347

Journal of Aging and Physical Activity, 2011, 19, 347-372© 2011 Human Kinetics, Inc.

Hauer and Schwenk are with the Bethanien-Krankenhaus-Geriatric Center, University of Heidelberg, Heidelberg, Germany. Lord is with the Prince of Wales Medical Research Institute, University of New South Wales, Sydney, Australia. Lindemann is with the Dept. of Clinical Gerontology, Robert Bosch Krankenhaus, Stuttgart, Germany. Lamb is with the Warwick Clinical Trials Unit Health Sciences Research Institute, University of Warwick, Warwick, UK. Aminian is with the Laboratory for Movement Analysis and Measurement, Lausanne Federal Poytechnical School, Lausanne, Switzerland.

Assessment of Physical Activity in Older People With and Without

Cognitive Impairment

Klaus Hauer, Stephen R. Lord, Ulrich Lindemann, Sarah E. Lamb, Kamiar Aminian, and Michael Schwenk

The purpose of this study was to validate a new interview-administered physical activity questionnaire (Assessment of Physical Activity in Frail Older People; APAFOP) in older people with and without cognitive impairment. The authors assessed feasibility, validity, and test–retest reliability in 168 people (n = 78 with, n = 88 without cognitive impairment). Concurrent validity was assessed against an inertia-based motion sensor and an established questionnaire. Sensitivity to change was tested in an ongoing study in patients with mild to moderate dementia (n = 81). Assessment of physical activity by the APAFOP and the motion sensor correlated well in the total sample (TS; p = .705), as well as in the subsamples with cognitive impairment (CI; p = .585) and without CI (p = .787). Excellent feasibility with an acceptance rate of 100%, test–retest reliability (intraclass correlation coefficients ranging from .973 (TS) to .975 (CI) to .966 (no CI), and sensitivity to change (effect sizes: 0.35–1.47) were found in both subsamples.

Keywords: activity questionnaire, dementia, validity, reliability, responsiveness, aged

A recent systematic review of questionnaires to measure physical activity in older people (Jorstad-Stein et al., 2005) concluded that although some measures had specific strengths, none were satisfactory for use in older frail or impaired people. Major limitations of these questionnaires derive from the fact that only a few have been developed specifically for older adults. Even those that were were developed for and validated in relatively “young older” people—those age 60–70 years (Stewart et al., 2001; Voorrips, Ravelli, Dongelmans, Deurenberg, & van Staveren, 1991). None were specifically developed for and validated in the “old old” or people with cognitive impairment.

348 Hauer et al.

The assessment of physical activity in very old people has specific challenges with regard to the accurate measurement of activity patterns. In contrast to sports activities in younger people, such activities are often characterized by short activi-ties of daily living (ADLs) or nonexercise activity thermogenesis activities, which are not easily remembered and therefore often not documented in assessment of physical activity. However, such low levels of physical activity represent the most prevalent form of activity even in the general population (Shephard, 2003; Wash-burn, Heath, & Jackson, 2000) and make a significant contribution to total energy expenditure (Blair, Kohl, & Barlow, 1993; Masse et al., 1998). Nonexercise activ-ity thermogenesis activities determine total caloric expenditure substantially and exceed the impact of sports activities in sedentary people (Levine et al., 2005). In frail older people or very sedentary people, health benefits may result from very low levels of activity that are unlikely to induce breathlessness, sweating, or increase aerobic fitness (Blair, Cheng, & Holder, 2001; Wannamethee & Shaper, 2001). It seems that documentation of multiple sporadic activities that are typical of ADLs is especially relevant in frail older people (Hardman, 2001).

A major challenge regarding the oldest old is the documentation of such low-level and fragmented physical activity. Many questionnaires suffer from floor effects (Tudor-Locke & Myers, 2001), and even well-established questionnaires do not measure activities less intense than brisk walking or activities with a duration less than 10 min (Blair et al., 1985), yet these are the typical activity patterns in old age.

Accuracy of physical activity documentation depends on recall of activities, and not every type of activity is recalled with the same accuracy. Previous studies have reported better accuracy in the recall of high-intensity exercise than more common, lower intensity activities (Dipietro, Caspersen, Ostfeld, & Nadel, 1993; Baranowski, 1988). Structured exercise activities are usually performed in a stable, scheduled time frame and are therefore easy to recall (Caspersen, 1989). In contrast, brief episodes or low-intensity activity as in ADLs are harder to remember. Other factors influencing recall and accuracy of physical activity include assessment factors such as form of administration, duration of assessment period, relevant and meaningful questionnaire items, and interview structure and strategies (Baranowski, 1988; Blair, Dowda, & Pate, 1991; Durante & Ainsworth, 1996; Shephard, 2003; Washburn, Smith, Jettre, & Janney, 1993).

Patients with cognitive impairment show illness-related symptoms such as memory impairment, loss of orientation in time and locus, impairment in semantic performance, decreased ability for mathematical calculation, and impaired self-perception (American Psychiatric Association, 1994). Such deficits may also occur in the course of age-related decline and substantially restrict the accuracy of physical activity reports, resulting in the exclusion of the old or cognitively impaired people from most previous studies.

To our knowledge no specific questionnaire has been developed for frail, impaired older people that addresses these limitations in a comprehensive approach. We therefore developed an interview-administered physical activity questionnaire (Assessment of Physical Activity in Frail, Older People [APAFOP]) specifically designed for frail older people with and without mild to moderate cognitive impair-ment. In this article we present data on its concurrent validity, test–retest reliability, feasibility, and sensitivity to change.

Physical Activity Questionnaire in the Elderly    349

Method

Participants

Participants were recruited from a geriatric rehabilitation ward and a community-dwelling population after screening for the following inclusion criteria: age >65 years, no severe psychological or somatic disease, ability to walk 10 m without using a walking aid, and provision of written, informed consent. In people with cognitive impairment with a legal representative, an additional written, informed consent was obtained. Participants with scores on the Mini Mental State Exami-nation (MMSE; Folstein, Folstein, & McHugh, 1975) below 24 were assigned to the cognitively impaired group, and those with scores of 24–30 to the cognitively intact group. The study was performed according to the Helsinki declaration, and approval by the ethics committee of the local university was obtained. Sensitivity to change of the questionnaire was determined in an ongoing study in patients with mild to moderate dementia using inclusion criteria similar to those in the original sample just described.

Descriptive Measures

Age, gender, education (years of educational and professional training), a single-item question on fear of falling (Maki, Holiday, & Topper, 1991), the Barthel Index on ADLs (Mahoney & Barthel, 1965), five chair stands (Guralnik et al., 1996), the SF-12 (Gandek et al., 1998), the MMSE, and number of falls in the previous year were documented by standardized patient interview or testing.

