In the April 2014 issue, Kahn and Davidson (1) assert that implementing structured lifestyle programs to prevent diabetes in U.S. communities is not supported by science, nor justified economically. We interpret the same evidence differently and argue that integrating lifestyle programs in clinical and public health systems is necessary and good value.
Following proof of concept established in five major diabetes prevention outcome trials, over 35 practical trials have tested community, clinical, and virtual/telephonic intervention delivery (2–4). These trials were not intended to measure diabetes incidence; rather, they aimed to identify feasible avenues to deliver interventions in the complex market-oriented U.S. health care system and test whether similar process and intermediate outcomes as observed in the principal outcomes trials could be achieved. Across these practical translation trials, an average 4% weight loss was observed at 1 year, which was comparable to that achieved in the Finnish Diabetes Prevention Study (DPS), less than the 7% in the U.S. Diabetes Prevention Program (DPP), but superior to weight loss achieved in three other successful outcomes trials (3,4).
Finding ways to improve weight loss and maintenance may further improve effectiveness, but the current approaches have sufficient evidence to justify implementation. Although mean weight loss is one barometer of success, we caution against its sole use for several reasons. Mean weight change reflects the average among diverse responses to intervention, wherein the prevention effect may be driven by those with stronger weight-loss responses. Furthermore, weight loss is probably not the sole mechanism in preventing diabetes. At least four randomized controlled trials (RCTs) found reduced diabetes incidence with little or no weight loss, consistent with cohort studies showing that physical activity and diet quality (whole grains, sugar intake, red meat, type of fat) are independently important (2,4). In the DPS, meeting multiple lifestyle goals was as important as weight loss (5). Observations from DPP that weight loss was the dominant factor could be partially influenced by weight change having less measurement error than other variables. Across studies, the common lesson is that supportive, sustained coaching to facilitate participation, self-monitoring, healthier diets, increased physical activity, and healthy weight is beneficial.
More important, the 58% relative reduction in diabetes incidence observed in DPP and DPS is a magnitude largely unheard of in chronic disease prevention and provides a large margin to account for some dilution of intervention intensity that generally occurs with real-world implementation (2,4). Other preventive interventions, including lipid-lowering and antihypertensive therapies and smoking cessation counseling, have similar or weaker effect sizes and are also diluted in practice due to implementation fidelity and adoption issues, yet are widely recommended and supported (6). Rather than demand repeated outcomes trials for those interventions, the health community has rightly focused on improving access and adherence to maximize their diffusion and impact. The same should be true for diabetes prevention programs.
Evidence that lifestyle programs lower cardiovascular disease (CVD) incidence indeed remains limited. The Da Qing study reported reductions in retinopathy and CVD mortality among lifestyle intervention participants (7), but to date, the DPS and DPP have not. However, CVD reduction is not essential to justifying implementing diabetes prevention from either a health impact or cost-effectiveness (CE) perspective as high-risk individuals and health plans alike will benefit from fewer medications and bothersome symptoms, improved quality of life, and reduced complications and costs that usually follow.
A newly released systematic review of CE of lifestyle intervention programs found CE ratios consistently around $10,000 per quality-adjusted life-year gained (2). These favorable CE ratios stem from delaying the need for costly medications and medical procedures and shifting from one-on-one to group-based intervention delivery. Of importance, these estimates assume lower effectiveness in community settings than observed in RCTs. Contrary to the argument of Kahn and Davidson (1), most CE studies used (higher) costs from the principal RCTs themselves and several used short time horizons, making estimates conservative. The single CE study highlighted by Kahn and Davidson as being high cost and low value is a far outlier, assumed one-on-one delivery, and reported much better CE ratios with group-based interventions (8). Continued progress reducing implementation costs without compromising quality and refining risk stratification will further solidify the value of diabetes prevention programs.
Finally, high prevalence of prediabetes is no argument against action given the progress made in developing efficient, effective community-based programs. Scaling up prevention will indeed stand a stronger chance of reducing diabetes incidence if it can be paired with complementary approaches improving our built environment, healthy food availability, and clinical services, as Kahn and Davidson mention. However, these are not substitutes for helping high-risk individuals to prolong their diabetes-free lives.
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Duality of Interest. No potential conflicts of interest relevant to this article were reported.
The findings and conclusions in this article are those of the authors and do not necessarily represent the official position of the Centers for Disease Control and Prevention.
