Measuring maternal body composition by biomedical impedance can predict risk for gestational diabetes mellitus: a retrospective study among 22,223 women

ObjectiveThe prediction of gestational diabetes mellitus (GDM) by body composition-related indicators in the first trimester was analyzed under different body mass index (BMI) values before pregnancy.MethodsThis was a retrospective analysis of pregnant women who were treated, had documented data, and received regular perinatal care at the Third Affiliated Hospital of Zhengzhou University from January 1, 2021, to December 31, 2021. Women with singleton pregnancies who did not have diabetes before pregnancy were included. In the first trimester (before the 14th week of pregnancy), bioelectric impedance assessment (BIA) was used to analyze body composition-related indicators such as protein levels, mineral levels, fat volume, and the waist-hip fat ratio. The Pearman’s correlation coefficient was used to evaluate the linear relationship between the continuous variables and pre-pregnancy body mass index (BMI). In the univariate body composition analysis, the association with the risk of developing GDM was included in a multivariate analysis using the relative risk and 95% confidence interval obtained from logarithmic binomial regression, and generalized linear regression was used for multivariate regression analysis. Furthermore, the area under the curve (AUC) was calculated by receiver operating characteristic (ROC) curves. The optimal cutoff value of each risk factor was calculated according to the Youden Index.ResultsIn a retrospective study consisting of 6698 pregnant women, we collected 1109 cases of gestational diabetes. Total body water (TBW), protein levels, mineral levels, bone mineral content (BMC), body fat mass (BFM), soft lean mass (SLM), fat-free mass (FMM), skeletal muscle mass (SMM), percent body fat (PBF), the waist-hip ratio (WHR), the visceral fat level (VFL), and the basal metabolic rate (BMR) were significantly higher in the GDM group than in the normal group (P<0.05). Under the pre-pregnancy BMI groupings, out of 4157 pregnant women with a BMI <24 kg/m2, 456 (10.97%) were diagnosed with GDM, and out of 2541 pregnant women with a BMI ≥24 kg/m2, 653 (25.70%) were diagnosed with GDM. In the generalized linear regression model, it was found that in all groups of pregnant women, pre-pregnancy BMI, age, gestational weight gain (GWG) in the first trimester, and weight at the time of the BIA had a certain risk for the onset of GDM. In Model 1, without adjusting for confounders, the body composition indicators were all positively correlated with the risk of GDM. In Model 3, total body water, protein levels, mineral levels, bone mineral content, soft lean mass, fat-free mass, skeletal muscle mass, and the basal metabolic rate were protective factors for GDM. After Model 4 was adjusted for confounders, only the waist-hip ratio was positively associated with GDM onset. Among pregnant women with a pre-pregnancy BMI <24 kg/m2, the body composition-related indicators in Model 2 were all related to the onset of GDM. In Model 3, total body water, soft lean mass, fat-free mass, and the basal metabolic rate were negatively correlated with GDM onset. In the body composition analysis of among women with a pre-pregnancy BMI ≥ 24 kg/m2, only Model 1 and Model 2 were found to show positive associations with GDM onset. In the prediction model, in the basic data of pregnant women, the area under the receiver operating characteristic curve predicted by gestational weight gain for GDM was the largest (0.795), and its cutoff value was 1.415 kg. In the body composition results, the area under the receiver operating characteristic curve of body fat mass for predicting GDM risk was larger (0.663) in all pregnant women.ConclusionsThrough this retrospective study, it was found that the body composition-related indicators were independently associated with the onset of GDM in both the pre-pregnancy BMI <24 kg/m2 and pre-pregnancy BMI ≥24 kg/m2 groups. Body fat mass, the visceral fat level, and the waist-hip ratio had a higher correlation with pre-pregnancy BMI. Total body water, protein levels, mineral levels, bone mineral content, soft lean mass, fat-free mass, skeletal muscle mass, and the basal metabolic rate were protective factors for GDM after adjusting for some confounders. In all pregnant women, the waist-hip ratio was found to be up to 4.562 times the risk of GDM development, and gestational weight gain had the best predictive power for GDM. Gestational weight gain in early pregnancy, body fat mass, and the waist-hip ratio can assess the risk of GDM in pregnant women, which can allow clinicians to predict the occurrence of GDM in pregnant women as early as possible and implement interventions to reduce adverse perinatal outcomes.

