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* From the Department of Pneumonology (Drs. Ischaki, Gaki, and Papa), Veterans Hospital of Athens; Clinical Research Unit (Dr. Papatheodorou), Athens Army General Hospital; and First Respiratory Medicine Department (Drs. Koulouris and Loukides), University of Athens Medical School, Athens, Greece.
Correspondence to: Stelios Loukides, MD, FCCP, Smolika 2, 16673 Athens, Greece; e-mail: ssat{at}hol.gr
Abstract
Background: COPD primarily affects the lungs but also produces systemic consequences that are not reflected by the recent staging according to Global Initiative for Chronic Obstructive Lung Disease (GOLD) guidelines. Body mass index (BMI) and fat-free mass index (FFMI) represent different aspects of nutrition abnormalities in COPD. We investigated whether BMI and FFMI could be related to parameters expressing airflow obstruction and limitation, exercise capacity, airway inflammation, and quality of life, and whether they would reflect the GOLD staging of the disease.
Methods: One hundred patients with clinically stable COPD equally classified into the five stages of the disease were evaluated for BMI, FFMI (measured by bioelectrical impedance analysis), airway obstruction and hyperinflation (FEV1, FEV1/FVC, inspiratory capacity), exercise capacity (6-min walk distance [6MWD], Borg scale before and after 6MWD]), chronic dyspnea using the Medical Research Council (MRC) scale, airway inflammation (sputum differential cell counts, leukotriene B4 in supernatant), and quality of life (emotional part of the chronic respiratory disease questionnaire).
Results: 6MWD was significantly associated with both BMI and FFMI values, while FFMI additionally presented significant correlations with MRC scale, percentage of predicted FEV1, and FEV1/FVC ratio. No association was observed between the two nutritional indexes. BMI was not statistically different among patients in the five stages of COPD, while FFMI reflected the staging of the disease, presenting the highest values in stage 0.
Conclusions: Nutritional status is mainly related to exercise capacity. FFMI seems to be more accurate in expressing variables of disease severity, as well as the current staging compared to BMI.
Key Words: airway obstruction • body mass index • COPD • exercise capacity • fat-free mass index
COPD is characterized by a range of pathophysiologic changes contributing to a highly variable clinical presentation as well as heterogeneity among the patients. One of the main consequences of the disease is the progressive loss of skeletal muscle mass and the presence of several bioenergetic abnormalities, mainly expressed by weight loss.1 The above systemic effects might enhance significantly clinical symptoms, such as limitation of exercise capacity, and have a negative impact on quality of life.23 Weight loss and low body mass index (BMI), as part of the BODE (BMI, airflow obstruction, dyspnea, and exercise capacity) index, are also negative prognostic factors for survival independent of other prognostic indexes based on the degree of pulmonary dysfunction.456
Nutritional status is mainly evaluated by BMI. The body mass is divided into two compartments, one called fat mass and the other fat free mass with the latter to contain the main metabolically active organs particularly skeletal muscle mass. However recent data suggests that fat-free mass index (FFMI) provides information beyond that provided by BMI.57 This might be attributed to the fact that loss of skeletal muscle mass is the main cause of weight loss in COPD, whereas loss of fat mass contributes to a lesser extent, leading to the plausible theory that FFMI reflects better the muscle mass than BMI. Low FFMI is significantly correlated with severity of COPD.7 Despite the fact that severity of the disease is assessed only with variables expressing airflow limitation and obstruction, parameters associated to weight loss are also considered powerful in assessing the disease prognosis.
We used data of COPD stable patients at all stages according to the Global Initiative for Chronic Obstructive Lung Disease (GOLD) classification in order to identify whether the above parameters are related to variables expressing airflow obstruction and limitation, exercise capacity, airway inflammation, and quality of life. As a secondary outcome, we investigated whether BMI and FFMI could equally be associated to the recent staging of GOLD classification.
