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Differences in Body Composition According to Gross Motor Function in Children With Cerebral Palsy
Accepted Manuscript Differences in body composition according to gross motor function in children with cerebral palsy Ki Hyuk Sung, MD, Chin Youb Chung, MD, Kyoung Min Lee, MD, Byung Chae Cho, MD, Seung Jun Moon, MD, Jaeyoung Kim, MD, Moon Seok Park, MD PII:
S0003-9993(17)30267-8
DOI:
10.1016/j.apmr.2017.04.005
Reference:
YAPMR 56877
To appear in:
ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
Received Date: 26 July 2016 Revised Date:
9 December 2016
Accepted Date: 3 April 2017
Please cite this article as: Sung KH, Chung CY, Lee KM, Cho BC, Moon SJ, Kim J, Park MS, Differences in body composition according to gross motor function in children with cerebral palsy, ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION (2017), doi: 10.1016/ j.apmr.2017.04.005. 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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Running head: Body composition in cerebral palsy Differences in body composition according to gross motor
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function in children with cerebral palsy Ki Hyuk Sung, MD, Chin Youb Chung, MD, Kyoung Min Lee, MD, Byung Chae Cho, MD, Seung Jun Moon, MD, Jaeyoung Kim, MD, Moon Seok Park, MD
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Department of Orthopaedic Surgery, Seoul National University Bundang Hospital, 300
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Gumi-Dong, Bundang-Gu, Sungnam, Kyungki 463-707, Korea
Acknowledgement
This research was supported by Projects for Research and Development of Police science and Technology under Center for Research and Development of Police science and Technology and Korean National Police Agency funded by the Ministry of Science, ICT and Future
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Planning (Grant No. PA-C000001-2015-202).
Conflict of Interest Statement
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The authors have no conflicts of interest to disclose.
Keywords: cerebral palsy, body composition, bioelectrical impedance analysis, GMFCS
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level, soft lean mass, bone mineral content
Correspondence to:
Moon Seok Park, MD,
Department of Orthopaedic Surgery, Seoul National University Bundang Hospital, 300 Gumi-Dong, Bundang-Gu, Sungnam, Kyungki 463-707, Korea. Tel: 82-31-787-7203 Fax: 82-31-787-4056 E-mail: [email protected]
ACCEPTED MANUSCRIPT Abstract Objectives: To assess differences in body composition according to gross motor function in children with cerebral palsy (CP) compared to healthy controls. Design: Retrospective case control study. Setting: Tertiary referral center for CP
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Participants: One hundred consecutive patients (mean age, 11.5 ± 4.2 years) with CP who were admitted for orthopedic surgery between May 2014 and March 2016 and 46 typically developing children (TDC, control group) were included. Intervention: Not applicable
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Main Outcome Measures: Bioelectrical impedance analysis (BIA) was used to assess body composition, including body fat, soft lean mass (SLM), fat free mass (FFM), skeletal muscle
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mass (SMM), body cell mass (BMC), bone mineral content (BMC), and basal metabolic rate (BMR). Body composition measures were compared according to gross motor function classification system (GMFCS) level, as well as between children with CP and TDC. Results: Children with CP with GMFCS levels IV and V had a lower height, weight, and body mass index than those with GMFCS levels I, II, and III. Children with CP with GMFCS levels IV and V had a significantly lower SLM, SLM index, FFM, FFM index, SMM, SMM
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index, BCM, BCM index, BMC, and BMC index than those with GMFCS levels I to III and TDC. GMFCS level significantly affected SLM and BMC. Conclusions: Body composition analysis using BIA showed that non-ambulatory children with CP had significantly lower FFM, SLM, SMM, BCM, and BMC than ambulatory
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children with CP and TDC. However, further study is required to allow the use of BIA as a valid nutritional assessment tool in patients with CP.
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Keywords: cerebral palsy, body composition, bioelectrical impedance analysis, GMFCS level, soft lean mass, bone mineral content
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List of abbreviations: CP cerebral palsy TDC typically developing children DXA dual-energy X-ray absorptiometry
BMD bone mineral density GMFCS gross motor function classification system BMI body mass index SMM skeletal muscle mass
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SLM soft lean mass
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BIA bioelectrical impedance analysis
BCM body cell mass BMC bone mineral content VFA visceral fat area
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BMR basal metabolic rate
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FFM fat free mass
ACCEPTED MANUSCRIPT Cerebral palsy (CP) is the most common cause of physical disability in childhood, and many
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children with CP are shorter and lighter than typically developing children (TDC). In addition,
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malnutrition is common in children with moderate and severe CP, leading to a poorer health
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status and limitations in social participation.1 Therefore, measuring body composition is
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important for assessing the nutritional status and development of children with CP.
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Methods for determining the body composition include dual-energy X-ray absorptiometry
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(DXA), doubly labeled water, skin fold methods, deuterium dilution, and bioelectrical
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impedance analysis (BIA). Among these methods, BIA has been widely employed for
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assessing body composition because it is inexpensive, portable, and easy to use. BIA uses the
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body’s conductance and impedance of a low-level electrical current to assess the total body
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water.2
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Numerous studies have described the body composition of children with CP3-12, and they
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have shown that such children have lower muscle mass and bone mineral density (BMD) than
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TDC. Several studies have reported differences in body composition according to functional
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ability levels.9, 12, 13 The authors found that children with more severe gross motor impairment
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had lower fat free mass and BMD. However, few studies have evaluated body composition
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according to functional ability levels in children with CP using the BIA method.
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Therefore, we performed this study to assess differences in body composition according to
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gross motor function in children with CP compared to healthy controls using BIA. In addition,
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we determined the factors that significantly affect body composition measurements.
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Methods
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This retrospective study was approved by the institutional review board at our hospital, which
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is a tertiary referral center for CP. The informed consent was waived because of the study’s
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retrospective design.
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Participants
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Consecutive patients with CP admitted for orthopedic surgery who underwent BIA between
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May 2014 and March 2016 were eligible for inclusion in this study. Children with a history of
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genetic, metabolic, or neurodegenerative disease and children with medical conditions that
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affect growth were excluded. Patients were assessed for functional motor impairment using
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the gross motor function classification system (GMFCS), a reliable and valid method for
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evaluating motor function in those with CP.14 Demographic data such as sex, age, and
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anatomical type of CP were obtained from medical records. Healthy TDC who were not
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taking any medications that alter body composition were included in the control group.
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Anthropometric measurements
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Anthropometric measurements were performed immediately before BIA. Height and weight
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were measured without shoes using an automatic weight-measuring and height-measuring
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machine (Kiker plus; G-Tech International Co., Ltd., Seoul, Korea). For non-ambulatory
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patients with GMFCS levels IV and V, body weight was measured using a digital bed scale
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(Scale-Tronix 2001 Sling Scale; Scale-Tronix, Inc, Wheaton, IL). If the height could not be
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measured accurately, knee height was measured with an anthropometer and used to estimate
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the height using published, validated equations based on a population of children with CP.15
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The body mass index (BMI) was calculated as body weight divided by the height squared
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(kg/m2).
