• Korean Journal of Social Welfare
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• v.61 no.2
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• pp.391-415
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• 2009

The purpose of this study is to examine the trends of income inequality by gender since 1997 economic crisis and to investigate what is the most influential factor on these changes for males and females. Data used for this study are nine waves of Korean Labor and Income Panel Study(KLIPS). Income inequality is measured by the Gini coefficient and the mean logarithmic deviation(MLD) and the MLDs are decomposed into three components to quantify within- and between-group inequalities. The results show that the extent of income inequality is greater for women during the whole period and is fluctuated more widely. Women's income inequality is mainly affected by the family-related variables, such as age and marital status, while men's inequality is primarily determined by the labor market factors, such as employment status, industrial types and occupation status. These results imply that gender-sensetive welfare policies need to be implemented and that it is necessary to assist the poor women and men through the benefits from the income assistance programs and labor market programs.

• Women's Health Nursing
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• v.21 no.2
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• pp.150-159
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• 2015

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.

• Journal of Preventive Medicine and Public Health
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• v.44 no.1
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• pp.22-31
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• 2011

Objectives: We examined gender differential changes in employment-related health inequalities according to occupational position (professional/nonprofessional) in South Korea during the last decade. Methods: Data were taken from four rounds of Social Statistical Surveys of South Korea (1995, 1999, 2003, and 2006) from the Korean National Statistics Office. The total study population was 55435 male and 33913 female employees aged 25-64. Employment arrangements were divided into permanent, fixed-term, and daily employment. Results: After stratification according to occupational position (professional/nonprofessional) and gender, different patterns in employment - related health inequalities were observed. In the professional group, the gaps in absolute and relative employment inequalities for poor self-rated health were more likely to widen following Korea's 1997 economic downturn. In the nonprofessional group, during the study period, graded patterns of employment-related health inequalities were continuously observed in both genders. Absolute health inequalities by employment status, however, decreased among men but increased among women. In addition, a remarkable increase in relative health inequalities was found among female temporary and daily employees (p = 0.009, < 0.001, respectively), but only among male daily employees (p = 0.001). Relative employment-related health inequalities had clearly widened for female daily workers between 2003 and 2006 (p = 0.047). The 1997 Korean economic downturn, in particular, seemingly stimulated a widening gap in employment health inequalities. Conclusions: Our study revealed that whereas absolute health inequalities in relation to employment status increased in the professional group, relative employment-related health inequalities increased in the nonprofessional group, especially among women. In view of the high concentration of female nonstandard employees, further monitoring of inequality should consider gender specific patterns according to employee's occupational and employment status.

• Journal of Agricultural Extension & Community Development
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• v.13 no.2
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• pp.299-312
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• 2006

This study reported on the cases about gender inequality in agriculture. Generally women have experienced something in vague situation as unequal to men in rural and agriculture. Despite of some women's have been complaining about this problem, it is not easy why and how many times they have been suffering. In this report, to get the information of gender unequality in agricultural laws and policies, the data was gathered by two steps. The first step, 175 cases into nine types was collected from leaders of several women farmer's associations, and after that, 60 cases selected to be interviewed by a specialist panel. The second step, it was analyzed the interviewed 60 cases based on real conditions compared with laws of items of policies. Among the cases, it was analyzed 8 rural women's who had been experienced to receive the inappropriate compensation in an unexpected accidents. From these cases, it was drew up some suggestions as follows; to make a rule to certify of the identity of woman farmer, and to build in a monitoring system of gender equality in agriculture.

• Journal of the Korean Society of School Health
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• v.20 no.1
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• pp.63-75
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• 2007

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.

• Korean Journal of Health Education and Promotion
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• v.28 no.1
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• pp.57-67
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• 2011

Objectives: This study gathered basic information for the development of a health promotion policy for employees and the selection of participants for health education by identifying the impact of socioeconomic status and health behavior on the health status of males and females. Methods: The 2008 National Health Nutrition and Examination Survey data were used to examine relationships between socioeconomic status, health behaviors, and health status of male and female employees. For the analysis, the $X^2$ test and logistic regression were used. Results: Heath behaviors had a very slight impact of the association between socioeconomic status and health status among male and female employees. And patterns of health inequality had the gender difference. Conclusions: When developing a health promotion policy for employees, and selecting health education subjects, it is necessary to consider both socioeconomic status and gender.

