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Test Yourself

Using the Kenya Rift Valley region (krvp2.sav) data set complete the following tasks to test your understanding of the material presented in this chapter. If you have any questions, use the analysis package for assistance. The Answer Key to these questions can be obtained at the end of the page.

1)  Given the following data for two districts calculate the prevalence of underweight for the region.

 

 

Child Population

Prevalence Underweight (%)

# Underweight Children*

District A

200,000

20

?

District B

50,000

40

?

Region  

?

?

* estimate that 20% of child population is underweight.

 

 

Prevalence Underweight (%)

Total Population (million)

District A

15

2.468

District B

30

1.234

Region

?

 

 

2)  Create a country level area profile, including information on: nutritional status, health care access, SES, literacy or education level, water and sanitation.

3)  Perform a district level area profile, then rank districts by prevalence of malnourished. It might also be good to consider the number of malnourished children in each district, and the percent of the total malnourished that each district contributes. Adding other independent variables like health care access (immunization rates) and mother's level of education are insightful.

4)  Explore current program targeting (national level), how well are current programs targeted to those most in need (malnourished)? Make suggestions for retargeting or shifting resources within these programs. Here it is useful to consider things like health care access, delivery (location or who attended) and immunization.

5)  Are water source, access to toilet (or latrine type), mother's education level, SES and healthcare access associated with weight/age Z score and/or prevalence of underweight? To do this, create a table showing values of the outcome (waz and prev underweight) by good/bad categories of the determining variables to calculate size and significance of differences. Summarize your data and explain your findings.

Explore associations between independent and dependent variables (nutritional status) to look for evidence of causality, to guide further analysis.

 

Compare your results with the Chapter Three Testing Questions answer key.