Cardiovascular disease risk factors in youth with type 1 and type 2 diabetes: implications of a factor analysis of clustering

Abstract

Background: The extent to which cardiovascular disease (CVD) risk factors cluster in youth with a diagnosis of type 1 (T1DM) or type 2 diabetes mellitus (T2DM) is unclear. Therefore, we aimed to evaluate potential clustering of traditional CVD risk factors that may reflect an unmeasured but unifying single pathology that may explain the phenomenon of the metabolic syndrome in these youths.

Methods: Youths who participated in the SEARCH for Diabetes in Youth study with diabetes diagnosed <20 years, with current age >10 years (maximum current age, 22 years) were included. Confirmatory factor analysis (CFA) was performed to determine statistical associations among CVD risk factors, including obesity, blood pressure, triglycerides, and high-density lipoprotein cholesterol (HDL-C). Diabetes type was defined by diabetes autoantibodies (DAA) and fasting C-peptide (FCP); type 1 (T1DM, DAA positive, and FCP <0.8 ng/mL, n = 1198) and type 2 (T2DM, DAA negative, and FCP >2.9 ng/mL, n = 95). For T1DM, the sample was split randomly and analyses were conducted separately in each split sample.

Results: Among five prespecified data structures ranging from a single underlying factor to a hierarchical structure of factors, the worst-fitting model for both of the T1DM split samples was the single-factor structure and the best-fitting model was a three-correlated-factor structure. The three correlated factors identified were obesity, lipids, and blood pressure. Results were very similar for youths with T2DM.

Conclusion: There is little evidence that a single factor underlies the CVD risk factor pattern in youths with diabetes. The concept of the metabolic syndrome provides a useful description of clinical characteristics but does not efficiently capture a single target for etiologic research among youths with diabetes.

FIG. 1.

Maximum likelihood parameter estimates from the best-fitting CVD risk factor model based on confirmatory factor analysis: three correlated factors. (Panel 1) Youths with T1DM first-half sample (n = 600) (top), second-half sample (n = 598) (bottom). (Panel 2) T2DM (n = 95), SEARCH for Diabetes in Youth 2001–2003.