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(Chest. 2001;120:734-742.)
© 2001 American College of Chest Physicians

Evaluation of Health Outcomes in Elderly Patients With Asthma and COPD Using Disease-Specific and Generic Instruments*

The Salute Respiratoria nell’Anziano (Sa.R.A.) Study

Raffaele Antonelli Incalzi, MD; Vincenzo Bellia, MD; Filippo Catalano, MD; Nicola Scichilone, MD; Claudio Imperiale, MD; Stefania Maggi, MD and Franco Rengo, MD

* From the Istituto di Medicina Interna e Geriatria (Drs. Incalzi and Imperiale), Catholic University of Rome, Rome; Istituto di Medicina Generale e Pneumologia (Drs. Bellia, Catalano, and Scichilone), University of Palermo, Palermo; Istituto di Medicina Interna (Dr. Maggi), University of Padua, Padua; and Cattedra di Gerontologia e Geriatria (Dr. Rengo), Federico II University of Naples, Naples, Italy.

Correspondence to: Vincenzo Bellia, MD, Istituto di Medicina Generale e Pneumologia, c/o Ospedale V. Cervello, via Trabucco 180, 90146 Palermo, Italy; e-mail: belliav{at}tin.it


   Abstract
TOP
 Abstract
Introduction
 Materials and Methods
 Results
 Discussion
 Conclusion
 Appendix 1
 References
 
Objectives: To compare the effects of asthma and COPD on health status (HS) in elderly patients, and to assess the correlation between disease-specific and generic instruments assessing HS.

Design: Multicenter, cross-sectional, observational study.

Setting: The Salute Respiratoria nell’Anziano (respiratory health in the elderly) Study network of outpatient departments.

Patients: One hundred ninety-eight asthma patients and 230 COPD patients >= 65 years old.

Measurements: HS was assessed by the Saint George’s Respiratory Questionnaire (SGRQ) and five generic outcomes: Barthel’s index, 6-min walk test, mini mental state examination, geriatric depression scale (GDS), and quality-of-sleep index. Independent correlates of SGRQ scores were assessed by logistic regression. Patients were considered to have a "good" HS or "poor" HS according to whether they did or did not perform worse than 75% of the corresponding population of asthma or COPD patients, on at least two of the five generic outcomes.

Results: On average, COPD patients had poorer HS than asthma patients on the SGRQ. Only polypharmacy (more than three respiratory drugs) and diagnosis of COPD qualified as independent correlates of the SGRQ score. The SGRQ "Activity" and "Impacts" scores shared the following independent correlates: polypharmacy, Barthel’s index < 92, and GDS > 6. Further correlates were waist/hip ratio > 1 for the Activity score, and age and occiput-wall distance > 9 cm for the Impacts score. All sections of the SGRQ except for the Symptoms score could significantly distinguish patients with good HS and poor HS.

Conclusions: Individual dimensions of HS recognize different determinants. COPD outweighs asthma as a cause of distressing respiratory symptoms. A high degree of concordance exists between SGRQ and generic health outcomes, except for the Symptoms dimension in COPD patients.

Key Words: asthma • COPD • elderly • health outcomes • quality of life • Salute Respiratoria nell’Anziano Study


   Introduction
TOP
 Abstract
 Introduction
Materials and Methods
 Results
 Discussion
 Conclusion
 Appendix 1
 References
 
Preserving a satisfactory quality of life (QoL) is considered one of the main objectives of health care.1 Thus, the approach to the treatment of chronic diseases should aim at improving both survival time and QoL. This implies that physicians should be aware of the effects of most common chronic conditions on this outcome. Among these conditions, chronic airflow limitation seems worthy of special attention because of its progressively rising prevalence and its well-recognized impact on QoL.2 3 4 5 Given the high prevalence of chronic airflow obstruction in the aged population, efforts should be made to distinguish the effects on QoL determined by the respiratory condition itself from those related to age, social factors, and frequently coexisting medical problems. Furthermore, the variability of mechanisms leading to airflow limitation contributes to make this patient population quite heterogeneous.6 Difficulty in distinguishing asthma from COPD in the elderly has also been reported7 8 and further increases the complexity of studies on QoL.

