Physical performance

Physical performance

LASA filenames:
LASA034

Contact: Laura Schaap

Background
Older persons’ physical functioning in the LASA study has been measured by an observation of performance on a short battery of tests. These physical performance measures are complementary to self-reported measures of physical (dis)ability as they assess different dimensions of physical function (Glass 1998). Self-reported physical (dis)ability measures assess subjects’ functional capacity in their own social and physical context in which functioning actually takes place. A performance measure tests subjects’ functional capability in an ‘experimental’ setting and, therefore, is less influenced by personality, cognition and mood than self-reports of ability (Guralnik et al. 1989; Cress et al. 1995; Kempen et al. 1996). Both physical performance and ability measures were shown to be highly predictive of subsequent morbidity, hospitalization, institutionalization and death (Guralnik et al. 1994, 1995; Ferrucci et al. 1997; Reuben et al. 1992).

Measurement instruments in LASA

Individual tests

1. For testing walking speed, subjects were ask to walk 3 meters, to turn around and walk back 3 meters as quickly as possible. The total time needed to do the test was recorded. As done by several researchers, this measure of walking speed can be used as a continuous variable and should be considered as an indicator of the functioning of the lower extremities (mobility). However, as other researchers prefer, walking speed can also be categorized according to quartiles of the time required in the total population. Based on the total LASA cohort at baseline (LASA-B), the following categories have been developed: unable (when respondent is in a wheelchair or physically unable, score 0); ≥10 seconds (score 1); 8-9 seconds (score 2); 6-7 seconds (score 3); and <6 seconds (score 4) (See syntax*).At waves H and 3B the time to walk 3 meters as quickly as possible was added to the measurements (without the turn and walk back). Due to technical difficulties, interviewers sometimes were unable to score the time to walk 3 meters and the time to walk 3 meters, turn and walk back in one test. As a consequence, the respondent was sometimes asked to perform the test twice; one time to score the 3 meter walk, and one time to score the total 6 meter walk including the turn. This might have influenced the scores on the test, for example due to fatigue (resulting in worse scores during the second test) or due to more practice or increased confidence (resulting in better scores during the second test). Whether respondents had performed the test once or twice has not been recorded. Researchers are advised to take this limitation into account when using these data.At the I wave, it was decided to always perform the test twice: the respondent first walked 3 meters, followed by 6 meters. The data from these tests were used to create an algorithm to recode the 6 meter walk test into a 3 meter walk test. The formula is as follows:Time to walk 3 meters = 0.573 + 0.35 * time to walk 6 meters.Preliminary analyses have been performed to investigate whether sex should be included in the formula to increase the explained variance. This was not the case, the explained variance remained the same (0.76). The formula has been used in a paper of Schaap et al. (2018). Other possible variables to be included in the formula have not been investigated yet.
2. For testing the ability to rise from a chair, subjects were asked to fold their arms across their chest and to stand up from a sitting position and sit down five times at usual pace. The time to perform these five repetitions can be used as a continuous variable and should be considered as an indicator of the functioning of (mainly) the lower extremities. The time can also be categorized, based on quartiles of the time required in the total population. Based on LASA-B, the categories are: unable (when respondent cannot stand up without using the hands or when respondent fails to complete five rises, score 0); ≥15 seconds (score 1); 12-14 seconds (score 2) 10-11 seconds (score 3); and ≤9 seconds (score 4) (See syntax*).
3. For testing the ability to put on and take off a cardigan, the time required to put on and take off a cardigan, which was brought in by the interviewer, was scored. This measure can be used as a continuous variable and should be considered as an indicator of the functioning of the upper extremities. At LASA-B the time needed to close the buttons of the cardigan was scored. At all subsequent waves this was no longer recorded. When the time is categorized according to quartiles of the time required in the total population (LASA-B), categories are: unable (unable to compete the test without help of the interviewer, score 0); ≥16 seconds (score 1); 12-15 seconds (score 2); 9-11 seconds (score 3); and ≤8 seconds (score 4). The cardigan test is the only performance test included in the short version of the main interview. Therefore, this test has the least amount of missing values (See syntax*).
4. For testing standing balance, subjects attempted to maintain their feet in the tandem position (heel of one foot directly in front of and touching the toes of the other foot) for 10 seconds. The standing balance test was not conducted at LASA-B. Based on the results of the LASA-C examination, three categories can be identified: unable, able to hold position for 3-9 seconds, and able to hold position for 10 seconds. Thus, in contrast to the other performance tests that are categorized into 5 groups (score 0-4), the balance test is categorized into three groups. For comparability, these three groups will receive the following scores: unable (0), able to hold position for 3-9 seconds (2), and able to hold position for 10 seconds (4) (See syntax*).Most respondents are able to hold their feet in the tandem position for 10 seconds. Therefore, from the H wave onwards, respondents were asked to maintain their feet in the tandem position for 30 seconds to better discriminate between poor and good performance on the test. However, many respondents could maintain the tandem position in 30 seconds as well. Therefore, the following categories were made: unable (0), able to hold position for 3-9 seconds (2), and able to hold position for 10 seconds or longer (4). Researchers who use these data should consider whether the use of these categories is appropriate or should be adapted, based on the research question.NOTE: if a researcher wishes to perform cross-sectional analyses with single performance tests, for example with data from the G wave, he/she needs to recalculate cut-offs based on the G wave and create new categories accordingly.  Also, if a researcher wants to perform longitudinal analyses from a certain wave other than the B wave, for example to investigate change in performance from wave G to H, again it is recommended that new categories are made based on data from the G wave.

