Invited Commentary: Particulate Matter-Mortality Exposure-Response Relations and Threshold
C. Arden Pope, III
From the Brigham Young University, Provo, UT.
Abbreviations:
PM, particulate matter air pollution.
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INTRODUCTION
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In this issue of the Journal, Daniels et al. (1
) report an analysis of the shape of the exposure-response relation between daily concentrations of particulate matter air pollution (PM) and mortality. They provide additional epidemiologic evidence of the absence of a population-based "no-effects" threshold level for PM within relevant ranges of exposure. Their results suggest that the PM-mortality exposure-response relation is near linear, with mortality risk occurring even at concentrations below current regulatory levels. This analysis is the latest of several important contributions to the literature on particuate matter and mortality by Samet, Zeger, and various colleagues.
In the early 1990s, following the publications of several studies that suggested a link between daily mortality and PM pollution at relatively low concentrations (2



7
), Samet and others argued that the findings could not be adequately interpreted and they encouraged new studies (8
). Samet and Zeger then led a reanalysis effort (9
, 10
) that largely replicated the PM-mortality associations observed in selected early studies while refining and contributing to applicable statistical methodologies. Most recently they, along with Dominici and others, have been developing approaches to incorporate multiple cities in a comprehensive analysis of daily time-series mortality and air pollution in the United States (11
, 12
). They have provided insights relating to the consistency of the observed PM-mortality associations (13
), the importance of mortality displacement (or harvesting) (14
), issues regarding measurement error (15
), alternative ways to control for weather variables (10
), and now the shape of the exposure-response relation (1
).
While this excellent work represents an important contribution, it does not stand alone. This commentary provides some context and perspective with respect to the development of the epidemiologic literature and the public health relevance of these findings.
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LITERATURE DEVELOPMENT
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Early episode studies
Much of the concern about the health effects of PM and public policy efforts to control this pollution originated from dramatic and severe air pollution episodes (16
, 17
) that included Meuse Valley, Belgium, in 1930 (18
), Donora, Pennsylvania, in 1948 (19
), and London, England, in 1952 (20
). Studies of these episodes were methodologically simple, comparing death counts for several days or weeks before, during, and after the pollution episodes. Nevertheless, a link between cardiopulmonary mortality and extremely elevated concentrations of particulate and/or sulfur oxide air pollution was demonstrated. These early episode studies contributed to a prevailing opinion that appreciable health effects occurred only at extremely high concentrations (21
). Early public policy efforts to improve air quality in Britain, the United States, and elsewhere were largely attempts to avoid or prevent these "killer" episodes.
Early time-series studies
In the 1970s and 1980s a few researchers began to collect daily mortality and pollution data from various cities or communities for several years and analyze correlations in the data (22
). Such an approach did not focus on only extreme pollution episodes but allowed for evaluations of potential mortality effects at relatively low and common levels of pollution. Ostro (23
), in 1984, presented one of the earliest analyses that formally evaluated the existence of a no-effects threshold level in the relation of PM to mortality. London data for 14 winters (1958/19591971/1972) were obtained, and regression analysis was used to estimate linear spline exposure-response functions that allowed for different exposure-response relations below and above 150 µg/m3. Mortality effects were observed even in winters without historically severe pollution episodes, and there was no evidence of a threshold level at 150 µg/m3.
Another interesting analysis that used the same London data was presented by Schwartz and Marcus (24
). In addition to estimating various autoregressive regression models, they plotted the data by sorting the observations in order of increasing pollution levels and taking the means of adjacent observations. They observed a curvilinear relation between pollution and mortality, but steeper slopes were observed at lower pollution levels than at the higher levels (figure 1A).

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FIGURE 1. Plots of exposure-response relations from selected early daily time-series mortality studies. A, mean daily deaths and British Smoke in London, England, plotted for 20 adjacent values of British Smoke (Am J Epidemiol 1990;131:18594); B to F, adjusted relative risk of death estimates plotted over quintiles of particulate pollution for Detroit, Michigan (Environ Res 1991;56:20413), St. Louis, Missouri (Environ Res 1992;59:36273), Utah Valley, Utah (Arch Environ Health 1992;47:21117), Philadelphia, Pennsylvania (Am Rev Respir Dis 1992;145:6004), and Sao Paulo, Brazil (Arch Environ Health 1995;50:15963). TSP, total suspended particles; PM10, particulate matter <10 µm in aerodynamic diameter.
