metadata: authors: 0: author: Horton,Susan E.
docna: 0: docna: Unit costs, cost - effectiveness, and
            financing of nutrition interventions
docty: Policy Research Working Paper
subtopic: Health Care Services Industry,Disability,Health Service Management and Delivery,Nutrition,Educational Sciences,Services & Transfers to Poor,Economic Assistance,Access of Poor to Social Services
teratopic: Education
abstracts: cdata!: The author summarizes what is known
            about unit costs, the cost structure, cost-effectiveness,
            and financing of eight nutrition interventions: maternal and
            child health (MCH) feeding, school feeding, nutrition
            education, the promotion of breastfeeding, targeted food
            subsidies, micronutrient supplementation, micronutrient
            fortification, and growth monitoring. Among items that she
            reports: (1) mass media nutrition education campaigns and
            the promotion of breastfeeding cost about $1 - $5 per
            beneficiary; face-to-face nutrition programs cost more ($23
            per beneficiary in the Dominican Republic). (2) Food
            distribution programs of different types have fairly similar
            costs. For distributing about 1,000 calories a day per
            beneficiary per year: $75 for untargeted food rations, $64
            for targeted food rations, $74 for MCH and school feeding
            programs, and $134 for highly targeted feeding programs.
            Micronutrient interventions cost from $0.04 to $4 per
            person-year of protection; supplementation is more expensive
            than fortification. (3) Medium-sized feeding programs
            (100,000 to 500,000 beneficiaries) are the least expensive.
            There is little difference in cost between programs operated
            by nongovernement organizations and those operated by
            governments. The more expensive programs are not necessarily
            less cost-effective, but may include more complementary
            inputs. (4) The cost per death averted was about 1,500 for
            both a targeted supplementary feeding program in Tamil Nadu
            and a vitamin A capsule distribution scheme in Bangladesh.
            (5) The cost per child removed from modrate and severe
            malnutrition ranged from $33 (Tamil Nadu) to $331 (targeted
            food subsidy, Philippines) to $493 (face-to-face nutrition
            program, Dominican Republic). (6) Nutrition expenditures
            seem to account for about 10 percent of health spending,
            both for donors and for individual countries (Chile is an
            outlier with 35 percent). Impact data on these topics are
            scarce, and these estimates should be interpreted cautiously.
repnme: repnme: Unit costs, cost - effectiveness, and
            financing of nutrition interventions
display_title: Unit costs, cost - effectiveness,
            and financing of nutrition interventions
listing_relative_url: /research/1992/08/699635/unit-costs-cost-effectiveness-financing-nutrition-interventions
topicv3: Food Subsidies m1326272 1626,Nutrition m1326779 644,Education m1327048 470,School Feeding m1504302 3655,Health m1504661 3480
publishtoextweb_dt: 2010-07-01T00:00:00Z
historic_topic: Education
origu: Pop & Human Resources Department
no_of_pages: 77
author_keys: 0: author_key: 773306
model_extractions: <!-- Start of picture text --> Polley Research<br>Population, Health, and Nulrltlon<br><!-- End of picture text --> WPS 952

- This paper a product of the Population, Health, and Nutrition Division, Population and Human - Resources Department is part of a larger effort in the department to quantify the costs of malnutrition and its alleviation. Copies of the paper are available free from the World Bank, 1818 H Street NW, Washington DC 20433. Please contact Otilia Nadora, room S6-065, extension 31091 (August 1992, 66 pages).

Horton summarizes what is known about unit costs, the cost structure, cost-effectiveness, and financing of eight nutrition interventions: matemal and child health (MCH) feeding, school feeding, nutrition education, the promotion of breastfeeding, targeted food subsidies, micronutient supplementation, micronutrient fortification, and growth monitoring. Among items that she reports:

* Mass media nutrition education campaigns and the promotion of breastfeeding cost about **_$1-$5_** per beneficiary; face-to-face nutrition programs cost more ($23 per beneficiary in the Dominican Republic).

> e Food distribution programs of different types have fairly similar costs. For distributing about 1,000 calories a day per beneficiary per year $75 for untargeted food rations, $64 for targeted food rations, $74 for MCH and school feeding programs, and $134 for highly targeted feeding programs. Micronutrient interventions cost from $0.04 to $4 per person-year of protection; supplementation is more expensive than fortification.

There is little difference in cost between programs operated by nongovenmuent organizations and those operated by governitiits. The more expensive programs are not necessarily less costeffective, but may include more complementary inputs.

> * The cost per death averted was about $1,500 for both a targeted supplementary feeding program in Tamil Nadu and a vitamin A capsule distribution scheme in Bangladesh.

> * The cost per child removed from moderate. and severe malnutrition ranged from $33 (Tamil Nadu) to $331 (targeted food subsidy, Pbilippines) to $493 (face-to-face nutrition program, Dominican Republic).

* Nutrition expenditures seem to account for about 10 percent of health spending, both for donors and for individual countries (Chile is an outlier with 35 percent).

Impact data on these topics are scarce, and these estimates should be interpreted cautiously.

* Medium-sized feeding programs (100,000 to 500,000 beneficiaries) are the least expensive.

The Policy Research Working Paper Series disseninates the fndings of work under way in the **Bank.** An objective of the series is to get these findings out quickly, even if presentations are less than fully polished. The fmdings, interpretations, and conclusions in these papers do not necessarily represent official Bank policy.

Produced by the Policy Research Dissemination Center
# Tableof ContertAJ

# Executive summary

# List of tables

# List of acronyms

|1.|Methodology|2|
|---|---|---|
|II.|Unit costs|7|
|111.|<br>Cost structure|12|
|IV.|Cost-effectiveness|16|
|V.|Financing|18|
|VI.<br>App|Summary<br>endices:|22|
|A.|Summary of main interventions in Chile|44|
|B.|Summary of main interventions in Philippines|50|
|C.|Summary of main interventions in Malawi|59|
|D.|List of contacts|62|

# Bibliography

63
ii

# List of tables.

|Text|tables,|Page|
|---|---|---|
|1.|Unit costs of education-type interventions.|25|
|2.|Unit costs of targeted food subsidies.|26|
|3.|Unit costs of feeding programs (school feeding and MCH):|27|
||summary.<br>||
|4.|Unit costs of micronutrient interventions.|28|
|_5._<br>|Non-food costs of selected NGO feeding programs.<br>|29|
|6.|Food cost as percent of total cost, feeding progtams:|30|
||summary.||
|7.|Costs of some of Brazil's nutrition programs, 1978-80.|31|
|8.|Summary of costs by different types of food distribution<br>programs.|32|
|9.|Cost-effectiveness of nutrition interventions: program data.|33|
|10.|Cost per death averted of nutrition, health and combined<br>interventions, Narangwal, India.|34|
|11.|ExpendItures on nutrition programs, selected countries.|35|
|12.|Expenditures on nutrition interventions, UN agencies and|36|
||<br>USAID.||
|ApD|endix tables.||
|1.|Unit costs of feeding progams (school feeding and MCH).|37-39|
|2.|Food cost as percent of total costs of feeding programs.|4042|
|3.|Percent of program cost financed externally.|43|
|Al.|Chile: annual expenditures on nutrition intervention|47|
||programs.||
|A2.|Chile: sources of central government expenditures on PNAC.|<br>48|
|A3.|Chile: financing of school feeding program (PAE).|49|
|A4.|Chile: cost per beneficiary and per calorie of major<br>interventions.|49|
|Bl.|Philippines: summary of main nutrition interventions.|52-55|
|B2.|Philippines: population, health and nlutrition share of|56|
||government spending (%).||
|B3.|Philippines: local government expenditures on population,<br>health and nutrition.|57|
|B4.|Philippines: government health funds by source.|57|
|B5.|<br>Philippines: average cost to supply 1000 calories of food<br>value.|58|
|B6.|Philippines: targeting of feeding programs.|58|
|B7.|Philippines: implicit average cost to supply 1000 calorie of<br>|58|
||food to targeted population.||
|C1.|Malawi: UNICEF and WFP expenditures on nutrition.|61|
# List of abbreviations.

ADRA CARE CRS Catholic Relief Services CIDA Canadian International Development Agency FHI Food for the Hungry International FFW Food for Work FNSU Food Security and Nutrition Unit (Malawi) ICDS Intensive Child Development Services (India) JUNJI National Association of Kindergartens (Chile) MCH Maternal and child health NGO Non-government organization NIPP Nutrition Intervention Pilot Project (Indonesia) PAF School Lunch Program (Chile) PCA Complementary Food Program (Brazil) PSA Food Supplement Program (Brazil) PINS Integrated Nutrition and Health Program (Brazil) PLF Pregnant and lactating females PNAC National Supplementary Feeding Program (Chile) PNS Nutrition through the Health System Program (Brazil) SNP Special Nutrition Program (India) USAID United States Agency for International Development WFP World Food Program

