Environmental Health Criteria 214

HUMAN EXPOSURE ASSESSMENT
investigation, especially during the design and data analysis stages.
Sample size determination is an important use of statistics during the
planning of an exposure assessment study. Numerical and graphical
descriptive statistics can be used to summarize exposure data and
perform preliminary analyses of relationships between and among
exposure variables. In many cases, exposure data are approximately
normally or lognormally distributed and can thus be readily
incorporated into standard parametric statistical inference methods
such as estimation and hypothesis testing. In addition, other
parametric statistical models such as ANOVA, linear regression and
logistic regression can be used to quantify associations among
exposure measures. In situations where the number of observations is
small or the data cannot be transformed to an approximately normal
distribution, non-parametric methods such as the sign, Mann-Whitney
and Kruskal-Wallis tests can be used to test hypotheses.
5. HUMAN TIME-USE PATTERNS AND EXPOSURE ASSESSMENT
5.1 Introduction
Methods for the collection and application of time-use data in
exposure studies are critically reviewed in this chapter. All methods
have their limitations. With appropriate quality assurance, however,
information on time use and activity patterns collected by
questionnaire, diary, interview, observation or technical means can be
very valuable for interpreting and modelling exposures. Although the
methodologies of time-activity data collection are universal, they
need to be applied and their vocabularies selected keeping in mind the
population and culture of concern and objectives of the study.
Accurately and reliably documenting the time-activity patterns of the
general and target populations are important components of
understanding and mitigating human exposure (see Table 15).
People's activity patterns, eating and drinking habits, and
lifestyle characteristics must be superimposed over concentrations in
environmental media before it is possible to derive realistic
estimates of actual human exposure. Too often in the past, pollutant
concentrations in a particular medium have been assumed to represent
exposure, only for it to be found later that they did not provide an
accurate picture owing to modifying factors such as the time people
spend indoors rather than outdoors, food preparation and cooking, and
use of bottled water instead of tap water. Experience has shown that
exclusive reliance on central monitoring sites (e.g., urban air
pollution monitoring sites, samples from drinking-water reservoirs)
and bulk sampling procedures (e.g., spot checks for pesticides in
food) for determining human exposures may be insufficient in many
cases.
In an exposure context, data about human time use and activity
patterns (often referred to as time-activity data) have four related
purposes.
1. Knowledge of the activities performed while a study participant
carried a personal monitor can aid in identifying the determinants of
exposure, i.e., "What did this person do that led her/him to have such
a high exposure?" and "To what extent can exposure be explained the
amount of time spent in specific activities or locations?" For
instance, several studies in which activity pattern data were
collected in conjunction with monitoring data have shown that
indicators such as commuter status, work status, cooking fuel type,
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