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      Educational inequality in Rio de Janeiro and its impact on multimorbidity: evidence from the Pró-Saúde study. A cross-sectional analysis

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          ABSTRACT

          BACKGROUND:

          Information about multimorbidity is scarce in developing countries. This study aimed to estimate the association of educational attainment with occurrences of multimorbidity in a population of public employees on university campuses in Rio de Janeiro.

          DESIGN AND SETTING:

          We conducted cross-sectional analyses on baseline data (1999-2001) from 3,253 participants in the Pró-Saúde study, conducted in Brazil.

          METHODS:

          The prevalence of multimorbidity, defined as a self-reported history of medical diagnoses of two or more chronic conditions, was estimated according to sex, age, smoking, obesity and educational level. The association between education and multimorbidity was estimated using odds ratios (OR) and the relative and slope indices of inequality, in order to quantify the degree of educational inequality among individuals with multimorbidity in this population.

          RESULTS:

          Greater age, female sex, smoking and obesity had direct associations with multimorbidity; and tobacco exposure and obesity also showed direct relationships with poorer educational level. There was a monotonic inverse linear trend between educational level and the presence of multimorbidity among women, with twice the odds (OR 2.47; 95% confidence interval, CI: 1.42-4.40) between extremities of schooling categories. There was excess multimorbidity of 22% at the lowest extremity of schooling, thus showing that women with worse educational status were more affected by the outcome. No trend and no excess multimorbidity was seen among men.

          CONCLUSIONS:

          Educational inequality is an important determinant for development of multimorbidity. Men and women experience its effect differently. Researchers need to consider that sex may be an effect modifier in multimorbidity studies.

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          Most cited references52

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          Epidemiology of multimorbidity and implications for health care, research, and medical education: a cross-sectional study.

          Long-term disorders are the main challenge facing health-care systems worldwide, but health systems are largely configured for individual diseases rather than multimorbidity. We examined the distribution of multimorbidity, and of comorbidity of physical and mental health disorders, in relation to age and socioeconomic deprivation. In a cross-sectional study we extracted data on 40 morbidities from a database of 1,751,841 people registered with 314 medical practices in Scotland as of March, 2007. We analysed the data according to the number of morbidities, disorder type (physical or mental), sex, age, and socioeconomic status. We defined multimorbidity as the presence of two or more disorders. 42·2% (95% CI 42·1-42·3) of all patients had one or more morbidities, and 23·2% (23·08-23·21) were multimorbid. Although the prevalence of multimorbidity increased substantially with age and was present in most people aged 65 years and older, the absolute number of people with multimorbidity was higher in those younger than 65 years (210,500 vs 194,996). Onset of multimorbidity occurred 10-15 years earlier in people living in the most deprived areas compared with the most affluent, with socioeconomic deprivation particularly associated with multimorbidity that included mental health disorders (prevalence of both physical and mental health disorder 11·0%, 95% CI 10·9-11·2% in most deprived area vs 5·9%, 5·8%-6·0% in least deprived). The presence of a mental health disorder increased as the number of physical morbidities increased (adjusted odds ratio 6·74, 95% CI 6·59-6·90 for five or more disorders vs 1·95, 1·93-1·98 for one disorder), and was much greater in more deprived than in less deprived people (2·28, 2·21-2·32 vs 1·08, 1·05-1·11). Our findings challenge the single-disease framework by which most health care, medical research, and medical education is configured. A complementary strategy is needed, supporting generalist clinicians to provide personalised, comprehensive continuity of care, especially in socioeconomically deprived areas. Scottish Government Chief Scientist Office. Copyright © 2012 Elsevier Ltd. All rights reserved.
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            Multimorbidity in older adults.

            M Salive (2013)
            Multimorbidity, the coexistence of 2 or more chronic conditions, has become prevalent among older adults as mortality rates have declined and the population has aged. We examined population-based administrative claims data indicating specific health service delivery to nearly 31 million Medicare fee-for-service beneficiaries for 15 prevalent chronic conditions. A total of 67% had multimorbidity, which increased with age, from 50% for persons under age 65 years to 62% for those aged 65-74 years and 81.5% for those aged ≥85 years. A systematic review identified 16 other prevalence studies conducted in community samples that included older adults, with median prevalence of 63% and a mode of 67%. Prevalence differences between studies are probably due to methodological biases; no studies were comparable. Key methodological issues arise from elements of the case definition, including type and number of chronic conditions included, ascertainment methods, and source population. Standardized methods for measuring multimorbidity are needed to enable public health surveillance and prevention. Multimorbidity is associated with elevated risk of death, disability, poor functional status, poor quality of life, and adverse drug events. Additional research is needed to develop an understanding of causal pathways and to further develop and test potential clinical and population interventions targeting multimorbidity. Published by Oxford University Press on behalf of the Johns Hopkins Bloomberg School of Public Health 2013.
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              The epidemiologic transition: a theory of the epidemiology of population change. 1971.

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                Author and article information

                Journal
                Sao Paulo Med J
                Sao Paulo Med J
                Sao Paulo Med J
                São Paulo Medical Journal
                Associação Paulista de Medicina - APM
                1516-3180
                1806-9460
                05 March 2018
                2018
                : 136
                : 1
                : 151-158
                Affiliations
                [I ] originalMD, MSc. Doctoral Student, Instituto de Medicina Social, Universidade do Estado do Rio de Janeiro (UERJ), and Coordinator, Residency Program in Family and Community Medicine, Secretaria Municipal de Saúde do Rio de Janeiro, Rio de Janeiro (RJ), Brazil.
                [II ] originalMSc. Doctoral Student, Instituto de Medicina Social, Universidade do Estado do Rio de Janeiro (UERJ), Rio de Janeiro (RJ), Brazil.
                [III ] originalMSc, PhD. Associate Professor, Instituto de Medicina Social, Universidade do Estado do Rio de Janeiro, Rio de Janeiro (RJ), Brazil.
                Author notes
                Address for correspondence: Adelson Guaraci Jantsch. Secretaria Municipal de Saúde do Rio de Janeiro, Programa de Residência em Medicina de Família e Comunidade. Rua Evaristo da Veiga, 16 - 4 o andar. Rio de Janeiro (RJ) - Brasil. CEP 20211-110. Cel. (+55 21) 97217-3177. E-mail: adelson.smsrio@ 123456gmail.com

                Conflict of interest: None

                Article
                10.1590/1516-3180.2017.0209100917
                9924166
                29513787
                98a54777-1070-407c-b9d5-f3fae69abaf4
                © 2022 by Associação Paulista de Medicina

                This is an open access article distributed under the terms of the Creative Commons license.

                History
                : 20 August 2017
                : 10 September 2017
                Page count
                Figures: 0, Tables: 3, Equations: 0, References: 49, Pages: 08
                Categories
                Original Article

                comorbidity,health status disparities,educational status,cross-sectional studies

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