Do pollution time-series studies contain uncontrolled or residual confounding by risk factors for acute health events?

Acute health effects from air pollution are based largely on weak associations identified in time-series studies comparing daily air pollution levels to daily mortality. Much of this mortality is due to cardiovascular disease. Time-series studies have many potential limitations, but are not thought to be confounded by traditional cardiovascular risk factors (e.g., smoking status or hypertension) because these chronic risk factors are not obviously associated with daily pollution levels. However, acute psychobehavioral variants of these risk factors (e.g., smoking patterns and episodes of stress on any given day) are plausible confounders for the associations observed in time-series studies, given that time-series studies attempt to predict acute rather than chronic health outcomes. There is a fairly compelling literature on the strong link between cardiovascular events and daily “triggers” such as stress. Stress-related triggers are plausibly associated with daily pollution levels through surrogate stressors such as ambient temperature, daily workload, local traffic congestion, or other correlates of air pollution. For example, variables such as traffic congestion and industrial activity increase both stress-related health events and air pollution, suggesting the potential for classical confounding. Support for this argument is illustrated through examples of the well-demonstrated relationship between emotional stress and heart attack/stroke.