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Nutrition security

Optimal consumer subsidies and income transfers for minimum nutritional requirements: A basic model
Malnutrition in rural highland Ecuador: The importance of intrahousehold food distribution, diet composition, and nutrient requirements
Multidisciplinary capacity-strengthening for food security and nutrition policy analysis: Lessons from Malawi

Optimal consumer subsidies and income transfers for minimum nutritional requirements: A basic model

Abstract
Introduction
Income transfers
Subsidies
Subsidies combined with income transfers
Summary and conclusions
References
Annex

Dov Chernichovsky, Uri Spiegel, Uri Ben Zion, and Mark Gradstein

Dov Chernichovsky is affiliated with the Department of Health Policy and Management and the Program for Health Policy in Economies Under Stress at the Ben-Gurion University of the Negev in Beer-Sheva, Israel. Uri Spiegel is with the Interdisciplinary Department of Social Sciences at Bar-Ilan University, Israel, and the Department of Economics at the University of Pennsylvania in Philadelphia, Pennsylvania, USA. Uri Ben Zion is affiliated with the Faculty of Industrial Engineering and Management in Technion, Haifa, Israel. Mark Gradstein is with the Department of Economics at the Ben-Gurion University of the Negev.

Abstract

The supply of food is no longer a major determinant of malnutrition in the developing world. Rather, a lack of purchasing power, ignorance about nutrition, and subjective tastes or preferences prevent some households and individuals from securing adequate diets. Some households spend more on food and other consumer items than would be needed for a minimum balanced diet. Yet they remain malnourished or have nutritionally undesirable diets. Food subsidies and income transfers have been major policy options available to governments to augment household purchasing power and change consumer preferences in order to alleviate malnutrition. Those options have traditionally addressed the problem by considering one critical nutrient and one common staple. The model discussed here provides and demonstrates a solution to the question: What is the combined optimal income-transfer and subsidy programme that would meet particular nutritional requirements with the least budget expense to the government? It is argued and shown, with the aid of an initial model, that a combination of income transfers and food subsidies that consider a range of foods, rather than a single staple, and a range of nutrients, rather than a particular nutrient, may lead to cost-beneficial policies that meet wider nutritional objectives for less cost.

Introduction

The supply of food is not a major determinant of malnutrition in the developing world. Rather, it is a lack of purchasing power of some households (and nations) that prevents them from securing adequate diets. This is one of the most important conclusions of the recent World Food Summit [1]. This view has been held for more than two decades [2].

In the classical articulation of the diet problem, Stigler [3] concluded that malnutrition is more than a problem of insufficient income to purchase enough food. Indeed, many households, especially in developing economies, probably spend more on food and other consumer items than would be needed for the minimum required diet. Yet many of them remain malnourished, in part because of ignorance about nutrition and in part because of subjective tastes or preferences that may lead to nutritionally undesirable diets.

Consequently, “ignorance” and “tastes” must be considered explicitly in food policies and programmes that in most instances attempt to modify human behaviour by changing incomes and relative prices in the short term, while relevant health education takes root [4].

Price subsidies and income transfers have been major policy options available to governments to augment household purchasing power and alleviate malnutrition [5]. Both income transfers and subsidies, largely confined to a market economy, are, however, innately problematic in that some “leakage,” i.e., support to some “wrong” people and for some “wrong” commodities, is inevitable. In spite of these shortcomings, income transfers and subsidies have major attractions. Compared with the alternatives (e.g., feeding programmes), subsidies and transfers are most effective [2]. They also rely on market rather than on administrative mechanisms. This makes them appealing in developing economies where the share of the market economy is growing but administrations may still be weak.

Through presentation of a basic model, we seek to outline the key parameters involved in the answer to the question: What is the optimal combined price subsidy and income-transfer programme that would meet particular nutritional requirements with the least budget expense? This issue of optimizing and minimizing the total amount of income transfers and subsidies has become especially significant as governments try to reduce their budgets as part of economic structural adjustment efforts.

To start answering the question, we follow earlier work by Reutlinger and Selowsky [2]. Similar to that work, we focus on “market-wide” subsidies and “target-group-oriented” income transfers. We deal also with the same parameters: income and price elasticities to capture consumer behaviour, and income distribution to capture the policy environment. The model also follows empirical research looking into the determinants of household food consumption and nutrition [6]. We depart from the work of Reutlinger and Selowsky and from common policy programmes in several ways. First, we attempt to deal with optimal combinations, from a fiscal perspective, of the alternative policies rather than viewing them as mutually exclusive options. The view that pertinent policies and programmes are mutually exclusive is also evident in the concluding remarks of the review of these policies by Pinstrup-Andersen [5]. Second, we consider a vector of nutrients rather than just one or two. Third, we deal with all foods rather than just with a particular item. A “single-nutrient, single-food” approach may be outright detrimental; it may induce consumption of, say, calories at the expense of some critical vitamins that may be ignored [7].

This paper should be viewed as part of a more general effort to develop a model that would consider optimizing income transfers and subsidies from a nutritional perspective under a variety of budgetary, production, and foreign-exchange constraints [8].

Income transfers

Income transfers involve, in our case, raising household incomes to levels that secure the minimum requirements of any desired nutrient. This option must be based on knowledge of the income distribution and demand functions that indicate how households of different income levels would modify their food consumption when their income was supplemented.

When demand functions and incomes are known, it is possible to identify the level of income (I*_tj) that provides minimum consumption of nutrient A_j (where j denotes the jth nutrient) in household t. (Households may have different I*_j values if they have different demand functions. See Annex, parts 1 and 2.) Once I*_tj is established, each household with income below or at this level needs to be supplemented with transfer payments to reach the level of income that meets the minimum requirement. (The simplest way to establish I*_j would be to estimate direct income-expenditure elasticities of consumption of nutrients [e.g., ref. 6, p. 43].) When more than one nutrient is involved, the one nutrient, A_k, requiring the highest income level to meet the minimum sets the minimum income needed, I*_tk, for household t. That is, each household with the income I*_t, < I*_tk needs to be supplemented (I_t - I*_tk)- The total cost of this programme is the sum of all such supplements or transfers across households, all with different (I*_t, - I*_tk) <0.

This policy leads, however, to some “waste.” When more than one nutrient is involved, the effort to bring consumption of the “marginal component,” Ak, to the required level causes “excess” consumption of other nutrients whose minima can be met through a lower supplement or none at all. In addition, the income transfer will also lead to an increase in consumption of other goods and services unrelated to the diet. The potential “waste” associated with the income transfer occurs even when households spend the entire transfer on food.

In general, the smaller the income elasticity and the (calculated) share of expenditure on the nutrient that is deficient (at the margin), A^, the higher the marginal waste or leakage of the income transfer, because a higher income supplement is required to bring about the desired results.

The problem stated thus far can be illustrated with a simple example. Suppose we have 100 households whose income distribution is as illustrated in table 1. We further assume that the households consume three goods, X₁, X₂, and X₃, of which the first two include the nutrients A₁ and A₂, which are of policy concern. The three goods have the properties given in table 2. The minimum requirements are set at 400 units for each nutrient B₁ = 400, B₂ = 400. In this case, only the upper-income group meets all nutritional requirements before intervention. The intermediate group is deficient in A₂ but not in A₁. The poor do not meet any of the requirements; they are at 50% of the minimum requirement for A₁ and 12.5% for A₂.

TABLE 1. Income distribution

No. of households	Income (US$)
25	120
55	900
20	1,800

TABLE 2. Properties of goods and nutrients

Good Xi	Nature	Price Pi (US$)	Share in expenditure µi,	Contents in nutrients
				t1	t2
X1	Food	3	0.5	10	1
X2	Food	2	0.1	1	5
X3,	Non-food	1	0.4	0	0

TABLE 3. Consumption and nutrition levels

Income group	Income(US$)	Consumption of			Diet
		X1	X2	X3	A1	A2
1	120	20	6	48	206	50
2	900	150	45	360	1,545	315
3	1,800	300	90	720	3,090	750

TABLE 4. Consumption and “waste” levels

Income group	Level of transfer	Consumption of					“Waste” in terms of
		X1	X2	X3	A1	A2	X3	A1	A2
1	840	160	48	384	1,648	400	336	1,248	0
2	60	160	48	384	1,648	400	24	103	0
3	0	300	90	720	3,090	750	0	0	0

Given these data and the specific demand function given in the Annex, part 1, the consumption and diet levels are established as given in table 3. Based on the derived “demand function” for each nutrient, it is possible to establish that for the poor to achieve the minimum requirements of the two nutrients, the following incomes are required:

I*₁ = US$ 233
I*₂ = US$ 960,

The “waste” associated with this policy programme is illustrated in table 4. Groups 1 and 2 increase their consumption of X₃, which has no nutritional value, and of nutrient A₁ above the level that the government is interested in achieving.

Subsidies

Rather than supporting households directly through their incomes, the government can support households indirectly through subsidized food items. (In the more general case, indirect taxes, i.e., negative subsidies, may be considered to discourage nutrition-ally detrimental consumption.) The fundamental advantage of subsidies vis-à-vis income transfers is that the former might secure better household spending of the extra resources on the foods nutritionally most desirable.

It should be noted that the model does not deal with the so-called Pareto optimum. It may be easily argued, however, that subsidies to a range of commodities are likely to be less distortive than a subsidy to one particular commodity. The model also assumes, at this stage, infinite supply elasticities; that is, all food quantities can be purchased at going (international) prices.

TABLE 5. Consumption levels by income groups after subsidy

Income group	Income(US$)	Consumption of			Consumption of
		X1	X2	X3	A1	A2
1	120	32	74	48	400	403
2	900	245	563	360	3,006	3,060
3	1,800	489	2,560	750	7,450	13,289

The government, it is assumed in this model, cannot discriminate among consumers or limit the subsidy to any particular group. [“Food stamps” are a form of subsidy to specific income groups. In the case of food stamps, our discussion would refer only to the (sub-) population that is entitled to the stamps, and would consider an optimal combined (income transfer and subsidy) policy confined to this population.] Any product X_i, the price of which is P_i, may be subsidized at the level C_i so that the effective price of X_i, to the consumer is (P_i - C_i). The total subsidy S to a household is the sum of all subsidized items purchased by the household times the value of the subsidy on each item. The total food subsidy for the economy is the sum of all subsidies across households. (For a formal presentation of the arguments, see the Annex, part 3.)

