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Circular bioeconomy practices and their associations with household food security in four RUNRES African city regions

  • Haruna Sekabira ,

    Roles Data curation, Formal analysis, Investigation, Methodology, Project administration, Resources, Software, Supervision, Visualization, Writing – original draft, Writing – review & editing

    H.Sekabira@cgiar.org

    Affiliation Division of Natural Resources Management, International Institute of Tropical Agriculture, Kigali, Rwanda

  • Shiferaw Feleke,

    Roles Methodology, Software, Validation, Visualization, Writing – review & editing

    Affiliation Division of Social Sciences and Agribusiness, International Institute of Tropical Agriculture, Dar es Salaam, Tanzania

  • Victor Manyong,

    Roles Methodology, Validation, Visualization, Writing – review & editing

    Affiliation Division of Social Sciences and Agribusiness, International Institute of Tropical Agriculture, Dar es Salaam, Tanzania

  • Leonhard Späth,

    Roles Conceptualization, Investigation, Project administration, Supervision, Validation, Visualization, Writing – review & editing

    Affiliations Department of Environmental Systems Science, Sustainable Agroecosystems, Eidgenössische Technische Hochschule Zürich, Universitätstrasse, Zurich Switzerland, Department of Environmental Systems Science, Transdisciplinary Lab, Eidgenössische Technische Hochschule Zürich, Universitätstrasse, Zurich Switzerland

  • Pius Krütli,

    Roles Conceptualization, Funding acquisition, Project administration, Resources, Validation, Visualization, Writing – review & editing

    Affiliation Department of Environmental Systems Science, Transdisciplinary Lab, Eidgenössische Technische Hochschule Zürich, Universitätstrasse, Zurich Switzerland

  • Guy Simbeko,

    Roles Conceptualization, Data curation, Formal analysis, Methodology, Software, Visualization, Writing – original draft, Writing – review & editing

    Affiliation Department of Social Sciences, Agribusiness and Monitoring Evaluation and Learning, International Institute of Tropical Agriculture—Rural-Urban Nexus: Establishing a Nutrient Loop to Improve City Region Food System Resilience, Bukavu, Democratic Republic of the Congo

  • Bernard Vanlauwe,

    Roles Funding acquisition, Project administration, Resources, Supervision, Validation, Visualization, Writing – review & editing

    Affiliation Division of Natural Resources Management, International Institute of Tropical Agriculture, Nairobi, Kenya

  • Johan Six

    Roles Funding acquisition, Project administration, Resources, Supervision, Validation, Visualization, Writing – review & editing

    Affiliation Department of Environmental Systems Science, Sustainable Agroecosystems, Eidgenössische Technische Hochschule Zürich, Universitätstrasse, Zurich Switzerland

Abstract

Achieving the United Nation’s 2030 agenda which aims, among other goals, to ensure sustainable consumption and production patterns, requires a sustainable resource use model deployed at scale across global food systems. A circular bioeconomy (CBE) model of resource use has been proposed to reuse of organic waste in agricultural production to enhance food security. However, despite several initiatives recently introduced towards establishing a CBE in sub-Saharan Africa (SSA), minimal scientific efforts have been dedicated to understanding the association of CBE practices and food security. This study use data from 777 smallholder farm households from DRC, Ethiopia, Rwanda, and South Africa, to examine associations between three CBE practices (use of organic waste as compost, as livestock feed, and sorting waste) and household food security. Using different regression and propensity score matching models (PSM). Result reveal that using CBE practices more likely adds a 0.203 score of food insecurity access prevalence (HFIAP), 1.283 food insecurity access scale (HFIAS-score) and 0.277 for household dietary diversity score (HDDS) among households using CBE practiced groups. Associations regarding using organic waste as compost are generally positive but insignificant, while those with sorting waste are significantly and consistently negative. Thus, CBE innovations aiming to enhance household food security could prioritize organic waste valorization into livestock feed consider socio economic aspects such as access to land, access to market, education level, using mobile phone, income and city regions where interventions took place. However, prior sorting of waste is necessary to enable effective waste valorization.

Author summary

The CBE aims to ensure the continuously cycled and reused of biological resources. Thus, the development of the CBE could have a significant and positive transformative impact on the attainment of SDGs 1 and SDGs 2. The latter respectively concerns the global pledge to end poverty in all its forms by 2030 and promote sustainable agriculture, which is essential for fighting hunger and thereby ensuring food security and enhancing nutrition. This study examine empirically the association of CBE practices; using organic waste as compost, or as livestock feed, or sorting organic from inorganic waste practices put in place in four RUNRES African city regions with household food security captured by HDDS, HFIAS-score, and HFIAP and socio economics factors as covariates. Hence, the study premised that, CBE practices provide a direct means of improving food security by firstly supplying organic manure to replenish soil nutrients and enhance biomass production, leading to increased food production, and secondly via income streams facilitated by market sales of CBE products such as waste sorted, compost, livestock feed and agricultural produce. Income from these sales contributes to food accessibility. Ensure sustainable food consumption by reducing the use of external inputs, thus minimizing resource extraction and soil deterioration. The evidence generated through this study inform public and private sector that CBE has the potential to promote sustainable, bio-based economic growth, contribute to the green circular economy implementation, new employment opportunities, improved livelihoods, food security and wealth creation.

