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Residential Area Sociodemographic and Breast Cancer Screening Venue Location Built Environmental Features Associated with Women’s Use of Closest Venue in Greater Sydney, Australia

Author

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  • Jahidur Rahman Khan

    (Australian Geospatial Health Laboratory, Health Research Institute, University of Canberra, Canberra, ACT 2617, Australia
    School of Health Sciences, University of South Australia, Adelaide, SA 5000, Australia)

  • Suzanne J. Carroll

    (Australian Geospatial Health Laboratory, Health Research Institute, University of Canberra, Canberra, ACT 2617, Australia)

  • Neil T. Coffee

    (Australian Geospatial Health Laboratory, Health Research Institute, University of Canberra, Canberra, ACT 2617, Australia
    Housing and Healthy Cities Research Group, School of Architecture and Built Environment, University of Adelaide, Adelaide, SA 5005, Australia)

  • Matthew Warner-Smith

    (Cancer Institute NSW, St Leonards, Sydney, NSW 2065, Australia)

  • David Roder

    (School of Health Sciences, University of South Australia, Adelaide, SA 5000, Australia
    Cancer Institute NSW, St Leonards, Sydney, NSW 2065, Australia)

  • Mark Daniel

    (Australian Geospatial Health Laboratory, Health Research Institute, University of Canberra, Canberra, ACT 2617, Australia
    Department of Medicine, St. Vincent’s Hospital, The University of Melbourne, Fitzroy, VIC 3065, Australia)

Abstract

Understanding environmental predictors of women’s use of closest breast screening venue versus other site(s) may assist optimal venue placement. This study assessed relationships between residential-area sociodemographic measures, venue location features, and women’s use of closest versus other venues. Data of 320,672 Greater Sydney screening attendees were spatially joined to residential state suburbs (SSCs) ( n = 799). SSC-level sociodemographic measures included proportions of: women speaking English at home; university-educated; full-time employed; and dwellings with motor-vehicles. A geographic information system identified each woman’s closest venue to home, and venue co-location with bus-stop, train-station, hospital, general practitioner, and shop(s). Multilevel logistic models estimated associations between environmental measures and closest venue attendance. Attendance at closest venue was 59.4%. Closest venue attendance was positively associated with SSC-level women speaking English but inversely associated with SSC-level women university-educated, full-time employed, and dwellings with motor-vehicles. Mobile venue co-location with general practitioner and shop was positively, but co-location with bus-stop and hospital was inversely associated with attendance. Attendance was positively associated with fixed venue co-location with train-station and hospital but inversely associated with venue co-location with bus-stop, general practitioner, and shop. Program planners should consider these features when optimising service locations to enhance utilisation. Some counterintuitive results necessitate additional investigation.

Suggested Citation

  • Jahidur Rahman Khan & Suzanne J. Carroll & Neil T. Coffee & Matthew Warner-Smith & David Roder & Mark Daniel, 2021. "Residential Area Sociodemographic and Breast Cancer Screening Venue Location Built Environmental Features Associated with Women’s Use of Closest Venue in Greater Sydney, Australia," IJERPH, MDPI, vol. 18(21), pages 1-12, October.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:21:p:11277-:d:665824
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    References listed on IDEAS

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    1. Hurley, S.F. & Huggins, R.M. & Jolley, D.J. & Reading, D., 1994. "Recruitment activities and sociodemographic factors that predict attendance at a mammographic screening program," American Journal of Public Health, American Public Health Association, vol. 84(10), pages 1655-1658.
    2. Vedat Verter & Sophie Lapierre, 2002. "Location of Preventive Health Care Facilities," Annals of Operations Research, Springer, vol. 110(1), pages 123-132, February.
    3. Wang, Lu & Rosenberg, Mark & Lo, Lucia, 2008. "Ethnicity and utilization of family physicians: A case study of Mainland Chinese immigrants in Toronto, Canada," Social Science & Medicine, Elsevier, vol. 67(9), pages 1410-1422, November.
    4. Navneet Vidyarthi & Onur Kuzgunkaya, 2015. "The impact of directed choice on the design of preventive healthcare facility network under congestion," Health Care Management Science, Springer, vol. 18(4), pages 459-474, December.
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