title: The prevalence of crash risk factors in a population-based study of motorcycle riders.
abstract: BACKGROUND
  Motorcyclists represent an increasing proportion of road traffic casualties but, while factors associated with crashes are readily identifiable, little is known about the prevalence of those risk factors in the motorcycling population.
  
  
  METHODS
  A stratified random-sampling frame was used to survey the population of registered motorcycles owners in New South Wales (NSW) when they attended motor registry offices. The postal codes in the State database of registered motorcycle were used to stratify the population into quartiles based on socioeconomic characteristics and to determine sample weights.
  
  
  RESULTS
  Participants (n=506) represented 47% of eligible riders approached. On average participants were aged 43, rode 7h/week and had 17 years of riding experience. Estimates based on multiple ownership rates suggest motorcycle registration numbers exceed the active riding population by approximately 15%. Less than half rode under 101km/week, 25% rode over 300km/week and just 42% rode every day. More rode frequently for leisure (70%) than for commuting (53%) and over half rarely rode in dark (52%) or wet (67%) conditions. Most wore protective clothing - helmets (100%), jackets (82%), pants (56%), boots (57%) and gloves (73%). Those with traffic infringements (32%) were mostly for driving (25%), not riding (10%) offences. In the past year, 13% had one or more motorcycle crashes including minor spills and 76% one or more near-crash experiences. The youngest riders (15-19) reported the highest rates of exposure in kilometres, hours, frequency of riding and commuting. They also reported lower crash involvement (3%) but more near-crashes (80%).
  
  
  CONCLUSIONS
  This study provides an account of the prevalence of key risk factors across age groups in a population of active motorcycle riders in NSW. Novice riders were represented in all age groups although most novices were under 40 years. These data can be used to guide the development of targeted countermeasures aimed at improving motorcycling safety for riders of different age groups.
authors.affiliation: Neuroscience Research Australia; School of Medical Sciences, University of New South Wales NeuRA, Margaret Ainsworth Building, Barker Street, Randwick, Sydney, NSW 2031, Australia. Electronic address: l.derome@neura.edu.au.
authors.forename: Liz
authors.initials: L
authors.lastname: de Rome
authors.affiliation: Regulation and In-depth Crash Investigations, Monash University Accident Research Centre, Australia.
authors.forename: Michael
authors.initials: M
authors.lastname: Fitzharris
authors.affiliation: The Centre for Automotive Safety Research, University of Adelaide, Australia.
authors.forename: Matthew
authors.initials: M
authors.lastname: Baldock
authors.affiliation: NSW Centre for Road Safety, Transport for NSW, Australia.
authors.forename: Ralston
authors.initials: R
authors.lastname: Fernandes
authors.affiliation: NSW Centre for Road Safety, Transport for NSW, Australia.
authors.forename: Alice
authors.initials: A
authors.lastname: Ma
authors.affiliation: Neuroscience Research Australia; School of Medical Sciences, University of New South Wales, Australia.
authors.forename: Julie
authors.initials: J
authors.lastname: Brown
mesh_terms: D000063:Accidents, Traffic / Q000517:prevention & control / Q000706:statistics & numerical data*; D000328:Adult; D017677:Age Distribution; D005260:Female; D006260:Head Protective Devices / Q000706:statistics & numerical data*; D006306:Health Surveys; D006801:Humans; D008297:Male; D008875:Middle Aged; D009049:Motorcycles / Q000706:statistics & numerical data*; D009517:New South Wales / Q000453:epidemiology; D011481:Protective Clothing / Q000706:statistics & numerical data*; D018570:Risk Assessment
keywords: Crash; Crash risk factors; Motorcycle; Population; Prevalence