Construct Validity of Activities of Daily Living Scale* - CHEST ...

Construct Validity of Activities of Daily
Living Scale*
A Clue To Distinguish the Disabling Effects of
COPD and Congestive Heart Failure
Raffaele Antonelli Incalzi, MD; Andrea Corsonello, MD; Claudio Pedone, MD;
Francesco Corica, MD; Pierugo Carbonin, MD; Roberto Bernabei, MD; on
Behalf of the GIFA Investigators†
Study objectives: To assess differences, if any, in the pattern of disability measured using basic
activities of daily living (BADL) and instrumental activities of daily living (IADL) in COPD and
congestive heart failure (CHF), using diabetes mellitus as a reference noncardiorespiratory
disabling condition.
Design: Multicenter survey.
Setting: General medicine or geriatric wards in tertiary hospitals throughout Italy.
Patients: Patients admitted because of CHF (n 432), COPD (n 305), and diabetes mellitus
(n 534).
Measurements and results: Construct validity of self-reported preadmission BADL-IADL was
assessed for each group by main component analysis. The three populations had a comparable
average degree of dependency in BADL-IADL. In both CHF and diabetes mellitus patients, three
components cumulatively explained most of variance in BADL-IADL: the BADL, 10 IADL, and
4 housework-related IADL. In COPD, a four-factor solution was generated, with factor 4 having
loading with IADL items assessing mobility and outdoor moving, and factor 3 with selected IADL
requiring both physical and mental capabilities such as managing money, taking medicine, and
traveling. Correlates of dependency in IADL related to factor 4 in COPD were older age,
cognitive impairment, widowhood, and comorbidity. Both factors 3 and 4 were associated with
longer stay (factor 3: 13.9 9.5 days vs 11.5 7.6 days, p < 0.05; factor 4: 14.2 8.8 days vs
11.0 5.5 days, p < 0.05) of COPD patients (mean SD).
Conclusion: COPD was associated with a distinctive pattern of disability expressed by loss of
selected BADL-IADL but not by the crude number of lost BADL-IADL.
(CHEST 2005; 127:830–838)
Key words: activities of daily living; congestive heart failure; construct validity; COPD; diabetes mellitus; disability
Abbreviations: ADL activities of daily living; AMT abbreviated mental test; BADL basic activities of daily
living; CHF congestive heart failure; GDS geriatric depression scale; GIFA Gruppo Italiano di Farmacovigilanza
nell’Anzianol; IADL instrumental activities of daily living; ICD-9 CM International Classification of Diseases,
Clinical Modification, Ninth Revision
Activities of daily living (ADL) include basic ADL
(BADL), which explore the basic capacity of
persons to care for themselves, and instrumental
ADL (IADL), which refer to higher levels of performance.
1 Both BADL and IADL should be evaluated
*From the Centro di Medicina dell’Invecchiamento (Drs. Incalzi,
Pedone, Carbonin, and Bernabei), Policlinico A. Gemelli, Università
Cattolica del Sacro Cuore, Roma, Italy; Divisione di
Medicina Geriatrica (Dr. Corsonello), Istituto Nazionale di
Ricovero e Cura per Anziani, Cosenza, Italy; and Dipartimento di
Medicina Interna (Dr. Corica), Università degli Studi di Messina,
Messina, Italy.
†The GIFA is a research group of the Italian Society of Gerontology
and Geriatrics—Fondazione Italiana per la Ricerca
sull’Invecchiamento.
to capture the full spectrum of disability. 2 Acute
disabling conditions such as stroke or hip fracture
have obvious and dramatic effects on ADL, whereas
chronic conditions that do not cause a segmental
motor deficit have a more complex and less easily
The GIFA is partially supported by a grant from the Italian
National Research Council (No. 94000402).
Manuscript received February 6, 2004; revision accepted October
26, 2004.
Reproduction of this article is prohibited without written permission
from the American College of Chest Physicians (e-mail:
permissions@chestnet.org).
Correspondence to: Andrea Corsonello, MD, Via D. Frugiuele,
39, I-87100 Cosenza, Italy; e-mail: andrea corsonello@tin.it
830 Clinical Investigations
Downloaded From: http://chestioumal.chestpubs.org/ on 07/03/2013

predictable effect. Among these conditions congestive
heart failure (CHF) and COPD are prime
examples. Ischemic heart disease, mainly as a cause
of CHF, and COPD are expected to become the first
and fifth cause of disability worldwide by the year
2020. 3 Both these conditions are highly prevalent in
the elderly, with CHF affecting 1 in 10 people 74
years of age, and COPD patients needing oxygen
therapy having a mean age of approximately 70
years. 4,5 Disability complicates mainly CHF in New
York Heart Association class III-IV and COPD with
chronic hypoxemia. 6,7 Furthermore, disability, as expressed
by the number of lost ADL, is an independent
predictor of survival in CHF. 8,9
The main determinants of disability are dyspnea
and loss of muscle mass in both CHF and COPD,
but comorbidity is an important contributor, at least
in COPD. 10,11 However, mechanisms and types of
dyspnea distinguish CHF from COPD 12–16 : it is
mainly inspiratory and due to the high respiratory
work needed to overcome the loss of pulmonary
compliance in CHF, while it is elicited mainly by
increased airway resistances and lung hyperinflation
worsening the tension-length relationship of the
diaphragm in COPD. Furthermore, the recruitment
of selected upper-arm and torso muscles as auxiliary
respiratory muscles makes COPD patients at risk of
dependency in upper-arm–based ADL. 16 Finally,
both CHF and COPD are frequently associated with
depression and cognitive impairment, which may
further contribute to limit the physical performance,
especially in the IADL domain. 17,18 However, both
the timing of onset of depression and the pattern of
cognitive impairment distinguish CHF from
COPD. 19,20
Physical dependency can be seen as the end result
of the complex interaction among physical, cognitive,
and affective factors. Such an interaction likely yields
different results for CHF and COPD patients, given
that factors at the basis of dependency are to some
extent different in CHF and COPD. As a consequence,
we can expect that the hierarchy of cumulatively
considered BADL and IADL are also different
in CHF and COPD patients.
