Effects of heat waves and cold spells on blood parameters: a cohort study of blood donors in Tianjin, China.

BACKGROUND: With the increasing occurrence of extreme temperature events due to climate change, the attention has been predominantly focused on the effects of heat waves and cold spells on morbidity and mortality. However, the influence of these temperature extremes on blood parameters has been overlooked. METHODS: We conducted a cohort study involving 2,752 adult blood donors in Tianjin, China, between January 18, 2013, and June 25, 2021. The generalized additive mixed model was used to investigate the effects and lagged effects of heat waves and cold spells on six blood parameters of blood donors, including alanine aminotransferase (ALT), white blood cell count (WBC), red blood cell count (RBC), hemoglobin (HB), hematocrit (HCT), and platelet count (PLT). Subgroup analyses were stratified by sex, age, and BMI. RESULTS: Heat waves and cold spells are associated with changes in blood parameters, particularly HB and PLT. Heat waves increased HB and PLT, while cold spells increased HB and decreased PLT. The effect of heat waves is greater than that of cold spells. The largest effect of heat waves on HB and PLT occurred at lag1 with 2.6 g/L (95% CI: 1.76 to 3.45) and lag7 with 9.71 × 10^9/L (95% CI: 6.26 to 13.17), respectively, while the largest effect of cold spells on HB and PLT occurred at lag0 with 1.02 g/L (95% CI: 0.71 to 1.33) and lag2 with -3.85 × 10^9/L (95% CI: -5.00 to -2.70), respectively. In subgroup analysis, the effect of cold spells on ALT was greater in the 40-49 age group. CONCLUSION: We indicated that heat waves and cold spells can impact hemoglobin and platelet counts in the human body. These findings provide evidence linking heat waves or cold spells to diseases and may reduce health risks caused by extreme temperature events.

Changes in muscle strength and risk of cardiovascular disease among middle-aged and older adults in China: Evidence from a prospective cohort study.

BACKGROUND: Evidence indicates that low muscle strength is associated with an increased cardiovascular diseases (CVDs) risk. However, the association between muscle strength changes based on repeated measurements and CVD incidence remains unclear. METHODS: The study used data from the China Health and Retirement Longitudinal Study in 2011 (Wave 1), 2013 (Wave 2), 2015 (Wave 3), and 2018 (Wave 4). Low muscle strength was defined as handgrip strength <28 kg for men or <18 kg for women, or chair-rising time ≥12 s. Based on changes in muscle strength from Waves 1 to 2, participants were categorized into four groups of Normal-Normal, Low-Normal, Normal-Low, and Low-Low. CVD events, including heart disease and stroke, were recorded using a self-reported questionnaire during Waves 3 and 4 visits. Cox proportional hazards models were used to investigate the association between muscle strength changes and CVD incidence after multivariable adjustments. Hazard ratios (HRs) and 95% confidence intervals (95% CIs) were estimated with the Normal-Normal group as the reference. RESULTS: A total of 1164 CVD cases were identified among 6608 participants. Compared to participants with sustained normal muscle strength, the CVD risks increased progressively across groups of the Low-Normal (HR = 1.20, 95% CI: 1.01-1.43), the Normal-Low (HR = 1.35, 95% CI: 1.14-1.60), and the Low-Low (HR = 1.76, 95% CI: 1.49-2.07). Similar patterns were observed for the significant associations between muscle strength status and the incidence risks of heart disease and stroke. Subgroup analyses showed that the significant associations between CVD and muscle strength changes were consistent across age, sex, and body mass index (BMI) categories. CONCLUSIONS: The study found that muscle strength changes were associated with CVD risk. This suggests that continuous tracking of muscle status may be helpful in screening cardiovascular risk.

Ambient PM2.5-bound polycyclic aromatic hydrocarbons (PAHs) associated with pro-thrombotic biomarkers among young healthy adults: A 16 times repeated measurements panel study.

