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.

Monitoring growth in rapidly urbanizing areas using remotely sensed data

Urbanization and the ability to manage for a sustainable future present numerous challenges for geographers and planners in metropolitan regions. Remotely sensed data are inherently suited to provide information on urban land cover characteristics, and their change over time, at various spatial and temporal scales. Data models for establishing the range of urban land cover types and their biophysical composition (vegetation, soil, and impervious surfaces) are integrated to provide a hierarchical approach to classifying land cover within urban environments. These data also provide an essential component for current simulation models of urban growth patterns, as both calibration and validation data. The first stages of the approach have been applied to examine urban growth between 1988 and 1995 for a rapidly developing area in southeast Queensland, Australia. Landsat Thematic Mapper image data provided accurate (83% adjusted overall accuracy) classification of broad land cover types and their change over time. The combination of commonly available remotely sensed data, image processing methods, and emerging urban growth models highlights an important application for current and next generation moderate spatial resolution image data in studies of urban environments.

Integrating attribute and space characteristics in choropleth display and spatial data mining

This paper develops an interactive approach for exploratory spatial data analysis. Measures of attribute similarity and spatial proximity are combined in a clustering model to support the identification of patterns in spatial information. Relationships between the developed clustering approach, spatial data mining and choropleth display are discussed. Analysis of property crime rates in Brisbane, Australia is presented. A surprising finding in this research is that there are substantial inconsistencies in standard choropleth display options found in two widely used commercial geographical information systems, both in terms of definition and performance. The comparative results demonstrate the usefulness and appeal of the developed approach in a geographical information system environment for exploratory spatial data analysis.

Assessing perceived need for mental health care in a community survey: development of the Perceived Need for Care Questionnaire (PNCQ)

Background: The Perceived Need for Care Questionnaire (PNCQ) was designed for the Australian National Survey of Mental Health and Wellbeing. The PNCQ complemented collection of data on diagnosis and disability with the survey participants' perceptions of their needs for mental health care and the meeting of those needs. The four-stage design of the PNCQ mimics a conversational exploration of the topic of perceived needs. Five categories of perceived need are each assigned to one of four levels of perceived need (no need, unmet need, partially met need and met need). For unmet need and partially met need, information on barriers to care is collected, Methods: Inter-rater reliabilities of perceived needs assessed by the PNCQ were examined in a study of 145 anxiety clinic attenders. Construct validity of these items was tested, using a multi-trait multi-method approach and hypotheses regarding extreme groups, in a study with a sample of 51 general practice and community psychiatric service patients. Results: The instrument is brief to administer and has proved feasible for use in various settings. Inter-rater reliabilities for major categories, measured by the kappa statistic, exceeded 0.60 in most cases; for the summary category of all perceived needs, inter-rater reliability was 0.62. The multi-trait multi-method approach lent support to the construct validity of the instrument, as did findings in extreme groups. Conclusions: The PNCQ shows acceptable feasibility, reliability and validity, adding to the range of assessment tools available for epidemiological and health services research.

Estimating HIV incidence rates from age prevalence data in epidemic situations

We present a method of estimating HIV incidence rates in epidemic situations from data on age-specific prevalence and changes in the overall prevalence over time. The method is applied to women attending antenatal clinics in Hlabisa, a rural district of KwaZulu/Natal, South Africa, where transmission of HIV is overwhelmingly through heterosexual contact. A model which gives age-specific prevalence rates in the presence of a progressing epidemic is fitted to prevalence data for 1998 using maximum likelihood methods and used to derive the age-specific incidence. Error estimates are obtained using a Monte Carlo procedure. Although the method is quite general some simplifying assumptions are made concerning the form of the risk function and sensitivity analyses are performed to explore the importance of these assumptions. The analysis shows that in 1998 the annual incidence of infection per susceptible woman increased from 5.4 per cent (3.3-8.5 per cent; here and elsewhere ranges give 95 per cent confidence limits) at age 15 years to 24.5 per cent (20.6-29.1 per cent) at age 22 years and declined to 1.3 per cent (0.5-2.9 per cent) at age 50 years; standardized to a uniform age distribution, the overall incidence per susceptible woman aged 15 to 59 was 11.4 per cent (10.0-13.1 per cent); per women in the population it was 8.4 per cent (7.3-9.5 per cent). Standardized to the age distribution of the female population the average incidence per woman was 9.6 per cent (8.4-11.0 per cent); standardized to the age distribution of women attending antenatal clinics, it was 11.3 per cent (9.8-13.3 per cent). The estimated incidence depends on the values used for the epidemic growth rate and the AIDS related mortality. To ensure that, for this population, errors in these two parameters change the age specific estimates of the annual incidence by less than the standard deviation of the estimates of the age specific incidence, the AIDS related mortality should be known to within +/-50 per cent and the epidemic growth rate to within +/-25 per cent, both of which conditions are met. In the absence of cohort studies to measure the incidence of HIV infection directly, useful estimates of the age-specific incidence can be obtained from cross-sectional, age-specific prevalence data and repeat cross-sectional data on the overall prevalence of HIV infection. Several assumptions were made because of the lack of data but sensitivity analyses show that they are unlikely to affect the overall estimates significantly. These estimates are important in assessing the magnitude of the public health problem, for designing vaccine trials and for evaluating the impact of interventions. Copyright (C) 2001 John Wiley & Sons, Ltd.

