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1 From the Lions Vision Center, the 2 Dana Center for Preventive Ophthalmology, and the 3 Department of Biostatistics, the Johns Hopkins University School of Medicine, Baltimore, Maryland.
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Abstract |
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METHODS. Two thousand five hundred twenty community-dwelling residents of Salisbury, Maryland, between the ages of 65 and 84 years of age were recruited for the study. Corrected visual acuity was measured monocularly and binocularly using ETDRS charts. Reading speed, face discrimination, and self-reported difficulty with visual tasks were also determined.
RESULTS. Binocular acuity is predicted with reasonable accuracy by acuity in the better eye alone, but not by the widely used American Medical Association (AMA) weighted-average algorithm. The AMA algorithm significantly underestimates binocular acuity when the interocular acuity difference exceeds one line. Monocular acuity and binocular acuity were significantly better predictors of reading speed than the AMA weighted score or a recently proposed Functional Vision Score (FVS). Monocular acuity in the better eye, binocular acuity, and the AMA and FVS algorithms were equally good predictors of self-reported vision disability. None of the acuity measures were good predictors of face recognition ability.
CONCLUSIONS. The binocular acuities of older individuals can be inferred from measures of monocular acuity. There is little evidence for binocular inhibition when the monocular acuities in the two eyes are unequal, as opposed to the widely used AMA algorithm for computing binocular visual impairment. For tasks that are strongly associated with visual acuity, such as reading, this association can be captured from measures of monocular acuity and does not require separate assessment of binocular acuity.
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Introduction |
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Many clinical investigators, see, for example, Tinetti et
al.2
and Mangione et al.,3
and governmental
agencies rely on an algorithm developed in 1955 for the American
Academy of Ophthalmology4
and subsequently adopted in 1958
by the Committee on Medical Rating of Physical Impairment of the
American Medical Association.5
According to this
algorithm, visual impairment of the individual is derived from vision
impairment measured separately for the two eyes by the following
formula:
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Neither the AMA guidelines, the FVS, nor the Social Security regulations provide any justification for their respective algorithms. One consequence of the AMA and better-eye rules is that binocular vision would never be better than monocular vision in the better eye. However, laboratory studies of binocular versus monocular visual acuity based on small samples of young normal adults with equal acuities in the two eyes have shown a 10% to 12% advantage for binocular viewing under high luminance, high contrast conditions.8 9 10 The AMA and better-eye algorithms do not allow for this "binocular summation." One laboratory study demonstrated that reduced luminance or contrast can increase the summation to as much as 50%.10 Many older adults have reduced retinal illuminance caused by senile miosis and nuclear sclerosis. In addition, some may experience reduced retinal contrast due to light scatter from early cataract. Therefore, we might expect binocular summation to be greater in older subjects than in young normal subjects. Indeed, one study of 16 older adults (mean age, 62.5 years) showed a 30% improvement in binocular compared with monocular acuity.11
Conversely, numerous studies of contrast sensitivity have shown that when the sensitivities of the two eyes differ, binocular sensitivity may be worse than the sensitivity of the better eye. The AMA algorithm incorporates this form of "binocular inhibition," but its applicability to visual acuity data is uncertain. Normal subjects show modest binocular acuity summation even when the target to one eye is reduced in contrast.8 Cataract patients with unequal cataract densities in the two eyes show neither summation nor inhibition for high contrast letters12 and inhibition for low contrast letters.11
Previous epidemiologic studies of vision impairment have generally measured monocular acuities,13 14 whereas studies of physical disability have typically obtained a subjective assessment of visual function based on reported difficulty seeing with both eyes (e.g., the Massachusetts Health Care Panel Study15 and EPESE Study16 ). The Salisbury Eye Evaluation (SEE) was initiated in 1992 as a multidisciplinary study of eye disease, vision impairment, and physical disability in older Americans. In the SEE project, visual acuity was measured monocularly and binocularly. In addition, self-report and performance-based measures were obtained for a variety of visual tasks under natural binocular viewing conditions. This provides an opportunity to determine how binocular acuity is related to monocular acuity and how both are related to difficulty with visual tasks.
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Methods |
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The overall participation rate was 65%, excluding the ineligibles. Approximately half of those who refused (refusals) agreed to answer a brief subset of the home questionnaire.19 Those refusing were somewhat older, more likely to be female, and less likely to have completed high school than those who participated. Refusals were also more likely to report difficulty with activities of daily living than participants. There were no significant differences between participants and refusals by race or self-assessed vision status.