Development of the APAFOP

The questionnaire was developed in a European research network (Prevention of Falls Network Europe; ProFaNE; http://www.profane.eu.org). In a systematic review of existing questionnaires to assess physical activity used in fall-prevention trials, no questionnaires were identified that met the criteria for adequately documenting the types of physical activity typical for frail older people (Jorstad-Stein et al., 2005). As a first step, the then unpublished questionnaire by Delbaere, Hauer, and Lord (the Incidental and Planned Activity Questionnaire; 2009) was used as an initial methodological approach to cover the main physical activity domains relevant to older people. This questionnaire was substantially modified to meet the needs of the target group. In contrast to previous questionnaires that have used an extended list of single activities, the newly developed APAFOP focuses on items such as walking (including walking periods for less than 3 min), standing and time on feet indoors and outdoors (including mixed activities such as standing or walking periods of less than 3 min), sitting, and lying, which have different intensity ratings and better represent typical forms of activity in old age. The focus on such ADL-related activities prevents floor effects in the otherwise sedentary target group. To prevent ceiling effects in high-functioning people and allow for documentation of physical training in intervention studies, sports activities were also included. The questionnaire items and ratings are provided in Appendix A.

350 Hauer et al.

Assessing Total Activity and Energy ExpenditureTo capture total activity we used an established calculation method for physical activity (Schuler, Richardson, Ochoa, & Wang, 2001): multiplication of MET levels by the duration of an activity per time unit (24 hr). As an option for energy estimation not used in this study, MET per time equivalents allows for an approximation of total individual energy expenditure when individual body weight is included (kcal/day).

Intensity Rating

We used adjusted intensity codes as suggested by Ainsworth et al. (2000) and modi-fied by Stewart et al. (2001) and adjusted MET values for our target population. Readjustment was necessary because the study participants were almost a decade older than the original target population and included frail people with multiple morbidities following the same strategy for modification as the previously men-tioned expert group. A comprehensive list of activities and related METs used in this study, including MET values by Ainsworth et al. and Stewart et al., on which our modification of MET values is based, is presented for comparison in the inter-viewer’s manual (see http://www.profane.eu.org/).

Methods to Facilitate Accurate Reporting and Diminish Recall Failure

Self-administered questionnaires and long retrospective assessment periods increase recall problems and decrease the accuracy of reports. We therefore developed a highly structured interview-based questionnaire to support recall and restricted the assessment period to 24 hr.

Theoretically based approaches to foster memory have been suggested in differ-ent research areas (Baranowski, 1988; Durante & Ainsworth, 1996), but divergent concepts have so far not been integrated into one comprehensive method to assess physical activity. In the development of the APAFOP we applied a number of strategies to foster recall aimed specifically at our target population with memory impairments. Methods used in this study included comprehensive verbal informa-tion and feedback from participants before and in the course of the assessment, to eliminate miscomprehension or ambiguities that are substantial sources of errors in the question-answering process (Durante & Ainsworth, 1996); reassurance and generation of an informal conversational approach to prevent fear of failure in comprehension and recall; use of specific time frames as “anchors” to segment the recall period to clue and structure memory (Baranowski, 1988; Baranowski, Sworkin, & Cieslik, 1984); addressing typical or habitual activities to clue recall and improve the completeness of reports (Baranowski, 1988); and rehearsal of activities reported by summarizing reported activities at the end of the interview (Souchay, Moulin, Isinarini, & Conway, 2008).

Documentation, Interview Process, and Physical Activity Measurements

Specific activity, duration, and intensity were documented using the assessment form (see Appendix B). Examples of MET-intensity scores for different forms of

Physical Activity Questionnaire in the Elderly    351

activities are listed to support intensity rating and allow comparison with compa-rable ratings (see Appendix B). The interview process and the use of assessment forms have been summarized in a comprehensive interviewer’s manual that will be published at an open-access Web site (http://www.profane.eu.org/) to enable training and comprehensive instruction for users.

Patients were interviewed at their homes without participation of proxies or caregivers, and the physical activity assessment was performed in both the impaired and nonimpaired groups in a standardized manner. Descriptive data were docu-mented for most of the participants (n = 123) during previous hospital stays. For those participants who had been recruited in the community, descriptive data were obtained during their interview at home. Interviewers were trained intensively with the test manual and underwent repeated, supervised test runs to be able to perform the standardized interview assessments. Measurements that covered a 24 hr-period were initiated between 8 and 10 a.m. and continued throughout the day and night on random days of the week except for Sundays. Measurements with wear times of less than 23 hr were excluded from analysis.

Assessment of Measurement Properties: Acceptability and Feasibility

To address issues of acceptability and feasibility we examined response rates for completion of the interview, missing data, and completion time for documentation.

Concurrent Validity

We used two independent measures of direct validation strategies: an objective, technologically advanced motion-capture system (Physilog) and the established Physical Activity Questionnaire for the Elderly (PAQE; Voorrips et al., 1991).

Objective Measurement Using the Physilog System. The Physilog system (BioAGM, CH) is a small (95 × 60 × 22 mm), light (122-g), long-term recording system containing inertial sensors (two accelerometers and one gyroscope) with software developed to identify postural positions and movements such as walking, standing, sitting, or lying every second during a measuring period of up to 48 hr. The analysis algorithm is described elsewhere in detail and has been validated in different groups of subjects including elderly adults. It has proven to be sensitive (87–99%) and specific (87–99.7%) for postural positions and detection of walking in different samples of older adults and patient groups (Najafi et al., 2003; Paraschiv-Ionescu, Buchser, Rutschmann, Najafi, & Aminian, 2004) and Parkinson’s patients (Salarian, Russmann, Vingerhoets, Burkhard, & Aminian, 2007). The technical features of the Physilog allowed a direct comparison of patient reports by the APAFOP for single items, as well as total scores (e.g., single activities such as walking could be directly compared with the APAFOP item “walking”). To evaluate the overall daily activity as measured by the Physilog, we developed an activity score based on the Physilog activity assessment. Activities such as lying or sitting were weighed by a factor of 1, standing by a factor of 1.5, and walking by a factor of 2 as an approach to adjust for typical intensities in this old-age cohort and to allow comparison with the intensity-weighted total APAFOP score.

