Factors associated with work ability in patients with chronic whiplash-associated disorder grade II-III: a cross-sectional analysis

Objective: To investigate the factors related to self-perceived work ability in patients with chronic whiplash-associated disorder grades II-III. Design: Cross-sectional analysis. Patients: A total of 166 working age patients with chronic whiplash-associated disorder. Methods: A comprehensive survey collected data on work ability (using the Work Ability Index); demographic, psychosocial, personal, work- and condition-related factors. Forward, stepwise regression modelling was used to assess the factors related to work ability. Results: The proportion of patients in each work ability category were as follows: poor (12.7%); moderate (39.8%); good (38.5%); excellent (9%). Seven factors explained 65% (adjusted R2= 0.65, p < 0.01) of the variance in work ability. In descending order of strength of association, these factors are: greater neck disability due to pain; reduced self-rated health status and health-related quality of life; increased frequency of concentration problems; poor workplace satisfaction; lower self-efficacy for performing daily tasks; and greater work-related stress. Conclusion: Condition-specific and psychosocial factors are associated with self-perceived work ability of individuals with chronic whiplash-associated disorder

Оценка финансового состояния предприятия и направления его улучшения (на примере ОАО «Гомельский мотороремонтный завод»)

Objectives: Sickness absence in workplaces may reflect working conditions. It may also reflect a "healthy hire effect," i.e., that workplaces recruit individuals with experience of sickness absence differently. The purpose of the study was to determine if a history of sickness absence among recruits is associated with the average level of sickness absence in workplaces. Material and Methods: In a register-based follow-up study, Swedish workplaces with at least 5 employees in 2006 were selected (approximately 127 000 workplaces with 3.9 million employees). The workplaces were categorized according to the average workplace sickness absence in 2006 and the recruits were categorized according to the individual sickness absence in 2005. The workplaces with a high average level of sickness absence were more likely than those with a low level to hire employees with high sickness absence in the year preceding employment: men - odds ratio (OR) = 7.2, 95% confidence interval (CI): 6.6-7.8, women OR = 7.5, 95% CI: 6.9-8.1. Results: The results show that there is a greater likelihood of employing individuals with high levels of sickness absence in the workplaces with many days of the average sickness absence than in the workplaces with few days of the average sickness absence. Conclusions: The results suggest that sickness absence in workplaces may reflect a healthy hire effect.Funding Agencies|AFA Insurance [090299]</p

Determining the end-date of long-ripening cheese maturation using NIR hyperspectral image modelling: A feasibility study

Near-infrared (874–1734 nm) hyperspectral (NIR-HS) imaging, coupled with chemometric tools, was used to explore the relationship between spectroscopic data and cheese maturation. A predictive tool to determine the end-date of cheese maturation (E-index, in days) was developed using a set of 425 NIR-HS images acquired during industrial-scale cheese production. The NIR-HS images were obtained by scanning the cheeses at 14, 16, 18 and 20 months of ripening, before a final sensorial assessment in which all cheeses were approved by 20 months. Regression modelling by partial least squares (PLS) was used to explore the relationship between average spectra and E-index. The best PLS model achieved 69.6% accuracy in the prediction of E-index when standard normal variate (SNV) correction and mean centring pre-processing were applied. Thus, NIR-HS image modelling can be useful as a complementary tool to optimise the logistics/efficiency of cheese ripening facilities by rapid and non-destructive prediction of the end-date of ripening for individual cheeses. However, the commercial application will require future improvements in the predictive capacity of the model, e.g. for larger datasets and repetitive scans of cheeses on random occasions

Use of near-infrared hyperspectral (NIR-HS) imaging to visualize and model the maturity of long-ripening hard cheeses

Spectroscopic measurements and imaging have great potential in rapid prediction of cheese maturity, replacing existing subjective evaluation techniques. In this study, 209 long-ripening hard cheeses were evaluated using a hyperspectral camera and also sensory evaluated by a tasting panel. A total of 425 NIR hyperspectral (NIR-HS) images were obtained during ripening at 14, 16, 18, and 20 months, until final sensorial approval of the cheese. The spectral data were interpreted as possible compositional changes between scanning occasions. Regression modelling by partial least squares (PLS) was used to explain the relationship between average spectra and cheese maturity. The PLS model was evaluated with whole cheeses (average spectrum), but also pixelwise, producing prediction images. Analysis of the images showed an increasing homogeneity of the cheese over the time of storage and ripening. It also suggested that maturation begins at the center and spreads to the outer periphery of the cheese

Formal caregivers’ perceptions of quality of care for older people: associating factors

Background Despite the growing number of studies concerning quality of care for older people, there is a lack of studies depicting factors associated with good quality of care from the formal caregivers’ perspective. The aim was to describe formal caregivers’ perceptions of quality of care for older people in the community and explore factors associated with these perceptions. In total, 70 nursing assistants, 163 enrolled nurses and 198 registered nurses from 14 communities in central Sweden participated in the study. They filled out the following questionnaires: a modified version of Quality from the Patient’s Perspective, Creative Climate Questionnaire, Stress of Conscience Questionnaire, items regarding education and competence, Health Index and Sense of coherence questionnaire. The overall response rate was 57 % (n = 431). Results In the perceived reality of quality of care respondents assessed the highest mean value in the dimension medical-technical competence and physical technical conditions and lower values in the dimensions; identity-oriented approach, socio-cultural atmosphere and in the context specific dimension. The caregivers estimated their competence and health rather high, had lower average values in sense of coherence and organizational climate and low values in stress of conscience. Conclusions The PR of quality of care were estimated higher among NA/ENs compared to RNs. Occupation, organizational climate and stress of conscience were factors associated with quality of care that explained 42 % of the variance. Competence, general health and sense of coherence were not significantly associated to quality of care. The mentioned factors explaining quality of care might be intertwined and showed that formal caregivers’ working conditions are of great importance for quality of care