1. Introduction

The African food crisis accompanied by poverty, dwindling production resources, climate change, urbanization, a rapid population growth; include increased demand for food, feed and fiber, makes it impossible to throw more than enough food away in a waste. Which in turn requires the development of sustainable, innovative food solutions adapted to the specific needs of the Continent [13]. An alternative model of resource use has been proposed to achieve efficient global production and consumption systems [24]. This alternative–the Circular Bioeconomy (CBE)—aims to maximize the use of biological resources, minimizes waste generation, reduces environmental impact and make transition from a linear economy, where resources are just extracted, used, and discarded, to a circular economy, where resources are continuously cycled and reused [4].

In light of the above, it is possible that the development of the circular bioeconomy could have a significant and positive transformative impact on the attainment of SDGs 1 [3], which concerns the global pledge to end poverty in all its forms by 2030. In addition, to SDGs 2 of the SDGs, focuses on the need to promote sustainable agriculture, which is essential for fighting hunger and thereby ensuring food security and enhancing nutrition [3,5]. To meet the SDGs 1 and 2, scholars [68] attested that it is necessary to capture holistically the association between CBE practices such as composting, anaerobic digestion, and using food waste for animal feed or bioenergy production and food security.

Hence [9], worked on circular Bioeconomy: countries’ studies and find that the circular bioeconomy is still a new concept for both the developing and developed countries and still in the emerging stage worldwide. [10] argued that with the growing the need for farmland and the utilization of farming commodities for food and heating purposes, the bioeconomy, along with the SDGs, has meant that the country has been viewed primarily as a regular supplier of land for the production of food and non-food crops. [11,12] note that the countries of East Africa; mostly Ethiopia, Democratic Republic of the Congo and Rwanda, are determined to set a new development course. To that aim, the nations have pinpointed the circular bioeconomy as a promissing pathway to improve food security. In South Africa [7], conducted a case study of the South Africa CBE, examining the factors driving a developing country’s shift to a CBE. The case revealed that national policies and strategies prioritize organic composting and anaerobic digestion as the main methods of diverting organic waste from landfill. However, in Africa, the majority of studies focussed on the CBE as attested by most of researchers [6,7,11], are from the perspective of technology feasibility. CBE relies heavily on basic scientific research, which is more often than not lacking in developing countries. Consequently, there is an urgent need for an empirical approach to CBE practices that would apply consistently and practically to the different agricultural sectors used to achieve the SDGs in the context of developing countries.

Interestingly, several global efforts have recently focused on the global south, especially Sub-Sahara Africa (SSA), with a prime goal of establishing circular food systems [13,14]. In 2019 a CBE project; Rural-Urban Nexus: Establishing a Nutrient Loop to Improve City Region Food Systems Resilience [15], was launched in four African city regions. RUNRES aims to establish a CBE, in locally important value chains (coffee in Bukavu, DRC; bananas in Arba Minch, Ethiopia; cassava in Kamonyi, Rwanda; and vegetables in Msunduzi, South Africa) and implementing rural/urban waste recycling solutions to generate an improved and sustainable flow of resources towards attaining resilient food systems. The precise geographical areas of each region have been named RUNRES city-regions, that were selected based on their importance in the production of the food products in point, and existing connections with the project’s stakeholders and associates. RUNRES intends to co-design, test, implement and scale safe, cost-effective, and socially acceptable three CBE practices (using organic waste as compost, or as livestock feed, or sorting organic from inorganic waste). That valorised urban and rural waste resources, and enhance food value chains to establish circular economies, thus leading to more resilient–rural-urban food systems [16,17]. Moreover, empirical evidence is even more scarce on associations of CBE practices with food and nutrition security [16] and constitute a key to informing proper policy instruments intended to enhance circular systems [18]. Hence, this study tend to respond to the following questions:

What is the empirical association of three common CBE practices put in place by RUNRES with food security?

More specifically, the study applies Ordinary Least Square (OLS) regressions and propensity score matching models (PSM) models, to examine the association of CBE practices (using organic waste as compost, or as livestock feed, or sorting organic from inorganic waste practices) with household food security. The outcome variables for household food security include household dietary diversity score (HDDS), household food insecurity access scale score (HFIAS-score), and household food insecurity access prevalence (HFIAP). In addition, for more accuracy and based on of the past research and robust findings [6,12,19], the study introduce socio economics variables (Age of household head, annual income, gender, access to land, access to credit, grows crops, education level and income source) as covariates in the regression model. Thus, the study hypotheses that, CBE practices provide a direct means of improving food security by firstly supplying organic manure to replenish soil nutrients and enhance biomass production, leading to increased food production, and secondly via income streams facilitated by market sales of CBE products such as (sorted) waste, compost, livestock feed and agricultural produce. Income from these sales contributes to food accessibility. CBE practices also ensure sustainable food consumption by reducing the use of external inputs, thus minimizing resource extraction and soil deterioration. The evidence generated through this study inform public and private sector investment decisions on CBE practices that would potentially improve smallholder food security, while enhancing environmental and human health, and establishing circular food systems. Furthermore, the strategy is thus premised on the belief that a successful deployment of the CBE has also the potential to promote sustainable, bio-based economic growth, new employment opportunities, improved livelihoods, food security and wealth creation. After this introduction section, the next section describes the materials and methods; the third section presents the results from data analyses; the fourth section discusses the findings from the study, and the last section is on the conclusion of the paper.

