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. Author manuscript; available in PMC: 2018 Mar 1.
Published in final edited form as: Hum Reprod. 2017 Sep 1;32(9):1941–1947. doi: 10.1093/humrep/dex243

Maternal hyperglycemia in singleton pregnancies conceived by IVF may be modified by first-trimester BMI

S Cai 1, P Natarajan 1, JKY Chan 2,3, PC Wong 1, KH Tan 3,4, KM Godfrey 5,6, PD Gluckman 7,8, LPC Shek 7,9,10, F Yap 11, MS Kramer 12,13, SY Chan 1,7, YS Chong 1,7,*
PMCID: PMC5638004  EMSID: EMS74379  PMID: 28854717

Abstract

Study Question

Does IVF independently increase the risk of gestational diabetes mellitus (GDM) and is this increase in risk modified by maternal body mass index?

Summary Answer

IVF appears to be an independent risk factor for GDM and elevated blood glucose levels in overweight women (BMI > 25 kg/m2).

What is Known Already

IVF has been associated with increased risk of GDM, but most previous studies did not adequately assess confounding or effect modification by other risk factors.

Study Design, Size, Duration

Cross-sectional study using data from 1089 women with singleton pregnancies who participated in a Singaporean birth cohort study (GUSTO) and received a 75 g oral glucose tolerance test (OGTT) at 26–28 weeks gestation.

Participants/Materials, Setting, Methods

A total of 1089 women (n = 1013 conceived spontaneously, n = 76 conceived through IVF) with singleton pregnancies received a 75 g OGTT at 26–28 weeks gestation. Fasting and 2 h postprandial blood glucose levels were assayed. World Health Organization criteria (1999) standard criteria were used to classify GDM: ≥7.0 mmol/L for fasting and/or ≥7.8 mmol/L for 2-h postprandial plasma glucose levels, which was the clinical guideline in use during the study.

Main Results and The Role of Chance

IVF pregnancies had nearly double the odds of GDM (OR = 1.83, 95% CI: 1.03–3.26) and elevated fasting (mean difference = 0.12 mmol/L, 95% CI: 0.00–0.24) and OGTT 2-h blood glucose levels (mean difference = 0.64 mmol/L, 95% CI: 0.27–1.01), after adjusting for commonly recognized risk factors for GDM. After stratification by first-trimester BMI, these increased risks of GDM (OR = 3.54, 95% CI: 1.44–8.72) and elevated fasting (mean difference = 0.39 mmol/L, 95% CI: 0.13–0.65) and 2-h blood (mean difference = 1.24 mmol/L, 95% CI: 0.56–1.91) glucose levels were significant only in the IVF group who is also overweight or obese (BMI > 25 kg/m2).

Limitations Reasons for Caution

One limitation of our study is the absence of a 1 h post-OGTT plasma glucose sample, as we were using the 1999 WHO diagnostic criteria (the clinical guideline in Singapore) at the time of our study, instead of the revised 2013 WHO diagnostic criteria. Our cohort may not be representative of the general Singapore obstetric population, although participants were recruited from the two largest maternity hospitals in the country and include both private and subsidized patients.

Wider Implications of the Findings

IVF appears to be an independent risk factor for GDM and elevated blood glucose levels in overweight women. Our findings reinforce the need to advise overweight or obese women contemplating IVF to lose weight before the procedure to reduce their risk of GDM and hyperglycemia-related adverse outcomes arising therefrom. In settings where universal GDM screening is not routine, overweight or obese women who conceive by IVF should be screened.

Study Funding/Competing Interest(s)

This research was supported by the Singapore National Research Foundation under its Translational and Clinical Research (TCR) Flagship Program and administered by the Singapore Ministry of Health’s National Medical Research Council (NMRC), Singapore (NMRC/TCR/004-NUS/2008; NMRC/TCR/012-NUHS/2014). Additional funding was provided by the Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR). K.M.G. and Y.S.C. have received lecture fees from Nestle Nutrition Institute and Danone, respectively. K.M.G., Y.S.C. and S.Y.C. are part of an academic consortium that has received research funding from Abbott Nutrition, Nestec and Danone. The other authors have nothing to disclose. The other authors have nothing to disclose.

