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Poor people may be more susceptibie, but poverty also fosters increased pollution
This issue of the journal includes three papers that touch on relations among socioeconomic status (SES), health, and air quality. Jerrett et al considered whether SES differentials in Hamilton, Ontario, modify the temporal relations between daily mortality and either coefficient of haze (COH) or SO2.1 Martins et al did a similar analysis with respect to PM10 in Sao Paulo, Brazil.2 The third paper, by Gouveia et al, also involved Sao Paulo but examined cross sectional relations between several pollutants and infant birth weight.3 As such, it involves SES factors only implicitly, by virtue of the trends seen by Martins et al2 that link levels of PM10 in Sao Paulo with residence in slums and other SES indicators. Inequitable distribution of environmental impacts within a city or region may raise issues of “environmental justice”,* but it may also be possible to get additional insights into the implied health relations by probing a little deeper into the nature and origins of such differential impacts.
Most time series studies are based on entire cities and spatially averaged air quality, in order to maximise statistical power and to preclude the necessity of assigning individual deaths to specific air quality monitors. Time series studies avoid SES confounding by design, as those factors do not vary on a daily basis. However, many air pollutants tend to vary in concert, especially those that are co-emitted by common sources, thus making it difficult to identify the most probable causal agent. Cross sectional studies may have less co-pollutant collinearity, but can suffer from SES confounding to the extent that SES may tend to decrease with residential proximity to major pollution sources. All of these issues are in …
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