Biomedical subjects

Gurumurthy Ramachandran

Publications and source records attributed to Gurumurthy Ramachandran.

15 recordsLinked to original sources

PubMed2006

Asthma, atopy, and lung function among racially diverse, poor inner-urban Minneapolis schoolchildren.

As part of an assessment of schoolchildren's environmental exposures and health, a probability sample of 136 children from diverse racial/ethnic backgrounds was drawn from grades 2-5 of two inner-urban Minneapolis schools (Whittier, Lyndale). Questionnaires were administered to a parent/guardian; blood samples for IgE and lung function tests were obtained. Overall adjusted rates for lifetime asthma (15.4%; 95%CI 9.3-21.5%), asthma in the last 12 months (13.6%; 7.8-19.4%), and current asthma medication use (10.5%; 5.3-15.7%) were higher than reported US national rates. Adjusted rates for lifetime physician-diagnosed asthma differed significantly among racial/ethnic groups (P<0.01): African-Americans (25.9%), White/Others (25.8%), Hispanics (9.3%), Somalis (1.8%), Asians (0%). Corresponding rates for atopy (total IgE>100 IU/mL or an allergen-specific IgE>0.35 IU/mL) were: African-Americans (66.6%), White/Others (100%), Hispanics (77.2%), Somalis (78.1%), Asians (81.8%). Lung function (FEV1, FVC) was analyzed by linear regression using log-transformed data: significant race-specific differences in lung function were found relative to White/Others (P<0.001 for each racial/ethnic group): African-Americans (FEV1 -16.5%, FVC -16.9%), Somalis (-22.7%, -26.8%), Hispanics (-12.2%, -11.4%) and Asians (-11.1%, -12.4%). Females had significantly lower FEV1 (-8.8%) and FVC (-11.0%) than males. An unexplained, significant difference in children's lung function was found between the two schools. A history of physician-diagnosed asthma was not associated with decreased lung function. Factors other than poverty, inner-urban living, and IgE levels (atopy) need to be considered in the development of childhood asthma.

Asthma↗

PubMed2006

Rating exposure control using Bayesian decision analysis.

A model is presented for applying Bayesian statistical techniques to the problem of determining, from the usual limited number of exposure measurements, whether the exposure profile for a similar exposure group can be considered a Category 0, 1, 2, 3, or 4 exposure. The categories were adapted from the AIHA exposure category scheme and refer to (0) negligible or trivial exposure (i.e., the true X 0.95 < or =1%OEL), (1) highly controlled (i.e., X 0.95 < or =10%OEL), (2) well controlled (i.e., X 0.95 < or =50%OEL), (3) controlled (i.e., X 0.95 < or =100%OEL), or (4) poorly controlled (i.e., X0.95 > or =1%OEL) exposures. Unlike conventional statistical methods applied to exposure data, Bayesian statistical techniques can be adapted to explicitly take into account professional judgment or other sources of information. The analysis output consists of a distribution (i.e., set) of decision probabilities: e.g., 1%, 80%, 12%, 5%, and 2% probability that the exposure profile is a Category 0, 1, 2, 3, or 4 exposure. By inspection of these decision probabilities, rather than the often difficult to interpret point estimates (e.g., the sample 95th percentile exposure) and confidence intervals, a risk manager can be better positioned to arrive at an effective (i.e., correct) and efficient decision. Bayesian decision methods are based on the concepts of prior, likelihood, and posterior distributions of decision probabilities. The prior decision distribution represents what an industrial hygienist knows about this type of operation, using professional judgment; company, industry, or trade organization experience; historical or surrogate exposure data; or exposure modeling predictions. The likelihood decision distribution represents the decision probabilities based on an analysis of only the current data. The posterior decision distribution is derived by mathematically combining the functions underlying the prior and likelihood decision distributions, and represents the final decision probabilities. Advantages of Bayesian decision analysis include: (a) decision probabilities are easier to understand by risk managers and employees; (b) prior data, professional judgment, or modeling information can be objectively incorporated into the decision-making process; (c) decisions can be made with greater certainty; (d) the decision analysis can be constrained to a more realistic "parameter space" (i.e., the range of plausible values for the true geometric mean and geometric standard deviation); and (e) fewer measurements are necessary whenever the prior distribution is well defined and the process is fairly stable. Furthermore, Bayesian decision analysis provides an obvious feedback mechanism that can be used by an industrial hygienist to improve professional judgment. For example, if the likelihood decision distribution is inconsistent with the prior decision distribution then it is likely that either a significant process change has occurred or the industrial hygienist's initial judgment was incorrect. In either case, the industrial hygienist should readjust his judgment regarding this operation.

