The aging of society has accelerated in recent decades. According to the 2011 general population census statistics on the Japanese Ministry of Health, Welfare, and Labor Web site, there were approximately 29.8 million elderly (ie, aged ≥65 years) people in Japan.1 The elderly population has tended to increase since 1950 and accounts for 23.3% of the population in 2011 compared with 19.0% in 2003, meaning that 1 in 5 people is elderly.1 The elderly population is predicted to increase to 26.0% of the overall population in 2015, meaning that 1 in 4 people will be in this group.2 Paralleling this trend, the number of elderly drivers is also increasing.
Vision is one of the most important senses for driving, accounting for approximately 95% of all sensory requirements,3 and visual acuity (VA) examination to confirm that drivers meet the VA standard required by law is therefore mandatory in many countries and/or states. One of the most important and frequently used visual function tests is VA. The provisions of the Road Traffic Law Article 23 in Japan require decimal bilateral VAs of 0.7 or greater for obtaining and/or renewing of a driver’s license (the renewal period is 3 or 5 years depending on whether a driver has committed a traffic violation). In addition, drivers 70 years or older are obligated to take a supplementary lecture on safe driving. Although standard VA testing is generally performed for a driver’s licensing purposes, tests of VA may not be adequate predictors of vehicle accidents.4
Standard VA testing measures the best-corrected VA at one specific point in time. In accordance with the general belief that driving requires continuous good visual performance, we measured functional VA, which is an index of visual function over time obtained by continuous measurement of the dynamics of VA.5–7 We believe that driving requires continuous good visual performance, but most of the time, such performance may depend more on continuous visual attention, which is critical for safety, than on high VA. No assessment of the continuous VA over time of motor vehicle drivers has yet been reported. In this study, we used the functional VA measurement system to investigate the specific changes in VA with conventional visual correction in drivers.
MATERIALS AND METHODS
This was a cross-sectional study of 124 subjects [101 males; mean (SD) age, 49.7 (15.0) years; range, 21–78 years; 23 females, mean (SD) age, 50.7 (15.0) years; range, 26–77 years] of approximately 1500 drivers who were randomly approached and asked to participate in the current study. The data were gathered at the expressway rest stop in Ashigara, Japan, on weekdays and weekends during brilliantly sunny daylight hours from 10 AM to 5 PM. People driving for personal and business reasons were enrolled in this study. The mean time required for the testing and completion of the questionnaire was 15 minutes. The sample size of 120 subjects for this exploratory study was determined by feasibility. Specifically, 20 subjects could be sampled in a day based on the calculation that this would require 5 hours at 15 minutes per subject. Data collection was performed on 6 days over 2 weeks. Forty-six subjects wore glasses and 18 wore contact lenses while driving to correct refractive error.
Ethical approval for the examination procedures in this study was obtained from the institutional review board of Keio University, Tokyo, Japan. All subjects were instructed about the nature and possible consequences of the study and provided informed consent to participate. Participants were given oral and written descriptions of the nature of the study, and their identities were kept anonymous to protect their private information. Individuals were identified only by their study subject identification number, age, and sex.
Functional Visual Acuity Measurement System
We measured both the conventional VA score and the changes in VA over time (60 seconds) binocularly using the same refractive correction the subjects used while driving and with natural blinking. During functional VA testing, the subjects indicated the orientations of the automatically presented Landolt optotypes by manipulating a joystick.
The Functional Visual Acuity Measurement System (Nidek, Japan) was used to examine both the conventional VA and the change in VA over time. The device is composed of 3 parts: a hard disk, a monitor, and a joystick. The Landolt optotypes are presented on the monitor and change in size depending on the responses. This device is used manually for measuring conventional VA and run automatically to measure the change in VA over time. The functional VA method is programmatically controlled according to the adaptive up-down procedure used in psychophysical threshold assessment, which is the most popular procedure used to estimate discrimination or detection performance in auditory psychophysics.8 In brief, the optotypes are displayed automatically starting with the smallest ones identified correctly during conventional VA measurement. When the first and second responses to an optotype are correct, the optotypes become smaller, whereas when the response is incorrect, the optotypes become larger. When there is no response within a set display time, the answer is assumed to be incorrect and the optotype is enlarged by 1 step. The optotype display time was set at 2 seconds. Visual acuity was continuously measured from the baseline VA, which was the best-corrected Landolt VA. The Functional Visual Acuity Measurement System can measure VAs from 20/10 to 20/2000, depending on the examination distance (5 m, 2.5 m, or 1 m) chosen. In the current study, the monitor was placed 5 m from the subjects. The testing distance information is entered into the computer database so that each Landolt optotype presented on the monitor subtends an angle equivalent to that of an optotype of the same VA level presented at a 5-m distance during the conventional Landolt VA testing. Each response is recorded on a table with the mark “○” for the correct answer and with the mark “×” for an erroneous response. No mark is recorded when there is no response. Functional VA and minimum VA scores were determined according to the measurement of the change in VA over time. The functional VA score was determined as the mean VA score of only the correct responses and the minimum VA as the worst VA score during the 60-second measurement period. The mean response time and the fastest response time for the correct answer to an optotype during the functional VA measurement were also recorded.
