Community-level socioeconomic inequality in the incidence of ischemic heart disease: a nationwide cohort study (original) (raw)
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BMJ Open
ObjectiveSeveral studies identified neighbourhood context as a predictor of prognosis in ischaemic heart disease (IHD). The present study investigates the relationships of neighborhood-level and individual-level socioeconomic status with the odds of ongoing management of IHD, using baseline survey data from the Korea Health Examinees-Gem study.DesignIn this cross-sectional study, we estimated the association of the odds of self-reported ongoing management with the neighborhood-level income status and percentage of college graduates after controlling for individual-level covariates using two-level multilevel logistic regression models based on the Markov Chain Monte Carlo function.SettingA survey conducted at 17 large general hospitals in major Korean cities and metropolitan areas during 2005–2013.Participants2932 adult men and women.Outcome measureThe self-reported status of management after incident angina or myocardial infarction.ResultsAt the neighbourhood level, residence in a h...
Socioeconomic Status and Coronary Heart Disease
2011
Background: Iran has undergone a remarkable demographic transition over the last three decades. Socioeconomic status (SES) indicators including education, income, and occupation are associated with coronary heart disease (CHD) risk factors, morbidity, and mortality. The aim of the present study was to describe demographic and socioeconomic characteristics, their association to the diseases, and to explore the predictive risk of CHD in Tabriz, the fourth largest city in Iran and the capital of East Azerbaijan Province. Methods: This cross-sectional descriptive study was carried out to explore and analyze the current SES status of CHD patients. The study was conducted in Tabriz and all patients (n=189) refereed to the Central Referral Hospital for cardiac patients (Shahid Madani Hospi-tal) from 2009 to 2010 were considered. A researcher structured questionnaire with 15 ques-tions was used to collect data. Descriptive statistics were used to describe the basic SES fea-tures of the CHD ...
PLOS ONE, 2015
Background A relatively consistent body of literature, mainly from high-income countries, supports an inverse association between socioeconomic status (SES) and risk of cardiovascular disease (CVD). Data from low-and middle-income countries are scarce. This study explores SES differences in cardiovascular health (CVH) in the Republic of Srpska (RS), Bosnia and Herzegovina, a middle-income country. Methods We collected information on SES (education, employment status and household's relative economic status, i.e. household wealth) and the 7 ideal CVH components (smoking status, body mass index, physical activity, diet, blood pressure, total cholesterol, and fasting blood glucose) among 3601 participants 25 years of age and older, from the 2010 National Health Survey in the RS. Based on the sum of all 7 CVH components an overall CVH score (CVHS) was calculated ranging from 0 (all CVH components at poor levels) to 14 (all CVH components at ideal levels). To assess the differences between groups the chi-square test, t-test and ANOVA were used where appropriate. The association between SES and CVHS was analysed with multivariate linear regression analyses. The dependent variable was CVHS, while independent variables were educational level, employment status and wealth index. Results According to multiple linear regression analysis CVHS was independently associated with education attainment and employment status. Participants with higher educational attainment and those economically active had higher CVHS (b = 0.57; CI = 0.
International Journal of Environmental Research and Public Health, 2018
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 inequali...
Journal of Clinical Epidemiology, 1994
As part of a multicentre collaborative study of'risk factors for cardiovascular disease (CVD) in the International Clinical Epidemiology Network (INCLEN), each of 12 Centres in 7 countries examined the relationship between CVD risk factors and socioeconomic variables. Each Centre (three in Thailand, two each in China, Chile and Brazil and one each in the Philippines, Indonesia and Colombia) examined approx. 200 men aged 35-65 drawn at random from a population within their locality (not designed to be necessarily representative of the general population). Standardized measures of CVD risk factors included body mass index (BMI), blood pressure, blood cholesterol and cigarette smoking habits. Education, occupation and current income were grouped into ordinal categories of socioeconomic status according to standard protocol guidelines, and comparisons were made between risk factor levels within each of these categories. Many of these populations had higher levels of education (as a marker of socioeconomic status) than would the general population of their country. For both BMI and blood cholesterol there were a number of centres which showed positive associations with socioeconomic status. These were predominately in China or urban or rural South East Asia. For blood pressure and cigarette smoking the associations with socioeconomic status tended to be negative, more in line with the direction of association seen in the "Developed" World. The high risk factor levels found in these populations, particularly the alarming prevalence of cigarette smoking in Asia and the high cholesterol levels in Latin America and Urban S.E. Asia suggest that CVD will emerge as a major public health problem in the Developing World. As this happens, knowledge of the patterns of association between risk and socioeconomic status is likely to be important in both understanding the reasons for the patterns of disease and directing efforts at prevention.
