• Journal of Preventive Medicine and Public Health
• /
• v.41 no.3
• /
• pp.186-194
• /
• 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.

• Journal of Preventive Medicine and Public Health
• /
• v.40 no.5
• /
• pp.345-350
• /
• 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.

• Journal of the Korean Regional Science Association
• /
• v.37 no.4
• /
• pp.75-93
• /
• 2021

By defining a travel disparity based on the degree to which travelers diversify their destinations, this paper examines how socioeconomic and spatial factors affect the travel disparity among the elderly in Seoul. This paper uses the COVID-19 pandemic as a natural experiment which can bring about different behavioral responses among the older travelers. Using the smart card data, we compare the destination diversification patterns before and after the pandemic. In the early morning(4:30-9:00), the degree of destination diversification varies between the core and the periphery and this trend persists through the pandemic. In the late morning(9:00-12:00), a new trend of disparity appeared after the pandemic. Although those who hold higher socioeconomic status and live closer to the core have a larger range of choices for destinations, the difference of range did not lead to differences in diversification before the pandemic, due to the discretionary nature of the elderly's trip. In contrast, as the elderly were forced to search alternative destinations right after the outbreak of the pandemic, the range of choices became an important factor causing observable differences in destination diversification. The findings suggest that the travel disparity observed during the pandemic is due to the difference in the range of choices by socioeconomic and spatial factors.

• Asian Pacific Journal of Cancer Prevention
• /
• v.13 no.6
• /
• pp.2955-2960
• /
• 2012

Background: Health disparities exist among and within countries, while developing and low income countries suffer more. The aim of this study was to quantify cancer disparities with regard to socioeconomic position (SEP) in 22 districts of Tehran, Iran. Method: According to the national cancer registry, 7599 new cancer cases were recorded within 22 districts of Tehran in 2008. Based on combined data from census and a population-based health equity study (Urban HEART), socioeconomic position (SEP) was calculated for each district. Index of disparity, absolute and relative concentration indices (ACI & RCI) were used for measuring disparities in cancer incidence. Results: The overall cancer age standardised rate (ASR) was 117.2 per 100,000 individuals (120.4 for men and 113.5 for women). Maximum ASR in both genders was seen in districts 6, 3, 1 and 2. Breast, colorectal, stomach, skin and prostate were the most common cancers. Districts with higher SEP had higher ASR (r=0.9, p<0.001). Positive ACI and RCI indicated that cancer cases accumulated in districts with high SEP. Female disparity was greater than for men in all measures. Breast, colorectal, prostate and bladder ASR ascended across SEP groups. Negative ACI and RCI in cervical and skin cancers in women indicate their aggregation in lower SEP groups. Breast cancer had the highest absolute disparities measure. Conclusion: This report provides an appropriate guide and new evidence on disparities across geographical, demographic and particular SEP groups. Higher ASR in specific districts warrants further research to investigate the background predisposing factors.

• Korean Journal of Social Welfare
• /
• v.60 no.4
• /
• pp.231-251
• /
• 2008

Academic interest has been drastically increased for the health disparities due to socioeconomic factors. For those who have a chronic illness such as diabetes, various psychosocial barriers related to illness management might affect and aggravate this disparity. This study focused on illness management barriers experienced by people with diabetes, and examined the differences by their Medicaid beneficiary status. The between group differences in illness management barriers, family support and health status were examined as well as the association between illness management barriers and health status. The sample of this study consists of 144 community dwelling adults who have diabetes, recruited from an outpatient diabetes clinic and a community welfare center. Medicaid beneficiaries reported poorer health status, and experienced more illness management barriers compared to their counterparts. Statistically significant differences were observed in barriers due to mental health, financial status, and lack of support. The between group difference in health status remained significant after controlling for the effect of demographic characteristics and illness related factors. Social work practitioners working with this population should address these illness management barriers to reduce socioeconomic health disparity.

• Journal of Korean society of Dental Hygiene
• /
• v.24 no.1
• /
• pp.17-26
• /
• 2024

Objectives: This study aimed to analyze the relationship between the socioeconomic status and oral health of adults. Methods: Data from the 7th Korea National Health and Nutrition Examination Survey (2016-2018) were analyzed, and 13,199 adults aged 19 years or older were selected as study subjects. Various oral health indicators were used to analyze the effect of socioeconomic status on oral health. Disparities in oral health according to socioeconomic status were analyzed using the complex sample chi-squared test and multiple logistic regression analysis. Results: A statistically significant difference was observed between income level, medical aid, and all oral health indicators, which indicated that the lower the income level, the lower the oral health level (p<0.001). Furthermore, all oral health indicators displayed statistically significant differences, with the exception of the prevalence of dental caries and education level. The lower the education level, the lower the oral health level (p<0.001). Therefore, the oral health level of adults presented significant differences according to different socioeconomic status indicators. Conclusions: To prevent oral health inequalities, the government and local governments need to intervene not only in the field of health care but also in the social determinants. Additionally, concerted efforts should be made to eliminate oral health disparities by improving policies and systems.

