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An Information Statistical Approach to the Modifiable Areal Unit Problem in Incidence Rate Maps

Author

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  • Tomoki Nakaya

    (Department of Geography, Ritsumeikan University Kita-ku, Kyoto 603-8577, Japan)

Abstract

The modifiable areal unit problem becomes apparent when incidence rates are mapped on the basis of areal units. Although small units with high spatial accuracy can present unreliable rates, large spatial units may remove relevant geographical variation. Regarding mapping as a kind of statistical modelling, this author proposes a new methodology to select appropriate areal units using the Akaike information criterion and two search methods for an informative geographical aggregation in map construction. The optimal zoning of similarity is suitable for finding spatial anomalies but presents a biased overall pattern. An alternative approach is to cluster areal units according to explanatory variables: this shows clear spatial patterns of elderly men's mortality matching the ecological structure in the Tokyo metropolitan area.

Suggested Citation

  • Tomoki Nakaya, 2000. "An Information Statistical Approach to the Modifiable Areal Unit Problem in Incidence Rate Maps," Environment and Planning A, , vol. 32(1), pages 91-109, January.
    • Handle: RePEc:sae:envira:v:32:y:2000:i:1:p:91-109
    DOI: 10.1068/a31145
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    References listed on IDEAS

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    1. Peter J. B. Brown & Alexander Hirschfield & Peter W. J. Batey, 1991. "Applications Of Geodemographic Methods In The Analysis Of Health Condition Incidence Data," Papers in Regional Science, Wiley Blackwell, vol. 70(3), pages 329-344, July.
    2. Mayer, Jonathan D., 1983. "The role of spatial analysis and geographic data in the detection of disease causation," Social Science & Medicine, Elsevier, vol. 17(16), pages 1213-1221, January.
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    2. Sun, Yeran & Wang, Shaohua & Zhang, Xucai & Chan, Ting On & Wu, Wenjie, 2021. "Estimating local-scale domestic electricity energy consumption using demographic, nighttime light imagery and Twitter data," Energy, Elsevier, vol. 226(C).
    3. Abolfazl Mollalo & Alireza Mohammadi & Sara Mavaddati & Behzad Kiani, 2021. "Spatial Analysis of COVID-19 Vaccination: A Scoping Review," IJERPH, MDPI, vol. 18(22), pages 1-14, November.
    4. Jamie Spinney & Pavlos Kanaroglou & Darren Scott, 2011. "Exploring Spatial Dynamics with Land Price Indexes," Urban Studies, Urban Studies Journal Limited, vol. 48(4), pages 719-735, March.
    5. Ortega, Emilio & López, Elena & Monzón, Andrés, 2014. "Territorial cohesion impacts of high-speed rail under different zoning systems," Journal of Transport Geography, Elsevier, vol. 34(C), pages 16-24.
    6. Juan C Duque & Henry Laniado & Adriano Polo, 2018. "S-maup: Statistical test to measure the sensitivity to the modifiable areal unit problem," PLOS ONE, Public Library of Science, vol. 13(11), pages 1-25, November.
    7. You, Liangzhi & Wood, Stanley, 2006. "An entropy approach to spatial disaggregation of agricultural production," Agricultural Systems, Elsevier, vol. 90(1-3), pages 329-347, October.
    8. Kelvyn Jones & David Manley & Ron Johnston & Dewi Owen, 2018. "Modelling residential segregation as unevenness and clustering: A multilevel modelling approach incorporating spatial dependence and tackling the MAUP," Environment and Planning B, , vol. 45(6), pages 1122-1141, November.
    9. James A. Cheshire & Paul A. Longley & Keiji Yano & Tomoki Nakaya, 2014. "Japanese surname regions," Papers in Regional Science, Wiley Blackwell, vol. 93(3), pages 539-555, August.
    10. Jared Hewko & Karen E Smoyer-Tomic & M John Hodgson, 2002. "Measuring Neighbourhood Spatial Accessibility to Urban Amenities: Does Aggregation Error Matter?," Environment and Planning A, , vol. 34(7), pages 1185-1206, July.
    11. B. d'Hombres & L. Rocco & M. Suhrcke & M. McKee, 2010. "Does social capital determine health? Evidence from eight transition countries," Health Economics, John Wiley & Sons, Ltd., vol. 19(1), pages 56-74, January.
    12. Briggs, David & Abellan, Juan J. & Fecht, Daniela, 2008. "Environmental inequity in England: Small area associations between socio-economic status and environmental pollution," Social Science & Medicine, Elsevier, vol. 67(10), pages 1612-1629, November.
    13. Nathaniel Bell & Nadine Schuurman, 2010. "GIS and Injury Prevention and Control: History, Challenges, and Opportunities," IJERPH, MDPI, vol. 7(3), pages 1-16, March.

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