Trial Registration Number

N/A.

Keywords: IVF, gestational diabetes, overweight, blood glucose, BMI

Introduction

Since the first birth conceived by IVF in 1978, the number of women receiving ART is increasing worldwide, with over 5 million children born with the help of ART (Kissin et al., 2014). With its increasing use and success, it is important to consider ART’s effects on maternal and child outcomes. Systematic reviews and meta-analyses have shown that women who conceived through IVF are at higher risk of pregnancy complications including hypertensive disorders and gestational diabetes (Jackson et al., 2004; Pandey et al., 2012). These increased risks may be partly attributable to multiple pregnancies (Qin et al., 2015), but studies have increasingly reported higher risks in singleton pregnancies as well (Helmerhorst et al., 2004; Pandey et al., 2012).

Many prior studies of ART and pregnancy complications examined a large number of pregnancy and perinatal complications, including gestational diabetes, pre-eclampsia, premature rupture of membranes and preterm birth (Jackson et al., 2004; Pandey et al., 2012; Qin et al., 2015; Zhu et al., 2016). Traditional risk factors for gestational diabetes mellitus (GDM), including family history of diabetes and previous GDM history, are rarely considered when comparing IVF and spontaneously conceived pregnancies. GDM is known to increase the risks of subsequent type 2 diabetes in the mother (Bellamy et al., 2009), adverse birth outcomes such as preterm birth, macrosomia, and neonatal hypoglycemia (Hay, 2012), and long-term offspring obesity, diabetes and cardiovascular diseases (Fraser and Lawlor, 2014). Given the increasing incidence of GDM (Buckley et al., 2012), it is important to establish whether IVF is an independent risk factor for GDM development. Additionally, amongst all the classic risk factors for GDM (Guideline Development Group, 2008), only maternal BMI is modifiable. We further hypothesized that overweight and obese women who underwent IVF would be more susceptible to GDM than underweight or normal-weight women, i.e. that first-trimester maternal BMI would modify the association of IVF with GDM and maternal blood glucose levels.

Materials and Methods

Study design and population

Data were obtained from Growing Up in Singapore Towards healthy Outcomes (GUSTO), a mother-offspring prospective cohort study in Singapore. From June 2009 to September 2010, 1247 (1162 who conceived spontaneously and 85 who conceived via IVF) pregnant women aged 18 years and above were recruited at 11–14 weeks of gestation from two major public maternity units in Singapore: KK Women’s and Children’s Hospital (KKH) and National University Hospital (NUH). Details on the study have been previously published (Soh et al., 2014). We excluded women who had Type 1 diabetes mellitus or were receiving chemotherapy or psychotropic drugs.

Maternal characteristics

Maternal demographic and clinical data were collected at multiple study visits. Data on age, ethnicity, educational level, pre-pregnancy BMI, family history of diabetes, menstrual history and obstetric history of GDM and delivery data from previous pregnancies were obtained by interviewer administered questionnaire at the recruitment visit. Data on parity, first-trimester BMI were obtained from hospital medical records.

Oral glucose tolerance test and GDM diagnosis

All participants who attended the clinic visit at 26–28 weeks of gestation were offered a 75 g oral glucose tolerance test (OGTT) after 8–10 h of overnight fasting; fasting and 2-h venous blood samples were collected in fluoride tubes. Fasting and 2-h postprandial plasma glucose concentrations were measured by colorimetry [Advia 2400 Chemistry system (Siemens Medical Solutions Diagnostics) and Beckman LX20 Pro analyzer (Beckman Coulter)] (Chong et al., 2014). World Health Organization criteria (1999) standard criteria were used to classify GDM: ≥7.0 mmol/L for fasting and/or ≥7.8 mmol/L for 2-h postprandial plasma glucose levels (2013), which was the clinical guideline in use during the study.

