Humans are widely exposed to environmental pollutants, affecting glucose homeostasis and resulting in gestational diabetes mellitus (GDM). However, studies about joint exposure of heavy metals and glucose homeostasis during pregnancy are limited and with the inconsistent findings. Blood concentrations of mercury (Hg), arsenic (As), lead (Pb), copper (Cu), vanadium (V), beryllium, strontium, zinc, nickel, cobalt, chromium, titanium, aluminum, antimony and iron were measured using inductively coupled plasma-mass spectrometry among 251 GDM women and 502 matched controls from Taiyuan, China. Multivariate logistic regression models, Bayesian kernel machine regression (BKMR), weighted quantile sum (WQS) regression, and quartile g-computation regression (QGCOMP) were used to assess the associations between metals exposures, maternal glucose homeostasis and GDM. An increased risk of GDM was associated with As, Pb and Hg in 1st trimester. Furthermore, exposure to Cu and Hg were associated with an elevated risk of GDM in 2nd trimester. The BKMR, WQS regression, and QGCOMP all found metals mixture exposure, predominated by Hg, As, and Pb in 1st trimester, was positively associated with GDM. The WQS regression revealed a positive correlation between metals characterized by Hg, Cu and As and GDM in 2nd trimester. The risk on GDM from joint metals was predominated by Hg, As, and Pb in 1st trimester, and by Hg, Cu, and As in 2nd trimester.

Background:It remains unclear whether non-optimum temperatures are associated with hospital admissions for subtypes of cardiovascular events, and how PM2.5 and black carbon (BC) modify these associations. Methods:Hospital admission data of major cardiovascular events were obtained from two major national health insurance systems across 270 cities of prefecture-level or above in China during 2013-2017. A two-stage time-series study was conducted using a generalized additive model with a quasi-Poisson family, combined with a distributed lag nonlinear regression model, to explore the exposure-response associations of non-optimum temperatures with hospital admissions. Effect modification was investigated by stratifying ambient particulate air pollution levels into quartile groups. Findings:In a total of 24,564,921 hospital admission records for major cardiovascular events, compared with the minimum morbidity temperature (18.3 °C), the relative risks (RRs) of hospital admissions for total major cardiovascular events associated with extreme cold temperature (-3.1 °C, 2.5th percentile) and extreme hot temperature (27.9 °C, 97.5th percentile) were 1.69 [95% confidence interval (CI): 1.46-1.96] and 1.27 (95% CI: 1.15-1.41), respectively. Such temperature-hospital admission associations were amplified at high BC levels, especially under extreme hot temperature, with RR increased from 1.14 (95% CI: 1.02-1.28) in the first quartile to 1.53 (95% CI: 1.31-1.78) in the fourth quartile group of BC levels. Interpretation:Our study suggests that both extreme cold and hot temperatures contribute to elevated hospital admission risks for major cardiovascular events, with high BC levels further exacerbating the risks associated with extreme hot temperature. Funding:National Science Fund for Distinguished Young Scholars of China (grant number 82525058), National Natural Science Foundation of China (grant number 82203991), and Youth Top Talent Program of Xi'an Jiaotong University.

Acute appendicitis (AA) is a predominant surgical emergency, yet its environmental risk factors remain poorly understood. While fine particulate matter (PM2.5) is a known risk factor for cardiopulmonary disease, its association with AA morbidity has not been well established. We conducted a nationwide time-stratified case-crossover study using hospital admission (HA) records of AA across 277 Chinese cities of prefecture level or above. The air pollutants studied were PM2.5 and its major constituents. We applied conditional logistic regression model and distributed lag non-linear model to estimate the exposure- and lag-response associations. During the study period (2013–2017), 1,287,040 HAs of AA were recorded. We observed that the impact of PM2.5 and its major constituents on the risk of HAs for AA emerged within 1–2 days after exposure and persisted for up to 7 days. Specifically, each interquartile range (30.99 μg/m3) increase in PM2.5 over lag 0–7 was associated with a 2.10% (95% CI: 1.02%, 3.19%) higher risk of HAs for AA. We found that black carbon (BC) was linked to the highest (2.44%, 95%CI: 1.31%, 3.58%) association with HAs for AA among the major PM2.5 constituents. The attributable fractions (AF) of AA due to BC and PM2.5 were 2.99% (95%CI: 1.64%, 4.32%) and 2.23% (95%CI:1.10%, 3.34%), respectively. This study provides nationwide evidence on the HA risk and burden of AA associated with PM2.5 and its major constituents. Our findings underscore the hazardous impact of PM2.5 on gastrointestinal health and the need for effective air quality control.

