Effect of levothyroxine treatment on fetal growth among women with mild subclinical hypothyroidism and thyroid peroxidase antibody negative: a cohort study.

BACKGROUND: Some clinicians used levothyroxine (LT4) treatment for mild subclinical hypothyroidism (SCH) pregnant women (2.5 < thyroid-stimulating hormone (TSH) ≤ the pregnancy-specific reference range with normal free thyroxine (FT4) level) with thyroid peroxidase antibody negative (TPOAb-), although the recent clinical guideline did not recommend it. It is unknown whether LT4 treatment for pregnant women with mild SCH and TPOAb- have impact on fetal growth. Therefore, the aim of the study was to investigate the effect of LT4 treatment on fetal growth and birth weight among mild SCH pregnant women with TPOAb-. METHODS: This was a birth cohort study including 14,609 pregnant women between 2016 and 2019 in Tongzhou Maternal and Child Health Hospital of Beijing, China. Pregnant women were divided into 3 groups as follows: Euthyroid (n = 14,285, 0.03 ≤ TSH ≤ 2.5mIU/L, normal FT4), TPOAb-; Untreated mild SCH with TPOAb- (n = 248, 2.5 < TSH ≤ 2.9mIU/L, normal FT4, without LT4 treatment); Treated mild SCH with TPOAb- (n = 76, 2.5 < TSH ≤ 2.9mIU/L, normal FT4, with LT4 treatment). The main outcome measures were Z-scores of fetal growth indicators (abdominal circumference (AC), biparietal diameter (BPD), femur length (FL), head circumference (HC), estimated fetal weight (EFW)), fetal growth restriction (FGR) and birth weight. RESULTS: There was no difference in fetal growth indicators and birth weight between the untreated mild SCH women with TPOAb- and the euthyroid pregnant women. But the HC Z-score was lower in the LT4 treated mild SCH women with TPOAb-, compared with the euthyroid pregnant women (ß = -0.223, 95%CI: -0.422, -0.023). The LT4 treated mild SCH women with TPOAb- had lower fetal HC Z-score (ß = -0.236, 95%CI: -0.457, -0.015), compared with the untreated mild SCH women with TPOAb-. CONCLUSIONS: We observed that LT4 treatment for mild SCH with TPOAb- was associated with decreased fetal HC, which was not observed for untreated mild SCH women with TPOAb-. The adverse effect of LT4 treatment for mild SCH with TPOAb- provided new evidence for the recent clinical guideline.

Individual and joint effect of indoor air pollution index and ambient particulate matter on fetal growth: a prospective cohort study.

BACKGROUND: Limited studies have examined the effect of prenatal exposure to particulate matter with diameter of <2.5 µm (PM2.5) and <1 µm (PM1) on fetal growth using ultrasound measurements with inconsistent results. No study has evaluated the joint effect of the indoor air pollution index and ambient particulate matter on fetal growth. METHODS: We conducted a prospective birth cohort study in Beijing, China in 2018, including 4319 pregnant women. We estimated prenatal PM2.5 and PM1 exposure using a machine-learning method and calculated the indoor air pollution index based on individual interviews. Gender- and gestational age-adjusted Z-score of the abdominal circumference (AC), head circumference (HC), femur length (FL) and estimated fetal weight (EFW) was calculated and then undergrowth was defined. A generalized estimating equation was used to evaluate the individual and joint effect of indoor air pollution index, PM2.5 and PM1 on fetal Z-score and undergrowth parameters. RESULTS: One unit increase in the indoor air pollution index was associated with -0.044 (95% CI: -0.087, -0.001) and -0.050 (95% CI: -0.094, -0.006) decrease in the AC and HC Z-scores, respectively. PM1 and PM2.5 were associated with decreased AC, HC, FL and EFW Z-scores, and higher risk of undergrowth. Compared with exposure to lower PM1 (≤ median) and no indoor air pollution, those exposed to higher PM1 (> median) and indoor air pollution had decreased EFW Z-scores (ß = -0.152, 95% CI: -0.230, -0.073) and higher risk of EFW undergrowth (RR = 1.651, 95% CI: 1.106, 2.464). Indoor air pollution and ambient PM2.5 exposure had a similar joint effect on the Z-scores and undergrowth parameters of fetal growth. CONCLUSIONS: This study suggested that indoor air pollution and ambient PM exposure had individual and joint negative effects on fetal growth.