BackgroundBeing overweight is an important risk factor for Gestational Diabetes Mellitus (GDM), but the underlying mechanisms are not understood. Weight change between pregnancies has been suggested to be an independent mechanism behind GDM. We assessed the risk for GDM in second pregnancy by change in Body Mass Index (BMI) from first to second pregnancy and whether BMI and gestational weight gain modified the risk.Methods and findingsIn this observational cohort, we included 24,198 mothers and their 2 first pregnancies in data from the Medical Birth Registry of Norway (2006–2014). Weight change, defined as prepregnant BMI in second pregnancy minus prepregnant BMI in first pregnancy, was divided into 6 categories by units BMI (kilo/square meter). Relative risk (RR) estimates were obtained by general linear models for the binary family and adjusted for maternal age at second delivery, country of birth, education, smoking in pregnancy, interpregnancy interval, and year of second birth. Analyses were stratified by BMI (first pregnancy) and gestational weight gain (second pregnancy). Compared to women with stable BMI (−1 to 1), women who gained weight between pregnancies had higher risk of GDM—gaining 1 to 2 units: adjusted RR 2.0 (95% CI 1.5 to 2.7), 2 to 4 units: RR 2.6 (2.0 to 3.5), and ≥4 units: RR 5.4 (4.0 to 7.4). Risk increased significantly both for women with BMI below and above 25 at first pregnancy, although it increased more for the former group. A limitation in our study was the limited data on BMI in 2 pregnancies.ConclusionsThe risk of GDM increased with increasing weight gain from first to second pregnancy, and more strongly among women with BMI < 25 in first pregnancy. Our results suggest weight change as a metabolic mechanism behind the increased risk of GDM, thus weight change should be acknowledged as an independent factor for screening GDM in clinical guidelines. Promoting healthy weight from preconception through the postpartum period should be a target.

Objective To investigate the relationship between maternal body composition in first trimester and gestational diabetes mellitus (GDM). Methods In this nested case-control study based on a prospective cohort study, we enrolled gravidas between 8 and 14 weeks of gestation, who received prenatal care and voluntary nutrition evaluation in Gansu Provincial Maternity and Children Health Care Hospital, from July 2016 to January 2017. Body mass index (BMI) of each gravida was recorded and the maternal body composition including body fat, body fat percentage and fat-free mass was measured by bioelectrical impedance analysis. Pregnancy outcomes were followed up. A total of 70 patients diagnosed with GDM were allocated to the GDM group and 140 healthy gravidas matching for age and pre-pregnancy BMI were selected as the control group. Differences in body composition between two groups and their relationships with GDM were analyzed by Chi-square test and multivariate logistic regression. Results Maternal BMI≥30 kg/m2 (OR=1.973, 95%CI: 1.095-7.664, P=0.024) and body fat percentage≥30%, ≥35% and ≥40% in first trimester (OR=1.261, 95%CI: 1.021-2.982, P=0.010; OR=4.020, 95%CI: 1.341-7.950, P<0.001; OR=8.311, 95%CI: 5.018-42.771, P<0.001) were the risk factors of GDM. Conclusions BMI≥30 kg/m2 and body fat percentage ≥30% in first trimester are risk factors for GDM and excessive adipose tissue may play an important role in the development of GDM. Key words: Pregnancy trimester, first; Body mass index; Diabetes, gestational; Risk factors

Association of serum folic acid levels in response to fasting blood glucose in early pregnancy with the risk of gestational diabetes mellitus: A retrospective cohort study

