IFPRI’s projects in Rwanda are committed to producing high quality, evidence-based outputs that contribute to agriculture development, food security, nutrition, and poverty alleviation. In particular, the publications below are representative of all IFPRI work related to Rwanda, not solely those produced as part of the Rwanda SSP.
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Regions/Countries
Year
Language
Warner, James; Rosenbach, Gracie; Benimana, Gilberthe; Mugabo, Serge; Niyonsingiza, Josue; Mukangabo, Emerence. 2024
Takeshima, Hiroyuki; Benimana, Gilberthe; Spielman, David J.; Warner, James. 2024
Benimana, Gilberthe; Warner, James; Mugabo, Serge. 2024
We use statistical methodologies, including factor and cluster analysis, combined with existing knowledge of the agricultural sector to define five types of Rwandan farmers, separated into two broad groups. The first group (Group A) includes three types broadly classified as less wealthy, less commercialized, with a net negative gross margin. Within this group the three types of farmers include: Type 1—Less commercialized older male headed households with larger families, Type 2—Better educated, youth headed households, who are more market oriented but have smaller land holdings, Type 3—Older female headed households who produce relatively lower agricultural production value relative to their assets owned.
Takeshima, Hiroyuki; Benimana, Gilberthe; Spielman, David J.; Warner, James. 2024
Warner, James; Benimana, Gilberthe; Mugabo, Serge; Ingabire, Chantal. 2024
Warner, James; Benimana, Gilberthe; Mugabo, Serge; Ingabire, Chantal. 2024
Benimana, Gilberthe; Warner, James; Mugabo, Serge. 2024
Warner, James; Manners, Rhys. 2024
Mugabo, Serge; Warner, James. 2024
Mugabo, Serge; Warner, James. 2024
Davis, Kristin; Rosenbach, Gracie; Spielman, David J.; Makhija, Simrin; Mwangi, Lucy. 2024
Warner, James; Benimana, Gilberthe Uwera; Mugabo, Serge; Niyonsingiza, Josue; Mukangabo, Emerence; Ingabire, Chantal. 2024
Schmidt, Emily; Mugabo, Serge; Rosenbach, Gracie. 2024
Mukashov, Askar; Robinson, Sherman; Thurlow, James; Arndt, Channing; Thomas, Timothy S.. 2024
International Food Policy Research Institute (IFPRI). Washington, DC 2023
Rosenbach, Gracie; Benimana, Gilberthe; Ingabire, Chantal; Spielman, David J.; Tumukunde, Ritha. Washington, DC 2023
• Compared to other countries in the region, women in Rwanda have relatively greater access to financial services and a relatively lower time burden in agriculture.
• However, when compared to men in Rwanda, inequalities persist. Women are significantly less likely than men to access financial services, participate in the marketing of agricultural commodities, access extension services, and spend their time on productive (rather than reproductive) work.
By adapting and promoting innovative and gender-inclusive financial products, shifting gendered cultural norms, providing extension to both the household head and the spouse, and investing in time-saving technologies and innovations, there are opportunities to reduce the gender gap in agriculture and increase agricultural productivity. Realization of these outcomes will depend partly on the implementation of the Gender and Youth Mainstreaming Strategy and PSTA 4, and partly on coordination with other gender-transformative programs in Rwanda.
Diao, Xinshen; Ellis, Mia; Rosenbach, Gracie; Mugabo, Serge; Pauw, Karl; Spielman, David J.; Thurlow, James. Washington, DC 2023
Rosenbach, Gracie; Benimana, Gilberthe; Ingabire, Chantal; Spielman, David J.; Tumukunde, Ritha. Washington, DC 2023
Diao, Xinshen; Ellis, Mia; Rosenbach, Gracie; Mugabo, Serge; Pauw, Karl; Spielman, David J.; Thurlow, James. Washington, DC 2023
The findings show that value chains differ in their effectiveness in promoting these different development outcomes. The wheat and sorghum value chain, for example, has strong anti-poverty effects and is effective at reducing hunger, but is less effective at increasing jobs. Trade-offs will emerge as no single value chain is most effective at achieving every desired outcome; therefore, promoting a few value chains jointly will diversify agrifood system growth and help achieve multiple development outcomes simultaneously.
Bryan, Elizabeth; Mawia, Harriet; Ringler, Claudia; Mane, Erdgin; Costa, Valentina; Ndoro, Rumbidzai. Rome, Italy; Washington, DC 2023
Warner, James; Rosenbach, Gracie; Benimana, Gilberthe; Mugabo, Serge; Niyonsingiza, Josue; Mukangabo, Emerence; Dushimayezu, Bertrand; Nshimiyimana, Octave; Ingabire, Chantal; Spielman, David J.. Washington, DC 2023
Bliznashka, Lilia; Jeong, Joshua; Jaacks, Lindsay M.. 2023
Warner, James; Marivoet, Wim; Covic, Namukolo; Umugwaneza, Maryse. 2023
Benimana, Gilberthe; Ritho, Cecilia; Irungu, Patrick. 2023
Hickman, William; Kramer, Berber; Mollerstrom, Johanna; Seymour, Greg. Fairfax, VA 2023
Lefore, Nicole; Ringler, Claudia . 2023
The research program’s five areas of inquiry will develop socio-technical bundles that support uptake of mechanization and irrigation, strengthen institutions for natural resource governance and climate resilience, enable scaling of suitable technologies and support development of human resources. The fifth area of inquiry makes a leap from technology to nutrition and health, with the specific aim to “formulate strategies for nutrition-sensitive mechanization and irrigation that safeguard and enhance health and inclusivity.”