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Body composition measurement
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Body composition was measured the day before orthopedic surgery using a multi-frequency
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bioelectrical impedance analyzer (InBody S10; InBody, Co., Ltd., Seoul, Korea) according to
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the manufacturer’s guidelines. Measurements were performed with subjects wearing light
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clothing in the supine position. BIA estimates body composition using differences of
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conductivity of various tissues due to differences in their biological characteristics.
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Conductivity is proportional to water content, and, more specifically, to electrolytes, and it
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decreases as the cell approaches a perfect spherical shape. Adipose tissue is composed of
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round-shaped cells, and it contains relatively little water compared to other tissues such as
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muscle; therefore, conductivity decreases as body fat increases. In practice, electrodes are
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placed at eight precise tactile points of the body to conduct a multi-segmental frequency
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analysis. Thirty impedance measurements are obtained using six different frequencies (1 kHz,
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5 kHz, 50 kHz, 250 kHz, 500 kHz, and 1000 kHz) at the five following segments of the body:
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the right and left arms, trunk, and right and left legs. Skeletal muscle mass (SMM), soft lean
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mass (SLM), fat free mass (FFM), body fat, body cell mass (BCM), bone mineral content
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(BMC), waist-hip ratio, visceral fat area (VFA), and basal metabolic rate (BMR) were
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measured using BIA. Percent body fat was calculated to account for weight differences
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between children.
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To account for the effect of height, the SLM, FFM, SMM, BCM, BMC, and VFA were
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adjusted to obtain the SLM index (SLM/height2), FFM index (FFM/height2), SMM index
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(SMM/height2), BCM index (BCM/height2), BMC index (BMC/height2), and VFA index
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(VFA/height2). All measurements and data collection were performed by a research assistant
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(HMK) who did not participate in this study.
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Statistical analysis
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Normality of each variable was tested using the Kolmogorov-Smirnov test. Demographic
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characteristics, including age, height, weight, and BMI, were compared between children
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with CP and TDC using the independent t-test. Demographic data were compared between
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functional ability groups and TDC using one-way analysis of variance. Body composition
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values were compared between the functional ability groups and TDC using one-way analysis
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of covariance with data corrected for the effect of age. Multiple comparison tests were
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performed using the Bonferroni correction. Partial correlation analysis was used to determine
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associations between the body composition measures while controlling for the effects of age,
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sex, BMI, and GMFCS level. For statistical analysis, children with CP were divided into two
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groups based on the GMFCS level: ambulatory children (GMFCS levels I, II, and III) and
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non-ambulatory children (GMFCS levels IV and V). Multiple regression analysis was used to
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determine the significantly contributing factors to SLM and BMC. The goodness of fit was
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determined using adjusted R2 values. Statistical analyses were conducted using the SPSS
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software for Windows (version 22.0; SPSS, Inc., Chicago, IL, USA), and null hypotheses of
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no difference were rejected if p values were <0.05.
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Results
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One hundred patients with CP (64.0% boys) were included in this study. The mean age was
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11.5 ± 4.2 years. Most patients had diplegia (46 patients) based on the anatomic classification.
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The distribution of GMFCS levels was as follows: I, 20 patients; II, 13; III, 24; IV, 23; and V,
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20. Among the 20 patients with GMFCS level V, 9 received anticonvulsants and 4 were fed
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via a gastrostomy tube. The control group consisted of 46 TDC with a mean age of 12.8 years.
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Children with CP with GMFCS levels IV and V had a lower height, weight, and BMI than
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those with GMFCS levels I, II, and III. No significant differences in age and sex were found
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between the children with CP and the TDC. However, children with CP had a lower height,
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weight, and BMI than TDC (Table 1).
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Children with CP with GMFCS levels IV and V had significantly lower SLM, SLM index,
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ACCEPTED MANUSCRIPT FFM, FFM index, SMM, SMM index, BCM, BCM index, BMC, BMC index, and BMR than
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TDC and children with CP with GMFCS levels I to III. However, there were no significant
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differences in body composition measures between the children with CP with GMFCS levels
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I to III and the TDC, except in terms of waist-hip ratio and VFA (Table 2).
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SLM was positively correlated with BCM (r = -0.947, p < 0.001), BMC (r = -0.717, p <
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0.001), and BMR (r = -0.952, p < 0.001) and negatively correlated with percent body fat (r =
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-0.660, p < 0.001) and body fat (r = -0.304, p = 0.003). BMC was positively correlated with
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BCM (r = -0.768, p < 0.001) and BMR (r = -0.796, p < 0.001) and negatively correlated with
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PBF (r = -0.403, p < 0.001). BMR was negatively correlated with body fat (r = -0.271, p =
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0.008) and percent body fat (r = -0.646, p < 0.001) (Table 3).
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According to the results of multiple regression analysis, age (p < 0.001), sex (p = 0.012),
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BMI (p = 0.003), and GMFCS level (p < 0.001) were significant factors that contributed to
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SLM (adjusted R2 = 0.777) (Table 4). In addition, age (p < 0.001) and GMFCS level (p <
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0.001) were significant factors that contributed to BMC (adjusted R2 = 0.751) (Table 5).
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Discussion
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Our body composition analysis using the BIA method showed that children with CP,
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especially non-ambulatory children (GMFCS levels IV and V), had a lower muscle mass,
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BCM, and BMC than TDC, which was consistent with findings from previous studies using
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DXA and the isotope dilution procedure. In addition, GMFCS level was an independent
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factor that affected SLM and BMC. However, body composition in ambulatory children with
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CP was not significantly different from that of TDC.
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Previous studies showed that children with more severe gross motor impairments were
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shorter than those with less severe gross motor impairments and TDC,9, 16, 17 consistent with
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the finding of our study.
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The prevalence of obesity among ambulatory children with CP has reportedly increased in the
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United States. Additionally, being overweight is more common, and the risk of being
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overweight is greater in patients with CP than in the general population.6, 18 Peterson et al.
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reported that adults with CP have significantly more intermuscular adipose tissue and larger
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visceral and subcutaneous adipose areas than healthy adults.11 However, the increase in the
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prevalence of obesity in Asian children with CP was lower than that in children without CP.19
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A present study showed that BMI, body fat, and WHR were lower in children with CP than in
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TDC. In addition, there was no significant difference in percent body fat and VFA index
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ACCEPTED MANUSCRIPT between children with CP and TDC. This inconsistency between Western and Asian
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populations may be due to differences in ethnicity, lifestyle, dietary habits, etc. Our finding
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that ambulatory children with CP had a higher BMI than non-ambulatory children with CP
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was consistent with the results of Hurvitz et al.6 Children with CP who have severely
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impaired motor function are chronically immobile; thus, they have significant feeding
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problems and are at a greater risk of malnutrition, which may explain these findings.4, 20
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Muscle weakness due to reduced muscle size is common in patients with CP and
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compromises their physical performance.21 Fat free mass or muscle mass was significantly
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decreased in patients with CP owing to poor linear growth, muscle mass depletion, and disuse
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atrophy. Several studies have evaluated muscle size of patients with CP using magnetic
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resonance imaging8, 22 and found a significantly decreased muscle volume of the lower limbs
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compared to typically developing children with non-paretic limbs. Peterson et al.
