Rasmus Wibaek1,2, Dorte Vistisen2, Tsinuel Girma3,4, Bitiya Admassu1,4,5, Mubarek Abera1,4,6, Alemseged Abdissa4,7, Kissi Mudie8, Pernille Kæstel1, Marit E Jørgensen2,9, Jonathan C K Wells10, Kim F Michaelsen1, Henrik Friis1, Gregers S Andersen2. 1. Department of Nutrition, Exercise and Sports, University of Copenhagen, Copenhagen, Denmark. 2. Clinical Epidemiology, Steno Diabetes Center Copenhagen, Gentofte, Denmark. 3. Department of Pediatrics and Child Health, Jimma University, Jimma, Ethiopia. 4. Jimma University Clinical and Nutrition Research Partnership, Jimma University, Jimma, Ethiopia. 5. Department of Population and Family Health, Jimma University, Jimma, Ethiopia. 6. Department of Psychiatry, Jimma University, Jimma, Ethiopia. 7. Department of Laboratory Sciences and Pathology, Jimma University, Jimma, Ethiopia. 8. Ethiopian Public Health Institute, Addis Ababa, Ethiopia. 9. National Institute of Public Health, Southern Denmark University, Copenhagen, Denmark. 10. Childhood Nutrition Research Centre, UCL Great Ormond Street Institute of Child Health, London, United Kingdom.
Abstract
BACKGROUND: Both impaired and accelerated postnatal growth have been associated with adult risks of obesity and cardiometabolic diseases, like type 2 diabetes and cardiovascular disease. However, the timing of the onset of cardiometabolic changes and the specific growth trajectories linking early growth with later disease risks are not well understood. OBJECTIVES: The aim of this study was to identify distinct trajectories of BMI growth from 0 to 5 y and examine their associations with body composition and markers of cardiometabolic risk at age 5 y. METHODS: In a prospective birth cohort study of 453 healthy and term Ethiopian children with BMIs assessed a median of 9 times during follow-up, we identified subgroups of distinct BMI trajectories in early childhood using latent class trajectory modeling. Associations of the identified growth trajectories with cardiometabolic markers and body composition at 5 y were analyzed using multiple linear regression analyses in 4 adjustment models for each outcome. RESULTS: We identified 4 heterogeneous BMI growth trajectories: stable low BMI (19.2%), normal BMI (48.8%), rapid catch-up to high BMI (17.9%), and slow catch-up to high BMI (14.1%). Compared with the normal BMI trajectory, children in the rapid catch-up to high BMI trajectory had higher triglycerides (TGs) (range of β-coefficients in Models 1-4: 19-21%), C-peptides (23-25%), fat masses (0.48-0.60 kg), and fat-free masses (0.50-0.77 kg) across the 4 adjustment models. Children in the stable low BMI trajectory had lower LDL cholesterol concentrations (0.14-0.17 mmol/L), HDL cholesterol concentrations (0.05-0.09 mmol/L), fat masses (0.60-0.64 kg), and fat-free masses (0.35-0.49 kg), but higher TGs (11-13%). CONCLUSIONS: The development of obesity and cardiometabolic risks may be established already in early childhood; thus, our data provide a further basis for timely interventions targeted at young children from low-income countries with unfavorable growth patterns. The birth cohort was registered at ISRCTN as ISRCTN46718296.
BACKGROUND: Both impaired and accelerated postnatal growth have been associated with adult risks of obesity and cardiometabolic diseases, like type 2 diabetes and cardiovascular disease. However, the timing of the onset of cardiometabolic changes and the specific growth trajectories linking early growth with later disease risks are not well understood. OBJECTIVES: The aim of this study was to identify distinct trajectories of BMI growth from 0 to 5 y and examine their associations with body composition and markers of cardiometabolic risk at age 5 y. METHODS: In a prospective birth cohort study of 453 healthy and term Ethiopian children with BMIs assessed a median of 9 times during follow-up, we identified subgroups of distinct BMI trajectories in early childhood using latent class trajectory modeling. Associations of the identified growth trajectories with cardiometabolic markers and body composition at 5 y were analyzed using multiple linear regression analyses in 4 adjustment models for each outcome. RESULTS: We identified 4 heterogeneous BMI growth trajectories: stable low BMI (19.2%), normal BMI (48.8%), rapid catch-up to high BMI (17.9%), and slow catch-up to high BMI (14.1%). Compared with the normal BMI trajectory, children in the rapid catch-up to high BMI trajectory had higher triglycerides (TGs) (range of β-coefficients in Models 1-4: 19-21%), C-peptides (23-25%), fat masses (0.48-0.60 kg), and fat-free masses (0.50-0.77 kg) across the 4 adjustment models. Children in the stable low BMI trajectory had lower LDL cholesterol concentrations (0.14-0.17 mmol/L), HDL cholesterol concentrations (0.05-0.09 mmol/L), fat masses (0.60-0.64 kg), and fat-free masses (0.35-0.49 kg), but higher TGs (11-13%). CONCLUSIONS: The development of obesity and cardiometabolic risks may be established already in early childhood; thus, our data provide a further basis for timely interventions targeted at young children from low-income countries with unfavorable growth patterns. The birth cohort was registered at ISRCTN as ISRCTN46718296.
Keywords:
body composition; child; cohort study; developmental origins of health and disease; growth; latent class trajectory modeling; noncommunicable diseases; sub-Saharan Africa
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