age ageing 2011 cesari ageing afr167

8/10/2019 Age Ageing 2011 Cesari Ageing Afr167

1/4

Research Letter

Physical performance, sarcopenia and

respiratory function in older patients withchronic obstructive pulmonary disease

SIRThe aging process is characterised by a progressivedecline of skeletal muscle (or sarcopenia) which, by closelyinteracting with chronic diseases, may predispose to theonset of physical disability [1]. Chronic obstructive pulmon-ary disease (COPD) is a highly prevalent condition asso-ciated with both depleted lean mass and impaired overallhealth status in older persons [2,3]. Furthermore, lean masshas shown to be inversely associated with the Medical

Research Council dyspnoea score [4] and the Activity com-ponent of the Saint George Respiratory Questionnaire [5],and directly related to pulmonary function parameters (in-cluding Forced Expiratory Volume in 1 second [FEV1]) [4].

Recently, Spruit et al. [6] reported the absence of rela-tionship between fat-free mass and 6-minute walking test(6mWT) results in the Evaluation of COPD Longitudinallyto Identify Predictive Surrogate Endpoints (ECLIPSE)study. On the other hand, Ischaki et al. [4] previouslyreported a positive correlation between results at the6mWT (the most commonly adopted and reliable physicalperformance measure in COPD [7]) and fat-free mass. The

ECLIPSE investigators [6] explained their negative resultsby their analytical choices and the evaluation of a highernumber of potential confounders.

To our knowledge, besides of these sparse data, the rela-tionships existing among respiratory function, sarcopeniaand physical performance have never been formallyexplored in literature, especially among older persons. Aimof the present study is to verify the respective strengths ofassociations between body composition (i.e. sarcopenia)and respiratory function (i.e. FEV1) with 6mWT results inolder COPD patients.

MethodsFor details about study methods, also see Supplementarydata available in Age and Ageingonline, Appendix S1.

Study participants

Data are from 71 subjects with COPD aged 65 years andolder consecutively recruited among those attending thepulmonary medicine outpatient clinic of the UniversityHospital Campus Bio-Medico in Rome (Italy) from

December 2009 to April 2010. Diagnosis of COPD wasascertained according to the American Thoracic Society/

European Respiratory Society (ATS/ERS) guidelines [8].

Six-minute walking test

All the study participants underwent the assessment ofphysical function through the administration of the 6mWT[9]. Oxyhaemoglobin desaturation during exercise wasdened as a 4% or more decrease of oxyhaemoglobin sat-uration from baseline value occurred during the 6mWTperformance.

Sarcopenia

Body composition was assessed in all the study participantsby a dual-energy X-ray absorptiometry (DEXA), using atotal-body scan performed with a QDR Explorer (HologicInc., Bedford, MA, USA).

For the present analyses, we used two denitions of sar-copenia [10,11]. Appendicular lean mass (ALM) was calcu-lated as the sum of lean mass (in kilograms) in arms andlegs, assuming that all non-fat and non-bone tissue is skel-etal muscle. The rst measure of sarcopenia (i.e.fat-adjusted rALM), was dened by residuals of a linearregression model predicting ALM (in kilograms) fromheight (in metres) and total fat mass (in kilograms). The

second de

nition was based on residuals of a linear regres-sion model between the dependent variable ALM (in kilo-grams) and height (in metres).

Forced Expiratory Volume in 1 second

FEV1 (expressed in litres), the other independent variableof interest, was assessed using a spirometric evaluation per-formed by a bell spirometer (Biomedin, Padua, Italy)according to ATS/ERS guidelines [12].

Covariates

Clinical conditions were dened on the basis of thepatients clinical documentation. Barthel Index was alsoassessed to measure physical disability [13]. The MiniNutritional Assessment (MNA) screening score (rangingfrom 0 [severe risk of malnutrition] to 14 [no risk of mal-nutrition]) was used as a measure of nutritional status [14].

