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Changes in Physical Functioning in the Active Living Every
Day Program of the Active for Life Initiative®
Meghan Baruth &Sara Wilcox &Stacy Wegley &
David M. Buchner &Marcia G. Ory &Alisa Phillips &
Karen Schwamberger &Terry L. Bazzarre
Published online: 30 June 2010
#International Society of Behavioral Medicine 2010
Abstract
Background Physical activity can prevent or delay the
onset of physical functional limitations in older adults.
There are limited data that evidence-based physical activity
interventions can be successfully translated into community
programs and result in similar benefits for physical
functioning.
Purpose The purpose of this study is to measure the effects
of the Active Living Every Day program on physical
functioning and physical functional limitations in a diverse
sample of older adults.
Methods As a part of the Active for Life initiative, the
Council on Aging of Southwestern Ohio implemented
Active Living Every Day (ALED), a group-based lifestyle
behavior change program designed to increase physical
activity. Performance-based physical functioning tests (30-s
Chair Stand Test, eight Foot Up-and-Go Test, Chair Sit-
and-Reach Test, 30-Foot Walk Test) were administered to
participants at baseline and posttest. Baseline to post-
program changes in physical functioning and impairment
status were examined with repeated measures analysis of
covariance. Interactions tested whether change over time
differed according to race/ethnicity, body mass index
(BMI), and baseline impairment status.
Results Participants significantly increased their perfor-
mance in all four physical functioning tests. The percentage
of participants classified as “impaired”according to
normative data significantly decreased over time. Physical
functioning improved regardless of BMI, race/ethnicity, or
baseline impairment status.
Conclusions ALED is an example of an evidenced-based
physical activity program that can be successfully translated
into community programs and result in significant and
clinically meaningful improvements in performance-based
measures of physical functioning.
Keywords Physical activity .Exercise .
Translational research .Behavioral intervention
Introduction
As adults age, limitations in functional abilities increase,
often resulting in impairments in tasks of everyday living.
S. Wilcox
University of South Carolina,
Columbia, SC, USA
S. Wegley :K. Schwamberger
Hamilton County Public Health,
Cincinnati, OH, USA
D. M. Buchner
University of Illinois at Urbana-Champaign,
Champaign, IL, USA
M. G. Ory
Texas A & M Science Center,
College Station, TX, USA
A. Phillips
Council on Aging of Southwestern Ohio,
Cincinnati, OH, USA
T. L. Bazzarre
Robert Wood Johnson Foundation,
Princeton, New Jersey, USA
M. Baruth (*)
Public Health Research Center, University of South Carolina,
921 Assembly Street, Suite 318,
Columbia, SC 29208, USA
e-mail: stritesk@mailbox.sc.edu
Int.J. Behav. Med. (2011) 18:199–208
DOI 10.1007/s12529-010-9108-7
Preventing functional limitations can help individuals
maintain their quality of life and reduce their medical care
expenditures [1]. Physical activity has been shown to
prevent or delay the onset of physical functional limitations
in older adults [2–4]. Unfortunately, both self-report and
objective data indicate that older adults are not engaging in
the recommended amounts of physical activity necessary
for health benefits [5,6].
A number of studies have shown that exercise interven-
tions can improve physical functioning [2,3,7–17]. Studies
in this area have typically been multicomponent (i.e.,
aerobic, strength, balance, and flexibility) [2,3,9–15], have
been conducted in a supervised, center-based setting [3,9,
12–17], and included exercise goals of three to five times per
week, for 20-60 min [3,9,11,12,14,16,17]. There is a
need to examine whether these benefits can occur through
less structured, community-based programs.
