Which anthropometric equation to predict body fat percentage is more strongly associated with maximum oxygen uptake in adolescents? A cross-sectional study

Autores

Palavras-chave:

Association, lifestyle, Physical activity, Adolescent health, Overweight

Resumo

BACKGROUND: Identifying the relationship between maximum consumption of oxygen and body fat percentage is important due to increased cardiovascular risk factors. OBJECTIVE: This study aimed to verify the association between body fat percentage determined by three predictive equations using anthropometric measures (Lohman, Boileau, and Slaughter) and maximum oxygen uptake (VO2max). We also aimed to estimate the capacity of these equations for explaining VO2max variations in adolescents according to sex. DESIGN AND SETTING: This was a cross-sectional study conducted in high schools in São José, Southern Brazil. METHODS: This study included 879 adolescents (14–19 years) from Southern Brazil. Aerobic fitness was assessed using the modified Canadian Aerobic Fitness Test. The independent variable was body fat percentage predicted by the Lohman, Boileau, and Slaughter equations. Analyses adjusted for sociodemographic variables, physical activity level, and sexual maturation were performed with P value < 0.05. RESULTS: All anthropometric prediction equations used to estimate body fat percentage explained VO2max variations in adolescents. In male adolescents, both regression models based on the Boileau et al.12 and Lohman10 equations revealed higher explanatory power for VO2max (20%) compared with that based on the Slaughter et al.13 equation (19%). In female adolescents, the model based on the anthropometric equation of Slaughter et al.13 showed the greatest explanatory power for VO2max (18%). CONCLUSION: The inverse relationship between VO2max and body fat intensifies the need for effective intervention programs that prioritize maintenance of appropriate body fat and aerobic fitness levels because inadequate levels of both factors result in negative health consequences.

Downloads

Não há dados estatísticos.

Biografia do Autor

Eliane Cristina de Andrade Gonçalves, High Schools

PhD. Assistant Professor, Department of Physical Education, Universidade Estadual de Maringá (UEM), Maringá (PR), Brazil.

Nelson Nardo Júnior, High Schools

PhD. Associate Professor, Department of Physical Education, Universidade Estadual de Maringá (UEM), Maringá (PR), Brazil.

Michele Caroline de Souza Ribas, High Schools

PhD. Assistant Professor, Department of Physical Education, Universidade Federal de Santa Catarina (UFSC), Florianópolis (SC), Brazil.

Diego Augusto Santos Silva, High Schools

PhD. Associate Professor, Department of Physical Education, Universidade Federal de Santa Catarina (UFSC), Florianópolis (SC), Brazil. Associate Researcher, Faculty of Health Sciences, Universidad Autónoma de Chile, Providencia, Chile.

Referências

Lang JJ, Tomkinson GR, Janssen I, et al. Making a Case for Cardiorespiratory Fitness Surveillance Among Children and Youth. Exerc Sport Sci Rev. 2018;46(2):66-75. PMID: 29346159; https://doi.org/10.1249/JES.0000000000000138.

Moreira C, Santos R, de Farias Júnior JC, et al. Metabolic risk factors, physical activity and physical fitness in Azorean adolescents: a cross-sectional study. BMC Public Health. 2011;11:214. PMID: 21470414; https://doi.org/10.1186/1471-2458-11-214.

American College of Sports Medicine. ACSM’s Guidelines for Exercise Testing and Prescription. 9nd ed. Philadelphia: Lippincott Williams & Wilkins; 2014.

Ministério do Planejamento, Desenvolvimento e Gestão. Instituto Brasileiro de Geografia e Estatística – IBGE. Direito de Pesquisar, Coordenação de População e Indicadores Sociais. Pesquisa Nacional de Saúde do Escolar, 2015. Rio de Janeiro: IBGE; 2016. Available from: https://biblioteca.ibge.gov.br/visualizacao/livros/liv97870.pdf. Accessed in 2022 (Jul 22).

Associação Brasileira para o Estudo da Obesidade e Síndrome Metabólica. Mapa da Obesidade. Available from: https://abeso.org.br/obesidade-e-sindrome-metabolica/mapa-da-obesidade/. Accessed in 2022 (Jul 22).

Rivera JÁ, de Cossío TG, Pedraza LS, et al. Childhood and adolescent overweight and obesity in Latin America: a systematic review. Lancet Diabetes Endocrinol. 2014;2(4):321-32. PMID: 24703050; https://doi.org/10.1016/S2213-8587(13)70173-6.

World Health Organization. Global Status Repor t on noncommunicable diseases. 2014. Available from: https://apps.who.int/iris/bitstream/handle/10665/148114/9789241564854_eng. pdf. Accessed in 2022 (Jul 22).

Silva DAS, Petroski EL, Gaya ACA. Secular changes in aerobic fitness levels in Brazilian children. Rev Bras Med Esporte. 2017;23(6):450-4. https://doi.org/10.1590/1517-869220172306150424.

Ronque ERV, Cyrino ES, Mortatti AL, et al. Relationship between cardiorespiratory fitness and indicators of body adiposity in adolescents. Rev Paul Pediatr. 2010;28(3):296-302. https://doi.org/10.1590/S0103-05822010000300007.

Lohman TG. Applicability of body composition techniques and constants for children and youth. In: Pandolf KB. Exercise and sport sciences reviews. New York: Macmillan, 1986.

