What does geo-demographic data show us about pediatric bicycle injuries? | 77 cases | Average age: 13 years | 8 years | Retrospective review of all bicycle injuries (ages ≤18 years) at a Level 1 trauma center | 83% male | 48% non-Hispanic white | Incidents were aggregated to zip codes | 98% were not wearing a helmet | Traumatic brain injury (TBI) occurred in 21% | ICU care required in 28% | operative intervention required in 36% | 6 zip codes encompassing several interstate exits & heavy-traffic roadways makes up a cluster of pediatric bicycle accidents | Conclusion: Risk of pediatric bicycle accidents is highest in areas of low income and heavy-traffic roadways high rates of TBI were associated with lack of helmet usage. | https://pubmed.ncbi.nlm.nih.gov/35109994/ | Source: Gilna CP et al. DeWitt Daughtry Family Department of Surgery, Division of Pediatric Surgery, University of Miami Miller School of Medicine, Miami, FL, United States | @EmTombash @emcincinnati @Cincinnati Children's | @StayCurrentMD | Journal of Pediatric Surgery
Analyzing pediatric bicycle injuries using geo-demographic data
Infographic · Jul 2022 · 1 min read
In brief
In brief
This geospatial study of 77 pediatric bicycle injuries found that 98% were not wearing helmets, with 21% sustaining traumatic brain injury. Injuries clustered in low-income neighborhoods near major roadways, suggesting targeted helmet distribution and safety education programs could reduce preventable trauma in high-risk areas.
- 98% of injured children were not wearing helmets, with 21% sustaining traumatic brain injury—highlighting critical prevention gap
- Pediatric bicycle injuries cluster in low-income zip codes near interstate exits and high-traffic roadways
- 36% required operative intervention and 28% needed ICU care, demonstrating severity of preventable injuries
- Spatial analysis identified 6 high-risk zip codes, enabling targeted helmet distribution and intersection safety interventions
- Male children (83%) aged 13±4 years represent highest-risk demographic for bicycle trauma requiring Level 1 care
Written by the GCMD Library team from the infographic.
A teal and yellow infographic divided into sections with icons including a calendar, helmet, bicycles with riders, and a map pin. The layout flows from top to bottom with demographic data, injury statistics highlighted in large yellow numbers, and a conclusion box in the bottom right. Illustrations show diverse children riding bicycles and a safety helmet.
Gareth P. Gilna, Justin Stoler, Rebecca A. Saberi, Adriana C. Baez, Walter A. Ramsey, Carlos T. Huerta, Christopher F. O'Neil, Rishi Rattan, Eduardo A. Perez, Juan E. Sola, Chad M. Thorson
Purpose: Bicycle accidents are potentially preventable, and helmets can mitigate the severity of injuries. The purpose of the study it to investigate geo-demographic areas to establish prevention policies and targeted programs.
Methods: From October 2013 to March 2020 all bicycle injuries at a Level 1 trauma center were collected for ages ≤18 years. Demographics, injuries, and outcomes were analyzed. Incidents were aggregated to zip codes and the Local Indicators of Spatial Association (LISA) statistic was used to test for spatial clustering of injury rates per 10,000 children.
Results: Over the 8-year time period, 77 cases were identified with an average age of 13±4 years, 83% male and 48% non-Hispanic white. The majority of patients (98%) were not wearing a helmet. Loss of consciousness was reported in 44% and 21% sustained a traumatic brain injury. Twenty-eight percent required ICU care and 36% required operative interventions. There was only 1 mortality in the cohort (<1%).Injuries were more common in lower household income zip codes (Figure 1). Six zip codes encompassing several interstate exits and the connected heavy-traffic roadways comprise a statistically significant cluster of pediatric bicycle accidents (Figure 1).
Conclusion: Low-income neighborhoods and those near major roadways held the highest risk for pediatric bicycle accidents. Use of helmets was extremely low in the patient population, with high rates of traumatic brain injury. With this information, targeted programs to address high-risk intersections, helmet access, and safety education can be implemented locally.