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Body composition, energy expenditure and physical activity

Raw BIA variables are predictors of muscle strength in patients with chronic obstructive pulmonary disease

Abstract

Background/Objectives:

Although loss of fat-free mass (FFM) and reduced muscle strength are highly prevalent in chronic obstructive pulmonary disease (COPD), only few data are available on the relationships of handgrip strength (HGS) and respiratory muscle strength with body composition in such disease. In particular, we aimed to assess whether raw bioelectrical impedance (BIA) variables were independent predictors of muscle strength in COPD patients, possibly more significant than anthropometric variables and BIA-based estimates of FFM.

Subjects/Methods:

Two hundred and thirty-seven COPD patients (161 males and 76 females) underwent respiratory, anthropometric, BIA, HGS and respiratory muscle strength (maximum inspiratory or expiratory pressure=MIP and MEP) measurements. Bioimpedance index (BI index=height square/whole-body impedance) and phase angle (PhA) were considered as raw BIA variables. FFM was estimated using three disease-specific BIA equations.

Results:

In COPD patients a stronger correlation was observed between HGS and PhA compared to the ones with anthropometric variables or FFM estimates. Multiple regression analysis showed that combining BI index and PhA (plus age in male patients) accounted for 50.2% and 42.6% of the variance in HGS in male and female patients, respectively. Similarly, BI index and PhA emerged as predictors of both MIP and MEP in males, while in females MIP was related only to PhA and MEP only to BI index.

Conclusions:

Raw BIA variables are independent and valuable predictors of HGS and respiratory muscle strength in COPD patients. BI index and PhA could provide useful information for evaluating body composition and better assessing muscle strength and physical fitness in COPD.

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References

  1. 1

    Nyberg A, Saey D, Maltais F . Why and how limb muscle mass and function should be measured in patients with chronic obstructive pulmonary disease. Ann Am Thorac Soc 2015; 12: 1269–1277.

    Article  Google Scholar 

  2. 2

    Maltais F, Decramer M, Casaburi R, Barreiro E, Burelle Y, Debigarè R et al. An official American Thoracic Society/European Respiratory Society statement: update on limb muscle dysfunction in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 2014; 189: e15–e62.

    Article  Google Scholar 

  3. 3

    Shoup R, Dalsky G, Warner S, Davies M, Connors M, Khan M et al. Body composition and health-related quality of life in patients with obstructive airways disease. Eur Respir J 1997; 10: 1576–1580.

    CAS  Article  Google Scholar 

  4. 4

    Schols AM, Broekhuizen R, Weling-Scheepers CA, Wouters EF . Body composition and mortality in chronic obstructive pulmonary disease. Am J Clin Nutr 2005; 82: 53–59.

    CAS  Article  Google Scholar 

  5. 5

    Schols AM, Ferreira IM, Franssen FM, Gosker HR, Janssens W, Muscaritoli M et al. Nutritional assessment and therapy in COPD: a European Respiratory Society statement. Eur Respir J 2014; 44: 1504–1520.

    Article  Google Scholar 

  6. 6

    Earthman CP . Body composition tools for assessment of adult malnutrition at the bedside: a tutorial on research considerations and clinical applications. J Parenter Enteral Nutr 2015; 39: 787–822.

    Article  Google Scholar 

  7. 7

    Earthman C, Traughber D, Dobratz J, Howell W . Bioimpedance spectroscopy for clinical assessment of fluid distribution and body cell mass. Nutr Clin Pract 2007; 22: 389–405.

    Article  Google Scholar 

  8. 8

    Maddocks M, Kon SS, Jones SE, Canavan JL, Nolan CM, Higginson IJ et al. Bioelectrical impedance phase angle relates to function, disease severity and prognosis in stable chronic obstructive pulmonary disease. Clin Nutr 2015; 34: 1245–1250.

    Article  Google Scholar 

  9. 9

    Norman K, Stobaus N, Zocher D, Bosy-Westphal A, Szramek A, Scheufele R et al. Cutoff percentiles of bioelectrical phase angle predict functionality, quality of life, and mortality in patients with cancer. Am J Clin Nutr 2010; 92: 612–619.

    CAS  Article  Google Scholar 

  10. 10

    Mulasi U, Kuchnia AJ, Cole AJ, Earthman CP . Bioimpedance at the bedside: current applications, limitations, and opportunities. Nutr Clin Pract 2015; 30: 180–193.

