Understanding Anemia: Guidance for Conducting a Landscape Analysis

Gathering Information on Anemia

While there are many different ways to conduct an anemia landscape analysis, a key piece is to assemble the data that will enable you to understand a situation as clearly as possible. Landscape analyses range from basic to complex, depending on your resources, data availability, audience, and goals. Generally, though, you will need to gather information from multiple sources and sectors. You will want to gather information on—

  • anemia prevalence
  • causes of anemia
  • anemia policies
  • status of anemia interventions.

Throughout this guidance, we ask you to review this information as a way to better understand the anemia situation in your country. Ideally, you will have recent, high-quality, comprehensive, and disaggregated data that are representative of your population of interest. While it is helpful to have high-quality data to carry out a landscape analysis, this guidance will walk you through a process that is appropriate for any level of data you can gather. For more information see the Additional Data Sources section below.

Where do you get these data?

Begin by investigating what sources are available in your country. Relevant information may be included in routine government reporting systems or regulatory monitoring systems. National alliances or working groups, or similar bodies that oversee health (e.g., nutrition, disease control, reproductive health, etc.), agriculture, or other relevant sectors, may have anemia-related information.

Routine data sources that may have relevant data include—

Routine health information collected through a national health monitoring information system.

Most countries collect routine data on health facility performance, prevalence of diseases (through treatment data), and coverage of preventive activities. These data are not always publically available, although ministries of health will often publish annual reports. While the chance of human error is high in many administrative reporting systems, countries with computer-based platforms that automate schedules and aggregation will probably have better reporting rates and data quality. More than 40 countries use the District Health Information System2 (DHIS2) platform to collect these data. For more information: www.dhis2.org or on country-specific DHIS2 websites.

Routine commodity tracking information may be available through a national logistics management and information system.

National agencies and development partners involved in health supply chain efforts maintain one or more tracking systems to oversee the movement of different classes of commodities. These data are not always publically available, but agencies that oversee the system may publish regular reports. Increasingly, these data are tracked through electronic systems that often have a public website. For more information: www.pmi.gov/docs/default-source/default-document-library/tools-curricula/elmis-selection-guide-electronically-managing-supply-chain-information.pdf?sfvrsn=6.

Periodically collected data sources that may have relevant data include—

Comprehensive food security and vulnerability analysis.

This survey assists in developing an understanding of the food security situation and household vulnerabilities in a given country. The survey aims to identify root causes of food insecurity; develop profiles of food insecure and vulnerable people; analyze markets; and analyze risks, such as natural disasters and their potential impact on the most vulnerable. For more information: www.wfp.org/food-security/assessments/comprehensive-food-security-vulnerability-analysis.

Demographic and Health Surveys (DHS).

These surveys are carried out in many countries on a regular schedule (usually every five years). They provide data on a wide range of indicators in the areas of population, health, and nutrition. Most surveys include estimates of anemia prevalence. The Demographic and Health Survey program also supports the Malaria Indicators Surveys¬—data on malaria treatment, prevention, and prevalence—and Service Provision Assessment surveys—data on health facility characteristics and provided services. For more information: www.dhsprogram.com.

Household Consumption and Expenditure Surveys.

This collective term refers to multipurpose household surveys that include data on the purchase and consumption of foods, as well as other socioeconomic indicators. While these surveys often report data at the household level and, therefore, do not allow for discussions of intra-household resource allocation, they are a tool for estimating nutrient intake patterns and possible prevalence of dietary inadequacy. For more information: www.spring-nutrition.org/about-us/activities/household-consumption-and-expenditure-surveys and in Fiedler et al. (2012).

Knowledge Practice and Coverage Survey.

This survey assesses the health situation at a local level, such as a program area or district, and then measures progress toward a result. The survey has eight modules, including sick child; malaria; immunization; maternal and newborn care; family planning; breastfeeding, infant, and young child feeding; water and sanitation; and background. Each module contains questionnaires and indicators that help track improved health outcomes. For more information: www.mchip.net/node/788.

List-based food questionnaire.

List-based questionnaires rely on participant recall of food consumed during the prior defined period of time, often 24 hours. Although these questionnaires cannot describe diet quality for an individual, they are a population-level proxy indicator for micronutrient adequacy. For more information: www.fao.org/3/a-i5486e.pdf.

Multiple Indicator Cluster Survey.

The United Nations Children’s Fund (UNICEF) periodically carries out these surveys in many countries, with some countries having data collection as often as every three years. Results from these household surveys provide data on a wide range of health and socioeconomic indicators for women and children in low- and middle-income countries. For more information: www.mics.unicef.org.

National Micronutrient Survey.

