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      A systematic review of real-world diabetes prevention programs: learnings from the last 15 years

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          Abstract

          Background

          The evidence base for the prevention of type 2 diabetes mellitus (T2DM) has progressed rapidly from efficacy trials to real-world translational studies and practical implementation trials over the last 15 years. However, evidence for the effective implementation and translation of diabetes programs and their population impact needs to be established in ways that are different from measuring program effectiveness. We report the findings of a systematic review that focuses on identifying the critical success factors for implementing diabetes prevention programs in real-world settings.

          Methods

          A systematic review of programs aimed at diabetes prevention was undertaken in order to evaluate their outcomes using the penetration, implementation, participation, and effectiveness (PIPE) impact metric. A search for relevant articles was carried out using PubMed (March 2015) and Web of Science, MEDLINE, CENTRAL, and EMBASE. A quality coding system was developed and included studies were rated independently by three researchers.

          Results

          Thirty eight studies were included in the review. Almost all (92 %) provided details on participation; however, only 18 % reported the coverage of their target population ( penetration). Program intensity or implementation—as measured by frequency of contacts during first year and intervention duration—was identified in all of the reported studies, and 84 % of the studies also reported implementation fidelity; however, only 18 % of studies employed quality assurance measures to assess the extent to which the program was delivered as planned. Sixteen and 26 % of studies reported ‘highly’ or ‘moderately’ positive changes ( effectiveness) respectively, based on weight loss. Six (16 %) studies reported ‘high’ diabetes risk reduction but ‘low’ to ‘moderate’ weight loss only.

          Conclusion

          Our findings identify that program intensity plays a major role in weight loss outcomes. However, programs that have high uptake—both in terms of good coverage of invitees and their willingness to accept the invitation—can still have considerable impact in lowering diabetes risk in a population, even with a low intensity intervention that only leads to low or moderate weight loss. From a public health perspective, this is an important finding, especially for resource constrained settings. More use of the PIPE framework components will facilitate increased uptake of T2DM prevention programs around the world.

          Electronic supplementary material

          The online version of this article (doi:10.1186/s13012-015-0354-6) contains supplementary material, which is available to authorized users.

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          Most cited references52

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          Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance. The Da Qing IGT and Diabetes Study.

          Individuals with impaired glucose tolerance (IGT) have a high risk of developing NIDDM. The purpose of this study was to determine whether diet and exercise interventions in those with IGT may delay the development of NIDDM, i.e., reduce the incidence of NIDDM, and thereby reduce the overall incidence of diabetic complications, such as cardiovascular, renal, and retinal disease, and the excess mortality attributable to these complications. In 1986, 110,660 men and women from 33 health care clinics in the city of Da Qing, China, were screened for IGT and NIDDM. Of these individuals, 577 were classified (using World Health Organization criteria) as having IGT. Subjects were randomized by clinic into a clinical trial, either to a control group or to one of three active treatment groups: diet only, exercise only, or diet plus exercise. Follow-up evaluation examinations were conducted at 2-year intervals over a 6-year period to identify subjects who developed NIDDM. Cox's proportional hazard analysis was used to determine if the incidence of NIDDM varied by treatment assignment. The cumulative incidence of diabetes at 6 years was 67.7% (95% CI, 59.8-75.2) in the control group compared with 43.8% (95% CI, 35.5-52.3) in the diet group, 41.1% (95% CI, 33.4-49.4) in the exercise group, and 46.0% (95% CI, 37.3-54.7) in the diet-plus-exercise group (P or = 25 kg/m2). In a proportional hazards analysis adjusted for differences in baseline BMI and fasting glucose, the diet, exercise, and diet-plus-exercise interventions were associated with 31% (P < 0.03), 46% (P < 0.0005), and 42% (P < 0.005) reductions in risk of developing diabetes, respectively. Diet and/or exercise interventions led to a significant decrease in the incidence of diabetes over a 6-year period among those with IGT.
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            Prevention of type 2 diabetes by lifestyle intervention: a Japanese trial in IGT males.