Bayes Theorem↗

PubMed2006

Generalized P-values and confidence intervals: a novel approach for analyzing lognormally distributed exposure data.

The problem of assessing occupational exposure using the mean of a lognormal distribution is addressed. The novel concepts of generalized p-values and generalized confidence intervals are applied for testing hypotheses and computing confidence intervals for a lognormal mean. The proposed methods perform well, they are applicable to small sample sizes, and they are easy to implement. Power studies and sample size calculation are also discussed. Computational details and a source for the computer program are given. The procedures are also extended to compare two lognormal means and to make inference about a lognormal variance. In fact, our approach based on generalized p-values and generalized confidence intervals is easily adapted to deal with any parametric function involving one or two lognormal distributions. Several examples involving industrial exposure data are used to illustrate the methods. An added advantage of the generalized variables approach is the ease of computation and implementation. In fact, the procedures can be easily coded in a programming language for implementation. Furthermore, extensive numerical computations by the authors show that the results based on the generalized p-value approach are essentially equivalent to those based on the Land's method. We want to draw the attention of the industrial hygiene community to this accurate and unified methodology to deal with any parameter associated with the lognormal distribution.

Air Pollutants, Occupational↗

PubMed2005

Mass, surface area and number metrics in diesel occupational exposure assessment.

While diesel aerosol exposure assessment has traditionally been based on the mass concentration metric, recent studies have suggested that particle number and surface area concentrations may be more health-relevant. In this study, we evaluated the exposures of three occupational groups-bus drivers, parking garage attendants, and bus mechanics-using the mass concentration of elemental carbon (EC) as well as surface area and number concentrations. These occupational groups are exposed to mixtures of diesel and gasoline exhaust on a regular basis in various ratios. The three groups had significantly different exposures to workshift TWA EC with the highest levels observed in the bus garage mechanics and the lowest levels in the parking ramp booth attendants. In terms of surface area, parking ramp attendants had significantly greater exposures than bus garage mechanics, who in turn had significantly greater exposures than bus drivers. In terms of number concentrations, the exposures of garage mechanics exceeded those of ramp booth attendants by a factor of 5-6. Depending on the exposure metric chosen, the three occupational groups had quite different exposure rankings. This illustrates the importance of the choice of exposure metric in epidemiological studies. If these three occupational groups were part of an epidemiological study, depending on the metric used, they may or may not be part of the same similarly exposed group (SEG). The exposure rankings (e.g., low, medium, or high) of the three groups also changes with the metric used. If the incorrect metric is used, significant misclassification errors may occur.

Aerosols↗

PubMed2005

A field comparison of volatile organic compound measurements using passive organic vapor monitors and stainless steel canisters.

Concurrent field measurements of 10 volatile organic compounds (VOCs) were made using passive diffusion-based organic vapor monitors (OVMs) and the U.S. Federal Reference Method, which comprises active monitoring with stainless steel canisters (CANs). Measurements were obtained throughout a range of weather conditions, repeatedly over the course of three seasons, and at three different locations in the Minneapolis/St. Paul metropolitan area. Ambient concentrations of most VOCs as measured by both methods were low compared to those of other large metropolitan areas. For some VOCs a considerable fraction of measurements was below the detection limit of one or both methods. The observed differences between the two methods were similar across measurement sites, seasons, and meteorological variables. A Bayesian analysis with uniform priors on the differences was applied, with accommodation of sometimes heavy censoring (nondetection) in either device. The resulting estimates of bias and standard deviation of the OVM relative to the CAN were computed by tertile of the canister-measured concentration. In general, OVM and CAN measurements were in the best agreement for benzene and other aromatic compounds with hydrocarbon additions (ethylbenzene, toluene, and xylenes). The two methods were not in such good agreement for styrene and halogenated compounds (carbon tetrachloride, p-dichlorobenzene, methylene chloride, and trichloroethylene). OVMs slightly overestimated benzene concentrations and carbon tetrachloride at low concentrations, but in all other cases where significant differences were found, OVMs underestimated relative to canisters. Our study indicates that the two methods are in agreement for some compounds, but not all. We provide data and interpretation on the relative performance of the two VOC measurement methods, which facilitates intercomparisons among studies.

