scholarly journals Cycling injuries in London: the impact of motor vehicle and cycle volumes, and road characteristics including speed limits

2018 ◽  
Author(s):  
Rachel Aldred ◽  
Anna Goodman ◽  
John Gulliver ◽  
James Woodcock
Keyword(s):  
Injury Risk ◽  
Motor Vehicle ◽  
Binary Logistic Regression ◽  
Flow Data ◽  
Binary Logistic Regression Model ◽  
Speed Limits ◽  
Route Network ◽  
Logarithmic Unit ◽  
Safety In Numbers ◽  
The Impact

Cycling injury risk is an important topic, but few studies explore cycling risk in relation to exposure. This is largely because of a lack of exposure data, in other words how much cycling is done at different locations. This paper helps to fill this gap. It reports a case-control study of cycling injuries in London in 2013-2014, using modelled cyclist flow data alongside datasets covering some characteristics of the London route network. A multilevel binary logistic regression model is used to investigate factors associated with injury risk, comparing injury sites with control sites selected using the modelled flow data. Findings provide support for ‘safety in numbers’: for each increase of a natural logarithmic unit (2.71828) in cycling flows, an 18% decrease in injury odds was found. Conversely, increased motor traffic volume is associated with higher odds of cycling injury, with one logarithmic unit increase associated with a 31% increase in injury odds. Twenty-mile per hour compared with 30mph speed limits were associated with 21% lower injury odds. Residential streets were associated with reduced injury odds, and junctions with substantially higher injury odds. Bus lanes do not affect injury odds once other factors are controlled for. These data suggest that speed limits of 20mph may reduce cycling injury risk, as may motor traffic reduction. Further, building cycle routes that generate new cycle trips should generate ‘safety in numbers’ benefits.

Presence of Additional Safety Belt Enforcement Increases Safety Belt Use by Drivers

2020 ◽  
Vol 2674 (3) ◽  
pp. 93-99
Author(s):  
Lusanni Acosta-Rodriguez ◽  
Valerian Kwigizile ◽  
Jun-Seok Oh ◽  
Timothy Gates
Keyword(s):  
Motor Vehicle ◽  
Geographical Location ◽  
Binary Logistic Regression ◽  
Influential Factors ◽  
Binary Logistic Regression Analysis ◽  
Traffic Enforcement ◽  
Safety Belt ◽  
Primary Means ◽  
The Impact ◽  
Additional Safety

The use of a safety belt is universally recognized as a primary means of reducing injuries and fatalities for motor vehicle occupants. There are several factors that contribute to safety belt utilization, including traffic enforcement, demographics, vehicle type, day of the week, and geographical location. These factors have been explored and found significant in relation to safety belt usage. Apart from these factors, the presence of additional traffic enforcement is generally believed to produce higher rates of safety belt use. However, the impacts provided by the presence/no-presence of additional traffic enforcement have been merely quantified on a disaggregated scale, broadly across an entire state while controlling for other influential factors. Thus, this paper presents an analysis that quantifies the impacts provided by the presence of additional safety belt enforcement on driver safety belt usage. Direct safety belt use observational surveys and traffic enforcement data were used for the analysis. Owing to the nature of the data, a binary logistic regression analysis was performed on the dataset from the state of Michigan. The results showed that for every location where additional traffic enforcement was present, safety belt usage increased by 6.4% per county compared with areas where no additional traffic enforcement was present. Finally, the results not only quantified the impact of traffic enforcement on safety belt use, but could help transportation safety agencies make more informed decisions about where additional safety belt enforcement may be needed to improve rates of safety belt use.

scholarly journals Modeling and Analyzing the Factors Affecting the Mortality of Pedestrians in Urban Accidents

2018 ◽  
Vol 14 (4) ◽  
pp. 10-21
Author(s):  
Ahmet Tortum ◽  
Alireza Motamadnia
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Motor Vehicle ◽  
Binary Logistic Regression ◽  
Education Level ◽  
Road Surface ◽  
Binary Logistic Regression Model ◽  
Factors Affecting ◽  
Surface Conditions