As we did not measure baseline blood glucose levels during first trimester, we included a sensitivity analysis, excluding participants with probable undiagnosed Type 2 diabetes defined as a fasting glucose ≥7.0 mmol/L or 2 h glucose ≥11.1 mmol/L at the 26–28 weeks OGTT (2013).

Statistical analysis

Continuous and categorical maternal characteristics were compared between spontaneous conception and IVF mothers using independent sample t-tests and chi-square tests, respectively. Multivariable logistic regression models were used to estimate the odds ratio (OR) of GDM in IVF versus spontaneous conceptions. Multivariable linear regression models were used to assess the mean difference in fasting and 2 h post-OGTT glucose levels between the two conception groups. All multivariable models adjusted for maternal age, ethnicity, first-trimester maternal BMI, family history of diabetes, previous history of GDM and prior history of a macrosomic (>4 kg) infant. To test the hypothesis that overweight and obese women may be more susceptible to GDM than their underweight or normal weight counterparts, we included a multiplicative interaction term in the multivariable logistic and linear regression models, respectively. As these interaction terms were statistically significant or near significant (all P < 0.10), we further stratified our analyses by BMI: under/normal weight (<25 kg/m2) compared with overweight/obese (≥25 kg/m2). No other effect modifiers were hypothesized, and no other interactions were assessed. Additional sensitivity analysis was done, where missing first-trimester BMI was replaced with self-reported pre-pregnancy BMI. All analyses were carried out using SPSS version 24.0 (IBM, Armonk, NY, USA).

Ethical approval

This study followed the principles of the Declaration of Helsinki. The study received approval from ethics committees of the hospitals involved: SingHealth Centralized Institutional Review Board and National Healthcare Group Domain Specific Review Board in Singapore. Written informed consent was obtained from all participants.

Results

Participant characteristics

Figure 1 shows the study flow diagram. We excluded participants who were lost to follow-up (n = 32) and did not complete the OGTT at 26–28 weeks because of a missed visit (n = 33) and refusal or unable to complete OGTT (n = 81), had multiple pregnancies (n = 10) or previously diagnosed type 2 diabetes (n = 1) or were not of homogenous ethnicity (n = 1). Participants who were excluded (n = 158) were comparable to those included in terms of maternal age, first-trimester BMI, previous history of GDM, delivery of a macrosomic baby, family history of diabetes and regularity of their menstrual cycle. However, included women were more likely to be of Chinese ethnicity than those excluded (57.2 versus 45.6%). In total, 1089 participants were included in our analysis, of whom 76 conceived through IVF. Women who conceived by IVF were older, more likely to be of Chinese ethnicity and nulliparous, but less likely to have a family history of diabetes (Table I).

Figure 1.

Figure 1

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Flowchart describing the recruitment and inclusion of participants from the GUSTO (Growing Up in Singapore toward Healthy Outcomes) birth cohort study.

Table I. Demographic characteristics of mothers with spontaneous conception versus IVF. Data are n (%) unless stated otherwise.

