U Sovio1, M Kaakinen2, I Tzoulaki3, S Das4, A Ruokonen5, A Pouta6, A-L Hartikainen7, J Molitor8, M-R Järvelin9. 1. 1] Department of Non-communicable Disease Epidemiology, Faculty of Epidemiology and Population Health, London School of Hygiene and Tropical Medicine, London, UK [2] Department of Epidemiology and Biostatistics, MRC-HPA Centre, School of Public Health, Imperial College London, Norfolk Place, London, UK. 2. 1] Institute of Health Sciences, University of Oulu, Oulu, Finland [2] Biocenter Oulu, University of Oulu, Oulu, Finland. 3. 1] Department of Epidemiology and Biostatistics, MRC-HPA Centre, School of Public Health, Imperial College London, Norfolk Place, London, UK [2] Department of Hygiene and Epidemiology, Medical School University of Ioannina, Ioannina, Greece. 4. Department of Epidemiology and Biostatistics, MRC-HPA Centre, School of Public Health, Imperial College London, Norfolk Place, London, UK. 5. Institute of Diagnostics, Clinical Chemistry, University of Oulu, Oulu, Finland. 6. 1] Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland [2] Department of Clinical Sciences/Obstetrics and Gynecology, University of Oulu, Oulu, Finland. 7. Department of Clinical Sciences/Obstetrics and Gynecology, University of Oulu, Oulu, Finland. 8. 1] Department of Epidemiology and Biostatistics, MRC-HPA Centre, School of Public Health, Imperial College London, Norfolk Place, London, UK [2] College of Public Health & Human Sciences, Oregon State University, Corvallis, OR, USA. 9. 1] Department of Epidemiology and Biostatistics, MRC-HPA Centre, School of Public Health, Imperial College London, Norfolk Place, London, UK [2] Institute of Health Sciences, University of Oulu, Oulu, Finland [3] Biocenter Oulu, University of Oulu, Oulu, Finland [4] Department of Children, Young People and Families, National Institute for Health and Welfare, Oulu, Finland.
Abstract
BACKGROUND/ OBJECTIVE: Postnatal growth patterns leading to obesity may have adverse influences on future cardiometabolic health. This study evaluated age and body mass index (BMI) at infant BMI peak (BMIP) and childhood BMI rebound (BMIR) in relation to adult cardiometabolic outcomes in the Northern Finland Birth Cohort 1966. METHODS: BMI at various ages was calculated from frequent height and weight measurements obtained from child health and welfare clinical records. Age and BMI at BMIP and BMIR were derived from random effect models fitted at >0-1.5 years (N=3 265) and >1.5-13 years (N=4 121). Cardiometabolic outcomes were obtained from a clinical examination at age 31 years. Multiple regression models were used to analyse associations between the derived growth parameters and cardiometabolic outcomes. RESULTS: Age and BMI at BMIP were positively associated with adult BMI and waist circumference (WC), independently of birth weight and infant height growth (P<0.05). Later BMIR was associated with a better cardiometabolic profile: adult BMI and insulin were 14% lower, WC and triglycerides were 10% lower and the odds of metabolic syndrome (MetS) were 74% lower per 2 s.d. (1.86 years) higher age at BMIR (P<0.0001). BMI at rebound had generally weaker associations with cardiometabolic outcomes, which attenuated after adjustment for age at BMIR. CONCLUSIONS: Age and BMI at infant BMIP were associated with adult adiposity but not with other cardiometabolic outcomes. Earlier timing of BMIR was a risk factor of an adverse cardiometabolic profile, independently of early growth or BMI at rebound. Identifying growth patterns harmful to cardiovascular health will give opportunities for early interventions.
BACKGROUND/ OBJECTIVE: Postnatal growth patterns leading to obesity may have adverse influences on future cardiometabolic health. This study evaluated age and body mass index (BMI) at infant BMI peak (BMIP) and childhood BMI rebound (BMIR) in relation to adult cardiometabolic outcomes in the Northern Finland Birth Cohort 1966. METHODS: BMI at various ages was calculated from frequent height and weight measurements obtained from child health and welfare clinical records. Age and BMI at BMIP and BMIR were derived from random effect models fitted at >0-1.5 years (N=3 265) and >1.5-13 years (N=4 121). Cardiometabolic outcomes were obtained from a clinical examination at age 31 years. Multiple regression models were used to analyse associations between the derived growth parameters and cardiometabolic outcomes. RESULTS: Age and BMI at BMIP were positively associated with adult BMI and waist circumference (WC), independently of birth weight and infant height growth (P<0.05). Later BMIR was associated with a better cardiometabolic profile: adult BMI and insulin were 14% lower, WC and triglycerides were 10% lower and the odds of metabolic syndrome (MetS) were 74% lower per 2 s.d. (1.86 years) higher age at BMIR (P<0.0001). BMI at rebound had generally weaker associations with cardiometabolic outcomes, which attenuated after adjustment for age at BMIR. CONCLUSIONS: Age and BMI at infant BMIP were associated with adult adiposity but not with other cardiometabolic outcomes. Earlier timing of BMIR was a risk factor of an adverse cardiometabolic profile, independently of early growth or BMI at rebound. Identifying growth patterns harmful to cardiovascular health will give opportunities for early interventions.
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