With approximately 50% more person-years of follow-up and twice the number of deaths compared with the original Six Cities chronic mortality air pollution analysis (7
), we observed significant associations of fine particulate air pollution with mortality. More importantly, we were able to evaluate the effect of changing average ambient PM2.5
concentrations since the original follow-up. Covariate adjusted mortality rates declined between 1974 and 1989 (Period 1) and 1990 and 1998 (Period 2), consistent with the general increase in adult life expectancy in the United States. However, the drop in the adjusted mortality rate was largest in the cities with the largest reductions in PM2.5
after controlling for such a period effect. The proportional hazards rate ratio for a 10-μg/m3
increase in PM2.5
was comparable in both of these periods. However, we found a reduction in risk: 0.73 for each 10-μg/m3
decrease in mean PM2.5
between periods. This reduction was observed specifically for deaths due to cardiovascular and respiratory disease and not from lung cancer, a disease with a longer latency period and less reversibility. These findings suggest that the mortality effects of long-term air pollution may be at least partially reversible over periods of a decade.
We found equivalent, statistically significant increased risk in overall mortality associated with each 10-μg/m3 increase in PM2.5 modeled either as average over the entire follow-up (RR, 1.16; 95% CI, 1.07–1.26) or as average in the year of death (RR, 1.14; 95% CI, 1.06–1.22). These findings also suggest that mortality effects may be partially reversible, but over time periods possibly as short as a year.
Exposure to PM2.5 was statistically significantly associated with deaths due to cardiovascular disease, and the association with lung cancer mortality was of borderline significance. The number of nonmalignant respiratory deaths was small (although comparable to numbers for lung cancer), but the PM2.5-associated risk was positive, although weak.
Chronic exposure studies have observed increased mortality rates associated with PM. However, the evidence is limited mainly to the Harvard Six Cities Study and three other studies. The American Cancer Society Study, a cohort of 552,138 adults with 7 yr of follow-up, assessed risk for 151 U.S. metropolitan statistical areas (8
). With an additional 9 yr of follow-up, statistically significant elevations in risk associated with PM2.5
were observed for all-cause, lung cancer, and cardiopulmonary mortality (10
). In analyses of cause-specific mortality, each 10-μg/m3
increase in PM2.5
was associated with 8 to 18% increases in cardiovascular mortality, but only weak associations were found with nonmalignant respiratory deaths (21
). In the Adventist Health Study of Smog, a 15-yr follow-up of 6,338 nonsmoking Californians, Abbey and coworkers found mean PM10
associated with increased lung cancer mortality in men and women, and nonsignificantly increased all-cause and cardiopulmonary mortality in men (9
). A pilot prospective study of 4,466 participants monitored for 8 yr in the Netherlands concluded that long-term exposure to traffic-related particulate air pollution measured by black smoke was associated with increased all-cause mortality (11
Although a large body of literature has shown associations between particulate air pollution and mortality, the relative contributions of acute and chronic exposures are not known. Effect estimates from prospective studies are substantially greater than those indicated by daily time-series studies (22
). The majority of this difference may be explained by expanding the exposure period from days to months. Two independent studies have assessed the mortality effects over 40 d rather than 1 or 2 d after particle exposure. In both studies, the extended PM effects for periods of up to 6 wk were at least twice the short-term effects (3
). Schwartz showed in a time-series study in Boston that moving the time scale from days to months (i.e., 60 d) increased the estimated PM effect and captured approximately half the difference between the time-series and long-term cohort studies (4
). He concluded that decades of exposure are not required to develop most of the risk increase seen in cohort studies. Our results show that PM-associated mortality decreased in the decade of the 1990s compared with the mid-1970s and 1980s, consistent with the decrease in ambient PM2.5
concentrations. Furthermore, the similarity of effect for the annual air pollution metric compared with the mean over the study period (1980–1998) suggests that air pollution during the last year may be important. At least part of the PM2.5
-associated mortality may be reversible, suggesting ambient PM2.5
is likely associated with exacerbation of existing disease. However, there also appears to be a second independent effect that could be described as development of chronic disease.
