Viewpoint A method to estimate a person or group health risks and benefits from additive and multiplicative factors Micha Peleg a, * , Mark D. Normand a and Maria G. Corradini b,1 a Department of Food Science, Chenoweth Laboratory, University of Massachusetts, Amherst, MA 01003, USA (Tel.: D1 413 545 5852; fax: D1 413 545 1262; e-mail: micha.peleg@foodsci.umass.edu) b Instituto de Tecnolog  ıa, Facultad de Ingenier  ıa y Ciencias Exactas, Universidad Argentina de la Empresa, Ciudad de Buenos Aires, Argentina Attempts to lower health risks through targeted diet alteration and nutraceuticals (frequently accompanied by lifestyle modi- fication) 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 ail- ments 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 over- all 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 sim- plicity that the factors’ effects on the overall risk are either additive or multiplicative, and developed a methodology to es- timate the overall health risk based on the Expanded Fermi So- lution. 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 hun- dreds 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 auto- mated and posted as a freely downloadable interactive Wol- fram 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 in- crease 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. Introduction A major concern of many people is how to reduce the health risks created by modern diet and lifestyle. With aging pop- ulation in many countries, heart ailments, cancer and other illnesses disorders have become increasingly an issue of public health (Gem, 2011). But the problem is not limited to the elderly. Children, adolescents and young adults, at least partly as a result of reduced physical activity and cal- ories rich diet are showing disorders that are unrelated to ag- ing. The same and other illnesses and disorders can also have different causes, of course. Heredity, air pollution, oc- cupational exposures and accidents are perhaps the most ob- vious. Yet, there is a growing pressure, exerted by public opinion, public health authorities and the medical profession to improve the population’s state of health and reduce the risk of illness through wholesome diet and physical activity. Food related health concerns and the changing consumer en- vironment in most developed countries are now increasingly addressed by the food industry, which is making great ef- forts to improve the wholesomeness of its products. Low fat, low sodium, low or no sugar, high fiber or Omega-3 rich food products and beverages are now common on the supermarket shelves, all aimed at reducing the health risk * Corresponding author. 1 Present address: Department of Food Science. Rutgers University, New Brunswick, NJ 08901, USA. 0924-2244/$ - see front matter Ó 2012 Elsevier Ltd. All rights reserved. doi:10.1016/j.tifs.2012.05.003 Trends in Food Science & Technology 28 (2012) 44e51