ABSTRACT
Background Previous research indicated that isomers and alternatives of per- and polyfluoroalkyl substances (PFAS) probably disturb glucose metabolism; however, current epidemiological evidence on the associations of PFAS with fasting blood glucose is inconsistent. Besides, studies on the joint association of multiple components of PFAS and fasting blood glucose as well as the key component are scarce. Objective To evaluate the associations of PFAS isomers and alternatives with fasting blood glucose and their joint effects, as well as identify the key component among population without glucose metabolism problems. Methods We selected 923 adults without glucose metabolism problems or missing data from the Isomers of C8 Health Project in China (2015—2016). Serum PFAS isomers and alternatives and fasting blood glucose were measured using ultra-performance liquid chromatography coupled with tandem mass spectrometry (UPLC-MS/MS) and automatic biochemical analyzer. We applied multiple linear regression to explore the associations of 16 pollutants which were detected among over 80% participants with fasting blood glucose. Meanwhile, we utilized qgcomp and Bayesian kernel machine regression (BKMR) models to explore the joint effects of PFAS isomers and alternatives mixture on target outcome indicators and identify the key component. Results The average age among the 923 participants in this study was (62.4±13.8) years old, including 472 men (51.1%) and 451 women (48.9%). Among selected PFAS isomers and alternatives, the highest serum concentration was ∑3+4+5m-PFOS (perfluoro-3/4/5-methylheptanesulfonate) with a median concentration of 10.20 ng·mL−1. The concentrations of linear perfluorooctane sulfonate (n-PFOS, 9.61 ng·mL−1), perfluorooctanoic acid (PFOA, 4.55 ng·mL−1), linear perfluorohexane sulfonic acid (n-PFHxS, 2.48 ng·mL−1), 6:2 chlorinated polyfluorinated ethersulfonic acid (6:2 Cl-PFESA, 1.90 ng·mL−1), perfluoro-6-methylheptanesulfonate (iso-PFOS, 1.85 ng·mL−1), perfluorobutanoic acid (PFBA, 1.81 ng·mL−1), perfluorinated n-nonanoic acid (PFNA, 1.39 ng·mL−1), and perfluoro-1-methylheptanesulfonate (1m-PFOS, 1.27 ng·mL−1) were higher than 1.00 ng·mL−1. After being adjusted for selected confounders, PFAS isomers and alternatives were positively associated with fasting blood glucose. With 1 ln unit concentration increment of 6:2 Cl-PFESA and PFNA, the estimated changes of fasting blood glucose were 0.18 (95%CI: 0.13, 0.23) mmol·L−1 and 0.24 (95%CI: 0.18, 0.30) mmol·L−1, respectively. The multi-pollutant models indicated a joint association of PFAS isomers and alternatives mixture with fasting blood glucose. The BKMR models reveals that as the quantiles of mixture elevated from the 50th to the 75th percentile, the values of fasting blood glucose increased 0.25 (95%CI: 0.21, 0.30) mmol·L−1, and the posterior inclusion probability of PFNA was 0.92, implying that PFNA was the key component. Conclusion PFAS isomers and alternatives are positively associated with fasting blood glucose. PFNA is the key component of the joint association.
ABSTRACT
Background Studies on the association between greenness exposure and allergic rhinitis (AR) in children are mostly conducted in developed countries, and the conclusion is not consistent. Objective Using street view data to explore the association between greenness exposure and allergic rhinitis (AR) prevalence in Chinese children. Methods A cross-sectional study was conducted among 40868 children aged 2-17 years in three cities of Northeast China from 2012 to 2013, which consisted of 20886 (51.1%) boys and 19982 (48.9%) girls. The information of AR prevalence was obtained through questionnaire. Based on downloaded street view images from Tencent Maps, a green view index (GVI) of green vegetation (trees and grass) within 800 m and 1000 m buffer of the participants' schools was calculated by using artificial intelligence, and it was used as a surrogate of the greenness exposure. A mixed-effect logistic regression model was used to estimate the odds ratio (OR) of AR prevalence in children for per increase of inter-quartile range (IQR) of GVI. In addition, according to ambient PM2.5 concentration, the participants were divided into a low PM2.5 exposure group (≤56.23 μg·m−3) and a high exposure group (>56.23 μg·m−3) to investigate whether PM2.5 was a modifier on the association between GVI and AR. Results The average age of the subjects was (10.40±3.68) years and 3 963 (9.7%) subjects reported diagnosed AR. Within 800 m buffer, an IQR increase in GVI for trees (IQR=0.031, OR=0.85, 95%CI: 0.81-0.90) and overall greenness (IQR=0.029, OR=0.86, 95%CI: 0.81-0.90) was associated with lower adjusted odds ratio of AR. The interaction between PM2.5 and GVI was statistically significant (P< 0.1), that is, the negative associations of trees and overall greenness with AR were observed only at low PM2.5 exposure levels. The sensitivity analysis results of GVI within 1000 m buffer was consistent with that within 800 m buffer. Conclusion Exposure to green vegetation, especially trees, may be associated with decreased risks of AR in children, and such associations may be more obvious in areas with a low PM2.5 concentration.