We designed the present study to assess the
applicability and utility of the BADL-IADL scale in
CHF and COPD as well as in diabetes mellitus. We
selected the last condition as a comparison disorder
due to the fact that the impact of diabetes mellitus
on physical independence is not primarily mediated
by dyspnea. 21 The objective of our study was to verify
whether these three chronic conditions correspond
to different internal structures of the BADL-IADL
scale. Finding distinctive multiple dimensions, ie,
different combinations of items, inside the BADL-
IADL scale as a function of the main disease would
demonstrate that CHF, COPD, and diabetes mellitus
affect physical function differently.
Patients
Materials and Methods
The present study uses data from a large collaborative observational
study group, the Gruppo Italiano di Farmacovigilanza
nell’Anziano (GIFA), based in community and university hospitals
located throughout Italy, that periodically surveys drug
consumption, occurrence of adverse drug reactions, and quality
of hospital care. We used data on patients consecutively admitted
to the 24 participating centers during the 4-month survey carried
out in 1998. Methods of the GIFA have been previously described.
22,23 Briefly, a study physician with specific training
completed a questionnaire for each patient at admission to
hospital and updated it daily. Data recorded included sociodemographic
characteristics, medical variables, CBC count, and
neuropsychological and physical function variables.
Overall, 3,010 patients were enrolled in the survey period. We
excluded patients who died during hospital stay (n 117) and
those for whom the BADL-IADL rating was not available
(n 132), with a final sample of 2,761 patients. On the basis of
the primary diagnosis coded according to criteria by International
Classification of Diseases, Clinical Modification, Ninth Revision
(ICD-9 CM), 24 we identified 432 patients (15.6%) with CHF
(ICD-9 CM 428–428.9), 305 (11.0%) with COPD (ICD-9
CM 490–492.8, 494, 496), and 534 (19.3%) with diabetes
mellitus (ICD-9 CM 250–250.7). These three groups represented
our study populations.
Preadmission functional capabilities, ie, those before the acute
exacerbation leading to the hospitalization, were rated by a
21-item ADL scale. 25 The patients were interviewed on the day
before the planned discharge because a great proportion of them
were too seriously ill to be interviewed on hospital admission.
Performance on individual ADL was scored according to the five
levels of difficulty recommended by the World Health Organization:
without difficulty, with difficulty but without help, help
for only part of the activity, help for total activity, and not able to
perform. 26
Variables specifically considered in this study were age, gender,
education, type of ward, living alone, and being widowed. The
cognitive and affective status were assessed by the Hodkinson
abbreviated mental test (AMT) and the 15-item geriatric depression
scale (GDS), respectively. 27,28 The Charlson index of comorbidity
was calculated. 29 Drugs were coded by anatomic and
therapeutic classification. 30 Procedures conformed to guidelines
provided by the Catholic University Ethical Committee.
Statistical Analysis
Characteristics of groups were compared by the 2 test for
categorical variables and the analysis of variance for continuous
variables. The construct validity of the BADL-IADL scale within
individual groups was assessed by the main component analysis. 31
As a first step, we tested the appropriateness of the main
component analysis by the Kaiser-Meyer-Olkin measure of sampling
adequacy and the Bartlett test of sphericity. 32 Commonalities
(the squared multiple correlation coefficients between a
variable and all other variables) were assumed to reflect the
strength of the linear association among the variables.
The basic assumption of factor analysis is that complex phenomena,
such as the BADL-IADL based profile of functional
www.chestjournal.org CHEST / 127 /3/MARCH, 2005 831
Downloaded From: http://chestioumal.chestpubs.org/ on 07/03/2013

independence, can be explained by underlying dimensions or
factors. Factors corresponding to a set of closely interrelated
BADL-IADL items were identified by the main component
analysis (factor extraction). The component matrix was obtained,
and then a rotated component matrix was derived through an
oblique rotation. The component matrix represents the crude
relationship between the factors and the individual BADL-IADL
items, but it fails to disclose an easily interpretable pattern of
correlation because many items have moderate-size correlations
with most factors. On the contrary, the oblique rotation simplifies
the relationship between individual items and factors by minimizing
the number of BADL-IADL items having loadings on a
factor. The rotation phase makes the initial matrix easier to
interpret, grouping BADL-IADL items to identify factors corresponding
to well-defined dimensions of physical independence.
