Association of MTNR1B rs10830963 C>G Polymorphism with the risk of Gestational Diabetes Mellitus: An Updated Meta-analysis

Association of Thyroid Function During Pregnancy With the Risk of Pre-eclampsia and Gestational Diabetes Mellitus

Introduction and Objective: Gestational diabetes mellitus (GDM) risk varies by area and is potentially associated with social disparity and variation in the built environment. There remains limited evidence examining the association between socio-ecological factors and GDM risk. This study examined the association between socio-ecological factors and GDM risk at local area level over time in Australia. Methods: An ecological study was undertaken using multisource national data at Statistical Area Level 2 (SA2: medium-sized geographical unit) in Australia from 2016-22. SA2-level GDM cases and births were obtained from national registries. Social and built environment covariates were aggregated to the SA2 level. Spatiotemporal ecological regression was undertaken using a Bayesian approach, and an adjusted risk ratio with 95% credible intervals (CrIs) was estimated. Results: Across 1,486 SA2s, 207,163 GDM cases occurred from 1,719,396 births. In areas with a high concentration of at-risk migrant women (location quotient ≥ 1), GDM was 1.10 (95% CrI; 1.07, 1.13) compared to low concentration. GDM risk was associated with a lower level of socioeconomic position, with least (vs most) advantaged areas having an 18% greater risk of GDM (1.18[95% CrI; 1.10, 1.26]). Compared to areas with the least access to fast food outlets (4th quartile), other quartiles were associated with increased GDM risk, with the greatest in the 1st (highest access) (1.12 [95% CrI; 1.04,1.20]). Residing in the least-moderate walkable areas (2nd quartile) was associated with higher GDM risk (1.08[95% CrI; 1.02, 1.14]) than most walkable areas. Conclusion: Area-level GDM risk was associated with socioeconomic disadvantage, high concentrations of at-risk migrant women, least-moderate walkability, and highest fast-food access. Tailored population-level interventions targeting socioeconomic, ethnic, and built environment attributes may improve preventive health efforts. Disclosure W.W. Takele: None. R. Beare: None. L.L. Dalli: None. S. Lim: None. J. Boyle: Other Relationship; Elsevier.

We aimed to examine the association between the quantity and quality of dietary fat in early pregnancy and gestational diabetes mellitus (GDM) risk. In total, 1477 singleton pregnant women were included from Sichuan Provincial Hospital for Women and Children, Southwest China. Dietary information was collected by a 3-d 24-h dietary recall. GDM was diagnosed based on the results of a 75-g, 2-h oral glucose tolerance test at 24-28 gestational weeks. Log-binomial models were used to estimate relative risks (RR) and 95% CI. The results showed that total fat intake was positively associated with GDM risk (Q4 v. Q1: RR = 1·40; 95 % CI 1·11, 1·76; Ptrend = 0·001). This association was also observed for the intakes of animal fat and vegetable fat. After stratified by total fat intake (< 30 %E v. ≥ 30 %E), the higher animal fat intake was associated with higher GDM risk in the high-fat group, but the moderate animal fat intake was associated with reduced risk of GDM (T2 v. T1: RR = 0·65; 95 % CI 0·45, 0·96) in the normal-fat group. Vegetable fat intake was positively associated with GDM risk in the high-fat group but not in the normal-fat group. No association between fatty acids intakes and GDM risk was found. In conclusion, total fat, animal and vegetable fat intakes were positively associated with GDM risk, respectively. Whereas when total fat intake was not excessive, higher intakes of animal and vegetable fat were likely irrelevant with increased GDM risk, even the moderate animal fat intake could be linked to lower GDM risk.

