Risk distribution and its influence on the population targets for diabetes prevention

Prev Med. 2014 Jan:58:17-21. doi: 10.1016/j.ypmed.2013.10.007. Epub 2013 Oct 23.

Abstract

Objective: To quantify the influence of type 2 diabetes risk distribution on prevention benefit and apply a method to optimally identify population targets.

Methods: We used data from the 2011 Canadian Community Health Survey (N=45,040) and the validated Diabetes Population Risk Tool to calculate 10-year diabetes risk. We calculated the Gini coefficient as a measure of risk dispersion. Intervention benefit was estimated using absolute risk reduction (ARR), number-needed-to-treat (NNT), and number of cases prevented.

Results: There is a wide variation of diabetes risk in Canada (Gini=0.48) and with an inverse relation to risk (r=-0.99). Risk dispersion is lower among individuals meeting an empirically derived risk cut-off (Gini=0.18). Targeting prevention based on a risk cut-off (10-year risk ≥ 16.5%) resulted in a greater number of cases prevented (340 thousand), higher ARR (7.7%) and lower NNT (13) compared to targeting individuals based on risk factor targets.

Conclusions: This study provides empirical evidence to demonstrate that risk variability is an important consideration for estimating the prevention benefit. Prioritizing target populations using an empirically derived cut-off based on a multivariate risk score will result in greater benefit and efficiency compared to risk factor targets.

Keywords: ARR; CCHS; Canadian Community Health Survey; DPoRT; Diabetes Population Risk Tool; Diabetes mellitus, type 2; Primary prevention; Risk assessment; absolute risk reduction.

Publication types

  • Validation Study

MeSH terms

  • Adult
  • Aged
  • Algorithms
  • Canada / epidemiology
  • Community Health Services*
  • Diabetes Mellitus / diagnosis
  • Diabetes Mellitus / epidemiology
  • Diabetes Mellitus / prevention & control*
  • Female
  • Health Surveys
  • Humans
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Numbers Needed To Treat
  • Predictive Value of Tests
  • Reproducibility of Results
  • Risk Assessment / standards*
  • Risk Factors