Journal of Geriatric Physical Therapy:
Relationship of Executive Function and Educational Status With Functional Balance in Older Adults
Voos, Mariana Callil PT, PhD1; Custódio, Elaine Bazilio PT2; Malaquias, Joel Jr. PT2
1Physical Therapy, Occupational Therapy and Speech Therapy Department, Faculty of Medicine. University of São Paulo, São Paulo, Brazil.
2Neurological Physical Therapy Specialization Course, Universidade Gama Filho, São Paulo, Brazil.
Address correspondence to: Mariana Callil Voos, PT, PhD, Departamento de Fisioterapia, Fonoaudiologia e Terapia Ocupacional da Faculdade de Medicina da Universidade de São Paulo. Rua Cipotânea, 51, 2º. Andar. 05360-160. São Paulo. Brasil (email@example.com).
Background: The Berg Balance Scale (BBS) is frequently used to assess functional balance in older adults. The relationship of executive function and level of education with the BBS performance has not been described. The aim of this study was to determine whether (1) the performance on a task requiring executive function (part B of the Trail Making Test, TMT-B) influences results of motor and cognitive tests and (2) the number of years of formal education could be related to performance on BBS in older adults. We also explored whether there would be differences, based on performance on TMT-B (high vs low) in motor function (BBS, the timed up and go [TUG]) or cognitive function (TMT-A and TMTDELTA), the Mini Mental State Examination (MMSE), as well as years of education.
Methods: Participants included 101 older adults (age range, 60-80 years) residing in São Paulo, Brazil. Functional balance was assessed using BBS and TUG. Executive function was assessed using the TMT and MMSE. Educational status was determined by self-report of participant's total number of years of formal education.
Results: The BBS scores were inversely related to TMT-A time (r = −0.63, r2 = 0.40, P < .001) and TMT-B time (r = −0.56, r2 = 0.31, P < .001). There was a similar relationship with TMTDELTA (r = −0.47, r2 = 0.22, P < .001). The BBS scores were positively correlated to years of formal education (r = 0.48, r2 = 0.23, P < .001). There was a ceiling effect on the TMT-B, with many individuals reaching maximum score of 300 seconds. Participants with high levels of executive function had higher BBS and MMSE scores, more education, and lower TMT-A, TMTDELTA and TUG scores (P < .001) than the lower functioning group.
Conclusions: Individuals with higher capacity on tasks requiring visuospatial abilities, psychomotor speed, and executive function, such as the TMT, had better performance on BBS. Individuals with a high executive function, measured by TMT-B, also performed better on other motor and cognitive tests.
In older adults, balance tends to decrease as a result of age-related physiological changes. This may be the result of factors including greater dependence on visual inputs to control posture,1 increased sensory detection thresholds,2 decreased nerve conduction velocity,3 increased central processing time,4 decreased muscle strength,5 and increased passive tissue stiffness.6 Other factors that may impact on effectiveness of balance responses include the type and condition of footwear,7 over the counter and prescription medication,8 and concurrent motor and cognitive demands occurring during function.9,10 Such factors interact to increase both risk and incidence of falls.11 It is important to identify those older adults most at risk of falling. The Berg Balance Scale (BBS) is one of the most commonly used clinical measure of functional balance.12–16
More than 1 aspects of cognition (eg, memory, visuospatial ability, attention, and executive function) impact of efficacy of balance in older people.17–18 Dimensions of executive function that influence balance include planning, cognitive flexibility, response inhibition, and sequencing; all of these are thought to be mediated in the prefrontal cortex.19,20 Executive function is responsible for monitoring and processing internal and external information, establishing and achieving goals over time, solving problems, making decisions and emitting behaviors necessary to meet environmental demands.19,20,21–23 These abilities are necessary for functional and independent balance17 and locomotion.21–23 Tasks requiring executive function tend to be more difficult for older than for younger adults because the prefrontal cortex is most affected by age-related change in the central nervous system.19,24 Even older adults with no clinical evidence of cognitive dysfunction and normal scores on the Mini Mental State Examination (MMSE)25 may have difficulty with executive function tasks.
