Body Composition Measurement in Bronchiectasis: Comparison between Bioelectrical Impedance Analysis, Skinfold Thickness Measurement, and Dual-Energy X-ray Absorptiometry before and after Pulmonary Rehabilitation

RESEARCH

Original Research: Brief

Body Composition Measurement in Bronchiectasis: Comparison between Bioelectrical Impedance Analysis, Skinfold Thickness Measurement, and Dual-Energy X-ray Absorptiometry before and after Pulmonary Rehabilitation Esperanza Doña, MD, PhD; Casilda Olveira, MD, PhD; Francisco Javier Palenque; Nuria Porras; Antonio Dorado, MD, PhD; Rocío Martín-Valero, PhD; Ana M. Godoy, MD, PhD; Francisco Espíldora, MD, PhD; Victoria Contreras, MD; Gabriel Olveira, MD, PhD ARTICLE INFORMATION Article history: Submitted 24 May 2017 Accepted 16 January 2018

Keywords: Anthropometry Bioelectrical impedance analysis Bronchiectasis Densitometry 2212-2672/Copyright ª 2018 by the Academy of Nutrition and Dietetics. https://doi.org/10.1016/j.jand.2018.01.013

ABSTRACT Background In individuals with bronchiectasis, fat-free mass depletion may be common despite a low prevalence of underweight and is considered a risk factor for increased morbidity and mortality. Techniques to adequately estimate fat-free mass and its changes over time are needed. Objective The purpose of this study was to assess agreement among values obtained with three different body composition techniques: skinfold thickness measurement (STM), bioelectrical impedance analysis (BIA), and dual-energy x-ray absorptiometry (DXA). Design The study was a secondary analysis of data from a randomized controlled trial. Participants/setting A respiratory rehabilitation program was administered for 3 months to individuals with bronchiectasis from the bronchiectasis unit of the Regional University Hospital in Malaga, Spain, from September 2013 to September 2014. Individuals with a body mass index (calculated as kg/m2) >18.5 who were aged 65 years or younger and those with a body mass index >20 who were older than 65 years were included. Main outcome measures At baseline and at 3 and 6 months, body composition was determined by DXA and STM. Statistical analyses performed Statistical concordance was assessed with the intraclass correlation coefficient (ICC), kappa coefficient, and the degree of agreement using the Bland Altman method. For comparison of the quantitative variables at baseline vs at 3 months and 6 months, the paired sample t test (or the Wilcoxon test) was used. Results Thirty participants were included. Strong agreement was observed between body composition values determined by BIA and DXA in fat mass (ICC: 0.92) and fat-free mass (ICC: 0.87). Strong agreement was observed between STM and DXA in the values for fat-free mass (ICC: 0.91) and fat mass (ICC: 0.94), and lower agreement was observed for the longitudinal data and in the regional values. The mean difference between fatfree mass determined by BIA and DXA was þ 4.7 with a standard deviation of 2.4 kg in favor of BIA. The mean difference between fat-free mass determined by STM and DXA was þ2.3 with a standard deviation of 2.7 kg in favor of STM. Six individuals were classified as having a low fat-free mass index (20%) by DXA vs four by STM (13%; kappa: 0.76) and only two by BIA (6.6%; kappa: 0.44) compared with DXA. Conclusions Despite good statistical agreement among values obtained with DXA, STM, and BIA, the study findings indicate that STM and BIA, above all, tended to overestimate fat-free mass compared with DXA. J Acad Nutr Diet. 2018;-:---.

B

RONCHIECTASIS IS A CONDITION INVOLVING IRREversible dilation of the bronchi and bronchioles as a consequence of the destruction of the elastic and muscular components of the bronchial wall.

ª 2018 by the Academy of Nutrition and Dietetics.

Bronchiectasis can be the outcome of many disorders that harm bronchial defense mechanisms and produce damage including alteration/imbalance in the mucociliary system, retention of secretions, and bacterial colonization.1 The