# Acknowledgements.

The author weuid like to thank the many people (listed in Appendix D) who provided<sup>references,</sup> suggestions and data for this survey. Thanks also to Ashu Handa for excellent<sup>research assistance,</sup> and in particular for undertaking the three country studies.
~~~~~~~~~Executive summMr.

y This paper summarizes what is known about unit costs, cost structure, cost-effectiveness and financing of nutrition interventions. Eight different interventions are covered (maternal and child feeding - MCH, school feeding, nutrition education, breastfeeding promotion, targeted food subsidies, micronutrient supplementation, micronutrient fortification and growth monitoring).

The following data were obtained on unit costs: mass media nutrition education campaigns cost about _$1-5_ per beneficiary, with a similar range for (hypothetical) data for breastfeeding promotion. Face-to-face nutrition programs are more costly ($23 per beneficiary in the Dominican Republic). (Data for education programs are current dollars, different years). Food distribution programs of different types have fairly similar costs, since food typically forms the major component of costs. Estimates here suggest that the cost of distributing 1000 calories per day per beneficiary per year is as follows: _$75_ for untargeted food rations (1 program), $64 for targeted food rations (median, 4 programs), $74 for MCH and school feeding programs (medi-an, 52 programs), and $134 for highly targeted feeding programs (I program) (all costs in 1988 US $). Micronutrient intervention costs range from $0.04 to $4 per person-year of protection, with supplementation being more expensive than fortification (current dollars, 14 programs).

Some crosstabulations were undertaken of data for 52 feeding programs, to examine the effects of program design on costs. Program costs do not differ consistently by region (sub-Saharan Africa, North Africa, Latin America and Asia), with the possible exception that programs in South Asia cost $10 per year less. There is no consistent difference between costs of school feeding and MCH programs. Program scale does affect costs: medium sized programs (100,000 - 500,000 beneficiaries) are the least expensive. Finally, there is little difference in cost between costs operated by NGO's and those operated by governments, although those with external finance might have higher costs. All these results have to be interpreted cautiously since there may be consistent biases in data quality. Also the more expensive programs are not necessarily less cost-effective, but may
include more complementary inputs. It is necessary to examine impact data in conjunction with costs.

The study also examines cost structure, in particular the share of food and non-food costs in program costs. The differences across program types are not very large. Non-food costs account<sup>for</sup> about 17% of the total for targeted food rations (median, 4 programs), 25% for feeding<sup>programs</sup> (median, 81 programs, although the share can be as high as 71% in highly targeted feeding programs such as that in Tamil Nadu), 20-34% in food for work programs (2 programs) and _29°o_ for<sup>I</sup> micronutrient supplementation program.

Again, cross-tabs were undertaken to find the effect of program design, using data for 81 feeding programs. In sub-Saharan African non-food costs are a lower share than food costs; medium size programs have the o-west non-food share if programs 2 diviied into three size groups; and NGO-operated (non-government organization) programs have lower mean non-food shares than those operated by governments. Lower non-food shares may imply more administrative efficiency, but they may also imply fewer complementary inputs.

Cost-effectiveness methods are useful when trying to compare across prog,ams of different types. Although the methodology is widely used in the health area, it is less frequently used for nutrition interventions. The study here summarizes available data on cost per death-averted, cost per child removed from moderate or severe malnutrition, cost per case of blindness prevented, and cost per discounted healthy life year gained. Although cost per death averted is the measure most conmmonly used in health studies, it is not a very useful measure for nutrition interventions. The main impact of nutrition interventions is not the reduction of mortality, but the improvement in quality<sup>of</sup> life for survivors. However data to calculate cost per discounted healthy life year gained are almost never available for individual nutrition intervention programs.

The cost per death averted was around $1500 both for a targeted supplementary feeding program in Tamil Nadu and a vitamin A capsule distribution scheme in Bangladesh. The cost per child removed from moderate and severe malnutrition ranged from $33 (Tamil Nadu), $331 (targeted
food subsidy, Philippines), to $493 (face-to-face nutrition education, Dominican Republic). The same cost for a mass-media nutrition education scheme ranged from $5-12 (costs in current prices). Costs per death averted would therefore generally be well above the $1500 figure, except for mass media projects (and the impact data on the latter are not very good). Data from the Narangwal study suggests that nuwrition interventions are most cost-effective for prenatal supplementation ($187 per death averted, 1988 prices), and become progressively more costly as children get older.

Financing data are also scanty. Nutrition expenditures seem to account for about 10% of health expenditures, both for donors and for individual countries (Chile is an outlier with 35%). For the 5 countries for which data were available, the share of nutrition expenditures in GDP ranged from 0.06 to 0.41% (three of the **five** were in the range 0.16-0.18%). About 90% of expenditures were financed by the central government, and 10% by local government. The poorer the country, the larger the share of central government financing from foreign sources.

More work is needed to improve data on costs, impacts and financing.

One priority area for future work includes better cost breakdowns for all programs (the food/non-food distinction is not very helpful: programs with high non-food costs for reasons of inefficiency cannot be distinguished from those with high non-food costs due to complementary service provision). One particular omission in the data is that there appear to be no data for the food/non-food cost breakdown for untargeted food subsidies. Another priority would be to obtain project cost data for nutrition education interventions and breastfeeding promotion (there are currently no data reported from any breastfeeding promortion projects): these data could be obtained for existing projects with limited work. More analysis of feeding programs could be undertaken using existing standardized project reports **(USAID PVO Child** Survival data, USAID Outreach data, WFP project proposals), to increase information about effects of project design. Another fruitful avenue for exploring the effect of project scale on costs would be to analyze existing feeding program data at the lowest service delivery unit level (e.g. anghanwadi level data for the Intensive Child Development Services
program - ICDS - for India).

Impact data are in general weak and available niainlv for (possibly unrepresentative) research studies. Hence data on cost-effectiveness are particularly deficient. This is also a priority area, since otherwise there is a possibility of misallocating health resources towards other types of interventions for which cost-effectiveness data are more readiiy available and more persuasive. Information on financing are also very limited. Data on all aspects tend to be (unsurprisingly) least good for Africa.
Increased pressure on government budgets in recent years has led to greater interest in issues of cost and effectiveness of government expenditure, and this has been true in the social sectors as in other areas. There has been a relatively large amount of work already done on the cost and effectiveness of education, health and social security expenditures, but relatively less attenticn has been paid to government expenditures on nutrition programs as distinct from health. This paper tries to sumrnarize what is known in the existing literature on unit costs, cost structire, cost-effectiveness and financing of nutrition programs. The paper tries to cover 8 different types of nutrition interventions (MCH feeding programs, school feeding programs, nutrition education, breastfeeding promotion, targeted food subsidies, micronutrient supplementation, micronutrient fortification and growth monitoring). Insufficient information was obtained to assess several other inter. entions (comprehensive early childhood interventions, home gardens and food safety and quality control).

Since a large number of interventions are covered, the paper relies on existing surveys of the costs of individual types of interventions. However in view of the paucity of available literature, there is some new analysis of project level data, either obtained from existing compilations, or directly from project documents (in particular World Food Program - WFP - project proposals). Suggestions are also made as to where further cost data might be obtained, particularly for those types of interventions where existing studies are most scarce. As regards financing, there are eoually very few studies. Previous studies containing data on government expenditure on nutrition interventions were found only for Brazil and India (in general, expenditures on nutrition are not presented separately from those on health). The present study therefore presents results from three country case studies, on Chile, Philippines and Malawi, to give some idea of the range of financing levels and sources in three countries of different levels of per capita income.

Section I of the paper discusses some of the methodological issues on costs, section II presents unit cost figures, section III deals with cost structure (in particular the share of food costs in total
2 costs of an intervention), section IV covers cost-effectiveness, section V financing, and section VI summarizes. The bulk of the results are presented in tables, with a brief text discussion. There is much that can (and has been) said about cost and effectiveness of interventions without recourse to - actual cost data. Rather than repeat the conclusions of other studies, this paper tri; to amass as large a database as available, in order to draw some new conclusions.

# I. Methodology.

This section discusses some of the methodological problems, both with respect to defining cost-effectiveness, and with obtaining data on costs and impact of nutrition interventions. Costeffectiveness methodology is widely used in the health area (as a more readily quantified alternative to cost-benefit), and it therefore seems natural to extend this to nutrition interventions. Costeffectiveness studies have been very widely undertaken for child survival initiatives in developing countries, for instance. Stewart (1988) for example surveys the cost-effectiveness of four types of child survival interventions, and Brenzel (1989) surveys 28 immunization projects in 16 developing countries. However there is a paucity of such studies in the nutrition area.

There are very few attempts to undertake cost-benefit analysis of nutrition interventions (Scandizzo and Swamy, 1982, for the food distribution system in India, and for micronutrients Levin, 1985, Correa, 1980 and Popkin et al, 1980). Cost-benefit studies will not be discussed here.

It is interesting to speculate as to why so few cost-effectivenes **s** tudies exist for nutrition interventions. One reason is perhaps that less is spent on nutrition interventions than on some health interventions (nutrition expenditures form about 10% of health expenditures in developing countries). More importantly, it is murch more difficult to assess the impact of nutrition interventions which occur over a reasonably long period of time, with equally long-lasting results, as compared to the impact of an immunization program with a very well defined, short duration "input", and an easily measured
