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Anthropometric trajectory in the course of life and occurrence of sarcopenia in men and women: results from the ELSA-Brasil cohort

Published online by Cambridge University Press:  04 November 2022

Clarice Alves Santos*
Affiliation:
Department of Biological Sciences, State University of the Southwest of Bahia, Jequié, BA 45208-091, Brazil
Helena Fraga-Maia
Affiliation:
State University of Bahia, Salvador, BA, Brazil
Francisco José Gondim Pitanga
Affiliation:
Department of Physical Education, Federal University of Bahia, Salvador, BA, Brazil
Maria da Conceição Chagas Almeida
Affiliation:
Oswaldo Cruz Foundation, Instituto Gonçalo Moniz, Salvador, BA, Brazil
Maria de Jesus Mendes Fonseca
Affiliation:
National School of Public Health – Fiocruz, Rio de Janeiro, Brazil
Estela Mota Leão Aquino
Affiliation:
Institute for Collective Health, Federal University of Bahia, Salvador, BA, Brazil
Letícia de Oliveira Cardoso
Affiliation:
National School of Public Health – Fiocruz, Rio de Janeiro, Brazil
Sandhi Maria Barreto
Affiliation:
Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
Bruce Duncan
Affiliation:
Federal University of Minas Gerais, Belo Horizonte, MG, Brazil
Maria Inês Schmidt
Affiliation:
Faculty of Medicine, Federal University of Rio Grande do Sul, Porto Alegre, RS, Brazil
Sheila Maria Alvim Matos
Affiliation:
Institute for Collective Health, Federal University of Bahia, Salvador, BA, Brazil
*
*Corresponding author: Dr C. A. Santos, email casantos@uesb.edu.br

Abstract

This study aimed to identify patterns of anthropometric trajectories throughout life and to analyse their association with the occurrence of sarcopenia in people from the Longitudinal Study of Adult Health (ELSA-Brasil). It is a cross-sectional study involving 9670 public servants, aged 38–79 years, who answered the call for new data collection and exams, conducted approximately 4 years after the study baseline (2012–2014). Data sequence analysis was used to identify patterns of anthropometric trajectory. A theoretical model was elaborated based on the directed acyclic graph (DAG) to select the variables of minimum adjustment in the analysis of the causal effect between trajectory and sarcopenia. Poisson regression with robust variance was adopted for data analysis. The patterns of change in the anthropometric trajectory were classified in stable weight (T1); change to normal weight (T2); change to excess weight (T3); weight fluctuation (T4) and change to low weight (T5). The prevalence of sarcopenia in men and women who changed the anthropometric path for the low weight was twice as large when compared to participants with a stable weight trajectory. A protective effect of the excess weight trajectory was observed for the occurrence of sarcopenia in them. The results pointed to the need for health policies that encourage the proper management of body components in order to prevent and control obesity, as well as to preserve the quantity and quality of skeletal muscle mass throughout life, especially in older adults.

Type
Research Article
Copyright
© The Author(s), 2022. Published by Cambridge University Press on behalf of The Nutrition Society

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References

Cruz-Jentoft, AJ, Bahat, G, Bauer, J, et al. (2019) Writing group for the European working group on sarcopenia in older people 2 (EWGSOP2), and the extended group for EWGSOP2. Sarcopenia: revised European consensus on definition and diagnosis. Age Ageing 48, 1631.CrossRefGoogle Scholar
Shafiee, G, Keshtkar, A, Soltani, A, et al. (2017) Prevalence of sarcopenia in the world: a systematic review and meta- analysis of general population studies. J Diabetes Metab Disord 16, 110.CrossRefGoogle ScholarPubMed
