Gender Dimorphism in Central Adiposity May Explain Metabolic Dysfunction After Spinal Cord Injury

Accepted Manuscript Gender Dimorphism in Central Adiposity may Explain Metabolic Dysfunction after Spinal Cord injury Ashraf S. Gorgey, Gary J. Farkas, David R. Dolbow, Refka E. Khalil, David R. Gater PII:

S1934-1482(17)30320-9

DOI:

10.1016/j.pmrj.2017.08.436

Reference:

PMRJ 1971

To appear in:

PM&R

Received Date: 16 March 2017 Revised Date:

20 June 2017

Accepted Date: 3 August 2017

Please cite this article as: Gorgey AS, Farkas GJ, Dolbow DR, Khalil RE, Gater DR, Gender Dimorphism in Central Adiposity may Explain Metabolic Dysfunction after Spinal Cord injury, PM&R (2017), doi: 10.1016/j.pmrj.2017.08.436. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

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Gender Dimorphism in Central Adiposity may Explain Metabolic Dysfunction after Spinal Cord injury

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Ashraf S. Gorgey1,2 ; Gary J. Farkas3; David R. Dolbow4; Refka E. Khalil1; David R. Gater3,5 1) Spinal Cord Injury and Disorders Service, Hunter Holmes McGuire VAMC, 1201 Broad Rock Boulevard, Richmond, VA 23249, USA

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2) Virginia Commonwealth University, Department of Physical Medicine & Rehabilitation, Richmond, VA 3) Department of Physical Medicine and Rehabilitation, Penn State College of Medicine, 500 University Drive, Hershey, Pennsylvania, 17033 4) School of Kinesiology, University of Southern Mississippi, 118 College Drive; Hattiesburg, Mississippi, 39406 5) Department of Public Health Sciences, Penn State College of Medicine; 500 University Drive, Hershey, Pennsylvania, 17033

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Running Title: Gender differences and Central Adiposity after SCI

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Acknowledgements Supported by VHA RR&D number B6232I and award number UL1RR031990 from the National Center for Research Resources.

Correspondence

Ashraf S. Gorgey, MPT, PhD, FACSM Department of Veterans Affairs Hunter Holmes McGuire Medical Center Spinal Cord Injury & Disorders Service 1201 Broad Rock Boulevard Richmond, VA 23249 Email: [email protected] Tel: + 1- (804)-675-5000 ext. 3386 Fax: + 1- 804-675-5223

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Gender Dimorphism in Central Adiposity may Explain Metabolic Dysfunction after

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Spinal Cord injury

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Abstract

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Background: Increase in visceral adipose tissue (VAT) is an independent risk for mortality and

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other health related comorbidities.

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Objective: To examine the gender differences in VAT and subcutaneous adipose tissue (SAT)

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cross-sectional areas (CSA) between men and women with chronic spinal cord injury (SCI). The

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differences in the distribution of central adiposity were used to determine the association of VAT

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and SAT to metabolic dysfunction after SCI.

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Design: cross-sectional design

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Setting: hospital based study

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Participants: Sixteen individuals [8 men and 8 women] with motor complete SCI were matched

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based on age, time since injury and level of injury.

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Methods: Anthropometrics, dual energy x-ray absorptiometry (DXA) and magnetic resonance

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imaging were captured to measure lean mass, fat mass (FM), percentage FM, VAT and SAT

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CSAs. Basal metabolic rate, intravenous glucose tolerance test and lipid panel were measured.

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Main Outcome Measurements: VAT, SAT and Metabolic Profile

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Results: SAT CSA was 1.6 -1.75 times greater in upper and lower trunks in women compared to

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men with SCI (P<.05). VAT CSA was 1.8-2.6 times greater in upper and lower trunks in men

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compared to women with SCI (P<.05). VAT adjusted to body weight was greater in men

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compared to women with SCI. HDL- C was positively related to SAT and negatively related to

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VAT. Glucose effectiveness was negatively related to lower trunk SAT (r=-0.60, P=.02).

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Cholesterol: HDL-C ratio and TG were positively related to upper VAT, lower VAT and VAT:

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SAT ratio.

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Conclusion: MRI demonstrated that there is a gender dimorphism in central adiposity in persons

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with chronic SCI. This gender dimorphism in central adipose tissue distribution may explain the

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higher prevalence of metabolic dysfunction in men with SCI, especially, the decrease in the

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HDL-C profile.

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Keywords: spinal cord injury, visceral adiposity, subcutaneous adiposity, body composition,

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metabolic profile

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Introduction Visceral adipose tissue (VAT) has been shown to have deleterious effects on metabolic and cardiovascular profiles in persons with spinal cord injury (SCI) and in the general

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population. [1- 4]. Cardio-metabolic disease is among the leading causes of death after SCI [5, 6,

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7]. Individuals with SCI have 48% greater VAT and greater VAT to subcutaneous adipose tissue

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(SAT) ratio than waist circumference matched able-bodied controls [2]. Strong correlations were

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noted among VAT and parameters of carbohydrate and lipid profiles including indices of insulin

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resistance and high density lipoprotein cholesterol (HDL-C) [2]. Maruyama et al. showed that an

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increase in VAT is related to increased leptin, plasminogen activator inhibitor-1, and insulin

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resistance index [8]. Significant associations have been observed with increasing VAT, SAT,

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VAT: SAT ratio, and impaired fasting plasma glucose and abnormal lipid profile [3].

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Unfortunately, the aforementioned studies reported relationships without establishing a clear

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model to distinguish the role of VAT on the metabolic profile, separate from changes in body

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composition following SCI [9].

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Persons with tetraplegia have 24% greater glucose area under the curve compared to those with paraplegia in response to oral glucose tolerance challenge, despite the lack of

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statistical significance in VAT cross-sectional area between the two groups [10]. Contrary to

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these findings, Inskip et al. noted that one month after injury VAT increased in rats with SCI at

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T3 but not at T10 [11]. The increase in VAT was associated with an increase in cardio-metabolic

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risk factors as manifested by altered lipid profile [3]. Another study noted that VAT and SAT

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represents only ~6% and 10%, respectively, of the total body FM in persons with motor

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complete SCI [10], which is lower than what has been reported in able-bodied controls [12]. The

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deleterious effects of VAT on metabolic profile following SCI is diluted by the changes in whole

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body and leg FM distribution [3, 13]. In a diabetes prevention study program, VAT was a strong

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predictor for the development of type II diabetes mellitus and none of the other body fat

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measurements or SAT predicted diabetes [14]. Therefore, the question of the real contribution of

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VAT to metabolic dysfunction after SCI has yet to be answered.

