PREVALENCIA DE SINTOMATOLOGÍA MÚSCULO ESQUELÉTICAS DE CUELLO, HOMBRO Y ESPALDA LUMBAR EN LOS TRABAJADORES DE MINAS SUBTERRÁNEAS DE CARBÓN EN EL DEPARTAMENTO DE BOYACÁ, COLOMBIA, 2013

Introducción. Trabajo de investigación realizado dentro del proyecto “EVALUACIÓN DE LA EXPOSICIÓN A POLVO DE CARBÓN EN MINERÍA SUBTERRÁNEA EN TRES DEPARTAMENTOS DE COLOMBIA” liderado por el grupo Salud Ocupacional y del Ambiente, con la participación de la Universidad del Rosario, la Universidad de los Andes, el Ministerio de Trabajo, la Administradora de Riesgos Laborales Positiva. Inmerso en este proyecto se determinará en el departamento de Boyacá la prevalencia de sintomatología músculo esquelética Objetivo. Determinar la sintomatología músculo esquelética en cuello, hombros y espalda lumbar, en trabajadores de minas de carbón subterráneas del departamento de Boyacá, mediante la aplicación del Cuestionario Nórdico Estandarizado específico y su relación con variables sociodemográficas y ocupacionales. Metodología. Estudio de corte transversal que se realizó en una población de minería subterránea del departamento mediante la aplicación del Cuestionario Nórdico Estandarizado específico. Resultados. La sintomatología en cuello, hombros y espalda reportada fue de 44,1%, 37,1% y 68,2% respectivamente por los trabajadores. La antigüedad laboral en promedio fue de 17,06 (DS 7,93), la media de edad fue 40,46 (DS 11,12 años). De los 170 trabajadores encuestados el 74,7% (127) se desempeñan como picadores, seguidos por cocheros 10,6% (18), malacatero 5,3% (9), el restante se desempeña en otras labores de minería. Conclusiones. Este estudio encontró un alta prevalencia de sintomatología músculo esquelética en los trabajadores de minería de carbón subterránea, lo que sugiere la necesidad de generar estudios ergonómicos y estrategias de prevención para evitar un aumento en la cifras de enfermedades profesionales como desordenes músculo esqueléticos.

A model for radiofrequency electromagnetic field predictions at outdoor and indoor locations in the context of epidemiological research

We present a geospatial model to predict the radiofrequency electromagnetic field from fixed site transmitters for use in epidemiological exposure assessment. The proposed model extends an existing model toward the prediction of indoor exposure, that is, at the homes of potential study participants. The model is based on accurate operation parameters of all stationary transmitters of mobile communication base stations, and radio broadcast and television transmitters for an extended urban and suburban region in the Basel area (Switzerland). The model was evaluated by calculating Spearman rank correlations and weighted Cohen's kappa (kappa) statistics between the model predictions and measurements obtained at street level, in the homes of volunteers, and in front of the windows of these homes. The correlation coefficients of the numerical predictions with street level measurements were 0.64, with indoor measurements 0.66, and with window measurements 0.67. The kappa coefficients were 0.48 (95%-confidence interval: 0.35-0.61) for street level measurements, 0.44 (95%-CI: 0.32-0.57) for indoor measurements, and 0.53 (95%-CI: 0.42-0.65) for window measurements. Although the modeling of shielding effects by walls and roofs requires considerable simplifications of a complex environment, we found a comparable accuracy of the model for indoor and outdoor points.

The GABRIEL Advanced Surveys: study design, participation and evaluation of bias

Exposure to farming environments has been shown to protect substantially against asthma and atopic disease across Europe and in other parts of the world. The GABRIEL Advanced Surveys (GABRIELA) were conducted to determine factors in farming environments which are fundamental to protecting against asthma and atopic disease. The GABRIEL Advanced Surveys have a multi-phase stratified design. In a first-screening phase, a comprehensive population-based survey was conducted to assess the prevalence of exposure to farming environments and of asthma and atopic diseases (n = 103,219). The second phase was designed to ascertain detailed exposure to farming environments and to collect biomaterial and environmental samples in a stratified random sample of phase 1 participants (n = 15,255). A third phase was carried out in a further stratified sample only in Bavaria, southern Germany, aiming at in-depth respiratory disease and exposure assessment including extensive environmental sampling (n = 895). Participation rates in phase 1 were around 60% but only about half of the participating study population consented to further study modules in phase 2. We found that consenting behaviour was related to familial allergies, high parental education, wheeze, doctor diagnosed asthma and rhinoconjunctivitis, and to a lesser extent to exposure to farming environments. The association of exposure to farm environments with asthma or rhinoconjunctivitis was not biased by participation or consenting behaviour. The GABRIEL Advanced Surveys are one of the largest studies to shed light on the protective 'farm effect' on asthma and atopic disease. Bias with regard to the main study question was able to be ruled out by representativeness and high participation rates in phases 2 and 3. The GABRIEL Advanced Surveys have created extensive collections of questionnaire data, biomaterial and environmental samples promising new insights into this area of research.

