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Article

Enhancing Nutrition and Cost Efficiency in Kenyan School Meals Using Neglected and Underutilized Species and Linear Programming: A Case Study from an Informal Settlement

1
School of Human Health Sciences, University of Florence, Largo Brambilla, 3, 50134 Florence, Italy
2
Food Environment and Consumer Behavior, Bioversity International, Via di San Domenico, 1, 00153 Rome, Italy
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(6), 2436; https://doi.org/10.3390/su17062436
Submission received: 21 January 2025 / Revised: 17 February 2025 / Accepted: 1 March 2025 / Published: 11 March 2025
(This article belongs to the Section Sustainable Food)

Abstract

:
Neglected and Underutilized Species (NUS)—locally available, climate-resilient species—possess significant nutritional, social, and environmental benefits, yet their use, research focus, and market presence have diminished over time. Incorporating NUS into school meal programs can potentially boost childhood nutrition, promote healthy eating, encourage sustainable food production, preserve food culture and heritage, and support biodiversity conservation. School meals offered in Kenya are often monotonous and nutritionally inadequate. We conducted a case study on a school in an informal urban settlement in Nairobi, targeting students between ages 6–12, to demonstrate how incorporating locally grown, nutrient-dense foods into school meals can result in better nutrition for school-age children, while making significant savings for schools. Using the World Food Programme’s School Meal Planner (SMP) PLUS software, the school meals offered were analyzed for nutrient adequacy and optimized including five NUS: African nightshade (Solanum spp.), spider plant (Cleome gynandra), Bambara groundnut (Vigna subterranea), bonavist or hyacinth bean (Lablab purpureus), and slender leaf (Crotalaria spp.). The optimization process was based on the commodity price fluctuations and nutrient composition of the local agrobiodiversity used. The study results show how NUS are a viable and healthy alternative to meet the recommended daily nutrient needs for school-aged children at affordable prices. The tool results showcased the effectiveness of linear programming in enabling national decision making for efficient school feeding program planning, by designing comprehensive, affordable food baskets using local agrobiodiversity. Future research should explore implementing optimized school menus while examining broader aspects, such as school lunch environmental impacts and direct procurement approach opportunities that source local ingredients from smallholder farmers.

