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1From the Departments of Ophthalmology, School of Medicine, and 2Epidemiology and International Health, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama; and the 3College of Optometry, Nova Southeastern University, Fort Lauderdale, Florida.
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Abstract |
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METHODS. A nested case–control study was conducted in patients with glaucoma aged 55 or more. Cases were patients who were involved in a police-reported motor vehicle collision (MVC) between January 1994 and June 2000; controls were those who had not experienced an MVC at the time of their selection. For each patient, an Advanced Glaucoma Intervention Study (AGIS) score was calculated on automated visual fields collected with the 24-2 or 3-2 programs.
RESULTS. With respect to the better-eye AGIS score, compared with patients with no visual field defect, those with severe defects (scores 12–20) had an increased risk of an MVC (odds ratio [OR] 3.2, 95% CI 0.9–10.4), although the association was not statistically significant. Moderate (6–11) or minor field defects (1–5) in the better eye were not associated with the risk of involvement in a crash. In the worse eye, patients with moderate or severe field defects were at significantly increased risk of an MVC (OR 3.6, 95% CI 1.4–9.4 and OR 4.4, 95% CI 1.6–12.4, respectively) compared with those with no defects. Minor field defects in the worse eye did not increase risk of MVC (OR 1.3, 95% CI 0.5–3.4).
CONCLUSIONS. Patients with glaucoma who have moderate or severe visual field impairment in the central 24° radius field in the worse-functioning eye are at increased risk of involvement in a vehicle crash.
Motor vehicle collisions (MVCs) are among the most potentially adverse mobility-related outcomes that have been reported to be associated with a diagnosis of glaucoma,3 4 5 although not all agree.6 Several limitations of these studies were self-reported diagnosis of glaucoma,3 4 5 failure to take driving exposure into account when assessing crash risk,3 and a small number of glaucoma cases in the study sample.3 5 Recently, we reported a cohort study that overcame these methodological problems, finding that adults aged 55 years or more with a diagnosis of glaucoma drive at least as safely as older persons without glaucoma.7
What was not addressed in this earlier report was whether the subpopulation of drivers who have glaucoma with visual field impairment are at increased risk for vehicle crash involvement compared with those with no field loss. There is reason to believe that this could be the case, because prior studies suggest that substantial visual field impairment elevates crash risk and impairs driving performance,4 8 although these earlier studies did not focus on persons with glaucoma per se. This issue has clear clinical and policy relevance, because information about how severe visual field loss has to be before negatively affecting driver safety is not well understood.
The objective of the current study was to examine the relationship between the severity of visual field defects in the central 24° radius field in drivers aged 
55 years with glaucoma and their risk of involvements in a vehicle crash.
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Methods |
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Data Collection
In addition to confirming the diagnosis of glaucoma, medical records were also used to obtain information on use of glaucoma medication, best corrected visual acuity in both eyes, and visual fields in both eyes. All patient visits during the period of January 1994 through December 1995 were abstracted. The visual field reports were then used to calculate a visual field defect score for each eye, based on the Advanced Glaucoma Intervention Study (AGIS) scoring system.9 AGIS scores were categorized into four categories based on previously described cutoff points9 : no defect (score 0), mild defect (scores 1–5), moderate defect (scores 6–11), and severe defect (scores 12–20).
To obtain additional information on demographic, driving, general health, smoking and alcohol use, we conducted a telephone survey between February and June 2000. Demographic information was gathered by using standard questions regarding age, gender, and race. History of cigarette smoking and alcohol use was assessed with standard questions.10 The Short Portable Mental Status Questionnaire,11 modified for telephone administration,12 was used to assess cognitive status. Respondents were asked to respond to a general health questionnaire and questions on driving habits, using 1995 as the reference point. The Driving Habits Questionnaire (DHQ),13 previously shown to be reliable and valid among older drivers, was used to collect information on driving exposure defined in terms of estimated weekly mileage.14 The DHQ was also used to calculate a driving avoidance score to estimate the extent to which a respondent avoided certain driving situations that are known to be especially problematic for older drivers. Items addressed driving at night, in fog, in the rain, alone, during rush hour, on the highway/freeway, with children, in high-density traffic, when passing other cars, when changing lanes, when making left-hand turns at intersections, and when parallel parking. The possible responses were "Always," "Often," "Sometimes," "Rarely," or "Never." For analytic purposes, subjects who reported "Always" or "Often" avoiding a specific situation were defined as avoiders and those who reported "Sometimes," "Rarely," or "Never" were defined as nonavoiders. A composite variable to reflect overall driving avoidance was created by summing the binary avoider and nonavoider variables. Given the 12 situations, the composite variable ranged from 0 to 12, with larger values representing more avoidance.
