Design aspects of 24 h recall assessments may affect the estimates of protein and potassium intake in dietary surveys

Abstract

Objective: To evaluate the impact of different modes of administration (face-toface v. telephone), recall days (first v. second), days of the week (weekday v. weekend) and interview days (1 d later v. 2 d later) on bias in protein and K intakes collected with 24 h dietary recalls (24-HDR).Design: Two non-consecutive 24-HDR (collected with standardised EPIC-Soft software) were used to estimate protein and K intakes by a face-to-face interview at the research centres and a telephone interview, and included all days of the week. Two 24 h urine collections were used to determine biomarkers of protein and K intake. The bias in intake was defined as the ratio between the 24-HDR estimate and the biomarker. Setting: Five centres in Belgium,

Impact of long-term use of oral nutritional supplement on nutritional adequacy, dietary diversity, food intake and growth of Filipino preschool children

“…two 24-h recalls at post-baseline visits may result in less comparable dietary intake data between baseline and post-baseline visits. In addition, as suggested by other authors, subsequent dietary recalls may be affected by a ‘learning effect’ where respondents overestimate food consumption on the first administration and become more familiar with the recall procedure leading to more accurate estimates of the food intake on subsequent administration ( 38 , 39 ) . However, the post-baseline improvement in dietary intake is in accordance with the improvement in growth and other observed health benefits, suggesting that a single 24-h recall at baseline provided a relative measure of dietary intake representing the true usual dietary intake values as two 24-h recalls, and the possible learning effect may be small.…”

Seasonal variation in food intake and the interaction effects of sex and age among adults in southern Brazil

“…Such 219 different results may be attributed to some known reasons. Each population has 220 different food habits (30), which could explain why the food groups for the interaction 221 effects found were different between the populations. Additionally, we used two 222 surveys, therefore, the first sample has a lower average income than the second, which 223 may influence the variability of diet (31).…”

“…were not linear with age (20)(21)(22)(23)(24)(25)(26)(27)(28)(29)(30)(31)(32)(33)(34)(35)(36)(37)(38)(39)(40)(41)(42)(43)(44)(45)(46)(47)(48)(49), and 60 + years old, respectively). There was a 32 linear and significant increase of vegetable intake for women, whereas the variation was 33 non-linear and of lesser magnitude for men (4).…”

Risk of hyperkalemia in patients with moderate chronic kidney disease initiating angiotensin converting enzyme inhibitors or angiotensin receptor blockers: a randomized study

“…We are aware that assessment may be biased by the type of ingestion and the methods of recall [45] and consequently we included continuous laboratory measurement of electrolyte balance. Lack of adherence was limited but caused some withdrawals.…”