Approaches to Uncertainty in Exposure Assessment in Environmental Epidemiology

Spiegelman, Donna

doi:10.1146/annurev.publhealth.012809.103720

Cited by 70 publications

(67 citation statements)

References 56 publications

(75 reference statements)

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“…It is well known that the use of widely spaced monitoring stations as an exposure metric in environmental epidemiology induces bias, which underestimates the effect size in many cases 30,31 . And this appears more prominent in a case where the exposure of interest dynamically changes in space, as occurs for temperature distribution within a city 32 .…”

Section: Discussionmentioning

confidence: 99%

Study on the association between ambient temperature and mortality using spatially resolved exposure data

Lee

Shi

Zanobetti

et al. 2016

Environmental Research

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There are many studies that have posited an association between extreme temperature and increased mortality. However, most studies use temperature at a single station per city as the reference point to analyze deaths. This leads to exposure misclassification and usually the exclusion of exurban, small town, and rural populations. In addition, few studies control for confounding by PM2.5, which is expected to induce upward bias. The high-resolution temperature and PM2.5 data at a resolution of 1 km2 were derived from satellite images and other land use sources. To capture the nonlinear association of temperature with mortality we fit a piecewise linear spline function for temperature, with a change in slope at −1 °C and 28 °C, the temperature threshold at which mortality in Georgia, North Carolina, and South Carolina increases due to cold and heat, respectively. We conducted stratified analyses by age group, sex, race, education, and urban vs nonurban, as well as sensitivity analyses of different temperature threshold and covariate sets. We found a 0.19% (95% CI = −0.98, 1.34%) increase in mortality for each 1 °C decrease in temperature below −1 °C and a 2.05% (95% CI = 0.87, 3.24%) increase in mortality for each 1°C increase in temperature above 28 °C, a 79.8% larger effect size for heat compared to the station-based metric. The effect estimates relying on the monitoring stations were 0.09% (95% CI = −0.79, 0.95%) and 1.14 % (95% CI = 0.08, 1.57%) for the equivalent temperature changes. The estimates were not confounded by PM2.5. Children under 15 years of age had the largest percentage increase per 1 °C increase in temperature (8.19%, 95% CI = −0.38 to 17.49%) followed by Blacks (4.35%, 95% CI = 2.22 to 6.53%). Higher education was a protective factor for the effect of extreme temperature on mortality. There was a suggestion that people in less urban areas were more susceptible to extreme temperature. The relationship between temperature and mortality was stronger when using exposure data with more spatial variability than using exposure data based on existing monitors alone.

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Section: Discussionmentioning

confidence: 99%

Study on the association between ambient temperature and mortality using spatially resolved exposure data

Lee

Shi

Zanobetti

et al. 2016

Environmental Research

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“…Traditionally, in large population based studies, environmental exposure assessment is performed using questionnaire methods (for overview of challenges and considerations of exposure assessment, see (Rothman and Greenland 1998)). These approaches are based on the recollection of the participant, and therefore are subject to error (Spiegelman 2010). More sophisticated quantitative methods of exposure assessment are often expensive and difficult to apply in large studies.…”

Section: Exposure Assessmentmentioning

confidence: 99%

“…Another challenge with environmental exposure assessment, is that unlike germline genetic variation, which is considered to remain constant in an individual's lifetime, environmental exposures are dynamic and change over time and an individual's lifespan (Spiegelman 2010). There is uncertainty in environmental data stemming from our lack of knowledge of the timing of effects.…”

Section: Exposure Assessmentmentioning

confidence: 99%

Gene-Environment Interactions in Human Health

Mechanic

Hutter

2015

Molecular and Integrative Toxicology

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Risk of most complex diseases is determined by a combination of environmental and genetic factors. By studying gene-environment interactions, it may be possible to describe disease mechanisms, discover novel genetic variants associated with disease, better understand heterogeneity between populations, identify populations with higher risk from exposure, and target preventive and therapeutic interventions. However, there are several challenges to the study of gene-environment interactions. As technologies and analytical tools improve, opportunities to better understand the complex interplay between genes and environment may result in improved insights in disease and treatment outcomes.

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“…In epidemiological studies, limitations in exposure assessment may lead to not detecting associations or underestimating their strength. 6,7 Moreover, knowledge of exposure in real conditions of use is crucial for the risk management and exposure reduction.…”

Section: Introductionmentioning

confidence: 99%

Levels and determinants of pesticide exposure in operators involved in treatment of vineyards: results of the PESTEXPO Study

Baldi

Lebailly

Rondeau

et al. 2012

J Expo Sci Environ Epidemiol

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Exposure assessment is a critical point for epidemiological studies on pesticide health effects. PESTEXPO study provides data on levels of exposure and their determinants in real conditions of pesticide use. We described levels of exposure in vineyards during treatment tasks (mixing, spraying and cleaning) and we analysed their determinants. Sixty-seven operators using dithiocarbamates or folpet were observed. Detailed information on the tasks (general conditions, operator, farm and equipment characteristics) were collected and dermal contamination was measured, using patches placed onto the skin on eleven body parts, and washing the hands at the end of each phase. The spraying phase represented roughly half of the contamination, whereas mixing and equipment cleaning accounted for 30% and 20% of the contamination, respectively. The main determinants of exposure were the number of phases, the characteristics of the equipment, the educational level of the operator and his status (farm -worker or -owner) and the general characteristics of the vines. Algorithms were built to estimate daily external contamination, according to these characteristics during mixing, spraying or equipment cleaning. With additional information of frequency and duration of use, they will enable to develop exposure indices usable in epidemiological studies on farmers' health.

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Approaches to Uncertainty in Exposure Assessment in Environmental Epidemiology

Cited by 70 publications

References 56 publications

Study on the association between ambient temperature and mortality using spatially resolved exposure data

Study on the association between ambient temperature and mortality using spatially resolved exposure data

Gene-Environment Interactions in Human Health

Levels and determinants of pesticide exposure in operators involved in treatment of vineyards: results of the PESTEXPO Study

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