TY - JOUR
T1 - Body Composition Profiling in the UK Biobank Imaging Study
AU - Linge, Jennifer
AU - Borga, Magnus
AU - West, Janne
AU - Tuthill, Theresa
AU - Miller, Melissa R.
AU - Dumitriu, Alexandra
AU - Thomas, E. Louise
AU - Romu, Thobias
AU - Tunón, Patrik
AU - Bell, Jimmy D.
AU - Dahlqvist Leinhard, Olof
N1 - Publisher Copyright:
© 2018 The Authors. Obesity published by Wiley Periodicals, Inc. on behalf of The Obesity Society (TOS).
PY - 2018/11
Y1 - 2018/11
N2 - Objective: This study aimed to investigate the value of imaging-based multivariable body composition profiling by describing its association with coronary heart disease (CHD), type 2 diabetes (T2D), and metabolic health on individual and population levels. Methods: The first 6,021 participants scanned by UK Biobank were included. Body composition profiles (BCPs) were calculated, including abdominal subcutaneous adipose tissue, visceral adipose tissue (VAT), thigh muscle volume, liver fat, and muscle fat infiltration (MFI), determined using magnetic resonance imaging. Associations between BCP and metabolic status were investigated using matching procedures and multivariable statistical modeling. Results: Matched control analysis showed that higher VAT and MFI were associated with CHD and T2D (P < 0.001). Higher liver fat was associated with T2D (P < 0.001) and lower liver fat with CHD (P < 0.05), matching on VAT. Multivariable modeling showed that lower VAT and MFI were associated with metabolic health (P < 0.001), and liver fat was nonsignificant. Associations remained significant adjusting for sex, age, BMI, alcohol, smoking, and physical activity. Conclusions: Body composition profiling enabled an intuitive visualization of body composition and showed the complexity of associations between fat distribution and metabolic status, stressing the importance of a multivariable approach. Different diseases were linked to different BCPs, which could not be described by a single fat compartment alone.
AB - Objective: This study aimed to investigate the value of imaging-based multivariable body composition profiling by describing its association with coronary heart disease (CHD), type 2 diabetes (T2D), and metabolic health on individual and population levels. Methods: The first 6,021 participants scanned by UK Biobank were included. Body composition profiles (BCPs) were calculated, including abdominal subcutaneous adipose tissue, visceral adipose tissue (VAT), thigh muscle volume, liver fat, and muscle fat infiltration (MFI), determined using magnetic resonance imaging. Associations between BCP and metabolic status were investigated using matching procedures and multivariable statistical modeling. Results: Matched control analysis showed that higher VAT and MFI were associated with CHD and T2D (P < 0.001). Higher liver fat was associated with T2D (P < 0.001) and lower liver fat with CHD (P < 0.05), matching on VAT. Multivariable modeling showed that lower VAT and MFI were associated with metabolic health (P < 0.001), and liver fat was nonsignificant. Associations remained significant adjusting for sex, age, BMI, alcohol, smoking, and physical activity. Conclusions: Body composition profiling enabled an intuitive visualization of body composition and showed the complexity of associations between fat distribution and metabolic status, stressing the importance of a multivariable approach. Different diseases were linked to different BCPs, which could not be described by a single fat compartment alone.
UR - http://www.scopus.com/inward/record.url?scp=85055056988&partnerID=8YFLogxK
U2 - 10.1002/oby.22210
DO - 10.1002/oby.22210
M3 - Article
C2 - 29785727
AN - SCOPUS:85055056988
SN - 1930-7381
VL - 26
SP - 1785
EP - 1795
JO - Obesity
JF - Obesity
IS - 11
ER -
