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 Table of Contents  
ORIGINAL ARTICLE
Year : 2013  |  Volume : 27  |  Issue : 2  |  Page : 115-120

Comparison of nutritional status in chronic obstructive pulmonary disease and asthma


Department of Pulmonary Medicine, Vallabhbhai Patel Chest Institute, University of Delhi, Delhi, India

Date of Web Publication4-Jan-2014

Correspondence Address:
Shailendra Nath Gaur
Department of Pulmonary Medicine, Vallabhbhai Patel Chest Institute, University of Delhi, Delhi - 110 007
India
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Source of Support: None, Conflict of Interest: None


DOI: 10.4103/0972-6691.124393

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  Abstract 

Introduction: The loss of body mass leading to cachexia is known to exist in chronic obstructive pulmonary disease (COPD). However, the role of body composition in asthmatics has not been widely explored. Materials and Methods: Body weight (BW), body mass index (BMI), percentage of ideal BW (PIBW), fat mass (FM), fat free mass index (FFMI), and midthigh cross-sectional were evaluated in COPD (n = 40) and asthma (n = 40) and compared with 20 healthy controls. Socioeconomic status served as a marker of dietary adequacy. Results: Weight (P < 0.001), BMI (P < 0.01), FMI (P < 0.05), and FFMI (P < 0.001) differed significantly among socioeconomic classes. Significant intergroup differences of weight and FFMI in the upper (P < 0.05) and BMI and PIBW in the upper-middle class (P < 0.05) were seen. BW in COPD was lower than bronchial asthma (BA) (P < 0.001) and controls (P < 0.001). BMI in COPD was lower than BA (P < 0.000) as were PIBW (P < 0.000) and FM (P < 0.001), whereas neither study group differed from controls. FFMI in COPD was lower than BA (P < 0.004) and controls (P < 0.01). No parameter differed between BA and control groups. Comparing by severity of airflow obstruction, all parameters were reduced in COPD, but statistical significance (P < 0.05) was noted for BMI and FFMI in mild/moderate cases and weight, BMI, PIBW, and FM in severe/very severe cases. No significant differences were noted when assessed with respect to severity of either disease. Correlations were noted between FFMI and post bronchodilator forced expiratory volume in the 1 st second (FEV) 1 (r = 0.342) and weight and post bronchodilator FEV 1 (r = 0.322) in COPD. Conclusion: COPD produces malnutrition with regards to both fat and fat free components, irrespective of the severity of the disease, whereas asthma bears no such association.

Keywords: Asthma, chronic obstructive pulmonary disease, fat free mass, fat mass, nutritional assessment


How to cite this article:
Agarwal K, Sharma L, Menon B, Gaur SN. Comparison of nutritional status in chronic obstructive pulmonary disease and asthma. Indian J Allergy Asthma Immunol 2013;27:115-20

How to cite this URL:
Agarwal K, Sharma L, Menon B, Gaur SN. Comparison of nutritional status in chronic obstructive pulmonary disease and asthma. Indian J Allergy Asthma Immunol [serial online] 2013 [cited 2019 Sep 17];27:115-20. Available from: http://www.ijaai.in/text.asp?2013/27/2/115/124393


  Introduction Top


Chronic obstructive pulmonary disease (COPD) is characterized by airflow obstruction produced by an inflammatory response to inhaled noxious particulate or gaseous matter. [1] COPD is conceptualized as a 'syndrome' that affects almost all body systems. Nutritional status disturbances and skeletal muscle weakness are among the most common extrathoracic manifestations of the disease. [2] Loss of body mass produces disturbances in breathing physiology; diminution of diffusion capacity and increased air-trapping occur as a consequence of dyspnea and vice versa. [2] Nearly 25% of patients with COPD develop cachexia, principally due to the loss of tissue mass other than fat, which is associated with up to 50% reduction in median survival. [3] Thus, loss of body mass in COPD is a loss of fat free mass (FFM) consisting mainly of muscles, with a relative increase or no change in fat mass (FM). [4] Cachexia in COPD is said to exist when body mass index (BMI) <21 kg/m 2 . However, BMI does not differentiate two people with similar BMI but different body compositions. Even those patients with COPD who have normal BMI have high chances of low FFM. Since FFM index (FFMI) is a prognostic marker, assessment of FFM provides important information in COPD and should be evaluated routinely in. [5] Thus, it has been proposed that cachexia be defined by FFMI. [3] In contrast to COPD, body composition and specifically, FFM has not been extensively evaluated in asthma. [6]