1. Introduction

In 2024, Kenya continued to face significant challenges in ensuring food and nutrition security for children and adolescents. Despite the ongoing efforts and various government programs, the malnutrition rates remain a concern, particularly in marginalized and drought-prone regions [1]. The country grapples with undernutrition, micronutrient deficiencies, and the rising prevalence of overweight and obesity among adults, adolescents, and children, reflecting a triple burden of malnutrition [2]. Furthermore, in 2022, almost eight out of ten Kenyans (79.2%) were unable to afford a healthy diet [3]. The primary staple food is ugali, a dish made from boiled maize flour, typically accompanied by a small serving of vegetables—most commonly sukuma wiki (a type of kale)—or beans. Meat may occasionally be included in meals, but the dietary variety remains limited throughout the week [4,5]. Adolescent girls and women in East Africa are particularly vulnerable―especially those belonging to poorer households and living in rural areas―where at least one in three do not consume the variety of foods from different food groups that they need for adequate nutrition [6,7]. Malnutrition in children and adolescents has detrimental short- and long-term health outcomes, by increasing the risk of morbidity and mortality, but also growth-related problems, like impaired physical and cognitive development [8]. Improving the access to affordable and nutritious foods—including fruits, vegetables, and animal-source foods (ASFs) such as milk, eggs, fish, and meat—is crucial to leveraging the food system to better protect, promote, and support children’s right to adequate food and nutrition [9]. At the United Nations Climate Change Conference (COP28), held in Dubai at the end of 2023, over 160 nations, including Kenya, signed the Declaration on sustainable agriculture, resilient food systems, and climate action, committing to enhancing food security through social protection programs. At the global climate meeting (COP29) held in 2024 in Baku, Azerbaijan, school feeding was highlighted as a climate crisis mitigation strategy [10].
Kenya has long prioritized nutrition and food security, enshrining the right to food in its 2010 Constitution (Art. 43) [11]. Since its first National Food Policy in 1981 [12], the Government of Kenya (GoK) has implemented various programs, including school feeding initiatives. In 1980, the GoK and the United Nations’ World Food Programme (WFP) launched school feeding in Arid and Semi-Arid Lands (ASAL), transitioning to a nationally led school meals program in 2009 fostering sustainability [13]. As at August 2022, the program was providing school lunches to more than 1.5 million pupils in primary schools [14]. Numerous school meal programs have followed, with the most recent—Dishi na County school feeding program—launched in Nairobi, Kenya at the end of August 2023, thanks to the collaboration between Nairobi County and the Kenyan charity, Food 4 Education [15]. Providing free or subsidized nutritious lunches to low-income students, the Dishi na County program sources food from local, women-led, smallholder farms, reinforcing biodiversity conservation, lowering the program’s carbon footprint, and reflecting Kenya’s commitment to climate action through planet-friendly school meals [15,16].
School feeding programs and initiatives to incorporate nutrient-dense, locally sourced foods into children’s diets have shown promise [17,18]. They can also catalyze demand-driven, eco-friendly practices within local food systems [10]. Regardless of its nutritional quality, food provision in schools also increases school enrolment and participation, allowing equitable access to education, especially for girls [19]. When school gardens are also implemented, they can also be used as educational tools, providing opportunities for hands-on involvement and activities related to agriculture, nutrition, and sustainability in real-world settings [20]. These simple educational tools are likely to influence the eating habits of children, their caregivers, and the entire community by promoting messaging on healthy eating and dietary habits, and agrobiodiversity conservation, in addition to improving their understanding of the effects of climate change on agriculture and food production, along with other benefits [10,21].
School meal programs also play a pivotal role in food systems’ transformation globally [10,19]. They may empower smallholder farmers, promote local food production, local sustainable development, and could represent a means to support food biodiversity production through public procurement strategies [19,22]. Indeed, implementing sustainable school meal programs could allow the creation of more-resilient, planet-friendly, sustainable food systems and climate-responsive diets, when less resource-intensive food items, like vegetables, fruit, and legumes are home-grown or purchased from local and smallholder producers [23].
Neglected and Underutilized Species (NUS), or “opportunity crops” as they have more recently been termed [24] are native, locally adapted, climate-resilient, nutrient-rich, and cost-efficient species. Their inclusion in school meals can result in multiple benefits [17,20,25]. These include a direct effect on children’s healthy dietary behaviors, which may prevent most of the risk factors linked to malnutrition and non-communicable diseases in later life [26,27,28]. NUS also increase the resilience of agricultural production systems to climate change, contribute to empowering traditional communities and Indigenous peoples, particularly women, and preserve cultural heritage [25,29]. Most NUS are well adapted to growing in poor soils, on marginal lands (in agroecological niches where common crops cannot grow), are resistant to several biotic and abiotic stresses, and require fewer external inputs. Moreover, many NUS are richer in micronutrients than their cultivated counterparts [17,30,31,32]. Incorporating these local species into community diets has the potential to address micronutrient deficiencies, promote more-nutritious and cost-effective meals, enhance dietary diversity, and support both human health and environmental sustainability [31,33,34].
For much of human history, NUS have been integral to local diets [35]. However, they have been increasingly marginalized in domestic and international agricultural markets, and perceived as less productive, competitive, and profitable than cash crops. Stigmatized as “poor people’s food”, their production and consumption have declined [36,37,38]. Although research on NUS and agrobiodiversity was initiated nearly 50 years ago by Bioversity International (formerly the International Plant Genetic Resources Institute) [39], their role in nutrition, income generation, and sustainability has gained recognition only in the last decade [10,21,40].
However, implementing school feeding programs that incorporate local foods faces several barriers on both the supply and demand side of the food value chain. Farmers are wary of the schools’ ability to pay promptly and reliably, while the farmers, in turn, often lack the necessary information and skills to manage their businesses effectively and establish contracts to supply food to schools [18]. Dishi na County tender notices, for example, are only advertised online, thus excluding the many smallholder farmers who do not have easy access to the internet. From the schools’ perspective, there is a noted absence of budget or delayed funding to feed all children reliably throughout the entire school year, as well as the lack of networks, contacts, and structures to facilitate negotiations between schools and farmers [14,41]. Also, logistical challenges, such as inconsistent supply chains and the seasonal availability of local produce, can hinder the reliable provision of primary meal ingredients [14,18,42]. The issue of inadequate infrastructure, including insufficient storage facilities and kitchen equipment, further complicates the preparation and preservation of fresh local foods [14]. Limited awareness and training among school staff about the benefits and methods of using local foods can also impede the successful integration of these programs. Finally, policy and regulatory hurdles, such as strict procurement policies and lack of supportive policies promoting local food systems, can further complicate the implementation process [19,43]. These barriers collectively pose significant challenges to the adoption of school feeding programs that leverage local food sources.
To showcase the possibility and benefits of effectively incorporating NUS into school meals, this study used the WFP’s School Meal Planner (SMP) PLUS software to calculate how school meals could be nutritionally improved while reducing costs.

2. Materials and Methods

2.1. NUS and School Selection

The study was undertaken between 2020 and 2021 in the city of Nairobi, Kenya. As a first step, a desk review was conducted to select the most suitable NUS to include in the study. Relevant articles on Kenyan NUS were found using Google Scholar, while additional scholarly literature was identified by reviewing relevant reference lists, reviews, reports, and by consulting agrobiodiversity experts. Based on their nutritional profiles, distribution within the study area, and accessibility, five target NUS were selected: African nightshade (Solanum spp.), spider plant (Cleome gynandra), Bambara groundnut (Vigna subterranea), bonavist or hyacinth bean (Lablab purpureus), and slender leaf (Crotalaria spp.) (Table 1). Indigenous to Sub-Saharan Africa (SSA), the spider plant’s wide adaptability and resilience have promoted the species from a weed to a cultivated crop [44]. Rich in nutrients, the plant’s leaves are a good source of minerals, vitamins—such as provitamin A carotenoids—as well as fiber, protein, carbohydrates, and essential amino acids. Raw spider plant also contributes about 152.88 kcal of energy per 100 g portion [45,46]. Bambara groundnut (Vigna subterranea) is another important indigenous crop native to SSA. Because of its rich nutritional profile and balanced macronutrient composition, the legume is considered a complete food and can contribute to reducing the impact of protein–energy malnutrition [47,48,49,50]. The fast-growing, multipurpose bonavist or hyacinth bean (Lablab purpureus) is a drought-tolerant, nutritious legume rich in proteins (with the beans containing up to 25% protein), dietary fiber, carbohydrates, calcium, phosphorus, and iron. The plant’s immature pods and young leaves are cooked as vegetables, while the dry beans are cooked and eaten as pulses [51,52]. Finally, slender leaf (Crotalaria spp.), another indigenous leguminous crop, which is consumed for its young leaves and shoots, is a rich source of provitamin A, vitamin C, iron, calcium, and proteins [53]. With other native crops, these NUS have shown potential in contributing to dietary diversity and food security in SSA [54] while also contributing to enhancing livelihoods in a pilot home-grown school feeding approach tested in Busia County, Western Kenya [18]. Rich in nutrients and used for its medicinal properties, African nightshade (Solanum spp.) is widespread throughout tropical Africa, but less used in community catering in Kenya. In this study it was therefore included in the list of target NUS during the optimization process. The plants’ leaves and seeds provide provitamin A and vitamins C and E, calcium, carbohydrates, antioxidants, carotenoids, folic acid, minerals, and amino acids [55,56,57,58]. The leaves are appreciated for their bitterness and are mostly used as a vegetable, often cooked with other greens, while the fruit is consumed in limited amounts as it is mildly toxic when unripe.
The school selection criteria were limited to identifying a school that: (a) had fully resumed operations following the COVID-19 pandemic; (b) provided daily school meals; and (c) was willing to participate in the study by sharing its menu plans. The choice fell on the Volunteers Foundation Academy (VFA), a charity-supported primary school situated in Kibera, an informal settlement in Nairobi. The school provides education to children aged between 6 and 12 years old from disadvantaged families and has a small kitchen garden where kale and spinach are mostly grown. At the time of the study, the school was not included in Kenya’s school feeding program.

