The Compounding Effect of Race/Ethnicity and Disability Status on Children's Health and Health Care by Geography in the United States.

OBJECTIVE: The objective of this study was to examine the potential compounding effect of race/ethnicity, and disability status on children's health and health care, stratified by selected geographies. METHODS: We used the 2011/2012 NSCH and the 2012 Boston Survey of Children's Health for our compounded disparity analysis. We used VanderWheel and Knol method to first predict combined risk ratios of race/ethnicity and disability and then compared them with the observed combined risk ratios. RESULTS: We demonstrated that racial/ethnic minority children with disabilities experience additional disparities in health care access outcomes that are greater than the sum of the effects from either characteristic alone. Further, we demonstrate that disparities persist across all selected geographies irrespective of whether children lived in states or metropolitan cities with the best health care systems in the United States. CONCLUSIONS: Despite reform efforts, our study demonstrates that racial/ethnic minority children with disabilities experience a double burden. Given the deleterious compounded disparities, public health and social service programs at all geographical levels should prioritize identifying participants that face this and tailor programs to meet their needs.

Measures of Local Segregation for Monitoring Health Inequities by Local Health Departments.

OBJECTIVES: To assess the use of local measures of segregation for monitoring health inequities by local health departments. METHODS: We analyzed preterm birth and premature mortality (death before the age of 65 years) rates for Boston, Massachusetts, for 2010 to 2012, using the Index of Concentration at the Extremes (ICE) and the poverty rate at both the census tract and neighborhood level. RESULTS: For premature mortality at the census tract level, the rate ratios comparing the worst-off and best-off terciles were 1.58 (95% confidence interval [CI] = 1.36, 1.83) for the ICE for income, 1.66 (95% CI = 1.43, 1.93) for the ICE for race/ethnicity, and 1.63 (95% CI = 1.40, 1.90) for the ICE combining income and race/ethnicity, as compared with 1.47 (95% CI = 1.27, 1.71) for the poverty measure. Results for the ICE and poverty measures were more similar for preterm births than for premature mortality. CONCLUSIONS: The ICE, a measure of social spatial polarization, may be useful for analyzing health inequities at the local level. Public Health Implications. Local health departments in US cities can meaningfully use the ICE to monitor health inequities associated with racialized economic segregation.

Racial/ethnic health disparities among children with special health care needs in Boston, Massachusetts.

BACKGROUND: Little is known about the factors that contribute to racial/ethnic disparities among children with special health care needs (CSHCN). OBJECTIVE: To quantify the contributions of determinants of racial/ethnic disparities in health and health care among CSHCN in Boston, Massachusetts. METHODS: A sample of 326 Black, Latino, and white CSHCN was drawn from the Boston Survey of Children's Health, a city-wide representative sample of children. The study implemented Oaxaca-Blinder-style decomposition techniques to examine the relative contributions of health resources and child-, family-, and neighborhood-level factors to disparities in four outcomes: health status, barriers to medical care, oral health status, and utilization of preventive dental care. RESULTS: White CSHCN had a greater likelihood of having very good/excellent health and oral health and were less likely to experience barriers to care than Black CSHCN. Compositional differences on predictors explained 63%, 98%, and 80% of these gradients, respectively. Group variation in household income, family structure, neighborhood support, and exposure to adverse childhood experiences accounted for significant portions of the Black-white gaps in health and access. White CSHCN were also more likely to have very good/excellent health and oral health compared to Latino CSHCN. Differences on predictors accounted for about 86% and 80% of these gaps, respectively. Household income, adverse childhood experiences, and household language emerged as significant determinants of Latino-white disparities. CONCLUSIONS: Racial/ethnic health disparities among CSHCN are explained by relatively few determinants. Several of the contributing factors that emerged from the analysis and could be targeted by public health and policy interventions.