Insert image of global prevalence of MN deficiencies- revised version by John
In September 1999, the World Summit for Children established micronutrient goals to be achieved by the year 2000:Assuring access to micronutrients in dietary change, fortification of food or water, and supplementation require political commitment and strategic planning. Designing micronutrient programs also require better targeting (universal, medical, or geographical/seasonal), improving the effectiveness and coverage of delivery systems, raising consumer awareness, and maximizing compliance with fortification mandates.
Structure for Considering Micronutrients
Situation
Prevention Methods for Deficiencies
Recent Progress and Outlook
To address all of the areas, some additional information (other than the data set) would likely need to be considered (e.g. current policies and programs, previous program reports, costs, etc.). But even with an understanding of nutrition programming and little contextual information, a great deal of insight can be gained from analyzing data provided in PANDA or the data that might be waiting for an analyst where you are. This package will address the fundamentals of looking at micronutrients in nutrition data analysis using commonly available large cross-sectional data sets (e.g. DHS and MICS) as well as a few smaller, micronutrient specific data.
Realm of the MN PANDA
Another point to be made in approaching micronutrients analysis, specifically interpretation for programming, is that deficiencies do not often stand-alone. Many times, this calls for consideration of multiple micronutrient interventions, although not frequently considered in the recent past. In a meeting of an expert committee formed to address the prevention of micronutrient deficiencies, the following two conclusions were made:
Source: Howson, CP, Kennedy, ET, and Horowitz, A., eds., 1998. Prevention of Micronutrient Deficiencies. Washington DC, National Academy Press.
Although the MN PANDA does address analysis individually considering VAD, IDA, and IDD, the structure was designed so that they are looked at also for overlapping deficiencies (considering micronutrient interactions) when the data is available. MN PANDA will include more information on the current understanding of micronutrient interactions (as the literature allows) and to address the applications to analysis (as data sets are released).
Micronutrient Interactions
MICRONUTRIENT INTERACTIONS Iron and Vitamin A- Vitamin A deficiency inhibits iron utilization and accelerates the development of anemia. Studies have shown that Vitamin A supplementation improves hematological indices in young children and pregnant women with an increased benefit when supplementation of iron and Vitamin A occurs. Iron and Folate- Routine iron and folate supplementation during pregnancy is widespread in the effort to combat anemia through the impact on birth outcomes. Studies on the interaction of these nutrients has not been reported, although one small study in India on pregnant women showed supplementation with folic acid and iron resulted in higher hematological results than that with iron alone. Iron and Zinc- Studies looking at the effects of iron and zinc absorption have shown conflicting results, it appears that the interrelationship between iron and zinc may be bi-directional. High iron concentrations appear to negatively affect zinc absorption when these micronutrients are given in solution but when given in a meal, this effect is not observed. Iron and Calcium- Calcium is a known inhibitor of iron absorption. Iron and Vitamin C- Vitamin C is a known to enhance iron absorption though the additional benefits of iron and Vitamin C supplementation have not been studied. Vitamin A and Zinc- In studies looking at the interaction of these among low-income pregnant teenagers of Mexican decent, supplementation with zinc did not improve vitamin A status. Zinc and Folic Acid- There is conflicting evidence as to whether folic acid supplementation may adversely affect intestinal zinc absorption. Zinc and Copper- Zinc supplementation could precipitate copper deficiency when given in high doses. |
Source: Annex 6 of the report on Multiple Micronutrient Supplementation in Tanzania UNICEF Dar es Salaam. Sources of the Annex: Ramakrishnan et al 1999, Nestel and Alnwick 1997, WHO 1995, MI 1998, Hunt et al, 1985, Whittaker, 1998.
VAD Introduction
Regional Prevalences and Numbers of Children Affected by Sub-clinical
Vitamin A Deficiency
RegionSub-clinical Vitamin A Deficiency
(preschool)
1995
Prevalence
Est. No.
Affected(millions)
South Asia
35.6 %
59.5
Sub-Saharan Africa
35.3 %
36.0
East Asia Pacific
18.2 %
29.6
Middle East & North Africa
9.8 %
4.2
Latin America and Caribbean
19.6 %
10.2
TOTAL
26.5 %
139.5
VAD: Prevalence data is from Progress in Controlling Vitamin A Deficiency, Tulane University, Micronutrient Initiative, UNICEF 1998. VAD Sub-clinical for SSA: weighted the E. & S. Africa and W. & C. Africa figures to collapse into SSA. E & S. Africa was 37.1 % VAD and 18.6 million affected, W & C. Africa was 33.5% VAD and 17.4 million affected, whereas the combined region of SSA is 35.3 % VAD and 36 million affected.
