Supplementary Material for: Statistical Analysis Plan for the AIRCARD Study: Individual Long-Term Air and Noise Pollution Exposure and Cardiovascular Disease Incidence and Mortality – A Prospective Cohort Study Utilizing DANCAVAS and VIVA Screening Trials

<b><i>Introduction:</i></b> The AIRCARD study is designed to investigate the relationship between long-term exposure to air and noise pollution and cardiovascular disease incidence and mortality. We aim to conduct a robust prospective cohort analysis assessing the cumulative and differential impacts of air and noise pollution exposure on cardiovascular disease and mortality. This study will adjust for relevant confounders, including traditional cardiovascular risk factors, socioeconomic indicators, and lipid-lowering agents. <b><i>Methods:</i></b> This prospective cohort study will include 27,022 male participants aged 65–74, recruited from the two large Danish DANCAVAS and VIVA trials, both population-based randomized, multicentered, clinically controlled studies. We will assess long-term exposure to air pollutants using the state-of-the-art DEHM/UBM/AirGIS modeling system and noise pollution through the Nord2000 and SoundPLAN models, covering data from 1979 to 2019. This statistical analysis plan is strictly formulated to predefine the analytical approach for all outcomes and key study variables before data access. The primary analysis will utilize Cox proportional hazards models, adjusted for confounders identified in our cohort (age, body mass index, hypertension, diabetes, smoking status, family history of heart disease, socioeconomic factors, and lipid-lowering agents). This statistical analysis plan further includes Spearman rank correlation to explore inter-pollutant associations. <b><i>Conclusion:</i></b> The AIRCARD study addresses global concerns about the impact of air and noise pollution on cardiovascular disease. This research is important for understanding how the pollutants contribute to cardiovascular disease. We aim to provide insights into this area, emphasizing the need for public health measures to mitigate pollution exposure. Our goal is to provide policymakers and healthcare professionals with information on the role of environmental factors in cardiovascular health that could influence global strategies to reduce the cardiovascular disease burden associated with pollution. The design of this SAP ensures transparency and verifiability, considering the complexities of evaluating environmental health impacts over an extended period.

<b><i>引言：</i></b> AIRCARD研究旨在探究长期暴露于空气与噪声污染和心血管疾病发病及死亡之间的关联。本研究计划开展一项严谨的前瞻性队列分析，以评估空气与噪声污染暴露对心血管疾病及死亡的累积效应与差异化影响。研究将对相关混杂因素进行校正，涵盖传统心血管疾病危险因素、社会经济指标以及降脂药物使用情况。<b><i>方法：</i></b> 本项前瞻性队列研究将纳入27022名年龄介于65至74岁的男性参与者，招募自两项大型丹麦人群研究DANCAVAS与VIVA，二者均为基于人群的随机多中心临床对照研究。研究将采用前沿的DEHM/UBM/AirGIS建模系统评估长期空气污染物暴露，并通过Nord2000与SoundPLAN模型评估噪声污染，数据覆盖1979年至2019年。本统计分析方案严格制定，旨在在获取研究数据前预先明确所有结局指标与关键研究变量的分析路径。主要分析将采用Cox比例风险模型（Cox proportional hazards models），并针对队列中已识别的混杂因素（年龄、体质指数、高血压、糖尿病、吸烟状况、心脏病家族史、社会经济因素及降脂药物使用情况）进行校正。本统计分析方案还纳入了斯皮尔曼秩相关（Spearman rank correlation）分析，以探究不同污染物间的关联关系。<b><i>结论：</i></b> AIRCARD研究针对全球范围内备受关注的空气与噪声污染对心血管疾病的影响这一议题展开探索。本研究对于阐明污染物如何参与心血管疾病的发生发展进程具有重要价值，旨在为该研究领域提供新的认知，并强调需通过公共卫生措施降低污染暴露水平。本研究旨在为政策制定者与医疗保健从业者提供相关信息，阐明环境因素在心血管健康中的作用，从而助力制定全球策略以减轻与污染相关的心血管疾病负担。考虑到长期评估环境健康影响的复杂性，本统计分析方案的设计确保了研究的透明度与可验证性。