Mortality Inequities and Socioeconomic Disadvantage in Australia

Introduction

According to the World Health Organization (WHO, 1978), health has been defined as "a state of complete physical, mental and social wellbeing, and not merely the absence of disease or infirmity." As a result, health outcomes cannot only include morbidity and mortality; rather, they should include psychological and social domains of wellbeing. Health can be evaluated by a range of outcomes such as mortality, physical health, and birth and developmental products.

Mortality Inequity and Literature Review

Health authorities in Australia have dealt with critical public health challenges over the course of many years. These health inequities have manifested into socioeconomic differences as experienced by men, women, urban and rural areas, Indigenous and non-Indigenous peoples, and ethnic groups. Although there is evidence that considerable gains have been made in life expectancy and other health results for the Australian population (AIHW 2002), these gains have not been equally dispersed across members of the population. Therefore, this paper aims to address inequities in mortality as a result of socioeconomic factors.

Mortality inequities for the purpose of this paper will be presented in the context of socioeconomic groups. Mainly, mortality differences are accounted for by two groups: privileged and underprivileged. This division allows mortality differences in males and females of different age groups to be considered as an inequity rather than an inequality, as we are accounting for those differences which can be prevented and which occur as a result of unfair disparities in income, education, and other socioeconomic factors.

Socioeconomic Mortality Data by Age Group

There has been a vast amount of international literature that has provided evidence about the connection between mortality and one's socioeconomic position (House & Williams 2000; Lynch & Kaplan 2000; Ostrove & Adler 1998; Williams & Collins 1995; Davey Smith et al. 1998; Kaplan et al. 1996). The research presents a strong correlation between disadvantaged groups and mortality rates. Socioeconomic differences in mortality are present during all stages of both males' and females' life spans; "these differences have been discovered in different historical time periods and in countries where socioeconomic data have been greatly accumulated" (Ancona et al. 2000; Mackenbach 1994; Song & Byeen 2000).

Although in its infancy, there is growing evidence that inequities in mortality have amplified over time in some countries. Several disparities exist as mortality rates have declined in areas of high socioeconomic positions while they have increased in areas heavily populated by those that are disadvantaged. According to McMichael et al. (1985), socioeconomic inequalities are a recurring and frequently observed phenomenon within the Australian population.

The following provides an in-depth discussion of socioeconomic mortality inequities by age in Australia during two year periods: 1985–1987 and 1998–2000. The ages studied are as follows: infants and children (0–14 years), young adults (15–24 years), working-aged adults (25–64 years), and older persons (65 years and older). Socioeconomic status was measured by the Index of Relative Socioeconomic Disadvantage (IRSD). The IRSD was created by the Australian Bureau of Statistics and utilizes census data from the population to reflect the overall level of socioeconomic disadvantage. The IRSD calculates socioeconomic disadvantage by taking into account factors such as low income, level of educational attainment, unemployment rates, and levels of public sector housing.

Upon calculating a socioeconomic disadvantage score, the IRSD categorizes that score into five groups or quintiles. Each quintile comprised 20 percent of the Australian population. The mortality differences between Quintiles 1 and 5 are described in detail. The 20 percent of the least disadvantaged or most advantaged comprised the first quintile. The 20 percent of the most disadvantaged comprised the fifth quintile. It was demonstrated that life expectancy for males at birth for both groups, the least and most disadvantaged, was 79.2 years. For females, it was 83.6 years.

Between 1985–1987 and 1998–2000, all-cause mortality rates for children aged 0–14 years diminished significantly for all socioeconomic quintiles. For boys, comparative mortality disparities for all reasons broadened over the period: in 1985–1987, death rates in the most deprived areas were roughly 50 percent higher than in the least underprivileged, and in 1998–2000, the resulting difference was 78 percent. In terms of total death rates, however, the discrepancy between the most and least destitute quintiles contracted: from 42 deaths per 100,000 in 1985–1987 to 32 deaths per 100,000 in 1998–2000. For girls, comparative mortality disparity for all causes between the most and least destitute areas dropped somewhat over the two periods, from 66 percent in 1985–1987 to 61 percent in 1998–2000. Declines were also witnessed in terms of total death rates: in the earlier period, there was a difference of 39 deaths per 100,000 between the most and least destitute areas, and in the later period, this variance was 22 deaths per 100,000.