Short-term ambient fine particulate matter (PM2.5) exposure has been related to an increased risk of myocardial infarction (MI) death, but which PM2.5 constituents are associated with MI death and to what extent remain unclear. We aimed to explore the associations of short-term exposure to PM2.5 constituents with MI death and evaluate excess mortality. We conducted a time-stratified case-crossover study on 237,492 MI decedents in Jiangsu province, China during 2015–2021. Utilizing a validated PM2.5 constituents grid dataset at 1 km spatial resolution, we estimated black carbon (BC), organic carbon (OC), sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and chloride (Cl-) exposure by extracting daily concentrations grounding on the home address of each subject. We employed conditional logistic regression models to evaluate the exposure-response relationship between PM2.5 constituents and MI death. Overall, per interquartile range (IQR) increase of BC (lag 06-day; IQR: 1.75 μg/m3) and SO42- (lag 04-day; IQR: 5.06 μg/m3) exposures were significantly associated with a 3.91% and 2.94% increase in odds of MI death, respectively, and no significant departure from linearity was identified in the exposure-response curves for BC and SO42-. If BC and SO42- exposures were reduced to theoretical minimal risk exposure concentration (0.89 μg/m3 and 1.51 μg/m3), an estimate of 4.55% and 4.80% MI deaths would be avoided, respectively. We did not find robust associations of OC, NO3-, NH4+, and Cl- exposures with MI death. Individuals aged ≥80 years were more vulnerable to PM2.5 constituent exposures in MI death (p for difference <0.05). In conclusion, short-term exposure to PM2.5-bound BC and SO42- was significantly associated with increased odds of MI death and resulted in extensive excess mortality, notably in older adults. Our findings emphasized the necessity of reducing toxic PM2.5 constituent exposures to prevent deaths from MI and warranted further studies on the relative contribution of specific constituents.

目的 建立连续流动分析仪同时测定水中挥发酚、氰化物、阴离子合成洗涤剂、总磷、总氮、硫化物的方法.方法 采用并联两台连续流动分析仪主机的方法,通过特定前处理,能同时测定生活饮用水中挥发酚、氰化物、阴离子合成洗涤剂、硫化物和地表水中总磷、总氮的含量.结果 测定的挥发酚、氰化物、阴离子合成洗涤剂、总磷、总氮、硫化物在线性范围内的相关系数R均在0.999以上,检出限分别为0.001、0.000 3、0.032、0.015、0.037和0.011 mg/L.各指标的相对标准偏差(RSD)为0.42％～4.22％,加标回收率在94.3％～106.4％的范围内.结论 该法简单、快速,检出限低,精密度高和准确度好,满足实验室质量控制要求,适用于大批量样品分析.

