Gestational Diabetes Mellitus andDiet: A Systematic Review andMeta-analysis of RandomizedControlled Trials Examining theImpact of Modified DietaryInterventions onMaternalGlucoseControl andNeonatalBirthWeightDiabetes Care 2018;41:1346–1361 | https://doi.org/10.2337/dc18-0102
OBJECTIVE
Medical nutrition therapy is a mainstay of gestational diabetes mellitus (GDM)treatment. However, data are limited regarding the optimal diet for achievingeuglycemia and improved perinatal outcomes. This study aims to investigatewhether modified dietary interventions are associated with improved glycemiaand/or improved birthweight outcomes inwomenwith GDMwhen comparedwithcontrol dietary interventions.
RESEARCH DESIGN AND METHODS
Data from published randomized controlled trials that reported on dietary com-ponents, maternal glycemia, and birth weight were gathered from 12 databases.Data were extracted in duplicate using prespecified forms.
RESULTS
From 2,269 records screened, 18 randomized controlled trials involving 1,151women were included. Pooled analysis demonstrated that for modified dietaryinterventions when compared with control subjects, there was a larger decreasein fasting and postprandial glucose (24.07 mg/dL [95% CI27.58,20.57]; P = 0.02and 27.78 mg/dL [95% CI 212.27, 23.29]; P = 0.0007, respectively) and a lowerneed formedication treatment (relative risk 0.65 [95%CI 0.47, 0.88];P=0.006). Forneonatal outcomes, analysis of 16 randomized controlled trials including 841 par-ticipants showed that modified dietary interventions were associated with lowerinfant birth weight (2170.62 g [95% CI 2333.64, 27.60]; P = 0.04) and lessmacrosomia (relative risk 0.49 [95%CI 0.27, 0.88];P=0.02). Thequality of evidencefor these outcomes was low to very low. Baseline differences between groups inpostprandial glucose may have influenced glucose-related outcomes. As well,relatively small numbers of study participants limit between-diet comparison.
CONCLUSIONS
Modified dietary interventions favorably influenced outcomes related to maternalglycemiaandbirthweight.This indicates that there is roomfor improvement inusualdietary advice for women with GDM.
1Division of Endocrinology and Metabolism, De-partment of Medicine, University of Calgary,Calgary, Canada2Norfolk and Norwich University Hospitals, Nor-folk, U.K.3Department of Endocrinology and Nutrition,Hospital Mutua de Terrassa, Terrassa, Spain4Institute of Biomedical Research, Hospitalde la Santa Creu i Sant Pau, Barcelona,Spain5Rabin Medical Center, Tel Aviv University, Tel Aviv,Israel6Iberoamerican Cochrane Centre, Hospital de laSanta Creu i Sant Pau, Barcelona, Spain7CIBER Epidemiologıa y Salud Publica, Institutode Salud Carlos III, Madrid, Spain8Department of Epidemiology, Hospital de laSanta Creu i Sant Pau, Barcelona, Spain9Department of Pharmacology, Therapeutics andToxicology, Universitat Autonoma de Barcelona,Bellaterra, Spain10Nutricia Research, Utrecht, the Netherlands11Department of Pediatrics, University MedicalCentre Groningen, University of Groningen, Gro-ningen, the Netherlands12Nestle Research Center, Lausanne, Switzerland13Department of Obstetrics and Gynecology,University of Helsinki, Helsinki, Finland14Helsinki University Hospital, Helsinki, Finland15Institute of Biomedicine, University of Turku,Turku, Finland16Turku University Hospital, Turku, Finland17Statens Serum Institut, Copenhagen, Denmark18King’s College London, London, U.K.19Research and Development Department, Ab-bott Nutrition, Granada, Spain20Department of Nutritional Sciences, Universityof Vienna, Vienna, Austria
Jennifer M. Yamamoto,1 Joanne E. Kellett,2
Montserrat Balsells,3
Apolonia Garcıa-Patterson,4 Eran Hadar,5
Ivan Sola,4,6,7 Ignasi Gich,7,8,9
Eline M. van der Beek,10,11
Eurıdice Casta~neda-Gutierrez,12
Seppo Heinonen,13,14 Moshe Hod,5
Kirsi Laitinen,15,16 Sjurdur F. Olsen,17
Lucilla Poston,18 Ricardo Rueda,19
Petra Rust,20 Lilou van Lieshout,21
Bettina Schelkle,21 Helen R. Murphy,2,22,23
and Rosa Corcoy24,25,26
1346 Diabetes Care Volume 41, July 2018
RECONSIDER
INGPREG
NANCY
WITHDIABETES
Gestational diabetes mellitus (GDM) isone of the most common medical com-plications in pregnancy and affects anestimated 14% of pregnancies, or one inevery seven births globally (1). Womenwith GDM and their offspring are at in-creased risk of both short- and longer-term complications, including, for mothers,later development of type 2 diabetes, andfor offspring, increased lifelong risks ofdeveloping obesity, type 2 diabetes, andmetabolic syndrome (2–6). The adverseintrauterine environment causes epige-netic changes in the fetus that maycontribute to metabolic disorders, theso-called vicious cycle of diabetes (7).The mainstay of GDM treatment is
dietary and lifestyle advice, which in-cludes medical nutrition therapy, weightmanagement, and physical activity (8).Women monitor their fasting and post-meal glucose levels and adjust their in-dividual diet and lifestyle to meet theirglycemic targets. This pragmatic approachachieves the glycemic targets in approx-imately two-thirds of women with GDM(8). However, despite the importance ofmedical nutrition therapy and its wide-spread recommendation in clinical prac-tice, there are limited data regarding theoptimal diet for achieving maternal eu-glycemia (8–11). It is also unknownwhether the dietary interventions forachieving maternal glycemia are alsoeffective for reducing excessive fetalgrowth and adiposity (12).Different dietary strategies have been
reported including low glycemic index(GI), energy restriction, increase or de-crease in carbohydrates, and modifica-tions of fat or protein quality or quantity(12–14). Three recent systematic reviewshave been performed examining specificdiets and pregnancy outcomes (15–17).Viana et al. (16) and Wei et al. (15)concluded that low-GI diets were asso-ciated with a decreased risk of infantmacrosomia. However, the most recent
systematic review from Cochrane, in-cluding 19 trials randomizing 1,398women, found no clear difference inlarge for gestational age or other primaryneonatal outcomes with the low-GI diet(17). The primary maternal outcomeswere hypertension (gestational and/orpreeclampsia), delivery by cesarean sec-tion, and type 2 diabetes, outcomes forwhich most trials lacked statisticalpower, even when dietary subgroupswere combined. Remarkably, no sys-tematic reviewsexamined the impactofmodified dietary interventions on thedetailedmaternal glycemic parameters,includingchange inglucose-relatedvar-iables, the outcomes that are most di-rectly influenced by diet.
To address this knowledge gap, weperformed a systematic review and meta-analysis of randomized controlled trialsto investigate whether modified dietaryinterventions (defined as a dietary in-tervention different from the usual oneused in the control group) inwomenwithGDM offer improved glycemic controland/or improved neonatal outcomeswhen compared with standard diets.
RESEARCH DESIGN AND METHODS
In accordance with a published protocol(PROSPERO CRD42016042391), we per-formed a systematic review and meta-analysis. Reporting is in accordance withthe Preferred Reporting Items for System-atic Reviews and Meta-Analyses (PRISMA)guidelines (18). An international panel ofexperts was formed by the InternationalLife Sciences Institute Europe. This paneldeterminedthereviewprotocolandcarriedout all aspects of the review.
