Analysis of anthropometric indicators used in the nutritional assessment of active elderly in the city of Macaé, Rio de Janeiro, Brazil

Main Article Content

Laís Vargas Botelho
Ana Eliza Port Lourenço
Luana Silva Monteiro
Renata Borba de Amorim Oliveira

Abstract

Introduction: Body composition changes related to aging alter the capacity of predicting risk through anthropometric parameters. Objective: To discuss methodological aspects of anthropometry in active elderly based on associations between Body Mass Index (BMI) and other nutritional indicators. Methods: Cross-sectional study with active elderly from Macaé, Rio de Janeiro, Brazil (2014/2015). Nutritional status was described according to the BMI (Nutritional Screening Initiative, 1994). Linear regression analysis was performed: the outcome variable was BMI and the dependent ones were circumferences of waist, hip, neck, calf, arm and waist-to-hip ratio (WHR). Results: We assessed 173 people (55.5% female; median 71 years old). Calf and neck circumferences and WHR presented low R2 value. Among women, hip (R2=0.825) and waist circumferences (R2=0.729) individually explained much of the variation in BMI; and among men, waist (R2=0.759) and arm circumferences (R2=0.741) performed better. The cut-off points for waist circumference corresponding to the critical BMI value (27 kg/m2) were 87.9 and 96.8 cm, respectively for women and men. In multiple analysis, the association of waist, hip and arm circumferences with BMI remained significant. Conclusion: Circumferences traditionally used to assess adults had higher linear association with BMI than specific indicators for elderly people. The body composition of active elderly can be more similar to adults’ than that of elderly with other profiles. The waist circumference cut-off points established for adults may not be suitable for elderly populations. We suggest testing the cut-off points obtained by this study on other groups of active elderly.

Downloads

Download data is not yet available.

Article Details

How to Cite
Botelho, L. V., Lourenço, A. E. P., Monteiro, L. S. ., & Oliveira, R. B. de A. (2021). Analysis of anthropometric indicators used in the nutritional assessment of active elderly in the city of Macaé, Rio de Janeiro, Brazil. ABCS Health Sciences, 46, e021220. https://doi.org/10.7322/abcshs.2020072.1525
Section
Original Articles

References

Miranda GMD, Mendes ACG, Silva ALA. O envelhecimento populacional brasileiro: desafios e consequências sociais atuais e futuras. Rev Bras Geriatr Gerontol. 2016;19(3):507-19. https://doi.org/10.1590/1809-98232016019.150140

Brasil. Ministério da Saúde. Portaria nº 2.528, de 19 de Outubro de 2006. Aprova a Política Nacional de Saúde da pessoa Idosa. Available from: http://bvsms.saude.gov.br/bvs/saudelegis/gm/2006/prt2528_19_10_2006.html.

Brasil. Ministério da Saúde. Secretaria de Atenção à Saúde. Departamento de Atenção Básica. Orientações para a coleta e análise de dados antropométricos em serviços de saúde: Norma Técnica do Sistema de Vigilância Alimentar e Nutricional. Available from: http://bvsms.saude.gov.br/bvs/publicacoes/orientacoes_coleta_analise_dados_antropometricos.pdf.

Sampaio LR, Figueiredo VC. Correlação entre o índice de massa corporal e os indicadores antropométricos de distribuição de gordura corporal em adultos e idosos. Rev Nutr. 2005;18(1):53-61. https://doi.org/10.1590/S1415-52732005000100005

Seidell JC, Visscher TLS. Body weight and weight change and their health implications for the elderly. Eur J Clin Nutr. 2000;54(Suppl 3):533-9. https://doi.org/10.1038/sj.ejcn.1601023

Tavares EL, Santos DM, Ferreira AA, Menezes MFG. Avaliação nutricional de idosos: desafios da atualidade. Rev Bras Geriatr Gerontol. 2015;18(3):643-50. https://doi.org/10.1590/1809-9823.2015.14249

Santos DM, Sichieri R. Índice de massa corporal e indicadores antropométricos de adiposidade em idosos. Rev Saude Publica. 2005;39(2):163-8. https://doi.org/10.1590/S0034-89102005000200004

Souza R, Fraga JS, Gottschall CBA, Busnello FM, Rabito EI. Avaliação antropométrica em idosos: estimativas de peso e altura e concordância entre classificações de IMC. Rev Bras Geriat Gerontol. 2013;16(1):81-90. https://doi.org/10.1590/S1809-98232013000100009

World Health Organization (WHO). Expert Committee on Physical Status: the Use and Interpretation of Anthropometry. Physical status: the use and interpretation of anthropometry, report of a WHO Expert Committee. Geneva: World Health Organization, 1995. Available from: https://apps.who.int/iris/handle/10665/37003

World Health Organization (WHO). Obesity: preventing and managing the global epidemic: report of a WHO consultation. Geneva: World Health Organization, 2000. Available from: https://apps.who.int/iris/handle/10665/42330

World Health Organization (WHO). WHO child growth standards: length/height-for-age, weight-for-age, weight-for-length, weight-for-height and body mass index-for-age; methods and development. Geneva: WHO, 2006. Available from: https://www.who.int/publications/i/item/924154693X

Cervi A, Franceschini SCC, Priore SE. Análise crítica do uso do índice de massa corporal para idosos. Rev Nutr. 2005;18(6):765-75. https://doi.org/10.1590/S1415-52732005000600007

The Nutriton Screening Initiative. Incorporating Nutrition Screening and Interventions into Medical Practice. A Monograph for Physicians. Washington: American Academy of Family Physicians. The American Dietetic Association. National Council on Aging, 1994.