Abstract The nature of urban and rural accidents has been different from each other in some of the factors and even the severity of damage rate, mayhem, and death. In this research, using statistical methods and binary logistic regression model, we have addressed to analyze important parameters such as age, gender, education level, the color of the pedestrian dress, season of accident, time of accident, the speed of the vehicle colliding with pedestrians and road surface conditions at the time of accident on the way of death (at the scene of the incident or in the hospital) pedestrians who have been traumatized. After the creation of the binary logistic regression model, it was determined that only the parameters of speed and the accident time have been significant in the level less than 5%. And other parameters such as age, gender, the season of accident occurrence, the color of the pedestrian dress, road surface conditions and education level had no significant effect in terms of statistical on the incidence of mortality arising from a pedestrian accident with the motor vehicle. The results revealed that by adopting decisions related to the traffic calming, attention to passages lighting and brightness the mortality rate of a pedestrian due to the urban accidents can be reduced.

scholarly journals The Impact of International Remittances on Poverty Alleviation in Bangladesh

2019 ◽  
Vol 4 (1) ◽  
pp. 67-86 ◽  
Author(s):  
Bezon Kumar
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Poverty Alleviation ◽  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Primary Data ◽  
Binary Logistic Regression Model ◽  
Household Poverty ◽  
International Remittances ◽  
The Impact

This article mainly explores to what extent international remittances alleviate household poverty in Bangladesh. This study uses primary data collected from 216 households and employs multi-methods. Firstly, I measure the level of household poverty through Foster-Greer-Thorbecke index. The article secondly focuses on the impact of remittances on household poverty using a binary logistic regression model. I found that the level of poverty among remittance recipient households is notably lower than households that are not receiving remittances. Similarly, the probability of a household being poor is alleviated by 28.07 per cent if the household receives remittance. It can be suggested that nursing international remittances can be useful for poverty alleviation in Bangladesh. 

The impact of employee participation in online innovation communities on idea quality

Kybernetes ◽  
2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jing Yu ◽  
Chen Liu
Keyword(s):  
New Product Development ◽  
Idea Generation ◽  
Binary Logistic Regression ◽  
Positive Influence ◽  
User Innovation ◽  
Binary Logistic Regression Model ◽  
Content Type ◽  
Idea Quality ◽  
The Impact ◽  
Innovation Community

Purpose Online user innovation community (OUIC) has become a vital source for enterprises to obtain user innovation ideas and interact with users in new product development. However, most studies only focus on the relationship between users and ideas, often ignoring the influence of employees in the innovation platform. The purpose of this study is to explore the impact of employee behaviors on idea quality in OUIC. Design/methodology/approach In this paper, the authors collected sample data of open user innovation community – Idea Exchange – and then, the authors examined the direct roles of employee’s idea generation behaviors and idea promotion behaviors on idea quality and the moderating roles of social networks position and enthusiasm by using binary logistic regression model. Findings Results indicated that employee’s idea generation behaviors and idea promotion behaviors have a positive influence on users’ idea quality. Also, the social network position and characteristics show the moderation effect of employee behavior and idea quality. Originality/value This study is different from prior studies because it emphasizes the role of employees in the open source platform. The findings suggest that enterprises and platform managers pay more attention to the impact of employees and improve the quality of ideas and promote the development of OUIC.

scholarly journals Neurocritical care complications and interventions influence the outcome in aneurysmal subarachnoid hemorrhage

BMC Neurology ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Alexander Hammer ◽  
Frank Erbguth ◽  
Matthias Hohenhaus ◽  
Christian M. Hammer ◽  
Hannes Lücking ◽  
...  
Keyword(s):  
Subarachnoid Hemorrhage ◽  
Decompressive Craniectomy ◽  
Odds Ratio ◽  
Neurocritical Care ◽  
Aneurysmal Subarachnoid Hemorrhage ◽  
Binary Logistic Regression ◽  
World Federation ◽  
Binary Logistic Regression Model ◽  
One Year ◽  
The Impact

