Evidence map›Paper›PMID 38191462›Full record

ArticleThe international journal of behavioral nutrition and physical activity2024

Trajectories of physical activity from mid to older age in women: 21 years of data from the Australian Longitudinal Study on Women's Health.

Yuta Nemoto, Wendy J Brown, Gregore Iven Mielke

Open access · goldAbstract read
In one paragraph

Article in The international journal of behavioral nutrition and physical activity, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed, 1 pooled it
5.6field-weighted citation impact, top 4% 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

11 citing papers in PubMed, 1 synthesis or guideline pooled it, 17 citations in OpenAlex.

  1. Pooled it
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  3. Observational
  4. Is the 10-Year Trajectory of Physical Activity Associated With the Incidence of Mild Cognitive Impairment in Older Adults?Psychogeriatrics : the official journal of the Japanese Psychogeriatric Society · 2026
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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

3 authors at 3 institutions in 2 countries.

Yuta NemotoSchool of Public Health, The University of Queensland, Brisbane, QLD, 4006, Australia. y.nemoto@uq.edu.au.ORCID 0000-0002-6439-0015
Wendy J BrownFaculty of Health Sciences and Medicine, Bond University, Gold Coast, 4229, Australia.
Gregore Iven MielkeSchool of Public Health, The University of Queensland, Brisbane, QLD, 4006, Australia.
Bond University · AUThe University of Queensland · AUTokyo Medical University · JP

Funding

Japan Society for the Promotion of Science 22J00945National Health and Medical Research Council APP2008702
6 · The paper itself

Abstract

backgroundWomen's physical activity varies across the adult lifespan. However, changes in physical activity among mid-aged women are not well understood. We analysed 21 years of data from women born in 1946-51 to identify: (1) trajectories of physical activity in the transition from mid- to old-age and (2) determinants of different physical activity trajectories.

methodsData were from the 1946-51 cohort of the Australian Longitudinal Study on Women's Health (N = 10,371). Surveys were mailed at three-year intervals from 1998 (age 47-52) to 2019 (age 68-73) to collect data on physical activity, sociodemographic factors (country of birth, area of residence, educational attainment, marital status, income management, paid work hours, living with children age < 18, providing care), health indicators (menopause status, BMI, physical and mental health, chronic conditions), and health behaviours (smoking, alcohol status). Group-based trajectory modelling was used to identify trajectories of physical activity. Multinomial logistic regression models were used to examine the determinants of physical activity trajectories.

resultsFive trajectories were identified: Low-stable (13.3% of participants), Moderate-stable (50.4%), Moderate-increasing (22.2%), High-declining (7.7%), and High-stable (6.6%). Sociodemographic characteristics (area of residence, education, income management, living with children, and providing care) were determinants of physical activity trajectories, but the strongest factors were BMI, physical and mental health. Women who were overweight/obese and had poor physical and mental health were less likely to be in the High-stable group than in any other group. Changes in these variables (increasing BMI, and declining physical and mental health) and in marital status (getting married) were positively associated with being in trajectories other than the High-stable group.

conclusionsAlthough most women maintained physical activity at or above current guidelines, very low physical activity levels in the Low-stable group, and declining levels in the High-declining group are concerning. The data suggest that physical activity promotion strategies could be targeted to these groups, which are characterised by socioeconomic disadvantage, high (and increasing) BMI, and poor (and worsening) physical and mental health. Removing barriers to physical activity in these women, and increasing opportunities for activity, may reduce chronic disease risk in older age.

Indexed as

ExerciseWomen's HealthAdultAgedAustraliaChildEducational StatusFemaleHumansLongitudinal StudiesMiddle AgedDeterminantsMenopauseMid-aged womenNumber of birthsPhysical activityTemporal changeTrajectories

Identifiers

PMID38191462
PMCPMC10773129
OpenAlexW4390669741

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.