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Equations based on anthropometric measurements for adipose tissue, body fat, or body density prediction in children and adolescents: a scoping review

2022; Springer Science+Business Media; Volume: 27; Issue: 7 Linguagem: Inglês

10.1007/s40519-022-01405-7

1590-1262

Matheus Santos Cerqueira, Paulo R. S. Amorim, Irismar Gonçalves Almeida da Encarnação, Leonardo Mateus Teixeira de Rezende, Paulo Henrique Ribeiro Fernandes Almeida, Analiza M. Silva, Manuel Sillero‐Quintana, Diego Augusto Santos Silva, Fernanda Karina dos Santos, João Carlos Bouzas Marins,

Thermoregulation and physiological responses

Assessing the body composition of children and adolescents is important to monitor their health status. Anthropometric measurements are feasible and less-expensive than other techniques for body composition assessment. This study aimed to systematically map anthropometric equations to predict adipose tissue, body fat, or density in children and adolescents, and to analyze methodological aspects of the development of anthropometric equations using skinfolds. A scoping review was carried out following the PRISMA-ScR criteria. The search was carried out in eight databases. The methodological structure protocol of this scoping review was retrospectively registered in the Open Science Framework ( https://osf.io/35uhc/ ). We included 78 reports and 593 anthropometric equations. The samples consisted of healthy individuals, people with different diseases or disabilities, and athletes from different sports. Dual-energy X-ray absorptiometry (DXA) was the reference method most commonly used in developing equations. Triceps and subscapular skinfolds were the anthropometric measurements most frequently used as predictors in the equations. Age, stage of sexual maturation, and peak height velocity were used as complementary variables in the equations. Our scoping review identified equations proposed for children and adolescents with a great diversity of characteristics. In many of the reports, important methodological aspects were not addressed, a factor that may be associated with equation bias. Evidence obtained from multiple time series analysis such as case studies. (NB: dramatic results in uncontrolled trials might also be regarded as this type of evidence).