Abstract Background This observational study was performed to show the impact of complications and interventions during neurocritical care on the outcome after aneurysmal subarachnoid hemorrhage (SAH). Methods We analyzed 203 cases treated for ruptured intracranial aneurysms, which were classified regarding clinical outcome after one year according to the modified Rankin Scale (mRS). We reviewed the data with reference to the occurrence of typical complications and interventions in neurocritical care units. Results Decompressive craniectomy (odds ratio 21.77 / 6.17 ; p < 0.0001 / p = 0.013), sepsis (odds ratio 14.67 / 6.08 ; p = 0.037 / 0.033) and hydrocephalus (odds ratio 3.71 / 6.46 ; p = 0.010 / 0.00095) were significant predictors for poor outcome and death after one year beside “World Federation of Neurosurgical Societies” (WFNS) grade (odds ratio 3.86 / 4.67 ; p < 0.0001 / p < 0.0001) and age (odds ratio 1.06 / 1.10 ; p = 0.0030 / p < 0.0001) in our multivariate analysis (binary logistic regression model). Conclusions In summary, decompressive craniectomy, sepsis and hydrocephalus significantly influence the outcome and occurrence of death after aneurysmal SAH.

scholarly journals Socio-economic Causes of Malnutrition among Pre-School Children in Pakistan: A Gender-Disaggregated Analysis

2020 ◽  
Vol V (II) ◽  
pp. 47-59
Author(s):  
Muhammad Shahid ◽  
Madeeha Gouhar Qureshi ◽  
Jam Farooq Ahmed
Keyword(s):  
Logistic Regression Model ◽  
Binary Logistic Regression ◽  
Child Malnutrition ◽  
Urban Place ◽  
Binary Logistic Regression Model ◽  
Male And Female ◽  
Female Children ◽  
Working Status ◽  
The Impact ◽  
Common Perception

The most common perception is that the prevalence of malnutrition among females is higher than males. To solve this dilemma, the present article analyzes the impact of socioeconomic factors on the nutritional status of under-five children by gender using a binary logistic regression model. Utilizing the Pakistan Demographic and Health Survey [PDHS]-2013 data, a CIAF index is constructed to measure child malnutrition. The disaggregation analysis illustrates that the working status of mothers, mothers not having ownership of assets, women not involved in income decisions, and urban place of residence are found major contributors in male child malnutrition. However, factors such as higher birth order and diarrhea contribute to malnutrition in female children. The study concludes that both male and female children have a higher probability of being malnourished, but effects have been found more in male children in disaggregated analysis than female counterparts.

scholarly journals Four biomechanical and anthropometric measures predict tibial stress fracture: a prospective study of 1065 Royal Marines

2016 ◽  
Vol 50 (19) ◽  
pp. 1206-1210 ◽  
Author(s):  
Michael Nunns ◽  
Carol House ◽  
Hannah Rice ◽  
Mohammod Mostazir ◽  
Trish Davey ◽  
...  
Keyword(s):  
Stress Fracture ◽  
Lower Limb ◽  
Injury Risk ◽  
Three Dimensional ◽  
Binary Logistic Regression ◽  
Tibial Rotation ◽  
Binary Logistic Regression Model ◽  
Anthropometric Measures ◽  
Tibial Stress Fracture ◽  
Increased Risk

BackgroundTibial stress fractures (TSFs) cause a significant burden to Royal Marines recruits. No prospective running gait analyses have previously been performed in military settings.AimWe aimed to identify biomechanical gait factors and anthropometric variables associated with increased risk of TSF.Methods1065 Royal Marines recruits were assessed in week 2 of training. Bilateral plantar pressure and three-dimensional lower limb kinematics were obtained for barefoot running at 3.6 m/s, providing dynamic arch index, peak heel pressure and lower limb joint angles. Age, bimalleolar breadth, calf girth, passive hip internal/external range of motion and body mass index (BMI) were also recorded. 10 recruits who sustained a TSF during training were compared with 120 recruits who completed training injury-free using a binary logistic regression model to identify injury risk factors.Results4 variables significantly (p<0.05) predicted increased risk of TSF (ORs and 95% CI): smaller bimalleolar width (0.73, 0.58 to 0.93), lower BMI (0.56, 0.33 to 0.95), greater peak heel pressure (1.25, 1.07 to 1.46) and lower range of tibial rotation (0.78, 0.63 to 0.96).SummaryReduced impact attenuation and ability to withstand load were implicated in tibial stress fracture risk.