Variables Spontaneous conception
(n = 1013)		 IVF
(n = 76)		 P-value
Maternal age (years), mean (SD) 30.4 (5.2) 33.9 (3.1) <0.001
Ethnicity, n (%) <0.001
    Chinese  561 (55.4)    62 (81.6)
    Malay  271 (26.8)      6 (7.9)
    Indian  181 (17.9)      8 (10.5)
First-trimester BMI   0.251
    <25 kg/m2  661 (65.3)    44 (57.9)
    ≥25 kg/m2  291 (28.7)    26 (34.2)
    Missing, n (%)    61 (6.0)      6 (7.9)
Nulliparous at recruitment  436 (43.0)    62 (81.6) <0.001
    Missing    10 (1.0)      0 (0.0)
Previous history of Gestational diabetes mellitus    35 (3.5)      0 (0.0)   0.112
    Missing    25 (2.5)      7 (9.2)
Previous delivery of babies >4 kg    17 (1.7)      0 (0)   0.252
    Missing    24 (2.4)      1 (1.3)
Family history of diabetes  310 (30.6)    12 (15.8)   0.006
    Missing    25 (2.5)      2 (2.6)
Menstrual cycle
    Regular  746 (73.6)    51 (67.1)   0.256
    Irregular  240 (23.7)    24 (31.6)
    Missing    27 (2.7)      1 (1.3)
Fasting plasma glucose concentration (mmol/L), mean (SD) 4.35 (0.46) 4.47 (0.65)   0.029
2-h postprandial plasma glucose concentration (mmol/L), mean (SD) 6.49 (1.44) 7.21 (1.78) <0.001
Gestational diabetes mellitus  179 (17.7)    23 (30.3)   0.006
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P-values are determined by chi-square or independent t-test.

Mode of conception and its association with GDM risk and glucose levels

In the unadjusted analysis, women who conceived through IVF had more than double the odds of GDM compared to the spontaneous conception group (Table II). After adjusting for maternal age, ethnicity, first-trimester maternal BMI, family history of diabetes, previous history of GDM and prior history of macrosomia, the odds of GDM remained significantly higher in the IVF group (Table II). Similarly, the 2 h OGTT blood glucose levels were significantly higher in the IVF group, both before and after adjustment for covariates (Table II). Fasting blood glucose levels were significantly higher in the IVF group before adjustment and continued to show the same trend after covariate adjustment (Table II).

Table II. Association of IVF with maternal glucose concentrations and gestational diabetes mellitus.

Unadjusted (n = 1089) Adjusteda (n = 930 versus 63)
OR (95% CI) P-value OR (95% CI) P-value
Normal (n = 1013) IVF (n = 76)
GDM Reference 2.02 (1.21–3.39)   0.007 1.83 (1.03–3.26) 0.040
Mean (SD) Mean difference (95% CI)
Fasting glucose (mmol/L) 4.35 (0.46) 4.47 (0.65)   0.029 0.12 (0.00–0.24) 0.050
OGTT 2-h glucose (mmol/L) 6.49 (1.44) 7.21 (1.78) <0.001 0.64 (0.27–1.01) 0.001
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OR, odds ratio; CI, confidence internal; OGTT, oral glucose tolerance test; GDM, gestational diabetes mellitus.

a

Adjusted for maternal age, ethnicity, first-trimester maternal BMI, family history of diabetes, previous history of GDM and delivery of macrosomic babies (>4 kg).

We observed a significant interaction between mode of conception and first-trimester BMI on both fasting and 2 h OGTT blood glucose levels (both P for interaction = 0.001), although the interaction was non-significant for risk of GDM (P = 0.080). When stratified by first-trimester BMI, the increase in GDM risk, as well as higher fasting and 2 h OGTT blood glucose, were statistically significant only in women with first-trimester BMI ≥ 25 kg/m2 (Table III).

Table III. Association of IVF with maternal glucose concentrations and gestational diabetes mellitus, stratified by first-trimester body mass index.

Unadjusted Adjusteda
Under/normal weight
(BMI < 25 kg/m2)
(n = 661 versus 44)		 Overweight/obese
(BMI ≥ 25 kg/m2)
(n = 291 versus 26)		 Under/normal weight
(BMI < 25 kg/m2)
(n = 645 versus 39)		 Overweight/obese
(BMI ≥ 25 kg/m2)
(n = 285 versus 24)
ORb (95% CI) OR (95% CI) P-value OR (95% CI) P-value
GDM    1.44 (0.67–3.09) 3.41 (1.51–7.71) 1.14 (0.51–2.55) 0.744 3.54 (1.44–8.72)    0.006
Mean differenceb (95% CI) Mean differenceb (95% CI) Mean differenceb (95% CI)
Fasting glucose (mmol/L)  −0.01 (−0.10–0.13) 0.36 (0.11–0.60) −0.04 (−0.17 to 0.08) 0.524 0.39 (0.13–0.65)    0.003
OGTT 2-hour glucose (mmol/L)    0.54 (0.12–0.97) 1.10 (0.46–1.75) 0.27 (−0.17 to 0.71) 0.227 1.24 (0.56–1.91)  <0.001
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OR, odds ratio; CI, confidence internal; OGTT, oral glucose tolerance test; GDM, gestational diabetes mellitus.

