Conventional lifestyle modification for type 2 diabetes involves 7% weight loss, avoidance of high-energy foods, and 150 min of weekly exercise (1). Although effective at preventing and treating diabetes, this approach is not appropriate for those who do not need or want to lose weight or who cannot maintain weight loss. An alternative may be to target postprandial glucose (PPG), the major contributor to HbA1c (2). The GEM (glycemic load, exercise, and monitoring blood glucose) lifestyle modification program focuses on diminishing PPG by selecting low–glycemic load foods to prevent PPG spikes, reducing PPG with postprandial exercise, and using systematic self-monitoring of blood glucose (SMBG). Systematic SMBG educates individuals about the impact of different foods and physical activities on PPG, activates them to take action when glucose is outside of desired limits, and motivates them to repeat choices that produce desired glucose levels. Therefore, GEM represents a paradigm shift from reducing insulin resistance through reducing fat to reducing PPG.
In a preliminary study, GEM effectively lowered HbA1c and promoted positive but not negative side effects (3). Despite the potential benefits of systematic SMBG to educate, activate, and motivate positive choices, GEM subjects in the preliminary study (3) did not perform more SMBG than subjects undergoing routine care, despite receiving free SMBG supplies. We hypothesized that more robust glucose feedback might be advantageous.
Here reported is the feasibility and efficacy of replacing systematic SMBG with continuous glucose monitoring (CGM) to increase qualitative and quantitative feedback. By simply glancing at a CGM device, individuals can immediately access their current glucose level and its direction and rate of change.
Six recently diagnosed adults followed the GEM program and monitored glucose with CGM. Two dropped out because of psychiatric issues. Participants read five GEM manual chapters at home and then discussed their relevance to their daily routine during each of five group sessions (see preliminary study for details [3]). Participants were assessed at baseline and at 3-month follow-up. Subject demographics and results are shown in Table 1; the last column shows results from the GEM/SMBG preliminary study.
All subjects substantially lowered their HbA1c. Mean HbA1c fell from 7.8 to 6.7%, which is a greater improvement than the reduction from 8.4 to 7.4% in the preliminary study. Participants also consumed fewer high–glycemic load foods, fewer grams of carbohydrate, and fewer calories without increasing fat intake.
Unlike those who used SMBG, subjects who monitored glucose with CGM during GEM reported eating more low–glycemic load foods in their daily routine and more frequently chose low–glycemic load foods in a behavioral challenge during pre/post assessments. Additionally, subjects who used CGM appeared to perform more SMBG and have fewer diabetes-associated problems (evaluated via Problem Areas in Diabetes [PAID] questionnaire) at follow-up.
This pilot study affirms the efficacy of GEM and further suggests that GEM intervention may be augmented with CGM to provide continuous and immediate feedback about the consequences of one’s food and activity choices on glucose levels. These CGM benefits are consistent with the findings of Vigersky et al. (4). Studies that highlight the central role of glucose feedback in GEM, to educate, activate, and motivate individuals, contrast with research that found little benefit of nonsystematic use of SMBG by individuals managing type 2 diabetes (5). The small sample size and two dropouts limit extrapolation of findings.
Article Information
Acknowledgments. The authors thank Lawrence Fisher, Department of Family and Community Medicine, University of California, San Francisco, for thoughtful review and critique of the manuscript.
Funding. Dexcom grant IIS-2014-047 provided G4 PLATINUM CGM sets, supplies, and partial financial support to conduct this project.
Duality of Interest. D.J.C. received a grant from Dexcom that provided G4 PLATINUM CGM sets, supplies, and partial financial support to A.D. for this project. D.J.C. has served as a consultant for Pfizer, Merck, and Sanofi. The University of Virginia received support for contract research from Eli Lilly and Sanofi conducted by A.L.M. No other potential conflicts of interest relevant to this article were reported.
The sponsor was not involved in the design or conduct of the study or in the preparation of the manuscript.
Author Contributions. D.J.C. wrote the manuscript and researched data. A.G.T., W.S.Y., and A.L.M. contributed to the discussion and reviewed and edited the manuscript. M.M. analyzed and researched data. A.D. ran the subjects and reviewed and edited the manuscript. S.H. was responsible for securing psychological questionnaire data. D.J.C. is the guarantor of this work and, as such, had full access to all the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.
Clinical trial reg. no. NCT02432391, clinicaltrials.gov.