Maternal sleep is closely related to subsequent gestational diabetes mellitus (GDM) in natural pregnancies. However, whether this connection exists in pregnant women conceiving with the help of assisted reproductive technology (ART) has not been confirmed. Hence, in this study, we evaluated whether early pregnancy sleep duration or sleep quality is associated with gestational diabetes mellitus in ART-pregnant women, as well as the influence of maternal age on this association. This prospective birth cohort study included 856 pregnant women who successfully conceived with the help of ART treatment. The sleep parameters of ART-pregnant women were assessed using the Pittsburgh Sleep Quality Index (PSQI) in early pregnancy. We explored the association between sleep and the risk of gestational diabetes mellitus using an unconditional binary logistic regression model. Different models were constructed to examine the robustness of the estimation by incorporating different confounding factors. Multivariable logistic regression revealed that sleep duration of more than 10 h among ART-pregnant women was significantly associated with the risk of GDM, and the association between sleep duration and gestational diabetes mellitus varied by maternal age. We found an increased risk of subsequent gestational diabetes mellitus with increasing sleep duration only in pregnant women aged <35 years. Additionally, no statistically significant association between sleep quality and gestational diabetes mellitus was found in this study. In conclusion, excessive sleep duration (≥10 h) is associated with a high risk of gestational diabetes mellitus in pregnant women who conceived with the help of assisted reproductive technology, and maternal age may modify this effect.

Environmental phenols are ubiquitous endocrine disruptors and putatively diabetogenic. However, data during pregnancy are scant. We investigated the prospective associations between pregnancy phenol concentrations and gestational diabetes mellitus (GDM) risk. In a nested matched case-control study of 111 individuals with GDM and 222 individuals without GDM within the prospective PETALS cohort, urinary bisphenol A (BPA), BPA substitutes (bisphenol F and bisphenol S [BPS]), benzophenone-3, and triclosan were quantified during the first and second trimesters. Cumulative concentrations across the two times were calculated using the area under the curve (AUC). Multivariable conditional logistic regression examined the association of individual phenols with GDM risk. We conducted mixture analysis using Bayesian kernel machine regression. We a priori examined effect modification by Asian/Pacific Islander (A/PI) race/ethnicity resulting from the case-control matching and highest GDM prevalence among A/PIs. Overall, first-trimester urinary BPS was positively associated with increased risk of GDM (adjusted odds ratio comparing highest vs. lowest tertile [aORT3 vs. T1] 2.12 [95% CI 1.00-4.50]). We identified associations among non-A/Ps, who had higher phenol concentrations than A/PIs. Among non-A/PIs, first-trimester BPA, BPS, and triclosan were positively associated with GDM risk (aORT3 vs. T1 2.91 [95% CI 1.05-8.02], 4.60 [1.55-13.70], and 2.88 [1.11-7.45], respectively). Triclosan in the second trimester and AUC were positively associated with GDM risk among non-A/PIs (P < 0.05). In mixture analysis, triclosan was significantly associated with GDM risk. Urinary BPS among all and BPA, BPS, and triclosan among non-A/PIs were associated with GDM risk. Pregnant individuals should be aware of these phenols' potential adverse health effects.

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.

Based on their higher risk of type 2 diabetes, non-Hispanic blacks (NHBs) would be expected to have higher gestational diabetes mellitus (GDM) risk compared to non-Hispanic whites (NHWs). However, previous studies have reported lower GDM risk in NHBs versus NHWs. We examined whether GDM risk was lower in NHBs and NHWs, and whether this disparity differed by age group. The cohort consisted of 462,296 live singleton births linked by birth certificate and hospital discharge data from 2004 to 2007 in Florida. Using multivariable regression models, we examined GDM risk stratified by age and adjusted for body mass index (BMI) and other covariates. Overall, NHBs had a lower prevalence of GDM (2.5 vs. 3.1%, p < 0.01) and a higher proportion of preconception DM births (0.5 vs. 0.3%, p ≤ 0.01) than NHWs. Among women in their teens (risk ratio 0.56, p < 0.01) and 20-29 years of age (risk ratio 0.85, p < 0.01), GDM risk was lower in NHBs than NHWs. These patterns did not change with adjustment for BMI and other covariates. Among women 30-39 years (risk ratio 1.18, p < 0.01) and ≥40 years (risk ratio 1.22, p < 0.01), GDM risk was higher in NHBs than NHWs, but risk was higher in NHWs after adjustment for BMI. Associations between BMI and GDM risk did not vary by race/ethnicity or age group. NHBs have lower risk of GDM than NHWs at younger ages, regardless of BMI. NHBs had higher risk than NHWs at older ages, largely due to racial/ethnic disparities in overweight/obesity at older ages.