International Food Policy Research Institute (IFPRI). Washington, DC 2022
Douthwaite, Boru; Johnson, Nancy L.; Wyatt, Amanda. Washington, DC 2022
Aragie, Emerta; Diao, Xinshen; Spielman, David J.; Thurlow, James; Mugabo, Serge; Rosenbach, Gracie; Benimana, Gilberthe. Washington, DC 2022
Aragie, Emerta; Diao, Xinshen; Spielman, David J.; Thurlow, James; Mugabo, Serge; Rosenbach, Gracie; Benimana, Gilberthe. Washington, DC 2022
Aragie, Emerta; Diao, Xinshen; Spielman, David J.; Thurlow, James; Mugabo, Serge; Rosenbach, Gracie; Benimana, Gilberthe. Washington, DC 2022
This study provides evidence that is designed to assist the Government of Rwanda in its selection of agricultural policy, investment, and expenditure portfolios that reflect the country’s broad focus on its food system and structural transformation. This process of prioritization will need to incorporate multiple public investments targeting multiple development outcomes and will need to be grounded in the costeffective use of public resources in a largely market-led transformation process. This data-driven and evidence-based approach must critically underpin an informed investment prioritization process that helps achieve ambitious targets in an environment constrained by limited public resources. The study uses the Rural Investment and Policy Analysis (RIAPA) economywide model developed by the International Food Policy Research Institute (IFPRI), with contributions from colleagues at the Ministry of Agriculture and Animal Resources (MINAGRI), the Ministry of Finance and Economic Planning (MINECOFIN) and the National Institute of Statistics of Rwanda (NISR). The study draws on data from multiple sources as well as expert insights to inform the application of RIAPA’s Agricultural Investment for Data Analyzer (AIDA) module as a tool to measure the impacts of alternative public expenditure options on multiple development outcomes. Using this integrated modeling framework, the study links agricultural and rural development spending to four specific outcomes: economic growth, job creation, poverty reduction, and diet quality improvement; at the same time, it considers the synergies and tradeoffs associated with the different investment options in the transformation process.
The paper first assesses the contribution of public expenditures to agricultural and rural development under the fourth Strategic Plan for Agriculture Transformation (PSTA 4) that extends between 2018 and 2024. These findings are important, given the fact that since the beginning of PSTA 4, the budget allocated to MINAGRI (measured in constant prices) has stagnated. Our results suggest that increased spending on agriculture is well justified and that such spending is essential if the Government of Rwanda is to achieve its long-term development goals.
Spielman, David J.; Mugabo, Serge; Rosenbach, Gracie; Ndikumana, Sosthene; Benimana, Gilberthe; Ingabire, Chantal. Washington, DC 2022
Using data from the Seasonal Agricultural Surveys, we simulate the impact of increasing fertilizer prices on fertilizer demand and use, which in turn affects fertilizer value-cost ratios at the plot level and, ultimately, maize, rice, and Irish potato output and the Government’s fertilizer subsidy bill. Findings indicate the following
• At current subsidy rates and market prices, national output across all seasons could decrease by up to 3 percent for maize, 2 percent for rice, and 12 percent for Irish potato under strong assumptions about farmers’ sensitivity to fertilizer prices. Weaker assumptions about their sensitivity result in much smaller decreases in output.
• At current subsidy rates and market prices, the fertilizer subsidy bill may increase from 7 percent of MINAGRI’s budget—inclusive of funds earmarked for districts—to 12 percent.
Ultimately, the policy challenge will be to determine whether a return to the original subsidy levels and rates is feasible and under what conditions. In the short term, volatility in international fertilizer prices may continue, particularly in light of the conflict in Ukraine, making it necessary to maintain the current subsidy regime. But I the medium term, it is possible to move towards market prices for fertilizer without dramatically affecting output, thereby providing more fiscal space for other priorities.
Dusingizimana, Petronille; Kazungu, Jules; Lalui, Armin; Milani, Peiman; Munanura, James; Nsabimana, Aimable; Sindi, Julius Kirimi; Spielman, David J.; Umugwaneza, Maryse. Washington, DC 2022
This note summarizes a recent diagnostic of Rwanda’s food systems and the policy landscape that shapes them. Emphasis is placed on six inter-related clusters: diet quality and nutrition security; livelihoods equity; environmental resilience; agricultural productivity; infrastructure capacity; and financing and investment.
