TY - JOUR T1 - Access to green space, physical activity and mental health: a twin study JF - Journal of Epidemiology and Community Health JO - J Epidemiol Community Health SP - 523 LP - 529 DO - 10.1136/jech-2014-204667 VL - 69 IS - 6 AU - Hannah Cohen-Cline AU - Eric Turkheimer AU - Glen E Duncan Y1 - 2015/06/01 UR - http://jech.bmj.com/content/69/6/523.abstract N2 - Background Increasing global urbanisation has resulted in a greater proportion of the world's population becoming exposed to risk factors unique to urban areas, and understanding these effects on public health is essential. The aim of this study was to examine the association between access to green space and mental health among adult twin pairs.Methods We used a multilevel random intercept model of same-sex twin pairs (4338 individuals) from the community-based University of Washington Twin Registry to analyse the association between access to green space, as measured by the Normalised Difference Vegetation Index and self-reported depression, stress, and anxiety. The main parameter of interest was the within-pair effect for identical (monozygotic, MZ) twins because it was not subject to confounding by genetic or shared childhood environment factors. Models were adjusted for income, physical activity, neighbourhood deprivation and population density.Results When treating twins as individuals and not as members of a twin pair, green space was significantly inversely associated with each mental health outcome. The association with depression remained significant in the within-pair MZ univariate and adjusted models; however, there was no within-pair MZ effect for stress or anxiety among the models adjusted for income and physical activity.Conclusions These results suggest that greater access to green space is associated with less depression, but provide less evidence for effects on stress or anxiety. Understanding the mechanisms linking neighbourhood characteristics to mental health has important public health implications. Future studies should combine twin designs and longitudinal data to strengthen causal inference. ER -