Evidence map›Paper›PMID 33071157›Full record

ArticleJournal of the American Medical Directors Association2021

Longitudinal Assessment of the Relationships Between Geriatric Conditions and Loneliness.

Kexin Yu, Shinyi Wu, Yuri Jang, Chih-Ping Chou, Kathleen H Wilber, María P Aranda, Iris Chi

Abstract read
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In one paragraph

Article in Journal of the American Medical Directors Association, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed
1.0field-weighted citation impact, top 18% 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

16 citing papers in PubMed, 18 citations in OpenAlex.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

7 authors at 1 institution in 2 countries.

Kexin YuSuzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA; Edward R. Roybal Institute on Aging, University of Southern California, Los Angeles, CA. Electronic address: kexin@usc.edu.
Shinyi WuSuzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA; Edward R. Roybal Institute on Aging, University of Southern California, Los Angeles, CA; Viterbi School of Engineering, Daniel J. Epstein Department of Industrial and Systems Engineering, University of Southern California, Los Angeles, CA.
Yuri JangSuzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA; Edward R. Roybal Institute on Aging, University of Southern California, Los Angeles, CA.
Chih-Ping ChouDepartment of Preventive Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA; Department of Bio-Industry Communication & Development, National Taiwan University, Taipei, Taiwan.
Kathleen H WilberLeonard Davis School of Gerontology, University of Southern California, Los Angeles, CA.
María P ArandaSuzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA; Edward R. Roybal Institute on Aging, University of Southern California, Los Angeles, CA.
Iris ChiSuzanne Dworak-Peck School of Social Work, University of Southern California, Los Angeles, CA; Edward R. Roybal Institute on Aging, University of Southern California, Los Angeles, CA.
University of Southern California · US

Funding

HRS Yrs29-34: Y33 SSA CoFundingU01AG009740 · NIA · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI Jessica Faul, KENNETH M LANGA · 1990 to 2026
$555.8M
NIA NIH HHS U01 AG009740
6 · The paper itself

Abstract

objectivesIn response to the lack of longitudinal evidence, this study aims to disentangle time sequence and directionality between the severity of geriatric conditions (GCs) and loneliness.

designLongitudinal panel study. SETTING AND

participantsThe working sample had 4680 participants of 2006, 2010, and 2014 waves of the Health and Retirement Study (HRS). All participants were at least 65 years old at baseline. Proxy responded cases and individuals who suffered from moderate to severe cognitive impairment were excluded from the analysis.

methodsLoneliness was measured with the 3-item UCLA loneliness scale. Five GCs were included: falls, incontinence, vision impairment, hearing impairment, and pain. Severity indicators were the number of times fallen in the past 2 years, number of days experiencing loss of bladder control in the past month, self-rated eyesight, self-rated hearing, and participants' perceived level of pain.

resultsRandom-intercept cross-lagged panel models were run to analyze the relationship between the severity of each individual GC and loneliness. All models were controlled for baseline demographics, social isolation, self-rated health, physical function, comorbidities, and hospitalization. The longitudinal association between loneliness and fall was bidirectional: a higher loneliness score predicted an increased number of falls and vice versa. Incontinence, vision impairment, hearing impairment, and pain were not significantly associated with loneliness longitudinally. The association between the random intercept of loneliness and some GCs (vision and pain) were significant, indicating the severity of these GCs were related to loneliness at the between-person level at baseline. CONCLUSION AND IMPLICATIONS: Findings of the longitudinal analysis suggest a reciprocal relationship between fall and loneliness. Fall prevention programs could be integrated with social service for addressing loneliness, and alleviating loneliness might be beneficial for preventing falls. Results of this study highlight the importance of integrating clinical management of falls with social services addressing loneliness in long term care.

Indexed as

Cognitive DysfunctionLonelinessAccidental FallsAgedHumansLongitudinal StudiesSocial Isolationfallgeriatric syndromelongitudinal analysisrandom intercept cross-lagged panel modelReciprocal relationships

Identifiers

PMID33071157
OpenAlexW3092666479

What OpenQuestion holds

Textmetadata
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.