5
views
0
recommends
+1 Recommend
3 collections
    0
    shares
      • Record: found
      • Abstract: found
      • Article: found

      Income related inequalities in avoidable mortality in Norway: A population-based study using data from 1994–2011

      , ,
      Health Policy
      Elsevier BV

      Read this article at

      ScienceOpenPublisherPubMed
      Bookmark
          There is no author summary for this article yet. Authors can add summaries to their articles on ScienceOpen to make them more accessible to a non-specialist audience.

          Related collections

          Most cited references53

          • Record: found
          • Abstract: found
          • Article: not found

          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.
            Bookmark
            • Record: found
            • Abstract: found
            • Article: not found

            Inequalities in access to medical care by income in developed countries.

            Most of the member countries of the Organization for Economic Cooperation and Development (OECD) aim to ensure equitable access to health care. This is often interpreted as requiring that care be available on the basis of need and not willingness or ability to pay. We sought to examine equity in physician utilization in 21 OECD countries for the year 2000. Using data from national surveys or from the European Community Household Panel, we extracted the number of visits to a general practitioner or medical specialist over the previous 12 months. Visits were standardized for need differences using age, sex and reported health levels as proxies. We measured inequity in doctor utilization by income using concentration indices of the need-standardized use. We found inequity in physician utilization favouring patients who are better off in about half of the OECD countries studied. The degree of pro-rich inequity in doctor use is highest in the United States and Mexico, followed by Finland, Portugal and Sweden. In most countries, we found no evidence of inequity in the distribution of general practitioner visits across income groups, and where it does occur, it often indicates a pro-poor distribution. However, in all countries for which data are available, after controlling for need differences, people with higher incomes are significantly more likely to see a specialist than people with lower incomes and, in most countries, also more frequently. Pro-rich inequity is especially large in Portugal, Finland and Ireland. Although in most OECD countries general practitioner care is distributed fairly equally and is often even pro-poor, the very pro-rich distribution of specialist care tends to make total doctor utilization somewhat pro-rich. This phenomenon appears to be universal, but it is reinforced when private insurance or private care options are offered.
              Bookmark
              • Record: found
              • Abstract: found
              • Article: not found

              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.
                Bookmark

                Author and article information

                Journal
                Health Policy
                Health Policy
                Elsevier BV
                01688510
                July 2015
                July 2015
                : 119
                : 7
                : 889-898
                Article
                10.1016/j.healthpol.2015.04.016
                25981708
                1522921b-f4cc-4bc8-a7cf-6e9f9d5a0d77
                © 2015

                https://www.elsevier.com/tdm/userlicense/1.0/

                History

                Comments

                Comment on this article