impaired Depth perception and restricted pitch

Journal of Gerontology: MEDICAL SCIENCES Cite journal as: J Gerontol A Biol Sci Med Sci. 2010 July;65(7):751–757 doi:10.1093/gerona/glq015

© The Author 2010. Published by Oxford University Press on behalf of The Gerontological Society of America. All rights reserved. For permissions, please e-mail: [email protected]. Advance Access published on February 12, 2010

Impaired Depth Perception and Restricted Pitch Head Movement Increase Obstacle Contacts When Dual-Tasking in Older People Jasmine C. Menant, Rebecca J. St George, Richard C. Fitzpatrick, and Stephen R. Lord Falls and Balance Research Laboratory, Prince of Wales Medical Research Institute, University of New South Wales, Sydney, Australia. Address correspondence to Professor Stephen R. Lord, PhD, DSc, Falls and Balance Research Laboratory, Prince of Wales Medical Research Institute, University of New South Wales, Barker Street, Randwick, New South Wales 2031, Australia. Email: [email protected]

Methods. Thirty community-living adults aged 65 years and older walked along a 14.5-m walkway containing 21 obstacles with and without a secondary task. The secondary task required participants to call out a series of letters presented in front of them at head height and the suit of a playing card framed on the sidewall. Obstacle contacts, secondary task errors, eye peak-to-peak pitch amplitude and head peak-to-peak pitch amplitude (PA-H), and head angle in pitch were measured. Participants also completed assessments of sensorimotor function and balance. Results. Compared with the obstacle-only trials, participants performed the dual-task trials more slowly (p < .001), contacted more obstacles (p = .032), showed greater PA-H (p < .001), and an extended head position (p < .001). Most participants also made secondary task errors. Regression analysis revealed that depth perception was the only significant determinant of obstacle contacts (explaining 20.6% of the variance) in the obstacle-only task and that depth perception and PA-H were independent and significant determinants of obstacle contacts (explaining 42.3% of the variance) in the dual task. Conclusion. The findings demonstrate the importance of depth perception and head movement for safe negotiation of obstacles in older people and suggest that depth perception in particular should form part of fall risk assessments. Key Words: Aged—Depth perception—Gait—Dual tasks—Obstacle avoidance. Received August 4, 2009; Accepted January 19, 2010 Decision Editor: Darryl Wieland MD, PhD

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rips are a commonly reported cause of falls and are reported to contribute between 35% and 53% of falls in older people (1,2). Poor lower limb strength as suggested by poor leg press push off force (3), fast walking speed prior to crossing an obstacle (4), and delayed support limb loading (4) are associated with a greater risk of falling following an obstacle contact in healthy older adults. Delayed lower extremity muscle activity onset and reduced amplitude of muscle responses (5), as well as visual factors such as refractive blur or the wearing of multifocal glasses (6–9) have also been implicated in obstacle contacts in healthy older adults. The generalizability of these findings is limited in that they relate only to the crossing of a single obstacle or step, either already present in the path or appearing suddenly. In everyday life, when older people navigate in a challenging and distracting environment such as a shopping mall or busy street, they might have to avoid ground level obstacles when their attention is divided. In this instance, obstacle negotiation performance is likely to be further impaired as revealed by most dual-task studies involving older adults (10–12).

To date, no studies have examined the underlying physiological mechanisms that contribute to safe obstacle course negotiation in older people, either with or without the addition of a secondary task. Such information is important for the selection of relevant sensorimotor screening tests to identify risk factors for trips and stumbles and prevent subsequent falls in older people. The objectives of this study, therefore, were to examine (i) the effect of a secondary visual task on obstacle contact when older people negotiated an obstacle course and (ii) physiological factors associated with obstacle course negotiation (obstacle contacts and trial time) in trials with and without the secondary task.

