Diabetes Prevention in the RealWorld: Effectiveness of PragmaticLifestyle Interventions for thePrevention of Type 2 Diabetesand of the Impact of Adherenceto Guideline RecommendationsA Systematic Review and Meta-analysisDiabetes Care 2014;37:922–933 | DOI: 10.2337/dc13-2195

OBJECTIVE

To summarize the evidence on effectiveness of translational diabetes preventionprograms, based on promoting lifestyle change to prevent type 2 diabetes in real-world settings and to examine whether adherence to international guidelinerecommendations is associated with effectiveness.

RESEARCH DESIGN AND METHODS

Bibliographic databases were searched up to July 2012. Included studies had afollow-up of ‡12 months and outcomes comparing change in body composition,glycemic control, or progression to diabetes. Lifestyle interventions aimed totranslate evidence from previous efficacy trials of diabetes prevention into real-world intervention programs. Data were combined using random-effects meta-analysis and meta-regression considering the relationship between interventioneffectiveness and adherence to guidelines.

RESULTS

Twenty-five studiesmet the inclusion criteria. The primarymeta-analysis included22 studies (24 study groups) with outcome data for weight loss at 12 months. Thepooled result of the direct pairwise meta-analysis shows that lifestyle interven-tions resulted in a mean weight loss of 2.32 kg (95%22.92 to21.72; I2 = 93.3%).Adherence to guidelines was significantly associatedwith a greater weight loss (anincrease of 0.4 kg per point increase on a 12-point guideline-adherence scale).

CONCLUSIONS

Evidence suggests that pragmatic diabetes prevention programs are effective.Effectiveness varies substantially between programs but can be improved bymaximizing guideline adherence. However, more research is needed to establishoptimal strategies for maximizing both cost-effectiveness and longer-term main-tenance of weight loss and diabetes prevention effects.

1Diabetes Research Centre, University of Leicester,Leicester, U.K.2Primary Care, University of Exeter MedicalSchool, Exeter, U.K.

Corresponding author: Alison J. Dunkley, ajd38@le.ac.uk.

Received 17 September 2013 and accepted 14January 2014.

This article contains Supplementary Data onlineat http://care.diabetesjournals.org/lookup/suppl/doi:10.2337/dc13-2195/-/DC1.

© 2014 by the American Diabetes Association.See http://creativecommons.org/licenses/by-nc-nd/3.0/ for details.

See accompanying articles, pp. 906,909, 912, 934, 943, 950, and 957.

Alison J. Dunkley,1 Danielle H. Bodicoat,1

Colin J. Greaves,2 Claire Russell,1

Thomas Yates,1 Melanie J. Davies,1 and

Kamlesh Khunti1

922 Diabetes Care Volume 37, April 2014

TYPE2DIABETES

PREV

ENTION

A major opportunity exists to drasti-cally reduce the incidence of type 2diabetes, a disease that has a huge im-pact on patients and health care sys-tems worldwide. Large, high-qualityclinical trials (1–3) show that relativelymodest changes in diet and physicalactivity reduce the incidence of type 2diabetes by .50% for people with im-paired glucose regulation. Impairedglucose regulation is an intermediatecondition between normal glucose reg-ulation and type 2 diabetes, which con-fers an increased risk of progression totype 2 diabetes (4). Indeed, within-trialdata show that the rate of progressionto type 2 diabetes at 7 years of follow-upwas reduced to almost zero for peoplewho had succeeded in making five mod-est lifestyle changes (2). The main driv-ers of diabetes prevention appear to beweight loss and physical activity (5,6).However, a substantial challenge re-mains in translating these findings intoroutine clinical practice. The intensiveand prohibitively expensive interven-tions used in clinical trials, to ensurelifestyle change, need to be translatedinto practical affordable interventionsthat are deliverable in real-worldhealth care systems and which, never-theless, retain a reasonable degree ofeffectiveness (7).Since the publication of the original

diabetes prevention clinical trials be-tween 1996 and 2001, a number oftranslational or “real-world” diabetesprevention programs (8,9) have aimedto translate the evidence (1,10–12). Ameta-analysis of the evidence on trans-lational interventions was published in2010 (9), although this review excluded15 studies that were conducted in non–health care settings. A more recentmeta-analysis was published in 2012(13). However, the authors only focusedon translation of evidence from the U.S.Diabetes Prevention Program and alsoincluded studies where up to half ofthe population already had diabetes.Other systematic reviews of diabetesprevention interventions have eithernot included a meta-analysis (6,8,14–17) or have not focused on translationalstudies (3,6,15,16,18–22). Overall, thesystematic reviews conducted to dateindicate that real-world diabetes pre-vention programs vary widely in theireffectiveness, although most producelower levels of weight loss than the

more intensive interventions used inthe clinical efficacy trials (9). Explainingthis variation is important. If we canidentify the components of lifestyle in-terventions that are reliably associatedwith increased effectiveness, this willinform the design of more efficient(cost-effective) diabetes preventionprograms.