352 Hauer et al.

PAQE. The PAQE has good construct validity and retest reliability (Voorrips et al., 1991) and has been rated highly in a previous systematic review (Jorstad-Stein et al., 2005). Although it is one of the few questionnaires especially developed for older people and shares some common features with the APAFOP (application as interview and inclusion of ADL activities), the PAQE has some substantial differences from the APAFOP. It was developed for and validated in the “young old.” ADLs and household activities are solely assessed as the frequency of different activities in a predefined scoring system not including duration and intensity, it emphasizes intensity in non-ADL activities, it has no specific interview techniques to prevent recall problems, and the assessment period is 1 year. To better compare results of the two questionnaires and adjust for memory limitations of the study group we restricted the assessment period of the PAQE to 1 week. The PAQE questionnaire was administered within 3 days of Physilog and APAFOP assessments to ensure that a comparable time period was covered by the three measurements.

Test–Retest Reliability

Test–retest reliability was assessed in 30 people recruited with subsamples of 15 people for each group according to cognitive status. The questionnaire was admin-istered twice with an interval of 24 hr between by the same interviewer to exclude interobserver variability.

Sensitivity to Change

For obtaining sensitivity-to-change data we used a subsample of 81 people with mild to moderate dementia from a large ongoing randomized, controlled interven-tion trial. The intervention group performed high-intensity, progressive strength (70–80% of maximal individual performance) and progressive functional training for 4 hr/week. The control group performed a low-intensity stretching/ball-game exercise program while seated for 2 hr/week. Both sessions were group-based, supervised by an experienced trainer, and strictly standardized with respect to duration and intensity. The total activity (including habitual and training activity) was documented by the questionnaire (APAFOP) and the objective measurement (Physilog system) at baseline before intervention and at the end of the intervention period including a day of training. Interobserver variability was excluded because all interviews were performed by the same interviewer.

Analytic Strategy

Group comparisons between subgroups for descriptive variables were made by t test for continuous or chi-square test for dichotomous variables as appropriate. Test-retest-reliability analysis was evaluated using intraclass correlations (ICCs) using a one-way random-effect model (single measure) or, alternatively, a two-way mixed-effects model (single measure), as indicated in tables. For correlations, Spearman’s rank correlation and Pearson’s correlation coefficient were used as appropriate. Correlations were considered low (r < .2), moderate (r = .2–.5), or high (r > .5) according to the recommendations of Cohen (1988).

Physical Activity Questionnaire in the Elderly    353

In addition, a Bland–Altman plot for visualization of study results was com-posed (Bland & Altman, 1986). Effect sizes for change within groups were cal-culated as mean changes divided by pooled standard deviation at baseline (Kazis, Anderson, & Meenan, 1989). Effect sizes represent established methods for report-ing the magnitude of change. They are expressed in units of variability without unit of measurement (Cohen, 1988, 1992). Effect sizes of .20 are considered small, .50 medium, and above .80 large (Cohen, 1992; Katz, Larson, Phillips, Fossel, & Liang, 1992; Kazis et al., 1989). We tested group differences in correlation coefficients by means of the standard procedure of applying Fisher’s z transformation and testing the critical ratio of the difference of the z scores as normally distributed (Altman & Gardner, 2000; Howell, 2007). Statistical analysis was performed with SPSS for Windows, Version 16.0.

ResultsThe total sample included 168 people living at home (n = 152, 90%) and in seniors’ homes (n = 16, 10%) comprising old and functionally limited people, with more than half of the participants reporting one or more falls during the previous 12 months. Data for the settings (community or institutionalized) were pooled and then stratified according to cognitive impairment to yield three samples for analysis: the whole sample (unstratified), a sample comprising people with an MMSE <23 (20.2 ± 2.5), and a sample comprising people with an MMSE ≥24 (26.1 ± 1.9). The subgroups did not differ with respect to motor performance, history of falls, depressive symptoms, or gender. The cognitively impaired group was on average 2.5 years older (Table 1).

Table 1 Sample Characteristics

VariableTotal group,

N = 166

Cognitively impaired,

n = 78

Cognitively intact, n = 88

Differences between

subgroupsAge, M (SD) 81.92 (6,80) 83.26 (6.05) 80,74 (7.22) p = .017Men, n (%) 39 (23.5) 21 (26.9) 18 (20.5) p = .327MMSE score, M (SD) 23.29 (3.64) 20.24 (2.49) 26.06 (1.87) p < .001Five-chair-rise, s, M (SD) 18.28 (8.98) 18.30 (8.73) 18.26 (9.26) p = .979Depression (SF12 Item 6/7), n (%) 58 (34.94) 32 (41.03) 26 (29.55) p = .132Fear of falling, n (%) 30 (18.1) 13 (16.7) 17 (19.3) p = .635One or more falls during pre-vious 12 months, n (%) 95 (57.2) 47 (60.3) 48 (54.5) p = .499

Note. MMSE = Mini Mental State Examination; SF = short form. Comparisons were made by t tests for continuous or chi-square test for dichotomous variables. Answer categories of fear of falling (no vs. some to very much) and SF12 Item 6/7 (depression: no vs. mostly to always) have been dichotomized.

354 Hauer et al.

Feasibility and Acceptability

We excluded 4 of 82 people (5%) with cognitive impairment because in these people recollection of physical activity events was not possible because of advanced memory impairment, disorientation on time and locus, or confabulation. No participant objected to the assessment procedure, and data documentation was comprehensive, with no missing responses for any questionnaire item in either subgroup. Physilog measurements were refused because of unwillingness to wear the device in at least one out of a series of four measurements in 19% of the people assessed. Three Physilog measurements could not be analyzed because of technical problems. Interviewer reports in a subsample of interviews indicated a mean time of 24 ± 5 min to complete the interview.

Association of Activity Scores by APAFOP With Objective Measurement (Physilog)

The results of the APAFOP correlated well with the results of the objective Physilog measurement. Associations for the total activity scores, time on feet, and sum-marized scores for inactivity (including sitting and lying) and activity (including walking, standing, and, for the APAFOP, sports activities) were more pronounced than with other activities. However, all except one correlation (sitting for the cog-nitively impaired: ρ = .172) showed significant associations (range ρ = .230–.787). Results for people without cognitive impairment showed higher associations for most activity-related parameters (including total score activity, walking, total activ-ity) but not for subscores associated with inactivity (including sitting, lying, total inactivity; see Table 2). The scores are based on duration and intensity of activities. To separately document the association of duration of activities, including stand-ing, time on feet, and walking, a Bland–Altman plot is provided in Figure 1. The mean association was –.306, indicating a moderate influence of activity status (low vs. high) on association between measures. Activity durations as measured by the Physilog and APAFOP correlated highly with each other (ρ = .691).

Association Between the APAFOP, PAQE, and Physilog

In a subsample of 108 participants including all patients of the intervention sample for which all measurements were available (cognitively impaired, n = 65; cogni-tively intact, n = 43), the APAFOP, Physilog, and PAQE results were compared. The subsample of 108 people did not differ from the total sample (N = 168). The APAFOP showed moderate to good association with the PAQE. Compared with the APAFOP, the PAQE had a weaker association with the objective measurement (Physilog), especially in the impaired group. The APAFOP showed excellent correlation to the Physilog in all study groups. In all correlations performed, the cognitively intact people tended to higher associations between assessment tools (see Table 3).

