Comparative epidemiology of gestational diabetes in ethnic Chinese from Shanghai birth cohort and growing up in Singapore towards healthy outcomes cohort.

BACKGROUND: Gestational diabetes mellitus (GDM) has been associated with adverse health outcomes for mothers and offspring. Prevalence of GDM differs by country/region due to ethnicity, lifestyle and diagnostic criteria. We compared GDM rates and risk factors in two Asian cohorts using the 1999 WHO and the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria.
METHODS: The Shanghai Birth Cohort (SBC) and the Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort are prospective birth cohorts. Information on sociodemographic characteristics and medical history were collected from interviewer-administered questionnaires. Participants underwent a 2-h 75-g oral glucose tolerance test at 24-28 weeks gestation. Logistic regressions were performed.
RESULTS: Using the 1999 WHO criteria, the prevalence of GDM was higher in GUSTO (20.8%) compared to SBC (16.6%) (p = 0.046). Family history of hypertension and alcohol consumption were associated with higher odds of GDM in SBC than in GUSTO cohort while obesity was associated with higher odds of GDM in GUSTO. Using the IADPSG criteria, the prevalence of GDM was 14.3% in SBC versus 12.0% in GUSTO. A history of GDM was associated with higher odds of GDM in GUSTO than in SBC, while being overweight, alcohol consumption and family history of diabetes were associated with higher odds of GDM in SBC.
CONCLUSIONS: We observed several differential risk factors of GDM among ethnic Chinese women living in Shanghai and Singapore. These findings might be due to heterogeneity of GDM reflected in diagnostic criteria as well as in unmeasured genetic, lifestyle and environmental factors.

Background

The Developmental Origins of Health and Disease (DoHaD) hypothesis states that exposure to environmental and lifestyle factors during critical window periods in the prenatal, perinatal and early postnatal phases influences the subsequent development of non-communicable diseases in the offspring [1]. Pregnancy is among the most important periods of development, which can be complicated by gestational diabetes mellitus (GDM) characterized by glucose intolerance with the first recognition during pregnancy [2], complicating about 14% of pregnancies globally [3].

GDM has been associated with adverse health outcomes for both mother and child [4]; women with GDM are at increased risk of developing type 2 diabetes mellitus [5], cardiovascular diseases [6] and renal diseases [7] later in life. The hyperglycemic intrauterine environment in GDM has been found to increase the risk of fetal macrosomia and associated fetal complications such as shoulder dystocia, hyperinsulinemia and neonatal morbidities [8]. In addition, babies born to women with GDM have a greater propensity to develop type 2 diabetes mellitus and obesity later in life. These findings highlight the importance of evaluating risk factors and deriving strategies to prevent and treat GDM which may induce epigenetic modifications in utero [9].

Established risk factors for GDM include a previous pregnancy with GDM [10], pre-pregnancy overweight and obesity [11, 12], excessive gestational weight gain [12, 13], advanced maternal age [14], family history of diabetes [14], infant sex, alcohol consumption, family history of hypertension, parity and smoking [15]. Maternal weight gain in early pregnancy that disproportionately consists of increased fat deposition could impact on subsequent maternal insulin resistance [13].

There are global differences in the prevalence of GDM which varies from pooled prevalence of 5.4% to 11.5% in meta-analyses of studies from Europe and Asia, respectively [16, 17] due to differences in factors such as diagnostic criteria, ethnicity, lifestyle, and environmental factors. Given the differences in GDM prevalence between Shanghai and Singapore [18, 19] as well as varying lifestyle and environmental exposures, we sought to compare the rates and risk factors of GDM in two contemporary Asian Chinese cohorts, the Shanghai Birth Cohort (SBC) and the Growing Up in Singapore Towards healthy Outcomes cohort (GUSTO).