BACKGROUND:Ambient fine particulate matter (PM2.5) exposure has been associated with an increased risk of gastrointestinal cancer mortality, but the attributable constituents remain unclear. OBJECTIVES:To investigate the association of long-term exposure to PM2.5 constituents with total and site-specific gastrointestinal cancer mortality using a difference-in-differences approach in Jiangsu province, China during 2015-2020. METHODS:We split Jiangsu into 53 spatial units and computed their yearly death number of total gastrointestinal, esophagus, stomach, colorectum, liver, and pancreas cancer. Utilizing a high-quality grid dataset on PM2.5 constituents, we estimated 10-year population-weighted exposure to black carbon (BC), organic carbon (OC), sulfate, nitrate, ammonium, and chloride in each spatial unit. The effect of constituents on gastrointestinal cancer mortality was assessed by controlling time trends, spatial differences, gross domestic product (GDP), and seasonal temperatures. RESULTS:Overall, 524,019 gastrointestinal cancer deaths were ascertained in 84.77 million population. Each interquartile range increment of BC (0.46 μg/m3), OC (4.56 μg/m3), and nitrate (1.41 μg/m3) was significantly associated with a 27%, 26%, and 34% increased risk of total gastrointestinal cancer mortality, respectively, and these associations remained significant in PM2.5-adjusted models and constituent-residual models. We also identified robust associations of BC, OC, and nitrate exposures with site-specific gastrointestinal cancer mortality. The mortality risk generally displayed increased trends across the total exposure range and rose steeper at higher levels. We did not identify robust associations for sulfate, ammonium, or chlorine exposure. Higher mortality risk ascribed to constituent exposures was identified in total gastrointestinal and liver cancer among women, stomach cancer among men, and total gastrointestinal and stomach cancer among low-GDP regions. CONCLUSIONS:This study offers consistent evidence that long-term exposure to PM2.5-bound BC, OC, and nitrate is associated with total and site-specific gastrointestinal cancer mortality, indicating that these constituents need to be controlled to mitigate the adverse effect of PM2.5 on gastrointestinal cancer mortality.

Chlorinated paraffins (CPs), particularly short-chain CPs (SCCPs), have been reported in human blood with high detection frequency and often high variation among individuals. However, factors associated with and their contributions to inter-individual variability in SCCP concentrations in human blood have not been assessed. In this study, we first measured SCCP concentrations in 57 human blood samples collected from individuals living in the same vicinity in China. We then used the PROduction-To-Exposure model to investigate the impacts of variations in sociodemographic data, biotransformation rates, dietary patterns, and indoor contamination on inter-individual variability in SCCP concentrations in human blood. Measured n-ary sumation SCCP concentrations varied by a factor of 10 among individuals with values ranging from 122 to 1230 ng/g, wet weight. Model results show that age, sex, body weight, and dietary composition played a minor role in causing variability in n-ary sumation SCCP concentrations in human blood given that modeled n-ary sumation SCCP concentrations ranged over a factor of 2 - 3 correlated to the

Fine particulate matter (PM2.5) chemical composition has strong and diverse impacts on the planetary environment, climate, and health. These effects are still not well understood due to limited surface observations and uncertainties in chemical model simulations. We developed a four-dimensional spatiotemporal deep forest (4D-STDF) model to estimate daily PM2.5 chemical composition at a spatial resolution of 1 km in China since 2000 by integrating measurements of PM2.5 species from a high-density observation network, satellite PM2.5 retrievals, atmospheric reanalyses, and model simulations. Cross-validation results illustrate the reliability of sulfate (SO42-), nitrate (NO3-), ammonium (NH4+), and chloride (Cl-) estimates, with high coefficients of determination (CV-R2) with ground-based observations of 0.74, 0.75, 0.71, and 0.66, and average root-mean-square errors (RMSE) of 6.0, 6.6, 4.3, and 2.3 μg/m3, respectively. The three components of secondary inorganic aerosols (SIAs) account for 21% (SO42-), 20% (NO3-), and 14% (NH4+) of the total PM2.5 mass in eastern China; we observed significant reductions in the mass of inorganic components by 40-43% between 2013 and 2020, slowing down since 2018. Comparatively, the ratio of SIA to PM2.5 increased by 7% across eastern China except in Beijing and nearby areas, accelerating in recent years. SO42- has been the dominant SIA component in eastern China, although it was surpassed by NO3- in some areas, e.g., Beijing-Tianjin-Hebei region since 2016. SIA, accounting for nearly half (∼46%) of the PM2.5 mass, drove the explosive formation of winter haze episodes in the North China Plain. A sharp decline in SIA concentrations and an increase in SIA-to-PM2.5 ratios during the COVID-19 lockdown were also revealed, reflecting the enhanced atmospheric oxidation capacity and formation of secondary particles.

