呼吸道疾病的环境驱动因素：地区层面分析
Environmental Drivers of Respiratory Disease: A District Level Analysis
AI总结：
该研究通过构建2014 - 2024年斯里兰卡25个行政区面板数据集，用XGBoost模型分析环境因素与呼吸道疾病关系，发现空气质量是主因，还得出风险指数及高风险地区，为政策提供定量依据。
摘要：
斯里兰卡经历森林退化和空气污染加剧，但地区呼吸道疾病入院率却下降，这表明医疗保健可及性起到了混杂作用。本研究通过构建一个跨越所有25个行政区的11年（2014 - 2024年）面板数据集来解决这一差距，该数据集整合了卫星衍生的植被指数、火灾辐射功率、污染物浓度、碳通量指标和人口标准化的呼吸道疾病入院率。创建了两个经过时间验证的XGBoost模型，分别用于年度地区层面的呼吸率（R^2 = 0.937）和月度PM2.5浓度（R^2 = 0.976），并在25个地区中的21个地区进行了泛化验证（平均绝对百分比误差（MAPE）<= 20%）。Shapley加法解释（SHAP）分析确定，累积空气质量负担是呼吸率变化的主要驱动因素（80.1%），领先于森林退化（15.6%）和火灾活动（4.3%）。森林 - 空气 - 健康（FAH）风险指数使用这些SHAP衍生的权重来找出风险最高的地区：科伦坡（FAH = 0.802）、甘巴哈（0.708）和卡卢特勒（0.682）。这些发现提供了首个基于证据的、地区层面的框架，将斯里兰卡的环境退化与呼吸健康联系起来，为重点公共卫生和环境政策建立了定量基础。
英文摘要：
Sri Lanka has experienced a decade of progressive forest degradation and rising atmospheric pollution, yet district-level respiratory admissions have paradoxically declined, pointing to the confounding role of healthcare access. This study addresses that gap by constructing an 11-year (2014-2024) panel dataset across all 25 administrative districts, integrating satellite-derived vegetation indices, fire radiative power, pollutant concentrations (particulate matter (PM2.5), nitrogen dioxide (NO2), sulfur dioxide (SO2)), carbon flux metrics and population-normalized respiratory admission rates. Two temporally validated XGBoost models were created for annual district-level respiratory rate (R^2 = 0.937) and monthly PM2.5 concentration (R^2 = 0.976) with generalization validated in 21 out of 25 districts (Mean Absolute Percentage Error (MAPE) <= 20%). Shapley Additive Explanations (SHAP) analysis established that cumulative air quality burden is the overwhelming driver of respiratory rate variance (80.1%), ahead of forest degradation (15.6%) and fire activity (4.3%). The Forest-Air-Health (FAH) Risk Index used these SHAP-derived weights to find the districts with the highest risk: Colombo (FAH = 0.802), Gampaha (0.708), and Kalutara (0.682). These findings present the inaugural evidence-based, district-level framework correlating environmental degradation with respiratory health in Sri Lanka, establishing a quantitative basis for focused public health and environmental policy.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
