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Review| Volume 12, ISSUE 5, P393-408, October 2018

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Effects of lifestyle changes on adults with prediabetes: A systematic review and meta-analysis

Open AccessPublished:August 01, 2018DOI:https://doi.org/10.1016/j.pcd.2018.07.003
Effects of lifestyle changes on adults with prediabetes: A systematic review and meta-analysis
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      Highlights

      • •
        Lifestyle intervention lowers type 2 diabetes risk in people with prediabetes.
      • •
        Weight loss is commonly achieved but there is great variation between studies.
      • •
        The majority of studies concluded that lifestyle intervention is cost-effective.
      • •
        Lifestyle intervention is most cost-effective over a lifelong analysis period.
      • •
        More research is necessary to compare different types of lifestyle intervention.

      Abstract

      Aims

      To assess the efficacy, safety, and cost-effectiveness of lifestyle intervention, compared with treatment as usual in people with prediabetes as defined by the American Diabetes Association. For older studies, we used the 1985 World Health Organization definition.

      Methods

      We systematically searched multiple electronic databases and referenced lists of pertinent review articles from January 1980 through November 2015. We performed an update search in MEDLINE on April 26, 2017. Based on a priori established eligibility criteria, we dually reviewed the literature, extracted data, and rated the risk of bias of included studies with validated checklists. To assess the efficacy of lifestyle intervention to prevent or delay further progression to type 2 diabetes, we conducted a random-effects meta-analysis. We assessed the certainty of evidence using the GRADE (Grading of Recommendations Assessment, Development and Evaluation) approach.

      Result

      Pooled results of 16 randomized controlled trials showed that people with prediabetes who received lifestyle intervention had a lower rate of progression to type 2 diabetes after one (4% vs. 10%, RR 0.46 [CI 0.32, 0.66]) and three years of follow-up (14% vs. 23%, RR 0.64 [95% CI 0.53, 0.77]). The majority of the studies also showed a greater weight loss in lifestyle intervention participants, with a great variation between studies. Costs per quality-adjusted life-year were lower when the benefits of lifestyle intervention were analyzed over a lifelong time horizon compared to only the period of lifestyle intervention (three years) or to modeling over a ten-year period.

      Conclusion

      Lifestyle intervention is an efficacious, safe, and cost-effective measure to reduce the risk of progression to type 2 diabetes in people diagnosed with prediabetes. More research is necessary to compare the efficacy of various modes, frequencies, and intensities of lifestyle intervention across studies.

      Abbreviations:

      ADA (American Diabetes Association), CI (Confidence interval), Finnish DPS (Finnish Diabetes Prevention Study), HR (Hazard ratio), IDPP-1 (Indian Diabetes Prevention Programme), IFG (Impaired fasting glucose), IGT (Impaired glucose tolerance), QALY (Quality-adjusted life-year), RCT (Randomized controlled trial), RR (Relative risk), U.S. DPP (United States Diabetes Prevention Program), vs. (versus), WHO (World Health Organization)

      Keywords

      1. Introduction

      According to the latest estimates from the International Diabetes Federation (IDF) (2017), 352 million adults between the ages of 20 and 79 (7.3% of that population) could be classified as having prediabetes [
      • International Diabetes Federation
      IDF Diabetes Atlas.
      8th ed. International Diabetes Federation, Brussels, Belgium2017
      ]. To date no general agreement on laboratory thresholds for prediabetes exists. The American Diabetes Association (ADA) defines prediabetes as impaired fasting glucose (IFG) of 5.6–6.9 mmol/L and/or 2 h post-challenge glucose of 7.8–11.0 mmol/L with a 75 g oral glucose tolerance test (impaired glucose tolerance [IGT]) or based on a HbA1c value of 5.7–6.4% [
      • American Diabetes Association
      Diagnosis and classification of diabetes mellitus.
      Diabetes Care. 2013; 36: S67-S74
      ]. The World Health Organization (WHO) sets the threshold for prediabetes at an IFG of 6.1–6.9 mmol/L [

      World Health Organization. Definition and diagnosis of diabetes mellitus and intermediate hyperglycaemia; Report of a WHO/IDF consultation. 2006.

      ]. The ADA’s lower threshold for IFG is based on the rationale that an IFG near the level of 6.1 mmol/L is associated with a higher risk of micro- and macrovascular complications [
      Report of the expert committee on the diagnosis and classification of diabetes mellitus.
      Diabetes Care. 2003; 26: S5-S20
      ].
      Compared to the current WHO criteria, applying the ADA criteria leads to a two- to three-fold increase in the number of people diagnosed with prediabetes [
      • Yudkin J.S.
      • Montori V.M.
      The epidemic of pre-diabetes: the medicine and the politics.
      BMJ (Clin. Res. Ed.). 2014; 349 (g4485)
      ]. This may include many people at lower risk for developing diabetes and cardiovascular disease who might not benefit from any intervention. However, since individuals with prediabetes are at higher risk for developing type 2 diabetes, with about five to ten percent progressing to type 2 diabetes annually [
      • Tabák A.G.
      • Herder C.
      • Rathmann W.
      • Brunner E.J.
      • Kivimäki M.
      Prediabetes: a high-risk state for developing diabetes.
      Lancet. 2012; 379: 2279-2290
      ], early detection of prediabetes offers the possibility of intervention to prevent or delay further progression to type 2 diabetes.
      In this context, we are specifically interested in the role of lifestyle intervention in achieving long-term behavioral changes in people at high risk of developing type 2 diabetes. A recent overview of systematic reviews, mostly containing RCTs, showed that there is sufficient evidence that lifestyle intervention, which often includes regular dietary advice and physical activity instruction, can delay or prevent the onset of type 2 diabetes in people with prediabetes [
      • Howells L.
      • Musaddaq B.
      • McKay A.J.
      • Majeed A.
      Clinical impact of lifestyle interventions for the prevention of diabetes: an overview of systematic reviews.
      BMJ Open. 2016; 6e013806
      ]. Since healthcare systems spend about two-fold more for people with diabetes than for people without diabetes [
      • American Diabetes A
      Economic costs of diabetes in the U.S. in 2012.
      Diabetes Care. 2013; 36: 1033-1046
      ] and healthcare costs have increased by eight percent worldwide since 2015 [
      • International Diabetes Federation
      IDF Diabetes Atlas.
      8th ed. International Diabetes Federation, Brussels, Belgium2017
      ], this is an important consideration.
      The objective of our systematic review was to assess the efficacy and safety of lifestyle intervention, targeted at dietary and exercise behavioral changes, in preventing or delaying further progression to type 2 diabetes in people with prediabetes. Furthermore, we evaluated the impact of lifestyle intervention on weight loss, on the long-term complications of type 2 diabetes, and on mortality. We also analyzed the cost-effectiveness of lifestyle intervention in preventing type 2 diabetes and secondary diseases. We included studies of populations with prediabetes as defined by the ADA [
      • American Diabetes Association
      Diagnosis and classification of diabetes mellitus.
      Diabetes Care. 2013; 36: S67-S74
      ]. We also accepted older studies that defined prediabetes according to the WHO in 1985 [
      • World Health Organization
      Diabetes Mellitus—Report of a WHO Study Group.
      WHO, Geneva1985: 113
      ]. To our knowledge, this is the first systematic review to include all of the relevant studies based on these criteria.

      2. Methods

      We registered the protocol of this review in PROSPERO (International prospective register of systematic reviews; http://www.crd.york.ac.uk/prospero/) under the following registration number: PROSPERO 2016:CRD42016033239.

      2.1 Data sources

      We performed a literature search covering research published from January 1980 through November 2015 by DIMDI (German Institute of Medical Documentation and Information) in MEDLINE (Medical Literature Analysis and Retrieval System Online), the Cochrane Library, BIOSIS, CINAHL (Cumulative Index to Nursing and Allied Health Literature), Embase (Excerpta Medica dataBASE), DAHTA (German Agency for Health Technology Assessment), DARE (Database of Abstracts of Reviews of Effects), Health Business Elite, Health Technology Assessment Database, NHS (United Kingdom National Health Services) Economic Evaluation Database, SciSearch (Science Citation Index), and SocINDEX. Because all of the included studies from the initial search could be found through MEDLINE, we performed an updated MEDLINE search through April 26, 2017 [
      • Garner P.
      • Hopewell S.
      • Chandler J.
      • MacLehose H.
      • Schunemann H.J.
      • Akl E.A.
      • et al.
      When and how to update systematic reviews: consensus and checklist.
      BMJ (Clin. Res. Ed.). 2016; 354 (i3507)
      ]. We used Medical Subject Headings (MeSH) and keywords as search terms and combined specific terms for prevention and control of diabetes mellitus and lifestyle intervention. We limited electronic searches to “adult 19 years or older” and “human.” The online supplementary file presents our complete search strategy. To minimize retrieval bias; we complemented the literature search with a manual search of reference lists of pertinent articles.

      2.2 Study selection

      Two investigators independently reviewed abstracts and full-text articles. Eligibility criteria for studies were defined a priori and are presented in Supplemental Table 1. We included systematic reviews and meta-analyses, health technology assessments, randomized controlled trials (RCTs), prospective cohort studies, and cost-effectiveness studies that compared lifestyle intervention with treatment as usual. Our population of interest was comprised of people with prediabetes as defined by the ADA [
      • American Diabetes Association
      Diagnosis and classification of diabetes mellitus.
      Diabetes Care. 2013; 36: S67-S74
      ]. Because our literature searches went back until 1980, we also accepted older studies that defined prediabetes according to the WHO in 1985 [
      • World Health Organization
      Diabetes Mellitus—Report of a WHO Study Group.
      WHO, Geneva1985: 113
      ]. The ADA and WHO classifications used fasting plasma glucose levels of 7.8 mmol/L as the lower threshold for diabetes until 1997 and 1999, respectively. We excluded studies involving populations with obesity or metabolic syndrome with prediabetes and studies that analyzed only women with prior gestational diabetes.
      Outcomes of interest included the incidence of type 2 diabetes, weight loss, health-related quality of life, diabetes-associated co-morbidity and mortality, and adverse events of people who participated in lifestyle intervention compared to treatment as usual. In cost-effectiveness studies, we extracted data of the following outcomes: costs per life-year gained, costs per quality-adjusted life-year (QALY), costs per disability-adjusted life-year (DALY), and costs per avoided diabetes-associated outcome.

      2.3 Data extraction and quality assessment

      We used standardized data abstraction forms. Trained reviewers abstracted data from each study and assigned an initial rating of the risk of bias. A senior reviewer checked the data for correctness and independently evaluated risk of bias ratings. To assess the risk of bias in systematic reviews, we used the ROBIS (Risk Of Bias In Systematic Reviews) tool [
      • Whiting P.
      • Savović J.
      • Higgins J.P.T.
      • Caldwell D.M.
      • Reeves B.C.
      • Shea B.
      • et al.
      ROBIS: a new tool to assess risk of bias in systematic reviews was developed.
      J. Clin. Epidemiol. 2016; 69: 225-234
      ]. For RCTs, we used the Cochrane Risk of Bias Tool [
      • Higgins J.
      • Green Se
      Cochrane Handbook for Systematic Reviews of Interventions Version 5.1.0 [updated March 2011].
      The Cochrane Collaboration, 2011
      ]. For prospective cohort studies, we used the Newcastle–Ottawa Scale (NOS) [
      • Wells G.A.
      • Shea B.
      • O’Connell D.
      • Peterson J.
      • Welch V.
      • Losos M.
      • et al.
      The Newcastle-Ottawa Scale (NOS) for Assessing the Quality of Nonrandomised Studies in Meta-analyses.
      Ottawa Hospital Research Institute, 2018
      http://www.ohri.ca/programs/clinical_epidemiology/oxford.asp
      ]. The overall risk of bias in studies was classified as low, unclear, or high. Cost-effectiveness studies were evaluated by the Drummond checklist [
      • Drummond M.F.
      • Jefferson T.O.
      Guidelines for authors and peer reviewers of economic submissions to the BMJ: The BMJ Economic Evaluation Working Party.
      BMJ (Clin. Res. Ed.). 1996; 313: 275-283
      ]. Two reviewers assessed the risk of bias independently with a third reviewer being consulted when there were disagreements.

      2.4 Data synthesis and analyses

      We summarized the evidence primarily in a narrative format because most of the data was insufficient for meta-analyses. When multiple studies of varying methodological quality analyzed the same outcome, we present the best available study in more detail.
      We conducted meta-analyses when three or more studies provided data for quantitative analysis and were similar with respect to populations and interventions. We calculated either the relative risk (RR) of reducing diabetes incidence or the weighted mean difference of changes on body weight. For each meta-analysis, we conducted a test of heterogeneity (I2 statistic, Cochran’s q-test) and applied the DerSimonian and Laird method for random-effects models. We performed sensitivity analyses excluding high risk of bias studies. If high heterogeneity was present (I2 statistic > 60%), we explored the reasons for heterogeneity using meta-regressions. We assessed publication bias using funnel plots, Egger’s regression intercept, and Kendall’s S statistic. All statistical analyses were conducted using Comprehensive Meta-Analysis (CMA), version 2.2.050 (www.meta-analysis.com).

      2.5 Grading the quality of evidence

      Two persons evaluated the quality of the body of evidence for each outcome of interest using an approach proposed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) working group [
      • Balshem H.
      • Helfand M.
      • Schunemann H.J.
      • Oxman A.D.
      • Kunz R.
      • Brozek J.
      • et al.
      GRADE guidelines: 3. Rating the quality of evidence.
      J. Clin. Epidemiol. 2011; 64: 401-406
      ]. The quality of evidence for each outcome that we graded incorporated scores on five domains: risk of bias, inconsistency, indirectness, imprecision, and reporting bias. We used four grades to designate strength of evidence: high, moderate, low, and very low. Grades reflect the quality of the body of evidence regarding differences in efficacy and risk of lifestyle intervention compared to treatment as usual. We reconciled all disagreements in grades through consensus discussion.

