Minority Health and Health Equity Archive
Permanent URI for this collectionhttp://hdl.handle.net/1903/21769
Welcome to the Minority Health and Health Equity Archive (MHHEA), an electronic archive for digital resource materials in the fields of minority health and health disparities research and policy. It is offered as a no-charge resource to the public, academic scholars and health science researchers interested in the elimination of racial and ethnic health disparities.
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Item Racial and Ethnic Differences in Access to and Use of Health Care Services, 1977 to 1996(2000) Weinick, Robin M.; Zuvekas, Samuel H.; Cohen, Joel W.Abstract available at publisher's web site.Item Measuring socioeconomic status/position in studies of racial/ethnic disparities: maternal and infant health.(2001) Braveman, P; Cubbin, C; Marchi, K; Egerter, S; Chavez, GOBJECTIVE: Theoretical and empiric considerations raise concerns about how socioeconomic status/position (abbreviated here as SES) is often measured in health research. The authors aimed to guide the use of two common socioeconomic indicators, education and income, in studies of racial/ethnic disparities in low birthweight, delayed prenatal care, unintended pregnancy, and breastfeeding intention. METHODS: Data from a statewide postpartum survey in California (N = 10,055) were linked to birth certificates. Overall and by race/ethnicity, the authors examined: (a) correlations among several measures of education and income; (b) associations between each SES measure and health indicator; and (c) racial/ethnic disparities in the health indicators "adjusting" for different SES measures. RESULTS: Education-income correlations were moderate and varied by race/ethnicity. Racial/ethnic associations with the health indicators varied by SES measure, how SES was specified, and by health indicator. CONCLUSIONS: Conclusions about the role of race/ethnicity could vary with how SES is measured. Education is not an acceptable proxy for income in studies of ethnically diverse populations of childbearing women. SES measures generally should be outcome- and population-specific, and chosen on explicit conceptual grounds; researchers should test multiple theoretically appropriate measures and consider how conclusions might vary with how SES is measured. Researchers should recognize the difficulty of measuring SES and interpret findings accordingly.Item Poverty and obesity: the role of energy density and energy costs.(2004) Drewnowski, Adam; Specter, S EMany health disparities in the United States are linked to inequalities in education and income. This review focuses on the relation between obesity and diet quality, dietary energy density, and energy costs. Evidence is provided to support the following points. First, the highest rates of obesity occur among population groups with the highest poverty rates and the least education. Second, there is an inverse relation between energy density (MJ/kg) and energy cost (US dollars/MJ), such that energy-dense foods composed of refined grains, added sugars, or fats may represent the lowest-cost option to the consumer. Third, the high energy density and palatability of sweets and fats are associated with higher energy intakes, at least in clinical and laboratory studies. Fourth, poverty and food insecurity are associated with lower food expenditures, low fruit and vegetable consumption, and lower-quality diets. A reduction in diet costs in linear programming models leads to high-fat, energy-dense diets that are similar in composition to those consumed by low-income groups. Such diets are more affordable than are prudent diets based on lean meats, fish, fresh vegetables, and fruit. The association between poverty and obesity may be mediated, in part, by the low cost of energy-dense foods and may be reinforced by the high palatability of sugar and fat. This economic framework provides an explanation for the observed links between socioeconomic variables and obesity when taste, dietary energy density, and diet costs are used as intervening variables. More and more Americans are becoming overweight and obese while consuming more added sugars and fats and spending a lower percentage of their disposable income on food.Item Income, Earnings, and Poverty Data From the 2007 American Community Survey,(U.S. Government Printing Office, 2008) Bishaw, Alemayehu; Semega, JessicaThis report presents data on income, earnings, and poverty by detailed socioeconomic characteristics for the United States, states, and lower levels of geography based on information collected in the 2006 and 2007 American Community Surveys (ACS). A description of the ACS is provided in the text box “What Is the American Community Survey?” The U.S. Census Bureau also reports income, earnings, and poverty data based on the Current Population Survey Annual Social and Economic Supplement (CPS ASEC). Following the standard specified by the Offi ce of Management and Budget (OMB) in Statistical Policy Directive 14, the Census Bureau computes offi cial national poverty rates using the CPS ASEC and reports the 2007 data in the publication Income, Poverty, and Health Insurance Coverage in the United States: 2007. The 2007 ACS is the second year of the survey’s implementation including both housing units and group quarters in its sample.2 The ACS is designed to provide detailed estimates of housing, demographic, social, and economic characteristics for the states, counties, places, and other localities. This report makes state-level comparisons over the 2006 to 2007 time period. Such comparisons should be interpreted with caution because of overlapping income reference periods.Item Current Population Reports, P60-235, Income, Poverty, and Health Insurance Coverage in the United States: 2007(U.S. Government Printing Office, 2008) Carmen, DeNavas-Walt; Proctor, Bernadette D.; Smith, Jessica C.This report presents data on income, poverty, and health insurance coverage in the United States based on information collected in the 2008 and earlier Annual Social and Economic Supplements (ASEC) to the Current Population Survey (CPS) conducted by the U.S. Census Bureau. Data presented in this report indicate the following: • Real median household income increased between 2006 and 2007—the third annual increase.1 • The poverty rate was not statistically different between 2006 and 2007. • Both the number and the percentage of people without health insurance coverage decreased between 2006 and 2007. These results were not uniform across groups. For example, between 2006 and 2007, real median household income rose for