ArticleAIMS public health2026
Rural-urban classification is associated with patient- and population-level disparities in leukemia relative to other pediatric cancers.
Article in AIMS public health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Background: Despite leukemia being the most commonly diagnosed form of pediatric cancer, prior surveillance research has not linked the odds of a given pediatric cancer being leukemia to rural-urban county designations. Purpose: We sought to elucidate the patient-level role of rural-urban county designations in predicting the odds of a given pediatric cancer diagnosis being leukemia while observing the role of these county designations in conveying leukemia/non-leukemia disparities in the U.S. pediatric cancer population. Methods: The sample included pediatric cancer diagnoses from the Surveillance, Epidemiology, and End Results (SEER) 21 dataset from 2010 through 2017. The study outcome was binary; cases were leukemia and controls were non-leukemia. The focal predictor was the rural-urban county designation. The analysis used patient- and community-level covariates in a logistic regression model to identify the role of rural-urban designations in predicting a leukemia diagnosis. The model also generated case scores, which were the population probabilities of diagnoses being leukemia, and used these to conduct mediation analyses to determine the population-average associations of the rural-urban designations with leukemia. Results: In the adjusted model, rural counties adjacent to metropolitan areas (henceforth, "metros") had a significant association with leukemia cases, with 29.4% greater odds compared to the largest metro counties. In the population-level mediation via case scores, not only rural counties adjacent to metros, but also medium and small metros, had greater population-average odds of leukemia compared to the largest metros. Conclusions: While only rural counties adjacent to metros were consequential for modeling leukemia diagnoses among patients, population-average disparities in leukemia odds were also apparent in small and medium metros compared to the largest metros. This may indicate that leukemia risk exposures, existing systematically in rural counties adjacent to metros, may also be present, to lesser extents, in the small and medium metros.
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