| Literature DB >> 33961647 |
Jan W van der Scheer1,2, Julia O Totosy de Zepetnek3, Cheri Blauwet4,5, Katherine Brooke-Wavell2, Terri Graham-Paulson6, Amber N Leonard2, Nick Webborn2,5,7,8, Victoria L Goosey-Tolfrey2.
Abstract
The objective of this scoping review was to map the evidence on measurement properties of body composition tools to assess whole-body and regional fat and fat-free mass in adults with SCI, and to identify research gaps in order to set future research priorities. Electronic databases of PubMed, EMBASE and the Cochrane library were searched up to April 2020. Included studies employed assessments related to whole-body or regional fat and/or fat-free mass and provided data to quantify measurement properties that involved adults with SCI. All searches and data extractions were conducted by two independent reviewers. The scoping review was designed and conducted together with an expert panel (n = 8) that represented research, clinical, nutritional and lived SCI experience. The panel collaboratively determined the scope and design of the review and interpreted its findings. Additionally, the expert panel reached out to their professional networks to gain further stakeholder feedback via interactive practitioner surveys and workshops with people with SCI. The research gaps identified by the review, together with discussions among the expert panel including consideration of the survey and workshop feedback, informed the formulation of future research priorities. A total of 42 eligible articles were identified (1,011 males and 143 females). The only tool supported by studies showing both acceptable test-retest reliability and convergent validity was whole-body dual-energy x-ray absorptiometry (DXA). The survey/workshop participants considered the measurement burden of DXA acceptable as long as it was reliable, valid and would do no harm (e.g. radiation, skin damage). Practitioners considered cost and accessibility of DXA major barriers in applied settings. The survey/workshop participants expressed a preference towards simple tools if they could be confident in their reliability and validity. This review suggests that future research should prioritize reliability and validity studies on: (1) DXA as a surrogate 'gold standard' tool to assess whole-body composition, regional fat and fat-free mass; and (2) skinfold thickness and waist circumference as practical low-cost tools to assess regional fat mass in persons with SCI, and (3) females to explore potential sex differences of body composition assessment tools. Registration review protocol: CRD42018090187 (PROSPERO).Entities:
Year: 2021 PMID: 33961647 PMCID: PMC8104368 DOI: 10.1371/journal.pone.0251142
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
The expert panel (n = 8) that collaboratively determined the scope and design of the review, and interpreted its findings.
| Expert panel member | Role/background |
|---|---|
| Blauwet, MD | Clinician |
| Researcher | |
| Lived SCI experience | |
| Brooke-Wavell, PhD | Researcher |
| Goosey-Tolfrey, PhD | Review team |
| Researcher | |
| Graham-Paulson, PhD | Nutritionist |
| Researcher | |
| Leonard, MSc | Review team |
| Researcher | |
| van der Scheer, PhD | Review team |
| Researcher | |
| Totosy de Zepetnek, PhD | Review team |
| Nutritionist | |
| Researcher | |
| Webborn, MD | Clinician |
| Researcher | |
| Lived SCI experience |
Note: Institutions and affiliations of each expert panel member can be found in the author section.
Fig 1PRISMA flow diagram of the identification of eligible studies.
Fig 2Mapping the available evidence: Total articles summarized by reliability and convergent validity.
Fig 3Number of studies with “acceptable” convergent validity (e.g. reported ICC > 0.70), that were “not acceptable” (e.g. reported ICC < 0.70), or “inconclusive” (e.g. reported statistics incomplete) for each of the most commonly evaluated assessment tools (whole-body and regional studies combined).
Data charting (extraction) of eligible studies in alphabetical order by first author.
