The gaps in healthy life expectancy (HLE) between Indigenous and non-Indigenous Australians are significant. Detailed and accurate information is required to develop strategies that will close these health disparities. This paper aims to quantify and compare the causes and their relative contributions to the life expectancy (LE) gaps between the Indigenous and non-Indigenous population in the Northern Territory (NT), Australia.The age-cause decomposition was used to analyse the differences in HLE and unhealthy life expectancy (ULE), where LE = HLE + ULE. The data was sourced from the burden of disease and injury study in the NT between 2014 and 2018.In 2014-2018, the HLE at birth in the NT Indigenous population was estimated at 43.3 years in males and 41.4 years in females, 26.5 and 33.5 years shorter than the non-Indigenous population. This gap approximately doubled the LE gap (14.0 years in males, 16.6 years in females) at birth. In contrast to LE and HLE, ULE at birth was longer in the Indigenous than non-Indigenous population. The leading causes of the ULE gap at birth were endocrine conditions (explaining 2.9-4.4 years, 23-26%), followed by mental conditions in males and musculoskeletal conditions in females (1.92 and 1.94 years, 15% and 12% respectively), markedly different from the causes of the LE gap (cardiovascular disease, cancers and unintentional injury).The ULE estimates offer valuable insights into the patterns of morbidity particularly useful in terms of primary and secondary prevention.

The introduction of activity-based funding (ABF) means that Australian Refined Diagnosis Related Groups and their relative costs will become the basis for reimbursing public hospitals for admitted patient services. This study sought to investigate the variation in admitted patient costs for Indigenous people and people from remote areas that cannot be explained by variation in the clinical mix of cases, and to interpret this variation within an ABF framework. The study used a dataset of discharges from public hospitals of Northern Territory residents between July 2007 and June 2009. Multivariate regression analysis was used to estimate the variation in average costs, using the logarithm of patient cost as the dependent variable and Major Diagnostic Categories (MDCs), hospitals and population subgroups (Indigenous v. non-Indigenous; urban v. remote) as independent variables. Although much of the additional cost of Indigenous and remote patients was found to be due to differences in severity and complexity between MDCs, there were extra costs for remote Indigenous patients that were not captured by the classification system. Hospitals servicing larger than average proportions of these patients could be systematically underfunded within an ABF framework unless a price adjustment is applied.

Net survival is the most common measure of cancer prognosis and has been used to study differentials in cancer survival between ethnic or racial population subgroups. However, net survival ignores competing risks of deaths and so provides incomplete prognostic information for cancer patients, and when comparing survival between populations with different all-cause mortality. Another prognosis measure, "crude probability of death", which takes competing risk of death into account, overcomes this limitation. Similar to net survival, it can be calculated using either life tables (using Cronin-Feuer method) or cause of death data (using Fine-Gray method). The aim of this study is two-fold: (1) to compare the multivariable results produced by different survival analysis methods; and (2) to compare the Cronin-Feuer with the Fine-Gray methods, in estimating the cancer and non-cancer death probability of both Indigenous and non-Indigenous cancer patients and the Indigenous cancer disparities. Cancer survival was investigated for 9,595 people (18.5% Indigenous) diagnosed with cancer in the Northern Territory of Australia between 1991 and 2009. The Cox proportional hazard model along with Poisson and Fine-Gray regression were used in the multivariable analysis. The crude probabilities of cancer and non-cancer methods were estimated in two ways: first, using cause of death data with the Fine-Gray method, and second, using life tables with the Cronin-Feuer method. Multivariable regression using the relative survival, cause-specific survival, and competing risk analysis produced similar results. In the presence of competing risks, the Cronin-Feuer method produced similar results to Fine-Gray in the estimation of cancer death probability (higher Indigenous cancer death probabilities for all cancers) and non-cancer death probabilities (higher Indigenous non-cancer death probabilities for all cancers except lung cancer and head and neck cancers). Cronin-Feuer estimated much lower non-cancer death probabilities than Fine-Gray for non-Indigenous patients with head and neck cancers and lung cancers (both smoking-related cancers). Despite the limitations of the Cronin-Feuer method, it is a reasonable alternative to the Fine-Gray method for assessing the Indigenous survival differential in the presence of competing risks when valid and reliable subgroup-specific life tables are available and cause of death data are unavailable or unreliable.

