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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 1st 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/m2 ), OW (26.2%), OB (13.9%; BMI ≥ 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 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/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 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

1. Introduction Abbreviations: GWG, Gestational weight gain; IOM, Institute of Medicine; HAPO, Hyperglycaemia and Adverse Pregnancy Outcomes; IADPSG, International Association of Diabetes and Pregnancy Study Groups; LGA, large for gestational age; SGA, small for gestational age. ∗ Corresponding author at: Department of Endocrinology-DiabetologyNutrition, 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).

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.

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

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[4–11], caesarean section [4,5,7,8,11,12], hypertensive disorders [4,5,7,8] and, in certain studies, shoulder dystocia [5]. Also, 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 the impact of GDM, obesity and GWG together. Some limitations may affect these observational studies. First, the prevalence of GDM is sometimes very low [9,16] with screening which might not have been universal [5,10,15,16]. Second, women with pregravid diabetes and hypertension were not excluded [5,9,10,15,16], whereas these conditions are often associated with overweight and obesity. Therefore, considering women with ‘isolated obesity’ might better evaluate the role of obesity per se [12]. Regarding body mass index (BMI), underweight women are not always considered separately [5,16] nor is the lower BMI cutoff point in Asian women [17] taken into account to define overweight and obesity [5,9]. Finally, excessive GWG [9,10], determined according to pregravid BMI status as proposed by the Institute of Medicine (IOM) [18] rather than GWG per se, has often been considered and is an additional confounding factor. Dietary advice and drugs are generally provided only to women with GDM, as GWG [5,8–10,13,14], treatment modalities and glycaemic levels achieved can modify the outcomes [19]. Only the Hyperglycaemia and Adverse Pregnancy Outcomes (HAPO) study reported obesity-related adverse events independently of glycaemic status and its treatment [4,7]. However, in that study, BMI was measured at the time of oral glucose tolerance tests at between 24 and 32 weeks of gestation, and not before pregnancy. Therefore, GWG could not be assessed. Given this context, a large multiethnic European cohort of non-Asian women who delivered singleton babies and were without pregravid diabetes or hypertension was selected for our present retrospective observational study. In this cohort, the adverse outcomes related to ‘isolated’ overweight, obesity and GWG were investigated in women with and without universally screened and treated GDM. 2. Methods 2.1. Participants, GDM screening and care A total of 20,653 women delivered at our hospital between January 2002 and December 2010. Data are routinely entered at birth for all women (no exceptions) giving birth at our university hospital by the midwife assisting at the delivery, then checked and collected during the maternity stay by a midwife qualified in data management and storage (I.P.), with no interactions with the women themselves. The authors did not have access to identification of patients’ information prior to anonymization. The purposes of the database are to assess the overall quality of obstetric care and to regularly update medical management protocols. The data are retrospective and observational, with no need for either approval by an ethics committee/institutional review board or patients’ written informed consent. The patients’ records/information are anonymous, and the database is declared