Data Sources and Search StrategyThe following databases were searchedfor all available dates using the searchtermsdetailed in Supplementary Table 1:PubMed, MEDLINE, Cochrane CentralRegister of Controlled Trials (CENTRAL),
Embase, Cumulative Index to Nursingand Allied Health Literature (CINAHL),Webof Science Core Collection, Applied SocialSciences Index and Abstracts, ProQuest,ProQuest Dissertations & ThesesdA&Iand UK & Ireland, National Institutefor Health and Care Excellence evidencesearch, Scopus, UK Clinical Trials Gate-way, ISRCTN, and ClinicalTrials.gov. Theinitial search was performed in July2016. An updated search of MEDLINE,Embase, CENTRAL, and CINAHL was per-formed on 3 October 2017 using thesame search terms.
A hand-search of relevant reviewsand all included articles was conductedto identify studies for potential inclu-sion. As well, experts on the panel wereconsulted for the inclusion of additionalarticles. Reference management wascarried out using EndNote.
Study SelectionAll titles and abstracts were assessedindependently and in duplicate to iden-tify articles requiring full-text review.Published studies fulfilling the followingcriteria were included: randomized con-trolled trials, evaluated modified dietaryinterventions on women with GDM, glu-cose intoleranceorhyperglycemiaduringpregnancy, reported-on primary mater-nal and neonatal outcomes, includedwomen aged 18–45 years, had a durationof 2 weeks or more, and were publishedin English, French, Spanish, Portuguese,Italian, Dutch, German, or Chinese. Weexcluded studies that included partic-ipants with type 1 or type 2 diabetes ifdata for participants with GDM werenot presented independently, if dietarycharacteristics were not available, if thestudy was in animals, or if the study didnot report outcomes of interest. We didnot include studies of nutritional supple-ments such as vitamin D or probiotics asrecent reviews have addressed thesetopics (19,20).
21International Life Sciences Institute Europe,Brussels, Belgium22Cambridge University Hospitals NHS Founda-tion Trust, Cambridge, U.K.23Norwich Medical School, University of EastAnglia, Norwich, U.K.24DepartmentofMedicine,UniversitatAutonomade Barcelona, Bellaterra, Spain25CIBER Bioengineering, Biomaterials and Nano-technology, Instituto de Salud Carlos III, Madrid,Spain
26Department of Endocrinology and Nutrition, Hos-pital de la Santa Creu i Sant Pau, Barcelona, Spain
Corresponding author: Helen R. Murphy, [email protected].
Received13January2018andaccepted10March2018.
This article contains Supplementary Data onlineat http://care.diabetesjournals.org/lookup/suppl/doi:10.2337/dc18-0102/-/DC1.H.R.M. and R.C. contributed equally to thiswork.
© 2018 by the American Diabetes Association.Readers may use this article as long as the workis properly cited, the use is educational and notfor profit, and the work is not altered. More infor-mation is available at http://www.diabetesjournals.org/content/license.
See accompanying commentary, p. 1343.See accompanying articles, pp. 1337,1339, 1362, 1370, 1378, 1385, 1391,and e111.
care.diabetesjournals.org Yamamoto and Associates 1347
All citations identified after title andabstract assessment were full-text re-viewed in duplicate. Reasons for exclu-sion at the full-text review stage wererecorded. Any disagreements betweenreviewers were resolved by consensusand with consultation with the expertgroup when required.
Data ExtractionData from included studies were ex-tracted in duplicate using prespecifieddata extraction forms. Extracted dataelements included study and participantdemographics, study design, diagnosticcriteria for GDM, glucose intolerance orhyperglycemia, funding source, descrip-tion of modified dietary intervention andcomparator, and maternal and neonataloutcomes. For studies with missing data,inconsistencies, orotherqueries, authorswere contacted. Record managementwas carried out usingMicrosoft Excel andRevMan.For articles providing information on
maternal weight, fasting glucose, post-prandial glucose, HbA1c, or HOMA insulinresistance index (HOMA-IR) at baselineand postintervention but not theirchange, change was calculated as thedifferencebetweenpostinterventionandbaseline. Standard deviations were im-puted using the correlation coefficientobserved in articles reporting full infor-mation on the variable at baseline andpostintervention and its change or acorrelation coefficient of 0.5 when thisinformation was not available (21). Asstudies differed in postprandial glucoseat baseline, glycemic control at studyentrywasnotconsideredtobeequivalentin both arms, and thus continuous glu-cose-related variables at follow-up arereported as change from baseline.
Data SynthesisThe primary outcomes were maternalglycemic outcomes (mean glucose, fast-ing glucose, postprandial glucose [afterbreakfast, lunch, and dinner and com-bined], hemoglobin A1c [HbA1c], assess-ment of insulin sensitivity by HOMA-IR,and change in these parameters frombaseline to assessment; medicationtreatment [defined as oral diabetesmed-ications or insulin]) and neonatal birthweight outcomes (birth weight, macro-somia, and large for gestational age).Data were pooled into relative risks
(RRs) or mean differences with 95% CI
for dichotomous outcomes and contin-uousoutcomes,respectively.Meta-analysiswas performed using random-effectsmodels. A prespecified analysis stratifiedby type of diet and quality assessment wasperformed to explore potential reasonsfor interstudy variation. Heterogeneitywas assessed using I2 statistics. Smallstudy effects were examined for usingfunnel plots. Analyses were conductedusing RevMan version 5.3. Pooled esti-mation of birth weight in the study andcontrol arms, both overall and accordingto the specific diet intervention, wasperformed using Stata 14.0.
Quality AssessmentMethodological quality and bias assess-ment was completed by two reviewers.Risk of bias was assessed using theCochrane Collaboration tool, which ratesseven items as being high, low, or unclearfor risk of bias (21). These items includedrandom sequence generation, allocationconcealment, blinding of participantsand personnel, blinding of outcome as-sessment, incomplete outcome data, se-lective outcome reporting, and otherpotential sources of bias (21). A sensi-tivity analysis was performed excludingarticles with relevant weaknesses in trialdesign or execution.
The overall quality of the evidencewasalso assessed using Grading of Recom-mendations Assessment, Developmentand Evaluation (GRADE) working groupguidelines (21). GRADE was assessedfor all primary and secondary outcomes,bothmaternal and neonatal, but withoutsubgroup analysis per different dietaryintervention for each outcome measure.
RESULTS
We screened 2,269 records for poten-tial inclusion, and 126 articles were re-viewed in full (Supplementary Fig. 1).Eighteen studies (12–14,22–36) were in-cluded in themeta-analysiswitha total of1,151 pregnant women with GDM.
Study CharacteristicsThe types of modified dietary interven-tion included low-GI (n = 4), Dietary Ap-proaches to Stop Hypertension (DASH)(n = 3), low-carbohydrate (n = 3), fat-modification (n = 2), soy protein–enrichment (n = 2), energy-restriction(n = 1), high-fiber (n = 1), and ethnic diets(i.e., foods commonly consumed ac-cording to participant’s ethnicity) (n = 1)
and behavioral intervention (n = 1).Details of the study characteristics areincluded in Table 1. Most trials were sin-gle centered and had small sample sizes(range 12–150). Only two trials (one eachfrom Spain and Australia) included over100 participants, nine had 50–100 par-ticipants, and seven studies had fewerthan 50 participants. They were per-formed in North America, Europe, orAustralasia and all had a duration of atleast 2 weeks. The ethnicity of partic-ipants was reported in seven studies(12,13,26,29,31,32,34).
Most studies assessed individual di-etary adherence using food diaries (13,23–36). Althoughmost studies did reportan overall difference in dietary compo-sition between the intervention diet andcontrol diet, few studies reported a de-tailed assessment of dietary adherence.Only five studies used a formal measure ofadherence (24,25,29,33,34), and four ofthem reported data (25,29,33,34). Ad-herence ranged from 20% to 76% in thecontrol groups and 60% to 80% in theintervention groups.
