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Original Investigation |

Explaining Racial Disparities in Child Asthma Readmission Using a Causal Inference Approach

Andrew F. Beck, MD, MPH1,2; Bin Huang, PhD3; Katherine A. Auger, MD, MS2; Patrick H. Ryan, PhD3; Chen Chen, PhD3; Robert S. Kahn, MD, MPH1
[+] Author Affiliations
1Division of General and Community Pediatrics, Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
2Division of Hospital Medicine, Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
3Division of Biostatistics and Epidemiology, Department of Pediatrics, Cincinnati Children’s Hospital Medical Center, Cincinnati, Ohio
JAMA Pediatr. 2016;170(7):695-703. doi:10.1001/jamapediatrics.2016.0269.
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Importance  Childhood asthma is characterized by disparities in the experience of morbidity, including the risk for readmission to the hospital after an initial hospitalization. African American children have been shown to have more than 2 times the hazard of readmission when compared with their white counterparts.

Objective  To explain why African American children are at greater risk for asthma-related readmissions than white children.

Design, Setting, and Participants  This study was completed as part of the Greater Cincinnati Asthma Risks Study, a population-based, prospective, observational cohort. From August 2010 to October 2011, it enrolled 695 children, aged 1 to 16 years, admitted for asthma or wheezing who identified as African American (n = 441) or white (n = 254) in an inpatient setting of an urban, tertiary care children’s hospital.

Main Outcomes and Measures  The main outcome was time to asthma-related readmission and race was the predictor. Biologic, environmental, disease management, access, and socioeconomic hardship variables were measured; their roles in understanding racial readmission disparities were conceptualized using a directed acyclic graphic. Inverse probability of treatment weighting balanced African American and white children with respect to key measured variables. Racial differences in readmission hazard were assessed using weighted Cox proportional hazards regression and Kaplan-Meier curves.

Results  The sample was 65% male (n = 450), and the median age was 5.4 years. African American children were 2.26 times more likely to be readmitted than white children (95% CI, 1.56-3.26). African American children significantly differed with respect to nearly every measured biologic, environmental, disease management, access, and socioeconomic hardship variable. Socioeconomic hardship variables explained 53% of the observed disparity (hazard ratio, 1.47; 95% CI, 1.05-2.05). The addition of biologic, environmental, disease management, and access variables resulted in 80% of the readmission disparity being explained. The difference between African American and white children with respect to readmission hazard no longer reached the level of significance (hazard ratio, 1.18; 95% CI, 0.87-1.60; Cox P = .30 and log-rank P = .39).

Conclusions and Relevance  A total of 80% of the observed readmission disparity between African American and white children could be explained after statistically balancing available biologic, environmental, disease management, access to care, and socioeconomic and hardship variables across racial groups. Such a comprehensive, well-framed approach to exposures that are associated with morbidity is critical as we attempt to better understand and lessen persistent child asthma disparities.

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Figure 1.
Illustration of the Directed Acyclic Graph Developed to Guide Analyses

The light blue ovals indicate variables thought to be directly associated with readmission; white oval, patient, parent, and family factors thought to be directly associated with race and certain variables; white rectangles, unavailable or unmeasured variables thought to be associated with race or readmission; and dark blue ovals, reported race is the primary predictor or exposure variable and time to first asthma-related readmission is the outcome of interest.

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Figure 2.
Illustration of the Balance Between African American and White Children Before and After Application of Inverse Probability of Treatment Weighting
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Figure 3.
Adjusted Kaplan-Meier Curves After Balancing Procedures Are Completed With Inverse Probability of Treatment Weighting

The curves use adjusted Kaplan-Meier estimator and log-rank test with inverse probability of treatment weighting.29 Using the trimmed inverse probability of treatment weighting, the log-rank test provides P = .04 in panel A and P = .16 in panel B. A, Comparison of an unadjusted model with a model adjusted for pertinent socioeconomic hardship variables. Adjusted model in panel A includes measures of financial and social hardship, caregiver educational attainment, and caregiver marital status. B, Comparison of an unadjusted model with a model adjusted for pertinent socioeconomic hardship, biological, environmental exposure, disease management, and access to care variables. Adjusted model in panel B includes measures of outdoor allergen sensitization, salivary cotinine, traffic-related air pollution, running out of or missing dose of medication, and vehicle ownership alongside measures of financial and social hardship, caregiver educational attainment, and caregiver marital status.

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