Body Composition Profiling in the UK Biobank Imaging Study.
Body Composition Profiling in the UK Biobank Imaging Study.
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英国生物库成像研究中的身体成分分析。
DOI：
10.1002/oby.22210
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发表时间：
2018-11
期刊：
影响因子：
--
通讯作者：
Dahlqvist Leinhard O
中科院分区：
文献类型：
--
作者：
Linge J;Borga M;West J;Tuthill T;Miller MR;Dumitriu A;Thomas EL;Romu T;Tunón P;Bell JD;Dahlqvist Leinhard O
本研究旨在通过描述基于成像的多变量身体成分分析与冠心病（CHD）、2型糖尿病（T2 D）和代谢健康在个体和人群水平上的相关性，研究其价值。英国生物银行扫描的前6,021名参与者被纳入其中。计算身体组成曲线（BCP），包括腹部皮下脂肪组织、内脏脂肪组织（VAT）、大腿肌肉体积、肝脏脂肪和肌肉脂肪浸润（MFI），使用磁共振成像测定。BCP和代谢状态之间的关联进行了研究，使用匹配程序和多变量统计建模。配对对照分析显示，高VAT和高MFI与CHD和T2 D相关（P < 0.001）。高肝脂与T2 D相关（P < 0.001），低肝脂与CHD相关（P < 0.05），与VAT匹配。多变量模型显示，较低的VAT和MFI与代谢健康相关（P < 0.001），肝脏脂肪无显著性。调整性别、年龄、BMI、饮酒、吸烟和体力活动后，相关性仍然显著。身体成分分析使身体成分的直观可视化成为可能，并显示了脂肪分布和代谢状态之间关联的复杂性，强调了多变量方法的重要性。不同的疾病与不同的BCP有关，不能仅用单一的脂肪区室来描述。
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. 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. 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. 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.
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