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Regional determinants of road trafficaccidents in Nigeria: identifying riskareas in need of interventionTolulope Osayomi aa Department of Geography , University of Ibadan , Ibadan ,NigeriaPublished online: 02 Jan 2013.

To cite this article: Tolulope Osayomi (2013) Regional determinants of road traffic accidents inNigeria: identifying risk areas in need of intervention, African Geographical Review, 32:1, 88-99,DOI: 10.1080/19376812.2012.750224

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RESEARCH ARTICLE

Regional determinants of road traffic accidents in Nigeria: identifyingrisk areas in need of intervention

Tolulope Osayomi*

Department of Geography, University of Ibadan, Ibadan, Nigeria

(Received 29 November 2011; accepted 13 November 2012)

Road traffic accidents have become an issue of great concern in recent times in Nigeria.Several intervention efforts have been designed to reduce the accident rates and traffic mor-tality levels. This article analyses regional variations in road traffic accidents in Nigeria andtheir causes. Data on road traffic accidents for year 2003 to 2007, economic development,traffic density, urbanization, population size, and road infrastructure were assembled andanalyzed using stepwise linear regression. Besides the national analysis, four separateregression models were estimated for northern, southern, urban and rural Nigeria. Resultsindicate that the length of asphalt concrete roads was a significant factor in road accidentsat the national (R2 = 19.7%; p = 0.006) and rural scales (R2 = 35.8%; p = 0.011). Equallysignificant was the length of federal roads in urban (R2 = 41.5%; p = 0.011) and southernNigeria (R2 = 50.1%; p = 0.001). Meanwhile, in northern Nigeria, urbanization and thelength of asphalt concrete roads appeared to be dominant factors in road traffic accidents(R2 = 54.3%; p = 0.001). Given the observed geographical differences, this study recom-mends the design of area-specific strategies for the prevention and control of road trafficaccidents in Nigeria.

Keywords: road traffic accidents; road safety; unsafe roads; Nigeria

Introduction

Across the world, road traffic accidents are a significant cause of mortality. Over 1.2 millionpeople die annually on the world’s roads while 20–50 million suffer non fatal injuries (WorldHealth Organisation, 2009). Indeed, road traffic accidents rank among the first ten importantcauses of death in the world and would rise to sixth position by 2020 (World Health Organi-sation, 2009). About 97% of road traffic accidents occur in the low and middle income coun-tries. Road traffic accidents are a bigger cause of mortality than many infectious diseases inthe developing world (Vasconcellos, 1996). For example, India, which has 1% of the world’svehicle population, has 6% of the world’s road accidents (Kanchan, Bakkannavar, Kumar, &Unnikrishnan, 2012) and in Iran, road traffic accidents are the second highest cause of mortal-ity after coronary heart disease (Montazeri, 2004).

With respect to Nigeria, the road accident situation is similar to the prevalent global sce-nario. Road traffic accidents are an important and rising health concern in Nigeria. Justrecently, the World Health Organisation (WHO) ranked Nigeria second in the incidence ofroad traffic accidents in the world as a result of ‘unsafe roads’ (Okwuofu, 2011). For instance,there were 16,478 reported cases of traffic fatalities and 79,409 road traffic accidents between

*Email: osayomi@yahoo.com

African Geographical Review, 2013Vol. 32, No. 1, 88–99, http://dx.doi.org/10.1080/19376812.2012.750224

� 2013 The African Specialty Group of the Association of American Geographers

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2006 and 2008 (The Punch, April 18, 2011). Therefore, reducing road accidents is an urgentnational concern in Nigeria.

Over the years, road traffic accidents in Nigeria have received some academic interestfrom various disciplines. This is mirrored in studies conducted in different disciplines. Thespatial aspects of road traffic accidents in the country have also been studied by scholars likeJegede (1988), Gbadamosi (2002) and Atubi and Onokala (2009). Jegede’s (1988) classicstudy of the spatio-temporal pattern of road accidents in the old Oyo state of Nigeria foundthat the number of industries, average daily traffic, and length of local government roads werecontributory factors to road traffic accidents. Gbadamosi (2002) analysed spatial variations inaccident occurrences in Nigeria from 1970 to 1995 and identified federal roads and state areaas risk factors. Similarly, Atubi and Onokala (2009) found that the spatial pattern of road traf-fic accidents in Lagos state was a function of the length of roads, presence of road safetycorps, and population size. Together, these studies have added to our understanding of thegeography of road traffic accidents in Nigeria.

