Home Food Environments of Mothers in South-Eastern Africa and California-An Illustration of Global Extremes
Bibliographic record
Abstract
INTRODUCTION: The type and availability of food in the home is known to directly shape food intake and weight status, but cross-cultural differences remain poorly documented. OBJECTIVE: The purpose of this study was to describe and compare the home food environments of low-income, childbearing women living in a low-income country (Malawi) and a high-income country (United States). METHODS: A home food environment survey was available in 714 mothers in Malawi (mean BMI 19.5, mean age 22.1 years) and 371 in California (mean BMI 31.8, mean age 28.1 years). RESULTS: Mothers in California vs. Malawi had on average (SD) 22.8 (4.4) vs. 1.2 (1.4) different food items in the home. The women in California had an abundance of fruits and vegetables that were virtually absent in the homes of Malawian women. The most prevalent food in the homes in Californian women was rice (in 97% homes) and in Malawian women was corn flour (in 47% of homes). CONCLUSIONS: Given the global extremes in food availability, efforts to address over and under food availabilities in the homes of childbearing women need to move beyond country centric approaches. It is time to consider maternal and child health as a global priority.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".