Studies have shown that the cardio/cerebrovascular toxicity of ambient PM2.5 is related to its bound polycyclic aromatic hydrocarbons (PAHs). Currently, only a few studies have reported the relationship between PM2.5-bound PAHs and promoted blood coagulation and thrombosis, but there isn't a consistent conclusion. Therefore, we conducted a prospective panel study to investigate the association. Thirty-three young healthy adults participated in sixteen repeated visits from 2014 to 2018 in Tianjin, China. During each visit, three pro-thrombotic biomarkers: ADAMTS13 (a disintegrin and metalloproteinase with thrombospondin motif 13), D-dimer and Myeloperoxidase (MPO) were measured. Before each visit, ambient PM2.5 samples were daily collected for one week. Sixteen PAHs were determined using Gas Chromatography-Mass Spectrometer, and the positive matrix factorization (PMF) model was applied to identify the sources. Linear mixed-effects models were fitted to investigate the associations between PM2.5-bound PAHs exposure and the biomarkers. Thirteen time-metrics were defined to identify significant time points of PM2.5-bound PAHs' effects. We observed that the increase of PM2.5-bound PAHs exposure was significantly associated with reduced ADAMTS13, elevated D-dimer and MPO. At lag0, each 5.7 ng/m3 increase in Benzo[j]fluoranthene and per 3.4 ng/m3 increase Dibenz[a,h]anthracene could make a maximum change of -19.08 % in ADAMTS13 and 132.60 % in D-dimer. Additionally, per 16.43 ng/m3 increase in Chrysene could lead to a maximum elevation of 32.14 % in MPO at lag4. The PM2.5-bound PAHs often triggered more significant changes at lag 3,4 and 6. The ambient PM2.5-bound PAHs originated from six sources: coal combustion (43.10 %), biomass combustion (20.77 %), diesel emission (14.78 %), gasoline emission (10.95 %), industrial emission (7.58 %), and cooking emission (2.83 %). The greatest contributors to alterations in ADAMTS13, D-dimer and MPO are industrial emission (-48.43 %), biomass combustion (470.32 %) and diesel emission (13.14 %) at lag4. Our findings indicated that short-term exposure to ambient PM2.5-bound PAHs can induce alterations of pro-thrombotic biomarkers among healthy adults.

Association of chromosomal abnormalities with prenatal exposure to heavy metals: A nested case-control study in high-risk pregnant women in China.

Prenatal exposure to heavy metals causes multiple hazards to fetal growth and development. Epidemiological studies on the association between heavy metals and fetal chromosomal abnormalities (CAs) are lacking. We conducted a nested case-control study in a cohort of high-risk pregnant women in China from September 2018 to June 2021. A total of 387 participants were diagnosed with fetal CAs in the case group and 699 were diagnosed with a normal karyotype in the control group. Amniotic fluid concentrations of 10 metals (barium, cobalt, antimony, manganese, ferrum, copper, selenium, strontium, vanadium, and chromium) were measured using inductively coupled plasma-mass spectrometry. We applied quantile g-computation and weighted quantile sum regression to assess the overall effect of metal mixtures and identify metals with significant weight. Logistic and Poisson regression analyses were used to estimate the effects of metals on CAs and CAs subtypes. Our results showed that the metal mixture concentrations were positively associated with the risk of fetal CAs. In adjusted logistic models, Sb was associated with fetal CAs (OR=1.15, 95% CI: 1.02-1.30), and revealed a linear dose-response relationship between Sb level and the risk of fetal CAs. Additionally, the exploratory analysis revealed that Sb levels were associated with Klinefelter syndrome (OR=1.452, 95% CI: 1.063-1.984) and Turner syndrome (OR=1.698; 95% CI,1.048-2.751). Our study revealed that metal mixtures are associated with a higher risk of fetal CAs and that this association may be driven primarily by Sb. Moreover, we provide a genetic perspective on the effects of heavy metals on sexual development in humans.

Individual and joint associations of long-term exposure to air pollutants and cardiopulmonary mortality: a 22-year cohort study in Northern China.

Background: Evidence on the associations between long-term exposure to multiple air pollutants and cardiopulmonary mortality is limited, especially for developing regions with higher pollutant levels. We aimed to characterise the individual and joint (multi-pollutant) associations of long-term exposure to air pollutants with cardiopulmonary mortality, and to identify air pollutant that primarily contributes to the mortality risk. Methods: We followed 37,442 participants with a mean age of 43.5 years in four cities in northern China (Tianjin, Shenyang, Taiyuan, and Rizhao) from January 1998 to December 2019. Annual particulate matter (PM) with diameters ≤2.5 µm (PM2.5), ≤10 µm (PM10), sulfur dioxide (SO2) and nitrogen dioxide (NO2) were estimated using daily average values from satellite-derived machine learning models and monitoring stations. Time-varying Cox proportional hazards model was used to evaluate the individual association between air pollutants and mortality from non-accidental causes, cardiovascular diseases (CVDs), non-malignant respiratory diseases (RDs) and lung cancer, accounting for demographic and socioeconomic factors. Effect modifications by age, sex, income and education level were also examined. Quantile-based g-Computation integrated with time-to-event data was additionally applied to evaluate the co-effects and the relative weight of contributions for air pollutants. Findings: During 785,807 person-years of follow-up, 5812 (15.5%) died from non-accidental causes, among which 2932 (7.8%) were from all CVDs, 479 (1.3%) from non-malignant RDs, and 552 (1.4%) from lung cancer. Long-term exposure to PM10 (mean [baseline]: 136.5 µg/m3), PM2.5 (mean [baseline]: 70.2 µg/m3), SO2 (mean [baseline]: 113.0 µg/m3) and NO2 (mean [baseline]: 39.2 µg/m3) were adversely and consistently associated with all mortality outcomes. A 10 µg/m3 increase in PM2.5 was associated with higher mortality from non-accidental causes (hazard ratio 1.20; 95% confidence interval 1.17-1.23), CVDs (1.23; 1.19-1.28), non-malignant RDs (1.37; 1.25-1.49) and lung cancer (1.14; 1.05-1.23). A monotonically increasing curve with linear or supra-linear shape with no evidence of a threshold was observed for the exposure-response relationship of mortality with individual or joint exposure to air pollutants. PM2.5 consistently contributed most to the elevated mortality risks related to air pollutant mixture, followed by SO2 or PM10. Interpretation: There was a strong and positive association of long-term individual and joint exposure to PM10, PM2.5, SO2, and NO2 with mortalities from non-accidental causes, CVDs, non-malignant RDs and lung cancer in high-exposure settings, with PM2.5 potentially being the main contributor. The shapes of associations were consistent with a linear or supra-linear exposure-response relationship, with no lower threshold observed within the range of concentrations in this study. Funding: National Key Research and Development Program of China, the China Scholarship Council, the National Natural Science Foundation of China, Natural Science Foundation of Guangdong Province.

