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\def\makelabel##1{\upshape ##1}}% } {\end{list}\end{raggedright}} \newenvironment{specHead}[2]% {\vspace{20pt}\hrule\vspace{10pt}% \phantomsection\label{#1}\markright{#2}% \pdfbookmark[2]{#2}{#1}% \hspace{-0.75in}{\bfseries\fontsize{16pt}{18pt}\selectfont#2}% }{} \def\TheFullDate{2017-01-15 (revised: 15 January 2017)} \def\TheID{\makeatother } \def\TheDate{2017-01-15} \title{Risk Factors of Road Traffic Accidents (RTAs) among Commercial Inter-State Drivers in Lagos State, Nigeria} \author{}\makeatletter \makeatletter \newcommand*{\cleartoleftpage}{% \clearpage \if@twoside \ifodd\c@page \hbox{}\newpage \if@twocolumn \hbox{}\newpage \fi \fi \fi } \makeatother \makeatletter \thispagestyle{empty} \markright{\@title}\markboth{\@title}{\@author} \renewcommand\small{\@setfontsize\small{9pt}{11pt}\abovedisplayskip 8.5\p@ plus3\p@ minus4\p@ \belowdisplayskip \abovedisplayskip \abovedisplayshortskip \z@ plus2\p@ \belowdisplayshortskip 4\p@ plus2\p@ minus2\p@ \def\@listi{\leftmargin\leftmargini \topsep 2\p@ plus1\p@ minus1\p@ \parsep 2\p@ plus\p@ minus\p@ \itemsep 1pt} } \makeatother \fvset{frame=single,numberblanklines=false,xleftmargin=5mm,xrightmargin=5mm} \fancyhf{} \setlength{\headheight}{14pt} \fancyhead[LE]{\bfseries\leftmark} \fancyhead[RO]{\bfseries\rightmark} \fancyfoot[RO]{} \fancyfoot[CO]{\thepage} \fancyfoot[LO]{\TheID} \fancyfoot[LE]{} \fancyfoot[CE]{\thepage} \fancyfoot[RE]{\TheID} \hypersetup{citebordercolor=0.75 0.75 0.75,linkbordercolor=0.75 0.75 0.75,urlbordercolor=0.75 0.75 0.75,bookmarksnumbered=true} \fancypagestyle{plain}{\fancyhead{}\renewcommand{\headrulewidth}{0pt}} \date{} \usepackage{authblk} \providecommand{\keywords}[1] { \footnotesize \textbf{\textit{Index terms---}} #1 } \usepackage{graphicx,xcolor} \definecolor{GJBlue}{HTML}{273B81} \definecolor{GJLightBlue}{HTML}{0A9DD9} \definecolor{GJMediumGrey}{HTML}{6D6E70} \definecolor{GJLightGrey}{HTML}{929497} \renewenvironment{abstract}{% \setlength{\parindent}{0pt}\raggedright \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt \textcolor{GJBlue}{\large\bfseries\abstractname\space} }{% \vskip8pt \textcolor{GJMediumGrey}{\rule{\textwidth}{2pt}} \vskip16pt } \usepackage[absolute,overlay]{textpos} \makeatother \usepackage{lineno} \linenumbers \begin{document} \author[1]{Ogunnaike Adewale Adeyemi} \affil[1]{ University of Ibadan} \renewcommand\Authands{ and } \date{\small \em Received: 6 December 2016 Accepted: 4 January 2017 Published: 15 January 2017} \maketitle \begin{abstract} Background: Road Traffic Accidents (RTAs) constitute a major public health problem globally with its effects felt more in low and middle income countries (LMICs). Millions of lives, globally, are lost annually and several others are disabled following RTAs with human, vehicular and road environment being identified by literatures as the common risk factors of RTAs. The Federal Road Safety Commission (FRSC) of Nigeria reported in 2014 that an estimated 1,991 lives were lost to RTAs in Lagos, Nigeria alone in the preceding four years. The majority of the populations affected in RTAs are within active working age group.Aim: This study was therefore designed to identify and discuss these risk factors as well as assess respondents' knowledge about road traffic signs.Methods: A descriptive cross-sectional survey was carried out among 422 consenting commercial drivers in Lagos state with a pretested, semi-structured interviewer-administered questionnaire.Statistical Analysis: Data were analysed using descriptive statistics, chi-square test and logistic regression with significance determined at p?0.05. \end{abstract} \keywords{road traffic accidents (RTAs), risk factors, road traffic signs, perception.} \begin{textblock*}{18cm}(1cm,1cm) % {block width} (coords) \textcolor{GJBlue}{\LARGE Global Journals \LaTeX\ JournalKaleidoscope\texttrademark} \end{textblock*} \begin{textblock*}{18cm}(1.4cm,1.5cm) % {block width} (coords) \textcolor{GJBlue}{\footnotesize \\ Artificial Intelligence formulated this projection for compatibility purposes from the original article published at Global Journals. However, this technology is currently in beta. \emph{Therefore, kindly ignore odd layouts, missed formulae, text, tables, or figures.