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Geographic Inequalities in Pediatric Asthma and Workforce Distribution
Anand Gourishankar1, Eugene Suwandhi1
1Children's National Hospital/George Washington University, Washington, DC, USA.
Background:
Asthma is one of the most common chronic diseases affecting children in the United States, with millions impacted annually. There is ongoing concern and disparity in the pediatric workforce. However, there is limited research evaluating how the geographic distribution of these providers aligns with pediatric asthma burden across states.
Objective:
To assess the degree of geographic alignment between pediatric asthma prevalence and the distribution of general pediatricians and pediatric hospitalists in the United States using inequality metrics and spatial analysis.
Methods:
This was a cross-sectional, state-level ecological study using publicly available data. Pediatric asthma prevalence was obtained from the CDC Behavioral Risk Factor Surveillance System. Pediatric provider data were sourced from the American Board of Pediatrics, and child population estimates were retrieved from the U.S. Census Bureau. Workforce density was calculated as the number of general pediatricians and pediatric hospitalists per 100,000 children in each state. Lorenz curves and Gini coefficients were used to quantify geographic inequality in asthma burden and workforce distribution. Bivariate choropleth maps and Pearson correlation coefficients were employed to assess spatial mismatch and association between asthma prevalence and provider availability.
Results:
General pediatricians had a mean state-level density of 70.6 per 100,000 children, while pediatric hospitalists had a mean density of 5.3 per 100,000 children (p < 0.0001). Gini coefficients revealed moderate inequality in the distribution of general pediatricians (0.20) and higher inequality among pediatric hospitalists (0.33). In contrast, the Gini index for pediatric asthma prevalence was 0.11. Correlation analysis showed a weak, marginally significant association between asthma prevalence and general pediatrician density (r = 0.30, p = 0.032), and a non-significant association with pediatric hospitalist density (r = 0.24, p = 0.094). Bivariate mapping identified several states with high asthma burden and low provider density, revealing substantial spatial mismatches.
Conclusion:
There is a misalignment between the burden of pediatric asthma and the distribution of pediatric healthcare providers in the U.S., particularly in pediatric hospital medicine. States with higher asthma prevalence are not consistently supported by proportionally larger pediatric workforces. Policies that support provider redistribution, rural practice incentives, and data-driven workforce modeling are essential to improving health equity and optimizing care for children with asthma.
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