Statistical analysis of the causes and effects of motorcycle accidents in the Gomoa East district in the Central Region of Ghana

 Corresponding author: Jonas Agyekum Mintah Copyright © 2025 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution License 4.0. Statistical analysis of the causes and effects of motorcycle accidents in the Gomoa East district in the Central Region of Ghana Jonas Agyekum Mintah 1, * and Margerat Mintah 2 1 Department of Statistics, George Washington University, Washington, D.C., United State of America. 2 Department of Applied Mathematics and Statistics, Faculty of Applied Sciences, Accra Technical University, Ghana. World Journal of Advanced Research and Reviews, 2025, 26(02), 3054-3067 Publication history: Received on 04 April 2025; revised on 20 May 2025; accepted on 22 May 2025 Article DOI: https://doi.org/10.30574/wjarr.2025.26.2.1991 Abstract Road traffic accidents involving motorcycle riders continue to pose a significant public health challenge, with a substantial portion of the health-related consequences occurring in developing nations, including Ghana. This research developed an appropriate model for assessing the causes and effects of a motorcycle accident in the Gomoa East District. Employing a cross-sectional research design, a random sample comprising 115 motorcycle riders was selected using the snowball sampling method. Structured questionnaires were employed to gather data from this selected sample. Statistical analysis included the utilization of the Chi-squared test of association and a binary logistic regression model. The findings indicated that most motorcycle accident victims were males (84.3%). Among the respondents, the majority (57.4%) were in the age categories of 26-35 years. Moreover, the study uncovered that age, frequency of maintenance, weight, adherence to speed limits, riding experience, and riding under the influence of alcohol all had a significant impact on motorcycle accidents in the Gomoa East district (p<0.05). The likelihood of motorcycle accidents occurring in the Gomoa East district was considerably high, primarily due to a prevalent issue of drunk riding among motorcycle riders. There was high prevalence of motorcycle accidents among males than females. It is imperative that policies and regulations designed to enhance road safety for both motorcycle riders and other road users be rigorously implemented in the Gomoa East district. Keywords: Motorcycle Accidents; Logistic Regression; Injuries; Gomoa East District; Ghana 1. Introduction In Ghana, road transport is the predominant mode of travel, with over 80% of passenger traffic and more than 70% of freight transportation relying on roads [1]. The surge in economic activities and investments in road infrastructure has led to an increased use of motorcycles, particularly in urban areas for commercial purposes, despite the fact that these operations are often unauthorized [2]. In Ghana and several other developing countries, motorcycles have become the preferred and most accessible mode of transportation for many people, even though it comes with considerable risks [3]. Shockingly, an average of 3,242 individuals succumb to road traffic injuries every day, amounting to 1.35 million lives lost annually due to road accidents, along with as many as 50 million people sustaining injuries [1]. Motorcyclerelated injuries present a notable but often overlooked public health issue in developing nations, ranking among the leading causes of injuries and fatalities resulting from accidents [2]. In sub-Saharan Africa, the utilization of commercial motorcycles for transportation, especially by young people, has become widespread and accepted, driven by rising unemployment. Several factors contribute to this surge in commercial motorcycle use, including inadequate mass transportation systems, poor road conditions, and traffic congestion, among other factors prevalent in developing countries [4]. World Journal of Advanced Research and Reviews, 2025, 26(02), 3054-3067 3055 According to Haworth and Rowden[5], the growing popularity of motorcycles as a mode of transportation has led to a rise in motorcycle accidents and associated fatal injuries in countries where they are widely used. Despite being a substantial public health issue, there is a notable lack of research in this field, especially