PT  - JOURNAL ARTICLE
AU  - Laura C Rosella
AU  - Douglas G Manuel
AU  - Charles Burchill
AU  - Thérèse A Stukel
AU  - for the PHIAT-DM team
TI  - A population-based risk algorithm for the development of diabetes: development and validation of the Diabetes Population Risk Tool (DPoRT)
AID  - 10.1136/jech.2009.102244
DP  - 2011 Jul 01
TA  - Journal of Epidemiology and Community Health
PG  - 613--620
VI  - 65
IP  - 7
4099  - http://jech.bmj.com/content/65/7/613.short
4100  - http://jech.bmj.com/content/65/7/613.full
SO  - J Epidemiol Community Health2011 Jul 01; 65
AB  - Background National estimates of the upcoming diabetes epidemic are needed to understand the distribution of diabetes risk in the population and to inform health policy.Objective To create and validate a population-based risk prediction tool for incident diabetes using commonly collected national survey data.Methods With the use of a cohort design that links baseline risk factors to a validated population-based diabetes registry, a model (Diabetes Population Risk Tool (DPoRT)) was developed to predict 9-year risk for diabetes. The probability of developing diabetes was modelled using sex-specific Weibull survival functions for people >20 years of age without diabetes (N=19 861). The model was validated in two external cohorts in Ontario (N=26 465) and Manitoba (N=9899). Predictive accuracy and model performance were assessed by comparing observed diabetes rates with predicted estimates. Discrimination and calibration were measured using a C statistic and Hosmer–Lemeshow χ2 statistic (χ2H–L).Results Predictive factors included were body mass index, age, ethnicity, hypertension, immigrant status, smoking, education status and heart disease. DPoRT showed good discrimination (C=0.77–0.80) and calibration (χ2H–L <20) in both external validation cohorts.Conclusions This algorithm can be used to estimate diabetes incidence and quantify the effect of interventions using routinely collected survey data.