    Article  Google Scholar 

  11. 11

    de Blasio F, Santaniello MG, De Blasio F, Miracco Berlingieri G, Bellofiore B, Scalfi L . BIoelectrical impedance analysis (bia) in the assessment of muscular function in patients suffering from copd. Chest 2014; 145: 468A–468A.

    Article  Google Scholar 

  12. 12

    de Blasio F, de Blasio F, Miracco Berlingieri G, Bianco A, La Greca M, Franssen FM et al. Evaluation of body composition in COPD patients using multifrequency bioelectrical impedance analysis. Int J Chron Obstruct Pulmon Dis 2016; 11: 2419–2426.

    Article  Google Scholar 

  13. 13

    Baumgartner RN, Chumlea WC, Roche AF . Bioelectric impedance phase angle and body composition. Am J Clin Nutr 1988; 48: 16–23.

    CAS  Article  Google Scholar 

  14. 14

    Gonzalez MC, Barbosa-Silva TG, Bielemann RM, Gallagher D, Heymsfield SB . Phase angle and its determinants in healthy subjects: influence of body composition. Am J Clin Nutr 2016; 103: 712–716.

    CAS  Article  Google Scholar 

  15. 15

    Abbatecola AM, Fumagalli A, Spazzafumo L, Betti V, Misuraca C, Corsonello A et al. Body composition markers in older persons with COPD. Age Ageing 2014; 43: 548–553.

    Article  Google Scholar 

  16. 16

    Swallow EB, Reyes D, Hopkinson NS, Man WD, Porcher R, Cetti EJ et al. Quadriceps strength predicts mortality in patients with moderate to severe chronic obstructive pulmonary disease. Thorax 2007; 62: 115–120.

    Article  Google Scholar 

  17. 17

    Cortopassi F, Celli B, Divo M, Pinto-Plata V . Longitudinal changes in handgrip strength, hyperinflation, and 6-minute walk distance in patients with COPD and a control group. Chest 2015; 148: 986–994.

    Article  Google Scholar 

  18. 18

    Gosselink R, Troosters T, Decramer M . Peripheral muscle weakness contributes to exercise limitation in COPD. Am J Respir Crit Care Med 1996; 153: 976–980.

    CAS  Article  Google Scholar 

  19. 19

    Shah S, Nahar P, Vaidya S, Salvi S . Upper limb muscle strength & endurance in chronic obstructive pulmonary disease. Indian J Med Res 2013; 138: 492–496.

    PubMed  PubMed Central  Google Scholar 

  20. 20

    Heijdra YF, Pinto-Plata V, Frants R, Rassulo J, Kenney L, Celli BR . Muscle strength and exercise kinetics in COPD patients with a normal fat-free mass index are comparable to control subjects. Chest 2003; 124: 75–82.

    Article  Google Scholar 

  21. 21

    Pleguezuelos E, Esquinas C, Moreno E, Guirao L, Ortiz J, Garcia-Alsina J et al. Muscular Dysfunction in COPD: Systemic Effect or Deconditioning? Lung 2016; 194: 249–257.

    CAS  Article  Google Scholar 

  22. 22

    Puhan MA, Siebeling L, Zoller M, Muggensturm P, ter Riet G . Simple functional performance tests and mortality in COPD. Eur Respir J 2013; 42: 956–963.

    Article  Google Scholar 

  23. 23

    Burtin C, Ter Riet G, Puhan MA, Waschki B, Garcia-Aymerich J, Pinto-Plata V et al. Handgrip weakness and mortality risk in COPD: a multicentre analysis. Thorax 2016; 71: 86–87.

    Article  Google Scholar 

  24. 24

    Engelen MP, Schols AM, Baken WC, Wesseling GJ, Wouters EF . Nutritional depletion in relation to respiratory and peripheral skeletal muscle function in out-patients with COPD. Eur Respir J 1994; 7: 1793–1797.

    CAS  Article  Google Scholar 

  25. 25

    Mostert R, Goris A, Weling-Scheepers C, Wouters EF, Schols AM . Tissue depletion and health related quality of life in patients with chronic obstructive pulmonary disease. Respir Med 2000; 94: 859–867.

    CAS  Article  Google Scholar 

  26. 26

    Yilmaz D, Capan N, Canbakan S, Besler HT . Dietary intake of patients with moderate to severe COPD in relation to fat-free mass index: a cross-sectional study. Nutr J 2015; 14: 35.