Liu-Ambrose et al17 found that individuals with lower scores on executive function tests tend to have higher risk of falling and greater postural sway. Ble et al,21 Hirota et al,22 and van Iersel et al23 found a relationship between executive function, measured by the Trail Making Test (TMT), and gait speed. In these studies, individuals with a poor executive function (detected by a high delta of the TMT, obtained by subtracting part A score from part B score) were more likely to have lower speed on an obstacle course than those with a high performance on the TMT.21,22 Hirota et al22 also showed that poor TMT performance was related to a lower speed on the Timed Up and Go test (TUG). Van Iersel et al23 assessed older adults walking with and without associated cognitive tasks and verified that individuals presenting increased stride length variability and trunk sway during the performance of animal naming tended to have poorer performance on TMT.
The TMT is a well-established measure of efficacy of executive function, with well established normative data stratified by educational status and age.26–31 Although Hanna-Pladdy19 classified the TMT as a response inhibition test, other authors suggest that the TMT can be used to assess other abilities, such as attention,26,29,30 visual scanning,26–31 information processing,27,31,32 sequencing,21,26,27 cognitive flexibility21–23,26–33 and psychomotor speed.23,26–29,32,33
Although the relations between TMT and TUG22 and between TUG and BBS9 have been described in the literature, no study investigating directly the relation between TMT and BBS was found. A study by Di Fabio et al34 that assessed the relationship of visual attention and executive function during obstacle clearance found that older individuals with better performance on the part B of the TMT (TMT-B) had higher scores on the BBS. This information supports the premise that executive function and functional balance might be related.
It is also possible that balance and risk of falling are influenced by the educational status. Individuals with little formal education are less capable of performing tasks involving visual perception, memory, divided attention, coordination, manual dexterity, and motor sequencing.35–37 In addition, they tend to have greater levels of cognitive decline and of functional dependence as they age.36,38–40 Snowdon et al38 studied the ability to perform self-care activities in aging nuns and concluded that those holding bachelor's or graduate degree were more likely to survive to old age while maintaining their functional independence.
Although the BBS is one of the most commonly used protocol to assess functional balance and detect the risk of falling in older adults, no study has investigated the relationship between level of formal education and performance on the BBS.
We hypothesized that (1) a poor performance on measures of executive function, as well as (2) a low number of years of formal education, could be associated with balance difficulties in older adults. We also hypothesized that (3) persons with high levels of executive function (TMT-B) would perform better on motor (BBS, TUG) and cognitive (TMT-A, TMTDELTA, MMSE) tests, and would have more years of education.
The purposes of this study were to evaluate the relationship between postural control (BBS score) and executive function (TMT times), and between postural control (BBS score) and level of education in a sample of older adults and to investigate motor and cognitive differences between high (HXF) and low (LXF) executive function groups using the framework described by Di Fabio et al.34 We expected to find a significant negative correlation between time to complete the TMT and the BBS score and a positive correlation between the number of years of formal education and the BBS score. We also expected to find better scores on motor and cognitive tests in individuals with a good performance on TMT-B than those with a poor performance on this task.
The examiners visited 2 senior centers in the city of São Paulo (SP, Brazil) and invited community-dwelling older adults aged between 60 and 80 to participate in this study. Exclusion criteria included acute or terminal illnesses, myocardial infarction in the last 6 months, moderate or severe chronic obstructive pulmonary disease, uncontrolled hypertension, uncontrolled metabolic disease, acute orthopedic injuries, neurological disease, muscular disease, inability to ambulate independently or need for assistance in daily life activities, inability to read and/or write, less than 3 years of formal education, inability to understand the instructions to perform the tests, inability to say the alphabet sequence, significant cognitive impairments (determined by the cut-points for each educational status, according to the Brazilian version of MMSE: 23 for individuals with 3 to 4 years and 26 for individuals with 5 to 16 years of formal education)25 or significant visual impairment (detected by the Snellen chart).41
A total of 101 older adults (78 women) were eligible to participate. All were living independently and could walk without ambulatory assistive devices. Individuals wearing corrective lenses were accepted. Participants were assessed individually in a quiet room at their senior centers. After receiving detailed explanation about the study individually, they signed a written informed consent approved by the Committee on Research at the University of São Paulo.
