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      The SPOTLIGHT virtual audit tool: a valid and reliable tool to assess obesogenic characteristics of the built environment

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          Abstract

          Background

          A lack of physical activity and overconsumption of energy dense food is associated with overweight and obesity. The neighbourhood environment may stimulate or hinder the development and/or maintenance of a healthy lifestyle. To improve research on the obesogenicity of neighbourhood environments, reliable, valid and convenient assessment methods of potential obesogenic characteristics of neighbourhood environments are needed. This study examines the reliability and validity of the SPOTLIGHT-Virtual Audit Tool (S-VAT), which uses remote sensing techniques (Street View feature in Google Earth) for desk-based assessment of environmental obesogenicity.

          Methods

          A total of 128 street segments in four Dutch urban neighbourhoods – heterogeneous in socio-economic status and residential density – were assessed using the S-VAT. Environmental characteristics were categorised as walking related items, cycling related items, public transport, aesthetics, land use-mix, grocery stores, food outlets and physical activity facilities. To assess concordance of inter- and intra-observer reliability of the Street View feature in Google Earth, and validity scores with real life audits, percentage agreement and Cohen's Kappa (k) were calculated.

          Results

          Intra-observer reliability was high and ranged from 91.7% agreement (k = 0.654) to 100% agreement (k = 1.000) with an overall agreement of 96.4% (k = 0.848). Inter-observer reliability results ranged from substantial agreement 78.6% (k = 0.440) to high agreement, 99.2% (k = 0.579), with an overall agreement of 91.5% (k = 0.595). Criterion validity was substantial to high for most of the categories ranging from 87.3% agreement (k = 0.539) to 99.9% agreement (k = 0.887) with an overall score of 95.6% agreement (k = 0.747).

          Conclusion

          These study results suggest that the S-VAT is a highly reliable and valid remote sensing tool to assess potential obesogenic environmental characteristics.

          Electronic supplementary material

          The online version of this article (doi:10.1186/1476-072X-13-52) contains supplementary material, which is available to authorized users.

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          Most cited references43

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          The Measurement of Observer Agreement for Categorical Data

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            The built environment and obesity: a systematic review of the epidemiologic evidence.

            We completed a systematic search of the epidemiologic literature on built environment and obesity and identified 63 relevant papers, which were then evaluated for the quality of between-study evidence. We were able to classify studies into one of two primary approaches for defining place and corresponding geographic areas of influence: those based on contextual effects derived from shared pre-determined administrative units and those based on individually unique geographic buffers. The 22 contextual papers evaluated 80 relations, 38 of which did not achieve statistical significance. The 15 buffer papers evaluated 40 relations, 24 of which did not achieve statistical significance. There was very little between-study similarity in methods in both types of approaches, which prevented estimation of pooled effects. The great heterogeneity across studies limits what can be learned from this body of evidence. Copyright 2009 Elsevier Ltd. All rights reserved.
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              The built environment and obesity.

              Obesity results from a complex interaction between diet, physical activity, and the environment. The built environment encompasses a range of physical and social elements that make up the structure of a community and may influence obesity. This review summarizes existing empirical research relating the built environment to obesity. The Medline, PsychInfo, and Web of Science databases were searched using the keywords "obesity" or "overweight" and "neighborhood" or "built environment" or "environment." The search was restricted to English-language articles conducted in human populations between 1966 and 2007. To meet inclusion criteria, articles had to 1) have a direct measure of body weight and 2) have an objective measure of the built environment. A total of 1,506 abstracts were obtained, and 20 articles met the inclusion criteria. Most articles (84%) reported a statistically significant positive association between some aspect of the built environment and obesity. Several methodological issues were of concern, including the inconsistency of measurements of the built environment across studies, the cross-sectional design of most investigations, and the focus on aspects of either diet or physical activity but not both. Given the importance of the physical and social contexts of individual behavior and the limited success of individual-based interventions in long-term obesity prevention, more research on the impact of the built environment on obesity is needed.
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                Author and article information

                Contributors
                j.bethlehem@outlook.com
                j.mackenbach@vumc.nl
                m.ben-rebah@uren.smbh.univ-paris13.fr
                sofie.compernolle@ugent.be
                ketevan.glonti@lshtm.ac.uk
                bardos.helga@sph.unideb.hu
                harry.rutter@lshtm.ac.uk
                helene.charreire@u-pec.fr
                jean-michel.oppert@psl.aphp.fr
                j.brug@vumc.nl
                j.lakerveld@vumc.nl
                Journal
                Int J Health Geogr
                Int J Health Geogr
                International Journal of Health Geographics
                BioMed Central (London )
                1476-072X
                16 December 2014
                16 December 2014
                2014
                : 13
                : 1
                : 52
                Affiliations
                [ ]Department of Epidemiology and Biostatistics, EMGO Institute for Health and Care Research, VU University Medical Center, Amsterdam, the Netherlands
                [ ]University Paris 13, Equipe de Recherche en Epidémiologie Nutritionnelle (EREN), UMR U1153 Inserm/U1125, Centre de Recherche en Epidémiologie et Biostatistiques Sorbonne Paris Cité, Bobigny, France
                [ ]Department of Movement and Sport Sciences, Faculty of Medicine and Health Sciences, Ghent University, Ghent, Belgium
                [ ]European Centre on Health of Societies in Transition, London School of Hygiene and Tropical Medicine, London, UK
                [ ]Department of Preventive Medicine, Faculty of Public Health, University of Debrecen, Debrecen, Hungary
                [ ]Department of Nutrition, GH Pitié-Salpêtrière (AP-HP), University Pierre et Marie Curie-Paris6; Institute of Cardiometabolism and Nutrition (ICAN), Paris, France
                Article
                615
                10.1186/1476-072X-13-52
                4279584
                25515179
                0005519f-d1b9-487b-9421-bd6ba473034b
                © Bethlehem et al.; licensee BioMed Central. 2014

                This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.

                History
                : 6 October 2014
                : 8 December 2014
                Categories
                Methodology
                Custom metadata
                © The Author(s) 2014

                Public health
                virtual audit tool,remote sensing techniques,environmental characteristics,reliability,validity,diet,physical activity

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