Effects of PM2.5 and high-fat diet interaction on blood glucose metabolism in adolescent male Wistar rats: A serum metabolomics analysis based on ultra-high performance liquid chromatography/mass spectrometry.

Fine particulate matter (PM2.5) and high-fat diet (HFD) are known to contribute to blood glucose metabolic disorders. However, limited research has investigated the combined impact of PM2.5 and HFD on blood glucose metabolism. This study aimed to explore the joint effects of PM2.5 and HFD on blood glucose metabolism in rats using serum metabolomics and to identify involved metabolites and metabolic pathways. The 32 male Wistar rats were exposed to filtered air (FA) or PM2.5 (real-world inhaled, concentrated PM2.5, 8 times the ambient level, ranging from 131.42 to 773.44 µg/m3) and fed normal diet (ND) or HFD for 8 weeks. The rats were divided into four groups (n = 8/group): ND-FA, ND-PM2.5, HFD-FA and HFD-PM2.5 groups. Blood samples were collected to determine fasting glucose (FBG), plasma insulin and glucose tolerance test and HOMA Insulin Resistance (HOMA-IR) index was calculated. Finally, the serum metabolism of rats was analyzed by ultra-high performance liquid chromatography/mass spectrometry (UHPLC-MS). Then we constructed the partial least squares discriminant analysis (PLS-DA) model to screen the differential metabolites, and performed pathway analysis to screen the main metabolic pathways. Results showed that combined effect of PM2.5 and HFD caused changes in glucose tolerance, increased FBG levels and HOMA-IR in rats and there were interactions between PM2.5 and HFD in FBG and insulin. By metabonomic analysis, the serum differential metabolites pregnenolone and progesterone, which involved in steroid hormone biosynthesis, were two different metabolites in the ND groups. In the HFD groups, the serum differential metabolites were L-tyrosine and phosphorylcholine, which involved in glycerophospholipid metabolism, and phenylalanine, tyrosine, and tryptophan biosynthesis. When PM2.5 and HFD coexist, they may lead to more severe and complex effects on glucose metabolism by affecting lipid metabolism and amino acid metabolism. Therefore, reducing PM2.5 exposure and controlling dietary structure are important measures for preventing and reducing glucose metabolism disorders.

The effect of PM2.5 exposure on the mortality of patients with hepatocellular carcinoma in Tianjin, China.

