Abstract
Background:
Motorcycle injuries are a major cause of death in Cameroon and the burden is on the rise. Low Personal Protective Equipment (PPE) use, especially helmets, exacerbates the burden.
Objectives:
This study investigated PPE uptake and determinants among motorcyclists in the crisis-affected Limbe and Tiko Health Districts.
Materials and Methods:
A community-based cross-sectional study was conducted among 499 commercial motorcyclists aged 18 years and above in all 16 health areas of the Limbe and Tiko Health Districts, Cameroon. Participants were recruited through consecutive sampling at motorcycle pick-up points after obtaining ethical clearance from the University of Buea. Trained research assistants used structured questionnaires to collect data on socio-demographics, riding habits, and determinants of PPE uptake. An observational checklist was use to collect data on helmet use. The data were analyzed using descriptive statistics and logistic regression to identify factors influencing helmet use among the riders.
Results:
The mean age of the motorcyclists was 32.2 (and the standard deviation was 7.6) years. A total of 242 (48.5%) were within the age range 21–30 years and all the riders were males. The majority of riders were single, 261 (52.3%) and 291 (58.3%) had attended secondary school. The proportion of riders who reported not having a valid motorcycle license was 339 (67.9%). Among the 499 riders studied, 81.8% used long trousers, 30.1% used boots, and 28.6% used helmets. Only 22.7% used gloves and 14.8% used eye glasses. Factors independently associated with helmet use were Being married (aOR:1.81, 95%CI:0.34–7.42, p<0.005), owning a valid license (aOR:1.97, 95% CI:1.22–3.19, p = 0.006), being an internally displaced person (aOR:0.83, 95% CI:1.18–2.84, p = 0.007). Also, having good knowledge of PPE(aOR:3.01, 95%CI:1.60–5.65, p=0.001), and being trained on PPE (aOR:2.48, 95%CI:1.61–3.84, p=0.000) were significant factors.
Conclusions:
The uptake of PPE is low, highlighting the need for targeted interventions to improve PPE uptake among commercial motorcyclists. The identified determinants of helmet use can inform evidence-based strategies to enhance road safety and reduce the burden of motorcycle-related injuries in this at-risk population.
Keywords: Personal protective equipment, Cameroon, Commercial motorcycle riders, injury prevention
Background
Road traffic injuries (RTIs) remain a major public health concern globally, particularly in low- and middle-income countries (LMICs), where over 90% of road traffic deaths occur despite having only about 60% of the world’s vehicles[1]. In Cameroon, RTIs are among the leading causes of morbidity and mortality, especially among young adults[2]. According to the Ministry of Public Health, an estimated 6,000 to 7,000 motorcycle road traffic crashes are recorded annually, with over 1,200 deaths[3].
Motorcycle-related crashes account for a significant and increasing proportion of RTIs in Cameroon. Studies have shown that motorcycles are involved in approximately 40–60% of all road traffic crashes in urban and peri-urban settings[4]. Commercial motorcycle riders— commonly known as “bendskin” operators—are particularly vulnerable due to poor road conditions, risky riding behaviors, inadequate training, and non-compliance with safety regulations[5–7].
Despite the known benefits of helmet use in preventing head injuries and fatalities, adherence remains low[8]. A survey reported that less than 10% of commercial motorcycle riders in Cameroon regularly use helmets, with even lower compliance among passengers[8].
Cameroon has existing road safety legislation that mandates the use of helmets for both riders and passengers (Law No. 2008/011 of 10 July 2008). The law also prohibits riding without a valid license and requires the use of other personal protective equipment (PPE) such as reflective jackets for improved visibility. However, enforcement of these regulations is weak, with irregular monitoring and limited penalties for non-compliance[9]. The lack of consistent enforcement contributes to the low compliance rates observed in many communities. Several global studies have highlighted the importance of PPE in reducing the severity of injuries sustained in motorcycle crashes[10–12]. For instance, research indicates that helmet use can reduce the risk of head injuries by up to 69% and the risk of death by 42%[12]. However, the adoption of PPE is influenced by a range of factors such as socio-economic and cultural barriers[13].
Despite the proven benefits of PPE in enhancing rider safety and reducing fatalities, its usage among commercial motorcycle riders in Cameroon as a whole and Limbe and Tiko in particular remains suboptimal[10].
In response to the rising burden of RTIs involving motorcycles, it is crucial to assess current levels of PPE use and understand the barriers and facilitators to compliance with safety regulations. This study was therefore designed to fill critical gaps in evidence around PPE uptake and determinants among commercial motorcycle riders in Cameroon.
Materials And Methods
Study Area
The study was carried out in the Limbe and Tiko Health Districts of the South West Region of Cameroon for a period of three months. Both the Limbe and Tiko health districts are located in the Southwest Region of Cameroon which is one of the two regions affected by the current socio-political crisis. Limbe and Tiko serve as the headquarters of their respective districts and are known for their economic activities, including agriculture, commerce, and in the case of Limbe, tourism due to its coastal location and natural attractions such as the Limbe Botanic Garden and the Limbe Wildlife Centre.
The road networks in both districts are vital for transportation and commerce, with a significant presence of motorcycle riders. Given the importance of transportation and the potential risks associated with road traffic, conducting research on road traffic injuries prevention among motorcycle riders in the Limbe and Tiko Health Districts is essential for understanding and addressing public health and safety concerns in these areas.
Study Design
The study adopted a community-based cross-sectional design to determine the uptake of personal protective equipment and associated factors among commercial motorcycle riders in the crisis-affected Limbe and Tiko health districts.
Study Population
The target population included commercial motorcycle riders aged 18 years and above who have been operating within the Limbe and Tiko health districts for the past six months. These individuals are the primary focus due to their high exposure to road traffic risks and potential as beneficiaries of health education interventions. A total of 499 commercial motorcycle riders were included in the study.
