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Published in: BMC Public Health 1/2016

Open Access 01-12-2016 | Research article

Buckling up in Singapore: residency and other risk factors for seatbelt non-compliance – a cross-sectional study based on trauma registry data

Authors: Ting Hway Wong, Gek Hsiang Lim, Khuan Yew Chow, Nyi Nyi Zaw, Hai Van Nguyen, Hoong Chor Chin, Marcus Eng Hock Ong, Trauma Coordinators and Trauma Service Representatives

Published in: BMC Public Health | Issue 1/2016

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Abstract

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.
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Metadata
Title
Buckling up in Singapore: residency and other risk factors for seatbelt non-compliance – a cross-sectional study based on trauma registry data
Authors
Ting Hway Wong
Gek Hsiang Lim
Khuan Yew Chow
Nyi Nyi Zaw
Hai Van Nguyen
Hoong Chor Chin
Marcus Eng Hock Ong
Trauma Coordinators and Trauma Service Representatives
Publication date
01-12-2016
Publisher
BioMed Central
Published in
BMC Public Health / Issue 1/2016
Electronic ISSN: 1471-2458
DOI
https://doi.org/10.1186/s12889-016-3080-3

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