The Association between Fat-Free Mass and Exercise Test Outcomes in People with Chronic Obstructive Pulmonary Disease: A Systematic Review

Abstract

People with chronic obstructive pulmonary disease (COPD) tend to have abnormally low levels of fat-free mass (FFM), which includes skeletal muscle mass as a central component. The purpose of this systematic review was to synthesise available evidence on the association between FFM and exercise test outcomes in COPD. MEDLINE, Cochrane Library, EMBASE, Web of Science, and Scopus were searched. Studies that evaluated exercise-related outcomes in relation to measures of FFM in COPD were included. Eighty-three studies, containing 18,770 (39% female) COPD participants, were included. Considerable heterogeneity was identified in the ways that FFM and exercise test outcomes were assessed; however, higher levels of FFM were generally associated with greater peak exercise capacity. This association was stronger for some exercise test outcomes (e.g. peak rate of oxygen consumption during incremental cycle exercise testing) than others (e.g. six-minute walking distance). This review identified heterogeneity in the methods used for measuring FFM and exercise capacity. There was, in general, a positive association between FFM and exercise capacity in COPD. There was also an identified lack of studies investigating associations between FFM and temporal physiological and perceptual responses to exercise. This review highlights the significance of FFM as a determinant of exercise capacity in COPD.

Supplemental data for this article is available online at https://doi.org/10.1080/15412555.2022.2049737 .

Keywords:

• Fat-free mass
• muscle
• COPD
• exercise test
• six-minute walk test
• CPET

Introduction

Chronic obstructive pulmonary disease (COPD) is a prevalent and disabling chronic health condition associated with abnormally high morbidity and mortality [1,2]. Beyond its established adverse effects on pulmonary structure and function, COPD is now recognised as a systemic disease affecting many extra-pulmonary tissues and organs [3,4]. Skeletal muscle dysfunction is a common and particularly important systemic consequence (or extra-pulmonary manifestation) of COPD because of its adverse effect on clinical and patient-reported outcomes [5].

The aetiology of muscle dysfunction in COPD is complex and multifactorial [5]. The rate of age-related decline in skeletal muscle function is accelerated in people with COPD compared to that of otherwise healthy adults [6]. Additionally, loss of muscle function begins early in the disease course, with ostensible muscle dysfunction observed in people with mild COPD [7]. A joint statement by the American Thoracic Society and European Respiratory Society identified several structural and morphological alterations that combine to contribute to skeletal (limb) muscle dysfunction in people with COPD, including: abnormally low muscle strength and endurance; mitochondrial dysfunction; poor oxidative capacity; shift in muscle fibre-type (i.e. abnormally low and high percentage of type I and type II fibres, respectively); and muscle atrophy or loss of fat-free mass (FFM) [5]. Exaggerated age-related loss of FFM, which includes skeletal muscle mass as a central component, is prevalent in COPD [3, 5, 8,9]. Prevalence estimates of muscle atrophy (or abnormally low FFM) in the COPD population have been reported to be as high as 35% [5] − 40% [8], with muscle atrophy observed in as many as 50% of people with very severe COPD [5].

Not only is abnormally low FFM prevalent in COPD, but it is associated with a host of negative health outcomes, including abnormally low levels of physical activity [10,11] and quality of life [12], and greater risk of premature death [13,14]. Exercise intolerance is another adverse health consequence of COPD-related loss of FFM, with multiple studies reporting positive correlations between indices of FFM and established measures of exercise capacity, including the distance walked during the six-minute walk test (6MWD) and peak rate of oxygen consumption (V^’O_2,peak) on symptom-limited incremental exercise testing [15,16]. This is significant considering that both 6MWD and V’O_2,peak are established independent predictors of multiple adverse health outcomes for people living with COPD, most notably premature death [17–19].

Considering the reported associations and potential interplay between FFM, exercise capacity, and mortality in COPD, it is imperative that researchers and healthcare providers are provided with the most up-to-date pooled scientific information on the association between FFM and exercise test outcomes in COPD. To this end, the aim of this systematic review was to summarise the extant literature reporting on the association between estimates of FFM and (1) peak exercise capacity and (2) temporal physiological and perceptual responses from rest to peak exercise in people with COPD.

Methods

Terminology

For the purposes of this review, FFM was considered as a term that encompassed any measure of muscle, such as fat-free mass index (FFMI) or appendicular muscle mass (refer to Table 1 for the full list of accepted evaluations of FFM). Therefore, any study that reported an association between any measure of muscle (i.e. a measure of FFM) and exercise responses in people with COPD were eligible for inclusion in this review.

Table 1. Study characteristics.

Author	Year	Study design	Sample size n = total (male/female)	FEV1%predicted	Body composition tool	Measure of fat-free mass	Exercise test(s) used
Schols et al. [20]	1989	Cross-sectional	83 (71/12)	Low performance: 31 ± 9Medium performance: 31 ± 9High performance: 36 ± 7	Blood sample measurements	Creatine height index	12MWT
Schols et al. [10]	1991	Cross-sectional	54 (43/11)	33 ± 9	BIA	FFM, creatine height index, arm-muscle circumference	12MWT
Schols et al. [21]	1993	Cross-sectional	255 (203/52)	Males: 33 ± 1 4 Females: 41 ± 17	BIA	FFM	12MWT
Shoup et al. [22]	1997	Cross-sectional	50 (20/30)	39 ± 19	DEXA	LBMI	6MWT
Baarends et al. [23]	1997	Cross-sectional	62 (44/18)	Depleted: 36 ± 11 Non-depleted: 41 ± 15	Deuterium labelled water	FFMI	INCR CY-CPET
Yoshikawa et al. [24]	1999	Cross-sectional	27 (27/0)	50 ± 26	DEXA	LBM	INCR CY-CPET
Kobayashi et al. [25]	2000	Cross-sectional	25 (25/0)	41 ± 18	BIA	FFM	INCR CY-CPET
Mostert et al. [26]	2000	Cross-sectional	45 (32/13)	Low BMI/Low FFMI: 32 ± 8 Low BMI/High FFMI: 34 ± 19 High BMI/Low FFMI: 33 ± 13	BIA	FFMI	12MWT
Yoshikawa et al. [27]	2001	Cross-sectional	38 (38/0)	47 ± 25	DEXA	LBM	INCR CY-CPET
Gosker et al. [28]	2003	Cross-sectional	25 (16/9)	32 ± 11	BIA	FFM	INCR CY-CPET
Mamoto et al. [29]	2003	Cross-sectional	20 (20/0)	65 ± 16	BIA	ICW, ECW, ICW/ECW, UW, LW, TW	INCR and CWR CY-CPET
Franssen et al. [15]	2004	Prospective cohort	50 (37/13)	39 ± 16	BIA	FFM and FFMI	INCR CY-CPET
Franssen et al. [30]	2005	Cross-sectional	87 (59/28)	Non-depleted: 37 ± 2 Depleted: 31 ± 3	BIA	FFM and FFMI	INCR CY-CPET
Steiner et al. [31]	2005	Cross-sectional	85 (53/32)	Males: 31 ± 13 Females: 41 ± 14	DEXA	LBM	ISWT and ESWT
Mathew et al. [32]	2006	Prospective cohort	25 (25/0)	55 ± 21	Skinfolds	FFM	12MWT
Eisner et al. [33]	2007	Cross-sectional	355 (143/212)	58 ± 23	BIA	LBM	6MWT
Ischaki et al. [16]	2007	Cross-sectional	80 (NR)	GOLD stage 1: 85 ± 3 GOLD stage 2: 65 ± 7 GOLD stage 3: 43 ± 5 GOLD stage 4: 28 ± 1.6	BIA	FFMI	6MWT
Villaca et al. [34]	2008	Cross-sectional	48 (38/10)	Unreported	DEXA	FFM and leg lean volume	6MWT
Budweiser et al. [35]	2008	Cross-sectional	93 (65/28)	Non-depleted: 37 ± 13 Depleted: 28 ± 9	BIA	FFMI	6MWT
Franssen et al. [36]	2008	Cross-sectional	13 (NR)	Sarcopenic: 53 ± 5 Underweight: 51 ± 5	BIA	FFM and FFMI	INCR CY-CPET
Van Wetering et al. [37]	2008	Cross-sectional	180 (132/48)	GOLD stage 2: 67 ± 11 GOLD stage 3: 43 ± 5	BIA	FFMI	INCR and CWR CY-CPET
Vilaro et al. [38]	2009	Cross-sectional	16 (16/0)	38 ± 15	MRI	Quadriceps muscle mass	INCR CY-CPET and 6MWT
Pelegrino et al. [39]	2009	Cross-sectional	68 (49/19)	Non-depleted: 64 ± 31 Depleted: 62 ± 25	BIA	LBMI	6MWT
Giron et al. [40]	2009	Cross-sectional and prospective cohort	78 (78/0)	42 ± 15	BIA	FFM and muscle mass	6MWT
Vogiatzis et al. [41]	2010	Prospective cohort	29 (29/0)	Cachectic: 38 ± 6 Non-Cachectic: 44 ± 5	BIA	FFMI	INCR CY-CPET and 6MWT
Sabino et al. [42]	2010	Cross-sectional	32 (23/9)	Overweight/Obese: 34 ± 4 Normal weight: 34 ± 2Underweight: 27 ± 4	BIA	FFMI	6MWT
Cortopassi et al. [43]	2011	Cross-sectional	18 (18/0)	45 ± 20	BIA	FFM	INCR CY-CPET
Hallin et al. [44]	2011	Cross-sectional	49 (14/35)	Low FFMI: 31 ± 9 Normal FFMI: 32 ± 10	BIA	FFMI	INCR CY-CPET, ISWT and 12MWT
Malaguti et al. [45]	2011	Cross-sectional	39 (31/8)	Depletion: 41 ± 15 Non-depleted: 51 ± 14	DEXA	LBM	INCR CY-CPET
Waatevik et al. [46]	2012	Cross-sectional	370 (223/147)	50 ± 14	BIA	FFMI	6MWT
Fermoselle et al. [47]	2012	Cross-sectional	29 (29/0)	Muscle wasted: 32 ± 14 Non-muscle wasted: 45 ± 19	NR	FFMI	CY-CPET
Cesari et al. [48]	2012	Cross-sectional	71 (40/31)	71 ± 19	DEXA	ALM	6MWT
Hillman et al. [49]	2012	Cross-sectional	26 (13/13)	32 ± 11	DEXA	LBM	6MWT
Roca et al. [50]	2013	Prospective case control study	31 (31/0)	38 ± 14	BIA	LBM, dry lean mass and impedance	6MWT
Berton et al. [51]	2013	Cross-sectional	62 (20/42)	Depleted: 34 ± 13 Non-depleted: 45 ± 21	BIA	FFMI	6MWT
Natanek et al. [52]	2013	Cross-sectional	32 (18/14)	Depleted: 30 [25-41] Non-depleted: 46 [24-60]	BIA	FFM and FFMI	INCR CY-CPET and 6MWT
Genc et al. [53]	2014	Cross-sectional	30 (30/0)	76 ± 14	BIA	LBM	Astrand CY-CPET
Teopompi et al. [54]	2014	Cross-sectional	57 (41/16)	Depleted: 48 ± 16 Non-depleted: 52 ± 16	BIA	FFMI	INCR CY-CPET
Aiello et al. [55]	2014	Cross-sectional	44 (28/16)	Normal weight: 52 ± 13 Obese: 50 ± 12	BIA	FFM	INCR CY-CPET
Frisk et al. [56]	2014	Prospective cohort	389 (236/153)	49 ± 14	BIA	FFMI	6MWT
McDonald et al. [57]	2014	Cross-sectional	484 (237/247)	49 ± 19	CT scan	Pectoralis muscle area	6MWT
Silveira et al. [58]	2014	Cross-sectional	54 (30/24)	42 ± 15	BIA	FFM and FFMI	INCR TM-CPET
Robles et al. [59]	2015	Cross-sectional	10 (5/5)	35 ± 9	MRI and PMRS	Knee extensor and plantar flexor muscle CSA	6MWT
Van de Bool et al. [60]	2015	Cross-sectional	505 (288/217)	Sarcopenia: 43 [32–59]Sarcopenia/Abdominal Obesity: 47 [36–63] No Sarcopenia: 64 [51–72]	DEXA	FFM, FFMI, ASM, ASMI	INCR and CWR CY-CPET and 6MWT
Maddocks et al. [61]	2015	Prospective cohort with cross-sectional analysis	502 (295/207)	25 [24-32]	BIA	FFMI and phase angle	ISWT
Ramos et al. [62]	2015	Cross-sectional	57 (37/20)	Males: 53 ± 20 Females: 44 ± 14	DEXA	ASM	6MWT
Jones et al. [63]	2015	Cross-sectional	622 (354/268)	Normal: 46 ± 19 Low SMI: 38 ± 17 Low function: 46 ± 18 Sarcopenia: 41 ± 20	BIA	SMM and SMMI	ISWT
De Blasio et al. [64]	2016	Cross-sectional	212 (144/68)	Below Median: 43 ± 18 Above Median: 48 ± 19	BIA	FFM, FFMI, and impedance ratio	6MWT
Luo et al. [65]	2016	Cross-sectional	235 (184/51)	Not reported	BIA	FFMI	6MWT
Cebron Lipovec et al. [66]	2016	Prospective cohort	112 (74/38)	Sarcopenia: 36 ± 13 No-sarcopenia: 40 ± 15	BIA and DEXA	AMSI	6MWT
Joppa et al. [67]	2016	Cross-sectional	2000 (1314/686)	Normal: 50 ± 16 Obesity: 49 ± 16 Sarcopenic: 46 ± 16 Sarcopenic-obese: 43 ± 16	BIA	FFMI	6MWT
Martin et al. [68]	2017	Retrospective cohort	511 (314/197)	41 ± 15	CT scan	Chest muscle tissue CSA	6MWT
Travassos et al. [69]	2017	Retrospective cohort and cross-sectional	96 (53/43)	41 [31–52]	BIA	FFMI	6MWT
Tunsupon and Mador[70]	2017	Retrospective cohort	72 (71/1)	Obese: 42 ± 14 Non-Obese: 43 ± 15 FFM-depleted: 30 ± 14	BIA	FFMI	INCR and CWR CY-CPET and 6MWT
Buttery et al. [71]	2017	Prospective cohort	31 (19/12)	47 ± 20	Ultrasound	Rectus femoris CSA	6MWT
Matkovic et al. [72]	2017	Cross-sectional	111 (76/35)	Lower 6MWT: 43 ± 14 Higher 6MWT: 54 ± 15	DEXA	FFM, LBMI, mid-arm muscle circumference and arm muscle area	6MWT
Byun et al. [73]	2017	Cross-sectional	80 (67/13)	Sarcopenia: 58 ± 14 No-Sarcopenia: 62 ± 14	BIA	SMMI	6MWT
Ju et al. [74]	2018	Cross-sectional	60 (58/2)	54 ± 22	CT scan	Intercostal muscles CSA	6MWT
Kapchinsky et al. [75]	2018	Cross-sectional	25 (25/0)	Normal FFM: 42 ± 3 Low FFM: 29 ± 4	DEXA	FFMI	INCR CY-CPET
Amado et al. [76]	2019	Prospective cohort	65 (47/18)	53 ± 17	BIA and serum creatine	Sarcopenia index	6MWT
Nijholt et al. [77]	2019	Cross-sectional	44 (19/25)	38 [27-56]	BIA and Ultrasound	Rectus femoris CSA and rectus femoris thickness	ISWT
Machado et al. [78]	2019	Cross-sectional	270 (152/118)	Normal: 50 ± 14 Obese: 47 ± 16 Sarcopenic: 43 ± 16 Sarcopenic-obese: 42 ± 16	BIA	FFMI	6MWT
Chua et al. [79]	2019	Cross-sectional	43 (37/4)	48 ± 14	BIA	FFMI	6MWT
Barreiro et al. [102]	2019	Cross-sectional	29 (24/5)	Non-cachectic: 35 ± 11Cachectic: 31 ± 12	BIA	FFMI	6MWT
Kyomoto et al. [80]	2019	Cross-sectional	133 (116/17)	71 ± 27	BIA	SMMI	6MWT
Mansour et al. [81]	2019	Cross-sectional	20 (16/4)	No sarcopenia: 45 ± 24 Sarcopenia: 34 ± 18 Sarcopenia + Dynapenia: 39 ± 18	BIA	LBM	ISWT
Kwan et al. [82]	2019	Prospective cohort	1755 (1003/752)	Pre-cachexia: 52 ± 21 Cachexia: 37 ± 19 No cachexia: 49 ± 19	BIA	FFMI	ISWT
Cinar et al. [83]	2019	Cross-sectional	70 (43/27)	55 ± 22	BIA	FFM	6MWT
Demircioğlu et al. [84]	2020	Cross-sectional	219 (196/23)	No Sarcopenia = 48 ± 19 Sarcopenia = 42 ± 17	BIA	SMM and SMMI	6MWT
Perrot et al. [85]	2020	Prospective cohort	54 (37/17)	Sarcopenia: 45 ± 11 No-sarcopenia: 46 ± 20	BIA	SMMI	6MWT
Attaway et al. [86]	2021	Retrospective cohort	117 (60/57)	31 ± 10	CT scan	Pectoralis muscle and erector spinae muscle CSA	6MWT
Bernardes et al. [87]	2021	Cross-sectional	114 (94/50)	40 ± 16	Measuring tape	Calf circumference	6MWT
Donovan et al. [88]	2021	Cross-sectional	65 (49/16)	GOLD stage 1: 93 ± 12 GOLD stage 2: 62 ± 8 GOLD stage 3: 39 ± 6 GOLD stage 4: 24 ± 4	CT scan	Pectoralis muscle and paraspinal muscle density and area	INCR CY-CPET
Fekete et al. [89]	2021	Cross-sectional	50 (NR)	Low FFMI: 39 ± 12 Normal FFMI: 47 ± 17	BIA	FFM, FFMI, SMM, and SMMI	6MWT
Higashimoto et al. [90]	2021	Retrospective cohort	78 (76/2)	51 ± 24	CT scan	Pectoralis muscle and erector spinae muscle CSA	6MWT
Kanezaki et al. [91]	2021	Cross-sectional	60 (43/17)	Sarcopenia: 54 ± 3 No Sarcopenia: 60 ± 3	BIA	SMMI	3MST and 6MWT
Lage et al. [92]	2021	Cross-sectional	35 (24/11)	Sarcopenia: 58 [49-67] No sarcopenia: 55 [44-65]	DEXA	ASMI	6MWT
Machado et al. [93]	2021	Cross-sectional	469 (256/213)	Normal weight/Normal FFMI: 45 [34-56] Normal weight/Low FFMI: 37 [27-51] Overweight/Normal FFMI: 56 [42-69] Overweight/Low FFMI: 41 [32-66] Obese/Normal FFMI: 56 [41-70] Obese/Low FFMI: 54 [43-63]	DEXA	FFMI and ASMI	CWR CY-CPET and 6MWT
Mason et al. [94]	2021	Prospective cohort	5716 (3061/2655)	NR	CT scan	Pectoralis muscle area	6MWT
Mjid et al. [95]	2021	Cross-sectional	104 (104/0)	49 ± 22	BIA	FFM, FFMI, and SMM	6MWT
Schneider et al. [96]	2021	Cross-sectional	176 (96/80)	47 ± 16	BIA	FFM and FFMI	6MWT
Tashiro et al. [97]	2021	Cross-sectional	69 (66/3)	60 ± 24	CT scan	Pectoralis muscle and erector spinae muscle CSA	6MWT
Zanella et al. [98]	2021	Cross-sectional	38 (12/26)	51 ± 24	BIA	FFM and FFMI	6MWT

