maternal obesity and risk of gestational diabetes mellitus

Maternal Obesity and Risk of GestationalDiabetes MellitusSUSAN Y. CHU, PHD, MSPH

1

WILLIAM M. CALLAGHAN, MD, MPH1

SHIN Y. KIM, MPH1

CHRISTOPHER H. SCHMID, PHD2

JOSEPH LAU, MD2

LUCINDA J. ENGLAND, MD, MSPH1

PATRICIA M. DIETZ, DRPH1

OBJECTIVE — Numerous studies in the U.S. and elsewhere have reported an increased riskof gestational diabetes mellitus (GDM) among women who are overweight or obese comparedwith lean or normal-weight women. Despite the number and overall consistency of studiesreporting a higher risk of GDM with increasing weight or BMI, the magnitude of the associationremains uncertain. This meta-analysis was conducted to better estimate this risk and to exploredifferences across studies.

RESEARCH DESIGN AND METHODS — We identified studies from three sources: 1)a PubMed search of relevant articles published between January 1980 and January 2006, 2)reference lists of publications selected from the PubMed search, and 3) reference lists of reviewarticles on obesity and maternal outcomes published between January 2000 and January 2006.We used a Bayesian model to perform the meta-analysis and meta-regression. We includedcohort-designed studies that reported obesity measures reflecting pregnancy body mass, that hada normal-weight comparison group, and that presented data allowing a quantitative measure-ment of risk.

RESULTS — Twenty studies were included in the meta-analysis. The unadjusted ORs ofdeveloping GDM were 2.14 (95% CI 1.82–2.53), 3.56 (3.05–4.21), and 8.56 (5.07–16.04)among overweight, obese, and severely obese compared with normal-weight pregnant women,respectively. The meta-regression analysis found no evidence that these estimates were affectedby selected study characteristics (publication date, study location, parity, type of data collection[retrospective vs. prospective], and prevalence of GDM among normal-weight women).

CONCLUSIONS — Our findings indicate that high maternal weight is associated with asubstantially higher risk of GDM.

Diabetes Care 30:2070–2076, 2007

G estational diabetes mellitus (GDM),or glucose intolerance that beginsor is first recognized during preg-

nancy, affects �7% of pregnancies, rep-resenting �200,000 cases annually in theU.S. (1). The risk of GDM is higher amongwomen who are obese, and the recentdramatic increase in obesity prevalence inthe U.S. mirrors a worrisome rise in theprevalence of GDM (2–4). Future indi-vidual health and societal medical costs

could be substantial as obesity and GDMnot only increase the risk of adverse preg-nancy and infant outcomes (5–7) but alsoare associated with a higher risk of devel-oping type 2 diabetes later in life in boththe mother and child (8–10).

Despite the number and consistencyof studies reporting a higher risk of GDMwith increasing body weight or BMI, themagnitude of this association remains un-certain. This is due in part to the wide

variation in reported GDM prevalenceamong different populations, as well asthe lack of consistency in diagnosticmethods and definitions for GDM (11).To provide a quantitative summary of theevidence, we conducted a meta-analysisof systematically identified studies thatexamined the association between mater-nal obesity and risk of GDM.

RESEARCH DESIGN ANDMETHODS

Search processUsing recommendations from the Meta-analysis of Observational Studies in Epi-demiology (MOOSE) guidelines (12), weidentified studies for possible inclusion inthis analysis using three sources. First, wesearched PubMed from January 1980 toJanuary 2006 using the following criteria:(overweight or obesity or BMI or bodymass index or weight gain) AND (preg-nancy or prepregnancy) AND (risks or ef-fects or complications).

From this search, the full text was re-trieved for abstracts that mentioned a re-lationship between maternal obesity andpregnancy complications from a case-control or cohort study. Studies that re-ported GDM as an outcome wereincluded for consideration. Studies thatdid not have the full text in English weretranslated for review.

Second, we manually reviewed thereference lists of the publications previ-ously retrieved and obtained the entiretext of studies that potentially could beincluded in the meta-analysis. Finally, weobtained review articles on obesity andmaternal outcomes published betweenJanuary 2000 and January 2006 andsearched their reference lists for addi-tional potential studies. If there were mul-tiple papers on GDM from the same studypopulation, we only included the mostcurrent publication. We did not attemptto locate any unpublished studies.

