Incidence and spatial variation of Parkinson's disease in the Netherlands (2017-2022): a population-based study.
retrospective_cohort · Level III
Where this comes from
- Record sourced from PubMed, PMID 41788426.
- Also identified by DOI 10.1016/j.lanepe.2025.101565 and PMC identifier 12959304.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
Parkinson's disease (PD) is a growing public health concern with a largely unknown aetiology. Understanding temporal trends, demographic drivers, and regional variations in PD risk is critical for guiding healthcare planning and identifying potential environmental and socioeconomic risk factors. We aimed to investigate the incidence and spatial distribution of PD in the Netherlands from 2017 to 2022, and examined demographic and socioeconomic disparities in PD risk. We conducted a nationwide, population-based study leveraging complementary strengths of multiple independent administrative health records linked to demographic and socioeconomic data. Incident PD cases were identified using a newly developed algorithm integrating mortality records, hospital data, health insurance claims, and medication prescriptions. We estimated overall and stratified age- and sex-internally standardized PD incidence rates (IRs). Spatial variations in PD risk were assessed using Bayesian hierarchical models to generate smoothed relative risk estimates at a fine-grained neighbourhood level. Between 2017 and 2022, we identified 22,343 incident PD cases in a population of 19,995,771 individuals (totalling 105,027,472 person-years at risk). Overall standardized IR was relatively stable across the evaluated time at 21.8 (95% confidence interval (CI): 21.6-22.1) per 100,000 person-years at risk. Incidence increased with age (peaking at 75-85 years) and was higher in men than women, in individuals with higher socioeconomic position, and residents of the northern provinces. Spatial analysis revealed significant geographic clustering of PD risk, which did not ecologically align with major environmental indicators such as air pollution, agricultural activity, or urbanization. The multifaceted algorithm offers a robust PD case ascertainment tool that allowed for a comprehensive nationwide assessment of PD incidence. In the Netherlands, this new approach uncovered regional disparities in PD risk that are not readily explained by known environmental indicators, warranting further investigation into potential environmental and socioeconomic determinants. Woelse Waard, Gieskes-Strijbis, and Ministry of Agriculture, Fisheries, Food Security and Nature of the Netherlands.