Methods

Study design and population

Shanghai birth cohort

The Shanghai Birth Cohort (SBC) recruited pregnant mothers who sought prenatal care at six obstetric care hospitals in Shanghai, from 2013–2016. Couples who were at least 20 years old, comprised of at least one registered Shanghai resident, intended to obtain prenatal care and deliver at hospitals involved in SBC, lived in Shanghai for at least 2 years and were willing to be involved in the study for at least 2 years were invited to participate [20]. The study protocol was approved by the ethics committee of Shanghai Xinhua Hospital (XHEC-C-2013-001, approved on 7 January 2013) and all participating hospitals. All methods were performed in accordance with the approved guidelines and regulations. All participants gave a written informed consent. In this study, we randomly sampled 1000 out of 3692 participants of Chinese ethnicity who were not receiving chemotherapy or psychotropic drugs from the SBC for comparisons to Chinese participants in the GUSTO cohort so that the selected cohort size is comparable to the GUSTO cohort size.

GUSTO cohort

The Growing Up in Singapore Towards healthy Outcomes (GUSTO) cohort study recruited pregnant women attending their first-trimester antenatal dating ultrasound scan clinics at two major public maternity units in Singapore, KK Women’s and Children’s Hospital and National University Hospital from June 2009 to September 2010. Pregnant women aged 18 years and above, from any one of the three major ethnic groups (Chinese, Malay and Indian), who were Singapore citizens or permanent residents and had the intention of delivering in either hospital as well as staying in Singapore for at least the next 5 years, and who had agreed to donate their birth tissues were invited to participate. Women who had type 1 diabetes mellitus, or who were receiving chemotherapy or psychotropic drugs were excluded. Information on sociodemographic characteristics and medical history were collected from interviewer administered questionnaires [21]. The study protocol was approved by the ethics committees of the hospitals involved: SingHealth Centralized Institutional Review Board (2018/2767, approved on 2 March 2019) and the National Healthcare Group Domain Specific Review Board (D/2009/021, approved on 26 February 2009) in Singapore. All methods were performed in accordance with the approved guidelines and regulations. All participants gave written informed consent. In this study, only GUSTO participants of Chinese ethnicity (out of 1247 subjects) were included in the analysis.

Subject follow up and assessment of maternal blood glucose concentrations

Participants from SBC were followed up at the recruitment visit (≤17 weeks) and at 24–26 weeks gestation. Questionnaires were administered to collect information on demographics, socio-economic status, lifestyle, obstetric and medical history [20]. Pre-pregnancy weight was self-reported while weight at early pregnancy was measured in the prenatal care clinic. Early pregnancy in SBC was defined as gestational age ≤ 17 weeks so as to include all women who received their first antenatal care in the hospital. Participants underwent a 75-g oral glucose tolerance test (OGTT) at 24–28 weeks’ gestation; fasting (FG), 1-h plasma glucose (1hPG) and 2-h plasma glucose (2hPG) concentrations were obtained using automated biochemical analyzer Hitachi LABOSPECT 008. Information on weight and length of the infant at birth was obtained from hospital medical records.

Participants from GUSTO were followed up at the recruitment visit (< 14 weeks) and at 24–28 weeks of gestation when questionnaires were administered to collect information on demographics, socio-economic status, lifestyle, obstetric and medical history [21]. Pre-pregnancy weight was self-reported while weight at early pregnancy was obtained from case notes. Participants underwent a 75-g OGTT at 24–28 weeks’ gestation; overnight fasting (8–10 h) and 2-h postprandial blood specimens were collected. Colorimetry [Advia 2400 Chemistry system (Siemens Medical Solutions Diagnostics) and Beckman LX20 Pro analyzer (Beckman Coulter)] was used to measure both fasting and 2-h postprandial plasma glucose concentrations. Information on weight and length of the infant at birth obtained from hospital medical records.

