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Accident Analysis and Prevention 49 (2012) 520– 524

Contents lists available at SciVerse ScienceDirect

Accident Analysis and Prevention

jo ur n al hom ep a ge: www.elsev ier .com/ locate /aap

eductions in transport mortality in Australia: Evidence of a public health success

elen L. Walls ∗, Andrea J. Curtis, Christopher E. Stevenson, Haider R. Mannan, John J. McNeil,osanne Freak-Poli, Belinda Gabbe

epartment of Epidemiology & Preventive Medicine, Monash University, The Alfred Centre, 99 Commercial Road, Victoria 3004, Australia

r t i c l e i n f o

rticle history:eceived 8 September 2011eceived in revised form 21 February 2012ccepted 20 March 2012

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Objective: To describe trends in transport mortality for a range of common transport types in Australiaover a 30-year period (1975–1977 to 2005–2007).Methods: Mortality data on all-cause and transport-related causes of death were supplied by theAustralian Institute of Health and Welfare (AIHW). Mortality rates, expected number of deaths andprobabilities of death were compared for three time periods: 1975–1977, 1990–1992 and 2005–2007.Results: There were significant decreasing trends between 1975–1977 and 2005–2007 in all-cause andmost other transport mortality types for both men and women. There were significant reductions in thecontribution of transport-related mortality to all-cause mortality; however the difference in mortalitybetween men and women (higher for men) changed little over the evaluated period.

ir and spaceustralia

Conclusions: Between 1975–1977 and 2005–2007 there were marked reductions in key causes oftransport-related mortality amongst Australian adults, and the reductions in transport-related mortalityexceeded reductions in all-cause mortality. The reductions could be attributed to better preventive mea-sures and improved medical treatment for people involved in transport crashes. Although there is scopefor further improvement, the reductions are evidence of a success in the prevention of crashes and themedical treatment of crash victims.

. Introduction

The United Nations has named 2011–2020 the global Decade ofction for Road Safety. The resolution was passed in March 2010 by

he UN General Assembly, who described the toll of death and injuryrom road crashes as “a major public health burden. . . which, ifnaddressed, may affect the sustainable development of countriesnd hinder progress towards the Millennium Development Goals”WHO, 2010; FIA Foundation, 2010).

Worldwide, the number of people killed in road traffic crashesach year is estimated at almost 1.2 million, while the numbernjured could be as high as 50 million (Peden et al., 2004). How-ver these figures attract considerably less media attention than

ther less frequent but more unusual types of tragedy (Peden et al.,004). Without increased efforts and new initiatives, the total num-er of road traffic deaths and injuries worldwide is forecast to rise

∗ Corresponding author at: The Australian National University, Building 62, Cnr ofggleston and Mills Roads, The Australian National University, Acton 2000, Australia.el.: +61 2 6125 9506.

E-mail addresses: Helen.walls@anu.edu.au (H.L. Walls),ndrea.curtis@monash.edu (A.J. Curtis), Chris.stevenson@monash.eduC.E. Stevenson), Haider.mannan@monash.edu (H.R. Mannan),ohn.mcneil@monash.edu (J.J. McNeil), Rosanne.freak-poli@monash.eduR. Freak-Poli), Belinda.gabbe@monash.edu (B. Gabbe).

001-4575/$ – see front matter © 2012 Elsevier Ltd. All rights reserved.ttp://dx.doi.org/10.1016/j.aap.2012.03.024

© 2012 Elsevier Ltd. All rights reserved.

by 65% between 2000 and 2020, and by as much as 80% in low- andmiddle-income countries (Peden et al., 2004).

In Australia, consistent with other countries belonging to theOrganisation for Economic Cooperation and Development (OECD),the number of traffic fatalities peaked in the early 1970s, andhas since declined (Elvik, 2010; WHO, 2009; Chen et al., 2010).However, death from external causes (considered as deaths fromaccident and injury) is still the leading cause of death amongstpeople aged under 55 years in Australia and transport crashesare the second most prevalent cause of fatal injury (after sui-cide), accounting for nearly 2000 deaths per year (ATSB, 2004).However, it is unclear to what extent transport-related fatali-ties have declined in Australia relative to reductions in all-causemortality, and whether such declines have also taken place forother transport-related mortality – for rail and air transportfatalities.