Trail Making Test
The subjects were administered part B of the Trail Making Test (TMT). The TMT, one of the most common cognitive tests used in neuropsychological assessment, consists of 2 parts, part A (numbers) and part B (numbers and letters).9,10 In part B, the subject is required to connect numbers and letters alternately in ascending order and sequential order (alphabetical order, eg, 1-A-2-B-3-C…). When an error was made, the subject was instructed to return to the point at which the error occurred and to continue until the test was completed. The total time taken to complete part B was recorded as the TMT-B score.
Questionnaire on Visual Function During Driving
A survey of operation characteristics and subjective visual function while driving was administered in the form of a questionnaire based on that used by Chu et al.11 The questionnaire was modified to consider 14 components of 3 categories of visual function while driving in the daytime and at night; each component was graded on a scale from 1 to 4 according to the severity of the involvement, with lower scores representing better performance. Based on their responses to the questionnaire, the drivers were scored in 3 categories: visual performance during driving, the difficulty of driving due to visual performance, and the frequency of visual disability during driving. Briefly, the questions for the category of vision performance during driving were as follows: “How clear is your vision when looking at a street directory in your car? (NOT while driving),” “How clear is your vision when looking at other cars in the side mirror while driving?,” “How clear is your vision when looking at the odometer?,” and “How clear is your vision when looking at street signs or road markings while driving?” The questions in the category of difficulty of driving due to visual performance were as follows: “How difficult is it for you to change focus while driving?,” “How difficult is it to judge the movement of other cars in a roundabout because of your vision?,” “How difficult is it to operate the radio because of your vision?,” “How difficult is it to judge your distance from the car in front while driving because of your vision?,” and “How difficult is it to judge gaps and angles during reverse parking because of your vision?” The questions in the category of the frequency of visual disability due to driving were as follows: “How often do you notice any blur in your peripheral vision while driving?,” “How often do you experience any blurry vision while looking at the road ahead?,” “How often do you notice any distorted movement of objects while driving?,” and “How often do you notice any glare while driving?” The results were summed to give overall scores from 4 to 16 in the category of visual performance and from 5 to 20 in the categories of the difficulty of driving and the frequency of visual disability.
The subjects were divided into 3 age groups: those younger than 40 years (younger group), those 40 years or older and younger than 60 years (middle-aged group), and those 60 years or older (older group). The proportions of the subjects with decimal VA, functional VA, and minimum VA scores less than the threshold decimal VA required for a driving license (Japan: 0.7) were compared among these 3 groups using χ2 tests. The means of the mean response times and the fastest times to respond to an optotype during the functional VA measurement were compared among the age groups by 1-way analysis of variance. The means of the TMT-B scores were also compared among the age groups by 1-way analysis of variance. Further analysis was performed by the Bonferroni method. The correlations between the TMT-B scores and the conventional VA, functional VA, and minimum VA in each age group were analyzed. Pearson correlation analysis was used to study the relationships between the questionnaire scores and the conventional VA, functional VA, and minimum VA in the total study population. Furthermore, the associations of the questionnaire scores with the subjective visual performance while driving were further analyzed by calculating the top and bottom quartiles in each category. Then, the mean VA, functional VA, and minimum VA scores were compared between subjects in the top and bottom quartiles using a t test. SPSS software version 17.0 J for Windows (SPSS, Inc, Chicago, Ill) was used for the statistical analysis. P < 0.05 was considered to indicate statistical significance.
Operation Characteristics and Age Distribution of the Subjects
The operation characteristics queried were the years of experience as a driver, mean number of hours and distance driven daily, and mean driving speed on the expressway. The overall mean (SD) years of driving experience was 27.3 (13.9) years. The mean (SD) hours and distance driven daily were 1.9 (2.1) hours and 1061.0 (1840.8) m, respectively. The mean (SD) driving speed on the expressway was 99.5 (12.4) km/h.