Barbosa L, Chaves OC, Ribeiro RCL. Anthropometric and body composition parameters to predict body fat percentage and lipid profile in schoolchildren. Rev Paul Pediatr. 2012;30(4):520-8. https://doi.org/10.1590/S0103-05822012000400010.

Boileau RA, Lohman TG, Slaughter MH. Exercise and body composition in children and youth. Scand J Med Sci Sports. 1985;7:17-27. Available from: https://experts.arizona.edu/en/publications/exercise-and-body-composition-of-children-and-youth. Accessed in 2022 (Jul 22).

Slaughter M, Lohman T, Boileau R, et al. Skinfold equations for estimation of body fatness in children and youth. Hum Biol. 1988;60(5):709-23. PMID: 3224965.

Canadian Society for Exercise Physiology. The Canadian Physical Activity, Fitness & Lifestyle Appraisal: CSEP’s Plan for Healthy Living. 2nd ed. Ottawa: Canadian Society for Exercise Physiology (CSEP); 1998.

Weller IM, Thomas SG, Gledhill N, Paterson D, Quinneu A. A study to validate the modified Canadian Aerobic Fitness Test. Can J Appl Physiol. 1995;20(2):211-21. PMID: 7640647; https://doi.org/10.1139/h95-015.

Pires-Neto CS, Petroski EL. Preposições de constantes para o uso em equações preditivas da gordura corporal para crianças e jovens. Anais da III Bienal de Ciência do Esporte 1993; 27.

Ministério do Planejamento, Orçamento e Gestão. Instituo Brasileiro de Geografia e Estatística – IBGE. Diretoria de Pesquisas, Coordenação de Trabalho e Rendimento. Pesquisa de Orçamentos Familiares 2008-2009. Despesas, rendimentos e condições de vida. Rio de Janeiro: IBGE; 2010. Available from: https://biblioteca.ibge.gov.br/visualizacao/livros/liv45130.pdf. Accessed in 2022 (Jul 22).

Associação Brasileira de Empresas De Pesquisa (ABEP). Critério de classificação econômica Brasil. São Paulo: ABEP, 2010.

Strong WB, Malina RM, Blimkie CJ, et al. Evidence based physical activity for school-age youth. J Pediatr. 2005;146(6):732-7. PMID: 15973308; https://doi.org/10.1016/j.jpeds.2005.01.055.

Tanner JM. Growth at adolescence. Oxford: Blackwell Scientific; 1962.

Matsudo SMM, Matsudo KR. Self-assessment and physician assessment of sexual maturation in Brazilian boys and girls: Concordance and reproducibility. Am J Hum Biol. 1994;6(4):451-5. PMID: 28548259; https://doi.org/10.1002/ajhb.1310060406.

Curran PJ, West SG, Finch JF. The robustness of test statistics to nonnormality and specification error in confirmatory factor analysis. Psychol Methods. 1996;1(1):16-29; https://doi.org/10.1037/1082-989X.1.1.16.

de Andrade Gonçalves EC, Augusto Santos Silva D, Gimenes Nunes HE. Prevalence and factors associated with low aerobic performance levels in adolescents: a systematic review. Curr Pediatr Rev. 2015;11(1):56-70. PMID: 25938376; https://doi.org/10.2174/1573396311666150501003435.

Haapala EA, Lankhorst K, de Groot J, et al. The associations of cardiorespiratory fitness, adiposity and sports participation with arterial stiffness in youth with chronic diseases or physical disabilities. Eur J Prev Cardiol. 2017;24(10):1102-11. PMID: 28374647; https://doi.org/10.1177/2047487317702792.

Silva AJ, Miranda Neto JT, Monteiro ADAF, et al. Medidas e Avaliação. In: Aspectos metodológicos e o uso de equações antropométricas para estimar a gordura corporal em crianças e adolescentes. Ed. CGB Artes Gráficas. Montes Claros, 2007.

Malina RM, Bouchard C, Bar-Or O. Growth, Maturation, and Physical Activity. Champaign, IL: Human Kinetics; 2009.

Ozmun JC, Gallahue DL. Motor development. Adapted Physical Education and Sport. 6ª ed. 2016.

Tomkinson GR, Olds TS. Secular changes in aerobic fitness test performance of Australasian children and adolescents. Med Sport Sci. 2007;50:168-82. PMID: 17387257; https://doi.org/10.1159/000101361.

Ferrari GL, Bracco MM, Matsudo VK, Fisberg M. Cardiorespiratory fitness and nutritional status of schoolchildren: 30-year evolution. J Pediatr (Rio J). 2013;89(4):366-73. PMID: 23791022; https://doi.org/10.1016/j.jped.2012.12.006.

Silva DA, Tremblay M, Pelegrini A, et al. Association Between Aerobic Fitness and High Blood Pressure in Adolescents in Brazil: Evidence for Criterion-Referenced Cut-Points. Pediatr Exerc Sci. 2016;28(2):312-20. PMID: 26731016; https://doi.org/10.1123/pes.2015-0172.

Downloads

Publicado

2023-10-05

Como Citar

1.
Gonçalves EC de A, Nardo Júnior N, Ribas MC de S, Silva DAS. Which anthropometric equation to predict body fat percentage is more strongly associated with maximum oxygen uptake in adolescents? A cross-sectional study. Sao Paulo Med J [Internet]. 5º de outubro de 2023 [citado 21º de novembro de 2024];141(6):1-7. Disponível em: https://periodicosapm.emnuvens.com.br/spmj/article/view/358

Edição

Seção

Artigo Original