  Materials and Methods Top


This study was conducted with the approval of the Institutional Ethics Committee between September 2009 and April 2011 in order to evaluate markers of nutritional status such as body weight (BW), BMI, percentage of ideal BW (PIBW), FM, FFMI, and midthigh cross-sectional area by computed tomogram scan (MTCSA CT ) and to find the correlation of these indices of nutritional status with the severity of the disease in patients with COPD and asthma. Forty clinically stable patients of both sexes ≥40 years of age with COPD or asthma diagnosed as per the Global Initiative for Chronic Obstructive Lung Disease (GOLD) [1] and Global Initiative for Asthma (GINA) [7] guidelines, respectively; not on systemic steroids, normal radiograph, and with an acceptable spirometric performance with a forced expiratory volume (FEV) 1 /forced vital capacity (FVC) ratio <70% were enrolled in the study through a written informed consent. Patients with any other comorbidity such as diabetes mellitus, chronic systemic or localized infections, renal failure, hepatocellular failure, heart failure, malignancies, etc.; lactating and pregnant women; and those with a history of use of systemic steroids, antibiotics, or hospitalization for an exacerbation within past 4 weeks were excluded from the study. Cases were compared to 20 healthy volunteers who served as controls. All study subjects were subjected to a through clinical examination and routine laboratory investigations such as hemogram, urine examination, chest roentgenogram, serum lipids, serum proteins, kidney and liver function tests, fasting and postprandial blood sugar, and electrocardiogram. Spirometry was performed on a computerized apparatus-Benchmark (P. K. Morgan and Co. Ltd. Chatham, Kent, England) and at least three acceptable and reproducible maneuvers were obtained and FVC, FEV 1 , and FEV 1 /FVC% were recorded. [8]

The disease severity in the study subjects was classified as proposed in the GOLD [1] and GINA [7] guidelines for COPD and asthma, respectively. Further, to enable a comparison between the two disease groups, patients in both these groups were classified for the severity of airflow obstruction as proposed by the American Thoracic Society/European Respiratory Society (ATS/ERS) Task Force. [9] Cases as well as controls were stratified for their socioeconomic status which was used as a marker of dietary adequacy. [10]

Study parameters

The outcome parameters of the study: BW, PIBW, BMI, FM, FFMI, and MTCSA CT were measured as per the standard method. The skin-fold thickness was obtained at four locations: Biceps, triceps, subscapular, and suprailiac regions. PIBW was deduced using the Broca's formula. [11] FM was calculated using the method of Durnin and Wormsley, [12] while the FFM was obtained by subtracting FM from the BW. BMI was classified as per the international classification. [13] FFMI was derived by dividing the FFM by the height in meters squared. A computed tomogram (CT) of the right and left thigh, halfway between the pubic symphysis and the inferior condyle of the femur was performed using Siemens SOMATOM Plus 4 scanner. Each image, 10-mm thick, was taken at 120 KV and 200 mA with a scanning time of 1 s with the subject supine. Thigh muscle cross-sectional area (CSA) was obtained by measuring the surface area of the tissue with a density of 40-100 Hounsfield units (HU) after exclusion of bone and fat components. The MTCSA CT was calculated by averaging the values for right and left thighs.