Recently published evidence-basedguidelines (23,24) make distinct recom-mendations about which interventioncomponents should be included to max-imize the effectiveness of lifestyle inter-ventions for diabetes prevention. Suchrecommendations include the use ofgroup-based interventions to minimizecost and the use of specific behavior-change strategies that are associatedwith increased effectiveness. These rec-ommendations come from systematicreviews of the wider literature on sup-porting changes in diet and physical ac-tivity in a range of populations (25,26).Lifestyle interventions for diabetes pre-vention vary in their content; however,whether closer adherence to the guide-line recommendations might improvethe performance of real-world diabetesprevention interventions remains un-clear. To consolidate the evidence, weundertook a systematic review of stud-ies considering the effectiveness oftranslational interventions for preven-tion of type 2 diabetes in high-riskpopulations. The primary aim was to con-duct a meta-analysis of the effectivenessof pragmatic interventions on weightloss and conduct a meta-regression toexamine whether closer adherence toguideline recommendations for diabetesprevention improves the effectiveness ofreal-world interventions. If sufficient datawere available, a secondary aim was toconsider other diabetes risk factors usingsimilar methods.

RESEARCH DESIGN AND METHODS

Search Strategy and Study SelectionWe included experimental and observa-tional studies that considered the effec-tiveness of a lifestyle intervention (dietor exercise) alone or compared withcontrol, where the stated aim of the in-tervention was diabetes risk reductionor prevention of type 2 diabetes, andwhere the focus of the study was totranslate evidence from previous diabe-tes efficacy trials into routine healthcare or a community setting. For studies

to be eligible for inclusion, we requiredthem to include adults ($18 years old)identified as being at high risk of devel-oping type 2 diabetes (for example,obese, sedentary lifestyle, family historyof diabetes, older age, metabolic syn-drome, impaired glucose regulation,prediabetes, or elevated diabetes riskscore) (24), have a minimum follow-upof 52 weeks, and have an outcome re-lating to diabetes risk, as measured by achange in body composition or a changein glycemic control or report progres-sion to diabetes (incidence or preva-lence). The focus of the review wasprimary prevention; therefore, we ex-cluded trials where .10% of the popu-lation had established diabetes. Weincluded only studies published in theEnglish language and as full-lengtharticles.

We searched Embase, MEDLINE, andthe Cochrane Library (Issue 7, 2012),using a combination of MeSH termsand keywords that were tailored to in-dividual bibliographic databases. We re-stricted searches to articles publishedafter January 1998; the starting pointof 1998 was chosen to facilitate theidentification of studies that were in-formed by or translating evidence fromprevious diabetes prevention efficacytrials (1,10–12). In order to avoid miss-ing papers, the final search strategy in-cluded only terms related to theintervention and the study design. Anexample search strategy (MEDLINE) isoutlined in Supplementary Table 1.We combined the results of an initialsearch and an updated supplementarysearch, which together identified papersup to the end of July 2012.

Two reviewers independently as-sessed abstracts and titles for eligibilityand retrieved potentially relevant ar-ticles, with differences resolved by athird reviewer where necessary. Wherestudies appeared to meet all the inclu-sion criteria but data were incomplete,we contacted authors for additionaldata or clarification. In an attempt toidentify further papers not identifiedthrough electronic searching, we exam-ined the reference lists of included pa-pers and relevant reviews.

Data Extraction and QualityAssessmentData were extracted by one reviewer,and a second reviewer subsequently

care.diabetesjournals.org Dunkley and Associates 923

checked for consistency. We extracteddata on sample size, population demo-graphics, intervention details, and lengthof follow-up. Where available, we re-corded outcome data for the meanchange from baseline to 12 months’follow-up for the following outcomes:weight, BMI, waist circumference, fastingglucose, 2-h glucose, glycated hemo-globin (HbA1c), total cholesterol, LDL cho-lesterol, HDL cholesterol, triglycerides,systolic blood pressure (BP), and diastolicBP. Incidence of type 2 diabetes wasalso recorded. We retrieved all papersrelating to a particular study, includingthose on design and methodology (ifreported separately), and any Supple-mentary Data.We assessed the quality of selected

studies according to the U.K.’s NationalInstitute for Health and Clinical Excel-lence (NICE) quality appraisal checklistfor quantitative intervention studies(27). The checklist includes criteria forassessing the internal and external val-idity of experimental and observationalquantitative studies (randomized con-trolled trials [RCTs], nonrandomized con-trolled trials, and before and afterstudies) and allows assignment of an over-all quality grade (categories ++, +, or2).

Coding of Intervention ContentWe coded intervention content (Supple-mentary Tables 1 and 3) in relation tothe recommendations for lifestyle inter-ventions for the prevention of diabetesprovided by both the IMAGE project(Development and Implementationof a European Guideline and TrainingStandards for Diabetes prevention)(23) and NICE (24). Where a study inter-vention was inadequately described, werequested further details from the au-thors. If available information was insuf-ficient to allow coding, we coded data asmissing; where an intervention ap-peared to be well described but a par-ticular component (e.g., engaging socialsupport) was not mentioned or couldnot be implied from other text, we as-sumed that the component was notused. In the analysis, we assumed thatmissing values indicated that the guide-line criterion was not met.

Data Synthesis and AnalysisWe converted all values reported in im-perial units into metric units. Capillaryblood glucose values were converted

to plasma equivalent values (28). If stud-ies did not directly report the mean SD,for change from baseline to 12 monthsfor the outcomes of interest, they werecalculated. We calculated the meanchange by subtracting the baselinemean value from the mean at 12months. We calculated the SD from re-ported P values or CI, as recommendedby the Cochrane Collaboration (29).Where data were insufficient, to allowcalculation of the SD, we imputed valuesfor each outcome based on the correla-tion estimates from those studies thatreported; for weight, the correlationused in these imputations was 0.95(30–34).

