Advertisement

Neighborhood Walkability

Field Validation of Geographic Information System Measures
  • Samantha Hajna
    Affiliations
    Department of Epidemiology, Biostatistics and Occupational Health, McGill University Health Centre, McGill University, Montréal, Quebec, Canada
    Search for articles by this author
  • Kaberi Dasgupta
    Affiliations
    Department of Epidemiology, Biostatistics and Occupational Health, McGill University Health Centre, McGill University, Montréal, Quebec, Canada

    Department of Medicine, Division of Clinical Epidemiology, McGill University Health Centre, McGill University, Montréal, Quebec, Canada
    Search for articles by this author
  • Max Halparin
    Affiliations
    Department of Geography, McGill University Health Centre, McGill University, Montréal, Quebec, Canada
    Search for articles by this author
  • Nancy A. Ross
    Correspondence
    Address correspondence to: Nancy A. Ross, PhD, McGill University, Department of Geography, 805 Sherbrooke Street West, Montréal, QC H3A 2K6 Canada
    Affiliations
    Department of Epidemiology, Biostatistics and Occupational Health, McGill University Health Centre, McGill University, Montréal, Quebec, Canada

    Department of Geography, McGill University Health Centre, McGill University, Montréal, Quebec, Canada
    Search for articles by this author

      Background

      Given the health benefits of walking, there is interest in understanding how physical environments favor walking. Although GIS-derived measures of land-use mix, street connectivity, and residential density are commonly combined into indices to assess how conducive neighborhoods are to walking, field validation of these measures is limited.

      Purpose

      To assess the relationship between audit- and GIS-derived measures of overall neighborhood walkability and between objective (audit- and GIS-derived) and participant-reported measures of walkability.

      Methods

      Walkability assessments were conducted in 2009. Street-level audits were conducted using a modified version of the Pedestrian Environmental Data Scan. GIS analyses were used to derive land-use mix, street connectivity, and residential density. Participant perceptions were assessed using a self-administered questionnaire. Audit, GIS, and participant-reported indices of walkability were calculated. Spearman correlation coefficients were used to assess the relationships between measures. All analyses were conducted in 2012.

      Results

      The correlation between audit- and GIS-derived measures of overall walkability was high (R=0.7 [95% CI=0.6, 0.8]); the correlations between objective (audit and GIS-derived) and participant-reported measures were low (R=0.2 [95% CI=0.06, 0.3]; R=0.2 [95% CI=0.04, 0.3], respectively). For comparable audit and participant-reported items, correlations were higher for items that appeared more objective (e.g., sidewalk presence, R=0.4 [95% CI=0.3, 0.5], versus safety, R=0.1 [95% CI=0.003, 0.3]).

      Conclusions

      The GIS-derived measure of walkability correlated well with the in-field audit, suggesting that it is reasonable to use GIS-derived measures in place of more labor-intensive audits. Interestingly, neither audit- nor GIS-derived measures correlated well with participants’ perceptions of walkability.
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to American Journal of Preventive Medicine
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

      1. WHO. Global health observatory: prevalence of insufficient physical activity. 2012. www.who.int/gho/ncd/risk_factors/physical_activity_text/en/index.html.

