Best Practice Guidelines
Please start by clicking on Define and follow the guidelines using the tick boxes to find the most appropriate tools for your research.
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Define:
Define what you want to measure in terms of dietary intake
- What? – Characteristics of the main dietary component of interest.
- Who? – Considerations around the characteristics of study participants.
- When? – Time frame considerations.
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Investigate:
Investigate the different types of Dietary Assessment Tools (DATs) and their suitability for your research question
- Consider and appraise the different DAT types.
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Evaluate:
Evaluate existing tools to fine-tune your choice of most appropriate Dietary Assessment Tool (DAT)
- Research and evaluate available tools of interest.
- If, based on the validation studies, none of the existing DATs are entirely or wholly suitable, consider the need to modify or update an existing DAT, or create a de novo (new) DAT, and evaluate it.
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Think Through:
Think through the implementation of your chosen Dietary Assessment Tools (DATs)
- Consider issues relating to the chosen DAT and the measurement of your dietary component of interest.
- Prepare an implementation plan to reduce potential biases when using your chosen DAT.
Define what you want to measure in terms of dietary intake - the key a priori considerations to guide your choice of the appropriate type of Dietary Assessment Tool (DAT).
- What? - Characteristics of the main dietary component of interest.
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Clearly define what needs to be measured (e.g. intake of energy; food groups; specific or a range of macro- or micro-nutrients).
Diet is usually described in terms of nutrient content, the food type or food group, or dietary pattern. Consider which of these you need in your study. Some nutrients are assessed more accurately than others; foods consumed in discrete amounts or consumed regularly are easier to report than infrequently consumed items.
Estimates of food and nutrient intake involve random error (e.g. due to limited food tables, recall error) and systematic bias (e.g. low energy reporters under-estimate foods high in fats and sugars).
A clear definition is needed of what is to be measured and the level of detail required, e.g. for energy intake the whole diet needs to be assessed but for nutrients concentrated in some foods an assessment of specific foods may be sufficient.
- Dietary Exposure
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Available Tools: out of 153
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Determine how the dietary data will be analysed and presented (e.g. total daily or meal level intakes; food groups or nutrients).
Diet can be presented in terms of composition (macro- and micro-nutrients, as well as other food constituents); food consumption and adherence to dietary patterns and guidelines.
The level of dietary information required will determine the type of DATs to be used. For example, if the aim is to assess nutrient intake over the whole day, a more detailed and extensive DAT will be required than if people’s eating patterns, such as breakfast consumption, snacks, or skipping meals is needed.
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- Who? - Considerations around the characteristics of study participants.
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Define the target sample in terms of characteristics (e.g. life stage; ethnicity; health status; BMI; socio-economic level; country/region and setting - home, school, hospital).
The target sample needs to be defined in terms of their age, ethnicity, BMI and other characteristics. It is important to assess whether the participant will be able to self-report dietary intake or whether a parent/proxy will be required.
For instance, assessing diet among young children or adolescents requires different methods due to their eating habits, ability to report dietary intake, as well as their motivation. Similarly, assessing diet in different ethnic groups is likely to require different FFQs that include specific foods.
- Lifestage
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Available Tools: out of 153
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Identify other issues that could affect the choice of DAT (e.g. literacy, numeracy, language, cultural, disability, time or familiarity with technology).
A DAT needs to be usable by the study population. Use of new technology to assess dietary intake is promising for children, adolescents and adults, as it can be faster and easier than the traditional methods.
However, some level of technological literacy and numeracy is required which might hinder use among older adults and participants with low literacy level. Self-administered dietary recall relies on memory, which is subject to a variety of errors.
- Format
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Available Tools: out of 153
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Consider the study sample size required in relation to the level of variation of your dietary component of interest and study power.
The sample size will depend on the characteristics of the dietary component to be measured. It needs to be large enough to provide precise estimates and have sufficient statistical power to detect any effects or associations of interest.
Intra-individual variation (variance in nutrient content from day to day in amount and in type of food consumed) and inter-individual variation (variations between persons in their usual nutrient intake averaged over time) in nutrient intake is important, and varies for different nutrients.
Nutrients with lower day-to-day variation are likely to require fewer days of recording diet in comparison with nutrients that are only eaten occasionally. If you are unsure how to calculate sample size, consult a statistician.
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- When? - Time frame considerations.
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Are you interested in ’actual’/short-term e.g. hours or several days, up to one week or ‘usual’/long term intake e.g. months or years. Consider what reference period e.g. daily, weekly, monthly, yearly would be best suited to your dietary component of interest.
Long-term average intake or the usual/habitual pattern differs from intake reported for a single day or a few days. Short term intake (e.g. over a single day) is also referred to as actual or acute intake.
Any short-term instrument, such as a 24HR, only represents a snapshot in time but may provide less biased dietary data than other methods. More than one day of dietary information is usually needed to estimate usual intake, and non-consecutive days may be preferable to capture more of the variability in an individual’s diet.
