Analysis of body composition values in men with different spinal cord injury levels

Ribeiro Neto, Frederico; Lopes, Guilherme Henrique Ramos

doi:10.1590/S0103-51502013000400004

Abstracts

INTRODUCTION: Políticas públicas de promoção de saúde contribuem para encorajar o envelhecimento ativo, com independência, e tem efeitos positivos na qualidade de vida da população idosa. OBJETIVO: Avaliar os efeitos de um programa de treinamento fisioterapia de baixa intensidade, realizado em grupo, sobre a qualidade de vida de mulheres da comunidade. MATERIAIS E MÉTODOS: Realizou-se estudo clinico randomi zado. Dezessete mulheres (67,8 ± 4,9 anos de idade) que completaram 12 semanas de treinamento, a dez mulheres (68,9 ± 5,7 anos de idade) que foram incluídas no grupo controle, responderam a versão abreviada do Questionário de Qualidade de Vida da Organização Mundial de Saúde - WHOQOL-bref. O Grupo Exercício realizou treinamento de flexibilidade, resistência e equilíbrio. Análises intragrupo e intergrupo foram feitas por meio dos testes não paramétricos Wilcoxon e Mann-Whitney U, respectivamente. Foi utilizado um nível de significância de 5%. Ainda, foi determinado o Índice de Mudança Confiável segundo o Método JT. RESULTADOS: O grupo treinamento apresentou uma melhora significativa para o domínio psicológico (p = 0,047) e o grupo controle apresentou uma piora significativa para o escore geral (p = 0,01) e os domínios físico (p = 0,01) e psicológico (p = 0,008). Para o grupo de exercícios, no domínio social, duas participantes apresentaram mudança positiva confiável (MPC) e no domínio ambiente, duas participantes. Para o escore geral e domínio físico, três participantes apresentaram MPC. Para o domínio psicológico quatro participantes apresentaram MPC e uma mudança negativa confiável. CONCLUSÃO: Um programa de fisioterapia em grupo pode contribuir para manter a qualidade de vida e melhorar especialmente aspectos psicológicos de mulheres idosas da comunidade.

Body composition; Exercise; Anthropometry; Spinal cord injury; Rehabilitation

INTRODUÇÃO: A proporção entre massa corporal magra e de gordura é um preditor de doenças metabólicas. Assim, quantificar variáveis de composição corporal, iniciando uma análise de valores de referência de acordo com o nível da lesão medular (LM), tornou-se importante para o planejamento e monitoramento de atividades físicas. OBJETIVOS: 1) Determinar valores de referências de somatório de dobras cutâneas (ΣDC) e percentual de gordura em diferentes níveis de LM. 2) Detectar diferenças de composição corporal entre níveis de LM. 3) Correlacionar ΣDC com tempo de lesão e índice de massa corpórea (IMC). MATERIAIS E MÉTODOS: Setenta e quatro pacientes homens com LM, de 18 a 52 anos, foram divididos em tetraplegia (TT - C4 a C8), paraplegia alta (PPa - T1 a T6) e paraplegia baixa (PPb - T7 a L3). A composição corporal foi avaliada pelas dobras cutâneas. RESULTADOS: Não houve diferença significativa entre TT, PPa e PPb para as variáveis tempo de lesão, estatura, massa corporal total, ΣDC, percentual de gordura, massa corporal magra e IMC. Apenas a idade diferenciou entre os grupos TT e PPb (P < 0,05). A variável ΣDC não se correlacionou com o nível de lesão (rho = -0,08; IC95%: -0,537 a 0,420) ou com tempo de lesão (rho = 0,18; IC95%: -0,050 a 0,393). Não houve diferença significativa entre lesão completa e incompleta para todas as variáveis antropométricas. O ΣDC correlacionou-se positivamente com o IMC (rho = 0,68; IC95%: 0,539 a 0,739). CONSIDERAÇÕES FINAIS: TT, PPa e PPb não apresentaram diferenças significativas nos valores de composição corporal. O IMC apresentou boa correlação com ΣDC entre os grupos.