Sayer, AA, Syddall, HE, Gilbody, HJ, et al. (2004) Does sarcopenia originate in early life? Findings from the Hertfordshire cohort study. J Gerontol A Biol Sci Med Sci 59, M930M934.CrossRefGoogle ScholarPubMed
Sayer, AA, Syddall, HE, Martin, H, et al. (2008) The developmental origins of sarcopenia. J Nutr Health Aging 12, 427432.CrossRefGoogle ScholarPubMed
Bunout, D, Maza, MP, Barrera, G, et al. (2011) Association between sarcopenia and mortality in healthy older people. Australas J Ageing 30, 8992.CrossRefGoogle ScholarPubMed
Bone, AE, Hepgul, N, Kon, S, et al. (2017) Sarcopenia and frailty in chronic respiratory disease. Chron Respir Dis 14, 8599.CrossRefGoogle ScholarPubMed
Lima, RM, Bezerra, LMA, Rabelo, HT, et al. (2009) Fat-free mass, strength, and sarcopenia are related to bone mineral density in older women. J Clin Densiom 12, 3541.CrossRefGoogle ScholarPubMed
Pierine, DT, Nicola, M & Oliveira, EP (2009) Sarcopenia: metabolic changes and consequences for aging. R Bras Ci Mov 17, 96103.Google Scholar
Sayer, AA, Syddall, HE, Martin, HJ, et al. (2006) Falls, sarcopenia, and growth in early life: findings from the Hertfordshire cohort study. Am J Epidemiol 164, 665671.CrossRefGoogle ScholarPubMed
Tanimoto, Y, Watanabe, M, Sun, W, et al. (2012) Association between sarcopenia and higher-level functional capacity in daily living in community-dwelling elderly subjects in Japan. Arch Gerontol Geriatr 55, e9e13.CrossRefGoogle ScholarPubMed
Janssen, I, Shepard, DS, Katzmarzyk, PT, et al. (2004) The healthcare costs of sarcopenia in the United States. J Am Geriatr Soc 52, 8085.CrossRefGoogle ScholarPubMed
Anker, SD, Morley, JE & Von Haehling, S (2016) Welcome to the ICD-10 code for sarcopenia. J Cachexia Sarcopenia Muscle 7, 512514.CrossRefGoogle Scholar
Cooper, R, Hardy, R, Bann, D, et al. (2014) Body mass index from age 15 years onwards and muscle mass, strength, and quality in early old age: findings from the MRC national survey of health and development. J Gerontol A Biol Sci Med Sci 69, 12531259.CrossRefGoogle ScholarPubMed
Murphy, RA, Ip, EH, Zhang, Q, et al. (2014) Transition to sarcopenia and determinants of transitions in older adults: a population-based study. J Gerontol A Biol Sci Med Sci 69, 751755.CrossRefGoogle ScholarPubMed
Shimazu, T, Kuriyam, S, Ohmori-Matsuda, K, et al. (2009) Increase in body mass index category since age 20 years and all-cause mortality: a prospective cohort study (the Ohsaki study). Int J Obes 33, 490496.CrossRefGoogle ScholarPubMed
Brown, LD (2014) Endocrine regulation of fetal skeletal muscle growth: impact on future metabolic health. J Endocrinol 221, 1329.CrossRefGoogle ScholarPubMed
Sayer, AA & Cooper, C (2005) Fetal programming of body composition and musculoskeletal development. Early Hum Dev 81, 735744.CrossRefGoogle ScholarPubMed
Wang, M, Yi, Y, Roebothan, B, et al. (2016) Body mass index trajectories among middle-aged and elderly Canadians and associated health outcomes. J Environ Public Health 2016, 19.CrossRefGoogle ScholarPubMed
Dodds, R, Macdonald-Wallis, C, Kapasi, T, et al. (2012) Grip strength at 4 years in relation to birth weight. J Dev Orig Health Dis 3, 111115.CrossRefGoogle ScholarPubMed
Ylihärsilä, H, Kajantie, E, Osmond, C, et al. (2007) Birth size, adult body composition and muscle strength in later life. Int J Obes 31, 13921399.CrossRefGoogle ScholarPubMed
Kensara, OA, Wootton, SA, Phillips, DI, et al. (2005) Fetal programming of body composition: relation between birth weight and body composition measured with dual-energy X-ray absorptiometry and anthropometric methods in older Englishmen. Am J Clin Nutr 82, 980987.CrossRefGoogle ScholarPubMed
