Yi Ying Ong1, Suresh Anand Sadananthan2, Izzuddin M Aris3, Mya Thway Tint2,4, Wen Lun Yuan1, Jonathan Y Huang2, Yiong Huak Chan5, Sharon Ng4, See Ling Loy2,6,7, Sendhil S Velan2,8, Marielle V Fortier2,9, Keith M Godfrey10, Lynette Shek1,2,11, Kok Hian Tan7,12, Peter D Gluckman2,13, Fabian Yap7,14, Jonathan Tze Liang Choo14, Lieng Hsi Ling15, Karen Tan2,16, Li Chen2, Neerja Karnani2, Yap-Seng Chong2,4, Johan G Eriksson2,4, Mary E Wlodek2,17, Shiao-Yng Chan2,4, Yung Seng Lee1,2,11, Navin Michael2. 1. Department of Pediatrics, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. 2. Singapore Institute for Clinical Sciences, Agency for Science, Technology, and Research, Singapore, Singapore. 3. Division of Chronic Disease Research Across the Lifecourse, Department of Population Medicine, Harvard Medical School and Harvard Pilgrim Health Care Institute, Boston, MA, USA. 4. Department of Obstetrics and Gynaecology, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. 5. Biostatistics Unit, Yong Loo Lin School of Medicine, National University of Singapore, Singapore, Singapore. 6. Department of Reproductive Medicine, KK Women's and Children's Hospital, Singapore, Singapore. 7. Duke-NUS Medical School, Singapore, Singapore. 8. Singapore Bioimaging Consortium, Agency for Science Technology and Research, Singapore, Singapore. 9. Department of Diagnostic and Interventional Imaging, KK Women's and Children's Hospital, Singapore, Singapore. 10. MRC Lifecourse Epidemiology Unit and NIHR Southampton Biomedical Research Centre, University of Southampton and University Hospital Southampton NHS Foundation Trust, Southampton, UK. 11. Department of Pediatrics, Khoo Teck Puat-National University Children's Medical Institute, National University Hospital, National University Health System, Singapore, Singapore. 12. Department of Maternal Fetal Medicine, KK Women's and Children's Hospital, Singapore, Singapore. 13. Liggins Institute, University of Auckland, Auckland, New Zealand. 14. Department of Pediatrics, KK Women's and Children's Hospital, Singapore, Singapore. 15. Department of Cardiology, National University Heart Centre, Singapore, Singapore. 16. Molecular Diagnosis Centre, Department of Laboratory Medicine, National University Health System, Singapore, Singapore. 17. Department of Physiology, University of Melbourne, Melbourne, VIC, Australia.
Abstract
BACKGROUND: Using longitudinal ultrasounds as an improved fetal growth marker, we aimed to investigate if fetal growth deceleration followed by rapid postnatal weight gain is associated with childhood cardiometabolic risk biomarkers in a contemporary well-nourished population. METHODS: We defined fetal growth deceleration (FGD) as ultrasound-measured 2nd-3rd-trimester abdominal circumference decrease by ≥0.67 standard deviation score (SDS) and rapid postnatal weight gain (RPWG) as 0-2-year-old weight increase by ≥0.67 SDS. In the GUSTO mother-offspring cohort, we grouped 797 children into four groups of FGD-only (14.2%), RPWG-only (23.3%), both (mismatch, 10.7%) or neither (reference, 51.8%). Adjusting for confounders and comparing with the reference group, we tested associations of these growth groups with childhood cardiometabolic biomarkers: magnetic resonance imaging (MRI)-measured abdominal fat (n = 262), liver fat (n = 216), intramyocellular lipids (n = 227), quantitative magnetic resonance-measured overall body fat % (BF%) (n = 310), homeostasis model assessment of insulin resistance (HOMA-IR) (n = 323), arterial wall thickness (n = 422) and stiffness (n = 443), and blood pressure trajectories (ages 3-6 years). RESULTS: Mean±SD birthweights were: FGD-only (3.11 ± 0.38 kg), RPWG-only (3.03 ± 0.37 kg), mismatch (2.87 ± 0.31 kg), reference (3.30 ± 0.36 kg). FGD-only children had elevated blood pressure trajectories without correspondingly increased BF%. RPWG-only children had altered body fat partitioning, higher BF% [BF = 4.26%, 95% confidence interval (CI) (2.34, 6.19)], HOMA-IR 0.28 units (0.11, 0.45)] and elevated blood pressure trajectories. Mismatch children did not have increased adiposity, but had elevated ectopic fat, elevated HOMA-IR [0.29 units (0.04,0.55)] and the highest blood pressure trajectories. Associations remained even after excluding small-for-gestational-age infants from analyses. CONCLUSIONS: Fetal growth deceleration coupled with rapid postnatal weight gain was associated with elevated childhood cardiometabolic risk biomarkers without correspondingly increased BF%.
BACKGROUND: Using longitudinal ultrasounds as an improved fetal growth marker, we aimed to investigate if fetal growth deceleration followed by rapid postnatal weight gain is associated with childhood cardiometabolic risk biomarkers in a contemporary well-nourished population. METHODS: We defined fetal growth deceleration (FGD) as ultrasound-measured 2nd-3rd-trimester abdominal circumference decrease by ≥0.67 standard deviation score (SDS) and rapid postnatal weight gain (RPWG) as 0-2-year-old weight increase by ≥0.67 SDS. In the GUSTO mother-offspring cohort, we grouped 797 children into four groups of FGD-only (14.2%), RPWG-only (23.3%), both (mismatch, 10.7%) or neither (reference, 51.8%). Adjusting for confounders and comparing with the reference group, we tested associations of these growth groups with childhood cardiometabolic biomarkers: magnetic resonance imaging (MRI)-measured abdominal fat (n = 262), liver fat (n = 216), intramyocellular lipids (n = 227), quantitative magnetic resonance-measured overall body fat % (BF%) (n = 310), homeostasis model assessment of insulin resistance (HOMA-IR) (n = 323), arterial wall thickness (n = 422) and stiffness (n = 443), and blood pressure trajectories (ages 3-6 years). RESULTS: Mean±SD birthweights were: FGD-only (3.11 ± 0.38 kg), RPWG-only (3.03 ± 0.37 kg), mismatch (2.87 ± 0.31 kg), reference (3.30 ± 0.36 kg). FGD-only children had elevated blood pressure trajectories without correspondingly increased BF%. RPWG-only children had altered body fat partitioning, higher BF% [BF = 4.26%, 95% confidence interval (CI) (2.34, 6.19)], HOMA-IR 0.28 units (0.11, 0.45)] and elevated blood pressure trajectories. Mismatch children did not have increased adiposity, but had elevated ectopic fat, elevated HOMA-IR [0.29 units (0.04,0.55)] and the highest blood pressure trajectories. Associations remained even after excluding small-for-gestational-ageinfants from analyses. CONCLUSIONS: Fetal growth deceleration coupled with rapid postnatal weight gain was associated with elevated childhood cardiometabolic risk biomarkers without correspondingly increased BF%.
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