Glycemic load, exercise, and monitoring blood glucose (GEM): A paradigm shift in the treatment of type 2 diabetes mellitus
Introduction
In 2012, the American Diabetes Association (ADA) and the European Association for the Study of Diabetes [1] recommended lifestyle modification (LM) as the sole initial treatment for type 2 diabetes mellitus when diagnostic glycosylated hemoglobin (HbA1c) is ≤7.5%. Specifically: “Weight reduction, achieved through dietary means alone or with adjunctive medical or surgical intervention, improves glycemic control and other cardiovascular risk factors. Modest weight loss (5–10%) contributes meaningfully to achieving improved glucose control … Foods high in fiber (such as vegetables, fruits, whole grains, and legumes), low-fat dairy products, and fresh fish should be emphasized. High-energy foods, including those rich in saturated fats, and sweet desserts and snacks should be eaten less frequently and in lower amounts … As much physical activity as possible should be promoted, aiming for at least 150 min/week of moderate activity, including aerobic, resistance, and flexibility training.”. Thus, the ADA recommends weight loss, less consumption of high-energy foods, and at least 150 min/week of moderate physical activity. It does not specify the role of self-monitoring of blood glucose (SMBG) in the management of type 2 diabetes mellitus [2].
Consistent with the ADA recommendations, a major NIH-funded, multi-center trial (Look AHEAD) [3] randomized 5145 overweight adults with poorly controlled type 2 diabetes mellitus to either 42 sessions of an intensive lifestyle modification intervention promoting weight loss through decreased caloric intake and increased exercise or to a diabetes support group. The weight loss group experienced an 8% reduction in weight and a 0.64% reduction in HbA1c, both significantly greater than the support group.
Since the conclusion of the Look AHEAD project, several investigations have focused on specific diets, exercise, and blood glucose (BG) monitoring strategies. Our review of this literature [7] suggests an optimal LM program should emphasize a low glycemic load (GL) diet [8], an exercise program combining aerobic and strength activities, and structured SMBG [2]. To the authors’ knowledge, an integrated combination of these three approaches has not been published. Therefore, we have devised a program called the Glycemic load, Exercise, and Monitoring blood glucose program (GEM) that incorporates these strategies.
This represents a paradigm shift from conventional approaches in that GEM:
- 1.
Focuses on reducing postprandial BG elevations, not weight loss.
- 2.
Emphasizes avoidance of high GL foods, not restriction of calories or macronutrients.
- 3.
Encourages eating a variety of available, culturally appropriate, affordable foods that do not produce large elevations in BG, rather than focusing on a specific diet.
- 4.
Recommends increasing physical activities during one's daily routine as opposed to following a structured exercise program.
- 5.
Relies heavily on systematic BG monitoring to [4], [5], [6]:
- a.
Educate individuals about their routine foods that significantly raise their BG levels and therefore should be avoided (e.g., banana, energy bars, corn), about familiar and new foods that do not significantly impact their BG and therefore should be encouraged, and about types of physical activities (plus the timing and duration during the day) that promote lowering BG.
- b.
Motivate individuals to repeat choices that led to desired BG levels and avoid choices that led to personally unacceptably high BG levels.
- c.
Activate individuals to eat foods and engage in physical activities based upon selected BG parameters.
- a.
This study used a randomized, 2 between (GEM vs. Routine Care [RC]) × 2 within (0- and 6-month assessments) design to test the primary hypothesis that GEM would lower HbA1c more than RC of adults with type 2 diabetes mellitus diagnosed within the past 5 years. The secondary hypotheses were that GEM would lead to more frequent SMBG, more physical activities, and ingestion of fewer high GL foods than would occur with RC. Ancillary benefits of better psychological functioning without worsening hyperlipidemia were also expected. The study was approved by the University of Virginia Institutional Review Board for Health Sciences Research.
Section snippets
Subjects, materials and methods
The general public was informed of the project through newspaper, Internet, and radio announcements, and physician referrals. Forty-seven individuals who satisfied the inclusion/exclusion criteria were consented. Given that enrollment was ongoing, three individuals who completed RC were subsequently crossed over to the GEM group. Inclusion criteria were: (1) Diagnosed with type 2 diabetes mellitus within the past 5 years, (2) Age >24 and <80 years, (3) HbA1c ≥7.0%, (4) Approval of primary care
Overview
2 between (Group) × 2 within (Time) Mixed-Model ANOVA's were used for continuous variables to determine change in variables (Time) and a differential effect of GEM (Interaction). Dichotomous variables were analyzed with Chi Square Tests for Independence. Pearson's correlations were used to explore relationships between behavior change variables and change in HbA1c for GEM subjects. Table 1, Table 2 show the pre- and post-intervention means and standard deviations of the outcome variables, the
Conclusions
The findings of this preliminary study demonstrate that this five-session, 15-week GEM program had a significant and robust effect on metabolic control. Most notable is the 1.03% reduction in HbA1c over the last 3 months of the 6-month observation period when there was no study-directed intervention being offered. This reduction compares favorably to the Look AHEAD program in terms of the magnitude of improvement in HbA1c (1.03 vs. 0.64%), number of treatment sessions (5 vs. 42), and length of
Conflict of interest
D.J.C. received a grant from LifeScan, Inc., which provided Verio IQ meters, supplies, and partial financial support to A.L.M., H.S., and A.D. for this project. The sponsor was not involved in the design or conduct of the study, or in the preparation of this manuscript. D.J.C. has served as a consultant to 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
Acknowledgments
Funding: A grant from LifeScan, Inc. (Totality 126392) provided Verio IQ meters, supplies, and partial financial support to conduct this project.
Assistance: The authors are indebted to the professional advisory board members who reviewed the content of the GEM manual: Bob Anderson, Sheri Colberg-Och, Lawrence Fisher, Kate Lorig, Carla Miller, William Polonsky, Donna Rice, John R. Sirard, Barbara Stetson, Heather Stuckey, and Diane E. Whaley; the following nurse practitioner students who
References (22)
- et al.
Results that matter: structured vs. unstructured self-monitoring of blood glucose in type 2 diabetes
Diabetes Res Clin Pract
(2012) - et al.
International table of glycemic index and glycemic load values: 2002
Am J Clin Nutr
(2002) - et al.
The Automated Self-Administered 24-Hour Dietary Recall (ASA24): a resource for researchers, clinicians, and educators from the National Cancer Institute
J Acad Nutr Diet
(2012) - et al.
Six minute walk distance in healthy subjects aged 55–75 years
Respir Med
(2006) - et al.
Management of hyperglycemia in type 2 diabetes: a patient-centered approach: position statement of the American Diabetes Association (ADA) and the European Association for the Study of Diabetes (EASD)
Diabetes Care
(2012) - et al.
Using the common sense model of self-regulation to review the effects of self-monitoring of blood glucose on glycemic control for non-insulin-treated adults with type 2 diabetes
Diabetes Educ
(2013) Long-term effects of a lifestyle intervention on weight and cardiovascular risk factors in individuals with type 2 diabetes: four year results of the Look AHEAD trial
Arch Intern Med
(2010)- et al.
Personalizing treatment in type 2 diabetes: a self-monitoring of blood glucose inclusive innovative approach
Diabetes Technol Ther
(2012) - et al.
Self-monitoring of blood glucose in noninsulin-using type 2 diabetic patients
Diabetes Care
(2013) - et al.
Impact of behavioral interventions in the management of adults with type 2 diabetes mellitus
Curr Diabetes Rep
(2013)