Evidence map›Paper›PMID 27073263›Full record

ArticleInternational journal of epidemiology2016

Objectively measured physical activity and plasma metabolomics in the Shanghai Physical Activity Study.

Qian Xiao, Steven C Moore, Sarah K Keadle, Yong-Bing Xiang, Wei Zheng, Tricia M Peters, Michael F Leitzmann, Bu-Tian Ji, Joshua N Sampson, Xiao-Ou Shu and 1 more

Registry-linked trialOpen access · bronzeAbstract readEvaluation Study
In one paragraph

Article in International journal of epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT05672758 (The Effect of Long-lasting Adaptation to Intensive Speed-power and Endurance Training on Plasma Free Amino Acids Concentration at Rest, During Graded Exercise and Post-exercise Recovery), which is not on this map. Cited by 58 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed, 1 pooled it
5.6field-weighted citation impact, top 4% 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.

NCT05672758 unknown statusnot on this mapstarted 2018, after this paper: background citation

The Effect of Long-lasting Adaptation to Intensive Speed-power and Endurance Training on Plasma Free Amino Acids Concentration at Rest, During Graded Exercise and Post-exercise Recovery

TypeobservationalSponsorPoznan University of Physical EducationRan2018 to 2023Enrolled58ConditionsHealthy Athletes Aged 18-35 YearsArmsSprint training, Endurance training, Recreational Training
3 · Its place in the literature

Who cites it

58 citing papers in PubMed, 1 synthesis or guideline pooled it, 81 citations in OpenAlex.

  1. Metabolomic profiles of being physically active and less sedentary: a critical review.Metabolomics : Official journal of the Metabolomic Society · 2021
    Pooled it
  2. Trial
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  8. Leisure-time physical activity and metabolomic trajectories over the transition from late midlife to old age.The journals of gerontology. Series A, Biological sciences and medical sciences · 2026
    Article
  9. Article
  10. Observational
  11. Article
  12. Article
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  14. Article
  15. Physical activity, metabolites, and breast cancer associations.Journal of the National Cancer Institute · 2025
    Article
  16. Review
  17. Article
  18. Article
  19. Review
  20. Trends in insufficient physical activity among adults in China 2010-18: a population-based study.The international journal of behavioral nutrition and physical activity · 2023
    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

11 authors at 7 institutions in 4 countries.

Qian XiaoNutritional Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA xiaoq2@mail.nih.gov.
Steven C MooreNutritional Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
Sarah K KeadleNutritional Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
Yong-Bing XiangDepartment of Epidemiology, Shanghai Cancer Institute, Shanghai, China.
Wei ZhengVanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA.
Tricia M PetersDepartment of Internal Medicine, McGill University Health Center, Montreal, QC, Canada.
Michael F LeitzmannDepartment of Epidemiology and Preventive Medicine, University of Regensburg, Regensburg, Germany.
Bu-Tian JiOccupational and Environmental Epidemiology Branch.
Joshua N SampsonBiostatistics Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
Xiao-Ou ShuVanderbilt Epidemiology Center and Vanderbilt-Ingram Cancer Center, Vanderbilt University School of Medicine, Nashville, TN, USA.
Charles E MatthewsNutritional Epidemiology Branch, Division of Cancer Epidemiology and Genetics, National Cancer Institute, Rockville, MD, USA.
Division of Cancer Epidemiology and GeneticsVanderbilt University · USMcGill University Health Centre · CANational Cancer Institute · USShanghai Cancer Institute · CNSociety of Environmental Toxicology and Chemistry · USUniversity of Regensburg · DE

Funding

Physical Activity, Energy Balance, and CancerZIACP010197 · NCI · DIVISION OF CANCER EPIDEMIOLOGY AND GENETICS · PI ALBANES, DEMETRIUS · 2009 to 2025
$17.5M
Shanghai Womens Health StudyUM1CA182910 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ZHENG, WEI · 2014 to 2018
$5.9M
Shanghai Men's Health StudyUM1CA173640 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI SHU, XIAO-OU · 2013 to 2017
$4.9M
NCI NIH HHS UM1 CA173640NCI NIH HHS UM1 CA182910
6 · The paper itself

Abstract

backgroundPhysical activity is associated with a variety of health benefits, but the biological mechanisms that explain these associations remain unclear. Metabolomics is a powerful tool to comprehensively evaluate global metabolic signature associated with physical activity and helps to pinpoint the pathways that mediate the health effects of physical activity. There has been limited research on metabolomics and habitual physical activity, and no metabolomics study has examined sedentary behaviour and physical activity of different intensities.

methodsIn a group of Chinese adults (N = 277), we used an untargeted approach to examine 328 plasma metabolites in relation to accelerometer-measured physical activity, including overall volume of physical activity (physical activity energy expenditure (PAEE) and duration of physically active time) and sedentary time, and measures related to different intensities of physical activity (moderate-to-vigorous activity (MVPA), light activity, average physical activity intensity).

resultsWe identified 11 metabolites that were associated with total activity, with a false discovery rate of 0.2 or lower. Notably, we observed generally lower levels of amino acids in the valine, leucine and isoleucine metabolism pathway and of carbohydrates in sugar metabolism among participants with higher activity levels. Moreover, we found that PAEE, time spent in light activity and duration of physically active time were associated with a similar metabolic pattern, whereas the metabolic signature associated with sedentary time mirrored this pattern. In contrast, average activity intensity and time spent in MVPA appeared to be associated with somewhat different metabolic patterns.

conclusionsOverall, the metabolomics patterns support a beneficial role of higher volume of physical activity in cardiometabolic health. Our findings identified candidate pathways and provide insight into the mechanisms underlying the health effects of physical activity.

Indexed as

Energy MetabolismExerciseAccelerometryAdultAgedAmino AcidsBody Mass IndexChinaFemaleGas Chromatography-Mass SpectrometryHumansLinear ModelsLipidsMaleMetabolomicsMiddle AgedAmino AcidsLipidschronotypemetabolomicssleep durationsleep timing

Identifiers

PMID27073263
PMCPMC5100606
OpenAlexW2413540870

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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.