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

HEALTH EFFECTS OF AIR POLLUTION: AN OVERVIEW
evaluation of epidemiological evidence (78). Such quantitative summary estimates
have been generated for Asia, Europe and Latin America (38,39,73). Another
such effort combined data from 109 studies conducted in different parts of
the world (79).
Quantitative summary estimates provide more robust information than data
from individual studies, and therefore facilitate regional comparisons and the
calculation of health impacts. One important problem in meta-analysis is the potential
for publication bias, which refers to the tendency of editors (and authors)
to publish articles containing positive findings rather than those that do not yield
“significant” results (76). Statistical techniques are available to assess this bias and
should be used when conducting meta-analysis (73,80).
Quantitative summary estimates are often used for estimating the costs and
benefits of air pollution (25). A limitation related to the usefulness of quantitative
summary estimates for decision-making has to do with the heterogeneity of effect
estimates from individual studies. Often in meta-analysis, effect estimates are
pooled without consideration of the location of the individual studies. This may
lead to the generation of quantitative summary estimates based on results that
are not comparable. As observed with the development of exposure–response
curves, more thought needs to go into how to address subgroup variations to enhance
generalizability without losing power. Similarly, sources of heterogeneity
include the air pollution mix, climate, and individual population sensitivities and
demographics (31,81).
Case-crossover analysis
The case-crossover study design was proposed by Maclure (82) to study the effects
of momentary and intermittent exposures on the risk of developing an acute
and rare health event supposed to occur soon after the exposure. Since this design
focuses on individual deaths rather than death counts, it is possible to control for
factors that may modify or influence the effects of air pollution on mortality at
the individual level. Therefore, this approach has been applied in studies of the
effects of air pollution on health as an alternative to time series analysis, since it
may improve causal inferences about air pollution effects (83).
The design can be seen as a variation on the case-control study, in which each
individual bearing the event of interest (the case) acts as his or her own control.
For each case, the distribution of exposures in the period just before the event is
compared with the distribution of exposures estimated from some separate referent
time period. Thus, by making within-subject comparisons, time-independent
confounders are controlled by design.
When this design is applied to exposures that exhibit a time trend, however,
there is great potential for confounding in the risk estimate owing to this trend in
the exposure series (84). Therefore, an important methodological feature of this
strategy is adequate selection of control or referent periods. Several simulation
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