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Poisson regression, quintile plots, and nonparametric smoothing
In the early 1990s several studies were published that used more advanced statistical modeling techniques. The primary statistical approach was formal time-series modeling of count data using Poisson regression and controlling for potential confounders such as season, temperature, and relative humidity. Many of these studies evaluated mortality effects over periods of time and in cities where pollution levels seldom, if ever, exceeded prevailing ambient air quality standards (2
3
4
5
6
7
, 22
). Yet, associations between daily mortality counts and PM were observed. Although log-linear Poisson regression models were common, to further evaluate the evidence of an exposure-response relation and to allow for nonlinearity, researchers often divided pollution into quintiles (or quartiles), and dummy variables were used in the regressions. This allowed for adjusted relative risk of death estimates to be plotted over various levels of pollution. As can be seen in plots from selected studies (3
, 4
, 6
, 24
26
) as presented in figure 1, B to F, associations between various measures of particulate pollution and mortality often persisted, even at lower concentrations.
After some of the early daily time-series studies were published, there were concerns about their reproducibility, modeling sensitivity, adequacy of control for confounders, and prematurity of death. However, the results of selected studies have been largely replicated (9
), their results have been found to be not highly sensitive to various approaches to controlling for seasonality and weather variables (10
, 27
), and PM-mortality effects appeared to be due to more than just short-term harvesting (i.e., mortality effects were not entirely due to advancing the date of death for those with life-threatening illness) (14
, 28
). The development and use of generalized additive models that use nonparametric smoothing have allowed for more flexible handling of long-term time trends, seasonality, and other variables. These nonparametric smoothing approaches also allowed for direct exploration for no-effects threshold levels. Estimated exposure-response relations from a few selected single-city studies that used this approach (7
, 27
, 29
, 30
) are presented in figure 2, A to D. The shapes of the estimated exposure-response relations were often near linear without consistent, well-defined thresholds.

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FIGURE 2. Plots of exposure-response relations from selected studies. A to D, nonparametric smooth curves of adjusted daily deaths or adjusted relative risk of death for selected daily time-series mortality studies from Cincinnati, Ohio (Environ Health Perspect 1994;102:1869), Birmingham, Alabama (Am J Epidemiol 1993;137:113647), Utah Valley, Utah (Environ Health Perspect 1996;104:41420), and Shenyang, China (Arch Environ Health 2000;47:11520). E and F, adjusted mortality rates or rate ratios for US cities plotted over mean fine particulate matter levels from two studies of long-term exposure (N Engl J Med 1993;329:17539; Am J Respir Crit Care Med 1995;151:66974). ACS, American Cancer Society; TSP, total suspended particles; PM10, particulate matter <10 µm in aerodynamic diameter (PM2.5 defined similarly).
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Publication bias and measurement error
Although there was a growing number of published studies that reported positive, near linear associations between PM and daily mortality, most were single-city studies. Because there were no clearly defined or uniform criteria for selecting the study cities, city selection bias and publication bias were concerns. However, recently several research efforts involving an integrated daily time-series mortality analysis of multiple cities have been conducted (31
33
).
Lipfert and Wyzga (34
) have argued that, even with multicity studies, exposure measurement error obscures the true shape of the exposure-response relation. Watt et al. (35
) also suggest that nonparametric smoothing approaches may not be able to identify no-effects thresholds. Cakmak et al. (36
), however, demonstrated that nonparametric smoothed functions can adequately identify the shape of the exposure-response relation between PM and mortality and provide unbiased estimates of the threshold levels, even in the presence of extreme exposure measurement error.