The government seeks, in this case, to minimize the total budgetary outlay on the subsidy by trying to support only households with incomes below that which meets nutritional requirements. If the highest income group in need of support is identifiable, it can be argued that only this and lower groups should be subsidized through food stamps, rather than subsidizing the entire population. The costs of a food stamp programme, as compared with an economy-wide subsidy, involve the cost of administration and the possibility that stamps will be traded. These costs need to be contrasted with the “waste” discussed in this paper. Clearly, the lower the income level of that lowest group, the higher the subsidy required to meet particular nutritional requirements.

In general, the critical parameters that influence this solution are the size of the target population in comparison with the entire population that will also benefit from the subsidy, and the price and income elasticities that determine how much of the subsidy will go to improving the diet and how much to other consumption. (For a formal discussion, see the Annex, part 3.)

Following the specific example outlined above, which is based on specific demand functions and income distribution, we can calculate the optimal subsidies on goods X₁ and X₂ by finding the subsidies (C₁ and C₂, respectively) for the lowest income groups in need. It can be shown (see the Annex, part 3) that with an income of US$ 120, the minimum requirements can be met with subsidies C₁ = 1.16 and C₂ = 1.84.

TABLE 6. Levels of subsidies by income groups

Income group	Subsidy per household (US$)	No. of households	Total subsidy(US$)
1	174	25	4,350
2	1.319	55	72,545
3	5,337	20	106,740
Totals		100	183,635

The overall consumption patterns subsequent to the subsidy are as shown in table 5, and the subsidy cost per household and across income groups is shown in table 6. It is clear from this particular example that the subsidy, requiring a budget of US$ 183,635, is a more expensive policy than the income transfer, requiring a budget of US$ 24,300, because of the levels of consumption of X₂ by households of high and intermediate incomes, and the relative sizes of these groups in the population. It is noteworthy that the main share of the subsidy in this particular case goes to the highest income group. It is findings of this nature that lend support to food stamps.

Subsidies combined with income transfers

As suggested earlier, a combination of subsidies and income transfers might yield a more efficient policy programme than either policy alone. This option is discussed and illustrated here.

Suppose that I_M is the income needed to secure minimum requirements for all households under the income-transfer policy as stated above. This income (according to our example) is a superior “opening position” to the subsidies option, which is, in our case, more costly. (The case in which subsidies are superior to income transfer as an opening position does not alter the nature of the proposed solution.) This position is used for commencing an iterative, computational trial-and-error process whereby the income transfer is reduced by marginal amounts and is substituted by subsidies that retain the same minimum requirements as under the opening position.

FIG. 1. Income transfers and subsidy combinations

The nature of the proposed solution is illustrated in figure 1. Points bb and cc on the vertical and horizontal axes indicate, respectively, the transfers needed to secure the minimum requirement either through income transfers or subsidies, as outlined earlier. The line bbcc is an “iso-requirements line” or a transformation line between subsidies and income transfers that shows the combination of income transfers and subsidies that retains particular levels of nutritional requirements. The 45° line represents an iso-cost or budget line on which government outlays remain the same regardless of the policy, whether subsidy or transfers. For a slope greater than 45° on the bbcc curve, it clearly pays to reduce the transfer and increase the subsidy, as total government outlays will decrease. For example, if the segment oq is smaller than o’q as we move from bb in the direction of cc, it pays to reduce income transfers and increase subsidies; the government will save o’q’ without sacrificing nutritional requirements. The optimal solution is reached at the tangency point o where the 45° line is tangent to the iso-requirement line; at this point there is no advantage in moving towards one policy at the expense of the other.

In practice, the optimal solutions can be obtained stepwise. For each income transfer, a vector of optimal subsidies is obtained by solving a non-linear programming problem, as suggested earlier. We then calculate the total amount of government support and find the minimum budget that maintains nutritional requirements.

TABLE 7. Income and subsidy alternatives and combinations (US$)

Minimum income	Total transfer	Total subsidy	Total government expenditure
120.00	0.00	127,512.24	127,512.24
170.00	1,250.00	75,441.72	76,691.72
220.00	2,500.00	46,698.70	49,198.70
270.00	3,750.00	39,291.67	43,041.67
320.00	5,000.00	31,166.67	36,166.67
370.00	6,250.00	25,181.31	31,431.31
420.00	7,500.00	20,571.43	28,071.43
470.00	8,750.00	16,898.05	25,648.05
520.00	10,000.00	13,891.03	23,891.03
570.00	11,250.00	11,375.00	22,625.00
620.00	12,500.00	9,231.18	21,731.18
670.00	13,750.00	7,376.24	21,126.24
720.00	15,000.00	5,750.00	20,750.00
770.00	16,520.00	4,307.90	20,557.90
820.00a	17,500.00	3,016.26	20,516.26
870.00	19,750.00	1,849.14	21,599.14
920.00	21,100.00	794.20	21,894.20
960.00	24,300.00	0.00	24,300.00

^a Boldface indicates minimum budget that secures minimum nutritional requirements.

Summary and conclusions

Both income transfers and subsidies, largely confined to a market economy, are innately problematic in that some “leakage,” i.e., support to some “wrong” people and for some “wrong” commodities, is inevitable. Income transfers are relatively efficient when it is easy to identify the needy groups and the income elasticities for food for these groups are high.

Food subsidies, on the other hand, are intended to induce consumption of those items the government is interested in supporting. In this particular regard, they have an advantage over income transfers, because they are targeted to products rather than to consumers, especially when the poor are not easily identifiable. Compared with income transfers, subsidies have, however, several shortcomings. First, since a subsidy is given to the population at large, high-income households are subsidized. This problem is particularly serious when the subsidized items have high income elasticities and consequently high-income groups may benefit substantially from the subsidy. Second, subsidies carry an income effect; the household can transfer part or all of the subsidy to consumption of other non-subsidized commodities. This problem would be relatively serious if households had low price elasticities for the subsidized goods. In that case, the quantitative response to the subsidy would be relatively small, and a larger part of the subsidy would be shifted to other consumption.

Generally, in a low-income environment where, on average, the share of expenditures on food is relatively large, food subsidies can be efficient mechanisms for targeting income transfers from a general income distribution perspective. This follows because of the low price elasticities and high income elasticities for foods in such an environment. Clearly, different price and income elasticities of different food items call for programmes that emphasize the foods with the desired elasticities and critical nutrients. As income levels rise, policies that emphasize a range of foods and micronutrients in addition to calories, for example, come into play. Such policies depend even more on models such as the one presented here.

There is no clear advantage to one policy over the other. We conclude, therefore, that it may be desirable to consider a policy that combines income transfers and subsidies, taking into account income and price elasticities for a range of foods, as well as income distribution. Such a policy could achieve minimum nutritional requirements at a lower budget cost than a policy based on either subsidies or income transfers alone.

As there are numerous combinations of income transfers and subsidies on food that can achieve desired nutritional levels, it is important to find the optimal mix also from fiscal, foreign exchange, and production perspectives that have not been considered in this discussion. These considerations should be included in an extended model. Furthermore, the basic model advanced in this paper should be applied to country data sets, and operational policy norms should be followed.

This model keeps a fairly narrow, albeit critical, nutritional perspective. At the same time, with this model it is possible to assess the effect of alternative programmes on income distribution in general, depending on the specific objectives of those programmes.

References

1. Anonymous. Will the world starve? London: The Economist, November 16, 1996.

2. Reutlinger S, Selowsky M. Malnutrition and poverty: magnitude and policy options. World Bank Occasional Papers No. 23. Baltimore, Md, USA, and London: Johns Hopkins University Press, 1976.

3. Stigler JG. The cost of subsistence. J Farm Econ 1945;27:303-14.

4. Chernichovsky D, Zangwill L. Microeconomic theory of the household and nutrition programmes. Food Nutr Bull 1990;12(1):34-52.

5. Pinstrup-Andersen P. Assuring food security and adequate nutrition for the poor during periods of economic crisis and macroeconomic adjustment: policy options and experience with food subsidies and transfer programmes. Washington, DC: International Food Policy Research Institute, 1986.

6. Chernichovsky D, Meesook AO. Patterns of food and nutrition consumption in Indonesia. World Bank Working Papers Series No. 670. Washington, DC: World Bank, 1984.

7. Williamson-Gray C. Food consumption parameters for Brazil and their application to food policy. Research Report No. 32. Washington, DC: International Food Policy Research Institute, 1982.

8. Grant SM. Food subsidies in Egypt: their impact on foreign exchange and trade. Washington, DC: International Food Policy Research Institute, 1983.

9. Lancaster KJ. A new approach to consumer theory. J Pol Econ 1966;74:132-57.

Annex

Part 1. General
Part 2. Income transfers
Part 3. Subsidies
Part 4. A combined strategy

Part 1. General

The intake of nutrient j can be expressed as a linear function of the consumption of n food items X_i,:

(1)

where t_ij is the amount of nutrient A_i, in food item X_i,. It is possible to substitute for each nutrient A_j and get m inequalities for m nutrients:

(2)

where B_j is the minimum requirement of nutrient j.

If the demand function for each X_i, as suggested by Lancaster [9], is

X_i=x_i (I_j,P₁,...,P_n+1), (3)

where X_n+1 is a composite good of all non-food items, then the demand function for each nutrient
A_j is

(4)

For simplicity and the specific illustration (in the text), it is assumed that all households share the same “Cobb-Douglas”-type utility function:

X_i =µ_i (I/P_i), (5)

where X_i is the level of consumption of X_i for the price P_i, and µ_i, is the share of total household expenditure on food X_i. This function implies that all demand functions have unitary price and income elasticities and that all cross-elasticities are zero. As implied by this function and in general, the household can be influenced to change its consumption levels of X_i by changing either income I or price P_i, or both. Accordingly, the “demand function” for each nutrient A_j is

(6)

Part 2. Income transfers

According to equation (4) in general, and equation (6) in our specific case, it is possible to identify the income level I*_j that yields A_j = B_j for each nutrient. To achieve minimum requirements across all nutrients, the highest value, I*_M, of all I*_j is needed; that is,

I*_M =Max (I*_j), (7)

so that when the household’s income is I*_M, its consumption is

A_j ³ B_j (8)

for all nutrients except A_k, for which minimum income I*_k will produce an equality in relationship (8). For most nutrients, an inequality would exist in this relationship.

