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.
Martínez et al. (2026) studied this question.