scholarly journals Adiposity, related biomarkers, and type 2 diabetes after gestational diabetes: The Diabetes Prevention Program

Obesity ◽  
2021 ◽  
Author(s):  
Pandora L. Wander ◽  
Costas A. Christophi ◽  
Maria Rosario G. Araneta ◽  
Edward J. Boyko ◽  
Daniel A. Enquobahrie ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Gestational Diabetes ◽  
Prevention Program ◽  
Diabetes Prevention ◽  
Diabetes Prevention Program

Weight and Physical Activity: a 12-month follow-up of a digital diabetes prevention program (VP Transform for Prediabetes) in adults with prediabetes (Preprint)

2020 ◽  
Author(s):  
Ryan Batten ◽  
Meshari F Alwashmi ◽  
Gerald Mugford ◽  
Misa Muccio ◽  
Angele Besner ◽  
...  
Keyword(s):  
Physical Activity ◽  
Type 2 Diabetes ◽  
Prevention Program ◽  
Diabetes Prevention ◽  
Secondary Analysis ◽  
Diabetes Prevention Program ◽  
Global Scale ◽  
Lifestyle Modifications ◽  
Behavior Tracking

BACKGROUND The prevalence of diabetes increasingly rapidly. Previous research has demonstrated the efficacy of a diabetes prevention program (DPP) in lifestyle modifications which can prevent or delay the onset of type 2 diabetes among individuals at-risk. Digital DPPs have the potential to utilize technology, in conjunction with behavior change science, to prevent prediabetes on a national and global scale OBJECTIVE The aim of this study was to investigate the effects of a digital DPP (VP Transform for Prediabetes) on weight loss and physical activity among participants who had completed twelve months of the program. METHODS This study was a secondary analysis of retrospective data of adults with prediabetes who were enrolled in VP Transform for Prediabetes for 12 months of the program. The program incorporates interactive mobile computing, remote monitoring, an evidence-based curriculum, behavior tracking tools, health coaching and online peer support to prevent or delay the onset of type 2 diabetes. Analysis included data that were collected at baseline and after 12 months of the VP Transform for Prediabetes DPP. RESULTS The sample (N=1,095) comprised people with prediabetes who completed 12 months of the VP Transform for Prediabetes program. Participants included 67.7% female, with a mean age of 53.6 (SD 9.75). On average, participants decreased their weight by 10.9 pounds (5.5%) and increased their physical activity by 91.2 minutes per week. CONCLUSIONS These results suggest that VP Transform for Prediabetes is effective at preventing type 2 diabetes through significant reduction in body weight and increase of physical activity. Furthermore, these results suggest that the DPP remains effective 12 months after beginning the program. A prospective, controlled clinical study is warranted to validate these findings.

Mobile Virtual reality vs. Mobile 360 Video to Promote Enrollment in the Diabetes Prevention Program Amongst Hispanic Adults (Preprint)

2020 ◽  
Author(s):  
Bryan Gibson ◽  
Sara Simonsen ◽  
Jakob Jensen ◽  
Leah Yingling ◽  
Julia Schaeffer ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Virtual Reality ◽  
Health Literacy ◽  
Mobile Phone ◽  
Prevention Program ◽  
Diabetes Prevention ◽  
Risk Perceptions ◽  
Diabetes Prevention Program ◽  
Pilot Test

BACKGROUND The Diabetes Prevention Program (DPP) reduces the risk of developing Type 2 Diabetes, however enrollment is very low. OBJECTIVE The goal of this project was to pilot test the efficacy of two brief, immersive mobile phone videos (presented either in virtual reality or 360 video) on risk perceptions and enrollment in the DPP. METHODS Adults with prediabetes were recruited at a clinic serving a low income Hispanic community. After consenting, participants completed a baseline survey that collected demographics and risk perceptions based on the tripartite model of risk perceptions.. They were then informed that they had prediabetes and provided with a link to an educational website that explains: what prediabetes and Type 2 Diabetes (T2DM) are, how lifestyle affects risk of T2DM, what the DPP is, and where to enroll. Participants then viewed two videos using their smartphone ; either with a cardboard VR headset (VR) or their smartphone alone (360 video), per random assignment. Two weeks later a follow-up survey collected measures of: enrollment in the DPP, risk perceptions, health literacy, the importance of contextual factors related to the DPP in their decision of whether or not to enroll in the DPP (e.g. distance to the class ), and qualitative feedback on the interventions. We used logistic regression to determine whether enrollment in the DPP differed by intervention mode, while accounting for heath literacy and contextual factors related to the DPP. We used unpaired t-tests to examine differences in change in risk perceptions between groups. We used paired t-tests to examine within-subject changes in risk perceptions. RESULTS 116 participants provided complete data. Most participants were middle-aged (mean age= 44.6 yrs.; SD= 11.9) Hispanic (114/116), female (79/116), with low health literacy (mean score =12.3/20; SD=3.4). Enrollment in the DPP was 44/116 overall (37.9% ) but did not differ by group ( OR for enrolling in VR group= 1.78 ; 95% CI: 0.75-4.3, p=0.19) . Individuals who rated t the distance needed to travel to attend the DPP as more important were less likely to enroll in the DPP (OR = 0.56, 95% CI:0.33-0.92; p=0.03) Risk perceptions did not differ by group ( mean change in 360 video group = -0.07, mean change in VR group = 0.03, t==0.6, p= 0.54) and did not change within subjects ( mean 0.02, t=0.21, p=0.83). Participants feedback suggested that the videos are emotionally engaging and educational. CONCLUSIONS We present a pilot test of immersive mobile phone videos which appear to be efficacious in promoting enrollment in the DPP. Further work to determine the replicability of these findings, the mechanism of action of the videos, and potential moderators of the efficacy of these videos is discussed.

