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Spatial Clustering Properties in the Temporal Variation of Suicide Rates/Numbers among Japanese Citizens: A Comprehensive Comparison and Discussion

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  • Makoto Tomita
  • Takafumi Kubota
  • Fumio Ishioka

Abstract

Objective: The number of suicides in Japan has remained high for many years. To effectively resolve this problem, firm understanding of the statistical data is required. Using a large quantity of wide-ranging data on Japanese citizens, the purpose of this study was to analyze the geographical clustering properties of suicides and how suicide rates have evolved over time, and to observe detailed patterns and trends in a variety of geographic regions. Methods: Using adjacency data from 2008, the spatial and temporal/spatial clustering structure of geographic statistics on suicides were clarified. Echelon scans were performed to identify regions with the highest-likelihood ratio of suicide as the most likely suicide clusters. Results: In contrast to results obtained using temporal/spatial analysis, the results of a period-by-period breakdown of evolving suicide rates demonstrated that suicides among men increased particularly rapidly during 1988–1992, 1993–1997, and 1998–2002 in certain cluster regions located near major metropolitan areas. For women, results identified cluster regions near major metropolitan areas in 1993–1997, 1998–2002, and 2003–2007. Conclusions: For both men and women, the cluster regions identified are located primarily near major metropolitan areas, such as greater Tokyo and Osaka.

Suggested Citation

  • Makoto Tomita & Takafumi Kubota & Fumio Ishioka, 2015. "Spatial Clustering Properties in the Temporal Variation of Suicide Rates/Numbers among Japanese Citizens: A Comprehensive Comparison and Discussion," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-11, July.
  • Handle: RePEc:plo:pone00:0127358
    DOI: 10.1371/journal.pone.0127358
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    Cited by:

    1. Ruth Benson & Jan Rigby & Christopher Brunsdon & Grace Cully & Lay San Too & Ella Arensman, 2022. "Quantitative Methods to Detect Suicide and Self-Harm Clusters: A Systematic Review," IJERPH, MDPI, vol. 19(9), pages 1-13, April.

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