      3. Results

      Our literature searches identified 11,425 relevant abstracts. We retrieved 419 full-text articles for detailed examination. A total of 58 of these articles, one systematic review (1 article), 22 RCTs (38 articles), three prospective studies (5 articles), and 13 cost-effectiveness studies (14 articles) were relevant for our systematic review. Supplemental Figs. 1 and 2 depict the results of our searches and the study selection process. The identified systematic review, published in 2015, included eight RCTs that were relevant for our research questions and other RCTs that only used pharmacological intervention to prevent or delay type 2 diabetes [
      • Glechner A.
      • Harreiter J.
      • Gartlehner G.
      • Rohleder S.
      • Kautzky A.
      • Tuomilehto J.
      • et al.
      Sex-specific differences in diabetes prevention: a systematic review and meta-analysis.
      Diabetologia. 2015; 58: 242-254
      ]. Results of this review were restricted to studies with sex-specific differences.
      In addition to the eight RCTs included in the systematic review, we found 14 RCTs in our literature search that met our inclusion criteria. Altogether, 22 RCTs (38 articles) involving 9796 people with prediabetes compared lifestyle intervention with treatment as usual [
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      Effect of a lifestyle intervention on weight change in south Asian individuals in the UK at high risk of type 2 diabetes: a family-cluster randomised controlled trial.
      Lancet Diabetes Endocrinol. 2014; 2: 218-227
      ,
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      Long-term nutrition education reduces several risk factors for type 2 diabetes mellitus in Brazilians with impaired glucose tolerance.
      Nutr. Res. (New York, NY). 2010; 30: 186-190
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      • Davies M.J.
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      A community based primary prevention programme for type 2 diabetes integrating identification and lifestyle intervention for prevention: the Let’s Prevent Diabetes cluster randomised controlled trial.
      Prev. Med. 2016; 84: 48-56
      ,

      M.J. Davies, L.J. Gray, D. Ahrabian, M. Carey, A. Farooqi, A. Gray, et al, A community-based primary prevention programme for type 2 diabetes mellitus integrating identification and lifestyle intervention for prevention: a cluster randomized controlled trial. 2017.

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      ]. Follow-up lasted from 1 to 6 years. One RCT originally compared lifestyle intervention with metformin or placebo [
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      Obesity (Silver Spring, Md.). 2009; 17: 2176-2181
      ,
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      • et al.
      The diabetes prevention program: Baseline characteristics of the randomized cohort.
      Diabetes Care. 2000; 23: 1619-1629
      ,
      • Florez H.
      • Pan Q.
      • Ackermann R.T.
      • Marrero D.G.
      • Barrett-Connor E.
      • Delahanty L.
      • et al.
      Impact of lifestyle intervention and metformin on health-related quality of life: the diabetes prevention program randomized trial.
      J. Gen. Intern. Med. 2012; 27: 1594-1601
      ,
      • Fujimoto W.Y.
      • Jablonski K.A.
      • Bray G.A.
      • Kriska A.
      • Barrett-Connor E.
      • Haffner S.
      • et al.
      Body size and shape changes and the risk of diabetes in the diabetes prevention program.
      Diabetes. 2007; 56: 1680-1685
      ,
      • Molitch M.E.
      • Fujimoto W.
      • Hamman R.F.
      • Knowler W.C.
      • Diabetes Prevention Program Research Group, N P
      The diabetes prevention program and its global implications.
      J. Am. Soc. Nephrol. 2003; 14: 103-107
      ,
      • Ratner R.E.
      • Diabetes Prevention Program Research
      An update on the Diabetes Prevention Program.
      Endocr. Pract. 2006; 12: 20-24
      ,
      • Diabetes Prevention Program Research Group
      Reduction of the incidence of type 2 diabetes with lifestyle intervention or metformin.
      Int. Urol. Nephrol. 2002; 34: 162-163
      ,
      • Diabetes Prevention Program Research Group
      • Schade D.
      • Ma Y.
      • Fujimoto W.Y.
      • Barrett-Connor E.
      • Fowler S.
      • et al.
      The influence of age on the effects of lifestyle modification and metformin in prevention of diabetes.
      J. Gerontol. Ser. A: Biol. Sci. Med. Sci. 2006; 61: 1075-1081
      ]. The placebo group received general advice for lifestyle changes or observation only and was therefore categorized as treatment as usual. Supplemental Table 2 summarizes population and study characteristics of the included RCTs. Three of these RCTs continued to observe participants after the lifestyle intervention ended. These three prospective studies (5 articles) analyzed the effect of lifestyle intervention on diabetes-associated long-term complications [
      • Uusitupa M.
      • Peltonen M.
      • Lindstroem J.
      • Aunola S.
      • Ilanne-Parikka P.
      • Keinaenen-Kiukaanniemi S.
      • et al.
      Ten-year mortality and cardiovascular morbidity in the Finnish Diabetes Prevention Study—secondary analysis of the randomized trial.
      PLoS One. 2009; 4: 5656
      ,
      • Nathan D.M.
      • Barrett-Connor E.
      • Crandall J.P.
      • Edelstein S.L.
      • Goldberg R.B.
      • Horton E.S.
      • et al.
      Long-term effects of lifestyle intervention or metformin on diabetes development and microvascular complications over 15-year follow-up: The Diabetes Prevention Program Outcomes Study.
      Lancet Diabetes Endocrinol. 2015; 3: 866-875
      ,
      • Gong Q.
      • Gregg E.W.
      • Wang J.
      • An Y.
      • Zhang P.
      • Yang W.
      • et al.
      Long-term effects of a randomised trial of a 6-year lifestyle intervention in impaired glucose tolerance on diabetes-related microvascular complications: the China Da Qing Diabetes Prevention Outcome Study.
      Diabetologia. 2011; 54: 300-307
      ,
      • Li G.
      • Zhang P.
      • Wang J.
      • Gregg E.W.
      • Yang W.
      • Gong Q.
      • et al.
      The long-term effect of lifestyle interventions to prevent diabetes in the China Da Qing Diabetes Prevention Study: a 20-year follow-up study.
      Lancet North Am. Ed. 2008; 371: 1783-1789
      ,
      • Li G.
      • Zhang P.
      • Wang J.
      • An Y.
      • Gong Q.
      • Gregg E.W.
      • et al.
      Cardiovascular mortality, all-cause mortality, and diabetes incidence after lifestyle intervention for people with impaired glucose tolerance in the Da Qing Diabetes Prevention Study: a 23-year follow-up study.
      Lancet Diabetes Endocrinol. 2014; 2: 474-480
      ]. We also included thirteen cost-effectiveness studies (14 articles) that evaluated the cost and benefit of lifestyle intervention compared to treatment as usual [
      • Palmer A.J.
      • Tucker D.M.
      Cost and clinical implications of diabetes prevention in an Australian setting: a long-term modeling analysis.
      Prim. Care Diabetes. 2012; 6: 109-121
      ,
      • Ackermann R.T.
      • Marrero D.G.
      • Hicks K.A.
      • Hoerger T.J.
      • Sorensen S.
      • Zhang P.
      • et al.
      An evaluation of cost sharing to finance a diet and physical activity intervention to prevent diabetes.
      Diabetes Care. 2006; 29: 1237-1241
      ,
      • Caro J.J.
      • Getsios D.
      • Caro I.
      • Klittich W.S.
      • O’Brien J.A.
      • Dissemination CfRa
      Economic evaluation of therapeutic interventions to prevent Type 2 diabetes in Canada.
      Diabetic Med.: J. Br. Diabetic Assoc. 2004; 21: 1229-1236
      ,
      • The Diabetes Prevention Program Research Group
      Within-trial cost-effectiveness of lifestyle intervention or metformin for the primary prevention of type 2 diabetes.
      Diabetes Care. 2003; 26: 2518-2523
      ,
      • Hernan W.H.
      • Brandle M.
      • Zhang P.
      • Williamson D.F.
      • Matulik M.J.
      • Ratner R.E.
      • et al.
      Costs associated with the primary prevention of type 2 diabetes mellitus in the diabetes prevention program.
      Diabetes Care. 2003; 26: 36-47
      ,
      • The Diabetes Prevention Program Research Group
      The 10-year cost-effectiveness of lifestyle intervention or metformin for diabetes prevention: an intent-to-treat analysis of the DPP/DPPOS.
      Diabetes Care. 2012; 35: 723-730
      ,
      • Eddy D.M.
      • Schlessinger L.
      • Kahn R.
      Clinical outcomes and cost-effectiveness of strategies for managing people at high risk for diabetes.
      Ann. Intern. Med. 2005; 143: 251-264
      ,
      • Herman W.H.
      • Hoerger T.J.
      • Brandle M.
      • et al.
      The cost-effectiveness of lifestyle modification or metformin in preventing Type 2 diabetes in adults with impaired glucose tolerance.
      Ann. Intern. Med. 2005; 142: 323-332
      ,
      • Herman W.H.
      • Edelstein S.L.
      • Ratner R.E.
      • Montez M.G.
      • Ackermann R.T.
      • Orchard T.J.
      • et al.
      Effectiveness and cost-effectiveness of diabetes prevention among adherent participants.
      Am. J. Manag. Care. 2013; 19: 194-202
      ,
      • Icks A.
      • Rathmann W.
      • Haastert B.
      • Gandjour A.
      • Holle R.
      • John J.
      • et al.
      Clinical and cost-effectiveness of primary prevention of Type 2 diabetes in a ‘real world’ routine healthcare setting: model based on the KORA Survey 2000.
      Diabetic Med.: J. Br. Diabetic Assoc. 2007; 24: 473-480
      ,
      • Lindgren P.
      • Lindstrom J.
      • Tuomilehto J.
      • Uusitupa M.
      • Peltonen M.
      • Jonsson B.
      • et al.
      Lifestyle intervention to prevent diabetes in men and women with impaired glucose tolerance is cost-effective (structured abstract).
      Health Technol. Assess. 2007; 23: 177-183
      ,
      • Ramachandran A.
      • Snehalatha C.
      • Yamuna A.
      • Mary S.
      • Ping Z.
      • et al.
      Cost-effectiveness of the interventions in the primary prevention of diabetes among Asian Indians: within-trial results of the Indian Diabetes Prevention Programme (IDPP).
      Diabetes Care. 2007; 30: 2548-2552
      ,
      • Leal J.
      • Ahrabian D.
      • Davies M.J.
      • Gray L.J.
      • Khunti K.
      • Yates T.
      • et al.
      Cost-effectiveness of a pragmatic structured education intervention for the prevention of type 2 diabetes: economic evaluation of data from the Let’s Prevent Diabetes cluster-randomised controlled trial.
      BMJ Open. 2017; 7e013592
      ,
      • Wong C.K.H.
      • Jiao F.-F.
      • Siu S.-C.
      • Fung C.S.C.
      • Fong D.Y.T.
      • Wong K.-W.
      • et al.
      Cost-effectiveness of a short message service intervention to prevent type 2 diabetes from impaired glucose tolerance.
      J. Diabetes Res. 2016; 2016 (1219581)
      ].