Several studies have shown the effects of PM2.5 exposure on respiratory and cardiovascular systems. However, there is no cohort study evidence of adverse effects of PM2.5 exposure on survival in patients with hepatocellular carcinoma (HCC) in China. This study is aimed at evaluating this association. This cohort study included 1440 HCC patients treated at the Third Central Clinical College of Tianjin Medical University from September 2013 to December 2018. We collected patient information, including demographic data, medical history, lifestyle characteristics, and disease characteristics. Based on PM2.5 concentrations measured at monitoring stations, the inverse distance weighted (IDW) method was used to assess the individuals' exposure during their survival period. Survival status was analysed by the Kaplan-Meier method. Restricted cubic splines and Cox proportional hazards models were used to estimate the relationship between PM2.5 and mortality, and potential confounders were adjusted for. The mortality rate of HCC patients exposed to PM2.5 ≥ 58.56 µg/m3 was significantly higher than that of HCC patients living in environments with PM2.5 < 58.56 µg/m3 (79.0% vs 50.7%, P < 0.001). The restricted cubic spline model showed a linear relationship between the PM2.5 concentration and mortality risk (P overall-association < 0.0001 and P nonlinear-association = 0.3568). Cox regression analysis showed that after adjusting for confounding factors, for every 10-µg/m3 increase in atmospheric PM2.5, the risk of death for HCC patients increased by 44% [hazard ratio (HR) = 1.44, 95% confidence interval (CI) 1.34, 1.56; P < 0.001]. Compared with patients exposed to PM2.5 <58.56 µg/m3, those exposed to PM2.5 ≥ 58.56 µg/m3 had a 1.55-fold increased risk of death. Stratified analysis results showed that the effects of PM2.5 on HCC mortality were more significant in patients aged ≥60 years or patients living in central urban areas. We found that exposure to elevated PM2.5 after HCC diagnosis may affect survival, with a higher concentration corresponding to a greater effect.

Metabolic biomarkers linking urinary arsenic species to gestational diabetes mellitus: A cross-sectional study in Chinese pregnant women.

Environmental arsenic (As) exposure has been associated with gestational diabetes mellitus (GDM) risk. Our recent study found that GDM was positively associated with urinary As3+ level while negatively correlated to As5+. However, the mechanisms underlying the association between arsenic species and GDM remain largely unknown. In the present study, through the measurement of urinary arsenic species and metabolome analysis in 399 pregnant women, we aimed to identify the metabolic biomarkers that may link arsenic exposure to GDM based on a novel systems epidemiology strategy termed meet-in-metabolite-analysis (MIMA). The metabolomics analysis revealed that 20 and 16 urinary metabolites were relevant to arsenic exposure and GDM, respectively. Among them, 12 metabolites were identified to be both arsenic- and GDM-related, which are mainly involved in purine metabolism, one­carbon metabolism (OCM) and glycometabolism. Moreover, it was further showed that the regulation of thiosulfate (AOR: 2.52; 95 % CI: 1.33, 4.77) and phosphoroselenoic acid (AOR: 2.35; 95 % CI: 1.31, 4.22) could significantly contribute to the negative association between As5+ and GDM. Considering the biological functions of these metabolites, it is suggested that As5+ may reduce GDM risk by disturbing OCM in the pregnant women. These data will provide novel insights into the mechanism of action of environmental arsenic exposure on GDM incidence from the aspect of metabolism disorder.

Perfluoroalkyl substances promote breast cancer progression via ERα and GPER mediated PI3K/Akt and MAPK/Erk signaling pathways.

Perfluoroalkyl substances (PFASs) are a classic environmental endocrine disruptor with carcinogenic risk. Epidemiological studies have shown that PFASs contamination is associated with breast cancer development, but the mechanism remains largely unknown. This study first obtained complex biological information about PFASs-induced breast cancer through the comparative toxicogenomics database (CTD). The Protein-Protein Interaction (PPI) network, Kyoto Encyclopedia of Genes and Genomes (KEGG) and Gene Ontology (GO) analysis were utilized to investigate molecular pathways. The ESR1 and GPER expression levels at different pathological stages and the prognosis of Breast Cancer patients were confirmed using the Cancer Genome Atlas (TCGA) database. Furthermore, we verified this by cellular experiments and the results showed breast cancer cell migration and invasion were promoted by PFOA. Two estrogen receptors (ER), ERα and G protein-coupled estrogen receptor (GPER), mediated the promoting effects of PFOA by activating MAPK/Erk and PI3K/Akt signaling pathways. These pathways were regulated by ERα and GPER in MCF-7 cells or independently by GPER in MDA-MB-231 cells. Overall, our study provides a better overview of the mechanisms associated with PFASs-induced breast cancer development and progression.

Sex-specific effect of perfluoroalkyl substances exposure on liver and thyroid function biomarkers: A mixture approach.

Although studies have investigated the effects of perfluoroalkyl substances (PFASs) on liver and thyroid function, little is known about its combined and sex-specific effect. A total of 688 participants were interviewed and serum PFASs concentration was measured using liquid chromatography/mass spectrometry. Five biomarkers of liver and thyroid function (ALT, GGT, TSH, FT3 and FT4) were chosen as outcomes. A restriction cubic spline function was applied to capture the dose-response relationship between PFASs and liver enzymes and thyroid hormones. Multivariable regression and Bayesian kernel machine regression (BKMR) models were performed to assess the single and overall associations of PFASs with targeted biomarkers. Single-pollutant analyses indicated that increased PFASs concentrations were associated with elevated ALT and GGT levels. BKMR models suggested positive dose-response relationships between PFASs mixtures and ALT and GGT levels. Significant associations were only detected between several PFASs and thyroid hormones, and joint effect of PFASs mixtures on FT3 levels was found at higher concentrations. Meanwhile, sex differences were found in the associations of PFASs with ALT and GGT levels, with significant results only in males. Our findings provide epidemiological evidence for combined and sex-specific effects of PFASs on ALT and GGT levels.

