An ecosystem-based fisheries management (EBFM) approach becomes more important as an alternative management method for a sustainable development of fisheries domestically and internationally. Many methods of applying a practical EBFM to fisheries management have been investigated, and considerable attention has been given to developing effective indicators of the present status of and changes in ecosystems and putting them to practical use. Among ecosystem indicators, developing socioeconomic indicators for EBFM is particularly important. This is because socioeconomic factors have direct effects on ecosystems, and ecosystems have direct effects on socioeconomic factors. Therefore, it is imperative that socioeconomic indicators are developed and evaluated in order to predict changes in ecosystems and to provide advice for effective fisheries management. This study is aimed to develop socioeconomic indicators which can be combined with biological and ecological indicators, in order to conduct the ecosystem-based fisheries assessment. In terms of socioeconomic indicators, five socioeconomic criteria were considered as important attributes of socioeconomic changes. These criteria include economical production, business conditions, income, market, and employment indicators. For evaluation of newly developed socioeconomic indicators, the Traffic Light System (TLS) method was used. In addition, on the basis of the application of developed indicators to the Korean large purse seine fishery, the socioeconomic conditions of the fishery and the usefulness of the indicators were evaluated and management implications were discussed.
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.
Objectives : Socioeconomic position (SEP) refers to the socioeconomic factors that influence which position an individual or group of people will hold within the structure of a society. In this study, we provide a comprehensive review of various indicators of SEP, including education level, occupation-based SEP, income and wealth, area SEP, life-course SEP, and SEP indicators for women, elderly and youth. Methods and results : This report provides a brief theoretical background and discusses the measurement, interpretation issues, advantages and limitations associated with the use of each SEP indicator. We also describe some problems that arise when selecting SEP indicators and highlight the indicators that appear to be appropriate for health inequality research. Some practical information for use in health inequality research in South Korea is also presented. Conclusions : Investigation into the associations between various SEP indicators and health outcomes can provide a more complete understanding of mechanisms between SEP and health. The relationship between specific SEP indicators and specific health outcomes can vary by country due to the differences in the historical, socioeconomic, and cultural contexts of the SEP indicators.
Objectives: The purpose of this study was to examine the associations among self-rated health and socioeconomic status. Methods: Analyses were conducted based on cross-sectional data obtained from the Korea Youth Risk Behavior Web-based Survey. A total of 79,202 students aged 12 to 18 years participated in the study and there was a response rate of 95.5%. Separate logistic regression analyses were performed on each gender group based on a set of independent variables. Those being: the level of parental education level; family affluence scale; subjective household economic status; and subjective school achievement with SRH as the dependent variable. Results: Multivariate analyses revealed significant associations between each SES and adolescent SRH after controlling for other covariates. However, in the models that included all SES indicators, subjective household economic status and subjective school achievement remained significant in boys and girls. Conclusions: The findings demonstrated that subjective SES indicators are more closely related to adolescent SRH when compared with objective indicators.
Objective : This study examined the socioeconomic differentials for the health and health related behaviors among South Korean middle school students. Methods : A nationwide cross-sectional interview survey of 3,449 middle school second-grade students and their parents was conducted using a stratified multi-stage cluster sampling method. The response rate was 93.3%. The socioeconomic position indicators were based on self-reported information from the students and their parents: parental education, father's occupational class, monthly family income, out-of-pocket expenditure for education, housing ownership, educational expectations, educational performance and the perceived economic hardships. The outcome variables that were measured were also based on the self-reported information from the students. The health measures included self-rated health conditions, psychological or mental problems, the feelings of loneliness at school, the overall satisfaction of life and the perceived level of stress. The health related behaviors included were smoking, alcohol drinking, sexual intercourse, violence, bullying and verbal and physical abuse by parents. Results : Socioeconomic differences for the health and health related behaviors were found among the eighth grade boys and girls of South Korea. However, the pattern varied with gender, the socioeconomic position indicators and the outcome measures. The prevalence rates of the overall dissatisfaction with life for both genders differed according to most of the eight socioeconomic position indicators. All the health measures were significantly different according to the perceived economic hardship. However, the socioeconomic differences in the self-rated health conditions and the psychosocial or mental problems were not clear. The students having higher socioeconomic position tended to be a perpetrator of bullying while those students with lower socioeconomic position were more likely to be a victim. Conclusions : The perceived economic hardships predicted the health status among the eighth graders of South Korea. The overall satisfaction of life was associated with the socioeconomic position indicators. Further research efforts are needed to explore the mechanisms on how and why the socioeconomic position affects the health and health related behaviors in this age group.
