Increasing socio-economic inequalities in drug-induced deathsin Australia: 1981 – 2002

JAKE M. NAJMAN1,2, GHASEM TOLOO3, & GAIL M. WILLIAMS2

1School of Social Science, University of Queensland, Brisbane, Queensland, Australia, 2School of Population Health,

University of Queensland, Brisbane, Queensland, Australia, and 3The University of Queensland Social Research Centre

(UQSRC), University of Queensland, Brisbane, Queensland, Australia

AbstractIntroduction and Aims. Since the 1990s illicit drug use death rates in Australia have increased markedly. There is anotable gap in knowledge about changing socio-economic inequalities in drug use death rates. Some limited Australian andoverseas data point to higher rates of drug death in the lowest socio-economic groups, but the paucity of available studies andtheir sometimes conflicting findings need to be addressed. Design and Methods. This paper uses data obtained from theAustralian Bureau of Statistics (ABS) to examine changes in age-standardised drug-induced mortality rates for Australianmales over the period 1981 – 2002. Socio-economic status was categorised as manual or non-manual work status. Results.With the rapid increase in drug-induced mortality rates in the 1990s, there was a parallel increase in socio-economic inequalitiesin drug-induced deaths. The decline in drug death rates from 2000 onwards was associated with a decline in socio-economicinequalities. By 2002, manual workers had drug death rates well over twice the rate of non-manual workers. Discussion.Three factors are identified which contribute to these socio-economic inequalities in mortality. First, there has been an age shift indeaths evident only for manual workers. Secondly, there has been an increase in availability until 1999 and a relative decline inthe cost of the drug, which most often leads to drug death (heroin). Thirdly, there has been a shift to amphetamine use whichmay lead to significant levels of morbidity, but few deaths. [Najman JM, Toloo G, Williams GM. Increasingsocio-economic inequalities in drug-induced deaths in Australia: 1981 – 2002. Drug Alcohol Rev 2008;27:613–618]

Key words: Australia, drug-induced death, socio-economic status, trend, 1981 – 2002.

Introduction

While a good deal is known about socio-economic

inequalities in mortality for various countries and most

causes of death [1 – 9], very little is known about socio-

economic inequalities in deaths attributable to the use

of illicit drugs. In Australia, there is some evidence that

socio-economic inequalities in overall mortality may be

increasing [10]. Little is known about whether there are

socio-economic inequalities in deaths attributable to

the use of illicit drugs, and whether these inequalities

have changed in recent years in Australia.

Although drug-induced deaths comprise a modest

proportion of deaths in Australia, the prevalence and

use of illicit drugs, and problems associated with them,

have increased in recent years [9] and remain of serious

concern. Using data provided by the Australian Bureau

of Statistics, this paper examines how the relationship

between socio-economic status and drug-induced

deaths has changed for males in Australia over the past

two decades.

Socio-economic inequalities in illicit drug use deaths

There are a number of studies suggesting that illicit drug

use death rates are highest in the groups that are most

economically disadvantaged. Unfortunately, much of

these data involve using area-based sources to infer

individual associations (the so-called ecological fallacy –

see Tunstall, Shaw & Dorling [11]. For example, an

Received 17 May 2007; accepted for publication 29 October 2007.

Jake M. Najman PhD, Professor of Medical Sociology, School of Social Science, University of Queensland, St Lucia, Brisbane and School ofPopulation Health, University of Queensland, University of Queensland, St Lucia, Brisbane, Queensland, Australia, Ghasem Toloo PhD, ResearchFellow, The University of Queensland Social Research Centre (UQSRC), University of Queensland, University of Queensland, St Lucia, Brisbane,Queensland, Australia, Gail M. Williams PhD, Professor of International Health Statistics, School of Population Health, University of Queensland,University of Queensland, St Lucia, Brisbane, Queensland, Australia. Correspondence to Professor Jake M. Najman, Schools of Population Healthand Social Science, University of Queensland, St Lucia 4072, Queensland, Australia. Tel: þ61 7 3365 5180. E-mail: j.najman@uq.edu.au

Drug and Alcohol Review (November 2008), 27, 613–618

ISSN 0959-5236 print/ISSN 1465-3362 online/08/060613–06 ª Australasian Professional Society on Alcohol and other Drugs

DOI: 10.1080/09595230801956108

ecological study in New York City compared poverty

status of various districts and concluded that nearly 62%

of all fatal drug overdoses could be accounted for by the

level of district poverty [12]. Similarly, a study of

mortality inequalities in Rome, Italy, showed that over

the 1990 – 92 period, younger men in the 15 – 44 age

group in the lowest socio-economic status (SES)

areas had nearly 3.5 times more chance of death as a

result of overdose than those in the least disadvantaged

areas [6, p. 689].

