Dietary Patterns and Household Food Insecurity in Rural Populations of Kilosa District, Tanzania
Bibliographic record
Abstract
INTRODUCTION: Few studies have investigated the relationship between dietary pattern and household food insecurity. The objective of the present analysis was to describe the food consumption patterns and to relate these with the prevalence of food insecurity in the context of a rural community. METHODOLOGY: Three hundred and seven (307) randomly selected households in Kilosa district participated in the study. Data were collected during the rainy season (February-May) and post harvest season (September-October) in the year 2011. Food consumption pattern was determined using a 24-h dietary recall method. Food insecurity data were based on the 30 day recall experience to food insecurity in the household. Factor analysis method using Principal Components extraction function was used to derive the dietary patterns and correlation analysis was used to establish the existing relationship between household food insecurity and dietary patterns factor score. RESULTS: Four food consumption patterns namely (I) Meat and milk; (II) Pulses, legumes, nuts and cooking oils; (III) fish (and other sea foods), roots and tubers; (IV) Cereals, vegetables and fruits consumption patterns were identified during harvest season. Dietary patterns identified during the rainy season were as follows: (I) Fruits, cooking oils, fats, roots and tubers (II) Eggs, meat, milk and milk products (III) Fish, other sea foods, vegetables, roots and tubers and (IV) Pulses, legumes, nuts, cereals and vegetables. Household food insecurity was 80% and 69% during rainy and harvest-seasons, respectively (P = 0.01). Household food insecurity access scale score was negatively correlated with the factor scores on household dietary diversity. CONCLUSION: Food consumption patterns and food insecurity varied by seasons with worst scenarios most prevalent during the rainy season. The risk for inadequate dietary diversity was higher among food insecure households compared to food secure households. Effort geared at alleviating household food insecurity could contribute to consumption of a wide range of food items at the household level.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".