Air Pollutants↗

PubMed2005

Indoor air quality in two urban elementary schools--measurements of airborne fungi, carpet allergens, CO2, temperature, and relative humidity.

This article presents measurements of biological contaminants in two elementary schools that serve inner city minority populations. One of the schools is an older building; the other is newer and was designed to minimize indoor air quality problems. Measurements were obtained for airborne fungi, carpet loadings of dust mite allergens, cockroach allergens, cat allergens, and carpet fungi. Carbon dioxide concentrations, temperature, and relative humidity were also measured. Each of these measurements was made in five classrooms in each school over three seasons--fall, winter, and spring. We compared the indoor environments at the two schools and examined the variability in measured parameters between and within schools and across seasons. A fixed-effects, nested analysis was performed to determine the effect of school, season, and room-within-school, as well as CO2, temperature and relative humidity. The levels of all measured parameters were comparable for the two schools. Carpet culturable fungal concentrations and cat allergen levels in the newer school started and remained higher than in the older school over the study period. Cockroach allergen levels in some areas were very high in the newer school and declined over the study period to levels lower than the older school. Dust mite allergen and culturable fungal concentrations in both schools were relatively low compared with benchmark values. The daily averages for temperature and relative humidity frequently did not meet ASHRAE guidelines in either school, which suggests that proper HVAC and general building operation and maintenance procedures are at least as important as proper design and construction for adequate indoor air quality. The results show that for fungi and cat allergens, the school environment can be an important exposure source for children.

Air Microbiology↗

PubMed2005

Children's exposure to volatile organic compounds as determined by longitudinal measurements in blood.

Blood concentrations of 11 volatile organic compounds (VOCs) were measured up to four times over 2 years in a probability sample of more than 150 children from two poor, minority neighborhoods in Minneapolis, Minnesota. Blood levels of benzene, carbon tetrachloride, trichloroethene, and m-/p-xylene were comparable with those measured in selected adults from the Third National Health and Nutrition Examination Survey (NHANES III), whereas concentrations of ethylbenzene, tetrachloroethylene, toluene, 1,1,1-trichloroethane, and o-xylene were two or more times lower in the children. Blood levels of styrene were more than twice as high, and for about 10% of the children 1,4-dichlorobenzene levels were greater than or equal to 10 times higher compared with NHANES III subjects. We observed strong statistical associations between numerous pairwise combinations of individual VOCs in blood (e.g., benzene and m-/p-xylene, m-/p-xylene and o-xylene, 1,1,1-trichloroethane and m-/p-xylene, and 1,1,1-trichloroethane and trichloroethene). Between-child variability was higher than within-child variability for 1,4-dichlorobenzene and tetrachloroethylene. Between- and within-child variability were approximately the same for ethylbenzene and 1,1,1-trichloroethane, and between-child was lower than within-child variability for the other seven compounds. Two-day, integrated personal air measurements explained almost 79% of the variance in blood levels for 1,4-dichlorobenzene and approximately 20% for tetrachloroethylene, toluene, m-/p-xylene, and o-xylene. Personal air measurements explained much less of the variance (between 0.5 and 8%) for trichloroethene, styrene, benzene, and ethylbenzene. We observed no significant statistical associations between total urinary cotinine (a biomarker for exposure to environmental tobacco smoke) and blood VOC concentrations. For siblings living in the same household, we found strong statistical associations between measured blood VOC concentrations.

