BACKGROUND Due to the opposing cardiovascular risk profiles of CAC volume and density, we tested the hypothesis that increased abdominal muscle area (AMA) and density (AMD) were significantly associated with lower coronary arterial calcium (CAC) volume and higher CAC density. METHODS Using data from 787 participants from the Multi-Ethnic Study of Atherosclerosis, Ancillary Body Composition Study, we analyzed abdominal and chest computed tomography (CT) scans. Abdominal scans were scored for muscle area, muscle density (attenuation) and visceral and subcutaneous fat. Chest scans were scored for CAC volume and Agatston values, which were used to derive CAC density scores. RESULTS The mean (SD) age and BMI of the participants was 67.8 (9.0) years and 27.9 (4.8) kg/m2, respectively. Forty-one percent were female, 46% were Caucasian, 60% had hypertension, 17% had diabetes, and 46% had dyslipidemia. AMA was positively associated with CAC volume (p < .001) and inversely associated with CAC density (p < .001). Conversely, AMD was inversely associated with CAC volume and positively associated with CAC density in minimally adjusted models (p < .001), but not significant in confounder adjusted models. CONCLUSION AMA and AMD had differing associations with CAC volume and density, with AMA significantly associated with a higher risk CAC profile (high volume, low density) and AMD not significantly associated with CAC volume or density. Future research needs to account for the unique components of both muscle composition and CAC.

中文翻译：

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腹肌面积和密度与冠状动脉钙量和密度的关系：动脉粥样硬化的多民族研究。

背景技术由于CAC量和密度的心血管危险性相反，我们检验了以下假设：腹肌面积（AMA）和密度（AMD）增加与较低的冠状动脉钙（CAC）量和较高的CAC密度显着相关。方法使用来自多民族动脉粥样硬化研究，辅助身体成分研究的787名参与者的数据，我们分析了腹部和胸部CT扫描。腹部扫描记录肌肉面积，肌肉密度（衰减）以及内脏和皮下脂肪。对胸部扫描进行CAC体积和Agatston值评分，以得出CAC密度评分。结果参与者的平均（SD）年龄和BMI分别为67.8（9.0）岁和27.9（4.8）kg / m2。女性占41％，白人占46％，60％患有高血压，17％患有糖尿病，46％患有血脂异常。AMA与CAC体积呈正相关（p <.001），与CAC密度呈负相关（p <.001）。相反，在最小调整模型中，AMD与CAC量呈负相关，与CAC密度呈正相关（p <.001），而在混杂变量调整模型中，AMD与CAC密度呈负相关。结论AMA和AMD与CAC体积和密度有不同的关联，AMA与较高风险的CAC配置文件（高体积，低密度）显着相关，而AMD与CAC体积或密度没有显着相关。未来的研究需要考虑肌肉成分和CAC的独特组成部分。001），并且与CAC密度成反比（p <.001）。相反，在最小调整模型中，AMD与CAC量呈负相关，与CAC密度呈正相关（p <.001），而在混杂变量调整模型中，AMD与CAC密度呈负相关。结论AMA和AMD与CAC体积和密度有不同的关联，AMA与较高风险的CAC配置文件（高体积，低密度）显着相关，而AMD与CAC体积或密度没有显着相关。未来的研究需要考虑肌肉成分和CAC的独特组成部分。001），并且与CAC密度成反比（p <.001）。相反，在最小调整模型中，AMD与CAC量呈负相关，与CAC密度呈正相关（p <.001），而在混杂变量调整模型中，AMD与CAC密度呈负相关。结论AMA和AMD与CAC体积和密度有不同的关联，AMA与较高风险的CAC配置文件（高体积，低密度）显着相关，而AMD与CAC体积或密度没有显着相关。未来的研究需要考虑肌肉成分和CAC的独特组成部分。结论AMA和AMD与CAC体积和密度有不同的关联，AMA与较高风险的CAC配置文件（高体积，低密度）显着相关，而AMD与CAC体积或密度没有显着相关。未来的研究需要考虑肌肉成分和CAC的独特组成部分。结论AMA和AMD与CAC体积和密度有不同的关联，AMA与较高风险的CAC配置文件（高体积，低密度）显着相关，而AMD与CAC体积或密度没有显着相关。未来的研究需要考虑肌肉成分和CAC的独特组成部分。