This Article Abstract Full Text (PDF) Services Download to citation manager Citing Articles Citing Articles via HighWire PubMed PubMed Citation

The Relationship Between Cognitive and Physical Performance

MacArthur Studies of Successful Aging

^a Department of Health Services, UCLA School of Public Health, Los Angeles, California
^b Andrus Gerontology Center, University of Southern California, Los Angeles
^c Division of Geriatrics, UCLA School of Medicine, Los Angeles, California

Melissa Tabbarah, Department of Health Services, UCLA School of Public Health, Campus Box 951772, Los Angeles, CA 90095-1772 E-mail: tabbarah{at}ucla.edu.

	Abstract

Top Abstract Methods Results Discussion Appendix References

 
Background. The relationship between change in cognitive and physical performance has yet to be fully understood. Because aging decreases the ability to learn new information while preserving more established knowledge, this article examines whether the association between change in cognitive and physical performance depends on the nature of the physical task.

Methods. Data from the MacArthur Research Network on Successful Aging Community Study—a longitudinal three-site, cohort study of high-functioning, disability-free Americans aged 70 to 79 in 1988 (reinterviewed in 1991 and 1995)—are used for this investigation. We examine the association between change in cognitive performance and two categories of physical performance: novel/attentional demanding physical tasks (e.g., standing on a single leg) or routine physical tasks (e.g., walking at a normal pace). Change in physical performance (over 7 years) is regressed on change in cognitive performance (over the same period) controlling for baseline cognitive ability, demographic factors, health status, and behavioral characteristics.

Results. The findings suggest that declines in cognitive performance are associated with declines in both novel/attentional demanding and routine physical tasks. In addition to decline in cognition, gender, prevalent health conditions (e.g., cancer, high blood pressure, and the fracture of a hip), and smoking behavior are associated with decline in performance on some physical tasks.

Conclusions. The findings suggest that the successful execution of physical tasks demands cognitive processes regardless of the nature of the task. Researchers using performance-based measures of physical functioning should pay particular attention to the cognitive capacities of their subjects and how these might influence their assessment.

PHYSICAL and cognitive dysfunction represent two of the most feared states among the elderly because they can lead to physical dependency and social isolation. Although researchers have examined the relationship between various indicators of cognition and self-reported and/or performance-based measures of physical functioning, scholars have yet to fully explore the connection between cognition and specific aspects of physical functioning. Using a longitudinal study of high-functioning Americans aged 70 to 79 at baseline, we examine whether cognitive abilities relate differentially to performance on novel/attentional demanding physical tasks versus more routine physical tasks.

Previous research has shown the interrelated nature of cognitive and physical functioning ^{(1)(2)(3)(4)(5)(6)}. For instance, persons who reported greater disability (modified Activities of Daily Living, ADL) scored lower on tests of cognition (immediate memory, delayed memory, attention, and orientation) ⁽¹⁾. Similarly, studies that have relied on the Mini-Mental State Examination (MMSE) have found that poorer cognitive status was independently associated with greater dependency on reported scales of ADL, Instrumental Activities of Daily Living (IADL), gross functional mobility (the Rosow-Breslau scale), and poorer scores on the summary Physical Performance Test (PPT) ⁽²⁾⁽³⁾. Furthermore, decrement on summary measures of reported ADL parallels decline in cognition (when using the MMSE) ⁽⁴⁾⁽⁵⁾. Recently, in a randomized controlled study of exercise and hormone replacement therapy, an independent, positive association between a series of psychometric tests (Wechsler Associated Learning and 20-minute Delayed Recall, Verbal Fluency test, Trailmaking A and B tests, and the Cancellation Random figures test) and the PPT was reported ⁽⁶⁾. Also, we have previously shown ⁽⁷⁾ that higher baseline cognitive performance is associated with decreased likelihood of decline and increased likelihood of improvement on a summary score of physical performance for a 2.5-year follow-up period.

Although these data show an association between cognitive and general physical performance, it is less clear how cognitive performance might influence different types of physical ability over time. Researchers have suggested that aging decreases fluid intelligence (e.g., tasks requiring sensorimotor coordination, original learning, and swift performance) while preserving crystallized intelligence (e.g., tasks requiring language skills and established habits) ⁽⁸⁾⁽⁹⁾. Based on these findings, Barberger-Gateau and Fabrigoule ⁽¹⁰⁾ suggest

[cognitive] Performances in the elderly may be globally characterized by a loss in efficiency in attentional demanding tasks, or in tasks presenting a great deal of novelty, and by a very good level of [cognitive] performance on more automatic tasks such as over-learned skills. (p. 179)

If Barberger-Gateau and Fabrigoule ⁽¹⁰⁾ are correct, and a positive association exists between cognitive and physical functioning, the association between cognitive and physical performance may depend on the type of physical task. The habitual nature of routine physical tasks may not demand the same level of cognitive functioning that novel/attentional demanding tasks require.