      3.1 Efficacy and safety of lifestyle intervention

      3.1.1 Diabetes incidence

      We performed a meta-analysis of 10 RCTs that included data on 1880 people with prediabetes to assess how effective lifestyle intervention is in delaying or preventing progression to type 2 diabetes within 1 year [
      • Pimentel G.D.
      • Portero-McLellan K.C.
      • Oliveira E.P.
      • Spada A.P.
      • Oshiiwa M.
      • Zemdegs J.C.
      • et al.
      Long-term nutrition education reduces several risk factors for type 2 diabetes mellitus in Brazilians with impaired glucose tolerance.
      Nutr. Res. (New York, NY). 2010; 30: 186-190
      ,
      • Penn L.
      • White M.
      • Oldroyd J.
      • Walker M.
      • Alberti K.G.
      • Mathers J.C.
      Prevention of type 2 diabetes in adults with impaired glucose tolerance: the European Diabetes Prevention RCT in Newcastle upon Tyne, UK.
      BMC Public Health. 2009; 9: 342
      ,
      • Eriksson J.
      • Lindstroem J.
      • Valle T.
      • Aunola S.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type II diabetes in subjects with impaired glucose tolerance: the Diabetes Prevention Study (DPS) in Finland. Study design and 1-year interim report on the feasibility of the lifestyle intervention programme.
      Diabetologia. 1999; 42: 793-801
      ,
      • Ilanne-Parikka P.
      • Eriksson J.G.
      • Lindstroem J.
      • Peltonen M.
      • Aunola S.
      • Haemaelaeinen H.
      • et al.
      Effect of lifestyle intervention on the occurrence of metabolic syndrome and its components in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 805-807
      ,
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Aunola S.
      • Cepaitis Z.
      • Hakumaeki M.
      • et al.
      Prevention of diabetes mellitus in subjects with impaired glucose tolerance in the Finnish Diabetes Prevention Study: results from a randomized clinical trial.
      J. Am. Soc. Nephrol. 2003; 14: 108-113
      ,
      • Lindstroem J.
      • Louheranta A.
      • Mannelin M.
      • Rastas M.
      • Salminen V.
      • Eriksson J.
      • et al.
      The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity.
      Diabetes Care. 2003; 26: 3230-3236
      ,
      • Tuomilehto J.
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance.
      N. Engl. J. Med. 2001; 344: 1343-1350
      ,
      • Uusitupa M.
      • Louheranta A.
      • Lindstroem J.
      • Valle T.
      • Sundvall J.
      • Eriksson J.
      • et al.
      The Finnish diabetes prevention study.
      Br. J. Nutr. 2000; 83: 137-142
      ,
      • Lindström J.
      • Peltonen M.
      • Eriksson J.G.
      • Aunola S.
      • Hmlinen H.
      • Ilanne-Parikka P.
      • et al.
      Determinants for the effectiveness of lifestyle intervention in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 857-862
      ,
      • Lindahl B.
      • Nilssoen T.K.
      • Borch-Johnsen K.
      • Roder M.E.
      • Soederberg S.
      • Widman L.
      • et al.
      A randomized lifestyle intervention with 5-year follow-up in subjects with impaired glucose tolerance: pronounced short-term impact but long-term adherence problems.
      Scand. J. Public Health. 2009; 37: 434-442
      ,
      • O’Brien M.J.
      • Perez A.
      • Scanlan A.B.
      • Alos V.A.
      • Whitaker R.C.
      • Foster G.D.
      • et al.
      PREVENT-DM comparative effectiveness trial of lifestyle intervention and metformin.
      Am. J. Prev. Med. 2017; 52: 788-797
      ,
      • Corpeleijn E.
      • Feskens E.J.
      • Jansen E.H.
      • Mensink M.
      • Saris W.H.
      • Bruin T.W.
      • et al.
      Improvements in glucose tolerance and insulin sensitivity after lifestyle intervention are related to changes in serum fatty acid profile and desaturase activities: the SLIM study.
      Diabetologia. 2006; 49: 2392-2401
      ,
      • Roumen C.
      • Corpeleijn E.
      • Feskens E.J.
      • Mensink M.
      • Saris W.H.
      • Blaak E.E.
      • et al.
      Impact of 3-year lifestyle intervention on postprandial glucose metabolism: the SLIM study.
      Diabet. Med. 2008; 25: 597-605
      ,
      • Roumen C.
      • Feskens E.J.
      • Corpeleijn E.
      • Mensink M.
      • Saris W.H.
      • Blaak E.E.
      • et al.
      Predictors of lifestyle intervention outcome and dropout: the SLIM study.
      Eur. J. Clin. Nutr. 2011; 65: 1141-1147
      ,
      • Wong C.K.H.
      • Fung C.S.C.
      • Siu S.C.
      • Lo Y.Y.C.
      • Wong K.W.
      • Fong D.Y.T.
      • et al.
      A short message service (SMS) intervention to prevent diabetes in Chinese professional drivers with pre-diabetes: a pilot single-blinded randomized controlled trial.
      Diabetes Res. Clin. Pract. 2013; 102: 158-166
      ,
      • Xu D.F.
      • Sun J.Q.
      • Chen M.
      • Chen Y.Q.
      • Xie H.
      • Sun W.J.
      • et al.
      Effects of lifestyle intervention and meal replacement on glycaemic and body-weight control in Chinese subjects with impaired glucose regulation: a 1-year randomised controlled trial.
      Br. J. Nutr. 2013; 109: 487-492
      ,
      • Yates T.
      • Davies M.
      • Gorely T.
      • Bull F.
      • Khunti K.
      • et al.
      Effectiveness of a pragmatic education program designed to promote walking activity in individuals with impaired glucose tolerance: a randomized controlled trial.
      Diabetes Care. 2009; 32: 1404-1410
      ,
      • Saito T.
      • Watanabe M.
      • Nishida J.
      • Izumi T.
      • Omura M.
      • Takagi T.
      • et al.
      Lifestyle modification and prevention of type 2 diabetes in overweight Japanese with impaired fasting glucose levels: a randomized controlled trial.
      Arch. Intern. Med. 2011; 171: 1352-1360
      ]. People with prediabetes who received lifestyle intervention had a 54 percent lower risk of progressing to type 2 diabetes than people receiving treatment as usual (4% vs. 10%; RR 0.46 [95% CI 0.32, 0.66], Fig. 1).
      Fig. 1
      Fig. 1Relative risk of developing type 2 diabetes after 1 year of lifestyle intervention compared with treatment as usual.
      Brazilian LSI: Brazilian Lifestyle Intervention Study; EDIPS: European Diabetes Prevention Study; CI: Confidence Interval; SLIM: Study on Lifestyle intervention and Impaired glucose tolerance Maastricht; EDIPS: European Diabetes Prevention Study.
      After 3 years of follow-up, pooled results of 11 RCTs involving a total of 5224 people with prediabetes showed that lifestyle intervention participants had a 36 percent lower risk of developing type 2 diabetes compared with those receiving treatment as usual (14% vs. 23%, RR 0.64 [95% CI 0.53, 0.77], Fig. 2) [
      • Bhopal R.S.
      • Douglas A.
      • Wallia S.
      • Forbes J.F.
      • Lean M.E.
      • Gill J.M.
      • et al.
      Effect of a lifestyle intervention on weight change in south Asian individuals in the UK at high risk of type 2 diabetes: a family-cluster randomised controlled trial.
      Lancet Diabetes Endocrinol. 2014; 2: 218-227
      ,
      • Davies M.J.
      • Gray L.J.
      • Troughton J.
      • Gray A.
      • Tuomilehto J.
      • Farooqi A.
      • et al.
      A community based primary prevention programme for type 2 diabetes integrating identification and lifestyle intervention for prevention: the Let’s Prevent Diabetes cluster randomised controlled trial.
      Prev. Med. 2016; 84: 48-56
      ,

      M.J. Davies, L.J. Gray, D. Ahrabian, M. Carey, A. Farooqi, A. Gray, et al, A community-based primary prevention programme for type 2 diabetes mellitus integrating identification and lifestyle intervention for prevention: a cluster randomized controlled trial. 2017.

      ,
      • Ackermann R.T.
      • Edelstein S.L.
      • Narayan K.M.
      • Zhang P.
      • Engelgau M.M.
      • Herman W.H.
      • et al.
      Changes in health state utilities with changes in body mass in the Diabetes Prevention Program.
      Obesity (Silver Spring, Md.). 2009; 17: 2176-2181
      ,
      • Bray G.A.
      • Culbert I.W.
      • Champagne C.M.
      • Dawson L.
      • Eberhardt B.
      • Greenway F.L.
      • et al.
      The diabetes prevention program: Baseline characteristics of the randomized cohort.
      Diabetes Care. 2000; 23: 1619-1629
      ,
      • Florez H.
      • Pan Q.
      • Ackermann R.T.
      • Marrero D.G.
      • Barrett-Connor E.
      • Delahanty L.
      • et al.
      Impact of lifestyle intervention and metformin on health-related quality of life: the diabetes prevention program randomized trial.
      J. Gen. Intern. Med. 2012; 27: 1594-1601
      ,
      • Fujimoto W.Y.
      • Jablonski K.A.
      • Bray G.A.
      • Kriska A.
      • Barrett-Connor E.
      • Haffner S.
      • et al.
      Body size and shape changes and the risk of diabetes in the diabetes prevention program.
      Diabetes. 2007; 56: 1680-1685
      ,
      • Molitch M.E.
      • Fujimoto W.
      • Hamman R.F.
      • Knowler W.C.
      • Diabetes Prevention Program Research Group, N P
      The diabetes prevention program and its global implications.
      J. Am. Soc. Nephrol. 2003; 14: 103-107
      ,
      • Ratner R.E.
      • Diabetes Prevention Program Research
      An update on the Diabetes Prevention Program.
      Endocr. Pract. 2006; 12: 20-24
      ,
      • Diabetes Prevention Program Research Group
      Reduction of the incidence of type 2 diabetes with lifestyle intervention or metformin.
      Int. Urol. Nephrol. 2002; 34: 162-163
      ,
      • Diabetes Prevention Program Research Group
      • Schade D.
      • Ma Y.
      • Fujimoto W.Y.
      • Barrett-Connor E.
      • Fowler S.
      • et al.
      The influence of age on the effects of lifestyle modification and metformin in prevention of diabetes.
      J. Gerontol. Ser. A: Biol. Sci. Med. Sci. 2006; 61: 1075-1081
      ,
      • Penn L.
      • White M.
      • Oldroyd J.
      • Walker M.
      • Alberti K.G.
      • Mathers J.C.
      Prevention of type 2 diabetes in adults with impaired glucose tolerance: the European Diabetes Prevention RCT in Newcastle upon Tyne, UK.
      BMC Public Health. 2009; 9: 342
      ,
      • Eriksson J.
      • Lindstroem J.
      • Valle T.
      • Aunola S.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type II diabetes in subjects with impaired glucose tolerance: the Diabetes Prevention Study (DPS) in Finland. Study design and 1-year interim report on the feasibility of the lifestyle intervention programme.
      Diabetologia. 1999; 42: 793-801
      ,
      • Ilanne-Parikka P.
      • Eriksson J.G.
      • Lindstroem J.
      • Peltonen M.
      • Aunola S.
      • Haemaelaeinen H.
      • et al.
      Effect of lifestyle intervention on the occurrence of metabolic syndrome and its components in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 805-807
      ,
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Aunola S.
      • Cepaitis Z.
      • Hakumaeki M.
      • et al.
      Prevention of diabetes mellitus in subjects with impaired glucose tolerance in the Finnish Diabetes Prevention Study: results from a randomized clinical trial.
      J. Am. Soc. Nephrol. 2003; 14: 108-113
      ,
      • Lindstroem J.
      • Louheranta A.
      • Mannelin M.
      • Rastas M.
      • Salminen V.
      • Eriksson J.
      • et al.
      The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity.
      Diabetes Care. 2003; 26: 3230-3236
      ,
      • Tuomilehto J.
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance.
      N. Engl. J. Med. 2001; 344: 1343-1350
      ,
      • Uusitupa M.
      • Louheranta A.
      • Lindstroem J.
      • Valle T.
      • Sundvall J.
      • Eriksson J.
      • et al.
      The Finnish diabetes prevention study.
      Br. J. Nutr. 2000; 83: 137-142
      ,
      • Lindström J.
      • Peltonen M.
      • Eriksson J.G.
      • Aunola S.
      • Hmlinen H.
      • Ilanne-Parikka P.
      • et al.
      Determinants for the effectiveness of lifestyle intervention in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 857-862
      ,
      • Hellgren M.I.
      • Jansson P.-A.
      • Wedel H.
      • Lindblad U.
      A lifestyle intervention in primary care prevents deterioration of insulin resistance in patients with impaired glucose tolerance: a randomised controlled trial.
      Scand. J. Public Health. 2016; 44 (Accepted: July 15, 2016 https://doi.org/10.1177/1403494816663539): 718-725
      ,
      • Ramachandran A.
      • Snehalatha C.
      • Mary S.
      • Mukesh B.
      • Bhaskar A.D.
      • Vijay V.
      • et al.
      The Indian Diabetes Prevention Programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1).
      Diabetologia. 2006; 49: 289-297
      ,
      • Lindahl B.
      • Nilssoen T.K.
      • Borch-Johnsen K.
      • Roder M.E.
      • Soederberg S.
      • Widman L.
      • et al.
      A randomized lifestyle intervention with 5-year follow-up in subjects with impaired glucose tolerance: pronounced short-term impact but long-term adherence problems.
      Scand. J. Public Health. 2009; 37: 434-442
      ,
      • Sakane N.
      • Sato J.
      • Tsushita K.
      • Tsujii S.
      • Kotani K.
      • Tsuzaki K.
      • et al.
      Prevention of type 2 diabetes in a primary healthcare setting: three-year results of lifestyle intervention in Japanese subjects with impaired glucose tolerance.
      BMC Public Health. 2011; 11: 40
      ,
      • Corpeleijn E.
      • Feskens E.J.
      • Jansen E.H.
      • Mensink M.
      • Saris W.H.
      • Bruin T.W.
      • et al.
      Improvements in glucose tolerance and insulin sensitivity after lifestyle intervention are related to changes in serum fatty acid profile and desaturase activities: the SLIM study.
      Diabetologia. 2006; 49: 2392-2401
      ,
      • Roumen C.
      • Corpeleijn E.
      • Feskens E.J.
      • Mensink M.
      • Saris W.H.
      • Blaak E.E.
      • et al.
      Impact of 3-year lifestyle intervention on postprandial glucose metabolism: the SLIM study.
      Diabet. Med. 2008; 25: 597-605
      ,
      • Roumen C.
      • Feskens E.J.
      • Corpeleijn E.
      • Mensink M.
      • Saris W.H.
      • Blaak E.E.
      • et al.
      Predictors of lifestyle intervention outcome and dropout: the SLIM study.
      Eur. J. Clin. Nutr. 2011; 65: 1141-1147
      ,
      • Saito T.
      • Watanabe M.
      • Nishida J.
      • Izumi T.
      • Omura M.
      • Takagi T.
      • et al.
      Lifestyle modification and prevention of type 2 diabetes in overweight Japanese with impaired fasting glucose levels: a randomized controlled trial.
      Arch. Intern. Med. 2011; 171: 1352-1360
      ]. After six years, the Da Qing Study, with 563 participants, reported that people in one of three different lifestyle intervention groups (diet, exercise, or diet and exercise) had a 28–41 percent lower risk of type 2 diabetes compared with treatment as usual (diet vs. control: 41% vs. 64%, RR 0.64 [95% CI 0.50, 0.80], exercise vs. control: 38% vs. 64%, RR 0.59 [95% CI 0.47, 0.75], diet and exercise vs. control: 46% vs. 64%, RR 0.72 [95% CI 0.57, 0.90], Table 1) [
      • Pan X.R.
      • Li G.W.
      • Hu Y.H.
      • Wang J.X.
      • Yang W.Y.
      • An Z.X.
      • et al.
      Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance: the Da Qing IGT and diabetes study.
      Diabetes Care. 1997; 20: 537-544
      ].
      Fig. 2
      Fig. 2Relative risk of developing type 2 diabetes after 3 years of lifestyle intervention compared with treatment as usual.
      CI: Confidence Interval; IDDP: Indian Diabetes Prevention Programme; EDIPS: European Diabetes Prevention Study; SLIM: Study on Lifestyle intervention and Impaired glucose tolerance Maastricht; Finnish DPS: Finnish Diabetes Prevention Study; U.S. DPP: United States Diabetes Prevention Program.
      Table 1Randomized controlled trials on the efficacy and safety of lifestyle intervention compared to usual care: findings and strength of evidence.
      Author, YearFollow-upResults:

