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      Urban Health Indicator Tools of the Physical Environment: a Systematic Review

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          Abstract

          Urban health indicator (UHI) tools provide evidence about the health impacts of the physical urban environment which can be used in built environment policy and decision-making. Where UHI tools provide data at the neighborhood (and lower) scale they can provide valuable information about health inequalities and environmental deprivation. This review performs a census of UHI tools and explores their nature and characteristics (including how they represent, simplify or address complex systems) to increase understanding of their potential use by municipal built environment policy and decision-makers. We searched seven bibliographic databases, four key journals and six practitioner websites and conducted Google searches between January 27, 2016 and February 24, 2016 for UHI tools. We extracted data from primary studies and online indicator systems. We included 198 documents which identified 145 UHI tools comprising 8006 indicators, from which we developed a taxonomy. Our taxonomy classifies the significant diversity of UHI tools with respect to topic, spatial scale, format, scope and purpose. The proportions of UHI tools which measure data at the neighborhood and lower scale, and present data via interactive maps, have both increased over time. This is particularly relevant to built environment policy and decision-makers, reflects growing analytical capability and offers the potential for improved understanding of the complexity of influences on urban health (an aspect noted as a particular challenge by some indicator producers). The relation between urban health indicators and health impacts attributable to modifiable environmental characteristics is often indirect. Furthermore, the use of UHI tools in policy and decision-making appears to be limited, thus raising questions about the continued development of such tools by multiple organisations duplicating scarce resources. Further research is needed to understand the requirements of built environment policy and decision-makers, public health professionals and local communities regarding the form and presentation of indicators which support their varied objectives.

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          The online version of this article (10.1007/s11524-018-0228-8) contains supplementary material, which is available to authorized users.

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          Most cited references 85

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          City planning and population health: a global challenge

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            Neighborhood environmental factors correlated with walking near home: Using SPACES.

            The physical environment plays an important role in influencing participation in physical activity, although the specific factors that are correlated with different patterns of walking remain to be determined. We examined correlations between physical environmental factors and self-reported walking for recreation and transport near home. The local neighborhood environments (defined as a 400-m radius from the respondent's home) of 1678 adults were assessed for their suitability for walking. The environmental data were collected during 2000 using the Systematic Pedestrian and Cycling Environmental Scan (SPACES) instrument together with information from other sources. We used logistic regression modeling to examine the relationship between the attributes of the physical environment and the self-reported walking behavior undertaken near home. Functional features were correlated with both walking for recreation (odds ratio (OR) 1.62; 95% confidence interval (CI): 1.20-2.19) and for transport (OR 1.30; 95% CI: 0.97-1.73). A well-maintained walking surface was the main functional factor associated with walking for recreation (OR 2.04; 95% CI: 1.43-2.91) and for transport (OR 2.13; 95% CI: 1.53-2.96). Destination factors, such as shops and public transport, were significantly correlated with walking for transport (OR 1.80; 95% CI: 1.33-2.44), but not recreation. The findings suggest that neighborhoods with pedestrian facilities that are attractive and comfortable and where there are local destinations (such as shops and public transport) are associated with walking near home.
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              Evaluating a brief self-report measure of neighborhood environments for physical activity research and surveillance: Physical Activity Neighborhood Environment Scale (PANES).

              Neighborhood environment attributes of walkability and access to recreation facilities have been related to physical activity and weight status, but most self-report environment measures are lengthy. The 17-item PANES (Physical Activity Neighborhood Environment Scale) was developed to be comprehensive but brief enough for use in multipurpose surveys. The current study evaluated test-retest and alternate-form reliability of PANES items compared with multi-item subscales from the longer NEWS-A (Neighborhood Environment Walkability Scale--Abbreviated). Participants were 291 adults recruited from neighborhoods that varied in walkability in 3 US cities. Surveys were completed twice with a 27-day interval. Test-retest ICCs for PANES items ranged from .52 to .88. Spearman correlations for the PANES single item vs NEWS-A subscale comparisons ranged from .27 to .81 (all P < .01). PANES items related to land use mix, residential density, pedestrian infrastructure, aesthetic qualities, and safety from traffic and crime were supported by correlations with NEWS-A subscales. Access to recreation facilities and street connectivity items were not supported. The brevity of PANES allows items to be included in studies or surveillance systems to expand knowledge about neighborhood environments.
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                Author and article information

                Contributors
                +44 (0)7902181768 , helen.pineo.15@ucl.ac.uk
                Journal
                J Urban Health
                J Urban Health
                Journal of Urban Health : Bulletin of the New York Academy of Medicine
                Springer US (New York )
                1099-3460
                1468-2869
                16 April 2018
                16 April 2018
                15 October 2018
                : 95
                : 5
                : 613-646
                Affiliations
                [1 ]ISNI 0000000121901201, GRID grid.83440.3b, Institute of Environmental Design and Engineering, Bartlett School of Environment, Energy and Resources, , University College London, ; Central House, 14 Upper Woburn Place, London, WC1H 0NN UK
                [2 ]ISNI 0000 0001 0816 3312, GRID grid.30073.37, Building Research Establishment, ; Bucknalls Lane, Garston, Hertfordshire, WD25 9XX UK
                [3 ]ISNI 0000 0004 0644 1675, GRID grid.38603.3e, School of Humanities and Social Sciences, , University of Split, ; Split, Croatia
                [4 ]ISNI 0000 0001 2188 0914, GRID grid.10992.33, Paris Descartes University, ; 12 Rue de l’École de Médecine, 75006 Paris, France
                [5 ]ISNI 0000 0004 0425 469X, GRID grid.8991.9, Centre for Global Chronic Conditions, , London School of Hygiene and Tropical Medicine, ; 15-17 Tavistock Place, London, WC1H 9SH UK
                [6 ]ISNI 0000 0004 0425 469X, GRID grid.8991.9, Department of Social and Environmental Health Research, , London School of Hygiene and Tropical Medicine, ; Keppel Street, London, WC1E 7HT UK
                Article
                228
                10.1007/s11524-018-0228-8
                6181826
                29663118
                © The Author(s) 2018

                OpenAccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.

                Funding
                Funded by: University College London (UCL)
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                © The New York Academy of Medicine 2018

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