Inclusion and Exclusion Criteria
Commercial motorcycle riders aged 18 years and above who have been operating in the Limbe or Tiko health districts for at least six months who gave their consent were included in the study while those who were unable to participate due to language barriers or health limitations were excluded.
Sampling Techniques
This study was conducted in the Limbe and Tiko Health Districts of Cameroon, purposively selected due to their high commercial motorcycle activity, relative stability amidst the ongoing crisis in the North West and South West Regions, and influx of internally displaced persons (IDPs), many of whom have taken up motorcycle riding for livelihood. This has significantly increased the number of riders in both districts, making them suitable for assessing PPE uptake in a high-risk, crisis-affected setting.
A multi-stage sampling approach was used. From a sampling frame of 132 major motorcycle pick-up points (98 in Limbe and 34 in Tiko), 80% were randomly selected—78 in Limbe and 27 in Tiko—giving 105 clusters. At each selected site, riders were recruited consecutively as they dropped off passengers, enabling direct observation of PPE use.
The sample size (n = 499) was calculated using Cochran’s formula for proportions, assuming 95% confidence, 50% prevalence, 5% margin of error, adjusted for a design effect of 1.3 and 5% non-response. The sample was proportionally distributed based on estimated rider populations— approximately 1,500 in Limbe and 700 in Tiko. Accordingly, 300 riders were recruited from Limbe and 199 from Tiko, ensuring fair representation across both districts. Each cluster’s allocation reflected its estimated rider volume.
This strategy ensured real-time observation and proportionate representation of riders across both districts.
Data Collection Tools and Procedures
Two structured tools were used to collect quantitative data in line with the study objectives. A direct observation checklist was used to assess the uptake of personal protective equipment (PPE) including helmets, reflective jackets, reflective strips, and headlamps, by observing riders as they arrived at designated pick-up points. An interviewer-administered structured questionnaire was used to collect data on socio-demographic characteristics, knowledge, attitudes, and other factors associated with PPE use, such as licensing status, alcohol consumption, IDP status, crash history, PPE training, and visibility material use.
Both tools were developed based on literature and validated through expert review. Face and content validity were assessed by a panel of three public health researchers with experience in road safety. Construct validity was ensured by aligning questionnaire items with theoretical constructs relevant to health behavior. The instruments were pre-tested among 30 riders in Mile 4 Limbe, a site similar to but not included in the study area. Modifications were made based on pre-test feedback. Reliability of the questionnaire was evaluated using Cronbach’s alpha, with a coefficient of 0.78, indicating acceptable internal consistency.
Data were collected using Kobo Collect, an open-source mobile data collection application developed by the Harvard Humanitarian Initiative. Kobo was selected for its ability to support real-time data capture, skip logic, offline functionality, encryption, and centralized data storage. The Kobo forms were created using the KoboToolbox web interface and deployed on Android devices.
A total of eight research assistants with at least a bachelor’s degree in health or social sciences were recruited. They received two days of training on the study tools, research ethics, Kobo use, and proper administration of the questionnaires and checklist. Interviews were conducted in English, with Pidgin English translations provided where necessary to ensure respondent understanding and data accuracy. This approach ensured systematic, valid, and reliable data collection.
Data Management and Analysis
Data collected via Kobo Collect were securely stored in a cloud-based database accessible only to the Principal Investigator (CEU). After data collection, the dataset was exported to SPSS version 26 for cleaning, coding, and analysis. While CEU managed database access, all co-authors participated in data review and interpretation.
Variables were coded appropriately (e.g., helmet use: 1 = Yes, 0 = No), and continuous variables were checked for outliers and normality. Descriptive statistics, including frequencies, percentages, means, and standard deviations, were used to summarize the data, and results were presented in tables and charts.
Simple logistic regression was used in bivariable analysis to examine associations between helmet use and independent variables. Variables with p < 0.2 were included in the multiple logistic regression (MLR) model to identify independent predictors of helmet use. Variables with a p-value <0.2 in bivariate analysis were considered for inclusion in the multivariable logistic regression model to ensure that potential confounders were not excluded prematurely, as recommended in epidemiological modeling guidelines[14,15]. The dependent variable was binary (helmet use: yes/no). Adjusted Odds Ratios (AORs) with 95% Confidence Intervals (CIs) and p-values were reported. Statistical significance was set at p < 0.05.
Ethical Considerations
Ethical Clearance was obtained from the Institutional Review Board of the Faculty of Health Sciences of the University of Buea (2024/2490-03/UB/SG/IRB/FHS). Participation was voluntary, and informed consent was sought from all respondents. Confidentiality and anonymity were maintained throughout the study. Administrative authorizations were obtained from the Department of Public Health of the University of Buea, South West Regional Delegation of Public Health and the District Health Services.
RESULTS
Socio-Demographic Variables of Commercial Motorcycle Riders
Regarding the socio-demographic characteristics of motorcycle riders (Table 1), 242 (48.5%) were within the age range 21–30 years and all the riders were males.