Data are expressed at mean ± standard deviation or median [interquartile range].

Definitions of abbreviations: 6MWT, six-minute walk test; 12MWT, 12-minute walk test; ASMI, appendicular skeletal muscle index; BIA, bioelectrical impedance analysis; CSA, cross-sectional area; CT scan, computed tomography scan; CWR CY-CPET, constant work-rate cycle cardiopulmonary exercise test; DEXA, dual-energy x-ray absorptiometry; ECW, extracellular water; ESWT, endurance shuttle walking test; FEV₁%predicted, maximum forced expiratory volume in one second expressed as percentage of predicted normal maximum; FFM, fat-free mass; FFMI, fat-free mass index; GOLD, global initiative for chronic obstructive lung disease; ICW, intracellular water; ICW/ECW, intracellular water to extracellular water ratio; INCR CY-CPET, incremental cycle cardiopulmonary exercise test; ISWT, incremental shuttle walk test; LBM, lean body mass; LBMI, lean body mass index; LW, lower limb water; MRI, magnetic resonance imaging; NR, not reported; PMRS, proton magnetic resonance spectroscopy; SMM, skeletal muscle mass; SMMI, skeletal muscle mass index; TM-CPET, treadmill cardiopulmonary exercise test; TW, total water; UW, upper limb water.

Protocol and registration

The protocol for this systematic review was registered on PROSPERO: International prospective register of systematic review database (ID: CRD42019141947). Due to the extent of relevant literature, this review deviated from the protocol and focussed solely on exercise test outcomes – as opposed to exercise test, clinical, and patient-reported outcomes.

Eligibility criteria

Observational studies, including research letters presenting primary data, were eligible for inclusion in this review if: 1) participants were humans aged ≥18 years with a diagnosis of COPD (physician or met spirometric criteria[1]); and 2) associations were reported between FFM and outcomes from exercise tests, including but not limited to: incremental (INCR) or constant work rate (CWR) cardiopulmonary exercise test (CPET); six-minute walk test (6MWT); incremental shuttle walk test (ISWT); endurance shuttle walk test (ESWT); or 12-minute walk test (12MWT).

Studies were excluded if: 1) they were of interventional design, a secondary data analysis (e.g. systematic review), an editorial, an opinion piece, a case study, or a conference abstract; and 2) study participants had a primary condition other than COPD or if data from COPD participants was not reported independently.

Search strategy

Five electronic databases – MEDLINE, EMBASE, Scopus, Web of Science, and Cochrane Library – were initially searched from inception to June 2020 by two independent researchers and updated in August 2021. Search terms were structured around population (e.g. COPD) and FFM (e.g. fat-free mass, muscle mass, cachexia). No search terms were developed specific to the exercise test outcomes, as the current review was conducted concurrently with another registered review (PROSPERO: CRD42020202052). Therefore, searches were performed to capture all possible outcomes. Studies were limited to the English language. The complete search strategy used for MEDLINE is shown in the supplementary material (Table S1).

Study selection

Search results were collated using Rayyan (Rayyan Systems Inc, Cambridge, MA, USA). Following removal of duplicate references, two reviewers screened titles and abstracts independently. Full-text papers were requested for studies not excluded based on title/abstract and independently assessed by two reviewers for eligibility. If consensus on eligibility could not be reached, a third reviewer was consulted to resolve the discrepancy.

Data extraction

A data extraction template was prospectively developed and pilot tested on 10 randomly selected eligible studies by two independent reviewers. Following refinement of the template, two independent reviewers extracted data on all eligible studies. Discrepancies were reviewed and discussed until consensus was reached. The list of characteristics extracted from eligible studies can be found in the supplementary materials (Table S2).

Table 2. Differences in rate of O₂ consumption (V^’O₂) during cardiopulmonary exercise testing (CPET) according to fat-free mass (FFM) status in people with COPD.

