Long-Term Exposure to Fine Particle Elemental Components and Natural and Cause-Specific Mortality-a Pooled Analysis of Eight European Cohorts within the ELAPSE Project

Research output: Contribution to journalJournal articleResearchpeer-review

  • Jie Chen
  • Sophia Rodopoulou
  • Kees de Hoogh
  • Maciej Strak
  • Richard Atkinson
  • Mariska Bauwelinck
  • Tom Bellander
  • Jorgen Brandt
  • Giulia Cesaroni
  • Hans Concin
  • Daniela Fecht
  • Francesco Forastiere
  • John Gulliver
  • Ole Hertel
  • Barbara Hoffmann
  • Ulla Arthur Hvidtfeldt
  • Nicole A. H. Janssen
  • Karl-Heinz Joeckel
  • Klea Katsouyanni
  • Matthias Ketzel
  • Jochem O. Klompmaker
  • Anton Lager
  • Karin Leander
  • Petter Ljungman
  • Conor J. MacDonald
  • Patrik K. E. Magnusson
  • Gabriele Nagel
  • Bente Oftedal
  • Goran Pershagen
  • Annette Peters
  • Ole Raaschou-Nielsen
  • Matteo Renzi
  • Debora Rizzuto
  • Evangelia Samoli
  • Yvonne T. van der Schouw
  • Sara Schramm
  • Per Schwarze
  • Torben Sigsgaard
  • Mette Sørensen
  • Massimo Stafoggia
  • Danielle Vienneau
  • Gudrun Weinmayr
  • Kathrin Wolf
  • Bert Brunekreef
  • Gerard Hoek

BACKGROUND: Inconsistent associations between long-term exposure to particles with an aerodynamic diameter

OBJECTIVES: We investigated the associations between long-term exposure to PM2.5 elemental components and mortality in a large pooled European cohort; to compare health effects of PM2.5 components estimated with two exposure modeling approaches, namely, supervised linear regression (SLR) and random forest (RF) algorithms.

METHODS: We pooled data from eight European cohorts with 323,782 participants, average age 49 y at baseline (1985-2005). Residential exposure to 2010 annual average concentration of eight PM2.5 components [copper (Cu), iron (Fe), potassium (K), nickel (Ni), sulfur (S), silicon (Si), vanadium (V), and zinc (Zn)] was estimated with Europe-wide SLR and RF models at a 100 X 100 m scale. We applied Cox proportional hazards models to investigate the associations between components and natural and cause-specific mortality. In addition, two-pollutant analyses were conducted by adjusting each component for PM2.5 mass and nitrogen dioxide (NO2) separately.

RESULTS: We observed 46,640 natural-cause deaths with 6,317,235 person-years and an average follow-up of 19.5 y. All SLR-modeled components were statistically significantly associated with natural-cause mortality in single-pollutant models with hazard ratios (HRs) from 1.05 to 1.27. Similar HRs were observed for RE-modeled Cu, Fe, K, S, V, and Zn with wider confidence intervals (CIs). HRs for SLR-modeled Ni, S, Si, V, and Zn remained above unity and (almost) significant after adjustment for both PM2.5 and NO2. HRs only remained (almost) significant for RE-modeled K and V in two-pollutant models. The HRs for V were 1.03 (95% CI: 1.02, 1.05) and 1.06 (95% CI: 1.02, 1.10) for SLR- and RF-modeled exposures, respectively, per 2 ng/m(3), adjusting for PM2.5 mass. Associations with cause-specific mortality were less consistent in two-pollutant models.

CONCLUSION: Long-term exposure to V in PM2.5 was most consistently associated with increased mortality. Associations for the other components were weaker for exposure modeled with RE than SLR in two-pollutant models.

Original languageEnglish
Article number047009
JournalEnvironmental Health Perspectives
Volume129
Issue number4
Number of pages12
ISSN0091-6765
DOIs
Publication statusPublished - 2021

    Research areas

  • USE REGRESSION-MODELS, PARTICULATE MATTER, RISK, PROFILE, ESCAPE, PM2.5, MEN

ID: 272709077