The strength of the relationship between factor and item was
assumed to be directly proportional to the magnitude of the
coefficient relating individual items to the extracted factor.
Furthermore, the oblique rotation provides a measure of correlations
among factors.
We identified factors to be retained in the final model on a
graphical plot of explained variance by corresponding factor:
retained factors can be recognized as those preceding the
boundary between factors explaining large and small proportions
of variance. 31 A scale that explains most of the observed variance
by a few factors has a solid internal structure, ie, chance variations
are unlikely to confound the interpretation of the differences
observed both within and between groups. The main component
analysis was repeated on subgroups defined by sex to verify to
which extent gender contributed to the loading of BADL//IADL
items on retained factors. All analyses were performed using
statistical software (SPSS V10.0; SPSS; Chicago, IL).
Results
Sociodemographic, neuropsychological, and clinical
characteristics of CHF, COPD, and diabetes
Table 1—General Characteristics of the Groups Studied*
mellitus patients are reported in Table 1. CHF
patients were characterized by older age and higher
prevalence of widowhood than COPD and diabetes
mellitus patients, whereas male gender prevailed in
the COPD group. Admission to a geriatric ward was
more frequent in both CHF and COPD groups. The
cognitive status, as reflected by the mean AMT
score, was fairly normal, whereas the mean GDS
score was consistent with a highly prevalent depressive
trait in all groups. CHF was recorded as a
secondary diagnosis in 24.9% of COPD patients and
in 19.5% of diabetes mellitus patients; 17.6% of
CHF patients and 8.6% of diabetics had a secondary
diagnosis of COPD. Finally, a secondary diagnosis of
diabetes mellitus was present in 24.1% of CHF
patients and 15.1% of COPD patients.
The functional status of groups is summarized in
Table 2. The observation of crude data did not reveal
any distinctive clustering of BADL/IADL within
individual groups.
The main component analysis was considered
feasible in all the three groups. Indeed, the high
Kaiser-Meyer-Olkin measures of sampling adequacy
(CHF 0.931, COPD 0.923, diabetes mellitus
0.943) confirm the hypothesis that the correlations
between pairs of variables can be explained
by the other variables. The highly significant Bartlett
test of sphericity (CHF 8680.904, p 0.001;
COPD 6674.681, p 0.001; diabetes mellitus
12208.377, p 0.001) denies that the item
correlation matrix is an identity matrix.
Three main components explained most of the
Characteristics CHF (n 432) COPD (n 305) Diabetes Mellitus (n 534) p Value†
Age, yr 77.0 10.6 74.7 11.8 71.0 12.7 0.008
Male gender 225 (52.1) 197 (64.6) 282 (52.8) 0.047
Education, yr 5.8 4.1 5.6 3.8 6.3 4.0 0.089
Living alone 70 (16.2) 36 (11.8) 77 (14.4) 0.288
Being widowed 161 (37.3) 93 (30.5) 164 (30.7) 0.146
Type of ward 0.046
Geriatric 295 (68.3) 219 (71.8) 331 (62.0)
Medicine 137 (31.7) 86 (28.2) 203 (38.0)
Charlson index of comorbidity 2.5 1.5 2.5 1.5 2.6 1.6 0.348
AMT score 7.9 2.1 7.9 2.2 8.0 2.1 0.568
GDS score 5.7 3.7 5.4 3.5 5.2 3.8 0.267
Coronary artery disease 139 (32.2) 82 (26.9) 191 (35.8) 0.091
Congestive heart failure 76 (24.9) 104 (19.5) 0.114
Peripheral vascular disease 27 (6.3) 21 (6.9) 24 (4.5) 0.283
Cerebral vascular disease 56 (13.0) 53 (17.4) 79 (14.8) 0.298
Stroke 18 (4.2) 20 (6.6) 23 (4.3) 0.323
Dementia 27 (6.3) 26 (8.5) 43 (8.1) 0.425
COPD 76 (17.6) 46 (8.6) 0.001
Chronic renal failure 93 (21.5) 38 (12.5) 84 (15.7) 0.010
Malignancies 26 (6.0) 22 (7.2) 37 (6.9) 0.763
Diabetes 104 (24.1) 46 (15.1) 0.010
*Data are expressed as mean SD or No. (%). An AMT score 6 and GDS score 6 are considered normal values.
†Values refer to the three (groups) by two (level) 2 test for categorical variables or one-way analysis of variance for continuous variables.