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demonstrated using computed tomography that adults with CP have a significantly smaller
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psoas major area than healthy adults.11 Our body composition analysis showed that muscle
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mass, including SLM, FFM, and SMM, was significantly lower in non-ambulatory children
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with CP than in ambulatory children with CP and TDC, which was consistent with the results
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of previous studies.9, 12, 13 The BMR was significantly lower in non-ambulatory children with
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CP than in ambulatory children with CP and healthy controls. This result is due to the lack of
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physical activity, malnutrition, and lower muscle mass, and it is in accordance with findings
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of previous studies.7, 23 In addition, multiple regression analysis showed that GMFCS level
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was a significant factor affecting SLM in our study. However, there was no difference in
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muscle mass between ambulatory children with CP and TDC. Therefore, muscle-training
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exercise should be considered to prevent sarcopenia and enhance long-term mobility in
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patients with CP, especially in those who have severely impaired motor function.
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BCM has been reported as a valuable indicator of nutritional status, physical activity, and
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metabolic response to stress.24 A previous study showed that children with spastic
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quadriplegic CP have a decreased BCM.25 The present study reported that BCM in patients
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with GMFCS levels IV and V was significantly lower than in TDC and patients with GMFCS
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levels I to III.
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Diminished bone density and susceptibility to fractures due to minor trauma are common in
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children with CP.26, 27 Multiple factors such as limited weight-bearing ambulation during
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skeletal growth, poor nutrition, low calcium intake, anticonvulsant medication, and decreased
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outdoor activity may adversely affect bone density and metabolism in patients with CP.10, 28
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ACCEPTED MANUSCRIPT Therefore, the International Society for Clinical Densitometry recommends that DXA
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measurements should be obtained in children with an increased risk of fracture, including
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children with chronic immobilization, such as those with CP.29 Henderson et al. reported that
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severity of neurologic impairment expressed by GMFCS level contributed to a lower BMD of
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the femur.3 Moon et al. reported that bone attenuation of the acetabulum and femur was
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significantly affected by GMFCS level in children with CP.30 Mosca et al. reported a negative
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correlation between BMC and percent body fat and between BMD and percent body fat in
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adolescents, which was consistent with the results of our correlation analysis.31 Our study
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also demonstrated that BMC and BMC index were lower in non-ambulatory children than in
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ambulatory children with CP and TDC. In addition, our multiple regression analysis showed
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that GMFCS level significantly affected BMC. Therefore, evaluating bone health status and
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providing effective interventions, including calcium and vitamin D supplementation and
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bisphosphonate medication, should be considered in patients with CP who have severely
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impaired motor function.
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Body composition is most accurately evaluated using the so-called reference methods such as
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isotope dilution, DXA, and hydrostatic weighing. However, owing to cost and availability,
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these methods are not always feasible to use. Simple and less expensive methods to assess
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body composition include BIA and skinfold measurement. A review of previous studies that
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assessed the validity of BIA and skinfold measurement in CP concluded that small sample
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sizes, lack of methodological quality, and use of inappropriate analytical methods hampered
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reliable conclusions.32 Therefore, we think that further validation of the BIA method is
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needed before BIA alone can be used as an assessment tool for body composition analysis in
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CP.
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Study limitations
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This study has some limitations. First, bone mineral content was measured using BIA rather
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than DXA. However, a previous study demonstrated a high correlation between BMC
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measured by BIA and DXA in healthy adults.33 A study of this correlation in children with CP
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is required. Second, body composition can be influenced by sex, pubertal state, and age.
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However, no significant differences in age and sex were found between the children with CP
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and the TDC and between the ambulatory and non-ambulatory patients with CP in this study.
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In addition, we have controlled for age in the statistical analysis. Therefore, we think that our
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results provide valuable clinical information. Third, this study included 9 patients with
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various other factors, including immobility, low nutritional status, and low vitamin D status,
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also increase the risk of low BMD in CP patients with severely impaired motor function.
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Therefore, we think that the inclusion of these 9 patients had little effect on the results of our
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analysis. Fourth, patients with GMFCS levels IV and V typically had oral or pharyngeal
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dysphagia, which might result in poor fluid intake and affect the results of BIA. However, we
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could not control for fluid intake status because of the retrospective nature of this study. A
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further prospective study that controls for fluid intake status is required. Fifth, Table 3
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presents a multiple comparison, and Bonferroni adjustments might be needed to avoid
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inflating a type I error. However, the main weakness of the Bonferroni method is that the
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interpretation of a finding depends on the number of other tests performed. In addition, the
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likelihood of type II errors is also increased so that truly important differences are deemed
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non-significant.35 Therefore, we did not perform a p-value adjustment for this exploratory
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analysis.
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Conclusions
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Our body composition analysis using the BIA method showed that non-ambulatory children
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with CP had significantly lower FFM, SLM, SMM, BCM, and BMC than ambulatory
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children with CP and TDC. In addition, GMFCS level was a significant contributing factor to
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SLM and BMC. However, further study is required before the BIA method can be used as a
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valid nutritional assessment tool in patients with CP.
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Suppliers a. Automatic weight-measuring and height-measuring machine (Kiker plus; G-Tech International Co., Ltd., Seoul, Korea) b. Digital bed scale (Scale-Tronix 2001 Sling Scale; Scale-Tronix, Inc, Wheaton, IL)
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c. Multi-frequency bioelectrical impedance analyzer (InBody S10; InBody, Co., Ltd., Seoul, Korea)
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d. SPSS software for Windows (version 22.0; SPSS, Inc., Chicago, IL, USA)
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30. Moon SY, Kwon SS, Cho BC, Chung CY, Lee KM, Sung KH, et al. Osteopenic features
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of the hip joint in patients with cerebral palsy: a hospital-based study. Dev Med Child Neurol 2016.
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31. Mosca LN, Goldberg TB, da Silva VN, da Silva CC, Kurokawa CS, Bisi Rizzo AC, et al. Excess body fat negatively affects bone mass in adolescents. Nutrition 2014;30:847-52. 32. Rieken R, Calis EA, Tibboel D, Evenhuis HM, Penning C. Validation of skinfold measurements and bioelectrical impedance analysis in children with severe cerebral palsy: a
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review. Clin Nutr 2010;29:217-21.
33. Patil BR, Patkar DP, Mandik SA, Kuswarkar MM, Jindal GD. Estimation of bone mineral content from bioelectrical impedance analysis in Indian adults aged 23-81 years: a
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comparison with dual energy X-ray absorptiometry. Int J Biomedical Engineering and Technology 2012;8:99-114.
