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Disease burden is the impact of a health problem as measured by financial cost, Mortality rate, morbidity, or other indicators. It is often quantified in terms of quality-adjusted life years (QALYs) or disability-adjusted life years (DALYs). Both of these metrics quantify the number of years lost due to disability (YLDs), sometimes also known as years lost due to disease or years lived with disability/disease. One DALY can be thought of as one year of healthy life lost, and the overall disease burden can be thought of as a measure of the gap between current health status and the ideal health status (where the individual lives to old age without disease and disability).
According to an article published in The Lancet in June 2015, low back pain and major depressive disorder were among the top ten causes of YLDs and were the cause of more health loss than diabetes, chronic obstructive pulmonary disease, and asthma combined. The study based on data from 188 countries, considered to be the largest and most detailed analysis to quantify levels, patterns, and trends in ill health and disability, concluded that "the proportion of disability-adjusted life years due to YLDs increased globally from 21.1% in 1990 to 31.2% in 2013."
The environmental burden of disease is defined as the number of DALYs that can be attributed to environmental factors. Similarly, the work-related burden of disease is defined as the number of deaths and DALYs that can be attributed to occupational risk factors to human health. These measures allow for comparison of disease burdens, and have also been used to forecast the possible impacts of health interventions. By 2014, DALYs per head were "40% higher in low-income and middle-income regions."
The World Health Organization (WHO) has provided a set of detailed guidelines for measuring disease burden at the local or national level. In 2004, the health issue leading to the highest YLD for both men and women was unipolar depression; in 2010, it was lower back pain. According to an article in The Lancet published in November 2014, disorders in those aged 60 years and older represent "23% of the total global burden of disease" and leading contributors to disease burden in this group in 2014 were "cardiovascular diseases (30.3%), malignant neoplasms (15.1%), chronic respiratory diseases (9.5%), musculoskeletal diseases (7.5%), and neurological and mental disorders (6.6%)."
In 2004, the World Health Organization calculated that 1.5 billion disability-adjusted life years were lost to disease and injury.
| Infectious and parasitic diseases, especially lower respiratory tract infections, diarrhea, AIDS, tuberculosis, and malaria | 37% | 26% | 9% | 6% | 5% | 3% |
| Neuropsychiatric conditions, such as depression | 2% | 13% | 3% | 19% | 5% | 28% |
| Injuries, especially motor vehicle accidents | 14% | 12% | 18% | 13% | 18% | 10% |
| Cardiovascular diseases, principally heart attacks and stroke | 14% | 10% | 35% | 23% | 26% | 14% |
| Premature birth and other deaths (infant mortality) | 11% | 8% | 4% | 2% | 3% | 2% |
| Cancer | 8% | 5% | 19% | 11% | 25% | 13% |
To measure the environmental health impact, environment was defined as "all the physical, chemical and biological factors external to a person, and all the related behaviours". The definition of modifiable environment included:
Certain environmental factors were excluded from this definition:
The exposure-based approach, which measures exposure via pollutant levels, is used to calculate the environmental burden of disease. This approach requires knowledge of the outcomes associated with the relevant risk factor, exposure levels and distribution in the study population, and dose-response relationships of the pollutants.
A dose-response relationship is a function of the exposure parameter assessed for the study population. Exposure distribution and dose-response relationships are combined to yield the study population's health impact distribution, usually expressed in terms of incidence. The health impact distribution can then be converted into health summary measures, such as DALYs. Exposure-response relationships for a given risk factor are commonly obtained from epidemiological studies. For example, the disease burden of outdoor air pollution for Santiago, Chile, was calculated by measuring the concentration of atmospheric particulate matter (PM10), estimating the susceptible population, and combining these data with relevant dose-response relationships. A reduction of particulate matter levels in the air to recommended standards would cause a reduction of about 5,200 deaths, 4,700 respiratory hospital admissions, and 13,500,000 days of restricted activity per year, for a total population of 4.7 million.
In 2002, the WHO estimated the global environmental burden of disease by using risk assessment data to develop environmentally attributable fractions (EAFs) of mortality and morbidity for 85 categories of disease. In 2007, they released the first country-by-country analysis of the impact environmental factors had on health for its then 192 member states. These country estimates were the first step to assist governments in carrying out preventive action. The country estimates were divided into three parts:
Necessary data include prevalence data, exposure-response relationships, and weighting factors that give an indication of the severity of a certain disorder. When information is missing or vague, experts will be consulted in order to decide which alternative data sources to use. An uncertainty analysis is carried out so as to analyze the effects of different assumptions.
Generally, it is not possible to estimate a formal confidence interval, but it is possible to estimate a range of possible values the environmental disease burden may take based on different input parameters and assumptions. When more than one definition has to be made about a certain element in the assessment, multiple analyses can be run, using different sets of definitions. Sensitivity and decision analyses can help determine which sources of uncertainty affect the final results the most.
Among the investigated factors, long-term PM10 exposure have the greatest impact on public health. As levels of PM10 decrease, related disease burden is also expected to decrease. Noise exposure and its associated disease burden is likely to increase to a level where the disease burden is similar to that of traffic accidents. The rough estimates do not provide a complete picture of the environmental health burden, because data are uncertain, not all environmental-health relationships are known, not all environmental factors have been included, and it was not possible to assess all potential health effects. The effects of a number of these assumptions were evaluated in an uncertainty analysis.
DALYs are a simplification of a complex reality, and therefore only give a crude indication of environmental health impact. Relying on DALYs may make donors take a narrow approach to health care programs. Foreign aid is most often directed at diseases with the highest DALYs, ignoring the fact that other diseases, despite having lower DALYs, are still major contributors to disease burden. Less-publicized diseases thus have little or no funding for health efforts. For example, maternal death (one of the top three killers in most poor countries) and pediatric respiratory and intestinal infections maintain a high disease burden, and safe pregnancy and the prevention of coughs in infants do not receive adequate funding.
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