Kuzawa, CW, Hallal, PC, Adair, L, et al. (2012) Birth weight, postnatal weight gain, and adult body composition in five low and middle income countries. Am J Hum Biol 24, 513.CrossRefGoogle ScholarPubMed
Victora, CG, Sibbritt, D, Horta, BL, et al. (2007) Weight gain in childhood and body composition at 18 years of age in Brazilian males. Acta Paediatr 96, 296300.CrossRefGoogle ScholarPubMed
Yang, Z & Huffman, SL (2013) Nutrition in pregnancy and early childhood and associations with obesity in developing countries. Matern Child Nutr 9, Suppl. 1, 105119.CrossRefGoogle ScholarPubMed
Koster, A, Ding, J, Stenholm, S, et al. (2011) Does the amount of fat mass predict age-related loss of lean mass, muscle strength, and muscle quality in older adults? J Gerontol A Biol Sci Med Sci 66, 888895.CrossRefGoogle ScholarPubMed
Cui, Z, Truesdale, KP, Bradshaw, PT, et al. (2015) Three-year weight change and cardiometabolic risk factors in obese and normal weight adults who are metabolically healthy: the atherosclerosis risk in communities study. Int J Obes 39, 12031208.CrossRefGoogle ScholarPubMed
Juhola, J, Magnussen, CG, Viikari, JS, et al. (2011) Tracking of serum lipid levels, blood pressure, and body mass index from childhood to adulthood: the cardiovascular risk in young Finns study. J Pediatr 159, 584590.CrossRefGoogle ScholarPubMed
Berentzen, TL, Jakobsen, MU, Halkjaer, J, et al. (2010) Changes in waist circumference and mortality in middle-aged men and women. PLOS ONE 5, 18.CrossRefGoogle ScholarPubMed
Soenen, S & Chapman, IM (2013) Body weight, anorexia, and undernutrition in older people. J Am Med Dir Assoc 14, 642648.CrossRefGoogle ScholarPubMed
Zajacova, A & Ailshire, J (2014) Body mass trajectories and mortality among older adults: a joint growth mixture-discrete-time survival analysis. Gerontologist 54, 221231.CrossRefGoogle ScholarPubMed
Bosomworth, NJ (2012) The downside of weight loss: realistic intervention in body-weight trajectory. Can Fam Physician 58, 517523.Google ScholarPubMed
Fonseca, FL, Brandão, AA, Pozzan, R, et al. (2010) Overweight and cardiovascular risc among young adults followed-up for 17 yeard: the Rio de Janeiro study, Brazil. Arq Bras Cardiol 94, 193201.Google Scholar
Oliveira, RMS, Franceschini, SCC, Rosado, GP, et al. (2009) Influence of prior nutritional status on the development of the metabolic syndrome in adults. Arq Bras Cardiol 92, 107112.Google ScholarPubMed
Aquino, EM, Barreto, SM, Bensenor, IM, et al. (2012) Brazilian longitudinal study of adult health (ELSA-Brasil): objectives and design. Am J Epidemiol 175, 315324.CrossRefGoogle ScholarPubMed
Aquino, EML, Vasconcelos-Silva, PR, Coeli, CM, et al. (2013) Ethical issues in longitudinal studies: the case of ELSA-Brasil. Rev Saúde Pública 47, Suppl. 2, 1926.CrossRefGoogle ScholarPubMed
Chor, D, Alves, MGM, Giatti, L, et al. (2013) Questionnaire development in ELSA-Brasil: challenges of a multidimensional instrument. Rev Saúde Pública 47, Suppl. 2, 2736.CrossRefGoogle ScholarPubMed
Schmidt, MI, Griep, RH, Passos, VM, et al. (2013) Strategies and development of quality assurance and control in the ELSA-Brasil. Rev Saúde Pública 47, Suppl. 2, 105112.CrossRefGoogle ScholarPubMed
Hodge, JM, Shah, R, McCullough, ML, et al. (2020) Validation of self-reported height and weight in a large, nationwide cohort of U.S. adults. PLOS ONE 15, e0231229.CrossRefGoogle Scholar
Fielding, RA, Vellas, B, Evans, WJ, et al. (2011) Sarcopenia: an undiagnosed condition in older adults. Current consensus definition: prevalence, etiology, and consequences. International working group on sarcopenia. J Am Med Dir Assoc 12, 249256.CrossRefGoogle ScholarPubMed