Composição corporal; Atividade física; Antropometria; Medula espinal; Reabilitação

ORIGINAL ARTICLES

Analysis of body composition values in men with different spinal cord injury levels

Frederico Ribeiro Neto^I; Guilherme Henrique Ramos Lopes^II

^IMS in Rehabilitation Science from Universidade Sarah, professor of Physical Education at Centro Internacional de Neurociências e Reabilitação Sarah, Brasília, DF -Brazil, e-mail: fredribeironeto@gmail.com

^IIMS in Physical Education from UnB, Brasília, DF -Brazil, e-mail: guilhermelopes@hotmail.com

ABSTRACT

INTRODUCTION: The proportion between lean body mass and fat mass is a predictor of metabolic diseases. Thus, quantifying body composition variables, starting an analysis of reference values according to the spinal cord injury (SCI) levels, became important for planning and monitoring physical activities.

OBJECTIVES: 1) Determine reference values for the sum of skinfolds (ΣSF) and fat mass percentage; 2) detect body composition differences between SCI levels; 3) correlate ΣSF to time since injury and body mass index (BMI).

MATERIALS AND METHODS: Seventy four male patients with SCI, aged from 18 to 52 years, were classified into quadriplegia (QP C4 to C8), high paraplegia (HPP T1 to T6), and low paraplegia (LPP T7 to L3). Body composition was assessed by means of skinfolds.

RESULTS: There was no significant difference between QP, HPP, and LPP for the variables time since injury, height, total body mass, ΣSF, fat mass percentage, lean body mass, and BMI. Only age differed between the groups QP and LPP (p < 0.05). The variable ΣSF did not correlate to injury level (rho = -0.08; CI 95%: -0.537 to 0.420) or to time since injury (rho = 0.18; CI 95%: -0.050 to 0.393). There was no significant difference between complete and incomplete injury for all anthropometric variables. The ΣSF positively correlated to BMI (rho = 0.68; CI 95%: 0.539 to 0.739).

FINAL REMARKS: TT, HPP and LPP showed no significant differences in the body composition values. The BMI showed a good correlation to ΣSF between groups.

Keywords: Body composition. Physical activity. Anthropometry. Spinal cord. Rehabilitation.

Introduction

Body composition assessment is the analysis of the distribution of different tissues, organs, and body components (1, 2). Determining the proportion of lean body mass and fat mass is an important predictor of cardiovascular diseases, diabetes type II, and dyslipidemia. Moreover, this relation may point out characteristics regarding performance in physical activities, as well as their changes may reveal the physiological responses of some training (2, 3).

Body composition analysis in people with spinal cord injury is different from that in healthy people. Spinal cord injury, defined as a trauma affecting sensory and motor control in the affected region, changes the proportion of components in body composition, which are used to calculate body density in both populations (3-6). Moreover, it promotes a number of morphological and functional changes, such as decreased bone and muscle mass, as well as decreased amount of water in the body, and increased body fat (3, 7). A possible answer to explain this increased fat is the decreased energy expenditure in higher injuries (8-12). In fact, it has already been found out a high prevalence of obesity among adolescents with spinal cord injury (6). Besides correlating to the risk factors for metabolic syndrome (glucose intolerance, hyperlipidemia, hypertension), obesity compromises ambulation and transfers, and it increases the risk for bedsores and the risk involved in surgeries among this population (6).

The physiological, morphological, and functional responses still vary considerably depending on the level of spinal cord injury (8-16). Thus, some studies categorize the spinal cord injury levels into groups, so that more systematized comparisons can be carried out (8-18). Usually, the divisions are characterized as quadriplegia, due to impairment of the upper limbs, high paraplegia, due to changes in the autonomic nervous system and muscles of the abdominal circumference, and low paraplegia.

Although it is not the gold standard, the dual-energy X-ray absorptiometry (DEXA) is used as reference with regard to the validity of methods for assessing body composition (3). However, formulas for calculating the body fat percentage did not have a good correlation to this assessment, although they are usually widely adopted in studies involving men with spinal cord injury (13, 14, 19-22). This limitation leads such measures to serve only for comparative analysis of the individual her/himself over time, instead of a relation to reference values. Some authors suggest using the sum of skinfolds as another parameter in the same type of analysis (1, 5).