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RESEARCH prevalence of bronchiectasis has been estimated at 53 to 566 cases per 100, 000 persons.2 Prevalence increases with age and female sex.2 The prevalence of malnutrition is high in individuals with chronic respiratory diseases, such as cystic fibrosis (CF), chronic obstructive pulmonary disease (COPD), and bronchiectasis, although in patients with the latter two diseases, there is a low prevalence of underweight.3-5 Hence, in individuals with non-CF bronchiectasis, fat-free mass (FFM) depletion is common (about one-third of individuals) despite a low prevalence of underweight.4 It is important to assess body composition with a precise technique. Body mass index (BMI; calculated as kg/m2), however, is not sensitive enough to detect FFM depletion.6,7 FFM depletion can influence the prognosis and treatment response, as well as the selection of candidates for pulmonary rehabilitation and adequate follow-up after its implementation. A deterioration in nutritional status, especially a decrease in FFM, is directly related to a decline in lung function parameters, with a decrease in exercise capacity and a worsening of health-related quality of life.3-5 A decrease in FFM has been proposed as a predictor of morbidity and mortality in patients with chronic respiratory diseases such as COPD, CF, and non-CF bronchiectasis.3,5,8-12 In most of these studies, FFM was quantified by bio-electrical impedance analysis (BIA). Regional FFM determination by measurement of the mid-upper arm circumference or cross-sectional area of the thigh using computed tomography scan has also been shown to predict survival in individuals with COPD.13,14 In individuals receiving oxygen therapy or ambulatory mechanical ventilation, FFM can be a sensitive and relevant nutritional parameter in relation to deterioration and disability.15 Dual-energy x-ray absorptiometry (DXA) was first developed to evaluate bone mass. It is also widely used and validated to measure FFM and fat mass and has been compared with other techniques for assessing body composition such as hydrostatic weighing, computed tomography, and magnetic resonance imaging. Currently, its use in the validation of other techniques is increasing, because it is considered the gold standard technique in clinical practice.16 Nonetheless, there is a need to know the degree of agreement between the values obtained with DXA and those obtained with other more easily implemented techniques in routine care, such as BIA or skinfold thickness measurement (STM), which are more readily available to health care teams. Although body composition has been evaluated in individuals with CF7 and COPD,17 this type of comparison has not been made in individuals with non-CF bronchiectasis either through measurements at a single point in time or longitudinally. Nor has there been an evaluation of the composition of regional body components (trunk, arms, legs) measured by DXA or BIA in this population. These measurements could be used to assess the presence of sarcopenia, which is related to increased mortality risk and causes impaired physical performance.18 Furthermore, the different estimation formulas must be validated for each specific population.17 The objective of this study was to evaluate the agreement among values obtained with different body composition measurement techniques (STM, BIA, and DXA) to assess FFM and fat mass in individuals with bronchiectasis both at baseline and longitudinally (at 3 and 6 months) after participation in a pulmonary rehabilitation (PR) program. The 2

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RESEARCH SNAPSHOT Research Question: What is the level of agreement among values obtained with the different techniques of body composition measurement for people with bronchiectasis? Key Findings: Despite good statistical agreement of skinfold thickness measurement (STM) and bioelectrical impedance analysis (BIA) with dual-energy x-ray absorptiometry (DXA), STM, and particularly, BIA tend to overestimate fat-free mass (FFM). This could inappropriately classify participants with bronchiectasis as not having FFM depletion when in fact they have FFM depletion. However, given its simplicity and accuracy, STM could be a reasonable and inexpensive option for the nutritional assessment of individuals with nonecystic fibrosis bronchiectasis, when DXA is not available. proposed hypothesis is that both STM and BIA could provide sufficient precision to be used in clinical practice for evaluation of individuals with bronchiectasis.

METHODS This study was a secondary analysis of data from individuals participating in a prospective clinical trial in which they were randomly assigned to complete a structured PR program for 3 months vs PR together with a high-protein dietary supplement.19 Participants were recruited from the bronchiectasis unit of the Regional University Hospital in Malaga, Spain, from September 2013 to September 2014. For this study, all 30 individuals included in the trial were evaluated in the same group, without differentiating between those who did and those who did not receive the high-protein supplement (Figure 1). The inclusion criteria were as follows: a diagnosis of nonCF bronchiectasis, age 18 to 80 years, a BMI >18.5 for individuals age 65 or younger and a BMI >20 for those older than 65. In all cases, bronchiectasis was diagnosed by highresolution computed tomography according to the criteria of Naidich and colleagues.20 The PR program description and the effect of interventions on body composition measured by DXA have been published previously.19 Demographic data, chronic colonization by pathogens, Bhalla scores on highresolution computed tomography (scoring system that evaluates lung structural damage, with the maximum score being 25 points, which would be equivalent to normality),21 FACED scale (multidimensional system capable of classifying the severity of bronchiectasis according to its prognosis, which includes forced expiratory volume in 1 second expressed as a percentage, age, whether there is colonization by Pseudomonas aeruginosa, number of lobes affected, and degree of dyspnea),22 and spirometry data23 were recorded. The study was a secondary analysis of data from a randomized controlled trial that included individuals with bronchiectasis. At baseline and at 3 and 6 months, body composition was assessed using three techniques: STM, BIA, and DXA.