Introduction Bioelectrical impedance analysis (BIA) is a rapid and noninvasive method of body composition analysis; however, reproducibility between BIA instruments in pregnancy is uncertain. Adverse maternal body composition has been linked to pregnancy complications including gestational diabetes mellitus (GDM). This study aimed to evaluate the reproducibility of three BIA instruments in pregnancy and analyse the relationship between the body composition and the GDM risk. Methods A prospective cohort (n = 117) of women with singleton pregnancies participating in the Microbiome Understanding in Maternity Study (MUMS) at St. George Hospital, Sydney, Australia. Anthropometric measurements and BIA body composition were measured at ≤13 weeks (T1), 20–24 weeks (T2), and 32–36 weeks (T3) of gestation. Body fat percentage (BFP), total body water (TBW), and impedance were estimated by three BIA instruments: Bodystat 1500, RJL Quantum III, and Tanita BC-587. GDM status was recorded after 75 g oral glucose tolerance test was performed at 28 weeks or earlier. Agreement between BIA instruments was assessed using Bland–Altman analysis. Logistic regression modelling explored associations of BFP with GDM. Results Method comparison reproducibility between Bodystat and RJL was stronger than between Bodystat and Tanita for both BFP and TBW% at all three time points. RJL overestimated BFP on average by 3.3% (p < 0.001), with limits of agreement within ±5% for all trimesters. Average BFP was not significantly different between Tanita and Bodystat although limits of agreement exceeded ±5%. GDM diagnosis was independently associated with increased BFP in T1 (adjusted OR 1.117 per 1% increase; 95% CI 1.020–1.224; p=0.017) and in T2 (adjusted OR 1.113 per 1% increase; 95% CI 1.010–1.226; p=0.031) and with Asian ethnicity in all models (OR 7.4–8.1). Conclusion Reproducibility amongst instruments was moderate; therefore, interchangeability between instruments, particularly for research purposes, cannot be assumed. In this cohort, GDM risk was modestly associated with increasing BFP and strongly associated with Asian ethnicity.

Gestational diabetes mellitus (GDM) is a common complication during pregnancy that poses serious health risks to both mothers and their offspring. Risk factors for GDM, such as obesity, have been extensively reported. However, the association between body composition and GDM risk remains unclear. Therefore, we conducted a retrospective cohort study to investigate the relationship between body composition in early pregnancy and the risk of developing GDM. A total of 3,159 pregnant women were enrolled between June 2020 and December 2021, with 280 (10.43%) diagnosed with GDM. Bioelectrical impedance analysis (BIA) was used to measure the percentage of body fat (PBF), fat mass (FM), fat-free mass (FFM), and lean mass (LM). Logistic regression and restricted cubic spline (RCS) analyses were performed to examine the associations between body composition and GDM risk. Compared with the bottom tertile, the top tertile levels of PBF and FM were significantly associated with an increased risk of GDM, with adjusted odds ratios (ORs) and corresponding 95% confidence intervals (95% CI) of 1.77 (1.13, 2.77) and 1.99 (1.23, 3.20), respectively. Each standard deviation (SD) increase in PBF and FM was associated with a 31% (95% CI: 1.07-1.60) and 27% (95% CI: 1.03-1.57) increased risk of GDM, respectively. RCS analysis indicated that the risk of GDM continuously increased with higher levels of PBF and FM, whereas it decreased with FFM and LM (p-overall < 0.001, p-non-linear range: 0.073-0.924). These findings provide important threshold values in predicting GDM risk, specifically 24.74% for PBF, 13.13 kg for FM, 39.81 kg for FFM, and 36.74 kg for LM. The risk of GDM is positively associated with PBF and FM whereas negatively associated with FFM and LM.