to the French data protection authority (Commission nationale de l’informatique et des libertés [CNIL]). In the present study, women with known diabetes (n = 204), previous hypertensive disorders (n = 448) and multiple pregnancies (n = 378) were not included. Furthermore, women whose prepregnancy BMI (n = 1669) and GWG (n = 2) were unknown were also not included. Finally, those also excluded were women from Asia (n = 628) or India/Pakistan/Sri Lanka (n = 1076), and those with a BMI < 18.5 kg/m2 (n = 687). Thus, 15,551 pregnancies were analyzed. Definitions of our parameters did not change over the 9 years of the study. BMI was calculated from self-reported pregravid weight and measured height during pregnancy, using the following formula: weight (in kg) divided by the height (in m) squared. Women were classified as normal weight, overweight and obese when their BMI was 18.5–24.9 kg/m2 , 25.0–29.9 kg/m2 and ≥ 30 kg/m2 , respectively [17]. GWG categories (< 7 kg, 7.0–11.5 kg, 11.6–16 kg and > 16 kg) were defined according to the usual thresholds proposed by IOM guidelines for overweight women (optimal GWG: 7–11.5 kg) and normal-weight women (optimal GWG: 11.6–16 kg) [18]. GDM was assessed using a one-step screening and diagnostic test, which always comprised a 75-g oral glucose tolerance test [2,20,21]. GDM was defined as a fasting plasma glucose value ≥ 5.3 mmol/L (the same fasting plasma glucose target as in previous French recommendations) and/or a 2-h blood glucose value ≥ 7.8 mmol/L (World Health Organization criteria) [2,20,21]. One-step screening was chosen to limit the number of participants lost to follow-up, as our study population was characterized by widespread geographical origins [21]. Screening was specifically prescribed during the hospital routine follow-up visit and then performed out of hospital. As is usual for epidemiological studies, the women without screening were considered to be without GDM [2,9,10,15]. Women who were overweight or obese had no specific follow-up unless they were diagnosed with GDM. All women with such a diagnosis were referred to a multidisciplinary team, which included a diabetologist, obstetrician, midwife, dietitian and nurse educator. These women received individualized dietary advice, were instructed on how to perform self-monitoring of blood glucose levels six times a day, and visited the diabetologist every two to four weeks. Insulin therapy was started if fasting and 2-h postprandial glucose levels were > 5.3 mmol/L and > 6.8 mmol/L, respectively. Antenatal visits were scheduled for every two to four weeks up to 34 weeks, and weekly thereafter, with cardiotocography and assessment of amniotic fluid volume [2,21]. 2.2. Prognosis The following outcomes were considered: LGA or SGA (birth weight > 90th percentile or < 10th percentile, respectively, of the general French population) [22]; caesarean section; preeclampsia (blood pressure ≥ 140/90 mmHg on two measurements taken 4 h apart and proteinuria ≥ 300 mg/24 h or 3+ or more on dipstick testing of a random urine sample); preterm delivery (before 37 full weeks); and shoulder dystocia, defined

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

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Table 1 Maternal characteristics and complications by gestational diabetes mellitus (GDM) status and pregravid body mass index (BMI).

Characteristics Pregravid BMI (kg/m2 ) BMI classification Normal weight (%) Overweight (%) Obesity (%) Age (years) Parity (n) Multiparity (%) Maternal smoking Before pregnancy (%) During pregnancy (%) Ethnicity Caucasian (%) Sub-Saharan African (%) Caribbean (%) Other (%) Family history of diabetes (%) Previous pregnancy with macrosomia (%) Previous pregnancy with GDM (%) Events GDM (%) Gestational weight gain (kg) Gestational weight gain classification < 7 kg (%) 7–11.5 kg (%) 11.6–16 kg (%) > 16 kg (%) Large-for-gestational-age babies (%) Small-for-gestational-age babies (%) Caesarean section (%) Preeclampsia (%) Preterm delivery (%) Shoulder dystocia (%)

Total cohort (n = 15,551)

No GDM (n = 13,436)

GDM (n = 2097)

ANOVA, Normal P weight (n = 9317)

Overweight (n = 4075)

Obesity (n = 2159)

ANOVA, P

24.6 ± 4.7

24.6 ± 4.7

24.9 ± 4.8

< 0.001 < 0.01

21.6 ± 1.6

26.6 ± 1.4a

33.6 ± 4.0a,b

< 0.001 –

9317 (59.9) 4075 (26.2) 2159 (13.9) 29.7 ± 5.8 2.1 ± 1.3 9045 (58.2)

8127 (60.4) 3489 (25.9) 1838 (13.7) 29.6 ± 5.8 2.0 ± 1.3 7728 (57.4)

1190 (56.7) 586 (27.9) 321 (15.3) 30.6 ± 5.8 2.2 ± 1.4 1317 (62.8)

– – – 29.7 ± 5.9 2.0 ± 1.2 5315 (57.0)

– – – 29.9 ± 5.8 2.1 ± 1.3a 2426 (59.5)a

– – – 29.7 ± 5.9 2.2 ± 1.4a 1304 (60.4)a

2243 (14.4) 1503 (9.7)

1994 (14.8) 1352 (10.0)

249 (11.9) 151 (7.2)

1421 (15.3) 946 (10.2)

526 (12.9)a 344 (8.4)a

296 (13.7) 213 (9.9)

