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      Different Income Information as an Indicator for Health Inequality among Japanese Adults

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          Abstract

          BACKGROUND

          There are several alternative indicators of income information, which is a fundamental measure of individual socioeconomic position. In this study, we compared the degrees of associations of four types of income information with health variables among Japanese adults.

          METHODS

          Using a nationally representative sample of 29,446 men and 32,917 women aged 20 years and over, the associations between four income indicators and health variables were examined using the odds ratio in logistic regression analysis and the concentration index by sex and age group (20-59 years and 60+ years). Income indicators consisted of total household income, equivalent household income, total household expenditure, and equivalent household expenditure. Current smoking and self-rated health statuses were used as health variables.

          RESULTS

          A low income was associated with a high prevalence of smoking and fair/poor self-rated health, with some differences among sex and age groups and income indicators, but less difference among methods of statistical analyses. Total and equivalent incomes were similarly and more markedly associated with smoking and self-rated health statuses, whereas equivalent expenditure showed the smallest degree of health difference. For the population aged 60+ years, the degree of health differences in smoking was similar between income and expenditure.

          CONCLUSIONS

          Although the degree of income-related health differences is dependent on health outcome and both sex and age group, this study suggests that either crude or equivalent household income is a useful indicator for health inequality among Japanese adults.

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          Most cited references27

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          On the measurement of inequalities in health.

          This paper offers a critical appraisal of the various methods employed to date to measure inequalities in health. It suggests that only two of these--the slope index of inequality and the concentration index--are likely to present an accurate picture of socioeconomic inequalities in health. The paper also presents several empirical examples to illustrate of the dangers of using other measures such as the range, the Lorenz curve and the index of dissimilarity.
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            Inequities in under-five child malnutrition in South Africa

            Objectives To assess and quantify the magnitude of inequalities in under-five child malnutrition, particularly those ascribable to socio-economic status and to consider the policy implications of these findings. Methods Data on 3765 under-five children were derived from the Living Standards and Development Survey. Household income, proxied by per capita household expenditure, was used as the main indicator of socio-economic status. Socio-economic inequality in malnutrition (stunting, underweight and wasting) was measured using the illness concentration index. The concentration index was calculated for the whole sample, as well as for different population groups, areas of residence (rural, urban and metropolitan) and for each province. Results Stunting was found to be the most prevalent form of malnutrition in South Africa. Consistent with expectation, the rate of stunting is observed to be the highest in the Eastern Cape and the Northern Province – provinces with the highest concentration of poverty. There are considerable pro-rich inequalities in the distribution of stunting and underweight. However, wasting does not manifest gradients related to socio-economic position. Among White children, no inequities are observed in all three forms of malnutrition. The highest pro-rich inequalities in stunting and underweight are found among Coloured children and metropolitan areas. There is a tendency for high pro-rich concentration indices in those provinces with relatively lower rates of stunting and underweight (Gauteng and the Western Cape). Conclusion There are significant differences in under-five child malnutrition (stunting and underweight) that favour the richest of society. These are unnecessary, avoidable and unjust. It is demonstrated that addressing such socio-economic gradients in ill-health, which perpetuate inequalities in the future adult population requires a sound evidence base. Reliance on global averages alone can be misleading. Thus there is a need for evaluating policies not only in terms of improvements in averages, but also improvements in distribution. Furthermore, addressing problems of stunting and underweight, which are found to be responsive to improvements in household income status, requires initiatives that transcend the medical arena.
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              Socioeconomic inequalities in mortality among elderly people in 11 European populations.

              To describe mortality inequalities related to education and housing tenure in 11 European populations and to describe the age pattern of relative and absolute socioeconomic inequalities in mortality in the elderly European population. Data from mortality registries linked with population census data of 11 countries and regions of Europe were acquired for the beginning of the 1990s. Indicators of socioeconomic status were educational level and housing tenure. The study determined mortality rate ratios, relative indices of inequality (RII), and mortality rate differences. The age range was 30 to 90+ years. Analyses were performed on the pooled European data, including all populations, and on the data of populations separately. Data were included from Finland, Norway, Denmark, England and Wales, Belgium, France, Austria, Switzerland, Barcelona, Madrid, and Turin. In Europe (populations pooled) relative inequalities in mortality decreased with increasing age, but persisted. Absolute educational mortality differences increased until the ages 90+. In some of the populations, relative inequalities among older women were as large as those among middle aged women. The decline of relative educational inequalities was largest in Norway (men and women) and Austria (men). Relative educational inequalities did not decrease, or hardly decreased with age in England and Wales (men), Belgium, Switzerland, Austria, and Turin (women). Socioeconomic inequalities in mortality among older men and women were found to persist in each country, sometimes of similar magnitude as those among the middle aged. Mortality inequalities among older populations are an important public health problem in Europe.
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                Author and article information

                Journal
                J Epidemiol
                J Epidemiol
                JE
                Journal of Epidemiology
                Japan Epidemiological Association
                0917-5040
                1349-9092
                2 June 2007
                2007
                : 17
                : 3
                : 93-99
                Affiliations
                [1 ]Department of Epidemiology, National Institute of Public Health.
                Author notes

                Address for correspondence: Yoshiharu Fukuda, Department of Epidemiology, Nationallnstitute of Public Health, 2-3-6 Minami, Wako, Saitama 351-0197, Japan. (E-mail fukuday@ 123456niph.go.jp )

                This research was supported by Grants-in-Aid for Scientific Research from the Japan Society for the Promotion of Science (Grant No. 14570326 and 16590497).

                Article
                17.93
                10.2188/jea.17.93
                7058454
                17545696
                53958ecd-a613-4625-a612-0c726ad4e3e5
                © 2007 Japan Epidemiological Association.

                This is an open access article distributed under the terms of Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 8 December 2006
                : 2 March 2007
                Categories
                Original Article

                health inequality,income,self-rated health,smoking,socioeconomic factors

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