Physical activity as a means of improving or maintaining
physical functioning is promising; however, a number of
gaps in the extant literature exist. It is unclear if and how
these evidence-based physical activity interventions in
older adults can be successfully translated into community
programs and if they result in similar benefits. In order for
such programs to make a public health impact, evidence-
based programs need to be successfully translated into
community settings. Second, the effect of physical activity
on functional limitations most likely varies depending on
baseline functioning. In older adults with substantial
existing functional limitations, physical activity probably
provides a therapeutic or rehabilitative effect, whereas in
older adults without substantial functional limitations, the
effect of physical activity is presumably to prevent
worsening of existing functional ability. Studies typically
do not stratify results by baseline functional ability [2,9–
11,13,14,17], and thus it is often difficult to discern the
severity of functional limitations in the participants from
the published results [18]. Third, because the prescribed
dose of physical activity does not vary much across studies,
it is difficult to determine whether a dose response exists, or
how much physical activity is necessary to improve or
maintain functional ability [18]. Finally, there is concern
that randomized controlled trials recruit non-representative
samples of community adults. Although some studies
include diverse populations [3,8,11,12,15], few report
differences across racial/ethnic groups [3,8,15]. We need
more information on the effects of physical activity in less
advantaged and more ethnically diverse subgroups [3,18].
Active for Life (AFL) was a 4-year translational
initiative that successfully implemented two evidence-
based behavior modification programs (Active Choices
[AC] and Active Living Every Day [ALED]) into “real-
world”community settings with diverse populations,
resulting in significant improvements in self-reported
physical activity in midlife and older adults [19]. One
AFL site, Council on Aging of Southwestern Ohio,
conducted baseline and post-program performance-based
physical functioning tests with participants taking part in
the ALED program. The purpose of this study was to
examine whether ALED was associated with improvements
in physical functioning and reductions in physical func-
tional limitations in a diverse sample of older adults.
Furthermore, we examined whether changes in physical
functioning differed according to selected baseline charac-
teristics, and if there was a dose response relationship
between physical activity and physical functioning.
Methods
Participants
Participants were recruited from various locations including
senior centers, YMCAs, community recreation centers,
retirement communities, and churches. The most successful
recruitment efforts were on-site staff recruitment, presenta-
tions at the facilities, direct mail, flyers, newsletters, and
local media. Participants were screened by the site staff for
eligibility. The site contracted with the program facilitators
and provided the expertise to oversee the program
development, implementation, and ongoing sustainability.
Participants were ≥50 years of age, sedentary or
underactive (≤2 days/week and <120 min/week), and free
of medical conditions or disabilities that required higher
levels of supervision, as determined by lead staff [19].
Although medical clearance to participate in the testing and
intervention was not required, participants who endorsed
any Physical Activity Readiness Questionnaire item were
excluded from the 30-s Chair Stand Test (n=186) and those
who endorsed the Physical Activity Readiness Question-
naire item about dizziness were excluded from the Eight
Foot Up-and-Go Test (n=12). All participants completed an
informed consent form approved by the Institutional
Review Boards at the University of South Carolina, Texas
A & M Health Science Center, and the legal counsel of the
Council on Aging of Southwestern Ohio.
Research Design and Procedure
This study used a pre-post design, with data collected from
2003 to 2007. Participants were recruited over a 4-year
period of time. Participants completed a survey assessing
sociodemographic characteristics, physical activity, other
health-related practices, and psychosocial variables, and
four performance-based physical functioning tests at base-
line and at 20 weeks. Approximately 100 participants in
each year completed full surveys. This decision was made a
200 Int.J. Behav. Med. (2011) 18:199–208
priori as it was not necessary for adequate statistical power
to collect survey data on all participants across all years.
Thus, the sample sizes are smaller for the analyses on the
physical functioning and self-reported physical activity
measures, due to missing physical activity data.
Program Overview
Details of AFL are described elsewhere [19,20]. In brief,
AFL was a translational initiative that evaluated the effects
of two evidence-based physical activity interventions,
ALED and AC, on self-reported physical activity and
related outcomes in midlife and older adults. AC was a
6-month telephone-based program [21–23], whereas ALED
was a 20-week group-based program (more details of
ALED are described below) [24,25]. Results showed
significant increases in moderate-to-vigorous intensity
physical activity (MVPA) and total physical activity.
Results were generally consistent across years and sites
[19]. Only participants recruited from the Council on Aging
of Southwestern Ohio/Hamilton County Health Depart-
ment, who implemented ALED, are reported in this paper,
as this was the only site that conducted physical functioning
measures.