In geriatric medicine, it has long been a common practice to assess the overall health status (HS) by evaluating separately various physical, cognitive, and affective domains. More recently, a different approach to the evaluation of HS has been proposed by developing disease-specific questionnaires. In the case of chronic airflow limitation, several instruments have been designed and validated by measuring reliability, validity, and responsiveness to the effects of therapeutic interventions.9 These questionnaires have been designed to measure QoL in patients with asthma or COPD, but not in both conditions, with the only exception being the Saint George’s Respiratory Questionnaire (SGRQ), which was originally validated in both asthma and COPD patients.10 However, to our knowledge, comparative evaluations of this disease-specific approach with the traditional approach (based on various generic instruments) in the elderly population have never been published.

The aims of the present study were (1) to compare the respective effects of asthma and COPD on QoL in the elderly, as reflected by the SGRQ; (2) to identify the independent correlates of these results; and (3) to assess the correlation between these results and those deriving from the assessment of various generic (ie, nondisease oriented) health-related outcomes.9


   Materials and Methods
TOP
 Abstract
 Introduction
 Materials and Methods
Results
 Discussion
 Conclusion
 Appendix 1
 References
 
One hundred ninety-eight asthma patients and 230 COPD patients were consecutively enrolled in the Salute Respiratoria nell’Anziano (respiratory health in the elderly) Study from January 1, 1996, to July 31, 1997. All gave their informed consent to participate in the study. The Salute Respiratoria nell’Anziano Study is a multicenter study designed to analyze various aspects of clinical and functional condition in older home-dwelling subjects with chronic respiratory and nonrespiratory conditions, as well as to assess the prognostic implications of measures of QoL. It involves 24 pulmonary or geriatric institutions, located throughout Italy (see Appendix). The study protocol conformed to guidelines issued by the relevant ethical committee. A detailed description of methods with special emphasis on respiratory function measurements and quality control is available elsewhere.11 Patients were classified into three categories (COPD, asthma, simple bronchitis, the last definition applying to subjects with symptoms of chronic bronchitis but FEV1 > 80% of predicted) on the basis of criteria relevant to history of wheezing and productive cough, physical examination findings, and baseline and postbronchodilator FEV1 (Table 1 ); these criteria were based on the classical definitions of asthma and COPD and on the available knowledge on asthma presentation in the elderly,12 13 although we were aware of the risk of some misclassification because of possible loss of reversibility in long-standing asthma,14 and because of possibility of overlapping syndromes (eg, the so-called "asthmatic bronchitis") in the elderly.15


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  		Table 1. Diagnostic Criteria Used To Classify Patients as Affected by Simple (Nonobstructive) Bronchitis, Asthma, or COPD

 
The present study was focused on the effect of airway obstruction and therefore will consider only asthma and COPD groups. Components of multidimensional assessment relevant to the present study are as follows:

(1) sociodemographic characteristics: age, sex, living condition (alone, with spouse, or with relatives), availability of a domestic heating system, and educational level;

(2) health-related habits: patients were classified as nonsmokers, smokers, and previous smokers, the last condition occurring if at least 1 year had elapsed from the time that smoking was stopped. The pack/year index was also computed;

(3) quality of sleep: four problems concerning sleep (trouble to fall asleep, waking at night, waking too early, feeling of tiredness after waking) were evaluated according to the established populations for epidemiologic studies of the elderly scale,16 codified so as each problem was graded from 0 to 4, and the final score ranged between 0 and 16;

(4) nutritional and anthropometric data: weight, height, and waist and hip circumferences were measured following a standardized procedure.17 The body mass index (BMI; weight divided by height squared) and the waist/hip ratio were computed. The occiput-wall distance was measured as an index of cervical and upper thoracic kyphosis, which is a risk factor for poor balance and a marker of severe osteoporosis of the spine18 19 ;

(5) cognitive function: the Mini-Mental State Examination (MMSE) score was used as a measure of mental function20 ; this test explores six cognitive domains (temporal and spatial orientation, short-term memory, computation, secondary memory, verbal attainment, and constructive ability; normal subjects score > 23);