In the following analyses, we test the hypothesis that patterns of change in cognition (specifically declines) will parallel change (i.e., declines) in performance on novel or attentional demanding tasks (e.g., standing on a single leg, standing with tandem foot placement [eyes closed and open], walking with tandem foot placement, tapping one's feet, and walking at a fast pace). By contrast, for routine physical tasks (e.g., completing five repeated chair stands, turning in a circle, signing one's name, walking at a normal pace, and gripping an object with one's hand), we hypothesize an absence of association between change in cognition and change in performance on these tasks.

	Methods

Top Abstract Methods Results Discussion Appendix References

 
Sample
The data used in the present study come from the MacArthur Research Network on Successful Aging Community Study, a longitudinal, three-site cohort study of high-functioning Americans aged 70 to 79 in 1988. Individuals were initially sampled from three community-based studies of individuals aged 65 and older in Durham, NC; East Boston, MA; and New Haven, CT (part of the National Institute on Aging's Established Populations for Epidemiologic Studies of the Elderly—EPESE) on the basis of age (70–79) and six criteria of physical and cognitive functioning (see Afor selection criteria). Age-eligible respondents (i.e., 70–79) were screened to identify a cohort of individuals who function at the top third of their age group in terms of physical and cognitive functioning. Of the 1313 subjects who met the criteria, 1189 individuals (90.6%) completed a 90-minute face-to-face interview between May 1988 and December 1989. Assessments included detailed measurement of physical performance, cognitive performance, health status, and social and psychological characteristics. Outcomes examined here are based on the 1996 follow-up (data collection from October 1995 to March 1997). The mean interval from baseline was 85 months (i.e., 7 years; standard deviation—SD = 7 months).

Data from only two sites (East Boston, MA, and New Haven, CT) are used because physical performance testing was not conducted in Durham, NC, at follow-up in 1995. This reduces the analytic sample to 762. Compared to the full original cohort (n = 1189), this subsample had slightly better average cognitive and physical performance scores at baseline (data available upon request). Of the 762 individuals in the subsample, 178 (23.4%) died before the follow-up interview in 1995, and 96 (12.6%) were lost to follow-up, reducing the sample to 488 individuals. There were no significant demographic (age, gender, education) differences between this sample and the original 1189 participants. Compared to the original sample of participants, however, these 488 individuals had slightly better average cognitive and physical performance scores (data available upon request).

Dependent Variables
The MacArthur Study included 11 performance-based measures of physical functioning. We classified these tasks as either routine physical tasks or novel/attentional demanding physical tasks based on whether we anticipated disability-free individuals would "routinely" perform a given task on a daily basis. For instance, we believed that participants would routinely walk (some distance) at a normal pace, whereas walking at a fast pace was seen as less routine and more demanding. Five tasks were defined as routine (e.g., completing five consecutive chair stands, turning in a circle, signing one's name, walking at a normal pace, and gripping an object with one's dominant hand), and six tasks were classified as novel/attentional demanding (e.g., standing on a single leg, standing with tandem foot placement [eyes closed and open], walking with tandem foot placement, tapping one's feet, and walking at a fast pace).

The ability to perform routine physical tasks was operationalized by recording the number of seconds to (a) complete five repeated chair stands ⁽¹¹⁾; (b) turn in a circle (360°) ⁽¹²⁾; (c) pick up a pencil and sign one's name (up to 30 seconds) ⁽¹³⁾; and (d) walk 10 feet at a normal pace, without the use of any aids (e.g., a cane), but permitted to do so if necessary ⁽¹¹⁾. A dynamometer documented maximum hand grip strength (in kilograms) in the dominant arm, based on the average of the best three measures. Of the six novel/attentional demanding tasks, five were strictly operationalized by the number of seconds required to complete them ⁽¹¹⁾: (a) standing on a single leg (up to 10 seconds); (b) standing with tandem foot placement (toe to heel) with eyes closed (up to 10 seconds); (c) standing with tandem foot placement with eyes open (up to 10 seconds); (d) tapping a foot (as fast as possible, up to 30 seconds) between a pair of two-inch circles placed one foot apart; and (c) walking a distance of 10 feet as fast as possible (without the use of any aids, but permitted to do so if necessary). In addition, participants were asked to walk with tandem foot placement, and the number of steps taken (up to 10) and the time to complete those steps were recorded. Change on each of these measures was defined as the difference between the 1995 and 1988 continuous scores. In order to make the interpretation of change scores consistent, the change scores for six physical tasks (completing five repeated chair stands, turning in a circle, signing one's name, walking at a normal pace, walking at a fast pace, and tapping one's feet) are multiplied by -1 so that all positive change scores mean people did better in 1995 and more negative change scores imply that individuals scored more poorly at follow-up.

