Findings from the Candrive/Ozcandrive study: Low mileage older drivers, crash risk and reduced fitness to drive

Marshall, Shawn; Man-Son-Hing, Malcolm; Charlton, Judith L. · 2013 · Accident Analysis & Prevention

DOI: 10.1016/j.aap.2013.02.006

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Summary

This study investigates the "low mileage bias" in older driver crash statistics, addressing the hypothesis that high per-mile crash rates among older drivers are not inherent to aging but rather reflect reduced fitness to drive among those who drive infrequently. While previous research suggested that controlling for annual mileage eliminates the apparent over-involvement of older drivers in crashes, this paper explores whether low mileage is associated with diminished physical, cognitive, and psychological fitness. The authors utilized Year 1 data from the Candrive/Ozcandrive longitudinal cohort study, which tracks drivers aged 70 and over in Canada, Australia, and New Zealand. The researchers analyzed data from 1,222 participants, categorizing them into three groups based on self-reported annual driving distances: low mileage (<5,001 km), middle mileage (5,001–15,000 km), and high mileage (≥15,000 km). The study compared these groups on self-reported crash involvement, physical/sensory performance (e.g., balance, visual acuity, reaction time), cognitive performance (e.g., memory, processing speed), and self-rated driving comfort and ability. Statistical analyses focused primarily on comparing the low and high mileage groups to test two hypotheses: that low mileage drivers perform at lower fitness levels and that high mileage drivers perform at higher levels. The results demonstrated that low mileage drivers had significantly higher indicative crash rates per million kilometers (21.6) compared to middle (14.3) and high mileage drivers (8.3). Demographically, low mileage drivers were more likely to be female and aged 80 or older. Crucially, low mileage drivers performed significantly worse than high mileage drivers on multiple physical and cognitive measures, including rapid pace walk, ruler drop test, visual acuity, and various cognitive assessments like the Trail Making Test and Digit Span. Furthermore, low mileage drivers reported lower comfort levels in daytime driving situations and perceived greater declines in their driving abilities compared to ten years prior. These associations remained significant even when controlling for age within the 70–74 age bracket. The findings suggest that the elevated crash risk associated with low mileage older drivers is linked to reduced fitness to drive, supporting the view that the "older driver problem" is pertinent primarily to a small subgroup of drivers with declining capabilities. However, the authors caution that the reliance on self-reported data for mileage and crashes introduces potential inaccuracies. They conclude that while the current bivariate analyses provide early support for the hypothesis, future studies using objective in-vehicle device data and more sophisticated statistical modeling are necessary to definitively establish the relationship between driving exposure, fitness, and crash risk.

Key finding

Low-mileage older drivers had the highest per-distance crash rate (21.6 vs 8.3 crashes per million km for high-mileage drivers) and poorer fitness-to-drive and self-rated driving measures, suggesting elevated risk concentrates in a low-mileage subgroup with reduced driving fitness rather than among all older drivers.

Methodology

field_study

Sample size: 1222

Provenance

The full processing record for this entry. Every stage of this paper's journey through the pipeline is logged — what ran, with which tool and model, how many attempts it took, and when it last completed. Discovered via openalex_abstract on 2026-05-08 (11 acquisition events logged).

Summary generated by qwen3.6-27b-prismaquant on 2026-06-10; verification: verified.

Topics

Ranked by relevance to this paper. Hover a topic for its definition.

• exposure measurement
• novice drivers
• older drivers
• mci dementia driving
• sex gender
• induced exposure

Information type

What kind of knowledge this paper contributes, grouped by family — independent of topic (what it is about) and method (how it was studied).

• Empirical Findings: crash risk outcomes, observational prevalence
• Methodological Resource: dataset resource