2.2. The School Meal Menus

Using its own budget, the school offered breakfast—primarily porridge—and a warm midday meal to 126 people, including the children (aged 6–12), teachers, and school staff (see Supplementary Materials S1 for the menus’ baseline composition, item quantity, and costs). Meals were prepared by two local women, who also worked in the school kitchen garden, together with the administrator and part of the school staff. Since the vegetables grown in the garden were insufficient to meet the children’s entire nutritional requirements, the school also purchased vegetables from external suppliers.
Vegetables were purchased at and delivered weekly by the Farm to Feed Foundation―a social enterprise that tackles food loss and waste by creating a market for imperfect/surplus produce (rescue vegetables) from family farmers. The vegetables delivered to the school were usually carrots, courgettes (zucchini), capsicum, kale, cabbages, spinach, and collard greens. Depending on their availability and on market prices, the variety and quantity of food items changed weekly, varying by plus or minus 10 kg per food item listed per week (Supplementary Materials S1). Some weeks, the school received only one type of vegetable, which was prepared with a base of tomatoes and onions purchased locally. However, when all the ingredients were available, the menu consisted of a fixed set of dishes that rotated on a weekly basis. All main courses were prepared using a similar cooking method: onions and tomatoes lightly sautéed with vegetable oil to form the base of the recipe, to which vegetables were then added. For recipes that included potatoes or legumes, water was added to cook them in the tomato and onion base. Maize meal (ugali) and rice were boiled separately in water and were served alongside the base with boiled vegetables, potatoes, or legumes. Fish and meat were never provided.
Given the wide variability in ingredient quantity and food type, the school offered multiple weekly menus, complicating the efforts to establish a standard menu. For this reason, this study considered two baseline menus representing extremes: a best-possible menu, indicative of an ideal scenario where all the ingredients were available in sufficient quantity, and a sub-optimal menu, or worst-case scenario, featuring only one type of vegetable and a weekly reduction of 10 kg in the quantity of food supplied to the school.
The study used the World Food Programme (WFP) school menu planner (SMP) PLUS creation platform to reproduce and analyze the nutritional profile of the two baseline menus offered by the school at the time of the study [60,61]. Qualitative and quantitative data provided by the school on the weekly ingredients and costs incurred for food procurement over a one-year period (from October 2020 to October 2021) were manually inserted into SMP PLUS to create a nutritional profile of the two baseline menus. Data on the ingredients purchased to prepare the school meals were entered following the harmonization of mass units into kilograms. By including data on food prices and the food items’ nutritional composition, the software used advanced algorithms to generate a series of optimized menus, which included different food items daily, for up to four weeks. The software also allowed for the inclusion of new food items, not originally listed on the platform, and the manual creation of menus.
National food composition tables were used as the reference document to generate the nutritional profile of commodities [57], except for the nutrient values of slender leaf, which was retrieved from the literature [59]. The per-person ration was determined by dividing the total quantity of ingredients by the number of beneficiaries, regardless of age. The weekly menus’ nutritional profile per person was analyzed using the SMP PLUS software and the results—shown as daily values—were then compared to the 30% threshold for energy and nutrient requirements established by the national school feeding guidelines [13,62].

2.3. The Menu Optimizations

Following the nutritional analysis of the baseline menus offered at the VFA, three optimizations (Figure 1) for both baseline menus were undertaken to establish what could be adjusted in the menus to maximize the meals’ nutritional value (in terms of energy and nutrient requirements) within the available budget (at the lowest possible price to meet the 30% RDA target for key nutrients per meal established by the national school feeding guidelines [13,62,63]). An example of the software’s capabilities and output report is provided in Supplementary Materials S2.
The SMP PLUS software allows users to design menus either manually or automatically, using a built-in algorithm―the specifics of which are not disclosed to the user [60,61]. However, in manual mode, users can generate menus by selecting food items and specifying the price and quantity of ingredients. This was the approach used to evaluate the two baseline menus. In automatic mode, the software’s algorithm generates the most cost-effective and nutrient-dense meals based on several configurable parameters, as used in the three optimization scenarios. All the optimizations used consistent parameters for menu duration (5 days per week) and basic nutritional recommendations. However, the food groups and item rules assigned by the software varied based on the specific optimization performed. The tool’s nutrition rules prioritize meeting the basic nutrient requirements for non-anemic children, while the item rules govern the selection of specific items within each food group. During the first optimization, the parameters were set to allow the tool to adjust only the quantities of food items already available to the VFA, without altering the existing ingredients list. In the second and third optimizations, the five target NUS (all except for amaranth, which was already included in the ingredients list) were added manually to the ingredients list, with the software allowed to freely choose among the following: plant-based food items in the second optimization and all food items in the ingredients list, including ASFs, in the third. Any ‘new’ food items—those introduced in the second and third optimized menus—could either be grown in the school’s garden (in the case of vegetables), purchased from the local market, or sourced through the Farm to Feed Foundation.

