The Built Environment and Health in Low- and Middle-Income Countries: a Review on Quantitative Health Impact Assessments

Purpose of Review Features and attributes of the built environment (BE) impact positively and negatively on health, especially in cities facing unprecedented urban population growth and mass motorization. A common approach to assess the health impacts of built environment is health impact assessment...

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Veröffentlicht in:Current environmental health reports 2022-03, Vol.9 (1), p.90-103
Hauptverfasser: Thondoo, M., Goel, R., Tatah, L., Naraynen, N., Woodcock, J., Nieuwenhuijsen, Mark
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Sprache:eng
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Zusammenfassung:Purpose of Review Features and attributes of the built environment (BE) impact positively and negatively on health, especially in cities facing unprecedented urban population growth and mass motorization. A common approach to assess the health impacts of built environment is health impact assessment (HIA), but it is rarely used in low- and middle-income countries (LMICs) where urbanization rates are fastest. This article reviews selected HIA case studies from LMICs and reports the methods and tools used to support further implementation of quantitative HIAs in cities of LMICs. Recent Findings In total, 24 studies were reviewed across Algeria, Brazil, China, India, Iran, Kenya, Thailand, Turkey, and Mauritius. HIAs examine specific pathways through which the built environment acts: air pollution, noise, physical activity, and traffic injury. Few HIAs of BE addressed more than one exposure pathway at a time, and most studies focused on air pollution across the sectors of transport and energy. A wide number of tools were used to conduct exposure assessment, and different models were applied to assess health impacts of different exposures. Those HIAs rely on availability of local concentration data and often use models that have set exposure–response functions (ERFs). ERFs were not adapted to local populations except for HIAs conducted in China. Summary HIAs of BE are being successfully conducted in LMICs with a variety of tools and datasets. Scaling and expanding quantitative health impact modeling in LMICs will require further study on data availability, adapted models/tools, low technical capacity, and low policy demand for evidence from modeling studies. As case studies with successful use of evidence from modeling emerge, the uptake of health impact modeling of BE is likely to increase in favor of people and planet.
ISSN:2196-5412
2196-5412
DOI:10.1007/s40572-021-00324-6