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Hanlon P, Politis M, Wightman H, Kirkpatrick S, Jones C, Khan M, Bezzina C, Mackinnon S, Rennison H, Wei L, Vetrano DL, Blane DN, Dent E, Hoogendijk EO. Frailty and socioeconomic position: A systematic review of observational studies. Ageing Res Rev 2024; 100:102420. [PMID: 39025269 DOI: 10.1016/j.arr.2024.102420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/02/2024] [Revised: 06/04/2024] [Accepted: 07/14/2024] [Indexed: 07/20/2024]
Abstract
BACKGROUND Frailty, an age-related state of reduced physiological reserve, is often associated with lower socio-economic position (SEP). This systematic review synthesised observational studies assessing (i) the association between SEP and frailty prevalence; (ii) how changes in frailty status over time vary by SEP; and (iii) whether the association between frailty and clinical outcomes is modified by SEP. METHODS We searched three electronic databases from 2001 to 2023. We included observational studies measuring early-, mid-, and late-life indicators of SEP (education, income, wealth, housing, occupation, and area-based measures of multiple deprivation) and frailty (assessed using any validated measure). Screening and extraction were performed in duplicate. Findings were synthesised using narrative synthesis. RESULTS We included 383 studies reporting findings from 265 independent samples/cohorts across 64 countries. Lower SEP was associated with higher frailty prevalence across all indicators (childhood deprivation 7/8 studies, education 227/248, occupation 28/32, housing 8/9, income 98/108, wealth 39/44 and area-based deprivation 32/34). Lower SEP was also associated with higher frailty incidence (27/30), with greater odds of transitioning towards a more severe frailty state (35/43), lower odds of frailty reversion (7/11), and (in some studies) with more rapid accumulation of deficits (7/15). The relationship between frailty and mortality was not modified by SEP. INTERPRETATION Preventative measures across multiple levels of individual and structural inequality are likely to be required to reduce the rising levels of frailty. Resourcing of interventions and services to support people living with frailty should be proportionate to needs in the population to avoid widening existing health inequalities.
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Affiliation(s)
- Peter Hanlon
- School of Health and Wellbeing, University of Glasgow, UK.
| | - Marina Politis
- School of Health and Wellbeing, University of Glasgow, UK
| | | | | | - Caitlin Jones
- School of Health and Wellbeing, University of Glasgow, UK
| | - Maryam Khan
- School of Health and Wellbeing, University of Glasgow, UK
| | - Cara Bezzina
- School of Health and Wellbeing, University of Glasgow, UK
| | | | - Heidi Rennison
- School of Health and Wellbeing, University of Glasgow, UK
| | - Lili Wei
- School of Health and Wellbeing, University of Glasgow, UK
| | - Davide Liborio Vetrano
- Aging Research Center, Department of Neurobiology, Care Sciences and Society, Karolinska Institutet, Tomtebodavägen 18 A, floors 9 and 10, Solna, Sweden; Stockholm Gerontology Research Center, Sveavägen 155, Stockholm, Sweden
| | - David N Blane
- School of Health and Wellbeing, University of Glasgow, UK
| | - Elsa Dent
- Caring Futures Institute, College of Nursing and Health Sciences, Flinders University, Adelaide, SA, Australia; Adelaide Primary Health Network, Adelaide, SA, Australia
| | - Emiel O Hoogendijk
- Department of Epidemiology & Data Science, Amsterdam UMC - Location VU University Medical Center, Amsterdam, the Netherlands
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Huang J, Gui Y, Wu J, Xie Y. Causal effects of socioeconomic traits on frailty: a Mendelian randomization study. Front Med (Lausanne) 2024; 11:1344217. [PMID: 39071086 PMCID: PMC11282504 DOI: 10.3389/fmed.2024.1344217] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/25/2023] [Accepted: 06/18/2024] [Indexed: 07/30/2024] Open
Abstract
Background The relationship between socioeconomic status and frailty has been extensively investigated in the literature, but it remains unclear whether a causal relationship exists. Our goal is to evaluate the causal relationship between six socioeconomic traits and the frailty index using summary-level data for single nucleotide polymorphisms from large genome-wide association studies with individuals of European ancestry. Methods A two-sample MR was performed. We applied the inverse variance weighted (IVW) method for the primary estimate, with sensitivity analyses conducted using alternative MR methods to evaluate the robustness of the findings. A subsequent multivariable MR was undertaken to adjust for the effects of body mass index (BMI). Finally, the MR Steiger directionality test was performed to confirm the causal direction. Results The IVW MR analysis revealed significant associations between various socioeconomic factors and the frailty index. Specifically, genetically predicated age completed full time education (β = -0.477, 95% confidence interval [CI]: -0.634 to -0.319) and average total household income before tax (β = -0.321, 95% CI: -0.410 to -0.232) were negatively associated with the frailty index. On the other hand, genetically predicted job involves heavy manual or physical work (β = 0.298, 95% CI: 0.113 to 0.484), job involves mainly walking or standing (β = 0.179, 95% CI: 0.013 to 0.345), Townsend deprivation index at recruitment (β = 0.535, 95% CI: 0.285 to 0.785), and social isolation/loneliness (β = 1.344, 95% CI: 0.834 to 1.853) were positively associated with the frailty index. Sensitivity analysis using other MR methods and multivariable MR analysis adjusting for BMI yielded stable results. The MR Steiger directionality test confirmed the causal direction. Conclusion Our findings highlight the importance of socioeconomic factors in affecting frailty risk. Future research should focus on unraveling the pathways through which these socioeconomic factors exert their effects on frailty, with the ultimate goal of developing targeted strategies to mitigate the risk of frailty.
