Evidence map›Paper›PMID 29529145›Full record

ArticleThe American journal of clinical nutrition2018

Contribution to the understanding of how principal component analysis-derived dietary patterns emerge from habitual data on food consumption.

Carolina Schwedhelm, Khalid Iqbal, Sven Knüppel, Lukas Schwingshackl, Heiner Boeing

Abstract read
In one paragraph

Article in The American journal of clinical nutrition, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
50citing papers in PubMed, 2 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

50 citing papers in PubMed, 2 syntheses or guidelines pooled it.

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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

5 authors.

Carolina SchwedhelmDepartment of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany.
Khalid IqbalDepartment of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany.
Sven KnüppelDepartment of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany.
Lukas SchwingshacklDepartment of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany.
Heiner BoeingDepartment of Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke (DIfE), Nuthetal, Germany.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Principal component analysis (PCA) is a widely used exploratory method in epidemiology to derive dietary patterns from habitual diet. Such dietary patterns seem to originate from intakes on multiple days and eating occasions. Therefore, analyzing food intake of study populations with different levels of food consumption can provide additional insights as to how habitual dietary patterns are formed. Objective: We analyzed the food intake data of German adults in terms of the relations among food groups from three 24-h dietary recalls (24hDRs) on the habitual, single-day, and main-meal levels, and investigated the contribution of each level to the formation of PCA-derived habitual dietary patterns. Design: Three 24hDRs were collected in 2010-2012 from 816 adults for an European Prospective Investigation into Cancer and Nutrition (EPIC)-Potsdam subcohort study. We identified PCA-derived habitual dietary patterns and compared cross-sectional food consumption data in terms of correlation (Spearman), consistency (intraclass correlation coefficient), and frequency of consumption across all days and main meals. Contribution to the formation of the dietary patterns was obtained through Spearman correlation of the dietary pattern scores. Results: Among the meals, breakfast appeared to be the most consistent eating occasion within individuals. Dinner showed the strongest correlations with "Prudent" (Spearman correlation = 0.60), "Western" (Spearman correlation = 0.59), and "Traditional" (Spearman correlation = 0.60) dietary patterns identified on the habitual level, and lunch showed the strongest correlations with the "Cereals and legumes" (Spearman correlation = 0.60) habitual dietary pattern. Conclusions: Higher meal consistency was related to lower contributions to the formation of PCA-derived habitual dietary patterns. Absolute amounts of food consumption did not strongly conform to the habitual dietary patterns by meals, suggesting that these patterns are formed by complex combinations of variable food consumption across meals. Dinner showed the highest contribution to the formation of habitual dietary patterns. This study provided information about how PCA-derived dietary patterns are formed and how they could be influenced.

Indexed as

DietHealth BehaviorPrincipal Component AnalysisAdultBreakfastCross-Sectional StudiesFemaleFollow-Up StudiesGermanyHumansMaleMealsMental RecallMiddle AgedNutrition AssessmentProspective Studies

Identifiers

PMID29529145
PMCPMC6411615

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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.