Baumgartner, RN, Koehler, KM, Gallagher, D, et al. (1998) Epidemiology of sarcopenia among the elderly in New Mexico. Am J Epidemiol 147, 755763.CrossRefGoogle ScholarPubMed
Janssen, I, Baumgartner, RN, Ross, R, et al. (2004) Skeletal muscle cutpoints associated with elevated physical disability risk in older men and women. Am J Epidemiol 159, 413421.CrossRefGoogle ScholarPubMed
Roberts, HC, Denison, HJ, Martin, HJ, et al. (2011) A review of the measurement of grip strength in clinical and epidemiological studies: towards a standardized approach. Age Ageing 40, 423429.CrossRefGoogle Scholar
Matsudo, S, Araújo, T, Matsudo, V, et al. (2001) International physical activity questionnaire (IPAQ): study of validity and reliability in Brazil. l. Rev Bras Ati Fís Saúde 6, 518.Google Scholar
Haskell, WL, Lee, IM, Pate, RR, et al. (2007) Physical activity and public health: updated recommendation for adults from the American College of Sports Medicine and the American Heart Association. Med Sci Sports Exerc 39, 14231434.CrossRefGoogle Scholar
World Health Organization (2010) Global Recommendations on Physical Activity for Health. Geneva: World Health Organization.Google Scholar
Duncan, BB, Schmidt, MI & Giugliani, ERJ (2004) Ambulatory Medicine: Primary Health Care. Porto Alegre: Artmed.Google Scholar
Di Milia, L, Vandelanotte, C & Duncan, MJ (2013) The association between short sleep and obesity after controlling for demographic, lifestyle, work and health related factors. Sleep Med 14, 319323.CrossRefGoogle ScholarPubMed
Foraita, R, Spallek, J & Zeeb, H (2014) Directed acyclic graphs. In Handbook of Epidemiology, pp.1481–1518 [Ahrens, W and Pigeot, I, editors],   New York, NY: Springer.Google Scholar
Evans, D, Chaix, B, Lobbedez, T, et al. (2012) Combining directed acyclic graphs and the change-in-estimate procedure as a novel approach to adjustment-variable selection in epidemiology. BMC Med Res Methodol 12, 11061114.CrossRefGoogle ScholarPubMed
Abbott, A & Tsay, A (2000) Sequence analysis and optimal matching methods in sociology: review and prospect. Sociol Methods Res 29, 333.CrossRefGoogle Scholar
Brzinsky-Fay, C & Kohler, U (2010) New developments in sequence analysis. Sociol Methods Res 38, 359364.CrossRefGoogle Scholar
Lera, L, Albala, C, Sánchez, H, et al. (2017) Prevalence of sarcopenia in community-dwelling Chilean elders according to an adapted version of the European working group on sarcopenia in older people (EWGSOP) criteria. J Frailty Aging 6, 1217.Google Scholar
Patel, HP, Syddall, HE, Jameson, K, et al. (2013) Prevalence of sarcopenia in community-dwelling older people in the UK using the European working group on sarcopenia in older people (EWGSOP) definition: findings from the Hertfordshire cohort study (HCS). Age Aging 42, 378384.CrossRefGoogle Scholar
Pelegrini, A, Mazo, GZ, Pinto, AA, et al. (2018) Sarcopenia: prevalence and associated factors among elderly from a Brazilian capital. Fisioter Movimento 31, 18.Google Scholar
Byrne, NM, Weinsier, RL, Hunter, GR, et al. (2003) Influence of distribution of lean body mass on resting metabolic rate after weight loss and weight regain: comparison of responses in white and black women. Am J Clin Nutr 77, 13681373.CrossRefGoogle ScholarPubMed
Argilés, JM, Campos, N, Lopez-Pedrosa, JM, et al. (2016) Skeletal muscle regulates metabolism via interorgan crosstalk: roles in health and disease. J Am Med Dir Assoc 17, 789796.CrossRefGoogle ScholarPubMed
Buford, TW, Anton, SD, Judge, AR, et al. (2010) Models of accelerated sarcopenia: critical pieces for solving the puzzle of age-related muscle atrophy. Aging Res Rev 9, 369383.CrossRefGoogle ScholarPubMed