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Magnetic resonance imaging (MRI) and computerized tomography (CT) were successful in separating VAT and SAT in the general population and persons with SCI [2, 3, 13, 15, 16].

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There are still equivocal findings concerning the use of anthropometrics to predict VAT in

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persons with SCI [2, 3, 17, 18]. Compared to MRI and CT, dual energy x-ray absorptiometry

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(DXA) identifies the pivotal roles of both trunk and leg FM in the metabolic profile [9, 19, 20,

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21]; however, DXA is limited to an extent in its ability to separate between trunk SAT or VAT

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and relies on software package in prediction of VAT. CT scans are limited in the ability to

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capture multi-axial slices because of the high risk of ionization [2, 3, 18], which challenges the

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accurate quantification of VAT across the whole trunk region and becomes highly important

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when quantifying VAT or SAT differences between men and women with SCI [12, 22]. Men

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have an android (apple) shaped central adiposity, whereas 60% of women have a gynoid (pear)

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shaped central adiposity [12, 22], suggesting that the distribution of VAT and SAT may be

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different among men and women with SCI. Despite variations in ethnic background, men have

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1.0 - 1.7 times greater VAT than women, whereas women have a greater SAT than men in the

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general population [14]. Moreover, lower trunk VAT region may respond differently compared

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to the whole trunk VAT in response to training in persons with SCI, highlighting the significance

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of studying VAT and SAT across the whole trunk compared to using a single axial slice as

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representation of whole trunk VAT and SAT.

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Compared to individuals with incomplete SCI, persons with complete SCI are at higher

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risks of developing cardio-metabolic disorders similar to type II diabetes mellitus, dyslipidemia

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and obesity because of decreased level of physical activity [5, 6, 23]. Deciphering the role of

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VAT and SAT in the prevalence of cardio-metabolic disorders may be clinically relevant for

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future rehabilitation interventions that target central adiposity, independent of the changes in

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body composition following SCI [2, 3, 9, 21]. Our research endeavors are focusing on clearly

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understanding the distribution of central adiposity and how this distribution is likely to lead to

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the development of cardio-metabolic disorders after SCI. Moreover, gender differences in

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central adiposity is associated with whole body metabolism and other health related

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consequences [24]. The purpose of the current work was to quantify the cross-sectional areas

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(CSAs) of VAT and SAT in men and women with a chronic SCI. We have used this model to

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assess the deleterious contribution of VAT on metabolic dysfunction in persons with SCI. We

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hypothesized that android VAT distribution is likely to contribute to metabolic dysfunction

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following SCI.

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Method

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Eight men (C7-T9; 37.5 ± 9 years old, 87 ± 21 kg, 1.8 ± 0.09 m and 26.5 ± 4.5 kg/m2)

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and eight women (C6-T11; 39 ± 13 years old, 75 ± 17.5 kg, 1.6 ± 0.06 m and 28 ± 6.5 kg/m2)

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with motor complete [(International Standards for Neurological Classification of SCI

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(ISNCSCI)], A or B) SCI were enrolled in the current study. The participants were part of a

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registered clinical trial (NCT00957762) investigating the effects of chronic SCI on body

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composition and metabolic profile. The men and women were closely matched based on age,

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level of injury and time since injury. The participants were involved in a 2-day cross-sectional

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study with an overnight stay evaluating body composition (day 1) and metabolic profile (day 2)

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similar to what has been previously described in details [26]. The study was conducted at the

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McGuire VA Medical Center (VAMC) in collaboration with the Clinical Research Center at

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Virginia Commonwealth University Medical Center. All participants were asked to read and sign

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consent forms that were approved by the local ethics committee and all study procedures were

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conducted according to the Declaration of Helsinki. Participants were recruited by word of

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mouth, flyers or from the associated SCI clinics at the participating institutions.

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Inclusion and Exclusion criteria

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Men and women (pre-or post-menopause) with chronic motor complete SCI (C5-L2; AIS

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A or B) were included if they were 18-65 years old and greater than one year post-injury [9, 25,

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26]. As previously described [26], participants with motor complete SCI were studied to control

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for variability in body composition changes that are likely to occur with motor incomplete SCI.

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Exclusion criteria included uncontrolled hypertension, uncontrolled hyperglycemia or a

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Hemoglobin A1C level greater than 7.0, chronic arterial diseases, recent deep vein thrombosis,

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uncontrolled autonomic dysreflexia, severe spasticity, fractures, or history of fractures, pressure

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ulcers greater than Grade II, documented osteoporosis, uncompensated hypothyroidism, renal

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disease. Pregnant women were also excluded and a urine pregnancy test was conducted to rule

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out pregnancy before participating in the study.

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Measurements A complete physical examination, a neurological assessment, and international standards for neurological classification of SCI (ISNCSCI) examination were conducted followed by a 7

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resting electrocardiogram and resting blood pressure measurements to rule out any possible

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cardiovascular conditions [26]. Body composition and metabolic profile measurements were

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conducted in one overnight stay over two days. After meeting the study inclusion and exclusion

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criteria, participants were invited to arrive at the laboratory around 1:00 pm to conduct body

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composition assessments [9, 25, 26]. This was followed by escorting the participant to the

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Clinical Research Center located at Virginia Commonwealth University for an overnight stay.

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After an overnight fast for 10-12 hours, each participant underwent basal metabolic rate (BMR)

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and a fasting blood lipid profile and intravenous glucose tolerance test (IVGTT) in the morning

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of the second day (see below).

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Prior to starting the two-day testing, all participants were asked to turn in 3-day dietary recall to monitor their caloric intake and macronutrients (data not shown). The 3-day dietary

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recall involved two weekdays and one weekend day. r.

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1. Body Composition Assessments (Day 1)

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Body composition assessments involved measuring body mass, height, anthropometrics and dual energy x-ray absorptiometry (DXA) for both groups.

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a. Body mass and height

Each participant was asked to void his/her bladder and then propel onto a wheelchair

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weighing scale (PW-630U; Tanita)a. After weighing the participant and his/her wheelchair (kg-

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1), participants were helped to transfer to an adjustable mat and their wheelchairs were weighted

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empty (kg-2). The body mass of each participant was determined by subtracting (2) from (1)

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(kg). The height of each participant was determined at the left side in the supine position after

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transferring to the mat and properly aligning the head, trunk and the legs. Two smooth wooden

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boards were placed at the participant’s head and heels and the distance between them 8

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corresponded to the height in nearest cm. Every effort was taken to maintain the knees in an

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extended position. The BMI (kg/m2) was calculated as the body mass (kg)/ height2 (m2) [9, 25,

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26].

