Occupational Musculoskeletal Disorders in Europe: Impact, Risk factors and Preventive Regulations

The aim of this article is to characterize musculoskeletal disorders (MSDs) in EU working population according to available Eurostat data, to identify relevant risk factors and to refer existing legislation and standards to prevent MSDs. The following questions will be answered: How often do MSDs occur in EU? What are the risk factors? Do legislation and standards exist to prevent these disorders?

Fungal burden in waste industry: an occupational risk to be solved

High loads of fungi have been reported in different types of waste management plants. This study intends to assess fungal contamination in one waste-sorting plant before and after cleaning procedures in order to analyze their effectiveness. Air samples of 50 L were collected through an impaction method, while surface samples, taken at the same time, were collected by the swabbing method and subject to further macro- and microscopic observations. In addition, we collected air samples of 250 L using the impinger Coriolis μ air sampler (Bertin Technologies) at 300 L/min airflow rate in order to perform real-time quantitative PCR (qPCR) amplification of genes from specific fungal species, namely Aspergillus fumigatus and Aspergillus flavus complexes, as well as Stachybotrys chartarum species. Fungal quantification in the air ranged from 180 to 5,280 CFU m−3 before cleaning and from 220 to 2,460 CFU m−3 after cleaning procedures. Surfaces presented results that ranged from 29 × 104 to 109 × 104 CFU m−2 before cleaning and from 11 × 104 to 89 × 104 CFU m−2 after cleaning. Statistically significant differences regarding fungal load were not detected between before and after cleaning procedures. Toxigenic strains from A. flavus complex and S. chartarum were not detected by qPCR. Conversely, the A. fumigatus species was successfully detected by qPCR and interestingly it was amplified in two samples where no detection by conventional methods was observed. Overall, these results reveal the inefficacy of the cleaning procedures and that it is important to determine fungal burden in order to carry out risk assessment.

Occupational co-exposure to several mycotoxins in the waste management setting

Contrary to fungi, exposure to mycotoxins is not usually identified as a risk factor present in occupational settings. This is probably due to the inexistence of limits regarding concentration of airborne mycotoxins, and also due to the fact that these compounds are rarely monitored in occupational environments. Despite the optimal conditions for fungal growth and, consequently, for mycotoxins production in all the waste management chain, only a few articles were dedicated to study occupational exposure to mycotoxins in this occupational setting. Aim of study: A study was developed in Portugal aiming to assess occupational co-exposure to mycotoxins in the waste management setting.

Occupational exposure to aflatoxin B1 and ochratoxin A: co-exposure in swine production

The most common scenario in occupational settings is the co-exposure to several risk factors. This aspect has to be considered in the risk assessment process because can alter the toxicity and the health effects when dealing with a co-exposure to two or more chemical agents. A study was developed aiming to elucidate if there is occupational co-exposure to aflatoxin B1 (AFB1) and ochratoxin (OTA) in Portuguese swine production. To assess occupational exposure to both mycotoxins, a biomarker of internal dose was used. The same blood samples from workers of seven swine farms and controls were consider to measure AFB1 and OTA. Twenty one workers (75%) showed detectable levels of AFB1 with values ranging from <1 ng/ml to 8.94 ng/ml and with significantly higher concentration when compared with controls. In the case of OTA, there wasn't found a statistical difference between workers and controls and the values for workers group ranged from 0.34 ng/ml to 3.12 ng/ml and 1.76 ng/ml to 3.42 ng/ml for control group. The results suggest that occupational exposure to AFB1 occurs. However, in the case of OTA results, seems that food consumption plays an important role in both groups exposure. The results claim attention for the possible implications on health of this co-exposure.

Occupational exposure to aflatoxin B1: new (old) occupational risk!

Contrary to fungi, exposure to mycotoxins is not usually identified as a risk factor present in occupational settings. This is probably due to the inexistence of limits regarding concentration of airborne mycotoxins, and also due to the fact that these compounds are rarely monitored in occupational environments. Aflatoxin B1 (AFB1) is the most prevalent aflatoxin and is associated with carcinogenicity, teratogenicity, genotoxicity and immunotoxicity but only a few studies examined exposure in occupational settings. Workers can be exposed to high airborne levels during certain operations in specific occupational settings. Aim of study: The study aimed to assess exposure to AFB1 in three settings: poultry, swine production and waste management.