Let us assume that the households’ income distribution is given by the density function F(I). That is, for each level of income î, we can find the percentage of households below this level by the integral:

(9)

and the share of population between any two levels, e.g., I₁ and I₂, by

(10)

Accordingly, total government outlays (TT) for all I £ I*_M under this policy are

(11)

where L is the number of households in the economy.

Part 3. Subsidies

The total subsidy to a household with income I that benefits from n subsidized goods is

(12)

and the total food subsidy (TS) in the economy for L households is

(13)

In this case the government seeks a vector of subsidies [C_g1... C_gn, C_gi ³ 0] that will secure the minimum requirements for the highest income group in need whose income is I₀ so that

(14)

As the total budget for the subsidies depends on the specific vector of subsidies [Cg], the solution involves seeking the vector with the lowest budget (TS₀). The minimization of function (13) subject to the set of constraints represented by (14) is a nonlinear programming problem that has a solution so that

TS₀ = Min TS([Cg]). (15)

The specific demand function for each good is

X_i = (µI_a)/(P_i - C_i) = V_iI_a (16)

where V_i = µ_i/(Pi - C_i) and I_a is the average level of income in the economy. With this demand function, which is shared by all households, the minimization problem for L households becomes

(17)

This objective function (17) is minimized subject to the minimum requirements to be met by the lowest income group with an income I₀:

(18)

In our example, the constraints for the lowest in come group with an income of US$ 120 are

120 (10V₁+V₂) = 400

120 (V₁+5V₂) = 400

These yield V₁ = .2718 and V₂. = .6122, and optimal solutions for subsidies: C₁ = 1.16 and C₂ = 1.84.

Part 4. A combined strategy

Formally, let us reduce I* by dI/* so that we get I**, i.e.,

I**=I* - dI*. (19)

I** is the “new” lowest income level in the population. The gross saving to the government in transfer payments is

(20)

* Note that From the definition of V_i, it follows that V_i,P_i, - V_i,C_i, = a_i, and from the definition of the utility function.

(21)

subject to the m constraints

The solution of the problem for nutrition levels B_j, for income group I** is an optimal vector [].

The additional subsidy needed for income group I**, and as a result for the entire population benefiting, is

(23)

The first term of this equation is the additional subsidy needed for those with income I** as a result of the reduction in transfer payment. The second term in the last equation indicates the additional “leakage” in subsidies to those people whose income is above I**. For as long as GS is larger than SS, subsidies are more efficient than transfer payments, and the process continues.

Malnutrition in rural highland Ecuador: The importance of intrahousehold food distribution, diet composition, and nutrient requirements

Abstract
Introduction
Methods
Results
Discussion
Acknowledgements
References

Peter R. Berti, William R. Leonard, and Wilma J. Berti

The authors are affiliated with the Department of Human Biology and Nutritional Sciences at the University of Guelph in Ontario, Canada.

Abstract

Our objectives were to quantify the intrahousehold distribution of food in an Andean community and to relate this distribution to dietary adequacy. Dietary information was collected using the 24-hour-recall method (n = 155 in 35 households; two or more recalls per subject). We found that food was served equitably (according to energy and protein requirements), yet the risk of inadequate intakes of four micronutrients was age-related. This was largely a function of age-based differences in micronutrient requirements per unit of energy, rather than variations in composition of the diet. A simple reallotment of food to those with higher requirements will not solve this problem, since the micronutrient density of the average diet is relatively low. Targeting of nutrient-dense foods would be difficult in this and other similar developing-world communities that are accustomed to a common pot from which foods of homogeneous composition are served. Feasible alternatives include nutrition education programmes and fortification of foods (salt, sugar, and oil) with micronutrients.

Introduction

It has been argued that throughout the developing world there is a preferential allocation of food to adult men at the expense of adult women and children. This has been observed in various countries in the developing world, but it is not a universal phenomenon. Many different food distribution patterns have been observed, including biases favouring all adults [1, 2], male adults [3-5], female adults [6], or children [7], or equitable distribution [4, 6]. The relative distribution is usually measured by energy or protein intake compared with estimated needs, although some studies examine the distribution of quality foods [6] or the pattern of serving order, the serving of second helpings, etc. [5].

There are two key reasons that knowledge of intrahousehold food distribution is important. First, for aid efforts, food distribution programmes, and research involving distribution of food supplements, workers must have an understanding of how food is distributed within households. Second, recent papers mention that malnourishment exists because of inappropriate distribution of food within households in places where the food supply is apparently sufficient [4]. It is imperative that genuine cases of insufficient food supply be recognized as such and not dismissed as cases of “inappropriate distribution.”

In this paper we will examine the intrahousehold distribution of food and its consequences for the prevalence of nutrient inadequacies in a rural highland community in Ecuador. Although the nature of the distribution is specific to this community, the interrelationships that are explored between diet composition, nutrient requirements, and food distribution are relevant to nutrition studies throughout the developing world.

Methods

Study population
Dietary methodology
Analyses

Study population

The study population was a highland Ecuadorian community of subsistence farmers, located between 3,300 and 3,600 m above sea level and 110 km south of Quito, the capital of Ecuador.

Two hundred twenty-three of the approximately 500 residents were recruited from throughout the geographic and socio-economic range of the community as part of a larger study of diet and health [8]. The dietary data were collected between January and June 1994 using the 24-hour-recall method. Data were collected from each subject for 1 to 6 days (mean, 3.1). Only two subjects refused to participate, and no subjects deliberately dropped out after recruitment. Repeat interviews were not done if the subjects could not be located (because they had temporarily left the community) or if the study period ended before an appointment could be made. Unless otherwise indicated, analyses include only those subjects for whom there were 2 or more days of dietary data and who lived in a house where there were 2 or more days of data for the male head of the household (n = 155 in 35 households).

Adult subjects were paid 2,500 sucres per interview, and adolescent subjects were paid 1,000 sucres. At the time of the study, 2,500 sucres was equivalent to approximately US$ 1.15. An adult labourer could earn between 5,000 and 10,000 sucres for one day’s work. The Human Ethics Committee of the University of Guelph approved this study.

Dietary methodology

Earlier work indicated that weighed food records would not be acceptable to most families in the community but 24-hour recalls would be acceptable and, with the modifications described below, would be reasonably accurate.

To increase the accuracy of the dietary recalls, representative samples of local foods were weighed to the nearest gram, and the volumes of all bowls and cups in which each individual’s meals were served were measured to the nearest 5 ml. In this community, family members usually eat the same food (typically soup, rice, or potatoes) from a common pot. We calculated the total volume in the pot and the proportion served to each subject. Homogeneity of contents was assumed (consistent with our extensive informal observations), unless otherwise indicated.

Each subject was questioned about the quantity of food (number of bowls or cups) consumed, but the cook was asked about the ingredients of common-pot foods. In practice, much of the interviewing proceeded as a “consensus recall,” with the husband and children helping the mother to recall the ingredients of the common pot, and all family members (especially children) helping one another to recall the amounts consumed, while two of the authors of this article prompted and recorded. If a member of the household was not present at the time of the dietary recall but had been with the family for all of the previous day, and the family knew what the missing member ate (usually the same food they ate), the family’s report of the missing member’s intake was used. All subjects were carefully probed about other foods eaten outside the home.

The first author checked the dietary data for completeness and feasibility nightly, and within six months the data were entered into a database and checked again. All days of the week were sampled, but unequally. However, there was no day-of-the-week effect on nutrient intake [8], and therefore the data were not weighted by day.

Ecuadorian [9] and occasionally Latin American [10] food composition tables were used to calculate the intakes of energy, protein, iron, vitamin A, thiamine, riboflavin, and niacin from most foods. For the few foods not listed in these tables and for zinc, vitamin B₁₂, and folate, values were obtained from Canadian food tables [11]. (Using “cross-border” food composition tables may lead to incorrect estimates of nutrient intakes [12], but if the errors in composition estimates are random, there will be little effect on estimated intake [13]. Still, extra caution needs be exercised in the assessment of the zinc, vitamin B₁₂, and folate intake.)

Analyses

The energy and protein requirements of each individual were estimated using modifications of published recommendations [14]. Energy requirements for those over 10 years of age can be estimated by the formula PAL · BMR, where PAL is the physical activity level and BMR is the basal metabolic rate, estimated with regression equations using age, sex, and weight. One year before the beginning of this study, research on energy expenditure was conducted in this community using heart-rate monitoring and activity recalls. PAL was determined to be “heavy” (2.17 in males and 1.84 in females) [15]. For the analyses in this paper, the PALs recommended by the Food and Agriculture Organization/World Health Organization/United Nations University for people doing heavy agricultural work (2.10 for males and 1.82 for females) [14] were assigned to those over 18 years of age. For those 10 to 18 years old, WHO/FAO/UNU [14] recommend PALs varying from 1.52 to 1.65 (females) and from 1.60 to 1.76 (males). However, in our experience in the community, adolescents generally take on adult-like work levels (“heavy”) by 13 to 16 years of age.

Adolescent boys work full days, caring for animals, planting, weeding, harvesting, and performing other heavy chores. Adolescent girls are similarly involved in agriculture, as well as with domestic chores, such as cooking, washing, and caring for younger siblings. The PALs used for adolescents were arbitrarily increased over the published recommendations to reflect their activity levels, so that, for example, a PAL of 1.90 (rather than 1.60) was used for males 17 and 18 years old. (Note that if these changes were not made, the results supporting our conclusions would be even stronger, i.e., Q_energy for adolescents [see below] would be higher.) Energy requirements for 0- to 10-year-olds and protein requirements for all individuals were estimated on the basis of sex, age, and body weight [14].

