Prevalence, distribution, and risk factor correlates of high thoracic periaortic fat in the Framingham Heart Study.

Prevalence, distribution, and risk factor correlates of high thoracic periaortic fat in the Framingham Heart Study.
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DOI:
10.1161/jaha.112.004200
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发表时间:
2012-12
影响因子:
5.4
通讯作者:
Fox CS
Fox CS
中科院分区:
医学2区
文献类型:
--
作者:
Britton KA;Pedley A;Massaro JM;Corsini EM;Murabito JM;Hoffmann U;Fox CS

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胸主动脉周围脂肪组织(TAT)与动脉粥样硬化和心血管疾病(CVD)危险因素相关,并且可能在肥胖介导的血管疾病中发挥作用。我们试图确定高 TAT 的患病率、分布和危险因素相关性。 Framingham 心脏研究的参与者(n=3246,48% 为女性,平均年龄 51.1 岁)接受了多排计算机断层扫描;高 TAT 和内脏脂肪组织 (VAT) 是根据健康参考样本中性别特异性第 90 个百分位数定义的。女性高 TAT 患病率为 38.1%,男性为 35.7%。在没有高增值税的个人中,10.1% 的人有高 TAT。调整年龄和增值税后,与没有高 TAT 的女性和男性相比,在没有高 VAT 的情况下,具有高 TAT 的女性和男性年龄更大,CVD 患病率更高(P<0.0001)。此外,该组中的男性更有可能吸烟(P=0.02),而女性更有可能患有低密度脂蛋白胆固醇(P=0.005)。我们基于社区的样本中,在没有高 VAT 的情况下具有高 TAT 的个体的特征是不良的心脏代谢特征。这种脂肪组织表型可以识别具有不同代谢特征的个体子集。
Thoracic periaortic adipose tissue (TAT) is associated with atherosclerosis and cardiovascular disease (CVD) risk factors and may play a role in obesity‐mediated vascular disease. We sought to determine the prevalence, distribution, and risk factor correlates of high TAT. Participants from the Framingham Heart Study (n=3246, 48% women, mean age 51.1 years) underwent multidetector computed tomography; high TAT and visceral adipose tissue (VAT) were defined on the basis of sex‐specific 90th percentiles in a healthy referent sample. The prevalence of high TAT was 38.1% in women and 35.7% in men. Among individuals without high VAT, 10.1% had high TAT. After adjustment for age and VAT, both women and men with high TAT in the absence of high VAT were older and had a higher prevalence of CVD (P<0.0001) compared with those without high TAT. In addition, men in this group were more likely to be smokers (P=0.02), whereas women were more likely to have low high‐density lipoprotein cholesterol (P=0.005). Individuals in our community‐based sample with high TAT in the absence of high VAT were characterized by an adverse cardiometabolic profile. This adipose tissue phenotype may identify a subset of individuals with distinct metabolic characteristics.