Methods

Participants Thirty community-living volunteers aged 65 years and older (women, n = 15; M [±SD] age: 76.7 ± 6.3 years; range: 66–91 years) were recruited from the intervention group of 751

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Background. Trips are the largest contributor to falls in older people, yet little is known about the underlying physiological mechanisms for safe obstacle negotiation. The aims of the study were to determine (i) the effect of a secondary visual task on obstacle contacts when older people negotiated an obstacle course and (ii) physiological factors associated with obstacle contacts.

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Glasses Conditions All 30 participants wore single lens glasses (prescribed by an optometrist to ensure appropriate visual correction) while undertaking the trials. As a major component of the RCT intervention, participants had been wearing these glasses when undertaking activities of daily living outside their homes for a minimum period of 1 month (M [±SD]: 8.33 ± 6.53 months) at the time of this study. Visual Tests Corrected visual acuity was assessed binocularly using a 3-m logMAR chart (16). Edge contrast sensitivity was assessed using the enlarged version of the Melbourne Edge Test (17), whereby participants were required to fixate targets placed at ground level, 135 cm in front of them (18). Depth perception was assessed using a Howard–Dohlman depth perception apparatus (19), which requires participants to align two vertical rods (0.8 cm diameter) in depth from a distance of 3 m (18). Error in aligning the rods was measured in millimeters. Sensorimotor Function Assessment As part of participation in the larger trial, the participants were assessed on a series of sensorimotor tests: proprioception, lower limb strength, simple reaction time, and postural sway, evaluating some key components of the human balance system. Descriptions of the apparatus, procedures, and

Figure 1. Experimental setup used for the dual-task trials.

test–retest reliability for these tests are reported elsewhere (20). In brief, proprioception was assessed using a lower limb–matching task. The angle of error (degrees) was determined using a protractor inscribed on a clear acrylic sheet (60 × 60 × 1 cm) placed between the legs. The average error from five trials was recorded. Simple reaction time (milliseconds) was measured using a handheld electronic timer and involved a light as the stimulus and a finger press as a response; the average of 10 trials was recorded. Knee isometric extension strength was assessed while the participant was sitting with both knee and hip placed at angles of approximately 90°. The best of three attempts was recorded. Postural sway (path length in millimeters) was recorded using a swaymeter that measured the displacement of the body at the level of the waist as the participants stood quietly barefoot on a foam mat (60 × 60 × 15 cm thick) for 30 seconds. Experimental Protocol Participants walked along a 14.5-m long-level walkway covered with light blue linoleum. They performed six walking trials, three of these were obstacle-only trials and three dual-task trials, presented in a randomized order. Participants wore their everyday shoes and were encouraged to keep walking during the trials. The obstacle course consisted of 7 foam blocks (smallest [Width × Height × Length]: 100 × 7 × 6.5 cm; largest: 100 × 6.5 × 21 cm) and 14 cardboard strips (100 × 0.5 × 3 cm) matching the floor color. These obstacles were placed across the walkway at intervals ranging from 0.35 to 1.30 m, on one side of a 1.90-m-wide corridor. They were chosen to create a challenging stepping task and placed in a scattered pattern to prevent participants from planning their steps. The first and last obstacles were placed at 1.20 and 12.95 m, respectively, from the start of the walkway. The order of obstacles was kept constant throughout the study. In the obstacle-only trials, participants were asked to walk along the walkway at a self-selected speed and to avoid contact with the obstacles. The dual-task trials comprised two visual tasks. While negotiating the obstacle course, participants were required to look up and read aloud three letters from a computer screen positioned at approximate head height at the end of the walkway (17.5 m away from the start; Figure 1). A sequence of three letters was