Intervention
ALED, as originally developed, is a 20-week lifestyle
physical activity intervention that teaches the cognitive and
behavioral skills necessary to become and remain physical-
ly active. Each week, participants attended a 60-min group-
based session that focused on cognitive and behavioral
strategies consistent with the Social Cognitive Theory [26]
and the Transtheoretical Model [27]. Participants received a
book that covered weekly class materials (e.g., goal setting,
problem-solving, self-monitoring) and contained work-
sheets and assignments. The goal of ALED was to help
participants accumulate at least 30 min of MVPA on most
days of the week.
After year 3, the lead organizations taking part in AFL
requested that the ALED program be shortened to 12 weeks.
Although the program was shortened in year 4, steps were
taken to ensure essential elements were maintained (e.g.,
extending class length and removing redundant informa-
tion) [19]. Participants taking part in the intervention during
year 4 completed the physical functioning tests at 12 weeks
and a post-program follow-up survey at 20 weeks.
Measures
Lead staff was trained by an expert in physical functioning
in how to administer the performance-based measures. The
training was interactive and included didactic and hands-on
assessments. These lead staff trained and oversaw staff
onsite to conduct the measurements. The test manual and
videotape provided by Human Kinetics, Inc. were used to
aid trainings [28].
Socio-demographic and Health-Related Variables Partici-
pants reported their date of birth, gender, race/ethnicity, and
presence of chronic health conditions. Height to the nearest
0.5 in. and weight to the nearest 0.1 pound were obtained
by trained staff. Body mass index (BMI) was calculated
using the standard equation in SI units.
Physical Activity The 41-item Community Health Activi-
ties Model Program for Seniors (CHAMPS) questionnaire
was used to assess physical activity [29]. This self-report
measure assesses the frequency and duration of various
activities typically undertaken by older adults for exercise,
activities undertaken in the course of their day that are
physical in nature, and recreational activities that provide
physical activity. The frequency of the activity is assessed
as the number of times per week, and the duration is
assessed as total time per week using a six-item scale
ranging from “less than 1 hour a week”to “9 or more hours
per week.”Minutes/week spent in MVPA (MET value
of ≥3.0) was calculated. This measure is valid [30], has
acceptable test-retest reliability [30], and is sensitive to
change [22,29,31–33]. In year 2 of the study, only those
21 items used to score the CHAMPS were administered in
order to reduce participant burden.
Physical Functioning Four performance-based measures
were used to assess physical functioning: the 30-s Chair
Stand Test, the Eight Foot Up-and-Go Test, the Chair Sit-and-
Reach Test, and the 30-Foot Walk Test. These tests, which we
expected would be sensitive to change as a result of the
intervention, did not require much time to administer, and
could be administered in most of the settings (i.e., did not
require special space). Each of these tests was administered
during all 4 years of AFL with the exception of the Chair Sit-
and-Reach Test, which was only administered during year 3.
30-s Chair Stand Test The 30-s Chair Stand Test assessed
lower body strength [28]. Participants sat in the middle of a
17-in. (37.4 cm) high chair with their back straight, feet flat
on the floor, with their arms crossed at the wrist and held
against the chest. On the signal, “go”participants rose to a
full stand and returned to a fully seated position, without
pushing off with the arms. Participants completed as many
stands as possible. The test score was the total number of
stands completed in 30 s.
Eight Foot Up-and-Go Test The Eight Foot Up-and-Go
Test assessed agility and dynamic balance [28]. Participants
Int.J. Behav. Med. (2011) 18:199–208 201
sat in the middle of a 17-in. high chair with their back
straight, feet flat on the floor, and their hands on the thighs.
On the signal “go”participants got up from the chair,
walked as quickly as possible around a cone placed 8 ft
(2.4 m) from the chair, and sat back down. Participants
completed one practice test and two test trials. The test
score was the faster of the two trials, recorded to the nearest
1/10 of a second by a standard stopwatch.
Chair Sit-and-Reach Test The Chair Sit-and-Reach Test
assessed lower-body (primarily hamstring) flexibility [28].
Participants sat on the front edge of a 17-in. high chair and
extended one leg out as straight as possible in front of the
hip, with the foot flexed and heel resting on the floor. With
their arms outstretched, hands overlapping, and middle
fingers even, participants slowly bent forward at the hip
joint, reaching as far forward as possible toward (or past) the
toes. Participants had to hold their maximum reach for 2 s.