For the primary outcome of interest(weight), we conducted direct pairwisecomparison meta-analyses to examinethe effect size (change from baselineto 12 months) where data were avail-able. Only intervention arms were in-cluded in the meta-analysis. This wasbecause we were interested in whetheradherence to guidelines improvedweight loss; therefore, only arms inwhich people received an interventionwere applicable. Meta-regression wasused to assess the relationship betweenweight change at 12 months and thetotal IMAGE guidance score and the to-tal NICE guidance score, as explanatoryvariables, in separate univariate analy-ses. We performed further metaregres-sion with the individual guidelinecomponents as the explanatory varia-bles where at least three studies fellinto each category. We conducted sim-ilar analyses for the secondary out-comes of interest; however, as theseoutcomes were reported in fewerstudies and to avoid multiple testing,metaregression of individual guidelinecomponents against secondary out-comes was not performed. We per-formed sensitivity analyses for theprimary outcome, weight, where miss-ing guideline data were treated as un-known and a total guidance scorewas not given for those studies andwhere we restricted the analysis toRCTs only.

We assessed publication bias using theEgger test and heterogeneity using the I2

statistic. Due to high levels of heteroge-neity, we used random-effects modelsthroughout to calculate effect sizes. Weperformed all analyses in Stata version12.1 (StataCorp, College Station, TX).

RESULTS

Identification of StudiesResults relating to identification and se-lection of eligible trials are summarizedin Fig. 1. Searches yielded 6,326 cita-tions, and 3,872 unique titles or ab-stracts were screened for eligibility.After full text retrieval of 114 potentiallyrelevant papers, 20 additional paperswere identified from reference lists,making a total of 134. Authors for 13studies were then contacted in orderto clarify eligibility criteria or for addi-tional outcome data. Replies were re-ceived for 12 studies, 10 of which weresubsequently included in the 25 studies(30–54) (35 articles [30–64]) that metthe review criteria.

Summary of Included StudiesThe 25 studies (30–54) included in thesystematic review are summarized inTable 1. Study interventions included ei-ther dietary intervention or physical ac-tivity intervention or both. Standard/brief advice on diet and/or exercisewas considered to be comparable withusual care and not judged to be an activeintervention. One study focused solelyon the effectiveness of physical activityintervention (54), 1 combined dietaryintervention and a supervised exerciseprogram (44), and 23 considered the ef-fectiveness of combined dietary andphysical activity intervention. Eleven ofthe studies were RCTs, 11 were beforeand after studies, and the remainingstudies included a matched cohort, aprospective cohort, and a nonrandom-ized controlled trial. All papers werepublished within the last 10 years.

Studies were conducted in the U.S.(n = 11), Australia (n = 2), Europe (n =11), and Japan (n = 1); however, ethnic-ity was poorly reported. The number ofpeople who were enrolled into the in-tervention arm in individual studiesranged from 8 to .2,700, with 22 stud-ies including at least 50 participants. Thecriteria used, alone or in combination,to identify high risk included elevatedBMI; elevated diabetes risk score (FinnishDiabetes Risk Score [FINDRISC] [65],American Diabetes Association [ADA][66]); raised random, fasting, or 2-h glu-cose (finger prick or venous sample);older age; ethnicity; family history ofdiabetes; and previous medical historyof cardiovascular disease, polycysticovary syndrome, gestational diabetes

924 Systematic Review of Pragmatic Diabetes Prevention Diabetes Care Volume 37, April 2014

mellitus, metabolic syndrome, or ele-vated BP or lipids. Length of follow-upranged from 12 months to ;4 years.The mean age and BMI of participantsranged from 38 to 65 years and 25 to37 kg/m2, respectively, and the propor-tion of males ranged from 7 to 66%.Outcome data for change in weight

were available for 24 of 25 studies (notCosta [39]); 22 of 25 studies reportedweight at 12 months (SupplementaryTable 4). Additional 12-month data re-ported for 23 studies (Supplementary Ta-bles 1 and 5) included change in BMI (18studies), waist size (16), fasting glucose(15), 2-h glucose (10) HbA1c (7), total cho-lesterol (13), LDL (7), HDL (12), triglycer-ides (10), systolic BP (13), diastolic BP(11), and the incidence of diabetes after12 months (8). Outcome data for changein physical activity and diet were poorlyreported. Overall, considerable hetero-geneity was evident between studies inrelation to several key characteristicsincluding the setting, population, crite-ria used to identify diabetes risk, inter-ventions, and follow-up.

Study QualityA breakdown of study quality is pre-sented in Supplementary Table 6. Most

studies achieved a high-quality gradingfor internal validity (19 of 25). However,details relating to the source/eligiblepopulation and area and the selectedparticipants were less well reported;only 11 studies achieved a high-qualityscore for external validity.

Scoring of Intervention ContentDetails of coding scores for study inter-ventions are presented in Supple-mentary Table 3. Fourteen of the 25intervention groups included in themain meta-analysis attained an overallscore of $9 out of a possible 12 in re-lation to meeting NICE guideline recom-mendations; 19 scored $7. For IMAGEguideline recommendations, an overallscore of $5 out of a possible 6 wasachieved by 12 study groups.

