Association of working conditions with self-reported work-related symptoms: results from the Swiss dataset of the European Working Conditions Survey

Working conditions are important determinants of health. The aims of this article are to 1) identify working conditions and work characteristics that are associated with workers' perceptions that their work is harmful to their health and 2) identify with what symptoms these working conditions are associated.We used the Swiss dataset from the 2005 edition of the European Working Conditions Survey. The dependent variable was based on the question "Does your work affect your health?". Logistic regression was used to identify a set of variables collectively associated with self-reported work-related adverse health effects.A total of 330 (32%) participants reported having their health affected by work. The most frequent symptoms included backache (17.1%), muscular pains (13.1%), stress (18.3%) and overall fatigue (11.7%). Scores for self-reported exposure to physicochemical risks, postural and physical risks, high work demand, and low social support were all significantly associated with workers' perceptions that their work is harmful to their health, regardless of gender or age. A high level of education was associated with stress symptoms, and reports that health was affected by work was associated with low job satisfaction.Many workers believe that their work affects their health. Health specialists should pay attention to the potential association between work and their patients' health complaints. This is particularly relevant when patients mention symptoms such as muscular pains, backache, overall fatigue, and stress. Specific attention should be given to complaints of stress in highly educated workers.

Estimating Design-Flood Discharges for Streams in Iowa Using Drainage-Basin and Channel-Geometry Characteristics, HR-322, 1993

Drainage-basin and channel-geometry multiple-regression equations are presented for estimating design-flood discharges having recurrence intervals of 2, 5, 10, 25, 50, and 100 years at stream sites on rural, unregulated streams in Iowa. Design-flood discharge estimates determined by Pearson Type-III analyses using data collected through the 1990 water year are reported for the 188 streamflow-gaging stations used in either the drainage-basin or channel-geometry regression analyses. Ordinary least-squares multiple-regression techniques were used to identify selected drainage-basin and channel-geometry regions. Weighted least-squares multiple-regression techniques, which account for differences in the variance of flows at different gaging stations and for variable lengths in station records, were used to estimate the regression parameters. Statewide drainage-basin equations were developed from analyses of 164 streamflow-gaging stations. Drainage-basin characteristics were quantified using a geographic-information-system (GIS) procedure to process topographic maps and digital cartographic data. The significant characteristics identified for the drainage-basin equations included contributing drainage area, relative relief, drainage frequency, and 2-year, 24-hour precipitation intensity. The average standard errors of prediction for the drainage-basin equations ranged from 38.6% to 50.2%. The GIS procedure expanded the capability to quantitatively relate drainage-basin characteristics to the magnitude and frequency of floods for stream sites in Iowa and provides a flood-estimation method that is independent of hydrologic regionalization. Statewide and regional channel-geometry regression equations were developed from analyses of 157 streamflow-gaging stations. Channel-geometry characteristics were measured on site and on topographic maps. Statewide and regional channel-geometry regression equations that are dependent on whether a stream has been channelized were developed on the basis of bankfull and active-channel characteristics. The significant channel-geometry characteristics identified for the statewide and regional regression equations included bankfull width and bankfull depth for natural channels unaffected by channelization, and active-channel width for stabilized channels affected by channelization. The average standard errors of prediction ranged from 41.0% to 68.4% for the statewide channel-geometry equations and from 30.3% to 70.0% for the regional channel-geometry equations. Procedures provided for applying the drainage-basin and channel-geometry regression equations depend on whether the design-flood discharge estimate is for a site on an ungaged stream, an ungaged site on a gaged stream, or a gaged site. When both a drainage-basin and a channel-geometry regression-equation estimate are available for a stream site, a procedure is presented for determining a weighted average of the two flood estimates.