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34. Baroncelli G, Bertelloni S, Sodini F, Saggese G. Osteoporosis in children and adolescents: etiology and management. Paediatr Drugs 2005;7:295-323. 35. Perneger TV. What’s wrong with Bonferroni adjustments. BMJ 1998;316:1236-38.
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Table 1. Patients demographics All children with GMFCS I, II and GMFCS IV and TDC (N=46) CP (N=100) III (N=57) V (N=43) 11.5 ± 4.2 11.6 ±4.5 11.4 ± 3.9 12.8 ± 4.5 64 / 36 39 / 18 25 / 18 24 / 22
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Age (years) Sex (M/F) Anatomical type (hemiplegia / 13 / 46/ 41 13 / 36 / 8 0 / 10 / 33 diplegia / quadriplegia) Height (cm) 133.2 ± 21.0 a 139.1 ± 20.6 b, c 125.4 ± 18.9 b 149.3 ± 19.0 32.8 ± 16.0 a 38.2 ± 17.2 c 25.5 ±10.6 b 45.6 ± 18.2 Weight (Kg) Body Mass Index (kg/m2) 17.5 ± 4.5 a 18.0 ± 4.3 c 15.9 ± 4.3 b 19.5 ± 3.9 CP, cerebral palsy; GMFCS, Gross Motor Function Classification System; TDC, typically developing children All values were presented in means ± SDs. a Significantly different from the TDC (p<0.05) by independent t-test b Significantly different from the TDC (p<0.05) by one-way ANOVA c Significantly different from the GMFCS IV and V group (p<0.05) by one-way ANOVA
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Table 2. Body composition measures for children with cerebral palsy according to GMFCS level and typically developing children All children with GMFCS I, II and GMFCS IV and TDC (N=46) CP (N=100) III (N=57) V (N=43) a a Body Fat (Kg) 6.9 ± 6.4 7.6 ± 6.9 5.9 ± 5.6 11.3 ± 7.2 Percent Body Fat (%) 18.8 ± 12.9 18.0 ± 11.0 19.9 ± 15.1 23.2 ± 10.1 29.1 ± 11.8b 18.4 ± 6.8 a 31.8 ± 12.5 Soft lean mass (Kg) 24.5 ± 11.2 a Soft lean mass index (Kg/m2) 13.1 ± 2.6 14.3 ± 2.4 b 11.4 ± 1.9 a 13.7 ± 2.5 a b a Fat free mass (Kg) 25.9 ± 11.9 30.6 ± 12.6 19.7 ± 7.2 34.4 ± 13.8 13.8 ± 2.6 15.0 ± 2.4 b 12.2 ± 1.9 a 14.7 ± 2.7 Fat free mass index (Kg/m2) Skeletal Muscle Mass (Kg) 13.5 ± 7.2 a 16.4 ± 7.6 b 9.6 ± 4.3 a 18.4 ± 8.3 7.0 ± 1.9 7.9 ± 1.7 b 5.9 ± 1.3 a 7.8 ± 1.8 Skeletal Muscle Mass index (Kg/m2) a b Body Cell Mass (Kg) 17.0 ± 7.9 20.2 ± 8.3 12.8 ± 4.7 a 22.4 ± 9.1 2 b a Body Cell Mass index (Kg/m ) 9.1 ± 1.8 9.9 ± 1.6 7.9 ± 1.4 9.6 ± 1.8 Bone Mineral Content (Kg) 1.5 ± 0.8 a 1.8 ± 0.8 b 1.1 ± 0.5 a 2.0 ± 0.8 2 b a 0.8 ± 0.2 0.9 ± 0.2 0.6 ± 0.2 0.9 ± 0.2 Bone Mineral Content index (Kg/m ) Waist-hip ratio 0.8 ± 0.1 a 0.7 ± 0.1 a, b 0.8 ± 0.1 0.8 ± 0.1 2 a a Visceral Fat Area (cm ) 28.7 ± 24.0 26.1 ± 25.1 32.3 ± 22.1 46.3 ± 29.2 Visceral Fat Area index (cm2/m2) 15.5 ± 11.2 12.7 ± 10.5 a, b 19.4 ± 11.2 19.7 ± 10.2 Basal Metabolic Rate (kcal) 929.7 ± 257.4 a 1030.6 ± 273.2 b 796.0 ± 156.6 a 1112.7 ± 297.9 CP, cerebral palsy; GMFCS, Gross Motor Function Classification System; TDC, typically developing children All values were presented in means ± SDs. a Significantly different from the TDC (adjusted p-value<0.05) by one-way ANCOVA using Bonferroni correction, accounting for the influence of age b Significantly different from the GMFCS IV and V group (adjusted p-value<0.05) by one-way ANCOVA using Bonferroni correction, accounting for the influence of age
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Table 3. Partial correlation between body composition measures after adjusting age, sex, BMI and GMFCS level SLM
FFM
SMM
PBF
BCM
BMC
WHR
VFA
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Body fat -0.304 0.003 -0.273 0.007 -0.323 0.001 0.662 <0.001 -0.322 0.001 -0.090 0.384 0.482 <0.001 0.837 <0.001 -0.271 0.008
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r p-value r 0.952 FFM p-value <0.001 r 0.947 0.984 SMM p-value <0.001 <0.001 r -0.660 -0.648 -0.694 PBF p-value <0.001 <0.001 <0.001 r 0.947 0.983 1.000 -0.693 BCM p-value <0.001 <0.001 <0.001 <0.001 r 0.717 0.796 0.768 -0.403 0.768 BMC p-value <0.001 <0.001 <0.001 <0.001 <0.001 r 0.102 0.125 0.033 0.046 0.031 0.013 WHR p-value 0.325 0.225 0.750 0.655 0.764 0.899 r -0.114 -0.087 -0.182 0.442 -0.182 0.047 0.777 VFA p-value 0.267 0.399 0.076 <0.001 0.076 0.651 <0.001 r 0.129 -0.083 0.952 0.999 0.982 -0.646 0.982 0.796 BMR p-value 0.209 0.420 <0.001 <0.001 0.001 <0.001 <0.001 <0.001 BMI, body mass index; GMFCS, Gross Motor Function Classification System; r, correlation coefficient; SLM. Soft lean mass; FFM, fat free mass; SMM, skeletal muscle mass; PBF, percent body fat; BCM, body cell mass; BMC, bone mineral content; WHR, waist-hip ratio; VFA. visceral fat area; BMR, basal metabolic rate SLM
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Table 4. Multiple regression analysis to identify significantly contributing factors to soft lean mass β-coefficient 10.102 1.757 -2.881 0.427 -3.032
95% CI 3.2 to 17.1 1.5 to 2.0 -3.0 to 0.3 0.1 to 0.7 -3.9 to -2.2
Standard error 3.484 0.139 0.821 0.142 0.424
p-value 0.005 <0.001 0.012 0.003 <0.001
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Variable Coefficient Age (years) Sex (M/F) BMI (Kg/m2) GMFCS level (I/II/III/IV/V) The adjusted R2 was 0.777.
