National Institute of Public Health, University of Southern Denmark, Studiestræde 6, 1455, Copenhagen, Denmark.
Department of Cardiology, The Cardiovascular Research Centre, Copenhagen University Hospital Herlev and Gentofte, Gentofte, Denmark.
Int J Health Geogr. 2021 Aug 30;20(1):41. doi: 10.1186/s12942-021-00294-w.
Disease mapping aims at identifying geographic patterns in disease. This may provide a better understanding of disease aetiology and risk factors as well as enable targeted prevention and allocation of resources. Joint mapping of multiple diseases may lead to improved insights since e.g. similarities and differences between geographic patterns may reflect shared and disease-specific determinants of disease. The objective of this study was to compare the geographic patterns in incident acute myocardial infarction (AMI), stroke and atrial fibrillation (AF) using the unique, population-based Danish register data.
Incident AMI, stroke and AF was modelled by a multivariate Poisson model including a disease-specific random effect of municipality modelled by a multivariate conditionally autoregressive (MCAR) structure. Analyses were adjusted for age, sex and income.
The study included 3.5 million adults contributing 6.8 million person-years. In total, 18,349 incident cases of AMI, 28,006 incident cases of stroke, and 39,040 incident cases of AF occurred. Estimated municipality-specific standardized incidence rates ranged from 0.76 to 1.35 for AMI, from 0.79 to 1.38 for stroke, and from 0.85 to 1.24 for AF. In all diseases, geographic variation with clusters of high or low risk of disease after adjustment was seen. The geographic patterns displayed overall similarities between the diseases, with stroke and AF having the strongest resemblances. The most notable difference was observed in Copenhagen (high risk of stroke and AF, low risk of AMI). AF showed the least geographic variation.
Using multiple-disease mapping, this study adds to the results of previous studies by enabling joint evaluation and comparison of the geographic patterns in AMI, stroke and AF. The simultaneous mapping of diseases displayed similarities and differences in occurrence that are non-assessable in traditional single-disease mapping studies. In addition to reflecting the fact that AF is a strong risk factor for stroke, the results suggested that AMI, stroke and AF share some, but not all environmental risk factors after accounting for age, sex and income (indicator of lifestyle and health behaviour).
疾病制图旨在识别疾病的地理模式。这可以更好地了解疾病的病因和危险因素，并能够进行有针对性的预防和资源分配。多种疾病的联合制图可能会带来更好的见解，因为例如地理模式之间的相似性和差异性可能反映了疾病的共同和特定决定因素。本研究的目的是使用独特的基于人群的丹麦登记数据比较急性心肌梗死（AMI）、中风和心房颤动（AF）的地理模式。
通过多变量泊松模型对 AMI、中风和 AF 进行建模，该模型包括通过多变量条件自回归（MCAR）结构建模的市政当局的疾病特异性随机效应。分析调整了年龄、性别和收入。
该研究包括 350 万成年人，贡献了 680 万人年。共有 18349 例 AMI 事件、28006 例中风事件和 39040 例 AF 事件。估计的市政特定标准化发病率范围为 AMI 的 0.76 至 1.35，中风的 0.79 至 1.38，AF 的 0.85 至 1.24。在所有疾病中，在调整后观察到具有疾病高或低风险集群的地理变异。疾病之间的地理模式显示出总体相似性，中风和 AF 具有最强的相似性。最显著的差异发生在哥本哈根（中风和 AF 风险高，AMI 风险低）。AF 显示出最小的地理变异性。
使用多疾病制图，本研究通过允许对 AMI、中风和 AF 的地理模式进行联合评估和比较，补充了以前研究的结果。同时对疾病进行制图显示了在发生方面的相似性和差异，这在传统的单疾病制图研究中是无法评估的。除了反映 AF 是中风的强烈危险因素这一事实外，结果表明，在考虑年龄、性别和收入（生活方式和健康行为的指标）后，AMI、中风和 AF 共享一些但不是所有环境危险因素。