Background: Obesity and maternal age are the two most important factors independently affecting the risk of gestational diabetes mellitus (GDM). However, the age differences in the association between obesity and GDM remain unclear. The objectives of this cohort study included: (1) to determine the current incidence of GDM in Qingdao; and (2) to evaluate the risk factors for GDM, such as the interaction between pre-pregnancy body mass index (BMI) and age.Methods: The cohort included 17,145 pregnant women who registered at 15 to 20 gestational weeks from August 1, 2018, to March 1, 2019. A 75-g 2-h oral glucose tolerance test (OGTT) was conducted for each participant at 24–28 gestational weeks. The age-adjusted incidence of GDM was calculated using logistic regression. Multivariate logistic regression analysis was used to identify risk factors. Interaction between age (reference group <30 years) and BMI (reference group <25 kg/m2) was determined using strata-specific analysis.Results: The incidence and age-adjusted incidence of GDM in Qingdao were 17.42 and 17.45%, respectively. The incidence of GDM appeared to increase steadily with age in all pre-pregnancy BMI groups (all P < 0.05). Older age (≥30 years), gestational BMI gain from pre-pregnancy to 15–20 weeks of gestation, history of GDM and thyroid diseases were risk factors for GDM. There were significant interactions between pre-pregnancy BMI and age (P < 0.05) after adjustment for other confounders. The odds ratio (OR) of pre-pregnancy BMI ≥ 30 kg/m2 at the age of <30 years, 30–34 years and ≥35 years was 1.30 (95% CI: 0.74–2.28, P = 0.36), 3.21 (95% CI: 2.28–4.52, P < 0.0001) and 1.55 (95% CI: 1.02–2.36, P = 0.0424), respectively. This indicated that pre-pregnancy BMI ≥ 30 kg/m2 had a stronger effect on GDM in the group aged 30–34 years than those under 30 years old.Conclusions: The incidence of GDM was high in Qingdao. Overweight and obesity prior to pregnancy, gestational BMI gain from conception to 15–20 weeks of gestation and older age were correlated with an increased risk of GDM. Public health measures may be helpful to prevent excessive gestational weight gain.

Gestational diabetes mellitus (GDM) is one of the most common complications of pregnancy and is associated with adverse outcomes for both mother and child as well as long-term maternal risk of type 2 diabetes. This study aimed to identify risk factors for the development of GDM and predictors of postpartum glucose intolerance. We conducted a single-center retrospective study at Sanno Hospital, Tokyo, including 11,694 pregnant women between 2015 and 2024. A total of 3177 women underwent a 75-g oral glucose tolerance test (OGTT) between 24 and 28 gestational weeks, and 1,025 were diagnosed with GDM (32.3%). The median maternal age at GDM diagnosis was 36 years, the mean prepregnancy body mass index (BMI) was 20.2 kg/m2, and the postpartum OGTT was performed at 6–12 weeks after delivery. As a result, women with GDM were more likely to have advanced maternal age, history of GDM, family history of diabetes, higher prepregnancy BMI, elevated hemoglobin A1c levels, higher 50-g glucose challenge test (GCT) results, and higher OGTT values at GDM diagnosis. Infertility treatment itself was not a risk factor, though age and obesity in this population likely contribute. Prepregnancy obesity had a stronger impact on GDM risk than maternal age, and combining both factors markedly increased risk. GDM was associated with a higher rate of large-for-gestational-age infants and neonatal hypoglycemia. Postpartum follow-up showed that 65.6% of women returned to normal glucose tolerance, 31.4% developed impaired glucose tolerance, and 3.0% developed diabetes mellitus. History of GDM, family history of diabetes, multiple positive points on 75-g OGTT, and 2-h 75-g OGTT results at GDM diagnosis were risk factors for postpartum glucose intolerance. The 50-g GCT results could significantly predict the risk of postpartum insulin deficiency. In conclusion, history of infertility treatment was not a risk factor for GDM; however, other factors such as prepregnacy BMI were consistent with previous report findings. These findings highlight the importance of prepregnancy weight management and postpartum monitoring, and emphasize the need for lifelong follow-up in women with GDM. A multidisciplinary approach from preconception through postpartum is recommended.