Physical performance summary score
Based on the categories of the individual tests summary scores can be created*. Overall performance score: walking + chair stands + cardigan (+ balance). Lower-extremity performance score: walking + chair stands (+ balance). The score ranges from 0-12 or 0-16, depending on the use of 3 or 4 tests, with higher scores indicating better performance. Summary scores are not calculated when respondents have missing data on one or more individual tests.

NOTE: categories of the individual tests are based on quartiles of the time needed to complete the test at the B wave. If a researcher wishes to use quartiles of the time needed to complete the performance tests of other waves, for example when performing cross-sectional analyses at the G wave, he/she needs to recalculate cut-offs based on the G wave and create new categories accordingly. Please check the document “How to obtain cut-of values”**. Next, a new summary score can be calculated. Also, if a researcher wants to perform longitudinal analyses from a certain wave other than the B wave, for example to investigate change in performance scores from wave G to H, again it is recommended that new categories are made based on data from the G wave.

* SPSS syntax to create categories and summary score can be found here.

** The document “How to obtain cut-off values” can be found here.

Questionnaires
LASAB034 / LASAC034 / LASAD034 /LASAE034 /LAS2B034 / LASAF034 / LASAG034 / LASAH034 / LAS3B034 / LASMB034 / LASAI034 / LASAJ034 / LASAK034 (main interview: in Dutch)

Variable information
LASAB034 / LASAC034 / LASAD034 /LASAE034 /LAS2B034 / LASAF034 / LASAG034 / LASAH034 / LAS3B034 / LASMB034 / LASAI034 / LASAJ034 / LASAK034
(pdf)

Availability of information per wave ¹

¹ More information about the LASA data collection waves is available here.

* 2B=baseline second cohort;
3B=baseline third cohort;
MB=migrants: baseline first cohort

Ma=data collected in main interview

Previous use in LASA
The summary performance measure has been used in a paper by Penninx et al. (2000). Deeg et al. (1994) also used the results of the baseline performance tests (note: in contrast to other studies, in this study a higher performance score indicates a poorer performance). Change in performance can be calculated by subtracting the scores of two examinations (Penninx et al. 2000). At baseline (LASA-B), a lower-extremity performance score can be calculated by summing up the categorized scores of the walking test and the chair stands test (Visser et al. 2000). Change in lower-extremity performance can be calculated by subtracting the scores of two examinations (Visser, 2000). At LASA follow-up examinations, the summary score can be based on the sum of three lower-extremity tests (Guralnik et al. 1994, 1995, Schaap et al. 2005, Wicherts et al. 2007).

Using results of a single performance test
When using the time of a single performance test as a continuous variable, please consider the following issues: 1) persons who were unable to perform the test will have a missing time and should probably be excluded from the analysis. 2) extreme outliers (e.g. a time of 200 seconds) do occur. One way to diminish the influence of these outliers is to assess the 99th percentile for the test and to replace the time of all persons with a time >99th with this value (Seeman et al. 1994).

Using physical performance information for a LASA subgroup
As described previously, the quartiles of time needed to perform a test are based on the total LASA cohort at LASA-B. Be aware that when using a subgroup of the LASA population, application of these cutoff values may result in a very skewed distribution of the performance variable. For example, when the standard cutoff values were applied to the subgroup of participants who came to the University Hospital for additional measurements, no persons were categorized into category 0 (unable) and hardly any person was categorized into category 1 (slowest quartile). To avoid empty categories, new categories can be created for each performance test based on the quartiles of time needed to perform the test. For an example, see Visser et al. (2000).

Additional observations performance tests
Apart from the time needed to perform a test, the interviewers also have registered additional information regarding the performance of the test. For each performance test the additional information is listed. Walking test: use of device during test, pain during test, type of floor, and walking observations (e.g. starting problems, walk with a limp, unstable turn). In case the test was terminated, the reason has been recorded by the interviewer (e.g., subject refused, was physically not able, not safe). Chairs stands: Height of the chair, subject unstable during test. Balance: In case the subject was not able to perform the test, the reason has been recorded by the interviewer (e.g., subject refused, was physically not able, subject almost fell down). At the I wave some of these additional information has been skipped. Please refer to the dataset for specific changes.

