ABSTRACT
OBJECTIVES: To compare growth velocity of two African child cohorts and examine the relationship between postnatal growth velocity in infancy/early childhood and the risk of overweight/stunting in early adolescence. METHODS: The study used data from two child cohorts from urban (Birth to Twenty Cohort, South Africa) and rural (Lungwena Child Survival Study, Malawi) African settings. Mixed effect modelling was used to derive growth and peak growth velocities. T-tests were used to compare growth parameters and velocities between the two cohorts. Linear and logistic regression models were used to determine the relationship between growth velocity and early adolescent (ages 9-11 years) body mass index and odds of being overweight. RESULTS: Children in the BH cohort were significantly taller and heavier than those in the Lungwena cohort, and exhibited faster weight and height growth velocity especially in the first year of life (P < 0.05). No significant association was shown between baseline weight (αw ) and overweight in early adolescence (OR = 1.25, CI = 0.67, 2.34). The weight growth velocity parameter ßw was highly associated with odds of being overweight. Association between overweight in adolescence and weight velocity was stronger in infancy than in early childhood (OR at 3 months = 4.80, CI = 2.49, 9.26; OR at 5 years = 2.39, CI = 1.65, 3.47). CONCLUSION: High weight and height growth velocity in infancy, independent of size at birth, is highly associated with overweight in early adolescence. However, the long term effects of rapid growth in infancy may be dependent on a particular population's socio-economic status and level of urbanization.
Subject(s)
Body Height , Body Weight , Overweight/epidemiology , Adolescent , Body Mass Index , Child , Child, Preschool , Cohort Studies , Female , Humans , Infant , Infant, Newborn , Male , Overweight/etiology , Pregnancy , Regression Analysis , Risk , Rural Population , Social Class , South Africa/epidemiology , Urban PopulationABSTRACT
Comparison of changes over time of a continuous response variable between treatment groups is often of main interest in clinical trials. When the distributional properties of the continuous response variable are not regular enough, or when the response is discrete, nonparametric techniques have been used. The relative performances of selected repeated measures nonparametric two-sample tests proposed by Wei and Lachin, Koziol, Wei and Johnson, and the adapted Wilcoxon Rank-Sum test are compared through simulations based on quality of life data. The Wilcoxon Rank-Sum test is the most powerful and is not significantly affected by the different patterns of missing data.
