“When you have stress because you don’t have food”: Climate, food security, and mental health during pregnancy among Bakiga and Indigenous Batwa women in rural Uganda
Bibliographic record
Abstract
Climate change exerts wide-ranging and significant effects on global mental health via multifactorial pathways, including food insecurity. Indigenous Peoples and pregnant women inequitably experience the harms associated with climate change and food insecurity. This study explores food security and maternal mental health during pregnancy among rural Ugandan Bakiga and Indigenous Batwa women in the context of climate change. Using a community-based research approach, we conducted a series of focus group discussions about climate, food security, and health during pregnancy in four Indigenous Batwa communities and four Bakiga communities in rural Kanungu District, Uganda, as well as longitudinal follow up interviews later in the year. Data were evaluated using a qualitative thematic analysis. Women consistently identified mental health as an important factor affecting maternal-fetal wellbeing during pregnancy. Many women identified that weather and climate extremes, such as prolonged droughts and unpredictable weather events, have made it more difficult for them to obtain sufficient food for themselves and their families during pregnancy, resulting in significant mental distress. More extreme weather conditions have made physical labour difficult or impossible during pregnancy, and resultant hunger further decreased ability to obtain food—a vicious cycle. Women described how anxiety was compounded by worry about future famine, as they anticipated further decreases in crop yields and rising food prices in a changing climate. Indigenous Batwa women experienced additional distress around their lack of access to Indigenous lands and its nutritious food sources. Overall, mothers in rural Uganda described food insecurity and climate extremes as major sources of stress during pregnancy, and they anticipate challenges will worsen. Interventions to enhance adaptive capacity to climate change are needed and should have a focus on the intricate connections with food insecurity and mental health as drivers of overall maternal health.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".