The Association of Frailty with Driving Habits Among Older Adults: AAA LongROAD Study

Linda Ng; Cora Man; Christopher L. Crowe; Howard F. Andrews; Linda L. Hill

Introduction

The present study uses data from the AAA Longitudinal Research on Aging Drivers (LongROAD) study to describe the association of frailty status with driving habits (crashes, driving space and annual mileage). Quality of life among older adults is dependent upon safe mobility and independence (Albert et al., 2017; Bond et al., 2017; Boot et al., 2014; Chihuri et al., 2016). Crashes and driving space (i.e., how close to home a driver stays) provide objective measures of safe driving, and research shows that older adult drivers who accrue fewer than 3,000 miles per year have higher crash rates per mile driven (Antin et al., 2017). If frailty is associated with these outcomes, interventions targeted at preventing or reducing the symptoms of frailty may lead to improved mobility among older adults (Davis et al., 2011; Gill et al., 2012; Mielenz et al., 2017; Durbin et al., 2017). This study found that the frailty phenotype is associated with objectively measured low-mileage driver status, but it is not associated with self-reported crashes and driving space.

Key Findings

Based on objectively measured driving data, frailty status is significantly associated with low-mileage drivers.
The association found in the present study that those who are frail are at a higher risk of being low-mileage drivers implies that they are also at risk for increased crash rates.

Methodology

LongROAD is a prospective multisite (San Diego, California; Denver, Colorado; Baltimore, Maryland; Ann Arbor, Michigan; and Cooperstown, New York) cohort study with 2,990 drivers. Details on the study methods are outlined elsewhere (Li et al., 2017).

Frailty status was measured using the frailty phenotype that was developed and validated by Fried and colleagues (Fried et al., 2001). Frailty status was measured on a scale from 0 to 5, with one point given for each of the following criteria the participant exhibited: shrinking, weakness, exhaustion, slowness, and low physical activity. Participants were classified as frail (3-5), pre-frail (1-2), or not frail (0). “DataLogger” devices (Danlaw, Inc., Novi, Michigan) were installed in participants’ vehicles after researchers received informed consent to monitor and record objective data on driving behaviors, such as distance traveled and vehicle speed. Self-reported crashes were measured based on responses to the Driving Habits Questionnaire (DHQ) question: “How many crashes have you been involved in over the past year when you were the driver?” (Owsley, Stalvey, Wells, & Sloane, 1999). Self-reported driving space was defined as the distance a participant drove from their immediate neighborhood in the past three months.

Depressive symptoms were measured using the Patient-Reported Outcomes Measurement Information System (PROMIS) instruments, with higher scores indicative of more depressive symptoms.

Results

Over the 2,965 drivers in the AAA LongROAD cohort who had frailty status data, more than half (55.85%) were classified as pre-frail. Only 87 participants (2.93%) were classified as frail. Almost 7% (6.75%) of the population were classified as low-mileage drivers, 11.23% reported involvement in a motor vehicle crash in the past year and 22.63% reported restricted driving space (0-3).

Frailty status was significantly associated with low mileage driver status at only one level of frailty. After adjusting for covariates, older drivers who are frail have 2.30 (95% CI: 1.40-3.78) times the risk of being low mileage drivers compared with those who are not frail. Frailty status was not significantly associated with self-reported driving space. After adjusting for covariates, older drivers who are frail have 1.52 (95% CI: 0.71-3.22) times and those who are pre-frail have 1.23 (95% CI: 0.85-1.80) times the odds of reporting restricted driving space compared with those who are not frail.

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