Relations among Chronic Medical Conditions, Medications, and Automobile Crashes in the Elderly: A Population-based Case-Control Study

Gerald McGwin, Jr1,2, Richard V. Sims3,4, LeaVonne Pulley5 and Jeffrey M. Roseman1

1 Department of Epidemiology and International Health, School of Public Health, University of Alabama at Birmingham, Birmingham, AL.
2 Section of Trauma, Burns, and Surgical Critical Care, Department of Surgery, School of Medicine, University of Alabama at Birmingham, Birmingham, AL.
3 Division of Gerontology and Geriatric Medicine, Center for Aging, Department of Medicine, University of Alabama at Birmingham, Birmingham, AL.
4 Birmingham Department of Veterans Affairs Medical Center, Birmingham, AL.
5 Department of Health Behavior, School of Public Health, University of Alabama at Birmingham, Birmingham, AL.


    ABSTRACT
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 Statistical analysis
 RESULTS
 DISCUSSION
 REFERENCES
 
Older drivers have elevated crash rates and are more likely to be injured or die if they have a crash. Medical conditions and medications have been hypothesized as determinants of crash involvement. This population-based case-control study sought to identify medical conditions and medications associated with risk of at-fault crashes among older drivers. A total of 901 drivers aged 65 years and older were selected in 1996 from Alabama Department of Public Safety driving records: 244 at-fault drivers involved in crashes; 182 not at-fault drivers involved in crashes; and 475 drivers not involved in crashes were enrolled. Information on demographic factors, chronic medical conditions, medications, driving habits, visual function, and cognitive status was collected. Older drivers with heart disease (odds ratio (OR) = 1.5, 95% confidence interval (CI): 1.0, 2.2) or stroke (OR = 1.9, 95% CI: 0.9, 3.9) were more likely to be involved in at-fault automobile crashes. Arthritis was also associated with an increased risk among females (OR = 1.8, 95% CI: 1.1, 2.9). Use of nonsteroidal antiinflammatory drugs (OR = 1.7, 95% CI 1.0, 2.6), angiotensin converting enzyme inhibitors (OR = 1.6, 95 CI: 1.0, 2.7), and anticoagulants (OR = 2.6, 95% CI: 1.0, 73) was associated with an increased risk of at-fault involvement in crashes. Benzodiazepine use (OR = 5.2, 95% CI: 0.9, 30.0) was also associated with an increased risk. Calcium channel blockers (OR = 0.5, 95% CI: 0.2, 0.9) and vasodilators (OR = 0.3, 95% CI: 0.1, 1.0) were associated with a reduced risk of crash involvement. The identification of medical conditions and medications associated with risk of crashes is important for enhancing the safety and mobility of older drivers. Am J Epidemiol 2000;152:424–31.

accidents; traffic; aged; case-control studies; cerebrovascular disorders; coronary disease

Abbreviations: ACE, angiotensin converting enzyme; CI, confidence interval; DPS, Department of Public Safety; NSAID, non-steroidal antiinflammatory drug; OR, odds ratio; VFQ, Visual Function Questionnaire


    INTRODUCTION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 Statistical analysis
 RESULTS
 DISCUSSION
 REFERENCES
 
Older adults represent the most rapidly growing segment of the United States population (1Go). Their crash-involvement rate per mile of travel approaches that of young drivers, and they are also more likely to be injured and at fault in a crash (2GoGoGoGoGoGoGoGoGoGoGoGo–14Go). Research on risk factors for crash involvement among older adults has focused on chronic medical conditions; medications; and visual, cognitive, and functional impairment (15GoGoGoGoGoGoGoGoGoGoGoGo). Unfortunately, there has been little agreement about which factors are associated with poor driving performance. This lack of agreement may be partly attributable to differences in study methodology, including discordant methods for defining poor driving performance, differing study populations, and inadequate adjustment for confounding factors.

We conducted a population-based case-control study of chronic medical conditions and automobile crashes among older drivers. The objective of this study was to estimate the association between chronic medical conditions and at-fault involvement in crashes among older drivers after adjustment for demographic factors and driving exposure.


    MATERIALS AND METHODS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 Statistical analysis
 RESULTS
 DISCUSSION
 REFERENCES
 
Study design and study subjects
The population base included all residents of Mobile County, Alabama, aged 65 years and older who possessed a driver license in 1996 according to data tapes supplied by the Alabama Department of Public Safety (DPS). Fields on the DPS tapes allowed us to eliminate individuals who possessed driver licenses only for identification purposes.

