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Editorial
. 2019 May 21;40(20):1597-1599.
doi: 10.1093/eurheartj/ehz200.

Estimating pollution-attributable mortality at the regional and global scales: challenges in uncertainty estimation and causal inference

Rachel C Nethery  1 , Francesca Dominici  1
Affiliations
Editorial

Estimating pollution-attributable mortality at the regional and global scales: challenges in uncertainty estimation and causal inference

Rachel C Nethery et al. Eur Heart J. .
No abstract available

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Figures

Figure 1
Figure 1
Sources of uncertainty introduced in each stage of the standard modelling approach for estimating pollution-attributable mortality at the global and regional scales. In the model used to estimate global/regional pollution exposures, uncertainty arises from measurement error in the input data, unknown model parameters, and the aggregation of the exposures to grid cells. The exposure–response models to estimate the hazard ratio (HR) function are constructed using many epidemiological studies. Here, uncertainty is introduced through measurement error in pollution and confounder data, within-study variability, unknown within-study model form, and inter-study heterogeneity. When global/regional pollution exposure estimates are plugged into the HR to estimate total pollution-attributable mortality, additional uncertainty is generated. This is because the data used to create the HR probably do not represent the global/regional population and because the HR function may need to be extrapolated to accommodate exposures outside the range observed in the epidemiological data.
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