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Archives of Environmental and Occupational Health 02/2013; · 0.85 Impact Factor
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ABSTRACT: Allergens and other pollutants in house dust are collected using a variety of dust samplers that are assumed to operate similarly. This factorial design study compared sampler performance under controlled environmental conditions. House dust with known particle sizes (212-90, 90-45, and <45 μm) and allergen concentrations were sampled from new carpet squares with varying denier, pile height and pile densities. Dust mass and allergen recovery for total dust mites (Der p 1 and Der f 1), cat (Fel d 1) and cockroach allergen (Bla g 1) were assessed using the Eureka Mighty Mite (EURK), the High Volume Small Surface Sampler (HVS), or the American Industrial Hygiene Association (AIHA) method. Allergen concentrations were quantified using enzyme-linked immunosorbent assays, and dust mass results were corrected for carpet fiber shedding. Samplers were compared by exploring mass collection efficiency (CE=fiber corrected dust mass/applied dust mass) and concentration ratio (CR=allergen concentration in collected sample/allergen concentration in test dust). Test dust allergen concentrations varied by particle size fraction due to varying laboratory performance over time. The EURK and HVS samplers had CEs of 41-63% in the small and medium particle size fractions, and collected less than 20% of the available dust from the large size fraction. The AIHA CE ranged from 10% to 17% in the medium and small particle size fractions, but collected little dust in the largest particle size fraction. The AIHA and HVS samplers were more likely to acquire more representative and less variable allergen CRs compared with the EURK method. Health studies that use allergen concentration as an exposure metric need to consider the implications of sampler performance when interpreting links to health outcomes and development of health-based standards for allergens in house dust.Journal of Exposure Science and Environmental Epidemiology advance online publication, 2 January 2013; doi:10.1038/jes.2012.112.
Journal of Exposure Science and Environmental Epidemiology 01/2013; · 2.93 Impact Factor
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ABSTRACT: The article focuses on issues relating to occupational exposures of researchers and lab workers, and exposures of bystanders such as health care workers and family members during HSR using nanomaterials. Such third-party exposures give rise to unique challenges relating to oversight as well as exposures to worker groups not previously studied. Given the current state of knowledge regarding health risks from such exposures, a more precautionary approach to oversight seems advisable.
The Journal of Law Medicine & Ethics 12/2012; 40(4):856-864. · 1.22 Impact Factor
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ABSTRACT: From 1974 through 2010, the Mine Safety and Health Administration (MSHA) collected nearly 147,000 respirable dust samples with a mass of at least 0.1 mg and a minimum of 1% quartz. These samples represent about 50% of all respirable dust compliance samples collected by MSHA. Analysis of these data shows that pockets of high concentrations and overexposure continue to exist. At underground mines, from 2005 to 2010, occupations with >20% of the samples exceeding the permissible exposure limit (PEL) and geometric mean quartz concentrations exceeding the ACGIH threshold limit value of 25 μg/m(3) included mucking, crusher operator, general laborer/utility, and front-end loader operator. During the same period, stone and rock saw operators and bagger and packers working at surface mines and mills also had >20% of the samples exceeding the PEL and geometric mean quartz concentrations >25 μg/m(3). Regardless of mine type or location, slow but steady improvement in exposure levels is seen in jobs involving crushing operations, which are widespread in the mining industry. Crusher operators are more likely to work in an enclosed area where it is easier to apply dust controls and air conditioning. A downward trend is also observed for vehicle equipment operators who drive load-haul-dumps, front-end loaders, trucks, and similar equipment. Crusher operators and vehicle equipment operators represent occupational categories that are widely sampled by MSHA inspectors. A small but statistically significant reduction in the overall mean respirable quartz dust and quartz concentrations from 1993 to 2010 was observed in most commodity groups. Variability from year to year and between commodities is high. Reduction in respirable quartz dust concentration does not necessarily correspond to a reduction in quartz concentration within the same commodity group. These trends are consistent with those reported in previous studies.