Test–Retest Reliability of the APAFOP

In a subsample of 30 participants (15 cognitively intact and 15 cognitively impaired) consecutively recruited in the intervention sample the APAFOP showed excellent

    355

Tab

le 2

C

orr

elat

ion

s B

etw

een

th

e A

sses

smen

t o

f P

hysi

cal A

ctiv

ity

in F

rail

Old

er P

eop

le (

APA

FO

P)

and

Phy

silo

g S

core

s

Tota

l Gro

up,

N =

166

Cog

nitiv

ely

Impa

ired,

n

= 7

8C

ogni

tivel

y In

tact

, n

= 8

8

Posi

tion/

Act

ivity

Cor

rela

tion

coef

ficie

nt95

% C

IC

orre

latio

n co

effic

ient

95%

CI

Cor

rela

tion

coef

ficie

nt95

% C

ID

iffer

ence

s be

twee

n su

bgro

ups

Tota

l act

ivity

ρ

= .7

05

(p <

.001

).6

18–.

773

ρ =

.585

(p

< .0

01)

.413

–.71

2ρ

= .7

87

(p <

.001

).6

90–.

854

p =

.013

Wal

king

ρ

= .5

11

(p <

.001

).3

88–.

614

ρ =

.351

(p

= .0

02)

.137

–.53

0ρ

= .6

00

(p <

.001

).4

44–.

718

p =

.039

Tim

e on

fee

t ρ

= .6

23

(p <

.001

).5

19–.

707

ρ =

. 62

3 (p

< .0

01)

.462

–.74

1ρ

= .6

24

(p <

.001

).4

74–.

736

p =

.991

Sitti

ng

ρ =

.230

(p

= .0

03)

.080

–.36

9ρ

= .1

72

(p =

.132

)–.

053

to

.379

ρ =

.271

(p

= .0

11)

.064

–.45

3p

= .5

10

Lyin

g ρ

= .4

22

(p <

.001

)

.287

–.53

9ρ

= .3

11

(p =

.006

)

.093

–.48

0ρ

= .4

69

(p <

.001

)

.285

–.61

6p

= .2

37

Act

ivity

ρ

= .7

15

(p <

.001

).6

30–.

782

ρ =

.615

(p

< .0

01)

.452

–.73

5ρ

= .

784

(p <

.001

).6

85–.

852

p =

.032

Inac

tivity

ρ

= .6

88

(p <

.001

).5

97–.

760

ρ =

.600

(p

< .0

01)

.433

–.72

4ρ

= .

753

(p <

.001

).6

43–.

830

p =

.070

Not

e. S

pear

man

’s r

ho (ρ)

is g

iven

for

cor

rela

tion

betw

een

vari

able

s. A

ctiv

ity s

umm

ariz

es w

alki

ng a

nd ti

me

on f

eet (

in P

hysi

log

mea

sure

men

ts/a

ll sp

ecifi

ed a

ctiv

ities

in A

PAFO

P);

Inac

tivity

sum

mar

izes

sitt

ing

and

lyin

g. C

orre

latio

n co

effic

ient

s w

ere

test

ed f

or s

tatis

tical

dif

fere

nces

bet

wee

n su

bgro

ups.

356 Hauer et al.

Figure 1 — Bland–Altman plot for comparison of Physilog and APAFOP measurements (Physilog + APAFOP/2 measurements for x axis and difference of scores (Physilog – APAFOP) for y axis), including mean deviation, mean, and limits of agreement. Regres-sion lines are given for subsamples according to cognitive status. Open circle = cognitively impaired (n = 78); closed circle = cognitively intact (n = 88); dashed line = trend line cognitively impaired; solid line = trend line cognitively intact.

reproducibility for the total sample (intraclass correlation [ICC] .973), as well as for the subsamples of cognitively impaired (ICC .975) and cognitively intact people (ICC .966) for the total score. Detailed analysis also showed good to excellent test–retest reliability for single activities for the total sample (ICC range .907–.973), as well as for the subgroups of cognitively impaired (ICC range .905–.998) and cognitively intact people (ICC range .800–.991). Group means of activities assessed at test and retest showed high agreement in all groups. Test–retest reliability tended to be higher in the subsample of cognitively impaired people. The activity level of the cognitively intact people was higher than that of the impaired people (Table 4).

Sensitivity to Change

The APAFOP adequately reproduced the changes in physical activity during the 3-month intervention in both study groups. High effect sizes were evident for the high-intensity training group when training periods were compared with the habitual sedentary lifestyle, indicating the substantial increase in physical activity induced by training. Moderate effect sizes were documented for the less intense training. The technical measurement was less responsive (Table 5). Patients with cognitive impairment showed higher responsiveness in questionnaire measurements (Table 6).

    357

Tab

le 3

C

orr

elat

ion

s B

etw

een

Phy

silo

g, A

PAF

OP,

an

d P

AQ

E

Tota

l Gro

up (N

= 1

08)

Cog

nitiv

ely

Impa

ired

(n =

65)

Cog

nitiv

ely

Inta

ct (n

= 4

3)

Ass

essm

ent

Cor

rela

tion

coef

ficie

nt95

% C

IC

orre

latio

n co

effic

ient

95%

CI

Cor

rela

tion

coef

ficie

nt95

% C

Ip

Phys

ilog–

PAQ

Er

= .4

62 (

p <

.001

).2

98–.

598

r =

.307

(p

= .0

13)

.065

–.51

0r

= .6

44 (

p <

.001

).4

20–.

789

.025

Phys

ilog–

APA

FOP

r =

.650

(p

< .0

01)

.580

–.78

0r

= .5

44 (

p <

.001

).3

58–.

700

r =

.755

(p

< .0

01)

.582

–.85

8.0

62

PAQ

E–A

PAFO

Pr

= .6

95 (

p <

.001

).5

29–.

749

r =

.601

(p

< .0

01)

.415

–.73

5r

= .7

94 (

p <

.001

).6

42–.

881

.053

Not

e. A

PAFO

P =

Ass

essm

ent

of P

hysi

cal A

ctiv

ity i

n Fr

ail

Old

er P

eopl

e; P

AQ

E =

Phy

sica

l Act

ivity

Que

stio

nnai

re f

or t

he E

lder

ly. P

rese

nted

are

Pea

rson

’s c

orre

latio

n co

effic

ient

(r

) an

d p

valu

es f

or s

igni

fican

ce f

or c

ompa

riso

n of

tota

l sco

res

of a

sses

smen

t ins

trum

ents

. p V

alue

s ar

e al

so g

iven

for

dif

fere

nces

of

corr

elat

ions

bet

wee

n su

bgro

ups

(rig

ht c

olum

n).