Table 1:
Socio-demographic variables of motorcycle riders
| Variable | Health Districts | |||
|---|---|---|---|---|
| Category | Limbe N (%) | Tiko N (%) | Total N (%) | |
| Age group (years) | 21–30 | 141(47) | 101(50.8) | 242(48.5) |
| 31–40 | 123(41) | 69(34.7) | 192(38.5) | |
| 41–50 | 33(11) | 24(12.1) | 57(11.4) | |
| 50+ | 3(1) | 5(2.5) | 8(1.6) | |
| Total | 300(100) | 199(100) | 499(100) | |
| Sex | Male | 300(100) | 199(100) | 499(100) |
| Total | 300(100) | 199(100) | 499(100) | |
| Marital status | Single | 145(48.3) | 116(58.3) | 261(52.3) |
| Married | 149(49.7) | 79(39.7) | 228(45.7) | |
| Divorced | 6(2) | 4(2) | 10(2) | |
| Total | 300(100) | 199(100) | 499(100) | |
| Highest level of education | No formal | 13(4.3) | 6(3) | 19(3.8) |
| Primary | 90(30) | 59(29.6) | 149(29.9) | |
| Secondary | 169(56.3) | 122(61.3) | 291(58.3) | |
| Tertiary | 28(9.3) | 12(6) | 40(8) | |
| Total | 300(100) | 199(100) | 499(100) | |
| Average monthly income from motorcycle riding (XAF. Note 1USD=600XAF) | <50000 | 10(3.3) | 10(5) | 20(4) |
| 50000–100000 | 169(56.3) | 101(50.8) | 270(54.1) | |
| 101000–150000 | 89(29.7) | 69(34.7) | 158(31.7) | |
| 150000+ | 32(10.7) | 19(9.5) | 51(10.2) | |
| Total | 300(100) | 199(100) | 499(100) | |
| 6. What do you think of the monthly income level | Insufficient | 101(33.7) | 119(59.8) | 220(44.1) |
| Sufficient | 180(60) | 79(39.7) | 259(51.9) | |
| Largely sufficient | 19(6.3) | 1(0.5) | 20(4) | |
| Total | 300(100) | 199(100) | 499(100) | |
| RIDINGDURATION | 1–5 | 188(62.7) | 120(60.3) | 308(61.7) |
| 11–15 | 25(8.3) | 20(10.1) | 45(9) | |
| 15+ | 11(3.7) | 9(4.5) | 20(4) | |
| 6–10 | 76(25.3) | 50(25.1) | 126(25.3) | |
| Total | 300(100) | 199(100) | 499(100) | |
| 8. Do you primary ride motorcycle in urban or rural areas? | Rural | 4(1.3) | 10(5) | 14(2.8) |
| Urban | 92(30.7) | 96(48.2) | 188(37.7) | |
| Both | 204(68) | 93(46.7) | 297(59.5) | |
| Total | 300(100) | 199(100) | 499(100) | |
| 9. Do you own the motorcycle you ride commercially? | No | 59(19.7) | 43(21.6) | 102(20.4) |
| Yes | 241(80.3) | 156(78.4) | 397(79.6) | |
| Total | 300(100) | 199(100) | 499(100) | |
| 10. Do you own a valid motorcycle riding license? | No | 176(58.7) | 163(81.9) | 339(67.9) |
| Yes | 124(41.3) | 36(18.1) | 160(32.1) | |
| Total | 300(100) | 199(100) | 499(100) | |
| 11. Do you smoke | No | 224(74.7) | 156(78.4) | 380(76.2) |
| Yes | 76(25.3) | 43(21.6) | 119(23.8) | |
| Total | 300(100) | 199(100) | 499(100) | |
| 12. Do you drink alcohol? | No | 90(30) | 68(34.2) | 158(31.7) |
| Yes | 210(70) | 131(65.8) | 341(68.3) | |
| Total | 300(100) | 199(100) | 499(100) | |
| 13. Are you an internally displaced person? | No | 171(57) | 143(71.9) | 314(62.9) |
| Yes | 129(43) | 56(28.1) | 185(37.1) | |
| Total | 300(100) | 199(100) | 499(100) | |
| Do you have any resting day in a week | No | 56(18.7) | 18(9) | 74(14.8) |
| Yes | 244(81.3) | 181(91) | 425(85.2) | |
| Total | 300(100) | 199(100) | 499(100) | |
| N=frequecy | ||||
The majority of riders were single, 261 (52.3%) and 291 (58.3%) had attended secondary school. The proportion of riders who reported not having a valid motorcycle license was 339 (67.9%).
Characteristics Related to Riding Behaviour of Motorcycle Riders
The majority of riders reported they had been involved in a road traffic crash, 341 (68.3% and 457 (91.6%) reported having near missed a road traffic crash. For compliance with traffic regulations, 375 (75.2%) reported that they obey traffic regulations and with respect to willingness to allocate money to buy vehicle maintenance equipment, most riders indicated they were willing, 447 (89.6%).
Personal Protective Equipment Use among Commercial Motorcycle riders by Direct Observation
Regarding direct observational report of personal protective equipment use by commercial motorcycle riders (Table 3), a total of 352 (70.5%) were not wearing helmet. Among 147 (29.5%) of riders observed wearing helmet, 101 (68.7%) helmets were securely fastened and 111 (75.5%) of their helmets overall condition were satisfactory. A total of 99 (67.3%) of the helmets were recommended type for riders. A total of 128 (25.7%) were observed wearing gloves and 66 (51.6%) of those wearing gloves had their hands covered by the gloves and 67 (52.3%) overall gloves conditions were satisfactory.
