Family History of Type 2 Diabetes: A Population-Based Screening Tool for Prevention?

Genet Med. 2006 Feb;8(2):102-8. doi: 10.1097/01.gim.0000200949.52795.df.


Purpose: To evaluate the use of self-reported family medical history as a potential screening tool to identify people at-risk for diabetes.

Methods: The HealthStyles 2004 mail survey comprises 4345 US adults who completed a questionnaire to ascertain personal and family history of diabetes, perceived risk of diabetes, and practice of risk-reducing behaviors. Using number and type of affected relatives, respondents were ranked into three familial risk levels. Adjusted odds ratios (AORs) were obtained to evaluate associations between familial risk and prevalent diabetes, perceived risk of disease, and risk-reducing behaviors. Validity of family history as a screening tool was examined by calculating sensitivity, specificity, and positive and negative predictive values.

Results: Compared to those of average risk, people with moderate and high familial risk of diabetes were more likely to report a diagnosis of diabetes (AOR: 3.6, 95% CI: 2.8, 4.7; OR: 7.6, 95% CI: 5.9, 9.8, respectively), a higher perceived risk of diabetes (AOR: 4.6, 95% CI: 3.7, 5.7; OR: 8.5, 95% CI: 6.6, 17.7, respectively), and making lifestyle changes to prevent diabetes (AOR: 2.2, 95% CI: 1.8, 2.7; OR: 4.5, 95% CI: 3.6, 5.6, respectively). A positive familial risk of diabetes identified 73% of all respondents with diabetes and correctly predicted prevalent diabetes in 21.5% of respondents.

Conclusion: Family history of diabetes is not only a risk factor for the disease but is also positively associated with risk awareness and risk-reducing behaviors. It may provide a useful screening tool for detection and prevention of diabetes.

Publication types

  • Evaluation Study

MeSH terms

  • Adolescent
  • Adult
  • Aged
  • Attitude to Health
  • Cross-Sectional Studies
  • Diabetes Mellitus, Type 2 / prevention & control*
  • Family Health*
  • Female
  • Humans
  • Male
  • Middle Aged
  • Obesity / complications
  • Population Surveillance
  • Predictive Value of Tests
  • Risk Assessment
  • Risk Factors
  • Risk-Taking