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AIM: To develop a visual prediction model for gestational diabetes (GD) in pregnant women and to establish an effective and practical tool for clinical application. METHODS: To establish a prediction model, the modelling set included 1756 women enrolled in the Zunyi birth cohort, the internal validation set included 1234 enrolled women, and pregnant women in the Wuhan cohort were included in the external validation set. We established a demographic-lifestyle factor model (DLFM) and a demographic-lifestyle-environmental pollution factor model (DLEFM) based on whether the women were exposed to environmental pollutants. The least absolute shrinkage and selection lasso-logistic regression analyses were used to identify the independent predictors of GD and construct a nomogram for predicting its occurrence. RESULTS: The DLEFM regression analysis showed that a family history of diabetes (odd ratio [OR] 2.28; 95% confidence interval [CI] 1.05-4.71), a history of GD in pregnant women (OR 4.22; 95% CI 1.89-9.41), being overweight or obese before pregnancy (OR 1.71; 95% CI 1.27-2.29), a history of hypertension (OR 2.61; 95% CI 1.41-4.72), sedentary time (h/day) (OR 1.16; 95% CI 1.08-1.24), monobenzyl phthalate (OR 1.95; 95% CI 1.45-2.67) and Q4 mono-ethyl phthalate concentration (OR 1.85; 95% CI 1.26-2.73) were independent predictors. The area under the receiver operating curves for the internal validation of the DLEFM and the DLFM constructed using these seven factors was 0.827 and 0.783, respectively. The calibration curve of the DLEFM was close to the diagonal line. The DLEFM was thus the more optimal model, and the one which we chose. CONCLUSIONS: A nomogram based on preconception factors was constructed to predict the occurrence of GD in the second and third trimesters. It provided an effective tool for the early prediction and timely management of GD.

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BACKGROUND: Polybrominated diphenyl ethers (PBDEs) are a group of widely used chemicals and humans are exposed to them in their daily life. PBDEs exposure during pregnancy may have adverse effects on pregnant women and their fetuses. Nevertheless, limited information is available on the levels and determinants of PBDEs exposure in Chinese pregnant women. METHODS: The internal exposure levels of eight PBDEs (BDE-28, 47, 99, 100, 153, 154, 183, and 209) in placental samples of 1280 pregnant women from Zunyi birth cohort were analyzed using gas chromatography tandem mass spectrometry. All PBDEs concentrations were lipid adjusted (ng/g lw). Determinants of exposure were assessed by multivariable logistic regression model. RESULTS: Eight PBDE homologues were quantifiable in more than 70% of the samples. The highest median concentrations were found for BDE-209 (2.78 ng/g lw), followed by BDE-153 (1.00 ng/g lw) and BDE-183 (0.93 ng/g lw). The level of ΣPBDEs ranged from 0.90 to 308.78 ng/g lw, with a median concentration of 10.02 ng/g lw. Multivariate logistic regression analysis showed that maternal age older than 30 years old (OR: 1.59; 95% CI: 1.14, 2.23), pre-pregnancy obesity (1.51; 1.08, 2.10), home renovation within 2 years (1.43; 1.08, 1.91), spending more time outdoors during pregnancy (0.70; 0.55, 0.89), high consumption of fish/seafood (1.46; 1.13, 1.90) and eggs (1.44; 1.04, 2.00), male infant sex (1.69; 1.18, 2.42) were associated with PBDEs exposure. CONCLUSION: The study population is generally exposed to PBDEs, of which BDE-209 is the dominant congener, indicating extensive application of products containing deca-BDE mixtures. Maternal age, pre-pregnancy BMI, home decoration, average outdoor time during pregnancy, fish, seafood, eggs consumption, and fetal sex were exposure-determinning factors. This study contributes to the knowledge on region-specific PBDEs contamination in pregnant women and related risk factors.