Overall findings suggest an opportunity for a tangible shift in how public policy in Rwanda approaches its food systems and how the systems contribute to the broader national transformation process. We offer several policy recommendations to support the design of a coherent country strategy and policy framework. First, strengthen existing entities and mechanisms, and innovate on them. Second, develop a national food systems transformation strategy that is integrative, multi-sectoral, and action-oriented. Third, innovate on existing programs. Fourth, allow for learning through both success and failure. Fifth, invest in rigorous impact evaluation.
Dusingizimana, Petronille; Kazungu, Jules; Lalui, Armin; Milani, Peiman; Munanura, James; Nsabimana, Aimable; Sindi, Julius Kirimi; Spielman, David J.; Umugwaneza, Maryse. Washington, DC 2022
A food system comprises the full range of actors and activities originating from agriculture, livestock, forestry, or fisheries, as well as the broader economic, societal, and natural environments in which they operate. An inclusive and sustainable food systems transformation is a process of growth and development that is profitable for the full range of individual actors engaged in the system, beneficial for society including marginalized and vulnerable groups, and advantageous for the natural environment.
Rwanda’s journey towards a food systems transformation is well captured in Vision 2050, the National Strategy for Transformation (NST 1), and strategic plans for sectors such as agriculture, health, nutrition, commerce, and the environment. Their priorities are echoed in ongoing programs and investments of the government, its development partners, the private sector, and civil society.
Nonetheless, there are still challenges facing Rwanda’s efforts to sustain and accelerate progress along this journey. Efforts to overcome these challenges call for a deeper and more significant shift in thinking—informed by the food systems perspective—that is highlighted by stronger multi-sectoral approaches to problem-solving.
Overall findings suggest an opportunity for a tangible shift in how public policy in Rwanda approaches its food systems and how the systems contribute to the broader national transformation process. This means addressing how balances are struck—and tradeoffs are managed—between and among agriculture, nutrition, health, and the environment in the face of a climate crisis. It also means giving greater attention to the demand-side drivers in Rwanda’s food system, recognizing that singularly focused supply-side strategies rarely succeed in isolation. Finally, it means deepening the integration of policies and policy actors in the design and implementation phases of interventions that shape the food system.
We offer several recommendations to translate abstract ideas into a coherent and focused set of actions in the policy space.
1. Strengthen existing entities and mechanisms rather than create new ones.
2. Develop a national food systems transformation strategy that is integrative, multi-sectoral, and action-oriented.
3. Innovate on existing programs.
4. Allow for learning through both success and failure.
5. Invest in rigorous impact evaluation.
These actions aim to strengthen the policy environment that enables a truly broad-based food systems transformation. This enabling environment is itself an outcome of broad-based national conversations, integration across sectors, domains, and levels; and the encouragement of policy and program innovation.
Diao, Xinshen; Dorosh, Paul A.; Thurlow, James; Spielman, David J.; Smart, Jenny; Benimana, Gilberthe; Mugabo, Serge; Rosenbach, Gracie. Washington, DC 2022
Marivoet, Wim. Washington, DC 2022
Spielman, David J.; Mugabo, Serge; Rosenbach, Gracie; Ndikumana, Sosthene; Benimana, Gilberthe; Ingabire, Chantal. Washington, DC 2022
Washington, DC 2022
Diao, Xinshen; Ellis, Mia; Mugabo, Serge; Pauw, Karl; Rosenbach, Gracie; Spielman, David J.; Thurlow, James. Washington, DC 2022
The paper’s forward-looking analysis assesses potentially differential impacts of value-chain develop-ment efforts on broad development outcomes. The analysis measures the synergies and trade-offs of value-chain development in the context of an inclusive agricultural transformation. Such analysis is conducted using the Rwanda Computable General Equilibrium (CGE) model – an adaption of IFPRI’s Rural Investment and Policy Analysis (RIAPA) model to the Rwandan context.
The modeling results indicate that value chains differ considerably in their effectiveness in achieving development goals and there are significant trade-offs among different development goals from pro-moting a specific value chain. The value chains that make a larger contribution to growth or job crea-tion are not necessarily effective in reducing poverty or improving dietary quality – for example, value chains for coffee and tea – while value chains that play an important role in improving dietary quality may contribute less to job creation – such as vegetables or fruits. While there is no single value chain that can achieve all development goals effectively, it is possible to select a diversified set of value chains that complement each other in achieving different development goals. This latter strategy is a more realistic approach to growth and development.
