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Keywords:

  • physical function;
  • elderly;
  • women

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Objective: We modified existing standardized measurement tools in the Physical Performance Test and tasks from the Frailty and Injuries: Cooperative Studies of Intervention Technique Study to evaluate physical function in older women. Our objectives were (1) to characterize physical function themes based on combinations of tasks (deriving factors or components) and (2) to quantify the correlation between derived factors and body mass index (BMI).

Research Methods and Procedures: Nutrition risk screens from enrollees in a Medicare-managed risk program served as the sampling frame. To obtain adequate representation for a range of BMI, a random sample was obtained of 90 women from the following BMI strata: BMI, 22 to <27 kg/m2; BMI, 27 to <30 kg/m2; and BMI, ≥30 kg/m2. Subjects were asked to perform a series of 18 functional tasks during a home visit.

Results: The mean age was similar in the three BMI groups with an overall mean age of 71 ± 4.9 years (SD). Factors characterized by lower-body function, upper-body function, coordination, and strength were responsible for 30%, 11%, 9%, and 9% of the variance in task scores, respectively. BMI, controlling for age, explained 5%, 14%, 3%, and 0% of the variation in these factors, respectively. Higher BMI is associated significantly with poorer upper- and lower-body function but is not associated significantly to strength or coordination.

Discussion: Higher BMI seems to differentially impede specific aspects of physical function, especially upper-body function, and to a lesser extent, lower-body function. BMI does not seem to be associated with levels of coordination or strength. Better understanding of how BMI impacts physical function will aid in the design of interventions to promote independent living in elderly, obese women.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Several studies have correlated excess body weight with the development of disability in older persons. High body mass index (BMI), a measure of weight standardized for height (kilograms per square meter), is positively associated with present disability (1,2) and with risk of developing impaired physical function among older men and women (3,4). Other studies showed an increased risk for disability in association with chronic disease, including cardiovascular disease, arthritis, diabetes, and pulmonary disease (2,5,6,7,8). Recent prospective data suggest that BMI is a strong predictor of long-term risk for mobility disability in older women, and that this risk persists even to very old age (9). In contrast, BMI below the 75th percentile (25.4 kg/m2 for men and 25.2 kg/m2 for women) was associated with a high likelihood for continued physical ability and high level of physical function (10).

The mechanisms through which body mass may affect disability have not been identified, although it is suspected that part of the increased risk of disability of overweight persons is caused by the development of chronic disease related to obesity, particularly cardiovascular disease and arthritis (11). However, other factors that are likely to be contributory to disability, especially in the elderly obese, include diminished exercise tolerance, frailty, and social or psychological disadvantages (12). Obesity may contribute to disability by decreasing endurance, by increasing the energy demands of ventilation, and by altering pulmonary function (13,14,15,16). Obesity may also impede mobility and flexibility (17). This suggests that the potential exists to design interventions that directly target obesity-related disability in the elderly, separate from treatments for obesity-related chronic disease.

Unfortunately, current research methodology relies on measures of disability for the elderly (18,19,20,21,22,23,24) that do not capture the specific effect of excess body weight on physical function. The Physical Performance Test (PPT; see Table 1) is an objective, quantifiable test assessing multiple domains of physical function using observed performance of tasks that simulate activities of daily living (24). It can be completed in <10 minutes using only a few simple props and can, therefore, be readily given in the office or community setting. This test demonstrates better sensitivity in detecting disabilities associated with chronic diseases affecting physical functioning than conventional self-reported functional scales. In general, timed physical performance measures have been found to be strong predictors of future functional dependence among nondisabled, free-living, older persons (25). A preliminary study tested the validity of the PPT as a predictor of disability specifically caused by obesity (26). The summary PPT score was associated significantly with measures of body fat. However, analysis of the individual tasks in the PPT did not clearly identify which tasks contributed most to this overall association. This suggested that additional tasks might enhance the yield of information from physical performance testing and that combinations of tasks may be more informative than single tasks in describing obesity-related decrements in performance.

Table 1.  Scoring of functional tasks
TaskRecorded valueTask score
  • *

    Unmodified task, timed tasks were rounded to the nearest half second prior to scoring.

  • Score derived as quartile of non-missing recorded value for completed task with zero assigned for those tasks the subject was unable to do.

  • Modified Physical Performance Test task, timed tasks were rounded to the nearest half second prior to scoring.

  • §

    Frailty and Injuries: Cooperative Studies of Intervention Techniques task.