Impacts on Safety of Left-Turn Treatment at High Speed Signalized Intersections, HR-347, 1994

Left-turning traffic is a major source of conflicts at intersections. Though an average of only 10% to 15% of all approach traffic turns left, these vehicles are involved in approximately 45% of all accidents. This report presents the results of research conducted to develop models which estimate approach accident rates at high speed signalized intersections. The objective of the research was to quantify the relationship between traffic and intersection characteristics, and accident potential of different left turn treatments. Geometric, turning movement counts, and traffic signal phasing data were collected at 100 intersections in Iowa using a questionnaire sent to municipalities. Not all questionnaires resulted in complete data and ultimately complete data were derived for 63 intersections providing a database of 248 approaches. Accident data for the same approaches were obtained from the Iowa Department of Transportation Accident Location and Analysis System (ALAS). Regression models were developed for two different dependent variables: 1) the ratio of the number of left turn accidents per approach to million left turning vehicles per approach, and 2) the ratio of accidents per approach to million traffic movements per approach. A number of regression models were developed for both dependent variables. One model using each dependent variable was developed for intersections with low, medium, and high left turning traffic volumes. As expected, the research indicates that protected left turn phasing has a lower accident potential than protected/permitted or permitted phasing. Left turn lanes and multiple lane approaches are beneficial for reducing accident rates, while raised medians increase the likelihood of accidents. Signals that are part of a signal system tend to have lower accident rates than isolated signals. The resulting regression models may be used to determine the likely impact of various left turn treatments on intersection accident rates. When designing an intersection approach, a traffic engineer may use the models to estimate the accident rate reduction as a result of improved lane configurations and left turn treatments. The safety benefits may then be compared to any costs associated with operational effects to the intersection (i.e., increased delay) to determine the benefits and costs of making intersection safety improvements.

Looking for Validity or Testing It? The Perils of Stepwise Regression, Extreme-Scores Analysis, Heteroscedasticity, and Measurement Error

When researchers introduce a new test they have to demonstrate that it is valid, using unbiased designs and suitable statistical procedures. In this article we use Monte Carlo analyses to highlight how incorrect statistical procedures (i.e., stepwise regression, extreme scores analyses) or ignoring regression assumptions (e.g., heteroscedasticity) contribute to wrong validity estimates. Beyond these demonstrations, and as an example, we re-examined the results reported by Warwick, Nettelbeck, and Ward (2010) concerning the validity of the Ability Emotional Intelligence Measure (AEIM). Warwick et al. used the wrong statistical procedures to conclude that the AEIM was incrementally valid beyond intelligence and personality traits in predicting various outcomes. In our re-analysis, we found that the reliability-corrected multiple correlation of their measures with personality and intelligence was up to .69. Using robust statistical procedures and appropriate controls, we also found that the AEIM did not predict incremental variance in GPA, stress, loneliness, or well-being, demonstrating the importance for testing validity instead of looking for it.

"Suddenly I get into the zone": Examining discontinuities and nonlinear changes in flow experiences at work

Work-related flow is defined as a sudden and enjoyable merging of action and awareness that represents a peak experience in the daily lives of workers. Employees" perceptions of challenge and skill and their subjective experiences in terms of enjoyment, interest and absorption were measured using the experience sampling method, yielding a total of 6981 observations from a sample of 60 employees. Linear and nonlinear approaches were applied in order to model both continuous and sudden changes. According to the R2, AICc and BIC indexes, the nonlinear dynamical systems model (i.e. cusp catastrophe model) fit the data better than the linear and logistic regression models. Likewise, the cusp catastrophe model appears to be especially powerful for modelling those cases of high levels of flow. Overall, flow represents a nonequilibrium condition that combines continuous and abrupt changes across time. Research and intervention efforts concerned with this process should focus on the variable of challenge, which, according to our study, appears to play a key role in the abrupt changes observed in work-related flow.

