The link between particulate pollution and mortality was originally recognized in the context of severe episodes of poor air quality in the 20th century, such as the London Fog of 1952.1 These episodes showed clear evidence that the number of deaths increased in association with high levels of particulate matter (PM). The policy response to the increasing evidence of the effects of air pollution on public health was for governments to develop air-quality regulations. In the United States, the Clean Air Act of 1970 mandated that the Environmental Protection Agency (EPA) develop national ambient air-quality standards (NAAQS) to protect even the most vulnerable members of the general population from adverse health effects.2 An NAAQS for PM was initially established in 1971.

The current primary NAAQS for PM applies to particles with an aerodynamic diameter of 2.5 μm or less (PM 2.5 ) — particles that are small enough to be deposited in the alveoli. A secondary NAAQS applies to particles with an aerodynamic diameter of 10 μm or less (PM 10 ) — particles that can be deposited in large airways. The epidemiologic evidence in support of the adoption of an NAAQS for PM 2.5 was largely from time-series studies.3 Time-series analyses include daily measures of health events (e.g., daily mortality), regressed against concentrations of PM (e.g., 24-hour average PM 2.5 ) and weather variables (e.g., daily average temperature) for a given geographic area. The population serves as its own control, and confounding by population characteristics is negligible because these are stable over short time frames. Time-series studies can be confounded by time-varying factors such as influenza epidemics and temperature; however, statistical methods to reduce such confounding have been developed.3

Many time-series studies have been conducted in cities in various countries around the world. Efforts have been made to include larger regions in time-series analyses to increase the generalizability of the reported associations.4 A meta-analysis has shown that the PM 2.5 –mortality association remains robust in pooled analyses.5 Multiple longitudinal cohort studies of the association between long-term PM 2.5 exposure and mortality, in which individual-level covariates were included in the analyses, have generally shown even stronger associations, providing important support for the evidence from time-series studies.6 Moreover, experimental data from exposure studies in animals and controlled exposure studies in humans have increasingly provided mechanistic evidence in support of the epidemiologic findings.

Given the abundance of evidence in support of an association between short-term PM 2.5 exposure and mortality, what is the contribution of the time-series study by Liu et al. in this issue of the Journal?7 First, this study included almost 60 million deaths from 652 cities in 24 countries, thereby greatly increasing the generalizability of the association and decreasing the likelihood that the reported associations are subject to confounding bias. In observations consistent with previous studies, all-cause (nonaccidental), cardiovascular, and respiratory mortality were associated with short-term exposures to both PM 10 and PM 2.5 . The strength of the associations was reduced but remained significant in two-pollutant models that addressed potential confounding by gaseous pollutants.

Perhaps the most interesting result of the study by Liu et al. is from their concentration–response analysis. On the basis of studies of exposure to multiple combustion sources of PM 2.5 (outdoor air pollution, secondhand tobacco smoke, and active tobacco smoking) and cardiovascular mortality, Pope et al. proposed that the shape of the concentration–response relation is curvilinear, with a lesser slope at higher exposure levels.8 Although other studies have reported evidence of such curvilinearity, the current study of PM data from many regions around the world provides the strongest evidence to date that higher levels of exposure may be associated with a lower per-unit risk. Regions that have lower exposures had a higher per-unit risk. This finding has profound policy implications, especially given that no threshold of effect was found. Even high-income countries, such as the United States, with relatively good air quality could still see public health benefits from further reduction of ambient PM concentrations (i.e., below the current NAAQS).