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  • ISSN: 2333-6706
    J Hum Nutr Food Sci 1(3): 1017.
    Submitted: 10 October 2013; Accepted: 14 December 2013; Published: 16 December 2013
    Research Article
    Relative Validity of Upper Arm Anthropometry as a Field Method for Estimating Skeletal Muscle Mass in Adults with Peripheral Arterial Disease
    Jolene Thomas1, Christopher Delaney2, James Ian Spark2 and Michelle Miller1*
    1Department of Nutrition and Dietetics, Flinders University, Australia
    2Department of Vascular Surgery, Flinders University, Australia
    *Corresponding author: Michelle Miller, Department of Nutrition and Dietetics, Flinders University, Bedford Park SA 5042, GPO BOX 2100 Adelaide SA 5001, Australia, Tel: 618-820-45328; Fax: 618-820-46406; Email: michelle.miller@flinders.edu.au
    Abstract
    Maintenance of skeletal muscle mass (SMM) is integral to better health outcomes for adults with peripheral arterial disease (PAD). For those with intermittent claudication (IC), muscle mass has a role in maximising pain free walking distance, in critical limb ischemia (CLI) there is risk of muscle atrophy secondary to disuse and increased protein requirements. The purpose of this study was to determine whether upper arm anthropometry would be an acceptable field method for estimating SMM in adults with PAD. Adults with IC (n=27) or CLI (n=25) were recruited from the Southern Adelaide Health Service. SMM was derived from dual energy x-ray absorptiometry (DEXA), the reference technique, according to an established equation. SMM was derived from corrected arm muscle area (CAMA), the field technique, according to an established equation. Correlation, t-tests and Bland-Altman analysis were performed to determine level of agreement between techniques. Mean (SD) age was 69.9 (11.8) years, n=36/52 male and body mass index was 28.5 (6.3) kg/m2. SMM from DEXA and CAMA were highly correlated (r=0.9, P<0.001) but significantly different, mean (SD) SMM from DEXA and CAMA were 23.7 (6.3) kg and 20.3 (5.7) kg respectively, P<0.001. Mean bias and limits of agreement for SMM between DEXA and CAMA were 3.5 (-3.1, 10.1) kg. Clinicians should be cautious in using CAMA to estimate SMM as the difference is clinically meaningful. Further work is required to determine whether a predictive equation using CAMA alongside other field measures of SMM can achieve a better level of agreement with DEXA.
    Keywords: Skeletal muscle mass; Peripheral arterial disease; Body composition; Nutrition assessment
    Introduction
    Body composition, specifically fat and skeletal muscle mass (SMM), has been demonstrated to be predictive of health outcomes across the lifecycle. High levels of fat mass have consistently been demonstrated to increase risk of vascular disease in children [1] and adults [2]. Low SMM, particularly in advanced age, has consistently been demonstrated to increase risk of falls, fragility fracture, infection and poor wound healing [3-6]. Assessment of body composition is therefore an important component of nutritional assessment, particularly in patient groups where alterations in body composition occur and poor nutritional health can be masked by higher total body weight as is the case with sarcopenic obesity.
    It has been proposed that adults with peripheral arterial disease (PAD) have alterations in body composition, with higher fat mass common in early stages of disease progression [2] and a decline in SMM or atrophy of skeletal muscle as the disease progresses [7]. Although evidence to support this assertion is scant, it is likely that muscle atrophy in these patients occurs as a result of disuse precipitated by ischaemic pain in claudication and increased protein and energy requirements associated with ischaemic ulcers and vascular intervention [8,9]. Significantly, such a decline in SMM is probably greater than the expected age related decline in SMM. Accurate and feasible methods for measurement of SMM in this patient group are therefore justified and required as this facilitates a more comprehensive nutritional assessment of this nutritionally vulnerable group of patients with the potential to improve both short and long term health outcomes.
    Assessing SMM accurately in the clinical setting is challenging in the absence of an acceptable field method for measuring or estimating SMM in adults with PAD. Dual-energy X-ray Absorptiometry (DEXA) is globally accepted as an acceptable method for measuring fat and fat free mass however use in everyday clinical practice is limited. Lack of availability and cost of equipment, lack of portability and the inability of some patients to assume the correct position for measurement all limit the feasibility of DEXA [10]. There is hence a need for a more practical method of assessing body composition, particularly SMM, which is valid and able to be used in the clinical setting as part of nutritional assessment.
    Corrected arm muscle area (CAMA) is an anthropometric index derived from non-invasive measures of the mid-upper arm circumference (MUAC) and the triceps skin fold (TSF) using established equations [11]. Corrected arm muscle area has been shown to be independently predictive of poor health outcomes in older adults and various patient groups including vascular and rehabilitation [12-15]. In these studies, CAMA has been shown to be a better indicator than BMI. CAMA can be converted to total SMM using an additional set of predictive equations [12]. These measures are considered more feasible in the clinical setting compared to the alternative of bioelectrical impedance given the cost of the equipment and consumables, the requirement for stable hydration, fasting and positioning of the electrodes at the wrist and ankle [16,17].
