Evidence map›Paper›PMID 37892491›Full record

ArticleNutrients2023

Sociodemographic and Health Indicators of Diet Quality in Pre-Frail Older Adults in New Zealand.

Esther Tay, Daniel Barnett, Maisie Rowland, Ngaire Kerse, Richard Edlin, Debra L Waters, Martin Connolly, Avinesh Pillai, Evelingi Tupou, Ruth Teh

Abstract read
In one paragraph

Article in Nutrients, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Review
  3. Review
  4. 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

10 authors.

Esther TayDepartment of General Practice and Primary Health Care, School of Population Health, University of Auckland, Auckland 1023, New Zealand.
Daniel BarnettDepartment of Statistics, Faculty of Science, University of Auckland, Auckland 1010, New Zealand.
Maisie RowlandHuman Nutrition Research Centre, Population Health Sciences Institute, Faculty of Medical Sciences, Newcastle University, Newcastle Upon Tyne NE2 4HH, UK.
Ngaire KerseDepartment of General Practice and Primary Health Care, School of Population Health, University of Auckland, Auckland 1023, New Zealand.ORCID 0000-0002-5992-3681
Richard EdlinHealth Systems Group, School of Population Health, University of Auckland, Auckland 1023, New Zealand.
Debra L WatersDepartment of Medicine, University of Otago, Dunedin 9016, New Zealand.
Martin ConnollyDepartment of Geriatric Medicine, Faculty of Medical and Health Sciences, University of Auckland, Auckland 1023, New Zealand.
Avinesh PillaiDepartment of Statistics, Faculty of Science, University of Auckland, Auckland 1010, New Zealand.
Evelingi TupouDepartment of General Practice and Primary Health Care, School of Population Health, University of Auckland, Auckland 1023, New Zealand.
Ruth TehDepartment of General Practice and Primary Health Care, School of Population Health, University of Auckland, Auckland 1023, New Zealand.ORCID 0000-0001-7135-1850

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study aimed to identify sociodemographic and health indicators of diet quality in pre-frail community-dwelling older adults. Pre-frail older adults are those at risk of progression to clinical manifestations of frailty and are targets for preventative intervention. We previously reported that pre-frail older adults have reasonably good overall diet quality. However, further analyses found a low intake of energy, protein and several micronutrients.

methodsWe collected detailed dietary intake from pre-frail (FRAIL scale 1-2) older adults using NZ Intake24, an online version of 24 h multiple pass dietary recall. Diet quality was ascertained with the Diet Quality Index-International (DQI-I). We used regression generalized linear models to determine predictors of diet quality as well as classification and regression tree (CART) analysis to examine the complex relationships between predictors and identified profiles of sub-groups of older adults that predict diet quality.

resultsThe median age in this sample (

conclusionsWe found that BMI, living arrangement and socioeconomic status were independent predictors of diet quality in pre-frail older adults, with BMI being the most important variable in this sample when the interaction of these variables was considered. Future research is needed to determine the similarities and/or differences in the profile of subgroups of older adults with poorer diet quality.

Indexed as

Frail ElderlyFrailtyAgedAged, 80 and overDietGeriatric AssessmentHumansIndependent LivingNew ZealandBMIdiet qualityfrailtyolder adultssociodemographic

Identifiers

PMID37892491
PMCPMC10610025

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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.