| Background: Identification of risk factors involved in road traffic deaths (RTDs) could help policymakers and road traffic managers to adopt
effective strategies and approaches for the prevention and control of these incidents, while the lack of accurate data on the risk factors of
RTDs causes the problem to persist. This systematic review aimed at assessing the national studies regarding the risk factors of RTDs in the
regions covered by the World Health Organization (WHO). Methods: This review study was conducted during 2008–2018 via searching
in databases of PubMed, Science Direct, Scopus, Cochrane, Thomson Reuters, Web of Science, EMBASE, ProQuest, and Trip databases.
Initially, a literature review was performed to find similar systematic reviews, followed by another literature review to retrieve the published
or registered protocols. At the next stage, PECOTS was developed for the search strategy, followed by the quality assessment. The eligibility
criteria in this study were the national‑level studies about the risk factors related to RTDs, English‑language studies, and studies published
during 2008–2018. Results: In total, 169 articles were included in this study, with the highest and lowest number of the published articles
in the United States and African countries, respectively. According to the reviewed studies, human factors accounted for the most common
risk factors involved in RTDs. In the southeastern regions of Asia, the main road‑related risk factor for RTDs was reported to be the type of
roads. Furthermore, roadside departure to the right side and long roads were denoted in the national data of the Western Pacific region on the
incidence of RTDs. Differences were observed between the six regions covered by the WHO in terms of the time‑related risk factors for RTDs.
Conclusions: Several risk factors have been reported for RTDs in the countries covered by the WHO, and each risk factor is considered to have
various subcategories. Therefore, it could be concluded that there are different epidemiological patterns for road traffic accidents and RTDs. |