2. Materials and methods

2.1. Conceptual framework

Sustainable productivity of agricultural land is highly dependent on the stability and sustainability of soil fertility [20]. However, the latter is highly dependent on human actions [20]. Human activity towards the reduction of soil stability and fertility has been enhanced by the linear model of resource use [16,18,20,21]. However, to revert the effects of the linear model, a CBE concept that focuses on reducing waste, recovering, recycling, and reusing waste in agricultural production to increase the sustainability of agricultural land via multiple pathways (organic compost production, job creation, agricultural processing, reduced mining, etc.) needs to be materialized, [16,21]. We rely on the general principles of the CBE concept and sustainability principles to draw our conceptual framework used in this study (Fig 1). We show hypothesized linkages between CBE practices (sorting waste, using organic waste as compost, or as livestock feed) and household food security. Currently, households do sometimes directly use organic waste (green waste, cassava peels, and food waste) to feed livestock and if they do, it is without processing it first. For this study, we considered only households that feed organic waste generated within households to livestock within these households. However, within studied city-regions, some households would sort waste, but instead sell it to other households to feed their livestock. We consider the former as waste sorting households because we could not verify that sold waste was indeed fed to livestock. Households also sometimes use organic waste as compost by directly dropping it in farms where it decomposes. Households, especially those in urban and peri-urban areas, did also sometimes sort waste with an incentive to ease collection hence paying fewer fees to collection companies or selling high-value sorted waste. Hence, we treat all three CBE practices as primary practices and independent of each other. Essentially, CBE practices directly contribute to food security through 1) directly providing organic manure to replenish soil nutrients and enhance biomass production, hence leading to adequate food production, and 2) indirectly via income pathways facilitated by market sales of CBE products like (sorted) waste, compost, livestock feed, and farm products. Income from these sales improves food accessibility. Thus, when food is available and accessible, its utilization becomes possible. If food is produced under a sustainable resource use model like CBE, then stability becomes possible; thus, fulfilling the four dimensions of food security. In a sustainable resource use sense, CBE practices contribute to sustainable food consumption by enabling reductions in the use of external inputs, thus minimizing resource extraction and land degradation. In our data, we captured food availability and access and modeled direct associations between CBE practices and food security indicators. Direct associations of farm practices like production diversification and food security indicators have been previously studied [2225].

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Fig 1. The author’s Conceptual framework linking circular bioeconomy (CBE) practices to food security.

Circled in green are CBE practices and arrows show how they influence food security. HDDS is household dietary diversity score, HFIAS is household food insecurity access scale, and HFIAP is household food insecurity access prevalence.

https://doi.org/10.1371/journal.pstr.0000108.g001

2.2. Sampling and data collection

The study use household data from the RUNRES city regions of Bukavu in the Democratic Republic of Congo (DRC), Arba Minch in Ethiopia, Kamonyi in Rwanda, and Msunduzi in South Africa, where the project was implemented (Fig 2). The identification of households was guided by participation in key food commodity value chains in 2019. The study applied a two-stage sampling procedure to identify participating households in September 2020, after obtaining the ethics approval for the RUNRES research protocols from ETH Zurich in June 2020. First, a sample of local CBE organizations was selected from each country. Six organizations were selected from DRC, four of which worked on municipal organic waste valorization for compost, and two on human waste (urine) valorization. From Ethiopia, three organizations were selected, two of which worked on organic waste valorization, and one on banana processing for flour. From Rwanda, four organizations were selected, one working on cassava peels processing for livestock feed, another on organic waste sorting, and one on black soldier fly larvae production from organic waste. From South Africa, four organizations were selected where two were working on green waste valorization for compost, while another two worked on the valorization of fecal sludge and urine. These organizations were testing the production of CBE products for potential sale to households. Therefore, our sample, even though some households practiced CBE, it was on a less effective scale due to costs and skills needed, and some were not practicing CBE at all. The sample was therefore that of households presumed that they would benefit from RUNRES with skills accessed from RUNRES supported CBE organizations, to engage in quality and effective CBE practices at a later stage of RUNRES. From the lists of names of potential beneficiaries working under each CBE organization, at least 50 households were randomly selected for interviews. Hence, authors had access to personal information of potential respondents that could identify individual participants during or after data collection. Nevertheless, this information was only to be used for research purposes as guided by authors’ ethical institutional rules. Moreover, consent was obtained first from the respondents if they were willing to participate in the study where we indicated that data shared would strictly be used for research purposes. The consent obtained was informed and of written form documented in local languages on a separate sheet of paper (see consent form in supporting information translated in English). Since respondents were all adults from the age of 18 years, there was no need for minors’ consent. From the list of names of households obtained from the local administrative unit (village), participating households were selected randomly at an odd interval of five (5), and these selected households were then recorded in a different template with their location details, and handed to enumerators for contact making and interview scheduling. Subsequently, 256 households were interviewed in Bukavu, 139 in Arba Minch, 187 in Kamonyi, and 195 in Msunduzi, thus a total sample of 777 households. Trained enumerators electronically using the open data kit (ODK) collected data from respondents between December 2020 and January 2021, a period during which this study was conducted. Data collected included household demographics, CBE practices, types of foods consumed in the last 7 days, household food insecurity access in the past month, income, education, and access to production and market resources. Indicators of food insecurity used here are the usual indicators for the food insecurity index, elaborated by [26].