        • Frank L.D.
        • Kerr J.
        • Sallis J.F.
        • Miles R.
        • Chapman J.
        A hierarchy of sociodemographic and environmental correlates of walking and obesity.
        Prev Med. 2008; 47: 172-178
        • Sundquist K.
        • Eriksson U.
        • Kawakami N.
        • Skog L.
        • Ohlsson H.
        • Arvidsson D.
        Neighborhood walkability, physical activity, and walking behavior: the Swedish Neighborhood and Physical Activity (SNAP) study.
        Soc Sci Med. 2011; 72: 1266-1273
        • De Meester F.
        • Van Dyck D.
        • De Bourdeaudhuij I.
        • Deforche B.
        • Sallis J.F.
        • Cardon G.
        Active living neighborhoods: is neighborhood walkability a key element for Belgian adolescents?.
        BMC Public Health. 2012; 12: 7
        • Van Dyck D.
        • Cardon G.
        • Deforche B.
        • Sallis J.F.
        • Owen N.
        • De Bourdeaudhuij I.
        Neighborhood SES and walkability are related to physical activity behavior in Belgian adults.
        Prev Med. Jan 2010; 50: S74-S79
        • Frank L.D.
        • Schmid T.L.
        • Sallis J.F.
        • Chapman J.
        • Saelens B.E.
        Linking objectively measured physical activity with objectively measured urban form: findings from SMARTRAQ.
        Am J Prev Med. 2005; 28: 117-125
        • Manjoo P.
        • Joseph L.
        • Dasgupta K.
        Abdominal adiposity and daily step counts as determinants of glycemic control in a cohort of patients with type 2 diabetes mellitus.
        Nutr Diabetes. 2012; 2: e25
        • Dasgupta K.
        • Joseph L.
        • Pilote L.
        • Strachan I.
        • Sigal R.J.
        • Chan C.
        Daily steps are low year-round and dip lower in fall/winter: findings from a longitudinal diabetes cohort.
        Cardiovasc Diabetol. 2010; 9: 81
        • Manjoo P.
        • Joseph L.
        • Pilote L.
        • Dasgupta K.
        Sex differences in step count-blood pressure association: a preliminary study in type 2 diabetes.
        PLoS One. 2010; 5: e14086
        • Dasgupta K.
        • Chan C.
        • Da Costa D.
        • et al.
        Walking behaviour and glycemic control in type 2 diabetes: seasonal and gender differences—study design and methods.
        Cardiovasc Diabetol. 2007; 6: 1
        • Clifton K.J.
        • Smith L.A.
        • Rodriguez D.
        The development and testing of an audit for the pedestrian environment.
        Landscape Urban Plann. 2007; 80: 95-110
        • Leslie E.
        • Coffee N.
        • Frank L.
        • Owen N.
        • Bauman A.
        • Hugo G.
        Walkability of local communities: using geographic information systems to objectively assess relevant environmental attributes.
        Health Place. 2007; 13: 111-122
        • Brownson R.C.
        • Chang J.J.
        • Eyler A.A.
        • et al.
        Measuring the environment for friendliness toward physical activity: a comparison of the reliability of 3 questionnaires.
        Am J Public Health. 2004; 94: 473-483
        • Zandbergen P.A.
        • Chakraborty J.
        Improving environmental exposure analysis using cumulative distribution functions and individual geocoding.
        Int J Health Geogr. 2006; 5: 23
        • Patterson L.
        • Urban M.
        • Myers A.
        • Bhaduri B.
        • Bright E.
        • Coleman P.
        Assessing spatial and attribute errors in large national datasets for population distribution models: a case study of Philadelphia county schools.
        GeoJournal. 2007; 69: 93-102
        • Liese A.D.
        • Colabianchi N.
        • Lamichhane A.P.
        • et al.
        Validation of 3 food outlet databases: completeness and geospatial accuracy in rural and urban food environments.
        Am J Epidemiol. 2010; 172: 1324-1333
        • Purciel M.
        • Neckerman K.M.
        • Lovasi G.S.
        • et al.
        Creating and validating GIS measures of urban design for health research.
        J Environ Psychol. 2009; 29: 457-466
        • Hoehner C.M.
        • Brennan Ramirez L.K.
        • Elliott M.B.
        • Handy S.L.
        • Brownson R.C.
        Perceived and objective environmental measures and physical activity among urban adults.
        Am J Prev Med. 2005; 28: 105-116
        • Cao X.
        • Handy S.L.
        • Mokhtarian P.L.
        The influences of the built environment and residential self-selection on pedestrian behavior: evidence from Austin, TX.
        Transportation. 2006; 33: 1-20
        • Sir Edwin Chadwick
        (1800-1890) sanitarian and social reformer.
        JAMA. 1968; 203: 45-46
      2. WHO. WHO framework convention on tobacco control. Geneva, Switzerland: WHO Document Production Services, 2003. ISBN 9241591013.

        • American Diabetes Association
        Diagnosis and classification of diabetes mellitus.
        Diabetes Care. 2012; 35: S64-S71
        • Roy T.
        • Lloyd C.E.
        Epidemiology of depression and diabetes: a systematic review.
        J Affect Disord. 2012; 142: S8-S21

      Linked Article

      • Corrections
        American Journal of Preventive MedicineVol. 45Issue 3
        • Preview
          Hajna S, Dasgupta K, Halparin M, Ross NA. Neighborhood Walkability: Field Validation of Geographic Information System Measures. Am J Prev Med 2013;44(6):e51–e55.
        • Full-Text
        • PDF