STM Measurement of skinfolds (triceps, abdominal, biceps, and subscapular) was performed using a Holtain constant --

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objects (eg, jewelry) removed. The participants fasted from the night before the measurements were taken. For determination of the values for resistance, reactance, and angle of phase, the device uses the frequencies of 1 kHz, 5 kHz, 50 kHz, 250 kHz, 500 kHz, and 1,000 kHz and measures by means of eight electrodes.

DXA Participants were scanned with a GE Healthcare Lunar Prodigy Advance densitometer. All the scans were performed according to the manufacturer’s standard scan and

Table 1. Main baseline clinical and demographic characteristics and degree of intervention adherence for 30 individuals with bronchiectasis Baseline clinical and demographic characteristics ƒƒƒƒƒƒƒƒƒƒƒ meanSDa ƒƒƒƒƒƒƒƒƒƒƒ! Completed program 12 weeks n=30

Age, y

56.113

Weight, kg

70.516.2

Height, cm

162.28.2

BMIb

26.64.7

Bhalla score

c

FACED scored FEV1e,

mL

1.91 1,815.6705.4

FEV1, %

66.123.6

f

2,512724.1

FVC (mL)

Completed 24 weeks follow-up n=28 -Withdrew from the study due to illness

17.62.1

ƒƒƒƒƒƒƒƒƒƒƒƒƒn (%ƒƒƒƒƒƒƒƒƒƒƒƒƒ! Sex

Figure 1. Flow diagram of screening, randomization, and follow-up for a study of individuals with nonecystic fibrosis bronchiectasis in Malaga, Spain. pressure caliper (Holtain Limited). The same investigator performed triplicate measurements in the dominant limb and calculated the mean according to the recommendations of the Spanish Society of Endocrinology and Nutrition.24 Percentiles were estimated from the reference values for the healthy Spanish population.25 Percentages and kilograms of fat mass and FFM were estimated according to the formulas of Siri26 and Durnin and Womersley.27 The formula took into account weight, age, sex, and the sum of four skinfolds (triceps, biceps, supra-iliac, and subscapular).

Male

12 (40)

Female

18 (60)

Colonizationg Staphylococcus 8 (26.7) aureus Haemophilus influenzae

17 (56.7)

Pseudomonas aeruginosa

21 (70)

Adherence,h sessions

19.5 (81.2)

a

Weight (sensitivity 0.1 kg) and total and regional body composition were measured with a hand-to-foot multi-frequency body composition monitor (TANITA MC980MA). Testing was performed with each participant in a resting position, after having emptied the bladder, in underwear and with all metal

SD¼standard deviation. BMI¼body mass index. Bhalla score on high-resolution computed tomography (scoring system that assesses lung structural damage, with a maximum score of 25 points being equivalent to normal). d FACED scale (multidimensional system capable of classifying the severity of bronchiectasis according to its prognosis, which includes forced expiratory volume in 1 second expressed as a percentage, age, whether there is colonization by Pseudomonas aeruginosa, number of lobes affected, and degree of dyspnea). e FEV1¼forced expiratory volume in 1second. f FVC¼forced vital capacity. g Colonization: chronic colonization by microorganisms. h Adherence: number of rehabilitation sessions attended.

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RESEARCH positioning protocols. The software used was EnCore 12.3.28 Weight, total and regional fat, and FFM were recorded. Height was calculated at baseline with a stadiometer (Holtain Limited). From weight, height, and FFM, the BMI and FFM index (FFM in kg/height2 in meters, in kg/m2)29 were calculated with each of the three techniques, performed on the same day for each participant at baseline and at 3 and 6 months. Similarly, with regional BIA and DXA data, the prevalence of sarcopenia was estimated according to the Baumgartner equation30: [(Fat-free mass arms in kgþFat free mass legs in kg)/height in m2] for men: <7.26 kg/m2 and women: <5.45 kg/m2.

