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Long-term exposure to a mixture of industrial SO(2), NO(2), and PM(2.5) and anti-citrullinated protein antibody positivity

BACKGROUND: Studies of associations between industrial air emissions and rheumatic diseases, or diseases-related serological biomarkers, are few. Moreover, previous evaluations typically studied individual (not mixed) emissions. We investigated associations between individual and combined exposures...

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Detalles Bibliográficos
Autores principales: Zhao, Naizhuo, Smargiassi, Audrey, Hatzopoulou, Marianne, Colmegna, Ines, Hudson, Marie, Fritzler, Marvin J., Awadalla, Philip, Bernatsky, Sasha
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7391811/
https://www.ncbi.nlm.nih.gov/pubmed/32727483
http://dx.doi.org/10.1186/s12940-020-00637-3
Descripción
Sumario:BACKGROUND: Studies of associations between industrial air emissions and rheumatic diseases, or diseases-related serological biomarkers, are few. Moreover, previous evaluations typically studied individual (not mixed) emissions. We investigated associations between individual and combined exposures to industrial sulfur dioxide (SO(2)), nitrogen dioxide (NO(2)), and fine particles matter (PM(2.5)) on anti-citrullinated protein antibodies (ACPA), a characteristic biomarker for rheumatoid arthritis (RA). METHODS: Serum ACPA was determined for 7600 randomly selected CARTaGENE general population subjects in Quebec, Canada. Industrial SO(2), NO(2), and PM(2.5) concentrations, estimated by the California Puff (CALPUFF) atmospheric dispersion model, were assigned based on residential postal codes at the time of sera collection. Single-exposure logistic regressions were performed for ACPA positivity defined by 20 U/ml, 40 U/ml, and 60 U/ml thresholds, adjusting for age, sex, French Canadian origin, smoking, and family income. Associations between regional overall PM(2.5) exposure and ACPA positivity were also investigated. The associations between the combined three industrial exposures and the ACPA positivity were assessed by weighted quantile sum (WQS) regressions. RESULTS: Significant associations between individual industrial exposures and ACPA positivity defined by the 20 U/ml threshold were seen with single-exposure logistic regression models, for industrial emissions of PM(2.5) (odds ratio, OR = 1.19, 95% confidence intervals, CI: 1.04–1.36) and SO(2) (OR = 1.03, 95% CI: 1.00–1.06), without clear associations for NO(2) (OR = 1.01, 95% CI: 0.86–1.17). Similar findings were seen for the 40 U/ml threshold, although at 60 U/ml, the results were very imprecise. The WQS model demonstrated a positive relationship between combined industrial exposures and ACPA positivity (OR = 1.36, 95% CI: 1.10–1.69 at 20 U/ml) and suggested that industrial PM(2.5) may have a closer association with ACPA positivity than the other exposures. Again, similar findings were seen with the 40 U/ml threshold, though 60 U/ml results were imprecise. No clear association between ACPA and regional overall PM(2.5) exposure was seen. CONCLUSIONS: We noted positive associations between ACPA and industrial emissions of PM(2.5) and SO(2). Industrial PM(2.5) exposure may play a particularly important role in this regard.