Perfluorononanoic Acid Induces Neurotoxicity via Synaptogenesis Signaling in Zebrafish.

Perfluorononanoic acid (PFNA), commonly used as an alternative polyfluorinated compound (PFC) of perfluorooctanoic acid (PFOA), has been widely detected in the aquatic environment. Previous ecotoxicological and epidemiological results suggested that some neurobehavioral effects were associated with PFC exposure; however, the ecological impacts and underlying neurotoxicity mechanisms remain unclear, particularly in aquatic organisms during sensitive, early developmental stages. In this study, zebrafish embryos were exposed to environmentally relevant concentrations of PFNA for 120 h, and the neurological effects of PFNA were comprehensively assessed using transcriptional, biochemical, morphological, and behavioral assays. RNA sequencing and advanced bioinformatics analyses predicted and characterized the key biological processes and pathways affected by PFNA exposure, which included the synaptogenesis signaling pathway, neurotransmitter synapse, and CREB signaling in neurons. Neurotransmitter levels (acetylcholine, glutamate, 5-hydroxytryptamine, γ-aminobutyric acid, dopamine, and noradrenaline) were significantly decreased in zebrafish larvae, and the Tg(gad67:GFP) transgenic line revealed a decreased number of GABAergic neurons in PFNA-treated larvae. Moreover, the swimming distance, rotation frequency, and activity degree were also significantly affected by PFNA, linking molecular-level changes to behavioral consequences.

Risk of De Novo Hypertensive Disorders of Pregnancy After Exposure to PM1 and PM2.5 During the Period From Preconception to Delivery: Birth Cohort Study.

BACKGROUND: Particulate matter (PM) is detrimental to the respiratory and circulatory systems. However, no study has evaluated the lag effects of weekly exposure to fine PM during the period from preconception to delivery on the risk of hypertensive disorders of pregnancy (HDPs). OBJECTIVE: We set out to investigate the lag effect windows of PM on the risk of HDPs on a weekly scale. METHODS: Data from women with de novo HDPs and normotensive pregnant women who were part of the Peking University Retrospective Birth Cohort, based on the hospital information system of Tongzhou district, were obtained for this study. Meteorological data and data on exposure to fine PM were predicted by satellite remote sensing data based on maternal residential address. The de novo HDP group consisted of pregnant women who were diagnosed with gestational hypertension or preeclampsia. Fine PM was defined as PM2.5 and PM1. The gestational stage of participants was from preconception (starting 12 weeks before gestation) to delivery (before the 42nd gestational week). A distributed-lag nonlinear model (DLNM) was nested in a Cox regression model to evaluate the lag effects of weekly PM exposure on de novo HDP hazard by controlling the nonlinear relationship of exposure-reaction. Stratified analyses by employment status (employed or unemployed), education level (higher or lower), and parity (primiparity or multiparity) were performed. RESULTS: A total of 22,570 pregnant women (mean age 29.1 years) for whom data were available between 2013 and 2017 were included in this study. The prevalence of de novo HDPs was 6.7% (1520/22,570). Our findings showed that PM1 and PM2.5 were significantly associated with an elevated hazard of HDPs. Exposure to PM1 during the 5th week before gestation to the 6th gestational week increased the hazard of HDPs. A significant lag effect of PM2.5 was observed from the 1st week before gestation to the 6th gestational week. The strongest lag effects of PM1 and PM2.5 on de novo HDPs were observed at week 2 and week 6 (hazard ratio [HR] 1.024, 95% CI 1.007-1.042; HR 1.007, 95% CI 1.000-1.015, respectively, per 10 µg/m3 increase). The stratified analyses indicated that pregnant women who were employed, had low education, and were primiparous were more vulnerable to PM exposure for de novo HDPs. CONCLUSIONS: Exposure to PM1 and PM2.5 was associated with the risk of de novo HDPs. There were significant lag windows between the preconception period and the first trimester. Women who were employed, had low education, and were primiparous were more vulnerable to the effects of PM exposure; more attention should be paid to these groups for early prevention of de novo HDPs.

Effects of fine ambient particulate matters on de novo hypertensive disorders of pregnancy and blood pressure before 20 weeks.

