Subjective assessments of income and social class on health and survival: An enigma

We examined the association between various measures of subjective social class identification (SSCI) and self-rated health as well as survival using the 2014 General Social Survey-National Death Index dataset (n = 21,108). We used multinomial logistic regression models to assess the association bet...

Full description

Bibliographic Details
Main Authors: Shukai Li, Qianyun Zhang, Peter Muennig
Format: Article
Language:English
Published: Elsevier 2018-12-01
Series:SSM: Population Health
Online Access:http://www.sciencedirect.com/science/article/pii/S2352827317301854
Description
Summary:We examined the association between various measures of subjective social class identification (SSCI) and self-rated health as well as survival using the 2014 General Social Survey-National Death Index dataset (n = 21,108). We used multinomial logistic regression models to assess the association between SSCI and self-rated health and used Cox proportional hazards to assess the association between SSCI and survival. All analyses were adjusted for age, year at interview, race, gender, family income, and educational attainment level. The measures of SSCI that we had available were strongly correlated with self-rated health after controlling for objective measures of social status. For example, those who saw themselves as lower class were nine times as likely to self-report poor rather than excellent health status (odds ratio = 8.69; 95% confidence interval = 5.04–14.98) compared with those saw themselves as upper class. However, no such associations were observed for survival. While our alternative measures of SSCI were important predictors of self-rated health, they were not predictive of survival. This suggests that there may be potential confounding between two perceptions: SSCI and self-rated health. Keywords: Subjective social status, Self-rated health, Survival time, Socioeconomic disparities and health, Health status, Health policy, Epidemiology, Longitudinal research
ISSN:2352-8273