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The association of polycyclic aromatic hydrocarbons (PAHs) with gestational diabetes mellitus (GDM) and gestational hypertension during pregnancy has not yet been established. To investigate the association between PAH exposure and GDM and gestational hypertension, we conducted a cross-sectional study of 4206 pregnant women from the Zunyi birth cohort in southwestern China. Gas chromatography/mass spectrometry was used to detect the urinary levels of 10 monohydroxylated PAHs (OH-PAHs). GDM and gestational hypertension were diagnosed and the relevant information was documented by specialist obstetricians and gynecologists. Logistic regression and restricted cubic spline regression were employed to investigate their single and nonlinear associations. Stratified analyses of pregnancy and body mass index data were conducted to determine their moderating effects on the abovementioned associations. Compared with the first quartile of urinary ∑OH-PAHs, the third or fourth quartile in all study participants was associated with an increased risk of GDM (quartile 3: odds ratio [OR] = 1.35, 95% confidence interval [CI]: 1.03-1.77) and gestational hypertension (quartile 3: OR = 1.88, 95% CI: 1.26-2.81; quartile 4: OR = 1.58, 95% CI: 1.04-2.39), respectively. Nonlinear associations of 1-OH-PYR with GDM (cutoff level: 0.02 µg/g creatinine [Cr]) and 1-OH-PHE with gestational hypertension (cutoff level: 0.06 µg/g Cr) were also observed. In pregnant women with overweight or obesity, 1-OH-PHE and 3-OH-PHE were more strongly associated with gestational hypertension. Our results indicate that exposure to PAH during pregnancy may significantly increase the maternal risks of GDM and gestational hypertension; however, this finding still needs to be confirmed through larger-scale prospective studies and biological evidence.

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In this study, we evaluated the extraction effect of three different extractants, namely hexane + ether (v/v = 3:1), acetonitrile and ethyl acetate, on polycyclic aromatic hydrocarbons (PAHs) and phthalic acid esters (PAEs) in placenta detected and analysed by triple quadrupole gas chromatography-mass spectrometry (GC-MS/MS). The results showed that n-hexane + ether (v/v = 3:1) had the highest extraction efficiency. Under the optimal conditions, the limits of detection (LOD) for the 10 PAHs were 0.003-0.0167 µg/L with relative standard deviations (RSD) of 1.4-5.48% and detection rates of 68.19-107.05%, and the correlation coefficients were (R2, 0.9982-0.9999). The LODs for the nine PAEs were 0.0015-3.5714 µg/L and the correlation coefficients were (R2, 0.9982-0.9999). The limits of detection (S/N = 3) for the nine PAHs were 0.0015-0.5714 µg/L with relative standard deviations (RSD) of 3.15-8.37%, and the detection rates were 80.45-112.59% with correlations of (R2, 0.9972-0.9998). The method was applied to the analysis of PAHs and phthalates in placenta samples from pregnant women. The method's accuracy and applicability were demonstrated. In comparison with other methods for the detection of PAEs and PAHs, the method proposed in this paper has a wider linear range, lower minimum detection limit and comparable recovery with good correlation. This paper is dedicated to providing another method for improving the performance of extracting solid tissues.

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Pregnant women are widely exposed to phthalic acid esters (PAEs) that are commonly used in most aspects of modern life. However, few studies have examined the cumulative exposure of pregnant women to a variety of PAEs derived from the living environmental conditions in China. Therefore, this study aimed to determine the urinary concentrations of nine PAE metabolites in pregnant women, examine the relationship between urinary concentrations and residential characteristics, and conduct a risk assessment analysis. We included 1,888 women who were in their third trimester of pregnancy, and we determined their urinary concentrations of nine PAE metabolites using high-performance gas chromatography-mass spectrometry. The risk assessment of exposure to PAEs was calculated based on the estimated daily intake. A linear regression model was used to analyze the relationship between creatinine-adjusted PAE metabolite concentrations and residential characteristics. The detection rate of five PAE metabolites in the study population was > 90%. Among the PAE metabolites adjusted by creatinine, the urinary metabolite concentration of monobutyl phthalate was found to be the highest. Residential factors, such as housing type, proximity to streets, recent decorations, lack of ventilation in the kitchen, less than equal to three rooms, and the use of coal/kerosene/wood/wheat straw fuels, were all significantly associated with high PAE metabolite concentrations. Due to PAE exposure, ~ 42% (n = 793) of the participants faced potential health risks, particularly attributed to dibutyl phthalate, diisobutyl phthalate, and di(2-ethyl)hexyl phthalate exposure. Living in buildings and using coal/kerosene/wood/wheat straw as domestic fuel can further increase the risks.