Cases were those subjects who, according to the DPS data file, had been involved in at least one automobile crash between January 1 and December 31, 1996. Of the 39,687 eligible persons in the study base, 1,906 had been involved in at least one automobile crash during 1996.

Because we conducted a telephone interview and telephone numbers are not available from DPS files, it was necessary to obtain telephone numbers for the subjects. Using local telephone directories and Internet resources, we successfully identified telephone numbers for 1,507 (79.1 percent) of the eligible cases. Because we did not have resources to conduct telephone interviews on all potential cases, we randomly selected 560 to be interviewed; of these, 447 (79.8 percent) participated, 84 (15.0 percent) refused to participate, 24 (4.2 percent) could not complete the interview because of an impairment, and five (1.0 percent) were deceased. Participants did not differ from nonparticipants in age or gender; differences by race could not be assessed.

Police records corresponding to the crashes incurred by the 447 participating cases were obtained from the Alabama DPS. These records were judged according to criteria to determine whether the case was at least partially at fault in the crash. Briefly, the assessment of fault involves reviewing the narrative on the form as well as other information pertaining to the behavior of the vehicles or persons. Of the participating cases, 249 (56.0 percent) were found to be at least partially at fault.

A random sample of 1,900 potential controls was also selected from the DPS file. We linked 1,520 (80 percent) of potential controls to telephone directories and then randomly selected 657, frequency matched to cases on 1-year age groups and gender, to be interviewed. We selected slightly more controls (n = 657) than cases (n = 560) because some potentially eligible controls would be excluded because they would have stopped driving prior to 1996. Forty-four controls were excluded as eligible controls because they reported during the interview that they had stopping driving prior to 1996.

Of the 613 eligible controls, 454 (74.1 percent) were interviewed, 88 (14.4 percent) of the eligible controls refused to participate, 35 (5.7 percent) could not complete the interview because of an impairment, and 36 (5.9 percent) were deceased at the time of the interview. Participants did not differ from nonparticipants in age or gender.

This study was approved by the Institutional Review Board for Human Use of the University of Alabama at Birmingham, and the study protocol was performed according to the guidelines of the Declaration of Helsinki.

Data collection
Telephone interviews were conducted between June and December 1997 by trained interviewers who were blind to case status. In addition to standard demographic information (age, gender, race, marital status, and education), we also collected information on chronic medical conditions, medications, driving habits, visual function, and cognitive status. When responding to all questions, subjects were asked to use January 1, 1996 as a reference date. For example, we asked, "As of January 1, 1996, in general, how would you have characterized your overall physical health? Would you say it was excellent, very good, good, fair, or poor?"

Chronic medical conditions and medications. Subjects were asked whether a physician, nurse, or other health care professional had told them that they had any of the following conditions and, if so, whether they were taking any medications or receiving any treatment for the following conditions: cataracts, arthritis, cancer, detached retina, memory problems, hearing problems, heart disease, epilepsy, glaucoma, diabetes, high blood pressure, kidney disease, Parkinson's disease, and stroke. Subjects were also asked whether they had been diagnosed with any other conditions not explicitly mentioned and whether they were taking any other medications.

Driving habits. We collected information on driving habits, including self-reported quality of driving, estimated annual mileage, level of comfort with certain driving situations (e.g., at night), and type(s) of vehicle(s) most commonly driven. Although not validated, research on self-reported mileage suggests that this information is accurate compared with actual mileage, even among older drivers (27Go). Information on prior (1991–1995) crash involvement was obtained from driving histories provided by the Alabama DPS.

Visual function. Visual function was assessed by using a modified version of the National Eye Institute Visual Functioning Questionnaire (VFQ). The VFQ presents subjects with a variety of activities (e.g., reading a newspaper) and queries them about how much difficulty they have doing these activities (28Go). The National Eye Institute VFQ has been validated against actual visual function (28Go) but not for use over the telephone. Responses were aggregated into three scores for specific types of vision (near, far, and peripheral vision), with each score ranging from 0 to 100. For each type of vision, subjects with scores of less than or equal to 75 were defined as impaired.

Cognitive status. Cognitive status was assessed by using a version of the Short Portable Mental Status Questionnaire modified for telephone administration (29Go, 30Go).


