  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 to assess antidepressant
prescription rates in relation to green space, and 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 percent quantiles to estimate
green space-prescription rate correlations, controlling for confounders. 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 percent needs to be established for health
gains. The highest effectiveness occurred at a municipality surface percentage
higher than 79 percent. This inverse dose-dependent relation has important
implications for setting future community-level health and planning policies.
