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Food and nutrition policy
Political and analytical barriers to solving
Proposal for a data base on food and nutrition
Political and analytical barriers to solving food problems
The article "National Agricultural Policies and World Hunger" by M. Urrutia [Food and Nutrition Bulletin, 6 (1 ): 1 ] raises some important points concerning the inability of some parts of the developing world to come to grips with their food problems. The points he raises are worth further elaboration and support. In attempting to do so, I will draw on the work being done by the Centre for World Food Studies in the Netherlands in close collaboration with the International Institute for Applied Systems Analysis (IIASA) in Austria. This work involves a major effort at modeling the relevant variables concerning food.
There is, no doubt, a lack of political will to tackle the issues adequately in many countries where people suffer from inadequate nutrition, and this lack of will is not limited to hesitations to undertake land reforms. By now there is fairly general agreement that a lack of food is closely linked to a lack of purchasing power to obtain food. The food problem, therefore, is a facet of the poverty problem, and it is unlikely that the food problem can be really solved without major inroads being made towards the eradication of poverty. Land reform may be helpful to this end, at least in some countries, but it is doubtful whether it is a sufficient means in countries where land is scarce and land reform benefits would only be marginal for the poor.
Still, the point made with regard to a perceived lack of political will regarding land reform is a valid one: it extends, however, to a much broader array of policies. In fact, as numerous authors have shown convincingly,* there is a significant preference for policies that benefit the formal urban sectors over informal urban groups, and more broadly for policies that benefit urban rather than rural populations. To benefit all of the poor, poverty eradication would need to pervade all government policies, irrespective of whether they concern prices, taxes, education, health, credit, transport, or investment allocations. These policies tend to have, however, the opposite effect in practice, worsening the relative position of the poor and sometimes even their absolute poverty. The rising tide of migration to the cities is a clear result of policies that fail to deal effectively with rural poverty.
In a number of instances governments that do face an aggravating food and poverty problem can defend themselves by saying that their policies could not be tested in advance in terms of their effects on the lower income groups. In most cases this is true: the analytical tools for dealing with the effects of economic policies on income distribution are weak or even non-existent. Progress is being made, but it is a slow process that requires a thorough rethinking of economic causalities and the development of new analytical techniques. Both are, by their nature, gradual processes with lots of trial-and-error stages where one needs to go back to the drawing board.
Many governments in developing countries are genuinely interested in policy analysis that, in due course, will enable them to address poverty issues as part of their general policy approach and as one target for their scarce resources. At present, the lack of an analytical basis for poverty-oriented policies and, therefore, the uncertainty about the effects of these policies on the poor are by themselves reasons to do the more certain thing of spending resources in urban areas. What is seen as a lack of political will may, therefore, to some extent be a lack of better insights into what can be done - or what not to do - to alleviate hunger and poverty. The perception that the costs may be excessive and the benefits too small cannot easily be dismissed or countered by sound analysis.
The type of study that needs to be undertaken for these purposes is complex, cumbersome, and time-consuming. In the climate in which most policies are made there is little or no patience with these approaches as decisions are continuously made under the pressure of prevailing circumstances. Analysis is welcome if it can be used right now, rather than in two or three years' time. Even the effort to put together a coherent set of data that show the sources of income and spending patterns for each relevant socio-economic group is already a major exercise. Such studies must draw on a multitude of statistical sources, surveys, and specialized studies to even approach an accurate portrayal. The models developed from data of that kind, which should preferably be based on general equilibrium approaches as Urrutia suggests, require another major effort.
It is clear that exercises of this kind cannot be looked at as useful for only one specified time period and then discarded - for example, a five-year plan, a temporary food strategy, or the equivalent. The models and their data base need to be seen as a real investment, to be maintained and improved over time, and to serve a broad range of purposes, all of which support the process of policy-making with continuous, sound analysis. This view represents a new stage in the evolution of analytical support to policies and deserves to be recognized as such, as it promises to benefit the quality of the policy-making process considerably.
The collaboration of the IIASA and the Centre for World Food Studies tries to help in establishing suitable analytical tools at the country level. With a general equilibrium approach to country modelling, supported by an evolving set of mathematical and programming tools, the two institutions have jointly been able to inspire a sizeable number of national research institutes to engage in this venture. The experience in a number of countries has been positive, and has initiated a learning process that has improved the quality and relevance of the analytical tools.
