Table 1 Characteristics of Studies included in Systematic Review

Sisimwo et al. 2014 [22]

Crash characteristics and injury patterns among commercial motorcycle users attending Kitale level IV district hospital, Kenya

Kenya

N = 384

Mean age of 30.7 years (range 3–80)

. 69.8% males; 30.2% females

Road Users: riders (45.1%), passengers (38.8%), pedestrians (15.9%)

Education: primary school (65.2%), secondary school (31.5%), college (3.3%)

Cross-Sectional

Victims of commercial motorcycle crashes at the Crash and Emergency department in Kitale level IV District Hospital in Trans-Nzoia Country

Data collected within 24 h of the motorcycle crash

Demographics

Crash mechanism, setting, road conditions, collision type, helmet use, road user type

Instruments: interviews,

questionnaire, patient’s file, medical history, clinical examination

Injury sustained, body region injured, Glasgow Coma Scale (GCS), radiological findings

Helmet Use and Injuries:

Head Injuries based on Helmet Use for Riders (χ² = 111.35, p < 0.001); 37.7% wore helmet; 62.3% did not wear helmet Helmet Users: 1.6% had a head injury and 98% did not

Non-Helmet Users: 85.6% had a head injury and 14% did not

Crash setting: highway (93.9%); rural roads (0.3%).

Crash mechanism: Motorcycle vs. vehicle (45.6%), Motorcycle vs motorcycle (23.4%), Motorcycle vs. Animal (18.5%), Motorcycle vs. bicycle (9.9%), Motorcycle vs. lone (0.5%), Motorcycle vs. tree/pole (0.5%)

Injury Severity based on Category of Road Users: Statistically significant (χ² = 129.94, p < 0.001)

1. Severe injuries: riders (29.3%); passengers (6.2%) and pedestrians (3.4%)

2. Moderate injuries: riders (63.5%); passengers (88.2%); pedestrians (42.4%)

3. Minor Injuries: riders (7.7%); passengers (5.6%); pedestrians (54.2%)

GCS: 64.7% patients with head injury had GSC scores between 9 and 12 (moderate injury); 7.8% were between 3 and 8 (severe injuries)

Hospitalization: 85.7% treated as in-patients; In those treated as outpatients, 73.1% had minor surgery and 63.8% had major surgery

Injuries: 40% head and neck; 39.9% lower body injury; 8.2% chest injury

Sisimwo et al. 2018 [22]

Epidemiology of head injuries and helmet use among motorcycle crash injury: a quantitative analysis from a local hospital in Western Kenya

Kenya

N = 341

Mean age of 31.0 ± 12.9

78.3% males; 21.7% females

Road Users: riders (49%), passengers (35%), pedestrians (16%)

Education:

primary school (62.5%), secondary school (34.9%), tertiary level (2.6%)

Cross-Sectional

Victims of commercial motorcycle crashes at the Crash and Emergency department in Kitale level IV District Hospital in Trans-Nzoia Country

Demographics

Crash mechanism, helmet use, road user, time of day, day of week, crash location

Instruments: Glasgow Coma Scale, interviews,

questionnaire, patient’s file, medical history, clinical examination, radiological findings

Injury sustained, type of Injury sustained, injury severity

Helmet Use: 28% wore a helmet, 72% did not

Helmet Use and Injuries: 27% had a head injury and 28% other injuries. Non-Helmet Users: 73% had a head injury and 72% other injuries. Use of helmet was protective of head injury (χ² = 55.78, p < 0.001)

Head Injuries by Road Users: riders - head injury (50%), passengers - head injury 50(35%), pedestrian - head injury 22(15%)

Being a motorcycle rider was significantly associated with head injuries (χ² = 80.66, p < 0.001)

Injuries based on age: 34.6% 20–29 years; 31.7% 30–39 years; 15.5% 10–19 years; 8.5% 40–49 years; 5.6% 50–59 years; 41% > 60 years

Crash Mechanism: (χ² = 97.97, p < 0.001); motorcycles vs vehicle (48.3%); motorcycles vs motorcycle (22.6%); motorcycles vs pedestrians (17%); motorcycle vs bicycle (9.4%); motorcycle vs animal (1.5%); motorcycle collision with poles and tress (0.6%); motorcycle vs lone (0.6%)

Time of Crash: 51% afternoon hours (12 pm-5:59 pm), 36.7% morning hours (7 am-11:59 am), 10.3% evening (6 pm-11:59 pm), 2% early morning hours (12 am- 6:59 am)

Day of Crash: 71.8% between Monday to Friday. Days with the highest number of injuries were Friday (16.1%) and Monday (15.8%)

Mogaka et al. 2011 [31]

Factors associated with severity of road traffic injuries, Thika, Kenya

Kenya

N = 300

n = 99 (vulnerable users); n = 54 (two-wheeled vehicle users Mean age of 32.4 years (range 3–75)

73% male

27% female Education: none (2%), post-secondary (15%), primary school (49%), secondary school (34%) Road Users: vehicle occupants (68%), two-wheel vehicle users (18%), pedestrians (15%)

Cross-sectional Crash & Emergency Department of Thika District Hospital.

