Dietary patterns by cluster analysis in pregnant women: relationship with nutrient intakes and dietary patterns in 7-year-old offspring

© 2016 The Authors. Maternal & Child Nutrition published by John Wiley & Sons Ltd. Little is known about how dietary patterns of mothers and their children track over time. The objectives of this study are to obtain dietary patterns in pregnancy using cluster analysis, to examine women's mean nutrient intakes in each cluster and to compare the dietary patterns of mothers to those of their children. Pregnant women (n = 12 195) from the Avon Longitudinal Study of Parents and Children reported their frequency of consumption of 47 foods and food groups. These data were used to obtain dietary patterns during pregnancy by cluster analysis. The absolute and energy-adjusted nutrient intakes were compared between clusters. Women's dietary patterns were compared with previously derived clusters of their children at 7 years of age. Multinomial logistic regression was performed to evaluate relationships comparing maternal and offspring clusters. Three maternal clusters were identified: ‘fruit and vegetables’, ‘meat and potatoes’ and ‘white bread and coffee’. After energy adjustment women in the ‘fruit and vegetables’ cluster had the highest mean nutrient intakes. Mothers in the ‘fruit and vegetables’ cluster were more likely than mothers in ‘meat and potatoes’ (adjusted odds ratio [OR]: 2.00; 95% Confidence Interval [CI]: 1.69–2.36) or ‘white bread and coffee’ (OR: 2.18; 95% CI: 1.87–2.53) clusters to have children in a ‘plant-based’ cluster. However the majority of children were in clusters unrelated to their mother dietary pattern. Three distinct dietary patterns were obtained in pregnancy; the ‘fruit and vegetables’ pattern being the most nutrient dense. Mothers' dietary patterns were associated with but did not dominate offspring dietary patterns

A semiquantitative food frequency questionnaire is a valid indicator of the usual intake of phytoestrogens by south Asian women in the UK relative to multiple 24-h dietary recalls and multiple plasma samples.

We investigated the relative validity of an interview-administered FFQ to estimate phytoestrogen intake among South Asian women in the UK. A population-based sample of 108 healthy South Asian women completed random repeated monthly 24-h recalls [with a subsample (n = 58) also providing multiple plasma samples] over a period of 1 y followed by administration of the FFQ. The FFQ produced slightly higher estimates of phytoestrogen intake than the 24-h recalls, but the percentage of women classified into the same +/- 1 quartile by the 2 methods was high for all phytoestrogens (from 81 to 94%) with only a small percentage (<5%) being misclassified into extreme opposite quartiles. Energy-adjusted Spearman correlations coefficients between the estimates obtained by the FFQ and the 24-h recalls were 0.55 for genistein, 0.60 for daidzein, 0.70 for secoisolariciresinol, and 0.63 for matairesinol (all P < 0.001). Spearman correlation coefficients between the FFQ estimates and plasma levels were 0.21 (P = 0.12) for genistein, 0.32 (P = 0.02) for daidzein and 0.10 (P = 0.43) for enterolactone; the corresponding values for the 24-h recalls compared with plasma levels were 0.43 (P < 0.001), 0.40 (P = 0.002), and 0.08 (P = 0.50), respectively. The method of triads was used to estimate the validity coefficients (VCs) between the estimates provided by each assessment method and "true intake." The FFQ had the highest VC for lignans (0.91 vs. 0.73 for 24-h recalls and 0.11 for plasma samples) and satisfactory VCs for both genistein (0.46 vs. 0.95 and 0.45, respectively) and daidzein (0.67 vs. 0.83 and 0.45, respectively). This FFQ is thus a relatively valid tool with which to estimate phytoestrogen intake among South Asian women in the UK