However, little research has focused on regional differentials in road traffic accidents inNigeria. This is important given the country’s regional inequalities in socio-economic devel-opment, e.g. between the North and South and its urban and rural areas (Aka, 1995; Abu-mere, 1998). This study therefore seeks to focus on the regional variations and determinantsof road traffic accidents in Nigeria. To this end, separate regression analyses were conductedto identify road accident risk factors in and between the study regions in the hope of strength-ening efforts designed to curb road traffic accidents in the country.

Methods

Study setting

Nigeria lies between Longitude 3° and 15° East of the Greenwich Meridian and Latitude 4° and14° North of the Equator. It is surrounded by Niger Republic in the north, the Republic of Beninin the west, Cameroon in the east, and, in the south, the Atlantic Ocean. Moreover, Nigeria isthe most populous country in Africa. The 2006 national census recorded the country’s popula-tion as 140,003,542, putting the national population density at 151 persons per square kilometre.There are a total of 36 states and the Federal Capital Territory better known as Abuja.

Nigeria has a total road network of 195,000 kilometres (See Figure 1). Of the network,32,100 kilometres (16%) are federal roads; 30,900 kilometres (16%) are state roads and132,000 kilometres (68%) are local government roads. Thirty one percent of the total roadnetwork is paved. Of the paved roads, 83% belong to the federal government, 49% to thestate governments, and 10% to local governments (Federal Republic of Nigeria, 2007).

Seriously bothered by the rising trend of road traffic crashes over the years, the federalgovernment created the Federal Road Safety Commission (FRSC) through Decree Number 45of 1988. The agency has the statutory responsibility of enforcing discipline, law, and order onNigerian roads and preventing road accidents and the associated deaths and injuries.

Data sources

The data used in this study is from different sources. Data on the incidence of road trafficaccidents for each of the 36 states and the Federal Capital Territory (FCT) from 2003–2007was collected from the Annual Abstract of Statistics 2009. The study period was selectedbased on the availability of aggregate data on road traffic accidents in Nigeria. Statepopulation figures were obtained from the same source, while explanatory variables – level ofeconomic development, traffic density, degree of urbanization, population size, and road

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infrastructure – were assembled from both the Annual Abstract of Statistics 2009 and UNDPNigeria Report 2009.

Study variables

Nine independent variables were selected based on the identification in the literature aspossible factors in the spatial variation in road traffic accidents. As shown in Table 1, these

Figure 1. Nigeria’s road network system.Source: http://www.vidiani.com/maps/maps_of_africa/maps_of_nigeria/large_detailed_road_map_of_nigeria_with_all_cities_roads_and_airports_for_free.jpg (� GEOALTAS. The author appreciates the kindpermission of GEOALTAS for the use of their diagram).

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were: population size, degree of urbanization, number of registered vehicles (a proxy for traf-fic density), number of financial institutions, state GDP per capita (surrogate for level of eco-nomic development), road infrastructure (the length of federal roads, the length of the asphaltconcrete roads, length of surface roads, and the length of gravel roads). All of these variableshave been shown in the literature to be positively correlated with road traffic accidents.

Nevertheless, it is pertinent to consider the limitations of some of these Nigerian datasources. Because of the country’s poor record keeping culture, its data are often under-reported or inaccurate, if available. This said, these are the best available data sets.

The study’s dependent variable, average road traffic accident rate for each state (road traf-fic accidents) was computed by dividing the sum of the road accident rates for the years2003–2007 by the five years in this period. A description of the predictor variables is asfollows:

Population size: This refers to the total population for each of the 36 states and theFederal Capital Territory of Nigeria. The population figures were obtained from the 2006census figures and were hence assumed to be constant throughout the study period. In accor-dance with Jones et al. (2008), Atubi and Onokala (2009), Kanchan et al. (2012), more popu-lated areas were expected to have a higher frequency of road traffic accidents than the lesspopulated ones.