832 Clinical Investigations
Downloaded From: http://chestioumal.chestpubs.org/ on 07/03/2013

Table 2—ADL and IADL Performance in the Groups Studied*
Variables CHF (n 432) COPD (n 305) Diabetes Mellitus (n 534) p Value†
1 Transferring 37 (8.6) 28 (9.2) 58 (10.9) 0.516
2 Ambulation 37 (8.6) 32 (10.5) 61 (11.4) 0.406
3 Dressing 36 (8.3) 28 (9.2) 58 (10.9) 0.447
4 Eating 25 (5.8) 20 (6.6) 42 (7.9) 0.391
5 Toileting 31 (7.2) 27 (8.9) 50 (9.4) 0.456
6 Bathing 35 (8.1) 29 (9.5) 57 (10.7) 0.454
7 Continence 34 (7.9) 27 (8.9) 58 (10.9) 0.313
Dependent in 3 BADL 37 (8.6) 30 (9.8) 60 (11.2) 0.409
8 Getting around outside 76 (17.6) 54 (17.7) 96 (18.0) 0.990
9 Going up or down the stairs 85 (19.7) 56 (18.4) 108 (20.2) 0.839
10 Walking for at least 400 m 87 (20.1) 58 (19.0) 111 (20.8) 0.861
11 Grocery shopping 135 (31.3) 83 (27.2) 145 (27.2) 0.413
12 Taking a bath or shower 82 (19.0) 54 (17.7) 100 (18.7) 0.896
13 Preparing meals 94 (21.8) 59 (19.3) 102 (19.1) 0.650
14 Light houseworking 103 (23.8) 65 (21.3) 111 (20.8) 0.594
15 Heavy houseworking 195 (45.1) 120 (39.3) 236 (44.2) 0.463
16 Cutting toe nails 113 (26.2) 76 (24.9) 125 (23.4) 0.698
17 Telephoning 51 (11.8) 34 (11.1) 71 (13.3) 0.705
18 Laundry 128 (29.6) 85 (27.9) 141 (26.4) 0.619
19 Traveling 141 (32.6) 86 (28.2) 150 (28.1) 0.368
20 Taking medicine 70 (16.2) 52 (17.0) 81 (15.2) 0.823
21 Managing money 92 (21.3) 54 (17.7) 108 (20.2) 0.541
Dependent 3 IADL 161 (37.3) 97 (31.8) 167 (31.3) 0.216
*Data are presented as absolute No. (% of patients dependent in individual BADL-IADL items).
†Values refer to the three (groups) by two (level) 2 test.
observed variance in BADL/IADL in CHF patients
(69% of variance) and diabetes mellitus patients
(73%); a four-component solution explained 75% of
variance in COPD group (Table 3).
Table 4 shows the rotated component matrix and
total variance explained by factors 1 to 3 in CHF
patients and in diabetes mellitus patients. Both
models were based on the loading of BADL items,
telephoning and, in diabetes mellitus, taking medicine
on the factor 1. Of the remaining IADL,
housework-related had loadings on factor 2, and the
others on factor 3. In both CHF and diabetes
mellitus populations, the main component analysis
limited to female gender gave a simpler solution
based on two factors having loadings with BADL and
IADL, respectively.
Table 5 shows the rotated component matrix and
total variance explained by factors 1 to 4 in COPD.
Factor 1 had loading with BADL and three IADL
(getting around outside, taking a bath or shower, and
Table 3—Main Components Identified and Percentage of Variance Explained in CHF, COPD, and Diabetes Mellitus
Groups*
Component
Initial Eigenvalues Extraction Sums of Squared Loadings Rotation Sums of Squared Loadings
Total % of Variance Cumulative % Total Cumulative % % of Variance Total Cumulative % % of Variance
CHF
1 10.057 47.891 47.891 10.057 47.891 47.891 7.190 34.237 34.237
2 2.889 13.757 61.647 2.889 13.757 61.647 4.366 20.792 55.029
3
COPD
1.572 7.484 69.132 1.572 7.484 69.132 2.962 14.103 69.132
1 10.132 48.250 48.250 10.132 48.250 48.250 7.304 34.781 34.781
2 3.124 14.876 63.126 3.124 14.876 63.126 3.021 14.386 49.167
3 1.411 6.721 69.847 1.411 6.721 69.847 2.938 13.991 63.158
4
Diabetes Mellitus
1.051 5.005 74.851 1.051 5.005 74.851 2.456 11.693 74.851
1 11.221 53.431 53.431 11.221 53.431 53.431 8.075 38.453 38.453
2 2.853 13.583 67.014 2.853 13.583 67.014 4.155 19.787 58.240
3 1.267 6.033 73.047 1.267 6.033 73.047 3.110 14.808 73.047
*Only factors preceding the boundary between factors explaining large and small fractions of the global variance in BADL-IADL are reported.
