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(Investigative Ophthalmology and Visual Science. 2007;48:4445-4450.)
© 2007 by The Association for Research in Vision and Ophthalmology, Inc.
DOI:  10.1167/iovs.07-0326
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Visual Field Loss Increases the Risk of Falls in Older Adults: The Salisbury Eye Evaluation

Ellen E. Freeman,1 Beatriz Muñoz,1 Gary Rubin,2 and Sheila K. West1

1From the Department of Ophthalmology, Wilmer Eye Institute, Johns Hopkins School of Medicine, Baltimore, Maryland; and the 2Institute of Ophthalmology, University College, London, United Kingdom.


   Abstract
Top
 Abstract
Materials and Methods
 Results
 Discussion
 References
 
PURPOSE. Falls are a serious and preventable problem in older adults. Impaired vision has been linked to risk of falls; however, the impact of deficits in specific components of vision on the risk of falls is not well known.

METHODS. Data on falls for up to 20 months were provided by 2375 individuals participating in the Salisbury Eye Evaluation (SEE). Visual acuity, contrast sensitivity, visual field, and stereoacuity were tested by using standard measures. To aid in the assessment, each participant recorded falls on a calendar that was sent every month to the SEE clinic. ß-Binomial regression analysis was used.

RESULTS. Worse visual field scores were associated with the risk of falling (OR = 1.08 for a 10-point loss of points, 95% CI 1.03–1.13). When both central (≤ 20° radius) and peripheral visual fields were in the same model, only the peripheral visual field was associated with falls (OR = 1.06, 95% CI 1.01–1.10). Visual acuity, contrast sensitivity, and stereoacuity were not associated with falls after adjustment for demographic and health variables.

CONCLUSIONS. Visual field loss is the primary vision component that increases the risk of falls. This finding highlights the importance of visual field deficits in the risk of falls and supports other findings on decrements in mobility and increased risk of bumping with worsening visual field function. Persons with visual field loss may benefit from mobility training to reduce the risk of falling.

Falls are a common occurrence in older adults and can have serious consequences. For example, studies report that approximately one third of older adults living in the community have at least one fall per year.1 2 Older adults who fall are at greater risk of hospitalization,3 nursing home admission,3 4 and death.3 5 6 However, multifactorial intervention strategies have demonstrated efficacy in preventing falls in older adults.7 8 9 10

One cause of falls in older people is poor vision, and several studies have found that visual acuity is associated the risk of falling.11 12 13 14 15 In fact, many multifactorial interventions designed to prevent falls include either an objective or subjective assessment of visual acuity.16 However, other components of visual function may be as or more important in the risk of falls.

Detailed studies of other measures of visual function besides acuity, such as contrast sensitivity, visual field, and/or depth perception, have reported associations with falls.11 13 14 17 18 For example, Ivers et al.11 and Klein et al.14 found that worse visual acuity, contrast sensitivity, and visual field function were associated with falls, while Lord and Dayhew17 found that worse low-contrast visual acuity, contrast sensitivity, and depth perception were associated with falls. These studies have provided valuable information on visual function and falls. However, many have had limitations, either due to a small sample,13 17 a retrospective assessment of falls (which may underestimate them),11 13 14 or the inability or failure to adjust for potential confounders such as age, gender, and comorbidities.13 17 Besides age and gender, other factors known to be important in the risk of falls include neurologic conditions, arthritis, poor balance, and use of sedatives.19

The objectives of this analysis were to examine the specific components of vision that are independently related to the risk of falling, by using a prospective assessment of falls in a large, population-based study of older adults.


   Materials and Methods
Top
 Abstract
 Materials and Methods
Results
 Discussion
 References
 
Study Population
The data for this analysis were obtained from individuals who participated in the Salisbury Eye Evaluation (SEE) and who provided monthly data on falls that they had experienced for up to 20 months. The SEE study was a population-based cohort study of 2520 older adults. Data were collected for the SEE baseline visit between September 1993 and September 1995. Follow-up data were collected 2 years later. The prospective monthly falls data collection began in August 1994 in the middle of the baseline data collection. Additional participants were recruited for the falls data collection during the follow-up SEE visit. Overall, 64% of the participants who provided falls data did so after the baseline visit and 36% did so after the follow-up visit. Approval from The Johns Hopkins University Joint Committee on Clinical Investigation was obtained. Written informed consent was obtained for all participants and the protocol adhered to the tenets of the Declaration of Helsinki.