}} \end{textblock*} \let\tabcellsep& \section[{I. Introduction a) Background}]{I. Introduction a) Background}\par i. RTAs oad Traffic Accidents (RTAs), classified as a noncommunicable disease, as for a long time received less attention to other diseases in its categories despite the fact that a WHO data in 2002 reported that nearly 1.2 million deaths occurred globally from RTAs with low and middle income countries (LMICs) suffering 85\% of the impact. This, in part, may be due to the assumption that RTAs are spontaneous and unavoidable occurrences; an assertion that has been voided by literatures through identification of the risk factors of RTAs-Human, Vehicular and Road environment sources. More than half of those killed in RTAs are in the productive age group, 15-44years, especially males who are the economic backbone of most families which point to the impact this neglected public health issue has on the economy of LMICs and especially the low-income groups whose earning capacity is mostly dependent on their physical activity (Global disease burden, 2002) \hyperref[b21]{(WHO, 1996)}.\par Having considered the extent of the impact of RTAs especially on the LMICs and a possibility of combating the menace provided by the Declaration of the UN through the Goal of the Decade of Action for Road Safety 2011-2020 that identifying and addressing the risk factors of road traffic accidents and provision of adequate post-crash care will reduce the rate of occurrence of RTAs, this survey was carried out to identify these risk factors as opposed to other studies that have studied these risk factors in part. The knowledge of the respondents about road traffic signs was also surveyed.In view of these, this survey aimed at providing raw evidence for policy-makers willing to make informed decisions in ensuring the safety of our traffic systems and saving as much as 5 million lives as targeted by the Decade of Action for Road Safety 2011-2020. \section[{II. Materials and Methods}]{II. Materials and Methods}\par This survey was a descriptive cross-sectional survey carried out among 422 (sample size of 425 was derived after using a prevalence of 21\% reported by \hyperref[b1]{Adekoya et al., (2011)} and adjusting for clustering effect and non-response rate) commercial inter-state drivers across ten randomly selected LGAs in Lagos State, Nigeria. Ethical approval was obtained from the UI/UCH ERC before commencement of this study. Permission was obtained from Lagos State Ministry of Transport and the NURTW, Lagos branch. Participation of the drivers was entirely voluntary and those who decided to withdraw during the study were permitted to do so.\par The questionnaire used for this survey was developed following review of related literatures on the subject matter which was followed by a pretest among 45 commercial inter-state drivers in Ibadan. The questionnaire was translated to Yoruba language (being the major language of the study area) and backtranslated to English language to ensure construct validity of the questionnaire. Valid informed consent was sought from eligible respondents (registered with the park under study and having commercial driving experience of three or more years). To gain respondents maximum attention, it was ensured that the respondents weren't the next to load passengers.\par The data were analysed using SPSS v16, Chisquare test was used to measure association between selected categorical variables while logistic regression was used to control for confounding variables by bringing factors significant at p ? 