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CI, confidence interval; BMI, body mass index; GMFCS, Gross Motor Function Classification System
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Table 5. Multiple regression analysis to identify significantly contributing factors to bone mineral content β-coefficient 0.644 0.124 -0.153 0.017 -0.221
95% CI 0.1 to 1.1 0.1 to 0.1 -0.3 to 0.0 -0.0 to 0.0 -0.3 to -0.2
Standard error 0.252 0.010 0.081 0.010 0.031
p-value 0.012 <0.001 0.063 0.101 <0.001
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Variable Coefficient Age (years) Sex (M/F) BMI (Kg/m2) GMFCS level (I/II/III/IV/V) The adjusted R2 was 0.751.
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CI, confidence interval; BMI, body mass index; GMFCS, Gross Motor Function Classification System
S0003-9993(17)30267-8
DOI:
10.1016/j.apmr.2017.04.005
Reference:
YAPMR 56877
To appear in:
ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION
Received Date: 26 July 2016 Revised Date:
9 December 2016
Accepted Date: 3 April 2017
Please cite this article as: Sung KH, Chung CY, Lee KM, Cho BC, Moon SJ, Kim J, Park MS, Differences in body composition according to gross motor function in children with cerebral palsy, ARCHIVES OF PHYSICAL MEDICINE AND REHABILITATION (2017), doi: 10.1016/ j.apmr.2017.04.005. 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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Running head: Body composition in cerebral palsy Differences in body composition according to gross motor
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function in children with cerebral palsy Ki Hyuk Sung, MD, Chin Youb Chung, MD, Kyoung Min Lee, MD, Byung Chae Cho, MD, Seung Jun Moon, MD, Jaeyoung Kim, MD, Moon Seok Park, MD
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Department of Orthopaedic Surgery, Seoul National University Bundang Hospital, 300
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Gumi-Dong, Bundang-Gu, Sungnam, Kyungki 463-707, Korea
Acknowledgement
This research was supported by Projects for Research and Development of Police science and Technology under Center for Research and Development of Police science and Technology and Korean National Police Agency funded by the Ministry of Science, ICT and Future
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Planning (Grant No. PA-C000001-2015-202).
Conflict of Interest Statement
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The authors have no conflicts of interest to disclose.
Keywords: cerebral palsy, body composition, bioelectrical impedance analysis, GMFCS
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level, soft lean mass, bone mineral content
Correspondence to:
Moon Seok Park, MD,
Department of Orthopaedic Surgery, Seoul National University Bundang Hospital, 300 Gumi-Dong, Bundang-Gu, Sungnam, Kyungki 463-707, Korea. Tel: 82-31-787-7203 Fax: 82-31-787-4056 E-mail: [email protected]
ACCEPTED MANUSCRIPT Abstract Objectives: To assess differences in body composition according to gross motor function in children with cerebral palsy (CP) compared to healthy controls. Design: Retrospective case control study. Setting: Tertiary referral center for CP
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Participants: One hundred consecutive patients (mean age, 11.5 ± 4.2 years) with CP who were admitted for orthopedic surgery between May 2014 and March 2016 and 46 typically developing children (TDC, control group) were included. Intervention: Not applicable
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Main Outcome Measures: Bioelectrical impedance analysis (BIA) was used to assess body composition, including body fat, soft lean mass (SLM), fat free mass (FFM), skeletal muscle
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mass (SMM), body cell mass (BMC), bone mineral content (BMC), and basal metabolic rate (BMR). Body composition measures were compared according to gross motor function classification system (GMFCS) level, as well as between children with CP and TDC. Results: Children with CP with GMFCS levels IV and V had a lower height, weight, and body mass index than those with GMFCS levels I, II, and III. Children with CP with GMFCS levels IV and V had a significantly lower SLM, SLM index, FFM, FFM index, SMM, SMM
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index, BCM, BCM index, BMC, and BMC index than those with GMFCS levels I to III and TDC. GMFCS level significantly affected SLM and BMC. Conclusions: Body composition analysis using BIA showed that non-ambulatory children with CP had significantly lower FFM, SLM, SMM, BCM, and BMC than ambulatory
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children with CP and TDC. However, further study is required to allow the use of BIA as a valid nutritional assessment tool in patients with CP.
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Keywords: cerebral palsy, body composition, bioelectrical impedance analysis, GMFCS level, soft lean mass, bone mineral content
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List of abbreviations: CP cerebral palsy TDC typically developing children DXA dual-energy X-ray absorptiometry
BMD bone mineral density GMFCS gross motor function classification system BMI body mass index SMM skeletal muscle mass
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SLM soft lean mass
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BIA bioelectrical impedance analysis
BCM body cell mass BMC bone mineral content VFA visceral fat area
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BMR basal metabolic rate
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FFM fat free mass
ACCEPTED MANUSCRIPT Cerebral palsy (CP) is the most common cause of physical disability in childhood, and many
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children with CP are shorter and lighter than typically developing children (TDC). In addition,
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malnutrition is common in children with moderate and severe CP, leading to a poorer health
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status and limitations in social participation.1 Therefore, measuring body composition is
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important for assessing the nutritional status and development of children with CP.
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Methods for determining the body composition include dual-energy X-ray absorptiometry
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(DXA), doubly labeled water, skin fold methods, deuterium dilution, and bioelectrical
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impedance analysis (BIA). Among these methods, BIA has been widely employed for
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assessing body composition because it is inexpensive, portable, and easy to use. BIA uses the
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body’s conductance and impedance of a low-level electrical current to assess the total body
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water.2
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Numerous studies have described the body composition of children with CP3-12, and they
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have shown that such children have lower muscle mass and bone mineral density (BMD) than
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TDC. Several studies have reported differences in body composition according to functional
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ability levels.9, 12, 13 The authors found that children with more severe gross motor impairment
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had lower fat free mass and BMD. However, few studies have evaluated body composition
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according to functional ability levels in children with CP using the BIA method.
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Therefore, we performed this study to assess differences in body composition according to
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gross motor function in children with CP compared to healthy controls using BIA. In addition,
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we determined the factors that significantly affect body composition measurements.
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1
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Methods
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This retrospective study was approved by the institutional review board at our hospital, which
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is a tertiary referral center for CP. The informed consent was waived because of the study’s
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retrospective design.
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Participants
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Consecutive patients with CP admitted for orthopedic surgery who underwent BIA between
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May 2014 and March 2016 were eligible for inclusion in this study. Children with a history of
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genetic, metabolic, or neurodegenerative disease and children with medical conditions that
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affect growth were excluded. Patients were assessed for functional motor impairment using
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the gross motor function classification system (GMFCS), a reliable and valid method for
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evaluating motor function in those with CP.14 Demographic data such as sex, age, and
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anatomical type of CP were obtained from medical records. Healthy TDC who were not
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taking any medications that alter body composition were included in the control group.
