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The Journals of Gerontology Series A: Biological Sciences and Medical Sciences 63:715-723 (2008)
© 2008 The Gerontological Society of America

Prevalence of Sleep Disturbances in a Cohort of Older Drivers

Carlos A. Vaz Fragoso, Katy L. B. Araujo, Peter H. Van Ness and Richard A. Marottoli

1 Yale University School of Medicine, Department of Internal Medicine, New Haven, Connecticut.
2 Clinical Epidemiology Research Center, VA Connecticut, West Haven.

Address correspondence to Carlos A. Vaz Fragoso, MD, Yale University School of Medicine, Department of Internal Medicine, 333 Cedar St., P.O. Box 208025, New Haven, CT 06250-8025. E-mail: carlos.fragoso{at}ynhh.org


   Abstract
Top
 Abstract
Methods
 Results
 Discussion
 References
 
Background. Lower levels of driving capacity in older persons are typically attributed to cognitive, visual, and/or physical impairments, with sleep disturbances rarely considered. This is in contrast to the general adult population for whom sleep disturbances are established risk factors for crashes. We thus set out to determine the prevalence of sleep disturbances in the form of insomnia symptoms, daytime drowsiness, and sleep apnea risk in a cohort of older drivers and to assess how these relate to self-reported driving capacity.

Methods. Participants included 430 active drivers aged ≥70 years. Questionnaires measured self-reported insomnia symptoms (Insomnia Severity Index [ISI]), drowsiness (Epworth Sleepiness Scale [ESS]), apnea risk (Sleep Apnea Clinical Score [SACS]), driving mileage, driver self-ratings (overall and nighttime), and prior adverse driving events.

Results. Mean age was 78.5 years, with 85% being male. Overall, 64% were dissatisfied with sleep patterns and 26% had an abnormal ISI (≥8). A large proportion (60%) reported a moderate-to-high chance of dozing in the afternoon, and 19% had an abnormal ESS (≥10). Habitual snoring was noted by 43%, with 20% at risk for sleep apnea (SACS > 15). Regarding driving, the most consistent finding was for lower levels of nighttime driver self-ratings in participants with insomnia symptoms or drowsiness. Lower levels of driving mileage were also noted but only with difficulty falling asleep. Otherwise, sleep disturbances were not associated with prior adverse driving events.

Conclusion. In our cohort of older drivers, insomnia symptoms and daytime drowsiness were prevalent and associated with lower levels of nighttime driver self-ratings. Although sleep apnea risk was also prevalent, it was not associated with self-reported driving capacity. These preliminary findings suggest that insomnia symptoms and drowsiness merit continued consideration as risk factors for lower levels of driving capacity in older persons, particularly given that effective interventions are available.

Key Words: Insomnia • Drowsiness • Sleep apnea risk • Drivers

AS the U.S. population ages, driving capacity in older persons becomes a rising public health concern (1–3). Although the absolute number of crashes involving older drivers is currently low, crash frequency per mile driven begins to increase at around 65 years of age (1). This is associated with an escalation in bodily-injury and property-damage liability claims, particularly in persons 75 years or older (2). In addition, despite accounting for only 8% of miles driven per year, drivers ≥65 years old are presently involved in 14% of crash fatalities, a figure that is expected to rise to 25% by 2030 (1).

Prior research has attributed reductions in geriatric driving capacity to cognitive, visual, and/or physical impairments (1,4–8), but sleep disturbances have rarely been evaluated. This is in contrast to the general adult population for whom sleep disturbances are established risk factors for motor vehicle crashes (9–21). Annually, there are approximately 100,000 sleep-related crashes in the United States (9,10). This is likely an underestimation given that up to 1,000,000 crashes per year are causally related to driver "inattention," a factor that may be substantially affected by sleepiness-induced reductions in vigilance, psychomotor coordination, and cognition (9–11). Sleep disturbances that underlie sleepiness-related driver inattention and adverse driving events include sleep deprivation, medications (e.g., benzodiazepines, diphenhydramine, sleep aids), shift work, insomnia, and primary sleep disorders, such as obstructive sleep apnea syndrome (OSAS) and narcolepsy (9–21). Alcohol, even at modest doses, is also a consideration as it can potentiate the adverse effects of sleep disturbances, as well as directly reduce driving capacity (20–23).