Meta-analysisTwenty-two studies involving 5,500 par-ticipants (estimated 43% male) were in-cluded in the meta-analysis for meanweight change at 12 months. One studywas excluded from the primary meta-analysis, as weight change was not re-corded as a study outcome (39), and twostudies were excluded from all analyses,as they only reported 18-month data(45,53). Two studies included in the

meta-analysis had two interventionarms (43,54), meaning that 24 studygroups were analyzed.

The pooled result of the direct pairwisemeta-analysis (Fig. 2) shows that lifestyleinterventions resulted in a mean weightloss of 2.32 kg (95% CI 22.92 to 21.72;I2 = 93.3%). Supplementary Figs. 1 and 2show the metaregression results for theNICE and IMAGE guidelines for weight,respectively. Greater adherence to guide-line recommendations was significantlyassociated with greater weight loss forboth sets of guidelines (Table 2). Adher-ence to individual guideline elements alsotended to result in greater weight loss,some of which were statistically signifi-cant (Table 2). Sensitivity analyses with-out imputed data are also shown in Table2. This showed that, where data werecomplete, the effect sizes were generallylarger for bothNICE and IMAGE guidance:20.52 kg per point increase on the 12-point adherence scale (95% CI 20.95 to20.10) and 20.77 kg per point increaseon the 6-point adherence scale (95% CI21.28 to20.26), respectively.

None of the study level covariates(proportion of males, mean age, propor-tion of white European ethnicity) weresignificantly associated with the mean

Figure 1—Flowchart of selection of studies from search to final inclusion. DM, diabetes mellitus; T2DM, type 2 diabetes mellitus.

care.diabetesjournals.org Dunkley and Associates 925

Table

1—Characteristicsofstudiesincludedin

thesy

stematicreview

Firstauthor

andyear

Studydesign

Studynam

eDefi

nitionof

highrisk

ofT2D

Focusof

interven

tions

No.recruited

overall(and

bygroup)

No.of

study

groups

Follow-up

(months)

Setting

Country

Ethnicity(%

)Age,

mean

M (%)

BMI

(kg/m

2),

mean

Absetz2007

(and2009)

Before

andafter

GOAL

Aged50

–65

years;

anyrisk

factor

from

obesity,

↑BP,

↑PG,

↑lipids;FINDRISC

score

$12

Lifestyle(diet

andexercise)

352

112

and36

Prim

ary

care

Finland

N/R

58(F);

59(M

)25

33(F);

32(M

)

Ackerman

n2008(and

2011)

RCT

DEP

LOY

BMI$24

kg/m

2

andADAdiabetes

risk

score

$10

,

CBGrandom

(110

–199mg/dL)

orfasting(100–

199mg/dL)

Lifestyle(diet

andexercise)

922

12Community

(YMCA)

U.S.

82%white,

3%Hispan

ic,

12%Af-Am,

5%other

5845

31

Alm

eida2010

Matched

cohort

KPCO

ExistingIFG

(110

–125mg/dL)

iden

tified

from

med

icalrecords

Lifestyle(diet

andexercise)

1,640

(1,520

data

available)

212

Integrated

healthcare

organization

U.S.

N/R

5547

30

Boltri2008

Before

andafter

DPP

infaith-based

community

ADAdiabetes

risk

score

$10,

CBGfasting

(100

–125mg/dL)

Lifestyle(diet

andsupervised

exercise)

81

12Community

(church)

U.S.

Af-Am

community

52*

42*

32

Costa2012

Prospective

cohort

DE-PLAN

Spain

FINDRISCscore

$14

or2-h

OGTT

($7.8

and,11

.1mmol/L)

Lifestyle(diet

andexercise)

552(219

+333)

2Med

ian4.2

years

Prim

arycare

Spain

White

European

6232

31

Davis-Smith

2007

Before

andafter

N/R

ADAdiabetes

risk

score

$10

,CBGfasting

(100

–125mg/dL)

Lifestyle

(dietandexercise)

111

12Community

(church)

U.S.

Af-Am

community

N/R

2736

†

Faridi2

010

Nonrandomized

controlledtrial

PRED

ICT

$1risk

factor

from

BMI

$25

kg/m

2,

FHdiabetes,

gestational

diabetes

mellitus

Lifestyle

(dietandexercise)

146

212

Community

(church)

U.S.

100%Af-Am

N/R

3233

Gilis- Januszew

ska

2011

Before

andafter

DE-PLAN

Poland

FINDRISC

score

$14

Lifestyle

(dietand

exercise,

optional

supervised

sessions)

175

112

Prim

arycare

Poland

NR

NR

2232

Katula20

11

RCT

HELPPD

BMI$

25,

40kg/m

2

andCBGrandom,

FPG(95–125mg/dL)

Lifestyle(diet

andexercise)

301(151

+150)

212

Community

various

venues

U.S.