the VISIBLE randomized controlled trial (RCT) on the effects of moderating the use of multifocal glasses as a falls prevention strategy (U.S. National Institutes of Health registration number NCT00350389) (13). All participants were independent in activities of daily living, such as dressing, bathing and toileting, and were able to walk 800 m without assistance. Cognitive functioning was examined using the MiniMental State Examination (14), and all participants scored more than or equal to 26, indicating intact cognitive function. Eleven participants reported a history of cataracts (nine in both eyes), and of these, six had undergone surgery. Two participants suffered from macular degeneration, one of them in both eyes. Two participants reported glaucoma. Thirteen participants reported hearing impairment, 6 diabetes, 2 stroke, 6 transient ischemic attack, and 14 arthritis. Sixteen participants reported falling in the previous 12 months and eight of them fell more than once. Concern about falls when carrying out activities was rated using the “Falls Efficacy Scale-International” (FES-I) (15). The mean FES-I score recorded was 24 ± 6 (range 16–39), indicating low concern about falls as this scale ranges from 16 (low fear) to 64 (high fear). The experimental protocol was approved by the University of New South Wales Human Research Ethics Committee (HREC 04229), and all participants gave written informed consent prior to data collection.

IMPAIRED DEPTH PERCEPTION INCREASES OBSTACLE CONTACTS

Data Collection Trial time, obstacle contacts, and secondary task errors.— Time to complete each walking trial was recorded using a stopwatch. The number of obstacles contacted and secondary task errors (letters both missed and incorrectly reported) was recorded during each trial. The number of secondary task errors was expressed as a percentage of the number of letters that had appeared on the screen during the walking trial. Eye movements.—Right eye vertical movements were recorded at 30 Hz using a lightweight custom-built videobased eye tracker firmly mounted to the head with a light plastic frame. This device used infrared pupil reflections to determine visual fixation relative to the head. The eye tracker was calibrated for each participant using a two-point calibration, whereby the participants were asked to alternatively fixate on one of two points vertically aligned on a wall and separated by 20 cm. Participants were seated with their chin resting on a chin rest so that the perpendicular distance between their eyes and the middle of the two points remained constant (106 cm). This ensured that the eye vertical displacement corresponding to switching focus from one point to the other was equal to 10°. The ratio of this known vertical eye movement to that recorded simultaneously by the eye tracker was then computed and used to calibrate the vertical eye movements recorded in the subsequent walking trials.

Head movements.—Head movements in pitch were sampled at 25 Hz using an inertial sensor (MTi; XSens Technologies B.V., Enschede, the Netherlands) fastened to a headpiece at the level of the superior coronal suture. Head movement data were collected through the data acquisition card of a laptop computer into custom written software in LabVIEW (LabVIEW 8.0; National Instruments, Austin, TX). Head movement data were recorded to understand better how head movement affects safe negotiation of a complex environment in older people. Data Analysis Data analysis was performed using a custom written program in LabVIEW (LabVIEW 8.0; National Instruments). The eye movement data were filtered using a low-pass second-order Butterworth filter with a cutoff frequency of 2.5 Hz to remove blink artifacts. The head movement data were low-pass filtered to isolate the volitional movement by removing the higher frequency components associated with heel contact with the ground (2.5 Hz, second-order Butterworth filter). The overall mean head angle (HA; degrees) in the pitch plane was computed for each trial. Positive angles corresponded to an extended head position and negative angles corresponded to a flexed head position. Mean peakto-peak pitch amplitudes of the eye (PA-E) and the head (PA-H; degrees), defined as the average movement from each minimum to each maximum over the course of the trial, were computed for each trial. The trial time, secondary task errors, obstacle contacts, HA, PA-E, and PA-H measurements derived from three trials in each task condition were averaged for each participant. The dual-task cost was calculated in terms of percentage increase time taken to complete the trials in the dual task compared with the obstacle-only task according to the following formula: Dual-task cost = ([trial time in dual-task trials − trial time in obstacle-only trials]/trial time in obstacle-only trials) × 100. Statistical Analysis To permit parametric analysis, variables with positive skewness, the FES-I, visual acuity, depth perception, hand reaction time, sway path, and obstacle contacts data were log10 transformed. Paired t tests were used to assess differences in trial time, obstacle contacts, PA-E, PA-H, and HA between the obstacle-only and the dual-task trials. The relationships among experimental variables and age, FES-I, visual, and sensorimotor function variables were examined with Pearson correlations and partial correlations adjusting for age. Stepwise linear regression analyses were performed to identify independent and significant explanatory variables for obstacle contacts for the two trial conditions. The variables, which showed the strongest significant correlations with obstacle contacts, were entered into the stepwise linear regression with a limitation of one predictor variable per 10 cases. Despite the multiple comparisons made, p values


