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  1. Haque MO
    Int J Inj Contr Saf Promot, 2011 Mar;18(1):45-55.
    PMID: 21409677 DOI: 10.1080/17457300.2010.517319
    In this article, we have investigated the pattern of road fatality in Brunei. It is seen from this analysis that road fatality in Brunei was one of the highest in the world in the early 1990s, but has been significantly reduced over the years, and is now one of the lowest in the world. Preliminary investigation shows that young male drivers are responsible for most road fatalities in Brunei. We have also fitted a linear regression model and found that road fatality is significantly positively related to people aged 18-24 years and new registered vehicles, both of which are expected to grow with the growth of population and economic development. Hence, road fatality in Brunei is also expected to grow unless additional effective road safety countermeasures are introduced and implemented to reduce road toll. Negative coefficient is observed for trend variable, indicating the reduction of road fatality due to the combined effects of improvements of vehicle safety, road design, medical facilities and road safety awareness among road user groups. However, short-term road fatality analysis based on monthly data indicates that the coefficient of the trend variable is positive, implying that in recent months road fatalities are increasing in Brunei, which is supported by media reports. We have compared Brunei's road fatality data with Australia, Singapore and Malaysia and found that Brunei's road fatality rate is lower than Singapore and Malaysia, but higher than Australia. This indicates that there are still opportunities to reduce road fatalities in Brunei if additional effective road safety strategies are implemented like in Australia without interfering in the economic and social development of Brunei.
    Matched MeSH terms: Automobiles/statistics & numerical data*
  2. Lee LK
    Med J Malaysia, 2002 Sep;57(3):266-77.
    PMID: 12440265 MyJurnal
    A survey was conducted in December 1995 to study car occupant restraint usage in Selangor. A total of 1082 car occupants were observed in 536 cars. The results of the study shows that only 57.3% of the car occupants observed were protected by any form of restraints. Most of the cars (99.8%) examined had front seat belts but only 44.2% had rear seat belts. Only 0.6% of the cars were found to have child restraints in the cars. 80.2% of drivers used restraints and only 65.4% of front seat passengers used any forms of restraints. In the case of the rear seat passengers, only 0.42% used an available restraint. More people in the urban areas (84.42%) than in the rural areas (66.51%) used seat belts. Usage of seat belts by car drivers influenced the use of seat belts by front seat passengers. Type of seat belts fitted was associated with usage rate. It is sad to note that 21.9% of the drivers used seat belts incorrectly.
    Matched MeSH terms: Automobiles/statistics & numerical data*
  3. Wong TH, Lim GH, Chow KY, Trauma Coordinators and Trauma Service Representatives, Zaw NN, Nguyen HV, et al.
    BMC Public Health, 2016 05 14;16:402.
    PMID: 27180046 DOI: 10.1186/s12889-016-3080-3
    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 

    Matched MeSH terms: Automobiles/statistics & numerical data
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