The American Association of Spinal Cord Injury (ASIA) has created international standards for neurological classification of traumatic spinal cord injuries among this population. The motor level of spinal cord injury is categorized according to the strength responses from key muscles corresponding to each myotome in the spinal cord segment. The extent of impairment due to the injury ASIA Impairment Scale (AIS), in turn, varies from A to E. Complete injuries are classified as A, incomplete, as B, C, or D, and individuals without injury are classified as E (23).

The need for quantifying the body composition variables, starting an analysis of reference values, and for associating them with the functional level of the spinal cord injury, has become important for a better planning of activities, adequate monitoring of the different types of training, besides being used as instruments to encourage patients. The magnitude of these variables is influenced by the impairment generated by spinal trauma (8-16, 24).

The objectives of this study are: 1) determine reference values for the sum of skinfolds (ΣSF) and body fat percentage at different levels and the extent of spinal cord injury; 2) detect differences in body composition between levels and the extent of spinal cord injury; 3) correlate ΣSF to time since injury and body mass index (BMI) (25, 26).

Materials and methods

Sample

The convenience sample consisted of 74 male subjects with traumatic spinal cord injury who were hospitalized at Rede Sarah de Hospitais de Reabilitação, Unidade Lago Norte Brasília, within the period from July 2007 to April 2010. This study was approved by the Research Ethics Committee of Hospital Sarah (Opinion 668).

The inclusion criteria were: male individuals, over 18 years of age, diagnosed with traumatic spinal cord injury, and authorized by the medical team to continue the rehabilitation program with no restrictions.

The exclusion criteria were: patients who could not be assessed due to any reason, for instance, difficulty in positioning for assessment.

Anthropometric measurements

The anthropometric measurements taken were skinfold thickness, body mass, and height, which were obtained by the same assessor.

Skinfolds: we used plicometer (Lange) to measure, in millimeters, the skinfolds of the biceps and triceps, as well as the subscapular, pectoral, mid axillary, suprailiac, and abdominal regions, besides the thigh, and leg, according to previous standardization (1,2).

Body mass: measured with weighing scale (Filizola) and calculated by determining the difference between the wheelchair mass and the total mass (patient plus the wheelchair).

Height: measured in the supine position with the plicometer designed by the sector responsible for creating equipment for the hospital (Equiphos).

Procedures

The study is characterized as cross-sectional, i.e. observational and analytical. Data on the individuals assessed were collected from the electronic medical record and the database of the Physical Education Team. The individuals participated in body composition assessments from July 2007 to April 2010 and they were admitted to a rehabilitation program at Rede Sarah de Hospitais de Reabilitação, Unidade Lago Norte de Brasília. Such assessments are part of the treatment program for these patients, contributing to the decision making process to advise on the regular physical activity practice. All assessments were performed by the same assessor during the first week of hospitalization at the institution mentioned above.

The individuals were classified according to ASIA (23) and the neurological level was obtained from the electronic medical record. For analytical purposes, the patients were categorized into 3 groups: quadriplegia (QP) C4 to C8, high paraplegia (PPA) T1 to T6, and low paraplegia (LPP) below T7. The division of the first group when compared to the other two is due to the classification of quadriplegia by ASIA and the impairment of upper limbs (23). The separation between the second and third groups took place because of the changes deriving from the sympathetic autonomic nervous system and of the trunk instability. This division criterion is commonly used in studies with spinal cord injury (8, 12).

The ASIA Impairment Scale (AIS) ranged from A to D. Due to the small number of patients with incomplete injuries (n = 25) to be distributed among the groups TT, PPA, and PPB, an assessment of the injury extent was performed with the total sample.

In this study, for comparing body composition, we used the body mass, the sum of 9 skinfolds, and the body fat percentage calculated by means of the formula proposed by Durnin & Womersley, in 1962 (13, 14, 19, 20), which uses the skinfolds of the biceps and triceps, as well as the subscapular and suprailiac regions. Complying with the Bulbullian protocol (4), measurements of upper limbs and trunk were performed in sitting position on a wheelchair and those of lower limbs in supine position, all of them in the patient's right side (Figure 1). The skinfolds were consecutively collected and, then, a second measurement was performed and we used average as the final result. In case of a difference greater than 5% between two measurements, a third measurement was performed and the median was used as the final result (1).

