Evidence map›Paper›PMID 25897837›Full record

ReviewNutrition journal2015

Application and interpretation of multiple statistical tests to evaluate validity of dietary intake assessment methods.

Martani J Lombard, Nelia P Steyn, Karen E Charlton, Marjanne Senekal

Abstract readReview
In one paragraph

Review in Nutrition journal, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 137 papers, 5 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
137citing papers in PubMed, 5 pooled it
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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

137 citing papers in PubMed, 5 syntheses or guidelines pooled it.

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77 more citing papers are in PubMed but not listed here.

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.

Martani J LombardCentre of Excellence for Nutrition (CEN), North-West University, Private Bag X6001, Nutrition, Box 594, Potchefstroom, 2520, South Africa. tani.lombard@nwu.ac.za.
Nelia P SteynDivision of Human Nutrition, University of Cape Town, Cape Town, South Africa. nelia.steyn@uct.ac.za.
Karen E CharltonSchool of Medicine, Faculty of Science, Medicine and Health, University of Wollongong, Wollongong, Australia. karenc@uow.edu.au.
Marjanne SenekalDivision of Human Nutrition, University of Cape Town, Cape Town, South Africa. marjanne.senekal@uct.ac.za.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSeveral statistical tests are currently applied to evaluate validity of dietary intake assessment methods. However, they provide information on different facets of validity. There is also no consensus on types and combinations of tests that should be applied to reflect acceptable validity for intakes. We aimed to 1) conduct a review to identify the tests and interpretation criteria used where dietary assessment methods was validated against a reference method and 2) illustrate the value of and challenges that arise in interpretation of outcomes of multiple statistical tests in assessment of validity using a test data set.

methodsAn in-depth literature review was undertaken to identify the range of statistical tests used in the validation of quantitative food frequency questionnaires (QFFQs). Four databases were accessed to search for statistical methods and interpretation criteria used in papers focusing on relative validity. The identified tests and interpretation criteria were applied to a data set obtained using a QFFQ and four repeated 24-hour recalls from 47 adults (18-65 years) residing in rural Eastern Cape, South Africa.

results102 studies were screened and 60 were included. Six statistical tests were identified; five with one set of interpretation criteria and one with two sets of criteria, resulting in seven possible validity interpretation outcomes. Twenty-one different combinations of these tests were identified, with the majority including three or less tests. Coefficient of correlation was the most commonly used (as a single test or in combination with one or more tests). Results of our application and interpretation of multiple statistical tests to assess validity of energy, macronutrients and selected micronutrients estimates illustrate that for most of the nutrients considered, some outcomes support validity, while others do not.

conclusionsOne to three statistical tests may not be sufficient to provide comprehensive insights into various facets of validity. Results of our application and interpretation of multiple statistical tests support the value of such an approach in gaining comprehensive insights in different facets of validity. These insights should be considered in the formulation of conclusions regarding validity to answer a particular dietary intake related research question.

Indexed as

Energy IntakeFeeding BehaviorNutrition AssessmentDatabases, FactualDietary CarbohydratesDietary FatsDietary ProteinsFolic AcidHumansIron, DietaryMental RecallMicronutrientsReproducibility of ResultsRural PopulationSouth AfricaSurveys and QuestionnairesDietary CarbohydratesDietary FatsDietary ProteinsFolic AcidIron, DietaryMicronutrientsVitamin A

Identifiers

PMID25897837
PMCPMC4471918

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.