Motor and Cognitive Assessment
Balance was assessed with the BBS12–16 and gait speed was assessed with the TUG.13,15 Functional testing (BBS and TUG) was administered by an experienced Physical Therapist. The TMT26–33 was used to assess executive function and the MMSE25 was used to as a screening for cognitive function. Educational status was assessed by asking “How many years of schooling have your completed?” If the participant responded that he/she had completed high school, a follow-up question was asked: “Have you been to college or university?” If yes, participants were asked how many years of college or university had been completed. The total number of years of formal education was recorded. The educational system in Brazil includes 9 years of elementary school and 3 years of high school. Undergraduate studies take place in 4, 5, or 6 years, depending on the area. Cognitive testing (TMT) was administered by an examiner with extensive experience using this test. Half of the participants completed functional tests, followed by cognitive testing. The other half started with the cognitive tests, followed by functional testing. This strategy was used to minimize effects of fatigue and testing order.
Trail Making Test
The reliability and validity of the TMT are well established.26,28,29,33 This paper and pencil test consists of 2 parts. Time to complete each part is measured by stopwatch and recorded in seconds. Part A requires the serial connection of numbers (1 to 25) randomly distributed on a white sheet of paper. Part A (TMT-A) assesses attention,26,29,42,43 visual scanning,28,29,32,42 motor speed and coordination.28,29,32 During part B (TMT-B), participants are asked to connect randomly positioned numbers (1-12) and letters (A-M) in the correct number—letter sequence (example: 1, A, 2, B, 3, C, etc). Before starting the test, participants say the alphabet to ensure that they are familiar with the alphabet sequence. The maximum time allowed to complete each part of the test is 300 seconds. If the allotted time is reached, the test stops and the maximum score of 300 is recorded.32 The TMT-B is more difficult and is used to asses mental flexibility20,26,28–30,32 and working memory42 in addition to the abilities assessed by part A. Both TMT-B33,34 and TMTDELTA21–23 are considered accurate measures of executive function.
Berg Balance Scale
The BBS is an ordinal scale with established reliability and validity12,14 measuring the ability to maintain balance while doing functional tasks. The 14 items of the BBS include common tasks such as sitting, transferring from one chair to another, rising from a chair, standing, reaching an object, and changing direction when standing. Each item is rated from 0 to 4. Item scores are summed for a total BBS score; scores can range from 0 to 56.
The BBS was specifically designed to assess balance ability of older adults, to monitor changes in balance over time, to screen patients in need of rehabilitation and to assess the risk of falls in community-dwelling and institutionalized older adults.8–16 A recent study by Muir et al found that individuals with BBS of 55 have a 35% chance of falling in the next 6 months; the risk of falls increases to 63% for those with BBS scores below 40.16
Descriptive statistics were used to characterize age, gender, level of education, executive function, and balance. As the scores on the tests did not display a normal distribution, a Spearman rho (ρ) nonparametric correlation coefficient was used to determine how each cognitive variable (TMT-A, TMT-B, TMTDELTA, and educational status) was related with the BBS. The coefficient of determination (r2) was also used to determine the shared variance. After that, a cut-point of 160 seconds on TMT-B was used to divide the participants in 2 groups: high (HXF) and low executive function (LXF).34 The Mann-Whitney nonparametric test was used to compare the motor (TUG, BBS) and cognitive (TMT-A, TMTDELTA, MMSE) performance, and the number of years of formal education of the HXF to the LXF. Statistica 8.0 for Windows (StatSoft Inc, Tulsa, OK) was used for all analyses.
The mean score on BBS was 53.4 (3.1) points; scores ranged from 44 to 56. The mean level of education was 7.1 (4.4) years, ranging from 3 to 16 years. Scores on TMT-A ranged from 23 to 127 seconds, with a mean of 63.0 (26.6) seconds. There was greater variability in TMT-B, with scores ranging from 40 to 300, with a mean of 178.4 (96.3) seconds (Figure 1; Table 1).
BBS scores were inversely related with time to complete TMT-A (r = −0.63, r2 = 0.40, P < .001) and TMT-B (r = −0.56, r2 = 0.31, P < .001) (Figure 2, Table 2). There was a similar, but less expressive relationship with TMTDELTA (r = −0.47, r2 = 0.22, P < .001, Table 2).
Twenty-nine individuals scored 300 seconds on TMT-B, the upper limit for the test. This means that these participants did not actually complete TMT-B. The percentage of individuals scoring 300 seconds on TMT-B increased as BBS score decreased: 0% for BBS = 56; 22.2% for BBS = 55; 27.8% for BBS = 54; 40.0% for BBS = 53; 40.0% for BBS = 52; 44.0% for BBS = 51; 50.0% for BBS = 50; 66.7% for BBS = 49; and 100% for scores below 49 (Table 3).