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b. Anthropometrics

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Circumferential measurements were performed while participants were seated or in a lying position, while wearing non-restrictive clothes [26, 27]. Participants were asked to take a

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deep breath and to exhale and measurements were than captured during the expiration phase.

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Waist (narrowest region below the ribcage), abdominal (widest region at the level of umbilicus)

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and calf (widest region of the bulk of the calf muscles) circumferences were captured while

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seated in their wheelchairs [26]. Waist, abdominal, hip (covering both right and left greater

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trochanters) and thigh (mid-distance between anterior superior iliac spine and superior border of

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the patella) circumferences were captured in a lying position after transferring to a flat mat.

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Measurements were reported to the nearest 0.1 cm and repeated until three measures were within

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0.5 cm range of one another [26].

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c. Dual energy x-ray absorptiometry (DXA).

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DXA was used to measure body composition, specifically regional and total fat mass

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(FM), fat-free mass (FFM; lean mass [LM] and bone mass), bone mineral content (BMC) and

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density (BMD). Total body and regional DXA scans were performed using a Lunar Prodigy

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Advance (Lunar Inc., Madison, WI)b at the VAMC hospital. The scans were performed after

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lying flat for at least 20 minutes to minimize fluid shift. All scans were performed and analyzed

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by a trained, certified DXA operator using Lunar software version 10.5. The coefficient of

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variability of two repeated scans for whole body percentage FM is less than 3% [9, 25, 26].

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d. Magnetic Resonance Imaging for VAT and SAT

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MRI scans were obtained using a 3 T whole body scanner (Philips scanner, USA). T1-weighted

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imaging was performed using a fast spin-echo sequence with the following parameters: axial in-

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phase/out-phase with a repetition time of 7.96 ms and echo time of 2.38 ms for the inphase and

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the out-phase, respectively; a 30 x 40 cm field of view, matrix size of 240 × 320, flip angle is 10,

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number of excitations = 1 and acquisition time of 4–5 minutes. Transverse slices (0.4 cm

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thickness) were acquired with 0.4 cm gap from the xiphoid process to the femoral heads. Images

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were acquired in a series of two stacks with L4–L5 used as a separating point.

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Procedures for acquiring MRI

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After escorting to the radiology service, participants were transported to the scanner for a

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non-contrast abdominal MRI. Participants were then screened by MRI technician to ensure no

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contraindications to conduct the scan. The MRI table was moved outside the magnet room and

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two persons (one MRI technician and one researcher) assisted in the participant’s transfer from

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the wheelchair to the table. To avoid movement artifacts due to spasms, knees and feet were

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strapped to ensure a neutral position inside the magnet The movable table was then docked to the

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magnet with the participant’s head slid in first and arms were placed across the chest due to

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range of motion limitations preventing overhead placements. The technician instructed

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participants to maintain their position and to avoid movement during scanning. All participants

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were provided earplugs to protect against the noise of the magnet and a sheet to maintain thermo-

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neutral body temperature inside the magnet to protect against triggering muscle spasms [3, 10,

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13].

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During acquisition of a localizer sequence [13], the inter-vertebral space between L4-L5 was identified by locating the umbilicus. This allowed the MRI technician to divide the scan into

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upper and lower trunk scans to allow a short breath holding. The upper trunk scan extends

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superiorly from the xiphoid process to L4-L5 and lower trunk scan extends from L4-L5 to the

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femoral heads. During scanning, participants were asked to take a deep breath in and hold their

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breath for 10–15 seconds. The breath holding technique was applied to reduce the respiratory

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motion artifact normally associated with acquisition of MRI in the abdominal region. The use of

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a fast spin echo and dividing the trunk region into two stacks ensured a short breath holding time

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for the participants, notably more tolerable for those with higher SCI [3, 10, 13].

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Calculation of VAT and SAT area

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Images were downloaded to a disk and then they were anatomically sequenced and

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analyzed by tracing the region of interest using Image J (National Institutes of Health, Bethesda,

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Maryland) software. Researcher manually traced regions of interest for collection of trunk total

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area, VAT and SAT regions. Selection of the images was based on visual distinction of VAT and

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SAT regions within a single slice. Because of differences in central adiposity distribution

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between men and women (android vs. gynoid), we have split the trunk into upper and lower

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compartments based on the anatomical location of the umbilicus. The upper trunk and lower

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trunk included the VAT and SAT regions that extend from the top of the liver to the umbilicus

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and from the umbilicus to both femoral heads, respectively [3, 10, 13].

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2. Metabolic Assessments (Day 2)

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a. Basal metabolic rate (BMR) & dietary records

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After an overnight fast for 10-12 hours, a BMR measurement was performed in a dark

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room with indirect calorimeter using a portable COSMED K4b2. After warming-up and

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calibration at 6 am, an investigator placed a see-through canopy that covers the whole head while 11

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participant in a supine position for 20 minutes. The investigator ensured that the participant’s lay

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still during testing to attain a resting state. . Basal metabolic rate and respiratory exchange ratio

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were then calculated as the average of the last 15 minutes of the test after discarding the first 5

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minutes [25, 26].

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In four pairs of men and women, self-reported food diaries were recorded daily for 3 days for breakfast, lunch and dinner, including food that was eaten as snacks between meals for two

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weekdays and one weekend day. Participants were clearly instructed not to change their dietary

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habits and the dietary logs were returned to the study personnel and analyzed using the Nutrition

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Data System for Research (NDSR) versions 2014 nutritional software package under the

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supervision of a registered dietitian [25].

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b. Lipid Profile

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Participants underwent a fasting lipid panel [HDL-C, LDL-C, total cholesterol, and

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triglycerides (TG] assessed, with total cholesterol: HDL-C ratios utilized as the criterion variable

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[26]. A Teflon catheter was inserted into an antecubital vein of one arm or dorsal hand vein for

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blood sampling and 4 ml/subject was sent for the analysis of TG, total cholesterol, HDL-C, and

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LDL-C. After allowing the blood sample to clot for 30 minutes, the blood was centrifuged at

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3000 RPM for 10 minutes and the serum transferred for analysis. All samples were sent to the

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Chemistry Pathology Laboratory for analysis and lipids were determined by standard analyses

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procedures employed by the Clinical Research Center [25, 26]. The plasma concentrations of

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TG, cholesterol, LDL-C, HDL-C and glucose concentrations were determined using

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commercially available colorimetric assays (Sigma, Wako, and Thermo DMA, respectively).

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LDL-C analysis was performed using the Friedewald equation [LDL-C= total cholesterol - HDL

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- (TG/5)]. The ratio of cholesterol: HDL was then calculated.

