Effect of early determinants on adolescent fat-free mass: RPS cohort of São Luís - MA.

Autor:	Lima RJCP; Instituto Federal de Educação. Ciência e Tecnologia do Maranhão. Departamento de Ensino. Açailândia, MA, Brasil., Batista RFL; Universidade Federal do Maranhão. Centro de Ciências Biológicas e da Saúde. Departamento de Saúde Pública. São Luís, MA, Brasil., Ribeiro CCC; Universidade Federal do Maranhão. Centro de Ciências Biológicas e da Saúde. Departamento de Odontologia II. São Luís, MA, Brasil., Simões VMF; Universidade Federal do Maranhão. Centro de Ciências Biológicas e da Saúde. Departamento de Saúde Pública. São Luís, MA, Brasil., Lima Neto PM; Universidade Federal do Maranhão. Centro de Ciências Sociais, Saúde e Tecnologia. Imperatriz, MA, Brasil., Bettiol H; Universidade de São Paulo. Faculdade de Medicina de Ribeirão Preto. Departamento de Puericultura e Pediatria. Ribeirão Preto, SP, Brasil., Silva AAMD; Universidade Federal do Maranhão. Centro de Ciências Biológicas e da Saúde. Departamento de Saúde Pública. São Luís, MA, Brasil.
Jazyk:	angličtina
Zdroj:	Revista de saude publica [Rev Saude Publica] 2020 Nov 20; Vol. 54, pp. 113. Date of Electronic Publication: 2020 Nov 20 (Print Publication: 2020).
DOI:	10.11606/s1518-8787.2020054002229
Abstrakt:	Objective: To analyze the effects of early determinants on adolescent fat-free mass. Methods: A cohort study with 579 adolescents evaluated at birth and adolescence in a birth cohort in São Luís, Maranhão. In the proposed model, estimated by structural equation modeling, socioeconomic status (SES) at birth, maternal age, pregestational body mass index (BMI), gestational smoking, gestational weight gain, type of delivery, gestational age, sex of the newborn, length and weight at birth, adolescent socioeconomic status, "neither study/nor work" generation, adolescent physical activity level and alcohol consumption were tested as early determinants of adolescent fat-free mass (FFM). Results: A higher pregestational BMI resulted in higher FFM in adolescence (Standardized Coefficient, SC = 0.152; p < 0.001). Being female implied a lower FFM in adolescence (SC = -0.633; p < 0.001). The negative effect of gender on FFM was direct (SC = -0.523; p < 0.001), but there was an indirect negative effect via physical activity level (SC = -0.085; p < 0.001). Women were less active (p < 0.001). An increase of 0.5 kg (1 Standard Deviation, SD) in birth weight led to a gain of 0.25 kg/m2 (0.106 SD) in adolescent FFM index (p = 0.034). Not studying or working had a negative effect on the adolescent's FFM (SC = -0.106; p = 0.015). Elevation of 1 SD in the adolescent's physical activity level represented an increase of 0.5 kg/m2 (0.207 SD) in FFM index (p < 0.001). Conclusions: The early determinants with the greatest effects on adolescent FFM are gender, adolescent physical activity level, pregestational BMI, birth weight and belonging to the "neither-nor" generation.
Databáze:	MEDLINE
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