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Fig. 1 | Environmental Health

Fig. 1

From: Association of ambient air pollution with cardiovascular disease risks in people with type 2 diabetes: a Bayesian spatial survival analysis

Fig. 1

Determination of air pollution at individual level and spatial correlations and event rate of composite cardiovascular disease events and 76 air quality monitoring station (dots) across 20 geographic regions in Taiwan. a shows the two main problems inherent to existing studies on the environmental pollution effects on health. First, personal location is typically defined at the geographic area (community) level (e.g., a person is known to live in Changhua but their exact location in Changhua is unclear). As a result, the conventional approach for the assessment of air pollution is to assign all residents within an area the same value of air pollution, regardless of the individual’s relative location with respect to the pollution source. For example, consider the 13 people living in Changhua County shown in Fig. 1a. The average concentration for the three air monitoring stations within the area (i.e., [46.49+ 49.67 + 53.88]/3 = 50.01 μg/m3 for the monthly concentration of PM2.5 in Dec. 2009) is generally used for people living in a given area. Second, due to the coarse resolution used for individual locations, the distance between two individuals or their proxies (i.e., their assigned air quality monitoring stations) is not ascertained and thus the spatial correlations in the pattern of air pollution and adverse pollution effects on health are not modeled in the analyses. b shows the spatial variations in the event rate of cardiovascular diseases across Taiwan

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