The journal of trauma and acute care surgery
March 31, 2026 · via Europe PMC
Beyond rural versus urban: A gradient of mortality risk among injured children across a four-level rurality scale.
Butler EK, Johnson R, Saltzman DA, Segura BJ.
AI summary — for doctors, generated from the abstract only
Injured children living outside large urban areas had higher inpatient mortality, with risk rising along a four-level rurality gradient independent of injury severity.
What was studied
A retrospective weighted analysis of about 402,255 US pediatric injury hospitalizations comparing outcomes across large urban, small urban, micropolitan and rural counties.
Key findings
- Severe injury (ISS over 25) rose from 7.0% in large urban to 10.9% in rural areas
- Adjusted mortality odds vs. large urban: rural OR 1.32, micropolitan 1.30, small urban 1.22
Clinical relevance
Highlights geographic disparities in pediatric trauma outcomes; causes such as transport time and readiness need further study.
Who should care
Limitations
Retrospective administrative data; methods are truncated in the abstract and causal factors were not examined.
Children injured outside large cities faced a graded higher risk of death in hospital.
This is an AI-generated summary of the published abstract, not a clinical recommendation. It may not reflect the full text or subsequent updates — verify against the original source before acting on it.
Abstract
Background
Children living in rural areas experience an increased incidence of injury and higher mortality relative to those in urban areas. Our aim was to better characterize rural-urban disparities in pediatric trauma outcomes among children admitted to US hospitals.
Methods
This is a retrospective, observational study of US hospitalizations of injured children and adolescents <20 years of age using the Kids' Inpatient Database (2016, 2019, and 2022). We categorized children's home counties as large urban, small urban, micropolitan, and rural. We compared demographics and injury characteristics of injured children among differing levels of rurality. We determined the unadjusted and adjusted risk of inpatient mortality using quasibinomial logistic regression, accounting for survey design, by level of rurality.
Results
A representative weighted 402,255 injured children were admitted in the survey years. The median age was 13 (IQR, 5-17) years and 39.1% were female. Motor vehicle crash (21.1%) and falls (21.1%) were the most common mechanisms of injury. As the level of rurality increased, the proportion of severely injured children (ISS >25) increased (7.0% large urban, 7.9% small urban, 9.6% micropolitan, and 10.9% rural areas). When adjusted for risk of mortality, compared to large urban counties, rural county was associated with 32% higher odds [odds ratio (OR), 1.32, 95% CI, 1.16-1.51], micropolitan 30% higher odds (OR, 1.30, 95% CI, 1.16-1.46), and small urban 22% higher odds (OR, 1.22, 95% CI, 1.12-1.32) of inpatient mortality.
Conclusions
Among injured children admitted to US hospitals, children residing outside of large urban areas have a higher risk of death independent of injury severity. To address disparities in pediatric rural injury outcomes, we must further investigate the root causes of this disparity, which may include nonoptimal location of pediatric trauma centers, long transport times, and low pediatric readiness in rural hospitals. ( J Trauma Acute Care Surg. 2026;101: 475-482. Copyright © 2026 Wolters Kluwer Health, LLC. All rights reserved.).
Level of evidence
Prognostic/Epidemiological; Level III.
DOI
10.1097/ta.0000000000004977
PMID
41925627
Research metadata (titles, abstracts, authors, publication dates) is sourced from Europe PMC, which aggregates content from PubMed/MEDLINE, PubMed Central, and other providers under the U.S. National Library of Medicine (NLM/NCBI). NLM does not claim copyright on abstracts; the original journal publishers or authors may hold rights to the full articles. AI-generated summaries are derived only from the abstract, never the full text, and are always labeled as AI-generated.
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