Stephen Begg

The burden of disease and injury in Australia

An overview of the results of the Australian Burden of Disease (ABD) study is presented. The ABD study was the first to use methodology developed for the Global Burden of Disease study to measure the burden of disease and injury in a developed country. In 1996, mental disorders were the main causes of disability burden, responsible for nearly 30% of total years of life lost to disability (YLD), with depression accounting for 8% of the total YLD. Ischaemic heart disease and stroke were the main contributors to the disease burden disability-adjusted life years (DALYs), together causing nearly 18% of the total disease burden. Risk factors such as smoking, alcohol consumption, physical inactivity, hypertension, high blood cholesterol, obesity and inadequate fruit and vegetable consumption were responsible for much of the overall disease burden in Australia. The lessons learnt from the ABD study are discussed, together with methodological issues that require further attention.

Burden of disease and injury in Aboriginal and Torres Strait Islander Peoples: the Indigenous health gap

BACKGROUND Disparities in health status between Aboriginal and Torres Strait Islander peoples and the total Australian population have been documented in a fragmentary manner using disparate health outcome measures. METHODS We applied the burden of disease approach to national population health datasets and Indigenous-specific epidemiological studies. The main outcome measure is the Indigenous health gap, i.e. the difference between current rates of Disability-Adjusted Life Years (DALYs) by age, sex and cause for Indigenous Australians and DALY rates if the same level of mortality and disability as in the total Australian population had applied. RESULTS The Indigenous health gap accounted for 59% of the total burden of disease for Indigenous Australians in 2003 indicating a very large potential for health gain. Non-communicable diseases explained 70% of the health gap. Tobacco (17%), high body mass (16%), physical inactivity (12%), high blood cholesterol (7%) and alcohol (4%) were the main risk factors contributing to the health gap. While the 26% of Indigenous Australians residing in remote areas experienced a disproportionate amount of the health gap (40%) compared with non-remote areas, the majority of the health gap affects residents of non-remote areas. DISCUSSION Comprehensive information on the burden of disease for Indigenous Australians is essential for informed health priority setting. This assessment has identified large health gaps which translate into opportunities for large health gains. It provides the empirical base to determine a more equitable and efficient funding of Indigenous health in Australia. The methods are replicable and would benefit priority setting in other countries with great disparities in health experienced by Indigenous peoples or other disadvantaged population groups.

Sensitivity and Uncertainty Analyses for Burden of Disease and Risk Factor Estimates

This volume is a single up-to-date source on the entire global epidemiology of diseases, injuries and risk factors with a comprehensive statement of methods and a complete presentation of results. It includes refined methods to assess data, ensure epidemiological consistency, and summarize the disease burden. Global Burden of Disease and Risk Factors examines the comparative importance of diseases, injuries, and risk factors; it incorporates a range of new data sources to develop consistent estimates of incidence, prevalence, severity and duration, and mortality for 136 major diseases and injuries. Drawing from more than 8,500 data sources that include epidemiological studies, disease registers, and notifications systems, this book incorporates information from more than 10,000 datasets relating to population health and mortality, representing one of the largest syntheses of global information on population health to date.Epidemiological studies report confidence or uncertainty intervals around their estimates. Estimates of the burden of diseases and risk factors are subject to a broader range of uncertainty because of the combination of multiple data sources and value choices. Sensitivity analysis can be used to examine the effects of social values that have been incorporated into the design of the disability–adjusted life year (DALY). Age weight, where a year of healthy life lived at one age is valued differently from at another age, is the most controversial value built into the DALY. The discount rate, which addresses the difference in value of current versus future health benefits, also has been criticized. The distribution of the global disease burden and rankings of various conditions are largely insensitive to alternate assumptions about the discount rate and age weighting. The major effects of discounting and age weighting are to enhance the importance of neuropsychiatric conditions and sexually transmitted infections. The Global Burden of Disease study also has been criticized for estimating mortality and disease burden for regions using incomplete and uncertain data. Including uncertain results, with uncertainty quantified to the extent possible, is preferable, however, to leaving blank cells in tables intended to provide policy makers with an overall assessment of burden of disease. No estimate is generally interpreted as no problem. Greater investment in getting the descriptive epidemiology of diseases and injuries correct in poor countries will do vastly more to reduce uncertainty in disease burden assessments than a philosophical debate about the appropriateness of social valueDetailed descriptions of the level and distribution of diseases and injuries and their causes are important inputs into strategies for improving population health. A substantial body of work has focused on quantifying causes of mortality and, more recently, the burden of disease (Murray and Lopez 1997; Preston, 1976; see also chapter 3 in this volume). Data on disease or injury outcomes alone, such as death or hospitalization, tend to focus on the need for curative or palliative services. Reliable and comparable analyses of risks to health are critical for preventing disease and injury. Investigators have frequently analyzed morbidity and mortality due to risk factors in the context of methodological traditions of individual risk factors and for selected populations (Kunzli and others 2000; Leigh and others 1999; McGinnis and Foege 1993; Peto and others 1992; Single and others 1999; Smith 2000; Smith, Corvalan, and Kjellstrom 1999; Willet 2002). As a result, most estimates have been affected by the following shortcomings, which limit comparability:

Evaluating national cause-of-death statistics: principles and application to the case of China.

