A year's trauma admissions and the effect of the weather

Injury. 2005 Jan;36(1):40-6. doi: 10.1016/j.injury.2003.10.027.

Abstract

Purpose of the study: To study the admissions to a busy trauma unit on a day-by-day basis over a 1 year period, and to look for any correlation with local weather variation or temporal factors (day of the week, weekends/school holidays, etc.).

Method: Admissions data for the Trauma Unit at the Leicester Royal Infirmary was collected from an administrative database and ward records for the calendar year of 1998. Admissions were split into four groups: all admissions, adult admissions, admissions for proximal femoral fractures (neck of femur (NOF)) and paediatric admissions. Weather information for the local area was obtained from the Meteorological Office. Details of school holidays were obtained from the local Education Department. The above variables were examined using Poisson regression analysis for their potential importance in explaining day-to-day variation in admission rates for the four groups.

Results: For adult and NOF admissions, none of the weather factors appeared to explain variation in incidence, only day of the week appears to be important, with the earlier part of the week yielding a highly statistically significant increase in the relative incidence of trauma admissions. For both paediatric and total admissions, a number of factors appear important, including maximum and minimum temperatures, hours of sunshine, day of the week and month of the year. Daily rainfall, significant weather and whether the day was a school day or school holiday did not appear to be important on univariate analysis.

Conclusion: Trauma admissions are related to both weather and temporal factors. This may have implications both in terms of prevention and in planning of care provision in trauma units.

MeSH terms

  • Adult
  • Child
  • England / epidemiology
  • Femoral Fractures / epidemiology
  • Hospitalization*
  • Humans
  • Incidence
  • Likelihood Functions
  • Regression Analysis
  • Seasons
  • Temperature
  • Time Factors
  • Trauma Centers / statistics & numerical data*
  • Weather*
  • Wounds and Injuries / epidemiology*