Prevalence, distribution and future projections of Parkinson disease in Brazil: insights from the ELSI-Brazil cohort study
Bibliographic record
Abstract
Background: There is limited epidemiological data regarding Parkinson's disease (PD) prevalence in Brazil, which hinders adequate public health policies planning and patient care. This study aimed to investigate the distribution, prevalence, and clinical characteristics of PD among older adults in Brazil. Methods: This cross-sectional study used data from the ELSI-Brazil cohort, a Brazilian nationally representative study of individuals aged 50 and older. Data were collected through door-to-door surveys with standardized questionnaires. PD diagnosis was based on self-reported data. We calculated PD prevalence in the general population and specific age groups, studied its association with clinical variables, and projected PD prevalence in Brazil from 2024 to 2060. Findings: A total of 9881 respondents were included in this study, and 93 reported a medical diagnosis of PD. The crude prevalence of PD among Brazilians aged 50 or more was 0.84% (95% CI: 0.64%-1.09%), with an age- and sex-standardized prevalence of 0.86% (95% CI: 0.62%-1.10%). Men were more affected than women (OR: 2.35, 95% CI: 1.35-4.08; p < 0.01), and the prevalence was higher in older age groups, from 0.39% in those aged 50-59 years to 2.75% in those 80 years and older. PD individuals had higher rates of stroke, depression, functional dependency, and were more likely to need walking support or be bedridden. Projections indicated that PD cases in Brazil will rise from 535,999 (95% CI: 309,963-922,948) in 2024 to 1,250,638 (95% CI: 734,660-2,117,585) by 2060. Interpretation: This study reveals the prevalence and distribution of PD in Brazil, showing many patients with advanced disease and suggesting underdiagnosis in early stages. There is a need for better diagnostic accuracy, improved access to neurologists, and comprehensive public health strategies to manage the rising prevalence and healthcare demands of PD in Brazil. Funding: This study did not receive any funding. The ELSI-Brazil cohort was funded by the Ministry of Health of Brazil.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".