      Lifestyle intervention versus treatment as usual      		In favor of lifestyle interventionStrength of evidence
      Type 2 diabetes
      Brazilian LIS, 2010
      • Pimentel G.D.
      • Portero-McLellan K.C.
      • Oliveira E.P.
      • Spada A.P.
      • Oshiiwa M.
      • Zemdegs J.C.
      • et al.
      Long-term nutrition education reduces several risk factors for type 2 diabetes mellitus in Brazilians with impaired glucose tolerance.
      Nutr. Res. (New York, NY). 2010; 30: 186-190
      		1 year0/21 (0%)
      Values calculated from the data of the included systematic review [16].
      vs. 1/30 (3%)a      		RR
      Values calculated from the data of the included systematic review [16].
      : 0.47 (95% CI: 0.02, 11.00)      		YESHIGH
      EDIPS, 2009
      • Penn L.
      • White M.
      • Oldroyd J.
      • Walker M.
      • Alberti K.G.
      • Mathers J.C.
      Prevention of type 2 diabetes in adults with impaired glucose tolerance: the European Diabetes Prevention RCT in Newcastle upon Tyne, UK.
      BMC Public Health. 2009; 9: 342
      		3/39 (8%)
      Values calculated from the data of the included systematic review [16].
      vs. 3/43 (7%)a      		RR
      Values calculated from the data of the included systematic review [16].
      : 1.10 (95% CI: 0.24, 5.15)
      Finnish DPS, 1999–2008
      • Eriksson J.
      • Lindstroem J.
      • Valle T.
      • Aunola S.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type II diabetes in subjects with impaired glucose tolerance: the Diabetes Prevention Study (DPS) in Finland. Study design and 1-year interim report on the feasibility of the lifestyle intervention programme.
      Diabetologia. 1999; 42: 793-801
      ,
      • Ilanne-Parikka P.
      • Eriksson J.G.
      • Lindstroem J.
      • Peltonen M.
      • Aunola S.
      • Haemaelaeinen H.
      • et al.
      Effect of lifestyle intervention on the occurrence of metabolic syndrome and its components in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 805-807
      ,
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Aunola S.
      • Cepaitis Z.
      • Hakumaeki M.
      • et al.
      Prevention of diabetes mellitus in subjects with impaired glucose tolerance in the Finnish Diabetes Prevention Study: results from a randomized clinical trial.
      J. Am. Soc. Nephrol. 2003; 14: 108-113
      ,
      • Lindstroem J.
      • Louheranta A.
      • Mannelin M.
      • Rastas M.
      • Salminen V.
      • Eriksson J.
      • et al.
      The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity.
      Diabetes Care. 2003; 26: 3230-3236
      ,
      • Tuomilehto J.
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance.
      N. Engl. J. Med. 2001; 344: 1343-1350
      ,
      • Uusitupa M.
      • Louheranta A.
      • Lindstroem J.
      • Valle T.
      • Sundvall J.
      • Eriksson J.
      • et al.
      The Finnish diabetes prevention study.
      Br. J. Nutr. 2000; 83: 137-142
      ,
      • Lindström J.
      • Peltonen M.
      • Eriksson J.G.
      • Aunola S.
      • Hmlinen H.
      • Ilanne-Parikka P.
      • et al.
      Determinants for the effectiveness of lifestyle intervention in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 857-862
      		5/256 (2%)
      Values calculated from the data of the publications.
      vs. 16/250 (6%)
      Values calculated from the data of the publications.
      		RR
      Values calculated from the data of the publications.
      : 0.31 (95% CI: 0.11, 0.82)
      Lindahl et al., 2009
      • Lindahl B.
      • Nilssoen T.K.
      • Borch-Johnsen K.
      • Roder M.E.
      • Soederberg S.
      • Widman L.
      • et al.
      A randomized lifestyle intervention with 5-year follow-up in subjects with impaired glucose tolerance: pronounced short-term impact but long-term adherence problems.
      Scand. J. Public Health. 2009; 37: 434-442
      		5/70 (7%)
      Values calculated from data received directly from the authors.
      vs. 20/79 (25%)
      Values calculated from data received directly from the authors.
      		RR
      Values calculated from data received directly from the authors.
      : 0.28 (95% CI: 0.11, 0.71)
      O’Brien et al., 2017
      • O’Brien M.J.
      • Perez A.
      • Scanlan A.B.
      • Alos V.A.
      • Whitaker R.C.
      • Foster G.D.
      • et al.
      PREVENT-DM comparative effectiveness trial of lifestyle intervention and metformin.
      Am. J. Prev. Med. 2017; 52: 788-797
      		0/30 (0%) vs. 1/28 (4%)RR
      Values calculated from the data of the publications.
      : 0.31 (95% CI: 0.01, 7.35)
      SLIM Study, 2006–2011
      • Corpeleijn E.
      • Feskens E.J.
      • Jansen E.H.
      • Mensink M.
      • Saris W.H.
      • Bruin T.W.
      • et al.
      Improvements in glucose tolerance and insulin sensitivity after lifestyle intervention are related to changes in serum fatty acid profile and desaturase activities: the SLIM study.
      Diabetologia. 2006; 49: 2392-2401
      ,
      • Roumen C.
      • Corpeleijn E.
      • Feskens E.J.
      • Mensink M.
      • Saris W.H.
      • Blaak E.E.
      • et al.
      Impact of 3-year lifestyle intervention on postprandial glucose metabolism: the SLIM study.
      Diabet. Med. 2008; 25: 597-605
      ,
      • Roumen C.
      • Feskens E.J.
      • Corpeleijn E.
      • Mensink M.
      • Saris W.H.
      • Blaak E.E.
      • et al.
      Predictors of lifestyle intervention outcome and dropout: the SLIM study.
      Eur. J. Clin. Nutr. 2011; 65: 1141-1147
      		2/50 (4%)
      Values calculated from the data of the included systematic review [16], subjects classified as type 2 diabetes were excluded (data supplied by authors).
      vs. 10/60 (17%)d      		RR
      Values calculated from the data of the included systematic review [16], subjects classified as type 2 diabetes were excluded (data supplied by authors).
      : 0.24 (95% CI: 0.06, 1.04)
      Wong et al., 2013
      • Wong C.K.H.
      • Fung C.S.C.
      • Siu S.C.
      • Lo Y.Y.C.
      • Wong K.W.
      • Fong D.Y.T.
      • et al.
      A short message service (SMS) intervention to prevent diabetes in Chinese professional drivers with pre-diabetes: a pilot single-blinded randomized controlled trial.
      Diabetes Res. Clin. Pract. 2013; 102: 158-166
      		3/54 (6%) vs. 8/50 (16%)RR: 0.35 (95% CI: 0.10, 1.24)
      Xu et al., 2013
      • Xu D.F.
      • Sun J.Q.
      • Chen M.
      • Chen Y.Q.
      • Xie H.
      • Sun W.J.
      • et al.
      Effects of lifestyle intervention and meal replacement on glycaemic and body-weight control in Chinese subjects with impaired glucose regulation: a 1-year randomised controlled trial.
      Br. J. Nutr. 2013; 109: 487-492
      		6/41 (15%) vs. 7/40 (18%)RR
      Values calculated from the data of the publications.
      : 0.84 (95% CI: 0.31, 2.27)
      Yates et al., 2009
      • Yates T.
      • Davies M.
      • Gorely T.
      • Bull F.
      • Khunti K.
      • et al.
      Effectiveness of a pragmatic education program designed to promote walking activity in individuals with impaired glucose tolerance: a randomized controlled trial.
      Diabetes Care. 2009; 32: 1404-1410
      		1/64 (2%)
      Values calculated from the data of the publications.
      vs. 3/34 (9%)
      Values calculated from the data of the publications.
      		RR
      Values calculated from the data of the publications.
      : 0.18 (95% CI: 0.02, 1.64)
      Zensharen Study, 2011
      • Saito T.
      • Watanabe M.
      • Nishida J.
      • Izumi T.
      • Omura M.
      • Takagi T.
      • et al.
      Lifestyle modification and prevention of type 2 diabetes in overweight Japanese with impaired fasting glucose levels: a randomized controlled trial.
      Arch. Intern. Med. 2011; 171: 1352-1360
      		13/311 (4%)
      Values calculated from the data of the publications.
      vs. 22/330 (7%)
      Values calculated from the data of the publications.
      		RR
      Values calculated from the data of the publications.
      : 0.63 (95% CI: 0.32, 1.22)
      Bhopal et al., 2014
      • Bhopal R.S.
      • Douglas A.
      • Wallia S.
      • Forbes J.F.
      • Lean M.E.
      • Gill J.M.
      • et al.
      Effect of a lifestyle intervention on weight change in south Asian individuals in the UK at high risk of type 2 diabetes: a family-cluster randomised controlled trial.
      Lancet Diabetes Endocrinol. 2014; 2: 218-227
      		3 years12/81 (15%) vs. 17/82 (21%)RR
      Values calculated from the data of the publications.
      : 0.71 (95% CI: 0.36, 1.40)      		YESHIGH
      Davies et al., 2016-2017
      • Davies M.J.
      • Gray L.J.
      • Troughton J.
      • Gray A.
      • Tuomilehto J.
      • Farooqi A.
      • et al.
      A community based primary prevention programme for type 2 diabetes integrating identification and lifestyle intervention for prevention: the Let’s Prevent Diabetes cluster randomised controlled trial.
      Prev. Med. 2016; 84: 48-56
      ,

      M.J. Davies, L.J. Gray, D. Ahrabian, M. Carey, A. Farooqi, A. Gray, et al, A community-based primary prevention programme for type 2 diabetes mellitus integrating identification and lifestyle intervention for prevention: a cluster randomized controlled trial. 2017.

      		64/447 (14%) vs. 67/433 (15%)HR: 0.74 (95% CI: 0.48, 1.14)
      U.S. DPP, 2000–2009 [22-29]
      Mean follow-up: 2.8 years.
      		132/1051 (13%)
      Values calculated from the data of the included systematic review [16].
      vs. 276/1057 (26%)
      Values calculated from the data of the included systematic review [16].
      		RR
      Values calculated from the data of the included systematic review [16].
      : 0.48 (95% CI: 0.40, 0.58)
      EDIPS, 2009
      • Penn L.
      • White M.
      • Oldroyd J.
      • Walker M.
      • Alberti K.G.
      • Mathers J.C.
      Prevention of type 2 diabetes in adults with impaired glucose tolerance: the European Diabetes Prevention RCT in Newcastle upon Tyne, UK.
      BMC Public Health. 2009; 9: 342
      		5/27 (19%)
      Values calculated from the data of the included systematic review [16].
      vs. 7/33 (21%)
      Values calculated from the data of the included systematic review [16].
      		RR
      Values calculated from the data of the included systematic review [16].
      : 0.87 (95% CI: 0.31, 2.44)
      Finnish DPS, 1999–2008
      • Eriksson J.
      • Lindstroem J.
      • Valle T.
      • Aunola S.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type II diabetes in subjects with impaired glucose tolerance: the Diabetes Prevention Study (DPS) in Finland. Study design and 1-year interim report on the feasibility of the lifestyle intervention programme.
      Diabetologia. 1999; 42: 793-801
      ,
      • Ilanne-Parikka P.
      • Eriksson J.G.
      • Lindstroem J.
      • Peltonen M.
      • Aunola S.
      • Haemaelaeinen H.
      • et al.
      Effect of lifestyle intervention on the occurrence of metabolic syndrome and its components in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 805-807
      ,
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Aunola S.
      • Cepaitis Z.
      • Hakumaeki M.
      • et al.
      Prevention of diabetes mellitus in subjects with impaired glucose tolerance in the Finnish Diabetes Prevention Study: results from a randomized clinical trial.
      J. Am. Soc. Nephrol. 2003; 14: 108-113
      ,
      • Lindstroem J.
      • Louheranta A.
      • Mannelin M.
      • Rastas M.
      • Salminen V.
      • Eriksson J.
      • et al.
      The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity.
      Diabetes Care. 2003; 26: 3230-3236
      ,
      • Tuomilehto J.
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance.
      N. Engl. J. Med. 2001; 344: 1343-1350
      ,
      • Uusitupa M.
      • Louheranta A.
      • Lindstroem J.
      • Valle T.
      • Sundvall J.
      • Eriksson J.
      • et al.
      The Finnish diabetes prevention study.
      Br. J. Nutr. 2000; 83: 137-142
      ,
      • Lindström J.
      • Peltonen M.
      • Eriksson J.G.
      • Aunola S.
      • Hmlinen H.
      • Ilanne-Parikka P.
      • et al.
      Determinants for the effectiveness of lifestyle intervention in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 857-862
      		22/256 (9%)
      Values calculated from the data of the publications.
      vs. 51/250 (20%)
      Values calculated from the data of the publications.
      		RR
      Values calculated from the data of the publications.
      : 0.42 (95% CI: 0.26, 0.67)
      Hellgren et. al., 2016
      • Hellgren M.I.
      • Jansson P.-A.
      • Wedel H.
      • Lindblad U.
      A lifestyle intervention in primary care prevents deterioration of insulin resistance in patients with impaired glucose tolerance: a randomised controlled trial.
      Scand. J. Public Health. 2016; 44 (Accepted: July 15, 2016 https://doi.org/10.1177/1403494816663539): 718-725
      		10/70
      Values calculated from data received directly from the authors.
      (14%) vs. 7/36
      Values calculated from data received directly from the authors.
      (19%)      		RR
      Values calculated from data received directly from the authors.
      :0.73 (95% CI: 0.31, 1.77)
      IDPP-1, 2006
      • Ramachandran A.
      • Snehalatha C.
      • Mary S.
      • Mukesh B.
      • Bhaskar A.D.
      • Vijay V.
      • et al.
      The Indian Diabetes Prevention Programme shows that lifestyle modification and metformin prevent type 2 diabetes in Asian Indian subjects with impaired glucose tolerance (IDPP-1).
      Diabetologia. 2006; 49: 289-297
      		47/120 (39%)
      Values calculated from the data of the included systematic review [16].
      vs. 74/133 (56%)
      Values calculated from the data of the included systematic review [16].
      		RR
      Values calculated from the data of the included systematic review [16].
      : 0.70 (95% CI: 0.54, 0.92)
      Lindahl et al., 2009
      • Lindahl B.
      • Nilssoen T.K.
      • Borch-Johnsen K.
      • Roder M.E.
      • Soederberg S.
      • Widman L.
      • et al.
      A randomized lifestyle intervention with 5-year follow-up in subjects with impaired glucose tolerance: pronounced short-term impact but long-term adherence problems.
      Scand. J. Public Health. 2009; 37: 434-442
      		12/70 (17%)
      Values calculated from data received directly from the authors.
      vs. 20/79 (25%)
      Values calculated from data received directly from the authors.
      		RR
      Values calculated from data received directly from the authors.
      : 0.68 (95% CI: 0.36, 1.28)
      Sakane, 2011
      • Sakane N.
      • Sato J.
      • Tsushita K.
      • Tsujii S.
      • Kotani K.
      • Tsuzaki K.
      • et al.
      Prevention of type 2 diabetes in a primary healthcare setting: three-year results of lifestyle intervention in Japanese subjects with impaired glucose tolerance.
      BMC Public Health. 2011; 11: 40
      		9/123 (7%)
      Values calculated from the data of the publications.
      vs. 18/131 (14%)
      Values calculated from the data of the publications.
      		RR
      Values calculated from the data of the publications.
      : 0.53 (95% CI: 0.25, 1.14)
      SLIM Study, 2006–2011
      • Corpeleijn E.
      • Feskens E.J.
      • Jansen E.H.
      • Mensink M.
      • Saris W.H.
      • Bruin T.W.
      • et al.
      Improvements in glucose tolerance and insulin sensitivity after lifestyle intervention are related to changes in serum fatty acid profile and desaturase activities: the SLIM study.
      Diabetologia. 2006; 49: 2392-2401
      ,
      • Roumen C.
      • Corpeleijn E.
      • Feskens E.J.
      • Mensink M.
      • Saris W.H.
      • Blaak E.E.
      • et al.
      Impact of 3-year lifestyle intervention on postprandial glucose metabolism: the SLIM study.
      Diabet. Med. 2008; 25: 597-605
      ,
      • Roumen C.
      • Feskens E.J.
      • Corpeleijn E.
      • Mensink M.
      • Saris W.H.
      • Blaak E.E.
      • et al.
      Predictors of lifestyle intervention outcome and dropout: the SLIM study.
      Eur. J. Clin. Nutr. 2011; 65: 1141-1147
      		8/44 (18%)
      Values calculated from the data of the included systematic review [16], subjects classified as type 2 diabetes were excluded (data supplied by authors).
      vs. 16/50 (32%)
      Values calculated from the data of the included systematic review [16], subjects classified as type 2 diabetes were excluded (data supplied by authors).
      		RR
      Values calculated from the data of the included systematic review [16], subjects classified as type 2 diabetes were excluded (data supplied by authors).
      : 0.57 (95% CI: 0.27, 1.20)
      Zensharen Study, 2011
      • Saito T.
      • Watanabe M.
      • Nishida J.
      • Izumi T.
      • Omura M.
      • Takagi T.
      • et al.
      Lifestyle modification and prevention of type 2 diabetes in overweight Japanese with impaired fasting glucose levels: a randomized controlled trial.
      Arch. Intern. Med. 2011; 171: 1352-1360
      		35/311 (11%)
      Values calculated from the data of the publications.
      vs. 51/330 (15%)
      Values calculated from the data of the publications.
      		RR
      Values calculated from the data of the publications.
      : 0.73 (95% CI: 0.49, 1.09)
      Sakane et al., 2015
      • Sakane N.
      • Kotani K.
      • Takahashi K.
      • Sano Y.
      • Tsuzaki K.
      • Okazaki K.
      • et al.
      Effects of telephone-delivered lifestyle support on the development of diabetes in participants at high risk of type 2 diabetes: J-DOIT1, a pragmatic cluster randomised trial.
      BMJ Open. 2015; 5e007316
      		4.2
      Median.
      years      		115/1,240 (9.3%) vs. 132/1367 (9.7%)HR: 1.0 (95% CI: 0.74, 1.34)No statistically significant differenceLOW
      Lindahl et al., 2009
      • Lindahl B.
      • Nilssoen T.K.
      • Borch-Johnsen K.
      • Roder M.E.
      • Soederberg S.
      • Widman L.
      • et al.
      A randomized lifestyle intervention with 5-year follow-up in subjects with impaired glucose tolerance: pronounced short-term impact but long-term adherence problems.
      Scand. J. Public Health. 2009; 37: 434-442
      		5 years17/70
      Values calculated from data received directly from the authors.
      (24%) vs. 23/79
      Values calculated from data received directly from the authors.
      (29%)      		RR
      Values calculated from data received directly from the authors.
      : 0.83 (95% CI: 0.49, 1.43)
      Da Qing Study, 1997
      • Pan X.R.
      • Li G.W.
      • Hu Y.H.
      • Wang J.X.
      • Yang W.Y.
      • An Z.X.
      • et al.
      Effects of diet and exercise in preventing NIDDM in people with impaired glucose tolerance: the Da Qing IGT and diabetes study.
      Diabetes Care. 1997; 20: 537-544
      		6 yearsdiet vs. control:

