Difference between revisions of "Estimating disability-adjusted life years"

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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.

The proponents of DALY's use the metric for atleast two separate exercise

1. Positive exercise of measuring the burden of disease.

2. The normative exercise for resource allocation.

The burden of disease is simply measured as the sum of DALYs attributable to premature mortality and morbidity. for resource allocation, Murrey suggested that DALYs be used "in conjunction with the literature on cost effectiveness of health intervention" so as "using estimates of the burden of disease in determining health resource allocations". In using DALY for this purpose, the object is to minimize and aggregate DALYs subject to a given budget.

Murrey states "{T}he he intended use of an indicator of the burden of disease is critical to its design. at least 4 objectives are very important

• to aid in sitting health service (both curative and preventive) priorities.

• to aid in sitting health research priorities.

• to aid in identifying disadvantaged group and targeting of health intervention

• to to provide a comparable measure of output for intervention, program and sector evaluation and planning.

Not everyone appreciate the ethical dimension of heath status indicator. Nevertheless, the first two objectives listed for measuring burden of disease could influence the allocation of resource among individuals, clearly establishing an ethical dimension to the construction of an indicator of the burden of disease.

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.

Definition

^[2]

Calculation

DALY in case of recovery:

Peffect  * (Prec* YLDrec * Sev)

DALY in case of death

Peffect * [Pdie *(YLDdie * Sev) + L.E. - C.A. - YLDdie]

DALY if 'diseased' to natural life expectancy (chronic disease)

Peffect * (1 - Prec - Pdie) * (L.E. - C.A.) * Sev

Where:

• Peffect = Probability of the considered effect (dose-response relationship)
• Prec = Probability to recover from a disease
• Pdie = Probability to die from a disease
• YLDrec = Years Lived with Disability in case of full recovery ^[3]
• YLDdie = Years Lived with Disability in case of death
• Sev = Severity of the effect (0-1)^{[2] [4] [5]}
• L.E. = Life expectancy
• C.A. = Current Age

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 ^[6]:

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.

Measuring the Burden of Disease:Implication of the DALY framework

What is Burden

The DALY approach measure the burden of disease through reduction in human function (Murray, 1994, p.438). The multiple dimensions of human function are mapped onto a undimensional scale between 0 (perfect health) and 1 (death) along which six discrete disability classes are distinguished. Human function is represented by ability to perform certain activities of daily living, such as learning, working, feeding and clothing oneself. The space in which ill-health is assessed is limitation in these actitivites rather than, for example, that of pain or suffering which would be the relevant categories in a utility based framework. Another space for assessment might be reduction well-being, a notion that is broader than utility and is captured by general capability to function - including physical functioning. Of course, there will be utility or well-being consequences associated with reduction in human function, but these are not the basis for the DALY metric.

An often-cited advantage of DALYs, and similar composite indicators such as QALYs, is that they allow fatal and non-fatal health outcomes to be combined into a single indicator. A necessary condition for a finite scale which has perfect health (or quality of life) at one end and death at the other is that the values of all health states, including death, be bounded. In the DALY scale death differs from disability merely by reducing human function to nought. While having an indicator that combines states of imperfect health with death is clearly convenient, there is an obvious information loss in reducing death to simply another health state. Some will argue that the two events are incommensurable, and that a lexical priority attaches to life over death. At any rate, this suggests that information about mortality and morbidity should be presented seperately - even if the trade-offs were conceded between the two events.

DALYs attempt to measure the burden of disease in a somewhat narrow sense. As discussed, they represent the qyantity of ill-health experienced by individuals through functional limitation and premature death. The burden that is measured does not reflect individuals' differential ability to cope with their functional limitation. Moreover, burdens which fall on family, friends and society at large (e.g. the economic cost of illness) are not included. Only in the use of unequal age-weights does there appear to be an attempt to capture the indirect health burden of illness. We return to the rationale for an ethical implications of unequal age-weighting

DALYs use standardized maximum life expectancies (80 years for men and 82.5 years for women) which are considerably higher than the levels of life expectancy currently achieved in developing countries. Using these standardized life expectancies either in measuring global burden of disease or in cost-effectiveness analysis implicitly assumes that health interventions alone are capable of achieving an increase in life expectancy to those higher levels. It is clear that many non-health circumstances will also need to change for life expectancy to rise to the level used in the DALY calculations. These interventions would have to address the socio-economic determinants of health. They would include raising incomes, increasing female education, improving water supply and sanitation conditions, improving workplace safety, and reducing accidents and violence. Hence the burden that is measured by DALYs is the burden of disease and underdevelopment, and not that disease alone.

Standard expectation of life and gender gap

To calculate the DALYs from morbidity and premature mortality, a standard expectation of life at birth of 82.5 years is chosen for women and of 80 years for men. This gap is considerably smaller than the observed gender gap in life expentancy in low mortality populations, for example, Japan which has a gender gap of some 6 years. However, the gender gap of 2.5 years is argued to correspond purely to the biological difference in survival potential between males and females (Murray, 1994, p.434), factoring out the effects on life expectancy of males' greater exposure to social and other risk factors. It is, nonetheless, an arbitary choice.

The assumed gender gap in life expectancy may have important implications for the estimation of the disease burden of women relative to that of men. World Bank (1993, p. 28) estimates that [F]emales have about a 10 percent lower disease burden per 1,000 per population than males for the world as a whole. The smaller the gender group, ceteris paribus, the smaller will be the female contribution to the burden of disease relative to the male contribution. If the true biological gap happens to be greater than 2.5 years, then the calculation in Murray et al. (1994) and World Bank (1993) will understate the burden of disease of females relative to that of males.

While DALYs take account of higher female life expectancy in calculating years lost to premature mortality, the valuation of those years can be sharply reduced by age-weightning and discounting. As an illustration Table 1 shows the estimate of time lost, and of its value, from the death of a female and a male infant, respectively. The female advantage in years lost of 3% is reduced by age-weighting to 1.5%, and is further reduced by discounting to 0.3% for the calculation of DALYs.

References