3. Results

3.1. Nutritional Analysis of the Two Baseline Menus

The two weekly baseline school menus—the BL Best-possible and BL Sub-optimal menus—were analyzed for their nutritional adequacy using SMP PLUS, and the results are presented in Figure 2.
In terms of ingredients, the two menus were composed as follows:
The best-possible baseline (BL Best-possible) weekly menu included mixed-flour porridge for breakfast and, in addition to the base of vegetable oil, tomatoes, and onion, consisted of the following food items:
  • Monday: White rice (Oryza sativa), green grams (Vigna radiata) (known locally as ndengu), and mixed vegetables;
  • Tuesday: Maize meal (ugali) and mixed vegetables;
  • Wednesday: White rice, yellow beans (Phaseolus vulgaris), and mixed vegetables;
  • Thursday: White rice, green grams, and Irish potatoes (Solanum tuberosum)
  • Friday: White rice, yellow beans, and mixed vegetables.
In the sub-optimal baseline menu (BL Sub-optimal), only one type of green leafy vegetable was available for the entire week, alongside legumes and different starchy staples, in addition to the base of vegetable oil, tomatoes, and onion. Vegetables were supplied in reduced quantities (10 kg less than the average weekly vegetable supply), and potatoes were excluded. Meals in the sub-optimal menu included mixed-flour porridge for breakfast and lunch and also included the following food items:
  • Monday: White rice, green grams (ndengu), and spinach;
  • Tuesday: Maize meal (ugali) and spinach;
  • Wednesday: White rice, yellow beans (Phaseolus vulgaris), and spinach;
  • Thursday: White rice and green grams;
  • Friday: White rice, yellow beans, and spinach.
The nutritional profile of the two menus is provided in Figure 2. The nutritional values are compared to the 30% threshold for energy and nutrient requirements established by the Kenyan national school feeding guidelines [13,62]. For detailed quantities, refer to Supplementary Materials S1.
Both baseline menus provided adequate amounts of protein, vitamin C, zinc, magnesium, and vitamins B1 to B9. The lack of ASFs in both menus, however, provided no vitamin B12. The weekly best-possible baseline menu was thus more nutritious than the sub-optimal menu; however, neither provided adequate calcium and fat, while the sub-optimal menu also provided inadequate energy (calories), vitamin A, and iron.
Following the analysis of the two baseline menus, the study proceeded to create three distinct optimizations for each of the two baseline menus. Each optimization allowed varying degrees of flexibility within the software.

3.2. SMP PLUS Optimizations

3.2.1. First Optimization: Baseline Menu Ingredients in Optimum Quantity

Best-possible menu (BL Best-possible+)
Despite the optimization, the provision of vitamin B12 continued to be inadequate due to the menu’s lack of ASFs. However, the optimization allowed the menu to reach the 30% mean daily threshold for calcium and fat requirements (Figure 3). To fill these nutrient gaps, SMP PLUS increased the quantity of millet, wheat, and sorghum flours (for porridge) from 30 g to 150 g per week and changed the vegetables’ proportion and variety. Kale quantities were increased by 133%, while the quantity of collard greens underwent a more than six-fold increase, from 48 g to 361 g per week. Conversely, the quantity of potatoes, rice, and courgettes decreased by 82%, 47%, and 65%, respectively (Supplementary Materials S3). The nutritional improvement was associated with a substantial cost reduction for the best-possible baseline meal, which decreased by approximately 44%, from USD 0.40 to USD 0.22 per school meal. This cost reduction would imply daily savings of USD 0.17 per meal, generating monthly savings of USD 3.45 per meal and a total monthly saving of USD 435 for the school.
Sub-optimal menu (BL Sub-optimal +)
Similarly to the best-possible menu, optimizing the sub-optimal menu could not ensure the provision of vitamin B12 due the absence of ASFs. However, increases in the quantity and portions of the available ingredients (Supplementary Materials S3) enabled the menu to meet the 30% average daily threshold for calcium and fat requirements, as well as the nutrient requirements for energy, vitamin A, and iron (see Figure 3 and Table 2).
In this optimization, SMP PLUS increased the quantity of most ingredients. The amount of porridge flour increased five-fold (from 30 g to 150 g per week), while the quantity of yellow beans, green grams, and spinach increased by 64.5%, 38%, and 160%, respectively. This resulted in a maximum portion size of 100 g of spinach per day (refer to the menu plans provided in the Supplementary Materials S3). Conversely, the quantities of the two most popular ingredients in contemporary Kenyan cuisine—tomato and onion—were reduced by 89% and 35%, respectively. The increases determined by the software for most food items caused a slight rise in the cost of each school meal, which rose by 3.6%, from USD 0.25 to USD 0.26 per day.

