Evidence map›Paper›PMID 41354857›Full record

ArticleScientific reports2025

Longitudinal trajectories of health-related quality of life and their predictors among community-dwelling older adults.

Ryoga Oshima, Yuki Ohashi, Takuro Iwane, Yoshinori Tamada, Fumie Kinoshita, Tomoya Ito, Yuto Okumura, Tatsuya Mikami, Ken Itoh, Koichi Murashita and 1 more

Abstract read
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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

11 authors.

Ryoga Oshima *Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20 Daiko-Minami, Higashi-ku, Nagoya, 461-8673, Japan.
Yuki Ohashi *Public Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20 Daiko-Minami, Higashi-ku, Nagoya, 461-8673, Japan.
Takuro IwaneResearch Institute of Health Innovation, Hirosaki University, Hirosaki, Japan.
Yoshinori TamadaDepartment of Medical Data Intelligence, Research Center for Health-Medical Data Science (RCoHMDS), Hirosaki University Graduate School of Medicine, Hirosaki, Japan.
Fumie KinoshitaDepartment of Advanced Medicine, Data Science Division, Data Coordinating Center, Nagoya University Hospital, Nagoya, Japan.
Tomoya ItoPublic Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20 Daiko-Minami, Higashi-ku, Nagoya, 461-8673, Japan.
Yuto OkumuraPublic Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20 Daiko-Minami, Higashi-ku, Nagoya, 461-8673, Japan.
Tatsuya MikamiDepartment of Preemptive Medicine, Innovation Center for Health Promotion, Hirosaki University Graduate School of Medicine, Hirosaki, Japan.
Ken ItohDepartment of Stress Response Science, Biomedical Research Center, Hirosaki University Graduate School of Medicine, Hirosaki, Japan.
Koichi MurashitaResearch Institute of Health Innovation, Hirosaki University, Hirosaki, Japan.
Masahiro NakatochiPublic Health Informatics Unit, Department of Integrated Health Sciences, Nagoya University Graduate School of Medicine, 1-1-20 Daiko-Minami, Higashi-ku, Nagoya, 461-8673, Japan. mnakatochi@met.nagoya-u.ac.jp.

Funding

Center of Innovation Program from Japan Science and Technology Agency JPMJCE1302Center of Innovation Program from Japan Science and Technology Agency JPMJPF2210
6 · The paper itself

Abstract

The 36-item Short-Form Health Survey (SF-36) is widely used to assess health-related quality of life. However, only few studies have examined longitudinal SF-36 trajectories in general populations, and even fewer have explored their relationships with lifestyle factors, including sleep quality. We conducted a longitudinal analysis of SF-36 subscale trajectories among 910 Japanese individuals aged ≥ 60 years from 2007 to 2018 (4,799 records). Using latent class mixed models, we identified distinct trajectory patterns for each subscale. Notably, the role-physical (RP) and role-emotional (RE) subscales exhibited multiple patterns, including rapid decline and non-decline trajectories. We further examined predictors that differentiated between these two trajectory patterns-rapid decline and non-decline-with similar baseline scores. Consequently, poor performance on the open-eye one-leg standing test and higher depression scores on the Centre for Epidemiologic Studies Depression Scale predicted RP and RE declines, respectively. Importantly, poor sleep quality, as measured by the Pittsburgh Sleep Quality Index-particularly the total score and component 7 (daytime dysfunction)-was associated with subsequent RP and RE declines. In contrast, sleep timing variables (bedtime, sleep onset, and wake-up time) were not predictive. These findings suggest that preserving good sleep quality may help prevent future limitations in daily physical and emotional roles.

Indexed as

Independent LivingQuality of LifeAgedAged, 80 and overDepressionFemaleHealth SurveysHumansJapanLongitudinal StudiesMaleMiddle AgedSleepSleep Quality

Identifiers

PMID41354857
PMCPMC12783101

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.