Visual Acuity Tests
As part of an extensive psychophysical test battery, visual acuity
was evaluated with the Lighthouse ETDRS distance charts
transilluminated with the Lighthouse Chart Illuminator (Lighthouse
International, New York, NY) to a level of approximately 130 (candela)
cd/m2. Acuity was tested at 3 m. If the
participant was unable to read the largest letters on the chart, test
distance was reduced to 1.5 m and testing repeated. This procedure
was repeated until an acuity measure was obtained or the participant
failed at a distance of 1 m. Only five participants failed to read
any letters with either eye. A strict forced-choice testing procedure
was used: The participant was required to guess even if the letters
appeared illegible until at least four of five letters on a row were
named incorrectly.
Acuity was measured binocularly then monocularly (right eye followed by
left eye) with the participant’s habitual refractive correction. If
the acuity was worse than 20/30 with either eye, then a complete
subjective refraction was performed using autorefractor findings as the
starting point. If acuity improved more than one line (
0.1 logMAR)
after subjective refraction, then binocular acuity was remeasured using
the new refraction worn in a trial frame. Acuity measurements for the
binocular, right eye, and left eye conditions were made with different
versions of the ETDRS chart.
Ten participants were unable to identify letters because of illiteracy and the Lea Symbols Chart was substituted. The Lea Symbols Chart has the same layout at the ETDRS chart but uses four pictorial optotypes instead of letters.20
Performance-Based Tests
Reading performance was tested with a computer-controlled video
display. Short passages of text were displayed for up to 15 seconds and
the participants read aloud. Four print sizes were tested ranging from
0.13° (about the size of small print on medicine bottles) to 0.53°
(about the size of a small newspaper headline). Each print size was
tested twice, in random order. Face discrimination was measured with a
four-alternative forced-choice paradigm. Sixteen faces (eight male,
eight female) were digitized in each of four poses. The faces subtended
2.5° (horizontal, ear to ear) by 3.2° (vertical, chin to forehead).
Three different poses of one individual and a fourth pose of another
individual were displayed on a monochrome monitor. The participant had
to choose the odd image. Fifteen trials were presented in random order.
Self-Reported Visual Disability
Visual disability was assessed with the Activities of Daily Vision
Scale, or ADVS.3
The ADVS is a 22-item questionnaire that
assesses difficulty performing a range of vision tasks that were judged
to be important to cataract patients. Trained interviewers administered
the ADVS as originally published, excluding one question on the use of
bus service, which is not available in Salisbury. For each item, it was
determined whether the participant had done the activity within the
past 3 months, and if not, was this because of vision problems.
Activities that were not done recently for reasons unrelated to vision
were not scored. The remaining items were scored according to level of
difficulty (1 = unable to do because of vision problems; 2 =
extreme difficulty; 3 = moderate difficulty; 4 = a little
difficulty; and 5 = no difficulty).
Data Analysis
Visual acuity was scored as the total number of letters read
correctly and converted to logMAR (log10 minimum
angle resolvable) according to the method recommended by Bailey et
al.21
Briefly, each correctly identified letter reduced
the logMAR acuity by 0.02. Participants who failed to read any letters
were arbitrarily assigned an acuity of 1.7 logMAR (20/1000), 0.2 logMAR
worse than the lowest acuity measured. The relationship between
monocular and binocular acuity was evaluated with scatter plots and
regression analyses. The analyses were repeated after exclusion of the
five participants with unmeasurable acuities, and the results did not
change.
For the reading test, the number of correctly read words was counted and converted to reading rate in words per minute. Reading data were analyzed separately for each letter size. Participants who could not read text of any size were excluded from the analyses of reading performance. Reading data were missing for 211 participants (8%), either because they could not read (87) or because of equipment malfunction (124). Among those who could not read, 55 (62%) had acuities of 20/40 or better and were presumed to be illiterate. The relationships between visual acuity and reading rate were similar for all letter sizes, and only the data for newsprint-sized text (0.26°) will be presented here. Face recognition was scored as the number of correct responses in 15 trials. Face recognition data were missing for 124 participants (5%) because of equipment malfunction. The ADVS score was computed by averaging all scored items and rescaling to a range of 0 to 100, where 0 = unable to do any activities because of vision and 100 = no difficulty with any activity.
