ReviewNature reviews. Neurology2026
Bridging global diversity gaps in Parkinson disease research.
Review in Nature reviews. Neurology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed.
- Global research synergy: Advancing fundamental Parkinson's research through international collaboration.Journal of Parkinson's disease · 2026Review
- Potential Relevance of Amazonian Diet Components in Parkinson's Disease: An Integrative Review with Multivariate Analysis.Nutrients · 2026Review
- Breaking barriers and fighting inequality in Parkinson's disease care: Personal reflections of movement disorders clinicians.Journal of Parkinson's disease · 2026Article
- Environmental determinants of Parkinson's disease and attributable burden in Latin America.Research square · 2026Article
- One world, one goal: Advocacy and policy for a unified Parkinson's response.Journal of Parkinson's disease · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The global burden of Parkinson disease (PD) is rapidly shifting towards low-income and middle-income countries (LMICs), which already account for 44% of all individuals with PD. Despite this trend, the populations of LMICs and other under-represented populations defined by ethnicity, sex, geography and minority groups within high-income countries remain largely excluded from PD research. The continuation of these disparities limits our knowledge of disease biology and restricts the applicability of advances in prevention, diagnosis and treatment, increasing inequity in global health. Substantial disparities persist across the PD research continuum, extending beyond resource limitations and encompassing epidemiology, environment, genetics, deep phenotyping and biomarkers, data integration and diversity-aware analytics, clinical trials and basic science. To repair structural diversity gaps that compromise validity and equity in PD research, we propose an ethically grounded, coordinated agenda that prioritizes increased funding and local capacity building in under-represented regions, the development and adoption of harmonized and context-adapted methods, sustained community engagement with cultural competence, the creation of collaborative research networks, and more inclusive editorial and regulatory policies. Moreover, because inequities in care and research commonly co-occur and are mutually reinforcing, PD research should advance alongside a worldwide commitment to minimum standards of care and access to treatment. This Perspective details diversity gaps across PD research, outlines priority actions to address them, and illustrates, through recent examples, how interventions along these axes can advance equity and representation in PD studies.
Indexed as
Identifiers
41667846What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.