Cos Son 2015
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Please cite this article in press as: Cosson E, et al. Pregnancy adverse outcomes related to pregravid body mass index and gestational weight gain, according to the presence or not of gestational diabetes mellitus: A retrospective observational study. Diabetes Metab (2015), http://dx.doi.org/10.1016/j.diabet.2015.06.001 ARTICLE IN PRESS +Model DIABET-702; No. of Pages 9 Available online at ScienceDirect www.sciencedirect.com Diabetes & Metabolism xxx (2015) xxx–xxx Original article Pregnancy adverse outcomes related to pregravid body mass index and gestational weight gain, according to the presence or not of gestational diabetes mellitus: A retrospective observational study E. Cosson a,b,∗ , C. Cussac-Pillegand a , A. Benbara c , I. Pharisien c , M.T. Nguyen a , S. Chiheb a , P. Valensi a , L. Carbillon c a Department of Endocrinology-Diabetology-Nutrition, CRNH-IdF, CINFO, Paris 13 University, Sorbonne Paris Cité, Jean-Verdier Hospital, AP–HP, Bondy, France b Sorbonne Paris Cité, UMR U1153 Inserm, U1125 Inra, Cnam, Université Paris 13, Bobigny, France c Department of Obstetrics and Gynecology, Paris 13 University, Sorbonne Paris Cité, Jean-Verdier Hospital, AP–HP, Bondy, France Received 6 February 2015; received in revised form 1 st June 2015; accepted 2 June 2015 Abstract Aim. – This study retrospectively evaluated the complications associated with prepregnancy overweight (OW) or obesity (OB) and gestational weight gain (GWG) in women with or without universally screened and treated gestational diabetes mellitus (GDM). Methods. – A total of 15,551 non-Asian women without pregravid diabetes or hypertension who delivered singleton babies (2002–2010) were classified according to GDM (13.5%), pregestational body mass index (BMI; normal range: 18.5–24.9 kg/m 2 ), OW (26.2%), OB (13.9%; BMI ≥ 30 kg/m 2 ) and GWG (< 7 kg: 32%; 7–11.5 kg: 37%; 11.6–16 kg: 23%; > 16 kg: 8%). Main outcome measures were large/small for gestational age (LGA/SGA), caesarean section, preeclampsia, preterm delivery and shoulder dystocia. Results. – GDM was associated with more LGA babies [Odds Ratio (OR): 2.12, 95% confidence interval (CI): 1.85–2.43], caesarean section (OR: 1.49, 95% CI: 1.34–1.65) and preeclampsia (OR: 1.59, 95% CI: 1.21–2.09). OW/OB and GWG were associated with LGA infants whatever the GDM status, and with SGA babies only in women without GDM. LGA status was independently associated with GWG in women with GDM (11.6–16 kg: OR: 1.74, 95% CI: 1.49–2.03 and > 16 kg OR: 3.42, 95% CI: 2.83–4.13 vs 7–11.5 kg) and in women without GDM (OR: 2.14, 95% CI: 1.54–2.97 or OR: 2.65, 95% CI: 1.68–4.17, respectively), and with BMI only in women without GDM (OR: 1.12, 95% CI: 1.00–1.24, per 10 kg/m 2 ). SGA status was independently associated with OW (OR: 0.86, 95% CI: 0.77–0.98), OB (OR: 0.84, 95% CI: 0.72–0.98) and GWG < 7 kg (1.14, 95% CI: 1.01–1.29) only in women without GDM. Conclusion. – In our European cohort and considering the triumvirate of GDM, BMI and GWG, GDM was the main contributor to caesarean section and preeclampsia. OW/OB and GWG contributed to LGA and SGA infants mainly in women without GDM. © 2015 Elsevier Masson SAS. All rights reserved. Keywords: Gestational diabetes mellitus; Gestational weight gain; Obesity; Pregnancy; Prognosis Abbreviations: GWG, Gestational weight gain; IOM, Institute of Medicine; HAPO, Hyperglycaemia and Adverse Pregnancy Outcomes; IADPSG, Interna- tional Association of Diabetes and Pregnancy Study Groups; LGA, large for gestational age; SGA, small for gestational age. ∗ Corresponding author at: Department of Endocrinology-Diabetology- Nutrition, hôpital Jean-Verdier, avenue du 14-juillet, 93143 Bondy cedex, France. Tel.: +33 148 02 65 80; fax: +33 148 02 65 79. E-mail address: [email protected] (E. Cosson). 1. Introduction Gestational diabetes mellitus (GDM) is defined as any degree of glucose intolerance with onset or first recognition during pregnancy, and is associated with adverse outcomes during pregnancy [1]. Obesity has a growing prevalence in women of childbearing age [2] and is a confounding factor. First, it is a risk factor for GDM [2,3]. Second, it shares complications with GDM, such as large-for-gestational-age (LGA) infants http://dx.doi.org/10.1016/j.diabet.2015.06.001 1262-3636/© 2015 Elsevier Masson SAS. All rights reserved.
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Diabetes & Metabolism xxx (2015) xxx–xxx
Original article
Pregnancy adverse outcomes related to pregravid body mass index andgestational weight gain, according to the presence or not of gestational
diabetes mellitus: A retrospective observational study
E. Cosson a,b,∗, C. Cussac-Pillegand a, A. Benbara c, I. Pharisien c, M.T. Nguyen a, S. Chiheb a,P. Valensi a, L. Carbillon c
a Department of Endocrinology-Diabetology-Nutrition, CRNH-IdF, CINFO, Paris 13 University, Sorbonne Paris Cité, Jean-Verdier Hospital, AP–HP, Bondy,France
b Sorbonne Paris Cité, UMR U1153 Inserm, U1125 Inra, Cnam, Université Paris 13, Bobigny, Francec Department of Obstetrics and Gynecology, Paris 13 University, Sorbonne Paris Cité, Jean-Verdier Hospital, AP–HP, Bondy, France
Received 6 February 2015; received in revised form 1st June 2015; accepted 2 June 2015
bstract
Aim. – This study retrospectively evaluated the complications associated with prepregnancy overweight (OW) or obesity (OB) and gestationaleight gain (GWG) in women with or without universally screened and treated gestational diabetes mellitus (GDM).Methods. – A total of 15,551 non-Asian women without pregravid diabetes or hypertension who delivered singleton babies (2002–2010)
ere classified according to GDM (13.5%), pregestational body mass index (BMI; normal range: 18.5–24.9 kg/m2), OW (26.2%), OB (13.9%;MI ≥ 30 kg/m2) and GWG (< 7 kg: 32%; 7–11.5 kg: 37%; 11.6–16 kg: 23%; > 16 kg: 8%). Main outcome measures were large/small for gestationalge (LGA/SGA), caesarean section, preeclampsia, preterm delivery and shoulder dystocia.