358

Table 4 Test–Retest Reliability for Single Activities

Total Sample (N = 30)

Cognitively Impaired (n = 15)

Cognitively Intact (n = 15)

Item M (SD) ICC M (SD) ICC M (SD) ICC

Total activity, S 28.57 (2.93 .973 27.49 (2.34) .975 29.66 (3.11) .966

28.49 (2.87) .972 27.48 (2.51) .974 29.49 (2.93) .965

Walking, S 1.44 (1.44) .944 1.27 (1.30) .966 1.62 (1.60) .932

1.38 (1.34) .944 1.18 (1.21) .966 1.59 (1.47) .927

Walking, RT 0.62 (0.56) .919 0.59 (0.59) .958 0.64 (0.54) .878

0.60 (0.52) .917 0.55 (0.54) .958 0.64 (0.50) .870

Time on feet OD, S 1.62 (2.47) .946 0.89 (1.58) .973 2.36 (3.00) .933

1.69 (2.32) .945 0.91 (1.58) .971 2.47 (2.71) .929

Time on feet OD, RT 0.69 (0.94) .933 0.37 (0.58) .949 1.00 (1.13) .920

0.73 (0.95) .932 0.39 (0.57) .945 1.08 (1.14) .917

Time on feet ID, S 6.34 (3.28) .925 4.58 (1.99) .916 8.10 (3.42) .890

6.28 (3.18) .923 4.61 (2.30) .911 7.95 (3.11) .884

Time on feet ID, RT 3.97 (1.76) .907 2.96 (1.20) .905 4.98 (1.96) .846

3.94 (1.79) .904 2.96 (1.30) .899 4.92 (1.71) .836

Sitting, S 8.56 (2.73) .844 8.55 (3.36) .950 8.58 (2.18) .651

8.55 (2.43) .839 8.77 (3.20) .898 8.33 (1.41) .657

Sitting, RT 8.56 (2.73) .910 8.55 (3.36) .950 8.58 (2.18) .800

8.55 (2.43) .907 8.77 (3.20) .949 8.33 (1.41) .796

Lying, S 9.96 (2.91) .967 11.24 (3.37) .981 8.67 (1.64) .954

9.93 (2.91) .963 11.08 (3.50) .963 8.78 (1.57) .954

Lying, RT 9.96 (2.91) .967 11.24 (3.37) .981 8.67 (1.64) .875

9.93 (2.91) .966 11.08 (3.50) .980 8.78 (1.57) .869

Sport activity, S 0.65 (1.66) .997 0.97 (2.09) .998 0.33 (1.04) .991

0.65 (1.65) .985 0.93 (2.09) .999 0.38 (1.07) .946

Sport activity, RT 0.22 (0.55) .997 0.33 (0.70) .998 0.11 (0.35) .991

0.22 (0.55) .996 0.32 (0.69) .998 0.13 (0.36) .991

Note. S = scores (Duration × Intensity); RT = real times measured (hr); OD = outdoors; ID = indoors. Presented are means for test (first line) and retest (second line) and ICCs for the total sample and subsamples according to cognitive status. ICC first line: one-way random-effects model single measure (Shrout & Fleiss, 1979, Model 1.1); ICC second line: two-way mixed-effects model single measure (Shrout & Fleiss, 1979, Model 3.1).

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Table 5 Standardized Effect Sizes for Sensitivity to Change

AssessmentTotal group

(N = 81)High-intensity

training (n = 37)Low-intensity

training (n = 44)APAFOP T2_T vs. T1 0.90 1.47 0.40

APAFOP T2_T vs. T2_N 0.86 1.47 0.35

APAFOP T2_T vs. T3 0.84 1.35 0.40

Physilog T2_T vs. T1 0.09 0.11 0.10

Physilog T2_T vs. T2_N 0.21 0.30 0.15

Physilog T2_T vs. T3 0.24 0.28 0.22

Note. APAFOP = Assessment of Physical Activity in Frail Older People; T2_T = measurement at the end of intervention (active day of training); T1 = baseline measurement before training started; T2_N = measurement at the end of intervention (habitual activity, day without training); T3 = measurement at follow-up after training had stopped. Presented are standardized effect sizes (difference between mean scores at assessments, divided by the standard deviation of baseline scores, Kazis et al., 1989) for the APAFOP and Physilog for 24-hr recordings during an intervention study for different training regimens.

Table 6 Standardized Effect Sizes for Change During Intervention

ParameterTotal group

(N = 98)MMSE scores <24

(n = 60)MMSE scores ≥24

(n = 38)

APAFOP 1.01 1.11 0.84

Physilog 0.16 0.23 0.03

Note. MMSE = Mini Mental State Examination; APAFOP = Assessment of Physical Activity in Frail Older People. Presented are standardized effect sizes for the total group (including high- and low-intensity training groups) and subgroups of participants according to cognitive impairment for comparison between sedentary baseline und active training period (training day).

DiscussionThe APAFOP is the first questionnaire to assess physical activity developed and validated for use in frail older people with and without cognitive impairment. The questionnaire is feasible, valid, reliable, and responsive and allows documentation of approximate energy expenditure (MET-related activity scoring per time unit) for a wide variety of activities ranging from ADL-related activities to sports activities.

Feasibility and Acceptability

Acceptability involves the physical and emotional burden of the respondent, and feasibility focuses on the demands on those who administer a measure (Fitzpatrick, Davey, Buxton, & Jones, 1998). As assessed in this study feasibility and accept-ability were high for the APAFOP; all the cognitively intact participants and most of the cognitively impaired could be interviewed, and physical activity could be documented adequately. Only a small number of more severely impaired people (5%) were excluded because of advanced disorientation in locus and time, severely

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impaired memory, or confabulation, indicating that such assessments are not feasible for those in advanced stages of cognitive impairment. Patients who were excluded ranged in the lower scores of the MMSE (<20), but not all the patients with lower scores had severe problems with the assessment. Insufficient discrimination of the relatively small group of these patients may relate to the limitations of the MMSE, which was developed as a screening tool for cognitive impairment, not as a detailed diagnostic instrument for performance in specific cognitive subdomains related to abilities specific for interview assessment.

