Ethnic Differences in the Association Between Body Mass Index and Type 2 Diabetes Risk: A Meta-Analysis of Prospective Cohort Studies
Bibliographic record
Abstract
The association between body mass index (BMI) and total body adiposity differs across ethnic groups. For instance, South Asians (SA) and East Asians (EA) have lower body fat for a given BMI level than Europeans, while the opposite is true for African-Caribbeans (AC). This suggests that the relationship between BMI and type 2 diabetes (T2D) risk may also vary depending on ethnicity. We conducted a meta-analysis to investigate whether the association between BMI and the risk of T2D differs across ethnic groups. MEDLINE, EMBASE and Web of Science were searched up to July 2020. We included prospective cohort studies of >2 years, which investigated the association between BMI and T2D incidence among adults of a specified ethnicity. Linear and non-linear dose-response meta-analyses were performed using random effects models, with subgroup analyses by ethnicity. The heterogeneity among studies was estimated using the Cochran Q test and I2 statistic. Study quality was assessed with the Newcastle-Ottawa Scale. 54 studies were included. Cohorts were stratified into the following ethnic subgroups: AC (N = 67,453), EA (N = 1,012,135), European (N = 206,424), Indigenous (N = 10,533), Latin American (LA) (N = 4,669), SA (N = 9,395), and Southeast Asian (SEA) (N = 51,129). Linear dose-response associations between 1 kg/m2 increase in BMI and T2D were observed for the SEA (RR = 1.26; 95% CI, 1.10, 1.30) and SA (RR = 1.11; 95% CI: 1.04, 1.19) subgroups with no evidence of departure from linearity. Associations departed from linearity for all other subgroups. At a BMI level of 30 kg/m2, the non-linear dose-response curves for each of the other subgroups displayed the following risk ratios; AC: RR = 3.13 (95% CI, 1.95, 5.02), EA: RR = 2.39 (95% CI, 1.96, 2.92), European: RR = 7.41 (95% CI, 3.88, 14.18), Indigenous: RR = 8.15 (95% CI, 6.07; 10.95), and LA: RR = 12.82 (95% CI, 5.50, 29.92). For all subgroups, there was a high degree of interstudy heterogeneity (I2 > 75%). Our findings indicated that the association between BMI and the risk of T2D differs across ethnic groups, suggesting that ethnic-specific BMI cut-offs could be helpful in identifying cardiometabolic risk profiles across different populations. Canadian Institutes for Health Research.
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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 | 0.021 | 0.031 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.017 | 0.060 |
| Bibliometrics | 0.006 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| 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".