No description available.

Background Hand-arm vibration (HAV) is an occupational hazard which, cumulatively, leads to hand-arm vibration syndrome (HAVS). Detection and reduction of HAV can help prevent the disease or slow down its progress. Unfortunately, assessment of HAV through direct measurement is difficult due to the high cost of measurement equipment, interruption of work performance, and long travel cost to worksites. An alternative assessment method is through development of an exposure prediction model to identify workplace, tool, and task characteristics which significantly predict HAV exposure. Purpose The purpose of this study is twofold: 1) to determine the extent and nature of previously published scientific journal articles on exposure prediction modeling of HAV through performing a systematic review; and 2) to develop a new exposure prediction model using administrative data to find significant HAV predictors. Methods A systematic review of relevant studies involved humans aged 18 or over, applicable to occupational setting, with vibration measured using tri-axial accelerometer and statistical modeling of the effects of occupational characteristics on measure HAV were identified. Five online bibliographic databases (Medline, CINAHL, Web of Science, Scopus, and EMBASE) were searched using a combined word list of terms under three categories: “occupational diseases”; “Hand-arm vibration”; and “Statistical Modelling”. Two multiple linear regression models predicting average hand-arm vibration exposure over 8 hour day, A(8), were built using enforcement data collected by Ministry of Labour Relations and Workplace Safety Saskatchewan using standard model building method. In addition, GEE was used to account for repeated data collection within workers and worksites. Results In the first manuscript, 7 articles found were deemed relevant. Four studies built regression models, while three used ANOVA to find significant HAV predictors. Examples of significant HAV predictors included: tool age, tool weight, participant, and operating power; the proportion of HAV variance explained varied from 46 to 90%. In the second manuscript, the models based on administrative data explained 16% to 27% of A(8) variance. The included variables were tool power source, vibration control, and job type for the parsimonious model; the comprehensive model has the same variables as parsimonious along with accelerometer attachment method and tool brand. Conclusion HAV prediction through exposure prediction modeling is a relatively new method for assessing occupational HAV. It is feasible to find HAV predictors using low-cost administrative data, and variables such as tool power source, job type, and vibration control make promising predictors. However, the variance explained will be lower than using data collected for research purposes. The significant predictors found in the systematic review can be considered when installing protective measures in the future. The significant predictors found and procedures used from the modeling study can be considered for future HAV exposure prediction modeling studies.

The purpose of this thesis was to assess the possible risk of myocardial infarction in work entailing exposure to vibration, and to study whether there is any relation between short-term exposure to vibration and cardiac regulation. Epidemiological methods were applied to investigate a possible association between occupational exposure to vibration and myocardial infarction. Two study populations were used; one case-control study (n=475) and one cohort of iron-ore miners in Kiruna and Malmberget, Sweden (n=13621). In the former, the cases were first-time myocardial infarction patients and the controls were selected to match for sex, age and hospital catchment area. Job-exposure matrixes for vibration were established for both the case-control study and the cohort study. In order to study acute effects on cardiac regulation, an experimental study was conducted on healthy subjects (n=20) who were exposed to hand-arm vibration exclusively and in combination with exposure to noise. The effect on the autonomic balance was measured by heart rate-variability. In the case-control study, an increased risk of contracting myocardial infarction was found among occupations entailing vibration exposure. The results from the cohort show an increased risk of myocardial infarction mortality compared to a reference population. The increment was higher for those younger than 60 years. Relative risks for myocardial infarction mortality increased with increasing exposure to vibration in the group at working-age and the increased risk remained after adjusting for exposure to dust. In the experimental study, exposure to hand-arm vibration was found to acutely affect the autonomic nervous system as the total heart-rate variability decreased during exposure to hand-arm vibration. To conclude: work entailing exposure to vibration is a risk factor for myocardial infarction, increased myocardial infarction mortality attributed to exposure to vibration seems to be mainly observed at working-age, and exposure to hand-arm vibration acutely decreases heart-rate variability and thus affects heart-rate regulation.

No description available.

La fatigue est un phénomène bien connu dans le monde du sport provoquant une chute des performances et une augmentation du risque de blessures. La communauté scientifique s’intéresse donc à la quantification de ce phénomène au moyen de différents outils d’analyse du mouvement. Cependant certains sports comme la course à pied soumettent les athlètes à des sollicitations mécaniques violentes impactant fortement sur leur santé et leurs performances. Ces sollicitations se traduisent souvent par des chocs importants, un nombre de cycles élevé et sont accompagnées de postures complexes du corps. Les outils d’analyse du mouvement ne sont alors pas toujours adaptés pour la mesures de ces données ni à l’étude du mouvement de l’athlète dans des conditions réelles de pratique. L’accélération apparait alors comme une caractéristique riche en informations. Elle peut permettre de mesurer et d’analyser la pratique de la course à pied afin de quantifier la dérive de la réponse mécanique du corps humain. Par la validation d’outils issus de l’accélérométrie, ces travaux de thèse permettront d’étudier les phénomènes mécaniques intervenant durant la pratique de la course à pied afin de quantifier et prédire leurs effets sur les phénomènes de fatigue des athlètes. / Fatigue is a well known phenomenon in the sports world causing a decrease of performance and an increase of injury risk. The scientific community is therefore concerned with the quantification of this phenomenon using different motion analysis tools. However some sports like running inflict violent mechanical loads to the athletes strongly impacting their health and performance. These loads frequently result in significant shocks, a high number of cycles and are accompanied by complex postures of the body. The motion analysis tools are then not always suitable for the measurement of this information or to study the athlete’s movement in real conditions of practice. The acceleration then appears as a feature rich in information.It can allow to measure and analyze the practice of running in order to quantify the drift of the mechanical response of the human body. By validating accelerometric tools, these thesis works will allow to study the mechanical phenomena intervening in the practice of running in order to quantify and predict their effects on the athlete’s fatigue.

No description available.