Our study demonstrates that preference-based HRQoL measures are significantly stratified by SES among U.S. adults. Income, education, and assets are each associated with multiple preference-based HRQoL measures and SRH, with income being the strongest, most consistent predictor. We also show that although there is some age variation in the size of the relationship between SES and HRQoL, SES disparities in HRQoL exist at all adult age groups—even at older ages. In particular, we find that those at the bottom of the socioeconomic distribution (with the lowest income, education, and assets) have much worse HRQoL and SRH than those with higher levels of SES. Indeed, those in the lowest income and education groups currently have worse HRQoL at ages 35–44 years than do those in the current 65+ age cohort in any of the higher income and education groups. Our results of persisting SES disparities at older ages are consistent with a recent Canadian prospective study that similarly found strong income differences in older adults’ ability to maintain exceptional health over a 10-year follow-up period (using the HUI3 HRQoL measure) (Kaplan et al., 2008
One of the goals of our research was to introduce several preference-based HRQoL measures to the literature on socioeconomic and age stratification and health. Our results are relatively consistent with previous work focusing on age differences in SES disparities in unidimensional measures of health. For example, our results show that income differentials in HRQoL and SRH exist at all ages, but the widest differentials are noted at about ages 45–54 years and the smallest at later old age. These results are generally consistent with research by House and colleagues (1994
, who found similar age patterns in the relationship between income and functional health and chronic conditions in a national study in the 1980s. Our multivariate results demonstrated that among all SES variables, income is the strongest predictor of HRQoL and SRH, with income strongly associated with HRQoL and SRH at all ages except at 75–89 years, net of other SES variables.
Our results indicated that education disparities in HRQoL and SRH are fairly constant across all current age cohorts, consistent with research demonstrating that education matters to health throughout the life course (Lynch, 2006
), including at older ages (Martin et al., 2007
; Schoeni, Martin, Andreski, & Freedman, 2005
). However, education was a weaker predictor than income and indeed appeared to be particularly weak at later old age (75–89 years). This is consistent with research suggesting that education may be more important earlier in life (affecting the onset of disease), whereas income may be more important in later life (affecting the progression of disease) (Herd et al., 2007
; House et al., 2005
; Melzer et al., 2001
; Ross &Wu, 1996
). Our results suggest that asset differentials in HRQoL exist net of other measures of SES for some HRQoL measures, particularly in middle age, consistent with previous research focusing on specific measures of morbidity (Robert & House, 1996
). However, our measure of assets was crude and likely underestimated asset effects—further research should employ more detailed measures of wealth.
Our analyses were cross-sectional, and therefore we did not aim to rigorously test cumulative advantage/disadvantage versus age-as-leveler hypotheses. However, our results are not consistent with a cumulative advantage/disadvantage hypothesis. Because the relationship between SES and health is generally much smaller at older ages in these data, our results are more consistent with an age-as-leveler hypothesis. In fact, our bivariate figures showed that those with the lowest income and asset levels actually had higher mean HRQoL in the later old age cohort than did those in the middle age cohorts. These results may be due to methodological issues (sampling and response bias), or they may be real and due to either age or cohort effects and/or availability of Medicare-supported health care to those older than 65 years.
As this research is based on a community sample, we do not have data on people who are most likely to be the sickest—those in nursing homes or other institutions. Therefore, it may be that our sample reflects the hardy survivors who lived to older ages who are physically and mentally healthy enough to participate in a phone survey. Indeed, Kaplan and colleagues (2008)
found that baseline income was strongly linked to maintaining exceptionally good health more than 10 years among Canadian elders, particularly when these “thrivers” were compared with older adults who were in institutions after 10 years. Future U.S. research needs to examine the health of all older adults, no matter where they reside, in order to fully understand age variations in health, and particularly if we want to well test cumulative advantage/disadvantage versus age-as-leveler hypotheses.
When comparing the results for the three preference-based HRQoL measures with the single SRH measure, we found that SRH appeared most strongly associated with or sensitive to SES. Whereas the preference-based HRQoL measures embody self-reported health status valued using community preferences, SRH embodies self-reported health implicitly valued by an individual's own rating. Perhaps lower SES individuals experiencing poor health are more likely to evaluate this health state much lower than the valuation of the general public. Our results suggest that this simple SRH measure remains useful in research aimed at understanding SES and health, particularly because it is much easier to measure than the preference-based HRQoL measures. However, because the preference-based HRQoL measures may increasingly be used in clinical, cost-effectiveness, and population-based studies, gerontologists should contribute to the discourse both over the use of these measures more generally (whether or when they are appropriate/inappropriate) and about the importance of examining their stratification by SES and age when they are used.
For researchers interested primarily in HRQoL, our results demonstrate whether and how social stratification by SES and age needs to be considered in future research and provides estimates across three common HRQoL measures that can be used for comparative purposes. Comparing the three preference-based HRQoL measures, we note larger SES disparities for the HUI3 than for the SF-6D and the EQ-5D in both bivariate and multivariate analyses. The HUI3 indicates much lower levels of HRQoL among those in the lowest income group in particular. It might be that the HUI3 is more able to discriminate among severe poor health states, as it includes eight attributes with five or six levels each. Alternately, it may be that these results reflect the fact that the preference values assigned to the same poor health states are given lower value weights in the HUI3. Future research should examine whether the HUI3 indeed captures more nuanced aspects of poor health that are more likely to be seen among low SES groups or whether differences in the assigned preference values are solely responsible for the different results. In any case, researchers with data without multiple measures of HRQoL should be aware that the values for lower SES groups may differ by HRQoL measure.
Another limitation to this study is that we excluded 4.7% of respondents reporting their race as neither White nor Black, meaning that our results are generalizable only to U.S. community-residing adults who report their race as either White or Black. Future research will need to examine the relationship between race and HRQoL more closely, including how it may vary by hard-to-reach racial subgroups of the population. Strengths of this study include that we use a recent national study on health among U.S. adults, using multiple preference-based measures of HRQoL and an SRH measure, and examine three SES measures (education, income, and assets). Our results provide an excellent basis of comparison for future studies that have more limited data on either SES or HRQoL measures.
In conclusion, given that people in the highest SES groups already have very high HRQoL and SRH in all age groups, we cannot expect overall mean population health to significantly improve in the United States unless it improves for people who currently have the lowest SES levels and the lowest HRQoL and SRH. Moreover, although the overall economic status of older adults has improved in recent decades, it has not improved for all older adults. Our results show that these SES disparities are associated with HRQoL and SRH disparities among all adult age groups. Policy and program efforts to improve population health might most effectively focus on those at the bottom of the SES distribution. Although this might involve efforts to buffer the health effects of having low SES, a fundamental cause theory would suggest that a more efficient policy effort might be to address educational attainment and income and asset security directly rather than to temporarily buffer their effects.