Effects of long-term exposure to traffic-related air pollution on respiratory and cardiovascular mortality in the Netherlands: the NLCS-AIR study.
Evidence is increasing that long-term exposure to ambient air pollution is associated with deaths from cardiopulmonary diseases. In a 2002 pilot study, we reported clear indications that traffic-related air pollution, especially at the local scale, was related to cardiopulmonary mortality in a randomly selected subcohort of 5000 older adults participating in the ongoing Netherlands Cohort Study (NLCS) on diet and cancer. In the current study, referred to as NLCS-AIR, our objective was to obtain more precise estimates of the effects of traffic-related air pollution by analyzing associations with cause-specific mortality, as well as lung cancer incidence, in the full cohort of approximately 120,000 subjects. Cohort members were 55 to 69 years of age at enrollment in 1986. Follow-up was from 1987 through 1996 for mortality (17,674 deaths) and from late 1986 through 1997 for lung cancer incidence (2234 cases). Information about potential confounding variables and effect modifiers was available from the questionnaire that subjects completed at enrollment and from publicly available data (including neighborhood-scale information such as income distributions). The NLCS was designed for a case-cohort approach, which makes use of all the cases in the full cohort, while data for the random subcohort are used to estimate person-time experience in the study. Full information on confounders was available for the subjects in the random subcohort and for the emerging cases of mortality and lung cancer incidence during the follow-up period, and in NLCS-AIR we used the case-cohort approach to examine the relation between exposure to air pollution and cause-specific mortality and lung cancer. We also specified a standard Cox proportional hazards model within the full cohort, for which information on potential confounding variables was much more limited. Exposure to air pollution was estimated for the subjects' home addresses at baseline in 1986. Concentrations were estimated for black smoke (a simple marker for soot) and nitrogen dioxide (NO2) as indicators of traffic-related air pollution, as well as nitric oxide (NO), sulfur dioxide (SO2), and particulate matter with aerodynamic diameter < or = 2.5 microm (PM2.5), as estimated from measurements of particulate matter with aerodynamic diameter < or = 10 microm (PM10). Overall long-term exposure concentrations were considered to be a function of air pollution contributions at regional, urban, and local scales. We used interpolation from data obtained routinely at regional stations of the National Air Quality Monitoring Network (NAQMN) to estimate the regional component of exposure at the home address. Average pollutant concentrations were estimated from NAQMN measurements for the period 1976 through 1996. Land-use regression methods were used to estimate the urban exposure component. For the local exposure component, geographic information systems (GISs) were used to generate indicators of traffic exposure that included traffic intensity on and distance to nearby roads. A major effort was made to collect traffic intensity data from individual municipalities. The exposure variables were refined considerably from those used in the pilot study, but we also analyzed the data for the full cohort in the current study using the exposure indicators of the pilot study. We analyzed the data in models with the estimated overall pollutant concentration as a single variable and with the background concentration (the sum of regional and urban components) and the local exposure estimate from traffic indicators as separate variables. In the full-cohort analyses adjusted for the limited set of confounders, estimated overall exposure concentrations of black smoke, NO2, NO, and PM2.5 were associated with mortality. For a 10-microg/m3 increase in the black smoke concentration, the relative risk (RR) (95% confidence interval [CI]) was 1.05 (1.00-1.11) for natural-cause (nonaccidental) mortality, 1.04 (0.95-1.13) for cardiovascular mortality, 1.22 (0.99-1.50) for respiratory mortality, 1.03 (0.88-1.20) for lung cancer mortality, and 1.04 (0.97-1.12) for noncardiopulmonary, non-lung cancer mortality. Results were similar for NO2, NO, and PM2.5. For a 10-microg/m3 increase in PM2.5 concentration, the RR for natural-cause mortality was 1.06 (95% CI, 0.97-1.16), the same as in the results of the American Cancer Society Study reported by Pope and colleagues in 2002. The highest relative risks were found for respiratory mortality, though confidence intervals were wider for this less-frequent cause of death. No associations with mortality were found for SO2. Some of the associations between the traffic indicator variables used to assess traffic intensity near the home and mortality reached statistical significance in the full cohort. For an increase in traffic intensity of 10,000 motor vehicles in 24 hours (motor vehicles/day) on the road nearest a subject's residence, the RR was 1.03 (95% CI, 