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2. Annex
3. NIPN Guidance Notes
4. Managing and analysing data
5. Data quality assessment
6. Quality assurance of routine data (8/10)

Quality assurance of routine data (8/10)

5. Additional considerations important to NIPN

Good data quality is not always sufficient to obtain strong evidence. It is also important to ensure that overlapping data are as comparable as possible. This can be done by:

• Harmonising geographical area
• Harmonising time frames
• Harmonising the way of asking questions
• Harmonising definitions of nutrition indicators (be mindful that these can slightly differ from one country to another, for instance in the definition of the age groups used, etc.

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