Materials and Methods
Patients
Four hundred twenty clinically stable COPD patients, all current smokers, were screened through the outpatient clinic of Veterans Hospital during a period of 1 year in order to select 100 patients and to form similar groups of each stage of the GOLD classification.8 Inclusion criteria were medication according to the stage of their disease, no self-reported asthma or reversibility > 12% of airway obstruction after administration of a ß2-agonist, and no participation to a rehabilitation program for the last year. Patients were excluded if they had respiratory infection in the last 4 weeks, history of chronic liver and renal failure, malignancy, insulin-dependent diabetes mellitus, use of systemic corticosteroids, atopy, and clinical apparent heart failure. Additionally, they were not eligible to participate if they had abnormal electrolyte values at their initial visit, or they were not able to cooperate. The principal cause for exclusion in our initial sample was the use of COPD treatment not recommended according to the stage of the disease. Atopic status was assessed by the negative history and the negative skin-prick test results to six common aeroallergens.
BMI and FFMI Assessment
The main variables of interest were BMI and FFMI. BMI was calculated as weight/height squared. Fat-free mass (FFM) was measured as previously described by bioelectrical impedance analysis (BIA 101 System Analyzer; Akern; Florence, Italy) with an operating frequency of 50 KHz at 800 µA.9 FFM was standardized for height and expressed the FFMI (FFM/height squared).10
Pulmonary Function Tests
FEV1, FVC, and FEV1/FVC ratio were measured with a dry spirometer (Vica-test, Model VEP2; Mijnhardt; Rotterdam, Holland).11 Inspiratory capacity (IC) was determined as previously described.12 Three trials were performed, and the two higher IC values had to agree within 5% or 60 mL. Arterial blood gases obtained in room air and were analyzed by a standard blood gas analyzer (Ecosys II, compact BGA; Eschweiler; Klel, Germany).
Sputum Induction and Processing
Sputum induction was performed with inhalation of hypertonic saline solution (3.5%) by an ultrasonic nebulizer (model 2696; DeVilbiss; Somerset, PA). Leukotriene B4 (LTB4) [Cayman Chemical; Ann Arbor, MI] was measured by enzyme-linked immunosorbent assay, with a lower limit of detection 13 pg/mL. Sputum cell counts were performed with standard procedures.13
Dyspnea and Exercise Capacity
Chronic dyspnea was assessed using the Medical Research Council (MRC) scale.14 Exercise capacity was assessed with the 6-min walking distance (6MWD) according to the American Thoracic Society guidelines15 in a walking cross of 50 m. All tests were supervised by an experienced pneumonologist. Oxygen saturation and pulse rate were recorded using a finger-adapted pulse oximeter. None of our patients experienced a desaturation < 90% during the test. All patients underwent a second test on a separate day with the highest value to be used in the study analysis. Additionally, the difference in breathlessness in the Borg scale (
Borg) before and after the end of 6MWD was assessed.16
Chronic Respiratory Disease Questionnaire
The emotional part of the chronic respiratory disease questionnaire (CRQ) validated for the Greek population was assessed in all patients.17
Study Protocol
On day 1, all subjects underwent a medical history and medical examination by an experienced pneumonologist, spirometry for measuring FEV1 and FEV1/FVC before and after bronchodilation, and biochemical blood tests for electrolytes, renal, and liver function. Patients eligible for the study were asked to come on a separate day (usually 2 days later) for measurement of BMI and FFMI. On the same day, blood gases, IC, MRC scale for dyspnea, and a questionnaire for assessing quality of life (CRQ, emotional part) were performed. On the following 2 days, exercise capacity was evaluated twice using the 6MWD in meters and the Borg before and after the end of the test. Finally, 4 days after the initial visit, induced sputum was performed and analyzed for LTB4 and sputum differential cell counts. All patients were classified in the five stages of COPD on the basis of FEV1/FVC < 70% and FEV1 percentage of predicted (FEV1%pred) values according to GOLD classification. Patients with productive cough and normal spirometry findings were included in stage 0. Study was approved by the scientific committee of Veterans Hospital, and all patients gave informed consent.