Ragasa, Catherine; Charo-Karisa, Harrison; Rurangwa, Eugene; Tran, Nhuong; Shikuku, Kelvin Mashisia. 2022
Musumba, Mark; Palm, Cheryl A.; Komarek, Adam M.; Mutuo, Patrick K.; Kaya, Bocary. 2022
Iruhiriye, Elyse; Olney, Deanna K.; Frongillo, Edward A.; Niyongira, Emmanuel; Nanama, Simeon; Rwibasira, Eugene; Mbonyi, Paul; Blake, Christine E.. 2022
Hawkes, Corinna; Ambikapathi, Ramya; Anastasiou, Kim; Brock, Jessica; Castronuovo, Luciana; Fallon, Naomi; Malapit, Hazel J.; Ndumi, Assumpta; Samuel, Folake; Umugwaneza, Mayse; Wanjohi, Milkah N.; Zorbas, Christina. 2022
Muhoza, Benjamin Kanze; De Herdt, Tom; Marivoet, Wim. Paris 2022
Babu, Suresh Chandra; Franzel, Steven; Davis, Kristin E.; Srivastava, Nandita. Washington, DC 2021
Policies and strategies play an important role in creating an enabling environment for youth engagement in agriculture, including by fostering transparency and accountability in the policy system and promoting youth engagement in the private sector through agricultural extension and other services. Institutions and intermediaries provide financial support, training, and access to market for youth entrepreneurs. Support in these areas should be strengthened. Systems approaches, such as multi-stakeholder platforms, provide holistic support to young agripreneurs (entrepreneurs in agriculture), but require effective coordination. Similarly, information and communication technologies can play a facilitating role by providing platforms to network and receive updated market information but need to be significantly scaled up. Individual capacities can drive youth engagement in agriculture and agripreneurship but must continue to be built up through expanded education and training on technical and functional skills.
As policymakers and program managers search for interventions that can promote youth involvement in agriculture in their own countries, the insights from the five countries examined that are presented in this paper may be useful for identifying context-specific challenges and pathways to successful youth engagement in agriculture in their own countries. The framework presented here can be applied to study youth engagement issues in any country or in sub-national, decentralized contexts to generate evidence to guide the design of youth-in-agriculture development programs. There is a need to support, strengthen, and implement the driving factors identified in this paper for expanding youth engagement in agriculture.
Aragie, Emerta; Diao, Xinshen; Robinson, Sherman; Rosenbach, Gracie; Spielman, David J.; Thurlow, James. Washington, DC 2021
- Results show that during the six-week lockdown that began in March, Rwanda’s GDP fell 39.1 percent (RWF 435 billion; USD 484 million) when compared to a no-COVID situation in the same period.
- Results further show that Rwanda’s GDP in 2020 will be between 12 and 16 percent lower than a predicted no-COVID GDP, depending on the pace of the recovery. The losses in annual GDP are between RWF 1.0 and 1.5 trillion (USD 1.1–1.6 billion).
- While GDP for the industrial and services sectors were estimated to have fallen during the lockdown period by 57 and 48 percent, respectively, exemptions of COVID-19 restrictions for the agricultural sector limited the decline in agricultural GDP to 7 percent compared to a noCOVID situation.
- During the lockdown period, the national poverty rate is estimated to have increased by 10.9 percentage points as 1.3 million people, mostly in rural areas, fell into temporary poverty. Poverty rates are expected to stabilize by the end of 2020, increasing only by between 0.4 and 1.1 percentage points. While these figures may be encouraging, they mask the impacts on poor households of the sharp poverty spike during the lockdown and the inherent complexity of poverty dynamics post-lockdown.
Looking forward, the speed and success of Rwanda’s recovery will depend critically on the expansion of Rwanda’s social protection programs, boosting enterprises of all sizes, support to the agri-food system, and restoration of international trade.
Aragie, Emerta; Diao, Xinshen; Robinson, Sherman; Rosenbach, Gracie; Spielman, David J.; Thurlow, James. Washington, DC 2021
• During the six-week lockdown that began in March 2020, we estimate Rwanda’s GDP fell 39.1 percent (RWF 435 billion; USD 484 million) when compared to a no-COVID situation.
• Rwanda’s GDP in 2020 will be between 12 and 16 percent lower than a predicted no-COVID GDP, depending on the pace of economic recovery. The losses in annual GDP are between RWF 1.0 and 1.5 trillion (USD 1.1 to 1.6 billion).
• While GDP for the industrial and services sectors were estimated to have fallen during the lockdown period by 57 and 48 percent, respectively, exemptions of COVID-19 restrictions for the agricultural sector limited the decline in agricultural GDP to 7 percent compared to a no-COVID situation.
• During the lockdown period, the national poverty rate is estimated to have increased by 10.9 percentage points as 1.3 million people, mostly in rural areas, fell into temporary poverty. Poverty rates are expected to stabilize by the end of 2020, increasing only by between 0.4 and 1.1 percentage points over the pre-COVID situation. While these figures are encouraging, they mask the impacts on poor households of the sharp poverty spike during the lockdown and the inherent complexity of poverty dynamics post-lockdown.
Looking forward, the speed and success of Rwanda’s economic recovery will depend critically on expanding Rwanda’s social protection programs, supporting enterprises of all sizes, providing broad assistance to the agri-food system, and restoring international trade.
Diao, Xinshen; Rosenbach, Gracie; Spielman, David J.; Aragie, Emerta. Washington, DC 2021
Diao, Xinshen; Rosenbach, Gracie; Spielman, David J.; Aragie, Emerta. Washington, DC 2021
Main results:
Nationally, during the lockdown period between March and May 2020, the simulation results estimate declines in household income by 33 percent on average. The urban population experienced the largest declines, averaging 40 percent during this period.