Automatic learning for the classification of chemical reactions and in statistical thermodynamics

This Thesis describes the application of automatic learning methods for a) the classification of organic and metabolic reactions, and b) the mapping of Potential Energy Surfaces(PES). The classification of reactions was approached with two distinct methodologies: a representation of chemical reactions based on NMR data, and a representation of chemical reactions from the reaction equation based on the physico-chemical and topological features of chemical bonds. NMR-based classification of photochemical and enzymatic reactions. Photochemical and metabolic reactions were classified by Kohonen Self-Organizing Maps (Kohonen SOMs) and Random Forests (RFs) taking as input the difference between the 1H NMR spectra of the products and the reactants. The development of such a representation can be applied in automatic analysis of changes in the 1H NMR spectrum of a mixture and their interpretation in terms of the chemical reactions taking place. Examples of possible applications are the monitoring of reaction processes, evaluation of the stability of chemicals, or even the interpretation of metabonomic data. A Kohonen SOM trained with a data set of metabolic reactions catalysed by transferases was able to correctly classify 75% of an independent test set in terms of the EC number subclass. Random Forests improved the correct predictions to 79%. With photochemical reactions classified into 7 groups, an independent test set was classified with 86-93% accuracy. The data set of photochemical reactions was also used to simulate mixtures with two reactions occurring simultaneously. Kohonen SOMs and Feed-Forward Neural Networks (FFNNs) were trained to classify the reactions occurring in a mixture based on the 1H NMR spectra of the products and reactants. Kohonen SOMs allowed the correct assignment of 53-63% of the mixtures (in a test set). Counter-Propagation Neural Networks (CPNNs) gave origin to similar results. The use of supervised learning techniques allowed an improvement in the results. They were improved to 77% of correct assignments when an ensemble of ten FFNNs were used and to 80% when Random Forests were used. This study was performed with NMR data simulated from the molecular structure by the SPINUS program. In the design of one test set, simulated data was combined with experimental data. The results support the proposal of linking databases of chemical reactions to experimental or simulated NMR data for automatic classification of reactions and mixtures of reactions. Genome-scale classification of enzymatic reactions from their reaction equation. The MOLMAP descriptor relies on a Kohonen SOM that defines types of bonds on the basis of their physico-chemical and topological properties. The MOLMAP descriptor of a molecule represents the types of bonds available in that molecule. The MOLMAP descriptor of a reaction is defined as the difference between the MOLMAPs of the products and the reactants, and numerically encodes the pattern of bonds that are broken, changed, and made during a chemical reaction. The automatic perception of chemical similarities between metabolic reactions is required for a variety of applications ranging from the computer validation of classification systems, genome-scale reconstruction (or comparison) of metabolic pathways, to the classification of enzymatic mechanisms. Catalytic functions of proteins are generally described by the EC numbers that are simultaneously employed as identifiers of reactions, enzymes, and enzyme genes, thus linking metabolic and genomic information. Different methods should be available to automatically compare metabolic reactions and for the automatic assignment of EC numbers to reactions still not officially classified. In this study, the genome-scale data set of enzymatic reactions available in the KEGG database was encoded by the MOLMAP descriptors, and was submitted to Kohonen SOMs to compare the resulting map with the official EC number classification, to explore the possibility of predicting EC numbers from the reaction equation, and to assess the internal consistency of the EC classification at the class level. A general agreement with the EC classification was observed, i.e. a relationship between the similarity of MOLMAPs and the similarity of EC numbers. At the same time, MOLMAPs were able to discriminate between EC sub-subclasses. EC numbers could be assigned at the class, subclass, and sub-subclass levels with accuracies up to 92%, 80%, and 70% for independent test sets. The correspondence between chemical similarity of metabolic reactions and their MOLMAP descriptors was applied to the identification of a number of reactions mapped into the same neuron but belonging to different EC classes, which demonstrated the ability of the MOLMAP/SOM approach to verify the internal consistency of classifications in databases of metabolic reactions. RFs were also used to assign the four levels of the EC hierarchy from the reaction equation. EC numbers were correctly assigned in 95%, 90%, 85% and 86% of the cases (for independent test sets) at the class, subclass, sub-subclass and full EC number level,respectively. Experiments for the classification of reactions from the main reactants and products were performed with RFs - EC numbers were assigned at the class, subclass and sub-subclass level with accuracies of 78%, 74% and 63%, respectively. In the course of the experiments with metabolic reactions we suggested that the MOLMAP / SOM concept could be extended to the representation of other levels of metabolic information such as metabolic pathways. Following the MOLMAP idea, the pattern of neurons activated by the reactions of a metabolic pathway is a representation of the reactions involved in that pathway - a descriptor of the metabolic pathway. This reasoning enabled the comparison of different pathways, the automatic classification of pathways, and a classification of organisms based on their biochemical machinery. The three levels of classification (from bonds to metabolic pathways) allowed to map and perceive chemical similarities between metabolic pathways even for pathways of different types of metabolism and pathways that do not share similarities in terms of EC numbers. Mapping of PES by neural networks (NNs). In a first series of experiments, ensembles of Feed-Forward NNs (EnsFFNNs) and Associative Neural Networks (ASNNs) were trained to reproduce PES represented by the Lennard-Jones (LJ) analytical potential function. The accuracy of the method was assessed by comparing the results of molecular dynamics simulations (thermal, structural, and dynamic properties) obtained from the NNs-PES and from the LJ function. The results indicated that for LJ-type potentials, NNs can be trained to generate accurate PES to be used in molecular simulations. EnsFFNNs and ASNNs gave better results than single FFNNs. A remarkable ability of the NNs models to interpolate between distant curves and accurately reproduce potentials to be used in molecular simulations is shown. The purpose of the first study was to systematically analyse the accuracy of different NNs. Our main motivation, however, is reflected in the next study: the mapping of multidimensional PES by NNs to simulate, by Molecular Dynamics or Monte Carlo, the adsorption and self-assembly of solvated organic molecules on noble-metal electrodes. Indeed, for such complex and heterogeneous systems the development of suitable analytical functions that fit quantum mechanical interaction energies is a non-trivial or even impossible task. The data consisted of energy values, from Density Functional Theory (DFT) calculations, at different distances, for several molecular orientations and three electrode adsorption sites. The results indicate that NNs require a data set large enough to cover well the diversity of possible interaction sites, distances, and orientations. NNs trained with such data sets can perform equally well or even better than analytical functions. Therefore, they can be used in molecular simulations, particularly for the ethanol/Au (111) interface which is the case studied in the present Thesis. Once properly trained, the networks are able to produce, as output, any required number of energy points for accurate interpolations.