In addition to providing a better understanding of past suc-cesses in public health, improved understanding of the types oftransport-related mortality and the way in which these contributeto overall transport-related and all-cause mortality should helpdetermine the most appropriate targets for public health and medi-

cal interventions to achieve further reductions in transport-relatedmortality, and assist our understanding of the likely future con-tributions to transport-related mortality from specific transporttypes.

sis and Prevention 49 (2012) 520– 524 521

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Table 1ICD-codes for conditions of interest.

Condition ICD-10 code

Transport accidents V01–V99Motor vehicle accidents V02–V04Other road vehicle accidentsa V01Railway accidentsb V05, V15, and V81Air and space transport accidents V95–V97

a ‘Other road vehicle accidents’ includes collisions between pedestrians and bicy-

to 2005–2007.Transport-related mortality rates and the number of deaths

expected in the Australian population were higher for men than

H.L. Walls et al. / Accident Analy

This study aimed to describe trends in transport-related mor-ality for a range of common transport types in Australia over a0-year period (1975–1977 to 2005–2007). First, the probability ofying from key transport types over the 30-year period was cal-ulated. Second, the contribution of transport-related mortality toll-cause mortality was examined.

. Materials and methods

.1. Data source

Mortality data for transport-related deaths, stratified by agend sex, for three time periods (1975–1977, 1990–1992 and005–2007) were compared. National death counts classified byge and sex for the top causes of death and for all deaths combinedor these three periods were supplied by the Australian Institutef Health and Welfare (AIHW). These data were derived from theIHW National Mortality Database comprising all deaths registered

n Australia (AIHW, 2011). For each three-year period, the deathsrom each year were aggregated and divided by the sum of thennual mid-year population to provide crude estimates of mortalityate.

Population data published by the Australian Bureau of Statisticsere used in the calculation of age-standardised mortality rates

ABS, 2010).

.2. Mortality analysis

Deaths were categorised into one of four age groups: 0–14,5–24, 25–64 and 65+ years.

Mortality for the three periods was expressed using annual age-tandardised mortality rates, expected number of deaths per 1000opulation, and associated five-year risks of death. The mortalityates were directly age-standardised (using five-year age groups)o the total Australian population at June 2010 (ABS, 2010). Theve-year risks of death were derived from the corresponding agetandardised annual mortality rate using the standard life tableelationship between rates and probabilities (see, for example,hiang, 1984).

Statistical significance was determined by the use of confidencentervals, calculated for the age standardised rates based on Bres-ow and Day’s method modified to use a normal assumption for ainomial distribution for the crude age-standardised rates (Breslownd Day, 1987). These limits were also translated to five-year risksf death and used as 95% confidence intervals for the risk estimates.

For deaths registered from 1 January 1997, Australia adoptedhe use of the Automated Coding System (ACS) and introducedCD-10 codes. Thus, deaths for the latest period included in thistudy were coded according to the 10th revision of the Internationallassification of Diseases (ICD-10). However in periods 1975–1977nd 1990–1992, ICD-7 and ICD-9 coding applied. In order to makeeaths information comparable over time, the AIHW mapped alleaths to ICD-10 codes using the methodology described by Tay-

or (1992) (AIHW and Taylor, 1992), and more recently ICD-9 toCD-10 mapping tables released by the World Health Organization.s a result of the change in the coding of deaths between 1996nd 1997, comparability factors given by the AIHW provide theink between the two data series, based on a direct comparisonf double-coded deaths. For comparability with data post 1997, anstimate of the number of deaths attributed to a particular cause forhe 1979–1996 data can be produced by multiplying the number ofeaths attributed to that cause by its corresponding comparability

actor (AIHW, 2010). The comparability factor to adjust 1979–1996ata for transport accidents to post-1997 standards is 1.03. How-ver comparability factors were unable to be estimated for railway,ir and space and other road vehicle mortality due to small numbers

cles, pedestrians, animals and fixed/stationary objects.b ‘Railway accidents’ includes collisions between pedestrians and cyclists with

railway trains/vehicles, and injury to occupants of railway trains/vehicles.

of these crashes (AIHW, 2010), so we used the unadjusted countsfor the earlier periods for these causes.

Table 1 lists the ICD-10 codes for the conditions described inthis paper. The system of groupings of causes of death developedby Becker et al. (2006), and recommended by the AIHW, for derivingleading causes of transport-related death was used.