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Anthropometric measurements
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Anthropometric measurements were performed immediately before BIA. Height and weight
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were measured without shoes using an automatic weight-measuring and height-measuring
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machine (Kiker plus; G-Tech International Co., Ltd., Seoul, Korea). For non-ambulatory
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patients with GMFCS levels IV and V, body weight was measured using a digital bed scale
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(Scale-Tronix 2001 Sling Scale; Scale-Tronix, Inc, Wheaton, IL). If the height could not be
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measured accurately, knee height was measured with an anthropometer and used to estimate
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the height using published, validated equations based on a population of children with CP.15
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The body mass index (BMI) was calculated as body weight divided by the height squared
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(kg/m2).
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Body composition measurement
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Body composition was measured the day before orthopedic surgery using a multi-frequency
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bioelectrical impedance analyzer (InBody S10; InBody, Co., Ltd., Seoul, Korea) according to
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the manufacturer’s guidelines. Measurements were performed with subjects wearing light
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clothing in the supine position. BIA estimates body composition using differences of
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conductivity of various tissues due to differences in their biological characteristics.
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Conductivity is proportional to water content, and, more specifically, to electrolytes, and it
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decreases as the cell approaches a perfect spherical shape. Adipose tissue is composed of
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round-shaped cells, and it contains relatively little water compared to other tissues such as
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muscle; therefore, conductivity decreases as body fat increases. In practice, electrodes are
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placed at eight precise tactile points of the body to conduct a multi-segmental frequency
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analysis. Thirty impedance measurements are obtained using six different frequencies (1 kHz,
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5 kHz, 50 kHz, 250 kHz, 500 kHz, and 1000 kHz) at the five following segments of the body:
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the right and left arms, trunk, and right and left legs. Skeletal muscle mass (SMM), soft lean
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mass (SLM), fat free mass (FFM), body fat, body cell mass (BCM), bone mineral content
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(BMC), waist-hip ratio, visceral fat area (VFA), and basal metabolic rate (BMR) were
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measured using BIA. Percent body fat was calculated to account for weight differences
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between children.
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To account for the effect of height, the SLM, FFM, SMM, BCM, BMC, and VFA were
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adjusted to obtain the SLM index (SLM/height2), FFM index (FFM/height2), SMM index
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(SMM/height2), BCM index (BCM/height2), BMC index (BMC/height2), and VFA index
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(VFA/height2). All measurements and data collection were performed by a research assistant
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(HMK) who did not participate in this study.
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Statistical analysis
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Normality of each variable was tested using the Kolmogorov-Smirnov test. Demographic
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characteristics, including age, height, weight, and BMI, were compared between children
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with CP and TDC using the independent t-test. Demographic data were compared between
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functional ability groups and TDC using one-way analysis of variance. Body composition
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values were compared between the functional ability groups and TDC using one-way analysis
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of covariance with data corrected for the effect of age. Multiple comparison tests were
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performed using the Bonferroni correction. Partial correlation analysis was used to determine
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associations between the body composition measures while controlling for the effects of age,
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sex, BMI, and GMFCS level. For statistical analysis, children with CP were divided into two
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groups based on the GMFCS level: ambulatory children (GMFCS levels I, II, and III) and
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non-ambulatory children (GMFCS levels IV and V). Multiple regression analysis was used to
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determine the significantly contributing factors to SLM and BMC. The goodness of fit was
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determined using adjusted R2 values. Statistical analyses were conducted using the SPSS
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software for Windows (version 22.0; SPSS, Inc., Chicago, IL, USA), and null hypotheses of
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no difference were rejected if p values were <0.05.
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Results
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One hundred patients with CP (64.0% boys) were included in this study. The mean age was
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11.5 ± 4.2 years. Most patients had diplegia (46 patients) based on the anatomic classification.
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The distribution of GMFCS levels was as follows: I, 20 patients; II, 13; III, 24; IV, 23; and V,
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20. Among the 20 patients with GMFCS level V, 9 received anticonvulsants and 4 were fed
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via a gastrostomy tube. The control group consisted of 46 TDC with a mean age of 12.8 years.
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Children with CP with GMFCS levels IV and V had a lower height, weight, and BMI than
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those with GMFCS levels I, II, and III. No significant differences in age and sex were found
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between the children with CP and the TDC. However, children with CP had a lower height,
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weight, and BMI than TDC (Table 1).
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Children with CP with GMFCS levels IV and V had significantly lower SLM, SLM index,
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TDC and children with CP with GMFCS levels I to III. However, there were no significant
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differences in body composition measures between the children with CP with GMFCS levels
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I to III and the TDC, except in terms of waist-hip ratio and VFA (Table 2).
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SLM was positively correlated with BCM (r = -0.947, p < 0.001), BMC (r = -0.717, p <
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0.001), and BMR (r = -0.952, p < 0.001) and negatively correlated with percent body fat (r =
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-0.660, p < 0.001) and body fat (r = -0.304, p = 0.003). BMC was positively correlated with
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BCM (r = -0.768, p < 0.001) and BMR (r = -0.796, p < 0.001) and negatively correlated with
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PBF (r = -0.403, p < 0.001). BMR was negatively correlated with body fat (r = -0.271, p =
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0.008) and percent body fat (r = -0.646, p < 0.001) (Table 3).
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According to the results of multiple regression analysis, age (p < 0.001), sex (p = 0.012),
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BMI (p = 0.003), and GMFCS level (p < 0.001) were significant factors that contributed to
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SLM (adjusted R2 = 0.777) (Table 4). In addition, age (p < 0.001) and GMFCS level (p <
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0.001) were significant factors that contributed to BMC (adjusted R2 = 0.751) (Table 5).
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Discussion
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Our body composition analysis using the BIA method showed that children with CP,
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especially non-ambulatory children (GMFCS levels IV and V), had a lower muscle mass,
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BCM, and BMC than TDC, which was consistent with findings from previous studies using
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DXA and the isotope dilution procedure. In addition, GMFCS level was an independent
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factor that affected SLM and BMC. However, body composition in ambulatory children with
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CP was not significantly different from that of TDC.
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Previous studies showed that children with more severe gross motor impairments were
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shorter than those with less severe gross motor impairments and TDC,9, 16, 17 consistent with
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the finding of our study.
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The prevalence of obesity among ambulatory children with CP has reportedly increased in the
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United States. Additionally, being overweight is more common, and the risk of being
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overweight is greater in patients with CP than in the general population.6, 18 Peterson et al.
