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ObjectiveA wide variety of methods are available to assess dietary intake, each one with different strengths and weaknesses. Researchers face multiple challenges when diet and nutrition need to be accurately assessed, particularly in the selection of the most appropriate dietary assessment method for their study. The goal of the current collaborative work is to present a collection of available resources for dietary assessment implementation.Design/Setting/ParticipantsAs a follow-up to the 9th International Conference on Diet and Physical Activity Methods held in 2015, developers of dietary assessment toolkits agreed to collaborate in the preparation of the present paper, which provides an overview of each toolkit. The toolkits presented include: the Diet, Anthropometry and Physical Activity Measurement Toolkit (DAPA; UK); the National Cancer Institute’s (NCI) Dietary Assessment Primer (USA); the Nutritools website (UK); the Australasian Child and Adolescent Obesity Research Network (ACAORN) method selector (Australia); and the Danone Dietary Assessment Toolkit (DanoneDAT; France). An at-a-glance summary of features and comparison of the toolkits is provided.ResultsThe present review contains general background on dietary assessment, along with a summary of each of the included toolkits, a feature comparison table and direct links to each toolkit, all of which are freely available online.ConclusionsThis overview of dietary assessment toolkits provides comprehensive information to aid users in the selection and implementation of the most appropriate dietary assessment method, or combination of methods, with the goal of collecting the highest-quality dietary data possible.

Most large prospective cohorts use an FFQ to measure dietary intake. It is well known that an FFQ has substantial measurement error that can affect the results of such studies, leading to bias and the loss of power to detect diet–disease relationships(1,2). In order to evaluate the measurement error in an FFQ, and to correct observed diet–disease relationships for bias due to measurement error, many cohort studies include calibration sub-studies in which another, less biased, dietary instrument is administered as a reference instrument. The reference instrument is usually a short-term instrument such as a 24 h dietary recall (24HR) or food record. Methods for evaluating an FFQ’s ability to measure foods/nutrients that are consumed daily have been developed based on measurement error models that explicitly or implicitly assume that true usual intake and reported intake from the FFQ and reference instrument are all continuous variables(3–5). These methods have sometimes been used to evaluate ‘episodically consumed’ foods, or foods that are not consumed nearly every day by almost everyone in the population(6–8). This can be problematic if the reference instrument covers only a short time period, since short-term instruments may have a substantial proportion of subjects reporting zero intake of an episodically consumed food, violating the assumption that the reported intake is continuous. Recently, a measurement error model for episodically consumed foods has been developed and used in dietary surveillance to estimate population distributions of usual intakes of such foods(9–11) and to correct for measurement error in diet–health relationships when the 24HR is the main dietary instrument(12). The model allows for nonconsumption on a given day by separating the probability to consume from the amount consumed on a consumption day using a two-part model(9). The model has also been extended to a ‘three-part’ model to estimate the joint distribution of intakes of an episodically consumed food and energy(10). In the present paper, we use these models to evaluate an FFQ’s ability to measure intake of episodically consumed foods when the reference instrument measures short-term intake. After fitting a model that describes the relationship between the short-term reference and the FFQ, we use Monte Carlo methods to estimate the relationship between true and FFQ-reported intakes. In 1995, the National Institutes of Health (NIH) and the AARP, formerly the American Association of Retired Persons, initiated a large prospective cohort study called the NIH–AARP Diet and Health Study, which was designed to study relationships between diet and cancer. The study uses an FFQ to measure diet and includes a calibration sub-study of about 2000 subjects who in addition to the FFQ were administered two 24HR. Thompson et al.(13) evaluated the ability of the NIH–AARP FFQ to measure nutrient intake. In the present paper we assess the FFQ’s ability to measure intakes of twenty-nine food groups.

Objective: To test the effect of image size and presence of size cues on the accuracy of portion size estimation by children. Design: Children were randomly assigned to seeing images with or without food size cues (utensils and checked tablecloth) and were presented with sixteen food models (foods commonly eaten by children) in varying portion sizes, one at a time. They estimated each food model’s portion size by selecting a digital food image. The same food images were presented in two ways: (i) as small, graduated portion size images all on one screen or (ii) by scrolling across large, graduated portion size images, one per sequential screen. Setting: Laboratory-based with computer and food models. Subjects: Volunteer multi-ethnic sample of 120 children, equally distributed by gender and ages (8 to 13 years) in 2008–2009. Results: Average percentage of correctly classified foods was 60?3 %. There were no differences in accuracy by any design factor or demographic characteristic. Multiple small pictures on the screen at once took half the time to estimate portion size compared with scrolling through large pictures. Larger pictures had more overestimation of size. Conclusions: Multiple images of successively larger portion sizes of a food on one computer screen facilitated quicker portion size responses with no decrease in accuracy. This is the method of choice for portion size estimation on a computer.