Write sentence*Time (seconds)0 if unable to do
  1 if ≥20.5 seconds
  2 if 15.5 to 20.0 seconds
  3 if 10.5 to 15.0 seconds
  4 if ≤10.0 seconds
Simulate eating*Time (seconds)0 if unable to do
  1 if ≥20.5 seconds
  2 if 15.5 to 20.0 seconds
  3 if 10.5 to 15.0 seconds
  4 if ≤10.0 seconds
Lift book*Time (seconds)0 if unable to do
  1 if ≥6.5 seconds
  2 if 4.5 to 6.0 seconds
  3 if 2.5 to 4.0 seconds
  4 if ≤2.0 seconds
Put on and remove a jacket*Time (seconds)0 if unable to do
  1 if ≥20.5 seconds
  2 if 15.5 to 20.0 seconds
  3 if 10.5 to 15.0 seconds
  4 if ≤10.0 seconds
Pick up penny from floor*Time (seconds)0 if unable to do
  1 if ≥6.5 seconds
  2 if 4.5 to 6.0 seconds
  3 if 2.5 to 4.0 seconds
  4 if ≤2.0 seconds
Circle turn*Continuous (yes/no) and steady (yes/no)0 if discontinuous and unsteady
  2 if discontinuous and steady
  2 if continuous and unsteady
  4 if continuous and steady
Walk 50 feet†,Time (seconds)1 if ≥20.5 seconds
  2 if 17.5 to 20.0 seconds
  3 if 15.5 to 17.0 seconds
  4 if ≤15.0 seconds
Stair climbing†,Time (seconds)0 if unable to do
  1 if ≥38.5 seconds
  2 if 29.5 to 38.0 seconds
  3 if 25.5 to 29.0 seconds
  4 if ≤25.0 seconds
Accelerated chair stand§See right1 if unable to do
  2 if uses assistance device to push up
  3 if uses arm to push up
  4 if able to stand up with arms crossed
Hand-grip dynamometry—dominant hand†,§Average force of three attempts (kg)0 if unable to do
  1 if ≤21.2 kg
  2 if 21.2 < force ≤ 25.2 kg
  3 if 25.2 < force ≤ 28.5 kg
  4 if >28.5 kg
Hand-grip dynamometry—non-dominant hand†,§Average force of three attempts (kg)0 if unable to do
  1 if ≤19.3 kg
  2 if 19.3 < force ≤ 23.0 kg
  3 if 23.0 < force ≤ 26.1 kg
  4 if >26.1 kg
Static balance—foot halfway in front of the other§Time up to 10 secondsActual time
Static balance—foot totally in front of the other§Time up to 10 secondsActual time
One-legged stance—eyes open—right side§Time up to 10 secondsActual time
One-legged stance—eyes open—left side§Time up to 10 secondsActual time
One-legged stance—eyes closed—right side§Time up to 10 secondsActual time
One-legged stance—eyes closed—left side§Time up to 10 secondsActual time

The Frailty and Injuries: Cooperative Studies of Intervention Techniques (FICSIT) trials were the first nationally sponsored set of clinical trials concerning physical frailty and risk for injuries in later life (27). The results are intended to serve as a reference in designing health interventions for older persons. A modification of the PPT combined with some of the tests used in FICSIT were used to evaluate physical function in elderly women over a wide range of BMI.

Research Methods and Procedures

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

Subjects for this study were gathered by random sampling through a nutrition screening program of the Geisinger Health Plan that is administered to all enrollees in a Medicare Managed-Risk Program (28). More than 100 Geisinger Clinic sites throughout largely rural central and eastern Pennsylvania implemented a one-page level II Screen developed by the Nutrition Screening Initiative (29). Clinic staff recorded height and weight, and enrollees completed remaining items during visits for usual care. Clinical staff forwarded completed assessment forms to our research center. A possible problem in ensuring equal representation of women across the range of BMI in this study population involved the potential for higher rates of refusal among women with higher BMI; therefore, a stratified random sampling scheme was used. Women were stratified into three groups defined by tertiles of healthy to high BMI: 22 to <27 kg/m2; 27 to <30 kg/m2; and ≥30 kg/m2. Women with BMI ≤22 kg/m2 were excluded because of the likelihood of disability secondary to frailty and sarcopenia. Women within each stratum, who were 65 years of age or older, were randomly selected as potential subjects. Medical record review excluded potential subjects who were not community-dwelling; had a history of severe depression or cognitive disability that could compromise meaningful consent and participation; had any disease or event that might compromise physical function independent of obesity including rheumatoid arthritis, Paget's disease of bone, or other bone diseases; or had disability caused by prior trauma. Potential subjects with diabetic neuropathy, osteoarthritis, sleep apnea, hypertension, hyperlipidemia, or any other comorbidity of obesity were eligible for the study. The study coordinator contacted eligible women by phone to invite study participation. The Geisinger Medical Center Institutional Research Review Board approved this study. Study staff obtained written informed consent in person from each subject at the home visit.

