Accidents: Risk Factors, Health Outcomes and Safety Measures by Carlo Giacomo Prato

By Carlo Giacomo Prato

This ebook emerges from the curiosity in enriching the physique of information approximately coincidence features, studying health and wellbeing results and offering measures to beat societal and monetary outcomes of injuries. Contributions from diversified disciplines compose a suite that gives solutions to popular questions from a variety of views. the 3 components of the publication provide a entire assessment of the hot state-of-the-practice wisdom approximately twist of fate features, possibility components, results and security interventions. Combining wisdom from either highway and occupational defense, and increasing via quite a few disciplines reminiscent of engineering, economics, medication, and data, this assortment stimulates readers in trying to find stronger options to security difficulties which are a massive chance to human lifestyles and value hundreds of thousands to our society.

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Accidents: Risk Factors, Health Outcomes and Safety Measures

This e-book emerges from the curiosity in enriching the physique of data approximately coincidence features, studying health and wellbeing results and featuring measures to beat societal and financial effects of injuries. Contributions from varied disciplines compose a suite that offers solutions to favourite questions from quite a few views.

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Sample The data used in the analysis come from Statistics Denmark’s collection of register data and are linked to individuals such that various registers of interest can be merged. For this analysis, all owners of a car or a motorcycle were extracted from the central vehicle register and split into three subgroups: Car, motorcycle (MC) or car and motorcycle owner, see table 1. The categories are mutually exclusive so that each person only falls in one category. As table 1 shows, the number of persons who own a motorcycle or both a car and a motorcycle is increasing much more over the period than the group of car owners.

In order to highlight the differences between accidents according to the age of the pedestrian involved, and therefore the characteristics of accidents involving elderly pedestrians, 358 of those reports involve at least one elderly pedestrian (65 years old and over), and the other 422 involve younger pedestrians. Moreover, these reports were selected according to the accident circumstances (Figure 3). 3. Study of How Elderly Pedestrians in Paris Perceive Risk This quantitative step of the study focuses on crossing the street, in order to better understand the process of decision-making of elderly pedestrians when crossing, to identify the environmental factors of strain components and fears and what the level of awareness of road safety is for the elderly pedestrian.

In a couple w. Children Income vs. income+1000 Education vs. education+1 2002 2,86 (2,223,68) 2,60 (2,043,31) 1,39 (1,201,62) 0,97 (0,970,97) 1,67 (1,421,93) 1,59 (1,132,23) 1,08 (0,911,28) 0,99 (0,980,99) 0,95 (0,930,97) 2003 3,16 (2,553,91) 2,71 (2,213,31) 1,44 (1,271,64) 0,97 (0,960,97) 1,86 (1,632,13) 2,25 (1,742,92) 1,19 (1,021,38) 0,99 (0,991,00) 0,95 (0,940,97) 2004 2,29 (1,782,95) 2,04 (1,622,56) 1,43 (1,251,64) 0,96 (0,960,97) 1,61 (1,401,84) 1,82 (1,392,39) 1,01 (0,871,18) 0,99 (0,991,00) 0,94 (0,920,95) 2005 2,69 (2,103,45) 2,56 (2,073,17) 1,42 (1,231,63) 0,96 (0,960,97) 1,77 (1,532,05) 1,92 (1,442,56) 1,13 (0,961,33) 0,99 (0,991,00) 0,93 (0,910,94) 2006 3,05 (2,423,84) 2,56 (2,093,13) 1,37 (1,191,58) 0,97 (0,960,97) 1,53 (1,321,76) 1,50 (1,122,02) 1,05 (0,901,23) 1,00 (0,991,00) 0,93 (0,910,95) 2007 3,09 (2,473,86) 2,22 (1,802,73) 1,42 (1,231,64) 0,96 (0,960,97) 1,50 (1,301,74) 1,76 (1,332,32) 0,95 (0,801,12) 1,00 (0,991,00) 0,90 (0,880,93) Quantifying the Influence of Social Characteristics on Accident and Injury Risk 43 DISCUSSION AND CONCLUSION It is evident from the results that the risk of motorcyclists being involved in an accident and getting injured in an accident was higher compared to car drivers.

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