Road traffic crash victims attending the hospital within 24 h of the road crash

Demographics

Helmet use, road users, day/time of crash, weather Instruments: questionnaires, interviews, clinical information from medical charts; info from police & medical staff

Glasgow Coma Scale, injury severity, body region injured

Injury Severity Score (ISS);ISS ≥ 9 (Severe) ISS < 9 (Non-Severe)

Injury Severity:

Severe Injury 44.6%; Non-Severe Injury 30.3%

Injury Type:: head & neck superficial injury (60.6%), head & neck laceration (4.0%), head & neck fracture (5.1%), head injury (11.1%), thorax & abdomen superficial injury (7.1%), thorax & abdomen fracture (9.1%), upper extremity soft tissue (13.1%), upper extremity fracture (9.1%), lower extremity soft tissue injuries (48.5%), lower extremity lacerations (4.0%), lower extremity fracture (32.3%) Crash Mechanism:: highway crash (80%), weekend crash (57.7%), rainy weather (12%), night time crash (33.3%), angled or head-on collisions (61%)

Saidi & Mutisto, 2013 [24]

Motorcycle injuries at a tertiary referral hospital in Kenya: injury patterns and outcome

Kenya

N = 205

Mean age of 30.8 ± 12.2 years old

Male (87.8%) Female (12.2%)

Education: primary (41.3%), secondary (39.5%), tertiary (11.6%)

Motorcycle road user: riders (67.8%), passengers (16.6%), pedestrians (15.1%)

Cross-sectional

All admissions due to motorcycle injuries; data collected from the admissions register of the Crash and Emergency Department at Kenyatta National Hospital

Inclusion criteria: motorcycle riders, passengers and pedestrians

Demographics

Road user, time of day, helmet use, reason for injury, mode of transport, treatment

Instruments: Abbreviated Injury Scale, Injury Severity Score, Trauma and Injury Severity Score, Glasgow Coma Scale

Injuries sustained, injury severity, outcome following treatment, length of hospital stay, cost of treatment, resources utilized, mortality at 2 weeks following admission

Helmet Use: 43% (50% of riders and 20% of passengers)

Injury Type: extremities (60.3%), head/neck (32.6%), head injuries (22.7%); femur fractures (18.7%), other lower limb fractures (24.1%), spine (1.97%); visceral (abdominal) injuries (1.97%); chest (0.99%); orbito-facial (3.9%); upper limb fractures/dislocations (3.9%); other injuries (5.4%); 16.3% of patients suffered multi-system injuries.

No significant difference in the pattern of predominant injuries sustained by motorcyclists and passengers

Head injuries sustained in 37.5% of riders or passengers who did not wear helmets compared to 13.5% in those who did (p = 0.049)

Hospitalization: 62% in hospital two-weeks following admission; 29% discharged; 9% died

Mortality: based on helmet use: p = 0.072; helmet users: 35 alive, 1 dead; non-helmet users: 41 alive; 8 dead

Scene of Crash: city road (29.6%) and residential areas/suburbs (70.4%)

Day of Crash: 65% of motorcycle collisions occurred during the day

Oginni et al. 2006 [32]

Motorcycle-related maxillofacial injuries among Nigerian intracity road users

Nigeria

N = 107

Mean age of 29.0 ± 12.5 (range 6–68)

Male (78%)

Female (22%)

Road Users:

riders (50.5%), passengers (37.4%), pedestrians (12.1%)

Cross-sectional

Two hospitals: patients presenting at the maxillofacial unit following a motor vehicle incident

Demographics

Context of crash, road user, helmet use

Instrument: questionnaire

Injury type, injury location

Helmet Use: 0%

Injury Type: 48.6% sustained isolated injuries whereas

51.4% had various combinations of injury, abrasion/contusion/hematoma (22.7%), mild laceration (26.9%), moderate laceration (31.9%), through-and-through laceration (11.8%), avulsion (1.7%)

