• Korean Journal of Organic Agriculture
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• v.24 no.1
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• pp.1-15
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• 2016

This paper aims to analyze inequality of maize self-sufficiency rate among countries in 1970-2011. Utilizing sub-group consistency of Generalized Entropy and Atkinson inequality index, the estimated maize self-sufficiency rate inequality is further decomposed into two steps' separate country groups. First, lower and upper income groups and then lower, lower middle, upper middle and high income groups are used based on the national classification of the world bank. It is inferred that 1980s' policy intervention and 1990s' Uruguay Round negotiations have different effect on the inequality among four different country groups.

• Korean Journal of Social Welfare Studies
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• v.41 no.1
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• pp.65-84
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• 2010

The purpose of Inequality Index Decomposition is to know the cause of overall inequality through decomposing aggregate inequality index into relevant components. Previous studies have mostly focused on the absolute contribution meaning that how much each component possesses out of overall inequality. However it could be more important to know the marginal contribution and inequality effect of each component in order to implement policies reducing overall inequality effectively. For this, we decomposed Gini Coefficient as representative inequality index into income sources or social welfare programs and calculated each Gini Income Elasticity(GIE). Analysis result says that regular employee income and employer(or the self-employed) income, of which GIE are 1.205 and 1.867, are classified as inequality-increasing income source. GIE can be one of good methods to analyse the inequality effect of various income sources and social welfare programs.

• Forest Science and Technology
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• v.14 no.4
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• pp.192-203
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• 2018

This study analyzed the distribution of forest income and other variable sources of rural household income and considered their importance for the reduction of income inequality and poverty. We employed Gini decomposition to measure the contribution of forest income and other sources of income to income equality and assess whether they were inequality-increasing or inequality-decreasing in the 14 villages. The forest income Gini correlation with total income was very high, $R_k=0.6960$, and the forest income share of total rural household income was 35% ($S_k=0.3570$). If the income earned from forest activities was removed, the Gini index would increase by 10.3%. Thus, if people could not access forest resources because of vast deforestation, perhaps from the limitations of government-managed forestry, unplanned clearing of forest land for agriculture or the granting of ELCs, there would be an increase in income inequality and poverty among rural households. The findings suggest that policy makers should look beyond agriculture for rural development, as forest resources provide meaningful subsistence income and perhaps contribute to both preventing and reducing poverty and inequality in rural communities. The study found that non-farm activities were inequality-increasing sources of income. The share of non-farm income to the total rural household income was $S_k=0.1290$ and the Gini index of non-farm income was very high, $G_k=0.8780$, compared with forest and farm income. This disagrees with other studies which have reported that non-farm income was inequality-decreasing for the rural poor.

• Journal of Preventive Medicine and Public Health
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• v.52 no.4
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• pp.214-223
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• 2019

Objectives: Equity in financial protection against healthcare expenditures is one the primary functions of health systems worldwide. This study aimed to quantify socioeconomic inequality in facing catastrophic healthcare expenditures (CHE) and to identify the main factors contributing to socioeconomic inequality in CHE in Iran. Methods: A total of 37 860 households were drawn from the Households Income and Expenditure Survey, conducted by the Statistical Center of Iran in 2017. The prevalence of CHE was measured using a cut-off of spending at least 40% of the capacity to pay on healthcare services. The concentration curve and concentration index (C) were used to illustrate and measure the extent of socioeconomic inequality in CHE among Iranian households. The C was decomposed to identify the main factors explaining the observed socioeconomic inequality in CHE in Iran. Results: The prevalence of CHE among Iranian households in 2017 was 5.26% (95% confidence interval [CI], 5.04 to 5.49). The value of C was -0.17 (95% CI, -0.19 to -0.13), suggesting that CHE was mainly concentrated among socioeconomically disadvantaged households in Iran. The decomposition analysis highlighted the household wealth index as explaining 71.7% of the concentration of CHE among the poor in Iran. Conclusions: This study revealed that CHE is disproportionately concentrated among poor households in Iran. Health policies to reduce socioeconomic inequality in facing CHE in Iran should focus on socioeconomically disadvantaged households.

• Korean Journal of Social Welfare
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• v.64 no.4
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• pp.163-188
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• 2012

This study examines recent trends in income inequality among the elderly in Korea. Aggregate income inequality trends are explained by examining evidence from inequality index decomposition by population subgroup and by income source. Data come from Korean Labor and Income Panel Study(KLIPS). The results are as follows. First, elderly income inequality increased from 1999 to 2002, and then decreased until 2008. Second, household composition changes appear to have disequalizing influence. The proportion of elderly people who are economically dependent on non-elderly family member or living with adult children has declined. Equalizing influence of private transfers also decreased between 2002 and 2008. These results indicate that the redistributive role of family has weakened over time. Third, the improvement of education level and changing occupational structure among the elderly household head contributed to increase in elderly income inequality. Fourth, earning's factor share has declined steadily, and the diminishing role of earnings provides equalizing influence on elderly income inequality from 2002 to 2008. Fifth, the impact of recent expansion of social insurance has changed over time. Inequality contribution of social insurance income increased from 1999 to 2002, and then decreased from 2002 to 2008.