Mortality statistics systems provide basic information on the levels and causes of mortality in populations. Only a third of the worlds countries have complete civil registration systems that yield adequate cause-specific mortality data for health policy-making and monitoring. This paper describes the development of a set of criteria for evaluating the quality of national mortality statistics and applies them to China as an example. The criteria cover a range of structural, statistical and technical aspects of national mortality data. Little is known about cause-of-death data in China, which is home to roughly one-fifth of the worlds population. These criteria were used to evaluate the utility of data from two mortality statistics systems in use in China, namely the Ministry of Health-Vital Registration (MOH-VR) system and the Disease Surveillance Point (DSP) system. We concluded that mortality registration was incomplete in both. No statistics were available for geographical subdivisions of the country to inform resource allocation or for the monitoring of health programmes. Compilation and publication of statistics is irregular in the case of the DSP, and they are not made publicly available at all by the MOH-VR. More research is required to measure the content validity of cause-of-death attribution in the two systems, especially due to the use of verbal autopsy methods in rural areas. This framework of criteria-based evaluation is recommended for the evaluation of national mortality data in developing countries to determine their utility and to guide efforts to improve their value for guiding policy.

Burden of Stroke in Indigenous Western Australians A Study Using Data Linkage

Background and Purpose— Despite the disproportionate burden of cardiovascular disease among indigenous Australians, information on stroke is sparse. This article documents the incidence and burden of stroke (in disability-adjusted life years) in indigenous and non-indigenous people in Western Australia (1997–2002), a state resident to 15% of indigenous Australians comprising 3.4% of the population of Western Australia. Methods— Indigenous and non-indigenous stroke incidence and excess mortality rates were estimated from linked hospital and mortality data, with adjustment for nonadmitted events. Nonfatal burden was calculated from nonfatal incidence, duration (modeled from incidence, excess mortality, and remission), and disability weights. Stroke death counts formed the basis of fatal burden. Nonfatal and fatal burden were summed to obtain disability-adjusted life years, by indigenous status. Results— The total burden was 55 099 and 2134 disability-adjusted life years in non-indigenous and indigenous Western Australians, respectively. The indigenous to non-indigenous age-standardized stroke incidence rate ratio (≥15 years) was 2.6 in males (95% CI, 2.3–3.0) and 3.0 (95% CI, 2.6–3.5) in females, with similar rate ratios of disability-adjusted life years. The burden profile differed substantially between populations, with rate ratios being highest at younger ages. Conclusions— The differential between indigenous and non-indigenous stroke burden is considerable, highlighting the need for comprehensive intersectoral interventions to reduce indigenous stroke incidence and improve outcomes. Programs to reduce risk factors and increase access to culturally appropriate stroke services are required. The results here provide the quantitative basis for policy development and monitoring of stroke outcomes.

Projecting the burden of diabetes in Australia--what is the size of the matter?

Objective: To analyse the implications of using different methods to predict diabetes prevalence for the future.

The burden of mental disorders in Victoria, 1996

Abstract  Background: Between 1998 and 1999, a burden of disease assessment was carried out in Victoria, Australia applying and improving on the methods of the Global Burden of Disease Study. This paper describes the methods and results of the calculations of the burden due to 22 mental disorders, adding 14 conditions not included in previous burden of disease estimates. Methods: The National Survey of Mental Health and Wellbeing provided recent data on the occurrence of the major adult mental disorders in Australia. Data from international studies and expert advice further contributed to the construction of disease models, describing each condition in terms of incidence, average duration and level of severity, with adjustments for comorbidity with other mental disorders. Disability weights for the time spent in different states of mental ill health were borrowed mainly from a study in the Netherlands, supplemented by weights derived in a local extrapolation exercise. Results: Mental disorders were the third largest group of conditions contributing to the burden of disease in Victoria, ranking behind cancers and cardiovascular diseases. Depression was the greatest cause of disability in both men and women. Eight other mental disorders in men and seven in women ranked among the top twenty causes of disability. Conclusions: Insufficient information on the natural history of many of the mental disorders, the limited information on the validity of mental disorder diagnoses in community surveys and considerable differences between ICD-10 and DSM-IV defined diagnoses were the main concerns about the accuracy of the estimates. Similar and often greater concerns have been raised in relation to the estimation of the burden from common non-fatal physical conditions such as asthma, diabetes and osteoarthritis. In comparison, psychiatric epidemiology can boast greater scientific rigour in setting standards for population surveys.