presented for more than 1.5 seconds (ie, each letter was presented for 500 milliseconds), and there was a 2-second break between presentation blocks. A distinct auditory cue signaled the imminent appearance of the first letter on the screen. The sequence of letters varied for each trial and, for clarity, each of the three letters in the sequence appeared in a different color: purple, green, and then brown. To ensure that the letters were similarly legible, 10 monosyllabic letters (C, D, E, F, L, N, O, P, T, and Z) from a visual acuity chart were displayed in Arial font. The letters were also of sufficient size (height: 261 mm, width: 224 mm, and line thickness: 34 mm) for participants to read them from the far end of the walkway. The second visual task required participants to glance to the side on two occasions and read aloud the suit of a playing card placed in frames at head height (one on either side of the walkway). A randomly chosen playing card was placed in each frame positioned at 3 and 7.5 m from the start; the cards were changed between each trial. For the dual-task trials, participants were instructed to prioritize avoiding contact with obstacles over successfully identifying the letters and cards. Participants were not given a practice of the obstacle course but were familiarized with the computer screen display of letters and the auditory cue prior to the first trial. The lighting conditions (267 lux at floor level) were kept constant throughout the walking trials.

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Table 1. Visual and Sensorimotor Function Variables M ± SD (n = 30)

Characteristics Visual function Visual acuity (logMAR) Edge-contrast sensitivity at 135 cm (dB) Depth perception (mm) Sensorimotor function Proprioception (error in °) Quadriceps strength (kg) Hand reaction time (ms) Postural sway on foam (mm2)

0.09 ± 0.12 24.27 ± 2.42 2.25 ± 1.86 1.57 ± 1.05 25.87 ± 10.85 240.69 ± 47.84 150.10 ± 74.08

Results Table 1 displays the mean (±SD) values for the visual and sensorimotor function variables. These values are consistent with those found in larger population studies of community-living older people (20). Comparison of Experimental Variables Between ObstacleOnly and Dual-Task Trials Table 2 shows the mean (±SD) values of the experimental measures in the obstacle-only and dual-task trials. The participants walked more slowly (t = 11.52, p < .001) and contacted more obstacles (t = 2.25, p = .032) in the dual-task trials compared with the obstacle-only trials. As expected, PA-H (t = 12.22, p < .001) and mean head position (t = 21.31, p < .001) differed significantly between trials, that is, participants walked with their head flexed in the obstacle-only trials and alternated head flexion and head extension in the dualtask trials. In addition, PA-E (t = 17.69, p < .001) increased

Table 2. Mean (±SD) Values for the Experimental Data in the Obstacle-Only and the Dual-Task Trials Variable Trial time (s) Obstacle contacts Secondary task errors (%) PA-E (°) PA-H (°) HA (°)

Obstacle-Only Trials (M ± SD)

Dual-Task Trials (M ± SD)

18.55 ± 3.87 1.40 ± 1.35 N/A‡ 14.00 ± 5.10 9.98 ± 2.92 −15.24 ± 6.73

25.58 ± 6.15* 1.87 ± 1.56† 5.32 ± 3.78 31.70 ± 9.24* 23.21 ± 7.53* 5.37 ± 6.24*

Notes: HA = head angle; PA-E = pitch amplitude of the eye; PA-H = pitch amplitude of the head. * Significant difference between trial conditions (p < .01). † Significant difference between trial conditions (p < .05). ‡ These data concerned the dual-task trials only.