74%white,

25%Af-Am,

1%other

5843

33

Con

tinuedon

p.92

7

926 Systematic Review of Pragmatic Diabetes Prevention Diabetes Care Volume 37, April 2014

Table

1—Continued

Firstauthor

andyear

Studydesign

Studynam

eDefi

nitionof

highrisk

ofT2D

Focusof

interven

tions

No.recruited

overall(and

bygroup)

No.of

study

groups

Follow-up

(months)

Setting

Country

Ethnicity(%

)Age,

mean

M (%)

BMI

(kg/m

2),

mean

Kram

er20

09

Before

andafter

GLB

2005–

2008

BMI$25

kg/m

2

andmetabolic

syndromeor

CBGfasting

(100

–125mg/dL)

Lifestyle(diet

andexercise)

421

12Prim

arycare

and

university-

based

support

center

U.S.

100%white

5721

35

Kram

er20

12

Before

andafter

GLB

2009

Fastingglucose

100–125mg/dl

Lifestyle(diet

andexercise)

60(31+29)

212

Community

(YMCA)an

duniversity

U.S.

90%Cau

casian

5535

;36

Kulzer

2009

RCT

PRED

IAS

FINDRISCscore

$10

or

assessed

as↑riskdiabetes

byprimary

care

physician

Lifestyle(diet

andexercise)

182(91+91)

212

Outpatient

setting

Germany

N/R

5657

32

Laatikainen

2007(and

2012)

Before

andafter

GGTstudy

FINDRISCscore

$12

Lifestyle(diet

andexercise)

311

112

Prim

arycare

Australia

N/R

5728

34

Makrilakis20

10

Before

andafter

DE-PLAN

Greece

FINDRISCscore

$15

Lifestyle(diet

andexercise)

191

112

Prim

arycare,

workplace

Greece

NR

5640

32

Men

sink2003

(and2003);

(Roumen

2008

and2011)

RCT

SLIM

study

Aged.40

years

andFH

diabetes

orBMI$

25kg/m

2,

IGT(OGTT

2-h

G$7.8and,12.5)

andFPG,7.8mmol/L

Lifestyle(dietan

dsupervised

exercise)

114(55+59)

212,24,36

,48 (Roumen

)

Unclear

Netherlands

WhiteCau

casian

5756

30

Nilsen

2011

RCT

N/R

FINDRISCscore

$9

Lifestyle(diet

andexercise)

213(104

+109)

218

Prim

arycare

Norw

ayNR

4750

37

Ocken

e2012

RCT

Lawrence

LatinoDPP

BMI$24

kg/m

2,

.30%increased

likelihoodof

diabetes

over

next7.5yearsfrom

validated

risk

algorithm

Lifestyle(diet

andexercise)

312(150

+162)

212

Community,

family

health

center

U.S.

60%Dominican

,40

%Pu

erto

Rican

5226

34

Parikh

2010

RCT

Project

HEED

BMI$25

kg/m

2

andprediabetes

(CBGfasting

,126mg/dL,

andIGTon2-h

CBGfollowing75

-gglucose)

Lifestyle(diet

andexercise)

99(50+49)

212

Various

community

venues

U.S.

89%Hispan

ic,9%

Af-Am

4815

32

Con

tinuedon

p.92

8

care.diabetesjournals.org Dunkley and Associates 927

Table

1—Continued

Firstauthor

andyear

Studydesign

Studynam

eDefi

nitionof

highrisk

ofT2D

Focusof

interven

tions

No.recruited

overall(and

bygroup)

No.of

study

groups

Follow-up

(months)

Setting

Country

Ethnicity(%

)Age,

mean

M (%)

BMI

(kg/m

2),

mean

Payne2008

Before

andafter

N/R

Aged$45

or

aged

$35

years;

Aboriginal,Torres

StraitIslanders,

PacificIslanders,

Indian,

Chinese;

andBMI

$30

kg/m

2an

d/or

↑BP;

existingCVD,

PCOS,gestational

diabetes

mellitus;

1st-degree

FHdiabetes;IGTorIFG

Lifestyle

(diet

andexercise

program

)

122(62+60)

212

Outpatient

facility

Australia

N/R

5322

35

Penn2009

RCT

N/R

BMI.25

kg/m

2an

daged

.40

years,

IGT(OGTT

2-hG

$7.8and

,11

.1mmol/L)

Lifestyle(diet

andexercise)

102(51+51)

212

and3.1

years

mean

Outpatient

setting

U.K.

N/R

5740

34

Ruggiero

2011

Before

andafter

N/R

BMI$24.9

kg/m

2Lifestyle(diet&

exercise)

691

12Various

community

venues

U.S.

Hispan

ic38

731

Saaristo

2010

(Rautio2011

and2012)

Before

andafter

FIN-D2D

FINDRISCscore

$15

,IFG,IGT,

CVDeven

t,or

gestational

diabetes

mellitus

Lifestyle(diet

andexercise)

2,79

81

12Prim

arycare

Finland

NR

5449

~31

Sakane2011

RCT

N/R

IGTiden

tified

asfollows:IFG$5.6

and,7.0mmol/L,

random

PG($

7.8,

11.1

mmol/Lwithin

2hofmeal)or

($6.1and,7.8

at$2haftermeal)

Lifestyle

(dietandexercise)

296(146

+150)

212

and36

Various:

primarycare,

workplace,

collaborative

center

Japan

N/R

5151

25

Vermunt20

12

(and2011)

RCT

N/R

FINDRISCscore

$13

Lifestyle(diet

andexercise)

925(479

+446)

218,30

Prim

arycare

Netherlands

NR

NR

NR

~29

Yates2009

(and2011)

RCT

PREP

ARE

BMI$25

kg/m

2

(23forSA

s),

screen

ed

detectedIGT

Lifestyle

(exercise)

98(33+31

+34)

312,24

Outpatient

setting

U.K.