Making investments in refined analytical tools is a costly and time-consuming process that asks more patience than policy-makers can afford. As a consequence, efforts to co-operate at the country level are not in all cases successful: sometimes interest fades away when it is understood how much effort is required, and sometimes projects are abandoned halfway because funds have been depleted. Still, since the start of the operation, models for 23 countries have been completed and are to various degrees being used. Some are not as yet sufficiently developed to be applied fully, but several have reached this stage.
Another interesting property of current models is that the individual country models are designed for international linkage. As several models for the industrial countries, particularly European countries, the United States, and Canada, are now available, it is possible to apply the system that Urrutia suggests elsewhere in his article, i.e., the tracing of the effects that food policies (or, more generally, agricultural policies) of the industrial countries have on world markets and prices. This topic is important as there is much controversy on the point. The use of the system of models will be able to shed more light on the alleged negative impact of agricultural protection in the industrial countries on trade and growth in the developing countries and will add considerably to the insights into these issues that have been raised for many years by a number of international organizations and by the FAO in particular.
Efforts like these take a very long time to mature. It has taken almost ten years of considerable world-wide effort to get to the point where results at the country and international levels are being brought into the open. Scenarios based on the international, linked system will for the first time be presented at a series of conferences to be organized by the IIASA in the course of 1985. It is hoped that this conference will stimulate enough new enthusiasm that countries not yet associated with the network will join in and strengthen the system further, making it a tool for improving quality and value over time. Many similar ventures of this kind have fallen by the wayside before they matured; this one, which is focused on an issue of global concern, has been able to mature, although there were times during its development when the total effort was brought close to the point of faltering. What is needed now is a close scrutiny of the value of what has been achieved by all concerned with the issue of food policies. Assuming the efforts will be found to have been worthwhile, a joint effort will be needed to keep alive what has been put together and to improve upon its quality. In that context those who have been associated with the programme for all these years would like to look to the United Nations University for support in mobilizing research, particularly in developing countries, to extend the system and to improve food policies through better analytical support.
Proposal for a data base on food and nutrition
PAHO/WHO Consultation Group on Nutritional Surveillance
A group of professionals from various disciplines in the basic and nutrition sciences served as a consultation, group for determining the responsibilities of the Pan American Health Organization and the World Health Organization in regard to food and nutrition surveillance. The meeting was organized by the Institute of Nutrition of Central America and Panama (INCAP) and held in Guatemala City on 5-6 April 1984.
While developed for the Western Hemisphere, the list of data in the following table, reprinted from the report of the meeting, represents the technical information that is desirable for the analyses required in any region. Such data are reasonably accessible in interested countries and from other sources of information such as the United Nations and its agencies.
This data base can be used to interpret the food and nutrition situation and its trends in relation to geographic, demographic, and socio-economic conditions in any country. It can contribute to the monitoring and evaluation of the Health-for-AII strategies and plans of action to improve the food and nutrition status of the countries of a region.
The data base can also provide current data on tendencies and changes in the social, economic, and health conditions that affect food and nutrition in countries and can serve as a basis for planning, executing, and evaluating regional and national policies and programmes in this field.
It can also help to strengthen the coordination of intersectoral measures and to rationalize the efforts and resources of external co-operation in support of the food and nutrition strategies and programmes of individual countries.
These data should be complemented by other data generally
available to WHO and its regional offices that bear closely on
food and nutrition problems and actions in the countries, such as
(a) births and deaths,
(b) population dynamics,
(c) health-related social and economic factors,
(d) health-service systems, and
(e) nutrition interventions.
Information Required for the PAHO/WHO Regional Food and Nutrition Programme
|Type of Information||Data||Indicators||Use||Level of Aggregation||Sources of Information||PAHO Data Base|
|1. HEALTH STATUS|
|1. Infant mortality:||Deaths of infants under 1 year and number of live births||Infant morta- lity rate||As indicators of
health and socio- economic conditions.
