Equity in Health

While the South African Treasury and Department of Health number-crunch to determine whether government can afford anti-retroviral (ARV) treatment in public health, a number of small ARV programmes are already up and running. Several others are in the pipeline, the most ambitious being the SA Medical Association pledge to raise R80-million to set up two ARV pilot projects in each province to treat 9 000 people.

Gaps in child mortality between rich and poor countries are unacceptably wide and in some areas are becoming wider, as are the gaps between wealthy and poor children within most countries. Poor children are more likely than their better-off peers to be exposed to health risks, and they have less resistance to disease because of undernutrition and other hazards typical in poor communities. Regular monitoring of inequities and use of the resulting information for education, advocacy, and increased accountability among the general public and decision makers is urgently needed, but will not be sufficient. Equity must be a priority in the design of child survival interventions and delivery strategies, and mechanisms to ensure accountability at national and international levels must be developed.

In this paper, the author argues that, contrary to popular belief, numerous Poverty Reduction Strategy Papers (PRSPs) and aid programmes do not adequately address the MDGs. The paper analyses the substance of 22 developing countries’ PRSPs and the policy frameworks of 21 bilateral programmes. Major findings of the analysis include noting that economic growth for income poverty reduction and social sector investments (education, health and water) are important priorities in most of the PRSPs, yet decent work, hunger and nutrition, the environment and access to technology tend to be neglected. PRSPs also emphasise governance as an important means of achieving the MDGs, but they focus mostly on economic governance rather than on democratic (participatory and equitable) processes.

Inequalities in health persist worldwide and one of the starting points for remedial action is collecting data that reveal patterns of inequality. Yet countries have varying capacities for monitoring health inequality. This is due in part to data-related issues such as weaknesses in the health information systems, especially in many low- and middle-income countries; lack of availability or poor quality of health data; and a limited ability to disaggregate data across all health topics within countries. Overcoming these challenges in the long term requires substantial investments in the health information infrastructure. In the short-term, countries need innovative approaches to best harness the potential of their existing data to improve monitoring efforts. In this article the authors make the case for stratifying data at the level of subnational geographical regions, such as provinces, states or districts. The wider use of an area-based unit of analysis as a complementary way to analyse data at the individual or household level has certain practical advantages that are relevant to low- and middle-income countries as well as high-income countries. First, this approach opens up new possibilities concerning the data that can be used for within-country monitoring, in terms of both health data and data about dimensions of inequality. Second, since interventions to reduce inequities are likely to be implemented at the local administrative level, regional monitoring of health inequalities may be a useful tool for benchmarking, with implications for resource allocation, planning and evaluation. Third, area-based measures may provide a more intuitive understanding of health inequalities and may help to identify possible points for intervention. Alongside these advantages, some caution is needed when adopting an area-based unit of analysis. There is the risk of committing a so-called ecological fallacy (i.e. making assumptions about individuals based on population-level patterns, or in this case, erroneously drawing conclusions about the health of individuals using area-based data). In many countries, health inequality monitoring systems could be strengthened by expanding the capacity for, and practice of, area-based health inequality monitoring. Adopting an area-based unit to express health inequality has several merits. Monitoring health inequalities by geographically defined subgroups can help to identify disadvantaged regions that are falling behind in terms of health indicators and to guide improvements in these areas.