Statistical methods

The relationship of the 6mWT with sarcopenia and FEV1was explored using multiple unadjusted and adjusted linear

1

Age and Ageing2011;0: 14 The Author 2011. Published by Oxford University Press on behalf of the British Geriatrics Society.All rights reserved. For Permissions, please email: [email protected]

Age and Ageing Advance Access published December 8, 2011
http://ageing.oxfordjournals.org/lookup/suppl/doi:10.1093/ageing/afr167/-/DC1http://ageing.oxfordjournals.org/lookup/suppl/doi:10.1093/ageing/afr167/-/DC1http://ageing.oxfordjournals.org/lookup/suppl/doi:10.1093/ageing/afr167/-/DC1http://ageing.oxfordjournals.org/lookup/suppl/doi:10.1093/ageing/afr167/-/DC1http://ageing.oxfordjournals.org/lookup/suppl/doi:10.1093/ageing/afr167/-/DC1http://ageing.oxfordjournals.org/lookup/suppl/doi:10.1093/ageing/afr167/-/DC1


2/4

regression models. Each independent variable of interest(i.e. rALM, fat-adjusted rALM and FEV1) was entered sep-arately from the other two in specic linear regressionmodels (except as indicated, i.e. Models 4a and 4b). Theexistence of possible interactions of age or gender in thestudied relationships was explored by including specicinteraction terms (age or gender * independent variable ofinterest) in the unadjusted linear regression models. To

exclude the relevant multicollinearities in the adjusted linearregression models, we estimated tolerances and varianceination factors (VIFs). A P-value of 0.2, all VIFs < 5). Atthe unadjusted analyses, fat-adjusted rALM and FEV1 weresignicantly related to metres walked at the 6mWT, whereasrALM did not appear to be associated with the outcome.

When potential confounders were subsequently included inthe regression models, only FEV1 consistently showed tobe signicantly and positively associated with 6mWT

(Models 1, 2 and 3). Finally, the respiratory function param-eter conrmed its superiority in predicting physical per-formance over the sarcopenia variables, even when rALMor fat-adjusted rALM were simultaneously included withFEV1 in fully adjusted models (Models 4a and 4b).

Consistent results were obtained if analyses were per-formed considering:

(i) the 6 mWT variable dened as the percentage betweenthe participants test result and the predicted value esti-mated according to the participants age and genderand based on validated algorithms [15];

(ii) the skeletal muscle variable determined as the ratio

between lean mass and total mass; and(iii) the FEV1 variable computed as the percentage of the

predicted value based on the European Communityfor Steel and Coal (ECSC) reference values [16].

Discussion

Our results show that respiratory function is a strongerindependent predictor of 6mWT results compared with thebody composition parameters. Such close association was

conrmed even after the inclusion of a wide range ofpotential confounders in the adjusted models (includinginammation), and consistent throughout the differentoperative denitions we adopted.

Consistently with the above-mentioned ndings fromthe ECLIPSE study [6] and by Ischaki et al. [4], our nd-ings support a crude association between lean mass andphysical performance, and at the same time demonstrate

that other factors (in particular, respiratory function) mayexplain such relationship. The superiority of FEV1 inexplaining physical function may be due to the inner natureof the variables denitions. In fact, sarcopenia is denedon the basis of one-point quantitative, and not qualitative,evaluation of the skeletal muscle, thus providing a staticdimension of it. On the other hand, FEV1 is a respiratoryparameter resulting from the dynamic interactions of amultitude of systems and apparati. This is particularly trueamong the weakest and frailest subjects that may easilybecome dependent on muscle strength in the FEV1production.

Consistently with previous studies [10, 11], the

fat-adjusted denition of sarcopenia showed to slightlybetter predict physical function than the other one onlyconsidering lean mass. This conrms a role that fat massmay play in the development of the age-related muscledecline [11, 17, 18], especially in conditions (such asCOPD) characterised by a body composition shift towardsthe adipose tissue gain [19,20].

Although the spirometric exam was often considereddifcult to performed and less reliable in older persons, itsimportance and clinical relevance have recently beendemonstrated even at advanced age [21,22]. Our data showthat measuring the older patients FEV1 does not only

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Table 1.Main characteristics of the study sample

N= 71

Age (years) 75.4 (5.9)

Gender (women) 43.7

Height (m) 1.60 (0.1)

Weight (kg) 72.5 (12.6)

Current smoking 21.1

Number of clinical conditions 2.3 (1.9)

MNA screening score 12.3 (2.1)

Risk of malnutrition (MNA < 12) 22.8

Barthel index 92.0 (86.097.0)

C-reactive protein (mg/l) 1.05 (0.402.98)

FEV1 (l) 1.4 (0.4)FEV1 (% of predicted value) 70.8 (19.1)

ALM (kg) 17.96 (3.48)

Total fat mass (kg) 26.06 (8.55)

6mWT (m) 307.2 (116.6)

6mWT (% of predicted value) 73.7 (26.0)

Patients experiencing relevant oxyhaemoglobin

desaturation (4%) during exercise

13.9

Values are expressed as means (standard deviations), medians (interquartile

range) or percentages.

