Evidence map›Paper›PMID 33774807›Full record

SynthesisSports medicine (Auckland, N.Z.)2021

Association of Cycling with Risk of All-Cause and Cardiovascular Disease Mortality: A Systematic Review and Dose-Response Meta-analysis of Prospective Cohort Studies.

Yang Zhao, Fulan Hu, Yifei Feng, Xingjin Yang, Yang Li, Chunmei Guo, Quanman Li, Gang Tian, Ranran Qie, Minghui Han and 12 more

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Sports medicine (Auckland, N.Z.), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers, 3 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed, 3 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

18 citing papers in PubMed, 3 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Pooled it
  4. Trial
  5. Article
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  13. Don't Ask Us to Stop Cycling: A Surgical Perspective.Annals of surgery open : perspectives of surgical history, education, and clinical approaches · 2024
    Article
  14. Review
  15. Article
  16. Review
  17. Article
  18. National Trends in Cycling in Light of the Norwegian Bike Traffic Index.International journal of environmental research and public health · 2021
    Article
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

22 authors.

Yang Zhao *Department of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Fulan Hu *Department of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.
Yifei FengDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Xingjin YangDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Yang LiDepartment of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.
Chunmei GuoDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Quanman LiDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Gang TianDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Ranran QieDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Minghui HanDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Shengbing HuangDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Xiaoyan WuDepartment of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.
Yanyan ZhangDepartment of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.
Yuying WuDepartment of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.
Dechen LiuDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Dongdong ZhangDepartment of Nutrition and Food Hygiene, College of Public Health, Zhengzhou University, Zhengzhou, Henan, People's Republic of China.
Cheng ChengDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Ming ZhangDepartment of Epidemiology, School of Public Health, Shenzhen University Health Science Center, Shenzhen, Guangdong, People's Republic of China.
Yongli YangDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Xuezhong ShiDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Jie LuDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China.
Dongsheng HuDepartment of Epidemiology and Health Statistics, College of Public Health, Zhengzhou University, 100 Kexue Avenue, Zhengzhou, 450001, Henan, People's Republic of China. dongshenghu563@126.com.ORCID http://orcid.org/0000-0002-9998-8041

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCycling has been suggested to be related to risk of all-cause and cardiovascular disease (CVD) mortality. However, a quantitative comprehensive assessment of the dose-response association of cycling with risk of all-cause and CVD mortality has not been reported. We performed a meta-analysis of cohort studies assessing the risk of all-cause and CVD mortality with cycling.

methodsPubMed and Embase databases were searched for relevant articles published up to December 13, 2019. Random-effects models were used to estimate the summary relative risk (RR) of all-cause and CVD mortality with cycling. Restricted cubic splines were used to evaluate the dose-response association.

resultsWe included 9 articles (17 studies) with 478,847 participants and 27,860 cases (22,415 from all-cause mortality and 5445 from CVD mortality) in the meta-analysis. Risk of all-cause mortality was reduced 23% with the highest versus lowest cycling level [RR 0.77, 95% confidence interval (CI) 0.67-0.88], and CVD mortality was reduced 24% (RR 0.76, 95% CI 0.65-0.89). We found a linear association between cycling and all-cause mortality (P

conclusionsOur findings based on quantitative data suggest that any level of cycling is better than none for all-cause mortality. However, for CVD mortality, one must choose an appropriate level of cycling, with an approximate optimum of 15 MET-h/week (equal to 130 min/week at 6.8 MET).

Indexed as

Cardiovascular DiseasesCohort StudiesHumansProspective StudiesRiskRisk Factors

Identifiers

PMID33774807

What OpenQuestion holds

Textmetadata
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.