Introduction
Within EDPHiS, it is necessary to have common methodologies and understanding of the
different concepts that are intrinsic to the overall study. A need for a universal understanding of
exposure has been identified following Martie’s realisation that the idea of exposure as used in
some of the DPSEEA maps (notably the DPSEEA map for road accidents where exposure is
considered to be “Transfer of kinetic energy from moving vehicle to pedestrian”) though accurate
had limited usefulness with respect to achieving the objectives of EDPHiS.
The aim of this note is to describe the development of a concept of exposure that more closely
serves the needs of the project. As discussed in the EDPHiS meeting dd 29 th May 2008, what is
needed is:



A common concept of what exposure is, that is broad enough to encompass the very wide
range of factors – with positive as well as negative effects – that EDPHiS will tackle.
This concept must distinguish between ‘state of environment’ and ‘exposure’
The concept must be able to help identify the influences on exposure: factors that
influence how people interact with the environment
Most of us have a background in traditional pollution studies within the context of environmental
and occupational exposure and most people are somewhat familiar with the concept of exposure
as it relates to these. This suggests that a logical approach in developing a common concept of
exposure for EDPHiS would be to start from this common ground.
Exposure in Traditional Pollution Studies
Some definitions of exposure in traditional pollution studies include:
 Concentration or amount of a particular agent that reaches a target organism, system, or
(sub)population in a specific frequency for a defined duration (IPCS, 2004)
 Contact of people with an environmental stressor for a specific duration of time (Figure 1).
A stressor is any biological, physical, or chemical agent that leads to an adverse impact. A
receptor is a living organism or group of organisms. (US EPA).
 Exposure in terms of occupational and environmental medicine is the process of contact
between an individual and a substance. Exposure assessment is “the science involved in
characterising the pathways, time course and magnitude of an individual’s contact with the
material under study (Semple, 2005).
Distribution of
stressors in time &
space
EXPOSURE
Distribution of receptor
in time and space
US EPA
MODEL
Figure 1 Exposure in traditional pollution studies
There are some common elements of exposure as defined for traditional pollution studies:
 There is often an implicit negative connotation associated with exposure. This is linked to
the fact that in these fields of study exposure assessment is often undertaken for risk
assessment or epidemiological studies where the focus is on the link between exposure
and a negative health outcome.
 A target population is explicitly identified
 There is a time element
 There is a tangible agent (solid, gas, liquid) to which the population is exposed.
These last two elements allows one to speak of the intensity, frequency and duration of exposure.
The intensity of exposure relates to the concentration of the material that the population is
exposed to and is expressed as mass of the substance per unit volume/area. The time element
allows the assessment of exposure within the context of different parts of a population’s lifetime.
The different time periods have different relevancies. For instance, in the work environment, this
time period could be the time it takes to complete a particular work-task, the exposure over an 8hour working day (8-hr. Time weighted average TWA) or cumulative exposure over the entire
period of the worker’s life.
A concept of exposure for EDPHiS
Our concept of exposure is encompassed within the Oxford definition….
1. The action of exposing; the fact or state of being exposed. a. The action of uncovering or
leaving without shelter or defence; unsheltered or undefended condition. Also, the action of
subjecting, the state or fact of being subjected, to any external influence.
Looking at the second part of the definition “the action of subjecting…to any external influence.” It
differs from the idea of exposure as used in traditional air pollution studies in that:
 It is more generalised – (‘external influence’ is a useful general term. For external
influence we can read ‘environment’ or ‘a state of the environment’. Further, it
encompasses both tangible and intangible elements. This is significant to EDPHiS given
the intangibility of some of the elements we need to assess exposure to, e.g. Elements
that influence mental health and well-being.
 There is no negative connotation associated with it (thus the idea of a positive or a
negative exposure leading to favourable or unfavourable outcome)
 There is no named target population
 There is no time element
 It can be either active or passive (active: the action of subjecting to; passive: the state/fact
of being subjected to…)
The first part of the Oxford definition is more narrow dealing with the action of removal of a
protective element and suggestive of negative consequences arising due to this action. This is
not relevant or useful for our purposes. We will focus on the second form of the definition only.
So at its most basic, exposure is simply defined as “the action of subjecting or being subjected to
any external influence” where time can be seen as an intrinsic element in the process. In order to
quantify exposure and express it within its full context, this time element needs to be explicitly
stated. Furthermore, within EDPHiS a target population has been defined: children from preconception to 8 years. This target population takes a passive role in its exposure so it is subjected
to an external influence.
Exposure for the purposes of EDPHiS can then be defined as “the state or fact of a population
being subjected to any external influence over a specified period of time.”
In DPSEEA this ‘external influence’ (EI) is the ‘state of the environment’ (ES) e.gs. subjected to
obesogenic environment, dangerous roads etc, greenspace (promoting physical activity). The
nature of the health impact (positive or negative) will naturally be a consequence of the
environmental state whether it promotes good health or not. This environmental state is partly
influenced by environmental policy. In EDPHiS the ‘population’ is children from pre-conception to
8 years. Sub-populations can be identified from these. The ‘specified period of time’ will vary
according to the circumstances of exposure. This concept of exposure where the population
takes a passive role in exposure can be represented in Figure 2 below.
