Evaluating Access to Infrastructural Facilities in Okene ...

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Sahel Journal of Geography, Environment and Development Vol. 1: No. 2December

ISSN: Online 2756-536X Print: 2756-5378

2020

Evaluating Access to Infrastructural Facilities in Okene Suburb KogiState, Central Nigeria: A Comparative Study

Balogun, G.F*, 1 Kekere A. A, 2lawal, L.O & 1 Habib, A.1 Department of Geography & Environmental Studies, Kogi State University

P.M.B, 1008, AnyigbaKogi State2 College Of Education, Ilorin, Kwara State.

Corresponding Author’s email: [email protected]. Telephone No. 08036137100

ABSTRACTThe study was carried out to evaluate access to public infrastructural facilities in Okene suburbs, KogiState. The specific objectives were to examine the distribution of infrastructural facilities, to determinethe settlement pattern, examine access to public infrastructure and; to compare access to publicinfrastructure. Primary and secondary data were used for this study. Multistage sampling techniquewas used to select four (4) suburbs based on their population and proximity to Okene town and thesesuburbs include: Ageva, Agassa, Upogoro and Achoze. The second aspects of the study employedgeographic information system (GIS) and remote sensing (RS) to determine the settlements pattern. TheKrejcie Morgan sample size calculator was used to determine the population size for the study. A totalof 367 questionaires were used for the study. Descriptive statistics such as frequency count, simplepercentages and graphs were used to summarize the data. Inferential statistics such as nearestneighborhood Analysis (NNA) was used to determine and show settlemen pattern of the study area.Similarly, a one way analysis of variance (ANOVA) was used to determine statistically significantdifferences in accessibility of public infrastructure in the study area. The results indicate that Agevacommunity exhibited clustering pattern with NNA ratio of 0.6 which is <1 and significant since z-score is-4.13. Similarly, the NNA ratio for Agassa community is 1.6 >1 and this an indication that it is adispersed settlement pattern with a significant z-score of 3.44. The NNA ratio of 4.5 for Upogorocommunity exhibited a dispersed pattern and significant with z-score of 14.8 while NNA ratio of 2.8 wasrecorded for Achoze community which is equally >1 and significant with z-score of 7.1. The study alsorevealed an uneven distribution of public infrastructure. Results show that 75% of Aggassa communitycovers a distance of over 1km access to public water supply, 52% of the respondents have access tohealth-care facilities and 69.5% to public institution. In Ageva community 70.2% have access to health-care facilities under less than 500m, 42.5% have access to public water supply in a distance of 500-1kmand 41.1% have access to public institution in a distance of above 1km. Results of ANOVA show that P-value of 1.00 is > than alpha level of 0.05of significance. This implies that access to publicinfrastructures was not adequately spread and by implication people in these communities cover a lot ofdistance to get access the facilities. The study therefore, recommends that more infrastructural facilitiesshould be built to meet the demands of the people in the study area while ensuring maintenance ofexisting infrastructure.Keywords: Community, Infrastructure, livelihoods, pattern, settlements.

1.0 INTRODUCTION

Rapid growth of towns and cities has been a common feature in the developing countries ofthe world since the last century. Infrastructural development is evolving in developing nationsof the world after several years of underdevelopment. Most developed countries of the worldensure the provision of infrastructure to improve the livelihood of their citizens and theirquality of life (Khoza, 2009). Provision of public infrastructural facilities such as electricity,healthcare, roads, telecommunications, pipe borne water, boreholes, institutions, libraries,recreation centers, among others is regular and guaranteed in developed nations whiledeveloping countries are still struggling to find solutions to the huge deficit of infrastructuralfacilities. The quality of life in urban areas is determined by the provision of infrastructures

mailto:[email protected]

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such as electricity supply, portable water, education, healthcare, waste disposal, amongothers (Aderamo, 2008).

Infrastructure is used as an umbrella term to describe basic structure and facilities necessaryfor a country’s development and to function efficiently. It is designed as the totality of basicphysical facilities upon which all other economic activities in a system depend (Geet, 2007).Infrastructure comprises the assets needed to provide people with access to economic andsocial facilities. Rural infrastructure is a broad term covering the basic facilities and servicesneeded for rural communities and rural development (FAO, 2006). Infrastructures are criteriafor measuring success aimed at accelerating economic development and it is obvious that onecannot expect rapid socio-economic development without adequate provision forinfrastructural facilities (Ndulu, 2006; Calderon and Serve, 2008; Egbetokun, 2009).