Task-based occupational exposure assessment and particle number concentration: two important data resources to perform risk assessment for occupational exposure to particles

Environment monitoring has an important role in occupational exposure assessment. However, due to several factors is done with insufficient frequency and normally don´t give the necessary information to choose the most adequate safety measures to avoid or control exposure. Identifying all the tasks developed in each workplace and conducting a task-based exposure assessment help to refine the exposure characterization and reduce assessment errors. A task-based assessment can provide also a better evaluation of exposure variability, instead of assessing personal exposures using continuous 8-hour time weighted average measurements. Health effects related with exposure to particles have mainly been investigated with mass-measuring instruments or gravimetric analysis. However, more recently, there are some studies that support that size distribution and particle number concentration may have advantages over particle mass concentration for assessing the health effects of airborne particles. Several exposure assessments were performed in different occupational settings (bakery, grill house, cork industry and horse stable) and were applied these two resources: task-based exposure assessment and particle number concentration by size. The results showed interesting results: task-based approach applied permitted to identify the tasks with higher exposure to the smaller particles (0.3 μm) in the different occupational settings. The data obtained allow more concrete and effective risk assessment and the identification of priorities for safety investments.

Environmental mycology in public health: fungi and mycotoxins risk assessment and management

Fungi are essential to the survival of our global ecology, but they might pose a significant threat to the health of occupants when they grow in our buildings. The exposure to fungi in homes is a significant risk factor for a number of respiratory symptoms. Well-known illnesses caused by fungi include allergy and hypersensitivity pneumonitis. Environmental monitoring for fungi and their disease agents are important aspects of exposure assessment, but few guidelines exist for interpreting their health impacts. This book answers the questions: How does one detect and measure the presence of indoor fungi? What is an acceptable level of indoor fungi? How do we relate this information to human health problems?