POLICY
Children
Aged 0 – 8
(Distribution in
space & time)
Figure 2. Exposure in EDPHiS
Back to traditional pollution studies
Going back to exposure in traditional pollution studies, there are other useful concepts and
terminologies that can be adopted or adapted here.
Exposure Scenario
A combination of facts, assumptions, and inferences that define a discrete situation where
potential exposures may occur. These may include the source, the exposed population, the time
frame of exposure, microenvironment(s) and activities (WHO/IPCS)
Exposure metric
The exposure metric is an indicator of exposure. It is usually related to a relevant health outcome
of exposure e.g the respirable fraction (metric) and respiratory disease (health outcome). To
ensure that relevant dose-response relationships can be established, the exposure metric should
be carefully chosen to avoid misclassification of exposure which may occur when non-specific
exposure indicators are used and it should be as close to actual exposure as practically possible
E.g. In air pollution studies two choices of exposure metrics for exposure to air pollutant are (1)
environmental exposure: environmental concentration of the contaminant(µg/m 3) and (2) personal
exposure: concentration of contaminant in the personal breathing zone (µg/m 3). The latter metric
is a more accurate measure of personal exposure. However, it is not always possible to obtain
the most accurate indicator of exposure and in such cases the uncertainty associated with the
exposure metric needs to be stated.
Micro-environment
A micro-environment is a small-scale, local, or specialised environment, especially as a distinct
part of a larger environment; the immediate environment of an organism, species (Oxford). In
traditional population studies, it is usually defined as surroundings that can be treated as
homogenous or well characterised in the concentrations of an agent (Wayne and Ott, 2007). So
it is usually defined, among other things, in terms of the pollutant source, pollutant
concentration, distribution of an environmental pollutant within a specified area. Due to the
distinct nature of a micro-environment, it will have a distinct exposure associated with it.
This can be characterised by determining the amount of time an individual/population spends
within the micro-environment exposed to the pollutant of interest and identifying the factors
influencing these. This can be obtained using Activity pattern data.
Activity pattern data
Information of human activities used in exposure assessment; these may include a description of
the activities, frequency of activities, duration of time spent performing activities and
microenvironment in which activity occurs.
These concepts as they are used in traditional pollutant studies is illustrated below. The basic
concept is that the time-weighted average exposure is a sum of partial exposures in the visited
microenvironments. Partial exposure is determined by the concentration and the time spent in the
microenvironment.
Ilustration 1:Exposure scenario:
Microenvironments:
Exposure metric:
Children of school age (6-10 years) living in a European city and
potentially exposed to an air pollutant.
outdoors, home, school, other indoor, transportation.
Environmental concentration of pollutant.
Table 1. Details of the microenvironment in terms of concentration of the pollutant and
time-activity patterns of children of school age 6-10 years
Microenvironments
Outdoors
Home
School
Other indoor
Transportation
Concentration
pollutant
(mass/m3)
Coutdoors
Chome
Cschool
Cother indoor
Ctransport
Partial exposure in each micro-environment is given by:
Ei  Ci Ti
where, Ei = exposure in microenvironment, i
Time spent in each
microenvironment (hours)
Toutdoors
Thome
Tschool
Tother indoor
Ttransport
i = outdoors, home, school, other indoor, transportation
The total exposure is given by:
ETOTAL 
 Ei
where,
ETOTAL = Total exposure for the exposure scenario.
This can be represented diagrammatically as shown in Figure 1:
AMBIENT AIR POLLUTION
CHOME
COUT
COUTTOU
CHOMETHOME
CSCH
CSCHTSC
COTH IND
CTRANS
CTRANSTTRANS
COTH INDTOTH IND
H
T
TOUT
THOME
TSCH
TOTH IND
TTRANS
TOTAL EXPOSURE:
COUTTOUT + CHOMETHOME + CSCHTSCH + COTH INDTOTH IND + CTRANSTTRANS
DOSE
stressor:
receptor:
HEALTH EFFECTS
Figure Representation of Illustration 1 showing composite exposure as the combined
exposure in different microenvironments: OUT: outdoors; HOME: home; SCH: school;
OTH IND: other indoors; TRANS: transportation
This model has mainly been used and validated for air pollution. However, the concepts used
can be extrapolated to exposure to any environmental factor whether positive or negative.
Exposure for EDPHiS, DPSEEA maps
In applying such a model to the ‘states to exposure’ section of the DPSEEA maps, the first step
would be to define the exposure scenario. This will usually be quite broad and cover all the
µenvironments (circumstances) within it as well as the study population. Next the state of the
environment (external influence) to which exposure is being assessed should be clearly defined:
e.gs: state of the environment (from DPSEEA maps):
 for obesity (diet):- Inadequate (or complicated) food labelling: nutritional information and
calorie content unknown or unclear to consumer; portion size information unclear;
 for obesity (physical activity):- School grounds conducive to physical activity: Fun;
Facilities for storing bikes and scooters securely; Natural play areas: natural trees & plants
at front of building, natural landscaping
 for mental health & well-being:- exposure to bullying at school; etc.
