Using and Interpreting Survey Results for Decision-Making
USING A CAUSAL FRAMEWORK TO CONSIDER THE RELATIVE
IMPORTANCE OF DIFFERENT CAUSES OF MALNUTRITION
A causal framework (see Conceptual Model of Malnutrition) is necessary to understand long-term causes of malnu- trition in the population and decide on the information to be gathered in a survey. Non-food causes of malnutri- tion and mortality may aggravate the situation rapidly even if rates are not alarming at the moment.
In an individual, malnutrition is the result of inadequate dietary intake, infec-
tion or a combination of both. The wide- ly used UNICEF conceptual model of the causes of malnutrition (Figure 4.2) organizes and explains malnutrition by layers of causes. Malnutrition is caused by more than a simple lack of food; there are other underlying causes that can con- tribute to adverse nutritional outcomes. The multisectoralcauses of malnutrition involve dietary intake, poor health, envi- ronmental factors and care practices. For an individual to be adequately nour- ished, the underlying causes of malnutri- tion - health, food, care - need to be addressed in tandem.
Table 4.4 Baseline reference mortality data by region5
Region
Sub-Saharan Africa Middle East and North Africa South Asia
East Asia and Pacific Latin America and Caribbean Central and Eastern European Region/CIS and Baltic States Industrialized countries Developing countries Least developed countries World CMR (deaths/ 10,000/day) 0.44 0.16 0.25 0.19 0.16 0.30 0.25 0.25 0.38 0,5 CMR emergency threshold (2 x crude mortality rate) 0.9 0.3 0.5 0.4 0.3 0.6 0.5 0.5 0.8 0.5 U5MR (deaths/ 10,000 children under 5/day) 1.14 0.36 0.59 0.24 0.19 0.20 0.04 0.53 1.03 0.48 U5MR emergency threshold (2 x under- 5 mortality rate) 2.3 0.7 1.2 0.5 0.4 0.4 0.1 1.1 2.1 1.0 2000 2005
Underlying causes of malnutrition The main underlying preconditions to adequate nutrition are food, health and care; the degree of an individual's or household's access to these precondi- tions affect how well they are nourished.
Food quantity and quality
Food security exists when, at all times, everyone has access to and control over sufficient quantities of good, quality food needed for an active and healthy life. For a household, this means the ability to secure adequate food to meet the dietary requirements of all its members, either through their own food production or through food purchases. Food production depends on a wide range of factors, including access to fertile land, availabil- ity of labor, appropriate seeds and tools, and climatic conditions. Factors affecting food purchases include household
income and assets as well as food avail- ability and price in local markets. In emergency situations, other factors - including physical security and mobility, the integrity of markets and access to land - may come into play.
Health and sanitation environment
Access to good, quality health services, safe water supplies, adequate sanita- tion and good housing are precondi- tions for adequate nutrition. These pre- conditions are affected by the existing primary health infrastructure, the types of services offered, their accessibility and affordability to the population, and the quality of these services. Key envi- ronmental issues include the degree of access to adequate quantities of safe drinking water, adequate sanitation and adequate shelter. Health and environ- mental factors influence incidence and
Source: the States of the world’s Children 1998 - UNICEF
9 The State of the World's Children 1998 (URL: http://www.unicef.org/sowc98/). New York: UNICEF; 1998.
Child malnutriction,
death and disability Outcomes
Immediate causes Underlyng causes at houseshold/ family level Basic causes at societal level Inadequate maternal and child-care practices
Poor water/sanitation and inadequate healt service
Insufficient acces to food
Inadeguate dietary intake
Quantity and quality of actual resources- human, economic and organizational- and the way they are controlled Inadequate and/or inappropriate
knowledge and discriminatory attitudes limit household acces to actual resources
Political, cultural, religious, economic and social systems, including women’s status, limit the utilization of potential resources
Disease
Potential resources: enviroment, technology, people
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severity of disease. Health and nutri- tion are closely linked in a “malnutri- tion-infection cycle” in which diseases contribute to malnutrition and malnu- trition makes an individual more sus- ceptible to disease.