Table 3:
Direct observation of personal protective equipment use among commercial motorcycle riders
| Variable | Category | Frequency | Percentage |
|---|---|---|---|
| Rider wearing Helmet | No | 352 | 70.5 |
| Yes | 147 | 29.5 | |
| Total | 499 | 100 | |
| Helmet securely fastened | No | 46 | 31.3 |
| Yes | 101 | 68.7 | |
| Total | 147 | 100 | |
| Helmet condition (e.g no visible damage, intact straps) | Satisfactory | 111 | 75.5 |
| Unsatisfactory | 36 | 24.5 | |
| Total | 147 | 100 | |
| Helmet is recommended type (full-face or open-face helmets meeting visible quality standards (e.g., inner padding, chin strap) | No | 48 | 32.7 |
| Yes | 99 | 67.3 | |
| Total | 147 | 100 | |
| Rider wearing gloves | No | 371 | 74.3 |
| Yes | 128 | 25.7 | |
| Total | 499 | 100 | |
| Gloves cover hands and wrists adequately | No | 62 | 48.4 |
| Yes | 66 | 51.6 | |
| Total | 128 | 100 | |
| Gloves condition (e.g no holes, proper grip) | Satisfactory | 67 | 52.3 |
| Unsatisfactory | 61 | 47.7 | |
| Total | 128 | 100 | |
| Rider wearing long protective trouser | No | 91 | 18.2 |
| Yes | 408 | 81.8 | |
| Total | 499 | 100 | |
| Trouser cover legs adequately | No | 76 | 18.6 |
| Yes | 332 | 81.4 | |
| Total | 408 | 100 | |
| Trouser condition (e.g no tears, proper fit) | Satisfactory | 285 | 69.9 |
| Unsatisfactory | 123 | 30.1 | |
| Total | 408 | 100 | |
| Riders wearing eye glasses | No | 439 | 88.0 |
| Yes | 60 | 12.0 | |
| Total | 499 | 100 | |
| Eye glasses cover the eyes well | No | 19 | 31.7 |
| Yes | 41 | 68.3 | |
| Total | 60 | 100 | |
| Eye glasses condition | Satisfactory | 37 | 61.7 |
| Unsatisfactory | 23 | 38.3 | |
| Total | 60 | 100 | |
| Rider wearing shoes | No | 103 | 20.6 |
| Yes | 396 | 79.4 | |
| Total | 499 | 100 | |
| Shoes cover toes adequately | No | 88 | 22.2 |
| Yes | 308 | 77.8 | |
| Total | 396 | 100 | |
| Shoe condition | Satisfactory | 266 | 67.2 |
| Unsatisfactory | 130 | 32.8 | |
| Total | 396 | 100 |
Proportion of Uptake of the Different Personal Protective Equipment in the Two Health Districts
Relative to the proportion of uptake of the different personal protective equipment by commercial motorcycle riders in the two health districts (Figure 1), riders in the Limbe Health District were observed using helmet than those in the Tiko Health District.
Figure 1:
Uptake of the Different Personal Protective Equipment in the Limbe and Tiko Health Districts
Factors Associated with Helmet Use among Commercial Motorcycle Riders Factors Associated with Helmet Use in the Bivariate Analysis
At the bivariable level, we used simple logistic regression models to examine the unadjusted association between helmet use (binary dependent variable: 1 = Yes, 0 = No) and each independent variable. The results are presented in Table 4. A total of twelve variables were found to be significantly associated with helmet use. These included: age group 41–50 years (p < 0.005), being married (p < 0.001), having an average monthly income of XAF 100,000 or more (p < 0.012), and positive perception of income sufficiency (p < 0.002). Other significant predictors were driver’s license ownership (p < 0.001), internally displaced person (IDP) status (p < 0.011), adherence to road traffic regulations (p < 0.002), and use of visibility materials (p < 0.001). Additionally, riders who had received prior training on PPE (p < 0.001), had experienced a road traffic crash where PPE played a role in reducing injury (p < 0.001), and those with good knowledge (p < 0.001) and good practices (p < 0.001) related to PPE use were significantly more likely to use helmets. These associations were tested independently without adjusting for potential confounders, and all variables with p-values < 0.2 were considered for inclusion in the multivariable analysis to ensure that potential confounders were not excluded prematurely, as recommended in epidemiological modeling guidelines[14,15].
Table 4:
Factors associated with helmet use using simple logistic regression
| Helmet Use | AOR | 95%CI | |||||
|---|---|---|---|---|---|---|---|
| Variable | Category | No | Yes | Lower | Upper | p value | |
| Age group (years) | 50+ | 5(1.0) | 3(0.6) | 1.820 | 0.422 | 7.843 | 0.422 |
| 41–50 | 32(6.4) | 25(5.0) | 2.370 | 1.302 | 4.314 | 0.005 | |
| 31–40 | 133(26.7) | 59(11.8) | 1.346 | 0.881 | 2.055 | 0.169 | |
| 21–30 | 182(36.5) | 60(12.0 | 1 | ||||
| Divorced | 5(1.0) | 5(1.0) | 2.010 | 0.467 | 8.656 | 0.349 | |
| Married | 145(29.1) | 83(16.6) | 1.918 | 1.292 | 2.846 | 0.001 | |
| Single | 201(40.3) | 60(12.0) | 1 | ||||
| Education | Tertiary | 22(4.4) | 18(3.6) | 1.773 | 0.561 | 5.602 | 0.329 |
| Secondary | 215(43.1) | 76(15.2) | 0.766 | 0.281 | 2.086 | 0.602 | |
| Primary | 102(20.4) | 47(9.4) | 0.998 | 0.357 | 2.789 | 0.998 | |
| No formal | 13(2.6) | 6(1.2) | 1 | ||||
| Average monthly income (X1000FCFA) | 150+ | 28(5.6) | 23(4.6) | 7.393 | 1.551 | 35.235 | 0.012 |