Joint effect of ambient PM2.5 exposure and vitamin B12 during pregnancy on the risk of gestational diabetes mellitus.

BACKGROUND: Evidence has indicated that the risk of gestational diabetes mellitus (GDM) was linked to PM2.5 exposure during pregnancy, but findings on susceptible exposure windows are inconsistent. Further, previous studies have not paid attention to B12 intake in the relationship between PM2.5 exposure and GDM. The study is aimed to identify the strength and exposure periods for associations of PM2.5 exposure with GDM, followed by exploring the potential interplay of gestational B12 levels and PM2.5 exposure on the risk of GDM. METHODS: The participants were recruited in a birth cohort between 2017 and 2018, and 1396 eligible pregnant women who completed a 75-g oral glucose tolerance test (OGTT) were included. Prenatal PM2.5 concentrations were estimated using an established spatiotemporal model. Logistic and linear regression analyses were used to test associations of gestational PM2.5 exposure with GDM and OGTT-glucose levels, respectively. The joint associations of gestational PM2.5 exposure and B12 level on GDM were examined under crossed exposure combinations of PM2.5 (high versus low) and B12 (insufficient versus sufficient). RESULTS: In the 1396 pregnant women, the median levels of PM2.5 exposure during the 12 weeks before pregnancy, the 1st trimester, and the 2nd trimesters were 59.33 µg/m3, 63.44 µg/m3, and 64.39 µg/m3, respectively. The risk of GDM was significantly associated with a 10 µg/m3 increase of PM2.5 during the 2nd trimester (RR = 1.44, 95 % CI: 1.01, 2.04). The percentage change in fasting glucose was also associated with PM2.5 exposure during the 2nd trimester. A higher risk of GDM was observed among women with high PM2.5 exposure and insufficient B12 levels than those with low PM2.5 and sufficient B12. CONCLUSION: The study supported higher PM2.5 exposure during the 2nd trimester is significantly associated with GDM risk. It first highlighted insufficient B12 status might enhance adverse effects of air pollution on GDM.

Impacts of heatwaves and cold spells on glaucoma in rural China: a national cross-sectional study.

China faces increasing health risks from climate change. The structure and function of the eye and vision were affected by extreme heat and cold. The study aimed to evaluate the impacts of heatwaves and cold spells on glaucoma. A national cross-sectional study of the Rural Epidemiology for Glaucoma (REG-China) was conducted in ten provinces of China, and 36,081 adults aged 40 years or more were included. Glaucoma signs were assessed via a standard examination. A total of 15 heatwave definitions, based on intensity (95th to 99th percentiles of temperature distribution) and duration (≥2 days, 3 days, and 4 days), were used to quantify heatwave effects, and 6 cold spell definitions were defined based on threshold temperature percentile (5th and 10th) and duration (3 days, 5 days, and 9 days). Multivariable-adjusted logistic regression models paired with interaction analysis were performed to investigate the impacts of heatwaves and cold spells on glaucoma, and the dose-response relationships were assessed using a restricted cubic spline (RCS) model. Subgroup analysis was conducted stratified by gender, age, smoking status, occupation, and family history of glaucoma. The overall prevalence of glaucoma was 2.1% (95% CI 1.94-2.25%). Higher heatwaves were significantly correlated with higher OR of glaucoma, with the OR (95% CI) ranging from 1.014 (1.009, 1.018) to 1.090 (1.065, 1.115) by different definitions. Glaucoma was affected by heatwaves more strongly than by cold spells. The effects of both heatwaves and cold spells were higher in males than females and in smokers than nonsmokers. These results of the present study evoked the attention of prospective research to elucidate the relationship between extreme temperatures and eye diseases.

Arsenic metabolism, N6AMT1 and AS3MT single nucleotide polymorphisms, and their interaction on gestational diabetes mellitus in Chinese pregnant women.