Degree of urbanization: Because of the lack of state level information on the percentageof the population that is urban, the degree of urbanization was represented by computed statepopulation density figures that were obtained by dividing the population of each state by itsarea in square kilometers. As urban areas are known to have high population densities, stateswhose population densities were above the national average of 151 persons per square kilo-metre were considered to be urban, and those below the national average were regarded asrural. Though there are divergent views on the effect of urbanization on road accidents (LaTorre, Van Beeck, Quaranta, Mannocci, & Ricciardi, 2007; Jones et al., 2008), it is assumedhere that accidents would be more common in urban areas than in rural areas.

Traffic density: This is an important contributor to road traffic accidents that is representedin this study by the number of registered vehicles in each state and the Federal CapitalTerritory (FCT) of Abuja. The extant literature has shown that increased road traffic accidentshave accompanied the increased use of motor vehicles around the world (Vasconcellos, 1996;Ansari, Akhdar, Mandoorah, & Montaery, 2000; Montazeri, 2004; La Torre et al., 2007;Erdogan, 2009; Kanchan et al., 2012). In addition, accidents are dependent on the vehicleownership rates; with a rise in these rates being linked to more collisions (Jones et al., 2008).

Table 1. Study variables.

Variable Sources Operational definitions

Road trafficaccidents

National Bureau of Statistics2009

Total number of accidents (2003–2007) dividedby five, for each state.

Population size National Bureau of Statistics2009

Population size for each state.

Degree ofurbanization

Calculated Number of persons per square kilometer.

Traffic density United Nations DevelopmentProgramme Report 2009

Number of registered vehicles per state.

Economicdevelopment

United Nations DevelopmentProgramme Report 2009

State GDP per capita, and Number of financialinstitutions

Road infrastructure National Bureau of Statistics2009

Length of federal roads,length of asphalt concrete roads, length ofgravel roads, and length of surface roads

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Level of economic development: Due to its multidimensional nature, economic develop-ment was measured using the state GDP per capita and the number of financial institutions.These were used as predictor variables, as states with higher levels of economic developmenttend to have heavier accident burdens because the level of economic development influencesthe intensity of flow of people, goods, and services, thereby increasing the risk of road acci-dents (Jegede, 1988; El-Sadig, 2002; La Torre et al., 2007).

Road infrastructure: The lengths of each state’s roads by type were used in this studybecause according to Jegede (1988) and Atubi and Onokala (2009), accidents rise withincreasing road length. As these data were incomplete for some states, estimates for length ofgravel and surface roads were based on averages for nearby states.

Data analysis

The study employed the stepwise multiple regression model because of its unique ability toidentify the most significant factors, in this case, influencing the observed spatial distributionof road traffic accidents in Nigeria. The stepwise regression model not only gets to the mag-nitude and significance of the overall variance explained by all independent variables, but alsoto the contribution of each individual independent variable. Moreover, the technique elimi-nates the independent variables that do not make any meaningful contribution to the explana-tion of the dependent variable.

The study’s regression model is expressed below:

Y= a + b1X1 + b 2X2 + … + bn Xn + e.

In this model,

Y is the road traffic accident rate;a is the intercept, constant, or the value of Y when X1, X2, …, Xn are all zero;X1 to Xn are predictor variables where: X1 is the total population of per state, X2 is thestate’s degree of urbanization, X3 is the gross domestic product per capita per state, X4

is the number of financial institutions per state, X5 is the traffic density per state, X6 isthe length of federal roads in per state, X7 is the length of asphalt concrete roads in perstate, X8 is the length of gravel roads in per state, and X9 is the length of surface roadsin per state and;b1 to bn are the regression coefficients and e is the error term or stochastic disturbance.

The study thus hypothesizes that the regional variation in road traffic accidents are signifi-cantly affected by the level of economic development, traffic density, degree of urbanization,population size, and road infrastructure.