a

Adjusted for maternal age, ethnicity, family history of diabetes, previous history of GDM and delivery of macrosomic babies (>4 kg).

b

Reference to control group of women who conceived spontaneously in the respective BMI group.

Three additional sensitivity analysis was performed. Firstly, where there was missing first-trimester BMI data, this was replaced with self-reported pre-pregnancy BMI. The two BMIs were highly correlated with a correlation coefficient of 0.962. The results are shown in Supplementary Table SI and the findings remained unchanged. Secondly, we excluded probable undiagnosed Type 2 diabetes (n = 8) and the findings remained unchanged (Supplementary Table SII). Lastly, we also carried out a sensitivity analysis adjusting for self-reported menstrual irregularities, as a surrogate for possible polycystic ovarian syndrome or other hormonal disorders that may contribute to GDM; our findings remained unchanged (Supplementary Table SIII).

Discussion

Our findings confirm the association between IVF and GDM risk (Maman et al., 1998; Pandey et al., 2012; Ashrafi et al., 2014; Qin et al., 2017). The association remained after adjusting for key GDM risk factors, namely family history of diabetes, previous history of GDM and previous macrosomic infant, which is a step often omitted in studies of adverse obstetric and perinatal outcomes associated with IVF. To the best of our knowledge, our study is the first to demonstrate effect modification by maternal BMI. Aside from higher rates of GDM, we also showed that IVF is associated with higher fasting and 2 h post-OGTT blood glucose concentrations in late second trimester, especially in overweight and obese women. This is important to note as it has been shown that the risk of adverse birth outcomes increases across the continuum of rising maternal blood glucose levels, even below GDM thresholds (Metzger et al., 2008; Aris, et al., 2014).

Szymanska et al. (2011) observed higher first-trimester fasting blood glucose in IVF pregnancies, but not in second-trimester blood glucose levels. Moreover, that study was restricted to women with GDM. Ashrafi et al. has carried out similar studies in an Iranian population but did not observe significant differences in blood glucose levels according to mode of conception (IVF, spontaneous and iatrogenic insemination) at both first trimester (fasting) and second trimester (fasting and post-OGTT 1, 2 and 3 h). Their different findings might be attributable to smaller sample sizes (n = 36 and 41) or to differences in the populations studied. The incidences of GDM and type two diabetes are higher in East Asian populations like Singapore.

To our knowledge, ours is the first study to find that first-trimester BMI modifies the effect of IVF on GDM risk and blood glucose levels. Machtinger et al. (2015) studied the link between BMI and IVF on adverse obstetric outcomes but found no significant effect of IVF on risk of GDM. However, it is important to note that their study subjects were mainly Caucasians, with much lower risk of GDM (Jenum et al., 2012).

The strengths of our study include the examination of an Asian population, considering Asians are not as well studied as their Caucasian counterparts despite their higher risk of GDM (Jenum et al., 2012). We also adjusted for many key risk factors for GDM, which were often not taken into consideration in previous studies of adverse outcomes following IVF pregnancies. One limitation of our study is the absence of a 1 h post-OGTT plasma glucose sample, as we were using the 1999 WHO diagnostic criteria (the clinical guideline in Singapore) at the time of our study, instead of the revised 2013 WHO diagnostic criteria (2013). We did not measure basal glucose levels of these women during the first trimester, but we added a sensitivity analysis excluding cases with probable undiagnosed Type 2 diabetes and the findings remained unchanged. Moreover, our cohort may not be representative of the general Singapore obstetric population, although participants were recruited from the two largest maternity hospitals in the country and include both private and subsidized patients.

