TY - JOUR
T1 - Combining education and income into a socioeconomic position score for use in studies of health inequalities
AU - Lindberg, Marie Hella
AU - Chen, Gang
AU - Olsen, Jan Abel
AU - Abelsen, Birgit
N1 - Funding Information:
Open Access funding provided by UiT The Arctic University of Norway. This project was part of the Tracing causes of inequalities in health and wellbeing project funded by the Research Council of Norway, grant 273812. The Tromsø Study of UiT – The Arctic University of Norway (UiT) provided the data, and the Department of Community Medicine at UiT funded the study. The study sponsors had no role in the design and implementation of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; or the decision to submit the manuscript for publication. The publication charges for this article have been funded by a grant from the publication fund of UiT.
Publisher Copyright:
© 2022, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - Background: In studies of social inequalities in health, there is no consensus on the best measure of socioeconomic position (SEP). Moreover, subjective indicators are increasingly used to measure SEP. The aim of this paper was to develop a composite score for SEP based on weighted combinations of education and income in estimating subjective SEP, and examine how this score performs in predicting inequalities in health-related quality of life (HRQoL). Methods: We used data from a comprehensive health survey from Northern Norway, conducted in 2015/16 (N = 21,083). A composite SEP score was developed using adjacent-category logistic regression of subjective SEP as a function of four education and four household income levels. Weights were derived based on these indicators’ coefficients in explaining variations in respondents’ subjective SEP. The composite SEP score was further applied to predict inequalities in HRQoL, measured by the EQ-5D and a visual analogue scale. Results: Education seemed to influence SEP the most, while income added weight primarily for the highest income category. The weights demonstrated clear non-linearities, with large jumps from the middle to the higher SEP score levels. Analyses of the composite SEP score indicated a clear social gradient in both HRQoL measures. Conclusions: We provide new insights into the relative contribution of education and income as sources of SEP, both separately and in combination. Combining education and income into a composite SEP score produces more comprehensive estimates of the social gradient in health. A similar approach can be applied in any cohort study that includes education and income data.
AB - Background: In studies of social inequalities in health, there is no consensus on the best measure of socioeconomic position (SEP). Moreover, subjective indicators are increasingly used to measure SEP. The aim of this paper was to develop a composite score for SEP based on weighted combinations of education and income in estimating subjective SEP, and examine how this score performs in predicting inequalities in health-related quality of life (HRQoL). Methods: We used data from a comprehensive health survey from Northern Norway, conducted in 2015/16 (N = 21,083). A composite SEP score was developed using adjacent-category logistic regression of subjective SEP as a function of four education and four household income levels. Weights were derived based on these indicators’ coefficients in explaining variations in respondents’ subjective SEP. The composite SEP score was further applied to predict inequalities in HRQoL, measured by the EQ-5D and a visual analogue scale. Results: Education seemed to influence SEP the most, while income added weight primarily for the highest income category. The weights demonstrated clear non-linearities, with large jumps from the middle to the higher SEP score levels. Analyses of the composite SEP score indicated a clear social gradient in both HRQoL measures. Conclusions: We provide new insights into the relative contribution of education and income as sources of SEP, both separately and in combination. Combining education and income into a composite SEP score produces more comprehensive estimates of the social gradient in health. A similar approach can be applied in any cohort study that includes education and income data.
KW - Composite indicator
KW - Health inequalities
KW - Health-related quality of life
KW - Socioeconomic position
KW - Socioeconomic status
UR - http://www.scopus.com/inward/record.url?scp=85130008147&partnerID=8YFLogxK
U2 - 10.1186/s12889-022-13366-8
DO - 10.1186/s12889-022-13366-8
M3 - Article
C2 - 35562797
AN - SCOPUS:85130008147
SN - 1471-2458
VL - 22
JO - BMC Public Health
JF - BMC Public Health
IS - 1
M1 - 969
ER -