Structural Validation of a French Food Frequency Questionnaire of 94 Items.
ABSTRACT: Background:Food frequency questionnaires (FFQs) are used to estimate the usual food and nutrient intakes over a period of time. Such estimates can suffer from measurement errors, either due to bias induced by respondent's answers or to errors induced by the structure of the questionnaire (e.g., using a limited number of food items and an aggregated food database with average portion sizes). The "structural validation" presented in this study aims to isolate and quantify the impact of the inherent structure of a FFQ on the estimation of food and nutrient intakes, independently of respondent's perception of the questionnaire. Methods:A semi-quantitative FFQ (n?=?94 items, including 50 items with questions on portion sizes) and an associated aggregated food composition database (named the item-composition database) were developed, based on the self-reported weekly dietary records of 1918 adults (18-79 years-old) in the French Individual and National Dietary Survey 2 (INCA2), and the French CIQUAL 2013 food-composition database of all the foods (n?=?1342 foods) declared as consumed in the population. Reference intakes of foods ("REF_FOOD") and nutrients ("REF_NUT") were calculated for each adult using the food-composition database and the amounts of foods self-reported in his/her dietary record. Then, answers to the FFQ were simulated for each adult based on his/her self-reported dietary record. "FFQ_FOOD" and "FFQ_NUT" intakes were estimated using the simulated answers and the item-composition database. Measurement errors (in %), spearman correlations and cross-classification were used to compare "REF_FOOD" with "FFQ_FOOD" and "REF_NUT" with "FFQ_NUT". Results:Compared to "REF_NUT," "FFQ_NUT" total quantity and total energy intake were underestimated on average by 198?g/day and 666 kJ/day, respectively. "FFQ_FOOD" intakes were well estimated for starches, underestimated for most of the subgroups, and overestimated for some subgroups, in particular vegetables. Underestimation were mainly due to the use of portion sizes, leading to an underestimation of most of nutrients, except free sugars which were overestimated. Conclusion:The "structural validation" by simulating answers to a FFQ based on a reference dietary survey is innovative and pragmatic and allows quantifying the error induced by the simplification of the method of collection.
Project description:The measurement of vitamin D nutritional status through dietary assessment is cost effective. Food frequency questionnaire (FFQ) is usually validated against food records (FR). There is no vitamin D-specific FFQ for Qatar population. The objective of this study was to develop a vitamin D-centric FFQ and validate FFQ against three-day FR for Qatar population. A quantitative FFQ based on vitamin D containing foods consumed in Qatar was developed. Vitamin D contents of foods were gathered from food labels and food composition tables from the United States Department of Agriculture. A vitamin D content database was developed for this study purpose. Dietary intakes while using FFQ and three-day FR were collected from 62 women. Vitamin D intakes from FFQ and three-day FR were validated with quartile comparison and Bland-Altman (BA) tests. BA plot showed an agreement between FFQ and three-day FR vitamin D intakes. The BA index was 3.23%, which is <5%, a commonly used standard for validation. Quartile correlation showed that ?73% of subjects were within the same or adjacent quartile. In conclusion, an agreement was found between vitamin D intakes from FFQ and three-day FR in Qatari women. More studies are needed to validate the vitamin D-specific FFQ in Qatari population at large.
Project description:<h4>Background</h4>There is little information in the literature on methods of food composition database development to calculate nutrient intake from food frequency questionnaire (FFQ) data. The aim of this study is to describe the development of an FFQ and a food composition table to calculate nutrient intake in a Black Zimbabwean population.<h4>Methods</h4>Trained interviewers collected 24-hour dietary recalls (24 hr DR) from high and low income families in urban and rural Zimbabwe. Based on these data and input from local experts we developed an FFQ, containing a list of frequently consumed foods, standard portion sizes, and categories of consumption frequency. We created a food composition table of the foods found in the FFQ so that we could compute nutrient intake. We used the USDA nutrient database as the main resource because it is relatively complete, updated, and easily accessible. To choose the food item in the USDA nutrient database that most closely matched the nutrient content of the local food we referred to a local food composition table.<h4>Results</h4>Almost all the participants ate sadza (maize porridge) at least 5 times a week, and about half had matemba (fish) and caterpillar more than once a month. Nutrient estimates obtained from the FFQ data by using the USDA and Zimbabwean food composition tables were similar for total energy intake intra class correlation (ICC) = 0.99, and carbohydrate (ICC = 0.99), but different for vitamin A (ICC = 0.53), and total folate (ICC = 0.68).<h4>Conclusion</h4>We have described a standardized process of FFQ and food composition database development for a Black Zimbabwean population.