Results. – GDM was associated with more LGA babies [Odds Ratio (OR): 2.12, 95% confidence interval (CI): 1.85–2.43], caesarean sectionOR: 1.49, 95% CI: 1.34–1.65) and preeclampsia (OR: 1.59, 95% CI: 1.21–2.09). OW/OB and GWG were associated with LGA infants whateverhe GDM status, and with SGA babies only in women without GDM. LGA status was independently associated with GWG in women with GDM11.6–16 kg: OR: 1.74, 95% CI: 1.49–2.03 and > 16 kg OR: 3.42, 95% CI: 2.83–4.13 vs 7–11.5 kg) and in women without GDM (OR: 2.14, 95%I: 1.54–2.97 or OR: 2.65, 95% CI: 1.68–4.17, respectively), and with BMI only in women without GDM (OR: 1.12, 95% CI: 1.00–1.24, per0 kg/m2). SGA status was independently associated with OW (OR: 0.86, 95% CI: 0.77–0.98), OB (OR: 0.84, 95% CI: 0.72–0.98) and GWG < 7 kg1.14, 95% CI: 1.01–1.29) only in women without GDM.
Conclusion. – In our European cohort and considering the triumvirate of GDM, BMI and GWG, GDM was the main contributor to caesarean
ection and preeclampsia. OW/OB and GWG contributed to LGA and SGA infants mainly in women without GDM.2015 Elsevier Masson SAS. All rights reserved.
eywords: Gestational diabetes mellitus; Gestational weight gain; Obesity; Pregnancy; Prognosis
Please cite this article in press as: Cosson E, et al. Pregnancy adverseweight gain, according to the presence or not of gestational diabetes mehttp://dx.doi.org/10.1016/j.diabet.2015.06.001
Abbreviations: GWG, Gestational weight gain; IOM, Institute of Medicine;APO, Hyperglycaemia and Adverse Pregnancy Outcomes; IADPSG, Interna-
ional Association of Diabetes and Pregnancy Study Groups; LGA, large forestational age; SGA, small for gestational age.∗ Corresponding author at: Department of Endocrinology-Diabetology-utrition, hôpital Jean-Verdier, avenue du 14-juillet, 93143 Bondy cedex,rance. Tel.: +33 148 02 65 80; fax: +33 148 02 65 79.
E-mail address: [email protected] (E. Cosson).
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http://dx.doi.org/10.1016/j.diabet.2015.06.001262-3636/© 2015 Elsevier Masson SAS. All rights reserved.
. Introduction
Gestational diabetes mellitus (GDM) is defined as any degreef glucose intolerance with onset or first recognition duringregnancy, and is associated with adverse outcomes during
outcomes related to pregravid body mass index and gestationalllitus: A retrospective observational study. Diabetes Metab (2015),
regnancy [1]. Obesity has a growing prevalence in womenf childbearing age [2] and is a confounding factor. First, it is
risk factor for GDM [2,3]. Second, it shares complicationsith GDM, such as large-for-gestational-age (LGA) infants
ARTICLE IN PRESS+ModelDIABET-702; No. of Pages 9
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4–11], caesarean section [4,5,7,8,11,12], hypertensive disor-ers [4,5,7,8] and, in certain studies, shoulder dystocia [5].lso, gestational weight gain (GWG) appears to be crucial
5,8–10,13,14].To date, only five recent studies, four from the United States
5,10,15,16] and only one from Europe [9], have explored thempact of GDM, obesity and GWG together. Some limitations
ay affect these observational studies. First, the prevalencef GDM is sometimes very low [9,16] with screening whichight not have been universal [5,10,15,16]. Second, womenith pregravid diabetes and hypertension were not excluded
5,9,10,15,16], whereas these conditions are often associatedith overweight and obesity. Therefore, considering womenith ‘isolated obesity’ might better evaluate the role of obesityer se [12]. Regarding body mass index (BMI), underweightomen are not always considered separately [5,16] nor is the
ower BMI cutoff point in Asian women [17] taken into accounto define overweight and obesity [5,9]. Finally, excessive GWG9,10], determined according to pregravid BMI status as pro-osed by the Institute of Medicine (IOM) [18] rather than GWGer se, has often been considered and is an additional confound-ng factor.
Dietary advice and drugs are generally provided only toomen with GDM, as GWG [5,8–10,13,14], treatment modal-
ties and glycaemic levels achieved can modify the outcomes19]. Only the Hyperglycaemia and Adverse Pregnancy Out-omes (HAPO) study reported obesity-related adverse eventsndependently of glycaemic status and its treatment [4,7]. How-ver, in that study, BMI was measured at the time of oral glucoseolerance tests at between 24 and 32 weeks of gestation, and notefore pregnancy. Therefore, GWG could not be assessed.
Given this context, a large multiethnic European cohort ofon-Asian women who delivered singleton babies and wereithout pregravid diabetes or hypertension was selected forur present retrospective observational study. In this cohort, thedverse outcomes related to ‘isolated’ overweight, obesity andWG were investigated in women with and without universally
creened and treated GDM.
. Methods
.1. Participants, GDM screening and care
A total of 20,653 women delivered at our hospital betweenanuary 2002 and December 2010. Data are routinely entered atirth for all women (no exceptions) giving birth at our universityospital by the midwife assisting at the delivery, then checkednd collected during the maternity stay by a midwife quali-ed in data management and storage (I.P.), with no interactionsith the women themselves. The authors did not have access to
dentification of patients’ information prior to anonymization.he purposes of the database are to assess the overall qualityf obstetric care and to regularly update medical management
Please cite this article in press as: Cosson E, et al. Pregnancy adversweight gain, according to the presence or not of gestational diabetes mehttp://dx.doi.org/10.1016/j.diabet.2015.06.001
rotocols. The data are retrospective and observational, witho need for either approval by an ethics committee/institutionaleview board or patients’ written informed consent. The patients’ecords/information are anonymous, and the database is declared
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o the French data protection authority (Commission nationalee l’informatique et des libertés [CNIL]).
In the present study, women with known diabetes (n = 204),revious hypertensive disorders (n = 448) and multiple pregnan-ies (n = 378) were not included. Furthermore, women whoserepregnancy BMI (n = 1669) and GWG (n = 2) were unknownere also not included. Finally, those also excluded were women
rom Asia (n = 628) or India/Pakistan/Sri Lanka (n = 1076), andhose with a BMI < 18.5 kg/m2 (n = 687).