Separate linear regression analyses were used to determine the association between acuity and reading or face recognition. Both analyses were adjusted for age, race, gender, years of education, and Mini-Mental score. Residuals were evaluated for evidence of nonlinearity, and, where appropriate, linear spline regressions were also performed.22
The ADVS scores were highly skewed; therefore, it was felt to be inappropriate to use continuous linear regression. Instead, logistic regression analyses were performed to determine the association between acuity and dichotomized ADVS score. Regression models for each of the binocular and monocular acuity algorithms were compared by means of their receiver-operating characteristic (ROC). As it is used here, the ROC provides a metric for determining each algorithm’s ability to classify individuals with regard to their dichotomized ADVS scores.23 At any acuity level, the regression model predicts whether each participant will fall above or below the cutoff. The prediction can be compared with actual data to determine proportion of participants correctly predicted to fall below the cutoff, or sensitivity, and the proportion of participants incorrectly predicted to fall below the cutoff, or false-positive rate, as a function of acuity. Separate analyses were conducted with ADVS score dichotomized at the median, 25th percentile, and 10th percentile. Because the results were similar for all three dichotomization schemes we will only present results for the case where participants were classified as falling above or below the 10th percentile in ADVS score (70.8). Each model was adjusted for age, race, gender, years of education, and Mini-Mental score. All statistical analyses were performed with SAS (SAS Institute, Cary, NC).
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Results |
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Figure 1 (left) compares binocular acuity to the AMA-recommended weighted average of monocular acuities. If the AMA weighted average accurately predicted binocular acuity, the data would be expected to cluster along the diagonal line. However, most of the points are below the diagonal, indicating that the AMA weighting predicts worse binocular acuity than what is actually measured.
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Figure 2 (left) compares binocular acuity to acuity in the best eye alone. The data cluster along the diagonal line, indicating good agreement between the best-eye prediction and the observed binocular measurement. The discrepancy between binocular acuity and best-eye acuity, shown in Figure 2 (right), averages less than 0.2 ETDRS lines (1 letter), well within the test–retest variability.25 26 27 28 For 85% of participants (2170), the discrepancy between binocular and best-eye acuity is less than one ETDRS line (5 letters). There is a small but statistically significant change in the discrepancy with increasing interocular acuity difference (0.2 lines of discrepancy per five lines of interocular difference). This trend is examined in greater detail below.
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ROC analysis was used to determine the association between acuity and ADVS score. The area under the ROC is the metric for comparing algorithms. If the algorithm is a perfect classifier the sensitivity will be 1, the false-positive rate will be 0, and the area under the ROC will equal 1.0. If the algorithm performs at chance the sensitivity will be equivalent to the false-positive rate and the area under the ROC will equal 0.5. The ROC area was 0.78 for baseline variables plus binocular acuity.
Table 2 compares the strength of the association between the three outcome measures and each of the binocular and monocular acuity combination rules. All of the combination rules are equivalent when there is no interocular acuity difference. Because one half of the observers have less than a one-line difference in acuities between the two eyes, one would expect little difference among the algorithms when they are applied to the entire data set. This was indeed the case, as shown in the left half of Table 2 . As a stronger test of differences between combination rules, the regression models were refit to the subset of data for participants with more than three lines of interocular acuity difference (n = 261). The summary statistics are listed in the right half of Table 2 . For reading speed, binocular acuity and monocular acuity accounted for 65% and 63% of the variance, whereas the AMA and FVS algorithms accounted for only 49% and 52%, respectively. For face recognition and ADVS score the four models still yield nearly equivalent results.
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Discussion |
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Based on previous studies with small groups of subjects it was expected that our participants with similar acuities in the two eyes would show binocular summation (i.e., the binocular acuity would be better than the monocular acuity in the better eye). Figure 4 shows that there is a small binocular summation, 0.03 logMAR units or 1.5 letters on average for the group with less than a one-line acuity difference between the two eyes. Although the binocular summation is statistically significant (t = 18.5; P < 0.0001), it is about half that reported in previous studies8 12 and of doubtful clinical significance. All the participants in the present study were 65 years of age and older. The previous studies included younger and older subjects. However, age itself is unlikely to explain the discrepancy because one of the previous studies12 compared binocular summation for younger (21 ± 2 years) and older (66 ± 6 years) subjects and found that the summation for the older group was somewhat greater than for the younger group.
