Development of a childhood metabolic syndrome risk score for predicting adult disease

Background:

The metabolic syndrome (MetS) is a cluster of clinical indices that increase risk for Type 2 diabetes (T2DM) and coronary artery disease (CAD). The diagnosis of MetS is based on cut-off points for these different components, including waist circumference, triglycerides, HDL cholesterol, blood pressure, and fasting glucose. However, the best way to diagnose MetS in children remains unclear, and current attempts result in racial/ethnic discrepancies.

Methods:

Using 1999-2006 data from the National Health and Nutrition Examination Survey (NHANES), we designed a MetS risk score for children. This score was based on elevations of serum factors associated with long-term risk for T2DM and CAD: fasting insulin, C-reactive protein, and uric acid. Principal components analysis was used to develop a score based on these surrogates, and linear regression was then employed to estimate the gender and racial/ethnic specific contributions of standard MetS components (e.g. lipids, glucose) to this score. These equations were validated using NHANES data (2007-2008).

Results:

Gender and racial/ethnic specific equations were developed to predict risk of MetS in children. The resulting scores from these equations, with higher values indicating higher risk, do not exhibit racial/ethnic discrepancies that were observed in previously proposed MetS criteria.

Discussion:

These new equations produce a clinically accessible and interpretable MetS score that can be used to identify children at higher risk for developing adult diseases related to MetS, who could then be targeted for increased intervention. Additionally, they provide a powerful new outcome that can be utilized in childhood obesity and MetS research.