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Background: The concept “one airway, one disease” for childhood rhinitis and asthma has been challenged in recent years. This study aimed to evaluate associations of environmental exposures with alone and co-morbid symptoms of rhinitis and asthma and identify critical risk factor. Methods: 5828 children aged 3–6 years in Shanghai were surveyed in 2019. Rhinitis and wheezing symptoms in the past 12 months were collected using questionnaire. 11 outdoor environment exposure factors were assessed by high-resolution spatial-temporal model based on residences. Logistic regression and random forest were applied to evaluate and rank the association of environmental exposure with rhinitis and wheezing symptoms. Results: The proportions of children with rhinitis alone, wheezing & rhinitis, and wheezing alone were 37.2 %, 4.6 %, and 2.6 %, respectively. Regression modeling of two exposure factors adjusted for each other showed that PM1, PM2.5 and nighttime light(NTL) remained the robust significant associations with rhinitis alone, whereas NO2 had the robust significant association with wheezing & rhinitis and wheezing alone. Random forest ranking analysis further corroborated the most significant environmental exposure for rhinitis alone was PM1, and for wheezing symptoms (both wheezing & rhinitis and wheezing alone) was NO2. Significant additive and multiplicative interactions were examined between indoor dampness and PM1 exposure on rhinitis alone. Conclusion: Children’s current rhinitis alone was more susceptible to ambient PM1 and PM2.5, while asthmatic wheezing symptom, either with or without rhinitis, was more susceptible to NO2. Co-exposure to indoor dampness and PM1 exposure had synergistic effects on rhinitis alone.

Background: Previous studies indicated that exposure to VOCs was linked to increased systemic inflammation levels. However, the dose-response relationships between urine VOCs metabolites and systemic inflammation have not been established, and the key metabolite of the toxic compounds has not been identified. Methods: We used data in 7007 US adults in the NHANES cycles (2011–2018) across 8 years. Urinary VOC metabolites were measured using ultra-performance liquid chromatography and electrospray tandem mass spectrometry (UPLC-ESI/MSMS). VOC metabolites were adjusted by urinary creatinine level before analysis. Systemic inflammation was assessed by systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) indices. Generalized linear models, restricted cubic splines (RCS), and weighted quantile sum (WQS) regression were applied to evaluate the associations, exposure-response (E-R) curve and identify the key contributor compound, adjusting for gender, age, race, BMI, marital condition, education level, smoking level, alcohol consumption and physical activity. Smoking status was assessed as an effect modifier. Results: Significant and robust positive correlations were found between 8 VOC metabolites and both SII and SIRI. They were N-Acetyl-S-(2-carboxyethyl)-L-cysteine (CEMA), N-Acetyl-S-(2-cyanoethyl)-L-cysteine (CYMA), N-Acetyl-S-(3,4-dihydroxybutyl)-L-cysteine (DHBMA), N-Acetyl-S-(3-hydroxypropyl)-L-cysteine (3HPMA), mandelic acid (MA), N-Acetyl-S-(4-hydroxy-2-butenyl)-L-cysteine (MHBMA3), phenylglyoxylic acid (PGA), and N-Acetyl-S-(3-hydroxypropyl-1-methyl)-L-cysteine (HPMMA). The RCS curves showed J-shaped or exponential shaped E-R relationships for most VOC metabolites. WQS regression found that exposure to the mixture of VOC metabolites was related to increased systemic inflammation, and MA was the key VOC metabolite contributing most to systemic inflammation levels. Smokers exhibited higher levels of urinary VOCs and larger susceptibility to VOC-related increases in SII and SIRI compared to non-smokers. Conclusion: This study demonstrated a strong link between urinary VOC metabolites and increased systemic inflammation, and smokers were more susceptible. Our findings highlighted the significance of reducing VOC exposure to mitigate the inflammation levels, particularly for smokers.

Background: Previous studies found that urinary phthalates (PAEs) metabolites may be associated with increased serum uric acid concentration and hyperuricemia risk. However, no population-based study has investigated the underlying biological mechanisms. Methods: This nationwide cross-sectional study analyzed the data from the National Health and Nutrition Examination Survey (NHANES) 2003–2018. Urinary PAEs metabolites were measured and 8 PAEs metabolites (MCPP, MECPP, MEHHP, MEOHP, MBzP, MiBP, MBP, and MEP) were incorporated into the analysis. Serum uric acid was determined and hyperuricemia cases were identified. Multi-variable generalized linear model, exposure-response (E-R) function and weighted quantile sum (WQS) regression were utilized to investigate the relationships of PAEs metabolites with serum uric acid concentration and hyperuricemia risk. Systemic immune inflammation (SII) was assessed using the SII index and its mediation effects were explored using causal mediation effect model. Results: Data from 10,633 US adults in the NHANES 2003–2018 was analyzed. Except for MEP, individual PAEs metabolite and total PAEs metabolites were associated with increased serum uric acid concentration and hyperuricemia risk. E-R function of PAEs metabolites with serum uric acid concentration and the risk of hyperuricemia showed significantly positive associations with most curves in a nearly linear relationship. WQS regression showed that the mixture of PAEs metabolites was related to elevated serum uric acid and hyperuricemia risk, and MBzP was identified as the most contributing PAEs metabolite. The causal mediation effect model found that SII significantly mediated the relationships of PAEs metabolites with serum uric acid and hyperuricemia risk. Conclusion: Individual and mixture of urinary PAEs metabolites were associated with increased serum uric acid concentration and the risk of hyperuricemia. MBzP exhibited the highest contribution to the overall effects. SII alteration may be an important biological mechanism underlining the impact of PAEs metabolites on serum uric acid concentration and hyperuricemia risk.

Background: The associations between long-term exposure to ozone (O3) and respiratory diseases are well established. However, its association with cardiovascular disease (CVD) remains controversial. In this study, we examined the associations between O3 and the prevalence of hypertension and blood pressure, and the mediation effects of body mass index (BMI) in Chinese middle-aged and older adults. Methods: In this national cross-sectional study, we estimated the O3 exposure of 12,028 middle-aged and older adults from 126 county-level cities in China, using satellite-based spatiotemporal models. Generalized linear mixed models were used to evaluate the associations of long-term exposure to O3 with hypertension and blood pressure, including systolic blood pressure (SBP), diastolic blood pressure (DBP), mean arterial pressure (MAP), and pulse pressure (PP). Mediation effect models were applied to examine the mediation effects of BMI among O3-induced hypertension and elevated blood pressure. Results: Each 10 μg/m3 increase in O3 concentration was significantly associated with an increase of 13.7% (95% confidence interval (CI): 4.8%, 23.3%) in the prevalence of hypertension, an increase of 1.128 mmHg (95% CI: 0.248, 2.005), 0.679 mmHg (95% CI: 0.059, 1.298), 0.820 mmHg (95%CI: 0.245, 1.358) in SBP, DBP, and MAP, respectively. Mediation effect models showed that BMI played 40.08%, 37.25%, 39.95%, and 33.51% mediation roles in the effects of long-term exposure to O3 on hypertension, SBP, DBP, and MAP, respectively. Conclusions: Long-term exposure to O3 can increase the prevalence of hypertension and blood pressure levels of middle-aged and older adults, and an increase of BMI would be an important modification effect for O3-induced hypertension and blood pressure increase.