The observations regarding the walking test and the chair stands test have been used by Deeg et al. (1994) to create a “performance problem score”. If one or more particularities were recorded at the walking observations the subject received a score of 1 for that test. When instability was observed during the chair stands test the subject received a score of 1 for that test. The performance problem score was calculated by summing up the score of the two individual tests and values range from 0 – 2 (Deeg et al. 1994).

References

1. Cress, M. E., Schechtman, K. B., Mulrow, C. D., Fiatarone, M. A., Gerety, M. B. & Buchner, D. M. Relationship between physical performance and self-perceived physical function. J. Am. Geriatr. Soc 1995;43:93-101.
2. Deeg DJH. Performance tests of physical ability. In: Deeg DJH, Westerndorp-de Seriere M (eds). Autonomy and well-being in the aging population I: report from the longitudinal aging study amsterdam 1992-1993. Amsterdam: VU University Press, 1996, pp. 21-29.
3. Ferrucci L, Guralnik JM, Pahor M, Corti MC, Havlik RJ. Hospital diagnoses, medicare charges, and nursing home admissions in the year when older persons become severely disabled. JAMA 1997;277:728-734.
4. Gill TM, Williams CS, Tinetti ME. Assessing risk for the onset of functional dependence among older adults: the role of physical performance. J Am Geriatr Soc 1995;43:603-609.
5. Glass TA. Conjugating the “tenses” of function: discordance among hypothetical, experimental, and enacted function in older adults. Gerontologist 1998;38:101-112.
6. Guralnik JM, Branch LG, Cummings SR, Curb D. Physical performance measures in aging research. J Gerontol: Med Sci 1989;44:141-146.
7. Guralnik JM, Simonsick EM, Ferrucci L, Glynn RJ, Berkman LF, Blazer DG, Scherr PA, Wallace RB. A short physical performance battery assessing lower extremity function: association with self-reported disability and prediction of mortality and nursing home admission. J Gerontol: Med Sci 1994:49:85-94.
8. Guralnik JM, Ferrucci L, Simonsick EM, Salive ME, Wallace RB. Lower-extremity function in persons over the age of 70 years as a predictor of subsequent disability. NEJM 1995:332:556-561.
9. Hoeymans N, Feskens EJM, van den Bos GAM, Kromhout D. Reproducibility of performance-based and self-reported measures of functional status. J Gerontol: Med Sci 1997;52:363-368.
10. Kempen R, Steverink N, Ormel J, Deeg DJH. The assessment of ADL among frail elderly in an interview survey: self-report versus performance based tests and determinants of discrepancies. J Gerontol: Psychol Sci 1996;51:254-260.
11. Magaziner J. Hip fracture recovery study patient-proxy concordance study field manual, Baltimore, MD, USA: University of Maryland School of Medicine, 1991.
12. Penninx BWJH, Deeg DJH, van Eijk JThM, Beekman ATF, Guralnik JM. Changes in depression and physical decline in older adults: A longitudinal perspective. Journal of Affective Disorders 2000: 61, 1-12.
13. Reuben, D B, Siu, A L, Kimpau S. The predictive validity of self-report and performance-based measures of function and health. J Gerontol 1992:47:106-110.
14. Schaap LA, Pluijm SM, Smit JH, van Schoor NM, Visser M, et al. The association of sex hormone levels with poor mobility, low muscle strength and incidence of falls among older men and women. Clin Endocrinol (Oxf) 2005;63:152–60.
15. Schaap LA, van Schoor NM, Lips P, Visser M. Associations of Sarcopenia Definitions, and Their Components, With the Incidence of Recurrent Falling and Fractures: The Longitudinal Aging Study Amsterdam. J Gerontol A Biol Sci Med Sci. 2018 Aug 10;73(9):1199-1204.
16. Seeman TE, Charpentier PA, Berkman LF, Tinetti ME, Guralnik JM, Albert M, Blazer D, Rowe JW. Predicting changes in physical performance in a high-functioning elderly cohort: MacArthur Studies of Succesful Aging. J Gerontol 1994;49:M97-108.
17. Visser M, Deeg DJH, Lips P, Harris TB, Bouter LM. Skeletal muscle mass and muscle strength in relation to lower-extremity performance in older men and women. J Am Geriatr Soc 2000;48:381-386.
18. Visser M. De invloed van lichaamsbeweging op de mobiliteit van ouderen: bewegen houdt je op de been. In D.J.H. Deeg, R.J. Bosscher, M.I. Broese van Groenou, L.M. Horn, C. Jonker (Eds.), Ouder worden in Nederland. Tien jaar Longitudinal Aging Study Amsterdam (LASA) (pp. 215-221). Amsterdam: Thela Thesis.
19. Winograd CH, Lindenberger EC, Chavez CM, Mauricio M, Shi H, Bloch DA. Identifying hospitalized older patients at varying risk for physical performance decline: a new approach. J Am Geriatr Soc 1997;45:604-609.

Date of last update: January, 2019