Independent Variables
Cognitive performance.-- In the MacArthur Study, the total cognitive score represented the sum of the performances on five subscales: (a) spatial memory, (b) similarity of abstract concepts, (c) language, (d) delayed verbal memory, and (e) spatial orientation. The delayed Span Test measures spatial memory by placing circular disks on a board in a specific order and then asking individuals to identify the new disk ⁽¹⁴⁾. By scoring individuals from 0 to17, this easily administered test measures spatial memory separate from verbal ability. The Boston Naming Test ⁽¹⁵⁾ measures language retention by showing individuals 18 drawings (e.g., broom, bench, tree, harp, etc.) and asking them to name each object. Only items correctly named within 10 seconds per picture were counted. Incidental recall was assessed by asking individuals to recall the names of objects shown during the Boston Naming Test ⁽¹⁵⁾. Four items from the Wechsler Adult Intelligence Scale–Revised (WAIS-R) measure grasp of abstract concepts ⁽¹⁶⁾. Participants are asked to explain how four different pairs of objects or concepts (e.g., work and play) are similar, scoring from 0 to 16 on this task. Finally, a drawing test measures spatial orientation by asking subjects to copy geometric figures including a diamond, a diamond in a square, and a three-dimensional cube ⁽¹⁷⁾. The drawings are then scored by a single rater using a standardized system. A total cognitive score, representing the sum of these five tests, was developed by Inouye and colleagues ⁽¹⁸⁾. Scores range from 0 to 89, with higher scores indicative of better functioning ⁽¹⁸⁾. At baseline, the total cognitive score was normally distributed with a mean score of 54.56 (SD = 9.11). Change in cognitive performance was defined as the difference between the 1995 and 1988 continuous scores. Normally distributed, the change score ranges from -49 to 21 with a mean of -4.78 (SD = 9.80).

In assessing any association between cognitive and physical functioning, one must also consider potential confounders (i.e., other factors associated with each of these domains that may account for the observed association between cognitive and physical functioning). Studies have shown that age, gender, and economic status influence physical functioning among older persons ⁽¹⁹⁾. As both physical and cognitive dysfunction occur more frequently with age, it is obviously important to control for age. Specific health conditions (e.g., hypertension, diabetes mellitus, injurious falls) may also confound the relationship between cognitive and physical dysfunction ^{(1)(20)(21)(22)}. Furthermore, depression is frequently encountered among the elderly ⁽²³⁾, and research studies reveal a significant correlation between depressive symptomatology and cognition ⁽²⁴⁾. Finally, although it is unclear whether some health behaviors (i.e., body mass index [BMI], smoking cigarettes) influence the relationship between cognitive and physical functioning, a positive correlation has been found with alcohol consumption and the MMSE ⁽²⁵⁾.

Demographic characteristics.-- Age is coded in years. Dichotomous variables are used to indicate gender (female/male) and level of education (< 12 years/12 or more years).

Health status.-- Baseline prevalence of eight health conditions (cancer, myocardial infarction, stroke, angina pectoris, diabetes, high blood pressure, broken hips, or other broken bones) was assessed by self-reports of physician-diagnosed conditions. Baseline angina pectoris was assessed by the Rose Angina scale ⁽²⁶⁾. Average systolic and diastolic blood pressures were calculated based on the second and third of three seated readings ⁽²⁷⁾. Individuals were classified as having high blood pressure if the average reading was greater than 140/90 mm Hg or if they were taking blood pressure medication. BMI (kg/m²) was examined based on sample tertiles. A categorical variable was developed to describe individuals with low ( 24.44 kg/m²), medium (24.45 kg/m² to 27.96 kg/m²), and high ( 27.97 kg/m²) BMI levels. Two dummy variables were used to indicate categories low BMI and high BMI with category medium BMI serving as the referent group. In order to evaluate pulmonary function, peak expiratory flow rate (liters/minute) was assessed by a mini-Wright meter ⁽²⁸⁾. The best of three readings was used. Depression was measured by an 11-item subscale of the 50-item version of the Hopkins Symptom Check List ⁽²⁹⁾. Participants were assigned a score ranging from 11 to 44. A dichotomous variable was created based on the highest tertile ( 15) to indicate higher levels of depression ("1" = high levels of depression vs "0" = moderate/low levels).

