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Neighborhood characteristics and depressive symptoms of older people: Local spatial analyses


  • Cromley, Ellen K.
  • Wilson-Genderson, Maureen
  • Pruchno, Rachel A.


Depressive symptoms in community-dwelling older people significantly increase the risk of developing clinically diagnosable depressive disorders. Knowledge of the spatial distribution of depressive symptoms in the older population can add important information to studies of neighborhood contextual factors and mental health outcomes, but analysis of spatial patterns is rarely undertaken. This study uses spatial statistics to explore patterns of clustering in depressive symptoms using data from a statewide survey of community-dwelling older people in New Jersey from 2006 to 2008. A significant overall pattern of clustering in depressive symptoms was observed at the state level. In a subsequent local clustering analysis, places with high levels of depressive symptoms near to other places with high levels of depressive symptoms were identified. The relationships between the level of depressive symptoms in a place and poverty, residential stability and crime were analyzed using geographically weighted regression. Significant local parameter estimates for the three independent variables were observed. Local parameters for the poverty variable were positive and significant almost everywhere in the state. The significant local parameters for residential stability and crime varied in their association with depressive symptoms in different regions of the state. This study is among the first to examine spatial patterns in depressive symptoms among community-dwelling older people, and it demonstrates the importance of exploring spatial variations in the relationships between neighborhood contextual factors and health outcomes.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:socmed:v:75:y:2012:i:12:p:2307-2316
    DOI: 10.1016/j.socscimed.2012.08.033

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    References listed on IDEAS

    1. A S Fotheringham & M E Charlton & C Brunsdon, 1998. "Geographically weighted regression: a natural evolution of the expansion method for spatial data analysis," Environment and Planning A, Pion Ltd, London, vol. 30(11), pages 1905-1927, November.
    2. A S Fotheringham & M E Charlton & C Brunsdon, 1998. "Geographically Weighted Regression: A Natural Evolution of the Expansion Method for Spatial Data Analysis," Environment and Planning A, , vol. 30(11), pages 1905-1927, November.
    3. Giggs, John A., 1986. "Mental disorders and ecological structure in Nottingham," Social Science & Medicine, Elsevier, vol. 23(10), pages 945-961, January.
    4. Curry, Aaron & Latkin, Carl & Davey-Rothwell, Melissa, 2008. "Pathways to depression: The impact of neighborhood violent crime on inner-city residents in Baltimore, Maryland, USA," Social Science & Medicine, Elsevier, vol. 67(1), pages 23-30, July.
    5. Carol S. Aneshensel & Richard G. Wight & Dana Miller-Martinez & Amanda L. Botticello & Arun S. Karlamangla & Teresa E. Seeman, 2007. "Urban Neighborhoods and Depressive Symptoms Among Older Adults," Journals of Gerontology: Series B, Gerontological Society of America, vol. 62(1), pages 52-59.
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    Cited by:

    1. Won, Jaewoong & Lee, Chanam & Forjuoh, Samuel N. & Ory, Marcia G., 2016. "Neighborhood safety factors associated with older adults' health-related outcomes: A systematic literature review," Social Science & Medicine, Elsevier, vol. 165(C), pages 177-186.


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