- Timeframe Tool Measures
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Available Tools: out of 153
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Will data collection in your study be retrospective or prospective?
Whether your study has a retrospective (the outcome has already occurred) or prospective design (the outcome is measured over time) determines the type of DATs that are suitable for use.
A cross-sectional survey is commonly used to obtain a ‘snapshot’ of the diet of a population at a specific point in time. A range of DATs may be suitable, depending on the level of detail and accuracy required. For example, a 4-day prospective diary is used in the National Diet and Nutrition Survey in the UK.
However local surveillance of diet for public health may use retrospective FFQs due to lower cost and ease of implementation.
- Reporting Method
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Available Tools: out of 153
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Investigate the different types of Dietary Assessment Tools (DATs) and their suitability for your research question.
- Consider and appraise the different Dietary Assessment Tools (DATs) types.
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In relation to your research question, consider the suitability, strengths and weaknesses of different DAT types.
Several approaches for self-administered instruments have been developed to assess dietary intake: food diaries, recalls, questionnaires, screeners and diet history. Each has distinct features and strengths and weaknesses.
At this stage, if you are new to dietary assessment methods explore each DAT’s profile, to learn about the different DATs. Then evaluate the suitability of using each method based on your research questions and study target group.
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Think about participant burden (e.g. study participants’ potential willingness, ability, ethical considerations, interest in using different tools and access issues associated with different DATs).
Reducing participant burden is important to ensure high participation rates, reduce attrition and minimise measurement error by minimising reactivity bias (participants changing their dietary behaviour during the study period).
Careful integration of the dietary method into the study will help. One method of reducing burden relates to portion size estimation, foods need not be weighed but portions could be estimated using food photographs or described in household measures.
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Identify the availability of resources (e.g. staff skill, time, finances).
It is important to consider the level of training and/or expertise required by staff to implement and analyse the selected DAT. Adequate training of the field researcher will help to produce reliable dietary intake measurements. Manual coding of recalls/diaries is expensive and time consuming.
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Evaluate existing tools to select the most appropriate Dietary Assessment Tool (DAT).
- Research and evaluate available tools of interest.
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Read any available published validation studies and determine the extent to which:
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Has the DAT been evaluated to measure the dietary component you are interested in?
When possible, validated DATs should be used, however the validation should be relevant to the foods/nutrients of interest in your study. Therefore DATs which have measured but not validated the specific nutrients of interest in your study should not be considered or may require additional validation.
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Has the DAT been evaluated in a population similar to your population of interest?
It is important that the DAT is able to provide valid estimates in a similar population to your study population. We therefore recommend reading any validation studies conducted on this DAT, and determine whether these studies support the use of the candidate DAT for your study population.
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Is the nutrient database used appropriate?
The nutrient database you use should be appropriate, comprehensive, and up-to-date for the study population. The relative importance of errors (e.g. limited coverage of food items in the database, missing data for some nutrients, differences in the use of software packages, incompatibility of databases, recipe, portion size allocations and bias in variability in recipes) should be considered.
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Are the portion sizes used relevant?
It is important to accurately estimate food portion sizes to obtain a true report of dietary intake. Materials such as food photographs or food models can be provided, however these only provide a limited number of foods and food portion sizes.
Portion sizes should be relevant to study population characteristics and life stage. The type of food will influence reliability of portion size estimation; pre-packaged foods will have a weight declared which could be recorded.
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Assess the quality of validation in terms of:
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Has the DAT been compared to an objective method (e.g. biomarker)?
Objective methods to assess nutrient intake includes clinical indicators or biomarkers, which are constituents in the blood or urine that vary in response to intake.
Biomarkers can reflect intake over short-term (past hours/days), medium-term (weeks/months) and long-term (months/years), the time will depend on the type of sample used e.g. blood, hair.
Ideally all DATs should be validated against an objective measure of intake. Recovery biomarkers (eg. urinary nitrogen, potassium and doubly labelled water) reflect absolute nutrient intake over a short period of time.
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Has the DAT been compared to a subjective method (e.g. a different self-reported diet assessment)?
Many dietary tools are validated by comparison with an alternative form of dietary assessment, referred to as ‘relative validity’. However comparison of one DAT against another may be problematic due to the risk of correlated error between dietary assessment methods. It is desirable that any new dietary assessment be calibrated against more established ‘gold standard’ dietary assessment methods.
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What were the limitations of the validation study?
The comparison DAT used in the validation study also needs to be assessed in terms of scope, the time frame/number of days, the main type of measurement error, memory requirements, together with an assessment of cognitive difficulty.
For an FFQ that is being validated, the agreement with an alternative method will be higher if more days of reference data have been collected rather than using a single day of dietary measurement.
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The strength of agreement between the two methods:
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Is there any evidence of bias; do the methods agree on average?
