title: The Washington University-EPRI Veterans' Cohort Mortality Study: preliminary results.
abstract: This article presents the design of and some results from a new prospective mortality study of a national cohort of about 50,000 U.S. veterans who were diagnosed as hypertensive in the mid 1970s, based on approximately 21 yr of follow-up. This national cohort is male with an average age at recruitment of 51 +/- 12 yr; 35% were black and 81% had been smokers at one time. Because the subjects have been receiving care at various U.S. Veterans Administration (VA) hospitals, access to and quality of medical care are relatively homogeneous. The health endpoints available for analysis include all-cause mortality and specific diagnoses for morbidity during VA hospitalizations; only the mortality results are discussed here. Nonpollution predictor variables in the baseline model include race, smoking (ever or at recruitment), age, systolic and diastolic blood pressure (BP), and body mass index (BMI). Interactions of BP and BMI with age were also considered. Although this study essentially controls for socioeconomic status by design because of the homogeneity of the cohort, selected ecological variables were also considered at the ZIP code and county levels, some of which were found to be significant predictors. Pollutants were averaged by year and county for TSP, PM10, CO, O3, and NO2; SO2 and Pb were considered less thoroughly. Both mean and peak levels were considered for gases. SO(4)2- data from the AIRS database and PM2.5, coarse particles, PM15, and SO(4)2- from the U.S. EPA Inhalable Particulate (IP) Network were also considered. Four relevant exposure periods were defined: 1974 and earlier (back to 1953 for TSP), 1975-1981, 1982-1988, and 1989-1996. Deaths during each of the three most recent exposure periods were considered separately, yielding up to 12 combinations of exposure and mortality periods for each pollutant. Associations between concurrent air quality and mortality periods were considered to relate to acute responses; delayed associations with prior exposures were considered to be emblematic of initiation of chronic disease. Preexposure mortality associations were considered to be indirect (noncausal). The implied mortality risks of long-term exposure to air pollution were found to be sensitive to the details of the regression model, the time period of exposure, the locations included, and the inclusion of ecological as well as personal variables. Both positive and negative statistically significant mortality responses were found. Fine particles as measured in the 1979-1984 U.S. EPA Inhalable Particulate Network indicated no significant (positive) excess mortality risk for this cohort in any of the models considered. Among the positive responses, indications of concurrent mortality risks were seen for NO2 and peak O3, with a similar indication of delayed risks only for NO2. The mean levels of these excess risks were in the range of 5-9%. Peak O3 was dominant in two-pollutant models and there was some indication of a threshold in response. However, it is likely that standard errors of the regression coefficients may have been underestimated because of spatial autocorrelation among the model residuals. The significant variability of responses by period of death cohort suggests that aggregation over the entire period of follow-up obscures important aspects of the implied pollution-mortality relationships, such as early depletion of the available pool of those subjects who may be most susceptible to air pollution effects.
authors.affiliation: Department of Veterans Affairs Medical Center and Washington University School of Medicine, Division of Hypertension, St. Louis, Missouri, USA. flipfert@suffolk.lib.ny.us
authors.forename: F W
authors.initials: FW
authors.lastname: Lipfert
authors.forename: H M
authors.initials: HM
authors.lastname: Perry
authors.forename: J P
authors.initials: JP
authors.lastname: Miller
authors.forename: J D
authors.initials: JD
authors.lastname: Baty
authors.forename: R E
authors.initials: RE
authors.lastname: Wyzga
authors.forename: S E
authors.initials: SE
authors.lastname: Carmody
mesh_terms: D000368:Aged; D000393:Air Pollutants / Q000009:adverse effects*; D000397:Air Pollution / Q000009:adverse effects; D015331:Cohort Studies; D006801:Humans; D008297:Male; D009026:Mortality / Q000639:trends*; D012044:Regression Analysis; D012307:Risk Factors; D014728:Veterans / Q000706:statistics & numerical data*
chemical_list: D000393:Air Pollutants