Sensitive to availability, use and effectiveness of health services
|National||Every 2 years||UN Popula- tion Divi- sion, CELADE/ ECLA country||Notification||In common use under Office of Health Statistics (PHS)|
|Perinatal||Regional (political- administrative, geographic, or health subdivi sion)|
|2. Child mortality||Deaths and population of respective age groups||Mortality rates||As complement to information for surveillance and evaluation of nutritional status of the population||Urban|
|From 12 to 23 months||Rural|
|From 1 to 4 years||Mother's schooling|
|Under 5 years|
|Proportion of under 5 years|
|3. Mortality by causes:||Deaths by causes and population||Cause-specific mortality rates|
|Diarrhoeas (004, 006-009)|
|Acute respiratory diseases (466, 480-486-487)|
|Hypertensive diseases and ischaemic heart disease (400-404 and 410-414)|
|Others: obesity, cerebrovascular accidents|
|B. NUTRITIONAL MORBIDITY||To shed light on the nutritional situation in a country or a group of coun- tries including inter-country variables, depending on degree of data breakdown.|
|Affords identifica- tion of population groups at risk, geographic areas with special problems, and surveillance of changes and tendencies in consequence of policies and pro- grammes.|
|1. Energy-protein malnutrition|
|Maternal||Birthweight in grams||Percentage of infants under 2,500 g malnutrition||For indirect quantification of magnitude of maternal||National Regional (political- administrative subdivision) Urban||Every 2 years||Ministry of Health Social security (Hospitals)||Surveys||HPN Social security (Hospitals)|
|Preschool chil- dren (under 6 years)||Age (months)
Sex: male and female
|Weight/age||For estimating prevalence of infant malnutrition||Every 2 years||Ministry of Health (Health centres and posts, hospitals)||Regular reports, survey||HPN|
|(Gomez classification): percentage of children with less than 75% of WHO reference standards|
|Weight/ height malnutrition: percentage of children with < 2 SD of WHO reference standards||For estimating prevalence of current infant malnutrition and evaluating effects of food aid programmes||National Regional (political administrative subdivision) Urban Rural|
|Height/age malnutrition: percentage of children with < 2 SD of WHO reference standards||For estimating pre valence of chronic infant malnutrition and evaluating effects of medium term social deve lopment pro grammes|
|School children||Age (years and months)||Weight/ height malnutrition: percentage of children with < 2 SD of WHO reference standards||For estimating prevalence of current malnutrition of schoolchildren||National Regional (political- administrative subdivision) Urban Rural||Every 2 years||Ministry of Education||Weight and height censuses of school children on entry into first grade||HPN|
72< 96 mos
|96-< 120 mos||Weight (kg and fractions in g)|
|Height/age malnutrition: percentage of children with < 2 SD of WHO reference standards|
|Sex: male and female
For estimating pre valence of chronic malnutrition in schoolchildren and summing up magnitude of nutritional damage to a community in last 5-1 0 years
|2. Anaemias||Serum haemo- globin levels||For estimating prevalence of anaemias in expectant mothers and preschool children||National Regional (political- administrative subdivision) Urban Rural||Every 4 years||Ministry of Health studies||Surveys Special||HPN|
|Expectant mothers||Haemoglobin (g/100 ml)||Percentage of expectant mothers with haemo globin levels < 11g/ 100 ml|
|Preschool chil- dren (under 6 years) by sex with||Haemoglobin (g/100ml)||Percentage of preschool children haemoglobin levels <11 g/ 100ml|
|3 Endemic goitre School children (6-14 years)||Degree of hypertrophy of thyroid gland as measured by WHO classification gland||Percentage of children with grade I, II, and III hyper- trophy of thyroid||For estimating prevalence of goitre in children and evaluating effect of salt ionization programmes and other prophylactic measures||National Regional (political- administrative subdivision) Urban Rural||Every 2 years||Ministry of Health Ministry of Education||Surveys in primary schools||HPN|
|4. Vitamin-A deficiency Children under 15 years||Serum retino levels (µg/ 100ml)||Percentage of children under 15 with serum retinol levels of 10 µg or lower||For estimating prevalence of vitamin-A deficiency in the population and evaluating effect of vitamin-A fortification programmes||National Regional (political- administrative subdivision)||Every 4 years||Ministry of Health||Surveys of population under 15||HPN|
|1. Breast-feeding||Breast-feed- ing practices for latest child||Percentage of children with breast- feeding of latest child to: 1 st month of age 3rd month of age 6th month of age||For estimating duration and frequency of breast-feeding at different ages of the child||National Urban Rural||Every 4 years||Ministry of Health||Surveys of mothers with child under 1 year old||HPN|
|2. Availability of foods||Energy (kcal) available per capita per day||Percentage of adequacy to energy re- quirements for average adult||For estimating apparent food consumption and monitoring tendencies||National||Every 2 years||Planning Office National Statistics Bureau Nutrition institute||Food balance sheets||HPN|
