Environmental predictors of survival in a cohort of U.S. military veterans: A multi-level spatio-temporal analysis stratified by race.

We analyzed racial differences in all-cause mortality rates associated with air pollution in a cohort of military veterans in which 37% of the 70,000 members identified as African-American (black). In this comprehensive analysis, spatial levels comprised individuals, zip-codes, and counties. Temporal levels comprised the 26-y follow-up period (1976-2001) and 4 subperiods. Proportional hazard regression models were used, controlling for individual age, race (white, black), smoking (current, ever), education, height, body-mass index, and systolic and diastolic blood pressure; zipcode-average socioeconomic indicators; and county-average climate. County-level air quality measures included vehicular traffic density as a surrogate for all traffic-related pollutants including noise. The model accounted for nonlinear mortality relationships with age, body-mass index, blood pressure and zip-code racial composition. Relative to whites, more of the black veterans smoked, had slightly higher blood pressure, and lived in predominately black zip-codes that had more poverty than whites. The black veterans lived in counties that had slightly worse ambient air quality and substantially higher levels of vehicular traffic density. We analyzed all-cause mortality associations with county-level average ozone, nitrogen dioxide, sulfur dioxide, carbon monoxide for 1975-81, and subsequent data on particulates by particle size. We also considered sulfate and elemental carbon particles, benzene, SO2, and NOx based on nationwide modeling for 2002. We had no information on indoor air quality or personal exposures; our risk estimates should thus be regarded as characterizing the counties of residence rather than individual exposures of inhabitants. In addition to age, the strongest predictors of veterans' survival were residence in high-poverty zip-codes, smoking, and diastolic blood pressure, to all of which black veterans were less sensitive than whites. Black veterans had significantly lower mortality risks from aging, smoking, and elevated diastolic blood pressure, but larger risks from excessive body-mass index. They were less at risk from living a high-poverty zip-code than whites. We assumed these risk factors to be stable during follow-up and thus applicable to chronic health effects. After controlling for them, the all-cause mortality risk for black veterans was 10% lower than whites. In an effort to reduce random scatter we computed mean risks associated with overlapping groups of similar pollutants. These means were statistically significant for both black and white veterans for traffic-related, gaseous, and NOx-O3 pollutants, for which the overall mean relative risk was 1.076 (1.057-1.090). Grouped mean risks for particulate pollutants, sulfur compounds, and non-traffic pollutants were not significant for either race. Black veterans carried more of the traffic-related risks than whites because of their greater exposures and risk coefficients. PM2.5 risk estimates were negative for black veterans (0.82 [0.75-0.89]) but positive for whites (1.05 [1.005-1.10]) which is consistent with regional differences in overall mortality. The temporal analyses compared mortality rates by follow-up subperiod for the pollutants measured at enrollment. We expected increasing (cumulative) risks for chronic effects and decreasing risks for delayed acute effects, but found no significant trend for either race. We concluded that the higher exposures and mortality risks associated with vehicular traffic posed environmental injustice for the black veterans.

Longitudinal relationships between lung cancer mortality rates, smoking, and ambient air quality: a comprehensive review and analysis.

Lung cancer mortality (LCM) has been associated with smoking and air pollution. This article draws on smoking relationships to clarify air pollution relationships. We analyzed cohort and population-based smoking studies and identified effects of latency and cumulative exposures. We found cogent relationships through longitudinal rather than cross-sectional analysis, thus involving historical data. We also considered passive smoking, occupational exposures, radon, and established carcinogens. We found stable nonsmoking LCM rates during periods of improving ambient air quality. We considered 59 cross-sectional studies of lung cancer and air pollution and found similar statistically significant relative risks for PM2.5, PM10, EC, NO2, SO2, SO2-4, and O3, and minimal risks for benzo(alpha)pyrene and trace metals. Most air pollution studies did not consider latency, exposure duration, or temporal trends; none included estimates of smoking risks implied by their models. We conclude that while LCM studies of smoking, radon, and occupational exposures appropriately considered latency and cumulative exposures; ambient air quality studies have not. Lung cancer has a long memory and exposure histories are required. Effects of cumulative exposures after pollution abatement include substantially reduced risk estimates, delayed health benefits, inability to show accountability for the abatement. However, associations of lung cancer with ambient air pollution cannot be ruled out, especially for historic periods when much higher exposures persisted. Given the major reductions in air quality and smoking habits that have been realized since the Clean Air Act, new studies of LCM and air pollution, including smoking histories and exposure data decades before diagnosis, are needed.HighlightsLifetime cigarette consumption is a good predictor of lung cancer risk.The latent period for lung cancer ranges from about 10 to 30 y.Lung cancer risks for nonsmokers have been stable during the period when ambient air quality improved substantially.Risks of established airborne carcinogens may have been important in the past but not under current conditions.Radon can be important.Air pollution-lung cancer risks should be evaluated jointly with smoking risks but are sensitive to their accuracy.When cumulative exposures to conventional air pollutants are considered rather than concurrent, the applicable risk estimates may decrease by an order of magnitude and abatement benefits will not be readily apparent.Most of the recent cross-sectional studies of lung cancer and regulated air pollutants did not consider latency, duration of exposure, or established carcinogens and their findings have been misinterpreted.Effects of smoking on LCM are now well established as are the spatial distributions of ambient air pollution; however, linkages among the three parameters remain uncertain.

Revisiting the Veterans Cohort Mortality Study: New results and synthesis.

The Veterans Cohort Mortality Study began in 1999 in collaboration with Washington University in St. Louis, comprising ~70,000 male military veterans. We published six research papers on this cohort, considering the dynamics of all-cause mortality as the subjects aged and environmental parameters changed. This paper summarizes those results and presents new results by age group. Pollutants included monitored and modeled criteria pollutants, vehicular traffic density (annual km driven per unit of county land area), and modeled nationwide levels of hazardous species. In addition to spatial relationships, we examined the effects of exposure timing through separate analyses of sequential follow-up and exposure periods from 1976 to 2001. Risks associated with peak ozone decreased with lag between exposure and response, suggesting acute effects. Risks associated with traffic were invariant over time and consistent across five exposure databases. Associations with ozone were also coherent across databases; we found no consistent associations with particulate matter. Epidemiology considers both spatial and temporal relationships; most long-term studies focus on spatial gradients at a given time, thus masking effects of cohort aging and other trends during follow-up. Our new analyses distinguished between these temporal effects by analyzing age deciles for which separate mortality risks had been estimated for nationwide levels of nitrogen oxides (NOx), benzene, and traffic density during four sequential follow-up subperiods, thus providing 40 sets of mortality risk coefficients. We used ordinary least squares regression to define relationships with subject age and follow-up year for the data set of 40 coefficients. We found strong nonlinear relationships between subject age and mortality coefficients for smoking, climate, poverty status, and air pollution; only smoking and climate coefficients changed over time as well. We concluded that these pollutant-mortality relationships reflected differences among the veterans' residential locations rather than changes in their pollution exposures during follow-up. We saw no evidence that cleaner air reduced mortality. Implications: Recent air pollution mortality studies emphasize PM2.5 (particulate matter with an aerodynamic diameter <2.5 µm); we show associations with many other pollutants and a measure of traffic intensity. Control policies should thus be based on multipollutant analyses. We found no reduced risks with improved air quality after distinguishing cohort aging from purely temporal effects; longitudinal studies of accountability must thus account for changes in demography and exposures. Our studies of exposure timing indicate mainly coincident responses and no evidence for cumulative effects typical of smoking; we had no information on personal exposures. We found the strongest risks were associated with high-traffic locations rather than outdoor air quality per se.