Potential confounding of particulate matter on the short-term association between ozone and mortality in multisite time-series studies

Abstract

Background: A critical question regarding the association between short-term exposure to ozone and mortality is the extent to which this relationship is confounded by ambient exposure to particles.

Objectives: We investigated whether particulate matter < 10 and < 2.5 microm in aerodynamic diameter (PM(10) and PM(2.5)) is a confounder of the ozone and mortality association using data for 98 U.S. urban communities from 1987 to 2000.

Methods: We a) estimated correlations between daily ozone and daily PM concentrations stratified by ozone or PM levels; b) included PM as a covariate in time-series models; and c) included PM as a covariate as in d), but within a subset approach considering only days with ozone below a specified value.

Results: Analysis was hindered by data availability. In the 93 communities with PM(10) data, only 25.0% of study days had data on both ozone and PM(10). In the 91 communities with PM(2.5) data, only 9.2% of days in the study period had data on ozone and PM(2.5). Neither PM measure was highly correlated with ozone at any level of ozone or PM. National and community-specific effect estimates of the short-term effects of ozone on mortality were robust to inclusion of PM(10) or PM(2.5) in time-series models. The robustness remains even at low ozone levels (< 10 ppb) using a subset approach.

Conclusions: Results provide evidence that neither PM(10) nor PM(2.5) is a likely confounder of observed ozone and mortality relationships. Further investigation is needed to investigate potential confounding of the short-term effects of ozone on mortality by PM chemical composition.

Keywords: PM10; PM2.5; confounding; mortality; ozone; particulate matter; sensitivity analysis.

Figure 1

Frequency of daily ozone concentrations (between brackets) and correlation between same-day ozone and PM₁₀ (blue) and PM_2.5 (gray) levels within specified strata of ozone concentrations. Not enough data were available for days with ozone levels > 80 ppb to generate a representative correlation coefficient.

Figure 2

Frequency of the daily 8-hr maximum ozone concentrations (between brackets) and correlation between same day ozone and PM₁₀ (blue) and PM_2.5 (gray) levels within specified strata of ozone concentrations

Figure 3

Frequency of the daily 1-hr maximum ozone concentrations (between brackets) and correlation between same day ozone and PM₁₀ (blue) and PM_2.5 (gray) levels within specified strata of ozone concentrations.

Figure 4

Frequency of the average of the same and previous day’s ozone concentrations (between brackets) and correlation between ozone and the previous day’s PM₁₀ (blue) and the previous day’s PM_2.5 (gray) levels within specified strata of ozone concentrations. Not enough data were available for days with ozone levels > 80 ppb to generate a representative correlation coefficient.

Figure 5

Percent increase in daily nonaccidental mortality per 10-ppb increase in the average of the same and previous day’s ozone levels (lag ), with and without adjustment by PM₁₀ (A) and PM_2.5 (B) at lag 1 day. Open symbols represent community-specific estimates; blue circles represent overall national effects.

Figure 6

Percent increase in daily nonaccidental mortality per 10 ppb increase in the lag ozone levels, with and without adjustment by PM₁₀ at lag 1 day, using the subset approach. (A) 93 communities, s = 60; (B) 93 communities, s = 50; (C) 93 communities, s = 40; (D) 91 communities, s = 30; (E) 83 communities, s = 20; (F) 34 communities, s = 10. The analysis without adjustment by PM includes only days for which lag 1 PM₁₀ data are available. Only days with ozone data < s are included. Open symbols represent community-specific estimates; blue circles represent overall national effects.