Social and care environment
Malnutrition can occur even when access to food and healthcare is suffi- cient and the environment is reason- ably healthy. The social and care envi- ronment within the household and local community also can directly influence malnutrition. Appropriate childcare, which includes infant and child feeding practices, is an essential element of good nutrition and health. Cultural fac- tors and resources, such as income, time and knowledge, influence caring practices. The values of the society dic- tate the priority given to the care of children, women and the elderly. Attitudes to modern health services, water supplies and sanitation also affect caring practices.
Immediate causes of malnutrition
On an immediate level, malnutrition results from an imbalance between the amount of nutrients needed by the body and the amount of nutrients being intro- duced or absorbed by the body. Adequacy of food intake relates to: a) the quantity of food consumed; b) the quality of the overall diet with
respect to various macro- and micronutrients;
c) the form of the food consumed, including palatability and energy density; and
d) how frequently the food is consumed.
However, malnutrition is not synony- mous with a lack of food. In an individ- ual, malnutrition is the result of inade- quate dietary intake, disease, or both. Health and nutrition are closely linked. Disease contributes to malnutrition through a loss of appetite, malabsorp- tion of nutrients, loss of nutrients through diarrhea or vomiting, or through altered metabolism. Malnutrition, in turn, makes an individ- ual more susceptible to disease. While the conceptual framework pro- vides a useful approach for considering the causes of malnutrition, its useful- ness depends on the availability of information about those causes. Such complementary information may include quantitative data from sources other than surveys and qualitative infor- mation gathered from focus groups, interviews with key persons, and per- sonal observations or observations by national or international colleagues who know the situation well. Sources of such data can vary widely and not all types are equally useful for all types of WFP needs. Even within the scope of WFP needs, uses of data can differ depending on the context of the data collection and objectives for the use of the informa- tion. A matrix (Table 4.1) provides rough guidance on suggested use of dif- ferent sources of information for a vari- ety of WFP purposes. This is by no means exhaustive, nor regulatory.
Complementary data may also include the causal framework or pathway of mal- nutrition and a seasonal calendar: A seasonal calendar provides informa- tion about harvests and hungry periods, seasonal disease epidemics and other events that may affect food insecurity (e.g., food distributions).
All primary and secondary information should be checked against other sour- ces of information and confirmed with partners.
Interpreting trends over time
In general, when you compare two or more surveys to assess trends in malnu- trition and mortality in a given popula- tion, these surveys must have used methodologies that meet similar quality and procedural standards. For example, did both samples use representative sampling methods and comparable
measuring techniques? Consider whe- ther the surveys used or collected data for the same:
• definitions of malnutrition (i.e., Z score [preferred] or percent of the median); • population;
• age groups;
• geographic area; and • season.
Whenever possible, WFP and partner organizations should conduct a baseline survey in the area where the nutrition pro- gram or intervention will later be conduc- ted. In acute emergencies, interventions may have to start immediately, and a sur- vey will be conducted as soon as is possi- ble. Any initial survey should consider sample size requirements for baseline and follow-up surveys (see Chapter 3). If conducting a baseline survey is not possible, other sources for surveys may be used. Note that national survey
Table 4.1 Matrix of sources of information for WFP purposes
Facility Based Data Sample Survey ENA Assessment VAM Survey Nutrition Surveillance National Survey Operations/ Program Management + + + + + + + + + + + + Targeting/ Prioritization + + + + + + + + + + + + + RBM/ Corporate Reporting + + + + + + + + + + + Advocacy + + + + + + + + + + + + + + + Population < > level Individual level
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results should not be used as a baseline because national prevalence may not be representative of smaller subsets of the population. If a national survey is con- ducted with survey methodology that allows for statistical disaggregation into subsets, then this disaggregated data might be useful for these purposes. However, consultation with statisticians or the Nutrition Service in Rome should be undertaken before such a decision is made. National surveys that usually have provincial-level estimates include MEA- SURE DHS (Demographic and Health Surveys; DHS)1, UNICEF's Multi
Indicator Cluster Surveys (MICS)2, or the
WHO Global Database on Child Growth and Malnutrition3.
What are some potential differences in geographical coverage and methods? Comparing current malnutrition preva- lence in a district in southern Ethiopia with a baseline estimate for the whole of Ethiopia or eastern Africa has little mea- ning. A current survey result may be compared to a previous survey that was conducted in a different season, or a baseline survey that has covered several seasons over one or several years. Differences in measuring mortality are ano- ther potential problem when comparing survey results. Child mortality is expressed by UNICEF and WHO as the probability of dying between birth and 5 years of age per 1,000 live births. Conversion to an age-spe- cific mortality rate for children under 5 years, as shown in Table 4.4, requires a mathematical transformation. That tran- sformation is based on certain assumptions that need to be considered as limitations when results are discussed.