The infrastructures in Nigerian towns and cities have been found to be in a state of decay;these problems have been attributed to the inability of government at all levels in theprovision of infrastructures to meet the needs of teaming population. Inadequate and lowqualities of infrastructures could have serious implication for persistent rise in poverty in oursociety. The critical factors that contribute to the high level of rural poverty is inadequateinfrastructural facilities and the role of infrastructural facilities in overall economic growth anddevelopment cannot be overemphasized (Omofonmwan, 2004; UN 2011). Similarly, Ale, et al(2011) asserted that that provision of basic infrastructures is a prerequisite for developingeconomies to stimulate economic growth and reach the state of economic recovery andpoverty alleviation through increasing and diversifying agricultural outputs.

Many studies have been carried out on infrastructural development in rural areas (Eyengheetal., 2015; Ganre, 2016, Ismail et al., 2017). For example, Ismail, et al. (2017) carried out astudy on spatial analysis of some indicators of development in the rural Areas of Okene LocalGovernment Area and found high positive correlation between infrastructure anddevelopment. Similarly, Eyenghe, et al.(2015) assessed location and availability of publicfacilities and services in Port Harcourt metropolis in Rivers State. The study found income tobe a major determining factor in the distribution of facilities and services in Port Harcourtwhile population threshold was not considered significant in the gap in the distribution offacilities and services in city.

Ganre (2016) studied the analysis of spatial distribution of rural infrastructural facilities inMakarfi Local Government Area of Kaduna State and found that there is spatial unevenness inthe distribution of rural infrastructural facilities in the study area. However, previous studieshave been unable to give a clearer and unique comparison of public infrastructures amongrural areas. Therefore, this study is aimed at evaluating access to infrastructural facilities inOkene Suburbs with the view to establishing differential access to public infrastructure in thestudy area.

2.0 MATERIALS AND METHODS

2.1 Study Area

Okene Local Government Area lies on latitude 07°33′N to the North and longitude 06°14′E tothe East. It has an area of 328 km/sq with a population of 320,260 persons at the 2006 (NPC,2006). The Local Government is bordered to the West by Okehi Local Government Area, to theEast by Ajaokuta Local Government Area, to the North by Adavi Local Government Area and tothe South by Ogori-Magongo Local Government Area and Edo State. The present Okene LocalGovernment Area is composed of Okene and Okengwe districts. The 11 wards in the LocalGovernment Area are Bariki, Otutu, Orietesu, Lafia/Obessa, Okene-Eba, Idoji, Onyukolo,Obehira-Eba, Obehira-Uvete, Abuga/Ozuja and Upogoro/Odenku wards (Figure 1).

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Okene Local Government Area is located in the tropical climatic zone influenced by twoclimatic conditions of wet and dry seasons. The rainy season starts from April to October,while the dry season starts from November to April. The dominant vegetation of Okene LocalGovernment Area is the Guinea Savannah type. The ecological zone in which the LocalGovernment Area is situated offers considerable potential for agricultural production.Geologically, Okene is underlain by the basement complex rocks which have been exposeddue to severe erosion over time. It is also characterized by massive chain of ridges and rockyhills all over the area. OkeneLocal Government Area is endowed with minerals resources suchas Clay, Feldspar, Gemstones, Kaolin Marble (Limestone), and Quartz Sandstones (Usman,2011). The inhabitants of the study area are well known for the famous Okene cloth weaving,farming, hunting and commercial activities (Usman, 2011).

Fig 1: Geographical location of study area

Source: GIS Lab, KSU, Anyigba (2020)

2.2 Methods of Data Collection and Analysis

The study design is purely descriptive survey method. Data required is both primary andsecondary data sources. A multistage sampling procedure was used for the study. The firststage involved a purposeful selection of four (4) major suburbs for the study based on theirpopulation and their proximity to Okene town. These suburbs are Agasa, Upogoro, Ageva andAchoze. The population of the selected suburbs as at 1991 population census was 12,192,10,568, 2,864 and 1,070 respectively (NPC, 1991). With an annual growth rate of 3.05 % in2018, this gives a total of 49,532, 21,301, 5,773 and 2,157 respectively. Krejcie and Morgansample size table (1970) where the population range of 100 – 90,000 has a sample size of 382

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was used as the target population for the study. However, only 367 questionnaires wereretrieved and used for the study. The questionnaires comprised two (2) sections. Section ‘A’dealt with socio-demographic characteristics while section ‘B’ sought information on access topublic infrastructures.