Physiological Determinants of Obstacle Negotiation Performance Table 3 displays the correlation coefficients among sensorimotor, balance, and experimental variables in the obstacle-only and dual-task trials. Only the sensorimotor and balance variables that were significantly associated with at least one experimental variable are presented, and inspections of scatter plots revealed that none of the associations were unduly influenced by outliers. Obstacle-only trials.—Longer trial time was associated with weaker quadriceps strength (p = .024) and with increased postural sway (p = .046). Increased obstacle contacts were associated with poorer depth perception (p = .007). All significant associations remained significant after adjusting for age. Stepwise regression analysis revealed that poor depth perception was the only significant and independent determinant of obstacle contacts. This variable explained 20.6% of the variance in obstacle contacts (adjusted R2 = .206; Table 4). Dual-task trials.—As shown in Table 3, longer trial time was associated with reduced quadriceps strength (p = .007). Increased obstacle contacts were associated with poorer depth perception (p = .001) and reduced PA-H (p = .023). Secondary task errors were associated with longer trial time (p = .021), increased PA-H (p = .015), and a more flexed head position (p < .001). All significant associations with the exception of that between obstacle contacts and PA-H remained significant after adjusting for age. Stepwise regression analysis revealed that poor depth perception and restricted PA-H were significant and independent determinants of obstacle contacts. These two variables explained 42.3% of the variance in obstacle contacts (adjusted R2 = .423; Table 4). Concern About Falls and Obstacle Negotiation Performance The FES-I scores were negatively correlated with mean head position in the obstacle-only and the dual-task trials (r = −.364, p = .048 and r = −.372, p = .043, respectively) indicating that the greater the concern about falls, the more flexed the head position. The FES-I scores were also positively correlated with increased secondary task errors (r = .500, p = .005) such that participants with increased concern about falls made more secondary task errors. Finally, there was a trend for a relationship between increased concern about falls and slower trial time in both the obstacle-only and the dual-task trials (r = .309, p = .097 and r = .351, p = .057, respectively).


were not adjusted in this exploratory study as such adjustments may increase Type II errors, especially in studies with small sample sizes (21). All significance levels were set at p < .05. All statistical analyses were performed using SPSS (Version 15.02 for Windows; SPSS Science, Chicago, IL).

during the dual-task trials suggesting more frequent up and down gaze shifts to attend to both tasks. The mean (±SD) dual-task cost in terms of trial time was 37.9 ± 16.1%.

755

Standardized Beta

Multiple R

Depth perception

0.483*

.483

Depth perception

0.543*

.680

−0.362†

Notes: PA-H = pitch amplitude of the head. * Significant beta weight (p < .01). † Significant beta weight (p < .05).

Notes: HA = head angle; N/A = not applicable; PA-E = pitch amplitude of the eye; PA-H = pitch amplitude of the head. * These data concerned the dual-task trials only. † Significant correlation (p < .05). ‡ Significant correlation (p < .01).

Postural Sway

0.367* 0.204 N/A* −0.355 −0.250 0.114 −0.038 −0.481† — −0.412* 0.190 N/A* 0.128 0.032 0.178 0.316 — −0.481‡

Quadriceps Strength

Determinant Variables

PA-H

−0.169 0.483† N/A* −0.252 0.002 0.151 — 0.316 −0.038

Depth Perception HA

Obstacle contacts (obstacle-only trials) Obstacle contacts (dual-task trials)

−0.002 0.238 N/A* −0.148 0.000 — −0.245 −0.158 0.100 −0.161 −0.161 N/A* 0.193 — −0.377* −0.094 −0.170 −0.216

PA-H PA-E

0.040 −0.298 N/A* — −0.091 −0.087 −0.014 −0.005 0.108 N/A* N/A* — −0.256 0.439† −0.652‡ 0.337 0.024 0.043

Secondary Task Errors Obstacle Contacts

0.081 — 0.291 −0.219 −0.413† −0.011 0.577‡ 0.073 0.056 — −0.036 0.421† 0.058 0.223 −0.113 −0.158 −0.407* 0.240