Author	Groups (size and definition)	Outcome measures	Group comparison
FFM
Aiello et al. [55]	Above median FFM (n = NR, FFM > 42kg for females and > 54 kg for males) Below median FFM (n = NR, FFM < 42kg for females and < 54 kg for males)	V^’O2,peak (ml/min) Above median FFM: 1438 ± 483 ml/min Below median FFM: 1141 ± 342 ml/min	V^’O2,peak (ml/min) Above median FFM versus below median FFM (p < 0.05)
FFMI
Fermoselle et al. [47]	Muscle wasted (n = 18, BMI ≤ 21 kg/m^2 and FFMI ≤ 18 kg/m^2 for males) Non-muscle wasted (n = 11, BMI > 21 kg/m^2 and FFMI > 18 kg/m^2 for males)	V^’O2,peak (% predicted) Muscle wasted: 29 ± 7% predicted Non-muscle wasted: 77 ± 18% predicted	V^’O2,peak (% predicted) Muscle wasted versus non-muscle wasted (p ≤ 0.001)
Vogiatzis et al. [41]	Cachectic (n = 10, FFMI < 17 kg/m^2) Non-Cachectic (n = 19, FFMI ≥ 17 kg/m^2)	V^’O2,peak (ml/kg/min) Cachectic: 14 ± 1.6 ml/kg/min Non-Cachectic: 15 ± 1 ml/kg/min	V^’O2,peak (ml/kg/min) Cachectic versus non-Cachectic (p > 0.05)
Teopompi et al. [54]	FFMI depleted (n = 14, FFMI < 14.6 kg/m^2 for females and < 16.7 kg/m^2 for males) FFMI non-depleted (n = 43, FFMI > 14.6 kg/m^2 for females and > 16.7 kg/m^2 for males)	V^’O2,peak (ml/min) FFMI depleted: 942 ± 258 ml/min FFMI non-depleted: 1218 ± 413 ml/min	V^’O2,peak (ml/min) FFMI depleted versus FFMI non-depleted (p = 0.02)
Natanek et al. [52]	FFMI depleted (n = 16, FFMI < 15 kg/m^2 for females and < 16 kg/m^2 for males) FFMI non-depleted (n = 16, FFMI > 15 kg/m^2 for females and > 16 kg/m^2 for males)	V^’O2,peak (ml/kg/min) FFMI depleted: 11.1 ml/kg/min [9.4-14.1] FFMI non-depleted: 13.6 ml/kg/min [9.7-15.1]	V^’O2,peak (ml/kg/min) FFMI depleted versus FFMI non-depleted (p = 0.27)
Baarends et al. [23]	FFMI Depleted (n = 26, FFMI ≤ 15 kg/m^2 for females and ≤ 16 kg/m^2 for males) FFMI non-depleted (n = 36, FFMI > 15 kg/m^2 for females and > 16 kg/m^2 for males)	V^’O2,peak (ml/min; % predicted) FFMI Depleted: 755 ± 205 ml/min; 55 ± 13% predicted FFMI non-depleted: 1015 ± 235 ml/min; 58 ± 19% predicted	V^’O2,peak (ml/min; % predicted) FFMI depleted versus FFMI non-depleted (p < 0.001 for ml/min; p > 0.05 for % predicted)
Silveira et al. [58]	FFMI Depleted (n = 21, FFMI ≤ 15 kg/m^2 for females and ≤ 16 kg/m^2 for males) FFMI non-depleted (n = 33, FFMI > 15 kg/m^2 for females and > 16 kg/m^2 for males)	V^’O2 at anaerobic threshold (ml/min) FFMI depleted: 693 ± 155 ml/min FFMI non-depleted: 931 ± 312 ml/min	V^’O2 at anaerobic threshold (ml/min) FFMI depleted versus FFMI non-depleted (p < 0.01)
Franssen et al. [36]	Sarcopenic (n = 7, comparable FMI but reduced FFMI compared to healthy controls) Underweight (n = 6, FMI and FFMI were reduced compared to sarcopenic COPD participants)	V^’O2,peak (% predicted) Sarcopenic: 62 ± 5% predicted Underweight: 57 ± 3% predicted	V^’O2,peak (% predicted) Sarcopenic versus underweight (p > 0.05)
Franssen et al. [30]	FFMI Depleted (n = 28, FFMI ≤ 15 kg/m^2 for females and ≤ 16 kg/m^2 for males) FFMI non-depleted (n = 59, FFMI > 15 kg/m^2 for females and > 16 kg/m^2 for males)	V^’O2,peak (ml/kg-FFM/min) FFMI Depleted: 21.9 ± 1.3 ml/kg-FFM/min FFMI non-depleted: 19.2 ± 0.8 ml/kg-FFM/min	V^’O2,peak (ml/kg-FFM/min) FFMI depleted versus FFMI non-depleted (p > 0.05)
Machado et al. [94]	Normal weight FFMI depleted (n = 118, BMI = 18.5-24.6 kg/m^2, FFMI < 10^th percentile) Normal weight FFMI non-depleted (n = 88, BMI = 18.5-24.6 kg/m^2, FFMI > 10^th percentile) Overweight FFMI depleted (n = 91, BMI = 25-29.99 kg/m^2, FFMI < 10^th percentile) Overweight FFMI non-depleted (n = 66, BMI = 25-29.99 kg/m^2, FFMI > 10^th percentile) Obese FFMI depleted (n = 45, BMI ≥ 30 kg/m^2, FFMI < 10^th percentile) Obese FFMI non-depleted (n = 61, BMI ≥ 30 kg/m^2, FFMI > 10^th percentile)	V^’O2,peak (ml/min; % predicted) Normal weight FFMI depleted: 811 ml/min [661–978]; 50% predicted [36–73] Normal weight FFMI non-depleted: 998 ml/min [805–1,234]; 57% predicted [47–78] Overweight FFMI depleted:1088 ml/min [900–1291]; 58% predicted [48–77] Overweight FFMI non-depleted: 1,108 ml/min [872–1,349]; 67% predicted [51–76] Obese FFMI depleted: 1267 ml/min [974–1542]; 64% predicted [54–75] Obese FFMI non-depleted: 1126 ml/min [892–1368; 81% predicted [55–112]	V^’O2,peak (ml/min; % predicted) Normal weight FFMI depleted versus Normal weight FFMI non-depleted (p < 0.001 for ml/min; p < 0.05 for % predicted) Overweight FFMI depleted versus Overweight FFMI non-depleted (p > 0.05 for ml/min; p > 0.05 for % predicted) Obese FFMI depleted versus Obese FFMI non-depleted (p > 0.05 for ml/min; p < 0.05 for % predicted)
LBMI
Malaguti et al. [45]	LBMI non-depleted (n = 28, LBMI ≥ 15 kg/m^2 for females and ≥ 16 kg/m^2 for males) LBMI depleted (n = 11, LBMI < 15 kg/m^2 for females and < 16 kg/m^2 for males)	V^’O2,peak (ml/min; ml/kg/min; % predicted) LBMI non-depleted: 1072 ± 289 ml/min; 16 ± 3.5 ml/kg/min; 68.3 ± 13.9% predicted LBMI depleted: 703 ± 171 ml/min; 14.9 ± 4.9 ml/kg/min; 59.1 ± 12% predicted	V^’O2,peak (ml/min; ml/kg/min; % predicted) LBMI non-depleted versus LBMI depleted (p ≤ 0.05 for ml/min; p > 0.05 for ml/kg/min; p ≤ 0.05 for % predicted)
ASMI/SMMI
Van de bool et al. [60]	Sarcopenic (n = 96, ASMI < 5.67 kg/m^2 for females and < 7.23 kg/m^2 for males) Sarcopenic and abdominally obese (n = 341, ASMI < 5.67 kg/m^2 for females and < 7.23 kg/m^2 for males and android/gynoid fat mass ratio > 0.8 for females and > 1 for males) Non-sarcopenic (n = 68, ASMI ≥ 5.67 kg/m^2 for females and ≥ 7.23 kg/m^2 for males)	V^’O2,peak (ml/min; % predicted) Sarcopenic: 935.5 ml/min [744–1098.3]; 45.9% predicted [27.8–71.9] Sarcopenic and abdominally obese: 1,045 ml/min [864.3–1238.8]; 38.3% predicted [28.3–53.0] Non-sarcopenic:1468.0 ml/min [1292.3–1682.8]; 40.8% predicted [34.6–52.6]	V^’O2,peak (ml/min) Sarcopenic versus Sarcopenic and abdominally obese versus Non-sarcopenic (p < 0.05) V^’O2,peak (% predicted) Sarcopenic versus Sarcopenic and abdominally obese (p < 0.05) Non-sarcopenic versus Sarcopenic or sarcopenic and abdominally obese (p > 0.05)
Machado et al. [94]	Normal weight ASMI depleted (n = 180, BMI = 18.5-24.6 kg/m^2, ASMI < 5.67 kg/m^2 for females and < 7.23 kg/m^2 for males) Normal weight ASMI non-depleted (n = 25, BMI = 18.5-24.6 kg/m^2, ASMI ≥ 5.67 kg/m^2 for females ≥ 7.23 kg/m^2 for males) Overweight ASMI depleted (n = 94, BMI = 25-29.99 kg/m^2, ASMI < 5.67 kg/m^2 for females and < 7.23 kg/m^2 for males) Overweight ASMI non-depleted (n = 62, BMI = 25-29.99 kg/m^2, ASMI ≥ 5.67 kg/m^2 for females ≥ 7.23 kg/m^2 for males) Obese ASMI depleted (n = 16, BMI ≥ 30 kg/m^2, ASMI < 5.67 kg/m^2 for females and < 7.23 kg/m^2 for males) Obese ASMI non-depleted (n = 87, BMI ≥ 30 kg/m^2, ASMI ≥ 5.67 kg/m^2 for females ≥ 7.23 kg/m^2 for males)	V^’O2,peak (ml/min; % predicted) Normal weight ASMI depleted: 888 ml/min [691–1034]; 52% predicted [37–72] Normal weight ASMI non-depleted: 1,244 ml/min [880–1438]; 77% predicted [51–102] Overweight ASMI depleted: 1060 ml/min [873–1303]; 56% predicted [46–76] Overweight ASMI non-depleted 1156 ml/min [900–1402]; 67% predicted [53–88] Obese ASMI depleted 958 ml/min [818–1147]; 55% predicted [46–70] Obese ASMI non-depleted 1230 ml/min [995–1501]; 67% predicted [55–97]	V^’O2,peak (ml/min; % predicted) Normal weight FFMI depleted versus Normal weight FFMI non-depleted (p < 0.001 for ml/min; p < 0.001 for % predicted) Overweight FFMI depleted versus Overweight FFMI non-depleted (p > 0.05 for ml/min; p < 0.01 for % predicted) Obese FFMI depleted versus Obese FFMI non-depleted (p < 0.05 for ml/min; p > 0.05 for % predicted)
Other
Vilaro et al. [38]	Normal thigh muscle mass index (n = 10, thigh muscle mass index > 19.40 kg/m^2) Low thigh muscle mass index (n = 6, thigh muscle mass index < 18.5 kg/m^2)	V^’O2,peak (L/min) Normal thigh muscle mass index:1.3 ± 0.3 L/min Low thigh muscle mass index: 0.90 ± 0.4 L/min	V^’O2,peak (L/min) Normal thigh muscle mass index versus Low thigh muscle mass index (p < 0.05)

Data are expressed at mean ± standard deviation or median [interquartile range].

Bold p-values indicate level of significance (p ≤ 0.05).

Definitions of abbreviations: ASMI, appendicular skeletal muscle index; BMI, body mass index; CSA, cross-sectional area; FFM, fat-free mass; FFMI, fat-free mass index; FMI, Fat mass index; LBMI, lean body mass index; METs, metabolic equivalents; NR, not reported; V^’O_2,peak, peak rate of oxygen consumption.

Risk of bias assessment

Risk of bias assessment was undertaken using the Quality in Prognosis Studies (QUIPS) [100] tool, which consists of six subdomains: study participation; study attrition; prognostic factor measurement; outcome measurement; study confounding; statistical analysis and reporting. Due to the cross-sectional nature of this systematic review, the study attrition subdomain was not recorded or scored. Two independent reviewers conducted the risk of bias assessment for all eligible studies. A study was classified as having a ‘high’ risk of bias if it had ≥1 ‘high’ subdomains or ≥3 ‘moderate’ subdomains. Additionally, a study was classified as ‘moderate’ if it had 1-2 ‘moderate’ subdomains and no ‘high’ subdomains. Finally, a study was classified as having a ‘low’ risk of bias when all subdomains were classified as ‘low’. This rating system was adapted and modified from a previous review that used the QUIPS tool [100].

Data analysis

Due to the considerable heterogeneity in the ways that FFM and exercise responses were assessed across the studies, the pre-planned meta-analysis was not possible. A narrative description of the data extracted was undertaken. Narrative descriptions included: participant characteristics; measures of body composition; study outcomes; and results. Reported associations between FFM measures and exercise test outcomes were recorded and tabulated for comparison across studies.

Results

Study breakdown

A total of 6,620 references (5,956 and 644 from the initial and follow-up searches, respectively) were identified from the electronic database searches. Of these, 6,537 studies did not meet our inclusion criteria and were subsequently excluded. Thus, a total of 83 studies were included in this review (Figure 1) [10, 15,16, 20–79, 81–99, 102].

Figure 1. PRISMA flow diagram of included and excluded studies for initial and second search.

