a1 Tropical Medicine Research Institute, University of the West Indies, Mona, Jamaica
a2 MRC Epidemiology Resource Centre, University of Southampton, Southampton, UK
Both intra-uterine and early childhood development contribute to the risk of developing CVD in adult life. We therefore evaluated the maternal, placental, fetal, birth, infant and childhood determinants of cardiovascular risk in a cohort of Afro-Jamaican children. The Vulnerable Windows Cohort is a longitudinal survey of 569 mothers and their offspring recruited from the first trimester. The offspring's anthropometry was measured at birth, at 6 weeks, every 3 months to 1 year and then every 6 months. At mean age 11·5 years, fasting blood was sampled for glucose, insulin and lipids. Analyses were confined to 296 women and their offspring who had complete data. Waist circumference (WC) was related to maternal weight and BMI, placental weight and to the size of the offspring in utero, at birth and the rate of growth in childhood (P < 0·05). Total cholesterol, TAG and glucose concentrations were unrelated to maternal, placental, fetal, neonatal and childhood measurements. Fasting insulin and homeostasis model assessment of insulin resistance were related to maternal weight and BMI (P < 0·05), but not after adjusting for WC. HDL-cholesterol was inversely related to placental and birth weight, and inversely related to weight and BMI throughout childhood (P < 0·001), but not after adjusting for WC. Systolic blood pressure was directly related to maternal weight, child's height, weight and BMI (P < 0·05), but not after adjustment for WC. Systolic blood pressure and fasting glucose concentration were inversely related to birth weight in boys but directly associated in girls. We concluded that maternal anthropometry during pregnancy, fetal size, and childhood growth rate contribute to cardiovascular risk factors in childhood.
(Received July 15 2009)
(Revised April 07 2010)
(Accepted April 08 2010)
(Online publication June 14 2010)
Abbreviations: HOMA-IR, homeostasis model assessment of insulin resistance