Predictors of fatal outcomes in pedestrian accidents in Tabriz Metropolis of Iran: Application of PLS-DA method

Predictors of fatal outcomes in pedestrian accidents in Tabriz Metropolis of Iran: Application of PLS-DA method


چاپ صفحه
پژوهان
صفحه نخست سامانه
چکیده مقاله
چکیده مقاله
نویسندگان
نویسندگان
دانلود مقاله
دانلود مقاله
دانشگاه علوم پزشکی تبریز
دانشگاه علوم پزشکی تبریز

نویسندگان: همایون صادقی بازرگانی , میلاد جمالی دولت آباد , پروین سربخش

کلمات کلیدی: Pedestrian; PLS-DA; road traffic deaths; multicollinearity; Tabriz Metropolis

نشریه: 33726 , 20 , 7 , 2019

اطلاعات کلی مقاله
hide/show

نویسنده ثبت کننده مقاله پروین سربخش
مرحله جاری مقاله تایید نهایی
دانشکده/مرکز مربوطه مرکز مدیریت و پیشگیری از مصدومیتهای حوادث ترافیکی
کد مقاله 69788
عنوان فارسی مقاله Predictors of fatal outcomes in pedestrian accidents in Tabriz Metropolis of Iran: Application of PLS-DA method
عنوان لاتین مقاله Predictors of fatal outcomes in pedestrian accidents in Tabriz Metropolis of Iran: Application of PLS-DA method
ناشر 3
آیا مقاله از طرح تحقیقاتی و یا منتورشیپ استخراج شده است؟ بلی
عنوان نشریه (خارج از لیست فوق)
نوع مقاله Original Article
نحوه ایندکس شدن مقاله ایندکس شده سطح یک – ISI - Web of Science
آدرس لینک مقاله/ همایش در شبکه اینترنت

خلاصه مقاله
hide/show

ABSTRACT Objectives: Road traffic deaths in walking pedestrians are a global public health problem. Considering that in Iran pedestrians have a high proportion of deaths caused by traffic accidents, the objective of the present study was to investigate mortality rate and related factors of fatal injury in pedestrian crashes in Tabriz Metropolis of Iran as the largest and most populous city of the northwestof Iran. Methods: The design of this study is case-control based on police and Forensic Medicine Organization data. All registered fatal pedestrian crashes in Tabriz Metropolis from 2014 to 2015 (146 cases) were included in the study as the case group. Also, 292 pedestrians (the ratio of cases to controls was 1:2) with non-fatal crashes were considered as the control group. Due to high dimensional data and multicollinearity issue, Partial least squares discriminant analysis (PLS-DA) was used for data analysis. Importance of the variables was determined by the VIP (Variable Importance in the Projection) index. Performance of the model was assessed by using training and test set validation method. The area under the ROC curve (AUC) and classification error rates were calculated for the test set. R software version 3.5.1 (mixOmcs packages) was used for data analysis. Results: According to the results of PLS-DA, the most important variables related to fatal outcome in pedestrian crashes with VIP > 1 were: pedestrian age (positive effect), type of vehicle (light machinery with a negative effect), kind of vehicle plate (private plate with a negative effect), season of accident occurrence (winter season with a positive effect), type of driver’s licenses (Class A with a positive effect), pedestrian gender (male with a positive effect) and Fault of Pedestrian (At-fault with a positive effect). The overall accuracy for the fitted model and AUC were 0.77 and 0.79, respectively. Conclusions: The results show that predictors of a fatal outcome in pedestrian accidents in Tabriz can be attributed to the pedestrian characteristics (which notably account for differences in vulnerability in case of an accident), the car and driver features, and weather (which may all notably influence the amount of energy involved in the collision, through the car mass, speed, and conditions delaying the braking response or reducing the braking effectiveness). Regarding the statistical method, the PLS-DA is a powerful method which can be used to analyze high dimension data with multicollinearity issue.

نویسندگان
hide/show

نویسنده نفر چندم مقاله
همایون صادقی بازرگانیدوم
میلاد جمالی دولت آباداول
پروین سربخشسوم

لینک دانلود مقاله
hide/show

نام فایل تاریخ درج فایل اندازه فایل دانلود
Predictors of fatal outcomes in pedestrian accidents in Tabriz Metropolis of Iran Application of PLS DA method.pdf1398/08/221316528دانلود