• Journal of Preventive Medicine and Public Health
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• v.44 no.6
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• pp.249-259
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• 2011

Objectives: This study aimed to analyze long-term trends in the contribution of each cause of death to socioeconomic inequalities in all-cause mortality among Korean adults. Methods: Data were collected from death certificates between 1990 and 2004 and from censuses in 1990, 1995, and 2000. Age-standardized death rates by gender were produced according to education as the socioeconomic position indicator, and the slope index of inequality was calculated to evaluate the contribution of each cause of death to socioeconomic inequalities in all-cause mortality. Results: Among adults aged 25-44, accidental injuries with transport accidents, suicide, liver disease and cerebrovascular disease made relatively large contributions to socioeconomic inequalities in all-cause mortality, while, among adults aged 45-64, liver disease, cerebrovascular disease, transport accidents, liver cancer, and lung cancer did so. Ischemic heart disease, a very important contributor to socioeconomic mortality inequality in North America and Western Europe, showed a very low contribution (less than 3%) in both genders of Koreans. Conclusions: Considering the contributions of different causes of death to absolute mortality inequalities, establishing effective strategies to reduce socioeconomic inequalities in mortality is warranted.

• Asian Pacific Journal of Cancer Prevention
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• v.15 no.2
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• pp.623-627
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• 2014

Background: Esophagus cancer (EC) is among the five most common cancers in both sexes in Iran, with an incidence rate well above world average. Social rank (SR) of individuals and regions are well-known independent predictors of EC incidence. The aim of current study was to assess gender and social disparities in EC incidence across Iran's provinces through 2003-2009. Materials and Methods: Data on distribution of population at province level were obtained from the Statistical Centre of Iran. Age-standardized incidence rates of EC were gathered from the National Cancer Registry. The Human Development Index (HDI) was used to assess the province social rank. Rate ratios and Kunst and Mackenbach relative indices of inequality ($RII_{KM}$) were used to assess gender and social inequalities, respectively. Annual percentage change (APC) was calculated using joinpoint regression. Results: EC incidence rate increased 4.6% and 6.5% per year among females and males, respectively. There were no gender disparities in EC incidence over the study period. There were substantial social disparities in favor of better-off provinces in Iran. These social disparities were generally the same between males and females and were stable over the study period. Conclusions: The results showed an inverse association between the provinces' social rank and EC incidence rate in Iran. In addition, I found that, in contrast with international trends, women are at the same risk of EC as men in Iran. Further investigations are needed to explain these disparities in EC incidence across the provinces.

• Journal of Preventive Medicine and Public Health
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• v.41 no.3
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• pp.165-172
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• 2008

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 Journal of Asian Finance, Economics and Business
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• v.7 no.11
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• pp.541-548
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• 2020

This study aimed to explain the factors that influenced an individual's decision to migrate. The method of analysis in this study was the estimation of the probit regression model with data from the Indonesian Family Life Survey (IFLS-5), which covered 30,000 individuals from 13 provinces in Indonesia. Data from IFLS-5 were longitudinal data, meaning that the study was looking for data consistently to get reliable data from respondents. The research variables to determine the individual's decision to migrate were education level, income level, employment status, marital status, land ownership status, health quality, gender, residence status, and poverty status. Individual decision to migrate as a dependent variable was placed as a dummy variable. The results showed that the level of education, income level, employment status, marital status, land ownership status, health quality, and poverty status significantly influenced an individual's decision to migrate. Meanwhile, gender and residence status did not significantly affect an individual's decision to migrate. This research recommends that it is necessary to pursue a policy of economic equality between regions because economic factors are the main trigger for an individual's decision to migrate. Policies to overcome economic disparities among regions will reduce the individual's decision to migrate.