The relationship between age at menarche (AAM) and gestational diabetes mellitus (GDM) risk is still inconclusive. This Mendelian randomization (MR) analysis was used to assess systematically the causal relationship between AAM and GDM risk in human beings. Single-nucleotide polymorphisms associated with AAM, oestradiol levels, sex hormone-binding globulin (SHBG) levels and bioavailable testosterone (BioT) levels were screened via the genome-wide association study enrolling individuals of European descent. Summary-level data for GDM (123 579 individuals) were extracted from the UK Biobank. An inverse-variance-weighted method was used for the primary MR analysis. Sensitivity analyses were examined via MR-Egger regression, heterogeneity tests, pleiotropy tests and leave-one-out tests. The directionality that exposure causes the outcome was verified using the MR-Steiger test. Genetically predicted early AAM was found to have a causal positive association with a higher risk of GDM (odds ratio=0.798, 95% confidence interval=0.649-0.980, p=.031). In the multivariable MR analysis adjusted for oestradiol, SHBG and BioT levels, the causal association between AAM and GDM risk remained (odds ratio=0.651, 95% confidence interval=0.481-0.881, p=.006). A 1-SD increase in SHBG or BioT levels was significantly associated with a 41.4% decrease or 20.8% increase in the overall GDM risk (p=3.71E-05 and .040), respectively. However, after controlling for AAM, oestradiol levels and BioT levels by multivariable MR analysis, there was no direct causal effect of SHBG levels on GDM risk (p=.084). Similarly, after adjusting for AAM, oestradiol levels and SHBG levels by multivariable MR analysis, there was no direct causal effect of BioT levels on the risk of GDM (p=.533). In addition, no direct causal association was identified between oestradiol levels and GDM risk in univariable MR analysis or multivariable MR analysis. Genetic variants predisposing individuals to early AAM were independently associated with higher GDM risk. Further research is required to understand the mechanisms underlying this putative causative association. In addition, AAM may be helpful in clinical practice to identify women at risk for GDM; pregnant women who are young for menarche may need to take precautions before GDM develops.

Objective: To investigate the risk factors for gestational diabetes mellitus (GDM) in elderly multipara women in the next pregnancy. Methods: A total of 219 elderly multipara women with 2 consecutive delivery records in Tianjin Binhai New Area Tanggu Obstetrics and Gynecology Hospital from January 2018 to May 2019 were included. Among them, 141 had normal glucose tolerance (NGT) and 78 of them had GDM. The clinical data of the previous and current pregnancy were collected to analyze the risk factors of GDM in elderly multipara women. Results: The average ages of 219 elderly women in previous pregnancy and this pregnancy were (31.9±2.2) and (36.7±1.5) years old, and the prevalence of GDM was 35.62% (78 cases). Compared to NGT group, GDM patients had higher fasting blood glucose(previous (5.51±1.43) vs (4.63±0.62) mmol/L; current (5.26±0.63) vs (4.59±0.30) mmol/L, 1 h blood glucose(previous (11.74±2.36) vs (9.50±1.82) mmol/L; current (11.03±2.03) vs (9.51±1.14) mmol/L) in 75 g oral glucose tolerance test (OGTT) in both previous and current pregnancy. The rates of cesarean section, in both previous and current pregnancy were higher in GDM group (previous 34.6% vs 4.3%; current 52.6% vs 22.0%). Furthermore, prenatal weight and body mass index (BMI) of the previous pregnancy, pre-pregnancy weight and BMI, and prenatal BMI of this pregnancy were also higher in GDM group, and the differences were all statistically significant (all P<0.05). Logistic multivariate regression analysis indicated cesarean section history (OR=10.80, 95%CI: (4.09-28.54)), GDM history of previous pregnancy (OR=10.64, 95%CI: (4.02-28.20)), 75 g OGTT fasting blood glucose≥ 4.86 mmol/L (OR=2.70, 95%CI: (1.27-5.70)), 1 h blood glucose after glucose administration ≥ 8.45 mmol/L (OR=1.78, 95%CI: (1.37-2.31)) were risk factors for GDM in elderly multipara women of this pregnancy. Conclusion: The risk of GDM in elderly multipara women with a history of cesarean section and GDM increases significantly. Results of OGTT in previous pregnancy also has predictive value.