    The aim of the current study is to compare SMM derived from CAMA with SMM derived from DEXA in a heterogeneous group of vascular patients to determine if it is a valid field technique for assessing SMM in this patient group.
    Materials and Methods
    Adults aged ≥ 18 years with intermittent claudication (n=27) or critical limb ischemia (n=25) were recruited from the Southern Adelaide Health Service Department of Vascular Surgery Claudication Clinic or from the inpatient service at Flinders Medical Centre respectively between July 2011 and May 2012. Data collected from two vascular surgery studies conveniently formed the basis for the analyses presented in this study. These data were collected according to the guidelines laid down in the Declaration of Helsinki and all procedures involving human subjects were approved by the Southern Adelaide Human Research and Ethics Committee. Written informed consent was obtained from all subjects.
    Participants with intermittent claudication were concurrently enrolled in a randomised controlled trial to evaluate the effects of two structured 12 week supervised exercise programs: treadmill alone or treadmill combined with resistance training. All participants had clinical and radiological evidence of infra-inguinal PAD manifesting as intermittent claudication and no underlying co-morbidities that would prohibit their participation in an exercise program. For the purpose of the current study, only the baseline measurements of body composition were used in the analyses. Participants with critical limb ischemia were concurrently enrolled in a study evaluating the impact of endovascular intervention on resting energy expenditure. All participants were diagnosed with critical limb ischemia based on the presence of arterial lower limb ulceration or ischaemic rest pain. For the purpose of the current study, only the pre-endovascular intervention measurements of body composition were used in the analyses. Standing height for all participants with intermittent claudication or critical limb ischemia was measured using a stadiometer to the nearest 0.1cm. Participants were then weighed to the nearest 0.1kg using the Lunar Prodigy Pro dual-energy x-ray absorptiometer (DEXA). Fat mass and lean mass were determined using the DEXA in conjunction with Encore software version 7.5. Lean mass from DEXA was subsequently converted to SMM (kg) according to the equation of Kim et al. [18]. Mid upper arm circumference (MUAC) was measured to the nearest 0.1cm using a flexible steel tape and triceps skinfold thickness (TSF) was measured to the nearest 0.2mm using a Harpenden skinfold caliper according to standard procedure [19]. Mid upper arm circumference and TSF measurements were performed in triplicate with the average of the measures used to calculate corrected arm muscle area (CAMA). Corrected Arm Muscle Area was converted to total skeletal muscle mass (SMM) (kg) according to the equation of Heymsfield et al [11].
    Data were analysed using SPSS version 19 (SPSS Inc, Chicago, IL, USA). Unless otherwise stated, mean ± standard deviation (SD) is presented. All tests were two-tailed and the level of statistical significance was set at α=0.05. Pearson’s correlation coefficients were calculated to examine the association between SMM estimated from DEXA and SMM estimated from CAMA. Group means for SMM estimated from DEXA and SMM estimated from CAMA were compared by paired samples t-tests for those with intermittent claudication or critical limb ischaemia separately and combined. To assess agreement between both methods of estimating SMM mean bias and 95% limits of agreement (LOA) were calculated and illustrated consistent with recommendations of Bland and Altman [20].
    Results
    Table 1 presents the descriptive characteristics of the 52 participants, 27 with intermittent claudication and 25 with critical limb ischemia and mean (SD) age of 69.9 (11.8) years. The mean age of those with intermittent claudication (69.0, SD 11.0) was not significantly difference from those with critical limb ischaemia (70.8, SD 12.6), P=0.593. There were statistically significant differences between males and females for mean weight and height with men being significantly heavier (P=0.002) and taller (P≤0.001). Similarly, SMM for males was statistically significantly greater than females when estimated by both DEXA (P=0.005) and CAMA (P≤0.001). Mean (SD) SMM estimated from DEXA was 24.2 (6.3) kg for participants with intermittent claudication versus 23.1 (6.4) kg for participants with critical limb ischemia, P=0.534. Mean (SD) SMM estimated from CAMA was 20.7 (5.7) kg for participants with intermittent claudication versus 19.8 (5.7) kg for participants with critical limb ischemia, P=0.585. Independently, those with intermittent claudication (SMM estimated from CAMA: mean 20.7 SD 5.7 kg versus SMM estimated from DEXA: mean 24.2 SD 6.3 kg, P≤0.001) and those with critical limb ischaemia (SMM estimated from CAMA: mean 19.8 SD 5.7 kg versus SMM estimated from DEXA: mean 23.1 SD 6.4 kg, P≤0.001) were significantly different for SMM when measured by both methods.
    Table 1 Descriptive characteristics of the 52 participants.