Background: Pregnant women have a risk of exposure to gestational diabetes mellitus. The first step that can be done is to detect the risk of gestational diabetes mellitus. The aim study to access the description of the prevalence of gestational diabetes mellitus risk. Method: The study design was descriptive with a cross sectional approach. This involved 70 pregnant women who were selected by purposive sampling. Data collection using the D3MG application. Results: The prevalence of gestational diabetes mellitus risk were BMI ≥ 30 kg/m2 as 2.7% (OR = 5.600; 95% CI = 1.729 – 18.141), family history 8.6% (OR = 7.308; 95% CI = 0.806 – 66.231), history giving birth to dead babies and abortion 20%(OR = 0.304; 95% CI = 0.204 – 0.451), low physical activity before pregnancy 54.3%(OR = 2.718; 95% CI = 1.016 – 7.268), low physical activity during pregnancy 95.7% (OR = 4.148; 95% CI = 1.053 – 16.343), eating habits – sugary foods 4.3% (OR = 2.621; 95% CI = 0.226 – 30.328), eating habits and foods containing high cholesterol 2.9% (OR = 0.426; 95% CI = 0.324 – 0.562), and the duration of poor sleep 24.3% (OR = 6.319; 95% CI = 1.799 – 22.203). Pregnant women who are at low risk of exposure gestational diabetes mellitus 55.7% and high risk 44.3%. Conclusion: There are pregnant women who have a low risk of exposure gestational diabetes mellitus detected by the application D3MG, however preventive efforts must continue to be done to prevent the occurrence of gestational diabetes mellitus and improve fetal well-being.

Fruit intake may influence gestational diabetes mellitus (GDM) risk. However, prospective evidence remains controversial and limited. The current study aimed to investigate whether total fruit and specific fruit intake influence GDM risk. A prospective cohort study was conducted. Dietary information was collected by a 3-d 24-h dietary recall. All participants underwent a standard 75-g oral glucose tolerance test at 24-28 gestational weeks. Log-binomial models were used to estimate the association between fruit intake and GDM risk, and the results are presented as relative risks (RR) and 95 % CI. Southwest China. Totally, 1453 healthy pregnant women in 2017. Total fruit intake was not associated with lower GDM risk (RR of 1·03 (95 % CI 0·83, 1·27) (Ptrend = 0·789)). The RR of GDM risk was 0·73 for the highest anthocyanin-rich fruit intake quartile compared with the lowest quartile (95 % CI 0·56, 0·93; Ptrend = 0·015). A higher grape intake had a linear inverse association with GDM risk (Q4 v. Q1: RR = 0·65; 95 % CI 0·43, 0·98; Ptrend = 0·044), and after further adjustment for anthocyanin intake, the inverse association tended to be non-linear (Q4 v. Q1: RR = 0·65; 95 % CI 0·44, 0·98; Ptrend = 0·079). However, we did not find an association between glycaemic index-grouped fruit, glycaemic load-grouped fruit or other fruit subtype intake and GDM risk. In conclusion, specific fruit intake (particularly anthocyanin-rich fruit and grapes) but not total fruit intake was inversely associated with GDM risk.

