Multicompartment body composition analysis in older adults: a cross-sectional study

Ana Claudia Rossini-Venturini; Lucas Veras; Pedro Pugliesi Abdalla; André Pereira Dos Santos; Márcio Fernando Tasinafo-Junior; Leonardo Santos Lopes da Silva; Thiago Cândido Alves; Eduardo Ferriolli; Vicente Romo-Perez; Jose Luis Garcia-Soidan; Jorge Mota; Dalmo Roberto Lopes Machado

doi:10.1186/s12877-023-03752-1

Multicompartment body composition analysis in older adults: a cross-sectional study

BMC Geriatr. 2023 Feb 9;23(1):87. doi: 10.1186/s12877-023-03752-1.

Authors

Ana Claudia Rossini-Venturini^{1

2}, Lucas Veras^{3

4}, Pedro Pugliesi Abdalla^{5

6}, André Pereira Dos Santos^{5

6

7}, Márcio Fernando Tasinafo-Junior^{6

7}, Leonardo Santos Lopes da Silva^{6

7}, Thiago Cândido Alves⁶, Eduardo Ferriolli^{8

9}, Vicente Romo-Perez¹⁰, Jose Luis Garcia-Soidan¹⁰, Jorge Mota^{3

4}, Dalmo Roberto Lopes Machado^{5

6

3

7

11}

Affiliations

¹ College of Nursing at Ribeirão Preto, University of São Paulo, Avenue of Bandeirantes nº 3900, University Campus - Monte Alegre, Ribeirão Preto-SP, Brazil. anacrv016@gmail.com.
² Study and Research Group in Anthropometry, Training, and Sport (GEPEATE), São Paulo, Brazil. anacrv016@gmail.com.
³ The Research Centre in Physical Activity, Health, and Leisure (CIAFEL), University of Porto, Porto, Portugal.
⁴ Laboratory for Integrative and Translational Research in Population Health (ITR), University of Porto, Porto, Portugal.
⁵ College of Nursing at Ribeirão Preto, University of São Paulo, Avenue of Bandeirantes nº 3900, University Campus - Monte Alegre, Ribeirão Preto-SP, Brazil.
⁶ Study and Research Group in Anthropometry, Training, and Sport (GEPEATE), São Paulo, Brazil.
⁷ School of Physical Education and Sport of Ribeirão Preto, University of São Paulo, Ribeirão Preto, Brazil.
⁸ Ribeirão Preto Medical School, University of São Paulo, Ribeirão Preto, Brazil.
⁹ Laboratório de Investigação Médica em Envelhecimento (LIM-66), Serviço de Geriatria, Hospital das Clínicas HCFMUSP, Faculdade de Medicina, Universidade de São Paulo (USP), São Paulo, Brazil.
¹⁰ Faculty of Education and Sport Sciences, University of Vigo, Vigo, Spain.
¹¹ ESEC - Universidade do Algarve. , Campus da Penha, Faro, Portugal.

Abstract

Background: During aging, changes occur in the proportions of muscle, fat, and bone. Body composition (BC) alterations have a great impact on health, quality of life, and functional capacity. Several equations to predict BC using anthropometric measurements have been developed from a bi-compartmental (2-C) approach that determines only fat mass (FM) and fat-free mass (FFM). However, these models have several limitations, when considering constant density, progressive bone demineralization, and changes in the hydration of the FFM, as typical changes during senescence. Thus, the main purpose of this study was to propose and validate a new multi-compartmental anthropometric model to predict fat, bone, and musculature components in older adults of both sexes.

Methods: This cross-sectional study included 100 older adults of both sexes. To determine the dependent variables (fat mass [FM], bone mineral content [BMC], and appendicular lean soft tissue [ALST]) whole total and regional dual-energy X-ray absorptiometry (DXA) body scans were performed. Twenty-nine anthropometric measures and sex were appointed as independent variables. Models were developed through multivariate linear regression. Finally, the predicted residual error sum of squares (PRESS) statistic was used to measure the effectiveness of the predicted value for each dependent variable.

Results: An equation was developed to simultaneously predict FM, BMC, and ALST from only four variables: weight, half-arm span (HAS), triceps skinfold (TriSK), and sex. This model showed high coefficients of determination and low estimation errors (FM: R²_adj: 0.83 and SEE: 3.16; BMC: R²_adj: 0.61 and SEE: 0.30; ALST: R²_adj: 0.85 and SEE: 1.65).

Conclusion: The equations provide a reliable, practical, and low-cost instrument to monitor changes in body components during the aging process. The internal cross-validation method PRESS presented sufficient reliability in the model as an inexpensive alternative for clinical field use.

Keywords: ALST; Aging; Bone mineral content; DXA; Equation; Fat mass.

Publication types

Research Support, Non-U.S. Gov't

MeSH terms

Absorptiometry, Photon
Aged
Anthropometry / methods
Body Composition* / physiology
Cross-Sectional Studies
Female
Humans
Male
Quality of Life*
Reproducibility of Results

Abstract

Publication types

MeSH terms

Grants and funding