A randomized controlled trial to test the effectiveness of two technology-enhanced diabetes prevention programs in primary care: The DiaBEAT-it study.

Objective: To evaluate the effectiveness of two technology-enhanced interventions for diabetes prevention among adults at risk for developing diabetes in a primary care setting. Methods: The DiaBEAT-it study employed a hybrid 2-group preference (Choice) and 3-group randomized controlled (RCT) design. This paper presents weight related primary outcomes of the RCT arm. Patients from Southwest Virginia were identified through the Carilion Clinic electronic health records. Eligible participants (18 and older, BMI ≥ 25, no Type 2 Diabetes) were randomized to either Choice (n = 264) or RCT (n = 334). RCT individuals were further randomized to one of three groups: (1) a 2-h small group class to help patients develop a personal action plan to prevent diabetes (SC, n = 117); (2) a 2-h small group class plus automated telephone calls using an interactive voice response system (IVR) to help participants initiate weight loss through a healthful diet and regular physical activity (Class/IVR, n = 110); or (3) a DVD with same content as the class plus the same IVR calls over a period of 12 months (DVD/IVR, n = 107). Results: Of the 334 participants that were randomized, 232 (69%) had study measured weights at 6 months, 221 (66%) at 12 months, and 208 (62%) at 18 months. Class/IVR participants were less likely to complete weight measures than SC or DVD/IVR. Intention to treat analyses, controlling for gender, race, age and baseline BMI, showed that DVD/IVR and Class/IVR led to reductions in BMI at 6 (DVD/IVR -0.94, p < 0.001; Class/IVR -0.70, p < 0.01), 12 (DVD/IVR -0.88, p < 0.001; Class/IVR-0.82, p < 0.001) and 18 (DVD/IVR -0.78, p < 0.001; Class/IVR -0.58, p < 0.01) months. All three groups showed a significant number of participants losing at least 5% of their body weight at 12 months (DVD/IVR 26.87%; Class/IVR 21.62%; SC 16.85%). When comparing groups, DVD/IVR were significantly more likely to decrease BMI at 6 months (p < 0.05) and maintain the reduction at 18 months (p < 0.05) when compared to SC. There were no differences between the other groups. Conclusions: The DiaBEAT-it interventions show promise in responding to the need for scalable, effective methods to manage obesity and prevent diabetes in primary care settings that do not over burden primary care clinics and providers. Registration: https://clinicaltrials.gov/ct2/show/NCT02162901, identifier: NCT02162901.

Mitochondrial Epigenetic Changes Link to Increased Diabetes Risk and Early-Stage Prediabetes Indicator.

Type 2 diabetes (T2D) is characterized by mitochondrial derangement and oxidative stress. With no known cure for T2D, it is critical to identify mitochondrial biomarkers for early diagnosis of prediabetes and disease prevention. Here we examined 87 participants on the diagnosis power of fasting glucose (FG) and hemoglobin A1c levels and investigated their interactions with mitochondrial DNA methylation. FG and A1c led to discordant diagnostic results irrespective of increased body mass index (BMI), underscoring the need of new biomarkers for prediabetes diagnosis. Mitochondrial DNA methylation levels were not correlated with late-stage (impaired FG or A1c) but significantly with early-stage (impaired insulin sensitivity) events. Quartiles of BMI suggested that mitochondrial DNA methylation increased drastically from Q1 (20 < BMI < 24.9, lean) to Q2 (30 < BMI < 34.9, obese), but marginally from Q2 to Q3 (35 < BMI < 39.9, severely obese) and from Q3 to Q4 (BMI > 40, morbidly obese). A significant change was also observed from Q1 to Q2 in HOMA insulin sensitivity but not in A1c or FG. Thus, mitochondrial epigenetic changes link to increased diabetes risk and the indicator of early-stage prediabetes. Further larger-scale studies to examine the potential of mitochondrial epigenetic marker in prediabetes diagnosis will be of critical importance for T2D prevention.

Insulin resistance is associated with epigenetic and genetic regulation of mitochondrial DNA in obese humans.

BACKGROUND: Mitochondrial alterations have been observed in subjects with metabolic disorders such as obesity and diabetes. Studies on animal models and cell cultures suggest aberrant glucose and lipid levels, and impaired insulin signaling might lead to mitochondrial changes. However, the molecular mechanism underlying mitochondrial aberrance remains largely unexplored in human subjects. RESULTS: Here we show that the mitochondrial DNA copy number (mtDNAn) was significantly reduced (6.9-fold lower, p < 0.001) in the leukocytes from obese humans (BMI >30). The reduction of mtDNAn was strongly associated with insulin resistance (HOMA-IR: -0.703, p < 0.05; fasting insulin level: -0.015, p < 0.05); by contrast, the correlation between fasting glucose or lipid levels and mtDNAn was not significant. Epigenetic study of the displacement loop (D-loop) region of mitochondrial genome, which controls the replication and transcription of the mitochondrial DNA as well as organization of the mitochondrial nucleoid, revealed a dramatic increase of DNA methylation in obese (5.2-fold higher vs. lean subjects, p < 0.05) and insulin-resistant (4.6-fold higher vs. insulin-sensitive subjects, p < 0.05) individuals. CONCLUSIONS: The reduction of mtDNAn in obese human subjects is associated with insulin resistance and may arise from increased D-loop methylation, suggesting an insulin signaling-epigenetic-genetic axis in mitochondrial regulation.

