Disability-adjusted life year: Difference between revisions
m (Added DALYs category) |
(Added category: 'Intarese Opasnet') |
||
Line 149: | Line 149: | ||
[[Category:WP1.4]] | [[Category:WP1.4]] | ||
[[Category:Disability-adjusted life years (DALYS)]] | [[Category:Disability-adjusted life years (DALYS)]] | ||
[[category:Intarese]] |
Revision as of 12:57, 13 October 2009
Related useful material on DALYs:
- DALY calculation model
- Health impact assessment and DALY review
- DALY weights
- Disability-adjusted life years (in Wikipedia)
Disability-adjusted life years (DALYs) are a method for combining different health impacts such as mortality and morbidity into a single common metric. The DALY is one of the most commonly used integrated health measures and was first introduced by Murray and Lopez (1996) in collaboration with World Health Organization and the Worldbank in an attempt to introduce morbidity in mortality-based health discussions. In effect, the DALY integrates many dimensions of public health impact e.g. the number of persons affected by a particular agent or event, the severity and duration of any health effects.[1]
This document describes briefly how Disability Adjusted Life Years (DALYs) can be used in a Health Impact Assessment (HIA). After a short introduction about integrated health measures, the calculation steps are described. Together with Excel sheets made for this purpose (“DALY worksheets Intarese”), this information can be used as a basis for the calculation of environmental DALYs.
As for any calculation, it is very important to carefully document the input data and assumptions in the HIA report.
Anne Knol - RIVM
Integrated health measures
Health effects of environmental factors can vary considerably with regard to their severity, duration and magnitude. This makes it difficult to compare different (environmental) health effects. An integrated health measure, using the same denominator for all health effects, can help with interpretation and comparison of health problems and policies. They quantify and summarize (environment-related) health effects and can be used for:
- Comparative evaluation of environmental health impacts (“how bad is it?”)
- Evaluation of the effectiveness of environmental policies (largest reduction of disease burden)
- Estimation of the accumulation of exposures to environmental factors (for example in urban areas)
- Communication of health risks
An example of an integrated health measure is the DALY (Disability Adjusted Life Years). DALYs combine information on quality and quantity of life. They give an indication of the (potential) number of healthy life years lost due to premature mortality or morbidity. In these calculations, morbidity is weighted for the severity of the disorder.
General information about other types of integrated health measures can be found in the appendix.
Calculating DALYs
DALYs can be calculated using the Excel sheets provided for the Intarese project (pilot version available only).
The formula of a DALY is as follows:
- Number of people with environment-related morbidity or mortality x
- Severity factor (0 = healthy, 1 = death) x
- Duration (YLL for mortality)
A more detailed formula is given below
[2]:
DALY = AB * D * S AB = AR * P * F AR = (RR’-1)/RR’ RR’ = ((RR-1) * C) + 1
where:
- AB: Attributable Burden; the number of people in a certain health state as a result of exposure to the (environmental) factor that is being analyzed, not corrected for comorbidity.
- D: Duration of the health state; for morbidity, prevalence numbers have been used and therefore duration is one year (except for hospital visits, for which the mean duration of the specific hospital visit has been used). For mortality, the duration of time lost due to premature mortality is calculated using standard expected years of life lost with model life tables.
- S: Severity; the reduction in capacity due to morbidity is measured using severity weights. A weight factor, varying from 0 (healthy) to 1 (death), is determined by experts (clinicians, researchers, etc).
- AR: Attributive Risk; risk of getting a specific disease as a result of exposure to a certain (environmental) factor.
- P: Base prevalence for morbidity; number of deaths for mortality
- F: Fraction of the population exposed to the (environmental) factor under investigation (for air pollution, this fraction is set to 1, meaning that everybody is exposed to a certain degree)
- RR’: Adjusted Relative Risk
- RR: Relative Risk
- C: Concentration of the environmental factor, expressed in the unit of the Relative Risk
Discounting
DALY calculations can also include discounting factors. In discounting, future years of healthy life lived are valued less than present years (discounting normally 3%), or years lived by people in a certain age group (productive ages) are valued more than years lived by the very old and young. Ethical questions can be raised with regard to the use of these factors, and they are currently not included in the calculation sheets. They might become optional in newer versions of DALY calculation tools. More information and templates can be found at WHO health info.
