Evidence map›Paper›PMID 36078704›Full record

ArticleInternational journal of environmental research and public health2022

Machine Learning for Prediction of Cognitive Health in Adults Using Sociodemographic, Neighbourhood Environmental, and Lifestyle Factors.

Govinda R Poudel, Anthony Barnett, Muhammad Akram, Erika Martino, Luke D Knibbs, Kaarin J Anstey, Jonathan E Shaw, Ester Cerin

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
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  4. Review
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  11. Article
  12. Machine Learning Models for Data-Driven Prediction of Diabetes by Lifestyle Type.International journal of environmental research and public health · 2022
    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

8 authors.

Govinda R PoudelMary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3065, Australia.ORCID 0000-0002-0043-7531
Anthony BarnettMary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3065, Australia.ORCID 0000-0002-6320-4073
Muhammad AkramMary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3065, Australia.ORCID 0000-0003-1073-3614
Erika MartinoMelbourne School of Population and Global Health, University of Melbourne, Melbourne, VIC 3010, Australia.ORCID 0000-0003-0827-6477
Luke D KnibbsSchool of Public Health, The University of Sydney, Sydney, NSW 2006, Australia.
Kaarin J AnsteySchool of Psychology, University of New South Wales, Sydney, NSW 2052, Australia.ORCID 0000-0002-9706-9316
Jonathan E ShawBaker Heart and Diabetes Institute, Melbourne, VIC 3004, Australia.
Ester CerinMary Mackillop Institute for Health Research, Australian Catholic University, Melbourne, VIC 3065, Australia.ORCID 0000-0002-7599-165X

Funding

Medical Research Council MR/T038500/1
6 · The paper itself

Abstract

The environment we live in, and our lifestyle within this environment, can shape our cognitive health. We investigated whether sociodemographic, neighbourhood environment, and lifestyle variables can be used to predict cognitive health status in adults. Cross-sectional data from the AusDiab3 study, an Australian cohort study of adults (34-97 years) (

Indexed as

Residence CharacteristicsSedentary BehaviorAdultAustraliaCognitionCohort StudiesCross-Sectional StudiesHumansLife StyleMachine Learningbuilt environmentcognitionmachine learningmemoryneighbourhood environmentphysical activitypredictionprocessing speedsedentary behavioursociodemographic

Identifiers

PMID36078704
PMCPMC9517821

What OpenQuestion holds

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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.