کاربرد مدل آمیخته رشد پنهان در تحلیل نرخ مرگ و میر حوادث ترافیکی سراسر جهان، 2007 تا 2013

Background: Road Traffic Accidents (RTA) is a major public health problem in the world. The RTAs patterns are different in various countries which require taking specific approach es and strategies. The purpose of this study was to use Growth Mixture Model (GMM) to study the pattern of RTAs death rate worldwide. Methods: In this longitudinal study, RTAs death rate data of 193 countries from 2007, 2010 and 2013 were extracted from the World Health Organization reports. In order to investigate the RTAs growth trajectory, linear and nonlinear Latent Growth Models (LGM) were used and compared to each other. Finally, the GMM was fitted to identify and classify countries based on RTAs death rate patterns. Statistical analyses were conducted by Mplus 6.12. Results: The nonlinear LGM fitted better than the linear model. According to nonlinear model, the estimated RTAs rate trend was downward in the first three years and then the rate changed to upward. By using GMM, seven subgroups with different RTAs death rate patterns were determined. Conclusion: From 2007 to 2013, the RTAs death rate in the world started to decline and then increased. Based on death rate growth trajectories, world countries classified into seven subgroups with various patterns. Therefore, in order to reduce RTAs death rate in the world different approaches need to be considered for each subgroup.