Journal of Occupational and Environmental Hygiene 12/2012; 9(12):720-32. · 1.19 Impact Factor
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ABSTRACT: Results are presented from a study that investigated the effect of data interpretation training on exposure judgment accuracy of industrial hygienists across several companies in different industry sectors. Participating companies provided monitoring information on specific exposure tasks. Forty-nine hygienists from six companies participated in the study, and 22 industrial tasks were evaluated. The number of monitoring data points for individual tasks varied between 5 and 24. After reviewing all available basic characterization information for the job, task, and chemical, hygienists were asked to provide their judgment on the probability of the 95th percentile of the underlying exposure distribution being located in one of four exposure categories relative to the occupational exposure limit as outlined in the AIHA exposure assessment strategy. Ninety-three qualitative judgments (i.e., without reviewing monitoring data) and 2142 quantitative judgments (i.e., those made after reviewing monitoring data) were obtained. Data interpretation training, with simple rules of thumb for estimating 95th percentiles, was provided to all hygienists. A data interpretation test was administered before and after training. All exposure task judgments were collected before and after training. Data interpretation test accuracy for the hygienists increased from 48% to 67% after training (p < 0.001) and a significant underestimation bias was removed. Hygienist quantitative task judgment accuracy improved from 46% to 69% (p < 0.001) post-training. Accuracy results showed good improvement in industrial hygienists' quantitative judgments as a result of training. Hence, the use of statistical tools is promoted to improve judgments based on monitoring data and provide feedback and calibration to improve qualitative judgments. It may be worthwhile to develop standard training programs to improve exposure judgments.
Journal of Occupational and Environmental Hygiene 04/2012; 9(4):242-56. · 1.19 Impact Factor
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ABSTRACT: The objective of this exposure assessment was to reconstruct cumulative historical exposures for workers who have been exposed to multiple chemicals and chemical groups to better understand a cluster of brain cancers within a research and development lab. Chemicals of interest, including acrylates, bis-chloromethyl ether (BCME), chloromethyl methyl ether (CMME), isothiazolones and nitrosoamines, were selected on the basis of the plausibility of penetrating the blood-brain barrier and the uniqueness of the chemical's biological activity. In a complicated exposure setting such as a chemical R&D facility, multiple exposure estimation methods were needed. First, similarly exposure groups (SEGs) were created for these materials based on department group, time period of the department's existence and function associated with job titles. A probabilistic framework for assessing exposures was developed using Bayesian analysis of historical monitoring data, mathematical exposure modeling and professional judgments of current and former industrial hygienists at the facility were used to reconstruct the exposure history for acrylates, BCME and CMME for each SEG over the time period of interest. Since sufficient measurement data for isothiazolones and nitrosoamines were not available, the exposure histories for each SEG for these chemicals were estimated. This was done using objective formaldehyde levels and subjective employee interviews. The interviews assessed workplace determinants of exposure as distinct surrogates for estimating inhalation and dermal exposures. The exposure assessments by these methods were compared against each other to estimate the potential for exposure misclassification. A job exposure matrix (JEM) was constructed that contained the exposures obtained from above multiple approaches for each of these chemical groups for each SEG for each year of interest. The combination of methods used in this work is a unique and potentially helpful framework that can be used in analogous workplace settings involving multiple exposures with incomplete objective measurement information.
Environment international 02/2012; 39(1):111-21. · 4.79 Impact Factor
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ABSTRACT: Community exposure to asbestos from contaminated vermiculite ore from Libby, Montana, occurred in many processing sites in the United States, including a densely populated urban residential neighborhood of Minneapolis, Minnesota.
We examined exposed community residents who never worked at the plant or never lived with a plant worker for radiographic evidence of lung changes consistent with asbestos exposure.
We obtained posteroanterior chest radiographs to identify the prevalence of pleural abnormalities consistent with pneumoconiosis, as determined by consensus of two National Institute for Occupational Safety and Health-certified B-reader radiologists. We estimated cumulative asbestos exposure (fibers per cubic centimeters × months) with air dispersion model data and activity-based modeled exposure estimates for vermiculite processing waste contact. We modeled associations between pleural abnormalities and asbestos exposure using multiple logistic regression to adjust for year of birth, sex, and potential occupational asbestos exposure.