Health behaviors.-- The two health behaviors considered here are smoking behavior and alcohol consumption. Smoking history was measured by self-reports, and subjects were classified as current, past, or never smokers. Two dummy variables were used to indicate categories current smoker and past smoker with category never smoked serving as the referent. Alcohol consumption was measured by two dummy variables indicating: < 1 g ethyl alcohol per month and 1 g ethyl alcohol per month with category "none in the past year" serving as the reference group ⁽³⁰⁾.

Analysis
Multivariate linear regression analyses are used to predict the change in the continuous measures of the physical performance tasks. Analyses assess the association between change in cognitive and physical performance, after controlling for baseline cognitive, demographic, health, and behavioral characteristics. Multivariate linear regression is used rather than survival analysis because the data reflected continuous change scores from two specific time points (i.e., baseline vs 1995 follow-up interview). These data do not provide specific information on the time when physical performance scores may actually have changed—only that they have or have not changed as of 1995 interview date.

A special issue for these analyses resulted from the lack of information for participants who tried but were unable to perform the physical task. These participants have unknown values for their change in physical performance. Ignoring these cases and restricting the sample (for each physical task) to able participants is problematic because the estimates would be based on a nonrandomly selected subset. As a result, we would ignore the cases of greatest interest, namely those who tried but were unable to perform a physical task at follow-up.

In the statistical literature, data that include information on observations where the dependent variable is unknown is referred to as right or left censored data. Data are right censored when all you know about a variable is that it is greater than some value ⁽³¹⁾. For instance, data on six of our physical tasks are right censored because we expect individuals unable to perform them to take more time (if they could) than the worst observed score (e.g., completing five repeated chair stands, signing one's name, turning in a circle, walking at a normal and fast pace, and tapping one's feet). Similarly, data are described as left censored when all we know about a variable is that it is less than some value ⁽³²⁾. Thus, data on the remaining tasks (e.g., standing on a single leg, standing with tandem foot placement—eyes open and closed, walking with tandem foot placement, and gripping an object) are left censored because we expect individuals unable to perform these tasks to score lower (if they could) than the poorest observed score.

In order to predict change in performing these physical tasks, we use a Tobit ⁽³²⁾ statistical technique to include the censored cases. By using the SAS statistical package, a Tobit regression is accomplished by specifying a "lifereg" procedure that allows for several varieties of censoring ⁽³¹⁾. Because this procedure does not permit censored data at two time points, we restrict the sample (for each physical task) to able persons at baseline. At baseline, the maximum number of censored cases was 2.9% (n = 14) for standing with tandem foot placement with eyes closed. The sample size for predicting change in performance for each physical task ranges from 281 (tandem stand, eyes closed) to 488 (repeated chair stands). The observed difference in sample size among these physical tasks is due to the omission of censored cases at baseline and missing data (i.e., refusal to perform the task) at baseline and follow-up. For censored observations at follow-up, this technique simultaneously estimates the probability of remaining "able" to complete the task and the expected change score.

	Results

Top Abstract Methods Results Discussion Appendix References

 
Descriptive Statistics
The average scores for the various physical and cognitive performance tasks are presented in Table 1 . On average, except for the task of repeated chair stands, individuals significantly declined on their performance of these tasks from 1988 to 1995. Among those with cognitive scores at both time periods, baseline cognitive performance significantly declined (mean -4.78, SD = 9.80, range -49 to 21).

Cognition and Routine Physical Tasks
The five regression models predicting change on the routine physical tasks (i.e., completing five repeated chair stands, signing one's name, turning in a circle, walking at a normal pace, and gripping objects with one's hand) are presented in Table 4 . After controlling for baseline levels of cognition and other covariates, change in cognition is associated with change in performance on all five of these routine physical tasks. As cognition changes in the direction of poorer performance, so too does change in physical performance. Per unit change in cognition, change in performance ranges from 0.04 units for turning in a circle to 0.17 units for signing one's name.

Demographic, Health, and Behavioral Characteristics
The 11 models also show that demographic, health, and behavioral characteristics are associated with change in performance on these physical tasks (Table 3 and Table 4 ). Older participants are more likely to experience a decline in ability to turn in a circle and walk at a fast pace. Prevalent health conditions such as stroke, diabetes, high blood pressure, and the fracture of a hip are also associated with a decline in the change scores for the respective tasks of walking at a fast pace, completing five repeated chair stands, and standing on a single leg. Participants who were depressed at baseline are also more likely to show a decline in ability to turn in a circle and walk at a fast pace. For every unit of lower (i.e., poorer) baseline rate of peak expiratory flow, there was a decline in the ability to stand with tandem foot placement (eyes open and closed) and to walk with tandem foot placement. Furthermore, compared to those who have never smoked, current smokers are more likely to exhibit a decline in grip strength.

