Understanding Anemia: Guidance for Conducting a Landscape Analysis
The prevalence and burden of anemia disproportionately affects children under 5 years of age, pregnant women, and non-pregnant women of reproductive age because of the increased nutrient needs and susceptibility to infections, as well as menstruation in non-pregnant women of reproductive age. Because of these biological factors, most data on anemia are collected for these three target groups. While men can suffer from anemia, women and children are most vulnerable and are the focus of most public health interventions.
Describe variations in anemia burden
While national prevalence rates can help you understand the overall burden of anemia in your country, variations at the subnational level are common. These subnational variations are important for programmers and policymakers interested in targeting their interventions to the most affected populations. Reviewing disaggregated national anemia data can help identify areas or groups with an anemia burden higher than the national average. Patterns of anemia may vary within countries because of many factors: the burden of anemia-related diseases and infections, functionality of supply chain and distribution networks, availability of micronutrient-rich foods for consumption, etc. Income inequality and women's empowerment are often reflected in anemia rates that vary with socioeconomic status and maternal education (Kassebaum et al. 2014).
Anemia prevalence varies over time and with populations. The anemia burden can shift from being more severe to less, or the opposite. Discuss with stakeholders the specific factors that could influence the anemia rates at the national and subnational levels. If data are available, review the anemia prevalence for your target groups by geographic area, income, education, or other similar factors to see if any populations are disproportionately affected by anemia. Disaggregation of data by additional indicators—such as sex, pregnancy status, age, education levels, and urban versus rural residence—may also reveal important information. You can prepare graphs of anemia prevalence–by target group or by various characteristics–to illustrate the variation in the anemia burden in your country. These types of basic data are often collected in surveys as part of a “Background” or “Household” characteristics section. For more details on these possible indicators, see Table 5.
Table 5: Possible Disaggregation Indicators for Anemia
| Indicator | Details |
|---|---|
| Socioeconomic status | Many surveys report a wealth index or percentiles. An example (based on wealth quintile) is poorest, poorer, middle, richer, and richest. |
| Sex | The prevalence of anemia often varies between females and males |
| Age | Nutrient requirements vary across age groups. Examples of these groupings are—
|
Pregnancy status | Pregnant and lactating women have additional nutrient requirements; they can be reached through a different set of delivery platforms than the non-pregnant population. |
| Education levels | Often grouped by level of school completed. Examples include no formal schooling, some primary schooling, completed primary, completed some secondary schooling, completed secondary, and completed post-secondary education. |
| Residence | Urban and rural populations have different risk factors for anemia; they often do not have access to the same delivery platforms for anemia prevention and control programs. |
| Social groups | In many countries, anemia can vary significantly across social groups that may face different risk factors and have different access to anemia prevention and control programs. These can include ethnicity, case, religion, indigenous groups, etc. |