A “mini-mental status” exam (30), given to each subject at the home visit, excluded two women who scored less than the average for the population reference group based on age and educational level, even though prior medical record review did not identify cognitive deficits (one woman with three errors and a high-school education, one woman with four errors and an elementary-school education). Study staff measured height and weight to verify qualifying BMI and to correctly classify women into BMI strata. This yielded several reclassifications between initial BMI strata. Study staff then administered a composite set of functional performance tests to study subjects.

Focusing on mobility and endurance, a composite set of tasks was designed to combine 8 of the 9 PPT tasks (excluding a four-flight stair climb) with 10 tasks used in the FICSIT trials (27). The added tasks included an accelerated chair stand, hand-grip dynamometry (dominant and non-dominant), static balance (feet together, foot halfway in front of the other, and foot totally in front of the other), one-legged stance (right and left), and one-legged stance with eyes closed (right and left). All timed measures were determined with a stopwatch. Two of the measurements—a 50-foot walk and climbing one flight of stairs—were revised from the description in Reuben and Siu (24) to accommodate testing in the home environment. The 50-foot walk was modified for home use by retracing steps after walking 25 feet. Climbing one flight of stairs (12 steps) was accomplished using a stair stepper built specifically for this purpose. Quartile rankings, based on the full complement of study data, replaced actual times for the 50-foot walk, stair climbing, and dominant and non-dominant hand-grip dynamometry. Those subjects unable to complete the task received scores of zero. This scheme handled uncompleted FICSIT tasks in a manner comparable with PPT tasks. Table 1 reports the correspondence between recorded values and scores for each of the 18 tasks. Although it is generally preferable to use continuous valued measurements such as those involving time where possible, it was necessary to use ordinal assignments to allow for the inability to complete a task (equivalently, an infinite time). The order of scores is consistent across tasks such that lower numbers indicate difficulty in completing tasks or poor performance, and higher numbers indicate successful completion or excellent performance. For some PPT tasks, this involved reversing the order of task scores. Such reordering does not fundamentally change the properties of the measurement.

Medians and bootstrapped 95% confidence intervals summarized task performance for each BMI group (Table 2). Medians permit meaningful summarizing of timed values that were right-skewed. Factor analysis (31) identified a parsimonious set of thematically meaningful factors comprised by weighted combinations of tasks. The sample size of 90 subjects was chosen because of a rule of thumb that suggests that a minimum of five subjects per variable—18 functional tasks here—be used to support a factor analysis. However, some data reduction before factor analysis seemed to be prudent after initial inspection of the data. This improves the statistical power for this analysis. The factor analysis excludes scores for the “Static Balance-Feet Together” task, which was the maximum of 10 seconds for all subjects. Further data reduction was achieved by averaging paired (left/right or dominant/non-dominant) measures. This left 14 variables for input into the factor analysis. A latent root criterion guided the retention of factors with a latent root of at least one. Varimax rotation of retained factors estimated factor loadings for the purpose of interpretation. Multiple linear regression analysis quantified associations between BMI, while controlling for age, with derived components characterized by specific dimensions of physical function. Data analyses used SAS software (Statistical Analysis Systems, Cary, NC).

Table 2.  Medians and bootstrap 95% confidence intervals (confidence intervals shown in parentheses) for selected* functional tasks and standardized factor scores
TasksBMI 22 to <27 (kg/m2)BMI 27 to <30 (kg/m2)BMI ≥ 30 (kg/m2)
  • *

    Summaries for some tasks are not reported. The ordinal scores for the circle turn and accelerated chair stand are not appropriately summarized by medians. More than one-half of subjects in each group maintained static balance (foot halfway and totally in front of other) for the full 10 seconds such that the median is 10 for all groups. All subjects maintained static balance with feet together for the full 10 seconds so that there was no variability in the data.

  • One subject (BMI ≥ 30 kg/m2) was unable to write sentence.

  • One subject (BMI 22 to <27 kg/m2) was unable to do hand-grip dynamometry on the dominant hand.

  • §

    Three subjects (2 with BMI 22 to <27 kg/m2 and 1 with BMI ≥ 30 kg/m2) were unable to complete the stair climbing task.