Associations between the Bacterial Composition of Farm Bulk Milk and the Microbiota in the Resulting Swedish Long-Ripened Cheese

The maturation of a traditional Swedish long-ripened cheese has shown increasing variation in recent years and the ripening time is now generally longer than in the past. While the cheese is reliant on non-starter lactic acid bacteria for the development of its characteristic flavour, we hypothesised that the observed changes could be due to variations in the microbiota composition and number of bacteria in the raw milk used for production of the cheese. To evaluate associations between microbiota in the raw milk and the resulting cheese, three clusters of commercial farms were created to increase variation in the microbiota of dairy silo milk used for cheese production. Cheese production was performed in three periods over one year. Within each period, milk from the three farm clusters was collected separately and transported to the cheese production facility. Following pasteurisation, the milk was processed into the granular-eyed cheese and matured at a dedicated cheese-ripening facility. For each cheese batch, farm bulk and dairy silo milk samples, a starter culture, early process samples and cheese samples from different stages of maturation (7-20 months) were collected and their microbiota characterised using 16S rRNA amplicon sequencing. The microbiota in the farm bulk milk differed significantly between periods and clusters. Differences in microbiota in dairy silo milk were observed between periods, but not between farm clusters, while the cheese microbiota differed between periods and clusters. The top 13 amplicon sequence variants were dominant in early process samples and the resulting cheese, making up at least 93.3% of the relative abundance (RA). Lactococcus was the dominant genus in the early process samples and, together with Leuconostoc, also dominated in the cheese samples. Contradicting expectations, the RA of the aroma-producing genus Lactobacillus was low in cheese during ripening and there was an unexpected dominance of starter lactic acid bacteria even at the later stages of cheese ripening. To identify factors behind the recent variations in ripening time of this cheese, future studies should address the effects of process variables and the dairy environment

Milking system and premilking routines have strong effect on the microbial community in bulk tank milk

In this study, we investigated the variation in the microbial community present in bulk tank milk samples and the potential effect of different farm management factors. Bulk tank milk samples were collected repeatedly over one year from 42 farms located in northern Sweden. Total and thermoresistant bacteria counts and 16S rRNA gene-based amplicon sequencing were used to characterize microbial community composition. The microbial community was in general heterogeneous both within and between different farms and the community composition in the bulk tank milk was commonly dominated by Pseudomonas, Acinetobacter, Streptococcus, unclassified Peptostreptococcaceae, and Staphylococcus. Principal component analysis including farm factor variables and microbial taxa data revealed that the microbial community in milk was affected by type of milking system. Milk from farms using an automatic (robot) milking system (AMS) and loose housing showed different microbial community composition compared with milk from tiestall farms. A discriminant analysis model revealed that this difference was dependent on several microbial taxa. Among farms using an automatic milking system, there were further differences in the microbial community composition depending on the brand of the milking robot used. On tiestall farms, routines for teat preparation and cleaning of the milking equipment affected the microbial community composition in milk. Total bacteria count (TBC) in milk differed between the farm types, and TBC were higher on AMS than tiestall farms (log 4.05 vs. log 3.79 TBC/mL for AMS and tiestalls, respectively). Among tiestall farms, milk from farms using a chemical agent in connection to teat preparation and a more frequent use of acid to clean the milking equipment had lower TBC in milk, than milk from farms using water for teat preparation and a less frequent use of acid to clean the milking equipment (log 3.68 vs. 4.02 TBC/mL). There were no significant differences in the number of thermoresistant bacteria between farm types. The evaluated factors explained only a small proportion of total variation in the microbiota data, however, despite this, the study highlights the effect of routines associated with teat preparation and cleaning of the milking equipment on raw milk microbiota, irrespective of type of milking system used

Световой прибор повышенной эффективности на основе светодиодов

Полезная модель относится к области светотехники и может быть использована при конструировании и эксплуатации световых приборов повышенной эффективности на основе светодиодов

Work-related psychosocial events as triggers of sick leave - results from a Swedish case-crossover study

<p>Abstract</p> <p>Background</p> <p>Although illness is an important cause of sick leave, it has also been suggested that non-medical risk factors may influence this association. If such factors impact on the period of decision making, they should be considered as triggers. Yet, there is no empirical support available.</p> <p>The aim was to investigate whether recent exposure to work-related psychosocial events can trigger the decision to report sick when ill.</p> <p>Methods</p> <p>A case-crossover design was applied to 546 sick-leave spells, extracted from a Swedish cohort of 1 430 employees with a 3-12 month follow-up of new sick-leave spells. Exposure in a case period corresponding to an induction period of one or two days was compared with exposure during control periods sampled from workdays during a two-week period prior to sick leave for the same individual. This was done according to the matched-pair interval and the usual frequency approaches. Results are presented as odds ratios (OR) with 95% confidence intervals (CI).</p> <p>Results</p> <p>Most sick-leave spells happened in relation to acute, minor illnesses that substantially reduced work ability. The risk of taking sick leave was increased when individuals had recently been exposed to problems in their relationship with a superior (OR 3.63; CI 1.44-9.14) or colleagues (OR 4.68; CI 1.43-15.29). Individuals were also more inclined to report sick on days when they expected a very stressful work situation than on a day when they were not under such stress (OR 2.27; CI 1.40-3.70).</p> <p>Conclusions</p> <p>Exposure to problems in workplace relationships or a stressful work situation seems to be able to trigger reporting sick. Psychosocial work-environmental factors appear to have a short-term effect on individuals when deciding to report sick.</p