      59/144 (41%)
      Values calculated from the data of the included systematic review [16].
      vs. 87/135 (64%)
      Values calculated from the data of the included systematic review [16].


      exercise vs. control:

      59/154 (38%)
      Values calculated from the data of the included systematic review [16].
      vs. 87/135 (64%)
      Values calculated from the data of the included systematic review [16].


      diet and exercise vs. control:

      60/130 (46%)
      Values calculated from the data of the included systematic review [16].
      vs. 87/135 (64%)
      Values calculated from the data of the included systematic review [16].


      all 3 lifestyle modification groups vs. control:

      178/428 (42%)
      Values calculated from the data of the included systematic review [16].
      vs. 87/135 (64%)
      Values calculated from the data of the included systematic review [16].


      RR
      Values calculated from the data of the included systematic review [16].
      : 0.64 (95% CI: 0.50, 0.80)



      RR
      Values calculated from the data of the included systematic review [16].
      : 0.59 (95% CI: 0.47, 0.75)



      RR
      Values calculated from the data of the included systematic review [16].
      : 0.72 (95% CI: 0.57, 0.90)



      RR
      Values calculated from the data of the included systematic review [16].
      : 0.65 (95% CI: 0.55, 0.76)      		YESHIGH
      Weight loss
      Brazilian LIS, 2010
      • Pimentel G.D.
      • Portero-McLellan K.C.
      • Oliveira E.P.
      • Spada A.P.
      • Oshiiwa M.
      • Zemdegs J.C.
      • et al.
      Long-term nutrition education reduces several risk factors for type 2 diabetes mellitus in Brazilians with impaired glucose tolerance.
      Nutr. Res. (New York, NY). 2010; 30: 186-190
      		1 year−2.96 kg
      Values calculated from the data of the included systematic review [16].
      ±2.35 (n = 21) vs. 0.43 kg
      Values calculated from the data of the included systematic review [16].
      ±2.35 (n = 30)      		MD
      Values calculated from the data of the included systematic review [16].
      : −3.40 kg (95% CI: −4.89, −1.90)      		YESMODERATE
      U.S. DPP, 2000–2009
      • Ackermann R.T.
      • Edelstein S.L.
      • Narayan K.M.
      • Zhang P.
      • Engelgau M.M.
      • Herman W.H.
      • et al.
      Changes in health state utilities with changes in body mass in the Diabetes Prevention Program.
      Obesity (Silver Spring, Md.). 2009; 17: 2176-2181
      ,
      • Bray G.A.
      • Culbert I.W.
      • Champagne C.M.
      • Dawson L.
      • Eberhardt B.
      • Greenway F.L.
      • et al.
      The diabetes prevention program: Baseline characteristics of the randomized cohort.
      Diabetes Care. 2000; 23: 1619-1629
      ,
      • Florez H.
      • Pan Q.
      • Ackermann R.T.
      • Marrero D.G.
      • Barrett-Connor E.
      • Delahanty L.
      • et al.
      Impact of lifestyle intervention and metformin on health-related quality of life: the diabetes prevention program randomized trial.
      J. Gen. Intern. Med. 2012; 27: 1594-1601
      ,
      • Fujimoto W.Y.
      • Jablonski K.A.
      • Bray G.A.
      • Kriska A.
      • Barrett-Connor E.
      • Haffner S.
      • et al.
      Body size and shape changes and the risk of diabetes in the diabetes prevention program.
      Diabetes. 2007; 56: 1680-1685
      ,
      • Molitch M.E.
      • Fujimoto W.
      • Hamman R.F.
      • Knowler W.C.
      • Diabetes Prevention Program Research Group, N P
      The diabetes prevention program and its global implications.
      J. Am. Soc. Nephrol. 2003; 14: 103-107
      ,
      • Ratner R.E.
      • Diabetes Prevention Program Research
      An update on the Diabetes Prevention Program.
      Endocr. Pract. 2006; 12: 20-24
      ,
      • Diabetes Prevention Program Research Group
      Reduction of the incidence of type 2 diabetes with lifestyle intervention or metformin.
      Int. Urol. Nephrol. 2002; 34: 162-163
      ,
      • Diabetes Prevention Program Research Group
      • Schade D.
      • Ma Y.
      • Fujimoto W.Y.
      • Barrett-Connor E.
      • Fowler S.
      • et al.
      The influence of age on the effects of lifestyle modification and metformin in prevention of diabetes.
      J. Gerontol. Ser. A: Biol. Sci. Med. Sci. 2006; 61: 1075-1081
      		−6.75 kg ±6.98 (n = 1023) vs. −0.43 kg ±4.73 (n = 1,082)MD
      Values calculated from the data of the publications.
      : −6.32 kg (95% CI: −6.84, −5.80)
      EDIPS, 2009
      • Penn L.
      • White M.
      • Oldroyd J.
      • Walker M.
      • Alberti K.G.
      • Mathers J.C.
      Prevention of type 2 diabetes in adults with impaired glucose tolerance: the European Diabetes Prevention RCT in Newcastle upon Tyne, UK.
      BMC Public Health. 2009; 9: 342
      		−2.41 kg
      Values calculated from the data of the included systematic review [16].
      ±4.49 (n = 39) vs. 0.14 kg
      Values calculated from the data of the included systematic review [16].
      ±3.64 (n = 43)      		MD
      Values calculated from the data of the included systematic review [16].
      : −2.55 kg (95% CI: −4.33, −0.77)
      Finnish DPS, 1999–2008
      • Eriksson J.
      • Lindstroem J.
      • Valle T.
      • Aunola S.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type II diabetes in subjects with impaired glucose tolerance: the Diabetes Prevention Study (DPS) in Finland. Study design and 1-year interim report on the feasibility of the lifestyle intervention programme.
      Diabetologia. 1999; 42: 793-801
      ,
      • Ilanne-Parikka P.
      • Eriksson J.G.
      • Lindstroem J.
      • Peltonen M.
      • Aunola S.
      • Haemaelaeinen H.
      • et al.
      Effect of lifestyle intervention on the occurrence of metabolic syndrome and its components in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 805-807
      ,
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Aunola S.
      • Cepaitis Z.
      • Hakumaeki M.
      • et al.
      Prevention of diabetes mellitus in subjects with impaired glucose tolerance in the Finnish Diabetes Prevention Study: results from a randomized clinical trial.
      J. Am. Soc. Nephrol. 2003; 14: 108-113
      ,
      • Lindstroem J.
      • Louheranta A.
      • Mannelin M.
      • Rastas M.
      • Salminen V.
      • Eriksson J.
      • et al.
      The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity.
      Diabetes Care. 2003; 26: 3230-3236
      ,
      • Tuomilehto J.
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance.
      N. Engl. J. Med. 2001; 344: 1343-1350
      ,
      • Uusitupa M.
      • Louheranta A.
      • Lindstroem J.
      • Valle T.
      • Sundvall J.
      • Eriksson J.
      • et al.
      The Finnish diabetes prevention study.
      Br. J. Nutr. 2000; 83: 137-142
      ,
      • Lindström J.
      • Peltonen M.
      • Eriksson J.G.
      • Aunola S.
      • Hmlinen H.
      • Ilanne-Parikka P.
      • et al.
      Determinants for the effectiveness of lifestyle intervention in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 857-862
      		−4.5 kg ±5.0 (n = 256)vs. −1.0 kg ±3.7 (n = 250)MD
      Values calculated from the data of the publications.
      : −3.5 kg (95% CI: −4.27, −2.73)
      Lindahl et al., 1999
      • Lindahl B.
      • Nilsson T.K.
      • Jansson J.H.
      • Asplund K.
      • Hallmans G.N.P.
      Improved fibrinolysis by intense lifestyle intervention. A randomized trial in subjects with impaired glucose tolerance.
      J. Intern. Med. 1999; 246: 105-112
      		−5.4 kg (95% CI: −6.5, −4.4, n = 93) vs. −0.5 kg

      (95% CI: −1.1, 0.2; n = 93)      		MD
      Values calculated from the data of the publications.
      : −4.9 kg (95% CI: −5.46, −4.34)
      Lindahl et al., 2009
      • Lindahl B.
      • Nilssoen T.K.
      • Borch-Johnsen K.
      • Roder M.E.
      • Soederberg S.
      • Widman L.
      • et al.
      A randomized lifestyle intervention with 5-year follow-up in subjects with impaired glucose tolerance: pronounced short-term impact but long-term adherence problems.
      Scand. J. Public Health. 2009; 37: 434-442
      		−5.0 kg (95% CI: −5.9, −4.1; n = 83) vs. −0.7 kg

      (95% CI: −1.6, 0.2; n = 85)      		MD: −4.3 kg (95% CI: −5.6, −3.0)
      O’Brien et al., 2017
      • O’Brien M.J.
      • Perez A.
      • Scanlan A.B.
      • Alos V.A.
      • Whitaker R.C.
      • Foster G.D.
      • et al.
      PREVENT-DM comparative effectiveness trial of lifestyle intervention and metformin.
      Am. J. Prev. Med. 2017; 52: 788-797
      		−4.0 kg (95% CI: −5.5, −2.6, n = 30) vs. 0.8 kg

