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      Socioeconomic position and use of healthcare in the last year of life: A systematic review and meta-analysis

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          Abstract

          Background

          Low socioeconomic position (SEP) is recognized as a risk factor for worse health outcomes. How socioeconomic factors influence end-of-life care, and the magnitude of their effect, is not understood. This review aimed to synthesise and quantify the associations between measures of SEP and use of healthcare in the last year of life.

          Methods and findings

          MEDLINE, EMBASE, PsycINFO, CINAHL, and ASSIA databases were searched without language restrictions from inception to 1 February 2019. We included empirical observational studies from high-income countries reporting an association between SEP (e.g., income, education, occupation, private medical insurance status, housing tenure, housing quality, or area-based deprivation) and place of death, plus use of acute care, specialist and nonspecialist end-of-life care, advance care planning, and quality of care in the last year of life. Methodological quality was evaluated using the Newcastle-Ottawa Quality Assessment Scale (NOS). The overall strength and direction of associations was summarised, and where sufficient comparable data were available, adjusted odds ratios (ORs) were pooled and dose-response meta-regression performed.

          A total of 209 studies were included (mean NOS quality score of 4.8); 112 high- to medium-quality observational studies were used in the meta-synthesis and meta-analysis (53.5% from North America, 31.0% from Europe, 8.5% from Australia, and 7.0% from Asia). Compared to people living in the least deprived neighbourhoods, people living in the most deprived neighbourhoods were more likely to die in hospital versus home (OR 1.30, 95% CI 1.23–1.38, p < 0.001), to receive acute hospital-based care in the last 3 months of life (OR 1.16, 95% CI 1.08–1.25, p < 0.001), and to not receive specialist palliative care (OR 1.13, 95% CI 1.07–1.19, p < 0.001). For every quintile increase in area deprivation, hospital versus home death was more likely (OR 1.07, 95% CI 1.05–1.08, p < 0.001), and not receiving specialist palliative care was more likely (OR 1.03, 95% CI 1.02–1.05, p < 0.001). Compared to the most educated (qualifications or years of education completed), the least educated people were more likely to not receive specialist palliative care (OR 1.26, 95% CI 1.07–1.49, p = 0.005).

          The observational nature of the studies included and the focus on high-income countries limit the conclusions of this review.

          Conclusions

          In high-income countries, low SEP is a risk factor for hospital death as well as other indicators of potentially poor-quality end-of-life care, with evidence of a dose response indicating that inequality persists across the social stratum. These findings should stimulate widespread efforts to reduce socioeconomic inequality towards the end of life.

          Abstract

          Joanna Davies and colleagues highlight the association between low socioeconomic status and poor end of life care as well as increased risk of hospital death.

          Author summary

          Why was this study done?
          • Social inequality in health is a global phenomenon; people with lower socioeconomic position (SEP) experience earlier onset of disease and have reduced life expectancy.

          • Studies have identified low SEP as a risk factor for worse care at the end of life, and several socioeconomic factors have been identified as determinants of care towards the end of life.

          • Despite growing recognition, no empirical synthesis of evidence exists to support efforts to reduce socioeconomic inequality at the end of life.

          What did the researchers do and find?
          • We carried out a systematic review of studies that reported an association between a measure of SEP (including income, education, occupation, private medical insurance status, housing tenure, housing quality, or area-based deprivation) and healthcare received by adults in their last year of life (including place of death, use of acute care, use of specialist palliative care, use of nonspecialist end-of-life care, use of advance care planning, or quality of care) in high-income countries.

          • A total of 209 studies were included in the review; we found consistent evidence that low SEP increases the odds of hospital versus home death and of using acute care services in the last 3 months of life and reduces the odds of using specialist palliative care in the last year of life.

          • We also found that measurement of SEP in this field is dominated by measures of area deprivation and education, and justification for choice of SEP measure(s) is often inadequately described.

          What do these findings mean?
          • We have found consistent evidence of socioeconomic inequality in the care received by people towards the end of life, in that people with lower SEP are more likely to experience worse care.

          • We must now make further efforts to reduce this inequality.

          • We recommend the following: that all research on care received towards the end of life should attempt to account for SEP, end-of-life care interventions should be analysed for their different effects across the social strata, and the planning and provision of end-of-life care services should consider SEP in local populations.

