Evidence map›Paper›PMID 38577154›Full record

ReviewFrontiers in nutrition2024

A systematic review of dietary data collection methodologies for diet diversity indicators.

Subeg Mahal, Christopher Kucha, Ebenezer M Kwofie, Michael Ngadi

Abstract readReview
In one paragraph

Review in Frontiers in 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
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  3. Review
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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

4 authors.

Subeg MahalDepartment of Bioresource Engineering, McGill University, Ste-Anne-de-Bellevue, QC, Canada.
Christopher KuchaDepartment of Food Science and Technology, University of Georgia, Athens, GA, United States.
Ebenezer M KwofieDepartment of Bioresource Engineering, McGill University, Ste-Anne-de-Bellevue, QC, Canada.
Michael NgadiDepartment of Bioresource Engineering, McGill University, Ste-Anne-de-Bellevue, QC, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of the current study was to critically assess the gaps in the existing methodologies of dietary data collection for diet diversity indicators. The study proposed the importance of smartphone application to overcome the drawbacks. The review paper identified and assessed the conventional methodologies used in diet diversity indicators including Minimum Dietary Diversity for Women (MDD-W), Minimum Dietary Diversity of Infant and Young Child Feeding Practices (IYCF-MDD), and Household Dietary Diversity Score (HDDS). The 80 research studies from 38 countries were critically assessed on the basis of their research aim, study design, target audience, dietary data collection methodology, sample size, dietary data type, dietary data collection frequency, and location point of dietary data collection. Results indicated that most studies employed interviewer-administered 24-h recall assessing the dietary diversity. The review paper concluded that smartphone application had potential to overcome the identified limitations of conventional methodologies including recall bias, social-desirability bias, interviewer training, and cost-time constraints.

Indexed as

diet assessmentdiet diversityHDDSIYCF-MDDMDD-Wsmartphone application

Identifiers

PMID38577154
PMCPMC10992480

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.