Trial Time

Dependent Variable

Trial time Obstacle contacts Secondary task errors PA-E PA-H HA Depth perception Quadriceps strength Postural sway

Variables

Table 4. Determinant Variables Identified by the Stepwise Linear Regression Analysis for Obstacle Contacts

Discussion The study findings demonstrate that when their attention is divided, older people negotiate obstacles more slowly, contact more obstacles, and elucidate physiological and biomechanical impairments that hinder obstacle negotiation. In the obstacle-only trials, participants shifted their gaze minimally and kept their heads flexed as indicated by the negative value of mean head position and reduced pitch movement amplitude. This strategy would have provided consistent fixation of the floor-level obstacles. Visual acuity and contrast sensitivity were not significantly associated with obstacle contacts, which indicate that the obstacles were sufficiently visible to all. This finding is consistent with that of Patel and colleagues (22) who reported no significant associations between visual acuity, contrast sensitivity, and the percentage of preferred walking speed between a simple walking trial and an obstacle course. However, our findings suggest that ability to accurately judge the position of obstacles as indicated by good depth perception is crucial for obstacle avoidance. This result may help explain the consistent findings from epidemiological studies that impaired depth perception is a strong risk factor for both falls and fall-related hip fractures in older people (23). The secondary visual task dividing the participants’ attention was used to increase overall task complexity (24) and simulate a distracting environment in which people often ambulate during everyday life. In this condition, the participants displayed greater PA-H necessary for the more extended head position required to read the letters of the computer screen. The participants took longer to complete the dual-task trials, although, contrary to some previous findings (25), this did not improve stepping accuracy, that is, the participants contacted more obstacles when their attention was divided and also made some secondary task errors. It is likely that the present dual task, involving an obstacle course, was more complex than that of previous studies, which found that older adults prioritized performance either in the gait (11) or in the secondary task (26). In the dual-task condition, restricted PA-H joined poor depth perception as a significant and independent determinant of obstacle contacts. This suggests that restricted pitch head movement reduces the older people’s ability to safely negotiate a complex walking environment. Interestingly,


Table 3. Correlations Coefficients (r) Among Experimental, Visual, and Sensorimotor Variables in the Obstacle-Only Trials (upper half) and in the Dual-Task Trials (bold lower half)


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Funding This work was supported by the National Health and Medical Research Council (grant number 358055).