| Author/Date | N (M/F) | Participants Characteristics mean±SD (range) | Body Composition Assessment Tools | Statistics (Results) |
|---|---|---|---|---|
| Beck et al., 2014 [ | 13 (7/6) | Age: | • BMI: mass measured on scale; height self-report | • |
| Buchholz et al., 2003 [ | 31 (19/12) | Age: | • BMI: mass measured on scale, length measured supine with adult-sized Plexiglas length board | • |
| Bulbulian et al., 1987 [ | 22 (22/0) | Age: | • Anthropometrics: dominant side for diameters (cm), circumferences (cm), skinfolds (mm, Harpenden calipers) to predict Db | • |
| Cirnigliarro et al. 2013 [ | 30 (29/1) | • BIS: 256 frequencies ranging from 3–1000 kHz to predict ECV & ICV in TB and legs/arms | • | |
| Cirnigliaro et al., 2015 [ | 63 (63/0) | Age: | • BMI: mass and length (electronic calipers) determined from DXA | • |
| Clasey et al., 2005 [ | 20 (14/6) | Age: | • ADP (BodPod): Vb measured [thoracic volume obtained]; Db calculated | • |
| Cragg et al., 2015 [ | 27 (19/8) | Age: | • BMI: mass determined from DXA, length from either self-report or electric ruler on DXA | • |
| Desport et al., 2000 [ | 20 (15/5) | Age: | • BIA: frequencies of 50 & 100kHz to predict TBW | • |
| Edwards et al., 2008 [ | 15 (12/3) | Age: | • WC: 3 sites supine: 1) immediately below lowest rib; 2) immediately above iliac crest; 3) midpoint btw lowest rib and iliac crest, all at end expiration | • |
| Emmons et al., 2011 [ | 24 (24/0) | Age: | • Ultrasound (GE): supine using 2–5 MHz curvilinear transducer to measure SAT & VAT | • |
| George et al. 1988 [ | 15 (10/5) | Age: | • TBW (ethanol dilution): 0.35g/kg body mass; breath analysis pre and post; to predict FFM | • |
| Goosey-Tolfrey et al., 2016 [ | 30 (30/0) | Age: | • Skinfolds: biceps, triceps, subscapular, iliac crest, supraspinale, abdominal, front thigh, medial calf (Harpenden calipders & several prediction equations) to predict Db & TB fat% | • |
| Gorgey et al. 2011 [ | 13 (13/0) | Age: | • WC: seated at level of narrowest part of torso at end expiration using inelastic tape | • |
| Gorgey et al. 2012 [ | 63 (63/0) | Age: | • Body mass: measured on wheelchair scale | • |
| Gorgey et al. 2018 [ | Short Term: | • DXA (GE Lunar Prodigy Advance): TB fat (kg, %), FFM, LM; regional (trunk, legs, arms, android, gynoid) fat (kg, %), FFM, LM; measured 2x by 1 technician | • | |
| Inayama et al. 2014 [ | 74 (74/0) | Age | • BMI: mass measured on wheelchair scale; length measured supine using inelastic tape measure | • |
| Jones et al. 2003 [ | 19 (19/0) | Age: | • BMI: mass determined from from DXA; height self-reported | • |
| Layec et al. 2014 [ | 8 (6/2) | Age: | • Anthropometrics: thigh and lower leg volume via circumferences, length, and skinfold thickness | • |
| Lester et al. 2019 [ | 32 (31/1) | Age: 37 | • DXA (Lunar iDXA): thigh LM | • |
| Maggioni et al. 2003 [ | 13 (13/0) | Age: | • Skinfolds: biceps, triceps, suprailiac and subscapular (Holtain calipers and Durnin-Womersley equation) to predict Db & TB fat% | • |
| McCauley et al. 2018 [ | 22 (22/0) | Age: | • Anthropometrics: WC (level of umbilicus in supine position at end expiration with an inflexible measuring tape) and skinfolds (abdominal & suprailiac using (Harpenden calipers) | • |
| McCauley et al. 2020 [ | 27 (27/0) | Age: | • DXA (GE Lunar iDXA): android regions for VATmass (encore software) | • |
| Mesbah et al., 2019 [52[ | 16 (13/3) | Age: | • MRI: 3T (Siemens): 50 images of thigh [between greater trochanter and lateral epicondyle of femur] analyzed for SAT, IMAT, and lean tissue; images obtained and analyzed via novel fully automated and manual volumetric segmentation | • |
| Modlesky et al. 2004 [ | 8 (8/0) | Age: | • DXA (Hologic, Delphi A): leg FFM | • |
| Mojtahedi et al. 2009 [ | 16 (8/8) | • Skinfolds: triceps, subscapular, biceps, chest, midaxillary, paraumbilical, suprailiac, thigh and lateral calf (Harpenden calipers and Jackson & Pollock protocol) to predict Db & TB fat% | • | |
| Olle et al. 1993 [ | 17 (17/0) | Age: | • TOBEC: supine using 2.5MHz electromagnetic field to estimate FFM; measured 2x by 1 technician | • |
| Panisset et al. 2018 [ | 20 (18/2) | Age: | • BIA (model SFB7, ImpdiMed Ltd): 256 frequencies ranging from 3–1000 kHz (7 prediction equations) to predict TBW & TB FFM | • |
| Pelletier et al. 2016 [ | 136 (100/36) | Age: | • BMI: mass measured on wheelchair scale; height self-reported | • |
| Rankin et al. 2018 [ | 22 (22/0) | Age: | • DXA (Lunar Prodigy): trunk fat (kg, %) & LM | • |
| Ravensbergen et al. 2014 [ | 27 (19/8) | Age: | • BMI: mass determined from DXA, length determined with electronic ruler from DXA | • |
| Singh et al. 2014 [ | 95 (71/24) | Age: | • BMI: methods NR | • |