1.00-1.08) for natural-cause mortality, 1.05 (0.99-1.12) for cardiovascular mortality, 1.10 (0.95-1.26) for respiratory mortality, 1.07 (0.96-1.19) for lung cancer mortality, and 1.00 (0.94-1.06) for noncardiopulmonary, non-lung cancer mortality. Results were similar for traffic intensity in a 100-m buffer around the subject's residence and living near a major road (a road with more than 10,000 motor vehicles/day). Distance in meters to the nearest major road and traffic intensity on the nearest major road were not associated with any of the mortality outcomes. We did not find an association between cardiopulmonary mortality and living near a major road as defined using the methods of the pilot study. In the case-cohort analyses adjusted for all potential confounders, we found no associations between background air pollution and mortality. The associations between traffic intensity and mortality were weaker than in the full cohort, and confidence intervals were wider, consistent with the smaller number of subjects. The lower relative risks of mortality associated with traffic variables in the case-cohort study population could be related to the particular subcohort that was randomly selected from the full cohort, as the risks estimated with the actual subcohort were well below the average estimates obtained for 100 new case-cohort analyses with 100 alternative subcohorts of 5000 subjects each that we randomly selected from the full cohort. Differences in adjusted relative risks between the full-cohort and the case-cohort analyses could be explained by random error introduced by sampling from the full cohort and by a selection effect resulting from the relatively large number of missing data for variables in the extensive confounder model used in the case-cohort analyses. More complete control for confounding probably did not contribute much to the lower relative risks in the case-cohort analyses, especially for the traffic variables, as results were similar when the limited confounder model for the full cohort was used in analyses of the subjects in the case-cohort study population. In additional analyses using black smoke concentrations as the exposure variables, we found that the association between overall black smoke and cardiopulmonary mortality was somewhat stronger for case-cohort subjects who did not change residence during follow-up, and in the full cohort, there was a tendency for relative risks to be higher for subjects living in the three major cities included in the study. Adjustment for estimated exposure to traffic noise did not affect the associations of background black smoke and traffic intensity with cardiovascular mortality. There was some indication of an association between traffic noise and cardiovascular mortality only for the 1.6% of the subjects in the full cohort who were exposed to traffic noise in the highest category of > 65 A-weighted decibels (dB(A); decibels with the sound pressure scale adjusted to conform with the frequency response of the human ear). Examination of sex, smoking status, educational level, and vegetable and fruit intake as possible effect modifiers showed that for overall black smoke concentrations, associations with mortality tended to be stronger in case-cohort subjects with lower levels of education and those with low fruit intake, but differences between strata were not statistically significant. For lung cancer incidence, we found essentially no relation to exposure to NO2, black smoke, PM2.5, SO2, or several traffic indicators. Associations of overall air pollution concentrations and traffic indicator variables with lung cancer incidence were, however, found in subjects who had never smoked, with an RR of 1.47 (95% CI, 1.01-2.16) for a 10-microg/m3 increase in overall black smoke concentration. In the current study, the mortality risks associated with both background air pollution and traffic exposure variables were much smaller than the estimate previously reported in the pilot study for risk of cardiopulmonary mortality associated with living near a major road (RR, 1.95; 95% CI, 1.09-3.51). The differences are most likely due to the extension of the follow-up period in the current study and to random error in the pilot study related to sampling from the full cohort. Though relative risks were generally small in the current study, long-term average concentrations of black smoke, NO2, and PM2.5 were related to mortality, and associations of black smoke and NO2 exposure with natural-cause and respiratory mortality were statistically significant. Traffic intensity near the home was also related to natural-cause mortality. The highest relative risks associated with background air pollution and traffic variables were for respiratory mortality, though the number of deaths was smaller than for the other mortality categories. (ABSTRACT TRUNCATED)
Brunekreef B
，Beelen R
，Hoek G
，Schouten L
，Bausch-Goldbohm S
，Fischer P
，Armstrong B
，Hughes E
，Jerrett M
，van den Brandt P
... -
《-》
Extended follow-up and spatial analysis of the American Cancer Society study linking particulate air pollution and mortality.