Contribution of multimorbidity to overall mortality in the population-based CoLaus study

Introduction : Multimorbidity (MM) is currently a major health concern for hospitalized patients but little is known about the relative importance of MM in the general population. Accordingly we assessed whether MM could be a good predictor of overall mortality. Method : Data from the population based CoLaus Study: 3239 participants (1731 women, mean age 50+/-9 years) followed for a median time of 5.4 years (range 0.4 to 8.5 years). MM was defined as presenting >=2 morbidities according to Barnett et al. (27 items, measured data). Survival analysis was conducted using Cox regression. Results : During follow-up, 53 (1.6%) participants died. Participants who died had a higher number of morbidities (2.4 +/- 1.6 vs. 1.9 +/- 1.5, p<0.05) and had a higher prevalence of MM (69.8% vs. 55.9%, p<0.05). On bivariate analysis, presence of MM (defined as a yes/no variable) was significantly related with overall mortality: relative risk (RR) of 1.84, 95% confidence interval [1.02; 3.31], p<0.05 (see figure), but this association became non-significant after adjusting for age, gender and smoking: RR=1.68 [0.93; 3.04], p=0.09. Similar results were obtained when using the number of morbidities: RR for an extra morbidity 1.22 [1.05; 1.44], p<0.02; after adjusting for age, gender and smoking, RR=1.16 [0.99; 1.37], p=0.07. Conclusion : During a short 5 year observation period, measured MM in the general population is associated with overall mortality. This association becomes borderline significant after multivariate adjustment. These observations will have to be confirmed during a longer follow-up period. This increased mortality in MM patients may require developing specific strategies of screening and prevention.

The pivot player in handball and patterns detection - instrument

The theoretical context of this study is related with the observational methodology in the context of group games and sports studies, specifically Handball. Thus, this study intends to analyze the performance of the pivot player in the World Cup 2007 - Germany, European 2008 - Norway 2008 and China OG 2008 in a qualitative dimension. Our purpose was to get as much information as possible about the whole activity of the pivot player, by identifying sequential patterns of behaviour or conduct of the player/game, by using the sequential analysis. The observation instrument used to meet the main purpose of this work consists of a combination of format fields (FF) and systems of categories (SC). The codifications undertaken occurred in several handball games. Using this instrument we have shown that it provides support for the purposes for which it was developed, allowing more research into the offensive process of handball. Besides this, it makes possible the analysis of aspects of the game through perspective and contextual sequences, which we consider to be more accurate, to fit the "reality" of a game such as handball.

Observational methodology in football: Development of an instrument to study the offensiva game in football.

The following paper introduces a new approach to the analysis of offensive game in football. Therefore, the main aim of this study was to create an instrument for collecting information for the analysis of offensive action and interactions game. The observation instrument that was used to accomplish the main objective of this work consists of a combination of format fields (FC) and systems of categories (SC). This methodology is a particular strategy of the scientific method that has as an objective to analyse the perceptible behaviour that occurs in habitual contexts, allowing them to be formally recorded and quantified and using an ad hoc instrument in order to obtain a behaviour systematic registration that, since they have been transformed in quantitative data with the necessary reliability and validity determined level, will allow analysis of the relations between these behaviours. The codifications undertaken to date in various games of football have shown that it serves the purposes for which it was developed, allowing more research into the offensive game methods in football.

Adapting football to the child: an application of the logistic regression model in observational mewthodology.

Logistic regression is included into the analysis techniques which are valid for observationalmethodology. However, its presence at the heart of thismethodology, and more specifically in physical activity and sports studies, is scarce. With a view to highlighting the possibilities this technique offers within the scope of observational methodology applied to physical activity and sports, an application of the logistic regression model is presented. The model is applied in the context of an observational design which aims to determine, from the analysis of use of the playing area, which football discipline (7 a side football, 9 a side football or 11 a side football) is best adapted to the child"s possibilities. A multiple logistic regression model can provide an effective prognosis regarding the probability of a move being successful (reaching the opposing goal area) depending on the sector in which the move commenced and the football discipline which is being played.

Improved multiple-locus variable-number tandem-repeat assay for Staphylococcus aureus genotyping, providing a highly informative technique together with strong phylogenetic value.