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Fig 2. Author’s Map of RUNRES city regions.

Produced under Humanitarian data exchange “numérisation Saint Moulin” source, in Arcgis Desktop software taken from the shape file https://data.humdata.org/m/dataset/cod-ab-cod.

https://doi.org/10.1371/journal.pstr.0000108.g002

2.3. Measurement of outcome variables

When analyzing food security [26], recommend using more than one indicator to achieve comprehensiveness. We, therefore, use three outcome variables as indicators of food security, including household dietary diversity score (HDDS), household food insecurity access scale score (HFIAS-score), and household food insecurity access prevalence (HFIAP).

Following [27], we measured HDDS using the aggregate food consumption index. The index measures the sum of food groups consumed in a household. HDDS reflects the dietary quality of foods consumed and is thus a good household nutrition security indicator [28]. HDDS is constituted by twelve food groups including cereals; white roots and tubers; vegetables; fruits; meat and its products; eggs; fish; legumes, nuts, and seeds; dairy and its products; oils and fats; sweets and sugars; and spices, condiments, and beverages. Hence, the maximum value of HDDS that a household can have is 12. HDDS has been previously widely used to analyze food and nutrition security [23,2830].

Following [26], the study calculated the HFIAS-score and HFIAP from household food insecurity modalities. Hence, HFIAS-score is a continuous variable measuring the degree of food insecurity access for each household, calculated by summing codes (0 to 3) for a particular food insecurity occurrence from responses to each of 9 questions. Therefore, the maximum HFIAS-score for any household is 27 and the minimum is 0. The higher the HFIAS-score, the more is the household experienced food insecurity (access) [26]. HFIAP is an ordinal (Ordinal is both Categorical and ordered) variable showing household food insecurity status in four categories: 1) food secure (generally experiences none of the food insecurity access conditions). 2) Mildly food insecure (generally worries about the sufficiency of food quantities). 3) moderately food insecure (can’t afford quality food, and cuts back on consumption volumes); and 4) severely food insecure (experiences one or more severe food insecurity conditions like no food, sleeping hungry, taking day and night without food. Hence, Similarities and differences are described in the table below between Household Dietary Diversity Score (HDDS), Household Food Insecurity Access Scale Score (HFIAS-score), and Household Food Insecurity Access Prevalence (HFIAP) are presented in Table 1 below.

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Table 1. Similarities and differences between Household Dietary Diversity Score (HDDS), Household Food Insecurity Access Scale Score (HFIAS-score), and Household Food Insecurity Access Prevalence (HFIAP).

https://doi.org/10.1371/journal.pstr.0000108.t001

2.4. Measurement of covariates

Alongside using CBE practices, we also used other covariates. The study introduces covariates and independent variables (using organic waste as compost, or as livestock feed, or sorting organic from inorganic waste practices) in the regression models. In order to reduce bias and increase statistical power and help to improve the accuracy of the model by accounting for the effect of other variables on the dependent variable (food security) [19,33]. For instance, the age of household heads was measured in years, which was hypothesized to affect food security positively. Household size, measured in persons within the household, was instead expected to negatively affect food security since more persons could reduce food volumes per person. Since some proportion of food is bought using income, income was expected to positively affect food security. Income is measured annually in mean United States dollars (USD). Access to production and market resources like land, credit, markets, use of mobile phones (measured as categorical variables), and higher education (measured in levels), were all expected to positively affect food security. Households engaging in growing crops (categorical) and being employed mainly in agriculture were also expected to affect food security positively. Male household headship (categorical) was expected to positively influence food security, due to differential access to resources and engagements in off-farm income-generating opportunities.

