Public Nutrition: Assessment and Advanced Analysis INHL 709 Spring 2009

1. Public Nutrition: Assessment and Advanced Analysis INHL 709 Spring 2009 Tues Thurs: 9.00—10.30 in 2200-23 + troubleshooting 1-2.30 Fridays

3. Introduction (lectures 1 & 2) • ‘Assessment and Analysis’ • Planning framework: questions to address • Research questions and dummy tables • Language, variables, indicators • Data sources • Data transformations, units of analysis.

7. ASSESSMENT AND ANALYSIS Practical aspects analytical approach data handling pragmatic analysis interpretation Concepts what is data? what is its relation to reality? levels and units of analysis preserve information types of variables outcome classifying determining -- causal, interactive, confounding process Uses program design policy advocacy monitoring evaluation

10. For programme planning … You need to decide: Coverage: how many people? Targeting: who? Intensity: resources/head Content: what activities (components)?

11. 2. Planning framework: questions to address (and dummy tables)

13. Research questions… Specify … keep going till you answer them … refer back to them when you get lost

14. Answer questions Produce results (tables, models, graphics) Work up dataset Collect data Research questions Dummy tables Define variables Design questionnaire

15. Research questions on malnutrition (examples): How serious/extensive is it? (Compare to norms) Is it worse in some places/for some populations? (Compare between groups at one time) Is it getting better or worse, for whom? (Compare between times, for groups: norm 0.5 – 1 ppt/yr) What is cause of current situation, or changes? (Analyze associations; includes evaluation) You could also ask: what problems are we trying to solve, and what resources do we have … this would come in at question 1, but then continue to ask how the resources address the problems ...

16. How serious/extensive is malnutrition? • E.g. prevalences of underweight, wasting, GAM etc. • Note: interpretation may need to differ by population group, e.g. pastoralists vs agriculturalists; mortality risk varies in relation to GAM. 10% cut-point for agriculturalists may be equivalent to 20% for pastoralists E.G of dummy table E.g. of cut-points: 10% warning, 20% emergency

17. Is malnutrition worse in some places/for some populations? Example of dummy table: compare districts A and B Don’t forget precise title! Prevalences of wasting and stunting in children < 110 cms in Northern province, January 2007

18. 3. Is malnutrition getting better or worse, for whom? Example of dummy table Prevalences of wasting in children 6-59 months in January and July 2007 in Northern province

19. or Prevalences of underweight children (6-59 mo) in 2001 (May-July) and 2005 (June-Nov) Sources: DHS, 2001; MICS, 2005

20. 4A. What are possible causes of the current levels of malnutrition? Prevalence of underweight in children (6-59 mo) by food security and district, controlling for education level

21. 4B. What are possible causes of changes in malnutrition? Changes in prevalences of malnutrition Jan – July 2007 in children (6-59 months) with receipt of food aid, for food insecure and secure households.

25. 3. Language, variables, indicators

38. 4. Data sources

42. 5. Data transformations, units of analysis

44. Units of analysis (file structure) • Preserve information • Decide early • Usually most disaggregated, repeating if needed (e.g. individual, household) • Beware confounding, ecological fallacies if aggregated (e.g. district) data • Care with hierarchical data, clusters, design effects.