Feasibility of future epidemiological studies on possible health effects of mobile phone base stations

The increasing deployment of mobile communication base stations led to an increasing demand for epidemiological studies on possible health effects of radio frequency emissions. The methodological challenges of such studies have been critically evaluated by a panel of scientists in the fields of radiofrequency engineering/dosimetry and epidemiology. Strengths and weaknesses of previous studies have been identified. Dosimetric concepts and crucial aspects in exposure assessment were evaluated in terms of epidemiological studies on different types of outcomes. We conclude that in principle base station epidemiological studies are feasible. However, the exposure contributions from all relevant radio frequency sources have to be taken into account. The applied exposure assessment method should be piloted and validated. Short to medium term effects on physiology or health related quality of life are best investigated by cohort studies. For long term effects, groups with a potential for high exposure need to first be identified; for immediate effect, human laboratory studies are the preferred approach.

Food-safety hazards in the pork chain in Nagaland, North East India: implications for human health.

Pork occupies an important place in the diet of the population of Nagaland, one of the North East Indian states. We carried out a pilot study along the pork meat production chain, from live animal to end consumer. The goal was to obtain information about the presence of selected food borne hazards in pork in order to assess the risk deriving from these hazards to the health of the local consumers and make recommendations for improving food safety. A secondary objective was to evaluate the utility of risk-based approaches to food safety in an informal food system. We investigated samples from pigs and pork sourced at slaughter in urban and rural environments, and at retail, to assess a selection of food-borne hazards. In addition, consumer exposure was characterized using information about hygiene and practices related to handling and preparing pork. A qualitative hazard characterization, exposure assessment and hazard characterization for three representative hazards or hazard proxies, namely Enterobacteriaceae, T. solium cysticercosis and antibiotic residues, is presented. Several important potential food-borne pathogens are reported for the first time including Listeria spp. and Brucella suis. This descriptive pilot study is the first risk-based assessment of food safety in Nagaland. We also characterise possible interventions to be addressed by policy makers, and supply data to inform future risk assessments.

Hazardous air pollutants and childhood lymphohematopoietic cancer in Southeast Texas, 1995--2004

Southeast Texas, including Houston, has a large presence of industrial facilities and has been documented to have poorer air quality and significantly higher cancer rates than the remainder of Texas. Given citizens’ concerns in this 4th largest city in the U.S., Mayor Bill White recently partnered with the UT School of Public Health to determine methods to evaluate the health risks of hazardous air pollutants (HAPs). Sexton et al. (2007) published a report that strongly encouraged analytic studies linking these pollutants with health outcomes. In response, we set out to complete the following aims: 1. determine the optimal exposure assessment strategy to assess the association between childhood cancer rates and increased ambient levels of benzene and 1,3-butadiene (in an ecologic setting) and 2. evaluate whether census tracts with the highest levels of benzene or 1,3-butadiene have higher incidence of childhood lymphohematopoietic cancer compared with census tracts with the lowest levels of benzene or 1,3-butadiene, using Poisson regression. The first aim was achieved by evaluating the usefulness of four data sources: geographic information systems (GIS) to identify proximity to point sources of industrial air pollution, industrial emission data from the U.S. EPA’s Toxic Release Inventory (TRI), routine monitoring data from the U.S. EPA Air Quality System (AQS) from 1999-2000 and modeled ambient air levels from the U.S. EPA’s 1999 National Air Toxic Assessment Project (NATA) ASPEN model. Further, once these four data sources were evaluated, we narrowed them down to two: the routine monitoring data from the AQS for the years 1998-2000 and the 1999 U.S. EPA NATA ASPEN modeled data. We applied kriging (spatial interpolation) methodology to the monitoring data and compared the kriged values to the ASPEN modeled data. Our results indicated poor agreement between the two methods. Relative to the U.S. EPA ASPEN modeled estimates, relying on kriging to classify census tracts into exposure groups would have caused a great deal of misclassification. To address the second aim, we additionally obtained childhood lymphohematopoietic cancer data for 1995-2004 from the Texas Cancer Registry. The U.S. EPA ASPEN modeled data were used to estimate ambient levels of benzene and 1,3-butadiene in separate Poisson regression analyses. All data were analyzed at the census tract level. We found that census tracts with the highest benzene levels had elevated rates of all leukemia (rate ratio (RR) = 1.37; 95% confidence interval (CI), 1.05-1.78). Among census tracts with the highest 1,3-butadiene levels, we observed RRs of 1.40 (95% CI, 1.07-1.81) for all leukemia. We detected no associations between benzene or 1,3-butadiene levels and childhood lymphoma incidence. This study is the first to examine this association in Harris and surrounding counties in Texas and is among the first to correlate monitored levels of HAPs with childhood lymphohematopoietic cancer incidence, evaluating several analytic methods in an effort to determine the most appropriate approach to test this association. Despite recognized weakness of ecologic analyses, our analysis suggests an association between childhood leukemia and hazardous air pollution.^