0.20 at bivariate level into the logistic regression model. A P < 0.05 was regarded as statistically significant. \section[{III. Result}]{III. Result}\par a) Socio-demographic information about respondents 422 commercial inter-state drivers representing 99\% response rate were recruited for this survey with mean age of respondents being 44.0 ± 10.3 years with majority, 82.7\%, being married and only 50.0\% or more of the respondents having secondary and/or postsecondary school education.More than 50\% of the respondents have spent 15 years or more on the job with mean job years being 15.5±8.2 years while 90\% of the respondents have no formal driving school experience. \section[{b) History of RTAs and associated risk factors}]{b) History of RTAs and associated risk factors}\par 40\% of the respondents reported ever been involved in RTA. The type of RTA reported by the respondents included head-on collision 28(19.7\%), rearend collision 47(33.1\%), rollovers 13(9.2\%), side collision 26(18.3\%) and single vehicle/lone accident 28(19.7\%) with almost half, 49.3\%, of the RTAs occurring in the afternoon. About two-third (65.5\%) of these RTAs involved no body injury. One-quarter of these RTAs were blamed on other road users, this was followed closely by faulty vehicle in 23.2\% of the cases. Brake failure, 45.5\%, was the most reported vehicular defect that resulted in the RTAs. Half of the reported RTA occurred on two-carriage ways while most of the RTAs, 60.6\%, occurred on tarred two-carriage roads with 54.9\% occurring when the weather was clear. About 16\% of the respondents sometimes or never use the seat-belt when driving while 61.4\% of the respondents have history of been arrested by road regulatory authorities (police, Vehicle Inspection Officers, FRSC) with only 23.2\% been arrested in the last three months because of over-speeding (15.7\%), nonuse of seat belt (12.6\%), overload of passengers/loads (25.3\%) among other reasons. \section[{Volume XVII Issue V Version I}]{Volume XVII Issue V Version I} \section[{c) Knowledge about road traffic signs and perception about risk factors of RTAs}]{c) Knowledge about road traffic signs and perception about risk factors of RTAs}\par The knowledge of road traffic signs was high among the respondents. Furthermore, respondents have better knowledge of regulatory signs compared to the warning signs. More than one-quarter of the respondents had no idea about road traffic signs "Roadway narrows".Overall, the respondents' had a favourable perceptionabout the risk factors for RTA. However, 53.5\%, 43.9\%, 49.2\%, 49.4\% and 48.6\% disagreed that "incompleteness of vehicle registration papers, not using seat-belt, not owning the vehicle being driven, no valid drivers' license and age of driver" respectively were possible risk factors for RTAs. \section[{e) Predictors of RTAs among respondents}]{e) Predictors of RTAs among respondents}\par Following logistic regression; Respondents that report consistent use of seat belt are 5 times less likelyto be involved in RTAs than seldom users while respondents that report regular arrest and alcohol use are 1.8 times and 1.7 times more likely respectively to be involved in RTAs than those not being arrested regularly or are not alcohol users. The analysis also showed that smokers of cigarette/cannabis are 2 times less likely to be involved in RTA than non-smokers. \section[{d) Factors associated with involvement in RTA among respondents}]{d) Factors associated with involvement in RTA among respondents}\par Statistically significant association exist between age (X 2 = 11.56, p = 0.009), years spent on the job (X 2 = 10.94, p = 0.004), seat belt use (X 2 = 23.86, p = <0.0001), being arrested regularly by road regulatory authority (X 2 = 22.56, p = <0.0001) and involvement in RTA. \section[{IV. Discussion}]{IV. Discussion}\par The rate of occurrence of RTAs among the study participants was high, similar to Pepple and Adio (2014) findings though relatively higher when compared to \hyperref[b1]{Adekoya et al., (2011)} report though this might be becauseAdekoya et al., (2011)covered a period of 10 years whereas this study captured the involvement in RTA all through the driving years of the respondents.