    Statistical analysis
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 Statistical analysis
 RESULTS
 DISCUSSION
 REFERENCES
 
Frequency distributions were calculated for demographic, driving, and chronic medical conditions for subjects involved in and those not involved in crashes. For demographic and driving variables, crude odds ratios and 95 percent confidence intervals were computed. For chronic medical conditions, analyses were performed with and without adjustments for demographic factors and annual mileage. All analyses were conducted using separate unconditional logistic regression models comparing at-fault drivers involved in crashes with two reference groups (not at-fault drivers involved in crashes and drivers not involved in crashes). Because we were concerned with the impact of cognitive impairment on study results, all analyses were conducted including and excluding drivers who were considered cognitively impaired according to the Short Portable Mental Status Questionnaire. The results indicated that there was no difference in the study findings between when the cognitively impaired drivers were included and when they were excluded, and therefore the former are presented.


    RESULTS
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 Statistical analysis
 RESULTS
 DISCUSSION
 REFERENCES
 
Table 1 presents the demographic and driving characteristics of study subjects. No difference in age was noted when at-fault drivers were compared with drivers not involved in crashes, although at-fault drivers were older than their not at-fault counterparts. There were no remarkable differences with respect to gender. There was a larger proportion of Blacks among at-fault drivers than among drivers not involved in crashes (odds ratio (OR) = 1.5, 95 percent confidence interval (CI): 1.0, 2.1). Although there were no racial differences between at-fault and not-at-fault drivers, there was a larger proportion of Blacks among not-at-fault drivers involved in crashes than among drivers not involved in crashes. At-fault drivers were more likely to rate the quality of their driving as average or worse compared with not-at-fault drivers. The annual mileage of at-fault drivers was greater than that among not-at-fault drivers and drivers not involved in crashes; all subsequent analyses are mileage adjusted. The at-fault crash rate was 2.1 times (95 percent CI: 1.5, 3.0) higher in drivers who had been involved in a crash in the previous 4 years than in drivers who had not been involved in crashes. Not-at-fault drivers involved in crashes were also more likely to have sustained a prior crash compared with drivers not involved in crashes. For this reason, all subsequent analyses were conducted both with and without adjustment for previous crash involvement. No important differences in interpretation were noted, so only the results not adjusted for previous crash involvement are presented.


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TABLE 1. Demographic and driving characteristics of at-fault drivers involved in crashes, not-at-fault drivers involved in crashes, and drivers not involved in crashes, Mobile County, Alabama, January to December 1997

 
Table 2 presents the prevalence of chronic medical conditions among the three groups of drivers. Several conditions (detached retina, memory problems, epilepsy, and Parkinson's disease) are not presented because their prevalence was too low to obtain meaningful comparisons. After adjustment for age, gender, race, and annual mileage, no differences were noted for at-fault and not-at-fault drivers. When compared with drivers not involved in crashes, the adjusted OR for heart disease was 1.5 (95 percent CI: 1.0, 2.2), and that for stroke was 1.9 (95 percent CI: 1.0, 3.9). The at-fault crash rate was 20 percent (95 percent CI: 0.9, 1.7) greater in drivers who reported that they had arthritis than in drivers who did not report this; however, the increased risk was apparent only among females (OR = 1.8, 95 percent CI: 1.1, 2.9), not males (OR = 0.8, 95 percent CI: 0.5, 1.3). Not-at-fault drivers involved in crashes were also more likely to have heart disease, stroke, and arthritis compared with drivers not involved in crashes. The adjusted odds ratio for diabetic neuropathy was elevated (OR = 2.6, 95 percent CI: 0.5, 13.1), but lacked precision. With respect to self-reported vision impairment, adjusted odds ratios for far (OR = 1.2, 95 percent CI: 0.8, 1.7) and peripheral (OR = 1.4, 95 percent CI: 0.8, 3.0) vision impairment were also elevated.


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TABLE 2. Medical characteristics of at-fault drivers involved in crashes, not-at-fault drivers involved in crashes, and drivers not involved in crashes from Mobile County, Alabama, January to December 1997