The distance from the tips of the middle fingers to the top of
the shoe (to the nearest 0.5 in) was measured. The “zero
point”was considered the midpoint at the top of the shoe. A
reach short of this point was recorded as a minus (−)score;a
reach touching this point was recorded as a zero; and a reach
past this point was recorded as a plus (+) score. Participants
completed two practice trials and two test trials. The test
score was the best (highest) of the two trials.
30-Foot Walk Test The 30-Foot Walk Test assessed walking
speed [34]. The test was performed twice; first at the
participants’preferred walking speed, and then at their
fastest walking speed. On the signal “ready, go”, partic-
ipants started walking. The stopwatch did not start until the
participant crossed the 10-ft (3.0 m) line, and was
subsequently stopped when the participant crossed the 40-
ft (12.2 m) line. The test score was the time to the nearest 1/
10 of a second. The fastest walking speed trial was used in
analyses.
Statistical Analyses
Participants who completed any baseline physical function-
ing test and had complete model covariates (gender, age,
race/ethnicity, and BMI) were included in the baseline
demographic analyses. Differences among participants who
completed baseline tests only versus those who completed
both baseline and post-program assessments were examined
with χ
2
or ttests. Square root transformations were
conducted on both baseline and post-program scores for
MVPA, the Eight Foot Up-and-Go Test, and the 30-Foot
Walk Test, as these measures were skewed and/or had high
kurtosis. The transformations successfully corrected the
problem(s).
Two types of change analyses were conducted. The first
used all available data from participants. Because of the
missing post-program data on a considerable number of
participants, the second type of change analyses used an
intent-to-treat model, which assumed no change in out-
comes among participants who did not complete post-
program measures by carrying forward baseline values.
This more conservative approach was compared to results
from analyses with all available data. Unless results were
significantly different, we report the findings based on the
first approach.
Changes in Physical Functioning
A repeated measures analysis of covariance (ANCOVA;
using a mixed model analysis) examined baseline to post-
program changes in physical functioning. Each of the four
performance-based measures was tested in a separate
model, and all models controlled for gender, age, race/
ethnicity, and BMI. Participants with modifications that
were the same at both time points, e.g., participants who
used the same assistive device at baseline and post-program
assessments for the Eight Foot Up-and-Go Test (all but six
participants) and the 30-Foot Walk test (all but nine
participants), were included in change analyses. Participants
with modifications that were not the same at both time
points were included in the carry forward analyses by
carrying forward their baseline test value. For the Chair Sit-
and-Reach Test, if the outstretched leg differed from
baseline to post-program assessments (n=52), the partic-
ipant’s data were only used in carry forward analyses by
carrying forward the baseline test value. Effect sizes (d=
post-program mean−baseline mean/baseline standard devi-
ation) using adjusted means were computed for each of the
four physical functioning measures [35]. Using Cohen’s
effect sizes [36], d= 0.2 was considered small, d=0.5
medium, and d=0.8 large.
Changes in Impairment Status
Based on Rikli and Jones’[28] normative data, participants’
30-Second Chair Stand, Eight Foot Up-and-Go, and Chair
Sit-and-Reach test scores were classified as impaired (≤
25th percentile) or within normal limits (>25th percentile)
at baseline and post-program (normative data are not
available for the 30-Foot Walk Test so this test was not
used for these analyses). Because norms have only been
developed for persons aged 60-94 years, we applied the 60-
64 years of age norms to any participant <60 years, and the
90-94 years of age norms to participants >94 years. Partic-
ipants who modified test procedures at baseline (e.g., used a
cane or walker, n=20 for the Eight Foot Up and Go) were
not included in any impairment status analyses. Participants
202 Int.J. Behav. Med. (2011) 18:199–208
with modifications at post-program only (not at baseline)
were included in the carry forward analyses by carrying
forward their baseline impairment status.
A repeated measures ANCOVA (using a mixed model
analysis) examined whether the percentage classified as
impaired (dichotomized variable) changed from baseline to
post-program. Each of the performance-base measures was
tested in a separate model, controlling for the same
variables listed above.