Degens, H, Gayan-Ramirez, G & van Hees, HW (2015) Smoking-induced skeletal muscle dysfunction: from evidence to mechanisms. Am J Respir Crit Care Med 191, 620625.CrossRefGoogle ScholarPubMed
Maltais, ML, Desroches, J & Dionne, IJ (2009) Changes in muscle mass and strength after menopause. J Musculoskelet Neuronal Interact 9, 186197.Google ScholarPubMed
Shad, BJ, Thompson, JL & Breen, L (2016) Does the muscle protein synthetic response to exercise and amino acid-based nutrition diminish with advancing age? A systematic review. Am J Physiol Endocrinol Metab 311, E803E817.CrossRefGoogle ScholarPubMed
Tyrovolas, S, Koyanagi, A, Olaya, B, et al. (2016) Factors associated with skeletal muscle mass, sarcopenia, and sarcopenic obesity in older adults: a multi-continent study. J Cachexia Sarcopenia Muscle 7, 312321.CrossRefGoogle ScholarPubMed
Yarmolinsky, J, Mueller, N, Duncan, B, et al. (2016) Sex-specific associations of low birth weight with adult-onset diabetes and measures of glucose homeostasis: Brazilian longitudinal study of adult health. Sci Rep 6, 37032.CrossRefGoogle ScholarPubMed
Cauley, JA (2015) An overview of sarcopenic obesity. J Clin Densitom 18, 499505.CrossRefGoogle ScholarPubMed
Biolo, G, Cederholm, T & Muscaritoli, M (2014) Muscle contractile and metabolic dysfunction is a common feature of sarcopenia of aging and chronic diseases: from sarcopenic obesity to cachexia. Clin Nutr 33, 737748.CrossRefGoogle ScholarPubMed
Teixeira, VON, Filippin, LI & Xavier, RM (2012) Mechanisms of muscle wasting in sarcopenia. Rev Bras Reumatol 52, 247259.Google ScholarPubMed
Cetin, DC & Nasr, G (2014) Obesity in the elderly: more complicated than you think. Cleve Clin J Med 81, 5161.CrossRefGoogle ScholarPubMed
Cho, IJ, Chang, HJ, Sung, JM, et al. (2017) Associations of changes in body mass index with all-cause and cardiovascular mortality in healthy middle-aged adults. PLOS ONE 12, e0189180.CrossRefGoogle ScholarPubMed
Flegal, KM, Graubard, BI, Williamson, DF, et al. (2005) Excess deaths associated with underweight, overweight, and obesity. JAMA 293, 18611867.CrossRefGoogle ScholarPubMed
McAuley, PA & Blair, SN (2011) Obesity paradoxes. J Sports Sci 29, 773782.CrossRefGoogle ScholarPubMed
Wannamethee, SG & Atkins, JL (2015) Muscle loss and obesity: the health implications of sarcopenia and sarcopenic obesity. Proc Nutr Soc 74, 405412.CrossRefGoogle ScholarPubMed
Chung, JY, Kang, HT, Lee, DC, et al. (2013) Body composition and its association with cardiometabolic risk factors in the elderly: a focus on sarcopenic obesity. Arch Gerontol Geriatr 56, 270278.CrossRefGoogle ScholarPubMed
Kohara, K (2014) Sarcopenic obesity in aging population: current status and future directions for research. Endocrine 45, 1525.CrossRefGoogle ScholarPubMed
Stephen, WC & Janssen, I (2009) Sarcopenic-obesity and cardiovascular disease risk in the elderly. J Nutr Health Aging 13, 460466.CrossRefGoogle ScholarPubMed
Baumgartner, RN (2000) Body composition in healthy aging. Ann N Y Acad Sci 904, 437448.CrossRefGoogle ScholarPubMed
Batsis, JA, Petersen, CL, Crow, RS, et al. (2020) Weight change and risk of the foundation of National Institute of Health sarcopenia-defined low lean mass: data from the National Health and Nutrition examination surveys 1999–2004. Clin Nutr 39, 24632470.CrossRefGoogle ScholarPubMed
Nilsen, TS, Kutschke, J, Brandt, I, et al. (2017) Validity of self-reported birth weight: results from a Norwegian twin sample. Twin Res Hum Genet 20, 406413.CrossRefGoogle ScholarPubMed
World Health Organization (1995) Physical status: the use and interpretation of anthropometry. Report of a WHO expert committee. World Health Organ Tech Rep Ser 854, 1452.Google Scholar