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Summaries for Patients |16 April 2002

Identifying People at High Risk for Type 2 Diabetes

Article, Author, and Disclosure Information
Author, Article, and Disclosure Information

  • The summary below is from the full report titled “Identification of Persons at High Risk for Type 2 Diabetes Mellitus: Do We Need the Oral Glucose Tolerance Test?” It is in the 16 April 2002 issue of Annals of Internal Medicine (volume 136, pages 575-581). The authors are MP Stern, K Williams, and SM Haffner.


Summaries for Patients are a service provided by Annals to help patients better understand the complicated and often mystifying language of modern medicine.
Summaries for Patients are presented for informational purposes only. These summaries are not a substitute for advice from your own medical provider. If you have questions about this material, or need medical advice about your own health or situation, please contact your physician. The summaries may be reproduced for not-for-profit educational purposes only. Any other uses must be approved by the American College of Physicians-American Society of Internal Medicine.
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What is the problem and what is known about it so far?

Type 2 diabetes mellitus, also known as adult-onset diabetes, is a common disease that interferes with the body's ability to use sugar, resulting in high levels in the blood. Over time, high blood sugar levels can lead to complications such as blindness, kidney failure, and heart disease. Diet, exercise, or medications can prevent people who are at high risk for type 2 diabetes from developing the disease. The standard way of identifying people at risk for type 2 diabetes is to measure blood sugar levels 2 hours after a standard amount of sugar is consumed. This test is called an oral glucose tolerance test, and it is inconvenient and costly. Easier and less costly ways of identifying people who might benefit from strategies to prevent diabetes would be useful.

Why did the researchers do this particular study?

To see whether a mathematical model that uses readily available medical information can predict who is likely to develop diabetes as accurately as an oral glucose tolerance test does.

Who was studied?

1791 Mexican Americans and 1112 non-Hispanic white people who did not have diabetes when they were enrolled in the study.

How was the study done?

The researchers collected information about each patient's medical history, blood pressure, body size, cholesterol levels, and sugar levels (during fasting and during an oral glucose tolerance test). They followed the participants to see who developed diabetes over the next 7.5 years. Then, the researchers developed three mathematical models. The first model used only oral glucose tolerance test results. The second model used only the other medical information (clinical model). The third model used both the oral glucose tolerance test results and the medical information.

What did the researchers find?

The model that used only the medical information was much better at predicting who would develop diabetes than the model that used only the oral glucose tolerance results. Adding the oral glucose tolerance test results to the clinical model improved prediction only slightly.

What were the limitations of the study?

This study included many Mexican Americans, who have a higher risk for type 2 diabetes than many other ethnic groups. Before such a model could be used widely, similar results would need to be demonstrated in more diverse sets of people. In addition, the mathematical models would need to be translated for use on doctors' own computers.

What are the implications of the study?

A mathematical model that uses readily available medical information may prove to be a good way to identify patients at risk for type 2 diabetes while avoiding the cost and inconvenience of oral glucose tolerance tests.

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Identifying People at High Risk for Type 2 Diabetes. Ann Intern Med. 2002;136:I–29. doi: https://doi.org/10.7326/0003-4819-136-8-200204160-00002

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Published: Ann Intern Med. 2002;136(8):I-29.

DOI: 10.7326/0003-4819-136-8-200204160-00002

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2002 American College of Physicians
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