It is important to understand the measurement errors of DATs through validation/calibration studies before selecting a DAT. One aspect of this is the extent to which a DAT under or over-estimates dietary intake compared to another, possibly better, DAT.
Such under or over-estimation would present a biased estimate of intake compared to the other tool, because on average one tool would have lower or higher estimates than the other.
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Is there any evidence of imprecision; how closely do the methods agree for an individual?
Precision provides a measure of the closeness of two different methods for estimating dietary intake for the individual, assessed over the whole sample.
A DAT is considered precise if the estimated intake from the tool is close to the estimate from the reference tool for each individual, taking account of any bias on average.
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- If, based on the validation studies, none of the existing DATs are entirely or wholly suitable, consider the need to modify or update an existing DAT, or create a new DAT, and evaluate it.
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Decide whether an existing tool can be improved. Investigate whether:
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Foods and portion sizes included are characteristic of your target population; and frequency categories are appropriate.
Food consumption patterns change over time, influenced by income and socio-cultural preferences, thus the DAT should be applicable to the population of study. Investigate whether the portion sizes used in the DAT are current portion sizes used in the study population.
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The time period that the questionnaire refers to could be modified to better suit your needs.
The time period the FFQ measures could be modified to better suit the research interest however this must be done with caution as this could affect the validity of the tool and may require the FFQ to be revalidated.
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Consider the face validity of existing tools. Is there evidence the tool has been used to measure dietary intake in your population of interest?
Face validity indicates whether results for the food or nutrient being measured are sensible. It is important to check face validity to ensure usability and adequate response rate.
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Updated or modified tools may require re-evaluation. Consider if validation can be integrated into your study.
If you plan to update or modify the DAT, such as the food list or food portion sizes then the tool should ideally be re-evaluated in another validation study.
When designing a new FFQ, obtain lists and portion sizes of the most important foods and the percentage of foods contributing to nutrients of interest in your population, for example, from national surveys.
Next Step - select your DAT.
The selection of the DAT will depend upon the purpose of your study; whether it is to capture regular eating patterns (e.g. FFQ or repeated 24HR) or recent food consumed (e.g. diet record or 24HR) and what is being assessed.
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Think through the implementation of your chosen Dietary Assessment Tools (DATs).
- Consider issues relating to the chosen DAT and the measurement of your dietary component of interest.
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Obtain information regarding DAT logistics (e.g. tool manual, relevant documents and other requirements from the DAT developer).
The researcher may have to contact the DAT owner to obtain the manual and relevant documents for using the DAT.
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Check that the chosen DAT has the most appropriate food/nutrient database and software.
An important pre-condition in selection of a DAT is an up to date, relevant nutrient database. Nutrient databases may be incomplete for some nutrients; however it may be adequate for the analysis of other nutrients of interest.
Evaluate which year the nutrient database refers to and whether there have been any updates.
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Check the requirements for dietary data collection (e.g. entry, coding and software).
It is crucial to check the requirements for dietary data entry. If a recipe was recorded, consider how to handle it. Ingredients may be entered individually or the food directly entered.
Conversion factors can also be used, for example from raw to cooked weights or from grams to volume, using specific gravity.
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Consider collecting additional related data (e.g. was intake typical; supplement use).
For acute measures of diet (24HR) participants should ideally be asked if the day of recording was typical and, if not, why not. DATs may gather additional information on dietary supplement intake.
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- Prepare an implementation plan to reduce potential biases when using your chosen DAT.
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Considering potential sampling/selection bias and track non-participation/dropout/withdrawal at different stages.
Researchers should minimise selection bias, and non-response bias using an appropriate sample size from the target population ensuring that participants are representative of the wider population.
Engaging the interest of participants prior to the study, may prevent dropouts that can affect the generalizability of findings.
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Minimise interviewer bias (e.g. ensure staff qualifications and training are appropriate; develop standardised training protocols and monitoring procedures).
If you decide to interview participants, such as an interview-administered 24HR, appropriate training of staff will reduce interviewer bias. Interviewers need knowledge to correctly identify, describe and check foods.
Question wording, probing questions, and an ability to establish a good relationship with the respondent can all influence the quality of the data collected.
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Minimise respondent biases (e.g. use prompts, clear instructions).
Social desirability bias is common. Under-reporters tend to be selective, by reporting fewer servings from food groups with higher energy densities. Prompt questions and reminders can be included to minimise likely omissions.
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Quantify misreporting.
It is essential to identify and minimise potential misreporting. Misreporting is a complex problem in dietary assessment that comprises both under and over reporting which introduce sources of error in the estimation of energy intake and nutrients.
A reasonable approach to identify under-reporters is the application of the Goldberg equation during analysis. However, it is worth noting that the use of this method may also lead to bias or misclassification because of the assumptions used to estimate total energy expenditure.
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