Analysis of transport and vehicular road crash cases in Metro Manila from 2016 to 2020

ABSTRACT

INTRODUCTION@#Metro Manila, the metropolitan center and seat of the national government, is composed of 16 cities and 1 municipality, and considered as the second-most populous region in the Philippines. Transport is a key sector that is needed for accessibility and economic progress. Yet, the question on safety of the roads of Manila remains as road crashes continue to be reported.@*OBJECTIVE@#The study aims to determine the trend of road crashes in Metro Manila, and the factors associated with both fatality and injury among three types of road users – the drivers, the passengers, and the pedestrians.@*METHODS@#A retrospective analysis of 523,059 road crash data between 2016 to 2020 was done. Using descriptive statistics, the road crash variables analyzed in the study were (1) crash classification according to damage to property, fatal, and non-fatal crash, (2) road user type according to driver, passenger, and pedestrian, (3) vehicle type, (4) junction type, and (5) risky road user behavior. Logistic and multinomial regression models were used to determine whether these variables were significant with road user fatality and injury.@*RESULTS@#The analysis of the MMARAS database (n=523,059) showed an increasing trend of road crashes occurred since 2016 and peaked in 2019, and declined in 2020. Majority (436,367, 83.426%) were damage to property, followed by non-fatal or injurious cases (84751, 16.203%) and fatal outcomes (1941, 0.371%). Drivers have the greatest number of fatalities and injuries compared to passengers and pedestrians. Cars (513482 52.322%) and motorcycles (136641, 13.923%) remain the major types of vehicles involved in road crashes. The factors that were significantly associated with increased odds ratio for driver death were involvement of pedicabs (OR=10.937, p=0.000), motorcycles (OR=55.061, p=0.000), bus (OR=5.835, p=0.000), truck (OR=7.073, p=0.000), hit object (OR=11.007, p=0.000), self-accident (OR=6.149, p=0.000), and collisions in bridges/flyovers (OR=2.713, p=0.010)). The factors that were significantly associated with increased odds ratio for passenger fatality were the involvement of motorcycle (OR=3.75, p=0.021), angle impact (OR=42.01, p=0.002), multiple collision (OR=18.42, p=0.040), self-accident (OR=32.66, p=0.010), and lost control (OR=82.98, p=0.001). The factors significantly associated with pedestrian fatality were hit and run (OR=56.04, p=0.000), hit pedestrian (OR=1085.17, p=0.000), and crashes in bridges/flyover (OR=4.20, p=0.025). Meanwhile, multinomial regression showed that classification of crash and vehicle type were significantly associated with fatal and non-fatal crashes.@*CONCLUSION@#The study showed the trend of fatality and injury among drivers, passengers, and pedestrians from 2016-2020, and factors of road crashes in Metro Manila including vehicle type, road behaviors, collision type and junction type.