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Phthalates (PAEs) are widespread persistent organic pollutants and endocrine disruptors. However, the associations between PAE exposure and the risk of miscarriage in humans are unclear, and an insufficient number of studies have evaluated the possible threshold or dose-dependent effects of first trimester PAE exposure on miscarriage risk. Our research measured the levels of mono-methyl phthalate (MMP), mono-ethyl phthalate, mono-isobutyl phthalate, MiBP mono-butyl phthalate (MBP), mono-octyl phthalate, mono-benzyl phthalate, mono(2-ethylhexyl) phthalate, mono(2-ethyl-5-oxohexyl) phthalate, and mono(2-ethyl-5-hydroxyhexyl) phthalate (MEHHP) in maternal urine collected in early gestation between 150 pregnancies ending in miscarriage and 150 pregnancies with live birth. We also estimated the odds ratios (ORs) and 95% confidence intervals (CIs) for miscarriage and each PAE as a continuous variable or quartile. A restrictive cubic splines was used to assess dose-dependent effects after controlling for maternal characteristics (e.g., age, educational level). we identified monotonically increasing dose-dependent effects of MEHHP and MMP on the risk of miscarriage. The largest effect estimates were approximately threefold higher for the highest MBP (OR = 2.57; 95% CI = 1.32-5.01) or MMP quartile (OR = 3.57; 95% CI = 1.82-7.00) and two-fold higher for the highest MEHHP quartile (OR = 2.12; 95% CI = 1.10-4.11). Our research preliminarily obtained possible thresholds of MBP, MEHHP, and MMP which were 18.07, 2.38, and 0.80 µg/g Cr for the risk of miscarriage, respectively. First-trimester exposure to MBP, MEHHP, and MMP exceeding certain thresholds increases the risk of miscarriage.

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OBJECTIVE: Our aim was to elucidate the polycyclic aromatic hydrocarbon (PAH) metabolites exposure levels of pregnant women in the underdeveloped region of Zunyi, southwest China. METHODS: Sociodemographic information was collected via questionnaires, and urine samples were collected at the same time. A total of 3047 pregnant women participated in the study. Gas chromatography/mass spectrometry was used to detect the urine concentrations of 10 PAH metabolites. A generalised linear model (GLM) was used to identify predictive factors of PAH metabolites. RESULTS: All PAH metabolites had a detection rate greater than 60% (67.21%-90.57%) except for 4-OH-PHE at 55.54%. The median concentrations were 0.02-0.11 µg/g Cre except for 1-OH-NAP, 2-OH-NAP, 2-OH-FLU and 9-OH-FLU (0.36-0.50 µg/g Cre). The cluster analysis identified the phenanthrene and fluorene metabolite clusters (containing no other metabolites), while naphthalene metabolites (1-OH-NAP, 2-OH-NAP) could not be clustered without other metabolites. GLM analysis identified that pregnant women with the following characteristics have high urinary concentration of PAH metabolites: overweight, in the last trimester of pregnancy, distance between their house and main traffic lines as <5 m, use fuel for cooking, passive smoking, renovated their residence for less than 3 years, middle family income and office workers. CONCLUSION: The results clarified pregnant women from the economically underdeveloped area could be the victims of PAHs. In addition, PAHs present a demographic and seasonal differential distribution, which will aid in the development of targeted interventions and reduce exposure to PAHs during pregnancy.