Sleep disturbances in the form of insomnia symptoms and daytime drowsiness are frequently noted in older persons. In the Established Populations for Epidemiologic Studies of the Elderly (EPESE), involving 9282 community-living persons 65 years old or older, 43% reported insomnia symptoms characterized by difficulties in sleep onset or maintenance, and 25% napped (24). These findings were confirmed in the National Sleep Foundation's (NSF) survey of community-living older persons, which reported insomnia symptoms in 46% of persons 65–74 years old and in 50% of those 75–84 years old, with corresponding rates for napping of 39% and 46% (25). Sleep disturbances related to primary sleep disorders are also prevalent in older persons, and often involve OSAS (26,27).

Nevertheless, rates of drowsy driving in older persons appear to be inexplicably low. Based on self-reported experiences in the prior 6–12 months, only 4%–6% of drivers ≥65 years old have "dozed-off" while driving, in contrast to 20%–27% of all drivers (25,28,29). This is perhaps a result of older persons self-regulating their driving, given their established pattern of avoiding high-risk settings like peak traffic times and nighttime (5,30). Such driving practices would suggest at least three possible scenarios regarding geriatric sleep disturbances. First, older persons with sleep disturbances may forego or restrict their driving. Second, older persons who drive may not have significant sleep disturbances. Third, relative to younger drivers, older drivers may demonstrate a unique sleep profile that differs in the pattern of sleep disturbances and/or in the capacity to recognize or resist drowsy driving.

To further address the relevance of sleep disturbances to older driver capacity, we set out to determine the prevalence of insomnia symptoms, daytime drowsiness, and sleep apnea risk in a cohort of active older drivers and to assess how these relate to self-reported driving mileage, driver self-ratings, and prior adverse driving events. Such findings may establish that sleep disturbances merit further consideration as relevant risk factors for lower levels of driving capacity in older persons.


   METHODS
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Results
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Study Population
Older drivers were recruited for an on-road driving evaluation from clinic and community sites in greater New Haven, Connecticut. The majority of participants (86%) were from the Veterans Administration Connecticut Healthcare System (VA-CHS). Eligibility criteria included age ≥ 70 years, having access to a telephone, English-speaking, not living in a nursing home or assisted living facility, and currently having a license and driving at least once a week. Exclusion criteria included substantial cognitive or vision impairment defined by a Mini-Mental State Examination (31) score < 18 and distance vision < 20/70. Of the 645 potential participants screened, 496 met eligibility criteria and completed an on-road driving evaluation, with 430 also administered sleep questionnaires (i.e., the sleep instruments were a late addition to the study design). Relative to those enrolled in the sleep component of this project, eligible individuals who did not participate had a similar age and were likewise predominantly male. The Yale Human Investigation Committee and the VA-CHS Human Studies Subcommittee approved the study protocol. All participants gave written informed consent.

Data Collection
Participants underwent on-site assessments by trained research assistants who used standard instruments. Data were collected on age, gender, ethnicity, education, cognition, depressive symptoms, medication use, and self-reported chronic conditions and driving capacity. Cognition was evaluated by the Mini-Mental State Examination (31), with an abnormal score being < 24. Depressive symptoms were assessed by the Center for Epidemiologic Studies Depression Scale (CES-D), with a score ≥ 16 indicating depression (32,33). Driving measures included "overall" and "nighttime" driver self-ratings that were recorded according to a discrete visual analog scale of 0–100, with a higher number indicating better-perceived capacity. Self-reports of driving mileage (average number of miles per day) and adverse driving events in the prior year (crashes, near-crashes, traffic infractions, and getting lost) were also noted.

Three separate sleep questionnaires were additionally administered, which measured insomnia symptoms and daytime drowsiness, as well as clinical risk for sleep apnea. As shown in Figure 1, the Insomnia Severity Index (ISI) is a validated single-administration questionnaire that targets the symptoms and consequences of insomnia (34), with scores ranging from 0 to 28. An ISI score ≥ 8 is considered abnormal (34). The contents of the ISI are based on the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV) criteria for insomnia, of which there are four subtypes: insomnia related to sleep onset, sleep maintenance, early morning awakenings, and perceived nonrestorative sleep (35). Regarding the latter, it is the perception of overnight sleep quality, rather than quantity, that best predicts excessive daytime drowsiness (36).


Figure 01
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  		Figure 1. Insomnia Severity Index (ISI). [Adapted from Bastien CH, et al. Validation of the Insomnia Severity Index as an outcome measure for insomnia research. Sleep Med. 2001;2:297–307; with permission from Elsevier.]