    Article  Google Scholar 

  27. 27

    Vermeeren MA, Creutzberg EC, Schols AM, Postma DS, Pieters WR, Roldaan AC et al. Prevalence of nutritional depletion in a large out-patient population of patients with COPD. Respir Med 2006; 100: 1349–1355.

    CAS  Article  Google Scholar 

  28. 28

    Kurosaki H, Ishii T, Motohashi N, Motegi T, Yamada K, Kudoh S et al. Extent of emphysema on HRCT affects loss of fat-free mass and fat mass in COPD. Intern Med 2009; 48: 41–48.

    Article  Google Scholar 

  29. 29

    Hillman CM, Heinecke EL, Hii JW, Cecins NM, Jenkins SC, Eastwood PR . Relationship between body composition, peripheral muscle strength and functional exercise capacity in patients with severe chronic obstructive pulmonary disease. Intern Med J 2012; 42: 578–581.

    CAS  Article  Google Scholar 

  30. 30

    Kyle UG, Janssens JP, Rochat T, Raguso CA, Pichard C . Body composition in patients with chronic hypercapnic respiratory failure. Respir Med 2006; 100: 244–252.

    Article  Google Scholar 

  31. 31

    Gologanu D, Ionita D, Gartonea T, Stanescu C, Bogdan MA . Body composition in patients with chronic obstructive pulmonary disease. Maedica 2014; 9: 25–32.

    PubMed  PubMed Central  Google Scholar 

  32. 32

    Nishimura Y, Tsutsumi M, Nakata H, Tsunenari T, Maeda H, Yokoyama M . Relationship between respiratory muscle strength and lean body mass in men with COPD. Chest 1995; 107: 1232–1236.

    CAS  Article  Google Scholar 

  33. 33

    Global Strategy for the Diagnosis, Management and Prevention of COPD, Global Initiative for Chronic Obstructive Lung Disease (GOLD) 2017. Available from http://goldcopd.org.

  34. 34

    Miller MR, Hankinson J, Brusasco V, Burgos F, Casaburi R, Coates A et al. Standardisation of spirometry. Eur Respir J 2005; 26: 319–338.

    CAS  Article  Google Scholar 

  35. 35

    Vestbo J, Hurd SS, Agusti AG, Jones PW, Vogelmeier C, Anzueto A et al. Global strategy for the diagnosis, management, and prevention of chronic obstructive pulmonary disease: GOLD executive summary. Am J Respir Crit Care Med 2013; 187: 347–365.

    CAS  Article  Google Scholar 

  36. 36

    Heitmann BL . Impedance: a valid method in assessment of body composition? Eur J Clin Nutr 1994; 48: 228–240.

    CAS  PubMed  Google Scholar 

  37. 37

    Rutten EP, Spruit MA, Wouters EF . Critical view on diagnosing muscle wasting by single-frequency bio-electrical impedance in COPD. Respir Med 2010; 104: 91–98.

    Article  Google Scholar 

  38. 38

    Steiner MC, Barton RL, Singh SJ, Morgan MD . Bedside methods versus dual energy X-ray absorptiometry for body composition measurement in COPD. Eur Respir J 2002; 19: 626–631.

    CAS  Article  Google Scholar 

  39. 39

    Kyle UG, Pichard C, Rochat T, Slosman DO, Fitting JW, Thiebaud D . New bioelectrical impedance formula for patients with respiratory insufficiency: comparison to dual-energy X-ray absorptiometry. Eur Respir J 1998; 12: 960–966.

    CAS  Article  Google Scholar 

  40. 40

    Ling CH, Taekema D, de Craen AJ, Gussekloo J, Westendorp RG, Maier AB . Handgrip strength and mortality in the oldest old population: the Leiden 85-plus study. CMAJ 2010; 182: 429–435.

    Article  Google Scholar 

  41. 41

    Vaz M, Thangam S, Prabhu A, Shetty PS . Maximal voluntary contraction as a functional indicator of adult chronic undernutrition. Br J Nutr 1996; 76: 9–15.

    CAS  Article  Google Scholar 

  42. 42

    Black LF, Hyatt RE . Maximal respiratory pressures: normal values and relationship to age and sex. Am Rev Respir Dis 1969; 99: 696–702.

    CAS  PubMed  Google Scholar 

  43. 43

    Fletcher CM, Elmes PC, Fairbairn AS, Wood CH . The significance of respiratory symptoms and the diagnosis of chronic bronchitis in a working population. Br Med J 1959; 2: 257–266.