Plasma glucose concentrations were used to classify GDM according to the 1999 WHO criteria: ≥7.0 mmol/L for FPG and/or ≥ 7.8 mmol/L for 2hPG in the 2-h 75-g OGTT, and the International Association of Diabetes and Pregnancy Study Groups (IADPSG) criteria: if any one of the plasma glucose values was at or above the following thresholds: 5.1 mmol/L for FPG, 10.0 mmol/L 1hPG and 8.5 mmol/L for 2hPG. Pre-pregnancy body mass index (BMI; kg/m2) was calculated as pre-pregnancy weight (kg) divided by height2 (m2) and categorized as underweight (< 18.5 kg/m2), normal weight (18.5–22.9 kg/m2), overweight (23.0–27.4 kg/m2) and obese (≥ 27.5 kg/m2) [22]. Gestational weight gain (GWG) in early pregnancy was defined by weight gain from pre-pregnancy to recruitment visit.

Statistical analysis

All analyses were performed using SPSS for Windows version 26.0 (SPSS Inc., Chicago, IL, USA) with statistical significance set at 2-sided p < 0.05. Descriptive statistics for numerical variables were presented as mean (SD) and n (%) for categorical variables. Differences in numerical variables were assessed using 2 sample t-test when normality and homogeneity assumptions were satisfied; otherwise, Mann-Whitney U test was used. Chi-square or Fisher exact test was used for categorical variables. Birthweight percentiles categorization was based on methods described by Mikolajczyk et al. Large and small for gestational age babies were defined >90th and < 10th percentiles, respectively [23]. We standardized GWG in early pregnancy and its velocity (kg/week) into z scores, using BMI category-specific mean and SD values derived from the corresponding study cohort [23]. Predictors of GDM were assessed in logistic regression models for each cohort separately. Interaction effects between predictors were tested in the regression models. We reported odds ratio as prospective data was collected on the prevalence of GDM. The differences across the two cohorts were compared using summarized Z-test. Further analysis was performed in GUSTO cohort by adding citizenship status into the model.

Results

Comparison of demographic variables between SBC and GUSTO cohort

After removal of subjects with late enrolment in the SBC, with non-singleton pregnancy, of non-Chinese ethnicity and with pre-existing diabetes, there were 734 and 677 subjects left in SBC and GUSTO, respectively, in the analysis (Fig. 1). Characteristics of study participants in the two cohorts were presented in Table 1. GUSTO participants had lower gestational age at delivery (38.8 ± 1.4 vs 39.0 ± 1.5 weeks, p = 0.002), fasting plasma glucose concentrations (4.3 ± 0.4 vs 4.4 ± 0.4 mmol/L, p < 0.001), pre-pregnancy weight (54.5 ± 9.5 vs 56.6 ± 8.7 kg, p < 0.001), weight at early pregnancy (56.8 ± 10.3 vs 59.1 ± 9.4 kg, p < 0.001), GWG during early pregnancy (1.9 ± 2.4 vs 2.5 ± 3.2 kg, p = 0.001), and were shorter (159.1 ± 5.6 vs 162.2 ± 4.6 cm, p < 0.001) and older (32.1 ± 4.8 vs 29.8 ± 3.7 years, p < 0.001) compared to SBC participants.

Fig. 1

Out of 1000 selected subjects from SBC and 1247 subjects in GUSTO, 734 and 677 respectively were included in the analysis after removal of subjects of non-Chinese ethnicity, with late enrolment, non-singleton pregnancy and pre-existing diabetes

