Evidence map›Paper›PMID 33228605›Full record

ArticleBMC geriatrics2020

Independent and synergistic effects of pain, insomnia, and depression on falls among older adults: a longitudinal study.

Yuxiao Li, Minhui Liu, Xiaocao Sun, Tianxue Hou, Siyuan Tang, Sarah L Szanton

Open access · goldAbstract read
In one paragraph

Article in BMC geriatrics, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
7.4field-weighted citation impact, top 3% 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

15 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Observational
  9. Review
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. 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

6 authors at 2 institutions in 2 countries.

Yuxiao LiCentral South University, Xiangya School of Nursing, Changsha, 172 Tongzipo Road of Yuelu District, Changsha, 410013, Hunan, China.
Minhui LiuCentral South University, Xiangya School of Nursing, Changsha, 172 Tongzipo Road of Yuelu District, Changsha, 410013, Hunan, China. mliu62@jhu.edu.ORCID 0000-0002-4554-3135
Xiaocao SunCentral South University, Xiangya School of Nursing, Changsha, 172 Tongzipo Road of Yuelu District, Changsha, 410013, Hunan, China.
Tianxue HouCentral South University, Xiangya School of Nursing, Changsha, 172 Tongzipo Road of Yuelu District, Changsha, 410013, Hunan, China.
Siyuan TangCentral South University, Xiangya School of Nursing, Changsha, 172 Tongzipo Road of Yuelu District, Changsha, 410013, Hunan, China.
Sarah L SzantonJohns Hopkins University School of Nursing, Baltimore, MD, USA.
Central South University · CNJohns Hopkins University · US

Funding

The National Health and Trends StudyU01AG032947 · NIA · JOHNS HOPKINS UNIVERSITY · PI VICKI A. FREEDMAN, JENNIFER ANN SCHRACK · 2008 to 2026
$169.4M
NIA NIH HHS U01 AG032947
6 · The paper itself

Abstract

backgroundFew studies have examined the relationship between falls and pain, insomnia and depressive symptoms which are common and risk factors in older adults. We aimed to examine the independent and synergistic effects of these risk factors on future falls among older adults.

methodsWe used data of 2558 community-dwelling older adults from 2011 (Y1) to 2015 (Y5) of the National Health and Aging Trends Study (NHATS). Pain was determined by whether participants reported bothersome pain in the last month. Insomnia was assessed by two questions about how often the participants had trouble falling asleep and maintaining sleep. Depressive symptoms were assessed by Patient Health Questionnaire-2. Generalized estimation equation (GEE) models were used to examine the independent effects of pain, insomnia and depressive symptoms at prior-wave (period y-1) on falls at current wave (period y) adjusting for covariates (age, sex, education, race/ethnicity, living arrangement, BMI, smoking, vigorous activities, number of chronic illnesses and hospitalization). The significance of the three-way interaction of these factors (pain*insomnia*depression) was tested using the aforementioned GEE models to determine their synergistic effects on falls.

resultsOverall, the participants were mainly 65-79 years old (68%), female (57%) and non-Hispanic White (70%). At Y1, 50.0% of the participants reported pain, 22.6% reported insomnia and 9.9% reported depressive symptoms. The incidence of falls from Y2 to Y5 was 22.4, 26.0, 28.3, and 28.9%, respectively. Participants with pain (Odds ratio [OR], 95% confidence interval [CI] = 1.36, 1.23-1.50) and depressive symptoms (OR, 95% CI = 1.43, 1.23-1.67) had high rates of falling adjusting for covariates. After further adjustment for insomnia and depressive symptoms, pain independently predicted falls (OR, 95% CI = 1.36, 1.22-1.51). Depressive symptoms also independently predicted falls after further adjusting for pain and insomnia (OR, 95% CI = 1.40, 1.20-1.63). After adjusting for pain and depression, the independent effects of insomnia were not significant. None of the interaction terms of the three risk factors were significant, suggesting an absence of their synergistic effects.

conclusionsPain and depressive symptoms independently predict falls, but synergistic effects seem absent. Further research is needed to develop effective strategies for reducing falls in older adults, particularly with pain and depressive symptoms.

Indexed as

Sleep Initiation and Maintenance DisordersAgedDepressionFemaleHumansIndependent LivingLongitudinal StudiesMalePainDepressive symptomsFallsInsomniaOlder adultsPain

Identifiers

PMID33228605
PMCPMC7684923
OpenAlexW3107756407

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.