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      Unmet healthcare needs and health inequalities in people with spinal cord injury: a direct regression inequality decomposition

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          Abstract

          Background

          Inequality in health is a prevalent and growing concern among countries where people with disabilities are disproportionately affected. Unmet healthcare needs explain a large part of the observed inequalities between and within countries; however, there are other causes, many non-modifiable, that also play a role.

          Aim

          This article explores the difference in health across income levels in populations with spinal cord injury (SCI). SCI is of special interest in the study of health systems, as it is an irreversible, long-term health condition that combines a high level of impairment with subsequent comorbidities.

          Methods

          We estimated the importance of modifiable and non-modifiable factors that explain health inequalities through a direct regression approach. We used two health outcomes: years living with the injury and a comorbidity index. Data come from the International Spinal Cord Injury Survey (InSCI), which has individual data on people with SCI in 22 countries around the world. Due to the heterogeneity of the data, the results were estimated country by country.

          Results

          On average, the results exhibit a prevalence of pro-rich inequalities, i.e., better health outcomes are more likely observed among high-income groups. For the years living with the injury, the inequality is mostly explained by non-modifiable factors, like the age at the time of the injury. In contrast, for the comorbidity index, inequality is mostly explained by unmet healthcare needs and the cause of the injury, which are modifiable factors.

          Conclusions

          A significant portion of health inequalities is explained by modifiable factors like unmet healthcare needs or the type of accident. This result is prevalent in low, middle, and high-income countries, with pervasive effects for vulnerable populations like people with SCI, who, at the same time are highly dependent on the health system. To reduce inequity, it is important not only to address problems from public health but from inequalities of opportunities, risks, and income in the population.

          Highlights

          • Better health status is evident among high-income groups, which is reflected in pro-rich inequalities.

          • Age at the time of the injury is the most important factor to explain inequalities in years living with the injury.

          • Unmet health care needs are the most important factor to explain inequalities in comorbidities.

          • The inequality in health varies by country dependent upon socioeconomic factors.

          Supplementary Information

          The online version contains supplementary material available at 10.1186/s12939-023-01848-z.

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          Most cited references32

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          Updating and validating the Charlson comorbidity index and score for risk adjustment in hospital discharge abstracts using data from 6 countries.

          With advances in the effectiveness of treatment and disease management, the contribution of chronic comorbid diseases (comorbidities) found within the Charlson comorbidity index to mortality is likely to have changed since development of the index in 1984. The authors reevaluated the Charlson index and reassigned weights to each condition by identifying and following patients to observe mortality within 1 year after hospital discharge. They applied the updated index and weights to hospital discharge data from 6 countries and tested for their ability to predict in-hospital mortality. Compared with the original Charlson weights, weights generated from the Calgary, Alberta, Canada, data (2004) were 0 for 5 comorbidities, decreased for 3 comorbidities, increased for 4 comorbidities, and did not change for 5 comorbidities. The C statistics for discriminating in-hospital mortality between the new score generated from the 12 comorbidities and the Charlson score were 0.825 (new) and 0.808 (old), respectively, in Australian data (2008), 0.828 and 0.825 in Canadian data (2008), 0.878 and 0.882 in French data (2004), 0.727 and 0.723 in Japanese data (2008), 0.831 and 0.836 in New Zealand data (2008), and 0.869 and 0.876 in Swiss data (2008). The updated index of 12 comorbidities showed good-to-excellent discrimination in predicting in-hospital mortality in data from 6 countries and may be more appropriate for use with more recent administrative data. © The Author 2011. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health. All rights reserved.
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            The COVID-19 pandemic and health inequalities

            This essay examines the implications of the COVID-19 pandemic for health inequalities. It outlines historical and contemporary evidence of inequalities in pandemics—drawing on international research into the Spanish influenza pandemic of 1918, the H1N1 outbreak of 2009 and the emerging international estimates of socio-economic, ethnic and geographical inequalities in COVID-19 infection and mortality rates. It then examines how these inequalities in COVID-19 are related to existing inequalities in chronic diseases and the social determinants of health, arguing that we are experiencing a syndemic pandemic. It then explores the potential consequences for health inequalities of the lockdown measures implemented internationally as a response to the COVID-19 pandemic, focusing on the likely unequal impacts of the economic crisis. The essay concludes by reflecting on the longer-term public health policy responses needed to ensure that the COVID-19 pandemic does not increase health inequalities for future generations.
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              Social determinants of health inequalities.

