• Korean Journal of Social Welfare
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• v.58 no.4
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• pp.265-289
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• 2006

Purpose of this research is to analyze process that poverty influences in academic attainment of children. Data comes from Korea Youth Panel Survey 2004(Primary School 4). Analysis method is Structural Equation Modeling. Results show that poverty influences through process variable such as family function, neighborhood environment, private education, self-confidence. Findings from this study suggest that societal support for poor families contributes to improving academic attainment of child. Specially, such societal support needs to be centered to factors that mediates factor of poverty.

• Journal of the Economic Geographical Society of Korea
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• v.19 no.4
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• pp.729-742
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• 2016

Socio-economic polarization in Korea partly due to recent globalization and industrial restructuring could reduce social mobility significantly through passing down educational achievement to one's children. Under the notion that residential segregation is geographical frame for the reproduction of educational inequality, this research investigates residential segregation by educational attainment and neighborhood disparity with a case study of Seoul. The statistical analyses employed local segregation measures such as Location Quotient and Local Moran's I and a variety of variables that reflect neighborhood characteristics. As a result, it found that there are sharp and clear contracts between low- and high-educational group concentrations/clusters particularly in terms of housing characteristics and educational facilities. This results provide some evidences that support the arguments about the causes of residential segregation by class in Korean Cities.

• Journal of Korean Public Health Nursing
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• v.29 no.3
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• pp.488-502
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• 2015

Purpose: This study was conducted to determine the neighborhood environmental factors associated with physical activity among adults living in rural communities. Methods: A cross-sectional descriptive survey was conducted with a convenience sample of 201 adults living in three Ri in Y-city, Gyeonggi-do. Data were collected from face-to-face interview by trained interviewers and were analyzed using a zero-inflated negative binominal regression model. Results: Participants reported engaged in moderate or vigorous physical activity was 76.1%; 10.5% of participants reported that they met moderate physical activity recommendations and 14.5% of participants reported that they met vigorous physical activity recommendations. Zero-inflated negative binominal regression analysis showed association of increasing days of physical activity with social cohesion (${\beta}=.130$, p=.005), social network (${\beta}=-.096$, p=.003), and safety for crime (${\beta}=-.151$, p=.036), and no days of physical activity was associated with no attainment of education and marginally associated with increasing BMI. Conclusion: Neighborhood environmental factors including social cohesion, social network, and crime for safety were significantly associated with physical activity of rural adults. Community health nurses should expand an approach for individual behavior change to incorporate rural adults' specific neighborhood environmental factors into physical activity interventions.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.12
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• pp.7133-7136
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• 2013

Background: We studied Surveillance, Epidemiology and End Results (SEER) breast cancer data of Georgia USA to analyze the impact of socio-economic factors on the disparity of breast cancer treatment outcome. Materials and Methods: This study explored socio-economic, staging and treatment factors that were available in the SEER database for breast cancer from Georgia registry diagnosed in 2004-2009. An area under the receiver operating characteristic curve (ROC) was computed for each predictor to measure its discriminatory power. The best biological predictors were selected to be analyzed with socio-economic factors. Survival analysis, Kolmogorov-Smirnov 2-sample tests and Cox proportional hazard modeling were used for univariate and multivariate analyses of time to breast cancer specific survival data. Results: There were 34,671 patients included in this study, 99.3% being females with breast cancer. This study identified race and education attainment of county of residence as predictors of poor outcome. On multivariate analysis, these socio-economic factors remained independently prognostic. Overall, race and education status of the place of residence predicted up to 10% decrease in cause specific survival at 5 years. Conclusions: Socio-economic factors are important determinants of breast cancer outcome and ensuring access to breast cancer treatment may eliminate disparities.

• Health Policy and Management
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• v.21 no.2
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• pp.329-348
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• 2011

This research analyzed 168,010 cases of death of the aged over 65 from 244,867cases of death excluding 7 unknown age cases from 244,874 all age cases of death by using the death data of the National Statistical Office for 2007 to figure out factors affecting the quality of causes of death statistics of the aged and to suggest the ways of improving the quality of death statistics of the aged in korea. This research tried to derive factors affecting ill-defined cause of death category in acordance with WHO's guidelines and to find causes of lowering the accuracy of causes of death statistics of the aged. This research identified the problems of causes of death statistics of the aged by using both demographic characteristics such as sex, age, marital status, educational attainment, residential region, region size and factors of death items as independent variable to find causes of ill-defined cause of death of the aged. Logistic regression analysis was executed to calculate the hazard ratio about the ill-defined causes of death of the aged and multiple regression analysis was conducted to derive factors affecting the ill-defined cause of death by regional groups through using these independent variables such as the component ratio of over age 65, female death rates, doctors insitutions rate, medical institutions rate, attaching rates of death certificate by neighborhood. As a results of this research, R-code was the highest of ill-defined causes of death, accounting for 82.1%, and senility death(R54) of R-code was the highest, accounting for 91.2%. through subdivided order distribution of the ill-defined causes of death of the aged. As ill-defined causes of death by regional groups, attaching rates of death certificate by neighborhood was the most important factor(p<0.05) and also showed regression model's description with 83.8% ($R^2$=83.8%). Furthermore, Jeon-nam was the highest in the regional groups and these regions such as Je-ju, Jeon-buk, Chung-nam were not only attaching the death certificate by neighborhood but also were high at the rate of ill-defined causes of death. Therefore, this research found that both reconsideration about death certificate by neighborhood and education for doctors who write death certificate were needed the most.