3 outcome. It is no accident that the greatest number of cost-efisctiveness and cost-benefit studies for nutrition interventions are for micronutrient projects, which have inputs and outcomes which are easier to measure and define.

More importantly, the most commonly used measure in health (cost per death-averted) is not very appropriate for nutrition interventions. It is rather an extreme outcome measure to use for nutrition interventions. Nutritional improvements have many effects other than lower mortality, such as decreased morbidity and hence decreased use of health care facilities, improved learning and ability, higher productivity and hence earnings, increased activity levels, etc. The effects on cases of severe malnutrition (both PEM and micronutrient deficiency) and hence on decreasing the probability of death, is therefore only the "tip of the iceberg". Huffman and Steel (1990) discuss what they call the "dark side of child survival", arguing that narrowly focussed health initiatives may decrease mortality but do little for the quality of life for survivors, whereas nutrition interventions have generalized effects on both morbidity and mortality. Thus an alternative cost-effectiveness measure which combines mortality and morbidity information into a measure of "healthy days saved" is probably preferable, but data requirements mean that such a measure has been only rarely used.

Using cost per death averted may make nutrition interventions compare unfavourably with health interventions. The simplest health interventions (immunization, ORT) have cost-effectiveness figures as low as $50-$100 (Stewart, 1988), whereas the lowest such figure for an actual feeding program is around $1500 (for Tamil Nadu's highly selective feeding program, in a region with very high prevalence of moderate and severe malnutrition, discussed in Ho, 1985). Estimates for prenatal maternal supplementary feeding are lower ($187 per death averted converted to 1988 dollars, for Narangwal, India). Many other health initiatives (e.g. water and sanitation projects, vaccines against cholera and rotavirus) have cost-effectiveness figures also around $1500 (Stewart, 1988). Nevertheless, it is clear that on a cost per death averted basis, interventions involving feeding do not
4 compare very favourably to health interventions<sup>(except for prenatal supplementation). However,</sup> arguably this is a problem of the measure being<sup>used, not that nutrition interventions are intrinsically</sup> more costly.

Other cost-effectiveness measures have<sup>been used, for example the cost of a given</sup> improvement in height (Burger et al, 1990),<sup>the cost per '000 calories delivered (Pinstrup-Andersen,</sup> 1988, although arguably this is more an output<sup>than an outcome measure), and value of a food</sup> transfer to the recipient compared to its<sup>cost to the donor (Katona-Apte, 1986, Reutlinger and Katona-</sup> Apte, 1983: this is the measure of cost-effectiveness<sup>used by the WFP). Information on calories</sup> transferred can usefully be modified using information<sup>on leakage (i.e. proportion of target group</sup> amongst beneficiaries) to calculate cost per '000<sup>calories per beneficiary in target group. Anderson</sup> (1979) for example presents information on<sup>the cost per calorie delivered to a child with a calorie</sup> deficit, and the cost per calorie delivered<sup>to a (severely) malnourished child. This type of calculation</sup> may be useful (in the absence of outcome<sup>data), for comparing programs of the same intervention</sup> type. For example there may be lower unit costs<sup>of nutrition interventions in countries in Latin</sup> America with good infrastructure but relatively lower<sup>rates of malhutrition, and higher unit costs in</sup> countries in Africa with weak infrastructure but<sup>possibly higher rates of malnutrition. Similarly unit</sup> cost data could be used to compare interventions<sup>which are untargeted, with similar targeted</sup> interventions: the former may have l wer costs per<sup>beneficiary, but on a cost-per-target-beneficiary</sup> basis the latter programs may be more cost-effective.<sup>In practice however, it is not easy to obtain</sup> comparative data on cost per target beneficiary,<sup>since the definition of the target group tends to vary</sup> across countries and across studies. However<sup>none of the alternative cost-effectiveness measures</sup> discussed in this paragraph allow comparison<sup>across different project types, and are therefore of more</sup> limited usefulness.

The above paragraphs have discussed<sup>some of the theoretical problems involved when</sup>
_5_ applying cost-effectiveness to nutrition interventions. There are of course the usual practical problems even with estimating costs. Most nutrition interventions are joint with other interventions: MCH feeding and growth monitoring occur in conjunction with health services, food stamp or food subsidy targeting frequently uses the health or social welfare system, and school feeding programs use the facilities of the education system. Often the overhead costs of these other vehicles are not taken into account, such that the costs of nutrition interventions are underestimated. At the same time, if these other services are not available (as in many cases in Africa), nutrition interventions can appear prohibitively expensive, if the full cost of setting up the delivery system is assigned to the nutrition project alone. Similarly there are biases in the costs reported of those projects where aid donors (such as USAID or WFP) require (or encourage) local co-financing. Developing country governments are encouraged to assign local expenses to the nutrition intervention in order to report a desirable level of local input. If the full cost of health worker salaries are included in the cost of a MCH feeding project via health centres, this is likely to overestimate the actual cost of the nutrition intervention. Cost data from NGO's also have problems, in that these organizations often maintain cost data not by program, but by source of funding, and do not fully cost items which are supplied free or at less than market value. There exist therefore very few studies with carefully collected cost data (e.g. Anderson, 1977), other than research projects (which may be highly unrepresentative).

Since unit cost data are difficult to come by, existing studies tend to cite over and over again data from the same few projects. Some types of interventions are covered better than others. Data on unit costs of school feeding programs are relatively common (both MCH and school feeding), although usually not presented in a standardized format allowing comparison across projects, and impact data are scarce. Likewise data on costs of food subsidies exist, although usually not in the form of cost per number of calories per beneficiary, and there are almost no impact studies which can be related to costs (with the sole exception of Garcia and Pinstrup-Andersen, 1987). Cost data are
6 more readily available on micronutrient interventions, and there are also more cost-effectiveness studies in this area. Data on the other nutrition interventions (nutrition education, breastfeeding promotion, growth monitoring) listed earlier are even more scanty.

The present study is therefore forced to use cost data which are less than ideal, in an effort to learn something about operation of projects other than research ones. There is a fair amount of consistency even with these less-than-ideal data, but there is also a lot of noise in the data. It is also not clear whether it is worth advocating that agencies operating nutrition interventions expend a great amount of effort in collecting cost data. USAID did a field test of a cost information system developed for PL-480 Title II programs operated by NGO's, and came to the conclusion that it was not worth the effort (Bremer and Gilmore, 1986). The authors argued that although the on-site costs of different interventions differed (school feeding, MCH, and food-for-work), this information was not used as an allocative devices for food aid. The same authors concluded that cross-country comparisons were also potentially dangerous. It would be politically extremely difficult to make value judgements about aid allocations, if for example it were shown that programs in Africa were more costly or less cost-effective that those in South Asia. However some of the programs (in particular the WFP and the USAID-funded PVO Child Survival Program) have made more efforts at standardizing cost and beneficiary data, and this lead might be followed especially by the larger NGO's and by the USAID title II food aid program.

Well-controlled impact data are even scarcer than good cost data. Indeed, some nutritionists have argued that one should not expect to see impacts of feeding programs on children's growth, when children are over 3 years old (Beaton, 1990). Haaga et al (1984) and others have discussed the methodology involved in interpreting change in nutritional status in the program setting. One problem with existing data is that the definition of severe malnutrition (in terms of number of standard deviations below the median, or percentiles of the reference population) is not always
7 consistent between studies (in particular the studies for India sometimes employ different reference standards). In calculating numbers of deaths averted, studies usually assume a particular death rate for severely malnourished children, and hence base effectiveness results on the reduction in numbers of severely malnourished children. There are ethical problems in collecting these data (severely malnourished children, once identified by health personnel, are usually referred for treatment). Thus these data are somewhat imprecise.

Having outlined some of the methodological and data problems, the next three sections go on to discuss in turn unit costs, cost structure, and cost-effectiveness of selected nutrition interventions.

# X1. Unit costs.

Unit cost data are more readily available than cost-effectiveness data, since it is relatively easier to calculate the number of beneficiaries of a project (or the volume of food delivered), than programn impact. However it is not very meaningful to compare unit costs across different programs. For example the cost of a radio message containing nutrition education information may be $1-5 per person, and a feeding program might cost $70-90 per person per year per '000 calories delivered per day, but these cannot meaningfully be compared in this form. Unit cost information is more useful when comparing different interventions of the same type, but even this has to be done with care. Is a $5 radio message simply more costly for the same outcome as a $1 one, or might it be more

# effective?

For feeding programs one important standardization which can be undertaken is to take account of the size of the ration and the number of feeding days. (Throughout this paper we use cost per beneficiary measures for unit costs of feeding programs, rather than the less preferable cost per unit of food delivered.) Mateus (1989), Beaton and Ghassemi (1979) and Ghassemi (1989) performed an enormous service in compiling unit costs of feeding programs, but stopped short of standardizing
8 by calories delivered per day. Without standardization it is difficult to compare for example MCH and school feeding programs. The latter tend to have smaller ration sizes which are supplied for fewer days per year. Unit costs of feeding programs are therefore presented here as the cost per '000 calories per personi per day per year. (In undertaking the calculation, it is assumed that there are no economies of scale in ration size or in number of days per year fed. I.e. the reported data are simply multiplied by 1000/actual number of calories in ration, and by 365/actual number of days per year fed) We discuss below some of the practical issues involved in calculating unit costs, before discussing the results, which are presented in tables 14 and Appendix table 1. Section I has already mentioned some of the problems involved in calculating costs, such as the difficulties involved with joint costs, and the cost of items not supplied at market prices. Data on the number of beneficiaries are also suspect. Although some feeding programs are very intensive, others are of the "truck and dump" variety. Bremer and Gilmore (1986) describe the NGO's general strategy of managing food distribution with limited resources as follows: " 1) They concentrate complementary inputs on a few carefully chosen sites where they can implement an integrated program combining food and other inputs.