Next all the different µenvironments within the scenario should be described. For each
µenvironment the relevant sub-population (child age-group) associated with it should be stated
since all µenvs within an exposure scenario will not be relevant to all population subsets. e.g. For
road traffic accidents a possible ‘state’ to which children are exposed is roads with heavy traffic
while walking to school. This µenvironment may only be relevant to the sub-population, children
7-8 years. Also, the exposure metric (indicator of exposure) should also be described for each
µenvironment e.g. for obesity (diet): time spent in each µenvironment.
The next stage would be to define the ‘partial exposure’ associated with the respective
µenvironments. Information for this will come from details of the µenvironment and activity pattern
data of the target population.
Finally, all
scenario.
partial exposures are combined to determine total exposure within the exposure
It is important to recognise that the overall exposure is always a summation of the exposure from
all the different µenvs. Where data for a particular µenv within a scenario is not available, it may
be necessary to make some assumptions or use a data source with the closest similarity to the
µenv we are assessing exposure within. Also, the element of uncertainty, which depends on data
availability and assumptions made, must be reported.
How these concepts can be used within the ‘states to exposure’ section of the DPSEEA maps are
illustrated below.
Illustration 2 - OBESITY (diet)
Scenario:
Children age 6-8 in Scotland who attend school
µenvs:
Home; school: private, public, special schools; leisure time: theme parks;
cinema;
Exposure metric:
time spent in µenvironment
Exposed to:
high caloric food; too many calories (i.e. caloric intake > caloric
expenditure)
Data requirements:
 Frequency of “meal” intake in each environment (meal intake as function of time; (“meal” =
snack, lunch, dinner etc))


Caloric value of meal in each environment (kcal)
Time spent in each µenvironment (hours)
Illustration 3 - ROAD TRAFFIC ACCIDENTS
Scenario:
Children age 6-8 in Scotland who attend school
µenvs:
travel to/from school: walk; car; public transport, cycle other; to/from playground;
playing around the neighbourhood
State of the
environment:
Roads on which cars are driven at speeds inappropriate to line of sight or risks
to other road users (from DPSEEA map for road traffic accidents).
A more useful description of this state is to define the accident rate of the road
used where accident rate is defined by Wolfe 1982 as:
Accident rate 
Number of accidents that take place on dangerous roads *
Time spent on dangerous roads
* Roads on which cars are driven at speeds inappropriate to line of sight or risks
to other road users
Exposure metric: Time spent on roads with accident rate of ----
Data requirements:
 Prevalence of different road types in each µenv.
 Accident rates on the different road types in each µenvironment
 Time spent on each of these road types
Note: It is not certain which is more relevant duration or frequency
Other issues
Exposure definitions in the DPSEEA maps
It may be necessary to re-define the exposure stage of some of the DPSEEA maps to obtain a
more relevant exposure metric. For instance, the DPSEEA map for road traffic accidents looks
at exposure as: Transfer of kinetic energy from moving vehicle to pedestrian. A more useful
definition by Wolfe (1982) defines exposure to the risk of a road traffic accident as:
A measure of the frequency of being in a given traffic situation, which number can be used as the
denominator in a fraction with the number of accidents which take place in that situation as the
numerator, thus producing an accident rate or risk of being in an accident when in that situation .
Probabilistic approach
It is preferable to use a probabilistic approach to estimate exposures. In this approach
distributions rather than point estimates are used where possible. For instance, in the example
for Obesity the required data can be represented as distributions. Assuming a triangular for all
required data, the distributions can be defined as indicated in Table 2.
Table 2: Data requirements for probabilistic approach to exposure
Data requirement
Frequency of meal intake in µenvironment, Fi
Caloric value of meal in µenvironment, CVi
Time spent in µenvironment, Ti
Distribution
range= 1 – 7 meals /hour;
average = 4 meals/hr
range= 300 – 600 kcal;
average = 200 kcal
range= 1 – 3 hours;
average = 2.5 hours
The partial exposure for µenv, i is given by:
Ei  Ti x Fi x CVi
where:
Ei : amount of calories population is exposed to in µenvironment, i
In the calculation of Ei, the distribution of each element of the equation is sampled repeatedly
depending on the number of simulations chosen. The result is a distribution of exposure
representing all possible exposures in µenvironment i. This approach can facilitate uncertainty
analysis
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References
IPCS (2004). International Programme on Chemical Safety. Risk Assessment Terminology. IPCS
harmonization project ; document no. 1. (WHO)
Semple S. (2005) Assessing occupational and environmental exposure. Occup Med (Lond)
55:419–424.
US EPA (2007). A Conceptual Framework for U.S. Draft report. National Exposure Research
Laboratory. Office of Research and Development U.S. Environmental Protection Agency
Cincinnati, OH 45268.
Wolfe A (1982). The concept of exposure to the risk of road traffic accident and an overview of
exposure data collection methods. Accid Anal & Prev 14(5): 337-340.