As a result of the fat percentage, we also calculated for analysis: 1) body fat mass kg G (body mass multiplied by the fat percentage); 2) lean body mass kg LBM (body mass minus body fat mass); 3) percentage of lean body mass % LBM (100% minus the fat percentage).

Statistical analysis

The distribution of variables under analysis was performed by means of the Komolgorov-Smirnov normality test, as the sample was greater than 50 individuals. We found out that the variables total body mass, body fat percentage, lean body mass percentage, lean body mass, and BMI had a normal distribution. On the other hand, the variables age, time since injury, sum of skinfolds, and fat mass showed a non-parametric distribution.

For characterizing the results, we used descriptive statistics by means of average and standard deviation. Spearman's correlation was used to check the relation between the sum of skinfolds and the variables injury level, time since injury, and BMI. In order to check differences between the average values intergroups, we performed the variance analysis test (ANOVA), type one-way, and in case of significance, a post hoc analysis, with Bonferroni's test. Since it is more conservative, this test reduces the chance of finding unreal differences (error type I). The t-test for independent samples was used to compare the complete and incomplete injuries. The significance was considered only for p < 0.05.

The statistical softwares SPSS (version 13.0) and MedCalc (version 9.0.1.0) were used for data processing. The statistical significance adopted was p < 0.05.

Results

The groups TT, PPA, and PPB did not differ with regard to their basal characteristics time since injury and height. Age ranged between TT and PPB (24.8 and 29.8 years, respectively, p < 0.05) (Table 1). Thirty-four percent of the impairment level of injuries was classified as incomplete.

Thumbnail

The three groups did not differ significantly (p > 0.05) for the variables time since injury, height, total body mass, ΣSF, fat percentage, lean body mass, and BMI (Table 2). The values may be compared to other studies which also used the formula proposed by Durnin & Womersley (Table 3).

Thumbnail

There was no significant difference between complete and incomplete injuries for all variables under analysis (Table 4).

Thumbnail

The sum of skinfolds did not show a good correlation between the variables level and time since injury (rho = -0.08; CI 95%: -0.537 to 0.420; and rho = 0.18, CI 95%: -0.050 to 0.393, respectively). However, ΣSF was positively correlated to BMI (rho = 0.68; CI 95%: 0.539 to 0.739) (Graph 1).

Discussion

Body composition did not differ significantly between the groups quadriplegia, high paraplegia, and low paraplegia for all variables under study, despite the higher amount of muscles preserved in the lower injuries. However, even among the most impaired groups, there were individuals with preservation of muscles below the motor level (incomplete injuries).

The large amount of incomplete injuries (around 34.0%) increases the confusing variables, compromising an adequate inter-group analysis. Individuals with quadriplegia or incomplete high paraplegia have more active muscles, increased energy expenditure and basal metabolic rate. These components directly interfere with body composition due to changes in energy expenditure and cost (8-12).

However, despite a trend towards a better body composition for individuals with incomplete injuries (lower values of the sum of skinfolds, fat percentage and mass, and higher relative and absolute lean body mass values), there was no significant difference between complete and incomplete injuries. The same research group found similar results in a previous study (24). Perhaps, the small number of patients with incomplete injuries may have created unrealistic equality between the analyses (error type II). Confirming these data through literature is difficult, because most studies do not specify the injury extent (4, 19-22, 27); a study using only subjects with complete injuries (3) and another one had only injuries A and B (28). The latter, in turn, did not perform comparisons between groups.

The variable sum of skinfolds did not show a good correlation to level and time since injury. It was expected that this correlation was significant and positive, because the lower the injury level, the greater the preservation of muscles (8-12). A study (20) also found no correlation between these variables (20). Thus, as argued with regard to the differences of these variables between the groups, the amount of incomplete injuries seems to have influenced on these correlations.

On the other hand, the sum of skinfolds was positively correlated to BMI (rho = 0.68; CI 95%: 0.539 to 0.739). However, there is no consensus in the literature. While some recent studies show similar responses (29, 30), others differ with regard to the results found (25,26). Nevertheless, all articles agree that, besides not predicting adequately body fat, BMI does not constitute a good tool for assessing fitness. In fact, a study (31) showed a good association between the classifications of BMI to the prevalence of diabetes among war veterans with spinal cord injury.