9881 (63.5) 3566 (22.9) 1365 (8.8) 739 (4.8) 3227 (20.8) 457 (2.9) 498 (3.2)

8434 (62.7) 3181 (23.6) 1196 (8.9) 643 (4.8) 2718 (20.2) 366 (2.7) 268 (2.0)

1447 (69.0) 385 (18.4) 169 (8.1) 96 (4.6) 509 (24.3) 91 (4.3) 230 (11.0)

5998 (64.4) 2058 (22.1) 817 (8.8) 444 (4.8) 1950 (20.9) 266 (2.9) 276 (3.0)

2530 (62.1) 1020 (25.0) 324 (8.0) 201 (4.9) 833 (20.4) 124 (3.0) 136 (3.3)

1353 (62.7) 488 (22.6) 224 (10.4) 94 (4.4) 444 (20.6) 27 (3.1) 86 (4.0)a

2097 (13.5) 8.9 ± 5.7

– 9.0 ± 5.7

– 8.5 ± 5.5

1190 (12.8) 9.1 ± 5.6

586 (14.4)a 8.8 ± 5.6

321 (14.9)a 8.5 ± 5.8a

5041 (32.4) 5695 (36.6) 3586 (23.1) 1229 (7.9) 1341 (8.6) 2114 (13.6) 3265 (21.0) 335 (2.2) 1207 (7.8) 231 (1.5)

4272 (31.8) 4945 (36.8) 3149 (23.4) 1088 (8.1) 1028 (7.6) 1837 (13.7) 2696 (20.0) 269 (2.0) 1032 (7.7) 193 (1.4)

769 (36.7) 750 (35.8) 437 (20.8) 141 (6.7) 313 (14.9) 277 (13.1) 569 (27.1) 66 (3.1) 175 (8.3) 38 (1.8)

2902 (31.1) 3481 (37.4) 2180 (23.4) 754 (8.1) 778 (8.4) 1332 (14.3) 1944 (20.9) 185 (2.0) 733 (7.9) 137 (1.5)

1362 (33.4) 1471 (36.1) 929 (22.8) 313 (7.7) 361 (8.9) 517 (12.7)a 863 (21.2) 88 (2.2) 296 (7.3) 59 (1.4)

777 (32.4) 743 (29.6) 477 (22.1) 162 (7.5) 202 (9.4) 123 (13.9)a 458 (21.2) 62 (2.9)a 178 (8.2) 35 (1.6)

< 000.1 < 000.1 < 000.1 < 000.1 < 000.1 < 000.1

< 000.1 < 000.1 < 000.1 – < 000.1 < 0.01

< 000.1 NS < 000.1 < 000.1 NS NS

NS < 0.001 < 0.01 < 0.001 < 0.01 < 0.01

NS NS < 0.05 < 0.01 < 0.001 < 0.001

NS < 0.01 NS < 0.05 NS 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 . b P < 0.05 vs women with BMI 25–29.9 kg/m2 .

as the use of obstetric manoeuvres (such as a McRoberts episiotomy after delivery of the fetal head, suprapubic pressure, posterior arm rotation to an oblique angle, rotation of the infant by 180 degrees and delivery of the posterior arm) [23].

SPSS software (SPSS, Chicago, IL, USA). The 0.05 probability level was considered statistically significant.

3. Results 2.3. Statistical analyses

3.1. Characteristics of the study population

Continuous variables were expressed as means ± SD, and compared by one-way analysis of variance (ANOVA) or the Mann–Whitney U test as adequate. The significance of differences in proportions was tested with the Chi2 test. Logistic regression was used for analyses of BMI and GWG effects on LGA and SGA infants, caesarean section and preeclampsia in women with and without GDM. Logistic regression was also used for multivariate analyses based on a model including factors associated with LGA and then SGA, with a P value < 0.10 on univariate analyses. All statistical analyses were carried out using

