Disability-adjusted life year

Disability-adjusted life years out of 100,000 lost due to any cause in 2004.[1]
  no data
  fewer than 9,250
  more than 80,000

The disability-adjusted life year (DALY) is a measure of overall disease burden, expressed as the number of years lost due to ill-health, disability or early death. It was developed in the 1990s as a way of comparing the overall health and life expectancy of different countries.

The DALY is becoming increasingly common in the field of public health and health impact assessment (HIA). It "extends the concept of potential years of life lost due to premature death...to include equivalent years of 'healthy' life lost by virtue of being in states of poor health or disability."[2] In so doing, mortality and morbidity are combined into a single, common metric.


The disability-adjusted life year is a societal measure of the disease or disability burden in populations. DALYs are calculated by combining measures of life expectancy as well as the adjusted quality of life during a burdensome disease or disability for a population. DALYs are related to the quality-adjusted life year (QALY) measure; however QALYs only measure the benefit with and without medical intervention and therefore do not measure the total burden. Also, QALYs tend to be an individual measure, and not a societal measure.

Traditionally, health liabilities were expressed using one measure, the Years of Life Lost (YLL) due to dying early. A medical condition that did not result in dying younger than expected was not counted. The Years lost due to disability (YLD) component measures the burden of living with a disease or disability.

DALYs are calculated by taking the sum of these two components:[3]


The DALY relies on an acceptance that the most appropriate measure of the effects of chronic illness is time, both time lost due to premature death and time spent disabled by disease. One DALY, therefore, is equal to one year of healthy life lost.

How much a medical condition affects a person is called the disability weight (DW). This is determined by disease or disability and does not vary with age. Tables have been created of thousands of diseases and disabilities, ranging from Alzheimer's disease to loss of finger, with the disability weight meant to indicate the level of disability that results from the specific condition.

Examples of Disability weight
Condition DW 2004[4] DW 2010[5]
Alzheimer's and other dementias 0.666 0.666
Blindness 0.594 0.195
Schizophrenia 0.528 0.576
AIDS, not on ART 0.505 0.547
Burns 20%-60% of body 0.441 0.438
Fractured femur 0.372 0.308
Moderate depression episode 0.350 0.406
Amputation of foot 0.300 0.021-0.1674
Deafness 0.229 0.167-0.281
Infertility 0.180 0.026-0.056
Amputation of finger 0.102 0.030
Low back pain 0.061 0.322-0.374

Examples of the disability weight are shown on the right. Some of these are "short term" and the long-term weights may be different.

The most noticeable change between the 2004 and 2010 figures for disability weights above are for blindness as it was considered the weights are a measure of health rather than wellbeing (or welfare) and a blind person is not considered to be ill. "In the GBD terminology, the term disability is used broadly to refer to departures from optimal health in any of the important domains of health."[6]

At the population level, the disease burden as measured by DALYs is calculated by adding YLL to YLD. YLL uses the life expectancy at the time of death. YLD is determined by the number of years disabled weighted by level of disability caused by a disability or disease using the formula:

YLD = I x DW x L

In this formula I = number of incident cases in the population, DW = disability weight of specific condition, and L = average duration of the case until remission or death (years). There is also a prevalence (as opposed to incidence) based calculation for YLD. Premature death is calculated by YLL = N x L, where N = number of deaths due to condition, L = standard life expectancy at age of death (expectancy - age at death).[7]

Japanese life expectancy statistics are used as the standard for measuring premature death, as the Japanese have the longest life expectancies.[8]

Age weighting

Some studies use DALYs calculated to place greater value on a year lived as a young adult. This formula produces average values around age 10 and age 55, a peak around age 25, and lowest values among very young children and very old people.[9]

A crucial distinction among DALY studies has been the use of "age-weighting", in which the value of each year of life depends on age. There are two components to this differential accounting of time: age-weighting and time-discounting. Age-weighting is based on the theory of human capital. Commonly, years lived as a young adult are valued more highly than years spent as a young child or older adult, as these are years of peak productivity. Age-weighting receives considerable criticism for valuing young adults at the expense of children and the old. Some criticize, while others rationalize, this as reflecting society's interest in productivity and receiving a return on its investment in raising children. This age-weighting system means that somebody disabled at 30 years of age, for ten years, would be measured as having a higher loss of DALYs (a greater burden of disease), than somebody disabled by the same disease or injury at the age of 70 for ten years.

This age-weighting function is by no means a universal methodology in HALY studies, but is common when using DALYs. Cost-effectiveness studies using QALYs, for example, do not discount time at different ages differently.[10] This age-weighting function applies only to the calculation of DALYs lost due to disability. Years lost to premature death are determined from the age at death and life expectancy.