Air Pollutants↗

PubMed2004

Evaluating differences between measured personal exposures to volatile organic compounds and concentrations in outdoor and indoor air.

Accurate estimation of human exposures to volatile organic compounds (VOCs) is a key element of strategies designed to protect public health from the adverse effects of hazardous air pollutants. The focus here is on examining the capability of three different exposure metrics (outdoor community concentrations, indoor residential concentrations, and a simple time-weighted model) to estimate observed personal exposures to 14 VOCs. The analysis is based on 2-day average concentrations of individual VOCs measured concurrently in outdoor (O) air in three urban neighborhoods, indoor (I) air in participant's residences, and personal (P) air near the breathing zone of 71 healthy, nonsmoking adults. A median of four matched P-I-O samples was collected for each study participant in Minneapolis/St. Paul over three seasons (spring, summer, and fall) in 1999 using charcoal-based passive air samplers (3M model 3500 organic vapor monitors). Results show a clear pattern for the 14 VOCs, with P > I > O concentrations. Intra-individual variability typically spanned at least an order of magnitude, and inter-individual variability spanned 2 or more orders of magnitude for each of the 14 VOCs. Although both O and I concentrations generally underestimated personal exposures, I concentrations provided a substantially better estimate of measured P concentrations. Mean squared error (MSE) as well as correlation measures were used to assess estimator performance at the subject-specific level, and hierarchical, mixed effects models were used to estimate the bias and variance components of MSE by tertile of personal exposure. Bias and variance both tended to increase in the upper third of the P exposure distribution for O versus P and I versus P. A simple time-weighted model incorporating measured concentrations in both outdoor community air and indoor residential air provided no improvement over I concentration alone for the estimation of P exposure.

Air Pollutants↗

PubMed2004

Comparing air dispersion model predictions with measured concentrations of VOCs in urban communities.

Air concentrations of nine volatile organic compounds were measured over 48-h periods at 23 locations in three communities in the Minneapolis-St. Paul metropolitan area. Concentrations at the same times and locations were modeled using a standard regulatory air dispersion model (ISCST3). The goal of the study was to evaluate model performance by comparing predictions with measurements using linear regression and estimates of bias. The modeling, done with mobile and area source emissions resolved to the census tract level and characterized as model area sources, represents an improvement over large-scale airtoxics modeling analyses done to date. Despite the resolved spatial scale, the model did not fully capture the spatial resolution in concentrations in an area with a sharp gradient in emissions. In a census tract with a major highway at one end of the tract (i.e., uneven distribution of emissions within the tract), model predictions atthe opposite end of the tract overestimated measured concentrations. This shortcoming was seen for pollutants emitted mainly by mobile sources (benzene, ethylbenzene, toluene, and xylenes). We suggest that major highways would be better characterized as line sources. The model also failed to fully capture the temporal variability in concentrations, which was expected since the emissions inventory comprised annual average values. Based on our evaluation metrics, model performance was best for pollutants emitted mainly from mobile sources and poorest for pollutants emitted mainlyfrom area sources. Important sources of error appeared to be the source characterization (especially location) and emissions quantification. We expect that enhancements in the emissions inventory would give the greatest improvement in results. As anticipated for a Gaussian plume model, performance was dramatically better when compared to measurements that were not matched in space or time. Despite the limitations of our analysis, we found thatthe regulatory air dispersion model was generally able to predict space and time matched 48-h average ambient concentrations of VOC species within a factor of 2 on average, results that meet regulatory model acceptance criteria.

Air Movements↗

PubMed2004

Comparison of personal, indoor, and outdoor exposures to hazardous air pollutants in three urban communities.

