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A Place-Oriented, Mixed-Level Regionalization Method for Constructing Geographic Areas in Health Data Dissemination and Analysis

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  • Lan Mu
  • Fahui Wang
  • Vivien W. Chen
  • Xiao-Cheng Wu

Abstract

Similar geographic areas often have great variations in population size. In health data management and analysis, it is desirable to obtain regions of comparable population by decomposing areas of large population (to gain more spatial variability) and merging areas of small population (to mask privacy of data). Based on the Peano curve algorithm and modified scale-space clustering, this research proposes a mixed-level regionalization (MLR) method to construct geographic areas with comparable population. The method accounts for spatial connectivity and compactness, attributive homogeneity, and exogenous criteria such as minimum (and approximately equal) population or disease counts. A case study using Louisiana cancer data illustrates the MLR method and its strengths and limitations. A major benefit of the method is that most upper level geographic boundaries can be preserved to increase familiarity of constructed areas. Therefore, the MLR method is more human-oriented and place-based than computer-oriented and space-based.

Suggested Citation

  • Lan Mu & Fahui Wang & Vivien W. Chen & Xiao-Cheng Wu, 2015. "A Place-Oriented, Mixed-Level Regionalization Method for Constructing Geographic Areas in Health Data Dissemination and Analysis," Annals of the American Association of Geographers, Taylor & Francis Journals, vol. 105(1), pages 48-66, January.
    • Handle: RePEc:taf:raagxx:v:105:y:2015:i:1:p:48-66
    DOI: 10.1080/00045608.2014.968910
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    Cited by:

    1. O'Connell, Heather A., 2015. "Where there's smoke: Cigarette use, social acceptability, and spatial approaches to multilevel modeling," Social Science & Medicine, Elsevier, vol. 140(C), pages 18-26.
    2. Hyunjoong Kim & Fahui Wang, 2019. "Disparity in Spatial Access to Public Daycare and Kindergarten across GIS-Constructed Regions in Seoul, South Korea," Sustainability, MDPI, vol. 11(19), pages 1-14, October.

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