BACKGROUND: Fat mass (FM) and fat-free body mass (FFB) are important parameters for assessing nutritional status, since they are associated with higher prevalence of excess body fat and malnutrition worldwide. AIM: To develop prediction equations for fat and fat-free body mass in adolescents using body circumferences. SUBJECTS AND METHODS: This cross-sectional study included 218 adolescents (10-16 years) with normal weight as defined by body mass index. FM(Pred) and FFB(Pred) were estimated using stepwise multiple linear regression, considering age and body circumferences. Response variables, FM(BIA) and FFB(BIA) were estimated using bioelectric impedance analysis (BIA). The accuracy of the prediction equations was evaluated using the coefficient of determination (R(2)) and Akaike's Information Criterion (AIC). RESULTS: The best prediction equations for males were FM(Pred) = -7.114 - 0.592(age) - 0.958(wrist)+0.191(hip)+0.295(abdomen); R(2) = 0.552; AIC = 416.04 and FFB(Pred) = - 52.180+1.913(age)+1.954(wrist)+1.635(forearm); R(2) = 0.869; AIC = 578.24. For females, the best equations were FM(Pred) = -17.580 - 0.678(wrist)+0.221(abdomen)+0.241(hip)+0.202(proximal thigh) - 0.228(calf); R(2) = 0.838; AIC = 415.36 and FFB(Pred) = -31.066+0.90(age)+1.090(wrist) - 0.139(abdomen)+0.326(hip)+0.632(calf); R(2) = 0.878; AIC = 512.48. CONCLUSION: The equations developed to estimate fat body mass in females and fat-free body mass in both genders had high adjusted coefficients of determination and are therefore preferable to those derived using BIA.
BACKGROUND:Fat mass (FM) and fat-free body mass (FFB) are important parameters for assessing nutritional status, since they are associated with higher prevalence of excess body fat and malnutrition worldwide. AIM: To develop prediction equations for fat and fat-free body mass in adolescents using body circumferences. SUBJECTS AND METHODS: This cross-sectional study included 218 adolescents (10-16 years) with normal weight as defined by body mass index. FM(Pred) and FFB(Pred) were estimated using stepwise multiple linear regression, considering age and body circumferences. Response variables, FM(BIA) and FFB(BIA) were estimated using bioelectric impedance analysis (BIA). The accuracy of the prediction equations was evaluated using the coefficient of determination (R(2)) and Akaike's Information Criterion (AIC). RESULTS: The best prediction equations for males were FM(Pred) = -7.114 - 0.592(age) - 0.958(wrist)+0.191(hip)+0.295(abdomen); R(2) = 0.552; AIC = 416.04 and FFB(Pred) = - 52.180+1.913(age)+1.954(wrist)+1.635(forearm); R(2) = 0.869; AIC = 578.24. For females, the best equations were FM(Pred) = -17.580 - 0.678(wrist)+0.221(abdomen)+0.241(hip)+0.202(proximal thigh) - 0.228(calf); R(2) = 0.838; AIC = 415.36 and FFB(Pred) = -31.066+0.90(age)+1.090(wrist) - 0.139(abdomen)+0.326(hip)+0.632(calf); R(2) = 0.878; AIC = 512.48. CONCLUSION: The equations developed to estimate fat body mass in females and fat-free body mass in both genders had high adjusted coefficients of determination and are therefore preferable to those derived using BIA.
Authors: Rossana Gomez-Campos; Thiago Santi-Maria; Miguel Arruda; Thiago Maldonado; Altamiro Albernaz; Marco Schiavo; Marco Cossio-Bolaños Journal: Front Psychol Date: 2019-03-29
Authors: José Ronaldo Ribeiro da Costa; Roberto Fernandes da Costa; Ciro Alexandre Mercês Goncalves; Michelle Vasconcelos de Oliveira Borges; Paulo Francisco De Almeida-Neto; Gilmara Gomes De Assis; Breno Guilherme De Araujo Tinoco Cabral; Paulo Moreira Silva Dantas Journal: Front Nutr Date: 2022-08-25