            Prevention of type 2 diabetes by intensive lifestyle intervention designed to achieve and maintain ideal body weight was assessed in subjects with impaired glucose tolerance (IGT). Male subjects with IGT recruited from health-screening examinees were randomly assigned in a 4:1 ratio to a standard intervention group (control group) and intensive intervention group (intervention group). The final numbers of subjects were 356 and 102, respectively. The subjects in the control group and in the intervention group were advised to maintain body mass index (BMI) of <24.0 kg/m2 and of <22.0 kg/m2, respectively, by diet and exercise. In the intervention group, detailed instructions on lifestyle were repeated every 3-4 months during hospital visits. Diabetes was judged to have developed when two or more consecutive fasting plasma glucose (FPG) values exceeded 140 mg/dl. A 100g oral glucose tolerance test was performed every 6 months to detect improvement of glucose tolerance. The subjects were seen in an ordinary outpatient clinic. The cumulative 4-year incidence of diabetes was 9.3% in the control group, versus 3.0% in the intervention group, and the reduction in risk of diabetes was 67.4% (P < 0.001). Body weight decreased by 0.39 kg in the control group and by 2.18 kg in the intervention group (P < 0.001). The control group was subclassified according to increase and decrease in body weight. The incidence of diabetes was positively correlated with the changes in body weight, and the improvement in glucose tolerance was negatively correlated. Subjects with higher FPG at baseline developed diabetes at a higher rate than those with lower FPG. Higher 2h plasma glucose values and higher BMI values at baseline were also associated with a higher incidence of diabetes, but the differences were not significant. Subjects with a low insulinogenic index (DeltaIRI/DeltaPG 30 min after an oral glucose load) developed diabetes at a significantly higher rate than those with a normal insulinogenic index. Comparison of the BMI data and incidence of diabetes in five diabetes prevention studies by lifestyle intervention revealed a linear correlation between the incidence of diabetes and the BMI values, with the exception of the DaQing Study. However, the slope of the reduction in incidence of diabetes in the intensive intervention groups was steeper than expected simply on the basis of the reduction of BMI, suggesting that the effect of lifestyle intervention cannot be solely ascribed to the body weight reduction. We conclude that lifestyle intervention aimed at achieving ideal body weight in men with IGT is effective and can be conducted in an outpatient clinic setting.
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              Translating the Diabetes Prevention Program lifestyle intervention for weight loss into primary care: a randomized trial.

              The Diabetes Prevention Program (DPP) lifestyle intervention reduced the incidence of type 2 diabetes mellitus (DM) among high-risk adults by 58%, with weight loss as the dominant predictor. However, it has not been adequately translated into primary care. We evaluated 2 adapted DPP lifestyle interventions among overweight or obese adults who were recruited from 1 primary care clinic and had pre-DM and/or metabolic syndrome. Participants were randomized to (1) a coach-led group intervention (n = 79), (2) a self-directed DVD intervention (n = 81), or (3) usual care (n = 81). During a 3-month intensive intervention phase, the DPP-based behavioral weight-loss curriculum was delivered by lifestyle coach-led small groups or home-based DVD. During the maintenance phase, participants in both interventions received lifestyle change coaching and support remotely-through secure email within an electronic health record system and the American Heart Association Heart360 website for weight and physical activity goal setting and self-monitoring. The primary outcome was change in body mass index (BMI) (calculated as weight in kilograms divided by height in meters squared) from baseline to 15 months. At baseline, participants had a mean (SD) age of 52.9 (10.6) years and a mean BMI of 32.0 (5.4); 47% were female; 78%, non-Hispanic white; and 17%, Asian/Pacific Islander. At month 15, the mean ± SE change in BMI from baseline was -2.2 ± 0.3 in the coach-led group vs -0.9 ± 0.3 in the usual care group (P < .001) and -1.6 ± 0.3 in the self-directed group vs usual care (P = .02). The percentages of participants who achieved the 7% DPP-based weight-loss goal were 37.0% (P = .003) and 35.9% (P = .004) in the coach-led and self-directed groups, respectively, vs 14.4% in the usual care group. Both interventions also achieved greater net improvements in waist circumference and fasting plasma glucose level. Proven effective in a primary care setting, the 2 DPP-based lifestyle interventions are readily scalable and exportable with potential for substantial clinical and public health impact. clinicaltrials.gov Identifier: NCT00842426.
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                Author and article information

                Contributors
                azizz@student.unimelb.edu.au
                pilvikki.absetz@gmail.com
                john.oldroyd@monash.edu
                Nico.P.Pronk@HealthPartners.com
                brian.oldenburg@unimelb.edu.au
                Journal
                Implement Sci
                Implement Sci
                Implementation Science : IS
                BioMed Central (London )
                1748-5908
                15 December 2015
                15 December 2015
                2015
                : 10
                : 172
                Affiliations
                [ ]Melbourne School of Population and Global Health, University of Melbourne, Melbourne, 3010 Australia
                [ ]School of Health Sciences, University of Tampere, Tampere, FI-33014 Finland
                [ ]Collaborative Care Systems Finland, Helsinki, Finland
                [ ]Department of Epidemiology and Preventive Medicine, Monash University, Melbourne, 3004 Australia
                [ ]HealthPartners Institute for Education and Research, 8170 33rd Ave. S, Minneapolis, MN 55425 USA
                Article
                354
                10.1186/s13012-015-0354-6
                4681022
                26670418
                3d3faa37-a632-4573-9580-7cba1c8ee3ab
                © Aziz et al. 2015

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 29 April 2015
                : 20 November 2015
                Categories
                Systematic Review
                Custom metadata
                © The Author(s) 2015

                Medicine
                implementation,translational research,diabetes prevention,penetration, implementation, participation, effectiveness (pipe) impact metric,systematic review,resource allocation

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