ArticlePopulation health metrics2016
Socioeconomic status and self-rated health of Japanese people, based on age, cohort, and period.
Article in Population health metrics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
15 citing papers in PubMed.
- Trends in income-related concentration and inequality in health in Japan: evidence from population-based National surveys from 2001 to 2022.Population health metrics · 2025Article
- Socio-economic position and the prevalence of ten chronic diseases in Australia, 2021: a whole of population census data analysis.The Medical journal of Australia · 2025Article
- Association between smartphone use, sleep deprivation, and self-rated health outcomes: A retrospective observational survey in rural Japan.Journal of general and family medicine · 2025Article
- (Not So) Lost in Translation: Considering the GA4GH Diversity in Datasets Policy in the Japanese Context.Asian bioethics review · 2025Article
- Combined associations of education and health literacy with preventive dental visits in patients with diabetes: a nationwide cross-sectional study.Diabetology international · 2025Article
- Socioeconomic inequalities in self-rated health in Japan, 32 European countries and the United States: an international comparative study.Scandinavian journal of public health · 2023Article
- Multimorbidity patterns and the relation to self-rated health among older Japanese people: a nationwide cross-sectional study.BMJ open · 2022Article
- Relationship between occupational injury and gig work experience in Japanese workers during the COVID-19 pandemic: a cross-sectional internet survey.Industrial health · 2022Article
- Mediators of Life-Course and Late-Life Financial Strain on Late-Life Health in Japan: Based on a Cross-Sectional Survey.Journal of multidisciplinary healthcare · 2022Article
- Trends and socioeconomic inequalities in self-rated health in Japan, 1986-2016.BMC public health · 2021Article
- An analysis of predictors for heavy alcohol drinking using nationally representative survey data in Japan.BMC public health · 2021Article
- Cross-classified multilevel models (CCMM) in health research: A systematic review of published empirical studies and recommendations for best practices.SSM - population health · 2020Review
- 36-year trends in educational inequalities in self-rated health among Finnish adults.SSM - population health · 2019Article
- Socioeconomic status and self-reported periodontal symptoms in community-dwelling individuals: data from the Korea Community Health Surveys of 2011 and 2013.International dental journal · 2018Article
- Relationships among Socioeconomic Factors and Self-rated Health in Japanese Adults: NIPPON DATA2010.Journal of epidemiology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDifferences in health resulting from differences in socioeconomic status (SES) have been identified around the world. Age, period, and cohort (A-P-C) differences in health are vital factors which are associated with disparities in SES. However, few studies have examined these differences simultaneously. Moreover, although self-rated health (SRH) has been frequently used as an indicator of health, biases in reporting SRH that depend on the socioeconomic characteristics of respondents have been scarcely adjusted in the previous studies. To overcome these limitations, we investigated the associations between disparities in SES and adjusted SRH based on A-P-C, by using a repeated, cross-sectional survey of a nationally representative sample of Japanese people. In addition, we further investigated how exogenous (macroeconomic) conditions unique to a period or cohort would explain trends across successive periods and cohorts.
methodsData were obtained from a sample of 653,132 Japanese people that responded to the Comprehensive Survey of Living Conditions (CSLC), which is a cross-sectional survey that had been conducted every three years from 1986 to 2013, on over 10 occasions. In the CSLC, SES has been assessed by household income. We simultaneously controlled for each A-P-C dimension by using the model for cross-classification of random effects, and adjusting SRH data for reporting biases caused by differences in income and A-P-C.
resultsDifferences in adjusted SRH associated with income differences decreased with age and reversed after 76 years of age. Period differences indicated that income differences peaked in 1992 and 2007. Moreover, differences in adjusted SRH associated with income differences decreased in periods with high unemployment across all periods. Furthermore, there were no cohort differences in adjusted SRH that were associated with income differences.
conclusionIn Japan, there are age and period variations associated with adjusted differences in SRH as assessed by income. Moreover, exogenous conditions in each period could help explain periodic trends across successive periods.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.