Beans for Healthy Aging: An Exploration of Factors Related to Bean Consumption in Older Adults and An Examination of the Effects of Canned Beans of Multiple Varieties in Different Daily Amounts on Cardiovascular Disease Risk Biomarkers in Adults with Elevated LDL Cholesterol
Bibliographic record
Abstract
Cardiovascular disease (CVD) is a leading cause of death in Canada and the United States and with rapidly aging populations, strategies promoting consumption of nutrient-dense foods to improve modifiable risk factors for CVD are needed. Beans are a candidate food for healthy aging since they are nutrient-dense and are associated with reduced CVD risk through their ability to reduce total and LDL cholesterol. However, studies focused on bean consumption in older adults and on the effects of multiple bean varieties in different daily amounts on lipid profile are lacking. Therefore, this research addressed these gaps with three objectives: (1) to determine the prevalence of bean consumption and identify motivators, barriers, and other factors related to bean consumption among older adults, (2) to determine the awareness and knowledge of the nutritional and health attributes of beans among older adults, and (3) to determine the effects of canned beans of multiple varieties in different daily amounts on fasting serum lipid profile in adults with elevated LDL cholesterol. Objectives #1 and #2 were addressed using a mixed-methods approach including a researcher-administered questionnaire (n=250) followed by focus groups (n=49). Objective #1 results showed that 51.2% of older adult (65 years) participants were bean consumers who were significantly more likely to indicate motivators to their bean consumption compared to bean non-consumers. Conversely, bean non-consumers were significantly more likely than bean consumers to indicate barriers to their bean consumption. Objective #2 results showed that most (99.2%) older adult participants considered beans a healthy food. However, gaps exist in participant’s awareness of the nutritional and health attributes of beans. Finally, objective #3 was addressed using a multi-centre, randomized, crossover clinical trial in adults with elevated LDL cholesterol. Participants consumed 1 cup beans (1CB; n=66), ½ cup beans (½CB; n=68) and 1 cup white rice (WR; n=64) for 4 weeks each separated by ≥4-week washout periods. Total and LDL cholesterol were significantly lower for 1CB but not ½CB compared to WR. Collectively, these studies provide evidence that can inform practical dietary strategies to increase bean consumption thereby reducing CVD risk and contributing to healthy aging in North America.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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".