 
The Epworth Sleepiness Scale (ESS), as shown in Figure 2, is a validated single-administration measure of drowsiness experienced during various levels of activity (37), with scores ranging from 0 to 24. It is a tool that assesses subjective sleepiness and is able to distinguish normal individuals (ESS < 10) from those with sleep disorders (ESS ≥ 10) (37).


Figure 02
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  		Figure 2. Epworth Sleepiness Scale (ESS). [Reproduced from Johns M. Sleepiness in different situations measured by the Epworth Sleepiness Scale. Sleep. 1991;14:540–545; with permission from the American Academy of Sleep Medicine.]

 
The Sleep Apnea Clinical Score (SACS) is a questionnaire that assesses clinical risk for OSAS. It is based on the predictor variables of neck circumference, hypertension, habitual snoring, and witnessed apneas or gasping arousals (38). In comparison to a reference group having laboratory-confirmed OSAS at an apnea–hypopnea index of > 10, a SACS of < 5 confers low risk for OSAS (likelihood ratio of 0.25; 95% confidence interval [CI] of 0.15–0.42); in contrast, a SACS > 15 indicates high risk for OSAS (likelihood ratio of 5.17; 95% CI, 2.54–10.51) (38). SACS values between 5 and 15 are considered indeterminate (28). Of all the variables contained within SACS, the most important risk factor is neck circumference, which typically averages ≥40 cm in individuals with OSAS (38,39).

Statistical Analysis
Participant characteristics and sleep questionnaire data were summarized as means accompanied by standard deviations or as counts accompanied by percentages. Frequency distributions of components of the ISI and ESS questionnaires were tabulated according to categories of perceived severity, as defined by the respective sleep instrument. Associations between categorical clinical characteristic variables and categorical version of the ISI (<8 vs ≥8) and ESS (<10 vs ≥10) variables were evaluated with the Pearson chi-square statistic, with p values at the.05 level reported as statistically significant.

Self-reported driving mileage, driver self-ratings, and prior adverse driving events were also tabulated according to categories of perceived severity in sleep disturbances, as defined by the respective sleep instrument. For the ISI and ESS, this included overall scores, as well as individual items that are based on DSM-IV criteria for a diagnosis of insomnia or specific to being in a car.

Significance was determined at the.05 level, using the nonparametric Kruskal–Wallis test for continuous variables and the Pearson chi-square test for the adverse events categorical variable. SAS version 9.1.3 (SAS Institute, Cary, NC) was used for all analyses.


   RESULTS
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 Methods
 Results
Discussion
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Participant Characteristics
As shown in Table 1, participants were active drivers, with a mean age approaching 80 years. They were predominantly white men and had on average a high school education. The five most prevalent chronic conditions were hypertension, arthritis, coronary artery disease, diabetes, and depression; only a small percentage reported a diagnosis of sleep apnea. Medication use was highly prevalent, with a small percentage being on central nervous system (CNS) active medications. About one quarter of participants reported their health status as only fair to poor.


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  		Table 1. Characteristics of Study Participants, N = 430.

 
Insomnia
As shown in Table 2, the most common insomnia symptom was difficulty in sleep maintenance, that is, staying asleep. This was reported by half of the driving cohort, with about one third describing it as moderate to very severe. Almost two thirds of the cohort also expressed dissatisfaction with sleep patterns, with nearly one third describing it as moderate to very severe. Overall, as noted in Table 3, one quarter of older drivers in the cohort had an abnormal ISI (≥8).


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  		Table 2. Frequency Distribution of Components of the Insomnia Severity Index and Epworth Sleepiness Scale.

 

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  		Table 3. Summary Scores of Sleep Questionnaires.

 
Drowsiness
As shown in Table 2, a high percentage of the cohort reported a moderate-to-high chance of dozing when sitting and reading, watching television, or when lying down to rest in the afternoon. Overall, as noted in Table 3, about one fifth of our older drivers had an abnormal ESS (≥10).

Sleep Apnea Risk
As shown in Table 3, one fifth of the cohort had an SACS > 15, which is consistent with high risk for OSAS. Additionally, almost half of the cohort reported habitual snoring or had a neck circumference ≥ 40 cm.