Radiographs were obtained for 461 participants. The prevalence of pleural abnormalities by B-reader consensus was 10.8%. A history of direct contact with the waste and ever playing in the waste piles was associated with pleural abnormalities {odds ratio [OR] 2.78 [95% confidence interval (CI): 1.26, 6.10] and 2.17 (95% CI: 0.99, 4.78), respectively, when adjusted for background exposure}. The regression coefficients for log-transformed measures (fibers per cubic centimeters × months) of background exposure and activity-based exposure were 0.322 (95% CI: 0.078, 0.567) and 0.063 (95% CI: -0.013, 0.139), respectively, when adjusted for each other, and 0.283 (95% CI: 0.104, 0.463) for cumulative exposure from all sources.
These results support the hypothesis that community exposure to asbestos-contaminated vermiculite originating from Libby, Montana, is associated with measurable effects based on radiographic evidence.
Environmental Health Perspectives 01/2012; 120(1):44-9. · 7.04 Impact Factor
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ABSTRACT: Results are presented from a study that investigated the effect of characteristics of occupational hygienists relating to educational and professional experience and task-specific experience on the accuracy of occupational exposure judgments. A total of 49 occupational hygienists from six companies participated in the study and 22 tasks were evaluated. Participating companies provided monitoring data on specific tasks. Information on nine educational and professional experience determinants (e.g. educational background, years of occupational hygiene and exposure assessment experience, professional certifications, statistical training and experience, and the 'need for cognition (NFC)', which is a measure of an individual's motivation for thinking) and four task-specific determinants was also collected from each occupational hygienist. Hygienists had a wide range of educational and professional backgrounds for tasks across a range of industries with different workplace and task characteristics. The American Industrial Hygiene Association exposure assessment strategy was used to make exposure judgments on the probability of the 95th percentile of the underlying exposure distribution being located in one of four exposure categories relative to the occupational exposure limit. After reviewing all available job/task/chemical information, hygienists were asked to provide their judgment in probabilistic terms. Both qualitative (judgments without monitoring data) and quantitative judgments (judgments with monitoring data) were recorded. Ninety-three qualitative judgments and 2142 quantitative judgments were obtained. Data interpretation training, with simple rules of thumb for estimating the 95th percentiles of lognormal distributions, was provided to all hygienists. A data interpretation test (DIT) was also administered and judgments were elicited before and after training. General linear models and cumulative logit models were used to analyze the relationship between accuracy of judgments and the various characteristics describing the participants. Data interpretation training (P < 0.0001), the company that the hygienist worked for (P < 0.0001), the total number of years hygienists had experience doing exposure assessments (P < 0.0001), and professional certifications (P < 0.0001) held by hygienists were found to be significant determinants of accurately predicting the correct exposure category for DITs as well as for task-specific judgment accuracy. Years of experience with a particular task (P < 0.0001), task evaluated, and the number of datapoints used for making judgments were found to be significant predictors of task-specific judgment accuracy. The NFC score was a predictor of the improvement in task judgment accuracy after training. The NFC score was itself predicted by determinants, such as company, years on current job, years of exposure assessment experience, and professional certifications. The results of this study are relevant not only for the case of industrial hygienists making exposure judgments prospectively but also possibly for those hygienists engaged in retrospective exposure assessments for epidemiological studies.
