Social Indicators Research

, Volume 127, Issue 2, pp 565–576 | Cite as

Conceptualising and Measuring Spatial Indicators of Employment Through a Liveability Lens

  • Hannah BadlandEmail author
  • Melanie Davern
  • Karen Villanueva
  • Suzanne Mavoa
  • Allison Milner
  • Rebecca Roberts
  • Billie Giles-Corti


Employment is a well-known social determinant of health and wellbeing and important for the liveability of a region. Yet, spatial data are rarely used to understand barriers and facilitators of accessing employment within a city. Therefore it remains challenging to plan cities that provide equitable opportunities for urban job seekers. This paper sought to: (1) identify urban planning and neighbourhood spatial attributes that facilitate access to employment; (2) conceptualise how neighbourhood attributes that facilitate accessible urban employment may be related to health and wellbeing behaviours and outcomes; and (3) isolate potentially important neighbourhood-level spatial measures that policy-makers and planners could use to assess urban employment accessibility. A conceptual framework was developed through a social determinants of health lens, where more upstream (e.g., neighbourhood attributes) and more downstream (e.g., behaviours, intermediate outcomes) determinants of urban employment were identified in relation to long-term health and social outcomes of interest. Six potential neighbourhood spatial measures of employment were identified. These were classified into measures of: access to employment (n = 4), local employment (n = 1), and neighbourhood employment level (n = 1). The spatial measures proposed rely on routinely collected administrative datasets existing within Australia (i.e., census data); therefore can be replicated over time and data are available nationally. Together, this research identified a suite of potential (and readily available) spatial measures that can be used to assess selected neighbourhood attributes as they relate to urban employment access. Such spatial measures can be used to inform future planning decisions that integrate policies across multiple sectors, thereby improving employment accessibility in an urban context.


Geographical information systems Liveability Policy Social determinants of health Urban planning 



This work was supported by the NHMRC Centre for Excellence in Healthy Liveable Communities (No. 1061404) and The Australian Prevention Partnership Centre (TAPPC) (the latter is supported by NHMRC, ACT Health, NSW Health, the Australian National Preventive Health Agency (ANPHA), the Hospitals Contribution Fund of Australia (HCF) and the HCF Research Foundation). BGC is supported by an NHMRC Principal Research Fellow Award (No. 1004900). All authors are in part, supported by VicHealth.