There was a positive correlation between level of education and the BBS score (r = 0.48, r2 = 0.23, P < 0.001) (Table 2). Although the P value was significant, there was a high variability of BBS scores for each number of years of education. For example, for those with a maximum BBS score of 56, the number of years of education ranged from 4 to 16.
When the participants were divided in HXF group and LXF group, the Mann-Whitney tests showed no differences in age and gender. The tests also showed that the HXF group had higher scores on MMSE and BBS, more years of formal education and lower scores on TUG, TMT-A, and TMTDELTA (P < .001 for all comparisons) than the LXF group (Table 4).
This study sought to expand understanding of possible relationships between cognitive function and level of education with balance. As we included only individuals who were living independently, postural control was fairly good among the participants.
Berg Balance Scale and Trail Making Test
The significant correlation between the time to complete the TMT and BBS score suggests that older adults with effective executive function (as indicated by low TMT times) may have better balance (as indicated by high BBS scores).
Visual attention influences visuomotor control, which is assessed by TMT-A and TMT-B.26,29,42 Visual attention also influences balance responses in older individuals.9,10 Older adults can use visual attention to compensate difficulties in maintaining static postures,10 which are tested in some items of the BBS (sitting unsupported, standing unsupported, standing with feet together, tandem standing, and standing on one leg). Thus, older adults with a more efficient visual attention may achieve better scores on BBS than older adults with a poor visual attention.
TMT-A and TMT-B also require the ability to sequence.26,29,32 Several tasks on the BBS may also demand motor sequencing, including transfers, turning 360 degrees or stool stepping. The fact that both BBS and TMT involve tasks that demand sequencing abilities may contribute to their relation. Motor speed is evaluated by both TMT28,29,32,33 and BBS. Ble et al21 and Hirota et al22 found a relation between TMT and gait speed: individuals with better performance on TMT also moved faster through an obstacle course. Our results are consistent with these findings: functional gait and balance are associated with speed as measured by TMT times.
There was a stronger correlation of BBS with TMT-A than with TMT-B. Forty percent of variance in the BBS was explained by TMT-A time (coefficient of determination: r2 = 0.40), while less of the BBS was accounted for by TMT-B times TMTDELTA (coefficients of determination r2 = 0.31 and r2 = 0.22, respectively).
TMT-B, which requires switching between numbers and letters in sequence, is a more complex cognitive task than TMT-A. Persons with fewer years of education tend to take more time to complete TMT-B.26–33,44 In this study, many participants did not complete TMT-B within the allotted 300 second maximum, creating a ceiling effect and a nonnormal distribution. This might explain the lower than expected relationship between TMT-B and BBS. Studies involving older adults with little formal education reported this same difficulty and concluded that TMT-B was less sensitive than TMT-A for this population.26,44 TMT-B requires mental flexibility26,28–31,32 and working memory,42 which may not be fundamental during BBS tasks. The components that TMT-B has in common with the BBS may be the same ones that TMT-A has in common with BBS: visual scanning, sequencing, and motor speed.
Although the percentage of individuals scoring 300 seconds on TMT-B tended to be higher for lower scores of the BBS, there were individuals who had a high score on BBS and a poor performance on the TMT. The relation between TMT and BBS cannot be taken as a general rule; it is possible to have both good functional balance and poor executive function.
We found stronger correlations between parts A and B of the TMT and the BBS than between the TMTDELTA and the BBS. Because many older adults could not complete part B in the maximal time allowed (300 seconds),32 there was a ceiling-effect, possibly underestimating the scores on TMT-B and, consequently, masked the delta, resulting in lower values for individuals who had much difficulty on the test.
Berg Balance Scale and Education
Year of education was correlated with the performance on the BBS 9 (r = .48, P < .05); however, there was great variability in our data. Year of education alone explained only 23% of BBS score (coefficient of determination (r2 = 0.23).
What is more, as we included only independently living older adults, most with little or no balance impairment (35.6% scored 56 and 36.6% scored between 55 and 53 on BBS). This resulted on a nonnormal distribution, which may have minimized the strength of the relationship of BBS and level of education. This fact must be considered because it implies that the relation between BBS and years of education cannot be taken as a general rule without considering that there will be exceptions for research use and clinical practice.