HIV risk practices by female sex workers according to workplace

OBJECTIVE To investigate differences in HIV infection- related risk practices by Female Sex Workers according to workplace and the effects of homophily on estimating HIV prevalence. METHODS Data from 2,523 women, recruited using Respondent-Driven Sampling, were used for the study carried out in 10 Brazilian cities in 2008-2009. The study included female sex workers aged 18 and over. The questionnaire was completed by the subjects and included questions on characteristics of professional activity, sexual practices, use of drugs, HIV testing, and access to health services. HIV quick tests were conducted. The participants were classified in two groups according to place of work: on the street or indoor venues, like nightclubs and saunas. To compare variable distributions by place of work, we used Chi-square homogeneity tests, taking into consideration unequal selection probabilities as well as the structure of dependence between observations. We tested the effect of homophily by workplace on estimated HIV prevalence. RESULTS The highest HIV risk practices were associated with: working on the streets, lower socioeconomic status, low regular smear test coverage, higher levels of crack use and higher levels of syphilis serological scars as well as higher prevalence of HIV infection. The effect of homophily was higher among sex workers in indoor venues. However, it did not affect the estimated prevalence of HIV, even after using a post-stratification by workplace procedure. CONCLUSIONS The findings suggest that strategies should focus on extending access to, and utilization of, health services. Prevention policies should be specifically aimed at street workers. Regarding the application of Respondent-Driven Sampling, the sample should be sufficient to estimate transition probabilities, as the network develops more quickly among sex workers in indoor venues.

Synopsis of global scenario and forecasting surveys scenarios in risk habitat megacity (RHM)

The main objective of the paper is to provide a synopsis of global scenario and forecasting surveys. First, the paper will give an overview on existing global scenario and forecasting surveys and their specific scenario philosophies and storylines. Second, the major driving forces that shape and characterise the different scenarios will be identified. The scenario analysis has been provided for the research project Risk Habitat Megacity (HRM) that aims at developing strategies for sustainable development in megacities and urban agglomerations. The analysis of international scenario surveys is an essential component within RHM. The scenario analysis will be the basis and source for the development of own RHM-framework scenarios and for defining specific driving forces of change.

Microstructure, mechanical properties and chemical degradation of brazed AISI 316 stainless steel/alumina systems

The main aims of the present study are simultaneously to relate the brazing parameters with: (i) the correspondent interfacial microstructure, (ii) the resultant mechanical properties and (iii) the electrochemical degradation behaviour of AISI 316 stainless steel/alumina brazed joints. Filler metals on such as Ag–26.5Cu–3Ti and Ag–34.5Cu–1.5Ti were used to produce the joints. Three different brazing temperatures (850, 900 and 950 °C), keeping a constant holding time of 20 min, were tested. The objective was to understand the influence of the brazing temperature on the final microstructure and properties of the joints. The mechanical properties of the metal/ceramic (M/C) joints were assessed from bond strength tests carried out using a shear solicitation loading scheme. The fracture surfaces were studied both morphologically and structurally using scanning electron microscopy (SEM), energy dispersive spectroscopy (EDS) and X-ray diffraction analysis (XRD). The degradation behaviour of the M/C joints was assessed by means of electrochemical techniques. It was found that using a Ag–26.5Cu–3Ti brazing alloy and a brazing temperature of 850 °C, produces the best results in terms of bond strength, 234 ± 18 MPa. The mechanical properties obtained could be explained on the basis of the different compounds identified on the fracture surfaces by XRD. On the other hand, the use of the Ag–34.5Cu–1.5Ti brazing alloy and a brazing temperature of 850 °C produces the best results in terms of corrosion rates (lower corrosion current density), 0.76 ± 0.21 μA cm−2. Nevertheless, the joints produced at 850 °C using a Ag–26.5Cu–3Ti brazing alloy present the best compromise between mechanical properties and degradation behaviour, 234 ± 18 MPa and 1.26 ± 0.58 μA cm−2, respectively. The role of Ti diffusion is fundamental in terms of the final value achieved for the M/C bond strength. On the contrary, the Ag and Cu distribution along the brazed interface seem to play the most relevant role in the metal/ceramic joints electrochemical performance.

Risk of dependence associated with health, social support, and lifestyle

OBJECTIVE To analyze the prevalence of individuals at risk of dependence and its associated factors.METHODS The study was based on data from the Catalan Health Survey, Spain conducted in 2010 and 2011. Logistic regression models from a random sample of 3,842 individuals aged ≥ 15 years were used to classify individuals according to the state of their personal autonomy. Predictive models were proposed to identify indicators that helped distinguish dependent individuals from those at risk of dependence. Variables on health status, social support, and lifestyles were considered.RESULTS We found that 18.6% of the population presented a risk of dependence, especially after age 65. Compared with this group, individuals who reported dependence (11.0%) had difficulties performing activities of daily living and had to receive support to perform them. Habits such as smoking, excessive alcohol consumption, and being sedentary were associated with a higher probability of dependence, particularly for women.CONCLUSIONS Difficulties in carrying out activities of daily living precede the onset of dependence. Preserving personal autonomy and function without receiving support appear to be a preventive factor. Adopting an active and healthy lifestyle helps reduce the risk of dependence.