    Characteristic

    Males

    Females

    Total

    P value

    Mean (SD) Age, years

    68.6 (10.8)

    72.7 (13.6)

    69.9 (11.8)

    0.255

    Rutherford’s Classification

         1-3: Intermittent claudication

         4-6: Critical limb ischemia

     

    18

    18

     

    9

    7

     

    27

    25

     

     

    0.677

    Mean (SD) Weight, kg

    86.2 (18.7)

    67.4 (19.3)

    80.4 (20.6)

    0.002

    Mean (SD) Height, cm

    173.0 (6.3)

    156.9 (4.3)

    168.2 (9.4)

    ˂0.001

    Mean (SD) BMI, kg/m2

    28.8 (6.0)

    27.6 (7.3)

    28.5 (6.3)

    0.522

    Mean (SD) SMMDEXA, kg

    27.7 (4.8)

    16.9 (3.3)

    23.7 (6.3)

    0.005

    Mean (SD) SMMCAMA, kg

    22.3 (5.1)

    15.4 (3.8)

    20.3 (6.0)

    ˂0.001

    Table 1 Descriptive characteristics of the 52 participants.

    ×
    Combining all participants (intermittent claudication and critical limb ischemia), a strong correlation was evident between SMM estimated from DEXA and SMM estimated from CAMA (r=0.854 and P≤0.001), however according to a paired-samples t-test there was a statistically significant difference between mean (SD) SMM estimated from DEXA and SMM estimated from CAMA, 23.8 (6.7) kg versus 20.3 (5.7), P≤0.001. (Figure 1) illustrates mean bias and LOA for SMM estimated from DEXA and SMM estimated from CAMA. Mean bias was 3.5 (3.3) kg and LOA -3.1, 10.1 kg.
    Figure 2 Implantation tools. A) Sheath B) Plastic dilator C) Ejector tool D) Stimulation probe E) Anodal lead F) Cathodal lead.

    Figure 2 Implantation tools. A) Sheath B) Plastic dilator C) Ejector tool D) Stimulation probe E) Anodal lead F) Cathodal lead.

