Centro Nacional de Investigaciones Cardiovasculares (CNIC), Madrid, Spain.
CIBER de Enfermedades CardioVasculares (CIBERCV), Madrid, Spain.
J Clin Endocrinol Metab. 2020 Dec 1;105(12):3734-44. doi: 10.1210/clinem/dgaa620.
The underlying relationship between body mass index (BMI), cardiometabolic disorders, and subclinical atherosclerosis is poorly understood.
To evaluate the association between body size phenotypes and subclinical atherosclerosis.
Cross-sectional.
Cardiovascular disease-free cohort.
Middle-aged asymptomatic subjects (n = 3909). A total of 6 cardiometabolic body size phenotypes were defined based on the presence of at least 1 cardiometabolic abnormality (blood pressure, fasting blood glucose, triglycerides, low high-density lipoprotein cholesterol, homeostasis model assessment-insulin resistance index, high-sensitivity C-reactive protein) and based on BMI: normal-weight (NW; BMI <25), overweight (OW; BMI = 25.0-29.9) or obese (OB; BMI >30.0).
Subclinical atherosclerosis was evaluated by 2D vascular ultrasonography and noncontrast cardiac computed tomography.
For metabolically healthy subjects, the presence of subclinical atherosclerosis increased across BMI categories (49.6%, 58.0%, and 67.7% for NW, OW, and OB, respectively), whereas fewer differences were observed for metabolically unhealthy subjects (61.1%, 69.7%, and 70.5%, respectively). When BMI and cardiometabolic abnormalities were assessed separately, the association of body size phenotypes with the extent of subclinical atherosclerosis was mostly driven by the coexistence of cardiometabolic risk factors: adjusted OR = 1.04 (95% confidence interval [CI], 0.90-1.19) for OW and OR = 1.07 (95% CI, 0.88-1.30) for OB in comparison with NW, whereas there was an increasing association between the extent of subclinical atherosclerosis and the number of cardiometabolic abnormalities: adjusted OR = 1.21 (95% CI, 1.05-1.40), 1.60 (95% CI, 1.33-1.93), 1.92 (95% CI, 1.48-2.50), and 2.27 (95% CI, 1.67-3.09) for 1, 2, 3, and >3, respectively, in comparison with noncardiometabolic abnormalities.
The prevalence of subclinical atherosclerosis varies across body size phenotypes. Pharmacologic and lifestyle interventions might modify their cardiovascular risk by facilitating the transition from one phenotype to another.
体重指数（BMI）、心血管代谢紊乱和亚临床动脉粥样硬化之间的潜在关系尚未得到充分理解。
评估体型表型与亚临床动脉粥样硬化之间的关联。
横断面研究。
无心血管疾病队列。
中年无症状受试者（n=3909）。共定义了 6 种心血管代谢体型表型，基于至少存在 1 种心血管代谢异常（血压、空腹血糖、甘油三酯、低高密度脂蛋白胆固醇、稳态模型评估-胰岛素抵抗指数、高敏 C 反应蛋白）和 BMI：正常体重（NW；BMI<25）、超重（OW；BMI=25.0-29.9）或肥胖（OB；BMI>30.0）。
通过二维血管超声和非对比心脏计算机断层扫描评估亚临床动脉粥样硬化。
对于代谢健康的受试者，亚临床动脉粥样硬化的发生率随着 BMI 类别而增加（NW、OW 和 OB 分别为 49.6%、58.0%和 67.7%），而代谢不健康的受试者的差异较小（分别为 61.1%、69.7%和 70.5%）。当单独评估 BMI 和心血管代谢异常时，体型表型与亚临床动脉粥样硬化程度的关联主要由心血管代谢危险因素的共存驱动：与 NW 相比，OW 的调整比值比（OR）为 1.04（95%置信区间[CI]，0.90-1.19），OB 的 OR 为 1.07（95%CI，0.88-1.30），而亚临床动脉粥样硬化程度与心血管代谢异常数量之间的关联呈递增趋势：与无心血管代谢异常相比，分别为调整 OR 为 1.21（95%CI，1.05-1.40）、1.60（95%CI，1.33-1.93）、1.92（95%CI，1.48-2.50）和 2.27（95%CI，1.67-3.09）。
亚临床动脉粥样硬化的发生率因体型表型而异。药物和生活方式干预可能通过促进从一种表型向另一种表型的转变来改变其心血管风险。