Global comparative assessments of life expectancy: the impact of migration with reference to Australia

OBJECTIVE To investigate the effect of immigration on life expectancy in Australia for the period from 1981 to 2003, and to compare life expectancy of the Australian-born population with that of other countries in the Organisation for Economic Cooperation and Development (OECD). METHODS Standard life-table methods using age-specific all-cause mortality and population data from 1981 to 2003 were used to calculate life expectancy at birth (e0) for the total Australian population (including migrants) and for people born in Australia (excluding migrants). Mean differences in life expectancy for each sex were compared using paired t-tests. Rankings of life expectancy among OECD countries were reassessed, and rank changes measured using the Wilcoxon signed rank test. FINDINGS Life expectancy of males and females was significantly lower in the Australian-born group than in the total Australian population. During 1981 to 2003, there was a mean difference in life expectancy of 0.41 years (95% confidence interval, CI: 0.37-0.44; t(17) = 27.0; P < 0.0001) in males and 0.29 years (95% CI: 0.26-0.31; t(17) = 27.6; P < 0.0001) in females between the Australian-born and the total population. After excluding migrant groups, Australia no longer ranked among the top five OECD countries with the highest life expectancy in the two most recent years examined. CONCLUSION While Australia has one of the highest life expectancies in the industrialized world, this is partly attributable to immigration of populations with low rates of mortality. This effect needs to be considered in international comparative assessments of mortality levels.

Disability burden due to stroke in Western Australia: new insights from linked data sources

Background The disability-adjusted life year index is used extensively to compare disease burden among diseases and locations, but difficulties remain in accurately estimating the nonfatal stroke burden in years lived with disability. Aims To improve stroke-related years lived with disability estimates in Western Australia for 2000, by improving the accuracy of component inputs: nonfatal (28-day survivor) incidence, disease duration and disability (severity) weights. Methods Nonfatal stroke incidence and the mortality difference between prevalent cases and the general population were estimated from linked hospital and mortality data using the Western Australian Data Linkage System. Dismod software used these inputs to model disease duration. Disability weights were estimated from population-based stroke survey data, using indirect health valuation methods and adjusting for prestroke disability. Years lived with disability were calculated from the three components. Results The annual age-standardised nonfatal incidence (n = 1985) was higher ***In males (121/100 000) than females (96/100 000). The duration varied between 35.8 (females 15–24 years) and 3.4 years (males 85+ years). The mean pre-stroke-adjusted disability weight was higher at 4-months (0.38) than at 12-months (0.31). The age-standardised rate of nonfatal burden in males (302/100 000; 95% CI 290–314) was significantly higher than that in females (250/100 000; 95% CI 240–260). The nonfatal proportion of stroke burden (males 45%; females 37%) was higher than estimated in previous studies. Conclusion This study illustrates that previous reports most likely underestimated disability burden as a contributor to the total stroke burden in Australia. Methodological refinements will contribute to burden of disease studies elsewhere.

Health in a ‘post-transition’ Australia: adding years to life or life to years?

OBJECTIVE To explore the likely impact of future trajectories of morbidity and mortality in Australia. METHODS Estimates of mortality and morbidity were obtained from a previous assessment of Australias health from 1993 to 2003, including projections to 2023. Outcomes of interest were the difference between life expectancy (LE0) and health-adjusted life expectancy (i.e. absolute lost health expectancy (ALHE0)), ALHE0 as a proportion of LE0 and the partitioning of changes in ALHE0 into additive contributions from changes in age- and cause-specific mortality and morbidity. RESULTS Actual and projected trajectories of mortality and morbidity resulted in an expansion of ALHE0 of 1.22 years between 1993 and 2023, which was equivalent to a relative expansion of 0.7% in morbidity over the life course. Most (93.8%) of this expansion was accounted for by cardiovascular disease, diabetes and cancer; of these, the only unfavourable trend of any note was increasing morbidity from diabetes. CONCLUSIONS Time spent with morbidity will most likely increase in terms of numbers of years lived and as a proportion of the average life span. This conclusion is based on the expectation that gains in LE0 will continue to exceed gains in ALHE0, and has important implications for public policy. WHAT IS KNOWN ABOUT THE TOPIC? Although the aging of Australias population as a result of declining birth and death rates is well understood, its relationship with levels of morbidity is not always fully appreciated. This is most noticeable in the policy discourse on primary prevention, in which such activities are sometimes portrayed as having unrealised potential with respect to alleviating growth in health service demand. WHAT DOES THIS PAPER ADD? This paper sheds new light on these relationships by exploring the likely impact of future trajectories of both morbidity and mortality within an additive partitioning framework. The results suggest a modest expansion of morbidity over the life course, most of which is accounted for by only three causes. In two of these (cardiovascular disease and cancer), the underlying trends in both mortality and morbidity have been favourable for some time due, at least in part, to success in primary prevention. WHAT ARE THE IMPLICATIONS FOR PRACTITIONERS? Although there may be good arguments in favour of a greater focus on primary prevention as currently practiced, reducing overall demand for health services is unlikely to be one of them. To make such an argument valid, policy makers should consider shifting their attention to the effectiveness of primary prevention as it relates to causes other than cardiovascular disease and cancer, particularly those with a predominantly non-fatal impact, such as diabetes and degenerative diseases of old age.