Journal of the Korean Society of Clothing and Textiles
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v.11
no.3
s.25
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pp.111-119
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1987
The main purposes of the study were to categorize the clothing items into product groups according to their product characteristics, and to find out the differences of consumer perception on clothing Product groups among different age and socioeconomic groups. A questionnaire about characteristics It?as constructed on the basis of Lipton, Darling, and Miracle's theories on product categorisations. The questionnaires were administered to female subjects in two age groups (20's and 40's) living in Seoul. Subjects were classified into 3 socioeconomic groups for the analysis. The Analysis of variance, post-hoc comparisons (Scheffe test and Tuckey test) were employed for the statistical inferences. The results were as follows ; Group I : none Group II : socks, undershirts, T-shirts (20's age group) Group III : blouse, sweater, blue jean, pajama, langerie, T-shirts (40's age group), skirt Group IV : jacket, skirt (high class of 40's age group) two-piece, half coat, long coat, Korean folk costume Group V : none Some of the clothing items were categorized into different product groups by different age and socioeconomic groups.
Objectives: This study was conducted in order to determine how the association between socioeconomic position(SEP) and health status changes with age among Seoul residents aged 25 and over. Methods: We utilized the 2001 and 2005 Seoul Citizens Health Indicators Surveys. We used self-rated 'poor' health status as an outcome variable, and family income as an indicator of SEP. In order to characterize the differential effects of socioeconomic position on health by age, we conducted separate multivariate analyses by 10-year age groups, controlling for sociodemographic covariates. In order to assess the relative health inequality across socioeconomic groups, we estimated the Relative Index of Inequality (RII). Results: The risk of 'poor health' is significantly high in low family income groups, and this increased risk is seen at all ages. However, the magnitude of relative socioeconomic inequality in health, as measured by the odds ratio and RII, is not identical across age groups. The difference in health across income groups is small in early adulthood (ages 25-34), but increases with age until relatively late in life (ages 35-64). It then decreases among the elderly population (ages more than 65). When the RII reported in 2005 is compared to that reported in 2001, RII can be seen to have increased across all ages, with the exception of individuals aged 25-34. Conclusions: The magnitude of health inequality is the greatest during mid- to late adulthood (ages 45-64). In addition, health inequalities have worsened between 2001 and 2005 across all age groups after economic crisis.
Objectives: This study aimed to examine how the relationship between socioeconomic factors at the macro level and suicide mortality rate of Korea was different from that of other OECD countries. Methods: We created OECD panel data of 29 OECD countries from 1985 to 2006 and analyzed the relationship between socioeconomic factors and suicide mortality rate for separate age and sex groups using a fixed-effect model. Economic factors included per capita GDP, per capita GDP growth rate, unemployment rate, and women's economic participation rate. Social factors included birth rate, alcohol consumption, and the percentage of population 65 and older. Results: Unemployment rate had a positive relationship with suicide in other countries but it had a negative relationship in some groups of Korea. Women's economic participation rate was both positively and negatively related with suicide in Korea but it did not relate to suicide in others. The negative relationship of birth rate and the positive relationship of alcohol consumption with suicide were evident in Korea, which were not found in other countries. The percentage of population 65 and older was negatively correlated in some female groups in Korea, while no significant relationship was found in other countries. Conclusions: Korea was substantially different from other OECD countries in the relationship between socioeconomic factors and suicide mortality rate.
Objectives: This study aimed to examined the socioeconomic disparities in oral health related behaviors and to assess if those behaviors eliminate socioeconomic disparities in oral health in a nationally representative sample of adults aged 30-64. Methods: Data are from the Korea Third National Health and Nutrition Examination Survey (2005). Behaviors were indicated by smoking, over intake of daily calories from carbohydrate, perceived stress, frequency of daily tooth brushing, use of oral hygiene goods, insufficient oral treatment. Oral health outcomes were self-reported dental caries and periodontitis during the last 12 months and perceived oral health. Education, household income, and employed status indicated socioeconomic position. Sex, age, residential area, marital status were adjusted for in the logistic regression analysis. Logistic regression analysis was used to assess socioeconomic disparities in behaviors. Logistic regression model adjusting and not adjusting for behaviors were compared to assess the change in socioeconomic disparities in oral health. Results: Clear socioeconomic disparities in all behaviors were showed. After adjusting for behaviors, the association between oral health and socioeconomic indicators attenuated but did not disappear. For example, the odd ratios of reporting poorer oral health for persons in no education or elementary school education and middle school education groups, compared with college or higher education group, were 1.77 (95% CI: 1.36-2.29) and 1.56 (1.19-1.97), respectively. After adjusting for all indicators of behaviors, these odds ratios attenuated to 1.54 (1.17-2.03) and 1.48 (1.15-1.91) for those groups, respectively. Conclusion: These findings suggest that the presence of more complex determinants of socioeconomic disparities in oral health should be considered with developing preventive policies for those disparities.
