Evidence map›Paper›PMID 42293150›Full record

ArticleFrontiers in aging neuroscience2026

The Green Parkinson's Belt: agricultural regions associated with increased Parkinson's disease burden in Mexico.

Hector R Martinez, Francisco A Luna-Rangel, Brenda Gonzalez-Bedolla, Cecilio Armengol-Garcia, Daniel Rebolledo-Garcia, Beatriz L Rodriguez, Jose A Figueroa-Sanchez

Abstract read
In one paragraph

Article in Frontiers in aging neuroscience, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Hector R MartinezTecnologico de Monterrey, School of Medicine and Health Sciences, Monterrey, Nuevo León, Mexico.
Francisco A Luna-RangelTecnologico de Monterrey, School of Medicine and Health Sciences, Monterrey, Nuevo León, Mexico.
Brenda Gonzalez-BedollaTecnologico de Monterrey, School of Medicine and Health Sciences, Monterrey, Nuevo León, Mexico.
Cecilio Armengol-GarciaTecnologico de Monterrey, School of Medicine and Health Sciences, Monterrey, Nuevo León, Mexico.
Daniel Rebolledo-GarciaClínica de Disautonomías y Movimientos Anormales, Santa Fe, Mexico.
Beatriz L RodriguezTecnologico de Monterrey, School of Medicine and Health Sciences, Monterrey, Nuevo León, Mexico.
Jose A Figueroa-SanchezTecnologico de Monterrey, School of Medicine and Health Sciences, Monterrey, Nuevo León, Mexico.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Parkinson's disease (PD) is projected to increase substantially in Mexico over coming decades, yet its geographic distribution has not been systematically examined at the state level. This study aimed to evaluate whether PD prevalence in Mexico exhibits geographic clustering, with particular attention to regions characterized by intensive agricultural and industrial activity. Methods: We conducted an ecological cross-sectional study using publicly available state-level data from Mexico covering the period 2015-2024. PD case counts were obtained from the national epidemiological surveillance system, and population denominators were derived from the 2020 national census. State-level prevalence was calculated per 100,000 inhabitants as annual averages across the study period. States were grouped into a Northern Hotspot, a Western Hotspot, and remaining states based on geographic clustering patterns and agricultural productivity profiles. Geographic inequality was assessed using the Gini index, Theil index, and coefficient of variation. Regional differences were evaluated with proportion tests and Poisson regression models with population offset, reported as prevalence ratios (PRs) with 95% confidence intervals (CIs). Results: PD prevalence showed substantial geographic heterogeneity across Mexican states over the 2015-2024 period. Colima recorded the highest average prevalence (38.8 per 100,000), followed by Durango (21.4), Sinaloa (14.9), Morelos (14.8), and Chihuahua (13.7 per 100,000). Inequality metrics confirmed marked dispersion in state-level prevalence (Gini 0.419; Theil 0.312; coefficient of variation 0.949). Average prevalence was higher in the Western Hotspot (8.6 per 100,000; PR 1.54, 95% CI 1.44-1.63) and the Northern Hotspot (13.8 per 100,000; PR 2.57, 95% CI 2.42-2.74) compared with the remaining states (4.9 per 100,000). Conclusion: PD prevalence in Mexico exhibits pronounced geographic heterogeneity, with distinct clustering observed in northern and western states. These patterns are consistent with a non-random spatial distribution and highlight regions where agricultural, industrial, and environmental exposures may warrant further investigation. Given the ecological design and important limitations including the absence of age standardization and variability in healthcare access across states, these findings are hypothesis-generating and do not permit causal inference. They underscore the need for more robust epidemiological surveillance, standardized case ascertainment, and individual-level studies to better characterize the determinants of PD distribution in Mexico.

Indexed as

agricultureenvironmental exposureepidemiologyParkinson’s diseasepesticides

Identifiers

PMID42293150
PMCPMC13253685

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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.