3. Results

Transport-related deaths contributed to all-cause mortality byapproximately 0.6–3.2% during the evaluated period. There werereductions in the contribution of transport-related mortality to all-cause mortality for both men and women (Fig. 1). The reductionin transport-related deaths for women was from a contribution of1.4–0.6% between 1975–1977 and 2005–2007 and for men from3.2% to 1.6%.

There was a decrease in all-cause and all other transport-relatedmortality types for both men and women between 1975–1977and 2005–2007, with the exception of ‘air and space’ mortality inmen (Table 2). However, the apparent increase from 1975–1977to 1990–1992 in ‘air and space’ mortality in men was not statisti-cally significant and there was a statistically significant reduction

Fig. 1. Burden of age-standardised transport-related mortality rates comparedto other-cause mortality per 100,000 population in 1975–1977, 1990–1992 and2005–2007.

522 H.L. Walls et al. / Accident Analysis and Prevention 49 (2012) 520– 524

Table 2Age-standardised all-cause and transport-related mortality per 100,000 population for all age groups (with 95% confidence intervals) and population-standardised numberof expected deaths for females and males in 1975–1977, 1990–1992 and 2005–2007.

Mortality type Mortality rates/100,000 population Expected number of deaths (population-standardised) in 3 year periods*

1975–1977 1990–1992 2005–2007 1975–1977 1990–1992 2005–2007

Females All-causes combined 1129.4 (1123.6, 1135.2) 861.8 (857.7, 865.8) 653.2 (650.4, 656.0) 126669 96,674 73,280All transport combined 16.0 (15.4, 16.5) 9.0 (8.6, 9.3) 3.7 (3.5, 3.8) 1789 1001 418Motor vehicle 15.0 (14.4, 15.5) 8.3 (8.0, 8.7) 3.5 (3.3, 3.7) 1679 941 397Other road vehicle 0.2 (0.1, 0.2) 0.1 (0.1, 0.1) 0.0 (0.0, 0.1) 18 11 4Railway 0.4 (0.3, 0.4) 0.2 (0.1, 0.2) 0.1 (0.1, 0.1) 39 19 10Air and space 0.2 (0.1, 0.2) 0.1 (0.1, 0.1) 0.1 (0.0, 0.1) 19 11 5

Males All-causes combined 1450.0 (1443.1, 1456.8 1051.9 (1047.3, 1056.6) 712.0 (709.0, 714.9) 161294 117020 79200All transport combined 45.8 (44.8, 46.8) 22.4 (21.8, 23.0) 11.4 (11.0, 11.8) 5097 2491 1269Motor vehicle 41.5 (40.5, 42.4) 19.5 (19.0, 20.1) 10.5 (10.1, 10.8) 4611 2173 1164Other road vehicle 0.4 (0.3, 0.5) 0.3 (0.2, 0.4) 0.2 (0.1, 0.2) 43 33 17Railway 1.2 (1.1, 1.4) 0.6 (0.5, 0.6) 0.2 (0.2, 0.3) 137 62 26Air and space 0.6 (0.5, 0.7) 0.8 (0.7, 0.9) 0.3 (0.2, 0.4) 70 85 34

a The mortality rates were age standardised to the 2010 total Australian population.b The expected number of deaths was derived by multiplying the age-specific mortality rates in each period by the age-specific population counts for 2010.

Table 3Risk of dying in the next 5 years (and 95% confidence intervals) from transport-related mortality for females and males in 1975–1977, 1990–1992 and 2005–2007.*.

Age group (years) Causes of death 5-Year risk of death per 1000 population

1975–1977 1990–1992 2005–2007

Females 0–14 Motor vehicle 0.4 (0.3, 0.4) 0.2 (0.1, 0.2) 0.1 (0.1, 0.1)Other transport 0.0 (0.0, 0.0) 0.0 (0.0, 0.0) 0.0 (0.0, 0.0)

15–24 Motor vehicle 1.1 (1.0, 1.2) 0.7 (0.6, 0.7) 0.3 (0.2, 0.3)Other transport 0.1 (0.1, 0.1) 0.0 (0.0, 0.0) 0.0 (0.0, 0.0)

25–64 Motor vehicle 0.6 (0.6, 0.7) 0.3 (0.3, 0.4) 0.1 (0.1, 0.1)Other transport 0.0 (0.0, 0.1) 0.0 (0.0, 0.0) 0.0 (0.0, 0.0)