3.2.2. Second Optimization: The Software Freely Selects Fruits, Legumes, and Vegetables, Including NUS

The outcome of the second optimization was identical for both baseline menus, as the difference between the best-possible and sub-optimal menus depended solely on the vegetable availability. The vitamin B12 requirements continued to fall short due to the lack of ASFs in both baseline menus, while all other micro- and macro-nutrient requirements were met (see Figure 4 and Table 2).
Alongside the NUS that were manually included in the software’s ingredients’ list, SMP PLUS selected amaranth—another important traditional crop—kale, and avocado. Interestingly, the amount of millet, sorghum, wheat, and groundnut porridge flours was left unchanged, but the overall quantity of cereals was integrated with 235 g of red sorghum grain per week (see Supplementary Materials S1).
The second optimization produced a more affordable school meal compared to both baseline menus. The cost dropped by around 66% for the best-possible baseline menu and 45% for the sub-optimal menu, decreasing from USD 0.40 to USD 0.14 per meal and USD 0.25 to USD 0.14 per meal, respectively. This translates into savings of USD 0.26 per meal per day and USD 5.20 per meal per month, amounting to a total monthly saving of USD 655 for the entire school with the best-possible menu. For the sub-optimal menu, the savings are USD 0.11 per meal per day and USD 2.25 per meal per month, resulting in a total monthly saving of USD 283.50 for the school.

3.2.3. Third Optimization: The Software Freely Selects All Possible Menu Ingredients Including NUS and ASF

Like the second SMP PLUS optimization, the third yielded identical results for both baseline menus. The software’s unrestricted selection of ingredients led to the development of a school menu capable of fulfilling 30% of children’s daily nutritional requirements. Based on these calculations, the 30% threshold was achieved for all macro- and micronutrients (Figure 5 and Table 2).
To achieve the 30% threshold for vitamin B12, the SMP PLUS optimization incorporated cow’s milk in weekly portions of 525 g (510 mL) per meal, equivalent to 105 g per day (approximately 102 mL—nearly half the average serving size). The mixed-flour porridge was replaced exclusively with maize flour. Additionally, this optimization included amaranth, kale, and avocado, alongside the NUS (Supplementary Materials S1).
This final optimization resulted in the most cost-effective school meal, priced at USD 0.13 per meal per day. Compared to the best-possible baseline menu, the costs decreased by approximately 67%, and by around 48% for the sub-optimal menu. For the best menu, the cost was reduced from USD 0.40 to 0.13 USD per meal, resulting in daily savings of USD 0.27, and monthly savings of USD 5.3 per meal. This would amount to a total monthly saving of approximately USD 668 for the entire school. Relative to the sub-optimal menu, the optimized menu reduced costs from USD 0.25 to USD 0.13 per meal, saving USD 0.12 per day per meal and USD 2.36 per month per meal. For the whole school, this represents a monthly saving of USD 297. A comparison of nutritional data and prices of all the VFA menus is shown in Table 2.

4. Discussion

School meals in Kenya often lack diversity and essential micronutrients, making it difficult to meet the national school feeding guidelines’ recommendations of providing school children with 30% of their daily energy and nutrient intake through these meals [13,62]. Many schools face budgetary constraints that limit their ability to procure fresh, high-quality ingredients, resulting in monotonous menus [64]. This issue is not limited to the study school but is prevalent across Kenya [65]. The economic challenges stemming from food and energy price inflation, compounded by the impacts of prolonged droughts and the COVID-19 pandemic, have further affected the quality and variety of school meals in Kenya [66]. This is particularly the case for smaller schools such as the VFA, which was forced to reduce the quantity and variety of food provided in its school meal program as a result of these constraints. Although the Kenyan Nationals School Meals and Nutrition Strategy2017–2022 provides examples of nutritionally balanced meals that could supply 38–66% of energy and nutrient needs, many schools rely heavily on fortified flours, super-cereal porridges, and micronutrient powders to compensate for the shortfall in key vitamins A, B1–B12, C, D, and E [13].
This study highlights the capacity for school meals to consistently meet the 30% minimum daily energy requirement at affordable prices, by introducing local foods and NUS into school meals. The results also highlight that, besides the selected NUS, other locally available vegetables and fruits, such as amaranth and avocado to name but two, could be included to optimize the school meals’ nutrient adequacy, while minimizing costs. However, potential costs like for additional labor for cleaning and cutting vegetables or purchasing pre-processed vegetables must be considered. These additional expenditures could be offset by overall cost savings from using locally available NUS.
The study also highlights the value of decision-support tools like SMP PLUS [61]. These tools are essential for designing cost-efficient, nutritionally balanced school menus, as recommended by the recent School Meals Coalition’s Task Force meeting (29 October 2024) [67]. By accounting for the fluctuations in food prices and commodity availability, SMP PLUS can help create more stable food baskets and guide national decision making in school feeding programs. Such tools could play a critical role in addressing Kenya’s ongoing school feeding challenges, as evidenced by a 2023 audit of Kenya’s National School Meals and Nutrition Program [14]. While the school meal program was found to enhance school attendance, it failed to meet expectations in several critical areas [14]. Budget constraints and delayed payments to beneficiary schools hindered the provision of sufficient meals throughout the school year. Additionally, the outdated per-child meal allocations (KES 10 or USD 0.07, using the exchange rate at the time of the study), failed to account for the fluctuations in food commodity prices and the rising cost of living, rendering it insufficient to provide nutritious meals for its beneficiaries. The audit noted that schools often lacked the essential components of the prescribed “complete food basket”, receiving only partial rations such as rice without accompanying iodized salt, pulses, or vegetables.
Among the audit’s recommendations to the State Department for Early Learning and Basic Education is to “continuously carry-out market research to ascertain the actual cost of a meal so as to better inform budgeting and planning of the program”. As our study has shown, the SMP PLUS software enables the user to input up-to-date pricing information for each commodity, ensuring that schools can adequately budget for the year. The study’s third menu optimization yielded a nutritionally balanced weekly menu costing USD 0.13 per student per day. Increasing the current meal allocation from USD 0.07 to USD 0.13 could enable the government to nourish all 10.4 million primary school students adequately. Even with a 5% annual inflation rate, the optimized menu costs remain lower than the national average meal cost of USD 0.27 as of October 2024 [68]. To further enhance the cost-efficiency and mitigate the seasonal price fluctuations, incorporating a broader range of NUS into school meal programs is essential. Detailed information on African NUS is becoming increasingly available [57,58], and integrating these data into existing school meal planning systems would raise awareness of the nutritional and economic benefits that these crops offer. Additionally, strengthening the capacity of smallholder farmers to supply schools with locally sourced produce is crucial for ensuring a steady, diversified food supply. Training school staff (e.g., chefs, procurement staff, teachers) on meal planning and nutrition could also enhance the quality and sustainability of school meal programs [65]. Partnering with the Ministry of Agriculture to incorporate local varieties of vegetables, tubers, pulses, and cereals into school meals could further diversify menus and improve the overall food security [14].
An approach known as “home-grown school feeding” already provides notable examples of direct procurement approaches that link smallholder farmers to schools for the supply of African indigenous vegetables in Kenya [18]. Innovative approaches such as urban gardening and aquaponics are being co-created and tested with a diverse range of food-system actors in informal urban settlements in Western Kenya [69]. Targeting African leafy vegetables and fish value chains, these initiatives could be linked to a range of schools for the supply of NUS and ASFs.
In addition to improving nutritional outcomes, well-structured school feeding programs can help combat hunger, enhance academic performance and attendance, and address childhood malnutrition. Such programs also offer long-term societal benefits by reducing healthcare costs and supporting the development of a more capable workforce. From an economic perspective, investments in school meals yield high returns, with every USD 1 invested generating up to USD 9 in societal benefits [70].