Unlike patterns seen with other shocks, middle-income households experienced the sharpest declines in income during the lockdown of an estimated 33 to 35 percent.
The share of individuals falling into poverty was highest among those in urban, middle income (Ubudehe 2) households (27 percent). However, the greatest absolute number of individuals in poverty remained concentrated in rural areas during the lockdown.
Poor individuals in the lowest expenditure quintile remain in the most severe poverty, with average expenditures during the lockdown estimated at 54 percent below the poverty line.
Under both the fast and slow post-COVID economic recovery scenarios used in the simulations, household incomes nearly return to pre-COVID levels for all household categories by the end of 2020. However, these results do not capture the potential longterm impacts of the substantial shocks of the pandemic to incomes, assets, and individual wellbeing.
These modeling results suggest that targeting should be a central component of the design and implementation of social protection programs and economic recovery policies to support a diverse set of beneficiaries. These beneficiaries include rural farming households and poor households, as well as nonagricultural household, and households in the middle expenditure quintiles.
Neza, Brian Nicholas; Higiro, Joseph; Mwangi, Lucy Wangari; Ochatum, Nathan. Rome, Italy 2021
Hirvonen, Kalle; Rosenbach, Gracie; Spielman, David J.. Washington, DC 2021
• Food prices did not significantly rise (or fall) during the COVID-19 pandemic in Rwanda.
• Prices of staple foods (cereals and other starches) declined following the pandemic’s onset in March 2020, while the prices of pulses (the second largest food consumption group in Rwanda after staple foods) experienced a seasonal spike at the end of 2021, but returned to below pre-pandemic levels throughout 2021.
• For most food groups, price trends in each province generally followed the national price trends during the pandemic, with the exception of poultry and eggs.
• Nationally, prices of poultry and eggs declined after the beginning of the pandemic, but these prices vary significantly by province, with prices in the Northern Province remaining above pre-pandemic levels and prices in all other provinces falling since the pandemic, with prices in Kigali City falling the most.
Overall, these results suggest that households in Rwanda were not hit by the “double whammy” of decreased incomes and rising food prices, since food prices remained stable Rather, they may instead have only suffered from decreased incomes. These findings suggest that continued efforts to expand Rwanda’s social protection programs are needed to boost household purchasing power and ensure that households are able to consume more – and more nutritious – foods.
Aragie, Emerta; Diao, Xinshen; Thurlow, James. Washington, DC 2021
Douthwaite, Boru. Washington, DC 2021
Arsenault, Joanne E.; Olney, Deanna K.. 2021
Gillespie, Stuart; Harris, Jody; Nisbett, Nicholas; van den Bold, Mara. 2021
Benimana, Gilberthe Uwera; Ritho, Cecilia; Irungu, Patrick. 2021
Franzel, Steven; Miiro, Richard; Uwitonze, Nicolas; Davis, Kristin; Luzobe, Beatrice; Rurangwa, Raphael. 2021
For-profit, private EAS is emphasized in this study because of the rapid growth of commercial agriculture, greater public policy emphasis on private market mechanisms and the sector’s potential for providing EAS on a sustainable basis (AUC, 2015; DLEC, 2019). While not a substitute for public EAS, private EAS often complement them effectively (Zhou and Babu, 2015, DLEC, 2019).
Okumu, Boscow Odhiambo; Rajendran, Srinivasulu; Okello, Julius; Ward, Patrick; Gatto, Marcel; Kilwinger, Fleur; Maredia, Mywish; Kirimi, Sindi; Nshimiyimana, Jean Claude; Spielman, David J.. Lima, Peru 2021
Kramer, Berber; Rose, Alison; Dejene, Samson; Mukangabo, Emerence; Mollerstrom, Johanna; Seymour, Greg; Kagabo, Desire. Wageningen, The Netherlands 2021
Mitik, Lulit; Fofana, Ismaël; Diallo, Mariam Amadou. Washington, DC 2020
Marivoet, Wim; Ulimwengu, John M.; Sall, Leysa Maty. Washington, DC 2020
Luna, Sarah V.; Pompano, Laura M.; Lung'aho, Mercy; Gahutu, Jean Bosco; Haas, Jere D.. 2020
Iron-biofortified staple foods can improve iron status and resolve iron deficiency. However, whether improved iron status from iron biofortification can improve physical performance remains unclear.
Objective
This study aimed to examine whether changes in iron status from an iron-biofortified bean intervention affect work efficiency.