The effects of fine particulate matter (PM) on de novo hypertensive disorders of pregnancy (HDP) were inconsistent during the first and second trimesters. This study aimed to assess the trimester-specific effects of PM2.5 and PM1 prior to diagnosis of de novo HDP. The exposure of fine PM was predicted by satellite remote sensing data according to maternal residential addresses. De novo HDP was defined as gestational hypertension and preeclampsia during the current pregnancy. A logistic regression model was performed to assess the association of PM2.5 and PM1 with HDP during the first and early second trimesters (0-13 weeks and 14-20 weeks). The generalized estimating equation model was conducted to assess the effect of PM2.5 and PM1 on blood pressure. The present study included 22,821 pregnant women (mean age, 29.1 years) from 2013 to 2017. PM2.5 and PM1 were significantly associated with an increased risk of de novo HDP during the first trimester (OR = 1.070, 95% CI: 1.013-1.130; OR = 1.264, 95% CI: 1.058-1.511 for per 10 µg/m3) and early second trimester (OR = 1.045, 95% CI: 1.003-1.088; OR = 1.170, 95% CI: 1.002-1.366 for per 10 µg/m3). Significant trends of increased de novo HDP risk was also observed with the increment of PM (all P for trend <0.05). The stratified analyses demonstrated that the associations between exposure to fine PM and the risk of HDP were more pronounced among the pregnant women with maternal age above 35 and low maternal education level (all OR >1.047). Each 10 µg/m3 increase of PM1 and PM2.5 before diagnosis of de novo HDP elevated 0.204 (95% CI: 0.098-0.310) and 0.058 (95%CI: 0.033-0.083) mmHg of systolic blood pressure. Exposure to PM2.5 and PM1 during the first and early second trimester were positively associated with the risk of de novo HDP. The fine PM before diagnosis of de novo HDP elevated the systolic blood pressure.

Prediction of Adverse Outcomes in De Novo Hypertensive Disorders of Pregnancy: Development and Validation of Maternal and Neonatal Prognostic Models.

Effectively identifying high-risk patients with de novo hypertensive disorder of pregnancy (HDP) is required to enable timely intervention and to reduce adverse maternal and perinatal outcomes. Electronic medical record of pregnant women with de novo HDP were extracted from a birth cohort in Beijing, China. The adverse outcomes included maternal and fetal morbidities, mortality, or any other adverse complications. A multitude of machine learning statistical methods were employed to develop two prediction models, one for maternal complications and the other for perinatal deteriorations. The maternal model using the random forest algorithm produced an AUC of 0.984 (95% CI (0.978, 0.991)). The strongest predictors variables selected by the model were platelet count, fetal head/abdominal circumference ratio, and gestational age at the diagnosis of de novo HDP; The perinatal model using the boosted tree algorithm yielded an AUC of 0.925 (95% CI (0.907, 0.945]). The strongest predictor variables chosen were gestational age at the diagnosis of de novo HDP, fetal femur length, and fetal head/abdominal circumference ratio. These prediction models can help identify de novo HDP patients at increased risk of complications who might need intense maternal or perinatal care.

Interpretable machine learning to identify important predictors of birth weight: A prospective cohort study.

Background: Predicting birth weight and identifying its risk factors are clinically important. This study aims to use interpretable machine learning to predict birth weight and identity important predictors. Methods: This prospective cohort study was conducted in Tongzhou Maternal and Child Health Care Hospital of Beijing, China, recruiting pregnant women between June 2018 and February 2019. We used 24 features to predict infant birth weight, including gestational age, mother's age, parity, history of macrosomia delivery, pre-pregnancy body mass index (BMI), height, father's BMI, lifestyle (diet, physical activity, smoking), and biomarker (fasting glucose and lipids) features. Study outcome was birth weight of infant. We used 8 supervised learning models including 4 individual [linear regression, ridge regression, lasso regression, support vector machines regression (SVR)], and 4 ensemble estimators (random forest, AdaBoost, gradient boosted trees, and voting ensemble for regression) to predict birth weight. Model accuracy was measured by root mean squared error (RMSE) of 10-fold cross validation on the training set and RMSE of prediction on the test set. We used permutation importance algorithm to understand the prediction from the models and what affected them. Result: This study included 4,754 mother-child dyads. RMSEs were lower in voting ensemble for regression, linear regression, and SVR than random forest, AdaBoost, and gradient boosted tree. The 5 most important predictors for infant birth weight were gestational age, fetal sex, preterm birth, mother's height, and pre-pregnancy BMI. After adding ultrasound-measured indicators of fetal growth into predictors, mother's height and pre-pregnancy BMI remained the most important predictors in predicting the outcome. Conclusion: Mother's height and pre-pregnancy BMI were identified as important predictors for infant birth weight. Interpretable machine learning is a promising tool in the prediction of birth weight.