Background and aims: Earlier studies have reported inconsistent association between selenium (Se) and homo-cysteine (Hcy) levels, while no evidence could be found from Chinese population. To fill this gap, we investigated the association between blood Se and hyperhomocysteinemia (HHcy) of rural elderly population in China.Methods: A cross-sectional study on 1823 participants aged 65 and older from four Chinese rural counties was carried out in this study. Whole blood Se and serum Hcy concentrations were measured in fasting blood samples. Analysis of covariance and restricted cubic spline models were used to examine the association between Se and Hcy levels. Logistic regression models were used to evaluate the risk of prevalent HHcy among four Se quartile groups after adjusting for covariates.Results: For this sample, the mean blood Se concentration was 156.34 (74.65) mu g/L and the mean serum Hcy concentration was 17.25 (8.42) mu mol/L. A significant non-linear relationship was found between blood Se and serum Hcy, the association was inverse when blood Se was less than 97.404 mu g/L and greater than 156.919 mu g/L. Participants in the top three blood Se quartile groups had significantly lower risk of prevalent HHcy compared with the lowest quartile group. When defined as Hcy> 10 mu mol/L, the odds ratios and 95% confidence interval of HHcy were 0.600 (0.390, 0.924), 0.616 (0.398, 0.951) and 0.479 (0.314, 0.732) for Q2, Q3, and Q4 Se quartile groups compared with the Q1 group, respectively. When defined as Hcy >= 15 mu mol/L, the odds ratios and 95% confidence interval of HHcy were 0.833 (0.633, 1.098) and 0.827 (0.626, 1.092), 0.647 (0.489, 0.857) for Q2, Q3, and Q4 Se quartile groups compared with Q1 group.Conclusions: Our findings suggest that higher blood Se level could be a protective factor for HHcy in the elderly.

OBJECTIVE:To investigate the effects of the concentration of fine particulate matter(PM_(2.5)) on the risk of death among residents in an urban area of Chongqing, China.METHODS:Daily data on mean PM_(2.5) concentration, meteorological factors(air temperature and relative humidity), and the number of deaths from 2013 to 2020 in this urban area were collected. A generalized additive model was used to analyze the association of PM_(2.5) concentration with the number of deaths, and stratified analyses by sex and age were further performed.RESULTS:In this area from 2013 to 2020, the median concentration of atmospheric ambient PM_(2.5) was 44.00 μg/m~3; 48 089 non-accidental deaths, 19 252 deaths from circulatory diseases, and 8753 deaths from respiratory diseases were reported. The PM_(2.5) concentration was higher in winter and spring. The number of deaths showed no obvious seasonal changes. The time series analysis showed that for every 10 μg/m~3 increase in the PM_(2.5) concentration, the risks of non-accidental death(lag03), circulatory diseases-caused death(lag3), and respiratory diseases-caused death(lag03) increased by 0.64%(95% CI 0.07%-1.21%), 0.68%(95% CI 0.05%-1.32%) and 1.72%(95% CI 0.54%-2.90%), respectively. After adjusting for several gaseous pollutants(PM_(10), NO_2, O_3, SO_2 and CO), the impact of PM_(2.5) concentration on residents&apos; health had no significant changes. The stratified analyses by sex and age showed that when the PM_(2.5) concentration increased, the risks of non-accidental death and death from respiratory diseases were higher in women and residents aged ≥65 years than in men and higher in residents aged ≥65 years than in those aged 5-64 years, but there were no significant differences between the groups.CONCLUSION:PM_(2.5) pollution may increase the risk of death for residents in this urban area in Chongqing.