65+ Motor vehicle 1.4 (1.3, 1.5) 0.8 (0.7, 0.8) 0.2 (0.2, 0.38)Other transport 0.0 (0.0, 0.1) 0.0 (0.0, 0.0) 0.0 (0.0, 0.0)

Males 0–14 Motor vehicle 0.6 (0.6, 0.7) 0.3 (0.3, 0.3) 0.1 (0.1, 0.1)Other transport 0.1 (0.0, 0.1) 0.0 (0.0, 0.0) 0.0 (0.0, 0.0)

15–24 Motor vehicle 4.6 (4.5, 4.8) 1.9 (1.8, 2.0) 1.0 (0.9, 1.0)Other transport 0.2 (0.2, 0.3) 0.2 (0.1, 0.2) 0.0 (0.0, 0.1)

25–64 Motor vehicle 0.9 (0.9, 1.0) 0.8 (0.8, 0.9) 0.5 (0.5, 0.6)Other transport 0.1 (0.1, 0.2) 0.1 (0.0, 0.1) 0.1 (0.1, 0.1)

65+ Motor vehicle 2.4 (2.2, 2.6) 1.4 (1.2, 1.5) 0.6 (0.5, 0.7)Other transport 0.2 (0.2, 0.3) 0.1 (0.1, 0.1) 0.1 (0.1, 0.1)

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The mortality rates were age standardised to the 2010 total Australian population‘Other transport’ represents all transport-related mortality other than motor vehi

omen in all time periods. For women, there was a 77% reduction inhe age standardised all transport-related mortality rate combined,ompared with a 42% reduction in the age standardised all-causeortality rate. For men, there was a 75% reduction in all the age-

tandardised transport-related mortality rate combined, comparedith a 51% reduction in the age standardised all-cause mortality

ate combined (Table 2).The difference between men and women for transport related

eaths changed little over the evaluated period, (from 2.9-foldigher in men in 1975–1977 to 3.1-fold higher in men in005–2007) (Table 2).

Motor vehicle mortality contributed to approximately 90% ofll transport-related mortality for both men and women in eachime period. The absolute reduction in motor vehicle mortalityetween 1975–1977 and 2005–2007 was 15.0–3.5 per 100,000opulation for women and 41.5–10.5 per 100,000 population foren. However, all transport-related mortality also reduced dur-

ng this period and the proportional contribution of motor vehicleortality remained relatively constant (91% in 1975–1977 to 92%

n 2005–2007 for males and 94% in 1975–1977 to 95% in 2005–2007or females) (Table 2).

Table 3 translates the mortality rate changes described abovento changes in the risk of dying in the next five years per 1000

2010).rtality (i.e. ‘other road vehicle’, ‘railway’ and ‘air and space’).

population. The risk of dying in the next 5 years from a motorvehicle crash decreased over time for all age and sex groups(Table 3). For women aged 25–64 years, the risk of dying in thenext 5 years from a motor vehicle crash decreased from 0.6 per1000 population in 1975–1977 to 0.1 per 1000 population in2005–2007. The risk of dying in the next 5 years from a motorvehicle crash for men aged 25–64 years decreased from 0.9 per1000 in 1975–1977 to 0.5 per 1000 in 2005–2007.

There were marked differences in these reductions by age, par-ticularly for men. For example, the risk of dying in the next fiveyears from a motor vehicle crash decreased by 44% for men aged25–64 years (from 0.9 per 1000 population in 1975–1977 to 0.5 per10,000 in 2005–2007), but the decline was 78% for men aged 15–24years (from 4.6 per 1000 population in 1975–1977 to 1.0 per 1000population in 2005–2007) (Table 3).

4. Discussion

During the 30 years between 1975–1977 and 2005–2007, there

were reductions in all main causes of transport-related deathsfor women and men. This decreasing trend mirrored reductionsin all-cause mortality across the same period. However while thereductions in all-cause mortality for women and men were 42%

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nd 51% respectively, the reductions in all-transport mortalityere 77% and 75% respectively. Motor vehicle crashes contributed

verwhelmingly to the main causes of transport-related mortalityn all time periods.