    ×
    Discussion
    This is the first study to investigate the validity of a field method for estimating skeletal muscle mass in patients with PAD. A strong correlation was observed between SMM derived from DEXA and CAMA, however there was a statistically significant and clinically meaningful difference between the mean SMM derived from CAMA compared to DEXA.
    The magnitude of the bias between the mean SMM derived from CAMA compared to DEXA was 3.5 (3.3) kg, so at the individual level, there is the potential to underestimate SMM by 6.6kg. In the current study the mean SMM was 24.2 (6.3) kg for participants with intermittent claudication and 23.1 (6.4) kg for participants with critical limb ischemia. An error of up to 6.6kg in SMM would result in a 30% under or over-estimate in SMM at an individual level which could lead to significant investment of resources for maintenance or gain of SMM that may not be warranted.
    While it is not surprising that the magnitude of the limits of agreement would be too wide to warrant application at an individual level, many similar studies in other patient groups do suggest that there is still potential for the use of the field method at a group level or for the purpose of research. The findings of the present study however would not concur with these recommendations as the mean bias equated to the potential for underestimating SMM by 3.5kg. Underestimation can lead to over identification of muscle depletion leading to overutilization of health resources and potentially excessive nutrition support.
    Given the evidence to suggest that there is a difference in body composition with the progression of PAD, with a reduction in SMM as the disease progresses [21] it might be possible that the use of CAMA performs differently according to the stage of disease. In the present study however, no statistically significant difference was found when comparing the SMM of the claudicants and the CLI participants despite a trend for claudicants having a higher SMM according to both DEXA and CAMA compared to those participants with CLI.
    The inability to reach statistical significance in SMM according to stage of disease in the present study may be due to the modest sample size. While the sample size is not dissimilar to comparable studies [16] it is possible that with a larger study sample a lower SMM would be observed with increasing severity of PAD. An increase in sample size would also likely lead to a narrowing of the limits of agreement between SMM estimated by CAMA and DEXA, although it is not possible to comment on whether the magnitude of this change would be sufficient to support the use of CAMA as a field method in this population. Whether the magnitude of the difference between the two methods is meaningful in terms of the impact on clinical practice is challenging to define given the lack of established cut-offs for desirable SMM in this patient group. Ideally the level of misclassification of patients according to established cut-offs with demonstrated high levels of sensitivity and specificity and predictive value would guide interpretation. These values however are currently unavailable.
    Conclusions
    It must be acknowledged that given the limitation of sample size for this study that these findings are preliminary and further work in this area is warranted to confirm these findings. Further work would also be valuable to include other stages of PAD including minor and major tissue loss, where nutritional status may be further compromised in comparison to claudicants and CLI patients. This is the first study however to test the validity of a field method for estimating SMM in the PAD patient group and provides important data to inform clinicians of the limitations of using SMM from CAMA as an estimate of SMM. It is possible that with further work CAMA might be able to be used as part of an algorithm to predict SMM with greater accuracy but for now it would be prudent for clinicians to be cautious of this field technique. Ultimately, given the health benefits associated with preservation of SMM, the addition of such methods to the armamentarium of dieticians would enable more comprehensive nutritional assessment of these vulnerable patients with the potential to improve health outcomes. Further research could also be undertaken using alternative field methods such as bioimpedance methods however the cost of equipment and consumables for these techniques would need to be considered. Furthermore there may be an issue with validity given the sensitivity of these devices to hydration status.
    Acknowledgements