Maternal characteristics are shown in Table 1. In summary, the women were 29.7 ± 5.8 years old, and their mean parity was 2.1 ± 1.3. GDM was diagnosed in 13.5%. The mean pregravid BMI was 24.6 ± 4.7 kg/m2 , with overweight and obesity observed in 26.2% and 13.9%, respectively. Mean GWG was 8.9 ± 5.7 kg. Of note, the cohort was multiethnic, with most of the subjects being Caucasian (from Europe or North Africa; 63.5%) or from sub-Saharan Africa (22.9%). Pregravid parameters associated with GDM were BMI, age, parity, maternal smoking, ethnicity, family history of diabetes

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

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and previous pregnancy with macrosomia or GDM (Table 1). Classes of increasing BMI (normal weight, overweight and obesity) were associated with higher parity, less smoking before and during pregnancy, ethnicity and a more frequent personal history of GDM. Mean GWG was lower in obese women (Table 1). 3.2. Pregnancy-related events associated with GDM and overweight/obesity Table 1 also shows that GDM was associated with less GWG, and more LGA infants (OR: 2.12, 95% 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). An increased BMI classification was associated with lower GWG, more GDM, preeclampsia and fewer SGA infants (Table 1). 3.3. Complications associated with BMI and GWG according to GDM status

11.5–16 kg and > 16 kg, but with none of the other parameters, including BMI (Table 2). The probability of delivering an SGA infant was associated with BMI classification, multiparity (60.0% in women without an SGA infant vs 57.7% in those with; P < 0.05), smoking before and during pregnancy (9.3% vs 10.7%, respectively; P < 0.05), family history of diabetes (21.2% vs 17.8%, respectively; P < 0.0001), previous pregnancy with macrosomia (3.1% vs 1.9%, respectively; P < 0.01), preeclampsia (1.9% vs 3.5%, respectively; P < 0.001) and GWG class (P < 0.01). On multivariate analyses, all of these parameters, except multiparity, were associated with SGA infants, including BMI (negative association) and GWG < 7 kg (positive association; Table 3). On multivariate analyses performed according to GDM status, overweight/obese and GWG classes remained independently associated with SGA infants in women without GDM, but no longer for women with GDM (Table 3). 4. Discussion

On analyzing the contribution of overweight/obesity and GWG classification to the incidence of LGA infants (Fig. 1A), SGA infants (Fig. 1B), caesarean sections (Fig. 1C) and preeclampsia (Fig. 1D) by GDM status, the GWG and BMI class were associated with LGA infants regardless of GDM status (Fig. 1A, P < 0.0001) and with SGA infants only in women without GDM (Fig. 1B, P < 0.01). Of note, the mean rate of SGA was 13.7% in women without GDM whereas, when GWG was < 7 kg with normal weight, overweight and obesity, the rates were 16.3%, 12.8% and 13.6%, respectively. There were no associations between GWG, BMI class, caesarean section (Fig. 1C) and preeclampsia (Fig. 1D) in women with and without GDM. 3.4. Factors independently associated with LGA and SGA infants The probability of delivering an LGA infant was associated with the following maternal and pregnancy characteristics: positive association with increasing age (29.7 ± 5.9 years in women without an LGA infant vs 30.2 ± 5.7 years in those with an LGA infant; P < 0.01), BMI (24.6 ± 4.7 kg/m2 vs 24.9 ± 4.8 kg/m2 , respectively; P < 0.05), multiparity (58.4% vs 73.2%, respectively; P < 0.0001), family history of diabetes (20.4% vs 24.4%, respectively; P < 0.05), previous pregnancy with macrosomia (2.1% vs 11.3%, respectively; P < 0.0001), GDM (12.6% vs 23.3%, respectively; P < 0.0001) and GWG classification (P < 0.001); negative association with smoking before and during pregnancy (9.9% vs 5.6%, respectively; P < 0.0001), sub-Saharan African (24.0% vs 19.8%, respectively; P < 0.0001) and Caribbean (9.1% vs 6.6%, respectively; P < 0.0001) origins, and preeclampsia (2.3% vs 11.0%, respectively; P < 0.01). Multivariate analyses taking into account these parameters to explain LGA infants showed that all of these factors, except age, were independently associated with LGA infants, including BMI and GWG (Table 2); this was also true when only women without GDM were considered. Factors independently associated with LGA in women with GDM were age, multiparity, previous pregnancy with macrosomia, and GWG

