Social, economic, and legislative factors and global road traffic fatalities
Abstract Background Road traffic fatalities (RTF) is the 8th cause of mortality around the world. At the end of the Decade of Action, it would be of utmost importance to revisit our knowledge on the determinants of RTF. The aim of this study is to assess factors related to RTF at global level. Metho...
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doaj-b895706358244c258fe9fdb704503b2c2020-11-25T03:27:53ZengBMCBMC Public Health1471-24582020-09-0120111210.1186/s12889-020-09491-xSocial, economic, and legislative factors and global road traffic fatalitiesMohammad Reza Rahmanian Haghighi0Mohammad Sayari1Sulmaz Ghahramani2Kamran Bagheri Lankarani3Health Policy Research Center, Institute of Health, Shiraz University of Medical SciencesHealth Policy Research Center, Institute of Health, Shiraz University of Medical SciencesHealth Policy Research Center, Institute of Health, Shiraz University of Medical SciencesHealth Policy Research Center, Institute of Health, Shiraz University of Medical SciencesAbstract Background Road traffic fatalities (RTF) is the 8th cause of mortality around the world. At the end of the Decade of Action, it would be of utmost importance to revisit our knowledge on the determinants of RTF. The aim of this study is to assess factors related to RTF at global level. Methods We used road safety development index which accounts for the interactions between system, human and products to assess the RTF in 115 and 113 countries in 2013 and 2016, respectively. To analyze data, three statistical procedures (linear regression, classification and regression trees, and multivariate adaptive regression splines) were employed. Results Classification and regression trees has the best performance amongst all others followed by multivariate adaptive regression splines for 2013 and 2016 data set with an R2 around 0.83. Results show that any increase in human development index was associated with RTF reduction. Comparing RTF data of 2013 and 2016, 8 countries experienced a change of more than 30%, which demonstrated a significant relationship with GINI index (named after Corrado Gini). Considering the three components of human development index, it is revealed that education explained most of RTF variation in classification and regression trees model followed by income and life expectancy. Conclusion Policymakers should consider road collisions as a socio-economic issue. In this regard, they can make provisions to reduce RTF in the long run by focusing on enhancing the three components of human development index, mainly education. However, there is a need to investigate the causation pathway among these three components with RTF with different time-trend procedures.http://link.springer.com/article/10.1186/s12889-020-09491-xHuman development indexEducationIncomeLife expectancyGINI indexRoad traffic fatalities |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Mohammad Reza Rahmanian Haghighi Mohammad Sayari Sulmaz Ghahramani Kamran Bagheri Lankarani |
spellingShingle |
Mohammad Reza Rahmanian Haghighi Mohammad Sayari Sulmaz Ghahramani Kamran Bagheri Lankarani Social, economic, and legislative factors and global road traffic fatalities BMC Public Health Human development index Education Income Life expectancy GINI index Road traffic fatalities |
author_facet |
Mohammad Reza Rahmanian Haghighi Mohammad Sayari Sulmaz Ghahramani Kamran Bagheri Lankarani |
author_sort |
Mohammad Reza Rahmanian Haghighi |
title |
Social, economic, and legislative factors and global road traffic fatalities |
title_short |
Social, economic, and legislative factors and global road traffic fatalities |
title_full |
Social, economic, and legislative factors and global road traffic fatalities |
title_fullStr |
Social, economic, and legislative factors and global road traffic fatalities |
title_full_unstemmed |
Social, economic, and legislative factors and global road traffic fatalities |
title_sort |
social, economic, and legislative factors and global road traffic fatalities |
publisher |
BMC |
series |
BMC Public Health |
issn |
1471-2458 |
publishDate |
2020-09-01 |
description |
Abstract Background Road traffic fatalities (RTF) is the 8th cause of mortality around the world. At the end of the Decade of Action, it would be of utmost importance to revisit our knowledge on the determinants of RTF. The aim of this study is to assess factors related to RTF at global level. Methods We used road safety development index which accounts for the interactions between system, human and products to assess the RTF in 115 and 113 countries in 2013 and 2016, respectively. To analyze data, three statistical procedures (linear regression, classification and regression trees, and multivariate adaptive regression splines) were employed. Results Classification and regression trees has the best performance amongst all others followed by multivariate adaptive regression splines for 2013 and 2016 data set with an R2 around 0.83. Results show that any increase in human development index was associated with RTF reduction. Comparing RTF data of 2013 and 2016, 8 countries experienced a change of more than 30%, which demonstrated a significant relationship with GINI index (named after Corrado Gini). Considering the three components of human development index, it is revealed that education explained most of RTF variation in classification and regression trees model followed by income and life expectancy. Conclusion Policymakers should consider road collisions as a socio-economic issue. In this regard, they can make provisions to reduce RTF in the long run by focusing on enhancing the three components of human development index, mainly education. However, there is a need to investigate the causation pathway among these three components with RTF with different time-trend procedures. |
topic |
Human development index Education Income Life expectancy GINI index Road traffic fatalities |
url |
http://link.springer.com/article/10.1186/s12889-020-09491-x |
work_keys_str_mv |
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