Elsevier

Annals of Epidemiology

Volume 25, Issue 3, March 2015, Pages 162-173
Annals of Epidemiology

Original article
Has reducing fine particulate matter and ozone caused reduced mortality rates in the United States?

https://doi.org/10.1016/j.annepidem.2014.11.006Get rights and content

Abstract

Purpose

Between 2000 and 2010, air pollutant levels in counties throughout the United States changed significantly, with fine particulate matter (PM2.5) declining over 30% in some counties and ozone (O3) exhibiting large variations from year to year. This history provides an opportunity to compare county-level changes in average annual ambient pollutant levels to corresponding changes in all-cause (AC) and cardiovascular disease (CVD) mortality rates over the course of a decade. Past studies have demonstrated associations and subsequently either interpreted associations causally or relied on subjective judgments to infer causation. This article applies more quantitative methods to assess causality.

Methods

This article examines data from these “natural experiments” of changing pollutant levels for 483 counties in the 15 most populated US states using quantitative methods for causal hypothesis testing, such as conditional independence and Granger causality tests. We assessed whether changes in historical pollution levels helped to predict and explain changes in CVD and AC mortality rates.

Results

A causal relation between pollutant concentrations and AC or CVD mortality rates cannot be inferred from these historical data, although a statistical association between them is well supported. There were no significant positive associations between changes in PM2.5 or O3 levels and corresponding changes in disease mortality rates between 2000 and 2010, nor for shorter time intervals of 1 to 3 years.

Conclusions

These findings suggest that predicted substantial human longevity benefits resulting from reducing PM2.5 and O3 may not occur or may be smaller than previously estimated. Our results highlight the potential for heterogeneity in air pollution health effects across regions, and the high potential value of accountability research comparing model-based predictions of health benefits from reducing air pollutants to historical records of what actually occurred.

Section snippets

Introduction: using data from natural experiments to understand causality

An aim of applied science in general and of epidemiology in particular is to draw sound causal inferences from observations. Students are taught to develop hypotheses about causal relations, devise testable implications of these causal hypotheses, carry out the tests, and objectively report and learn from the results to refute or refine the initial hypotheses. For at least the past two decades, however, epidemiologists and commentators on scientific methods and results have raised concerns that

Data and methods

Cause-specific mortality rates, by county and age group, were downloaded from the Centers for Disease Control and Prevention Wonder “Compressed Mortality, 1999 to 2010” database [43]. To create a geographically diverse sample, mortality rates were extracted at the county level for the 15 largest states in the United States (California, Texas, New York, Florida, Illinois, Pennsylvania, Ohio, Georgia, Michigan, North Carolina, New Jersey, Virginia, Washington, Massachusetts, and Arizona)

Descriptive statistics

Figure 1 shows trends in average pollution levels, population, and mortality rates for all counties from 2000 to 2010. For each time series, values are normalized by dividing by the value in 2000, so that all time series values in 2000 are defined as 1.0. PM2.5 and CVD mortality rates declined most steeply over this interval (two lowest curves), whereas population levels and external-cause mortality rates (e.g., from accidents) increased, perhaps reflecting a longer-lived aging population.

Discussion and conclusions: caveats for causal interpretations of regression coefficients

The epidemiologic and risk assessment literature on human health effects of air pollution contains dozens of studies that attribute reductions in mortality risks to reductions in air pollution levels and that estimate the slope of the concentration-response association between exposures to pollutants and corresponding mortality rates [12], [20], [22], [47], [51], [52]. The work reported here contributes a new data set to this literature. It supports previous findings of positive PM2.5-mortality

Acknowledgments

The research described here was supported in part by the American Petroleum Institute and by Cox Associates, LLC. The research questions asked, methods used, and conclusions reached are solely those of those the authors. The authors thank reviewers for their comments and suggestions, which improved the clarity of the exposition.

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