BMC public health · 2016
Buckling up in Singapore: residency and other risk factors for seatbelt non-compliance - a cross-sectional study based on trauma registry data.
СтатьяНазвание и аннотация: Перевод в очереди
Обработка статьи · этапы, ошибки и управление
Загрузка состояния…
Ошибки и ограничения
История · было → стало
Состояние обновляется каждые 5 секунд, пока блок открыт. Процент показывается только там, где известен объём работы. Пауза останавливает продолжение этапа; текущий запрос к источнику может завершиться.
Wong Ting Hway, Lim Gek Hsiang, Chow Khuan Yew, Trauma Coordinators and Trauma Service Representatives, Zaw Nyi Nyi, Nguyen Hai Van, Chin Hoong Chor, Ong Marcus Eng Hock
Аннотация
BACKGROUND: Seatbelt non-compliance is a problem in middle income countries, and little is known about seatbelt compliance in populations with a high proportion of non-residents. This study analyses the profile of seatbelt non-compliance in Singapore based on trauma registry data from five of the six public hospitals.
METHODS: This is a cross-sectional study of seatbelt compliance of patients aged over 18 years, attending the emergency departments of five public hospitals in Singapore after road collisions from 2011-2014. Seatbelt data was obtained from paramedic and patient history.
RESULTS: There were 4,576 patients studied. Most were Singapore citizens (83.4 %) or permanent residents (2.4 %), with the largest non-resident groups from Malaysia, India, and China. Overall seatbelt compliance was 82.1 %. On univariate analysis, seatbelt compliance was higher in older patients (OR 1.02, 95 % CI 1.001-1.021, p < 0.0001); drivers, followed by front passengers (OR 0.65, 95 % CI 0.51-0.83, p < 0.0001), were more compliant than rear passengers (OR 0.08, 0.06-0.09, p < 0.0001); occupants of larger vehicle types (buses, heavy transport vehicles, minibuses and vans) were more non-compliant compared to occupants of private cars and taxis. Morning peak travel (0700 h-0900 h) and being a non-resident were other risk factors for non-compliance. On multivariable analysis, older age (OR 1.01, 95 % CI 1.001-1.014, p = 0.03) was associated with compliance, while non-residents from China (OR 0.43, 95 % CI 0.18-0.99, p = 0.05), seat position (front passenger compared to driver, OR 0.64, 95 % CI 0.48-0.85, p = 0.002; rear passenger compared to driver, OR 0.067, 95 % CI 0.05-0.09, p < 0.0001), vehicle type (bus compared to car, OR 0.04, 95 % CI 0.017-0.11, p < 0.0001, van compared to car, OR 0.55, 95 % CI 0.36-0.83, p = 0.004), and travel at morning peak periods were independent predictors of seatbelt non-compliance. When the sub-group of drivers was analysed, only vehicle type was a significant predictor of seatbelt compliance, with bus drivers least likely to be compliant to seatbelts (multivariable analysis, OR 0.057 compared to cars, 95 % CI 0.019-0.18, p < 0.0001).
CONCLUSIONS: While overall seatbelt compliance in our study is high, efforts can be made to increase compliance for morning rush hour passengers, rear seat passengers, and occupants of buses, heavy transport vehicles, and vans or pickups.
METHODS: This is a cross-sectional study of seatbelt compliance of patients aged over 18 years, attending the emergency departments of five public hospitals in Singapore after road collisions from 2011-2014. Seatbelt data was obtained from paramedic and patient history.
RESULTS: There were 4,576 patients studied. Most were Singapore citizens (83.4 %) or permanent residents (2.4 %), with the largest non-resident groups from Malaysia, India, and China. Overall seatbelt compliance was 82.1 %. On univariate analysis, seatbelt compliance was higher in older patients (OR 1.02, 95 % CI 1.001-1.021, p < 0.0001); drivers, followed by front passengers (OR 0.65, 95 % CI 0.51-0.83, p < 0.0001), were more compliant than rear passengers (OR 0.08, 0.06-0.09, p < 0.0001); occupants of larger vehicle types (buses, heavy transport vehicles, minibuses and vans) were more non-compliant compared to occupants of private cars and taxis. Morning peak travel (0700 h-0900 h) and being a non-resident were other risk factors for non-compliance. On multivariable analysis, older age (OR 1.01, 95 % CI 1.001-1.014, p = 0.03) was associated with compliance, while non-residents from China (OR 0.43, 95 % CI 0.18-0.99, p = 0.05), seat position (front passenger compared to driver, OR 0.64, 95 % CI 0.48-0.85, p = 0.002; rear passenger compared to driver, OR 0.067, 95 % CI 0.05-0.09, p < 0.0001), vehicle type (bus compared to car, OR 0.04, 95 % CI 0.017-0.11, p < 0.0001, van compared to car, OR 0.55, 95 % CI 0.36-0.83, p = 0.004), and travel at morning peak periods were independent predictors of seatbelt non-compliance. When the sub-group of drivers was analysed, only vehicle type was a significant predictor of seatbelt compliance, with bus drivers least likely to be compliant to seatbelts (multivariable analysis, OR 0.057 compared to cars, 95 % CI 0.019-0.18, p < 0.0001).
CONCLUSIONS: While overall seatbelt compliance in our study is high, efforts can be made to increase compliance for morning rush hour passengers, rear seat passengers, and occupants of buses, heavy transport vehicles, and vans or pickups.