Evidence map›Paper›PMID 38886353›Full record

ArticleNature communications2024

Accelerometer-derived physical activity and mortality in individuals with type 2 diabetes.

Zhi Cao, Jiahao Min, Han Chen, Yabing Hou, Hongxi Yang, Keyi Si, Chenjie Xu

Erratum issuedAbstract read
In one paragraph

Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
–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

26 citing papers in PubMed, 1 synthesis or guideline pooled it.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors.

Zhi Cao *School of Public Health, Hangzhou Normal University, Hangzhou, China.
Jiahao Min *School of Public Health, Hangzhou Normal University, Hangzhou, China.
Han ChenSchool of Public Health, Hangzhou Normal University, Hangzhou, China.
Yabing HouYanjing Medical College, Capital Medical University, Beijing, China.
Hongxi YangSchool of Basic Medical Sciences, Tianjin Medical University, Tianjin, China.
Keyi SiSchool of Public Health, Shanghai Jiao Tong University School of Medicine, Shanghai, China. sikeyi0219@163.com.ORCID http://orcid.org/0000-0002-7413-615X
Chenjie XuSchool of Public Health, Hangzhou Normal University, Hangzhou, China. xuchenjie@hznu.edu.cn.ORCID http://orcid.org/0000-0002-8997-9299

Funding

Hangzhou Normal University (HNU) 4265C50221204119National Natural Science Foundation of China (National Science Foundation of China) 72204071Natural Science Foundation of Zhejiang Province (Zhejiang Provincial Natural Science Foundation) LY23G030005
6 · The paper itself

Abstract

Physical activity (PA) has been shown to reduce diabetes mortality, but largely based on imprecise self-reported data, which may hinder the development of related recommendations. Here, we perform a prospective cohort study of 19,624 individuals with type 2 diabetes (T2D) from the UK Biobank with a median follow-up of 6.9 years. Duration and intensity of PA are measured by wrist-worn accelerometers over a 7-day period. We observe L-shaped associations of longer duration of PA, regardless of PA intensity, with risks of all-cause and cancer mortality, as well as a negatively linear association with cardiovascular disease mortality. 12.7%, 15.8%, and 22.3% of deaths are attributable to the lowest level of light-intensity, moderate-intensity PA, and vigorous-intensity PA, respectively. Collectively, our findings provide insights for clinical guidelines that should highlight the potential value of adherence to greater intensity and duration of PA for patients with T2D.

Indexed as

AccelerometryDiabetes Mellitus, Type 2ExerciseAdultAgedCardiovascular DiseasesFemaleHumansMaleMiddle AgedNeoplasmsProspective StudiesUnited Kingdom

Identifiers

PMID38886353
PMCPMC11183112

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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.