A new theory-based social classification in Japan and its validation using historically collected information

Ayako Hiyoshi, Yoshiharu Fukuda, Martin J. Shipley, Mel Bartley and Eric J. Brunner

Social Science & Medicine, 2013, vol. 87, issue C, 84-92

Abstract: Studies of health inequalities in Japan have increased since the millennium. However, there remains a lack of an accepted theory-based classification to measure occupation-related social position for Japan. This study attempts to derive such a classification based on the National Statistics Socio-economic Classification in the UK. Using routinely collected data from the nationally representative Comprehensive Survey of the Living Conditions of People on Health and Welfare, the Japanese Socioeconomic Classification was derived using two variables – occupational group and employment status. Validation analyses were conducted using household income, home ownership, self-rated good or poor health, and Kessler 6 psychological distress (n ≈ 36,000). After adjustment for age, marital status, and area (prefecture), one step lower social class was associated with mean 16% (p < 0.001) lower income, and a risk ratio of 0.93 (p < 0.001) for home ownership. The probability of good health showed a trend in men and women (risk ratio 0.94 and 0.93, respectively, for one step lower social class, p < 0.001). The trend for poor health was significant in women (odds ratio 1.12, p < 0.001) but not in men. Kessler 6 psychological distress showed significant trends in men (risk ratio 1.03, p = 0.044) and in women (1.05, p = 0.004). We propose the Japanese Socioeconomic Classification, derived from basic occupational and employment status information, as a meaningful, theory-based and standard classification system suitable for monitoring occupation-related health inequalities in Japan.

Keywords: Social class; Health inequality; Socioeconomic; NS-SEC; Erikson–Goldthorpe class schema; Japan (search for similar items in EconPapers)
Date: 2013
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DOI: 10.1016/j.socscimed.2013.03.021

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