The values of body fat percentage in each of the three groups were higher than those found in other studies assessing individuals with spinal cord injuries, from C4 to L1, with the same formula proposed by Durnin & Womersley (4, 20, 22). It is not possible to say whether the differences observed are related to social and cultural characteristics or the measurement techniques. Only one study (4) referred in its methodology to the measurement techniques (4). Furthermore, the sampling number is smaller than that used in this study and the injury impairment extent, according to AIS, was not specified (Table 3). Thus, the results found serve as reference with regard to low values of fat percentage in the groups quadriplegia, high paraplegia, and low paraplegia. These values, however, may not be classified as ideal and appropriate from a health perspective. For this, we must perform other comparisons to health markers, such as lipid profile, cardiovascular capacity, or even strength level.

Although this investigation provides a large sample, when compared to other studies with the same outcome, there is a need for analyzing the same variables with an even larger number of subjects or for carrying out a study only with traumatic complete spinal cord injuries (AIS A). Studies correlating the body fat percentage and the sum of skinfolds with indicators of health risks (e.g. lipid profile) must be carried out to assess whether the patterns observed in these studies are ideal.

Conclusion

This study provides an initial analysis to determine body composition values at different spinal cord injury levels. The use of patterns as initial reference enables a more adequate control of responses in the physical activities, as well as a motivational factor favoring health and improved functionality.

Yet, we did not observe significant differences in body composition between the groups. There was also no significant correlation between the sum of skinfolds and the variables level and time since injury. Perhaps, this was due to a sample with many patients with incomplete injuries, depriving each group of its homogeneity characteristics.

Finally, the BMI showed a good correlation to the sum of skinfolds. However, this analysis has to be assessed with caution, taking into account the limitations of BMI with regard to this specific population.

Acknowledgements

The authors thank to the Physical Education team of Rede Sarah for the provision of support in this research. This manuscript had no financial support.