www.chestjournal.org CHEST / 127 /3/MARCH, 2005 833
Downloaded From: http://chestioumal.chestpubs.org/ on 07/03/2013

BADL-IADL Item
Table 4—Rotated Structure Matrix in Patients Affected by CHF and Diabetes Mellitus*
telephoning). Factor 2 had loading with houseworkrelated
IADL. Two IADL strictly related to physical
mobility (going up or down the stairs, walking for at
Congestive Heart Failure Diabetes Mellitus
Factor 1 Factor 2 Factor 3 Factor 1 Factor 2 Factor 3
1 Transferring 0.951† 0.106 0.536 0.951† 0.184 0.650
2 Ambulation 0.936† 0.117 0.562 0.935† 0.193 0.651
3 Dressing 0.948† 0.144 0.592 0.952† 0.194 0.661
4 Eating 0.917† 0.090 0.434 0.926† 0.140 0.512
5 Toileting 0.952† 0.116 0.501 0.950† 0.153 0.585
6 Bathing 0.962† 0.104 0.520 0.960† 0.153 0.604
7 Continence 0.860† 0.030 0.412 0.897† 0.140 0.493
8 Getting around outside 0.687 0.140 0.827† 0.741 0.215 0.841†
9 Going up or down the stairs 0.656 0.126 0.743† 0.598 0.215 0.850†
10 Walking for at least 400 m 0.658 0.127 0.741† 0.611 0.266 0.855†
11 Grocery shopping 0.143 0.700† 0.376 0.232 0.674† 0.513
12 Taking a bath or shower 0.674 0.176 0.811† 0.761 0.288 0.808†
13 Preparing meals 0.145 0.780† 0.215 0.198 0.771† 0.264
14 Light houseworking 0.210 0.796† 0.211 0.281 0.782† 0.286
15 Heavy houseworking 0.011 0.794† 0.087 0.099 0.829† 0.233
16 Cutting toe nails 0.457 0.216 0.662† 0.644 0.245 0.725†
17 Telephoning 0.633† 0.190 0.619 0.851† 0.157 0.577
18 Laundry 0.061 0.732† 0.049 0.016 0.772† 0.114
19 Traveling 0.281 0.041 0.745† 0.439 0.198 0.790†
20 Taking medicine 0.584 0.184 0.692† 0.793† 0.201 0.640
21 Managing money 0.286 0.242 0.661† 0.381 0.395 0.567†
*The magnitude of coefficients relating individual items to the extracted factor is a measure of the strength of this association. Extraction
method main component analysis; rotation method oblimin with Kaiser normalization.
†The greatest loading is reported to show the relationship with the main components.
least 400 m) had loading on factor 4, whereas five
IADL requiring highly efficient physical and mental
status had loading on factor 3. After stratification for
Table 5—Rotated Structure Matrix in Patients Affected by COPD*
BADL-IADL Item Factor 1 Factor 2 Factor 3 Factor 4
1 Transferring 0.926† 0.063 0.372 0.496
2 Ambulation 0.924† 0.079 0.389 0.506
3 Dressing 0.957† 0.071 0.440 0.461
4 Eating 0.932† 0.045 0.322 0.345
5 Toileting 0.951† 0.064 0.362 0.395
6 Bathing 0.962† 0.039 0.422 0.414
7 Continence 0.823† 0.023 0.376 0.184
8 Getting around outside 0.749† 0.101 0.565 0.700
9 Going up or down the stairs 0.616 0.105 0.434 0.880†
10 Walking for at least 400 m 0.611 0.105 0.446 0.879†
11 Grocery shopping 0.117 0.577† 0.480 0.266
12 Taking a bath or shower 0.717† 0.166 0.691† 0.576
13 Preparing meals 0.077 0.806† 0.236 0.022
14 Light houseworking 0.126 0.819† 0.240 0.098
15 Heavy houseworking 0.025 0.824† 0.159 0.074
16 Cutting toe nails 0.525 0.238 0.655† 0.413
17 Telephoning 0.678† 0.138 0.487 0.086
18 Laundry 0.050 0.815† 0.102 0.020
19 Traveling 0.305 0.133 0.733† 0.408
20 Taking medicine 0.649 0.209 0.762† 0.160
21 Managing money 0.257 0.237 0.715† 0.076
*The magnitude of coefficients relating individual items to the extracted factor is a measure of the strength of this association. Extraction
method main component analysis; rotation method oblimin with Kaiser normalization.
†The greatest loading is reported to show the relationship with the main components.
834 Clinical Investigations
Downloaded From: http://chestioumal.chestpubs.org/ on 07/03/2013

gender, a simpler three-factor solution was identified
in COPD female patients, whereas the four-factor
solution identified in male patients was comparable
to that generated in the whole COPD population.
In all the statistical models, the ratio of the
variance explained by factor 1 to that explained by
factor 2 was inferior to the cut off of 3.5 that defines
a test as unidimensional. 18 This finding is consistent
with the partitioning of ADL in two groups of items
(BADL and IADL) assessing different levels of
physical capacity.
Table 6 shows the correlations among factors in
individual groups of patients. In both CHF and
diabetes mellitus groups, the strongest correlation
was found between factors 1 and 3; both these
factors were weakly correlated with factor 2, ie, to
housework-related IADL. In COPD group, correlations
among factors were weaker than in CHF and
diabetes mellitus groups.
In COPD patients, dependency in mobility-related
IADL (going up or down the stairs, walking for
at least 400 m) was associated with older age (82 8
years vs 74 12 years, p 0.001 [mean SD]),
male gender (67.4% vs 43.6%, p 0.01), lower
cognitive performance (AMT 6.0 2.7 vs
AMT 8.0 2.1, p 0.001), and greater comorbidity
(Charlson index 3.3 1.9 vs 2.4 1.5, p 0.01),
but not with depression (GDS 5.8 4.5 vs
5.3 3.4, p 0.522). Arterial hypoxemia requiring
long-term oxygen therapy was not significantly less
prevalent in patients identified by factor 2 (7.5%) than
in those identified by factor 1 (11.1%), factor 3 (11.7%),
and factor 4 (12.3%).