Although the majority of the characteristics examined are associated with decline in change scores for some of the physical tasks, some characteristics are associated with an increase (i.e., improvement) in the change score. For instance, compared to men, women show an increase in the change score (i.e., decline less) on the tasks of standing on a single leg, standing with tandem foot placement—eyes open, and gripping objects. In addition, compared to persons with at least 12 years of education, those with fewer years of education complete the foot tapping exercise more efficiently at follow-up. Individuals who have a history of stroke also show an increase in the change score for grip strength. The prevalence of cancer, myocardial infarction, angina, and nonhip fractures is not significantly associated with change in performing any of these physical tasks.

	Discussion

Top Abstract Methods Results Discussion Appendix References

 
Contrary to the idea proposed by Barberger-Gateau and Fabrigoule ⁽¹⁰⁾, analyses presented here suggest that declines in cognitive performance are associated with decrement on both novel/attentional demanding physical tasks (e.g., balancing, standing on a single leg, standing with tandem foot placement—eyes open and closed, walking with tandem foot placement, tapping one's feet, and walking at a fast pace) and routine physical tasks (e.g., completing five repeated chair stands, turning in a circle, signing one's name, walking at a normal pace, and gripping an object with one's hand). These findings suggest that the successful execution of both novel/attentional demanding and routine physical tasks is affected by basic cognitive processes.

Our finding that patterns of change in cognitive and physical performance are interrelated suggests that cognition plays an integral role in the execution of most physical tasks. The performance of a physical task most likely requires the coordination of multiple biological and nonbiological (i.e., social, behavioral, etc.) systems. Indeed, the observed concomitant change between cognitive and physical performance illustrates the role cognition plays in organizing the communication between such systems. Though cognitively dysfunctional individuals may remain able to accomplish a given physical task, their efficiency in performing the task appears to be diminished.

The multidimensional nature of physical performance emphasizes the complexity of assessing physical functioning. The interrelated nature of cognitive and physical performance highlights the importance of cognition when assessing the physical functioning of older persons. Performance-based measures of physical functioning are not "gold-standard" measures of physical assessment. As such, researchers assessing the physical functioning of older persons, through the implementation of performance-based measures, should pay particular attention to the cognitive capacities of their subjects and how they might influence their measurement.

In regards to our findings specific to the demographic, health, and behavioral characteristics that influence change in physical performance, caution should be taken when interpreting some of our results. Our finding that individuals with a history of stroke show improvement in grip strength seems counterintuitive. Given the large number of covariates in our models, it is possible that this reflects only a chance finding. Also, given the high-functioning nature of our participants at baseline, it is likely that any strokes reported by participants at baseline were quite mild in nature and thus would be less likely to adversely influence physical performance. More generally, it was interesting to note that health behaviors were seen to influence change on only a few physical tasks (i.e., standing with tandem foot placement—eyes open, walking at a normal pace, and gripping objects). Although these findings stand in contrast to those of others ⁽³³⁾, it may be that this discrepancy results from the relatively high-functioning nature of the participants in the MacArthur Study.

Indeed, one limitation of this study that should be noted is that the cohort was originally selected for the individuals' high cognitive and physical functioning, and thus it is not comparable to the general population of elderly. This study, however, granted the opportunity to explore (in parallel) change in both physical and cognitive performance among a cohort without significant impairment in either domain at baseline. In so doing, this study showed that change in physical functioning is associated with concomitant change in cognition.

A second possible limitation of our study relates to the causal links between these two domains. Our data prohibited us from examining the causal relationships between cognitive and physical performance because they reflected change scores from two specific time points (i.e., baseline and 1995 follow-up interview). Consequently, we examined the concomitant change between cognitive and physical performance. The widely accepted conceptual models of functioning describe individuals moving through a single linear path from cellular pathology or disease to a state of physical disability or handicap ^(34)(35). Between these two extreme states, an anatomical or structural abnormality in psychological or anatomical structures follows the initial identification of pathology. From this stage of impairment, persons would progress along the continuum to a stage of inefficiency in performing physical activities. This third stage is referred to as either functional limitation ⁽³⁴⁾ or disability ⁽³⁵⁾. Eventually, individuals reach a state of physical disability ⁽³⁴⁾ or handicap ⁽³⁵⁾ where they are at a disadvantage in executing their socially defined roles. These models suggest that physical dysfunction is affected by prior stages of cognitive dysfunction. These models, however, propose a single causal pathway, and researchers have begun to ask whether physical dysfunction might also cause cognitive dysfunction ⁽³⁶⁾. Our own data provide clear evidence linking changes in cognition to concomitant changes in an array of domains of physical functioning but do not allow us to address the causal links between these patterns of changes. In light of the salience of two domains of functioning to individuals' ability to live independently and to maintain high quality of life, more research is clearly needed to elucidate the causal relationship between cognitive and physical dysfunction.

