The Association between Acculturation and Dietary Patterns of South Asian Immigrants
Bibliographic record
Abstract
Dietary acculturation, specifically the adoption of western dietary habits, may result in adverse health effects such as obesity and type 2 diabetes. Therefore, it is necessary to explore the role of acculturation in dietary patterns as well as awareness and knowledge of healthy nutrition among South Asian immigrants. This is an especially important population to target as South Asians have higher prevalence rates of type 2 diabetes and cardiovascular disease, which may be magnified with immigration. The current investigation is a sub-study of the Multi-Cultural Community Health Assessment Trial (M-CHAT). There were 207 participants of South Asian origin included in the initial study, 129 were born outside of Canada and had immigrated after the age of 18. The length of residence in Canada was used as a marker for acculturation. A questionnaire addressing perceived changes in dietary patterns, food preparation, and nutrition knowledge and awareness since immigration was used to assess dietary practices. The association between length of residence and variables related to perceived changes in dietary patterns was explored with Spearman correlation and significant associations were subsequently analyzed with ordinal logistic regression analysis adjusted for age, sex, education and body mass index. South Asian immigrants in Canada reported a variety of positive dietary practices, including an increased consumption of fruits and vegetables and an improvement in food preparation (including an increase in grilling and a decrease in deep frying when cooking). However, there was a reported increase in the consumption of convenience foods, sugar-sweetened beverages, red meat and in dining out. South Asian immigrants in Canada reported a variety of positive dietary practices including an improvement in food preparation. Future health promotion strategies should encourage cultural sensitivity in efforts to reduce the consumption of sugar-sweetened beverage, convenience foods and to encourage eating at home rather than dining out.
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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 | 0.002 |
| 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 | 0.000 |
| 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".