Study Limitations

The study focused on a single school that relies on charitable donations to implement its school meal program. This is not a typical scenario for Kenya, and future research should expand to encompass both state and private schools in rural and urban areas across Kenya, allowing for a comprehensive assessment of menu quality across diverse settings and varying funding sources.
It is important to acknowledge that the nutritional values used in the optimized menus are based on estimates for raw ingredients, without adjustments for factors such as special dietary needs, nutrient retention during cooking, or the bioavailability of nutrients. This could result in an overestimation of nutrient availability, particularly for iron and zinc in the second optimization. The third optimization includes ASFs, which are known to provide these nutrients in forms with higher bioavailability, making the estimates more accurate for those essential nutrients.
This study focused solely on meeting the students’ basic nutritional requirements. Children with special (dietary) needs may have higher-than-average nutritional demands or specific dietary requirements, depending on their type of malnutrition, and separate thresholds should be established for them. To obtain more precise nutrient values for each meal, future enhancements to the software and methodology will be required.
Additionally, to meet the 30% threshold established by the national school feeding guidelines for the students’ daily macro- and micronutrient requirements, the optimized menus occasionally exceeded the recommended levels of certain micronutrients. The highest levels were observed for vitamin C and magnesium. In the first and second optimizations of the best-possible menu, vitamin C levels were over three times the daily requirement, while in the first optimization of the sub-optimal menu, magnesium levels were more than double the recommended amount. However, these values do not reflect the actual daily intakes. Notably, the calculations were performed using raw ingredients as a reference and considered a period of five school days. Cooking leafy vegetables, which in the meals were the primary source of vitamin C, significantly reduces their vitamin C content. Moreover, as previously highlighted, many Kenyan households are unable to meet a child’s full daily nutritional requirements at home, making school meals the only significant meal that children will receive daily. As a result, excess micronutrient levels should be distributed over seven days to account for the days when children are not in school. However, the micronutrients concerned are still within the Tolerable Upper Intake Level listed by the European Food Safety Authority [71]. Finally, the bioavailable portion of a nutrient that reaches the gastrointestinal tract is significantly smaller than the amounts in food items (often raw) listed in food composition tables. Plant-based foods are typically consumed as part of composite dishes, which can either enhance or inhibit nutrient bioavailability. For instance, compounds such as lignin, phytates, and oxalates can reduce the absorption of magnesium, whereas vitamin C can improve the bioavailability of plant-based iron [72]. However, emphasizing the importance of a varied menu is crucial, as it helps balance the nutrient intake, ensures a more diverse and comprehensive nutrient profile, and is more appealing due to its variety.
Other limitations are those related to the constraints inherent in SMP PLUS. For instance, the food basket from which users could select at the time of this study were limited and excluded traditional, culturally acceptable, yet nutritious food options, such as underutilized traditional crops, cheese, fungi, and insects. Thus, the algorithm generated the optimized menus according to a wide but non-exhaustive list of commodities. The tool did not always provide detailed information about food items; while it sometimes specified whether a product was fresh or dried, this detail was often omitted. Furthermore, the nutrient database within the software appeared incomplete. For instance, amino acids were not specified, making it impossible to assess the biological value of the proteins selected by the tool. Another software limitation was its inability to establish minimum diversity requirements within the food groups. Although the optimized menus typically include five or more food groups, the variety of items within a single food group was often very limited in some menus. Lastly, the algorithm used by the software is not disclosed to users, and no publicly available general description is provided. This lack of transparency limits users’ ability to understand and tailor the software to model different nutritional objectives. By contrast, a study on mixed-integer programming for enhancing workers’ food programs in a Brazilian context demonstrated how transparency can facilitate targeted nutritional improvements [60].

