Abstract

Objective: Optimal prevention of young-onset type 2 diabetes requires identification of the early-life modifiable risk factors. We aimed to do this using longitudinal data in 1,604 5–19yr old initially non-diabetic American Indians.

Research Design and Methods: For type 2 diabetes prediction, we derived an optimally-weighted, continuously distributed, standardized multivariate score (zMS) comprised of commonly measured metabolic, anthropometric and vascular traits (i.e., fasting and 2hr glucose, HbA1c, BMI, waist circumference, fasting insulin, HDL-C, triglycerides, blood pressures), and compared the predictive power for each feature against zMS.

Results: In separate Cox proportional hazard models, adjusted for age, sex, and ethnicity, zMS and each of its component risk factors were associated with incident type 2 diabetes. Stepwise proportional hazards models selected fasting glucose, 2hr glucose, HDL-C, and BMI as independent diabetes predictors; individually these were weaker predictors than zMS (p<0.01). However, a parsimonious summary score combining only these variables had similar predictive power as zMS (p=0.33). Although intrauterine diabetes exposure or parental history of young-onset diabetes increased a child's absolute risk of developing diabetes, the magnitude of the diabetes-risk relationships for zMS and the parsimonious score were similar irrespective of familial risk factors.

Conclusions: We have determined the relative value of the features of the metabolic syndrome in childhood for the prediction of subsequent type 2 diabetes. Our findings suggest that strategies targeting obesity, dysregulated glucose homeostasis and low HDL-C during childhood and adolescence may have most success in preventing diabetes.