• 한국컴퓨터정보학회논문지
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• 제24권3호
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• pp.143-150
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• 2019

This study aimed to analyze the keyword related to Health Disparity in Korea through the method of keyword network analysis and to establish a basic database for suggesting ideas for prospective studies in physical education. To achieve the goal, this study crawled co-occured keyword with 'health' and 'disparity' from news casted in 20 different channels. The duration of the news was 3 months, from September 11th, 2018 to December 11th. The results are as follows. First, among the news during recent 3 months, there were 1,383 keyword related to health disparity and this study selected 173 keyword which had co-occured over 3 times. Second, the inclusiveness of the network was 97.674% and the density was .038. Third, analyzing news related to health disparity, 'mortality' was the most co-occured keyword and 'disparity', 'reinforcement', 'the most', 'health', '6 times', 'Seoul', 'half', 'medicine', and 'local' were shown similarly. And common keyword in 4 centrality were 13 keyword. Lastly, by analyzing eigenvector centrality, significantly different result has shown. 'Disparity' was the most co-occured keyword. Based on this result, this study showed the necessity for reinforcing the public physical education in public education system in Korea. In order to achieve it, the field of physical education must look beyond present elite-focused physical education to public physical activity.

• Child Health Nursing Research
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• 제19권4호
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• pp.247-251
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• 2013

Children from low income families are vulnerable to physical problems including obesity, asthma, hypertension and psychological problems including depression, anxiety. This study was done to identify trends in welfare policy for children from low-income families and future direction for solving health disparity problems. Dream Start is a government-sponsored project that offers services for vulnerable children, ages 0 (include pregnant woman) to 12 years and their families. The Korean Government has made an effort to alleviate health disparity through the 'Health Plan' by establishing health objectives. However, in spite of these efforts by the Korean government, health disparity has worsened in Korea. In order to strengthen family function as well as promote growth and development for vulnerable children, experts in child care need to be significantly involved in identifying neglected children in the community.

• 한국학교보건학회지
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• 제22권2호
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• pp.25-36
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• 2009

Purpose: The purpose of this study was to estimate income-related health inequalities among adolescent population across regions in Korea. Methods: Data of 8,456 adolescents from 1998, 2001, 2005, 2007 Korean Health and Nutrition Examination Survey were used for the analysis. True health status was proxied by self-rated health and overweight status. Per capita income was computed from household monthly average income adjusted by consumer price with base year 2005. Adolescent health inequalities were estimated by Concentration Index (CI) across income and space. Results: Ill health score was related with age (p<0.0001), gender (p=0.0155) and income (p<0.0001). Negative relationship between income and ill-health indicated that higher income group tended to enjoy better health and less overweight. These evidences suggested ill health were accumulated on the economically disadvantaged adolescents. The size of health inequalities (ill-health score) were estimated as CI=-0.057 and CI=-0.030 across income groups and regions, respectively. Comparable measures of within region health disparities were also observed. Conclusion: Since health disparity among adolescent population was small compared to adult population, lessening adolescent health inequality could be a helpful way of mitigating health disparities in later stage. Considering life stage of adolescents, school system and local communities could play important roles toward adolescent health distribution. Although health disparity between regions existed, health disparity within a region should not be neglected.

• Journal of Preventive Medicine and Public Health
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• 제40권5호
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• pp.345-350
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• 2007

Objectives: To determine the disparity in the rate people undergo health examinations according to socioeconomic position (SEP) and the changes in this disparity with time. Methods: Seoul citizens' health profile data from 1997 to 2005 were analyzed. The study subjects were 40 years old and over, and the total number of subjects was 6,601 in 1997, 8,994 in 2001, and 8,819 in 2005. Those aged 60 years and over were eliminated from the analysis of subjects' occupation. We used education, family income and occupation as indicators of SEP. The age-standardized health examination attendance rate for each year was calculated according to the education, family income and occupation. The odds ratios (ORs) from multiple logistic regressions were adjusted for age. Results: The disparity in the rate of attendance according to the SEP decreased from 1997 to 2005 but still existed. Even though the disparities among the subgroups according to education, family income and occupation were not that high, the disparity between the group with the highest SEP and the other groups was considerable. Conclusions: Our findings suggest that unequal access to health examination services according to socioeconomic position still exists. This disparity has decreased recently but the disparity according to level of education was the greatest.