The ratios Q_energy and Q_protein were calculated as (intake of individual ÷ requirements)/(intake of male head of the household ÷ requirements).

The micronutrient requirements were compiled from various FAO/WHO publications [17-20]. For vitamin A and zinc, FAO/WHO provide estimates of both basal and normative requirements. The basal requirements are the levels of intake required to satisfy all demonstrable functional needs. Normative requirements are set higher than basal, providing for desirable levels of storage or “adaptive capacity.”

The prevalence of inadequacy of protein, zinc, iron, vitamin A, thiamine, niacin, riboflavin, vitamin B₁₂, and folate in seven groups (males and females 2-10 years old; males and females 10-20 years old; non-pregnant, non-lactating women 20 years or more old; pregnant or lactating women; and male heads of households) was estimated using probability analysis [16]. Although probability analysis does not allow for specific comparisons within households, it is the most reasonable way of calculating dietary adequacy at the population level and comparing dietary adequacy between groups.

All statistical analyses were done with UNIX-based SAS, version 6.09 [21].

Results

Energy and protein were distributed approximately equitably within households (figs. 1 and 2), but there was a notably higher prevalence of inadequacy of zinc, vitamin A, and vitamin B₁₂ in the youngest age group (table 1). Two possible explanations for this finding are that (1) the nutrient density of the adult diet was higher than that of children, i.e., the adults were preferentially allocated micronutrient-dense foods; or (2) other nutrient requirements in relation to energy needs are greater in children. The first of these potential explanations was tested by comparing nutrient/energy ratios between age groups. The results are presented in table 2.

The children’s diets had slightly lower densities of protein, zinc, and vitamins A and B₁₂, but the differences were slight and were not large enough to be responsible for the higher rates of inadequacy in children (as shown in figs. 3-7, discussed below). Thus, there is a puzzling situation of nearly equal distribution of food but unequal distribution of inadequate intakes, suggesting that the second explanation may be true. We therefore examined the change in nutrient requirements with age. The requirements of thiamine, riboflavin, and niacin are based on energy intake, and so an identical density is required at all ages. Thus, the prevalence of inadequacy of these nutrients should be approximately equal throughout all ages. This is indeed the case, with 0% prevalence of thiamine and niacin deficiency and approximately 70% prevalence of riboflavin deficiency (table 1). Iron intake is so high that the risk of iron dietary deficiency is uniformly less than 1% for all ages.

FIG. 1. Ratio of energy intake to energy requirement for individuals divided by the ratio of energy intake to energy requirement for the male head of the household. Mean values (Q_energy ± SD) are shown for various sex and age groups: M, male; F, female; FNPNL, female, non-pregnant, non-lactating; FPL, female, pregnant or lactating; numbers after M and F are age ranges in years

FIG. 2. Ratio of protein intake to safe level of protein intake for individuals divided by the ratio of protein intake to safe level of protein intake for the male head of the household. Mean values (Q_protein ± SD) are shown for various sex and age groups: M, male; F, female; FNPNL, female, non-pregnant, non-lactating; FPL, female, pregnant or lactating; numbers after M and F are age ranges in years

TABLE 1. Percent prevalence of nutrient deficiency in diets of different subgroups of the study community^a

Subgroup	n	Protein	Fe (PA)	Fe (B)	Zn (B)	Zn (N)	Vit A (B)	Vit A (N)	Thiamine	Riboflavin	Niacin	Vit B12	Folate
M <10 yr	26	16	0	0	15	35	15	46	0	83	0	54	5
P <10 yr	23	12	0	0	15	40	23	51	0	76	0	57	5
M 10-20 yr	19	5	0	0	2	12	0	17	0	55	0	37	4
F 10-20 yr	12	30	-	7	6	22	1	14	0	70	0	52	25
NPNL	30	8	-	7	0	2	3	26	0	73	0	24	22
PL	7	9	0	14	21	55	0	14	0	60	0	31	95
MHH	35	11	0	0	0	6	8	25	0	68	0	21	17

^a. Assuming a protein correction factor of 0.85, intermediate bioavailability of iron (10%), and intermediate bioavailability of zinc (30%). Abbreviations: B, basal; F, female; M, male; MHH, male head of household; N, normative; NPNL, non-pregnant, non-lactating women over 20 years of age (“prevent anaemia” iron levels do not exist for menstruating women); PA, prevent anaemia; PL, pregnant or lactating women over 18 years of age; Vit, vitamin.

Subgroup	n	Protein(g/kcal)	Zinc (mg/kcal)	Vitamin A (RE/kcal)	Vitamin B12 (µg/kcal)	Folate (µg/kcal)
All subjects	693	1.5±0.3	0.18 ±0.07	15 ±13	0.04 ± 0.05	4,5 ±1.9
M <10 yr	117	1.3±0.3a	0.16 ±0.06a	14 ±12a	0.03 ±0.05a	4.3 ±2.2a
F <10 yr	87	1.3±0.3	0.16 ±0.06	13 ±11	0.03 ±0.05	4.3 ±2.2
M 10-20 yr	93	1.5 ±0.3b	0.19 ±0.08b	16 ±12b	0.04 ±0.04a	4.5 ±2.2a
F 10-20 yr	63	1.4 ±0.3	0.17 ±0.05	21 ±15	0.03 ±0.03	4.1 ±1.2
M >20 yr	159	1.5±0.3b	0.19 ±0.07b	15 ±13a	0.04 ±0.04a	4.5±1.9a
F >20 yr	173	1.5±0.3	0.18 ±0.08	15 ±13	0.04 ±0.05	4.5±1.9
Age effect (p)		,0001	.0002	.0002	.06	.50

a,b. The general linear model was used to test for an age effect (sexes combined). The p-value for an age effect for each nutrient is shown. Cells with unlike superscript letters within each column are unequal (p = .05, pairwise Tukey’s LSD).

Discussion

These analyses indicate that, because of the difference in relative requirements of children, adolescents, pregnant or lactating women, and other adults, it is not sufficient to distribute food from a common pot according to energy requirements, but rather certain higher-quality foods must be preferentially allocated to individuals with higher nutritional needs. This would be difficult in this and other communities in which people are accustomed to eating from a common pot. Energy intake is correlated with (and driven by) energy requirements, but such a relationship is not likely to exist for protein or any of the micronutrients [16]. Eating to satiety, therefore, may satisfy energy requirements, but if the diet is not sufficiently nutrient-dense, it will lead to nutrient deficiencies.

FIG. 3 Dietary density of protein required to meet the safe level of intake of protein, given each individual’s energy intake. The protein density in the community diet (assuming a protein correction factor of 0.85) is shown by a solid horizontal line

FIG. 4 Dietary density of zinc required to meet the safe level of intake of zinc, given each individual’s energy intake. The zinc density in the community diet (assuming a bioavailability of 30%) is shown by a solid horizontal line

FIG. 5. Dietary density of vitamin A required to meet the safe level of intake of vitamin A, given each individual’s energy intake. The vitamin A density in the community diet is shown by a solid horizontal line

FIG. 6. Dietary density of vitamin B₁₂ required to meet the safe level of intake of vitamin B₁₂ given each individual’s energy intake. The vitamin B₁₂ density in the community diet is shown by a solid horizontal line

FIG. 7. Dietary density of folate required to meet the safe level of intake of folate, given each individual’s energy intake. The folate density in the community diet is shown by a solid horizontal line

The study community and many other Andean communities are characterized by stunted, yet otherwise apparently healthy, adults. The issues addressed in this paper may partly explain this phenomenon. The diet is apparently adequate for adults, but not for children. The inadequacy of the childhood diet, along with other environmental stressors such as water quality, hygiene, cold, and hypoxia, results in almost ubiquitous severe stunting [8]. As individuals age and mature, the nutrient density requirements drop, and as adults they are able to achieve adequate nourishment.

It is recognized that stunting most often occurs in the first few years of life [22, 23]. Although non-nutritional factors surely are important in the stunting process [24], malnourishment is often the limiting factor [25]. Targeting nutrient-dense foods available in the community to the children may cause a decrease in stunting and its associated complications. It is not known if targeting would be feasible in this community, but other work in the community suggests it might be. Stansbury [26] observed that when children were ill, their mothers gave them specific, relatively nutritious foods (toasted barley flour and toasted corn) and avoided feeding them other foods (potatoes). It may well be possible to educate the mothers in other beneficial feeding patterns.

It is unlikely that targeting alone would be sufficient to end micronutrient inadequacy in this or other similarly situated communities. Even if a household is willing to adjust and target quality foods, it may not be logistically possible to do so. Folate-rich foods need to be targeted to all adults, folate-and zinc-rich foods need to be targeted to pregnant and lactating women, and zinc-, vitamin A-, and vitamin B₁₂-rich foods need to be targeted to children.

There are three alternative strategies to targeting. One strategy, advocated by Beaton [27] and others, is to increase the nutrient density of the household diet to satisfy the individual with the highest requirements. The possibility of increasing the nutrient density of the community’s diet is explored below.

For each of the 113 foods in the community diet, the nutrient density (in grams of nutrient per unit of energy) was calculated for each nutrient for which the risk of inadequate intake was high (protein, calcium,* zinc, vitamin A, riboflavin, vitamin B₁₂, and folate). The foods that had a higher density than the arbitrary cut-off of “community mean density +1 standard deviation” and that were produced in the community were identified. The single most nutrient-dense food is turnip leaves. However, the mass of leaves that would have to be eaten to cause a substantial increase in the intake of any nutrient except vitamin A would be so high that they cannot be expected to be more than a small supplement to the diet. A 10-g serving of the leaves would supply about 20% of an adult’s daily vitamin A requirement (assuming that the provitamin A in the leaves is bioavailable) [28, 29]. The problem of consuming a sufficient quantity also applies to carrots, onions, and beets (with the exception of vitamin A from carrots). In fact, the reason that they are the most nutrient-dense foods is largely a function of their low energy content rather than their high nutrient content.