	Acknowledgments

 
This work was supported in part by Grant T32 AG00037 from the National Institute on Aging, the National Research Services Award T32 HS00046 from the Agency for Healthcare Research Quality, grants from the National Institutes of Health (AG-17056, AG-11235, AG-17265), and by the MacArthur Research Networks on Successful Aging and on Socio-Economic Status and Health through grants from the John D. and Catherine T. MacArthur Foundation. We thank C. Edward Paul, PhD, for his thoughtful comments on an earlier draft of this manuscript.

Received June 29, 2001

Accepted October 2, 2001

	Appendix

Top Abstract Methods Results Discussion Appendix References

 
The six selection criteria were (i) answering 6 or more correct on the 9-item Short Portable Mental Status Questionnaire ⁽³⁷⁾; (ii) remembering 3 or more of 6 elements on a delayed recall of a short story; (iii) reporting no dysfunction on a 7-item scale of activities of daily living (ADLs) ⁽³⁸⁾ (e.g., inability in bathing, grooming, walking, transferring, eating, toileting, dressing); (iv) reporting no more than one dysfunction on 8 items measuring gross mobility and range of motion developed by Rosow and Breslau ⁽³⁹⁾ (e.g., walking half a mile, climbing stairs, doing heavy housework) and Nagi ⁽⁴⁰⁾ (e.g., pushing/pulling heavy objects, lifting 10 lb, raising arms above shoulder, stooping/crouching/kneeling, picking up small objects); (v) holding a semitandem balance for at least 10 seconds; and (vi) standing from a seated position five times within 20 seconds.

	References

Top Abstract Methods Results Discussion Appendix References

 

