SOCIOECONOMIC STATUS AND SELF-RATED HEALTH IN KOREA AND JAPAN: A META-REGRESSION OF INCOME AND EDUCATION EFFECTS
Author(s)
Neha Tripathi, MPH1, Akanksha Sharma, MSc1, Kushagra Pandey, MA1, Shubhram Pandey, MSc2;
1Heorlytics Pvt. Ltd., Mohali, India, 2Heorlytics Pvt. Ltd., SAS Nagar, Mohali, India
1Heorlytics Pvt. Ltd., Mohali, India, 2Heorlytics Pvt. Ltd., SAS Nagar, Mohali, India
OBJECTIVES: Despite universal health coverage and advanced health systems in both Korea and Japan, socioeconomic inequalities in population health persist, and the relative contribution of income versus education to self-rated health remains insufficiently quantified across these settings. To investigate the relationship between income and education with self-rated health (SRH) in Korea and Japan using meta-regression, and to explore how socioeconomic status (SES) influences health outcomes in these two high-income countries with distinct health and social systems
METHODS: A mixed-effects meta-regression model was employed to examine the relationship between income and education and self-rated health (SRH) in Korea and Japan, with income and education serving as socioeconomic indicators and poor SRH as the outcome. The PubMed database contained studies from 2014 to 2025 while displaying effect sizes for the income and education on SRH correlation. The country variable was treated as a moderator, and Japan was used as the reference category. The model was estimated using restricted maximum likelihood (REML). The focus was on understanding how income and educational differences influence health in both countries
RESULTS: Education demonstrated a statistically robust association with self-rated health, with a pooled effect estimate of −0.0598 (p = 0.0076), indicating that higher educational attainment is consistently associated with better health outcomes. Similarly, income showed a pooled effect estimate of −0.1631 (p = 0.1994), suggesting a potential trend toward better health with higher income
CONCLUSIONS: This meta-regression indicates a strong and significant association between the socioeconomic status, in terms of income and education, and self-rated health in both Korea and Japan. Although health and social systems varied, education proved to be a more predictable determinant of health in both environments than income, and education-oriented solutions were found to resolve socioeconomic health disparities
METHODS: A mixed-effects meta-regression model was employed to examine the relationship between income and education and self-rated health (SRH) in Korea and Japan, with income and education serving as socioeconomic indicators and poor SRH as the outcome. The PubMed database contained studies from 2014 to 2025 while displaying effect sizes for the income and education on SRH correlation. The country variable was treated as a moderator, and Japan was used as the reference category. The model was estimated using restricted maximum likelihood (REML). The focus was on understanding how income and educational differences influence health in both countries
RESULTS: Education demonstrated a statistically robust association with self-rated health, with a pooled effect estimate of −0.0598 (p = 0.0076), indicating that higher educational attainment is consistently associated with better health outcomes. Similarly, income showed a pooled effect estimate of −0.1631 (p = 0.1994), suggesting a potential trend toward better health with higher income
CONCLUSIONS: This meta-regression indicates a strong and significant association between the socioeconomic status, in terms of income and education, and self-rated health in both Korea and Japan. Although health and social systems varied, education proved to be a more predictable determinant of health in both environments than income, and education-oriented solutions were found to resolve socioeconomic health disparities
Conference/Value in Health Info
2026-05, ISPOR 2026, Philadelphia, PA, USA
Value in Health, Volume 29, Issue S6
Code
MSR24
Topic
Methodological & Statistical Research
Topic Subcategory
PRO & Related Methods, Survey Methods
Disease
No Additional Disease & Conditions/Specialized Treatment Areas