Table 1 shows the age distribution of the subjects in the current study with reference to that of driver’s license holders in Japan in 2008. The age distribution shows that the current study included smaller numbers of subjects in their 20s and 40s and a larger number of subjects in their 60s than the general driving population. The percentage of driver’s license holders among the subjects who were 65 years or older was 19.4%, which was approximately 5% higher than the reference values released by the Japanese government. The sex distribution of driver’s license holders in this study was similar to that reported by the Japanese Government.
Results of Assessment of Continuous Visual Acuity Over Time
Figure 1 shows the distribution of the subjects according to their VA, functional VA, and minimum VA scores. Table 2 shows the numbers of the subjects with VA scores lower than the regulated threshold decimal VA scores required to obtain a driver’s license in Japan. The numbers of subjects with functional VA scores and minimum VA scores of less than 0.7 were significantly higher in the older group than in the younger group (P < 0.05), although the conventional VA scores did not differ significantly between the older and younger groups (P = 0.621; Table 3). The proportion of the older group with a minimum VA score of less than 0.7 was 70%. Although continuous regression analysis showed no correlation between age and VA group (<0.7 or ≥0.7; P > 0.05), age did correlate significantly with the functional and minimum VA groups (<0.7 or ≥0.7; P < 0.05, both).
The averages of the mean times to respond to an optotype during functional VA measurement were [mean (SD)] 0.92 (0.15) seconds in the younger group and 0.95 (16.6) seconds in the middle-aged group compared with 1.06 (0.13) seconds in the older group (P < 0.05). In contrast, the average fastest response times were [mean (SD)] 0.28 (0.22) seconds in the younger group and 0.25 (0.21) seconds in the middle-aged group compared with 0.18 (0.19) seconds in the older group (P > 0.05).
Figure 2 shows representative examples of the typical pattern of functional VA recording in younger and older individuals.
Trail Making Test
The TMT-B scores were [mean (SD)] 60.1 (17.9) seconds in the younger group, 66.5 (19.0) seconds in the middle-aged group, and 109.5 (37.6) seconds in the older group. The TMT-B scores of the older group were significantly higher than those of the younger and middle-aged groups (P < 0.05).
Analysis of the correlations between the TMT-B scores and the conventional VA, functional VA, and minimum VA in each age group showed significant correlation between the TMT-B scores and minimum VAs (r = 0.45, P = 0.002) but not between the TMT-B scores and VAs (r = −0.13, P = 0.40) or functional VAs (r = 0.30, P = 0.051) in the older group. On the other hand, there were no significant correlations either between the TMT-B scores and logMAR functional VAs in the younger (r = 0.006, P = 0.97) and middle-aged (r = −0.25, P = 0.12) groups or between the TMT-B scores and logMAR VAs in the younger (r = −0.08, P = 0.61) and middle-aged (r = 0.18, P = 0.26) groups.
Correlations Between Questionnaire Scores and Visual Acuity Measures
Table 4 shows the correlations between the total scores on the questionnaire and each VA value. The total score of the category “visual performance during driving at night” correlated significantly with the logMAR functional VA and logMAR minimum VA (P < 0.05) but not the logMAR VA. No correlations were observed between the total score of “visual performance during driving in the daytime” and the logMAR VA, functional VA, or minimum VA. Likewise, no correlations were observed between the total of “the difficulty of driving due to visual performance in the daytime and at night” or “the frequency of visual disability due to driving in the daytime and at night” and the logMAR VA, functional VA, or minimum VA.
Questionnaire Results for the Subjective Visual Function During Driving
The averages of questionnaire scores for visual performance while driving during the day and at night were [mean (SD)] 5.2 (1.6) points and 6.5 (2.5) points, respectively. The averages of questionnaire scores for the difficulty of driving due to visual performance while driving during the day and at night were [mean (SD)] 6.6 (2.0) points and 7.2 (2.5) points, respectively. The averages of the questionnaire scores for the frequency of visual disability while driving during the day and at night were [mean (SD)] 8.0 (2.1) points and 8.3 (2.5) points, respectively.
The values of the top and bottom quartiles for visual performance were 4 and 6 points, respectively, for driving during the day and 4 and 8 points, respectively, for driving at night. The scores of the top and bottom quartiles for the difficulty of driving due to visual performance were 5 and 7 points, respectively, for driving during the day and 5 and 8.75 points, respectively, for driving at night. The scores of the top and bottom quartiles for the frequency of visual disability were 6.25 and 9.75 points, respectively, for driving during the day and 6 points and 10 points, respectively, for driving at night. Then, the mean VA, functional VA, and minimum VA scores were compared between subjects in the top and bottom quartiles, as shown in Table 5.
