Consistent with a growing body of research, this study documented education and income differences in inflammation burden in young to middle-aged adults, although associations between SES and inflammation variables varied somewhat across race and gender subgroups. CRP and IL-6 levels were inversely associated wi Pth education and income levels in both White males and females. Inflammation biomarker levels were also inversely associated with SES variables in Black females, except for CRP by income level. Overall, SES showed little association to inflammation biomarker levels in Black males, with the exception of a significant inverse association between IL-6 and income. Pollitt and colleagues (2007)
also found that SES-inflammation associations were less consistent in middle-aged Blacks as compared to Whites, but they did not report whether associations further varied by gender. In regards to gender differences, previous studies have noted no differences in SES-inflammation associations across men and women (e.g., Kivimaki et al., 2005
), or stronger associations in women (e.g., Rathmann et al., 2006
). Our findings clearly suggest that ties between social status and inflammation vary across race/gender subgroups and indicate that more attention may need to be directed to the intersection of race and gender in regards to understanding SES differences in inflammation burden.
Examination of the health status, behavioral and psychosocial factors that may account for SES-inflammation associations suggest a similar role for some variables (e.g., BMI, smoking) across most groups, but group-specific roles for other factors (e.g., sleep quality, depressed mood). BMI was a strong and consistent predictor of CRP and IL-6 in each group, and its inclusion in analytic models tended to reduce the magnitude of the association between SES and inflammation variables, especially in White females, and to a lesser extent in Black females and White males. Although BMI was as sociated with higher inflammation burden in Black males, higher income was associated with higher BMI in Black males, and the inclusion of BMI into regression models tended to streng inflammatory biomarkers. Anthropometric then the association between income and variables have been found to account for a significant proportion of SES-inflam mation associations in other investigations (Kivimaki et al., 2005
; Koster et al., 2006
; Rathmann et al., 2006
), suggesting that social status variations in body size may partially account for SES disparities in inflammation burden. However, the temporal nature of associations between SES, body size and inflammatory biomarker levels remains to be fully elucidated. Previous research has documented greater weight gain in lower SES CARDIA participants over the first five years of follow-up (Burke, Bild, Hildner, Folsom, Wagenknecht, & Sidney, 1996), and SES has been found to be inversely associated with obesity in a large number of studies, with this relationship being stronger and more consistent in women (see Sobal & Stunkard, 1989
, for a review). Adipose tissue can synthesize inflammatory biomarkers, such as IL-6 (which may, in turn, promote synthesis of CRP; Coppack, 2001
), suggesting that SES may impact biomarker levels through fat accumulation. However, it is also possible that obesity may impact socioeconomic success (Sobal & Stunkdard, 1989).
Smoking was another covariate factor that emerged as a significant predictor of higher CRP and IL-6 levels in most analyses across the four race/gender groups, a factor that has been found to partially account for associations between SES and inflammation biomarker levels in other investigations (Koster et al., 2006
; Pollitt et al., 2007
). Other significant covariate predictors tended to vary across models for race/gender groups. For example, poor sleep quality predicted higher inflammation burden in Black females and White males, frequent alcohol use predicted lower IL-6 in White females, a greater number of chronic health conditions predicted higher IL-6 levels in White females, higher physical activity intensity was associated with lower inflammation burden in Black females and males, and higher depressed mood was associated with higher IL-6 in Black females. The inclusion of these covariates into analytic models was associated with slight to moderate reductions in the magnitude of differences in CRP and IL-6 levels between education and income categories, suggesting that these factors may partially account for SES variations in inflammation burden in the race and gender groups studied. The lack of complete attenuation of SES-inflammation associations with the inclusion of model covariates in some models s uggests that other important factors not measured in this investigation may underlie SES-inflammation associations and/or that our measures failed to completely capture the behavioral and psychosocial constructs of interest, limiting power to find a meditational effect.
There are a number of limitations of the present analysis. One is the low representation of individuals of very low SES (e.g., those with only an elementary education, living in poverty) in the CARDIA cohort, which precludes our ability to capture inflammatory biomarker levels in those at the lowest end of the SES spectrum. Nonetheless, the finding of SES gradients even across higher levels of education and income may point to the general robustness of SES disparities in biological risk factors. The distribution of race and gender subgroup participants was also uneven across education and income categories with the distribution of Black females and males skewed toward the lower end of the SES distribution and the distribution of White females and males toward the higher end of the SES spectrum. While such distributions likely reflect the socioeconomic realities of each of these groups, they may also suggest qualitatively different socioeconomic experiences across groups even within a particular SES category. Nonetheless, patterns of inflammation burden across levels of education and income were fairly similar across the groups, with the exception of inflammation patterns for education in Black males. The distribution was especially skewed to wards lower levels of educational attainment in Black males, which may have limited power to find significant education differences. The cross-sectional nature of the present analyses also precludes the ability to more carefully discern the temporal nature of associations between SES Pvariables, health, behavioral and psychosocial covariates, and inflammatory biomarker levels. However, the change in the association between SES variables and inflammation biomarkers when in cluding covariates into analytic models does suggest potential pathways through which social status may impact biological well-being. The longitudinal dynamics of associations between SES, psychosocial, behavioral, health and inflammatory factors is an important target for future research. Greater attention should also be given to understanding periods of the life course in which SES might have the greatest impact on inflammation burden, the pathways which might link SES to inflammatory processes at different ages, and the potential cumulative impact of lifetime socioeconomic disadvantage (e.g., Tabassum, Kumari, Rumley, Lowe, Power, & Strachan, 2008
A strength of this study is the examination of SES-inflammation associations, and potential mediating factors, in race and gender subgroups. A number of race/gender subgroup differences emerged in our analyses, which would have been obscured with the simple inclusion of race and gender covariates in models. For example, the finding that income, but not education, was significantly associated with IL-6 levels in Black males, and that regression estimates for SES predictors were differentially affected by inclusion of BMI as a covariate in Black males as compared to the other race/gender groups, are findings that would not have clearly emerged from analysis of the entire sample. Stratified race/gender analyses also allowed for the discernment of health status, behavioral and psychosocial factors that differentially accounted for SES-inflammation associations across the four groups. Another contribution of the present investigation is the inclusion of a large array of potential mediating factors, including psychosocial variables, in analyses of SES-biomarker associations. Although psychosocial variables were less consistent predictors of inflammation biomarkers in full multivariate models, their inclusion in analyses along with standard health status and behavioral variables allowed for examination of a comprehensive set of factors that may help explain observed SES gradients to in inflammation burden.
In conclusion, the present analyses indicate SES gradients in inflammatory biomarker levels in young to middle-aged Black and Wh ite males and females in the CARDIA Study. Observed SES differences may persist and even widen over time as these individuals age into older adulthood, leading to greater levels of cardiovascular and other disease risk in those of lower SES to the degree that higher levels of CRP and IL-6 act to promote the development and progression of disease. Results of multivariable analyses point to the potentially important role of body mass/weight and smoking in accounting for observed SES differences in inflammation burden in most of the race/gender groups studied in the present analysis, while other behavioral and psychosocial factors varied in prominence in terms of accounting for SES variations in different race/gender groups. Taken together, these findings suggest potential foci (e.g., weight, smoking) of intervention efforts to reduce social disparities in physiological health, which may need to be tailored for different race and gender groups. Whether variations in inflammation burden, in turn, account for social disparities in actual disease outcomes is an important area of future research.