Modelling life history strategies with capture-recapture data: Evolutionary demography of the water skink Eulamprus tympanum

Matrix population models, elasticity analysis and loop analysis can potentially provide powerful techniques for the analysis of life histories. Data from a capture-recapture study on a population of southern highland water skinks (Eulamprus tympanum) were used to construct a matrix population model. Errors in elasticities were calculated by using the parametric bootstrap technique. Elasticity and loop analyses were then conducted to identify the life history stages most important to fitness. The same techniques were used to investigate the relative importance of fast versus slow growth, and rapid versus delayed reproduction. Mature water skinks were long-lived, but there was high immature mortality. The most sensitive life history stage was the subadult stage. It is suggested that life history evolution in E. tympanum may be strongly affected by predation, particularly by birds. Because our population declined over the study, slow growth and delayed reproduction were the optimal life history strategies over this period. Although the techniques of evolutionary demography provide a powerful approach for the analysis of life histories, there are formidable logistical obstacles in gathering enough high-quality data for robust estimates of the critical parameters.

Disaggregation of polygons of surficial geology and soil maps using spatial modelling and legacy data

Examples from the Murray-Darling basin in Australia are used to illustrate different methods of disaggregation of reconnaissance-scale maps. One approach for disaggregation revolves around the de-convolution of the soil-landscape paradigm elaborated during a soil survey. The descriptions of soil ma units and block diagrams in a soil survey report detail soil-landscape relationships or soil toposequences that can be used to disaggregate map units into component landscape elements. Toposequences can be visualised on a computer by combining soil maps with digital elevation data. Expert knowledge or statistics can be used to implement the disaggregation. Use of a restructuring element and k-means clustering are illustrated. Another approach to disaggregation uses training areas to develop rules to extrapolate detailed mapping into other, larger areas where detailed mapping is unavailable. A two-level decision tree example is presented. At one level, the decision tree method is used to capture mapping rules from the training area; at another level, it is used to define the domain over which those rules can be extrapolated. (C) 2001 Elsevier Science B.V. All rights reserved.

Post-traumatic stress disorder: Findings from the Australian National Survey of Mental Health and Well-being

Background. We report on the epidemiology of post-traumatic stress disorder (PTSD) in the Australian community, including information on lifetime exposure to trauma, 12-month prevalence of PTSD, sociodemographic correlates and co-morbidity. Methods. Data were obtained from a stratified sample of 10641 participants as part of the Australian National Survey of Mental Health and Well-being. A modified version of the Composite International Diagnostic Interview was used to determine the presence of PTSD, as well as other DSM-IV anxiety, affective and substance use disorders. Results. The estimated 12-month prevalence of PTSD was 1.33%, which is considerably lower than that found in comparable North American studies. Although females were at greater risk than males within the subsample of those who had experienced trauma, the large gender differences noted in some recent epidemiological research were not replicated. Prevalence was elevated among the never married and previously married respondents, and was lower among those aged over 55. For both men and women, rape and sexual molestation were the traumatic events most likely to be associated with PTSD. A high level of Axis I co-morbidity was found among those persons with PTSD Conclusions. PTSD is a highly prevalent disorder in the Australian community and is routinely associated with high rates of anxiety, depression and substance disorders. Future research is needed to investigate rates among other populations outside the North American continent.

Baseline laboratory bioassay data for spinosad against populations of Australian sheep blowfly, Lucilia cuprina (Wiedemann) (Diptera : Calliphoridae)

Spinosad was an effective larvicide against the Australian sheep blowfly, Lucilia cuprina. A survey of 41 field populations indicated no cross-resistance to spinosad from existing organophosphate resistance. The data presented serve as baseline data for future resistance surveys.

Are we too busy to volunteer? The relationship between time and volunteering using the 1997 ABS Time Use Data

Time availability is a key concept in relation to volunteering, leading to organisations and governments targeting those outside paid work as a potential source of volunteers. It may be that factors such as a growth in female participation in the labour market and an increase in work hours will lead to more people saying they are simply too busy to volunteer This paper discusses how social and economic change, such as changing work patterns, are impacting on time availability. Using the 1997 ABS Time Use data, it identifies a predictive model of spare time by looking at demographic, life stage and employment related variables. Results confirm that those outside paid work, particularly the young, males and those without partners or children, are the groups most likely to have time to spare. These groups do not currently report high rates of volunteering. The paper concludes by questioning the premise that people will volunteer simply because they have time to spare. This is just one component of a range of motivations and factors that influence the decision to volunteer.