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Owing to the complexity of phthalates (PAEs) components and the diversity of their sources, the health hazards of their metabolites to pregnant women remain unclear. This study aimed to explore the relationship between exposure to PAEs during early pregnancy and gestational diabetes mellitus (GDM) in rural pregnant women. We assessed pregnant women with (n = 338) or without (n = 3082) GDM from the ongoing Zunyi Birth Cohort. Participants' urine samples were collected to measure the levels of 10 metabolites of PAEs. GDM was diagnosed using the 75-g oral glucose tolerance test at 24-28 weeks of gestation. We adopted propensity score matching based on GDM-related factors and pregnant women's backgrounds to establish two groups of 338 patients: those with or without GDM. In the cohort, we included 5734 pregnant women; 519 of them developed GDM, yielding a GDM incidence rate of 9.05%. Urinary concentrations of monooctyl phthalate (MOP), mono-benzyl phthalate (MBzP), mono(2-ethyl-5-oxyhexyl) phthalate (MEOHP), and mono(2-ethyl-5-carboxypentyl) phthalate (MECPP) during early pregnancy were significantly associated with GDM (P < 0.05). Logistic regression models revealed that MEOHP in the urine was positively associated with GDM (odds ratio [OR] = 1.55; 95% confidence interval [CI]: 1.00-2.39). Furthermore, restricted cubic spline models revealed that urine MEOHP concentrations greater than 15.6 µg/L were positively associated with GDM, and approximately 23.5% pregnant women had urine MEOHP concentrations greater than 15.6 µg/L. Thus, approximately 23.5% of pregnant women were at the risk of developing GDM due to MEOHP, which suggested that pregnant women should reduce the use of packaged food and cosmetics to reduce the risk of GDM. However, further molecular biology experiments are required to confirm these findings and to elucidate the underlying mechanisms.

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Background: The sleep quality of undergraduates is considerably worse than that in general population, a cross sectional study was conducted to evaluate sleep quality and identify related factors. Methods: All participants from the freshmen to senior were recruited by the stratified cluster sampling from December 1, 2018 to January 12, 2019. The questionnaire used in this research was primarily composed of three sections: demographic characteristics, Pittsburgh Sleep Quality Index (PSQI) questionnaire and influencing factors of sleep quality. The data were analyzed using SPSS 18.0. Results: A total of 1,063 valid questionnaires were collected. Among them, 53.7% subjects suffered poor sleep quality. PSQI general score was 5.94 ± 2.73. There were significantly differences in sleep quality in sex, majors and grades. The survey reported that women suffered worse sleep quality than that of men, and medical students suffered worse sleep quality than non-medical students. Meanwhile, it also found that freshmen had better sleep quality than that of sophomores and juniors, sophomores suffered worst sleep quality. The logistic regression analysis showed that bad physical condition (OR (Odds ratio): 2.971 (2.034∼4.339)) and smoking (OR: 1.754 (1.258∼2.446)) were associated with poor sleep quality in males. However, more factors associated with poor sleep quality among females were found, including noisy dormitory environment (OR: 2.025 (1.354-3.030)), skipping breakfast more times per week (OR: 1.332 (1.031∼1.721)), drinking coffee before sleep (OR: 2.111 (1.155∼3.861)), playing with mobile phones for more than 45 minutes before sleep (OR: 1.745 (1.210∼2.515)), more time spent playing games per day (OR: 1.347 (1.048∼1.730)), bad physical condition (OR: 2.507 (1.797-3.497)), and severe academic stress (OR: 1.561 (1.126-2.166)). Conclusion: About half of college students experienced poor sleep, and poor sleep quality was prevalent in women, medical students, and sophomores. Moreover, there were more risk factors associated with the poor sleep quality of women than with men. Health policymakers should fully consider these factors in improving the sleep quality of college students.

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Emerging evidence from observational studies proves the association between preterm birth (PTB) and phthalate metabolites; however, such findings are inconsistent and inconclusive. This meta-analysis aimed to clarify this association by accessing the connection between 11 phthalate metabolites and PTB, and 6 phthalate metabolites and spontaneous PTB. The PubMed, Embase, and WOS (Web of Science) databases were searched up to July 2020. Seven prospective studies met the inclusion criteria. Pooled odds ratios (OR) with 95 % confidence intervals (CIs) were calculated for risk estimation. Our results indicated that mono-n-butyl phthalate (MBP), sum of di-2-ethylhexyl phthalate (ΣDEHP), and mono 3-carboxypropyl phthalate (MCPP) significantly correlated with the risk of PTB (MBP: OR = 1.23, 95 % CI = 1.05-1.45; ΣDEHP: OR = 1.21, 95 % CI =1.01-1.44; MCPP: OR = 1.09, 95 % CI = 1.00-1.19). Pooled results showed that spontaneous PTB was associated with higher urinary levels of mono-ethyl phthalate (MEP), MCPP, mono-isobutyl phthalate (MIBP), and MBP (MBP: OR = 1.27, 95 % CI = 1.02-1.58; MEP: OR = 1.19, 95 % CI = 1.01-1.40; MCPP: OR = 1.15, 95 % CI = 1.02-1.30; MIBP: OR = 1.38, 95 % CI = 1.12-1.71). Overall, we conclude that during pregnancy, MBP, ΣDEHP, and MCPP levels are associated positively with PTB. MBP, MEP, MCPP, and MIBP levels had increased odds of spontaneous PTB. No significant associations were observed between other phthalate metabolites and PTB or spontaneous PTB. Further research is needed to verify these findings and elucidate the association of phthalate levels and PTB.