Besides the analysis at the national level, four stepwise regression models were estimatedfor northern Nigeria (Sokoto, Jigawa, Adamawa, Yobe, Zamfara, Benue, Kwara, Kogi, Pla-teau, Nasarawa, Kaduna, Kano, Katsina, Taraba, Gombe, Bauchi, Borno, Niger states and theFCT, Abuja); southern Nigeria (Oyo, Ogun, Ondo, Lagos, Osun, Ekiti, Edo, Delta, Rivers,Bayelsa, Cross rivers, Akwa Ibom, Imo, Anambra, Abia, Ebonyi and Enugu states); urbanNigeria (Abia, Akwa Ibom, Anambra, Bayelsa, Delta, Ebonyi, Edo, Ekiti, Enugu, Imo, Jiga-wa, Kano, Katsina, Lagos, Ogun, Ondo, Oyo and the Federal Capital Territory); and ruralNigeria (Adamawa, Bauchi, Benue, Borno, Cross River, Gombe, Kaduna, Kebbi, Kogi,Kwara, Nasarawa, Niger, Plateau, Rivers, Sokoto, Taraba, Yobe, and Zamfara states).

In addition, the global Moran’s I test was used to test whether there is significant cluster-ing of road traffic accidents in space in Nigeria. The value of this global autocorrelation

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statistic ranges from �1 to 0 to +1, where positive values indicate observations with similarvalues (or those that are close to each other) and negative values suggest observations wherehigh values are near those with low values or vice versa.

Results

A total of 91,935 road traffic accidents were recorded in Nigeria from 2003 to 2007 and theirspatial distribution is shown in Figure 2. An examination of the figure shows that accidentsfor that period were widely dispersed across the entire country, with higher rates generally

Figure 2. Spatial distribution of road traffic accidents in Nigeria 2003–2007.

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concentrated in southern Nigeria particularly in Oyo and Ogun states. Though the northshows some degree of dispersion, there were high accident burdens in Benue and Kano states.The map also generally depicts a clear association between accident rates and urbanization.For instance, high accident rates were found in the urbanized states of Kano, Oyo and Ogun.

The results of the stepwise regression for Nigeria, northern Nigeria, southern Nigeria,Urban and Rural Nigeria are shown in Table 2 and Figures 3–8. Table 2 shows the results ofthe four regression models, identifying the most important variables contributing to road traf-fic accidents at each scale of analysis. The coefficient of determination (represented by R2)indicates the proportion of observed variance in road traffic accidents as explained by the riskfactors. The regression models explained 19.7% of traffic accidents in Nigeria, 54.3% innorthern Nigeria, 50.1% in southern Nigeria, 41.5% in urban Nigeria, and 35.8% in ruralNigeria.

For Nigeria as a whole, higher road traffic accident rates were positively associated withthe length of asphalt concrete roads; a positive association that also applies in rural Nigeria.In northern Nigeria, the road traffic accidents were directly and significantly related to thedegree of urbanization and the length of asphalt concrete roads with results for southern and

Table 2. Summary of regression results.

Variables National Northern Southern Urban Rural

Degree of urbanization - 0.579 - - -Length of federal roads - - 0.708 0.644 -Length of asphalt concrete roads 0.444 0.435 - - 0.598Coefficient of determination(R2) 19.7% 54.3% 50.1% 41.5% 35.8%

Figure 3. Regression plot of accidents and length of asphalt roads (national).

0

500

1000

1500

0 200 400 600Degree of urbanisation

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Y

Predicted Y

Figure 4. Regression plot of accidents and degree of urbanization (northern Nigeria).

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urban Nigeria being similar. The length of federal roads was the strongest factor accountingfor the road traffic accidents in urban and southern Nigeria. Overall, the length of asphaltconcrete roads emerged as the dominant risk factor in road traffic accidents in Nigeria.

The scattergrams in Figures 3–8 clearly show the positive relationships between road traf-fic accidents and the various explanatory factors in each of the four study regions. The graphs

0

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0 500 1000 1500 2000Length of asphalt concrete roads

(in kilometres)

Roa

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Figure 5. Regression plot of accidents and length of asphalt concrete roads (northern Nigeria).