The second aspect of the study employed geographic information system (GIS) and remotesensing (RS) for information on settlement pattern. Descriptive statistics such as frequencycounts, simple percentage score and graphs were used to summarize the data obtained. TheNNA graphs were used to show settlement patterns. The one way analysis of variance(ANOVA) was used to test for significant differences in accessibility of public infrastructureamong the sampled communities. The Nearest Neighborhood Analysis (NNA) was used todetermine the level of randomness clustering and dispersal nature of settlement points in thestudy area. The Nearest Neighborhood Analysis is given as:-

Rn= 2đ √n/A

Rn= The description of the distribution

đ = The mean distance between the nearest neighbors

n= the number of settlements in the study area

A= the area under study (km)

The results obtained from the nearest neighborhood analysis were used diagrammatically inthe form of NNA graph to show settlement patterns in the study area.

3.0 RESULTS AND DISCUSSIONS

3.1 Demographic and Socio-economic characteristics

The summaries of results of the demographic and socio-economic characteristics of therespondents are presented in Table 1.

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Table 1: Socioeconomic characteristics of Respondents

Variables Frequency Percentage (%)Gender

Male 191 52.0Female 176 48.0

Total 367 100Age Range

Less than 20 18 4.920-29 years 82 22.330-39 years 121 32.740-49 years 112 31.0

≥50 34 9.1Total 367 100

Marital statusMarried 54 14.7Single 215 58.6

Separated 82 22.3widow/widower 16 4.4

Total 367 100Educational status

No formal education 147 40.1Primary school 53 14.4

Secondary school 122 33.2Tertiary education 45 12.3

Total 367 100Occupation

Farming 96 26.2Trading 53 14.4

Civil Service 91 24.8Unemployed 127 34.6

Total 367 100 Source: Author’s Field work, (2020).

Results from Table 1 show that. 52% of the respondents are males, while 48% are females.The results also show that 63.7% of the respondents are between 30-49 years old andindicates that, majority are within the active age group. The findings indicate that majority(58.6%) of the respondents are single with 32.2% having only secondary school education.With this type of socio-demographic status, there’s likely to be a greater consciousness of thepeople of these communities to be aware of the provision and presence of some basicinfrastructures because majority is youths and by implication they utilizes this infrastructurescompare to the adults population within these suburbs. The results also show that, 14.4%were traders, 24.8% were civil servants, and 26.2% are farmers while 34.65% are unemployed.This finding is in agreement with Ismail et al., (2017) which also show peculiarity of socio-economic status of communities in Okene and its environs.

3.2 Distribution of Public infrastructural facilities

The results of the distribution of public infrastructures are presented in Table 2

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Table 2 Facilities available in the Communities in the study area

Responses Total Yes No

Facilities Hospital(s) 340 27 36792.6% 7.4% 100%

Public Boreholes

348 19 36794.8% 5.2% 100%

School (s) 330 37 36789.9% 10.1% 100%

Source: Author’s Field work, (2020).

The results indicate that, 92.6% of the respondents agreed that there is hospital in theircommunity while 7.4% of the respondents do not have hospitals in their community. While94.8% have access to public boreholes 5.2% respondents do not have access. Majority of therespondents (89.9%) have schools in their communities while 10.1% do not have schools.

3.3 Access to Public infrastructure

Ageva community

A summary statistics on respondents’ access to public infrastructure in Ageva community ispresented in Table 3 while Figure 2 shows the points of location in settlements pattern of thecommunity.