MNA, Mini Nutritional Assessment; FEV1, Forced Expiratory Volume in 1

second; 6mWT, 6-minute walking test.

2

Research letter


3/4

provide a useful parameter for his/her respiratory evalu-ation and treatment, but also a possible surrogate ofphysical function.

Some limitations of our study deserve consideration.The relatively small size of our sample, which could not betailored to the working hypothesis, might have limited ourndings. Our conclusions apply to an overall well-nourished population and, thus, might not be entirely truefor COPD population with a greater prevalence of malnu-trition. This does not mean that conclusions are poorlygeneralisable: a recent Spanish nutritional survey [23]reported a similar mean body mass index in a large cohortof stable COPD patients (i.e. 28 kg/m2) to our sample(i.e. 28.7 kg/m2). Moreover, the mean 6mWT resultsobtained in our population (i.e. 307.2 m walked) areconsistent with those previously reported by Sciurba et al.[24] (i.e. 308.3 m walked, including a 10% reduction due tothe methodological differences in the administration of thetest) in a large multicenter trial. We assessed body compos-ition by DEXA, a widely adopted method, but not thegold standard. Furthermore, we dened sarcopenia on thebasis of pure quantitative parameters of body composition,thus unable to provide information about the qualitativedimension of sarcopenia (e.g. muscle strength). Third

factors not considered in the present analyses (e.g. physicalactivity) might differently explain our ndings. Finally, thecross-sectional design of the study does not allow to estab-lish any cause-effect sequence among the studiedrelationships.

Body composition might be an important determinantof physical performance in older COPD patients, butFEV1 represents a stronger predictor. Research is neededto conrm this observation on larger samples with the aim

of improving our understanding of determinants of physic-al performance in a complex population such as that withCOPD.

Key points

COPD is highly prevalent in the elderly, and signicantlyassociated with both depleted lean mass and impairedoverall health status.

FEV1 is strongly associated with physical performance inolder COPD patients, more than body compositionparameters.

Body composition still represents an important determin-ant of physical performance in older COPD patients.

Supplementary data

Supplementary data mentioned in the text is available tosubscribers inAge and Ageingonline.

Conflicts of interest

None declared.

MATTEO CESARI*, CLAUDIO PEDONE, DOMENICACHIURCO,

LIVIO CORTESE, MARIA ELISABETTACONTE, SIMONE SCARLATA,

RAFFAELEA NTONELLIINCALZI

Universit Campus Biomedico-Cattedra di Geriatria, Via dei

Compositori 128, Roma 00128, Italy

Email: [email protected]*To whom correspondence should be addressed

. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .

Table 2. Results from separate linear regression models predicting 6mWT results (expressed in metres, dependent variable)from appendicular lean mass (rALM), fat-adjusted rALM or FEV1 (all per standard deviation increase) as independent

variables (considered one per each model, except for Models 4a and 4b in which FEV1 is simultaneously included withone sarcopenia definition)

Unadjusted Model 1 Model 2 Model 3 Model 4a Model 4b

rALM

Beta coefficient (95%

confidence interval)

9.42 (18.75, 37.59) 51.57 (15.29, 87.85) 26.77 (5.88, 59.41) 28.83 (8.02, 65.67) 20.07 (16.10, 56.24)

P-value 0.51 0.006 0.11 0.12 0.27

Fat-adjusted rALM



29.49 (2.15, 56.84) 42.51 (15.05, 69.98) 24.19 (0.17, 48.55) 26.10 (1.33, 53.53) 19.22 (7.92, 46.37)

P-value 0.04 0.003 0.052 0.06 0.16

FEV1



65.82 (43.06, 88.58) 53.12 (29.38, 76.86) 30.83 (7.52, 54.14) 31.99 (6.60, 57.38) 30.61 (3.66, 57.57) 29.40 (2.55, 56.25)

P-value


4/4

References

1. Roubenoff R. Sarcopenia: effects on body composition andfunction. J Gerontol A Biol Sci Med Sci 2003; 58: 10127.

2. Morley JE, Thomas DR, Wilson MM. Cachexia: pathophysi-ology and clinical relevance. Am J Clin Nutr 2006; 83:73543.

3. Gelberg J, McIvor RA. Overcoming gaps in the managementof chronic obstructive pulmonary disease in older patients:

new insights. Drugs Aging 2010; 27: 36775.4. Ischaki E, Papatheodorou G, Gaki E et al. Body mass and

fat-free mass indices in COPD: relation with variablesexpressing disease severity. Chest 2007; 132: 1649.

