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Abdominal Body Composition Reference Ranges and Association With Chronic Conditions in an Age- and Sex-Stratified Representative Sample of a Geographically Defined American Population.
Weston, Alexander D; Grossardt, Brandon R; Garner, Hillary W; Kline, Timothy L; Chamberlain, Alanna M; Allen, Alina M; Erickson, Bradley J; Rocca, Walter A; Rule, Andrew D; St Sauver, Jennifer L.
Afiliação
  • Weston AD; Digital Innovation Lab, Department of Quantitative Health Sciences, Mayo Clinic, Jacksonville, Florida, USA.
  • Grossardt BR; Division of Clinical Trials and Biostatistics, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
  • Garner HW; Division of Musculoskeletal Radiology, Department of Radiology, Mayo Clinic, Jacksonville, Florida, USA.
  • Kline TL; Department of Radiology, Mayo Clinic, Rochester, Minnesota, USA.
  • Chamberlain AM; Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
  • Allen AM; Department of Cardiovascular Medicine, Mayo Clinic, Rochester, Minnesota, USA.
  • Erickson BJ; Division of Gastroenterology and Hepatology, Mayo Clinic, Rochester, Minnesota, USA.
  • Rocca WA; Mayo Artificial Intelligence Laboratory, Department of Radiology, Mayo Clinic, Rochester Minnesota, USA.
  • Rule AD; Division of Epidemiology, Department of Quantitative Health Sciences, Mayo Clinic, Rochester, Minnesota, USA.
  • St Sauver JL; Department of Neurology, Mayo Clinic, Rochester, Minnesota, USA.
Article em En | MEDLINE | ID: mdl-38373180
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Composição Corporal / Sarcopenia Limite: Humans Idioma: En Revista: J Gerontol A Biol Sci Med Sci Assunto da revista: GERIATRIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Composição Corporal / Sarcopenia Limite: Humans Idioma: En Revista: J Gerontol A Biol Sci Med Sci Assunto da revista: GERIATRIA Ano de publicação: 2024 Tipo de documento: Article País de afiliação: Estados Unidos