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Burden of Disease Due to Ambient Particulate Matter in Germany—Explaining the Differences in the Available Estimates

Author

Listed:
  • Myriam Tobollik

    (German Environment Agency, Department Environmental Hygiene, Corrensplatz, 14195 Berlin, Germany)

  • Sarah Kienzler

    (German Environment Agency, Department Environmental Hygiene, Corrensplatz, 14195 Berlin, Germany)

  • Christian Schuster

    (German Environment Agency, Department Environmental Hygiene, Corrensplatz, 14195 Berlin, Germany
    Berlin-Brandenburg Academy of Sciences and Humanities, Transfer Unit Science Communication, 10117 Berlin, Germany)

  • Dirk Wintermeyer

    (German Environment Agency, Department Environmental Hygiene, Corrensplatz, 14195 Berlin, Germany)

  • Dietrich Plass

    (German Environment Agency, Department Environmental Hygiene, Corrensplatz, 14195 Berlin, Germany)

Abstract

Ambient particulate matter (PM 2.5 ) pollution is an important threat to human health. The aim of this study is to estimate the environmental burden of disease (EBD) for the German population associated with PM 2.5 exposure in Germany for the years 2010 until 2018. The EBD method was used to quantify relevant indicators, e.g., disability-adjusted life years (DALYs), and the life table approach was used to estimate the reduction in life expectancy caused by long-term PM 2.5 exposure. The impact of varying assumptions and input data was assessed. From 2010 to 2018 in Germany, the annual population-weighted PM 2.5 concentration declined from 13.7 to 10.8 µg/m 3 . The estimates of annual PM 2.5 -attributable DALYs for all disease outcomes showed a downward trend. In 2018, the highest EBD was estimated for ischemic heart disease (101.776; 95% uncertainty interval (UI) 62,713–145,644), followed by lung cancer (60,843; 95% UI 43,380–79,379). The estimates for Germany differ from those provided by other institutions. This is mainly related to considerable differences in the input data, the use of a specific German national life expectancy and the selected relative risks. A transparent description of input data, computational steps, and assumptions is essential to explain differing results of EBD studies to improve methodological credibility and trust in the results. Furthermore, the different calculated indicators should be explained and interpreted with caution.

Suggested Citation

  • Myriam Tobollik & Sarah Kienzler & Christian Schuster & Dirk Wintermeyer & Dietrich Plass, 2022. "Burden of Disease Due to Ambient Particulate Matter in Germany—Explaining the Differences in the Available Estimates," IJERPH, MDPI, vol. 19(20), pages 1-16, October.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:20:p:13197-:d:941417
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    References listed on IDEAS

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    1. Dimitris Evangelopoulos & Roman Perez-Velasco & Heather Walton & Sophie Gumy & Martin Williams & Frank J. Kelly & Nino Künzli, 2020. "The role of burden of disease assessment in tracking progress towards achieving WHO global air quality guidelines," International Journal of Public Health, Springer;Swiss School of Public Health (SSPH+), vol. 65(8), pages 1455-1465, November.
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