Conflict of interest



  1. Australian Bureau of Statistics. (2011a). Australian rural profile. Canberra: Australian Bureau of Statistics.Google Scholar
  2. Australian Bureau of Statistics. (2011b). Statistical geography fact sheet. Canberra: Australian Bureau of Statistics.Google Scholar
  3. Australian Bureau of Statistics. (2012). New data from the 2011 census released today: Occupation.Google Scholar
  4. Badland, H., Hickey, S., Bull, F., & Giles-Corti, B. (2014a). Public transport access and availability in the RESIDE study: Is it taking us where we want to go? Journal of Transport and Health, 1, 45–49.CrossRefGoogle Scholar
  5. Badland, H., Schofield, G., & Schluter, P. (2007). Objectively measured commute distance: Associations with actual travel modes and perceptions to place of work or study in Auckland, New Zealand. Journal of Physical Activity & Health, 4(1), 80–86.Google Scholar
  6. Badland, H., Whitzman, C., Lowe, M., Davern, M., Aye, L., Butterworth, I., et al. (2014b). Urban liveability: Emerging lessons from Australia for exploring the potential for indicators to measure the social determinants of health. Social Science and Medicine, 111, 64–73.CrossRefGoogle Scholar
  7. Baum, F., Ziersch, A., Zhang, G., & Osborne, K. (2009). Do perceived neighbourhood cohesion and safety cohesion contribute to neighbourhood differences in health? Health & Place, 15(4), 925–934.CrossRefGoogle Scholar
  8. Brownson, R., Boehmer, T., & Luke, D. (2005). Declining rates of physical activity in the United States: What are the contributors? Annual Review of Public Health, 26, 421–443.CrossRefGoogle Scholar
  9. Cervero, R., & Duncan, M. (2006). Which reduces vehicle travel more: Jobs-housing balance or retail-housing mixing? Journal of the American Planning Association, 72(4), 475–490.CrossRefGoogle Scholar
  10. Chaloff, J. (2008). Management of low-skilled labour migration. International migration outlook. Paris: OECD.Google Scholar
  11. Chandola, T., Ferrie, J., Sacker, A., & Marmot, M. (2007). Social inequities in self-reported health in early old age: Follow-up of prospective cohort study. BMJ, 334(7601), 990–994.CrossRefGoogle Scholar
  12. Currie, G., & Delbosc, A. (2011). Mobility vs. affordability as motivations for car ownership choice in urban fringe, low income Australia. In K. Lucas, E. Blumenberg, & R. Weinberger (Eds.), Auto motives: Understansing car use behaviours (pp. 193–208). Bingley: Emerald Publishing Group.CrossRefGoogle Scholar
  13. Department for Transport. (2013). National travel survey statistics. London: Department for Transport.Google Scholar
  14. Department of State Development, B. a. I. (2013). Industry atlas of Victoria 2013. Melbourne: Department of State Development, Business and Innovation.Google Scholar
  15. Dobbs, L. (2005). Wedded to the car: Women, employment, and the importance of private transport. Transport Policy, 12(3), 266–278.CrossRefGoogle Scholar
  16. Florida, R. (2011). The rise of the creative class: Revisited. New York: Basic Books.Google Scholar
  17. Frank, L., Andresen, M., & Schmid, T. (2004). Obesity relationships with community design, physical activity, and time spent in cars. American Journal of Preventive Medicine, 27(2), 87–96.CrossRefGoogle Scholar
  18. Galster, G. (2010). The mechanism(s) of neighborhood effects. Theory, evidence, and policy implications. Paper presented at the ESRC seminar: Neighbourhood effects: Theory & evidence. Scotland: St Andrews University. February 4–5.Google Scholar
  19. Jackson, L. (2003). The relationship of urban design to human health and condition. Landscape and Urban Planning, 64, 191–200.CrossRefGoogle Scholar
  20. Kjellstrom, T., & Hinde, S. (2006). Car culture, transport policy, and public health. In I. Kawachi & S. Wamala (Eds.), Globalization and health (pp. 98–121). New York: Oxford University Press.CrossRefGoogle Scholar
  21. Korsu, E., & Wenglenski, S. (2010). Job accessibility, residential segregation and risk on long-term unemployment in the Paris region. Urban Studies, 47, 2279–2324.CrossRefGoogle Scholar
  22. Kwan, M.-P. (2012). The uncertain geographic context problem. Annals of the Association of American Geographers, 102(5), 958–968.CrossRefGoogle Scholar
  23. Learnihan, V., Van Neil, K., Giles-Corti, B., & Knuiman, M. (2011). Effect of scale on the links between walking and urban design. Geographical Research, 49(2), 183–191.CrossRefGoogle Scholar
  24. Lowe, M., Whitzman, C., Badland, H., Davern, M., Hes, D., Aye, L., et al. (2013). Liveable, health, sustainable: What are the key indicators for Melbourne neighbourhoods? In Place, health, and liveability research program (Vol. Research paper 1). University of Melbourne.Google Scholar