Data Analysis Data analysis was performed using SPSS version 22.0.31 The distribution of quantitative variables was examined using the Shapiro-Wilk test. For comparison of the quantitative variables at baseline vs 3 months and 6 months, the paired sample t test (or the Wilcoxon test in the absence of normality) was used. For all calculations, statistical significance was set at P<0.05. The intraclass correlation coefficient (ICC)32 was used to study the degree of agreement between the body composition data determined using the different techniques, and Bland-Altman plots were chosen to analyze the individual differences. The kappa coefficient was used to evaluate the concordance between the different methods in the classification of individuals with a low FFM index. The study was approved by the Research Ethics Committee of Malaga Province, and all of the participants provided

written informed consent. The study was registered at the Clinical Trials site (http://clinicaltrials.gov): NCT02048397.

RESULTS A total of 30 individuals were enrolled in the clinical trial. All participants completed the 12-week PR program. Two participants withdrew from the study during the 6-month follow-up period because of an illness unrelated to bronchiectasis (Figure 1). Baseline characteristics of the 30 participants are presented in Table 1; 23.4% of the participants in the study had severe obstruction (participants who had a forced expiratory volume in 1 second expressed as <50%) as determined by spirometry. Table 2 shows the changes in the different body composition parameters at baseline and 3 and 6 months after the intervention. A statistically significant increase from baseline was noted for the FFM index and FFM at 3 months when DXA was used and at 3 and 6 months when STM was used. Fat mass also significantly decreased at 6 months compared with baseline when STM was used. Table 3 illustrates the agreement between the body composition values obtained with BIA and DXA. There was high agreement between the values for fat mass (ICC: 0.92) and FFM (ICC: 0.87). Less agreement was observed for regional values (with ICCs ranging from 0.26 for fat-free arm mass to 0.92 for fat mass in the legs) and for FFM changes at 3 and 6 months (ICC: 0.49 to 0.54). With regard to agreement between values obtained by STM and DXA, there was strong agreement in the values for FFM (ICC: 0.91) and fat mass (ICC: 0.94) between values obtained

Table 2. Longitudinal body composition data for 30 individuals with bronchiectasis at baseline and at 3 and 6 months after a pulmonary rehabilitation program in Malaga, Spain Baseline n[30

3 months n[30

6 months n[28 (m–SD)

ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒmeanSDa ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ! STMb Fat mass, kg

24.28.5

Fat-free mass, kg

46.310.4

Fat-free mass index (kg/m2) 17.42.5

23.87.9

23.47.5*

47.110.3**

47.010.7**

17.72.5**

17.72.6**

DXAc Fat mass, kg

26.010.5

25.99.9

26.110.5

Fat-free mass, kg

43.59.6

44.39.6*

43.99.9

17.62.3**

17.42.4

2

Fat-free mass index (kg/m ) 17.32.3 BIAd Fat mass, kg

22.21

22.59.9

21.99.9

Fat-free mass, kg

48.39.9

48.59.6

48.510

Fat-free mass index (kg/m ) 18.12.3

18.32.1

18.22.2

2

a

SD¼standard deviation. STM¼skinfold thickness measurement. c DXA¼dual-energy x-ray absorptiometry. d BIA¼bioelectrical impedance analysis. *P<0.05. **P<0.01 compared to baseline. b

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RESEARCH with the two techniques. The longitudinal data showed lower agreement (ICC: 0.53). With regard to agreement between BIA and STM, strong agreement was observed between values obtained with the two techniques at baseline, with an ICC of 0.94 for fat mass and an ICC of 0.95 for FFM. Agreement between values obtained with the two techniques was lower for the data on fat mass and FFM changes at 3 and 6 months (ICC: 0.25 to 0.38). A baseline comparison of the individuals with low FFM (classified as FFM index <16 kg/m2 in men and <15 kg/m2 in

women10) detected by using the different techniques was performed. When STM was compared with DXA, the kappa coefficient33 was 0.76 (good agreement). In the comparison between BIA and DXA, the kappa coefficient was 0.44 (moderate agreement), and when STM was compared with BIA, the kappa coefficient was 0.63 (good agreement). If DXA is considered the gold standard technique for classification of FFM depletion, six individuals were classified as having low FFM when DXA was used, four individuals as having low FFM when STM was used, and two individuals as having low FFM

Table 3. Concordance among three different body composition measurement techniques in 30 individuals with bronchiectasis at baseline and at 3 and 6 months after a respiratory rehabilitation program in Malaga, Spain DXAa

BIAb

ICCc

ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ ƒ meanSDd ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ ƒ! Baseline Fat mass total, kg

