A method to estimate a person or group health risks and benefits from additive and multiplicative factors

Attempts to lower health risks through targeted diet alteration and nutraceuticals (frequently accompanied by lifestyle modification) have been growing in recent years. A method of quantifying the benefits of such strategies, and the extent to which they can reduce the risk of contracting a variety of ailments or premature death, would be useful to all involved. However, an individual, apart from age and gender might also belong to several risk groups for which epidemiological data might be hard to find or nonexistent. Thus his or her overall personal risk or that of a particular group, and the efficacy of measures to reduce it, could be determined by several risk factors whose magnitudes are rarely if ever known exactly. Although other possibilities exist, we have assumed for simplicity that the factors’ effects on the overall risk are either additive or multiplicative, and developed a methodology to estimate the overall health risk based on the Expanded Fermi Solution. The combined personal or group’s risk is calculated from the estimated lower and upper bounds of each risk factor. Monte Carlo simulations generate random values within these ranges, which are added or multiplied to produce a set of hundreds of overall risk estimates. When the effects are additive the distribution of the generated estimates is approximately normal (Gaussian) and when multiplicative lognormal. The pertinent distribution’s mode is considered the best estimate of the overall risk. The calculation procedure has been automated and posted as a freely downloadable interactive Wolfram Demonstration where the parameters and ranges are entered with sliders on the screen. The Demonstration can also be used to create numerous age, dietary, occupational and behavioral scenarios and examine their implications. The method’s utility to assess health risks and benefits will increase when integrated with the results of epidemiological and clinical research presented as tables of absolute risks that can be added and subtracted, or risk factors that can be multiplied, accompanied by their confidence intervals.

► Monte Carlo method is used to estimate risk or benefits of foods and nutrients.
► Factors are entered as ranges to account for inherent uncertainties.
► Additive factors’ estimates have normal distribution and multiplicative lognormal.
► The mode of the Monte Carlo estimates distribution is the best estimate.
► The program is on the Internet as a freely downloadable Wolfram Demonstration.