Journal of Exposure Science and Environmental Epidemiology ( IF 4.5 ) Pub Date : 2023-12-11 , DOI: 10.1038/s41370-023-00619-w Zhiyang Wang , Alyce M. Whipp , Marja Heinonen-Guzejev , Maria Foraster , Jordi Júlvez , Jaakko Kaprio
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Background
Depressive symptoms lead to a serious public health burden and are considerably affected by the environment. Land use, describing the urban living environment, influences mental health, but complex relationship assessment is rare.
Objective
We aimed to examine the complicated association between urban land use and depressive symptoms among young adults with differential land use environments, by applying multiple models.
Methods
We included 1804 individual twins from the FinnTwin12 cohort, living in urban areas in 2012. There were eight types of land use exposures in three buffer radii. The depressive symptoms were assessed through the General Behavior Inventory (GBI) in young adulthood (mean age: 24.1). First, K-means clustering was performed to distinguish participants with differential land use environments. Then, linear elastic net penalized regression and eXtreme Gradient Boosting (XGBoost) were used to reduce dimensions or prioritize for importance and examine the linear and nonlinear relationships.
Results
Two clusters were identified: one is more typical of city centers and another of suburban areas. A heterogeneous pattern in results was detected from the linear elastic net penalized regression model among the overall sample and the two separated clusters. Agricultural residential land use in a 100 m buffer contributed to GBI most (coefficient: 0.097) in the “suburban” cluster among 11 selected exposures after adjustment with demographic covariates. In the “city center” cluster, none of the land use exposures was associated with GBI, even after further adjustment with social indicators. From the XGBoost models, we observed that ranks of the importance of land use exposures on GBI and their nonlinear relationships are also heterogeneous in the two clusters.
Impact
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This study examined the complex relationship between urban land use and depressive symptoms among young adults in Finland. Based on the FinnTwin12 cohort, two distinct clusters of participants were identified with different urban land use environments at first. We then employed two pluralistic models, elastic net penalized regression and XGBoost, and revealed both linear and nonlinear relationships between urban land use and depressive symptoms, which also varied in the two clusters. The findings suggest that analyses, involving land use and the broader environmental profile, should consider aspects such as population heterogeneity and linearity for comprehensive assessment in the future.
中文翻译：
城市土地利用与青年期抑郁症状之间的关联：FinnTwin12 队列研究
背景
抑郁症状会导致严重的公共健康负担，并且很大程度上受到环境的影响。描述城市生活环境的土地利用影响心理健康，但复杂的关系评估很少见。
客观的
我们的目的是通过应用多种模型来研究城市土地利用与具有不同土地利用环境的年轻人抑郁症状之间的复杂关联。
方法
我们纳入了来自 FinnTwin12 队列的 1804 名双胞胎，他们于 2012 年居住在城市地区。在三个缓冲半径中存在八种类型的土地利用暴露。通过成年早期的一般行为量表（GBI）评估抑郁症状（平均年龄：24.1 岁）。首先，进行 K 均值聚类以区分具有不同土地利用环境的参与者。然后，使用线性弹性网络惩罚回归和极限梯度提升 (XGBoost) 来减少维度或确定重要性优先级并检查线性和非线性关系。
结果
确定了两个集群：一个是更典型的城市中心，另一个是郊区。从整个样本和两个独立簇之间的线性弹性净惩罚回归模型中检测到结果的异质模式。在对人口协变量进行调整后，在 11 个选定的暴露中，“郊区”集群中 100 m 缓冲区内的农业住宅用地对 GBI 的贡献最大（系数：0.097）。在“市中心”集群中，即使在根据社会指标进行进一步调整后，没有任何土地利用风险与GBI相关。从 XGBoost 模型中，我们观察到土地利用暴露对 GBI 的重要性排序及其非线性关系在两个集群中也是异质的。
影响
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这项研究探讨了芬兰城市土地利用与年轻人抑郁症状之间的复杂关系。基于 FinnTwin12 队列，首先确定了具有不同城市土地利用环境的两个不同的参与者群体。然后，我们采用了两种多元模型：弹性网络惩罚回归和 XGBoost，并揭示了城市土地利用与抑郁症状之间的线性和非线性关系，这些关系在两个集群中也有所不同。研究结果表明，涉及土地利用和更广泛的环境概况的分析应考虑人口异质性和线性等方面，以便将来进行综合评估。
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