A systematic review and meta-analysis of the prevalence of Parkinson’s disease in lower to upper-middle-income countries
Bibliographic record
Abstract
Parkinson's disease (PD) is a common neurodegenerative disease that is a growing public health challenge. Estimates of the burden of PD have focused on data from high-income countries, with lower-income countries poorly described. We reviewed and examined the prevalence of PD reported by studies in low- to upper-middle-income countries. A systematic literature search was performed in the Medline/PubMed, Embase, LILACS, and Web of Science databases. Age group, sex, and geographic region were considered when analyzing the data. Of the 4327 assessed articles, 57 met the inclusion criteria for qualitative review, and 36 were included in the meta-analysis. Heterogeneity measures were high both as a whole and in each geographic region. Data analysis by geographic region showed that reported prevalence differed across regions, ranging from 49 per 100,000 (Sub-Saharan Africa) to 1081 per 100,000 (Latin America and the Caribbean). There was an increasing prevalence of PD with advancing age (per 100,000): 7 in 40-49 years, 158 in 50-59 years, 603 in 60-69 years, 1251 in 70-79 years, and 2181 in over the age of 80. The prevalence of PD in men and women was similar. There was a greater PD prevalence in populations with a higher 5-year GDP per capita and a higher life expectancy. Our findings suggest a higher prevalence of PD in lower and upper-middle-income countries than previously reported. Comparisons between regions are difficult, as the sociocultural differences and lack of methodological standardization hinder understanding key epidemiological data in varied populations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.006 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".