References

1. Fernandes R. Composição corporal: teoria e prática da avaliação. Barueri: Manole; 2001.
2. Heyward V. Avaliação física e prescrição de exercício: técnicas avançadas. 4. ed. Porto Alegre: Artmed; 2004.
3. Mojtahedi MC, Valentine RJ, Evans EM. Body composition assessment in athletes with spinal cord injury: comparison of field methods with dual-energy X-ray absorptiometry. Spinal Cord. 2009;47(9):698-704.
4. Bulbulian R, Johnson RE, Gruber JJ, Darabos B. Body composition in paraplegic male athletes. Med Sci Sports Exerc. 1987;19(3):195-201.
5. Kocina P. Body composition of spinal cord injured adults. Sports Med. 1997;23(1):48-60.
6. Liusuwan RA, Widman LM, Abresch RT, Styne DM, McDonald CM. Body composition and resting energy expenditure in patients aged 11 to 21 years with spinal cord dysfunction compared to controls: comparisons and relationships among the groups. J Spinal Cord Med. 2007;30(Suppl 1):S105-11.
7. Levine AM, Eismont FJ, Garfin SR, Zigler JE. Spine trauma. Philadelphia: WB Saunders Co; 1998.
8. Coutinho ACB, Beraldo PSS. Validação de índices baseados em batimentos cardícos na estimativa do gasto energético durante a propulsão em cadeira de rodas por indivíduos com lesão medular. Brasília: Postgraduate Rehabilitation Sciences, Sarah Rehabilitation Hospital Network; 2007.
9. Dreisinger TE, Londeree BR. Wheelchair exercise: a review. Paraplegia. 1982 Feb;20(1):20-34.
10. Haisma JA, Bussmann JB, Stam HJ, Sluis TA, Bergen MP, Post MW, et al. Physical fitness in people with a spinal cord injury: the association with complications and duration of rehabilitation. Clin Rehabil. 2007 Oct;21(10):932-40.
11. Hopman MT, Monroe M, Dueck C, Phillips WT, Skinner JS. Blood redistribution and circulatory responses to submaximal arm exercise in persons with spinal cord injury. Scand J Rehabil Med. 1998 Sep;30(3):167-74.
12. Ribeiro FN, Beraldo PSS. Reprodutibilidade e responsividade dos índices baseados em batimentos cardíacos na propulsão de cadeira de rodas em indivíduos com lesão medular. Brasilia: Postgraduate Rehabilitation Sciences, Sarah Rehabilitation Hospital Network; 2009.
13. Vinet A, Bernard PL, Poulain M, Varray A, Le GD, Micallef JP. Validation of an incremental field test for the direct assessment of peak oxygen uptake in wheelchair-dependent athletes. Spinal Cord. 1996;34(5):288-93.
14. Vinet A, Le Gallais D, Bouges S, Bernard PL, Poulain M, Varray A, et al. Prediction of VO(2peak) in wheelchair-dependent athletes from the adapted Leger and Boucher test. Spinal Cord. 2002 Oct;40(10):507-12.
15. Middleton JW, Harvey LA, Batty J, Cameron I, Quirk R, Winstanley J. Five additional mobility and locomotor items to improve responsiveness of the FIM in wheelchair-dependent individuals with spinal cord injury. Spinal Cord. 2006;44(8):495-504.
16. Rimaud D, Calmels P, Roche F, Mongold JJ, Trudeau F, Devillard X. Effects of graduated compression stockings on cardiovascular and metabolic responses to exercise and exercise recovery in persons with spinal cord injury. Arch Phys Med Rehabil. 2007 Jun;88(6):703-9.
17. Hooker SP, Greenwood JD, Hatae DT, Husson RP, Matthiesen TL, Waters AR. Oxygen uptake and heart rate relationship in persons with spinal cord injury. Med Sci Sports Exerc. 1993 Oct;25(10):1115-9.
18. Nash MS, Spielholz NI, Jacobs PL. Passive leg cycling in persons with spinal cord injury. Arch Phys Med Rehabil. 2000 Jul;81(7):1000-2.
19. Desport JC, Preux PM, Guinvarc'h S, Rousset P, Salle JY, Daviet JC, et al. Total body water and percentage fat mass measurements using bioelectrical impedance analysis and anthropometry in spinal cord-injured patients. Clin Nutr. 2000;19(3):185-90.
20. Maggioni M, Bertoli S, Margonato V, Merati G, Veicsteinas A, Testolin G. Body composition assessment in spinal cord injury subjects. Acta Diabetol. 2003;40 (Suppl 1):S183-6.
21. Spungen AM, Adkins RH, Stewart CA, Wang J, Pierson RN Júnior., Waters RL, et al. Factors influencing body composition in persons with spinal cord injury: a cross-sectional study. J Appl Physiol. 2003;95(6):2398-407.
22. Spungen AM, Bauman WA, Wang J, Pierson RN Júnior. Measurement of body fat in individuals with tetraplegia: a comparison of eight clinical methods. Paraplegia. 1995;33(7):402-8.
23. Marino RJ, Barros T, Biering-Sorensen F, Burns SP, Donovan WH, Graves DE, et al. International standards for neurological classification of spinal cord injury. J Spinal Cord Med. 2003 Spring; 26 (Suppl 1): S50-6.
24. Ribeiro FN, Lopes GH. Body composition modifications in people with chronic spinal cord injury after supervised physical activity. Journal of Spinal Cord Medicine. 2011;34(6):586-93.
25. Buchholz AC, Bugaresti JM. A review of body mass index and waist circumference as markers of obesity and coronary heart disease risk in persons with chronic spinal cord injury. Spinal Cord. 2005;43(9):513-8.
26. McDonald CM, Abresch-Meyer AL, Nelson MD, Widman LM. Body mass index and body composition measures by dual x-ray absorptiometry in patients aged 10 to 21 years with spinal cord injury. J Spinal Cord Med. 2007;30(Suppl 1):S97-104.
27. Phillips WT, Kiratli BJ, Sarkarati M, Weraarchakul G, Myers J, Franklin BA, et al. Effect of spinal cord injury on the heart and cardiovascular fitness. Curr Probl Cardiol. 1998;23(11):641-716.
28. Hjeltnes N, Aksnes AK, Birkeland KI, Johansen J, Lannem A, Wallberg-Henriksson H. Improved body composition after 8 wk of electrically stimulated leg cycling in tetraplegic patients. Am J Physiol. 1997;273(3 Pt 2):R1072-9.
29. Arsenault BJ, Cartier A, Cote M, Lemieux I, Tremblay A, Bouchard C, et al. Body composition, cardiorespiratory fitness, and low-grade inflammation in middle-aged men and women. Am J Cardiol. 2009 Jul 15;104(2):240-6.
30. Pietrobelli A, Tato L. Body composition measurements: from the past to the future. Acta Paediatr Suppl. 2005;94(448):8-13.
31. Rajan S, McNeely MJ, Hammond M, Goldstein B, Weaver F. Association between obesity and diabetes mellitus in veterans with spinal cord injuries and disorders. Am J Phys Med Rehabil. 2010;89(5):353-61.