2) They devote the remaining resources to comparatively intensive development activities that do not use food aid, while implementing the food distribution programs as efficiently as possible (i.e. as cheaply as possible consistent with sound management and control.)" In the "truck and dump" types of feeding programs operated by NGO's, information on numbers of beneficiaries tends to be inexact. This may also be true of many government-operated distribution systems. Brazil is one of the countries which has undertaken the most evaluations of its food programs. Checks on numbers of beneficiaries suggested that reported and actual numbers of beneficiaries differed widely (Musgrove, 1989, World Bank documents). Thus the cost per beneficiary data are prone to errors.
9 The unit cost data presented in the tables here are drawn from compilations by other authors. For the feeding programs the costs were standardized by this author. In addition, the feeding program data were supplemented by costs of 13 WFP feeding programs, calculated by the author from a sample of WFP project documents. The WFP allots between 20 and 30% of its resources for feeding programs for what they term vulnerable groups (MCH and primary school). In 1989 for example such feeding programs accounted for 28% of their commitments (WFP Annual Report, 1990). The 13 projects examined here are those which were reviewed at the 25th and 26th sessions of the WFP donors' review group (costs were calculated for any phase of these projects for which data were on file at CIDA - Canadian International Development Agency, not necessarily the exact phase under review at those sessions). Costs were calculated from project proposal documents, excluding non-recurrent costs. According to the sample of evaluation documents available, most projects have beneficiary numbers quite similar to those projected in the proposals (evaluation data are more scanty and less standardized than proposal data). In those cases in which project size increases unexpectedly, additional budget requests are usually made. Thus the WFP are prospective not actual project data, but projects usually operate pretty much on the planned scale (if not necessarily the planned schedule).

Table 1 presents information on education-type interventions, both nutrition education, and breastfeeding promotion. Mass media nutrition education campaigns are quite inexpensive, ranging from $1-5 per beneficiary. Breastfeeding promotion efforts (including changed legislation on infant formula, education efforts in hospitals for both mothers and hospital staff, and policies encouraging "rooming in") are also estimated to cost $1-5 per mother. Levine and Huffman (1990) present additional data on costs and savings of breastfeeding promotion, although not in the unit cost format used here. Costs of face-to-face nutrition education programs such as that in the Dominican Republic (integrated with growth monitoring) are higher ($23 per beneficiary), and costs of other programs to
10 encourage breastfeeding (nursing breaks, workplace creches, maternity leave) are over $100 per beneficiary.

Table 2 presents information on the unit costs of targeted food subsidies, adapted from Pinstrup-Andersen (1988). There is a large variation. Costs, standardized as described above, range from $36-172 per beneficiary, with a median of $75 and a mean of $82. The item subsidized obviously affects costs: milk subsidies are expensive on a cost per calorie basis, whilst subsidies on oil seem to be cheaper than those on grains. There exist data on too few programs to make other generalizations.

Table 3 presents summary information on the 52 feeding programs studied, calculated from the data in Appendix table 1. There exists again an enormous range of costs ($19-300, with a median of $74 and a mean of $89, i.e. on average very slightly higher than the costs of targeted food subsidies in table 2).

Cross-tabulations were undertaken to see how program cost varied with location, project size, project type (school feeding as compared to MCH), and the operating agency. This type of analysis has been undertaken only infrequently before, due to lack of data on sufficient numbers of projects. Information was available here on project location for all 52 programs, project type (school feeding versus MCH) for 48 programs (those of mixed type were excluded), project scale for 24 programs, and project operating agency for 51 programs.

Robert R. Nathan Associates (1987) did attempt some earlier analysis of costs of feeding programs, reproduced here as table 5. Their results were extremely tentative since they were based on only 7 programs, possibly an unusual subset of programs (those applying for USAID Outreach grants), and only contained data on the non-food costs. Nathan Associates concluded that the African programs were on average 10 times as expensive as the Latin American ones (in terms of non-food costs only), and that the cost difference might partly be attributed to their much smaller scale (the
11 African programs had about a tenth as many beneficiaries per program). If one assumes that nonfood costs are around 30% of the costs of Latin American feeding programs, then Nathan Associates' data would suggest that African programs would still cost about 3 times as much as Latin American ones, if food costs in Africa and Latin America were about the same. However these data are not standardized by size of ration and number of days fed, and it proved impossible to retrieve the data on ration size and days fed from all the NGO's concerned.

The data here suggest that the Nathan Associates' results are somewhat unrepresentative. The costs of programs in Asia and Latin America are lower than those in North and sub-Saharan Africa (by $10-20 per beneficiary) if the median is used, but programs in South Asia and sub-Saharan Africa are about $10 cheaper per beneficiary than those in North Africa and Latin America if the mean is used. It is possible that there are differences in cost structure, an issue addressed in section III. Costs of ocean transport and food distribution are quite likely higher in Africa due to lower population density and weaker infrastructure, but programs elsewhere may compensate by including more complementary inputs.

As regards the comparison between school feeding and MCH programs, there seems to be little difference. Mateus (1989) had commented that school feeding programs were cheaper on a straight cost per beneficiary per year basis, but this disappears once the smaller ration size and fewer feeding days of the school feeding programs is taken into account. MCH programs could potentially include more complementary non-food inputs than school feeding programs, which could account for the larger range of costs for MCH programs. (One might also suspect that the most costly school feeding programs are somewhat inefficient).

As regards program scale, this is an issue on which there has been very little information. Cost functions have been very standardly calculated for health interventions (e.g. hospitals), but rarely if ever for nutrition interventions. The limited data here suggest that small programs are the most
12 costly (small implies less than 100,000 beneficiaries), and medium sized _ones_ the least costly (where medium implies 100,000 to less than 500,000 beneficiaries). The most expensive programs tend to be small scale, likely because these intensive feeding programs simply cannot be afforded on a larger scale. These data should be interpreted cautiously since it may be the case that small projects have more complementary inputs, and do not necessarily suffer from diseconomies of scale. The scale issue is one which could fruitfully be examined for homogeneous programs (or using information on delivery unit variation within one program such as the ICDS).

There seems to be little difference in cost by operating agency (government versus NGO), although there may be differences by availability of external funding (the data were not complete enough to allow further investigation of funding source, but this might be an interesting point to investigate in future work).

Table 4 presents information on unit costs of micronutrient interventions (this is table 7.12 from Levin et al, 1990). The costs per person-year of protection are very low, ranging from about 4 cents to about $4. The costs vary somewhat by micronutrient, iron being the most expensive on average, and supplementation in general seems more expensive than fortification.

# 111. Cost structure.

Ihis section focusses on one aspect of cost structure, namely the share of food and non-food costs in project cost (where food costs include any costs of ocean transport, where applicable). This measure of cost structure is the one most widely mentioned in other studies (Berg, 1987, Beaton and Ghassemi, 1979, Anderson, 1979, Mateus, 1983, Pinstrup-Andersen, 1988, Sahn, 1980, etc.). This criterion cannot however be used for nutrition education, growth monitoring, and breastfeeding promotion programs. Micronutrient interventions can be included if the cost of the micronutrier! source is included in place of food costs. Data on the share of food in total costs are presented in
13 tables 2, 6, and 8 (the results in table 6 are calculated from figures in Appendix tables 1 and 2). Table 2 presents information on food subsidies, table 6 on feeding programs, and table 8 has summary information for a range of programs also including micronutrients and food for work.

There are no clear guidelines as to what a desirable level of non-food costs is: high values may either indicate administrative inefficiencies, or a high level of complementary inputs. The nonfood cost share of a targeted food subsidy (particularly a food coupon scheme) is a somewhat nebulous concept. For the Jamaican food stamp project the costs are those of printing the stamps, security, and mailing them out: costs of identification and screening beneficiaries are omitted (these are incurred by other agencies). Thus the non-food cost share would decline if the face value of the stamps were for example doubled. This would however not imply that the program had become more efficient. Thus non-food cost share data have to be interpreted somewhat cautiously.

Table 2 shows that food costs range from 63-88% of program costs for targeted food subsidies (with a mean of 79% and a median of 83%). Non-food costs are a slightly higher fraction for feeding programs (table 6), and range from 11-95% (with a mean of 70% and a median of 75%: note however that data are available for a far greater number of feeding programs than food subsidies). Some of the outliers in the feeding program data likely reflect bad data, where non-food costs are inadequately quantified, or cases where the programs have a large share of complementary inputs.

There exist some interesting variations across feeding programs. Programs in Latin America have larger non-food cost shares, and Africa smaller ones, than for other regions. Bearing in mind that no consistent region,l differences in unit costs were found (table 3), one possibility is that the food costs alone in Africa are higher (in particular transportation costs), whereas in Latin America due to better infrastructure there are larger complementary inputs. As regards program scale, the medium-size programs which were earlier found to have lower unit costs, also have lower non-food