This case–control study explored the associations between autism spectrum disorder (ASD) and the serum concentration of nine chemical elements in children. The study recruited 92 Chinese children with ASD and 103 typically developing individuals. Serum concentrations of nine chemical elements (calcium, iodine, iron, lithium, magnesium, potassium, selenium, strontium, and zinc) were determined by inductively coupled plasma mass spectrometry (ICP-MS) and inductively coupled plasma atomic emission spectrometry (ICP-AES). An unconditional logistic regression model was used to analyze the associations between the serum concentrations of the elements and the risk of ASD. After adjusting for confounders, the multivariate analysis results showed that zinc ≤ 837.70 ng/mL, potassium > 170.06 μg/mL, and strontium ≤ 52.46 ng/mL were associated with an increased risk of ASD, while selenium > 159.80 ng/mL was associated with a decreased risk of ASD. Furthermore, the degree of lithium and zinc deficiency was associated with ASD severity. The results indicated that metallomic profiles of some specific elements might play important roles in the development of ASD, a finding of scientific significance for understanding the etiology, and providing dietary guidance for certain ASD types.

Background: Short-term exposure to ambient air pollution has been linked to an increased risk of mortality from a variety of causes, but its effects on mortality from dementia remain largely unknown. Objectives: To investigate the association between short-term exposure to ambient air pollution and dementia mortal-ity, and quantitatively assess the excess mortality.Methods: In this time-stratified case-crossover study, 47,108 dementia deaths were identified in Jiangsu province, China during 2015-2019. Exposure to particulate matter with an aerodynamic diameter <= 2.5 mu m (PM2.5), PM10, sul-fur dioxide (SO2), nitrogen dioxide (NO2), carbon monoxide (CO), and ozone (O3) was assessed by extracting daily concentrations from a validated grid dataset based on each subject's residential address. Conditional logistic regression models were applied for exposure-response analyses.Results: There were 47,108 case days and 159,852 control days during the study period. Each 10 mu g/m3 increase of lag 04-day exposure to PM2.5, PM10, and NO2 was significantly associated with a 1.43 % (95 % CI: 0.77, 2.09 %), 1.06 % (0.59, 1.54 %), and 2.80 % (1.51, 4.10 %) increase in odds of dementia mortality, corresponding to an excess mortality of 4.87 %, 5.50 %, and 6.43 %, respectively. We estimated that reducing ambient air pollutant exposures to the WHO air quality guidelines would avoid up to 4.17 % of the dementia deaths, while the ambient air quality standards in China would only help avoid up to 0.39 %.Conclusions: This study provides consistent evidence that short-term exposure to PM2.5, PM10, and NO2 is associated with increased odds of dementia mortality, which can be translated to a considerable excess mortality. Our findings highlight a potential approach to prevent deaths from dementia by reducing individual exposures to ambient air pol-lution, especially in areas with high levels of ambient air pollution.

Cadmium (Cd) exposure has been reported to have neurotoxic effects in animal studies and associated with increased Alzheimer's Disease mortality and lower cognitive function in cross-sectional and case-control studies. However, no results from longitudinal studies on Cd and cognitive decline are available. In this prospective cohort study, we recruited 1867 participants aged 65 years or older from rural areas in China, blood Cd and cognitive function were measured at baseline (2010-2012), and 1554 participants completed cognitive function tests during a 3-year follow-up (2013-2015). Cognitive function was evaluated using nine standardized cognitive tests: The Community Screening Instrument for Dementia, the CERAD Word List Learning. Word list recall, IU Story Recall, Animal Fluency Test, Boston Naming Test, Stick Design, Delayed Stick Design and the IU Token Test. Analysis of covariance models and logistic regression models were used to determine the association between Cd and standardized cognitive decline adjusting for covariates. The median blood Cd concentration of this study population was 2.12 mu g/L and the interquartile range was 1.42-4.64 mu g/L Significant association of higher Cd levels with lower cognitive scores were observed in five individual cognitive tests ( Delayed Stick Design Test, Boston Naming Test, CERAD Word List Learning Test, Word List Recall Test and IU Story Recall Test) and the composite cognitive score adjusting for multi-covariates at baseline. Higher Cd levels were significantly associated with greater 3-year cognitive decline in Delayed Stick Design Test, Boston Naming Test, Hi Token Test, Word List Recall Test and Composite cognitive score. For these cognitive tests, participants in the top two Cd quartile groups had significantly greater decline than those in the lowest Cd quartile group, while the two lowest Cd quartile groups were not significantly different Our findings suggest that higher Cd exposure is associated with greater cognitive decline in older Chinese adults. (C) 2020 Elsevier B.V. All rights reserved.