2.5. Analytical framework

The study used regression models to analyze associations between CBE practices and household food security indicators. Generally, we use a regression model specified in Eq (1). However, because outcome variables are different, the Eq (1) was modify accordingly. For continuous outcome variables like HDDS and HFIAS-core, we estimate Eq (1) as an Ordinary Least Squares (OLS) regression. However, because HDDS and HFIAS-score are censored with natural thresholds (0–12, and 0–27, respectively), OLS provides inconsistent parameter estimates. Hence, Eq (1) was estimated as a Tobit regression, which generates more robust estimates [34]. Nevertheless, results from both OLS and Tobit models were presented for comparison but discuss Tobit results only. To analyze associations between CBE practices and HFIAP, which is ordinal, the study estimated Eq (1) as an ordered logistic regression [35]. Ordinary Least Squares (OLS): This linear regression was used to estimates the relationship between a dependent variable and one or more independent variables. OLS works by minimizing the sum of the squared differences between the observed values and the corresponding fitted values. It is used to estimate the parameters in a regression model by drawing a line through the data points that best fits the data. Tobit Regression was used to estimate the parameters of a linear regression model when the dependent variable is either left-censored, right-censored, or both. The method is named after James Tobin, who developed it in the 1950s [35]. Ordered logistic regression was used to estimate the parameters of a logistic regression model as the dependent variable was ordinal. The method is used to model the relationship between a dependent variable and one or more independent variables. In addition, the study proceeded in Stata by using the "psmatch2" command [34]. The Propensity Score Matching (PSM) statistical technique to reduce selection bias in observational studies and to estimate the effect of CBE practices on food security. However, the data violated the proportional odds assumption for an ordered logit, hence, the study estimated Eq (1) as a generalized ordered logistic regression [36]. (1) Where FSIi is a food security indicator of interest (HDDS, HFIAS-score, or HFIAP) for householdi, Xij is a vector of J predictors for the ith household, including three independent CBE practices. β0 and βj are vectors of parameters to be estimated; εi is a random error term. Data were analyzed using Stata SE/16.0.

3. Results

3.1. Descriptive results

The study made intra, inter, city-region, and general descriptions of the sample (Table 2). However, due to limited space, we elaborated the results of the general sample and key variables across city-regions. For instance, from Fig 3, our sample had an average HDDS of 9 out of a maximum possible of 12 food groups–with Msunduzi having the highest average of 10, followed by Bukavu at 9, and least was Arba Minch and Kamonyi that consumed an average of 8 food groups. Regarding HFIAS-score, we observed a sample average of seven out of a maximum of 27. Bukavu and Arba Minch had the highest HFIAS-core values averaging at 8, followed by Msunduzi at 7, and least was Kamonyi at 4.

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Fig 3. Average values of Household Dietary Diversity Score (HDDS) and Household Food Insecurity Access Scale (HFIAS) score across city-regions.

https://doi.org/10.1371/journal.pstr.0000108.g003

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Table 2. Descriptive statistics of variables used in this study.

https://doi.org/10.1371/journal.pstr.0000108.t002

From Fig 4, results show that nearly 37% of our sample was severely food insecure, 30% moderately food insecure, 10% mildly food insecure, and only 23% were food secure. Kamonyi had the highest proportion of food-secure households (49%), followed by Arba Minch (32%), then Msunduzi (19%), and least was Bukavu (3%). However, severe food insecurity was highest in Arba Minch (51%), followed by Bukavu (39%), then Msunduzi (36%), and least was Kamonyi (25%).

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Fig 4. Proportions of households per Household Food Insecurity Access Prevalence (HFIAP) category per city-region.

https://doi.org/10.1371/journal.pstr.0000108.g004

From Table 2, regarding other key dependent variables, most households in the general sample (58%) were sorting waste, however, just 41% and 19% of households used organic waste as compost or livestock feed, respectively. At the country level, the highest levels of waste sorting were observed in Arba Minch (72%), followed by Kamonyi (68%), then Msunduzi (62%), and the least was in Bukavu (40%). However, the use of organic waste as compost was mostly observed in Kamonyi (76%), then Bukavu (38%), followed by Msunduzi (35%), and least was Arba Minch at 7%. Instead, organic waste was mostly used as livestock feeds in Msunduzi (34%), followed by Kamonyi (27%), then Arba Minch (16%), and least was Bukavu (4%). Within city regions, the use of organic waste as compost was more observed compared to other CBE practices like using organic waste as livestock feeds.

Regarding independent variables, households had on average heads of an age of about 45 years, an average household size of 8 persons, and a male household headship (77%) dominated. Most households (58%) grew crops, and most of them could access land (72%), credit (56%), and markets (51%). The sample massively used mobile phones (87%). A sizeable proportion (68%) was never formally educated beyond the secondary level, while only 18% had attained university education. The sample heavily depended on salaried employment or casual labor as the main source of income (34%), agriculture accounted for 28% of the income and grants remittances and pensions for 20%, while annual earnings were on average USD 1,478.

3.2. Regression results

Using organic waste as compost or as livestock feed are associated with a positive but insignificant effect on HDDS (Table 3). However, the effect of sorting waste on HDDS is significantly negative. In other words, households that sort waste were associated with a 0.3 unit decrease in HDDS. Such a decrease implies about a 3-percentage points (Percentage points increases or decreases are calculated based on sample averages of respective outcome variables in Table 1) reduction on average in several food groups consumed by households. Regarding HFIAS-score, using organic waste as livestock feed bears a very strong negative association, while sorting waste bears a strong positive association. The association with using organic waste as compost is not significant. Essentially, households using organic waste as livestock feed are associated with a reduction of 2.2 units in HFIAS-score, implying a 33-percentage point decrease in food insecurity, while those that sort waste are associated with an increase of 1.4 units in HFIAS-score, implying a 21-percentage point increment.