14 cost shares. This may reflect either scale economies,<sup>or also the fact that programs with intensive</sup> health inputs tend to be smaller. There is little differenca in<sup>non-food cost share by operating agency.</sup> NGO-operated programs (and also WFP-funded ones)<sup>have lower mean non-food cost shares than</sup> government-operated ones (although the medians are not<sup>different.</sup> Table 7 provides some information on non-food costs<sup>for programs within one country,</sup> namely Brazil. There was some experimentation in program<sup>design which yields some interesting</sup> information. Firstly, the exclusion or inclusion of health<sup>inputs can change the share of food in total</sup> costs from 25% to 73% (data from the Nutrition through<sup>the Health System - PNS - program).</sup> Secondly, the Complementary Food Program (PCA) distributing<sup>weaning foods has a lower share of</sup> non-food costs than the PNS variant without health inputs,<sup>but only because of the much higher unit</sup> costs of food (blended foods being more expensive than traditional<sup>ones). Finally, the degree of</sup> subsidization of foods also affects the share of food in total<sup>costs, but at the same time has quite</sup> dramatic effects on participation (The Integrated Nutrition<sup>and Health Program - PINS - study</sup> experimented with different levels of subsidy). Data on the<sup>proportion of families continuing to buy</sup> subsidized foods after two years were as follows: 74% in<sup>the group with the 60% subsidy continued</sup> buying, 37% in the group with the 45% subsidy and a growth<sup>monitoring requirement,</sup><sup>_55%_in the</sup> group with the _45%_ subsidy (and no growth monitoring),<sup>and 25% in the group with the 30%</sup> subsidy. Participation data such ase these are extremely<sup>useful as an additional way to assess cost</sup> data, but are rarely available.

Table 8 provides a typology of the costs of different programs,<sup>both unit costs and non-food</sup> cost share in total costs. For comparison, older information<sup>on these topics are included from Mateus</sup> (1983). The latter document is somewhat of an advocacy<sup>piece on targeting food subsidies, and the</sup> data in his table appear to be notional, rather than being<sup>based on specific project data. Since the</sup> Mateus study has been cited (for example by Kennedy and Alderman,<sup>1987, one of the more</sup>
_15_ influential articles in the area of costs), the present author is concerned to update somewhat the impression conveyed by Mateus' figures. Two of the most striking aspects of Mateus' figures are the extremely high cost per beneficiary of untargeted food subsidies, and the extremely low administrative costs of food coupons. Neither of these could be substantiated with more recent empirical data.

Firstly, regarding unit costs. The more recent data in table 8 show that the median value for unit costs is in fact rather similar for three programs, namely untargeted food rations ($75 per beneficiary, albeit this is derived from only one program), targeted food subsidies ($64) and untargeted MCH and school feeding programs ($74) (Tamil Nadu, as an example of a highly targeted feeding program, was about twice as expensive). Although no data were found on untargeted food subsidies, it is unlikely these would be much different on a per-beneficiary basis. Unit costs of different programs might differ if costs per beneficiary in a specific target group were calculated, but almost none of the unit cost data are available on this basis.

Secondly, as regards non-food costs. These are somewhat lower for the targeted food subsidies (the median is 17%) than for feeding programs (median 25%), and food for work programs (20-34%, based on only two programs). However none of the three programs using income targeting of food subsidies (from which these data were obtained) include any cost of identifying the target group, which may bias the figures down somewhat. Moreover Mateus' (1983) estimate of non-food costs of 2-5% for non-food costs of targeted food subsidies seems unduly low Oikely being based on early estimates of the costs of the Colombian food coupon program, which have since been revised upwards).

It is not very surprising that the different programs are so similar in costs. If similar items (i.e. grains or oil) are subsidized, and if non-food costs are fairly low (e.g. a monthly ration pickup at a health centre, a geographically targeted food subsidy using existing outlets, or a school feeding program involving trucking food to schools and paying for a cook), then. it is likely that ration,
16 subsidy and feeding programs will have similar costs. 75% of the costs after all are those of the food. Thus it is unlikely that the differentials are as wide as suggested by Mateus (1983). Programs which provide greater services are definitely more costly on a unit cost basis, although potentially more cost-effective. However data on cost-effectiveness, discussed in the next section, are not as yet adequate to address that issue.

# IV. Cost-effectiveness.

ection I has already described the methodological and practical difficulties involved in costeffectiveness measures for nutrition interventions. Table 9 summarizes the available estimates from program data either on the basis of cost per death averted, case of malnutrition averted and case of blindness prevented. Only 7 projects provided information of this type, of which 1 provided information on cost per death averted, 5 on cost per case of malnutrition averted (child removed from moderate or severe malnutrition), and 1 on cost per case of blindness prevented. The estimate of cost per case of blindness prevented is converted into cost per death averted, using estimates of casefatality rates. Similarly the cost per case of malnutrition averted could be converted to cost per death averted, using data such as in Ho (1985) or Burger et al (1990). (This is an upper bound since not only might children with moderate or severe malnutrition move into the mild malnutrition class, but some children might also move from mild malnutrition to the normal group, which also reduces the mortality rate).

The data tabulated here are direct estimates from individual projects. Other authors have calculated cost per death averted or cost per discounted healthy life year (DHLY) gained, making assumptions using "typical" project cost data and "typical" outcome data. Burger et al (1990) estimate cost per death averted from preschool food supplementation to be $1,236 ($40 per DHLY), and from prenatal maternal supplementation to be $724 ($24 per DHLY). McGuire (1990) also
17 provides information on cost per death averted and per DHLY gained for a wide range of nutrition interventions.

The cost per death averted figures in table 9 are $1482 for (hig>'ly targeted) supplementary feeding in Tamil Nadu, and $1522 for a vitamin A capsule distribution scheme in Bangladesh. These figures (as discussed in section I) are comparable to some other health interventions, but definitely more costly than EPI and ORT interventions. Tamil Nadu is evidently at the low end of cost per death averted as compared to food subsidies and face-to-face nutrition education: the cost per child removed from moderate or severe malnutrition in Tamil Nadu is $33 compared to $331 for a food subsidy in the Philippines, and $493 for a nutrition education/growth monitoring project in the Dominican Republic. Comparable costs for mass media nutrition education efforts are lower ($12 for Indonesia NIPP and $5 for Morocco), although the outcome data for these projects are not as well controlled as some of the other studies.

Table 10 presents estimates of costs per death averted from the Narangwal project. Data are available for 3 different types of intervention (nuttition, medical care, and combined nutrition and medical care), for three different age groups (perinatal, infants, and children 1-3). The study was unusual in that it included a control group. It was also primarily a research study and not a largescale service-delivery project. There are some interesting findings. Firstly, cost per death averted increases with age: perinatal deaths are the least expensive to avert, followed by infant deaths, with child deaths being the most costly to avert. The type of intervention which is the least costly varies with age. For perinatal deaths, nutrition interventions (pre-natal maternal supplementation) alone are the cheapest, whereas for infant and child deaths, medical interventions alone are most cost-effective. The high figures for cost per death averted for children 1-3 ($3053 for nutrition interventions alone, $1617 if combined with medical interventions) underscore the discussion in section I earlier. Another useful source of information to supplement cost-effectiveness calculations, are
18 estimates of program leakage to non-target beneficiaries. This allows a potential link between cost per beneficiary (as discussed in section II), and cost per child removed from severe malnutrition (as presented in table 9), although additional information or assumptions are required to actually make that linkage. Anderson (1977) finds that **to** convert cost per beneficiary to cost per malnourished child fed requires multiplying by a factor of between 1.6 and 10.5. (he actual figures, for five different CARE projects, were: Tamil Nadu, 1.6; Pakistan, 1.9; Costa Rica, 3.1; Dominican Republic, 4.9; and 10.5, Colombia). Anderson however does not present information such that it is possible to calculate cost per child removed from malnutrition.

Obviously program data on cost-effectiveness of nutrition interventions are severely deficient.

# V. Financing.

As in the area of costs, the financing of nutrition programs has received far less attention than the financing of other social sectors such as education or health. Recent World Bank work on social sector expenditures in Latin America for example does not include disaggregated information on nutrition expenditures. Although some of the nutrition expenditures may be included in health expenditures, those which go through institutions other than the Ministry of Health are likely to be excluded. Detailed information on country expenditures on nutrition could be obtained only for India (Subbarao, 1989) and Brazil (Musgrove, 1989, and unpublished World Bank documents). For India information is available on state and central government expenditures, and for Brazil for federal government expenditures (state level expenditures are estimated to be about 10% of federal ones for Brazil: Saxenian, personal communication). In addition, Mateus (1989) painstakingly compiles information on expenditures on MCH and school feeding programs **iti** 16 Latin American countries. (These data obviously form only part of country expenditure on nutrition interventions, although possibly the lion's share). Finally, Huffman and Steel (1990) reproduce data from two other
19 sources, on expenditures on health and nutrition by UN agencies in 1987, and on allocations for health and nutrition under child survival by USAID in 1988. Figures are generally available only for expenditures by international agencies and national or local governments (Mateus 1989 is an exception). Figures for private aAid NGO funding of nutrition interventions (which may be an important component for some countries) are not readily available. To supplement these data, country studies were undertaken for Chile, Malawi and the Philippines (Appendices A, B and C respectively).

The available data are reproduced and summarized here in table 11 (on expenditures by country) and table 12 (expenditures by UN agencies and USAID). Appendix tables 1 and 3 also contain additional information on the percentage of nutrition expenditures financed externally. One finding from tables 11 and 12 is that nutrition interventions account for only about 10% of expenditures on health (9% for Malawi, 10% fo- the Philippines, 11% for Brazil, 13% for UN agencies, and 15% for USAID child survival). Chile however is unusual in that its nutrition programs account for 35% of health expenditure. Nutrition expenditures as a share of GDP vary widely, from a low of 0.06 in the Philippines, to a high of 0.41 in Chile, with the other three countries in the table clustered at 0.16-0.18.