Despite the exclusion of such severely impaired participants we found that the assessment of specific activity patterns in older people and most people with mild to moderate cognitive impairment was feasible. With the interview-based admin-istration method we ascertained that data documentation was comprehensive and no questionnaire items were left out as previously reported for self-administered questionnaires in old or cognitively impaired people (Hauer et al., 2010). The time to complete the interview was sufficient for a detailed questionnaire such as the APAFOP and is comparable to the data that are available for other questionnaires with completion times ranging from 15 min to 90 min (Sallis et al., 1985; Stewart et al., 2001). Willingness to participate in the technical measurement was somewhat lower than with the questionnaire assessment, although the Physilog measurement used an individually customized, easy-to-wear support system and participants had been contacted at home for installation and deinstallation of the system. Reasons for discontinuing the technical measurement were “felt uncomfortable,” “could not sleep or have a shower with device,” “forgot to put it on again,” and “forgot what the measurement was about” and were partly related to the impaired cognitive status of the participants.

Validity

We used two independent direct validation strategies: an objective, technologically advanced motion-capture system (Physilog) and the PAQE based on the participant’s physical activity ratings. Results obtained by direct measurements carry the most weight because they measure the same construct (direct validity; McDowell & Newell, 1996). Previous studies used different measurements as external standards for validation (Jorstad-Stein et al., 2005). Depending on the relationship between measurements and quality of methods used, reported correlations have been low to moderate and have partly been limited by the indirect nature of associations, for example, when fitness-related markers were related to physical activity mea-surements (Dipietro et al., 1993; Jorstad-Stein et al., 2005). Accelerometer-based motion sensors, as used in this study, provide valid data on physical activity as objective external measurements by detecting activity such as walking, sitting, standing, and lying (Aminian et al., 1999; Bonnefoy et al., 2001; Bussmann, van de Laar, Neeleman, & Stam, 1998; Grant, Dall, Mitchell, & Granat, 2008; Levine, Melanson, Westerterp, & Hill, 2001).

In the current study, results of the APAFOP correlated very well with the objective results derived from the motion sensors. As would be expected the associations tended to be higher in people without cognitive impairment, because cognitive deficits may have limited recall of activities. However, based on the type of method to support recall, such as the structured face-to-face interview,

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short assessment period, and so on, the validity of reports in people with cognitive impairment was comparable to results of other successful validation studies for questionnaires targeting unimpaired older people (Dipietro et al., 1993; Harada, Chiu, King, & Stewart, 2001; Jorstad-Stein et al., 2005; Stel et al., 2004). The total activity scores and summarized scores for inactivity (including sitting and lying) and activity (including walking, standing, and sports activities) all showed high associations to the objective measurement (Physilog), confirming the excellent recording of overall physical activity by the APAFOP. Comparison of single activi-ties (e.g., sitting) between the Physilog system and single questionnaire items was somewhat limited by technical issues. Differentiation between lying and sitting is difficult because many older people rest in armchairs while seated in an almost lying position or may lift their upper body in bed because of breathing problems when lying. A motion-capturing system such as the Physilog, based on algorithms to determine relative positions of the body, is therefore limited when defining a position. However, when both sitting and lying were combined in an inactivity score, associations between technical measurements and APAFOP results were excellent. When comparing single questionnaire items such as walking (defined as walking periods reported by participants) or time on feet (which includes a combination of walking, standing, and other leisure sports activities) with the Physilog items walk-ing or standing summarizing all walking and all standing measured objectively, it is obvious that associations will be limited. However, the correlations were good to excellent for single or combined activities and compared favorably with previous validation studies (Dipietro et al., 1993; Jorstad-Stein et al., 2005; Stel et al., 2004).

Comparison of the APAFOP and PAQE

We chose the PAQE, a questionnaire developed for and validated in older people and rated highly in a systematic review of questionnaires for use with older people (Jorstad-Stein et al., 2005) to compare with the APAFOP. The PAQE showed moderate (cognitively impaired) to good (cognitively intact) correlations with the APAFOP. Compared with objective measurements (Physilog) it showed weaker associations, especially in the cognitively impaired group (see Table 3). The modi-fication of the original PAQE with a shortened recall period of 1 week instead of 1 year as used in this study may have altered the results in favor of the PAQE, because many of the participants had not been able to give estimates of activities for a time period of 1 year as suggested for the original PAQE version. This shorter recall period also ensured that the 24-hr Physilog measurement covered a current activity level comparable to that documented by the APAFOP and Physilog. The superior results of the APAFOP may derive from the short recall period and the specific interview techniques used in the APAFOP, supporting the accuracy of reports, especially in people with cognitive impairment.

Test–Retest Reliability of the APAFOP

As reported in the systematic review, previous test–retest reliability studies on questionnaires used to measure physical activity in older people have shown dif-fering results depending on the setting and method, with only some questionnaires presenting solid evidence of retest stability (Jorstad-Stein et al., 2005). In previous

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studies test–retest reliability was measured by repeated assessment of physical activity, with time intervals ranging from 2–3 weeks (Voorrips et al., 1991) to 6–12 months (Stel et al., 2004; Stewart et al., 2001) between assessments, which reduces comparability of results. Such a methodological approach implies that the test parameter (physical activity) is stable over time. This may be problematic because methodological aspects (unreliable documentation from the method of investiga-tion vs. unreliable, modified test criteria) are mixed because physical activity may change for many reasons. High variability (Stel et al., 2004) and long time periods between assessments have been discussed as reasons for low test–retest reliability in established physical activity questionnaires, resulting in lower bound estimates of reliability (Harada et al., 2001; Stel et al., 2004; Stewart et al., 2001). In some questionnaires the risk of documenting such individual variance has been limited by asking the participant to give a mean of average activities over time ranging from 1 week (Stewart et al., 2001) to 1 year (Voorrips et al., 1991). However, such complex questions (e.g., “What was the average walking time per week last year?” “At what intensity?”) presuppose an intact memory, orientation in time and locus, ability for mathematical calculation, and intact self-perception besides advanced interviewer skills. Frail older people, especially those with cognitive impairment, may be seriously overtaxed by such an approach.

In the current study we used a different methodological approach based on the APAFOP’s short recall period of 24 hr. Participants were interviewed twice for the same recall period (24 hr) within 2 days. The recall period was thereby identical, so results were not influenced by individual variance of physical activity as in other reliability studies using longer assessment periods. Results of the current study therefore relate exclusively to physical activity reports and not to varying activity levels. In this approach the APAFOP showed excellent test–retest reliability for both study groups in total scores, as well as single activities. The trend for slightly higher test–retest reliability in the subsample of cognitively impaired people may have been the result of lower but stable activity levels that are remembered more easily than more frequent and more variable activities in the cognitively intact participants. High reliability was also achieved by the specific strategies to improve recall of individual physical activity as developed for the APAFOP, which is par-ticularly relevant for older people with cognitive impairments.