The SEE sample was selected from the Health Care Financing Administration Medicare database. The eligibility criteria were age between 65 and 84 years; residence in the Salisbury area, but not in a nursing home; ability to communicate; and a score higher than 17 on the Mini-Mental State Examination (MMSE). A more detailed description of the study population is available elsewhere.20 21 There were 3906 individuals eligible for the SEE study, of which 2520 completed both the home questionnaire and the clinical examination (65% response rate). There were 2375 (94%) participants who provided monthly prospective data on falls.

Falls Assessment
Falls were assessed over a 20-month period through the use of a monthly calendar.22 A fall was defined as "unintentionally coming to rest on the ground or at some other level." Individuals were asked to record whether a fall occurred for each day of the month. At the end of the month, they were asked to mail the calendar to the SEE clinic. For the falls that had occurred, participants were called and asked additional questions about the circumstances. If no calendar was received by the clinic, the participant was asked in a telephone call about falls for the month. Seventh-nine percent of the falls data were obtained by mailed calendar, and 21% were obtained by telephone.

Vision Assessment
Visual function was evaluated during the baseline examination at the SEE clinic, as described previously.20 Presenting (or habitual) visual acuity was scored as the number of letters read correctly on the Early Treatment of Diabetic Retinopathy Study (ETDRS) chart while participants wore their normal prescriptions and was then converted to logMAR (log minimum angle of resolution) units.23 The luminance of the chart was 130 cd/m2, back illuminated. Contrast sensitivity in each eye was measured with a Pelli-Robson chart that was illuminated at approximately 100 cd/m2. Measures for the better eye were used in analyses. Visual fields were measured in each eye using an 81-point, single-intensity (24 dB), full-field (60°) screen (Humphrey Instruments; Carl Zeiss Meditec, Dublin, CA). The binocular visual field was estimated from a composite of the more sensitive of the two visual field locations for each eye.24 A total of 96 visual field locations composed the binocular visual field. The binocular central visual field (≤ 20° radius) was measured at 56 centrally located points. The binocular lower peripheral visual field (>20°and ≤ 60°) was measured at 22 points located in the lower peripheral field, whereas the remaining 18 points composed the binocular upper peripheral visual field. Stereoacuity was measured with the Randot Circles test. Stereodeficiency was present if the individual could not identify the disparity in any of the 10 panels (stereoacuity worse than 457 arc sec).

Questionnaire and Clinic Examination
An interviewer-administered questionnaire that collected information on demographic and medical information was given to the participants in their homes. They were asked whether they had received a physician’s diagnosis of any of 15 medical conditions including arthritis, stroke, and Parkinson’s disease. The total number of these comorbid conditions was calculated as an overall measure of comorbidity. A complete list of currently used medications was recorded for each participant. For analysis, all drugs were coded according to the Iowa Drug Information System.25 Sedatives were defined as any benzodiazepines, phenothiazines, or antidepressants, as defined in a study of falls by Tinetti et al.2

Depressive symptoms were evaluated with the General Health Questionnaire Part D.26 Performance measures were used to assess grip strength (a measure of frailty) and balance. Grip strength was measured two times with a hand dynamometer (Jamar; Pro-Med Products, Inc., Atlanta, GA). The average of the two measures was used in the analysis. Balance was measured by a series of three timed stands that varied in difficulty.27 Poor balance was defined as the inability to stand with feet side-by-side, eyes open, and arms folded across the chest for 30 seconds.

Data Analysis
The characteristics of individuals were compared by whether falls data were provided. Differences between those who did and did not provide falls data were tested for statistical significance by using logistic regression models adjusted for age.

Baseline vision and covariate data were used if the falls data were collected after the baseline visit. Follow-up vision and covariate data were used if the falls data were collected after the follow-up visit.

The outcome for the analysis was whether at least one fall had occurred during each month of follow-up per person. The associations of vision, health, and demographic variables with the odds of falling were determined by using ß-binomial regression, an extension of the traditional logistic regression model. The ß-binomial model is appropriate for binary clustered data such as may occur for an individual who falls repeatedly.

