Epidemiology of foot injury in a high-income developing country

Injury. 2010 Feb;41(2):137-40. doi: 10.1016/j.injury.2009.05.031. Epub 2009 Jun 30.

Abstract

Objectives: To study the epidemiology of foot injuries and factors predicting their severity in a high-income developing country so as to define prevention priorities.

Patients and methods: All patients admitted to Al-Ain Hospital with foot injury between March 2003 and March 2006 were identified from a prospectively collected Trauma Registry. Injuries were scored using foot and ankle severity scale (FASS). Bilateral, multiple or segmental injuries, open fractures or those with FASS score higher than 3 were included in severe foot injury group and compared with simple foot injury group regarding patients' demography, co-morbidities, trauma mechanism and energy, incident location, number of associated injuries, Injury Severity Score (ISS) and hospital stay using a univariate analysis. A logistic regression model was then used to study factors predicting severity of foot injury.

Results: 171 patients (156 males) were studied. The average (range) age was 34 (2-75). 95 had right foot injury, 66 had left, and 10 had both. Fall from height was the most common mechanism. 105 (61%) had work-related injuries. 130 (76%) had isolated foot injury. 151 (88%) had 212 foot fractures. 20 (12%) had soft tissue injuries. 70 (41%) had severe injuries while 101 (59%) had simple ones. The multiple logistic model was highly significant (p=0.002). Number of associated injuries (p=0.025) and location of trauma (p=0.044) were significant while the amount of energy (p=0.054) showed a strong trend to predict severity.

Conclusions: Fall from height is the most common mechanism of foot injury in United Arab Emirates. The number of associated injuries, high-energy trauma, and being work related are predictors of foot injury severity. Prevention priorities include counteractions against falling from height and falling heavy objects as occupational hazards.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Accidental Falls / statistics & numerical data*
  • Accidents, Occupational / statistics & numerical data*
  • Accidents, Traffic / statistics & numerical data
  • Adolescent
  • Adult
  • Aged
  • Ankle Injuries / epidemiology
  • Child
  • Child, Preschool
  • Developing Countries / economics
  • Developing Countries / statistics & numerical data*
  • Female
  • Foot Injuries / epidemiology*
  • Foot Injuries / etiology
  • Fractures, Bone / epidemiology
  • Humans
  • Income
  • Industry
  • Injury Severity Score
  • Logistic Models
  • Male
  • Middle Aged
  • Motorcycles / statistics & numerical data
  • Registries / statistics & numerical data
  • United Arab Emirates / epidemiology
  • Young Adult