An Analysis of the Association between U.S. Mortality and Air Pollution

Lave, Lester B.; Seskin, Eugene P.

doi:10.1080/01621459.1973.10482421

Cited by 40 publications

(25 citation statements)

References 9 publications

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“…Some research revisited mortality in London (e.g., 68,97,113,163). Additional time-series analyses were performed for New York City (9,53,63,84,85,116,139,141), Tokyo (87), Philadelphia (182), and 117 U.S. metropolitan areas (81). Investigators recognized the importance of the potential confounding effects of: (a) the levels of other pollutants; (b) weather; and (c) seasonal variations in mortality due to influenza, which might be associated erroneously with the seasonal variations in PM.…”

Section: The Evolution Of the Time-series Approach To Studying Air Pomentioning

confidence: 99%

Time-Series Studies of Particulate Matter

Bell

Samet

Dominici

2004

Annu. Rev. Public Health

274

138

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Key Words air pollution, public health, epidemiology, regression models s 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.

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Section: The Evolution Of the Time-series Approach To Studying Air Pomentioning

confidence: 99%

Time-Series Studies of Particulate Matter

Bell

Samet

Dominici

2004

Annu. Rev. Public Health

274

138

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“…In a previous study (Lave and Seskin, 1970a) we determined the "'best" set of regressions for a number of mortality rates. The specification was reestimated with data from another year.…”

Section: Methodsmentioning

confidence: 99%

“…We have investigated the health effects of air pollution and reported several sets of results (Lave and Seskin, 1970, 1970a, 1970b, 1971, Lave, 1972. The basic approach is to explain differences in the mortality rates among U.S. cities by the level of air pollution and socioeconomic variables.…”

Section: Introductionmentioning

confidence: 99%

Air pollution, climate, and home heating: their effects on U.S. mortality rates.

Lave¹,

Seskin²

1972

Am J Public Health

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The aim of this report is to determine whether changes in air pollution have an effect on health. Climate and home heating variables are included to see whether they may be involved. These studies indicate a close association between mortality rates and air pollution and lead to the conclusion that mortality rates could be lowered by abating pollution. Estimates of economic benefits from improved health are discussed.

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“…Over the past three decades, epidemiologists have identified various physical and chemical mass -based measures of airborne particulate matter, for example, total suspended particles ( TSP ), PM 10 (particulate matter less than 10 m in aerodynamic diameter ), PM 2.5 ( particulate matter less than 2.5 m in aerodynamic diameter ), and sulfate as important aerosol measures or components to be statistically significantly associated with observed acute or chronic health effects data. These include premature mortality, increased hospital admissions and emergency room visits ( primarily among the elderly and individuals with cardiopulmonary disease), increased respiratory symptoms and disease (in children and individuals with cardiopulmonary disease such as asthma), decreased lung function (particularly in children and individuals with asthma ) and alterations in lung tissue, structure and respiratory tract defense mechanisms (Logan, 1953;Lave and Seskin, 1973;Dockery et al, 1989;Schwartz and Dockery, 1992;Ito and Thurston, 1996 A key concern with the approach provided by PM epidemiological studies involves its sole reliance on ambient monitoring station measurements of PM, and relationships derived from these data. Since PM health effects should derive from total personal exposure to PM, including PM inhaled while indoors and outdoors, the plausibility of the empirical relationship between ambient PM and acute mortality ( and morbidity ) is called into question ( Mage et al, 1999 ).…”

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confidence: 99%

Incorporating exposure models in probabilistic assessment of the risks of premature mortality from particulate matter

Yeh

Small

2002

J Expo Sci Environ Epidemiol

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This paper examines the link between the ambient level of particulate pollution and subsequent human health effects and various sources of uncertainty when total exposure is taken into consideration. The exposure simulation model statistically simulates daily personal total exposure to ambient PM and nonambient PM generated from indoor sources. It incorporates outdoor -indoor penetration of PM, contributions of PM from indoor sources, and time -activity patterns for target groups of the population. The model is illustrated for Los Angeles County using recent 1997 monitoring data for both PM 10 and PM 2.5 . The results indicate that, on average, outdoor -source PM contributes about 20 -25% of the total PM exposure to Los Angeles County individuals not exposed to environmental tobacco smoking ( ETS ), and about 15% for those who are exposed to ETS. The model computes both the fractional contribution of outdoor concentrations to total exposure and the effect of exposure uncertainties on the estimated slope of the ( linear ) concentration -response curve in time -series studies for PM health effects. The latter considers the effects of measurement and misclassification error on PM epidemiological time -series studies. The paper compares the predictions of a conventional PM epidemiological model, based solely on ambient concentration measurements at a central monitoring station, and an exposure simulation model, which considers the quantitative relationship between central -monitoring PM concentrations and total individual exposures to particulate matter. The results show that the effects of adjusting from outdoor concentrations to personal exposures and correcting dose -response bias are nearly equal, so that roughly the same premature mortalities associated with short -term exposure to both ambient PM 2.5 and PM 10 in Los Angeles County are predicted with both models. The uncertainty in the slope of the concentration -response curve in the time -series studies is the single most important source of uncertainty in both the ambient -and the exposure -health model. Journal of Exposure Analysis and Environmental Epidemiology ( 2002 ) 12, 389 -403 doi:10.1038/sj.jea.7500240Keywords: exposure, measurement error, particulate matter, premature mortality, uncertainty. IntroductionAmbient particulate matter originates both from natural processes and anthropogenic emissions such as fossil fuel combustion, industrial manufacturing, and construction. Over the past three decades, epidemiologists have identified various physical and chemical mass -based measures of airborne particulate matter, for example, total suspended particles ( TSP ), PM 10 (particulate matter less than 10 m in aerodynamic diameter ), PM 2.5 ( particulate matter less than 2.5 m in aerodynamic diameter ), and sulfate as important aerosol measures or components to be statistically significantly associated with observed acute or chronic health effects data. These include premature mortality, increased hospital admissions and emergency room visits ( primarily a...

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An Analysis of the Association between U.S. Mortality and Air Pollution

Cited by 40 publications

References 9 publications

Time-Series Studies of Particulate Matter

Time-Series Studies of Particulate Matter

Air pollution, climate, and home heating: their effects on U.S. mortality rates.

Incorporating exposure models in probabilistic assessment of the risks of premature mortality from particulate matter

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