Diabetics dependent in at least three IADL were
older (77.7 10.0 years vs 68.0 12.6 years,
p 0.001), more depressed (GDS 6.7 4.1 vs
4.7 3.5, p 0.001), and cognitively impaired
Table 6—Components Correlation Matrix in Patients
Affected by CHF, Diabetes Mellitus, and COPD*
Component 1 2 3 4
CHF
1 1.000 0.103 0.533
2 0.103 1.000 0.191
3
Diabetes mellitus
0.533 0.191 1.000
1 1.000 0.165 0.620
2 0.165 1.000 0.303
3
COPD
0.620 0.303 1.000
1 1.000 0.060 0.426 0.348
2 0.060 1.000 0.260 0.057
3 0.426 0.260 1.000 0.255
4 0.348 0.057 0.255 1.000
*Extraction method main component analysis; rotation
method oblimin with Kaiser normalization.
(AMT 6.8 2.5 vs 8.4 1.8, p 0.001), and had
greater comorbidity (Charlson index 3.2 1.7 vs
2.3 1.5, p 0.01) and prevalence of chronic renal
failure (20.4% vs 10.1%, p 0.001) and cerebrovascular
disease (21% vs 12%, p 0.01) than the
remaining ones. Except for chronic renal failure and
cerebrovascular diseases, the same conditions were
found to be associated with dependency in three or
more IADL in CHF and COPD patients.
The relationship between factors and length of
stay is represented in Figure 1. Both factors 3 and 4
were associated with a longer length of stay in the
COPD group, whereas such an association was found
for factor 2 only in the CHF group. The latter
finding reflects the longer stay of female patients
(14.5 9.9 days vs 12.0 6.7 days, p 0.05) but
not of male patients (12.6 8.4 days vs 12.9 6.9
days, p 0.864) identified by factor 2. No factor was
associated with a longer stay in the diabetes mellitus
group. Conventional measures of physical dependency,
such as dependency in at least half of BADL
or IADL, were unrelated to the length of stay.
Discussion
The main finding from this study is that BADL-
IADL cluster in a very similar manner in two
populations with different chronic conditions such as
CHF and diabetes mellitus. A quite different hierarchy
of IADL characterizes COPD, with a factor
being expression of IADL related to outdoor mobility
and another summarizing selected highly demanding
IADL. These findings demonstrate that the
crude computation of lost IADL may not be fully
representative of the impact the loss has on personal
independence. Furthermore, the clustering of selected
IADL within a given population may be a
distinctive feature of the profile of personal independence
of subjects belonging to that population.
The pattern of segregation of IADL in COPD
patients deserves consideration. The two components
respectively based on IADL exploring outdoor
mobility and selected highly demanding IADL accounted
for about one third of the cumulatively
explained variance in BADL-IADL. The former
component confirms that difficulty in moving outdoor
is a distinctive feature of COPD-related disability
in the elderly. 33 Both these components are
related to neuropsychological status and comorbidity,
but also to older age and widowhood. The
relationship with age might reflect either the negative
effect of aging per se on cognition or the role of
age as a surrogate marker of COPD duration. Indeed,
both self-medication and managing money
require an intact cognition, whereas traveling implies
www.chestjournal.org CHEST / 127 /3/MARCH, 2005 835
Downloaded From: http://chestioumal.chestpubs.org/ on 07/03/2013

Figure 1. Length of hospital stay in relation to factors identified by main component analysis in the
three groups studied. See Tables 4, 5 for definition of factors. NIDDM non–insulin-dependent
diabetes mellitus.
that both physical and mental capabilities are preserved.
In agreement with our findings, dependency
in taking medications and handling finances is distinctively
associated with cognitive impairment in the
broad population of elderly community residents. 34
These findings might have implication for the management
of COPD patients because they identify
clusters of functions that are lost or retained together.
Theoretically, selected patients might regain
a cluster of functions by a dedicated intervention.
For example, outdoor mobility could be regained by
using a portable device for oxygen delivery. However,
measures of nonphysical capabilities might
help to recognize patients with distinctive problems
and, then, need of care; for example, scoring 6at
the AMT might target patients at risk of low compliance
with pharmacologic and oxygen therapy,
which is very common among COPD patients with
hypoxemia. 35 Collaterally, our results confirm that
dependency is highly prevalent among older COPD
patients. 36 However, COPD patients have been reported
to receive less formal support (home care,
district nurse input, physiotherapy) than patients
having a similar degree of dependency due to neurologic
or orthopedic problems, as if the health-care
professionals did not fully appreciate the disabling
effect of COPD. 37
The slightly higher prevalence of important limitations
in BADL and IADL in diabetic than in CHF
and COPD population is only to some extent unexpected.
