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Background: Longitudinal epidemiological studies require both the periodic update of intake information via repeated dietary survey and the minimization of subject burden in responding to questionnaires. We developed a 66-item Food Frequency Questionnaire (short-FFQ) for the Japan Public Health Center-based prospective Study for the Next Generation (JPHC-NEXT) follow-up survey using major foods from the FFQ developed for the original JPHC Study. For the JPHC-NEXT baseline survey, we used a larger 172-item FFQ (long-FFQ), which was also derived from the JPHC-FFQ. We compared the validity of ranking individuals by levels of dietary consumption by these FFQs among residents of selected JPHC-NEXT study areas. Methods: From 2012 to 2013, 240 men and women aged 40-74 years from five areas in the JPHC-NEXT protocol were asked to respond to the long-FFQ and provide 12-day weighed food records (WFR) as reference; 228 also completed the short-FFQ. Spearman's correlation coefficients (CCs) between estimates from the FFQs and WFR were calculated and corrected for intra-individual variation of the WFR. Results: Median CC values for energy and 53 nutrients for the short-FFQ for men and women were 0.46 and 0.44, respectively. Respective values for the long-FFQ were 0.50 and 0.43. Compared with the long-FFQ, cross-classification into exact plus adjacent quintiles with the short-FFQ ranged from 68% to 91% in men and 58% to 85% in women. Conclusions: Similar to the long-FFQ, the short-FFQ provided reasonably valid measures for ranking middle-aged and elderly Japanese for many nutrients and food groups. The short-FFQ can be used in follow-up surveys in prospective cohort studies aimed at updating diet rank information.

There is no recent validated short food frequency questionnaire (FFQ) for use in New Zealand (NZ) adults. This study aimed to evaluate the relative validity and reproducibility of a short FFQ in free-living NZ adults aged 30–59 years. A 57-item, semi-quantitative FFQ was developed and pre-tested. During a 12-month study period the FFQ was administrated twice with a 9-month interval between administrations. Four two-day diet records were collected at months 0, 3, 6, and 9 and a blood sample was taken at month 9. Spearman correlations were used to evaluate the validity of the FFQ with the eight-day diet records and selected biomarkers. Cross-classification analysis and the Bland–Altman method were used to assess the agreement between the FFQ and the diet record. Reproducibility over nine months was assessed using intra-class correlations. A total of 132 males and females completed both FFQs, the eight-day diet record, and provided a blood sample. The highest energy-adjusted correlation coefficients were observed for alcohol (0.81), cholesterol (0.61), and carbohydrate (0.61), with the lowest for sodium (0.29), thiamin (0.33), and niacin equivalents (0.34). More than three quarters of the participants were correctly classified into the same or adjacent quartile for most nutrients, with a low proportion of participants being grossly misclassified (<10%). For most nutrients, the limits of agreement from the Bland–Altman analyses were between 50% and 250%. A positive correlation was observed between dietary intakes and plasma biomarkers for all selected nutrients. The FFQ showed moderate to good reproducibility, with almost all reliability coefficients ranging from 0.60 to 0.80. This short FFQ was shown to validly and reliably rank individuals by their habitual intake of most major nutrients, indicating that the FFQ will offer a time-efficient way to assess the nutrient intake of NZ adults in future research.

The diet quality index (DQI) for preschool children is a new index developed to reflect compliance with four main food-based dietary guidelines for preschool children in Flanders. The present study investigates: (1) the validity of this index by comparing DQI scores for preschool children with nutrient intakes, both of which were derived from 3 d estimated diet records; (2) the reproducibility of the DQI for preschoolers based on a parentally reported forty-seven-item FFQ DQI, which was repeated after 5 weeks; (3) the relative validity of the FFQ DQI with 3 d record DQI scores as reference. The study sample included 510 and 58 preschoolers (2·5–6·5 years) for validity and reproducibility analyses, respectively. Increasing 3 d record DQI scores were associated with decreasing consumption of added sugars, and increasing intakes of fibre, water, Ca and many micronutrients. Mean FFQ DQI test–retest scores were not significantly different: 72 (sd 11) v. 71 (sd 10) (P = 0·218) out of a maximum of 100. Mean 3 d record DQI score (66 (sd 10)) was significantly lower than mean FFQ DQI (71 (sd 10); P < 0·001). The reproducibility correlation was 0·88. Pearsons correlation (adjusted for within-person variability) between FFQ and 3 d record DQI scores was 0·82. Cross-classification analysis of the FFQ and 3 d record DQI classified 60 % of the subjects in the same category and 3 % in extreme tertiles. Cross-classification of repeated administrations classified 62 % of the subjects in the same category and 3 % in extreme categories. The FFQ-based DQI approach compared well with the 3 d record approach, and it can be used to determine diet quality among preschoolers.