Parental transfer of an antibiotic mixture induces cardiotoxicity in early life-stage zebrafish: A cross-generational study.

Antibiotic residues in the aquatic environment have been shown to induce significant adverse effects on the early-life stage development of aquatic organisms, though the underlying molecular mechanisms of these effects have not been well characterized. In this study, we performed global mRNA-miRNA sequencing, canonical pathway analyses, morphological, physiological, immunohistochemical, and behavioral analyses to comprehensively assess the cross-generational cardiotoxicity and mechanisms of antibiotic mixtures in zebrafish. Following parental treatment to 1 and 100 µg/L antibiotic mixtures (15 of the most commonly detected antibiotics) for 150 days, all 15 assessed antibiotics were detected in the F1 eggs, indicating the cross-generational transfer of antibiotics. Global mRNA-miRNA sequencing functional analysis predicted cardiotoxicity in the F1 generation by using the F1 whole fish. Consistent with canonical pathway analyses, significant cardiotoxicity was observed in F1 larvae, as well as the apoptosis of cardiac cells. Furthermore, let-7a-5p regulated the cardiac hypertrophy signaling pathway, suggesting mechanisms of miRNA of let-7 family mediating cross-generational cardiotoxicity of antibiotics in zebrafish. This study lays some groundwork for developing interventions to prevent parental exposure to environmental pollutants such as antibiotics from adversely affecting offspring development.

Enrofloxacin Induces Intestinal Microbiota-Mediated Immunosuppression in Zebrafish.

The immunosuppressive effects of antibiotics and the potential associations with the intestinal microbiota of the host have been increasingly recognized in recent years. However, the detailed underlying mechanisms of immune interference of antibiotics in environmental organisms remain unclear, particularly at the early life stage of high sensitivity. To better understand the gut microbiome and immune function interactions, the vertebrate model, zebrafish, was treated with environmentally relevant concentrations of a frequently detected antibiotic, enrofloxacin (ENR), ranging from 0.01 to 100 µg/L. 16S ribosomal RNA sequencing indicated diminished diversity, richness, and evenness of intestinal flora following ENR treatment. Twenty-two taxa of gut bacteria including Rickettsiales, Pseudomonadales, and Flavobacteriales were significantly correlated with immunosuppressive biomarkers, including a significant decrease in the abundance of macrophages and neutrophils. To validate the immunomodulatory effects due to altered intestinal microbial populations, zebrafish reared under sterile and non-sterile husbandry conditions were compared after ENR treatment. A significant inhibitory effect was induced by ENR treatment under non-sterile conditions, while the number of macrophages and neutrophils, as well as biomarkers of immunosuppressive effects, were significantly salved in zebrafish under sterile conditions, confirming for the first time that immunosuppression by ENR was closely mediated through alterations of the intestinal microbiome in fish.

The First-Trimester Gestational Weight Gain Associated With de novo Hypertensive Disorders During Pregnancy: Mediated by Mean Arterial Pressure.