Project description:To address limited food frequency questionnaire (FFQ) capacity in public health monitoring in Malaysia, we aimed to develop a semi-quantitative FFQ for an adult multiethnic population for comprehensive fatty acid (FA) profiling inclusive of saturated (SFA), monounsaturated (MUFA), polyunsaturated fatty acids (PUFA), PUFA:SFA ratio, trans fatty acids, omega-3 and omega-6 FAs. A 240-food itemed FFQ used diet records (DR) of Malaysia Lipid Study (MLS) participants and fatty acid composition database from laboratory analyzed foods. The developed MLS-FFQ underwent face and content validation before relative validation in a free-living population (<i>n</i> = 114). Validation was facilitated for macronutrient data comparisons between DR and FFQ via Spearman's correlation coefficient analyses; and for fatty acid composition data by independent pairing of DR, FFQ and plasma triglyceride using the triads method. Moderate correlation between dietary methods was obtained for macronutrients and FAs (<i>r</i> = 0.225-0.457, <i>p</i> < 0.05) except for ?-3 FAs, presenting good agreement with grossly misclassified nutrients <10%. For fatty acid composition data, the magnitude of validity coefficients (<i>z</i>) for SFA, PUFA, PUFA:SFA ratios and ?-6 FAs by all 3 methods were not significantly different (<i>p</i> > 0.05). In conclusion, the MLS-FFQ was shown to be a valid tool to assess population dietary intakes.
Project description:Qualitative food frequency questionnaires (Q-FFQ) omit portion size information from dietary assessment. This restricts researchers to consumption frequency data, limiting investigations of dietary composition (i.e., energy-adjusted intakes) and misreporting. To support such researchers, we provide an instructive example of Q-FFQ energy intake estimation that derives typical portion size information from a reference survey population and evaluates misreporting. A sample of 1,919 Childhood Determinants of Adult Health Study (CDAH) participants aged 26-36 years completed a 127-item Q-FFQ. We assumed sex-specific portion sizes for Q-FFQ items using 24-h dietary recall data from the 2011-2012 Australian National Nutrition and Physical Activity Survey (NNPAS) and compiled energy density values primarily using the Australian Food Composition Database. Total energy intake estimation was daily equivalent frequency × portion size (g) × energy density (kJ/g) for each Q-FFQ item, summed. We benchmarked energy intake estimates against a weighted sample of age-matched NNPAS respondents (<i>n</i> = 1,383). Median (interquartile range) energy intake was 9,400 (7,580-11,969) kJ/day in CDAH and 9,055 (6,916-11,825) kJ/day in weighted NNPAS. Median energy intake to basal metabolic rate ratios were 1.43 (1.15-1.78) in CDAH and 1.35 (1.03-1.74) in weighted NNPAS, indicating notable underreporting in both samples, with increased levels of underreporting among the overweight and obese. Using the Goldberg and predicted total energy expenditure methods for classifying misreporting, 65 and 41% of CDAH participants had acceptable/plausible energy intake estimates, respectively. Excluding suspected CDAH misreporters improved the plausibility of energy intake estimates, concordant with expected body weight associations. This process can assist researchers wanting an estimate of energy intake from a Q-FFQ and to evaluate misreporting, broadening the scope of diet-disease investigations that depend on consumption frequency data.
Project description:<h4>Background</h4>To investigate the association between dietary components and development of chronic diabetic complications, the dietary evaluation should include a long period, months or years. The present manuscript aims to develop a quantitative food frequency questionnaire (FFQ) and a portfolio with food photos to assess the usual intake pattern of Brazilian patients with type 2 diabetes to be used in future studies.<h4>Methods</h4>Dietary data using 3-day weighed diet records (WDR) from 188 outpatients with type 2 diabetes were used to construct the list of usually consumed foods. Foods were initially clustered into eight groups: "cereals, tubers, roots, and derivatives"; "vegetables and legumes"; "fruits"; "beans"; "meat and eggs"; "milk and dairy products"; "oils and fats", and "sugars and sweets". The frequency of food intake and the relative contribution of each food item to the total energy and nutrient intakes were calculated. Portion sizes were determined according to the 25th, 50th, 75th, and 95th percentiles of intake for each food item.<h4>Results</h4>A total of 62 food items were selected based on the 3-day WDR and another 27 foods or how they are prepared and nine beverages were included after the expert examination. Also, a portfolio with food photos of each included food item and portion sizes was made to assist the patients in identifying the consumed portion.<h4>Conclusions</h4>We developed a practical quantitative FFQ and portfolio with photos of 98 food items covering those most commonly consumed in the past 12 months, to assess the usual diet pattern of patients with type 2 diabetes in Southern Brazil.