Information regarding all MVCs that occurred between January 1994 and June 2000 wherein the study subject was the driver was obtained from the Alabama Department of Public Safety. Information of specific relevance to the study was abstracted from hard-copy accident reports, including the date of the accident and whether the study subject was deemed to be at fault according to the officer at the scene.
The Institutional Review Board for Human Use at UAB approved the study protocol. The study followed the tenets of the Declaration of Helsinki, and informed consent was obtained from the subjects after explanation of the nature and possible consequences of the study.
Study Design
Within the study cohort, a nested case–control study was conducted. Cases were those enrollees who had experienced an MVC during the observation period. Incidence density sampling was used to select a single control for each case. In general, incidence density sampling refers to a situation wherein one (or more) control subjects are selected from those members of the cohort who have not experienced the event of interest as of the time the case event occurred. Thus, the control subjects have been under observation in the cohort for as long as the given case, yet have not experienced the relevant outcome of interest. In the present study, control subjects were those who, at the time of their selection, had not been involved in an MVC. For a control subject to be eligible for selection for a given case, the enrollee must have had the first clinic visit during the chart abstraction period (i.e., January 1994 and December 1995) before the date of the MVC. This criterion ensured that both the case and the matched control had contemporaneous data. For each case and matched control, the collision date for the case was used to identify the visual field measurement in closest proximity before the collision, and that measurement was used in the current analysis. Among the eligible control subjects for a given case, a single patient was randomly selected. A proportion of the cases were, according to the police report, responsible for the collision. For this subset of at-fault cases, incidence-density sampling was used to select the controls for at-fault cases from those individuals who have not experienced an at-fault MVC as of the time the at-fault case event occurred.
A total of 406 patients met the inclusion criteria for the study. During the observation period (January 1994 and June 2000), 120 collisions were observed and selected as cases for study. Of these, 84 (70%) were determined at the collision scene to be caused by the patient (at-fault cases). Regarding the number of collision each patient had, 75 had one collision, 18 had two collisions, and 3 had three collisions. For these 120 cases, a total of 120 controls were selected.
Statistical Analysis
Demographic, behavioral, driving, and general health characteristics were not available for 40% of the selected cases and 37% of the selected controls because of failure to complete the telephone survey. Reasons for failing to complete the survey included death of the study subject, failure to contact the study subject after multiple attempts, and refusal to participate. Those with complete and incomplete survey data were similar with respect to age (72.2 vs. 74.0, P = 0.06), gender (56.4% female vs. 45.7% female, P = 0.11), and AGIS score in the better (3.54 vs. 3.10, P = 0.45) and worse (7.10 vs. 7.44, P = 0.65) eyes. To prevent the exclusion of these subjects from the analysis, we used multiple imputation to create values for the missing observations using a Markov Chain Monte Carlo (MCMC) method.15 16 17 This method was appropriate because the pattern of missing data tended to be monotone (i.e., for a given subject, groups of variables were missing information). The following characteristics were imputed: age, gender, race, smoking status, alcohol consumption, self-reported medical conditions, number of glaucoma medications, cognitive impairment, visual acuity, driving avoidance, and annual miles driven. Not all these variables had missing values because some information was available from the medical record; however, they were used in the imputation process to yield improved estimates for the missing values. To prevent the imputation of values outside the boundary of real observed values, limitations were set for each variable.
Descriptive statistics were generated for demographic, behavioral, driving and clinical characteristics. These variables were then compared between the case and control groups using 
2 and t-tests for categorical and continuous variables, respectively. Crude and adjusted odds ratios (ORs) and associated 95% confidence intervals (CIs) for the association between field defects and the risk of MVC involvement were calculated by using generalized estimating equations (GEEs). GEEs were used to account for the dependence among those subjects who contributed multiple cases. Separate analyses were conducted using the AGIS score from the better and worse eyes (defined according to the AGIS score). Adjusted analyses were used to account for the possible confounding effects of demographic and medical characteristics. A parsimonious approach retained in the model only those variables that appeared to be confounders for the association between crash involvement and AGIS score. By including fewer variables in the model, this approach provides an opportunity to obtain more precise estimates. The determination of which variables should be retained as confounders was based on the change-in-estimate criteria18 using a value of 10%. Finally, analyses were also conducted with the at-fault cases and their matched control subjects.