In the context of all-cause mortality in Australia in 2005–2007,and transport crashes were the third leading cause of death in

oman aged 25–44 years (comprising of 5% of deaths in this group,nd following breast cancer and suicide) and the second-rankedause of death in men aged 25–44 years (comprising 12% of deathsn this group, and following suicide). However (based on data of atudy of mortality trends in Australia; Walls et al., in preparation), in985–1987, land transport crashes were the second-ranked causef deaths in women aged 25–44 (comprising 10% of all deaths) andn both 1965–1967 and 1985–1987 land transport crashes were theeading cause of death in men aged 25–44 years (comprising 17%f deaths in both time periods in this age group).

There was a marked decrease in the risk of dying in the nextve years from a motor vehicle crash, particularly in men aged5–24 years, for whom the risk of death declined by nearly 80% overhe 30-year period. Considering the significant contribution trafficollisions have made to mortality amongst people aged 15–24, par-icularly males, for some decades (AIHW, 2005), targeting youngeople for traffic safety behaviour including speeding and driv-

ng under the influence of alcohol and drugs has been a priority ofany government preventative campaigns (TAC, in press; DoHA, in

ress). These Australian results are consistent with other countrieselonging to the OECD, which have undergone a decline in trafficatalities since 1970–1972 (Elvik, 2010) and reductions in the riskf death from vehicle collisions amongst young people (Kopits andropper, 2005).

A number of factors are likely to have contributed to this decline,nd will have impacted differently on mortality risk for men andomen and different ages. Each state has invested significantly

n public health policies and road safety interventions such asrink driving restrictions (Homel et al., in press; Horwood andergusson, 2000; Homel, 1994), the compulsory use of seat beltsRobertson, 1976), lower speed limits (Ameratunga, 2009), betteroads (Stidger, 2003; Wegman, 2003) and improved car design andafety (Richter et al., 2005; AIHW, 2006). Improved medical treat-ent of transport-related crash victims is also likely to play a role

Gabbe et al., 2011). A key strength of our study is that it is basedn registered deaths for the whole population in Australia over thetudy period. We also based our analyses on standard, robust lifeable methods which are well known to accurately reflect currentbserved mortality (Chiang, 1984).

One limitation of our study is that we were unable to addresshe non-fatal morbidity arising from road traffic crashes. A signif-cant non-fatal morbidity burden related to transport crashes haseen demonstrated in previous studies (Vos et al., 2007) but com-rehensive national data analogous to the mortality data are notvailable. Furthermore an appropriate assessment of nonfatal mor-idity is beyond the scope of this paper (Lyons et al., 2010; Polindert al., 2011). The Australian Transport Safety Bureau has estimatedn average of 36,000 people seriously injured annually in transportrashes between 2000 and 2002 (ATSB, 2004). Serious injury wasefined as ‘an injury which results in the person being admitted toospital, spending at least one night in hospital and subsequentlyecovering (i.e. deaths are excluded)’ (ATSB, 2004). The Nationalnjury Surveillance Unit also publishes on serious injury due to landransport crashes (Henley and Harrison, 2009a,b).

Another limitation of our study is that our projected mortalitythe 5 year risk of death – is based on current mortality and so our

stimates do not take account of any potential changes in mortalityrends over the subsequent 5 years. This is a feature of the life table

ethodology which is designed as a summary of current mortalityather than a prediction of future mortality.

Prevention 49 (2012) 520– 524 523

5. Conclusions

In summary, between 1975–1977 and 2005–2007 there weremarked reductions in all key causes of transport-related mortalityamongst Australian adults, and the reductions in transport-relatedmortality were far in excess of the reduction in all-cause mortality(Walls et al., in preparation). The reductions could be attributed tobetter preventive measures and improved medical treatment forpeople involved in transport crashes. Although there is scope forfurther improvement, the reductions are evidence of a success inthe prevention of injury-related mortality and the medical treat-ment of crash victims.

Acknowledgements

During this preparation of this manuscript, Helen L. Walls,Christopher E. Stevenson and Haider R. Mannan were supported byan NHMRC Health Services Research grant (no. 465130). RosanneFreak-Poli was supported by an Australian Postgraduate Award anda Monash Departmental/Baker IDI Scholarship. Belinda Gabbe wassupported by an NHMRC Career Development Award (465103).Karen Bishop from the Australian Institute of Health and Welfareprovided the mortality data and advice on its interpretation.

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