Between 1985–1987 and 1998–2000, all-cause death rates for persons aged 15–24 years declined for all socioeconomic quintiles. For males, relative mortality disparities for all causes widened over the period: in 1985–1987, mortality rates in the most disadvantaged areas were about 49 percent greater than in the least deprived, and in 1998–2000, the equivalent difference was 90 percent. In terms of total death rates, the difference between the most and least underprivileged quintiles also increased: from 49 deaths per 100,000 in 1985–1987 to 57 deaths per 100,000 in 1998–2000. For females, relative mortality disparity for all causes between the most and least disadvantaged areas amplified slightly over the two periods, from 55 percent in 1985–1987 to 57 percent in 1998–2000. In terms of absolute death rates, however, declines were observed: in the earlier period, there was a difference of 22 deaths per 100,000 between the most and least disadvantaged areas, and in the later period, this difference was 16 deaths per 100,000.

Between 1985–1987 and 1998–2000, all-cause mortality rates for persons aged 25–64 years decreased for all socioeconomic quintiles. For males, relative mortality inequalities for all causes widened over the period: in 1985–1987, death rates in the most disadvantaged areas were approximately 68 percent higher than in the least disadvantaged, and in 1998–2000, the corresponding difference was 75 percent. In terms of absolute death rates, however, the difference between the most and least disadvantaged quintiles narrowed: from 230 deaths per 100,000 in 1985–1987 to 163 deaths per 100,000 in 1998–2000. For females, relative mortality inequality for all causes between the most and least disadvantaged areas remained stable over the two periods at approximately 50 percent. In terms of absolute death rates, however, declines were observed: in 1985–1987, there was a difference of 95 deaths per 100,000 between the most and least disadvantaged areas, and in 1998–2000, this difference was 70 deaths per 100,000.

Between 1985–1987 and 1998–2000, all-cause mortality rates for persons aged 65 years and over decreased for all socioeconomic quintiles. For males, relative mortality inequalities for all causes widened slightly over the period: in 1985–1987, death rates in the most disadvantaged areas were approximately 14 percent higher than in the least disadvantaged, and in 1998–2000, the corresponding difference was 17 percent. In terms of absolute death rates, the difference between the most and least disadvantaged quintiles was similar at each period: 8 deaths per 1,000 in 1985–1987 and 7 deaths per 1,000 in 1998–2000. For females, relative mortality inequality for all causes between the most and least disadvantaged areas remained stable over the two periods at approximately 11 percent. In terms of absolute death rates, things also remained relatively stable: in 1985–1987, there was a difference of 4 deaths per 1,000 between the most and least disadvantaged areas, and in 1998–2000, this difference was 3 deaths per 1,000.

Males and females in all age groups of the most disadvantaged groups had higher all-cause death rates. For males, there was a large gap between the least and most disadvantaged groups for the young adult and adolescent age group, resulting in 57 more deaths per 100,000 for males inhabiting the most disadvantaged areas. For females, the largest gap between the least and most disadvantaged groups lay between children aged 0 to 14 years, resulting in 22 more deaths per 100,000 for females living in the most disadvantaged areas.

Nearly 23,000 deaths could have been avoided for the two-year period between 1998 and 2000 if all statistical local areas in Australia experienced the same death rate as the least socioeconomically disadvantaged area. This was specifically true for individuals aged 25 to 64, whose socioeconomic inequity accounted for a total of 13,749 male deaths and 5,250 female deaths.

Between 1998 and 2000, death rates drastically declined across all IRSD quintiles for males and females aged 25 to 64. For males, mortality inequities increased for all causes, ranging from cancers to cardiovascular disease. When considering absolute death rate causes for males, differences between the most and least disadvantaged areas fell from 230 to 163 deaths. A similar pattern was demonstrated for females.

Social Determinants and Underlying Causes

The social determinants of health as outlined by Frank Baum provide an exemplary framework to understand inequities in mortality as a result of socioeconomic disadvantage. The model allows us to understand how social determinants affect our health and equity, and how societies create and aggravate illness. According to the social model, inequity in mortality results from bad policies, racism, lack of access to education, unemployment, and low income, which prevent people from taking control over their lives and prevent them from carrying the burden of disease throughout their lives. The underlying premise in the social model is to question the value of treating an illness if the treated are not empowered to prevent or hamper the relapse of the disease. For example, what good does it do to treat a person's kidney failure if that person cannot afford the insulin to control his or her diabetes, which caused the kidney failure in the first place? By giving people control over the conditions that cause a disease, the social model advocates for preventing mortality inequity caused as a result of disparities in income, education, and other factors. A variety of social factors affects our mental and behavioral capacities, which adversely affect our health, resulting in death.