1

Contribuição dos autores: os autores Ribeiro F Neto e Lopes GHR foram responsáveis pela ideia da pesquisa e elaboração do manuscrito. A coleta de dados foi realizada por Ribeiro F Neto

Publication Dates

Publication in this collection
03 Feb 2014
Date of issue
Dec 2013

History

Received
11 Sept 2012
Accepted
21 June 2013

This work is licensed under a Creative Commons Attribution 4.0 International License.

[1] 1. Fernandes R. Composição corporal: teoria e prática da avaliação. Barueri: Manole; 2001.

[2] 2. Heyward V. Avaliação física e prescrição de exercício: técnicas avançadas. 4. ed. Porto Alegre: Artmed; 2004.

[3] 3. Mojtahedi MC, Valentine RJ, Evans EM. Body composition assessment in athletes with spinal cord injury: comparison of field methods with dual-energy X-ray absorptiometry. Spinal Cord. 2009;47(9):698-704.

[4] 4. Bulbulian R, Johnson RE, Gruber JJ, Darabos B. Body composition in paraplegic male athletes. Med Sci Sports Exerc. 1987;19(3):195-201.

[5] 5. Kocina P. Body composition of spinal cord injured adults. Sports Med. 1997;23(1):48-60.

[6] 6. Liusuwan RA, Widman LM, Abresch RT, Styne DM, McDonald CM. Body composition and resting energy expenditure in patients aged 11 to 21 years with spinal cord dysfunction compared to controls: comparisons and relationships among the groups. J Spinal Cord Med. 2007;30(Suppl 1):S105-11.

[7] 7. Levine AM, Eismont FJ, Garfin SR, Zigler JE. Spine trauma. Philadelphia: WB Saunders Co; 1998.

[8] 8. Coutinho ACB, Beraldo PSS. Validação de índices baseados em batimentos cardícos na estimativa do gasto energético durante a propulsão em cadeira de rodas por indivíduos com lesão medular. Brasília: Postgraduate Rehabilitation Sciences, Sarah Rehabilitation Hospital Network; 2007.

[9] 9. Dreisinger TE, Londeree BR. Wheelchair exercise: a review. Paraplegia. 1982 Feb;20(1):20-34.

[10] 10. Haisma JA, Bussmann JB, Stam HJ, Sluis TA, Bergen MP, Post MW, et al. Physical fitness in people with a spinal cord injury: the association with complications and duration of rehabilitation. Clin Rehabil. 2007 Oct;21(10):932-40.

[11] 11. Hopman MT, Monroe M, Dueck C, Phillips WT, Skinner JS. Blood redistribution and circulatory responses to submaximal arm exercise in persons with spinal cord injury. Scand J Rehabil Med. 1998 Sep;30(3):167-74.

[12] 12. Ribeiro FN, Beraldo PSS. Reprodutibilidade e responsividade dos índices baseados em batimentos cardíacos na propulsão de cadeira de rodas em indivíduos com lesão medular. Brasilia: Postgraduate Rehabilitation Sciences, Sarah Rehabilitation Hospital Network; 2009.

[13] 13. Vinet A, Bernard PL, Poulain M, Varray A, Le GD, Micallef JP. Validation of an incremental field test for the direct assessment of peak oxygen uptake in wheelchair-dependent athletes. Spinal Cord. 1996;34(5):288-93.

[14] 14. Vinet A, Le Gallais D, Bouges S, Bernard PL, Poulain M, Varray A, et al. Prediction of VO(2peak) in wheelchair-dependent athletes from the adapted Leger and Boucher test. Spinal Cord. 2002 Oct;40(10):507-12.

