Evidence map›Paper›PMID 40018553›Full record

ArticleBMJ public health2024

Association between bike-sharing systems and the blood pressure of local citizens: a cross-sectional study in China.

Sumit Agarwal, Bing Li, Wenlan Qian, Yuan Ren, Rongju Sun

Abstract read
In one paragraph

Article in BMJ public health, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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

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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

1 citing paper in PubMed.

  1. Review
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

5 authors.

Sumit AgarwalBusiness School, National University of Singapore, Singapore.
Bing LiDepartment of Economics, Lingnan College, Sun Yat-sen University, Guangzhou, Guangdong, China.
Wenlan QianBusiness School, National University of Singapore, Singapore.
Yuan RenSchool of Economics and Academy of Financial Research, Zhejiang University, Hangzhou, Zhejiang, China.ORCID 0009-0000-1498-8900
Rongju SunDepartment of Emergency, Eighth Medical Center, Chinese PLA General Hospital, Beijing, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Introduction: Globally, hypertension stands as the foremost preventable risk factor for cardiovascular disease and premature death. However, scalable approach to lowering blood pressure (BP) at the population level remains lacking. We investigated whether shared bikes, a sustainable method of transportation gaining increasing popularity across the world, can serve as a supplemental instrument to combat the increasing prevalence of hypertension. Methods: Based on 8 107 363 physical examination visits to one of the largest medical examination centres in China during the period of June 2016 to August 2017, we perfermed a staggered difference-in-differences (DiD) analysis that exploited the roll-out of bike-sharing systems across different cities. The main outcome was the blood pressure among adult participants who were likely to adopt shared bikes (age <45), measured by (1) systolic blood pressure (SBP), (2) diastolic blood pressure (DBP) and (3) a binary indicator of hypertension status (SBP≥130 or DBP≥80 mm Hg). Results: Blood pressure showed a decreasing trend after a bike-sharing platform entered the local city. After 6 months post an entry event, SBP reduced by 0.67 mm Hg (β (SE), -0.672 (0.245); 95% CI, -1.154 to -0.191); the prevalence of hypertension reduced by 1.4 percentage points (β (SE), -0.014 (0.007); 95% CI, -0.027 to -0.000); the reduction in DBP was statistically insignificant (β (SE), -0.193 (0.193); 95% CI, -0.572 to 0.187). Participants less likely to adopt shared bikes (age ≥45) showed no significant response. The number of visits and the age of participants were also unaffected by the entry events. Reduction in blood pressure was more pronounced in male, younger and non-obese participants. Conclusion: The findings of this study suggest that bike-sharing systems in China may be associated with lowered blood pressure, and thus may serve as a supplemental instrument to combat the increasing prevalence of hypertension, especially among young adults.

Indexed as

EpidemiologyPrevalencePublic Health

Identifiers

PMID40018553
PMCPMC11816577

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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.