Abstract
OBJECTIVE: The current study prospectively examines the intra-uterine hypothesis by comparing maternal, paternal and grandparental lineage influences on children’s diet and also maternal–child aggregation patterns during pregnancy and early childhood. DESIGN: Prenatal dietary information was available for expectant mothers, fathers and up to four grandparents through a detailed validated semi-quantitative FFQ. At 6-year follow-up, when children averaged 5 years of age, dietary information was re-collected for mothers and a subset of maternal grandmothers using the same FFQ. Child’s FFQ version was used for children. Anthropometric and sociodemographic variables were also collected. SETTINGS: Three-generation familial cohort representative of the contemporary Irish national population. SUBJECTS: Children aged 5 years (n 567) and their parents and grandparents. RESULTS: Associations for energy, macronutrient and fibre intakes were compared using Pearson’s correlations, intra-class correlations (ICC) and linear regression models, adjusted for energy and potential confounders. Significant, moderatestrength positive correlations were observed for nutrient intakes in children’s nuclear families (ICC (range)50?22–0?28). The father–child associations (r (range)5 0?13–0?20) were weaker than the mother–child associations (r (range)50?14–0?33). In general, associations were stronger for maternal postnatal intake–child intake than for maternal prenatal intake–child intake, except for percentage of energy from fat (adjusted b50?16, 95% CI 0?05, 0?26; P50?004), which was stronger for maternal prenatal intake, specifically in non-breast-fed children (adjusted b50?28, 95% CI 0?12, 0?44; P50?001). Among all grandparents, correlations were significant only for maternal grandmother–mother pairs (r (range)50?10–0?36). Significant positive ICC were observed for nutrient intakes of maternal grandmother–mother–child triads (ICC (range)50?12–0?27), not found in paternal lines. CONCLUSIONS: These findings suggest that maternal-environment programming influences dietary intake.