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Table 4 Unadjusted and adjusted associations among race, income, education, and healthcare fragmentation

From: Differences in ambulatory care fragmentation by race

  Coefficients (95% Confidence Intervals)
Unadjusted Model 1 Model 2 Model 3 Model 4
Race (black vs. white) −0.039*** (−0.047,-0.031) −0.033*** (−0.043,-0.024) − 0.037*** (− 0.047,-0.027) −0.024*** (− 0.034,-0.013) −0.027*** (− 0.040,-0.015)
Annual household income (<$35,000 vs. ≥$35,000) − 0.029*** (− 0.037,− 0.021) -0.021*** (− 0.030,-0.012) −0.017*** (− 0.027,-0.007) −0.013* (− 0.024,-0.003) −0.010 (− 0.021,0.002)
Educational attainment (high school or less vs. some college or more) − 0.030*** (− 0.034,-0.019) −0.013*** (− 0.022,-0.004) −0.012** (− 0.022,-0.003) −0.009 (− 0.019,0.001) −0.002 (− 0.013,0.009)
  1. These models used linear regression to determine associations among race, income, and educational attainment (as independent variables) and healthcare fragmentation (as a dependent variable, using the continuous reversed Bice-Boxerman Index). Negative coefficients indicate lower fragmentation scores than the reference group
  2. Unadjusted models were bivariate models, with race, income, and education in separate models
  3. Model 1 includes race, income, and education in the same model
  4. Model 2 includes Model 1 covariates plus age, sex, marital status, geographic region, and type of geography
  5. Model 3 includes Model 2 covariates plus medical conditions and medications (as shown in Table 1)
  6. Model 4 includes Model 3 covariates plus health behaviors, psychosocial variables, physiological variables, and self-rated health (as shown in Table 1)
  7. *p < 0.05. **p ≤ 0.01. ***p ≤ 0.001
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