Assessing Differences in Household Food Insecurity Vulnerabilities Post-Cyclone Idai in Beira, Mozambique
Notice bibliographique
Résumé
Food insecurity is a complex sustainability challenge that is being worsened by frequent extreme weather disasters, especially within low-to-middle-income-countries (LMICs). Mitigating post-disaster food insecurity requires data for targeted interventions. Yet, there is limited research on household-characteristics connections with post-disaster food insecurity in LMICs. This study therefore focused on the aftermath of the 2019 Cyclone Idai disaster in Beira, Mozambique, and examined the differences in household food insecurity vulnerabilities using household and personal food environment characteristics, and adaptations to the disaster. Social-ecological systems (SES) theoretical and disaster management lenses informed the collection of data across household (microsystem), community (mesosystem) and humanitarian institutions (macrosystem) levels, as well as the assessment of household food insecurity vulnerabilities. A mixed-methods sequential explanatory study design was employed. The quantitative study entailed a household survey that collected data from 975 households. However, descriptive, univariate and bivariate statistical analyses were conducted on n=709, which had a complete set of data for the Household Food Insecurity Access Scale (HFIAS) measurement of food insecurity, and the household, personal food environment and adaptation to disaster variables. The follow-up qualitative study entailed the use of interview guides to conduct audio-recorded focus-group discussions with households and community leaders, and key-informant interviews with selected personnel from humanitarian institutions addressing food insecurity. The qualitative data was transcribed verbatim, and thematic content analysis was applied. Both quantitative and qualitative results were triangulated to present the findings. There were statistically significant increases in household food insecurity one month after the cyclone compared to the month before levels (p<0.05), with the median HFIAS score increasing from 14 to 18 post-Cyclone Idai. The presence of multiple vulnerability characteristics such as large household sizes, severe underlying food insecurity and low-income within a household, influenced more severe food insecurity post-Cyclone Idai. Also, the displaced households of the study were isolated from food markets and had pre-existing food accessibility challenges within their personal food environment, which was compounded by the loss of houses post-cyclone. Most adaptations were made during Cyclone Idai response and not preparedness. Adaptations to the disaster that enabled food access included the use of household savings, and food-sourcing facilitated by bridging and linking social capital at the mesosystem and macrosystem levels. Regardless, the facilitation of food-sourcing adaptations was constrained by macrosystem level challenges in targeting vulnerable households for food aid distribution. Additionally, non-reciprocal bonding social capital interactions created food access constraints for households that gave to others. The findings support the mitigation of recurrent, severe post-disaster household food insecurity episodes in Beira, Mozambique. This requires the integration of interventions for household food insecurity, disaster risk reduction and equitable food systems, all underpinned by well-coordinated stakeholder collaborations across all SES levels.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
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Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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 ».