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      Income inequalities in multimorbidity prevalence in Ontario, Canada: a decomposition analysis of linked survey and health administrative data

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          Abstract

          Background

          The burden of multimorbidity is a growing clinical and health system problem that is known to be associated with socioeconomic status, yet our understanding of the underlying determinants of inequalities in multimorbidity and longitudinal trends in measured disparities remains limited.

          Methods

          We included all adult respondents from four cycles of the Canadian Community Health Survey (CCHS) (between 2005 to 2011/12), linked at the individual-level to health administrative data in Ontario, Canada (pooled n = 113,627). Multimorbidity was defined at each survey response as having ≥2 (of 17) high impact chronic conditions, based on claims data. Using a decomposition method of the Erreygers-corrected concentration index (C Erreygers), we measured household income inequality and the contribution of the key determinants of multimorbidity (including socio-demographic, socio-economic, lifestyle and health system factors) to these disparities. Differences over time are described. We tested for statistically significant changes to measured inequality using the slope index (SII) and relative index of inequality (RII) with a 2-way interaction on pooled data.

          Results

          Multimorbidity prevalence in 2011/12 was 33.5% and the C Erreygers was − 0.085 (CI: -0.108 to − 0.062), indicating a greater prevalence among lower income groups. In decomposition analyses, income itself accounted more than two-thirds (69%) of this inequality. Age (21.7%), marital status (15.2%) and physical inactivity (10.9%) followed, and the contribution of these factors increased from baseline (2005 CCHS survey) with the exception of age. Other lifestyle factors, including heavy smoking and obesity, had minimal contribution to measured inequality (1.8 and 0.4% respectively). Tests for trends (SII/RII) across pooled survey data were not statistically significant ( p = 0.443 and 0.405, respectively), indicating no change in inequalities in multimorbidity prevalence over the study period.

          Conclusions

          A pro-rich income gap in multimorbidity has persisted in Ontario from 2005 to 2011/12. These empirical findings suggest that to advance equality in multimorbidity prevalence, policymakers should target chronic disease prevention and control strategies focused on older adults, non-married persons and those that are physically inactive, in addition to addressing income disparities directly.

          Electronic supplementary material

          The online version of this article (10.1186/s12939-018-0800-6) contains supplementary material, which is available to authorized users.

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          Most cited references27

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          The bounds of the concentration index when the variable of interest is binary, with an application to immunization inequality.

          When the health sector variable whose inequality is being investigated is binary, the minimum and maximum possible values of the concentration index are equal to micro-1 and 1-micro, respectively, where micro is the mean of the variable in question. Thus as the mean increases, the range of the possible values of the concentration index shrinks, tending to zero as the mean tends to one and the concentration index tends to zero. Examples are presented on levels of and inequalities in immunization across 41 developing countries, and on changes in coverage and inequalities in selected countries. Copyright (c) 2004 John Wiley & Sons, Ltd.
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            Correcting the concentration index.

            In recent years attention has been drawn to several shortcomings of the Concentration Index, a frequently used indicator of the socioeconomic inequality of health. Some modifications have been suggested, but these are only partial remedies. This paper proposes a corrected version of the Concentration Index which is superior to the original Concentration Index and its variants, in the sense that it is a rank-dependent indicator which satisfies four key requirements (transfer, level independence, cardinal invariance, and mirror). The paper also shows how the corrected Concentration Index can be decomposed and generalized.
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              Accuracy of administrative databases in identifying patients with hypertension

              Background Traditionally, the determination of the occurrence of hypertension in patients has relied on costly and time-consuming survey methods that do not allow patients to be followed over time. Objectives To determine the accuracy of using administrative claims data to identify rates of hypertension in a large population living in a single-payer health care system. Methods Various definitions for hypertension using administrative claims databases were compared with 2 other reference standards: (1) data obtained from a random sample of primary care physician offices throughout the province, and (2) self-reported survey data from a national census. Results A case-definition algorithm employing 2 outpatient physician billing claims for hypertension over a 3-year period had a sensitivity of 73% (95% confidence interval [CI] 69%–77%), a specificity of 95% (CI 93%–96%), a positive predictive value of 87% (CI 84%–90%), and a negative predictive value of 88% (CI 86%–90%) for detecting hypertensive adults compared with physician-assigned diagnoses. Compared with self-reported survey data, the algorithm had a sensitivity of 64% (CI 63%–66%), a specificity of 94%(CI 93%–94%), a positive predictive value of 77% (76%–78%), and negative predictive value of 89% (CI 88%–89%). When this algorithm was applied to the entire province of Ontario, the age- and sex-standardized prevalence of hypertension in adults older than 35 years increased from 20% in 1994 to 29% in 2002. Conclusions It is possible to use administrative data to accurately identify from a population sample those patients who have been diagnosed with hypertension. Given that administrative data are already routinely collected, their use is likely to be substantially less expensive compared with serial cross-sectional or cohort studies for surveillance of hypertension occurrence and outcomes over time in a large population.
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                Author and article information

                Contributors
                luke.mondor@ices.on.ca
                dcohen@cihi.ca
                anumirfan.khan@mail.utoronto.ca
                1 (416) 946-7387 , walter.wodchis@utoronto.ca
                Journal
                Int J Equity Health
                Int J Equity Health
                International Journal for Equity in Health
                BioMed Central (London )
                1475-9276
                26 June 2018
                26 June 2018
                2018
                : 17
                : 90
                Affiliations
                [1 ]ISNI 0000 0000 8849 1617, GRID grid.418647.8, Institute for Clinical Evaluative Sciences (ICES), ; G1 06 2075 Bayview Ave, Toronto, ON M4N 3M5 Canada
                [2 ]Health System Performance Research Network (HSPRN), 155 College St 4th Floor, Toronto, ON M5T 3M6 Canada
                [3 ]ISNI 0000 0001 2182 2255, GRID grid.28046.38, School of Epidemiology and Public Health, , University of Ottawa, ; 600 Peter Morand Crescent, Ottawa, ON K1G Z53 Canada
                [4 ]ISNI 0000 0001 2157 2938, GRID grid.17063.33, Institute of Health Policy, Management, and Evaluation (IHPME), , University of Toronto, ; 155 College St 4th Floor, Toronto, ON M5T 3M6 Canada
                [5 ]ISNI 0000 0004 0459 7334, GRID grid.417293.a, Institute for Better Health, Trillium Health Partners, ; 100 Queensway West, Mississauga, ON L5B 1B8 Canada
                Article
                800
                10.1186/s12939-018-0800-6
                6019796
                29941034
                f09220b5-6b98-42b4-89f7-ea69bc7280f2
                © The Author(s). 2018

                Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License ( http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. 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.

                History
                : 4 December 2017
                : 11 June 2018
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100000226, Ontario Ministry of Health and Long-Term Care;
                Award ID: 06034
                Award Recipient :
                Categories
                Research
                Custom metadata
                © The Author(s) 2018

                Health & Social care
                adult,chronic disease,comorbidity,health status disparities,ontario/ epidemiology,prevalence,socioeconomic factors,trends,advance equality in multimorbidity prevalence

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