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      Global Diabetes Prevention Interventions: A Systematic Review and Network Meta-analysis of the Real-World Impact on Incidence, Weight, and Glucose

      , , , , ,
      Diabetes Care
      American Diabetes Association

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          Abstract

          <div class="section"> <a class="named-anchor" id="d9326568e192"> <!-- named anchor --> </a> <h5 class="section-title" id="d9326568e193">OBJECTIVE</h5> <p id="d9326568e195">Understanding the real-world impacts of lifestyle modification (LSM) for diabetes prevention is imperative to inform resource allocation. The purpose of this study was to synthetize global evidence on the impact of LSM strategies on diabetes incidence and risk factors in one parsimonious model. </p> </div><div class="section"> <a class="named-anchor" id="d9326568e197"> <!-- named anchor --> </a> <h5 class="section-title" id="d9326568e198">RESEARCH DESIGN AND METHODS</h5> <p id="d9326568e200">PubMed, Embase, Cochrane Library, and <a data-untrusted="" href="http://www.ClinicalTrials.gov" id="d9326568e202" target="xrefwindow">ClinicalTrials.gov</a> were searched for studies published between January 1990 and April 2015. Effectiveness/translation studies of any design testing LSM strategies, targeting high-risk populations (with prediabetes or diabetes risk factors), and reporting diabetes incidence, weight, or glucose outcomes were included. We extracted number of diabetes cases/incidence rates and mean changes in weight (kg), fasting blood glucose (FBG, mmol/L), 2-h postload glucose (mmol/L), and hemoglobin A <sub>1c</sub> (%). Pairwise random-effects and frequentist random-effects network meta-analyses were used to obtain pooled effects. </p> </div><div class="section"> <a class="named-anchor" id="d9326568e208"> <!-- named anchor --> </a> <h5 class="section-title" id="d9326568e209">RESULTS</h5> <p id="d9326568e211">Sixty-three studies were pooled in the meta-analysis ( <i>n</i> = 17,272, mean age 49.7 years, 28.8% male, 60.8% white/European). In analyses restricted to controlled studies ( <i>n</i> = 7), diabetes cumulative incidence was 9% among intervention participants and 12% among control participants (absolute risk reduction 3%; relative risk 0.71 [95% CI 0.58, 0.88]). In analyses combining controlled and uncontrolled studies ( <i>n</i> = 14), participants receiving group education by health care professionals had 33% lower diabetes odds than control participants (odds ratio 0.67 [0.49, 0.92]). Intervention participants lost 1.5 kg more weight [−2.2, −0.8] and achieved a 0.09 mmol/L greater FBG decrease [−0.15, −0.03] than control participants. Every additional kilogram lost by participants was associated with 43% lower diabetes odds (β = 0.57 [0.41, 0.78]). </p> </div><div class="section"> <a class="named-anchor" id="d9326568e222"> <!-- named anchor --> </a> <h5 class="section-title" id="d9326568e223">CONCLUSIONS</h5> <p id="d9326568e225">Real-world LSM strategies can reduce diabetes risk, even with small weight reductions.</p> </div>

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          How can we increase translation of research into practice? Types of evidence needed.

          This review summarizes key factors that have interfered with translation of research to practice and what public health researchers can do to hasten such transfer, focusing on characteristics of interventions, target settings, and research designs. The need to address context and to utilize research, review, and reporting practices that address external validity issues-such as designs that focus on replication, and practical clinical and behavioral trials-are emphasized. Although there has been increased emphasis on social-ecological interventions that go beyond the individual level, interventions often address each component as if it were an independent intervention. Greater attention is needed to connectedness across program levels and components. Finally, examples are provided of evaluation models and current programs that can help accelerate translation of research to practice and policy.
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            Evaluating the impact of health promotion programs: using the RE-AIM framework to form summary measures for decision making involving complex issues.

            Current public health and medical evidence rely heavily on efficacy information to make decisions regarding intervention impact. This evidence base could be enhanced by research studies that evaluate and report multiple indicators of internal and external validity such as Reach, Effectiveness, Adoption, Implementation and Maintenance (RE-AIM) as well as their combined impact. However, indices that summarize the combined impact of, and complex interactions among, intervention outcome dimensions are not currently available. We propose and discuss a series of composite metrics that combine two or more RE-AIM dimensions, and can be used to estimate overall intervention impact. Although speculative and, at this point, there have been limited empirical data on these metrics, they extend current methods and are offered to yield more integrated composite outcomes relevant to public health. Such approaches offer potential to help identify interventions most likely to meaningfully impact population health.
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              Pragmatic measures: what they are and why we need them.

              Pragmatic measures are important to facilitate implementation and dissemination, address stakeholder issues, and drive quality improvement. This paper proposes necessary and recommended criteria for pragmatic measures, provides examples of projects to develop and identify such measures, addresses potential concerns about these recommendations, and identifies areas for future research and application. Key criteria for pragmatic measures include importance to stakeholders in addition to researchers, low burden, broad applicability, sensitivity to change, and being actionable. Examples of pragmatic measures are provided, including ones for different settings (e.g., primary care, hospital) and levels (e.g., individual, practitioner, setting) that illustrate approaches to produce broad-scale dissemination and the development of brief, standardized measures for use in pragmatic studies. There is an important need for pragmatic measures to facilitate pragmatic research, guide quality improvement, and inform progress on public health goals, but few examples are currently available. Development and evaluation of pragmatic measures and metrics would provide useful resources to advance science, policy, and practice. Copyright © 2013. Published by Elsevier Inc. on behalf of American Journal of Medicine.
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                Author and article information

                Journal
                Diabetes Care
                Dia Care
                American Diabetes Association
                0149-5992
                1935-5548
                June 22 2018
                July 2018
                June 22 2018
                July 2018
                : 41
                : 7
                : 1526-1534
                Article
                10.2337/dc17-2222
                6463613
                29934481
                3ee7d8c7-5537-418e-a09f-f5c35f7a327c
                © 2018

                Free to read

                http://www.diabetesjournals.org/site/license

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