Evidence map›Paper›PMID 36815559›Full record

ArticleThe journals of gerontology. Series A, Biological sciences and medical sciences2023

The Association of Physical Activity Behaviors and Patterns With Aging Acceleration: Evidence From the UK Biobank.

Jianwei Zhu, Yao Yang, Yu Zeng, Xin Han, Wenwen Chen, Yao Hu, Yuanyuan Qu, Huazhen Yang, Unnur A Valdimarsdóttir, Fang Fang and 1 more

Open access · hybridAbstract read
In one paragraph

Article in The journals of gerontology. Series A, Biological sciences and medical sciences, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.5field-weighted citation impact, top 13% 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

15 citing papers in PubMed, 17 citations in OpenAlex.

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  12. Optimal lifestyle patterns for delaying ageing and reducing all-cause mortality: insights from the UK Biobank.European review of aging and physical activity : official journal of the European Group for Research into Elderly and Physical Activity · 2024
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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

11 authors at 3 institutions in 3 countries.

Jianwei ZhuDepartment of Orthopedic Surgery and West China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
Yao YangWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
Yu ZengWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
Xin HanWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
Wenwen ChenDivision of Nephrology, Kidney Research Institute, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, China.
Yao HuWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
Yuanyuan QuWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
Huazhen YangWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.
Unnur A ValdimarsdóttirCenter of Public Health Sciences, Faculty of Medicine, University of Iceland, Reykjavík, Iceland.
Fang FangInstitute of Environmental Medicine, Karolinska Institute, Stockholm, Sweden.ORCID 0000-0002-3310-6456
Huan SongWest China Biomedical Big Data Center, West China Hospital, Sichuan University, Chengdu, China.ORCID 0000-0003-3845-8079
Sichuan University · CNKarolinska Institutet · SEUniversity of Iceland · IS

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Prior evidence suggests that physical activity may reduce the risk of multiple diseases and mortality. However, whether and how physical activity affects the aging process remains largely unexplored. We included 284 479 UK Biobank participants and computed leukocyte telomere length (LTL) deviation (ie, the difference between genetically determined and observed LTL) and biological age acceleration (defined as the discrepancy between the phenotypic age of a person and the average phenotypic age in the cohort of individuals with the same age and sex) as the indexes for aging acceleration. Linear and logistic models were used to estimate the associations of self-reported physical activity items and patterns (identified by principal component analysis), as well as accelerometer-assessed physical activity, with aging acceleration. Analyses of physical activity patterns indicated, a higher level of adherence to activity patterns predominated by strenuous sports, other exercises, walking for pleasure, heavy and light housework, and public transportation use was associated with a lower risk of aging acceleration, whereas a higher level of adherence to patterns predominated by job-related activities was associated with a higher risk of aging acceleration. Analysis among 62 418 participants with accelerometer-measured physical activity corroborated these results. Physical activity, such as strenuous sports and other exercises in leisure time and the use of public transportation, was associated with reduced biological aging. Besides highlighting the importance of engaging in physical activity for healthy aging, our results provide further evidence for the beneficial effect of physical activity on the telomere attrition process.

Indexed as

AgingBiological Specimen BanksExerciseHumansLeukocytesMotor ActivityTelomereUnited KingdomBiological agingLeukocyte telomere lengthPhysical activityPolygenic risk scorePrincipal component analysis

Identifiers

PMID36815559
PMCPMC10172984
OpenAlexW4321611339

What OpenQuestion holds

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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.