There is increasingly concern that PM2.5 constituents play a significant role in PM2.5-related cardiovascular outcomes. However, little is known about the associations between specific constituents of PM2.5 and risk for cardiovascular health. To evaluate the exposure to specific chemicals of PM2.5 from various sources and their cardiac effects, a longitudinal investigation was conducted with four repeated measurements of elderly participants' HRV and PM2.5 species in urban Beijing. Multiple chemicals in PM2.5 (metals, ions and PAHs) were characterized for PM2.5 source apportionment and personalized exposure assessment. Five sources were finally identified with specific chemicals as the indicators: oil combustion (1.1%, V & PAHs), secondary particle (11.3%, SO42- & NO3-), vehicle emission (1.2%, Pd), construction dust (28.7%, Mg & Ca), and coal combustion (57.7%, Se & As). As observed, each IQR increase in exposure to oil combustion (V), vehicle emission (Pd), and coal combustion (Se) significantly decreased rMSSD by 13.1% (95% CI: -25.3%, -1.0%), 27.4% (95% CI: -42.9%, -7.6%) and 24.7% (95% CI: -39.2%, -6.9%), respectively, while those of PM2.5 mass with decreases of rMSSD by 11.1% (95% CI: -19.6%, -1.9%) at lag 0. Elevated exposures to specific sources/constituents of PM2.5 disrupt cardiac autonomic function in elderly and have more adverse effects than PM2.5 mass. In the stratified analysis, medication and gender modify the associations of specific chemicals from variable sources with HRV. The findings of this study provide evidence on the roles of influential constituents of ambient air PM2.5 and their sources in terms of their adverse cardiovascular health effects.

Objective:The STOP-Bang（S-B） questionnaire is widely used for screening patients with OSA. However, BMI and NC cutoff value in the original S-B questionnaire is 35 kg/m²and 40cm, the BMI and NC value in the young and middle-aged female patients in China is lower than that. We aimed to establish a more appropriate modified STOP-Bang（MS-B） questionnaire. Method:A total of 523 cases with suspected OSA in the young and middle-aged female were included in this study. All patients were asked to completed the S-B, MS-B questionnaire and undergo overnight polysomnography（PSG）. The BMI and NC value of the MS-B were determined by the optimal operating points of the ROC. The ability of S-B and MS-B were assessed by ROC and McNemar's test. Result:BMI=28 kg/m²and NC=36 cm as alternative cutoff is to refine S-B questionnaire. When taking apnea hypopnea index（AHI） ≥5 times/h, ≥15 times/h and ≥30 times/h as cut-offs, MS-B had higher sensitivity（88.7% vs 86.7%, 92.8% vs 87.7%, 95.0% vs 90.1%, respectively） and the area under the curve（0.74 vs 0.706, 0.734 vs 0.703, 0.739 vs 0.699, respectively） than S-B. There were significant differences in McNemar test（P<0.05）. Conclusion:This study examined the clinical utility of MS-B. MS-B may improve predictive performance of S-B questionnaire in the young and middle-aged female with OSA.

