Education and Income --- United States, 2005 and 2009

Gloria L. Beckles, MD1

Benedict I. Truman, MD2

1National Center for Chronic Disease Prevention and Health Promotion, CDC

2Epidemiology and Analysis Program Office, CDC

Corresponding author: Gloria L. Beckles, MD, Division of Diabetes Translation, National Center for Chronic Disease Prevention and Health Promotion, CDC, 1600 Clifton Road, N.E., MS K-10, Atlanta, GA 30333. Telephone: 770-488-1272; Fax: 770-488-8364; E-mail: glb4@cdc.gov.

The socioeconomic circumstances of persons and the places where they live and work strongly influence their health (1,2). In the United States, as elsewhere, the risk for mortality, morbidity, unhealthy behaviors, reduced access to health care, and poor quality of care increases with decreasing socioeconomic circumstances (2,3). This association is continuous and graded across a population and cumulative over the life course (2,3). Educational attainment and family or household income are two indicators used commonly to assess the influence of socioeconomic circumstances on health (4). Education is a strong determinant of future employment and income. In the majority of persons, educational attainment reflects material and other resources of family of origin and the knowledge and skills attained by young adulthood. Therefore, it captures both the long-term influence of early life circumstances and the influence of adult circumstances on adult health. Income is the indicator that most directly measures material resources. Income can influence health by its direct effect on living standards (e.g., access to better quality food and housing, leisure-time activities, and health-care services).

To assess disparities in the prevalence of noncompletion of high school and poverty, CDC analyzed data from the 2005 and 2009 Integrated Public Use Microdata Series --- Current Population Survey (IPUMS-CPS) (5). CPS is a cross-sectional monthly household survey of a representative sample of the civilian, noninstitutionalized U.S. household population and is conducted jointly by the U.S. Census Bureau and the Bureau of Labor Statistics. Adults are asked demographic and employment-related questions, including age, sex, race/ethnicity, level of education attained, total family income, family composition, and disability status. Poverty status, measured by the poverty-to-income ratio (PIR), was derived from the established federal poverty level (FPL), which is revised annually to reflect changes in the cost of living as measured by the Consumer Price Index (6). Group disparities in age-standardized prevalence of noncompletion of high school and poverty (PIR <100% of FPL) were assessed according to sex, race/ethnicity, age, education, PIR, and disability. Referent groups were selected that demonstrated the most favorable group estimates; for racial/ethnic disparities, white males and females were selected as referent groups because they were the largest groups (7,8). Absolute disparity was measured as the simple difference between a group estimate and the estimate for its respective referent group. Relative disparity (percentage difference) was obtained by expressing the value for the absolute difference as a percentage of the value for the referent group. For example, with females as the referent group, the relative disparity in prevalence between males and females is the absolute disparity divided by the value for females, with the fraction expressed as a percentage. To evaluate change in disparity during 2005--2009, CDC used these same methods to calculate absolute and relative differences for the groups in 2005 and subtracted statistically significant relative differences in 2005 from their counterparts in 2009 (7,8). Statistically significant increases and decreases in relative difference from 2005 to 2009 were interpreted as increases and decreases in disparity with time, respectively. SAS-callable (SAS Institute Inc., Cary, North Carolina) SUDAAN (Research Triangle Institute, Research Triangle Park, North Carolina) software that accounted for the CPS complex sample design was used, with sample weights, replicate weights, and the balanced repeated replication (with Fay's correction = 4) design option used to produce point estimates, standard errors, and 95% confidence intervals (5). Absolute disparities and the differences between significant relative disparities were assessed by using the z statistic and a two-tailed test; a p-value of <0.05 was used to assess statistical significance. A relative disparity was considered statistically significant if its numerator was a significant absolute disparity. Estimates were age-adjusted to the year 2000 age distribution of the U.S. population (9). Comparative terms (e.g., higher and similar) indicate the results of statistical testing at the 0.05 level.

Among the 2009 population, statistically significant disparities were identified in noncompletion of high school for all the characteristics studied (Table 1). The absolute difference between the age-standardized percentages of males and females who had not completed high school (1.85 percentage points; p<0.05) indicated a limited sex disparity. Except for non-Hispanic Asian/Pacific Islander males, the absolute differences between the age-standardized percentages of each nonwhite racial/ethnic group and non-Hispanic whites who had not completed high school were statistically significant. The racial/ethnic relative disparity from non-Hispanic whites was greatest for Hispanics and non-Hispanic American Indians/Alaska Natives, lowest for the non-Hispanics of mixed race and Asians/Pacific Islanders, and intermediate for non-Hispanic blacks. The degree of racial/ethnic relative disparity varied markedly among the nonwhite racial/ethnic groups, ranging from three to nine times greater for Hispanics than for other groups. Absolute differences between the age-standardized prevalence of noncompletion of high school in each PIR group and the referent group (<100% below FPL) were statistically significant overall and among both males and females. Income disparity in prevalence of noncompletion of high school increased with decreasing PIR, such that the disparity was >200% for the group living below FPL. Significant absolute differences in age-standardized prevalence of noncompletion of high school were identified between the youngest age group, age groups ≥65 years, and the referent group (age 45--65 years). Significant disability relative disparity in noncompletion of high school was also present overall and among both sexes, with a greater degree of disparity among females than males because of the lower value of the referent point for females. No statistically significant differences were observed between the relative disparities in noncompletion of high school for 2005 and 2009.

During 2009, the group disparities in poverty observed were similar to those for noncompletion of high school (Table 2). Marked absolute and relative racial/ethnic disparity in poverty was greatest for non-Hispanic blacks, American Indians/Alaska Natives, and Hispanics of both sexes. The age-standardized prevalence of poverty was 15--20 percentage points higher among persons who had not completed high school than it was among those with more education than high school; an approximate twofold relative disparity existed among both sexes. No statistically significant differences were identified between relative disparities in poverty observed for 2005 and 2009.

The findings presented in this report are subject to at least two limitations. First, all data were self-reported and therefore subject to recall and social desirability bias. Second, because cross-sectional data were used for the analyses, no causal inferences can be drawn from the findings.

Striking disparities in noncompletion of high school and poverty exist within the U.S. adult population; no improvement was realized between 2005 and 2009. The patterning of the disparities is consistent with sociodemographic differences reported by multiple national surveys (2,10--12). These findings indicate that a substantial proportion of the adult population is vulnerable to health problems because of insufficient resources. The data provided in this report can be used as a baseline for subsequent monitoring of progress toward the elimination of health disparities.

References

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