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c. Intravenous Glucose Tolerance Tests (IVGTT) An intravenous glucose tolerance test (IVGTT) was performed between the hours of 8:00

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and 11:00 following an overnight 10-12-hour fast to determine insulin sensitivity (Si) and

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glucose effectiveness (Sg) [28]. Briefly, an indwelling catheter was placed in an antecubital vein

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and with an intravenous saline drip (0.9% NaCl) was initiated to maintain the patency of the

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catheter, and another intravenous line was placed in a contralateral hand vein to facilitate

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infusion of glucose and blood sampling during the IVGTT. Glucose samples were taken at –6,

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−4, −2, 0, 2, 3, 4, 5, 6, 8, 10, 12, 14, 16, 19, 22, 23, 24, 25, 27, 30, 35, 40, 50, 60, 70, 80, 90, 100,

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120, 140, 160, and 180 minutes after a rapid glucose injection (0.3 gm/kg IV over 30 seconds at

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time zero). In addition, 20 minutes after the glucose injection, a bolus of insulin (0.02 U/kg) was

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injected. The results of the IVGTT were modeled using MinMod analysis (MinMod Inc.,

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Pasadena, CA, USA). Fasting glucose, fasting insulin, insulin sensitivity (Si) and glucose

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effectiveness (Sg) were calculated [28].

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Statistical analyses

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Independent t-tests were used to test for the differences in demographics (age, time since

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injury body mass, height and BMI), body composition (anthropometrics and outcomes of DXA

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scans), MRI (VAT, SAT, VAT: SAT ratio) and metabolic profile (BMR, full lipid panel and

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IVGTT) between men and women with SCI. Pearson’s correlations were used to test for the

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relationships between body composition and metabolic variables. Statistical analyses were

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performed using SPSS version 23.0 (IBM- SPSS, Chicago, IL). All values were reported as

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mean ± SD and statistical significance was set at alpha less than 0.05. 13

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Results

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Demographics

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The physical characteristics of both groups are presented in Table 1. Both genders were closely matched based on age, level of injury (LOI) and time since injury (TSI). Men were

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significantly taller (P <.001) and were non-significantly heavier (P=.2) than women with SCI.

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Dietary intake analysis revealed that caloric intake were not different between 4 men and 4

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women with SCI (1565 ± 666 and 1380 ± 451 kcal/day, respectively; P=.4). Percentage

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macronutrients from carbohydrates (46 ± 6% vs. 48 ± 11%; P=.8) and protein (17 ± 5% vs. 18 ±

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4%; P=.8) were not significantly different, with a trend of higher fat intake (37 ± 4% vs. 30 ±

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7%; P=.07) in men compared to women with SCI.

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Gender differences and body composition

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Tables 2 and 3 present differences in anthropometrics, whole body and regional body composition between men and women with SCI. In Table 2, there was a trend (P=.06) towards

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greater waist circumference in men (97 ± 10 cm) compared to women (84 ± 13 cm) with SCI.

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The rest of supine and sitting circumferences or diameters were not different between men and

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women with SCI.

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In Table 3, % FM of arms (P=.003), legs (P=.001) and total body (P=.006) were

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significantly greater in women compared to men with SCI. Moreover, lean mass of arms

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(P=.001), legs (P=.03), trunk (P=.02) and total body (P=.003) were significantly greater in men

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compared to women with SCI. Android %FM was not different (P =.2) between men (43 ± 8%)

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and women (47 ± 7%) with SCI. Women had greater %FM at the gynoid region compared to

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men with SCI (53.5±5 vs. 42±7.7%, P =.004).

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Gender differences and Metabolic Profile

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Table 4 presents the metabolic profile in men and women with SCI. Systolic blood

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pressure was not different between women and men with SCI (women: 108 ± 15 mmHg vs. men:

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119 ± 13 mmHg, P =.1). There was a trend of greater diastolic blood pressure in men compared

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to women with SCI (women: 62 ± 11 mmHg vs. men: 74 ± 11mmHg, P =.06). Moreover,

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women had a trend towards higher glucose effectiveness compared to men with SCI (women:

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0.03 ± 0.01 min-1 vs. men: 0.02 ± 0.01 min-1, P =.06). Basal metabolic rate was not different

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between men and women with SCI (women: 1367 ± 396 kcal/day vs. men: 1421 ± 503 kcal/day,

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P =.8). However, BMR adjusted to whole body lean mass was significantly greater in women

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compared to men with SCI (women: 37.5 ± 11 kcal/day/kg vs. men: 26.4 ± 6.2 kcal/day/kg, P

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=.04)

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Gender differences and Trunk SAT and VAT

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There was a trend towards greater upper trunk SAT CSA in women compared to men

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with SCI (women: 307.5 ± 152.7 cm2 vs. men: 189± 87.5 cm2, P =.08). Moreover, lower trunk

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SAT CSA was greater in women compared to men with SCI (women: 441.5 ± 209 cm2 vs. men:

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252 ±127 cm2, P =.05).

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Upper trunk VAT CSA was significantly greater in men compared to women with SCI

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(women: 55 ± 48 cm2 vs. men: 142 ± 76 cm2, P =.02). There was a trend towards greater lower

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VAT CSA in men compared to women with SCI (women: 69 ± 57cm2 vs. men: 125 ± 54 cm2, P

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Upper trunk VAT: SAT ratio was significantly greater in men compared to women with SCI (women 0.19 ± 0.13 vs. men: 0.78 ± 0.42, P =.005). Lower trunk VAT: SAT ratio was

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significantly greater in men compared to women with SCI (women: 0.16 ± 0.1 cm2 vs. men: 0.52

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± 0. 2, P <.0001).

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Upper trunk SAT adjusted to total body FM or trunk FM was not different between men and women with SCI (total body FM: women 8.8 ± 4.25 vs. men: 6.2 ± 1.5 cm2/kg, P =.1 and

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trunk FM: women 15.5 ± 6 vs. men: 11.5 ± 3.6 cm2/kg, P =.1). Lower trunk SAT adjusted to

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total body FM or trunk FM were significantly different between men and women with SCI (total

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body FM: women 13±6 vs. men: 8±2cm2/kg, P =.04 and trunk FM: women 22±4.3 vs. men:

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14.6±3.4 cm2/kg, P =.003).

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Upper trunk VAT adjusted to total body FM or trunk FM was different between men and women with SCI (total body FM: women 8.8 ± 4.25 vs. men: 6.2 ± 1.5 cm2/kg, P =.1 and trunk

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FM: women 15.5 ± 6 vs. men: 11.5 ± 3.6 cm2/kg, P =.1). Lower trunk SAT adjusted to total

317

body FM or trunk FM were significantly different between men and women with SCI (total body

318

FM: women 13 ± 6 vs. men: 8 ± 2cm2/kg, P =0.04 & trunk FM: women 22 ± 4.3 vs. men: 14.6 ±

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3.4 cm2/kg, P =.003).