Crash momentum index and closing velocity as crash severity index

2019 ◽  
Vol 233 (13) ◽  
pp. 3318-3326 ◽  
Author(s):  
Dario Vangi ◽  
Michelangelo-Santo Gulino ◽  
Anita Fiorentino ◽  
Antonio Virga
Keyword(s):  
Injury Risk ◽  
Principal Direction ◽  
A Priori ◽  
Binary Logistic Regression ◽  
Severity Index ◽  
Crash Severity ◽  
Driver Assistance Systems ◽  
Velocity Change ◽  
Application Fields ◽  
The Impact

The velocity change Δ V of a vehicle subject to a collision, widely recognized as an efficient crash severity indicator, is a typical ‘a posteriori’ parameter, not generally known until the crash phase has been reconstructed. Δ V is the result of a combination of factors, regarding the impact velocities of the colliding vehicles and the geometry of the impact (as eccentricity, etc.): for this reason, its value alone gives no clear indications on the actions which can be undertaken to reduce crash severity. This feature is particularly critical in some application fields, for example, in case of advanced driver assistance systems assessment in different accident scenarios. This work proposes the disaggregation of Δ V into two different ‘a priori’ parameters to assess crash severity of an impact before its occurrence: the crash momentum index, representing the impact configuration, and the closing velocity projected along the principal direction of force ( Vr_pdof), as an index of the kinetic energy exchanged between the two vehicles. It is preliminarily shown how the proposed parameters can be calculated using established procedures – as momentum-based analysis – in a predictive (‘a priori’) approach. It is also evidenced how crash momentum index, Vr_pdof and the velocity change Δ V are in relation. To illustrate the procedure by means of examples, binary logistic regression on accident data is applied to correlate crash momentum index and Δ V to injury risk at Maximum Abbreviated Injury Scale level higher than 2. The use of crash momentum index as an additional severity index allows an improved correlation with injury risk, for the dataset used, in case of front and near side impacts. The use of the plane Vr_pdof– crash momentum index, on which curves at constant injury risk are drawn, provides clear indications on the possible strategies to reduce injury risk, as shown by generic examples to which the predictive procedure is applied.

Does the Presence of a Physical Disability Affect Classification of Sexual Assault?

2021 ◽  
pp. 088626052199795
Author(s):  
Alec Dalton ◽  
Dayna Henry ◽  
Sarah Blackstone ◽  
Julia Passuth ◽  
Haley Birchfield ◽  
...  
Keyword(s):  
Sexual Assault ◽  
Physical Disability ◽  
Online Survey ◽  
Statistical Significance ◽  
Binary Logistic Regression ◽  
Binary Logistic Regression Model ◽  
Clear Trend ◽  
Disability Status ◽  
The Impact

The occurrence of sexual assault is common and problematic, especially among those with disabilities. While many other characteristics of the victim, perpetrator, and situation involving a sexual assault have been shown to affect perceptions, only one study has examined the impact of a hypothetical victim with a physical disability. Therefore, the purpose of this study was to explore the effect that a victim and/or perpetrator’s physical disability status has on individuals’ classification of encounters as sexual assault. University students over the age of 18 ( n = 207) completed an anonymous online survey which included reading an ambiguous scenario involving a sexual assault in which either the victim, perpetrator or neither was in a wheelchair. Participants classified the scenario as either representing a sexual assault or not and completed the Illinois Rape Myth Acceptance scale and demographic information. A binary logistic regression model was conducted to examine the effects of conditions, participant gender and RMA score on sexual assault classification. In the scenario with the victim in a wheelchair, 71.6% of participants agreed sexual assault occurred; when the perpetrator was in a wheelchair 58.6% classified the scenario as sexual assault. In the control condition 61.4% agreed sexual assault occurred. Condition was not associated with classification at a statistically significant level; however, the effect sizes indicate participants were more likely to classify sexual assault when the victim was in a wheelchair (OR = 1.41), but less likely to blame a perpetrator in a wheelchair (OR = 0.69) compared to the control condition. Despite a lack of statistical significance, the data show a clear trend away from blaming individuals with disabilities in sexual assault scenarios. These findings can have implications within the legal system where incorrect decisions may be made due to bias based on disability status.

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