|Protein (g) available per capita per day||Percentage of adequacy to recom- mended protein and fats for average adult||For estimating apparent food consumption and monitoring tendencies|
|Fat (g ) available per capita per day|
|Availability of foods (Mt)||Deficit of staple foods||For guidance to policy on national food production||National||Every 2 years||Planning Office National Statistics Bureau Nutrition institute||Food balance sheets|
|3. Food consumption||Real consumption of 10- 15 basic foods, depending on country, per capita per day||For evaluating nutritional status of population re- garding food intake||National Regional (political- administrative subdivision or ecological or socio- economic areas) Urban Rural||Every 4 years||National Statistics Bureau Nutrition institute||Food survey or module incorporated in house hold and similar surveys||HPN|
|For determining food patterns in specific groups and monitoring changes and tendencies|
|Energy intake (kcal) per capita per day||Percentage of adequate energy intake|
|Protein intake (g) per capita per day||Percentage of adequate protein intake|
|Price of staple foods relative to:||Percentage of increase or decrease of basic food prices||For monitoring food price tendencies||National Regional (political- administrative subdivision or ecological, socio- economic and special areas)||Annual||Planning Office National Statistics Bureau Ministry of Agriculture||Surveys of income and expendi tures Reports|
|Income level||Percentage of family income required to pay for staple food basket||For directly evaluating food con- sumption and family purchasing power|
wage and structure of family ex- penditures
4. Food aid to vulnerable population groups
|Percentage of family ex- penditures going for staple food basket||For estimating per centage of families able to obtain minimum adequate diet|
|Numbers of beneficiaries by categories (mothers and children)||Population served as percentage of targeted groups||For determining volume of national programmes, eveluating their ef- ficiency, and eventually computing a cost- benefit ratio for them||National Regional Urban Rural||Annual||Ministry of Health Ministry of Education||Reports||HPN|
|Quantities and types of foods distributed (Mt) Cost of programmes: local and external cooperation (US$)||Percentage fulfillment of food dis- tribution targets|
|5. Food fortification|
|Salt iodization||Quantity (Mt) of iodized salt produced and distribused per year||Iodized salt as percentage of salt production and imports||For evaluating endemic goitre-control programmes||National Regional||Annual||Ministry of Health Salt industry||Reports||HPN|
|Vitamin-A fortification of sugar and other foods||Quantity (Mt) of sugar and other foods fortifled with vitamin A per year||Percentage of sugar forti- fied with vitamin A||To evaluate programmes for prevention of vitamin-A deficiency||National||Annual||Ministry of Health Industry||Reports||HPN|
|Salt fortified with fluorine||Quantity (Mt) of salt fortified with fluorine per year||Percentage of salt fortifled with fluorine||To evaluate dental caries prevention programmes||National||Annual||Ministry of Health Industry||Reports|
|III. HEALTH SERVICES|
|1. Use of
|Number of persons served and of deliveries per year||Percentage of care in each group||As indicator of coverage of health services: proportion of population using health services (in hospitals and centres or of health promoters or auxiliaries)||National Regional (political- administrative subdivision)||Every 2 years||Ministry of Health||Reports||In common use under HSC/PHS|
|Children under 5 years|
|2. Health manpower for food and nutrition programmes|
|Medical nutri- tionists||Numbers of profes- sionals available in the different categories||Ratio per 10,000 inhabitants||As indirect indicator of criteria for allocation of resources and funds when analysed for for geographic distribution (equity)||National Regional (political- administrative subdivision)||Every 2 years||Ministry of Health studies||Reports or special||In common use under PHS|
|IV. ENVIRON MENTAL HEALTH|
|1. Drinking water||Proportion of inhabitants with drinking water in home or easy access to acceptable source||To determine coverage of drinking water and sewerage services||National Rural Urban||Every 2 years||Ministry of Health||Reports of special studies||HPN|
|2. Excreta disposal||Proportion of inhabitants with sanitary excreta- disposal facilities|
|By age and sex:||Demographic
factors (changes in population and its structure) are
useful to complement evaluation of the nutrition
Also useful as denominators for calculation of indicators
Regional (political- administrative subdivision)
As to population in localities of different sizes
|Every 2 years||Ministry of Health National Statistics Bureau||Population censuses, demographic projections, and special studies||In common use under PHS|
|VI. SOCIAL AND ECONOMIC FACTORS|
|Literacy (older than 15 years)||Percentage of literacy and schooling among women||Important for inter- pretation of specific nutrition and health indicators||National Regional (political- administrative subdivision)||Every 2 years||Ministry of Education United Nations||Population censuses, periodic reports, and special studies||In common use under PHS|
|Per capita gross
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