Is Air Pollution Associated with Higher Risk of Parkinson's Disease?

The study investigates whether exposure to air pollution, specifically PM2.5 and NO2, increases the risk of Parkinson's disease (PD) and influences its clinical characteristics. Using a population-based case-control design from the Rochester Epidemiology Project, data from 346 PD patients and 4,813 matched controls were analyzed. Results indicate that higher PM2.5 exposure significantly increases PD risk, with an odds ratio (OR) of 1.23 (95% CI, 1.11-1.35) for those in metropolitan areas. NO2 exposure also raised PD risk (OR, 1.13; 95% CI, 1.07-1.19). Additionally, increased PM2.5 levels were linked to a 42% higher risk of dyskinesia (HR, 1.42; 95% CI, 1.17-1.73)​.

Full Citation

Krzyzanowski, B., Mullan, A. F., Turcano, P., Camerucci, E., Bower, J. H., & Savica, R. (2024). Air Pollution and Parkinson Disease in a Population-Based Study. JAMA Network Open, 7(9), e2433602. https://doi.org/10.1001/jamanetworkopen.2024.33602.

Here is the link to the article on the publisher's website​.

Extended Summary

1. Central Research Question

The central research question of this study is whether exposure to specific air pollutants, particularly fine particulate matter (PM2.5) and nitrogen dioxide (NO2), is associated with an increased risk of developing Parkinson's disease (PD). The study also examines whether these pollutants influence clinical characteristics and progression of the disease, including PD subtypes and complications such as dyskinesia.

2. Previous Literature

Previous research has highlighted environmental factors, including air pollution, as potential risk factors for PD. Studies have demonstrated that ultrafine particles from air pollution may penetrate the blood-brain barrier, causing neuroinflammation, oxidative stress, and microglial activation—key processes involved in PD pathogenesis. Despite this, the evidence remains inconsistent, particularly concerning which pollutants are most associated with PD risk and how exposure influences PD phenotypes and outcomes. Several studies have shown an association between PM2.5 exposure and neurological disorders, but data specific to PD and its progression remain limited. Prior studies also suggest a link between NO2 exposure and PD, but further research is needed to substantiate these associations and explore pollutant-specific effects on PD characteristics.

3. Data

The study utilizes data from the Rochester Epidemiology Project (REP), a comprehensive medical records linkage system in Olmsted County, Minnesota. This case-control study spans the period from 1998 to 2015 and includes 346 PD patients, matched by age and sex, with 4,813 control subjects without PD. The REP's extensive dataset ensures a population-based sample, making it an effective source for investigating environmental and health outcomes.

For air pollution exposure, mean annual PM2.5 levels (1998-2015) and NO2 levels (2000-2014) were obtained. The data were sourced from high-resolution atmospheric composition models and environmental data repositories. Participants’ residential addresses were linked to these pollution estimates, ensuring a localized and individualized approach to exposure measurement. This allowed the researchers to assess participants' air pollution levels over a 10-year period preceding the onset of PD symptoms.

4. Methods

This study adopted a population-based case-control design to explore the association between air pollution exposure and the incidence and characteristics of PD. For each identified PD case, controls were matched based on sex and age, ensuring comparability. The study's primary outcome was the risk of developing PD, while secondary outcomes included the impact of pollution exposure on PD subtype (tremor-predominant vs. akinetic-rigid) and the development of dyskinesia.

Exposure levels to PM2.5 and NO2 were modeled using logistic regression to assess their associations with PD risk. The exposures were categorized into quintiles, and linear splines were applied to capture any non-linear relationships. Regression models were adjusted for key variables such as age, sex, race, ethnicity, and urban versus rural residence (as determined by Rural Urban Commuting Area (RUCA) classification). A separate analysis focused on metropolitan cores to further explore the effects in urban settings, which typically have higher pollution levels.

For secondary outcomes, the study used Cox proportional hazards regression models to evaluate the association between air pollution exposure and the risk of developing dyskinesia among PD patients. Kaplan-Meier curves were also generated to illustrate the cumulative incidence of dyskinesia based on exposure levels. Statistical significance was set at p < 0.05 for all analyses.

5. Findings/Size Effects

The study found that higher exposure to PM2.5 and NO2 was significantly associated with an increased risk of developing PD. Specifically, individuals in the top quintile of PM2.5 exposure had a 23% increased risk of PD when restricted to metropolitan cores (OR, 1.23; 95% CI, 1.11-1.35). For NO2, the top quintile also showed an elevated risk (OR, 1.13; 95% CI, 1.07-1.19). These findings indicate that air pollution, particularly in urban areas, plays a notable role in PD risk.

Further analysis revealed that higher PM2.5 exposure was associated with the akinetic-rigid PD subtype, with a 36% increased risk per 1 μg/m³ increase in PM2.5 exposure (OR, 1.36; 95% CI, 1.02-1.80). This suggests that air pollution may influence not only the incidence of PD but also its clinical manifestation. However, NO2 exposure did not show a significant association with PD subtypes.

The study also found that higher PM2.5 levels significantly increased the risk of developing dyskinesia among PD patients. Each 1 μg/m³ increase in PM2.5 exposure was associated with a 42% greater risk of dyskinesia (HR, 1.42; 95% CI, 1.17-1.73). This highlights the potential role of environmental pollutants in influencing PD progression and complications, such as treatment-related side effects.

Contrary to expectations, there was no significant association between PM2.5 exposure and all-cause mortality among PD patients (HR per 1 μg/m³ increase, 0.93; 95% CI, 0.82-1.05). The authors speculate that factors such as improved access to healthcare in the study region may mitigate the effects of pollution on mortality outcomes in PD patients.

6. Conclusion

This study provides robust evidence that exposure to higher levels of PM2.5 and NO2 is associated with an increased risk of developing PD. The results suggest that the effects of air pollution extend beyond the onset of the disease to influence its subtype and progression, particularly dyskinesia. These findings underscore the importance of reducing air pollution to potentially lower the risk of PD and its complications. The study highlights the need for stricter air quality standards and emphasizes further research into how specific components of air pollution contribute to neurodegenerative processes. Addressing air pollution may be a critical strategy in reducing the public health burden of PD.