Effectiveness of a worksite-based weight loss randomized controlled trial: the worksite study.

OBJECTIVE: To determine the effectiveness of an individually targeted Internet-based intervention with monetary incentives (INCENT) at reducing weight of overweight and obese employees when compared with a less-intensive intervention (Livin' My Weigh [LMW]) 6 months after program initiation. METHODS: Twenty-eight worksites were randomly assigned to either INCENT or LMW conditions. Both programs used evidence-based strategies to support weight loss. INCENT was delivered via daily e-mails over 12 months while LMW was delivered quarterly via both newsletters and on-site educational sessions. Generalized linear mixed models were conducted for weight change from baseline to 6 months post-program and using an intention-to-treat analysis to include all participants with baseline weight measurements. RESULTS: Across 28 worksites, 1,790 employees (M = 47 years of age; 79% Caucasian; 74% women) participated. Participants lost an average of 2.27 lbs (P < 0.001) with a BMI decrease of 0.36 kg/m(2) (P < 0.001) and 1.30 lbs (P < 0.01) with a BMI decrease of 0.20 kg/m(2) (P < 0.01) in INCENT and LMW, respectively. The differences between INCENT and LMW in weight loss and BMI reduction were not statistically significant. CONCLUSIONS: This study suggests that INCENT and a minimal intervention alternative may be effective approaches to help decrease the overall obesity burden within worksites.

The association between worksite physical environment and employee nutrition, and physical activity behavior and weight status.

OBJECTIVE: To explore the relationship between worksite physical environment and employee dietary intake, physical activity behavior, and weight status. METHODS: Two trained research assistants completed audits (Checklist of Health Promotion Environments at Worksites) at each worksite (n = 28). Employees (n = 6261) completed a brief health survey before participation in a weight loss program. RESULTS: Employees' access to outdoor areas was directly associated with lower body mass index (BMI), whereas access to workout facilities within a worksite was associated with higher BMI. The presence of a cafeteria and fewer vending machines was directly associated with better eating habits. Better eating habits and meeting physical activity recommendations were both related to lower BMI. CONCLUSIONS: Selected environmental factors in worksites were significantly associated with employee behaviors and weight status, providing additional intervention targets to change the worksite environment and promote employee weight loss.

Design and methods of "diaBEAT-it!": a hybrid preference/randomized control trial design using the RE-AIM framework.

BACKGROUND: Diabetes prevention is a public health priority that is dependent upon the reach, effectiveness, and cost of intervention strategies. However, understanding each of these outcomes within the context of randomized controlled trials is problematic. PURPOSE: To describe the methods and design of a hybrid preference/randomized control trial using the RE-AIM framework. METHODS: The trial, which was developed using the RE-AIM framework, will contrast the effects of 3 interventions: (1) a standard care, small group, diabetes prevention education class (SG), (2) the small group intervention plus 12 months of interactive voice response telephone follow-up (SG-IVR), and (3) a DVD version of the small group intervention with the same IVR follow-up (DVD-IVR). Each intervention includes personal action planning with a focus on key elements of the lifestyle intervention from the Diabetes Prevention Program (DPP). Adult patients at risk for diabetes will be randomly assigned to either choice or RCT. Those assigned to choice (n=240) will have the opportunity to choose between SG-IVR and DVD-IVR. Those assigned to RCT group (n=360) will be randomly assigned to SG, SG-IVR, or DVD-IRV. Assessment of primary (weight loss, reach, & cost) and secondary (physical activity, & dietary intake) outcomes will occur at baseline, 6, 12, and 18 months. CONCLUSION: This will be the first diabetes prevention trial that will allow the research team to determine the relationships between reach, effectiveness, and cost of different interventions.

Beginning a patient-centered approach in the design of a diabetes prevention program.

OBJECTIVE: The purpose of this study was to identify patient preferences for different components of a local diabetes prevention program that would improve reach. A secondary purpose was to determine if patient characteristics were related to program preferences. METHODS: Participants were identified through electronic medical records from two family medicine clinics in Virginia. Participants completed a mailed survey addressing demographics, economic status, risk factors for diabetes, and preferences regarding diabetes prevention interventions-delivery mode, program length, and duration. RESULTS: Twenty-nine percent of eligible participants responded (n = 142); 83% of participants were at risk for diabetes and 82% had a household income <$20,000. When presented with the choice between a class-based vs. a technology-based program, 83% preferred a technology-based program. Whites were less likely to choose the technology-based program, with no significant differences based on age, education, income, or gender. CONCLUSIONS: Contrary to beliefs that lower income individuals may not use technology-based interventions, lower socioeconomic patients indicated a preference for a technology- and telephone-supported diabetes prevention program over in-person class approaches. Findings provide formative data to support the design of a patient-centered, technology-enhanced diabetes prevention program in a real-world setting, thereby increasing potential participation and reach.