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CURRENT MULTICITY STUDIES
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Schwartz and Zanobetti (37
) also conducted a simulation analysis that demonstrated the ability of nonparametric smoothing methods to detect thresholds and other nonlinear relations even in the presence of exposure measurement error. They then conducted a "meta-smoothing" analysis using daily mortality and pollution data from 10 US cities. The combined or "meta-smoothed" exposure-response relation was calculated by fitting a Poisson, generalized additive model using a flexible smoothed function of PM for each city and calculating the inverse variance weighted average across the 10 cities for each 2-µg/m3 increment of PM. The estimated combined 10-city exposure-response relation was near linear with no evidence of a threshold, even down to the lowest PM concentrations observed.
This leads us to the present study by Daniels et al. (1
). It is the most extensive PM-mortality exposure-response multicity study conducted, using data from the 20 largest US cities. The authors correctly note that the use of many locations enhances the study's statistical power and generalizability. They fit a series of Poisson, generalized additive models controlling for such factors as day of the week, age groups, weather variables, and long-term time trends including seasonality. The PM-mortality exposure-response relation was modeled several ways including: 1) log-linear functions, 2) flexible smoothed functions, and 3) models that assumed specific threshold levels. For all-cause mortality and for cardiovascular and respiratory mortality combined, a linear model without a threshold fit better than threshold models or even more flexible cubic spline models. These results may not be definitive but, when taken within the context of the overall literature, they provide increasingly compelling evidence that PM is a risk factor for cardiopulmonary mortality, even at relatively low concentrations.
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RESPONSE TO LONGER-TERM PM EXPOSURE
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The majority of studies of mortality effects of PM evaluated only short-term exposure. Longer-term, chronic exposure, however, may be much more important in terms of overall public health impacts. Several population-based, cross-sectional mortality studies evaluated associations between annual mortality rates and longer-term PM concentrations across US metropolitan areas (38

41
). In addition, a few prospective cohort studies have estimated mortality risk associated with air pollution after controlling for subject-specific differences in age, sex, cigarette smoking, and other risk factors (42
44
). These studies have generally observed that mortality, especially cardiopulmonary mortality, was significantly associated with PM pollution. The associations were strongest with fine and/or sulfate particles and were larger than those observed in the daily time-series studies.
Given the much smaller number of studies, the shape of the exposure-response relation of longer-term exposure has not been as carefully explored as has been done for the daily time-series studies. Figure 2, E and F, presents adjusted mortality rates or rate ratios for US cities plotted over corresponding fine PM levels based on data originally presented in reports of two prospective cohort studies of PM and mortality (43
, 44
). Based on casual viewing, the mortality effects can be reasonably modeled as linear, although Krewski et al. (45
) used flexible smoothing techniques and found some evidence of a nonlinear exposure response using these same data.
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CONCLUSIONS
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The paper by Daniels et al. (1
), reported in this issue of the Journal, is a commendable contribution that further indicates that assumptions or scientific priors of no-effects threshold levels for PM are not well supported by the empiric evidence. These results suggest a need to rethink the wisdom of regulatory standards for criteria pollutants (especially PM) that are based on the assumption of an observable and definable no-effects threshold. These results do not imply that current standards should not be health-based, nor do they provide the degree to which current standards need to be either relaxed or strengthened. They do imply, however, that health-based standards for PM may not be realistically designed to eliminate all risk, but to define levels that represent "acceptable" risk.
From at least one perspective, these results are good newsnot because exposure to PM contributes to cardiopulmonary disease mortality even at relatively low concentrations, but because it may represent a preventable cause of death. The fact that cardiopulmonary disease is a highly prevalent cause of death is well understood. Exposure to PM is just one of many risk factors, but it is one that can be directly modified. The results of this paper imply that further improvements in air quality, especially reductions in respirable PM, are likely to result in corresponding health improvements.
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NOTES
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Correspondence to Dr. C. Arden Pope III, 142 FOB, Brigham Young University, Provo, UT 84602 (e-mail: cap3{at}byu.edu).