              The gross inequalities in health that we see within and between countries present a challenge to the world. That there should be a spread of life expectancy of 48 years among countries and 20 years or more within countries is not inevitable. A burgeoning volume of research identifies social factors at the root of much of these inequalities in health. Social determinants are relevant to communicable and non-communicable disease alike. Health status, therefore, should be of concern to policy makers in every sector, not solely those involved in health policy. As a response to this global challenge, WHO is launching a Commission on Social Determinants of Health, which will review the evidence, raise societal debate, and recommend policies with the goal of improving health of the world's most vulnerable people. A major thrust of the Commission is turning public-health knowledge into political action.
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                Author and article information

                Contributors
                ana.ona@paraplegie.ch
                thankyriakides@gmail.com
                tederko.pl@gmail.com
                Reuben.Escorpizo@uvm.edu
                mohit.arora@sydney.edu.au
                Sturm.Christian@mh-hannover.de
                rekiny@126.com
                diana.pachecobarzallo@paraplegie.ch
                Journal
                Int J Equity Health
                Int J Equity Health
                International Journal for Equity in Health
                BioMed Central (London )
                1475-9276
                30 March 2023
                30 March 2023
                2023
                : 22
                : 56
                Affiliations
                [1 ]GRID grid.419770.c, Swiss Paraplegic Research, Guido A. Zäch Institute, ; Nottwil, Switzerland
                [2 ]GRID grid.449852.6, ISNI 0000 0001 1456 7938, Department of Health Sciences and Medicine, , University of Lucerne, ; Lucerne, Switzerland
                [3 ]GRID grid.11047.33, ISNI 0000 0004 0576 5395, Spinal Cord Rehabilitation Unit, , Medical University of Patras, ; Patras, Greece
                [4 ]GRID grid.13339.3b, ISNI 0000000113287408, Department of Rehabilitation, , Medical University of Warsaw, ; Warsaw, Poland
                [5 ]GRID grid.59062.38, ISNI 0000 0004 1936 7689, The University of Vermont, ; Burlington, USA
                [6 ]GRID grid.412703.3, ISNI 0000 0004 0587 9093, John Walsh Centre for Rehabilitation Research, The Kolling Institute, Royal North Shore Hospital, Northern Sydney Local Health District, ; Sydney, Australia
                [7 ]GRID grid.1013.3, ISNI 0000 0004 1936 834X, Faculty of Medicine and Health, , Sydney Medical School – Northern, The University of Sydney, ; Sydney, Australia
                [8 ]GRID grid.10423.34, ISNI 0000 0000 9529 9877, Department of Rehabilitation Medicine, Hannover Medical School, ; Hanover, Germany
                [9 ]GRID grid.13291.38, ISNI 0000 0001 0807 1581, China School of Public Health and West China Fourth Hospital, , Sichuan University, ; Chengdu, China
                [10 ]International Institute of Spatial Lifecourse Epidemiology (ISLE), Beijing, China
                [11 ]Center for Rehabilitation in Global Health Systems, WHO Collaborating Center, Lucerne, Switzerland
                Article
                1848
                10.1186/s12939-023-01848-z
                10060928
                622ae3b4-1f2b-46ad-8eb2-8929c66a20fa
                © The Author(s) 2023

                Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver ( http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

                History
                : 6 October 2022
                : 18 February 2023
                Categories
                Research
                Custom metadata
                © The Author(s) 2023

                Health & Social care
                health disparities,bivariate inequality,socioeconomic health inequality,comorbidity index,spinal cord injury

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