There are a myriad of chemicals in food products consumed by populations. Each chemical in its own right may not be harmful to the population, but in combination with other chemicals, there may be risk of high levels of exposure to potentially harmful substances.
An effective probabilistic exposure assessment needs to handle the variability and uncertainty of this real world situation. Variability characterises the natural differences between consumers' characteristics and habits. These are natural variations such as people's bodyweight, different people eating different things or people changing their own eating habits from day to day. Note that the variability in these values would not be reduced by further measurement.
Uncertainty on the other hand is an actual lack of information about the situation. The exact concentration of a pesticide on a food item being consumed is not known exactly (this data is not measured for every single food item), hence the analyst is genuinely uncertain as to the value of the chemical concentration of each food item. The uncertainty of a situation could be reduced by further measurement, but this is not always practical or feasible.
Uncertainty and variability have to be treated using a probabilistic method such as the Monte Carlo simulation. Probabilistic methods are well established in other areas of risk analysis such as financial risk. By analysing large samples of the population's eating habits, including quantifying the concentration of the contaminants, hazards and chemicals in their diet, we get a better picture of how people's health is affected by what they eat.
|