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Affiliation(s)
- Jian Huang
- Clinical Laboratory Center, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Ying Gui
- Clinical Laboratory Center, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Jing Wu
- Clinical Laboratory Center, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Yubo Xie
- Department of Anesthesiology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
- Guangxi Key Laboratory of Enhanced Recovery After Surgery for Gastrointestinal Cancer, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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Gordon EH, Peel NM, Hubbard RE, Reid N. Frailty in younger adults in hospital. QJM 2023; 116:845-849. [PMID: 37467071 PMCID: PMC10593383 DOI: 10.1093/qjmed/hcad173] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/17/2023] [Revised: 07/13/2023] [Indexed: 07/21/2023] Open
Abstract
BACKGROUND Even though frailty has been extensively measured in the acute care setting, relatively little is known about the frailty of younger adult inpatients. AIM This study aimed to measure frailty in a sample of hospitalized adults aged 18 years and over and to examine how frailty in younger adult inpatients differs from middle-aged and older adult inpatients. DESIGN Secondary analyses of prospectively collected cohort data. METHODS Research nurses assessed 910 patients at admission to four Australian hospitals using the interRAI Acute Care instrument. Comparison of frailty index (FI) scores and domains was conducted across three age groups: younger (18-49 years), middle-aged (50-69 years) and older adults (≥70 years). Multivariable logistic regression examined risk of prolonged length of stay and unfavourable discharge destination. RESULTS Younger adults (n = 214; 23.5%) had a mean (SD) FI of 0.19 (0.10). Approximately 27% (n = 57) of younger adults were frail (FI > 0.25). Mood and behaviour, health symptoms and syndromes, nutrition and pain were the most frequently affected domains in younger adults and 50% had ≥3 comorbidities. Frailty increased the risk of long length of stay (odds ratio (OR) = 1.77, P < 0.001) but not the risk of an unfavourable discharge (OR = 1.40, P = 0.20) in younger adults. CONCLUSIONS This study showed that frailty is prevalent in younger patients admitted to acute care and is associated with adverse outcomes. This study was a critical first step towards establishing an understanding of frailty in younger hospitalized adults.
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Affiliation(s)
- E H Gordon
- From the Centre for Health Services Research, The University of Queensland, Brisbane, Australia
| | - N M Peel
- From the Centre for Health Services Research, The University of Queensland, Brisbane, Australia
| | - R E Hubbard
- From the Centre for Health Services Research, The University of Queensland, Brisbane, Australia
| | - N Reid
- From the Centre for Health Services Research, The University of Queensland, Brisbane, Australia
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Chitalu P, Tsui A, Searle SD, Davis D. Life-space, frailty, and health-related quality of life. BMC Geriatr 2022; 22:646. [PMID: 35931955 PMCID: PMC9356461 DOI: 10.1186/s12877-022-03355-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 07/30/2022] [Indexed: 11/10/2022] Open
Abstract
INTRODUCTION Life-space and frailty are closely linked to health-related quality of life and understanding their inter-relationship could indicate potential intervention targets for improving quality of life. We set out to examine the relationship between frailty and life-space and their relative impact on quality of life measures. METHODS Using cross-sectional data from a population-representative cohort of people aged ≥ 70 years, we assessed quality of life with the EuroQol Health Index tool (5-levels) (EQ-5D-5L). We also undertook a life-space assessment and derived a frailty index. Linear regression models estimated EQ-5D-5L scores (dependent variable) using life-space assessment, frailty index and interactions between them. All models were adjusted by age, sex, lifestyle, and social care factors. RESULTS A higher EQ-5D Index was associated with higher life-space (0.02 per life-space assessment score, 95%CI: 0.01 to 0.03, p < 0.01) and decreasing frailty (-0.1 per SD, 95%CI: -0.1 to -0.1, p < 0.01). There was evidence of an interaction between life-space and frailty, where the steepest gradient for life-space and EQ-5D was in those with the highest frailty (interaction term = 0.02 per SD of frailty, 95%CI: 0.01 to 0.03, p < 0.01). CONCLUSION Individuals with the highest frailty were twice as likely to have higher quality of life in association with a larger life-space. Interventions designed to improve quality of life in frail older people could focus on increasing a person's life-space.