A national strategy for obesity prevention has been promoted in Paraguay, reflecting the situation where half of adults and 23.4% of children (under 5 years old) are overweight. However, the detailed nutritional intake of the population has not yet been studied, especially in rural areas. Therefore, this study aimed to identify obesity-causing factors in Pirapó by analyzing the results from a food frequency questionnaire (FFQ) and one-day weighed food records (WFRs). From June to October 2015, 433 volunteers (200 males and 233 females) completed the FFQ with 36 items and one-day WFRs. Body mass index (BMI) positively correlated with the consumption of sandwiches, hamburgers, and bread and with age and diastolic blood pressure, although pizza and fried bread (pireca) had a negative correlation in males (p < 0.05). BMI positively correlated with systolic blood pressure, whereas it negatively correlated with the consumption of cassava and rice in females (p < 0.05). The FFQ revealed that fried food with wheat flour was consumed once a day. WFRs showed that 40% of meals consisted of two or more carbohydrate-rich dishes, significantly higher in energy, lipids, and sodium than those containing only one carbohydrate-rich dish. These results imply that less oily wheat dish consumption and healthy combinations of dishes should be considered for obesity prevention.

In Japan, nutritional guidance based on food-recording apps and food frequency questionnaires (FFQs) is becoming popular. However, it is not always recognized that different dietary assessment methods have different nutritional values. Here, we compared the compatibility of dietary intake data obtained from an app with those obtained from FFQs in 59 healthy individuals who recorded information regarding their diet for at least 7 days per month using an app developed by Asken (Tokyo, Japan). The diurnal coefficient of variation in total energy and protein intake was 20%, but those for vitamins B12 and D were >80%, reflecting the importance of 7 days of recording rather than a single day of recording for dietary intake analyses. Then, we compared the results of two FFQs—one based on food groups and one based on a brief self-administered diet history questionnaire—for 7 days, as recorded by the app. There was a correlation coefficient of >0.4 for all the items except salt. Regarding the compatibility between the app and FFQs, the percentage errors for total energy and nutrients were >40–50%, suggesting no agreement between the app and the two FFQs. In conclusion, careful attention should be paid to the impact of different dietary assessment methods on nutrient assessment.

•To assess validity of a 253-item FFQ, containing 54 nutrients and 22 food groups.•Median validation coefficients were 0.50 for nutrients.•Median validation coefficients were 0.64 for food groups. The aim of this study was to develop and validate a comprehensive food frequency questionnaire (FFQ) for The Maastricht Study, a population-based prospective cohort study in Maastricht, The Netherlands. 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). 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. 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.

Background Humans have a long history of consuming fermented foods. However, their prevalence in human diets remains largely undetermined, and there is a lack of validated dietary assessment tools assessing the intake of different fermented products. This study aimed to identify fermented foods consumed in The Netherlands and determine the relative validity of a food frequency questionnaire (FFQ) compared to multiple 24-h recalls for estimating their intake. Methods The validation population consisted of 809 participants (53.1 ± 11.9 years) from a Dutch observational cohort (NQplus) who completed a FFQ and multiple 24-h recalls. Fermented foods from the FFQ and recalls were identified and aggregated into conventional food groups. Percent difference in mean intakes, quintile cross-classification, Spearman’s correlations, and Bland-Altman analyses were used to evaluate the agreement between the two dietary assessment methods. Results Approximately 16–18% of foods consumed by this population were fermented, and a further 9–14% were dishes containing a fermented ingredient. Fermented foods with the highest consumption included coffee (~ 453 g/day;~ 0.5% of daily energy intake), yoghurts (~ 88 g/day;~ 2.2%), beer (~ 84 g/day;~ 1.7%), wholegrain bread (~ 81 g/day;~ 9.4%), wine (~ 65 g/day;~ 2.7%), and cheese (~ 32 g/day;~ 5.0%). Mean percent difference between the FFQ and recalls was small for fermented beverages (coffee), breads (brown, white, wholegrain, rye), and fermented dairy (cheeses) (0.3–2.8%), but large for buttermilk and quark (≥53%). All fermented food groups had > 50% of participants classified into the same or adjacent quintile of intake (58%-buttermilk to 89%-fermented beverages). Strong Spearman’s correlations (crude/energy-adjusted r s  ≥ 0.50) were obtained for fermented beverages (coffee, beer, wine), cereals/grains (wholegrain bread), and dairy (yoghurts). For ‘other bread’, quark, and buttermilk, correlations were low (r s  < 0.20). Bland-Altman analyses revealed good agreement for fermented beverages (coffee, beer), breads (brown, wholegrain, rye, other), pastries, chocolate, and fermented dairy (cheeses) (mean difference: 0.1–9.3). Conclusions Fermented food groups with acceptable or good validity across all measures included commonly consumed foods in The Netherlands: fermented beverages (coffee), wholegrain and rye bread, and fermented dairy (cheeses). However, for less frequently consumed foods, such as quark and buttermilk, the levels of agreement were poor and estimates of intake should be interpreted with caution. This report provides the basis for developing a FFQ specific for fermented foods.