\par The type of RTA reported majorly by the respondents was rear-end collision with almost half of the RTA occurring in the afternoon with human error being the reported primary cause of most of the RTAs. This was in agreement with most literatures on RTAs which identifies human related factors as the major cause of RTA. This study however disagrees with \hyperref[b6]{Bekibele et al., (2007)} findings that reported mechanical fault as the main cause of RTAs. Brake failurewas the most reported vehicular defect that resulted in the RTA. It should be noted that about half of the reported RTA occurred on two-carriage ways which disagrees with Arthur, (2015) findings that more RTAs occurred on single carriage ways and surprisingly most of the RTAoccurred on tarred roads with many occurring when the weather was clear. This agrees with Amo, (2014) and Arthur, (2015) both of whom identified that a higher number of crashes were recorded on roads classified as good for transportation. This is probably due to the fact that most drivers tend to over-speed on smooth and wider roads. The high percentage of RTAs that occur when weather was clear contradicts \hyperref[b15]{Margie and Scurfield (2004)} findings that road crashes among road users in LMICs are mostly influenced by poor visibility.\par This study found that respondents had good knowledge about road traffic signs used in the survey which agreed with \hyperref[b12]{Hulbert et al., (1979)} that reported a similar finding. However, it contradicts Makinde et al., (2012) findings that reported poor knowledge and Okafor et al., (2013) that reported that many of the respondents surveyed had poor knowledge of road traffic signs. The reason of this might be because of the methods of assessment that differs between these studies. Makinde et al., (2012) and Okafor et al., (2013) used multiple choice answers for their assessment while this study allows the respondents to describe what the signs means to them and "right knowledge, wrong knowledge or no idea" was recorded depending on the explanation. Also, Lagos State Government is issuing a State's drivers' permit for inter-state drivers based in Lagos state and were assessed and trained on road traffic signs and other driving skills before been given the permit. This may partly be responsible for the better knowledge among these present study participants.\par This study also shows that majority of the respondents had right knowledge for regulatory signs when compared to the warning signs. For the warning signs, \hyperref[b13]{Makinde et al.,(2012)} reported "Narrow bridge ahead and Dangerous double bend" as the traffic signs with best and poor knowledge respectively, this study identified "Slippery road and Double dangerous bend" as the most wrongly identified and "T-junction" as the traffic sign with the most right knowledge respectively. In addition, this study identified road traffic sign "Roadway narrows" as the sign cited mainly as the one which respondents could not recognise.\par For the regulatory signs, Makinde et al., (2012) reported road traffic signs "No U-turn and No parking" for best knowledge and "No overtaking" for poor knowledge, findings which are similar to this study. There was no significant association between road traffic sign knowledge score and involvement in RTAs which agreed with Al-Madani, (2000) and Al-Madani et al., {\ref (2002)} that also reported no significant association between knowledge of road traffic signs and involvement in RTAs. This study's respondents identified overspeeding as the major human factor for RTA occurrence which was similar to Arthur (2015) findings that of the behavioural factors studied, speeding had the highest on record for perceived cause of RTAs. In this study, reported cases of RTAs was higher among respondents that are seldom users of seat belt than those that are regular users. This is in consonance with several other studies; \hyperref[b10]{Evans and Bloomfield (2004)}, \hyperref[b7]{Cummings et al., (2003)}, \hyperref[b9]{Evans (1986)}, \hyperref[b11]{Huelke and Sherman (1987)}, {\ref Marburger and Friedel (1987)}, \hyperref[b19]{Rivara et al., (1999)} that reported the effectiveness of seat belts in reducing the severity of injuries, thus affirming its protective function.