Annals of Occupational Hygiene 12/2011; 56(3):292-304. · 1.95 Impact Factor
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ABSTRACT: This study examines the impact of several experience and education determinants on exposure judgment accuracy. The study used desktop assessments performed on several different tasks with different exposure profiles to identify correlations between determinants and judgment accuracy using logistic regression models. The exposure judgments were elicited from industrial hygienists with varying levels of experience, education, and training. Videos and written and oral information about the exposure tasks were presented to all participants as they documented a series of qualitative and quantitative exposure judgment probabilities in four exposure categories. Participants (n = 77) first documented their qualitative and then their quantitative exposure assessments after receiving the series of sampling data points. Data interpretation tests and training in simple rules-of-thumb for data interpretation were also given to each participant to investigate the impact of data interpretation skills on exposure judgment accuracy. Logistic regression analysis indicated "years of exposure assessment experience" (p < 0.05), "highest EHS degree" (p < 0.05), and a participant's "data interpretation test score" (p < 0.05) directly impacted qualitative exposure judgment accuracy. Logistic regression models of quantitative judgment accuracy showed positive correlation with "greater than 10 years of exposure assessment experience" (p < 0.05), "highest EHS degree" (p < 0.05), a participant's "data interpretation test score" (p < 0.001), rules-of-thumb data interpretation training (p < 0.001), and the number of sample data points available for a judgment (p < 0.005). Analyzing judgments in subsets for participants with less or more than 10 years' experience indicated additional correlations with Certified Industrial Hygienist and Certified Safety Professional certifications, total number of task exposure assessments, and career number of air surveys. The correlation of qualitative and quantitative exposure judgment accuracy with "greater than 10 years experience" supports similar research findings from other fields. The results of this study indicate that several determinants of experience, education, and training, in addition to the availability of sampling data, significantly impact the accuracy of exposure assessments. The findings also suggest methods for enhancing exposure judgment accuracy through statistical tools, mathematical exposure modeling, and specific training.
Journal of Occupational and Environmental Hygiene 12/2011; 8(12):746-58. · 1.19 Impact Factor
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ABSTRACT: This article describes a highly tailorable exposure assessment strategy for nanomaterials that enables effective and efficient exposure management (i.e., a strategy that can identify jobs or tasks that have clearly unacceptable exposures), while simultaneously requiring only a modest level of resources to conduct. The strategy is based on strategy general framework from AIHA® that is adapted for nanomaterials and seeks to ensure that the risks to workers handling nanomaterials are being managed properly. The strategy relies on a general framework as the basic foundation while building and elaborating on elements essential to an effective and efficient strategy to arrive at decisions based on collecting and interpreting available information. This article provides useful guidance on conducting workplace characterization; understanding exposure potential to nanomaterials; accounting methods for background aerosols; constructing SEGs; and selecting appropriate instrumentation for monitoring, providing appropriate choice of exposure limits, and describing criteria by which exposure management decisions should be made. The article is intended to be a practical guide for industrial hygienists for managing engineered nanomaterial risks in their workplaces.
Journal of Occupational and Environmental Hygiene 11/2011; 8(11):673-85. · 1.19 Impact Factor
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ABSTRACT: Recently, the appropriateness of using the 'mass concentration' metric for ultrafine particles has been questioned and surface area (SA) or number concentration metrics has been proposed as alternatives. To assess the abilities of various exposure metrics to distinguish between different exposure zones in workplaces with nanoparticle aerosols, exposure concentrations were measured in preassigned 'high-' and 'low-'exposure zones in a restaurant, an aluminum die-casting factory, and a diesel engine laboratory using SA, number, and mass concentration metrics. Predetermined exposure classifications were compared by each metric using statistical parameters and concentration ratios that were calculated from the different exposure concentrations. In the restaurant, SA and fine particle number concentrations showed significant differences between the high- and low-exposure zones and they had higher contrast (the ratio of between-zone variance to the sum of the between-zone and within-zone variances) than mass concentrations. Mass concentrations did not show significant differences. In the die cast facility, concentrations of all metrics were significantly greater in the high zone than in the low zone. SA and fine particle number concentrations showed larger concentration ratios between the high and low zones and higher contrast than mass concentrations. None of the metrics were significantly different between the high- and low-exposure zones in the diesel engine laboratory. The SA and fine particle number concentrations appeared to be better at differentiating exposure zones and finding the particle generation sources in workplaces generating nanoparticles. Because the choice of an exposure metric has significant implications for epidemiologic studies and industrial hygiene practice, a multimetric sampling approach is recommended for nanoparticle exposure assessment.