In the assessment of visual performance in the daytime, the mean minimum VA scores were significantly higher in the top quartiles than in the bottom quartiles (P < 0.05), whereas the top and bottom quartiles did not differ significantly in conventional VA or functional VA (P > 0.05). However, the mean conventional VA, functional VA, and minimum VA scores were significantly higher in the top quartiles than in the bottom quartiles for driving at night (P < 0.05).
The overall proportion of subjects in this study with a decimal bilateral VA of less than 0.7, the threshold score for obtaining and renewing a driver’s license in Japan, was approximately 10%. This observation may be due to factors including loss of VA after obtaining the driver’s license or inadequacy of eyeglass prescriptions.
The proportions of elderly subjects with functional and minimum VA values below the Japanese VA threshold standard of 0.7 were 39.5% and 69.8%, respectively. These proportions were significantly higher in the older group than in the younger group. Whatever the reason, our findings that 10% of the drivers in this study had conventional VA values below the threshold required by Japanese government regulations and 39.5% and 69.8% of drivers had functional VA and minimum VA values, respectively, below the threshold described by Japanese government regulations are important information as far as the risk of motor vehicle accidents is concerned. This result raises the possibility that older drivers might experience decreased functional VA and an increased frequency of VA loss (indicated by the significantly higher minimum VA scores in the elderly) while driving. Indeed, analysis of the representative functional VA from a 66-year-old elderly individual in Figure 2B shows that the subject is continuously experiencing VA scores below the mean VA score, namely, the functional VA, from the 36-second mark until the 58th second measurement. In other words, the driver is experiencing VA below the mean VA score for 22 seconds. If we assume that this driver drove his/her car at a speed of 100 km/h, this result translates into another startling piece of information: this driver would have driven approximately 500 m with VA below his/her mean VA score. The hypothesis that this constitutes a high-risk factor for motor vehicle accidents should be tested in future studies of functional VA in drivers who actually caused traffic accidents.
Many societies face various problems due to aging populations. One such is the upward trend of motor vehicle accidents among the elderly, which has become a social issue. The population of driver’s license holders in Japan who are 60 years or older is rising, accounting for 26.6% of the total in 2011 versus 18.7% in 2001.12,13 The number of motor vehicle accidents involving elderly drivers is increasing yearly in parallel with the increasing proportion of elderly drivers. In Japan, the annual number of motor vehicle accidents causing injury and/or death that involved drivers older than 65 years increased no less than 2.23-fold in the decade ending in 2006. Moreover, although the total number of fatalities from motor vehicle accidents has tended to decrease, the fatalities among those 65 years or older have remained steady. Accordingly, the percentage of the fatalities from motor vehicle accidents constituted by elderly victims increased to 50.4% in 2010.14 Indeed, traffic incidents caused by elderly drivers have alerted officials to this increasingly serious societal issue.
The causes of motor vehicle accidents involving elderly drivers may be influenced by slowing of brain responses, impaired judgment, and physical deterioration.15–17 In the context of VA studies, aging is well known to be associated with general slowing, more conservative decision making, poorer understanding of the test task(s), and less practice with computer (joystick) use.18–20 Therefore, we also assessed the TMT performance of each driver and investigated the relationship between TMT performance and functional VA. Hamdanl and Hamdanll21 reported that age significantly impacted TMT performance in healthy adult subjects. We found that the TMT-B scores were significantly higher in the older group than in the younger and middle-aged groups and that the TMT-B scores correlated significantly with the minimum VAs in the older group. These results demonstrate that poor TMT performance may be relevant to the poor driving performance predicted by the diminished visual sensory function, poor cognitive ability, impaired judgment, and/or decreased physical capabilities exhibited by the older group during the functional VA measurement. However, according to the data on the effects of aging on TMT-B scores in healthy adults,21 the subjects enrolled in the current study can be regarded as normal, with only age-related impairments in TMT performance. Indeed, the average of the mean times to respond to an optotype during the functional VA measurement was significantly higher in the older age group than in the younger and middle-aged groups [mean (SD), 0.92 (0.15) seconds in the younger group and 0.95 (16.6) seconds in the middle-aged group versus 1.06 (0.13) seconds in the older group]. However, the average of the fastest response did not differ among the younger, middle-aged, and older age groups. These outcomes suggest that cognitive factors have little influence on the assessment of visual performance by the functional VA measurement used in the current study. Because the average of the mean times to respond to an optotype was [mean (SD)] 1.06 (0.13) seconds in the older age group, the maximal optotype display time of 2 seconds may be supposed to have been adequate for the judgment and manipulation of the functional VA measurement task for not only the younger and middle-aged groups but also the older age group. We administered only the TMT-B in this study. However, the difference in score, defined as ΔTMT and calculated as the difference between the times of the 2 parts (Part B − Part A), is a more accurate assessment of cognitive function.22,23 More accurate determination of the relationship between cognitive function and functional and/or minimum VA is an issue for further study.
