| Background:Globally deaths and injuries resulting from road traffic crashes have emerged as an important public health concern. Road traffic injuries involving agricultural vehicle, in particular, should not be ignored. In developed countries, although the total incidence rate of road traffic injuries involving all kinds of vehicles has decreased in last decades, the incidence rate of agricultural vehicle traffic accident remains in a stable level. The number of agricultural vehicles has increased more rapidly from 14.76 million in 2003 to more than 22.79 million in 2013 in China according to the official statistics. Strong evidences have been presented to demonstrate that the agricultural vehicle could cause more death and serious injuries. It should be recognized that agriculture-vehicle-involved roadway crashes posed a constant threat to traffic safety. However, little research has been carried out on the field of agricultural vehicle collisions in China. Most of the researches abroad were simple descriptive epidemiological analysis based on monitoring data. Meanwhile, the role of agricultural vehicles in the total traffic safety problem is somewhat hidden because most national statistics, including China, do not explicitly report road collision involved agricultural vehicle but include them within a general category of "other vehicles". As a consequence, there are few well established studies which focus on influencing factors of agricultural vehicle crash based on epidemiological investigation. Therefore this study was designed by epidemiological survey to estimate the prevalence and characteristics of agricultural vehicle-related road crashes and to identify risk factors among agricultural vehicle drivers in southern China through cross-sectional study, structural equation model, case-crossover study and to put forward strategies and measures for the prevention of agricultural vehicle road crashes.Objectives:1. To assess the epidemiological features and determinants of agricultural vehicle road traffic injuries in China;2. To investigate the influencing factors of agricultural vehicle road traffic injuries by structural equation model tentatively;3. To provide comprehensive prevention strategies and effective measures for road traffic injuries involving agricultural vehicle.Methods:1. Cross-sectional study:The agricultural vehicle drivers of Yixing city were obtained with convenience sampling method. A questionnaire survey was adopted to collect information on general situation, health status, life situation, driving behavior, driving emotion and crash characteristics;2. Structural equation model:Using the data from the cross-sectional study, confirmatory factor analysis was used to construct measure model and then structural model was established based on theory, literature, rule of thumb and research purpose. Parameters and final model were fitted and revised by mean and variance-adjusted weighted least square. The final structural equation model was determined by comprehensive evaluation and necessary modification;3. Case-crossover study:A face to face interview was conducted to agricultural vehicle drivers using self-administered questionnaire in the agriculture machinery station of Yixing city. A 1:1 matching unidirectional case-crossover design was used to collect information on exposures during intervals just before the accident occurred and exposure in earlier control windows of analogous length;4. Strategies and measures:Several strategies and measures for the prevention of traffic injuries involved agricultural vehicle were developed based on research results, literature, "5E" injury prevention strategies and interviewing and communicating with agricultural vehicle drivers and staff of agriculture machinery station of Yixing city.Results:1. In the cross-sectional study, a total of 1422 effective questionnaires were obtained, valid respondent rate was 94.8%. The incidence rate of road traffic accident among the investigated agricultural vehicle drivers was 7.2%(103/1422). The results of multiple logistic regression analysis suggested that crash history (OR=2.90,95%CI:1.67-5.04), vision(OR=2.33,95%CI:1.22～4.43), sleep disorder(OR=2.03,95%CI:1.10～3.76), history of driving under the influence of alcohol(OR=5.96,95%CI:2.86～12.39), life stress(OR=3.38,95%CI:1.21～9.39), fatigued driving(OR=2.25,95%CI:1.28～3.95), driving anxiety(OR=2.05,95%CI:1.19～3.52) and driving anger(OR=1.95,95%CI:1.15～3.30) were predictors of agricultural vehicle road traffic accidents among agricultural vehicle drivers of Yixing city;2. The results of structural equation model suggested that driving behavior、driving emotion had direct effect on agricultural vehicle road traffic accident and the total effect were 0.230、0.658 respectively. Personal characteristics had indirect effect on traffic crash through driving behavior while physical and psychological status had indirect effect traffic crash through driving behavior and driving emotion. The total effect of personal characteristics and physical and psychological status were-0.066、0.708 respectively;3. As the results of case-crossover study indicated, transient factors that were associated with agricultural vehicle road traffic collision would include irritation/anxiety (OR=24.63,95%CI: 3.10～195.60), driving distraction (OR=9.37,95%CI:2.35～37.41), improper operation (OR=20.74, 95%CI:2.82～152.70), violating traffic signal、traffic signs、traffic markings when driving (OR=12.53,95%CI:2.94-53.47).Conclusions:1. The prevalence of agricultural vehicle road traffic accident in Yixing was still high, Effective measures on the prevention and control of agricultural vehicle road traffic accidents should be emphasized;2. Crash history, vision, sleep disorder, history of driving under the influence of alcohol, life stress, fatigued driving, driving anxiety and driving anger have all been reported as major determinants of agricultural vehicle road traffic accident. Transient factors as irritation/anxiety, driving distraction, improper operation, violating traffic signal、traffic signs、traffic markings when driving have been demonstrated to increase the probability of crash involvement;3. Structural equation modeling showed more advantages than traditional statistical methods and can provide guidance for analyzing the factors contributing to the occurrence of agricultural vehicle road crash. However, a modified research is needed to study in depth. |
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