Population Heterogeneity of Diabetes in Indigenous Peoples of the Americas: A Systematic Scoping Review of Existing Literature
Bibliographic record
Abstract
Background: Diabetes is a growing public health concern worldwide, with an estimated 537 million people affected in 2021. This number is projected to increase by 46% over the next 25 years. In the Americas, the prevalence of diabetes is expected to rise from 84 million in 2021 to 112 million by 2045. Indigenous populations may face unique risk factors, yet there is limited consolidated data on diabetes prevalence within these communities. This systematic review examines the prevalence of diabetes among Indigenous populations in the Americas. Methods: Following PRISMA-ScR guidelines, a systematic search was conducted in Scopus and PubMed. Studies were included if they reported population-based surveys on diabetes prevalence among Indigenous and mestizo adults in the Americas. Data extraction focused on study location, population characteristics, diagnostic criteria, and reported prevalence. Results: A total of 60 documents, representing 73 studies, met the inclusion criteria and covered 45,503 individuals from 16 countries between 1975 and 2025. Mexico contributed the largest number of studies (17), followed by the United States (15), Brazil (10), Canada (7), Chile (6), and Guatemala (5). Most participants were from North America (29,093), followed by Central America (8,144) and South America (6,911). No eligible reports were identified from Caribbean nations, Peru, or Guyana. In total, 111 Indigenous groups were represented. The most frequently used diagnostic method was fasting blood glucose (FBG), applied in 50 studies (75%), followed by the oral glucose tolerance test (OGTT) in 41 studies (61%). The combined prevalence of diabetes among Indigenous and mestizo populations was 12% overall (17% among women and 14% among men). Mean diabetes prevalence was highest in North America (17%), followed by Central America (8.9%) and South America (4.9%). Notably, five studies—from Brazil, Chile, Colombia, Mexico, and Paraguay—reported no cases of diabetes. Conclusions: The prevalence of diabetes among Indigenous populations in the Americas is highly heterogeneous, with considerably higher rates reported in North America compared with Central and South America. Although genetic predisposition may play an important role, environmental and lifestyle factors likely contribute substantially to these differences. The decline in published studies in recent years suggests a reduction in research focus on this topic. Further investigation into modifiable risk factors—such as diet, physical activity, and socioeconomic conditions—is essential to better understand the epidemiology of diabetes, clarify how these determinants interact, and support the development of targeted interventions to reduce risk and address health disparities among Indigenous populations across the region. Keywords: Diabetes, Indigenous populations, Americas, epidemiology, public health, prevalence, systematic review.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".