Loading…
Estimation of Socioeconomic Inequalities in Mortality in Japan Using National Census-linked Longitudinal Mortality Data
Background: We aimed to develop census-linked longitudinal mortality data for Japan and assess their validity as a new resource for estimating socioeconomic inequalities in health.Methods: Using deterministic linkage, we identified, from national censuses for 2000 and 2010 and national death records...
Saved in:
Published in: | Journal of Epidemiology 2023/05/05, Vol.33(5), pp.246-255 |
---|---|
Main Authors: | , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
cited_by | cdi_FETCH-LOGICAL-c693t-c0a9f7267626adf78146b9f7a828938b4a7485acdf95b1157ca14bba13d5e2043 |
---|---|
cites | cdi_FETCH-LOGICAL-c693t-c0a9f7267626adf78146b9f7a828938b4a7485acdf95b1157ca14bba13d5e2043 |
container_end_page | 255 |
container_issue | 5 |
container_start_page | 246 |
container_title | Journal of Epidemiology |
container_volume | 33 |
creator | Tanaka, Hirokazu Mackenbach, Johan P. Kobayashi, Yasuki |
description | Background: We aimed to develop census-linked longitudinal mortality data for Japan and assess their validity as a new resource for estimating socioeconomic inequalities in health.Methods: Using deterministic linkage, we identified, from national censuses for 2000 and 2010 and national death records, persons and deceased persons who had unique personal identifiers (generated using sex, birth year/month, address, and marital status). For the period 2010–2015, 1,537,337 Japanese men and women aged 30–79 years (1.9% in national census) were extracted to represent the sample population. This population was weighted to adjust for confounding factors. We estimated age-standardized mortality rates (ASMRs) by education level and occupational class. The slope index of inequality (SII) and relative index inequality (RII) by educational level were calculated as inequality measures.Results: The reweighted sample population’s mortality rates were somewhat higher than those of the complete registry, especially in younger age-groups and for external causes. All-cause ASMRs (per 100,000 person-years) for individuals aged 40–79 years with high, middle, and low education levels were 1,078 (95% confidence interval [CI], 1,051–1,105), 1,299 (95% CI, 1,279–1,320), and 1,670 (95% CI, 1,634–1,707) for men, and 561 (95% CI, 536–587), 601 (95% CI, 589–613), and 777 (95% CI, 745–808) for women, respectively, during 2010–2015. SII and RII by educational level increased among both sexes between 2000–2005 and 2010–2015, which indicates that mortality inequalities increased.Conclusion: The developed census-linked longitudinal mortality data provide new estimates of socioeconomic inequalities in Japan that can be triangulated with estimates obtained with other methods. |
doi_str_mv | 10.2188/jea.JE20210106 |
format | article |
fullrecord | <record><control><sourceid>proquest_doaj_</sourceid><recordid>TN_cdi_doaj_primary_oai_doaj_org_article_b50532f436cf4d06a05cc0151718baa7</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><doaj_id>oai_doaj_org_article_b50532f436cf4d06a05cc0151718baa7</doaj_id><sourcerecordid>2822802500</sourcerecordid><originalsourceid>FETCH-LOGICAL-c693t-c0a9f7267626adf78146b9f7a828938b4a7485acdf95b1157ca14bba13d5e2043</originalsourceid><addsrcrecordid>eNpVUc1v0zAUtxCIlcKVcyTO6fwRO84Joa6wTgUOsLP14jiZQ2p3tjO0_55kHa12sfXe78Pv-YfQR4JXlEh52RtY3WwopgQTLF6hBWFFlVe4oq_RAlekzDku8AV6F2OPMROS4rfoghWCVkywBfq7icnuIVnvMt9mv7y23mjv_N7qbOvM_QiDTdbEzLrsuw9pLh_n4gYO4LLbaF2X_XgygCFbGxfHmA_W_TFNtvOus2ls7AydxVeQ4D1608IQzYfne4luv25-r6_z3c9v2_WXXa5FxVKuMVRtSUUpqICmLSUpRD11QFJZMVkXUBaSg27aiteE8FIDKeoaCGu4obhgS7Q9-jYeenUI067hUXmw6qnhQ6cgJKsHo2qOOaNtwYRuiwYLwFxrTDgpiawBysnr89HrMNZ702jjUoDhhelLxNk71fkHRfA0CeHzNJ-eHYK_H01MqvdjmH4nKioplZjyKaQlWh1ZOvgYg2lPTxCs5tTVlLo6pz4Jro6CPibozIn-f7OZzpji83GWnWB9B0EZx_4BGwy4Iw</addsrcrecordid><sourcetype>Open Website</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>2822802500</pqid></control><display><type>article</type><title>Estimation of Socioeconomic Inequalities in Mortality in Japan Using National Census-linked Longitudinal Mortality Data</title><source>Publicly Available Content Database</source><source>PubMed Central (Training)</source><creator>Tanaka, Hirokazu ; Mackenbach, Johan P. ; Kobayashi, Yasuki</creator><creatorcontrib>Tanaka, Hirokazu ; Mackenbach, Johan P. ; Kobayashi, Yasuki</creatorcontrib><description>Background: We aimed to develop census-linked longitudinal mortality