Participant CharacteristicsWhen baseline characteristic data werepooled,women in the intervention groupwere older than women in the controlgroup (pooled mean difference 0.60years [95% CI 0.06, 1.14]) and had higherpostprandialglucose(5.47[0.86,10.08]),most influenced by the DASH and ethnicdiet studies. There was no overall sig-nificant difference between the inter-vention and control groups for BMI,gestational age at enrollment, fastingglucose, HbA1c, or HOMA-IR.
Maternal Glycemic Outcomes for AllModified Dietary InterventionsPooled risk ratios in 15 studies involving1,023womendemonstratedalowerneedfor medication (RR 0.65 [95% CI 0.47,0.88]; I2 = 55) (Table 2). Thirteen studies(n = 662 women) reported fasting glu-cose levels, nine (n = 475) reported com-binedpostprandial glucosemeasures, andthree (n = 175) reported post-breakfastglucose measures. Pooled analysis dem-onstrated a larger decrease in fasting, com-bined postprandial, and post-breakfastglucose levels in modified dietary inter-ventions (mean 24.07 mg/dL [95% CI27.58,20.57],I2=86,P=0.02;27.78mg/dL[212.27, 23.29], I2 = 63, P = 0.0007;and24.76mg/dL [29.13,20.38], I2 =34,P = 0.03, respectively) compared with
1348 GDM and Diet Diabetes Care Volume 41, July 2018
Table
1—Characteristicsofstudiesincluded
Author,year
(ref.)
Country
nEstimated
sample
size
Defi
nition
ofGDM
Durationof
dietary
interven
tion
Gestationalagein
weeks
aten
rollm
ent
(mean6
SD)
BaselineBMI,
kg/m
2(m
ean6
SD)
Meanmaternal
age,
years
(mean6
SD)
Dietary
interven
tion
Dietcomposition
(mean6
SD)*
Low-GIdiet
Grant,
2011
(26)
Canada
4750
todetect
a0.6mmol/L
difference
incapillary
glucose;nnot
achieved
CanadianDiabetes
Association(40)
28weeks
until
delivery
Control:
296
2.35
Interven
tion†:
296
3.21
Control:26
64.69
Interven
tion:
276
4.58
(prepregnancy)
Control:
346
0.46
Interven
tion:
346
5.16
Low
GI:Women
were
provided
withalist
ofstarch
choices
specificto
either
interven
tion(low
GI)orcontrol
Control:GI
58.0
60.5
Interven
tion:
GI49
.06
0.8
Louie,
2011
(29)
Australia
99120to
detect
a26
0-g
difference
inbirth
weight
(stoppe
dearly
because
of
smallerthan
expectedSD
)
Australasian
Diabetes
inPregnancySociety
criteria
(41)
Randomization
untildelivery
Control:
29.7
63.5
Interven
tion:
296
4.0
Control:
24.1
65.7
Interven
tion:
23.9
64.4
(prepregnancy)
Control:
32.4
64.5
Interven
tion:
346
4.1
LowGI:Target
GI#
50butotherwise
similarcomposition
tothecontroldiet
Control:en
ergy
1,93
46
465;
carbohydrate
40.3
68.3;
protein
22.2
67.5;
fat
35.1
616
.9;GI
53.0
66.5
Interven
tion:
energy
1,83
66
403;
carbohydrate
38.7
68.3;
protein
23.4
65.8;
fat
34.9
611
.0;GI
47.0
66.5
Ma, 20
15(30)
China
95Notreported
ChineseMed
ical
Associationand
American
Diabetes
Association(42)
24–26
weeks
until
delivery
Control:
27.9
61.1
Interven
tion:
27.5
61.1
Control:
21.156
2.75
Interven
tion:
21.906
3.14
(prepregnancy)
Control:
30.0
63.5
Interven
tion:
30.1
63.8
Low
GI:Women
provided
withan
exchange
listfor
starch
choices
specificto
either
interven
tion(low
GI)orcontrol
Control:en
ergy
2,03
06
215;
carbohydrate
49.8
66.8;
protein
18.8
62.5;
fat
31.8
63.8;
GI
53.8
62.5
Interven
tion:
energy
2,00
66
215;
carbohydrate
48.566
7.0;
protein
18.9
62.9;
fat32
.16
4.1;
GI
50.1
62.2
Con
tinu
edon
p.13
50
care.diabetesjournals.org Yamamoto and Associates 1349
Table
1—Continued
Author,year
(ref.)
Country
nEstimated
sample
size
Defi
nition
ofGDM
Durationof
dietary
interven
tion
Gestationalagein
weeks
aten
rollm
ent
(mean6
SD)
BaselineBMI,
kg/m
2(m
ean6
SD)
Meanmaternal
age,
years
(mean6
SD)
Dietary
interven
tion
Dietcomposition
(mean6
SD)*
Moses,
2009
(13)
Australia
63Notreported
Australasian
Diabetes
inPregnancySociety
(41)
28–32
weeks
until
delivery
Control:
29.9
61.11
Interven
tion:
30.3
61.11
Control:32
.86
7.92
Interven
tion:
32.0
66.68
(aten
rollm
ent)
Control:
31.3
64.52
Interven
tion:
30.8
63.90
LowGI:Women
asked
toavoid
specific
high-GIfoodsand
wereprovided
with
abooklet
outlining
carbohydrate
choices
Control:en
ergy
1,65
66
433;
carbohydrate
36.2
68.2;
protein
24.0
64.4;
fat
34.3
69.9;
GI
52.2
66.0
Interven
tion:
energy
1,71
36
368;
carbohydrate
36.7
66.1;
protein
23.9
63.9;
fat
33.4
66.12
;GI
48.0
65.0
DASH
diet
Asemi,
2013
(22)
Iran
3432
for“keyvariable
serum
HDL”
50-gglucose
challenge
.14
0mg/dL→
100gOGTT;G
DM
iftw
oormore
of
fasting.95
mg/dL,
1-h18
0mg/dL,2-h
155mg/dL,or3-h
140mg/dL
4weeks
Notreported
Control:
31.4
65.7
Interven
tion:
29.0
63.2(at
enrollm
ent)
Control:
29.4
66.2
Interven
tion:
30.7
66.7
DASH
diet:dietrich
infruit,vegetables,
wholegrains,and
low-fat
dairy;lowin
saturatedfats,
cholesterol,refined
grains,andsw
eets
Control:en
ergy
2,39
26
161;
carbohydrate
54.0
66.9;
protein
17.6
62.8;
fat
29.3
65.6
Interven
tion:
energy
2,40
06
25;
carbohydrate
66.8
62.2;
protein
16.8
61.2;
fat
17.6
60.9
Asemi,
2014
(23)
Iran
5242
todetecta75
-gdifference
inbirth
weight
Asabove
4weeks
Control:
25.9
61.4
Interven
tion:
25.8
61.4
Control:31
64.9
Interven
tion:
29.2
63.5
(aten
rollm
ent)
Control:
30.7
66.3
Interven
tion:
31.9
66.1
DASH
diet:as
above
Control:en
ergy
2,35
26
163;
carbohydrate
54.2
67.1;
protein
18.2
63.4;
fat
28.5
65.6
Interven
tion:
energy
2,40
76
30;
carbohydrate
66.4
62.04
;protein
17.0
61.3;
fat17
.46
1.0
Con
tinu
edon
p.13
51
1350 GDM and Diet Diabetes Care Volume 41, July 2018
Table
1—Continued
Author,year
(ref.)
