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

By Carlo Giacomo Prato

This ebook emerges from the curiosity in enriching the physique of data approximately coincidence features, interpreting healthiness results and presenting measures to beat societal and fiscal effects of injuries. Contributions from diversified disciplines compose a suite that gives solutions to favourite questions from numerous views. the 3 components of the booklet supply a finished assessment of the hot state-of-the-practice wisdom approximately twist of fate features, hazard elements, results and safeguard interventions. Combining wisdom from either highway and occupational defense, and increasing via numerous disciplines equivalent to engineering, economics, drugs, and statistics, this assortment stimulates readers in searching for more desirable recommendations to defense difficulties which are a big risk to human existence and price thousands to our society.

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Indeed, according to the analysis of the accident sheets (BAACC), they are more often victims when they cross with right of way, that is to say either on pedestrian-crossings with traffic lights, during their allotted time or on pedestrian-crossings without traffic lights. 2. Prototypical Accident Scenarios The results of the analysis of BAACC sheets are supported by the scripting of 780 police reports of road accidents involving at least one pedestrian. Elderly pedestrians, compared to younger ones (0-64 years), are over-represented in the families of prototypical accident scenarios "the pedestrian crosses on a pedestrian-crossing, equipped with traffic lights, during his allotted time" (P1) and " the pedestrian crosses on a pedestrian-crossing not equipped with traffic lights" (P4) and conversely, under-represented in the family "the pedestrian crosses on a pedestrian-crossing, equipped with traffic lights, outside his allotted time" (P2) (Table 1).

One important 44 Allan Lyckegaard, Morten N. Olesen and Tove Hels issue that has not been discussed in this chapter is exposure in terms of the yearly travelled distance. It is assumed that all individual owning a car or a motorcycle have the same exposure which is not the case. Unfortunately, yearly access to this kind of data is not easy on an individual level, although some data exist from vehicle inspections. To be able to develop a more precise model of the data, estimates for the yearly travelled distance on an individual level is needed.

2. Data Analysis The basis of the risk analysis is the logistic regression which is known from many epidemiologic studies. The purpose is to estimate a person’s probability pi of being in an accident or an accident with injury or fatality given a number of socio-demographic factors βvehicle, βgender, βage, βeducation, βincome and βfamily for each individual. The relationship between the probability pi and the socio-demographic factors β is modelled by logistic regression (Madsen and Thyregod, 2010):  p  log  i   β 0  β vehicle x vehicle  β gender x gender  β age x age    β family x family  1  pi  (1) With this model it is assumed that the underlying unobserved behaviour is equally distributed over both the categorical and the continuous variables.

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