Department of Human Geography and Spatial Planning, Utrecht University, The Netherlands.
Chair of Statistics, University of Cologne, Germany.
Environ Res. 2018 Oct;166:290-297. doi: 10.1016/j.envres.2018.06.010. Epub 2018 Jun 21.
Exposure to green space seems to be beneficial for self-reported mental health. In this study we used an objective health indicator, namely antidepressant prescription rates. Current studies rely exclusively upon mean regression models assuming linear associations. It is, however, plausible that the presence of green space is non-linearly related with different quantiles of the outcome antidepressant prescription rates. These restrictions may contribute to inconsistent findings.
Our aim was: a) to assess antidepressant prescription rates in relation to green space, and b) to analyze how the relationship varies non-linearly across different quantiles of antidepressant prescription rates.
We used cross-sectional data for the year 2014 at a municipality level in the Netherlands. Ecological Bayesian geoadditive quantile regressions were fitted for the 15%, 50%, and 85% quantiles to estimate green space-prescription rate correlations, controlling for physical activity levels, socio-demographics, urbanicity, etc. RESULTS: The results suggested that green space was overall inversely and non-linearly associated with antidepressant prescription rates. More important, the associations differed across the quantiles, although the variation was modest. Significant non-linearities were apparent: The associations were slightly positive in the lower quantile and strongly negative in the upper one.
Our findings imply that an increased availability of green space within a municipality may contribute to a reduction in the number of antidepressant prescriptions dispensed. Green space is thus a central health and community asset, whilst a minimum level of 28% needs to be established for health gains. The highest effectiveness occurred at a municipality surface percentage higher than 79%. This inverse dose-dependent relation has important implications for setting future community-level health and planning policies.
接触绿色空间似乎对自我报告的心理健康有益。在这项研究中，我们使用了一个客观的健康指标，即抗抑郁药处方率。目前的研究仅依赖于假设线性关联的均值回归模型。然而，绿色空间的存在与抗抑郁药处方率的不同分位数之间可能呈非线性关系。这些限制可能导致研究结果不一致。
我们的目的是：a）评估绿色空间与抗抑郁药处方率的关系，b）分析这种关系在不同抗抑郁药处方率分位数上的非线性变化。
我们使用了荷兰一个市一级的 2014 年的横截面数据。使用生态贝叶斯地理加性分位数回归来估计第 15%、50%和 85%分位数的绿色空间-处方率相关性，同时控制了身体活动水平、社会人口统计学、城市化程度等因素。
结果表明，绿色空间总体上与抗抑郁药处方率呈负相关且呈非线性关系。更重要的是，尽管变化幅度不大，但这种相关性在分位数之间存在差异。明显的非线性关系表明：在较低的分位数中，相关性略有正相关，而在上限的分位数中则呈负相关。
我们的发现表明，一个市一级内绿色空间的增加可能有助于减少抗抑郁药的处方数量。因此，绿色空间是一个重要的健康和社区资产，而需要建立 28%的最低水平才能获得健康收益。在市一级表面面积超过 79%时，效果最高。这种负相关的剂量依赖性关系对未来的社区一级健康和规划政策具有重要意义。