25.910.5

22.210

0.92

Fat-free mass total, kg

43.59.6

48.39.9

0.87

8.53.9

8.23.9

0.92

13.63.2

15.83.4

0.76

Fat mass legs, kg Fat-free mass legs, kg Fat mass arms, kg

2.40.90

2.31.5

0.62

Fat-free mass arms, kg

4.71.5

5.582.9

0.26

Fat mass trunk, kg

14.16.4

11.54.9

0.84

Fat-free mass trunk, kg

21.34.8

27.55.3

0.54

Fat-free mass, total change in kg at 3 mo 0.801.4

0.201.5

0.54

Fat-free mass, total change in kg at 6 mo 0.411.2

0.301.5

0.49

DXA

STMe

ICC

ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒmeanSDƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ! Baseline Fat mass total, kg

25.910.5

24.28.5

0.94

Fat-free mass total, kg

43.59.6

46.310.4

0.91

Fat-free mass total, kg: change at 3 mo 0.801.4

0.861.1

0.53

Fat-free mass total, kg: change at 6 mo 0.411.2

0.761.3

0.53

BIA

STM

ICC

ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒmeanSD ƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒƒ! d

Baseline Fat mass total, kg

22.210

24.28.5

0.94

Fat-free mass total, kg

48.39.9

46.310.4

0.95

Fat mass total, kg: change at 3 mo 0.201.5

0.861.1

0.25

Fat mass total, kg: change at 6 mo 0.301.5

0.761.3

0.38

a

DXA¼dual-energy x-ray absorptiometry. BIA¼bioelectrical impedance analysis. c ICC¼intraclass correlation coefficient: the interpretation of the concordance according to ICC values is as follows: very good 0.9; good: between 0.7 and 0.89; moderate between 0.5 and 0.69; fair for values between 0.3 and 0.49; poor <0.3.32 d SD¼standard deviation e STM¼skinfold thickness measurement. b

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RESEARCH when BIA was used. STM would misclassify two of six individuals (33%; kappa: 0.76) and BIA would misclassify four of six (66%; kappa: 0.44) (see Figure 2). The values for appendicular skeletal mass/height2 were 6.91.2 kg/m2 as determined by DXA and 8.11.5 kg/m2 as determined by BIA. Three (10%) participants were identified as having sarcopenia according to the Baumgartner criteria30 with DXA but none were identified with BIA. The degree of agreement between baseline body composition data obtained with the different techniques was also assessed by analyzing the individual differences using BlandAltman plot analysis. Figure 3A compares FFM estimated by STM and by DXA (in kg). The difference between FFM measured by STM and DXA had a mean of þ2.32.7 kg in favor of STM. The values were homogeneously distributed around the FFM mean. Figure 3B shows the comparison of FFM as determined by BIA and DXA. The mean difference between the two was 4.72.4 kg in favor of BIA. The values were homogeneously distributed around the FFM mean. Figure 3C shows the comparison of FFM as determined by BIA and STM. The mean difference between FFM determined by BIA and by STM was 2.3 kg2 kg in favor of BIA. The values were homogeneously distributed around the FFM mean.

DISCUSSION This study revealed that BIA (especially) and STM (to a lesser extent) overestimate FFM and underestimate the prevalence of low FFM compared with DXA, which is the clinical gold standard.16 This assessment is important because studies suggest that loss of FFM is associated with a greater severity of respiratory disease.3,4,34 Accordingly, validated, accurate, and simple techniques to adequately estimate fat-free body mass and its changes over time are needed for use in clinical practice. DXA is considered the gold standard technique in clinical practice.16 However, because of the lack of availability and higher cost of DXA compared with simpler techniques such as STM and BIA, the aim of this study was to compare STM and

DXAa

BIA with DXA. DXA is potentially beneficial for evaluation of body composition because it has a high degree of accuracy35; good agreement with results obtained using the fourcompartment model (fat, protein, water, and mineral), which is based on measurements of weight, total body water, and whole-body density by different techniques such as densitometry, isotope dilution, and others36; and good shortterm reproducibility37 and because it enables assessment of total and regional body composition. Limitations of DXA include lack of portability of the equipment (meaning that participants can only be evaluated at centers that have a DXA scanner), exposure to radiation associated with the scan, and the requirement for the patient to lie still for a few minutes, which may be difficult for individuals with severe lung disease who cannot avoid coughing during the examination.35 For these reasons, previous research has explored the possibility of replacing DXA with BIA or other measures in a population already frequently exposed to radiation from x-rays.38 In this study a high degree of statistical agreement was found between the tests (ICC) in the values for FFM and fat mass at baseline. Conversely, the results showed lower agreement for the regional values and for the longitudinal data (changes at 3 and 6 months after PR). Despite the strong agreement, it was noted that STM and, especially, BIA tended to overestimate FFM and to underestimate fat mass. Several studies have evaluated the use of BIA for patients with CF.7,38 The study of adults with CF by Ziai and colleagues38 revealed that BIA overestimated FFM (mean 3.2 kg) and underestimated fat mass (by more than 1.3 kg). In the present study, in individuals with non-CF bronchiectasis, the mean overestimation by BIA compared with DXA was even higher (þ4.7 kg) and was homogeneously distributed according to FFM values. Clinically, this overestimation could result in individuals who had FFM depletion as determined by DXA being inappropriately classified as individuals without FFM depletion by BIA. Similarly, in the present study, BIA did not detect any cases of sarcopenia (according to the

