Exploring the associations of overweight and obesity with pregnancy outcomes in type 1 and type 2 diabetes: An Australian retrospective cohort study

Xi May Zhen; Glynis Ross; Amanda Gauld; Arianne Sweeting; Alberto Nettel‐Aguirre; Stephanie Noonan; Maria Constantino; Anna‐Jane Harding; Adam Mackie; Hend Chatila; Margaret McGill; Timothy Middleton; Ted Wu; Stephen M Twigg; Jencia Wong

doi:10.1111/jdi.70440

. 2026 Oct 1:10.1111/jdi.70440. Online ahead of print. doi: 10.1111/jdi.70440

Exploring the associations of overweight and obesity with pregnancy outcomes in type 1 and type 2 diabetes: An Australian retrospective cohort study

Xi May Zhen ^1,^2,^3,^4,^✉, Glynis Ross ^1,², Amanda Gauld ², Arianne Sweeting ^1,², Alberto Nettel‐Aguirre ^5,⁶, Stephanie Noonan ², Maria Constantino ^1,², Anna‐Jane Harding ², Adam Mackie ⁷, Hend Chatila ⁷, Margaret McGill ^1,², Timothy Middleton ^1,², Ted Wu ², Stephen M Twigg ^1,², Jencia Wong ^1,²

PMCID: PMC13628177 PMID: 42817769

ABSTRACT

Objective

To explore the associations of maternal overweight/obesity and pre‐pregnancy body mass index (BMI) on glycemia and pregnancy outcomes in women with pregestational type 1 diabetes mellitus (T1DM) or type 2 diabetes mellitus (T2DM).

Research Design and Methods

We examined prospectively collected data (2010–2019) involving 264 singleton pregnancies affected by pregestational T1DM or T2DM. On separate analyses within each diabetes subtype, pregnancy outcomes were compared across maternal BMI categories and using BMI as a continuous variable. Co‐primary outcomes included preterm delivery, large‐for‐gestational age (LGA) infants, and pre‐eclampsia.

Results

In those with T1DM (N = 124, 46% overweight or obese), we did not find an association between increasing BMI category and greater risks of pre‐eclampsia, preterm delivery, or LGA infants. However, amongst the women with T1DM, overweight and obesity were associated with higher odds of exceeding the first trimester HbA1c target (6.5%), and each 1 kg/m² increase in BMI was associated with higher odds of excess GWG as well as caesarean delivery. In the T2DM cohort (N = 140, 90% overweight or obese), each 1 kg/m² increase in BMI above ethnicity‐adjusted normal range was associated with increased odds of pre‐eclampsia (aOR 1.082, 95% CI 1.024 to 1.144) and preterm delivery (aOR 1.042, 95% CI 1.001 to 1.084). In the T2DM cohort, the odds of LGA were numerically higher with each 1 kg/m² increase in BMI, but this was no longer statistically significant after adjustment for potential confounders.

Conclusions

On separate analyses within each diabetes subtype, maternal overweight/obesity was potentially associated with increased odds of pre‐eclampsia and preterm delivery in the T2DM cohort. Amongst those with T1DM, maternal overweight/obesity was associated with non‐attainment of first trimester HbA1c targets. Regression analyses were performed in an exploratory and hypothesis‐generating manner, and larger‐scale studies are required to directly compare the effects of maternal overweight/obesity on pregnancy outcomes in T1DM vs T2DM.

Keywords: diabetes mellitus, obesity, pregnancy

INTRODUCTION

With obesity rates increasing in many regions worldwide, ¹ an increasing number of pregnancies are complicated by maternal overweight or obesity. ² , ³ This is associated with poorer pregnancy outcomes; women with class II and III obesity have been shown to have double the risk of infant death compared to mothers with normal weight. ⁴ Pregnant women with obesity have been shown to have higher risks of thromboembolism, ⁵ gestational diabetes, ⁶ pre‐eclampsia/hypertensive disorders of pregnancy, ⁷ , ⁸ preterm delivery, ⁸ , ⁹ caesarean delivery, ⁸ , ¹⁰ vaginal instrumental deliveries, ¹¹ large‐for‐gestational‐age (LGA) infants, ⁸ , ¹⁰ infants with neonatal jaundice, ¹² infants requiring neonatal intensive care unit (NICU) admission, ⁸ , ¹¹ postpartum hemorrhage, ¹¹ , ¹³ wound infections, ¹¹ , ¹³ and longer hospital stays. ¹¹ Furthermore, exposure to maternal obesity is likely to have inter‐generational effects. Studies have shown that maternal obesity is associated with increased risks of excess adiposity, ¹⁴ insulin resistance, ¹⁴ type 2 diabetes mellitus (T2DM), ¹⁵ metabolic syndrome, ¹⁶ and cardio‐metabolic disease risk ¹⁴ in the offspring. Mechanistically, in addition to potential epigenetic modifications in utero, ¹⁷ children and their parents tend to share similar dietary, environmental, and potentially genetic drivers of obesity. Data from a multiethnic population suggested that around 47% of type 2 diabetes mellitus in youth could be attributed to the combined effect of intrauterine exposures to maternal diabetes and obesity. ¹⁸ Maternal obesity has even been associated with unfavorable changes to offspring myocardial function ¹⁹ and kidney function. ²⁰

There appears to be a direct relationship between adverse pregnancy outcomes and the degree of maternal obesity. ²¹ Women with pregestational diabetes also remain at significantly elevated risk of adverse pregnancy outcomes despite modern medical therapy. ²² , ²³ , ²⁴ While maternal obesity itself is a significant risk factor for adverse pregnancy outcomes, the combined impact of varying degrees of excess maternal weight in pregestational diabetes is a complex and less extensively studied area. At present, there is no clear consensus in the literature on whether increasing maternal BMI affects specific pregnancy outcomes in women with type 1 diabetes mellitus (T1DM) and T2DM. Gaining an understanding of the impact of excess maternal weight is not just relevant for those with T2DM. It is notable that overweight and obesity are now increasingly observed in people with T1DM, a condition not traditionally associated with obesity. ² , ³ , ²⁵ The increase in the ‘double diabetes’ phenotype, characterized by overweight/obesity in individuals with T1DM, may be a reflection of the rising body mass index (BMI) of the general population as well as the contemporary use of intensive glycemic management regimens. ²⁶ Our recent findings indicate that pregnancies affected by T1DM have higher risk profiles compared to those with T2DM, despite the greater apparent sociodemographic disadvantage, lower measures of pregnancy preparedness, and higher rates of obesity seen amongst the women with T2DM. ²⁵ Notably, in the same study, over 45% of women with T1DM were affected by overweight or obesity, and it is unclear how much of the excess risk is attributable to this. ²⁵ Understanding the effects of maternal overweight/obesity on pregnancy outcomes in women with pregestational diabetes is important for improving risk‐reduction strategies in pregnancy. The present study examines how maternal overweight and obesity impact pregnancy outcomes and diabetes complications in a ten‐year single‐center cohort study (2010–2019) of women with T1DM and T2DM.

