Great gains have been made in providing researchers geo-spatial data that can be combined with population health data. This development is crucial given concerns over the human health outcomes associated with a changing climate. Merging population and environmental data remains both conceptually and technically challenging because of a large range of temporal and spatial scales. Here we propose a framework that addresses and advances both conceptual and technical aspects of population-environment research. This framework can be useful for considering how any time or space-based environmental occurrence influences population health outcomes and can be used to guide different data aggregation strategies. The primary consideration discussed here is how to properly model the space and time effects of environmental context on individual-level health outcomes, specifically maternal, child and reproductive health outcomes. The influx of geospatial health data and highly detailed environmental data, often at daily scales, provide an opportunity for population-environment researchers to move towards a more theoretically and analytically sound approach for studying environment and health linkages.
Bibliographical noteFunding Information:
The authors gratefully acknowledge support from the Minnesota Population Center ( P2C HD041023 ) funded through a grant from the Eunice Kennedy Shriver National Institute for Child Health and Human Development ( NICHD ). Grace also acknowledges support from the National Science Foundation Grant #1639214 and the United States Agency for International Development ( USAID ) cooperative agreement #72DFFP19CA00001 .
© 2020 Elsevier Ltd
- Health geography
PubMed: MeSH publication types
- Journal Article