Health inequities persist among First Nations people living in developed countries. Surgical care is pivotal in addressing a significant portion of the global disease burden. Evidence regarding surgical outcomes among First Nations people in Australia is limited. The perioperative mortality rate (POMR) indicates timely access to safe surgery and predicts long-term survival after major surgery. This systematic review will examine POMR among First Nations and non-First Nations peoples in Australia.A systematic search strategy using MEDLINE, Embase, Emcare, Global Health, and Scopus will identify studies that include First Nations people and non-First Nations people who underwent a surgical intervention under anaesthesia in Australia. The primary focus will be on documenting perioperative mortality outcomes. Title and abstract screening and full-text review will be conducted by independent reviewers, followed by data extraction and bias assessment using the ROBINS-E tool. Meta-analysis will be considered if there is sufficient homogeneity between studies. The quality of cumulative evidence will be evaluated following the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) criteria.This protocol describes the comprehensive methodology for the proposed systematic review. Evaluating disparities in perioperative mortality rates between First Nations and non-First Nations people remains essential in shaping the discourse surrounding health equity, particularly in addressing the surgical burden of disease.PROSPERO CRD42021258970.

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Understanding health inequity is necessary for addressing the disparities in health outcomes in many populations, including the health gap between Indigenous and non-Indigenous Australians. This report investigates the links between Indigenous health outcomes and socioeconomic disadvantage in the Northern Territory of Australia (NT). Data sources include deaths, public hospital admissions between 2005 and 2007, and Socio-Economic Indexes for Areas from the 2006 Census. Age-sex standardisation, standardised rate ratio, concentration index and Poisson regression model are used for statistical analysis. There was a strong inverse association between socioeconomic status (SES) and both mortality and morbidity rates. Mortality and morbidity rates in the low SES group were approximately twice those in the medium SES group, which were, in turn, 50% higher than those in the high SES group. The gradient was present for most disease categories for both deaths and hospital admissions. Residents in remote and very remote areas experienced higher mortality and hospital morbidity than non-remote areas. Approximately 25-30% of the NT Indigenous health disparity may be explained by socioeconomic disadvantage. Socioeconomic disadvantage is a shared common denominator for the main causes of deaths and principal diagnoses of hospitalisations for the NT population. Closing the gap in health outcomes between Indigenous and non-Indigenous populations will require improving the socioeconomic conditions of Indigenous Australians.

The health inequalities experienced by Aboriginal and Torres Strait Islander Australians are well documented but there are few empirical data outlining the burden, consequences, experience and expression of depressive illness. This paper seeks to address the lack of accessible, culturally specific measures of psychosocial stress, depression or quality of life developed for, and validated within, this population. Building on an extensive qualitative phase of research, a psychosocial questionnaire comprising novel and adapted scales was developed and piloted with 189 Aboriginal men across urban and remote settings in central Australia. With a view to refining this tool for future use, its underlying structure was assessed using exploratory factor analysis, and the predictive ability of the emergent psychosocial constructs assessed with respect to depressive symptomatology. The latent structure of the psychosocial questionnaire was conceptually aligned with the components of the a priori model on which the questionnaire was based. Regression modelling indicated that depressive symptoms were driven by a sense of injury and chronic stress and had a non-linear association with socioeconomic position. This represents the first community-based survey of psychosocial stress and depression in Aboriginal men. It provides both knowledge of, and an appropriate process for, the further development of psychometric tools, including quality of life, in this population. Further research with larger and more diverse samples of Aboriginal people is required to refine the measurement of key constructs such as chronic stress, socioeconomic position, social support and connectedness. The further refinement, validation against criterion-based methods and incorporation within primary care services is essential.

The estimated life expectancy at birth for Indigenous Australians is 10-11 years less than the general Australian population. The mean family income for Indigenous people is also significantly lower than for non-Indigenous people. In this paper we examine poverty or socioeconomic disadvantage as an explanation for the Indigenous health gap in hospital morbidity in Australia. We utilised a cross-sectional and ecological design using the Northern Territory public hospitalisation data from 1 July 2004 to 30 June 2008 and socio-economic indexes for areas (SEIFA) from the 2006 census. Multilevel logistic regression models were used to estimate odds ratios and confidence intervals. Both total and potentially avoidable hospitalisations were investigated. This study indicated that lifting SEIFA scores for family income and education/occupation by two quintile categories for low socio-economic Indigenous groups was sufficient to overcome the excess hospital utilisation among the Indigenous population compared with the non-Indigenous population. The results support a reframing of the Indigenous health gap as being a consequence of poverty and not simplistically of ethnicity. Socio-economic disadvantage is a likely explanation for a substantial proportion of the hospital morbidity gap between Indigenous and non-Indigenous populations. Efforts to improve Indigenous health outcomes should recognise poverty as an underlying determinant of the health gap.