It is necessary to highlight the factors that result in the disparities reported in mortality rates for different socioeconomic areas. According to the Department of Aboriginal Affairs, Aboriginal people are the most underprivileged group in Australia as estimated by a variety of socioeconomic indicators that comprise employment, income, education, contact with the justice system, and housing. However, it is important to note that the disease burden of Aboriginal people is not explained by the fact that they are the most underprivileged group alone. According to the Australian Institute of Health and Welfare, Aboriginal people's experience of colonization and subsequent loss of land has had an adverse impact on the economic, cultural, and spiritual basis of their society and could be a probable cause for their poor health.

A review of socioeconomic standards from the 2006 Census reveals the comparative detriment of the Aboriginal populace in New South Wales. For instance, in 2006, Aboriginal people had an unemployment rate which was three times the rate of non-Aboriginal people (19.3 percent versus 5.7 percent). In addition, around three-fourths of the Aboriginal population over the age of 15 years had no education beyond high school, in comparison to just over half (51.3 percent) of their non-Aboriginal counterparts.

Evidence has demonstrated that weekly income rates differ between households that include Aboriginal people as compared to those households that do not. For example, households comprised of Aboriginal people have a weekly income of less than $500 versus those households that do not contain Aboriginal people. Households that contain Aboriginal people are twice as likely to be rented homes, multi-family dwellings, and be comprised of seven or more inhabitants.

Access to internet services is another important factor that separates Aboriginal households from other households. The internet allows one to stay well informed about best educational practices, current events, facilitates the job hunting process, and aids in the development of social interactions through networking. Despite the positive benefits of internet access, half of Aboriginal households had no access to internet services compared to 35.9 percent of other households.

Conclusion

There has been a growing and steady rise in drug use among Australian youth. Because of this, it is imperative that a discussion of mortality trends due to drug dependence be offered. There was a decrease seen in inequality for drug use, which can be attributed to an increasing rate of illicit drugs being utilized in higher socioeconomic areas. This might be reflected in the wide availability of heroin use in Australia among all socioeconomic groups.

At the end of the twentieth century, there were a great range of socioeconomic inequalities in mortality in Australia. These socioeconomic inequalities were area-based. Predicted longevity was highest in areas with socioeconomic advantage and lowest in areas of economic disadvantage. This was true for life expectancy at birth and at the ages of fifteen, twenty-five, and sixty-five. Also, apart from a few exceptions, mortality rates were greatest in areas of economic disadvantage for both males and females of all age groups. In addition to this, mortality rates showed a continuous decline in both advantaged and disadvantaged areas. This tells us that in Australia, as well as in other countries (Adler et al. 1994), mortality inequalities are not subject to wealth disparities; instead, they exist across the whole socioeconomic continuum.

The study also estimated the degree to which socioeconomic disparities in mortality rates added to the entire death burden in the population. This is to say that if it were possible to decrease mortality frequency among the socioeconomic regions to a level corresponding to that of the least underprivileged quintile, what would be the likely savings in mortality? The results presented that the mortality burden associated with area-based socioeconomic inequity was great: during 1998–2000, this was projected to be 1,197 deaths among infants (children under 1 year); 1,491 deaths among 0–14 year-olds; 1,550 deaths among youths and young adults (15–24 years); and 18,999 deaths among working-aged adults (25–64 years). The magnitude of the death burden associated with disparity amid the quintiles of disadvantaged areas in Australia evidently has far-reaching consequences, not only in terms of the unnecessary loss of life, but also in terms of the cost of economically productive members of society and extra expenditures for the health care system and other public sectors more broadly (Woodward & Kawachi 2000).

Mortality inequities related to all death causes showed an increase for males in each age group, even though the total differences in the gaps for each age group have declined. Likewise, other studies done on the subject exhibited similar results between the periods of 1985–1987 to 1995–1997 (Turrell & Mathers 2001). This is consistent with studies conducted in other countries such as Britain, which reported widening relative socioeconomic inequities in mortality (Marang van de Mheen et al. 1998), the United States (Pappas et al. 1993), and Europe (Borrell et al. 1997). Amongst females, however, a rather different trend was recorded—comparative death disparities for all causes dropped between 1985–1987 and 1995–1997 for 0–14 year-olds, and remained steady or marginally increased for females aged 15–24, 25–64, and 65 years and over. In relation to absolute death rates for all causes, differences between the most and least deprived quintiles dropped for males and females in every age group, with one exception—among males aged 15–24, where the death rate difference between the most and least disadvantaged regions grew from 49 deaths per 100,000 people in 1985–1987 to 57 deaths per 100,000 in 1998–2000. The social model applied to understanding the inequity in mortality allowed us to observe the underlying causes of the differences in mortality rates between the privileged and underprivileged groups. Ultimately, the model estimated the extent of influence social factors have on the well-being of individuals and society in general and underscored the need for policy decisions that could alter the mortality inequity in Australia.