Country
nEstimated
sample
size
Defi
nition
ofGDM
Durationof
dietary
interven
tion
Gestationalagein
weeks
aten
rollm
ent
(mean6
SD)
BaselineBMI,
kg/m
2(m
ean6
SD)
Meanmaternal
age,
years
(mean6
SD)
Dietary
interven
tion
Dietcomposition
(mean6
SD)*
Yao, 2015
(36)
China
3342
todetecta75
-gdifference
inbirthweight;not
achieved
50-gglucose
challenge
→10
0gOGTT
resultswithtw
oor
more
of
fasting.95
mg/dL,
1-h$18
0mg/dL,
2-h$15
5mg/dL,or
3-h$14
0mg/dL
4weeks
Control:
25.7
61.3
Interven
tion:
26.9
61.4
Control:30
.96
3.6
Interven
tion:
30.2
64.1
(aten
rollm
ent)
Control:
28.3
65.1
Interven
tion:
30.7
65.6
DASH
diet:same
asabove
Control:en
ergy
2,38
66
174;
carbohydrate
52.3
67.2;
protein
18.0
63.3;
fat
28.3
65.1
Interven
tion:
energy
2,40
86
54;
carbohydrate
66.7
62.3;
protein
16.9
61.2;
fat
17.176
1.16
Low-carbohydrate
diets
Cypryk,
2007
(25)
Poland
30Notreported
WorldHealth
Organization
criteria
2weeks
29.2
65.4
Notreported
28.7
63.7
Low
(interven
tion)vs.
high(control)
carbohydrate
(45%
vs.60
%oftotal
energy,
respectively)
Control‡:
carbohydrate
60;
protein
25;fat
15Interven
tion‡:
carbohydrate
45;
protein
25;fat30
Hernandez,
2016
(12)
U.S.
12Pilotstudyto
estimateSD
Carpen
terandCoustan
criteria
(43)
30–31
weeks
until
delivery
Control§:
31.7
62.45
Interven
tion:
31.2
60.98
Control:34
.36
3.92
Interven
tion:
33.4
63.43
(aten
rollm
ent)
Control:
306
2.45
Interven
tion:
286
4.90
Low
carbohydrate
(interven
tion)vs.
higher-complex
carbohydrate/
lower
fat(control)
Control‡:
carbohydrate
60;
protein
15;fat
25Interven
tion‡:
carbohydrate
40;
protein
15;fat45
Moreno-
Castilla,
2013
(31)
Spain
152
152todetecta
22%
difference
inneedforinsulin
2006
National
Diabetes
and
Pregnancy
Clinical
Guidelines
(44,45)
#35
weeks
until
delivery
Control:
30.1
63.5
Interven
tion:
30.4
63.0
Control:26
.66
5.5
Interven
tion:
25.4
65.7
(prepregnancy)
Control:
32.1
64.4
Interven
tion:
30.4
63.0
Low
carbohydrate
(interven
tion)vs.
control(40%vs.55%
oftotaldieten
ergy
ascarbohydrate)
Control‡:en
ergy
1,80
0minim
um;
carbohydrate
55;
protein
20;fat
25Interven
tion‡:
energy
1,80
0minim
um;
carbohydrate
40;
protein
20;fat40
Con
tinu
edon
p.13
52
care.diabetesjournals.org Yamamoto and Associates 1351
Table
1—Continued
Author,year
(ref.)
Country
nEstimated
sample
size
Defi
nition
ofGDM
Durationof
dietary
interven
tion
Gestationalagein
weeks
aten
rollm
ent
(mean6
SD)
BaselineBMI,
kg/m
2(m
ean6
SD)
Meanmaternal
age,
years
(mean6
SD)
Dietary
interven
tion
Dietcomposition
(mean6
SD)*
Soyprotein–en
richmen
tdiets
Jamilian,
2015
(27)
Iran
6856
(minim
um
clinical
difference
not
reported
)
One-step
75gOGTT,
American
Diabetes
Association(46)
6weeks
Notreported
Control:28
.46
3.4
Interven
tion:
28.9
65.0
Control:
29.3
64.2
Interven
tion:
28.2
64.6
Soyprotein
diethad
thesameam
ountof
protein
ascontrol
dietbuttheprotein
portionwas
made
upof35
%anim
alprotein,35
%soy
protein,30
%other
plantproteins
Control:en
ergy
2,42
66
191;
carbohydrate
54.6
67.1;
protein
14.4
61.7;
fat
32.1
65.4
Interven
tion:
energy
2,30
86
194;
carbohydrate
54.6
67.3;
protein
15.0
62.6;
fat
30.3
64.7
Sarathi,
2016
(14)
India
62Notreported
International
Associationof
Diabetes
and
Pregnancy
Study
Groupscriteria
(47)
From
diagnosis
untildelivery
Control:
25.566
1.69
Interven
tion:
25.196
1.92
Notreported
Control:29
.176
3.38
Interven
tion:
29.436
2.98
Soyprotein
diet:25
%ofcereal
partof
high-fiber
complex
carbohydrates
replacedwithsoy
Control‡:en
ergy
1,60
0–2,00
0;minim
um
carbohydrate
175g
Interven
tion‡:
energy
1,60
0–2,00
0;minim
um
carbohydrate
175g
Fat-modificationdiets
Lauszus,
2001
(28)
Den
mark
2720
todetect
adifference
incholesterolof
0.65
mmol/L
3-h75
gOGTT
with
bloodsamples
takenevery
30minutes,GDM
if2ormore
glucoses.3SD
above
themean
34weeks
until
delivery
Notreported
Control:32
.26
5.61
Interven
tion:
35.3
68.65
(aten
rollm
ent)
Control:
296
3.74
Interven
tion:
316
3.61
High monounsaturated
fattyacids:source
was
hybrid
sunflower
oilwith
high-contentoleic
acid
andsnacks
of
almondsand
hazelnuts
Control:en
ergy
1,727;
carbohydrate
50.0
63.6;
protein
19.0
63.6;
fat
30.0
67.2
Interven
tion:
energy
1,98
2;carbohydrate
466
3.5;
protein
166
3.5;
fat37
63.5
Con
tinu
edon
p.13
53
1352 GDM and Diet Diabetes Care Volume 41, July 2018
Table
1—Continued
Author,year
(ref.)
Country
nEstimated
sample
size
Defi
nition
ofGDM
Durationof
dietary
interven
tion
Gestationalagein
weeks
aten
rollm
ent
(mean6
SD)
BaselineBMI,
kg/m
2(m
ean6
SD)
Meanmaternal
age,
years
(mean6
SD)
Dietary
interven
tion
Dietcomposition
(mean6
SD)*
Wang,
2015
(35)
China
84Notreported
International
Associationof
Diabetes
and
Pregnancy
Study
Groupscriteria
(47)
;27
weeks
until
delivery
Control:
27.3
61.96
Interven
tion:
27.4
61.52
Control:22
.26
3.6
Interven
tion:
21.4
63.0
(prepregnancy)
Control:
29.7
64.64
Interven
tion:
30.3
64.17
Polyunsaturatedfatty
acid
meals(50–54
%carbohydrate,31–
35%fatw
ith45–40
gsunflower
oil)
Control:en
ergy
1,97
86
107;
carbohydrate
55.4
62.0;
protein
17.9
61.0;
fat
26.7
61.3
Interven
tion:
energy
1,96
06
90;
carbohydrate
47.7
60.7;
protein
18.0
60.7;
fat
34.3
60.2
Other
diets
Bo, 2014
(24)
Italy
99in
diet
study
(total
n=20
0)
200todetecta
10%
difference
infastingglucose
(based
on
exercise
portion
oftrial)
75gOGTT
24–26
weeks
until
delivery
Notreported
Control:26
.86
4.1
Interven
tion:
26.9
64.6
Control:
33.9
65.3
Interven
tion:
35.1
64.4
Beh
avioraldietary
recommen
dations:
individual
recommen
dations
forhelpingdietary
choices
Control:en
ergy
2,11
66
383;
carbohydrate
46.9
65.9;
protein
15.6
62.6;
fat
37.4
64.2
Interven
tion:
energy
2,15
66
286;
carbohydrate
47.8
64.9;
protein
15.5
62.4;
fat
36.7
63.9
Rae, 2000
(32)
Australia
124
120to
detect
adecreasein
insulin
use
from
40%to
15%and
adecreasein
macrosomia
from
25%to
5%
OGTT
fasting
glucose.5.4mmol/
Land/or2-h
glucose.7.9mmol/
L(48)
,36
weeks
until
delivery
Control:
28.3
64.6
Interven
tion:
28.1
65.8
Control:38
.06
0.7
Interven
tion:
37.9
60.7(at
diagnosis)
Control:30
.6Interven
tion:
30.2
(SDnot
reported
)
Moderateen
ergy
restriction(1,590–
1,776kcal/day)vs.
