Mortality variation across Australia: descriptive data for States and Territories, and statistical divisions

OBJECTIVE: To describe variation in all cause and selected cause-specific mortality rates across Australia. METHODS: Mortality and population data for 1997 were obtained from the Australian Bureau of Statistics. All cause and selected cause-specific mortality rates were calculated and directly standardised to the 1997 Australian population in 5-year age groups. Selected major causes of death included cancer, coronary artery disease, cerebrovascular disease, diabetes, accidents and suicide. Rates are reported by statistical division, and State and Territory. RESULTS: All cause age-standardised mortality was 6.98 per 1000 in 1997 and this varied 2-fold from a low in the statistical division of Pilbara, Western Australia (5.78, 95% confidence interval 5.06-6.56), to a high in Northern Territory-excluding Darwin (11.30, 10.67-11.98). Similar mortality variation (all p<0.0001) exists for cancer (1.01-2.23 per 1000) and coronary artery disease (0.99-2.23 per 1000), the two biggest killers. Larger variation (all p<0.0001) exists for cerebrovascular disease (0.7-11.8 per 10,000), diabetes (0.7-6.9 per 10,000), accidents (1.7-7.2 per 10,000) and suicide (0.6-3.8 per 10,000). Less marked variation was observed when analysed by State and Territory. but Northern Territory consistently has the highest age-standardised mortality rates. CONCLUSIONS: Analysed by statistical division, substantial mortality gradients exist across Australia, suggesting an inequitable distribution of the determinants of health. Further research is required to better understand this heterogeneity.

Youth suicide trends in Australian metropolitan and non-metropolitan areas, 1988-1997

Objective: The objective of this study was to examine trends in suicide among 15-34-year-olds living in Australian metropolitan and non-metropolitan areas between 1988 and 1997. Method: Suicide and population data were obtained from the Australian Bureau of Statistics. We calculated overall and method-specific suicide rates for 15-24 and 25-34-year-old males and females separately, according to area of residence defined as non-metropolitan (less than or equal to 20 000 people) or metropolitan. Results: Between 1988 and 1997 suicide rates in 15-24-year-old non-metropolitan males were consistently 50% higher than metropolitan 15-24-year-olds. In 1995-1997, for example, the rates were: 38.2 versus 25.1 per 100 000 respectively (p < 0.0001). The reverse pattern was seen in 25-34-year-old females with higher rates in metropolitan areas (7.5 per 100 000) compared with non-metropolitan areas (6.1 per 100 000, p = 0.21) in 1995-1997. There were no significant differences according to area of residence in 25-34-year-old males or 15-24-year-old females. Over the years studied we found no clear evidence that suicide rates increased to a greater extent in rural than urban areas. Rates of hanging suicide have approximately doubled in both sexes and age groups in both settings over this time. Despite an approximate halving in firearm suicide, rates remain 3-fold higher among non-metropolitan residents. Conclusion: Non-metropolitan males aged 15-24 years have disproportionately higher rates of suicide than their metropolitan counterparts. Reasons for this require further investigation. Hanging is now the most favoured method of non-metropolitan suicide replacing firearms from 10 years ago. Although legislation may reduce method-specific suicide the potential for method-substitution means that overall rates may not fall. More comprehensive interventions are therefore required.

Variation in mortality rates in Australia: correlation with Indigenous status, remoteness and socio-economic deprivation

