Disability adjusted life year (DALY): a useful tool for quantitative assessment of environmental pollution

Sci Total Environ. 2015 Apr 1:511:268-87. doi: 10.1016/j.scitotenv.2014.11.048. Epub 2014 Dec 27.

Abstract

Disability adjusted life year (DALY) has been widely used since 1990s for evaluating global and/or regional burden of diseases. As many environmental pollutants are hazardous to human health, DALY is also recognized as an indicator to quantify the health impact of environmental pollution related to disease burden. Based on literature reviews, this article aims to give an overview of the applicable methodologies and research directions for using DALY as a tool for quantitative assessment of environmental pollution. With an introduction of the methodological framework of DALY, the requirements on data collection and manipulation for quantifying disease burdens are summarized. Regarding environmental pollutants hazardous to human beings, health effect/risk evaluation is indispensable for transforming pollution data into disease data through exposure and dose-response analyses which need careful selection of models and determination of parameters. Following the methodological discussions, real cases are analyzed with attention paid to chemical pollutants and pathogens usually encountered in environmental pollution. It can be seen from existing studies that DALY is advantageous over conventional environmental impact assessment for quantification and comparison of the risks resulted from environmental pollution. However, further studies are still required to standardize the methods of health effect evaluation regarding varied pollutants under varied circumstances before DALY calculation.

Keywords: Chemical pollutants; Disability adjusted life year (DALY); Environmental pollution; Impact assessment; Pathogens.

Publication types

  • Research Support, Non-U.S. Gov't
  • Review

MeSH terms

  • Environmental Monitoring / methods*
  • Environmental Pollutants / analysis
  • Environmental Pollution / statistics & numerical data*
  • Humans
  • Models, Theoretical
  • Quality-Adjusted Life Years*
  • Risk Factors

Substances

  • Environmental Pollutants