Studies that were considered poten-tially eligible were then screened for in-clusion in the pooled analysis if they metthe following criteria: 1) obesity measures(maternal weight, percent over idealweight, and BMI) reflected status preced-ing any significant pregnancy weight gain(i.e., was measured or reported prepreg-

● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ● ●

From the 1Division of Reproductive Health, Centers for Disease Control and Prevention, Atlanta, Georgia;and the 2Institute for Clinical Research and Health Policy Studies, Tufts-New England Medical Center,Boston, Massachusetts.

Address correspondence and reprint requests to Susan Y. Chu, Centers for Disease Control and Preven-tion, Mailstop K-23, 1600 Clifton Rd., Atlanta, GA 30333. E-mail: [email protected].

Received for publication 18 December 2006 and accepted in revised form 25 March 2007.Published ahead of print at http://care.diabetesjournals.org on 6 April 2007. DOI: 10.2337/dc06-2559a.The findings and conclusions in this report are those of the authors and do not necessarily represent the

views of the Centers for Disease Control and Prevention.Abbreviations: GDM, gestational diabetes mellitus.A table elsewhere in this issue shows conventional and Systeme International (SI) units and conversion

factors for many substances.© 2007 by the American Diabetes Association.The costs of publication of this article were defrayed in part by the payment of page charges. This article must therefore be hereby

marked “advertisement” in accordance with 18 U.S.C. Section 1734 solely to indicate this fact.

P a t h o p h y s i o l o g y / C o m p l i c a t i o n sO R I G I N A L A R T I C L E

2070 DIABETES CARE, VOLUME 30, NUMBER 8, AUGUST 2007

nancy or during the first trimester or firstprenatal visit), 2) there was a comparisongroup of normal-weight women, and 3)data were presented in tables, figures, orthe text that allowed for a quantitativemeasurement of obesity and risk of GDM.

Data abstractionAll articles were read and abstracted bytwo reviewers using the same structureddata form. A final abstraction was com-piled from the two forms after correctionor resolution of any differences betweenthe reviewers. Abstracted information in-cluded study design, setting, location,time period, number and characteristicsof study subjects, the source and catego-rization of obesity measures, the diagnos-tic criteria and the source(s) for GDM(e.g., medical records, clinical databases),and statistical methods, including adjust-ment factors.

Statistical analysisFor each study, we constructed separatetwo-by-two tables to calculate the oddsratios (ORs) and 95% CIs of GDM foreach BMI/weight category analyzed (i.e.,overweight, obese, and severely obeseversus normal BMI/weight, respectively).Because about two-thirds of the studiesdid not present adjusted ORs, only crudeORs were used in the primary meta-analysis. However, we also performedsensitivity analyses, combining adjustedORs when available. The BMI/weight cat-egories used varied somewhat among thestudies. In general, we used the BMI/weight categories for normal, overweight,obese, and severely obese as defined byeach study (Table 1); in two studies, nar-row intervals were collapsed into group-ing that more appropriately fit overweight,obese, and severely obese categories(e.g., 19.8–22.0 and 22.1–24.9 were com-bined into one 19.8–24.9 normal-weightcategory).

Sources for information on prepreg-nancy BMI/weight, GDM, and other vari-ables varied among studies but mostfrequently were medical records or clini-cal databases (Table 1). Diagnostic criteriafor GDM varied among the studies andwere based on the following: Fourth In-ternational Workshop Conference onGDM (n � 3) (11), National DiabetesData Group (n � 4) (13), Carpenter andCoustan (n � 2) (14), and other pub-lished criteria (n � 4) (15–17); sevenstudies did not specify criteria used forGDM diagnosis.

Meta-analyses combining ORs

across studies were conducted usingboth DerSimonian-Laird and Bayesianrandom-effects models (18,19), both ofwhich incorporate within- and be-tween-study variances. In addition, theBayesian model incorporates uncer-tainty in the between-study variance,which gives slightly wider CIs. Becausethe point estimates of the two modelswere similar, we chose to use the moreconservative Bayesian estimates.