MATERIALS AND METHODS

We performed a retrospective analysis of data from 264 singleton pregnancies affected by pregestational T1DM or T2DM, with the initial antenatal diabetes clinic visit to a quaternary hospital in metropolitan Sydney, Australia, occurring between 01/01/2010 and 31/12/2019. Pregnancies were not included if the woman was transferred to another health facility for care during the index pregnancy. Only the first pregnancy from each woman during the study period was included. Otherwise, we did not exclude pregnancies based on factors such as incomplete records, maternal age, pre‐existing obstetric complications, or use of assisted reproductive technologies. The study protocol was approved by the Sydney Local Health District human ethics review committee (X18‐0521 & 2019/ETH08968). This study conforms to the provisions of the Declaration of Helsinki in 1995 (as revised in Fortaleza, Brazil, October 2013) and also meets the requirements of the National Statement on Ethical Conduct in Human Research (issued in 2007, Australia). The Sydney Local Health District human ethics review committee granted a waiver of the usual requirement for the consent of the individual for the use of their health information in a research project, in accordance with the Health Records and Information Privacy Act 2002 (NSW), the NSW Privacy Commissioner's Statutory guidelines on research, and the National Health and Medical Research Council (NHMRC) Guidelines approved under Section 95A of the Privacy Act 1988.

Primary outcomes were pre‐eclampsia, preterm delivery, and LGA infants (defined as sex‐ and gestational age‐specific birth weight >90th centile). Other maternal outcomes included first trimester HbA1c [mean (SD), proportion >48 mmol/mol (6.5%)], second and third trimester HbA1c [mean (SD), proportion >42 mmol/mol (6.0%)], mean of HbA1c measurements over three trimesters, total daily insulin dose at delivery, gestational weight gain (GWG) and the proportion exceeding the US Institute of Medicine (IOM) ²⁷ recommendations for GWG, polyhydramnios, gestational hypertension (defined as systolic blood pressure ≥140 mmHg and/or diastolic blood pressure ≥90 mmHg in a pregnant woman who is at ≥20 weeks of gestation, was previously normotensive, and has no proteinuria or new signs of end‐organ dysfunction), significant proteinuria (defined as urine protein:creatinine ratio ≥30 mg/mmol or urine albumin:creatinine ratio ≥ 8 mg/mmol during pregnancy), retinopathy, miscarriage (defined as pregnancy loss <20 weeks of gestation), termination of pregnancy, induction of labor, preterm delivery, instrumental delivery, and caesarean delivery. The trimester‐specific HbA1c thresholds were chosen in line with HbA1c targets included in the Australasian Diabetes in Pregnancy Society (ADIPS) 2020 guideline for pre‐existing diabetes and pregnancy. ²⁸ Other neonatal outcomes included birth weight centile (sex‐ and gestational age‐specific), small‐for‐gestational age (SGA) infants (defined as sex‐ and gestational age‐specific birth weight <10th centile), birth weight >4,000 g (macrosomia), neonatal hypoglycemia (defined as blood glucose level <2.6 mmol/L), APGAR scores <7 at 1/5/10 min, neonatal respiratory distress, neonatal jaundice, shoulder dystocia, congenital malformations (major malformations were defined as structural changes that have significant medical, social or cosmetic consequences), stillbirth (defined as fetal death prior to birth of a baby at ≥20 completed weeks of gestation), and neonatal mortality (defined as deaths amongst live births within the first 28 completed days of life).

Analyses were performed separately in the T1DM and T2DM cohorts. Given the limited sample size, formal interaction testing and direct comparisons between cohorts were not performed. We compared baseline characteristics between BMI categories. BMI categories were defined as follows using ethnicity‐adjusted cut‐offs from the Australian Obesity Management Algorithm (2022) ²⁹ which are based on the World Health Organization (WHO) cut‐offs ³⁰ : (1) normal weight: 18.5–24.9 kg/m² (18.5–22.9 kg/m² for Asians and Australian Indigenous individuals), (2) overweight: 25.0–29.9 kg/m² (23.0–27.4 kg/m² for Asians and Australian Indigenous individuals), (3) class I obesity: 30.0–34.9 kg/m² (27.5–32.4 kg/m² for Asians and Australian Indigenous individuals), (4) class II obesity: 35.0–39.9 kg/m² (32.5–37.4 kg/m² for Asians and Australian Indigenous individuals), and (5) class III obesity: ≥ 40 kg/m² (37.5 kg/m² for Asians and Australian Indigenous individuals). When possible, maternal BMI was taken within 3 months prior to conception or otherwise measured during the first antenatal visit. No maternal BMI values were taken more than 3 months preconception. Comparisons were performed within each diabetes subtype by BMI category and also with BMI as a continuous variable [centered using the upper limit of ethnicity‐adjusted cut‐offs for normal weight from The Australian Obesity Management Algorithm ²⁹ , that is, BMI of 24.9 kg/m² (22.9 kg/m² for Asians and Australian Indigenous individuals)]. Comparisons between BMI subgroups involved comparing those with normal weight, overweight, or obesity (all classes). We analyzed all available data without imputation of missing data. Analyses were performed using IBM SPSS statistics 29.0. A significance level (alpha) of 0.05 was used for all tests. When BMI was assessed as a categorical variable, categorical outcomes were compared using Pearson's chi‐squared test or Fisher's exact test as appropriate. One‐way anova was used to compare 3 or more means. Regression analyses were performed in an exploratory manner to assess variable associations in an a priori set of variables. Given the small sample size and in the context of the numerous exploratory analyses performed in this single‐center study, the P‐values and widths of the CIs were not adjusted for multiplicity and statistical significance cannot be interpreted as confirming definitive effects. Exploratory analyses were performed to demonstrate potential associations and are presented for predominantly hypothesis‐generating purposes. Forest plots were generated using GraphPad Prism version 11.0.2 for Mac.

RESULTS

Baseline characteristics stratified by BMI category for pregnancies affected by type 1 and type 2 diabetes

The study flowchart is included as Figure 1. Baseline characteristics are presented in Table 1. There were 124 pregnancies affected by T1DM (normal weight = 67, overweight = 43, and obesity = 14) and 140 pregnancies affected by T2DM (normal weight = 14, overweight = 39, and obesity = 87). For Tables 1, 2, 3, 4, we presented data for Class I obesity separately in addition to obesity (all classes), as almost all women with T1DM and obesity had Class I obesity [12/14 (85.7%)] whereas in the T2DM group, less than half of those with obesity had Class I obesity [32/87 (36.8%)]. Amongst those with T1DM, 2/124 (1.6%) were affected by Class II or III obesity whereas 55/140 (39.3%) of those with T2DM were affected by Class II or III obesity. Lipid profile data are not routinely available in this electronic dataset as this was often checked outside of our service by community healthcare providers. None of the women included in this study used statins/other lipid‐lowering medications during pregnancy. There was a known diagnosis of obstructive sleep apnea amongst 3 women with T2DM and obesity (Table 1). None of the women had a known history of ischemic heart disease.

Table 1.