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Table 3. Regression results of circular bioeconomy (CBE) practices on household dietary diversity score (HDDS) and household food insecurity access scale (HFIAS) score.

https://doi.org/10.1371/journal.pstr.0000108.t003

Other covariates, alongside CBE practices, showed significant associations with both HDDS and HFIAS-score (Table 3). Market access was significantly associated with increases of 0.4 units in HDDS (4 percentage point increase), while each 100 USD increment in annual income was associated with a 1-unit increase in HDDS (11-percentage points increment). Additionally, using mobile phones was associated with an increase of 0.7 units in HDDS (8-percentage point increment). Having a household head with vocational education was associated with an increase of 0.9 units in HDDS (10-percentage point increment), while university-level was associated with an increase of one unit (11-percentage point increment). Surprisingly, being unemployed compared to relying on agriculture as the main source of income, was associated with an increase of 3.3 units (37 percentage point increment) in HDDS. Using city region fixed effects–represented by their names (lower section of Table 3), we assessed possible effects of households being in a particular city region on HDDS and HFIAS-score. Therefore, compared to Kamonyi, where the study finded the highest proportion of food-secure household in the context of this research, households in Msunduzi were associated with increases of 1.3 units in HDDS (14 percentage point increment), while those in Bukavu had even larger increases of up to 2.4 units (26 percentage point increment). However, Arba Minch households instead had a decrease of 0.5 units (6-percentage point decrease).

A one-year increase in the age of household heads was associated with a reduction of 0.1 units in HFIAS-score (2-percentage point decrease). Again, market access linked variables were tremendously associated with reductions in food insecurity. For instance, access to markets was associated with a reduction of 2.7 units in HFIAS-score (41 percentage point decrease), while each 100 USD increment in annual income was associated with a reduction of two units in HFIAS-score (30 percentage point decrease). Again, having higher education that favors access to better-paying jobs was associated with significant reductions in food insecurity. Having attained secondary, vocational, and university level education was associated with reductions of 3.3, 3.4, and 6.1 units in HFIAS-score, implying respectively a 50, 52, and 92-percentage points decrease. The use of mobile phones was also associated with a reduction of 1.6 units in HFIAS-score (24-percentage point decrease) while having male household heads was associated with a reduction of 1.4 units in HFIAS-score (21-percentage point decrease). Unemployment was surprisingly associated with a reduction of 5.1 units (78-percentage points) in the HFIAS-score. After controlling for city-region fixed effects, results revealed that households in other city regions compared to Kamonyi were associated with increases of about six units in HFIAS-score (90 percentage points increase).

Taking all thing evenly (See Table 4), the trend of associations between CBE practices and HFIAP categories, especially severe food insecurity, was such as using organic waste as compost was positively associated with severe food insecurity although insignificantly. Similarly, households that sorted waste were significantly more likely by 7 percent to be severely food insecure. More profoundly, households that used organic waste as livestock feed were significantly less likely to be severely food insecure by 18 percent. On the food, secure status, even though associations were insignificant, again households that used organic waste as livestock feed were the only ones likely to be food secure. Considering mild food insecurity, which is by order next preferred to the food secure category, still, households that used organic waste as livestock feed were significantly more likely to be mildly food insecure by 5 percent.

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Table 4. Regression results of circular bioeconomy (CBE) practices on household food insecurity access prevalence (HFIAP) categories.

https://doi.org/10.1371/journal.pstr.0000108.t004

3.3. Propensity score matching results

According to Table 5, the average food security would be 0.203 for household food insecurity access prevalence (HFIAP) category more than the average that would occur if all of the households has used CBE practices (using organic waste as compost, or as livestock feed, or sorting organic from inorganic waste). In addition, the average food security would be 1.283 for household food insecurity access scale score (HFIAS-score) more than the average that would occur if all of the households has used CBE practices (using organic waste as compost, or as livestock feed, or sorting organic from inorganic waste). Finally, the average food security would be 0.277 for household dietary diversity score (HDDS) score more than the average that would occur if all of the households has used CBE practices (using organic waste as compost, or as livestock feed, or sorting organic from inorganic waste).

4. Discussions

4.1. Descriptive results

Msunduzi had the highest HDDS, a factor that may be attributed to a more efficient functional market infrastructure in South Africa that enables food production, distribution, and access to markets. Access to markets has been found to be positively influential towards HDDS [37]. The high proportions of severe food insecurity were largely from Arba Minch (51%) and from Bukavu (39%). This does not come as a surprise because [38,39] stressed that food insecurity is a thorny issue in Arba Minch—Ethiopia, and that it can be determined by various parameters, such as poverty, climate change, political instability and conflicts and about 16% of the DRC population is suffering from severe food insecurity [40]. Furthermore, the high proportions of those sorting waste compared to those using organic waste as compost or livestock feed implies that there are other purposes or CBE practices under which households use sorted organic waste. For instance, waste is sold to other livestock farming households, waste collection companies also often require sorting for easier waste management, and or waste collection companies are paid or charge less to take it away sorted waste [41]. Therefore, it was more possible to find the use of waste as compost in crop farms. Access to land and other agricultural enabling infrastructures like credit, markets, and information exchange (mobile phone use) were essential for households to realize better returns from food systems [30,4244]. In this study, households reporting that salaries or casual labor were their main source of income, may not necessarily have their entire livelihood fully depend on salaries or casual labor. Finally, waste management is labor-intensive, and youths and women take advantage to provide labor and bolster their incomes [14,17,41]. Hence, this could also explain the high proportions of people dependent on supplying labor.