It was hypothesized that binocular summation would be greater in the present study than in previous studies with younger observers because summation is enhanced under conditions of reduced retinal illuminance or contrast,10 both of which are common in the elderly, even among those without frank eye disease. Weale29 has estimated that there is an overall two- to threefold reduction in retinal illumination from 20 to 60 years of age, mostly caused by increased lenticular absorption and pupillary miosis. Age-related increases in intraocular light scatter reduce retinal image contrast.30 31 32 Given these ocular changes and resultant loss in illumination and contrast at the retina, we expected to see greater binocular summation in participants with equal vision in the two eyes. The absence of such an effect may indicate that the age-related loss of retinal illumination and contrast is small compared with that required for a change in binocular summation. On the other hand, previous studies of binocular contrast33 and luminance summation34 have shown a decrease rather than an increase in summation with advancing age.
Our results also show less than a one letter difference, on average, between monocular and binocular acuities for participants with unequal acuities in the two eyes. Equal numbers showed binocular inhibition and binocular summation. Previous data on individuals with unequal monocular acuities have been equivocal. One study of unilateral cataract patients showed minimal binocular inhibition, averaging 0.05 logMAR (2.5 letters),35 one study showed minimal summation (also averaging approximately 0.05 logMAR),36 and two studies showed neither inhibition nor summation.11 12 A detailed study of four subjects with normal vision in whom the contrast of the targets presented to one eye was reduced showed no binocular inhibition.8 Thus, there is little consistent evidence for significant binocular inhibition.
This study also demonstrates that the influence of visual acuity on the performance of everyday tasks can be accounted for by monocular acuity in the better eye. Considering all participants in the study, monocular acuity in the better eye was as good a predictor of performance as binocular acuity or algorithms based on weighted sums of monocular acuities. However, the various algorithms are differentiated only for people with significant discrepancies between the acuities in the two eyes. For the subset of participants with interocular acuity differences greater than three lines, monocular acuity was equivalent to binocular acuity and both were as good or better predictors of performance than the weighted monocular acuity algorithms.
In comparing the various algorithms, all analyses were based on best-corrected visual acuities. One might expect everyday visual function to be more closely associated with habitual acuity than with corrected acuity. However, a recently published study by Wang et al. in this journal37 showed that best-corrected acuity was a better predictor of self-rated health than was habitual acuity. When we reanalyzed the present data using habitual binocular acuity, the variance accounted for changed by no more than 1% compared with analyses based on habitual acuity.
One implication of this study concerns the expected benefit of second-eye cataract surgery. If binocular acuity, self-reported visual function, and performance are controlled by acuity in the better-seeing eye, then second-eye surgery should have little effect on acuity, visual function, or performance. However, results from a prospective study of 613 patients undergoing cataract surgery showed similar improvement in subjective visual function for first-eye and second-eye surgeries.38 The results of two smaller studies may help explain the apparent paradox. The first study showed significant changes in reading speed, face recognition, mobility performance, and perceived visual disability after second-eye surgery.39 In the second study there was a marked decrease in reported symptoms, and all patients reported that their vision had improved after second surgery.40 Although statistically significant, the acuity differences in both studies were small and comparable to the average difference between monocular and binocular acuities reported in the present study. The authors attribute much of the subjective improvement to gains in contrast sensitivity, binocularity, and other visual factors that may not be captured by tests of acuity alone. Therefore, although the gains in binocular acuity after second-eye cataract surgery may be modest, the effect of such surgery on overall visual ability can be substantial. It is important to consider that visual acuity is certainly not the only or perhaps even the best predictor of function. We41 and others42 have shown that contrast sensitivity is an important predictor of self-reported difficulty with daily visual activities among the elderly.
In summary, the widely used AMA algorithm does not provide an accurate method for predicting binocular visual function when the acuities in the two eyes are dissimilar. If a measure of binocular acuity is not available, it may be inferred from acuity in the better-seeing eye. For tasks that are strongly associated with visual acuity, such as reading, this association can be captured by monocular acuity in the better-seeing eye rather than the weighted average of acuities in the two eyes.
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Footnotes |
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Submitted for publication December 9, 1999; revised May 5, 2000; accepted June 9, 2000.
Commercial relationships policy: N.
Corresponding author: Gary S. Rubin, Institute of Ophthalmology, 11-43 Bath Street, London EC1V 9EL, UK. g.rubin{at}ucl.ac.uk
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