Thus, 15,551 pregnancies were analyzed. Definitions of ourarameters did not change over the 9 years of the study. BMI wasalculated from self-reported pregravid weight and measuredeight during pregnancy, using the following formula: weightin kg) divided by the height (in m) squared. Women were clas-ified as normal weight, overweight and obese when their BMIas 18.5–24.9 kg/m2, 25.0–29.9 kg/m2 and ≥ 30 kg/m2, respec-
ively [17]. GWG categories (< 7 kg, 7.0–11.5 kg, 11.6–16 kgnd > 16 kg) were defined according to the usual thresholdsroposed by IOM guidelines for overweight women (optimalWG: 7–11.5 kg) and normal-weight women (optimal GWG:1.6–16 kg) [18].
GDM was assessed using a one-step screening and diagnos-ic test, which always comprised a 75-g oral glucose toleranceest [2,20,21]. GDM was defined as a fasting plasma glucosealue ≥ 5.3 mmol/L (the same fasting plasma glucose target asn previous French recommendations) and/or a 2-h blood glu-ose value ≥ 7.8 mmol/L (World Health Organization criteria)2,20,21]. One-step screening was chosen to limit the numberf participants lost to follow-up, as our study population was cha-acterized by widespread geographical origins [21]. Screeningas specifically prescribed during the hospital routine follow-upisit and then performed out of hospital. As is usual for epidemi-logical studies, the women without screening were consideredo be without GDM [2,9,10,15].
Women who were overweight or obese had no specificollow-up unless they were diagnosed with GDM. All womenith such a diagnosis were referred to a multidisciplinary
eam, which included a diabetologist, obstetrician, midwife,ietitian and nurse educator. These women received individ-alized dietary advice, were instructed on how to performelf-monitoring of blood glucose levels six times a day, andisited the diabetologist every two to four weeks. Insulin ther-py was started if fasting and 2-h postprandial glucose levelsere > 5.3 mmol/L and > 6.8 mmol/L, respectively. Antenatalisits were scheduled for every two to four weeks up to 34 weeks,nd weekly thereafter, with cardiotocography and assessment ofmniotic fluid volume [2,21].
.2. Prognosis
The following outcomes were considered: LGA or SGAbirth weight > 90th percentile or < 10th percentile, respectively,f the general French population) [22]; caesarean section;
e outcomes related to pregravid body mass index and gestationalllitus: A retrospective observational study. Diabetes Metab (2015),
reeclampsia (blood pressure ≥ 140/90 mmHg on two measure-ents taken 4 h apart and proteinuria ≥ 300 mg/24 h or 3+ orore on dipstick testing of a random urine sample); preterm
elivery (before 37 full weeks); and shoulder dystocia, defined
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Table 1Maternal characteristics and complications by gestational diabetes mellitus (GDM) status and pregravid body mass index (BMI).
Total cohort(n = 15,551)
No GDM(n = 13,436)
GDM(n = 2097)
ANOVA,P
Normalweight(n = 9317)
Overweight(n = 4075)
Obesity(n = 2159)
ANOVA,P
CharacteristicsPregravid BMI (kg/m2) 24.6 ± 4.7 24.6 ± 4.7 24.9 ± 4.8 < 0.001 21.6 ± 1.6 26.6 ± 1.4a 33.6 ± 4.0a,b < 0.001BMI classification < 0.01 –
Normal weight (%) 9317 (59.9) 8127 (60.4) 1190 (56.7) – – –Overweight (%) 4075 (26.2) 3489 (25.9) 586 (27.9) – – –Obesity (%) 2159 (13.9) 1838 (13.7) 321 (15.3) – – –
Age (years) 29.7 ± 5.8 29.6 ± 5.8 30.6 ± 5.8 < 000.1 29.7 ± 5.9 29.9 ± 5.8 29.7 ± 5.9 NSParity (n) 2.1 ± 1.3 2.0 ± 1.3 2.2 ± 1.4 < 000.1 2.0 ± 1.2 2.1 ± 1.3a 2.2 ± 1.4a < 0.001Multiparity (%) 9045 (58.2) 7728 (57.4) 1317 (62.8) < 000.1 5315 (57.0) 2426 (59.5)a 1304 (60.4)a < 0.01Maternal smoking
Before pregnancy (%) 2243 (14.4) 1994 (14.8) 249 (11.9) < 000.1 1421 (15.3) 526 (12.9)a 296 (13.7) < 0.001During pregnancy (%) 1503 (9.7) 1352 (10.0) 151 (7.2) < 000.1 946 (10.2) 344 (8.4)a 213 (9.9) < 0.01
Ethnicity < 000.1 < 0.01Caucasian (%) 9881 (63.5) 8434 (62.7) 1447 (69.0) 5998 (64.4) 2530 (62.1) 1353 (62.7)Sub-Saharan African (%) 3566 (22.9) 3181 (23.6) 385 (18.4) 2058 (22.1) 1020 (25.0) 488 (22.6)Caribbean (%) 1365 (8.8) 1196 (8.9) 169 (8.1) 817 (8.8) 324 (8.0) 224 (10.4)Other (%) 739 (4.8) 643 (4.8) 96 (4.6) 444 (4.8) 201 (4.9) 94 (4.4)
Family history of diabetes (%) 3227 (20.8) 2718 (20.2) 509 (24.3) < 000.1 1950 (20.9) 833 (20.4) 444 (20.6) NSPrevious pregnancy with macrosomia (%) 457 (2.9) 366 (2.7) 91 (4.3) < 000.1 266 (2.9) 124 (3.0) 27 (3.1) NSPrevious pregnancy with GDM (%) 498 (3.2) 268 (2.0) 230 (11.0) < 000.1 276 (3.0) 136 (3.3) 86 (4.0)a < 0.05
EventsGDM (%) 2097 (13.5) – – – 1190 (12.8) 586 (14.4)a 321 (14.9)a < 0.01Gestational weight gain (kg) 8.9 ± 5.7 9.0 ± 5.7 8.5 ± 5.5 < 000.1 9.1 ± 5.6 8.8 ± 5.6 8.5 ± 5.8a < 0.001Gestational weight gain classification < 0.01 < 0.001
< 7 kg (%) 5041 (32.4) 4272 (31.8) 769 (36.7) 2902 (31.1) 1362 (33.4) 777 (32.4)7–11.5 kg (%) 5695 (36.6) 4945 (36.8) 750 (35.8) 3481 (37.4) 1471 (36.1) 743 (29.6)11.6–16 kg (%) 3586 (23.1) 3149 (23.4) 437 (20.8) 2180 (23.4) 929 (22.8) 477 (22.1)> 16 kg (%) 1229 (7.9) 1088 (8.1) 141 (6.7) 754 (8.1) 313 (7.7) 162 (7.5)
Large-for-gestational-age babies (%) 1341 (8.6) 1028 (7.6) 313 (14.9) < 000.1 778 (8.4) 361 (8.9) 202 (9.4) NSSmall-for-gestational-age babies (%) 2114 (13.6) 1837 (13.7) 277 (13.1) NS 1332 (14.3) 517 (12.7)a 123 (13.9)a < 0.01Caesarean section (%) 3265 (21.0) 2696 (20.0) 569 (27.1) < 000.1 1944 (20.9) 863 (21.2) 458 (21.2) NSPreeclampsia (%) 335 (2.2) 269 (2.0) 66 (3.1) < 000.1 185 (2.0) 88 (2.2) 62 (2.9)a < 0.05Preterm delivery (%) 1207 (7.8) 1032 (7.7) 175 (8.3) NS 733 (7.9) 296 (7.3) 178 (8.2) NSShoulder dystocia (%) 231 (1.5) 193 (1.4) 38 (1.8) NS 137 (1.5) 59 (1.4) 35 (1.6) NS
Data are presented as means ± SD or as n (%); NS: not significant.a P < 0.05 vs women with BMI 18.5–24.9 kg/m2.