Write sentence (seconds)10.911.012.1
 (10.0, 12.1)(10.5, 11.7)(11.3, 12.8)
Simulate eating (seconds)9.810.311.8
 (9.3, 11.2)(8.6, 11.0)(10.2, 12.6)
Lift book (seconds)2.72.42.7
 (2.5, 2.8)(2.1, 2.4)(2.4, 3.0)
Put on and remove a jacket (seconds)6.66.47.0
 (5.7, 7.2)(5.9, 6.9)(6.4, 8.5)
Pick up penny from floor (seconds)2.22.32.3
 (2.0, 2.6)(2.1, 2.3)(2.1, 2.5)
Walk 50 feet (seconds)17.017.619.1
 (15.1, 18.1)(17.0, 18.4)(17.3, 20.0)
Hand-grip dynamometry—dominant hand (kg)21.724.727.3
 (19.7, 22.2)(22.3, 25.0)(22.0, 29.5)
Hand-grip dynamometry—non-dominant hand (kg)21.922.725.0
 (19.3, 23.7)(20.3, 24.2)(21.8, 26.7)
One-legged stance—eyes open—right side (seconds)9.64.55.8
 (4.8, 10.0)(1.9, 7.5)(2.2, 6.9)
One-legged stance—eyes open—left side (seconds)8.13.83.7
 (4.3, 10.0)(2.0, 6.5)(2.1, 6.1)
One-legged stance—eyes closed—right side (seconds)1.51.91.6
 (1.3, 2.2)(1.1, 2.1)(0.8, 2.0)
One-legged stance—eyes closed—left side (seconds)1.71.81.2
 (1.1, 1.9)(1.2, 2.0)(1.0, 1.8)
Stair climbing (seconds)§26.730.434.4
 (24.5, 29.7)(25.1, 31.4)(28.5, 38.6)
Factors
Lower-body function0.27− 0.01− 0.29
 (−0.10, 0.64)(−0.36, 0.33)(−0.67, 0.10)
Upper-body function0.330.06− 0.42
 (−0.02, 0.68)(−0.20, 0.32)(−0.87, 0.02)
Standing coordination− 0.320.170.20
 (−0.89, 0.24)(0.08, 0.26)(0.05, 0.35)
Strength− 0.250.220.06
 (−0.64, 0.15)(−0.11, 0.56)(−0.32, 0.44)

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

A total of 90 women, with a BMI >22 kg/m2, were enrolled in this study, with two exclusions after the mini-mental status exam. The 88 remaining participants were assigned BMI categories; 32 women were in the lowest BMI group, 27 women were in the middle BMI group, and 29 women were in the highest. There was no difference in age between the three BMI groups (p = 0.276; 71 ± 5 years).

A comparison of women who were in the sampling frame but who did not participate in the study (n = 951) to those enrolled (n = 88) partially addressed the representativeness of the study sample. The study and nonstudy groups did not differ with respect to BMI (29.1 and 29.7, respectively; p = 0.297), and age (70.8 and 70.3 years; respectively, p = 0.412). Additionally, the two groups did not differ with respect to the self-reported responses on the Nutrition Risk Level II Screen, except for a loss of 10 lbs in the last 6 months (14.8% and 7.3%, respectively; p = 0.012).

Table 2 summarizes task performance by BMI group using medians and confidence intervals. There is considerable overlap between groups for most tasks, although performance on some tasks demonstrates clear associations with BMI. For example, median strength from hand-grip dynamometry and median time for stair-climbing performance are ordered according to BMI group, with greater strength and longer stair-climbing times evident among those with higher BMI. For a number of other tasks such as the one-legged stances, medians seem to differ for one group relative to the other two. This suggests that BMI-related performance may not be graded throughout the range of BMI; rather, performance may be subject to a threshold BMI beyond which decrements are incurred.

Table 3 summarizes the results from the factor analysis. The factor analysis produced four factors with latent root values greater than one; however, factors 3 and 4 were considered marginal. These four factors comprised 59% of the variance and were retained for further analysis. Factor loadings of ∼0.60 or higher are statistically significant at the 0.05 level with a sample size of 85 (31), roughly corresponding to the sample size here. A somewhat more relaxed criterion of 0.50 considers the importance of tasks for which the factor accounts for 25% of its variance, and that is the criterion used here. The first factor was characterized as a measure of lower-body function because the high-loaded tasks included the following: walking 50 feet, static balance—foot totally in front of the other, one-legged stance (eyes open), one-legged stance (eyes closed), and stair climbing. The second factor may be interpreted as a measure of upper-body function because the high-loaded tasks included the following: writing a sentence, simulating eating, putting on and removing a jacket, and picking up a penny from floor. The third factor may be interpreted as a measure of coordination in standing because the high- loaded tasks included only the accelerated chair stand and the static balance task with one foot halfway in front of the other. The fourth factor may be interpreted as a measure of strength because the high-loaded tasks included only a lifting task and hand-grip dynamometry. Table 2 illustrates the extent to which factor scores vary with BMI, with mean factor scores and their 95% confidence intervals reported.

