4.4 Article

Built environment in local relation with walking: Why here and not there?

Journal

JOURNAL OF TRANSPORT & HEALTH
Volume 3, Issue 4, Pages 500-512

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jth.2015.12.004

Keywords

Active mobility; Contextual effect; Spatial nonstationarity; Geographically weighted regression; Discriminant analysis

Funding

  1. French National Cancer Institute (Institut National du Cancer, INCa) through the Social sciences and humanities and public health programme [2011-1-PL-SHS-10]
  2. Ministere de la Sante
  3. Institut de Veille Sanitaire (InVS)
  4. Institut National de la Prevention et de l'Education pour la Sante (INPES)
  5. Fondation pour la Recherche Medicale (FRM)
  6. Institut National de la Sante et de la Recherche Medicale (INSERM)
  7. Institut National de la Recherche Agronomique (INRA)
  8. Conservatoire National des Arts et Metiers (CNAM)
  9. Paris 13 University

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Walking, as both a major mode of transport and the most common form of every-day physical activity, deserves further attention in health-related transportation studies. In this paper, we focused on the built environmental correlates of walking for errands and leisure in a sample of 409 adults (Paris, France) through a cross-sectional study based on an internet survey. The main aims were (i) to delineate places with contrasting relationships between the built environment and walking, using geographically weighted regression models and (ii) to determine what differentiated the contexts we uncovered, in terms of both environmental and individual characteristics, using canonical discriminant analyses. Our results showed that the spatial heterogeneity of relationships between walking and the built environment occurred across the entire studied area and concerned the two walking outcomes, with odds-ratios (ORs) ranging from 1.01 to 131 and from 1.07 to 1.35 for walking for errands and leisure, respectively. We suggest that the spatial patterning of convergent relationships is due to contextual effects, i.e., the effect of places with specific intrinsic arrangement of environmental and individual features. Data-driven identification of local contexts should be a key step in future contextual analyses of walking and health related outcomes. (C) 2015 Elsevier Ltd. All rights reserved.

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