BACKGROUND: Single nucleotide polymorphisms (SNPs) in N6AMT1 and AS3MT are associated with arsenic (As) metabolism, and efficient As methylation capacity has been associated with diabetes. However, little is known about the gene-As interaction on gestational diabetes mellitus (GDM). OBJECTIVE: This study aimed to explore the individual and combined effects of N6AMT1 and AS3MT SNPs with As metabolism on GDM. METHODS: A cross-sectional study was performed among 385 Chinese pregnant women (86 GDM and 299 Non-GDM). Four SNPs in N6AMT1 (rs1997605 and rs1003671) and AS3MT (rs1046778 and rs11191453) were genotyped. Urinary inorganic arsenic (iAs), monomethylarsonic acid (MMA), and dimethylarsinic acid (DMA) were determined, and the percentages of As species (iAs%, MMA%, and DMA%) were calculated to assess the efficiency of As metabolism. RESULTS: Pregnant women with N6AMT1 rs1997605 AA genotype had lower iAs% (B: 2.11; 95% CI: 4.08, -0.13) and MMA% (B: 0.21; 95% CI: 0.39, -0.04) than pregnant women with GG genotype. The AS3MT rs1046778 and rs11191453 C alleles were negatively associated with iAs% and MMA% but positively associated with DMA%. Higher urinary MMA% was significantly associated with a lower risk of GDM (OR: 0.54; 95% CI: 0.30, 0.97). The A allele in N6AMT1 rs1997605 (OR: 0.46; 95% CI: 0.26, 0.79) was associated with a decreased risk of GDM. The additive interactions between N6AMT1 rs1997605 GG genotypes and lower iAs% (AP: 0.50; 95% CI: 0.01, 0.99) or higher DMA% (AP: 0.52; 95% CI: 0.04, 0.99) were statistically significant. Similar additive interactions were also found between N6AMT1 rs1003671 GG genotypes and lower iAs% or higher DMA%. CONCLUSIONS: Genetic variants in N6AMT1 and efficient As metabolism (indicated by lower iAs% and higher DMA%) can interact to influence GDM occurrence synergistically in Chinese pregnant women.

Early prenatal exposure to air pollutants and congenital heart disease: a nested case-control study.

BACKGROUND: Congenital heart disease (CHD) is one of the most common congenital malformations in humans. Inconsistent results emerged in the existed studies on associations between air pollution and congenital heart disease. The purpose of this study was to evaluate the association of gestational exposure to air pollutants with congenital heart disease, and to explore the critical exposure windows for congenital heart disease. METHODS: The nested case-control study collected birth records and the following health data in Tianjin Women and Children's Health Center, China. All of the cases of congenital heart disease from 2013 to 2015 were selected matching five healthy controls for each case. Inverse distance weighting was used to estimate individual exposure based on daily air pollution data. Furthermore, the conditional logistic regression with distributed lag non-linear model was performed to identify the association between gestational exposure to air pollution and congenital heart disease. RESULTS: A total of 8,748 mother-infant pairs were entered into the analysis, of which 1,458 infants suffered from congenital heart disease. For each 10 µg/m3 increase of gestational exposure to PM2.5, the ORs (95% confidence interval, 95%CI) ranged from 1.008 (1.001-1.016) to 1.013 (1.001-1.024) during the 1st-2nd gestation weeks. Similar weak but increased risks of congenital heart disease were associated with O3 exposure during the 1st week and SO2 exposure during 6th-7th weeks in the first trimester, while no significant findings for other air pollutants. CONCLUSIONS: This study highlighted that gestational exposure to PM2.5, O3, and SO2 had lag effects on congenital heart disease. Our results support potential benefits for pregnancy women to the mitigation of air pollution exposure in the early stage, especially when a critical exposure time window of air pollutants may precede heart development.

Joint effects of meteorological factors and PM2.5 on age-related macular degeneration: a national cross-sectional study in China.

BACKGROUND: Weather conditions are a possible contributing factor to age-related macular degeneration (AMD), a leading cause of irreversible loss of vision. The present study evaluated the joint effects of meteorological factors and fine particulate matter (PM2.5) on AMD. METHODS: Data was extracted from a national cross-sectional survey conducted across 10 provinces in rural China. A total of 36,081 participants aged 40 and older were recruited. AMD was diagnosed clinically by slit-lamp ophthalmoscopy, fundus photography, and spectral domain optical coherence tomography (OCT). Meteorological data were calculated by European Centre for Medium-Range Weather Forecasts (ECMWF) reanalysis and were matched to participants' home addresses by latitude and longitude. Participants' individual PM2.5 exposure concentrations were calculated by a satellite-based model at a 1-km resolution level. Multivariable-adjusted logistic regression models paired with interaction analysis were performed to investigate the joint effects of meteorological factors and PM2.5 on AMD. RESULTS: The prevalence of AMD in the study population was 2.6% (95% CI 2.42-2.76%). The average annual PM2.5 level during the study period was 63.1 ± 15.3 µg/m3. A significant positive association was detected between AMD and PM2.5 level, temperature (T), and relative humidity (RH), in both the independent and the combined effect models. For PM2.5, compared with the lowest quartile, the odds ratios (ORs) with 95% confidence intervals (CIs) across increasing quartiles were 0.828 (0.674,1.018), 1.105 (0.799,1.528), and 2.602 (1.516,4.468). Positive associations were observed between AMD and temperature, with ORs (95% CI) of 1.625 (1.059,2.494), 1.619 (1.026,2.553), and 3.276 (1.841,5.830), across increasing quartiles. In the interaction analysis, the estimated relative excess risk due to interaction (RERI) and the attributable proportion (AP) for combined atmospheric pressure and PM2.5 was 0.864 (0.586,1.141) and 1.180 (0.768,1.592), respectively, indicating a synergistic effect between PM2.5 and atmospheric pressure. CONCLUSIONS: This study is among the first to characterize the coordinated effects of meteorological factors and PM2.5 on AMD. The findings warrant further investigation to elucidate the relationship between ambient environment and AMD.