Over 100 million children suffer from vitamin A deficiency contributing to over 2.2 million deaths each year from diarrhea and 1 million deaths from measles (UNICEF, 1998). Over 350 thousand pre-school children suffer from partial or total loss of vision from Vitamin A deficiency each year (WHO, 1998). It was a result of field trails in Indonesia in the 1980s that the international community began to recognize the profound impact of giving vitamin A supplementation for the prevention of illness and mortality from a weakened immune response as well as visual impairment and blindness. Since that time many trials and programs have worked to better understand how vitamin A intake affects the health of a population and how to most effectively prevent its deficiency.
Vitamin A deficiency manifests in several stages so that the effects of mild depletion might not manifest into common clinical symptoms (e.g. nightblindness) when it has already begun weakening the immune system, increasing susceptibility to infection. Since vitamin A is fat soluble, stores can remain in the liver for up to 6 months. When dietary intake is not sufficient and the liver stores become deplete, the effects might include decreased epithelial barriers and immune function, which lead to infection. At a further point in depletion, the reduction rhodopsin occurs, which decreases vision in low light/ night—this is referred to as nightblindness. Even further depletion then leads to other frank clinical signs such as xeropthalmia, bitot’s spots, and even blindness.
When analyzing vitamin A deficiency data, it is important to identify which outcome indicators have been collected and how effective these indictors are at measuring the impact of the deficiency on a population. The earlier you catch a deficiency the better, therefore recognizing that frank signs such as nightblindness and xeropthalmia come in the latter stages of deficiency (and therefore underestimate the true affected population) is important. It is now accepted as good practice to consider dietary availability and food habits in assessing risk for vitamin A deficiency in a population, even before clinical signs develop. (Helen Keller International has developed a vitamin A Food Frequency Survey that is used around the world for assessing population risk.)
The following list provides some of the data sources for Vitamin A deficiency (and comments on their applicability):
Source: International Conference on Nutrition: Major Issues for Nutrition Strategies, WHO and FAO, 1992.
Data Sources for Assessing Vitamin A Deficiency
Data Source Comment on Usefulness
Food Balance Sheet Useful for national trends
Food consumption/ Food Frequency Survey (FFQ) Useful; includes frequency in diet of Vitamin A foods
Clinical Signs Preliminary assessment
Prevalence Survey
Case finding; needs expert scouting
Eye signs important; large samples needed
Biochemical test Serum retinol estimates in blood samples; distributions, dose responses
Clinic Records Eye lesions may be noted, but not very specific
Schools Not the most sensitive age group
Control Programs Supplement distribution through Public Health Care, immunizations may be noted
The MN PANDA is a tool to teach people working in nutrition to handle micronutrient data and interpret the data effectively for use in program development. The micronutrient module includes sample data sets (DHS …) with Vitamin A indicators that have been collected over the past 10 years, to teach the process of analyzing data collected on vitamin A deficiency and to interpret associations and links to causality. MN PANDA will provide a data set with process indicators only (such as Vitamin A capsules and dietary intake) as well as a data set with process and outcome indicators (such as nightblindness, xeropthalmia, serum retinol). The many exercises that follow will allow for familiarity and skill building in analyzing surveys with micronutrient data.
The first step will be to look at the data sets provided and begin to characterize the data and clean the variables used in the analysis. Continue on to Section 1 VAD: Data Characterization and Cleaning.
IDA Introduction
|
Anemia 1975-98 1995 |
|
| Prevalence | Est. No. Affected(millions) |
|
South Asia |
59 % |
149.0 |
Sub-Saharan Africa |
38 % |
41.5 |
East Asia Pacific |
42 % |
140.4 |
Middle East & North Africa |
33 % |
20.3 |
Latin America and Caribbean |
24 % |
27.2 |
TOTAL |
43 % |
378.4 |
Sources and Notes Anemia: Prevalence data is from Progress in Controlling Iron Deficiency, Tulane University and Micronutrient Initiative June 1998.For Latin America and Caribbean: the regional prevalence was determined by weighting the prevalence figures of 27% and 17% with 0.675 and 0.325 for South America and Middle America/ Caribbean respectively. Anemia estimated numbers affected were estimated by calculating the percent pregnant in each region using WHO estimations 1995 and applying these percentages to the 1995 population figures for the regions from UN Population Division 1995 (SOWC 1997). These estimations of non-pregnant women were multiplied by the prevalence of anemia in the region to determine the number of affected women. Adjustments to the age structure from 15-59 used by WHO to 15-49 used in this presentation were made using 1995 population estimations for women (UN Populations Division, Demographics Indicators 1950 ? 2050, 1996 revision).
