Global Progress in Road Injury Mortality since 2010

<div><p>We aimed to examine progress in global road injury mortality since the initiation of Global Plan for the Decade of Action for Road Safety 2011–2020. We examined annual percent changes in age-adjusted road traffic mortality using data from the Global Burden of Disease Study 2013. Association between changes in road traffic mortality and legislative efforts in individual nations was explored using data from Global Status Reports on Road Safety 2013 and 2015. We found that global age-adjusted mortality, both overall and for user-specific road traffic injuries, decreased significantly between 2010 and 2013 (annual percent change in rates range from -1.43% to -0.99%). Developed countries witnessed a larger decrease than developing countries in both overall and user-specific road mortality (about 2.0–4.6 times). However, there were substantial disparities within developed countries and within developing countries, with some countries seeing large reductions in mortality rates and others seeing none. The annual percent change in road traffic mortality during 2010–2013 was significantly correlated with total national law enforcement score (Spearman <i>r</i>_<i>s</i> = -0.38). We concluded that results highlight the need for continued effort to reduce the burden of road injury mortality, especially in LMIC countries.</p></div

Reimbursement for medical expenses caused by injuries having no responsible person/party and not caused by given reasons in Chinese legislative documents (number/proportion).

<p>Reimbursement for medical expenses caused by injuries having no responsible person/party and not caused by given reasons in Chinese legislative documents (number/proportion).</p

Annual percent change in age-adjusted mortality per 100,000 population in 2010–2013 by type of road user and country.

<p>Notes: 1. Annual percent change in age-adjusted mortality was estimated based on negative binomial regression. 2. Mortality data from Global Burden of Disease 2013. (<a href="http://www.healthdata.org/gbd/data-visualizations" target="_blank">http://www.healthdata.org/gbd/data-visualizations</a>).</p

Age-adjusted road injury mortality per 100,000 population between 2010 and 2013 by development status and type of road user.

<p>Age-adjusted road injury mortality per 100,000 population between 2010 and 2013 by development status and type of road user.</p

Laws/regulations involving reimbursement for injury-induced medical expense in Chinese social medical insurance schemes.

<p>Laws/regulations involving reimbursement for injury-induced medical expense in Chinese social medical insurance schemes.</p

Total enforcement score of five kinds of national road traffic laws in 2011 and 2014 by development status.

<p>Notes: 1. National law enforcement scores in 2011 and in 2014 were from the Global Status Report on Road Safety 2013⁴ and 2015⁵, respectively. Total enforcement scores of five kinds of national road traffic laws were calculated, including speed limit law, drink-driving law, motorcycle helmet law, seat-belt law, and child restraint law. Total enforcement score ranged from 0 to 50; 0 points indicated the weakest legislation effort and 50 points mean the strongest legislation effort. 2. Differences in total law enforcement scores was statistically significant between developed countries and developing countries in 2011 (<i>Z</i> = 7.21, <i>P</i><0.05) and in 2014 (<i>Z</i> = 8.09, <i>P</i><0.05). 3. Change in total law enforcement score between 2011 and 2014 was not significant for developing countries (<i>Z</i> = -0.90, <i>P</i>>0.05) but was significant for developed countries (<i>Z</i> = -2.10, <i>P</i><0.05).</p

Reimbursement for injury-induced medical expense in Chinese social medical insurance laws/regulations, number (percentage).

<p>Reimbursement for injury-induced medical expense in Chinese social medical insurance laws/regulations, number (percentage).</p

Additional file 1: of Effectiveness of an app-based intervention for unintentional injury among caregivers of preschoolers: protocol for a cluster randomized controlled trial

SPIRIT 2013 Checklist: Recommended Items to Address in a Clinical Trial Protocol and Related Documents. (DOC 88 kb

Additional file 1 of Validity across four common street-crossing distraction indicators to predict pedestrian safety

Additional file 1: Appendix A. Brief description of the video-based observational study in Changsha, China. Fig. A1. Geographic location of 20 road intersections for video-based observations in Changsha city, China. Fig. A2. Placement of cameras for video-based observation at road intersections. Appendix B. Appendix Tables and Figures. Table B1. Sample characteristics of pedestrians at 20 road intersections in Changsha, China collected between June 29 and July 21, 2019. Table B2. Basic road characteristics of the 20 included road intersections in Changsha, China. Table B3. Description of the grouping of the four pedestrian distraction indicators for primary analysis, by type of distraction. Table B4. Description of the grouping of four distraction indicators by type of distraction for sensitivity analysis. Table B5. Sensitivity analyses for discriminant validity of the four distraction indicators by alternating the classification of distraction indicators, all walking distractions combined. Table B6. Sensitivity analyses for discriminant validity of four distraction indicators by alternating the grouping of distraction indicator, mobile phone use. Table B7. Sensitivity analyses for discriminant validity of four distraction indicators by alternating the grouping of distraction indicator, talking with other pedestrians. Table B8. Sensitivity analyses for discriminant validity of four distraction indicators by changing the grouping of distraction indicator, eating, drinking, or smoking. Fig. B1. Linear graph showing the associations between the four distraction indicators and near-crash incidence, all walking distractions combined. Fig. B2. Linear graph showing the associations between the four distraction indicators and frequency of looking left and right, all walking distractions combined. Fig. B3. Linear graph showing the associations between the four distraction indicators and speed crossing the street, all walking distractions combined. Fig. B4. Linear graph showing the associations between the four distraction indicators and near-crash incidence, mobile phone use. Fig. B5. Linear graph showing the associations between the four distraction indicators and frequency of looking left and right, mobile phone use. Fig. B6. Linear graph showing the associations between the four distraction indicators and speed crossing the street, mobile phone use. Fig. B7. Linear graph showing the associations between the four distraction indicators and near-crash incidence, talking with other pedestrians. Fig. B8. Linear graph showing the associations between the four distraction indicators and frequency of looking left and right, talking with other pedestrians. Fig. B9. Linear graph showing the associations between the four distraction indicators and speed crossing the street, talking with other pedestrians. Fig. B10. Linear graph showing the associations between the four distraction indicators and speed near-crash incidence, eating, drinking, or smoking. Fig. B11. Linear graph showing the associations between the four distraction indicators and frequency of looking left and right, eating, drinking, or smoking. Fig. B12. Linear graph showing the four distraction indicators and speed crossing the street, eating, drinking, or smoking

Additional file 2: of Effectiveness of an app-based intervention for unintentional injury among caregivers of preschoolers: protocol for a cluster randomized controlled trial

Homepage of app intervention (English version). Note: This version is translated from the original Chinese version (Fig. 3). (PDF 2445 kb