Evidence map›Paper›PMID 36271338›Full record

ArticleBMC public health2022

Accelerometer-measured physical activity in mid-age Australian adults.

Gregore Iven Mielke, Nicola W Burton, Wendy J Brown

Abstract read
In one paragraph

Article in BMC public health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. The relationship between clinical characteristics, sociodemographic factors and sedentary behavior in adults with chronic conditions: a cross-sectional study from the Lolland-Falster Health Study.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 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.

Gregore Iven MielkeSchool of Public Health, The University of Queensland, 4006, Brisbane, QLD, Australia. g.ivenmielke@uq.edu.au.ORCID 0000-0002-3043-2715
Nicola W BurtonMenzies Health Institute, Griffith University, Gold Coast, Australia.ORCID 0000-0002-3221-2265
Wendy J BrownSchool of Human Movement and Nutrition Sciences, The University of Queensland, Brisbane, Australia.ORCID 0000-0001-9093-4509

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRaw data from accelerometers can provide valuable insights into specific attributes of physical activity, such as time spent in intensity-specific activity. The aim of this study was to describe physical activity assessed with raw data from triaxial wrist-worn accelerometers in mid-age Australian adults.

methodsData were from 700 mid-age adults living in Brisbane, Australia (mean age: 60.4; SD:7.1 years). Data from a non-dominant wrist worn triaxial accelerometer (Actigraph wGT3X-BT), expressed as acceleration in gravitational equivalent units (1 mg = 0.001 g), were used to estimate time spent in moderate-vigorous intensity physical activity (MVPA; >100 mg) using different bout criteria (non-bouted, 1-, 5-, and 10-min bouts), and the proportion of participants who spent an average of at least one minute per day in vigorous physical activity.

resultsMean acceleration was 23.2 mg (SD: 7.5) and did not vary by gender (men: 22.4; women: 23.7; p-value: 0.073) or education (p-value: 0.375). On average, mean acceleration was 10% (2.5 mg) lower per decade of age from age 55y. The median durations in non-bouted, 1-min, 5-min and 10-min MVPA bouts were, respectively, 68 (25th -75th : 45-99), 26 (25th -75th : 12-46), 10 (25th -75th : 3-24) and 8 (25th -75th : 0-19) min/day. Around one third of the sample did at least one minute per day in vigorous intensity activities.

conclusionThis population-based cohort provided a detailed description of physical activity based on raw data from accelerometers in mid-age adults in Australia. Such data can be used to investigate how different patterns and intensities of physical activity vary across the day/week and influence health outcomes.

Indexed as

AccelerometryExerciseAdultAustraliaCohort StudiesFemaleHumansMaleMiddle AgedWristAccelerometerAdulthoodCohortsDevicesGGIRPhysical activity monitor

Identifiers

PMID36271338
PMCPMC9585757

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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.