Evidence map›Paper›PMID 38710447›Full record

Trial reportThe American journal of clinical nutrition2024

Accuracy of energy and nutrient intake estimation versus observed intake using 4 technology-assisted dietary assessment methods: a randomized crossover feeding study.

Clare Whitton, Clare E Collins, Barbara A Mullan, Megan E Rollo, Satvinder S Dhaliwal, Richard Norman, Carol J Boushey, Edward J Delp, Fengqing Zhu, Tracy A McCaffrey and 8 more

Abstract readRandomized Controlled Trial
PubMed Full text at PMC Publisher
In one paragraph

Trial report in The American journal of clinical nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Understanding the Motivations, Perceptions and Nutritional Implications of Plant-Based Milk Consumption Compared to Dairy-Based Milk.Journal of human nutrition and dietetics : the official journal of the British Dietetic Association · 2026
    Article
  4. Article
  5. Article
  6. Article
  7. Article
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  9. Article
  10. Observational
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

18 authors.

Clare WhittonCurtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth 6845, WA, Australia; Curtin Health Innovation Research Institute, Curtin University, Kent Street, GPO Box U1987, Perth 6845, Australia; School of Medical and Health Sciences, Edith Cowan University, 270 Joondalup Drive, Joondalup WA 6027, Australia. Electronic address: clare.whitton@curtin.edu.au.
Clare E CollinsSchool of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia; Food and Nutrition Research Program, Hunter Medical Research Institute, New Lambton Heights, Newcastle, Australia. Electronic address: clare.collins@newcastle.edu.au.
Barbara A MullanCurtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth 6845, WA, Australia; Enable Institute, Curtin University, Perth, Australia. Electronic address: barbara.mullan@curtin.edu.au.
Megan E RolloCurtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth 6845, WA, Australia; School of Health Sciences, College of Health, Medicine and Wellbeing, University of Newcastle, Newcastle, Australia. Electronic address: megan.rollo@curtin.edu.au.
Satvinder S DhaliwalCurtin Health Innovation Research Institute, Curtin University, Kent Street, GPO Box U1987, Perth 6845, Australia; Obstetrics & Gynaecology Academic Clinical Program, Duke-NUS Medical School, National University of Singapore, 8 College Rd, 169857, Singapore; Institute for Research in Molecular Medicine (INFORMM), Universiti Sains Malaysia, Pulau Pinang, Malaysia; Singapore University of Social Sciences, 463 Clementi Road, 599494, Singapore. Electronic address: S.Dhaliwal@curtin.edu.au.
Richard NormanCurtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth 6845, WA, Australia; Enable Institute, Curtin University, Perth, Australia. Electronic address: richard.norman@curtin.edu.au.
Carol J BousheyEpidemiology Program, University of Hawaii Cancer Center, Honolulu, HI, USA. Electronic address: cjboushey@cc.hawaii.edu.
Edward J DelpSchool of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, United States. Electronic address: ace@ecn.purdue.edu.
Fengqing ZhuSchool of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, United States. Electronic address: zhu0@purdue.edu.
Tracy A McCaffreyDepartment of Nutrition, Dietetics and Food, Monash University, Melbourne, Australia. Electronic address: tracy.mccaffrey@monash.edu.
Sharon I KirkpatrickSchool of Public Health Sciences, University of Waterloo, Waterloo, ON, Canada. Electronic address: sharon.kirkpatrick@uwaterloo.ca.
Christina M PollardCurtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth 6845, WA, Australia; Curtin Health Innovation Research Institute, Curtin University, Kent Street, GPO Box U1987, Perth 6845, Australia; Enable Institute, Curtin University, Perth, Australia. Electronic address: C.Pollard@curtin.edu.au.
Janelle D HealyCurtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth 6845, WA, Australia; Curtin Health Innovation Research Institute, Curtin University, Kent Street, GPO Box U1987, Perth 6845, Australia. Electronic address: janelle.healy@curtin.edu.au.
Amira HassanCurtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth 6845, WA, Australia; Curtin Health Innovation Research Institute, Curtin University, Kent Street, GPO Box U1987, Perth 6845, Australia. Electronic address: amira.hassan@curtin.edu.au.
Shivangi GargCurtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth 6845, WA, Australia. Electronic address: shivangi.garg@curtin.edu.au.
Paul AtyeoHealth Section, Health and Disability Branch, Australian Bureau of Statistics, Canberra, Australia. Electronic address: paul.atyeo@abs.gov.au.
Syed Aqif MukhtarCurtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth 6845, WA, Australia. Electronic address: Aqif.Mukhtar@curtin.edu.au.
Deborah A KerrCurtin School of Population Health, Curtin University, Kent Street, GPO Box U1987, Perth 6845, WA, Australia; Curtin Health Innovation Research Institute, Curtin University, Kent Street, GPO Box U1987, Perth 6845, Australia. Electronic address: d.kerr@curtin.edu.au.