The relationship between first-trimester GWG ( T1GWG) and risk of hypertensive disorders of pregnancy (HDP) remained uncertain. This study aimed to investigate the association between T1GWG and risk of de novo HDP. Meanwhile, we explored the mediated effect and constructed an early GWG category to evaluate the predictive capacity for HDP. T1GWG was defined as the weight difference between 13 ± 1 gestational weeks and pre-conception. HDP group was defined as having diagnosis of de novo HDP, including gestational hypertension or de novo pre-eclampsia (PE) during the current pregnancy. Early GWG category was constructed according to the risk of HDP within each pre-pregnancy body mass index (BMI) group. Cox regression model was utilized to check the association between the T1GWG and HDP. Serial mediation model was adopted to evaluate the potential mediators including mean arterial pressure (MAP) at 13th and 20th week. The logistic regression model with bootstrap was performed to assess the predictive capacity of Early GWG category and MAP for the risk of HDP. A total of 17,901 pregnant women (mean age, 29.0 years) were recruited from 2013 to 2017 at the Tongzhou Maternal and Child Health Hospital in Beijing, China. Compared to women in Class 1 of early GWG category, women in the Class 2, 3, 4 have increased risks of HDP by 1.42, 4.27, and 4.62 times, respectively (hazard ratio [HR] = 2.42, 95% CI: 2.11-2.77; HR = 5.27, 95% CI: 4.05-6.86; HR = 5.62, 95% CI: 4.05-7.79). The MAP measured at 13th and 20th week totally mediated 33.1 and 26.7% of association between T1GWG GWG and HDP in total participants and overweight/obesity pregnancies, respectively. The area under receiver operator characteristic curve for predictive model utilizing early GWG category and MAP measured at 13th and 20th week for the risk of HDP is 0.760 (95% CI: 0.739-0.777). The T1GWG was associated with de novo HDP, which was partially mediated by MAP measured at 13th and 20th week. Early GWG category showed a better predictive capacity for the risk of HDP compared to the National Academy of Medicine criteria for T1GWG.

Individual and joint effects of prenatal green spaces, PM2.5 and PM1 exposure on BMI Z-score of children aged two years: A birth cohort study.

BACKGROUND: Few studies examined the association of prenatal exposure to green spaces with children's body mass index (BMI) Z-score, and no study evaluated the joint effect of prenatal green spaces and PM2.5 or PM1 exposure on children's BMI Z-score. We aimed to assess the individual and joint effects of prenatal green spaces, PM2.5, and PM1 exposure on BMI Z-score of children aged two years. METHODS: The study was based on a birth cohort in Beijing, China, in which 13,253 mothers (LMP from 2014 to 2017) and their children were included. We estimated prenatal green spaces exposure by calculating average normalized difference vegetation index with 500 m buffers (NDVI-500), prenatal PM2.5 and PM1 exposure based on maternal residential addresses. Weight and height of children were measured at 2 years old. We calculated children's BMI Z-score based on the WHO Standards. Generalized linear regression was used to examine the individual and joint effects of prenatal NDVI-500, PM2.5 and PM1 exposure on children's BMI Z-score. RESULTS: A 0.1 increase in prenatal NDVI-500 exposure, a 10 µg/m3 decrease in PM2.5, a 10 µg/m3 decrease in PM1 were associated with 0.185 [95% confidence interval (95%CI): 0.155, 0.216], 0.034 (95%CI: 0.015, 0.052) and 0.041 (95%CI: 0.020, 0.061) increase of children's BMI Z-score, respectively. Compared with those exposed to low-level NDVI-500 (not greater than median) and high-level PM2.5 (greater than median), the BMI Z-score was higher in children whose mother exposed to high-level of NDVI-500 and low-level PM2.5 [ß:0.172 (95%CI: 0.131, 0.214), Pinteraction = 0.003]. Compared with those exposed to low-level NDVI-500 and high-level PM1, the BMI Z-score was higher in children whose mother exposed to high-level of NDVI-500 and low-level PM1 [ß:0.169 (95%CI: 0.127, 0.210), Pinteraction<0.001]. In the trimester-specific analysis, NDVI-500 and PM exposure during the second trimester have a consistent individual effect, together with a joint effect, on child growth. CONCLUSION: The study suggested the beneficial effect of prenatal exposure to green spaces on child growth and its interaction with PM2.5 and PM1, especially in the second trimester. The findings call for developing public health policy to improve green infrastructure and control PM2.5 and PM1 concentrations, in order to promote child growth.

Gestational weight gain and the risk of gestational diabetes mellitus: A latent class trajectory analysis using birth cohort data.