      (95% CI: −0.8; 2.3; n = 28)      		MD: −4.8 (95% CI: −7.3, −2.2)
      Sakane et al., 2011
      • Sakane N.
      • Sato J.
      • Tsushita K.
      • Tsujii S.
      • Kotani K.
      • Tsuzaki K.
      • et al.
      Prevention of type 2 diabetes in a primary healthcare setting: three-year results of lifestyle intervention in Japanese subjects with impaired glucose tolerance.
      BMC Public Health. 2011; 11: 40
      		−1.5 kg ±0.7 (n = 123) vs. −0.7 kg ±2.5 (n = 131)MD
      Values calculated from the data of the publications.
      : −0.8 kg (95% CI: −1.25, −0.35)
      Sakane et al., 2015
      • Sakane N.
      • Kotani K.
      • Takahashi K.
      • Sano Y.
      • Tsuzaki K.
      • Okazaki K.
      • et al.
      Effects of telephone-delivered lifestyle support on the development of diabetes in participants at high risk of type 2 diabetes: J-DOIT1, a pragmatic cluster randomised trial.
      BMJ Open. 2015; 5e007316
      		−1.8 ±3.6 (n = 1240) vs. −1.0 ±3.4 (n = 1367)MD
      Values calculated from the data of the publications.
      : −0.8 kg (95% CI: −1.07, −0.53)
      SLIM Study, 2006–2011
      • Corpeleijn E.
      • Feskens E.J.
      • Jansen E.H.
      • Mensink M.
      • Saris W.H.
      • Bruin T.W.
      • et al.
      Improvements in glucose tolerance and insulin sensitivity after lifestyle intervention are related to changes in serum fatty acid profile and desaturase activities: the SLIM study.
      Diabetologia. 2006; 49: 2392-2401
      ,
      • Roumen C.
      • Corpeleijn E.
      • Feskens E.J.
      • Mensink M.
      • Saris W.H.
      • Blaak E.E.
      • et al.
      Impact of 3-year lifestyle intervention on postprandial glucose metabolism: the SLIM study.
      Diabet. Med. 2008; 25: 597-605
      ,
      • Roumen C.
      • Feskens E.J.
      • Corpeleijn E.
      • Mensink M.
      • Saris W.H.
      • Blaak E.E.
      • et al.
      Predictors of lifestyle intervention outcome and dropout: the SLIM study.
      Eur. J. Clin. Nutr. 2011; 65: 1141-1147
      		−2.24 kg
      Values calculated from the data of the included systematic review [16], subjects classified as type 2 diabetes were excluded (data supplied by authors).
      ±3.80 (n = 50) vs. −0.64 kg
      Values calculated from the data of the included systematic review [16], subjects classified as type 2 diabetes were excluded (data supplied by authors).
      ±3.89 (n = 60)      		MD
      Values calculated from the data of the included systematic review [16], subjects classified as type 2 diabetes were excluded (data supplied by authors).
      : −1.60 kg (95% CI: −3.04, −0.16)
      Xu et al., 2013
      • Xu D.F.
      • Sun J.Q.
      • Chen M.
      • Chen Y.Q.
      • Xie H.
      • Sun W.J.
      • et al.
      Effects of lifestyle intervention and meal replacement on glycaemic and body-weight control in Chinese subjects with impaired glucose regulation: a 1-year randomised controlled trial.
      Br. J. Nutr. 2013; 109: 487-492
      		−1.75 kg ±0.35
      Mean and standard error.
      (n = 41) vs. −0.55 kg ±0.40
      Mean and standard error.
      (n = 40)      		MD
      Values calculated from the data of the publications.
      : −1.20 kg (95% CI: −2.22, −0.18)
      Yeh et al., 2015
      • Yeh M.C.
      • Heo M.
      • Suchday S.
      • Wong A.
      • Poon E.
      • Liu G.
      • et al.
      Translation of the Diabetes Prevention Program for diabetes risk reduction in Chinese immigrants in New York City.
      Diabet. Med. 2016; 33: 547-551
      		−2.17 kg
      Values calculated from the data of the publications.
      ±2.52 (n = 30) vs. 0.21 kg
      Values calculated from the data of the publications.
      ±2.20 (n = 28)      		MD
      Values calculated from the data of the publications.
      : −2.38 kg (95% CI:−3.59; −1.16)
      Zensharen Study, 2011
      • Saito T.
      • Watanabe M.
      • Nishida J.
      • Izumi T.
      • Omura M.
      • Takagi T.
      • et al.
      Lifestyle modification and prevention of type 2 diabetes in overweight Japanese with impaired fasting glucose levels: a randomized controlled trial.
      Arch. Intern. Med. 2011; 171: 1352-1360
      		−2.5 ±3.2 kg (n = 311) vs. −1.1 ±3.2 kg (n = 330)MD
      Values calculated from the data of the publications.
      : −1.4 kg (95% CI: −1.90, −0.90)
      Davies et al., 2016-2017
      • Davies M.J.
      • Gray L.J.
      • Troughton J.
      • Gray A.
      • Tuomilehto J.
      • Farooqi A.
      • et al.
      A community based primary prevention programme for type 2 diabetes integrating identification and lifestyle intervention for prevention: the Let’s Prevent Diabetes cluster randomised controlled trial.
      Prev. Med. 2016; 84: 48-56
      ,

      M.J. Davies, L.J. Gray, D. Ahrabian, M. Carey, A. Farooqi, A. Gray, et al, A community-based primary prevention programme for type 2 diabetes mellitus integrating identification and lifestyle intervention for prevention: a cluster randomized controlled trial. 2017.

      		1 year−0.19 kg ±4.57 (n = 368) vs. 0.02 kg ±4.22 (n = 382)MD: -0.27 kg (95% CI: −1.17, 0.63)No statistically significant differenceLOW
      Hesselink et al., 2015
      • Hesselink A.E.
      • Rutten G.E.H.
      • Slootmaker S.M.
      • de Weerdt I.
      • Raaijmakers L.G.M.
      • Jonkers R.
      • et al.
      Effects of a lifestyle program in subjects with Impaired Fasting Glucose, a pragmatic cluster-randomized controlled trial.
      BMC Fam. Pract. 2015; 16: 183
      		−1.8 kg ±16.2 (n = 171) vs. −2.5 kg ±18.1 (n = 129)MD
      Values calculated from the data of the publications.
      : +0.7 kg (95% CI: −0.33, 4.66)
      Juul et al., 2015
      • Juul L.
      • Andersen V.J.
      • Arnoldsen J.
      • Maindal H.T.
      Effectiveness of a brief theory-based health promotion intervention among adults at high risk of type 2 diabetes: one-year results from a randomised trial in a community setting.
      Prim. Care Diabetes. 2016; 10: 111-120
      		−2.4 kg (95% CI: −3.43, −1.3; n = 63) vs. −1.1 kg

      (95% CI: −2.3, 0.2; n = 64)      		MD: −1.1 (95% CI: −2.8, 0.5)
      Mean difference adjusted for gender, age, and educational level.
      Wong et al., 2013
      • Wong C.K.H.
      • Fung C.S.C.
      • Siu S.C.
      • Lo Y.Y.C.
      • Wong K.W.
      • Fong D.Y.T.
      • et al.
      A short message service (SMS) intervention to prevent diabetes in Chinese professional drivers with pre-diabetes: a pilot single-blinded randomized controlled trial.
      Diabetes Res. Clin. Pract. 2013; 102: 158-166
      		−1.09 kg
      Values calculated from the data of the publications.
      (n = 41) vs. −0.02 kgb (n = 37)      		MD
      Values calculated from the data of the publications.
      : −1.07 kg, CI not reported,

      p = 0.94 (follow-up 6 months to 2 years)
      Yates et al., 2009
      • Yates T.
      • Davies M.
      • Gorely T.
      • Bull F.
      • Khunti K.
      • et al.
      Effectiveness of a pragmatic education program designed to promote walking activity in individuals with impaired glucose tolerance: a randomized controlled trial.
      Diabetes Care. 2009; 32: 1404-1410
      		−0.04 kg
      Values calculated from the data of the publications.
      ±3.64 (n = 58) vs. −0.67 kg ±3.31
      Values calculated from the data of the publications.
      (n = 29)      		MD
      Values calculated from the data of the publications.
      : with and without pedometer vs. control: +0.63 kg (95% CI: −0.89, 2.16)
      U.S. DPP, 2000–2009
      • Ackermann R.T.
      • Edelstein S.L.
      • Narayan K.M.
      • Zhang P.
      • Engelgau M.M.
      • Herman W.H.
      • et al.
      Changes in health state utilities with changes in body mass in the Diabetes Prevention Program.
      Obesity (Silver Spring, Md.). 2009; 17: 2176-2181
      ,
      • Bray G.A.
      • Culbert I.W.
      • Champagne C.M.
      • Dawson L.
      • Eberhardt B.
      • Greenway F.L.
      • et al.
      The diabetes prevention program: Baseline characteristics of the randomized cohort.
      Diabetes Care. 2000; 23: 1619-1629
      ,
      • Florez H.
      • Pan Q.
      • Ackermann R.T.
      • Marrero D.G.
      • Barrett-Connor E.
      • Delahanty L.
      • et al.
      Impact of lifestyle intervention and metformin on health-related quality of life: the diabetes prevention program randomized trial.
      J. Gen. Intern. Med. 2012; 27: 1594-1601
      ,
      • Fujimoto W.Y.
      • Jablonski K.A.
      • Bray G.A.
      • Kriska A.
      • Barrett-Connor E.
      • Haffner S.
      • et al.
      Body size and shape changes and the risk of diabetes in the diabetes prevention program.
      Diabetes. 2007; 56: 1680-1685
      ,
      • Molitch M.E.
      • Fujimoto W.
      • Hamman R.F.
      • Knowler W.C.
      • Diabetes Prevention Program Research Group, N P
      The diabetes prevention program and its global implications.
      J. Am. Soc. Nephrol. 2003; 14: 103-107
      ,
      • Ratner R.E.
      • Diabetes Prevention Program Research
      An update on the Diabetes Prevention Program.
      Endocr. Pract. 2006; 12: 20-24
      ,
      • Diabetes Prevention Program Research Group
      Reduction of the incidence of type 2 diabetes with lifestyle intervention or metformin.
      Int. Urol. Nephrol. 2002; 34: 162-163
      ,
      • Diabetes Prevention Program Research Group
      • Schade D.
      • Ma Y.
      • Fujimoto W.Y.
      • Barrett-Connor E.
      • Fowler S.
      • et al.
      The influence of age on the effects of lifestyle modification and metformin in prevention of diabetes.
      J. Gerontol. Ser. A: Biol. Sci. Med. Sci. 2006; 61: 1075-1081
      Mean follow-up: 2.8 years.
      		3 years−5.6 kg vs. −0.1 kg (n = not reported)
      From 3234 people assigned to metformin, lifestyle intervention and placebo at baseline; 1510 were examined at 3 years.
      		MD
      Values calculated from the data of the publications.
      , 
      Mean follow-up: 2.8 years.
      : −5.5 kg, CI not reported, p < 0.001      		YESMODERATE
      Finnish DPS, 1999–2008
      • Eriksson J.
      • Lindstroem J.
      • Valle T.
      • Aunola S.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type II diabetes in subjects with impaired glucose tolerance: the Diabetes Prevention Study (DPS) in Finland. Study design and 1-year interim report on the feasibility of the lifestyle intervention programme.
      Diabetologia. 1999; 42: 793-801
      ,
      • Ilanne-Parikka P.
      • Eriksson J.G.
      • Lindstroem J.
      • Peltonen M.
      • Aunola S.
      • Haemaelaeinen H.
      • et al.
      Effect of lifestyle intervention on the occurrence of metabolic syndrome and its components in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 805-807
      ,
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Aunola S.
      • Cepaitis Z.
      • Hakumaeki M.
      • et al.
      Prevention of diabetes mellitus in subjects with impaired glucose tolerance in the Finnish Diabetes Prevention Study: results from a randomized clinical trial.
      J. Am. Soc. Nephrol. 2003; 14: 108-113
      ,
      • Lindstroem J.
      • Louheranta A.
      • Mannelin M.
      • Rastas M.
      • Salminen V.
      • Eriksson J.
      • et al.
      The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity.
      Diabetes Care. 2003; 26: 3230-3236
      ,
      • Tuomilehto J.
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance.
      N. Engl. J. Med. 2001; 344: 1343-1350
      ,
      • Uusitupa M.
      • Louheranta A.
      • Lindstroem J.
      • Valle T.
      • Sundvall J.
      • Eriksson J.
      • et al.
      The Finnish diabetes prevention study.
      Br. J. Nutr. 2000; 83: 137-142
      ,
      • Lindström J.
      • Peltonen M.
      • Eriksson J.G.
      • Aunola S.
      • Hmlinen H.
      • Ilanne-Parikka P.
      • et al.
      Determinants for the effectiveness of lifestyle intervention in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 857-862
      		−3.5 kg ±5.1 (n = 231) vs. −0.9 kg ±5.4 (n = 203)MD
      Values calculated from the data of the publications.
      :- 2.60 kg (95% CI: −3.59, −1.61)
      Sakane et al., 2015
      • Sakane N.
      • Kotani K.
      • Takahashi K.
      • Sano Y.
      • Tsuzaki K.
      • Okazaki K.
      • et al.
      Effects of telephone-delivered lifestyle support on the development of diabetes in participants at high risk of type 2 diabetes: J-DOIT1, a pragmatic cluster randomised trial.
      BMJ Open. 2015; 5e007316
      		4.2f years−1.1 kg ±3.4 (n = 1240) vs. −0.6 kg ±3.6 (n = 1367)MD
      Values calculated from the data of the publications.
      : −0.5 kg (95% CI: −0.77, −0.23)
      Bhopal et al., 2014
      • Bhopal R.S.
      • Douglas A.
      • Wallia S.
      • Forbes J.F.
      • Lean M.E.
      • Gill J.M.
      • et al.
      Effect of a lifestyle intervention on weight change in south Asian individuals in the UK at high risk of type 2 diabetes: a family-cluster randomised controlled trial.
      Lancet Diabetes Endocrinol. 2014; 2: 218-227
      		3 years−1.01 kg
      Values calculated from the data of the publications.
      (n = 84) vs. +0.31 kg
      Values calculated from the data of the publications.
      (n = 83)      		MD
      Mean difference adjusted by stratification variables in randomization (ethnic groups, cities) and baseline values.
      : −1.64 kg (95% CI: −2.83 to 0.45)      		No statistically significant differenceLOW
      Davies et al., 2016-2017
      • Davies M.J.
      • Gray L.J.
      • Troughton J.
      • Gray A.
      • Tuomilehto J.
      • Farooqi A.
      • et al.
      A community based primary prevention programme for type 2 diabetes integrating identification and lifestyle intervention for prevention: the Let’s Prevent Diabetes cluster randomised controlled trial.
      Prev. Med. 2016; 84: 48-56
      ,

      M.J. Davies, L.J. Gray, D. Ahrabian, M. Carey, A. Farooqi, A. Gray, et al, A community-based primary prevention programme for type 2 diabetes mellitus integrating identification and lifestyle intervention for prevention: a cluster randomized controlled trial. 2017.