To evaluate the reproducibility of a semi-quantitative FFQ used in the Seguimiento Universidad de Navarra (SUN) project. The data that were analysed were collected from an FFQ answered twice by a 326-participant subsample of the SUN project (115 men, 35.3 %; 211 women, 64.7 %), with either less than 1 year or more than 1 year between responses. The questionnaire included 136 items. Pearson correlation coefficients (r) were calculated to evaluate the magnitude of the association between both measures after energy adjustment and correcting for within-person variability. We also evaluated misclassification by quintiles distribution. The highest corrected correlations among participants who answered before 1 year were found for PUFA (r = 0.99). Among participants who answered after 1 year between both questionnaires, olive oil had the highest corrected correlation (r = 0.99). The highest percentage of gross misclassification, lowest quintile in FFQ1 and highest quintile in FFQ2 or highest quintile in FFQ1 and lowest quintile in FFQ2 was for cereals, fish or seafood, and n-3 fatty acids (7.6 %). Alcoholic drinks had the highest percentage of reasonable classification, same or adjacent quintile, in FFQ1 and FFQ2 (86.4 %). Our study suggests that FFQ reproducibility is acceptable for participants who answered the same questionnaire twice less than 1 year apart. Participants who answered FFQ more than 1 year apart showed worse values on reproducibility. We consider this Spanish FFQ as an important, valid and reproducible tool in nutritional epidemiology.

PurposeTo improve human health and environmental sustainability, red meat consumption should decrease and legume consumption increase in diets. More information on food motives, however, is required when developing more tailored and effective interventions targeting legume and meat consumption. We aimed to examine the associations between food motives and red meat and legume consumption, and whether these associations differ between different subgroups (gender, age groups, marital status, education, BMI).MethodsTen food motives (health, mood, convenience, sensory appeal, natural content, price-cheap, price-value, weight control, familiarity and ethical concern measured with Food Choice Questionnaire) were studied in 3079 Finnish adults in the population-based DILGOM study. Food consumption was assessed with Food Frequency Questionnaire. The adjusted estimates from multivariable regression models are reported.ResultsHigher relative importance of natural content (β = − 0.275, 95% CI − 0.388; − 0.162) and ethical concern (β = − 0.462, 95% CI − 0.620; − 0.305) were associated with lower red meat consumption, and higher appreciation of sensory appeal (β = 0.482, 95% CI 0.347; 0.616) and price-cheap (β = 0.190, 95% CI 0.099; 0.281) with higher red meat consumption. Higher importance of health (β = 0.608, 95% CI 0.390; 0.825) was associated with higher legume consumption, and higher appreciation of convenience (β = − 0.401, 95% CI − 0.522; − 0.279), price-value (β = − 0.257, 95% CI − 0.380; − 0.133) and familiarity (β = − 0.278, 95% CI − 0.393; − 0.164) with lower legume consumption. The associations of particularly ethical concern, weight control, sensory appeal and mood varied according to gender, age, marital status or BMI.ConclusionThe development and implementation of actions to decrease red meat and increase legume consumption should focus on several food motives across different subgroups.

Adult diet quality indices are shown to predict nutritional adequacy of dietary intake as well as all-cause morbidity and mortality. This study describes the reproducibility and validity of a food-based diet quality index, the Australian Recommended Food Score (ARFS). ARFS was developed to reflect alignment with the Australian Dietary Guidelines and is modelled on the US Recommended Food Score. Dietary intakes of 96 adult participants (31 male, 65 female) age 30 to 75 years were assessed in two rounds, five months apart. Diet was assessed using a 120-question semi-quantitative food frequency questionnaire (FFQ). The ARFS diet quality index was derived using a subset of 70 items from the full FFQ. Reproducibility of the ARFS between round one and round two was confirmed by the overall intraclass correlation coefficient of 0.87 (95% CI 0.83, 0.90), which compared favourably to that for the FFQ at 0.85 (95% CI 0.80, 0.89). ARFS was correlated with FFQ nutrient intakes, particularly fiber, vitamin A, beta-carotene and vitamin C (0.53, 95% CI 0.37–0.67), and with mineral intakes, particularly calcium, magnesium and potassium (0.32, 95% CI 0.23–0.40). ARFS is a suitable brief tool to evaluate diet quality in adults and reliably estimates a range of nutrient intakes.