Dose-Response Relationship—MVPA and Physical
Functioning
Residualized change scores were computed for both MVPA
and each of the four physical functioning measures. Linear
regression was used to examine the relationship between
change in physical activity and change in each of the four
physical functioning measures, after controlling for the
same covariates listed above.
Changes in Physical Functioning by Baseline Variables
A repeated measures ANCOVA (using a mixed model
analysis) was conducted to examine whether changes in
physical functioning from baseline to post-program differed
according to race/ethnicity (White vs. Non-white), BMI
(normal weight, overweight, obese), and baseline impair-
ment status (impaired vs. not impaired). Time× baseline
predictor interactions were tested for each of the four
physical functioning measures, after controlling for the
same covariates listed above.
Results
This study included 877 participants who completed at least
one baseline performance-based physical functioning test.
Of the total sample, 83% were white and 16% were African
American, 85% were female, 85% were overweight or
obese, 43% were married or partnered, 56% had at least
some college education, and 67% self-reported at least two
chronic health conditions. The mean age was 71.2±
9.1 years, and the mean BMI was 31.5± 7.0 kg/m
2
.
Participants engaged in 2.7±4.0 h/week of MVPA at
baseline. Table 1shows the adjusted baseline scores for
each of the four physical functioning tests, whereas Table 2
shows the percentage (adjusted) of participants impaired
according to Rikli and Jones’[28] normative data.
Participants attended 68.5% of the ALED sessions during
the intervention period.
Participants who completed baseline and post-program
assessments performed significantly better on the baseline
30-s Chair Stand Test, the Eight Foot Up-and-Go Test, and
the 30-Foot Walk Test compared to those who completed
baseline assessments only. There were no significant
differences in demographic variables or baseline physical
activity among these two groups.
Changes in Physical Functioning
Participants experienced significant baseline to post-
program improvements in all four performance-based
physical functioning tests. Table 1shows the adjusted
baseline and post-program mean scores for all tests, as well
as the calculated effect sizes for the change. The magnitude
of the effects was small ranging from −0.17 to 0.37.
Changes in Impairment Status
The percentage of participants classified as “impaired”signif-
icantly decreased over time for all three physical functioning
measures. Table 2shows the percentage impaired at baseline
and post-program for the physical functioning tests.
Associations between Changes in MVPA and Changes
in Functional Fitness
Increases in MVPA were related to significant improve-
ments in the Eight Foot Up-and-Go Test (r=−0.27, p=
0.03), suggesting a dose-response relationship. This signif-
icant association remained after controlling for race/ethnic-
ity, age, BMI, and gender (p=0.006). The same relationship
was found for the 30-s Chair Stand Test (r=0.18, p= 0.03),
however, the relationship was not statistically significant
after controlling for covariates (p=0.32). Changes in
MVPA were not significantly associated with changes in
the Chair Sit-and-Reach Test (r=−0.11, p=0.48) or the 30-
Foot Walk Test (r=−0.11, p=0.13).
Associations between Baseline Variables and Changes
in Functional Fitness
Table 3shows whether changes in physical functioning
over time differed by race/ethnicity, BMI, and baseline
impairment status. Race/ethnicity and BMI category were
unrelated to improvements in any of the four physical
functioning measures, indicating that improvements were
similar across race and weight status groups.
Baseline impairment status was significantly related
to post-program changes in the Eight Foot Up-and-Go Test
(p<0.0001) and the 30-s Chair Stand Test (p<0.0001).
Although all participants had significant improvements in
both tests, participants who were classified as impaired at
baseline showed significantly greater post-program
improvements in both tests compared to those who were
not impaired at baseline.
Int.J. Behav. Med. (2011) 18:199–208 203
Discussion
The major finding of this study is that ALED significantly
improved physical functioning and reduced the percentage
of participants classified as “impaired”according to fitness
norms [28] in a sample of older adults with diverse levels of
baseline physical functioning statuses. Effect sizes were in
the small to medium range; applied to the entire population,
these changes in functional ability would be very meaning-
ful. ALED, a behavioral intervention, resulted in significant
increases in physical activity. Although strength and
flexibility exercises were encouraged during the group-
based sessions, the main focus of ALED was increasing
aerobic activity to 30 min of MVPA on most days. Therefore,
it is likely that the changes seen in physical activity were via
aerobic activity. Effect sizes may have been larger had
strength, flexibility, and balance activities been specifically
targeted, as a number of exercise modes may contribute to
improvements in functional fitness [10].
