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Background: Socioeconomic inequalities in mortality are evident in all high-income countries, and ongoing monitoring is recommended using linked census-mortality data. Using such data, we provide the first estimates of education-related inequalities in cause-specific mortality in Australia, suitable for international comparisons.Methods: We used Australian Census (2016) linked to 13 months of Death Registrations (2016-17). We estimated relative rates (RR) and rate differences (RD, per 100 000 person-years), comparing rates in low (no qualifications) and intermediate (secondary school) with high (tertiary) education for individual causes of death (among those aged 25-84 years) and grouped according to preventability (25-74 years), separately by sex and age group, adjusting for age, using negative binomial regression.Results: Among 13.9 M people contributing 14 452 732 person-years, 84 743 deaths occurred. All-cause mortality rates among men and women aged 25-84 years with low education were 2.76 [95% confidence interval (CI): 2.61-2.91] and 2.13 (2.01-2.26) times the rates of those with high education, respectively. We observed inequalities in most causes of death in each age-sex group. Among men aged 25-44 years, relative and absolute inequalities were largest for injuries, e.g. transport accidents [RR = 10.1 (5.4-18.7), RD = 21.2 (14.5-27.9)]). Among those aged 45-64 years, inequalities were greatest for chronic diseases, e.g. lung cancer [men RR = 6.6 (4.9-8.9), RD = 57.7 (49.7-65.8)] and ischaemic heart disease [women RR = 5.8 (3.7-9.1), RD = 20.2 (15.8-24.6)], with similar patterns for people aged 65-84 years. When grouped according to preventability, inequalities were large for causes amenable to behaviour change and medical intervention for all ages and causes amenable to injury prevention among young men.Conclusions: Australian education-related inequalities in mortality are substantial, generally higher than international estimates, and related to preventability. Findings highlight opportunities to reduce them and the potential to improve the health of the population. [ABSTRACT FROM AUTHOR]

Background: National linked mortality and census data have not previously been available for Australia. We estimated education-based mortality inequalities from linked census and mortality data that are suitable for international comparisons.Methods: We used the Australian Bureau of Statistics Death Registrations to Census file, with data on deaths (2011-2012) linked probabilistically to census data (linkage rate 81%). To assess validity, we compared mortality rates by age group (25-44, 45-64, 65-84 years), sex and area-inequality measures to those based on complete death registration data. We used negative binomial regression to quantify inequalities in all-cause mortality in relation to five levels of education ['Bachelor degree or higher' (highest) to 'no Year 12 and no post-secondary qualification' (lowest)], separately by sex and age group, adjusting for single year of age and correcting for linkage bias and missing education data.Results: Mortality rates and area-based inequality estimates were comparable to published national estimates. Men aged 25-84 years with the lowest education had age-adjusted mortality rates 2.20 [95% confidence interval (CI): 2.08‒2.33] times those of men with the highest education. Among women, the rate ratio was 1.64 (1.55‒1.74). Rate ratios were 3.87 (3.38‒4.44) in men and 2.57 (2.15‒3.07) in women aged 25-44 years, decreasing to 1.68 (1.60‒1.76) in men and 1.44 (1.36‒1.53) in women aged 65-84 years. Absolute education inequalities increased with age. One in three to four deaths (31%) was associated with less than Bachelor level education.Conclusions: These linked national data enabled valid estimates of education inequality in mortality suitable for international comparisons. The magnitude of relative inequality is substantial and similar to that reported for other high-income countries. [ABSTRACT FROM AUTHOR]

Summary: Motivated by the Australian National University poll, we consider a situation where survey data have been collected from respondents for several categorical variables and a primary geographic classification, e.g. postcode. Here, a common and important problem is to obtain estimates for a second target geography that overlaps with the primary geography but has not been collected from the respondents. We examine this problem when areal level census information is available for both geographic classifications. Such a situation is challenging from a small area estimation perspective for several reasons: there is a misalignment between the census and survey information as well as the geographical classifications; the geographic areas are potentially small and so prediction can be difficult because of the sparse or spatially missing data issue; and there is the possibility of non‐stationary spatial dependence. To address these problems we develop a Bayesian model using latent processes, underpinned by a non‐stationary spatial basis that combines Moran's I and multiresolution basis functions with a small but representative set of knots. The study results based on simulated data demonstrate that the model can be highly effective and gives more accurate estimates for areas defined by the target geography than several existing models. The model also performs well for the Australian National University poll data to predict on a second geographic classification: statistical area level 2. [ABSTRACT FROM AUTHOR]

To understand the population dynamics of Indigenous Australians, changes in identification (from Indigenous to non-Indigenous or vice versa) must be studied. Comparing these changes reported at two successive censuses not only allows the transitions to be counted but also their determinants to be examined. Using individual linked data from the 2006 and 2011 censuses, the authors demonstrate the impact of identification changes on the observed growth of the Indigenous population. These changes concern children, but they often coincide with the change in status of one of the parents. [ABSTRACT FROM AUTHOR]