Objective In this study, we aimed to evaluate the relationship between body fat percentage (BFP) and the risk of gestational diabetes mellitus (GDM). Methods We conducted a cohort study involving 336 singleton pregnant women attending an antenatal care clinic before 14 weeks of gestation. Body compositionwas measured during their first antenatal visit by using a multi-frequency segmental body composition analyzer. GDM was diagnosed by a 50-g glucose challenge test (GCT) and a 100-g oral glucose tolerance test (OGTT) during thefirst visit and repeated during 24-28 weeks of gestation. Rates of GDM were compared between women with BFP ≥30% and those with BFP <30%. The ability of BFP and body mass index (BMI) to diagnose GDM was assessed, as well as their correlation. Results Of the 296 women included in the analysis, 171 had BFP ≥30%, and 125 had BFP <30%. The prevalence of GDM was 17.9%. BFP correlated well with BMI (correlation coefficient: 0.956, p<0.001). BFP ≥30% and BMI ≥25 kg/m2 significantly increased the risk of GDM (22.2% vs. 12%, p=0.023 and 26.4% vs. 14.4%, p=0.014, respectively). The sensitivity of BFP ≥30% and BMI ≥25 kg/m2 for GDM diagnosis was 71.1% and 43.3%, respectively while the specificity was 45.3% and 73.7%, respectively. Both BFP and BMI had comparableefficacy in diagnosing GDM [areas under the receiver operating characteristic (ROC) curves (AUC) of 0.634 and 0.642, respectively]. Conclusions BFP ≥30% and BMI ≥25 kg/m2 significantly increased the risk of GDM. BFP correlated well with BMI and had similarefficacy in diagnosing GDM.

The aim of the present study was to define cut-off points of body mass index (BMI) and waist circumference (WC) for gestational diabetes mellitus (GDM) and to investigate any interactions between high BMI and high WC on the risk of GDM in pregnant Chinese women. From 2010 to 2012, 17 803 women in Tianjin, China, who were at 4-12 weeks gestation were recruited to the study. Gestational diabetes mellitus was diagnosed according to the criteria of the International Association of Diabetes and Pregnancy Study Group at 24-28 weeks gestation. Binary logistic regression was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs) while controlling for the confounding effects of traditional risk factors. Restricted cubic spline was used to identify cut-off points of WC and BMI, if any, for GDM. Gestational diabetes mellitus developed in 1383 (7.8%) women. The risk of GDM increased steeply with increasing WC from ≥78.5 cm and BMI ≥22.5 kg/m2 . If BMI <22.5 kg/m2 and WC <78.5 cm were used as the reference, BMI between ≥22.5 and <24.0 kg/m2 (multivariable OR 1.76; 95%CI 1.47-2.10) and WC between ≥78.5 and <85.0 cm (multivariable OR 1.53; 95%CI 1.31-1.78) were independently associated with increased risks of GDM. In addition, the presence of both BMI ≥22.5 kg/m2 and WC ≥78.5 cm further increased the OR to 2.83 (95% CI 2.44-3.28), with significant additive interaction. Body mass index ≥22.5 kg/m2 and WC ≥78.5 cm measured up to 12 weeks of gestation were independently and synergistically associated with increased risks of GDM in Chinese pregnant women.

