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.

Table 1

Demographics and pre/post measurements of subjects in the CGM/GEM study and group means for the earlier SMBG/GEM study

AssessmentSubjectsMeanSDSMBG/GEM (group mean)
GEM052GEM053GEM054GEM055
Demographics 
 Age (years)  60 57 66 65 62.0 4.2 55.3 
 Sex     
 BMI (kg/m2 55.5 30.6 26 38.1 37.6 13.0  
 Duration of type 2 diabetes (years)  4.5 2.6 1.5 2.1 
 Medication (0 = none, 1 = metformin, 2 = two medications)  1.3 0.5 
Metabolic control 
 HbA1c (%) (Labs_HbA1cPre 7.8 0.5 8.4 
Post 6.3 7.2 6.1 6.7 0.5 7.4 
Self-regulatory behaviors 
 Knowledge (Qz total score) Pre 17 10 18 13 14.5 3.7 15.5 
Post 15 18 20 22 18.8 3.0 16.9 
 High–glycemic load foods (Qx_HGL) Pre 21 25 18 45 27.3 12.2 30.7 
Post 6.3 4.3 14.9 
 Low–glycemic load foods (Qx_LGL) Pre 22 36 47 34 34.8 10.2 42.4 
Post 42 22 76 89 57.3 30.7 37.5 
 Behavioral challenge (1 = low, 0 = high) Pre 0.25  0.41 
Post  0.54 
 Total carbohydrates (ASA24_CARB) Pre 328 328 126 191 243.3 101.4 223.3 
Post 215 161 110 116 150.5 48.7 131.1 
 Total fiber (ASA24_FIBE) Pre 43 15 20 18 24.0 12.8 19.9 
Post 17 11 26 12 16.5 6.9 15.9 
 Total fat (ASA24_TFAT) Pre 122 192 64 142 130.0 52.9 93.6 
Post 119 108 89 54 92.5 28.5 77.7 
 Saturated fat (ASA24_SFAT) Pre 30 63 15 41 37.3 20.2 28.9 
Post 37 46 36 29 37.0 7.0 23.9 
 Protein (ASA24_PROT) Pre 87 129 119 161 124.0 30.5 88.8 
Post 122 111 127 29 97.3 46.0 83.3 
 Calories (ASA24_KCAL) Pre 2,698 3,557 1,510 2,956 2,680.3 859.2 2,085 
Post 2,399 2,059 1,708 1,019 1,796.3 590.0 1,545 
 Pedometer (steps) Pre 1.67 32 8.4 15.7 20.1 
Post 13 39 13.0 18.4 35.4 
 #SMBG (SMBG/day) Pre 4.3 0.6 2.9 
Post 2.4 0.4 1.6 
Physical measurements 
 SBP (Stats_Sys) Pre 123 128 139 149 134.8 11.6 124.4 
Post 119 138 146 129 133.0 11.6 128.4 
 DBP (Stats_Dia) Pre 70 70 90 77 76.8 9.4 79.1 
Post 79 85 98 84 86.5 8.1 81.4 
 Weight (Stats_Wt) Pre 347 180 182 214 230.8 79.1 221 
Post 315 173 169 202 214.8 68.4 213.2 
Blood tests 
 HDL (Labs_HDL) Pre 40 69 44 53 51.5 12.9 38.8 
Post 44 75 45 48 53.0 14.8 41.8 
 LDL (Labs_LDL) Pre 85 176 122 128 127.8 37.4 101.9 
Post 69 176 134 152 132.8 45.9 110 
 Triglycerides (Labs_Tri) Pre 130 180 96 153 139.8 35.6 161.9 
Post 82 71 83 192 107.0 56.9 175 
Psychological measurements 
  PAID-5 Pre 13 11 6.5 6.5 7.9 
Post 11 3.3 5.3 5.8 
AssessmentSubjectsMeanSDSMBG/GEM (group mean)
GEM052GEM053GEM054GEM055
Demographics 
 Age (years)  60 57 66 65 62.0 4.2 55.3 
 Sex     
 BMI (kg/m2 55.5 30.6 26 38.1 37.6 13.0  
 Duration of type 2 diabetes (years)  4.5 2.6 1.5 2.1 
 Medication (0 = none, 1 = metformin, 2 = two medications)  1.3 0.5 
Metabolic control 
 HbA1c (%) (Labs_HbA1cPre 7.8 0.5 8.4 
Post 6.3 7.2 6.1 6.7 0.5 7.4 
Self-regulatory behaviors 
 Knowledge (Qz total score) Pre 17 10 18 13 14.5 3.7 15.5 
Post 15 18 20 22 18.8 3.0 16.9 
 High–glycemic load foods (Qx_HGL) Pre 21 25 18 45 27.3 12.2 30.7 
Post 6.3 4.3 14.9 
 Low–glycemic load foods (Qx_LGL) Pre 22 36 47 34 34.8 10.2 42.4 
Post 42 22 76 89 57.3 30.7 37.5 
 Behavioral challenge (1 = low, 0 = high) Pre 0.25  0.41 
Post  0.54 
 Total carbohydrates (ASA24_CARB) Pre 328 328 126 191 243.3 101.4 223.3 
Post 215 161 110 116 150.5 48.7 131.1 
 Total fiber (ASA24_FIBE) Pre 43 15 20 18 24.0 12.8 19.9 
Post 17 11 26 12 16.5 6.9 15.9 
 Total fat (ASA24_TFAT) Pre 122 192 64 142 130.0 52.9 93.6 
Post 119 108 89 54 92.5 28.5 77.7 
 Saturated fat (ASA24_SFAT) Pre 30 63 15 41 37.3 20.2 28.9 
Post 37 46 36 29 37.0 7.0 23.9 
 Protein (ASA24_PROT) Pre 87 129 119 161 124.0 30.5 88.8 
Post 122 111 127 29 97.3 46.0 83.3 
 Calories (ASA24_KCAL) Pre 2,698 3,557 1,510 2,956 2,680.3 859.2 2,085 
Post 2,399 2,059 1,708 1,019 1,796.3 590.0 1,545 
 Pedometer (steps) Pre 1.67 32 8.4 15.7 20.1 
Post 13 39 13.0 18.4 35.4 
 #SMBG (SMBG/day) Pre 4.3 0.6 2.9 
Post 2.4 0.4 1.6 
Physical measurements 
 SBP (Stats_Sys) Pre 123 128 139 149 134.8 11.6 124.4 
Post 119 138 146 129 133.0 11.6 128.4 
 DBP (Stats_Dia) Pre 70 70 90 77 76.8 9.4 79.1 
Post 79 85 98 84 86.5 8.1 81.4 
 Weight (Stats_Wt) Pre 347 180 182 214 230.8 79.1 221 
Post 315 173 169 202 214.8 68.4 213.2 
Blood tests 
 HDL (Labs_HDL) Pre 40 69 44 53 51.5 12.9 38.8 
Post 44 75 45 48 53.0 14.8 41.8 
 LDL (Labs_LDL) Pre 85 176 122 128 127.8 37.4 101.9 
Post 69 176 134 152 132.8 45.9 110 
 Triglycerides (Labs_Tri) Pre 130 180 96 153 139.8 35.6 161.9 
Post 82 71 83 192 107.0 56.9 175 
Psychological measurements 
  PAID-5 Pre 13 11 6.5 6.5 7.9 
Post 11 3.3 5.3 5.8 

See the preliminary study (3) for more details on SMBG/GEM study data. DBP, diastolic blood pressure; F, female; M, male; SBP, systolic blood pressure.

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.

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.

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