Survival hazards of road environment factors between motor-vehicles and motorcycles.
Motorcycles are frequently used in middle- and low-income societies. They are often involved in crashes, and account for a noticeable percentage of fatalities secondary to crashes. Comparing motor-vehicle occupants and motorcycle riders, the present study examined the survival hazard of crash injuries with respect to road environmental factors (i.e., area, road type, and location). We investigated the effects of such factors on survival and survival time after crashes via a binary logistic regression analysis and a Cox proportional hazard regression analysis, respectively. Results indicated that, for both motor-vehicle occupants and motorcycle riders, the fatal prevalence, occurrence likelihood, and risk based on time were decreased in urban areas and elevated on highways. The three indexes were also higher for motor-vehicle occupants on non-straight or non-level roadway sections. The prevalence of death on local roads and at intersections was relatively higher for motorcycle riders compared to motor-vehicle occupants. Speed may contribute to the survival hazard with respect to road environment factors. Speed management initiatives account for hazardous roadway, curve alignment re-examination, and increased traffic enforcement density are suggested. Collaboration among the roadway authorities, vehicle industry, and medical systems for a timely rescue is also advised. In addition, the attention to crashes at intersections and on local roads is a promising intervention for motorcycle riders.
Li
Ming-Der
MD
Department of Mechanical Engineering, National Central University, Jhongli City, Taoyuan 320, Taiwan, ROC.
Doong
Ji-Liang
JL
Huang
Wei-Shin
WS
Lai
Ching-Huei
CH
Jeng
Ming-Chang
MC
D000063:Accidents, Traffic / Q000401:mortality* / Q000706:statistics & numerical data; D000293:Adolescent; D000328:Adult; D000368:Aged; D001334:Automobile Driving / Q000706:statistics & numerical data*; D001336:Automobiles / Q000706:statistics & numerical data*; D016001:Confidence Intervals; D004777:Environment; D005260:Female; D006306:Health Surveys; D006801:Humans; D053208:Kaplan-Meier Estimate; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D009049:Motorcycles / Q000706:statistics & numerical data*; D016017:Odds Ratio; D016016:Proportional Hazards Models; D012044:Regression Analysis; D012307:Risk Factors; D012309:Risk-Taking; D013624:Taiwan; D055815:Young Adult