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Affiliation(s)
- Petronella Chitalu
- MRC Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK.
| | - Alex Tsui
- MRC Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
| | - Samuel D Searle
- MRC Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK.,Division of Geriatric Medicine, Dalhousie University, Nova Scotia, Canada
| | - Daniel Davis
- MRC Unit for Lifelong Health and Ageing at UCL, 1-19 Torrington Place, London, WC1E 7HB, UK
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Tsui A, Searle SD, Bowden H, Hoffmann K, Hornby J, Goslett A, Weston-Clarke M, Hamill Howes L, Street R, Perera R, Taee K, Kustermann C, Chitalu P, Razavi B, Magni F, Das D, Kim S, Chaturvedi N, Sampson EL, Rockwood K, Cunningham C, Ely EW, Richardson SJ, Brayne C, Muniz Terrera G, Tieges Z, MacLullich A, Davis D. The effect of baseline cognition and delirium on long-term cognitive impairment and mortality: a prospective population-based study. THE LANCET. HEALTHY LONGEVITY 2022; 3:e232-e241. [PMID: 35382093 PMCID: PMC7612581 DOI: 10.1016/s2666-7568(22)00013-7] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/26/2023] Open
Abstract
Background There is an unmet public health need to understand better the relationship between baseline cognitive function, the occurrence and severity of delirium, and subsequent cognitive decline. Our aim was to quantify the relationship between baseline cognition and delirium and follow-up cognitive impairment. Methods We did a prospective longitudinal study in a stable representative community sample of adults aged 70 years or older who were registered with a Camden-based general practitioner in the London Borough of Camden (London, UK). Participants were recruited by invitation letters from general practice lists or by direct recruitment of patients from memory clinics or patients recently discharged from secondary care. We quantified baseline cognitive function with the modified Telephone Interview for Cognitive Status. In patients who were admitted to hospital, we undertook daily assessments of delirium using the Memorial Delirium Assessment Scale (MDAS). We estimated the association of pre-admission baseline cognitive function with delirium prevalence, severity, and duration. We assessed subsequent cognitive function 2 years after baseline recruitment using the Telephone Interview for Cognitive Status. Regression models were adjusted by age, sex, education, illness severity, and frailty. Findings We recruited 1510 participants (median age 77 [IQR 73-82], 57% women) between March, 2017, and October, 2018. 209 participants were admitted to hospital across 371 episodes (1999 person-days of assessment). Better baseline cognition was associated with a lower risk of delirium (odds ratio 0·63, 95% CI 0·45 to 0·89) and with less severe delirium (-1·6 MDAS point, 95% CI -2·6 to -0·7). Individuals with high baseline cognition (baseline Z score +2·0 SD) had demonstrable decline even without delirium (follow-up Z score +1·2 SD). However, those with a high delirium burden had an even larger absolute decline of 2·2 SD in Z score (follow-up Z score -0·2). Once individuals had more than 2 days of moderate delirium, the rates of death over 2 years were similar regardless of baseline cognition; a better baseline cognition no longer conferred any mortality benefit. Interpretation A higher baseline cognitive function is associated with a good prognosis with regard to likelihood and severity of delirium. However, those with a high baseline cognition and with delirium had the highest degree of cognitive decline, a change similar to the decline observed in individuals with a high amyloid burden in other cohorts. Older people with a healthy baseline cognitive function who develop delirium stand to lose the most after delirium. This group could benefit from targeted cognitive rehabilitation interventions after delirium.
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Affiliation(s)
- Alex Tsui
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Samuel D Searle
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
- Geriatric Medicine, Dalhousie University, Halifax, NS, Canada
| | - Helen Bowden
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Katrin Hoffmann
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Joanne Hornby
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Arley Goslett
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Maryse Weston-Clarke
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Lee Hamill Howes
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Rebecca Street
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Rachel Perera
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Kayvon Taee
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Christoph Kustermann
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Petronella Chitalu
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Benjamin Razavi
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Francesco Magni
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Devajit Das
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Sung Kim
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | - Nish Chaturvedi
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
| | | | - Kenneth Rockwood
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
- Geriatric Medicine, Dalhousie University, Halifax, NS, Canada
| | - Colm Cunningham
- School of Biochemistry & Immunology, Trinity Biomedical Sciences Institute, Dublin, Ireland
| | - E Wesley Ely
- Critical Illness, Brain Dysfunction, and Survivorship Center, Tennessee Valley Veterans Affairs Geriatric Research Education Clinical Center and Vanderbilt University Medical Center, Nashville, TN, USA
| | - Sarah J Richardson
- AGE Research Group, Translational and Clinical Research Institute, Newcastle University, Newcastle, UK
| | - Carol Brayne
- Department of Public Health and Primary Care, University of Cambridge, Cambridge, UK
| | | | - Zoë Tieges
- Geriatric Medicine, Edinburgh Delirium Research Group, Usher Institute, University of Edinburgh, Edinburgh, UK
- SMART Technology Centre, Glasgow Caledonian University, Glasgow, UK
| | - Alasdair MacLullich
- Geriatric Medicine, Edinburgh Delirium Research Group, Usher Institute, University of Edinburgh, Edinburgh, UK
| | - Daniel Davis
- Medical Research Council Unit for Lifelong Health and Ageing at University College London, University College London, London, UK
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