Characteristics of included studies and participants

Studies included in this review are described in Table 1. There were 18 770 participants with COPD (61% male, 39% female) included across the 83 studies, which were published between 1989 and 2021. Sixty-five of the 83 studies (78%)[10, 16, 20–31, 33–39, 42–49, 51–55, 57–60, 62–65, 67, 72–75, 77–79, 81,82, 84,85, 88–90, 92–94, 96–99, 102] employed a cross-sectional design, whereas 15 (18%)[15, 32, 41, 50, 56, 66, 68, 70,71, 76, 83, 86,87, 91, 95] and three (4%)[40, 61, 69] studies utilised a longitudinal or combined cross-sectional and longitudinal design, respectively (Table 1).

FFM was most commonly assessed by bioelectrical impedance analysis (BIA) (n = 53, 64%)[10, 15,16, 21, 25,26, 28–30, 33, 35–37, 39–44, 46, 50–56, 58, 61, 63–67, 69,70, 73, 76–79, 81–86, 90, 92, 96,97, 99, 102] or dual energy x-ray absorptiometry (DEXA) (n = 15, 18%) [22, 24, 27, 31, 34, 45, 48,49, 60, 62, 66, 72, 75, 93,94]. Fewer studies used computed tomography (CT) (n = 8, 10%) [57, 68, 74, 87, 89, 91, 95, 98], magnetic resonance imaging (MRI) (n = 2, 2%) [38, 59], ultrasound (n = 2, 2%)[71, 77] or other assessment methods (n = 5, 6%) [20, 23, 32, 76, 88]. Three (4%) studies[66, 76,77] used more than one body composition assessment technique, whereas a single (1%) study[47] did not specify the method of assessment used (Table 1).

A range of exercise tests were used, including: 6MWT (n = 52, 63%) [16, 22, 33–35, 38–42, 46, 48–52, 56,57, 59,60, 62, 64–74, 76, 78,79, 81, 84–88, 90–99, 102]; CPET (n = 26, 31%) [15, 23–25, 27–30, 36–38, 41, 43–45, 47, 52–55, 58, 60, 70, 75, 89, 94]; ISWT (n = 7, 8%) [31, 44, 61, 63, 77, 82,83]; 12MWT (n = 6, 7%) [10, 20,21, 26, 32, 44]; ESWT (n = 1, 1%) [31]; and 3-minute constant rate step test (3MST) (n = 1, 1%) (Table 1) [92].

Risk of bias

Sixty-nine of the 83 studies (83%) were classified as having a ‘high’ risk of bias. Of the remaining 14 studies, nine (11%) and five (6%) were classified as having a ‘moderate’ and ‘low’ risk of bias, respectively. Table S3 in the supplementary material outlines the risk of bias classification for each study.

Table 3. Differences in the distance walked during the six-minute walk test (6MWD) according to fat-free mass (FFM) status in people with COPD.