(6) affective status: the short form of the geriatric depression scale (GDS) was used to rate depressive symptoms; scoring > 5 on this 15-item scale is consistent with having a depressive trait of the mood21 ;

(7) physical performance: rated by Barthel’s index and the 6-min walk test22 ; Barthel’s scale includes nine items exploring self care and six items assessing mobility (subjects can score between 0 [complete dependency] and 100 [complete independence], a score > 79 but < 100 being consistent with a mild impairment in physical independence). The 6-min walk test was performed according to a standard procedure, and the walked distance was recorded23 ;

(8) comorbidity: comorbid diseases were codified according to the International Classification of Diseases, Ninth Revision,24 and the global number of comorbid diseases was computed for each patient;

(9) pharmacologic therapy: patients and their caregivers were requested to display all containers of drugs or, if these were not available, to recall their names. Drugs were classified according to anatomical, therapeutic, and chemical codes, ninth version25 ;

(10) QoL: the SGRQ is a 76-item questionnaire with three components (Symptoms, which measures frequency and severity of respiratory symptoms; Activity, which focuses on physical activities that either cause or are limited by dyspnea; and Impacts, which quantifies the impact of the respiratory disease on the daily life by assessing psychological problems, need of care, adverse drug reactions, expectations for health, and disturbances of daily life); each item of the questionnaire has a weight that has been derived empirically. Because of weights of individual items, each section of the questionnaire is scored between 0 (no impairment) and 100 (maximal impairment); a cumulative score for the whole questionnaire is also computed and ranges between 0 and 100.10

From the above list, we selected five generic instruments measuring health-related outcomes (listed at points 3, 5, 6, and 7) because of their well-proven discriminative and evaluative properties and predictive validity in broad geriatric populations.16 26 27

Statistical Analysis
Differences between asthma and COPD groups were evaluated by Student’s t test for unpaired data or by {chi}2 test, as applicable. Correlates of various scores of the SGRQ were assessed first by univariate analysis using {chi}2 test for dichotomous variables and the correlation coefficient for continuous variables. Then, variables univariately correlated with the outcome were entered into a logistic regression analysis aimed at identifying independent correlates of each score. The dependent variable in each logistic regression, ie, any score, was dichotomized using the threshold corresponding to the 75th percentile of the value distribution. The independent variable was considered to predict the outcome if the corresponding coefficient/SD ratio was > 1.96, the odds ratio differed from 1, and the 95% confidence limits did not enclose 1. The strength of the logistic regression was estimated by computing the C. C. Brown goodness-of-fit coefficient; this index was preferred to both the goodness of fit {chi}2 and the Hosmer-Lemeshow test because the logistic models were characterized by small cell frequencies and several discrete covariates.28

In order to obtain easily interpretable and comparable logistic models, variables used to define the group membership (ie, baseline and postbronchodilator FEV1, history of wheezing and/or productive cough) were excluded from the statistical analysis. Thus, the predictive role of group membership itself (COPD vs asthma) was assessed.

In order to evaluate whether and to what extent generic and disease-specific indicators differed in estimating disease-related HS, the SGRQ results were correlated with those coming from the five generic instruments measuring health-related outcomes cited above (Barthel’s index, 6-min walk test, MMSE, GDS, quality-of-sleep index). Individual patients were considered to have "poor" HS or "good" HS, as reflected by generic assessment instruments, if they did or did not perform worse than 75% of the corresponding population (ie, of asthmatic or COPD patients) on at least two of these instruments. In order to assess whether and to what extent generic and disease-specific indicators differed in estimating disease-related HS, differences in SGRQ components and summary scores between good HS and poor HS subgroups were computed by the unpaired Student’s t test.


   Results
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
Discussion
 Conclusion
 Appendix 1
 References
 
Table 2 shows the main characteristics of the patients. The COPD group was characterized by a higher prevalence of male patients and smokers or ex-smokers, lower formal education, worse nutritional status (as expressed by the BMI), and higher consumption of respiratory drugs. The groups did not differ in the distribution of health outcomes, with the only exception being a worse quality of sleep in asthmatic patients and a trend toward a lower MMSE score in COPD patients.