If 95 percent confidence intervals are provi- ded, as in Tables 4.1-4.3, overlapping con- fidence intervals alone are not sufficient to
assume that there is not a statistically signi- ficant difference between the baseline and the current survey. However, they at least indicate that the results of the two surveys may not be different. Non-overlapping con- fidence intervals show that the two surveys are significantly different. Always determi- ne the statistical difference between a base- line and follow-up survey by either compa- ring confidence intervals or calculating a P value for the difference. Confidence inter- vals should be presented for all outcomes in your survey, independent of their availa- bility from a previous baseline survey. How should I interpret changes from baseline to follow-up?
Interpretation of changes between baseli- ne and follow-up(s) depends on the magnitude of the change, trends and the context. A doubling of the baseline often indicates the presence of an acute emer- gency. However, it is essential to verify that such an increase is actually “real,” as described above.
The causes of malnutrition are complex. Emergency settings and perceptions of what is “typical” or “atypical” in a given country or a given district within a coun- try differ. Such differences make it diffi- cult to develop and make available a standardized, generally agreed upon classification of severity of malnutrition to match to baseline information. However, some internationally agreed upon cut-off values have been developed to provide a guide for classifying malnu- trition and mortality rates. Tables 4.5 and 4.6 show malnutrition classifications and mortality benchmarks, as defined by WHO6and Sphere7. These classifications
are based on acute malnutrition, chronic malnutrition, underweight and mortality. Population benchmarks for other outco- mes, such as low birth weight or mater- nal mortality, are not available.
Table 4.5 Classification of severity of malnutrition in a community by prevalence of acute malnutrition, chronic malnutrition and underweight for children under 5 years of age 6
Severity of malnutrition Acceptable Poor Serious Critical Acute malnutrition (%) (weight-for-height) < -2 z scores <5 5-9 10-14 ≥ 15 Chronic malnutrition (%) (height-for-age) < -2 z scores <20 20-29 30-39 ≥ 40 Underweight (%) (weight-for-age) < -2 z scores <10 10-19 20-29 ≥ 30
Table 4.6 Mortality benchmarks 7
Indicator Crude mortality rate Prevalence of anaemia Baseline 0.5/10,000/day 1/10,000/day
Benchmark for alert
1/10,000/day 2/10,000/day Benchmark for critical emergency 2/10,000/day 4/10,000/day
Table 4.7 Classification of public health significance of anemia based on the prevalence of anemia 8
Category of public health significance
Normal Mild Moderate Severe Prevalence of anaemia (%) ≤ 4.9 5.0-19.9 20.0-39.9 ≥ 40.0
Note: The prevalence of iron-deficiency disorder is likely to be 2-2.5 times greater than the prevalence of anaemia
USING AND INTERPRETING SURVEY RESULTS FOR DECISION-MAKING CHAPTER
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Table 4.8 Classification of public health significance of iodine deficiency disorders based on the prevalence of goiter or urinary iodine6
Category of public health significance Normal Mild Moderate Severe
Total goiter rate (%)
< 5.0 5.0 - 19.9 20.0 - 29.9 ≥ 30.0
Median urinary iodine level in school children µg/L (%)
≥ 100.0 50.0 - 99.9 20.0 - 49.9 < 20.0
Table 4.9 Classification of public health significance of vitamin-A deficiency in children (6-71 months) based on the prevalence of night blindness or serum retinol 9
Category of public health significance Normal Mild Moderate Severe Night blindness (%) 0 0 < 1 ≥ 1 < 5 ≥ 5
Serum retinol < 0.7 µmol/L (20 µg/dL) (%)
< 2 ≥ 2 < 10 ≥ 10 < 20 ≥ 20
At least 95 percent of children 6 months to 15 years of age should be vaccinated against measles and have received an appropriate dose of vita- min A supplementation7. All infants
vaccinated between 6-9 months of age receive another dose of vitamin A upon reaching 9 months. Routine vac- cination programs ensure the mainte- nance of 95 percent coverage.
INTERPRETING MORTALITY IN LIGHT