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      Demographic and biologic influences on survival in whites and blacks: 40 years of follow-up in the Charleston heart study

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          Abstract

          Background

          In the United States, life expectancy is significantly lower among blacks than whites. We examined whether socioeconomic status (SES) and cardiovascular disease (CVD) risk factors may help explain this disparity.

          Methods

          Forty years (1961 through 2000) of all-cause mortality data were obtained on a population-based cohort of 2,283 subjects in the Charleston Heart Study (CHS). We examined the influence of SES and CVD risk factors on all-cause mortality.

          Results

          Complete data were available on 98% of the original sample (647 white men, 728 white women, 423 black men, and 443 black women). After adjusting for SES and CVD risk factors, the hazard ratios (HRs) for white ethnicity were 1.14 (0.98 to 1.32) among men and 0.90 (0.75 to 1.08) among women, indicating that the mortality risk was 14% greater for white men and 10% lower for white women compared to their black counterparts. However the differences were not statistically significant.

          Conclusion

          While there are marked contrasts in mortality among blacks and whites in the CHS, the differences can be largely explained by SES and CVD risk factors. Continued focus on improving and controlling cardiovascular disease risk factors may reduce ethnic disparities in survival.

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          Most cited references25

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          Socioeconomic factors, health behaviors, and mortality: results from a nationally representative prospective study of US adults.

          A prominent hypothesis regarding social inequalities in mortality is that the elevated risk among the socioeconomically disadvantaged is largely due to the higher prevalence of health risk behaviors among those with lower levels of education and income. To investigate the degree to which 4 behavioral risk factors (cigarette smoking, alcohol drinking, sedentary lifestyle, and relative body weight) explain the observed association between socioeconomic characteristics and all-cause mortality. Longitudinal survey study investigating the impact of education, income, and health behaviors on the risk of dying within the next 7.5 years. A nationally representative sample of 3617 adult women and men participating in the Americans' Changing Lives survey. All-cause mortality verified through the National Death Index and death certificate reviews. Educational differences in mortality were explained in full by the strong association between education and income. Controlling for age, sex, race, urbanicity, and education, the hazard rate ratio of mortality was 3.22 (95% confidence interval [CI], 2.01-5.16) for those in the lowest-income group and 2.34 (95% CI, 1.49-3.67) for those in the middle-income group. When health risk behaviors were considered, the risk of dying was still significantly elevated for the lowest-income group (hazard rate ratio, 2.77; 95% CI, 1.74-4.42) and the middle-income group (hazard rate ratio, 2.14; 95% CI, 1.38-3.25). Although reducing the prevalence of health risk behaviors in low-income populations is an important public health goal, socioeconomic differences in mortality are due to a wider array of factors and, therefore, would persist even with improved health behaviors among the disadvantaged.
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            Preventable hospitalizations and access to health care.

            To examine whether the higher hospital admission rates for chronic medical conditions such as asthma, hypertension, congestive heart failure, chronic obstructive pulmonary disease, and diabetes in low-income communities resulted from community differences in access to care, prevalence of the diseases, propensity to seek care, or physician admitting style. Analysis of California hospital discharge data. We calculated the hospitalization rates for these five chronic conditions for the 250 ZIP code clusters that define urban California. We performed a random-digit telephone survey among adults residing in a random sample of 41 of these urban ZIP code clusters stratified by admission rates and a mailed survey of generalist and emergency physicians who practiced in the same 41 areas. Community based. A total of 6674 English- and Spanish-speaking adults aged 18 through 64 years residing in the 41 areas were asked about their access to care, their chronic medical conditions, and their propensity to seek health care. Physician admitting style was measured with written clinical vignettes among 723 generalist and emergency physicians practicing in the same communities. We compared respondents' reports of access to medical care in an area with the area's cumulative admission rate for these five chronic conditions. We then tested whether access to medical care remained independently associated with preventable hospitalization rates after controlling for the prevalence of the conditions, health care seeking, and physician practice style. Access to care was inversely associated with the hospitalization rates for the five chronic medical conditions (R2 = 0.50; P < .001). In a multivariate analysis that included a measure of access, the prevalence of conditions, health care seeking, and physician practice style to predict cumulative hospitalization rates for chronic medical conditions, both self-rated access to care (P < .002) and the prevalence of the conditions (P < .03) remained independent predictors. Communities where people perceive poor access to medical care have higher rates of hospitalization for chronic diseases. Improving access to care is more likely than changing patients' propensity to seek health care or eliminating variation in physician practice style to reduce hospitalization rates for chronic conditions.
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              Race, socioeconomic status, and health. The added effects of racism and discrimination.

              Higher disease rates for blacks (or African Americans) compared to whites are pervasive and persistent over time, with the racial gap in mortality widening in recent years for multiple causes of death. Other racial/ethnic minority populations also have elevated disease risk for some health conditions. This paper considers the complex ways in which race and socioeconomic status (SES) combine to affect health. SES accounts for much of the observed racial disparities in health. Nonetheless, racial differences often persist even at "equivalent" levels of SES. Racism is an added burden for nondominant populations. Individual and institutional discrimination, along with the stigma of inferiority, can adversely affect health by restricting socioeconomic opportunities and mobility. Racism can also directly affect health in multiple ways. Residence in poor neighborhoods, racial bias in medical care, the stress of experiences of discrimination and the acceptance of the societal stigma of inferiority can have deleterious consequences for health.
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                Author and article information

                Journal
                Int J Equity Health
                International Journal for Equity in Health
                BioMed Central (London )
                1475-9276
                2006
                3 July 2006
                : 5
                : 8
                Affiliations
                [1 ]Department of Biostatistics, Bioinformatics, and Epidemiology, Medical University of South Carolina, 135 Cannon St., Suite 303, P.O. Box 250835, Charleston, SC 29425, USA
                [2 ]Mission Hospitals, Inc., Research Institute, 509 Biltmore Avenue, Asheville, NC 28801, USA
                [3 ]Department of Neurosciences, Medical University of South Carolina, 96 Jonathan Lucas Street, P.O. Box 250606, Charleston, SC, USA
                Article
                1475-9276-5-8
                10.1186/1475-9276-5-8
                1533830
                16817956
                53791b86-0d83-4210-9c2f-6ec43bd87069
                Copyright © 2006 Nietert et al; licensee BioMed Central Ltd.

                This is an Open Access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 8 July 2005
                : 3 July 2006
                Categories
                Research

                Health & Social care
                Health & Social care

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