Steps to Targeting
Return to Previous Page
Here is the Step by Step Process:
For ease of presentation in this exercise use only those districts in division 2. To do this select data, select cases and press the if button. Select the div variable and move to the right and type "=2" so that the formula reads "div=2". Press Continue and then OK.
1. Rank districts by Prevalence
Try creating a Case Summaries list using the Bangladesh data set:
2. Add Number of Malnourished, and Percentage of Total Malnourished
To add the number of malnourished and percent total malnourished, run the same Case summaries and add the variables labeled maln# and totmalpt to the list run before, then press OK.
The result should be something like the following.
Remember that since we selected only district two the %total malnourished will not equal 100%.
If the number of malnourished children was not given as it is here, then it could easily be calculated using the Transform, Compute option in the menu. The new target variable would be named maln# The prevalence of low arm circumference would be multiplied by the population of children under five. In this case, the population under five is not given, therefore an estimate must be made by taking the average for that region of the world (probably about 20% of the total population). The Numeric Expression would be acprvfm*(pop*.2)
3. Rank by the number of malnourished
To rank by the number of malnourished, go back to the previous routine of sorting the data set by a variable (in this case use maln#). Recall that sorting is done by clicking on Data, Sort cases, insert maln# as the variable (descending order) and click on OK. This will order the data with the greatest number of malnourished at the top and the least number of malnourished at the bottom of the list instead of the current ranking by district.
4. Note which districts go up to the top of the ranking list
The top five districts for number of malnourished children are: Dhaka, Kishorenganj, Mymensingh, Madaripur, and Jamalpur, in that order. Take a note of the order of these districts and which ones are at the top so that they can be compared to the order in the next steps.
5. Rank again by prevalence and make initial selection
Under Data, then Sort cases sort by prevalence of low ac (acprvfm), descending
Here you see that the top five in prevalence are highlighted in red and the top five in number of malnourished are highlighted in yellow. This is the comparison between districts with the highest prevalence vs. the highest number of malnourished and it shows how they do not always perfectly coincide. Depending on what the intervention strategy is and how much per head the cost of implementing, the district targeting will be modified to most efficiently provide for the most children in need and those that are the worst off (considering both numbers and prevalence). This will depend on the amount of resources available as well and the specification of the funding agency.
6. Add an Indicator of Health Services (measles immunization rate here called meas)
Click on Statistics, Summarize, Case Summaries and insert the variables div, district, acprvfm, maln#, totmalpt, meas and click on OK.
When estimating the other potential influences, an indicator of health service might be helpful. Here Jamalpur, Madaripur, and Narsingdi do not have good access to health care (at least measles immunization). This may be helpful in furthering the decision on which areas to provide alleviation programs to and which ones might already have a high level of services provided.
Return to Top of Page