Breast adipose metabolites mediates the association of tetrabromobisphenol a with breast cancer: A case-control study in Chinese population.

Studies exploring the association of tetrabromobisphenol A (TBBPA) with breast cancer and related mechanisms are limited. To investigate the relationship between TBBPA levels in breast adipose and breast cancer, we carried out case-control research. As well as further examine the mediating role of adipose metabolites between TBBPA and breast cancer using the metabolomics approach. In this study, the concentration of TBBPA was determined utilizing ultra-performance liquid chromatography tandem mass spectrometry (UPLC-MS/MS) after a solid phase extraction (SPE) pretreatment. High-performance liquid chromatography tandem mass spectrometry (HPLC-MS/MS) was employed to analyze adipose metabolomics. Evaluation of metabolites linked to TBBPA exposure and breast cancer was performed utilizing mediation analysis. With an estimated OR (95%CI) of 1.153 (1.023, 1.299), TBBPA was firmly linked with breast cancer. We also used propensity score matching analysis and sensitivity analysis to reduce the effect of confounding factors on the results. Metabolomics of adipose suggested significant perturbation in the linoleic acid metabolism pathway. In addition, for PC (16:0/16:0) as phospholipids, a mediation effect on the associations of TBBPA exposure with breast cancer risks was observed (estimated mediation percentage: 56.58%). Understanding the relationship between TBBPA exposure and the risk of breast cancer may be facilitated by the findings, which point to potential mediation metabolites.

Glaucoma in rural China (the Rural Epidemiology for Glaucoma in China (REG-China)): a national cross-sectional study.

OBJECTIVE: This study aimed to investigate the prevalence of glaucoma with associated factors in the rural populations of 10 provinces in China. DESIGN: A population-based cross-sectional study. METHODS: All participants aged 6 years or older from 10 provinces completed visual acuity testing, slit-lamp examination, ophthalmoscopy and non-contact tonometry. Glaucoma suspects underwent fundus photography, Goldmann applanation tonometry, visual field testing and gonioscopy. Glaucoma was determined according to the International Society of Geographical and Epidemiological Ophthalmology classification scheme. Associations of demographics and medical factors with glaucoma were assessed using multiple logistic regression models. RESULTS: From June 2017 to October 2018, 48 398 of 52 041 participants were included in the final analyses. The age-standardised prevalence of glaucoma was 1.7% (95% CI 1.55% to 1.78%) among the participants older than 6 years, which was 2.1% (95% CI 1.93% to 2.23%) in participants aged over 40 years. The constituent ratios of glaucoma were: 44.4% primary angle-closure glaucoma (PACG), 34.7% primary open-angle glaucoma, 2.6% congenital glaucoma and 18.3% other types of glaucoma. Increasing age, smoking, cerebral stroke, type 2 diabetes, higher education (college or more) and higher personal income were significant risk factors for PACG. The unilateral and bilateral blindness rates in the entire study population were 4.692% and 1.068%, respectively. A family history of glaucoma was a significant risk factor for the prevalence of glaucoma and blindness in at least one eye. CONCLUSIONS: Rural populations have a high prevalence of glaucoma, which should be included in chronic disease management programmes in China for long-term care.

Association between exposure to perfluoroalkyl substances and uric acid in Chinese adults.