There were numerous evidences that subjective health evaluation was a powerful indicator for morbidity and mortality in many countries. Since self-rated health (SRH) was a reasonable health measure, identifying predictors for SRH would be beneficial for assessment of overall health, monitoring health status, and development of health promotion programs. Health risks, health behavior, socioeconomic characteristics and social capital were potential indicators for SRH. We examined association. between SRH and indicators such as health risk factors, subjective living condition, income, education level and dietary variety score. Total 4,262 subjects, aged between 20 and 69 years old, were selected from KNHANES 2001; those who completed health examination, nutrition survey, and provided their socioeconomic information. Results of logistic regression showed that it was likely to have better SRH for those who were younger, male and have higher education, higher income, better living condition, no metabolic syndrome and higher dietary variety.
Objectives : The aim of this study is to summarize the current conditions and implications of health inequalities in South Korea. Methods : Through a literature review of empirical studies and supplementary analysis of the data presented in the 1998, 2001, and 2005 KNHANEs, we evaluated the extent and trends of socioeconomic inequalities in both health risk factors, such as smoking, physical activity, and obesity, and outcomes, such as total mortality, subjective poor health status by self-reports and metabolic syndrome. Relative risks and odds ratios were used to measure differences across socioeconomic groups, and the relative index of inequality was used to evaluate the changes in inequalities over time. Results : We found clear inequalities to various degrees?in most health indicators. While little change was observed in mortality differences over time, the socioeconomic gaps in risk factors and morbidity have been widening, with much larger differences among the younger population. Conclusions : Socioeconomic inequalities are pervasive across various health indicators, and some of them are increasing. The trends in socioeconomic inequalities in health should be carefully monitored, and comprehensive measures to alleviate health inequalities are needed, especially for young populations.
Purpose: The purpose of the study is to identify workload measurement indicators for school nurses in order to provide high-quality health care and deploy school nurses effectively. Methods: A second Delphi survey was conducted on 21 experts with more than 5 years of school nurses experience. To develop indicators related to the workload of school nurses, the importance and measurability of a total of 21 workload indicators were investigated, including school nurses characteristics, school characteristics, health needs of students, and socioeconomic determinants. Results: As a result of the Delphi survey, it was found that 6 indicators were suitable in terms of importance and 8 indicators in terms of measurability. The important indicators the panel agreed on include the size of the city where the school is located, the total number of students, the number of classes, the percentage of students with chronic illness, the percentage of students visiting the health office per day, and the percentage of wound care in the health office per day. Conclusion: The percentage of students with chronic illness and the percentage of wound care per day need to be reflected in school nurse workload indicators and follow-up studies are required to shed more light on the socioeconomic determinants of schools.
Objectives: There are at least three conceptual models for the effects of the childhood social environment on adult health: the critical period model, the social mobility model, and the cumulative risk model. However, few studies have investigated all three different models within the same setting. This study aims to examine the impact of childhood and adulthood socioeconomic positions and intergenerational social mobility over the life course on the health in adulthood based both on the critical period model and the social mobility model. Methods: This study was conducted on 9583 adults aged between 25 and 64 years old and they were the respondents to the Korea Welfare Panel Study (2006). A multivariate logistic regression analysis was carried out, using the critical period model and the social mobility model out of the life course approaches, to look into the impact of childhood and adulthood socioeconomic positions and intergenerational social mobility on the health status in adulthood. Results: Household income and occupation out of the adulthood socioeconomic position indicators had an independent influence on the adulthood health status. The childhood socioeconomic position indicators, except for the place of childhood residence, affected the adulthood health status even after adjustment for the adulthood socioeconomic position. The effect of intergenerational social mobility was also statistically significant even after adjusting for the adulthood socioeconomic position, but it became insignificant when the childhood socioeconomic position was additionally adjusted for. Conclusions: Adulthood health is indeed affected by both the childhood and adulthood socioeconomic positions as well as intergenerational social mobility. This result shows that a life course approach needs to be adopted when dealing with health issues.
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.
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