Table 1

Characteristics of included study participants in SBC and GUSTO cohort

Characteristics	SBC(n = 734)	GUSTO(n = 677)	P-value
Maternal age	29.8 ± 3.7	32.1 ± 4.8	< 0.001
Plasma glucose fasting, mmol/L	4.4 ± 0.4	4.3 ± 0.4	< 0.001
Plasma glucose 1 h, mmol/L	7.6 ± 1.6	NA	NA
Plasma glucose 2 h, mmol/L	6.5 ± 1.4	6.6 ± 1.4	0.143
Pre-pregnancy BMI, kg/m2	21.5 ± 3.2	21.6 ± 3.4	0.637
BMI at early pregnancy, kg/m2	22.5 ± 3.4	22.4 ± 3.7	0.320
Pre-pregnancy weight, kg	56.6 ± 8.7	54.5 ± 9.5	< 0.001
Weight at early pregnancy, kg	59.1 ± 9.4	56.8 ± 10.3	< 0.001
GWG at early pregnancy, kg	2.5 ± 3.2	1.9 ± 2.4	0.001
GWG velocity at early pregnancy, kg/week	0.2 ± 0.2	0.2 ± 0.2	0.911
Height, cm	162.2 ± 4.6	159.1 ± 5.6	< 0.001
Pre-pregnancy BMI (kg/m2)			0.369
<18.5(underweight)	109(14.9 %)	82(13.5 %)
≥ to < 23 (normal)	436(59.4 %)	365(60.2 %)
≥ to < 27.5 (overweight)	154(21.0 %)	118(19.5 %)
≥ (obese)	35(4.8 %)	41(6.8 %)
GWG in early pregnancy (z score)			0.985
<-1	82(11.2 %)	68(11.5 %)
-1 to 1	552(75.6 %)	446(75.2 %)
> 1	96(13.2 %)	79(13.3 %)
Alcohol consumption during pregnancy	2(0.3 %)	21(3.3 %)	< 0.001
Family history of diabetes	62(9.2 %)	165(24.4 %)	< 0.001
Family history of hypertension	225(32.7 %)	279(41.2 %)	0.001
Current or ever smoker	22(3.0 %)	61(9.4 %)	< 0.001
History of GDM in previous pregnancy	3(0.4 %)	22(3.2 %)	< 0.001
Personal history of chronic hypertension	1(0.1 %)	8(1.2 %)	0.017
Parous	84(11.5 %)	316(48.8 %)	< 0.001
Gestational age at delivery, week	39.0 ± 1.5	38.8 ± 1.4	0.002
Male fetus	349(49.7 %)	340(52.6 %)	0.298
Citizenship status	NA		NA
Singapore Citizen born in Singapore		379(56.0 %)
Converted Citizen or permanent resident		298(44.0 %)

A higher proportion of GUSTO participants consumed alcohol during pregnancy compared to SBC participants (3.3% versus 0.3%, Table 1), were currently smoking or had ever smoked (9.4% versus 3.0%), had a family history of diabetes (24.4% versus 9.2%), had a family history of hypertension (41.2% versus 32.7%), had a history of GDM in a previous pregnancy (3.2% versus 0.4%) and had a personal history of hypertension (1.2% vs 0.1%) compared to SBC participants. More GUSTO participants were parous compared to SBC participants (48.8% versus 11.5%).

Comparison of risk factors of GDM between SBC and GUSTO cohort

Using the 1999 WHO criteria, the prevalence of GDM was higher in GUSTO cohort (20.8%) compared to SBC (16.6%) (p = 0.046). Using the IADPSG criteria, the prevalence of GDM was 14.3% in SBC (using all three glucose time point measures) versus 12.0% in GUSTO (defined by the fasting and 2 h glucose data only).

1999 WHO criteria

Using the 1999 WHO criteria in the SBC, GDM was associated with maternal age (OR 1.1, 95% CI 1.0–1.2, p = 0.020) and pre-pregnancy BMI (OR 1.1, 95% CI 1.0–1.2, p = 0.028, Table 2). Further analysis with pre-pregnancy BMI categories showed that overweight (OR 2.3, 95% CI 1.3–3.9, p = 0.004, Table 3) was associated with GDM. Family history of hypertension and alcohol consumption were associated with higher odds of GDM in SBC than in GUSTO cohort (Tables 2 and 3). The analysis was repeated with the use of GWG velocity z score and similar results were obtained (Supplementary Tables 1 and 2, Additional file 1).

