We agree with Murphy and O’Connor that alignment of dietary assessment tools with the purposes, populations, and settings to which they are applied and an evidence-based understanding of tools’ strengths and limitations are crucial to support appropriate use and interpretation.
1
,2
As recognized by Murphy and O’Connor, each administration of a short-term tool, such as a 24-hour recall or food record, captures intake on a single day, or a small number of days in the case of multiple-day records. With repeat administrations and the application of statistical methods,3
data from these tools can be used to estimate distributions of usual intake in both surveillance and epidemiologic research. The design of surveillance systems has embraced this method; for example, the US Department of Agriculture administers two 24-hour recalls to National Health and Nutrition Examination Survey participants4
and makes use of statistical modeling to estimate distributions of usual intakes among subgroups of Americans.5
Within epidemiologic research, evidence indicates that multiple administrations of these tools in long-term cohort studies is superior to food frequency questionnaires (FFQs) alone for capturing intake, with the potential to use emerging statistical models to estimate how time-varying intake relates to disease outcomes.6
Data from tools such as FFQs that rely on the respondent to average usual intake over a period of time, often the past year, are less amenable to such analyses.The ability of 24-hour recalls and food records to measure contextual details associated with intake is a strength that sets them apart from FFQs. For example, multiple-pass methods such as the Automated Multiple-Pass Method
7
enable analysis of meal and snack patterning as well as sources (eg, supermarket, restaurant) of foods and beverages. Short-term tools also can capture where and with whom eating occasions occurred and activities such as the use of digital devices while eating. Data from FFQs may allow for examinations of clustering of foods and beverages but do not provide extensive opportunities to investigate other contextual factors.Food frequency questionnaires must be tailored to the eating patterns of the respondent population.
1
Conversely, recalls and records are designed to allow respondents to report any and all foods and beverages consumed, even those not identified by the researcher a priori. In the case of online recalls and records that integrate search capabilities, adaptations may be needed to tailor the foods and beverages listed to the food supplies available to different populations. For example, the Automated Self-Administered 24-hour Dietary Assessment Tool8
was developed for the United States but has been adapted to the food supplies in Canada and Australia, with an identical user interface across countries. Because they are collected by using consistent methods, harmonizing short-term intake data from such systems is relatively straightforward, whereas harmonizing data from distinct FFQs that capture different sets of foods and beverages using varied time frames, frequency responses, and portion size probes can be challenging.The debate between short-term and long-term tools is one that has been ongoing for some time.
9
Biomarker-based validation studies show that estimates of absolute intake from 24-hour recalls and food records are less affected by bias as compared with data from FFQs.10
, 11
, 12
Given their long-term focus, FFQs can, however, provide useful insights into dietary components consumed episodically, such as fish. Thus, neither self-report assessment method should be abandoned. Researchers and practitioners need to identify the best method(s) for a given purpose,1
,2
which may involve using multiple tools in combination to leverage strengths and minimize limitations.13
,14
As Murphy and O’Connor noted, ensuring that tools are culturally appropriate is important in identifying the best assessment strategy. Furthermore, assessing the suitability of a given tool should consider equivalence across populations or cultural appropriateness for a given population.1
,2
References
- Best practices for conducting and interpreting studies to validate self-report dietary assessment methods.J Acad Nutr Diet. 2019; 119: 1801-1816
- Establishing validity and cross-context equivalence of measures and indicators.J Acad Nutr Diet. 2019; 119: 1817-1830
- Statistical methods for estimating usual intake of nutrients and foods: a review of the theory.J Am Diet Assoc. 2006; 106: 1640-1650
- National Health and Nutrition Examination Survey.(Revised December 26, 2019. Accessed February 14, 2020)
- What We Eat In America usual intake data tables.(Revised January 29, 2020. Accessed February 14, 2020)
- A statistical model for measurement error that incorporates variation over time in the target measure, with application to nutritional epidemiology.Stat Med. 2015; 34: 3590-3605
- The US Department of Agriculture Automated Multiple-Pass Method reduces bias in the collection of energy intakes.Am J Clin Nutr. 2008; 88: 324-332
- The Automated Self-Administered 24-hour dietary recall (ASA24): a resource for researchers, clinicians, and educators from the National Cancer Institute.J Acad Nutr Diet. 2012; 112: 1134-1137
- Abandon neither the food frequency questionnaire nor the dietary fat-breast cancer hypothesis.Cancer Epidemiol Prev Biomarkers. 2007; 16: 1321-1322
- Pooled results from 5 validation studies of dietary self-report instruments using recovery biomarkers for energy and protein intake.Am J Epidemiol. 2014; 180: 172-188
- Pooled results from 5 validation studies of dietary self-report instruments using recovery biomarkers for potassium and sodium intake.Am J Epidemiol. 2015; 181: 473-487
- Evaluation and comparison of food records, recalls, and frequencies for energy and protein assessment by using recovery biomarkers.Am J Epidemiol. 2011; 174: 591-603
- Taking advantage of the strengths of 2 different dietary assessment instruments to improve intake estimates for nutritional epidemiology.Am J Epidemiol. 2012; 175: 340-347
- Combining a food frequency questionnaire with 24-hour recalls to increase the precision of estimation of usual dietary intakes: evidence from the Validation Studies Pooling Project.Am J Epidemiol. 2018; 187: 2227-2232
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STATEMENT OF POTENTIAL CONFLICT OF INTEREST There are no conflicts of interest to report.
FUNDING/SUPPORT The authors have no funding to declare specific to this paper.
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- Dietary Assessment Methodology in Response to November 2019 IssueJournal of the Academy of Nutrition and DieteticsVol. 120Issue 6
- PreviewThe November 2019 issue of JAND neatly frames the issues surrounding the methods by which researchers measure food intake and dietary patterns. Kirkpatrick and colleagues’ article, “Best Practices for Conducting and Interpreting Studies to Validate Self-Report Dietary Assessment Methods,”1 sets a framework for the remainder of the issue, which includes assessment and associations of specific nutrient and diet patterns in the United States,2 Korea,3 Mexico,4 Brazil,5 and China,6 as well as knowledge translation in Switzerland.
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