State-level variations in income-related inequality in health and health achievement in the US
Section snippets
Background
The positive correlation between poverty and poor health has been well documented in the literature. In studies of the US, income inequality was used to predict health (measured by several indicators such as mortality and prevalence of diseases) at the state level (Kawachi & Kennedy, 1997; Kennedy, Kawachi, & Prothrow-Stith, 1996). Over half of the variation in age-adjusted total mortality was explained by income inequality. Furthermore, one study using multi-level analysis found that
Measures of income-related inequality in health and health achievement
Although inequality in health can be generally measured by contrasting the health status of individuals who differ by socio-economic characteristics, such as educational achievement (Kunst & Mackenbach, 1994) and race/ethnicity, (Baker, Hoel, Mohr, Lipsitz, & Lackland, 2000; Keppel, Pearcy, & Wagener, 2002; Saftlas, Koonin, & Atrash, 2000; Stewart & Silverstein, 2002) income distribution has been predominantly used in the literature because it is the strongest predictor of the availability of
Results
The average health value of the population in the United States was 0.867, with the average health for the states ranging from 0.845 to 0.887. All states in the US including the District of Columbia had a positive HCI, indicating health inequalities favoring the well offs (Table 1). For the entire US population, the HCI had a value of 0.0166, with the states’ values ranging from 0.0072 to 0.0259. The higher the HCI value, the greater the degree of inequalities. All HCIs were significantly
Discussion
The investigation of health inequality suggests that income-related inequality in health exists in not only the developing countries, but also industrialized countries, among which the United States as a nation often ranks at the low end when income-related inequality in health is measured by HCI as in the current study (Humphries & van Doorslaer, 2000; van Doorslaer et al., 1997). It is possible that the lower rank of the United States compared to the other industrialized countries, in terms
References (33)
- et al.
Racial, age, and rural/urban disparity in cervical cancer incidence
Annals of Epidemiology
(2000) - et al.
On the measurement of relative and absolute income-related health inequality
Social Science and Medicine
(2002) - et al.
A note on validating Wagstaff and van Doorslaer's health measure in the analysis of inequalities in health
Journal of Health Economics
(1999) - et al.
Income-related health inequality in Canada
Social Science and Medicine
(2000) - et al.
Socioeconomic inequalities in health: Measurement, computation, and statistical inference
Journal of Econometrics
(1997) - et al.
The relationship of income inequality to mortality: Does the choice of indicator matter?
Social Science and Medicine
(1997) - et al.
Measuring the magnitude of socio-economic inequalities in health: An overview of available measures illustrated with two examples from Europe
Social Science and Medicine
(1997) - et al.
Journal of Clinical Epidemiology
(1989) - et al.
Aggregation and the measurement of income inequality: Effects on morbidity
Social Science and Medicine
(1999) - et al.
Income-related inequalities in health: Some international comparisons
Journal of Health Economics
(1997)
Equity in the delivery of health care in Europe and the US
Journal of Health Economics
On the measurement of inequalities in health
Social Science and Medicine
Inequality aversion, health inequalities and health achievement
Journal of Health Economics
Regression analysis by example
Distress and perceived health: Mechanisms of health decline
Journal of Health and Social Behavior
Health trajectories: Long-term dynamics among black and white adults
Journal of Health and Social Behavior
Cited by (30)
Environmental pollution and socioeconomic health inequality: Evidence from China
2023, Sustainable Cities and SocietyRevealing mental health status in Iran's capital: Putting equity and efficiency together
2012, Social Science and MedicineCitation Excerpt :Adam Wagstaff first proposed the AI method (Wagstaff, 2002) in order to assess the status of 44 developing countries with regard to the three health variables of mortality in the under-five age group, child malnutrition and adult fertility rates. Following on from Wagstaff's seminal work, this method has been applied in several studies, including Ke Xu's study of general health in the US (Xu, 2006), Hernandez-Quevedo's investigation into physical disabilities across Europe (Hernandez-Quevedo,Jones, Lopez-Nicolas, & Rice, 2006), Olalekan Uthman's study of chronic childhood malnutrition in Nigeria (Uthman, 2009) and finally, Arokiasamy and Pradhan's analysis of children's health in India (Arokiasamy & Pradhan, 2010). In this paper, we applied the AI approach in an attempt to reveal mental health status in Iran's capital, Tehran.
Measuring inequalities in health: What do we know? What do we need to know?
2012, Health PolicyCitation Excerpt :If ill-health declines monotonically with income, the greater the degree of inequality aversion, the greater the gap between the mean μ and the value of the index IHA(v). Several applications of the IHA have been provided in the literature; Hernández Quevedo et al. [13], who exploit the European Community Household Panel (ECHP) database, Meheus and van Doorslaer [32] study based on the Demographic and Health Surveys and Xu [33] using the US Current Population Survey, are some examples. Wagstaff et al. [34] show that the health concentration index can be decomposed into the contributions of individual factors to income-related health inequality, in which each contribution is the product of the sensitivity of health with respect to that factor and the degree of income-related inequality in that particular factor.
Measuring achievement: Changes in risk factors for cardiovascular disease in Australia
2009, Social Science and MedicineCitation Excerpt :The AI combines both a measure of average morbidity (or health) and an absolute measure of inequality in morbidity (or health) into a single measure. The AI has been used to compare measures of child health across developing countries (Wagstaff, 2002), measures of self-reported health across states within a country (Xu, 2006), and indicators of health limitations within eight European countries across time (Hernandez-Quevedo, Jones, Lopez Nicolas, & Rice, 2006). To date, comparisons conducted using the AI, have been based on rankings of point estimates and have not taken into account uncertainty, or undertaken hypothesis testing using statistical methods.
Calculating concentration index with repetitive values of indicators of economic welfare
2009, Journal of Health EconomicsCitation Excerpt :To compare the two variance estimates, we need a baseline variance estimate. Because there are no well-established analytical variance estimators in such cases, we use bootstrapped standard errors as an approximate baseline estimate, as suggested in the literature (e.g., Xu, 2006). The first exercise involves the use of the NHIS 2004.