Annals of Occupational Hygiene 10/2010; 54(7):799-812. · 1.95 Impact Factor
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ABSTRACT: Measurements using several exposure metrics were carried out in a restaurant and a die casting plant to compare the spatial distributions of particle surface area (SA), number, and mass concentrations and rank exposures in different areas by those metrics. The different exposure metrics for incidental nanoparticle and fine particle exposures were compared using the concentration rankings, statistical differences between areas, and concentration ratios between different areas. In the die casting plant, area concentration rankings and spatial distributions differed by the exposure metrics chosen. Surface area and fine particle number concentrations were greatest near incidental nanoparticle sources and were significantly different between three areas. However, mass and coarse particle number concentrations were similar throughout the facility, and rankings of the work areas based on these metrics were different from those of SA and fine number concentrations. In the restaurant, concentrations in the kitchen for all metrics except respirable mass concentration were significantly greater than in the serving area, although SA and fine particle number concentrations showed larger differences between the two areas than either the mass or coarse particle number concentrations. Thus, the choice of appropriate exposure metric has significant implications for exposure groupings in epidemiologic and occupational exposure studies.
Journal of Occupational and Environmental Hygiene 08/2010; 7(8):466-76. · 1.19 Impact Factor
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ABSTRACT: The primary objective was to develop a framework for using exposure models in conjunction with two-dimensional Monte Carlo methods for making exposure judgments in the context of Bayesian decision analysis. The AIHA exposure assessment strategy will be used for illustrative purposes, but the method has broader applications beyond these specific exposure assessment strategies. A two-dimensional Monte Carlo scheme by which the exposure model output can be represented in the form of a decision chart is presented. The chart shows the probabilities of the 95th percentile of the exposure distribution lying in one of the four exposure categories relative to the occupational exposure limit (OEL): (1) highly controlled (<10% of OEL), (2) well controlled (10-50% of OEL), (3) controlled (50-100% of OEL), and (4) poorly controlled (>100% of OEL). Such a decision chart can be used as a "prior" in the Bayesian statistical framework, which can be updated using monitoring data to arrive at a final decision chart. Hypothetical examples using commonly used exposure models are presented, along with a discussion of how this framework can be used given a hierarchy of exposure models.
Journal of Occupational and Environmental Hygiene 07/2009; 6(6):353-62. · 1.19 Impact Factor
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ABSTRACT: Mathematical modeling is being increasingly used as a means for assessing occupational exposures. However, predicting exposure in real settings is constrained by lack of quantitative knowledge of exposure determinants. Validation of models in occupational settings is, therefore, a challenge. Not only do the model parameters need to be known, the models also need to predict the output with some degree of accuracy. In this paper, a Bayesian statistical framework is used for estimating model parameters and exposure concentrations for a two-zone model. The model predicts concentrations in a zone near the source and far away from the source as functions of the toluene generation rate, air ventilation rate through the chamber, and the airflow between near and far fields. The framework combines prior or expert information on the physical model along with the observed data. The framework is applied to simulated data as well as data obtained from the experiments conducted in a chamber. Toluene vapors are generated from a source under different conditions of airflow direction, the presence of a mannequin, and simulated body heat of the mannequin. The Bayesian framework accounts for uncertainty in measurement as well as in the unknown rate of airflow between the near and far fields. The results show that estimates of the interzonal airflow are always close to the estimated equilibrium solutions, which implies that the method works efficiently. The predictions of near-field concentration for both the simulated and real data show nice concordance with the true values, indicating that the two-zone model assumptions agree with the reality to a large extent and the model is suitable for predicting the contaminant concentration. Comparison of the estimated model and its margin of error with the experimental data thus enables validation of the physical model assumptions. The approach illustrates how exposure models and information on model parameters together with the knowledge of uncertainty and variability in these quantities can be used to not only provide better estimates of model outputs but also model parameters.