Covariates
Table 4 describes the frequency distribution of clinical characteristics known to affect sleep quality and daytime alertness, stratified according to ISI and ESS threshold scores. For participants having an ISI ≥ 8, there was a significantly greater prevalence of loneliness, hypertension, arthritis, pain, and depression (CES-D ≥ 16). For an ESS ≥ 10, there was a significantly greater prevalence of sleep apnea risk, depression (CES-D ≥ 16), and chronic lung disease.


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  		Table 4. Covariates According to ISI and ESS Threshold Scores.

 
Self-Reported Driving Capacity
As shown in Table 5, the most consistent finding was for nighttime driver self-ratings to be significantly lower in participants with insomnia symptoms that included difficulties in falling or staying asleep, early morning awakenings, dissatisfaction or distress with sleep, sleep-related impairment in functioning, and an ISI ≥ 8. Similarly, nighttime driver self-ratings were lower in those who were drowsy as a passenger in a car, or at an ESS ≥ 10.


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  		Table 5. Self-Reported Driving Capacity Relative to Sleep Disturbances.

 
Table 5 also indicates a greater prevalence of sleep disturbances in older drivers with lower levels of overall driver self-ratings and driving mileage. Specifically, overall driver self-ratings were lower in participants with insomnia symptoms characterized by difficulties in falling asleep or being dissatisfied with sleep, as well as in those with drowsiness as a passenger in a car or in a car stopped for a few minutes, and at an ESS ≥ 10. Lower levels of driving mileage were similarly noted but only in those with difficulty falling asleep. Otherwise, sleep disturbances, in general, were not associated with prior adverse driving events, nor was sleep apnea risk associated with any measure of self-reported driving capacity.


   DISCUSSION
Top
 Abstract
 Methods
 Results
 Discussion
References
 
In our cohort of active older drivers, insomnia symptoms and daytime drowsiness were highly prevalent and associated with lower levels of driver self-ratings, especially regarding nighttime driving, and with lower levels of self-reported driving mileage. Although sleep apnea risk was also prevalent, it was not associated with any measure of self-reported driving capacity, nor were sleep disturbances, in general, associated with self-reported adverse driving events in the prior year. These preliminary findings suggest that insomnia symptoms and daytime drowsiness merit continued consideration as risk factors for lower levels of driving capacity in older persons, particularly given that effective interventions are available.

Older persons are known to self-regulate their driving, as evidenced by their avoidance of high-risk settings such as peak traffic times and nighttime (5,30). Accordingly, in response to sleep disturbances, it could be that older persons may forego driving. This, however, was not the case in our cohort of older persons, as a large percentage continued to drive despite expressing dissatisfaction with their sleep patterns, with the predominant insomnia symptom being difficulties in sleep maintenance. Many participants additionally reported a high probability of dozing in the afternoon, with some describing their drowsiness at a level typical of a primary sleep disorder (37), that is, at an ESS ≥ 10. In fact, one fifth of our older drivers were at high risk for sleep apnea (SACS > 15), with nearly one half reporting habitual snoring, a characteristic that is associated with moderate-to-severe levels of sleep apnea (38,40). Our findings thus suggest that older persons who continue to drive retain a high burden of sleep disturbances.

Sleep disturbances are known to contribute to lower levels of driving capacity (9–21), but whether this is the case in older drivers remains to be seen. In our elderly driving cohort, lower levels of self-reported driving mileage and driver self-ratings, especially regarding nighttime driving, occurred in participants with insomnia symptoms or daytime drowsiness, including at an ISI ≥ 8 and an ESS ≥ 10. As to mechanisms that underlie these associations, prior work has shown that symptoms of insomnia and drowsiness are typically multifactorial in older persons, often including cardiovascular disease, depression, arthritis, pain, medications, sleep apnea, and social isolation (25,41,42). In our cohort, a similar profile is noted, especially at more severe levels of insomnia symptoms and daytime drowsiness. Specifically, at an ISI ≥ 8, there is a higher prevalence of hypertension, arthritis, depression, pain, and loneliness; at an ESS ≥ 10, depression, sleep apnea risk, and chronic lung disease are more prevalent. Thus, independent of a primary sleep disorder such as sleep apnea, comorbid conditions may engender both sleep disturbances (25,41,42) and cognitive and physical impairments (1,4–8) that either alone or in combination may contribute to lower levels of driving capacity in older drivers. Nighttime driving capacity is particularly vulnerable because there is a progressive buildup of sleepiness-induced reductions in vigilance, psychomotor coordination, and cognition that normally occur in response to a day's prolonged period of wakefulness (43–45). These reductions are substantially exacerbated by nonrestorative nocturnal sleep, regardless of the underlying cause.