Sensitivity to Change

Sensitivity to change is a mandatory biometrical property of questionnaires to detect changes in physical activity over time or effects of interventions in random-ized controlled trials. As reported in the systematic review on questionnaires used in geriatrics research (Jorstad-Stein et al., 2005), sensitivity to change has rarely been addressed. For questionnaires that have reported responsiveness, results were derived from very different observation periods ranging from 2 weeks to 1 year, limiting direct comparisons between results. In some but not all studies present-ing responsiveness data, a standardized intervention targeted to influence the physical activity in the study group was performed during the observation period (Jorstad-Stein et al., 2005). The interventions differed from each other, further limiting comparability of the results. Effect sizes reported in these studies were small, ranging from .03 to .30, with only one questionnaire presenting detailed and moderate to good sensitivity-to-change data with effects size ranging from

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.38 to .64 (Stewart et al., 2001). Sensitivity-to-change measurements suffer from a methodological problem: Do insufficient effect sizes represent a methodological fault of the questionnaire, or do insufficient results represent insufficient change of physical activity over time? In the case of intervention studies to increase physical activity, this might relate to an insufficient effect of the study intervention. Such methodological pitfalls have also been identified in previous studies, leading to the request that “ideally the outcome measure would focus primarily on the types of physical activities that are being targeted for change in the intervention to improve sensitivity” (Stewart et al., 2001, p. 1128).

To prevent methodological inconsistency in this study we examined the effect sizes of two strictly standardized training regimens to control for a standardized change in physical activity over time. The APAFOP adequately assessed the dif-ferences between study groups and the change from primarily sedentary life style to comparatively high physical activity induced by two different training regimens during a standardized intervention. It also showed moderate to large responsiveness in both subsamples with respect to cognitive status. The slightly higher effect sizes in impaired people may be attributable to the lower overall activity at baseline and the higher increase induced by training. The good responsiveness of the APAFOP exceeded that of the objective external standard. Despite rapid technological development, even advanced motion-analytic systems are not able to detect and classify all physical activities performed by humans. Because the system used in this study (Physilog) classifies posture positions rather than their intensity, activi-ties such as bicycling or strength training while seated on training machines were classified as sitting position without considering the activity of lower limbs. As a consequence these training activities were estimated with lower energy expendi-ture. Such methodological pitfalls have been reported before in comparable stud-ies indicating specific limitations of objective measurements (Westerterp, 1999). Because the training intervention of the trial included bicycling on a stationary bike and strength training while seated, the substantial change of activity induced by this intervention was not adequately recorded by the Physilog system. However, such limitations will not be relevant in most other interventions or daily activities that are not performed while seated. In these cases intervention effects will be well assessed by the Physilog or other comparable devices documenting walking, running, and standing as physical activity categories. Although riding a bicycle or performing strength training on machines may still not be a very frequent activity for most old, frail, and multimorbid people in everyday life, results point to the limitations, as well as the potential, of both technical and interview-based assess-ment of physical activity.

Limitations

Some limitations of the APAFOP should be noted. Normative values for the meta-bolic performance of the oldest old and impaired people are lacking, so the scoring system of the APAFOP is based on an MET- or time-unit-based concept modified for use in very old people according to an established scoring system suggested by Ainsworth et al. (2000). Although an approximation of caloric expenditure is feasible for the APAFOP, we did not make use of this option because we only have exact caloric values for younger people.

364 Hauer et al.

The short assessment period of the APAFOP, which promotes better recall of activities, may not fully cover day-to-day variability in physical activity, although physical activity variance seems to decrease with age and limited functional status. For a younger population, data from pedometers suggest a minimum of 3 days of recording to counterbalance day-to-day variability in physical activity (Tudor-Locke et al., 2005). Another study with people over 60 years old (some were still employed) using pedometers and devices with one accelerometer suggested 2 days of recording (Rowe, Kemble, Robinson, & Mahar, 2007). Nonetheless, there is very limited information on the variability of physical activity patterns in older retired persons using well-validated movement sensors. When examined on a group level a low day-to-day variability could be detected in a recent study in older, community-dwelling people including high-functioning participants (Nicolai et al., 2010). To our knowledge no data on older adults with cognitive impairment and advanced frailty have been published. The current study used such a sedentary sample. A 24-hr monitoring may therefore prove to be sufficient to document habitual physical activity because of the low day-to-day variability in frail, impaired, sedentary people.

For comparative validation we used the PAQE questionnaire. To allow an assessment period comparative to the APAFOP and feasibility of the assessment in patients with dementia, we reduced the assessment period of the PAQE to 1 week. The assessment of activities during 1 week is already part of the original PAQE assessment, complemented for sport and leisure activities by year-round activity. For the modified PAQE, results of validation are therefore limited.

As with any other subjective reports by questionnaires, assessment of physi-cal activity depends on preserved cognitive performance. Supported by specific methodological approaches, the APAFOP showed good to excellent measurement qualities even in the subgroup of people with mild to moderate cognitive impair-ment. However, assessment by questionnaire may not be feasible in more severely impaired people.

Because of the rapid aging of populations worldwide, programs promoting health and related research will increasingly focus on the old and oldest-old. Physical activity has been identified as a high-impact lifestyle factor to improve health even in frail, multimorbid, and impaired people. The APAFOP closes a methodological gap and demonstrates good to excellent biometric qualities to adequately assess physical activity in frail older people with and without cognitive impairment. It may be useful in future studies to further examine cognitive and psychological processes influencing physical activity assessment to further improve the accuracy of documentation.

Acknowledgments

This research was supported in parts by the Dietmar Hopp Stiftung, the Robert Bosch Stiftung, the Landesstiftung Baden-Württemberg, and the Landesgraduiertenstiftung Baden-Württemberg. We thank Ruth Hofrichter and Laura Coll-Planas for support in data collection, Anna Tremmel and Anna Czempik for support in patient management, and Clemens Becker for support in developing the questionnaire.

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Appendix A: Questionnaire Items and Intensity Rating of the APAFOP

Specific questionnaire items have been developed and an intensity rating has been established for the APAFOP. Appendix Table 1 gives additional information and examples for the questionnaire items, and Appendix Table 2 on the intensity rating of the APAFOP compared with an established questionnaire in which the rating has been based.

Intensities of activities are rated in the APAFOP according to a MET-based scoring system. MET values of different intensity levels for examples of frequent activities are given in Appendix Table 2. MET values are derived from an estab-lished coding system by Ainsworth et al. (1993, 2000) that has been modified for use in older populations (CHAMPS; Stewart et al., 2001). We adjusted those MET values for the older and frailer target population of the APAFOP. The original MET levels suggested by Ainsworth et al. and Stewart et al. are integrated in Appendix Table 2 for comparison.

