Evidence map›Paper›PMID 32674307›Full record

ArticleNutrients2020

Dietary Protein Intake and Determinants in Māori and Non-Māori Octogenarians. Te Puāwaitanga o Ngā Tapuwae Kia Ora Tonu: Life and Living in Advanced Age: A Cohort Study in New Zealand.

Anishka Ram, Ngaire Kerse, Simon A Moyes, Marama Muru-Lanning, Carol Wham

Open access · goldAbstract read
In one paragraph

Article in Nutrients, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 36% of its field
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

3 citing papers in PubMed, 6 citations in OpenAlex.

  1. Article
  2. Article
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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 at 2 institutions in 1 country.

Anishka RamCollege of Health, Massey University, Auckland 0632, New Zealand.
Ngaire KerseSchool of Population Health, University of Auckland, Auckland 1072, New Zealand.ORCID 0000-0002-5992-3681
Simon A MoyesSchool of Population Health, University of Auckland, Auckland 1072, New Zealand.
Marama Muru-LanningJames Henare Māori Research Centre, University of Auckland, Auckland 1142, New Zealand.
Carol WhamCollege of Health, Massey University, Auckland 0632, New Zealand.ORCID 0000-0002-5136-1346
University of Auckland · NZMassey University · NZ

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Protein intake, food sources and distribution are important in preventing age-related loss of muscle mass and strength. The prevalence and determinants of low protein intake, food sources and mealtime distribution were examined in 214 Māori and 360 non-Māori of advanced age using two 24 h multiple pass recalls. The contribution of food groups to protein intake was assessed. Low protein intake was defined as ≤0.75 g/kg for women and ≤0.86 g/kg for men. A logistic regression model was built to explore predictors of low protein intake. A third of both women (30.9%) and men (33.3%) had a low protein intake. The main food group sources were beef/veal, fish/seafood, milk, bread though they differed by gender and ethnicity. For women and men respectively protein intake (g/meal) was lowest at breakfast (10.1 and 13.0), followed by lunch (14.5 and 17.8) and dinner (23.3 and 34.2). Being a woman (

Indexed as

Nutritional StatusNutrition SurveysAged, 80 and overAge FactorsCohort StudiesCross-Sectional StudiesDentitionDepressionDietary ProteinsElder Nutritional Physiological PhenomenaFemaleHumansMaleNew ZealandNutritional RequirementsSarcopeniaDietary Proteinsfood sourcesLiLACS NZolder adultsprotein distributionprotein intake

Identifiers

PMID32674307
PMCPMC7400903
OpenAlexW3043315437

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.