0200400600800

1000120014001600

0 500 1000 1500Length of federal roads

(in kilometres)

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YPredicted Y

Figure 6. Regression plot of accidents and length of federal roads (southern Nigeria).

0200400600800

1000120014001600

0 500 1000 1500

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YPredicted Y

Length of federal roads (in kilometres)

Figure 7. Regression plot of accidents and length of federal roads (urban Nigeria).

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strengthen earlier observations that each of the explanatory factors contributes to road trafficaccidents in Nigeria.

In order to determine spatial clustering of road traffic accidents, the global Moran’s I wasused. It yielded a negative value of �0.09 (z score: 1.23; p > 0.05), which means that roadtraffic accidents are randomly distributed in space.

Discussion

This study has described the regional patterns of road traffic accidents in Nigeria and identi-fied their key determinants. There are clear regional differences in road traffic accidents inNigeria. Besides the pronounced South–North differences in accident rates, the urban–ruralpattern is also glaring. The regional differences reported in this study are observed to be con-sistent with La Torre et al.’s (2007) findings from Italy and Erdogan’s (2009) work from Tur-key. The study’s findings also establish that the observed regional accident variations inNigeria were mainly explained by the length of federal roads, the length of asphalt concreteroads, and the degree of urbanization.

The finding that the length of federal roads was positively related to road traffic accidentsin southern and urban Nigeria corroborates Gbadamosi’s (2002) and Onakomaiya’s (1988)findings that road traffic accidents were high on the relatively good quality federal roads. Inparticular, Gbadamosi (2002) posited that ‘…drivers are generally tempted to overspeed ongood [federal] roads, leading to more frequent and fatal accidents…’. However, an alternativecause of the country’s high numbers of accidents is that only 15% of Nigeria‘s federal roadsare in good condition today due to either poor maintenance or poor construction (Nwaneri,2011). As the governor of Oyo state, Abiola Ajimobi lamented recently:

All our roads are in very deplorable conditions. In fact it will not be out of place to call themdeath traps. It takes an average of two to three hours to travel Ibadan to Lagos on the expressway,a journey which normally takes one hour. This is because of the lack of maintenance… (TheNation, 2011, p. 8)

Besides the Ibadan-Lagos expressway, other federal highways like Kaduna-Abuja, Sagamu-Ore-Benin, Kano–Kaduna, Okene-Lokoja-Abuja, Ontisha-Enugu have recorded heavy acci-dent tolls and have thus become ‘death traps’ thereby justifiably helping to earn Nigeria itsterrible WHO (2009) ranking as the 191st (out of 192) country with the most unsafe roads inthe world.

0

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0 500 1000 1500 2000

Length of asphalt concrete roads(in kilometres)

Roa

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Predicted Y

Figure 8. Regression plot of accidents and length of asphalt concrete roads (rural Nigeria).

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The contribution of length of asphalt concrete roads to accidents was positive and signifi-cant in rural, northern Nigeria and the country as a whole. Despite the 360 million naira(about US$2,227,172) investment on road construction and rehabilitation between 1999 and2003, Nigerian roads (particularly asphalt concrete ones) are unsafe as they are dotted withpotholes and gullies due to either bad construction or poor maintenance (The Punch, 2011p.18). Despite their usefulness, asphalt concrete surfaces have their disadvantages. Forinstance, they are often damaged by extreme weather conditions and oil leaks than other roadsurfaces like cement. They eventually become soft and worn out (Wallace, 2012).

In general, the role of road infrastructure in motor vehicle accidents in Nigeria is consis-tent with findings of Jones et al.’s (2008) England and Wales study, Sobngwi-Tambekou,Bhatti, Kounga, Salmi, & Largarde (2010) study in Cameroun, and Erdogan’s (2009) Turkeystudy which all show that the length of highways is a significant contributor to vehicle acci-dents, injuries and deaths.