Methods
A total of 125 iron-depleted (ferritin <20 μg/L) female Rwandan university students (18–26 y) were selected from a larger sample randomly assigned to consume iron-biofortified beans (Fe-Bean; 86.1 mg Fe/kg) or conventional beans (control: 50.6 mg Fe/kg) twice daily for 18 wk (average of 314 g beans consumed/d). Blood biomarkers of iron status (primary outcome) and physical work efficiency (secondary outcome) were measured before and after the intervention. Work performed was assessed during 5-min steady-state periods at 0-, 25-, and 40-W workloads using a mechanically braked cycle ergometer. Work efficiency was calculated at 25 W and 40 W as the work accomplished divided by the energy expended at that workload above that expended at 0 W. General linear models were used to evaluate the relation between changes in iron status biomarkers and work efficiency. Results The Fe-Bean intervention had significant positive effects on hemoglobin, serum ferritin, and body iron stores but did not affect work efficiency. However, 18-wk change in hemoglobin was positively related to work efficiency at 40 W in the full sample (n = 119; estimate: 0.24 g/L; 95% CI: 0.01, 0.48 g/L; P = 0.044) and among women who were anemic (hemoglobin <120 g/L) at baseline (n = 43; estimate: 0.64 g/L; 95% CI: 0.05, 1.23 g/L; P = 0.036). Among women who were nonanemic at baseline, change in serum ferritin was positively related to change in work efficiency at 40 W (n = 60; estimate: 0.50 μg/L; 95% CI: 0.06, 0.95 μg/L; P = 0.027). Conclusions Increasing iron status during an iron-biofortified bean feeding trial improves work efficiency in iron-depleted, sedentary women. This trial was registered at clinicaltrials.gov as NCT01594359.
Thurlow, James. 2020
Petry, Nicolai; Wirth, James; Friesen, Valerie; Rohner, Fabian; Nkundineza, Arcade; Boy, Erick; Birol, Ekin; Mudyahoto, Bho. 2020
Davis, Kristin E.; Franzel, Steven; Luzobe, Beatrice; Miiro, Richard; Rurangwa, Raphael; Uwitonze, Nicholas. 2020
Franzel, Steven; Lowicki-Zucca, Jane; Miiro, Richard; Uwitonze, Nicolas. 2020
Franzel, S.; Miiro, R.; Uwitonze, N.; Davis, Kristin E.; Luzobe, B.; Rurangwa, R.. Washington, DC 2020
Franzel, S.; Miiro, R.; Uwitonze, N.; Davis, Kristin E.; Luzobe, B.; Rurangwa, R.. Washington, DC 2020
Resnick, Danielle; Haggblade, Steven; Benson, Todd; Crawford, Eric. East Lansing, MI 2019
Ramani, Gayathri V.; Heckert, Jessica; Go, Ara; Iruhiriye, Elyse; Niyongira, Emmanuel; Olney, Deanna K.. Washington, DC 2019
Iruhiriye, Elyse; Olney, Deanna K.; Ramani, Gayathri V.; Heckert, Jessica; Niyongira, Emmanuel; Frongillo, Edward A.. Washington, DC 2019
Iruhiriye, Elyse; Olney, Deanna K.; Ramani, Gayathri V.; Heckert, Jessica; Niyongira, Emmanuel; Frongillo, Edward A.. Washington, DC 2019
Resnick, Danielle; Haggblade, Steven; Benson, Todd; Crawford, Eric. East Lansing, MI 2019
International Food Policy Research Institute (IFPRI). Washington, DC 2019
Vaiknoras, Kate; Larochelle, Catherine; Birol, Ekin; Asare-Marfo, Dorene; Herrington, Caitlin. 2019
Del Prete, Davide; Ghins, Léopold; Magrini, Emiliano; Pauw, Karl. 2019
Iruhiriye, Elyse; Olney, Deanna K.; Heckert, Jessica; Ramani, Gayathri; Frongillo, Edward A.; Niyongira, Emmanuel. 2019
Funes, José; Sun, Laixiang; Benson, Todd; Sedano, Fernando; Baiocchi, Giovanni; Birol, Ekin. 2019
Funes, José; Sun, Laixiang; Benson, Todd; Sedano, Fernando; Baiocchi, Giovanni. 2019
Wenger, Michael J.; Rhoten, Stephanie E.; Murray-Kolb, Laura E.; Scott, Samuel P.; Boy, Erick; Gahutu, Jean-Bosco; Haas, Jere D.. 2019
Franzel, S.; Kinyua, H.; Rucibigango, M.; Davis, Kristin E.; Makh, S.. Washington, DC 2019
del Prete, Davide; Ghins, Leopold; Magrini, Emiliano; Pauw, Karl. Washington, DC 2018
Compact2025. Washington, D.C. 2018