The Bayesian model assumes that thecounts in the exposed and unexposedgroups follow binomial distributions withdifferent mean probabilities. These meansare modeled on the logit scale so that theirdifference represents the logOR and thusis a hierarchical logistic regression model.The mean and variance of the logOR arerandom variables in the Bayesian model.To represent our lack of prior knowledgeabout the value of these hyperparameters,we used diffuse priors that encompassed awide range of possible values. For meansand regression coefficient parameters,these were normal distributions withmean 0 and extremely large variance 107;for the variance parameters, we used in-verse � (1.0, 0.1) distributions. To com-pute the Bayesian estimates, we used aMarkov chain Monte Carlo algorithmrunning three parallel chains and moni-toring convergence with the Gelman-Rubin diagnostic (20). On convergence,which generally occurred within 1,000runs, we saved 15,000 samples from eachchain to estimate posterior distributionsof model parameters. The Markov chainMonte Carlo algorithm used is describedin greater detail by Schmid et al. (19).

We also conducted a Bayesian meta-regression analysis to assess whether therelationship between obesity and GDMvaried by certain study characteristics. Inthese models, the logORs are related tothe study characteristics by a linear re-gression model. These included date ofpublication (1985–1999, 2000–2003, or2004–2006), study location (U.S. versusall others), type of data collection (pro-spective versus retrospective), and GDMprevalence (as a percentage) in the studypopulation.

RESULTS — The PubMed searchidentified 7,327 studies; 142 abstractsreported a finding on the relationshipbetween maternal obesity and preg-nancy complications from a case-control or cohort study, and the full textof these articles were retrieved for de-tailed examination. Of the retrieved ar-

ticles, 40 studies mentioned GDM as anoutcome. Because only three case-control studies (GDM case versus no-GDM control) were identified, weexcluded those studies and only in-cluded those with a cohort design, leav-ing a total of 37 studies from thePubMed search to be screened for inclu-sion. After reviewing the reference listsof the 142 studies retrieved, we identi-fied another 16 studies for possible in-clusion. Three additional studies wereidentified from our examination of re-cent review article reference lists. Of thetotal 56 studies screened for final inclu-sion in the meta-analysis, 36 studies wereexcluded because the BMI or weight mea-sure did not reflect prepregnancy status(n � 12), there was no normal-weightcomparison group or overweight andobese groups were combined (n � 15), ordata were not presented in a way to allowthe construction of appropriate two-by-two tables (n � 9).

A total of 20 studies were included inthe meta-analysis; of these, 15, 18, and 7presented data for overweight, obese, andseverely obese pregnant women, respec-tively, compared with normal-weightpregnant women (21–40). Eight studieswere conducted in the U.S.; the remain-der were from Canada, Australia, Italy,France, United Arab Emirates, Israel, Fin-land, Nova Scotia, and the U.K. (Table 1).Five of the studies were prospectively de-signed. GDM prevalence varied amongthe studies, ranging from 1.3 to 19.9%;the higher rates were among studies thatincluded high-risk populations (e.g.,Cree Native Indians) or were not popula-tion based.

Based on our meta-analysis, the un-adjusted ORs of developing GDM were2.14 (95% CI 1.82–2.53), 3.56 (3.05–4.21), and 8.56 (5.07–16.04) amongoverweight, obese, and severely obesewomen, respectively, compared with nor-mal-weight pregnant women. None of thecovariates in the meta-regression analysis(study year [�2000, 2000 –2003, or2004–2005], study design [prospectiveor retrospective], geographic location[U.S., non-U.S.], or rate of GDM in thestudy population) were significant.

CONCLUSIONS — Based on meta-analysis of the literature, we estimatethat the risk of developing GDM isabout two, four, and eight times higheramong overweight, obese, and severelyobese women, respectively, comparedwith normal-weight pregnant women.