Author	Groups (size and definition)	Outcome measures	Group comparison
FFMI
Joppa et al. [67]	Sarcopenic obesity (n = 197, FFMI < 10^th percentile and FMI ≥ 90^th percentile) Sarcopenia (n = 485, FFMI < 10^th percentile and FMI < 90^th percentile) Obese (n = 309, FFMI ≥ 10^th percentile and FMI ≥ 90^th percentile) Normal body composition (n = 1009, FFMI ≥ 10^th percentile and FMI < 90^th percentile)	6MWD (metres) Sarcopenic obesity: 342 ± 143 metres Sarcopenia: 372 ± 125 metres Obese: 376 ± 125 metres Normal body composition: 380 ± 114 metres	6MWD (metres) Sarcopenic obesity versus Sarcopenia, Obese, and Normal body composition participant (p < 0.01)
Matkovic et al. [72]	Reduced 6MWD (n = 53, 6MWD ≤ 350 metres) Preserved 6MWD (n = 58, 6MWD > 350 metres)	FFMI (kg/m^2) Reduced 6MWD: 17.6 ± 2.8 kg/m^2 Preserved 6MWD: 19.0 ± 2.5 kg/m^2	FFMI (kg/m^2) Reduced 6MWD versus preserved 6MWD (p < 0.01)
Lou et al. [65]	Group 1 (n = 44, 6MWD ≥ 350 metres) Group 2 (n = 34, 6MWD = 259-349 metres) Group 3 (n = 51, 6MWD = 150-258 m) Group 4 (n = 106, 6MWD ≤ 149 metres)	FFMI (kg/m^2): Group 1: 16.2 ± 2.1 kg/m^2 Group 2: 15.4 ± 2.0 kg/m^2 Group 3: 15.6 ± 1.8 kg/m^2 Group 4: 14.2 ± 1.5 kg/m^2	FFMI (kg/m^2) Group 4 versus Group 1, Group 2, and Group 3 (p < 0.001)
Villaca et al. [34]	FFMI depleted (n = 19, FFMI < 15 kg/m^2 for females and < 16 kg/m^2 for males) FFMI non-depleted (n = 29, FFMI ≥ 15 kg/m^2 for females and ≥ 16 kg/m^2 for males)	6MWD (metres) FFMI depleted: 443.5 ± 65.5 metresFFMI non-depleted: 506.1 ± 68 metres	6MWD (metres): FFMI depleted versus FFMI non-depleted (p < 0.05)
Fekete et al. [90]	FFMI depleted (n = 14, FFMI < 15 kg/m^2 for females and < 16 kg/m^2 for males) FFMI non-depleted (n = 36, FFMI ≥ 15 kg/m^2 for females and ≥ 16 kg/m^2 for males)	6MWD (metres) FFMI depleted: 223 ± 126 metres FFMI non-depleted: 321 ± 90 metres	6MWD (metres) FFMI depleted versus FFMI non-depleted (p = 0.002)
Vogiatzis et al. [41]	FFMI depleted (n = 10, FFMI < 17 kg/m^2 for males) FFNI non-depleted (n = 19, FFMI ≥ 17 kg/m^2 for males)	6MWD (metres) FFMI depleted: 273 ± 44 metres FFMI non-depleted: 344 ± 21 metres	6MWD (metres) FFMI depleted versus FFMI non-depleted (p < 0.05)
Mjid et al. [96]	FFMI depleted (n = 21, FFMI < 16 kg/m^2) FFMI non-depleted (n = 83, FFMI ≥ 16 kg/m^2)	6MWD (metres; % predicted) FFMI depleted: 424 ± 117 metres; 56 ± 25% predicted FFMI non-depleted: 462 ± 110 metres; 67 ± 22% predicted	6MWD (metres; % predicted) FFMI depleted versus FFMI non-depleted (p = 0.042 for metres; p = 0.05 for % predicted)
Tunsupon and Mador[70]	Obese (n = 34; BMI ≥ 30 kg/m^2 and FFMI ≥ 16 kg/m^2) Non-obese (n = 30; BMI < 30 kg/m^2 and FFMI ≥ 16 kg/m^2) FFMI depleted (n = 8; FFMI < 16 kg/m^2)	6MWD (metres) Obese: 374 ± 82 metres Non-obese: 434 ± 108 metres FFMI depleted: 423 ± 88 metres	6MWD (metres) FFMI depleted versus FFMI non-depleted (p = 0.044 for all between-group comparisons)
Machado et al. [78]	Sarcopenic obesity (n = 74, FFMI < 10^th percentile and FMI ≥ 90^th percentile) Sarcopenic (n = 56, FFMI < 10^th percentile and FMI < 90^th percentile) Normal body composition (n = 106, FFMI ≥ 10^th percentile and FMI < 90^th percentile) Obese (n = 34, FFMI ≥ 10^th percentile and FMI ≥ 90^th percentile)	6MWD (metres; % predicted) Sarcopenic obesity: 472 metres [390–506]; 83% predicted [72–90] Sarcopenic: 473 metres [416–524]; 85% predicted [71–95] Normal body composition: 465 metres [414–505]; 88% predicted [81–99] Obese: 480 metres [365–541]; 90% predicted [73–98]	6MWD (% predicted) Sarcopenic obesity versus normal body composition (p < 0.05). Normal body composition versus sarcopenic and obese (p > 0.05). 6MWD (metres) Between all groups (p > 0.05)
Schneider et al. [97]	Inactive Sarcopenic obesity (n = 29, METs < 3, FFMI < 10^th percentile and FMI ≥ 90^th percentile) Active Sarcopenic obesity (n = 14, METs ≥ 3, FFMI < 10^th percentile and FMI ≥ 90^th percentile) Inactive Sarcopenic (n = 15, METs < 3, FFMI < 10^th percentile and FMI < 90^th percentile) Active Sarcopenic (n = 22, METs ≥ 3, FFMI < 10^th percentile and FMI < 90^th percentile) Inactive Normal body composition (n = 38, METs < 3, FFMI ≥ 10^th percentile and FMI < 90^th percentile) Active Normal body composition (n = 30, METs ≥ 3, FFMI ≥ 10^th percentile and FMI < 90^th percentile) Inactive Obese (n = 17, METs < 3, FFMI ≥ 10^th percentile and FMI ≥ 90^th percentile) Active obese (n = 11, METs ≥ 3, FFMI ≥ 10^th percentile and FMI ≥ 90^th percentile)	6MWD (metres; % predicted) Inactive Sarcopenic obesity: 415 ± 91 metres; 75 ± 17% predicted Active Sarcopenic obesity: 455 ± 121 metres; 81 ± 20% predicted Inactive Sarcopenic: 425 ± 85 metres; 77 ± 17% predicted Active Sarcopenic: 496 ± 49 metres; 88 ± 9% predicted Inactive Normal body composition: 444 ± 83 metres; 87 ± 16% predicted Active Normal body composition: 474 ± 56 metres; 89 ± 11% predicted Inactive Obese: 424 ± 94 metres; 85 ± 16% predicted Active obese: 510 ± 75 metres; 94 ± 15% predicted	6MWD (metres) Inactive sarcopenic obesity versus active obese and active sarcopenic (p < 0.05) All other group comparison (p > 0.05) 6MWD (% predicted) Inactive sarcopenic obesity versus active normal body composition and active obese groups (p < 0.05) All other group comparison (p > 0.05)
Budweiser et al. [35]	FFMI depleted (n = 33, FFMI < 15 kg/m^2 for females and < 17.4 kg/m^2 for males) FFMI non-depleted (n = 60, FFMI ≥ 15 kg/m^2 for females and ≥ 17.4 kg/m^2 for males)	6MWD (% predicted) FFMI depleted: 60 ± 16% predicted FFMI non-depleted: 48 ± 16% predicted	6MWD (% predicted) FFMI depleted versus FFMI non-depleted (p < 0.001)
Machado et al. [94]	Normal weight FFMI depleted (n = 118, BMI = 18.5-24.6 kg/m^2, FFMI < 10^th percentile) Normal weight FFMI non-depleted (n = 88, BMI = 18.5-24.6 kg/m^2, FFMI > 10^th percentile) Overweight FFMI depleted (n = 91, BMI = 25-29.99 kg/m^2, FFMI < 10^th percentile) Overweight FFMI non-depleted (n = 66, BMI = 25-29.99 kg/m^2, FFMI > 10^th percentile) Obese FFMI depleted (n = 45, BMI ≥ 30 kg/m^2, FFMI < 10^th percentile) Obese FFMI non-depleted (n = 61, BMI ≥ 30 kg/m^2, FFMI > 10^th percentile)	6MWD (metres; % predicted) Normal weight FFMI depleted: 410 ± 122 metres; 62 ± 18% predicted Normal weight FFMI non-depleted: 458 ± 121 metres; 70 ± 17% predicted Overweight FFMI depleted: 414 ± 126 metres; 67 ± 17% predicted Overweight FFMI non-depleted: 434 ± 118 metres; 70 ± 70% predicted Obese FFMI depleted: 430 ± 118 metres; 69 ± 16% predicted Obese FFMI non-depleted: 402 ± 108 metres; 70 ± 17% predicted	6MWD (metres; % predicted) Normal weight FFMI depleted versus Normal weight FFMI non-depleted (p < 0.01 for metres; p < 0.001 for % predicted) Overweight FFMI depleted versus Overweight FFMI non-depleted (p > 0.05 for metres; p > 0.05 for % predicted) Obese FFMI depleted versus Obese FFMI non-depleted (p > 0.05 for metres; p > 0.05 for % predicted)
Barreiro et al. [102]	FFMI non-depleted (n = 14; BMI > 21 kg/m^2 and FFMI > 18 kg/m^2) FFMI depleted (n = 15; BMI ≤ 21 kg/m^2 FFMI ≤ 18 kg/m^2)	6MWD (metres) FFMI non-depleted: 408 ± 11 metres FFMI depleted: 380 ± 113 metres	6MWD (metres) FFMI non-depleted versus FFMI depleted (p > 0.05)
Berton et al. [51]	FFMI depleted (n = 31, FFMI < 15 kg/m^2 for females and < 16 kg/m^2 for males) FFMI non-depleted (n = 31, FFMI ≥ 15 kg/m^2 for females and ≥ 16 kg/m^2 for males)	6MWD (metres) FFMI depleted: 387 ± 92 metresFFMI non-depleted: 406 ± 89 metres	6MWD (metres) FFMI depleted versus FFMI non-depleted (p > 0.05)
Chua et al. [79]	Philippine Normative value based FFMI depleted (n = 20. FFMI < 8.33 kg/m^2 for females and < 12.5 kg/m^2 for males) Philippine Normative value based FFMI non-depleted (n = 21, FFMI ≥ 8.33 kg/m^2 for females and ≥ 12.5 kg/m^2 for males) Extrapolated 10^th percentile value based FFMI depleted (n = 30, FFMI < 10.5 kg/m^2 for females and < 13.8 kg/m^2 for males) Extrapolated 10^th percentile value based FFMI non-depleted (n = 11, FFMI ≥ 10.5 kg/m^2 for females and ≥ 13.8 kg/m^2 for males)	6MWD (metres) Philippine Normative value based FFMI depleted: 389 ± 59 metres Philippine Normative value based FFMI non-depleted: 373 ± 114 metres Extrapolated 10^th percentile value based FFMI depleted: 385 ± 66 metres Extrapolated 10^th percentile value based FFMI non-depleted: 369 ± 142 metres	6MWD (metres) Philippine Normative value based FFMI depleted versus Philippine Normative value based FFMI non-depleted (p > 0.05) Extrapolated 10^th percentile value based FFMI depleted versus Extrapolated 10^th percentile value based FFMI non-depleted (p > 0.05)
Natanek et al. [52]	FFMI depleted (n = 16, FFMI < 15 kg/m^2 for females and < 16 kg/m^2 for males) FFMI non-depleted (n = 16, FFMI ≥ 15 kg/m^2 for females and ≥ 16 kg/m^2 for males)	6MWD (metres): FFMI depleted: 384 ± 140 metresFFMI non-depleted: 398 ± 139 metres	6MWD (metres) FFMI depleted versus FFMI non-depleted (p > 0.05)
LBMI
Shoup et al. [22]	Low LBMI (n = 13, LBMI < 12.9 kg/m^2 in females and < 16.3 kg/m^2 in males) Preserved LBMI (n = 37, LBMI ≥ 12.9 kg/m^2 in females and ≥ 16.3 kg/m^2 in males)	6MWD (data not reported)	6MWD Low LBMI versus preserved LBMI (p > 0.05)
Pelegrino et al. [39]	Low LBMI (n = 32, LBMI < 15 kg/m^2 in females and < 16 kg/m^2 in males) Preserved LBMI (n = 36, LMBI ≥ 15 kg/m^2 in females and ≥ 16 kg/m^2 in males)	6MWD (metres; % predicted) Low LBMI: 470.3 ± 68.5 metres; 91.9 ± 11.7% predicted Preserved LBMI: 448.2 ± 89.2 metres; 94.4 ± 17.2% predicted	6MWD (metres; % predicted) Low LBMI versus Preserved LBMI (p > 0.05 for metres; p > 0.05 for % predicted)
Matkovic et al. [72]	Reduced 6MWD (n = 53, 6MWD ≤ 350 metres) Preserved 6MWD (n = 58, 6MWD > 350 metres)	LMBI (kg/m^2): Reduced 6MWD: 16.7 ± 2.6 kg/m^2 Preserved 6MWD: 18.0 ± 2.4 kg/m^2	LMBI (kg/m^2) Reduced 6MWD versus Preserved 6MWD (p < 0.05)
ASMI/SMMI
Vilaro et al. [38]	Normal thigh muscle mass index (n = 10, thigh muscle mass index > 19.40 kg/m^2) Low thigh muscle mass index (n = 6, thigh muscle mass index < 18.5 kg/m^2)	6MWD (metres) Normal thigh muscle mass index: 532 ± 67 metres Low thigh muscle mass index: 406 ± 92 metres)	6MWD (metres) Higher versus lower thigh muscle mass index (p < 0.01)
Byun et al. [73]	Sarcopenic (n = 20, SMMI ≤ 2 SDs below normal sex specific mean and HGS ≤ 20kg for females and ≤ 30kg for males) Non-sarcopenic (n = 60, SMMI > 2 SDs below normal sex specific mean and HGS > 20kg for females and > 30kg for males)	6MWD (metres) Sarcopenic: 351 ± 78 metres Non-sarcopenic: 389 ± 67 metres	6MWD (metres) Sarcopenic vs non-sarcopenic (p = 0.042)
Cebron Lipovec et al. [66]	Sarcopenic (ASMI < 5.67 kg/m^2 for females and < 7.23 kg/m^2 for males) Non-sarcopenic (ASMI ≥ 5.67 kg/m^2 for females and ≥ 7.23 kg/m^2 for males)	6MWD (metres) Sarcopenic: 316 ± 113 metres Non-sarcopenic: 357 ± 92 metres	6MWD (metres) Sarcopenic vs non-sarcopenic (p = 0.046)
Demircioglu et al. [85]	Sarcopenic (SMMI < 9.84 kg/m^2 for females and < 10.37 kg/m^2 for males) Non-sarcopenic (SMMI ≥ 9.84 kg/m^2 for females and ≥ 10.37 kg/m^2 for males)	6MWD (metres) Sarcopenia: 238 ± 106 metres Non-sarcopenic: 309 ± 123 metres	6MWD (metres) Sarcopenic vs non-sarcopenic (p < 0.001)
Van de Bool et al. [60]	Sarcopenic (n = 96, ASMI < 5.67 kg/m^2 for females and < 7.23 kg/m^2 for males) Sarcopenic and abdominally obese (n = 341, ASMI < 5.67 kg/m^2 for females and < 7.23 kg/m^2 for males and android/gynoid fat mass ratio > 0.8 for females and > 1 for males) Non-sarcopenic (n = 68, ASMI ≥ 5.67 kg/m^2 for females and ≥ 7.23 kg/m^2 for males)	6MWD (metres, data not reported)	6MWD (metres) Sarcopenic and sarcopenic and abdominally obese males versus non-sarcopenic males (p < 0.05) All three groups for females (p > 0.05)
Perrot et al. [86]	Sarcopenic (n = 26, SMMI < 8.87/6.42 kg/m^2 and handgrip strength (HGS)<30/20 kg for males/females) Non-sarcopenic (n = 28, SMMI ≥ 8.87/6.42 kg/m^2 and HGS ≥ 30/20 kg for males/females)	6MWD (metres) Sarcopenic: 161 ± 111 metres Non-sarcopenic: 217 ± 111 metres	6MWD (metres): Sarcopenic versus Non-sarcopenic (p = 0.10)
Kanezaki et al. [92]	Sarcopenic (n = 16, ASMI < 5.7 kg/m^2 + HGS < 18 kg for females and ASMI < 7.0 kg/m^2 + HGS < 28 kg for males) Non-sarcopenic (n = 44, ASMI ≥ 5.7 kg/m^2 + HGS ≥ 18 kg for females and ASMI ≥ 7.0 kg/m^2 + HGS ≥ 28 kg for males)	6MWD (metres; % predicted) Sarcopenic: 322 ± 100 metres; 78 ± 22% predicted Non-sarcopenic: 430 ± 93 metres; 100 ± 26% predicted	6MWD (metres; % predicted) Sarcopenic versus Non-sarcopenic (p < 0.005 for metres; p < 0.01 for % predicted)
Lage et al. [93]	Sarcopenic (n = 20, ASMI < 5.5 kg/m^2 for females and < 7.0 kg/m^2 for males) Non-sarcopenic (n = 15, ASMI ≥ 5.5 kg/m^2 for females and ≥ 7.0 kg/m^2 for males)	6MWD (metres; % predicted) Sarcopenic: 356 metres [309–404]; 68% predicted [59–77] Non-sarcopenic: 379 metres [317–440]; 71.6% predicted [60.9–82.2]	6MWD (metres; % predicted) Sarcopenic versus Non-sarcopenic (p = 0.54 for metres; p = 0.56 for % predicted)
Machado et al. [94]	Normal weight ASMI depleted (n = 180, BMI = 18.5-24.6 kg/m^2, ASMI < 5.67 kg/m^2 for females and < 7.23 kg/m^2 for males) Normal weight ASMI non-depleted (n = 25, BMI = 18.5-24.6 kg/m^2, ASMI ≥ 5.67 kg/m^2 for females ≥ 7.23 kg/m^2 for males) Overweight ASMI depleted (n = 94, BMI = 25-29.99 kg/m^2, ASMI < 5.67 kg/m^2 for females and < 7.23 kg/m^2 for males) Overweight ASMI non-depleted (n = 62, BMI = 25-29.99 kg/m^2, ASMI ≥ 5.67 kg/m^2 for females ≥ 7.23 kg/m^2 for males) Obese ASMI depleted (n = 16, BMI ≥ 30 kg/m^2, ASMI < 5.67 kg/m^2 for females and < 7.23 kg/m^2 for males) Obese ASMI non-depleted (n = 87, BMI ≥ 30 kg/m^2, ASMI ≥ 5.67 kg/m^2 for females ≥ 7.23 kg/m^2 for males)	6MWD (metres; % predicted) Normal weight ASMI depleted: 417 ± 123 metres; 63 ± 18% predicted Normal weight FFMI non-depleted: 523 ± 92 metres; 81 ± 12% predicted Overweight FFMI depleted: 391 ± 122 metres; 64 ± 17% predicted Overweight FFMI non-depleted: 471 ± 110 metres; 76 ± 15% predicted Obese FFMI depleted: 356 ± 97 metres; 59 ± 15% predicted Obese FFMI non-depleted: 426 ± 114 metres; 71 ± 16% predicted	6MWD (metres; % predicted) Normal weight ASMI depleted versus Normal weight ASMI non-depleted (p < 0.001 for metres; p < 0.001 for % predicted) Overweight ASMI depleted versus overweight ASMI non-depleted (p < 0.001 for metres; p < 0.01 for % predicted) Obese ASMI depleted versus Obese ASMI non-depleted (p < 0.05 for metres; p < 0.01 for % predicted)
Other
De Blasio et al. [64]	Above median impedance ratio (n = 106, 122.7 kHz for females and 124.4 kHz) Below median impedance ratio (n = 106, 122.7 kHz for females and 124.4 kHz)	6MWD (metres) Above median impedance ratio: Females [240–349] metres; males [300–434] metres Below median impedance ratio: Females [0–60] metres; males [0–348] metres	6MWD (metres) Above median impedance ratio versus below median impedance ratio (Females, p < 0.05; males, p < 0.005)
Villaca et al. [34]	Depleted (n = 19, leg lean volume of ≤ 9.2 litres/metre) Non-depleted (n = 29, leg lean volume > 9.2 litres/metre)	6MWD (metres): Depleted: 438 ± 61 metres Non-depleted: 517 ± 63 metres	6MWD (metres) Depleted versus non-depleted (p < 0.05)
Bernardes et al. [88]	Muscle wasted (n = 65, calf circumference ≤ 33cm for females and ≤ 34cm for males) Muscle non-wasted (n = 79, calf circumference > 33cm for females and > 34cm for males)	6MWD (metres; percentage of participants achieving<80% predicted) Muscle wasted: 357 ± 102 metres; 79.3% Muscle non-wasted: 391 ± 87 metres; 78.4%	6MWD (metres; percentage of participants achieving<80% predicted) Muscle wasted versus Muscle non-wasted (p = 0.046 for metres;p = 0.90 for percentage of participants achieving < 80% predicted)

Data are expressed at mean ± standard deviation or median [interquartile range].

Bold p-values indicate level of significance (p ≤ 0.05).

Definitions of abbreviations: 6MWD, distance walked during the six-minute walk test; ASMI, appendicular skeletal muscle index; BMI, body mass index; CSA, cross-sectional area; FFMI, fat-free mass index; FMI, fat mass index; HGS, hand-grip strength; LBMI, lean body mass index; METs, metabolic equivalents; NR, not reported; SMMI, skeletal muscle mass index.

