2016 Progress Report: Project 3: Causal Estimates of Effects of Regional and National Pollution Mixtures on Health: Providing Tools for Policy MakersEPA Grant Number: R835872C003
Subproject: this is subproject number 003 , established and managed by the Center Director under grant R835872
(EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
Center: Regional Air Pollution Mixtures
Center Director: Koutrakis, Petros
Title: Project 3: Causal Estimates of Effects of Regional and National Pollution Mixtures on Health: Providing Tools for Policy Makers
Investigators: Schwartz, Joel , Coull, Brent , Koutrakis, Petros , Zanobetti, Antonella
Institution: Harvard University , Massachusetts Institute of Technology
EPA Project Officer: Keating, Terry
Project Period: December 1, 2015 through November 30, 2020
Project Period Covered by this Report: December 1, 2015 through November 30,2016
RFA: Air, Climate And Energy (ACE) Centers: Science Supporting Solutions (2014) RFA Text | Recipients Lists
Research Category: Air , Climate Change , Air Quality and Air Toxics , Airborne Particulate Matter Health Effects , Particulate Matter
The objective of Project 3 is to estimate the causal impact of changes in pollution concentrations and mixtures (annual averages and daily patterns), how they vary by modifiable factors, the causal impacts of AQI triggers, how climate change that occurred in the last 20 years has increased mortality due to pollution, how temperature modifies the effects of pollution mixtures, and how these effects change for exposures less than the ambient standards for PM2.5. Project 3 provides region-specific causal estimates of effects of pollution mixtures; provides causal estimates of the impact of modifiable factors; assesses the impact of climate change on mortality from air pollution using historic data, avoiding any dependence on the accuracy of climate models; and provides causal estimates of how changes in particular components of mixtures affect mortality, to guide region-specific policy decisions on air pollution. Project 3 has five specific objectives.
Objective 1 is to identify and estimate the causal effects of air pollution and mixtures on human health. We will use methods of causal inference to a) identify the causal effects of regional annual air pollution concentration fluctuations and temperature fluctuations during the last 16 years on human health; b) identify the causal effects of regional air pollution trends during the last 16 years; c) identify the causal effects of pollution mixtures, sources, and emissions on health; d) identify differences in these effects by modifiable factors; e) conduct a national risk assessment on the causal impact of past pollution on mortality, including the regional differences in concentration-response; and f) investigate the causal impact of AQI thresholds for PM2.5 and O3 due to behavioral adaptation. Objective 2 is to analyze relative acute toxicity of pollution mixtures. We will a) examine spatial (across regions) and temporal heterogeneity in the acute toxicity of pollution mixtures and emissions to understand which source types, atmospheric processes, and exposure factors influence the toxicity of regional mixtures and b) use causal mediation analysis to determine how much of the temperature effect on mortality is mediated by its effects of pollution concentrations, and how that varies regionally. This will allow us to obtain local- and region specific estimates of future health effects and the benefits of changes in modifiable factors and adaptation. Objective 3 is to estimate the excess deaths resulting from air pollutant concentration changes due to weather changes in the last 20 years. We will demonstrate the extent to which public health impacts of climate change through pollution have already occurred, by using causal estimates of C-R relationships. Regional health impacts will be assessed using region-specific mortality risks estimates from Objective 1. Objective 4 is to estimate the causal health effects of low-level air pollution exposure. Specifically, we will examine whether the observed effects at low pollutant levels are due to the synergistic effect of multiple pollutants (mixtures) present at low levels. And Objective 5 is to investigate air pollution-related health effects at high and low temperatures. We will examine this by region and determine whether populations, especially those that include sensitive individuals, adapt to abrupt temperature changes.
We have made considerable advancements in the first year. In terms of exposure, we developed a deep neural network to fuse satellite remote sensing data, GEOS-Chem predictions, land use, and monitoring data, to predict daily ozone (8-hour maximum) on a 1x1km grid for the entire United States (Di, 2017). This model had a cross-validated R2 of 0.76.
In terms of health studies, we have a paper in press (Wang 2017) which took the entire Medicare population (13 million) of the Southeastern U.S. as a cohort, and examined the association of their survival with their PM2.5 exposure. Importantly, this model examined low dose exposure, by restricting to locations where PM2.5 was less than 12 µg/m3, examined, and found effect modification by chemical components of PM2.5 and by mean summer temperature, and examined effect modification by race, sex, and poverty.
Another health study (Schwartz, 2017, in press) used two different causal modeling techniques to examine the effect of short-term changes in PM2.5 and daily deaths in Boston. We used the height of the planetary boundary layer and wind speed as instrumental variables for short term changes in particle concentrations that are not correlated with any confounders, and showed these changes were associated with changes in daily deaths, which, given the lack of association with confounders, are causal. We also used a negative exposure control to similarly demonstrate the lack of any confounder whose short-term association was correlated with these variations in local air pollution, unless that correlation was very short lived.
Further work on particle components includes the paper of Peng (2017, in press) looking at the effects of long term exposure to particle components on mitochondrial damage, a key determinant of biological aging.
Using our national exposure models we expect to complete both a national cohort study and a national case-crossover study in the next year using the entire Medicare population as a cohort. In addition, we will continue working on causal modeling methods and applying them to examining both the short and long-term effects of particle and ozone exposure. Other work will focus on birth outcomes.
Journal Articles on this Report : 3 Displayed | Download in RIS Format
|Other subproject views:||All 3 publications||3 publications in selected types||All 3 journal articles|
|Other center views:||All 60 publications||51 publications in selected types||All 51 journal articles|
||Schwartz J, Bind MA, Koutrakis P. (2017) Estimating causal effects of local air pollution on daily deaths:effect of low levels. Environ Health Perspect 125:23–29; http://dx.doi.org/10.1289/EHP232.||
||Di Q, Rowland S, Koutrakis P, Schwartz J. (2017) A hybrid model for spatially and temporally resolved ozone exposures in the continental United States. J Air and Waste Management Association, 67.1:39-52.||
||Wang, Y., Shi, L.H., Lee, M., Liu, P.F., Di, Q., Zanobetti, A., and Schwartz, J. (2017). Long-term Exposure to PM2.5 and Mortality Among Older Adults in the Southeastern US. Epidemiology 28, 207-214.||
Supplemental Keywords:particles, particulate matter, pollutant mixtures, regional pollution, risk analysis, causal modeling
Progress and Final Reports:Original Abstract
Main Center Abstract and Reports:R835872 Regional Air Pollution Mixtures
Subprojects under this Center: (EPA does not fund or establish subprojects; EPA awards and manages the overall grant for this center).
R835872C001 Project 1: Regional Air Pollution Mixtures: The Past and Future Impacts of Emission Controls and Climate Change on Air Quality and Health
R835872C002 Project 2: Air Pollutant Mixtures in Eastern Massachusetts: Spatial Multi-resolution Analysis of Trends, Effects of Modifiable Factors, Climate and Particle-induced Mortality
R835872C003 Project 3: Causal Estimates of Effects of Regional and National Pollution Mixtures on Health: Providing Tools for Policy Makers
R835872C004 A Causal Inference Framework to Support Policy Decisions by Evaluating the Effectiveness of Past Air Pollution Control Strategies for the Entire United States
R835872C005 Project 5: Projecting and Quantifying Future Changes in Socioeconomic Drivers of Air Pollution and its Health-Related Impacts