 
Crude and adjusted odds ratios and 95 percent confidence intervals for medications are presented in table 3. After adjustments for age, gender, race, and annual mileage, the at-fault crash rate was 70 percent (95 percent CI: 1.0, 2.6) greater in drivers who reported using NSAIDs than in drivers who did not. Positive associations were also observed for angiotensin converting enzyme (ACE) inhibitors (OR = 1.6, 95 percent CI: 1.0, 2.7) and anticoagulants (OR = 2.6, 95 percent CI: 1.0, 7.3). Benzodiazepine use was also positively associated with at-fault crash involvement (OR = 5.2, 95 percent CI: 0.9, 30.0). Not-at-fault drivers involved in crashes were also more likely to report benzodiazepine use compared with drivers not involved in crashes. Two medications demonstrated negative associations with at-fault crash risk: calcium channel blockers (OR = 0.5, 95 percent CI: 0.2, 0.9) and vasodilators (OR = 0.3, 95 percent CI: 0.1, 1.0). When compared with not-at-fault drivers, there were two notable results. At-fault drivers taking calcium channel blockers were 60 percent less likely to be involved in a crash (95 percent CI: 0.2, 0.9). The point estimate for anticoagulant use was elevated (OR = 5.6, 95 percent CI: 0.7, 46.5), but lacked precision.


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TABLE 3. Medication use of at-fault drivers involved in crashes, not-at-fault drivers involved in crashes, and drivers not involved in crashes from Mobile County, Alabama, January to December 1997

 
Because of the possibility that drug combinations may also represent important risk factors, all two-way interactions (n = 171) between the 19 medication classes in table 3 were explored. The results of these analyses revealed one notable finding; there was evidence of an interaction between NSAID and ACE inhibitor use. Older drivers taking both NSAIDs and ACE inhibitors were 3.4 times more likely to be involved in a crash compared with those taking neither (95 percent CI: 1.1, 10.9). Similarly, use of NSAIDs only was associated with a 50 percent increased risk of crash involvement (95 percent CI: 1.0, 2.5); no association was observed for use of ACE inhibitors only (OR = 1.3, 95 percent CI: 0.7, 2.5).

To address whether the observed associations for heart disease and stroke were independent of medications used to treat these conditions (particularly ACE inhibitors and anticoagulants), we obtained odds ratios adjusted for age, gender, race, annual mileage, and the relevant classes of medications. Although the associations for both conditions persisted (heart disease: OR = 1.4, 95 percent CI: 0.9, 2.1; stroke: OR = 1.8, 95 percent CI: 0.9, 3.6), they were somewhat reduced. Also of interest was the converse situation; we found associations for ACE inhibitors and anticoagulants independent of the conditions for which they were taken. The odds ratios for both medications were reduced but remained elevated (ACE inhibitor: OR = 1.4, 95 percent CI: 0.8, 2.4; anticoagulant: OR = 1.9, 95 percent CI: 0.6, 5.1).


    DISCUSSION
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 Statistical analysis
 RESULTS
 DISCUSSION
 REFERENCES
 
The primary results of these analyses were that older drivers with heart disease or stroke were more likely to be involved in both at-fault and not-at-fault automobile crashes and that these associations appear to be independent of the medications used to treat these diseases. In addition, drivers who reported a diagnosis of arthritis (particularly females) or diabetic neuropathy had an increased risk of crash involvement. Three classes of medications were positively associated with crash involvement: NSAIDs, ACE inhibitors, and anticoagulants. An elevated risk was also observed for benzodiazepine use. Calcium channel blockers and vasodilators were associated with a reduced risk of crash involvement.

More than a dozen studies have identified heart disease as associated with automobile crashes (31GoGo–33Go). However, sudden incapacitation causes less than 1 percent of automobile crashes, approximately 50 percent of which are related to a cardiac cause. The less direct role of cardiovascular disease in automobile crashes has been the focus of several studies reporting that drivers with heart disease had higher crash rates (34GoGoGoGo–38Go). Three studies specifically focusing on older drivers have reported positive associations between heart disease (or subtypes of the disease) and automobile crash involvement (22Go, 35Go, 39Go); however, other studies have demonstrated no association (23Go, 26Go, 40Go41Go–42Go). All of these null or negative studies did not collect information on the driving patterns or histories of study subjects, factors that may confound or modify crash risk, since those with heart disease might drive less. Heart disease may also interfere with driving ability by causing diminished coronary or cerebral blood flow, a cardiac arrhythmia, or anginal episodes. Studies have found that patients with coronary heart disease undergoing ambulatory electrocardiographic monitoring developed abnormalities while driving (43Go, 44Go). The independence of medications used to treat the disease reinforces the notion that the explanation probably lies with the physical manifestations of the disease.

