Utility of existing diabetes risk prediction tools for young black and white adults: Evidence from the Bogalusa Heart Study

Benjamin D. Pollock, Tian Hu, Wei Chen, Emily W. Harville, Shengxu Li, Larry S. Webber, Vivian Fonseca, Lydia A. Bazzano

Research output: Contribution to journalArticlepeer-review

7 Scopus citations


Aims To evaluate several adult diabetes risk calculation tools for predicting the development of incident diabetes and pre-diabetes in a bi-racial, young adult population. Methods Surveys beginning in young adulthood (baseline age ≥ 18) and continuing across multiple decades for 2122 participants of the Bogalusa Heart Study were used to test the associations of five well-known adult diabetes risk scores with incident diabetes and pre-diabetes using separate Cox models for each risk score. Racial differences were tested within each model. Predictive utility and discrimination were determined for each risk score using the Net Reclassification Index (NRI) and Harrell's c-statistic. Results All risk scores were strongly associated (p < .0001) with incident diabetes and pre-diabetes. The Wilson model indicated greater risk of diabetes for blacks versus whites with equivalent risk scores (HR = 1.59; 95% CI 1.11–2.28; p = .01). C-statistics for the diabetes risk models ranged from 0.79 to 0.83. Non-event NRIs indicated high specificity (non-event NRIs: 76%–88%), but poor sensitivity (event NRIs: − 23% to − 3%). Conclusions Five diabetes risk scores established in middle-aged, racially homogenous adult populations are generally applicable to younger adults with good specificity but poor sensitivity. The addition of race to these models did not result in greater predictive capabilities. A more sensitive risk score to predict diabetes in younger adults is needed.

Original languageEnglish (US)
Pages (from-to)86-93
Number of pages8
JournalJournal of Diabetes and Its Complications
Issue number1
StatePublished - Jan 1 2017

Bibliographical note

Publisher Copyright:
© 2017 Elsevier Inc.


  • Diabetes
  • Pre-diabetes
  • Race
  • Risk prediction
  • Young adults


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