A major gap in the existing literature is whether physical
activity programs can effectively improve physical func-
tioning across racial/ethnic and weight status groups [18].
We found significant improvements irrespective of race and
BMI. Our findings are consistent with the results from the
Table 1 Baseline and post-program means (SE) in performance-based physical functioning measures and self-reported physical activity
Baseline Post-program Fstatistic, pvalue Effect size (d)
Mean (SE) Mean (SE)
30-sec Chair Stands, # 10.7 (0.22) 12.1 (0.24) 81.62, <0.0001 0.37
Eight Foot Up & Go, seconds 6.8 (0.12) 6.4 (0.12) 77.82, <0.0001 −0.23
Chair Sit-and-Reach, inches −1.6 (0.57) −0.5 (0.57) 9.02, 0.0030 0.32
30-Foot Walk Test, seconds 6.1 (0.10) 5.8 (0.10) 40.88,<0.0001 −0.17
Physical Activity, hours/week of MVPA 3.5 (0.35) 5.6 (0.38) 88.50, ≤0.0001 0.55
Means and standard errors are adjusted for race/ethnicity (White vs. Non-white), age, BMI, and gender. Effect sizes (d) are computed using
adjusted baseline and post-program means and baseline unadjusted standard deviations. For the Eight Foot Up & Go and 30 Foot Walk Test, a
negative effect size indicates a more favorable change. Square root transformations were conducted for Eight Foot Up & Go, 30-Foot Walk Test,
and PA, and were used in all change analyses and effect size calculations. Because the untransformed means and standard deviations are more
meaningful, they are presented in this table. Means and standard errors are presented for those who completed the measure at both time periods
(change analyses). For the 30-s Chair Stand, 354 participants were used in change analyses and 656 were used in carry forward analyses. For the
Eight Foot Up & Go, 546 participants were used in change analyses and 834 were used in carry forward analyses. For the Chair Sit-and-Reach, 98
participants were used in change analyses and 267 were used in carry forward analyses. For the 30-Foot Walk, 485 participants were used in
change analyses and 865 were used in carry forward analyses. For physical activity, 263 participants were used in change analyses and 376 were
used in carry forward analyses
Table 2 Baseline and post-program impairments (%) in physical functioning impairment status
Baseline % Post-program % Fstatistic, pvalue
30-sec Chair Stands
Impaired, % 60.86 41.38 103.78, <0.0001
Not Impaired, % 39.14 58.65
Eight Foot Up & Go
Impaired, % 50.16 39.56 71.75, <0.0001
Not Impaired, % 49.84 60.44
Chair Sit-and-Reach
Impaired, % 42.64 28.97 10.19, 0.0019
Not Impaired, % 57.36 71.06
Percentages are adjusted for race/ethnicity (white vs. non-white), age, BMI, and gender. Because there are not established norms for the 30-Foot
Walk Test, analyses were not preformed on this physical functioning measure
Percentages are presented for those who completed the measure at both time periods (change analyses). For the 30-s Chair Stand, 354 participants
were used in change analyses and 656 were used in carry forward analyses. For the eight Foot Up & Go, 447 participants were used in change
analyses and 789 were used in carry forward analyses. For the Chair Sit-and-Reach, 98 participants were used in change analyses and 267 were
used in carry forward analyses
204 Int.J. Behav. Med. (2011) 18:199–208
Table 3 Baseline and post-program means (SE) in physical functioning, by baseline variables
Baseline Post-Program Fstatistic, pvalue Effect size (d)
n, Mean (SE) n, Mean (SE)
30-sec Chair Stands, #
Time× race/ethnicity
White 11.0 (0.20) 12.3 (0.24) 0.03, 0.8668 0.37
Non-white 10.5 (0.37) 11.8 (0.42) 0.37
Time× BMI
Normal 11.6 (0.33) 13.3 (0.40) 0.76, 0.4702 0.49