| 101–150 | 102(20.4) | 56(11.2) | 4.941 | 1.106 | 22.074 | 0.036 | |
| 50–100 | 204(40.9) | 66(13.2) | 2.912 | 0.658 | 12.881 | 0.159 | |
| <50 | 18(3.6) | 6(0.4) | 1 | ||||
| Monthly income perception | Largely sufficient | 8(1.6) | 12(2.4) | 4.611 | 1.791 | 11.873 | 0.002 |
| Sufficient | 178(35.7) | 81(16.2) | 1.399 | 0.934 | 2.095 | 0.104 | |
| Insufficient | 166(33.3) | 54(10.8) | 1 | ||||
| Biker ownership | Self | 274(54.9) | 123(24.6) | 1.459 | 0.881 | 2.416 | 0.142 |
| Not self | 78(15.6) | 24(4.8) | 1 | ||||
| Own a license | Yes | 82(16.4) | 78(15.6) | 3.722 | 2.477 | 5.594 | <0.001 |
| No | 270(54.1) | 69(13.8) | 1 | ||||
| Smoke | Yes | 84(16.8) | 35(7.0) | 0.997 | 0.635 | 1.566 | 0.990 |
| No | 268(53.7) | 112(22.4) | 1 | ||||
| Drink alcohol | Yes | 246(49.3) | 95(19.0) | 0.787 | 0.524 | 1.183 | 0.250 |
| No | 106(21.2) | 52(10.4) | 1 | ||||
| Internally Displaced | Yes | 118(23.6) | 67(13.4) | 0.661 | 0.121 | 1.460 | 0.011 |
| No | 234(46.9) | 80(16.0) | 1 | ||||
| Riding hours daily | 16–20 | 32(6.4) | 21(4.2) | 1.543 | 0.820 | 2.902 | 0.179 |
| 11–15 | 186(37.3) | 69(13.8) | 0.872 | 0.576 | 1.321 | 0.518 | |
| 6–10 | 134(26.9) | 57(11.4) | 1 | ||||
| Involved in road traffic crash | Yes | 235(47.1) | 106(21.2) | 1.287 | 0.843 | 1.965 | 0.242 |
| No | 117(23.4) | 41(8.2) | 1 | ||||
| Obey traffic regulations | Yes | 251(50.3) | 124(24.8) | 2.169 | 1.314 | 3.582 | 0.002 |
| No | 101(20.2) | 23(4.6) | 1 | ||||
| Willing to allocate money to buy PPE | Yes | 309(61.9) | 138(27.7) | 2.134 | 1.012 | 4.499 | 0.046 |
| No | 43(8.6) | 9(1.8) | 1 | ||||
| Use visibility materials | Yes | 243(48.7) | 130(26.1) | 3.430 | 1.972 | 5.967 | <0.001 |
| No | 109(21.8) | 17(3.4) | 1 | ||||
| Trained on PPE | Yes | 85(17.0) | 74(14.8) | 3.184 | 2.124 | 4.775 | <0.001 |
| No | 267(53.5) | 73(14.6) | 1 | ||||
| Involved in a RTC where PPE played a role | Yes | 198(39.7) | 115(23.0) | 2.795 | 1.792 | 4.361 | <0.001 |
| No | 154(30.9) | 32(6.4) | 1 | ||||
| Knowledge on PPE | Good | 90(18.0) | 63(12.6) | 2.183 | 1.456 | 3.274 | <0.001 |
| Poor | 262(52.5) | 84(16.8) | 1 | ||||
| Attitudes toward PPE | Good | 89(17.8) | 41(8.2) | 1.143 | 0.741 | 1.763 | 0.545 |
| Poor | 263(52.7) | 106(21.2) | 1 | ||||
| Practices toward PPE | Good | 31(6.2) | 35(7.0) | 3.236 | 1.906 | 5.493 | <0.001 |
| Poor | 321(64.3) | 112(22.4) | 1 | ||||
Factors Independently Associated with Helmet Use
To determine factors independently associated with helmet use, we conducted multiple logistic regression (MLR) analysis using variables that had a p-value < 0.2 from the bivariable (simple logistic regression) analysis (Table 4). While simple logistic regression examined the unadjusted association between each independent variable and helmet use, the MLR model allowed us to adjust for potential confounders and assess the independent effect of each predictor on helmet use (Table 5). The outcome variable was binary (helmet use: 1 = Yes, 0 = No), and results were reported as Adjusted Odds Ratios (AORs) with 95% Confidence Intervals (CIs) and corresponding p-values.
Table 5:
Factors independently associated with helmet use using multiple logistic regression
| HELMET USE | 95%CI | ||||||
|---|---|---|---|---|---|---|---|
| Variable | Category | No | Yes | AOR | LCL | UCL | p value |
| Marital Status | Divorced | 5(1.0) | 5(1.0) | 1.59 | 0.34 | 7.42 | 0.558 |
| Married | 145(29.1) | 83(16.6) | 1.81 | 1.19 | 2.75 | 0.005 | |
| Single | 201(40.3) | 60(12.0) | 1 | ||||
| Owns a license | Yes | 82(16.4) | 78(15.6) | 1.97 | 1.22 | 3.19 | 0.006 |
| No | 270(54.1) | 69(13.8) | 1 | ||||
| Drink alcohol | Yes | 246(49.3) | 95(19.0) | 0.61 | 0.37 | 0.98 | 0.040 |
| No | 106(21.2) | 52(10.4) | 1 | ||||
| IDP | Yes | 118(23.6) | 67(13.4) | 0.83 | 0.18 | 2.84 | 0.007 |
| No | 234(46.9) | 80(16.0) | 1 | ||||
| Use visibility materials | Yes | 243(48.7) | 130(26.1) | 3.06 | 1.62 | 5.80 | 0.001 |
| No | 109(21.8) | 17(3.4) | 1 | ||||
| Involved in RTI and PPE played a role | Yes | 198(39.7) | 115(23.0) | 1.72 | 1.04 | 2.87 | 0.036 |
| No | 154(30.9) | 32(6.4) | 1 | ||||
| Knowledge of PPE | Good | 90(18.0) | 63(12.6) | 3.01 | 1.60 | 5.65 | 0.001 |
| Poor | 262(52.5) | 84(16.8) | 1 | ||||
| Trained on PPE | Yes | 85(17.0) | 74(14.8) | 2.48 | 1.61 | 3.84 | 0.000 |
| No | 267(53.5) | 73(14.6) | 1 | ||||
From the MLR analysis, eight factors were significantly associated with helmet use among commercial motorcycle riders. Riders who were married were nearly two times more likely to use helmets than those who were single (AOR = 1.81, 95% CI: 1.34–7.42, p = 0.005). Similarly, riders who owned a driver’s license were significantly more likely to use helmets compared to those without a license (AOR = 1.97, 95% CI: 1.22–3.19, p = 0.006). Riders who reported being internally displaced persons (IDPs) were less likely to use helmets (AOR = 0.83, 95% CI: 0.41–0.96, p = 0.007).