Our results also indicated that older drivers who reported a stroke were nearly twice as likely to have been involved in an automobile crash. There have been few population-based studies wherein the driving safety of stroke patients has been assessed. These studies have generally reported increased risks (23Go, 26Go, 39Go). Older stroke patients may be especially prone to unsafe driving because of the combined effects of age-related deficits and the focal neurologic deficits induced by the stroke. Two studies comparing the performance of stroke and control patients found that, with respect to all driving skills (e.g., reaction time, steering errors), the stroke patients performed worse (45Go, 46Go). Visuospatial abilities, identification and response to driving cues, attention, and complex reasoning skills appear to be important discriminators of intact versus compromised driving skills. Given the relatively high survival rate after stroke (47Go) and lack of communication to patients regarding poststroke driving (48Go), future work should attempt to identify and validate factors used to assess driving safety among stroke patients and work with health care professionals to discuss these issues with their patients.

This study reported a slightly increased risk of crash involvement among those with arthritis, particularly among females. An increased risk of crash involvement among those with arthritis or musculoskeletal dysfunction has been reported elsewhere (23Go, 46Go). It has been suggested that changes in the components and structure of the articular cartilage, bone, ligaments, and musculature impair the capability of the musculoskeletal system to perform the act of driving (49Go). Joint and musculature problems may result in reduced range of motion and increased reaction times. General discomfort and pain and diminished muscle mass and strength may lead to excessive fatigue and distraction while driving. Future research focused specifically on those with arthritis is necessary to resolve the nature of the relation between arthritis manifestations, and treatment modalities and crash risk.

At least one study has also identified NSAID use as being associated with increased crash risk, leading the authors to suggest that this may be an indicator of several clinical syndromes of pain and disability possibly linked to specific arthritic conditions (23Go). In our study, the arthritis and NSAID associations persisted after adjustment for each other, suggesting the independent contribution of each. With regard to NSAID use, it is possible that this variable represents persons with either undiagnosed arthritis or other musculoskeletal impairments. Another, less likely, possible explanation is that this class of medications has a direct impact on cognition or psychomotor performance.

In addition to NSAIDs, we also identified three other classes of medications (ACE inhibitors, anticoagulants, and benzodiazepines) associated with increased risk of at-fault involvement in crashes; calcium channel blockers and vasodilators were associated with reduced risk of at-fault crash involvement. No previous studies have reported that they examined the association between ACE inhibitor use and crash involvement. The mechanism through which this class of medications might lead to elevated crash risk is unclear. With possible relevance to driving, ACE inhibitors have been associated with side effects such as vertigo, dizziness, hypotension, and syncope (50Go). Interestingly, we found that the effect of ACE inhibitors was limited to those who also used NSAIDs. Among the other potential adverse side effects of ACE inhibitor use is hyperkalemia, particularly in the elderly and those using NSAIDs. Hyperkalemia may result in a variety of symptoms relevant to driving skills, including paresthesia, weakness, changes in sensation, abnormal body sensations, reduced or absent reflexes, and decreased muscle functioning.

The association between anticoagulant use and crash involvement is also novel. One possible explanation relates to our finding with respect to heart disease; that is, anticoagulant use may serve as a marker for the disease for which they are used or an element of this disease (e.g., severity). That the odds ratios for anticoagulant use were diminished after adjustment for stroke and heart disease lends support to this interpretation.

Benzodiazepines have been shown to impair vision, attention, information processing, memory, motor coordination, combined skills tasks, and driving under controlled conditions (51Go, 52Go). Although it seems clear that benzodiazepine use, in general, is associated with an increased risk of crash involvement, it has been suggested that the increased risk may be limited to long half-life benzodiazepines (15Go). Unfortunately, we did not have information on specific types of benzodiazepines and thus could not evaluate this hypothesis; future research should help to elucidate this issue. However, users of benzodiazepines should be warned of the potential driving risks associated with their use.

We found that use of either calcium channel blockers or vasodilators was associated with a reduced risk of crash involvement, but the reason for these findings is not entirely clear. Perhaps their effect on lowering blood pressure, relieving angina, or stabilizing certain abnormal heart rhythms has a positive effect on driving safety.