Mateus' data allow comparison of expenditures on feeding programs in 16 Latin American countries (table 11). Whilst these programs do not .ccount for all expenditures on nutrition interventions, they certainly are an impoartant and expensive component. The countries with large total (i.e. domestic plus foreign) expenditures on feeding programs are not necessarily the poorest. Although expenditures on feeding programs are large in Bolivia and Haiti, they are also large in Brazil, Chile, Jamaica, Mexico and Costa Rica which are better off, and small in (relatively poor) Peru. Poorer countries do tend to attract a higher proportion of external financing (Appendix tables 1 and 3). As regards domestic resources applied to feeding programs, the best performers are Chile,
20 followed by Brazil, Costa Rica and Mexico. Chile allots almost 0.5% of its GDP<sup>to nutrition, whilst</sup> the others allot 0.25% or more. Once external resources are added in, Bolivia,<sup>Haiti and Jamaica</sup> join the ranks of Latin countries with expenditures on feeding programs<sup>of over 0.25% of GDP.</sup> Three country studies were undertaken in order to try to supplement the rather<sup>meagre</sup> available data on financing of nutrition interventions. Data were generally available<sup>for these</sup> countries to estimate the contribution of central government and external funding,<sup>but not usually for</sup> that of local government.

For Chile (Appendix A), there are three major nutrition interventions (the National Supplementary Feeding Program, PNAC, for preschoolers, the School Lunch Program,<sup>PAE, and the</sup> National Association of Kindergartens, JUNJI, a daycare feeding program). Appendix table<sup>Cl</sup> presents information on expenditures on these programs from 1974 to 1988, and appendix tables C2 and C3 contain information on sources of financing. The preschool program (PNAC)<sup>obtains around</sup> a quarter of its funding from external donors (appendix table C2). The school feeding<sup>program</sup> (PAE) receives about 10% of its funding from municipal governments, and the rest from<sup>the central</sup> government, although the municipal share rose quite sharply in 1987 and 1988<sup>(Appendix table C3).</sup> Appendix table C4 presents some information on costs of different interventions, which<sup>show the</sup> relatively high costs of the daycare feeding program (JUNJI) compared to the other<sup>two. Further</sup> recent information on Chile's nutrition programs can be obtained from Muchnik and Vial (1990),<sup>and</sup> Castaneda (1990).

The Philippines (Appendix B) has a strong Institute of Food and Nutrition, domestic<sup>support</sup> for nutrition interventions, as well as long-established external assistance. It is<sup>quite surprising that</sup> nutrition expenditures are therefore not higher as a share of GDP (the World Bank figures<sup>cited in</sup> table 11 suggest that the Philippines allots a smaller percentage of GDP to nutrition<sup>than the other</sup> four countries with available data). Appendix table B1 lists in detail the different<sup>nutrition</sup>
21 interventions, by Ministry, expenditure level, and number of beneficiaries, and World Bank estimates of total nutrition and health expenditures are reproduced in Appendix table B2. About 90% of the financing for nutrition interventions is from central government, and 10% from local government (Appendix table B4). The central government contribution is divided into receipts from taxes (80% of the total expenditures on nutrition), with the other 10% contributed by central government coming about equally from user fees and from foreign contributions (Appendix table B4). As regards local government contributions, about three quarters is from city governments, with the rest from provincial governments. (Municipal governments contribute a very small amount: Appendix table B3).

Appendix tables B5-7 present some comparative cost information for USAID-supported programs. There are differences by operating agency: CARE tends to report higher costs than CRS (Catholic Relief Services), however CARE tend to document costs better than most other NGO's. Of the 3 intervention types (school feeding, MCH and food for work), MCH programs are the cheapest.

ARE reports the highest cost program is food for work, whereas CRS report the highest cost program is school feeding. Food for work and school feeding interventions cost 1.5-2 times as much as MCH programs. However once targeting is taken account of, they cost 4 to 6 times as much as MCH programs, per beneficiary with 2nd or 3rd degree malnutrition. Further information on programs in the Philippines is available in USAID (1982) and Aguillon (1986).

Data for Malawi are much more scanty. The majority of expenditures are financed externally. Domestic funding goes to the relatively new Food Security and Nutrition Institute, and as a contribution towards the WFP-financed feeding programs. Appendix table Cl presents information on WFP and UNICEF expenditures. There are few published sources describing nutrition interventions in Malawi, other than World Food Program project documents.
22

# VI. Summary.

This paper has tried to draw together a large amount of disparate information on costs, costeffectiveness and financing of nutrition interventions in developing countries. This final section summarizes what information was obtained, but does not draw specific conclusions.

Section I on methodology discussed the problems of the cost per death-averted measure, and raised the issue that this measure is not highly appropriate for nutrition interventions. Practical difficulties in measurement were also discussed, both problems in obtaining cost data, and the fact that impact data are so scarce.

Section II discussed how to standardize appropriately information on unit costs, and presented data on 52 feeding programs, 6 nutrition education programs (1 of which incorporated growth monitoring), 1 (hypothetical) breastfeeding promotion program, and 14 micronutrient fortification or supplementation programs. The costs of distributing 1000 calories per day per beneficiary per year was found to be about $75 for untargeted food rations (1 program), $64 for targeted food rations (median, 4 programs), $74 for MCH and school feeding programs (median, 52 programs), and $134 for highly targeted feeding programs (1 program) (all costs in 1988 US $). Costs of nutrition education ranged from $1-23 per beneficiary, and of breastfeeding promotion from $1-5 per beneficiary. Micronutrient intervention costs ranged from $0.04 to $4 per person-year of protection.

Section II also examined how program size, geographic location, operating agency, and type, affected unit costs of feeding programs. Program size does appear to matter, with the lowest costs being reported for medium-size programs. Location does not matter, except perhaps that programs in South Asia were slightly cheaper to run. There is no consistent difference between MCH and schoolfeeding programs, and between government-operated and NGO-operated programs. Externally financed programs might be somewhat more expensive, but this could not be fully investigated without better data.
23 Section III examined cost structure, and in particular the food/non-food breakdown for 81 feeding programs, 5 food subsidy programs, and I micronutrient intervention. Non-food costs account for about 17% of the total for targeted food rations (median, 4 programs), 25% for feeding programs (median, 81 programs), 20-34% in food for work programs (2 programs) and 29% for micronutrient supplementation programs (1 program). Non-food costs are lower in sub-Saharan Africa than in other regions, in medium-size programs, and possibly in NGO-operated programs. A summary table (table 8) highlighted some of the main findings of sections II and III, and compared them to the previous "received wisdom" on the topic.

Only limited information could be obtained on cost-effectiveness (section IV). A total of 8 estimates were available, 2 on cost per death-averted, 5 on cost per child removed from moderate or severe malnutrition (from which cost per death-averted could be extrapolated), and I on cost per case of blindness prevented (from which cost per death-averted was estimated). Data from the Narangwal project were also cited, on cost per death-averted for different age groups, for nutrition and medical interventions alone and combined. These figures are given in tables 9 and 10.

Section V on financing presented information on share of nutrition interventions in health budgets and GNP for 5 countries, and share in health budgets for 2 donor agencies. Information on expenditures on feeding programs was cited, for 16 Latin American countries. Information on the share of external financing was presented for 81 feeding programs. Three country studies were undertaken, providing somewhat fragmentary evidence on local versus central government funding. In general nutrition expenditures seem to account for about 10% of the health budget, both for individual developing countries, and for external donors. The share of nutrition expenditures in GDP had a median of 0.16% of GDP. About 90% of domestic nutrition finance seemed to come from central government, and 10% local government. External finance accounted for a larger share of nutrition expenditures in poorer countries.
24 More work is needed to improve data on costs, impacts and financing. An urgent priority is to obtain some project cost data for breastfeeding promotion (none is available). More work on the impact of project design could fruitfully be done using standardized project proposals or reports (in particular WFP proposals, USAID PVO Child Survival data and USAID Outreach grant data seem promising). Work could be done on project scale using service-delivery-unit level data (anghanwadi level data for the ICDS in India might be promising). More work could be done disaggregating components of costs (in more detail than the food/non-food breakdown used here). Again, WFP proposal documents might be a useful starting point. Many existing agencies could improve their record keeping, both with respect to standardized cost treatment, and with regard to recording estimates of impact. Better cost data need not involve much additional resources, but better impact data would. Nevertheless, better data are important so that important nutritional interventions are not de-emphasized in child survival initiatives relative to health interventions whose benefits are more easily quantified.
25 Table 1 Unit Costs of Education-Type Interventions

|Country|Cost/Beneficiary|Comments|Source|
|---|---|---|---|
||Nutrition Educ|ation||
|Morocco|$1- $3|monthly class:<br>additional to<br>MCH program|Hornick(1985)|
|Indonesia|$2|mass media<br>component of<br>MCH program|Hornick (1985)|
|Honduras|$2.50|mass media<br>effort on ORT|Hornick (1985)|
|Philippines<br>(Manoff)|$3.33|mass media<br>efforts to<br>add oil to<br>weaning food|Hornick (1985)|
|Burkina Faso|$0.22|volunteers<br>taught mothers<br>to prepare<br>weaning foods|Heimendinger,<br>et al. (1981)|
|Dominican Republic|$23.17|combined with<br>growth monitoring<br>community workers<br>receive only<br>token wages|USAID (1988)<br>:|
||Breastfeeding Pro|motion||
|Hypothetical<br>NOTE: costs are in cur|$1-$5<br>rent dollars.|no program data<br><br> <br><br>|Phillips,<br>Mills and<br>Feachem<br>(1987)|
26

# Table 2

# Unit Costs of Targeted Food Subsidies

|Country|Energy<br>Transfer<br>Cal/Day|Cost '000<br>Cals/Person/<br>Day/Year<br>in 1988SUS|Program<br>Food as X<br>Type<br>Total Cost|Operating<br>Agency|Source|
|---|---|---|---|---|---|
|Brazil (PINS)|300|86.41|regionally<br>83'<br>targeted<br>subsidy|gov't (WB loan)|_Th5t4_<br>**hre#n**<br>(1988)|
|Colombia<br>(coupons)|---|...|coupons<br>63'<br>targeted<br>via MCH system|gov't||
|Egypt|626|74.68|untargeted<br>--<br>ration shops|gov't||
|Mexico|95g<br>248'|172.72|milk subsidy<br>74^<br>geog. targeted<br>to children<br>and PLF|gov't||
|Philippines|2726<br>454'|36.01|geographically<br>86'<br>targeted oil<br>and rice subsidy|gov't||
|Sri Lanka|228|42.34|food stamps<br>--<br>(income targeting)|gov't||
|Jamaica|---|---|food stamps<br>88b<br>(income targeting)|govt: (USAID<br>assistance)||

Notes

- a: Source: Berg (1987).

- b: Source: Margaret Grosch (personal communication): estimate only.

- c: assuming all household members were intended beneficiaries.

- d: assuming only certain household members were intended beneficiaries.
27

# Table 3 Unit Costs of Peeding Programs (MCH ind School Feeding) Costs in USS of 198

|Categorv|Range|Median|<br>Mean|Number of Programs|