* Calcium was not included in the earlier assessment of the diet because of the lack of an adequate description of the distribution of calcium requirements [17], which is required for probability analysis. However, the dietary intake of calcium is low (the daily averages are 228 mg in children, 337 mg in adolescents, and 431 mg in adults), and therefore strategies to increase calcium intake are considered here.

A second strategy is to get the children to eat more of the foods they already eat. Although we did not collect data supporting this, our informal observations suggest that most families could feed more staple foods to their children. The low, if not inadequate, energy intake of the children (approximately 80% to 85% of estimated requirements** [8]) does not appear to be due to the limited quantity of food available, but to the high bulk and low nutrient density of the children’s diets. Zinc deficiency leads to appetite suppression, but this is likely to be only partly responsible for the low intake. Boiled potatoes were the most satiating of the 38 foods tested in a recent study [33]. They are about 3.2 times more satiating than white bread and 2.3 times more satiating than boiled white rice. (Satiation was measured both by a subjective feeling of fullness and by energy intake at a meal two hours later.)

** Recent publications, however, suggest that the WHO/ FAO/UNU 1985 recommended energy intakes for children are 15% to 30% too high [30-32].

However, increasing the total amount of food consumed does not eliminate all risk of inadequacy and may increase the risk of obesity without preventing stunting [37, 38]. If children up to 10 years of age simply increased the total amount of food consumed without changing the composition of the diet, so that their intakes met the FAO/WHO/UNU requirements [14] (note that this would put their intakes in excess of some of the newer estimates of energy requirements [30-32]), the prevalence of dietary inadequacy of protein, zinc (basal levels), and folate would fall to 0%, and the prevalence of inadequacy of vitamin A (basal) would fall to about 10%. The prevalence of inadequacy of riboflavin would be unchanged (requirements are proportional to energy intake), and the prevalence of inadequacy of vitamin Biz would remain high (42%). While still posing a health problem, mild to moderate deficiencies of vitamin A, riboflavin, and vitamin B₁₂ would probably not limit statural growth.

Because of logistical difficulties and nutritional shortcomings, neither of these first two strategies is likely to be successfully and widely implemented. A third strategy for implementation throughout Ecuador is a national food-fortification programme. An important difficulty in implementing such programmes is identifying suitable foods for micronutrient fortification. The fortified foods must be bought in stores rather than produced at home (where they could not be easily and consistently fortified), and they must be consumed by almost all people almost every day [38]. A number of candidate foods exist in this community. Vegetable lard was consumed on 98% of the surveyed days, and vegetable lard, pork lard, margarine, or corn oil was consumed on 99% of the days. Refined sugar and salt were consumed on 85% and 97% of the surveyed days, respectively. Similar results were obtained in a 1986 national survey of Ecuadorian children one to five years of age in rural and urban, coastal and highland communities. Oil or lard was consumed an average of 1.3 times per day (ranging from 1.2 on the rural coast to 1.5 in the urban highlands), and sugar was consumed an average of 1.1 times per day (ranging from 1.0 on the rural coast to 1.3 in the urban highlands) [39]. The successful implementation of a national salt iodization programme in Ecuador since the 1980s is evidence that the technical capacity and political will required for fortification programmes exist in the country.

TABLE 3. Technical possibility of fortification of foods with nutrients for which Ecuadoreans are at substantial risk of deficiency

Nutrient	Food
	Salt	Sugar	Cereal	Oil	Margarine
ß-Carotene	No	No	-a	Yes	Yes
Vitamin A	-	-	-	Yes	Yes
Riboflavin	No	No	Yes	No	No
Niacin	No	No	Yes	No	-
Folic acid	No	-	Yes	-	-
Vitamin B12	No	-	Yes	-	-
Iron	Yes	Yes	Yes	-	-
Calcium	Yes	No	Yes	-	No
Iodine	Yes”	Yes	Yes	No	No
Zinc	-	-	-	-	-

Adapted from ref. 39.

a. - indicates that possibility is not known.
b. Fortification of salt with iodine is already done in Ecuador.

In this paper dietary adequacy was considered as required density versus actual density (grams of nutrients per unit of energy, even for those nutrients whose requirements are conventionally considered as a function of body weight). The results suggest that the relative distribution of nutrient inadequacies (i.e., particular age and sex groups within a population at greater risk) might be identified given only estimates of diet composition. The ability to identify rapidly the individuals at highest risk (even if the magnitude of the risk is not known) would be a very useful tool in international development and food relief programmes. It is worthy of further study.

Acknowledgements

We thank the residents of the study community for their willing participation in this study. We thank Professor George H. Beaton for his comments on an earlier draft of this paper. Two anonymous reviewers provided very helpful comments. PRB was supported by a Natural Science and Engineering Council PGS B postgraduate scholarship, an Ontario graduate scholarship, and an International Development Research Centre of Canada Young Canadian Researchers Award. WRL was supported by grants from the Natural Science and Engineering Council (OGP-0116785) and the US National Science Foundation (SBR-9106378).

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Multidisciplinary capacity-strengthening for food security and nutrition policy analysis: Lessons from Malawi

Abstract
Introduction
A conceptual framework for choosing the focal points for capacity-strengthening in food and nutrition policy analysis
Food security and nutrition monitoring as a method of multidisciplinary capacity-strengthening
Multidisciplinary capacity-strengthening for food and nutrition policy analysis
Lessons for capacity-strengthening in food and nutrition policy analysis
Conclusions
Acknowledgements
References

Suresh Chandra Babu

Suresh Chandra Babu is a research fellow and head of the Training and Capacity Strengthening Program at the International Food Policy Research Institute in Washington, DC.

Abstract

Lack of sufficient analytical capacity in most of the developing countries in sub-Saharan Africa has been frequently suggested as a major factor in determining the appropriateness of food and nutrition policy interventions. This paper documents an approach implemented in Malawi for the past seven years to develop multidisciplinary capacity to analyse food and nutrition policies and programmes. A conceptual framework for identifying the areas of capacity-strengthening in food and nutrition planning and policy analysis is developed. Generalizable lessons from the Malawi experience are presented. Various issues that relate to enhancing the efficiency of capacity-strengthening programmes in sub-Saharan Africa are addressed. It is argued that continuous dialogue between food and nutrition researchers and policy decision makers and between the trainers in academic institutions and donor agencies is fundamental for achieving the goals of improved capacity for food and nutrition policy analysis.

Introduction

It is well recognized that food and nutrition policies that are ill-conceived and poorly designed could have negative effects and result in worsening the welfare of the population [1]. Although some policy analytical capacity exists in most developing countries, it has not been sufficient to meet the increasing demand for it in the assessment and evaluation of various policy reforms for their impact on the food and nutrition well-being of the population. The absence of adequate analytical capacity has been suggested frequently as a major factor in determining the appropriateness of food and nutrition policy interventions [2]. Considerable efforts have been made in developing and strengthening institutions and the necessary human capacity for designing and implementing food and nutrition programmes in developing countries [3]. However, the impact of such efforts in creating a sustainable core of food and nutrition policy analysts and planners has been limited.

Several factors contribute to the low level of capacity in food and nutrition policy analysis. In the past, national development plans - of which food and nutrition was a multisectoral theme - designed for five to ten years were the most important instruments through which governments made decisions on resource allocation among various sectors. To meet these planning needs, the capacity-building approaches emphasized sectoral planning, monitoring, and evaluation of development projects, including food and nutrition interventions. However, recently governments in developing countries have focused on policy reforms as a major tool of intervention in the process of economic development [4]. Although the methods of capacity-strengthening have changed accordingly, the capacity generated by such efforts remains grossly inadequate to meet the policy analysis needs of the governments [5].

The capacity-strengthening programmes currently offered in food and nutrition policy analysis focus largely on national macro price policies. Although the role of macroeconomic policies and their influence on the food and nutrition sector has been recognized as a potential area for capacity-strengthening, such approaches continue to emphasize policy-making at the national level [6]. Among the few approaches that focus on food and nutrition policy analysis, most concentrate on national policies, such as foodstock management, food trade, and food-aid policies, to achieve the goals of national food security and place less attention on multisectoral policies, such as food and nutrition programmes that have implications at the household level [7].

The capacity-strengthening approaches in food and nutrition policy analysis in the past have been able to cover the training needs of various groups at the same training sessions. Although this has generated some capacity in understanding the overall food and nutrition policy issues, the impact on the design of specific policies and programmes has been limited [8]. Because of limited institutions and associated infrastructure for policy analysis in many developing countries, the approach to capacity-strengthening in food and nutrition policy analysis has been confined to national institutions and headquarters of ministries, such as health, planning, finance, and agriculture. The role of these institutions, however, is limited to designing policies that will have an impact at the sectoral level or that will spread across several sectors with some spill-over effects [9]. Hence, their immediate impact on improving food security and the nutritional situation at the household level has been negligible [10].

It is recognized that policies designed to address problems of food and nutrition at the national level do not guarantee the alleviation of food insecurity and malnutrition at the household level. The farming systems, cropping patterns, and resource constraints are so diverse, even within a country, that few policies designed at the national level could have similar effects on rural households [11]. Although it is important to formulate efficient national and sectoral policies, there is a need to design programmes and policies that will have a direct and immediate effect on the food security and nutritional status of the population. However, this requires creating capacity and strengthening the existing capacity for designing such interventions. It should be noted that adequate human capacity for better policy analysis is not enough to ensure successful policy design and implementation. An overall institutional arrangement that facilitates the use of existing capacity for policy analysis is also necessary [3].

This paper documents an approach implemented in Malawi for the past seven years to develop a decentralized, multidisciplinary capacity to analyse food and nutrition policies and programmes. The specific objectives of this paper are to (1) develop a conceptual framework for identifying the areas of capacity-strengthening in food and nutrition policy analysis; (2) provide an example of a decentralized, multidisciplinary capacity-strengthening approach in food and nutrition policy analysis; (3) present specific examples of policy analysis skills that could be imparted at a multidisciplinary level; and (4) outline some of the generalizable lessons for similar approaches in other sub-Saharan African countries.