Previous studies reported that individuals with less years of formal education are likely to have greater functional dependency as older adults.38–40 A study by Gitlin et al45 suggested that level of education influenced efficacy of interventions to improve balance. As someone gets older, balance abilities tend to decline, and balance performance may be influenced by availability of additional resources that can be allocated to a functional task. This availability may depend on motor resources acquired and practiced throughout life, as well as cognitive resources.4,17–19,21,34,40 Cognitive resources that help to mitigate risk of falls and compensate for balance impairment in older adults include memory, visuospatial ability, attention, and executive function.17,18 These resources are influenced by an individual's level of education: persons limited education may have less resource available in terms of visual perception, memory, divided attention, coordination, and motor sequencing.35–37 They may, in consequence, have less efficacy in postural control and balance ability.
Differences Between High and Low Executive Function Groups
Di Fabio et al34 considered the raw score of 160 seconds on TMT-B as a cut-point for grouping elderly participants for high (HXF, below 160 seconds) or low executive function (LXF, above 160 seconds). When we divided our data using this criteria, we found a difference between means of the high (90.8 seconds) and low (264.2 seconds) executive function groups on TMT-B performance (P < .001). This difference might be the results of unequal subsample size or of years of education. The mean BBS scores in this study were 54.8 for the HXF group and 52.0 for LXF group, whereas Di Fabio et al34 reported mean BBS scores of 49.3 and 47.6, respectively. Although our sample was younger and had better and less variable functional balance, the variability on TMT-B scores was still striking. The differences found between HXF and LXF in TMT-A and TMTDELTA scores can be attributed to the strong correlation of these scores with TMT-B.33
The groups also differed significantly in MMSE and TUG scores and in educational level. This information reinforces the importance of executive function in the performance of both motor19,21–23,34 and cognitive19,27,34 tasks in older adults. The relations between TMT and TUG22 and between TMT and educational status26–31 have also been previously described. Difference in MMSE may be, to some extent, a reflection of the educational difference, because the cut-point was 23 for individuals with 3 to 4 years of formal education and 26 for individuals with 5 to 16 years of formal education. This is consistent with the findings of Hall et al,46 who suggest that while executive function and other cognitive tests, such as the digit symbol, seem to be related, this association may be predominantly attributable to level of education. Individuals with more years of education tend to have a better performance in most cognitive tests.44,46
As methodological limitations, it is important to mention that the information about health and number of years of formal education was collected by self-report and was dependent on accurate recall and report by the participants. There was also a marked ceiling effect in the scores of TMT-B. Although our results were consistent with findings of Di Fabio et al,34 we may have underestimated the average score of TMT-B, which may also have decreased the correlation between TMT-B and BBS and TMTDELTA and BBS. Given the level of variability in our data, the relationships are likely to have clinically important exceptions.
There is no clear consensus about the set of abilities measured by the trail making test tasks. While Hanna-Pladdy19 classifies the TMT as an inhibition test, others have postulated that TMT also assesses attention,26,29,33,43 visual scanning,26–31 information processing,27,31 sequencing,26,27 cognitive flexibility, 26–29,31,33 motor speed, and coordination.26–29,33 We discussed the similarities between BBS and TMT considering these multiple aspects assessed by TMT.
The present study verified that the performance in TMT, mainly on part A, is correlated to the performance in BBS. In additional, years of education was related to the BBS score. In general, patients with better visuospatial abilities and psychomotor speed, (assessed by TMT-A) and better executive function (assessed by TMT-B), demonstrated better performance on BBS and, therefore, may be less likely to fall. Individuals with a high executive function ability (measured by TMT-B) performed better in other motor and cognitive tests. Because findings presented a large variability, the correlations should not be extrapolated to clinical practice without taking into account that there might be exceptions.
1. Lord SR, Visual risk factors for falls in older people. Age Ageing. 2006;35-S2:ii42–ii45.
2. Jankelowitz SK, McNulty PA, Burke D, Changes in measures of motor axon excitability with age. Clin Neurophysiol. 2007;118:1397–1404.
3. Valerio BC, Nobrega JA, Tilbery CP, Neural conduction in hand nerves and the physiological factor of age. Arq Neuropsiquiatr. 2004;62:114–118.
4. Finkel D, Reynolds CA, McArdle JJ, Pedersen LL, Age chances in processing speed as a leading indicator of cognitive aging. Psychol Aging. 2007;22:558–568.