scholarly journals Recruitment, retention, and training of people with type 2 diabetes as diabetes prevention mentors (DPM) to support a healthcare professional-delivered diabetes prevention program: the Norfolk Diabetes Prevention Study (NDPS)

2019 ◽  
Vol 7 (1) ◽  
pp. e000619
Author(s):  
Nikki J Garner ◽  
Melanie Pascale ◽  
Kalman France ◽  
Clare Ferns ◽  
Allan Clark ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Prevention Program ◽  
Diabetes Prevention ◽  
Healthcare Professionals ◽  
Diabetes Management ◽  
Low Cost ◽  
Diabetes Prevention Program ◽  
Lifestyle Interventions ◽  
Effective Prevention

ObjectiveIntensive lifestyle interventions reduce the risk of type 2 diabetes in populations at highest risk, but staffing levels are usually unable to meet the challenge of delivering effective prevention strategies to a very large at-risk population. Training volunteers with existing type 2 diabetes to support healthcare professionals deliver lifestyle interventions is an attractive option.MethodsWe identified 141 973 people at highest risk of diabetes in the East of England, screened 12 778, and randomized 1764 into a suite of type 2 diabetes prevention and screen detected type 2 diabetes management trials. A key element of the program tested the value of volunteers with type 2 diabetes, trained to act as diabetes prevention mentors (DPM) when added to an intervention arm delivered by healthcare professionals trained to support participant lifestyle change.ResultsWe invited 9951 people with type 2 diabetes to become DPM and 427 responded (4.3%). Of these, 356 (83.3%) were interviewed by phone, and of these 131 (36.8%) were interviewed in person. We then appointed 104 of these 131 interviewed applicants (79%) to the role (mean age 62 years, 55% (n=57) male). All DPMs volunteered for a total of 2895 months, and made 6879 telephone calls to 461 randomized participants. Seventy-six (73%) DPMs volunteered for at least 6 months and 66 (73%) for at least 1 year.DiscussionIndividuals with type 2 diabetes can be recruited, trained and retained as DPM in large numbers to support a group-based diabetes prevention program delivered by healthcare professionals. This volunteer model is low cost, and accesses the large type 2 diabetes population that shares a lifestyle experience with the target population. This is an attractive model for supporting diabetes prevention efforts.

scholarly journals Updated Genetic Score Based on 34 Confirmed Type 2 Diabetes Loci Is Associated With Diabetes Incidence and Regression to Normoglycemia in the Diabetes Prevention Program

Diabetes ◽  
2011 ◽  
Vol 60 (4) ◽  
pp. 1340-1348 ◽  
Author(s):  
M.-F. Hivert ◽  
K. A. Jablonski ◽  
L. Perreault ◽  
R. Saxena ◽  
J. B. McAteer ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Prevention Program ◽  
Diabetes Prevention ◽  
Diabetes Prevention Program ◽  
Diabetes Incidence ◽  
Genetic Score

scholarly journals Lifestyle Intervention for Prevention of Type 2 Diabetes in Primary Health Care: One-year follow-up of the Finnish National Diabetes Prevention Program (FIN-D2D)

Diabetes Care ◽  
2010 ◽  
Vol 33 (10) ◽  
pp. 2146-2151 ◽  
Author(s):  
T. Saaristo ◽  
L. Moilanen ◽  
E. Korpi-Hyovalti ◽  
M. Vanhala ◽  
J. Saltevo ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Health Care ◽  
Primary Health Care ◽  
Prevention Program ◽  
Diabetes Prevention ◽  
Diabetes Prevention Program ◽  
Primary Health ◽  
One Year

OP3 BIDIRECTIONAL ASSOCIATIONS BETWEEN DEPRESSION AND TYPE 2 DIABETES IN ADULTS: RESULT FROM QINGDAO DIABETES PREVENTION PROGRAM

2014 ◽  
Vol 106 ◽  
pp. S2
Author(s):  
F. Ning ◽  
Y.M. Wang ◽  
S.J. Wang ◽  
H.R. Nan ◽  
J.P. Sun ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Prevention Program ◽  
Diabetes Prevention ◽  
Diabetes Prevention Program ◽  
Bidirectional Associations

scholarly journals Extension of Type 2 Diabetes Genome-Wide Association Scan Results in the Diabetes Prevention Program

Diabetes ◽  
2008 ◽  
Vol 57 (9) ◽  
pp. 2503-2510 ◽  
Author(s):  
A. F. Moore ◽  
K. A. Jablonski ◽  
J. B. McAteer ◽  
R. Saxena ◽  
T. I. Pollin ◽  
...  
Keyword(s):  
Type 2 Diabetes ◽  
Prevention Program ◽  
Diabetes Prevention ◽  
Diabetes Prevention Program ◽  
Genome Wide Association ◽  
Genome Wide
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