Overweight 11.4 (0.23) 12.6 (0.28) 0.36
Obese 10.8 (0.20) 12.3 (0.23) 0.41
Time× baseline
Impairment status
Impaired 8.8 (0.19) 10.9 (0.23) 18.94, <0.0001 0.65
Not impaired 13.8 (0.22) 14.6 (0.25) 0.37
Eight Foot Up & Go, seconds
Time× race/ethnicity
White 6.7 (0.11) 6.3 (0.11) 0.00, 0.9607 −0.23
Non-white 6.9 (0.20) 6.5 (0.20) −0.25
Time× BMI
Normal 5.9 (0.23) 5.6 (0.14) 0.23, 0.7959 −0.21
Overweight 6.5 (0.17) 6.1 (0.17) −0.20
Obese 7.3 (0.14) 6.8 (0.14) −0.24
Time× baseline
Impairment status
Impaired 8.3 (0.11) 7.5 (0.12) 60.83, <0.0001 −0.42
Not impaired 5.8 (0.11) 5.7 (0.11) −0.09
Chair Sit-and-Reach, inches
Time× race/ethnicity
White −1.9 (0.53) −0.6 (0.54) 1.22, 0.2710 0.35
Non-white −0.9 (0.99) −0.8 (0.99) 0.06
Time× BMI
Normal −2. 7 (1.54) 1.5 (1.54) 1.85, 0.1610 0.93
Overweight −1.4 (0.89) −0.5 (0.90) 0.34
Obese −1.1 (0.78) −0.0 (0.79) 0.29
Time× baseline
Impairment status
Impaired −1.9 (0.73) −0.6 (0.75) 0.00, 0.9532 0.51
Not impaired −0.6 (0.91) 0.7 (0.91) 0.64
30-Foot Walk Test, seconds
Time× race/ethnicity
White 6.2 (0.08) 5.9 (0.08) 0.39, 0.5329 −0.16
Non-white 6.0 (0.16) 5.8 (0.16) −0.14
Time× BMI
Normal 5.3 (0.16) 5.2 (0.16) 0.15, 0.8650 −0.16
Overweight 5.7 (0.11) 5.5 (0.11) −0.17
Obese 6.0 (0.10) 5.7 (0.10) −0.15
Means, standard errors, and repeated measures analyses examining change over time (time × baseline variable) are adjusted for race/ethnicity
(White vs. Non-white), age, BMI, and gender. Square root transformations were conducted for Eight Foot Up & Go and 30-Foot Walk Test, and
were used in all change analyses and effect size calculations. Because the untransformed means and standard deviations are more meaningful, they
are presented in Table 4. Because there are not established norms for the 30-Foot Walk Test, the time x baseline impairment status analyses were
not performed on this physical functioning measure. Effect sizes (d) are computed using adjusted baseline and post-program means and baseline
unadjusted standard deviations. For the Eight Foot Up & Go and 30-Foot Walk Test, a negative effect size indicates a more favorable change
Int.J. Behav. Med. (2011) 18:199–208 205
LIFE-P study [3], the EnhanceFitness program [15], and the
Fitness Arthritis and Seniors Trial (FAST) [8], which found
improvements in physical functioning across all race/ethnic
groups. We found only one community-based study that
examined intervention effects across BMI categories, and
similar to our findings, the FAST intervention found improve-
ments in physical functioning across BMI categories [8].
Although all participants showed significant improve-
ments in the 30-s Chair Stand Test and the Eight Foot Up-
and-Go Test, those who were impaired at baseline improved
significantly more than those not impaired. Those impaired
likely had more room for improvement relative to those
who were not (i.e., ceiling effect), resulting in larger effect
sizes. Our results are similar to those of the LIFE-P study
which found significant improvements in physical func-
tioning regardless of participant’s baseline physical perfor-
mance scores [3]. Similarly in the EnhanceFitness program,
Belza et al. [15] found significant improvements at 4 and
8 months in the 30-s Chair Stand and Arm Curl Tests for
participants who were both below or within Rikli and
Jones’age and gender normative data [28]. Although there
were significant improvements in the Eight Foot Up-and-
Go Test at both time points for those below normal limits at
baseline, those who were within this threshold significantly
worsened their score at 4 months and had no change at
8 months [15].