      		−0.59 kg ±4.59 (n = 321) vs. −0.46 ±5.02 (n = 321)MD: −0.26 kg (95% CI: −1.17, 0.65)
      EDIPS, 2009
      • Penn L.
      • White M.
      • Oldroyd J.
      • Walker M.
      • Alberti K.G.
      • Mathers J.C.
      Prevention of type 2 diabetes in adults with impaired glucose tolerance: the European Diabetes Prevention RCT in Newcastle upon Tyne, UK.
      BMC Public Health. 2009; 9: 342
      		−2.68 kg
      Values calculated from the data of the included systematic review [16].
      ±5.00 (n = 27) vs. −1.52 kg
      Values calculated from the data of the included systematic review [16].
      ±5.32 (n = 33)      		MD
      Values calculated from the data of the included systematic review [16].
      : −1.16 kg; 95% CI: −3.78; 1.46
      Hellgren et al., 2016
      • Hellgren M.I.
      • Jansson P.-A.
      • Wedel H.
      • Lindblad U.
      A lifestyle intervention in primary care prevents deterioration of insulin resistance in patients with impaired glucose tolerance: a randomised controlled trial.
      Scand. J. Public Health. 2016; 44 (Accepted: July 15, 2016 https://doi.org/10.1177/1403494816663539): 718-725
      		−0.8 kg vs. (n = 63)
      Values calculated from data received directly from the authors.
      vs. 0.1 kg (n = 29)
      Values calculated from data received directly from the authors.
      		MD: −0.4 (95% CI: −2.8, 2.0)
      Lindahl et al., 2009
      • Lindahl B.
      • Nilssoen T.K.
      • Borch-Johnsen K.
      • Roder M.E.
      • Soederberg S.
      • Widman L.
      • et al.
      A randomized lifestyle intervention with 5-year follow-up in subjects with impaired glucose tolerance: pronounced short-term impact but long-term adherence problems.
      Scand. J. Public Health. 2009; 37: 434-442
      		−1.1
      Values calculated from the data of the publications.
       kg (n = 83) vs. −0.2
      Values calculated from the data of the publications.
       kg (n = 85)      		MD
      Values calculated from the data of the publications.
      : −0.9 kg, CI not reported, p > 0.05
      Sakane et al., 2011
      • Sakane N.
      • Sato J.
      • Tsushita K.
      • Tsujii S.
      • Kotani K.
      • Tsuzaki K.
      • et al.
      Prevention of type 2 diabetes in a primary healthcare setting: three-year results of lifestyle intervention in Japanese subjects with impaired glucose tolerance.
      BMC Public Health. 2011; 11: 40
      		−1.8
      Values calculated from the data of the publications.
       kg (n = 103) vs. −1.4
      Values calculated from the data of the publications.
       kg (n = 110)      		MD
      Values calculated from the data of the publications.
      : −0.4 kg, CI not reported, p = 0.069
      SLIM Study, 2006–2011
      • Corpeleijn E.
      • Feskens E.J.
      • Jansen E.H.
      • Mensink M.
      • Saris W.H.
      • Bruin T.W.
      • et al.
      Improvements in glucose tolerance and insulin sensitivity after lifestyle intervention are related to changes in serum fatty acid profile and desaturase activities: the SLIM study.
      Diabetologia. 2006; 49: 2392-2401
      ,
      • Roumen C.
      • Corpeleijn E.
      • Feskens E.J.
      • Mensink M.
      • Saris W.H.
      • Blaak E.E.
      • et al.
      Impact of 3-year lifestyle intervention on postprandial glucose metabolism: the SLIM study.
      Diabet. Med. 2008; 25: 597-605
      ,
      • Roumen C.
      • Feskens E.J.
      • Corpeleijn E.
      • Mensink M.
      • Saris W.H.
      • Blaak E.E.
      • et al.
      Predictors of lifestyle intervention outcome and dropout: the SLIM study.
      Eur. J. Clin. Nutr. 2011; 65: 1141-1147
      		−0.79 kg
      Values calculated from the data of the included systematic review [16], subjects classified as type 2 diabetes were excluded (data supplied by authors).
      ±4.52 (n = 44) vs. −0.44 kg
      Values calculated from the data of the included systematic review [16], subjects classified as type 2 diabetes were excluded (data supplied by authors).
      ±4.42(n = 50)      		MD
      Values calculated from the data of the included systematic review [16], subjects classified as type 2 diabetes were excluded (data supplied by authors).
      : −0.35 kg (95% CI: −2.16, 1.46)
      Lindahl et al., 2009
      • Lindahl B.
      • Nilssoen T.K.
      • Borch-Johnsen K.
      • Roder M.E.
      • Soederberg S.
      • Widman L.
      • et al.
      A randomized lifestyle intervention with 5-year follow-up in subjects with impaired glucose tolerance: pronounced short-term impact but long-term adherence problems.
      Scand. J. Public Health. 2009; 37: 434-442
      		5 years−1 kg
      Values calculated from the data of the publications.
      (n = 83) vs. 0 kg
      Values calculated from the data of the publications.
      (n = 85)      		MD
      Values calculated from the data of the publications.
      : −1 kg, CI not reported, p > 0.05
      Quality of life
      Davies et al., 2016-2017
      • Davies M.J.
      • Gray L.J.
      • Troughton J.
      • Gray A.
      • Tuomilehto J.
      • Farooqi A.
      • et al.
      A community based primary prevention programme for type 2 diabetes integrating identification and lifestyle intervention for prevention: the Let’s Prevent Diabetes cluster randomised controlled trial.
      Prev. Med. 2016; 84: 48-56
      ,

      M.J. Davies, L.J. Gray, D. Ahrabian, M. Carey, A. Farooqi, A. Gray, et al, A community-based primary prevention programme for type 2 diabetes mellitus integrating identification and lifestyle intervention for prevention: a cluster randomized controlled trial. 2017.

      		3 yearsConversion to scale 0 to 100: Lifestyle intervention by 2 points higher

      Quality of life 15D scale: 0.02 (95% CI: 0.01, 0.03), p = 0.01, 0.0 = bad, 1.0 = best

      Lifestyle intervention: n = 354, treatment as usual (placebo): n = 367      		YESHIGH
      U.S. DPP, 2000–2009
      • Ackermann R.T.
      • Edelstein S.L.
      • Narayan K.M.
      • Zhang P.
      • Engelgau M.M.
      • Herman W.H.
      • et al.
      Changes in health state utilities with changes in body mass in the Diabetes Prevention Program.
      Obesity (Silver Spring, Md.). 2009; 17: 2176-2181
      ,
      • Bray G.A.
      • Culbert I.W.
      • Champagne C.M.
      • Dawson L.
      • Eberhardt B.
      • Greenway F.L.
      • et al.
      The diabetes prevention program: Baseline characteristics of the randomized cohort.
      Diabetes Care. 2000; 23: 1619-1629
      ,
      • Florez H.
      • Pan Q.
      • Ackermann R.T.
      • Marrero D.G.
      • Barrett-Connor E.
      • Delahanty L.
      • et al.
      Impact of lifestyle intervention and metformin on health-related quality of life: the diabetes prevention program randomized trial.
      J. Gen. Intern. Med. 2012; 27: 1594-1601
      ,
      • Fujimoto W.Y.
      • Jablonski K.A.
      • Bray G.A.
      • Kriska A.
      • Barrett-Connor E.
      • Haffner S.
      • et al.
      Body size and shape changes and the risk of diabetes in the diabetes prevention program.
      Diabetes. 2007; 56: 1680-1685
      ,
      • Molitch M.E.
      • Fujimoto W.
      • Hamman R.F.
      • Knowler W.C.
      • Diabetes Prevention Program Research Group, N P
      The diabetes prevention program and its global implications.
      J. Am. Soc. Nephrol. 2003; 14: 103-107
      ,
      • Ratner R.E.
      • Diabetes Prevention Program Research
      An update on the Diabetes Prevention Program.
      Endocr. Pract. 2006; 12: 20-24
      ,
      • Diabetes Prevention Program Research Group
      Reduction of the incidence of type 2 diabetes with lifestyle intervention or metformin.
      Int. Urol. Nephrol. 2002; 34: 162-163
      ,
      • Diabetes Prevention Program Research Group
      • Schade D.
      • Ma Y.
      • Fujimoto W.Y.
      • Barrett-Connor E.
      • Fowler S.
      • et al.
      The influence of age on the effects of lifestyle modification and metformin in prevention of diabetes.
      J. Gerontol. Ser. A: Biol. Sci. Med. Sci. 2006; 61: 1075-1081
      		3.2 yearsConversion to scale 0 to 100: Lifestyle intervention by 1 point higher

      SF-6D scale: 0.0084 (±0.0041), p < 0.05, 0.0 = bad, 1.0 = best

      Lifestyle intervention: n = 1048, treatment as usual (placebo): n = 1041
      Adverse events
      U.S. DPP, 2000–2009
      • Ackermann R.T.
      • Edelstein S.L.
      • Narayan K.M.
      • Zhang P.
      • Engelgau M.M.
      • Herman W.H.
      • et al.
      Changes in health state utilities with changes in body mass in the Diabetes Prevention Program.
      Obesity (Silver Spring, Md.). 2009; 17: 2176-2181
      ,
      • Bray G.A.
      • Culbert I.W.
      • Champagne C.M.
      • Dawson L.
      • Eberhardt B.
      • Greenway F.L.
      • et al.
      The diabetes prevention program: Baseline characteristics of the randomized cohort.
      Diabetes Care. 2000; 23: 1619-1629
      ,
      • Florez H.
      • Pan Q.
      • Ackermann R.T.
      • Marrero D.G.
      • Barrett-Connor E.
      • Delahanty L.
      • et al.
      Impact of lifestyle intervention and metformin on health-related quality of life: the diabetes prevention program randomized trial.
      J. Gen. Intern. Med. 2012; 27: 1594-1601
      ,
      • Fujimoto W.Y.
      • Jablonski K.A.
      • Bray G.A.
      • Kriska A.
      • Barrett-Connor E.
      • Haffner S.
      • et al.
      Body size and shape changes and the risk of diabetes in the diabetes prevention program.
      Diabetes. 2007; 56: 1680-1685
      ,
      • Molitch M.E.
      • Fujimoto W.
      • Hamman R.F.
      • Knowler W.C.
      • Diabetes Prevention Program Research Group, N P
      The diabetes prevention program and its global implications.
      J. Am. Soc. Nephrol. 2003; 14: 103-107
      ,
      • Ratner R.E.
      • Diabetes Prevention Program Research
      An update on the Diabetes Prevention Program.
      Endocr. Pract. 2006; 12: 20-24
      ,
      • Diabetes Prevention Program Research Group
      Reduction of the incidence of type 2 diabetes with lifestyle intervention or metformin.
      Int. Urol. Nephrol. 2002; 34: 162-163
      ,
      • Diabetes Prevention Program Research Group
      • Schade D.
      • Ma Y.
      • Fujimoto W.Y.
      • Barrett-Connor E.
      • Fowler S.
      • et al.
      The influence of age on the effects of lifestyle modification and metformin in prevention of diabetes.
      J. Gerontol. Ser. A: Biol. Sci. Med. Sci. 2006; 61: 1075-1081
      		2.8 yearsMusculoskeletal symptoms: n = 2161

      24.1 vs. 21.1 per 100 people per year, effect size and CI not reported, p < 0.0167,      		NOHIGH
      U.S. DPP, 2000–2009
      • Ackermann R.T.
      • Edelstein S.L.
      • Narayan K.M.
      • Zhang P.
      • Engelgau M.M.
      • Herman W.H.
      • et al.
      Changes in health state utilities with changes in body mass in the Diabetes Prevention Program.
      Obesity (Silver Spring, Md.). 2009; 17: 2176-2181
      ,
      • Bray G.A.
      • Culbert I.W.
      • Champagne C.M.
      • Dawson L.
      • Eberhardt B.
      • Greenway F.L.
      • et al.
      The diabetes prevention program: Baseline characteristics of the randomized cohort.
      Diabetes Care. 2000; 23: 1619-1629
      ,
      • Florez H.
      • Pan Q.
      • Ackermann R.T.
      • Marrero D.G.
      • Barrett-Connor E.
      • Delahanty L.
      • et al.
      Impact of lifestyle intervention and metformin on health-related quality of life: the diabetes prevention program randomized trial.
      J. Gen. Intern. Med. 2012; 27: 1594-1601
      ,
      • Fujimoto W.Y.
      • Jablonski K.A.
      • Bray G.A.
      • Kriska A.
      • Barrett-Connor E.
      • Haffner S.
      • et al.
      Body size and shape changes and the risk of diabetes in the diabetes prevention program.
      Diabetes. 2007; 56: 1680-1685
      ,
      • Molitch M.E.
      • Fujimoto W.
      • Hamman R.F.
      • Knowler W.C.
      • Diabetes Prevention Program Research Group, N P
      The diabetes prevention program and its global implications.
      J. Am. Soc. Nephrol. 2003; 14: 103-107
      ,
      • Ratner R.E.
      • Diabetes Prevention Program Research
      An update on the Diabetes Prevention Program.
      Endocr. Pract. 2006; 12: 20-24
      ,
      • Diabetes Prevention Program Research Group
      Reduction of the incidence of type 2 diabetes with lifestyle intervention or metformin.
      Int. Urol. Nephrol. 2002; 34: 162-163
      ,
      • Diabetes Prevention Program Research Group
      • Schade D.
      • Ma Y.
      • Fujimoto W.Y.
      • Barrett-Connor E.
      • Fowler S.
      • et al.
      The influence of age on the effects of lifestyle modification and metformin in prevention of diabetes.
      J. Gerontol. Ser. A: Biol. Sci. Med. Sci. 2006; 61: 1075-1081
      		2.8 yearsHospital admission: n = 2161