• Asian Pacific Journal of Cancer Prevention
• /
• v.14 no.5
• /
• pp.3219-3221
• /
• 2013

Background: This study used receiver operating characteristic (ROC) curves to screen Surveillance, Epidemiology and End Results (SEER) skin melanoma data to identify and quantify the effects of socioeconomic factors on cause specific survival. Methods: 'SEER cause-specific death classification' used as the outcome variable. The area under the ROC curve was to select best pretreatment predictors for further multivariate analysis with socioeconomic factors. Race and other socioeconomic factors including rural-urban residence, county level % college graduate and county level family income were used as predictors. Univariate and multivariate analyses were performed to identify and quantify the independent socioeconomic predictors. Results: This study included 49,999 parients. The mean follow up time (SD) was 59.4 (17.1) months. SEER staging (ROC area of 0.08) was the most predictive foctor. Race, lower county family income, rural residence, and lower county education attainment were significant univariates, but rural residence was not significant under multivariate analysis. Living in poor neighborhoods was associated with a 2-4% disadvantage in actuarial cause specific survival. Conclusions: Racial and socioeconomic factors have a significant impact on the survival of melanoma patients. This generates the hypothesis that ensuring access to cancer care may eliminate these outcome disparities.

• Health Policy and Management
• /
• v.26 no.1
• /
• pp.12-23
• /
• 2016

Background: Many studies have explained regional disparities in health by socioeconomic status and healthcare resources, focusing on differences between urban and rural area. However some cities in Korea have the highest cardiovascular mortality, even though they have sufficient healthcare resources. So this study aims to confirm three hypotheses. (1) There are also regional health disparities between cities not only between urban and rural area. (2) It has different regional risk factors affecting cardiovascular mortality whether it is urban or rural area. (3) Besides socioeconomic and healthcare resources factors, there are remnant factors that affect regional cardiovascular mortality such as health behavior and physical environment. Methods: The subject of this study is 227 local authorities (si, gun, and gu). They were categorized into city (gu and si consisting of urban area) and non-city (gun consisting of rural area), and the city group was subdivided into 3 parts to reflect relative different city status: city 1 (Seoul, Gyeonggi cities), city 2 (Gwangyeoksi cities), and city 3 (other cities). We compared their mortalities among four groups by using analysis of variance analysis. And we explored what had contributed to it in whole authorities, city and non-city group by using multiple regression analysis. Results: Cardiovascular mortality is highest in city 2 group, lowest in city 1 group and middle in non-city group. Socioeconomic status and current smoking significantly increase mortality regardless of group. Other than those things, in city, there are some factors associated with cardiovascular mortality: walking practice(-), weight control attempt(-), deficiency of sports facilities(+), and high rate of factory lot(+). In non-city, there are other factors different from those of city: obesity prevalence(+), self-perceiving obesity(-), number of public health institutions(-), and road ratio(-). Conclusion: To reduce cardiovascular mortality and it's regional disparities, we need to consider differentiated approach, respecting regional character and different risk factors. Also, it is crucial to strengthen local government's capacity for practicing community health policy.

• Safety and Health at Work
• /
• v.11 no.1
• /
• pp.41-49
• /
• 2020

Background: We performed this study to investigate the inequalities in site-specific cancer incidences among workers across different occupations in Korea. Methods: Subjects included members of the national employment insurance. Incident cancers among 8,744,603 workers were followed from 1995 to 2007. Occupational groups were classified according to the Korean Standard Occupational Classification. Age-standardized incidence rate ratios were calculated. Results: We found that men in service/sales and blue-collar occupations had elevated rates of esophageal, liver, laryngeal, and lung cancer. Among women, service/sales workers had elevated incidences of cervical cancer. Male prostate cancer, female breast, corpus uteri, and ovarian cancers, as well as male and female colorectal, kidney, and thyroid cancer showed lower incidences among workers in lower socioeconomic occupations. Conclusions: Substantial differences in cancer incidences were found depending on occupation reflecting socioeconomic position, in the Korean working population. Cancer prevention policy should focus on addressing these socioeconomic inequalities.

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