Race/ethnicity, SES, & policy implications Flashcards
Adler & Stewart. (2010). Health disparities across the lifespan: Meanings, methods, and mechanisms.
Gist: Over the last 20 years, empirical research regarding SES & health has progressed through five eras. The first era was the threshold model of poverty & health (few studies focused on income as a continuum). The second era focused on gradients in the SES-health relationship, ushered in by the Whitehall studies. The third era begins to ask questions about the mechanisms by which SES affects health: What is it about more money, more education, & higher social class that lead to better health or how does SES get under the skin? Common mechanisms studied include: (a) differential access to health care, (b) environmental exposures, (c) health behaviors, and (d) differential exposure to stress. The fourth era expands to look at multiple levels of influence, commonly focused on characteristics of the neighborhood or community and the individual. Studies in this era examine the ecological embeddedness of risk factors for disease that differ by socioeconomic level & the unjust distribution of environmental resources that enable healthy living & hazards that constrain health living. The fifth era focuses on not just independent associations by also how effects are moderated by combinations of factors (interactions). Approaches include the interaction of individual & neighborhood SES, racial/ethnic differences in health moderated by neighborhood characteristics, & SES-health relationship differing by race/ethnicity.
Muennig, Franks, Jia, Lubetkin, & Gold. (2005). The income-associated burden of disease in the United States.
Gist: They calculated relationships between income and life expectancy, health-adjusted life expectancy, annual years of lost (YLLs), & health adjusted life years (HALYs) using 2000 MEPS & 1990-92 NHIS-NDI. People in the top 20% of households by income have longer lives & experiences less morbidity than the bottom 80% (4.3 years longer & 6.4 HALYs longer). Mechanisms for the health gradient among the wealthy may be driven by psychobiological factors than by resource-related factors. Another argument is that higher mortality among middle-income persons relative to those with higher incomes is an extension of the cumulative effects seen among the low-income.
Definitions:
Health adjusted life years (HALYs): Calculated using health-related qualify of life (HRQL), which is an assessment of the importance people place on the morbidity associated with illness; a year of life lived at an HRQL of 0.8 is equal to 0.8 HALYs.
Health adjusted life expectancy (HALE): Calculated using HRQL; simplified estimation of HALE is the product of life expectancy & the mean HRQL for a particular group.
HRQL: Scores assume a value between 0 (death) & 1 (perfect health).
Mechanic. (2005). Policy challenges in addressing racial disparities and improving population health.
Gist: SES is a fundamental cause of disease but blacks in the U.S. are doubly disadvantaged by low status, discrimination, & residential segregation. Policies due to health disparities should focus on the following issues: (1) new technology can lead to inequality, (2) initiatives aimed at the population (instead of individuals) are more effective (e.g., fluoridated water), (3) should focus on health interconnections instead of single diseases, and (4) school/education is an important vehicle for upward mobility (e.g., programs that prepare children early in life for school success).
Mechanic. (2002). Disadvantage, inequality, and social policy.
Gist: Based on Link & Phelan’s fundamental cause theory, a hypothesis that follows is that overall major initiatives intended to improve population health may also increase disparities. This is because a fundamental cause, social class in this case, has a robust relationship with health over time even as the pathways change. Interventions that depend on voluntary involvement may place greater impediments for the disadvantaged. Interventions that focus on improving population health for problems prevalent among the disadvantaged may not increase disparities (e.g., desegregation, simpler & less costly medical treatments, research on illnesses that impact the poor). Looking internationally, some poor countries have superior infant survival & adult longevity: Kerala in India, Costa Rica, China, Cuba, Sri Lanka, & Jamaica. Three factors are important in these countries: (1) emphasis on educational attainment, (2) empowerment of women, and (3) well-organized primary medical care systems. Although educational opportunity has many advantages, there is evidence that income support to the disadvantaged also providers opportunities for improved health (e.g., health insurance for the elderly, social security benefits, earned income tax credit, TANF).
Marmot. (2002). The influence of income on health: Views of an epidemiologist.
Gist: Income is related to health in 3 ways: (1) through the GNP of countries, (2) the income of individuals, & (3) the income inequalities among rich nations & geographic areas. This paper focuses on two ways in which income could be causally related to health: (1) directly via material conditions & (2) indirectly through social participation & opportunity to control life circumstances. At the low end of the SES scale, individual incomes matter for health because of their link with both material deprivation & restriction on social participation & control. Above a threshold of material deprivation, income may be more important because of its link with the social factors related to social conditions.
Deaton. (2002). Policy implications of the gradient of health and wealth.
