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We aimed to investigate the association between air pollution and advanced fibrosis among patients with metabolic associated fatty liver disease (MAFLD) and chronic hepatitis B virus (HBV) and hepatitis C virus (HCV) infections. A total of 1376 participants who were seropositive for HBV surface antigen (HBsAg) or antibodies to HCV (anti‐HCV) or had abnormal liver function in a community screening program from 2019 to 2021 were enrolled for the assessment of liver fibrosis using transient elastography. Daily estimates of air pollutants (particulate matter ≤2.5 μm in diameter [PM2.5], nitrogen dioxide [NO2], ozone [O3] and benzene) were aggregated into mean estimates for the previous year based on the date of enrolment. Of the 1376 participants, 767 (52.8%) and 187 (13.6) had MAFLD and advanced fibrosis, respectively. A logistic regression analysis revealed that the factors associated with advanced liver fibrosis were HCV viremia (odds ratio [OR], 3.13; 95% confidence interval [CI], 2.05–4.77; p < 0.001), smoking (OR, 1.79; 95% CI, 1.16–2.74; p = 0.01), age (OR, 1.04; 95% CI, 1.02–1.05; p < 0.001) and PM2.5 (OR, 1.10; 95% CI, 1.05–1.16; p < 0.001). Linear regression analysis revealed that LSM was independently correlated with PM2.5 (β: 0.134; 95% CI: 0.025, 0.243; p = 0.02). There was a dose‐dependent relationship between different fibrotic stages and the PM2.5 level (the PM2.5 level in patients with fibrotic stages 0, 1–2 and 3–4: 27.9, 28.4, and 29.3 μg/m3, respectively; trend p < 0.001). Exposure to PM2.5, as well as HBV and HCV infections, is associated with advanced liver fibrosis in patients with MAFLD. There was a dose‐dependent correlation between PM2.5 levels and the severity of hepatic fibrosis. [ABSTRACT FROM AUTHOR]

Background: Air pollution is a risk factor for hepatocellular carcinoma (HCC). However, the effect of air pollution on HCC risk in patients with hepatitis remains unclear., Methods: This cross-sectional study recruited 348 patients with chronic hepatitis who were tested for serum hepatitis B surface antigen (HBsAg) and for antibodies against hepatitis B core antigen (HBcIgG) and hepatitis C virus (anti-HCV) in 2022. The diagnosis of HCC was based on the International Classification of Diseases, 10th revision (ICD-10). Daily estimates of air pollutants were aggregated into mean estimates for the previous year based on the date of recruitment or HCC diagnosis., Results: Out of 348 patients, 12 had HCC (3.4%). Patients with HCC were older (71.7 vs 50.9 years; p = 0.004), had higher proportion of HBsAg seropositivity (41.7% vs 5.1%; p < 0.001), and substantially higher levels of particulate matter 2.5 (PM 2.5 ) (21.5 vs 18.2 μg/m 3 ; p = 0.05). Logistic regression analysis revealed that the factors associated with HCC were age (odds ratio [OR]: 1.10; CI, 1.03-1.17; p = 0.01), PM 2.5 level (OR: 1.51; CI, 1.02-2.23; p = 0.04), and HBsAg seropositivity (OR: 6.60; CI, 1.51-28.85; p = 0.01) ( Table 3 ). There was a combined effect of PM 2.5 and HBsAg seropositivity on the risk of HCC development (OR: 22.17; CI, 3.33-147.45; p = 0.001)., Conclusion: In this study, we demonstrated that PM 2.5 and HBsAg seropositivity were associated with HCC occurrence and had synergistic effects after adjusting for confounding factors., Competing Interests: Conflicts of interest: The authors declare that they have no conflicts of interest related to the subject matter or materials discussed in this article., (Copyright © 2024, the Chinese Medical Association.)

Biochemical response is an important prognostic indicator in chronic hepatitis B (CHB) patients receiving nucleotide/nucleoside analogues (NAs). However, the effects of air pollution in alanine aminotransferase (ALT) normalization remain elusive. This longitudinal study recruited 80 hepatitis B e antigen-negative CHB patients who received NAs. ALT levels were measured during the first year of anti-hepatitis B virus therapy. Normal ALT levels were defined as <19 U/L for females and <30 U/L for males, and the risk factors associated with ALT abnormalities were analyzed. The daily estimations of air pollutants (particulate matter ≤2.5 µm in diameter (PM2.5), nitrogen dioxide, ozone (O3), and benzene) were aggregated into the mean estimation for the previous month based on the date of recruitment (baseline) and 1 year later. Sixteen patients (20.0%) had a baseline ALT > 40 U/L; overall, 41 (51.6%) had an abnormal ALT (≥19 U/L for females and ≥ 30 U/L for males). After 1 year of NA therapy, 75 patients (93.8%) had undetectable hepatitis B virus DNA levels. Mean post-treatment ALT levels were significantly lower than mean pretreatment levels (21.3 vs 30.0 U/L, respectively; P < .001). The proportion of patients with a normal ALT was also significantly higher after versus before treatment (71.2% vs 51.2%, respectively; P = .001). The strongest factors associated with ALT abnormality after 1 year of NA treatment were body mass index (odds ratio [OR], 1.28; 95% confidence interval [CI], 1.05-1.54; P = .01) and ozone level (OR, 1.11; 95% CI, 1.02-1.22; P = .02). Among hepatitis B e antigen-negative CHB patients with relatively low viral loads, 1 year of NA treatment improved ALT levels after the adjustment for confounding factors and increased the proportion of patients with normal ALT levels. Air pollution affects the efficacy of ALT normalization., Competing Interests: The authors have no funding and conflicts of interest to disclose., (Copyright © 2023 the Author(s). Published by Wolters Kluwer Health, Inc.)

A widespread monitoring network of Airbox microsensors was implemented since 2016 to provide high-resolution spatial distributions of ground-level PM 2.5 data in Taiwan. We developed models for estimating ground-level PM 2.5 concentrations for all the 3 km × 3 km grids in Taiwan by combining the data from air quality monitoring stations and the Airbox sensors. The PM 2.5 data from the Airbox sensors (AB-PM 2.5 ) was used to predict daily mean PM 2.5 levels at the grids in 2017 using a semiparametric additive model. The estimated PM 2.5 level at the grids was further applied as a predictor variable in the models to predict the monthly mean concentration of PM 2.5 at all the grids in the previous year. The modeling-predicting procedures were repeated backward for the years from 2016 to 2006. The model results revealed that the model R 2 increased from 0.40 to 0.87 when the AB-PM 2.5 data were included as a nonlinear component in the model, indicating that AB-PM 2.5 is a significant predictor of ground-level PM 2.5 concentration. The cross-validation (CV) results demonstrated that the root of mean squared prediction errors of the estimated monthly mean PM 2.5 concentrations were smaller than 5 μg/m 3 and the R 2 of the CV models of 0.79-0.88 during 2006-2017. We concluded that Airbox sensors can be used with monitoring data to more accurately estimate long-term exposure to PM 2.5 for cohorts of small areas in health impact assessment studies., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2020 Elsevier Ltd. All rights reserved.)