Epidemiology and outcomes of brain trauma in rural and urban populations: a systematic review and meta-analysis

• Published in: Brain injury Vol. 38; no. 12; pp. 953 - 976
• Main Authors: Chequer de Souza, Julia, Dobson, Geoffrey P, Lee, Celine J, Letson, Hayley L
• Format: Journal Article
• Language: English
• Published: England 14-10-2024
• Subjects: Brain Injuries - epidemiology; Brain Injuries, Traumatic - epidemiology; Humans; Rural Population - statistics & numerical data; Urban Population - statistics & numerical data; injury; urban; brain; Trauma; rural
• ISSN: 0269-9052; 1362-301X; 1362-301X
• DOI: 10.1080/02699052.2024.2361641

To identify and describe differences in demographics, injury characteristics, and outcomes between rural and urban patients suffering brain injury.
CINAHL, Emcare, MEDLINE, and Scopus.
A systematic review and meta-analysis of studies comparing epidemiology and outcomes of rural and urban brain trauma was conducted in accordance with PRISMA and MOOSE guidelines.
36 studies with ~ 2.5-million patients were included. Incidence of brain injury was higher in males, regardless of location. Rates of transport-related brain injuries, particularly involving motorized vehicles other than cars, were significantly higher in rural populations (OR:3.63, 95% CI[1.58,8.35],
 = 0.002), whereas urban residents had more fall-induced brain trauma (OR:0.73, 95% CI[0.66,0.81],
 < 0.00001). Rural patients were 28% more likely to suffer severe injury, indicated by Glasgow Coma Scale (GCS)≤8 (OR:1.28, 95% CI[1.04,1.58],
 = 0.02). There was no difference in mortality (OR:1.09, 95% CI[0.73,1.61],
 = 0.067), however, urban patients were twice as likely to be discharged with a good outcome (OR:0.52, 95% CI[0.41,0.67],
 < 0.00001).
Rurality is associated with greater severity and poorer outcomes of traumatic brain injury. Transport accidents disproportionally affect those traveling on rural roads. Future research recommendations include addition of prehospital data, adequate follow-up, standardized measures, and sub-group analyses of high-risk groups, e.g. Indigenous populations.