Additionally, commercial riders with good knowledge of PPE were three times more likely to use a helmet compared to those with poor knowledge (AOR = 3.01, 95% CI: 1.60–5.65, p = 0.001). Those who had received training on PPE were also significantly more likely to use helmets (AOR = 2.48, 95% CI: 1.61–3.84, p < 0.001). Use of visibility materials (AOR = 2.11, 95% CI: 1.38–3.24, p = 0.001), adherence to road traffic regulations (AOR = 1.56, 95% CI: 1.10–2.32, p = 0.018), and experience with road crashes where PPE played a role in reducing injury (AOR = 1.69, 95% CI: 1.12–2.55, p = 0.013) were also significant predictors.
Among these, the strongest independent determinants of helmet use were: Good knowledge of PPE, PPE training, Use of visibility materials, Driver’s license ownership.
Discussion
Uptake of Personal Protective Equipment Among Commercial Motorcycle Riders
The findings highlight significant gaps in PPE usage, particularly concerning helmet wear, which is crucial for reducing the risk of head injuries among motorcyclists[16].
This study documented a 29.5% helmet usage among motorcycle riders. Among the riders who were observed using helmets, only 68.7% of their helmets were securely fastened. The observation that 70.5% of riders were not wearing helmets is alarming and underscores a major public health concern. This implied that, a majority of commercial motorcycle riders are not protected in their head and therefore exposed to the risk of brain injury[16]. This finding aligns with previous studies conducted in Douala, Cameroon which reported 78.8% non-use of helmets among commercial motorcycle riders[17]. It is however different from the study in Tanzania where 73.3% reported consistent helmet usage[18]. These differences could be due to the fact that this study reported observed helmet use while the study findings of the study in Tanzania were reported by the riders themselves with a possibility of over reporting. Among the riders who did wear helmets in this study, only 68.7% had their helmets securely fastened, raising questions about the effectiveness of helmet use in protecting against injuries. This is consistent with a study in Tanzania which reported a 82.5% improperly fitted or damaged helmet use among motorcycle riders[18]. In contrast, a study in India found that 82.9% of helmet users used standard and secured helmets[19] suggesting that cultural attitudes toward helmet use may vary significantly across regions.
Furthermore, while 75.5% of the helmets were reported to be in satisfactory condition, only 67.3% were of the recommended type for riders. This indicates a potential lack of awareness or access to appropriate safety gear, which could be addressed through targeted educational campaigns and policy interventions. The proportion of riders who were observed using gloves in this study was 25.7%. Of those who were observed using gloves, only 51.6% of them had their hands adequately covered. The low uptake of gloves further emphasized the need for comprehensive safety measures. It is similar to the low glove use that was reported by Afelumo and his colleagues among motorcycle riders in Nigeria where 38.8% of riders was reported using gloves[20]. This was however lower than the proportion reported by a study in Kenya by Franklin and his colleagues in 2023 where 64.2% glove use was documented among motorcycle riders[21]. Among those who wore gloves in this study, only 51.6% had their hands adequately covered, and just over half (52.3%) reported satisfactory glove conditions. This suggests that while some riders recognize the importance of hand protection, many do not adhere to proper usage guidelines or may lack access to quality gloves.
In contrast, a majority of riders (81.8%) were observed wearing long protective trousers, with 81.4% having their legs adequately covered. This suggests a higher level of compliance with trouser use compared to other forms of PPE. A similar trend was noted in a study in Kenya, where 85.1% of motorcycle riders wore long trousers[22]. However, it is concerning that only 69.9% of these trousers were in satisfactory condition, indicating the need for an educational intervention and possibly regulations regarding the quality and maintenance of protective clothing among motorcycle riders.
The use of eyeglasses was notably low, with only 12.0% of riders observed wearing them. Among those who wore eyeglasses, 68.3% had their eyes adequately protected, but only 61.7% of eyeglasses were in satisfactory condition. This indicates a significant gap in eye protection that could lead to increased risk of injury from environmental factors such as dust, debris, insects, and UV exposure during riding. The findings of this study that only 12.0% of riders used protective eye wears is consistent with the 9.2% compliance reported in Ghana by Hagan and his colleagues in 2021[23].
Factors Associated with Helmet Use
Factors found significantly associated with helmet use among commercial motorcycle riders were: marital status, licensing status, alcohol consumption, internally displaced persons, visibility material use, experience with road traffic crash, knowledge and training on PPE.
The results indicated that married commercial motorcycle riders were approximately two times more likely to wear helmets compared to their single counterparts. This finding is consistent with previous research suggesting that marital status can influence safety behaviors[24]. For instance, a study conducted in Ghana found that married riders exhibited higher compliance with helmet use, potentially due to increased responsibility towards family members and a greater desire to ensure personal safety[24].
The association between helmet use and possession of a motorcycle license is noteworthy, with licensed riders being nearly two times more likely to wear helmets compared to those without a license. This finding aligns with studies in other contexts, such as in Ghana and Ethiopia, where licensed riders demonstrated higher compliance with safety regulations, likely due to formal training and awareness of traffic laws and the protective effect of PPE[24,25].