AIMS: To explore trajectories of gestational weight gain (GWG) before diagnosis and its association with risk of gestational diabetes mellitus (GDM). METHODS: A population-based retrospective cohort study including 37,060 women with live singleton was conducted between 2013 and 2019 in China. Latent class trajectory model (LCTM) was used to identify GWG trajectories, and Poisson regression with robust error estimates was used to estimate risk ratio (RR) of GDM. RESULTS: Among total 37,060 participants, 25.47% of women were developed with GDM. Two trajectories of GWG were identified as non-excessive weight gain (94.31%) and excessive weight gain (5.69%) before diagnosis of GDM. Women with excessive GWG trajectory before diagnosis had significantly 32.8% (aRR = 1.328, 95 %CI: 1.252 âˆ¼ 1.409, P < 0.001) increased risk of developing GDM compared with non-excessive GWG trajectory. Women with excessive GWG trajectory also had higher risk of macrosomia (aRR = 1.476, 95 %CI: 1.307 âˆ¼ 1.666, P < 0.001) and cesarean delivery (aRR = 1.126, 95 %CI: 1.081 âˆ¼ 1.174, P < 0.001). The impact of excessive GWG trajectory on GDM was greater among pre-pregnancy normal weight women compared with overweight/obese or underweight women. CONCLUSION: Women with excessive GWG trajectory before diagnosis had significantly higher risk of GDM and GDM-related adverse outcomes, and pre-pregnancy normal weight women with excessive GWG trajectory should also be concerned.

Risk of Gestational Diabetes Mellitus in relation to Plasma Concentrations of Fatty Acid-Binding Protein 4: A Nested Case-Control Study in China.

OBJECTIVE: The study is aimed at examining the effects of fatty acid-binding protein 4 (FABP4) on insulin resistance and gestational diabetes mellitus (GDM). METHODS: Based on a prospective birth cohort in Beijing, China, we conducted a nested case-control study and analyzed 135 GDM case-control pairs matched by age and the gestational week when they took the oral glucose tolerance test. We performed linear regression to analyze the association of plasma FABP4 concentrations with insulin resistance. We used logistic regression to estimate odds ratios (ORs) of FABP4 for GDM, controlling for potential confounders, including dietary intake and physical activity. RESULTS: Plasma FABP4 levels in the first and second trimesters were positively associated with fasting insulin and homeostasis model assessment for insulin resistance (HOMA-IR) in the second trimester (both P < 0.001). Compared with those in the lowest FABP4 tertile, women in the highest tertile of FABP4 levels in the first and second trimesters had 1.053 times (OR = 2.053, 95% CI 1.091 to 3.863) and 1.447 times (OR = 2.447, 95% CI 1.305 to 4.588) higher risk of developing GDM. CONCLUSIONS: Elevated FABP4 levels in the first and second trimesters were associated with a higher level of insulin resistance and greater GDM risk, indicating FABP4 might predict women with high risk of developing GDM.

Exploring the mediating role of serum retinol-binding protein 4 in the relationship between sleep quality and insulin resistance in pregnant women.

AIMS: We aimed to explore the mediating role of plasma retinol-binding protein 4 (RBP4) in the relationship between sleep quality and insulin resistance (IR) among pregnant women. METHODS: We conducted a cross-sectional study including 263 pregnant women in the first trimester. Sleep quality was evaluated by Pittsburgh Sleep Quality Index (PSQI). The ELISA and homeostasis model assessment (HOMA) was used to analyze plasma RBP4 and estimate IR. The mediating model was used to analyze the mediating role of RBP4 in the relationship between PSQI score and IR. RESULTS: In the multivariable linear regression model, the three terms were positively related with each other, PSQI score was positively associated with IR levels (ß = 0.55, p < 0.05). In the mediating model, RBP4 levels mediated completely the relationship between PSQI scores and IR levels (ß = 0.29, p < 0.0001). The indirect effect of RBP4 in the relation between sleep quality and IR explained 89.10% of total effect. CONCLUSIONS: RPB4 may play a complete mediating role in the relation between sleep quality and insulin resistance in early pregnancy. Improvements in sleep quality in the first trimester may provide a pathway to reduce plasma RBP4, which is beneficial for less IR and GDM prevention.

Maternal sleep quality during early pregnancy, risk factors and its impact on pregnancy outcomes: a prospective cohort study.