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s the use of obstetric manoeuvres (such as a McRoberts epi-iotomy after delivery of the fetal head, suprapubic pressure,osterior arm rotation to an oblique angle, rotation of the infanty 180 degrees and delivery of the posterior arm) [23].
.3. Statistical analyses
Continuous variables were expressed as means ± SD, andompared by one-way analysis of variance (ANOVA) or theann–Whitney U test as adequate. The significance of differ-
nces in proportions was tested with the Chi2 test. Logisticegression was used for analyses of BMI and GWG effects onGA and SGA infants, caesarean section and preeclampsia in
Please cite this article in press as: Cosson E, et al. Pregnancy adverseweight gain, according to the presence or not of gestational diabetes mehttp://dx.doi.org/10.1016/j.diabet.2015.06.001
omen with and without GDM. Logistic regression was alsosed for multivariate analyses based on a model including factorsssociated with LGA and then SGA, with a P value < 0.10 on uni-ariate analyses. All statistical analyses were carried out using
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PSS software (SPSS, Chicago, IL, USA). The 0.05 probabilityevel was considered statistically significant.
. Results
.1. Characteristics of the study population
Maternal characteristics are shown in Table 1. In summary,he women were 29.7 ± 5.8 years old, and their mean parityas 2.1 ± 1.3. GDM was diagnosed in 13.5%. The mean pre-ravid BMI was 24.6 ± 4.7 kg/m2, with overweight and obesitybserved in 26.2% and 13.9%, respectively. Mean GWG was.9 ± 5.7 kg. Of note, the cohort was multiethnic, with most of
outcomes related to pregravid body mass index and gestationalllitus: A retrospective observational study. Diabetes Metab (2015),
he subjects being Caucasian (from Europe or North Africa;3.5%) or from sub-Saharan Africa (22.9%).
Pregravid parameters associated with GDM were BMI, age,arity, maternal smoking, ethnicity, family history of diabetes
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E. Cosson et al. / Diabetes &
nd previous pregnancy with macrosomia or GDM (Table 1).lasses of increasing BMI (normal weight, overweight and obe-
ity) were associated with higher parity, less smoking before anduring pregnancy, ethnicity and a more frequent personal historyf GDM. Mean GWG was lower in obese women (Table 1).
.2. Pregnancy-related events associated with GDM andverweight/obesity
Table 1 also shows that GDM was associated with less GWG,nd more LGA infants (OR: 2.12, 95% CI: 1.85–2.43), cae-arean section (OR: 1.49, 95% CI: 1.34–1.65) and preeclampsiaOR: 1.59, 95% CI: 1.21–2.09). An increased BMI classificationas associated with lower GWG, more GDM, preeclampsia and
ewer SGA infants (Table 1).
.3. Complications associated with BMI and GWGccording to GDM status
On analyzing the contribution of overweight/obesity andWG classification to the incidence of LGA infants (Fig. 1A),GA infants (Fig. 1B), caesarean sections (Fig. 1C) andreeclampsia (Fig. 1D) by GDM status, the GWG and BMI classere associated with LGA infants regardless of GDM status
Fig. 1A, P < 0.0001) and with SGA infants only in women with-ut GDM (Fig. 1B, P < 0.01). Of note, the mean rate of SGA was3.7% in women without GDM whereas, when GWG was < 7 kgith normal weight, overweight and obesity, the rates were6.3%, 12.8% and 13.6%, respectively. There were no asso-iations between GWG, BMI class, caesarean section (Fig. 1C)nd preeclampsia (Fig. 1D) in women with and without GDM.
.4. Factors independently associated with LGA and SGAnfants
The probability of delivering an LGA infant was associ-ted with the following maternal and pregnancy characteristics:ositive association with increasing age (29.7 ± 5.9 years inomen without an LGA infant vs 30.2 ± 5.7 years in thoseith an LGA infant; P < 0.01), BMI (24.6 ± 4.7 kg/m2 vs4.9 ± 4.8 kg/m2, respectively; P < 0.05), multiparity (58.4%s 73.2%, respectively; P < 0.0001), family history of diabetes20.4% vs 24.4%, respectively; P < 0.05), previous pregnancyith macrosomia (2.1% vs 11.3%, respectively; P < 0.0001),DM (12.6% vs 23.3%, respectively; P < 0.0001) and GWG
lassification (P < 0.001); negative association with smokingefore and during pregnancy (9.9% vs 5.6%, respectively;
< 0.0001), sub-Saharan African (24.0% vs 19.8%, respec-ively; P < 0.0001) and Caribbean (9.1% vs 6.6%, respectively;
< 0.0001) origins, and preeclampsia (2.3% vs 11.0%, respec-ively; P < 0.01). Multivariate analyses taking into account thesearameters to explain LGA infants showed that all of theseactors, except age, were independently associated with LGA
Please cite this article in press as: Cosson E, et al. Pregnancy adversweight gain, according to the presence or not of gestational diabetes mehttp://dx.doi.org/10.1016/j.diabet.2015.06.001
nfants, including BMI and GWG (Table 2); this was also truehen only women without GDM were considered. Factors inde-endently associated with LGA in women with GDM were age,ultiparity, previous pregnancy with macrosomia, and GWG
oaoa
abolism xxx (2015) xxx–xxx
1.5–16 kg and > 16 kg, but with none of the other parameters,ncluding BMI (Table 2).