Gist: Due to the existence of a health gradient in the U.S., the author argues that there should be income redistribution in favor of the poor but that targeting health inequalities will not be sound policy. The relationship between health & income is a gradient & poverty has a “threshold” effect. Focusing on downstream causes of health are futile without reforming upstream causes in the underlying socioeconomic structure. Causes of the gradient include (1) the effects of health on income, (2) the effects of income on health, (3) the access argument (i.e., better access to health care), (4) effect of life-saving technology, and (5) role of health-related behavior. There is a question as to whether education or income matters for health; evidence suggests there are overlapping and independent effects. There is also the view that income itself doesn’t matter but that relative income impacts health. Overall, economic policy should be health policy. The Pareto criterion states that a policy that harms no one while making at least some people better off is a good thing. There is a need for more general health policies.
Adler & Newman. (2002). Socioeconomic disparities in health: Pathways and policies.
Gist: SES underlies 3 major determinants of health: health care, environmental exposure, & health behavior (& potentially mediated by chronic stress exposure). Three primary components of SES include: (1) education - shapes future occupational opportunities & earning potential, (2) income - providing means for purchasing health care, better nutrition, housing, etc., (3) occupational status - complex & measurement varies depending on theoretical perspective. Policies relating to income include redistributive policies, welfare benefits, & labor market policies (little research focusing on effects of policies). These 3 work indirectly to impact health & are primarily mediated through behavior & lifestyle (50%), environmental exposure (20%), & health care (10%). Environmental exposure can include aspects of both the physical & social environment (suspect the latter makes a larger impact). The biggest impact of behavior is smoking. Chronic stress can impact health directly or indirectly via behaviors. Policies & priorities include a need for cost-benefit analysis, behavioral justice, & need for strong analyses.
Kawachi, Daniels, & Robinson. (2006). Health disparities by race and class: Why both matter.
Gist: Examined 3 competing causal interpretations of racial disparities in health: (1) race as biology, (2) race as a proxy for class, & (3) race and class as separate constructs. The first interpretation is that racial disparities can be explained by inherited biological differences in susceptibility to disease & has long been discredited. The second interpretation is that race is a proxy for class, as evidenced by the fact that in the U.S., blacks are overrepresented among the SES-disadvantaged groups. Analysis of racial differences that adjusts for class might be “overcontrolling” since race is an antecedent for class (& not the other way around). The third (& defensible) view is that race and class are separate constructs and can have independent & interactive effects in producing health disparities & both should be considered in analyses. Class may mediate the relationship between race and health. Often, however, class is rarely discussed regarding health disparities.
Chen, Matthews, & Boyce. (2002). Socioeconomic differences in children’s health: How and why do these relationships change with age?
Gist: Depending on the health outcome, there are three general patterns of the SES-health relationship as children age.
Childhood-adolescent persistent model: SES differences in health are established early in life & remain fairly constant throughout childhood.
Childhood-limited model: SES effects initially are large but gradually decrease over time & are most modest during teenage years; type of model proposed by West.
Adolescent-emergent model: SES effects initially are modest but gradually increase over time & are most apparent during the teenage years; similar model as Power & Hertzman.
The authors’ overall model suggests that although mediational pathways remain similar from childhood to adolescence, normal developmental changes affect the degree of influence of each mediator across time & may help explain how SES developmental trajectories change through childhood & adolescence. The relationship between SES & health follows a monotonic pattern in childhood & adolescence: As SES decreases, mortality & morbidity rates increase (i.e., relationship not simply due to poverty). Collapsing data across all ages of children & adolescents obfuscates the understanding of when & how SES influences their health.
Franks, Muennig, Lubetkin, & Jia. (2006). The burden of disease associated with being African-American in the United States and the contribution of socio-economic status.
Gist: They quantified the contribution of SES & being black in the U.S. in the burden of disease. Overall compared to whites, blacks suffered more deaths annually, more years of life lost (YLLs), & more QALYs lost. SES differences between blacks and whites explained all the HRQL disparity but only 1/2 the mortality disparity.
Braveman, Cubbin, Marchi, Egerter, & Chavez. (2001). Measuring socioeconomic status/position in studies of racial/ethnic disparities: Maternal and infant health.
Gist: How SES is measured impacts conclusions that can be made about the role of race/ethnicity in health. The authors looked at both education & income in the study of racial/ethnic disparities in LBW, delayed prenatal care, unintended pregnancy, & breastfeeding intention. Racial/ethnic associations with the health indicators varied by SES measure, how SES was specified, & by the health indicator. This study shows the importance of choosing SES measures that are outcome- & population-specific and that researchers should test multiple theoretically appropriate measures & consider how conclusions may vary with how SES is measured.
