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Rothman (1976) uses the inheritance of the phenylketonuria gene and phenylalanine in the diet as an example of synergy breast cancer 60 mile walk san diego order fosamax on line. Comparative Quantification of Health Risks: Global and Regional Burden of Disease Attributable to menstrual irregularities order fosamax 35 mg fast delivery Selected Major Risk Factors women's health center medina ny generic fosamax 70mg online. Lopez, and others "Selected Major Risk Factors and Global and Regional Burden of Disease. Comparative Quantification of Mortality and Burden of Disease Attributable to Selected Major Risk Factors 395 Murray, C. Mortality Patterns in National Populations: With Special Reference to Recorded Causes of Death. Other Risk Factors as the Cause of Smoking-Attributable Mortality: Confounding in the Courtroom. International Statistical Classification of Disease and Related Health Problems, 10th ed. Lopez Modern epidemiological studies generally report confidence or uncertainty intervals around their estimates, often based on the variation observed in sample data. Estimates of the burden of disease and of risk factors, which extrapolate from specific data sources and epidemiological studies to population-level measures, are subject to a broader range of uncertainty because of the combination of multiple data sources and value choices. Hence, the reported uncertainty intervals should ideally include all sources of uncertainty, including those arising from measurement error, systematic biases, and modeling and extrapolation to compensate for incomplete data. In contrast to uncertainty analysis, which attempts to formally quantify the limitations of available data, sensitivity analysis examines how key analytic outputs vary when input quantities are systematically varied. Taking account of uncertainty in such value parameters as the rate of time preference used to discount future outcomes is not common. Even if there is empirical evidence on population preferences for discount rates and uncertainty in these estimates, investigators have argued that the choice of discount rate for use in analysis is essentially a social value judgment and should not include uncertainty (Morgan and Henrion 1990). Although there is uncertainty about the social value judgment and about its effects on decisions based on the analysis, varying the value deterministically in the analysis and performing a sensitivity analysis to examine the impact on the outcomes of interest is usually preferable to uncertainty analysis. Health state valuations, which link mortality information with information on nonfatal health outcomes in summary measures of population health, fit somewhat more ambiguously within the framework of uncertainty analysis. If we conceptualize a health state in terms of levels in multiple domains of health, health state valuation involves the weighting of these domains to arrive at an overall assessment of the health level associated with the state. These valuations, unlike 399 values such as time preference, do not have any clear normative basis; that is, while we might rely on philosophical arguments about intergenerational equity in choosing a discount rate, no obvious arguments pertain to the relative importance of mobility versus cognition in overall assessments of health levels. The choice of measurement strategies for eliciting health state valuations does sometimes introduce normative questions, but these pertain to additional considerations, such as concern for fair distribution, which are orthogonal to the assessment of the health state itself. Discounting Discounting future benefits is standard practice in economic analysis. Murray (1996) and Murray and Acharya (1997) review the theoretical and empirical arguments for and against discounting with a specific emphasis on health, including the possibility of negative discount rates. In addition to individual discounting and discount rates, policies dealing with risk must address the issue of benefits for different populations across time. As a result, these policies must address ethical and analytical dilemmas related to the valuation of current and future health and welfare in the form of social discount rates (Kneese 1999). Epidemiologists and demographers, who tend to focus on measuring or estimating years of life or health without "valuing" either, rarely use discounting. Murray and Acharya (1997) conclude that the strongest argument for discounting is the disease eradication and health research paradox. Such an excessive intergenerational "sacrifice" is a particularly powerful argument for discounting future health (Parfit 1984). Note that this argument does not claim that future welfare or health is less valuable than current welfare or health, but rather uses discounting as a tool to avoid excessive sacrifice by the current generation to the point of investing all resources in future health. Murray and Acharya argue that the social discount rate should be smaller than the return on capital investment, but note that the choice of a discount rate for health benefits, even if technically desirable, may result in morally unacceptable allocations between generations (see also Dasgupta, Mдler, and Barrett 1999). Panel on Cost-Effectiveness in Health and Medicine has recommended that health economic analyses use a 3 percent real discount rate to adjust both costs and health outcomes (Gold and others 1996), but that analysts should examine the sensitivity of the results to the discount rate. This choice was based on a number of studies that indicated a broad social preference to value a year lived by a young adult more highly than a year lived by a young child or an older adult (Murray 1996).
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