5. Perry MC, Carville SF, Smith IC, Rutherford OM, Newham DJ, Strength, power output and symmetry of leg muscles: effect of age and history of falling. Eur J Appl Physiol. 2007;100:553–561.
6. DeVita P, Hortobagyi T, Age increases the skeletal versus muscular component of lower extremity stiffness during stepping down. J Gerontol A Biol Sci Med Sci. 2000;55A:593–600.
7. Koepsell TD, Wolf ME, Buchner DM, et al., Footwear style and risk of falls in older adults. J Am Geriatr Soc. 2004;52:1495–1501.
8. Boele van Hensbroek P, van Dijk M, van Breda GF, et al., The CAREFALL triage instrument identifying risk factors for recurrent falls in elderly patients. Am J Emerg Med. 2009;27:23–36.
9. Melzer I, Oddsson LIE, The effect of a cognitive task on voluntary step execution in healthy elderly and young individuals. J Am Geriatr Soc. 2004;52:1255–1262.
10. Weeks DL, Forget R, Mouchnino L, Gravel D, Bourbonnais D, Interaction between attention demanding motor and cognitive tasks and static postural stability. Gerontology. 2003;49:225–232.
11. Scheffer AC, Schuurmans MJ, Dijk N, Hooft T, Rooij SE, Fear of falling: measurement strategy, prevalence, risk factors and consequences among older persons. Age Ageing. 2008;37:19–24.
12. de Figueiredo KM, de*Lima KC, Cavalcanti Maciel AC, Guerra RO, Interobserver reproducibility of the Berg Balance Scale by novice and experienced physiotherapists. Physioter Theor Pract. 2009;25:30–36.
13. Kornetti DL, Fritz SL, Chiu YP, Light KE, Velozo CA, Rating scale analysis of the Berg Balance Scale. Arch Phys Med Rehabil. 2004;85:1128–1135.
14. Berg KO, Wood-Dauphinee SL, Williams JI, Maki B, Measuring balance in the elderly: validation of an instrument. Can J Public Health. 1992;83:S7–11.
15. Steffen TM, Hacker TA, Mollinger L, Age- and gender-related test performance in community-dwelling elderly people: Six-Minute Walk Test, Berg Balance Scale, Timed Up & Go Test, and gait speeds. Phys Ther. 2002;82:128–137.
16. Muir SW, Berg K, Chesworth B, Speechley M, Use of the Berg Balance Scale for predicting multiple falls in community-dwelling elderly people: a prospective study. Phys Ther. 2008;88:449–459.
17. Liu-Ambrose TY, Ashe MC, Graf P, Beattie BL, Khan KM, Increased risk of falling in older community-dwelling women with mild cognitive impairment. Phys Ther. 2008;88:1482–1491.
18. Martin K, Thomson R, Blizzard L, Wood A, Garry M, Srikanth V, Visuospatial ability and memory are associated with falls risk in older people: a population-based study. Dement Geriatr Cogn Disord. 2009;27:451–457.
19. Hanna-Pladdy B, Dysexecutive syndromes in neurologic disease. J Neurol Phys Ther. 2007;31:119–127.
20. Nelson AP, O'Connor MG, Mild cognitive impairment: a neuropsychological perspective. CNS Spectr. 2008;13:56–64.
21. Ble A, Volpato S, Zuliani G, et al., Executive function correlates with walking speed in older persons: the InCHIANTI study. J Am Geriatr Soc. 2005;53:410–415.
22. Hirota C, Watanabe M, Tanimoto Y, Kono R, Higuchi Y, Kono K, A cross-sectional study on the relationship between the Trail Making Test and mobility-related functions in community-dwelling elderly. Nippon Ronen Igakkai Zasshi. 2008;45:647–654.
23. Van*Iersel MB, Kessels RPC, Bloem BR, Verbeek ALM, Olde*Rikkert MGM, Executive functions are associated with gait and balance in community-living elderly people. J Gerontol. 2008;63:1344–1349.
24. Zimmerman ME, Brickman AM, Paul RH, et al., The relationship between frontal gray matter volume and cognition varies across the healthy adult lifespan. Am J Geriatr Psychiatry. 2006;14:823–833.
25. Brucki SMD, Nitrini R, Caramelli P, Bertolucci PHF, Okamoto IH, Sugestões para o uso do mini-exame do estado mental no Brasil. Arq Neuro-Psiquiatr. 2003;61:777–781.
