Diabetes Prevention Success in American Indians
Researcher Luohua Jiang, PhD, studies success factors in diabetes prevention programs for American Indians
Luohua Jiang, PhD
Epidemiologist and Biostatistician, University of California, Irvine
Psychosocial Behavioral Medicine
ADA Research Funding
Clinical Translational Research, Sponsored in part by Video Gaming Technologies, Inc. Jon Yarbrough, Founder and CEO
There are hundreds of American Indian tribes in the U.S. each with different cultures, languages, histories, and lifestyles. And yet they have at least one thing in common: type 2 diabetes.
“In 2011, American Indians had the highest age-adjusted rates of diabetes in the U.S.” says Luohua Jiang, an epidemiologist at the University of California, Irvine. “It’s about 16 percent, almost twice the rate in the general population.”
To address the problem, the Indian Health Service began a program in 2004 to fund a demonstration project in dozens of communities across the nation. The project was based on the findings of the Diabetes Prevention Program, a study of thousands of people with prediabetes conducted in the 1990s. The DPP showed that dietary changes and exercise were very effective at preventing type 2 diabetes, even more so than the medication metformin, which often is the first drug prescribed to treat the condition.
The interventions the Indian Health Service launched were part of a 16-session course focusing on things such as, physical activity, eating less fat, and stress management. Between 2006 and 2009, locally applied versions of the course were given in 36 American Indian communities across the U.S. from Chehalis, Wash. to Wisconsin’s Ho-Chunk Nation to Zuni Pueblo in New Mexico. More than 2,500 people took part, and researchers collected data on everything from income and child care to blood sugar levels and weight loss.
With the help of a grant from the American Diabetes Association, Jiang is crunching those numbers to understand what worked and what didn’t. “We want to evaluate the implementation in a real-world setting,” she says. “The idea is to design interventions to help those who are benefiting less right now.”
One finding, for example, was that showing up was important. “Compared to those who attended all 16 classes, those who did not had a significantly higher incidence rate [of type 2 diabetes],” she says. That may seem obvious, but Jiang wanted to dive deeper, to figure out why some people made it to class and others missed out.
First, she combed through the data and discovered that people who attended more classes had some things in common. “Older age, being retired, and a higher household income all relate to higher retention and success,” she says. On the other side of the coin, “people with lower socioeconomic status and more baseline chronic pain had higher dropout rates.”
Outside factors also played a role. “Younger staff members had a harder time retaining participants,” Jiang notes. “Culturally, perhaps that’s because people respect their elders more.” And the larger the geographic size of the reservation, she found, the smaller the attendance. When homes are spread out, it can be more difficult or time-consuming to reach weekly classes.
In the future, Jiang’s analyses may help tailor education programs to American Indian communities. Research has shown that diabetes’ impact on American Indian and Alaskan Native communities is as varied as their cultures and geography would suggest. While the overall rate of diabetes in American Indians is 16 percent, it’s just 6 percent in Alaskan Natives and more than 33 percent in southwest Arizona. “If you ask a young man in an American Indian community in southern Arizona if he has diabetes, the answer could be ‘not yet,’ ” Jiang says. “It’s really sad.”
One idea she’s working on is a sort of scoring system. By identifying risk factors and sorting out who is most likely to drop out (and why), she thinks she can keep them coming to class and prevent type 2 diabetes. “If they have a high score, you’d put them in the high-risk group, and allocate resources in a more focused way and teach them,” she says. “For those who are lower risk, you don’t have to worry so much, or spend as much time tracking their progress.”
Jiang’s work won’t produce a pill you can take or a new medical device. But in a world with limited resources, crunching the numbers to understand what works and what doesn’t is a way to make prevention efforts as effective and efficient as possible.
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