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Cited by 244Health disparities and outcomesHealth and Well-being StudiesHealth Systems, Economic Evaluations, Quality of Life

Quality of life and mortality in the general population: a systematic review and meta-analysis

Open access
Phyo, Aung Zaw Zaw, Freak-Poli, Rosanne, Craig, Heather, Gasevic, Danijela, Stocks, Nigel P., Gonzalez-Chica, David A., Ryan, Joanne·2020·BMC Public Health
DOI 10.1186/s12889-020-09639-9PMC PMC7646076

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Abstract

BACKGROUND: Quality of life (QoL) is multi-dimensional concept of an individual' general well-being status in relation to their value, environment, cultural and social context in which they live. This study aimed to quantitatively synthesise available evidence on the association between QoL and mortality in the general population. METHODS: An electronic search was conducted using three bibliographic databases, MEDLINE, EMBASE and PsycINFO. Inclusion criteria were studies that assessed QoL using standardized tools and examined mortality risk in a non-patient population. Qualitative data synthesis and meta-analyses using a random-effects model were performed. RESULTS: Of 4184 articles identified, 47 were eligible for inclusion, involving approximately 1,200,000 participants. Studies were highly heterogeneous in terms of QoL measures, population characteristics and data analysis. In total, 43 studies (91.5%) reported that better QoL was associated with lower mortality risk. The results of four meta-analyses indicated that higher health-related QoL (HRQoL) is associated with lower mortality risk, which was consistent for overall HRQoL (HR 0.633, 95% CI: 0.514 to 0.780), physical function (HR 0.987, 95% CI: 0.982 to 0.992), physical component score (OR 0.950, 95% CI: 0.935 to 0.965), and mental component score (OR 0.980, 95% CI: 0.969 to 0.992). CONCLUSION: These findings provide evidence that better QoL/HRQoL was associated with lower mortality risk. The utility of these measures in predicting mortality risk indicates that they should be considered further as potential screening tools in general clinical practice, beyond the traditional objective measures such as body mass index and the results of laboratory tests.

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  • SF-36v2 measures predict long-term mortality risk.

    “While the SF‐36v2 provides participants' subjective responses, these measures are relevant, as they have been shown to predict long‐term mortality risk.”

    From Body composition changes during weight reduction with tirzepatide in the <scp>SURMOUNT</scp> ‐1 study of adults with obesity or overweight (2025) · cites this paper as [20]

    The Results (Meta-analyses) link SF-36 physical scores to all-cause mortality, and the Description of included studies reports associations over follow-up periods extending to 12–15 years. The paper identifies these measures as SF-36, however, and does not establish the finding specifically for SF-36v2. (LLM, conf=0.83)

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  1. [34]Covidence systematic review software, Veritas Health Innovation, Melbourne, Australia [cited 2019 June 10]. Available from: www.covidence.org.

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Authors
Phyo, A. Z. Z., Freak-Poli, R., Craig, H., Gasevic, D., Stocks, N. P., Gonzalez-Chica, D. A., & Ryan, J.
Affiliations
  • Monash University (AU)
  • The University of Adelaide (AU)
  • Inserm (FR)
Corresponding author
Ryan, Joanne
ORCID
Venue
BMC Public Health
Publisher
Springer Science and Business Media LLC
Published
2020-11-06
Volume
20
Issue
1
Pages
1596-1596
ISSN
1471-2458 (ISSN-L)
DOI
10.1186/s12889-020-09639-9
PMC
PMC7646076
OpenAlex
W3097138102
Cited by
243
References
94
Citations by year
2026: 26 · 2025: 68 · 2024: 58 · 2023: 41 · 2022: 29 · 2021: 18 · 2020: 1 · 2012: 1
FWCI
3.49
Type
journal article
Language
en
Open access
Licence
Locations
  • BMC Public Health (publishedVersion, cc-by)
  • Research Square (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • EUR Research Repository (Erasmus University Rotterdam) (publishedVersion, other-oa)
  • Cross Connect (Southern Cross University) (submittedVersion)
  • Minerva Access (University of Melbourne) (submittedVersion, cc-by)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, cc-by)
  • EUR Research Repository (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • RePub (Erasmus University Rotterdam) (submittedVersion, other-oa)
  • Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion, cc-by)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
  • Figshare (cc-by)
Funders
  • Monash University (Monash International Tuition Scholarship and Monash Graduate Scholarship Student ID: 30072360)
  • National Health and Medical Research Council (Dementia Research Leader Fellowship (APP1135727))
Topics
  • Social Sciences › Health › Health disparities and outcomes
  • Social Sciences › Psychology › Clinical Psychology › Health and Well-being Studies
  • Social Sciences › Economics, Econometrics and Finance › Economics and Econometrics › Health Systems, Economic Evaluations, Quality of Life
Keywords
quality of life, health-related quality of life, mortality risk, physical function, physical component summary, mental component score, mortality prediction, screening tool, general population
MeSH terms
Humans, Mass Screening, Quality of Life

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