Statistical analysis

Statistical analysis was carried out using Statistical Package for Social Sciences (SPSS) 16.0 (IBM Corporation Software Group, Somers, NY, USA) and GraphPad Prism 4.01 (GraphPad Software, Inc. La Jolla, CA 92037 USA) software. The data was examined for distribution and homogeneity of variances was checked before applying parameters tests.

The following tests were used: (i) Unpaired t-test to compare independent groups (asthma vs. COPD), (ii) analysis of variance (ANOVA) to compare multiple groups (control, asthma, and COPD) followed by Bonferroni's test for post-hoc between group comparisons of ANOVA indicated significant differences, and (iii) Chi-square (χ2 ) test to compare proportions.


  Results Top


Among the 40 patients with COPD, two had mild, 15 moderate, 20 severe, and three very severe COPD as classified by GOLD. [1] Of the 40 asthmatics, four had mild intermittent, 21 moderate-persistent, and 15 severe-persistent asthma as defined by GINA. [7] Classifying for the severity of airflow limitation, [9] in the COPD group two had mild, 10 moderate, 19 severe, and nine very severe airflow limitation; while 11 asthmatics had mild, 20 moderate, seven severe, and two very severe airflow limitation. Further, patients with COPD were clubbed into two categories, combining mild-moderate stages into one and severe-very severe stages into another group. Likewise patients with mild intermittent and moderate persistent asthma were clubbed together in one and those with severe persistent asthma into another group. Thus, there were 17 patients in the mild/moderate and 23 patients in the severe/very severe stage of COPD and 25 in the intermittent/moderate persistent and 15 in severe groups in asthma. Similarly, for purpose of statistical analysis and to address the objectives of the study, the COPD and asthma groups based on severity of airflow obstruction were also clubbed as mild/moderate and severe/very severe. Subsequently, there were 12 patients in mild/moderate and 28 patients in severe/very severe groups of COPD and 31 patients in mild/moderate and nine in the severe/very severe groups of asthma.

Sociodemographic parameters

The distribution of sociodemographic and study parameters (mean ± 2 standard deviation (SD)) of the subjects are presented in [Table 1]. Those with COPD had significantly a higher mean age in comparison to asthmatics as well as controls. Out of 40 COPD patients, 32 were males and eight were females; while in BA, 25 were males and 15 females. Among the 20 controls, 17 were males and three females. When the distribution of the study parameters was studied with respect to socioeconomic status [Table 2], the distribution of weight (P < 0.001), BMI (P < 0.01), FMI (P < 0.05), and FFMI (P < 0.001) differed significantly (P < 0.001) among different socioeconomic classes. Also, significant intergroup differences were observed in terms of weight and FFMI in the upper class (P < 0.05) and BMI and PIBW in the upper-middle class (P < 0.05).
Table 1: Distribution of descriptive parameters in the study and control groups

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Table 2: Distribution of study parameters among different socioeconomic categories

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Study parameters

[Table 1] depicts the distribution of demographic variables and parameters in the study and control groups. Upon stratifying the study population using BMI, 11 subjects were underweight (eight COPD, two asthma, and one control), 28 overweight (seven COPD, 16 asthma, and five controls), and seven obese (one COPD, five asthma, and one control) (P < 0.05). Defined through PIBW (PIBW < 90% and PIBW >90%, respectively), malnutrition was observed in 15 patients with COPD, four with asthma, and five controls (P < 0.05). When malnutrition was defined by FFMI (<15 kg/m 2 for females and <16 kg/m 2 for males), 22 patients with COPD, 14 asthmatics, and eight controls were malnourished (P > 0.05). In addition to the intergroup differences explained above, no significant intragroup differences in any of the study parameters were observed when their distribution was assessed with respect to the severity of disease. However, on comparing the study parameters based on the degree of airflow obstruction, as per the ATS/ERS classification, all the nutritional parameters were quantitatively lower in COPD patients than in asthmatics [Table 3] and [Table 4].