This collective term refers to surveys that use biological markers to collect data on micronutrient deficiencies. While not available in most countries, these surveys have been conducted in more countries in recent years in response to demands for greater detail on the prevalence of micronutrient deficiencies. In addition, national micronutrient surveys increasingly include factors beyond micronutrient status that are relevant to anemia, such as malaria, human immunodeficiency virus (HIV), and helminths. For more information: www.cdc.gov/immpact/index.html.

Global databases and repositories that may have relevant data include—

Global Burden of Disease study.

This comprehensive study includes data from 120 countries and covers a variety of health topics in its effort to measure global epidemiological levels and trends. For more information: www.healthdata.org/gbd.

Global database on the Implementation of Nutrition Action.

The World Health Organization (WHO) houses a database of country policies related to anemia. For more information: www.who.int/nutrition/gina/en/.

Nutrition Landscape Information System.

This information system, a web-based tool, presents country profiles that include a snapshot of nutrition, health, and development data from several available sources, at a national level. For more information: www.who.int/nutrition/nlis/en/.

Vitamin and Mineral Nutrition Information System.

This database provides up-to-date national, regional, and global assessments of vitamin and mineral deficiencies; summarizes data on the vitamin and mineral status of the population; tracks progress toward elimination of deficiencies; and offers tools and resources to support a nutritional status assessment. For more information: www.who.int/vmnis/en/.

e-Library of Evidence for Nutrition Actions.

This e-Library provides the latest evidence-informed nutrition guidelines, recommendations, and related information for nutrition interventions. While it is not a specific data source, it is a useful resource for scaling up nutrition interventions. For more information: www.who.int/elena/en/.

Additional data sources

Of course, the ideal data source is not always available. Even without information that fits the characteristics above, you can still conduct an anemia landscape analysis if you have information that provides a picture of the current situation. Additional data sources for your landscape analysis can include one-time or irregular survey data, subnational surveys, key informant interviews, or systematic reviews. After you identify possible data sources, selecting what to use is more of an art than a science. When deciding whether or not to use these data sources, consider their quality and representativeness with stakeholders, and ensure that you clearly state any limitations when sharing the findings. We included questions to ask as you consider using each data source. No clear guidelines govern what data is “too old” or “too small” to use for an anemia landscape analysis, but you can decide with your colleagues whether the data improves your understanding of the anemia situation in your country or provides helpful information to your landscape analysis audience.

Government websites.

Government websites—such as Ministry of Health and Sanitation and other sector website—can provide national data reports and provide information on the status of current nutrition-related policies, interventions, and infrastructure.
  • How recent are the latest pieces of information?
  • Are resources missing that should be available?

One-time or irregular survey data.

Many research organizations or projects conduct surveys that represent the national, subnational, or project levels, at various points. Talk to implementers, or your national statistics body, to identify surveys that you can use.
  • Did the data collectors use appropriate methods for their outcomes of interest?
  • Are the findings recent enough to present an accurate picture of the current situation?
  • If not nationally representative: How does this population compare to your population of interest?

Subnational surveys or data collection.

To conserve resources, or focus on a specific target group, data are often collected that are not nationally representative. Talk to subnational implementers, subnational policymakers, or the national statistics body to identify data that may apply to your population of interest.
  • Why was this specific population chosen for the data collection?
  • What do you know about this group in relation to the rest of the country that may affect your findings?

Older data.

Data from sources that are not considered recent can still be informative if you believe the situation has not changed much in the intervening time. Most likely, you will not want to go back further than 10 years.
  • How has this situation changed in the time since the data were collected?
  • How often or quickly does this situation generally change?
  • Do you believe these data give an accurate description of the current situation?

Key informant interviews.

Many times, data are not available for the programs or issues you are interested in. In these situations, experts in the field may have enough experience to help you understand the general trends in this area or informal data from on-the-ground implementers. These qualitative or general data may be helpful in the early stages of a landscape analysis.
  • Where does their information come from and what do you know about those sources?
  • What should you keep in mind or consider regarding their understanding of the issue?
  • What preconceived notions or biases might this expert have when forming their opinion?

Conduct a systematic search for data on anemia and its risk factors.

If high-quality nationally representative data are not available, it only takes a few steps to identify additional data sources for your anemia landscape analysis. Box 2 includes steps to follow in conducting a search and a list of relevant terms. You can build on these searches by specifying population groups of interest relevant for your context—women of reproductive age, pregnant women, adolescents, school-age children, young children, children, or infants. Remember, most findings are linked to specific geographic areas within a country, or to a specific target group, and cannot be generalized to the whole country. Even so, these data can offer a gauge and range. You may need to conduct a systematic search to find data on risk factors for anemia; data on interventions are often more readily available.