Acknowledgments We thank Marcella Kwan and Mamta Porwal for participant recruitment. References 1. Hill K, Schwarz J, Flicker L, Carroll S. Falls among healthy, community-dwelling, older women: a prospective study of frequency, circumstances, consequences and prediction accuracy. Aust N Z J Public Health. 1999;23: 41–48. 2. Lord SR, Ward JA, Williams P, Anstey KJ. An epidemiological study of falls in older community-dwelling women: the Randwick falls and fractures study. Aust J Public Health. 1993;17: 240–245. 3. Pijnappels M, van der Burg PJ, Reeves ND, van Dieen JH. Identification of elderly fallers by muscle strength measures. Eur J Appl Physiol. 2008;102: 585–592. 4. Pavol MJ, Owings TM, Foley KT, Grabiner MD. Mechanisms leading to a fall from an induced trip in healthy older adults. J Gerontol A Biol Sci Med Sci. 2001;56: M428–M437. 5. Weerdesteyn V, Nienhuis B, Geurts AC, Duysens J. Age-related deficits in early response characteristics of obstacle avoidance under time pressure. J Gerontol A Biol Sci Med Sci. 2007;62: 1042–1047. 6. Heasley K, Buckley JG, Scally A, Twigg P, Elliott DB. Stepping up to a new level: effects of blurring vision in the elderly. Invest Ophthalmol Vis Sci. 2004;45: 2122–2128. 7. Heasley K, Buckley JG, Scally A, Twigg P, Elliott DB. Falls in older people: effects of age and blurring vision on the dynamics of stepping. Invest Ophthalmol Vis Sci. 2005;46: 3584–3588. 8. Johnson L, Buckley JG, Harley C, Elliott DB. Use of single-vision eyeglasses improves stepping precision and safety when elderly habitual multifocal wearers negotiate a raised surface. J Am Geriatr Soc. 2008;56: 178–180. 9. Johnson L, Buckley JG, Scally AJ, Elliott DB. Multifocal spectacles increase variability in toe clearance and risk of tripping in the elderly. Invest Ophthalmol Vis Sci. 2007;48: 1466–1471. 10. Chen HC, Schultz AB, Ashton-Miller JA, Giordani B, Alexander NB, Guire KE. Stepping over obstacles: dividing attention impairs performance of old more than young adults. J Gerontol A Biol Sci Med Sci. 1996;51: M116–M122. 11. Harley C, Wilkie RM, Wann JP. Stepping over obstacles: attention demands and aging. Gait Posture. 2009;29: 428–432. 12. Kim HD, Brunt D. The effect of a dual-task on obstacle crossing in healthy elderly and young adults. Arch Phys Med Rehabil. 2007;88: 1309–1313. 13. Haran MJ, Cameron ID, Ivers RQ, et al. Preventing falls in older multifocal glasses wearers by providing single-lens distance glasses: the protocol for the VISIBLE randomised controlled trial. BMC Geriatr. 2009;9. 14. Tombaugh TN, McIntyre NJ. The mini-mental state examination: a comprehensive review. J Am Geriatr Soc. 1992;40: 922–935. 15. Yardley L, Beyer N, Hauer K, Kempen G, Piot-Ziegler C, Todd C. Development and initial validation of the Falls Efficacy Scale-International (FES-I). Age Ageing. 2005;34: 614–619. 16. Bailey IL, Lovie JE. New design principles for visual acuity letter charts. Am J Optom Physiol Opt. 1976;53: 740–745. 17. Verbaken JH, Johnston AW. Population norms for edge contrast sensitivity. Am J Optom Physiol Opt. 1986;63: 724–732. 18. Lord SR, Dayhew J, Howland A. Multifocal glasses impair edgecontrast sensitivity and depth perception and increase the risk of falls in older people. J Am Geriatr Soc. 2002;50: 1760–1766. 19. Graham CH. Visual space perception. In: Graham, CH ed. Vision and Visual Perception. New York, NY: John Wiley & Sons Inc; 1965: 504–547. 20. Lord SR, Menz HB, Tiedemann A. A physiological profile approach to falls risk assessment and prevention. Phys Ther. 2003;83: 237–252. 21. Perneger TV. What’s wrong with Bonferroni adjustments? BMJ. 1998;316: 1236–1238. 22. Patel I, Turano KA, Broman AT, Bandeen-Roche K, Munoz B, West SK. Measures of visual function and percentage of preferred walking