\par Large number of the respondents in this study who have had history of RTA also reported being arrested by regulatory authorities in the last three months prior to this study. The arrests were as a result of violation of traffic rules which may be responsible for the reported RTAs amongst them. \section[{V. Conclusions}]{V. Conclusions}\par This study showed that respondents had a good knowledge of the ten road traffic signs sampled in this survey though respondents have better knowledge of regulatory road traffic signs than warning road traffic signs.\par This study shows that RTA occurrence was high among inter-state commercial drivers in Lagos State with rear-end collision occurring the most especially in the afternoon though most are without bodily injuries. Brake failure was identified as the most reported K vehicular defect that resulted in RTAs among the respondents with most occurring on tarred two-carriage roads occurring when the weather was clear. Human factor, however, was the major contributory factor identified as the cause of RTAs by this survey. Conclusively, history of arrest by road regulatory agencies (VIO, FRSC, and Police) was identified as a risk factor for RTAs and non-use of seat belts as associated risk factors of RTAs among the respondents of this survey.\par VI. Recommendations \begin{figure}[htbp] \noindent\textbf{3} \par \begin{longtable}{P{0.6274373259052924\textwidth}P{0.2225626740947075\textwidth}} \multicolumn{2}{l}{1: Socio-demographic characteristics of respondents (N=422)}\\ Variable\tabcellsep Percentage (\%)\\ Age (years)(n=417)\tabcellsep \\ ?30\tabcellsep 10.3\\ 31-50\tabcellsep 67.9\\ 51-60\tabcellsep 14.6\\ ?61\tabcellsep 7.2\\ Mean ± SD\tabcellsep 44.0 ± 10.3\\ Marital status\tabcellsep \\ Single\tabcellsep 9.5\\ Married\tabcellsep 82.7\\ Other\tabcellsep 7.8\\ Religion\tabcellsep \\ Christian\tabcellsep 40.3\\ Islam\tabcellsep 52.8\\ Traditionalist\tabcellsep 5.2\\ Other\tabcellsep 1.7\\ Educational status\tabcellsep \\ None\tabcellsep 19.0\\ Primary\tabcellsep 31.0\\ Secondary\tabcellsep 41.9\\ Post-secondary\tabcellsep 8.1\\ Ethnicity\tabcellsep \\ Yoruba\tabcellsep 76.1\\ Igbo\tabcellsep 2.4\\ Hausa\tabcellsep 0.7\\ Others\tabcellsep 20.9\end{longtable} \par \caption{\label{tab_0}Table 3 .}\end{figure} \begin{figure}[htbp] \noindent\textbf{32} \par \begin{longtable}{P{0.85\textwidth}} Variable\end{longtable} \par \caption{\label{tab_1}Table 3 . 2 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{33} \par \begin{longtable}{P{0.15210526315789474\textwidth}P{0.13421052631578947\textwidth}P{0.10736842105263159\textwidth}P{0.15210526315789474\textwidth}P{0.17\textwidth}P{0.13421052631578947\textwidth}} Variable\tabcellsep Cut-off score\tabcellsep Score\tabcellsep Mean ± SD\tabcellsep Percentage\tabcellsep Remark\\ Knowledge\tabcellsep 10\tabcellsep <10 ?10\tabcellsep 12.7±3.9\tabcellsep 17.8 82.2\tabcellsep Poor Good\end{longtable} \par \caption{\label{tab_2}Table 3 . 3 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{34} \par \begin{longtable}{P{0.3074002574002574\textwidth}P{0.20566280566280568\textwidth}P{0.1837837837837838\textwidth}P{0.059073359073359075\textwidth}P{0.038288288288288286\textwidth}P{0.05579150579150578\textwidth}} Variable\tabcellsep \multicolumn{3}{l}{Ever been involved in RTA?