To study the risk factors for gestational diabetes mellitus (GDM). This retrospective case-control study was conducted among women registered at the Department of Obstetrics of West China Second University Hospital between March, 2016 and May, 2018. The women were divided into case group (GDM) and control group (Non- GDM) according to the diagnosis of GDM based on the International Association of Diabetes Pregnancy Study Groups (IADPSG) criteria. The data including age, education level, ethnicity and other socio-demographic data, as well as the gestational week, parity, polycystic ovary syndrome, family history of diabetes, fat mass, total body water, minerals and other clinical characteristics were collected. Univariate Logistic regression analysis was performed and the variables with statistical difference and clinical significance were included in multivariate Logistic regression analysis to identify the risk factors of GDM. A total of 3608 pregnant women were included in the study. Univariate logistic analysis revealed that age, previous GDM, intracellular/extracellular water, fat mass, arm circumference, skeletal muscle mass were risk factors for GDM. Multivariate logistic analysis showed that age, previous GDM, family history of DM, and an arm circumference ≥28.5 cm were independent risk factors for GDM after controlling pre-pregnancy BMI. The risk of GDM in pregnant women aged 30-35 years and 36 years or older was 1.883 (P &lt; 0.001) and 2.883 (P &lt; 0.001) times of that in women aged 20-29 years, respectively. Women with a history of GDM had a 6.604 (P &lt; 0.001) greater risk of developing GDM than women without a history of GDM. Compared with those without a family history of diabetes, those with a family history of diabetes were 2.518 times more likely to develop GDM (P &lt; 0.001). Compared with those with an arm circumference no greater than 25.5 cm, pregnant women with an arm circumference over 28.5 cm had an increased risk of GDM by 2.815 times (P &lt; 0.001). High fat free mass was a protective factor for GDM, and compared with a fat free mass below 35.1 kg, a fat free mass over 40.1 kg was associated with a lowered risk of GDM by 0.515 times (P &lt; 0.001). The onset of GDM was affected by multiple factors. Age, history of GDM, family history of diabetes, and a large arm circumference are all independent risk factors of GDM and should be controlled to reduce the incidence of GDM.

The ABO blood types are associated with cancers, cardiovascular diseases and type 2 diabetes mellitus but whether they are also associated with gestational diabetes mellitus (GDM) is unknown. We examined the relationship between the ABO blood types and the risk of GDM in a prospective population-based Chinese cohort. From 2010 to 2012, we recruited 14,198 pregnant women within the first 12 weeks of gestation in Tianjin, China. All women had a glucose challenge test (GCT) at 24-28 gestational weeks, followed by a 75-g 2-h oral glucose tolerance test if the results from GCT were ≥7.8 mmol/L. GDM was diagnosed based on the glucose cut-points of the International Association of Diabetes and Pregnancy Study Group criteria. Logistic regression was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs) adjusted for traditional risk factors. Stratified analysis was performed by family history of diabetes (yes versus no). Sensitivity analyses were also performed by using the World Health Organization (WHO) criteria for GDM. Women with blood groups A, B or O (i.e. non-AB) were associated with increased risk of GDM as compared with those with blood group AB (adjusted OR: 1.44, 95% CI: 1.13-1.83). Sensitivity analyses showed that the result was consistent using WHO criteria. The adjusted OR of blood group non-AB versus AB for GDM was enhanced among women with a family history of diabetes (2.69, 1.21-5.96) and attenuated among those without (1.33, 1.03-1.71). Blood group AB was a protective factor against GDM in pregnant Chinese women.

Objectives To investigate whether the prothrombotic state (PTS), calcium deficiency and iron deficiency anemia (IDA) in early pregnancy is associated with the risk of gestational diabetes mellitus (GDM). Methods We conducted a retrospective cohort study, including consecutive pregnant women tested for PTS, calcium deficiency and IDA before 20 weeks' gestation between September 1, 2017 and March 21, 2021. For routine prenatal care, pregnant women underwent a 75-g oral glucose tolerance test (OGTT) to make a GDM diagnosis during 24–28 weeks of gestation. Testing data and relevant clinical information were obtained from Shenzhen Baoan Women's and Children's Hospital. To estimate GDM risk of exposures (PTS, calcium deficiency and IDA) in early pregnancy, we used logistic regression to obtain odds ratio (OR) adjusted for maternal age, parity, family history of diabetes and pre-pregnancy body mass index. Results The cohort included 8396 pregnant women with complete data of exposures and GDM outcomes. Baseline characteristics were not comparable between exposure and control groups. PTS (adjusted OR 2.38, 95% CI 1.61–3.52) or calcium deficiency (adjusted OR 1.23, 95% CI 1.02–1.49) in early pregnancy was independently associated with increased GDM risk after adjusting covariates. There was no significant association between IDA status and GDM risk (adjusted OR 0.86, 95% CI 0.63–1.18). Conclusions PTS and calcium deficiency in early pregnancy may be independent risk factors of GDM. These findings need further validation in well-designed prospective cohorts.