Discussion
As described in chapter 3, the data requirements for adequate measurements of the global burden of disease are substantial and include information about age at death, cause of death, age-specific incidence of diseases and injuries, typical duration of life lived with the sequelae of diseases and injuries, and some quantification of the severity of disability assessed according to a common framework. While the ethical, philosophical, and conceptual issues involved in quantifying states of health other than perfect health are still very much a matter of debate, a substantial body of empirical evidence on the variations across individuals and populations in health state valuations is now available.
We have shown in this chapter that the distribution of the global burden of disease and the overall rankings of various conditions in terms of their contribution to it are largely insensitive to alternative assumptions about the discount rate and age weighting. The major effect of discounting and age weighting is to enhance the importance of neuropsychiatric conditions and sexually transmitted infections. While disease rankings are relatively unaffected, the share of the burden due to disability, the age distribution of the burden, and the distribution of the burden by broad cause group are sensitive to the discount rate but less affected by age weighting.
When compared with the discounted and age-weighted DALY used in the 1990 GBD study and the WHO updates for 2000-2, the DCPP's use of discounted but not age-weighted DALYs results in somewhat more weight being given to the chronic diseases of older ages and somewhat less weight being given to mental disorders and injuries, which affect younger adults disproportionately. Of the value choices incorporated into the standard DALYs(3,1), the nonuniform age weights have been the most controversial. Apart from the DCPP, a number of national burden of disease studies, including those in Australia and Canada (Mathers, Vos, and Stevenson 1999; Public Health Agency of Canada 2005), have chosen not to apply the nonuniform age weights, presumably on equity grounds. In contrast, some investigators concerned with the inequitable health burden of the low- and middle-income countries have argued for ignoring all deaths over a certain age on the grounds that they are not premature—an extreme form of age weighting (Williams 1997). Chapter 6 presents some empirical evidence in making the case for a stronger form of age weighting for infants and younger children, that is, age weights that depart further from unity than the standard age weighting used in the DALY.
Although the choices for discounting and age weighting do affect the cause and age distributions of the burden of disease to some extent, and the results of specific cost-effectiveness studies may be even more sensitive to these choices, we conclude that the uncertainty of the underlying epidemiological choices is vastly more consequential than these social preferences when interpreting the results of burden of disease analysis. The validity and reliability, and hence the utility, of burden of disease studies for public policy depend much more strongly on the quality and availability of the underlying epidemiological data.
The GBD study has been criticized for making estimates of mortality and burden of disease for regions with limited, incomplete, and uncertain data (Cooper and others 1998; Gupta, Sankaranarayanan, and Ferlay 1994). Murray and Lopez describe the GBD approach as a "`meta-synthesis,' or in other words, the construction of a comprehensive and comparable view of health problems using all available sources of information" (Murray and Lopez 1996b, p. 289). The incorporation of many types of information about a comprehensive set of causes of death and disability results in estimates that are much less likely to be biased than those that emerge from an examination of specific health conditions in isolation. It also avoids the tendency to assume that if no data are available or the data are highly uncertain, then there is no disease burden.
We argue that including uncertain results (with quantified uncertainty to the extent possible) is far preferable than leaving blank cells in tables intended to provide policy makers with an overall assessment of the burden of disease in populations. We maintain that providing large volumes of unsynthesized, biased, and incomplete data relating to population health does not generally allow policy makers to make the best use of such information. Unless they have considerable analytic resources of their own, the unsynthesized products of the research enterprise are of little help to decision makers, who will often then resort to decisions on the basis of ideology, of their own beliefs about what is important, or of political imperatives.
The quantities of interest for the GBD study are the underlying rates of incidence, remission, and mortality for defined causes for whole populations for a specified time period, and the assessment of these often requires synthesizing data from multiple studies or making adjustments for biases in relation to population, age groups, or time periods. A major source of uncertainty for the GBD estimates is the uncertainty associated with extrapolating from one or more subgroups to a regional population. For example, how representative of the incidence and prevalence patterns of dementia in Sub-Saharan Africa are two or three population-representative studies of rural or urban populations in specific regions of specific countries? The uncertainty associated with extrapolating from a set of studies in subpopulations to the regional population is related to potential systematic (selection) biases and is much more difficult to quantify than the uncertainty associated with stochastic variation due to sample size or measurement error.
Estimates of deaths from specific causes undergo continual revision as new data and syntheses become available, yet drawing a time cutoff is a necessary (if somewhat arbitrary) condition for preparing any volume such as this which reports comprehensive and consistent global and regional estimates of deaths and burden of disease (see also annex 6C). During 2001 WHO established the Child Health Epidemiology Reference Group (CHERG) to review and synthesise data on cause of deaths under age 5. While early CHERG results contributed substantially to the GBD analyses in this volume, much of their work became available well after the cutoff date for this publication. While CHERG has published revised estimates of the distribution of child deaths by cause (Bryce and others 2005), based on recent comprehensive reviews of epidemiological data, these analyses used cause categories not consistent with the GBD (including use of incompatible cause categories for neonatal and other child deaths), fewer cause categories than the GBD, and left study deaths assigned to ill-defined categories in the `Other' category. Additionally, at the date of writing, the CHERG evidence has not been brought into the GBD analytic and consistency framework, involving consistent mapping to causal categories and checking of internal consistency between incidence, prevalence and mortality estimates for specific causes.
To the extent that they can be compared with the GBD 2001 estimates, the WHO/CHERG estimates at the global level are differ substantially for tetanus (46% higher), lower respiratory infections (56% higher), and are somewhat lower for measles, malaria, low birthweight and noncommunicable diseases. It is not possible at this stage, to conclude whether or how much the WHO/CHERG analyses would modify the GBD 2001 results reported in this volume, when they are properly brought into the GBD analytic framework. However, they do give some indications that new evidence is becoming available for child deaths, and that uncertainty ranges for GBD estimates of child deaths may be greater for some causes than indicated by the analyses presented in this chapter.
The 1990 GBD study and GBD 2001 were both meta-syntheses of the available data, using the best models and tools available at the time, whose primary aims were to provide a comprehensive assessment of the current burden of disease. The assessment of trends between 1990 and 2001 is a much more difficult task, as discussed in chapter 2. The comparability of best point in time estimates is difficult to assess given changes in both the availability of data and in the methods used to synthesize those data for many of the causes. Murray, Mathers, and Salomon (2003) discuss this issue in more detail and conclude that to assess change or evaluate programs, extrapolating current levels of burden of disease from past measurements is inadequate, and that the assessment must include measurements carried out at both points in time or explicit measurement of the relevant trends or rates of change.
