Evidence map›Paper›PMID 26058056›Full record

ArticlePloS one2015

Physical Activity and Different Concepts of Fall Risk Estimation in Older People--Results of the ActiFE-Ulm Study.

Jochen Klenk, Ngaire Kerse, Kilian Rapp, Thorsten Nikolaus, Clemens Becker, Dietrich Rothenbacher, Richard Peter, Michael Dieter Denkinger, ActiFE Study Group

Abstract read
In one paragraph

Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 45 papers.

0numbers the graph read from it
0cells of the map it votes in
45citing 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

45 citing papers in PubMed.

  1. Trial
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  3. Falls Risk in Relation to Activity Exposure in High-Risk Older Adults.The journals of gerontology. Series A, Biological sciences and medical sciences · 2020
    Trial
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  5. Trial
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  13. Frailty after COVID-19: The wave after?Aging medicine (Milton (N.S.W)) · 2023
    Review
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  15. Article
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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.

Jochen KlenkInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany; Department of Clinical Gerontology and Rehabilitation, Robert-Bosch-Hospital, Stuttgart, Germany.
Ngaire KerseDepartment of General Practice and Primary Health Care, School of Population Health, University of Auckland, Auckland, New Zealand.
Kilian RappInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany; Department of Clinical Gerontology and Rehabilitation, Robert-Bosch-Hospital, Stuttgart, Germany.
Thorsten NikolausAgaplesion Bethesda Clinic, Ulm, Germany.
Clemens BeckerDepartment of Clinical Gerontology and Rehabilitation, Robert-Bosch-Hospital, Stuttgart, Germany.
Dietrich RothenbacherInstitute of Epidemiology and Medical Biometry, Ulm University, Ulm, Germany.
Richard PeterInstitute of the History, Philosophy and Ethics of Medicine, Ulm University, Ulm, Germany.
Michael Dieter DenkingerAgaplesion Bethesda Clinic, Ulm, Germany.
ActiFE Study Group

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesTo investigate the relationship between physical activity and two measures of fall incidence in an elderly population using person-years as well as hours walked as denominators and to compare these two approaches.

designProspective cohort study with one-year follow-up of falls using fall calendars. Physical activity was defined as walking duration and recorded at baseline over one week using a thigh-worn uni-axial accelerometer (activPAL; PAL Technologies, Glasgow, Scotland). Average daily physical activity was extracted from these data and categorized in low (0-59 min), medium (60-119 min) and high (120 min and more) activity.

settingThe ActiFE Ulm study located in Ulm and adjacent regions in Southern Germany.

participants1,214 community-dwelling older people (≥65 years, 56.4% men). MEASUREMENTS: Negative-binomial regression models were used to calculate fall rates and incidence rate ratios for each activity category each with using (1) person-years and (2) hours walked as denominators stratified by gender, age group, fall history, and walking speed. All analyses were adjusted either for gender, age, or both.

resultsNo statistically significant association was seen between falls per person-year and average daily physical activity. However, when looking at falls per 100 hours walked, those who were low active sustained more falls per hours walked. The highest incidence rates of falls were seen in low-active persons with slow walking speed (0.57 (95% confidence interval (95% CI): 0.33 to 0.98) falls per 100 hours walked) or history of falls (0.60 (95% CI: 0.36 to 0.99) falls per 100 hours walked).

conclusionFalls per hours walked is a relevant and sensitive outcome measure. It complements the concept of incidence per person years, and gives an additional perspective on falls in community-dwelling older people.

Indexed as

Motor ActivityAccidental FallsAgedAged, 80 and overFemaleHumansMaleRisk Assessment

Identifiers

PMID26058056
PMCPMC4461251

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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.