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Discussion |
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In the present study, visual field loss was defined in terms of each eye separately, as is the clinical convention when managing glaucoma and monitoring its potential progression. One might argue, based on face validity, that it is the binocular visual field assessed by conventional automated perimetry methods or by the Esterman grid,19 not the monocular central field of each eye, that is the most direct way to evaluate risk for the adverse events such as falling, problems locating objects, and vehicle crashes; however, this conjecture remains to be proved. In clinical practice each eye’s health and functionality is routinely evaluated separately. In view of this, it is important to recognize based on this study’s results that the convention of assessing each eye’s field by itself, even just the central field, is informative with respect to crash risk. It is further interesting that the worse eye’s field sensitivity was more strongly related to crash risk than that for the better eye. There is a conventional notion in clinical practice that the eye with better function dictates visual performance. However, the worse eye’s visual field characteristics were significantly associated with crash involvement, whereas those of the better eye were not. These findings are reminiscent of our earlier findings on contrast sensitivity and crash risk in drivers with cataract, in which severe contrast-sensitivity impairment in one eye only elevated crash risk.20 However, it should also be noted that despite the lack of statistical significance of the better eye results, a general pattern of increased risk with worsening impairment was observed.
Strengths of this study are as follows: The medical records of all study subjects were reviewed to confirm glaucoma as the primary eye disorder and cause of visual dysfunction. This factor is important because other eye diseases common in the elderly (e.g., diabetic retinopathy, age-related macular degeneration) can cause central visual field impairment. Second, the AGIS score was used to define severity of field defect. The AGIS score is an already-established metric of field loss severity in glaucoma and is computed based on the output of the most common automated perimetry programs (30-2, 24-2) used in glaucoma management. Third, an independent and impartial source (the Alabama Department of Public Safety) was used to obtain information on MVCs for the study participants. Crash data were not based on driver self-reports, known to be unreliable.21 Procurement of the accident report also allowed us to obtain information on who was responsible for the MVC and therefore refine our case definition to focus on those MVCs in which the study subject was deemed at fault.
Study limitations must also be acknowledged. General health and driving habits were collected in 2000 by using a telephone survey that relied on participants’ ability to recall these characteristics, with 1995 as the reference point. However, there is little reason to suspect differential bias among the cases and controls in the ability to recall the requested information accurately, and thus any misclassification is likely to result in a conservative bias. Second, the response rate for the telephone survey was not ideal (approximately 61% overall due), yet it did not differ between the cases (60%) and controls (63%). For those who did not complete the survey, multiple imputation was used to create values for the missing information. Fortunately, the primary independent variable (i.e., visual field defect) was obtained from each patient’s medical record and therefore not vulnerable to survey nonresponse. Moreover, when the adjusted analyses were performed excluding patients with imputed data, the overall results were highly consistent with the results based on all patients, suggesting that little bias resulted from the imputation process.
In conclusion, this study suggests that drivers with glaucoma aged 55 or more with moderate to severe impairment in the central 24° field of the worse-functioning eye are at increased risk for vehicle crash involvement. This finding has clinical relevance for ophthalmologists caring for patients with glaucoma, because it provides some guidance as to the point in disease progression at which it is prudent to begin a dialog with the patient about driver safety. What is practically useful is that the marker for increased crash risk identified in this study can be computed from the automated perimetry tests commonly used in the management of glaucoma, and thus there is no additional patient or economic burden.
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Footnotes |
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Submitted for publication June 14, 2005; revised July 26, 2005; accepted September 20, 2005.
Disclosure: G. McGwin, Jr, None; A. Xie, None; A. Mays, None; W. Joiner, None; D. K. DeCarlo, None; T. A. Hall, None; C. Owsley, None
The publication costs of this article were defrayed in part by page charge payment. This article must therefore be marked "advertisement" in accordance with 18 U.S.C. 
1734 solely to indicate this fact.
Corresponding author: Gerald McGwin, Jr, Department of Ophthalmology, School of Medicine, University of Alabama at Birmingham, 700 S. 18th Street, Suite 609, Birmingham, AL 35294-0009; mcgwin{at}uab.edu.
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This article has been cited by other articles:
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  S. A. Haymes, R. P. LeBlanc, M. T. Nicolela, L. A. Chiasson, and B. C. Chauhan Glaucoma and On-Road Driving Performance Invest. Ophthalmol. Vis. Sci., July 1, 2008; 49(7): 3035 - 3041. [Abstract] [Full Text] [PDF]
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S. A. Haymes, R. P. LeBlanc, M. T. Nicolela, L. A. Chiasson, and B. C. Chauhan Risk of Falls and Motor Vehicle Collisions in Glaucoma Invest. Ophthalmol. Vis. Sci., March 1, 2007; 48(3): 1149 - 1155. [Abstract] [Full Text] [PDF]
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