Baseline characteristics stratified by maternal pre‐pregnancy BMI category: comparisons within type 1 diabetes mellitus and type 2 diabetes mellitus cohorts

	T1DM Normal weight N = 67	T1DM Overweight N = 43	T1DM Class I obesity N = 12	T1DM Obesity all classes N = 14 Class I = 12 Class II = 1 Class III = 1	T1DM (P‐value comparing normal weight, overweight, and obesity all classes within T1DM cohort)	T2DM Normal weight N = 14	T2DM Overweight N = 39	T2DM Class I obesity N = 32	T2DM Obesity all classes N = 87 Class I = 32 Class II = 23 Class III = 32	T2DM (P‐value comparing normal weight, overweight, and obesity all classes within T2DM cohort)
Age (years) at first antenatal visit	31.7 (4.7)	31.1 (5.7)	32.3 (4.8)	32.1 (4.5)	0.749	33.4 (4.7)	34.0 (4.4)	35.0 (4.6)	33.1 (5.2)	0.679
BMI (kg/m²)	22.1 (1.5)	27.0 (1.6)	31.7 (1.7)	33.3 (5.1)	<0.001	22.0 (1.0)	26.1 (1.6)	31.5 (2.0)	38.1 (7.8)	<0.001
Nulliparous (i.e., has not given birth to a child prior to the index pregnancy)	40/67 (59.7%)	22/43 (51.2%)	9/12 (75.0%)	10/14 (71.4%)	0.395	6/14 (42.9%)	14/39 (35.9%)	8/32 (25.0%)	32/87 (36.8%)	0.929
Duration of diabetes (years) at booking visit	14.4 (8.4)	16.2 (10.0)	17.0 (10.4)	16.6 (10.1)	0.536	2.1 (2.6)	3.9 (3.9)	4.7 (5.3)	4.3 (4.9)	0.246
Subcutaneous insulin pump use	28/67 (41.8%)	18/43 (41.9%)	4/12 (33.3%)	5/14 (35.7%)	0.963	0/14 (0%)	0/39 (0%)	0/32 (0%)	0/87 (0%)	^*
Post‐secondary school qualifications	36/50 (72%)	20/32 (62.5%)	7/8 (87.5%)	8/9 (88.9%)	0.303	11/11 (100%)	22/32 (68.8%)	17/21 (81%)	37/52 (71.2%)	0.117
SEIFA IRSD quintile 1 ^†	7/67 (10.4%)	11/40 (27.5%)	2/12 (16.7%)	4/14 (28.6%)	0.050	5/14 (35.7%)	14/39 (35.9%)	8/32 (25.0%)	31/87 (35.6%)	1.000
Maternal ^‡ White ethnicity	52/67 (77.6%)	24/43 (55.8%)	8/12 (66.7%)	9/14 (64.3%)	0.047	0/14 (0%)	5/39 (12.8%)	6/32 (18.8%)	18/87 (20.7%)	0.125
Paternal ^§ White ethnicity	47/66 (71.2%)	29/41 (70.7%)	10/12 (83.3%)	10/14 (71.4%)	1.000	0/14 (0%)	3/39 (7.7%)	8/31 (25.8%)	27/85 (31.8%)	<0.001
Smoking during pregnancy	7/66 (10.6%)	0/43 (0%)	1/12 (8.3%)	1/14 (7.1%)	0.060	0/14 (0%)	2/38 (5.3%)	3/31 (9.7%)	13/85 (15.3%)	0.152
Chronic hypertension	6/65 (9.2%)	3/40 (7.5%)	1/12 (8.3%)	0/14 (0%)	0.640	0/13 (0%)	3/37 (8.1%)	6/31 (19.4%)	19/84 (22.6%)	0.031
Systolic blood pressure (mmHg)	107.3 (13.0)	113.3 (18.2)	119.3 (11.1)	117.9 (10.8)	0.019	106.4 (11.2)	107.9 (13.6)	117.3 (10.9)	118.8 (13.1)	<0.001
Diastolic blood pressure (mmHg)	62.8 (8.4)	66.4 (10.3)	73.8 (6.4)	72.5 (7.0)	<0.001	65.8 (6.3)	65.9 (8.2)	70.5 (9.6)	73.3 (12.9)	0.002
Previous pre‐eclampsia or gestational hypertension amongst parous women	2/26 (7.7%)	2/18 (11.1%)	0/3 (0%)	0/4 (0%)	1.000	0/8 (0%)	3/23 (13.0%)	1/23 (4.3%)	3/54 (5.6%)	0.403
Known diagnosis of obstructive sleep apnea	0/59 (0%)	0/41 (0%)	0/12 (0%)	0/14 (0%)	^*	0/13 (0%)	0/36 (0%)	0/30 (0%)	3/84 (3.6%)	0.673
Known pre‐pregnancy history of ischemic heart disease	0/67 (0%)	0/43 (0%)	0/12 (0%)	0/14 (0%)	^*	0/14 (0%)	0/39 (0%)	0/32 (0%)	0/87 (0%)	^*
History of bariatric surgery ^¶	0/59 (0%)	0/41 (0%)	0/12 (0%)	0/14 (0%)	^*	0/13 (0%)	2/36 (5.6%)	0/30 (0%)	0/84 (0%)	0.134
Use of anti‐obesity medications (including glucagon‐like peptide‐1 receptor agonists) during pregnancy or within 3 months preconception	0/67 (0%)	0/43 (0%)	0/12 (0%)	0/14 (0%)	^*	0/14 (0%)	0/39 (0%)	0/32 (0%)	0/87 (0%)	^*
Use of statins/other lipid‐lowering medications	0/67 (0%)	0/43 (0%)	0/12 (0%)	0/14 (0%)	^*	0/14 (0%)	0/39 (0%)	0/32 (0%)	0/87 (0%)	^*
Pregnancy planned by mother^#	57/67 (85.0%)	31/43 (72.1%)	8/12 (66.7%)	10/14 (71.4%)	0.202	10/14 (71.4%)	23/39 (59.0%)	14/32 (43.8%)	38/87 (43.7%)	0.076
Periconceptual folic acid use	66/67 (98.5%)	42/43 (97.7%)	12/12 (100%)	14/14 (100%)	0.602	13/14 (92.9%)	37/39 (94.9%)	29/32 (90.6%)	77/87 (88.5%)	0.733
Aspirin use	14/67 (20.9%)	7/43 (16.3%)	6/12 (50.0%)	7/14 (50.0%)	0.035	0/14 (0%)	5/39 (12.8%)	7/32 (21.9%)	18/87 (20.7%)	0.118
Index pregnancy documented as achieved via in vitro fertilization	1/59 (1.7%)	0/41 (0%)	0/12 (0%)	0/14 (0%)	1.000	0/13 (0%)	0/36 (0%)	1/30 (3.3%)	1/84 (1.2%)	1.000

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Values presented in this table are mean (SD) or n/N (%) unless otherwise indicated.

No P‐value was calculated because values were 0% in all BMI categories.

^{^†}

For the Socio‐Economic Indexes for Areas Index of Relative Socio‐economic Disadvantage (SEIFA IRSD) by postcode, the lowest scoring 20 percent of areas (i.e., areas with greatest disadvantage) are given a quintile number of one.

^{^‡}

‘Maternal White ethnicity’ refers to the pregnant woman's ethnicity.

^{^§}

‘Paternal White ethnicity’ refers to the ethnicity of the biological father of the pregnant woman's offspring.

^{^¶}

All bariatric surgeries were sleeve gastrectomy procedures performed >2 years preconception.

^{^#}

‘Pregnancy planned by mother’ refers to self‐reported pregnancy planning and does not imply medical input in planning the pregnancy.

Table 2.