    The authors of this manuscript declare that they have no conflicts of interest. The research received no specific grant or funding from any agency in the public, commercial or not-for-profit sectors.
    J Thomas was involved in data analysis and the writing of this manuscript
    C Delaney was involved in the design and implementation of the project and the writing of this manuscript
    JI Spark was involved in the project design and writing of this manuscript
    M Miller was involved in the design and implementation of the project, data analysis and the writing of this manuscript.
    References
    1. Montero D, Walther G, Perez-Martin A, Roche E, Vinet A. Endothelial dysfunction, inflammation, and oxidative stress in obese children and adolescents: markers and effect of lifestyle intervention. Obes Rev. 2011; 13: 441-55.
    2. Barton M, Baretella O, Meyer MR. Obesity and risk of vascular disease: importance of endothelium-dependent vasoconstriction. Br J Pharmacol. 2012; 165: 591-602.
    3. Miller MD, Giles, LC, Crotty M, Harrison JE, Andrews G. A clinically relevant criterion for grip strength: relationship with falling in a sample of older adults. Nutrition and Dietetics. 2003; 60: 248-52.
    4. Miller MD, Thomas JM, Cameron ID, Chen JS, Sambrook PN, March LM, et al. BMI: a simple, rapid and clinically meaningful index of under-nutrition in the oldest old? Br J Nutr. 2009; 101: 1300-1305.
    5. Cosquéric G, Sebag A, Ducolombier C, Thomas C, Piette F, Weill-Engerer S. Sarcopenia is predictive of nosocomial infection in care of the elderly. Br J Nutr. 2006; 96: 895-901.
    6. Chernoff R. Protein and older adults. J Am Coll Nutr. 2004; 23: 627S-630S.
    7. Regensteiner JG, Wolfel EE, Brass EP, Carry MR, Ringel SP, Hargarten ME, et al. Chronic changes in skeletal muscle histology and function in peripheral arterial disease. Circulation. 1993; 87: 413-421.
    8. Evans WJ, Campbell WW. Sarcopenia and age-related changes in body composition and functional capacity. J Nutr. 1993; 123: 465-468.
    9. Ayello EA, Thomas DR, Litchford MA. Nutritional aspects of wound healing. Home Healthc Nurse. 1999; 17: 719-729.
    10. Cruz-Jentoft AJ, Baeyens JP, Bauer JM, Boirie Y, Cederholm T, Landi F, et al. Sarcopenia: European consensus on definition and diagnosis: Report of the European Working Group on Sarcopenia in Older People. Age Ageing. 2010; 39: 412-423.
    11. Heymsfield SB, McManus C, Stevens V, Smith J. Muscle mass: reliable indicator of protein-energy malnutrition severity and outcome. Am J Clin Nutr. 1982; 35: 1192-1199.
    12. Miller MD, Crotty M, Giles LC, Bannerman E, Whitehead C, Cobiac L, et al. Corrected arm muscle area: an independent predictor of long-term mortality in community-dwelling older adults? J Am Geriatr Soc. 2002; 50: 1272-1277.
    13. Miller M, Wong WK, Wu J, Cavenett S, Daniels L, Crotty M. Upper-arm anthropometry: an alternative indicator of nutritional health to body mass index in unilateral lower-extremity amputees? Arch Phys Med Rehabil. 2008; 89: 2031-2033.
    14. Neumann SA, Miller MD, Daniels L, Crotty M. Nutritional status and clinical outcomes of older patients in rehabilitation. J Hum Nutr Diet. 2005; 18: 129-136.
    15. Isenring EA, Banks M, Ferguson M, Bauer JD. Beyond malnutrition screening: appropriate methods to guide nutrition care for aged care residents. J Acad Nutr Diet. 2012; 112: 376-381.
    16. Yaxley A, Miller M, Masters S, Ahern M, Crotty M. Body composition in older orthopaedic rehabilitation inpatients: are field methods valid? J Nutr Diet. 2010; 67: 160-65.
    17. Lukaski HC. Requirements for clinical use of bioelectrical impedance analysis (BIA). Ann N Y Acad Sci. 1999; 873: 72-76.
    18. Kim J, Wang Z, Heymsfield SB, Baumgartner RN, Gallagher D. Total-body skeletal muscle mass: estimation by a new dual-energy X-ray absorptiometry method. Am J Clin Nutr. 2002; 76: 378-383.
    19. Norton K, Olds T (editors) Anthropometrica. Sydney: University of New South Wales Press. 1996.
    20. Bland JM, Altman DG. Statistical methods for assessing agreement between two methods of clinical measurement. Lancet. 1986; 1: 307–10.
    21. McDermott MM, Criqui MH, Greenland P, Guralnik JM, Liu K, Pearce WH, et al. Leg strength in peripheral arterial disease: associations with disease severity and lower-extremity performance. J Vasc Surg. 2004; 39: 523-530.
    Cite this article: Thomas J, Delaney C, Spark JI, Miller M (2013) Relative Validity of Upper Arm Anthropometry as a Field Method for Estimating Skeletal Muscle Mass in Adults with Peripheral Arterial Disease. J Hum Nutr Food Sci 1(3): 1017.
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