|---|---|---|---|---|
|All Programs|19.25- 300|74.48|88.51|52|
|Asia<br>|32.1- 300<br>|70.01<br>|91.29*<br>|<br>21|
|North Africa<br>|65.53- 104.7<br>|87.34<br>|88.63<br>|5|
|Sub-Saharan Africa<br>|55.80- 96.25<br>|81.46<br>|78.95<br>|5|
|Latin America|19.25- 272.54|67.18|87.96|21|
|School Feeding<br>|19.25- 208.59<br>|81.46|88.74|11|
|MCH|26.75- 272.54|73.84|85.64|37|
|Small(<br><100,000)<br> <br>|26.75 - 272.54<br> <br>|96.48<br>|121.92<br>|7|
|Medium (1<br>500,000)<br> <br>|24.38-<br>96.25<br>|68.11<br>|62.99<br>|10|
|Large_(_<br>2 500,000)|19.25- 139.0|96.90|89.85|7|
|Gov't. Operated<br>|19.25- 272.54<br>|75.11<br>|91.73<br>|37|
|NGO Operated|24.38- 300|77.98|89.70|14|

Source: Calculated from Appendix Table 1.

Notes:

* Falls to 80.32 for South Asia only. Costs are in $ of 1988, cost per '000 calories/day/year
28 Table 4. Unit costs of micronutrient interventions.

|Iodine|Country/Year|Cost per<br>Person<br>(US $)|Estimated<br>Cost<br>per Person<br>(1987 US S)|Estimated<br>Cost per<br>Person per<br>Year of<br>Protection<br>(US S)|
|---|---|---|---|---|
|Oil inj.'|Peru 1978|1.30|2.30|.46|
|Oil inj.'|Zaire 1977|0.35|0.67|.14|
|Oil inj.'|Indonesia 1986|l.00/inj|1.05|.21|
|Water fort.'|Italy 1986|0.04|0.04|.04|
|Salt'|India 1987|0.02-0.04|<br>0.02-0.04|.04|
|Oil irLj.<br>2|Bangladesh 1983|0.70|0.76|0.25|
|Vitamin<br>A|||||
|Sugar fort.'|Guatemala<br>1976|0.07|0.14|.14|
|Capsule'|Haiti 1978|0.13-0.19|<br>0.23-0.34|.46-.68|
|Capsule'|Indonesia/<br>Philippines 1975|0.10|0.21|.42|
|Capsule<sup>2</sup>|Bangladesh 1983|0.05|0.05|0.05|
|Iron|||||
|Salt fort.'|India 1980|0.07|0.10|.10|
|Sugar fort.'|Guatemala 1980|0.07|0.10|.10|
|Sugar fort.'|<br>1980|0.60|0.84|.84|
|Tablets'|1980|1.89-3.17|<br>2.65-4.44|2.65-4.44|

# Sources:

1. Levin et al (1990)

2. Mills (1983)
29 Table A Administrative Costs of Selected NGO Feeding Programs

|Country|Dperating Agency Non-food<br>Num<br>Cost\Beneficiary|ber of Beneficiaries|
|---|---|---|
|Benin|CRS<br>28.33|53,000|
|Ghana|ADRA<br>13.10|41,000|
|Sudan|ADfA<br>76.11|20,000|
|Average, 3 African<br>Programs|---<br>31.24|---|
|Bolivia|ADRA<br>3.24|1,035,300|
|n|CRS<br>1.67|401,100|
|of|FHI<br>17.57|53,100|
|Haiti|ADRA<br>10.39|108,500|
|Average, 4 Latin<br>American Programs|---<br>3.24||

Source: Robert R. Nathan Assoc. Inc. (1987).

Programs were those which applied for a USAID Outreach grant in 1987. Costs are in US $ of 1987
30 Table 6 Food Cost as Percent of Total Cost. Poeding Programs: Summary

|Category|Range|Median|Mean|Number of Programs|
|---|---|---|---|---|
|All Programs|11-95|75|69.7|81|
|Asia|22- 95|76|74.4|26|
|North Africa|(69 -92)|(v-)|(80.5)|<br>2|
|Sub-Saharan Africa|80- 90|84|84.4|5|
|Latin America|11-<br>90|71|65.1|48|
|School Feeding|25- 95|71|71.5|19|
|MCH|11- 95|63|68.4|39|
|Small(<br><100,000)|43- 90|79.5|74.5|6|
|Medium (1- 500,000)|58- 90|85|82.0|8|
|Large(<br>2 500,000)|31- 92|69|70.7|7|
|Gov't. Operated|11- 95|77|70.4|67|
|NGO Operated|54- 90|74.5|77.3|14|
|[Targeted Food<br>Subsidies|63- 88|83|78.8|5]|
|[Micronutrient<br>interventions|29|||11|

Source: Calculated from Appendix Table 1 (excluding references from Mateus) and Appendix Table 2 (including references from Mateus).

Food costs include external transport where applicable.

Food costs bracketed in appendix are not included in the calculation. Micronutrient data from iodine program in Bangladesh, Mills (1983).
Table 7 Costs of **Some** of Brazil's Nutrition Programs. **1978-80**

|**Proexaw**NaMe<br>PNS Model A|Descrintio<br>Food As %<br>Total<br>Cost<br>Food distribution<br>25|Unit Cost<br>(cruzeiro<br>per<br>kgi|UnitCost<br>C<br>(cruzeiro<br>per<br>000cals)|ost/Beneficiary/Year<br>(cruzeiro)|
|---|---|---|---|---|
|<br>PNSModel B|<br><br>via health posts<br>73|10- 27|2.8- 8.0|595*|
|PCA<br>PINSModel A|Distribution of<br>86<br>special weaning foods<br>Food subsid<br>91|100<br>37|22-26<br>|1,460*|
|<br>PINS Model B<br>PINS Model C|y<br> <br>experiment<br>66<br>67|<br>33<br>83|10<br>9<br>|*|
|<br>PINS Model D|<br>80|<br>22|23<br>|29|
|<br>PINS Average|<br>--|<br>31|6<br>9||

Source: Musgrove (19X9). Conversion to cruzeiro/kg by author using data in Musgrove (1989). The PNS program distributes food via health posts. Model A includes the cost of complementary health services, B excludes them. The PCA distributes food via community centres. The PINS operated a subsidy experiment, Model A had a 60% subsidy, B a 45% subsidy, but participants had to undertake regular monitoring to be eligible. Version C had a 45% subsidy, Version D a 30% subsidy.

*Note, these data are not standardized by size of ration. PCA provides a smaller quantity of food.
32

|Table 8<br>Summary of costs by|different tvDes of|food distribution programs|
|---|---|---|
|From Mateus (|l983)|From present paper|
|ProgrsmTVDO<br>$/'O0O Calories/<br>Beneficiarv|Non Food Costs<br>AsXTotal|$/'000 Calories/<br>Non Food Costs<br>Day/Year/Beneficiary<br>As X Total<br>In 1988 US S|
|1. Untargeted<br>food subsidies<br>500-600|(very<br>low)|-|
|2. Untargeted<br>food rations<br>50-120|20-30|75^<br>-|
|3. Targeted<br>food rations<br>-<br>(geographic/self<br>targeting)|20-30|36-172b<br>14-26b<br>164<br>117|
|4. Food coupons|||
|- income targeting<br>60-180|2-5|42c<br>12-37d|
|- health status<br>60-120|2-5||
|5. Feeding programs<br>- MCH and school feeding<br>80-200|10-30|74<br>25'|
|- mostvulnerable<br>group<br>80-150<br>targeting|10-30|134'<br>71'|
|6. Food for work<br>-|-|-<br>20-34b|

# Notes and Sources:

- a. Egypt: Table 2.

- b. Brazil, Mexico, Philippines: Table 2.

- c. Sri Lanka: Table 2.

- d. Colombia and Jamaica: Table 2.

- e. Median, 52 programs: Table 3. f. Median, 81 programs: Table 6.

- g. Tamil Nadu: Appendix Table 1: note non food costs fall to 56 per cent of health component is excluded: targeting is based on growth monitoring.

- h. Bangladesh: Mills (1983). He argues higher figure is from program with better data, and therefore more accurate.
# 33

|Tab|le9<br>Cost-ef|fectiveness<br>of Nutri|tion Interventio|ns: Program Da|ta|
|---|---|---|---|---|---|
|Intervention and|Cost per<br>|Cost per<br>|Cost per|||
|<br>Country<br>l|death<br>averted|malnutrition<br>averted'|blindness<br>averted|Date|Source|
|Suppementary feeding<br>Tamil Nadu|1482|||||
|||33|--|1982|Ho (1985)|
|Targeted food subsidy<br>Philippines||||||
|Micronutrient suRplementat|--<br>ion|331|--|1982|Kennedy<br>and<br>Alderman<br>(1987) calculated from<br>Garcia<br>and<br>Pinstrup-<br>Andersen (1987)|
|<br>Bangladesh|<br>1522|||||
|||--|350|1983|Mills (1983)|
|Nutrition education<br>Dominican Republic|--|||||
|<br>Indonesia NIPP||493<br>|--|1984-6|USAID<br>(1988: excluding<br>TA costs)|
|Morocco|--|12<br>|--|1983?|Hornik, 1985|
|||5||1980?|Hornik, 1985|

'Cost per child removed from moderate or severe malnutrition.
34 Table 10. Cost-effectiveness of nutrition, health and combined interventions. Narangwal. India.

|Awe|||TyRe of interve|ntion|
|---|---|---|---|---|
||Nutri<br>only|tion<br>|Nutrition+<br>Medical care|Medicalcare<br>only|
|perinatal||570<br>(74)|710<br>(92)|1,010<br>(131)|
|infant (<1)||1,640<br>(213)|1,800<br>(233)|1,110<br>(144)|
|child (1-3)||23,540<br>(3,053)|31,030<br>(4,025)|7,690<br>(997)|

Source: Taylor et al (1984). Costs are in Rupees of 1971, wi,.h US $ amounts in brackets. To convert to US $ of 1988, multiply by 2.45.
35

# Table 11 Expenditures on Nutrition Programs. Selected Countries

|Country|Year|As X<br>Health<br>Budzet|Domestic<br>Contrib.<br>as X GDP|Total<br>Exp.<br>as X GDP|Source|
|---|---|---|---|---|---|
|Brazil|1986|10.8|0.18|-|Musgrove (1989)<br>World Bank Docs.|
|India- state govt<br>-<br>central govt|1986-7|<br>1.86).<br>0.5)|0.16|-|Subbarao (1989)|
|Chile|1988|34.8|0.41|-|Author's<br>calculations|
|Malawib|1988|8.5|0.16|0.56||
|Philippines|1985|10.0|0.06|-||
|MCH and School Feeding<br>|Program<br>|s Only||||
|Brazil|1987|--|0.27|0.27|Mateus (1989)|
|Bolivia|1987|--|0.18|0.52||
|Chile|1987|--|0.53|0.57||
|Costa Rica|1987|--|0.29|0.29||
|Dominican Republic|1987|--|0.12|0.15||
|Ecuador|1987|--|0.19|0.22||
|Guatemala|1987|--|0.04|0.14||
|Haiti|1987|--|0.01|0.41||
|Honduras|1987|--|0.02|0.16||
|Jamaica|1987|--|0.10|0.30||
|Mexico|1987|--|0.24|0.44||
|Panama|1987|--|0.03|0.01||
|Paraguay|1987|--|0.06|0.09||
|Peru|1987|--|0.02|0.04||
|Uruguay|1987|--|0.17|0.17||
|<br>Venezuela|1987|--|0.13|0.13||

# Notes

- a X of government budget.

- b domestic contribution to WFP project only
36

# Table 12. ExRenditures on nutrition interventions. UN agencies and USAID.

<!-- Start of picture text --> Agency S Spent an $ Spent on<br>Direct Nutrition Health<br>UN Agencies: FY 1987<br>FAO 450,000<br>UNICEF 31,660,000 165,000,000<br>WHO 6,800,000 138,000,000<br>UNDP 180,000 2,072,000<br>TOTAL UN AGENCIES 39,090,000 305,072,000<br>USAID FY 1988<br>USAID Child Survival 26,000,000 170,000,000<br><!-- End of picture text --> Source: reproduced from Huffman and Steel, 1990.

Direct nutrition is defined as projects having a direct impact on the nutrition status of the individual. Examples include direct feeding projects, growth monitoring and nutrition surveillance. Not included are health or food security.
37

||||A_oendi|2ableI|Unit<br>Costs<br>of|Weedina Programs<br>|(School<br>Feedlna|*ndMM)2|||
|---|---|---|---|---|---|---|---|---|---|---|
||Ration|_hzi_|Cost'000CaL<br>lyF (1988 SUS|s<br>Number of<br>)a BeneficiarLes|Pcogram<br> <br>T. De|Food**as**I<br>TotalCostb|I Cost<br>Total<br>Cost<br>Estetnally<br>Financed|Funding<br>Agency|Operating<br>-Agenc|Source|
|Indle-Posbak<br>(-atens';,<br>)<br>|400<br>|365<br>|60.51|--|wC|77|--|-|Cov't|Seaton<br>and<br>Chassemi<br>(1979)|
|Morocc,|774|365|87.34|__|MCD|__|__|USAID|CRS|e|
|Sri La'ka|185|365|97.16|--|MCD|60|--|USAID|CARE||
|Tunisia|560|300|88.69|--|NCR|--|--|USAID|CR5?||
|IndLa (SUP)<br>(Andhra<br>Pradesh)<br>|300<br>|300|70.01<br>|--|MCd|75|--||Cov't||
|NMeangual<br>|400<br>|120|76-106<br>|--|MCH|--|--||G<br>Cov't|Ohassemi(1989)|
|Fhiltppines<br>|400<br>|90<br>|232-369|--|7|__|__|USAID|||
|Morocco<br>|526<br>|365|65.53||MG<br>MCH|--|--|USAID|CRS||
|SrlLanka<br>|190|365|32.21|--|I|--|--|USAID|CARE?||
|India (ICDS)<br>|330|365|66.67|--|MCD|--|--|WFP|Cov't||
|til_<br>Nadu<br>**Midday Meals**<br>|418|200|67.02|--|SF|75|--|-|Covt|Inudsent<br>(1981)|
|_Tmtl Nadu_SUP<br>|||||||||||
|Modifled<br>|347|300|52.57<br>|--|MCR|95|--||*||
|tinLlNadu SUP|--|--|69.55|--|MCH|95|--|-|*||
|t<br>S|282|300|71.61|--|NCd|87|--|-|||
|Tamil "t<br>tochild<br>|--|-|60.49|--|MCH|94|--|-*|||
|NlddayMeals Madras|418|--|132.47|--|SF|95|--|-|||
|TamilNadu<br>|280<br>|--|65.14<br>|--|MCH<br>|91|--|-|||
|balwadles aon-ANP<br>|296|__|114.44|__|MCH|94|--|-|||
|TamilNadu<br>AMP<br>|397|--|73.84|--|MCH|80|--|-s|||
|Bolivia (4)|150|365|52.48|na<br>8CH||81|_|ME?|Gov't<br>O|Msteusd<br>(1989)|
|Do.nican Rtcublic<br>tc4mpteme cay coeding|490<br>)|365|67.18|92,000|MCH|82|||Cov't||
|Costa Rlc- (2 progs)|240|365|272.54|67,500|MCH|82|--|-|Cov t||
|Ecuadoc (2 progs)|498|365|89.16|550,000|MCH|82|||Cov't||
|Guatemala-<br>CARE|625|365|28.90|286,000|MCH|90||US-ID|CARE||
|**Guatemala**-<br>UFP<br> <br>|891|365|55.19|35,000|MCH|72||WEP|Cov't||
|Honduras<br>(3progs)|1286|365|26.75|(e4,0O00)|MCH|90|-r||t Iv<br>tady||
|**Paraguay**|684|365|96.48|33,000|mCII|83|||Cov't||
||||||38||||||
|---|---|---|---|---|---|---|---|---|---|---|
|Country|Ratlon|Days|Cost/'000 Cals<br>_ITC_(1988<br>SUSi|Nummbe of<br> <br>8eneficiaries|Prostm<br>Ty"e|Food as X<br>Total<br>Cost|ZCost<br>Total<br>C0ot<br>Eaterna<br>lly<br>Financed|Funding<br>Aaency|Operating<br>Asency|Souree|
|Bolivia (4 pross)|325|165|53.53|-s<br>laf3|SF|82|--|USAID|moO|mateusd(1989)|
|**EcuAdor**<br>(collacclon)|365|165|61.10|200,000|SF|84|||G<br>Cov't||
|Custemala|456|165|19.25|1,093.000|SF|49|--||Gov't||
|**Hbnduras**<br>(2 pros.)|180|165|24.38|MM3|SF|71||USAID|CARE/EEC||
|Paraguay|324|165|208.59|76,493|SF|25|--|_|Gov't||
|**El**SaLvador 2317|1300|182.5|<br>75.11|164,250|**NCM**|58|57|**WFP**|Gov't|**Wppe**documents|
|**Gambia**625|858|196|81.46|376,202|SF|90|93|_4VFP-_|Cov't||
|**Horocco**2288 Exp II|900|140|96.90|1,024.350|SF|69|56|UFP|Gov't||
|**Somalia**<br>2349 Exp 1<br>Exp II|734<br>719|335<br>280|96.25<br>86.21|270,000<br>496,000|refugee, MCM<br>and141 SF|84<br>30|81<br>83|UFP<br>FPG|Gov't<br>Cov't||
|Tunisia<br>3408|843|120|104.70|775,400|Sr<br>|92|66|WFP|Gov't||
|Nepal3718|622|293|56.50|377,650|**WHI**3i|86|93|WFP|Gov't||