HbA1c and gestational weight gain (GWG) stratified by maternal pre‐pregnancy BMI category: comparisons within type 1 diabetes mellitus and type 2 diabetes mellitus cohorts

	T1DM Normal weight N = 67	T1DM Overweight N = 43	T1DM Class I obesity N = 12	T1DM Obesity all classes N = 14 Class I = 12 Class II = 1 Class III = 1	P‐value (comparing normal weight, overweight, and obesity all classes in T1DM)	T2DM Normal weight N = 14	T2DM Overweight N = 39	T2DM Class I obesity N = 32	T2DM Obesity all classes N = 87 Class I = 32 Class II = 23 Class III = 32	P‐value (comparing normal weight, overweight, and obesity all classes in T2DM)
Metformin use in the first trimester of pregnancy	1/67 (1.5%)	1/43 (2.3%)	1/12 (8.3%)	1/14 (7.1%)	0.812	6/14 (42.9%)	29/39 (74.4%)	13/32 (40.6%)	37/87 (42.5%)	0.029
Mean of HbA1c measurements over 3 trimesters
mmol/mol	46 (8.7)	48 (7.7)	51 (8.7)	51 (7.7)	0.213	41 (7.7)	43 (6.6)	44 (7.7)	45 (8.7)	0.107
%	6.4 (0.8)	6.5 (0.7)	6.8 (0.8)	6.8 (0.7)		5.9 (0.7)	6.1 (0.6)	6.2 (0.7)	6.3 (0.8)
First trimester HbA1c
mmol/mol	51 (10.9)	55 (14.2)	56 (13.1)	57 (13.1)	0.143	48 (13.1)	49 (12.0)	53 (14.2)	55 (17.5)	0.036
%	6.8 (1.0)	7.2 (1.3)	7.3 (1.2)	7.4 (1.2)		6.5 (1.2)	6.6 (1.1)	7.0 (1.3)	7.2 (1.6)
First trimester HbA1c >48 mmol/mol (6.5%)	30/66 (45.5%)	30/41 (73.2%)	9/12 (75.0%)	11/14 (78.6%)	0.004	6/13 (46.2%)	14/38 (36.8%)	16/31 (51.6%)	49/84 (58.3%)	0.076
Second trimester HbA1c
mmol/mol	45 (8.7)	44 (6.6)	48 (9.8)	49 (8.7)	0.306	36 (6.6)	38 (6.6)	39 (7.7)	41 (8.7)	0.112
%	6.3 (0.8)	6.2 (0.6)	6.5 (0.9)	6.6 (0.8)		5.4 (0.6)	5.6 (0.6)	5.7 (0.7)	5.9 (0.8)
Second trimester HbA1c >42 mmol/mol (6.0%)	35/61 (57.4%)	23/36 (63.9%)	8/12 (66.7%)	10/14 (71.4%)	0.578	2/10 (20.0%)	3/29 (10.3%)	7/26 (26.9%)	24/69 (34.8%)	0.030
Third trimester HbA1c
mmol/mol	44 (7.7)	43 (6.6)	48 (6.6)	49 (6.6)	0.336	38 (6.6)	40 (5.5)	41 (6.6)	43 (9.8)	0.054
%	6.2 (0.7)	6.1 (0.6)	6.5 (0.6)	6.6 (0.6)		5.6 (0.6)	5.8 (0.5)	5.9 (0.6)	6.1 (0.9)
Third trimester HbA1c >42 mmol/mol (6.0%)	38/65 (58.5%)	22/39 (56.4%)	9/12 (75.0%)	11/14 (78.6%)	0.123	3/13 (23.1%)	8/35 (22.9%)	11/31 (35.5%)	34/83 (41.0%)	0.127
Total daily insulin dose (units) at delivery	58.7 (25.9)	88.6 (38.9)	107.1 (54.1)	114.3 (53.2)	<0.001	118.8 (117.1)	98.8 (78.4)	139.2 (64.0)	163.3 (105.7)	0.011
GWG (kg)	13.4 (5.2)	12.5 (6.0)	11.6 (4.8)	12.2 (5.9)	0.629	12.6 (5.1)	11.6 (6.3)	11.7 (6.3)	12.3 (8.6)	0.881
GWG above IOM recommendations ^†	18/65 (27.7%)	25/39 (64.1%)	9/12 (75.0%)	10/14 (71.4%)	<0.001	2/12 (16.7%)	19/34 (55.9%)	20/30 (66.7%)	47/81 (58.0%)	0.047

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Values presented in this table are mean (SD) or n/N (%).

^{^†}

IOM recommendations for GWG (total weight gain) by pre‐pregnancy BMI: BMI <18.5 kg/m² = 12.5 to 18.0 kg, BMI 18.5 to 24.9 kg/m² = 11.5 to 16.0 kg, BMI 25.0 to 29.9 kg/m² = 7.0 to 11.5 kg, BMI ≥30.0 kg/m² = 5.0 to 9.0 kg.

Table 3.

Maternal outcomes stratified by maternal pre‐pregnancy BMI category: comparisons within type 1 diabetes mellitus and type 2 diabetes mellitus cohorts

	T1DM Normal weight N = 67	T1DM Overweight N = 43	T1DM Class I obesity N = 12	T1DM Obesity all classes N = 14 Class I = 12 Class II = 1 Class III = 1	P‐value (comparing normal weight, overweight, and obesity all classes in T1DM)	T2DM Normal weight N = 14	T2DM Overweight N = 39	T2DM Class I obesity N = 32	T2DM Obesity all classes N = 87 Class I = 32 Class II = 23 Class III = 32	P‐value (comparing normal weight, overweight, and obesity all classes in T2DM)
Pre‐eclampsia	10/65 (15.4%)	7/40 (17.5%)	2/12 (16.7%)	2/14 (14.3%)	0.936	1/13 (7.7%)	1/37 (2.7%)	3/31 (9.7%)	17/83 (20.5%)	0.017
Preterm delivery	27/65 (41.5%)	16/39 (41.0%)	4/12 (33.3%)	6/14 (42.9%)	1.000	0/13 (0%)	11/36 (30.6%)	12/31 (38.7%)	35/83 (42.2%)	0.005
Miscarriage (<20 weeks of gestation)	2/67 (3.0%)	3/43 (7.0%)	0/12 (0%)	0/14 (0%)	0.409	1/14 (7.1%)	2/39 (5.1%)	1/32 (3.1%)	3/87 (3.4%)	0.541
Termination of pregnancy	0/65 (0%)	1/40 (2.5%)	0/12 (0%)	0/14 (0%)	0.460	0/13 (0%)	1/37 (2.7%)	0/32 (0%)	0/84 (0%)	0.381
Retinopathy assessment during pregnancy	51/65 (78.5%)	35/38 (92.1%)	10/12 (83.3%)	11/14 (78.6%)	0.226	8/13 (61.5%)	15/39 (38.5%)	17/31 (54.8%)	47/84 (56.0%)	0.152
Retinopathy amongst those assessed at any time during pregnancy	17/51 (33.3%)	12/35 (34.3%)	7/10 (70%)	8/11 (72.7%)	0.046	0/8 (0%)	4/15 (26.7%)	0/17 (0%)	3/47 (6.4%)	0.074
Significant proteinuria at any time during pregnancy	13/67 (19.4%)	9/43 (20.9%)	2/12 (16.7%)	2/14 (14.3%)	0.401	1/14 (7.1%)	2/39 (5.1%)	5/32 (15.6%)	23/87 (26.4%)	0.030
Gestational hypertension	3/65 (4.6%)	2/39 (5.1%)	2/12 (16.7%)	2/14 (14.3%)	0.313	0/13 (0%)	2/36 (5.6%)	1/31 (3.2%)	5/83 (6.0%)	1.000
Polyhydramnios	2/65 (3.1%)	5/39 (12.8%)	1/11 (9.1%)	1/13 (7.7%)	0.137	0/13 (0%)	1/34 (2.9%)	0/29 (0%)	2/79 (2.5%)	1.000
Induction of labor	31/65 (47.7%)	16/39 (41.0%)	5/12 (41.7%)	6/14 (42.9%)	0.805	8/13 (61.5%)	13/36 (36.1%)	11/31 (35.5%)	32/83 (38.6%)	0.263
Instrumental delivery	10/63 (15.9%)	8/39 (20.5%)	2/12 (16.7%)	2/14 (14.3%)	0.327	1/13 (7.7%)	4/36 (11.1%)	2/31 (6.5%)	5/82 (6.1%)	0.384
Emergency caesarean delivery	23/63 (36.5%)	17/38 (44.7%)	8/12 (66.7%)	9/14 (64.3%)	0.164	4/13 (30.8%)	13/36 (36.1%)	10/31 (32.3%)	29/83 (34.9%)	0.963
All caesarean delivery	35/65 (53.8%)	31/39 (79.5%)	12/12 (100.0%)	13/14 (92.9%)	0.002	6/13 (46.2%)	27/36 (75.0%)	21/31 (67.7%)	58/83 (69.9%)	0.160

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Values presented in this table are n/N (%).