in the Gomoa East district, where the problem is particularly acute. Injuries resulting from motorcycle accidents constitute a significant yet frequently overlooked emerging public health issue in developing nations, making a substantial contribution to the overall tally of road traffic injuries [6, 8]. According to an exclusive report obtained by the Ghana report, motorcycles were responsible for approximately 45% of the total 1,454 fatalities documented in the first half of 2021. During this period, motorcycle-related deaths exceeded the 518 fatalities involving commercial vehicles and were 308 more than the fatalities linked to private vehicles [9]. According to the World Health Organization (WHO), even in developed countries with low morbidity and mortality rates from motorcycle accidents, the risk of fatality in a motorcycle crash is twenty times higher than in a motor vehicle collision [10]. Thus, this research aims to establish the causes and effect of motorcycle accidents in the Gomoa East Constituency where motorcycle accidents is on the rise. This will go a long way in providing information that could influence policy makers and road users to help curb motorcycle accidents and the formulation and proper implementation of plausible solutions like sanctioning for reckless driving, adequate traffic control and road safety policy enhancement. 2. Methods 2.1. Study Area and Population The Gomoa East district is positioned in the southeastern portion of the Central Region, lying between latitudes 5014’ North and 5035’ North, as well as longitudes 0022 West and 0054’ West. This district holds a distinctive geographical position, bordered to the northeast by the Agona East district, to the southwest by Gomoa West, to the east by the Awutu-Senya District, and to the south by the Efutu Municipality. The southernmost part of the district meets the Atlantic Ocean. It covers an approximate area of 260.69 square kilometers [11]. According to the 2021 population and housing census, the district's population stands at 308,697, comprising 152,238 males and 156,459 females [12]. The study population comprised of individuals who operate motorcycles within the Gomoa East district. 2.2. Study Design This was a quantitative cross-sectional study conducted at the Gomoa East district in the Central Region of Ghana. 2.3. Sampling Techniques In this research, a snowball sampling approach was employed. Using this method, the researcher initially reached out to a participant from the target population who met specific criteria. This initial participant then assisted in identifying and recruiting other motorcycle riders who shared similar characteristics for the study. 2.4. Sample Size Determination The sample size was calculated using Yamane’s formula as shown below at a 95% Confidence Interval and a 5% margin of error [13]. A total of 161 motorcyclists were identified in the Gomoa East district. The formula is given as follows: 𝑛 = 𝑁 1 + 𝑁(𝑒)² where; n = Sample size, N = Total number of motorcyclists in the district (161), and e = Margin of error set at 5% (0.05). 𝑛 = 161 1 + 161(0.05)² =114.795 =115 The sample size was rounded up to 115 to increase the precision of the values. World Journal of Advanced Research and Reviews, 2025, 26(02), 3054-3067 3056 2.5. Source of Data This research utilized primary data as its main source of information. Data collection was carried out through a structured questionnaire distributed to respondents in the Gomoa East district during fieldwork. Additionally, supplementary information was obtained from diverse sources, including textbooks, journals, articles, previous research studies, media reports, and online platforms, contributing to the literature review. 2.6. Data Collection Procedure Data collection occurred between April and July 2024. Prior to data collection, two research assistants were recruited and trained in the fundamental ethical principles of data collection and in using the study instrument. The research assistants were stationed at locations where commercial motorcycle riders typically gather to pick up passengers and recruit respondents. On average, it took approximately 5 minutes to complete each questionnaire. The data collection instrument was an interviewer-administered questionnaire consisting of 31 questions divided into six sections. Section A of the questionnaire focused on capturing demographic information about the respondents, including their gender, age, educational level, marital status, employment status, and weight. Section B contained general questions about motorcycle usage. Section C aimed to determine whether speeding contributed to motorcycle accidents. Section D aimed to investigate if alcohol consumption played a role in motorcycle accidents. Finally, Section E examined the economic and social consequences of motorcycle accidents on the victims [14]. 