Notice bibliographique
Résumé
Food and Nutrition Security (FNS) is recognised by the international community as one of the most fundamental human rights and basic needs. Despite the political will and the resource mobilisation to address this pressing subject, achieving long-term FNS remains a major societal challenge. The persistence of malnutrition also suggests profound inequalities in the distribution of and access to food. Poor and disadvantaged people in low- and middle-income countries (LMICs), especially in Asia and Sub-Saharan Africa, are most affected. Past experiences show that interventions to address the FNS challenge are often fragmented, taking a mono-sectoral perspective. Also they tend to address the immediate causes of FNS rather than the underlying ones. It has been advocated that a food system approach, which is holistic and inter-sectoral in nature, could better address the persistent FNS challenge. In the transformation towards more sustainable, resilient and equitable food systems, nutrition-sensitive agriculture (NSA) could play a significant role. NSA is an approach that seeks to maximize agriculture’s contribution to nutrition. It uses agriculture as a delivery platform but includes other sectors, such as health, education, social protection, environment and natural resource management, to address the interlinked underlying determinants of undernutrition. Though NSA is presented as a promising example, evidence of its potential is not yet sufficient to justify long-term investments. Gaps exists regarding the factors that influence the implementation and scale-up of NSA, the effects of NSA interventions, and the pathways to improve nutrition. Therefore, the aim of this PhD research was to unravel the complexity of NSA as a multi-sectoral food system innovation that has the potential to reduce undernutrition in low- and middle-income countries in a sustainable way as well as to gain insights into evidence from NSA interventions in LMICs, especially in remote areas. This PhD research comprised five studies: a scoping review to develop an integrated FNS conceptual framework for NSA interventions; two systematic reviews respectively on impact pathways and factors influencing the implementation and scale-up of NSA in LMICs; two empirical case studies (qualitative and mixed methods) on the implementation of NSA interventions in Vietnam. The findings of the systematic reviews and the empirical case studies have been published in four peer-reviewed articles. This research demonstrated that NSA interventions through a combination of interlinked pathways can simultaneously address multiple underlying determinants of undernutrition especially when synergy among program/project components is achieved. The strengthening of local institutions was identified as a novel pathway, instrumental in promoting NSA sustainability and scale-up. Although NSA appears to have limited capacity to reduce stunting and wasting, it does improve the quantity and quality of diets, which along with other changes in the local communities (e.g., context-appropriate agricultural models, child care and feeding practices) could contribute to better FNS and to the transition towards sustainable food systems. Finally, building an enabling environment for NSA needs not just funding but actions at multiple levels. Programming should include flexibility, context-appropriateness, embedding and strengthening of local structures as well as supportive and coherent policies to facilitate the cross-sectoral collaboration. These findings will be useful for policy-makers, program planners, and implementers to improve the success of future NSA interventions in LMICs. However, not only LMICs but also high-income countries could benefit from the findings of this research when the NSA approach is implemented in areas with vulnerable populations prone to malnutrition problems.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,007 | 0,006 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,003 | 0,008 |
| Communication savante | 0,010 | 0,010 |
| Science ouverte | 0,002 | 0,012 |
| Intégrité de la recherche | 0,005 | 0,004 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,019 | 0,006 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».