Association between measures of FFM and exercise-related outcomes

Cardiopulmonary exercise testing – rate of oxygen consumption

Four studies reported associations between whole-body FFM (kg) and V^’O_2,peak (ml/min) [15, 25, 28, 55]. All four found significant correlations between FFM and V^’O_2,peak ranging from r = 0.52 to 0.71[25, 28, 55] for bivariate analyses and r = 0.55[15] for a multivariate regression analysis (all p < 0.01). Kobayashi et al.[25] also reported an association between FFM expressed as a percentage of ideal body weight (FFM%IBW) and V^’O_2,peak (r = 0.65, p < 0.01). Moreover, multivariate regression analyses performed by Kobayashi et al.[25] and Aiello et al.[55] identified FFM as a statistically significant determinant of V^’O_2,peak. A single study found that people with COPD who had a FFM above versus below the median value of 42 kg for females and 54 kg for males achieved a significantly higher mean V^’O_2,peak (ml/min) on a symptom-limited INCR cycle CPET (Table 2) [55].

Nine studies investigated potential associations between FFMI (kg/m²) and a measure of V^’O₂ either at peak exercise (n = 8)[23, 30, 36, 41, 47, 52, 54, 94] or the anaerobic threshold (n = 1) [58]. All three studies that explored bivariate correlations reported statistically significant positive associations between FFMI and each of: V^’O₂ (ml/min) at the anaerobic threshold (r = 0.51, p < 0.01) [58]; V^’O_2,peak (ml/min) (r = 0.57, p < 0.01) [23]; and percent predicted normal V^’O_2,peak (r = 0.68, p < 0.05) (Figure 2) [36]. Nine studies compared V^’O_2,peak between groups defined by varied FFMI thresholds, alone or in combination with body mass index (BMI) (Table 2) [23, 30, 36, 41, 47, 52, 54, 58, 94]. Three reported that V^’O_2,peak was higher in the FFMI non-depleted participants versus the FFMI depleted participants [47, 54, 58]. Two studies reported significant and non-significant between-group differences [23, 94]. Specifically, significant between-group differences in V^’O_2,peak were reported between FFMI depleted versus FFMI non-depleted participants when assessed in ml/min [23]; and between normal weight and obese FFMI depleted versus FFMI non-depleted participants when assessed in ml/min and as a percentage of predicted normal V^’O_2,peak for normal weight participants, and as a percentage of predicted normal V^’O_2,peak for obese participants (Table 2) [94]. However, these same studies also reported non-significant between-group differences in V^’O_2,peak when it was assessed as a percentage of predicted normal V^’O_2,peak [23]; and between overweight and obese FFMI depleted versus FFMI non-depleted participants when assessed in ml/min and as a percentage of predicted normal V^’O_2,peak for overweight participants, and ml/min for obese participants (Table 2) [94]. Three[30, 41, 52] of the four[30, 36, 41, 52] studies that reported non-significant findings between groups of higher compared to lower FFMI, assessed V^’O_2,peak in either ml/kg/min or ml/kg-FFM/min (Table 2).

Figure 2. Reported correlations (r values) between fat-free mass index (FFMI) and exercise-related outcomes. Definitions of abbreviations: 6MWD, distance walked in six-minutes; CPET, cardiopulmonary exercise test; CPET-Other, peak-CPET inspiratory capacity related measures; EET, exercise endurance time; ISWD, distance walked during the incremental shuttle walk test; PPO, peak power output; V’O₂, rate of oxygen consumption. Visual representation of all reported correlational values between FFMI and exercise-related outcomes. With closed circles representing statistically significant (p < 0.05) associations and open circles indicating statistically non-significant associations (p > 0.05). If correlation coefficients were not reported, they were not included in the graph.

Significant positive associations were reported in three[24, 27, 53] of four[24, 27, 45, 53] studies that investigated the relationship between measures of lean-body mass (LBM) and V^’O_2,peak. Positive associations were observed between V^’O_2,peak (ml/min) and each of LBM (kg) (r = 0.73, p < 0.001) [27], leg-LBM (kg) (r = 0.69, p < 0.001) [27], LBM expressed as a percentage of IBW (LBM%IBW) (r = 0.66, p < 0.001[24] and r = 0.67, p < 0.001[27]), and leg-LBM expressed as a percentage of IBW (r = 0.66, p < 0.001) [27]. LBM%IBW was a significant predictor of V^’O_2,peak (ml/min) in participants with COPD (β = 0.32, p = 0.009) [24]. Genc et al.[53] reported that LBM (kg) was associated with V^’O_2,peak when measured in ml/min (r = 0.48, p < 0.001), but not ml/kg/min (p > 0.05). Malaguti et al.[45] reported no significant associations between total leg-LBM (kg) and V^’O_2,peak.

A single study reported on group differences in V^’O₂,_peak between participants with higher versus lower lean body mass index (LBMI, kg/m²) [45]. People with COPD with LBMI values above versus below sex-specific threshold values achieved a significantly higher V^’O_2,peak expressed in both ml/min and as a percentage of predicted normal V^’O_2,peak [45]. However, these differences did not persist when V^’O_2,peak was referenced to whole-body mass (ml/kg/min) (Table 2) [45].

Two studies compared V^’O_2,peak between groups defined by thresholds of appendicular skeletal muscle mass index (ASMI, kg/m²) and either BMI or android to gynoid fat ratios [60, 94]. Both studies reported significant and non-significant results depending on the specific groups compared and/or the specific measurement of V^’O_2,peak used. Significant between-group differences in V^’O_2,peak were reported between ASMI depleted versus ASMI non-depleted participants when assessed in ml/min [60]; and between normal weight, overweight, and obese ASMI depleted versus ASMI non-depleted participants when assessed in ml/min and as a percentage of predicted normal V^’O_2,peak for normal weight participants, as a percentage of predicted normal V^’O_2,peak for obese participants, and ml/min for obese participants (Table 2) [94]. However, these same studies also reported non-significant between-group differences in V^’O_2,peak when assessed as a percentage of predicted normal V^’O_2,peak [60]; and between overweight and obese ASMI depleted versus ASMI non-depleted participants when assessed in ml/min for overweight participants, and as a percentage of predicted normal V^’O_2,peak for obese participants (Table 2) [94].

Two studies investigated the association between CT-derived measures of muscle area/density and V^’O_2,peak [89, 98]. In unadjusted analyses, Donovan et al.[89] reported that for each one standard deviation decrease in pectoralis muscle density (Hounsfield units [HU]), pectoralis muscle area (cm²), paraspinal muscle density (HU), and paraspinal muscle area (cm²), there was a statistically significant decline in V^’O_2,peak on symptom-limited INCR cycle CPET: −2.76 ml/kg/min [95%CI −3.85, −1.67]; −2.35 ml/kg/min [95%CI −3.50, −1.20]; −1.32 ml/kg/min [95%CI −2.56, −0.07]; and −2.04 ml/kg/min [95%CI −3.22, −0.85], respectively (p < 0.05). Associations between V^’O_2,peak and pectoralis muscle density (HU), pectoralis muscle area (cm²), and paraspinal muscle area (cm²) remained statistically significant after adjusting for age, sex, height, BMI, and smoking status: −2.86 ml/kg/min [95%CI −4.34, −1.37], −2.60 ml/kg/min [95%CI −3.95, −1.25], and −1.77 ml/kg/min [95%CI −3.25, −0.29], respectively (p < 0.05) [89]. During a symptom-limited INCR cycle CPET, Tashiro et al.[98] found that erector spinae muscle cross-sectional area (CSA) (r = 0.39, p = 0.003) and pectoralis muscle CSA (r = 0.36, p = 0.007) were positively associated with V^’O_2,peak (ml/kg/min). In multivariate analysis, the authors found that pectoralis muscle CSA was a significant predictor of V^’O_2,peak (β = 0.175 [95%CI 0.03, 0.319], p = 0.02), whereas erector spinae muscle CSA was not (β = 0.192 [95%CI −0.001, 0.385], p = 0.052) [98].

Two studies reported associations between various other measures of FFM (kg) and V^’O_2,peak assessed during a symptom-limited INCR cycle CPET [29, 38]. One study reported significant positive associations between measures of FFM and V’O_2,peak (ml/min) [29]. The other study reported a significantly lower V^’O_2,peak (L/min) in people with COPD with a lower compared to higher measure FFM (Table 2) [38]. Further details on the specific measures and associations can be found in the supplementary materials (refer specifically to S2.2i Cardiopulmonary exercise testing – Rate of oxygen consumption).

Cardiopulmonary exercise testing – power output

Three studies reported associations between FFM (kg) and peak power output (PPO, watts) [15, 37, 55]. Statistically significant associations between FFM and PPO were reported in two studies; bivariate linear regression (r = 0.55, p = 0.001)[55] and multiple stepwise regression (r = 0.22, p < 0.001) [15]. Additionally, FFM was identified as a statistically significant predictor of PPO in a multiple regression analysis (p < 0.05) [55]. The third study did not find a statistically significant relationship between FFM and PPO (p > 0.05) [37]. One study reported that PPO (watts) was significantly higher in people with COPD with FFM values above versus below the group median value (Table S4) [55].

Three studies reported relationships between FFMI (kg/m²) and PPO (watts) [37, 44, 60]. Two found statistically significant positive associations and one reported mixed findings (significant associations in bivariate analyses and non-significant associations in multivariate analyses): r²=0.41, β = 1.92, p = 0.01 for females and r²=0.48, β = 2.90, p < 0.01 for males [60]; r = 0.49, p < 0.001 (bivariate linear regression) and β = 3.0, p = 0.02 (multiple linear regression) [44]; data not reported (p < 0.05) (bivariate linear regression) and data not shown (p > 0.05) (multiple linear regression) (Figure 2) [37]. Three[41, 47, 75] of 10[23, 30, 36, 41, 44, 47, 54, 70, 75, 94] studies reported statistically significant differences and one[94] reported both significant and non-significant results in PPO (watts) according to groups defined by their FFMI status (Table S4).

Three studies explored associations between other measures of FFM and PPO [24, 38, 60]. Yoshikawa et al.[24] found that LBM%IBW was both a correlate (r = 0.70, p < 0.001) and predictor (β = 0.34, p = 0.006) of PPO (watts). Van de Bool et al.[60] reported lower PPO (watts) in people with COPD classified as sarcopenic or sarcopenic and abdominally obese compared to non-sarcopenic (p < 0.01 for all). Moreover, predictive models identified ASMI (kg/m²) as a significant predictor of PPO (watts) in both men (r²=0.56, β = 8.06, p < 0.01) and women with COPD (r²=0.47, β = 10.68, p < 0.01) [60]. One study, using an alternative measure of FFM, reported no statistically significant difference in PPO (watts) between people with COPD with low compared to normal thigh muscle mass index (Table S4) [38].

Cardiopulmonary exercise testing – exercise endurance time

Only one study assessed the relationship between FFMI (kg/m²) and exercise endurance time (EET, seconds) [60]. They reported that FFMI was a significant predictor of constant-load cycle EET for males with COPD (r²=0.02, β = 17.53, p = 0.01), but not females with COPD (r²=0.02, p > 0.05) (Figure 2).

Two studies compared constant-load cycle EET (seconds) between groups defined by varied thresholds of FFMI in combination with BMI [70, 94]. One study reported no statistically significant difference in EET among obese, non-obese, or FFMI depleted participants [70]. The other study reported significantly lower EET in the FFMI depleted normal weight group compared to the FFMI non-depleted normal weight group, but reported no significant differences when comparing within the overweight or obese subgroups (Table S5) [94].

Two studies compared constant-load cycle EET (seconds) between groups defined by varied thresholds of ASMI in combination with either BMI or android/gynoid fat ratio [60, 94]. Both studies reported significant and non-significant findings, with results varying based on the specific sex or BMI category assessed (refer to Table S5 for detailed summary of results).

Further measures assessing the relationship between measures of FFM and other CPET-related outcomes are reported in the supplementary material (refer specifically to S2.2.iv Cardiopulmonary exercise testing – Other measures).

