Association Between Body Size Phenotypes and Subclinical Atherosclerosis

• Published in: The journal of clinical endocrinology and metabolism 2020-12, Vol.105 (12), p.1-3744
• Main Authors: Rossello, Xavier, Fuster, Valentin, Oliva, Belén, Sanz, Javier, Fernández Friera, Leticia A, López-Melgar, Beatriz, Mendiguren, José María, Lara-Pezzi, Enrique, Bueno, Héctor, Fernández-Ortiz, Antonio, Ibanez, Borja, Ordovás, José María
• Format: Article
• Language: English
• Subjects: Adult; Arteriosclerosis; Asymptomatic Diseases; Atherosclerosis; Atherosclerosis - diagnosis; Atherosclerosis - epidemiology; Atherosclerosis - etiology; Blood pressure; Body mass index; Body size; Body Size - physiology; Body weight; C-reactive protein; Cardiovascular diseases; Cholesterol; Clinical s; Coexistence; Cohort Studies; Computed tomography; Cross-Sectional Studies; Female; Genetic aspects; Homeostasis; Humans; Insulin; Male; Medical research; Medicine, Experimental; Metabolic diseases; Middle Aged; Overweight; Phenotype; Phenotypes; Prevalence; Risk Factors; Spain - epidemiology; Triglycerides
• ISSN: 0021-972X; 1945-7197
• DOI: 10.1210/clinem/dgaa620

Abstract Context The underlying relationship between body mass index (BMI), cardiometabolic disorders, and subclinical atherosclerosis is poorly understood. Objective To evaluate the association between body size phenotypes and subclinical atherosclerosis. Design Cross-sectional. Setting Cardiovascular disease-free cohort. Participants 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 30.0). Main Outcome Measures Subclinical atherosclerosis was evaluated by 2D vascular ultrasonography and noncontrast cardiac computed tomography. Results 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. Conclusions 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.