    CAS  Article  Google Scholar 

  44. 44

    Celli BR, Cote CG, Marin JM, Casanova C, Montes de Oca M, Mendez RA et al. The body-mass index, airflow obstruction, dyspnea, and exercise capacity index in chronic obstructive pulmonary disease. N Engl J Med 2004; 350: 1005–1012.

    CAS  Article  Google Scholar 

  45. 45

    Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing 2010; 39: 412–423.

    Article  Google Scholar 

  46. 46

    Norman K, Stobaus N, Pirlich M, Bosy-Westphal A . Bioelectrical phase angle and impedance vector analysis—clinical relevance and applicability of impedance parameters. Clin Nutr 2012; 31: 854–861.

    Article  Google Scholar 

  47. 47

    Elia M . Body composition by whole-body bioelectrical impedance and prediction of clinically relevant outcomes: overvalued or underused? Eur J Clin Nutr 2013; 67: S60–S70.

    Article  Google Scholar 

  48. 48

    Basile C, Della-Morte D, Cacciatore F, Gargiulo G, Galizia G, Roselli M et al. Phase angle as bioelectrical marker to identify elderly patients at risk of sarcopenia. Exp Gerontol 2014; 58: 43–46.

    Article  Google Scholar 

  49. 49

    de Blasio F, Santaniello MG, de Blasio F, Berlingieri GM, Bellofiore B, Scalfi L . Bioelectrical impedance analysis (BIA) in the assessment of muscular function in patients suffering from COPD. Chest 2014; 145: 468A.

    Article  Google Scholar 

  50. 50

    Norman K, Wirth R, Neubauer M, Eckardt R, Stobaus N . The bioimpedance phase angle predicts low muscle strength, impaired quality of life, and increased mortality in old patients with cancer. J Am Med Dir Assoc 2015; 16: 117–122.

    Article  Google Scholar 

  51. 51

    Hodgev VA, Kostianev SS . Maximal inspiratory pressure predicts mortality in patients with chronic obstructive pulmonary disease in a five-year follow-up. Folia Med 2006; 48: 36–41.

    Google Scholar 

  52. 52

    Gea J, Agusti A, Roca J . Pathophysiology of muscle dysfunction in COPD. J Appl Physiol (1985) 2013; 114: 1222–1234.

    CAS  Article  Google Scholar 

  53. 53

    Polkey MI, Kyroussis D, Hamnegard CH, Mills GH, Green M, Moxham J . Diaphragm strength in chronic obstructive pulmonary disease. Am J Respir Crit Care Med 1996; 154: 1310–1317.

    CAS  Article  Google Scholar 

  54. 54

    Vilaró J, Ramirez-Sarmiento A, Martínez-Llorens JM, Mendoza T, Alvarez M, Sánchez-Cayado N et al. Global muscle dysfunction as a risk factor of readmission to hospital due to COPD exacerbations. Respir Med 2010; 104: 1896–1902.

    Article  Google Scholar 

  55. 55

    Luo Y, Zhou L, Li Y, Guo S, Li X, Zheng J et al. Fat-free mass index for evaluating the nutritional status and disease severity in COPD. Respir Care 2016; 61: 680–688.

    Article  Google Scholar 

  56. 56

    Sabino PG, Silva BM, Brunetto AF . Nutritional status is related to fat-free mass, exercise capacity and inspiratory strength in severe chronic obstructive pulmonary disease patients. Clinics 2010; 65: 599–605.

    Article  Google Scholar 

  57. 57

    Hui D, Bansal S, Morgado M, Dev R, Chisholm G, Bruera E . Phase angle for prognostication of survival in patients with advanced cancer: preliminary findings. Cancer 2014; 120: 2207–2214.

    Article  Google Scholar 

  58. 58

    Ferreira IM, Brooks D, White J, Goldstein R . Nutritional supplementation for stable chronic obstructive pulmonary disease. Cochrane Database Syst Rev 2012; 12: Cd000998.

    PubMed  Google Scholar 

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Correspondence to F de Blasio.

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LS designed the research. FdB, MGS and FrdB conducted the research. FdB and LS analyzed the data and performed statistical analysis, which was reviewed by FMEF, LL, AB and GM. FdB and LS produced a first draft of the manuscript and had primary responsibility for final content. All authors read and approved the final manuscript.

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de Blasio, F., Santaniello, M., de Blasio, F. et al. Raw BIA variables are predictors of muscle strength in patients with chronic obstructive pulmonary disease. Eur J Clin Nutr 71, 1336–1340 (2017). https://doi.org/10.1038/ejcn.2017.147

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