      8 vs. 7.9 per 100 people per year, p-value unknown      		No statistically significant differenceMODERATE
      Abbreviations: Brazilian LIS: Brazilian Lifestyle Intervention Study, CI: Confidence interval, EDIPS: European Diabetes Prevention Study, Finnish DPS: Finnish Diabetes Prevention Study, IDPP-1: Indian Diabetes Prevention Programme 1, n: number of participants, NNT: Number needed to treat, p: probability value, RR: relative risk, vs.: versus, SD: standard deviation, Short form—6 dimensions (SF-6D): body function, role restrictions, social functions, pain, mental health, vitality, SLIM: Study on Lifestyle intervention and Impaired glucose tolerance Maastricht, U.S. DPP: United States Diabetes Prevention Program.
      Continuous endpoints are shown as means with standard deviation.
      a Values calculated from the data of the included systematic review
      • Glechner A.
      • Harreiter J.
      • Gartlehner G.
      • Rohleder S.
      • Kautzky A.
      • Tuomilehto J.
      • et al.
      Sex-specific differences in diabetes prevention: a systematic review and meta-analysis.
      Diabetologia. 2015; 58: 242-254
      .
      b Values calculated from the data of the publications.
      c Values calculated from data received directly from the authors.
      d Values calculated from the data of the included systematic review
      • Glechner A.
      • Harreiter J.
      • Gartlehner G.
      • Rohleder S.
      • Kautzky A.
      • Tuomilehto J.
      • et al.
      Sex-specific differences in diabetes prevention: a systematic review and meta-analysis.
      Diabetologia. 2015; 58: 242-254
      , subjects classified as type 2 diabetes were excluded (data supplied by authors).
      e Mean follow-up: 2.8 years.
      f Median.
      g Mean and standard error.
      h Mean difference adjusted for gender, age, and educational level.
      i From 3234 people assigned to metformin, lifestyle intervention and placebo at baseline; 1510 were examined at 3 years.
      j Mean difference adjusted by stratification variables in randomization (ethnic groups, cities) and baseline values.
      The U.S. DPP (Diabetes Prevention Program) and the Finnish DPS (Diabetes Prevention Study), which together included 2,683 people with prediabetes, showed that lifestyle intervention was more effective in older participants compared to younger counterparts in reducing diabetes incidence [
      • Diabetes Prevention Program Research Group
      Reduction of the incidence of type 2 diabetes with lifestyle intervention or metformin.
      Int. Urol. Nephrol. 2002; 34: 162-163
      ,
      • Diabetes Prevention Program Research Group
      • Schade D.
      • Ma Y.
      • Fujimoto W.Y.
      • Barrett-Connor E.
      • Fowler S.
      • et al.
      The influence of age on the effects of lifestyle modification and metformin in prevention of diabetes.
      J. Gerontol. Ser. A: Biol. Sci. Med. Sci. 2006; 61: 1075-1081
      ,
      • Lindström J.
      • Peltonen M.
      • Eriksson J.G.
      • Aunola S.
      • Hmlinen H.
      • Ilanne-Parikka P.
      • et al.
      Determinants for the effectiveness of lifestyle intervention in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 857-862
      ]. The U.S. DPP showed that in the lifestyle intervention group, people aged 60–85 had a type 2 diabetes incidence of 3.3 cases per 100 persons per year, compared to 4.9 cases per 100 persons per year in those aged 45–59, and 6.3 cases per 100 persons per year in those aged 25–44 (p trend = 0.07), a trend that the authors described as borderline significant. No age-related differences could be detected in people who received treatment as usual (p = 0.71). The Finnish DPS further substantiated the U.S. DPP, showing decreasing incidence rates of type 2 diabetes in lifestyle intervention participants with increasing age over the course of the 4-year study (p = 0.039) [
      • Lindström J.
      • Peltonen M.
      • Eriksson J.G.
      • Aunola S.
      • Hmlinen H.
      • Ilanne-Parikka P.
      • et al.
      Determinants for the effectiveness of lifestyle intervention in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 857-862
      ].

      3.1.2 Body weight

      Eighteen RCTs analyzed weight change after one year of lifestyle intervention compared to treatment as usual [
      • Pimentel G.D.
      • Portero-McLellan K.C.
      • Oliveira E.P.
      • Spada A.P.
      • Oshiiwa M.
      • Zemdegs J.C.
      • et al.
      Long-term nutrition education reduces several risk factors for type 2 diabetes mellitus in Brazilians with impaired glucose tolerance.
      Nutr. Res. (New York, NY). 2010; 30: 186-190
      ,
      • Davies M.J.
      • Gray L.J.
      • Troughton J.
      • Gray A.
      • Tuomilehto J.
      • Farooqi A.
      • et al.
      A community based primary prevention programme for type 2 diabetes integrating identification and lifestyle intervention for prevention: the Let’s Prevent Diabetes cluster randomised controlled trial.
      Prev. Med. 2016; 84: 48-56
      ,

      M.J. Davies, L.J. Gray, D. Ahrabian, M. Carey, A. Farooqi, A. Gray, et al, A community-based primary prevention programme for type 2 diabetes mellitus integrating identification and lifestyle intervention for prevention: a cluster randomized controlled trial. 2017.

      ,
      • Ackermann R.T.
      • Edelstein S.L.
      • Narayan K.M.
      • Zhang P.
      • Engelgau M.M.
      • Herman W.H.
      • et al.
      Changes in health state utilities with changes in body mass in the Diabetes Prevention Program.
      Obesity (Silver Spring, Md.). 2009; 17: 2176-2181
      ,
      • Bray G.A.
      • Culbert I.W.
      • Champagne C.M.
      • Dawson L.
      • Eberhardt B.
      • Greenway F.L.
      • et al.
      The diabetes prevention program: Baseline characteristics of the randomized cohort.
      Diabetes Care. 2000; 23: 1619-1629
      ,
      • Florez H.
      • Pan Q.
      • Ackermann R.T.
      • Marrero D.G.
      • Barrett-Connor E.
      • Delahanty L.
      • et al.
      Impact of lifestyle intervention and metformin on health-related quality of life: the diabetes prevention program randomized trial.
      J. Gen. Intern. Med. 2012; 27: 1594-1601
      ,
      • Fujimoto W.Y.
      • Jablonski K.A.
      • Bray G.A.
      • Kriska A.
      • Barrett-Connor E.
      • Haffner S.
      • et al.
      Body size and shape changes and the risk of diabetes in the diabetes prevention program.
      Diabetes. 2007; 56: 1680-1685
      ,
      • Molitch M.E.
      • Fujimoto W.
      • Hamman R.F.
      • Knowler W.C.
      • Diabetes Prevention Program Research Group, N P
      The diabetes prevention program and its global implications.
      J. Am. Soc. Nephrol. 2003; 14: 103-107
      ,
      • Ratner R.E.
      • Diabetes Prevention Program Research
      An update on the Diabetes Prevention Program.
      Endocr. Pract. 2006; 12: 20-24
      ,
      • Diabetes Prevention Program Research Group
      Reduction of the incidence of type 2 diabetes with lifestyle intervention or metformin.
      Int. Urol. Nephrol. 2002; 34: 162-163
      ,
      • Diabetes Prevention Program Research Group
      • Schade D.
      • Ma Y.
      • Fujimoto W.Y.
      • Barrett-Connor E.
      • Fowler S.
      • et al.
      The influence of age on the effects of lifestyle modification and metformin in prevention of diabetes.
      J. Gerontol. Ser. A: Biol. Sci. Med. Sci. 2006; 61: 1075-1081
      ,
      • Penn L.
      • White M.
      • Oldroyd J.
      • Walker M.
      • Alberti K.G.
      • Mathers J.C.
      Prevention of type 2 diabetes in adults with impaired glucose tolerance: the European Diabetes Prevention RCT in Newcastle upon Tyne, UK.
      BMC Public Health. 2009; 9: 342
      ,
      • Eriksson J.
      • Lindstroem J.
      • Valle T.
      • Aunola S.
      • Haemaelaeinen H.
      • Ilanne-Parikka P.
      • et al.
      Prevention of type II diabetes in subjects with impaired glucose tolerance: the Diabetes Prevention Study (DPS) in Finland. Study design and 1-year interim report on the feasibility of the lifestyle intervention programme.
      Diabetologia. 1999; 42: 793-801
      ,
      • Ilanne-Parikka P.
      • Eriksson J.G.
      • Lindstroem J.
      • Peltonen M.
      • Aunola S.
      • Haemaelaeinen H.
      • et al.
      Effect of lifestyle intervention on the occurrence of metabolic syndrome and its components in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 805-807
      ,
      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Aunola S.
      • Cepaitis Z.
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      Prevention of diabetes mellitus in subjects with impaired glucose tolerance in the Finnish Diabetes Prevention Study: results from a randomized clinical trial.
      J. Am. Soc. Nephrol. 2003; 14: 108-113
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      • Lindstroem J.
      • Louheranta A.
      • Mannelin M.
      • Rastas M.
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      • et al.
      The Finnish Diabetes Prevention Study (DPS): lifestyle intervention and 3-year results on diet and physical activity.
      Diabetes Care. 2003; 26: 3230-3236
      ,
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      • Lindstroem J.
      • Eriksson J.G.
      • Valle T.T.
      • Haemaelaeinen H.
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      Prevention of type 2 diabetes mellitus by changes in lifestyle among subjects with impaired glucose tolerance.
      N. Engl. J. Med. 2001; 344: 1343-1350
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      The Finnish diabetes prevention study.
      Br. J. Nutr. 2000; 83: 137-142
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      • Aunola S.
      • Hmlinen H.
      • Ilanne-Parikka P.
      • et al.
      Determinants for the effectiveness of lifestyle intervention in the Finnish Diabetes Prevention Study.
      Diabetes Care. 2008; 31: 857-862
      ,
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      Prim. Care Diabetes. 2016; 10: 111-120
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      J. Intern. Med. 1999; 246: 105-112
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      A randomized lifestyle intervention with 5-year follow-up in subjects with impaired glucose tolerance: pronounced short-term impact but long-term adherence problems.
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      Am. J. Prev. Med. 2017; 52: 788-797
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      Diabetologia. 2006; 49: 2392-2401
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      A short message service (SMS) intervention to prevent diabetes in Chinese professional drivers with pre-diabetes: a pilot single-blinded randomized controlled trial.
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      Arch. Intern. Med. 2011; 171: 1352-1360
      ]. Due to the unexplained very high heterogeneity between study results (perhaps due to the mode of communication or intensity of lifestyle intervention), we did not conduct any meta-analyses. We performed sensitivity analyses with less and more frequent lifestyle intervention, and without Asian studies (as the populations had a lower Body Mass Index [BMI] at the beginning of the studies) but these factors did not influence the high heterogeneity.
      After one year, the majority of RCTs showed a statistically significant greater weight loss in lifestyle intervention participants compared to treatment as usual (Table 1), though differences in weight change varied substantially among the studies. For example, the 1023 participants in the lifestyle intervention group of the U.S. DPP (2049 people total) lost an average of 6.3 kg [95% CI −6.84, −5.80] compared to treatment as usual [
      • Ackermann R.T.
      • Edelstein S.L.
      • Narayan K.M.
      • Zhang P.
      • Engelgau M.M.
      • Herman W.H.
      • et al.
      Changes in health state utilities with changes in body mass in the Diabetes Prevention Program.
      Obesity (Silver Spring, Md.). 2009; 17: 2176-2181
      ]. While a British study with 750 people only showed 0.27 kg [95% CI −1.17, 0.63] greater weight loss in the lifestyle intervention group, which was not statistically significant [
      • Davies M.J.
      • Gray L.J.
      • Troughton J.
      • Gray A.
      • Tuomilehto J.
      • Farooqi A.
      • et al.
      A community based primary prevention programme for type 2 diabetes integrating identification and lifestyle intervention for prevention: the Let’s Prevent Diabetes cluster randomised controlled trial.
      Prev. Med. 2016; 84: 48-56
      ,

      M.J. Davies, L.J. Gray, D. Ahrabian, M. Carey, A. Farooqi, A. Gray, et al, A community-based primary prevention programme for type 2 diabetes mellitus integrating identification and lifestyle intervention for prevention: a cluster randomized controlled trial. 2017.

      ].
      After three years, nine RCTs analyzed weight change [
      • Bhopal R.S.
      • Douglas A.
      • Wallia S.
      • Forbes J.F.
      • Lean M.E.
      • Gill J.M.
      • et al.
      Effect of a lifestyle intervention on weight change in south Asian individuals in the UK at high risk of type 2 diabetes: a family-cluster randomised controlled trial.
      Lancet Diabetes Endocrinol. 2014; 2: 218-227
      ,
      • Davies M.J.
      • Gray L.J.
      • Troughton J.
      • Gray A.
      • Tuomilehto J.
      • Farooqi A.
      • et al.
      A community based primary prevention programme for type 2 diabetes integrating identification and lifestyle intervention for prevention: the Let’s Prevent Diabetes cluster randomised controlled trial.
      Prev. Med. 2016; 84: 48-56
      ,

      M.J. Davies, L.J. Gray, D. Ahrabian, M. Carey, A. Farooqi, A. Gray, et al, A community-based primary prevention programme for type 2 diabetes mellitus integrating identification and lifestyle intervention for prevention: a cluster randomized controlled trial. 2017.

      ,
      • Ackermann R.T.
      • Edelstein S.L.
      • Narayan K.M.
      • Zhang P.
      • Engelgau M.M.
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