Table 2

Associations between risk factors and GDM defined by 1999 WHO criteria in SBC and GUSTO cohort

GDM	Shanghai Birth cohortUnadjusted		GUSTO Birth CohortUnadjusted		Shanghai Birth cohortAdjusted		GUSTO Birth CohortAdjusted		P-value*
	OR (95 % CI)	P-value	OR (95 % CI)	P-value	OR (95 % CI)	P- value	OR (95 % CI)	P- value
Maternal age	1.08(1.03–1.14)	0.003	1.09(1.04–1.14)	< 0.001	1.1(1.0-1.2)	0.020	1.09(1.03–1.14)	0.001	1.000
Pre-pregnancy BMI	1.08(1.03–1.15)	0.005	1.11(1.05–1.17)	< 0.001	1.1(1.0-1.2)	0.028	1.1(1.0-1.2)	0.002	1.000
GWG at early pregnancy (z score)
<-1	1.0		1.0		1.0		1.0
-1 to 1	0.96(0.52–1.78)	0.894	1.6(0.8–3.2)	0.208	1.0(0.5–2.2)	0.955	1.7(0.8–3.5)	0.175	0.189
> 1	0.97(0.44–2.13)	0.942	1.8(0.8–4.2)	0.173	0.88(0.34–2.25)	0.786	1.7(0.7-4.0)	0.258	0.211
Alcohol consumption	5.1(0.3–82.0)	0.251	0.67(0.19–2.32)	0.526	8.8(0.5-144.8)	0.128	0.73(0.20–2.64)	0.632	< 0.001
Family history of diabetes	1.6(0.8-3.0)	0.165	1.0(0.6–1.6)	0.981	1.0(0.5–2.1)	0.996	0.86(0.52–1.43)	0.566	0.755
Family history of hypertension	1.6(1.0-2.4)	0.032	0.78(0.53–1.16)	0.223	1.5(0.9–2.5)	0.092	0.67(0.43–1.04)	0.076	0.016
Current or ever smoker	1.1(0.4–3.4)	0.842	0.79(0.39–1.61)	0.515	1.6(0.4-6.0)	0.509	1.1(0.5–2.3)	0.858	0.528
Parous	1.0(0.5–1.8)	1.000	1.2(0.8–1.7)	0.470	0.74(0.34–1.61)	0.443	0.97(0.64–1.49)	0.893	0.610
Male fetus	1.1(0.7–1.7)	0.633	1.1(0.7–1.6)	0.781	1.1(0.7–1.7)	0.801	1.1(0.7–1.6)	0.744	1.000

Adjusted for maternal age, pre-pregnancy BMI, GWG at early pregnancy (z score), alcohol consumption, family history of diabetes, family history of hypertension, smoking status, parity, fetal sex

In the adjusted model, 74.4 % of SBC subjects (546 out of 734) were used, 82.9 % of GUSTO subjects (561 out of 677) were used

*P value for the difference between the two cohorts in the adjusted model

Table 3

Effect of GWG among women of different pre-pregnancy BMI and fetal sex on GDM development defined by 1999 WHO criteria