  25. Lyseen, A., Nøhr, C., Sørensen, E., Gudes, O., Geraghty, E., Shaw, N., et al. (2014). A review and framework for categorizing current research and development in health related geographical information systems (GIS) studies. Yearbook of Medical Informatics, 9, 110–124.CrossRefGoogle Scholar
  26. Mackinnon, D., Krull, J., & Lockwood, C. (2000). Equivalence of the mediation, confounding and suppression effect. Preventive Science, 1, 173–181.CrossRefGoogle Scholar
  27. Milner, A., Kavanagh, A., Krnjacki, L., Bentley, R., & LaMontagne, A. (2013). Area-level unemployment and job insecurity: Evidence from a longitudinal study conducted in the Australian working age population. Annuals of Occupational Hygiene,. doi: 10.1093/annhyg/met066.Google Scholar
  28. Milner, A., Page, S., & LaMontagne, A. (2014). Cause and effect in studies of unemployment, mental health, and suicide: A meta-analytic and conceptual review. Psychological Medicine, 44, 909–917.CrossRefGoogle Scholar
  29. Milner, A., Smith, P., & LaMontagne, A. (under review). Working hours and mental health: Evidence from an Australian population-based cohort, 2001 to 2012. Occupational and Environmental Medicine.Google Scholar
  30. New South Wales Planning and Infrastructure. (2014). Community guide: Draft metropolitan strategy for Sydney to 2031. Sydney: New South Wales Planning and Infrastructure.Google Scholar
  31. Roberts, K. (2012). Country note: Australia. Education at a glance: OECD indicators 2012. Paris: OECD.Google Scholar
  32. Roelfs, D., Shor, E., Davidson, K., & Schwartz, J. (2011). Losing life and livelihood: A systematic review and meta-analysis of unemployment and all-cause mortality. Social Science and Medicine, 72, 840–854.CrossRefGoogle Scholar
  33. Sanchez, T. (1999). The connection between public transit and employment. Journal of the American Planning Association, 65(3), 284–297.CrossRefGoogle Scholar
  34. State Government Victoria. (2014). Plan Melbourne. Metropolitan planning strategy 2014. Melbourne: State Government Victoria.Google Scholar
  35. Stoll, M. (2005). Geographical skills mismatch, job search and race. Urban Studies, 42, 695–717.CrossRefGoogle Scholar
  36. Strategic Review of Health Inequalities in England post-2010. (2010). Fair society, healthy lives. London: Department of Health.Google Scholar
  37. Theorell, T. (2000). Working conditions and health. In L. Berkman & I. Kawachi (Eds.), Social epidemiology (pp. 95–117). New York: Oxford University Press.Google Scholar
  38. US Department of Transportation, & Bureau of Transportation Statistics. (2003). NHTS: Highlights of the 2001 national household travel survey. Washington: US Department Transport Bureau and Transportation Statistics.Google Scholar
  39. van Lenthe, F., Borrell, L., Costa, G., Diez Roux, A., Kauppinen, T., Marinacci, C., et al. (2005). Neighbourhood unemployment and all cause mortality: A comparison of six countries. Journal of Epidemiology and Community Health, 59, 231–237.CrossRefGoogle Scholar
  40. Van Rooy, D. (2006). Effects of automobile commute characteristics on affect and job candidate evaluations. Environment and Behavior, 38(5), 626–655.CrossRefGoogle Scholar
  41. Warr, D., Feldman, P., Tacticos, T., & Kelaher, M. (2009). Sources of stress in impoverished neighbourhoods: Insights into links between neighbourhood environments and health. Australian and New Zealand Journal of Public Health, 33(1), 25–35.CrossRefGoogle Scholar
  42. Weir, M., Weintraub, J., Humphreys, E., Seto, E., & Bhatia, R. (2009). An area-level model of vehicle-pedestrian injury collisions with implications for land use and transportation planning. Accident Analysis and Prevention, 41(1), 137–145.CrossRefGoogle Scholar
  43. Western Australian Planning Commission, & Department for Planning and Infrastructure. (2009). Liveable neighbourhoods: A Western Australian Government sustainable cities initiative (2nd ed.). Perth: Western Australian Planning Commission.Google Scholar
  44. Wilkinson, R., & Marmot, M. (2003). Social determinants of health: The solid facts. Copenhagen: World Health Organization.Google Scholar
  45. Wilson, J. (2000). Volunteering. Annual Review of Sociology, 26, 215–240.CrossRefGoogle Scholar
  46. Wilson, K., Stemp, K., & McGinty, S. (2011). Re-engaging young people with education and training. What are the alternatives. Youth Studies Australia, 30, 32–39.Google Scholar
  47. Zhao, P., Lu, B., & de Roo, G. (2011). The impact of urban growth on commuting patterns in a restructuring city: Evidence from Beijing. Papers in Regional Science, 90, 735–754.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2015

Authors and Affiliations

  1. 1.McCaughey VicHealth Centre for Community Wellbeing, Melbourne School of Population and Global HealthThe University of MelbourneMelbourneAustralia

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