ObjectiveWe evaluated the performance of the food-frequency questionnaire (FFQ) administered to participants in the US NIH–AARP (National Institutes of Health–American Association of Retired Persons) Diet and Health Study, a cohort of 566 404 persons living in the USA and aged 50–71 years at baseline in 1995.DesignThe 124-item FFQ was evaluated within a measurement error model using two non-consecutive 24-hour dietary recalls (24HRs) as the reference.SettingParticipants were from six states (California, Florida, Pennsylvania, New Jersey, North Carolina and Louisiana) and two metropolitan areas (Atlanta, Georgia and Detroit, Michigan).SubjectsA subgroup of the cohort consisting of 2053 individuals.ResultsFor the 26 nutrient constituents examined, estimated correlations with true intake (not energy-adjusted) ranged from 0.22 to 0.67, and attenuation factors ranged from 0.15 to 0.49. When adjusted for reported energy intake, performance improved; estimated correlations with true intake ranged from 0.36 to 0.76, and attenuation factors ranged from 0.24 to 0.68. These results compare favourably with those from other large prospective studies. However, previous biomarker-based studies suggest that, due to correlation of errors in FFQs and self-report reference instruments such as the 24HR, the correlations and attenuation factors observed in most calibration studies, including ours, tend to overestimate FFQ performance.ConclusionThe performance of the FFQ in the NIH–AARP Diet and Health Study, in conjunction with the study’s large sample size and wide range of dietary intake, is likely to allow detection of moderate (≥1.8) relative risks between many energy-adjusted nutrients and common cancers.

Background and objectiveDespite assumed similarities in Canadian and US dietary habits, some differences in food availability and nutrient fortification exist. Food-frequency questionnaires designed for the USA may therefore not provide the most accurate estimates of dietary intake in Canadian populations. Hence, we undertook to evaluate and modify the National Cancer Institute's Diet History Questionnaire (DHQ) and nutrient database.MethodsOf the foods queried on the DHQ, those most likely to differ in nutrient composition were identified. Where possible these foods were matched to comparable foods in the Canadian Nutrient File. Nutrient values were examined and modified to reflect the Canadian content of minerals (calcium, iron, zinc) and vitamins (A, C, D, thiamin, riboflavin, niacin, B6, folate and B12). DHQs completed by 13 181 Alberta Cohort Study participants aged 35–69 years were analysed to estimate nutrient intakes using the original US and modified versions of the DHQ databases. Misclassification of intake for meeting the Dietary Reference Intake (DRI) was determined following analysis with the US nutrient database.ResultsTwenty-five per cent of 2411 foods deemed most likely to differ in nutrient profile were subsequently modified for folate, 11% for vitamin D, 10% for calcium and riboflavin, and between 7 and 10% for the remaining nutrients of interest. Misclassification with respect to meeting the DRI varied but was highest for folate (7%) and vitamin A (7%) among men, and for vitamin D (7%) among women over 50 years of age.ConclusionErrors in nutrient intake estimates owing to differences in food fortification between the USA and Canada can be reduced in Canadian populations by using nutrient databases that reflect Canadian fortification practices.

Objectives:We describe the methods used to develop and score a 17-item ‘screener’ designed to estimate intake of fruit and vegetables, percentage energy from fat and fibre. The ability of this screener and a food-frequency questionnaire (FFQ) to measure these exposures is evaluated.Design:Using US national food consumption data, stepwise multiple regression was used to identify the foods to be included on the instrument; multiple regression analysis was used to develop scoring algorithms. The performance of the screener was evaluated in three different studies. Estimates of intakes measured by the screener and the FFQ were compared with true usual intake based on a measurement error model.Setting:US adult population.Subjects:For development of instrument,n= 9323 adults. For testing of instrument, adult men and women in three studies completing multiple 24-hour dietary recalls, FFQ and screeners,n= 484, 462 and 416, respectively.Results:Median recalled intakes for examined exposures were generally estimated closely by the screener. In the various validation studies, the correlations between screener estimates and estimated true intake were 0.5–0.8. In general, the performances of the screener and the full FFQ were similar; estimates of attenuation were lower for screeners than for full FFQs.Conclusions:When coupled with appropriate reference data, the screener approach described may yield useful estimates of intake, for both surveillance and epidemiological purposes.