Covariates that were considered for inclusion in final regression models included factors thought to contribute to the risk of falls, based on prior literature. These included age, gender, race, cognitive impairment, comorbid conditions, medication use, balance, and grip strength. Cognitive impairment was retained in the final model regardless of statistical significance, to assure readers that it had been taken into account, whereas other variables were only retained in the final regression models if P ≤ 0.10, to avoid overfitting the model. History of falls and fear of falling were associated with prospective falls but were not included in the final regression models because these variables may be in the causal pathway for vision loss and incident falls and thus could attenuate the results. Balance was included in the final model, although a model without balance was also examined because of similar concerns that balance is in the causal pathway for vision loss and falls. Odds ratios for the continuous vision variables were given per 10% increment of the total range to provide odds ratios that were more clinically meaningful. Interactions between the vision variables and demographic factors such as gender and race were examined by entering interaction terms into the regression models. The round of data collection (baseline or follow-up) was also examined as a confounder and effect modifier.

Analyses were performed with commercial software (Egret for Windows; Cytel Statistical Software Corp., Cambridge, MA).


   Results
Top
 Abstract
 Materials and Methods
 Results
Discussion
 References
 
Of the total participants, 145 did not provide prospective information on falls. In addition, 63 individuals completed less than 20% (4 months) of the follow-up time and therefore were not included in the analysis. The 208 individuals who were not included in the analysis were older and more likely to be African-American; to have lower MMSE scores; and to have depressive symptoms, more comorbid conditions, poor balance, a slower walking speed, and worse vision, and a greater history of falls (Table 1) .


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  		TABLE 1. Characteristics of Those Who Provided Data on Falls Compared with Those Who Did Not

 
Of the 2312 individuals who had between 4 and 20 months of follow-up, 29% (n = 680) had at least one fall during the follow-up period. The mean number of months of follow-up was 17. At least one fall occurred in 3.1% of follow-up months, whereas the total number of falls divided by the total number of follow-up months was 4.2%. The circumstances of the first fall per month (index fall) were obtained for 743 individuals (61% of the 1227 index falls). When asked "What were you doing when you fell?", 50% of participants reported doing a mildly displacing activity such as standing still, walking, or dressing, whereas 46% reported doing a moderately displacing activity like bending, reaching, or stepping, and 4% reported doing a markedly displacing activity like sports or climbing. Forty percent stated that a trip or slip caused the fall and 10% mentioned falling on the stairs. Eleven percent of falls resulted in serious injury.

The nonvision characteristics associated with increased risk of falling after adjustment for age included female gender; white race; depressive symptoms; use of sedatives; three or more comorbid conditions; a history of Parkinson’s disease, arthritis, diabetes, vertigo, or stroke; poor balance; slower walking speed; low grip strength; a history of falling; and fear of falling (Table 2) .


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  		TABLE 2. Falls Rate by Demographic and Health Characteristics in 2312 Community-Dwelling Older Adults

 
The only vision variable associated with falling after adjustment for age was binocular visual field. We further explored the location of the visual field deficit–central visual field and lower and upper peripheral visual fields—and all were significantly associated with an increased risk of falls (Table 3) . Visual acuity, contrast sensitivity, and stereodeficiency were not significantly associated with falls after adjustment for age, although the odds ratios were in the predicted direction.


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  		TABLE 3. The Odds of Falling at Least Once Per Month by Baseline Vision Variables in Simple or Age-Adjusted Regression Models

 
The independent relationships between total visual field and other nonvision variables with the odds of falling are presented in Table 4 . Older age, white race, depressive symptoms, low grip strength, Parkinson’s disease, arthritis, stroke, sedative use, and poor balance, in addition to visual field deficit, were all independently related to the odds of falling. After further adjustment for visual acuity and contrast sensitivity, the odds ratio for total visual field increased slightly to 1.11, and neither visual acuity nor contrast sensitivity was statistically significant (data not shown).


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  		TABLE 4. The Odds of Falling by Visual Field and Nonvision Variables in Multiple Regression Model

 
Central and peripheral visual field losses were also associated with the odds of falling after adjustment for demographic and health variables (Table 5 , models 2 and 3). In a model to determine the independent associations of central and peripheral visual field deficits by mutual adjustment for each other, peripheral visual field loss remained statistically significant, whereas the estimate associated with losses in the central visual field was reduced and fell short of statistical significance (Table 5 , model 4). Although we attempted to separate the contributions of upper and lower peripheral visual field losses, neither was statistically significant when considered together in a model (Table 5 , model 5).


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  		TABLE 5. The Odds of Falling by Visual Field Measures in Five Separate Multiple Regression Models

 
No statistically significant interactions were identified.