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Because men were heavier than women with SCI, upper trunk SAT adjusted to body

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weight were greater in women compared to men with SCI (women: 4 ± 2 cm2/kg vs. men: 2.15 ±

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0.65 cm2/kg, P =.02). Also lower trunk SAT adjusted to body weight were greater in women

323

compared to men with SCI (women: 5.84 ± 2.6 cm2/kg vs. men: 2.8 ± 0.84 cm2/kg, P =.008).

324

Contrary, upper trunk VAT adjusted to body weight were greater in men compared to women

325

with SCI (women: 0.69 ± 0.5 cm2/kg vs. men: 1.6 ± 0.8 cm2/kg, P =.02). Finally, lower trunk

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VAT adjusted to body weight were non-significantly greater in men compared to women with

327

SCI (women: 0.86 ± 0.55 cm2/kg vs. men: 1.44 ± 0.6 cm2/kg, P =.06).

328

Relationships between trunk SAT or VAT and metabolic profile

329

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HDL- C was positively related to upper trunk SAT adjusted to total FM (r = 0.51, P =.04) or SAT adjusted to trunk FM (r = 0.45, P =.07) and lower trunk SAT adjusted to total FM (r =

331

0.55, P =.03) or SAT adjusted to trunk FM (r = 0.51, P =.04). Cholesterol showed trends towards

332

SAT adjusted to trunk FM (r = 0.47, P =.06) and lower trunk SAT adjusted to total FM (r = 0.44,

333

P =.08) or SAT adjusted to trunk FM (r = 0.46, P =.07).

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Fasting plasma glucose showed trends for negative associations with adjusted upper trunk SAT, body weight (r = -0.45, P =.06) and both upper (r = -0.47, P=.06) or lower (r = 0.44, P

336

=.08) trunk SAT adjusted to trunk FM. Percentage HBA1c was positively related to upper (r =

337

0.70, P =.003) and lower (r = 0.73, P =.002) trunk SAT. Glucose effectiveness (Sg) was

338

negatively related to lower trunk SAT (r = -0.60, P =.02), lower trunk SAT adjusted to body

339

weight (r = -0.59, P =.02) and lower trunk SAT adjusted to total body FM (r= -0.56, P =.04). HDL-C was negatively related to upper trunk VAT (r = -0.59, P = .01), lower trunk VAT

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(r= -0.63, P =.008), VAT: SAT ratio (r = -0.56, P =.024), adjusted VAT to body weight (r = -

342

0.57, P =.02), adjusted VAT to total body FM (r = -0.54, P =.03) and adjusted VAT to trunk FM

343

(r = -0.51, P=.04). Cholesterol: HDL-C ratio was positively related to upper trunk VAT (r =

344

0.73, P =.01), lower trunk VAT (r = 0.63, P =.01), VAT: SAT ratio (r = 0.56, P=.03), adjusted

345

VAT to body weight (r =0.62, P =.01), adjusted VAT to total body FM (r = 0.6, P =.014) and

346

adjusted VAT to trunk FM (r = 0.62, P =.01). TG was positively related to upper trunk VAT (r =

347

0.51, P =.04), lower trunk VAT (r = 0.69, P =.003), VAT: SAT ratio (r = 0.67, P =.004),

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348

adjusted VAT to body weight (r = 0.78, P =.0001), adjusted VAT to total body FM (r = 0.73, P

349

=.001) and adjusted VAT to trunk FM (r = 0.69, P =.003). Diastolic blood pressure was positively related to the VAT adjusted to total body FM (r =

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350 351

0.56, P =.001) and the VAT adjusted to trunk FM (r = 0.55, P =.03).

352

Discussion

The current study was undertaken to determine the actual association of VAT to

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metabolic dysfunction following SCI. Gender difference plays a significant role in the

355

distribution of central adiposity. Anthropometrics and DXA were not sensitive to detect

356

differences in central adiposity between men and women with SCI. Women have a greater %FM

357

in the arms, legs and total body compared to men with SCI. Absolute SAT CSA is 1.6 - 1.75

358

times greater in upper and lower trunks in women compared to men with SCI. While absolute

359

VAT CSA is 1.8 - 2.6 times greater in upper and lower trunks in men compared to women with

360

SCI. Moreover, adjusted VAT: SAT ratio were greater in men compared to women independent

361

of the anatomical distribution. Adjusted VAT and SAT to trunk FM, whole body FM and whole

362

body mass confirmed the findings that men with SCI are likely to have greater VAT and lower

363

SAT accumulation compared to women with SCI. VAT is metabolically related to dysfunction

364

in lipid profile as evidenced by decrease in HDL-C and increase in cholesterol to HDL-C ratio

365

and TG.

366

Rationale of the work

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Abdominal fat distribution, particularly increased VAT, is associated with the

368

development of cardio-metabolic disease in persons with SCI and able-bodied individuals [2, 9,

369

10, 29, 30, 31]. Considering the wide spectrum of metabolic dysfunction [4, 5, 6], most of the 18

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previous published works rely on establishing the association between central adiposity (VAT or

371

SAT) and metabolic profile [2, 3, 10, 13, 29]. A handful of cross-sectional studies have

372

compared VAT, SAT and VAT: SAT ratio between persons with SCI and able-bodied

373

individuals [2,8]. While such comparisons are informative, several limitations may contribute to

374

the magnitude of differences in central adiposity between these two groups, i.e. the level of

375

physical activity [30], hormonal disruption and different dietary habits following SCI [4, 25].

376

Moreover, previous studies relied on performing single axial slice using CT compared to multi-

377

axial slices [2, 8, 18]. The use of a single axial slice is likely to overestimate the magnitude of

378

central adiposity by not accounting for the actual anatomical distribution of VAT or SAT

379

throughout the trunk [13]. Unlike previous work that established associations, the current study

380

addressed whether gender explained the relationship between VAT and cardio-metabolic profile.

381

This was performed to decipher the role of VAT or SAT to the metabolic profile by examining

382

men and women with chronic SCI matched based on age, level of injury and time since injury;

383

SCI-specific factors that may likely influence adipose tissue distribution [31]. The current design

384

may shed light on hormonal differences between genders and its role on adipose tissue

385

distribution after SCI [12].

