A systematic review and meta-analysis of the prevalence and risk factors of type 2 diabetes mellitus in Nigeria
Bibliographic record
Abstract
Abstract Background Type 2 diabetes mellitus (T2DM) is a major global non-communicable disease, leading to increased morbidity and mortality. Its prevalence in Nigeria is driven by various risk factors. This review assesses the national and regional prevalence and risk factors of T2DM in Nigeria. Methods Following PRISMA guidelines, electronic databases (PubMed, Scopus, Google Scholar, African Journals Online) and gray literature were searched for English-language studies. The quality of the included studies was assessed using the Newcastle–Ottawa Scale. Data were extracted with Microsoft Excel and analyzed using Stata version 16 software. Random effect meta-regression analysis at 95% CI was used to assess pooled prevalence and risk factors. Heterogeneity was determined using the I 2 statistic, and publication bias was evaluated with a funnel plot. Results Sixty studies from different Nigerian geopolitical zones met eligibility criteria, with a total sample size of 124,876 participants and a mean age of 48 ± 9.8 years. The pooled prevalence of T2DM in Nigeria was 7.0% (95% CI: 5.0-9.0%). Moderate publication bias was observed. The South-south zone had the highest prevalence at 11.35% (95% CI: 4.52-20.72%), while the North-central zone had the lowest at 2.03% (95% CI: 1.09-3.40%). Significant risk factors included family history (9.73), high socioeconomic status (6.72), physical inactivity (5.92), urban living (4.79), BMI > 25/m 2 (3.07), infrequent vegetable consumption (2.68), and abdominal obesity (1.81). Conclusion The prevalence of T2DM in Nigeria (7.0%) nearly doubled the 2019 International Diabetes Federation estimate (3.7%) and shows a 21.3% increase from the 2019 review. Efforts should focus on modifying identified risk factors to reduce prevalence and prevent complications.
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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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.015 | 0.004 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".