Data
Number of people
The number of people with environment-related morbidity or mortality can be calculated using baseline incidence or prevalence of a disease, population exposure, and a proper exposure response function. It is important the definition and units of the environmental factor and the definition of the related health outcome match exactly with the definitions used in the exposure response function.
The input data can be found using the help of SP2 and WP1.3.
Severity factors
Severity weights (or disability weights) give an indication of the reduction in capacity due to the specific disease. A weight factor, varying from 0 (healthy) to 1 (death), is determined by experts (clinicians, researchers, etc). An overview of severity weights that have been collected in various studies can be found in an Australian report (appendix 1).
If severity weights for the selected health outcomes are not available in this overview, or not judged suitable, they can be derived using expert judgments. A helpful tool is the EuroQol (5D+) model. This is a model which evaluates health states based on six health dimensions: mobility, self-care, daily activities, pain or discomfort, anxiety or depression and cognitive functions.
If deriving new severity weights using expert panels is too time-consuming, it is sometimes possible to use existing severity weights for similar conditions, using expert judgment.
Duration
The duration of a health effect describes the number of healthy life years lost.
For morbidity, this is the time someone has the specified disease condition. This duration can be set to one year if prevalence data are used (assuming that prevalence approximately equals incidence multiplied by duration, and thereby assuming a steady-state equation where the rates are not changing). If incidence data are used, an estimation of the duration of a certain health state should be based on literature research, hospital registries or expert judgments.
For mortality caused by those environmental factors that are completely responsible for death (such as traffic is completely responsible for traffic accident mortality), the mean life expectancy minus mean age of death can be used as the number of years of life lost. The YLL are thus very dependent on the age group of the people that are affected and the remaining life expectancy they have. If age-specific information is available, this should be used to derive the value for duration. For national estimates, values based on national statistics should be used. For international calculations, or calculations that compare various countries, standard (European) values should be used. These can be derived from national statistics offices or Eurostat. If gender-specific health effect estimates are available, gender-specific duration estimates should be used. Life table analysis (not included in this file) can help to identify YLL. Some templates (excel sheets) are provided at WHO health info.
For environmental conditions that only accelerate death in people that are already diseased, only a percentage of the actual Year of Life Lost (YLL) can be attributed to the environmental factor. This estimate of the duration should then be based on literature research or expert judgments. Also here, it is important to take into account which age group/ gender is affected.
Uncertainty
DALYs capture number of people, duration and severity of conditions in one number, thereby greatly simplifying reality. This simplification can be very useful to make different health states or environmental disease burdens comparable, but it may also lead to significant uncertainty in the output.
Uncertainty can relate to:
- Definitions (what is health? what is environment?)
- Assumptions (for example: causality, stable situations, etc)
- Environment and health data (concentrations / emissions, exposed population, dose effect relationships)
- DALY specific data (estimates of duration and severity of the effect)
DALYs should therefore always be interpreted taking their context and input data into account. They DALYs can only be used to give an indication of the potential order of magnitude of different (environmental) health problems, and can not be presented as absolute or completely representative numbers.
A thorough assessment of uncertainty should be carried out while doing the assessment, resulting in a quantitative estimate of the related uncertainty (for example by carrying out Monte Carlo analysis). A tool for this analysis will be provided at a later stage of the Intarese project. For now, a detailed (quantitative) description of sources of uncertainty should be provided together with the results (WP1.5).
Uncertainty analysis is not (yet) included in the Excel sheets for DALY calculations.
Appendix: common integrated health measures
Common health measures include mortality, morbidity, healthy life expectancy, attributable burden of disease measures, and monetary valuation. Some of these measures will be further described below. All methods have several associated difficulties, such as imprecision of the population exposure assessment; uncertain shapes of the exposure-response curves for the low environmental exposure levels; insufficient (quality of) epidemiological data; extrapolation from animal to man or from occupational to the general population; generalisation of exposure-response relations from locally collected data for use on regional, national or global scale; combined effects in complex mixtures, etc.
Mortality figures
The annual mortality risk or the number of deaths related to a certain (environment-related) disease can be compared with this risk or number in another region or country, or with data from another period in time. Subsequently, different policies can be compared and policies that do or do not work can be identified. Within a country, time trends can be analyzed. This method is easy to comprehend. No ethical questions are attached; everyone is treated equal. Since this method only includes mortality, it is not suitable for assessing factors with less severe consequences (morbidity). Also, it is difficult to attribute mortality to specific environmental causes.