Another study, conducted in Madrid and Barcelona,

suggested that while drug overdose was the second

major cause of deaths among those aged 25 – 34 years,

people with low or no education were three to seven

times more likely to die than those with secondary or

higher education [2]. A longitudinal study of injecting

drug users in Valencia, Spain, showed that those with

higher education were half as likely to die as a result of

drug use as those with less education [13].

There is some limited evidence that the number of

deaths associated with drug use in Australia is

associated with social and economical inequalities.

Turrell & Mathers [9] compared data for two periods

of 1985 – 87 and 1995 – 97 and included ‘drug

dependence’ as a cause. They included death rates

as a separate category for 15 – 24-year-old age group

only. Their study showed that while the drug

dependence mortality rate among the 15 – 24-year-

old group increased over the study period generally,

the magnitude of increase was faster for the least

socio-economically disadvantaged areas [9, p. 234].

Given that drug-induced deaths in Australia peaked in

1999 [14,15], there is a need to determine whether the

changes prior and subsequent to this peak were

differentially experienced by higher and lower socio-

economic groups.

With such a small number of studies documenting

inequalities in drug-induced deaths, it is useful to look

at the studies that have investigated socio-economic

inequalities in the use/abuse of illicit drugs. Surpris-

ingly, such studies do not abound either. In their review

of the adverse health consequences of low socio-

economic status among drug users, Galea, Ahern &

Vlahov [16] noted how ‘sparse’ these studies are. Their

review indicated that ‘poor socio-economic conditions’

are associated with ‘greater morbidity and mortality

among drug users’ [16, S138]. However, existing

studies greatly differ in their findings. For example,

the 2001 National Drug Strategy Household Survey

(NDSHS) found that there was little difference

between socio-economic groups in terms of recent or

lifetime illicit drug use. About 35 – 40% of people in all

socio-economic groups reported ever using illicit drugs

and 16 – 18% reported recent use [17]. While other

studies may point to a strong association between drug

use and unemployment, the impact of drug use on

employment status makes it difficult to determine the

cause – effect direction of such an association.

The reason for conflicting findings concerning the

association between socio-economic status and drug use

lies not only in the populations studied, but also in the

design differences between studies. Many studies have

focused on specific groups such as injecting drug users,

homeless people, prisoners, people from various ethnic

backgrounds or people with human immunodeficiency

virus/acquired immunodeficiency syndrome (HIV/

AIDS) or hepatitis as their subjects. The findings from

these studies cannot be generalised and compared with

studies that may involve other social groups or general

population samples. Also, differences in the definition

of drugs or substances used could contribute to the

contradictory results. For instance, the type of drugs or

substances studied range from alcohol and tobacco to

marijuana, opiates, cocaine, methamphetamines and so

on. Prevalence of such drugs may vary among different

social groups, hence leading to different pictures of the

association between SES and drug use.

Method

From the Australian Bureau of Statistics we obtained

details of deaths (from death certification) attributable

to illicit drug use (ICD9-304) between 1981 and 2002

(inclusive) for Australian males aged 15 – 64 years. Use

of drugs as an underlying cause of death in Australia

has been classified by the Australian Bureau of Statistics

(ABS) since 1907, which has repeatedly refined the

definition of the ‘causes of death’ according to

International Classification of Diseases (ICD) revi-

sions. Denominator occupational data are derived from

successive census collections (1981, 1986, 1991, 1996

and 2001). Population counts for the years between a

census were estimated by assuming average rates of

annual population growth. Death rates were standar-

dised to the Australian 1996 population distribution

(males only). Comparisons are limited to males only

because in the early 1980s few women were in some

sectors of the Australian work-force – making compar-

isons over time for women impracticable.

