Fulfilling the potential of the National Diabetes Prevention Program

Date: July 1, 2021

By Natalia Olchanski, PhD, MS, Research Assistant Professor and Sam Weidner, BS, Research Assistant

The National Diabetes Prevention Program (NDPP), in operation since 2010, is a 12-month lifestyle and exercise program shown to reduce participant weight by more than 4% and, crucially, to cut diabetes prevalence.  Nonetheless, the program faces hurdles to achieve its intended population impact.

A key issue has been the program’s reach.  While the program itself has expanded to be present in all 50 US states and most territories, only 15% of pre-diabetics in the U.S. are aware of their elevated risk status for developing type 2 diabetes.  Moreover, program participation is low among men, some racial/ethnic minorities, low-income populations, and younger individuals.  Some of these groups include individuals at higher diabetes risk than average for pre-diabetics.

Outreach could be costly. Our research indicates that targeting the highest risk populations would confer the greatest health benefits per dollar invested.  Investing to reach high-risk individuals is even more cost-effective if they are underrepresented in the population now enrolled in the NDPP.  Identifying at-risk individuals has presented a challenge, but recent advancements in screening could provide a tool for achieving that goal.

Expanding point-of-care referrals could also expand the NDPP’s reach.  A large study found that these referrals had a 56% enrollment rate, far better than the 11% enrollment rate achieved by conventional, algorithm-based referrals.  Point-of-care referrals have been rare.  One 2019 study found providers to be 2-to-3 times more likely to suggest general physical activity or dietary advice than to refer patients to a formal program like the NDPP.  Another found that fewer than one-fourth of primary care visits involving pre-diabetic patients addressed diet, exercise, and weight reduction.

Possibly, providers cannot easily identify pre-diabetic patients at greatest risk, but new predictive models could change that.  For example, a new model predicts a pre-diabetic patient’s 3-year risk of developing diabetes using clinical data routinely collected in electronic health records.

As the population of diabetics and pre-diabetics in the United States continues to grow, prevention efforts will remain important. We should use new screening and outreach tools to make those strategies as efficient as possible.  Our ongoing research, funded by a PhRMA Foundation Value Assessment Research Award, explores the variation in value of diabetes prevention programs and the impact of targeting by diabetes risk in real world populations, as they frequently differ from cohorts studied in clinical trials.

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