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.
Routine commodity tracking information may be available through a national logistics management and information system.
Periodically collected data sources that may have relevant data include—
Comprehensive food security and vulnerability analysis.
Demographic and Health Surveys (DHS).
Household Consumption and Expenditure Surveys.
Knowledge Practice and Coverage Survey.
List-based food questionnaire.
Multiple Indicator Cluster Survey.
National Micronutrient Survey.
Global databases and repositories that may have relevant data include—
Global Burden of Disease study.
Global database on the Implementation of Nutrition Action.
Nutrition Landscape Information System.
Vitamin and Mineral Nutrition Information System.
e-Library of Evidence for Nutrition Actions.
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.
- How recent are the latest pieces of information?
- Are resources missing that should be available?
One-time or irregular survey data.
- 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.
- 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?
- 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.
- 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.
Box 2: Steps for Conducting a Systematic Search for Anemia-Related Data in Your Country
- 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.
- 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:
- Ovid MEDLINE*: http://ospguides.ovid.com/OSPguides/medline.htm
- Cochrane Database of Systematic Reviews: http://onlinelibrary.wiley.com/cochranelibrary/search
- Cochrane Central Register of Controlled Trials: http://onlinelibrary.wiley.com/cochranelibrary/search?searchRow.searchOptions.searchProducts=clinicalTrialsDoi
- CAB Abstracts: http://www.cabi.org/publishing-products/online-information-resources/cab-abstracts/
- Global Health: https://www.ebscohost.com/academic/global-health
- Global Health Archive: https://www.ebscohost.com/archives/stm-database-archives/global-health-archive
- 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.
- 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.
- 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 Group||Search 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
YOUR COUNTRY NAME
|#2 Populations||Pregnancy OR Women of Reproductive Age OR Adolescent OR Women OR Children OR Infants
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.
Fiedler, John L., Keith Lividini, Odilia I. Bermudez, and Marc-Francois Smitz. 2012. “Household Consumption and Expenditures Surveys (HCES): A Primer for Food and Nutrition Analysts in Low- and Middle-Income Countries.” Food and Nutrition Bulletin 33 (3 Suppl): S170-184. doi:10.1177/15648265120333S205.