46
views
0
recommends
+1 Recommend
0 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found
      Is Open Access

      Identifying built environmental patterns using cluster analysis and GIS: Relationships with walking, cycling and body mass index in French adults

      research-article

      Read this article at

      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Abstract

          Background

          Socio-ecological models suggest that both individual and neighborhood characteristics contribute to facilitating health-enhancing behaviors such as physical activity. Few European studies have explored relationships between local built environmental characteristics, recreational walking and cycling and weight status in adults. The aim of this study was to identify built environmental patterns in a French urban context and to assess associations with recreational walking and cycling behaviors as performed by middle-aged adult residents.

          Methods

          We used a two-step procedure based on cluster analysis to identify built environmental patterns in the region surrounding Paris, France, using measures derived from Geographic Information Systems databases on green spaces, proximity facilities (destinations) and cycle paths. Individual data were obtained from participants in the SU.VI.MAX cohort; 1,309 participants residing in the Ile-de-France in 2007 were included in this analysis. Associations between built environment patterns, leisure walking/cycling data (h/week) and measured weight status were assessed using multinomial logistic regression with adjustment for individual and neighborhood characteristics.

          Results

          Based on accessibility to green spaces, proximity facilities and availability of cycle paths, seven built environmental patterns were identified. The geographic distribution of built environmental patterns in the Ile-de-France showed that a pattern characterized by poor spatial accessibility to green spaces and proximity facilities and an absence of cycle paths was found only in neighborhoods in the outer suburbs, whereas patterns characterized by better spatial accessibility to green spaces, proximity facilities and cycle paths were more evenly distributed across the region. Compared to the reference pattern (poor accessibility to green areas and facilities, absence of cycle paths), subjects residing in neighborhoods characterized by high accessibility to green areas and local facilities and by a high density of cycle paths were more likely to walk/cycle, after adjustment for individual and neighborhood sociodemographic characteristics (OR = 2.5 95%CI 1.4-4.6). Body mass index did not differ across patterns.

          Conclusions

          Built environmental patterns were associated with walking and cycling among French adults. These analyses may be useful in determining urban and public health policies aimed at promoting a healthy lifestyle.

          Related collections

          Most cited references36

          • Record: found
          • Abstract: not found
          • Article: not found

          How Accessibility Shapes Land Use

            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Limits to the measurement of habitual physical activity by questionnaires.

            Despite extensive use over 40 years, physical activity questionnaires still show limited reliability and validity. Measurements have value in indicating conditions where an increase in physical activity would be beneficial and in monitoring changes in population activity. However, attempts at detailed interpretation in terms of exercise dosage and the extent of resulting health benefits seem premature. Such usage may become possible through the development of standardised instruments that will record the low intensity activities typical of sedentary societies, and will ascribe consistent biological meaning to terms such as light, moderate, and heavy exercise.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              Increasing walking: how important is distance to, attractiveness, and size of public open space?

              Well-designed public open space (POS) that encourages physical activity is a community asset that could potentially contribute to the health of local residents. In 1995-1996, two studies were conducted-an environmental audit of POS over 2 acres (n =516) within a 408-km2 area of metropolitan Perth, Western Australia; and personal interviews with 1803 adults (aged 18 to 59 years) (52.9% response rate). The association between access to POS and physical activity was examined using three accessibility models that progressively adjusted for distance to POS, and its attractiveness and size. In 2002, an observational study examined the influence of attractiveness on the use of POS by observing users of three pairs of high- and low-quality (based on attractiveness) POS matched for size and location. Overall, 28.8% of respondents reported using POS for physical activity. The likelihood of using POS increased with increasing levels of access, but the effect was greater in the model that adjusted for distance, attractiveness, and size. After adjustment, those with very good access to large, attractive POS were 50% more likely to achieve high levels of walking (odds ratio, 1.50; 95% confidence level, 1.06-2.13). The observational study showed that after matching POS for size and location, 70% of POS users observed visited attractive POS. Access to attractive, large POS is associated with higher levels of walking. To increase walking, thoughtful design (and redesign) of POS is required that creates large, attractive POS with facilities that encourage active use by multiple users (e.g., walkers, sports participants, picnickers).
                Bookmark

                Author and article information

                Journal
                Int J Behav Nutr Phys Act
                Int J Behav Nutr Phys Act
                The International Journal of Behavioral Nutrition and Physical Activity
                BioMed Central
                1479-5868
                2012
                23 May 2012
                : 9
                : 59
                Affiliations
                [1 ]Lab-Urba, Urbanism Institute of Paris, University of Paris Est, Créteil, France
                [2 ]UREN, INSERM U557/INRA U1125/CNAM/University of Paris 13/CRNH, Ile-de-France, Bobigny, France
                [3 ]Image, Ville, Environnement, CNRS ERL730, University of Strasbourg, Strasbourg, France
                [4 ]INSERM U707, University Pierre et Marie Curie-Paris 6, UMR-S 707, Paris, France
                [5 ]CarMeN, INSERM U1060/INRA U1235/University of Lyon, CRNH Rhône-Alpes, Lyon, France
                [6 ]Géographie-Cité, UMR 8504 CNRS, Paris, France
                [7 ]Department of Nutrition, Pitié-Salpêtrière Hospital (AP-HP), University Pierre et Marie Curie-Paris 6, CRNH Ile-de-France, Paris, France
                Article
                1479-5868-9-59
                10.1186/1479-5868-9-59
                3441260
                22620266
                77e2f0ec-3e09-477b-9f92-6fa70d55fd9c
                Copyright ©2012 Charreire et al.; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 5 September 2011
                : 1 May 2012
                Categories
                Research

                Nutrition & Dietetics
                geographical information systems,built environment,health-enhancing physical activity,body mass index,walking,urban form,cluster analysis,cycling

                Comments

                Comment on this article