Two-day average concentrations of 15 individual volatile organic compounds (VOCs) were measured concurrently in (a) ambient air in three urban neighborhoods, (b) air inside residences of participants, and (c) personal air near the breathing zone of 71 healthy, nonsmoking adults. The outdoor (O), indoor (I), and personal (P) samples were collected in the Minneapolis/St. Paul metropolitan area over three seasons (spring, summer, and fall) in 1999 using charcoal-based passive air samplers (3M model 3500 organic vapor monitors). A hierarchical, mixed-effects statistical model was used to estimate the mutually adjusted effects of monitor location, community, and season while accounting for within-subject and within-time-index (monitoring period) correlation. Outdoor VOC concentrations were relatively low compared to many other urban areas, and only minor seasonal differences were observed. A consistent pattern of P > I > O was observed across both communities and seasons for 13 of 15 individual VOCs (exceptions were carbon tetrachloride and chloroform). Results indicate that ambient VOC measurements at central monitoring sites can seriously underestimate actual exposures for urban residents, even when the outdoor measurements are taken in their own neighborhoods.

Air Pollutants↗

PubMed2004

Children's exposure to environmental tobacco smoke: using diverse exposure metrics to document ethnic/racial differences.

Four metrics were used to assess exposure to environmental tobacco smoke (ETS) for a probability sample (n = 152) of elementary school-age children in two economically disadvantaged neighborhoods: a) caregiver responses to a baseline questionnaire (BQ) about smoking status and behavior; b) 48-hr time-activity (T-A) data on location and time spent by children in the presence of tobacco smoke; c) total urinary cotinine as a marker for nicotine uptake; and d) urinary NNAL [4-(methylnitrosamino)-1-(3-pyridyl)-1-butanol] + NNAL-Gluc [4-(methylnitrosamino)-1- (3-pyridyl)-1-(O-beta-D-glucopyranuronosyl)butane] as a marker for uptake of the tobacco-specific lung carcinogen 4-(methylnitrosamino)-1-(3-pyridyl)-1-butanone (NNK). Consistent differences in ETS exposure by ethnicity and race were observed. Although data were insufficient to determine differences for NNAL + NNAL-Gluc, BQ responses, T-A data, and cotinine levels all indicated that average ETS exposure was highest for African-American children, moderately high for those designated "other" (white, Southeast Asian, Native American), moderately low for Hispanic children, and lowest for Somali immigrant children. For example, in February 2000, mean cotinine levels were 14.1 ng/mL for African Americans, 12.2 ng/mL for other, 4.8 ng/mL for Hispanics, and 4.4 ng/mL for Somalis. The BQ and T-A data together were reasonably good predictors of total cotinine levels (adjusted r2 = 0.69), and based on limited data, measured total cotinine values were a relatively good predictor of NNAL + NNAL-Gluc (adjusted r2 = 0.73). The results suggest that when children are exposed to ETS primarily in their homes, questionnaires and T-A logs might be effective screening tools for identifying those likely to experience higher uptake of nicotine.

Biomarkers↗

PubMed2004

Outdoor, indoor, and personal exposure to VOCs in children.

We measured volatile organic compound (VOC) exposures in multiple locations for a diverse population of children who attended two inner-city schools in Minneapolis, Minnesota. Fifteen common VOCs were measured at four locations: outdoors (O), indoors at school (S), indoors at home (H), and in personal samples (P). Concentrations of most VOCs followed the general pattern O approximately equal to S < P less than or equal to H across the measured microenvironments. The S and O environments had the smallest and H the largest influence on personal exposure to most compounds. A time-weighted model of P exposure using all measured microenvironments and time-activity data provided little additional explanatory power beyond that provided by using the H measurement alone. Although H and P concentrations of most VOCs measured in this study were similar to or lower than levels measured in recent personal monitoring studies of adults and children in the United States, p-dichlorobenzene was the notable exception to this pattern, with upper-bound exposures more than 100 times greater than those found in other studies of children. Median and upper-bound H and P exposures were well above health benchmarks for several compounds, so outdoor measurements likely underestimate long-term health risks from children's exposure to these compounds.

Air Pollutants↗

PubMed2003

Expert judgment and occupational hygiene: application to aerosol speciation in the nickel primary production industry.