data for Japan and assess their validity as a new resource for estimating socioeconomic inequalities in health.Methods: Using deterministic linkage, we identified, from national censuses for 2000 and 2010 and national death records, persons and deceased persons who had unique personal identifiers (generated using sex, birth year/month, address, and marital status). For the period 2010–2015, 1,537,337 Japanese men and women aged 30–79 years (1.9% in national census) were extracted to represent the sample population. This population was weighted to adjust for confounding factors. We estimated age-standardized mortality rates (ASMRs) by education level and occupational class. The slope index of inequality (SII) and relative index inequality (RII) by educational level were calculated as inequality measures.Results: The reweighted sample population’s mortality rates were somewhat higher than those of the complete registry, especially in younger age-groups and for external causes. All-cause ASMRs (per 100,000 person-years) for individuals aged 40–79 years with high, middle, and low education levels were 1,078 (95% confidence interval [CI], 1,051–1,105), 1,299 (95% CI, 1,279–1,320), and 1,670 (95% CI, 1,634–1,707) for men, and 561 (95% CI, 536–587), 601 (95% CI, 589–613), and 777 (95% CI, 745–808) for women, respectively, during 2010–2015. SII and RII by educational level increased among both sexes between 2000–2005 and 2010–2015, which indicates that mortality inequalities increased.Conclusion: The developed census-linked longitudinal mortality data provide new estimates of socioeconomic inequalities in Japan that can be triangulated with estimates obtained with other methods.</description><identifier>ISSN: 0917-5040</identifier><identifier>EISSN: 1349-9092</identifier><identifier>DOI: 10.2188/jea.JE20210106</identifier><identifier>PMID: 34629363</identifier><language>eng</language><publisher>Fukuoka: Japan Epidemiological Association</publisher><subject>Census ; Censuses ; Confidence intervals ; deterministic linkage ; Education ; Estimates ; Estimation ; Inequality ; Men ; Mortality ; mortality inequalities ; Original ; Social Epidemiology ; Socioeconomic factors ; socioeconomic inequalities ; Socioeconomics ; vital statistics ; Women</subject><ispartof>Journal of Epidemiology, 2023/05/05, Vol.33(5), pp.246-255</ispartof><rights>2021 Tanaka, Hirokazu et al.</rights><rights>2023. This work is published under https://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2021 Hirokazu Tanaka et al. 2021 Hirokazu Tanaka et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c693t-c0a9f7267626adf78146b9f7a828938b4a7485acdf95b1157ca14bba13d5e2043</citedby><cites>FETCH-LOGICAL-c693t-c0a9f7267626adf78146b9f7a828938b4a7485acdf95b1157ca14bba13d5e2043</cites><orcidid>0000-0002-3153-8802 ; 0000-0002-9616-0687</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC10043154/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.proquest.com/docview/2822802500?pq-origsite=primo$$EHTML$$P50$$Gproquest$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,881,25731,27901,27902,36989,44566,53766,53768</link.rule.ids></links><search><creatorcontrib>Tanaka, Hirokazu</creatorcontrib><creatorcontrib>Mackenbach, Johan P.</creatorcontrib><creatorcontrib>Kobayashi, Yasuki</creatorcontrib><title>Estimation of Socioeconomic Inequalities in Mortality in Japan Using National Census-linked Longitudinal Mortality Data</title><title>Journal of Epidemiology</title><addtitle>Journal of Epidemiology</addtitle><description>Background: We aimed to develop census-linked longitudinal mortality data for Japan and assess their validity as a new resource for estimating socioeconomic inequalities in health.Methods: Using deterministic linkage, we identified, from national censuses for 2000 and 2010 and national death records, persons and deceased persons who had unique personal identifiers (generated using sex, birth year/month, address, and marital status). For the period 2010–2015, 1,537,337 Japanese men and women aged 30–79 years (1.9% in national census) were extracted to represent the sample population. This population was weighted to adjust for confounding factors. We estimated age-standardized mortality rates (ASMRs) by education level and occupational class. The slope index of inequality (SII) and relative index inequality (RII) by educational level were calculated as inequality measures.Results: The reweighted sample population’s mortality rates were somewhat