Our ability to assess the appropriate time scale is limited because, although PM2.5 levels declined, the ranking of cities did not change substantially over most of the study period. However, the largest improvements in PM2.5 concentrations were in cities with the highest initial concentrations. There was also some variation in city-specific annual mean PM2.5 concentrations. We did not examine time periods shorter than 1 yr in this analysis.
The original Six Cities Study mortality analysis has undergone an extensive reanalysis performed by an independent group of researchers (23
). The original data were validated, the original findings reproduced, and these estimates were found to be robust to alternative models and to inclusion of other posited city-specific confounders. Alternative metrics of PM2.5
were not found to alter risk of all-cause mortality during the original period of follow-up (15
Cardiovascular mortality rates have decreased in the United States over the course of this study (24
). However, this improvement in cardiovascular mortality should affect all cities, and should not be larger in cities with the greatest improvement in PM2.5
concentrations. Moreover, PM2.5
concentrations fluctuated year to year, including increases as well as decreases from the preceding year. Yet, using PM2.5
as a time-varying covariate did not noticeably change the association. Thus, long-term secular trends are unlikely to explain our results.
This analysis lacked continuous monitoring of PM2.5
levels during the extended follow-up period. Six Cities monitoring of air pollutants ended in 1987 in most cities. The AIRS monitoring network began collecting PM10
data in 1985. PM2.5
measurements did not start until 1999, and even then did not include monitoring in all of the Six Cities or in the original monitoring sites. Therefore, Period 2 is completely dependent on estimated PM2.5
levels. We estimated the levels and patterns of PM2.5
during the missing years using city-specific regression of the original Six Cities PM2.5
measurements against the relative humidity–adjusted extinction coefficients from nearby airports and routine PM10
measurements from multiple nearby monitors. We assumed that the local change in PM2.5
would follow the local PM10
and extinction coefficient measurements, and that differences due to siting of the monitors and methodologies would have remained constant. Differences in measurement techniques and measurement locations preclude comparisons with current observations. Estimating the pattern of PM2.5
over time using the actual measured PM10
and extinction data has its limitations, but it is likely to be closer to reality than extrapolating levels beyond the available sampling data, as has been done previously (15
Follow-up information on individual risk factors was available during the course of the first 12 yr of follow-up. Three follow-up questionnaires were administered to the participants. There was no updated information available on individual risk factors or residence during the extended period of follow-up. In the original study, baseline characteristics were used to control for confounding factors (7
). Although these factors were significantly associated with mortality, they did not substantially confound the relationship with air pollution. In the reanalysis, Krewski and colleagues (23
) evaluated the effect of updating smoking status and body mass index during the course of the original study. They restricted the study population to the 81.5% of the people who did not move from their original cities at any time during the study period. These alternative analyses did not change the conclusions about the association of air pollution and mortality. Therefore, we elected to use baseline characteristics in this analysis. We acknowledge that this modeling choice may lead to misclassification of confounders such as smoking status and body mass index, and that the associations of these factors and air pollution may have changed. For example, trends in smoking cessation are different in different parts of the country (25
). Although these factors were significantly associated with mortality, they did not substantially confound the relationship with air pollution. In addition, censoring movers as defined in Krewski and colleagues' analysis (23
) at the start of the continued follow-up or excluding all movers from the analysis did not change our results (data not presented). A limitation of this analysis is that individual level covariates were not available for this population in the second period of follow-up.
In this extended follow-up during a time of air pollution reductions, we had a unique opportunity to assess the effect of recent versus past exposures. City-specific average PM2.5 levels were lower in the extended follow-up during the 1990s than in the first follow-up (1974–1989) and mortality risk ratios in this period also were lower. This suggests that the PM2.5-associated mortality in this 25-yr follow-up was at least in part reversible.