Risky Driving: Relationship Between Cellular Phone and Safety Belt Use

2003 ◽  
Vol 1843 (1) ◽  
pp. 20-23 ◽  
Author(s):  
David W. Eby ◽  
Lidia P. Kostyniuk ◽  
Jonathon M. Vivoda
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Motor Vehicle ◽  
Cellular Phone ◽  
Motor Vehicle Crash ◽  
Public Health Issue ◽  
Cellular Phones ◽  
Safety Belt ◽  
Phone User

The main purpose of the study was to explore the relationship between cellular phone and safety belt use. Rates of safety belt use of drivers using and drivers not using handheld cellular phones were compared. All data for safety belt and handheld cellular phone use were collected through direct observation while vehicles were stopped at intersections and freeway exit ramps in Michigan. Data were weighted to be representative of drivers during daylight hours in Michigan. Analyses included statistical comparisons of safety belt use rates and a logistic regression model to determine the effects of handheld cellular phone use on safety belt use. The study found that safety belt use for drivers using a handheld cellular phone was significantly lower than for drivers not using cellular phones. This same significant relationship was found within nearly all demographic categories analyzed. The logistic regression model showed that the odds of a handheld cellular phone user not using a safety belt were 1.77 times that of a driver not using a cellular phone. These results stress the importance of the public health issue posed by cellular phone use; not only are those who are conversing on cellular phones potentially more likely to be in a motor vehicle crash, they are also more likely to sustain greater injury because of the lack of safety belt use.

scholarly journals Factors Contributing to Police Attendance at Motor Vehicle Crash Scenes

2014 ◽  
Author(s):  
Richard Tay ◽  
Lina Kattan ◽  
Yuan Bai
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Logistic Regression Model ◽  
Motor Vehicle ◽  
Motor Vehicle Crash ◽  
Crash Data ◽  
Police Services ◽  
Vehicle Crash ◽  
Secondary Crashes ◽  
The City

Police attendance at a motor vehicle crash scene is important for investigating the causes of crashes, reducing secondary crashes, managing traffic, and reducing congestion. However, very little research has been conducted to examine the factors contributing to the likelihood of police attendance. This study hypothesizes that the policies of the police services concerned, convenience and comfort, and expectations of injuries or driver violations will increase the likelihood of police attendance at a crash scene. This conceptual framework is supported by the results from fitting a logistic regression model to crash data from the City of Calgary in Alberta, Canada.

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 Work absence and multimorbidity in Portugal: results from the 1st National Health Examination Survey

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
J Matos ◽  
C Matias Dias ◽  
A Félix
Keyword(s):  
Logistic Regression ◽  
Regression Model ◽  
Chronic Diseases ◽  
National Health ◽  
Logistic Regression Model ◽  
Health Examination ◽  
Work Absence ◽  
Health Examination Survey ◽  
Absence From Work ◽  
The Impact

Abstract Background Studies on the impact of patients with multimorbidity in the absence of work indicate that the number and type of chronic diseases may increase absenteeism and that the risk of absence from work is higher in people with two or more chronic diseases. This study analyzed the association between multimorbidity and greater frequency and duration of work absence in the portuguese population between the ages of 25 and 65 during 2015. Methods This is an epidemiological, observational, cross-sectional study with an analytical component that has its source of information from the 1st National Health Examination Survey. The study analyzed univariate, bivariate and multivariate variables under study. A multivariate logistic regression model was constructed. Results The prevalence of absenteeism was 55,1%. Education showed an association with absence of work (p = 0,0157), as well as professional activity (p = 0,0086). It wasn't possible to verify association between the presence of chronic diseases (p = 0,9358) or the presence of multimorbidity (p = 0,4309) with absence of work. The prevalence of multimorbidity was 31,8%. There was association between age (p < 0,0001), education (p < 0,001) and yield (p = 0,0009) and multimorbidity. There is no increase in the number of days of absence from work due to the increase in the number of chronic diseases. In the optimized logistic regression model the only variables that demonstrated association with the variable labor absence were age (p = 0,0391) and education (0,0089). Conclusions The scientific evidence generated will contribute to the current discussion on the need for the health and social security system to develop policies to patients with multimorbidity. Key messages The prevalence of absenteeism and multimorbidity in Portugal was respectively 55,1% and 31,8%. In the optimized model age and education demonstrated association with the variable labor absence.

Sign in / Sign up

Export Citation Format

Share Document