Spatial Analysis for Environmental Health Research: Concepts, Methods, and Examples

Abstract

Spatial analysis can illuminate environmental health research in two ways. First, spatial analysis may suggest possible causal factors in disease pathogenesis. Association between disease and place may imply that the population living there either possesses inherent traits that make it more susceptible to disease or experiences elevated exposure to a risk factor such as air pollution. Second, spatial analysis can help identify how populations adapt and relate to their environment. This knowledge may lead to improved understanding of how people perceive and avoid health risks of environmental origin. The potential for spatial analysis to uncover these aspects of the association between health and the environment is limited by data and methodological problems that are discussed in the article. To familiarize researchers and policymakers with this increasingly important approach, we review spatial-analytic methods under three headings: visualization, exploration, and modeling. We use illustrative examples to assist readers in understanding the strengths and weaknesses of specific methods.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 73 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.