Table 4.

Neonatal outcomes: comparisons between maternal pre‐pregnancy BMI categories within each diabetes subtype

	T1DM Normal weight N = 67	T1DM Overweight N = 43	T1DM Class I obesity N = 12	T1DM Obesity all classes N = 14 Class I = 12 Class II = 1 Class III = 1	P‐value (comparing normal weight, overweight, and obesity all classes in T1DM)	T2DM Normal weight N = 14	T2DM Overweight N = 39	T2DM Class I obesity N = 32	T2DM Obesity all classes N = 87 Class I = 32 Class II = 23 Class III = 32	P‐value (comparing normal weight, overweight, and obesity all classes in T2DM)
Birth weight >90^th centile (LGA)	36/65 (55.4%)	22/39 (56.4%)	5/12 (41.7%)	6/14 (42.9%)	0.673	0/13 (0%)	6/35 (17.1%)	7/31 (22.6%)	24/83 (28.9%)	0.040
Birth weight centile	82.8 (20.2)	80.1 (24.7)	71.5 (30.3)	74.4 (28.9)	0.447	43.7 (23.6)	51.8 (29.2)	55.6 (32.3)	64.2 (31.0)	0.021
Birth weight <10^th centile (SGA)	1/65 (1.5%)	1/39 (2.6%)	1/12 (8.3%)	1/14 (7.1%)	0.352	1/13 (7.7%)	2/35 (5.7%)	2/31 (6.5%)	5/83 (6.0%)	1.000
Birth weight >4,000 g (macrosomia)	7/65 (10.8%)	6/39 (15.4%)	2/12 (16.7%)	2/14 (14.3%)	0.726	0/13 (0%)	3/36 (8.3%)	2/31 (6.5%)	9/83 (10.8%)	0.727
NICU admission	56/64 (87.5%)	37/39 (94.9%)	11/12 (91.7%)	13/14 (92.9%)	0.552	6/13 (46.2%)	17/35 (48.6%)	18/28 (64.3%)	59/76 (77.6%)	0.010
Neonatal hypoglycemia	27/65 (41.5%)	15/37 (40.5%)	4/12 (33.3%)	6/14 (42.9%)	1.000	1/13 (7.7%)	6/31 (19.4%)	5/28 (17.9%)	24/76 (31.6%)	0.171
Neonatal respiratory distress	21/64 (32.8%)	13/38 (34.2%)	2/12 (16.7%)	4/14 (28.6%)	1.000	1/13 (7.7%)	4/31 (12.9%)	6/28 (21.4%)	19/76 (25.0%)	0.241
Shoulder dystocia	2/61 (3.3%)	0/38 (0%)	0/12 (0%)	0/14 (0%)	0.634	0/12 (0%)	0/35 (0%)	0/30 (0%)	1/81 (1.2%)	1.000
APGAR score <7 at 1 min	8/64 (12.5%)	10/39 (25.6%)	0/12 (0%)	1/14 (7.1%)	0.165	1/13 (7.7%)	6/36 (16.7%)	6/31 (19.4%)	16/83 (19.3%)	0.693
APGAR score <7 at 5 min	2/64 (3.1%)	2/39 (5.1%)	1/12 (8.3%)	2/14 (14.3%)	0.201	0/13 (0%)	1/36 (2.8%)	3/31 (9.7%)	8/83 (9.6%)	0.362
Neonatal jaundice	22/64 (34.4%)	8/38 (21.1%)	3/12 (25.0%)	4/14 (28.6%)	0.332	2/13 (15.4%)	6/31 (19.4%)	6/29 (20.7%)	21/78 (26.9%)	0.583
All congenital malformations	6/63 (9.5%)	3/37 (8.1%)	0/12 (0%)	1/14 (7.1%)	1.000	0/13 (0%)	2/31 (6.5%)	2/31 (6.5%)	7/82 (8.5%)	0.871
Major congenital malformations	4/63 (6.3%)	3/37 (8.1%)	0/12 (0%)	1/14 (7.1%)	0.881	0/13 (0%)	0/31 (0%)	2/31 (6.5%)	6/82 (7.3%)	0.258
Stillbirth	0/65 (0%)	0/40 (0%)	0/12 (0%)	0/14 (0%)	*	0/13 (0%)	1/37 (2.7%)	1/32 (3.1%)	3/84 (3.6%)	1.000
Neonatal mortality (death after live birth)	0/65 (0%)	0/38 (0%)	0/12 (0%)	1/14 (7.1%)	0.120	0/13 (0%)	0/35 (0%)	0/29 (0%)	0/77 (0%)	^*

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Values presented in this table are mean (SD) or n/N (%).

No P‐value was calculated because values were 0% in all BMI categories.

Comparisons between BMI subgroups involved comparing those with normal weight, overweight, and obesity (all classes). In the T1DM cohort, we observed statistically significant differences in the proportion of women with White ethnicity between BMI categories (P = 0.047), with White ethnicity being most common amongst those with normal weight (Table 1). In the T2DM cohort, all women with normal weight were of non‐White ethnicity with higher rates of white ethnicity amongst those with overweight and obesity, although we did not find a statistically significant difference between BMI categories.

In the T2DM cohort only, we observed statistically significant differences in chronic hypertension rates between BMI categories (P = 0.031), with the highest rates in those with obesity (Table 1). In the T1DM and T2DM cohorts, the mean systolic and diastolic blood pressures trended slightly higher with increasing BMI category. Amongst those with hypertension, the specific antihypertensive medications used are currently not routinely available in this electronic dataset. There were no statistically significant differences between BMI categories in either diabetes subtype with regard to crude markers of sociodemographic disadvantage (as denoted by no post‐secondary school qualifications and residence in areas of highest disadvantage as per the Socio‐Economic Indexes for Areas Index of Relative Socio‐economic Disadvantage (SEIFA IRSD) by postcode ³¹ ), or indices of pre‐pregnancy preparedness (as denoted by pregnancy planned by mother and periconceptual folic acid use).

We noted statistically significant differences in rates of aspirin use between BMI categories (P = 0.035) in the T1DM cohort, with highest rates of use in those with obesity. For the T2DM cohort, there were no statistical differences in aspirin use between BMI groups. Overall, rates of aspirin use were relatively low in both diabetes subtypes as most women included gave birth prior to 2018; aspirin was only prescribed systematically following the publication of practice changing data by Nicolaides et al. ³²

Exploring associations between maternal BMI and glycemia or gestational weight gain (GWG) in type 1 diabetes mellitus and T2DM type 2 diabetes mellitus cohorts

Maternal glycemic outcomes and GWG by BMI category are presented in Table 2, with exploratory regressions presented in Table S1 (BMI as a categorical variable, categorical outcomes), Table S2 (BMI as a continuous variable, categorical outcomes), and Table S3 (BMI as a continuous variable, continuous outcomes). As expected, a greater proportion of patients with type 2 diabetes mellitus used metformin during the first trimester (Table 2). In the T2DM cohort, metformin use appeared highest in overweight women (74.4%) when compared to those with normal weight (42.9%) or obesity (42.5%).

