Regional Technical Working Group Meeting on Developing Nutrition Information Systems
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Regional Technical Working Group Meeting on Developing Nutrition Information Systems Nairobi, 1-3 Feb 2007 Aims of Nutrition Information John B Mason, Tulane SPHTM. Area level survey results, Kenya: GAM % by season. Area level survey results, pooled & smoothed: Kenya, GAM%, by season.

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Regional Technical Working Group Meeting on Developing Nutrition Information Systems

Nairobi, 1-3 Feb 2007

Aims of Nutrition

Information

John B Mason, Tulane SPHTM






  • Usual sources of data are: GAM%, by season

  • repeated large-scale surveys (e.g. natl, DHS, MICS)

  • area level surveys (e.g. 30 by 30)

  • reporting systems using data from clinics, screeening, programmes

  • sentinels systems, from sites (e.g. clinics) or special surveys




  • Sampling procedures GAM%, by season

  • PPS, then issue is at last stage

    • Options: spin-the-bottle; segmentation-full enumeration; segmentation then sample

  • Consider bias; re-estimating pop numbers (for weights)

  • Depends on feasibility (incl. habitation features: e.g. along road/river vs round); and use

    • Compare results with norms, use for targeting, get trends


  • Child mortality estimates from area level surveys GAM%, by season

  • Issues are

    • Estimate and state confidence intervals, which will be wide with 30*30 design, and calculate design effect

    • Care in interpreting these -- e.g. what does 0.5-2.0/10,000/day over last 3 months mean?


  • Indicators GAM%, by season

  • Malnutrition can worsen without showing in wasting -- see Srn Africa 02-3: use wt/age if possible

  • Evidence suggests: interpret wasting WITHIN populations, not across, because of different growth patterns and relations to mortality

  • More focus on getting ages?




Maternal and new born data GAM%, by season

Birth weight relates to maternal BMI, but that is not directly related to MMR as indicator of health care ...


Different relations between GAM% and child mortality in different populations

Hence interpret GAM within populations, not across ...



  • Capacity different populations

  • Enough people?

  • Is this useful for them?

  • Needed skills?

  • Resources and priorities?

  • How to meet these needs…?


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