The age of our cohort may also predispose insomnia symptoms and daytime drowsiness. Specifically, normal aging-related declines in sleep physiology are characterized by nonrestorative forms of sleep that include increased nocturnal awakenings and reductions in homeostatic (slow wave sleep) and circadian (rapid-eye-movement) sleep (46). Additionally, there is phase advancement of the sleep–wake cycle, which may result in older persons being more alert in the early morning but drowsier in the early evening (47–49). Whether these aging-related changes affect driving capacity remains to be seen. For example, it is unknown if advancement of the sleep–wake cycle in older persons contributes to the practice of avoiding nighttime driving (5,30) or to the lower nighttime driver self-ratings that were seen in our driving cohort.

Surprisingly, in our study population, sleep apnea risk was not associated with lower levels of driving mileage or driver self-ratings. The reasons for this are unclear but could be attributed to our sleep apnea instrument (SACS) being less valid in older persons (i.e., the value of predictors such as obesity and witnessed apneas is known to be reduced in an older age group) (50). Alternatively, it may be that the clinical importance of sleep apnea diminishes with advancing age. For instance, nocturnal oxygen desaturation attributed to OSAS is milder in older persons than in younger persons (51), and OSAS, even when severe, may not confer excess mortality in adults older than 50 years (52). Further research is required to determine whether and to what degree OSAS may affect driving capacity in older persons.

Also surprising was the finding that, in our cohort, sleep disturbances were not associated with an increase in prior adverse driving events. This may be explained by older drivers self-regulating their driving to less risky settings, such as avoiding nighttime driving. Alternatively, it could be that our study design is limited in its capacity to evaluate the association between sleep disturbances and adverse driving events, for several reasons. First, although an earlier study has demonstrated the benefits of self-reporting driving events (53), older drivers with sleep disturbances may be reluctant to report, or even recall or be aware of such events. Second, our time period for recording driving events was limited to only 1 year, was retrospective, and did not include a time-of-day stratification (i.e., individuals with lower levels of nighttime driver self-ratings may have had more driving events specific to the late afternoon or early evening). Third, there was only a modest number of participants with an ESS ≥ 10 (n = 83) and an ISI ≥ 8 (n = 112). Accordingly, to avoid these limitations, future work will need to consider a prospective design with a population large enough to detect an adequate number of adverse driving events that include both self-reported measures and state records, stratified by time of day. In addition, risk levels for subsequent adverse driving events may be further defined by direct observation of driver performance, such as tests of psychomotor vigilance, on-road driving, or driving simulators (54–56), and by diagnostic confirmation of specific sleep disorders, as determined through sleep diaries, actigraphy, and polysomnography (57–59).

Our study is also limited by its participants being predominantly male. Although this precludes an evaluation of gender-related differences, our findings regarding the prevalence of sleep disturbances remain relevant to older drivers, in general. For example, older postmenopausal women are likely to have even higher rates of insomnia symptoms (24,60), whereas their sleep apnea prevalence is expected to approach that of older men (61). Moreover, in our cohort, the prevalence of insomnia symptoms at 54% and sleep apnea risk at 20% approaches that of the general elderly population, which is at 43% and 30%, respectively (24,42).

Conclusion
In our cohort of active older drivers, insomnia symptoms and daytime drowsiness were highly prevalent and associated with lower levels of driver self-ratings, especially regarding nighttime driving. These preliminary findings suggest that insomnia symptoms and daytime drowsiness merit continued consideration as risk factors for lower levels of driving capacity in older persons, particularly given that effective interventions are available.


   Acknowledgments
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 Results
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This study was supported in part by a Donaghue Foundation Investigator Award (Dr. Marottoli; grant DF 01-127) and by the AAA Foundation for Traffic Safety (grant AAAFTS 51074). This study was conducted using the Biostatistics, Data Management, and Field cores of the Claude D. Pepper Older Americans Independence Center at Yale University School of Medicine (P30 AG21342 National Institutes of Health/National Institute on Aging [NIA]). Dr. Fragoso is a postdoctoral research fellow in geriatric clinical epidemiology and is supported by an NIA training grant (T32AG1934).


   Footnotes
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Decision Editor: Darryl Wieland, PhD, MPH

Received March 28, 2007

Accepted October 18, 2007


   References
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