No significant difference was noted between the serum protein or lipid concentrations of either of the study and control groups or between patients with different severities of COPD and asthma [Table 1]. Similarly, no significant difference was found in the study groups using the MTCSA CT .
Table 3: Comparison of mild/moderate airflow obstruction in COPD and asthma (ATS severity)

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Table 4: Comparison of severe-very severe airflow obstruction in COPD and asthma

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Relationship between PFT and study parameters

There were significant correlation between FFMI and post bronchodilator FEV 1 (mL) (Pearson coefficient, r = 0.342) in asthmatics and weight and post bronchodilator FEV 1 (mL) (Pearson coefficient, r = 0.322) in COPD.


  Discussion Top


This study was planned on the working hypothesis that both COPD and asthma have an impact on nutritional status and there are changes in the nutritional indices in both diseases with increase in severity. In this study, socioeconomic status was used as a surrogate marker for dietary adequacy. In general, majority of the patients belonged to the upper middle class. However, the number of COPD patients in lower socioeconomic status was significantly more as compared to asthmatics and controls. Four of our study parameters (weight, BMI, FM, and FFMI) differed significantly among different socioeconomic categories implying thereby, that socioeconomic status does affect the nutritional status and thus, could be a confounding factor in our study. However, significant differences between COPD and asthma patients were noted for weight and FFMI in the upper class; weight, BMI, and PIBW in the upper middle class; while no significant differences were seen in the other two categories which indicate that the diseases do have an independent effect on nutritional status even after stratifying by socioeconomic status. There was no significant correlation of age, duration of illness, and pack years of smoking with study parameters in COPD which signifies that the disease itself produces malnutrition and is not affected by the duration of disease, smoking, or age.

With regards to the study parameters, it was seen that the average weight of the COPD group was significantly lesser than asthmatics as well as controls, whereas no such difference was observed between the asthma and control groups; thereby implying that those affected by COPD tend to have a lower BW than the healthy population as well as asthmatics. This can be explained by the fact that resting energy expenditure and the oxygen cost of augmented ventilation are higher in patients with COPD who thus, lose more weight than patients with a stable weight or are healthy. [14]],[[15]],[[16] Additionally, no significant differences existed in the distribution of BWs of the study subjects of either group when stratified by the clinical severity of the disease or by the degree of airflow limitation. However, a correlation between the BW and post bronchodilator FEV 1 (r = 0.322) was seen in the COPD group, implying a favorable effect of a greater body mass on the management of COPD.

The BMI of patients with COPD was found to be significantly lower than asthmatics, but no significant differences of this parameter were found between either study groups when compared to controls. This finding was in concordance with that of Ran et al.,[17] but was in contrast to the findings of Kuznar-Kaminska et al.[2] It was also reported that BMI was inversely proportional to the severity of COPD (P < 0.01) which was however, not observed in our study. Although many studies have been undertaken to analyze the relationship between high BMI/obesity and the risk of developing asthma, [18],[19],[20],[21],[22],[23],[24],[25],[26],[27],[28] very few studies have analyzed the impact of BMI on the severity of asthma. Although Varrasso et al.,[28] found that asthma severity in women was directly proportional to BMI; our study failed to demonstrate any such relationship in either of the sexes. It was also seen that while a majority (60%) of COPD patients had normal weight, 20% of COPD patients were underweight and 20% were overweight or obese. In contrast, majority (57.5%) of asthmatics were overweight or obese with only 5% patients falling in the underweight category. These findings indicate that though patients with COPD maintained a normal BMI, malnutrition (assessed by BMI) was present in a small proportion of COPD patients; whereas, asthma was associated with weight gain. These findings were in consonance with other studies done in patients with COPD [29] and asthma. [30]

The PIBW of COPD patients was significantly lower compared to asthmatics. Malnutrition (PIBW < 90%) was present in 24% subjects, of which 37.5% were patients with COPD. This percentage was higher in comparison with other studies in which malnutrition was found in 5.45-35% [2],[31],[32] of COPD patients. We did not find any significant difference in the PIBW in terms of disease severity or degree of airflow obstruction in either COPD or asthma. Also, no significant correlation between PIBW and lung function parameters in COPD was seen. However, FEV 1 /FVC showed significant correlation (r = 0.348) with PIBW in asthma.