1. Scherr PA, Albert MS, Fukenstein HH, et al. 1988. Correlates of cognitive function in an elderly community population. Am J Epidemiol. 128:1084-1101. [Abstract/Free Full Text]
2. Barberger-Gateau P, Chaslerie A, Dartigues JF, Commenges D, Gagnon M, Salamon R, 1992. Health measures correlates in a French elderly community population: the PAQUID study. J Gerontol Soc Sci. 47:S88-S95.
3. Rozzini R, Frisoni GB, Bianchetti A, Zanetti O, Trabucchi M, 1993. Physical performance test and activities of daily living scales in the assessment of health status in elderly people. J Am Geriatr Soc. 41:1109-1113. [Medline]
4. Cress ME, Schechtman KB, Mulrow CD, Fiatarone MA, Gerety MB, Buchner DM, 1995. Relationship between physical performance and self-perceived physical function. J Am Geriatr Soc. 43:93-101. [Medline]
5. Jagger C, Clarke M, Cook AJ, 1989. Mental and physical health of elderly people: five-year follow-up of a total population. Age Ageing. 18:77-82. [Abstract/Free Full Text]
6. Binder EF, Storandt M, Birge S, 1999. The relationship between psychometric test performance and physical performance in older adults. J Gerontol Med Sci 54A:M428-M432. [Abstract]
7. Seeman TE, Charpentier PA, Berkman LF, et al. 1994. Predicting changes in physical performance in a high-functioning elderly cohort: MacArthur Studies of Successful Aging. J Gerontol Med Sci. 49:M97-M108.
8. Albert MS, Kaplan EF. Organic implications of neuropsychological deficits in the elderly. In: Poon LW, Fozard J, Cermak L, Arenberg D, Thompson LW, eds. New Directions in Memory and Aging: Proceedings of the George A. Talland Memorial Conference. Hillsdale, NJ: Lawrence Erlbaum; 1980:403–432.
9. Kaufmann PG, McMahon RP, Becker LC, et al. 1989. The psychophysiological investigations of myocardial-ischemia (PIMI) study—objective, methods, and variability of measures. Psychosom Med. 60: (1) 56-63. [Abstract/Free Full Text]
10. Barberger-Gateau P, Fabrigoule C, 1997. Disability and cognitive impairment in the elderly. Disabil Rehabil. 19: (5) 175-193. [Medline]
11. Nevitt MC, Cummings SR, Kidd S, Black D, 1989. Risk factors for recurrent nonsyncopal falls. JAMA. 261:2663-2668. [Abstract/Free Full Text]
12. Tinetti ME, 1986. Performance-oriented assessment of mobility problems in elderly patients. J Am Geriatr Soc. 34:119-126. [Medline]
13. Jebsen RH, Taylor N, Trieschmann RB, Trotter MJ, Howard LA, 1969. An objective and standardized test of hand function. Arch Phys Med Rehab. 50:311-319. [Medline]
14. Moss M, Albert M, Butters N, Payne M, 1986. Differential patterns of memory loss among patients with Alzheimer's disease, Huntington's disease, alcoholic Korsakoff's syndrome. Arch Neurol. 43:239-246. [Abstract/Free Full Text]
15. Kaplan E, Goodglass H, Weintraub S. Boston Naming Test. Philadelphia, PA: Lea & Fabiger; 1983.
16. Wechsler D. Adult Intelligence Scale–Revised. New York: Psychological Corporation; 1981.
17. Rosen W, Mohs R, Davis R, 1984. A new rating scale for Alzheimer's disease. Am J Psychiatry. 141:1356-1364. [Abstract/Free Full Text]
18. Inouye SK, Albert MS, Mohs R, Sun K, Berkman LF, 1993. Cognitive performance in a high functioning community-dwelling elderly population. J Gerontol Med Sci. 48:M146-M151.
19. Crimmins EM, Saito Y, 1993. Getting better and getting worse: transitions in functional status among older Americans. Journal of Aging Health. 5:3-36. [Abstract/Free Full Text]
20. Dey J, Misra A, Desai NG, Mahapatra AK, Padma MV, 1997. Cognitive function in younger type II diabetes. Diabetes Care. 20:32-35. [Abstract]
21. Guo Z, Fratiglioni L, Winblad B, Vinanen M, 1997. Blood pressure and performance in the Mini-Mental State Examination in the very old. Cross-sectional and longitudinal data from the Kungsholment Project. Am J Epidemiol. 145: (12) 1106-1113. [Abstract/Free Full Text]
22. Tinetti ME, Doucette J, Claus E, Marottoli R, 1995. Risk factors for serious injury during falls by community elderly persons. J Am Geriatr Soc. 43: (11) 214-221.
23. Livingston G, Hawkins A, Graham N, Blizard B, Mann A, 1990. The Gospel Oak Study: prevalence rates of dementia, depression and activity limitation among elderly residents in inner London. Psychol Med. 20:137-146. [Medline]
24. Lichtenberg PA, Ross T, Millis SR, Manning CA, 1995. The relationship between depression and cognition in older adults: a cross-validation study. J Gerontol Psychol Sci. 50B:P25-P32.
25. Pradignac A, Schlienger JL, Velten M, Mejean L, 1995. Relationships between macronutrient intake, handicaps, and cognitive impairments in free living elderly people. Aging Clin Exp Res. 7:67-74.
26. Rose GA, Blackburn H, Gillium RF, Prineas RJ, 1982162–165. Cardiovascular Survey Methods World Health Organization;, Geneva. 162–165.
27. HDFP–Hypertension detection and follow-up program cooperative group 1978. Variability of blood pressure and results of screening in HDFP program. J Chronic Dis. 31:651-667. [Medline]
28. Cook NR, Evans DA, Scherr PA, Speizer FE, Taylor JO, Hennekens CH, 1991. Peak expiratory flow rate and 5-year mortality in an elderly population. Am J Epidemiol. 133:784-794. [Abstract/Free Full Text]
29. Derogatis LR, Lipman RS, Rickels K, Uhlenhuth EH, Covi L, 1974. The Hopkins Symptom Checklist (HSCL): a self-report symptom inventory. Behav Sci. 19:1-15. [Medline]
30. Armor DJ, Polich M, Stambul HB. Alcoholism and Treatment. New York: John Wiley & Sons; 1975:Appendix A.
31. Allison PD, 1995. Survival Analysis Using the SAS System SAS Institute Inc.;, Cary, NC.
32. Breen R. Regression Models: Censored, Sample Selected, or Truncated Data. Thousand Oaks, CA: Sage; 1996.
33. Nelson HD, Nevitt MC, Scott JC, Stone KL, Cummings SR, 1994. Smoking, alcohol and neuromuscular and physical function of older women. JAMA. 272:1825-1831. [Abstract/Free Full Text]
34. Nagi SZ, 1976. An epidemiology of disability among adults in the United States. Milbank Q. 54:439-468.
35. World Health Organization. International Classification of Impairments, Disabilities and Handicaps: A Manual of Classification Relating to the Consequences of Disease. Geneva: World Health Organization; 1980.
36. Bickenback JE, Chatterji S, Badley EM, Ustun TB, 1999. Models of disablement, universalism and the international classification of impairments, disabilities and handicaps. Soc Sci Med. 48:1173-1187.
37. Pfeiffer EA, 1975. A short portable mental status questionnaire for the assessment of organic brain deficit in elderly patients. J Am Geriatr Soc. 23:433-441. [Medline]
38. Katz S, Ford AB, Moskowitz RW, Jackson BA, Jaffe MW, 1963. Studies of illness in the aged. JAMA. 185:914-919.
39. Rosow I, Breslau N, 1966. A Guttman health scale for the aged. J Gerontol. 21:556-559. [Free Full Text]
40. Nagi SZ, 1976. An epidemiology of disability among adults in the United States. Milbank Q. 54:439-468.

