Identifying developmental trajectories of worldwide road traffic accident death rates using a latent growth mixture modeling approach
Authors: Tofigh Mobaderi
Masoud Salehi
Mohammadreza Mehmandar
Afsaneh Dehnad
Journal: PLoS ONE (2019)
Discipline: Multidisciplinary
Keywords: Road Traffic Accidents; Mortality Rate Patterns; Growth Mixture Model; Clustering Countries; World Health Organization
Affiliations: Department of Biostatistics, Iran University of Medical Sciences, Tehran, Iran., Department of Traffic Operations, Amin Police University, Tehran Traffic Police, Tehran, Iran., Department of Foreign Languages, Iran University of Medical Sciences, Tehran, Iran.

Abstract:  Road Traffic Accidents (RTA) are a major worldwide public health problem. The aim of this study was to use the growth mixture model for clustering countries on the basis of the mortality rate patterns of RTAs from 2007 to 2013. We obtained the data on RTA death rates from World Health Organization reports and Human Development Index (HDI) of United Nations Development Programme reports for the years 2007, 2010 and 2013. Simple Latent Growth Models (LGM) in 181 countries were applied to estimate overall RTA mortality rate growth trajectories and the latent growth mixture modeling utilized to cluster them. According to non-linear LGM, the overall mortality rate of RTAs showed a decrease from 2007 to 2010 followed by an increase from 2010 to 2013. The HDI covariate had a significant negative and positive effect on intercept and slope of the LGM, respectively. The extracted mixture model appeared to have seven classes with different trends in RTA mortality rates. The worldwide countries were clustered into seven classes. Further studies on each of the seven classes are suggested to provide recommendations for reducing the mortality rate of the RTAs. Additionally, increasing HDI in some countries could have a significant effect on reducing the RTA death rates. 

Retracted: Yes

PubPeer comments:
 2021 retraction. https: journals.plos.org plosone article?id=10.1371 journal.pone.0253092 After this article [1] was published, concerns were raised that this work was published previously in the Razi Journal of Medical Sciences [2]. The dataset, LGM and LGMM methods, and the following results in [1] appear to duplicate material published previously in [2]: Figs 1, 2a, and 2b [1] appear to duplicate results reported in Figs 3 and 4 of [2]. Fig 3 [1] includes estimated mean growth trajectories previously reported in Fig 5 of [2]. Comparing the two figures it appears that the estimated versus observed trajectories for Class 3 may be mislabelled in the PLOS ONE figure. The data reported for u201cUnconditional linear LGMu201d and u201cUnconditional Nonlinear LGMu201d in Table 2 [1] were reported in Table 1 of [2]. Tables 3 and 4 [1] duplicate results reported in Tables 2 and 3 of [2]. S1 Fig panel A [1] duplicates Fig 6 in [2]. The 2017 article [2] was published under a CC-BY-NC license, but the PLOS ONE article did not discuss, cite, or provide attribution to [2], and did not mention that the above results had been published previously. As such, the republication of the above material in [1] did not comply with the terms of the CC-BY-NC license. The authors apologized for not citing [2] in the PLOS ONE article. The PLOS ONE article reported some results that were not reported in [2]. Even so, the PLOS ONE Editors concluded that the degree of overlap exceeds what is acceptable and presents concerns regarding redundancy in the literature and adherence to PLOS ONEu2019s policy on Submission and Publication of Related Studies. In light of the above concerns, the PLOS ONE Editors retract this article. MS and TM did not agree with retraction. MM and AD either could not be reached or did not respond directly. References 1.Salehi M, Mobaderi T, Mehmandar M, Dehnad A (2019) Identifying developmental trajectories of worldwide road traffic accident death rates using a latent growth mixture modeling approach. PLoS ONE 14(2): e0212402. https: doi.org 10.1371 journal.pone.0212402 pmid:30785919 2.Salehi M, Mehmandar MR, Mobaderi T. (2017) Application of growth mixture model to analysis of road traffic death rate in the world, 2007u20132013. Razi Journal of Medical Science 24(161): 1u201312. ,