4.2. Regression and propensity score matching results

The significant negative association between sorting waste and HDDS could be explained by the nature of our sample, whose food consumption is also based on direct produce from their farm, as crops or animal products. Any potential income from sorting was prioritized towards other essential basic needs, such as, housing, education, clothing, health, and others. However, because sorting of waste could take away time that would be diverted to on-farm production (crop and livestock farming), yet realized incomes are also diverted to non-food consumption [30]. This easily turns the association to be negative. Some households sometimes must pay their waste to be taken away [41], thus reducing income reserves that would facilitate household food security. Therefore, CBE innovations could need to be cautious with promoting waste sorting in isolation if they aim to improve household food security. On the other hand, keeping livestock can help households alleviate household food insecurity in multiple ways; first by consuming livestock products (milk, eggs, meat) directly, secondly by selling livestock products for income, which can be used to buy other consumption items including food. Lastly, livestock provides manure that can be used in crop farms to increase biomass production, which can be consumed directly or indirectly through market sales for income [4548]. Therefore, it is not surprising that using organic waste as livestock feed within households that generate such organic waste is strongly associated with reductions in food insecurity within such households.

Larger contributions to HDDS in studied city-regions are mostly associated with market access enabling variables, like physical access to markets, increments in income, use of mobile phones, and higher education levels. With a generally functioning market infrastructure, like passable roads that enable physical access, and better income to enable financial access to markets, etc., the household in general was likely to have better HDDS via markets rather than own farming, thus concurring with [37] study. Higher education levels (vocational and university) enhance skills needed for higher-paying employment, from which earned income can be used to smooth consumption via markets [49]. Mobile phones enhance quick access to reliable markets and nutrition information, which also indirectly drives access to better and quality food types at competitive prices [30,50]. Given the advanced development in South Africa, households in Msunduzi could have an enhanced market access infrastructure thus being associated with better HDDS compared to households in Kamonyi. Some evidence points to market access being associated with better nutrition outcomes [37,51]. On the reverse, the Bukavu sample was from a more remote city-region where road and markets infrastructure were in poor conditions. Therefore, better HDDS in Bukavu could have been realized through enhanced diversification of the own farm. Evidence from neighboring Uganda has shown own-farm production diversity to be associated with better HDDS [25,29].

Results illustrate that, market access variables are associated with significant reductions in food insecurity, especially where most of our sample countries generally have a good market infrastructure. Gender (male household headship) are explicit regarding HFIAS-score and this findings corroborate with [24,37,51] studies. Males are usually less attached to household chores and usually leave homesteads for off-farm income opportunities [30,52,53]. Such opportunities allow males earn more incomes to smooth consumption, which is also consistent with [5355] and [56]. The higher likelihood of other city regions being associated with food insecurity compared to Kamonyi could be explained by government efforts in Rwanda to distribute food shortly before data collection in December 2020, while responding to the COVID-19 pandemic. Nevertheless, these food supplies were never the sole source of all household food needs. Rwandan households have enjoyed decades of political stability that could have fostered sustainable household food resources, unlike in some parts of Ethiopia and Eastern part of DR Congo, where armed conflicts have hampered stable food production. High living costs in South Africa, witnessed through a very high GDP, according to [57], could explain Msunduzi’s higher likelihood towards food insecurity, more so that the city region is dominantly inhabited by poor households.

The positive association between using organic waste as livestock feed and food security, as well as its strong significant negative association with severe food insecurity, further shows the potential of using organic waste as livestock feed towards enhancing household food security, while ensuring circular food systems. This is because, the CBE practice can easily impact household food security through livestock farming via multiple fronts as earlier highlighted, and documented by [47,46]. Therefore, CBE innovations that strongly aim to enhance food security while as well establishing circular food systems may have to prioritize valorization of organic waste into livestock feeds. Merely sorting organic waste could just fuel severe food insecurity because resources invested are not reused optimally. Hence, CBE innovations need to prioritize using sorted organic waste for food security viable enterprises like livestock feed. Nevertheless, we acknowledge that there may be other welfare indicators other than enhancing food security that could be achieved through CBE innovations for instance income generation, only that we provide no evidence of the latter in this study. On the other hand, using organic waste as compost currently bears insignificant associations with food security. This may point to a need for CBE innovations to produce quality compost effectively and help households harness sizeable benefits. Finally, the coefficient of all food security indicators were positive meaning, that the average food security would be improved for households more than the average that would occur if all of the households had used CBE practices (using organic waste as compost or as livestock feed, or sorting organic from inorganic waste).

