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. 2016 Mar 15;13(3):319.
doi: 10.3390/ijerph13030319.

A Conceptual Framework for the Assessment of Cumulative Exposure to Air Pollution at a Fine Spatial Scale

Kihal-Talantikite Wahida  1   2 , Cindy M Padilla  3 , Zmirou-Navier Denis  4   5   6 , Blanchard Olivier  7   8 , Le Nir Géraldine  9 , Quenel Philippe  10   11 , Deguen Séverine  12   13
Affiliations

A Conceptual Framework for the Assessment of Cumulative Exposure to Air Pollution at a Fine Spatial Scale

Kihal-Talantikite Wahida et al. Int J Environ Res Public Health. .

Abstract

Many epidemiological studies examining long-term health effects of exposure to air pollutants have characterized exposure by the outdoor air concentrations at sites that may be distant to subjects' residences at different points in time. The temporal and spatial mobility of subjects and the spatial scale of exposure assessment could thus lead to misclassification in the cumulative exposure estimation. This paper attempts to fill the gap regarding cumulative exposure assessment to air pollution at a fine spatial scale in epidemiological studies investigating long-term health effects. We propose a conceptual framework showing how major difficulties in cumulative long-term exposure assessment could be surmounted. We then illustrate this conceptual model on the case of exposure to NO₂ following two steps: (i) retrospective reconstitution of NO₂ concentrations at a fine spatial scale; and (ii) a novel approach to assigning the time-relevant exposure estimates at the census block level, using all available data on residential mobility throughout a 10- to 20-year period prior to that for which the health events are to be detected. Our conceptual framework is both flexible and convenient for the needs of different epidemiological study designs.

Keywords: air pollution; cumulative exposure assessment; fine spatial scale; long-term; residential mobility.

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Figures

Figure 1
Figure 1
Assessment of cumulative exposure accounting for residential mobility.
Figure 2
Figure 2
Spatiotemporal distribution of the modeled annual averages of NO2 concentrations at the census block level over the 2002−2012 period in Paris.
Figure 3
Figure 3
Distribution of NO2 concentrations at the census block level (in µg/m3) from 2002 to 2012. Box plots (fifth percentile, first quartile, median, third quartile, ninety-fifth percentile).
Figure 4
Figure 4
Distribution of intra-census block variability (difference between maximum and minimum of NO2 concentrations at the census block level (in µg/m3)) for the entire study period from 2002 to 2012. Box plots of the difference between the maximum and the minimum (fifth percentile, first quartile, median, third quartile, ninety-fifth percentile).
Figure 5
Figure 5
Dendogram of distances between all census blocks and monitoring stations.
Figure 6
Figure 6
Illustration of time trends during the study period (2002–2012): (a) the variability of daily concentrations measured at three monitoring stations named the “index” monitors; (b) the variability of annual concentrations estimated for three census blocks among all the census blocks represented by each monitoring station.
Figure 7
Figure 7
Spatial distribution of the proportion of people residing in 2006 in census block and living in the same census block 5 and 10 year before.
Figure 8
Figure 8
Retrospective modelling of pollutants’ concentrations at a fine spatial scale.
See this image and copyright information in PMC

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