Evidence map›Paper›PMID 22032767›Full record

ArticleAustralasian journal on ageing2011

Understanding ageing in older Australians: the contribution of the Dynamic Analyses to Optimise Ageing (DYNOPTA) project to the evidence base and policy.

Kaarin J Anstey, Allison A M Bielak, Carole L Birrell, Colette J Browning, Richard A Burns, Julie Byles, Kim M Kiely, Binod Nepal, Lesley A Ross, David Steel and 2 more

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In one paragraph

Article in Australasian journal on ageing, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

12 authors.

Kaarin J AnsteyCentre for Mental Health Research, Australian National University, Canberra, Australian Capital Territory, Australia. kaarin.anstey@anu.edu.au
Allison A M Bielak
Carole L Birrell
Colette J Browning
Richard A Burns
Julie Byles
Kim M Kiely
Binod Nepal
Lesley A Ross
David Steel
Timothy D Windsor
DYNOPTA team

Funding

Pilot CoreP30AG022838 · NIA · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI BALL, KARLENE K · 2003 to 2020
$5.7M
CIHRNIA NIH HHS 2 P30 AG022838NIA NIH HHS P30 AG022838
6 · The paper itself

Abstract

aimTo describe the Dynamic Analyses to Optimise Ageing (DYNOPTA) project and illustrate its contributions to understanding ageing through innovative methodology, and investigations on outcomes based on the project themes. DYNOPTA provides a platform and technical expertise that may be used to combine other national and international datasets.

methodsThe DYNOPTA project has pooled and harmonised data from nine Australian longitudinal studies to create the largest available longitudinal dataset (n= 50652) on ageing in Australia.

resultsA range of findings have resulted from the study to date, including methodological advances, prevalence rates of disease and disability, and mapping trajectories of ageing with and without increasing morbidity. DYNOPTA also forms the basis of a microsimulation model that will provide projections of future costs of disease and disability for the baby boomer cohort.

conclusionDYNOPTA contributes significantly to the Australian evidence base on ageing to inform key social and health policy domains.

Indexed as

AgingHealth PolicyAgedAged, 80 and overAustraliaDementiaFemaleHealth BehaviorHumansLongitudinal StudiesMaleMental DisordersMiddle AgedPrevalence

Identifiers

PMID22032767
PMCPMC3947607

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Registered trials

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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.