Preis SR, Massaro JM, Hoffmann U, D'Agostino RB, Levy D, Robins SJ, et al. Neck circumference as a novel measure of cardiometabolic risk: the Framingham Heart study. J Clin Endocrinol Metab. 2010;95(8):3701-10. https://doi.org/10.1210/jc.2009-1779

Barbosa-Silva TG, Bielemann RM, Gonzalez MC, Menezes AM. Prevalence of sarcopenia among community-dwelling elderly of a medium-sized South American city: results of the COMO VAI? Study. J Cachexia Sarcopenia Muscle. 2016;7:136-43. https://doi.org/10.1002/jcsm.12049

Pagotto V, Santos KF, Malaquias SG, Bachion MM, Silveira EA. Circunferência da panturrilha: validação clínica para avaliação de massa muscular em idosos. Rev Bras Enferm. 2018;71(2):322-8. https://doi.org/10.1590/0034-7167-2017-0121

World Health Organization (WHO). Envelhecimento ativo: uma política de saúde. Brasília: Organização Pan-Americana de Saude, 2005. Available from: https://bvsms.saude.gov.br/bvs/publicacoes/envelhecimento_ativo.pdf

Lauretani F, Russo CR, Bandinelli S, Bartali B, Cavazzini C, Di Iorio A, et al. Age-associated changes in skeletal muscles and their effect on mobility: an operational diagnosis of sarcopenia. J Appl Physiol. 2003;95:1851-60. https://doi.org/10.1152/japplphysiol.00246.2003

Ben-Noum LL, Laor A. Neck circumference as a simple screening measure for identifying overweight and obesity patients. Obes Res. 2001;9(8):470-7. https://doi.org/10.1038/oby.2001.61

Instituto Brasileiro de Geografia e Estatística (IBGE). Pesquisa de Orçamentos Familiares 2008-2009: antropometria e estado nutricional de crianças, adolescentes e adultos no Brasil. Rio de Janeiro: Instituto Brasileiro de Geografia e Estatística, 2010.

Ferreira APS, Szwarcwald CL, Damacena GN. Prevalência e fatores associados da obesidade na população brasileira: estudo com dados aferidos da Pesquisa Nacional de Saúde, 2013. Rev Bras Epidemiol. 2019;22:e190024. https://doi.org/10.1590/1980-549720190024

Barbosa AR, Souza JMP, Lebrãos, ML, Laurenti R, Marucci MFN. Anthropometry of elderly residents in the city of São Paulo, Brazil. Cad Saude Publica. 2005;21(6):1929-38. https://doi.org/10.1590/S0102-311X2005000600043

Menezes T, Marucci M. Antropometria de idosos residentes em instituições geriátricas Fortaleza, CE. Rev Saude Publica. 2005;39(2):169-75. https://doi.org/10.1590/S0034-89102005000200005

Lebrão ML. O projeto SABE em São Paulo: uma visão panorâmica. In: Lebrão ML, Duarte, YAO. SABE: Saúde, Bem-estar e envelhecimento. O Projeto SABE no Município de São Paulo: uma abordagem inicial. Brasília: Organização Pan-Americana de Saúde, 2003; p. 33-43.

Sass A, Marcon SS. Comparação de medidas antropométricas de idosos residentes em área urbana no sul do Brasil, segundo sexo e faixa etária. Rev Bras Geriatr Gerontol. 2015;18(2):361-72. https://doi.org/10.1590/1809-9823.2015.13048

Oliveira CC, Costa ED, Roriz AKC, Ramos LB, Gomes Neto M. Predictors of Metabolic Syndrome in the Elderly: A Review. Inter J Cardiovasc Sci. 2017;30(4);343-53. https://doi.org/10.5935/2359-4802.20170059

Di Angelantonio E, Bhupathiraju SN, Wormser D, Gao P, Kaptoge S, Gonzalez AB, et al. Body-mass index and all-cause mortality: individual-participant-data meta-analysis of 239 prospective studies in four continents. Lancet. 2016;388(10046):776-86. https://doi.org/10.1016/S0140-6736(16)30175-1

Ping Z, Pei X, Xia P, Chen Y, Guo R, Hu C, et al. Anthropometric indices as surrogates for estimating abdominal visceral and subcutaneous adipose tissue: A meta-analysis with 16,129 participants. Diabetes Res Clin Pract. 2018;143:310-9. https://doi.org/10.1016/j.diabres.2018.08.005

Winter JE., Maclnnis RJ, Wattanapenpaiboon N, Nowson CA. BMI and all-cause mortality in older adults: a meta-analysis. Am J Clin Nutr. 2014;99:875-90. https://doi.org/10.3945/ajcn.113.068122

Westerterp KR. Exercise, energy balance and body composition. Eur J Clin Nutr. 2018;72(9):1246-50. https://10.1038/s41430-018-0180-430

Silva ICM, Mielke GI, Bertoldi AD, Arrais PSD, Luiza VL, Mengue SS, et al. Overall and Leisure-Time Physical Activity Among Brazilian Adults: National Survey Based on the Global Physical Activity Questionnaire. J Phys Act Health. 2018;15(3):212-8. https://doi.org/10.1123/jpah.2017-0262