Evidence map›Paper›PMID 31077187›Full record

ArticleBMC public health2019

Study protocol: associations between dietary patterns, cognitive function and metabolic syndrome in older adults - a cross-sectional study.

Karen D Mumme, Pamela R von Hurst, Cathryn A Conlon, Beatrix Jones, Crystal F Haskell-Ramsay, Welma Stonehouse, Anne-Louise M Heath, Jane Coad, Kathryn L Beck

Abstract read
In one paragraph

Article in BMC public health, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing 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

14 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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  4. Study Protocol for the Interactions between Dietary Patterns andInternational journal of preventive medicine · 2023
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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

9 authors.

Karen D MummeCollege of Health, Massey University, Private Bag 102904, Auckland, 0745, New Zealand.
Pamela R von HurstCollege of Health, Massey University, Private Bag 102904, Auckland, 0745, New Zealand.
Cathryn A ConlonCollege of Health, Massey University, Private Bag 102904, Auckland, 0745, New Zealand.
Beatrix JonesDepartment of Statistics, University of Auckland, Private Bag 92019, Auckland, 1142, New Zealand.
Crystal F Haskell-RamsayDepartment of Psychology, Northumbria University, Newcastle-upon-Tyne, NE1 8ST, UK.
Welma StonehouseHealth and Biosecurity Business Unit, Commonwealth Scientific Industrial Research Organisation, PO Box 11060, Adelaide, SA, 5001, Australia.
Anne-Louise M HeathDepartment of Human Nutrition, University of Otago, PO Box 56, Dunedin, 9054, New Zealand.
Jane CoadCollege of Sciences, Massey University, Private Bag 11222, Palmerston North, 4442, New Zealand.
Kathryn L BeckCollege of Health, Massey University, Private Bag 102904, Auckland, 0745, New Zealand. k.l.beck@massey.ac.nz.ORCID http://orcid.org/0000-0003-1825-1927

Funding

Health Research Council of New Zealand 17/566
6 · The paper itself

Abstract

backgroundLoss of cognitive function is a significant issue as the world's population ages. Preserving cognitive function maintains independence in older adults bringing major societal and financial benefits. Lifestyle factors such as diet are modifiable risk factors, which may help preserve cognitive function. Most nutrition research aimed at preserving cognitive function and metabolic health has focussed on individual nutrients and foods, not allowing for food combinations and interactions. A dietary pattern approach considers the entire diet including its complexity. Previous research investigating dietary patterns and cognitive function has not always considered relevant covariates such as physical activity and the Apolipoprotein E genotype, which are known to have associations with cognitive function. The aim of the REACH (Researching Eating, Activity and Cognitive Health) study is to investigate associations between dietary patterns, cognitive function and metabolic syndrome, accounting for a range of covariates.

methodsThis cross-sectional study design will recruit older, community-living adults (65-74 years) from Auckland, New Zealand. Dietary data will be collected via a 109-item food frequency questionnaire validated using a 4-day food record. Cognitive function will be assessed using the Montreal Cognitive Assessment (paper based) and the Computerised Mental Performance Assessment System (COMPASS) - a testing suite covering six domains. Additional data will include genetic (Apolipoprotein E ε4) and biochemical markers (fasting glucose, HbA1c, lipids profile), anthropometric measurements (weight, height, waist and hip circumference, body composition using dual X-ray absorptiometry), blood pressure, physical activity (International Physical Activity Questionnaire - short form) and health and demographics (questionnaire). Dietary patterns will be derived by principal component analysis. Associations between cognitive function and dietary patterns will be examined using multiple regression analysis. Covariates and interaction factors will include age, education, socio-economic status, physical activity, Apolipoprotein E ε4 genotype, family history of dementia or cognitive impairment, and lifestyle factors. Differences between participants with and without metabolic syndrome will also be examined. DISCUSSION: This study will bring new knowledge regarding associations between dietary patterns and cognitive function and metabolic health in older adults living in New Zealand. This is important for developing nutrition related recommendations to help older adults maintain cognitive function.

Indexed as

ExerciseLife StyleAgedBody WeightCognitionCognitive DysfunctionCross-Sectional StudiesDietElder Nutritional Physiological PhenomenaFemaleFood PreferencesHumansMaleMetabolic SyndromeNew ZealandRisk FactorsCognitionCognitive declineDietary patternsMetabolic syndromeNew ZealandOlder adultsPrincipal component analysis

Identifiers

PMID31077187
PMCPMC6509830

What OpenQuestion holds

Textmetadata
LicenceCC BY
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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.