Evidence map›Paper›PMID 41721286›Full record

ArticleBMC public health2026

Trends and lifestyle contributions to frailty in US adults aged 50 and older: analysis of health and retirement study data (2004-2020).

Shui-Kit Cheuk, Hui-Wen Xu, Yuming Chen, He-Xuan Su, Hui Liu, Kaipeng Wang, Zhou Yang, Le Ma, Hui-Jing Zhang, Yanran Deng and 2 more

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in BMC public health, 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.

Shui-Kit CheukDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Hui-Wen XuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Yuming ChenDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
He-Xuan SuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Hui LiuMedical Informatics Center, Institute of Advanced Clinical Medicine, Peking University, Beijing, China.
Kaipeng WangSchool of Social Work, University of Washington, Seattle, WA, USA.
Zhou YangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Le MaDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Hui-Jing ZhangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Yanran DengDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Ngeemasara ThapaMedical Informatics Center, Institute of Advanced Clinical Medicine, Peking University, Beijing, China.
Beibei XuMedical Informatics Center, Institute of Advanced Clinical Medicine, Peking University, Beijing, China. xubeibei@bjmu.edu.cn.

Funding

National Natural Science Foundation of China 82273712
6 · The paper itself

Abstract

backgroundFrailty is a critical geriatric syndrome associated with modifiable lifestyle factors, yet their population-level contributions remain unclear. This study aimed to quantify the proportion of frailty incidence attributable to modifiable lifestyle factors and assess temporal trends in the US.

methodsWe analyzed data from 26,247 participants in the Health and Retirement Study (2004–2020) involving adults aged ≥ 50 years. Frailty was assessed using the Paulson-Lichtenberg Frailty Index. Lifestyle exposures included smoking, drinking, physical inactivity, and sleep disturbance. Associations between lifestyle factors and frailty were examined using Cox models. Population attributable fractions (PAFs) were calculated for each factor, with temporal trends assessed using generalized estimating equations with splines.

resultsFrom 2004 to 2020, frailty incidence declined from 55.2 to 46.6 per 1,000 person-years. Current smoking (HR = 1.46, 95% CI: 1.38, 1.55), physical inactivity (HR = 1.56, 95% CI: 1.48, 1.65), and sleep disturbance (HR = 1.42, 95% CI: 1.36, 1.47) were positively associated with frailty, while current drinking (HR = 0.79, 95% CI: 0.76, 0.83) was negatively associated. The PAFs analyses revealed that sleep disturbance (PAF = 14.43%) and non-current drinking (13.91%) were the leading contributors of frailty, followed by physical inactivity (5.45%) and smoking (5.08%). Only the contribution of physical inactivity increased significantly over time (Ptrend < 0.01).

conclusionFour lifestyle factors collectively accounted for nearly 40% of frailty cases among US adults aged ≥ 50 years. The apparent protective role of drinking warrants caution due to potential “sick quitter” bias. The increasing contribution of physical inactivity highlights the need for prioritizing exercise promotion in frailty prevention.

Indexed as

FrailtyLife StyleAgedAged, 80 and overAlcohol DrinkingFemaleHumansIncidenceMaleMiddle AgedRisk FactorsSedentary BehaviorSmokingUnited StatesDrinkingFrailtyLifestylesMiddle-aged and older adultsPhysical activity

Identifiers

PMID41721286
PMCPMC13032618

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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.