5. Shoup R, Dalsky G, Warner S et al. Body composition andhealth-related quality of life in patients with obstructiveairways disease. Eur Respir J 1997; 10: 157680.

6. Spruit MA, Watkins ML, Edwards LD et al. Determinants ofpoor 6-min walking distance in patients with COPD: theECLIPSE cohort. Respir Med 2010; 104: 84957.

7. Kocks JW, Asijee GM, Tsiligianni IG et al. Functional statusmeasurement in COPD: a review of available methods and theirfeasibility in primary care. Prim Care Respir J 2011; 20: 26975.

8. Celli BR, MacNee W. Standards for the diagnosis and treat-

ment of patients with COPD: a summary of the ATS/ERSposition paper. Eur Respir J 2004; 23: 93246.

9. ATS statement: guidelines for the six-minute walk test. Am JRespir Crit Care Med 2002; 166: 1117.

10. Newman AB, Kupelian V, Visser M et al. Sarcopenia: alterna-tive denitions and associations with lower extremity func-tion. J Am Geriatr Soc 2003; 51: 16029.

11. Cesari M, Kritchevsky SB, Baumgartner RN et al. Sarcopenia,obesity, and inammationresults from the Trial of AngiotensinConverting Enzyme Inhibition and Novel Cardiovascular RiskFactors study. Am J Clin Nutr 2005; 82: 42834.

12. Miller MR, Hankinson J, Brusasco Vet al. Standardisation ofspirometry. Eur Respir J 2005; 26: 31938.

13. Shah S, Vanclay F, Cooper B. Improving the sensitivity of theBarthel Index for stroke rehabilitation. J Clin Epidemiol1989; 42: 7039.

14. Guigoz Y, Vellas B, Garry PJ. Assessing the nutritionalstatus of the elderly: the Mini Nutritional Assessment aspart of the geriatric evaluation. Nutr Rev 1996; 54:S5965.

15. Enright PL, Sherrill DL. Reference equations for the six-minute walk in healthy adults. Am J Respir Crit Care Med1998; 158: 13847.

16. Quanjer PH, Tammeling GJ, Cotes JE et al. Lung volumesand forced ventilatory ows. Report Working Party

Standardization of Lung Function Tests, EuropeanCommunity for Steel and Coal. Ofcial Statement of theEuropean Respiratory Society. Eur Respir J Suppl 1993; 16:540.

17. Morley JE, Baumgartner RN, Roubenoff R et al. Sarcopenia.J Lab Clin Med 2001; 137: 23143.

18. Roubenoff R. Sarcopenia: a major modiable cause of frailtyin the elderly. J Nutr Health Aging 2000; 4: 1402.

19. Franssen FM, ODonnell DE, Goossens GH et al. Obesityand the lung: 5. Obesity and COPD. Thorax 2008; 63:11107.

20. Sood A. Obesity, adipokines, and lung disease. J ApplPhysiol 2010; 108: 74453.

21. Bellia V, Pistelli R, Catalano Fet al. Quality control of spirom-

etry in the elderly. The SA.R.A. study. SAlute RespirationnellAnziano = Respiratory Health in the Elderly. Am J RespirCrit Care Med 2000; 161: 1094100.

22. Bellia V, Sorino C, Catalano F et al. Validation of FEV6 inthe elderly: correlates of performance and repeatability.

Thorax 2008; 63: 606.23. Garcia-Aymerich J, Serra I, Gomez FP et al. Physical activity

and clinical and functional status in COPD. Chest 2009; 136:6270.

24. Sciurba F, Criner GJ, Lee SM et al. Six-minute walk distancein chronic obstructive pulmonary disease: reproducibility andeffect of walking course layout and length. Am J Respir CritCare Med 2003; 167: 15227.

doi: 10.1093/ageing/afr167

4

Research letter

age ageing 2011 cesari ageing afr167

Documents