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  		Table 2. Main Characteristics of Asthma and COPD Patients*

 
Table 3 reports the distribution of the SGRQ scores. The COPD group scored higher (ie, had a worse QoL) in all the explored dimensions, the largest difference between groups being evident in the section. In both groups, the wide SD of scores testifies to the heterogeneity of QoL among patients.


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  		Table 3. Differences Between Groups in Individual Components and Summary Score of the SGRQ*

 
Differences between groups in the SGRQ reported in Table 3 were mainly due to the higher prevalence of selected problems among COPD patients: inadequate control of chest problems (30% vs 17%, p = 0.02) and feeling of frailty or invalidity (27% vs 13%, p = 0.007) in the Impacts section, a higher frequency of attacks of chest trouble in the last year (27% vs 13%, p = 0.007) in the Symptoms section, and a more severe limitation in taking a bath or shower (23% vs 13%, p < 0.05) in the Activity section. Only lack of confidence in the effect of pharmacologic therapy, from the Impacts section, prevailed among asthmatics (21% vs 10%, p = 0.015).

Tables 4 , 5 summarize results from univariate analysis: the Symptoms score was highly correlated (p < 0.001) with the diagnosis of COPD and with the following variables: number of respiratory drugs used, GDS score, and disturbed sleep index. Barthel’s index, 6-min walk distance, and, to a lesser degree of significance, MMSE and years of formal education were inversely correlated with the Symptoms score.


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  		Table 4. Univariate Correlates of Symptoms and Activity Scores of the SGRQ in Pooled Asthma and COPD Groups*

 
Activity and Impacts scores shared with the Symptoms score most of the correlates, with the following differences: the Activity score lacked correlation with years of formal education but was directly correlated with the waist/hip ratio and the occiput-wall distance; the Impacts score lacked correlation with the group membership (COPD vs asthma) and was directly correlated with the occiput-wall distance.

The Summary score was correlated with the diagnosis of COPD, the number of respiratory drugs used, the GDS score, the disturbed sleep index, and the occiput-wall distance. It was inversely correlated with the Barthel’s index, the 6-min walk distance, the MMSE score, and years of formal education.

Table 6 reports results from logistic regression analysis. Only a diagnosis of COPD and the use of more than three respiratory drugs were independent correlates of a high Symptoms score. Conversely, high Activity and Impacts scores shared the following predictors: GDS, Barthel’s index, quality of sleep, and use of respiratory drugs. A waist/hip ratio > 1 was a further predictor of high (ie, worse) Activity score; both older age and occiput-wall distance >= 8 cm increased the impact of the respiratory disease on daily life. The "Summary" score showed a predictive model comparable to that of the Impacts score.


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  		Table 6. Independent Correlates of Individual Components and Summary Score of the SGRQ According to Logistic Regression Analysis in Pooled Asthma and COPD Groups

 
Since Barthel’s index had an attributable fraction of 86% in the model predicting Activity, an alternative predictive model excluding this index was tested in order to disclose any concealed predictor of the outcome.29 However, no additional variable qualified as independent correlate of the outcome.

The C. C. Brown coefficients of logistic models were 1.032 (p = 0.579) for Symptoms, 2.343 (p = 0.31) for Activity, 0.287 (p = 0.866) for Impacts, and 0.287 (p = 0.866) for Summary. Since a large p value is consistent with the logistic model adequately fitting data, the best predictive models were obtained for the outcomes for Impacts and Summary.30

Differences in SGRQ scores between patients with good HS and poor HS outcome profiles within the asthma and COPD groups are summarized in Figure 1 . All sections of the SGRQ could distinguish between good HS and poor HS subjects, with the only exception being the Symptoms section in the COPD group.



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  		Figure 1. Distribution of individual and summary scores of the SGRQ in asthma patients (upper panel) and COPD patients (lower panel) grouped according to whether their HS was rated as good or poor by generic instruments.