Bioelectrical Impedance Analysis

STMb 13%

7% 20%

80%

93%

FFMc malnourished

87%

FFM normally nourished

Figure 2. Comparison of malnourished and normally nourished individuals with bronchiectasis in Malaga, Spain, according to fatfree mass measured by three techniques (n¼30). aDXA¼dual-energy x-ray absorptiometry. bSTM¼skinfold thickness measurement. c FFM¼fat-free mass. 6

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Figure 3. Degree of agreement between body composition data with the different techniques by evaluation of the individual differences with Bland-Altman plot analysis. (A) Comparison of fat-free mass (in kilograms) by STM and DXA in individuals with bronchiectasis in Malaga, Spain. (B) Bland Altman, Comparison of fat-free mass (in kilograms) by BIA and DXA in individuals with bronchiectasis in Malaga, Spain. (C) Comparison of fat-free (in kilograms) mass by BIA and STM in individuals with bronchiectasis in Malaga, Spain. aSTM¼skinfold thickness measurement. bDXA¼dual-energy x-ray absorptiometry. cBIA¼bioelectrical impedance analysis. --

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Baumgartner criteria)30 compared with the three cases detected using DXA; thus BIA also tended to underestimate the prevalence of sarcopenia. This percentage of underdiagnosis of FFM depletion when BIA was used was higher than that observed with STM. King and colleagues7 compared values obtained with BIA and STM with those obtained with DXA for adults with CF.7 STM overestimated FFM by a mean of almost 2.4 kg compared with DXA. In the present study, STM also overestimated FFM with very similar values (mean 2.3 kg) and was homogeneously distributed according to FFM values. STM is used to estimate FFM and fat mass with the assumptions that subcutaneous adipose tissue represents a constant proportion of total body fat and that the sites selected for measurement are representative of the mean thickness of subcutaneous adipose tissue throughout the body.39 These assumptions may not be valid under certain conditions, depending on age, gender, race, and the presence of disease.37 Other limitations of this technique include inter- and intra-observer variability.36 In the present study, the same investigator performed all measurements, and the concordance and degree of agreement between values obtained with DXA and STM were greater than those for BIA. Chomtho and colleagues40 evaluated the use of arm STM compared with DXA in healthy children and children with CF, concluding that arm STM is less accurate for measuring total and regional FFM. The results were better for fat mass determination. In the study by King and colleagues,7 the results of FFM measurements by BIA compared with DXA were dependent on the formula used. Thus, FFM was underestimated compared with results obtained by Lukaski39 and overestimated compared with those obtained by Segal, especially in women (þ4 kg).7 The prediction equations used to calculate body composition have been developed and validated, generally, in healthy individuals. To date, no prediction equations have been described that have been specifically developed and/or validated for use in individuals with bronchiectasis, although some have been developed for people with COPD.17,41-43 It is important to note that most BIA devices use different prediction equations for estimates of body composition parameters and that frequently the details of these equations are not available to users. Because these equations are formulated based on specific population data, they can contribute to error in body composition measurements.7 A study of 24 healthy participants compared with 24 participants with COPD, in which three techniques for assessing body composition (STM, BIA, and DXA) were also applied, revealed that in the group of healthy participants, body composition was not significantly different when values obtained by BIA or STM were compared with those obtained by DXA. However, participants with COPD had significantly higher fat mass values and significantly lower FFM values when BIA was compared with DXA. In contrast, there were no differences between the values for these variables when STM was compared with DXA.44 Unlike other studies in which body composition measurements taken on a single occasion are assessed, in the present study, the longitudinal changes in the data were JOURNAL OF THE ACADEMY OF NUTRITION AND DIETETICS