Impairment of visual attention in elderly drivers may be related to vehicle crashes.24,25 Visual attention is the mechanism by which individuals effectively perceive information and make judgments, preferably instantaneously, as to which of the signals provided by the eyes carry important information.26 The test of visual attention consists of a central target identification task coupled with a peripheral target location task; together, these provide a measure of the size of the useful field of view.24,25 The useful field of view provides a measure of the spatial area within which a person can be alerted to visual stimuli in a variety of situations.27,28 Owsley29 investigated the relationships between crash frequency and eye health, visual sensory function, the size of the useful field of view, and cognitive status in elderly drivers and suggested that the test of the useful field of view is highly reflective and predictive of the risk for crashes in the elderly. Functional VA measurements, which assess only the central target identification component of visual attention, may have limited ability to predict vehicle crashes.
Another cause of traffic accidents may be impaired visual function. Many studies around the world have reported relationships between visual performance and traffic accidents.30–33 The Blue Mountains Eye Study suggested that impaired vision due to age-related eye diseases is an important factor that should be considered in any decision to review the guidelines related to driving by elderly people.29 Subzwari et al34 reported and suggested positive relationships between measures of VA and traffic accidents. On the other hand, some reports show negative relationships between measures of VA and traffic accidents.30,32,33
Another noteworthy observation in this study was that individuals 60 years or older reported age-related eye disorders, including cataract, dry eye, age-related macular degeneration, and glaucoma, twice often as individuals younger than 60 years (data not shown), which may explain the worse minimum VA scores while driving during the day and the worse conventional, functional, and minimum VA scores of those who reported poor visual performance while driving at night. One example of an age-related eye disease is cataract, which decreases the VA and the quality of vision. Patients with cataract have been reported to exhibit reduced VA, deterioration of contrast sensitivity, and glare disability. Such visual disabilities may very well be disadvantageous while driving.35–37 Owsley et al reported that drivers with cataracts have 2.5 times as many crashes as controls and also that deficits in contrast sensitivity predict crash involvement.38,39 Wood et al reported that cataract surgery improved not only VA, contrast sensitivity, and glare sensitivity but also sign recognition, which is the ability to detect and avoid hazards. These specific improvements have positive effects on driving performance.40 One interesting article showed the rate of traffic accidents among individuals who underwent cataract surgery to be half that of individuals who did not undergo cataract surgery.41 Functional VA scores have been reported to deteriorate in patients with mild cataract. Some patients have reported improved functional VA after surgery although their conventional VA scores remained the same as their preoperative values.42 Future studies investigating the relationships between the incidence and type of cataract and functional VA, as well as whether these are risk factors for traffic accidents, are definitely essential.
The main limitation of our study is that we assessed visual function and cognitive function in drivers but not the relationships between vehicle accidents and visual and cognitive function because it is difficult to gain accurate information on vehicle accidents by self-reporting. Another limitation is that the VA measurement was conducted only during the daytime. Future studies should be conducted to investigate the age-related changes in night vision in drivers. The relationships between traffic accidents and functional VA/minimum VA in individuals who actually caused accidents are another question to address in the near future.
The category in the questionnaire concerning visual performance during driving may be interpreted to refer to high-frequency tasks in which high VA is relevant. On the other hand, the difficulty of driving due to visual performance may refer to low-frequency tasks and visual attention, such as task switching, rather than to acuity-relevant tasks and may be related to age-related cognitive decline, whereas the category of frequency of visual disability during driving may refer to visual disturbances that cause problems while driving. Functional VA scores tended to be related to subjective visual performance, and minimum VA scores were significantly related to subjective visual performance while driving during the daytime as assessed by the questionnaire, although the conventional VA and functional VA scores did not differ significantly. These results might suggest that the functional and minimum VAs measured by the functional VA system may be superior for predicting the visual performance during driving. The functional VA measurement system may be recommended for the assessment of visual function relevant to driving.
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“Never look down to test the ground before taking your next step; only he who keeps his eye fixed on the far horizon will find the right road”