The Robert D. and Patricia E. Kern Center for the Science of Health Care Delivery, Mayo Clinic , Rochester, Minnesota , USA

Abstract

Abstract Background Body composition can be accurately quantified from abdominal computed tomography (CT) exams and is a predictor for the development of aging-related conditions and for mortality. However, reference ranges for CT-derived body composition measures of obesity, sarcopenia, and bone loss have yet to be defined in the general population. Methods We identified a population-representative sample of 4 900 persons aged 20 to 89 years who underwent an abdominal CT exam from 2010 to 2020. The sample was constructed using propensity score matching an age and sex stratified sample of persons residing in the 27-county region of Southern Minnesota and Western Wisconsin. The matching included race, ethnicity, education level, region of residence, and the presence of 20 chronic conditions. We used a validated deep learning based algorithm to calculate subcutaneous adipose tissue area, visceral adipose tissue area, skeletal muscle area, skeletal muscle density, vertebral bone area, and vertebral bone density from a CT abdominal section. Results We report CT-based body composition reference ranges on 4 649 persons representative of our geographic region. Older age was associated with a decrease in skeletal muscle area and density, and an increase in visceral adiposity. All chronic conditions were associated with a statistically significant difference in at least one body composition biomarker. The presence of a chronic condition was generally associated with greater subcutaneous and visceral adiposity, and lower muscle density and vertebrae bone density. Conclusions We report reference ranges for CT-based body composition biomarkers in a population-representative cohort of 4 649 persons by age, sex, body mass index, and chronic conditions.

Funder

National Institute on Aging

Mayo Clinic Research Committee

REP users

Publisher

Oxford University Press (OUP)

Reference51 articles.

1. Ratio of visceral-to-subcutaneous fat area predicts cardiovascular events in patients with type 2 diabetes;Fukuda,2018

2. Visceral fat quantification in asymptomatic adults using abdominal CT: is it predictive of future cardiac events;Ryckman,2015

3. The ratio of visceral to subcutaneous fat, a metric of body fat distribution, is a unique correlate of cardiometabolic risk;Kaess,2012

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