5. Conclusions

This study demonstrates that incorporating underutilized nutrient-rich food species into school meals can offer a viable and healthy solution to meeting the recommended daily nutrient needs for school-age children at affordable prices, while also generating significant cost savings for schools. These savings could be reinvested to increase the size of meal portions (going beyond the 30% threshold of the students’ minimum nutritional requirements), enhance nutritional diversity, and incorporate animal-source foods (ASFs) or alternative sources of protein and vitamins (e.g., vitamin B12), which are critical for children’s development, especially in under-resourced areas such as informal settlements and arid or semi-arid regions. Incorporating fresh or dried NUS into school meals would also help diversify menus, promote sustainable food production, preserve cultural heritage, and support biodiversity conservation and use.
The study also highlighted the value of programming tools like SMP PLUS in guiding national decision making for school feeding programs [60,61]. These tools enable the design of cost-effective, nutritionally optimized menus using locally available agrobiodiversity, helping to stabilize food costs amid economic and commodity price fluctuations. This can lead to more resilient and sustainable food systems while supporting community livelihoods.
Given the diverse nature of school feeding programs, developing universal regional recommendations is inherently challenging. Local dietary habits, agricultural production systems, policy frameworks, procurement mechanisms, cultural preferences, and government capacity all vary significantly across regions [64]. Climate and environmental considerations, such as regional differences in sourcing sustainable ingredients, further complicate the standardization efforts. Governance structures and funding models also play a crucial role, with some programs fully integrated into national social protection schemes, while others rely on donor support, raising concerns about long-term sustainability [73].
Considering these complexities, adaptable, evidence-based frameworks are essential for effective school feeding programs. These frameworks should emphasize the core principles such as nutritional adequacy, affordability, and sustainability while allowing localized customization based on specific regional contexts. This approach ensures equitable and effective implementation across diverse settings.
To further improve the impact of school feeding programs, future research should evaluate the additional costs associated with increasing the nutrient provision threshold to 50%, with 30% allocated to lunch and 20–25% to snacks and breakfast—a common practice in many other national programs. Testing optimized menus in diverse school settings is essential to ensure their nutritional and economic feasibility, as well as their practical implementation.
Moreover, evaluating the environmental impact of school meals—such as carbon footprints and land use implications—can help guide the adoption of more sustainable food practices. This holistic approach aligns school feeding programs with public health objectives, economic feasibility, and environmental sustainability. It positions these programs as powerful tools for addressing the global challenges related to malnutrition, poverty, and climate change.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su17062436/s1, S1: Volunteers Foundation Academy baseline menus’ composition, item quantity and cost; S2: Screenshots of the SMP Plus optimization results for VFA; S3: Weekly school menu composition stemming from the SMP PLUS optimizations.

Author Contributions

Conceptualization, I.P. and T.B.; methodology, I.P.; validation, I.P., T.B. and I.J.; formal analysis, I.P.; investigation, I.P.; resources, I.P.; data curation, I.P.; writing—original draft preparation, I.P. and T.B.; writing—review and editing, T.B. and I.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in this study are included in the article/Supplementary Materials. Further inquiries can be directed to the corresponding author.

Acknowledgments

We gratefully acknowledge the World Food Programme (WFP) for providing access to the School Meal Planner SMP PLUS software and for their invaluable guidance, both of which were pivotal in achieving the results presented in this pilot study. Additionally, we express our appreciation to the University of Florence for its contribution and assistance throughout this project. Our sincere gratitude is also extended to the Volunteers Foundation Academy, particularly Pauline Martin and Farm to Feed Foundation for sharing detailed data on the school menus, ingredients, and recipes. We also acknowledge and thank Olga Spellman for the copyediting of this manuscript.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