Tailor, Anish; Bugenimana, Eric Derrick; Aimable, Gatete; Beintema, Nienke M.. Washington, DC 2018
Tailor, Anish; Aimable, Gatete; Beintema, Nienke M.. Washington, DC 2018
Flaherty, Kathleen; Beintema, Nienke M.; Gatete, Aimable. Washington, DC 2018
Muange, Elijah N.; Oparinde, Adewale. Washington, DC 2018
Diao, Xinshen; McMillan, Margaret S.. 2018
MacNairn, Ian; Davis, Kristin E.. Washington, DC 2018
International Food Policy Research Institute (IFPRI) . Washington, D.C. 2017
Malabo Montpellier Panel. Dakar, Senegal 2017
Oparinde, Adewale; Murekezi, Abdoul; Birol, Ekin; Katsvairo, Lister. Washington, D.C. 2017
van Soesbergen, Arnout; Arnell, Andrew P.; Sassen, Marieke ; Stuch, Benjamin; Schaldach, Rüdiger; Göpel, Jan; Vervoort, Joost; Mason-D’Croz, Daniel; Islam, Shahnila; Palazzo, Amanda. 2017
Murekezi, Abdoul; Oparinde, Adewale; Birol, Ekin. 2017
Almanzar, Miguel; Torero, Maximo. 2017
Diao, Xinshen. New York, NY 2017
Mulambu J.; Andersson, Meike S.; Palenberg, M.; Pfeiffer, Wolfgang; Saltzman, Amy; Birol, Ekin; Oparinde, Adewale; Boy, Erick; Herrington, Caitlin; Asare-Marfo, Dorene; Lubobo, A.; Mukankusi, C.; Nkalubo, S.. 2017
Larochelle, Catherine; Asare-Marfo, Dorene; Birol, Ekin; Alwang, Jeffrey. Washington, D.C. 2016
International Food Policy Research Institute (IFPRI). Washington, D.C. 2016
Asare-Marfo, Dorene; Herrington, Caitlin; Alwang, Jeffrey; Birachi, Eliud; Birol, Ekin; Diressie, Michael Tedla; Dusenge, Leonidas; Funes, José; Katungi, Enid; Labarta, Ricardo; LaRochelle, Catherine; Katsvairo, Lister; Lividini, Keith; Lubowa, Abdelrahman; Moursi, Mourad; Mulambu, Joseph; Murekezi, Abdoul; Musoni, Augustine; Nkundimana, Jean d’Amour; Oparinde, Adewale; Vaiknoras, Kate; Zeller, Manfred. Washington, D.C. 2016
Beintema, Nienke M.; Gatete, Aimable; Perez, Sandra. Washington, D.C. 2016
Asare-Marfo, Dorene; Herrington, Caitlin; Birachi, Eliud; Birol, Ekin; Cook, Kristy; Diressie, Michael Tedla; Dusenge, Leonidas; Funes, José; Katsvairo, Lister; Katungi, Enid; Labarta, Ricardo; LaRochelle, Catherine; Lividini, Keith; Moursi, Mourad; Mulambu, Joseph; Murekezi, Abdoul; Musoni, Augustine; Nkundimana, Jean d'Amour; Vaiknoras, Kate; Zeller, Manfred. Washington, D.C. 2016
growing an HIB—the equivalent of approximately 350,000 households. Detailed results of the listing exercise are available in a separate report3. The second part of the study was a more detailed household survey, which was conducted among a subsample of nearly 1,400 bean-farming households, immediately after harvest had taken place. Both the listing and main household survey are nationally representative of rural bean producing households in Rwanda. This report presents key descriptive results from the main survey and sheds light on issues that may be investigated further in forthcoming publications. Key takeaways from the report are summarized below.
International Food Policy Research Institute (IFPRI). Washington, D.C. 2016
Compact2025. Washington, D.C. 2016
Compact2025. Washington, D.C. 2016
Petry, Nicolai; Rohner, Fabian; Gahutu, Jean B.; Campion, Bruno; Boy, Erick; Tugirimana, Pierrot L.; Zwahlen, Christian; Wirth, James P.; Moretti, Diego; Zimmermann, Michael B. 2016
Taylor, J. Edward; Filipski, Mateusz J.; Alloush, Mohamad; Gupta, Anubhab; Rojas Valdes, Ruben Irvin; Gonzalez-Estrada, Ernesto. 2016
Oparinde, Adewale; Birol, Ekin; Murekezi, Abdoul; Katsvairo, Lister; Diressie, Michael Tedla; Nkundimana, Jean d'amour; Butare, Louis. 2016
Johnson, Nancy L.; Guedenet, Hannah; Saltzman, Amy. Washington, D.C. 2015
Oparinde, Adewale; Birol, Ekin; Murekezi, Abdoul; Katsvairo, Lister; Diressie, Michael T.; Nkundimana, Jean d'Amour; Butare, Louis. Washington, D.C. 2015
HarvestPlus. Washington, D.C. 2015
