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    • Table compares age specific mortality

    2018-11-05

    Table 2 compares age-specific mortality rates between whites and African-Americans, aggregated over the four time periods. Consistent with the literature, African-American mortality rates exceed those of whites in all age groups except for 75 years or higher. The gap between whites and African-Americans is the largest among infants, followed by 65–74 years. The oldest group (75+) shows the well-documented mortality “crossover” where white mortality exceeds that of African-Americans (Martin & Soldo, 1987). Table 3 provides results of the two GEE analyses – one for each race/ethnicity. We analyzed 5768 age-specific mortality rates for whites, and 5628 rates for African-Americans across 226 counties in the U.S. (189 counties for 1972, 197 for 1977, 215 for 1982, and 223 for 1987). We excluded counties if population size did not reach 200,000 for a specific year. Thus, the number of observations varies with the time period. The coefficients of fragmentation are positive and statistically significant for both whites (coef: 2.60, Standard Error [SE]: 0.60, p<0.001) and African-Americans (coef: 5.31, SE: 1.56, p<0.001). The positive coefficient for African-Americans is more than twice the magnitude of that for whites. To give the reader a sense of the magnitude of the results, we calculated the health disparities in mortality rate statistically attributable to political fragmentation. We applied the estimated coefficients to Cook County (IL), which shows relatively high fragmentation among the 20 largest counties. Applying the coefficients in Table 3 to the population size of Cook County shows a rise of 3.55 deaths per 100,000 for whites and 7.25 deaths per 100,000 for African-Americans with one standard deviation (SD) increase in political fragmentation. This result implies an excess of 3.70 African-American deaths per 100,000 persons statistically attributable to a one SD increase in political fragmentation. The magnitude of this excess BIS-TRIS is similar to the current death rate due to cervical cancer in the U.S. (Murphy, Xu, & Kochanek, 2013). Median household income has a negative but weak association with mortality only for African-Americans (coef: −0.094, p=0.0001). Consistent with previous research (Elo & Preston, 1996; Lleras-Muney, 2005; Pappas et al., 1993), the proportion of some college graduates varies inversely with mortality for both races (coef: −0.08, p<0.0001 for whites, coef: −0.19, p<0.0001 for African-Americans). The proportion of African-American population varies positively with mortality rates among both whites (coef: 4.68, p<0.0001) and African-Americans (coef: 2.88, p=0.04). The coefficient is higher for whites in higher percentage African-American areas. Given the debate about whether to include proportion African-American in ecological studies of mortality disparities, we assessed potential multicollinearity between this variable and political fragmentation (Ash & Robinson, 2009; Deaton & Lubotsky, 2003, 2009). We also re-ran the GEE model after removing proportion African-American to assess whether the political fragmentation coefficient changed. We find no evidence of multicollinearity; inference in the revised GEE model also remained similar to the original test (results available upon request). We conducted four additional analyses to assess the robustness of our results. First, we re-estimated the GEE model with one equation that included both races and a race indicator variable (African-American=1; white=0) and its interaction term with political fragmentation, controlling for other covariates. Consistent with the initial test, we find that the African-American-fragmentation interaction term is positive and significant (coef: 3.28, p=0.02 for interaction). Second, we added the numeric year variable, year squared variable, and the interaction term of year and state indicator to determine whether state-specific time trends in mortality drove results. The control of time trends also addresses the possibility that mortality rates show an autocorrelated pattern not captured by use of binary indicator variables for year. The test shows similar results to the original model, indicating an increase in health disparities (coef: 1.53, SE: 0.47, p=0.001 for whites; coef: 4.89, SE: 1.47, p=0.007 for African-Americans). Third, consistent with Hutson and colleagues (Hutson et al., 2012), we re-ran the GEE analysis at the level of MSA to examine whether choice of geographic unit affected results. Whereas the magnitude of the findings differed from the original test, we found a larger association between political fragmentation and mortality among African-Americans relative to that of whites (coef: 4.54, SE: 1.95, p=0.02 for African-Americans; coef: 3.01, SE: 0.62, p<0.001 for whites). Fourth, we partitioned the variance of political fragmentation to determine whether there exists substantial within-county variation over time to examine our hypothesis in a fixed effects framework. A fixed effect framework exploits only changes across time, within county, by holding county “fixed” in the regression equation. We discovered relatively little within-county variation over time (results available upon request), which precluded a fixed-effects estimation.