control(2,010–
2,220kcal/day)
Control:en
ergy
1,63
06
339;
carbohydrate
41.0
64.6;
protein
24.0
62.3;
fat
34.0
65.3
Interven
tion:
energy
1,56
66
289;
carbohydrate
42.0
65.7;
protein
25.0
62.4;
fat
31.0
65.7
Con
tinu
edon
p.13
54
care.diabetesjournals.org Yamamoto and Associates 1353
control group. There were no significantdifferences in change in HbA1c (sevenstudies), HOMA-IR (four studies), or inpost-lunch or -dinner glucose levels (twostudies).
Neonatal Birth Weight Outcomesfor All DietsPooled mean birth weight was 3,266.65 g(95% CI 3,172.15, 3,361.16) in the modi-fied dietary intervention versus 3,449.88 g(3,304.34, 3,595.42) in the control group.Pooled analysis of all 16 modified die-tary interventions including 841 partic-ipants demonstrated lower birth weight(mean2170.62g[95%CI2333.64,27.60],I2=88;P=0.04)and lessmacrosomia (RR0.49 [95% CI 0.27, 0.88], I2 = 11; P = 0.02)compared with conventional dietary ad-vice (Table 2 and Fig. 1). There was nosignificant difference in the risk of large-for-gestational-age newborns in modi-fied dietary interventions as comparedwith control diets (RR 0.96 [95% CI 0.63,1.46], I2 = 0; P = 0.85).
Subgroup Meta-analysis by Typesof Dietary InterventionsPooled analysis of low-GI diets showeda larger decrease in fasting (26,29,30),postprandial, and post-breakfast glu-cose compared with control diets (26,30)(Table 2). However, the pooled analysis ofthe DASH diet showed significant favor-able modifications in several outcomes,including change in fasting (22,36) andpostprandial glucose (22), HOMA-IR (35),HbA1c (22), medication need (22,23,36),infant birth weight (23,36), and macro-somia (23,36) (Tables 2 and3). Last, pooledanalysis of the soy protein–enriched dietdemonstrated a significant decrease inmedication use and birth weight (14,27)(Tables 2 and 3). One soy–protein inter-vention (n = 68 participants) describedsignificantly lowerHOMA-IR(27) (Table2).
Behavioral (one study) and ethnic-specific modified dietary interventions(one study) were included. The behav-ioral changedietary interventionreportedsignificant differences in change in post-prandial glucose and in HbA1c (Table 2)(24). The ethnic diet study demonstrateda significantly larger decrease in fastingand postprandial glucose (Table 2) (34).Fat-modification, low-carbohydrate, andenergy-restriction diets were not asso-ciated with a significant difference inour primary outcomes in the stratifiedanalysis.
Table
1—Continued
Author,year
(ref.)
Country
nEstimated
sample
size
Defi
nition
ofGDM
Durationof
dietary
interven
tion
Gestationalagein
weeks
aten
rollm
ent
(mean6
SD)
BaselineBMI,
kg/m
2(m
ean6
SD)
Meanmaternal
age,
years
(mean6
SD)
Dietary
interven
tion
Dietcomposition
(mean6
SD)*
Reece,
1995
(33)
U.S.
50Po
sthoc
calculation
Notreported
24–29
weeks
until
delivery
Notreported
Notreported
Notreported
Fiber-enriched
diet:
fiber
takenas
fiber-
rich
foods
(40g/day)
andahigh-fiber
drink(40g/day)
Control‡:
carbohydrate50
;fat
30;fiber
20g/day
Interven
tion‡:
carbohydrate60
;fat
20with80
gfiber/
day
Valen
tini,
2012
(34)
Italy
20Notrep
orted
(pilot
study)
FourthInternational
Workshop
Conferen
ceon
Gestational
Diabetes
Mellitus
(49)
From
diagnosis
(screeningat
24–28
weeks)
untildelivery
Control
27.1
65.9
Interven
tion:
21.3
66.8
Control:24
.16
4.7
Interven
tion:
25.7
63.6
(prepregnancy)
Control:
30.2
64.7
Interven
tion:
28.9
63.3
Ethnicmealplan:foods
commonly
consumed
per
participant’s
ethnicity
withthe
samekcal
and
nutrient
compositionas
the
controldiet
Control‡:
carbohydrate
53;
protein
18;fat28
;fiber
26g/day
Interven
tion‡:
carbohydrate
55;
protein
17;fat28
;fiber
21g/day
Unless
otherwisestated
,theunitsarekcal/day
foren
ergy,%
forcarbohydrate,protein,andfat.OGTT,oralglucose
tolerance
test.*R
eported
actual
dietary
intake.When
notreported
,prescribed
dietary
intake
isreported
.†Interven
tionisdefi
ned
asdietary
interven
tiondifferentfrom
theusual
dietary
interven
tionusedin
thecontrolgroup.‡Indicates
prescribed
diet.§Thecontroland
interven
tiongroupswerereversed
forthepurpose
ofmeta-analysisso
itcould
beincluded
inthelow-carbohydrate
group.