2.7. Pretesting of Questionnaire The research instruments were pretested in the Cape Coast Municipality, after which essential adjustments were made to the questionnaire prior to the main study. These modifications addressed ambiguities, ensuring clarity in the questions. Furthermore, the pretesting process helped identify the most suitable timing for conducting the study. 2.8. Ethical Consideration The study participants received a detailed explanation of the study's purpose and procedures, and their verbal consent was secured before participation. Moreover, strict protocols were implemented to maintain the confidentiality of the collected data. 2.9. Data Analysis After gathering questionnaires from the study’s participants, the data was processed using IBM SPSS Inc. version 16 (Chicago, Illinois, USA). Descriptive statistical tables were utilized to construct a demographic profile for the respondents, and the results of other variables were conveyed through frequencies, percentages, and graphical representations. To investigate the relationship between motorcycle accidents and the demographic attributes of the respondents, Pearson's chi-square test was employed. Finally, logistic regression analysis was employed to establish a suitable model for evaluating the factors contributing to motorcycle accidents in the Gomoa East district. 3. Results 3.1. Preliminary Analysis In the preliminary analysis, descriptive statistics were used to provide an overview of the demographic characteristics of the participants. Following this, the Pearson Chi-Square test was conducted to evaluate the relationship between each contributing factor and motorcycle accidents. The study gathered responses from 115 participants who fully completed the structured questionnaire, achieving a 100% response rate due to the accessibility of the entire target population. Table 1 Demographic Characteristics of Respondents Variables Frequency (n) Percentage (%) Gender Male 97 84.3 Female 18 15.7 Age 15 – 25 13 11.3 World Journal of Advanced Research and Reviews, 2025, 26(02), 3054-3067 3057 26 – 35 66 57.4 36 – 45 23 20 46 – 55 9 7.8 55 and above 4 3.5 Level of Education Basic 28 24.3 Secondary 64 55.7 Tertiary 19 16.5 None 4 3.5 Marital Status Married 39 33.9 Divorced 6 5.2 Single 68 59.1 Separated 2 1.7 Employment Status Government employee 26 22.6 Self-employed 70 60.9 Unemployed 10 8.7 Student 9 7.8 Weight 40 - 60kg 28 24.3 61 - 80kg 54 47 81 - 100kg 32 27.8 Above 100kg 1 0.9 Source: Field survey (2024) Table 1 shows the demographic characteristics of the participants in this study. The findings indicate that the majority (84.3%) of respondents were male, while females constituted 15.7%. In terms of age distribution, 57.4% of participants were aged between 26 and 35 years, with only 3.5% being over 40 years old. Regarding education, 55.7% had completed secondary education, 16.5% had attained tertiary education, and 3.5% had no formal education. Marital status revealed that 59.1% of respondents were single, while 1.7% were separated. For employment status, 60.9% were self-employed, and 7.8% were students. Concerning weight, the majority (47%) fell within the 61–80 kg range, while only 0.9% weighed over 100 kg. Table 2 Respondent Knowledge about Motorcycle Usage Variables Frequency (n) Percentage (%) Riding experience Less than six months 12 10.4 1 - 5 years 41 35.7 6 - 10 years 45 39.1 More than 10 years 17 14.8 World Journal of Advanced Research and Reviews, 2025, 26(02), 3054-3067 3058 License to ride Yes 68 59.1 No 47 40.9 Helmet usage Never 16 13.9 Sometimes 41 35.9 Always 58 50.4 Motorcycle insurance Yes 76 66.1 No 39 33.9 Maintenance frequency Never 1 0.9 Monthly 58 50.4 Every three months 36 31.3 Every six months 20 17.4 Adherence to speed limit Yes 88 76.5 No 27 23.5 Source: Field survey (2024) The results shown