New Study Highlights Potential for Early Detection of Diabetes through Household Analysis

A recent study presented at the European Association for the Study of Diabetes (EASD) Annual Meeting in Vienna, Austria, suggests that analyzing electronic health records of people living in the same household as individuals with prediabetes can help identify those at high risk of developing type 2 diabetes. The study, led by Dr. Tainayah Thomas from Stanford University, used electronic health record (EHR) and administrative data to identify household members of adult patients with prediabetes and evaluate their diabetes risk factors.

Key Findings

The study identified nearly 30,000 adults with type 2 diabetes and almost 50,000 with prediabetes living in the same households as index cases with prediabetes. The researchers found that [1]:

  • 65% of adult household members had diabetes risk factors, including overweight or obesity, hypertension, abnormal blood fats, or cardiovascular disease.
  • 32% of adult household members had an abnormal blood sugar profile, indicating prediabetes.
  • 20% of adult household members had prediabetes laboratory results, and 12% had blood test results showing full-blown type 2 diabetes.

Implications for Diabetes Prevention

The study’s findings highlight the potential for early detection and prevention of diabetes by analyzing household members of individuals with prediabetes. By identifying high-risk individuals within households, healthcare providers can target prevention efforts and promote lifestyle changes to reduce the risk of developing type 2 diabetes.

Future Directions

The researchers plan to further investigate household members, including assessing follow-up care, diagnosis of diabetes or other conditions, enrollment in lifestyle interventions, and prescription of glucose-lowering medications. This study’s approach could be used by health systems to identify and tailor diabetes prevention messaging and programs to entire households instead of just individuals.

This study demonstrates the potential for using electronic health records to assess household diabetes risk and identify high-risk individuals. By targeting prevention efforts at the household level, healthcare providers may be able to reduce the incidence of type 2 diabetes and improve health outcomes for individuals and families.

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