Linear trend or graded association: an international study of objective and subjective socioeconomic inequalities in self-rated health

Abstract

Despite the well-documented socioeconomic inequalities in health, it is less known about how objective and subjective socioeconomic statuses (SES) are related to self-rated health (SRH) in an international context. Using data from the 2007 International Social Survey Program (ISSP) that included 33 countries across six continents (N = 40,049), we found that for objective SES, either education or income, or both were related to SRH as general linear trends (i.e., higher SES was associated with better SRH as a general trend) rather than graded associations (i.e., adjacent levels of SES were associated with SRH in a dose–response relationship). After controlling for subjective SES, the magnitude of the associations between objective SES and SRH reduced, whereas the associations between subjective SES and SRH remained strong in nearly all countries. Findings suggested that more rigorous analyses are needed to clearly describe the SES-health associations, and future international research should expand to include subjective measures of SES.

Additional information

Notes on contributors

Fang Gong

Fang Gong is an associate professor of sociology at Ball State University. Her research areas include medical sociology, sociology of mental health, aging and the life course, and race and ethnicity. Her recent projects examine the social contexts and determinants of health and wellbeing among population groups in the United States and China. She has published in journals such as American Journal of Public Health, Journal of Health and Social Behavior, Sociology of Race and Ethnicity, and Social Science & Medicine.

Jun Xu

Jun Xu is a professor of sociology at Ball State University. His primary research interests include Asia and Asian America, comparative sociology, health, and statistical modeling and programming. His work has appeared in journals such as Social Forces, Social Science & Medicine, Sociological Methods and Research, Social Science Research, and The Stata Journal. He is also an author (with Andrew S. Fullerton) of the statistical monograph, Ordered Regression Models: Parallel, Partial, and Non-Parallel Alternatives, published by Chapman and Hall of Taylor & Francis Group.