Box 2: Steps for Conducting a Systematic Search for Anemia-Related Data in Your Country

  1. Decide on the timeframe: How far in the past do you want to go in each of the databases you search? For the maximum number of results, start from their earliest available dates, but this will probably result in too much information. Because you want data that represent the current situation, consider limiting your results to the last 15 to 20 years. If you limit your options, track the timeline you use and be consistent across databases. In addition, track the dates when you run the search. Monitoring the dates (both start and end) will keep your landscape analysis up-to-date.
  2. Identify databases: Some databases let you search their content for free, while others require payment. As with your search dates, track the databases you use. The following databases have anemia-related content:
    1. Ovid MEDLINE*: http://ospguides.ovid.com/OSPguides/medline.htm
    2. Cochrane Database of Systematic Reviews: http://onlinelibrary.wiley.com/cochranelibrary/search
    3. Cochrane Central Register of Controlled Trials: http://onlinelibrary.wiley.com/cochranelibrary/search?searchRow.searchOptions.searchProducts=clinicalTrialsDoi
    4. CAB Abstracts: http://www.cabi.org/publishing-products/online-information-resources/cab-abstracts/
    5. Global Health: https://www.ebscohost.com/academic/global-health
    6. Global Health Archive: https://www.ebscohost.com/archives/stm-database-archives/global-health-archive
    7. Google Scholar (scholar.google.com) and Web of Science (ipscience.thomsonreuters.com/product/web-of-science) are additional search options, but they will give you many more results; make your searches of these databases more specific and be prepared to screen many more results.
    8. Choose your search terms: By carefully defining your search terms, you will identify the most appropriate results. See Table 1 for an example of search terms used in an anemia landscape analysis search. Always include the relevant terms for your country, which may not be on this list. Note: A space is included for you to add your country at the end of both search term groups.
    9. Conduct the search: To identify the most data sources, first search for each group of terms separately (i.e., run the search terms in #1, then run a separate search with the terms in #2). After you finish each search, remove any duplicate results.

*Note that Ovid MEDLINE includes results from PubMed, but with a three-month lag

Table 1: Terms for Anemia-Related Data Systematic Search

Search Term GroupSearch Terms
#1 Risk factors (separate with “OR”)General terms: Anemia, Nutrition, Nutritional Status, Nutritional Deficiency, Hypochromic, Macrocytic, Microcytic
Genetic variations: Sickle Cell, Thalassaemias, Hemoglobinopathies, Ovalocytosis, G6PD deficiency
Micronutrient deficiency: Megaloblastic, Transferrin, Ferritin, Hepciidn, Zinc Protoporphyrin, Micronutrients, Iron-Deficiency, Fortification, Supplementation, Receptors, Vitamin B12, Vitamin B12 Deficiency, Cyanocobalamine, Vitamin A Deficiency, Night Blindness, Xerophthalmia, Folic Acid, Folic Acid Deficiency, Folate Deficiency, Neural Tube Defects, Zinc, Zinc Deficiency
Infection: HIV-AIDS, Helminths, Nematode Infections, Ascariasis, Cestoda, Leishmaniasis, Trichuriasis, Trichuris, Helminthiasis, Ancylostomatoidea, Filariasis, Microfilaria, Fasciola Hepatica, Filarioidea, Wuchereria Bancrofti, Strongyloides, Enterobius, Necator, Schistosomiasis, Round Worm, Hookworm, Tapeworm, Whipworm, Filarial, Malaria, Plasmodium
Inflammation: Inflammation, obesity, anemia of chronic disease, anemia of chronic inflammation
AND
YOUR COUNTRY NAME
#2 PopulationsPregnancy OR Women of Reproductive Age OR Adolescent OR Women OR Children OR Infants
AND
YOUR COUNTRY NAME

How to include this information in your landscape analysis

Your landscape analysis report should include a description of the data you selected and explain why you selected it. Use the “Methodology” section of your report to describe the decision-making process and include details of the sources. While many sources for data relating to anemia causes and interventions are available, often important data are not regularly collected. In particular, National Micronutrient Surveys usually provide the most comprehensive picture of the anemia situation in a country. These surveys often include information on micronutrient status, but also the prevalence of other infections, as well as coverage of relevant interventions. These surveys are expensive, but they will provide the most comprehensive data on anemia-related issues.

As you start to use the findings from your landscape analysis, having recent and representative data can greatly aid the process of planning and targeting programs. If your country does not have up-to-date information on anemia prevalence, causes of anemia, anemia policies, and status of anemia interventions, note this in your landscape analysis and consider working with policymakers in your country to collect the relevant data. It is important to keep in mind that there is value to conducting a landscape analysis, even when you lack some of the “ideal” data—as understanding the available data and gaps is necessary for planning future activities.