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reported that adults with CP have significantly more intermuscular adipose tissue and larger
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visceral and subcutaneous adipose areas than healthy adults.11 However, the increase in the
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prevalence of obesity in Asian children with CP was lower than that in children without CP.19
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A present study showed that BMI, body fat, and WHR were lower in children with CP than in
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TDC. In addition, there was no significant difference in percent body fat and VFA index
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ACCEPTED MANUSCRIPT between children with CP and TDC. This inconsistency between Western and Asian
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populations may be due to differences in ethnicity, lifestyle, dietary habits, etc. Our finding
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that ambulatory children with CP had a higher BMI than non-ambulatory children with CP
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was consistent with the results of Hurvitz et al.6 Children with CP who have severely
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impaired motor function are chronically immobile; thus, they have significant feeding
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problems and are at a greater risk of malnutrition, which may explain these findings.4, 20
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Muscle weakness due to reduced muscle size is common in patients with CP and
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compromises their physical performance.21 Fat free mass or muscle mass was significantly
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decreased in patients with CP owing to poor linear growth, muscle mass depletion, and disuse
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atrophy. Several studies have evaluated muscle size of patients with CP using magnetic
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resonance imaging8, 22 and found a significantly decreased muscle volume of the lower limbs
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compared to typically developing children with non-paretic limbs. Peterson et al.
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demonstrated using computed tomography that adults with CP have a significantly smaller
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psoas major area than healthy adults.11 Our body composition analysis showed that muscle
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mass, including SLM, FFM, and SMM, was significantly lower in non-ambulatory children
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with CP than in ambulatory children with CP and TDC, which was consistent with the results
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of previous studies.9, 12, 13 The BMR was significantly lower in non-ambulatory children with
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CP than in ambulatory children with CP and healthy controls. This result is due to the lack of
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physical activity, malnutrition, and lower muscle mass, and it is in accordance with findings
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of previous studies.7, 23 In addition, multiple regression analysis showed that GMFCS level
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was a significant factor affecting SLM in our study. However, there was no difference in
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muscle mass between ambulatory children with CP and TDC. Therefore, muscle-training
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exercise should be considered to prevent sarcopenia and enhance long-term mobility in
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patients with CP, especially in those who have severely impaired motor function.
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BCM has been reported as a valuable indicator of nutritional status, physical activity, and
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metabolic response to stress.24 A previous study showed that children with spastic
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quadriplegic CP have a decreased BCM.25 The present study reported that BCM in patients
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with GMFCS levels IV and V was significantly lower than in TDC and patients with GMFCS
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levels I to III.
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Diminished bone density and susceptibility to fractures due to minor trauma are common in
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children with CP.26, 27 Multiple factors such as limited weight-bearing ambulation during
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skeletal growth, poor nutrition, low calcium intake, anticonvulsant medication, and decreased
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outdoor activity may adversely affect bone density and metabolism in patients with CP.10, 28
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ACCEPTED MANUSCRIPT Therefore, the International Society for Clinical Densitometry recommends that DXA
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measurements should be obtained in children with an increased risk of fracture, including
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children with chronic immobilization, such as those with CP.29 Henderson et al. reported that
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severity of neurologic impairment expressed by GMFCS level contributed to a lower BMD of
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the femur.3 Moon et al. reported that bone attenuation of the acetabulum and femur was
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significantly affected by GMFCS level in children with CP.30 Mosca et al. reported a negative
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correlation between BMC and percent body fat and between BMD and percent body fat in
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adolescents, which was consistent with the results of our correlation analysis.31 Our study
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also demonstrated that BMC and BMC index were lower in non-ambulatory children than in
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ambulatory children with CP and TDC. In addition, our multiple regression analysis showed
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that GMFCS level significantly affected BMC. Therefore, evaluating bone health status and
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providing effective interventions, including calcium and vitamin D supplementation and
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bisphosphonate medication, should be considered in patients with CP who have severely
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impaired motor function.
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Body composition is most accurately evaluated using the so-called reference methods such as
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isotope dilution, DXA, and hydrostatic weighing. However, owing to cost and availability,
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these methods are not always feasible to use. Simple and less expensive methods to assess
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body composition include BIA and skinfold measurement. A review of previous studies that
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assessed the validity of BIA and skinfold measurement in CP concluded that small sample
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sizes, lack of methodological quality, and use of inappropriate analytical methods hampered
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reliable conclusions.32 Therefore, we think that further validation of the BIA method is
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needed before BIA alone can be used as an assessment tool for body composition analysis in
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CP.
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Study limitations
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This study has some limitations. First, bone mineral content was measured using BIA rather
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than DXA. However, a previous study demonstrated a high correlation between BMC
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measured by BIA and DXA in healthy adults.33 A study of this correlation in children with CP
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is required. Second, body composition can be influenced by sex, pubertal state, and age.
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However, no significant differences in age and sex were found between the children with CP
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and the TDC and between the ambulatory and non-ambulatory patients with CP in this study.
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In addition, we have controlled for age in the statistical analysis. Therefore, we think that our
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results provide valuable clinical information. Third, this study included 9 patients with
ACCEPTED MANUSCRIPT GMFCS level V who received anticonvulsants, which can reduce bone mass.34 However,
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various other factors, including immobility, low nutritional status, and low vitamin D status,
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also increase the risk of low BMD in CP patients with severely impaired motor function.
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Therefore, we think that the inclusion of these 9 patients had little effect on the results of our
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analysis. Fourth, patients with GMFCS levels IV and V typically had oral or pharyngeal
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dysphagia, which might result in poor fluid intake and affect the results of BIA. However, we
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could not control for fluid intake status because of the retrospective nature of this study. A
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further prospective study that controls for fluid intake status is required. Fifth, Table 3
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presents a multiple comparison, and Bonferroni adjustments might be needed to avoid
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inflating a type I error. However, the main weakness of the Bonferroni method is that the
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interpretation of a finding depends on the number of other tests performed. In addition, the
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likelihood of type II errors is also increased so that truly important differences are deemed
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non-significant.35 Therefore, we did not perform a p-value adjustment for this exploratory
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analysis.
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Conclusions
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Our body composition analysis using the BIA method showed that non-ambulatory children
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with CP had significantly lower FFM, SLM, SMM, BCM, and BMC than ambulatory
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children with CP and TDC. In addition, GMFCS level was a significant contributing factor to
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SLM and BMC. However, further study is required before the BIA method can be used as a
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valid nutritional assessment tool in patients with CP.
