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Building an interdisciplinary framework to advance conceptual and technical aspects of population-environment research focused on women's and children's health
Stockholm University, Faculty of Social Sciences, Department of Sociology.
Number of Authors: 32020 (English)In: Social Science and Medicine, ISSN 0277-9536, E-ISSN 1873-5347, Vol. 250, article id 112857Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
2020. Vol. 250, article id 112857
Keywords [en]
GIS, Population-environment, Climate, Spatial, Health geography
National Category
Public Health, Global Health and Social Medicine Health Care Service and Management, Health Policy and Services and Health Economy
Identifiers
URN: urn:nbn:se:su:diva-181735DOI: 10.1016/j.socscimed.2020.112857ISI: 000528208000008PubMedID: 32151780OAI: oai:DiVA.org:su-181735DiVA, id: diva2:1433359
Available from: 2020-05-29 Created: 2020-05-29 Last updated: 2025-02-20Bibliographically approved

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Billingsley, Sunnee

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