• 보건교육건강증진학회지
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• 제18권3호
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• pp.11-36
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• 2001

The purpose of this study is to analyze health behavior by comparing the difference between self-perceived health status and health examination results. The study subjects consist of 7,702 people aged over 20, surveyed by Health Interview survey, Health Examination survey, Dietary Life survey, Health Consciousness and Behavior survey. Data used in the study are drawn from raw data from a 1998 National Health and Nutrition survey. General characteristics variables are sex, age, education level, residential area, marital status, occupation, and living standard while dichotomous variables, ‘not healthy’ and ‘healthy’ are used to measure self-perceived health status. Variables for health examination results are high blood pressure, high cholesterol, diabetes, liver diseases, liver inflammation, kidney diseases, normal weight, regular diet, optimum sleeping time(7-8 hours), regular health examination and health behavior practice group. Major findings of the study are as follows: 1) Analysis of self-perceived health status and health behavior by disease: Variables significantly correlated with high self-perceived health status have strong associations with high health behavior practice, which supports the hypothesis that as one has high self-perceived health status, one is more likely to practice health promoting behavior. The results of analysis of health behavior differences by dividing subjects into two categories, ‘cases of illness’ and ‘cases of no illness’ indicate that drinking, sleeping time, health examination are significant variables (p〈0.001, 0.05) whereas smoking, weight control, regular exercise, regular diet are not significant. 2) Analysis of disparity patterns between self-perceived health status and health examination: The hypothesis that health behaviors would be different according to the disparity pattern between self-perceived health status and health examination is supported as a result of χ2 test. Among Type I : Self-perceived health status is high and actual health status is good (no disease) Type II: Self-perceived health status is high and actual health status is poor(have disease) Type III: Self-perceived health status is low and actual health status is good(no disease) Type IN: Self-perceived health status is low and actual health status is poor(have disease) Type I and Type IV show no disparity, Type I shows the highest health promoting behavior whereas Type IV shows the lowest health promoting behavior. Type II, and III, compared to Type I, practise lower health promoting behavior. Multi-logistics regression analysis was conducted to find out the degree of impact on health behavior. Independent variables are general characteristics, self-perceived health status and health examination result and presence of illness, while the dependent variable is health promoting behavior. The analysis of the impact of self-perceived health status on the health promoting behavior shows that smoking, drinking, weight control, regular exercise, health examination practice, and/or regular diet are significantly correlated to self-perceived health status. High self-perceived health status is inversely related to high health promoting behavior. This finding supports the hypothesis that the higher one perceives one's health, the more likely one is to practice health promoting behavior. On the contrary, the presence of illness has little impact on health promoting behavior. 3) Multiple logistics analysis on how disparity patterns between self-perceived health status and health examination affect health behavior: The results of multiple logistics analysis made on health behavior variables compared to the standard variable are as follows: When analyzed on the standard of Type I, smoking is a significant risk factor for the Type IV. In case of drinking, all the patterns show a high probability of relative risk ratio. With regard to weight control, it is a risk factor for Type II while all the patterns show high probability of not practising when analyzed on the standard of type IV. Type III and IV show high probability of not doing regular exercise while Type IV, shows a high probability of not taking appropriate sleeping time. When analyzed on the standard of type IV, all the patterns show a high probability of not taking health examinations. Type III and IV show a high probability of not having regular meals. As for overall health promoting behavior, Type III and IV show a high relative risk ratio. These two groups have low self-perceived health status. It implies that self-perceived health status has significant impact on health promoting behavior. This is also supported by the fact that Type I with high self-perceived health status and no illness shows a high practice rate of health promoting behavior. Types II and III the groups with high disparity between self-perceived health status and health examination results, show a low practice rate of health promoting behavior when compared to Type I. Type IV, that is the group with low self-perceived health status and actual illness, shows the lowest practice of health promoting behavior. It is highly probable that this type proves to be the poorest health group.

