Urban street tree biodiversity and antidepressant prescriptions

Abstract

Growing urbanisation is a threat to both mental health and biodiversity. Street trees are an important biodiversity component of urban greenspace, but little is known about their effects on mental health. Here, we analysed the association of street tree density and species richness with antidepressant prescribing for 9751 inhabitants of Leipzig, Germany. We examined spatial scale effects of street trees at different distances around participant's homes, using Euclidean buffers of 100, 300, 500, and 1000 m. Employing generalised additive models, we found a lower rate of antidepressant prescriptions for people living within 100 m of higher density of street trees-although this relationship was marginally significant (p = 0.057) when confounding factors were considered. Density of street trees at further spatial distances, and species richness of street trees at any distance, were not associated with antidepressant prescriptions. However, for individuals with low socio-economic status, high density of street trees at 100 m around the home significantly reduced the probability of being prescribed antidepressants. The study suggests that unintentional daily contact to nature through street trees close to the home may reduce the risk of depression, especially for individuals in deprived groups. This has important implications for urban planning and nature-based health interventions in cities.

Figure 1

Distribution of street trees and antidepressant prescriptions amongst participants in the LIFE-Adult-Study. Circles indicate the location of participants within the city of Leipzig, Germany. Circles with a black outline represent individuals who have been prescribed antidepressants. Coloured circles shaded yellow-green reflect the density of street trees within 100 m of the home. Tree density values are number of trees per meter of road within 100 m buffer. The figure was created with ggplot2 available for R (ver. 3.5.2). It is an own creation by D. Eichenberg. Polygons for the city districts were taken from City of Leipzig, Office for Statistics and Elections; Data license Germany—Attribution—Version 2.0 .

Figure 2

Effect size of covariates and street tree density and richness at 100 m around the home on antidepressant prescriptions. Shown are the regression coefficients (change in log OR) and 95% confidence intervals. Regression coefficients for continuous variables (pessimism, optimism, tree richness and density) were scaled to units of standard deviation; for the categorical variables, the effect sizes represent differences between levels. The dashed line is the line of no effect. BMI (Body Mass Index): 1 = underweight, 2 = normal weight, 3 = overweight, 4 = obese. Age: young = 18–39 years; middle = 40–64 years; old = 65–79 years. Imputed cases dataset (n = 9571).

Figure 3

Effect size of street tree density and species richness at different spatial distances around the participants’ home (buffer widths) on antidepressant prescriptions. Street tree density and richness were standardized to units of standard deviation prior to analysis. Imputed dataset (n = 9571).

Figure 4

(a) Probability of antidepressant prescriptions as a function of street tree density 100 m around the home and individual socio-economic status (SES). The black line is the mean and the shaded area are the 95% confidence intervals. The regression is statistically significant ( p< 0.01) for low SES but not for medium or high SES. (b) Probability of antidepressant prescriptions as a function of low (0), medium (average) and high (max) street tree density 100 m around the home stratified by SES. The black dot is the mean and the black line is the 95% confidence interval.