non-Hispanic Whites and Blacks but remained statistically unchanged for Asians and Hispanics; the poverty rate increased for children under 18 years old but remained statistically unchanged for people 18 to 64 years old and people 65 and over; and the percentage of people without health insurance decreased for the native-born population, while the foreign-born population remained statistically unchanged.2, 3 These results are discussed in more detail in the three main sections of this report income, poverty, and health insurance coverage. Each section presents estimates by characteristics such as race, Hispanic origin, nativity, and region. Other topics include earnings of year-round, full-time workers; families in poverty; and health insurance coverage of children. This report concludes with a section discussing health insurance coverage by state using 2- and 3-year averages.Item A methodological note on modeling the effects of race: the case of psychological distress(2008) Nuru-Jeter, Amani; Williams, Chyvette T.; LaVeist, Thomas A.Psychological distress is an important indicator of the mental well-being of the population. Findings regarding racial differences in distress are inconclusive but may represent an important pathway through which disparities exist across a number of physical health outcomes. We used data from the 1994 Minority Health Survey, a nationally representative multiracial/ethnic sample of adults in US households, to examine racial/ethnic differences in psychological distress (n = 3623). Our primary study aim was to examine differences between additive and multiplicative models in assessing the influence of income and gender on the race/distress relationship. We hypothesized that additive models do not suffi ciently account for potential interactions of race with income and gender, and may therefore mask important differences in distress between racial groups. The results suggest that our hypotheses were supported. After adjusting for income, there were no statistically signifi cant differences in distress levels between racial groups. However, significant differences emerge when multiplicative models are used demonstrating the complexities of the intersection of race, income and gender in predicting psychological distress. Black men and women of higher income status represent a particularly vulnerable group, whereas Hispanic men are especially hardy. We discuss the implications of our fi ndings for future work on racial health disparities.Item Endometrial Cancer: Socioeconomic Status and Racial/Ethnic Differences in Stage at Diagnosis, Treatment, and Survival(2004) Madison, Terri; Schottenfeld, David; James, Sherman A.; Schwartz, Ann G.; Gruber, Stephen B.Objective. We evaluated the association between socioeconomic status and racial/ ethnic differences in endometrial cancer stage at diagnosis, treatment, and survival. Methods. We conducted a population-based study among 3656 women. Results. Multivariate analyses showed that either race/ethnicity or income, but not both, was associated with advanced-stage disease. Age, stage at diagnosis, and income were independent predictors of hysterectomy. African American ethnicity, increased age, aggressive histology, poor tumor grade, and advancedstage disease were associated with increased risk for death; higher income and hysterectomy were associated with decreased risk for death. Conclusions. Lower income was associated with advanced-stage disease, lower likelihood of receiving a hysterectomy, and lower rates of survival. Earlier diagnosis and removal of barriers to optimal treatment among lower-socioeconomic status women will diminish racial/ethnic differences in endometrial cancer survival.Item Income, Poverty, and Health Insurance Coverage in the United States: 2005(2006) DeNavas-Walt, Carmen; Proctor, Bernadette D.; Lee, Cheryl HillThis report presents data on income, poverty, and health insurance coverage in the United States based on information collected in the 2006 and earlier Annual Social and Economic Supplements (ASEC) to the Current Population Survey (CPS) conducted by the U.S. Census Bureau. Real median household income increased between 2004 and 2005. Both the number of people in poverty and the poverty rate were not statistically different between 2004 and 2005. The number of people with health insurance coverage increased, while the percentage of people with health insurance coverage decreased between 2004 and 2005. Both the number and the percentage of people without health insurance coverage increased between 2004 and 2005. These results were not uniform across demographic groups. For example, the poverty rate for non-Hispanic Whites decreased, while the overall rate was statistically unchanged. This report has three main sections— income, poverty, and health insurance coverage.Item Fast Food, Race/Ethnicity, and Income: A Geographic Analysis(2004) Block, Jason P; Scribner, Richard A; DeSalvo, Karen BBackground: Environmental factors may contribute to the increasing prevalence of obesity, especially in black and low-income populations. In this paper, the geographic distribution of fast food restaurants is examined relative to neighborhood sociodemographics. Methods: Using geographic information system software, all fast-food restaurants within the city limits of New Orleans, Louisiana, in 2001 were mapped. Buffers around census tracts were generated to simulate 1-mile and 0.5-mile “shopping areas” around and including each tract, and fast food restaurant density (number of restaurants per square mile) was calculated for each area. Using multiple regression, the geographic association between fast food restaurant density and black and low-income neighborhoods was assessed, while controlling for environmental confounders that might also influence the placement of restaurants (commercial activity, presence of major highways, and median home values). Results: In 156 census tracts, a total of 155 fast food restaurants were identified. In the regression analysis that included the environmental confounders, fast-food restaurant density in shopping areas with 1-mile buffers was independently correlated with median household income and percent of black residents in the census tract. Similar results were found for shopping areas with 0.5-mile buffers. Predominantly black neighborhoods have 2.4 fast-food restaurants per square mile compared to 1.5 restaurants in predominantly white neighborhoods. Conclusions: The link between fast food restaurants and black and low-income neighborhoods may contribute to the understanding of environmental causes of the obesity epidemic in these populations.