|BraaLl 3242|1265|313|44.79|160,000|MC0|8l|14|WFP|Gov't||
|Malawt<br>Exp II|668|365?|75.20|258.112|7<br>C+ho pit.i)|<br>87|74|WFP|Gov't||
|Exp III|733|365?|55.80|506,495|g|81|69|UFP|Cov't||
|India SNPIICDS 2206<br>Exp IV|386|270|115.18|2,120,000|MCH<br>|67|67|WFP|Cov't||
|Paraguay 2376 Exp 11|307|224|139.0|736,200|VFH3III|65|63|-WFP|Gov't||
|Bolvia 2795|1175|200|126.7|70,500|SF|77|73|WFP|Gov't||
|Colombia|305|365|130.93|--|MCH TH|54|49|USAID|CARE|Anderson (1977)|
|Costa<br>Rica|959|200|159.06|--|ECH SUPE|74|94|-|CARE||
|Dominican<br>Repubilo|337|165|63.92|--|MCH TR|77|29|-|CARE||
|India|340|200|68.62|--|HCH SUPE|75|39|-|CARE||
|Pakistan|298|365|127.29|--|MCH TH|70|6|-|CARE||
|Brazil PROAPE|500|365(?)|<br>112.98|--|MCH|44||11<br>us|Gov't|Pinstrup-Anderson<br>(1988)|
|India<br>**TamLil**Nadu|300|365(7)|<br>134.10|--|MCH|29||WB|Cov't||
|Indonesia HIPP|--|--|--|--|MCH|Sl|-B||Cov't||
39 Notes

# **a)**

Unit costs source. February All costs 1989, OffIce, per recipLent were transferred 1989. per '000 calorLes Washington: to US daily S US Government Printing of 1988 using for a year vere calculated the producer Office, pice 1989.using index of consumter foods information on costs per recipLent, from Economic teport cation sLze of the President: and number of feeding transmiLted days to Congress in original b) Foo4 costs Irclude external transport costs where appicable.

- c) ehLaugse rate from IPF InternatloQal Financial Statistics was used to convert from Rupees to US $ of 1976-7. d) For data approxImately In Mateus the _same_ (1989) adminLstrative for aLl MCM-type programs costs vere within only avaLlable one country, for and for several aLl program school feeding combined within programs each cuunrry. within one country.It was assumed that admLnistrative costs were

- **a)** Data on bFP programs were calculated by this author from W?P documents. Pon-recurrent costs In UFP budgets oere excluded.

S School feeding.
40

# ARpendix Table 2:

# Food as % of Total Costs of Feeding Programs

|Country|Operating<br>Agency|Numbe<br>Benef|r of<br>iciaries|Program<br> <br>Mepe|Food As<br>Total Co|%<br>Source<br>st|
|---|---|---|---|---|---|---|
|India Special Nutrition Program<br>|Gov't.||-|MCH|77|Sahn (1980)|
|India- Poshak<br>-exploratory hase|||||||
|p<br>-extensive primar health ntr|||||(42)n<br>||
|y cee<br>-extensive secondar hlth t|||||79<br>||
|y ea cenre<br>-<br>intensive tk-hm||||**n**|(76)<br>||
|aeoe<br>-<br>intensive suervised||**n**|||(42)<br>||
|p||||**i**|(35)||
|India<br>|CRS||||89|n|
|India: Indo-Dutch project for child|n.a.||-||79||
|India ICDs<br>-rural|'||||||
|<br>-<br>tribal|Govt.||-||66<br>|_n_|
|<br>|||||69|n|
|India: Child care nutrition centre|n.a.||-||56|n|
|India: Kasa MCHN project|n.a.||-|"|22|n|
|Brazil<br>-MCHN|'||||||
|<br>-<br>PCA|Govt.<br>||--|MCH<br>|51<br>|Mateus (1989)|
|<br>-<br>PSA|t|||n|551<br>|n|
||||-n||51||
|Bolivia|Several P|VO's|--||81||
|Chile|Cov't.||-|"|82||
|||41|||
|---|---|---|---|---|
|Costa Rica|_n_|67,500||82|
|Dominican Republic||--||82|
|Ecuador|n|550,000||90|
|Guatemala|CARE<br>WFP|286,000<br>35,000|n<br>n|90<br>72|
|Haiti|CARE|- -||55|
|Honduras|Gov't.|3 Programs<br>each about<br>40,000||90|
|Jamaica<br>|Gov't.?|<br>--||78|
|Mexico<br>- DIF<br>IMSS|Gov't.|--|MCH|62<br>|
|- <br>||--||63<br>|
|-<br>SSA<br>|.,|||63|
|- Liconsa||--|**"**|76|
|Panama<br>-MCHN|CARE<br>'|--|n|71.<br>|
||Govt.|--||43|
|Paraguay<br>|Gov't.|33,000||83|
|Uruguay<br>- MCHN<br>|Gov't.|21,000|**"**|11<br>n<br>|
|- MSP<br>||||31|
|- PNCA<br>|"|592,000|"|50<br>|
|- AIPP|,,||,|50|
|-<br>ACAM<br>Venezuela|**"**<br>Gov't.|-i-|n|50<br>45|
|||42||||
|---|---|---|---|---|---|
|Brazil|Gov't.|<br>--|School<br>Feeding|51||
|Bolivia|Severa|l NGO's<br>**-i-**||82||
|Chile|**Gov't.**|<br>--|**"**|78||
|Costa Rica|n|||74||
|Dominican Republic|n|-|school<br>**feeding**|81||
|Ecuador||2 Programs:||||
|||200,000||84||
|||128,000|n|84||
|Guatemala|'|1,093,000||49||
|Honduras|CARE|2 Programs:||||
||+ECC|300,000<br>|**"**|71<br>|**t**|
|||294,000|n|71||
|Jamaica|Gov't.|<br>**--**||78||
|Mexico<br>||||||
|- INI<br>|Gov't.|||55<br> <br>||
|-<br>PIF'<br>-<br>**PIF**|**"**<br>*-|-|~~~~~|61<br>~~n<br>**61**||
|Panama|.|||71||
|Paraguay||76,000|<br>**"**|25||
|Uruguay- PNCA|**"**|126,000|'|**(unilikely)**||
|Vernezuela||-|.|82||
3 3 _-

* l~~~~~~~~~~~~~~~~~~ ~~~_ S

# Appendix Table 3:

# Per Cent of Program Cost Financed<sup>Externally</sup>

|Country|Program Type<br>% Cost Financed Externally|
|---|---|
|Brazil|MCH<br>0<br>SF<br>0|
|Bolivia|MCH<br>88<br>SF<br>18|
|Chile|MCH<br>6<br>SF<br>5|
|Costa Rica|MCH<br>0<br>SF<br>0|
|Dominican Republic|MCH<br>20<br>SF<br>20|
|Ecuador|MCH<br>69<br>_SF_<br>88|
|Guatemala|MCH<br>69<br>SF<br>49|
|Haiti|MCH<br>98|
|Honduras|MCH<br>90|
||SF<br>71|
|Jamaica|MCH<br>50|
||SF<br>88|
|Mexico|--<br>61|
|Panama|MCH<br>64|
||SF<br>70|
|Paraguay|MCH<br>71<br>SF<br>25|
|Peru|MCH<br>63|
|Uruguay|MCH+SF<br>0|
|Venezuela|MCH+SF<br>0|

Source: Mateus (1989).
-44-

# Appendix A: Summary of main interventions in Chile.

Appendix tables Al to A4 provide some information on costs and financing, and a brief description of the main programs follows.

# 1. National SuRRlementary Feeding Program (PNAC)

-Started in 1937, this is the oldest program, and has the largest number of beneficiaries. Around 1.2m children under 6 are covered (80% of infants under one year and 70% of 2-5 year olds). Pregnant and lactating mothers covered also.

- The supplement is distributed via public health system and varies by age and nutritional/health status. Rations are provided on a monthly basis. E.g. 0-5 month olds receive 2kg of 26% milk per month in the basic program.

- To promote targetting of poor income groups, the service was linked formally to primary health service in 1980. This has kept down administration costs. Food costs represented 98% of budget in 1989.

- Finances come from the Ministry of Health, Central Government, and Municipalities. The latter must finance transport and distribution of food via the primary health care facilities. Project costs are linked closely with food prices and supply. Costs per beneficiary vary significantly between groups.

- Substantial leakage to high income groups occur through the basic program. Further targeting will be required to avoid this.

# 2. Corporation for Infant Nutrition (CONIN)

Established by INTA (National Nutrition Institute) in 1975 to provide inpatient care for infants suffering severe malnutrition. 80% of funding comes from the central government, 20% from private sources via INTA. Infants are identified through the National Health Service nutrition surveillance system. In 1985 cost per beneficiary was approximately US$600.

# 3. Colocacion Familiar para Ninos Desnutridos (COFADE)

Children in Metro Santiago suffering from 2nd and 3rd degree malnutrition are placed with a foster family. The family is given US$46 per month(1987) to help care for the child. Funds come from the municipality (of Santiago) involved (40%) and from the Health Service Area (60%) (Min. of Health Budget). 150 children served per year- very low cost program, especially when compared to CONIN.
45

# 4. Junta Nacional de Jardines Infantiles (JUNJI)

- Formed as an autonomous body in 1970 to provide a comprehensive daycare program for pre-school children in urban areas. A complementary feeding program is an integral part of the project

- The day care facility operates M-F 8:30 a.m.- 5:30 p.m. all year except February, and nursery care is provided for 0-2 yr olds, mid level care for 2-4 yr olds, transitional level for 4-5 yr olds. Language, psychomotor and social skills are developed.

-

This program is the most expensive on a cost/beneficiary basis:

||1986|1989|
|---|---|---|
|personnel|54%|60.35%|
|food|35%|31.9%|
|other|10.9%|7.8%|

Cost/beneficiary is around US$418 due to high salarieR of university trained pre-school teachers.

- Total coverage is below need. 45% of children enrolled in JUNJI were in the greater Santiago metropolitan area. Poorer regions and rural areas receive much less help. In 1987, 59% of pre-school subsidies went to families in the two lowest income quintiles (22% went to the two upper quintiles)

# 5. Centros de Alimentacion v Estimulo (CADELI

In response to the high cost and inadequate coverage of JUNJI, Centros de Alimentacion y Estimulo were established in 1987 it: urban neighborhoods.

- Community based approach with volunteers from the neighborhood. Services are offered half day only. Lunches and snacks provide about 750 cal. per day (50% of average dietary requirement). CADEL centres average about 30 children each, there are about 360 of them in most urban and semi-urban areas. Food costs represent 75% of CADEL expenditures.

# 6. Other Preschool Proarams

-Private non-profit agencies such as CARITAS and FNACO operate day care programs. FNACO assists about 45,000 children per year, and CARITAS and JJII (Fundacion Jardines Infantiles) about 37,000 children per year.

# 7. Proorama de Alimentacion Escolar (PAE)

- Provides free lunches and a breakfast or snack to poor children between the ages of 6 and 14 attending public and private primary schools, and all
46

# students in rural residential primary and secondary schools.

- Means tested system ueed to target beneficiaries, based on<sup>family income,</sup> mother's education, teacher's opinion, nutritional status, etc.

- 189 davi coverage, and additional summer coverage for<sup>low income</sup> children (Jan/Feb). About 700 calories and 20g protein (33% ofRDA of protein/calories) are provided each day. Daily participation<sup>rates fluctuate</sup> depending on enrollment and socioeconomfic level of region. 57% of students enrolled in eligible rural schools are served, and 28% in urban eligible schools:

1988 1985 Beneficiaries 610,714 616,526 (534,465 exc JUNJI)

- Cost per beneficiary (per year) is around US$19 for breakfast and<sup>US$51 for</sup> lunch (US$70 for a full ration). 85% of budget is allocated<sup>to food costs.</sup> Municipalities usually fund just under 10% of the program.

Sources: Muchnik and Vial (1990), World Bank unpublished<sup>documents, Castaneda</sup> (1990).
47

# An2endix table Al. Chile: annual expenditures on nutrition intervention Droarams. umillion 1987 Us S

|YEAR|PNAC|PAZ|JUNJ1I(CADELincluded<br>after<br>1987)|TOAL|
|---|---|---|---|---|
|1974|35.4|-|6.4|-|
|1975|36.2|-|5.1||
|1976|36.4|-|6.5||
|1977|43.1||10.8||
|1978|36.9|35.8|19.2|91.9|
|1979|40.1|37.3|19.7|97.1|
|1980|29.3|38.7|17.1|85.1|
|1981|36.3|44.7|16.8|97.3|
|1982|37.9|43.0|17.9|98.8|
|1983|29.7|43.8|16.9|90.4|
|1984|47.9|46.7|16.0|110.6|
|1985|42.1|47.6|17.0|106.7|
|1986|35.9|43.1|18.2|97.2|
|1987|44.0|34.4|17.2|95.6|
|1988|42.7|31.5|19.8|94.0|

Source: Muchnik and Vial (1990)
48

# A&Mendix table A2. **Chile: sources of cntral governMent expenditures**

# on PNAC (million 1986 **Us S$**

||BUDGET FROM<br>MINISTRY AF<br>ABMT|FOREIGN<br>DONATIONS|TOTAL<br>BUDGE|
|---|---|---|---|
|1978|35.0|n.a.|n.a.|
|1979|38.1|n.a.|n.a.|
|1980|27.8|n.a.|n.a.|
|1981|34.5|n.a.|n.a.|
|1982|35.9|n.a.|n.a.|
|1983|28.2|n.a.|n.a.|
|1984|35.1|10.3|45.4|
|1985|29.7|10.3|40.0|
|1986|26.1|9,.0|35.1|
|1987|38.5|3.2|41.7|
|1988|31.1|9.8|40.9|

- not including municipal expenditures

- 1986 period average exchange rate used - Ch $193.016:US $1.00

- Source: World Bank unpublished documents
49 A,oendix table A3. Chile: Financing of school feeding grooras **(PAB).** (1988 US$m) <!-- Start of picture text --> Year Central Govt Municipal Govt<br>1981 47.3 0.5<br>1982 41.4 4.6<br>1983 43.7 5.7<br>1984 45.3 5.0<br>1985 47.7 4.1<br>1986 44.0 5.6<br>1987 34.7 7.5<br>1988 34.9 8.6<br><!-- End of picture text --> Based on CH$245.048: US$1.00 Source: World Bank unpublished documents

# Appendix table C4. Cost ver beneficiary and ver calorie of maior interventions.

|PROGRAM|Total<br>Annual<br>Cost (USSM)|K Cal.<br>Delivered<br> (Million)|**_I_**of<br>Benef.<br> ('000)|Cost/Ben<br>per year<br>(USS)|Cost/Kcal<br>(US cents)<br>_|Cal/Benef<br>per day<sup>1</sup>|
|---|---|---|---|---|---|---|
|PNAC|39.7|135,457|1,042.0|<br>38.1|0.0293|130.2|
|PAR|35.0|80,244|557.3|<br>62.8|0.0436|394.0|
|JUNJI|16.0|10,571|55.9|300.0|0.1510|518.0|

I Average calories received per beneficiary per day, assuming the total amount of calories provided were distributed in 365 days. Sources Muchnik and Vial (1990).