In deriving occupational mortality rates it must be

acknowledged that the different sources of data used to

derive mortality rates may lead to some error, and

possibly bias. Questions in the census relate to current

occupation. Occupational categories derived from

death certificates is provided by next of kin and relates

generally to usual occupation rather than the occupa-

tion of that person prior to death. To correct for the so-

called numerator/denominator bias, we have examined

imputed data such that all those not currently in the

work-force (between 28 and 39% of deaths and

23 and 33% of the population – varies by year)

are redistributed according to known population

614 J. M. Najman et al.

estimates [10]. This involves using the information

published periodically by the ABS on work-force

surveys of the ‘usual’ work category of those not

currently in the work-force. The data are available by

age and gender. We have examined both the imputed

and non-imputed data and the findings are identical.

To conserve space we have presented only the non-

imputed data.

Drug deaths in Australia

In this paper, we have acquired the drug-induced death

data for all the years between 1981 and 2002 from the

ABS. The Bureau defines drug-induced death as:

Any death where the underlying cause of death was

due to: an acute episode of poisoning or toxicity to

drugs. Included are deaths from accidental overdoses

due to misuse of drugs, intentional self-harm, assault

and deaths undetermined as to intent [18, p. 2].

Socio-economic status

Current occupations as specified in the ABS data were

used to determine the socio-economic classification of

individuals. The occupations were then aggregated into

manual and non-manual categories.

Data analysis

Age-standardised mortality rates (ASMRs) were calcu-

lated for all years using the ABS population census data

(1981, 1986, 1991, 1996 and 2001) and population

estimates for the non-census years. The data were

standardised to the Australian 1996 population. We also

computed the ratio of manual to non-manual occupa-

tions in terms of drug deaths to compare the trend and

magnitude of changes between 1981 and 2002.

Results

Table 1 (column 1) shows the changes in drug-induced

age-standardised mortality rates for Australian males

aged 15 – 64 years over the period 1981 – 2002. For all

time-periods the proportions of manual workers whose

deaths are attributable to drug use appear to be greater

than for non-manual workers. The drug-induced death

rate reached a peak in 1999. Using 1981 as the

reference year, by 1999 death rates attributable to drug

use had increased greatly, and even by 2002 drug-

induced death rates remained substantially higher than

they were in 1981. Generally, over time, deaths

attributable to drug use have increased more for

manual than non-manual workers. We consider the

extent to which deaths attributable to drug use

comprise a changing percentage of all deaths. In

1981, drug-induced deaths were about 1% of all

deaths. By 1999, drug-induced deaths were 6.3% of

manual worker deaths and 4.3% of non-manual worker

deaths. Finally, we also consider the changing ratio of

manual to non-manual death rates over the period

1981 – 2002. In the early 1980s, manual workers had

death rates which were somewhat higher than those

experienced by non-manual workers. By 1999 the

differences had increased, and even in the early 2000s

manual workers had death rates more than twice those

of non-manual workers.

Table 2 presents the changing percentage of deaths in

each age group for drug-induced deaths for each year

category. For manual workers in 1981, three of every

four deaths (76%) were in the 15 – 34 age group

compared to about half the deaths for non-manual

workers occurring in that age group. Over time (from

1981 – 2002) there has been a marked shift in the age

distribution of drug-induced deaths experienced by

manual workers. For manual workers, there is an

Table 1. Drug-induced deaths (ICD9-304) Australian males 15–64 years, 1981–2002 comparison of manual/non-manual occupa-

tional groups

Drug-induceddeaths: age-standardisedmortality rate(per 100 000population)