Iron deficiency anemia is probably the most prevalent nutritional problem in the world, affecting over half the women in developing countries and a large percentage of young children (UNICEF, 1998). About 1 billion people suffer from clinical anemia around the globe, in both developing and developed countries. Iron deficiency occurs most commonly among groups that are experiencing rapid growth (children and pregnant women) or individuals who are burdened by infection (often young children). When iron is insufficient to restore the hemoglobin in blood production, then the results are alarming. Individuals become weak, fatigued, and susceptible to infection, children experience decreased cognitive ability, adults lose work capacity, and mothers sometimes miscarry children and sometimes die in child birth. The effects of iron deficiency anemia are not slight, and unfortunately the programs addressing the problem have not seen overwhelming success as of yet. Understanding IDA and tackling the ill effects should be a primary focus in nutrition programs and policies.
Iron deficiency anemia results from several factors; low intake, iron loss, increased need, and inability to absorb the iron. It is often important to look at many or all of these factors to fully understand who is at risk in a population, who is affected, and why. First, understanding iron’s role in the body is essential. Iron is used in the production of hemoglobin, a component of red blood that allows for transport of oxygen to the tissues in the body. Without adequate oxygen supplied to the tissues, fatigue and illness results. Two-thirds of the iron in the body is actively used (functional), mostly as this oxygen-carrying molecule, hemoglobin. About one-third of the iron in the body is kept in the liver (storage), although it can rapidly be depleted when bodily needs are high and iron intake is low (e.g. iron supplementation must be daily or weekly at minimum).
Iron intake is usually through one of two forms, heme (meat source) or non-heme (non-meat source such as eggs, dark greens, nuts, unrefined cereals). Absorption of the heme iron is far greater than non-heme, although it depends on other components in the meal (enhancers and inhibitors). Vitamin C (or acidic/ fermented foods) and other meats increase iron absorption in a meal with non-heme sources, whereas coffee and teas (tannins) and whole grains (phytate) decrease absorption. In response to decreased iron storage and circulation, the body naturally increases the absorption of dietary iron through the gut (from 1% to as much as 50% in deficient individuals). Losses of iron occur mostly through intestinal mucosal cell loss through the feces (this is drastically increased during infection) and through blood loss (especially in menstruating women).
When analyzing iron deficiency data, it is important to identify which outcome indicators have been collected and how effective these indictors are at measuring the impact of the deficiency on a population. Measuring for iron deficiency clinical outcome is actually not at all precise, therefore difficult. The clinical effects of IDA are also a result of other things, therefore using fatigue and pallor as the outcome measure for IDA is not effective. In addition, the earlier you catch a deficiency the better, therefore be sure to recognizing that clinical signs such pallor come in the later stages of deficiency (and therefore underestimate the true affected population). Although anemia is actually one of the latest stages of iron deficiency, it is a reliable way to diagnose anemia and quite easy to measure through a simple finger prick and a hemoglobin test. Because iron deficiency is so widespread in identified groups, it is most recommended to take preventative measure through iron supplementation to women of reproductive age (and often, young children).
The following list provides some of the data sources for Iron deficiency (and comments on their applicability):
Data Sources for Assessing Iron Deficiency
Data Source Comment on Usefulness
Food Balance Sheet Useful for national trends, look at animal source iron (as bioavailability varies greatly by source)
Food consumption/ Food Frequency Survey (FFQ) Useful; include absorption inhibitors (e.g. phytate) and enhancers (vitamin C)
Clinical Signs Preliminary assessment
Prevalence Survey
Not really necessary
Not very reliable
Biochemical test Hemoglobin and/ or hematocrit in capillary samples
Clinic Records Anemia if recorded may be usefully compiled
Schools Not usual (not most at-risk group)
Control Programs Ferrous sulphate tablet (with folate preferably) distribution through health system: monitor as for essential drugs
Source: International Conference on Nutrition: Major Issues for Nutrition Strategies, WHO and FAO, 1992.
