Association Between Body Size Phenotypes and Subclinical Atherosclerosis

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 <25), overweight (OW; BMI = 25.0-29.9) or obese (OB; 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.

Keywords: body size phenotypes; cardiovascular risk; obesity; subclinical atherosclerosis.

© Endocrine Society 2020.

Figures

Figure 1.

Definition of cardiometabolic abnormalities and body size phenotypes and description of their prevalence by gender. Abbreviations: BMI, body mass index (kg/m2); HDL-C, high-density lipoprotein–cholesterol; HOMA-IR, homeostasis model assessment of insulin resistance; hsCRP, high-sensitivity C-reactive protein. HOMA was calculated through the following formula: Fasting Serum Insulin Level (Microunits per Milliliter) × Fasting Plasma Glucose Level (Millimoles per Liter)/22.5.

Figure 2.

Subclinical atherosclerosis assessed by 2D-vascular ultrasound and noncontrast cardiac computed tomography (CCT) in all participants (observed outcomes). Percentages of outcomes within each body size phenotype. Number of plaques (panel A) was assessed using two-dimensional vascular ultrasound, whereas coronary artery calcium score (panel B) was obtained by noncontrast CCT. The multi-territorial extent (panel C) was defined by the combination of both imaging techniques and classified subjects as disease-free (0 vascular sites affected) or having focal (1 site), intermediate (2 to 3 sites), or generalized atherosclerosis (4 to 6 sites) (10). Abbreviations: M.H., metabolically healthy; M.U., metabolically unhealthy.

Figure 3.

Unadjusted and adjusted risk for subclinical atherosclerosis by body mass index and cardiometabolic abnormalities. Unadjusted (red estimates) and adjusted (blue estimates) are both reported. Multivariate models were adjusted for age, gender, smoking status, physical activity level, alcohol intake, resting sleeping patterns, eating patterns, and psychosocial characteristics.

Figure 4.

Unadjusted and adjusted associations between subclinical atherosclerosis and body size phenotypes. Panel A shows OR (95% CI) for the number of plaques assessed by two-dimensional vascular ultrasound (2DVUS), whereas panel B displays the estimates for coronary artery calcium score, and panel C for the multi-territorial extent. Unadjusted (black estimates) and adjusted (blue estimates) are reported in all panels. The model was adjusted by age, gender, smoking status, physical activity level, alcohol intake, resting sleeping patterns, eating patterns, and psychosocial characteristics.