[15] 15. Middleton JW, Harvey LA, Batty J, Cameron I, Quirk R, Winstanley J. Five additional mobility and locomotor items to improve responsiveness of the FIM in wheelchair-dependent individuals with spinal cord injury. Spinal Cord. 2006;44(8):495-504.

[16] 16. Rimaud D, Calmels P, Roche F, Mongold JJ, Trudeau F, Devillard X. Effects of graduated compression stockings on cardiovascular and metabolic responses to exercise and exercise recovery in persons with spinal cord injury. Arch Phys Med Rehabil. 2007 Jun;88(6):703-9.

[17] 17. Hooker SP, Greenwood JD, Hatae DT, Husson RP, Matthiesen TL, Waters AR. Oxygen uptake and heart rate relationship in persons with spinal cord injury. Med Sci Sports Exerc. 1993 Oct;25(10):1115-9.

[18] 18. Nash MS, Spielholz NI, Jacobs PL. Passive leg cycling in persons with spinal cord injury. Arch Phys Med Rehabil. 2000 Jul;81(7):1000-2.

[19] 19. Desport JC, Preux PM, Guinvarc'h S, Rousset P, Salle JY, Daviet JC, et al. Total body water and percentage fat mass measurements using bioelectrical impedance analysis and anthropometry in spinal cord-injured patients. Clin Nutr. 2000;19(3):185-90.

[20] 20. Maggioni M, Bertoli S, Margonato V, Merati G, Veicsteinas A, Testolin G. Body composition assessment in spinal cord injury subjects. Acta Diabetol. 2003;40 (Suppl 1):S183-6.

[21] 21. Spungen AM, Adkins RH, Stewart CA, Wang J, Pierson RN Júnior., Waters RL, et al. Factors influencing body composition in persons with spinal cord injury: a cross-sectional study. J Appl Physiol. 2003;95(6):2398-407.

[22] 22. Spungen AM, Bauman WA, Wang J, Pierson RN Júnior. Measurement of body fat in individuals with tetraplegia: a comparison of eight clinical methods. Paraplegia. 1995;33(7):402-8.

[23] 23. Marino RJ, Barros T, Biering-Sorensen F, Burns SP, Donovan WH, Graves DE, et al. International standards for neurological classification of spinal cord injury. J Spinal Cord Med. 2003 Spring; 26 (Suppl 1): S50-6.

[24] 24. Ribeiro FN, Lopes GH. Body composition modifications in people with chronic spinal cord injury after supervised physical activity. Journal of Spinal Cord Medicine. 2011;34(6):586-93.

[25] 25. Buchholz AC, Bugaresti JM. A review of body mass index and waist circumference as markers of obesity and coronary heart disease risk in persons with chronic spinal cord injury. Spinal Cord. 2005;43(9):513-8.

[26] 26. McDonald CM, Abresch-Meyer AL, Nelson MD, Widman LM. Body mass index and body composition measures by dual x-ray absorptiometry in patients aged 10 to 21 years with spinal cord injury. J Spinal Cord Med. 2007;30(Suppl 1):S97-104.

[27] 27. Phillips WT, Kiratli BJ, Sarkarati M, Weraarchakul G, Myers J, Franklin BA, et al. Effect of spinal cord injury on the heart and cardiovascular fitness. Curr Probl Cardiol. 1998;23(11):641-716.

[28] 28. Hjeltnes N, Aksnes AK, Birkeland KI, Johansen J, Lannem A, Wallberg-Henriksson H. Improved body composition after 8 wk of electrically stimulated leg cycling in tetraplegic patients. Am J Physiol. 1997;273(3 Pt 2):R1072-9.

[29] 29. Arsenault BJ, Cartier A, Cote M, Lemieux I, Tremblay A, Bouchard C, et al. Body composition, cardiorespiratory fitness, and low-grade inflammation in middle-aged men and women. Am J Cardiol. 2009 Jul 15;104(2):240-6.

[30] 30. Pietrobelli A, Tato L. Body composition measurements: from the past to the future. Acta Paediatr Suppl. 2005;94(448):8-13.

[31] 31. Rajan S, McNeely MJ, Hammond M, Goldstein B, Weaver F. Association between obesity and diabetes mellitus in veterans with spinal cord injuries and disorders. Am J Phys Med Rehabil. 2010;89(5):353-61.