Background The aim of this study was to study ecological correlations between age-adjusted all-cause mortality rates in Australian statistical divisions and (1) the proportion of residents that self-identify as Indigenous, (2) remoteness, and (3) socio-economic deprivation. Methods All-cause mortality rates for 57 statistical divisions were calculated and directly standardized to the 1997 Australian population in 5-year age groups using Australian Bureau of Statistics (ABS) data. The proportion of residents who self-identified as Indigenous was obtained from the 1996 Census. Remoteness was measured using ARIA (Accessibility and Remoteness Index for Australia) values. Socioeconomic deprivation was measured using SEIFA (Socio-Economic index for Australia) values from the ABS. Results Age-standardized all-cause mortality varies twofold from 5.7 to 11.3 per 1000 across Australian statistical divisions. Strongest correlation was between Indigenous status and mortality (r = 0.69, p < 0.001). correlation between remoteness and mortality was modest (r = 0.39, p = 0.002) as was correlation between socio-economic deprivation and mortality (r = -0.42, p = 0.001). Excluding the three divisions with the highest mortality, a multiple regression model using the logarithm of the adjusted mortality rate as the dependent variable showed that the partial correlation (and hence proportion of the variance explained) for Indigenous status was 0.03 (9 per cent; p = 0.03), for SEIFA score was -0.17 (3 per cent; p = 0.22); and for remoteness was -0.22 (5 per cent; p = 0.13). Collectively, the three variables studied explain 13 per cent of the variability in mortality. Conclusions Ecological correlation exists between all-cause mortality, Indigenous status, remoteness and disadvantage across Australia. The strongest correlation is with indigenous status, and correlation with all three characteristics is weak when the three statistical divisions with the highest mortality rates are excluded. intervention targeted at these three statistical divisions could reduce much of the variability in mortality in Australia.

Spatial and temporal patterns in Australian wheat yield and their relationship with ENSO

Spatial and temporal variability in wheat production in Australia is dominated by rainfall occurrence. The length of historical production records is inadequate, however, to analyse spatial and temporal patterns conclusively. In this study we used modelling and simulation to identify key spatial patterns in Australian wheat yield, identify groups of years in the historical record in which spatial patterns were similar, and examine association of those wheat yield year groups with indicators of the El Nino Southern Oscillation (ENSO). A simple stress index model was trained on 19 years of Australian Bureau of Statistics shire yield data (1975-93). The model was then used to simulate shire yield from 1901 to 1999 for all wheat-producing shires. Principal components analysis was used to determine the dominating spatial relationships in wheat yield among shires. Six major components of spatial variability were found. Five of these represented near spatially independent zones across the Australian wheatbelt that demonstrated coherent temporal (annual) variability in wheat yield. A second orthogonal component was required to explain the temporal variation in New South Wales. The principal component scores were used to identify high- and low-yielding years in each zone. Year type groupings identified in this way were tested for association with indicators of ENSO. Significant associations were found for all zones in the Australian wheatbelt. Associations were as strong or stronger when ENSO indicators preceding the wheat season (April-May phases of the Southern Oscillation Index) were used rather than indicators based on classification during the wheat season. Although this association suggests an obvious role for seasonal climate forecasting in national wheat crop forecasting, the discriminatory power of the ENSO indicators, although significant, was not strong. By examining the historical years forming the wheat yield analog sets within each zone, it may be possible to identify novel climate system or ocean-atmosphere features that may be causal and, hence, most useful in improving seasonal forecasting schemes.

Muslims and the Australian labour market, 1980-2001

The unemployment of Muslims in Australia was 28 and 25 per cent compared to the national total of around nine per cent in 1986 and 1996 respectively (Australian Bureau of Statistics). This article conceptually analyses the disadvantaged position of the Muslims in the Australian labour market from 1980 to 2001 within a framework of 'structural racism'. It studies the Muslims from three perspectives: first, a comparative study of the qualifications and unemployment of the Muslim labour force in relation to the dominant population. Secondly, it examines the extent of this disadvantaged position in comparison with other ethnic minorities within an historical context. Finally, the basis of structural racism is explored to demonstrate how the Muslims have become systematically victimized. The analysis concludes that Muslims are significantly disadvantaged in Australia on the basis of their ethnicity and religion.

A simple regional-scale model for forecasting sorghum yield across North-Eastern Australia

Sorghum is the main dryland summer crop in NE Australia and a number of agricultural businesses would benefit from an ability to forecast production likelihood at regional scale. In this study we sought to develop a simple agro-climatic modelling approach for predicting shire (statistical local area) sorghum yield. Actual shire yield data, available for the period 1983-1997 from the Australian Bureau of Statistics, were used to train the model. Shire yield was related to a water stress index (SI) that was derived from the agro-climatic model. The model involved a simple fallow and crop water balance that was driven by climate data available at recording stations within each shire. Parameters defining the soil water holding capacity, maximum number of sowings (MXNS) in any year, planting rainfall requirement, and critical period for stress during the crop cycle were optimised as part of the model fitting procedure. Cross-validated correlations (CVR) ranged from 0.5 to 0.9 at shire scale. When aggregated to regional and national scales, 78-84% of the annual variation in sorghum yield was explained. The model was used to examine trends in sorghum productivity and the approach to using it in an operational forecasting system was outlined. (c) 2005 Elsevier B.V. All rights reserved.

