Self-rated Health Status of Japanese and Europeans in Later Life: Evidence from JSTAR and SHARE

Fujii, Mayu; Oshio, Takashi; Shimizutani, Satoshi

doi:10.1111/jere.12029

Cited by 4 publications

(5 citation statements)

References 24 publications

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“…In adjusting for reporting biases due to income and A-P-C when responding to SRH categories, we used the empirical method described by Fujii et al [ 24 ] and Jürges [ 30 ], which consisted of constructing a normalized health index ranging from 0 to 1, in which 0 represented the worst health condition and 1 represented the best health condition across income and A-P-C. The health index was based on objective information on health problems, such as physical and mental health problems that had been diagnosed by a physician.…”

Section: Methodsmentioning

confidence: 99%

“…Third, although the majority of studies have used self-rated health (SRH) as an indicator for examining SES-related health differences, few studies have adjusted for reporting biases caused by heterogeneity, or different thresholds across populations with differing demographic or socioeconomic status when they evaluate their own health. According to a review by Fujii et al [ 24 ], threshold levels in SRH depend on sex, age, education, time points, and income. As a result, reporting biases might have caused A-P-C differences in SES gaps in health reported in some studies.…”

Section: Introductionmentioning

confidence: 99%

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Socioeconomic status and self-rated health of Japanese people, based on age, cohort, and period

Sugisawa

Harada

Sugihara

et al. 2016

Popul Health Metrics

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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.

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Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Socioeconomic status and self-rated health of Japanese people, based on age, cohort, and period

Sugisawa

Harada

Sugihara

et al. 2016

Popul Health Metrics

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“…Our study examines both physical (e.g., self-reports of functional impairment/disability) and cognitive impairments (e.g., memory tests conducted by interviewers). The former are considered as a quasi-objective indicator of health, which arguably provides a more accurate assessment than SRH [ 23 ] and is likely less sensitive to the cross-cultural biases identified for SRH [ 24 – 26 ]. By contrast, the latter are objective measures of health that are less subject to individual recall bias.…”

Section: Introductionmentioning

confidence: 99%

Wealth inequalities in physical and cognitive impairments across Japan and Europe: the role of health expenditure and infrastructure

Quashie

Brandt

et al. 2023

Int J Equity Health

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Although prior research has provided insights into the association between country-level factors and health inequalities, key research gaps remain. First, most previous studies examine subjective rather than objective health measures. Second, the wealth dimension in health inequalities is understudied. Third, a handful of studies explicitly focus on older adults. To bridge these research gaps, this study measures wealth-related inequalities in physical and cognitive impairments and examines the extent to which welfare states moderate wealth inequalities in physical and cognitive impairments among older people across Japan and Europe. We utilized harmonized data on non-institutionalized individuals aged 50–75 from the Japanese Study of Aging and Retirement (JSTAR) and the Survey of Health, Ageing and Retirement in Europe (SHARE) (N = 31,969 for physical impairments and 31,348 for cognitive impairments). Our multilevel linear regression analyses examined whether national public health spending and healthcare access resources explained cross-country differences in wealth inequalities in physical and cognitive impairments. We applied a concentration index to quantify the degree of wealth inequalities in impairments. The findings indicate that inequalities in both impairment outcomes favored wealthier individuals in all countries, but the magnitude of inequality varied by country. Furthermore, a higher share of public health spending, lower out-of-pocket expenditure, and higher investment in healthcare resources were associated with lower wealth inequalities, especially for physical impairments. Our findings suggest that different health interventions and policies may be needed to mitigate specific impairment inequalities.

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“…SRH is related to socioeconomic factors such as age, gender, educational level, standard of living, and economic activities [6], and emotional states and health-related lifestyle [6][7]. Obesity is a factor affecting health status, as obese people tend to have lower SRH scores [8][9]. Physical activity is another factor influencing health status [4,6,9], and little or no physical activity can lead to premature death [10].…”

mentioning

confidence: 99%

“…Despite the availability of studies on depression and physical activity in relation to SRH in many countries, most of them rely on cross-sectional survey data [1,[5][6][7], showing limitations in identifying the cause-effect relationship [2,8,16].…”

mentioning

confidence: 99%

Depression, Physical activity, and self-rated health: Panel analysis of adults in South Korea

Yoon¹

2020

Preprint

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Background: The health status of an individual is determined by socio-economic factors and behavioral factors. Socio-economic factors include marital status, educational level, living expenses, and housing type, among others. The differences of health status across individuals are mainly determined by these socioeconomic factors, which cannot be altered in a short run. However, even if the socioeconomic factors cannot be altered in the short run, there are ways for an individual to improve the health status in a relatively short period of time. These are behavioral factors, such as physical activities and management of depression. Methods: We provided evidence of the first statement by running a pooled OLS regression with self-rated health (SRH) as dependent variable and with walking, management of depression, sex, age, marital status, educational level, housing type, living expenses, and economic activity as independent variables. We proved the second statement by running a fixed-effect panel regression with the same dependent and independent variables. The 2010–2013 Korea Health Panel Survey data were used for analysis. Subjects were 34,436 adults (≥19 years) in 8,609 panel groups. Results: All the variables, including socio-economic variables as well as behavioral variables, were significant in the Pooled OLS regression. Whereas behavioral variables, such as walking and management of depression, were significant in the fixed-effect panel regression, socio-economic variables were not. The reason is that socio-economic variables are stable and not variant for an individual in the short-run.Conclusion: Whereas the differences of health status across individuals are mainly determined by socioeconomic factors, the health of an individual is significantly affected by his/her behavior. It is shown that regular walking and reduction of depression are important in improving SRH. There is a need for strategies designed to address depression and aging and encourage walking.

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Self-rated Health Status of Japanese and Europeans in Later Life: Evidence from JSTAR and SHARE

Cited by 4 publications

References 24 publications

Socioeconomic status and self-rated health of Japanese people, based on age, cohort, and period

Socioeconomic status and self-rated health of Japanese people, based on age, cohort, and period

Wealth inequalities in physical and cognitive impairments across Japan and Europe: the role of health expenditure and infrastructure

Depression, Physical activity, and self-rated health: Panel analysis of adults in South Korea

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