The MN PANDA is a tool to teach people working in nutrition to handle micronutrient data
and interpret the data effectively for use in program development. The micronutrient
module includes sample data sets (DHS …) with IDA indicators that have been collected
over the past 10 years, to teach the process of analyzing data collected on iron
deficiency and to interpret associations and links to causality. MN PANDA will provide a
data set with process indicators only (such as iron supplementation and dietary intake) as
well as a data set with process and outcome indicators (such hemoglobin or hematocrit).
The many exercises that follow will allow for familiarity and skill building in analyzing
surveys with micronutrient data.
The first step will be to look at the data sets provided and begin to characterize the data and clean the variables used in the analysis. Continue on to IDA section 1: Data Characterization and Cleaning.
IDD Introduction
Regional Prevalences and Numbers affected by
Iodine Deficiency (TGR)
RegionTotal Goitre Rate
(all ages)
1985-1996 1995
Prevalence
Est. No. Affected
(millions)South Asia
17 %
203
Sub-Saharan Africa
18 %
91
East Asia Pacific
21 %
329
Middle East & North Africa
20 %
42
Latin America and Caribbean
11 %
41
TOTAL
18 %
706
IDD: Prevalence data is from Progress in Controlling Iodine Deficiency Disorders, Tulane University and Micronutrient Initiative June 1998. IDD for East Asia/Pacific: weighted the China and SE Asia figures to collapse into East Asia /Pacific. China was 20.4% TGR and 236 mill affected, SE Asia was 21% TGR and 93 million affected, thus the combined region is 20.6% TGR and 329 million affected. IDD for Latin America/Caribbean: weighted Middle America and South America figures to collapse into Latin Am./Caribbean
Intro paragraph on the background of IDD…prevalence, current situation…
Iodine deficiency disorders have been studied in great detail, facilitating the response to tackling the global IDD problem. Also, the international promotion of IDD awareness through the WHO, UNICEF, and International Council for the Control of Iodine Deficiency Disorders (ICCIDD) has led to a more "successful" micronutrient story than some of the others. In addressing iodine deficiency disorders, iodizing salt is usually the key to solving the problem. Essentially all populations around the world use salt making it (initially) a good choice for a fortified food. Also, fortification is relatively inexpensive, leading to the global push is to universally iodize salt (USI). This approach is catching on quickly, although monitoring needs are not necessarily met and the coverage is by no means global, yet. In general, the IDD situation has seen improvement throughout the 1990s, therefore with increased advocacy for USI, the improvement should continue. Also, as a short-term measure to combat iodine deficiency in areas not yet iodizing salt, supplementation with iodized oil can be provided.
Iodine has the advantage of long term storage in the human body (similar to Vitamin A) so that if supplementation is used, it only needs to be given a few times a year.
Analyzing data for on IDD should include consideration of many data sources. To come up with the most useful recommendations, it is important to be familiar with the other data sources other than the survey data that have been gathered recently. These other sources will help guide the analysis, both to recognize the high-risk areas in the country or region (from previous prevalence, ecological, and dietary information) and to understand what current programs are on-going (especially iodization of salt). When looking specifically at the data set you will analyze, be sure to identify if the data has included a test for iodization of salt (usually at the household level).
The following list provides some of the data sources for Iodine deficiency (and comments on their applicability):
Data Sources for Assessing IDD
Data Source Comment on Usefulness
Food Balance Sheet Not available
Food consumption/ Food Frequency Survey (FFQ) Not very important; estimate goitrogens, especially cassava
Clinical Signs Preliminary assessment
Prevalence Survey
Goitre existence from casual reports useful first step
Goitre classifications and rates essential (often from schools)
Biochemical test Casual urine samples for iodine concentration
Clinic Records Goitre reports if available
Schools Survey point for goitre surveys
Control Programs Salt iodization: quality control and surveillance
Source: International Conference on Nutrition: Major Issues for Nutrition Strategies, WHO and FAO, 1992.
The MN PANDA will now proceed to teaching methods in handling micronutrient data and interpreting the data effectively for use in program development. The next step is to begin using sample data sets provided with the MN PANDA that include IDD indicators. MN PANDA will provide a data set with process indicators only (such as household use of iodized salt) as well as a data set with process and outcome indicators (such as goitre and urinary iodine). The many exercises that follow will allow for familiarity and skill building in analyzing surveys with micronutrient data.
The first step will be to define the deficiencies and the indicators used to measure them in Section 1: Causes, Manifestations, and Indicators. Use the link at the top to proceed to Section 1.