PMID- 25972600
OWN - NLM
STAT- MEDLINE
DCOM- 20160906
LR  - 20181113
IS  - 1475-5785 (Electronic)
IS  - 1353-8047 (Print)
IS  - 1353-8047 (Linking)
VI  - 21
IP  - 6
DP  - 2015 Dec
TI  - Does transport time help explain the high trauma mortality rates in rural areas? 
      New and traditional predictors assessed by new and traditional statistical 
      methods.
PG  - 367-73
LID - 10.1136/injuryprev-2014-041473 [doi]
AB  - BACKGROUND: Trauma is a leading global cause of death. Trauma mortality rates are 
      higher in rural areas, constituting a challenge for quality and equality in 
      trauma care. The aim of the study was to explore population density and transport 
      time to hospital care as possible predictors of geographical differences in 
      mortality rates, and to what extent choice of statistical method might affect the 
      analytical results and accompanying clinical conclusions. METHODS: Using data 
      from the Norwegian Cause of Death registry, deaths from external causes 1998-2007 
      were analysed. Norway consists of 434 municipalities, and municipality population 
      density and travel time to hospital care were entered as predictors of 
      municipality mortality rates in univariate and multiple regression models of 
      increasing model complexity. We fitted linear regression models with continuous 
      and categorised predictors, as well as piecewise linear and generalised additive 
      models (GAMs). Models were compared using Akaike's information criterion (AIC). 
      RESULTS: Population density was an independent predictor of trauma mortality 
      rates, while the contribution of transport time to hospital care was highly 
      dependent on choice of statistical model. A multiple GAM or piecewise linear 
      model was superior, and similar, in terms of AIC. However, while transport time 
      was statistically significant in multiple models with piecewise linear or 
      categorised predictors, it was not in GAM or standard linear regression. 
      CONCLUSIONS: Population density is an independent predictor of trauma mortality 
      rates. The added explanatory value of transport time to hospital care is marginal 
      and model-dependent, highlighting the importance of exploring several statistical 
      models when studying complex associations in observational data.
CI  - Published by the BMJ Publishing Group Limited. For permission to use (where not 
      already granted under a licence) please go to 
      http://www.bmj.com/company/products-services/rights-and-licensing/
FAU - Roislien, Jo
AU  - Roislien J
AD  - Department of Health Sciences, University of Stavanger, Stavanger, Norway 
      Department of Biostatistics, Institute of Basic Medical Sciences, University of 
      Oslo, Oslo, Norway.
FAU - Lossius, Hans Morten
AU  - Lossius HM
AD  - Department of Health Sciences, University of Stavanger, Stavanger, Norway 
      Department of Research, Norwegian Air Ambulance Foundation, Drobak, Norway.
FAU - Kristiansen, Thomas
AU  - Kristiansen T
AD  - Department of Research, Norwegian Air Ambulance Foundation, Drobak, Norway 
      Department of Anaesthesiology, Vestre Viken Hospital Trust, Drammen, Norway.
LA  - eng
PT  - Journal Article
DEP - 20150513
PL  - England
TA  - Inj Prev
JT  - Injury prevention : journal of the International Society for Child and Adolescent 
      Injury Prevention
JID - 9510056
SB  - IM
MH  - Age Factors
MH  - Humans
MH  - *Models, Statistical
MH  - Multiple Trauma/*mortality
MH  - Multivariate Analysis
MH  - Norway/epidemiology
MH  - Population Density
MH  - Registries
MH  - Risk Factors
MH  - Rural Population/*statistics & numerical data
MH  - Time Factors
MH  - Transportation of Patients/*statistics & numerical data
PMC - PMC4717406
EDAT- 2015/05/15 06:00
MHDA- 2016/09/07 06:00
PMCR- 2016/01/19
CRDT- 2015/05/15 06:00
PHST- 2014/10/22 00:00 [received]
PHST- 2015/03/27 00:00 [accepted]
PHST- 2015/05/15 06:00 [entrez]
PHST- 2015/05/15 06:00 [pubmed]
PHST- 2016/09/07 06:00 [medline]
PHST- 2016/01/19 00:00 [pmc-release]
AID - injuryprev-2014-041473 [pii]
AID - 10.1136/injuryprev-2014-041473 [doi]
PST - ppublish
SO  - Inj Prev. 2015 Dec;21(6):367-73. doi: 10.1136/injuryprev-2014-041473. Epub 2015 
      May 13.