Association of environmental pollutants with asthma and allergy, and the mediating role of oxidative stress and immune markers in adolescents

Asthma and allergic diseases are among the common causes of morbidity and mortality globally. Various environmental pollutants are linked to the development of asthma and allergic diseases. Evidence on the role of oxidative stress and immune markers in the association of environmental pollutants wit...

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Veröffentlicht in:Environmental research 2025-01, Vol.265, p.120445, Article 120445
Hauptverfasser: Hassen, Hamid Y., Govarts, Eva, Remy, Sylvie, Cox, Bianca, Iszatt, Nina, Portengen, Lützen, Covaci, Adrian, Schoeters, Greet, Den Hond, Elly, Henauw, Stefaan De, Bruckers, Liesbeth, Koppen, Gudrun, Verheyen, Veerle J.
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Sprache:eng
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Zusammenfassung:Asthma and allergic diseases are among the common causes of morbidity and mortality globally. Various environmental pollutants are linked to the development of asthma and allergic diseases. Evidence on the role of oxidative stress and immune markers in the association of environmental pollutants with asthma and allergy is scant. We examined cross-sectional associations between environmental pollutants and asthma and allergy, investigated mixture effects and possible mediation by oxidative stress or immune markers. We used data from the Flemish Environment and Health Study 2016–2020 (FLEHS IV), including 409 adolescents aged 13–16 years. Fifty-four pollutants, including metals, phthalates, Di(isononyl) cyclohexane-1,2-dicarboxylate (DINCH), bisphenols, currently used and legacy pesticides, flame retardants, per- and polyfluoroalkyl substances (PFAS), polyaromatic hydrocarbons (PAHs), and polychlorinated biphenyls (PCBs) were analyzed. Outcomes were self-reported asthma, rhinitis, eczema, allergies, respiratory infection, and airway inflammation, measured through fractional exhaled nitric oxide (FeNO). Single pollutant models using multiple regression analysis and multipollutant models using Bayesian Kernel Machine Regression (BKMR) were fitted. As sensitivity analysis, Bayesian model averaging (BMA) and elastic net (ENET) models were also performed. For Bayesian models, posterior inclusion probabilities (PIP) were used to identify the most important chemicals. Mediation analysis was performed to investigate the role of oxidative stress, measured by urinary 8-hydroxy-2' -deoxyguanosine (8-OHdG), and immune markers (eosinophils, basophils, InterLeukin 8, InterLeukin 6, and Interferon-ᵧ in blood). In single pollutant models, FeNO was significantly higher by 20% (95% CI: 6, 36%) and 13% (95% CI: 2, 25%) per interquartile range (IQR) fold in mono-n-butyl phthalate (MnBP) and mono-benzyl phthalate (MBzP), respectively. In BKMR analysis, the group PIPs indicated phthalates and DINCH as the most important group (group PIP = 0.509), with MnBP being the most important pollutant within that group (conditional PIP = 0.564; %change = 28%; 95%CI: 6, 54%). Similar patterns were observed in all multipollutant models. Eosinophil count mediated 37.8% (p = 0.018) and 27.9% (p = 0.045) of the association between MBzP and FeNO, and the association between MnBP and FeNO, respectively. 8-OHdG plays a significant mediating role in the association of 2,4-Dichlorophenoxyacetic acid
ISSN:0013-9351
1096-0953
1096-0953
DOI:10.1016/j.envres.2024.120445