Exploring the Associations Between Vegetarianism and Cardiometabolic Risk Factors in South Asian Populations: A Systematic Review
Bibliographic record
Abstract
Vegetarianism has historically been associated with cardiometabolic benefits and reduced diabetes risk. Despite having the highest prevalence of vegetarians globally, the prevalence of type 2 diabetes in South Asians is amongst the highest globally. This review explores the relationship between vegetarianism and cardiometabolic measures in South Asian populations to clarify this paradoxical relationship. Five databases were searched to identify observational studies published between January 2000 and May 2025 that compared vegetarian diets with non-vegetarian diets and reported cardiometabolic measures. A total of 973 articles were identified, 590 articles were assessed, and 7 studies (n = 184,345) were ultimately included. Overall, each study utilized different dietary intake assessments and reported variable cardiometabolic measures. The three highest-quality studies found that vegetarian adherence was associated with a lower BMI, waist circumference, diastolic blood pressure, lipid levels, and fasting blood glucose compared with non-vegetarian diets. Conclusive findings were limited by the small number of studies, variability in dietary assessment methods, and heterogeneity in the reporting of cardiometabolic measures. These results underscore the importance of conducting more methodologically robust studies to assess cardiometabolic measures and demonstrate the need for culturally consistent dietary assessment tools to reduce inter-study variability and improve dietary reporting in South Asians.
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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 | 0.005 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.005 |
| Bibliometrics | 0.008 | 0.011 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".