Chu and Associates

DIABETES CARE, VOLUME 30, NUMBER 8, AUGUST 2007 2071

Tab

le1—

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tics

ofco

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ount

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peri

od

GD

Mpr

eval

ence

(%)

Coh

ort

size

BMI/

wei

ght

cate

gori

es(k

g/m

2)

Nor

mal

Ove

rwei

ght

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seSe

vere

lyob

ese

Baet

en,2

001

U.S

.Pr

ospe

ctiv

eco

hort

from

birt

hce

rtifi

cate

reco

rds,

1992

–199

62.

196

,801

20–2

4.9

25–2

9.9

�30

NA

Berk

owit

z,19

92U

.S.

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pect

ive

coho

rtfr

omm

edic

alce

nter

data

base

,198

7–19

893.

210

,187

�27

.327

.3–3

2.2

�32

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ABi

anco

,199

8U

.S.

Ret

rosp

ecti

veco

hort

from

med

ical

cent

erpe

rina

tald

atab

ase,

1988

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54.

811

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925

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Maternal obesity and risk of GDM


The public health implications for theU.S. are significant because of the highprevalence of obesity, increasing preva-lence of GDM, and the potential adverseconsequences associated with obesityand GDM, including higher risk of ad-verse infant outcomes, higher risk of di-abetes for the mother later in life, and ahigher risk of diabetes and overweightfor the offspring.

Fetal macrosomia is a common ad-verse infant outcome related to GDM, es-pecially if GDM is unrecognized anduntreated (5,7,41– 43). For the infant,macrosomia increases the risks of shoul-der dystocia, clavical fractures, and bra-chial plexus injury and is also associatedwith depressed 5-min Apgar scores andincreased rates of admission to neonatalintensive care unit (44). For the mother,the primary risk associated with macroso-mia is an increased risk of cesarean deliv-ery; these mothers also have an increasedrisk of postpartum hemorrhage and vagi-nal lacerations (42).

Also of concern is the finding fromseveral longitudinal studies that infants ofwomen with GDM are at increased risk ofbecoming overweight or obese as youngchildren and adolescents (45–47) and aremore likely to develop type 2 diabeteslater in life (48–50). It has been suggestedthat the relationship between decreasedinsulin sensitivity and excessive fetalgrowth in obese women and women with

GDM may explain some of the increasedincidence of obesity and glucose intoler-ance in their offspring (51). Some of thisassociation is likely explained by otherfactors associated with maternal obesity,such as shared genetic factors or similardietary and physical activity behaviors infamilies (9); however, if this associationdoes prove causal, an increasing GDMprevalence could further elevate type 2diabetes rates in future generations.

An increase in GDM prevalence alsohas implications for prevention of type 2diabetes in women who have had GDM.Because �50% of women with a historyof GDM develop diabetes within 5–10years after delivery (10), the postpartumperiod offers an opportunity to bothscreen women at an early stage for preex-isting diabetes and to counsel womenabout type 2 diabetes prevention. Boththe American College of Obstetriciansand Gynecologists and the American Di-abetes Association have recommendedfollow-up glucose testing of women witha history of GDM (52,53). However, cur-rent postpartum GDM screening rates arelow (54–56), resulting in many missedopportunities for counseling and treat-ment of women who are at high risk fortype 2 diabetes. Improving postpartumfollow-up rates will require a better un-derstanding of patient, provider, andhealth care system barriers to postpartumscreening (56).

There are several possible biases toconsider in our analysis. First, the studiesincluded in this meta-analysis used vary-ing weight and BMI categories for normal,overweight, obese, and severely obesewomen; thus, the pooled estimate doesnot exactly reflect the same comparisonfor all studies. In addition, because of thedifferent BMI/weight categories and dif-ferent diagnostic criteria used for GDM,there is likely some misclassification ofthe exposure and the outcome; if signifi-cant, the findings would be biased towarda null result or cause significant heteroge-neity in the meta-analysis model. The ORsfor the comparisons between normal-weight and overweight and obese women,respectively, were fairly consistent amongthe studies, suggesting that the varied def-initions of exposure and outcome did nothave major effects on these findings (Figs.1 and 2). Results were more disparate inthe comparison between normal-weightand severely obese women (Fig. 3). Al-though there is clearly a positive associa-tion between severe obesity and GDM, themagnitude of the association variedwidely among studies. Hence, there is lessconfidence in this summary measure thanfor the other comparisons; however, thetwo outlying ORs were from studies withthe smallest sample sizes.