higher than those of the complete registry, especially in younger age-groups and for external causes. All-cause ASMRs (per 100,000 person-years) for individuals aged 40–79 years with high, middle, and low education levels were 1,078 (95% confidence interval [CI], 1,051–1,105), 1,299 (95% CI, 1,279–1,320), and 1,670 (95% CI, 1,634–1,707) for men, and 561 (95% CI, 536–587), 601 (95% CI, 589–613), and 777 (95% CI, 745–808) for women, respectively, during 2010–2015. SII and RII by educational level increased among both sexes between 2000–2005 and 2010–2015, which indicates that mortality inequalities increased.Conclusion: The developed census-linked longitudinal mortality data provide new estimates of socioeconomic inequalities in Japan that can be triangulated with estimates obtained with other methods.</description><subject>Census</subject><subject>Censuses</subject><subject>Confidence intervals</subject><subject>deterministic linkage</subject><subject>Education</subject><subject>Estimates</subject><subject>Estimation</subject><subject>Inequality</subject><subject>Men</subject><subject>Mortality</subject><subject>mortality inequalities</subject><subject>Original</subject><subject>Social Epidemiology</subject><subject>Socioeconomic factors</subject><subject>socioeconomic inequalities</subject><subject>Socioeconomics</subject><subject>vital statistics</subject><subject>Women</subject><issn>0917-5040</issn><issn>1349-9092</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2023</creationdate><recordtype>article</recordtype><sourceid>PIMPY</sourceid><sourceid>DOA</sourceid><recordid>eNpVUc1v0zAUtxCIlcKVcyTO6fwRO84Joa6wTgUOsLP14jiZQ2p3tjO0_55kHa12sfXe78Pv-YfQR4JXlEh52RtY3WwopgQTLF6hBWFFlVe4oq_RAlekzDku8AV6F2OPMROS4rfoghWCVkywBfq7icnuIVnvMt9mv7y23mjv_N7qbOvM_QiDTdbEzLrsuw9pLh_n4gYO4LLbaF2X_XgygCFbGxfHmA_W_TFNtvOus2ls7AydxVeQ4D1608IQzYfne4luv25-r6_z3c9v2_WXXa5FxVKuMVRtSUUpqICmLSUpRD11QFJZMVkXUBaSg27aiteE8FIDKeoaCGu4obhgS7Q9-jYeenUI067hUXmw6qnhQ6cgJKsHo2qOOaNtwYRuiwYLwFxrTDgpiawBysnr89HrMNZ702jjUoDhhelLxNk71fkHRfA0CeHzNJ-eHYK_H01MqvdjmH4nKioplZjyKaQlWh1ZOvgYg2lPTxCs5tTVlLo6pz4Jro6CPibozIn-f7OZzpji83GWnWB9B0EZx_4BGwy4Iw</recordid><startdate>20230505</startdate><enddate>20230505</enddate><creator>Tanaka, Hirokazu</creator><creator>Mackenbach, Johan P.</creator><creator>Kobayashi, Yasuki</creator><general>Japan Epidemiological Association</general><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7QL</scope><scope>7QP</scope><scope>7TS</scope><scope>7U7</scope><scope>7U9</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8C1</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AEUYN</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BVBZV</scope><scope>C1K</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>H94</scope><scope>K9.</scope><scope>M0S</scope><scope>M1P</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0002-3153-8802</orcidid><orcidid>https://orcid.org/0000-0002-9616-0687</orcidid></search><sort><creationdate>20230505</creationdate><title>Estimation of Socioeconomic Inequalities in Mortality in Japan Using National Census-linked Longitudinal Mortality Data</title><author>Tanaka, Hirokazu ; Mackenbach, Johan P. ; Kobayashi, Yasuki</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c693t-c0a9f7267626adf78146b9f7a828938b4a7485acdf95b1157ca14bba13d5e2043</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2023</creationdate><topic>Census</topic><topic>Censuses</topic><topic>Confidence intervals</topic><topic>deterministic linkage</topic><topic>Education</topic><topic>Estimates</topic><topic>Estimation</topic><topic>Inequality</topic><topic>Men</topic><topic>Mortality</topic><topic>mortality inequalities</topic><topic>Original</topic><topic>Social Epidemiology</topic><topic>Socioeconomic factors</topic><topic>socioeconomic inequalities</topic><topic>Socioeconomics</topic><topic>vital statistics</topic><topic>Women</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Tanaka, Hirokazu</creatorcontrib><creatorcontrib>Mackenbach, Johan P.</creatorcontrib><creatorcontrib>Kobayashi, Yasuki</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Bacteriology Abstracts (Microbiology B)</collection><collection>Calcium & Calcified Tissue Abstracts</collection><collection>Physical Education Index</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>Public Health Database</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest One Sustainability</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>East & South Asia Database</collection><collection>Environmental Sciences and Pollution Management</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>Journal of Epidemiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Tanaka, Hirokazu</au><au>Mackenbach, Johan P.