A cross-sectional study of human symptomatology and residential formaldehyde concentrations

The cross-sectional study was performed to quantify the prevalence of symtomatology in residents of mobile homes as a function of indoor formaldehyde concentration. Formaldehyde concentrations were monitored for a seven hour period with an automated wet-chemical colorimetric analyzer. The health status of family members was ascertained by administration of questionnaires and physical exams. This is the first investigation to perform clinical assessments on residents undergoing concurrent exposure assessment in the home.^ Only 22.8% of households eligible for participation chose to cooperate. Monitoring data and health evaluations were obtained from 155 households in four Texas counties. A total of 428 residents (86.1%) were available for examination during the sampling hours. The study population included 45 infants, 126 children, and 257 adults.^ Formaldehyde concentration was not found to be significantly associated with increased risks for symptoms and signs of ocular irritation, dermal anomalies, or malaise. Three associations were identified that warrant further investigation. The relative odds associated with a doubling of formaldehyde concentration was significantly associated with parenchymal rales in adults and children. However, risk was modified by log respirable suspended particulate concentrations. Due to the presence of modification by a continuous variable, prevalence odds ratios (POR) and 95% confidence intervals (95% CI) for these associations are presented in tables. A doubling of formaldehyde concentration was also associated with an increased risk of perceived tightness in the chest in adults. Prevalence odds ratios are presented in a table due to effect modification by the average number of hours spent indoors on weekdays. Furthermore, a doubling of formaldehyde concentration was associated with an increased risk of drowsiness in children (POR = 2.60; 95% CI 1.04-6.51) and adults (POR = 1.94; 95% CI 1.20-3.14). ^

Associations between ambient levels of combustion pollutants and small for gestational age infants in Texas

There is scant evidence regarding the associations between ambient levels of combustion pollutants and small for gestational age (SGA) infants. No studies of this type have been completed in the Southern United States. The main objective of the project presented was to determine associations between combustion pollutants and SGA infants in Texas using three different exposure assessments. ^ Birth certificate data that contained information on maternal and infant characteristics were obtained from the Texas Department of State Health Services (TX DSHS). Exposure assessment data for the three aims came from: (1) U.S. Environmental Protection Agency (EPA) National Air Toxics Assessment (NATA), (2) U.S. EPA Air Quality System (AQS), and (3) TX Department of Transportation (DOT), respectively. Multiple logistic regression models were used to determine the associations between combustion pollutants and SGA. ^ For the first study looked at annual estimates of four air toxics at the census tract level in the Greater Houston Area. After controlling for maternal race, maternal education, tobacco use, maternal age, number of prenatal visits, marital status, maternal weight gain, and median census tract income level, adjusted ORs and 95% confidence intervals (CI) for exposure to PAHs (per 10 ng/m3), naphthalene (per 10 ng/m3), benzene (per 1 µg/m3), and diesel engine emissions (per 10 µg/m3) were 1.01 (0.97–1.05), 1.00 (0.99–1.01), 1.01 (0.97–1.05), and 1.08 (0.95–1.23) respectively. For the second study looking at Hispanics in El Paso County, AORs and 95% confidence intervals (CI) for increases of 5 ng/m3 for the sum of carcinogenic PAHs (Σ c-PAHs), 1 ng/m3 of benzo[a]pyrene, and 100 ng/m3 in naphthalene during the third trimester of pregnancy were 1.02 (0.97–1.07), 1.03 (0.96–1.11), and 1.01 (0.97–1.06), respectively. For the third study using maternal proximity to major roadways as the exposure metric, there was a negative association with increasing distance from a maternal residence to the nearest major roadway (Odds Ratio (OR) = 0.96; 95% CI = 0.94–0.97) per 1000 m); however, once adjusted for covariates this effect was no longer significant (AOR = 0.98; 95% CI = 0.96–1.00). There was no association with distance weighted traffic density (DWTD). ^ This project is the first to look at SGA and combustion pollutants in the Southern United States with three different exposure metrics. Although there was no evidence of associations found between SGA and the air pollutants mentioned in these studies, the results contribute to the body of literature assessing maternal exposure to ambient air pollution and adverse birth outcomes. ^