The probability of delivering an SGA infant was associatedith BMI classification, multiparity (60.0% in women with-ut an SGA infant vs 57.7% in those with; P < 0.05), smokingefore and during pregnancy (9.3% vs 10.7%, respectively;
< 0.05), family history of diabetes (21.2% vs 17.8%, respec-ively; P < 0.0001), previous pregnancy with macrosomia (3.1%s 1.9%, respectively; P < 0.01), preeclampsia (1.9% vs 3.5%,espectively; P < 0.001) and GWG class (P < 0.01). On mul-ivariate analyses, all of these parameters, except multiparity,ere associated with SGA infants, including BMI (negative
ssociation) and GWG < 7 kg (positive association; Table 3).n multivariate analyses performed according to GDM status,verweight/obese and GWG classes remained independentlyssociated with SGA infants in women without GDM, but noonger for women with GDM (Table 3).
. Discussion
Our present findings confirm and extend previous reportsinking GDM, high maternal BMI and GWG with pregnancyutcomes. In our large European, non-Asian cohort of womenithout pregestational diabetes or hypertension, both pregravidMI and GWG were associated with LGA and SGA infants inomen without GDM. In contrast, in women with treated GDM,verweight/obesity was not independently associated with LGAnd SGA infants, and GWG was only associated with LGAnfants. Considered altogether, these results suggest that bothverweight/obesity and GWG are crucial for fetal growth inomen without GDM, whereas GWG is the main additional
ontributor in GDM to fetal overgrowth, with the role of BMIlunted in women treated for GDM.
.1. GDM prevalence, BMI excess and GWG in oururopean cohort
As previously reported, GDM prevalence was high in ourollowed-up women [2]. This was due to our diagnostic criteria,hich used low thresholds even before our adoption of Inter-ational Association of Diabetes and Pregnancy Study GroupsIADPSG) criteria for defining GDM in 2011. In addition, manyf our patients have risk factors for GDM: 20% of our women arerom North Africa [21] and are particularly vulnerable. Indeed, itas recently reported that more than half the women with GDM
n the four largest maternity units in our area had psychosocialnsecurity [24,25]. A large proportion of women in our cohortegan their pregnancies while overweight (26.2%) or obese13.9%); these are among the highest rates in France and mostikely due to the large proportion of deprived populations livingn our area. In addition, the proportion of women of childbearingge with obesity is increasing in France [26,27]; it was recentlyeported that the proportion of pregnant women with overweight
e outcomes related to pregravid body mass index and gestationalllitus: A retrospective observational study. Diabetes Metab (2015),
r obesity had increased from 30.8% in 2002 to 37.6% in 2010t our centre [2]. The prevalence of obesity was higher than thatf Friuli–Venezia Giulia, a region in northeastern Italy [9], andlmost the same as that reported by the international HAPO study
Please cite this article in press as: Cosson E, et al. Pregnancy adverse outcomes related to pregravid body mass index and gestationalweight gain, according to the presence or not of gestational diabetes mellitus: A retrospective observational study. Diabetes Metab (2015),http://dx.doi.org/10.1016/j.diabet.2015.06.001
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Fig. 1. Crude prevalences in women with and without gestational diabetes mellitus (GDM) of (A) large-for-gestational-age (LGA) and (B) small-for-gestational-age(SGA) infants, (C) caesarean section and (D) preeclampsia, according to body mass index (obesity, overweight and normal weight) and gestational weight gain.
Please cite this article in press as: Cosson E, et al. Pregnancy adverse outcomes related to pregravid body mass index and gestationalweight gain, according to the presence or not of gestational diabetes mellitus: A retrospective observational study. Diabetes Metab (2015),http://dx.doi.org/10.1016/j.diabet.2015.06.001
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Table 2Parameters associated with large-for-gestational-age (LGA) infants in the total cohort and in women without and with gestational diabetes mellitus (GDM).
Total cohort Women without GDM Women with GDM
Multivariate analysis Multivariate analysis Multivariate analysis
OR [95 CI] P OR [95 CI] P OR [95 CI] P
Age (10 years) NS NS 1.29 [1.07–1.51] < 0.01
Maternal BMI (10 kg/m2) 1.12 [1.00–1.24] < 0.05 1.17 [1.03–1.31] < 0.001 NS
Multiparity (%) 1.87 [1.64–2.14] < 0.001 1.90 [1.64–2.21] < 0.001 1.74 [1.30–2.35] < 0.001
Maternal smokingNo (%) REF REF REFBefore (%) NS NS NSBefore and during (%) 0.48 [0.37–0.61] < 0.001 0.42 [0.32–0.56] < 0.001 NS
EthnicityCaucasian (%) REF REF REFSub-Saharan African (%) 0.74 [0.64–0.89] < 0.001 0.70 [0.59–0.83] < 0.001 NSCaribbean (%) 0.63 [0.50–0.80] < 0.001 0.64 [0.49–0.83] < 0.001 NSOther (%) NS NS NS
Family history of diabetes (%) 1.16 [1.01–1.33] < 0.05 1.18 [1.01–1.38] < 0.05 NS
Previous pregnancy with macrosomia (%) 4.52 [3.65–6.00] < 0.001 4.86 [3.82–6.19] < 0.001 3.78 [2.39–5.96] < 0.001
GDM (%) 2.01 [1.75–2.32] < 0.001 – – – –
Preeclampsia (%) 0.49 [0.29–0.83] < 0.01 0.42 [0.21–0.84] < 0.05 NS
GWG classification< 7 kg (%) NS NS NS7–11.5 kg (%) REF REF REF11.6–16 kg (%) 1.74 [1.49–2.03] < 0.001 1.64 [1.38–1.95] < 0.001 2.14 [1.54–2.97] < 0.001> 16 kg (%) 3.42 [2.83–4.13] < 0.001 3.58 [2.91–4.40] < 0.001 2.65 [1.68–4.17] < 0.001
Mutivariate analyses used a logistic-regression model including the above factors associated with LGA infants and P < 0.10 on univariate analyses; NS: not significant;REF: reference group.
Table 3Parameters associated with small-for-gestational-age (SMA) infants in the total cohort, and in women without and with gestational diabetes mellitus (GDM).
Total cohort Women without GDM Women with GDM
Multivariate analysis Multivariate analysis Multivariate analysis
OR [95 CI] P OR [95 CI] P OR [95 CI] P
BMI classificationNormal weight (%) REF REF REFOverweight (%) 0.87 [0.78–0.97] < 0.05 0.86 [0.77–0.98] < 0.05 NSObesity (%) 0.83 [0.72–0.96] < 0.05 0.84 [0.72–0.98] < 0.05 NSMultiparity (%) NS 0.90 [0.82–1.00] 0.05 NS
Maternal smokingNo (%) REF REF REFBefore (%) NS NS NSBefore and during (%) 1.2 [1.03–1.4] < 0.05 1.2 [1.03–1.4] < 0.05 NS
Family history of diabetes (%) 0.81 [0.72–0.91] < 0.001 0.84 [0.74–0.95] < 0.01 0.65 [0.47–0.91] < 0.05
Preeclampsia (%) 1.87 [1.44–2.44] < 0.001 1.90 [1.42–2.54] < 0.001 1.85 [1.01–3.40] 0.05
GWG classification< 7 kg (%) 1.13 [1.01–1.26] < 0.05 1.14 [1.01–1.29] < 0.05 NS7–11.5 kg (%) REF REF REF11.6–16 kg (%) NS NS NS> 16 kg (%) NS NS NS
Multivariate analyses used a logistic-regression model including the above factors, which were associated with SGA and P < 0.10 on univariate analyses, plus previouspregnancy with macrosomia; REF: reference group; NS: not significant.