Associations of liver function with the risk of gestational diabetes mellitus (GDM) remain unclear. This study aimed to examine the relationship and the potential causality between maternal liver biomarkers and the risk of subsequent GDM, as well as to evaluate the interaction between liver biomarkers and lipids on GDM risk. In an ongoing Zhoushan Pregnant Women Cohort, pregnant women who finished the first prenatal follow-up record, underwent liver function tests in early pregnancy, and completed the GDM screening were included in this study. Logistic regression models were used to investigate the association, and the inverse-variance weighted method supplemented with other methods of two-sample Mendelian randomization (MR) analysis was applied to deduce the causality. Among 9,148 pregnant women, 1,668 (18.2%) developed GDM. In general, the highest quartile of liver function index (LFI), including ALT, AST, GGT, ALP, and hepatic steatosis index, was significantly associated with an increased risk of GDM (OR ranging from 1.29 to 3.15), especially an elevated risk of abnormal postprandial blood glucose level. Moreover, the causal link between ALT and GDM was confirmed by the MR analysis (OR=1.28, 95%CI:1.05-1.54). A significant interaction between AST/ALT and TG on GDM risk was observed (P interaction = 0.026). Elevated levels of LFI in early pregnancy were remarkably associated with an increased risk of GDM in our prospective cohort. Besides, a positive causal link between ALT and GDM was suggested.

Overweight and obesity rates are consistently increasing worldwide. Many countries, including Australia report higher increases in obesity rates in women compared to men. In particular, weight gain in younger, reproductive aged women is escalating. Obesity, being an insulin resistant state, has serious health consequences. Traditionally, the focus has been on type II diabetes and cardiovascular disease in older individuals. However, in women of reproductive age, adverse lifestyle, obesity and insulin resistance has significant reproductive health implications that often occur well before type II diabetes. These include polycystic ovary syndrome and gestational diabetes mellitus in pregnancy. With high rates of weight gain and clear complications, young women present an important target group for intervention strategies. Insulin resistance is challenging to assess and relevant literature and novel new methods are explored early in the thesis. I then aimed to explore the role of lifestyle change and increased physical activity in two groups of overweight reproductive aged women with insulin resistance; women with polycystic ovary syndrome (PCOS) and pregnant women at high risk for developing gestational diabetes mellitus (GDM). As lifestyle improvement including exercise is highly effective in alleviating insulin resistance in other high risk groups, the studies presented in this thesis have a focus on promoting and evaluating healthy lifestyle and physical activity as a primary theme. I performed an extensive systematic literature review which highlighted research gaps and set the context for our intervention study in PCOS. In a comprehensive mechanistic study in overweight women with and without PCOS, intensified exercise training was evaluated without specified dietary prescription over 12 weeks. I assessed the effects on the key outcome measures; insulin resistance and body composition. This comprehensive study demonstrated worsened insulin resistance in PCOS women compared to non-PCOS control women. Following exercise, insulin resistance improved in both groups without change in weight suggesting the value of exercise in PCOS exceeds its impact on weight alone. Reproductive function also improved with exercise in PCOS women. Women with PCOS showed reduced visceral fat following exercise which is linked to insulin resistance; with no change in the control group. Despite reduced levels of visceral fat and improved insulin resistance, women with PCOS still had greater insulin resistance following exercise in comparison to controls. This study advanced the understanding of insulin resistance in PCOS but also highlighted the need to further mechanistically explore intrinsic insulin signalling defects in PCOS and evaluate the role of exercise in PCOS. In a large randomised controlled public health trial with overweight and obese pregnant women at risk for GDM, a healthy lifestyle program promoting increased physical activity, behaviour change and simple key messages related to improving diet was applied from early pregnancy to six weeks postpartum to assess key outcome measures including gestational weight gain, GDM incidence and physical activity levels. Pregnant women at increased risk for GDM were identified by the development and implementation of a risk screening tool. This Healthy Lifestyle Program (HeLP-her) in pregnancy study is modified from a previously successful intervention in mothers of school children developed by my supervisors and is set in a hospital setting. We have successfully recruited over 200 women (May 2008 – Oct 2010), with 166 of these having completed final data collection. The study is currently ongoing however interim results are presented in this thesis. I have investigated optimal measurement of physical activity in pregnancy, confirming the accuracy of pedometers in this setting. In the setting of a randomised controlled trial with the results of intervention still to be revealed, I have evaluated key lifestyle behaviours in women during pregnancy in the control group not receiving the intervention; drawing on key characteristics of women recruited for this study, describing early pregnancy weight gain, early pregnancy health behaviours and GDM incidence. Results to date demonstrate excess weight gain, a high GDM prevalence and sedentarism in early- to mid- pregnancy, highlighting the urgent need for lifestyle intervention in this high-risk group. The studies presented in this thesis add significantly to the literature, in young, insulin resistant women. The findings provide further evidence that lifestyle change incorporating increased physical activity is important for targeting insulin resistance, particularly in overweight women with PCOS. Final results are pending for lifestyle intervention in women at risk for GDM; however results to date demonstrate increased weight gain in early pregnancy and development of adverse health as evident by a high GDM incidence, mandating increased public health action towards improving lifestyle in this high-risk group. I have successfully finalised recruitment and await the results from the GDM intervention trial which will allow future clarification of the role of lifestyle change in overweight and obese insulin resistant pregnancies. Our group is building on the work presented in this thesis and has successfully obtained NHMRC funding to extend the intensified exercise training program in PCOS women to explore the effects in lean PCOS women. Additionally, we have also adapted the healthy lifestyles program to other populations at-risk, including women with PCOS, those with diabetes and high-risk ethnic subgroups. The findings presented in this thesis have made a significant contribution to women’s health, in settings where insulin resistance is present, creating an evidence base for the importance of lifestyle change in insulin resistant, reproductive aged women.