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REFERENCES
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-
Daniels MJ, Dominici F, Samet JM, et al. Estimating particulate matter-mortality dose-response curves and threshold levels: an analysis of daily time-series for the 20 largest US cities. Am J Epidemiol 2000;152:397406.[Abstract/Free Full Text]
-
Fairley D. The relationship of daily mortality to suspended particulates in Santa Clara County, 19801986. Environ Health Perspect 1990;89:15968.[ISI][Medline]
-
Dockery DW, Schwartz J, Spengler JD. Air pollution and daily mortality: associations with particulates and acid aerosols. Environ Res 1992;59:36273.[ISI][Medline]
-
Pope CA III, Schwartz J, Ransom MR. Daily mortality and PM 10 pollution in Utah Valley. Arch Environ Health 1992;47:21117.[ISI][Medline]
-
Schwartz J, Dockery DW. Particulate air pollution and daily mortality in Steubenville, Ohio. Am J Epidemiol 1992;135:1219.[Abstract]
-
Schwartz J, Dockery DW. Increased mortality in Philadelphia associated with daily air pollution concentrations. Am Rev Respir Dis 1992;145:6004.[ISI][Medline]
-
Schwartz J. Air pollution and daily mortality in Birmingham, Alabama. Am J Epidemiol 1993;137:113647.[Abstract]
-
Utell MJ, Samet JM. Particulate air pollution and health: new evidence on an old problem. Am Rev Respir Dis 1993;147:13345.[ISI][Medline]
-
Samet JM, Zeger SL, Berhane K. The association of mortality and particulate air pollution. Cambridge, MA: Health Effects Institute, 1995.
-
Samet JM, Zeger SL, Kelsall JE, et al. Does weather confound or modify the association of particulate air pollution with mortality? An analysis of the Philadelphia data 19731980. Environ Res 1998;77:919.[ISI][Medline]
-
Samet JM, Zeger S, Dominici F, et al. The National Morbidity, Mortality, and Air Pollution Study (NMAPS). Part I. Methods and methodological issues. Cambridge, MA: Health Effects Institute, 2000. (Report no. 94).
-
Dominici F, Samet JM, Xu J, et al. Combining evidence on air pollution and daily mortality from the largest 20 U.S. cities: a hierarchical modeling strategy (with discussion). J R Stat Soc (A) (in press).
-
Samet JM, Dominici F, Xu J, et al. Particulate air pollution and mortality: findings from 20 U.S. cities. N Engl J Med 2000 (in press).
-
Zeger SL, Dominici F, Samet J. Harvesting-resistant estimates of air pollution effects on mortality. Epidemiology 1999;10:1715.[ISI][Medline]
-
Dominici F, Zeger S, Samet JM. A measurement error correction model for time-series studies of air pollution and mortality. Biostatistics 2000 (in press).
-
Brimblecombe P. The big smoke. London, England: Methuen, 1987.
-
Lipfert FW. Air pollution and community health: a critical review and data sourcebook. New York, NY: Van Nostrand Reinhold, 1994.
-
Firket J. The cause of the symptoms found in the Meuse Valley during the fog of December, 1930. Bull Acad R Med Belg 1931;11:683741.
-
Ciocco A, Thompson DJ. A follow-up of Donora ten years after: methodology and findings. Am J Public Health 1961;51:15564.
-
Logan WPD, Glasg MD. Mortality in London fog incident, 1952. Lancet 1953;1:3368.
-
Holland WW, Bennett AE, Cameron IR, et al. Health effects of particulate pollution: reappraising the evidence. Am J Epidemiol 1979;110:527659.[Medline]
-
Pope CA III, Dockery DW. Epidemiology of particle effects. In: Holgate ST, Samet JM, Koren HS, et al, eds. Air pollution and health. London, England: Academic Press, 1999:673705.
-
Ostro B. A search for a threshold in the relationship of air pollution to mortality: a reanalysis of data on London winters. Environ Health Perspect 1984;58:3979.[ISI][Medline]
-
Schwartz J, Marcus A. Mortality and air pollution in London: a time series analysis. Am J Epidemiol 1990;131:18594.[Abstract]
-
Schwartz J. Particulate air pollution and daily mortality in Detroit. Environ Res 1991;56:20413.[ISI][Medline]
-
Saldiva PHN, Pope CA III, Schwartz J, et al. Air pollution and mortality in elderly people: a time series study in Sao Paulo, Brazil. Arch Environ Health 1995;50:15963.[ISI][Medline]
-
Pope CA III, Kalkstein LS. Synoptic weather modeling and estimates of the exposure-response relationship between daily mortality and particulate air pollution. Environ Health Perspect 1996;104:41420.[ISI][Medline]
-
Schwartz J. Harvesting and long term exposure effects in the relation between air pollution and mortality. Am J Epidemiol 2000;151:4408.[Abstract]
-
Schwartz J. Total suspended particulate matter and daily mortality in Cincinnati, Ohio. Environ Health Perspect 1994;102:1869.[ISI][Medline]
-
Xu Z, Yu D, Jing L, et al. Air pollution and daily mortality in Shenyang, China. Arch Environ Health 2000;47:11520.