Crash Mechanism: head-on collision with vehicle (19.6%), head-on collision with other objects (19.6%), rear collision (10.3%), falls (25.2%), collision with motorcycle (10.3%), others (15.0%)

Osifo et al. 2012 [25]

Pediatric Road Traffic Accident Deaths Presenting to a Nigerian Referral Center

Nigeria

N = 143

Mean age of 9.3 ± 5.2 (1–18)

Male (67%) Female (33%)

Retrospective cross-sectional

Pediatric road traffic crashes admitted to a Nigerian trauma and pediatric surgical center

Demographics

Cause of injury, mechanism of injury, helmet use

Injury type, mortality, duration of stay, clinical condition on arrival, resuscitation, treatment

Helmet Use: 35.6% wore a helmet; 64.4% did not

Injury Type: skin laceration/abrasion (35.7%), multiple blunt trauma (27.3%), skull fracture/cerebral injury (11.9), solid visceral rupture (8.4%), fractured bones (10.5%), spinal cord injury (0.7%), lung/heart confusion (5.6%)

Mortality: Of those using a helmet, 0% died and 35.6% were injured. Of those not wearing a helmet, 10.5% died and 89.5% were injured

Injury User: 42% were motorcycle users; 63.6% were pedestrians and 36.4% were passengers

Matheka et al. 2015 [33]

Road traffic injuries in Kenya: a survey of commercial motorcycle drivers

Kenya

N = 200

Mean age of 28.4 ± 6.6

Male (98%)

Female (2%)

Road users: motorcyclists (61.5%), bicyclists (35.5%), auto rickshaw riders (3%)

Cross-sectional

survey of commercial motorcycle taxis at 11 sites (convenience sampling)

Inclusion criteria: involved in a road traffic crash within the past 3 months

Vehicle type, time of crash, injury type, crash mechanism, safety measures used

Instrument: questionnaire

Injuries sustained

Helmet Use and Other Protective Gear: 4% wore a helmet only; 44% reported wearing more than one protective gear; 16% wore reflective clothing, 33% did not use any protective equipment

Those using protective equipment were 27% less likely to be injured

Injury Type: Cuts (14.5%), bruises (36%), fracture/dislocations (11%); concussion (1.5%); minor or no injuries (38%)

Time of Crash: 32.0% occurred during daytime, 22% in the morning, 29% at sunset and 17% at night

People injured at night 5x more likely to sustain an injury compared to daytime (OR 5.3, 95% CI 1.7–16.2, p < 0.01)

Type of Road: 36.6% on paved non-highway roads; 31.7% dirt road; 22.0% highway; 8.9% gravel; 0.8% parking lot

Oluwadiya et al. 2014 [34]

Vulnerability of motorcycle riders and co-riders to injuries in multi-occupant crashes

Nigeria

N = 181

Mean age of passengers (29.3)

Mean age of riders (32.0)

Males: (87%)

Females: (13%)

Cross-sectional

Patients with motorcycle injuries admitted to the emergency department over a one-year period

125 crashes; 229 patients were injured

37.6% of the crashes involved motorcycles carrying only the rider; 62.4% involved motorcycles with two or more occupants.

Demographics

Crash location, road user, number of riders/passengers, helmet use

Instrument: hospital intake form, interview with participant, medical records

Moderate and severe injuries were defined as ISS of 9–15 and ISS =/>  16, respectively

Injuries sustained, injury severity

Helmet use: Rider: Helmet 9.1%; Non-Helmet 90.9%

Co-Rider: Helmet 9.4%; Non-Helmet 90.6%

Injury Prevalence: 69.6% sustained injuries; 30.4% did not. Those with injuries were riders (42.1%) and co-riders (57.9%)

Of the 78 crashes involving 2 or more motorcycle occupants:

53.8% caused injuries to riders and passengers together

30.8% caused injuries to passengers alone

15.4% caused injuries to riders alone

A significantly higher percentage of females (p = .045) were also injured on > 2-occupant motorcycles (19.7%) compared to 2-occupant motorcycles (12.2%)

Injury Location:

Head (n = 36): Rider: 30.5%; Co-rider: 69.5%

Face (n = 34): Rider: 50.0%; Co-rider: 50.0%

Chest (n = 8): Rider: 62.5%; Co-rider: 37.5%

Abdomen (n = 2): Rider: 50.0%; Co-rider: 50.0%

Extremities (n = 80): Rider: 31.3%; Co-rider: 68.7%

External (n = 41): Rider: 53.7%; Co-rider: 46.3%

Injury Severity:

moderate injury (co-riders 90.4%; riders 100%)

severe injury (co-riders 9.6%; riders 0%)