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Every effort was made to enroll women in the study, yet, due to limited access to women

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with SCI; we have enrolled both pre-and post-menopausal women. As postmenopausal women

388

exhibit a more android shape [12, 13], this may explain why android %FM was not different

389

between men and women in this current study. However, women have greater differences of

390

%FM in their arms, legs and total body (10-15%) compared to men with SCI. This is in

391

accordance with previous work in the general population that showed 10% higher FM compared

392

to men [33, 34]. Women predominantly accumulate SAT in the abdominal or gluteo-femoral 19

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regions; whereas men have greater tendency to accumulate VAT [22, 36, 37, 38], resulting in a

394

typical android and gynoid fat distribution. The gender difference in VAT may likely follow

395

menopause, suggesting that gonadal hormones are likely to still be intact in women with SCI [22,

396

37]. Most of the women with SCI in this current study (n = 7) were in the age range of 19-52,

397

which may explain the findings of the current study. Gender dimorphism in adipose tissue

398

distribution is likely to be influenced by ethnic background and genetic makeup [39, 14].

399

Moreover, this dimorphism in adipose tissue distribution is likely to also influence secretions of

400

adipokines, inflammatory biomarkers, and leptin hormonal balance [40-42].

401

Hormonal contribution to gender differences in central adiposity

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The work is likely to stimulate future research endeavors regarding the study of

403

hormonal, genetic and environmental factors that are likely to influence VAT and SAT

404

distribution. VAT accumulation is known to have an independent cardio-metabolic risk factor

405

compared to SAT [2]. This exposes men to greater cardio-metabolic risk compared to women

406

with SCI. Women are less likely to store VAT, because estrogen protect against VAT

407

accumulation, reduces inflammatory signaling and enhances insulin sensitivity [12]. Moreover,

408

estrogen increases the number of antilipolytic alpha 2A-adregeneric receptors in SAT, but not in

409

VAT [43]. Persons with SCI suffer lower testosterone levels. Sixty percent of men with SCI

410

have low testosterone levels in the first six months after SCI [35]. Reduced testosterone levels

411

predispose men to a greater VAT accumulation. Disruption in the sympathetic nervous system

412

may impact the effects of catecholamine on adipose tissue lipolysis [36, 37]. Based on the T6

413

cut-off for intact sympathetic preganglionic neurons, we believe that 6-7 of our participants per

414

group suffered from sympathetic nervous system modulation of adipose tissue distribution [44,

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45]. In a preliminary study, the level of injury between tetraplegia and paraplegia did not

416

influence distribution of VAT or SAT CSA but did influence the metabolic profile in persons

417

with SCI [10]. Using DXA, a recent study confirmed previous findings and showed that VAT

418

volume was not different between persons with SCI above T4 compared to those with below T5

419

[46]. Those with SCI below T5 are experiencing elevated levels of TG and very LDL-C

420

compared to those with SCI above T4 [46]. Contrary in the rat model an injury at T3 is likely to

421

be accompanied with greater VAT acclamation than SCI at T10 [11]. The gonadal hormones are

422

likely to influence the genetic makeup of adipose tissue and lead to the observed distribution

423

between men and women with SCI [22, 12].

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Body composition assessment techniques have evolved from using BMI, anthropometrics, measuring whole body FM to more sophisticated imaging techniques that can

426

quantify regional adiposity [17, 35, 47]. Regional adiposity may explain a significant proportion

427

of the variance in metabolic dysfunction after SCI [9, 21]. Moreover, the use of MRI allows

428

separation of VAT and SAT and an appreciation of their independent roles on metabolic profile

429

after SCI. We have implemented three levels of measurement to quantify central adiposity

430

including anthropometrics, DXA and MRI. Anthropometrics were not sensitive to detect

431

differences in central adiposity between men and women with SCI. Previously in SCI, waist

432

circumference was found to be correlated with SAT but not VAT [13]. This is contrary to others

433

who have shown that WC is strongly correlated to VAT [2, 18]. DXA revealed that women are

434

likely to accumulate greater %FM compared to men with SCI in the gynoid region, but this

435

difference was not statistically significant between genders in the trunk region. The gynoid

436

region represents the inverted triangle at the lower trunk and supported the pear-shape

437

distribution of adipose tissue in women with SCI. Dietary habits may have influenced the

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outcomes of the current study as men consumed a greater fat intake compared to women with

439

SCI. In general, men with SCI consume a high fat diet close to 40%, which is likely to

440

contribute to the overall findings [25]. VAT is highly rich in macrophages, high-fat diet is likely

441

to activate innate immunity and triggers low grade inflammation via the release of pro-

442

inflammatory cytokines that are likely to influence metabolic profile in persons with SCI [48,

443

49].

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SAT accumulation may exert a cardio-metabolic protective effect in women with SCI. SAT has previously been noted to exert a protective effect on metabolic profile after SCI [9, 10].

446

Dyslipidemia is a common problem after SCI characterizing by low HDL-C and elevated TG [5,

447

23]. The increase in SAT may be associated with positive HDL-C profile and increase in VAT is

448

inversely associated with HDL-C. In persons with tetraplegia, greater SAT accumulation was

449

associated with an abnormal lipid profile but not in paraplegics [10]. A finding that has been

450

attributed to hyper-responsive activity of the sympathetic nervous system [50]. In the current

451

study, we observed protective of effects of SAT on lipid profile; however, seven out of eight in

452

each group were individuals with paraplegia [10]. Taking together these findings, it is possible to

453

assume that SAT may exert protective effects on the lipid profile independent of the level of SCI.

454

The current findings rule out the hypothesis that sympathetic hyperactivity may be responsible

455

for the association between SAT and lipid dysfunction after SCI.

456

Limitations

457

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445

There are a few limitations that need to be considered in the current study. Despite our

458

effort to establish the role of VAT on metabolic profile after SCI, our results were limited by the

459

small sample size. It is difficult to recruit women with SCI, especially women with motor 22

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complete SCI which further compounded the small sample size issue. Moreover, our study

461

design is cross-sectional and was based on close matching of individuals based on their level of

462

injury and AIS classification. The cross-sectional design may not provide the detailed changes

463

that are likely to be observed in body composition and metabolic profiles after SCI. Considering

464

these limitations, the current preliminary data may need to be viewed with caution and further

465

studies are warranted to investigate the gender differences in central adiposity after SCI.

466

However, we have provided 3 levels of body composition assessment (including the gold

467

standard MRI) that are likely to increase the confidence in the outcomes of the current study.

468

Considering these limitations, the current preliminary data may need to be used with caution in

469

view of our small sample size and further studies are warranted to investigate the gender

470

differences in central adiposity after SCI.