Table 3 Accessibility to public infrastructure in Ageva community

1 Distance to health facilities No of Respondents (%)Less than 500m 130 35.4500m-1km 191 52Above 1km 46 12,5Total 367 100

2 Distance to public water Supply Less than 500m 35 9.5500m-1km 56 15.2Above 1km 276 75.2Total 367 100

3 Distance to Schools Less than 500m 63 17.2500m-1km 49 13.5Above 1km 255 69.5Total 367 100


Result from Table 3 explains the variance in point location of public infrastructure asperceived by respondents in Ageva community. Results show that 35.4% of the sampledrespondents cover a distance of less than 500m to have access to public health facility, 52%maintained a distance of 500m-1km and 12.5% cover a distance of above 1km. The point ofwater supply also varies 9.5% of the respondents cover a distance of 500m to have access topublic water supply; 15.2% maintained a distance between 500m-1km while 75.2% attainedabove 1km to access water supply. 17.2% have access to public institution with a distance of500m; 13.5% maintained a distance of between 500-1km while 69.5% cover a distance ofabove 1km. The results of nearest neighborhood analysis (NNA) show that the point index ofthe nearest neighbor ratio is 0.6 which is < 1 and this indicate that there is a clustered patternin Ageva community. This clustering is significant since z-score is -4.13 (Fig.2). The points of

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location in settlements pattern and uneven distribution of public infrastructure show thatthere is need for more public infrastructure to desirable spread to enable the inhabitants haveequal access to infrastructure. This finding agrees with a study carried out by Akinola (2007)on infrastructural deprivation among rural dwellers in Nigeria.

Figure 2: NNA for Ageva community.

Average nearest Neighbor Summary

Source: Author’s Construct (2020)

3.4 Agassa community

A summary statistics on respondents’ access to public infrastructure in Agassa community ispresented in Table 4 while Figure 2 shows the points of location in settlement pattern of thecommunity.

Average Nearest Neighbor Summary

Observed Mean Distance: 1209. Meters

Expected Mean Distance: 2127. Meters

Nearest Neighbor Ratio: 0.6

z-score: -4.127212

p-value:

Study Area:

0.000037

452413508.421460

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Table 4: Accessibility to public infrastructure in Agasa community

1 Distance to health facilities No of Respondents (%)Less than 500m 258 70.2500m-1km 82 22.3Above 1km 27 7.5Total 367 100


3 Distance to Schools Less than 500m 127 34500m-1km 88 24Above 1km 152 41.4Total 367 100


The results in Table 4 show the variance in point location of public infrastructure as perceivedby respondents in Agassa community. Results presented show that, 70.2% of the sampledrespondents have more access to public health facility in a distance of less than 500m, 22%maintained a distance of 500m-1km and 12.5% cover a distance above 1km. The distance ofpublic water supply also varies according to location points of respondents, 30.8% of therespondents have access to public water supply in a distance of less than 500m, and 26.7%cover a distance between 500m - 1km and 42.5% above 1km. Distance of public institutionalso varies. For example, 34% have access to public institution in a distance of less than 500m,24% cover a distance between 500m-1km and 41.4% maintained a distance of above 1km. Thepoint’s index of the nearest neighbor ratio is 1.6 and this indicates that the settlement patternis dispersed in Agassa community. This dispersed nature is significant since z-score is 3.44 (Fig.3). The settlement pattern is dispersed and uneven distribution of infrastructure make lifeunbearable to the people. This finding agrees with the study carried out by Egbetokun (2009).

Figure 3: NNA for Agassa community

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Average NearestNeighbor Summary


Observed Mean Distance: 158.2718 Meters

Expected Mean Distance: 96.7594 Meters


z-score: 3.439894

p-value:

Study Area

0.000582

299596.191041

Source: author’s construct (2020)

3.5 Upogoro community

The summary statistics on respondents’ access to public infrastructure in Upogoro communityis presented in Table 5 while Figure 4 shows points of location in settlement pattern of thecommunity.

Table 5: Accessibility to public infrastructure in Upogoro community

1 Distance to health facilities No of Respondents (%)Less than 500m 77 21500m-1km 120 32.7Above 1km 170 46.3Total 367 100




Respondents’ perception in the variance in point location to public infrastructure in Upogorocommunity is shown in Table 5. Results presented show that 21% of the sampled respondentshave access to public health facility in a distance of less than 500m, 32.7% maintained adistance of 500m-1km and 46.3% cover a distance above 1km. Similarly, 40.3% have access towater supply in a distance less than 500m, 32.2% maintained a distance of 500m-1km while27.5% cover above 1km distance to public water supply. The result also show that 24.7% haveaccess to public institution with a distance of less than 500m, 29.5% cover a distance between500m-1km and 45.8% maintained above 1km. The point index of the nearest neighbor ratio asindicated on the plotted graph is 4.5 and this indicates the dispersed settlement pattern inUpogoro community. This dispersed pattern is significant hence z-score is 14.8 (Fig.4).