The global burden of disease (GBD) 2001–2002 study counted disability adjusted life years equally for all ages, but the GBD 1990 and GBD 2004 studies used the formula[11]

[12] where is the age at which the year is lived and is the value assigned to it relative to an average value of 1.

In these studies future years were also discounted at a 3% rate to account for future health care losses. Time discounting, which is separate from the age-weighting function, describes preferences in time as used in economic models.[13]

The effects of the interplay between life expectancy and years lost, discounting, and social weighting are complex, depending on the severity and duration of illness. For example, the parameters used in the GBD 1990 study generally give greater weight to deaths at any year prior to age 39 than afterward, with the death of a newborn weighted at 33 DALYs and the death of someone aged 5–20 weighted at approximately 36 DALYs.[14]

As a result of numerous discussions, by 2010 the World Health Organization had abandoned the ideas of age weighting and time discounting.[15] They had also substituted the idea of prevalence for incidence (when a condition started) because this is what surveys measure.

Economic applications

The methodology is not an economic measure. It measures how much healthy life is lost. It does not assign a monetary value to any person or condition, and it does not measure how much productive work or money is lost as a result of death and disease. However, HALYs, including DALYs and QALYs, are especially useful in guiding the allocation of health resources as they provide a common denominator, allowing for the expression of utility in terms of DALYs/dollar, or QALY/dollar.[10] For example, in Gambia, provision of the pneumococcal conjugate vaccine costs $670 per DALY saved.[16] This number can then be compared to other treatments for other diseases, to determine whether investing resources in preventing or treating a different disease would be more efficient in terms of overall health.


Schizophrenia has a 0.53 weighting and a broken femur a 0.37 weighting in the latest WHO weightings.[17][18]


Cancer (25.1/1,000), cardiovascular (23.8/1,000), mental problems (17.6/1,000), neurological (15.7/1,000), chronic respiratory (9.4/1,000) and diabetes (7.2/1,000) are the main causes of good years of expected life lost to disease or premature death.[19] Despite this, Australia has one of the longest life expectancies in the world.


These illustrate the problematic diseases and outbreaks occurring in 2013 in Zimbabwe, shown to have the greatest impact on health disability were typhoid, anthrax, malaria, common diarrhea, and dysentery.[20]

PTSD rates

Posttraumatic stress disorder (PTSD) DALY estimates from 2004 for the world's 25 most populous countries give Asian/Pacific countries and the United States as the places where PTSD impact is most concentrated (as shown here).

Noise-Induced Hearing Loss

The disability-adjusted life years attributable to hearing impairment for noise-exposed U.S. workers across all industries was calculated to be 2.53 healthy years were lost annually per 1,000 noise-exposed workers. Workers in the mining and construction sectors lost 3.45 and 3.09 healthy years per 1,000 workers, respectively. Overall, 66% of the sample worked in the manufacturing sector and represented 70% of healthy years lost by all workers.[21]

History and usage

Originally developed by Harvard University for the World Bank in 1990, the World Health Organization subsequently adopted the method in 1996 as part of the Ad hoc Committee on Health Research "Investing in Health Research & Development" report. The DALY was first conceptualized by Murray and Lopez in work carried out with the World Health Organization and the World Bank known as the global burden of disease study, which was published in 1990. It is now a key measure employed by the United Nations World Health Organization in such publications as its Global Burden of Disease.[22]

The DALY was also used in the 1993 World Development Report.[23]:x


Although some have criticized DALYs as essentially an economic measure of human productive capacity for the affected individual,[24] this is not so. DALYs do have an age-weighting function that has been rationalized based on the economic productivity of persons at that age, but health-related quality of life measures are used to determine the disability weights, which range from 0 to 1 (no disability to 100% disabled) for all disease. These weights are based not on a person's ability to work, but rather on the effects of the disability on the person's life in general. This is why mental illness is one of the leading diseases as measured by global burden of disease studies, with depression accounting for 51.84 million DALYs. Perinatal conditions, which affect infants with a very low age-weight function, are the leading cause of lost DALYs at 90.48 million. Measles is fifteenth at 23.11 million.[10][25][26]

Some commentators have expressed doubt over whether the disease burden surveys (such as EQ-5D) fully capture the impacts of mental illness, due to factors including ceiling effects.[27][28][29]

