Evidence map›Paper›PMID 41249987›Full record

ArticleBMC geriatrics2025

Two-year evolution of frailty status and predictive factors in Chinese older adults: a national longitudinal study.

Jing Shi, Luyao Zhang, Yongkang Tao, Chao Gao, Yan Cen, Sainan Li, Ying Li, Botao Sang, Xiangfei Liu, Qinan Ma and 3 more

Abstract read
In one paragraph

Article in BMC geriatrics, 2025. 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

13 authors.

Jing Shi *The Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital, National Center of Gerontology of National Health Commission, Beijing, 100730, China.
Luyao Zhang *Department of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Yongkang TaoDepartment of Gastroenterology, China-Japan Friendship Hospital, Beijing, 100029, China.
Chao GaoThe Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital, National Center of Gerontology of National Health Commission, Beijing, 100730, China.
Yan CenThe Key Laboratory of Geriatrics, Beijing Institute of Geriatrics, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing Hospital, National Center of Gerontology of National Health Commission, Beijing, 100730, China.
Sainan LiDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Ying LiDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Botao SangDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Xiangfei LiuDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Qinan MaDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Xuezai ZengDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China.
Yan ZhangDepartment of General Practice/VIP Medical Service, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China. zhangyan3025@bjhmoh.cn.
Deping LiuDepartment of Cardiology, Beijing Hospital, National Center of Gerontology, Institute of Geriatric Medicine, Chinese Academy of Medical Sciences, Beijing, 100730, China. lliudeping@263.net.

Funding

National High Level Hospital Clinical Research Funding BJ-2023-018National Key R&D Program of China 2020YFC2003000 and 2020YFC2003001
6 · The paper itself

Abstract

backgroundWith the global aging population, frailty in older adults has emerged as a critical focus in health and aging research. As a dynamic and multifactorial process, the transition to frailty is shaped by not only biological factors but also a range of social, psychological, and environmental influences. Identifying the key factors that drive the progression of frailty is essential for developing preventive interventions for at-risk individuals and for implementing more effective health practices and healthcare strategies for older adults.

methodsData for this study were drawn from the Fourth Sample Survey of the Aged Population in Urban and Rural China, organized by the China National Committee on Ageing. The baseline data were collected from older individuals who participated in the 2017 survey, and the follow-up data were from the 2019 survey. Frailty in older adults was assessed using the Frailty Index (FI) model, which was used to examine the current frailty status among older adults in China and to prospectively analyze the developmental trajectory of frailty. Logistic regression was used to identify the factors influencing the progression of frailty.

resultsA total of 9,093 older adults were included in the analysis. FI values increased with age and were consistently higher in women than in men, indicating that older women had higher levels of frailty. During the two-year follow-up period, frailty status remained stable in most older adults (56.2%, 5,111/9,093), while 1,292 (14.2%, 1,292/9,093) experienced an improvement and 2,690 (29.6%, 2,690/9,093) experienced a worsening of frailty. Transitions to a more frail state were more common than transitions to an improved state. Additionally, transitions between adjacent frailty statuses were much more frequent than transitions across multiple frailty categories (3,669 (40.3%) versus 313 (3.4%)). Logistic regression analysis identified several factors influencing the progression of frailty status in older adults, including demographic factors (age, sex, residence, education, and marital status); family and economic status (living alone, employment, pension receipt, home ownership, financial status); health and medical factors (exercise, recent illness, annual medical checkups, hospitalizations); caregiver support; and social participation (public welfare participation, involvement in senior associations, helping seniors in need, recreational participation, and regular internet access).

conclusionThe worsening of frailty with age is more common in older adults than the improvement of frailty. Among robust and pre-frail individuals, older women are more likely to experience a deterioration in frailty status. The factors influencing frailty transitions are multifaceted and complex. Therefore, when intervening in the progression of frailty among older adults, it is essential to comprehensively assess frailty risks and influencing factors based on the diverse characteristics and current status of individuals. Individualized, comprehensive, and targeted interventions and management strategies, tailored to different frailty stages and transition pathways, can help improve frailty in older adults.

Indexed as

AgingFrail ElderlyFrailtyGeriatric AssessmentAgedAged, 80 and overChinaDisease ProgressionEast Asian PeopleFemaleFollow-Up StudiesHumansLongitudinal StudiesMaleFrailty statusLongitudinal studyNational surveyPredictive factors

Identifiers

PMID41249987
PMCPMC12625474

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