Body mass can be divided into two compartments: FM and FFM. The first is, in principle, a metabolic inactive energy store, whereas the latter refers to the mass of metabolically active organs; skeletal muscle being the largest of such organs. It is reasonable to assume that loss of or a low FFM is unfavorable. This assumption is supported by epidemiologic observations on general population from which it is known that the effects of BMI on mortality can be inferred as an inverse association between FFM and mortality and a direct relationship between FM and mortality. [5] In our study, FM of COPD patients was significantly lower compared to asthmatics, but no significant difference were seen between either of the study and control groups. Also, no significant differences were observed with increasing severity of the disease or severity of airflow limitation in either group. Moreover, there was no significant correlation between FM and lung function parameters in either study groups. This finding in the asthma group was in concordance with that of Bafadhel et al., who found no cross-sectional association between FM, airway inflammation, and lung function in patients with refractory asthma. [33] With regards to the FFM, it was seen that COPD patients had a significantly lower FFMI in comparison to asthmatics as well as controls whereas no such relationship was seen in the latter two groups. When FFMI was used to assess malnutrition (FFMI < 15 kg/m 2 for females and <16 kg/m 2 for males) in the study sample, it was observed that 55% COPD patients had low FFMI against 35% in the asthma group. Other studies have reported low FFMI in 18-20% outpatients, [2],[34] 35% inpatients, [31] and 45% of those awaiting lung transplantation; [32] depending upon the severity of the disease. Moreover, our study conforms to the findings of the study done by Kuznar-Kaminska et al.,[2] who showed that malnutrition; measured by PIBW, BMI, BMI percentiles, and FFMI was observed in 5.45, 3.64, 3.64, and 18.18% of COPD patients, respectively against 3.12, 0, 3.12, and 3.12% controls, respectively. Although, the mean BMI did not differ significantly between groups, cachexia, assessed by FFMI was seen to occur more frequently in COPD patients than in the control group (19.05 vs 20.55 kg/m 2 ; P = 0.04). Additionally, we have shown that FFMI in patients with COPD was significantly lower than that in asthmatics. Also, FFMI correlated significantly with the post bronchodilator FEV1 (absolute value) (r = 0.323) as well as % predicted (r = 0.342) in asthmatics. No such correlation was found between lung function and FFMI in COPD.

The other parameters used to assess nutritional status of study subjects in this study such as serum protein and lipid concentration did not show significant differences in the two study groups. Also, we did not find a significant difference between any of the study groups when MTCSA CT was used as a marker probably because only a small number of patients and controls got the CT done. Thus, it is difficult to draw any significant conclusions from this parameter. A limitation of this study is that an individualized dietary assessment could not be performed due to an inconsistency in the quality and quantity of dietary factors in the study subjects which rendered a comparison difficult; instead socioeconomic scale was used as a surrogate marker of dietary adequacy. Another limitation could be that since consecutive patients were enrolled in the study and were later classified into different severity groups, the numbers of patients in each category group were not comparable. Hence, we had to club the severity groups together.

We therefore conclude that COPD produces malnutrition with regards to both fat and fat free components. In contrast, bronchial asthma does not produce any malnutrition. Since the severity of COPD did not demonstrate any intergroup differences it may be concluded that it is the disease process, independent of the stage of the disease that is responsible for the malnutrition. It is recommended on the basis of this study that COPD patients be treated accordingly, with individualized overall dietary additions along with pharmacotherapy, whereas the same does not apply to asthmatics. It is suggested for further study to look for any reversal of nutritional disturbances in patients with COPD through a pulmonary rehabilitation program.

 
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  [Table 1], [Table 2], [Table 3], [Table 4]



 

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