We found significant dose response relationships for the
Eight Foot Up-and-Go Test and the 30-s Chair Test
(although not after controlling for covariates), where
increases in physical activity were associated with signif-
icant improvements in physical functioning. The lack of
significant findings for the Sit-and-Reach test may have
been due to the much smaller sample size (n=41).
Although the sample size for the 30-Foot Walk Test was
larger, this test had a smaller effect size (in change
analyses), which could also speak to reduced power to
detect a small change over time. Furthermore, as mentioned
above, the primary target of ALED was aerobic activity.
Strength, flexibility, and balance activities may be more
important for changing particular functional tests (e.g., sit
and reach).
The appropriateness of ALED for those who are already
experiencing declines in physical functioning, and likely
have the most to gain from such physical activity-based
programs, is especially encouraging. Low levels of physical
functioning have been associated with subsequent disabil-
ity, mortality, mobility limitations, falls, hospitalization,
requirement of a caregiver, and nursing home admissions
[37–40]. Our findings have clinical significance, as
community-based prevention programs that focus on
increasing physical activity (e.g., ALED), may be able to
reverse physical functional impairments, and reduce the risk
for these adverse events associated with low levels of
physical functioning. Furthermore, given the potential large
reach, ALED can result in significant improvements in an
important public health problem.
This study had a number of strengths including the use
of objective measures to assess multiple components of
physical functioning and the large sample size. Very few
studies have been able to examine intervention effects
according to participant characteristics with such high
power. The findings from this study corroborate the overall
positive results of the AFL initiative [19].
We also recognize study limitations. First, and perhaps
the biggest limitation to our study, is the lack of a control
group, which can threaten internal validity. While this
limitation is important, we believe that our focus on
external validity ads to the overall physical activity and
health science base. The goal of AFL was not to test the
efficacy of the ALED program, but instead to impact
communities by translating the program broadly. Second is
the difference among those who did and did not complete
posttest assessments. However, results from our carry
forward analyses found that even if participants who had
no post-program measurement showed no change at post-
test, significantly meaningful improvements would still
exist. Third, over half of participants had at least some
college education. These people may be more likely to
succeed in a self-directed intervention that involves
attending group-based classes and completing worksheets,
limiting generalizability. However, earlier reports from AFL
show that changes in physical activity were seen across
sites, with some sites recruiting more disadvantaged
participants [41]. Finally, only one of the 12 AFL sites
administered physical functioning tests. It is not certain
whether results would be the same across other study sites
or if AC would have yielded similar findings.
Conclusions
Our findings address some of the gaps in the existing
literature [18], and particularly address the need for
translational research on physical functioning and function-
al limitations in diverse samples of older adults. ALED is
an example of an evidenced-based physical activity
program that can be successfully translated into community
programs and result in significant improvements in physical
functioning, similar to those achieved in efficacy studies.
Significant improvements in all performance-based physi-
cal functioning tests were seen in participants regardless of
BMI, race/ethnicity, and baseline impairment status, which
points to the appropriateness of ALED across diverse older
adult populations. The significant improvement among
those with existing limitations is particularly meaningful,
and supports late-life physical activity as a means to reverse
206 Int.J. Behav. Med. (2011) 18:199–208
the potentially debilitating effects, both physically and
mentally, of functional impairments.
Authors Notes We do not have a financial relationship with the
organization that sponsored our research. We have full control of all
primary data and agree to allow the journal to review our data if
requested.
Acknowledgement The Active for Life (AFL) initiative was funded
by the Robert Wood Johnson Foundation. The findings and
conclusions in this report are those of the authors and do not
necessarily represent the views of the Robert Wood Johnson
Foundation or other institutions affiliated with the authors.
We gratefully acknowledge the many participants who took part in
the Active for Life program and evaluation at the Council on Aging of
Southwestern Ohio. We also acknowledge the involvement and
significant contribution of staff from Council on Aging of Southwestern
Ohio, Hamilton County Public Health, Human Kinetics, Inc, Texas
A&M Health Science Center, and the University of South Carolina. We
thank the National Advisory Committee for its valuable contributions to
Active for Life. Finally, we thank Dr. Jessie Jones for her training and
consultation in the functional fitness tests.
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