Implementing food-based dietary guidelines for - United Nations ...

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level of exposure. Furthermore, the BMD can be used
on data from which an NOAEL cannot be derived;
however, the dose exposure spacing for the NOAEL
approach is not always useful for the BMD. It is thought
or hoped by its advocates that the advantages of the
BMD would provide an incentive for more rigorous
studies that would decrease both scientific and mathematical
uncertainty. These advantages have been
discussed by a number of investigators [11, 12].
It is possible to apply uncertainty factors as part of
the BMD approach, for example, to allow for interindividual
differences. Unfortunately, datasets from
studies designed to support the use of the NOAEL
approach to setting a UL are not easily used for the
BMD approach.
Categorical regression
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FIG. 1. Benchmark dose (BMD) modeling: A representation
of a benchmark dose–response curve of an adverse effect in a
population. The 95% confidence interval has been calculated
from all the plotted data points, and the horizontal dotted line
represents the derivation of an intake, the lower benchmark
dose (LBMD), at which there is a 2.5% response or risk of
an adverse effect occurring in a population. Hypothetical
no observed adverse effect levels (NOAELs) and lowest
observed adverse effect levels (LOAELs) are indicated, as
are the lower bound benchmark dose (BMDL or LBMD),
uncertainty factor (UF), and the upper level of intake (UL).
Source: International Programme on Chemical Safety [2],
modified by Przyrembel for the Joint FAO/WHO Task Force
on Nutrient Risk Assessment [1]
Categorical regression [11] can use combined qualitative
and quantitative data. It fits ordinal data (i.e.,
outcomes that are ranked by severity of effect) to a
dose–response model that can be applied to a benchmark
dose–response approach. It can take into consideration
the severity and duration of exposure of
effect (i.e., the effects of different periods of exposure
to single levels of intakes, which is a common design
feature in nutritional studies), use data from multiple
studies, and address a variety of endpoints. As with the
BMD, it gives equal weight to studies and their data,
though it is possible, as with the other approaches,
to evaluate the quality of the studies against objective
criteria. For example, data amenable to this approach
are those from histopathological studies in which the
evolution of architectural damage is monitored in relation
to the period of exposure. This approach therefore
provides information about the evolution and mechanisms
of effects at single exposure levels over time; this
would be helpful in assessment of prolonged exposure
at constant levels of intake.
Exposure assessment and risk characterization
These are the last two stages of risk assessment.
Exposure/intake assessment is the measurement or
estimation of exposure to a chemical by any route for
the population or its subgroups (e.g., toddlers, children,
adults, and ethnic groups). It includes consideration of
the pattern, frequency, and duration of exposure and it
informs the next step of risk characterization.
Risk characterization (sometimes called “advice for
decision making”) is the integrative consideration of
hazard identification, hazard characterization, and
exposure assessment to predict whether effects in
humans are likely and the nature and severity of such
effects. If data permit, it may include identification of
the proportion of the population affected and the existence
of any vulnerable subpopulations. The product of
this exercise is an overall report describing the process,
including a description of the nature of the risk, its
extent, and all the associated uncertainties [8].
Risk management and risk communication
P. J. Aggett
Risk management and risk communication are the last
two elements of risk analysis. Risk management has two
main functions. The first, as has been mentioned, is to
frame the question, or set the task for the risk assessors;
the second is to act on the risk assessment. This
involves option assessment, which is the identification
and assessment of possible control options; implementation
of management decisions; and monitoring and
evaluation of the effectiveness of the risk management
measure.
Although risk management and risk assessment are
discrete activities, it is accepted that the system works
most effectively if there is some interaction between
the stages to ensure that the assessment is accurately
conveyed between the two stages and is properly
understood. However, the prime intention of separating
risk assessment and risk management is to protect
the integrity of the scientific and objective assessment
by the expert risk assessment process, leaving those
responsible for risk management to take into account
other issues, such as the concerns and interests of other
stakeholders.
Finally, risk communication represents the exchange
of information taking place throughout the process,