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Spatial clustering of suicide mortality and associated community characteristics in Kanagawa prefecture, Japan, 2011–2017

BACKGROUND: Suicide mortality is high in Japan and early interventional strategies to solve that problem are needed. An accurate evaluation of the regional status of current suicide mortality would be useful for community interventions. A few studies in Kanagawa prefecture, located next to Tokyo and...

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Autores principales: Yamaoka, Kazue, Suzuki, Masako, Inoue, Mariko, Ishikawa, Hirono, Tango, Toshiro
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029524/
https://www.ncbi.nlm.nih.gov/pubmed/32070316
http://dx.doi.org/10.1186/s12888-020-2479-7
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author Yamaoka, Kazue
Suzuki, Masako
Inoue, Mariko
Ishikawa, Hirono
Tango, Toshiro
author_facet Yamaoka, Kazue
Suzuki, Masako
Inoue, Mariko
Ishikawa, Hirono
Tango, Toshiro
author_sort Yamaoka, Kazue
collection PubMed
description BACKGROUND: Suicide mortality is high in Japan and early interventional strategies to solve that problem are needed. An accurate evaluation of the regional status of current suicide mortality would be useful for community interventions. A few studies in Kanagawa prefecture, located next to Tokyo and with the second largest population in Japan, have identified spatial clusters of suicide mortality at regional levels. This study examined spatial clustering and clustering over time of such events using spatial data from regional statistics on suicide deaths. METHODS: Data were obtained from regional statistics (58 regions in Kanagawa prefecture) of the National Vital Statistics of Japan from 2011 to 2017. The standardized mortality ratio (SMR) and Empirical Bayes estimator for the SMR (EBSMR) were used as measures. Spatial clusters were examined by Kulldorff’s circular spatial scan statistic, Tango-Takahashi’s flexible spatial scan statistic and Tango’s test. Linear regression and conditional autoregressive (CAR) models were used not only to adjust for covariates but also to estimate regional effects. The analyses were conducted for each year, inclusive. RESULTS: Among male suicide deaths, being unemployed (50%) was most frequently related to suicide while among female health problem (50%) were frequent. Spatial clusters with significance detected by FlexScan, SatScan and Tango’s test were few and varied somewhat according to the method used. Spatial clusters were detected in some regions including Kawasaki ward after adjustment by covariates. By the linear regression models, selected variables with significance were different between the sexes. For males, unemployment, family size, and proportion of higher education were detected for several of the years studied while for females, family size and divorce rate were detected over this period. These variables were also observed by the CAR model with 5 covariates. Regional effects were much clearer by considering the spatial parameter for both males and females and especially, Kawasaki ward was detected as a high risk region in many years. CONCLUSION: The present results detected some spatial clustering of suicide deaths within certain regions. Factors related to suicide deaths were also indicated. These results would provide important information in policy making for suicide prevention.
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spelling pubmed-70295242020-02-25 Spatial clustering of suicide mortality and associated community characteristics in Kanagawa prefecture, Japan, 2011–2017 Yamaoka, Kazue Suzuki, Masako Inoue, Mariko Ishikawa, Hirono Tango, Toshiro BMC Psychiatry Research Article BACKGROUND: Suicide mortality is high in Japan and early interventional strategies to solve that problem are needed. An accurate evaluation of the regional status of current suicide mortality would be useful for community interventions. A few studies in Kanagawa prefecture, located next to Tokyo and with the second largest population in Japan, have identified spatial clusters of suicide mortality at regional levels. This study examined spatial clustering and clustering over time of such events using spatial data from regional statistics on suicide deaths. METHODS: Data were obtained from regional statistics (58 regions in Kanagawa prefecture) of the National Vital Statistics of Japan from 2011 to 2017. The standardized mortality ratio (SMR) and Empirical Bayes estimator for the SMR (EBSMR) were used as measures. Spatial clusters were examined by Kulldorff’s circular spatial scan statistic, Tango-Takahashi’s flexible spatial scan statistic and Tango’s test. Linear regression and conditional autoregressive (CAR) models were used not only to adjust for covariates but also to estimate regional effects. The analyses were conducted for each year, inclusive. RESULTS: Among male suicide deaths, being unemployed (50%) was most frequently related to suicide while among female health problem (50%) were frequent. Spatial clusters with significance detected by FlexScan, SatScan and Tango’s test were few and varied somewhat according to the method used. Spatial clusters were detected in some regions including Kawasaki ward after adjustment by covariates. By the linear regression models, selected variables with significance were different between the sexes. For males, unemployment, family size, and proportion of higher education were detected for several of the years studied while for females, family size and divorce rate were detected over this period. These variables were also observed by the CAR model with 5 covariates. Regional effects were much clearer by considering the spatial parameter for both males and females and especially, Kawasaki ward was detected as a high risk region in many years. CONCLUSION: The present results detected some spatial clustering of suicide deaths within certain regions. Factors related to suicide deaths were also indicated. These results would provide important information in policy making for suicide prevention. BioMed Central 2020-02-18 /pmc/articles/PMC7029524/ /pubmed/32070316 http://dx.doi.org/10.1186/s12888-020-2479-7 Text en © The Author(s). 2020 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Yamaoka, Kazue
Suzuki, Masako
Inoue, Mariko
Ishikawa, Hirono
Tango, Toshiro
Spatial clustering of suicide mortality and associated community characteristics in Kanagawa prefecture, Japan, 2011–2017
title Spatial clustering of suicide mortality and associated community characteristics in Kanagawa prefecture, Japan, 2011–2017
title_full Spatial clustering of suicide mortality and associated community characteristics in Kanagawa prefecture, Japan, 2011–2017
title_fullStr Spatial clustering of suicide mortality and associated community characteristics in Kanagawa prefecture, Japan, 2011–2017
title_full_unstemmed Spatial clustering of suicide mortality and associated community characteristics in Kanagawa prefecture, Japan, 2011–2017
title_short Spatial clustering of suicide mortality and associated community characteristics in Kanagawa prefecture, Japan, 2011–2017
title_sort spatial clustering of suicide mortality and associated community characteristics in kanagawa prefecture, japan, 2011–2017
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7029524/
https://www.ncbi.nlm.nih.gov/pubmed/32070316
http://dx.doi.org/10.1186/s12888-020-2479-7
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