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Use of Geographic Information Systems to Explore Associations between Neighborhood Attributes and Mental Health Outcomes in Adults: A Systematic Review

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  • Young-Shin Park

    (School of Nursing, University of Minnesota, Minneapolis, MN 55455, USA
    Mo-Im Kim Nursing Research Institute, College of Nursing, Yonsei University, Seoul 03722, Korea)

  • Barbara J. McMorris

    (School of Nursing, University of Minnesota, Minneapolis, MN 55455, USA)

  • Lisiane Pruinelli

    (School of Nursing, University of Minnesota, Minneapolis, MN 55455, USA)

  • Ying Song

    (Geography, Environment and Society, University of Minnesota, Minneapolis, MN 03722, USA)

  • Merrie J. Kaas

    (School of Nursing, University of Minnesota, Minneapolis, MN 55455, USA)

  • Jean F. Wyman

    (School of Nursing, University of Minnesota, Minneapolis, MN 55455, USA)

Abstract

Background: Neighborhood attributes are increasingly recognized as factors shaping mental health in adults. Geographic information systems (GIS) offer an innovative approach for quantifying neighborhood attributes and studying their influence on mental health outcomes. Our aim was to describe GIS applications used in neighborhood-related mental health research and how neighborhood attributes are related to depressive symptoms or psychological distress in community-residing adults. Methods: We conducted a systematic review of studies published in English that included GIS techniques and a validated questionnaire of depressive symptoms or psychological distress. Medline, PsycInfo, Embase, Scopus, CINAHL, GEOBASE, and Compedex were searched to June 2020. Study quality was assessed by a modification of the Joanna Briggs Institute’s Checklist for Analytical Cross-sectional Studies. Results: Thirty-two studies met the inclusion criteria. Studies varied in definitions of neighborhood and GIS-derived measurements of neighborhood attributes. Neighborhood attributes were significantly associated with mental health outcomes, although findings were not consistent. Moderating factors (e.g., gender, living conditions) significantly influenced depressive symptoms or psychological distress. Conclusion: Neighborhood attributes are important factors influencing mental health in adults. Consensus may be needed on how to standardize the neighborhood unit or GIS-derived measures of neighborhoods in order to explain depression or psychological distress in diverse adult populations.

Suggested Citation

  • Young-Shin Park & Barbara J. McMorris & Lisiane Pruinelli & Ying Song & Merrie J. Kaas & Jean F. Wyman, 2021. "Use of Geographic Information Systems to Explore Associations between Neighborhood Attributes and Mental Health Outcomes in Adults: A Systematic Review," IJERPH, MDPI, vol. 18(16), pages 1-28, August.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:16:p:8597-:d:614424
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    References listed on IDEAS

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    1. Kirsten M. M. Beyer & Andrea Kaltenbach & Aniko Szabo & Sandra Bogar & F. Javier Nieto & Kristen M. Malecki, 2014. "Exposure to Neighborhood Green Space and Mental Health: Evidence from the Survey of the Health of Wisconsin," IJERPH, MDPI, vol. 11(3), pages 1-20, March.
    2. Cromley, Ellen K. & Wilson-Genderson, Maureen & Pruchno, Rachel A., 2012. "Neighborhood characteristics and depressive symptoms of older people: Local spatial analyses," Social Science & Medicine, Elsevier, vol. 75(12), pages 2307-2316.
    3. Matilda Annerstedt Van den Bosch & Per-Olof Östergren & Patrik Grahn & Erik Skärbäck & Peter Währborg, 2015. "Moving to Serene Nature May Prevent Poor Mental Health—Results from a Swedish Longitudinal Cohort Study," IJERPH, MDPI, vol. 12(7), pages 1-16, July.
    4. Yongxin Deng, 2016. "Challenges and complications in neighborhood mapping: from neighborhood concept to operationalization," Journal of Geographical Systems, Springer, vol. 18(3), pages 229-248, July.
    5. David Moher & Alessandro Liberati & Jennifer Tetzlaff & Douglas G Altman & The PRISMA Group, 2009. "Preferred Reporting Items for Systematic Reviews and Meta-Analyses: The PRISMA Statement," PLOS Medicine, Public Library of Science, vol. 6(7), pages 1-6, July.
    6. Hung Chak Ho & Kevin Ka-Lun Lau & Ruby Yu & Dan Wang & Jean Woo & Timothy Chi Yui Kwok & Edward Ng, 2017. "Spatial Variability of Geriatric Depression Risk in a High-Density City: A Data-Driven Socio-Environmental Vulnerability Mapping Approach," IJERPH, MDPI, vol. 14(9), pages 1-16, August.
    7. Médicoulé Traoré & Cécile Vuillermoz & Pierre Chauvin & Séverine Deguen, 2020. "Influence of Individual and Contextual Perceptions and of Multiple Neighborhoods on Depression," IJERPH, MDPI, vol. 17(6), pages 1-20, March.
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