in Table 2 reveal that most respondents (39.1%) had 6–10 years of riding experience, while 10.4% had less than six months of experience. Approximately 68% of participants possessed a valid motorcycle license, whereas 47% did not have one. The study also found that 50.4% of respondents regularly wore helmets while riding, while a smaller group (16%) reported never using a helmet. Regarding motorcycle insurance, 66.1% had insured their motorcycles, while 39% had not secured insurance coverage. About 50.4% of participants stated that they serviced their motorcycles monthly, with only 0.9% indicating they never did so. Additionally, the majority (88%) reported adhering to speed limits, while 27% admitted to not following speed regulations while riding. 3.2. Respondent Involvement in Motorcycle Accident Figure 1 Respondent Involvement in Motorcycle Accident World Journal of Advanced Research and Reviews, 2025, 26(02), 3054-3067 3059 Figure 1 depicts the respondents' experiences with motorcycle accidents. The findings reveal that approximately 87% reported having been involved in a motorcycle accident, while the remaining 13% indicated they had never experienced one. Table 3 Nature of Motorcycle Accident Variables Frequency (n) Percentage (%) Collision with another motorcycle/car 19 16.5 Loss of control 42 36.5 Knocked down a pedestrian 44 38.3 Mechanical fault 10 8.7 Total 115 100.0 Source: Field survey (2024) Table 3 highlights the common types of motorcycle accidents observed in this study. About 16.5% of accidents in the Gomoa East district were due to collisions with other motorcycles or cars, while 36.5% were caused by a loss of control. Additionally, 38.3% of the incidents involved motorcycle riders hitting pedestrians, and 8.7% were attributed to mechanical failures. Notably, the majority of motorcycle accidents in the district were linked to riders colliding with pedestrians. Table 4 Economic and Social Effect of Motorcycle Accident Variables Frequency (n) Percentage (%) Have you lost any property Yes 55 47.8 No 60 52.2 Cost of treatment after accident Less than 250 cedis 41 35.7 250 - 450 cedis 52 45.2 451 - 650 cedis 14 12.2 Above 650 cedis 8 7 Unemployed as a result of accident Yes 10 8.7 No 105 91.3 Are able to carry out your economic activities after the accident Yes 109 94.8 No 2 1.7 Some of them 4 3.5 Did the insurance covered the cost of treatment Yes 109 94.8 No 2 1.7 Some of them 4 3.5 Source: Field survey (2024) World Journal of Advanced Research and Reviews, 2025, 26(02), 3054-3067 3060 Table 4 outlines the economic and social impacts of motorcycle accidents on the respondents. Around 52.2% reported no property loss because of motorcycle accidents, while 47.8% acknowledged experiencing property damage. Approximately 45.2% of those involved in accidents incurred expenses ranging from 250 to 450 Ghana cedis, with 7.0% spending over 650 Ghana cedis. In terms of employment, 91.3% of respondents who had been in accidents remained employed, while 8.7% lost their jobs due to the incident. Additionally, 94.8% were able to resume their economic activities after the accident, whereas 1.7% could not. Furthermore, the majority (94.8%) indicated that their medical expenses were covered by insurance, while 1.7% had no insurance coverage for medical treatment, as their motorcycles were uninsured. Table 5 Association between Demographic Characteristics and Motorcycle Accident Variables Motorcycle Accident χ² p - value Yes No Gender Male 84(86.6) 13(13.4) 0.07 0.87 Female 16(88.9) 2(11.1) Age 15 – 25 12(92.3) 1(7.7) 26 – 35 57(86.9) 9(13.6) 36 – 45 19(82.6) 4(17.4) 1.362 <0.002* 46 – 55 8(88.9) 1(11.1) 55 and above 3(90.0) 1(10.0) Level of Education Basic 27(96.4) 1(3.6) Secondary 53(82.8) 11(17.2) 3.91 0.205 Tertiary 16(84.2) 3(15.8) None 3(90.0) 1(10.0) Marital Status Married 36(92.3) 3(7.7) Divorced 5(90.0) 1(10.0) 3.455 <0.037* Single 56(82.4) 12(17.6) Separated 1(50.0) 1(50.0) Employment Status Government employee 23(88.5) 3(11.5) Self-employed 59(84.3) 11(15.7) 1.924 <0.03* Unemployed 9(90.0) 1(10.0) Student 6(70.0) 2(30.0) Weight 40 - 60kg 26(92.9) 2(7.1) 61 – 80kg 46(85.2) 8(14.8) 1.347 <0.005* 81 - 100kg 27(87.1) 4(12.9) Above 100kg 1(50.0) 1(50.0) Significance level at (p<0.05) World Journal of Advanced Research and Reviews, 2025, 26(02), 3054-3067 3061 Table 5 shows the relationship between