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      Are estimates of socioeconomic inequalities in chronic disease artefactually narrowed by self-reported measures of prevalence in low-income and middle-income countries? Findings from the WHO-SAGE survey

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          Abstract

          Background

          The use of self-reported measures of chronic disease may substantially underestimate prevalence in low-income and middle-income country settings, especially in groups with lower socioeconomic status (SES). We sought to determine whether socioeconomic inequalities in the prevalence of non-communicable chronic diseases (NCDs) differ if estimated by using symptom-based or criterion-based measures compared with self-reported physician diagnoses.

          Methods

          Using population-representative data sets of the WHO Study of Global Ageing and Adult Health (SAGE), 2007–2010 (n=42 464), we calculated wealth-related and education-related concentration indices of self-reported diagnoses and symptom-based measures of angina, hypertension, asthma/chronic lung disease, visual impairment and depression in three ‘low-income and lower middle-income countries’—China, Ghana and India—and three ‘upper-middle-income countries’—Mexico, Russia and South Africa.

          Results

          SES gradients in NCD prevalence tended to be positive for self-reported diagnoses compared with symptom-based/criterion-based measures. In China, Ghana and India, SES gradients were positive for hypertension, angina, visual impairment and depression when using self-reported diagnoses, but were attenuated or became negative when using symptom-based/criterion-based measures. In Mexico, Russia and South Africa, this distinction was not observed consistently. For example, concentration index of self-reported versus symptom-based angina were: in China: 0.07 vs −0.11, Ghana: 0.04 vs −0.21, India: 0.02 vs −0.16, Mexico: 0.19 vs −0.22, Russia: −0.01 vs −0.02 and South Africa: 0.37 vs 0.02.

          Conclusions

          Socioeconomic inequalities in NCD prevalence tend to be artefactually positive when using self-report compared with symptom-based or criterion-based diagnostic criteria, with greater bias occurring in low-income countries. Using standardised, symptom-based measures would provide more valid estimates of NCD inequalities.

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          Most cited references61

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          Revisiting the Behavioral Model and Access to Medical Care: Does it Matter?

          The Behavioral Model of Health Services Use was initially developed over 25 years ago. In the interim it has been subject to considerable application, reprobation, and alteration. I review its development and assess its continued relevance.
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            Socioeconomic Inequalities in Health in 22 European Countries

            Comparisons among countries can help to identify opportunities for the reduction of inequalities in health. We compared the magnitude of inequalities in mortality and self-assessed health among 22 countries in all parts of Europe. We obtained data on mortality according to education level and occupational class from census-based mortality studies. Deaths were classified according to cause, including common causes, such as cardiovascular disease and cancer; causes related to smoking; causes related to alcohol use; and causes amenable to medical intervention, such as tuberculosis and hypertension. Data on self-assessed health, smoking, and obesity according to education and income were obtained from health or multipurpose surveys. For each country, the association between socioeconomic status and health outcomes was measured with the use of regression-based inequality indexes. In almost all countries, the rates of death and poorer self-assessments of health were substantially higher in groups of lower socioeconomic status, but the magnitude of the inequalities between groups of higher and lower socioeconomic status was much larger in some countries than in others. Inequalities in mortality were small in some southern European countries and very large in most countries in the eastern and Baltic regions. These variations among countries appeared to be attributable in part to causes of death related to smoking or alcohol use or amenable to medical intervention. The magnitude of inequalities in self-assessed health also varied substantially among countries, but in a different pattern. We observed variation across Europe in the magnitude of inequalities in health associated with socioeconomic status. These inequalities might be reduced by improving educational opportunities, income distribution, health-related behavior, or access to health care. Copyright 2008 Massachusetts Medical Society.
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              Manufacturing Epidemics: The Role of Global Producers in Increased Consumption of Unhealthy Commodities Including Processed Foods, Alcohol, and Tobacco

              In an article that forms part of the PLoS Medicine series on Big Food, David Stuckler and colleagues report that unhealthy packaged foods are being consumed rapidly in low- and middle-income countries, consistent with rapid expansion of multinational food companies into emerging markets and fueling obesity and chronic disease epidemics.
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                Author and article information

                Journal
                J Epidemiol Community Health
                J Epidemiol Community Health
                jech
                jech
                Journal of Epidemiology and Community Health
                BMJ Publishing Group (BMA House, Tavistock Square, London, WC1H 9JR )
                0143-005X
                1470-2738
                March 2015
                30 December 2014
                : 69
                : 3
                : 218-225
                Affiliations
                [1 ]Public Health Foundation of India , New Delhi, India
                [2 ]Department of Sociology, Oxford University , Oxford, UK
                [3 ]Department of Primary Care and Public Health, Imperial College London , London, UK
                [4 ]Prevention Research Center, Stanford University, Stanford , Palo Alto, California, USA
                [5 ]Department of Public Health and Policy, London School of Hygiene and Tropical Medicine , London, UK
                [6 ]Department of Epidemiology & Public Health, University College London , UK
                [7 ]Department of Non-Communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine , London, UK
                Author notes
                [Correspondence to ] Dr Sukumar Vellakkal, Public Health Foundation of India, 4 Institutional A, VasantKunj, New Delhi 110070, India; sukumar.vellakkal@ 123456phfi.org
                Article
                jech-2014-204621
                10.1136/jech-2014-204621
                4345525
                25550454
                cc6453bc-7cc7-4478-adb8-7373389e815e
                Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions

                This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) license, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: http://creativecommons.org/licenses/by/4.0/

                History
                : 3 July 2014
                : 21 October 2014
                : 27 October 2014
                Categories
                1506
                Health Inequalities
                Custom metadata
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                Public health
                epidemiology of chronic non communicable diseases,inequalities,public health
                Public health
                epidemiology of chronic non communicable diseases, inequalities, public health

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