Comparison of machine learning approaches and statistical methods for estimation of airborne chemical exposures

Accurate quantitative estimation of exposure using retrospective data has been one of the most challenging tasks in the exposure assessment field. To improve these estimates, some models have been developed using published exposure databases with their corresponding exposure determinants. These models are designed to be applied to reported exposure determinants obtained from study subjects or exposure levels assigned by an industrial hygienist, so quantitative exposure estimates can be obtained. ^ In an effort to improve the prediction accuracy and generalizability of these models, and taking into account that the limitations encountered in previous studies might be due to limitations in the applicability of traditional statistical methods and concepts, the use of computer science- derived data analysis methods, predominantly machine learning approaches, were proposed and explored in this study. ^ The goal of this study was to develop a set of models using decision trees/ensemble and neural networks methods to predict occupational outcomes based on literature-derived databases, and compare, using cross-validation and data splitting techniques, the resulting prediction capacity to that of traditional regression models. Two cases were addressed: the categorical case, where the exposure level was measured as an exposure rating following the American Industrial Hygiene Association guidelines and the continuous case, where the result of the exposure is expressed as a concentration value. Previously developed literature-based exposure databases for 1,1,1 trichloroethane, methylene dichloride and, trichloroethylene were used. ^ When compared to regression estimations, results showed better accuracy of decision trees/ensemble techniques for the categorical case while neural networks were better for estimation of continuous exposure values. Overrepresentation of classes and overfitting were the main causes for poor neural network performance and accuracy. Estimations based on literature-based databases using machine learning techniques might provide an advantage when they are applied to other methodologies that combine `expert inputs' with current exposure measurements, like the Bayesian Decision Analysis tool. The use of machine learning techniques to more accurately estimate exposures from literature-based exposure databases might represent the starting point for the independence from the expert judgment.^

Technical assistance document for sampling and analysis of toxic organic compounds in ambient air /

Mode of access: Internet.

Asbestos-containing materials in school buildings : bulk sample analysis quality assurance program : bulk sample rounds 16, 17 and 18 /

Mode of access: Internet.

The Across North America Tracer Experiment (ANATEX) model evaluation study /

Mode of access: Internet.

Studies to determine the absorption and excretion dynamics of lead /

Mode of access: Internet.

National performance audit program : acid rain audits - 1988 - /

Mode of access: Internet.

Challenges to environmental toxicology and epidemiology: where do we stand and which way do we go?

Modern toxicology investigates a wide array of both old and new health hazards. Priority setting is needed to select agents for research from the plethora of exposure circumstances. The changing societies and a growing fraction of the aged have to be taken into consideration. A precise exposure assessment is of importance for risk estimation and regulation. Toxicology contributes to the exploration of pathomechanisms to specify the exposure metrics for risk estimation. Combined effects of co-existing agents are not yet sufficiently understood. Animal experiments allow a separate administration of agents which can not be disentangled by epidemiological means, but their value is limited for low exposure levels in many of today's settings. As an experimental science, toxicology has to keep pace with the rapidly growing knowledge about the language of the genome and the changing paradigms in cancer development. During the pioneer era of assembling a working draft of the human genome, toxicogenomics has been developed. Gene and pathway complexity have to be considered when investigating gene-environment interactions. For a best conduct of studies, modem toxicology needs a close liaison with many other disciplines like epidemiology and bioinformatics. (C) 2004 Elsevier Ireland Ltd. All rights reserved.