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Table 1 Characteristics of Studies included in Systematic Review

From: 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

Article (title, author(s), year, and location) Sample Characteristics Study Design (inclusion/exclusion criteria) Independent Variable (including instrument) Outcome Variable Results
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%)