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Metrics in Urban Health: Current Developments and Future Prospects
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The research community has shown increasing interest in developing and using metrics to determine the relationships between urban living and health. In particular, we have seen a recent exponential increase in efforts aiming to investigate and apply metrics for urban health, especially the health impacts of the social and built environments as well as air pollution. A greater recognition of the need to investigate the impacts and trends of health inequities is also evident through more recent literature. Data availability and accuracy have improved through new affordable technologies for mapping, geographic information systems (GIS), and remote sensing. However, less research has been conducted in low- and middle-income countries where quality data are not always available, and capacity for analyzing available data may be limited. For this increased interest in research and development of metrics to be meaningful, the best available evidence must be accessible to decision makers to improve health impacts through urban policies.
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“The populations of urban informal settlements will continue to grow as rural migration escalates in LMICs over the coming decades 2,9 , and are expected to double from 1 to 2 billion by 2050 10 .”
From Urban informal settlements as hotspots of antimicrobial resistance and the need to curb environmental transmission. (2020) · cites this paper as [10]
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Nadimpalli, M. L., Marks, S. J., Montealegre, M. C., Gilman, R. H., Pajuelo, M. J., Saito, M., Tsukayama, P., Njenga, S. M., Kiiru, J., Swarthout, J., et al. (2020) · Nature microbiology · doi:10.1038/s41564-020-0722-0 · Cited by 223
Urban Form, Air Pollution, and Health
Hankey, S., & Marshall, J. D. (2017) · Current Environmental Health Reports · doi:10.1007/s40572-017-0167-7 · Cited by 183
Molecular Epidemiology of Human Cryptosporidiosis in Low- and Middle-Income Countries
Yang, X., Guo, Y., Xiao, L., & Feng, Y. (2021) · Clinical Microbiology Reviews · doi:10.1128/cmr.00087-19 · Cited by 146
Public and Population Health Informatics: The Bridging of Big Data to Benefit Communities
Gamache, R. E., Kharrazi, H. H. K., & Weiner, J. P. (2018) · Yearbook of Medical Informatics · doi:10.1055/s-0038-1667081 · Cited by 129
“As the population living in urban areas is increasing rapidly, our understanding of SDH and city-related livability factors will be important, particularly for low and middle income countries [24].”
BackgroundUrban Health Indicator Tools of the Physical Environment: a Systematic Review
Pineo, H., Glonti, K., Rutter, H., Zimmermann, N., Wilkinson, P., & Davies, M. (2018) · Journal of Urban Health · doi:10.1007/s11524-018-0228-8 · Cited by 112
“We used relevant literature [9, 19, 27] and the data gathered in the review to identify five key characteristics of UHI tools for built environment professionals: spatial scale, purpose, topic, scope and format.”
BackgroundMethod
Metadata
- Authors
- Prasad, A., Gray, C. B., Ross, A., & Kano, M.
- Affiliations
- World Health Organization (CH)
- ORCID
- Prasad, Amit
- Venue
- Annual Review of Public Health
- Publisher
- Annual Reviews
- Published
- 2016-03-18
- Volume
- 37
- Issue
- 1
- Pages
- 113-133
- ISSN
- 0163-7525 (ISSN-L)
- 1545-2093
- OpenAlex
- W2262093774
- Cited by
- 49
- References
- 90
- Citations by year
- 2026: 1 · 2024: 7 · 2023: 4 · 2022: 6 · 2021: 8 · 2020: 7 · 2019: 5 · 2018: 7 · 2017: 3 · 2016: 1
- FWCI
- 0.66
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Annual Review of Public Health (publishedVersion)
- PubMed (publishedVersion)
- Funders
- World Health Organization
- Topics
- Social Sciences › Transportation › Urban Transport and Accessibility
- Social Sciences › Urban Studies › Urban Green Space and Health
- Social Sciences › Health › Health disparities and outcomes
- Keywords
- built environment, social environment, air pollution, health disparities, low- and middle-income countries, geographic information systems, remote sensing, urban health policy, data availability
- MeSH terms
- Air Pollution, Climate, Developing Countries, Environment, Epidemiologic Methods, Health Status Indicators, Humans, Poverty Areas, Social Environment, Urban Health, Urbanization, Global Health, Geographic Information Systems, Health Status Disparities
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
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