Conversely, the study found that riders who consumed alcohol were 39% less likely to wear helmet as compared to their non-alcohol consumption counterparts. This relationship highlights a critical public health concern, as alcohol consumption has been consistently linked to risky behaviors among motorcyclists, including reduced helmet use and increased road traffic crashes rates[26,27]. The finding that internally displaced persons were about 17% less likely to use helmets sheds light on the unique challenges faced by this population. IDPs may experience increased vulnerability due to socioeconomic instability and lack of access to resources, including safety equipment.
The study found that good knowledge of PPE was associated with a threefold increase in helmet use while riders who received training on PPE were about 2.5 times more likely to wear helmets. These findings underscore the critical role of education and awareness in promoting helmet use. Previous studies have demonstrated that targeted educational interventions can significantly improve knowledge and compliance regarding helmet use among motorcyclists[28]. Therefore, implementing community-based training programs focused on the importance of PPE could lead to improved safety outcomes.
Conclusion
The findings indicated that a substantial majority of riders were not wearing helmets, highlighting a critical area for intervention. Factors such as marital status, licensing, alcohol consumption, and previous experiences with road traffic incidents were found to significantly influence helmet use.
Table 2:
Riding Behaviour Characteristics of motorcycle riders
| Variable | Category | Frequency | Percentage |
|---|---|---|---|
| Daily riding hours | 6–10 | 191 | 38.3 |
| 11–15 | 255 | 51.1 | |
| 16–20 | 53 | 10.6 | |
| Total | 499 | 100 | |
| Riding frequency in the night | Frequently | 108 | 21.6 |
| Never | 133 | 26.7 | |
| Occasionally | 151 | 30.3 | |
| Rarely | 107 | 21.4 | |
| Total | 499 | 100 | |
| Have been involved in a road traffic crash | No | 158 | 31.7 |
| Yes | 341 | 68.3 | |
| Total | 499 | 100 | |
| Has almost missed a road traffic crash | No | 42 | 8.4 |
| Yes | 457 | 91.6 | |
| Total | 499 | 100 | |
| Obey traffic regulations when riding | No | 124 | 24.8 |
| Yes | 375 | 75.2 | |
| Total | 499 | 100 | |
| Will to allocate money to buy VM | No | 52 | 10.4 |
| Yes | 447 | 89.6 | |
| Total | 499 | 100 | |
| Willing to allocate money to buy PPE | No | 85 | 17.0 |
| Yes | 414 | 83.0 | |
| Total | 499 | 100 |
1. What is already known on this topic.
Commercial motorcycle riders are at high risk of road traffic injuries, particularly in low- and middle-income countries where enforcement of road safety regulations is weak. Previous studies have identified low usage of personal protective equipment (PPE) among riders, but there is limited evidence on the factors influencing PPE uptake in semi-urban African settings. Understanding these factors is critical to designing effective interventions.
2. What this study adds.
This study provides empirical evidence on the current level of PPE use among commercial motorcycle riders in two health districts in Cameroon and identifies key determinants influencing uptake. This study highlights that the uptake of helmets and other protective gear remains low among commercial motorcycle riders in the study setting. Factors such as ownership status of the motorcycle, previous road traffic injury experience, and participation in road safety education significantly influence PPE use.
3. How might this study affect research, practice, or policy.
The findings offer a strong foundation for developing targeted road safety interventions, such as promoting safety education and incentivizing PPE use among commercial riders. Policymakers and road safety advocates can use this evidence to support more comprehensive PPE policies and improve enforcement strategies in similar contexts. The study also opens avenues for further research into context-specific behavioural drivers and intervention effectiveness.
Funding
This work was supported by the Fogarty International Center of the National Institutes of Health under Award Number D43TW012186.
Footnotes
Patient and Public Involvement Statement
Patients and the public were not involved in the design, conduct, reporting, or dissemination of this research. However, key stakeholders such as motorcycle union leaders and local health officers were consulted during the planning and data collection phases.
Competing interests:
The authors declare that they have no competing interests.
Ethical Considerations
Ethical clearance for this study was obtained from the Institutional Review Board of the Faculty of Health Sciences, University of Buea (Reference Number: 2024/2490-03/UB/SG/IRB/FHS). Administrative authorizations were also obtained from the Department of Public Health, University of Buea; the South West Regional Delegation of Public Health; and the District Health Services of Limbe and Tiko. Participation in the study was entirely voluntary. Written informed consent was obtained from all respondents prior to data collection. Confidentiality and anonymity were strictly maintained throughout the research process.
References
- 1.Road traffic injuries [Internet].
- 2.Ngekeng S, Oke R, Yost M, Dissak-Delon F, Hubbard A, McCoy SI, Christie A, Shoptaw S, Chichom-Mefire A, Juillard C. Prevalence and factors associated with alcohol-related road traffic injuries in Cameroon. Journal of surgical research. 2024;302:116–24. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 3.Abdi N, Robertson T, Petrucka P, Crizzle AM. Do motorcycle helmets reduce road traffic injuries, hospitalizations and mortalities in low and lower-middle income countries in Africa? A systematic review and meta-analysis. BMC public health. 2022;22(1):824. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 4.Ngaroua D, Neossi NM, Amvene JM, Mefire AC, Eloundou NJ. Epidemiology and pattern of road traffic injuries in Ngaoundéré, Cameroon: a retrospective hospital based study prior to the implementation of a formal trauma registry. HEALTH SCIENCES AND DISEASE. 2014;15(2). [Google Scholar]
- 5.Mukherjee D, Mitra S. Development of a systematic methodology to enhance the safety of vulnerable road users in developing countries. Transportation in developing economies. 2022;8(2):28. [Google Scholar]
- 6.Corgozinho MM, Montagner MÂ. Sociodemographic profile of motorcyclists and their vulnerabilities in traffic. Revista Brasileira de Medicina do Trabalho. 2022;20(2):262. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 7.Geary GM. Infrastructure Measures to Protect the Unrecognized Vulnerable Road User: Motorcyclists. Engineering Proceedings. 2023;36(1):36. [Google Scholar]
- 8.Wankie C, Al-Delaimy W, Stockman J, Alcaraz J, Shaffer R, Hill L. Prevalence of crashes and associated factors among commercial motorcycle riders in Bamenda, Cameroon. Journal of Transport & Health. 2021;20:100993. [Google Scholar]
- 9.Kwalar GI, Siysi VV, Asangbeng TE, Nguedia A. Knowledge and practice of road safety regulation by commercial motorbike riders in Douala-Cameroon. 2023;
- 10.Abdi N, Robertson T, Petrucka P, Crizzle AM. Do motorcycle helmets reduce road traffic injuries, hospitalizations and mortalities in low and lower-middle income countries in Africa? A systematic review and meta-analysis. BMC public health. 2022;22(1):824. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Perticone A, Barbani D, Baldanzini N. Enhancing rider safety through Personal Protective Equipment: investigating the influence of Powered Two-Wheeler styles on the performance of the Belted Safety Jacket. TRAFFIC INJURY PREVENTION. 2023;0–0.
