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      Predictive ability of underlying factors of motorcycle rider behavior: an application of logistic quantile regression for bounded outcomes

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          Abstract

          Background: The human factors are of great importance, especially Motorcycle Rider Behavior Questionnaire (MRBQ) and attention deficit hyperactivity disorder (ADHD) in motorbike riders in road traffic injuries. This study aimed to predict MRBQ score by ADHD score and the underlying predictors by the logistic quantile regression (LQR), as a new strategy.

          Methods: In this cross-sectional study, 311 motorbike riders were randomly sampled by a clustering method in Bukan, northwest of Iran. The data were collected by MRBQ and ADHD standard surveys. To assess the relationship at all levels of MRBQ distribution, LQR in 5th, 25th, 50th, 75th and 95th quantiles of MRBQ score was utilized to assess the predictability of ADHDscore and its subscales in addition to the underlying predictors of MRBQ score. To do this, an unadjusted and as well as adjusted 4-step hierarchical modeling was used.

          Results: Almost in all quantiles of MRBQ scores, direct and significant relationships were observed between MRBQ score and ADHD score and its subscales (coefficients: 0.02 to 0.10, all P < 0.05). Besides, the driving period (coefficients: -0.58 to -0.95, P < 0.05) and hour driving (coefficients: 0.42 to 0.52, P < 0.05) also came to be the significant predictors of MRBQ score.

          Conclusion: ADHD score and driving parameters can be taken into the consideration when planning actions on the motorcycle rider behaviors at all levels of the MRBQ.

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          Most cited references26

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          Traffic fatalities and economic growth.

          This paper examines the relationship between traffic fatality risk and per capita income and uses it to forecast traffic fatalities by geographic region. Equations for the road death rate (fatalities/population) and its components--the rate of motorization (vehicles/population) and fatalities per vehicle (F/V)--are estimated using panel data from 1963 to 1999 for 88 countries. The natural logarithm of F/P, V/P, and F/V are expressed as spline (piecewise linear) functions of the logarithm of real per capita GDP (measured in 1985 international prices). Region-specific time trends during the period 1963-1999 are modeled in linear and log-linear form. These models are used to project traffic fatalities and the stock of motor vehicles to 2020. The per capita income at which traffic fatality risk (fatalities/population) begins to decline is 8600 US dollars (1985 international dollars) when separate time trends are used for each geographic region. This turning point is driven by the rate of decline in fatalities/vehicles as income rises since vehicles/population, while increasing with income at a decreasing rate, never declines with economic growth. Projections of future traffic fatalities suggest that the global road death toll will grow by approximately 66% over the next twenty years. This number, however, reflects divergent rates of change in different parts of the world: a decline in fatalities in high-income countries of approximately 28% versus an increase in fatalities of almost 92% in China and 147% in India. The road death rate is projected to rise to approximately 2 per 10,000 persons in developing countries by 2020, while it will fall to less than 1 per 10,000 in high-income countries.
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            Logistic quantile regression for bounded outcomes.

            When research interest lies in continuous outcome variables that take on values within a known range (e.g. a visual analog scale for pain within 0 and 100 mm), the traditional statistical methods, such as least-squares regression, mixed-effects models, and even classic nonparametric methods such as the Wilcoxon's test, may prove inadequate. Frequency distributions of bounded outcomes are often unimodal, U-shaped, and J-shaped. To the best of our knowledge, in the biomedical and epidemiological literature bounded outcomes have seldom been analyzed by appropriate methods that, for one, correctly constrain inference to lie within the feasible range of values. In many respects, continuous bounded outcomes can be likened to probabilities or propensities. Yet, what has long been heeded when modeling the probability of binary outcomes with the widespread use of logistic and probit regression, so far appears to have been overlooked with continuous bounded outcomes with consequences at times disastrous. Logistic quantile regression constitutes an effective method to fill this gap.
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              Errors and violations in relation to motorcyclists' crash risk.

              This study was conducted to: (a) develop a questionnaire that reliably measures the behaviour of motorcyclists and (b) test which types of behaviour predict motorcyclists' crash risk. A Motorcycle Rider Behaviour Questionnaire (MRBQ), consisting of 43 items to measure the self-reported frequency of specific riding behaviours, was developed and administered to a sample of motorcyclists (N=8666). Principal components analysis revealed a 5-factor solution (traffic errors, control errors, speed violations, performance of stunts and use of safety equipment). Generalised linear modelling showed that, while controlling for the effects of age, experience and annual mileage, traffic errors were the main predictors of crash risk. For crashes in which respondents accepted some degree of blame, control errors and speed violations were also significant predictors of crash risk. Implications of the findings are discussed in relation to deciding which countermeasures may be most effective at reducing motorcycle casualty rates.
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                Author and article information

                Journal
                Health Promot Perspect
                Health Promot Perspect
                Health Promot Perspect
                TBZMED
                Health Promotion Perspectives
                Tabriz University of Medical Sciences
                2228-6497
                2017
                26 September 2017
                : 7
                : 4
                : 230-237
                Affiliations
                1Department of Statistics and Epidemiology, Faculty of Health, Tabriz University of Medical Sciences, Tabriz, Iran
                2Road Traffic Injury Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
                Author notes
                [* ]Corresponding Author: Mohammad Asghari Jafarabadi, Email: m.asghari862@ 123456gmail.com
                Article
                10.15171/hpp.2017.40
                5647359
                721a3186-53e5-4c14-aeea-33290f86b1ca
                © 2017 The Author(s).

                This is an open access article distributed under the terms of the Creative Commons Attribution License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 31 May 2017
                : 16 June 2017
                Page count
                Tables: 4, References: 36
                Categories
                Original Article

                logistic quantile regression,bounded outcomes,motorcycle traffic accidents,adhd,mrbq

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