A conceptual framework for choosing the focal points for capacity-strengthening in food and nutrition policy analysis

In developing institutional and human capacity for food and nutrition policy analysis, it is important to understand the process by which information from the field is converted into policy interventions through the various institutions involved. Also, the target audience for strengthening policy analytical capacity and their training needs should be clearly identified to achieve tangible results.

The institutions that are generally involved in food and nutrition policy analysis in a country include the sectoral ministries, such as the Ministry of Health, the Ministry of Agriculture, and the Ministry of Planning, as well as specialized research centres in the universities and other academic institutions. More recently, non-governmental organizations have played key roles in generating food and nutrition information during food emergencies [12]. Figure 1 presents a conceptual model that could be used to identify different methods of training and various target groups in an institution involved in food and nutrition planning and policy analysis. In order to distinguish data management and analysis systems from training needs, the activities related to data-processing and policy analysis are represented by diamonds, the personnel by circles, and training activities by rectangular boxes.

The availability of adequate data is a prerequisite for food and nutrition planning and policy analysis. In general, in developing countries, the data for policy analysis come from two sources: primary data collected through sample surveys and participatory methods by both governmental and non-governmental organizations, and secondary data published in various official documents that either fully or partly depend on the primary data collected in the field [13]. Primary data are collected by various methods: field surveys, rapid rural appraisal, participatory methods, and key informant interviews. Sample surveys, however, continue to form a major source of data for food and nutrition policy analysis in these countries. The conceptual framework presented here could be modified for any type of governmental or non-governmental institution and for any method of data collection. It should be noted that it is not a model of policy analysis but an overall framework for identifying training needs in food and nutrition policy analysis. Generally, the data are collected by field enumerators who are supervised by field officers. Field officers compile the data for processing [14]. They jointly represent the core groups for training in data-collection methods. Given the recent advances in computer technology and its use at the field level, the data compilation is generally done using existing data-entry programmes. This introduces an element of training in operating these programmes so that data collected from the field are properly entered and checked for possible errors.

FIG. 1. Conceptual framework for identifying training needs in food and nutrition policy analysis

Once the data are entered into the computer, the process by which they are converted into policy information involves two major groups with distinct roles that are often not fully recognized by the current efforts in food and nutrition policy training. As shown in figure 1, the policy analysis group includes nutritionists, economists, sociologists, policy analysts, and other specialists, such as food technologists and agronomists. In the figure this segment is shown with solid lines to distinguish it from the other components involved in the process of converting data into policy alternatives. They are generally involved in designing various food and nutrition policy alternatives and evaluating them for their potential impact on the welfare of the population. Major areas of training for this group would involve data management: manipulating data files and processing data for policy analysis using computers. On the left side of the flow diagram, the data-processing group, or what may be called a research support group, and their training needs are presented. In most of the sub-Saharan African countries, there is a distinct group of civil service employees who work exclusively on computer information-processing [15]. Although they play an important role in policy analysis, this group has been largely ignored in capacity-strengthening efforts. Within this group, three different categories of personnel are involved, depending on the nature of the data-processing: data-processing clerks, statistical clerks, and computer programmers. Their major area of training involves understanding computer software for processing data collected from the field. They are shown with broken lines in figure 1. The computer programmes for data-processing that are widely used in sub-Saharan Africa include Lotus-123, dBASE, and Statistical Package for the Social Sciences (SPSS). Although this group of support personnel is relied upon heavily for entry, manipulation, processing, and management of data, the level of their expertise to meet these needs remains low because of inadequate training and experience.* It is not uncommon in many government ministries to find adequate computer resources with necessary software but no trained computer operators. This is in spite of established posts of computer programmers and their placement in these posts.** In figure 1 the diamond boxes with dotted lines represent the areas of their interaction with policy analysts at various stages.

* Elison M, Mthindi G, Malewa V. Optional resource use in computerization planning in the Ministry of Agriculture. Paper presented at the workshop on Computerization in Malawi - Policy and Program Planning, Mangochi, Malawi, October 1989.

** Mthindi GB, Hazeltine S. Manpower needs and capacity development for computerization in Malawi. Paper presented at the workshop on Computerization in Malawi - Policy and Program Planning, Mangochi, Malawi, October 1989.

The current models of short-term capacity-strengthening concentrate mostly on training in the collection, processing, and analysis of data, the areas shown with solid lines in figure 1. The broken lines indicate areas where additional attention should be paid in future efforts to strengthen capacity. Although the above conceptual framework could be used to identify training needs in any institution involved in food and nutrition policy analysis - governmental, non-governmental, academic, and donor agencies - some modifications may be required, depending on the type of institution in which the capacity is developed.

As pointed out, although the required human capacity for food and nutrition policy analysis may exist within an institution, it is not sufficient in itself to generate meaningful policy alternatives to implement them. The necessary institutional arrangements to facilitate the use of policy information by decision makers should be in place to benefit from this human capacity [3]. In places where adequate policy analysis capacity exists, this is frequently suggested as a major constraint to policy implementation. For example, in several countries in sub-Saharan Africa, food and nutrition policy-making remains a sectoral decision. Experience from countries that have placed the responsibility for making decisions about food and nutrition on the central ministries indicates that such an arrangement enhances the effective use of human capacity in the sectoral ministries and academic institutions [16].

Food security and nutrition monitoring as a method of multidisciplinary capacity-strengthening

The Malawi approach primarily relied upon food security and nutrition monitoring (FSNM) to develop a multidisciplinary capacity for converting information into policy interventions. A brief description of the FSNM system in Malawi is given below. The details of the design and implementation are given elsewhere [17].

The lack of appropriate and timely information on the food security and nutritional status of different groups of households has been a major constraint on formulating efficient food and nutrition policies in Malawi. Provision of food security and nutrition information to the policy makers requires establishing a system of information generation from the local level to collect data that can be compiled, analysed, and presented to policy makers at both the regional and national levels. This can be achieved by developing institutional capacity to undertake data collection, data-processing, and policy analysis.

Based on the principles of nutritional surveillance [13], the Malawi Ministry of Agriculture initiated an FSNM system in 1989. The overall purpose of FSNM is to generate information that is useful for food and nutrition policy decision-making at both the national and the regional or Agricultural Development Division (ADD) levels. The information collected through FSNM forms a major part of the Food and Nutrition Information system (FNIS) in the Ministry of Agriculture. The other components of the FNIS are food and nutrition-related data from the Annual Surveys of Agriculture, crop estimate information from the ADDs, market price information from rural markets, and national food security and meteorological updates from the National Early Warning System in the Ministry of Agriculture.

The specific objectives of the FSNM system are:

» to establish a system to generate information on food security and nutritional status from different regions and various socio-economic groups;

» to generate household-level data periodically on the adoption of technology; the production, storage, sales, and purchase of food; employment availability; wages; food prices; expenditures; coping strategies; and nutritional status;

» to develop a reporting procedure for timely dissemination of information from the local (ADD) level to headquarters and to share it with appropriate ministries and institutions at the national level;

» to produce national-level reports on the characteristics of households with various degrees of food insecurity and nutritional problems after every round of information-gathering based on geographic and socio-economic classifications;

» to generate short-, medium-, and long-term intervention plans and policies both at the local (ADD) and national levels to reduce food insecurity and malnutrition at the household level.

The process of implementation of the FSNM has concentrated on both the demand for and the supply of information on the food security and nutritional status of the rural population. Major emphasis is placed on the supply side of information generation and on strengthening the capacities at local levels for information-gathering, information analysis, and policy-making. Based on the principles of nutritional surveillance, FSNM has been implemented in all eight regional ADDs of Malawi.

The FSNM surveys involve the collection of periodic information with four different modules: household food security, household income and expenditure, markets and prices, and nutrition monitoring. Before each survey, a three-day training for enumerators and field supervisors is conducted to explain the need to collect data on each of the variables and to undertake field training using an enumerator manual. A data-entry programme is written to compile the data in dBASE, and a manual on guidelines for data analysis with a programme in SPSS is also prepared and distributed to the ADDs.

A week-long training course in statistical data analysis is conducted after every survey for the evaluation staff of the ADDs, which enables them to undertake advanced analysis of the data collected. Using the results of the analysis, the ADDs prepare a Food Security and Nutrition Working Paper and present the results to the management. The results are discussed in each ADD to determine policy recommendations and identify persons responsible for action. The results of the policy proposals are then presented to senior officers of the Ministry of Agriculture to prepare a plan of action based on the policy recommendations [18]. Some of these plans of action are sent to the national offices on food security and nutrition policy-making in the Ministry of Economic Planning and Development and to the Office of the President and Cabinet. On the basis of the results of analysis from each round of information-gathering, a national report is prepared for use by senior officials in the Ministry of Economic Planning, as well other ministries and donor agencies, as a quick reference to indicators and variables affecting food security and nutrition [19].

On the demand side of information generation, efforts have been made to create a system that will use food security and nutrition information constantly in planning, policy-making, and project implementation. To this end, a Food and Nutrition Information Committee (FNIC) has been established at the Ministry of Agriculture. The FNIC coordinates the Food and Nutrition Information System (FNIS) with the essential task of reviewing the existing food- and nutrition-related information and identifying additional data needs. The committee also channels the flow of food security and nutrition information for the use of other ministries and donor agencies. For example, during the Southern Africa drought of 1991-1992, the committee was able to provide the National Disaster Preparedness Committee with a constant flow of information gathered from the field, thereby enhancing the speed of decision-making [20]. The committee is also responsible for relating the information generated on food security to policy issues and making policy suggestions to the Ministry of Agriculture. The members of the FNIC include the Food and Nutrition Unit, Evaluation Unit, Marketing and Pricing Unit, Early Warning Unit, and Data-Processing Unit in the Ministry of Agriculture.

The approach followed in Malawi is multidisciplinary, in which nutritionists and economists work together with agricultural specialists at both the regional and the headquarters levels. In strengthening the national capacity to generate food security and nutrition information and in making food and nutrition policy interventions, emphasis has been placed on the decentralization of activities. Such a process of decentralization has been useful in generating food and nutrition policy recommendations from the lowest levels that are specific to their areas (e.g., extension-planning areas). This also provides an opportunity for officials involved in implementing interventions at the lowest levels to participate in policy generation and become involved fully in the implementation of policies with enhanced motivation. The discussions of the first FSNM survey results at the ADD and Rural Development Project levels and the policy recommendations made from them have demonstrated that such a “bottom-up” approach in food and nutrition policy-making and implementation is possible in Malawi.

