TY - JOUR
T1 - Geographical socioeconomic inequalities in healthy life expectancy in Japan, 2010-2014
T2 - An ecological study: Geographical socioeconomic inequalities in healthy life expectancy in Japan
AU - Kataoka, Aoi
AU - Fukui, Keisuke
AU - Sato, Tomoharu
AU - Kikuchi, Hiroyuki
AU - Inoue, Shigeru
AU - Kondo, Naoki
AU - Nakaya, Tomoki
AU - Ito, Yuri
N1 - Funding Information:
Data on the number of deaths by sex and 5-year age group, and municipalities of residence at death are not disclosed and were requested from the Ministry of Health, Labor, and Welfare in Japan. Other data in this study are published on the following websites and are freely available. https://www.e-stat.go.jp/stat-search/files?page=1&layout=datalist&toukei=00200521&tstat=000001049104&cycle=0&tclass1=000001049105&tclass2val=0, https://www.mhlw.go.jp/topics/0103/tp0329-1.html, This project was supported by The Ministry of Education, Science and Culture of Japan (a Grant-in-Aid for Scientific Research [A] No. 20H00040 to NT, SI, YI and 18H04071 to NK). The funders had no role in the study design, data collection, data analysis, data interpretation, or writing of the report.
Funding Information:
This project was supported by The Ministry of Education, Science and Culture of Japan (a Grant-in-Aid for Scientific Research [A] No. 20H00040 to NT, SI, YI and 18H04071 to NK). The funders had no role in the study design, data collection, data analysis, data interpretation, or writing of the report.
Publisher Copyright:
© 2021
PY - 2021/9
Y1 - 2021/9
N2 - Background: Area differences in life expectancy (LE) and healthy life expectancy (HLE) in large geographical units have been monitored around the world. Area characteristics may be based on culture, history, socioeconomic status and discrimination in smaller geographical units, so it is important to consider these when looking at health inequality. We aimed to evaluate LE, HLE, and non-healthy life expectancy (NHLE) in 1707 municipalities using Areal Deprivation Index (ADI) in Japan for the first time. Methods: We calculated the observed LE, HLE, and NHLE using death, population, and Long-term care insurance data for 2010-2014 and applied the variance weighted least squares model to estimate LE, HLE, and NHLE by 100 percentiles using the standardized ADI. Findings: The estimated LE, HLE, and NHLE became lower as the deprivation index worsened: the differences between the most and least deprived areas for HLE were 2·49 years for LE and 2·32 years for HLE in males; 1·22 years for LE and 0·93 years for HLE in females. The observed LE and HLE in the most deprived areas were much lower than other areas. Interpretation: Using ADI has enabled us to see the disparity within municipalities precisely. LE and HLE outlier for the 100th percentile might be linked to historical areal deprivation and marginalization. Precise monitoring of socioeconomic status-based health inequalities could help manage these inequalities by identifying the groups most in need of intervention.
AB - Background: Area differences in life expectancy (LE) and healthy life expectancy (HLE) in large geographical units have been monitored around the world. Area characteristics may be based on culture, history, socioeconomic status and discrimination in smaller geographical units, so it is important to consider these when looking at health inequality. We aimed to evaluate LE, HLE, and non-healthy life expectancy (NHLE) in 1707 municipalities using Areal Deprivation Index (ADI) in Japan for the first time. Methods: We calculated the observed LE, HLE, and NHLE using death, population, and Long-term care insurance data for 2010-2014 and applied the variance weighted least squares model to estimate LE, HLE, and NHLE by 100 percentiles using the standardized ADI. Findings: The estimated LE, HLE, and NHLE became lower as the deprivation index worsened: the differences between the most and least deprived areas for HLE were 2·49 years for LE and 2·32 years for HLE in males; 1·22 years for LE and 0·93 years for HLE in females. The observed LE and HLE in the most deprived areas were much lower than other areas. Interpretation: Using ADI has enabled us to see the disparity within municipalities precisely. LE and HLE outlier for the 100th percentile might be linked to historical areal deprivation and marginalization. Precise monitoring of socioeconomic status-based health inequalities could help manage these inequalities by identifying the groups most in need of intervention.
KW - Areal Deprivation
KW - Health Inequalities
KW - Healthy Life Expectancy
KW - Japan
KW - Life Expectancy
KW - Small-Area Study
KW - Socioeconomic Status
UR - http://www.scopus.com/inward/record.url?scp=85110154746&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85110154746&partnerID=8YFLogxK
U2 - 10.1016/j.lanwpc.2021.100204
DO - 10.1016/j.lanwpc.2021.100204
M3 - Article
AN - SCOPUS:85110154746
SN - 2666-6065
VL - 14
JO - The Lancet Regional Health - Western Pacific
JF - The Lancet Regional Health - Western Pacific
M1 - 100204
ER -