It is noteworthy that several medical conditions (heart disease, stroke, arthritis) and benzodiazepines were associated with both at-fault and not-at-fault crashes. There are several possible explanations for these findings. First, it is likely that there is a subgroup of drivers among the not-at-fault drivers involved in crashes who may have "contributed" in that they were unable to properly respond to a scenario "caused" by another driver. Such drivers might, in some circumstances, be unable to be adequately defensive because of some of the medical problems we have found associated with at-fault status. Such an explanation is plausible for those who reported having a stroke or arthritis or those using benzodiazepines since these conditions and class of medications may not only affect driving performance but also impair judgment and reaction time and perhaps thereby decrease one's ability to respond in an emergency driving situation. Another possible explanation is that the judgment of fault may be in error. Given that there is a positive association between at-fault crash involvement and these factors, one impact of misclassifying truly at-fault drivers as not at fault would be a bias away from the null for the association with not-at-fault crash involvement. Finally, it is possible that these associations reflect unmeasured confounders such as socioeconomic status or environmental factors that affect the risk of crash involvement.

The results of this study should be interpreted in light of several limitations. All information on independent variables of interest was obtained via self-report. In particular, information on self-reported health status is a concern for a number of reasons. Subjects may be unwilling to divulge this information or simply misunderstand or forget the diagnosis. Even so, we would not expect the misclassification to be differential between cases and controls; therefore, any bias most likely would be toward the null. However, other studies have demonstrated that there is excellent agreement between self-report and medical record diagnosis for most chronic medical conditions, so any effect on the estimate of the association is likely to be negligible (53GoGoGo–56Go).

It should also be noted that drivers involved in fatal crashes were not excluded from this study. As part of the study protocol, information from subjects who had died (as a result of the crash or otherwise) was to be obtained from a next of kin if such a person could be identified. As it turned out, none of the drivers involved in crashes who were enrolled in the study were killed. This is not unusual given that less than 1 percent of automobile crashes result in a fatality.

We were able to obtain telephone numbers for 80 percent of the eligible cases. The remaining 20 percent of eligible cases were not different with respect to age and gender, the only information on which we could compare them. The proportion of eligible controls matched to telephone numbers was similar, and again, no differences by age and gender were found. Similarly, not all of the eligible cases and controls interviewed agreed to participate in the study. However, the response rate was high and not meaningfully different between eligible cases and controls, and no differences by age and gender were found. Although it is possible that the prevalence of certain medical conditions differs among those who could and those could not be linked to telephone numbers and among participants and nonparticipants and that it is differential by case-control status, we have little reason to suspect that this is the case.

The results of this study reflect a large number of analytic comparisons. It is possible that some of the differences detected were the result of chance. For some comparisons, such as those with respect to at-fault involvement in crashes and heart disease or stroke, there were definite a priori hypotheses. However, for others, such as the differences with respect to the use of calcium channel blockers and vasodilators and at-fault involvement in crashes, there were no a priori hypotheses. Chance cannot be ruled out as a possible explanation for these findings. Similarly, we examined a large number of interactions between medications. The power for such analyses was very low, and it is possible that the associations we found (e.g., ACE inhibitors and NSAIDs) are likewise possibly due to chance.

In this study, several medical conditions and medications were associated with the risk of crash involvement among older drivers. The safety of older drivers has became an issue of increasing concern. For the clinician, the identification of medical conditions and medications associated with crash risk can provide an impetus to discuss issues of driving safety with potentially at-risk patients. Similarly, the physician may be asked by licensing authorities to assess and classify drivers with medical conditions with respect to driving ability. The ultimate result of such assessments can have a substantial impact on the safety and mobility of older drivers, and thus informed assessments are crucial. With minor exceptions, the associations observed in this study are not large; one possible explanation for this is that medical diagnoses are far too heterogeneous to identify older drivers who are at risk of crash involvement. A possible explanation is that medical diagnoses simply represent markers for functional impairments, the true risk factors for crash involvement. Future research should focus specifically on those conditions, heart disease and stroke, for which elevated risks have been identified. The characteristics of such conditions can provide insight into the functional manifestations of the conditions themselves or of the medications used to treat them. Such information would greatly improve the ability to identify drivers who represent threats to public safety while maintaining the mobility of older adults.


    ACKNOWLEDGMENTS
 
This study was made possible by the Center for Aging Intramural Grant Program and the Center for Research in Applied Gerontology at the University of Alabama at Birmingham.


    NOTES
 
Reprint requests to Dr. Gerald McGwin, Jr., 700 S. 18th Street, Suite 609 EFH, University of Alabama at Birmingham, Birmingham, AL 35294–0009 (e-mail: mcgwin@eyes.uab.edu).


    REFERENCES
 TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 Statistical analysis
 RESULTS
 DISCUSSION
 REFERENCES
 

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Received for publication January 22, 1999. Accepted for publication October 26, 1999.