Our present findings confirm and extend previous reports linking GDM, high maternal BMI and GWG with pregnancy outcomes. In our large European, non-Asian cohort of women without pregestational diabetes or hypertension, both pregravid BMI and GWG were associated with LGA and SGA infants in women without GDM. In contrast, in women with treated GDM, overweight/obesity was not independently associated with LGA and SGA infants, and GWG was only associated with LGA infants. Considered altogether, these results suggest that both overweight/obesity and GWG are crucial for fetal growth in women without GDM, whereas GWG is the main additional contributor in GDM to fetal overgrowth, with the role of BMI blunted in women treated for GDM. 4.1. GDM prevalence, BMI excess and GWG in our European cohort As previously reported, GDM prevalence was high in our followed-up women [2]. This was due to our diagnostic criteria, which used low thresholds even before our adoption of International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria for defining GDM in 2011. In addition, many of our patients have risk factors for GDM: 20% of our women are from North Africa [21] and are particularly vulnerable. Indeed, it was recently reported that more than half the women with GDM in the four largest maternity units in our area had psychosocial insecurity [24,25]. A large proportion of women in our cohort began their pregnancies while overweight (26.2%) or obese (13.9%); these are among the highest rates in France and most likely due to the large proportion of deprived populations living in our area. In addition, the proportion of women of childbearing age with obesity is increasing in France [26,27]; it was recently reported that the proportion of pregnant women with overweight or obesity had increased from 30.8% in 2002 to 37.6% in 2010 at our centre [2]. The prevalence of obesity was higher than that of Friuli–Venezia Giulia, a region in northeastern Italy [9], and almost 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 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

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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 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

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Table 2 Parameters 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

Age (10 years) Maternal BMI

OR [95 CI]

NS (10 kg/m2 )

Multiparity (%) Maternal smoking No (%) Before (%) Before and during (%) Ethnicity Caucasian (%) Sub-Saharan African (%) Caribbean (%) Other (%)

P

OR [95 CI]

P

NS

1.29 [1.07–1.51]

< 0.01

1.12 [1.00–1.24]

< 0.05

1.17 [1.03–1.31]

< 0.001

1.87 [1.64–2.14]

< 0.001

1.90 [1.64–2.21]

< 0.001

NS

0.48 [0.37–0.61]

REF NS < 0.001

0.42 [0.32–0.56]

REF NS < 0.001

REF NS NS

1.74 [1.30–2.35]

< 0.001

0.74 [0.64–0.89] 0.63 [0.50–0.80]

REF < 0.001 < 0.001 NS

0.70 [0.59–0.83] 0.64 [0.49–0.83]

REF < 0.001 < 0.001 NS

REF 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

1.74 [1.49–2.03] 3.42 [2.83–4.13]

NS REF < 0.001 < 0.001

1.64 [1.38–1.95] 3.58 [2.91–4.40]

NS REF < 0.001 < 0.001

NS REF < 0.001 < 0.001

GWG classification < 7 kg (%) 7–11.5 kg (%) 11.6–16 kg (%) > 16 kg (%)

2.14 [1.54–2.97] 2.65 [1.68–4.17]

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 3 Parameters associated with small-for-gestational-age (SMA) infants in the total cohort, and in women without and with gestational diabetes mellitus (GDM).

BMI classification Normal weight (%) Overweight (%) Obesity (%) Multiparity (%) Maternal smoking No (%) Before (%) Before and during (%)

Total cohort

Women without GDM

Women with GDM

Multivariate analysis

Multivariate analysis

Multivariate analysis

OR [95 CI]

P

0.87 [0.78–0.97] 0.83 [0.72–0.96]

REF < 0.05 < 0.05 NS

OR [95 CI]

P

OR [95 CI]

P

0.86 [0.77–0.98] 0.84 [0.72–0.98] 0.90 [0.82–1.00]

REF < 0.05 < 0.05 0.05

REF NS NS NS REF NS NS

1.2 [1.03–1.4]

REF NS < 0.05

1.2 [1.03–1.4]

REF NS < 0.05

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

1.13 [1.01–1.26]

< 0.05 REF NS NS

1.14 [1.01–1.29]

