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Objective: Food frequency questionnaires (FFQs) assess habitual dietary intake and are relatively inexpensive to process, but may take up to 60 minutes to complete. This article describes the validation of the Flower-FFQ, which consists of four short FFQs measuring the intake of energy and macronutrients or specific (micro)nutrients/foods that can be merged into one complete daily assessment using predefined algorithms. Design: Participants completed the Flower-FFQ and validated regular-FFQ (n=401). Urinary nitrogen (n=242) and potassium excretions (n=361) were measured. We evaluated: 1) group-level bias, 2) correlations, and 3) cross-classification. Setting: Observational study. Participants: Dutch adults, 54±11(mean±SD) years. Results: Flower-FFQ1, Flower-FFQ2, Flower-FFQ3, and Flower-FFQ4 were completed in ±24, 9, 8 and 9 minutes (±50 minutes total), respectively. The regular-FFQ was completed in ±43 minutes. Mean energy (flower vs. regular: 7953 vs. 8718 kJ/day) and macronutrient intakes (carbohydrates: 204 vs. 222 g/day; protein: 75 vs. 76 g/day; fat: 74 vs. 83 g/day; ethanol: 8 vs. 12 g/day) were comparatively similar. Spearman correlations between Flower-FFQ and regular-FFQ ranged from 0.60-0.80 for macronutrients and from 0.40-0.80 for micronutrients and foods. For all micronutrients and foods, ≥78% of the participants classified in the same/adjacent quartile. The flower-FFQ underestimated urinary nitrogen and potassium excretions by 24% and 18%; 75% and 73% of the participants ranked in the same/adjacent quartile. Conclusion: Completing the Flower-FFQ required 50 minutes with a maximum of 25 minutes per short FFQ. The Flower-FFQ has a moderate to good ranking ability for most nutrients and foods and performs sufficiently to study diet-disease associations.

The original version of this article unfortunately contained a mistake in Table 4.

Background: Inaccurate self-report of portion sizes is a major cause of measurement error in dietary assessment. To reduce this error, different portion size estimation aids (PSEAs) have been developed, including food images (image based, IB-PSE) and textual descriptions of portion sizes (text-based, TB-PSE). We assessed the accuracy of portion size estimation by IB-PSE and TB-PSE. Methods: True intake of one lunch was ascertained in forty participants. Self-reported portion sizes were assessed after 2 and 24 hours by means of TB-PSE and IB-PSE, in random order. Wilcoxon's tests were used to compare mean true intakes to reported intakes. Moreover, proportions of reported portion sizes within 10% and 25% of true intake were assessed. An adapted Bland-Altman approach was used to assess agreement between true and reported portion sizes. Analyses were conducted for all foods and drinks combined and for predetermined food types. Results: No significant differences were observed between reported portion sizes at 2 and 24 hours after lunch. Combining median relative errors of all foods items resulted in an overall 0% error rate for TB-PSE and 6% error rate for IB-PSE. Comparing reported portion sizes within 10% (31% vs. 13%) and 25% (50% vs. 35%) of the true intake showed a better performance for TB-PSE compared to IP-PSE, respectively. Bland-Altman plots indicated a higher agreement between reported and true intake for TB-PSE compared to IB-PSE. Conclusions: Although the use of TB-PSE still results in measurement error, our results suggest a more accurate dietary intake assessment with TB-PSE than IB-PSE.

