The association of long-term exposure to PM2.5 on all-cause mortality in the Nurses’ Health Study and the impact of measurement-error correction

Abstract

BackgroundLong-term exposure to particulate matter less than 2.5 μm in diameter (PM2.5) has been consistently associated with risk of all-cause mortality. The methods used to assess exposure, such as area averages, nearest monitor values, land use regressions, and spatio-temporal models in these studies are subject to measurement error. However, to date, no study has attempted to incorporate adjustment for measurement error into a long-term study of the effects of air pollution on mortality.MethodsWe followed 108,767 members of the Nurses’ Health Study (NHS) 2000–2006 and identified all deaths. Biennial mailed questionnaires provided a detailed residential address history and updated information on potential confounders. Time-varying average PM2.5 in the previous 12-months was assigned based on residential address and was predicted from either spatio-temporal prediction models or as concentrations measured at the nearest USEPA monitor. Information on the relationships of personal exposure to PM2.5 of ambient origin with spatio-temporal predicted and nearest monitor PM2.5 was available from five previous validation studies. Time-varying Cox proportional hazards models were used to estimate hazard ratios (HRs) and 95 percent confidence intervals (95%CI) for each 10 μg/m3 increase in PM2.5. Risk-set regression calibration was used to adjust estimates for measurement error.ResultsIncreasing exposure to PM2.5 was associated with an increased risk of mortality, and results were similar regardless of the method chosen for exposure assessment. Specifically, the multivariable adjusted HRs for each 10 μg/m3 increase in 12-month average PM2.5 from spatio-temporal prediction models were 1.13 (95%CI:1.05, 1.22) and 1.12 (95%CI:1.05, 1.21) for concentrations at the nearest EPA monitoring location. Adjustment for measurement error increased the magnitude of the HRs 4-10% and led to wider CIs (HR = 1.18; 95%CI: 1.02, 1.36 for each 10 μg/m3 increase in PM2.5 from the spatio-temporal models and HR = 1.22; 95%CI: 1.02, 1.45 from the nearest monitor estimates).ConclusionsThese findings support the large body of literature on the adverse effects of PM2.5, and suggest that adjustment for measurement error be considered in future studies where possible.

An Exposure-Mortality Relationship for Residential Indoor PM2.5 Exposure from Outdoor Sources

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A simulation study to quantify the impacts of exposure measurement error on air pollution health risk estimates in copollutant time-series models

“…Both identified a comprehensive understanding of exposure measurement error in the context of multipollutant studies as a key issue to address and investigate further. However while these papers detail work on multipollutant exposure metrics and statistical methods for analyzing multipollutant exposures, previous work to quantify the impact of exposure error on health risk estimates has focused on single-pollutant time-series models [6–8, 11–14]. While there are inherent difficulties in examining multipollutant exposures, we still do not have a clear understanding of the relationship of exposure measurement error in a more simplistic two pollutant model [15–17].…”

An automated online instrument to quantify aerosol-bound reactive oxygen species (ROS) for ambient measurement and health-relevant aerosol studies

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