471

Conclusions

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The current work is considered a step towards establishing a direct link between VAT

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and cardio-metabolic disorders after SCI. Gender dimorphism was noted to play a role in central

474

adiposity in persons with chronic SCI. Men are more likely to store greater VAT and lower SAT

475

compared to women with SCI. Men are likely to have greater VAT accumulation in the upper

476

trunk compared to lower trunk. The findings support the association between central adiposity

477

and metabolic regulation, especially with lipid profile. Trunk SAT and VAT have reciprocal

478

associations with HDL-C. Further research needs to be accomplished to understand the

479

mechanisms responsible for differences in central adiposity after SCI. The findings of the

480

current study may be linked to several of the metabolic dysfunctions in lipid and carbohydrate

481

profiles after SCI.

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1. Després JP, Lemieux I. Abdominal obesity and metabolic syndrome. Nature 444:881-887, 2006. 2. Edwards LA, Bugaresti JM, Buchholz AC. Visceral adipose tissue and the ratio of visceral to subcutaneous adipose tissue are greater in adults with than in those without spinal cord injury, despite matching waist circumferences. Am J Clin Nutr 87:600-607, 2008. 3. Gorgey AS, Mather K, Gater DR. Central adiposity association to carbohydrate and lipid metabolism in individuals with complete motor spinal cord injury. Metabolism 60:843-851, 2011a. 4. Gorgey AS, Dolbow DR, Dolbow JD, Khalil RK, Castillo C, Gater DR. Effects of spinal cord injury on body composition and metabolic profile - part I. J Spinal Cord Med 37(6):693-702, 2014. 5. Bauman WA, Spungen AM, Zhong YG, Rothstein JL, Petry C, Gordon SK. Depressed serum high density lipoprotein cholesterol levels in veterans with spinal cord injury. Paraplegia 30:697-703, 1992. 6. Bauman WA, Spungen AM. Disorders of carbohydrate and lipid metabolism in veterans with paraplegia or quadriplegia: a model of premature aging. Metabolism 43:749-756, 1994. 7. Nash MS, Mendez AJ. A guideline-driven assessment of need for cardiovascular disease risk intervention in persons with chronic paraplegia. Arch Phys Med Rehabil 88:751-7, 2007. 8. Maruyama Y, Mizuguchi M, Yaginuma T, et al. Serum leptin, abdominal obesity and the metabolic syndrome in individuals with chronic spinal cord injury. Spinal Cord 46:494-499, 2008. 9. Gorgey AS, Gater DR. Regional and relative adiposity patterns in relation to carbohydrate and lipid metabolism in men with spinal cord injury. Appl Physiol Nutr Metab 36 (1):10714, 2011a. 10. Gorgey AS, Gater DR. A preliminary report on the effects of the level of spinal cord injury on the association between central adiposity and metabolic profile. PMR 3:440-446, 2011b. 11. Inskip JA, Plunet W, Ramer LM, et al. Cardiometabolic risk factors in experimental spinal cord injury. J Neurotrauma 27:275-285, 2010. 12. Karastergiou K, Smith SR, Greenberg AS, Fried SK. Sex differences in human adipose tissues - the biology of pear shape. Biol Sex Differ 31;3(1):13, 2012. 13. Gorgey AS, Mather KJ, Poarch H, Gater DR. Influence of motor complete spinal cord injury on visceral and subcutaneous adipose tissue measured by multi-axial magnetic resonance imaging. J Spinal Cord Med 2011;34:99-10, 2011b. 14. Bray GA, Jablonski KA, Fujimoto WY, Barrett-Connor E, Haffner S, Hanson RL, Hill JO, Hubbard V, Kriska A, Stamm E, Pi-Sunyer FX; Diabetes Prevention Program Research Group. Relation of central adiposity and body mass index to the development of diabetes in the Diabetes Prevention Program. Am J Clin Nutr 87(5):1212-8, 2008. 15. Ross R, Rissanen J, Pedwell H, Clifford J, Shragge P. Influence of diet and exercise on skeletal muscle and visceral adipose tissue in men. J Appl Physiol 81:2445-55; 1996. 16. Thomas EL, Saeed N, Hajnal JV, Brynes A, Goldstone AP, Frost G, et al. Magnetic resonance imaging of total body fat. J Appl Physiol 85:1778-85, 1998. 17. Maki KC, Briones ER, Langbein WE, Inman-Felton A, NemchauskyB, Welch M, et al. Associations between serum lipids and indicators of adiposity in men with spinal cord injury. Paraplegia 33:102-9, 1995.

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50. Teasell RW, Arnold JM, Krassioukov A, Delaney GA. Cardiovascular consequences of loss of supraspinal control of the sympathetic nervous system after spinal cord injury. Arch Phys Med Rehabil 81:506-516, 2000.

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Age (years)

Weight (kg)

Height (cm)

BMI (Kg/m2)

M M M M M M M M Mean ± SD

27 31 49 47 32 47 30 36 37.5 ± 9

82 76 71 97.5 84.5 67 85.5 133 87 ± 21

185.0 178.5 1767 196.5 174 171 172 190 180.5 ± 9

23.9 23.9 22.8 25.2 28.0 22.9 28.9 36.9 26.5 ± 5

F F F F F F F F Mean ± SD

19 29 52 44 34 46 30 58 39 ± 13

52.1 61.5 66.0 64.3 96.1 80.7 76.2 102.5 75 ± 17.5

173 157 165 155 161 164 161 167 163 ± 6

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TSI (years)

LOI

AIS

6 12 32 22 2 3.5 2.25 7 11±10.75

T8 T5 T2 T4 T3 C7 T5 T4 C7-T8

A A A A A B A A 7A/1B

4.5 10 30 23 3 5 2 4 10±10.5

T7 T5 T11 T5 T2 C6 T6 T11 C6-T11

A B A B A A A A 6A/2B

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Table 1. Physical characteristics of 8 men and 8 women with motor complete SCI

17.5 24.9 24.2 26.8 37.1 30.2 29.3 36.8 28 ± 6.5

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Table 2. Differences in anthropometrics between women and men with SCI

Abdominal (cm)

Hips (cm)

Thigh (cm)

Waist (cm)

Abdominal (cm)

67.0 76.8 76.5 82.8 102.6 81.3 84 104.7 84.5±13

69.1 82.3 75.2 87.8 112.8 92.1 84.1 124.8 91±19

87.4 91.7 107.9 104.7 123.1 108 104.3 129.5 107±14

39.6 44.2 50.2 49.7 52.7 53.9 58.3 66.3 52±8

68.6 76.3 71.7 81.7 101.4 83.5 86.8 105.8 84±13

77.1 79.7 75.1 88.4 120.9 95 95.1 121 94±18

86.6 81.0 91.7 93.3 96.9 87.4 99.1 114.7 94±10

89.7 83.2 90.2 91.6 98.3 91.5 98.9 119.9 95±11

102.9 96.2 86.4 108.6 106.4 98.9 105.2 130.8 104±13

40.9 43.4 36.4 58 53.4 51.5 63.5 50±10

89.7 87.6 94.2 98.8 98.1 87.7 99.5 116.8 97±10

0.1

0.6

0.7

0.6

0.06

Calf (cm)