< 0.05 REF NS NS

GWG classification < 7 kg (%) 7–11.5 kg (%) 11.6–16 kg (%) > 16 kg (%)

NS REF 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 previous pregnancy 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. However, obesity is still far less than reported in recent US reports, which ranged from 20.0% [28] to 31.9% [29]. Indeed, as in the US [15], our study shows that race/ethnicity is a determinant of overweight/obesity. As previously reported, women with overweight and obesity had less GWG than those with a normal BMI [5,8,13,14]. As women diagnosed with GDM are followed-up with dietary counselling, this probably explains why this is so [30]. For this reason, our study analyzed the incidence of pregnancy events according to mutually exclusive BMI/GWG groups in women without GDM and then in those treated for GDM. 4.2. Roles of BMI and GWG on fetal growth in women with and without GDM As in the five studies looking at the triumvirate of GDM, BMI and GWG, multivariate analyses of our total cohort showed that these three factors were independently associated with LGA infants. Interestingly, Black et al. [5] recently reported on the contributions of BMI, mild untreated GDM and GWG to fetal overgrowth: 21.6% of LGA infants were attributable to maternal overweight or obesity and 23.3% to overweight or obesity with GDM, with an increasing GWG associated with a greater prevalence of LGA in all groups. Similarly, Kim et al. [10] showed, in another US cohort, that for all racial or ethnic groups, GDM contributed the least, whereas GWG contributed the most, to LGA. This result was partly due to a notably high prevalence of overweight/obesity in that cohort. Indeed, their calculation of the partial population attributable fraction took into account both the prevalence and OR of a given risk factor, and was interpreted as the proportion of cases that would be prevented if it were possible to eliminate that risk factor from the population [10]. As the partial population attributable fraction of GDM, BMI and GWG was < 50%, other factors may be important contributors to LGA infants. Similar to the findings of others, our data indicate that, while ethnicity [15,16], a familial history of diabetes and personal history of a child with macrosomia [15,29] suggest genetic causes of macrosomia, smoking habits [6], multiparity and preeclampsia [31] are also possible, non-genetic causes of macrosomia. All these factors may play a role through epigenetic mechanisms, with fetal epigenetic programming of adipokines involved when considering BMI and GWG [32]. The effects of BMI and GWG may vary according to GDM status. Our present study found that the effects of BMI and GWG were greatest in patients without GDM, who received no specific care in our maternity unit at the time. This has been consistently reported in women without GDM [5,15,16,28]. For example, Di Benedetto et al. [8] showed, in an Italian cohort, that the effect of overweight and obesity was present only in glucose-tolerant women who had excess weight gain during pregnancy. This suggests that the risk of macrosomia associated with overweight/obesity might be limited by well-controlled GWG. The counterpart of a low GWG would be a higher incidence of SGA infants [14,18]. In our cohort, however, this effect was blunted in overweight/obese women, who were unlikely to

