Principles of nutritional data analysis

1. Principles of nutritional data analysis • start with planning needs • research questions, dummy tables, variables and indicators • analytical sequence Ctown3.ppt

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

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

5. Research question Dummy tables Define variables Design questionnaire

6. Research questions on malnutrition: 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 ...

7. 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

8. 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

9. 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

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

11. 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

12. 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.

13. Variables and comparisons Define dependent (outcome) and independent variables Measures Indices Indicators Define comparisons – are they valid? Checks? By season, sampling, age band, measurement/question? Define population groups sampled (i.e. universe) or post-defined. In planning, from effect size, variation, design effect, calculate needed sample size.

14. Now, if planning the survey, the questionnaire can be designed. If you are using an existing dataset, you can see if the needed variables can be derived from those in it.

20. Analytical sequence (after cleaning, transforming, structuring (PANDA Chs 1 & 2)) • Situation analysis: aggregate indicators, compare with norms • Then disaggregate to • One-way analyses or comparisons (PANDA Ch 3) • by area, population group, for targeting • by potential factor for intervention, to examine associations (good/bad, high/low), for causality (or context) • Two-way (PANDA Ch 4) for causality • one-way factors within categories of another • to control for possible confounding • or to see possible effect modifications (interactions) • Multi-way (PANDA Ch 5) for causality • for more control, interactions …

21. Where and who: have unmet needs for family planning services? are sick, becoming disabled, dying prematurely? are malnourished (and what type)?

24. Framework for assessment and analysis (1)

30. Framework for assessment and analysis (2)

33. Framework for assessment and analysis (3) Here we need associations to suggest causes to tackle ...

37. Assembling ... • set of questions • format of analyses to answer them