Project description:<h4>Background</h4>Food Frequency Questionnaires (FFQs) are commonly used in epidemiologic studies to assess long-term nutritional exposure. Because of wide variations in dietary habits in different countries, a FFQ must be developed to suit the specific population. Sri Lanka is undergoing nutritional transition and diet-related chronic diseases are emerging as an important health problem. Currently, no FFQ has been developed for Sri Lankan adults. In this study, we developed a FFQ to assess the regular dietary intake of Sri Lankan adults.<h4>Methods</h4>A nationally representative sample of 600 adults was selected by a multi-stage random cluster sampling technique and dietary intake was assessed by random 24-h dietary recall. Nutrient analysis of the FFQ required the selection of foods, development of recipes and application of these to cooked foods to develop a nutrient database. We constructed a comprehensive food list with the units of measurement. A stepwise regression method was used to identify foods contributing to a cumulative 90% of variance to total energy and macronutrients. In addition, a series of photographs were included.<h4>Results</h4>We obtained dietary data from 482 participants and 312 different food items were recorded. Nutritionists grouped similar food items which resulted in a total of 178 items. After performing step-wise multiple regression, 93 foods explained 90% of the variance for total energy intake, carbohydrates, protein, total fat and dietary fibre. Finally, 90 food items and 12 photographs were selected.<h4>Conclusion</h4>We developed a FFQ and the related nutrient composition database for Sri Lankan adults. Culturally specific dietary tools are central to capturing the role of diet in risk for chronic disease in Sri Lanka. The next step will involve the verification of FFQ reproducibility and validity.
Project description:OBJECTIVE:Nitrate and nitrite are probable human carcinogens when ingested under conditions that increase the formation of N-nitroso compounds. There have been limited efforts to develop US databases of dietary nitrate and nitrite for standard FFQ. Here we describe the development of a dietary nitrate and nitrite database and its calibration. DESIGN:We analysed data from a calibration study of 1942 members of the NIH-AARP (NIH-AARP, National Institutes of Health-AARP) Diet and Health Study who reported all foods and beverages consumed on the preceding day in two non-consecutive 24 h dietary recalls (24HR) and completed an FFQ. Based on a literature review, we developed a database of nitrate and nitrite contents for foods reported on these 24HR and for food category line items on the FFQ. We calculated daily nitrate and nitrite intakes for both instruments, and used a measurement error model to compute correlation coefficients and attenuation factors for the FFQ-based intake estimates using 24HR-based values as reference data. RESULTS:FFQ-based median nitrate intake was 68·9 and 74·1 mg/d, and nitrite intake was 1·3 and 1·0 mg/d, in men and women, respectively. These values were similar to 24HR-based intake estimates. Energy-adjusted correlation coefficients between FFQ- and 24HR-based values for men and women respectively were 0·59 and 0·57 for nitrate and 0·59 and 0·58 for nitrite; energy-adjusted attenuation factors were 0·59 and 0·57 for nitrate and 0·47 and 0·38 for nitrite. CONCLUSIONS:The performance of the FFQ in assessing dietary nitrate and nitrite intakes is comparable to that for many other macro- and micronutrients.