Funding

University of Hawaii Cancer Center CCSGP30CA071789 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI GERTRAUD MASKARINEC · 1996 to 2026
$56.2M
Traditional and New Dietary Assessment Methods (TANDAM) for Personalized NutritionU24CA268228 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI EDWARD J DELP, MEGAN A MCCRORY · 2022 to 2026
$10.2M
Improving Dietary Assessment Methods Using the Cell Phone and Digital ImagingU01CA130784 · NCI · UNIVERSITY OF HAWAII AT MANOA · PI BOUSHEY, CAROL J · 2007 to 2010
$2.1M
Improving Diet Assessment in AdolescentsR01DK073711 · NIDDK · PURDUE UNIVERSITY · PI BOUSHEY, CAROL J · 2007 to 2009
$904k
NCI NIH HHS P30 CA071789NCI NIH HHS U01 CA130784NCI NIH HHS U24 CA268228NIDDK NIH HHS R01 DK073711
6 · The paper itself

Abstract

backgroundTechnology-assisted 24-h dietary recalls (24HRs) have been widely adopted in population nutrition surveillance. Evaluations of 24HRs inform improvements, but direct comparisons of 24HR methods for accuracy in reference to a measure of true intake are rarely undertaken in a single study population.

objectivesTo compare the accuracy of energy and nutrient intake estimation of 4 technology-assisted dietary assessment methods relative to true intake across breakfast, lunch, and dinner.

methodsIn a controlled feeding study with a crossover design, 152 participants [55% women; mean age 32 y, standard deviation (SD) 11; mean body mass index 26 kg/m

resultsThe mean difference between true and estimated energy intake as a percentage of true intake was 5.4% (95% CI: 0.6, 10.2%) using ASA24, 1.7% (95% CI: -2.9, 6.3%) using Intake24, 1.3% (95% CI: -1.1, 3.8%) using mFR-TA, and 15.0% (95% CI: 11.6, 18.3%) using IA-24HR. The variances of estimated and true energy intakes were statistically significantly different for all methods (P < 0.01) except Intake24 (P = 0.1). Differential accuracy in nutrient estimation was present among the methods.

conclusionsUnder controlled conditions, Intake24, ASA24, and mFR-TA estimated average energy and nutrient intakes with reasonable validity, but intake distributions were estimated accurately by Intake24 only (energy and protein). This study may inform considerations regarding instruments of choice in future population surveillance. This trial was registered at Australian New Zealand Clinical Trials Registry as ACTRN12621000209897.

Indexed as

Cross-Over StudiesDiet RecordsEnergy IntakeNutrition AssessmentAdultDietFemaleHumansMaleMental RecallMiddle AgedNutrientsYoung AdultNutrientsAutomated Self-Administered Dietary Assessment Toolcontrolled feedingdietary assessmentdietary measurement errorimage-assistedIntake24interview-administered dietary recallmobile food recordmobile technologyvalidation

Identifiers

PMID38710447
PMCPMC11347807

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.