Examining the relationship between BMI category and HbA1c in those with T1DM (Table 2), we did not observe a statistically significant difference between BMI categories with regard to the mean of HbA1c measurements over 3 trimesters or the mean first, second, or third trimester HbA1c measurements. However, we observed that, despite treatment, the proportion of women exceeding the first trimester HbA1c target [>48 mmol/mol (6.5%)] was different between BMI categories in the T1DM cohort (P = 0.004, Table 2). Amongst the women with T1DM, overweight women had almost threefold higher odds (aOR 2.995, 95% CI 1.246 to 7.202) and those with obesity had a fourfold higher odds (aOR 4.114, 95% CI 1.036 to 16.332) of having a first trimester HbA1c >48 mmol/mol (6.5%) when compared to women with normal weight (Table S1). Each one unit (kg/m²) increase in BMI (above the ethnicity‐adjusted upper limit of normal weight) was associated with a higher odds of having a first trimester HbA1c >48 mmol/mol (6.5%) in the T1DM cohort after adjustment for potential confounders (Table S2).

In the T2DM cohort, the mean of HbA1c measurements over 3 trimesters or the mean second and third trimester HbA1c measurements were not significantly different between BMI categories (Table 2). The mean first trimester HbA1c was different between BMI categories in the T2DM cohort (P = 0.036). However, the proportion of women exceeding the first trimester HbA1c target [>48 mmol/mol (6.5%)] was not significantly different between BMI categories in the T2DM cohort (P = 0.076). Each 1 kg/m² increase in BMI (above the ethnicity‐adjusted upper limit of normal weight) was associated with a small but statistically significant increase in the mean first trimester as well as third trimester HbA1c (Table S3). Furthermore, in the T2DM cohort, women with obesity were more likely to exceed the first and second trimester HbA1c targets when compared to those with overweight (but not significantly different to those with normal weight) (Table S1). None of the patients in this study experienced diabetic ketoacidosis in the peripartum period.

As seen in Table S3, for those with T1DM, each 1 kg/m² increase in BMI (above the ethnicity‐adjusted upper limit of normal weight) was associated with an approximate 4.6 unit increase in the mean total daily insulin dose at delivery (P < 0.001). For T2DM, the equivalent incremental increase in insulin dose was approximately 2.1 units for each 1 kg/m² increase in BMI (P = 0.030).

Table 2 shows the absolute GWG in kg between BMI categories in the T1DM and T2DM cohorts. In both cohorts, the proportion of women exceeding the IOM recommendations ²⁷ for GWG was highest amongst those with obesity. Specifically, in T1DM, those with overweight or obesity had higher odds of excess GWG compared to those with normal weight (Table S1). Moreover, each 1 kg/m² increase in BMI (above the ethnicity‐adjusted upper limit of normal weight) was associated with an approximately 20% increase in the odds of excess GWG in the T1DM cohort even after adjustment for potential confounders (Table S2). In the T2DM cohort, those with overweight or obesity had a higher odds of excess GWG when compared to normal weight women on unadjusted analyses (Table S1). We did not find a statistically significant relationship between increasing BMI (as a continuous variable) and the odds of exceeding IOM recommendations for GWG in the T2DM cohort (Table S2).

Exploring associations between maternal BMI and pre‐eclampsia, preterm delivery, or other maternal outcomes in type 1 diabetes mellitus and type 2 diabetes mellitus cohorts

In the T2DM cohort only, pre‐eclampsia rates differed significantly between BMI categories (P = 0.017, Table 3). Those with T2DM and overweight had significantly lower odds of pre‐eclampsia than those with obesity (OR 0.108, 95% CI 0.014 to 0.844); this persisted even after adjustments for potential confounders (Table S1). When BMI was treated as a continuous variable, each 1 kg/m² increase above the ethnicity‐adjusted normal range was associated with a small but statistically significant rise in pre‐eclampsia risk in T2DM (aOR1 1.082, 95% CI 1.024 to 1.144) (Table S2). No such association was found in the T1DM cohort. Based on data from Table S1, Figures S1 and S2 present forest plots depicting aOR (95% CI) for pre‐eclampsia by BMI category in the T1DM and T2DM cohorts. There was no statistically significant difference between BMI categories in gestational hypertension rates for both T1DM and T2DM cohorts (Table 3).

In the T2DM cohort only, rates of preterm delivery were significantly different between BMI categories (P = 0.005, Table 3). Based on data from Table S1, Figure S3 presents a forest plot depicting aOR (95% CI) for preterm delivery by BMI category in the T1DM cohort (forest plot not available for T2DM as none of the normal weight women with T2DM had preterm delivery). Amongst those with T2DM, each 1 kg/m² increase in BMI was associated with a small but statistically significant increase in the odds of preterm delivery which remained significant after adjusting for potential confounders (aOR1 1.042, 95% CI 1.001 to 1.084, Table S2).

In the T2DM cohort only, each 1 kg/m² increase in maternal BMI above the ethnicity‐adjusted upper limit of normal weight was associated with a small but statistically significant increase in the odds of significant proteinuria. There was no statistically significant difference between BMI categories in retinopathy screening rates in either the T1DM or T2DM cohorts (Table 3). Amongst screened women with T1DM, those with obesity had over five times the odds of retinopathy compared to normal weight women (Table S1). In the T2DM cohort, the retinopathy screening rates during pregnancy were relatively low; no cases of retinopathy were found in the normal weight women, while those with overweight were noted to have a higher odds of retinopathy when compared to those with obesity (OR 5.333, 95% CI 1.038 to 27.392).

In the T1DM cohort only, women with overweight and obesity had higher odds of caesarean delivery (all types) compared to normal weight women (Table S1). Furthermore, each 1 kg/m² increase in maternal BMI was associated with a ~ 20% increase in the odds of caesarean delivery in T1DM (Table S2). However, no significant differences were observed across BMI categories with regard to the proportion requiring emergency caesarean delivery for either diabetes type (Table 3).

No significant differences in the rates of miscarriage, termination of pregnancy, polyhydramnios, induction of labor, or instrumental delivery were observed across BMI categories in either the T1DM or T2DM cohorts (Table 3).

Exploring associations between maternal BMI and rates of LGA infants or other neonatal outcomes in type 1 diabetes mellitus and type 2 diabetes mellitus cohorts

Neonatal outcomes are presented in Table 4, with exploratory regression analyses presented in Table S4 (BMI as a categorical variable, categorical outcomes), Table S5 (BMI as a continuous variable, categorical outcomes), and Table S6 (BMI as a continuous variable, continuous outcomes).

In the T2DM cohort, both the proportion of LGA infants and the mean birth weight centile differed significantly between maternal BMI categories (P < 0.05 for both, Table 4). For those with T2DM, each 1 kg/m² increase in maternal BMI was associated with a small increase in the odds of having an LGA infant, though this was no longer significant following adjustment for maternal age and total daily insulin dose at delivery, or chronic hypertension and mean HbA1c over 3 trimesters, or aspirin use and smoking status (Table S5). Similarly, each 1 kg/m² increase in BMI was associated with a small rise in the birth weight centile in the T2DM cohort, though this was no longer significant after adjustment for maternal ethnicity, paternal ethnicity, mean HbA1c over 3 trimesters, aspirin use, and smoking status (Table S6). In the T1DM cohort, we did not find statistically significant differences between BMI categories with regard to the proportion of LGA infants or the mean birth weight centile. Based on data from Table S4, Figure S4 presents a forest plot depicting aOR (95% CI) for LGA by BMI category in the T1DM cohort (forest plot not available for T2DM as none of the normal weight women with T2DM had LGA babies). The proportion of SGA infants did not differ by BMI category for either T1DM or T2DM cohorts (Table 4).