GDM	Shanghai Birth cohortUnadjusted		GUSTO Birth CohortUnadjusted		Shanghai Birth cohortAdjusted		GUSTO Birth CohortAdjusted		P-value*
	OR (95 % CI)	P-value	OR (95 % CI)	P-value	OR (95 % CI)	P-value	OR (95 % CI)	P-value
Maternal age	1.08(1.03–1.14)	0.003	1.09(1.04–1.14)	< 0.001	1.1(1.0-1.2)	0.014	1.08(1.03–1.13)	0.003	1.000
GWG at early pregnancy (z score)	0.86(0.70–1.05)	0.133	1.2(1.0-1.5)	0.085	0.69(0.44–1.08)	0.106	1.2(0.8–1.7)	0.444	0.088
Pre-pregnancy BMI
< 18.5	0.72(0.37–1.39)	0.324	0.93(0.49–1.80)	0.838	0.85(0.38–1.90)	0.687	1.0(0.5–2.1)	0.911	0.785
≥ 18.5 to < 23	1.0		1.0		1.0		1.0
≥ 23 to < 27.5	1.8(1.2–2.9)	0.009	1.9(1.1-3.0)	0.014	2.3(1.3–3.9)	0.004	1.7(1.0-2.9)	0.047	0.124
≥ 27.5	2.0(0.9–4.5)	0.088	3.7(1.8–7.3)	< 0.001	1.9(0.7–5.5)	0.239	3.7(1.8–7.8)	< 0.001	0.005
Alcohol consumption	5.1(0.3–82.0)	0.251	0.67(0.19–2.32)	0.526	8.7(0.5-144.1)	0.130	0.75(0.21–2.69)	0.656	< 0.001
Family history of diabetes	1.6(0.8-3.0)	0.165	1.0(0.6–1.6)	0.981	0.99(0.48–2.04)	0.967	0.84(0.50–1.41)	0.512	0.717
Family history of hypertension	1.6(1.0-2.4)	0.032	0.78(0.53–1.16)	0.223	1.5(0.9–2.5)	0.100	0.69(0.43–1.08)	0.103	0.021
Current or ever smoker	1.1(0.4–3.4)	0.842	0.79(0.39–1.61)	0.515	1.8(0.4-7.0)	0.421	1.1(0.5–2.3)	0.880	0.398
Parous	1.0(0.5–1.8)	1.000	1.2(0.8–1.7)	0.470	0.68(0.31–1.50)	0.338	1.0(0.7–1.6)	0.880	0.481
Male fetus	1.1(0.7–1.7)	0.633	1.1(0.7–1.6)	0.781	1.1(0.7–1.7)	0.783	1.0(0.7–1.6)	0.868	0.747

Adjusted for maternal age, GWG at early pregnancy, pre-pregnancy BMI group, alcohol consumption, family history of diabetes, family history of hypertension, smoking status, parity, fetal sex

In the adjusted model, 74.4 % of SBC subjects (546 out of 734) were used, 82.9 % of GUSTO subjects (561 out of 677) were used

*P value for the difference between the two cohorts in the adjusted model

Interaction between GWG and pre pregnancy BMI group and fetal sex were included in the model but not significant

Overall interaction for GWG and pre pregnancy BMI group: p = 0.737 for SBC, p = 0.088 for GUSTO

Interaction for GWG and fetal sex: p = 0.254 for SBC, p = 0.674 for GUSTO

In the GUSTO cohort, GDM was associated with maternal age (OR 1.09, 95% CI 1.03–1.14, p = 0.001) and pre-pregnancy BMI (OR 1.1, 95% CI 1.0–1.2, p = 0.002, Table 2). Further analysis with pre-pregnancy BMI categories showed that overweight (OR 1.7, 95% CI 1.0–2.9, p = 0.047) and obesity (OR 3.7, 95% CI 1.8–7.8, p < 0.001, Table 3) were associated with GDM. Obesity was associated with higher odds of GDM in GUSTO than in SBC (Table 3). The analysis was repeated using GWG velocity z score and similar results were obtained (Supplementary Tables 1 and 2, Additional file 1). GWG velocity in early pregnancy was associated with higher odds of development of GDM in GUSTO compared to SBC (p = 0.022, Supplementary Table 1, Additional file 1).

Further analysis was performed in GUSTO cohort by adding citizenship status in the model. Using the 1999 WHO criteria, maternal age remained significantly associated with GDM (OR 1.1, 95% CI 1.0–1.2, p = 0.003, Supplementary Table 3, Additional file 1). Analysis with pre-pregnancy BMI categories also showed that maternal age remained significantly associated with GDM (OR 1.1, 95% CI 1.0–1.2, p = 0.003) and obesity (OR 12.2, 95% CI 1.6–93.4, p = 0.016, Supplementary Table 4, Additional file 1) was associated with GDM. There were no significant interactions between citizenship status and all risk factors (Supplementary Tables 3 and 4, Additional file 1). The analysis was repeated using GWG velocity z score and similar results were obtained (Supplementary Tables 5 and 6, Additional file 1).