motorcycle accidents and the demographic characteristics of the respondents. The analysis revealed significant associations between motorcycle accidents and factors such as age, marital status, employment status, and weight (p<0.05). However, gender and educational level did not show a significant association with motorcycle accidents (p>0.05). Table 6 Association between Motorcycle Usage and Motorcycle Accident Variables Motorcycle Accident χ² p - value Yes No Riding experience Less than six months 11(91.7) 1(8.3) 1 - 5 years 37(90.2) 4(9.8) 1.539 <0.034* 6 - 10 years 37(82.2) 8(17.8) More than 10 years 15(88.2) 2(11.8) License to ride Yes 61(89.7) 7(10.3) 1.109 0.219 No 39(83) 8(17.0) Helmet usage Never 11(68.8) 5(31.3) Sometimes 37(90.2) 4(9.8) 5.439 <0.02* Always 52(89.7) 6(10.3) Motorcycle insurance Yes 68(89.5) 8(10.5) 1.252 <0.025* No 32(82.1) 7(17.9) Maintenance frequency Never 1(50.0) 1(50.0) Monthly 51(89.5) 6(10.5) 1.17 <0.005* Every three months 32(88.9) 4(11.1) Every six months 16(80.0) 4(20.0) Adherence to speed limit Yes 78(88.6) 10(11.4) 0.933 <0.02* No 22(81.5) 5(18.5) Speeding Yes 84(86.6) 13(13.4) 0.07 0.281 No 16(88.9) 2(11.1) Riding under the influence of alcohol Yes 46(90.2) 5(9.8) 0.848 <0.001* No 54(84.4) 10(15.6) Significance level at (p<0.05) World Journal of Advanced Research and Reviews, 2025, 26(02), 3054-3067 3062 Table 6 examines the relationship between motorcycle accidents and motorcycle usage. The findings indicate significant associations between motorcycle accidents and factors such as riding experience, helmet usage, motorcycle insurance, maintenance frequency, adherence to speed limits, and riding under the influence of alcohol (p<0.05). However, possessing a riding license and speeding were not significantly associated with motorcycle accidents (p>0.05). Consequently, non-significant factors were excluded, and the analysis proceeded with the remaining variables 3.3. Further Analysis Due to the dichotomous nature of the dependent variable, binary logistic regression analysis was carried out as an advanced analysis to investigate the effect of the predictor variables on the dependent variable. 3.4. Detecting Multicollinearity between explanatory variables One of the assumptions in logistic regression is that explanatory variables should not be highly correlated with each other. Therefore, before applying logistic regression, multicollinearity was checked among explanatory variables. Tolerance and VIF values were used to confirm multicollinearity, and the results were indicated in Table 7 below. Table 7 Collinearity Statistics Collinearity Statistics Model Tolerance (VIF) Gender 0.099 10.112 Age 0.821 1.217 Level of education 0.059 11.125 Marital status 0.06 10.105 Employment status 0.047 12.167 Weight 0.905 1.105 Riding license 0.046 15.766 Helmet usage 0.044 12.366 Maintenance frequency 0.817 1.299 Motorcycle insurance 0.043 16.299 Adherence to speed limit 0.921 1.218 Alcohol consumption 0.056 13.483 Riding under the influence of alcohol 0.869 1.495 Riding experience 0.948 1.336 Table 7 revealed that age, weight, maintenance frequency, adherence to speed limit, riding under the influence of alcohol and riding experience exhibit low variance inflation factors (VIFs) with their tolerance level closer to 1. This indicates that multicollinearity does not exist between these variables and other predictor variables. Hence, these variables can be included in the model. However, gender, level of education, marital status, employment status, possession of a riding license, helmet usage, motorcycle insurance, and alcohol consumption have high variance inflation factors (VIFs) with their tolerance level not closer to 1. This indicates the presence of severe multicollinearity between these variables and other predictor variables. Hence, these variables cannot be included in the final model due to the potential for unstable coefficient estimates and unreliable results. 3.5. Binary logistic regression analysis Given that the response variable is dichotomous, binary logistic regression model was utilized for the analysis. The parameters of the model were estimated using the maximum likelihood method. A forward stepwise selection approach was employed in the logistic regression analysis, with variables included based on the significance of the score statistic, set at p<0.05.