Sitting Diameter

Transverse (cm)

Sagittal (cm)

Transverse (cm)

Sagittal (cm)

27.9 29.1 28.6 36.8 41.9 36.6 38.4 41.8 35±6

27.3 31.7 32.3 35.3 45.4 35 29.4 35.6 34±5

15.6 19.5 16.6 18.0 25.2 19.8 22.1 22.7 20±3

26.3 31.6 28.7 31.1 39.1 31.6 29.8 34.9 32±4

17.1 26.0 18.0 25.2 38.4 24.5 26.8 30 26±7

98.6 94.0 102.9 107.3 108.8 100.9 113.0 136.9 107±13

32.8 31.5 27.3 39.8 37 30.8 33.7 42.5 34±5

31.3 31.6 32.5 31.9 36.5 29.8 35.5 43.3 34±4

19.2 18.5 22.8 21.2 21.7 20.5 22.5 29.4 22±3

31.6 32.5 34.0 34.8 37 30.3 34.5 43.7 35±4

25.1 25.6 31.4 30.3 31.2 27.2 33.2 35.8 30±4

0.1

0.8

0.10

0.2

0.1

0.1

M AN U

TE D

EP

Supine Diameter

SC

Waist (cm)

AC C

W W W W W W W W Mean± SD M M M M M M M M Mean± SD Pvalues

Sitting Circumference

RI PT

Supine Circumference

ACCEPTED MANUSCRIPT

Table 3. Differences in regional and total body composition between women and men with SCI

% Fat

0.68 0.65 0.73 0.73 0.88 0.90 0.66 1.02 0.8±0.13

37.0 45.0 34.0 37.2 53.2 53.8 44.7 50.1 44.4±7.7

9.7 9.9 8.1 10.9 5.3 4.3 7.9 8.6 8.1±2.3

0.51 0.56 0.53 0.67 0.33 0.44 0.51 0.4 0.49±0.1

45.5 26.9 26.0 35.9 39.1 42.2 44.5 46.9 38.4±8

10.2 16.4 10.8 19.1 15.7 12.6 11.7 22.9 15±4.4

1.14 0.93 0.83 1.22 0.95 0.96 1.03 1.24 1 ± 0.14

40.8 24.5 34.4 37.8 42.2 40.3 48.1 40.9 38.7±7

0.001

0.0001

0.001

0.03

0.003

0.14

M AN U

0.003

BMC (kg)

0.87 0.95 0.85 0.82 1.41 1.20 1.15 0.98 1±0.21

36.8 43.0 43.5 41.2 51.8 52.9 42.7 53.9 45.7±6.3

23.8 26.4 25.6 26.1 22.5 18.0 21.8 35.9 25±5.2

1.55 1.08 1.05 1.44 1.08 0.79 1.36 1.19 1.2±0.24

37.0 22.8 29.1 33.2 38.2 38.3 42.6 41.5 35.3±6.7

47.4 56.9 48.1 60.4 47.7 38.1 45.5 71.8 52±10.5

3.8 3.0 3.0 3.9 2.9 2.7 3.6 3.5 3.3±0.45

0.016

0.17

0.006

0.003

0.03

RI PT

46.9 46.9 57.5 51.5 53.4 56.1 47.2 63.5 53±6

Total Lean Mass (Kg) 30.5 32.4 35.5 35.9 44.0 31.9 41.0 43.8 37±5.4

SC

0.33 0.32 0.4 0.33 0.31 0.28 0.30 0.27 0.32±0.04

% Fat

Trunk Lean Mass (Kg) 15.9 16.7 17.0 17.4 23.2 14.9 19.9 25.5 18.8±2.5

TE D

W W W W W W W W Mean± SD M M M M M M M M Mean± SD Pvalues

BMC (kg)

EP

17.3 14.0 19.3 19.0 28.8 28.4 28.9 35.6 24±7.5

% Fat

Legs Lean Mass (Kg) 6.9 8.2 11.2 11.2 12.2 11.0 12.5 12.4 10.7±2.1

AC C

26.3 40.1 35.5 33.2 53.0 54.2 32.9 49.3 40.5±10.4

Arms Lean Mass (Kg) 4.8 4.5 5.0 4.6 5.1 3.3 5.4 3.4 4.5±0.7

BMC (kg)

% Fat

BMC (kg) 2.4 2.6 2.4 2.3 3.1 3.1 2.7 2.8 2.7±0.3

ACCEPTED MANUSCRIPT

Table 4. Differences in Metabolic Profile between women and men with SCI

153 134 153 127 143 157 153 207 153±24

0.5

0.3

0.9

4.0 3.8 5.5 3.3 4.3 2.6 5.3 6.1 4±1 0.1

5.3 5.1 5.5 5.7 5.3 5.6 6.6 6±0.5

Fasting Glucose (mg/dL) 89 89 74 90 90 83 106 100 90±10

0.021098 0.018546 0.016557 0.021968 0.020846 0.002956 0.028066 0.012690 0.02±0.01

3.746900 6.062400 8.328700 10.341000 0.308760 1.791400 1.178200 2.164200 4±4

1449 953 1749 1923 1640 854 1362 1010 1367±396

102 83 227 82 86 91 237 103 126±66

5.5 5.4 5.2 4.8 5.5 5.5 5.8 6.5 6±0.5

88 101 123 102 82 80 96 106 97±14

0.013823 0.030190 0.020472 0.033971 0.040500 0.027116 0.020708 0.03±0.01

1.277900 5.263600 1.802300 4.281100 139.69000 2.940700 0.192070 22±52

1203 2197 1339 1493 1107 700 1910 1421±503

0.3

0.8

0.3

0.06

0.3

0.8

56 144 30 61 139 58 98 183 96±54

RI PT

38 35 28 39 33 60 29 34 37±10

HgA1C (%)

SC

95 82 104 72 93 79 77 152 94±26

Triglycerides (mg/dL)

M AN U

48 43 55 47 30 35 36 40 42±8

Total Cholesterol:HDL Decimal 3.0 3.9 3.4 3.3 3.8 3.9 3.7 4.4 4±0.4

TE D

77 94 110 97 57 89 78 97 87±16

Total Cholesterol (mg/dL) 142 166 186 156 115 136 134 174 151±24

EP

W W W W W W W W Mean± SD M M M M M M M M Mean± SD Pvalues

HDL (mg/dL)

AC C

LDL (mg/dL)

Sg (min-1)

Si (µu/l).min-

BMR (kcal/day)

1