IADPSG criteria

Using the IADPSG criteria in the SBC, GDM was associated with maternal age (OR 1.1, 95% CI 1.0–1.2, p = 0.046) and pre-pregnancy BMI (OR 1.14, 95% CI 1.05–1.23, p = 0.001, Table 4). Further analysis with pre-pregnancy BMI categories showed that overweight (OR 2.5, 95% CI 1.4–4.4, p = 0.002) and obesity (OR 3.6, 95% CI 1.3–9.6, p = 0.011, Table 5) were associated with GDM. Being overweight, having family history of diabetes and alcohol consumption were associated with higher odds of GDM in the SBC than in the GUSTO cohort (Tables 4 and 5). The analysis was repeated using GWG velocity z score and similar results were obtained (Supplementary Tables 7 and 8, Additional file 1).

Table 4

Associations between risk factors and GDM defined by IADPSG criteria in SBC and GUSTO cohort

GDM	Shanghai Birth cohortUnadjusted		GUSTO Birth CohortUnadjusted		Shanghai Birth cohortAdjusted		GUSTO Birth CohortAdjusted		P-value*
	OR (95 % CI)	P-value	OR (95 % CI)	P-value	OR (95 % CI)	P- value	OR (95 % CI)	P- value
Maternal age	1.1(1.0-1.2)	0.002	1.08(1.03–1.14)	0.004	1.1(1.0-1.2)	0.046	1.06(1.00-1.13)	0.064	1.000
Pre-pregnancy BMI	1.14(1.07–1.21)	< 0.001	1.13(1.06–1.21)	< 0.001	1.14(1.05–1.23)	0.001	1.1(1.0-1.2)	0.006	1.000
GWG at early pregnancy (z score)
<-1	1.0		1.0		1.0		1.0
-1 to 1	1.0(0.5-2.0)	0.998	1.2(0.5–2.8)	0.662	1.4(0.6–3.5)	0.403	1.2(0.5–2.8)	0.727	0.750
> 1	1.6(0.7–3.6)	0.260	1.4(0.5–3.8)	0.529	2.1(0.8–5.6)	0.159	1.3(0.5–3.8)	0.616	0.265
Alcohol consumption	5.8(0.4–93.9)	0.214	0.85(0.19–3.72)	0.824	12.0(0.7–198.0)	0.083	0.99(0.22–4.55)	0.988	< 0.001
Family history of diabetes	2.3(1.3–4.3)	0.008	1.3(0.7–2.2)	0.388	1.8(0.9–3.6)	0.089	0.67(0.35–1.30)	0.240	0.020
Family history of hypertension	1.5(1.0-2.3)	0.077	1.1(0.7–1.8)	0.649	1.4(0.8–2.3)	0.262	0.88(0.51–1.54)	0.661	0.182
Current or ever smoker	0.94(0.27–3.25)	0.928	0.70(0.27–1.80)	0.456	1.6(0.4–6.3)	0.507	0.87(0.31–2.42)	0.783	0.405
Parous	1.2(0.7–2.3)	0.519	1.3(0.8–2.2)	0.225	0.75(0.33–1.72)	0.502	0.90(0.52–1.58)	0.717	0.768
History of GDM in previous pregnancy	12.2(1.1-135.3)	0.042	8.3(3.3–20.7)	< 0.001	2.5(0.2–42.7)	0.520	7.7(2.6–22.4)	< 0.001	< 0.001
Male fetus	0.97(0.63–1.49)	0.873	1.0(0.6–1.6)	0.988	1.0(0.6–1.6)	0.862	0.83(0.49–1.41)	0.496	0.644

Adjusted for maternal age, pre-pregnancy BMI, GWG at early pregnancy (z score), alcohol consumption, family history of diabetes, family history of hypertension, smoking status, parity, history of GDM in previous pregnancy, fetal sex

In the adjusted model, 74.4 % of SBC subjects (546 out of 734) were used, and 82.9 % of GUSTO subjects (561 out of 677) were used