Annals of Occupational Hygiene 05/2009; 53(4):409-24. · 1.95 Impact Factor
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ABSTRACT: Information about the toxicity of nanoparticles is important in determining how nanoparticles will be regulated. In the U.S., the burden of collecting this information and conducting risk assessment is placed on regulatory agencies without the budgetary means to carry out this mandate. In this paper, we analyze the impact of testing costs on society's ability to gather information about nanoparticle toxicity and whether such costs can reasonably be borne by an emerging industry. We show for the United States that costs for testing existing nanoparticles ranges from $249 million for optimistic assumptions about nanoparticle hazards (i.e., they are primarily safe and mainly require simpler screening assays) to $1.18 billion for a more comprehensive precautionary approach (i.e., all nanomaterials require long-term in vivo testing). At midlevel estimates of total corporate R&D spending, and assuming plausible levels of spending on hazard testing, the time taken to complete testing is likely to be very high (34-53 years) if all existing nanomaterials are to be thoroughly tested. These delays will only increase with time as new nanomaterials are introduced. The delays are considerably less if less-stringent yet risk-averse perspectives are used. Our results support a tiered risk-assessment strategy similar to the EU's REACH legislation for regulating toxic chemicals.
Environmental Science and Technology 05/2009; 43(9):3030-4. · 5.23 Impact Factor
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ABSTRACT: Accurate exposure assessments are critical for ensuring that potentially hazardous exposures are properly identified and controlled. The availability and accuracy of exposure assessments can determine whether resources are appropriately allocated to engineering and administrative controls, medical surveillance, personal protective equipment and other programs designed to protect workers. A desktop study was performed using videos, task information and sampling data to evaluate the accuracy and potential bias of participants' exposure judgments. Desktop exposure judgments were obtained from occupational hygienists for material handling jobs with small air sampling data sets (0-8 samples) and without the aid of computers. In addition, data interpretation tests (DITs) were administered to participants where they were asked to estimate the 95th percentile of an underlying log-normal exposure distribution from small data sets. Participants were presented with an exposure data interpretation or rule of thumb training which included a simple set of rules for estimating 95th percentiles for small data sets from a log-normal population. DIT was given to each participant before and after the rule of thumb training. Results of each DIT and qualitative and quantitative exposure judgments were compared with a reference judgment obtained through a Bayesian probabilistic analysis of the sampling data to investigate overall judgment accuracy and bias. There were a total of 4386 participant-task-chemical judgments for all data collections: 552 qualitative judgments made without sampling data and 3834 quantitative judgments with sampling data. The DITs and quantitative judgments were significantly better than random chance and much improved by the rule of thumb training. In addition, the rule of thumb training reduced the amount of bias in the DITs and quantitative judgments. The mean DIT % correct scores increased from 47 to 64% after the rule of thumb training (P < 0.001). The accuracy for quantitative desktop judgments increased from 43 to 63% correct after the rule of thumb training (P < 0.001). The rule of thumb training did not significantly impact accuracy for qualitative desktop judgments. The finding that even some simple statistical rules of thumb improve judgment accuracy significantly suggests that hygienists need to routinely use statistical tools while making exposure judgments using monitoring data.
Annals of Occupational Hygiene 04/2009; 53(4):311-24. · 1.95 Impact Factor
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ABSTRACT: The OSHA system for oversight of chemicals in the workplace was evaluated to derive lessons for oversight of nanotechnology. Criteria relating to the development, attributes, evolution, and outcomes of the system were used for evaluation that was based upon quantitative expert elicitation and historical literature analysis. The oversight system had inadequate resources in terms of finances, expertise, and personnel, and insufficient incentive for compliance. The system showed a lack of flexibility in novel situations. There were minimal requirements on companies for data on health and safety of their products. These factors have a strong influence on public confidence and health and safety. The oversight system also scored low on attributes such as public input, transparency, empirical basis, conflict of interest, and informed consent. The experts in our sample tend to believe that the current oversight system for chemicals in the workplace is neither adequate nor effective. It is very likely that the performance of the OSHA oversight system for nanomaterials will be equally inadequate.
