title: Time-series studies of particulate matter.
abstract: Studies of air pollution and human health have evolved from descriptive studies of the early phenomena of large increases in adverse health effects following extreme air pollution episodes to time-series analyses based on the use of sophisticated regression models. In fact, advanced statistical methods are necessary to address the challenges inherent in the detection of a relatively small pollution risk in the presence of potential confounders. This paper reviews the history, methods, and findings of the time-series studies estimating health risks associated with short-term exposure to particulate matter (PM), though much of the discussion is applicable to epidemiological studies of air pollution in general. We review the critical role of epidemiological studies in setting regulatory standards and the history of PM epidemiology and time-series analysis. We also summarize recent time-series results and conclude with a discussion of current and future directions of time-series analysis of particulates, including research on mortality displacement and the resolution of results from cohort and time-series studies.
authors.affiliation: Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland 21205, USA. mbell6@jhu.edu
authors.forename: Michelle L
authors.initials: ML
authors.lastname: Bell
authors.forename: Jonathan M
authors.initials: JM
authors.lastname: Samet
authors.forename: Francesca
authors.initials: F
authors.lastname: Dominici
mesh_terms: D000393:Air Pollutants / Q000633:toxicity*; D003627:Data Interpretation, Statistical; D004782:Environmental Health / Q000331:legislation & jurisprudence; D015340:Epidemiologic Research Design; D006801:Humans; D009026:Mortality / Q000639:trends; D010316:Particle Size; D018570:Risk Assessment; D012307:Risk Factors; D013997:Time Factors
chemical_list: D000393:Air Pollutants