Paquette and colleagues (27) demonstrated that older people might be reluctant to excessively and rapidly move their heads when walking in an attempt to minimize ensuing postural instability. In addition, decreased range of motion in the cervical spine with older age has been documented (28), and the prevalence of arthritis and related neck pain in older adults (29) might further limit head movement. It is also possible that participants with lower PA-H values had difficulty attending to both tasks and thus prioritized the obstacle task at all times as instructed. The participants who were the most concerned about falls according to their FES-I scores held their head more flexed throughout the trials; this was likely a cautious strategy to maintain a visual focus on the obstacles that presented a risk of tripping. As a consequence, they made more secondary task errors. This is in agreement with recent research that showed that postural threat elicited gait adaptations in older people concerned about falls (30). It is acknowledged that despite the range of factors available as possible determinants, more than half of the variance in obstacle contacts was left unaccounted. Other factors that may have added additional information about performance in the task include ankle and knee joint range of motion, tactile sensitivity, and lower limb power. Depth perception and restricted PA-H were not significantly associated with previous falls (data not shown). Such lack of associations may be due to limitations with regard to the retrospective recording of falls and the fact that the participants were regular wearers of multifocal glasses during the falls surveillance period—a factor that influences both depth perception (18) and pitch head movement (31) as well as falls (18). In conclusion, older adults contacted more obstacles when their attention was divided, despite taking longer time to complete the trials and adapting their head movement strategy. Stepwise regression analysis revealed that depth perception and PA-H explained more than 40% of the variance in obstacle contacts in the dual-task trials. These findings demonstrate that ability to judge depth and pitch head movement are important contributors to safe negotiation of complex walking environments in older people and suggest that depth perception in particular should be included in routine falls risk screening. Furthermore, the associations between reduced quadriceps strength and increased sway and time to complete the obstacle course are consistent with other studies that have found that measures of lower limb strength and balance are determinants of stair climbing (32) and gait speed (33). There is some evidence that exercise training improves obstacle avoidance abilities (34,35). The present results imply that visual interventions may further enhance older people’s ability to negotiate obstacles in a safe and efficient manner.


29. March LM, Brnabic AJ, Skinner JC, et al. Musculoskeletal disability among elderly people in the community. Med J Aust. 1998;168: 439–442. 30. Delbaere K, Sturnieks DL, Crombez G, et al. Concern about falls elicits changes in gait parameters in conditions of postural threat in older people. J Gerontol A Biol Sci Med Sci. 2009;64: 237–242. 31. Menant JC, Sandery B, St George R, Fitzpatrick R, Lord SR. Older people contact more obstacles when wearing multifocal glasses while walking. J Am Geriatr Soc. 2009;57: 1833–1838. 32. Tiedemann AC, Sherrington C, Lord SR. Physical and psychological factors associated with stair negotiation performance in older people. J Gerontol A Biol Sci Med Sci. 2007;62: 1259–1265. 33. Tiedemann A, Sherrington C, Lord SR. Physiological and psychological predictors of walking speed in older community-dwelling people. Gerontology. 2005;51: 390–395. 34. Lamoureux E, Sparrow WA, Murphy A, Newton RU. The effects of improved strength on obstacle negotiation in community-living older adults. Gait Posture. 2003;17: 273–283. 35. Weerdesteyn V, Rijken H, Geurts AC, et al. A five-week exercise program can reduce falls and improve obstacle avoidance in the elderly. Gerontology. 2006;52: 131–141.


speed in older adults: the Salisbury Eye Evaluation Project. Invest Ophthalmol Vis Sci. 2006;47: 65–71. 23. Menant JC, Smith S, Lord SR. Visual determinants of instability and falls. Aging Health. 2008;4: 643–650. 24. McDowd JM, Craik FI. Effects of aging and task difficulty on divided attention performance. J Exp Psychol Hum Percept Perform. 1988;14: 267–280. 25. Alexander NB, Ashton-Miller JA, Giordani B, Guire K, Schultz AB. Age differences in timed accurate stepping with increasing cognitive and visual demand: a walking trail making test. J Gerontol A Biol Sci Med Sci. 2005;60: 1558–1562. 26. Schrodt LA, Mercer VS, Giuliani CA, Hartman M. Characteristics of stepping over an obstacle in community dwelling older adults under dual-task conditions. Gait Posture. 2004;19: 279–287. 27. Paquette C, Paquet N, Fung J. Aging affects coordination of rapid head motions with trunk and pelvis movements during standing and walking. Gait Posture. 2006;24: 62–69. 28. Castro WH, Sautmann A, Schilgen M, Sautmann M. Noninvasive three-dimensional analysis of cervical spine motion in normal participants in relation to age and sex. An experimental examination. Spine. 2000;25: 443–449.

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