• Journal of Preventive Medicine and Public Health
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• 제41권3호
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• pp.186-194
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• 2008

Objectives : This study describes trends in the socioeconomic disparities in breast cancer screening among US women aged 40 or over, from 2000 to 2005. We assessed 1) the disparities in each socioeconomic dimension; 2) the changes in screening mammography rates over time according to income, education, and race; and 3) the sizes and trends of the disparities over time. Methods : Using data from the Behavioral Risk Factor Surveillance System (BRFSS) from 2000 to 2005, we calculated the age-adjusted screening rate according to relative household income, education level, health insurance, and race. Odds ratios and the relative inequality index (RII) were also calculated, controlling for age. Results : Women in their 40s and those with lower relative incomes were less likely to undergo screening mammography. The disparity based on relative income was greater than that based on education or race (the RII among low-income women across the survey years was 3.00 to 3.48). The overall participation rate and absolute differences among socioeconomic groups changed little or decreased slightly across the survey years. However, the degree of each socioeconomic disparity and the relative inequality among socioeconomic positions remained quite consistent. Conclusions : These findings suggest that the trend of the disparity in breast cancer screening varied by socioeconomic dimension. Continued differences in breast cancer screening rates related to income level should be considered in future efforts to decrease the disparities in breast cancer among socioeconomic groups. More focused interventions, as well as the monitoring of trends in cancer screening participation by income and education, are needed in different social settings.

• 헬스앤미션
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• 통권39호
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• pp.20-23
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• 2015

• 농촌의학ㆍ지역보건
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• 제48권3호
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• pp.165-177
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• 2023

이 연구에서는 신체활동 수준 격차의 근본적인 원인을 해결하기 위해서 1) 중재모형을 개발하고 적용하였으며, 2) 중재모형 평가를 통해 지역 간 격차 해소 전략을 제시하였다. 취약지역 1개동을 선정하여 사업을 진행하였으며 주민자치회를 기반으로 주민건강조직을 구성하고 역량강화 교육을 시행하였다. 리빙랩을 활용하여 주민건강조직 중심으로 사업을 계획하고 추진하였다. 이러한 주민참여 활동을 바탕으로 주민자치회 건강행복분과를 신설하여 지속적인 사업의 토대를 마련하였다. 사업 평가를 통해서 주민자치회 건강분과를 중심으로 보건소, 주민센터 등이 협력하고, 보건영역과 공동체 영역에서 사업을 지원하는 사업 모형을 개발하였다. 주민자치회가 주민건강조직으로 작동할 수 있는 가능성을 확인하였으며, 지역사회에서 이루어지고 있는 주민참여나 자치활동과의 연계를 통해서 주민참여형 보건사업 전략이 활성화 될 수 있다고 생각된다.

• 한국사회복지학
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• 제60권4호
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• pp.231-251
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• 2008

본 연구는 성인당뇨병 환자들을 대상으로 의료급여수급여부에 따라 건강수준 및 질병관리 장애요인에 차이가 나타나는지를 분석하고 질병관리 장애요인이 건강수준에 미치는 영향을 살펴보았다. 자료수집은 서울의 종합병원 당뇨병클리닉 및 지역사회 복지기관에서 편의표집한 55세이상 성인당뇨병 환자 144명을 대상으로 조사를 실시하였다. 분석결과, 의료급여환자가 건강보험환자에 비하여 건강수준이 더 나쁘다고 인식하고 있었으며, 질병관리 장애요인을 더 많이 경험하고 있는 것으로 나타났다. 건강보험환자와 의료급여환자간 건강수준의 차이는 인구학적 요인 및 질병관련 특성들을 통제한 이후에도 유의하였다.

• 보건의료산업학회지
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• 제6권4호
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• pp.13-25
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• 2012

There is growing evidence that substance use such as tobacco or alcohol consumption influences health disparity among adolescents. Previous research papers have shown an inconsistency in the relationship between socio-economic status (SES) and substance use in adolescents. However, little is known about socio-economic differences in unhealthy behaviors among Korean adolescents. The purpose of the present study is to explore associations between SES and substance use in Korean adolescents. The analysis was performed using data from the 2009 Korean Youth Risk Behavior Web-based Survey (YRBS), which included a nationally representative sample of middle and high school students. Drinking/heavy drinking and smoking/daily smoking behavior indices were used for dependent variables, and perceived economic status, family affluence score, parents' education were used for independent variables. Chi-square test were used to compare tobacco and alcohol consumption among 3 SES groups. Logistic regression models were used to identify statistically significant socio-economic factors after adjusting other covariates. Higher perceived economic status and higher family affluence were associated with higher rates of smoking, daily smoking, drinking, and heavy drinking, while lower level of parents' education was related to higher use of tobacco and alcohol. Socio-economic status significantly influences health behaviors in adolescents, and it may consequently affect health disparity in their adulthood. Therefore, there is a need of continuous monitoring and follow-up research of health disparity among adolescents.