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Figure 4: NNA for Upogoro community.






z-score: 14.828289

p-value:

Study Area

0.000000

40332990.630279

Source: author’s construct (2020).

The point location in settlement pattern and uneven distribution of public infrastructure showthat there is need for more public infrastructure to desirable spread to enable the inhabitantshave equal access to infrastructural facilities.

3.6 Achoze community

A summary statistics on respondents’ access to public infrastructure in Achoze community is presented in Table 6 while Figure 5 shows point of location in the settlement pattern of the community.

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Table 6: Accessibility to public infrastructure in Achoze community

1 Distance to health facilities No of Respondents (%)Less than 500m 107 29.7500m-1km 210 58.3Above 1km 50 12Total 367 100




The variance in point location of public infrastructure as perceived by respondents in Achozecommunity is explicit in Table 6. Results also show that 29.7% of the sampled respondentscover a distance of less than 500m to have access to public health facility, 58.3% maintained adistance of 500m-1km and 12% cover a distance of above 1km. Distance to public institutionalso varies accordingly; 37.6% a distance of less than 500m to public schools, 35.3% of therespondents maintained a distance of 500m-1km and 27.7% of the respondents cover adistance of above 1km to public schools.

The results Nearest Neighbor Analysis (NNA) show that the point index of the nearestneighbor ratio is 2.8 which is also an indication that there is a clustered settlement pattern inAchoze community. This clustering is significant since z-score is 7.1 (Fig.5).

Figure 5: NNA for Achoze community.

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z-score: 7.071793

p-value:

Study Area

0.000000

215563.902174

Source: author’s construct (2020)

The spatial variation in point location of public infrastructures in the study area is presented intable 7

Table 7 Spatial variation in point of location of infrastructure in the study area

ANOVA Properties SS df MS F-cal P-value

Between Groups .000 3 .000 .000 1.000

Within Groups 136756.000 32 4273.625

Total 136756.000 35

*significant, P < 0.05:

Authors’ computation 2019

The ANOVA presented in Table 7 showed calculated p-value of 1.000 is greater than the 0.05level of significance. Therefore, there is significant difference in point of location of publicinfrastructures in the sampled areas, since cal. p-value is > 0.05 level, hence the nullhypothesis is rejected suggesting that, significant differences exist in points of location ofpublic infrastructure in the study area.

3.7 Implication of the study

From the findings of the study it is clearly shown that the settlements pattern varies accordingto location. The study revealed that Ageva is a clustered settlement pattern while Agassa,Upogoro and Achoze are all dispersed. The findings also suggest that there is unevendistribution of infrastructural facilities in the study area. In Ageva community, majority of therespondents cover a long distance to access health facilities, water supply and to schoolcompared to Agassa community. This is because of the uneven distribution of facilities inthese areas. By implication, some areas tend to have more infrastructural facilities than theothers. In Upogoro community a lot of the respondents have access to infrastructures such ashealth, public water supply and schools but have to cover a long distance. This also impliesthat, more of them cover above 1km to have access to these facilities compared to Achozecommunity.

4.0 CONCLUSION AND RECOMMENDATIONS

The study evaluated access to infrastructures in Okene suburbs. Across the suburbs sampled,the study found out that, the points of settlements are majorly clustered and dispersed. Theunevenness in the distribution of infrastructure may have constituted a burden to inhabitants

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in these communities. The study also found out people move long distances to have access topublic infrastructure most of which are over stretched, obsolete and in a state of decay.

Based on the findings, the study recommends an expansion of the infrastructure in thesuburbs to reduce the rate of poverty, improve on livelihood of the population and reduceintra-urban movement of people. Similarly, basic infrastructural facilities such as water andhealth facilities should be increased to meet up with the rising population while communitypolicing should be used to guard public infrastructure against vandalization.

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