Lucy Ruderman, Research Fellow, FHI 360
Last year, R4S led the development of the High Impact Practice (HIP) Strategic Planning Guide (SPG) for equity in family planning. The SPG has adopted this definition: “‘Health equity’ or ‘equity in health’ implies that ideally everyone should have a fair opportunity to attain their full health potential and that no one should be disadvantaged from achieving this potential.” When there is health equity, societal structures are optimized such that worse-off groups are not put at continued disadvantage by giving everyone the same thing. Rather, worse-off groups are given an extra advantage to achieve similar outcomes as more advantaged groups. That’s fair, that’s equity. But how do you measure fairness, specifically the fairness of an opportunity to attain health?
The immediate idea that may have popped into your head is to disaggregate, or separate out, the data into groups. Think of the gender data gap—the notion that women are not accounted for in the data because we do not separate data by sex. The gender data gap has led to women dying in car crashes more often than men and heart disease in females going undetected until it’s too late. When you apply the principle of disaggregating data to other dimensions (e.g., age, economic status, educational attainment, etc.), you’re able to see how different population groups fare in respect to a health outcome. However, disaggregation alone does not quantify the burdens one overcomes to reach said favorable health outcome and therefore does not fully measure equity. The Strategic Planning Guide for equity in family planning outlines four key steps to measuring equity. Step 2, “determine what barriers individuals from this population group face in accessing high-quality family planning information and services,” helps us realize exactly this—quantitative data alone does not adequately measure inequities in family planning.
Picture this—teenagers in Country X have a harder time accessing contraception. If you measure demand satisfied for family planning by age group, you may see that 30% of people under 18 have their demand satisfied, 45% of 19–25-year-olds have their demand satisfied, and 55% of the 26-35 age group have their demand satisfied. It’s clear that there is disparity here, but the extent of the inequity is unknown because these percentages do not measure the additional hurdles younger people would have to overcome to access family planning—missing school, stigmatization, using limited pocket change to pay for contraception, and others. Similarly, if the demand satisfied is 55% across each of these age groups, we are seeing equality, not equity, because those additional barriers for young people are not captured in this metric. In this example, barrier analyses or client feedback tools are excellent ways to additionally capture the hurdles those young people would need to overcome for their family planning needs to be satisfied. We need to advocate for qualitative and quantitative data to be married at every step of an equity analysis.
We also need to advocate for more routine measurement. The world’s data systems are built in such a way that by the time we have the data, life has moved on. We rely on the Demographic Health Survey (DHS) and similar large-scale population snapshots, but these surveys only come around every 5-10 years. This can be a problem because if we lean too heavily on periodic data to inform equitable approaches for family planning, we may be applying outdated information. Not to say that we should abandon the DHS, but because its data are only available infrequently, these data are not sufficient for assessing equity within family planning programs. We need to identify additional data sources and set up feedback loops where program managers and policy makers can routinely understand an initiative’s impact on the population and regularly iterate an approach to best reach those who are most affected by inequities at any given time.
R4S is collaborating with national equity working groups in Malawi, Niger, and Uganda to explore these difficult but necessary questions. Recently, the Family Planning Equity and Self-Care Technical Working Group in Niger used the SPG as well as documents developed by R4S—Measuring Equity in Family Planning: Considerations from the Literature and An Illustrative Case Study in Measuring Equity in Family Planning—to ignite conversations around equity definitions, dimensions, and measurement and how these principles can be incorporated into family planning programming and evaluation. The Technical Working Group used these documents to conceptualize how equity applies to the Niger context and to ideate key activities for improving family planning equity measurement at the country-level.
Measuring equity within family planning is not a simple feat, but it is important and worthwhile. Accurate and compelling equity data can push policy makers to action, make the case for increased focus and funding to diminish such inequities, and contribute to achieving country and global commitments, including the Sustainable Development Goals.