In many situations characterized by sparse data, occupational hygienists have used subjective judgments that are claimed to be derived from their experience and knowledge. While this practice is widespread, there has been no systematic study of 'expert judgment' or the 'art' of occupational hygiene. Indeed, there is a need to address the question of whether there is such a thing as 'expert opinion' in occupational hygiene that is broadly shared by practicing professionals. This research, employing 11 experts who estimate an exposure parameter (the percentages of four nickel species) in 12 workplaces in a nickel primary production industry, provides a large dataset from which useful inferences can be drawn about the quality of expert judgments and the variability among the experts. A well-designed questionnaire that provided succinct information about the processes and baseline data served to calibrate the experts. The Bayesian framework has been used in this work to develop posterior means and standard deviations of the percentages of the four nickel species in the 12 workplaces of interest in the company. These estimates of the nickel speciation are at least as precise as--and most of the time more precise than--those provided by the sparse measurement data. There was a very high degree of agreement among the experts. A majority of the experts agreed among themselves 92% of the time, while almost two-thirds agreed 73% of the time. This, coupled with the fact that the experts came from varied backgrounds, seems to suggest that there is indeed some broad body of specialized knowledge that the experts are drawing on to reach similar judgments. It also seems that one type of expert is not necessarily any better than any other kind, and expertise does not necessarily require intimate familiarity with the workplace. In this example, the expert judgment exercise has indeed enhanced the quality of our knowledge of the exposure 'fingerprints' for the nickel industry workplaces studied and the combination of expert judgment and sparse data is better than the sparse data alone. For occupational hygiene exposure assessment, our experience suggests that such expert judgment methods can provide a cost-effective means to improve and refine information about workplace hazards. However, more study is warranted for situations where the domain of the quantity of interest has a much wider range of values, e.g. actual exposure values.

Air Pollutants, Occupational↗

PubMed2003

Recruitment, retention, and compliance results from a probability study of children's environmental health in economically disadvantaged neighborhoods.

The School Health Initiative: Environment, Learning, and Disease (SHIELD) study used a probability sample of children (second through fifth grades) from two low-income and racially mixed neighborhoods of Minneapolis, Minnesota, to assess childhood environmental health. Children were eligible to participate in SHIELD regardless of whether they or their families spoke a foreign language, their household had a telephone, or they were enrolled in a special education program. The overall enrollment rate in year 1 was 57%, with a substantial disparity between children from English-speaking (42%) versus non-English-speaking (71%) families. At the end of year 1, 85% were retained in the study. A relatively high percentage of children provided the two requested blood (82%) and urine (86%) samples in year 1, and 90% provided a valid spirometry sample. Eighty-two percent provided both requested volatile organic chemical badge samples, and both time-activity logs were obtained from 66%. However, only 32% provided both peak flow measurements. All percentages increased for those participating in the second year of the study. Results indicate that a school-based research design makes it feasible and practical to conduct probability-based assessments of children's environmental health in economically disadvantaged and ethnically diverse neighborhoods. There is an ongoing need, however, to improve understanding of the cultural, economic, psychologic, and social determinants of study participation among this population.

Child↗

PubMedDate not supplied

Statistical comparison of diesel particulate matter measurement methods.

Four methods are used to quantify diesel particulate matter (DPM) in the mine environment: respirable combustible dust sampling (RCD), size selective sampling with gravimetric analysis (SSG), respirable dust sampling with elemental carbon (EC) analysis, and respirable dust sampling with total carbon (TC) analysis. The authors assembled data from three underground mine studies to statistically compare these methods. The sampling protocol used in each study was similar. For all the four methods, samples were collected in triplicate at three locations-upwind and downwind of the diesel scoop and on the scoop. The methods were compared with respect to their precision, selectivity, sensitivity, and LOD, as well as their limitations in measuring DPM concentrations. This constitutes a meta-analysis of the available data and provides information over a broader range of mining conditions and DPM concentrations than any of the individual studies. The weighing imprecision for the SSG method is almost twice that for the RCD technique. The imprecision of the EC and TC methods are a function of the mass loading, and EC has a lower imprecision than TC. The EC method was used as the reference "gold standard" against which the other methods were evaluated. The RCD, SSG, and TC methods exhibited substantial levels of interference, leading to much higher minimum concentrations that can be measured by these methods. Of the three, the SSG method has the highest level of interference, primarily from nondiesel material that is collected in the <0.8 microm size range.

Air Pollutants, Occupational↗