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RESEARCH examined by using these three techniques after completion of a PR program. A lower agreement was noted between the longitudinal values with respect to the baseline values, in which the concordance was greater. Assuming that the error in STM and BIA is constant over time, these differences should not have a significant impact when body composition measurements are compared from one visit to the next. In the present study, FFM increased by a mean of 0.8 kg in 3 months (at completion of PR) as measured by DXA, compared with 0.2 kg as measured by BIA, and 0.86 kg as measured by STM. The study by De Meer and colleagues,45 in which the changes in FFM were determined by STM in malnourished children with CF after a physical exercise program, indicated that this method is applicable to detect changes in FFM regardless of the severity of the disease. Stettler and colleagues46 also prospectively evaluated body composition using various techniques such as doubly labeled water, STM, and BIA. Their study showed high agreement for FFM but not for fat mass. Regarding regional composition, the degree of agreement between values obtained with BIA and DXA was greater in fat mass (with an acceptable ICC) than in FFM (with poor coefficients in arms, moderate in trunk, and good in legs). However, the mean differences were high in the FFM of the legs and trunk. Ling and colleagues,47 in the Netherlands, studied 484 healthy participants and concluded that agreement between values obtained with BIA and DXA was very high for FFM in arms and legs (ICC>0.8) and somewhat lower for the trunk (ICC>0.7). Nevertheless, despite finding elevated ICC, they also found high mean differences of approximately 3 kg in favor of DXA. Again, it is possible that the formulas used for healthy people may not be applicable to individuals with chronic diseases, in whom the inflammatory component is important, as is the case in patients with bronchiectasis. The present study is the first to compare three different techniques that are useful in clinical practice for assessing body composition in people with bronchiectasis and to include a longitudinal follow-up. However, it is not without limitations. A greater number of participants would have provided more accurate information. Furthermore, less conventional methods that are not usually used in clinical practice—such as quantitative computed tomography, magnetic resonance imaging, or dilution techniques—were not evaluated.

2.

Polverino E, Goeminne PC, McDonnell MJ, et al. European Respiratory Society guidelines for the management of adult bronchiectasis. Eur Respir J. 2017;50(3).

3.

Aniwidyaningsih W, Varraso R, Cano N, Pison C. Impact of nutritional status on body functioning in chronic obstructive pulmonary disease and how to intervene. Curr Opin Clin Nutr Metab Care. 2008;11(4): 435-442.

4.

Olveira G, Olveira C, Gaspar I, et al. Fat-free mass depletion and inflammation in patients with bronchiectasis. J Acad Nutr Diet. 2012;112(12):1999-2006.

5.

King SJ, Nyulasi IB, Strauss BJG, Kotsimbos T, Bailey M, Wilson JW. Fat-free mass depletion in cystic fibrosis: Associated with lung disease severity but poorly detected by body mass index. Nutrition. 2015;26(7-8):753-759.

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Ionescu AA, Nixon LS, Luzio S, et al. Pulmonary function, body composition, and protein catabolism in adults with cystic fibrosis. Am J Respir Crit Care Med. 2002;165(4):495-500.

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King S, Wilson J, Kotsimbos T, Bailey M, Nyulasi I. Body composition assessment in adults with cystic fibrosis: Comparison of dual-energy x-ray absorptiometry with skinfolds and bioelectrical impedance analysis. Nutrition. 2005;21(11-12):1087-1094.

8.

Vendrell M, de Gracia J, Olveira C, et al. Diagnosis and treatment of bronchiectasis. Spanish Society of Pneumology and Thoracic Surgery [in Spanish]. Arch Bronconeumol. 2008;44(11): 629-640.

9.

Olveira G, Olveira C. Nutrition, cystic fibrosis and the digestive tract [in Spanish]. Nutr Hosp. 2008;23(suppl 2):71-86.

10.

Schols AMWJ, Broekhuizen R, Weling-Scheepers CA, Wouters EF. Body composition and mortality in chronic obstructive pulmonary disease. Am J Clin Nutr. 2005;82(1):53-59.

11.

Vestbo J, Prescott E, Almdal T, et al. Body mass, fat-free body mass, and prognosis in patients with chronic obstructive pulmonary disease from a random population sample: Findings from the Copenhagen City Heart Study. Am J Respir Crit Care Med. 2006;173(1):79-83.

12.

Faisy C, Rabbat A, Kouchakji B, Laaban JP. Bioelectrical impedance analysis in estimating nutritional status and outcome of patients with chronic obstructive pulmonary disease and acute respiratory failure. Intensive Care Med. 2000;26(5):518-525.