</au><au>Kobayashi, Yasuki</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimation of Socioeconomic Inequalities in Mortality in Japan Using National Census-linked Longitudinal Mortality Data</atitle><jtitle>Journal of Epidemiology</jtitle><addtitle>Journal of Epidemiology</addtitle><date>2023-05-05</date><risdate>2023</risdate><volume>33</volume><issue>5</issue><spage>246</spage><epage>255</epage><pages>246-255</pages><artnum>JE20210106</artnum><issn>0917-5040</issn><eissn>1349-9092</eissn><abstract>Background: We aimed to develop census-linked longitudinal mortality data for Japan and assess their validity as a new resource for estimating socioeconomic inequalities in health.Methods: Using deterministic linkage, we identified, from national censuses for 2000 and 2010 and national death records, persons and deceased persons who had unique personal identifiers (generated using sex, birth year/month, address, and marital status). For the period 2010–2015, 1,537,337 Japanese men and women aged 30–79 years (1.9% in national census) were extracted to represent the sample population. This population was weighted to adjust for confounding factors. We estimated age-standardized mortality rates (ASMRs) by education level and occupational class. The slope index of inequality (SII) and relative index inequality (RII) by educational level were calculated as inequality measures.Results: The reweighted sample population’s mortality rates were somewhat higher than those of the complete registry, especially in younger age-groups and for external causes. All-cause ASMRs (per 100,000 person-years) for individuals aged 40–79 years with high, middle, and low education levels were 1,078 (95% confidence interval [CI], 1,051–1,105), 1,299 (95% CI, 1,279–1,320), and 1,670 (95% CI, 1,634–1,707) for men, and 561 (95% CI, 536–587), 601 (95% CI, 589–613), and 777 (95% CI, 745–808) for women, respectively, during 2010–2015. SII and RII by educational level increased among both sexes between 2000–2005 and 2010–2015, which indicates that mortality inequalities increased.Conclusion: The developed census-linked longitudinal mortality data provide new estimates of socioeconomic inequalities in Japan that can be triangulated with estimates obtained with other methods.</abstract><cop>Fukuoka</cop><pub>Japan Epidemiological Association</pub><pmid>34629363</pmid><doi>10.2188/jea.JE20210106</doi><tpages>10</tpages><orcidid>https://orcid.org/0000-0002-3153-8802</orcidid><orcidid>https://orcid.org/0000-0002-9616-0687</orcidid><oa>free_for_read</oa></addata></record> |
fulltext | fulltext |
identifier | ISSN: 0917-5040 |
ispartof | Journal of Epidemiology, 2023/05/05, Vol.33(5), pp.246-255 |
issn | 0917-5040 1349-9092 |
language | eng |
recordid | cdi_doaj_primary_oai_doaj_org_article_b50532f436cf4d06a05cc0151718baa7 |
source | Publicly Available Content Database; PubMed Central (Training) |
subjects | Census Censuses Confidence intervals deterministic linkage Education Estimates Estimation Inequality Men Mortality mortality inequalities Original Social Epidemiology Socioeconomic factors socioeconomic inequalities Socioeconomics vital statistics Women |
title | Estimation of Socioeconomic Inequalities in Mortality in Japan Using National Census-linked Longitudinal Mortality Data |
url | http://sfxeu10.hosted.exlibrisgroup.com/loughborough?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-07T07%3A33%3A48IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_doaj_&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Estimation%20of%20Socioeconomic%20Inequalities%20in%20Mortality%20in%20Japan%20Using%20National%20Census-linked%20Longitudinal%20Mortality%20Data&rft.jtitle=Journal%20of%20Epidemiology&rft.au=Tanaka,%20Hirokazu&rft.date=2023-05-05&rft.volume=33&rft.issue=5&rft.spage=246&rft.epage=255&rft.pages=246-255&rft.artnum=JE20210106&rft.issn=0917-5040&rft.eissn=1349-9092&rft_id=info:doi/10.2188/jea.JE20210106&rft_dat=%3Cproquest_doaj_%3E2822802500%3C/proquest_doaj_%3E%3Cgrp_id%3Ecdi_FETCH-LOGICAL-c693t-c0a9f7267626adf78146b9f7a828938b4a7485acdf95b1157ca14bba13d5e2043%3C/grp_id%3E%3Coa%3E%3C/oa%3E%3Curl%3E%3C/url%3E&rft_id=info:oai/&rft_pqid=2822802500&rft_id=info:pmid/34629363&rfr_iscdi=true |