Evidence map›Paper›PMID 35875029›Full record

ArticleFrontiers in public health2022

Poor Physical Capacity Combined With High Body Fat Percentage as an Independent Risk Factor for Incident Hypertension in Chinese Suburb-Dwelling Older Adults.

Peipei Han, Yuanyuan Zhang, Xiaoyu Chen, Zhenwen Liang, Xing Yu, Yuewen Liu, Sijia Sang, Jiayin Mao, Jingxuan Liu, Wuxiong Chen and 6 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in public health, 2022. 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
0.1field-weighted citation impact, top 55% 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.

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 citations in OpenAlex.

  1. 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

16 authors at 4 institutions in 1 country.

Peipei HanDepartment of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Yuanyuan ZhangDepartment of Rehabilitation Medicine, TEDA International Cardiovascular Hospital, Cardiovascular Clinical College of Tianjin Medical University, Tianjin, China.
Xiaoyu ChenCollege of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Zhenwen LiangCollege of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Xing YuCollege of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Yuewen LiuCollege of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Sijia SangCollege of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Jiayin MaoCollege of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Jingxuan LiuCollege of Rehabilitation Sciences, Shanghai University of Medicine and Health Sciences, Shanghai, China.
Wuxiong ChenDepartment of Rehabilitation Medicine, Shanghai Health Rehabilitation Hospital, Shanghai, China.
Junxue LiDepartment of Rehabilitation Medicine, Shanghai Health Rehabilitation Hospital, Shanghai, China.
Yazhou ChengDepartment of Rehabilitation Medicine, Shanghai Health Rehabilitation Hospital, Shanghai, China.
Yaqing ZhengFujian Provincial Hospital, Fuzhou, China.
Ziwei ZhangFujian Provincial Hospital, Fuzhou, China.
Ming LiDepartment of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Qi GuoDepartment of Rehabilitation Medicine, Shanghai University of Medicine and Health Sciences Affiliated Zhoupu Hospital, Shanghai, China.
Shanghai University of Medicine and Health Sciences · CNFujian Provincial Hospital · CNTEDA International Cardiovascular Hospital · CNTianjin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: This study examined the effects of poor physical capacity and high body fat percentage (BF%) on the incidence of hypertension in Chinese suburb-dwelling older adults. Methods: This study was conducted on 368 Chinese suburb-dwelling participants aged ≥ 60 years without hypertension (mean age: 66.74 ± 5.59 years, 48.9% men). Poor physical capacity is defined by the Asian Working Group for Sarcopenia (AWGS) criteria as grip strength < 26 kg for men and < 18 kg for women or walking speed <0.8 m/s. High BF% was defined as values that are greater than the upper tertile for BF% as stratified by sex. The outcome was the incidence of hypertension. Results: Overall, 5.7% of subjects had both poor physical capacity and high BF%. After the average follow-up duration of 2 years, the incidence of hypertension was 39.7%, and those experiencing both poor physical capacity and high BF% had the highest incidence (81.0%). After multivariate adjustments, the incidence of hypertension was associated with the combination of poor physical capacity and high BF% [odds ratio (OR) = 6.43, 95% CI = 1.91-21.64] but not solely with poor physical capacity (OR = 1.11, 95% CI = 0.55-2.25) or only high BF% (OR = 1.37, 95% CI = 0.80-2.34). Conclusion: The combination of poor physical capacity and high BF% can significantly increase the incidence of hypertension in Chinese suburb-dwelling older adults. For hypertension prevention, ideally, we should strive toward decreasing body fat mass while simultaneously improving physical capacity.

Indexed as

HypertensionAdipose TissueAgedBody Mass IndexChinaFemaleHumansMaleMiddle AgedRisk Factorsbody fat percentage (BF%)Chineseincident hypertensionolder adultsphysical capacity

Identifiers

PMID35875029
PMCPMC9296771
OpenAlexW4283834984

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.