International Food Policy Research Institute (IFPRI). Washington, D.C. 2015
van Rijn, F.; Nkonya, Ephraim M.; Adekunle, A.. 2015
Diao, Xinshen; McMillan, Margaret S.. Cambridge, MA 2015
Benin, Samuel. Washington, D.C. 2014
Malapit, Hazel J.; Sproule, Kathryn; Kovarik, Chiara; Meinzen-Dick, Ruth Suseela; Quisumbing, Agnes R.; Ramzan, Farzana; Hogue, Emily; Alkire, Sabina. Washington, D.C. 2014
Diao, Xinshen; Bahiigwa, Godfrey; Pradesha, Angga. Washington, D.C. 2014
HarvestPlus. Washington, DC 2014
Katsvairo, Lister. Washington, D.C. 2014
Rahija, Michael; Gatete, Aimable. Washington, D.C. 2014
Diao, Xinshen; McMillan, Margaret S.. Washington, D.C. 2014
International Food Policy Research Institute (IFPRI). Washington, D.C. 2014
Bizoza, Alfred R.; Rwirahira, John; Bizimana, Claude. Washington, D.C. 2014
Pradesha, Angga; Diao, Xinshen. Washington, D.C. 2014
Murekezi, Abdoul; Jin, Songqing; Loveridge, Scott. 2014
Petry, Nicolai; Egli, Ines; Gahutu, Jean B.; Tugirimana, Pierrot L.; Boy, Erick; Hurrell, Richard. 2014
Fiedler, John L.; D'Agostino, Alexis; Sununtnasuk, Celeste. Arlington, VA 2014
Bizimana, Claude. Washington, D.C. 2013
Tenge, Ngoga G.; Alphonse, Mutabazi; Thomas, Timothy S.. Washington, D.C. 2013
Farrow, Andrew; Opondo, Chris; Rao, KPC; Tenywa, Moses; Njeru, Rose; Kashaija, Imelda; Kamugisha, Rick; Ramazani, Michel; Nkonya, Ephraim M.; Kayiranga, Didace; Lubanga, Lunze; Nabahungu, Leon; Kamale, Kambale; Mugabo, Josaphat; Mutabazi, Sunday. 2013
Diao, Xinshen, ed.; Thurlow, James, ed.; Benin, Samuel, ed.; Fan, Shenggen, ed.. Washington, D.C. 2012
Diao, Xinshen; Fan, Shenggen; Kanyarukiga, Sam; Yu, Bingxin. Washington, D.C. 2012
Tenge, Ngoga G.; Alphonse, Mutabazi; Thomas, Timothy. Washington, D.C. 2012
Diao, Xinshen; Thurlow, James; Benin, Samuel; Fan, Shenggen. Washington, D.C. 2012
Bizimana, Claude; Usengumukiza, Felicien; Kalisa, John; Rwirahira, John. Nairobi, Kenya 2012
Flaherty, Kathleen; Munyengabe, Jean Marie. Washington, D.C. 2011
Diao, Xinshen; Fan, Shenggen; Kanyarukiga, Sam; Yu, Bingxin. Washington, D.C. 2010
Lambert, Melissa; MacNeil, Marcia. Washington, D.C. 2009
Diao, Xinshen; Fan, Shenggen; Kanyarukiga, Sam; Yu, Bingxin. New York, NY 2008
Diao, Xinshen; Hazell, P. B. R.; Resnick, Danielle; Thurlow, James. Washington, DC 2007
Diao, Xinshen; Fan, Shenggen; Yu, Bingxin; Kanyarukiga, Sam. Washington, D.C. 2007
Diao, Xinshen; Hazell, P. B. R.; Resnick, Danielle; Thurlow, James. Washington, DC 2007
Diao, Xinshen; Hazell, P. B. R.; Resnick, Danielle; Thurlow, James. Washington, DC 2006
Gillespie, Stuart. Washington, D.C. 2006
Donovan, Cynthia; Bailey, Linda A.. Washington, D.C. 2006
Gillespie, Stuart, ed.. Washington, DC 2006
Jayne, Thomas S.; Villarreal, Marcela; Pingali, Prabhu; Hemrich, Gunter. Washington, D.C. 2006
Stillwaggon, Eileen. Washington, D.C. 2006
Bond, Virginia. Washington, D.C. 2006
Gillespie, Stuart; Kadiyala, Suneetha; Binswanger-Mkhize, Hans P.. Washington, DC 2006
Gavian, Sarah; Galaty, David; Kombe, Gilbert. Washington, D.C. 2006
Loevinsohn, Michael. Washington, DC 2006
Egge, Kari; Strasser, Susan. Washington, D.C. 2006
Barnett, Tony. Washington, D.C. 2006
Minot, Nicholas. 1998
Bliven, Neal Wayne. Washington, DC 1995
Bliven, Neal Wayne. Washington, D.C. 1994
Bouis, Howarth. Baltimore, MD 1994
Islam, Nural. Baltimore, MD 1994
Kennedy, Eileen. Baltimore, MD 1994
von Braun, Joachim. Baltimore, MD 1994
von Braun, Joachim. Baltimore, MD 1994
Abbott, John C.. Baltimore, MD 1994
von Braun, Joachim, ed.; Kennedy, Eileen T., ed.. Baltimore, MD 1994
Glover, David. Baltimore, MD 1994
Blanken, Jürgen; von Braun, Joachim; de Haen, Hartwig. Baltimore, MD 1994
von Braun, Joachim; Kennedy, Eileen T.. Baltimore, MD 1994
Blanken, Juergen; von Braun, Joachim; de Haen, Hartwig. Baltimore, MD 1994