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7], in which 13.7% had a BMI ≥ 33 kg/m2 at inclusion. How-ver, obesity is still far less than reported in recent US reports,hich ranged from 20.0% [28] to 31.9% [29]. Indeed, as in theS [15], our study shows that race/ethnicity is a determinant ofverweight/obesity.
As previously reported, women with overweight and obe-ity had less GWG than those with a normal BMI [5,8,13,14].s women diagnosed with GDM are followed-up with dietary
ounselling, this probably explains why this is so [30]. For thiseason, our study analyzed the incidence of pregnancy eventsccording to mutually exclusive BMI/GWG groups in womenithout GDM and then in those treated for GDM.
.2. Roles of BMI and GWG on fetal growth in women withnd without GDM
As in the five studies looking at the triumvirate of GDM, BMInd GWG, multivariate analyses of our total cohort showed thathese three factors were independently associated with LGAnfants. Interestingly, Black et al. [5] recently reported on theontributions of BMI, mild untreated GDM and GWG to fetalvergrowth: 21.6% of LGA infants were attributable to maternalverweight or obesity and 23.3% to overweight or obesity withDM, with an increasing GWG associated with a greater preva-
ence of LGA in all groups. Similarly, Kim et al. [10] showed,n another US cohort, that for all racial or ethnic groups, GDMontributed the least, whereas GWG contributed the most, toGA. This result was partly due to a notably high prevalencef overweight/obesity in that cohort. Indeed, their calculation ofhe partial population attributable fraction took into account bothhe prevalence and OR of a given risk factor, and was interpreteds the proportion of cases that would be prevented if it were pos-ible to eliminate that risk factor from the population [10]. Ashe partial population attributable fraction of GDM, BMI andWG was < 50%, other factors may be important contributors
o LGA infants. Similar to the findings of others, our data indi-ate that, while ethnicity [15,16], a familial history of diabetesnd personal history of a child with macrosomia [15,29] suggestenetic causes of macrosomia, smoking habits [6], multiparitynd preeclampsia [31] are also possible, non-genetic causes ofacrosomia. All these factors may play a role through epigeneticechanisms, with fetal epigenetic programming of adipokines
nvolved when considering BMI and GWG [32].The effects of BMI and GWG may vary according to GDM
tatus. Our present study found that the effects of BMI andWG were greatest in patients without GDM, who receivedo specific care in our maternity unit at the time. This has beenonsistently reported in women without GDM [5,15,16,28]. Forxample, Di Benedetto et al. [8] showed, in an Italian cohort,hat the effect of overweight and obesity was present only inlucose-tolerant women who had excess weight gain duringregnancy. This suggests that the risk of macrosomia associated
Please cite this article in press as: Cosson E, et al. Pregnancy adverseweight gain, according to the presence or not of gestational diabetes mehttp://dx.doi.org/10.1016/j.diabet.2015.06.001
ith overweight/obesity might be limited by well-controlledWG. The counterpart of a low GWG would be a higher inci-ence of SGA infants [14,18]. In our cohort, however, this effectas blunted in overweight/obese women, who were unlikely to
adnr
abolism xxx (2015) xxx–xxx 7
eliver SGA infants. The increase in SGA infants associatedith GWG < 7 kg was balanced by a decreased incidence ofverweight/obese women. To illustrate this point, GWG < 7 kgas associated with the highest prevalence of SGA infants only
n lean women whereas, in the overweight/obese women, SGAates were similar to the mean rate of the overall cohort. Thesendings suggest that closer monitoring of GWG in womenith pregravid BMIs ≥ 25 kg/m2 may be warranted to preventGA infants with no negative impact on SGA births, as rec-mmended by the IOM [18]. Nevertheless, meta-analyses alsohow that, although antenatal interventions for overweight orbesity can limit GWG [33], the outcomes are often unchanged33,34].
Our present results differed in women with GDM, who wereollowed-up to control both their diets and blood glucose levels.n fact, as found by others [30], these women had less GWGhan women without GDM. Also, in these women, BMI noonger had any effect on LGA births. Indeed, the effect of BMI
ight be driven by GDM, which is more frequent when BMIs increased [3,15]. Otherwise, GWG remained an importantontributor to fetal overgrowth in this subpopulation, with theame result as found in an Italian cohort. When only womenith GDM were considered, GWG, but neither overweight norbesity, were associated with macrosomia [9]. However, an inde-endent effect of GWG and obesity on LGA infants was foundn three American studies [16,28,29]. This was also the case ofhe study by Black et al. [5] although, in that study, GDM wasreated by neither diet nor medication.
.3. Other outcomes
As in previous reports, GDM [1,5,9,10,15] and obesity4,5,7,8] were associated in our cohort with more preeclamp-ia, and GDM with more caesarean section, after examining theontributions of BMI and GWG to these outcomes accordingo GDM status. Regarding preeclampsia, there was no influencef overweight/obesity and GWG classification, thus stressinghe role of GDM per se. Also, no association was identifiedetween BMI and GWG classes for caesarean section regard-ess of GDM status, whereas such an association has often beeneported [4,5,7,8,12]. Several population-based studies foundhat planned and especially emergency caesarean delivery wasignificantly increased with increasing BMI [35]. However,hese studies did not stratify patients according to GDM status.aregivers were inclined to perform caesarean sections in obeseatients because of concerns about obesity-related macrosomia,nd perinatal complications such as shoulder dystocia [5] anderinatal mortality [36].
.4. Strengths and weaknesses of the study
Our study involved a large sample size, thereby giving powero its significant differences, and allowing multivariate analyses
outcomes related to pregravid body mass index and gestationalllitus: A retrospective observational study. Diabetes Metab (2015),
nd strict selection criteria, including no known hypertensiveisorders or diabetes before pregnancy, no underweight women,o women of Asian origin and no twin pregnancies. Thisemoved the major sources of potential confounders. The data
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ame from a single institution with a comprehensive and consis-ent perinatal care programme, and the multiethnic populationncluded a large proportion of women living with psychoso-ial vulnerability [24,25]. All information was collected at aniversity hospital, precluding generalization of the results.
