Sarah Edwards, Health Poverty Action’s Head of Policy and Campaigns, blogs on data and how it can be used to make sure indigenous people and ethnic minorities count.
Building capacity for collecting and analysing data is emerging as a key issue in the debates about the Millennium Development Goals and what comes next. Current measurement practices are woefully inadequate in many developing countries, concealing the truth about the poverty levels, health and well-being of millions of the poorest and most marginalised groups worldwide.
The High Level Panel report and subsequent calls for a ‘data revolution’, with a strong emphasis on disaggregated data, are extremely welcome. This means that progress against any new goals should be tracked in sub-groups including income level, rural/ urban divide, regions, and gender. This will help us understand better how poverty and poor health affect the most vulnerable. Breaking down data into groupings allows us to see what disparities there are within a country and what can be done to resolve them.
To take Millennium Development Goal 4 on child mortality as an example, progress is being made to improve the health of children across the world – Ethiopia is just one country recently heralded as having already met the target to reduce national under-five mortality rate by two-thirds. This is, of course, excellent news which should not be underrated. But this statistic obscures significant variations within the population, such as among cultural minorities like pastoralists. In Ethiopia’s 2011 Demographic and Health Survey, the national under-five mortality rate was 88 per 1000 live births, but in the Somali region where there is a concentration of pastoralists, it was much higher at 122.
The use of aggregate data can thus present an image of progress when, for some of the most poor-off communities, there has been little change. Disaggregating data can expose these realities, enabling better targeting of resources in the areas that need them most and uncovering the underlying causes for such inequities.
However, many international discussions about breaking down data fail to consistently include one category: ethnicity, which is one of the key variables of a person’s life chances. Disaggregating data by ethnic group would help improve the lives of some of the world’s most marginalised communities. In Guatemala, one study showed indigenous women having a maternal mortality rate three times the national average. In Namibia, studies show life expectancy is 27 years lower among the minority San community compared with German-speaking population.
Even though the tools for collecting data on ethnicity may exist, governments often don’t use them, or only capture headline figures rather than delving deeper. For example in Sierra Leone, data was collected on the religion of the head of the household but neither language nor ethnicity. As a result, governments are only able to put together part of the picture of health for ethnic groups. And where ethnicity is captured it is often only published as background information on the population, as in Ethiopia’s DHS mentioned above, rather than broken down in terms of how those ethnic groups’ outcomes differ.
There are understandable concerns regarding breaking down data by ethnicity; many governments are reluctant because they fear it will confirm negative stereotypes or fuel ethnic tension. Other barriers to progress include lack of technical expertise; the disruption caused by conflict or disasters; and having the resources to repeat surveys regularly in order to build up sufficient data. But the impact of not highlighting the true health situation of marginalised communities is too great for these challenges not to be overcome.
To make disaggregating data by ethnic group more common – to make sure some of the most marginalised women, men and children count – everyone has a role to play. For governments, development organisations, donors and international institutions, the goal must be to build up national-level statistical capacity; to ensure all progress towards the new post-2015 goals is disaggregated by ethnicity; and to give a full role to marginalised indigenous and ethnic minority communities, ensuring their participation in decision making processes and in holding their governments to account. Only by taking these steps collectively will we reach a stage where people from indigenous groups and ethnic minorities no longer simply disappear in the data.
Click here to read Health Poverty Action’s full report on disaggregating data.