Most of the collected data used in nutrition related analysis fall into one of the following categories:
Some examples of where to look for data are: HH surveys, clinical growth monitoring or school data, or weighing programs.
Birth Weight Underweight (weight for age z-scores) Stunting (height for age z-scores) Wasting (weight for height z-scores) Middle Upper Arm Circumference (MUAC)
Indices such as weight, height, and age, are compared to the values of a reference population to see if they are worse than expected from the reference. For the same age child, the height or the weight is compared to the height and weight of the reference population. Chapter 6 Submodule takes you through hand calculations using the reference tables which have been calculated from the data collected by the National Center for Health Statistics (NCHS).
The "Z-score" of a child uses the standard deviation of the reference distribution for a given measurement. The index expressed in z-scores represents the difference between the observed weight and the median weight of the refernce population at the same age.
Weight/height index = (Observed weight - Reference weight)
Iodine -measure total goitre rate in school children; urinary iodine concentration, salt
iodization surveys, and iodization of salt as a proxy of iodine deficiency
Vitamin A - clinical measure of night blindness (a word in the local language for nightblindness may be an indication that the community is aware of this clinical sign), Bitot's spots, serum retinol <70 ug/l, food frequency questionnaire, vitamin A capsule distribution
Iron - hemoglobin or hematocrit readings, anemia, distribution of ferrous sulfate, consumption
of absorption inhibitors like phytate and enhancers like vitamin C
For more details, click on 'outcome variables' at the start of this section.
Area Gender Age Occupation Distance from health post Rural/Urban location Education level (e.g.,of mother); literacy Socio-economic status (usually as proxy, like housing, assets) Water source, sanitation (e.g., latrine)
Breastfeeding behaviors - breastfed in first hour, exclusive breastfeeding, age breastfeeding ceased Complementary feeding - age complementary feeding began Immunization - age of immunization, individual types of immunization, percent receiving immunizations Water and sanitation - access to safe water source, habits for water use, hand washing, food washing,
access to latrine, type of latrine, etc.
Look for interactions between variables that might show different effects at different levels and also for confounding, which can mislead in the interpretation of results.
Conceptually and methodologically, classifying and determining variables are similar and differ mainly in interpretation.
Percent receiving immunizations Coverage of media message Number of facilitators trained Percent of children exclusively breastfed from 4-6 months
Note: These will be numerous and varied depending on the goals of the program. They may also be tested analytically in the same way as outcome variables. For example, you might have to know the distribution by area of immunization coverage, or the correlates of exclusive breastfeeding.
These variables types:
OUTCOME CLASSIFYING DETERMINING PROCESS
... are often interchangeable depending on the precise research question being studied. If this question is explicitly stated, confusion can be avoided!!
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