| Literature DB >> 28512475 |
Edrisa Sanyang1,2, Corinne Peek-Asa2, Paul Bass1, Tracy L Young2, Babanding Daffeh3, Laurence J Fuortes4.
Abstract
We identified risk factors for road traffic injuries among road users who received treatment at two major trauma hospitals in urban Gambia. The study includes pedestrians, bicyclists, motorcyclists, and drivers/passengers of cars and trucks. We examined distributions of injury by age, gender, collision vehicle types and vehicle category, and driver and environment factors. Two hundred and fifty-four patients were included in the study. Two-thirds were male and one-third female. Two-thirds (67%) of road traffic injuries involved pedestrians, bicyclists, and motorcyclists; and these were more common during weekdays (74%) than weekends. Nearly half (47%) of road traffic injuries involved pedestrians. One-third (34%) of injured patients were students (mean age of students was less than 14 years), more than half (51%) of whom were injured on the roadway as pedestrians. Head/skull injuries were common. Concussion/brain injuries were 3.5 times higher among pedestrians, bicyclists, and motorcyclists than vehicle occupants. Crashes involving pedestrians were more likely to involve young people (<25 years; aOR 6.36, 95% CI: 3.32-12.17) and involve being struck by a motor car (aOR 3.95, 95% CI: 2.09-7.47). Pedestrians contribute the largest proportion of hospitalizations in the Gambia. Young pedestrians are at particularly high risk. Prevention efforts should focus on not only vehicle and driver factors, but also protecting pedestrians, bicyclists, and motorcyclists.Entities:
Mesh:
Year: 2017 PMID: 28512475 PMCID: PMC5420414 DOI: 10.1155/2017/8612953
Source DB: PubMed Journal: J Environ Public Health ISSN: 1687-9805
Figure 1Map of the Gambia showing location of study hospitals.
Patient demographics by road user type1.
| Factors | Total2 | Pedestrian | Bicyclist/motorcyclist | In-vehicle occupant | ||||
|---|---|---|---|---|---|---|---|---|
|
| (%) |
| (%) |
| (%) |
| (%) | |
|
| 254 | (100.0) | 118 | (46.5) | 52 | (20.5) | 79 | (31.1) |
|
| ||||||||
| Age (years) | ||||||||
| <25 | 127 | (52.0) | 85 | (73.3) | 15 | (29.4) | 26 | (34.7) |
| >25 | 117 | (48.0) | 31 | (26.7) | 36 | (70.6) | 49 | (65.3) |
| Gender | ||||||||
| Male | 169 | (67.6) | 74 | (62.7) | 49 | (94.2) | 45 | (57.7) |
| Female | 81 | (32.4) | 44 | (37.3) | 3 | (5.8) | 33 | (42.3) |
| Occupation | ||||||||
| Skilled | 42 | (17.4) | 12 | (10.5) | 12 | (24.0) | 18 | (23.7) |
| Professional | 44 | (18.2) | 11 | (9.6) | 15 | (30.0) | 18 | (23.7) |
| Unskilled | 14 | (5.8) | 3 | (2.6) | 5 | (10.0) | 6 | (7.9) |
| Student | 82 | (33.9) | 58 | (50.9) | 12 | (24.0) | 12 | (15.8) |
| Other | 56 | (23.1) | 30 | (26.3) | 6 | (12.0) | 18 | (23.7) |
| Missing | 4 | (1.7) | 0 | (0.0) | 0 | (0.0) | 4 | (5.3) |
1Road user type: “Other” was not depicted as separate column in table due to small number (n = 2; 0.78% of total) yet is included in total column.
2Numbers may not add to 254 due to missing data.
Crash/environment and driver/vehicle factors by road user type1.