*P value for the difference between the two cohorts in the adjusted model

Table 5

Effect of GWG among women of different pre-pregnancy BMI and fetal sex on GDM development defined by IADPSG criteria

GDM	Shanghai Birth cohortUnadjusted		GUSTO Birth CohortUnadjusted		Shanghai Birth cohortAdjusted		GUSTO Birth CohortAdjusted		P-value*
	OR (95 % CI)	P-value	OR (95 % CI)	P-value	OR (95 % CI)	P-value	OR (95 % CI)	P-value
Maternal age	1.1(1.0-1.2)	0.002	1.08(1.03–1.14)	0.004	1.1(1.0-1.2)	0.030	1.06(0.99–1.12)	0.099	1.000
GWG at early pregnancy (z score)	1.0(0.8–1.3)	0.690	1.1(0.9–1.5)	0.277	1.1(0.7–1.7)	0.722	1.1(0.7–1.8)	0.611	1.000
Pre-pregnancy BMI
< 18.5	0.82(0.40–1.67)	0.579	0.58(0.22–1.53)	0.274	1.0(0.4–2.3)	0.972	0.69(0.25–1.89)	0.471	0.650
≥ 18.5 to < 23	1.0		1.0		1.0		1.0
≥ 23 to < 27.5	2.5(1.5-4.0)	< 0.001	1.5(0.8–2.8)	0.190	2.5(1.4–4.4)	0.002	1.3(0.7–2.6)	0.415	0.007
≥ 27.5	3.7(1.7-8.0)	0.001	4.3(2.0-9.1)	< 0.001	3.6(1.3–9.6)	0.011	3.8(1.7–8.8)	0.001	0.762
Alcohol consumption	5.8(0.4–93.9)	0.214	0.85(0.19–3.72)	0.824	11.8(0.7-196.4)	0.086	1.1(0.2–4.9)	0.939	< 0.001
Family history of diabetes	2.3(1.3–4.3)	0.008	1.3(0.7–2.2)	0.388	1.8(0.9–3.6)	0.081	0.67(0.34–1.32)	0.247	0.022
Family history of hypertension	1.5(1.0-2.3)	0.077	1.1(0.7–1.8)	0.649	1.4(0.8–2.3)	0.250	0.91(0.52–1.60)	0.746	0.213
Current or ever smoker	0.94(0.27–3.25)	0.928	0.70(0.27–1.80)	0.456	1.9(0.5–7.9)	0.373	0.87(0.31–2.44)	0.793	0.241
Parous	1.2(0.7–2.3)	0.519	1.3(0.8–2.2)	0.225	0.68(0.29–1.58)	0.365	0.93(0.53–1.65)	0.810	0.631
History of GDM in previous pregnancy	12.2(1.1-135.3)	0.042	8.3(3.3–20.7)	< 0.001	2.4(0.1–44.6)	0.552	8.3(2.8–24.4)	< 0.001	< 0.001
Male fetus	0.97(0.63–1.49)	0.873	1.0(0.6–1.6)	0.988	0.94(0.56–1.58)	0.822	0.82(0.48–1.42)	0.480	0.754

Adjusted for maternal age, GWG at early pregnancy, pre-pregnancy BMI group, alcohol consumption, family history of diabetes, family history of hypertension, smoking status, parity, history of GDM in previous pregnancy, fetal sex

In the adjusted model, 74.4 % of SBC subjects (546 out of 734) were used while 82.9 % of GUSTO subjects (561 out of 677) were used

*P value refers to the difference between cohorts in the adjusted model

Interaction between GWG and pre pregnancy BMI group and fetal sex was included in the model but not significant

Overall interaction for GWG and pre pregnancy BMI group: p = 0.379 for SBC, p = 0.729 for GUSTO

Interaction for GWG and fetal sex: p = 0.798 for SBC, p = 0.582 for GUSTO

Supplementary Information

Additional file 1. Supplementary tables