Errors in the interpretation of dietary assessments

Abstract

Two years ago, I reviewed the analytic effect of error in the estimation of dietary intake, describing the emphasis on the "random" day-to-day variation in reported intake. Interest in this area is increasing and there are signs of progress in analytic strategies. This paper focuses on two concerns about the use of dietary data in analyses. The effect of different methods of adjusting analyses of fat and a health outcome for energy is illustrated through an exploration of the association between fat intake and high body mass index in data sets from the US Department of Agriculture and a Dutch national survey. Both a shift in the analytic question and a change in the error structure occur as analysis strategies are changed, leading to confusion in interpretation. The paper also addresses the growing concern about bias in the estimation of intake and the possibility that differential bias moves with stratification variables of analytic interest. The increasing use of doubly labeled water estimates of energy expenditure as a gold standard for checking on overall bias in reporting is commendable. There will always be error in dietary assessments. The challenge is to understand, estimate, and make use of the error structure during analysis.

Dietary energy density as a marker of dietary quality in Swedish children and adolescents: the European Youth Heart Study

“…The relatively large sample size and the use of both an objective and subjective method of identifying recalls of potentially lower quality are strengths of this study. The limitations of 24-h recalls in capturing habitual intake at the individual level are well known (Bingham, 1991;Beaton et al, 1997), because of the large day-to-day variation in intake that exists. However, for the purpose of this study, a 24-h recall on a reasonably large group, with no obvious bias, was deemed appropriate to show an association with energy density and dietary quality.…”

Minimizing random error in dietary intakes assessed by 24-h recall, in overweight and obese adults

“…Random error is an inherent part of dietary intake measurement, evident as the day-to-day variation in dietary intake both within (intra-) and between (inter-) individuals (Bingham, 1991;Beaton et al, 1997;Grunwald et al, 2003;Palaniappan et al, 2003). Although intra-individual variation will have a component of day-to-day variation distinctive to each individual, between individual differences in dietary intake will also occur.…”

“…The multiple-day, multiple-pass, 24-h dietary recall method was chosen for the current study. Compared with single-day 24-h recalls, multiple-day food intake records (food diaries) and weighed food records, this method of dietary data collection is currently accepted as a more accurate measurement of true intake among respondents (Bingham, 1991;Bingham et al, 1994;Beaton et al, 1997;Hebert et al, 1997;Vuckovic et al, 2000;Dodd et al, 2006), particularly if the day and time of the recall is unannounced (Johnson, 2002).…”

Fat intake is more strongly associated with lifestyle factors than with socio-economic characteristics, regardless of energy adjustment approach

“…Also, the calculated intakes of other macronutrients may differ depending on how fat intake is de®ned (Macdiarmid et al, 1996). Furthermore, it is not clear how results obtained with risk assessment models, using other de®nitions of fat intake, should be translated into nutrient recommendations expressed in energy percentage from fat (Beaton et al, 1997).…”