Spatial data mining for enhanced soil map modelling

The principle of using induction rules based on spatial environmental data to model a soil map has previously been demonstrated Whilst the general pattern of classes of large spatial extent and those with close association with geology were delineated small classes and the detailed spatial pattern of the map were less well rendered Here we examine several strategies to improve the quality of the soil map models generated by rule induction Terrain attributes that are better suited to landscape description at a resolution of 250 m are introduced as predictors of soil type A map sampling strategy is developed Classification error is reduced by using boosting rather than cross validation to improve the model Further the benefit of incorporating the local spatial context for each environmental variable into the rule induction is examined The best model was achieved by sampling in proportion to the spatial extent of the mapped classes boosting the decision trees and using spatial contextual information extracted from the environmental variables.

Epidemiological modelling (including economic modelling) and its role in preventive drug therapy

In contrast to curative therapies, preventive therapies are administered to largely healthy individuals over long periods. The risk-benefit and cost-benefit ratios are more likely to be unfavourable, making treatment decisions difficult. Drug trials provide insufficient information for treatment decisions, as they are conducted on highly selected populations over short durations, estimate only relative benefits of treatment and offer little information on risks and costs. Epidemiological modelling is a method of combining evidence from observational epidemiology and clinical trials to assist in clinical and health policy decision-making. It can estimate absolute benefits, risks and costs of long-term preventive strategies, and thus allow their precise targeting to individuals for whom they are safest and most cost-effective. Epidemiological modelling also allows explicit information about risks and benefits of therapy to be presented to patients, facilitating informed decision-making.

The incidence of schizophrenia: A systematic review

There has been a debate on whether or not the incidence of schizophrenia varies across time and place. In order to optimise the evidence upon which this debate is based, we have undertaken a systematicsystematic review of the literature. In this paper we provide an overview of the methods of the review and a preliminary analysis of the studies identified to date. Electronic databases (Medline, Psychlnfo, Embase, LILAC) were systematically searched for articles published between January 1965 and December 2001. The search terms were: (schizo* OR psycho*)AND (incidence OR prevalence). References were also identified from review articles, reference list and by writing to authors. To date we have identified 137 papers drawn from 33 nations. 37 papers in language other than English await translation. The currently included papers have generated 1413 different items of rate information data. In order to analyze these data we have undertaken several sequential filters in order to identify (a) non-overlapping data, (b) birth cohort study versus noncohort studies, (c) overall and sex-specific rates, (d) diagnostic criteria, (e) age ranges, (f) epoch of study, and (g) data on migrant or other special interest groups. In addition, we will examine the impact of urbanicity of site, age and/or sex standardization, and quality score on the incidence rates. The various discrete incidence rates will be presented graphically and the impact of various filters on these rates will be inspected using meta-analytic techniques. The use of meta-analysis may help elucidate the epidemiological landscape with respect to the incidence of schizophrenia and aid in the generation of new hypothesis. Acknowledgements: The Stanley Medical Research Institute supported project

Cytokine-related genes identified from the RIKEN full-length mouse cDNA data set

To identify novel cytokine-related genes, we searched the set of 60,770 annotated RIKEN mouse cDNA clones (FANTOM2 clones), using keywords such as cytokine itself or cytokine names (such as interferon, interleukin, epidermal growth factor, fibroblast growth factor, and transforming growth factor). This search produced 108 known cytokines and cytokine-related products such as cytokine receptors, cytokine-associated genes, or their products (enhancers, accessory proteins, cytokine-induced genes). We found 15 clusters of FANTOM2 clones that are candidates for novel cytokine-related genes. These encoded products with strong sequence similarity to guanylate-binding protein (GBP-5), interleukin-1 receptor-associated kinase 2 (IRAK-2), interleukin 20 receptor alpha isoform 3, a member of the interferon-inducible proteins of the Ifi 200 cluster, four members of the membrane-associated family 1-8 of interferon-inducible proteins, one p27-like protein, and a hypothetical protein containing a Toll/Interleukin receptor domain. All four clones representing novel candidates of gene products from the family contain a novel highly conserved cross-species domain. Clones similar to growth factor-related products included transforming growth factor beta-inducible early growth response protein 2 (TIEG-2), TGFbeta-induced factor 2, integrin beta-like 1, latent TGF-binding protein 4S, and FGF receptor 4B. We performed a detailed sequence analysis of the candidate novel genes to elucidate their likely functional properties.

Identification of novel "pathologs" (human disease-related gene candidates) from the RIKEN full-length mouse cDNA data set

The majority of common diseases such as cancer, allergy, diabetes, or heart disease are characterized by complex genetic traits, in which genetic and environmental components contribute to disease susceptibility. Our knowledge of the genetic factors underlying most of such diseases is limited. A major goal in the post-genomic era is to identify and characterize disease susceptibility genes and to use this knowledge for disease treatment and prevention. More than 500 genes are conserved across the invertebrate and vertebrate genomes. Because of gene conservation, various organisms including yeast, fruitfly, zebrafish, rat, and mouse have been used as genetic models.