Objectives: This study aimed to explore the health inequality discourse in the Korean press by analyzing newspaper articles using a relatively new content analysis technique. Methods: This study used the search term "health inequality" to collect articles containing that term that were published between 2000 and 2018. The collected articles went through pre-processing and topic modeling, and the contents and temporal trends of the extracted topics were analyzed. Results: A total of 1038 articles were identified, and 5 topics were extracted. As the number of studies on health inequality has increased over the past 2 decades, so too has the number of news articles regarding health inequality. The extracted topics were public health policies, social inequalities in health, inequality as a social problem, healthcare policies, and regional health gaps. The total number of occurrences of each topic increased every year, and the trend observed for each theme was influenced by events related to its contents, such as elections. Finally, the frequency of appearance of each topic differed depending on the type of news source. Conclusions: The results of this study can be used as preliminary data for future attempts to address health inequality in Korea. To make addressing health inequality part of the public agenda, the media's perspective and discourse regarding health inequality should be monitored to facilitate further strategic action.
The degree of income inequality deepened by health care expenditure was useful in assessing the health security level. This exploratory study was conducted to provide a basic evidence to prove the necessity of reinforcement the benefit coverage of South Korea's health security systems. Data from the Household Income and Expenditure Survey of Korea and Luxembourg Income Study were used. Income inequality indices before and after deduction of health care expenditure were computed, and the degree of the increase in the indices was compared among 13 countries. The degree of decrease against the effect of income inequality reduction policies by health care expenditure was determined. The relationships between the national characteristics and the increase in income inequality were examined. In South Korea, all income inequality indices increased after deducting health care expenditure, but the difference was not high compared to the mean of 13 countries. However, the degree of decrease against the effect of income inequality reduction policies by health care expenditure was high, compared to the mean of 13 countries. The proportion of public sector spending on health care proved to be statistically significant with the increase of income inequality indices (p<0.05). In the context of the continuous increase in health care expenditure, if benefit coverage of health security systems is not reinforced, income inequality will all the more increase due to health care expenditure. In the establishment of the policies for reinforcement of the benefit coverage, income inequality after deduction of health care expenditure should be continuously monitored.
Objectives : Despite various government initiatives, including the expansion of national health insurance coverage, health inequality has been a key health policy issue in South Korea during the past decade. This study describes and compares the extent of the total health inequality and the income-related health inequality over time among Korean adults. Methods : This study employs the 1998, 2001 and 2005 Korean National Health and Nutrition Examination Surveys (KNHANESs). The self-assessed health (SAH) ordinal responses, measured on a five-point scale, resealed to cardinal values to measure the health inequalities with using interval regression. The boundaries of each threshold for the interval regression analysis were obtained from the empirical distribution of the EuroQol-5 Dimension (EQ-5D) valuation weights estimated from the 2005 KNHANES. The final model predicting the individuals' health status included age, gender, educational attainment, occupation, income, and the regional prosperity index. The concentration index was used to measure and analyze the health inequality. Results : The KNHANES data showed an unequal distribution of the total health inequality in favor of the higher income groups, and this is getting worse over time (0.0327 in 1998, 0.0393 in 2001 and 0.0924 in 2005). The income-related health inequality in 2005 was 0.0278, indicating that 30.1% of the total health inequality can be attributed to income. Conclusions : The findings indicate there are health inequalities across the sociodemographic and income groups despite the recent government's efforts. Further research is warranted to investigate what potential policy actions are necessary to decrease the health inequality in Korea.
The socioeconomic inequalities in health have recently become an important public health concern in South Korea, and the issue has gained increasing attention from many South Korean researchers due to the increasing income inequality and Widening social polarization following its economic crisis in the late 1990s. However, despite the mounting literature on health inequalities published in recent years, the history of research on health inequality in South Korea is premature in comparison to the long histories in several Western countries. Understanding the historical background underlying the issue of health inequality research may aid in establishing and accumulating scientifically solid evidence in South Korea. It may also direct the South Korean research community to develop research agendas that are. more politically and academically appropriate for South Korean society. This paper describes the historical development of health inequality research in the West and introduces several important issues contributing to the advancement of health inequality research. Specifically, the major studies conducted before and after the UK Black Report are presented. In addition, the history and current status of health inequality research in South Korea are documented and evaluated. Finally, several research agendas for the quantitative and qualitative improvement of health inequality research in South Korea are proposed.
Purpose: The purpose of this study was to explore ways to define the concept of health inequality. Methods: The concept analysis process by Walker and Avant was used to clarify the meaning of health inequality. Results: Defining attributes of health inequality included differences in health status between individuals or groups, infringement of fundamental rights to health, unfair use of medical services, and social discrimination. The antecedents of health inequality included differences in demographic characteristics (age, gender, education, occupation, residential location), limitations in accessibility to health care, and social exclusion. Consequences of health inequality were increased costs for medical care, decreased health-related quality of life, and lack of ability to cope with health problems resulting in crisis situations, increases in morbidity and mortality, and shortening of life span. The concept was clarified through presentation of model, borderline, related, and contrary cases. Conclusion: Results of this study can be used to guide the direction of future studies through concept analysis in which conceptual attributes in the context of health inequality are examined. Also, based on the result of this study, development of standardized tools to measure health inequality is recommended as well as development of educational programs to reduce health inequalities.
