Metabolic Risk Factors and Type 2 Diabetes Incidence in American Indian Children

Abstract

Context: Data are lacking on how metabolic risk factors during childhood affect the long-term risk of type 2 diabetes.

Objectives: Assess four metabolic risk factors as predictors of type 2 diabetes and determine whether the risk differs between younger and older children.

Design: In a prospective cohort study conducted between 1965 and 2007, participants were followed for development of diabetes. Baseline measurements included body mass index (BMI), blood pressure, serum cholesterol, and 2-hour plasma glucose after an oral glucose tolerance test. Additional analyses divided subjects into two groups according to baseline age, 5–11 and 12–19 years.

Setting: Gila River Indian Community in Arizona.

Participants: A total of 5532 nondiabetic Pima Indian children 5–19 years old.

Results: A total of 1281 children developed diabetes (median follow-up, 12.4 years). Diabetes incidence was higher in overweight children (BMI ≥ 85th percentile) than in nonoverweight children. Nonoverweight children had the lowest risk of diabetes (20-year cumulative incidence, 9.5%), whereas overweight children with impaired glucose tolerance (2-hour glucose ≥ 140 mg/dL) had the highest (79.0%). The relative risk for children with metabolic abnormalities compared with their healthy counterparts was higher in younger children than in older children early in follow-up. BMI and 2-hour glucose were related to incident diabetes in multivariable models (predicted 15-year cumulative incidence for the highest vs lowest quartile was 3.9 and 1.8 times as high for BMI and 2-hour glucose, respectively; P < .001), whereas blood pressure and cholesterol were not.

Conclusions: BMI and impaired glucose tolerance in children are strong predictors of type 2 diabetes. Other components of the “metabolic syndrome” are not.

Figure 1.

Twenty-year cumulative incidence of type 2 diabetes by baseline metabolic category.

Figure 2.

Predicted cumulative incidence of diabetes by quartile rank of risk factor. A–C, Model 1 is adjusted for follow-up age, sex, and the interaction between age and the risk factor of interest. D–F, Model 2 is further adjusted for the other risk factors and their age-interactions. P values are given for the linear trend.