Morbidity figures
Similar to mortality figures, morbidity numbers (prevalences or incidences based on hospital admissions or doctor visits) can be used to evaluate a (population) health state. Advantages and drawbacks are comparable to those applying to using mortality figures. The use of morbidity numbers is therefore similarly limited, especially when (environmental) causes of the diseases vary.
Healthy life expectancy
Using mortality tables, one can calculate the total average life expectancy for different age groups in a population, subdivided into years with good and years with less-than-good health. This measure is especially useful to review the generic health state in a country for the long term, but it doesn’t give insight into specific health effects, effects of specific policy interventions, or trends in certain subgroups.
Attributable burden of disease
Health impact assessments can also be executed by calculating the attributable burden of disease. There are several ways to assess the burden of disease attributable to an (environmental) factor, such as the QALY and the DALY. Quality Adjusted Life Years, QALYs, capture both the quality and quantity elements of health in one indicator. Essentially, time spent in ill health (measured in years) is multiplied by a weight measuring the relative (un)desirability of the illness state. Thereby a number is obtained which represents the equivalent number of years with full health. QALYs are commonly used for cost-utility analysis and to appraise different forms of health care. To do that, QALYs combine life years gained as a result of these health interventions/health care programs with a judgment about the quality of these life years. Disability adjusted life years, DALYs, are comparable to QALYs in that they both combine information on quality and quantity of life. However, contrary to QALYs, DALYs give an indication of the (potential) number of healthy life years lost due to premature mortality or morbidity and are estimated for particular diseases, instead of a health state. Morbidity is weighted for the severity of the disorder.
With QALY, the focus is on assessing individual preference for different non-fatal health outcomes that might result from a specific intervention, whereas the DALY was developed primarily to compare relative burdens among different diseases and among different populations (Morrow and Bryant, 1995). DALYs are suitable for analyzing particular disorders or specific factors that influence health. Problems associated with the DALY approach include the difficulty of estimating the duration of the effects (which have hardly been studied) and the severity of a disease; and allowing for combined effects in the same individual (first you have symptoms, then you go to a hospital and then you may die). The DALY concept, which has been used in our study, will be further described in the next chapter. More information on the drawbacks of the method can be found in Chapter 6.4.
Monetary valuation
Another approach to health impact assessment is monetary valuation. In this measure, money is used as a unit to express health loss or gain, thereby facilitating the comparison of policy costs and benefits. It can help policy makers in allocating limited (health care) resources and setting priorities. There are different approaches to monetary valuation such as cost of illness and willingness to pay/accept.
The cost of illness (COI) approach estimates the material costs related to mortality and morbidity. It includes the costs for the whole society and considers loss of income, productivity and medical costs. This approach does not include immaterial costs, such as impact of disability (pain, fear) or decrease in quality of life. This could lead to an underestimation of the health costs. Furthermore, individual preferences are not considered.
The willingness to pay (WTP) approach measures how much money one would be willing to pay for improvement of a certain health state or for a reduction in health risk. The willingness to accept (WTA) approach measures how much money one wants to receive to accept an increased risk. WTP and WTA can be estimated by observing the individual’s behaviour and expenditures on related goods (revealed preference). For example, the extra amount of money people are willing to pay for safer or healthier products (e.g. cars with air bags), or the extra salary they accept for compensation of a risky occupation (De Hollander, 2004). Another similar method is contingent valuation (CV), in which people are asked directly how much money they would be willing to pay (under hypothetical circumstances) for obtaining a certain benefit (e.g. clean air or good health).
References
- ↑ Havelaar A., De Hollander A.E.M., Teunis P.F.M., Evers E.G., Van Kranen H.J., Versteegh J.F.M., Van Koten J.E.M., Slob W. Balancing the Risks and Benefits of Drinking Water Disinfection : Disabiliity Adjusted Life-Years on the Scale. Environ Health Perspect 108:315-321 (2000)
- ↑ Knol, A.B. en Staatsen, B.A.M. (2005). Trends in the environmental burden of disease in the Netherlands, 1980-2020. Rapport 500029001, RIVM, Bilthoven. Downloadable at http://www.rivm.nl/bibliotheek/rapporten/500029001.html