To examine whether or notfolic acid (FA) supplementation may modify the relationships between duration or quality of sleep and gestational diabetes mellitus (GDM) risk. In a case-control study of patients with GDM and controls, mothers were interviewed face-to-face at enrollment. The Pittsburgh Sleep Quality Scale was used to assess duration and quality of sleep during early pregnancy, and information on FA supplementation and covariates was obtained using a semiquantitative questionnaire. Among 396 patients with GDM and 904 controls, GDM risk increased by 328% and 148% among women with short (< 7h) and long (≥ 9h) sleep durations, respectively, compared to those averaging 7-8.9h sleep.Mothers with poor sleep quality increased their GDM risk by an average of 75% (all p < 0.05). The effect of short sleep duration on GDM risk was much weaker among women with adequate FA supplementation (taking supplements containing ≥ 0.4mg FA daily for each day of the first three months of pregnancy) than that among women with inadequate FA supplementation, with a p-value for interaction = 0.003. There wereno significant effects of FA on links among long duration and poor quality of sleep with GDM risk. Sleep duration and quality in early gestation were related to increased GDM risks. FA supplementation may reduce GDM risk associated with short sleep duration.

We aimed to assess the association between gut bacterial biomarkers during early pregnancy and subsequent risk of gestational diabetes mellitus (GDM) in Chinese pregnant women. Within the Tongji-Shuangliu Birth Cohort study, we conducted a nested case-control study among 201 incident GDM cases and 201 matched controls. Fecal samples were collected during early pregnancy (at 6-15 weeks), and GDM was diagnosed at 24 to 28 weeks of pregnancy. Community DNA isolated from fecal samples and V3-V4 region of 16S rRNA gene amplicon libraries were sequenced. In GDM cases versus controls, Rothia, Actinomyces, Bifidobacterium, Adlercreutzia, and Coriobacteriaceae and Lachnospiraceae spp. were significantly reduced, while Enterobacteriaceae, Ruminococcaceae spp., and Veillonellaceae were overrepresented. In addition, the abundance of Staphylococcus relative to Clostridium, Roseburia, and Coriobacteriaceae as reference microorganisms were positively correlated with fasting blood glucose, 1-hour and 2-hour postprandial glucose levels. Adding microbial taxa to the base GDM prediction model with conventional risk factors increased the C-statistic significantly (P < 0.001) from 0.69 to 0.75. Gut microbiota during early pregnancy was associated with subsequent risk of GDM. Several beneficial and commensal gut microorganisms showed inverse relations with incident GDM, while opportunistic pathogenic members were related to higher risk of incident GDM and positively correlated with glucose levels on OGTT.