   Discussion
Top
 Abstract
 Materials and Methods
 Results
 Discussion
References
 
Our findings indicate that visual field deficits are associated with the risk of falling, whereas, after adjustment, acuity, contrast sensitivity, and stereodeficiency were not associated with falling. When central and peripheral visual field were entered into the model together, only the peripheral visual field remained statistically significant, whereas the estimate for the central visual field was attenuated. This result may indicate that losses in the peripheral visual field was a more important risk factor for falling, although the moderate correlation between the two visual field components makes it difficult to tease apart the independent relationships. We were unable to determine whether the upper or lower peripheral visual field was more important.

Visual field reduction is most likely related to the risk of falls, at least in part, through its effects on postural stability and the ability to maneuver around objects. Studies have found that people with a worse visual fields have worse postural stability,28 29 which is associated with falling.30 31 32 Other studies have found that worse visual field scores are associated with greater incidence of bumping into objects on a mobility course,27 which could also lead to a greater tendency to fall. Other ways in which visual field deficits may be related to the risk of falling may include a decreased ability to detect steps or changes in surface. Our results showing the association between visual field function and falls extend and confirm the associations found in several other large population-based studies11 13 14 33 and further suggest the greater importance of the peripheral visual field.

In a previous analysis of risk factors for falls in this population, we used a retrospective recall of falling over a 12-month period and focused on clarifying the temporal relationship of falling and fear of falling. In that analysis, we did not find that any vision measures were associated with a fall.34 Differences between our previous results and our current results are probably due to the different assessment of falling (retrospective versus prospective) and to a different analytical strategy.

The proportion of older adults who had at least one fall in our study is consistent with findings in other community-based studies that measured falls by prospective assessment. In our study, 29% of individuals 65 to 84 years of age fell at least once over an average follow-up period of 17 months. Tinetti et al.2 found that 32% of adults 75 years of age and older fell at least once over a 1-year period. Campbell et al.35 found that 35% of adults 70 years of age and older fell at least once in a 1-year period.

Our results showing that visual acuity, contrast sensitivity, and stereoacuity were not associated with falls are in conflict with findings in some studies and in agreement with those in others. Several large, prospective studies have found worse visual acuity to be associated with the risk of falls.11 13 14 15 However, other prospective studies have not found an association with visual acuity.17 35 36 Inconsistent results have also been found for contrast sensitivity. Some studies have shown an association between contrast sensitivity and falls,11 14 37 and some have not.13 36 Reasons for these different results are unclear. Finally, we did not find a relationship between stereoacuity and falls, but at least two other studies have.17 36 The use of different tests may explain disparate results for stereoacuity, since we used the Randot Circles test, whereas Lord and Dayhew17 used the Frisby Stereotest, and it is unclear what test and procedures Nevitt et al.36 used. It has been suggested that tests such as the Randot circles yield an excessively high number of failures because of the difficulty in fusing the disparate targets.38 This misclassification could result in an association between stereoacuity and falls that is biased toward the null.

The strengths of this analysis include the large sample of older adults, the multiple, objectively assessed measures of visual function, and in particular, the prospective assessment of falls. Some individuals (n = 208) did not provide complete data on falls, and these tended to be those whose risk factor profile suggest they are at high risk of falling and had worse visual function. Therefore, their exclusion from the analysis may have resulted in conservative estimates of the associations between vision and falling.

Our data indicate that visual field deficit, rather than reduced acuity, contrast sensitivity, or stereoacuity, is a risk factor for incident falls. For each 10% loss in visual field, individuals experienced an 8% higher odds of falling after adjustment for other factors. Therefore, people with bilateral glaucoma, who on average would miss 48 points in the total visual field, would have had a 46% higher odds of falling. Although visual field loss cannot be reversed, persons with such deficits may benefit from mobility training to navigate the environment more safely and reduce the risk of falling.


   Footnotes
 
Supported by Grant AG16294 from the National Institute on Aging (SKW). SKW is funded by a senior scientific investigator award from Research to Prevent Blindness.

Submitted for publication March 16, 2007; revised June 18, 2007; accepted August 22, 2007.

Disclosure: E.E. Freeman, None; B. Muñoz, None; G. Rubin, None; S.K. West, 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: Sheila K. West, Wilmer Eye Institute Room 129, Johns Hopkins School of Medicine, Baltimore, MD 21287; shwest{at}jhmi.edu.


   References
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 Abstract
 Materials and Methods
 Results
 Discussion
 References
 

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