Employment restrictions among persons with ICD-10 anxiety disorders: characteristics from a population survey

Disability, employment, and employment restrictions among persons with ICD-10 anxiety disorders were investigated at a population level in comparison to persons without disability or long-term health conditions. Data were provided by the Australian Bureau of Statistics (ABS) collected in a 1998 national survey. Multistage sampling obtained a probability sample of 37,580 individuals in the household component of the survey. Trained lay interviewers using ICD-10 computer-assisted interviews identified household residents with anxiety disorders. Details of employment restrictions are reported and discussed. The four most commonly reported restrictions were: restricted in the type of job (24.0%); need for a support person (23.3%); difficulty changing jobs (18.6%); and restricted in the number of hours (15.4%). The nature and extent of employment restrictions characterizing persons with anxiety disorders indicates a need for strengthened disability and health condition screening at application for Government income support and at gateways to public funded vocational assistance. (c) 2004 Elsevier Inc. All rights reserved.

Correcting for numerator/denominator bias when assessing changing inequalites in occupational class mortality, Australia 1981-2002

Objective Comparisons of the changing patterns of inequalities in occupational mortality provide one way to monitor the achievement of equity goals. However, previous comparisons have not corrected for numerator/denominator bias, which is a consequence of the different ways in which occupational details are recorded on death certificates and on census forms. The objective of this study was to measure the impact of this bias on mortality rates and ratios over time. Methods Using data provided by the Australian Bureau of Statistics, we examined the evidence for bias over the period 1981-2002, and used imputation methods to adjust for this bias. We compared unadjusted with imputed rates of mortality for manual/non-manual workers. Findings Unadjusted data indicate increasing inequality in the age-adjusted rates of mortality for manual/non-manual workers during 1981-2002, Imputed data suggest that there have been modest fluctuations in the ratios of mortality for manual/non-manual workers during this time, but with evidence that inequalities have increased only in recent years and are now at historic highs. Conclusion We found that imputation for missing data leads to changes in estimates of inequalities related to social class in mortality for some years but not for others. Occupational class comparisons should be imputed or otherwise adjusted for missing data on census or death certificates.

Labor force activity among Australians with musculoskeletal disorders comorbid with depression and anxiety disorders

Aim: Musculoskeletal disorders (MSD) are a leading cause of work-related disability. This investigation explored the impact of MSD comorbid with depression and anxiety disorders, on labor force activity. Methods: The Australian Bureau of Statistics provided confidentialized data files collected from a household sample of 37,580 people. MSD, affective, and anxiety disorders were identified and employment restrictions were assessed at four levels of severity. Results: Anxiety and depression of six months duration was present in 12.1% of people with MSD. Comorbidity magnified the negative impacts of single conditions on labor force activity. Most at risk were people with back problems and comorbid depression, people with arthritis or other MSD and comorbid anxiety, males with MSD and comorbid depression, and females with MSD and comorbid anxiety. Conclusions: The results suggest that the occupational rehabilitation needs of people with MSD comorbid with depression or anxiety may currently be underestimated.

The National Mental Health Strategy and Geographical Access to Mental Health Services: Some empirical results

In 1992 the Australian Government adopted the National Mental Health Strategy in an attempt to improve the provision of mental health services. A component was to improve geographical access to hospital-based mental health services. This paper is concerned with determining if this objective has been achieved. Time-series data on patients (at a regional level) with mental illness in the State of Queensland are available for the years from 1968-69 to 2002-03. A change in regional classification by the Australian Bureau of Statistics complicates the analysis by precluding certain empirical tests such as converging utilisation rates by region. To overcome this problem, it was decided to apply concepts of concentration and equality that are commonly employed in industrial economics to the regional data. The empirical results show no evidence of improving regional access following the National Mental Health Strategy: in fact the statistical results show the opposite, i.e. declining regional access.