Psychosocial Predictors of Diet and Acculturation in Chinese American and Chinese Canadian Women
Bibliographic record
Abstract
OBJECTIVE: To examine the influence of diet-related psychosocial constructs on the dietary practices of Chinese populations living in North America. DESIGN: Data are from a cross-sectional survey of 244 women of Chinese ethnicity living in Seattle, WA, USA and Vancouver, BC, Canada. Using an interviewer-administered questionnaire and PRECEDE/PROCEED as our model, we collected information on diet-related psychosocial (predisposing, enabling, and reinforcing) factors; consumption of foods reflecting Western and Chinese dietary practices; and past and current consumption of fruits, vegetables and fat. RESULTS: Participants generally believed that there were strong relationships between diet and health, but only about a quarter were aware of nutrition information from the government. Food cost, availability, and convenience did not appear to be major concerns among these participants. Respondents' older relatives and spouses tended to prefer a Chinese diet and also had a strong influence on the household diet. Associations of the psychosocial factors with demographic characteristics, adoption of Western dietary practices, and consumption of fruits and vegetables were informative. For example, older, less educated respondents considered it very important to eat a low fat, high fruit and vegetable diet; while younger, more educated participants who were employed outside the home did not think the Chinese diet is healthier than a typical Western diet (all p < 0.05). Western acculturated respondents were more likely to believe in a relationship between diet and cancer/heart disease and report that preparing Chinese meals is inconvenient (p < 0.05). Respondents with in-family normative pressure to maintain Chinese eating patterns ate more fruits and vegetables (4.4 vs 3.7 servings), while knowledge of nutrition information from the government was associated with increased fruit and vegetable consumption after immigration (all p < 0.05). CONCLUSIONS: Chinese cultural beliefs play an important role in the dietary practices of Chinese living in North America. Therefore, traditional health beliefs, as well as socioeconomic and environmental factors related to diet should be incorporated into the design and implementation of culturally appropriate health promotion programs for Chinese immigrants.
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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 | 0.002 | 0.001 |
| 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".