Evidence map›Paper›PMID 38238892›Full record

ArticlePublic health nutrition2024

Harmonising dietary datasets for global surveillance: methods and findings from the Global Dietary Database.

Dimitra Karageorgou, Laura Lara Castor, Victoria Padula de Quadros, Rita Ferreira de Sousa, Bridget Anna Holmes, Sofia Ioannidou, Dariush Mozaffarian, Renata Micha

Abstract read
In one paragraph

Article in Public health nutrition, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–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

18 citing papers in PubMed.

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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

8 authors.

Dimitra KarageorgouFriedman School of Nutrition Science and Policy, Tufts University, 150 Harrison Ave, Boston, MA02111, USA.ORCID 0000-0002-5451-3835
Laura Lara CastorFriedman School of Nutrition Science and Policy, Tufts University, 150 Harrison Ave, Boston, MA02111, USA.
Victoria Padula de QuadrosFood and Agriculture Organization of the United Nations, Rome, Italy.
Rita Ferreira de SousaFood and Agriculture Organization of the United Nations, Rome, Italy.ORCID 0000-0002-9462-568X
Bridget Anna HolmesFood and Agriculture Organization of the United Nations, Rome, Italy.
Sofia IoannidouEuropean Food Safety Authority, Parma, Italy.
Dariush MozaffarianFriedman School of Nutrition Science and Policy, Tufts University, 150 Harrison Ave, Boston, MA02111, USA.ORCID 0000-0001-7958-9492
Renata MichaFriedman School of Nutrition Science and Policy, Tufts University, 150 Harrison Ave, Boston, MA02111, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveThe Global Dietary Database (GDD) expanded its previous methods to harmonise and publicly disseminate individual-level dietary data from nutrition surveys worldwide.

designAnalysis of cross-sectional data.

settingGlobal.

participantsGeneral population.

methodsComprehensive methods to streamline the harmonisation of primary, individual-level 24-h recall and food record data worldwide were developed. To standardise the varying food descriptions, FoodEx2 was used, a highly detailed food classification and description system developed and adapted for international use by European Food Safety Authority (EFSA). Standardised processes were developed to: identify eligible surveys; contact data owners; screen surveys for inclusion; harmonise data structure, variable definition and unit and food characterisation; perform data checks and publicly disseminate the harmonised datasets. The GDD joined forces with FAO and EFSA, given the shared goal of harmonising individual-level dietary data worldwide.

resultsOf 1500 dietary surveys identified, 600 met the eligibility criteria, and 156 were prioritised and contacted; fifty-five surveys were included for harmonisation and, ultimately, fifty two were harmonised. The included surveys were primarily nationally representative (59 %); included high- (39 %), upper-middle (21 %), lower-middle (27 %) and low- (13 %) income countries; usually collected multiple recalls/ records (64 %) and largely captured both sexes, all ages and both rural and urban areas. Surveys from low- and lower-middle

conclusionsDiverse 24-h recalls/records can be harmonised to provide highly granular, standardised data, supporting nutrition programming, research and capacity development worldwide.

Indexed as

DietNutritional StatusCross-Sectional StudiesDiet SurveysFemaleFoodHumansMale24-h recallDietary datadietary intakesfood intakesharmonisationnutrient intake

Identifiers

PMID38238892
PMCPMC10882534

What OpenQuestion holds

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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.