PM_2.5 Constituents and Related Air Quality Variables As Predictors of Survival in a Cohort of U.S. Military Veterans

Abstract

Air quality data on trace metals, other constituents of PM_2.5, and criteria air pollutants were used to examine relationships with long-term mortality in a cohort of male U.S. military veterans, along with data on vehicular traffic density (annual vehicle-miles traveled per unit of land area). The analysis used county-level environmental data for the period 1997–2002 and cohort mortality for 1997–2001. The proportional hazards model included individual data on age, race, smoking, body mass index, height, blood pressure, and selected interactions; contextual variables also controlled for climate, education, and income. In single-pollutant models, traffic density appears to be the most important predictor of survival, but potential contributions are also seen for NO₂, NO₃⁻, elemental carbon, nickel, and vanadium. The effects of the other main constituents of PM_2.5, of crustal particles, and of peak levels of CO, O₃, or SO₂ appear to be less important. Traffic density is also consistently the most important environmental predictor in multiple-pollutant models, with combined relative risks up to about 1.2. However, from these findings it is not possible to discern which aspects of traffic (pollution, noise, stress) may be the most relevant to public health or whether an area-based predictor such as traffic density may have an inherent advantage over localized measures of ambient air quality. It is also possible that traffic density could be a marker for unmeasured pollutants or for geographic gradients per se. Pending resolution of these issues, including replication in other cohorts, it will be difficult to formulate additional cost-effective pollution control strategies that are likely to benefit public health.