Table describes demographic, behavioral and clinical characteristics of the WHS study cohort by quartiles of state-level median household income. State-level distribution of participants in the Women's Health Study have been detailed previously [15
]. WHS participants who lived in states in the highest quartile of state median income (e.g., California, Connecticut, Massachusetts) tended to be younger, had higher personal incomes, less frequently smoked, more frequently exercised, were less likely to be obese, were less likely to have diabetes, and had a better HDL-C profile than WHS participants living in states in the lowest quartile of state median income (e.g., Mississippi, West Virginia, Arkansas). High-income states had a higher percentage of non-White WHS participants, chiefly Asian/Pacific Islander groups (e.g., California, 10% non-White WHS participants) than lower-income states (e.g., West Virginia, 2% non-White WHS participants). Caloric intake was slightly higher among WHS participants in the highest-income states than lower-income states. The mean systolic blood pressure category was not substantively different across quartiles of state-level median household income. The median value of each inflammatory biomarker decreased with increasing quartiles of state-level median household income (Table ).
Selected Demographic, Lifestyle, and Clinical Characteristics of Women's Health Study Participants: By Quartiles of State-Level Median Household Income
Table describes the range of socioeconomic conditions at the state level. Spearman rank correlation coefficients show that the measures of wealth and prosperity (real per-capita GDP, state median household income) and labor productivity (per employee earnings) were tightly correlated (Table ). Wealthy and prosperous states tended to have stable economies (low levels of average economic growth) between 1990 and 1996. Poorer states, measured by the prevalence of state-level poverty, tended to have higher levels of average annual economic growth during this period. State-level income inequality was directly correlated with state-level poverty, and inversely related to median household income (Table ).
U.S. State-Level Socioeconomic Conditions: Wealth and Prosperity, Growth, Income Inequality, Poverty and Labor Productivity Measures
Spearman Correlation Coefficients Among State-Level Wealth and Prosperity, Growth, Income Inequality, Poverty, and Labor Productivity
Figure shows the multilevel relationship between hsCRP, personal household income, and state-level economic conditions. Across almost all state-level indicators, women with low personal household incomes (≤ $19,999 annually) who lived in states with the most favorable economic conditions (wealthy and prosperous, high productivity, low poverty, low inequality) had lower levels of inflammation than similarly low-income women (≤ $19,999 annually) who lived in states with the least favorable economic conditions. For example, the median hsCRP for the lowest-income women who lived in states in the least wealthy GDP quartile was 3.6 mg/L (standard error 0.47), compared to 2.0 mg/L (standard error 0.54) for the lowest-income women who lived in states in the most wealthy GDP quartile (Figure ).
Figure 1 Median C-reactive protein (mg/L) levels among Women's Health Study participants by state-level characteristics and individual-level household income. Figures display unadjusted inflammatory biomarker median values and associated standard errors by personal (more ...)
Additionally, for most state-level indicators, the disparity in hsCRP levels between women with the highest ($100,000 and greater) and lowest (≤ $19,999) personal incomes was smallest under the most favorable economic conditions. In particular, state-level income inequality appeared to influence the range of inflammatory hsCRP values. The difference in hsCRP between the highest-income women (median hsCRP 1.5, standard error 0.19), and the lowest-income women (median hsCRP 2.0, standard error 0.41) was 0.5 points among women living in states with the lowest income inequality. The difference in hsCRP between women with the highest and lowest personal income was 1.5 points among women in states with the highest income inequality (Figure ).
The trend in biomarker values associated with average annual economic growth was the reverse of that seen with other indicators. Women in states with the highest average annual growth tended to have the highest levels of hsCRP, with high hsCRP levels among the lowest-income women.
Figures and display patterns for sICAM and fibrinogen. The protective pattern of favorable state-level economic conditions on sICAM and fibrinogen levels among low-income women was not as pronounced as that seen for hsCRP.
Figure 2 Median sICAM-1 (ng/ml) levels among Women's Health Study participants by state-level characteristics and individual-level household income. Figures display unadjusted inflammatory biomarker median values and associated standard errors by personal household (more ...)
Figure 3 Median fibrinogen (mg/dL) levels among Women's Health Study participants by state-level characteristics and individual-level household income. Figures display unadjusted inflammatory biomarker median values and associated standard errors by personal household (more ...)
Table quantifies the association between personal household income and biomarkers of inflammation, as well as the association between each state-level characteristic and biomarker of inflammation in excess of personal household income, all adjusted for women's demographic, behavioral and clinical characteristics. Personal household income was independently associated with sICAM-1 and fibinogen, where higher levels of personal income were associated with lower levels of sICAM-1 and fibrinogen, after adjustement for individual-level covariates (Table ). When adjusted for individual-level covariates, personal household income had a positive association with hsCRP, where higher personal incomes were associated with higher hsCRP. After propensity score adjustment for metabolic variables, this association crossed zero (Std B 0.01, 95% CI -0.005, 0.02).
Fixed Effect Estimates of Personal Household Income and State-Level SES Measures on Log(hsCRP), ICAM, and Fibrinogen
Income inequality was independently associated with all three biomarkers, where rising quartiles of inequality were associated with rising levels of hsCRP, sICAM-1 and fibrinogen (Table ).
Rising quartiles of state-level wealth and prosperity (real per-capita GDP and median household income) were independently associated with lower levels of hsCRP and sICAM-1, in excess of personal household income and individual-level covariates (Table ). Rising quartiles of state-level poverty were associated with an increase in hsCRP and sICAM-1, independent of personal household income. Labor productivity was associated with hsCRP, but not sICAM-1 or fibrinogen. Quartiles of average annual economic growth were independently associated with fibrinogen, but not other biomarkers. The relation between economic growth and fibrinogen levels appeared non-linear; a quadratic term did not appear to fit the data (Std B -0.01, 95% CI -0.03, 0.01).