PloS one, 2018
This study aimed to examine socioeconomic inequalities in the prevalence of biomarkers of cardiovascular disease and diabetes in the newly developed large-scale genomic cohort study of Korean adults, the Health Examinees-Gem (HEXA-G), with a comparison of the nationally representative cross-sectional study, the Korea National Health and Nutrition Examination Survey (K-NHANES). Using the HEXA-G and the K-NHANES from 2007-2012, we analyzed the age-adjusted relative risk (RR) and prevalence of enlarged waist circumference (EWC), elevated triglycerides (ET), low HDL cholesterol (LHC), elevated blood pressure (EBP) and elevated blood glucose (EBG) by income and educational groups for adults at age 40-69. For men, the prevalence of risk factors was similar across different income and educational groups (p>0.1), and between the K-NHANES and the HEXA-G. Among five risk factors, EBG showed the greatest discrepancy by 7 to 11 percentage points (i.e., the prevalence of 0.43 and 0.36 for col...
International journal for equity in health, 2016
Previous studies have shown that contextual factors and individual socioeconomic status (SES) were associated with mortality in Western developed countries. In Korea, there are few empirical studies that have evaluated the association between SES and health outcomes. We conducted cohort study to investigate the socioeconomic disparity in all-cause mortality for patients newly diagnosed with hypertension in the setting of universal health care coverage. We used stratified random sample of Korean National Health Insurance enrollees (2002-2013). We included patients newly diagnosed with hypertension (n = 28,306) from 2003-2006, who received oral medication to control their hypertension. We generated a frailty model using Cox's proportional hazard regression to assess risk factors for mortality. A total of 7,825 (27.6%) of the 28,306 eligible subjects died during the study period. Compared to high income patients from advantaged neighborhoods, the adjusted hazard ratio (HR) for high...
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South Asian countries have a high prevalence of coronary heart disease (CAD) in line with their economic development. In these countries, we find nearly one quarter of the total world population in the process of nutritional transition, from poverty to affluence due to rapid economic development. India; in particular , with a population of over one billion has a high burden of CAD. To evaluate the role of socioeconomic and demographic variables on the coronary artery disease. A hospital based case-control study was conducted to investigate the role of social related risk factors on coronary artery disease (CAD) in an urban area of East Delhi from April 2002 to December 2004. To obtain more validate comparisons, a control group also was selected from community of East Delhi. The tools of enquiry were a pre-tested and pre-coded questionnaire , physical examination and laboratory testes. A confidence level of 95% and study power of 80% were considered for the interpretation of possible...
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Cardiovascular diseases (CVDs) was one of the three leading cause of death in Thai population. Whether socioeconomics (SES) determinates are associated with CVDs is unclear. This study aimed to determine the association between socioeconomics factors and CVDs prevalence. The study used the data form the NationalSocioeconomics Survey that was a crosssectional study conducted by the National Statistical Office in 2012 The 16,905 sampleswere multi stages randomly selectedfrom all 77 provinces in Thailand to response to a structure questionnaire. The association between SES and CVDs was modeling by multiple logistic regression with controlling the covariates. Most of the samples were female (53.21%) with the average age of 44.38 (S.D.=18.16) years old. The prevalence of CVDs was 10.64% (95% CI: 0.10% To 0.11%.).The result of multivariate analysis indicated that, SES that were risk factors of CVDs were female (ORadj=1.59, 95% CI=1.36 to 1.85), aged ≥ 62 years old (ORadj=83.53, 95% CI=38....
American Journal of Epidemiology, 1996
Much remains to be understood about how low socioeconomic status (SES) increases cardiovascular disease and mortality risk. Data from the Kuopio Ischemic Heart Disease Risk Factor Study (1984)(1985)(1986)(1987)(1988)(1989)(1990)(1991)(1992)(1993) were used to estimate the associations between acute myocardial infarction and income, all-cause mortality, and cardiovascular mortality in a population-based sample of 2,272 Finnish men, with adjustment for 23 biologic, behavioral, psychologic, and social risk factors. Compared with the highest income quintile, those in the bottom quintile had age-adjusted relative hazards of 3.14 (95% confidence interval (Cl) 1.77-5.56), 2.66 (95% Cl 1.25-5.66), and 4.34 (95% Cl 1.95-9.66) for all-cause mortality, cardiovascular mortality, and AMI, respectively. After adjustment for risk factors, the relative hazards for the same comparisons were 1.32 (95% Cl 0.70-2.49), 0.70 (95% Cl 0.29-1.69), and 2.83 (95% Cl 1.14-7.00). In the lowest income quintile, adjustment for risk factors reduced the excess relative risk of all-cause mortality by 85%, that of cardiovascular mortality by 118%, and that of acute myocardial infarction by 45%. These data show how the association between SES and cardiovascular mortality and all-cause mortality is mediated by known risk factor pathways, but full "explanations" for these associations will need to encompass why these biologic, behavioral, psychologic, and social risk factors are differentially distributed by SES. Am J Epidemiol 1996;144:934-42.