75%white,†24

%SA

,1%black

65†

66†

29.2†

Payne20

08randomlyallocatedto

twoexercise

groups,butmostresultsarepresentedoverall.2-hG,2-h

glucose;A

f-Am,A

frican

American

;CBG,capillarybloodglucose;C

VD,cardiovasculardisease;D

E-PLAN,

Diabetes

inEuropePreven

tionUsingLifestyle,Ph

ysicalActivityandNutritionalInterven

tion;D

EPLO

Y,Diabetes

EducationandPreven

tionwithaLifestyleInterven

tionOffered

attheYM

CA;F,fem

ale;FH

,fam

ilyhistory;FIN-D2D

,FinnishNationalDiabetes

Preven

tionProgram

;FPG

,fastingplasm

aglucose;G

GT,Greater

Green

Triangle;GLB,G

roupLifestyleBalance;G

OAL,GoodAgeinginLahtiRegion;H

EED,H

elpEducate

toElim

inateDiabetes;H

ELPPD

,HealthyLivingPartnershipsto

Preven

tDiabetes;IFG

,impairedfastingglucose;IGT,im

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928 Systematic Review of Pragmatic Diabetes Prevention Diabetes Care Volume 37, April 2014

difference in weight change. Sensitivityanalysis, restricted to RCTs only, indi-cated a mean weight change (22.7 kg[95% CI 24.2 to 21.2]) that is similar tothe overall result. Additional analysis

comparing the difference in weight lostbetween the treatment and controlarms, for RCTs only, suggests that onaverage the intervention arm lost anextra 21.93 kg (95% CI23.10 to20.76;

P = 0.001). Furthermore, sensitivity anal-yses that included studies scoring ++ forexternal validity demonstrated a slightlygreater weight loss in higher-qualitystudies (23.1 kg [95% CI 24.6 to

Table 2—Meta-regression results for weight change from baseline to 12 monthsExplanatory variable No. of studies No. of participants Effect (95% CI), kg P

NICE (continuous) 24 5,500 20.37 (20.64 to 20.11) 0.008

NICE without imputation (continuous) 17 4,885 20.52 (20.95 to 20.10) 0.020

IMAGE (continuous) 24 5,500 20.56 (20.96 to 20.17) 0.008

IMAGE without imputation (continuous) 18 4,942 20.77 (21.28 to 20.26) 0.006

IMAGE B (continuous) 24 5,500 20.61 (20.99 to 20.22) 0.004

IMAGE B without imputation (continuous) 18 4,942 20.78 (21.26 to 20.29) 0.004

Engage social support (yes vs. no) 24 5,500 21.58 (23.06 to 0.10) 0.037

No. of contacts (frequency) 23 5,417 20.09 (20.13 to 20.05) ,0.001

Contact time (h) 23 5,147 20.15 (20.21 to 20.08) ,0.001

$16 h of contact time (yes vs. no) 23 5,147 22.20 (23.61 to 20.79) 0.004

Self-regulatory techniques (yes vs. no) 24 5,500 21.17 (23.00 to 0.66) 0.200

Empathy-building approach (yes vs. no) 24 5,500 0.86 (20.71 to 2.43) 0.269

Spread sessions over 9–18 months (yes vs. no) 24 5,500 21.62 (23.07 to 20.18) 0.029

Motivation (yes vs. no) 24 5,500 21.49 (23.05 to 0.07) 0.060

Gradual building of confidence (yes vs. no) 24 5,500 20.58 (22.24 to 1.08) 0.477

Fidelity (yes vs. no) 24 5,500 20.79 (22.59 to 1.02) 0.377

Additional physical activity sessions (yes vs. no) 24 5,500 20.53 (22.62 to 1.56) 0.604

Figure 2—Forest plot showingmeanweight change in each study and the overall pooled estimate. Boxes and horizontal lines representmean weightchange and 95% CI for each study. Size of box is proportional to weight of that study result. Diamonds represent the 95% CI for pooled estimates ofeffect and are centered on pooled mean weight change. PREPARE, Pre-diabetes Risk Education and Physical Activity Recommendation andEncouragement.

care.diabetesjournals.org Dunkley and Associates 929

21.6]). Additionally, there was very lim-ited evidence of publication bias (P =0.05, Egger test).All other outcomes showed an im-

provement at 12 months (Supplemen-tary Table 7), but not all of thesereached statistical significance. Supple-mentary Table 8 shows the effect of ad-herence to NICE and IMAGE guidelineson the other outcomes. For both NICE andIMAGE guidelines, respectively, greateradherence resulted in better outcomesfor waist circumference (20.52 cm, P =0.007; 20.80 cm, P = 0.001) and tri-glycerides (20.03 mmol/L, P = 0.016;20.04 mmol/L, 0.023). For BMI, the im-provements were only significant for ad-herence to NICE guidelines (20.12 kg/m2,P = 0.028). There was no effect on any ofthe other outcomes. Across the eightstudies that reported incident diabetes,the pooled incidence rate was 34 casesper 1,000 person-years (95% CI 22–56),which gives the number needed to treatas 29.