1354 GDM and Diet Diabetes Care Volume 41, July 2018
Table 2—Pooled analyses of primary maternal glycemic and infant birth weight outcomes
Outcome Diet subgroup N of studies N of women Effect estimate I2 (%)
Maternal glycemic outcomes
Mean [95% CI]
Change in fasting glucose (mg/dL) All diets 13 662 24.07 [27.58, 20.57] 86Low GI (26,29,30) 3 195 25.28 [26.83, 23.73] 0DASH (22,36) 2 67 211.55 [214.00, 29.09] 0Low carbohydrate (12,25) 2 42 3.81 [24.29, 11.92] 69Fat modification (28,35) 2 109 4.87 [20.44, 10.18] 0Soy protein (14,27) 2 130 27.47 [220.28, 5.34] 91Behavior (24) 1 99 21.50 [25.66, 2.66] dEthnic (34) 1 20 225.34 [237.57, 213.11] d
Change in postprandial glucose (mg/dL) All diets 9 475 27.78 [212.27, 23.29] 63Low GI (26,30) 2 121 27.08 [212.07, 22.08] 4DASH (22) 1 34 245.22 [268.97, 221.47] dLow carbohydrate (25) 1 30 23.00 [210.06, 4.06] d
Fat modification (28,35) 2 109 26.43 [213.08, 0.22] 0Soy protein (14) 1 62 21.05 [211.03, 8.93] d
Behavior (24) 1 99 26.90 [211.68, 22.12] dEthnic (34) 1 20 216.28 [222.83, 29.73] d
Change in post-breakfast glucose (mg/dL) All 3 175 24.76 [29.13, 20.38] 34Low GI (30) 1 83 28.6 [214.11, 23.09] d
Low carbohydrate (25) 1 30 23.00 [28.15, 2.15] dSoy protein (14) 1 62 21.05 [29.73, 7.63] d
Change in post-lunch glucose (mg/dL) All 2 92 4.50 [21.90, 10.90] 0Low carbohydrate (25) 1 30 4.00 [24.56, 12.56] d
Soy protein (14) 1 62 5.14 [24.51, 14.79] d
Change in post-dinner glucose (mg/dL) All 2 92 1.81 [25.28, 8.90] 13Low carbohydrate (25) 1 30 1.00 [28.14, 10.14] d
Soy protein (14) 1 62 3.03 [28.20, 14.26] d
Change in HOMA-IR (mIU/mL 3 mmol/L) All 4 212 21.10 [22.26, 0.07] 90DASH (36) 1 33 21.90 [22.36, 21.44] dLow carbohydrate (12) 1 12 0.60 [21.90, 3.10] d
Soy protein (27) 1 68 22.00 [23.17, 20.83] d
Behavior (24) 1 99 20.30 [20.71, 0.11] d
Change in HbA1c (%) All 7 407 20.05 [20.13, 0.02] 84Low GI (29,30) 2 167 0.01 [20.02, 0.03] 0DASH (22) 1 34 20.25 [20.42, 20.08] d
Fat modification (28) 1 25 0.10 [20.14, 0.34] d
Soy protein (14) 1 62 20.01 [20.07, 0.05] dBehavior (24) 1 99 20.19 [20.26, 20.12] d
Ethnic diet (34) 1 20 20.05 [20.27, 0.17] d
RR [95% CI]
Medication treatment All 15 1023 0.65 [0.47, 0.88] 55Low GI (13,26,29,30) 4 293 0.80 [0.55, 1.14] 34DASH (22,23,36) 3 119 0.29 [0.17, 0.50] 0Low carbohydrate (31) 1 150 1.00 [0.75, 1.34] d
Energy restriction (32) 1 117 1.05 [0.47, 2.34] d
Fat modification (35) 1 84 Not estimable dSoy protein (14,27) 2 130 0.44 [0.21, 0.91] 0Behavior (24) 1 99 0.61 [0.15, 2.42] d
Ethnic (34) 1 20 2.00 [0.21, 18.69] dFiber (33) 1 11 Not estimable d
Infant birth weight outcomes
Mean [95% CI]
Birth weight (g) All 16 841 2170.62 [2333.64, 27.60] 88
Low GI (13,26,29,30) 4 276 254.25 [2178.98, 70.47] 0
DASH (22,23,36) 3 119 2598.19 [2663.09, 2533.30] 0
Low carbohydrate (12,25) 2 42 57.73 [2164.93, 280.39] 0
Energy restriction (32) 1 122 194.00 [242.58, 430.58] d
Fat modification (28,35) 2 109 2139.61 [2294.80, 15.58] 0
Soy protein (14,27) 2 131 2184.67 [2319.35, 249.98] 0
Continued on p. 1356
care.diabetesjournals.org Yamamoto and Associates 1355
Secondary OutcomesWeight gain from inclusion was lowerfor low-carbohydrate diets and cesareanbirth for DASH diets (SupplementaryTable 2). Specific diet interventions didnot show significant between-group dif-ferences in maternal gestational weightgain throughout pregnancy, preeclamp-sia/eclampsia, neonatal hypoglycemia asdefined by the authors, preterm birth,neonatal intensive care unit admission,or small-for-gestational-age newborns(Supplementary Tables 2 and 3).
Sensitivity Analysis of PrimaryOutcomesSensitivity analysis was performed toexplore reasons for heterogeneity andto assess outcomes when studies withmethodological concernswere removed.We were unable to include four studies(22,23,34,36), including all the DASHdiet studies, where clarification of certainaspects of the results could not be ob-tained,evenafteradirectapproachtotheauthors. The authors of the ethnic dietstudy responded to queries but did notprovide the required information re-garding gestational age at randomiza-tion (34). After these studies are removed,the changes in postprandial glucose(mean 25.90 mg/dL [95% CI 27.93,23.88], I2 = 0; P = 0.0001), post-breakfastglucose levels (24.76 mg/dL [29.13,20.38], I2 = 34; P = 0.03), and birth weight(274.88 g [2144.86, 24.90], I2 = 1; P =0.04) remained significant when alldietswere combined (Table 3). Further-more, the heterogeneity in most primary
outcomes decreased after removal ofthese four studies.
When dietary subgroups were as-sessed, low-GI diets had significant differ-ences in changes in fasting (mean 25.33mg/dL [95%CI26.91,23.76]) (26,29,30),postprandial (27.08 mg/dL [212.07,22.08]) (26,30), and post-breakfast(28.6 mg/dL [214.11,23.09]) glucose(26,30). The soy protein–enriched diethad differences in change of HOMA-IR(mean 22.00 [95% CI 23.17, 20.83])(27), required less medication use (RR0.44 [95% CI 0.21, 0.91]), and had alower birth weight (mean 2184.67 g[95% CI 2319.35, 249.98]) (14,27). Thebehavior modification diet had signifi-cant differences in change in postpran-dial glucose (mean26.90 mg/dL [95% CI29.85, 23.95]) and in HbA1c (20.19%[20.26, 20.12]) (24) (Table 3).
Assessment of Bias and Quality of theEvidenceNone of the included studies were as-sessed as having a low risk of bias in allseven items of the Cochrane Collabora-tion tool (Supplementary Fig. 2). Moststudies were high risk for blinding ofparticipants and personnel and for othersources of bias (Supplementary Fig. 3).Studies scored high risk for other sourcesof bias for concerns such as baseline differ-ences and industry funding. Most studieshad an unclear risk of bias for selectiveoutcome reporting and very few had reg-istered protocols (Supplementary Fig. 3).
GRADE assessment for the outcomesof interest reveals overall low to very
lowquality of evidence (SupplementaryTable 4). Considerations to downgradequality of evidence involved the entirespectrum, including limitations in thestudy design, inconsistency in study results,and indirectness and imprecision in effectestimates.
Evaluation for Small Study EffectFunnel plots of means and RRs of theprimary outcomes for the main analysisare shown in Supplementary Figs. 4 and5 and for the sensitivity analysis in Sup-plementary Figs. 6 and 7. Overall, funnelplot asymmetry improves with the sen-sitivityanalysiscomparedwiththemainanalysis for neonatal birth weight out-comes.
CONCLUSIONS
In this meta-analysis, we pooled resultsfrom 18 studies including 1,151 womenwith a variety of modified dietary inter-ventions. Remarkably, this is the firstmeta-analysis with a comprehensiveanalysisonmaternalglucoseparameters.Despite the heterogeneity between stud-ies, we found a moderate effect of dietaryinterventions on maternal glycemic out-comes, including changes in fasting, post-breakfast, and postprandial glucose levelsand need for medication treatment, andon neonatal birth weight. After removal offour studies with methodological con-cerns, we saw an attenuation of the treat-ment effect. Nonetheless, the change inpost-breakfast and postprandial glucoselevels and lowering of infant birth weight
Table 2—Continued
Outcome Diet subgroup N of studies N of women Effect estimate I2 (%)
Ethnic diet (34) 1 20 2370.00 [2928.87, 188.87] d
Fiber (33) 1 22 294.00 [2446.68, 258.68] d
RR [95% CI]
Large for gestational age All 8 647 0.96 [0.63, 1.46] 0Low GI (13,26,29) 3 193 1.33 [0.54, 3.31] 0Low carbohydrate (31) 1 149 0.51 [0.13, 1.95] d
Energy restriction (32) 1 123 1.17 [0.65, 2.12] dSoy protein (14) 1 63 0.45 [0.04, 4.76] d
Behavior (24) 1 99 0.73 [0.25, 2.14] d
Ethnic diet (34) 1 20 0.14 [0.01, 2.45] d
Macrosomia All 12 834 0.49 [0.27, 0.88] 11Low GI (13,26,29,30) 4 276 0.46 [0.15, 1.46] 0DASH (23,36) 2 85 0.12 [0.03, 0.51] 0Low carbohydrate (25,31) 2 179 0.20 [0.02, 1.69] d
Energy restriction (32) 1 122 1.56 [0.61, 3.94] dFat modification (35) 1 84 0.35 [0.04, 3.23] d
Soy protein (27) 1 68 0.60 [0.16, 2.31] d
Ethnic diet (34) 1 20 0.20 [0.01, 3.70] d
1356 GDM and Diet Diabetes Care Volume 41, July 2018
remained significant. Given the inconsis-tencies between the main and sensitivityanalyses, we consider that conclusionsshould be drawn from the latter. Thesedata suggest that dietary interventionsmodified above and beyond usual dietaryadviceforGDMhavethepotentialtoofferbetter maternal glycemic control andinfant birth weight outcomes. However,the quality of evidencewas judged as lowto very low due to the limitations in thedesign of included studies, the inconsis-tency between their results, and theimprecision in their effect estimates.