This article has been cited by other articles:

				A. L. Fitzpatrick, C. K. Buchanan, R. L. Nahin, S. T. DeKosky, H. H. Atkinson, M. C. Carlson, J. D. Williamson, and for the Ginkgo Evaluation of Memory (GEM) Study In Associations of Gait Speed and Other Measures of Physical Function With Cognition in a Healthy Cohort of Elderly Persons J. Gerontol. A Biol. Sci. Med. Sci., November 1, 2007; 62(11): 1244 - 1251. [Abstract] [Full Text] [PDF]

				M. Inzitari, M. Baldereschi, A. D. Carlo, M. D. Bari, N. Marchionni, E. Scafato, G. Farchi, D. Inzitari, and for the ILSA Working Group Impaired Attention Predicts Motor Performance Decline in Older Community-Dwellers With Normal Baseline Mobility: Results From the Italian Longitudinal Study on Aging (ILSA) J. Gerontol. A Biol. Sci. Med. Sci., August 1, 2007; 62(8): 837 - 843. [Abstract] [Full Text] [PDF]

				H. H. Atkinson, C. Rosano, E. M. Simonsick, J. D. Williamson, C. Davis, W. T. Ambrosius, S. R. Rapp, M. Cesari, A. B. Newman, T. B. Harris, et al. Cognitive Function, Gait Speed Decline, and Comorbidities: The Health, Aging and Body Composition Study J. Gerontol. A Biol. Sci. Med. Sci., August 1, 2007; 62(8): 844 - 850. [Abstract] [Full Text] [PDF]

				A. K. Coppin, A. Shumway-Cook, J. S. Saczynski, K. V. Patel, A. Ble, L. Ferrucci, and J. M. Guralnik Association of executive function and performance of dual-task physical tests among older adults: analyses from the InChianti study. Age Ageing, November 1, 2006; 35(6): 619 - 624. [Abstract] [Full Text] [PDF]

				P. A. Tun and M. E. Lachman Telephone assessment of cognitive function in adulthood: the Brief Test of Adult Cognition by Telephone Age Ageing, November 1, 2006; 35(6): 629 - 632. [Full Text] [PDF]

				A. Bowling and S. Iliffe Which model of successful ageing should be used? Baseline findings from a British longitudinal survey of ageing Age Ageing, November 1, 2006; 35(6): 607 - 614. [Abstract] [Full Text] [PDF]

				I. J. Deary, L. J. Whalley, G. D. Batty, and J. M. Starr Physical fitness and lifetime cognitive change. Neurology, October 10, 2006; 67(7): 1195 - 1200. [Abstract] [Full Text] [PDF]

				A. Soumare, A. Elbaz, V. Ducros, B. Tavernier, A. Alperovitch, and C. Tzourio Cross-sectional association between homocysteine and motor function in the elderly. Neurology, September 26, 2006; 67(6): 985 - 990. [Abstract] [Full Text] [PDF]

				H. Littbrand, E. Rosendahl, N. Lindelof, L. Lundin-Olsson, Y. Gustafson, and L. Nyberg A High-Intensity Functional Weight-Bearing Exercise Program for Older People Dependent in Activities of Daily Living and Living in Residential Care Facilities: Evaluation of the Applicability With Focus on Cognitive Function Physical Therapy, April 1, 2006; 86(4): 489 - 498. [Abstract] [Full Text] [PDF]

				A. K. Coppin, L. Ferrucci, F. Lauretani, C. Phillips, M. Chang, S. Bandinelli, and J. M. Guralnik Low Socioeconomic Status and Disability in Old Age: Evidence From the InChianti Study for the Mediating Role of Physiological Impairments J. Gerontol. A Biol. Sci. Med. Sci., January 1, 2006; 61(1): 86 - 91. [Abstract] [Full Text] [PDF]

				J. E. Morley Editorial. Mobility Performance: A High-Tech Test for Geriatricians J. Gerontol. A Biol. Sci. Med. Sci., August 1, 2003; 58(8): M712 - 714. [Full Text] [PDF]

				J. E. Morley Editorial: Hot Topics in Geriatrics J. Gerontol. A Biol. Sci. Med. Sci., January 1, 2003; 58(1): M30 - 36. [Full Text] [PDF]

This Article Abstract Full Text (PDF) Services Download to citation manager Citing Articles Citing Articles via HighWire PubMed PubMed Citation