The aim of study to compare the change trajectory of socioeconomic deprivation and depression the middle-aged in the single-person household and that in the Multi-person Household and to confirm the difference between the two groups. It is to examine the Longitudinal relationship between socioeconomic deprivation and depression. To do so, we studied 4,212 single-person household and Multi-person Household cases in the 7th to 11th Korea Welfare Panel Study (2012~2016). To verify the difference between both groups, we go on analysis with the latent growth curve model. According to our analysis, it is confirmed that the socioeconomic deprivation and depression of single-person households is higher than those of Multi-person Household and thus there is meaningful difference between both groups. Also, we reveal that the socioeconomic deprivation of Multi-person Household tends to decease while that of single-person household doesn't decline significantly. Furthermore, it appears that the socioeconomic deprivation is directly proportional to the depression in both groups. This research has meaningful significance in that we discussed in depth the relationship between the socioeconomic deprivation and depression of both groups, suggesting that welfare approach should be needed in the middle-aged in the single-person household.
The study is investigated socioeconomic variations in perceived oral health status and contribution of oral health behavioral factors. A nationally representative sample (365 health and 1,787 unhealth aged 20 over years) from the 2015 Korea National Health and Nutrition Surveys was analyzed using logistic regression. Perceived oral health was lower among lower socioeconomic groups compared with higher socioeconomic groups. This association was increased when demo-socioeconomic factors and oral health behavioral were adjusted. When each oral health behavioral factor was considered separately, mediators such as smoking, frequency of tooth brushing and used oral care products or oral health examination explained a large part of the increased socioeconomic oral health status. Subjective bad oral health arise from different socioeconomic status, but this difference is increased by oral health behavioral factors. Therefore, socioeconomic inequity in perceived oral health status can be corrected more effectively by promotional oral health behaviors.
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.
The objectives of the study were two folds. The first objective was to determine the dimensions of the evaluative criteria of various clothing items (underwear, pajamas, jeans, blouse, two-piece, coat). The second objective was to compare the importance of the dimensions according to the clothing items and the socioeconomic status of the subjects. The questionnaires were administered to college female students living in Seoul. Principal component factor analysis with varimax rotation and ANOVA were used for the analysis. The results were as follows; 1) The evaluative criteria dimensions were found to be different according to clothing items. (1) In underwear, pajamas, jeans, evaluative criteria were classified into Aesthetic dimension, economic dimension and Functional dimension. (2) In blouse, two-piece, coat, evaluative criteria were classified into Aesthetic dimension and practical dimension. 2) there were partially significant differences in placing importance on each evaluative criteria dimension between socio-economic groups. (1) In jeans, there was a significant difference in placing importance on Aesthetic dimension between socioeconomic status groups. (2) In blouse and two-piece there was a significant difference in placing importance on Practical dimension between socioeconomic status groups.
Kim, Min-Kyung;Chung, Woo-Jin;Lim, Seung-Ji;Yoon, Soo-Jin;Lee, Ja-Kyoung;Kim, Eun-Kyung;Ko, Lan-Ju
Journal of Preventive Medicine and Public Health
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v.43
no.1
/
pp.50-61
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2010
Objectives: The study is investigated socioeconomic variations in self-rated health status and contribution of health behavioral factors in Korea. Methods: A nationally representative sample (2,800 men and 3,230 women aged 20-64 years) from the 2005 Korea National Health and Nutrition Surveys was analyzed using logistic regression. Results: Self-rated health was lower among lower socioeconomic groups compared with higher socioeconomic groups, with gender being irrelevant. This association was attenuated when health behavioral and socio-demographic factors were adjusted. When each health behavioral factor was considered separately, mediators such as smoking in men, and stress or exercise in women explained a large part of the decreased socioeconomic health inequalities. Conclusions: In Korea, subjective health inequalities arise from different socioeconomic status, but this difference is decreased by health behavioral factors. Therefore, socioeconomic inequity in self-rated health status can be corrected more effectively by promotional health behaviors.
Objectives: The aim of this study was to assess the socioeconomic inequality in malnutrition in under-5 children in Iran in order to help policymakers reduce such inequality. Methods: Data on 8443 under-5 children were extracted from the Iran Multiple Indicator Demographic and Health Survey. The wealth index was used as proxy for socioeconomic status. Socioeconomic inequality in stunting, underweight, and wasting was calculated using the concentration index. The concentration index was calculated for the whole sample, as well as for subcategories defined in terms of categories such as area of residence (urban and rural) and the sex of children. Results: Stunting was observed to be more prevalent than underweight or wasting. The results of the concentration index at the national level, as well as in rural and urban areas and in terms of children's sex, showed that inequality in stunting and underweight was statistically significant and that children in the lower quintiles were more malnourished. The wasting index was not sensitive to socioeconomic status, and its concentration index value was not statistically significant. Conclusions: This study showed that it can be misleading to assess the mean levels of malnutrition at the national level without knowledge of the distribution of malnutrition among socioeconomic groups. Significant socioeconomic inequalities in stunting and underweight were observed at the national level and in both urban and rural areas. Regarding the influence of nutrition on the health and economic well-being of preschool-aged children, it is necessary for the government to focus on taking targeted measures to reduce malnutrition and to focus on poorer groups within society who bear a greater burden of malnutrition.
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