There was no statistically significant difference between BMI categories in the proportion with NICU admissions in the T1DM cohort (Table 4). For the obesity vs overweight comparison in the T2DM cohort, the odds of NICU admission remained lower for those with overweight after adjustment for potential confounders [aOR1 0.387 (95% CI 0.162 to 0.808]; Table S4). Rates of neonatal hypoglycemia, neonatal respiratory distress, and shoulder dystocia were not significantly different between BMI categories for both the T1DM and T2DM cohorts (Table 4).

The rates of congenital anomalies (both total and major) were not significantly different between BMI categories for both T1DM and T2DM cohorts (noting the rarity of this outcome), though it is important to note that all six cases of major congenital anomalies in the T2DM cohort occurred in those with obesity while the distribution was relatively even between BMI categories in the T1DM cohort (Table 4). The rates of stillbirth or neonatal mortality did not significantly differ between BMI categories for both T1DM and T2DM cohorts (Table 4).

DISCUSSION

We found that, amongst those with treated T1DM, obesity was associated with higher odds of exceeding the first trimester HbA1c target as well as increased odds of excess GWG, caesarean delivery, and retinopathy (amongst screened women), but without an additional independent effect on overall neonatal outcomes. Amongst the women with T2DM, increasing maternal BMI (as a continuous variable) was associated with increased odds of pre‐eclampsia, preterm delivery, and significant proteinuria. For both T1DM and T2DM, increasing BMI was associated with significant increases in the total daily insulin dose at delivery. We reported outcomes separately in the T1DM and T2DM cohorts, allowing informal and indirect comparisons at most. We performed regression analyses in an exploratory and hypothesis‐generating manner, and the data should not be interpreted as confirming definitive effects. Larger‐scale studies are required to directly compare the effects of maternal overweight/obesity on pregnancy outcomes in T1DM vs T2DM.

The high rates of suboptimal glycemia during the first trimester, especially in those with T1DM and overweight or obesity, are particularly concerning due to the critical effects of glycemia on fetal organogenesis. ³³ , ³⁴ With regard to the increasing odds of exceeding first trimester HbA1c targets with increasing BMI (as both a continuous and categorical variable) in the T1DM cohort, we speculate that this glycemia treatment gap may partly result from increased difficulty with aggressively treating the presumably more insulin resistant women with obesity in the context of known susceptibility to hypoglycemia during this period. ³⁵ Achieving HbA1c targets in women with T2DM was challenging for women of normal weight and those with obesity, with the best profiles seen in the overweight subgroup. It is possible that women with normal weight and T2DM have a more insulinopenic phenotype, requiring more intensive insulin therapy than currently used. A previous study in Asian Indians with young‐onset T2DM found that, after adjustment for family history of T2DM, sex, insulin sensitivity, and HDL‐cholesterol, the stimulated C‐peptide was 492 pmoL/mL (IQR 353 to 616, P < 0.0001) lower in lean individuals in comparison to those with obesity. ³⁶ The authors of this study proposed that the phenotype of lean, young‐onset diabetes appeared at least in part due to lower beta‐cell function. ³⁶ Our findings are somewhat similar to a UK national cohort study by Murphy et al., ²⁴ which also found that the likelihood of having a first trimester HbA1c of 48 mmol/mol (6.5%) or higher increased with rising maternal BMI in those with T1DM or T2DM.

While we did not find a statistically significant difference in the rates of congenital malformations between BMI categories for either T1DM or T2DM cohorts, it is important to note that all cases of major congenital malformations in the T2DM cohort occurred in infants born to mothers with obesity. It would be important to clarify this trend in larger‐scale studies given the rarity of major congenital malformations.

In the T1DM cohort, we did not find a statistically significant relationship between BMI (as both a categorical and continuous variable) and the risk of pre‐eclampsia, and this aligns with the findings of Abell et al. (2016) ³⁷ who also found that an increase in BMI (as a continuous variable) was not associated with a higher risk of hypertensive complications in pregnancies affected by T1DM. However, Persson et al. (2016) ⁷ found that an increase in maternal BMI (as a categorical variable) was positively associated with pre‐eclampsia risk in women with T1DM. We speculate that differences in glycemia and/or treatment approaches as well as the distribution of adiposity may have contributed to the differences seen between studies. Women with T2DM in our study appear to be vulnerable to the adverse effects of increased BMI on pre‐eclampsia. It is possible that obesity‐related effects on inflammatory adipokines and endothelial dysfunction, which underlie hypertensive disorders, ³⁸ are pronounced in those with T2DM and further research is required to elucidate this. Alternatively, the greater severity of obesity in T2DM and low overall use of aspirin in T2DM may have played a role. We noted that Persson et al. (2016) ⁷ previously reported that obesity was not associated with increased pre‐eclampsia risk in women with T2DM.

Each 1 kg/m² increase in pre‐pregnancy BMI was associated with an increased odds of preterm delivery in women with T2DM; this association remained statistically significant after adjustment for potential confounders, suggesting that obesity is likely associated with increased preterm delivery risk in women with T2DM. There are minimal data in the literature specifically looking at the impact of increasing maternal BMI on preterm delivery risk specifically in women with T2DM. Abell et al. (2017) reported that women with T2DM and overweight/obesity had higher risks of having babies requiring special care nursery admission, but maternal overweight/obesity was not associated with increased risk of other adverse pregnancy outcomes. ³⁹ Amongst the women with T1DM, we did not find a statistically significant association between increasing maternal BMI and the risk of preterm delivery, which is in accordance with the findings of Abell et al. (2016). ³⁷ Persson et al. (2012) ⁴⁰ reported that, when compared to the normal weight (BMI 18.5 to 24.9 kg/m²) women with T1DM, those with T1DM and BMI 25 to 29.9 kg/m² had a small but statistically significant increase in the odds of preterm delivery (aOR 1.22, 95% CI 1.02 to 1.47) while this was borderline for those with T1DM and BMI ≥30 kg/m² (aOR 1.25, 95% CI 1.00 to 1.56). It should be noted that Persson et al. (2012) ⁴⁰ reported markedly lower preterm delivery rates in T1DM (20% for BMI 18.5 to 24.9 kg/m², and 23% for BMI 25 to 29.9 kg/m² as well as BMI ≥30 kg/m²) when compared with our study. In our cohort, the relatively high proportion with preterm delivery in normal weight women with T1DM may have masked any effect of obesity on preterm delivery.

We did not find a statistically significant difference in the odds of emergency caesarean delivery between BMI categories in both T1DM and T2DM cohorts. In the T1DM cohort only, the odds of having any type of caesarean delivery were significantly higher in those with overweight or obesity when compared with the women with normal weight. Persson et al. (2012) ⁴⁰ previously also reported that, amongst women with T1DM, the odds of caesarean delivery were significantly increased in women with obesity and overweight, when compared to normal weight women. In contrast, Abell et al. (2016) ³⁷ reported that increasing maternal BMI (as a continuous variable) was not associated with an increased risk of caesarean delivery in women with T1DM.