Purpose: In this study, we investigated the association between adherence to the Dutch Healthy Diet index 2015 (DHD15-index) and incidence of prediabetes (preT2D) and Type 2 Diabetes (T2D) in a representative sample for the general Dutch population. Methods: Two prospective cohort studies, The Hoorn and The New Hoorn Study, were used for data analyses. In total, data from 2951 participants without diabetes at baseline (mean age 56.5 ± 7.5 years; 49.6% male) were harmonized. Baseline dietary intake was assessed with validated Food Frequency Questionnaires and adherence to the DHD15-index was calculated (range 0–130). PreT2D and T2D were classified according to the WHO criteria 2011. Poisson regression was used to estimate prevalence ratios between participant scores on the DHD15-index and preT2D and T2D, adjusted for follow-up duration, energy intake, socio-demographic, and lifestyle factors. Change in fasting plasma glucose levels (mmol/L) over follow-up was analysed using linear regression analyses, additionally adjusted for baseline value. Results: During a mean follow-up of 6.3 ± 0.7 years, 837 participants developed preT2D and 321 participants developed T2D. The highest adherence to the DHD15-index was significantly associated with lower T2D incidence [model 3, PRT3vsT1: 0.70 (0.53; 0.92), ptrend = 0.01]. The highest adherence to the DHD15-index pointed towards a lower incidence of preT2D [PRT3vsT1: 0.87 (0.74; 1.03), ptrend = 0.11]. Higher adherence to the DHD15-index was not associated with change in fasting plasma glucose levels [β10point: − 0.012 (− 0.034; 0.009)mmol/L]. Conclusion: The present study showed that the highest compared to the lowest adherence to the DHD15-index was associated with a lower T2D incidence, and pointed towards a lower incidence of preT2D. These results support the benefits of adhering to the guidelines in T2D prevention.

Although the importance of maternal nutrition is evident, adherence to dietary guidelines is limited in pregnant women, especially in those with a low socioeconomic status. Promotion of a healthy diet in midwifery practice is promising, as prenatal diet affects both maternal and child health, pregnant women are open to dietary changes during this critical transition, and midwives are their first and most important source of information. Unfortunately, nutrition communication by Dutch midwives is limited.Objective: The objective of this study is to optimize the dietary intake of low–socioeconomic status pregnant women by contributing to the further development and adjustment of a tool or toolbox to support midwives in providing nutrition communication.Methods: This interdisciplinary, mixed-methods study includes 2 phases, in which quantitative and qualitative research are complementary. In phase 1, we will conduct a literature study and interviews to gain insight into midwives’ knowledge, needs, and practice. We will obtain data on the dietary intake of low–socioeconomic status pregnant women and factors influencing this intake from another literature study, an interviewer-administered meal-based food frequency questionnaire, and qualitative interviews with pregnant women. We will identify the availability of suitable tools to improve pregnant women’s dietary intake from the literature, interviews, focus groups, and expert meetings. In phase 2, we shall adapt an existing tool or develop a new tool(box), depending on the results of phase 1, and implement it in 5 midwifery practices. Ultimately, a process evaluation will provide insight into barriers and facilitating factors playing a role in the implementation of the tool(box).Results: The main outcome of this study will be a tool(box) to optimize the dietary intake of Dutch pregnant women. We anticipate that the developed or adjusted tool(s) will be available in February 2020. After we implement the tool(s) and evalu

It is suggested that nutrient densities are less affected by measurement errors than absolute intake estimates of dietary exposure. We compared the validity of absolute intakes and densities of protein (kJ from protein/total energy (kJ)), potassium, and sodium (potassium or sodium (in mg)/total energy (kJ)) assessed by different dietary assessment methods. For 69 Dutch subjects, two duplicate portions (DPs), five to fifteen 24-h dietary recalls (24 hRs, telephone-based and web-based) and two food frequency questionnaires (FFQs) were collected and compared to duplicate urinary biomarkers and one or two doubly labelled water measurements. Multivariate measurement error models were used to estimate validity coefficients (VCs) and attenuation factors (AFs). This research showed that group bias diminished for protein and sodium densities assessed by all methods as compared to the respective absolute intakes, but not for those of potassium. However, the VCs and AFs for the nutrient densities did not improve compared to absolute intakes for all four methods; except for the AF of sodium density (0.71) or the FFQ which was better than that of the absolute sodium intake (0.51). Thus, using nutrient densities rather than absolute intakes does not necessarily improve the performance of the DP, FFQ, or 24 hR.