Air Quality Guidelines Global Update 2005 - World Health ...

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AIR QUALITY GUIDELINES
Extrapolation of CR functions beyond the observed air quality concentrations
The accuracy of the underlying CR function may be altered by extrapolating the
existing function to concentrations either below or above the range of the original
study. The current evidence has failed to detect the existence of a threshold at the
population level, so calculating effects down to a background concentration is a
scientifically supportable assumption. However, some analysts use a conservative
approach to extrapolation and only apply the study to a range equal to that of the
original study. Others extrapolate the CR functions down to zero, while some
have assumed the existence of threshold concentrations below which health effects
are unlikely. Regarding the upper range of concentrations, some analysts
have extrapolated the CR functions up to the highest observed concentrations in
the area under study. The accuracy of these extrapolations depends on the shape
of the underlying CR function and is often not observable. Thus an appropriate
strategy is to explore the sensitivity of these assumptions on the ultimate result.
One issue that is of particular concern is the extrapolation of a linear function to
the highest observed concentrations in highly polluted cities or regions. At very
high concentrations, it is likely that the CR function will begin to flatten; therefore
a linear extrapolation well beyond the range of the underlying data should be
carefully evaluated. The global burden of disease project specifically addressed
this issue by considering non-linear functional forms and assuming a maximum
for the relative risk estimates (2).
Choice of health outcomes
Often, the analyst must choose to focus on a subset of several health end-points
that have been studied. The choice of which end-points to include in the quantitative
assessment may be determined by the strength of available evidence from
the epidemiological as well as other scientific literature, the accuracy of the definition
of the end-point under consideration, the availability of information on
baseline rates, and the importance of the impact from both the health and, perhaps,
the economic viewpoint. It is much easier to choose a given end-point to
include if many studies of this health effect exist, particularly if the studies involve
a wide range of cities, seasonal patterns, meteorology, co-pollutants and
background health status. The daily time series studies of mortality and PM provide
a good example of this, in that they have been conducted in five continents
and show reasonably consistent results. In addition, all-cause mortality has a
clear and consistent definition (as opposed to, for example, asthma or mortality
from cardiovascular disease) regardless of location. Finally, most of the analyses
to date indicate that effects on mortality, particularly those relating to long-term
exposure to air pollution, tend to dominate the economic effects, often accounting
for 80% or more of the total.
The consistency of the daily time series studies among so many locations
suggests it is reasonable to extrapolate the findings of the effects of long-term