Journal of exposure science & environmental epidemiology
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J Expo Sci Environ Epidemiol · Jul 2010
Randomized Controlled TrialPersonal child and mother carbon monoxide exposures and kitchen levels: methods and results from a randomized trial of woodfired chimney cookstoves in Guatemala (RESPIRE).
During the first randomized intervention trial (RESPIRE: Randomized Exposure Study of Pollution Indoors and Respiratory Effects) in air pollution epidemiology, we pioneered application of passive carbon monoxide (CO) diffusion tubes to measure long-term personal exposures to woodsmoke. Here we report on the protocols and validations of the method, trends in personal exposure for mothers and their young children, and the efficacy of the introduced improved chimney stove in reducing personal exposures and kitchen concentrations. Passive diffusion tubes originally developed for industrial hygiene applications were deployed on a quarterly basis to measure 48-hour integrated personal carbon monoxide exposures among 515 children 0-18 months of age and 532 mothers aged 15-55 years and area samples in a subsample of 77 kitchens, in households randomized into control and intervention groups. ⋯ No significant deterioration in stove effect was observed over the 18 months of surveillance. The reliability of these findings is strengthened by the large sample size made feasible by these unobtrusive and inexpensive tubes, measurement error reduction through instrument calibration, and a randomized, longitudinal study design. These results from the first randomized trial of improved household energy technology in a developing country and demonstrate that a simple chimney stove can substantially reduce chronic exposures to harmful indoor air pollutants among women and infants.
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J Expo Sci Environ Epidemiol · May 2010
Comparative StudyArsenic exposure in US public and domestic drinking water supplies: a comparative risk assessment.
Although approximately 35 million people in the US obtain drinking water from domestic wells, few studies have investigated the risk of arsenic exposure from this source. In this paper arsenic concentrations were modeled for public and domestic wells using a dataset from the US Geological Survey (USGS). Excess lifetime and annual risks for lung and bladder cancer were calculated based on the carcinogenic potency and average arsenic concentrations in public and domestic water supplies. ⋯ Domestic wells and public wells in the western US have the highest arsenic levels with excess fatality risks estimated to be in the range of 1 per 9300 to 1 per 6600 in these regions. Uncertainty distributions of excess fatalities were developed and resultant uncertainties were propagated in arsenic exposure and potency factor. Uncertainty in the carcinogenic potency of arsenic was the dominant source of uncertainty in most regions, but for domestic wells in the New England and Southeast regions uncertainty in arsenic exposure was dominant, indicating that additional data on arsenic concentrations in these areas would substantially improve regional risk estimates.
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J Expo Sci Environ Epidemiol · Nov 2009
ReviewUrine-sampling methods for environmental chemicals in infants and young children.
This review paper examines and evaluates urine-sampling methodologies in infants and young children, to determine which methods are suitable for use in large biomonitoring surveys or studies of environmental chemicals in children younger than 6 years. Methods for non-toilet-trained children include the use of urine bags, collection pads (e.g., cotton or gauze inserts), disposable diapers, cotton diapers, and the clean catch method. ⋯ Collection methods must not introduce contamination or affect the integrity of the sample, should be logistically practical, and should minimize discomfort experienced by the child. Although collection of urine samples from children who are not toilet-trained is more challenging than collection from older toilet-trained children, the vulnerability of younger children to the exposure to and health effects of environmental chemicals makes finding suitable methods a priority.
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J Expo Sci Environ Epidemiol · Mar 2008
Comparative StudyComparison of regression models with land-use and emissions data to predict the spatial distribution of traffic-related air pollution in Rome.
Spatial modeling of traffic-related air pollution typically involves either regression modeling of land-use and traffic data or dispersion modeling of emissions data, but little is known to what extent land-use regression models might be improved by incorporating emissions data. The aim of this study was to develop a land-use regression model to predict nitrogen dioxide (NO2) concentrations and compare its performance with a model including emissions data. The association between each land-use variable and NO2 concentrations at 68 locations in Rome in 1995 and 1996 was assessed by univariate linear regression and a multiple linear regression model that was constructed based on the importance of each variable. ⋯ A multiple regression model including these variables resulted in an R2 of 0.686. The best-fitting model adding an emission term of benzene resulted in an R2 of 0.690, but was not significantly different from the model without emissions (P=0.147). In conclusion, these results suggest that a land-use regression model explains the traffic-related air pollution levels with reasonable accuracy and that emissions data do not significantly improve the model.
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J Expo Sci Environ Epidemiol · Jan 2008
A new approach for combining information available from multiple particulate air pollution monitors.
In time-series studies on the effect of particulate matter (PM) air pollution on an adverse health outcome, PM time-series data are often available from multiple monitoring stations. Published studies have combined the data from the multiple monitors using a simple or trimmed average. We investigate an alternative method of combining the data available from multiple PM-monitoring sites. ⋯ The new model is illustrated by applying it to actual data from Cook County, IL, USA and through a simulation study. Using the new model, for the Cook County data, it was found that two of the six monitors provided essentially as much information about the effect of PM on mortality as all six monitors combined. The simulation study suggests that the weights assigned to each monitor by the new model are appropriate, that is, that the model assigns the largest weight to the monitor most highly correlated with the underlying PM time series used to generate mortality.