Regarding the parameters of interest, although GDM screen-ng was universal, some women were not screened. Therefore,ur study considered the presence of GDM in the intention-o-screen population, as done in other studies [10,15]. Theroportion of unscreened women was 12.5% in 2011 at ourospital and is likely to have remained stable over the pastecade. GDM was not defined according to IADPSG criteria.owever, the association between BMI and pregnancy out-
omes is reportedly not influenced by the definition of GDM37,38], and our cohort had a GDM prevalence rate similar tohat of the IADPSG criteria. Our results were not adjusted forlucose control, as these data were not available. BMI was cal-ulated from measured height, but weight before pregnancy waself-reported.
One strength of our study is that GWG was not consideredccording to BMI, as that would have led to consideration of theMI effect twice–first per se and then through ‘excessive GWG’,efined according to normal weight, overweight and obesity sta-us. However, GWG was not adjusted for gestational age atelivery, which is difficult as GWG is not linear during preg-ancy, but increases during the lattermost weeks of pregnancy.inally, LGA and SGA infants were defined by comparison
o the general French population [22] with similar thresholdscross ethnicities. However, their determinants were adjustedor ethnicity.
. Conclusion
In the context of the current escalation of obesity [26,27] andDM [39], our present study confirms that GDM, even when
reated, is associated with adverse pregnancy outcomes. In oururopean cohort of women with GDM, GWG is additionallynd independently associated with more LGA infants, whereasverweight/obesity is not. This suggests that, even after rein-orcing GWG control in women treated for GDM, the most thisould achieve does not appear to include more SGA infants in
his pregnant population. However, weight loss subsequent to aiagnosis of GDM has recently been reported to be associatedith a 1.69-fold increased rate of SGA infants [40].In women without GDM, our data show that considering pre-
ravid BMI and GWG is crucial for estimating the risk for LGAnfants. Our observational results suggest that dietary adviceould be offered to overweight/obese women before pregnancyo reduce the risk of preeclampsia and LGA as well as the riskf GDM. In women without GDM, controlling weight gainuring pregnancy might limit the incidence of LGA withoutnducing fetal restriction in those who are overweight/obese. Itas recently shown that a low-intensity lifestyle intervention in
Please cite this article in press as: Cosson E, et al. Pregnancy adversweight gain, according to the presence or not of gestational diabetes mehttp://dx.doi.org/10.1016/j.diabet.2015.06.001
omen at high risk for GDM optimalized healthy GWG, whileimiting weight gain was more effective in overweight women41].
[
abolism xxx (2015) xxx–xxx
isclosure of interest
The authors declare that they have no conflicts of interestoncerning this article.
cknowledgements
We thank Prof Eric Vicaut (AP–HP, Unit of Clinicalesearch, Lariboisière Hospital, Paris 7 University, Paris,rance) for his help with the statistical analyses.
eferences
[1] World Health Organization. Diagnostic criteria and classification ofhyperglycaemia first detected in Pregnancy; 2013 http://apps.who.int/iris/bitstream/10665/85975/1/WHO NMH MND 13.2 eng.pdf
[2] Cosson E, Benbara A, Pharisien I, Nguyen MT, Revaux A, Lormeau B, et al.Diagnostic and prognostic performances over 9 years of a selective screen-ing strategy for gestational diabetes mellitus in a cohort of 18,775 subjects.Diabetes Care 2013;36:598–603.
[3] Galtier F. Definition, epidemiology, risk factors. Diabetes Metab2010;36:628–51.
[4] Hyperglycaemia and adverse pregnancy outcome (HAPO) study: associa-tions with neonatal anthropometrics. Diabetes 2009;58:453–9.
[5] Black MH, Sacks DA, Xiang AH, Lawrence JM. The relative contribu-tion of prepregnancy overweight and obesity, gestational weight gain, andIADPSG-defined gestational diabetes mellitus to fetal overgrowth. Dia-betes Care 2013;36:56–62.
[6] Djelantik AA, Kunst AE, van der Wal MF, Smit HA, Vrijkotte TG. Contri-bution of overweight and obesity to the occurrence of adverse pregnancyoutcomes in a multi-ethnic cohort: population attributive fractions for Ams-terdam. BJOG 2012;119:283–90.
[7] Catalano PM, McIntyre HD, Cruickshank JK, McCance DR, Dyer AR,Metzger BE, et al. The hyperglycaemia and adverse pregnancy outcomestudy: associations of GDM and obesity with pregnancy outcomes. Dia-betes Care 2012;35:780–6.
[8] Di Benedetto A, D’Anna R, Cannata ML, Giordano D, Interdonato ML,Corrado F. Effects of prepregnancy body mass index and weight gain dur-ing pregnancy on perinatal outcome in glucose-tolerant women. DiabetesMetab 2012;38:63–7.
[9] Alberico S, Montico M, Barresi V, Monasta L, Businelli C, Soini V, et al.The role of gestational diabetes, pre-pregnancy body mass index and ges-tational weight gain on the risk of newborn macrosomia: results from aprospective multicentre study. BMC Pregnancy Childbirth 2014;14:23.
10] Kim SY, Sharma AJ, Sappenfield W, Wilson HG, Salihu HM. Associa-tion of maternal body mass index, excessive weight gain, and gestationaldiabetes mellitus with large-for-gestational-age births. Obstet Gynecol2014;123:737–44.
11] Oteng-Ntim E, Kopeika J, Seed P, Wandiembe S, Doyle P. Impact of obesityon pregnancy outcome in different ethnic groups: calculating populationattributable fractions. PLoS One 2013;8:e53749.
12] Gilead R, Yaniv Salem S, Sergienko R, Sheiner E. Maternal “iso-lated” obesity and obstetric complications. J Matern Fetal Neonatal Med2012;25:2579–82.
13] Blomberg M. Maternal and neonatal outcomes among obese women withweight gain below the new Institute of Medicine recommendations. ObstetGynecol 2011;117:1065–70.
14] Hinkle SN, Sharma AJ, Dietz PM. Gestational weight gain in obese mothersand associations with fetal growth. Am J Clin Nutr 2010;92:644–51.
e outcomes related to pregravid body mass index and gestationalllitus: A retrospective observational study. Diabetes Metab (2015),
15] Bowers K, Laughon SK, Kiely M, Brite J, Chen Z, Zhang C. Ges-tational diabetes, pre-pregnancy obesity and pregnancy weight gain inrelation to excess fetal growth: variations by race/ethnicity. Diabetologia2013;56:1263–71.