• Journal of Preventive Medicine and Public Health
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• v.56 no.1
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• pp.50-58
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• 2023

Objectives: Socioeconomic inequality in metabolic syndrome (MetS) remains poorly understood in Iran. The present study examined the extent of the socioeconomic inequalities in MetS and quantified the contribution of its determinants to explain the observed inequality, with a focus on middle-aged adults in Iran. Methods: This cross-sectional study used data from the Ravansar Non-Communicable Disease cohort study. A sample of 9975 middleaged adults aged 35-65 years was analyzed. MetS was assessed based on the International Diabetes Federation definition. Principal component analysis was used to construct socioeconomic status (SES). The Wagstaff normalized concentration index (CI_n) was employed to measure the magnitude of socioeconomic inequalities in MetS. Decomposition analysis was performed to identify and calculate the contribution of the MetS inequality determinants. Results: The proportion of MetS in the sample was 41.1%. The CI_n of having MetS was 0.043 (95% confidence interval, 0.020 to 0.066), indicating that MetS was more concentrated among individuals with high SES. The main contributors to the observed inequality in MetS were SES (72.0%), residence (rural or urban, 46.9%), and physical activity (31.5%). Conclusions: Our findings indicated a pro-poor inequality in MetS among Iranian middle-aged adults. These results highlight the importance of persuading middle-aged adults to be physically active, particularly those in an urban setting. In addition to targeting physically inactive individuals and those with low levels of education, policy interventions aimed at mitigating socioeconomic inequality in MetS should increase the focus on high-SES individuals and the urban population.

• 한국노년학
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• v.32 no.3
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• pp.759-776
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• 2012

This study analysed the income-related health inequality of the aged in Korea applied to EQ-5D. Two decompositions were used in analysis. One was the decomposition of income-related health inequality into six different dimensions of EQ-5D, and the other was to decompose it by sub-group such as sex, region, existence of spouse. The results are summarized as follows. First, the health concentration index(CI) of the aged was .0254, which meant that there were pro-rich inequality in elderly people's health levels. The same patterns were also seen in the analysis of different dimensions of EQ-5D such as mobility, self-care, usual activities, pain/discomfort, and anxiety/depression. Second, mobility accounted for 35.8% of total EQ-5D score, most contributing to CI of the dimensions of EQ-5D. The CIs by the dimensions ranged from .0091 for mobility to .0013 for self-care. Third, The decompositions by sub-groups showed that the contributions of sex, region, and existence of spouse to health inequality was similar to each other, all of three sub-groups accounted for 10 % of inequality respectively. Fourth, the inequality within group was higher in female group, rural area, and the aged without spouse. The average health level of these groups was lower than that of the other ones, too. These facts indicated that old women, the aged without spouse, and the elderly in rural area were the most vulnerable groups in health problems. Therefore, it is necessary to pay more attention to health problems of these groups in the policy making of health security and social welfare services.

• Journal of Preventive Medicine and Public Health
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• v.55 no.3
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• pp.297-306
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• 2022

Objectives: The incidence of cardiovascular disease (CVD) mortality is increasing in developing countries. This study aimed to decompose the socioeconomic inequality of CVD in Iran. Methods: This cross-sectional population-based study was conducted on 20 519 adults who enrolled in the Ardabil Non-Communicable Disease cohort study. Principal component analysis and multivariable logistic regression were used, respectively, to estimate socioeconomic status and to describe the relationships between CVD prevalence and the explanatory variables. The relative concentration index, concentration curve, and Blinder-Oaxaca decomposition model were used to measure and decompose the socioeconomic inequality. Results: The overall age-adjusted prevalence of CVD was 8.4% in northwest Iran. Multivariable logistic regression showed that older adults, overweight or obese adults, and people with hypertension and diabetes were more likely to have CVD. Moreover, people with low economic status were 38% more likely to have CVD than people with high economic status. The prevalence of CVD was mainly concentrated among the poor (concentration index, -0.077: 95% confidence interval, -0.103 to -0.060), and 78.66% of the gap between the poorest and richest groups was attributed to differences in the distribution of the explanatory variables included in the model. Conclusions: The most important factors affecting inequality in CVD were old age, chronic illness (hypertension and diabetes), marital status, and socioeconomic status. This study documented stark inequality in the prevalence of CVD, wherein the poor were more affected than the rich. Therefore, it is necessary to implement policies to monitor, screen, and control CVD in poor people living in northwest Iran.

• Journal of the Economic Geographical Society of Korea
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• v.22 no.2
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• pp.196-213
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• 2019

This paper attempts to analyze the contribution of different socioeconomic factors such as income, age, gender, household composition, education and employment status etc. to the difference between the Capital and Non-Capital Regions in the net wealth inequality of household in Korea. To this end, a two-stage Oaxaca-Blinder type decomposition is employed regarding the regional gap in the inequality of net wealth based upon the Recentered Influence Function of the Gini index for 'the 2018 Household Finance and Living Conditions Survey.' Despite the shortcomings of the survey data on wealth, the findings reveal that regional differences in income, marriage status (divorce), job type (agriculture, forestry and fishery related, and technical and assembly), family type (multi-cultural) variables deepen the regional gap in the net-wealth inequality, but employment status (full-time), job type (administrative and specialized, and service sales), household size variables mitigate the gap, and that regional differences in life cycles play an offsetting role.

• 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.