发表机构
Martin Centre for Architectural and Urban Studies, University of Cambridge; Cambridge Public Health, University of Cambridge（剑桥大学马丁建筑与城市研究中心; 剑桥大学剑桥公共卫生）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
研究主动出行对心理健康的影响，用因果机器学习等方法分析英国成年人数据，发现主动出行对焦虑等的个体影响有不平等，且随时间扩大，受城市环境强烈影响，未考虑个体和环境差异会加剧健康不平等。
AI 中文摘要
主动出行被广泛推广以实现可持续和更健康的生活，但随着时间推移，它是否能在个体和不同地点带来公平的心理健康益处仍不明确。我们在264168名英国成年人中使用因果机器学习和因果深度学习，发现主动出行对焦虑、抑郁和常见精神障碍的个体影响存在显著不平等。这些不平等随时间扩大，并由城市环境强烈构建。例如，随访时焦虑风险在个体间从降低40.6%到增加10.1%不等，而基线时为降低10.4%到增加0.1%。在更绿色、更安全、污染更少和贫困程度更低的邻里环境中益处最大，81.8%的个体受益高于平均水平，平均焦虑风险降低26.4%，而在最不利环境中只有10.4%的个体受益，焦虑风险降低7.4%。城市紧凑形态通过与邻里环境的非线性相互作用进一步改变这些影响，仅在有利条件下放大益处。尽管存在这些强烈的环境梯度，基因调节作用可忽略不计。这些发现表明，如果不考虑个体和背景差异，普遍推广主动出行可能会扩大健康不平等。
英文摘要
Active mobility is widely promoted for sustainable and healthier living, but whether it translates into equitable mental health benefits across individuals and places over time remains unknown. Using causal machine learning and causal deep learning in 264168 UK adults, we find substantial inequalities in individualized effects of active mobility on anxiety, depression, and common mental disorders. These inequalities widen over time and are strongly structured by urban context. For example, anxiety risk at follow-up ranges from a 40.6% reduction to a 10.1% increase across individuals, versus a 10.4% reduction to a 0.1% increase at baseline. Benefits are greatest in greener, safer, less polluted, and less deprived neighborhood environments, with 81.8% of individuals experiencing above-average benefits and mean anxiety risk reduced by 26.4%, versus 10.4% of individuals and 7.4% reduction in the least supportive environments. Urban compact form further modifies these effects through nonlinear interactions with neighborhood environments, amplifying benefits only under supportive conditions. Despite these strong environmental gradients, genetic moderation is negligible.
