Acculturation and Food Intake Among Ghanaian Migrants in Europe: Findings From the RODAM Study
Bibliographic record
Abstract
OBJECTIVE: This study examined the role of migration and acculturation in the diet of Ghanaian migrants in Europe by (1) comparing food intake of Ghanaian migrants in Europe with that of Ghanaians living in Ghana and (2) assessing the association between acculturation and food intake. DESIGN: Data from the cross-sectional multicenter study Research on Obesity and Diabetes among African Migrants were used. Food intake was assessed using a Ghana-specific food propensity questionnaire (134 items and 14 food groups); foods were grouped based on a model of dietary change proposed by Koctürk-Runefors. SETTING: Ghana, London, Amsterdam, and Berlin. PARTICIPANTS: A total of 4,534 Ghanaian adults living in Ghana and Europe, with complete dietary data. Of these, 1,773 Ghanaian migrants had complete acculturation data. MAIN OUTCOME MEASURE: Food intake (the weighted intake frequency per week of food categories). ANALYSIS: Linear regression. RESULTS: Food intake differed between Ghanaians living in Ghana and Europe. Among Ghanaian migrants in Europe, there were inconsistent and small associations between acculturation and food intake, except for ethnic identity, which was consistently associated with intake only of traditional staples. CONCLUSIONS AND IMPLICATIONS: Findings indicate that migration is associated with dietary changes that cannot be fully explained by ethnic, cultural, and social acculturation. The study provides limited support to the differential changes in diet suggested by the Koctürk-Runefors' model of dietary change.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".