}\tabcellsep \tabcellsep \\ \tabcellsep Yes (\%)\tabcellsep No (\%)\tabcellsep Total\tabcellsep X 2\tabcellsep p-value\\ Age (years)\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ ?30\tabcellsep 9(20.9)\tabcellsep 34(79.1)\tabcellsep 43\tabcellsep \tabcellsep \\ 31-50\tabcellsep 120(42.4)\tabcellsep 163(57.6)\tabcellsep 283\tabcellsep \tabcellsep \\ 51-60\tabcellsep 30(49.2)\tabcellsep 31(50.8)\tabcellsep 61\tabcellsep 11.56\tabcellsep \\ ?61\tabcellsep 8(26.7)\tabcellsep 22(73.3)\tabcellsep 30\tabcellsep \tabcellsep 0.009*\\ Highest educational status\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ None\tabcellsep 25(31.2)\tabcellsep 55(68.8)\tabcellsep 80\tabcellsep \tabcellsep \\ Primary\tabcellsep 50(38.2)\tabcellsep 81(61.8)\tabcellsep 131\tabcellsep \tabcellsep \\ Secondary\tabcellsep 76(42.9)\tabcellsep 101(57.1)\tabcellsep 177\tabcellsep 5.74\tabcellsep 0.125\\ Post-secondary\tabcellsep 18(52.9)\tabcellsep 16(47.1)\tabcellsep 34\tabcellsep \tabcellsep \\ Years spent on the job\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ ?5\tabcellsep 9(25.7)\tabcellsep 26(74.3)\tabcellsep 35\tabcellsep \tabcellsep \\ 6-14\tabcellsep 53(33.1)\tabcellsep 107(66.9)\tabcellsep 160\tabcellsep \tabcellsep 0.004*\\ ?15\tabcellsep 107(47.1)\tabcellsep 120(52.9)\tabcellsep 227\tabcellsep 10.94\tabcellsep \\ Visual/eye check\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Regularly\tabcellsep 73(51.0)\tabcellsep 70(49.0)\tabcellsep 143\tabcellsep 8.76\tabcellsep \\ Rarely\tabcellsep 96(36.0)\tabcellsep 171(64.0)\tabcellsep 267\tabcellsep \tabcellsep 0.003*\\ Use of seat-belt\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Everytime\tabcellsep 124(35.3)\tabcellsep 227(64.7)\tabcellsep 351\tabcellsep \tabcellsep \\ Seldom\tabcellsep 44(67.7)\tabcellsep 21(32.3)\tabcellsep 65\tabcellsep 23.86\tabcellsep <0.0001*\\ Arrest by road regulatory authority\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Regularly\tabcellsep 127(49.0)\tabcellsep 132(51.0)\tabcellsep 259\tabcellsep \tabcellsep \\ Rarely\tabcellsep 42(25.8)\tabcellsep 121(74.2)\tabcellsep 163\tabcellsep 22.56\tabcellsep <0.0001*\\ Knowledge score\tabcellsep \tabcellsep \tabcellsep \tabcellsep \tabcellsep \\ Poor knowledge\tabcellsep 27(36.5)\tabcellsep 47(63.5)\tabcellsep 74\tabcellsep 0.50\tabcellsep 0.479\\ Good knowledge\tabcellsep 140(40.9)\tabcellsep 202(59.1)\tabcellsep 342\tabcellsep \tabcellsep \end{longtable} \par \caption{\label{tab_3}Table 3 . 4 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{35} \par \begin{longtable}{P{0.4337931034482759\textwidth}P{0.1250574712643678\textwidth}P{0.17781609195402298\textwidth}P{0.11333333333333333\textwidth}} Year 2017\tabcellsep \tabcellsep \tabcellsep \\ Volume XVII Issue V Version I\tabcellsep \tabcellsep \tabcellsep \\ D D D D )\tabcellsep \tabcellsep \tabcellsep \\ (\tabcellsep \tabcellsep \tabcellsep \\ Variable\tabcellsep aOR*\tabcellsep 95\% C.I**\tabcellsep p value\\ Marital status\tabcellsep \tabcellsep \tabcellsep \\ Single\tabcellsep 0.491\tabcellsep 0.13-1.84\tabcellsep 0.292\\ Married\tabcellsep 0.385\tabcellsep 0.15-1.02\tabcellsep 0.054*\\ Others***\tabcellsep REF\tabcellsep \tabcellsep \\ Educational status\tabcellsep \tabcellsep \tabcellsep \\ None\tabcellsep REF\tabcellsep \tabcellsep \\ Primary\tabcellsep 1.071\tabcellsep 0.52-2.21\tabcellsep 0.853\\ Secondary\tabcellsep 1.429\tabcellsep 0.70-2.91\tabcellsep 0.326\\ Post-secondary\tabcellsep 2.394\tabcellsep 0.86-6.63\tabcellsep 0.093\\ Years on occupation\tabcellsep \tabcellsep \tabcellsep \\ ?5\tabcellsep 0.539\tabcellsep 0.20-1.46\tabcellsep 0.225\\ 6-14\tabcellsep 0.544\tabcellsep 0.32-0.91\tabcellsep 0.021*\\ ?15\tabcellsep REF\tabcellsep \tabcellsep \\ Seat belt use\tabcellsep \tabcellsep \tabcellsep \\ Everytime\tabcellsep 0.213\tabcellsep 0.11-0.41\tabcellsep <0.0001*\\ Seldom\tabcellsep REF\tabcellsep \tabcellsep \\ History of arrest\tabcellsep \tabcellsep \tabcellsep \\ Yes\tabcellsep 1.779\tabcellsep 1.09-2.90\tabcellsep 0.021*\\ No\tabcellsep REF\tabcellsep \tabcellsep \end{longtable} \par {\small\itshape [Note: K Risk Factors of Road Traffic Accidents (RTAs) among Commercial Inter-State Drivers in Lagos State, Nigeria]} \caption{\label{tab_4}Table 3 . 5 :}\end{figure} \begin{figure}[htbp] \noindent\textbf{} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_5}}\end{figure} \begin{figure}[htbp] \noindent\textbf{} \par \begin{longtable}{} \end{longtable} \par \caption{\label{tab_6}}\end{figure} \footnote{© 2017 Global Journals Inc. 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