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      An Assessment of Magnitudes and Patterns of Socioeconomic Inequalities across Various Health Problems: A Large National Cross-Sectional Survey in Korea

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          Abstract

          Magnitudes of health inequalities present consequences of socioeconomic impact on each health problem. To provide knowledge on the size of health problems in terms of socioeconomic burden, we examined the magnitudes and patterns of health inequalities across 12 health problems. A total of 17,292 participants older than 30 years were drawn from the Korea National Health and Nutrition Examination Survey (KNHANES, 2010–2012). The age-adjusted prevalence ratios were compared across socioeconomic positions (SEPs) based on income, education, and occupation. The magnitudes of socioeconomic inequalities varied across 12 health problems and, in general, the patterns of socioeconomic inequalities were similar among groups of health problems (i.e., non-communicable diseases (NCDs), mental health, and subjective health states). Significant health inequalities across NCDs, such as diabetes, hypertension, ischemic heart disease, and arthritis, were observed mainly in women. Socioeconomic inequalities in mental health problems, such as depression, suicidal ideation, and suicide attempts, were profound for both genders and across SEP measures. Significant socioeconomic inequalities were also observed for subjective health. No or weak associations were observed for injury and HBV infection. The patterns of socioeconomic inequalities were similar among groups of health problems. Mental illnesses appeared to require prioritization of socioeconomic approaches for improvement in terms of absolute prevalence and relative socioeconomic distribution.

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          South Korean time trade-off values for EQ-5D health states: modeling with observed values for 101 health states.

          This study establishes the South Korean population-based preference weights for EQ-5D based on values elicited from a representative national sample using the time trade-off (TTO) method. The data for this paper came from a South Korean EQ-5D valuation study where 1307 representative respondents were invited to participate and a total of 101 health states defined by the EQ-5D descriptive system were directly valued. Both aggregate and individual level modeling were conducted to generate values for all 243 health states defined by EQ-5D. Various regression techniques and model specifications were also examined in order to produce the best fit model. Final model selection was based on minimizing the difference between the observed and estimated value for each health state. The N3 model yielded the best fit for the observed TTO value at the aggregate level. It had a mean absolute error of 0.029 and only 15 predictions out of 101 had errors exceeding 0.05 in absolute magnitude. The study successfully establishes South Korean population-based preference weights for the EQ-5D. The value set derived here is based on a representative population sample, limiting the interpolation space and possessing better model performance. Thus, this EQ-5D value set should be given preference for use with the South Korean population.
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            Socioeconomic inequalities in morbidity and mortality in western Europe. The EU Working Group on Socioeconomic Inequalities in Health.

            Previous studies of variation in the magnitude of socioeconomic inequalities in health between countries have methodological drawbacks. We tried to overcome these difficulties in a large study that compared inequalities in morbidity and mortality between different countries in western Europe. Data on four indicators of self-reported morbidity by level of education, occupational class, and/or level of income were obtained for 11 countries, and years ranging from 1985 to 1992. Data on total mortality by level of education and/or occupational class were obtained for nine countries for about 1980 to about 1990. We calculated odds ratios or rate ratios to compare a broad lower with a broad upper socioeconomic group. We also calculated an absolute measure for inequalities in mortality, a risk difference, which takes into account differences between countries in average rates of illhealth. Inequalities in health were found in all countries. Odds ratios for morbidity ranged between about 1.5 and 2.5, and rate ratios for mortality between about 1.3 and 1.7. For men's perceived general health, for instance, inequalities by level of education in Norway were larger than in Switzerland or Spain (odds ratios [95% CI]: 2.57 [2.07-3.18], 1.60 [1.30-1.96], 1.65 [1.44-1.88], respectively). For mortality by occupational class, in men aged 30-44, the rate ratio was highest in Finland (1.76 [1.69-1.83]), although there was no large difference in the size of the inequality in those countries with data. For men aged 45-59, for whom France did have data, this country had the largest inequality (1.71 [1.66-1.77]). In the age-group 45-64, the absolute risk difference ranked Finland second after France (9.8% [9.1-10.4], 11.5% [10.7-12.4]), with Sweden and Norway coming out more favourably than on the basis of rate ratios. In a scatter-plot of average rank scores for morbidity versus mortality. Sweden and Norway had larger relative inequalities in health than most other countries for both measures; France fared badly for mortality but was average for morbidity. Our results challenge conventional views on the between-country pattern of inequalities in health in western European countries.
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              Socioeconomic inequalities in non-communicable diseases and their risk factors: an overview of systematic reviews