We conducted an extended follow-up and spatial analysis of the American Cancer Society (ACS) Cancer Prevention Study II (CPS-II) cohort in order to further examine associations between long-term exposure to particulate air pollution and mortality in large U.S. cities. The current study sought to clarify outstanding scientific issues that arose from our earlier HEI-sponsored Reanalysis of the original ACS study data (the Particle Epidemiology Reanalysis Project). Specifically, we examined (1) how ecologic covariates at the community and neighborhood levels might confound and modify the air pollution-mortality association; (2) how spatial autocorrelation and multiple levels of data (e.g., individual and neighborhood) can be taken into account within the random effects Cox model; (3) how using land-use regression to refine measurements of air pollution exposure to the within-city (or intra-urban) scale might affect the size and significance of health effects in the Los Angeles and New York City regions; and (4) what exposure time windows may be most critical to the air pollution-mortality association. The 18 years of follow-up (extended from 7 years in the original study [Pope et al. 1995]) included vital status data for the CPS-II cohort (approximately 1.2 million participants) with multiple cause-of-death codes through December 31, 2000 and more recent exposure data from air pollution monitoring sites for the metropolitan areas. In the Nationwide Analysis, the influence of ecologic covariate data (such as education attainment, housing characteristics, and level of income; data obtained from the 1980 U.S. Census; see Ecologic Covariates sidebar on page 14) on the air pollution-mortality association were examined at the Zip Code area (ZCA) scale, the metropolitan statistical area (MSA) scale, and by the difference between each ZCA value and the MSA value (DIFF). In contrast to previous analyses that did not directly include ecologic covariates at the ZCA scale, risk estimates increased when ecologic covariates were included at all scales. The ecologic covariates exerted their greatest effect on mortality from ischemic heart disease (IHD), which was also the health outcome most strongly related with exposure to PM2.5 (particles 2.5 microm or smaller in aerodynamic diameter), sulfate (SO4(2-)), and sulfur dioxide (SO2), and the only outcome significantly associated with exposure to nitrogen dioxide (NO2). When ecologic covariates were simultaneously included at both the MSA and DIFF levels, the hazard ratio (HR) for mortality from IHD associated with PM2.5 exposure (average concentration for 1999-2000) increased by 7.5% and that associated with SO4(2-) exposure (average concentration for 1990) increased by 12.8%. The two covariates found to exert the greatest confounding influence on the PM2.5-mortality association were the percentage of the population with a grade 12 education and the median household income. Also in the Nationwide Analysis, complex spatial patterns in the CPS-II data were explored with an extended random effects Cox model (see Glossary of Statistical Terms at end of report) that is capable of clustering up to two geographic levels of data. Using this model tended to increase the HR estimate for exposure to air pollution and also to inflate the uncertainty in the estimates. Including ecologic covariates decreased the variance of the results at both the MSA and ZCA scales; the largest decrease was in residual variation based on models in which the MSA and DIFF levels of data were included together, which suggests that partitioning the ecologic covariates into between-MSA and within-MSA values more completely captures the sources of variation in the relationship between air pollution, ecologic covariates, and mortality. Intra-Urban Analyses were conducted for the New York City and Los Angeles regions. The results of the Los Angeles spatial analysis, where we found high exposure contrasts within the Los Angeles region, showed that air pollution-mortality risks were nearly 3 times greater than those reported from earlier analyses. This suggests that chronic health effects associated with intra-urban gradients in exposure to PM2.5 may be even larger between ZCAs within an MSA than the associations between MSAs that have been previously reported. However, in the New York City spatial analysis, where we found very little exposure contrast between ZCAs within the New York region, mortality from all causes, cardiopulmonary disease (CPD), and lung cancer was not elevated. A positive association was seen for PM2.5 exposure and IHD, which provides evidence of a specific association with a cause of death that has high biologic plausibility. These results were robust when analyses controlled (1) the 44 individual-level covariates (from the ACS enrollment questionnaire in 1982; see 44 Individual-Level Covariates sidebar on page 22) and (2) spatial clustering using the random effects Cox model. Effects were mildly lower when unemployment at the ZCA scale was included. To examine whether there is a critical exposure time window that is primarily responsible for the increased mortality associated with ambient air pollution, we constructed individual time-dependent exposure profiles for particulate and gaseous air pollutants (PM2.5 and SO2) for a subset of the ACS CPS-II participants for whom residence histories were available. The relevance of the three exposure time windows we considered was gauged using the magnitude of the relative risk (HR) of mortality as well as the Akaike information criterion (AIC), which measures the goodness of fit of the model to the data. For PM2.5, no one exposure time window stood out as demonstrating the greatest HR; nor was there any clear pattern of a trend in HR going from recent to more distant windows or vice versa. Differences in AIC values among the three exposure time windows were also small. The HRs for mortality associated with exposure to SO2 were highest in the most recent time window (1 to 5 years), although none of these HRs were significantly elevated. Identifying critical exposure time windows remains a challenge that warrants further work with other relevant data sets. This study provides additional support toward developing cost-effective air quality management policies and strategies. The epidemiologic results reported here are consistent with those from other population-based studies, which collectively have strongly supported the hypothesis that long-term exposure to PM2.5 increases mortality in the general population. Future research using the extended Cox-Poisson random effects methods, advanced geostatistical modeling techniques, and newer exposure assessment techniques will provide additional insight.
Krewski D
，Jerrett M
，Burnett RT
，Ma R
，Hughes E
，Shi Y
，Turner MC
，Pope CA 3rd
，Thurston G
，Calle EE
，Thun MJ
，Beckerman B
，DeLuca P
，Finkelstein N
，Ito K
，Moore DK
，Newbold KB
，Ramsay T
，Ross Z
，Shin H
，Tempalski B
... -
《-》
ResearchGate
(全网免费下载)
钛学术
(全网免费下载)
