Diet quality and risk factors for cardiovascular disease among South Asians in Alberta
Bibliographic record
Abstract
South Asians have a higher prevalence of early onset cardiovascular disease risk compared with other populations. Dietary intake is a modifiable risk factor for cardiovascular disease. Dietary patterns in immigrants and successive generations of South Asians settled in Western countries undergo adaptions. Little is known about the dietary intake of South Asians in Alberta, thus the objective of the present study was to describe the dietary patterns among South Asians and their risks for cardiovascular diseases. A retrospective analysis of data collected from 140 South Asian adults participating in the Alberta's Tomorrow Project was conducted. Dietary intake was assessed using a food frequency questionnaire and the Healthy Eating Index (HEI) was used an indicator of overall diet quality and adherence to dietary recommendations made by Health Canada. Central obesity (70%), hypercholesterolemia (27%), and hypertension (14%) were predominant health conditions observed in the study participants. About 56% and 44% of participants obtained moderate and poor HEI scores, respectively. The diet quality of the majority of participants was inadequate to meet macro- and micronutrient intake recommendations. The high prevalence of poor/moderate diet quality and pre-existing chronic health conditions across all body mass index groups is a cause for concern in this population.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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) | 0.001 | 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".