              Background Non-communicable diseases (NCDs) are the largest cause of premature death worldwide. Socioeconomic inequalities contribute to a disparity in the burden of NCDs among disadvantaged and advantaged populations in low (LIC), middle (MIC), and high income countries (HIC). We conducted an overview of systematic reviews to systematically and objectively assess the available evidence on socioeconomic inequalities in relation to morbidity and mortality of NCDs and their risk factors. Methods We searched PubMed, The Cochrane Library, EMBASE, SCOPUS, Global Health, and Business Source Complete for relevant systematic reviews published between 2003 and December 2013. Two authors independently screened abstracts and full-text publications and determined the risk of bias of the included systematic reviews. Results We screened 3302 abstracts, 173 full-text publications and ultimately included 22 systematic reviews. Most reviews had major methodological shortcomings; however, our synthesis showed that having low socioeconomic status (SES) and/or living in low and middle income countries (LMIC) increased the risk of developing cardiovascular diseases (CVD), lung and gastric cancer, type 2 diabetes, and chronic obstructive pulmonary disease (COPD). Furthermore, low SES increased the risk of mortality from lung cancer, COPD, and reduced breast cancer survival in HIC. Reviews included here indicated that lower SES is a risk factor for obesity in HIC, but this association varied by SES measure. Early case fatalities of stroke were lower and survival of retinoblastoma was higher in MIC compared to LIC. Conclusions The current evidence supports an association between socioeconomic inequalities and NCDs and risk factors for NCDs. However, this evidence is incomplete and limited by the fairly low methodological quality of the systematic reviews, including shortcomings in the study selection and quality assessment process. Electronic supplementary material The online version of this article (doi:10.1186/s12889-015-2227-y) contains supplementary material, which is available to authorized users.
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                Author and article information

                Journal
                Int J Environ Res Public Health
                Int J Environ Res Public Health
                ijerph
                International Journal of Environmental Research and Public Health
                MDPI
                1661-7827
                1660-4601
                14 December 2018
                December 2018
                : 15
                : 12
                : 2868
                Affiliations
                [1 ]Department of Preventive Medicine, School of Medicine, Kyungpook National University, Daegu 41944, Korea; jyshin@ 123456knu.ac.kr
                [2 ]Department of Preventive Medicine, College of Medicine, Eulji University, Daejeon 34824, Korea; jslim@ 123456eulji.ac.kr
                [3 ]Department of Preventive Medicine, College of Medicine, Korea University, 73 Inchon-ro, Seongbuk-gu, Seoul 02841, Korea
                [4 ]Jeonnam communicable disease management support team, Chonnam national university Hwasun, Hwasun 58128, Korea; syjace@ 123456nate.com
                [5 ]Department of Health Administration, Jungwon University, Goesan 28024, Korea; heeranchun@ 123456gmail.com
                [6 ]Health Care Policy Research Department, Korea Institute for Health and Social Affairs, Sejong 30066, Korea; djkim@ 123456kihasa.re.kr
                Author notes
                [* ]Correspondence: myungki@ 123456korea.ac.kr ; Tel.: +82-(0)2-2286-1173
                [†]

                These 1st authors contributed equally to this work.

                Author information
                https://orcid.org/0000-0002-8761-3744
                https://orcid.org/0000-0002-5543-8574
                Article
                ijerph-15-02868
                10.3390/ijerph15122868
                6313447
                30558216
                62f6e482-93ea-4904-ab59-17a0eab2524d
                © 2018 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 10 September 2018
                : 11 December 2018
                Categories
                Article

                Public health
                socioeconomic inequalities in common health problems,socioeconomic factors,health inequalities in non-communicable diseases,health inequalities in mental diseases,health inequalities policy,korea

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