26. Seo EH, Lee DY, Kim KW, et al., A normative study of the Trail Making Test in Korean elders. Int J Geriatr Psychiatry. 2006;21:844–852.
27. Periáñez JA, Rìos-Lago M, Rodrıguez-Sanchez JM, et al., Trail Making Test in traumatic brain injury, schizophrenia, and normal ageing: sample comparisons and normative data. Arch Clin Neuropsychol. 2007;22:433–447.
28. Hashimoto R, Meguro K, Lee E, Kasai M, Ishii H, Yamaguchi S, Effect of age and education on the Trail Making Test and determination of normative data for Japanese elderly people: the Tajiri Project. Psychiatry Clin Neurosci. 2006;60:422–428.
29. Zalonis I, Kararizou E, Triantafyllou NI, et al., A normative study of the trail making test A and B in greek adults. Clin Neuropsychol. 2008;22:842–850.
30. Hester RL, Kinsella GJ, Ong B, McGregor J, Demographic influences on baseline and derived scores from the trail making test in healthy older Australian adults. Clin Neuropsychol. 2005;19:45–54.
31. Tombaugh TN, Trail Making Test A and B: normative data stratified by age and education. Arch Clin Neuropsychol. 2004;19:203–214.
32. Bowie CR, Harvey PD, Administration and interpretation of the Trail Making Test. Nat Protoc. 2006;1:2277–2281.
33. Lezak MD, Orientation and attention. In: Lezak MD. Neuropsychological Assessment. 3rd ed. New York, NY: Oxford University Press; 1995:335–384.
34. Di*Fabio RP, Zampieri C, Henke J, Olson K, Rickheim D, Russell M, Influence of elderly executive cognitive function on attention in the lower visual field during step initiation. Gerontology. 2005;51:94–107.
35. Custodio EB, Malaquias Júnior J, Voos MC, Relação entre cognição (função executiva e percepção espacial) e equilíbrio de idosos de baixa escolaridade. Fisioter Pesq. 2010;17:46–51.
36. Snowdon DA, Ostwald SK, Kane RL, Keenan NL, Years of life with good and poor mental and physical function in the elderly. J Clin Epidemiol. 1989;42:1055–1066.
37. Nitrini R, Caramelli P, Herrera E, Charcat-Fichman H, Porto CS, Performance in Luria's fist-edge-palm test according to educational level. Cog Behav Neurol. 2005;18:211–214.
38. Snowdon DA, Ostwald SK, Kane RL, Education, survival, and independence in elderly Catholic sisters, 1936-1988. Am J Epidemiol. 1989;130:999–1012.
39. Jagger C, Matthews R, Melzer D, Matthews F, Brayne C, Educational differences in the dynamics of disability incidence, recovery and mortality: findings from the MRC Cognitive Function and Ageing Study (MRCCFAS). Int J Epidemiol. 2007;36:358–365.
40. Yao S, Zeng H, Sun S, Investigation on status and influential factors of cognitive function of the community: dwelling elderly in Changsha City. Arch Gerontol Geriatr. 2009;49(3):329–334.
41. Kalinowski MA, “Eye” dentifying vision impairment in the geriatric patient. Geriatr Nurs. 2008;29:125–132.
42. Crowe SF, The differential contribution of mental tracking, cognitive flexibility, visual search, and motor speed to performance on parts A and B of the Trail Making Test. J Clin Psychol. 1998;54:585–591.
43. Gottwald B, Mihajlovic Z, Wilde B, Mehdorn HM, Does the cerebellum contribute to specific aspects of attention? Neuropsychologia. 2003;41:1452–1460.
44. Yassuda MS, Diniz BSO, Flaks MK, et al., Neuropsychological profile of Brazilian older adults with heterogeneous educational backgrounds. Arch Clin Neuropsychol. 2009;24:71–79.
45. Gitlin LN, Winter L, Dennis MP, Hauck WW, Variation in response to a home intervention to support daily function by age, race, sex and education. J Gerontol A Biol Sci Med Sci. 2008;63:745–750.
46. Hall PA, Dubin JA, Crossley M, Holmquist MG, D'Arcy C, Does executive function explain the IQ-mortality association? Evidence from the Canadian Study on Health and Aging. Psychosom Med. 2009:71:196–204.
balance; Berg Balance Scale; cognition; education; older adults
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