Table 3.  Rotated factor loadings for retained factors
 Factor
 1234
  • *

    Bold numbers correspond to the functional tasks that loaded highly for each factor.

Latent root4.31.61.31.2
Percent variance explained30%11%9%9%
Lower-body function    
 One-legged stance—eyes open0.79*0.190.030.27
 Static balance—foot totally in front of other0.75−0.190.24−0.07
 One-legged stance—eyes closed0.510.170.000.39
 Stair climbing0.500.490.010.34
Upper-body function    
 Put on and remove a jacket0.030.710.010.12
 Pick up a penny0.280.620.04−0.14
 Write a sentence0.190.610.180.13
 Simulated eating−0.120.500.270.19
Standing coordination    
 Static balance—foot halfway in front of the other0.030.030.860.18
 Accelerated chair stand0.130.250.830.04
Strength    
 Hand-grip dynamometry0.16−0.010.150.75
 Lift a book0.130.410.140.68

Regression analysis evaluated the ability of BMI, while controlling for age, to predict physical function based on the derived components (Table 4). BMI, controlling for age, explained modest variation in factor scores for lower-body function (5%; p = 0.032) and upper-body function (14%; p < 0.001), but not standing coordination or strength.

Table 4.  Summary of regressions of BMI and age on each factor separately
 BMIAge
FactorPartial R2pPartial R2p
  1. BMI, body mass index.

Lower-body function0.0500.0320.0690.012
Upper-body function0.137<0.0010.193<0.001
Standing coordination0.0290.1110.0130.281
Strength0.9210.203<0.001

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

The study population is generally representative of the health system membership from which the sample was drawn. An isolated finding that self-reported recent weight loss was more prevalent among nonparticipants is the only evidence of potential nonrepresentativeness. Because this was the only difference found by comparing a number of responses on the Nutrition Screen, this finding is likely spurious.

It has been previously determined that nutritional status, indicated by BMI, is related to the functional capabilities of the elderly, and that the relationship fits roughly the same U-shaped curve that has described the relationship between mortality and BMI (3). However, just as the causes of higher mortality in persons with low and high BMI differ, so likely do the causes of impaired functionality in persons with low and high BMI. Tests of physical function should ideally be able to distinguish these two types of disability.

This study found associations between excess body weight (BMI) on functional performance in older women. The results suggest that higher BMI seems to impede specific aspects of physical function. It was previously thought that weight-related disability would primarily affect lower-body function (9). Our results indicate that while controlling for age, upper-body function and, to a lesser extent, lower-body function were related to BMI. No evidence was provided to support a link between BMI and strength or BMI and coordination.

In older, obese women, use of the upper body (for tasks such as eating, writing, and dressing) and use of the lower body (for tasks such as standing, walking, and climbing) become more difficult. By focusing on upper-body and lower-body functions, the design of interventions to promote independent living in elderly, obese women may improve.

Prior studies on disability have focused on that subset of the elderly considered “frail,” those with low BMI and sarcopenia (32). We propose that obese older women are also frail in that they also exhibit specific impairments in functionality (33). A strong association between weight and physical function in women has been documented in longitudinal data using quality-of-life questionnaires to measure aspects of functionality (34). This study used a set of direct measures of physical function to test the effect of weight on specific tasks that could be related to activities of daily living. We hope our findings will ultimately improve the design of future physical performance testing to detect disability of obese older persons. Additional effort is needed to determine whether findings presented here can be generalized to other rural, and perhaps also to urban, populations. Similarly, efforts to replicate these findings as well as to establish the face validity of the derived factors would be an important next step. Finally, consideration of the potential confounding or modifying effects of habitual activity levels on physical function would substantially improve the design of meaningful future interventions aimed at improving function in elderly obese women.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References

This work was supported by a grant from Geisinger Medical Center, which supported the principal investigator: The Geisinger Clinic Clinician-Investigator Career Development Award.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Research Methods and Procedures
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References