BackgroundPer- and polyfluoroalkyl substances (PFAS) are persistent synthetic chemicals and are commonly found in everyday items. PFAS have been linked to disrupting glucose homeostasis, however, whether they are associated with gestational diabetes mellitus (GDM) risk remains inconclusive. We examined prospective associations of PFAS concentrations measured twice in pregnancy with GDM risk.MethodsIn the PETALS pregnancy cohort, a nested case–control study which included 41 GDM cases and 87 controls was conducted. PFAS analytes were measured in blood serum collected in both early and mid-pregnancy (mean [SD]: 13.9 [2.2] and 20.2 [2.2] gestational weeks, respectively), with cumulative exposure calculated by the area-under-the-curve (AUC) to integrate both the PFAS concentration and the timing of the exposure. Individual adjusted weighted unconditional logistic regression models examined seven PFAS in association with GDM risk. P-values were corrected using the false-discovery-rate (FDR). Mixture models were analyzed with Bayesian kernel machine regression (BKMR).ResultsPFDA, PFNA and PFOA were individually associated with higher GDM risk per interquartile range (IQR) in early pregnancy (OR [95% CI]: 1.23 [1.09, 1.38]), 1.40 [1.24, 1.58]), and 1.15 [1.04, 1.27], respectively), mid-pregnancy (1.28 [1.15, 1.43], 1.16 [1.05, 1.28], and 1.20 [1.09, 1.33], respectively), and with cumulative exposure (1.23 [1.09, 1.38], 1.21 [1.07, 1.37], and 1.19 [1.09, 1.31], respectively). PFOS in mid-pregnancy and with cumulative exposure was associated with increased GDM risk (1.41 [1.17, 1.71] and 1.33 [1.06, 1.58], respectively). PFUnDA in early pregnancy was associated with lower GDM risk (0.79 [0.64, 0.98]), whereas mid-pregnancy levels were associated with higher risk (1.49 [1.18, 1.89]). PFHxS was associated with decreased GDM risk in early and mid-pregnancy (0.48 [0.38, 0.60] and 0.48 [0.37, 0.63], respectively) and with cumulative exposure (0.49 [0.38,0.63]). PFPeA was not associated with GDM. Similar conclusions were observed in BKMR models; however, overall associations in these models were not statistically significant.ConclusionsHigher risk of GDM was consistently observed in association with PFDA, PFNA, and PFOA exposure in both early and mid-pregnancy. Results should be corroborated in larger population-based cohorts and individuals of reproductive age should potentially avoid known sources of PFAS.

To examine the influence of maternal sleep quality and nocturnal sleep duration on risk of gestational diabetes mellitus (GDM) in a multiethnic Asian population. A cohort of 686 women (376 Chinese, 186 Malay, and 124 Indian) with a singleton pregnancy attended a clinic visit at 26-28 weeks of gestation as part of the Growing Up in Singapore Towards healthy Outcomes mother-offspring cohort study. Self-reported sleep quality and sleep duration were assessed using the Pittsburgh Sleep Quality Index (PSQI). GDM was diagnosed based on a 75-g oral glucose tolerance test administered after an overnight fast (1999 WHO criteria). Multiple logistic regression was used to model separately the associations of poor sleep quality (PSQI score > 5) and short nocturnal sleep duration (<6 h) with GDM, adjusting for age, ethnicity, maternal education, body mass index, previous history of GDM, and anxiety (State-Trait Anxiety Inventory score). In the cohort 296 women (43.1%) had poor sleep quality and 77 women (11.2%) were categorized as short sleepers; 131 women (19.1%) were diagnosed with GDM. Poor sleep quality and short nocturnal sleep duration were independently associated with increased risk of GDM (poor sleep, adjusted odds ratio [OR] = 1.75, 95% confidence interval [CI] 1.11 to 2.76; short sleep, adjusted OR = 1.96, 95% CI 1.05 to 3.66). During pregnancy, Asian women with poor sleep quality or short nocturnal sleep duration exhibited abnormal glucose regulation. Treating sleep problems and improving sleep behavior in pregnancy could potentially reduce the risk and burden of GDM.