1. Effect of early determinants on adolescent fat-free mass: RPS cohort of São Luís – MA
- Author
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Raina Jansen Cutrim Propp Lima, Rosângela Fernandes Lucena Batista, Cecília Claudia Costa Ribeiro, Vanda Maria Ferreira Simões, Pedro Martins Lima Neto, Heloisa Bettiol, and Antônio Augusto Moura da Silva
- Subjects
Male ,Adolescent ,Social Determinants of Health ,Birth weight ,Subcutaneous Fat ,Adolescent Health ,Gestational Age ,Muscle Development ,Body Mass Index ,Cohort Studies ,Fetal Development ,03 medical and health sciences ,Biological Factors ,Medicine ,Birth Weight ,Humans ,Adiposity ,030505 public health ,business.industry ,Public Health, Environmental and Occupational Health ,Infant, Newborn ,Gestational age ,Adolescent Development ,Physical activity level ,Socioeconomic Factors ,Latent Class Analysis ,Cohort ,Body Composition ,Gestation ,Female ,Original Article ,Public aspects of medicine ,RA1-1270 ,medicine.symptom ,0305 other medical science ,business ,Body mass index ,Weight gain ,Brazil ,Demography ,Cohort study - Abstract
OBJECTIVE: To analyze the effects of early determinants on adolescent fat-free mass. METHODS: A c ohort s tudy w ith 5 79 a dolescents e valuated a t b irth a nd a dolescence i n 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.
- Published
- 2020