Six-minute walk test (6MWT)

Four studies reported correlative associations between FFM (kg) and the 6MWD (metres) [34, 37, 40, 84]. One study reported a significant positive association (r = 0.47, p < 0.05) [40], one reported a significant negative association (Coefficient (SE)=-5.1 (1.2), p < 0.001) [37], one reported mixed findings based on FFM status [non-depleted (BMI ≥ 21 kg/m² and FFMI ≥ 15 kg/m² for females or ≥16 kg/m² for males), r = 0.48, p < 0.05; depleted (BMI < 21 kg/m² and/or FFMI < 15 kg/m² for females or <16 kg/m² for males), r = 0.02, p > 0.05] [34], and one reported no significant association between FFM and 6MWD (mild-moderate COPD, r = 0.10, p = 0.533; severe-very severe COPD, r = 0.15, p = 0.437) [84].

Twenty three studies investigated the association between FFMI and 6MWD [16, 34,35, 37, 41,42, 46, 51,52, 56, 60, 65, 67, 69,70, 72, 78,79, 90, 94, 96,97, 102]. Of these 23 studies, 13 assessed correlations between FFMI (kg/m²) and 6MWD [16, 35, 37, 42, 46, 56, 60, 65, 67, 69, 72, 79, 90]. Eight[16, 35, 42, 46, 56, 65, 72, 90] of 10[16, 35, 37, 42, 46, 56, 65, 72, 79, 90] studies reporting bivariate regression analyses found significant associations between FFMI and 6MWD (metres and percent predicted normal 6MWD) (r²=0.11–0.36, all p < 0.05[16]; r = 0.13–0.53, all p < 0.05[35, 42, 46, 65, 90]; OR = 0.814, p = 0.008[72]; 1.4 metre/year change in 6MWD per kg/m² increase in baseline FFMI, p = 0.046[56]) (Figure 2). Two studies reported non-significant bivariate correlations between FFMI (kg/m²) and 6MWD (metres) (r=-0.21–0.09, p > 0.5 [79]; data not reported) [37]. Three[16, 42, 69] of eight[16, 42, 46, 56, 60, 67, 69, 72] studies reporting multivariate regression analyses found statistically significant associations, and one[60] reported both significant and non-significant associations between FFMI and a measure of 6MWD. Details of specific outcomes of multivariate analyses are detailed in the supplementary material (refer specifically to S2.2.v Six-minute walk test (6MWT)).

Significant group differences, between some or all groups, in 6MWD were reported in 12[34,35, 41, 65, 67, 70, 72, 78, 90, 94, 96,97] of 16 studies [34,35, 41, 51,52, 65, 67, 70, 72, 78,79, 90, 94, 96,97, 102]. Machado et al.[94] reported that 6MWD (metres and percent predicted normal 6MWD) was significantly lower in normal weight FFMI depleted participants compared to normal weight FFMI non-depleted participants, but these differences did not persist when FFMI depleted versus non-depleted participants were compared within the overweight and obese categories (Table 3).

Three studies reported statistically significant positive bivariate associations between various measures of LBMI and 6MWD (metres) (r = 0.40–0.51, all p < 0.05[49,50]; OR = 0.81, p = 0.008[72]). However, one of the studies also reported a non-significant bivariate correlation between central-LBM (kg) and 6MWD (metres) (r = 0.40, p = 0.07) [49]. One[49] of three[33, 49, 72] studies to conduct multivariate analyses reported a significant relationship between LBM (kg) and 6MWD (metres). A significant relationship was reported by Hillman et al. [49], who included leg-LBM (kg) in an equation that accounted for 76% of the variance in 6MWD. The other two studies reported non-significant multivariate associations between 6MWD and LBM and (p > 0.05) [33, 72]. Three[22, 39, 72] studies reported group differences between LBMI and 6MWD, of which only one[72] reported a statistically significant between-group difference; reporting that people with COPD who walked ≤350 metres compared to >350 metres during the 6MWT had a significantly lower LBMI (Table 3).

Two[81, 85] of seven[40, 48, 62, 73, 81, 85, 93] studies reported significant bivariate associations between 6MWD (metres) and ASMI (kg/m²) or skeletal muscle mass index (SMMI) (kg/m²) (r = 0.23, p = 0.001[85]; r²=0.11, p < 0.001[81]). In contrast, five studies reported non-significant associations [40, 48, 62, 73, 93]. Three studies performed multivariate analyses between 6MWD (metres) and ASMI (kg/m²) or SMMI (kg/m²) [48, 60, 81]. One[48] reported both significant and non-significant findings based on the specific model used (refer section S2.2.v Six-minute walk test (6MWT) in the supplementary material for breakdown of individual models), whereas the other two[60, 81] found no significant relationship between 6MWD and SMMI [60, 81].

Significant differences in 6MWD between people with COPD with higher compared to lower ASMI (kg/m²) or SMMI (kg/m²) were reported in five[66, 73, 85, 92, 94] of eight studies [60, 66, 73, 85, 86, 92–94], with a seventh study[60] having significant and non-significant results based on participant sex (Table 3). In all six studies reporting significant differences, the higher ASMI or SMMI group achieved a greater 6MWD compared to the lower ASMI or SMMI group (Table 3).

Seven studies reported bivariate associations between 6MWD and measures of muscle area [59, 68, 71,72, 74, 91, 95]. Of these seven, two reported significant associations [68, 72], two reported mixed findings [59, 91], and three reported no significant associations [71, 74, 95]. Three studies[57, 72, 87] performed multivariate analyses of which only one[57] reported a significant relationship between 6MWD and a measure of FFM. The details of these associations are reported in detail in the supplementary file (refer specifically to S2.2.v Six-minute walk test (6MWT)).

The one study that reported group differences in 6MWD and muscle area in people with COPD found significantly lower mid-arm muscle circumference and arm muscle area in people with COPD that walked ≤350 metres compared to >350 metres during the 6MWT (Table 3) [72].

Six studies reported associations between various other measures of FFM and 6MWD [34, 38, 50, 64, 76, 99]. Five[34, 38, 50, 76, 99] found significant positive associations between the two variables with the sixth[64] being undetermined due to not reporting p-values. Further details on the specific measures and associations can be found in the supplementary materials (refer specifically to S2.2.v Six-minute walk test (6MWT)). Three studies assessed differences in 6MWD between groups of COPD participants with higher compared to lower measures of FFM [34, 64, 88]. Two studies[34, 64] reported significantly higher 6MWD values in the higher versus lower FFM group, whereas the third study[88] reported mixed values based on the specific 6MWD measure used (Table 3).

Incremental shuttle walk test (ISWT)

A single study by Maddocks et al.[61] reported a positive association between FFM (kg) and the distance walked during the ISWT (ISWD, metres) (r = 0.11, p = 0.02).

Two studies reported non-significant correlations between FFMI (kg/m²) and the ISWD (metres): r=-0.02, p > 0.05 (Figure 2) [61]; and β = 7.8, p = 0.27 [44]. Three studies reported differences in ISWD (metres) between COPD participants with higher compared to lower FFMI (kg/m²) [44, 61, 83]. One study reported significantly lower ISWD in the low FFMI group [83], one reported higher ISWD in the lower FFMI group [61], and one reported no difference in ISWD between the two FFMI groups (Table S9) [44].

Steiner et al.[31] reported that neither whole-body LBM (kg) nor lower-limb LBM (kg) was a significant correlate of ISWD (metres): r = 0.11, β = 1.4, [95%CI −1.4, 4.1] (p = 0.330); and r = 0.16, β = 0.51, [95%CI 0.3, 0.7] (p = 0.16), respectively. Furthermore, neither measure of LBM was a significant predictor of ISWD in multivariate linear regression analysis (p > 0.05).

Two studies [63, 82] looked at differences in ISWD (metres) between groups categorised by varied thresholds of ASMI (kg/m²), alone[63, 82] or in combination[63] with additional criteria for group allocation (Table S9). When looked at alone, one[82] of two studies[63, 82] reported a significantly shorter ISWD in the group of people with lower compared to higher ASMI. Similar results were found when ASMI was combined with additional thresholds for group separation (Table S9) [63].

Using ultrasound, Nijholt et al.[77] measured rectus femoris CSA (cm²) and rectus femoris thickness (cm) and found that neither were associated with ISWD (metres): r = 0.22 (p = 0.274) and r = 0.21 (p = 0.297), respectively. Maddocks et al.[61] reported that BIA-derived phase angle (degree) was both a significant correlate (r = 0.43, p < 0.001) and predictor of ISWD (metres) in people with COPD (β = 52.87, [95%CI 35.3-70.2], p < 0.001).

Using BIA-derived phase angle <5^th percentile of the normal reference value to dichotomise participants, Maddocks et al.[61] found that people with COPD with a phase angle <5^th percentile of the normal reference value had a significantly shorter ISWD than those with a phase angle >5^th percentile (Table S9).

Endurance shuttle walk test (ESWT)

A single study by Steiner et al.[31] reported no statistically significant bivariate associations between the distance walked during the ESWT (ESWD, metres) and either whole-body LBM (kg) (r=-0.09, β=-1.5 [95%CI −4.9, 1.9], p = 0.394) or lower-limb LBM (kg) (r=-0.05, β=-2.1 [95%CI −11.6, 7.4], p = 0.662). Similarly, neither measure of LBM emerged as a statistically significant determinant of ESWD (metres) in multivariable regression analyses (p > 0.05) [31].

The associations between FFM and the outcomes from the 12MWT and 3MST have been summarised in the supplementary materials (refer specifically to S2.2.vii 12-minute walk test (12MWT) and S2.2.viii Three-minute constant-rate step test (3MST)).

Discussion

This systematic review provides a comprehensive and up-to-date summary for scientists and healthcare professionals on the current research reporting on the association between FFM – a proxy for skeletal muscle mass – and exercise test outcomes in people with COPD, including measures of exercise capacity as well as the physiological and perceptual factors that contribute to exercise (in)tolerance.

In capturing 83 studies with a total of 18,770 participants, this is the largest systematic review to report on the relationship between FFM and a variety of important exercise test outcomes in people with COPD. Based on the results of our review, four main take home messages were identified. First, we concluded that there exists, with a few caveats (discussed below), a positive association between FFM and multiple established measures of peak exercise capacity in COPD, particularly V^’O_2,peak, PPO and 6MWD. This was demonstrated through correlative analyses as well as differences in both absolute and relative measures of exercise capacity between groups of COPD participants with higher versus lower FFM. Second, considerable heterogeneity exists in the strength of the reported associations between FFM and measures of exercise capacity when assessed using different approaches. For example, the reported associations between FFM and both V^’O_2,peak and PPO on symptom-limited INCR cycle CPET (i.e. non-weight bearing exercise) were consistently stronger and less variable than those reported between FFM and 6MWD (i.e. weight bearing exercise). Third, few studies (n = 8, 10%) reported on the association between FFM and cardiac, ventilatory, breathing pattern, operating lung volume and/or perceptual responses at peak exercise. In the few studies that did, there appeared to be no consistent differences in physiological and/or perceptual outcomes at peak exercise between people with COPD with lower versus higher FFM, despite measures of peak exercise capacity (e.g. 6MWD, V^’O_2,peak, PPO) being consistently lower in the former. Finally, just two (2%) studies investigated associations between FFM and the physiological and/or perceptual responses during submaximal exercise: Silveira et al.[58] reported a positive correlation between FFM and V^’O₂ at the anaerobic threshold; and Kanezaki et al.[92] reported that, from rest to the end of the 3MST, people with COPD and a lower FFMI adopted a more rapid and shallow breathing pattern, and reported higher multidimensional breathlessness responses compared to people with COPD and a higher FFMI, despite these groups achieving similar exercise-induced changes in IC and similar absolute levels of ventilation at the end of the 3MST.

Variations in fat-free mass and exercise capacity assessment methods

While the majority of scientific evidence supports the existence of a positive association between FFM and exercise capacity in people with COPD, the methodologies used to assess both FFM and exercise capacity varied considerably across the 83 studies included in this systematic review. As a result of this heterogeneity, we were unable to perform a meta-analysis.

BIA was used most often to quantify FFM in the studies meeting our inclusion criteria (n = 53, 64%). BIA is a safe, non-invasive, inexpensive, easy to administer, and widely available method of assessing FFM that does not require special personnel nor a large amount of space [61]. Moreover, BIA-derived measures of FFM are reliable and positively correlated to other body composition assessment tools; for instance, high levels of agreement between BIA and DEXA-derived measures of FFM have been reported in healthy adults and people with COPD [103,104]. Other assessment methods used were DEXA (n = 15, 18%), CT-scan (n = 8, 10%), MRI (n = 2, 2%), ultrasound (n = 2, 2%), or other techniques, including creatine height index (n = 1, <2%), sarcopenia index (n = 1, <2%), sum of skinfolds (n = 1, <2%), calf-circumference (n = 1, <2%) and deuterium labelled water (n = 1, <2%).