We describe an improved multiple-locus variable-number tandem-repeat (VNTR) analysis (MLVA) scheme for genotyping Staphylococcus aureus. We compare its performance to those of multilocus sequence typing (MLST) and spa typing in a survey of 309 strains. This collection includes 87 epidemic methicillin-resistant S. aureus (MRSA) strains of the Harmony collection, 75 clinical strains representing the major MLST clonal complexes (CCs) (50 methicillin-sensitive S. aureus [MSSA] and 25 MRSA), 135 nasal carriage strains (133 MSSA and 2 MRSA), and 13 published S. aureus genome sequences. The results show excellent concordance between the techniques' results and demonstrate that the discriminatory power of MLVA is higher than those of both MLST and spa typing. Two hundred forty-two genotypes are discriminated with 14 VNTR loci (diversity index, 0.9965; 95% confidence interval, 0.9947 to 0.9984). Using a cutoff value of 45%, 21 clusters are observed, corresponding to the CCs previously defined by MLST. The variability of the different tandem repeats allows epidemiological studies, as well as follow-up of the evolution of CCs and the identification of potential ancestors. The 14 loci can conveniently be analyzed in two steps, based upon a first-line simplified assay comprising a subset of 10 loci (panel 1) and a second subset of 4 loci (panel 2) that provides higher resolution when needed. In conclusion, the MLVA scheme proposed here, in combination with available on-line genotyping databases (including http://mlva.u-psud.fr/), multiplexing, and automatic sizing, can provide a basis for almost-real-time large-scale population monitoring of S. aureus.

Low-cost microprocessed instrument for evaluating soil temperature profile

This paper describes a low-cost microprocessed instrument for in situ evaluating soil temperature profile ranging from -20.0°C to 99.9°C, and recording soil temperature data at eight depths from 2 to 128 cm. Of great importance in agriculture, soil temperature affects plant growth directly, and nutrient uptake as well as indirectly in soil water and gas flow, soil structure and nutrient availability. The developed instrument has potential applications in the soil science, when temperature monitoring is required. Results show that the instrument with its individual sensors guarantees ±0.25°C accuracy and 0.1°C resolution, making possible localized management changes within decision support systems. The instrument, based on complementary metal oxide semiconductor devices as well as thermocouples, operates in either automatic or non-automatic mode.

Development and validation of a clinical prediction rule for chest wall syndrome in primary care.

ABSTRACT: BACKGROUND: Chest wall syndrome (CWS), the main cause of chest pain in primary care practice, is most often an exclusion diagnosis. We developed and evaluated a clinical prediction rule for CWS. METHODS: Data from a multicenter clinical cohort of consecutive primary care patients with chest pain were used (59 general practitioners, 672 patients). A final diagnosis was determined after 12 months of follow-up. We used the literature and bivariate analyses to identify candidate predictors, and multivariate logistic regression was used to develop a clinical prediction rule for CWS. We used data from a German cohort (n = 1212) for external validation. RESULTS: From bivariate analyses, we identified six variables characterizing CWS: thoracic pain (neither retrosternal nor oppressive), stabbing, well localized pain, no history of coronary heart disease, absence of general practitioner's concern, and pain reproducible by palpation. This last variable accounted for 2 points in the clinical prediction rule, the others for 1 point each; the total score ranged from 0 to 7 points. The area under the receiver operating characteristic (ROC) curve was 0.80 (95% confidence interval 0.76-0.83) in the derivation cohort (specificity: 89%; sensitivity: 45%; cut-off set at 6 points). Among all patients presenting CWS (n = 284), 71% (n = 201) had a pain reproducible by palpation and 45% (n = 127) were correctly diagnosed. For a subset (n = 43) of these correctly classified CWS patients, 65 additional investigations (30 electrocardiograms, 16 thoracic radiographies, 10 laboratory tests, eight specialist referrals, one thoracic computed tomography) had been performed to achieve diagnosis. False positives (n = 41) included three patients with stable angina (1.8% of all positives). External validation revealed the ROC curve to be 0.76 (95% confidence interval 0.73-0.79) with a sensitivity of 22% and a specificity of 93%. CONCLUSIONS: This CWS score offers a useful complement to the usual CWS exclusion diagnosing process. Indeed, for the 127 patients presenting CWS and correctly classified by our clinical prediction rule, 65 additional tests and exams could have been avoided. However, the reproduction of chest pain by palpation, the most important characteristic to diagnose CWS, is not pathognomonic.