METHODS: Item selection for the FFQ was based on explained variation and contribution to intake of energy and 24 nutrients. For validation, the FFQ was completed by 135 participants (25-70 y of age) of the Nutrition Questionnaires plus study. Per person, on average 2.8 (range 1-5) telephone-based 24-h dietary recalls (24HRs), two 24-h urinary samples, and one blood sample were available. Validity of 54 nutrients and 22 food groups was assessed by ranking agreement, correlation coefficients, attenuation factors, and ultimately deattenuated correlation coefficients (validity coefficients).
RESULTS: Median correlation coefficients for energy and macronutrients, micronutrients, and food groups were 0.45, 0.36, and 0.38, respectively. Median deattenuated correlation coefficients were 0.53 for energy and macronutrients, 0.45 for micronutrients, and 0.64 for food groups, being >0.50 for 18 of 22 macronutrients, 16 of 30 micronutrients and >0.50 for 17 of 22 food groups. The FFQ underestimated protein and potassium intake compared with 24-h urinary nitrogen and potassium excretion by -18% and -2%, respectively. Correlation coefficients ranged from 0.50 and 0.55 for (fatty) fish intake and plasma eicosapentaenoic acid and docosahexaenoic acid, and from 0.26 to 0.42 between fruit and vegetable intake and plasma carotenoids.
CONCLUSION: Overall, the validity of the 253-item Maastricht FFQ was satisfactory. The comprehensiveness of this FFQ make it well suited for use in The Maastricht Study and similar populations.
METHODS: This study includes 235,880 participants, 25-70 years old, recruited between 1992 and 2000 in 10 European countries. Intakes of 23 nutrients were estimated from country-specific validated dietary questionnaires using the harmonized EPIC Nutrient DataBase. Four nutrient patterns, explaining 67 % of the total variance of nutrient intakes, were previously identified from principal component analysis. Body weight was measured at recruitment and self-reported 5 years later. The relationship between nutrient patterns and annual weight change was examined separately for men and women using linear mixed models with random effect according to center controlling for confounders.
RESULTS: Mean weight gain was 460 g/year (SD 950) and 420 g/year (SD 940) for men and women, respectively. The annual differences in weight gain per one SD increase in the pattern scores were as follows: principal component (PC) 1, characterized by nutrients from plant food sources, was inversely associated with weight gain in men (-22 g/year; 95 % CI -33 to -10) and women (-18 g/year; 95 % CI -26 to -11). In contrast, PC4, characterized by protein, vitamin B2, phosphorus, and calcium, was associated with a weight gain of +41 g/year (95 % CI +2 to +80) and +88 g/year (95 % CI +36 to +140) in men and women, respectively. Associations with PC2, a pattern driven by many micro-nutrients, and with PC3, a pattern driven by vitamin D, were less consistent and/or non-significant.
CONCLUSIONS: We identified two main nutrient patterns that are associated with moderate but significant long-term differences in weight gain in adults.