Indeed, home-dwelling Mexican Americans
60 years old with non–insulin-dependent diabetes
mellitus were found to be more impaired than
nondiabetics in both BADL and IADL, with an
average loss of eight IADL. 38 Interestingly, lower
functional status was associated with diabetic complications
and was predictive or more rapid further
decline. 38 Also, in a more healthy population 65
years old, diabetes mellitus was associated with lower
functional status. 21 Thus, our findings confirm that
diabetes mellitus carries a high risk of dependency in
the elderly. The association between dependency in
the IADL and both renal failure and cerebrovascular
disease was particular to diabetic patients, and seems
to confirm that microvascular and macrovascular
complications dramatically affect the functional status
in diabetics. However, the analogy in the patterning
of BADL-IADL between CHF and diabetes
mellitus demonstrates that differences in the correlates
of disability are not automatically associated
with different patterns of disability.
The fact that IADL related to outdoor mobility
and selected highly demanding IADL identified
COPD patients with a longer length of stay testifies
836 Clinical Investigations
Downloaded From: http://chestioumal.chestpubs.org/ on 07/03/2013

that selected patterns of disability might be relevant
to explain the need of care. We could not clarify
whether these patterns qualified as generic indexes
of COPD severity or identified a distinctive effect of
COPD on the health status. However, the association
between longer stay and housework-related
IADL in CHF was mainly due to the longer stay of
female patients and is therefore unlikely to reflect a
distinctive effect of CHF on physical independence
of selected patients. Instead, it reflects the greater
reliability of housework-related IADL as indicators
of physical capabilities in CHF female patients.
Limitations of this study deserve considerations.
First, we could not assess the relationship between
disease severity and physical limitation because the
database did not include any index of COPD and
CHF severity, except for the use of long-term oxygen
therapy by COPD patients. Indeed, a recent spirometry,
ie, a spirometry performed in the 6 months
before hospital admission, was available only for a
minority of COPD patients, whereas approximately
two thirds of them had an old spirometry. Similarly,
a recent echocardiogram was available for a minority
of CHF patients. Limiting the analysis to these
subgroups could have introduced a selection bias by
focusing on patients cared for or posing special
diagnostic problems. Thus, we can draw conclusions
about the pattern of disability, but not about its
determinants. Second, a variable proportion of patients
grouped according to an index main disease
had one or both of the other two conditions as
comorbid diseases. The corresponding BADL-IADL
pattern to some extent reflects the effect of the other
two chronic diseases. However, CHF, COPD, and
diabetes mellitus are highly prevalent and frequently
coexisting conditions. As a consequence, a pure CHF
or COPD or diabetes mellitus population would be
poorly representative of the reality.
In conclusion, this study identifies a relatively
uniform modality of BADL-IADL partitioning in
main components within two older populations having
CHF and diabetes mellitus as the main disease.
However, the identification of two distinctive main
components of BADL-IADL in COPD cautions
health-care professionals against oversimplifying the
interpretation of the individual performance in terms
of the number of activities lost or retained. Testing
the prognostic implications of individual components
of BADL-IADL scale in COPD might help to clarify
both meaning and usefulness of present findings.
References
1 Guralnik JM, Simonsick EM. Physical disability in older
Americans. J Gerontol 1993; 48:3–10
2 Thomas VS, Rockwood K, McDowell I. Multidimensionality
in instrumental and basic activities of daily living. J Clin
Epidemiol 1998; 51:315–321
3 Murray CJL, Lopez AD. Alternative projections of mortality
and disability by cause 1990–2020: Global Burden of Disease
Study. Lancet 1997; 349:1498–1504
4 Ho KK, Pinsky JL, Kannel WB, et al. The epidemiology of
heart failure: the Framingham Study. J Am Coll Cardiol 1993;
22:6A–13A
5 Pelletier-Fleury N, Lanoe JL, Fleury B, et al. The cost of
treating COPD patients with long-term oxygen therapy in a
French population. Chest 1996; 110:411–416
6 Hobbs FD, Kenkre JE, Roalfe AK, et al. Impact of heart
failure and left ventricular systolic dysfunction on quality of
life: a cross-sectional study comparing common chronic cardiac
and medical disorders and a representative adult population.
Eur Heart J 2002; 23:1867–1876
7 Okubadejo AA, O’Shea L, Jones PW, et al. Home assessment
of activities of daily living in patients with severe chronic
obstructive pulmonary disease on long-term oxygen therapy.
Eur Respir J 1997; 10:1572–1575
8 Konstam V, Salem D, Pouler H, et al, for the SOLVD
Investigators. Baseline quality of life as a predictor of mortality
and hospitalization in 5,025 patients with congestive
heart failure. Am J Cardiol 1996; 78:890–895
9 Teno JM, Harrell FE, Knaus W, et al. Prediction of survival
for older hospitalized patients: the HELP survival model.