OBJECTIVES: We aimed to assess the prevalence of poor sleep quality during early pregnancy and its risk factors, and to explore the association between sleep quality and adverse pregnancy outcomes. METHODS: This was a prospective birth cohort study that included 4352 pregnant women. Sleep quality were assessed using the Pittsburgh Sleep Quality Index (PSQI). The risk factors for poor sleep quality were analyzed by a logistic regression model. Log-binomial regression models were used to analyze the association between sleep quality and pregnancy outcomes. RESULTS: The prevalence of maternal poor sleep quality during early pregnancy was 34.14%. The multivariate logistic model showed that stillbirth history (OR = 2.45; 95% CI: 1.34, 4.47), history of induced abortion (OR = 1.26; 95% CI: 1.07, 1.49), general health-related quality of life (OR = 3.98; 95% CI: 2.97, 5.34), insufficient physical activity (OR = 1.18; 95% CI: 1.03, 1.36), smoking (OR = 1.59; 95% CI: 1.18, 2.15), and vegetarian (OR = 2.18; 95% CI: 1.54, 3.08) were risk factors for poor sleep quality, while taking folic acid consistently before pregnancy (OR = 0.83; 95% CI: 0.72,0.97) was the protective factor. After controlling for all the confounders, poor sleep quality during early pregnancy increased the risk of premature rupture of membranes by 12% (95% CI: 1.00, 1.25). CONCLUSION: Pregnant women with a history of stillbirth and induced abortion, general health-related quality of life, insufficient physical activity, smoking, and a vegetarian diet tended to have poor sleep quality. More attention should be paid to healthy lifestyle of pregnant women to improve sleep quality and better pregnancy outcomes.

Association between sleep duration in early pregnancy and risk of gestational diabetes mellitus: a prospective cohort study.

AIMS: As cohort studies of the impact of sleep duration during early pregnancy on gestational diabetes mellitus (GDM) are lacking, our study aimed to explore the association between sleep duration in the first trimester and GDM in one region of mainland China. METHODS: For this prospective cohort study, sleep duration data were collected from 3692 pregnant women at the first prenatal care appointment before 14 weeks of gestation. Multivariable log-binomial regression models were used to analyze the association of sleep duration with GDM after adjusting for demographic characteristics, health status (such as family history of diabetes, history of GDM, prepregnancy body mass index, gestational weight gain) and lifestyle habits (such as physical activity, dietary intakes). RESULTS: Our cohort included 166 (4.5%) short sleepers and 505 (14%) long sleepers. Shorter sleep duration was more likely to be observed in women aged ≥35 years who were multiparous, and had previous pregnancy, insufficient gestational weight gain, engaged in more vigorous physical activity, drank alcohol, were vegan and/or never took folic-acid supplements. Compared with normal sleepers (29%), the prevalence of GDM was significantly higher in short sleepers (38%; P = 0.01), but not in long sleepers (31%; P = 0.224). In the multivariable model, women with short sleep durations during early pregnancy had a 32% greater risk of GDM [adjusted risk ratio (aRR): 1.32, 95% CI: 1.06-1.63], whereas long sleepers did not (aRR: 1.09, 95% CI: 0.94-1.26). CONCLUSION: Short sleep duration during early pregnancy is associated with an increased risk of GDM. This suggests that more attention should be paid to controlling the development of GDM in pregnant women with insufficient sleep.

The association between maternal fat-soluble vitamin concentrations during pregnancy and infant birth weight in China.

Fat-soluble vitamins during pregnancy are important for fetal growth and development. The present study aimed at exploring the association between vitamin A, E and D status during pregnancy and birth weight. A total of 19 640 women with singleton deliveries from a retrospective study were included. Data were collected by the hospital electronic information system. Maternal serum vitamin A, E and D concentrations were measured during pregnancy. Logistic regression was performed to estimate the association between the vitamin status and low birth weight (LBW) or macrosomia. Women with excessive vitamin E were more likely to have macrosomia (OR 1·30, 95 % CI 1·07, 1·59) compared with adequate concentration. When focusing on Z scores, there was a positive association between vitamin E and macrosomia in the first (OR 1·07, 95 % CI 1·00, 1·14), second (OR 1·27, 95 % CI 1·11, 1·46) and third (OR 1·28, 95 % CI 1·06, 1·54) trimesters; vitamin A was positively associated with LBW in the first (OR 1·14, 95 % CI 1·01, 1·29), second (OR 1·31, 95 % CI 1·05, 1·63) and third (OR 2·00, 95 % CI 1·45, 2·74) trimesters and negatively associated with macrosomia in the second (OR 0·79, 95 % CI 0·70, 0·89) and third (OR 0·77, 95 % CI 0·62, 0·95) trimesters. The study identified that high concentrations of vitamin E are associated with macrosomia. Maintaining a moderate concentration of vitamin A during pregnancy might be beneficial to achieve optimal birth weight. Further studies to explore the mechanism of above associations are warranted.

