Epidemiology and risk factors of Alzheimer’s disease and related dementias in South and Southeast Asia: a systematic review and meta-analysis protocol
Bibliographic record
Abstract
Background Alzheimer’s disease (AD) impacts over 55 million individuals worldwide and remains the leading cause of dementia (60–70% of cases). By 2050, South and Southeast Asia are projected to have an older adult population more than double, bearing a major share of Alzheimer’s disease burden. This will exert a heavy strain on healthcare systems, particularly in resource-limited countries where support and infrastructure are already stretched. Despite this, no review has yet explored the regional epidemiology and associated risk factors in this context. Thus, this study protocol outlines to synthesise prevailing evidence from these densely populated regions, particularly low- and middle-income nations within South and Southeast Asia. Methods This review will include studies that reported epidemiological characteristics including prevalence, age of onset, mortality, and risk factors of AD and related dementias comprising in South and Southeast Asian regions. Studies published in any language from inception to date will be extracted from PubMed, Scopus, CINAHL, EMBASE and APA PsycNet, following Preferred Reporting Items for Systematic Review and Meta-Analysis (PRISMA) and Meta-Analysis of Observational Studies in Epidemiology (MOOSE) guidelines. We will also search grey literature sources and screen the reference lists of the articles selected for full-text review to identify additional relevant studies. Observational studies including case–control, cohort, and cross-sectional designs reporting desired outcomes will be included and appraised for quality assessment with the modified Newcastle-Ottawa Scale (mNOS). The included articles will be appraised by two independent reviewers, with a third resolving any conflicts. Pooled estimates of prevalence, age of onset and mortality will be analysed using random effect meta-analysis (REML) model. Associated risk factors, including modifiable and non-modifiable will be narratively synthesised. Forest plots will be used to visualise the findings, and heterogeneity across the included studies will be assessed using the I ² and Cochrane’s Q statistics. Potential publication bias will be assessed using a funnel plot along with the Begg’s and Egger’s tests. Sensitivity and subgroup analyses will also be conducted to assess the robustness of pooled estimates and to explore potential sources of heterogeneity. Statistical analysis will be conducted using Rstudio (v.4.3.2) and GraphPad Prism V.9.0.2. Ethics and disseminations The systematic review is focused on the analysis of secondary data from published literature; thus, no ethical approval will be needed. The protocol will follow international standard guidelines, findings will be reported in a reputed journal and disseminated through (inter)national conferences, webinars and key stakeholders to inform policy, research and AD management strategies. PROSPERO registration number CRD 420251047105.
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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 | 0.056 | 0.081 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.020 | 0.025 |
| Bibliometrics | 0.013 | 0.012 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.005 | 0.005 |
| Research integrity | 0.006 | 0.005 |
| Insufficient payload (model declined to judge) | 0.064 | 0.006 |
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".