 

   Discussion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
Conclusion
 Appendix 1
 References
 
The results of the present study show that in older patients, all dimensions of QoL were more compromised in COPD patients than in asthma patients; however, COPD qualified as an independent predictor of worse QoL only with regard to the Symptoms dimension, possibly because of the reported higher frequency of exacerbations in this disease. A very high concordance between disease-specific and generic instruments rating HS was observed, except for the Symptoms dimension in COPD patients. The latter finding might reflect either differences in the perception of symptoms between COPD and asthmatic subjects or a more linear (and then predictable) relationship between symptoms and physical limitations in asthmatics; the use of generic instruments more directly assessing physical limitations could have contributed to disclose such a relationship.

A high daily consumption of respiratory drugs was the only independent correlate of all components scores and of the total SGRQ score. This variable is likely an index of disease severity, although a direct negative effect of polypharmacy on QoL cannot be excluded. At variance with the results of a previous study31 pertaining to a broader geriatric population followed up for 1-year, a close relationship seemed to link the need of care, as reflected by the severity of impairment in QoL, and the consumption of health-care resources, as expressed by drug use. Lack of information on the use of health-care facilities prevented us from exploring this relationship in more detail. Interestingly, 1 of 5 asthma patients and 1 of 10 COPD patients were poorly confident in drug therapy. This finding and the repeatedly reported positive attitude of respiratory patients toward rehabilitation programs, even in the absence of any measurable improvement in QoL, further stress the need for a comprehensive and multidimensional approach to treatment of chronic airflow limitation in the elderly.32 33 Collaterally, the fact that asthma patients were less confident in therapy than COPD patients might depend on the variable and poorly predictable course of asthma and, then, the experience of dramatic fluctuations in physical capabilities and QoL. Paradoxically, a progressive disease could make the patient more confident in the pharmacologic therapy, because a return to baseline in physical capabilities and QoL never occurs nor is expected to occur; accordingly, the expectancy of well-being is lesser than in asthmatic patients, and comparably lesser is the psychological discomfort caused by experiencing progressively declining HS despite even optimal pharmacologic therapy.

Depressed mood, as reflected by the GDS score, was the main determinant of the Summary score as well as an important predictor of both Activity and Impacts scores. The well-known association between chronic airflow limitation, anxiety, and depression explains this observation.3 4 However, the prevalence of depressed mood was 20.2% and 17% only in asthma and COPD groups, respectively, which compares favorably with previously reported prevalence figures, at least in COPD patients.3 4 5 Differences in the severity of the respiratory disease likely account for this disagreement. The relatively low prevalence and the strong predictive power of depression in the present study further testifies that depression is an important marker of worse QoL in both asthma and COPD patients.

As expected, Barthel’s index was the main predictor of the Activity score, but several variables contributed to the logistic model. Of these variables, the waist/hip ratio deserves some attention; since both the percentage of ideal weight and BMI lacked predictability, it can be inferred that central obesity rather than generically obesity negatively affects physical performance. This finding further adds to the series of negative effects (eg, on metabolism, cardiovascular function, and survival) ascribed to central obesity.34 The negative repercussion of high abdominal pressure on the length/tension relationship of the diaphragm and the ensuing reduced efficiency of the breathing pattern and increased dyspnea can likely account for the role of central obesity in reducing physical activity.35 Interestingly, a diagnosis of COPD did not qualify as a predictor of the outcome, even after removing Barthel’s index from the logistic model. This finding further stresses the fact that, at least in mild-to-moderate forms, COPD only slightly outweighs asthma in limiting physical performance. Aging, by requiring progressively less demanding physical activities, likely contributes to smooth differences between asthma and COPD.

An occiput-wall distance > 8 cm contributed to explain the Impacts score of the SGRQ. Uncertainty exists about the mechanism of this relationship; as a measure of cervical kyphosis, a wider occiput-wall distance might be associated also with increased dorsal kyphosis and, thus, rib cage deformity negatively conditioning the breathing pattern. This seems an unlikely interpretation, because a wider occiput-wall distance was not associated with a trend toward a restrictive spirometric pattern (FVC of 77.9% predicted vs 79.6% predicted in the remaining patients, p = 0.43). Thus, osteoporosis, which has in itself the potential for negatively affecting QoL, probably explains the relationship between a wider occiput-wall distance and the Impact score.

