Validity of Geolocation and Distance to Exposure Sources from Geographical Information Systems for Environmental Monitoring of Toxic Metal Exposures Based on Correlation with Biological Samples: a Systematic Review.

In epidemiologic studies, biomarkers are the best possible choice to assess individual exposure to toxic metals since they integrate all exposure sources. However, measuring biomarkers is not always feasible, given potential budgetary and time constraints or limited availability of samples. Alternatively, approximations to individual metal exposure obtained from geographic information systems (GIS) have become popular to evaluate diverse metal-related health outcomes. Our objective was to conduct a systematic review of epidemiological studies that evaluated the validity of GIS-based geolocation and distance to pollutant sources as an approximation of individual metal exposure based on correlation with biological samples. We considered 11 toxic metals: lead (Pb), cadmium (Cd), antimony (Sb), aluminum (Al), arsenic (As), chromium (Cr), nickel (Ni), mercury (Hg), tungsten (W), uranium (U), and vanadium (V). The final review included 12 manuscripts which included seven metals (Pb, Cd, Al, As, Cr, Hg, and Ni). Many studies used geolocation of the individuals to compare exposed (industrial, urban, agricultural, or landfill sources) and unexposed areas and not so many studies used distance to a source. For all metals, except lead, there was more animal than human biosampling to conduct biological validation. We observed a trend towards higher levels of Cd, Cr, Hg, and Pb in biosamples collected closer to exposure sources, supporting that GIS-based proxies for these metals might approximate individual exposure. However, given the low number and heterogeneity of the retrieved studies, the accumulated evidence is, overall, not sufficient. Given the practical benefits and potential of modern GIS technologies, which allow environmental monitoring at a reasonable cost, additional validation studies that include human biosampling are needed to support the use of GIS-based individual exposure measures in epidemiologic studies.

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© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.