Previous systematic reviews havefocused on the easier-to-quantify out-comes, such as the decision to startadditional pharmacotherapy and glucose-related variables at follow-up, but did notaddress change from baseline (15–17). Themost recently published Cochrane sys-tematic review by Han et al. (17) did notfind any clear evidence of benefit otherthan a possible reduction in cesareansection associated with DASH diet.The very high-carbohydrate intake (;400g/day) and 12 servings of fruit andvegetables in the DASH diet (22,23,36)
limit its clinical applicability and general-izability to women from lower socioeco-nomic, inner city backgrounds inWesterncountries. The Cochrane review sharedone of our primary outcomes, largefor gestational age (17). Neither meta-analysis detected a significant differ-ence in risk of large for gestational agebecause the trialswith a larger effect onbirth weight (the three DASH studies)did not report on large for gestationalage.
Our findings regarding pooled analy-sis of low-GI dietary interventions are
Figure 1—Forest plot of birth weight for modified dietary interventions compared with control diets in women with GDM. Reference citationsfor studies can be found in Table 1. CHO, carbohydrate; IV, inverse variance.
care.diabetesjournals.org Yamamoto and Associates 1357
Table 3—Sensitivity analysis of primary maternal glycemic and infant birth weight outcomes
Outcome Diet subgroup N of studies N of women Effect estimate I2 (%)
Maternal glycemic outcomes
Mean [95% CI]
Change in fasting glucose (mg/dL) All diets 10 575 21.98 [25.41, 1.45] 74Low GI (26,29,30) 3 195 25.33 [26.91, 23.76] 0DASH 0 0 Not estimable dLow carbohydrate (12,25) 2 42 3.66 [24.42, 11.73] 57Fat modification (28,35) 2 109 4.88 [21.45, 11.21] 0Soy protein (14,27) 2 130 27.51 [220.31, 5.30] 90Behavior (24) 1 99 21.50 [26.47, 3.47] dEthnic 0 0 Not estimable d
Change in postprandial glucose (mg/dL) All diets 7 421 25.90 [27.93, 23.88] 0Low GI (26,30) 2 121 27.08 [212.07, 22.08] 4DASH 0 0 Not estimable dLow carbohydrate (25) 1 30 23.00 [28.15, 2.15] d
Fat modification (28,35) 2 109 24.85 [213.32, 3.62] 40Soy protein (14) 1 62 21.05 [29.73, 7.63] d
Behavior (24) 1 99 26.90 [29.85, 23.95] dEthnic 0 0 Not estimable d
Change in post-breakfast glucose (mg/dL) All diets 3 175 24.76 [29.13, 20.38] 34Low GI (30) 1 83 28.6 [214.11, 23.09] d
Low carbohydrate (25) 1 30 23.00 [28.15, 2.15] dSoy protein (14) 1 62 21.05 [29.73, 7.63] d
Change in post-lunch glucose (mg/dL) All diets 2 92 4.50 [21.90, 10.90] 0Low carbohydrate (25) 1 30 4.00 [24.56, 12.56] d
Soy protein (14) 1 62 5.14 [24.51, 14.79] d
Change in post-dinner glucose (mg/dL) All diets 2 92 1.81 [25.28, 8.90] 0Low carbohydrate (25) 1 30 1.00 [28.14, 10.14] d
Soy protein (14) 1 62 3.03 [28.20, 14.26] d
Change in HOMA-IR (mIU/mL 3 mmol/L) All diets 3 179 20.74 [22.09, 0.61] 75DASH 0 0 Not estimable dLow carbohydrate (12) 1 12 0.60 [21.90, 3.10] d
Soy protein (27) 1 68 22.00 [23.17, 20.83] d
Behavior (24) 1 99 20.30 [20.71, 0.11] d
Change in HbA1c (%) All diets 5 353 20.03 [20.11, 0.05] 87Low GI (29,30) 2 167 0.01 [20.02, 0.03] 0DASH 0 0 Not estimable d
Fat modification (28) 1 25 0.10 [20.14, 0.34] d
Soy protein (14) 1 62 20.01 [20.07, 0.05] dBehavior (24) 1 99 20.19 [20.26, 20.12] d
Ethnic diet 0 0 Not estimable d
RR [95% CI]
Medication treatment All diets 11 884 0.82 [0.65, 1.04] 24Low GI (13,26,29,30) 4 293 0.80 [0.55, 1.14] 34DASH 0 0 Not estimable d
Low carbohydrate (31) 1 150 1.00 [0.75, 1.34] d
Energy restriction (32) 1 117 1.05 [0.47, 2.34] d
Fat modification (35) 1 84 Not estimable dSoy protein (14,27) 2 130 0.44 [0.21, 0.91] 0Behavior (24) 1 99 0.61 [0.15, 2.42] d
Ethnic 0 0 Not estimable dFiber (33) 1 11 Not estimable d
Infant birth weight outcomes
Mean [95% CI]
Birth weight (g) All diets 12 702 274.88 [2144.86, 24.90] 1
Low GI (13,26,29,30) 4 276 254.25 [2178.98, 70.47] 0
DASH 0 0 Not estimable d
Low carbohydrate (12,25) 2 42 57.73 [2164.93, 280.39] 0
Energy restriction (32) 1 122 194.00 [242.58, 430.58] d
Fat modification (28,35) 2 109 2139.61 [2294.80, 15.58] 0
Soy protein (14,27) 2 131 2184.67 [2319.35, 249.98] 0
Continued on p. 1359
1358 GDM and Diet Diabetes Care Volume 41, July 2018
broadly consistent with those of Vianaet al. (16) and Wei et al. (15). Viana et al.(16) noted decreased birth weight andinsulin use based on four studies of low-GIdiet among 257 women (mean difference2161.9 g [95%CI2246.4,277.4] and RR0.767[95%CI0.597,0.986], respectively).Wei et al. (15) also reported decreasedrisk of macrosomia with a low-GI diet infive studies of 302 women (RR 0.27 [95%CI 0.10, 0.71]). In our analyses of fourstudies in a comparable number of par-ticipants (n = 276), we found the samedirection of these effect estimates, with-out significant between-group differen-ces. This ismost likely due to thedifferentstudies included. For example, we wereunable to obtain effect estimates strat-ified by type of diabetes in the study byPerichart-Perera et al. (which includedwomen with type 2 diabetes) and there-fore did not include this study (37). Animportant difference between our anal-yses and that ofWei et al. (15) is that theyincluded DASH diet as a low-GI dietarysubtype.We also included a recent studyby Ma et al. (30) not included by theprevious reviews.Our sensitivity analyses highlighted con-
cerns regarding some studies included inprevious reviews. Notably, after removalof the studies with the most substantialmethodological concerns in the sensitiv-ity analysis, differences in the change infasting plasma glucose were no longersignificant. Although differences in thechange in postprandial glucose and birthweight persisted, they were attenuated.