Interestingly, age added to the prediction of the Impacts score, but not of the Symptoms and Activity scores. The direct relationship between age and the Impacts score might partially be explained by reduced self-esteem and more negative perception of this dimension of daily life by older patients. Indeed, a positive correlation between age and depressed mood, as reflected by GDS score, was observed (Spearman’s {rho} = 0.159, p = 0.001). However, a similar negative effect of age on the "perception" of QoL did not emerge in the Symptoms and Activity sections. Thus, age seems to be a real multiplier of the effect of the respiratory disease on the composite measure of well-being represented by the Impacts score.

Poor quality of sleep characterized subjects with a high Impacts score. Although the poorer quality of sleep of asthmatic subjects is consistent with the well-known nocturnal prevalence of asthmatic symptoms,36 the available information does not allow to distinguish whether the disturbed sleep was an index of disease severity or just reflected the relatively high prevalence of sleep problems in the elderly.12 Furthermore, selected medical conditions, such as gastroesophageal reflux, could to some extent be responsible for sleep fragmentation and, then for a higher Impact score in asthma patients.37 Historical data seemed to exclude such a possibility in our patients, but their diagnostic accuracy has been reported to be poor and the prevalence of reflux high in asthmatics.38

Some limitations of this study may be discussed. Firstly, the choice of excluding respiratory function data and symptoms from the analysis, yet founded on solid logical bases, might seem debatable when considering that the final aim of the study was to identify predictors of QoL in the presence of chronic airflow obstruction. Nevertheless, this represented the only possibility of comparing patients with clinically and pathophysiologically distinct patterns of obstruction. Secondly, the study was limited to ambulatory patients, so that no inference can be made on respiratory patients unable to attend the laboratory because of severe physical impairment. The lack of this extreme, yet not uncommon, condition might weaken the discriminatory power of both generic health outcomes and the SGRQ. Thirdly, it can be very difficult to distinguish asthma from COPD in the elderly.12 13 14 15 This could limit the reliability of our algorithm or any diagnostic algorithm applied to an elderly population. Even selected historical data could not help us in distinguishing these conditions. For example, a history of or a current smoking addiction, which is commonly considered as distinctly rare in asthma populations, was recorded in the majority of older asthmatics studied by Burrows et al.15 The lack of more refined respiratory function parameters, in our study as well as in other epidemiologic studies,15 further limited the accuracy of the differential diagnosis.


   Conclusion
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusion
Appendix 1
 References
 
The present study shows that, on average, COPD has a greater impact than asthma on the QoL of geriatric patients in stable clinical conditions, and that substantial differences exist among correlates of individual dimensions of QoL. The poor discriminatory power of the SGRQ Symptoms section with respect to classification of COPD patients as having poor HS or good HS by generic instruments suggests that subjective perception, which accounts for rating of symptoms in the SGRQ, is to some extent dissociated from objective rating of physical and cognitive performance by generic instruments. Future research should aim at comparing disease-specific and generic instruments in older respiratory patients in order to evaluate their sensitivity to changes in disease state (eg, during acute exacerbations) and their prognostic implications. The available knowledge, including the present contribution, suggests that these kinds of instruments provide closely correlated (but not completely interchangeable) accounts on HS at least in COPD patients.


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  		Table 5. Univariate Correlates of Impact and Summary Scores of the SGRQ in Pooled Asthma and COPD Groups*

 

   Appendix 1
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusion
 Appendix 1
References
 
Coordinators
V. Bellia (Palermo), F. Rengo (Napoli)

Scientific Committee Members
R. Antonelli Incalzi (Taranto), V. Grassi (Brescia), S. Maggi (Padua), G. Masotti (Florence), G. Melillo (Naples), D. Olivieri (Parma), M. Palleschi (Rome), R. Pistelli (Rome), M. Trabucchi (Rome), S. Zuccaro (Rome)