| Smith et al. 2016 [ | 5 (5/0) | Age: | • MRI: 3D dual-echo fat-water technique (2-pt Dixon method) to quantify lower leg fat infiltration (gastrocnemius, soleus, tibialis anterior, fibularis longus); measured 1x by 6 technicians | • |
| Spungen et al. 1995 [ | 12 (12/0) | Age: | • BIA (RJL Systems, Model 101A): predict TB FM & FFM | • |
| Spungen et al. 2000 [ | 8 (8/0) | Age: | • BMI: mass measured on scale, length measured supine | • |
| Sumrell et al. 2018 [ | 22 (22/0) | Age: | • Anthropometrics (seated & supine): WC (midpoint between crest of ilium and interior margin of last rib) and abdominal circumference (level of umbilicus) at end expiration | • |
| Swaine et al. 2018 [ | 16 (8/0) | Age: | • Ultrasound (Philips, B-Mode) to measure 5 soft tissue layers (total, skin, fat, tendon, muscle) between the lowest point of the ischial tuberosity and overlying skin in loaded & unloaded sitting position; measured 3x by 2 sonographers | • |
| Wade and Gorgey 2017 [ | 22 (22/0) | Age: | • Anthropometrics: thigh circumference and thigh skinfold thickness to determine thigh CSA | • |
| Wade et al. 2018 [ | 22 (22/0) | Age: | • Cross validate SCI-specific thigh CSA equation developed in Wade and Gorgey 2017 above | • |
| Wielopolski et al. 2009 [ | 21 (NR) | Age: | • PBK: legs body potassium measurement to determine body cell mass and ICW; calculate legs LM | • |
| Willems et al. 2015 [ | 14 (14/0) | Age: | • BMI: mass measured on scale, length measured supine | • |
| Wong et al., 2015 [ | 17 (12/5) | Age: | • pQCT (Stratec XCT2000): single image at 66% site of tibia; 2 images obtained and analyzed via watershed (MD & MSCA), threshold-based (MD & MSCA) | • |
| Yun et al. 2019 [ | 52 (52/0) | Age: | • BMI: mass measured on digital wheelchair scale; length measured supine | • |
Acronyms (in alphabetical order): ADP = air displacement plethysmography; AIS = American Spinal Injury Association Impairment Scale; BIA = bioelectrical impedance; BIS = bioelectrical spectroscopy; BMI = body mass index; CSA = cross sectional area; CT = computed tomography; D2O = deuterium oxide; Db = body density; DXA = dual-energy x-ray absorptiometry; ECV = extracellular volume; ECW = extracellular water; FFM = fat free mass (kg); FM = fat mass (kg); HW = hydrostatic weighing; ICV = intracellular volume; ICW = intracellular water; LM = lean mass (kg); MRI = magnetic resonance imaging; NLI = neurological level of injury; NR = not reported; O2 = oxygen; PBK = partial body potassium; SAT = subcutaneous adipose tissue; TB = total body; TOBEC = total body electrical conductivity; TBK = total body potassium; TBW = total body water; TSI = time since injury; US = ultrasound; Vb = body volume; VATmass = visceral adipose tissue mass (kg); VATvol = visceral adipose tissue transformed to volume using a constant correction factor (density of adipose tissue = 0.94 g/cm3); WC = waist circumference.
Future priorities and considerations for research on measurement properties of body composition in the SCI population.
| 1 | Establish standardized SCI-specific protocols for assessing body composition via DXA, waist circumference, and skinfold thickness, regarding pre-assessment conditions (e.g., bladder voiding, time of day, exercise and nutrition intake) and recognizing the physical barriers persons with SCI experience (e.g., contractures, spasticity, hardware in the body, urine reservoirs, obesity). These protocols will help reduce measurement error and improve reliability and validity outcomes. |
| 2 | Establish reliability over time and across assessors and commercial manufacturers for DXA, waist circumference and skinfold thickness measures. Given that reliability decreases when DXA is performed with special populations (i.e., obese, osteoporotic) [ |
| 3 | Establish criterion validity of DXA for whole-body composition and regional body composition measures of fat and fat-free mass, using a four-compartment model as the reference method. DXA currently holds the most promise as a reliable and valid imaging technique relatively commonly available in research and clinical settings, but further SCI-specific evidence is needed to endorse it as the surrogate gold standard. |
| 4 | Establish responsiveness of waist circumference and skinfold thickness measures as practical, low-cost tools, using a longitudinal design with a comparison to a convergent measure (e.g., DXA site-specific measures) on at least two time points. Along with the reliability studies, this is a prerequisite for obtaining confidence that a change in these measures can be attributed to an intervention and not measurement error. |
| 5 | Assess potential sex differences by including females in reliability and validity study designs, and consider the influence of various injury characteristics (e.g., injury level and completeness). |