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Reported evidence has increasingly indicated that exposure to phthalates can cause adverse pregnancy outcomes. However, phthalate exposure levels among pregnant women remains unclear. We aimed to evaluate the concentrations and predictors of phthalate metabolites in urine samples of the ongoing Zunyi cohort of pregnant women from Southwest China. The urine samples were collected from 1003 pregnant women during their third trimester of pregnancy. The concentrations of nine phthalate metabolites in urine samples were then determined. Data on socio-demographic profiles of the participants, lifestyle during pregnancy, parity, and sampling season were collected using questionnaires. The detectable rate of phthalate metabolites ranged from 76 to 100%. On average, mono-butyl phthalate exhibited the highest median concentration (62.45 µg/L), while mono-benzyl phthalate exhibited the lowest median concentration (0.04 µg/L). Urine concentrations of phthalate metabolites were significantly higher in older, multiparous, higher body mass index, higher income, and passive smoking during pregnancy participants. The levels of low-molecular-weight phthalate metabolites were highest during the summer. The findings indicate the health of pregnant women and fetuses in Zunyi may be generally harmed by the high exposure of phthalate metabolites, especially by mono-n-butyl phthalate. In addition, phthalate metabolites present a demographic and seasonal differential distribution among the study population. Targeted measures to reduce phthalate exposure for high-risk pregnant women and during high-exposure seasons may have potential benefits for maternal and fetal health protection.

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BACKGROUND: Prenatal exposures to polybrominated diphenyl ethers (PBDEs) may affect fetal growth. Small for gestational age (SGA) is a measure based on birth weight and gestational age at birth and represents a good indicator of fetal growth but it has been used only in a small number of studies. The present study aimed to examine the associations between PBDEs exposure and the risk of SGA among participants from a birth cohort in Southwest China. METHODS: The concentrations of eight common PBDE congeners (BDE-28, BDE47, BDE-99, BDE-100, BDE-153, BDE-154, BDE-183, and BDE-209) in 996 human placental samples collected between May to October 2020 were determined. A questionnaire survey was administered regarding maternal characteristics. The outcome data of the newborns were obtained from the medical record. The Mann-Whitney U test and binomial logistic regression analysis were used to assess associations between PBDEs concentrations (as a continuous or categorical variable) and SGA. RESULTS: All PBDE congeners were detected in more than 73% of samples. The median concentrations of ΣPBDEs were 10.08 ng/g lipid weight (lw). BDE-209 was the most abundant PBDE congener, contributed 28% to ΣPBDEs. There were 114 (11.4%) SGA infants. The levels of BDE-99, BDE-100, BDE-209, and the total levels of ΣPBDEs in the SGA group were significantly higher than those in the controls. When classifying the PBDEs concentrations as two categories: low and high, high level of ΣPBDEs was associated with increased risk of SGA [odds ratio (OR): 2.203, 95% confidence interval (CI): 1.453-3.340] after adjusting for potential covariates. The association remained significant when stratifying the data by gender of the newborn (OR: 2.572, 95% CI: 1.337-4.947 for boys; OR: 2.385, 95% CI: 1.315-4.325 for girls). CONCLUSION: The present study adds to the literature by using placenta to measure PBDEs exposure during pregnancy, and provides evidence that prenatal exposure to PBDEs may be associated with the risk of SGA, at least at the levels of exposure in our population.

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