Evidence map›Paper›PMID 39856732›Full record

ArticleInjury epidemiology2025

Age-related mortality risk in cycling trauma: analysis of the National Trauma Databank 2017-2023.

Marta A W Rowh, Taylor A Giller, John N Bliton, Randi N Smith, Tim P Moran

Abstract read
In one paragraph

Article in Injury epidemiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

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2citing papers in PubMed
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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Marta A W RowhDepartment of Emergency Medicine, Emory University, 531 Asbury Circle, Annex Building Suite N340, Atlanta, GA, 30322, USA. marta.rowh@emory.edu.
Taylor A GillerDepartment of Emergency Medicine, Emory University, 531 Asbury Circle, Annex Building Suite N340, Atlanta, GA, 30322, USA.
John N BlitonJamaica Hospital Medical Center, 8900 Van Wyck Expy, Richmond Hill, NY, 11418, USA.
Randi N SmithDepartment of Surgery, Emory University, 69 Jesse Hill Jr. Dr. SE, Atlanta, GA, 30303, USA.
Tim P MoranDepartment of Emergency Medicine, Emory University, 531 Asbury Circle, Annex Building Suite N340, Atlanta, GA, 30322, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCycling promotes health but carries significant injury risks, especially for older adults. In the U.S., cycling fatalities have increased since 1990, with adults over 50 now at the highest risk. As the population ages, the burden of cycling-related trauma is expected to grow, yet age-specific factors associated with mortality risk remain unclear. This study identifies age-specific mortality risk thresholds to inform targeted public health strategies.

methodsWe conducted a cross-sectional analysis of the National Trauma Data Bank (NTDB) data (2017-2023) on non-motorized cycling injuries. A total of 185,960 records were analyzed using logistic regression with splines to evaluate the relationship between age and mortality risk. The dataset was split into training (80%) and testing (20%) sets. Age thresholds where mortality risk changed were identified, and models were adjusted for injury severity, comorbidities, and helmet use.

resultsThe median patient age was 43 years (IQR 20-58). Four key age thresholds (12, 17, 31, and 69) were identified, with the largest mortality increase after age 69. Our model achieved an AUC of 0.93, surpassing traditional age cutoff models, with 84.6% sensitivity and 88.0% specificity.

conclusionsAge is a significant predictor of mortality in cycling trauma, with marked increases in risk during adolescence and for adults over 69. These findings underscore the need for age-targeted interventions, such as improved cycling infrastructure for teens and enhanced safety measures for older adults. Public health initiatives should prioritize these vulnerable age groups to reduce cycling-related mortality.

Indexed as

CyclingGeriatricsMortalityTrauma

Identifiers

PMID39856732
PMCPMC11760107

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.