The Journal of Law Medicine & Ethics 01/2009; 37(4):633-50. · 1.22 Impact Factor
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ABSTRACT: House dust samples were collected up to six times over a 1-year period to explore seasonal variability of individual fungal genera in inner-city households in Minneapolis, Minnesota. General linear mixed-effects models were used to explore the variability of 13 fungal genera (Cladosporium, yeasts, Aureobasidium, Alternaria, Penicillium, Epicoccum, Mucor, Rhodotorula, Aspergillus, sterile fungi, Phoma, Pithomyces, and Fusarium) found in more than 20% of total dust samples. The five most common fungi (% of samples detected) were Cladosporium (81%), yeasts (63%), Aureobasidium (57%), Alternaria (56%), and Penicillium (55%), with the remaining genera found in 20-50% of the samples. When expressed as frequency of occurrence (%), genus fraction of total fungal concentration (%), or concentration of individual genera (CFU/g), these five genera also varied substantially by season. In contrast, Aureobasidium, Fusarium, and Mucor levels remained relatively constant throughout the year. The observed concentrations of the five most common fungal genera were higher than levels associated with increased respiratory symptoms reported in previous studies. Our results indicate that seasonal variability in common fungal genera is large: within-home to between-home variance ratios of Penicillium (4.1), Alternaria (4.9), Cladosporium (7.1), and yeasts (20.3) were substantially larger than that observed for total fungi (2.5). These results suggest that future studies attempting to link individual fungal genera to health effects need to characterize and control for this seasonal variability.
Journal of Occupational and Environmental Hygiene 01/2009; 5(12):780-9. · 1.19 Impact Factor
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Gurumurthy Ramachandran
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ABSTRACT: NIOSH has embarked on a project to update its exposure sampling strategies manual. The current NIOSH strategy has a number of limitations. This is an opportunity to develop a robust and comprehensive exposure assessment strategy. Some of the key features of such a strategy are outlined. The importance of accurate professional judgment and exposure modeling is discussed. Bayesian statistics offers a rational approach to integrating sampling data, professional judgments, and the outputs of exposure models in a comprehensive framework.
Annals of Occupational Hygiene 08/2008; 52(5):297-301. · 1.95 Impact Factor
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ABSTRACT: Allergens in house dust are risk factors for asthma causation and exacerbation, and asthma interventions often focus on exposure reduction using methods that may not be sustainable over time in low-income communities. A randomized controlled trial with up to six home visits was used to evaluate the effectiveness of two interventions focused on reducing dust loading and allergen concentrations in 47 low-income inner-city households in Minneapolis, MN. The interventions, which included education and relatively inexpensive cleaning procedures, were developed using a community-based participatory consultation process with focus groups held in English, Somali, and Spanish to incorporate community feedback from participants into protocols and study design decisions. Change in levels of cat, cockroach, dust mite, and culturable fungi as well as overall dust loading were evaluated by measuring the difference in concentrations before and after the cleaning intervention, and mixed models were used to assess the effect of education and cleaning on baseline allergen levels during the final three home visits. The cleaning intervention significantly lowered dust loading in all households and culturable fungi levels in single family homes, reduced cat allergen concentrations in homes with cats, but had no significant effect on cockroach allergen levels. The cleaning intervention also modestly decreased the frequency of observed allergen concentrations above suggested health benchmarks for cat, cockroach, and fungi. The cleaning and education interventions had similar effects on baseline allergen levels measured during subsequent home visits; both interventions significantly reduced baseline levels of cat and fungal allergens observed in pre-cleaning samples, but had no significant effect on cockroach allergen levels. Overall, the cleaning intervention modestly reduced potential exposure to risk factors associated with asthma mortality and morbidity in a way that can be implemented by most homeowners or renters, independent of education, income, or the ability to speak English.
Journal of Exposure Science and Environmental Epidemiology 08/2008; 18(4):430-40. · 2.93 Impact Factor