CONCLUSIONS

The 22 translational diabetes preven-tion programs included in our meta-analysis significantly reduced weight intheir intervention arms by amean 2.3 kgat 12 months of follow-up. Where datawere available, we found significant re-ductions in other diabetes and cardio-vascular risk factors, including bloodglucose, BP, and some cholesterolmeasures. Adherence to guideline rec-ommendations on intervention contentand delivery was significantly associatedwith a greater weight loss such that, foreach 1-point increase on the 12-pointscale for adherence to NICE recommen-dations an additional 0.4 kg (P = 0.008)of weight loss was achieved; further-more, for waist size a significant reduc-tion of 0.5 cm was achieved for eachpoint increase. The pooled diabetes in-cidence rate was 34/1,000 person-years(number needed to treat: 29). Outcomedata on changes in the key lifestyle be-havior targets (physical activity and diet)were poorly reported.

Relationship With Other LiteratureThe mean level of weight loss achievedwas approximately one-half to one-thirdof the levels reported at the same timepoint within the intervention arms ofclinical efficacy trials such as the U.S.Diabetes Prevention Program [DPP]

(;6.7 kg) and the Finnish Diabetes Pre-vention Study [DPS] (;4.2 kg) (1,10).This is consistent with the findings of ameta-analytic systematic review pub-lished in 2010 by Cardona-Morrellet al. (9), which identified a mean netweight loss after 12 months of 1.82 kg(95% CI 22.7 to 20.99). Cardona-Morrell et al. interpreted the lower levelof weight loss and a lack of significantdifferences in fasting plasma glucoseand 2-h glucose as meaning that the in-terventions “appear to be of limitedclinical benefit.” Our view is that, de-spite the drop-off in intervention effec-tiveness in translational studies, thelevel of weight loss found in our analysisis still likely to have a clinically meaning-ful effect on diabetes incidence. This isbased on data from the U.S. DPP study,which show that each kilogram of meanweight loss is associated with a reduc-tion of;16% in future diabetes incidence(5). Furthermore, a recent meta-analysis,which included studies without an in-tervention in order to look at natural di-abetes progression rates in high-riskindividuals, found progression rates todiabetes from impaired fasting glucose,impaired glucose tolerance, and bothwere 47, 56, and 76 per 1,000 person-years, respectively (67). The rate of 34per 1,000 person-years that we foundsuggests that the real-world lifestyle in-terventions studied here did lower dia-betes progression rates.

For our review, the mean proportionof weight lost at 12 months’ follow-upwas 22.6%. This amount was slightlylower than was demonstrated by a re-cent meta-analysis conducted by Aliet al. (13), which considered transla-tional studies aimed at populationswith existing diabetes (#50%) or athigh future risk. They found a meanweight loss of 24.1% (95% CI 25.9 to22.4) after at least 9 months of follow-up (13). This difference may in part bedue to a lower mean BMI at baselinefor studies included in our review,compared with the Ali et al. review(range 25–36 kg/m2 and 31–40 kg/m2,respectively) and a slightly longerfollow-up period (12 months vs. $9).Additionally, their review focused oninterventions based only on the U.S.DPP, where we considered a broaderset of interventions.

Changes in the four key dietary andphysical activity targets (#30% energy

from fat, #10% energy from saturatedfat, fiber $15 g/1,000 kcal, $30 minmoderate physical activity daily) havealso been shown to have independenteffects on diabetes risk reduction, irre-spective of weight loss (5). However,few of the studies that we examinedprovided data on dietary intake or phys-ical activity, so we cannot be surewhether diabetes prevention in thesestudies is driven by increased physicalactivity, dietary change, or both.

The strong association between in-creased weight loss and increased ad-herence to guideline recommendationsis of particular interest.Where completedata were available, the coefficientswere larger: 20.52 kg per point increase(95% CI 20.95 to 20.10) for adherenceto NICE guidance on a 12-point scaleand 20.77 kg per point increase (95%CI21.28 to20.26) for adherence to IM-AGE guidance on a 6-point scale. Thismay reflect a reduction in the statisticalnoise caused by missing data, or it mayreflect the fact that studies that had astronger behavioral science input weremore likely to report the interventioncontent in detail (and were also morelikely to be effective). Overall, thesedata suggest that a high proportion ofthe variation in weight loss could be ex-plained by variations in intervention de-sign. The implication is that a designbased on guideline recommendationsshould lead to performance at the higherend of the range ($4 kg).

Strengths and LimitationsThis study is novel in that it provides anupdated meta-analysis of a global set oflifestyle interventions for diabetes pre-vention. Our study used comprehensivesearch criteria and focused on establish-ing the utility of pragmatic attempts toachieve diabetes prevention in real-world service delivery settings. It alsoprovides novel data that appear to vali-date the usefulness of recent guideline-based recommendations on the contentof lifestyle interventions for diabetesprevention.