We found that the odds of having an LGA infant was significantly different between BMI categories in the T2DM cohort. The association of maternal obesity with LGA risk in T2DM was potentially in part explained by associated differences in glycemic control rather than an independent effect of obesity or GWG. Any independent effect of obesity on LGA risk in T1DM may be masked by the already high rate of LGA infants (55.4%) amongst normal weight women with T1DM in our cohort. Previously, Abell et al. (2016) ³⁷ found that the aOR for LGA babies in those with T1DM and BMI ≥30 kg/m² was 3.7 (95% CI 1.02 to 13.2, adjusted for maternal age and with normal weight T1DM as the reference), but no significant difference in the likelihood of LGA babies was found when BMI was assessed as a continuous variable.

A major strength of our study is the granularity of our data as well as the inclusion of analyses with maternal BMI as both a categorical and continuous variable, in the context of previous studies ⁷ , ³⁷ reporting different results for certain outcomes depending on how BMI was analyzed. Furthermore, our exploratory regression analyses have incorporated adjustments for both maternal and paternal ethnicity when able, which is highly relevant given there is some evidence indicating increased risk of adverse perinatal outcomes amongst interracial couples. ⁴¹ Given this is a single‐center study, our data were limited by the availability of a relatively small number of women with obesity in the T1DM cohort, and a relatively small number of normal weight women in the T2DM cohort. We acknowledge that the small subgroup sizes (particularly in the T1DM with obesity subgroup and the T2DM with normal weight subgroup) limited statistical power and increased the risk of type II error. Consequently, null findings in these subgroups should be interpreted with caution and should not be considered as definitive evidence of no association. We acknowledge that adjustment for a single covariate does not adequately control for confounding in the exploratory regression analyses for pre‐eclampsia; in this case, there were not enough events to facilitate adjustment for several covariates in the same model. Due to our relatively small sample size, in some instances we adjusted for groups of covariates in separate models. Larger‐scale studies would allow the analysis of a wider range of covariates of interest and also facilitate the analysis of variables that seemed significant on the separate models in an overall model as appropriate. The trends shown in our separate exploratory analyses in T1DM and T2DM require confirmation and clarification with larger studies. Larger‐scale studies are required to make direct and formal comparisons of the effects of maternal overweight/obesity on pregnancy outcomes in T1DM vs T2DM. Ideally, larger prospective cohorts should be specifically designed to investigate this, though this may not always be possible given the nature of the data required. Our single‐center cohort study is strengthened by the consistency of the medical care provided to the women included. For improved generalizability of results, pooling of data from multiple centers could be considered for future studies.

Family history of diabetes, as well as pre‐existing nephropathy, neuropathy, lipid profile data, or antihypertensive treatment data are currently not routinely available in our electronic dataset. We acknowledge that unmeasured baseline differences may have influenced the observed associations across BMI groups for the T1DM and T2DM cohorts. Preconception data such as HbA1c, total daily insulin dose, or urine albumin: creatinine ratio measurements were not routinely available in the electronic dataset for this study as preconception care often occurred outside of our center. We acknowledge this as a limitation of our study. Additionally, we acknowledge that the interpretation of HbA1c measurements can be challenging in the context of hematological conditions or physiological changes during pregnancy. At present, fasting and postprandial capillary or plasma glucose levels are not routinely available at standardized timepoints in our electronic dataset, and it would be useful to capture this data in future studies to facilitate a broader view of glycemia and any excursions. Continuous glucose monitoring (CGM) data were not routinely available in the study dataset as CGM devices are currently not funded by the Australian government for people with T2DM. With the increasing uptake of technologies such as CGM devices and automated insulin delivery systems, it would be important for future studies to explore the effects of these technologies on pregnancy outcomes in women with obesity and pregestational diabetes.

Our findings highlight the potential need for tailored interventions and careful monitoring of pregnant women with pregestational diabetes, with consideration of their degree of overweight/obesity. Overall, our data provisionally support the need for optimizing early trimester glycemia in those with T1DM and obesity, as well as the need to pay greater attention to the escalating risks of pre‐eclampsia and preterm delivery in those with T2DM and obesity. The majority of women with overweight or obesity in both our T1DM and T2DM cohorts had excess GWG, and strategies to improve adherence to GWG recommendations may potentially improve any weight and/or GWG‐mediated risks on pregnancy outcomes. Given the potential for complex interplay between BMI, diabetes subtype, and pregnancy outcomes, further large‐scale studies are required to confirm our findings by directly comparing the effects of maternal overweight/obesity on pregnancy outcomes in T1DM vs T2DM and to deepen our understanding of the underlying biological mechanisms.

DISCLOSURE

The authors declare no conflicts of interest.

Approval of the research protocol: The study protocol was approved by the Sydney Local Health District human ethics review committee (X18‐0521 & 2019/ETH08968). This study conforms to the provisions of the Declaration of Helsinki in 1995 (as revised in Fortaleza, Brazil, October 2013) and also meets the requirements of the National Statement on Ethical Conduct in Human Research (issued in 2007, Australia).

Informed consent: N/A. The Sydney Local Health District human ethics review committee granted a waiver of the usual requirement for the consent of the individual for the use of their health information in a research project, in accordance with the Health Records and Information Privacy Act 2002 (NSW), the NSW Privacy Commissioner's Statutory guidelines on research, and the National Health and Medical Research Council (NHMRC) Guidelines approved under Section 95A of the Privacy Act 1988.

Registry and the registration no. of the study/trial: N/A. This is a retrospective cohort study.

Animal studies: No.

PRIOR PRESENTATION

Early preliminary data were presented at the International Congress on Obesity (2024) in Sao Paulo, Brazil (accepted as an oral presentation, but delivered as a virtual poster presentation due to personal reasons) and also at the 2023 International Association of the Diabetes and Pregnancy Study Groups (IADPSG) Meeting in Sydney, New South Wales, Australia (poster presentation).

Supporting information

Table S1. Association of maternal pre‐pregnancy BMI as a categorical variable with maternal categorical outcomes (analyses within diabetes subtype).

Table S2. Association of maternal pre‐pregnancy BMI as a continuous variable with maternal categorical outcomes (analyses within diabetes subtype).

Table S3. Association of maternal pre‐pregnancy BMI as a continuous variable with maternal continuous outcomes (analyses within diabetes subtype).

Table S4. Association of maternal pre‐pregnancy BMI as a categorical variable with neonatal categorical outcomes (analyses within diabetes subtype).

Table S5. Association of maternal pre‐pregnancy BMI as a continuous variable with neonatal categorical outcomes (analyses within diabetes subtype).

Table S6. Association of maternal pre‐pregnancy BMI as a continuous variable with neonatal continuous outcomes (analyses within diabetes subtype).

Figure S1. Forest plot: Pre‐eclampsia in T1DM by BMI category (based on data from Table S1).

Figure S2. Forest plot: Pre‐eclampsia in T2DM by BMI category (based on data from Table S1).

Figure S3. Forest plot: Preterm delivery in T1DM by BMI category (based on data from Table S1).

Figure S4. Forest plot: LGA in T1DM by BMI category (based on data from Table S4).

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ACKNOWLEDGMENT

X.M.Z is supported by an Australian National Health and Medical Research Council (NHMRC) Postgraduate Scholarship. No funding was received specifically for this study. Open access publishing facilitated by The University of Sydney, as part of the Wiley ‐ The University of Sydney agreement via the Council of Australasian University Librarians

DATA AVAILABILITY STATEMENT

The data that support the findings of this study are available on request from the corresponding author. The data are not publicly available due to privacy or ethical restrictions.

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