Incidence and risk factors for intimate partner violence during the postpartum period

OBJECTIVE To estimate the incidence and identify risk factors for intimate partner violence during postpartum.METHODS This prospective cohort study was conducted with women, aged between 18-49 years, enrolled in the Brazilian Family Health Strategy in Recife, Northeastern Brazil, between 2005 and 2006. Of the 1.057 women interviewed during pregnancy and postpartum, 539 women, who did not report violence before or during pregnancy, were evaluated. A theoretical-conceptual framework was built with three levels of factors hierarchically ordered: women’s and partners’ sociodemografic and behavioral characteristics, and relationship dynamics. Incidence and risk factors of intimate partner violence were estimated by Poisson Regression.RESULTS The incidence of violence during postpartum was 9.3% (95%CI 7.0;12.0). Isolated psychological violence was the most common (4.3%; 95%CI 2.8;6.4). The overlapping of psychological with physical violence occurred at 3.3% (95%CI 2.0;5.3) and with physical and/or sexual in almost 2.0% (95%CI 0.8;3.0) of cases. The risk of partner violence during postpartum was increased for women with a low level of education (RR = 2.6; 95%CI 1.3;5.4), without own income (RR = 1.7; 95%CI 1.0;2.9) and those who perpetrated physical violence against their partner without being assaulted first (RR = 2.0; 95%CI 1.2;3.4), had a very controlling partner (RR = 2.5; 95%CI 1.1;5.8), and had frequent fights with their partner (RR = 1.7; 95%CI 1.0;2.9).CONCLUSIONS The high incidence of intimate partner violence during postpartum and its association with aspects of the relationship’s quality between the couple, demonstrated the need for public policies that promote conflict mediation and enable forms of empowerment for women to address the cycle of violence.

Chemical composition and antioxidante activity of Tunisian Origanum glandulosum Desf. essential oil and volatile oil obtain by supercritical CO2 extraction

Dried flowers and leaves of Origanum glandulosum Desf. were submitted to hydrodistillation (HD) and supercritical fluid extraction with CO2 (SFE). The essential oils isolated by HD and volatile oils obtained by SFE were analysed by GC and GC/MS. Total phenolics content and antioxidant effectiveness were performed. The main components of the essential oils from Bargou and Nefza were: p-cymene (40.4% and 39%), thymol (38.7% and 34.4%) and γ- terpinene (12.3% and 19.2%), respectively. The major components obtain by SFE in the volatile oil, from Bargou and Nefza, were: p-cymene (32.3% and 36.2%), thymol (41% and 40%) and γ-terpinene (20.3% and 13.3%). Total phenolic content, expressed in gallic acid equivalent (GAE) g kg-1 dry weight, varied from 12 to 27 g kg-1 dw, and the ability to scavenge the DPPH radicals, expressed by IC50 ranged from 44 to143 mg L-1.

Occupational conditions and the risk of the use of amphetamines by truck drivers

OBJECTIVE To test whether the occupational conditions of professional truck drivers are associated with amphetamine use after demographic characteristics and ones regarding mental health and drug use are controlled for.METHODS Cross-sectional study, with a non-probabilistic sample of 684 male truck drivers, which was collected in three highways in Sao Paulo between years 2012 and 2013. Demographic and occupational information was collected, as well as data on drug use and mental health (sleep quality, emotional stress, and psychiatric disorders). A logistic regression model was developed to identify factors associated with amphetamine use. Odds ratio (OR; 95%CI) was defined as the measure for association. The significance level was established as p < 0.05.RESULTS The studied sample was found to have an average age of 36.7 (SD = 7.8) years, as well as low education (8.6 [SD = 2.3] years); 29.0% of drivers reported having used amphetamines within the twelve months prior to their interviews. After demographic and occupational variables had been controlled for, the factors which indicated amphetamine use among truck drivers were the following: being younger than 38 years (OR = 3.69), having spent less than nine years at school (OR = 1.76), being autonomous (OR = 1.65), working night shifts or irregular schedules (OR = 2.05), working over 12 hours daily (OR = 2.14), and drinking alcohol (OR = 1.74).CONCLUSIONS Occupational aspects are closely related to amphetamine use among truck drivers, which reinforces the importance of closely following the application of law (Resting Act (“Lei do Descanso”); Law 12,619/2012) which regulates the workload and hours of those professionals. Our results show the need for increased strictness on the trade and prescription of amphetamines in Brazil.