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Figure 1. The software optimizations undertaken on the two baseline menus as part of this study using the SMP PLUS tool. Source: Authors’ own elaboration. NOTE: The “+” sign next to the two baseline menus denotes the optimization of existing school meal ingredients. The results of the second and third optimizations were identical for both baseline menus, as the variation between the best-possible and sub-optimal menus was solely influenced by vegetable availability. Consequently, BL best-possible and BL sub-optimal were consolidated by the software into a single baseline average (BL average).
Figure 1. The software optimizations undertaken on the two baseline menus as part of this study using the SMP PLUS tool. Source: Authors’ own elaboration. NOTE: The “+” sign next to the two baseline menus denotes the optimization of existing school meal ingredients. The results of the second and third optimizations were identical for both baseline menus, as the variation between the best-possible and sub-optimal menus was solely influenced by vegetable availability. Consequently, BL best-possible and BL sub-optimal were consolidated by the software into a single baseline average (BL average).
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Figure 2. Percentage of daily nutrient requirements supplied on average through best-possible (BL best-possible) and sub-optimal (BL sub-optimal) menus offered at the Volunteers Foundation Academy (VFA) compared to the 30% mean daily threshold (dotted line) for energy and nutrient requirements established by the national school feeding guidelines [13,62,63].
Figure 2. Percentage of daily nutrient requirements supplied on average through best-possible (BL best-possible) and sub-optimal (BL sub-optimal) menus offered at the Volunteers Foundation Academy (VFA) compared to the 30% mean daily threshold (dotted line) for energy and nutrient requirements established by the national school feeding guidelines [13,62,63].
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Figure 3. Percentage of daily nutrient requirements supplied on average per menu following the first optimization for the best-possible and sub-optimal menus, elaborated by the SMP PLUS software. Values are compared to both baseline menus and the 30% mean daily threshold (dotted line) for energy and nutrient requirements established by the Kenyan national school feeding guidelines [13,62,63].
Figure 3. Percentage of daily nutrient requirements supplied on average per menu following the first optimization for the best-possible and sub-optimal menus, elaborated by the SMP PLUS software. Values are compared to both baseline menus and the 30% mean daily threshold (dotted line) for energy and nutrient requirements established by the Kenyan national school feeding guidelines [13,62,63].
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Figure 4. The percentage of required daily nutrients supplied after including neglected and underutilized species (NUS) and free selection of plant-based food items (VEG) to the mean baseline menu (BL average + VEG), elaborated by the SMP PLUS software. NUS’ contribution (light green) is shown separately to other foods (dark green) [40]. No ASFs were included. Values are compared to the 30% mean daily threshold (dotted line) for energy and nutrient requirements established by the Kenyan national school feeding guidelines [13,62,63].
Figure 4. The percentage of required daily nutrients supplied after including neglected and underutilized species (NUS) and free selection of plant-based food items (VEG) to the mean baseline menu (BL average + VEG), elaborated by the SMP PLUS software. NUS’ contribution (light green) is shown separately to other foods (dark green) [40]. No ASFs were included. Values are compared to the 30% mean daily threshold (dotted line) for energy and nutrient requirements established by the Kenyan national school feeding guidelines [13,62,63].
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Figure 5. Percentage of daily nutrient requirements supplied after including NUS and free selection of any other food to the mean baseline menu (BL average + NUS + ALL), elaborated by the SMP PLUS software. NUS’ contribution (light green) is shown separately to other foods (blue) [40]. Values are compared to the 30% mean daily threshold (dotted line) for energy and nutrient requirements established by the Kenyan national school feeding guidelines [13,62,63].
Figure 5. Percentage of daily nutrient requirements supplied after including NUS and free selection of any other food to the mean baseline menu (BL average + NUS + ALL), elaborated by the SMP PLUS software. NUS’ contribution (light green) is shown separately to other foods (blue) [40]. Values are compared to the 30% mean daily threshold (dotted line) for energy and nutrient requirements established by the Kenyan national school feeding guidelines [13,62,63].
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Table 1. Overview of selected NUS included in this study and added to the SMP Plus tool’s list of ingredients.
Table 1. Overview of selected NUS included in this study and added to the SMP Plus tool’s list of ingredients.
Common NameScientific NameParts UsedNutritional PropertiesReferences
African nightshade *Solanum spp.Leaves and seedsProvitamin A, vitamins C, E, calcium, carbohydrates, antioxidants, folic acid, iron, phosphorous, magnesium, and amino acids[55,56,57,58,59]
Bambara groundnutVigna subterraneaNutsCarbohydrates, protein, fibers and minerals, including potassium, phosphorus, and magnesium[57]
Bonavist (hyacinth) bean Lablab purpureusBeansProtein, B-complex vitamins, folates, phosphorus, potassium, iron, and magnesium[57]
Slender leafCrotalaria spp.LeavesProtein, calcium, iron, vitamin C.[59]
Spider plantCleome gynandraLeavesProtein, provitamin A, folic acid, vitamins C and E, calcium, iron, antioxidants, oxalic acid[45,46,57]
* African nightshade (Solanum spp.) was already available as a plant-based food item in the School Meal Planner (SMP) Plus software and was included in the initial food analysis as NUS.
Table 2. A summary of the nutritional analysis and SMP PLUS optimizations of the baseline menus offered at VFA. Nutrition adequacy and nutrient deficiencies are identified, as well as the cost per school meal (USD) before and after the optimizations.
Table 2. A summary of the nutritional analysis and SMP PLUS optimizations of the baseline menus offered at VFA. Nutrition adequacy and nutrient deficiencies are identified, as well as the cost per school meal (USD) before and after the optimizations.
Nutritional Analysis and OptimizationsVFA MenusCost per Meal per Day (USD)KcalProt (g)Fat (g)Vit A (µg)Vit C (mg)Vit B12 (µg)Ca (mg)Fe (mg)Zn (mg)Mg (mg)
Baseline menusBest menu0.40X
Sub-optimal menu0.25X
First optimizationBL best-possible +0.22X
BL sub-optimal +0.26X
Second optimizationBL average + NUS + VEG *0.14X
Third optimizationBL average + NUS + ALL *0.13
√ = 30% threshold met; ▲ = value > 100% daily needs; ▼ = value < 30% daily needs; X = Value missing. * The financial outcomes of the second and third optimizations were the same for both baseline menus, as the variation between the best-possible and sub-optimal menus was solely determined by vegetable availability, influenced by the school’s financial situation and donations.
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Proietti, I.; Jordan, I.; Borelli, T. Enhancing Nutrition and Cost Efficiency in Kenyan School Meals Using Neglected and Underutilized Species and Linear Programming: A Case Study from an Informal Settlement. Sustainability 2025, 17, 2436. https://doi.org/10.3390/su17062436

AMA Style

Proietti I, Jordan I, Borelli T. Enhancing Nutrition and Cost Efficiency in Kenyan School Meals Using Neglected and Underutilized Species and Linear Programming: A Case Study from an Informal Settlement. Sustainability. 2025; 17(6):2436. https://doi.org/10.3390/su17062436

Chicago/Turabian Style

Proietti, Ilaria, Irmgard Jordan, and Teresa Borelli. 2025. "Enhancing Nutrition and Cost Efficiency in Kenyan School Meals Using Neglected and Underutilized Species and Linear Programming: A Case Study from an Informal Settlement" Sustainability 17, no. 6: 2436. https://doi.org/10.3390/su17062436

APA Style

Proietti, I., Jordan, I., & Borelli, T. (2025). Enhancing Nutrition and Cost Efficiency in Kenyan School Meals Using Neglected and Underutilized Species and Linear Programming: A Case Study from an Informal Settlement. Sustainability, 17(6), 2436. https://doi.org/10.3390/su17062436

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