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3. Common metrics for integration of risks and benefits

The purpose of the Qalibra framework is to provide methodology and software for quantitative integration of health risks and benefits, as in Tiers 3 and 4 of the BRAFO tiered approach. Quantitative integration requires the use of a common metric for aggregation and comparison of different adverse and beneficial health effects.

Ideally a risk-benefit assessment should consider all relevant aspects of health, such as mortality, morbidity, and quality of life. The challenge is how to add up different kinds of health effects. How to compare, for example liver cancer with a gastrointestinal infection? Or, how to compare death with a decline in cognitive functioning? The solution is to weigh or value these different health effects using a valuation function that rates all health effects on the same scale.

Summary measures of population health combine information on mortality and non-fatal health outcomes to represent the health of a particular population as a single number. Also for the quantification of the net health effect of a food or ingredient of interest, both positive and negative effects need to be expressed in the same endpoint of interest. Several methods have been developed for evaluating the impact of illness and disability on public health, including monetary methods and methods that quantify disease burden as a result of (premature) death and impaired quality of life such as disability-adjusted-life-years (DALYs), quality-adjusted-life-years (QALYs), and healthy-life-expectancy (HALE) (Havelaar et al.   2000; Ezzati et al.   2003; Ponce et al.   2000) . In the case of cost benefit analysis health state is often expressed in a monetary value such as Willingness To Pay (WTP) or Willingness To Accept (WTA). Ponce et al. (Ponce et al.   2001) and Wong et al. (Wong et al.   2003) provide a general review of such metrics. Qalibra Deliverable D3 also reviewed several health metrics.

The choice of the common currency and whether to apply such things as age weighting and discounting is not trivial. Ethical and equity issues play a role. Anand and Hanson (1998) nicely show that if the DALY (but also the QALY) measure is used, one would favour saving the life of a baby girl over that of a baby boy because the life expectancy of women is larger. The same goes for extending the life of a man in a wheelchair compared to extending the life of an equally old man who can walk. More disability adjusted life years will be gained when treatment is given to the able man. Nord (2005) would argue that the more weight should be given to the life years gained by the disabled man because it would be fair that both man could experience a comparable number of quality-adjusted life years.

The choice of health measure and associated parameter values such as disability weights and discount rate give, deliberate or not, priority to one age- or disease subgroup at the expense of another. Therefore, it is important to be transparent about the choices that are made. Not only the final DALY (or other summary measure) should be presented but also intermediate variables such as incidences, and these are provided by the Qalibra software.

DALYs and QALYs were chosen as the common metrics for use in the Qalibra framework and software. DALYS and QALYs are commonly used integrated health measures. It was decided not to include economic measures such as WTP and WTA, because they are associated with additional difficulties in interpretation, particularly because they may reflect wealth of respondents more than differences in valuation of health.

The use of QALY or DALY measures in a risk-benefit assessment is illustrated in Figure 1. This illustrates how the net health impact of a dietary change is obtained as the difference between the QALY or DALY calculations for the reference and alternative scenarios. It also indicates the types of data that are required for using these metrics, including QALY or DALY weights, age of onset and duration for each health effect. In addition, information is needed on the recovery and mortality rates for each disease or health state considered (see later).

Figure 1. Diagrammatic representation of the calculation of the net health impact of a dietary change (from reference to alternative scenario) on a single individual, using quality-adjusted life years (QALYs). Calculation using disability-adjusted life years (DALYS) is equivalent but with the vertical scale reversed, so that 0 represents full health and 1 represents death.