Evidence map›Paper›PMID 30356824›Full record

ArticleFrontiers in nutrition2018

Data Mapping From Food Diaries to Augment the Amount and Frequency of Foods Measured Using Short Food Questionnaires.

Michael Crowe, Michael O'Sullivan, Breige A McNulty, Oscar Cassetti, Aifric O'Sullivan

Abstract read
In one paragraph

Article in Frontiers in nutrition, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

5 authors.

Michael CroweDivision of Restorative Dentistry and Periodontology, Dublin Dental University Hospital, Trinity College Dublin, Dublin, Ireland.
Michael O'SullivanDivision of Restorative Dentistry and Periodontology, Dublin Dental University Hospital, Trinity College Dublin, Dublin, Ireland.
Breige A McNultyUCD School of Agriculture and Food Science, UCD Institute of Food and Health, University College Dublin, Dublin, Ireland.
Oscar CassettiDivision of Restorative Dentistry and Periodontology, Dublin Dental University Hospital, Trinity College Dublin, Dublin, Ireland.
Aifric O'SullivanUCD School of Agriculture and Food Science, UCD Institute of Food and Health, University College Dublin, Dublin, Ireland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Collecting accurate and detailed dietary intake data is costly at a national level. Accordingly, limited dietary assessment tools such as Short Food Questionnaires (SFQs) are increasingly used in large surveys. This paper describes a novel method linking matched datasets to improve the quality of dietary data collected. Growing Up in Ireland (GUI) is a nationally representative longitudinal study of infants in the Republic of Ireland which used a SFQ (with no portion sizes) to assess the intake of "healthy" and "unhealthy" food and drink by 3 years old preschool children. The National Preschool Nutrition Survey (NPNS) provides the most accurate estimates available for dietary intake of young children in Ireland using a detailed 4 days weighed food diary. A mapping algorithm was applied using food name, cooking method, and food description to fill all GUI food groups with information from the NPNS food datafile which included the target variables, frequency, and amount. The augmented data were analyzed to examine all food groups described in NPNS and GUI and what proportion of foods were

Indexed as

dental cariesdietary intake assessmentfood diaryfood frequency questionnairemapped databaseobesityshort food questionnaireunhealthy food

Identifiers

PMID30356824
PMCPMC6190565

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.