The first step when analyzing data for Iron deficiency after cleaning and characterizing the data, is to compile a situation profile that describes the population using the cleaned data and data from previous surveys and compilations. Iron deficiency is so very widespread that it is not usually a question of does it exist, but to what extent are individuals affected. It is most practical to look at the high-risk groups such as children, women, and pregnant women specifically. Children, due to rapid growth, are at especially high risk of IDA. Once girls reach pubescence, they have increased blood loss and therefore higher demands for iron. When women become pregnant, the demands on the body for iron are dramatically increased. This risk of IDA is further increased when women do not space their births so that iron stores can be replenished between pregnancies.

When we obtain an appropriate data set the following examples will be added:

Now using dataset name.sav, try compiling a situation analysis for IDA to help summarize the situation in country name. This should help to begin formulating ideas about further exploratory analysis on the causes and possible interventions that might be needed to control anemia. Because anemia is so often a response to many causal factors such as low iron intake, poverty, infection, lack of breastfeeding, etc., it is favorable to include these risk factors in the summarization if the data is available from this data set or from previous studies. If data is available in one data set for many different deficiencies (e.g. IDA, VAD, IDD) then make one overall situation analysis to begin seeing overlaps in the groups with deficiencies and regions where they exist. Also include information on general malnutrition (stunting, wasting, and underweight) and socio-demographic data.