-
Schwartz J, Dockery DW, Neas LM. Is daily mortality associated specifically with fine particles? J Air Waste Manag Assoc 1996;46:92739.[ISI]
-
Katsouyanni K, Touloumi G, Spix C, et al. Short term effects of ambient sulphur dioxide and particulate matter on mortality in 12 European cities: results from time series data from the APHEA project. BMJ 1997;314:165863.[Abstract/Free Full Text]
-
Burnett RT, Cakmak S, Brook JR. The effect of the urban ambient air pollution mix on daily mortality rates in 11 Canadian cities. Can J Public Health 1998;89:1526.[ISI][Medline]
-
Lipfert FW, Wyzga RE. Air pollution and mortality: the implications of uncertainties in regression modeling and exposure measurement. J Air Waste Manag Assoc 1997;47:51723.[ISI][Medline]
-
Watt M, Godden D, Cherrie J, et al. Individual exposure to particulate air pollution and its relevance to threshold for health effects: a study of traffic wardens. Occup Environ Med 1995;52:7902.[Abstract]
-
Cakmak S, Burnett RT, Krewski D. Methods for detecting and estimating population threshold concentrations for air pollution-related mortality with exposure measurement error. Risk Anal 1999;19:48796.[ISI][Medline]
-
Schwartz J, Zanobetti A. Is there a threshold in the relation between particulate air pollution and daily deaths: a meta-smoothing approach. Epidemiology (in press).
-
Lave LB, Seskin EP. Air pollution and human health. Science 1970;169:72333.[ISI][Medline]
-
Evans JS, Tosteson T, Kinney PL. Cross-sectional mortality studies and air pollution risk assessment. Environ Int 1984;10:5583.[ISI]
-
Lipfert FW, Malone RG, Daum ML, et al. A statistical study of the macroepidemiology of air pollution and total mortality. Upton, NY: Brookhaven National Laboratory, 1988. (BNL report no. 52122).
-
Ozkaynak H, Thurston GD. Associations between 1980 U.S. mortality rates and alternate measures of airborne particle concentrations. Risk Anal 1987;7:44961. (BNL report no. 52112).[ISI][Medline]
-
Abbey DE, Nishino N, McDonnell WF, et al. Long-term inhalable particles and other air pollutants related to mortality in nonsmokers. Am J Respir Crit Care Med 1999;159:37382.[Abstract/Free Full Text]
-
Dockery DW, Pope CA III, Xu X, et al. An association between air pollution and mortality in six U.S. cities. N Engl J Med 1993;329:17539.[Abstract/Free Full Text]
-
Pope CA III, Thun MJ, Namboodiri MM, et al. Particulate air pollution as a predictor of mortality in a prospective study of U.S. adults. Am J Respir Crit Care Med 1995;151:66974.[Abstract]
-
Krewski D, Burnett RT, Goldberg MS, et al. Re-analysis of the Harvard Six-Cities Study and the American Cancer Society Study of air pollution and mortality. Cambridge, MA: Health Effects Institute, 2000.
Received for publication July 3, 2000.
Accepted for publication July 20, 2000.
Related articles in Am. J. Epidemiol.:
- Estimating Particulate Matter-Mortality Dose-Response Curves and Threshold Levels: An Analysis of Daily Time-Series for the 20 Largest US Cities
- Michael J. Daniels, Francesca Dominici, Jonathan M. Samet, and Scott L. Zeger
Am. J. Epidemiol. 2000 152: 397-406.
[Abstract]
[FREE Full Text]