The study is limited in that there wereinsufficient data to analyze outcomesbeyond 12 months; our findings may nottranslate into long-term therapeutic valuedue to uncertainty around sustainingoutcomes, such as weight loss, in thelonger term (68). Furthermore, results inindividual studies were not always

930 Systematic Review of Pragmatic Diabetes Prevention Diabetes Care Volume 37, April 2014

reported on an intention-to-treat basis,leading to a likely overestimation of effectsizes. Assuming no change in weight forthose with missing data, sensitivity anal-yses that we conducted suggest thatweight loss could be up to 0.5 kg less inpractice than the figures reported in thestudies.Due to the nature of pragmatic imple-

mentation studies, which include anumber of uncontrolled studies, ouranalysis was restricted to interventionarms only; however, sensitivity analysis,restricted to RCTs only, indicated amean weight change (22.7 kg [95% CI24.2 to 21.2]) that is similar to theoverall result. These findings suggestthat the estimate based on interventionarms only is likely to be robust.

Implications for PracticeOur review suggests that pragmatic life-style interventions are effective at pro-moting weight loss and could potentiallylead to a reduced risk of developingdiabetes and cardiovascular disease inthe future. However, the difficulties intranslating this evidence into practiceand in delivering guideline-based in-terventions need to be overcome. Theability to implement these findings inpractice may be further hampered by alack of resource for service provision, thedesign of efficient risk identification sys-tems, and engagement of politicians andhealth care organizations in funding na-tional diabetes prevention programs;diabetes prevention strategies requiresubstantial up-front investment to accruelonger-term benefits (7).

Future DirectionsMore research is needed to examinethe longer-term effectiveness andcost-effectiveness of pragmatic lifestyleinterventions for diabetes prevention,including diabetes incidence as well asweight loss outcomes. The practicalvalue of diabetes prevention interven-tions would be much clearer if we haddata on longer-term outcomes. Re-search is also needed to identify therole of different types of physical activ-ity and dietary changes (6,69) and onways to increase effectiveness withoutincreasing cost. Possible approachesmight include the use of larger group sizesand substitution or supplementationof intervention techniques using self-delivered formats (e.g., Internet, smartphone, or workbook) (70).

SummaryOverall, the interventions were effec-tive, but there was wide variation ineffectiveness. Adherence to interna-tional guidelines on intervention con-tent and delivery explained much ofthe variance in effectiveness, implyingthat effectiveness could be improvedby maximizing guideline adherence.However, more research is needed toestablish optimal strategies for maxi-mizing both cost-effectiveness andlonger-term maintenance of the life-style changes that these programs canachieve.

Acknowledgments. The authors specificallythank the following people who contributedto the conduct of the study: Lauren Cooper,Janette Camosso-Stefinovic, Navneet Aujla, andLaura Gray (all from the University of Leicester).The authors thank the following people forresponding to requests for additional informa-tion or data from the studies they were involvedin: Ellen Blaak (Mensink et al.), John Boltri,Bernardo Costa, Aleksandra Gilis-Januszewska,David L. Katz (Faridi et al.), Marie-France Langlois(Bouchard/Gagnon et al.), Euny C. Lee (Parikh),Kathleen McTigue, Vegard Nilsen, Linda Penn,David Simmons, and Paulien Vermunt.Funding. This project was supported by theNational Institute for Health Research (NIHR) Col-laboration for Leadership in Applied Health Re-search and Care–Leicestershire, Northamptonshireand Rutland, the University of Leicester ClinicalTrials Unit, and the NIHR Leicester-LoughboroughDiet, Lifestyle and Physical Activity Biomedical Re-search Unit. C.J.G.’s time was partly supported bythe NIHR (Career Development Fellowship CDF-2012-05-259).

This report is independent research, and theviews expressed in this publication are those ofthe author(s) and not necessarily those of theNational Health Service, the NIHR, or the De-partment of Health. No funding bodies had anyrole in study design, data collection and analy-sis, decision to publish, or preparation of themanuscript.Duality of Interest. C.J.G., T.Y., M.J.D., and K.K.were involved in the development of the NICEguidelines on diabetes prevention, and C.J.G.was involved with development of the IMAGEguidelines. C.J.G. in the last 3 years has receivedpayment from 1) Weight Watchers to make apresentation to some of their U.K. staff, sum-marizing evidence on weight-loss interven-tions, the health/economic consequences ofweight loss, and the content of current NICEguidance; 2) Stanford Burgess Health for con-sultancy on the development of a Web site tosupport diabetes prevention; and 3) NovartisPharma Service, Inc., for delivery of a work-shop on supporting behavior change at theMiddle East Summit on Cardiovascular Man-agement in October 2011. No other potentialconflicts of interest relevant to this articlewere reported.

Author Contributions. A.J.D. conceived theidea for the review, developed the searchstrategy, selected and retrieved relevant pa-pers, made the final decisions regarding in-clusion/exclusion of all papers, designed thedata extraction tool, carried out extraction/checking of data and quality assessments, andwrote the manuscript. D.H.B. conducted themeta-analyses and meta-regression and wrotethe manuscript. C.J.G. conceived the idea forthe review, coded interventions for adherenceto guidelines, and wrote the manuscript. C.R.selected and retrieved relevant papers, carriedout extraction/checking of data and qualityassessments, and reviewed and edited themanuscript. T.Y. andM.J.D. reviewed and editedthe manuscript. K.K. conceived the idea for thereview, made the final decisions regardinginclusion/exclusion of all papers, and reviewedand edited the manuscript.Prior Presentation. Parts of this study werepresented in abstract form at the U.K. Societyfor Behavioural Medicine Annual ScientificMeeting, Oxford, U.K., 9–10 December 2013.

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