Indigenous Australians make up a small segment of the country’s population, but one with a distinct demographic profile. Academics and the central statistical agency of Australia regularly create Indigenous-specific population estimates. Changes in the identification (from Indigenous to non-Indigenous or vice versa) contribute to that population’s dynamic. Until now, however, there has been no individual-level Australian population data that would allow researchers to analyse the characteristics of those whose identification changes. This paper explores a new data source containing the largest longitudinal sample of Indigenous Australians, the Australian Census Longitudinal Dataset. We show, quantitatively, that Indigenous identification is not necessarily a fixed construct. New identification appears to account for a considerable proportion of the growth in the Indigenous population between 2006 and 2011. The newly identified group also appear to possess different characteristics to those who consistently identified as Indigenous across the two time points. They were more likely to live in urban areas (and unlikely to live in remote communities) and had higher socioeconomic status, a finding that has implications for policy design and implementation. [ABSTRACT FROM AUTHOR]

There has been an increasing interest in the level and change in income inequality across much of the developed world. In Australia, this research has extended our knowledge by using new measures (for example wealth), longer time periods, and income inequality dynamics. One area for which we have relatively little recent evidence is on the spatial distribution of income inequality, especially at small areas of geography. Specifically, we look at the level of income inequality for the eight Australian capital cities in 2006 and 2011 (using relevant Census and survey data), as well as inequality between and within suburbs within those capital cities. A number of interesting findings emerge from the analysis. The most obvious finding is that there are differences across cities in the extent to which income is unevenly distributed. While this has been demonstrated in previous research, we were able to use new data and new techniques to show that the type of income which one uses has a small but noticeable effect on the spatial distribution of inequality. Differences in household sizes and the tax system change how income inequality is spatially distributed. [ABSTRACT FROM AUTHOR]

In recent years, social scientists have turned increasing scholarly focus to the ‘post-colonial city’, as it relates to the lived experiences and socio-cultural worlds of urban-dwelling Indigenous peoples. In Australia, this literature is concerned primarily with issues of identity, power and representation in big cities. More conventional geographic analyses regarding socio-spatial, economic and demographic aspects of urban Indigenous experience have been mostly absent from this discourse. In this paper, we begin to address this gap within the literature by identifying notable socio-spatial, economic, and demographic features of urban Indigenous experience in regional Australian cities. We draw on census and administrative data to empirically examine Indigenous residency, presence, and uneven housing market access in regional urban centres. The analysis builds a national comparative picture regarding population change, tenure type, crowding and housing affordability in these localities. At the same time, it ‘drills down’ to explore some of the drivers and implications of change against these indicators in one case study locality: Geraldton Western Australian. This case study analysis, based on recent fieldwork, grounds the broad identified trends in a localised narrative, illuminating some of general and specific socio-economic and socio-spatial dynamics that shape urban life for Indigenous peoples in regional Australia and the implications of these dynamics for broader questions of co-existence between Indigenous and non-Indigenous Australians. [ABSTRACT FROM AUTHOR]

The intercensal period (2006-2011) was a time of significant policy and population change in Indigenous affairs. The aim of this paper is to document the changing distribution of Aboriginal and Torres Strait Islander population and housing geographies over that period. We use the Indigenous Region structure developed by the Australian Bureau of Statistics to show that Indigenous Australians grew at a rate that significantly outstrips the non-Indigenous population with an increasing concentration of the Indigenous population on the urban eastern seaboard and particularly among older people. We present results that show that for certain measures, the housing situation of the Indigenous population in 2011 had improved relative to the Indigenous population in 2006. A smaller proportion of Indigenous households were estimated to live in an overcrowded dwelling compared with Indigenous households in 2006. There were also significant increases in the per cent of Indigenous households that owned or were purchasing their own home. Other results might be seen as less positive with community housing (a tenure type identified as having benefits in both qualitative and quantitative analysis) declining in importance. In net terms though, Indigenous households continue to experience a high degree of housing need. Compared with other households, they were 3.7 times as likely to live in an overcrowded dwelling. [ABSTRACT FROM AUTHOR]

Practical reconciliation’ and more recently ‘closing the gap’ have been put forward as frameworks on which to base and evaluate policies to address Indigenous disadvantage. This paper analyses national-level census-based data to examine trends in Indigenous wellbeing since 1971. There has been steady improvement in most socioeconomic outcomes in the last 35 years; a finding at odds with the current discourse of failure. Evidence of convergence between Indigenous and non-Indigenous outcomes, however, is not consistent. For some outcomes, relatively rapid convergence is predicted (within 25 years), but for the majority of outcomes, convergence is unlikely to occur within a generation, if at all. [ABSTRACT FROM AUTHOR]

This paper looks at the factors associated with the decision by school students in Australia to work part-time. I find substantial variation in the probability of working across the eight Australian states and territories, as well as by remoteness. Those who live in households with low income are less likely to work. A person's ancestry is also associated with variation in the probability of working, as is the type of school they attend. This paper also looks at unemployment amongst school students. In addition to Indigenous Australians, one group of students found to be substantially more likely to be unemployed are those who live in a household where no one else is employed. Other authors have found that those who spend long hours at work have been found to achieve poorly across a number of outcomes. The biggest differences in the probability of working long hours are associated with the industry in which the student works. [ABSTRACT FROM AUTHOR]