Objectives: This study aimed to find a way to solve oral health inequality in old age by understanding the effect of the socioeconomic level of the elderly on oral health. Methods: We used data from the 7th Korea National Health and Nutrition Examination Survey. A chi-square test was performed to investigate differences in oral health according to socioeconomic status and demographic and oral health-related factors. Socioeconomic status and oral health inequality were analyzed using multiple logistic regression. Results: The average number of teeth in the elderly was 17.20, which is insufficient for the minimum number of teeth required for mastication. In the analysis of the correlation between socioeconomic status and oral health inequality, education level, income level, and home ownership were factors influencing the oral health of the elderly; education level was found to have the strongest effect. Conclusions: Oral health inequality according to socioeconomic status was confirmed, and it is necessary to measure the level of oral health inequality with active efforts at the government level to resolve the gap in oral health by social class.
Purpose: This study was aimed to identify gender-based health inequality and explore impacting factors on health inequality in one province in Korea. Methods: This was an explanatory study using the secondary data on Chungnam province from the Fifth Community Health Survey from August 16 to Oct 31, 2012. Variables included in this analysis were education level, poverty, marital status, and residential community for socio-cultural characteristics and subjective health status as an indicator of health inequality. Data were analyzed by ${\chi}^2$-test, t-test, ANOVA, and multiple linear regression. Results: There were gender inequalities and disparities in health, and these inequalities were greater in woman than in man (${\chi}^2$=161.8, p<.001). The impacting factors were education level, poverty, marital status, and residential community, which was accounted for 22.6% of variances of health inequality. Among these variables, gender showed the largest influence in health inequalities. Conclusion: To solve health inequalities, it should be considered gender differences based on social determinants of health. It is necessary to develop long term project based on these results and the social determinants model of World Health Organization.
Objectives: Socioeconomic factors are one of the significant factors explaining drinking problems in our society. From the poverty and inequality perspective, not only absolute poverty but perceived level of poverty or inequality has a direct effect on one's health and health behaviors. The purpose of the study is to explore the growth trajectories of problem drinking in Korea in relation to poverty and perceived income. Methods: Data from 13,414 adults were analyzed using 4 years of data (2010 to 2014) from the Korea Welfare Panel. Main variables included poverty status, perceived income inequality, and problem drinking. A latent growth modeling was employed for the analysis. Results: The non-poverty group had higher initial level of problem drinking; however, the poverty group showed higher rate of increase in problem drinking rate. The perceived income inequality had no significant influence on the initial level, but over time, those with higher level of perceived income inequality showed higher rate of increase in problem drinking. Conclusions: Findings showed that poverty and inequality affect changes in problem drinking. Efforts to prevent and decrease problems related to alcohol should not only focus on changing individuals' behavior but also on decreasing the inequality gap.
Purpose: With economic development and prolonged longevity, the level of health and health disparities have became growing concerns for individual and society as well. Since youth's health status are influenced by households' socioeconomic status and associated with heath status in later stage of life, assessing health inequality in the youth is a significant step toward lessening health disparity and promoting health. We measured health inequality in high school students and decomposed it into health factors. Methods: The subjects included 3,787 high school students of 12th graders from the Korea Education and Employment Panel (KEEP) in 2004. True health status was assumed as a latent variable and estimated by ordered logistic regression model. The predicted health was used as a measure of individual health after rPSraling to [0,1] interval. Total health inequality was then measured by Gini coefficient and was decomposed into health factors. Results: Health inequality in high school students was observed. Of total health inequality, 44% was explained by biological factors such as body mass index (BMI) (32.5%) and gender (13.5%). Behavioral factors such as smoking, drinking, physical activity, hours in bed and hours of computer ussge added to 11.7%. Household income and work experiences explained 5.6% and 8.8%, respectively. School satisfaction explained 14.6%. Other school related factors such as self-assessed achievement and experience of being bullied accounted for 15.5%. Conclusion: Among the health factors, biological factor was the most important contributor in health disparity. Other factors such as health behaviors, socioeconomic factors, school satisfaction and school related factors exhibited somewhat similar magnitude. For policy purposes, it is recommended to look into modifiable factors depending BM, gender and school surroundings.
Objective: Taking action on health inequalities starts with the production of information laying out the problems of inequalities, but Korean society has no national database to view related data at a glance. This study aimed to compare Korean national database with the Public Health Profile (PHP), a health inequality database of the UK. Methods: Data were collected from the websites of government and relevant organizations in the both countries between March and August 2020, which was updated in August 2021. Two themes including Co-occurring substance misuse and mental health issues in mental health and INteractive Health Atlas of Lung conditions in England were selected for comparison in terms of data accessibility, data usability and data visualization. Results: The British PHP is being served on a web-based platform, Fingertips. The data collected at the regional level were presented on 31 health inequality themes. The data are displayed at a level that can be compared between comparable communities, and visualized into various tables and figures. Comparable Korean data were scattered in several themes and websites, and mostly provided as a 17 administrative region base, which was too vast to make a meaningful comparisons. Conclusion: The findings proposed several considerations which could be useful for establishing a database of health inequality in the Korean society.
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