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          Most cited references99

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          The Quality of Care

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            Facilitating meta-analyses by deriving relative effect and precision estimates for alternative comparisons from a set of estimates presented by exposure level or disease category.

            Epidemiological studies relating a particular exposure to a specified disease may present their results in a variety of ways. Often, results are presented as estimated odds ratios (or relative risks) and confidence intervals (CIs) for a number of categories of exposure, for example, by duration or level of exposure, compared with a single reference category, often the unexposed. For systematic literature review, and particularly meta-analysis, estimates for an alternative comparison of the categories, such as any exposure versus none, may be required. Obtaining these alternative comparisons is not straightforward, as the initial set of estimates is correlated. This paper describes a method for estimating these alternative comparisons based on the ideas originally put forward by Greenland and Longnecker, and provides implementations of the method, developed using Microsoft Excel and SAS. Examples of the method based on studies of smoking and cancer are given. The method also deals with results given by categories of disease (such as histological types of a cancer). The method allows the use of a more consistent comparison when summarizing published evidence, thus potentially improving the reliability of a meta-analysis. Copyright (c) 2007 John Wiley & Sons, Ltd.
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              Evidence based cardiology: psychosocial factors in the aetiology and prognosis of coronary heart disease. Systematic review of prospective cohort studies.

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                Author and article information

                Contributors
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: InvestigationRole: MethodologyRole: Project administrationRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: Data curationRole: Writing – review & editing
                Role: Funding acquisitionRole: ResourcesRole: SoftwareRole: SupervisionRole: Writing – review & editing
                Role: Funding acquisitionRole: SupervisionRole: Writing – review & editing
                Role: ConceptualizationRole: Data curationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: ConceptualizationRole: Formal analysisRole: Funding acquisitionRole: MethodologyRole: SupervisionRole: Writing – original draftRole: Writing – review & editing
                Role: Academic Editor
                Journal
                PLoS Med
                PLoS Med
                plos
                plosmed
                PLoS Medicine
                Public Library of Science (San Francisco, CA USA )
                1549-1277
                1549-1676
                23 April 2019
                April 2019
                : 16
                : 4
                : e1002782
                Affiliations
                [1 ] Cicely Saunders Institute of Palliative Care, Policy and Rehabilitation, King’s College London, London, United Kingdom
                [2 ] Health Intelligence, Public Health England, Bristol, United Kingdom
                [3 ] Wolfson Palliative Care Research Centre, Hull York Medical School, University of Hull, Hull, United Kingdom
                Weill Cornell Medical College, UNITED STATES
                Author notes

                The authors have declared that no competing interests exist.

                Author information
                http://orcid.org/0000-0002-6375-0023
                http://orcid.org/0000-0002-9777-4373
                http://orcid.org/0000-0002-9315-4871
                http://orcid.org/0000-0003-4709-7260
                Article
                PMEDICINE-D-18-03471
                10.1371/journal.pmed.1002782
                6478269
                31013279
                6bfbf5b8-dc65-433e-852b-8fff001db2c8
                © 2019 Davies et al

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

                History
                : 9 October 2018
                : 14 March 2019
                Page count
                Figures: 7, Tables: 1, Pages: 23
                Funding
                Funded by: funder-id http://dx.doi.org/10.13039/501100000377, Dunhill Medical Trust;
                Award ID: RTF74/0116
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000265, Medical Research Council;
                Award ID: CS-2015-15-005
                Award Recipient :
                Funded by: funder-id http://dx.doi.org/10.13039/501100000272, National Institute for Health Research;
                Award ID: CDF-2017-009
                Award Recipient :
                JMD is supported by a Research Training Fellowship from The Dunhill Medical Trust (RTF74/0116); //dunhillmedical.org.uk/. KES is supported by a National Institute for Health Research (NIHR) Clinician Scientist Fellowship (CS-2015-15-005); nihr.ac.uk. MM is supported by a National Institute for Health Research (NIHR) Career Development Fellowship (CDF-2017-009); nihr.ac.uk. IJH holds an NIHR Emeritus Senior Investigator Award; nihr.ac.uk. This work was supported by the NIHR Collaboration for Leadership in Applied Health Research and Care (CLAHRC) South London at King’s College Hospital NHS Foundation Trust. The funders had no role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Research Article
                Custom metadata
                All relevant data are within the manuscript and its Supporting Information files.

                Medicine
                Medicine

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