This review highlights limitations ofthe current literature examining dietaryinterventions in GDM. Most studies aretoo small to demonstrate significant dif-ferences in our primary outcomes. Sevenstudies had fewer than 50 participantsand only two had more than 100 partic-ipants (n = 125 and 150). The shortduration of many dietary interventionsand the late gestational age atwhich theywere started (38) may also have limitedtheir impactonglycemicandbirthweightoutcomes. Furthermore, we cannot con-clude if the improvements in maternalglycemia and infant birth weight are dueto reduced energy intake, improved nu-trient quality, or specific changes in typesof carbohydrate and/or protein.
We have not addressed the indirectmodifications of nutrients. For example,reducing intake of dietary carbohydratestodecreasepostprandial glucosemaybecompensated by a higher consumptionof fat potentially leading to adverse ef-fects on maternal insulin resistance andfetal body composition. Beneficial oradverse effects of other nutrients such asn-3 long-chain polyunsaturated fatty acid,vitamin D, iron, and selenium cannot beruled out.
Our study has important strengths andweakness. To our knowledge, ours is thefirst systematic review of dietary inter-ventions inGDMcomprehensively exam-ining the impact of diet on maternalglycemic outcomes assessing the changein fasting and postprandial glucose,HbA1c, and HOMA-IR from baseline.
This is especially important given thatgroups were not well balanced at base-line. Our review also benefits from therigorousmethodology used aswell as thescientific, nutritional, and clinical exper-tise from an international interdisciplin-arypanel.However, italsohaslimitations.Baseline differences between groups inpostprandial glucose may have influ-enced glucose-related outcomes. Fur-thermore, three of the included trialswere pilot studies and therefore notdesigned to find between-group differ-ences (12,26,34). The low number ofstudies reporting on adherence clearlyillustrates that the quality of the evi-dence is far fromideal. Theheterogeneityof the dietary interventions even withina specific type (varied macronutrientratios, unknown micronutrient intake,and short length of some dietary inter-ventions) and baseline characteristics ofwomen included (such as prepregnancyBMI or ethnicity) may have also affectedourpooledresults. It shouldalsobenotedthat the relatively small numbers of studyparticipants limit between-diet compar-isons. Last, we were unable to resolvequeries regarding potential concerns forsources of bias because of lack of authorresponse to our queries. We have ad-dressed this by excluding these studiesin the sensitivity analysis.
Modified dietary interventions favor-ably influenced outcomes related to ma-ternal glycemia and birth weight. Thisindicates that there is room for improve-ment in usual dietary advice for women
Table 3—Continued
Outcome Diet subgroup N of studies N of women Effect estimate I2 (%)
Ethnic diet 0 0 Not estimable d
Fiber (33) 1 22 294.00 [2446.68, 258.68] d
RR [95% CI]
Large for gestational age All diets 7 627 1.00 [0.66, 1.53] 0Low GI (13,26,29) 3 193 1.33 [0.54, 3.31] 0Low carbohydrate (31) 1 149 0.51 [0.13, 1.95] d
Energy restriction (32) 1 123 1.17 [0.65, 2.12] dSoy protein (14) 1 63 0.45 [0.04, 4.76] d
Behavior (24) 1 99 0.73 [0.25, 2.14] d
Ethnic diet 0 0 Not estimable d
Macrosomia All 9 729 0.73 [0.40, 1.31] 0Low GI (13,26,29,30) 4 276 0.46 [0.15, 1.46] 0DASH 0 0 Not estimable 0Low carbohydrate (25,31) 2 179 0.20 [0.02, 1.69] d
Energy restriction (32) 1 122 1.56 [0.61, 3.94] dFat modification (35) 1 84 0.35 [0.04, 3.23] d
Soy protein (27) 1 68 0.60 [0.16, 2.31] d
Ethnic diet 0 0 Not estimable d
care.diabetesjournals.org Yamamoto and Associates 1359
with GDM. Although the quality ofthe evidence in the scientific literatureis low, our review highlights the key roleof nutrition in the management of GDMand the potential for improvement ifbetter recommendations based on ad-equately powered high-quality studieswere developed. Given the prevalenceof GDM, new studies designed to eval-uate potential dietary interventions forthese women should be based in largerstudy groups with appropriate statisti-cal power. As most women with GDMare entering pregnancy with a high BMI,evidence-based recommendations re-garding both dietary components andtotal energy intake are particularly impor-tant for overweight and obese women.The evaluation of nutrient quality, in ad-dition to their quantity, as well as dietarypatterns such as Mediterranean diet (39)wouldalsoberelevant. Inparticular, thereisanurgentneedforwell-designeddietaryintervention studies in the low- and mid-dle-income countries where the globalhealth consequences of GDM are greatest.
Funding.H.R.M.wasfundedbytheU.K.NationalInstitute for Health Research (CDF 2013-06-035).This work was conducted by an expert group ofthe European branch of the International LifeSciences Institute (ISLI Europe). This publicationwas coordinated by the ISLI Europe Early Nutri-tion and Long-Term Health and the Obesity andDiabetes task forces. Industry members of thesetask forcesare listedonthe ILSI Europewebsiteatwww.ilsi.eu. Experts are not paid for the timespent on this work; however, the nonindustrymembers within the expert group were offeredsupport for travel and accommodation costsfrom the Early Nutrition and Long-Term Healthand the Obesity and Diabetes task forces to at-tend meetings to discuss the manuscript and asmall compensatory sum (honoraria) with theoption to decline. The expert group carried outthe work, i.e. collecting and analyzing data andinformation and writing the scientific paper,separate to other activities of the task forces.The research reported is the result of a scientificevaluation in line with ILSI Europe’s frameworkto provide a precompetitive setting for public-private partnership. ILSI Europe facilitated sci-entific meetings and coordinated the overallproject management and administrative tasksrelating to the completion of this work.The opinions expressed herein and the con-
clusions of this publication are those of theauthors and do not necessarily represent theviews of ILSI Europe nor those of its membercompanies. For further information about ILSIEurope, please email [email protected] or call+32 2 771 00 14.Duality of Interest. E.M.v.d.B. works part-timefor Nutricia Research. E.C.-G. works full-time forNestec. R.R. works full-time for Abbott Nutrition.
No potential conflicts of interest relevant to thisarticle were reported.Author Contributions. J.M.Y. contributed todata extraction, statistical analyses, and writingthe first draft manuscript. J.E.K. contributed todata extraction and writing the first draft sum-mary tables. M.B. and A.G.-P. contributed toliterature extraction, statistics, and manuscriptrevision. E.H. contributed to data extraction andGRADE assessments. I.S. and I.G. contributed tostatistics and manuscript revision. E.M.v.d.B.,E.C.-G., S.H., and S.F.O. contributed to conceptand design, data extraction, and manuscriptreview. M.H. contributed to concept and designanddraftmanuscriptevaluation.K.L. contributedto concept and design, data extraction, andcritical review for intellectual content. L.P. con-tributed to concept and design and manuscriptreview. R.R., P.R., and H.R.M. contributed toconcept and design, data extraction, and revisingthe draft manuscript. L.v.L. contributed to dataextraction and draft summary tables. B.S. con-tributed to data extraction and critical reviewfor intellectual content. R.C. contributed to lit-erature extraction, statistical analyses, and re-vising the draftmanuscript. R.C. is the guarantorof this work and, as such, had full access to allthe data in the study and takes responsibilityfor the integrity of the data and the accuracy ofthe data analysis.Prior Presentation. Parts of this work werepresentedattheDiabetesUKNationalDiabetesinPregnancy Conference, Leeds, U.K., 14 Novem-ber 2017, and the XXIX National Congress ofthe Spanish Society of Diabetes, Oviedo, Spain,18–20 April 2018.
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