Evidence map›Paper›PMID 29329536›Full record

ArticleNutrition journal2018

Dietary flavonoid intake in older adults: how many days of dietary assessment are required and what is the impact of seasonality?

Katherine Kent, Karen E Charlton, Simone Lee, Jonathon Mond, Joanna Russell, Paul Mitchell, Victoria M Flood

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Article in Nutrition journal, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
12citing papers in PubMed, 1 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

12 citing papers in PubMed, 1 synthesis or guideline 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

7 authors.

Katherine KentCentre for Rural Health, Faculty of Health, University of Tasmania, Locked Bag 1322, Launceston, TAS, 7250, Australia. Katherine.Kent@utas.edu.au.ORCID 0000-0002-5330-7044
Karen E CharltonFaculty of Science, Medicine and Health, University of Wollongong, Wollongong, Australia.
Simone LeeCentre for Rural Health, Faculty of Health, University of Tasmania, Locked Bag 1322, Launceston, TAS, 7250, Australia.
Jonathon MondCentre for Rural Health, Faculty of Health, University of Tasmania, Locked Bag 1322, Launceston, TAS, 7250, Australia.
Joanna RussellFaculty of Social Sciences, University of Wollongong, Wollongong, Australia.
Paul MitchellCentre for Vision Research, University of Sydney, Sydney, Australia.
Victoria M FloodFaculty of Health Sciences, University of Sydney, Sydney, Australia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundWithin- and between-person variation in nutrient intake is well established, but little is known about variability in dietary flavonoid intake, including the effect of seasonality.

methodsWithin- and between-individual variability of flavonoid intake, and intake of flavonoid subclasses was examined in older adults (n = 79; mean age 70.1 y (range: 60y-80y)), using three separate 4-day weighed food records (WFR) collected approximately 4 months apart. The effects of seasonality were also examined. Mixed-effects linear regression models were used to estimate within- and between-individual variance components for flavonoids and subclasses. The number of days of dietary assessment required for a high level of hypothetical accuracy was calculated from variance ratios.

resultsWithin- and between-individual variability was high for flavonoid intake, and intake of flavonoid subclasses, with variance ratios > 1. It was calculated that six days of WFR data are required for total flavonoid intake, and between 6 and 10 days was required for flavonoid subclasses. There was no effect of seasonality for total flavonoid intake or intake of flavonoid subclasses, with the exception that flavan-3-ol and flavanone intakes which were relatively low in summer, and in summer and winter, respectively.

conclusionWhile the effects of seasonality on total flavonoid intake may be small, within- and between-individual variation associated with flavonoid intake assessment appears to be substantial across 12 days of WFR data in older adults. It is recommended that a minimum of 6 days of weighed food records are collected to minimise the impact of within- and between-individual variability on total flavonoid intake assessments in this population.

Indexed as

Research DesignSeasonsAgedAged, 80 and overAustraliaDietFemaleFlavonoidsGeriatric AssessmentHumansMaleNutrition AssessmentNutrition SurveysTimeFlavonoidsBetween-individual variationDietary assessmentFlavonoidsSeasonalityVariance ratioWithin-individual variation

Identifiers

PMID29329536
PMCPMC5767040

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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.