Statistical Analysis
Data are presented as mean ± SD. Statistical significance of differences in all study groups were estimated with one-way analysis of variance with an appropriate post hoc test for multiple comparisons (Bonferroni). The associations between FFMI and BMI (dependent variables) and study parameters (independent variables) were determined using Pearson correlation coefficient analysis. The significant variables were then introduced in a stepwise multiple regression analysis model to determine the most related value to BMI and FFMI values. Main analysis was performed in all subjects and in each group separately. Analysis was performed using statistical software (SPSS 12.0; SPSS; Chicago, IL); p < 0.05 was considered significant.
Results
Correlations
Patient Characteristics are summarized in Table 1
. Correlation data for the whole study group are summarized in Table 2
. Briefly, BMI was weakly correlated with exercise capacity as assessed by 6MWD (Fig 1
, left, A). FFMI presented significant correlations with 6MWD (Fig 1, right, B), MRC dyspnea, and airway obstruction and limitation as assessed with FEV1/FVC ratio and FEV1%pred, respectively. Stepwise linear regression analysis showed that 6MWD and MRC were the best predictors of FFMI, explaining 53% of FFMI variance.
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Borg, MRC, neutrophils (percentage), and LTB4 in induced sputum were significantly lower (p < 0.0001, p < 0.0001, p < 0.05, and p < 0.001, respectively). PaO2 was significantly lower in stage IV compared to the other stages (p = 0.03). No significant differences were found regarding CRQ and PaCO2. When we excluded from statistical comparisons patients with stage 0 COPD, FEV1, IC, and 6MWD were significantly higher in stage I (p < 0.0001, p < 0.001, p < 0.0001, respectively), and FEV1/FVC ratio was significantly lower in stage IV (p < 0.0001), whereas Borg, MRC, and LTB4 were significantly lower in stage I (p < 0.001, p < 0.0001, and p = 0.02, respectively) [Table 1]. Discussion
Our study, which included COPD patients with a wide range of severity, shows that FFMI provides information beyond BMI regarding variables expressing disease severity and exercise capacity, and should be considered in the routine assessment of patients with COPD. FFMI seems to be more accurate in predicting the recent staging of the disease compared to BMI.
Our study showed that FFMI values were higher in those stages where no or minimal airflow limitation and obstruction exists. The above finding was not observed for BMI values. The quite strong association between stages and FFMI and the absence of a relationship between stages and BMI might imply that fat mass increases significantly with progression of disease. However no data exists regarding fat mass and disease progression, and further studies are needed for this purpose.
FFMI better reflects the skeletal muscle mass; thus, an important issue is to explain why the skeletal muscle mass diminishes as the disease progress while it remains stable in early stages. This might be attributed to the high rest energy expenditure due to increased work of breathing in combination with inadequate dietary intake,18 to physical inactivity due to exercise intolerance,2 to excessive apoptosis of skeletal muscle due to increased systemic inflammation,19 and/or to the presence of hypoxia and the more frequent use of systemic corticosteroids.1 Although our study does not provide any data in order to confirm the above theories, it is important to emphasize that the other study variables presented similar findings in early stages, in parallel with the FFMI differences. Specifically, low exercise capacity (as expressed by 6MWD and Borg values), progressively deteriorating chronic dyspnea (as expressed by MRC scale), more severe airway obstruction and hyperinflation (as expressed by FEV1/FVC ratio and IC), and increased local airway inflammation (as expressed by sputum supernatant LTB4) may represent some of the critical factors that lead to the systemic consequences that may affect the FFMI as the disease progresses. This is partially confirmed by our findings, where FFMI significantly correlated with chronic dyspnea and airway obstruction and limitation in the whole study population, and by the fact that this significant relation did not exist in early stages of the disease. However, regarding the relation between FFMI and exercise capacity, this existed from the early stages, confirming a previous study20 supporting that skeletal muscle mass is diminished from the early stages of COPD and leads to mild exercise inability that can be improved through a rehabilitation program. It still remains a controversial issue whether muscle wasting represents the defect that leads to diminished exercise capacity, or it is the result of a multifactorial process, by which low exercise capacity in relation to severe obstruction, airflow limitation, and progressive dyspnea lead to loss of skeletal mass. A possible explanation in this issue might be provided by a study that would examine whether low FFMI represents a risk factor for more severe COPD developing earlier.
