Evidence map›Paper›PMID 42482005›Full record

ArticleBMC geriatrics2026

Associations of uric acid with wearable sensor-derived digital gait characteristics in older adults: vigor, symmetry, and stability.

Chi Zhang, Ye Liu, Yushan Zhang, Jing An, Yuting Kang, Jie Zhang, Guoqing Fan, Zehong Huo, Ping Zeng, Hong Shi and 2 more

Abstract read
In one paragraph

Article in BMC geriatrics, 2026. 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

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. 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

12 authors.

Chi Zhang *Department of Basic Innovation Research, Beijing Hospital, National Center for Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Beijing Key Laboratory of Aging Mechanism and Intervention Research On Aging-Related Diseases; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Ye Liu *Peking University Fifth School of Clinical Medicine, Beijing Hospital, National Center for Gerontology, Beijing, China.
Yushan ZhangDepartment of Geriatrics, Beijing Hospital, National Center for Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Jing AnCentral University of Finance and Economics Hospital, Beijing, China.
Yuting KangDepartment of Science Research, Beijing Hospital, National Center for Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Jie ZhangDepartment of Geriatrics, Beijing Hospital, National Center for Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Guoqing FanDepartment of Geriatrics, Beijing Hospital, National Center for Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Zehong HuoDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Beijing Key Laboratory of Aging Mechanism and Intervention Research On Aging-Related Diseases; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Ping ZengDepartment of Basic Innovation Research, Beijing Hospital, National Center for Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Beijing Key Laboratory of Aging Mechanism and Intervention Research On Aging-Related Diseases; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Hong ShiDepartment of Geriatrics, Beijing Hospital, National Center for Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China.
Ji ShenDepartment of Geriatrics, Beijing Hospital, National Center for Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China. shenji4350@bjhmoh.cn.
Jing LiDepartment of Geriatrics, Beijing Hospital, National Center for Gerontology; National Clinical Research Center for Gerontology; The Key Laboratory of Geriatrics of NHC; Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, China. lijing2762@bjhmoh.cn.

Funding

High Level Hospital Clinical Research Funding BJ-2022-133, BJ-2024-219National High Level Hospital Clinical Research Funding BJ-2025-240, BJ-2024-171National High Level Hospital Clinical Research Funding BJ-2025-253
6 · The paper itself

Abstract

objectiveElevated uric acid (UA) has been linked to impaired nervous system and skeletal muscle function. This study aimed to investigate the relationship between UA and digital gait characteristics in older adults.

methodsWe enrolled 651 older adults (≥ 60 years) who completed a wearable device-based walking test and blood sample detection. Multidimensional sensors were used to measure 15 gait parameters. Asymmetry index (AI) and coefficient of variation (CV) were calculated for each parameter. Multiple linear regression analyses were employed to examine the associations between UA and gait characteristics.

resultsThe mean age of all participants was 70.45 ± 6.12 years, with a mean UA concentration of 298.60 ± 92.39 μmol/L. After full adjustment for demographic characteristics and multiple health indicators, per 1-SD increase in UA was positively associated with swing time (β = 6.953, P = 0.007). Conversely, UA was negatively associated with thigh swing work (β = - 0.023, P = 0.003), foot landing control force (β = - 0.134, P < 0.001), stride frequency (β = - 1.074, P = 0.049) and stride length (β = - 0.014, P = 0.012). After false discovery rate (FDR) correction for multiple comparisons, all these associations remained statistically significant except for stride frequency. Higher UA levels were associated with higher AIs of thigh acceleration (β = 0.034, P = 0.013), ground reaction force (β = 0.033, P = 0.002), foot landing control force (β = 0.048, P < 0.001) and toe-off angle (β = 0.061, P = 0.001). UA was positively associated with CVs of swing time (β = 0.032, P < 0.001), ground reaction force (β = 0.015, P = 0.001), foot landing control force (β = 0.018, P = 0.001) and toe-off angle (β = 0.035, P = 0.002). All these associations with gait symmetry and stability indices remained statistically significant after FDR correction. Exploratory analyses identified high-sensitivity C-reactive protein, interleukin-6, superoxide dismutase, and glutathione reductase as potential biomarkers linking the association between UA and gait performance.

conclusionHigher UA levels are associated with poorer gait performance in terms of vigor, symmetry, and stability. The underlying inflammatory and oxidative stress mechanisms need to be elucidated in future experimental studies. CLINICAL TRIAL NUMBER: Not applicable.

Indexed as

GaitGait AnalysisUric AcidWearable Electronic DevicesAgedBiomarkersCross-Sectional StudiesFemaleHumansMaleMiddle AgedBiomarkersUric AcidGait mobilityOlder adultsUric acidWearable sensor

Identifiers

PMID42482005
PMCPMC13681825

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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.