Drug-induceddeaths as

percentage ofall deaths

Ratio ofmanual/

non-manualmortality

rate*

Year ManualNon-

manualManual

%

Non-manual

%Manual/

non-manual

1981 5.81 3.44 1.1 0.9 1.691982 6.10 3.61 1.1 1.0 1.691983 6.97 3.78 1.3 1.1 1.841984 6.62 3.68 1.3 1.1 1.801985 7.95 4.84 1.5 1.4 1.641986 7.39 3.41 1.3 1.0 2.171987 9.55 4.69 1.7 1.3 2.041988 11.78 5.82 2.1 1.6 2.021989 10.55 4.39 1.9 1.3 2.401990 13.73 5.66 2.4 1.6 2.431991 10.51 5.38 2.0 1.5 1.951992 11.64 5.46 2.1 1.6 2.131993 11.26 5.17 2.1 1.5 2.181994 14.33 5.95 2.6 1.8 2.411995 18.45 6.24 3.4 2.0 2.961996 16.95 6.79 3.1 2.3 2.501997 19.49 7.36 4.0 2.8 2.651998 24.07 8.56 5.1 3.6 2.811999 27.16 9.82 6.3 4.3 2.772000 23.75 7.52 5.8 3.6 3.162001 12.92 5.11 3.3 2.4 2.532002 10.46 4.60 2.8 2.2 2.27

*Ratio compared the age-standardised rates.

Socio-economic inequalities in drug-induced deaths in Australia 615

‘ageing’ of deaths, with deaths being shifted progres-

sively to older age groups over time. By contrast, the

changes in the age of death for non-manual workers

have not fluctuated in a consistent manner. Indeed, the

age distribution of drug-induced deaths for non-

manual workers is, in 2002, little different from 1981.

Over time, the age distribution of drug-induced deaths

experienced by manual workers has changed to

resemble the pattern in non-manual workers.

Discussion

Using a national-level mortality data set, we have

examined drug-induced death inequality trends in

Australia over the period of 1981 – 2002. Overall,

socio-economic inequalities in drug-induced deaths

are of a substantial magnitude and have increased with

the increase in the number of deaths attributed to the

use of illicit drugs, and decreased as the overall number

of drug-induced deaths has decreased. The change in

the age distribution of drug use by manual workers (an

ageing effect) may indicate a shift in (largely) heroin use

from younger to somewhat older manual workers.

Two important issues derive from these findings.

First, why have drug-induced death rates changed over

time? It seems likely that the increase in deaths attri-

butable to drug use reflects the increased availability

and affordability (increased access) of illicit drugs,

particularly heroin. It is probable that an increased

access to (primarily) heroin has a disproportionate

impact on overall mortality rates and on the mortality

risk of manual workers in particular. Anderson [19] has

argued persuasively that the two major factors influen-

cing the uptake of licit and illicit drugs are affordability

and availability. Mann [20] has argued that availability

not only ‘drives’ use, but that increased availability of

drugs is the major determinant of use. In one of the

only studies to test the above causal sequence, Caulkins

[21] has found a strong association between the price of

illicit drugs and the rate of emergency department

presentations attributed to illicit drug use. Degenhardt

and colleagues [22] examined the heroin shortage in

Australia in 2001 and found that fatal overdoses of

heroin dropped by 40%. The routine monitoring of the

availability and price of illicit drugs in Australia

commenced in 1997 – 98 with the advent of the Illicit

Drug Reporting System (IDRS). These data confirm

that, over the period 1996 – 2005, the price of heroin

has remained relatively stable and that there has been a

steady decline in the median purity of heroin seized by

police since 1999 [23]. Arguably, the decline in the

availability and purity of heroin has led to the decline in

socio-economic inequalities in drug-induced deaths

since 1999.

Table 2. Drug-induced deaths (ICD9-304) by age and occupational category Australian males 1981-2002 (percentage of each age categorydying each year)

Manual%

Non-manual%

Year 15 – 34 35 – 49 50 – 64 Total 15 – 34 35 – 49 50 – 64 Total

1981 76 13 11 128 43 38 20 611982 72 14 14 130 52 33 15 671983 71 19 9 150 57 23 20 691984 70 19 11 139 57 31 12 721985 78 15 7 171 61 27 12 931986 77 16 8 159 53 29 18 681987 72 23 5 201 45 30 25 881988 73 22 5 247 50 37 13 1101989 71 23 6 218 45 36 18 881990 71 26 4 277 51 31 18 1121991 66 28 5 208 42 39 18 1141992 67 26 7 232 51 34 15 1091993 62 31 7 224 41 50 8 1191994 58 35 7 280 49 44 7 1351995 60 32 8 362 42 44 14 1491996 61 35 4 342 44 44 12 1511997 56 40 4 388 45 43 11 1751998 64 34 2 489 51 38 11 2151999 62 34 3 545 47 42 11 2422000 59 38 3 477 46 43 11 1882001 53 38 9 255 43 36 21 1332002 49 39 12 212 41 43 16 120

616 J. M. Najman et al.

Secondly, do the changing socio-economic inequal-

ities in drug-induced deaths reflect changing inequal-

ities in drug use? It is difficult to know whether socio-

economic inequalities in drug-induced mortality are

consistent with patterns of drug use. While many

studies have noted the high rate of unemployment in

those who are accessing treatment services, much of

this will reflect the impact of heavier levels of drug use

on employment. The above finding is not inconsistent

with the possibility that drug use levels are similar for

various socio-economic groups.