ARTICLE IN PRESS+ModelDIABET-702; No. of Pages 9
Met
[
[
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[
[
[
[
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[
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[
[
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[
[
E. Cosson et al. / Diabetes &
16] Ellerbe CN, Gebregziabher M, Korte JE, Mauldin J, Hunt KJ. Quantifyingthe impact of gestational diabetes mellitus, maternal weight and race onbirthweight via quantile regression. PLoS One 2013;8:e65017.
17] Alberti KG, Eckel RH, Grundy SM, Zimmet PZ, Cleeman JI, Donato KA,et al. Harmonizing the metabolic syndrome: a joint interim statement ofthe International Diabetes Federation Task Force on Epidemiology andPrevention; National Heart, Lung, and Blood Institute; American HeartAssociation; World Heart Federation; International Atherosclerosis Soci-ety; and International Association for the Study of Obesity. Circulation2009;120:1640–5.
18] Rasmussen KM, Catalano PM, Yaktine AL. New guidelines for weightgain during pregnancy: what obstetrician/gynecologists should know. CurrOpin Obstet Gynecol 2009;21:521–6.
19] Langer O, Yogev Y, Xenakis EM, Brustman L. Overweight and obesein gestational diabetes: the impact on pregnancy outcome. Am J ObstetGynecol 2005;192:1768–76.
20] Cosson E, Benchimol M, Carbillon L, Pharisien I, Paries J, Valensi P, et al.Universal rather than selective screening for gestational diabetes mellitusmay improve fetal outcomes. Diabetes Metab 2006;32:140–6.
21] Cosson E, Cussac-Pillegand C, Benbara A, Pharisien I, Jaber Y, Banu I,et al. The diagnostic and prognostic performance of a selective screeningstrategy for gestational diabetes mellitus according to ethnicity in Europe.J Clin Endocrinol Metab 2014;99:996–1005.
22] Leroy B, Lefort F. [The weight and size of newborn infants at birth]. RevFr Gynecol Obstet 1971;66:391–6.
23] Spong CY, Beall M, Rodrigues D, Ross MG. An objective definition ofshoulder dystocia: prolonged head-to-body delivery intervals and/or theuse of ancillary obstetric maneuvers. Obstet Gynecol 1995;86:433–6.
24] Bihan H, Cosson E, Khiter C, Vittaz L, Faghfouri F, Leboeuf D, et al. Fac-tors associated with screening for glucose abnormalities after gestationaldiabetes mellitus: baseline cohort of the interventional IMPACT study.Diabetes Metab 2014;40:151–7.
25] Cosson E, Bihan H, Vittaz L, Khiter C, Carbillon L, Faghfouri F, et al.Improving postpartum glucose screening after gestational diabetes melli-tus: a cohort study to evaluate the multicentre IMPACT initiative. DiabetMed 2015;32:189–97.
26] Diouf I, Charles MA, Ducimetiere P, Basdevant A, Eschwege E, Heude B.Evolution of obesity prevalence in France: an age-period-cohort analysis.Epidemiology 2010;21:360–5.
27] Eschwege E, Basdevant A, Crine A, Moisan C, Charles MA. Type 2 diabetes
Please cite this article in press as: Cosson E, et al. Pregnancy adverseweight gain, according to the presence or not of gestational diabetes mehttp://dx.doi.org/10.1016/j.diabet.2015.06.001
mellitus in France in 2012: results from the ObEpi survey. Diabetes Metab2015;41:55–61.
28] Kim C. Maternal outcomes and follow-up after gestational diabetes melli-tus. Diabet Med 2014;31:292–301.
[
abolism xxx (2015) xxx–xxx 9
29] Ouzounian JG, Hernandez GD, Korst LM, Montoro MM, Battista LR,Walden CL, et al. Pre-pregnancy weight and excess weight gain are riskfactors for macrosomia in women with gestational diabetes. J Perinatol2011;31:717–21.
30] Bo S, Menato G, Bardelli C, Lezo A, Signorile A, Repetti E, et al. Lowsocioeconomic status as a risk factor for gestational diabetes. DiabetesMetab 2002;28:139–40.
31] Eskild A, Romundstad PR, Vatten LJ. Placental weight and birth-weight: does the association differ between pregnancies with and withoutpreeclampsia? Am J Obstet Gynecol 2009;201:595e1–5.
32] Houde AA, Hivert MF, Bouchard L. Fetal epigenetic programming ofadipokines. Adipocyte 2013;2:41–6.
33] Quinlivan JA, Julania S, Lam L. Antenatal dietary interventions inobese pregnant women to restrict gestational weight gain to Institute ofMedicine recommendations: a meta-analysis. Obstet Gynecol 2011;118:1395–401.
34] Dodd JM, Grivell RM, Crowther CA, Robinson JS. Antenatal interven-tions for overweight or obese pregnant women: a systematic review ofrandomised trials. BJOG 2010;117:1316–26.
35] Ovesen P, Rasmussen S, Kesmodel U. Effect of prepregnancy mater-nal overweight and obesity on pregnancy outcome. Obstet Gynecol2011;118:305–12.
36] Cresswell JA, Campbell OM, De Silva MJ, Filippi V. Effect of maternalobesity on neonatal death in sub-Saharan Africa: multivariable analysis of27 national datasets. Lancet 2012;380:1325–30.
37] Owens LA, O’Sullivan EP, Kirwan B, Avalos G, Gaffney G, Dunne F.ATLANTIC DIP: the impact of obesity on pregnancy outcome in glucose-tolerant women. Diabetes Care 2010;33:577–9.
38] Dennedy MC, Avalos G, O’Reilly MW, O’Sullivan EP, Gaffney G, Dunne F.ATLANTIC-DIP: raised maternal body mass index (BMI) adversely affectsmaternal and fetal outcomes in glucose-tolerant women according to Inter-national Association of Diabetes and Pregnancy Study Groups (IADPSG)criteria. J Clin Endocrinol Metab 2012;97:E608–12.
39] Feig DS, Hwee J, Shah BR, Booth GL, Bierman AS, Lipscombe LL. Trendsin incidence of diabetes in pregnancy and serious perinatal outcomes: alarge, population-based study in Ontario, Canada, 1996–2010. DiabetesCare 2014;20:176–83.
40] Yee LM, Cheng YW, Inturrisi M, Caughey AB. Gestational weight lossand perinatal outcomes in overweight and obese women subsequentto diagnosis of gestational diabetes mellitus. Obesity (Silver Spring)
outcomes related to pregravid body mass index and gestationalllitus: A retrospective observational study. Diabetes Metab (2015),
2013;21:E770–4.41] Harrison CL, Lombard CB, Strauss BJ, Teede HJ. Optimizing healthy
gestational weight gain in women at high risk of gestational diabetes: arandomized controlled trial. Obesity (Silver Spring) 2013;21:904–9.
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