Our findings suggest that in Asian women who conceive by IVF, the risk of GDM is significantly elevated particularly among those who are overweight or obese. Our results suggest that overweight or obese women should be advised to lose weight before embarking on IVF, to reduce their risk of hyperglycemia and GDM. Most risk-based screening strategies for GDM only included obesity (BMI > 30) as a risk factor (Guideline Development Group, 2008). In the absence of universal screening, overweight or obese women who conceive by IVF, should also be screened for GDM using the OGTT.

Supplementary Material

Supplementary data

Supplementary data are available at Human Reproduction online.

Supplementary Tables

Acknowledgements

We thank the staff and participants of the GUSTO study. The GUSTO study group includes Allan Sheppard, Amutha Chinnadurai, Anne Eng Neo Goh, Anne Rifkin-Graboi, Anqi Qiu, Arijit Biswas, Bee Wah Lee, Birit F.P. Broekman, Boon Long Quah, Borys Shuter, Chai Kiat Chng, Cheryl Ngo, Choon Looi Bong, Christiani Jeyakumar Henry, Cornelia Yin Ing Chee, Yam Thiam Daniel Goh, Doris Fok, George Seow Heong Yeo, Helen Chen, Hugo P S van Bever, Iliana Magiati, Inez Bik Yun Wong, Ivy Yee-Man Lau, Jeevesh Kapur, Jenny L. Richmond, Joanna D. Holbrook, Joshua J. Gooley, Kenneth Kwek, Krishnamoorthy Niduvaje, Leher Singh, Lin Lin Su, Lourdes Mary Daniel, Marielle V. Fortier, Mark Hanson, Mary Foong-Fong Chong, Mary Rauff, Mei Chien Chua, Michael Meaney, Mya Thway Tint, Neerja Karnani, Ngee Lek, Oon Hoe Teoh, Pratibha Agarwal, Rob M. van Dam, Salome A. Rebello, Seang-Mei Saw, Shang Chee Chong, Shu-E Soh, Sok Bee Lim, Chin-Ying Stephen Hsu, Victor Samuel Rajadurai, Walter Stunkel, Wee Meng Han, Wei Wei Pang, Yin Bun Cheung, Yiong Huak Chan and Yung Seng Lee.

Funding

The Singapore National Research Foundation under its Translational and Clinical Research (TCR) Flagship Program and administered by the Singapore Ministry of Health’s National Medical Research Council (NMRC), Singapore (NMRC/TCR/004-NUS/2008; NMRC/TCR/012-NUHS/2014). Additional funding was provided by the Singapore Institute for Clinical Sciences, Agency for Science, Technology and Research (A*STAR).

Footnotes

Authors’ roles

Authors’ contributions as follows: P.D.G., K.M.G., F.Y. and Y.S.C. conceived, designed and supervised the cohort study. Y.S.C. and S.C. conceptualized idea for this article. J.K.Y.C., P.C.W., K.H.T., L.P.C.S. and F.Y. were involved in design of questionnaire or protocol as well as supervision of data collection. S.C., P.N., M.S.K., S.Y.C. and Y.S.C. analyzed and interpreted the data. S.C., P.N., M.S.K. and S.Y.C. contributed to the preparation of the article. All authors critically revised the article for intellectual and scientific content and have approved this submission for publication.

Conflict of interest

K.M.G. and Y.S.C. have received lecture fees from Nestle Nutrition Institute and Danone respectively. K.M.G., Y.S.C. and S.Y.C. are part of an academic consortium that has received research funding from Abbott Nutrition, Nestec and Danone. The other authors have nothing to disclose.

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Supplementary Materials

Supplementary Tables
NIHMS74379-supplement-Supplementary_Tables.docx (24.3KB, docx)

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