In the absence of studies of comparable scope,

magnitude and methodology, it is very difficult to

assess how our findings compare with those of others in

Australia and in other developed countries. Turrell &

Mather’s [9] finding was limited to the 15 – 24-year-old

age group and used a Gini coefficient and socio-

economic index for geographical areas (SEIFA) to

study mortality inequalities. Despite methodological

differences, our data are consistent with the observation

of a reduction in mortality inequality of the younger age

group between the 1985 – 87 and 1995 – 97 periods. Of

course, the changing age distribution of deaths in the

manual workers largely explains this finding. Turrell &

Mathers concluded that the decline in inequality in

drug dependence death rates among Australian youth

was due mainly to ‘a faster rate of increase in illicit drug

deaths in higher socio-economic areas, and is likely to

reflect the increasing use and availability of heroin in

Australia across all socio-economic groups’ [9, p. 238].

However, had Turrell & Mathers included all age

groups they would have observed increasing socio-

economic inequalities over time, with the lowest

socio-economic group having the largest increase in

drug-induced deaths.

The previously mentioned study of mortality inequal-

ities in Rome, Italy, showed that over the 1990 – 92

period younger men aged 15 – 44 in the lowest SES

areas had nearly 3.5 times more chance of deaths as a

result of overdose than those in the least disadvantaged

areas. The authors attributed the high overdose-related

deaths in low SES areas to injecting drug users, and to

‘an increase in illicit drug use in lower socio-economic

levels and/or an increase in susceptibility of extremely

poor drug users’ [6, p. 692]. One possible explanation

for the changing socio-economic inequalities in illicit

drug deaths acknowledges that the rate of illicit drug

use may be similar for socio-economic groups, but that

the pattern of use may be different. There are few data

available to assess the possibility that when lower SES

groups use illicit drugs, their pattern of use involves

higher-risk behaviour. Certainly, studies of socio-

economic differences in alcohol and tobacco use would

suggest the possibility that there are important differ-

ences not only in rates of use but in the level of risk

associated with use [24 – 26].

Limitations

It is important to acknowledge four limitations of our

study. First, we used occupational categories (manual

and non-manual) as the sole indicator of socio-

economic inequalities. Broad occupational groupings

were necessary to permit stable comparisons over time.

However, limiting ourselves to manual/non-manual

occupations restricts the nature of the occupational

comparisons which can be made. As Braveman et al.

[27] have noted, findings may vary depending upon the

measure of SES which is selected. In this study

alternative indicators of SES were not available.

Secondly, we did not have other work-related variables

that could have helped to estimate the net effects of SES

on drug-induced deaths. Thirdly, the absence of

females limits the generalisability of the findings. This

limitation was necessary given the rapid changes which

have occurred in women’s work-force participation.

There is a need to conduct current comparisons of

drug-induced deaths for women in the work-force – but

such comparisons will depend upon sufficient data

becoming available. Fourthly, it seems likely that drug-

induced deaths may not always be recorded and that

death certificates may represent a conservative estimate

of the number of deaths attributable to illicit drug use.

It is also possible that this source of error may have

changed in degree over time, although there is no way

of assessing the extent to which this influenced our

findings.

None of the above limitations constitutes a major

threat to our findings. To our knowledge this is the first

study that has analysed the trend and magnitude of

change in drug-induced deaths as experienced by men

of different age groups and socio-economic status. The

findings can be used as a baseline by other researchers

to develop further detailed analyses of the drug trends

in other countries; and by policy makers to assess how

their decisions may affect the public domain; how to set

priorities and identify target groups that may be high

risk. The findings may also help to understand how

and where intervention programmes need to place

emphasis.

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