See also


  1. "WHO Disease and injury country estimates". World Health Organization. 2009. Retrieved Nov 11, 2009.
  2. "Death and DALY estimates for 2004 by cause for WHO Member States: Persons, all ages" (xls). World Health Organization. 2002. Retrieved 2009-11-12.
  3. Havelaar, Arie (August 2007). "Methodological choices for calculating the disease burden and cost-of-illness of foodborne zoonoses in European countries" (PDF). Med-Vet-Net. Archived from the original (PDF) on 21 Jan 2009. Retrieved 2008-04-05.
  4. "GLOBAL BURDEN OF DISEASE 2004 UPDATE: DISABILITY WEIGHTS FOR DISEASES AND CONDITIONS" (PDF). World Health Organization. 2004. Retrieved Jul 25, 2016.
  5. WHO 2013.
  6. WHO 2013, p. 15.
  7. "Metrics: Disability-Adjusted Life Year (DALY)". Retrieved 29 October 2014.
  8. Menken M, Munsat TL, Toole JF (March 2000). "The global burden of disease study: implications for neurology". Arch. Neurol. 57 (3): 418–20. doi:10.1001/archneur.57.3.418. PMID 10714674.
  9. Murray, Christopher J (1994). "Quantifying the burden of disease: the technical basis for disability-adjusted life years". Bulletin of the World Health Organization. 72: 429–45. PMC 2486718Freely accessible. PMID 8062401.
  10. 1 2 3 Gold, MR; Stevenson, D; Fryback, DG (2002). "HALYS and QALYS and DALYS, oh my: similarities and differences in summary measures of population health". Annual Review of Public Health. 23: 115–34. doi:10.1146/annurev.publhealth.23.100901.140513. PMID 11910057.
  11. "Disability weights, discounting and age weighting of DALYs". WHO.
  12. Prüss-Üstün, A.; Mathers, C.; Corvalán, C.; Woodward, A. (2003). "3 The Global Burden of Disease concept" (PDF). Introduction and methods: Assessing the environmental burden of disease at national and local levels. Environmental burden of disease. 1. World Health Organization. ISBN 92 4 154620 4.
  13. Kramer, Alexander; Hossain, Mobarak; Kraas,, Frauke (2011). Health in megacities and urban areas. Heidelberg: Physica-Verlag. ISBN 978-3-7908-2732-3.
  14. Mathers CD, Ezzati M, Lopez AD (2007). "Measuring the burden of neglected tropical diseases: the global burden of disease framework". PLoS Negl Trop Dis. 1 (2): e114. doi:10.1371/journal.pntd.0000114. PMC 2100367Freely accessible. PMID 18060077.
  15. "WHO methods and data sources for global burden of disease estimates 2000-2011" (PDF). World Health Organization. 2013. Retrieved Jul 27, 2016.
  16. Kim, SY; Lee, G; Goldie, SJ (Sep 3, 2010). "Economic evaluation of pneumococcal conjugate vaccination in The Gambia.". BMC infectious diseases. 10: 260. doi:10.1186/1471-2334-10-260. PMID 20815900.
  17. http://www.who.int/healthinfo/global_burden_disease/daly_disability_weight/en/
  18. http://www.who.int/healthinfo/global_burden_disease/GBD2004_DisabilityWeights.pdf
  19. Chant, Kerry (November 2008). "The Health of the People of New South Wales (summary report)" (PDF). Chief Health Officer, Government of New South Wales. Retrieved 2009-01-17.
  20. Zimbabwe, Ministry of Health and Child Welfare (December 2013). "Zimbabwe Weekly Epidemiological Bulletin" (PDF). World Health Organization, Government of Zimbabwe. Retrieved 2014-02-24.
  21. Masterson EA, Bushnell PT, Themann CL, Morata, TC (2016). "Hearing Impairment Among Noise-Exposed Workers — United States, 2003–2012.". MMWR Morb Mortal Wkly Rep 2016;65:389–394. Retrieved 05/04/2016. Check date values in: |access-date= (help)
  22. Global Burden of Disease
  23. World Bank (1993). World Development Report 1993: Investing in Health. Oxford University Press.
  24. Thacker SB, Stroup DF, Carande-Kulis V, Marks JS, Roy K, Gerberding JL (2006). "Measuring the public's health". Public Health Rep. 121 (1): 14–22. PMC 1497799Freely accessible. PMID 16416694.
  25. Kramer, Alexander , Md. Mobarak Hossain Khan, Frauke Kraas, (2011). Health in megacities and urban areas. Heidelberg: Physica-Verlag. ISBN 978-3-7908-2732-3.
  26. "Quantifying the burden of disease: the technical basis for disability-adjusted life years.". Bull World Health Organ. 72: 429–45. 1994. PMC 2486718Freely accessible. PMID 8062401.
  27. http://www.valueinhealthjournal.com/article/S1098-3015(11)01415-X/abstract
  28. http://bjp.rcpsych.org/content/197/5/348.full.pdf
  29. http://bjp.rcpsych.org/content/197/5/386.full

External links

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