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Suppliers a. Automatic weight-measuring and height-measuring machine (Kiker plus; G-Tech International Co., Ltd., Seoul, Korea) b. Digital bed scale (Scale-Tronix 2001 Sling Scale; Scale-Tronix, Inc, Wheaton, IL)
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c. Multi-frequency bioelectrical impedance analyzer (InBody S10; InBody, Co., Ltd., Seoul, Korea)
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d. SPSS software for Windows (version 22.0; SPSS, Inc., Chicago, IL, USA)
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Table 1. Patients demographics All children with GMFCS I, II and GMFCS IV and TDC (N=46) CP (N=100) III (N=57) V (N=43) 11.5 ± 4.2 11.6 ±4.5 11.4 ± 3.9 12.8 ± 4.5 64 / 36 39 / 18 25 / 18 24 / 22
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Age (years) Sex (M/F) Anatomical type (hemiplegia / 13 / 46/ 41 13 / 36 / 8 0 / 10 / 33 diplegia / quadriplegia) Height (cm) 133.2 ± 21.0 a 139.1 ± 20.6 b, c 125.4 ± 18.9 b 149.3 ± 19.0 32.8 ± 16.0 a 38.2 ± 17.2 c 25.5 ±10.6 b 45.6 ± 18.2 Weight (Kg) Body Mass Index (kg/m2) 17.5 ± 4.5 a 18.0 ± 4.3 c 15.9 ± 4.3 b 19.5 ± 3.9 CP, cerebral palsy; GMFCS, Gross Motor Function Classification System; TDC, typically developing children All values were presented in means ± SDs. a Significantly different from the TDC (p<0.05) by independent t-test b Significantly different from the TDC (p<0.05) by one-way ANOVA c Significantly different from the GMFCS IV and V group (p<0.05) by one-way ANOVA
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Table 2. Body composition measures for children with cerebral palsy according to GMFCS level and typically developing children All children with GMFCS I, II and GMFCS IV and TDC (N=46) CP (N=100) III (N=57) V (N=43) a a Body Fat (Kg) 6.9 ± 6.4 7.6 ± 6.9 5.9 ± 5.6 11.3 ± 7.2 Percent Body Fat (%) 18.8 ± 12.9 18.0 ± 11.0 19.9 ± 15.1 23.2 ± 10.1 29.1 ± 11.8b 18.4 ± 6.8 a 31.8 ± 12.5 Soft lean mass (Kg) 24.5 ± 11.2 a Soft lean mass index (Kg/m2) 13.1 ± 2.6 14.3 ± 2.4 b 11.4 ± 1.9 a 13.7 ± 2.5 a b a Fat free mass (Kg) 25.9 ± 11.9 30.6 ± 12.6 19.7 ± 7.2 34.4 ± 13.8 13.8 ± 2.6 15.0 ± 2.4 b 12.2 ± 1.9 a 14.7 ± 2.7 Fat free mass index (Kg/m2) Skeletal Muscle Mass (Kg) 13.5 ± 7.2 a 16.4 ± 7.6 b 9.6 ± 4.3 a 18.4 ± 8.3 7.0 ± 1.9 7.9 ± 1.7 b 5.9 ± 1.3 a 7.8 ± 1.8 Skeletal Muscle Mass index (Kg/m2) a b Body Cell Mass (Kg) 17.0 ± 7.9 20.2 ± 8.3 12.8 ± 4.7 a 22.4 ± 9.1 2 b a Body Cell Mass index (Kg/m ) 9.1 ± 1.8 9.9 ± 1.6 7.9 ± 1.4 9.6 ± 1.8 Bone Mineral Content (Kg) 1.5 ± 0.8 a 1.8 ± 0.8 b 1.1 ± 0.5 a 2.0 ± 0.8 2 b a 0.8 ± 0.2 0.9 ± 0.2 0.6 ± 0.2 0.9 ± 0.2 Bone Mineral Content index (Kg/m ) Waist-hip ratio 0.8 ± 0.1 a 0.7 ± 0.1 a, b 0.8 ± 0.1 0.8 ± 0.1 2 a a Visceral Fat Area (cm ) 28.7 ± 24.0 26.1 ± 25.1 32.3 ± 22.1 46.3 ± 29.2 Visceral Fat Area index (cm2/m2) 15.5 ± 11.2 12.7 ± 10.5 a, b 19.4 ± 11.2 19.7 ± 10.2 Basal Metabolic Rate (kcal) 929.7 ± 257.4 a 1030.6 ± 273.2 b 796.0 ± 156.6 a 1112.7 ± 297.9 CP, cerebral palsy; GMFCS, Gross Motor Function Classification System; TDC, typically developing children All values were presented in means ± SDs. a Significantly different from the TDC (adjusted p-value<0.05) by one-way ANCOVA using Bonferroni correction, accounting for the influence of age b Significantly different from the GMFCS IV and V group (adjusted p-value<0.05) by one-way ANCOVA using Bonferroni correction, accounting for the influence of age
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Table 3. Partial correlation between body composition measures after adjusting age, sex, BMI and GMFCS level SLM
FFM
SMM
PBF
BCM
BMC
WHR
VFA
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Body fat -0.304 0.003 -0.273 0.007 -0.323 0.001 0.662 <0.001 -0.322 0.001 -0.090 0.384 0.482 <0.001 0.837 <0.001 -0.271 0.008
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r p-value r 0.952 FFM p-value <0.001 r 0.947 0.984 SMM p-value <0.001 <0.001 r -0.660 -0.648 -0.694 PBF p-value <0.001 <0.001 <0.001 r 0.947 0.983 1.000 -0.693 BCM p-value <0.001 <0.001 <0.001 <0.001 r 0.717 0.796 0.768 -0.403 0.768 BMC p-value <0.001 <0.001 <0.001 <0.001 <0.001 r 0.102 0.125 0.033 0.046 0.031 0.013 WHR p-value 0.325 0.225 0.750 0.655 0.764 0.899 r -0.114 -0.087 -0.182 0.442 -0.182 0.047 0.777 VFA p-value 0.267 0.399 0.076 <0.001 0.076 0.651 <0.001 r 0.129 -0.083 0.952 0.999 0.982 -0.646 0.982 0.796 BMR p-value 0.209 0.420 <0.001 <0.001 0.001 <0.001 <0.001 <0.001 BMI, body mass index; GMFCS, Gross Motor Function Classification System; r, correlation coefficient; SLM. Soft lean mass; FFM, fat free mass; SMM, skeletal muscle mass; PBF, percent body fat; BCM, body cell mass; BMC, bone mineral content; WHR, waist-hip ratio; VFA. visceral fat area; BMR, basal metabolic rate SLM
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Table 4. Multiple regression analysis to identify significantly contributing factors to soft lean mass β-coefficient 10.102 1.757 -2.881 0.427 -3.032
95% CI 3.2 to 17.1 1.5 to 2.0 -3.0 to 0.3 0.1 to 0.7 -3.9 to -2.2
Standard error 3.484 0.139 0.821 0.142 0.424
p-value 0.005 <0.001 0.012 0.003 <0.001
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Variable Coefficient Age (years) Sex (M/F) BMI (Kg/m2) GMFCS level (I/II/III/IV/V) The adjusted R2 was 0.777.
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CI, confidence interval; BMI, body mass index; GMFCS, Gross Motor Function Classification System
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Table 5. Multiple regression analysis to identify significantly contributing factors to bone mineral content β-coefficient 0.644 0.124 -0.153 0.017 -0.221
95% CI 0.1 to 1.1 0.1 to 0.1 -0.3 to 0.0 -0.0 to 0.0 -0.3 to -0.2
Standard error 0.252 0.010 0.081 0.010 0.031
p-value 0.012 <0.001 0.063 0.101 <0.001
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Variable Coefficient Age (years) Sex (M/F) BMI (Kg/m2) GMFCS level (I/II/III/IV/V) The adjusted R2 was 0.751.
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CI, confidence interval; BMI, body mass index; GMFCS, Gross Motor Function Classification System