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Explaining the Association between Driver’s Age and the Risk of Causing a Road Crash through Mediation Analysis

Author

Listed:
  • Karoline Gomes-Franco

    (Department of Preventive Medicine and Public Health, University of Granada, 18016 Granada, Spain)

  • Mario Rivera-Izquierdo

    (Department of Preventive Medicine and Public Health, University of Granada, 18016 Granada, Spain
    Service of Preventive Medicine and Public Health, Hospital Universitario San Cecilio, 18016 Granada, Spain)

  • Luis Miguel Martín-delosReyes

    (Department of Preventive Medicine and Public Health, University of Granada, 18016 Granada, Spain)

  • Eladio Jiménez-Mejías

    (Department of Preventive Medicine and Public Health, University of Granada, 18016 Granada, Spain
    Biomedical Network Research Centers of Epidemiology and Public Health (CIBERESP), ISCIII, 28029 Madrid, Spain)

  • Virginia Martínez-Ruiz

    (Department of Preventive Medicine and Public Health, University of Granada, 18016 Granada, Spain
    Biomedical Network Research Centers of Epidemiology and Public Health (CIBERESP), ISCIII, 28029 Madrid, Spain)

Abstract

It has been widely reported that younger and older drivers have an excess risk of causing a road crash. Two casual hypotheses may coexist: the riskier driving behaviors and age-related mechanisms in extreme age groups (direct path) and the different environmental and vehicle circumstances (indirect path). Our aim was to quantify, through a mediation analysis, the percentage contribution of both paths. A case-control study was designed from the Spanish Register of Road Crashes with victims from 2014 to 2017. Assuming a quasi-induced exposure approach, controls were non-responsible drivers involved in clean collisions between two or more vehicles ( n = 52,131). Responsible drivers for these collisions plus drivers involved in single crashes constituted the case group ( n = 82,071). A logit model in which the outcome was the log (odds) of causing a road crash and the exposure was age groups was adjusted for driver, vehicle and environmental factors. The highest crash risk was observed in extreme age groups, compared to the 35–44 year old age group: the youngest (18–24 years old, odds ratio = 2.14, 95% confidence interval: 2.06–2.24) and the oldest drivers (>74 years old, odds ratio = 3.30, 95% confidence interval: 3.04–2.58). The mediation analysis identified the direct path as the main explanatory mechanism for these increases: 89% in the youngest and 93% in the oldest drivers. These data support the hypothesis that the excess crash risk observed for younger and older drivers is mainly related to their higher frequency of risky driving behaviors and age-related loss of capabilities. Preventive strategies in extreme-aged drivers should focus on decreasing these behaviors.

Suggested Citation

  • Karoline Gomes-Franco & Mario Rivera-Izquierdo & Luis Miguel Martín-delosReyes & Eladio Jiménez-Mejías & Virginia Martínez-Ruiz, 2020. "Explaining the Association between Driver’s Age and the Risk of Causing a Road Crash through Mediation Analysis," IJERPH, MDPI, vol. 17(23), pages 1-12, December.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:23:p:9041-:d:456649
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    References listed on IDEAS

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    1. Mark S. Horswill & Shelby A. Marrington & Cynthia M. McCullough & Joanne Wood & Nancy A. Pachana & Jenna McWilliam & Maria K. Raikos, 2008. "The Hazard Perception Ability of Older Drivers," The Journals of Gerontology: Series B, The Gerontological Society of America, vol. 63(4), pages 212-218.
    2. Maarten L. Buis, 2010. "Direct and indirect effects in a logit model," Stata Journal, StataCorp LP, vol. 10(1), pages 11-29, March.
    3. Peter Barraclough & Anders af Wåhlberg & James Freeman & Barry Watson & Angela Watson, 2016. "Predicting Crashes Using Traffic Offences. A Meta-Analysis that Examines Potential Bias between Self-Report and Archival Data," PLOS ONE, Public Library of Science, vol. 11(4), pages 1-32, April.
    4. Tingru Zhang & Alan H. S. Chan & Hongjun Xue & Xiaoyan Zhang & Da Tao, 2019. "Driving Anger, Aberrant Driving Behaviors, and Road Crash Risk: Testing of a Mediated Model," IJERPH, MDPI, vol. 16(3), pages 1-13, January.
    5. Elizabeth A. Walshe & Chelsea Ward McIntosh & Daniel Romer & Flaura K. Winston, 2017. "Executive Function Capacities, Negative Driving Behavior and Crashes in Young Drivers," IJERPH, MDPI, vol. 14(11), pages 1-16, October.
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    Cited by:

    1. Petya Ventsislavova & David Crundall & Pedro Garcia-Fernandez & Candida Castro, 2021. "Assessing Willingness to Engage in Risky Driving Behaviour Using Naturalistic Driving Footage: The Role of Age and Gender," IJERPH, MDPI, vol. 18(19), pages 1-20, September.
    2. Miguel Santolino & Luis Céspedes & Mercedes Ayuso, 2022. "The Impact of Aging Drivers and Vehicles on the Injury Severity of Crash Victims," IJERPH, MDPI, vol. 19(24), pages 1-16, December.

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