4.3. Implication to the theory

According to [9], the circular bio economy is still a new concept for both the developing and developed countries. It offers a range of viable alternative strategies and is still in the emerging stage worldwide and the concept is now shifting from circular bioeconomy to the circular green economy theory [58]. The circular green economy theory is based on the concepts of sustainability, efficiency and circularity [59]. It aims to create a system in which resources are used efficiently, waste is minimized and the environment is protected. Circular bioeconomy practices, such as using organic waste as compost, feeding livestock and sorting waste, promote the theory of the circular green economy by encouraging sustainable resource use and reducing waste production [60]. By using organic waste as compost, we can minimize the amount of waste ending up in landfill and create a useful resource for agriculture. Using organic waste to feed livestock can decrease the need for alternative feed sources and promote sustainable livestock rearing practices [12]. Similarly, in terms of food security, the methods of the circular bioeconomy make it possible to increase the amount of food available and access to it, especially in low-income regions. By using organic waste as compost, we can increase soil fertility and boost crop yields. Using organic waste to feed livestock can reduce the cost of animal feed and increase the availability of animal protein. Sorting waste can also help reduce food waste, foster recycling and reuse and increase the availability of food for human consumption. By promoting circular bioeconomy practices, this study sheds light and lays the cornerstone for how the theory of the circular green economy could be materialize in the association between bio waste management and food security.

4.4. Study limitations

This study referred to the CBE concept, the key CBE independent variables were use of organic waste as compost or livestock feed and captured as dichotomous variables–thus only giving two dimensions (use or non-use) regarding waste usage, without information on quantities of waste used. Therefore, inferences that are more exact based on the amount of waste used for each purpose, was impossible to establish. Moreover, the variable “use of organic waste for livestock feed” would only be verified within that household where waste was generated. Those households who sorted waste but sold organic waste to other households that used it for livestock feed, were only considered as sorters, and the latter was not even considered in this study as households that used organic waste for livestock feed because we could verify that by our study design. Hence, the effects of using organic waste as livestock feed presented in this study could be understated. Furthermore, for households that sorted waste, some were incentivized by the fact that sorted waste could cost them less if they used waste collection companies or sold high-value waste for income. However, in our study, we could not disentangle the effect of such incentives from that of a preferred behavioral change–where households would naturally sort waste. Nevertheless, given the scarcity of literature on CBE practice on food security, we are optimistic that our results provide an informative foundation.

4.5. Lessons learnt

The lesson learned from the association of using circular bioeconomy practices of organic waste as compost, as livestock feed and sorting waste with food security is that circular bioeconomy practices can help to increase food availability and access, particularly in low-income communities. However, it is important to prioritize economically viable circular bioeconomy practices and incorporate mechanisms to reduce labor intensity to promote sustainable adoption. Hence, the study provides valuable insights into the adoption and impact of circular bioeconomy practices in African food systems as policies to stimulate CBE investments are roughly lapsed in all four countries. The current linear production model is insufficient to address global food insecurity. The CBE model, which emphasizes resource conservation through recycling and reusing organic waste, is crucial. Specifically, focusing on recycling and reusing organic waste helps close nutrient loops and establish resilient rural-urban nexus food systems. In addition, quality scientific evidence is more needed to guide CBE development and implementation and promoting CBE practices requires coordinated efforts by public authorities, integrative approaches, and inclusive stakeholder engagement. Bioeconomy should be considered part of the circular economy strategy in which public authorities taking a lead role in fostering circular bioeconomy.

5. Conclusions and recommendations

The study postulated that CBE practices provide a direct means of improving food security. Hence, result indicates that using CBE practices more likely adds a 0.203 score of food insecurity access prevalence (HFIAP), 1.283 food insecurity access scale (HFIAS-score) and 0.277 for household dietary diversity score (HDDS) among household using CBE practiced groups. Using organic waste as livestock feed consistently shows positive and generally significant associations with food security, while just sorting organic waste is consistently negatively and generally significantly associated with food security. This implies that promoting waste sorting in isolation may not be optimally beneficial for food security. However, associations between using organic waste as compost and food security are generally positive but insignificant–implying that using organic waste as compost could be a less viable CBE practice concerning food security. In addition, the average food security would be improved for households more than the average that would occur if all of the households had used all CBE practices. Therefore, CBE innovations aiming to optimally enhance household food security, while establishing circular food systems, could need to prioritize organic waste valorization into livestock feeds and take into account other socio-economics parameters, such as access to land, mobile phone, access to market, education level, income and city region where interventions took place. Further research should study the use of organic waste respectively as a continuous variable, to enable inferences based on the amount of waste used. This will foster a proper understanding of how unitary changes in waste could influence household dietary diversity and food security.

Supporting information

Acknowledgments

Authors are thankful to all RUNRES scientists, enumerators, and staff of RUNRES partners that have contributed to data collection, and technical guidance in writing this article.

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