BACKGROUND: A growing body of evidence suggests the deleterious effects of perfluoroalkyl substances (PFASs) on kidney, but little is known on the association between PFASs joint exposure and uric acid. METHODS: Serum PFASs concentrations were measured in 661 participants recruited from Tianjin, China using liquid chromatography/mass spectrometry. The associations of single PFASs exposure with uric acid levels and hyperuricemia were assessed using multivariable linear and logistic regression models, respectively. Restricted cubic spline models were established to investigate the dose-response relationships between PFASs concentrations and uric acid levels. Bayesian Kernel Machine Regression (BKMR) model with a hierarchical variable selection was performed to assess the joint effect of PFASs on uric acid. RESULTS: Potassium perfluoro-1-octanesulfonate (PFOS) and perfluoro-n-octanoic acid (PFOA) were the dominated contributors with median concentrations of 16.80 ng/ml and 9.42 ng/ml, respectively. Increased PFOA concentration (per log2-unit) was associated with elevated uric acid level (ß = 0.088, 95% CI: 0.033-0.143) and higher risk of hyperuricemia (OR = 1.134, 95% CI: 1.006-1.289). Conversely, the estimated change of uric acid associated with log2-unit increment in perfluoro-n-decanoic acid (PFDA) was -0.081 mg/dL (95% CI: -0.154, -0.009). A significant linear dose-response pattern was found between log2-transformed PFOA concentration and uric acid level. BKMR analyses indicated a non-significant overall effect of PFASs mixture on uric acid. CONCLUSIONS: Significant associations between PFOA and PFDA and uric acid, and between PFOA and hyperuricemia were found in the single-pollutant models, but the joint effect of PFASs mixture on uric acid was not observed in the BKMR model, which provided new insights in regulation policies and risk assessment of PFASs.

Shift work and nonalcoholic fatty liver disease incidence among Chinese rail workers: a 4-year longitudinal cohort study.

PURPOSE: Occupational harmful factors, such as shift work, are attracting increasing attention as a potential cause of nonalcoholic fatty liver disease (NAFLD). In this study, we aimed to identify the association between shift work and NAFLD incidence in Chinese rail population. METHODS: A cohort study was conducted among 14,112 rail workers for 4-year follow-up. Shift work frequency and other potential variables were recorded by questionnaires, including demographic, lifestyle, and occupation information. Besides, body mass index, blood pressure, fasting blood glucose, total cholesterol, triglyceride, alanine aminotransferase, and aspartate aminotransferase were measured by anthropometric measurement and blood test. Diagnosis of new NAFLD case was based on abdominal ultrasonography. Cox proportional hazards regression model was used to determine whether shift work has effect on occurrence of NAFLD. RESULTS: The incidence of NAFLD was 30.43% in total subjects. After adjustment for possible confounders, the RRs of NAFLD were 1.069 (95% CI 0.998-1.146) and 1.179 (95% CI 1.059-1.312) in occasionally shift work group and frequently shift work group respectively, compared to the seldom shift work group. In stratified analyses, the RRs of NAFLD incidence linked to shift work exposure seems increase among female and elder. The results of three sensitivity analyses were similar with main analysis. CONCLUSIONS: This research provided further evidence of positive harmful effect of shift work on NAFLD incidence in Chinese rail workers, particularly in frequently shift work population. The risk estimate of shift work on NAFLD was higher in female and elder.

Long-term PM2.5 exposure in association with chronic respiratory diseases morbidity: A cohort study in Northern China.

Several literatures have examined the risk of chronic respiratory diseases in association with short-term ambient PM2.5 exposure in China. However, little evidence has examined the chronic impacts of PM2.5 exposure on morbidity of chronic respiratory diseases in cohorts from high pollution countries. Our study aims to investigate the associations. Based on a retrospective cohort among adults in northern China, a Cox regression model with time-varying PM2.5 exposure and a concentration-response (C-R) curve model were performed to access the relationships between incidence of chronic respiratory diseases and long-term PM2.5 exposure during a mean follow-up time of 9.8 years. Individual annual average PM2.5 estimates were obtained from a satellite-based model with high resolution. The incident date of a chronic respiratory disease was identified according to self-reported physician diagnosis time and/or intake of medication for treatment. Among 38,047 urban subjects analyzed in all-cause chronic respiratory disease cohort, 482 developed new cases. In CB (38,369), asthma (38,783), and COPD (38,921) cohorts, the onsets were 276, 89, and 14, respectively. After multivariable adjustment, hazard ratio and 95% confidence interval for morbidity of all-cause chronic respiratory disease, CB, asthma, and COPD were 1.15 (1.01, 1.31), 1.20 (1.00, 1.42), 0.76 (0.55, 1.04), and 0.66 (0.29, 1.47) with each 10 µg/m3 increment in PM2.5, respectively. Stronger effect estimates were suggested in alcohol drinkers across stratified analyses. Additionally, the shape of C-R curve showed an increasing linear relationship before 75.00 µg/m3 concentrations of PM2.5 for new-onset all-cause chronic respiratory disease, and leveled off at higher levels. These findings indicated that long-term exposure to high-level PM2.5 increased the risks of incident chronic respiratory diseases in China. Further evidence of C-R curves is warranted to clarify the associations of adverse chronic respiratory outcomes involving air pollution.