Evidence map›Paper›PMID 37948020›Full record

ReviewCurrent hypertension reports2024

Effects of the Timing of Intense Physical Activity on Hypertension Risk in a General Population: A UK-Biobank Study.

Xiaying Li, Jingjing Zeng, Bo Chen, Menglin Fan, Jie Wang, Lingqi Wei, Yong Ren, Shaoyong Xu

Abstract readReview
PubMed Publisher
In one paragraph

Review in Current hypertension reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing 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

6 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
  5. Article
  6. 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

8 authors.

Xiaying LiCollege of Medicine, Wuhan University of Science & Technology, Wuhan, 430081, China.
Jingjing ZengCenter for Clinical Evidence-Based and Translational Medicine, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, 441021, China.
Bo ChenCenter for Clinical Evidence-Based and Translational Medicine, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, 441021, China.
Menglin FanCenter for Clinical Evidence-Based and Translational Medicine, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, 441021, China.
Jie WangDepartment of Endocrinology, Daxing Hospital, Xi'an, 710000, China.
Lingqi WeiCollege of Medicine, Wuhan University of Science & Technology, Wuhan, 430081, China.
Yong RenDepartment of Cardiology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, 441021, China. Renyong@hbuas.edu.cn.
Shaoyong XuDepartment of Endocrinology, Xiangyang Central Hospital, Affiliated Hospital of Hubei University of Arts and Science, Xiangyang, 441021, China. yoji_xu@hotmail.com.ORCID 0000-0002-8260-2456

Funding

Science and Technology Program of Hubei Province D20212602the Young Talents Project of Hubei Provincial Health Commission, China WJ2021Q012Xiangyang Science and Technology Plan Project, China 2019ZD12
6 · The paper itself

Abstract

purpose of reviewIt has recently been suggested that the timing of exercise is important in the subsequent development of hypertension. We used the UK Biobank database which prospectively collates data in over 500,000 people aged between 40 and 69 years to determine the relationship between the chronoactivity pattern of exercise and the risk of incident hypertension. RECENT

findingsWe analyzed data from 70,617 participants with 7-day Axivity AX3 triaxial accelerometry information available. Comparisons were made by a K-means clustering analysis separating groups according to the daily timing of physical activity and intensity. Subgroup, sensitivity analyses, and Cox proportional hazard model were performed. The mean age of the cohort was 61.17 (± 7.89) years with 40.05% men, and there was a mean follow-up of 7.54 (± 1.65) years. Participants were separated into 4 clusters with 6341 developing hypertension. Cluster 1 (early morning physical activity) and Cluster 2 (early morning and later physical activity) had a significantly reduced risk of incident hypertension (adjusted HR 0.870 [95%CI 0.812-0.932) vs. 0.895 [95%CI 0.825-0.972], respectively) when compared with Cluster 3 (physical activity intensity spread evenly throughout the day). Cluster 1 and Cluster 2 cases with High Intensity physical activity had a lower risk of hypertension; however, Low Intensity physical activity in Cluster 1 still reduced the risk of incident hypertension. There was a lower risk of hypertension in Cluster 1 and Cluster 2 in both morning and evening sleep chronotypes. The development of incident hypertension is significantly reduced in those who engage in some level of physical activity earlier in the day. Hypertension (high blood pressure) is a global problem with a high economic health burden that has been shown to be a major risk factor for diabetes, cardiovascular, and kidney disease. Our study has used a large maintained UK biological database to determine the impact of physical exercise on reducing the subsequent development of hypertension during follow-up from data provided by more than 70,000 participants. When we segregated patients into clusters of exercise timing, we found that the risk of developing hypertension over time was reduced for patients who performed exercise earlier in the morning than at other times of the day. This benefit was still evident even when the intensity of regular physical activity was low.

Indexed as

HypertensionAdultAgedBiological Specimen BanksExerciseFemaleHumansMaleMiddle AgedRisk FactorsUnited KingdomHypertensionPatternsPhysical activityTiming

Identifiers

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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.