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Long-term Traffic-related Air Pollutant Exposure and Amyotrophic Lateral Sclerosis Diagnosis in Denmark: A Bayesian Hierarchical Analysis

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  • Robbie M. Parks, Columbia University
  • ,
  • Yanelli Nunez, Columbia University
  • ,
  • Arin A. Balalian, Columbia University
  • ,
  • Elizabeth A. Gibson, Columbia University, Harvard University
  • ,
  • Johnni Hansen, Danish Cancer Society
  • ,
  • Ole Raaschou-Nielsen
  • Matthias Ketzel
  • Jibran Khan
  • Jørgen Brandt
  • Roel Vermeulen, Utrecht University
  • ,
  • Susan Peters, Utrecht University
  • ,
  • Jeff Goldsmith, Columbia University
  • ,
  • Diane B. Re, Columbia University
  • ,
  • Marc G. Weisskopf, Harvard University
  • ,
  • Marianthi Anna Kioumourtzoglou, Columbia University

BACKGROUND: Amyotrophic lateral sclerosis (ALS) is a fatal neurodegenerative disease. Limited evidence suggests ALS diagnosis may be associated with air pollution exposure and specifically traffic-related pollutants. METHODS: In this population-based case-control study, we used 3,937 ALS cases from the Danish National Patient Register diagnosed during 1989-2013 and matched on age, sex, year of birth, and vital status to 19,333 population-based controls free of ALS at index date. We used validated predictions of elemental carbon (EC), nitrogen oxides (NO x ), carbon monoxide (CO), and fine particles (PM 2.5 ) to assign 1-, 5-, and 10-year average exposures pre-ALS diagnosis at study participants' present and historical residential addresses. We used an adjusted Bayesian hierarchical conditional logistic model to estimate individual pollutant associations and joint and average associations for traffic-related pollutants (EC, NO x , CO). RESULTS: For a standard deviation (SD) increase in 5-year average concentrations, EC (SD = 0.42 µg/m 3 ) had a high probability of individual association with increased odds of ALS (11.5%; 95% credible interval [CrI] = -1.0%, 25.6%; 96.3% posterior probability of positive association), with negative associations for NO x (SD = 20 µg/m 3 ) (-4.6%; 95% CrI = 18.1%, 8.9%; 27.8% posterior probability of positive association), CO (SD = 106 µg/m 3 ) (-3.2%; 95% CrI = 14.4%, 10.0%; 26.7% posterior probability of positive association), and a null association for nonelemental carbon fine particles (non-EC PM 2.5 ) (SD = 2.37 µg/m 3 ) (0.7%; 95% CrI = 9.2%, 12.4%). We found no association between ALS and joint or average traffic pollution concentrations. CONCLUSIONS: This study found high probability of a positive association between ALS diagnosis and EC concentration. Further work is needed to understand the role of traffic-related air pollution in ALS pathogenesis.

Original languageEnglish
JournalEpidemiology (Cambridge, Mass.)
Pages (from-to)757-766
Publication statusPublished - Nov 2022

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