Age-adjusted MET values are given for the APAFOP and for original values given by the CHAMPS questionnaire (Stewart et al., 2001) for comparison. For categories such as lying or indoor activity, which were not presented in the CHAMPS, MET values derived from the original compendium by Ainsworth et al. (1993, 2000) were documented.

    369

Appendix Table 1 Types of Activity as Examples for Questionnaire Items

Item Related activity, clues for interrogation Inclusion of specific activities1. Walking (longer than 3 min)

Walking, hiking, walking the dog, shopping, going to doctor, walking to run errands, going to the cemetery, going to social events, walking around in the garden; Walking in the house in case of bad weather or restriction to home, walking passages or corridors in institutions (seniors’ homes).

Short walking activities mixed with other activities (indoors, e.g., walking to the toilet, walking around the kitchen) relates to Item 3; mixed outdoor activity relates to Item 2.

2. Outdoor activity

Gardening, construction, or cleaning activity around the house (e.g., sweep the yard), time spent in shops with mixed activity.

Walking to shops relates to Item 1.

3. Indoor activity

Mixed household activities (walking or standing), all activities while standing or walking, such as talking to a neighbor, standing at a window, going to the toilet, fetching something from the basement, doing the laundry, personal hygiene, care for dependent proxy.

Short walking periods relate to this item.

4. Sitting Sitting at home (while watching TV, while preparing meals, reading newspaper, knitting); sitting in a restaurant or theater, during transportation (car, bus), or outdoors (garden).

Difference between sitting and lying depends on the postural position or definition.

5. Lying Lying in bed at night, taking a nap during the day, lying on a sofa while watching TV or reading a book.

6. Sports activity

Home training (stretching exercise, home trainer, unsupervised fitness exercise). Exercise/sport clubs, training sessions in seniors’ homes.

370

Ap

pen

dix

Tab

le 2

In

ten

sity

Sco

rin

g o

n t

he

Ass

essm

ent

of

Phy

sica

l Act

ivit

y in

Fra

il O

lder

Peo

ple

(A

PAF

OP

) fo

r D

iffer

ent

Typ

es o

f Act

ivit

y

Item

/ Act

ivity

Item

-rel

ated

act

iviti

es a

ccor

ding

to d

iffer

ent i

nten

sity

leve

ls

Orig

inal

ME

Ts a

ccor

ding

to

Ain

swor

th e

t al.

(199

3, 2

000)

&

Ste

war

t et a

l. (2

001)

ME

Ts

mod

ified

fo

r APA

FOP

1. W

alki

ngH

abitu

al w

alki

ng (

doin

g er

rand

s, w

alki

ng le

isur

ely)

.2.

52

Bri

sk w

alki

ng (

wal

king

as

an e

xerc

ise)

.3.

53

Wal

king

uph

ill o

r br

iskl

y in

non

frai

l peo

ple.

64

2. O

utdo

or a

ctiv

ityN

onst

renu

ous

activ

ity: a

roun

d th

e ho

me

(e.g

., w

ater

ing

the

gard

en, s

trol

ling

in

gard

en)

or a

way

fro

m h

ome

(mix

ed a

ctiv

ity w

hile

sho

ppin

g).

2.25

2M

oder

ate

activ

ity: C

lean

ing

win

dow

s, s

wee

ping

the

yard

or

stre

et, s

hopp

ing

whi

le

carr

ying

a b

aske

t, in

crea

sed

perc

enta

ge o

f w

alki

ng d

urin

g m

ixed

act

iviti

es.

3.0

3St

renu

ous

activ

ities

: Cho

ppin

g w

ood,

law

n m

owin

g, m

ore

stre

nuou

s ga

rden

ing

activ

ities

.4.

04

3. I

ndoo

r ac

tivity

Non

stre

nuou

s ac

tiviti

es: h

ouse

hold

act

iviti

es: (

was

hing

dis

hes,

coo

king

, wat

er-

ing

flow

ers,

per

sona

l hyg

iene

, mak

ing

a te

leph

one

call

whi

le s

tand

ing,

talk

ing

to a

ne

ighb

or, d

urin

g m

ixed

act

iviti

es f

ocus

on

stan

ding

.1.

8–2.

5a1.

5M

oder

ate

activ

ities

: doi

ng th

e la

undr

y, s

tori

ng s

hopp

ing

good

s, v

acuu

min

g, m

ixed

ac

tiviti

es f

ocus

on

wal

king

.2.

0–3.

0a2

Stre

nuou

s ac

tiviti

es: c

lean

ing

floor

, clim

bing

sta

irs,

car

ryin

g he

avy

load

s, in

tens

ive

care

or

supp

ort f

or d

epen

dent

pro

xies

.3.

5–7.

5a3

4. S

ittin

gA

ctiv

ities

whi

le s

ittin

g: r

eadi

ng, w

atch

ing

TV

, mak

ing

a te

leph

one

call,

hav

ing

a co

nver

satio

n, s

ittin

g du

ring

tran

spor

t, et

c.1–

1.8a

15.

Lyi

ngA

ctiv

ities

whi

le ly

ing:

rea

ding

, wat

chin

g T

V, s

leep

ing.

0.9–

1.0a

16.

Spo

rts

activ

ityN

onst

renu

ous

activ

ity: s

tret

chin

g ex

erci

se w

hile

sea

ted

or ly

ing,

non

stre

nuou

s m

ixed

act

ivity

.2.

52

Mod

erat

e ac

tivity

: mod

erat

e en

dura

nce

hom

e tr

aini

ng, m

oder

ate

exer

cise

whi

le

stan

ding

or

wal

king

, mix

ed a

ctiv

ities

.3

3St

renu

ous

activ

ity: p

rogr

essi

ve r

esis

tanc

e tr

aini

ng; c

halle

ngin

g pr

ogre

ssiv

e fu

nc-

tiona

l tra

inin

g; f

all-

prev

entio

n ex

erci

se; m

ore

stre

nuou

s en

dura

nce

exer

cise

suc

h as

bi

cycl

ing,

sw

imm

ing,

wal

king

/jogg

ing;

oth

er c

halle

ngin

g sp

orts

exe

rcis

e.4–

54

a Fro

m th

e or

igin

al c

ompe

ndiu

m b

y A

insw

orth

et a

l. (1

993,

200

0).

    371

Appendix Figure A — Assessment form: Activities of daily living daily protocol. Note. MET = metabolic equivalent.

372 Hauer et al.

Appendix Figure B — Assessment form: Sport activity and activity type. Note. MET = metabolic equivalent.

Appendix B: APAFOP Assessment Form The documentation form allows an assessment of type of activity and intensity during the interrogation period of 24 hr for subscores and total scores.