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To evaluate the effects of CREB1 gene polymorphisms and long-term exposure to fluoride on thyroid function of children.A total of 424 children (including 226 boys and 198 girls) aged 7-12 years old were enrolled in Kaifeng, China by cross-sectional study in 2017. The concentrations of urinary fluoride (UF) and creatinine (UCr) were measured using fluoride ion-selective electrode assay and creatinine assay kit (picric acid method), respectively. The concentration of UCr-adjusted UF (CUF) was calculated. Children were divided into high fluoride exposure group (HFG, CUF1.41 mg/L) and low fluoride exposure group (LFG, CUF ≤1.41 mg/L) according to the median concentration of CUF (1.41 mg/L). The serum thyroid-stimulating hormone (TSH), total triiodothyronine (TT3) and total thyronine (TT4) levels were detected by the radiation immunoassay. The B-mode ultrasound was performed to test the thyroid volume (Tvol). Genotyping of CREB1 gene was conducted by a custom-by-design 48-plex SNPscan™ Kit. Associations between CUF concentration, CREB1 single nucleotide polymorphisms (SNPs) and thyroid function were assessed by multiple linear regression models.Negative and positive associations between serum TT4 level (β = -0.721, 95%CI: -1.209, -0.234) and Tvol (β = 0.031, 95%CI: 0.011, 0.050) and CUF concentration were observed respectively. Children carrying CREB1 rs11904814 TG and rs2254137 AC genotypes had lower TT3 levels (P 0.05). Children in HFG carrying rs11904814 TT, rs2253206 GG genotypes and rs6740584 C allele easily manifested lower serum TT4 levels (P 0.05). Moreover, interactions between excessive fluoride exposure and CREB1 SNPs on Tvol were observed, and the interaction among different loci of CREB1 gene could modify serum TT3 level (P 0.05, respectively).Fluoride could alter children's serum TT4 levels and Tvol. Interactions between fluoride exposure and CREB1 polymorphisms may modify thyroid volume of children.

Due to the poor living and healthcare conditions, preterm birth (PTB) in rural population is a pressing health issue. However, PTB studies in rural population are rare. To explore the effects of air pollutants on PTB in rural population, we collected 697,316 medical records during 2014–2016 based on the National Free Preconception Health Examination Project. Logistic regression models were used to estimate the association between air pollutants and PTB and the modifying effects of demographic characteristics. Relative contribution and principal component analysis-generalized linear model (PCA-GLM) analysis were used to explore the most significant air pollutant and gestational period. Our results demonstrated that PTB risk is positively associated with exposure to air pollutants including PM10, PM2.5, SO2, NO2, and CO, while negatively associated with O3 exposure (P