Years of life lost

It is cmcial that an economic study includes the health-related consequences of morbidity and mortality. These could be measured as number of years of life lost, reductions in health status, and quality of remaining years of life due to morbidity for both patients and informal carers. These consequences should also be valued to reflect the preferences of individuals and society for changes in the length and quality of life or health. 

Furthermore, health policy makers in Europe and Canada can point to widely respected statistics gathered annually by the Organization for Economic Cooperation and Development, according to which the United States ranks remarkably low in the OECD on many standard health status indicators, such as the infant mortality rate, life expectancy at birth and at age 60, and potential years of life lost per 100,000 population, that is, life... 

One potential difficulty of cost-benefit analysis is that it requires researchers to express an intervention s costs and outcomes in the same units. Thus, monetary values must be associated with years of life lost and morbidity due to disease and with years of life gained and morbidity avoided due to intervention. Expressing costs in this way is obviously difficult in health care analyses. Outcomes (treatment benefits) may be difficult to measure in units of currency. Translating disease and treatment outcomes into monetary measures may be more difficult than translating them into clinical outcome measures, such as years of life saved or years of life saved adjusted for quality. 

Incidence. In the first option, the common measure of stochastic response from exposure to radionuclides and hazardous chemicals would be incidence, without any modifications to account for such factors as differences in lethality fractions for responses in different organs or tissues or expected years of life lost per fatality. Such modifications are intended to represent differences in the severity of different stochastic responses. 

One difficulty with genetic-risk estimation is that the end point is diffuse, both in the diversity of effects and in their time distribution. Cancer-risk estimation differs sharply, in that there are distinct end points. The expectation of survival and death rates associated with different kinds of cancer are much better known, it is simpler for an increase in cancer incidence to be expressed in quantitative units, such as years of life lost, than for this to be done for genetic disorders, although there have been recent attempts to do it. Furthermore, there is a... 

Bipolar disorder (BAD, manic-depressive illness) is a severe and chronic illness, which is a major public health problem, in any given year affecting approximately 1-3% of the US population (Narrow et al., 2002). In the World Health Organization Global Burden of Disease study, BAD ranked sixth among all medical disorders in years of life lost to death or disability worldwide, and is projected to have a greater impact in the future (Murray and Lopez, 1996). 

Some category indicators can be further cross-aggregated and compared on a natural science basis. Further aggregation can be to calculate the overall sum of years of human life lost, for example, the years of life lost that are attributable to climate change, potential carcinogenic effects, noise, traffic accidents, etc. 

Metrics such as DALYs are derived from statistics for mortality. These are dominant for cancer effects. Equivalent numbers of DALYs, calculated using social science techniques, are provided for the years of life lost for morbidity (nonfatal) effects. Further developments remain necessary for noncancer toxicological effects. Although some DALY-based characterization factors are available from epidemiological data for respiratory illness, including for secondary particulate matter (nitrates and sulfates). 

Finally the added value of the years of life lost (U) caused by the health damage terminal j, which is aroused by the dust emissions in the space model during a year, can be obtained via equation (4) and equation (5). 

Table 4 shows that the years of life lost caused by dust emissions in the construction phase is 2.7014 years according to the table above. The society s WTP value is RMB208, 000. 

After determining the health damage caused by dust and willingness to pay values, we find that coal miners experience more years of life lost than construction workers. According to their economic significance and model evaluation, the results indicate that coal dust poses a serious health risk and can cause considerable damage to the human body. 

A measure of the relative impaet of various diseases and injuries on a defined population. Potential years of life lost due to a particular cause is the sum of the years that the persons in a population would have lived had they experienced normal life expectaney. 

Some people see this tremendous and increasing toll as an unavoidable cost of progress . As the number of cars increases and as the world population increases, so will the number of crashes and victims. Thus, given the current trends, death from a motor-vehicle crash is projected to become the third most common cause of death by 2020 (less than fifteen years from now), versus the 9 place in 1990 (over fifteen years ago) (Fallon and O Neill, 2005). The data in Table 1-1, of the leading causes of death in the U.S., show that in the U.S. this future is almost here. In fact, motor-vehicle crashes are the number one cause of death in the U.S. for people of ages 4-34, and the third leading cause in terms of years of life lost. The measure of years of life lost also has significant economic implications, especially when calculated in terms of composite measures that include the quality of life (such as DALY -disability-adjusted life years). 

Table 1-1. Leading causes of death in the U.S. as a function of age, based on National Center for Health Statistics Mortality Data 2002. Motor-Vehicle Traffic Crashes are in Bold. Total annual deaths = 4,886,426. Total years of life lost = 37,341,511 (from BLS, 2003 NHTSA, 2005b). 

Infants Under 1 Toddlers 1-3 Young Children 4-7 Children 8-15 Youlii 16-20 Young Adults 21 -24 Other Adults Elderly 65+ All Ages Years Of Life lost... 

The risk exposure of the young is not confined to developing nations. In the United States, road crashes are the single most frequent cause of death for every year of age from the ages of 11 through 27. Further, while deaths from road crashes are the 11th most common cause (the first time out of the top 10 in the United States), they are 5th in terms of years of life lost, which takes into account the age distributions of the various causes of death. ... 

When the measures of years of life lost and disability-adjusted life years are used, there can be no dispute that road crashes comprise one of society s most prevalent diseases—the disease of mobility—and constitute one of our most prevalent public health problems. Yet, most nations continue to drive their traffic safety strategies and programs from their road transport-based institutions. 

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