Additionally, and as illustrated in Tables 2 and 3, the specific FFM measurement of interest varied considerably across studies, with some studies reporting estimates of whole-body, height-adjusted, appendicular, CSA, or volumetric measures of FFM (e.g. FFM, FFMI, ASMI, pectoralis muscle CSA, thigh muscle volume). Furthermore, studies varied considerably in the criteria used to characterise their participants with COPD as being FFM depleted or non-depleted. For example, Mostert et al.[26] used FFMI values of ≤16 kg/m² for males and ≤15 kg/m² females, whereas Travassos et al.[69] used FFMI values <17.4 kg/m² for males and <14.65 kg/m² for females.

Considerable heterogeneity was also observed across studies for the exercise-related outcome measures (e.g. 6MWT, INCR or constant-load CPET on a cycle ergometer or treadmill, 12MWT, ISWT, ESWT, 3MST) and the way these outcomes were expressed or reported (e.g. absolute, relative and/or percent predicted normal 6MWD, V^’O_2,peak, PPO, EET). Notwithstanding the observed heterogeneity in methods used to respectively assess and quantify FFM and exercise capacity, a positive association was reported between FFM and exercise capacity in COPD by the majority of studies included in our systematic review.

Whether peak exercise test outcomes were reported in absolute or relative terms is likely responsible, at least in part, for some of the statistically non-significant associations between FFM and measures of peak exercise capacity. For instance, of the four studies that reported no statistically significant differences in V^’O_2,peak between FFMI depleted and non-depleted adults with COPD, two expressed V^’O_2,peak in millilitres of O₂ per kilogram of body mass per minute (ml/kg/min)[41, 52] and another in millilitres of O₂ per kilogram of FFM per minute (ml/kg-FFM/min) [30]. Moreover, Malaguti et al.[45] reported that V^’O_2,peak expressed in ml/min and as percentage of predicted normal V^’O_2,peak but not ml/kg/min was significantly lower in LBMI depleted compared to LBMI non-depleted participants with COPD. It stands to reason that, by indirectly (ml/kg/min) and directly (ml/kg-FFM/min) adjusting V^’O_2,peak for between-group differences in FFM, the authors of these studies would not likely observe a significant difference in V^’O_2,peak between their FFMI depleted and non-depleted participants with COPD. By all accounts, the lack of a statistically significant between-group difference in V^’O_2,peak expressed in ml/kg/min and especially ml/kg-FFM/min reinforces the negative impact that loss of FFM has on peak exercise capacity in people with COPD.

Weight bearing versus non-weight bearing exercise

The positive association between FFM and measures of exercise capacity was most consistent during non-weight bearing exercise tests (e.g. INCR cycle CPET) and most heterogenous during weight bearing exercise tests (e.g. 6MWD, ISWT). We suspect that inconsistencies (or discrepancies) in the results between studies employing non-weight bearing and weight bearing exercise modalities may be due, at least in part, to a potentially confounding influence of BMI (or excess adiposity) on cardiometabolic and ventilatory responses to exercise, especially weight bearing exercise like walking.

In a study of 186,975 adults aged 45-69 years from the general population of the United Kingdom, Franssen et al.[105] reported a strong positive correlation between FFMI and BMI (r = 0.62, p < 0.001). Similar observations were made by Kyle et al.[106] who reported strong positive correlations between BMI and FFMI in 2,647 healthy adult females (r²=0.60, p < 0.001) and 2,982 healthy adult males (r²=0.61, p < 0.001). Thus, as an individual’s body mass (and fat mass) increases, so too does their FFM. That is, people with overweight or obese BMI classification tend to have more FFM than their normal-weight counterparts. This may have direct implications on the results reported in this systematic review, in as much as higher levels of fat mass (adipose tissue) may obscure or confound the relationship between FFM and exercise capacity in COPD when exercise capacity is assessed using a weight-bearing (e.g. 6MWT) as compared to a non-weight bearing exercise test (e.g. cycle CPET). Indeed, studies have found that both overweight (25 ≤ BMI < 30 kg/m²) and obese (BMI ≥ 30 kg/m²) adults with COPD walked significantly shorter distances during the 6MWT than their normal-weight counterparts (18.5 ≤ BMI < 25 kg/m²), despite comparable levels of chronic airflow obstruction [106,107]. In contrast, neither PPO (watts) on INCR cycle CPET[107] nor constant-load cycle EET (seconds)[107] were significantly different between normal-weight, overweight and obese adults with COPD. From an exercise physiological perspective, Ciavaglia et al.[107] found that absolute V^’O₂ (L/min) was consistently higher, while oxyhaemoglobin saturation (SpO₂) was consistently lower in obese adults with COPD (BMI ≥ 30 kg/m²) at respective standardised submaximal power outputs of ≥20 watts and ≥30 watts during symptom-limited INCR treadmill (weight-bearing) versus cycle (non-weight bearing) CPET protocols matched for the rate of increase in external power output (10 watts/2-min). It follows that the combination of a higher metabolic cost of external work and greater SpO₂ desaturation during a weight-bearing exercise test (e.g. 6MWT) may obscure or mask an otherwise positive association between FFM and peak exercise capacity in COPD, especially in the presence of abnormally high levels of adiposity. The corollary of this is that the “true” effect of COPD-related loss of FFM on peak exercise capacity (independent of corresponding changes in fat mass or adiposity) is likely best assessed using a non-weight bearing exercise test (e.g. cycle ergometry). By extension, it could be argued that the impact of therapeutic interventions targeting abnormally low levels of FFM (e.g. resistance exercise training, nutritional supplementation, anabolic hormones) on exercise capacity in COPD are also likely best assessed using a non-weight bearing exercise test where the potentially confounding effect of contemporaneous changes in fat mass is minimised.

Potential misclassification of fat-free mass depletion and non-depletion

The positive relationship between BMI and FFMI may also lead to systematic misclassification of overweight and obese adults with COPD as being FFMI non-depleted since they are more likely to have a FFMI that surpasses the absolute FFMI threshold value used to define FFMI depletion, a threshold that is usually derived from normal-weight and/or slightly overweight populations [105]. In contrast, due to this relationship, underweight (BMI < 18.5 kg/m²) people with COPD are more likely to be classified as FFMI depleted. To minimise this risk of misclassification, Franssen et al.[105] created age-, sex-, and BMI-specific reference values for FFMI depletion in underweight, overweight, and obese adults. They reported FFMI depletion threshold values ranging from ≤18.6-21.3 kg/m² for overweight-obese males and ≤15.4-17.2 kg/m² for overweight-obese females. Moreover, FFMI depletion threshold values for underweight people (BMI < 18.5 kg/m²) ranged from ≤14.0-14.9 kg/m² for males and ≤12.7-13.3 kg/m² for females. These age-, sex-, and BMI-specific FFMI depletion threshold values are quite different than the non-BMI specific FFMI depletion threshold values of ≤16-17 kg/m² for males and ≤14-15 kg/m² for females employed by almost all studies included within this systematic review. This may have resulted in underweight and overweight-obese people with COPD being systematically misclassified as FFMI depleted and non-depleted, respectively. The potential systematic misclassification may be at least partly responsible for the discrepancies or inconsistencies we observed between studies concerning the influence of FFMI depletion on exercise capacity in people with COPD. Thus, we feel that, in moving forward, it is important for COPD researchers and healthcare providers alike to use age-, sex-, and BMI-specific FFMI reference values or to employ statistical models (or experimental study designs) that account for variability in BMI when assessing the effect of changes in FFMI due to COPD and/or therapeutic intervention(s) on exercise capacity in this clinical population. Indeed, Machado et al.[94] compared the prevalence estimates of FFMI depletion in people with COPD when using traditional fixed FFMI cut-offs of 15 kg/m² for females and 17 kg/m² for males compared to Franssen and colleague’s[105] age-, sex-, and BMI-specific FFMI thresholds. The authors reported a significantly higher prevalence of FFMI depletion among overweight and obese participants with COPD when the age-, sex- and BMI-specific cut-off values were used compared to the fixed FFMI cut-off values. However, prevalence rates of FFMI depletion were not different within the normal weight participants regardless of how FFMI depletion was defined [94].

Strengths and limitations

One of the main strengths of our systematic review is that we purposefully employed a broad and general keyword search strategy aimed at capturing any study that assessed FFM in people with COPD. From there, we included all studies that reported on the association between FFM and any one or combination of exercise test outcomes. As a result, this systematic review was able to narratively synthesise the relationship between FFM and multiple established measures of exercise capacity from 83 studies that included a total of almost 19,000 adults with COPD.

Data on skeletal muscle strength and endurance – two determinants of skeletal muscle dysfunction in COPD beyond abnormally low skeletal muscle mass (or FFM)[109,110] – while positively related to FFM [38, 77, 111], were not the focus of this systematic review and thus were not investigated or accounted for in our narrative synthesis of the relationship between FFM and exercise capacity in people with COPD. As such, we cannot comment on the role, whether dependent or independent, that concurrent COPD-related changes in skeletal muscle strength and/or endurance had on the observed (i) associations or lack thereof between FFM and exercise test outcomes and/or (ii) differences or lack thereof in exercise test outcomes between COPD patients with lower compared to higher FFM.

Finally, our systematic review focussed almost exclusively on cross-sectional or correlative studies. Thus, we cannot comment on the efficacy of therapeutic interventions targeting abnormally low levels of FFM in COPD (e.g. rehabilitative exercise training, nutritional supplementation, anabolic hormones) nor the impact of longitudinal changes in FFM on concurrent changes in exercise test outcomes in COPD.

Conclusion and clinical implications

Despite an appreciable amount of heterogeneity in the methods used to assess FFM and quantify exercise capacity across studies in people with COPD, a positive association was reported between these two outcome variables in most of the studies included in this systematic review. We identified a lack of studies investigating the association between FFM and temporal physiological and perceptual responses to exercise. This gap in knowledge needs to be addressed to advance our understanding of the pathophysiological mechanisms underlying the association between loss of FFM and exercise intolerance in COPD.

Considering the prognostic significance of exercise capacity on health-related outcomes (e.g. mortality) in COPD as well as the generally positive association between FFM and exercise capacity reported in this review, skeletal muscle mass should be seen as an important prognostic variable for the health and well-being of people living with COPD. These findings, along with the fact that skeletal muscle is a targetable and treatable bodily organ (or trait) in people with COPD [5], reinforces the need for healthcare providers and researchers alike to develop and implement more effective therapeutic interventions focussed on increasing FFM and improving related health outcomes, specifically exercise capacity. For example, placing a greater emphasis on the importance of resistance exercise training, a component of pulmonary rehabilitation programs [112], may help to increase FFM and improve both the quality and quantity of life lived by people with COPD. This is of particular physiological and clinical importance for those men or women with abnormally low FFMI (especially abnormally low BMI-specific FFMI) and severe exercise intolerance.

Acknowledgements

The authors would like to thank Pardise Elmi and Jade Fraser for their time and contributions to data search and entry. The authors would also like to acknowledge and thank the entire Clinical Exercise and Respiratory Physiology Laboratory (CERPL) for providing support and guidance throughout this process.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

There are no operating funds to report for this paper. KGS was supported by (1) a Graduate Studentship Award from the Research Institute of the McGill University Health Centre; (2) a Graduate Supplement for Masters Students from the Quebec Respiratory Health Network of the Fonds de Recherche du Québec-Santé; and (3) a Canadian Graduate Scholarship-Masters from the Canadian Institutes of Health Research. ARJ was supported by Le Fonds de Recherche du Québec Santé — Postdoctoral Training. HL was supported by (1) Le Fonds de Recherche du Québec Santé — Postdoctoral Training; and (2) Australian Government Department of Education and Training Endeavour Research Fellowship. LFB was supported by the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – Brasil. EK was supported by a Canadian Graduate Scholarship-Masters from the Canadian Institutes of Health. AM was supported by a Graduate Supplement for Masters Students from Quebec Respiratory Health Network of the Fonds de Recherche du Québec-Santé. DR was supported by the Canadian Graduate Scholarship-Masters from the Canadian Institutes of Health. LT was supported by the Canadian Graduate Scholarship-Masters from the Canadian Institutes of Health. DJ holds a Canada Research Chair in Clinical Exercise & Respiratory Physiology (Tier 2) from the Canadian Institutes of Health Research.