A second limitation is that studies didnot or could not (e.g., birth registries)specify whether all pregnant women were

0.01 0.1 1 10 1000.02 0.05 0.2 0.5 2 5 20 50

Odds Ratio 95% CI

Study Year N

Baeten 2001 67535

Berkowitz 1992 5681

Brennand 2005 307

Callaway 2006 9325

DiCianni 2003 3627

Dyck 2002 971

Dye 1997 8275

Galtier 1995 102

Harris 1997 505

Oguntemi 1998 301

Raatikainen 2006 23721

Ramos 2005 15128

Rosenberg 2003193690

Sebire 2001247937

Solomon 1997 10790

Overall 587895

Figure 1—Association of GDM with overweight versus normal maternal BMI.

Chu and Associates


screened for GDM or if screening wasdone based on a risk profile (e.g., previ-ous adverse pregnancy outcome). Risk-based screening could bias our findings ifscreening was done preferentially onoverweight or obese women comparedwith normal-weight women. However,because recommended risk-based screen-ing for GDM excludes relatively fewwomen, as a practical matter, cliniciansroutinely screen all pregnant women forGDM (52). However, we were not able toaccount for differences in screening prac-tices, if they exist.

Third, because not all studies pre-sented adjusted odds and adjustment fac-tors varied among those that did, we onlyused crude study estimates in our meta-

analysis. If there were strong effects fromconfounding factors (e.g., maternal age isassociated with both increased bodyweight and risk of GDM), the estimatesincluded in the meta-analysis might be bi-ased. When we did a separate meta-analysis pooling studies that providedadjusted ORs, the summary adjusted ORswere lower than the unadjusted estimates,although they were still of substantialmagnitude (overweight vs. normal ad-justed OR 1.86 [95% CI 1.22–2.78],obese vs. normal adjusted 3.34 [2.43–4.55], and severely obese vs. normal ad-justed 5.77 [3.60 –9.39]). Finally, ourfindings may be biased because publishedstudies do not represent all studies everdone on a particular subject and because

statistically significant results are morelikely to be submitted and published thannonsignificant and null results (57). Ifstudy publication bias were strong, wewould overestimate the risk of GDM withincreasing BMI.

In summary, our findings suggest thatGDM risk increases substantially with in-creasing maternal BMI. The increasingprevalence of obesity and related condi-tions such as GDM and type 2 diabetes inthe U.S. are already changing predictionsof the cost of medical care in the future(58,59). Preventing GDM depends onpreventing obesity in young women; pre-venting type 2 diabetes in obese womenwho have GDM depends on effective nu-trition and physical activity interventions

0.01 0.1 1 10 1000.02 0.05 0.2 0.5 2 5 20 50

Odds Ratio 95% CI

Study Year N

Baeten 2001 59828Berkowitz 1992 5268Bianco 1998 11926Brennand 2005 435Callaway 2006 8122DiCianni 2003 3328Dyck 2002 882Dye 1997 7876Galtier 1995 88Harris 1997 431Michlin 2000 334Oguntemi 1998 426Raatikainen 2006 22213Ramos 2005 15537Robinson 2005 88360Rosenberg 2003 148829Sebire 2001 208199Solomon 9485

Overall 591567

Figure 2—Association of GDM with obese versus normal maternal BMI.

0.01 0.1 1 10 1000.02 0.05 0.2 0.5 2 5 20 50

Odds Ratio 95% CI

Study Year N

Callaway 2006 6691

Dye 1997 7858

Galtier 1995 84

Grossetti 2004 2498

Kumari 2001 488

Robinson 2005 79784

Rosenberg 2003136347

Overall 233750

Figure 3—Association of GDM with severely obese versus normal maternal BMI.



that produce weight loss. These and otherprevention strategies, aimed at both indi-vidual and societal levels, are needed tocontrol the growing epidemic of diabetes.

Acknowledgments— We thank Carol Bruce,RN, MPH, for her support and helpful input.

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