Multidisciplinary capacity-strengthening for food and nutrition policy analysis

On a country basis, there are generally three different levels of capacity-strengthening required for food and nutrition policy analysis. For the purpose of identifying targets for capacity-strengthening, they could be classified as national-, sectoral-, and local-level capacities. The policy analysis skills that are required to address macro issues and their role in food and nutritional well-being and the issues relating to food trade, stock management, and food aid are generally developed at the national level. The capacity to deal with the sectoral policies relating to food sectors, such as food production and food price policies, is seen as a basic requirement in the Ministry of Food. Although the need has been recognized for some time, there is a general consensus that issues relating to capacity-strengthening to meet the decentralized-level food and nutrition policy analysis have not been addressed adequately.

The decentralized-level capacity to generate public and private action against food emergencies has been recognized as an important factor in mitigating the effects of famines and other food-related calamities [2]. The policy analysis capacity at the decentralized level is also essential for monitoring and evaluating food security and nutrition intervention programmes. In addition, local capacity to analyse food and nutrition issues and address them in a policy and programme context is essential for intervention and action at the community and grass-roots levels. Such capacity also enhances the effectiveness of governmental and private voluntary organizations in mobilizing and targeting their resources to improve the food security and nutritional situation of the population. Above all, a multidisciplinary capacity to analyse and interpret information from the field and to design appropriate interventions related to the food and nutrition sector is fundamental for implementing intervention programmes to meet the local needs of the population.

The FSNM system in Malawi provides an opportunity to generate information for designing policy interventions and development programmes that could improve the welfare of the population at three different levels. As described earlier, in the first stage the data collected from rural households on indicators and factors affecting food security and nutritional status are processed and analysed for decision-making at the agricultural district level. The nutritionists and evaluation economists in each of the eight agricultural development divisions analyse the data collected from their divisions. They are the primary targets for the multidisciplinary capacity-strengthening approach discussed in this paper. Besides this group, capacity-strengthening efforts in Malawi have also concentrated on improving the policy analytical skills of two other target groups, namely nutritionists and economists at the sectoral level, particularly in the Ministry of Health and Agriculture, and in national-level organizations, such as the Ministry of Economic Planning and the Office of the President. It should be noted that capacity-strengthening efforts in food and nutrition policy analysis in the past invariably focused only on the latter groups [21].

In training policy analysts at a multidisciplinary level, it is important to recognize the need for policy information that is expected from them, although the demand for such outputs may not necessarily exist. Related to this is a good understanding of the already existing capacity at the local level on which policy analytical skills could be built. Hence, the types of skills imparted to these target groups should be such that they meet the requirements of their jobs and at the same time are easily absorbed, assimilated, and used in their regular work.

An inventory of the levels of training in terms of regular undergraduate and postgraduate programmes, computer skills, and other short-term training in policy analysis was made by eliciting the backgrounds of the district-level nutritionists and economists through a questionnaire. The questionnaire also asked for information on the university from which the degree was obtained and the texts used in courses, particularly for those with postgraduate training in nutrition and economic and social sciences. This inventory provided an opportunity to judge the levels of skills and educational attainment of the participants and was useful in designing the contents of training programmes, pedagogical methods, and implementation strategies for training. An example of assessing the capacity-strengthening needs for food and nutrition policy analysis has been described elsewhere [22].

Based on the need for analysis of data for various policy and programme designs, the approach adopted by the Malawi exercise involved two major steps: first, data-processing that entails converting data from instruments to readily usable forms for policy analysis; and second, transforming the data into meaningful policy information. Because of the limited computer skills of nutritionists and economists at the district level, it was necessary to initiate a training programme in data-processing. This training also included the support staff at district levels, such as statistical clerks and computer programmers who are generally involved in data entry, manipulation, and management. Such joint training is essential to bring data processors and policy analysts to the same level of understanding of the database structure, the variables on which the data are collected, and how these variables could be used for purposes of analysis. This also enabled the analysts to request help from the data-processing personnel in the analysis of data for policy interventions. The capacity for processing data could be developed quickly with frequent training workshops in which real data collected from the field are used. The FSNM surveys periodically conducted by the Ministry of Agriculture provided an opportunity for such an approach.

In addition to the combined training in data-processing skills, policy analysts and data processors were jointly trained in basic statistics. This helped in better communication in terms of statistical data-processing between these two groups. One specific example may be worth pointing out. One of the important procedures that make data-processing more efficient and useful for improving the quality of information is data-cleaning, which requires input from both the data processor and the data analyst. The training programmes designed for cleaning data sets necessarily involve imparting basic knowledge of statistics. The training approach followed in Malawi enabled data analysts to interact better with the processing personnel in producing jointly a data set of improved quality.

Once the basic skills for using various kinds of computer software for data-processing are attained, it is relatively easy to initiate the training in data analysis. At this stage, the support staff included in training programmes for data-processing could be weaned from the capacity-strengthening exercise, although training workshops in learning advanced techniques in data management and maintenance should be continued for this group. The second stage in increasing the capacity for policy analysis is training in data analysis for deducing policy directions and identification of food and nutrition programmes and projects. Specific components of training at this stage involve three sets of subject areas: converting data to policy, transforming policy directions into specific projects, and policy communication skills.

Training in food and nutrition policy analysis at the multidisciplinary level involves, as a first step, developing an inventory of potential policy alternatives and programmes that could be implemented at the district level without much involvement of national-level decision-making. The nutritionists and economists from the ADDs were involved in this process through a series of training workshops. The major content of this training was to develop a conceptual framework that could be used to analyse the issues relating to household food security and nutrition. The conceptual framework was then used to differentiate the indicators of household food security and nutritional status that reflect the welfare of the population from their causal factors. The workshops also addressed the potential areas of intervention that have immediate, medium-term, and long-term impact on the welfare of the population. Since this conceptual model was similar to the one the evaluation economists and nutritionists used for developing FSNM questionnaires, it was easy to relate the model to the variables on which the data had been collected.

The variables (indicators and causal factors) for analysis were also classified according to their level of influence, namely at the household and community levels. Followed by the conceptualization exercise, the participants were trained to relate the indicators of food security and nutritional status to causal factors to infer the degree of their association. Some of the specific analytical skills developed during the training workshops included functional classification of food-insecure households, analysis of production-oriented policies, and analysis of household coping mechanisms and their implications for designing intervention programmes.

The following examples illustrate the conversion of data to information from FSNM during the training courses. In Lilongwe ADD, it was found that the percentage of households running out of food in different areas ranged from 13% in June to 75% in December of the same year. The most common strategies for coping with food insecurity that were reported by households were to undertake casual farm labour and then to sell livestock. In Ngabu ADD, households with vegetable gardens along the streams and small rivers had greater food security, although no specific extension messages were available for such gardens. In response to this information, a message was developed. In Ngabu ADD, where sorghum and millet have been grown traditionally, the government in recent years has encouraged maize cultivation in order to increase maize production at the national level. The results of the ADD-level analysis in Ngabu indicated that households that grew drought-tolerant sorghum ran out of food later than the maize growers. In response to this information, the ADD is reconsidering its strategy to expand maize areas. In Liwonde ADD, the results indicated that households change their food preference to cope with reduced food availability. A majority of the households indicated that they shifted from eating ufa (fine maize flour with 40% extraction) to mgaiwa (coarse maize flour with 96% extraction).

A summary of the levels of training, participants, and contents of the training courses described above is given in table 1. For example, the training course on data collection methods and questionnaire design was primarily conducted for field enumerators, supervisors, and field officers, but it also included specialists in district-level subject matter and national officers dealing with food and nutrition issues. The course on food and nutrition data-processing and management was conducted for field officers, data processors, statistical clerks, computer programmers, district officers, and national officers. The course on statistical analysis with SPSS was offered to statistical clerks, district officers, and national officers and involved training in the fundamentals of applying statistical principles to data analysis and generation of information through cross-tabulation and hypothesis testing. The course on analysis of food and nutrition intervention policies and programmes was primarily offered to nutritionists, economists, sociologists, anthropologists, and agronomists at the district and national levels. Finally the senior-level decision makers were given one- to two-day training workshops to discuss the outcome of policy analysis and evaluate policy alternatives. National- and district-level officers also attended these workshops. The cost of conducting these training courses during 1990 to 1993 constituted about 60% to 70% of the total cost of implementing the FSNM system. For example, depending on the number of participants for every round of information generation, the cost of training ranged between US$ 67, 000 and $96, 000. A detailed account of the costs and benefits of the FSNM system as a food and nutrition policy-generating mechanism is given elsewhere [23].

Lessons for capacity-strengthening in food and nutrition policy analysis

One of the important lessons learned from Malawi is that a critical mass of people trained in food and nutritional policy analysis from various sectors, including the university and other academic institutions, is a prerequisite for designing successful food security and nutrition interventions. Lack of such capacity to translate data into policy decisions and to design interventions poses a formidable challenge in most sub-Saharan African countries. Associated with this is the need to strengthen the capacity for policy analysis at the decentralized level. This would require re-orientation of the approaches to capacity-strengthening in food and nutrition policy analysis to meet specific requirements for such an approach.