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deliver SGA infants. The increase in SGA infants associated with GWG < 7 kg was balanced by a decreased incidence of overweight/obese women. To illustrate this point, GWG < 7 kg was associated with the highest prevalence of SGA infants only in lean women whereas, in the overweight/obese women, SGA rates were similar to the mean rate of the overall cohort. These findings suggest that closer monitoring of GWG in women with pregravid BMIs ≥ 25 kg/m2 may be warranted to prevent LGA infants with no negative impact on SGA births, as recommended by the IOM [18]. Nevertheless, meta-analyses also show that, although antenatal interventions for overweight or obesity can limit GWG [33], the outcomes are often unchanged [33,34]. Our present results differed in women with GDM, who were followed-up to control both their diets and blood glucose levels. In fact, as found by others [30], these women had less GWG than women without GDM. Also, in these women, BMI no longer had any effect on LGA births. Indeed, the effect of BMI might be driven by GDM, which is more frequent when BMI is increased [3,15]. Otherwise, GWG remained an important contributor to fetal overgrowth in this subpopulation, with the same result as found in an Italian cohort. When only women with GDM were considered, GWG, but neither overweight nor obesity, were associated with macrosomia [9]. However, an independent effect of GWG and obesity on LGA infants was found in three American studies [16,28,29]. This was also the case of the study by Black et al. [5] although, in that study, GDM was treated by neither diet nor medication. 4.3. Other outcomes As in previous reports, GDM [1,5,9,10,15] and obesity [4,5,7,8] were associated in our cohort with more preeclampsia, and GDM with more caesarean section, after examining the contributions of BMI and GWG to these outcomes according to GDM status. Regarding preeclampsia, there was no influence of overweight/obesity and GWG classification, thus stressing the role of GDM per se. Also, no association was identified between BMI and GWG classes for caesarean section regardless of GDM status, whereas such an association has often been reported [4,5,7,8,12]. Several population-based studies found that planned and especially emergency caesarean delivery was significantly increased with increasing BMI [35]. However, these studies did not stratify patients according to GDM status. Caregivers were inclined to perform caesarean sections in obese patients because of concerns about obesity-related macrosomia, and perinatal complications such as shoulder dystocia [5] and perinatal mortality [36]. 4.4. Strengths and weaknesses of the study Our study involved a large sample size, thereby giving power to its significant differences, and allowing multivariate analyses and strict selection criteria, including no known hypertensive disorders or diabetes before pregnancy, no underweight women, no women of Asian origin and no twin pregnancies. This removed the major sources of potential confounders. The data

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

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came from a single institution with a comprehensive and consistent perinatal care programme, and the multiethnic population included a large proportion of women living with psychosocial vulnerability [24,25]. All information was collected at a university hospital, precluding generalization of the results. Regarding the parameters of interest, although GDM screening was universal, some women were not screened. Therefore, our study considered the presence of GDM in the intentionto-screen population, as done in other studies [10,15]. The proportion of unscreened women was 12.5% in 2011 at our hospital and is likely to have remained stable over the past decade. GDM was not defined according to IADPSG criteria. However, the association between BMI and pregnancy outcomes is reportedly not influenced by the definition of GDM [37,38], and our cohort had a GDM prevalence rate similar to that of the IADPSG criteria. Our results were not adjusted for glucose control, as these data were not available. BMI was calculated from measured height, but weight before pregnancy was self-reported. One strength of our study is that GWG was not considered according to BMI, as that would have led to consideration of the BMI effect twice–first per se and then through ‘excessive GWG’, defined according to normal weight, overweight and obesity status. However, GWG was not adjusted for gestational age at delivery, which is difficult as GWG is not linear during pregnancy, but increases during the lattermost weeks of pregnancy. Finally, LGA and SGA infants were defined by comparison to the general French population [22] with similar thresholds across ethnicities. However, their determinants were adjusted for ethnicity. 5. Conclusion In the context of the current escalation of obesity [26,27] and GDM [39], our present study confirms that GDM, even when treated, is associated with adverse pregnancy outcomes. In our European cohort of women with GDM, GWG is additionally and independently associated with more LGA infants, whereas overweight/obesity is not. This suggests that, even after reinforcing GWG control in women treated for GDM, the most this would achieve does not appear to include more SGA infants in this pregnant population. However, weight loss subsequent to a diagnosis of GDM has recently been reported to be associated with a 1.69-fold increased rate of SGA infants [40]. In women without GDM, our data show that considering pregravid BMI and GWG is crucial for estimating the risk for LGA infants. Our observational results suggest that dietary advice could be offered to overweight/obese women before pregnancy to reduce the risk of preeclampsia and LGA as well as the risk of GDM. In women without GDM, controlling weight gain during pregnancy might limit the incidence of LGA without inducing fetal restriction in those who are overweight/obese. It was recently shown that a low-intensity lifestyle intervention in women at high risk for GDM optimalized healthy GWG, while limiting weight gain was more effective in overweight women [41].

Disclosure of interest The authors declare that they have no conflicts of interest concerning this article.

Acknowledgements We thank Prof Eric Vicaut (AP–HP, Unit of Clinical Research, Lariboisière Hospital, Paris 7 University, Paris, France) for his help with the statistical analyses.

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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

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.

This study retrospectively evaluated the complications associated with prepregnancy overweight (OW) or obesity (OB) and gestational weight gain (GWG) ...
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