Perceived barriers and enablers for consuming a diverse diet in women residing in resource-poor communities in Cape Town, South Africa: a qualitative study
Bibliographic record
Abstract
Background: Several studies have shown that South Africans consume a diet low in variety.Objective: To explore the barriers and enablers for consuming a diverse diet in resource-poor communities around Cape Town.Design: A qualitative study design was used. Data were collected from focus-group discussions (FGDs) conducted in Afrikaans, IsiXhosa, and English, using a semi-structured guide.Setting: Twelve community sites in Cape Town, South Africa.Subjects: Study participants were 24 Black and 21 Mixed-ancestry women (n = 45) with a mean age of 49.7 ± 7.8 years.Results: Fourteen FGDs were conducted with an average of three participants per FGD. Six themes were identified from the FGDs, which included nutrition knowledge, perceptions of dietary diversity and its impact on health, individual factors, and social, physical environment, and societal influences on food choices. Perceived barriers to consuming a diverse diet included financial constraints, high food prices, and family taste preferences. Perceived enablers identified were individual taste preferences, access to food stores, community food aid, and food-store specials. Proposed facilitators to achieving a diverse diet included budgeting, income-generation activities, lowering food prices, and increasing community food aid.Conclusions: The findings of this study suggest that financial constraints, high food prices, and social factors limit the ability of women from resource-poor communities to consume a diverse diet and make healthy food choices. Public health interventions aimed at promoting healthier food choices and reducing diet-related diseases should address financial barriers and the cost of food.
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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 | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".