Early Pregnancy Exposure to Rare Earth Elements and Risk of Gestational Diabetes Mellitus: A Nested Case-Control Study.

Objective: The extensive use of rare earth elements (REEs) in many technologies was found to have effects on human health, but the association between early pregnancy exposure to REEs and gestational diabetes mellitus (GDM) is still unknown. Methods: This nested case-control study involved 200 pregnant women with GDM and 200 healthy pregnant women from the Peking University Birth Cohort in Tongzhou. We examined the serum concentrations of 14 REEs during early pregnancy and analyzed their associations with the risk of GDM. Results: When the elements were considered individually in the logistic regression model, no significant associations were found between REEs and GDM, after adjusting for confounding variables (P > 0.05). In weighted quantile sum (WQS) regression, each quartile decrease in the mixture index for REEs resulted in a 1.67-fold (95% CI: 1.12-2.49) increased risk of GDM. Neodymium (Nd), Praseodymium (Pr), and Lanthanum (La) were the most important contributors in the mixture. Conclusion: The study findings indicated that early pregnancy exposure to lower levels of REE mixture was associated with an increased risk of GDM, and Nd, Pr, and La exhibited the strongest effects in the mixture.

The comparative toxicities of BPA, BPB, BPS, BPF, and BPAF on the reproductive neuroendocrine system of zebrafish embryos and its mechanisms.

Bisphenol A (BPA) is a well-known endocrine disruptor that has elicited great concern because of its potential toxic effects in organisms. In this study, the effects of BPA and several BPA structural analogs, including BPB, BPS, BPF, and BPAF, on the reproductive neuroendocrine system were evaluated during zebrafish embryonic and larval development. Our results showed that the numbers of gonadotropin-releasing hormone 3 neurons in zebrafish embryos increased after 100 µg/L BPA analog treatment, and exposure to BPA or its analogs at 1 or 100 µg/L increased the expression of reproductive neuroendocrine-related genes and the levels of typical hormones such as LH, FSH, E2, and GH. Moreover, the effects were associated with increases in the activities of erα, erß, and cyp19a genes. The respective estrogen receptors (ER) and aromatase (AROM) antagonists significantly attenuated the stimulation of lhß, fshß, LH, and FSH expression, thereby proving that BPA analogs affect the reproductive neuroendocrine system via ERs and AROM pathway. Furthermore, we observed that the reproductive neuroendocrine toxicity of BPAF was more similar to that of BPA. This was the first study to comparatively explore the reproductive neuroendocrine toxicities of bisphenols in aquatic organism.

The individual and joint effects of maternal 25(OH)D deficiency and gestational diabetes on infant birth size.

BACKGROUND AND AIMS: To examine the independent effect of maternal serum 25-hydroxyvitamin D [25(OH)D] deficiency and its joint effect with gestational diabetes mellitus (GDM) on infant birth size. METHODS AND RESULTS: This retrospective cohort study was conducted in 15,724 mother-offspring dyads in Beijing, China between 2016 and 2017. Outcomes included infant birth weight Z-score (adjusted for gestational age and sex) and large for gestational age (LGA). Exposures were maternal 25(OH)D concentrations. Linear and logistic regression models were used to assess the associations of exposures with continuous and binary outcomes, respectively. Exposure-outcome associations were not observed when analyzing 25(OH)D concentrations continuously or in quartiles (P > 0.05); however, mothers with severely deficient 25(OH)D concentrations (n = 307) had a decreased risk of LGA compared with those with sufficient 25(OH)D concentrations (≥30.0 ng/mL; n = 5400) (adjusted odds ratio (OR): 0.63; 95% confidence interval (CI): 0.42, 0.93). Compared to mothers with no 25(OH)D deficiency (≥20.0 ng/mL) and no GDM (n = 7975), those with both 25(OH)D deficiency and GDM (n = 1090) had 0.15 (95% CI: 0.09, 0.21) higher infant birth weight Z-score and a higher risk of LGA (OR: 1.29; 95% CI: 1.09, 1.52). Maternal 25(OH)D deficiency and GDM had additive interaction on the risk of LGA (relative risk due to interaction: 0.18). CONCLUSION: Mothers with severely deficient 25(OH)D might have a decreased risk of LGA. However, the joint effect of maternal 25(OH)D deficiency and GDM might increase the risk of LGA. Our findings have clinical and public health implications and provide potential directions for future studies.