Participating Centers, Principal Investigator, and Associated Investigators (in Parentheses)
Div. Medicina I, Osp. Geriatrico INRCA, Ancona. D.L. Consales (P. Paggi, D. Lo Nardo); Div. Geriatria, Osp. Civile, Asti. F. Goria (P. Fea, G. Iraldi, R. Corradi); Catt. Geront. e Geriatria, Policlinico Universitario, Bari. A. Capurso (R. Flora, F. Torres, G. Venezia, M. Mesto); V Div. Geriatria, Osp. Malpighi, Bologna. S. Semeraro (L. Bellotti, A. Tansella); I Div. Med. Generale, Osp. Civile, Brescia. V. Grassi (S. Cossi, G. Guerini, C. Fantoni, M. De Martinis, L. Pini); Clinica Pneumologica, Fondazione "E. Maugeri," Telese (BN). G. Melillo (R. Battiloro, C. Gaudiosi, S. De Angelis); Ist. Med. Int. e Geriatria, Osp. Cannizzaro, Catania. L. Motta (I. Alessandria, S. Savia); Ist. Geront. e Geriat., Osp. Ponte Nuovo, Univ. of Florence. G. Masotti (M. Chiarlone, D. Matteuzzi, S. Zacchei); Div. Geriatria, Osp. Morgagni, Forlì, V. Pedone (D. Angelini, D. Cilla; Div. Geriatria, Osp. Galliera, Genova E. Palummeri (M. Agretti, P. Costelli, D. Torriglia; G.ppo Ricerca Geriatrica, Osp. Richiedei, Gussago (BS). M. Trabucchi (F. Guerini, P. Ranieri, P. Barbisoni); Div. Geriatria, Osp. Generale, L’Aquila. F. Caione (D. Caione, M. La Chiara); I Div. Geriatria, Osp. San Gerardo, Monza. G. Galetti (A. Cantatore, D. Casarotti, G. Anni); Catt. Gerontologia e Geriatria, Univ. Federico II, Napoli. F. Rengo (F. Cacciatore, A.I. Pisacreta, C. Calabrese); Ist. Med. Int., Osp. Geriatrico, Padova. G. Enzi (P. Dalla Montà, S. Peruzza, P. Albanese, F. Tiozzo); Ist. Mal. App. Resp., Osp. Rasori, Parma. D. Olivieri (V. Bocchino, A. Comel, N. Barbarito; Ist. Geront. e Geriatria, Policlin. Monteluce, Perugia. U. Senin (F. Arnone, L. Camilli, S. Peretti; Div. Geriatria, Osp. Israelitico, Roma. S.M. Zuccaro (M. Marchetti, L. Palleschi); Div. Geriatria, Osp. Gen. Addolorata, Roma. M. Palleschi (C. Cieri, F. Vetta); Ist. Med. Int. e Geriatria, Polic. Gemelli, Roma. P.U. Carbonin (F. Pagano, P. Ranieri); Ist. SEM. Med. e Geriatria, Pol. Le Scotte, Siena. S. Forconi (G. Abate, G. Marotta, E. Pagni; Fond. San Raffaele, Cittadella della Carità, Taranto. R. Antonelli-Incalzi (C. Imperiale, C. Spada); Catt. Geront. e Geriatria, Osp. Maggiore, Milano. C. Vergani (M.C. Sandrini, G. Giardini, I. Dallera); Catt. Mal. App. Resp., Osp. V. Cervello, Palermo. V. Bellia (F. Catalano, N. Scichilone, S. Battaglia)

Coordinating Center
Istituto di Medicina Generale e Pneumologia, Catt. Mal. App. Respiratorio, Università degli Studi di Palermo


   Acknowledgements
 
All participants thank G. Torresin and the staff of Biomedin (Padua, Italy) for technical assistance.


   Footnotes
 
Abbreviations: BMI = body mass index; GDS = geriatric depression scale; HS = health status; MMSE = Mini-Mental State Examination; QoL = quality of life; SGRQ = Saint George’s Respiratory Questionnaire

Supported by a research grant of Boehringer Ingelheim Italia.

Received for publication April 24, 2000. Accepted for publication April 9, 2001.


   References
TOP
 Abstract
 Introduction
 Materials and Methods
 Results
 Discussion
 Conclusion
 Appendix 1
 References
 

  1. Constitution of the World Health Organization. In: World Health Organization: handbook of basic documents. 5th ed. Geneva, Switzerland: Palais des Nations, 1952; 3–20
  2. Data from National Health Interview Survey. Hyattsville, MD: Department of Health and Human Services, 1991; 92–1509
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