- 12.Urréchaga EM, Kodadek LM, Bugaev N, Bauman ZM, Shah KH, Abdel Aziz H, Beckman MA, Reynolds JM, Soe-Lin H, Crandall ML, Rattan R. Full-face motorcycle helmets to reduce injury and death: A systematic review, meta-analysis, and practice management guideline from the Eastern Association for the Surgery of Trauma. The American Journal of Surgery. 2022;224(5):1238–46. [DOI] [PubMed] [Google Scholar]
- 13.Mohammadi E, Azadnajafabad S, Keykhaei M, Shakiba A, Meimand SE, Shabanan SH, Sharif PM, Asgardoon MH, Shafieian M, Ghodsi Z. Barriers and factors associated with the use of helmets by Motorcyclists: A scoping review. Accident Analysis & Prevention. 2022;171:106667. [DOI] [PubMed] [Google Scholar]
- 14.Bursac Z, Gauss CH, Williams DK, Hosmer DW. Purposeful selection of variables in logistic regression. Source Code for Biology and Medicine. 2008;3:17. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 15.Malhotra RK. Errors in the use of Multivariable Logistic Regression Analysis: An Empirical Analysis. Indian Journal of Community Medicine : Official Publication of Indian Association of Preventive & Social Medicine. 2020;45(4):560–2. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Høye A. Bicycle helmets–To wear or not to wear? A meta-analyses of the effects of bicycle helmets on injuries. Accident Analysis & Prevention. 2018;117:85–97. [DOI] [PubMed] [Google Scholar]
- 17.Kwalar GI, Verla VS, Tanue E, Assob J, Nsagha DS. Road safety regulations among commercial motorcyclists in Douala, Cameroon. Special J Public Heatlh Nutr Dietetics. 2022;2(2):1–12. [Google Scholar]
- 18.Nguyen T, Vissoci JRN, Joelson T, Pesambili M, Haglund M, Gerardo CJ, Mvungi M, Staton CA. Injury prevalence and safety habits of boda boda drivers in Moshi, Tanzania: A mixed methods study. PloS one. 2018;13(11):e0207570. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 19.Setty NKH, Sukumar GM, Majgi SM, Goel AD, Sharma PP, Anand MB. Prevalence and factors associated with effective helmet use among motorcyclists in Mysuru City of Southern India. Environmental Health and Preventive Medicine. 2020;25(1):47. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 20.Afelumo OL, Abiodun OP, Sanni FO. Prevalence of protective measures and accident among motorcycle riders with road safety compliance in a Nigerian semi-urban community. International Journal of Occupational Safety and Health. 2021;11(3):129–38. [Google Scholar]
- 21.Senaji FMA, Muhonja F, Maathai R. Association between Utilization of Personal Protective Equipment and Prevalence of Road Traffic Injuries amongst Motorcycle Users in Kibera Constituency, Nairobi County Kenya. 2023; [Google Scholar]
- 22.Senaji FMA, Muhonja F, Maathai R. Association between Utilization of Personal Protective Equipment and Prevalence of Road Traffic Injuries amongst Motorcycle Users in Kibera Constituency, Nairobi County Kenya. 2023; [Google Scholar]
- 23.Hagan D, Tarkang EE, Aku FY. Compliance of commercial motorcycle riders with road safety regulations in a peri-urban town of Ghana. PLoS one. 2021;16(3):e0246965. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 24.Aidoo EN, Bawa S, Amoako-Yirenkyi C. Prevalence rate of helmet use among motorcycle riders in Kumasi, Ghana. Traffic Injury Prevention. 2018; [DOI] [PubMed]
- 25.Bedru D, Teshome F, Kebede Y, Birhanu Z. Helmet wearing behavior where people often ride motorcycle in Ethiopia: A cross-sectional study. PLOS ONE. 2022;17(1):e0262683. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 26.Heydari ST, Vossoughi M, Akbarzadeh A, Lankarani KB, Sarikhani Y, Javanmardi K, Akbary A, Akbari M, Mahmoodi M, Shirazi MK. Prevalence and risk factors of alcohol and substance abuse among motorcycle drivers in Fars province, Iran. Chinese journal of traumatology. 2016;19(02):79–84. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Sarmiento JM, Gogineni A, Bernstein JN, Lee C, Lineen EB, Pust GD, Byers PM. Alcohol/illicit substance use in fatal motorcycle crashes. Journal of surgical research. 2020;256:243–50. [DOI] [PubMed] [Google Scholar]
- 28.Akaateba MA, Yakubu I, Akanbang BAA. Correlates and barriers associated with motorcycle helmet use in Wa, Ghana. Traffic injury prevention. 2015;16(8):809–17. [DOI] [PubMed] [Google Scholar]