| Factors | Total2 | Pedestrian | Bicyclist/motorcyclist | In-vehicle occupant | ||||
|---|---|---|---|---|---|---|---|---|
|
| (%) |
| (%) |
| (%) |
| (%) | |
| Total ( | 254 | (100.0) | 118 | (46.5) | 52 | (20.5) | 79 | (31.1) |
|
| ||||||||
|
| ||||||||
| Day of week | ||||||||
| Weekend | 65 | (25.9) | 23 | (19.5) | 15 | (28.8) | 27 | (34.2) |
| Weekday | 186 | (74.1) | 95 | (80.5) | 37 | (71.2) | 52 | (65.8) |
| Time of day | ||||||||
| 12:00–5:59 AM | 14 | (5.6) | 5 | (4.2) | 2 | (3.8) | 7 | (8.9) |
| 6:00–11:59 AM | 77 | (30.7) | 32 | (27.1) | 13 | (25.0) | 30 | (38.0) |
| 12:00–5:59 PM | 100 | (39.8) | 56 | (47.5) | 24 | (46.2) | 20 | (25.3) |
| 6:00–11:59 PM | 60 | (23.9) | 25 | (21.2) | 13 | (25.0) | 22 | (27.8) |
| Season | ||||||||
| Dry | 183 | (72.9) | 75 | (63.6) | 43 | (82.7) | 64 | (81.0) |
| Rainy | 68 | (27.1) | 43 | (36.4) | 9 | (17.3) | 15 | (19.0) |
| Poor visibility | ||||||||
| No | 182 | (72.5) | 86 | (72.9) | 34 | (65.4) | 60 | (75.9) |
| Yes | 69 | (27.5) | 32 | (27.1) | 18 | (34.6) | 19 | (24.1) |
| Collision vehicle type | ||||||||
| Motor car | 112 | (44.6) | 74 | (62.7) | 18 | (34.6) | 19 | (24.1) |
| Van | 36 | (14.3) | 17 | (14.4) | 1 | (1.9) | 18 | (22.8) |
| Mini bus | 25 | (10.0) | 5 | (4.2) | 1 | (1.9) | 18 | (22.8) |
| Pickup | 15 | (6.0) | 4 | (3.4) | 3 | (5.8) | 8 | (10.1) |
| Truck/truck trailer | 21 | (8.4) | 3 | (2.5) | 2 | (3.8) | 16 | (20.3) |
| Motorcycle | 31 | (12.4) | 11 | (9.3) | 20 | (38.5) | 0 | (0.0) |
| Other/unknown | 11 | (4.4) | 4 | (3.4) | 7 | (13.5) | 0 | (0.0) |
| Collision vehicle category | ||||||||
| Private | 101 | (41.1) | 60 | (52.2) | 23 | (46.0) | 18 | (22.8) |
| Commercial | 125 | (50.8) | 50 | (43.5) | 18 | (36.0) | 55 | (69.6) |
| Other/unknown | 20 | (8.1) | 5 | (4.3) | 9 | (18.0) | 6 | (7.6) |
|
| ||||||||
|
| ||||||||
| Drug/alcohol influence | ||||||||
| No | 246 | (98.0) | 118 | (100.0) | 51 | (98.1) | 75 | (94.9) |
| Yes | 5 | (2.0) | 0 | (0.0) | 1 | (1.9) | 4 | (5.1) |
| Speeding | ||||||||
| No | 52 | (20.7) | 21 | (17.8) | 12 | (23.1) | 19 | (24.1) |
| Yes | 199 | (79.3) | 97 | (82.2) | 40 | (76.9) | 60 | (75.9) |
| Brake failure | ||||||||
| No | 206 | (82.1) | 92 | (78.0) | 46 | (88.5) | 68 | (86.1) |
| Yes | 45 | (17.9) | 26 | (22.0) | 6 | (11.5) | 11 | (13.9) |
| Burst tire | ||||||||
| No | 232 | (92.4) | 118 | (100.0) | 50 | (96.2) | 63 | (79.7) |
| Yes | 19 | (7.6) | 0 | (0.0) | 2 | (3.8) | 16 | (20.3) |
1Road user type: “Other” was not depicted as separate column in table due to small number (n = 2; 0.78% of total) yet is included in total column.
2Numbers may not add to 254 due to missing data.
Injury characteristics by road user type.
