Incidence and spatial variation of Parkinson's disease in the Netherlands (2017–2022): a population-based study

IF 15.7 Q1 HEALTH CARE SCIENCES & SERVICES

Lancet Regional Health-Europe Pub Date : 2026-03-01 Epub Date: 2026-01-21 DOI:10.1016/j.lanepe.2025.101565

Mariana Simões , Susan Peters , Anke Huss , Sirwan K.L. Darweesh , Bastiaan R. Bloem , Roel Vermeulen

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引用次数: 0

Abstract

Background

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.

Methods

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.

Findings

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.

Interpretation

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.

Funding

Woelse Waard, Gieskes-Strijbis, and Ministry of Agriculture, Fisheries, Food Security and Nature of the Netherlands.

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荷兰帕金森病的发病率和空间变化（2017-2022）：一项基于人群的研究

背景：帕金森病（PD）是一个日益受到关注的公共卫生问题，其病因在很大程度上是未知的。了解PD风险的时间趋势、人口驱动因素和区域差异对于指导医疗保健计划和识别潜在的环境和社会经济风险因素至关重要。我们旨在调查2017年至2022年荷兰PD的发病率和空间分布，并检查PD风险的人口统计学和社会经济差异。方法：我们开展了一项全国性的、以人口为基础的研究，利用与人口统计和社会经济数据相关的多个独立行政健康记录的互补优势。使用一种新开发的算法，综合死亡率记录、医院数据、健康保险索赔和药物处方，确定偶发性PD病例。我们估计了总体和分层的年龄和性别内部标准化PD发病率（IRs）。使用贝叶斯分层模型评估帕金森病风险的空间变化，以在细粒度的社区水平上生成平滑的相对风险估计。研究结果：在2017年至2022年期间，我们在19,995,771人的人群中确定了22,343例PD病例（总计105,027,472人年的风险）。总体标准化IR在整个评估时间内相对稳定，为每100,000人年21.8（95%置信区间（CI）： 21.6-22.1）。发病率随着年龄的增长而增加（在75-85岁达到高峰），男性高于女性、社会经济地位较高的个体和北部省份的居民。空间分析显示，PD风险具有显著的地理聚类性，与空气污染、农业活动或城市化等主要环境指标在生态上不一致。解释：多方面的算法提供了一个强大的PD病例确定工具，允许对PD发病率进行全面的全国评估。在荷兰，这种新方法揭示了PD风险的地区差异，这些差异不容易用已知的环境指标来解释，需要进一步调查潜在的环境和社会经济决定因素。资助：Woelse Waard， Gieskes-Strijbis和荷兰农业、渔业、粮食安全和自然资源部。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Lancet Regional Health-Europe Multiple-

CiteScore

19.90

自引率

1.40%

发文量

260

审稿时长

9 weeks

期刊介绍： The Lancet Regional Health – Europe, a gold open access journal, is part of The Lancet's global effort to promote healthcare quality and accessibility worldwide. It focuses on advancing clinical practice and health policy in the European region to enhance health outcomes. The journal publishes high-quality original research advocating changes in clinical practice and health policy. It also includes reviews, commentaries, and opinion pieces on regional health topics, such as infection and disease prevention, healthy aging, and reducing health disparities.