13.

Marquis K, Debigaré R, Lacasse Y, et al. Midthigh muscle crosssectional area is a better predictor of mortality than body mass index in patients with chronic obstructive pulmonary disease. Am J Respir Crit Care Med. 2002;166(6):809-813.

14.

Soler-Cataluña JJ, Sánchez-Sánchez L, Martínez-García MA, Sánchez PR, Salcedo E, Navarro M. Mid-arm muscle area is a better predictor of mortality than body mass index in COPD. Chest. 2005;128(4):2108-2115.

15.

Cano NJM, Roth H, Court-Ortuné I, et al. Nutritional depletion in patients on long-term oxygen therapy and/or home mechanical ventilation. Eur Respir J. 2002;20(1):30-37.

16.

Toombs RJ, Ducher G, Shepherd JA, De Souza MJ. The impact of recent technological advances on the trueness and precision of DXA to assess body composition. Obesity (Silver Spring). 2012;20(1):30-39.

17.

Schols AM, Wouters EF, Soeters PB, Westerterp KR. Body composition by bioelectrical-impedance analysis compared with deuterium dilution and skinfold anthropometry in patients with chronic obstructive pulmonary disease. Am J Clin Nutr. 1991;53(2):421424.

18.

Schols AM, Ferreira IM, Franssen FM, et al. Nutritional assessment and therapy in COPD: A European Respiratory Society statement. Eur Respir J. 2014;44(6):1504-1520.

19.

Olveira G, Olveira C, Doña E, et al. Oral supplement enriched in HMB combined with pulmonary rehabilitation improves body composition and health related quality of life in patients with bronchiectasis (Prospective, Randomised Study). Clin Nutr. 2016;35(5):1015-1022.

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CONCLUSIONS In conclusion, there is good statistical agreement among values obtained with DXA, STM, and BIA; but STM and BIA, above all, tend to overestimate FFM. Given the simplicity and accuracy of these results, in expert hands, STM could be a reasonable and inexpensive option for the nutritional assessment of individuals with non-CF bronchiectasis when DXA is not available.

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RESEARCH AUTHOR INFORMATION E. Doña is a physician doctor, Neumología, Hospital de Alta Resolución de Benalmádena, Málaga, Spain. C. Olveira is a physician doctor and professor, Pneumology, Malaga Regional University Hospital, Instituto de Biomedicina de Málaga (IBIMA), Malaga University, Spain. F. J. Palenque is a physiotherapist and A. M. Godoy is a physician doctor, UGC Rehabilitación, Hospital Regional Universitario de Málaga, Spain. N. Porras is a registered dietitian, UGC Endocrinología y Nutrición. Instituto de Biomedicina de Málaga (IBIMA), Malaga University, Spain. A. Dorado is a physician doctor, and F. Espíldora is a physician doctor, UGC Neumología, Hospital Regional Universitario de Málaga, Spain. R. Martín-Valero is a physiotherapist and professor, Facultad de Ciencias de la Salud, Málaga, Spain. V. Contreras is a physician, UGC de Endocrinología y Nutrición, Hospital Regional Universitario de Málaga, Spain. G. Olveira is physician doctor and professor, chief of section, UGC de Endocrinología y Nutrición, Hospital Regional Universitario de Málaga, Instituto de Biomedicina de Málaga (IBIMA), Malaga University, Spain, and CIBERDEM, CIBER of Diabetes and Associated Metabolic Diseases (CB07/08/0019), Instituto de Salud Carlos III, Spain. Address correspondence to: Gabriel Olveira MD, PhD, UGC de Endocrinología y Nutrición, Nutrition Unit, 4a planta, Pabellón A. Hospital Regional Universitario de Málaga, Avenida Carlos Haya, Malaga 29010, Spain. E-mail: [email protected]

STATEMENT OF POTENTIAL CONFLICT OF INTEREST No potential conflict of interest was reported by the authors.

FUNDING/SUPPORT Funded by the Regional Ministry of Health of the Junta de Andalucía (PI-0239-2013); SEPAR 016/2013 and Neumosur 3/2013; Costa del Sol Health Agency. Clinical Trial Registration: NCT02048397 (clinicaltrials.gov).

AUTHOR CONTRIBUTIONS G. Olveira, C. Olveira, and E. Doña designed the study and wrote the draft of the work. All authors recruited patients, reviewed the final version, and provided approval.

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