| Factors | Total1 | Pedestrian | Bicyclist/motorcyclist | In-vehicle occupant | ||||
|---|---|---|---|---|---|---|---|---|
|
| (%) |
| (%) |
| (%) |
| (%) | |
| Total ( | 254 | (100.0) | 118 | (46.5) | 52 | (20.5) | 79 | (31.1) |
|
| ||||||||
| Primary nature of injury3 | ||||||||
| Soft tissue (open wound/abrasion/contusion) | 94 | (37.5) | 42 | (35.6) | 23 | (44.2) | 29 | (36.7) |
| Fracture | 88 | (35.1) | 43 | (36.4) | 19 | (36.5) | 26 | (32.9) |
| Dislocation/sprain/strain | 13 | (5.2) | 4 | (3.4) | 2 | (3.8) | 7 | (8.9) |
| Concussion/brain injury | 42 | (16.7) | 26 | (22.0) | 6 | (11.5) | 9 | (11.4) |
| Other/unknown | 14 | (5.6) | 3 | (2.5) | 2 | (3.8) | 8 | (10.1) |
| Primary body part | ||||||||
| Head/skull | 74 | (29.5) | 46 | (39.0) | 10 | (19.2) | 17 | (21.5) |
| Face/neck | 33 | (13.1) | 9 | (7.6) | 11 | (21.2) | 13 | (16.5) |
| Thorax/lumbar spine/abdomen | 10 | (4.0) | 5 | (4.2) | 1 | (1.9) | 4 | (5.1) |
| Lower extremity/pelvis/hip | 96 | (38.2) | 50 | (42.4) | 21 | (40.4) | 24 | (30.4) |
| Upper extremity | 29 | (11.6) | 5 | (4.2) | 7 | (13.5) | 17 | (21.5) |
| Multiple body parts | 8 | (3.2) | 3 | (2.5) | 2 | (3.8) | 3 | (3.8) |
| Other/unknown | 1 | (0.4) | 0 | (0.0) | 0 | (0.0) | 1 | (1.3) |
| Multiple injuries3 | ||||||||
| Yes | 55 | (21.9) | 29 | (24.6) | 11 | (21.2) | 15 | (19.0) |
| No | 196 | (78.1) | 89 | (75.4) | 41 | (78.8) | 64 | (81.0) |
1Numbers may not add to 254 due to missing data.
2Road user type: “Other” was not depicted as separate column in table due to small number (n = 5; 2% of total) yet is included in “Total” column.
3Primary nature of injury: these variables are not mutually exclusive but are the most prevalent injury reported by the patients.
Predictors of crash/injury by road user type1,2.
| Covariates | Total3 | Pedestrians versus all other road users | Motorcyclist/bicyclists versus all other road users | Vehicle occupants versus all other road users | |||||||||
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Crude | Adjusted | Crude | Adjusted | Crude | Adjusted | ||||||||
| OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | OR | 95% CI | ||
| Age (years) | |||||||||||||
| <25 | 132 | 5.38 | 3.12–9.26 | 6.36 | 3.32–12.17 | 0.29 | 0.15–0.57 | 0.24 | 0.1–0.52 | 0.38 | 0.22–0.67 | 0.36 | 0.19–0.69 |
| 25+ | 118 | Ref | NA | Ref | NA | Ref | NA | Ref | NA | Ref | NA | Ref | NA |
| Day of week | |||||||||||||
| Weekday | 133 | Ref | NA | Ref | NA | Ref | NA | NA3 | NA3 | Ref | NA | NA3 | NA3 |
| Weekend | 118 | 0.53 | 0.29–0.94 | 0.34 | 0.16–0.71 | 1.21 | 0.61–2.39 | NA3 | NA3 | 1.8 | 1.02–3.3 | NA3 | NA3 |
| Collision vehicle type | |||||||||||||
| Motor car | 118 | 4.2 | 2.48–7.14 | 3.95 | 2.09–7.47 | 0.6 | 0.31–1.12 | NA3 | NA3 | 3.6 | 1.95–6.74 | 0.24 | 0.12–0.47 |
| Other | 133 | Ref | NA | Ref | NA | Ref | NA | NA3 | NA3 | Ref | NA | Ref | NA |
| Collision vehicle category4 | |||||||||||||
| Commercial | 110 | 0.46 | 0.27–0.78 | 0.43 | 0.22–0.82 | NA3 | NA3 | 0.55 | 0.27–1.12 | NA3 | NA3 | 3.7 | 1.81–7.6 |
| Private | 116 | Ref | NA | Ref | NA | NA3 | NA3 | Ref | NA | NA3 | NA3 | Ref | NA |
| Speeding | |||||||||||||
| Yes | 118 | 1.4 | 0.75–2.61 | NA3 | NA3 | 0.84 | 0.4–1.74 | NA3 | NA3 | 0.75 | 0.34–1.42 | NA3 | NA3 |
| No | 133 | Ref | NA | NA3 | NA3 | Ref | NA | NA3 | NA3 | Ref | NA | NA3 | NA3 |
| Poor visibility | |||||||||||||
| Yes | 118 | 0.97 | 0.55–1.68 | NA3 | NA3 | 1.54 | 0.8–3.0 | 1.9 | 0.89–394 | 0.77 | 0.42–1.43 | 0.6 | 0.29–1.3 |
| No | 133 | Ref | NA | NA3 | NA3 | Ref | NA | Ref | NA | Ref | NA | Ref | NA |
1Road user type: “Other” was not depicted as separate column in table due to low number (n = 5; 2% of total) yet is included in “Total” column.
2Adjusting for all the variables in the table.
3Numbers may not add to 254 due to missing data.
4Did not meet the 0.2 significance level for entry into the model.