Background: Several studies with small sample size have reported inconsistent associations between single metal and preeclampsia (PE). Very few studies have investigated metal mixtures and PE. Methods: Blood concentrations of chromium (Cr), cadmium, mercury (Hg), arsenic (As), lead (Pb), nickel, cobalt, and antimony were measured using inductively coupled plasma-mass spectrometry among 427 PE women and 427 matched controls from Taiyuan, China. Multivariate logistic regression models, weighted quantile sum (WQS) regression, and principal component analysis were employed to examine exposure to single metals and metal mixtures in relation to PE. Results: An increased prevalence of PE was associated with Cr (OR = 1.76, 95% CI: 1.18, 2.62 and 1.90, 1.22, 2.93 for the middle and high vs. low), Hg (OR = 1.60, 95% CI: 1.08, 2.38 for the high vs. low) and As (OR = 1.64, 95% CI: 1.07, 2.52 for the middle vs. low). The WQS index, predominated by Cr, Hg, Pb, and As, was positively associated with PE. A principal component characterized by Cr and As also exhibited excessive association with PE. The highest PE prevalence was found among women who were overweight/obese before pregnancy and had high Cr levels compared to women who had pre-pregnancy normal body mass index (BMI) and low Cr levels. Conclusions: Our study provided evidence that exposure to multiple metals was associated with increased prevalence of PE, and the observed association with multiple metals was dominated by Cr, As. Our study also suggested that pre-pregnancy BMI might modify the association between Cr and PE.

Background: Zinc (Zn) has been suggested to impact fetal growth. However, the effect may be complicated by gestational diabetes mellitus (GDM) due to its impact on fetal growth and placental transport. This study aims to investigate whether GDM modifies the association between Zn levels and birth weight. Method: A cohort matched by GDM was established in Taiyuan, China, between 2012 and 2016, including 752 women with GDM and 744 women without. Dietary Zn intake was assessed during pregnancy. Maternal blood (MB) and cord blood (CB) Zn levels were measured at birth. Birth weight was standardized as the z score and categorized as high (HBW, >4000 g) and low (LBW, <2500 g) groups. Multivariate linear regression and multinomial logistic regression were used to examine the association between Zn levels and birth weight in offspring born to women with or without GDM. Results: 88.8% (N = 1328) of the population had inadequate Zn intake during pregnancy. In women with GDM, MB Zn level was inversely associated with birth weight (beta = -.17; 95% confidence interval (CI), -0.34 to -0.01), while CB Zn level was positively associated with birth weight (beta = .38; 95% CI, 0.06-0.70); suggestive associations were observed between MB Zn level and LBW (odds ratio 2.01; 95% CI, 0.95-4.24) and between CB Zn level and HBW (odds ratio 2.37; 95% CI, 1.08-5.21). Conclusions: GDM may modify the associations between MB and CB Zn levels and birth weight in this population characterized by insufficient Zn intake. These findings suggest a previously unidentified path of adverse effects of GDM.

An efficient and accurate method was developed for the simultaneous determination of 12 monohydroxylated polycyclic aromatic hydrocarbon metabolites in human urine. A 10.0-mL urine sample was hydrolyzed by enzyme and extracted using solid phase extraction. The metabolites were separated on an Acquity UPLC®HSS T3 column (100 mm×2.1 mm, 1.8 μm) with a mobile phase comprising methanol and water. The analytes were detected by electrospray ionization (ESI)-MS/MS in negative mode and multiple reaction monitoring (MRM) mode. The linear ranges of the 12 metabolites were 0.04-20.0 μg/L with correlation coefficients above 0.99. The detection limits were in the range of 0.01-0.41 μg/L and the recoveries were 80.0%-105%. The intra-group relative standard deviations (RSDs) were less than 9.12% and the inter-group RSDs were less than 19.7%. This method was applied to the analysis of 100 urine samples and the results showed that the method was simple, sensitive and selective.