Seasonality, climate change, and food security during pregnancy among Indigenous and non-Indigenous women in rural Uganda: Implications for maternal-infant health
Notice bibliographique
Résumé
BACKGROUND: Climate change is expected to decrease food security globally. Many Indigenous communities have heightened sensitivity to climate change and food insecurity for multifactorial reasons including close relationships with the local environment and socioeconomic inequities which increase exposures and challenge adaptation to climate change. Pregnant women have additional sensitivity to food insecurity, as antenatal undernutrition is linked with poor maternal-infant health. This study examined pathways through which climate change influenced food security during pregnancy among Indigenous and non-Indigenous women in rural Uganda. Specific objectives were to characterize: 1) sensitivities to climate-associated declines in food security for pregnant Indigenous women; 2) women's perceptions of climate impacts on food security during pregnancy; and 3) changes in food security and maternal-infant health over time, as observed by women. METHODS: Using a community-based research approach, we conducted eight focus group discussions-four in Indigenous Batwa communities and four in non-Indigenous communities-in Kanungu District, Uganda, on the subject of climate and food security during pregnancy. Thirty-six women with ≥1 pregnancy participated. Data were analysed using a constant comparative method and thematic analysis. RESULTS: Women indicated that food insecurity was common during pregnancy and had a bidirectional relationship with antenatal health issues. Food security was thought to be decreasing due to weather changes including extended droughts and unpredictable seasons harming agriculture. Women linked food insecurity with declines in maternal-infant health over time, despite improved antenatal healthcare. While all communities described food security struggles, the challenges Indigenous women identified and described were more severe. CONCLUSIONS: Programs promoting women's adaptive capacity to climate change are required to improve food security for pregnant women and maternal-infant health. These interventions are particularly needed in Indigenous communities, which often face underlying health inequities. However, resiliency among mothers was strong and, with supports, they can reduce food security challenges in a changing climate.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».