Project description:Dietary record tools such as food frequency questionnaire (FFQ) and food diaries (FD) are the most commonly used choices for assessing dietary intakes in most large-scale epidemiological studies. The authors developed a self-administered 360-item food frequency questionnaire (FFQ) to assess dietary intakes amongst a population-based cohort in South Kerala. In the validation study (n = 460), the data were collected using FFQs that were administered on three different occasions which were then compared to 7-day food records. The intake of foods and nutrients was higher as determined by the FFQ than that assessed using food records. Spearman correlations for macro-nutrients ranged from 0.72 for protein to 0.61 for carbohydrates and for micronutrients, from 0.71 for vitamin B6 to 0.34 for magnesium. The correlation was improved with energy-adjusted nutrient intakes. On average, the exact agreement for the macronutrients ranged from 48.2% to 57.1%, and that for micronutrients ranged from 66.7% to 41.9%, with the median percentage of 49.58%. The authors conclude that the FFQ has an acceptable reproducibility, however, there was a systematic trend towards higher estimates with the FFQ for most nutrients compared to the FD records.
Project description:BACKGROUND:In Asia, little is known about how maternal feeding practices are associated with dietary intakes and body mass index (BMI) in preschoolers. OBJECTIVE:To assess the relationships between maternal feeding practices with dietary intakes and BMI in preschoolers in Asia using cross-sectional analysis in the GUSTO (Growing Up in Singapore Towards healthy Outcomes) cohort. PARTICIPANT SETTINGS:Mothers (n = 511) who completed the Comprehensive Feeding Practices Questionnaire (CFPQ) and a semi-quantitative Food Frequency Questionnaire (FFQ) when children were 5 years old. STATISTICAL ANALYSIS:Associations between 12 maternal feeding practices (mean scores divided into tertiles) and children's dietary intakes of seven food groups and BMI z-scores were examined using the general linear regression model. Weight and height of the child were measured, and dietary intakes derived from the FFQ. RESULTS:Compared to those in the low tertile, mothers in the high tertile of modelling healthy food intakes had children with higher intakes of vegetables[+20.0g/day (95%CI:11.6,29.5)] and wholegrains[+ 20.9g/day (9.67,31.1)] but lower intakes of sweet snacks[-10.1g/day (-16.3,-4.94)] and fast-foods[-5.84g/day (-10.2,-1.48)]. Conversely, children of mothers in the high tertile for allowing child control (lack of parental control) had lower intake of vegetables[-15.2g/day (-26.6,-5.21)] and wholegrains[-13.6g/day (-22.9,-5.27)], but higher intakes of sweet snacks[+13.7g/day (7.7, 19.8)] and fast-foods[+6.63g/day (3.55,9.72)]. In relation to BMI at 5 years, food restrictions for weight was associated with higher BMI z-scores [0.86SD (0.61,1.21)], while use of pressure was associated with lower BMI z-scores[-0.49SD(-0.78,-0.21)]. CONCLUSIONS AND IMPLICATIONS:Modelling healthy food intakes by mothers was the key feeding practice associated with higher intakes of healthy foods and lower intakes of discretionary foods. The converse was true for allowing child control. Only food restrictions for weight and use of pressure were associated with BMI z-scores.
Project description:Empirical prediction models that weight food frequency questionnaire (FFQ) food items by their relation to nutrient biomarker concentrations may estimate nutrient exposure better than nutrient intakes derived from food composition databases. Carotenoids may especially benefit because contributing foods vary in bioavailability and assessment validity. Our objective was to develop empirical prediction models for the major plasma carotenoids and total carotenoids and evaluate their validity compared with dietary intakes calculated from standard food composition tables. 4180 nonsmoking women in the Nurses' Health Study (NHS) blood subcohort with previously measured plasma carotenoids were randomly divided into training (n = 2787) and testing (n = 1393) subsets. Empirical prediction models were developed in the training subset by stepwise selection from foods contributing ?0.5% to intake of the relevant carotenoid. Spearman correlations between predicted and measured plasma concentrations were compared to Spearman correlations between dietary intake and measured plasma concentrations for each carotenoid. Three to 12 foods were selected for the ?-carotene, ?-carotene, ?-cryptoxanthin, lutein/zeaxanthin, lycopene, and total carotenoids prediction models. In the testing subset, Spearman correlations with measured plasma concentrations for the calculated dietary intakes and predicted plasma concentrations, respectively, were 0.31 and 0.37 for ?-carotene, 0.29 and 0.31 for ?-carotene, 0.36 and 0.41 for ?-cryptoxanthin, 0.28 and 0.31 for lutein/zeaxanthin, 0.22 and 0.23 for lycopene, and 0.22 and 0.27 for total carotenoids. Empirical prediction models may modestly improve assessment of some carotenoids, particularly ?-carotene and ?-cryptoxanthin.