J Am Geriatr Soc 2000; 48:S16–S24
10 Burns RB, McCarthy EP, Moskowitz MA, et al. Outcomes for
older men and women with congestive heart failure. J Am
Geriatr Soc 1997; 45:276–280
11 Ferrer M, Alonso J, Morera J, et al. Chronic obstructive
pulmonary disease stage and health-related quality of life:
The Quality of Life of Chronic Obstructive Pulmonary Disease
Study Group. Ann Intern Med 1997; 127:1072–1079
12 Stassijns G, Lysens R, Decramer M. Peripheral and respiratory
muscles in chronic heart failure. Eur Respir J 1996;
9:2161–2167
13 American Thoracic Society. Dyspnea: mechanisms, assessment,
and management; a consensus statement. Am J Respir
Crit Care Med 1999; 159:321–340
14 Laghi F, Tobin MJ. Disorders of respiratory muscles. Am J
Respir Crit Care Med 2003; 168:10–48
15 Harver A, Mahler DA, Schwartzstein RM, et al. Descriptors
of breathlessness in healthy individuals: distinct and separable
constructs. Chest 2000; 118:679–690
16 Lebzelter J, Klainman E, Yarmolovsky A, et al. Relationship
between pulmonary function and unsupported arm exercise
in patients with COPD. Monaldi Arch Chest Dis 2001;
56:309–314
17 Antonelli Incalzi R, Gemma A, Marra C, et al. Chronic
obstructive pulmonary disease: an original model of cognitive
decline. Am Rev Respir Dis 1993; 148:418–420
18 Antonelli Incalzi R, Trojano L, Acanfora D, et al. Verbal
memory impairment in congestive heart failure. J Clin Exp
Neuropsychol 2003; 25:14–23
19 Trojano L, Antonelli Incalzi R, Acanfora D, et al. Cognitive
impairment: a key feature of congestive heart failure in the
elderly. J Neurol 2003; 250:1456–1463
20 Antonelli Incalzi R, Chiappini F, Fuso L, et al. Predicting
cognitive decline in patients with hypoxemic chronic obstructive
pulmonary disease. Respir Med 1998; 92:527–533
21 Bourdel-Marchasson I, Dubroca B, Manciet G, et al. Prevalence
of diabetes and effect on quality of life in older French
living in the community: the PAQUID Epidemiologic Survey.
J Am Geriatr Soc 1997; 45:295–301
22 Carbonin PU, Pahor M, Bernabei R, et al. Is age an independent
risk factor of adverse drug reactions in hospitalized
www.chestjournal.org CHEST / 127 /3/MARCH, 2005 837
Downloaded From: http://chestioumal.chestpubs.org/ on 07/03/2013

medical patients? J Am Geriatr Soc 1991; 39:1093–1099
23 Carosella L, Pahor M, Pedone C, et al. Pharmacosurveillance
in hospitalized patients in Italy: study design of the Gruppo
Italiano di Farmacovigilanza nell’Anziano’ (GIFA). Pharmacol
Res 1999; 40:287–295
24 PHS-HCF. International classification of diseases, ninth revision,
clinical modifications. Washington, DC: Public Health
Service, Health Care Financing Administration, 1980
25 Katz S, Ford AB, Moskowitz RW, et al. Studies of illness in
aged: the index of ADL, a standardized measure of biological
and psychosocial function. JAMA 1963; 185:94–106
26 Heikkinen E, Waters WE, Brzezinski ZJ. The elderly in
eleven countries: a sociodemographic survey. Copenhagen,
Denmark: World Health Organization, 1983
27 Jitapunkul S, Pillay I, Ebrahim S. The abbreviated mental
test: its use and validity. Age Ageing 1991; 20:332–336
28 Lesher EL, Berryhill JS. Validation of the Geriatric Depression
Scale-Short Form among inpatients. J Clin Psychol 1994;
50:256–260
29 Charlson ME, Pompei P, Ales KL, et al. A new method of
classifying prognostic comorbidity in longitudinal studies:
development and validation. J Chronic Dis 1987; 40:373–383
30 Pahor M, Chrischilles EA, Guralnik JM, et al. Drug data
coding and analysis in epidemiologic studies. Eur J Epidemiol
1994; 10:405–411
31 Gruijter DNM, Van der Kamp LJT. Statistical models in
psychological and educational testing. Lisse, the Netherlands:
Swets & Zeitlinger, 1984
32 Zwick W, Velicer W. Comparison of five rules for determining
the number of components to retain. Psychol Bull 1986;
99:432–442
33 Isohao R, Puolijoki H, Huhti E, et al. Chronic obstructive
pulmonary disease and self-maintaining functions in the
elderly: a population-based study. Scand J Prim Health Care
1995; 13:122–127
34 Cromwell DA, Eagar K, Poulos RG. The performance of
instrumental activities of daily living scale in screening for
cognitive impairment in elderly community residents. J Clin
Epidemiol 2003; 56:131–137
35 Antonelli Incalzi R, Gemma A, Marra C, et al. Verbal memory
impairment in COPD: its mechanisms and clinical relevance.
Chest 1997; 112:1506–1513
36 Antonelli Incalzi R, Bellia V, Catalano F, et al. Evaluation of
health outcomes in elderly patients with asthma and COPD
by using disease-specific and generic instruments: the Sa.R.A.
study. Chest 2001; 120:734–742
37 Yohannes AM, Roomi J, Connolly MJ. Elderly people at
home disabled by chronic obstructive pulmonary disease. Age
Ageing 1998; 27:523–525
38 Wu JH, Haan MN, Liang J, et al. Diabetes as a predictor of
change in functional status among Mexican Americans: a
population-based cohort study. Diabetes Care 2003; 26:314–
319
838 Clinical Investigations
Downloaded From: http://chestioumal.chestpubs.org/ on 07/03/2013