TABLE 1. Levels and contents of decentralized training courses in food and nutrition policy analysis

	Course (number of times given 1990 - 93)
Level of training (number of participants 1990-93)	Data collection methods and questionnaire design (5)	Food and nutrition data-processing and management (5)	Statistical training for analysis of food and nutrition policy interventions (8)	Food and nutrition intervention policies and programmes (8)	Food and nutrition policy decision-making and implementation (8)
	Course contents
Field enumerators (320)	Implementing food and nutrition data collection
Data collection supervisors and field officers (60)	Supervising food and nutrition data collection	Supervising data collection to help data entry
Data-processing and statistical clerks, computer programmers (40)		Data entry, data manipulation, and management for future use	Statistical management of data to help in statistical analysis of data
District officers: nutritionists, economists, sociologists, anthropologists, agronomists, etc. (48)	Designing data collection procedures and questionnaires based on information needs	Data management for statistical analysis	Fundamentals of statistical analysis, cross-tabulations, and hypothesis testing	Overview of food security nutrition issues	Decision-making at decentralized (district) levels and implementation of food and nutrition interventions
National officers based at headquarters of Sectoral Ministries involved in food and nutrition policy-making (25)	Designing data collection procedures and questionnaires based on information needs	Data management for statistical analysis	Fundamentals of statistical analysis, cross-tabulations, and hypothesis testing	Defining concepts and determinants of food security and nutrition, identifying characteristics of food-insecure and malnourished, identifying and describing policy intervention for improvement	Decision-making at the sectoral level (agriculture, health, community services, local government) and implementation of food and nutrition interventions
Information users and decision makers, ministers and permanent secretaries involved in food and nutrition policy-making (20)				Obtaining relevant information for food and nutrition policy decision-making	Decision-making at the national level and implementation of food and nutrition interventions

It is increasingly realized that successful design and implementation of food security and nutrition interventions involves pulling together a group of practitioners with various subject-matter orientations. Specifically, there is a need to integrate the specialties such as nutrition, food-processing, agronomy, and policy analysis to meet the need for multidisciplinary capacity-strengthening. This could be achieved by exposing nutritionists to the fields of economics and policy analysis and by expanding the knowledge of policy analysts in fields related to food security and nutrition. The contents of the training courses reflected the capacity-strengthening needs of a multidisciplinary group of participants. Replicating such efforts elsewhere would mean that the curricula and courses of training institutions both in sub-Saharan Africa and abroad should be reviewed to promote such an integration.

Given the wide variation in the existing capacity to undertake food security and nutrition planning and policy interventions among the countries in sub-Saharan Africa, there is an urgent need to strengthen the capabilities of training institutions to ensure the long-term sustainability of institution-building efforts. This is best done when institutions in the region collaborate to share information and facilities in capacity-strengthening. For example, the Malawi case study provided an opportunity to involve academic institutions in training activities so that they would have the capacity to conduct such training courses in the future. This ensured the sustainability of capacity-strengthening activities. Also, the right balance should be achieved between investments in long-term postgraduate training and short-term in-service training efforts. This is particularly important to optimize the limited resources available for capacity-strengthening efforts in food security and nutrition policy analysis.

There is a general consensus that much of the food and nutrition training currently offered remains academic and is not used for policy analysis, and that food and nutrition policies continue to be made under the veil of ignorance. Thus, bridging the gap between theory and policy analysis should be the prime objective of policy analysis training. Decentralized, multidisciplinary training programmes provide such an opportunity. Since the training activities described in this paper were a large and integral part of an overall effort to establish a sustainable FSNM system, real issues were addressed in the training courses. The training courses were also output-oriented. The results of data analysis were prepared by participants as working papers for their institutions.

Developing policy analysis capacity in third world countries without developing and strengthening the institutions and processes that facilitate the use of these capacities may not be sustainable in the long term [24]. Weak analytical advice that results in a declining demand for policy analysis is one of the major causes of the hesitation of developing-country governments to make serious efforts to use policy analysis in the process of decision-making. The Malawi approach to food and nutrition policy analysis and capacity-strengthening generated the necessary demand for policy information among senior level decision makers. This helped to place food and nutrition issues in the centre of the policy-making agenda at the national level.

Multidisciplinary decision-making could be seen as an improved method for designing and implementing locality-specific policies. Training programmes in food and nutrition policy analysis should delineate the target groups and the policy issues to meet this demand at the district or subregional levels in a country. Identifying various levels of participants and their capacity-strengthening needs enabled a better design of the training courses and their contents for a multidisciplinary group of participants.

Training in food and nutrition policy formulation should consider a set of policy measures that are internally consistent with the economic and political environment of the participants’ countries. In designing training programmes, policy alternatives should be distinguished on the basis of the levels of implementation, such as emergency programmes, short-term policies, production-related policies, sectoral polices, and macroeconomic policies. The contents of the Malawi training courses reflected this need. Thus, training courses during the period of drought (1991-1992) primarily addressed analysis of policies related to food and nutrition emergencies.

Strengthening the capacity of the enumerators and field supervisors to collect better data in Malawi resulted in high-quality and reliable data sets that were further used in the analysis of food and nutrition issues. The capacity-strengthening efforts in food and nutrition policy analysis may not achieve their final goal of improved policy recommendations unless policy analysis is conducted on the basis of reliable data. Thus, there is also a need to strengthen the capacity of the staff involved in information generation as a part of training in food and nutrition policy analysis.

Short-term training activities often place too much emphasis on the tools of analysis, with little attention paid to developing the capacity to ask questions that are pertinent for the country. Training in quantitative analysis and modelling should also be seen as a method of asking the right questions and an incentive for understanding the need for reliable data for policy analysis. In designing food and nutrition policies, the government ministries rely more on judgements and debate on issues. This approach formed a part of policy analysis training in Malawi by involving various levels of participants in one- to two-day workshops on food and nutrition policy decision-making and implementation.

The division of labour between the personnel involved in data-processing and analysis at various levels of policy formulation in developing-country governments should be adequately recognized, and training programmes should be designed to develop capacity in each of these areas. Developing skills for outlining a conceptual framework to investigate various food and nutrition issues is a prerequisite for building policy analysis skills. Whereas the regular university training provides the latter, the skills for translating food and nutrition problems into conceptual issues should be taught in the short-term training programmes.

In many cases, formal postgraduate training programmes do not provide adequate opportunities for learning the simple techniques used most often by policy analysts in the governments of developing countries. Capacity-strengthening for food and nutrition policy analysis should focus more on “fire-fighting” techniques and skills through case studies. Often, the wrong people are selected by the governments to attend short-term courses in policy analysis. Training programmes are frequently regarded as an incentive rather than an investment. This results in troublemakers within the government system being sent for overseas training. Working with food and nutrition institutions on a long-term basis and adequately maintaining the institutional memory involved in capacity-strengthening, helps avoid such misuse of training funds. In addition, an initial assessment of existing human and institutional capacity helps to identify the target groups better. Experience from such an exercise in Malawi is documented in detail elsewhere [21]. Strategic planning in strengthening the capacity for policy analysis within each country is needed [3].

Given the increasing demand for policy reforms and the lack of adequate capacity to undertake food and nutrition policy analysis to incorporate food security and nutritional considerations in designing and implementing structural adjustment and stabilization policies, the long- and short-term training efforts in food and nutrition policy analysis should be continued for a considerable time in the future. This is also important because of the continuous exodus of trained government policy analysts to the private sector in developing countries.

Microcomputers have become an increasingly integral part of food and nutrition policy training programmes. However, constraints on the availability and accessibility of computers in the regular work of policy analysts in developing countries have largely been ignored by the designers of training programmes. Considerable resources need to be mobilized for the procurement of computers and software that match the training programmes if the capacity-strengthening efforts in policy analysis using computer skills are to be successful.

Training institutions involved in the development of computer-based simulation as a food and nutrition policy analysis tool should collaborate in sharing the course material to reduce the cost of training programmes and to minimize duplication of effort. The linkages between government ministries and academic institutions in each country should be strengthened for increased policy dialogue and to improve the capacity for policy analysis training. A leading institution that develops sufficient capacity for training in a country could be further strengthened to cater to the training needs of the countries in the region.

In the past, a lack of clear objectives of several training programmes made the evaluation of their work difficult. Evaluation of training programmes should include evaluation of the participants and the institutions involved in training. Participatory techniques through group discussions between the trainees and trainers may be better than soliciting suggestions for improvements through questionnaires [25].

One of the weakest areas in the process of translation of food security and nutrition information into useful policy decision is the effective communication and presentation of information. The presentation of information must be user-specific and sensitive to the level of decision-making. For example, senior policy decision makers should be presented with a one-page summary of policy issues, results, and recommendations that can be quickly read while they travel from one meeting to another within the capital city. This would enhance the use of information for intervention planning and appropriate decision-making at national, regional, and community levels. However, this requires additional specialized training in developing communication skills and should form an integral part of capacity-strengthening initiatives in food security and nutrition policy analysis.

Conclusions

This paper documents an approach to strengthening a multidisciplinary capacity for planning and policy analysis to improve the food security and nutritional status of the population. A case study of food and nutrition policy, a major component of development policy in developing countries, was presented from Malawi. To aid in the identification of various target groups for decentralized capacity-strengthening and their training needs, a conceptual framework was developed. The FSNM system currently implemented in Malawi for food and nutrition planning and policy-making was described as an approach to develop a multidisciplinary capacity. Some generalizable lessons from the Malawi exercise were also presented.

Concerns have been expressed recently about the declining funds and reduced support of donors for short-term training programmes. However, the response from policy makers in developing countries for increasing the capacity of their institutions in policy analysis has not been enough. Although long-term commitment from the donors is a prerequisite for successful capacity-strengthening in food and nutrition policy analysis, efforts should also be made among the donors to coordinate the training programmes jointly [26].

Efforts have been made recently in sub-Saharan Africa to identify regional and national institutions that could offer training programmes in food and nutrition planning and policy analysis [27]. Although this approach has been successful to some extent, it increases the workload of the trainers and necessitates increasing staffing positions in the country institutions if the training programmes are to be conducted on a sustainable basis. Nevertheless, the challenge of strengthening the developing-country institutions and the human capacity for food and nutrition policy analysis remains. There is an increasing need to address various issues that could enhance the efficiency of capacity-strengthening programmes in the developing countries. The role of continuous dialogue between the researchers and trainers in academic institutions and the policy decision makers, and between the developing-country governments and training and donor agencies, in achieving the goals of improved capacity for food and nutrition policy analysis, and hence informed policy decisions, cannot be overemphasized.

Acknowledgements

The author would like to thank Per Pinstrup-Andersen, Sudhir Wanmali, Wilbert Gooneratne, and Joachim Von Braun for their encouragement and discussions during the preparation of this paper. The author alone is responsible for any remaining errors.

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