Evidence map›Paper›PMID 33899149›Full record

ReviewEuropean journal of nutrition2021

Advances in dietary pattern analysis in nutritional epidemiology.

Christina-Alexandra Schulz, Kolade Oluwagbemigun, Ute Nöthlings

Abstract readReview
In one paragraph

Review in European journal of nutrition, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 80 papers, 7 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
80citing papers in PubMed, 7 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

80 citing papers in PubMed, 7 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Pooled it
  5. Pooled it
  6. Pooled it
  7. Pooled it
  8. Article
  9. Observational
  10. Article
  11. Article
  12. Article
  13. Low Prevalence and Abundance ofMicroorganisms · 2026
    Article
  14. Article
  15. Article
  16. Article
  17. Article
  18. Article
  19. Article
  20. Article

20 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

3 authors.

Christina-Alexandra Schulz *Department of Nutrition and Food Sciences, Nutritional Epidemiology, University of Bonn, Endenicher Allee 19b, 53115, Bonn, Germany.ORCID https://orcid.org/0000-0001-6535-3972
Kolade Oluwagbemigun *Department of Nutrition and Food Sciences, Nutritional Epidemiology, University of Bonn, Endenicher Allee 19b, 53115, Bonn, Germany.ORCID https://orcid.org/0000-0002-9454-5970
Ute NöthlingsDepartment of Nutrition and Food Sciences, Nutritional Epidemiology, University of Bonn, Endenicher Allee 19b, 53115, Bonn, Germany. noethlings@uni-bonn.de.ORCID http://orcid.org/0000-0002-5789-2252

Funding

Bundesministerium für Bildung und Forschung 01EA1410AJoint Programming Initiative A healthy diet for a healthy life 01EA1705A
6 · The paper itself

Abstract

background and purposeIt used to be a common practice in the field of nutritional epidemiology to analyze separate nutrients, foods, or food groups. However, in reality, nutrients and foods are consumed in combination. The introduction of dietary patterns (DP) and their analysis has revolutionized this field, making it possible to take into account the synergistic effects of foods and to account for the complex interaction among nutrients and foods. Three approaches of DP analysis exist: (1) the hypothesis-based approach (based on prior knowledge regarding the current understanding of dietary components and their health relation), (2) the exploratory approach (solely relying on dietary intake data), and (3) the hybrid approach (a combination of both approaches). During the recent past, complementary approaches for DP analysis have emerged both conceptually and methodologically.

methodWe have summarized the recent developments that include incorporating the Treelet transformation method as a complementary exploratory approach in a narrative review.

resultsUses, peculiarities, strengths, limitations, and scope of recent developments in DP analysis are outlined. Next, the narrative review gives an overview of the literature that takes into account potential relevant dietary-related factors, specifically the metabolome and the gut microbiome in DP analysis. Then the review deals with the aspect of data processing that is needed prior to DP analysis, particularly when dietary data arise from assessment methods other than the long-established food frequency questionnaire. Lastly, potential opportunities for upcoming DP analysis are summarized in the outlook.

conclusionBiological factors like the metabolome and the microbiome are crucial to understand diet-disease relationships. Therefore, the inclusion of these factors in DP analysis might provide deeper insights.

Indexed as

Feeding BehaviorGastrointestinal MicrobiomeDietDiet SurveysFoodDietary patternExploratoryGut microbiomeHypothesis basedMetabolome

Identifiers

PMID33899149
PMCPMC8572214

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.