An investigation into the relationships between area social characteristics and road accident casualties

Abdalla, Ibrahim; Raeside, Robert; Barker, D; McGuigan, D

doi:10.1016/s0001-4575(97)00011-0

Cited by 75 publications

(35 citation statements)

References 4 publications

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“…The finding that areas with higher levels of social deprivation have relatively higher casualty rates is also consistent with other findings (Abdalla et al, 1997), although this effect is less strong when only motorized casualties are considered. It is unclear what residual factor associated with more deprived areas may be leading to increased casualty rates from traffic flowing through those areas.…”

Section: Discussionsupporting

confidence: 90%

“…We also find a positive association with increased fatalities but only at the 90% level of significance. This is consistent with the results of Abdalla et al (1997), Chichester et al (1998) and Beattie et al (2001) who also found that there is a positive correlation between area deprivation and traffic casualties. However, our results are less convincing when we look at only motorized casualties.…”

Section: Demographic Characteristicssupporting

confidence: 92%

“…In our study we control for the social deprivation of geographic areas and the road traffic accidents that occur in those areas. Abdalla al (1997) examined the relationship between area social characteristics and road accident casualties. Initially, consideration was given to the relationship between casualty frequencies and the distance of the accidents from the zones of residence.…”

Section: Literature Reviewmentioning

confidence: 99%

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A spatially disaggregate analysis of road casualties in England

Noland

Quddus

2004

Accident Analysis & Prevention

231

128

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A Spatially Disaggregate Analysis of Road Casualties in England AbstractSpatially disaggregate ward level data for England is used in an analysis of various area-wide factors on road casualties. Data on 8414 wards was input into a geographic information system that contained data on land use types, road characteristics and road casualties. Demographic data on area-wide deprivation (the index of multiple deprivation) for each ward was also included.Negative binomial count data models were used to analyze the associations between these factors with traffic fatalities, serious injuries and slight injuries. Results suggest that urbanized areas are associated with fewer casualties (especially fatalities) while areas of higher employment density are associated with more casualties. More deprived areas tend to have higher levels of casualties, though not of motorized casualties (except slight injuries). The effect of road characteristics are less significant but there are some positive associations with the density of "A" and "B" level roads.

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Section: Discussionsupporting

confidence: 90%

Section: Demographic Characteristicssupporting

confidence: 92%

Section: Literature Reviewmentioning

confidence: 99%

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A spatially disaggregate analysis of road casualties in England

Noland

Quddus

2004

Accident Analysis & Prevention

231

128

View full text Add to dashboard Cite

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“…This level is sufficiently fine to measure the risks run by the resident populations (Abdalla et al, 1997;Edwards et al, 2006) on the relevant urban area levels.…”

Section: Data Availabilitymentioning

confidence: 99%

“…More generally, accident rates in relation to the population are higher in the most deprived neighbourhoods. For example, Abdalla et al (1997) show that the traffic injury accident rate (per 10000 inhabitants) among the residents of the 15% most deprived areas is nearly twice as high as for the residents of the 15% most affluent areas, in the former Lothian region of Scotland. Edwards et al (2006) show that the pedestrian injury accident rate among the residents of the 10% most deprived areas of London is nearly three times as high as for the residents of the 10% least deprived areas.…”

Section: Introductionmentioning

confidence: 99%

Excess accident risk among residents of deprived areas

Fleury¹,

Peytavin²,

Alam³

et al. 2010

Accident Analysis & Prevention

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This study examines road risks among residents of deprived neighbourhoods targeted by social policy compared with residents of other contiguous neighbourhoods that are socially more privileged. The data used are from accident reports filled in by the police. When these data are brought to the level of the population in the areas studied, the adjusted relative risk for those living in sensitive urban areas compared with those living in other areas is assessed at 1.366 (with a 95% confidence interval from 1.240 to 1.502). Distributions by age and gender are then studied. In the discussion, several hypotheses concerning behaviour, mobility and socio-spatial factors are discussed.

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Severity analysis of powered two wheeler traffic accidents in Uttarakhand, India

Kumar

Toshniwal

2017

Eur. Transp. Res. Rev.

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Objective Powered Two Wheeler (PTW) vehicles are one of the preferred modes of transport used in India. Also, PTWs accidents are comparatively more frequent than other type of accidents on road. The influencing factors of PTW accidents are also differ from factors that affect other accident types. The objective of this study is to analyze newly available PTWs road accident data from Uttarakhand state in India and revealing the factors that affect the severity of these accidents in various districts of Uttarakhand.. Methodology To analyze the factors that affect the severity of road accidents in Uttarakhand, initially we have compared three popular classification algorithms i.e. decision tree (CART), Naïve Bayes and Support vector machine on PTW accident data set. The decision tree algorithm's (CART) classification accuracy was found better than other two techniques. Hence we have preferred CART algorithm to extract the factors that affect the severity of PTWVs accidents in whole Uttarakhand state and its 13 districts separately. Experimental Results The analysis of PTWVs accident data using CART for 13 districts of Uttarakhand and the whole state reveals that every districts have different factors associated with PTW accidents severity. There are some districts in Uttarakhand state which have similar PTW accident patterns, whereas few districts are found to have different PTW accident patterns. These results are very useful to understand the pattern of PTW accidents in Uttarakhand state. These results can certainly be helpful to overcome the PTWs accident rate in Uttarakhand state.

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An investigation into the relationships between area social characteristics and road accident casualties

Cited by 75 publications

References 4 publications

A spatially disaggregate analysis of road casualties in England

A spatially disaggregate analysis of road casualties in England

Excess accident risk among residents of deprived areas

Severity analysis of powered two wheeler traffic accidents in Uttarakhand, India

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