Another interesting finding in this study is the association between MRC scale and FFMI values. This might be related to the fact that actually MRC represents exercise capacity and inability, and this is the main reason that in combination with 6MWD are the stronger parameters related to the FFMI values variance. This was not observed for BMI, indicating that apart from airflow limitation FFMI is more significantly related to exercise capacity compared to BMI. Surprisingly, less potent yet significant correlations between FFMI and FEV1%pred, as well as with FEV1/FVC ratio, were observed in this study. This finding might be explained by the fact that exercise capacity and functional dyspnea are considered more critical parameters compared to airflow limitation and airway obstruction in the assessment of nutritional depletion.
A previous study21 showed that alterations in skeletal muscle mass influenced health-related quality of life mainly due to the increased dyspnea. Our initial hypothesis was that nutritional depletion might affect the quality of life and mainly the emotional part of CRQ questionnaire. However, no significant relation was observed in the present study, indicating that nutritional status is not the critical factor that affects the emotional part of quality of life. The absence of significant correlations between FFMI and markers of airway inflammation might be explained by the fact that systemic rather than local inflammation correlates better with alterations in weight loss.22
Our study has some limitations. Firstly, our COPD patients were not characterized as malnutritioned and were not classified on the basis of the presence of emphysema. However, in the Greek COPD population, the malnutritioned type is not the common one due to Greek nutritional habits, which are based on the Mediterranean diet that is already known worldwide. Additionally, it is generally difficult to distinguish patients with predominant chronic bronchitis and emphysema since there is a significant overlap. The second limitation is that bioelectrical impedance may be less precise than other techniques, such as the MRI and dual–x-ray absorptiometry, for the assessment of FFM.
Factors that could limit the use of bioelectrical impedance analysis are apparent old age; severe underlying condition; specific disease states, such as cancer, insulin dependent diabetes, and renal failure; and, finally, patients with noncontrolled hydration (usually in apparent heart failure). In our study, we tried to diminish the above limitations by excluding older, unstable patients, those with specific disease states, as well as those with clinically apparent heart failure. However, in the recently published literature, FFMI has repeatedly been assessed by the use of a simpler and more easily accessible method, such as bioelectrical impedance.2324
If we take into account that FFMI represents a significant determinant of COPD mortality,7 is diminished even in well-nourished patients, and also consider that 6MWD represents another predictor of mortality,25 then the combination of our results that showed a close relationship between the two variables suggest that they should be involved in the routine daily assessment of COPD. Furthermore, we believe that the next step for FFMI evaluation is to investigate whether a close relationship between FFMI initial values and disease progression exists.
In conclusion, we report that nutritional status is mainly related to exercise capacity. FFMI, a significant predictor of mortality in COPD, seems to be more accurate in expressing variables of disease severity compared to BMI.
Footnotes
Abbreviations: BMI = body mass index; Borg = difference in breathlessness in Borg scale; CRQ = chronic respiratory disease questionnaire; FEV1%pred = percentage of predicted FEV1; FFM = fat-free mass; FFMI = fat-free mass index; GOLD = Global Initiative for Chronic Obstructive Lung Disease; IC = inspiratory capacity; LTB4 = leukotriene B4; MRC = Medical Research Council; 6MWD = 6-min walk distance
This work was performed at the Department of Pneumonology, Veterans Hospital of Athens, Greece.
The authors have no conflicts of interest to disclose.
Received for publication November 16, 2006. Accepted for publication March 7, 2007.
References
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; stage I, n = 20 
; stage II, n = 20 
; stage III, n = 20 
; stage IV, n = 20 
. Each symbol represents one individual. Significantly lower values were observed in stage 0, p > 0.0001; significantly higher values were observed in stage I (p < 0.05) when stage 0 patients were excluded. Horizontal bars represent mean values.