A higher degree of urbanization was associated with higher accident rates in northernNigeria because urban areas in the North especially tend to have higher levels of vehicleownership and higher traffic densities than the surrounding rural areas. This is confirmed by apositive though insignificant correlation between urbanization and traffic density (r= 0.42; p >0.05). The higher rate of urban road traffic accidents in northern Nigeria agrees with Oyesi-ku’s (2002) claim that traffic accidents are major features of urban centers in Nigeria. Thestrong association between urbanization and road traffic accidents has also been confirmed byLa Torre et al. (2007) and Vasconcellos (1999).

The association between urbanization and high rates of road traffic accidents is howeverin contrast with other studies which have shown rural areas experience more road trafficaccidents and deaths than urban areas (e.g. NHSTA, 2002, cited in Babcock, Zlaptoper, &Welki, 2008; Dissanayake & Ratnayake, 2006; Jones et al., 2008; Spoerri, Egger, & VonElm, 2011). This is possibly due to lower traffic speed limits and better medical care in urbanareas (Coben, 2006) and higher traffic speeds observed in rural areas (Babcock et al., 2008).

Study limitations

There are a number of limitations in this study that must be highlighted. First, there is insuffi-cient data on the length of state and local government roads, though these could be stronginfluences on road traffic accidents. Second, this study was not able to examine the effect ofroad safety agencies in accident occurrences. Unlike Atubi and Onokala (2009) who arguethat the presence, or absence, of road safety corps explains some of Nigeria’s the road trafficaccidents, this study was unable to explore this factor because of the lack of data. Third, thisstudy lacked the data to explore the role of the weather in the country’s road accidents.Research has shown that many road traffic accidents from around the world are weatherrelated (Edwards, 1996; Nofal & Saeed, 1997; Keavy & Simmonds, 2005, 2006; Jones et al.,2008; Andersson & Chapman, 2011). Fourth, although many road accidents have been attrib-uted to the road unworthiness of many Nigerian vehicles (Asogwa, 1992), this study lackedthe data to explore that angle also. Fifth, this study somehow runs the risk of falling into the‘ecological fallacy trap,’ which assumes that regional patterns of road traffic accidents alsohold at the local scale. As such, it would be rather misleading to assume that the ‘length ofasphalt concrete roads’ factor, for example, influences traffic accidents uniformly throughoutNigeria. Lastly, unlike Atubi and Onokala (2009), this study did not determine the role ofbad driving behaviour (e.g. reckless driving, drunk driving, non-adherence to traffic rules, andexcessive speeding) in many of Nigeria’s road traffic accidents.

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Conclusion

The study’s findings have not only identified regional determinants of road traffic accidentsbut have also noted risk areas in need of intervention. Therefore, a number of policy implica-tions emerge from the study.

First, the Nigerian Federal Road Safety Commission (FRSC) needs to design region-spe-cific strategies for the prevention and control of accidents. The agency should, specifically,design local road safety policies and intensify road safety campaigns in the high accident riskareas identified in this study, e.g. Oyo, Ogun, Benue and Kano states (see Figure 2). Thoughpolicies such as the use of safety seat belts and helmet use are in use already, the FRSC mustensure stricter enforcement of these safety measures to achieve greater compliance.

Second, quality road provision and maintenance must be a top national concern. Thefederal government needs to urgently address the dreadful conditions of its roads by moreclosely monitoring the work of its Federal Road Maintenance Agency (FERMA).

Third, sustainable road construction in Nigeria should be encouraged. The option ofcement roads is growing globally because such roads are more environment-friendly, moredurable, and less expensive in the long run than asphalt concrete roads. Nigeria might gainimmensely from this road construction alternative (Dada, 2012).

Adopting these suggestions might help the FRSC to meet its Safe Road Initiative to‘reduce road traffic crashes and injuries accidents by 50 percent in 2020’ (FRSC 2012).

AcknowledgementsAn earlier version of this article was presented at 53rd Annual Conference of the Association ofGeographers (ANG), 21–25 November, 2011, Lagos State University, Lagos state. The author gratefullyacknowledges the input of two anonymous reviewers.

Notes on contributorTolulope Osayomi is a lecturer at the Department of Geography, University of Ibadan, Ibadan, Nigeria.

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